Handbook of Well-Being
By E. Diener, S. Oishi, & L. Tay
Contents
INTRODUCTION TO THE HANDBOOK 4
Introduction by the Editors 5
INTRODUCTION, HISTORY, AND MEASUREMENT 7
Scientific Answers to the Timeless Philosophical Question of Happiness 8
From the Paleolithic to the Present: Three Revolutions in the Global History of Happiness 21
Religion and Well-being 31
Well-Being Concepts and Components 43
Reevaluating the Strengths and Weaknesses of Self-Report Measures of Subjective Well-Being 58
Non-Traditional Measures of Subjective Well-Being and Their Validity: A Review 69
What do Subjective Well-Being Judgments Mean? Sources and Distinctions, Processes and
Mechanisms
80
The Cornerstone of Research on Subjective Well-Being: Valid Assessment Methodology 96
Statistical Approaches to Analyzing Well-being Data 107
Qualitative Approaches to Culture and Well-Being 122
THEORIES OF SUBJECTIVE WELL-BEING 141
Cognitive Outlooks and Well-Being 142
Affective Forecasting 158
Eudaimonia in the Contemporary Science of Subjective Well-Being: Psychological Well-Being,
Self-Determination, and Meaning in Life
167
Do It! Activity Theories and The Good Life 181
The Way is the Goal: The Role of Goal Focus for Successful Goal Pursuit and Subjective Well-
Being
199
Hedonic Adaptation and the Set Point for Subjective Well-Being 218
Well-Being, Self-Actualization, and Fundamental Motives: An Evolutionary Perspective 243
Exploring the Associations Between Personality and Subjective Well-Being 256
Hedonomics: On Subtle Yet Significant Determinants of Happiness 271
BIOLOGY 282
The Genetics of Well-being 283
Neuroscience and Well-Being 303
Stress, Development, and Well-being 328
Foods, Sex, and Drugs: Appetitive Desires and Subjective Well-Being 339
Hormones and Well-being 350
DEMOGRAPHICS 366
A Lifespan Perspective on Subjective Well-Being 367
Gender Differences in Subjective Well-Being 381
Race and Subjective Well-being: Critical Race Perspective and Empirical Review of Key Predictors 396
1
Intersection of Religion and Subjective Well-Being 412
Married...With Children: The Science of Well-Being in Marriage and Family Life 421
LIFE DOMAINS 436
Work, the Work-Family Interface, and Subjective Well-being 437
The Importance of Leisure for Subjective Well-Being 456
Well-being and Psychopathology: A Deep Exploration into Positive Emotions, Meaning and
Purpose in Life, and Social Relationships
470
Subjective Well-Being and Physical Health 495
RESOURCES 514
Time, Money, and Subjective Well-Being 515
Income and Subjective Well-Being: Review, Synthesis, and Future Research 531
Beggars do not Envy Millionaires: Social Comparison, Socioeconomic Status, and Subjective Well-
Being
542
Healthy social bonds: A necessary condition for well-being 552
Social Capital and Prosocial Behaviour as Sources of Well-Being 566
Meaning and Well-Being 582
Multiple Levels in Job Demands–Resources Theory: Implications for Employee Well-being and
Performance
592
Wisdom and Well-Being 604
What’s Love Got to Do With it? Romantic Relationships and Well-Being 618
Resilience and Well-Being 642
OUTCOMES 654
Living Healthier and Longer Lives: Subjective Well-Being’s Association with Better Health 655
Using Multiple Methods to More Fully Understand Causal Relations: Positive Affect Enhances
Social Relationships
669
Wellbeing and Work Performance 685
Optimal Levels of Happiness 707
Affective Ingredients: Recipes for Understanding How Affective States Alter Cognitive Outcomes 717
INTERVENTIONS 739
Malleability and Intentional Activities 740
Physical Activity Interventions: Effects on Well-Being Outcomes in Older Adults 753
Cultivating Subjective Well-Being through Positive Psychological Interventions 769
Psychology Therapies and Interventions that Raise Subjective Well-Being 780
Stress Management Interventions: Improving Subjective Psychological Well-Being in the Workplace 793
CULTURE 806
Predictors of Subjective Well-Being Across Cultures 807
Subjective Well-Being in Nations 819
Culture and Subjective Well-Being: Conceptual and Measurement Issues 833
2
The Subjective Well-Being of Small Societies 848
Materialism and Living Well 859
Values and Subjective Well-Being 871
SOCIETAL DIFFERENCES AND POLICY 886
Happiness comes Naturally: Engagement with Nature as a Route to Positive Subjective Well-Being 887
Geographical Variation in Subjective Well-Being 904
The Psychology of Life Balance 914
Subjective Well-Being and the Law 932
How Political Systems and Social Welfare Policies Affect Well-being 945
Subjective Well-Being and Public Policy 954
Media Technology and Well-Being: A Complementarity-Interference Model 969
Accounts of Psychological and Emotional Well-Being for Policy Purposes 982
3
INTRODUCTION TO THE HANDBOOK
4
Introduction by the Editors
By Ed Diener, University of Virginia and University of Utah, The Gallup Organization; Shigehiro Oishi,
University of Virginia; Louis Tay, Purdue University
Citation
Diener, E., Oishi, S., & Tay, L. (2018). Introduction by the editors. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
Keywords: Subjective well-being; happiness; life satisfaction; well-being
It is a pleasure to bring to you the eHandbook of Subjective Well-Being, the science of when and
why people experience and evaluate their lives in positive ways, including aspects such as positive feelings,
life satisfaction, and optimism. There are chapters in this eHandbook on the philosophy and history of
well-being, as well as reviews of empirical research on the ways to assess well-being, the circumstances
that predict it, the outcomes that it produces, the societal policies that enhance it, and many other social,
biological, and cultural processes that help us understand why some people are happy and satisfied with
their lives, while others are not. There are also chapters on theories of well-being, such as the baseline or
set-point models.
We believe that Open publication is the wave of the future (Jhangiani & Biswas-Diener, 2017).
Therefore, we are presenting the handbook in an electronic format so that it is widely available to everyone
around the world. The handbook is entirely open and free – anyone can read and use it without cost. This is
important to us as we desire to lower knowledge barriers for individuals and communities, especially
because it provides access to students, educators, and scholars who do not have substantial financial
resources. We are not certain if this is the first free and open handbook in the behavioral sciences, but
hopefully it will not be the last. In the past the prohibitive price of many handbooks have made them
available only to scholars or institutions in wealthy nations, and this is unfortunate. We believe scientific
scholarship should be available to all.
The field of subjective well-being has grown at rapid pace over the last several decades, and many
discoveries have been made. When Ed Diener began his research within the field in 1981 there were about
130 studies published that year on the topic, as shown using a Google Scholar search on “subjective wellbeing.”
Eighteen years later when Shigehiro Oishi earned his Ph.D. in 2000 there were 1,640 publications
that year on the topic, and when Louis Tay was awarded a Ph.D. in 2011 there were 10,400 publications
about subjective well-being. Finally, in 2016 there were 18,300 publications – in that single year alone! In
other words, during the time that Diener has been studying the topic, scholarship on subjective well-being
has grown over 100-fold!
It is not merely the number of published studies that has grown, but there have been enormous leaps
forward in our understanding. In the 1980s, there were questions about the reliability and validity of
subjective well-being assessments, and the components that underlie it. One notable advance is our
understanding and measurement of well-being. We now know a great deal about the validity of self-report
measures, as well as the core evaluative and affective components that make up subjective well-being.
Further, scholars have a much greater understanding of the processes by which people report their
subjective well-being, and various biases or artifacts that may influence these reports. In 1982 many studies
were focused on demographic factors such as income, sex, and age that were correlated with subjective
well-being. By 2016 we understood much more about temperament and other internal factors that influence
happiness, as well as some of the outcomes in behavior that subjective well-being helps produce (e.g.,
income, performance, physical health, longevity).
In the 1980s, researchers assumed that people adapt to almost any life event, and that different life
events only have a short-term effect on subjective well-being. A number of large-scale longitudinal studies
later showed that that is not the case. By now we know what kinds of life events affect our subjective wellbeing,
how much, and for roughly how long. In the 1980s researchers believed that economic growth
would not increase the happiness of a given nation. Now we know when economic growth tends to increase
the happiness of a given nation. Additionally, we know much more about the biology of subjective wellbeing,
and an enormous amount more about culture and well-being, a field that was almost nonexistent in
1982.
With the advent of positive psychology, we are also beginning to examine practices and
5
interventions that can raise subjective well-being. Given the broad interest in subjective well-being in
multiple fields like psychology, economics, political science, and sociology, there have been important
developments made toward understanding how societies differ in well-being. This understanding led to the
development of national accounts of well-being – societies using well-being measures to help inform policy
deliberations. This advance changes the focus of governments away from a narrow emphasis on economic
development to a broader view which sees government policies as designed to raise human well-being.
We were fortunate to have so many leading scholars of subjective well-being and related topics
contribute to this volume. We might be slightly biased but most of the chapters in this eHandbook are truly
superb. Not only do they provide a broad coverage of a large number of areas, but many of the chapters
present new ways of thinking about these areas. Below is a brief overview of each of the sections in this
volume:
In Section 1 we begin the volume with chapters on philosophical, historical, and religious thinking on wellbeing
through the ages. Next, we cover the methods and measures used in the scientific study of well-
being.
Section 2 is devoted to theories of well-being such as the top-down theory, activity theory, goal theory,
self-determination theory, and evolutionary theory.
Section 3 covers the personality, genetics, hormones, and neuroscience of well-being. Then, demographic
factors such as age, gender, race, religion, and marital status are discussed.
Section 4 is devoted to how domains of life – such as work, finance, close relationships, and leisure – are
related to overall subjective well-being.
Section 5 covers the various outcomes of subjective well-being, ranging from work outcomes, to cognitive
outcomes, to health, and finally relationship outcomes.
Section 6 covers interventions to increase subjective well-being.
Finally, Section 7 is devoted to cultural, geographical, and historical variations in subjective well-being.
This eHandbook presents the most up-to-date and comprehensive understanding of subjective well-being –
and it is freely available to all!
The editors would like to extend their thanks to several individuals who have been critical to the
success of the handbook. First, our gratitude is immense toward Chris Wiese, Keya Biswas-Diener, and
Danielle Geerling, who organized and kept the entire venture on track. Their hard work and organizational
skills were wonderful, and the book would not have been possible without them. Second, we extend our
thanks to the Diener Education Fund, a charitable organization devoted to education that in part made this
project possible. In particular we express deep gratitude to Mary Alice and Frank Diener. Not only did
their help make this eHandbook possible, but their lives stood as shining examples of the way to pursue
well-being!
References
Jhangiani, R. S., & Biswas-Diener, R. (Eds.) (2017). Open: The philosophy and practices that are
revolutionizing psychological science and education. London: Ubiquity Press.
2018 Ed Diener. Copyright Creative Commons: Attribution, noncommercial, no derivatives
6
INTRODUCTION, HISTORY, AND MEASUREMENT
7
Scientific Answers to the Timeless Philosophical Question of
Happiness
By Pelin Kesebir, University of Wisconsin-Madison
Citation
Kesebir, P. (2018). Scientific answers to the timeless philosophical question of happiness. In E. Diener,
S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
This chapter aims to serve as an introduction to the science of happiness, by providing a catalogue of the
main questions that have been posed about the topic across millennia. I cover the various answers that have
been offered to these questions, by philosophers and more recently by research psychologists. The chapter
starts with the questions of what happiness is and how it can be measured, after which I turn to explore the
possibility, desirability, and justifiability of happiness. The last portion of the chapter is devoted to the
perennial question of how to be happy.
Keywords: Well-Being, Happiness, Philosophy
Academics who love their jobs sometimes hold their own study topic in exaggeratedly high esteem,
deeming it to be among the most consequential topics ever to be studied, if not the most. As a scholar of
happiness, however, I cannot help feeling somewhat justified in that belief. I am not alone in thinking that
happiness, by whatever name we refer to it and however we go about looking for it, is a most fundamental
and universal human aspiration. It is “the motive of every act of every man” (Pascal, 1995), “the goal of all
goals” (Ricard, 2006), the “supreme good” —that which we always choose for its own sake and not as a
means to something else (Aristotle, 2000). Given the centrality of happiness to the human experience, it is
not surprising that the annals of humanities are replete with inquiries into it: From the Bhagavad Gita to the
Bible, from the Stoics to Michel de Montaigne, from Tolstoy to the Dalai Lama, the intellectual and
spiritual masterpieces of history unfailingly probe into the existence, nature, and attainment of happiness.
In the last couple of decades, the timeless question of happiness also began to interest psychologists,
who used empirical methods to investigate the causes, correlates, and consequences of happiness. The
result has been the vibrant field of Positive Psychology and its ever-expanding contribution to the
understanding of happiness. This accumulation of knowledge also meant that questions about happiness
that have vexed thinkers for millennia could now be answered with more confidence—some of them, if not
all (Kesebir & Diener, 2008). My goal for this chapter is to survey the main questions that come up when
philosophers (and lay people alike) think about this topic: Is happiness possible? How much of it is in our
hands? Isn’t it selfish to want to be happy? How to be happy?
I will delve into these and similar questions and whenever possible, indicate where the current
empirical science of well-being stands relative to the various ideas proposed by philosophers. My intention
is neither to provide a comprehensive history of the idea of happiness, nor offer a philosophical account of
the meaning, nature, or value of happiness. Philosophy is sometimes referred to as “the art of wondering”
and this chapter, in keeping with that, is meant as an overview of what philosophers most wonder about
happiness. As such, it aspires to serve as an introduction to and preparation for the more detailed treatments
of the myriad aspects of happiness that are covered in this Handbook.
What Is Happiness?
Philosophers studying happiness agree, if on nothing else, on the challenges of defining the term.
Notwithstanding the variety of definitions, when philosophers write about happiness, they typically use the
term in one of two broad senses (Haybron, 2008). The first usage, similar to the lay understanding of the
term, regards happiness as a state of mind: It denotes a preponderance of positive emotions and positive
attitudes toward one’s life and its diverse components. The second usage of happiness, on the other hand,
refers to a life of well-being or flourishing, a life that is good for a person, benefits the person. It is more
about “doing good” than “feeling good”.
These two different usages in philosophy roughly correspond to the distinction between hedonic
and eudaimonic theories of happiness (Ryan & Deci, 2001). Hedonic approaches conceive of happiness in
terms of pleasure attainment and pain avoidance, where the pleasure and pain may pertain not only to those
of the body, but also those of the mind and the heart. Hedonic theories of happiness are considered to be
“subjectivist”, in that they ground happiness in people’s subjective states, like their felt emotions and
personal evaluations (Haybron, 2011). Eudaimonic approaches, on the other hand, emphasize the process
8
of living well and aspects of positive psychological functioning that go beyond positive emotions and
evaluations (Jayawickreme, Forgeard, & Seligman, 2012; Ryff, 1989; also see Heintzelman, this volume).
Unlike hedonic theories, eudaimonic theories do not assume that what is good to the person is necessarily
good for the person. Instead, they specify certain objective qualities or psychological states that need to be
present for happiness (e.g., virtuous activity, autonomy, positive relationships), independent of what the
person cares about or likes.
To what extent hedonic and eudaimonic happiness overlap is both a philosophical and empirical
question. It is easily imaginable that a person could feel subjectively happy without leading a life of virtue
and flourishing. Likewise, it is possible that a flourishing, meaningful, virtuous life would not always be
accompanied by high degrees of positive affect. Hence, hedonic and eudaimonic happiness appear to be
distinct concepts, and the most desirable life presumably requires high levels of each. That said, it stands to
reason that hedonic and eudaimonic happiness are interdependent to a certain degree, and subjectively and
objectively desirable ways of existing overlap considerably. This was at least the stance of many ancient
philosophers. Even Epicurus, whose name has become synonymous with hedonism, believed that virtue
and pleasure were interdependent and that it was simply impossible “to live pleasantly without living
prudently, honorably, and justly” (1994, p. 31).
Empirical attempts to distinguish hedonic happiness from eudaimonic happiness have proved to be
challenging, yielding mostly inconsistent findings. These inconsistencies are in no small part due to the
multiplicity of conceptual and operational definitions for each construct, especially eudaimonia (Huta &
Waterman, 2014; Kashdan, Biswas-Diener, & King, 2008). Another difficulty is that both constructs are
currently being studied subjectively, and there is no separate gold-standard measure against which to
compare the merits of the two approaches. Citing these and other reasons, some scholars have argued that
although of philosophical interest, the constructs of hedonic and eudaimonic happiness do not translate
well to scientific inquiry and drawing a sharp line between them might have unintended costs to the
progression of well-being research (Kashdan et al., 2008). For now, it seems fair to conclude from the
research that hedonia and eudaimonia are very strongly correlated, even if they may be distinct concepts.
This close overlap echoes the intuitions of many ancient philosophers, including Aristotle, for whom
happiness was acting virtuously and feeling good because of that.
How to Conceptualize and Measure Happiness?
As difficult as it may be to converge on a single definition of happiness, to be able to study it
scientifically, we need to define and operationalize it. Psychologists pioneering the study of happiness dealt
with this challenge by proposing the concept of “subjective well-being” (SWB; Diener, 1984). SWB refers
to people’s evaluations of their lives and encompasses both affective and cognitive elements. These
elements include life satisfaction (global judgments of one’s life), satisfaction with important life domains
(satisfaction with one’s relationships, work, health, etc.), high levels of positive affect, and low levels of
negative affect.
SWB emphasizes the subjective nature of happiness and holds human beings to be the best judges of
their own happiness. In this regard, it is akin to hedonic theories, which ground happiness in a person’s
subjective states, and differs from the more prescriptive conceptualizations of happiness such as Ryff and
Singer’s (1996) construct of psychological well-being and Ryan and Deci’s (2000) self-determination
theory. These approaches, more in the eudaimonic tradition, specify certain needs (such as relatedness, selfacceptance,
or meaning and purpose in life) as imperative to human well-being.
The measurement of happiness in current psychological research overwhelmingly relies on selfreports—for
constructs from both hedonic and eudaimonic traditions. This democratic method of regaling
personal authority to ordinary people in matters of happiness would likely meet with disapproval from
classical philosophers such as Socrates, who had little faith in the intellectual prowess of the masses
(Haybron, 2007b). Yet self-reports seem the most suited method to study subjective well-being, which by
definition prioritizes people’s own evaluations of their lives. This does not change the fact that self-reports
of happiness suffer from the same limitations that characterize other self-report measures, such as being
fallible to memory biases, mood or context effects, and social desirability concerns (e.g., Deaton & Stone,
2016; Haybron, 2007a; Schwarz & Strack, 1999; Lucas, this volume). Notwithstanding this, research
suggests that these effects are far from being large enough to render self-reports of happiness unhelpful
(Lucas & Lawless, 2013). In fact, several studies attest to the reliability and validity of self-report happiness
measures in informing research (e.g., Diener & Suh, 1997). Still, implementing multimethod assessments
of happiness whenever possible (e.g., informant reports, experience sampling, smiling behavior), would be
advisable (also see Scollon, this volume). Happiness is a construct without a gold standard measure, but the
available methods, albeit imperfect, are still adequate enough to substantially contribute to our
understanding of it.
9
Is Happiness Possible?
The answer to the question of whether happiness is possible clearly depends on the way we define
happiness. If we conceive of it as a perfect, pure, and perpetual state—a complete absence of negativity
and constant positivity—it indeed seems unattainable, as well as unrealistic and unhealthy. When Hegesias
of Cyrene, also known as Peisithanatos (the death persuader) in the 3rd century BC argued that happiness
was unattainable, life was not worth living, and that the sage would choose death (Matson, 1998), he
probably was holding such an idealized view of happiness. Although probably none of them were as
extreme in their pessimism as Hegesias, many philosophers throughout history saw human happiness as
either impossible or at least quite improbable, given the nature of the world and the nature of humans. Of
course, we should remember that many a distrustful stance toward the possibility of happiness was
advanced in a social context of much lower quality of life and more common unhappiness relative to
modern times (Veenhoven, 2005).
Leaving extreme and idealized versions of happiness aside, it seems entirely possible for people to
experience predominantly positive emotions and be satisfied with their lives. At any rate, this is what
worldwide surveys suggest. In an article titled “Most People Are Happy,” Diener and Diener (1996)
reviewed the available evidence and concluded that an overwhelming majority of individuals fall in the
positive range of the happiness scale, including people with apparent disadvantages, such as quadriplegics
or those in the lowest income groups. Likewise, 86% of the 43 nations included in Diener and Diener’s
study had average happiness levels above the midpoint of the happiness scale. Available evidence suggests
that humans, on average, have a predisposition to mild levels of positive moods and happiness (Diener,
Kanazawa, Suh, & Oishi, 2015). For such a disposition to be evolutionarily feasible, it should have some
adaptive functions. Research strongly supports this view, by showing that positive emotions help people
build intellectual, psychological, social, and physical resources, thereby increasing the likelihood of
adaptive behaviors such as creativity, planning, mating, and sociality (Diener et al., 2015; Fredrickson,
1998).
How Much Control Do We Have Over Our Happiness?
The psychological discoveries of the last decades refute the pessimistic idea that happiness is
impossible. But for whom is it possible? Can anybody who sets their mind to it become happy, or happier?
How much of our happiness is up to us? Early answers to these questions were not very encouraging: The
concept of happiness in antiquity largely centered on fortune, and happiness was regarded as something
that might be bestowed on the person by the gods or by fate, if they were lucky (McMahon, 2006; Oishi,
Graham, Kesebir, & Galinha, 2013). The etymology of the word “happiness”, at least in Indo-European
languages, carries the traces of the same understanding. In English, for instance, happiness comes from the
Old Norse root hap, meaning luck or chance, whereas the words for luck and happiness are identical in
German to this day (Glück).
Despite the incontrovertible role of chance, happiness in many philosophers’ eyes was still
something that could be successfully pursued. Both in the West and the East—from Aristotle to the Stoics,
from Daoism to Buddhism—philosophical and spiritual traditions aimed to transform people’s way of
being, so that they could achieve wisdom and happiness (Hadot, 1995; Lenoir, 2015). Many of them
advocated “spiritual exercises”, such as looking at oneself from a distance or reflecting on one’s mortality,
which are not that different from modern positive psychological interventions. Their intuition that
happiness is something that can be developed through willful activity overlaps with the current
understanding of “well-being as a skill” and is compatible with research on the determinants of happiness.
Accordingly, a person’s happiness level is determined by three major factors: (1) a genetically determined
set point for happiness, (2) life circumstances (e.g., age, gender, education, culture), and (3) factors under
one’s voluntary control, such as the activities and practices one chooses to engage in (Lyubomirsky,
Sheldon, & Schkade, 2005).
After surveying the literature, Lyubomirsky and colleagues (2005) concluded that among these
components, the genetically determined set point explains about 50% of variation in happiness, whereas life
circumstances account for only 10%, and intentional activities are responsible for the remaining 40%.
Recent meta-analyses suggest that the heritability of well-being might be even lower, in the 32-41% range
on average (Røysamb & Nes, this volume). We should bear in mind that the estimates for the influence of
genetic and situational factors are not fixed statistics, but depend on the population and the situational
factors involved. Still, the lesson from research on the determinants of happiness is that although some
factors outside of our control constrain our chances for greater happiness (e.g., genes, unalterable life
circumstances), we still have significant room for increasing our happiness levels through personal effort
(also see Layous, this volume). The possibility of change is reinforced by studies revealing the brain’s
neuroplasticity—the capacity of neural circuits underlying social and emotional behavior to change in
10
response to experience (e.g., physical exercise, cognitive behavioral therapy, mindfulness meditation) and
support positive outcomes (Davidson & McEwen, 2012).
Is Hedonic Adaptation Inevitable?
Any discussion about the possibility of happiness would be remiss not to mention concerns about
adaptation. Adam Smith, in Theory of Moral Sentiments, writes about “the never-failing certainty with
which all men, sooner or later, accommodate themselves to whatever becomes their permanent situation”
(2002, p. 172). The so-called hedonic treadmill theory—the idea that our emotional systems adjust to
almost anything that happens in our lives, good or bad—has been embraced as a guiding principle in
happiness research since the early studies showing that lottery winners are not happier than controls and
that even paralyzed accident victims revert approximately to their initial levels of happiness (e.g.,
Brickman, Coates, & Janoff-Bulman, 1978). Relatedly, the set-point theory posits that major life events
(e.g., marriage, unemployment, illness) affect a person’s happiness only temporarily, after which the
person’s happiness level regresses to a default determined by heritable factors (Lykken & Tellegen, 1996).
The implication of these assertions is that attempts at becoming happier are ultimately doomed to
fail, and that the search for the causes of happiness may be quite pointless. Accumulating research,
however, contradicts the hopelessness of this message. The recent consensus in the field is that people do
not adapt quickly and/or completely to everything and a person’s happiness level can be permanently
altered (Lucas, 2007; Sheldon & Lucas, 2014; Tay & Kuykendall, 2013; see Luhmann & Intelisano, this
volume, for an overview). Systematic reviews of therapeutic and positive psychological interventions
further support the conclusion that long-term positive changes to happiness-related personality traits (e.g.,
neuroticism, extraversion) and increases to subjective well-being do happen (Bolier et al., 2013; Roberts et
al., 2017). Interventions that cultivate character strengths and thereby increase well-being (e.g., Niemiec,
2017; Quinlan, Swain, & Vella-Brodrick, 2012) similarly attest to the malleability of eudaimonic
happiness.
Is Pursuing Happiness Self-Defeating?
Another argument raised against our capacity to exercise control over our happiness has been that
the search for happiness will necessarily be self-defeating—that the harder we strive for happiness, the
further we will retreat from it. Schopenhauer, for instance, observed that wherever joy makes its
appearance, “it as a rule comes uninvited and unannounced, by itself and sans façon” (Schopenhauer,
2001, p. 409). Several other philosophers, including Aristotle, agreed that happiness should not be pursued
directly as a goal, but should be found along the way as the byproduct of virtues and virtuous activities. In
the words of John Stuart Mill, only those are happy who “have their minds fixed on some object other than
their own happiness; on the happiness of others, on the improvement of mankind, even on some art or
pursuit, followed not as a means, but as itself an ideal end” (Mill, 1944, p. 100).
It is easy to see that the pursuit of happiness could thwart happiness under certain circumstances.
Being obsessed with or feeling compelled to be “happy” are undoubtedly not healthy states of mind, and
especially combined with misguided notions about happiness (e.g., rejection of negative emotions), such a
quest could hurt a person’s well-being (Gruber, Mauss, & Tamir, 2011). Even under less extreme
conditions, “trying to make oneself as happy as possible” could prove deleterious to one’s well-being, to
the extent this effort leads to high levels of self-consciousness and self-monitoring (Schooler, Ariely, &
Loewenstein, 2003). After all, it is unhappiness that is associated with high levels of self-focus, whereas
happy moods are typically characterized by low self-focused attention (Green, Sedikides, Saltzberg, Wood,
& Forzano, 2003; Ingram, 1990).
Yet at the same time, as noted above, we find support for the effectiveness of interventions to
increase happiness, suggesting that deliberately pursuing happiness does not necessarily have to be selfdefeating.
Philosopher Frederic Lenoir (2015) writes about pursuing happiness “while being supple and
patient, without any excessive expectations, without stress, with hearts and minds in a state of constant
openness”. This sounds like a healthy way of seeking happiness, especially when accompanied by an
accurate understanding of where happiness lies and where it does not.
Is Happiness Justifiable?
Happiness might be desirable, and even possible, but is it also justifiable? Aren’t happy people
stupid, self-centered, or at least deeply insensitive to the problems darkening the world? Although such
criticisms against happiness carry an air of plausibility and even nobility, some reflection reveals that they
rely on a distorted understanding of happiness—one of giddy, empty-headed, relentless positivity. Studies
operationalizing happiness as subjective well-being or life satisfaction fail to substantiate claims about it
being an egotistic, apathetic, or otherwise objectionable state; instead, they disclose the opposite pattern.
Growing evidence suggests that happiness is causally related to many favorable outcomes in life. Among
11
other things, happiness and positive affect have been shown to foster better health, better work
performance, better social relationships, and more altruistic behavior (De Neve, Diener, Tay, & Xuereb,
2013; Lyubomirsky, King, & Diener, 2005). The positive relationship between happiness and socially
desirable outcomes also holds true on a national level: Happier countries tend to score higher on
generalized trust, volunteerism, and democratic attitudes (Tov & Diener, 2008). Claims about happiness
entailing “a well-fleshed indifference to sorrow outside it” (Eliot, 1996, p. 796) lose their credibility in the
face of such findings. Rather, as elaborated on by the broaden-and-build theory of positive emotions
(Fredrickson, 2004), happiness seems to provide the fuel—the physical, intellectual, and psychosocial
resources—that enable people to go out in the world and solve problems.
Another notable argument in defense of the justifiability of happiness is that our personal happiness
is deeply connected with the happiness of everyone else. The happier we are, the happier we make others,
both through our virtuous actions and through the contagious, uplifting effect of our positive emotions.
When we conceive of happiness as something in the service of others and the world, it feels less like selfabsorbed
indulgence and more like a moral duty. French author André Gide expresses this sentiment
eloquently when he writes: “There are on this earth such immensities of misery, distress, poverty and
horror that the happy man cannot think of it without feeling ashamed of his happiness. And yet no-one can
do anything for the happiness of others if he cannot be happy himself. I feel an imperious obligation to be
happy.” (as cited in Lenoir, 2015).
The notion that the ultimate aim of the quest for happiness should be to serve others in wiser and
more effective ways is common in many ancient teachings, including Buddhism (Ricard, 2006). Indeed,
some commentators have noted that an important difference between contemporary forms of the quest for
happiness and ancient forms is that the latter saw a strong bond between the individual good and the
common good (Lenoir, 2015). Whereas improving individual well-being and improving society went hand
in hand in the eyes of Plato, Aristotle, Confucius or the Buddha, increasing levels of individualism and
consumerism in the modern era changed this: People started to pursue their individual happiness less and
less as part of a larger collective happiness project. While there might be some merit to this observation, the
accumulating evidence about the positive societal outcomes associated with happiness and the
accompanying efforts to make happiness a public policy concern (Odermatt & Stutzer, this volume) point
to a turning of the tide.
Where and How to Find Happiness?
Let us say that we arrived at the conclusion that happiness is desirable, possible, and justifiable.
Therefore, we want to pursue it. Yet how should we go about this? Where does happiness lie? And where
does it not? How can we cultivate it? Philosophers throughout ages have offered various and at times
contrary answers to these questions. Yet, clearly, some advice is sounder than the rest, and some methods
of achieving happiness are more effective than others. In this section, we will look at philosophical and
empirical answers offered to the question of where and how to find happiness.
Before turning to where happiness lies, however, I want to devote some discussion to where it does
not lie. It is well established that people are prone to make mistakes in predicting what will make them
happy, holding on to some “myths of happiness” (Gilbert, 2006; Lyubomirsky, 2013). What are some of
these less fruitful ways of seeking happiness, as revealed by philosophers and psychologists?
Seeking Happiness in Pleasure
In everyday English, we use the word “hedonist” to describe somebody who seeks fulfillment in
pleasure, and especially in sensory, bodily ones. In philosophy, hedonism is more broadly defined as the
view that our happiness depends wholly on how we feel, that all and only positive experiences are good for
us (Gregory, 2015). Many arguments can be and have been raised against hedonism, the most famous one
being Nozick’s (1974) “pleasure machine” thought experiment. Nozick imagines an extremely effective
brain stimulation machine that would allow a person to experience whatever pleasurable or desirable
experience they could want, while floating in a tank all the time, and not being aware of it. Would you plug
into this machine, choosing it over real life? If pleasurable experiences were all that mattered in life, then
people would want to be hooked up to the machine, however, typically they do not, suggesting that there is
more to happiness than hedonism fails to capture.
Another reason why chasing pleasures is a suboptimal happiness strategy lies in the fact that
pleasures, by their nature, are fleeting. The quest for pleasures could thus easily mutate into an endless
cycle of ups and downs, with bursts of pleasure being followed by a sense of disillusionment, deprivation,
and craving for more. Especially in Buddhism, it is a common idea that happiness should not depend on all
our experiences being pleasurable and that prioritizing pleasure could lead us into a trap of unhealthy,
unhelpful patterns. Indeed, the constant pursuit of rewarding stimuli and “highs” is a hallmark of addiction
12
disorders and come with grave costs. These ideas are consistent with findings showing that seeking
happiness primarily in pleasure is associated less strongly with subjective well-being than seeking
happiness in engagement or meaning (Schueller & Seligman, 2010). Furthermore, whereas engagement and
meaning orientations to happiness were positively associated with educational and occupational attainment
in a large sample of adults, a pleasure orientation was associated negatively, highlighting its potential costs.
Seeking Happiness in Money and Consumption
Aristotle believed that wealth was a necessary ingredient of happiness (1991). Stoics, in contrast,
believed that material possessions and wealth were in no way required for happiness. Inhabiting the middle
ground were the Epicureans, who maintained that although we should have sufficient money to shelter us
from harm and pain, money ceases to offer greater levels of happiness beyond a certain threshold.
Empirical research on the relationship between income and happiness supports this latter view. In a
worldwide sample of over 1.7 million respondents, Jebb, Tay, Diener, and Oishi (2018) have demonstrated
that despite substantial variation across regions, higher incomes stopped contributing to more positive life
evaluations at $95,000, and to higher emotional well-being at $60,000 to $75,000. Thus, we can say that an
adequate amount of money is a necessary condition of happiness, albeit not a sufficient one.
Whereas having money can have a beneficial effect on well-being, at least until a certain point,
valuing and wanting money too much turns out to have a detrimental effect. Materialism, defined as
viewing possessions and acquisitions as central to one’s life and essential to one’s happiness (Richins &
Rudmin, 1994) has been consistently linked to lower well-being (Dittmar, Bond, Hürst, & Kasser, 2014;
also see Kasser, this volume). Wanting money seems to have an especially toxic influence on happiness, if
it is fueled by motives such as seeking power, showing off, and overcoming self-doubt (Srivastava, Locke,
& Bartol, 2001). These findings dovetail with studies demonstrating that placing a strong emphasis on
extrinsic goals (e.g., wealth, fame, an attractive image) relative to intrinsic goals (e.g., affiliation, personal
growth, community) is linked to poorer psychological and physical well-being (Kasser, 2003).
Seeking Happiness in the Fulfillment of Our Desires
Desire fulfillment theories of well-being, in their simplest form, hold that well-being consists in the
satisfaction of the desires or preferences of the person (Heathwood, 2015). Desire theories have been
enjoying wide acceptance among philosophers and economists, and they also overlap with how lay people
commonly conceive of happiness—as satisfying the needs and desires of the ego, as in “I’d be happy, if
only I could get everything I want, and get rid of everything I don’t want”. Yet expecting the universe to
yield to all our wants is not very realistic, suggesting that we might be setting ourselves up for
disappointment if we have our happiness depend too much on the gratification of our desires. This does not
even take into consideration the fact that not everything we desire turns out to be good for our well-being—
that in the words of Saint Teresa of Avila, “there are more tears shed over answered prayers than over
unanswered ones.”
Furthermore, research shows that happiness is not necessarily the result of good things happening to
oneself. For one, as noted earlier, people’s circumstances in life, including their marital status, income, or
their personal history (e.g., having experienced a childhood trauma, having won a prestigious award)
account for a fairly limited amount of happiness differences among people (Lyubomirsky et al., 2005).
Similarly, when Diener and Seligman (2002) compared “extremely happy” students (upper 10% of the
happiness distribution) to students with average happiness levels, they found that the two did not differ
from each other in the number of objectively positive and negative life events. These findings corroborate
one of the most frequently encountered ideas in ancient wisdom, namely that happiness is less a matter of
what happens to us and more a matter of how we see the world and respond to it.
Especially in Stoicism and Buddhism, there is a strong sense that it is not external causes that
determine our happiness, but our state of mind. These philosophies emphasize that enduring happiness
becomes possible once we transform the way we look at the world. The notion that our mental outlook—
such as what we pay attention to and how we interpret what we encounter—has a major impact on our
happiness receives wide support from research (Diener & Biswas-Diener, 2008; Lyubomirsky, 2001; also
see Margolis & Lyubomirsky, this volume). In keeping with this, many positive psychological
interventions are variations on training people to notice positive things more frequently and interpreting
things in a more positive light (Quoidbach, Mikolajczak, & Gross, 2015). To sum up, although there is
nothing wrong with having desires and striving after goals, tying our happiness too tightly to their
attainment appears to be less productive as a happiness strategy than training ourselves to love life even
when things do not go our way.
How to Cultivate Happiness?
We have contemplated some methods of seeking happiness that presumably are less effective in
13
leading to enduring happiness. In this final section, I want to turn to methods that bear more promise, as
proposed by the distinguished minds of the past and as revealed by modern research. Specifically, I will
argue that happiness will become more achievable if we cultivate (1) healthy habits of the body, (2) a
healthy relationship with ourselves, (3) healthy habits of the heart and mind (i.e., virtues), (4) healthy
relationships with others and (5) a healthy connection to a larger beyond (e.g., God, nature).
Healthy Habits of the Body
We would be hard-pressed to find any philosopher, or any ordinary person for that matter, who
would contest the crucial importance of bodily health to happiness. Our well-being is affected by our
physical health, and at the same time it affects our physical health: Happier people are more likely to be
physically healthier and live longer (Diener & Chan, 2011; also see Cross, Hofschneider, Grimm, &
Pressman, this volume). This bidirectional relationship suggests that working on our health would benefit
our happiness, just as working on our happiness would benefit our health. Studies consistently show that
cultivating healthy habits of the body, such as eating well (e.g., increased consumption of fruits and
vegetables), exercising, and getting enough sleep improve well-being (e.g., Conner, Brookie, Carr, Mainvil,
& Vissers, 2017; Mujcic & Oswald, 2016; Reed & Buck, 2009; Steptoe, O'Donnell, Marmot, & Wardle,
2008).
A Healthy Relationship with Oneself
It has been said that the self is at once our greatest ally and fiercest enemy (Leary, 2004). Selfgenerated
thoughts and feelings can cause a great deal of unhappiness (Ingram, 1990) and the self can be
so burdensome at times that the urge to escape it takes self-destructive forms such as drug and alcohol
abuse, binge eating, and even suicide (Baumeister, 1991). Through both conscious and unconscious routes,
how we relate to ourselves has a powerful impact on how we relate to others and the world around us, and
is therefore essential to well-being. What then makes for a healthy relationship with oneself?
The self-construct that has been most robustly linked with happiness and mental health is selfesteem
(Baumeister, Campbell, Krueger, & Vohs, 2003). Self-esteem refers to a feeling born from the I’s
evaluation of the me—it is a general sense of comfort and happiness with all the things one is. A love for
oneself and a love for life typically go together, explaining the link between happiness and self-esteem.
Crucially, not all types of high self-esteem are created equal, with some being healthier and more conducive
to well-being than others. More preferable are types like “true self-esteem” (Deci & Ryan, 1995) or
“optimal self-esteem” (Kernis, 2003), which entail a firmly grounded sense of self-worth and calm selfconfidence,
standing in opposition to fragile, unstable, or overly contingent forms of self-esteem.
Self-compassion (Neff, 2003) and a quite ego (Bauer & Wayment, 2008) have also been proposed
as alternative ways of relating to oneself that bypass some potential pitfalls of self-esteem. Both of these
constructs emphasize self-acceptance and an awareness of the self’s interdependence with others. Recently,
humility and, defined more broadly, hypo-egoic functioning have also been attracting interest from
researchers (Brown & Leary, 2016; Tangney, 2000). These constructs are defined by low levels of selffocus
and self-centeredness, which are considered foundational to well-being in many spiritual and
religious traditions. Buddhist notions of happiness, for instance, regard attachment to the self as the source
of our most disruptive thoughts and a main impediment to inner peace. Inspired by this understanding,
Dambrun and Ricard (2011) proposed that self-centered psychological functioning attracts considerable
suffering and leads to unstable, fluctuating happiness, whereas a selfless psychological functioning is
linked to authentic-durable happiness.
Healthy Relationships with Others
The history of philosophy had its own share of misanthropes, like Arthur Schopenhauer, who
argued that loneliness was a superior condition to human company. This view, fittingly, was hardly popular
however, and is powerfully contradicted by research. The desire to belong is considered a fundamental
human motivation, and its satisfaction through love, friendship and close emotional ties is robustly linked
to well-being (Baumeister & Leary, 1995; Diener & Seligman, 2002; Reis & Gable, 2003). In contrast,
loneliness and poor quality social relationships have been strongly associated with low emotional and
physical health (Cacioppo & Patrick, 2008; House, Landis, & Umberson, 1988). It must be true that ‘‘it is
man, who is essential to man’s happiness’’ (Tatarkiewicz, 1976, p. 130), and as much as some may believe
that hell is other people, so, apparently, is heaven. To cultivate happiness, then, it is critical to cultivate
close relationships characterized by mutual trust, caring, and understanding.
Virtues: Healthy Habits of the Heart and Mind
Frequently figuring in philosophers’ discussions on the happiest, best possible life is the concept of
“virtue”. Aristotle, for instance, believed that happiness (eudaimonia) lay in the exercise of virtue. Taking
this idea to its logical conclusion, Roman Stoic Cicero maintained that a man in possession of virtue could
14
be happy even while being tortured (McMahon, 2006). More recently, Hursthouse (1999) argued that
possessing virtue does not necessarily result in happiness, as luck plays an irrefutable role in human affairs,
yet it is the only reliable bet for a happy, flourishing life—just as adopting a healthy lifestyle is the best bet
for being healthy, even though it does not guarantee perfect health or longevity. Is there any merit to these
claims? Does possessing and exercising virtue truly lead to happiness?
Studies conducted in the last decades using the VIA classification of character strengths and virtues
(Peterson & Seligman, 2004) yielded substantial evidence for the association between happiness and virtue.
For example, in a large-scale study Park, Peterson, and Seligman (2004) showed that almost all of the 24
character strengths in the VIA classification correlated with global life satisfaction, even though the
strengths of love, gratitude, hope, curiosity, zest, and perspective/wisdom emerged as most strongly linked
to life satisfaction (correlations in the .35 to .60 range). Experimental and longitudinal studies further
corroborate the age-old wisdom that virtue leads to happiness (e.g., Proctor et al., 2011; Proyer, Ruch, &
Buschor, 2013). After reviewing the literature on the relationship between happiness and virtue, Kesebir
and Diener (2014) concluded that while virtue leads to happiness, there is also support for the notion that
happiness leads to virtuous behavior. They have argued that these reciprocal causation dynamics are
conducive to virtuous cycles running from virtue to happiness to virtue, potentially leading to enhanced
happiness and enhanced virtue over time. This account is also parallel to Bishop’s network theory of wellbeing
(2015), according to which “having well-being is to be ‘stuck’ in a self-perpetuating cycle of positive
emotions, positive attitudes, positive traits, and successful engagement with the world” (p. 8).
The question about whether virtue leads to happiness is at some level also a question about human
nature: Is it fundamentally good, or is there an insurmountable conflict between the love of self and love of
others? A portrayal of human nature as deeply egoistic has characterized the writings of many thinkers,
from Thomas Hobbes to Adam Smith to Freud, and might even have been inherited from the Christian
doctrine of original sin (Lenoir, 2015). Yet recent scientific studies from diverse disciplines cast doubt on
this pessimistic conception of human nature (Ricard, 2015) and suggest that humans might flourish in
loving and giving (also see Helliwell, Aknin, Shiplett, Huang, & Wang, this volume).
A Healthy Connection to a Larger Beyond
Transcending the self and connecting to something larger than the self (e.g., God, universe, nature)
has been regarded as a recipe for happiness across ages (Haidt, 2006; Leary, 2004). Self-transcendent
connections act as a powerful source of meaning and purpose, which are critical ingredients of well-being
(also see Steger, this volume). Connection to nature, for example, has been widely documented to
contribute to well-being (Bratman, Hamilton, & Daily, 2012; Hartig, Mitchell, de Vries, & Frumkin, 2014;
McMahan, this volume) and a sense of meaning in life seems to mediate the association between nature
connectedness and well-being (Howell, Passmore, & Buro, 2013) .
For a lot of people, religious faith is the central self-transcendent connection in their lives and a
major provider of a sense of meaning and purpose. Although the positive association between happiness
and religiosity might depend on societal factors, religious people on average still report higher subjective
well-being, and the enhanced sense of purpose they report does not depend on societal conditions (Diener,
Tay, & Myers, 2011; Newman, this volume). Self-transcendent emotions such as compassion, gratitude,
and awe have also been linked to greater physical and emotional well-being (Stellar et al., 2017), echoing
the insight that self-transcendence might be a more promising strategy for cultivating happiness than
strategies focusing heavily on the self.
Conclusion
The goal of this chapter was to familiarize the reader with the crucial questions that define the
philosophy and science of happiness. Relying on philosophers’ careful thinking and using the methods of
science, we have been able to provide some initial answers to questions that have vexed humanity for
millennia. It is simultaneously thrilling and touching to realize that while the questions asked about
happiness are timeless and will stay the same centuries hence, the answers offered will become much more
precise and accurate with time. We are fortunate to be living in an era when our understanding of the causes
and conditions of happiness is growing day by day, and grateful to all the thinkers and scholars, ancient and
modern, who asked these questions and provided the answers.
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From the Paleolithic to the Present: Three Revolutions in the
Global History of Happiness
By Darrin M. McMahon, Dartmouth College
Citation
McMahon, D. M. (2018). From the Paleolithic to the present: Three revolutions in the global history of
happiness. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF
Publishers. DOI:nobascholar.com
Abstract
This article examines three crucial turning points or “revolutions” in the world history of happiness from
the Paleolithic to the present, focusing on the impact of the Agricultural Revolution that began c. 10,000
BCE, the “Axial Age” of the first millennium BCE, and the “Revolution in Human Expectations” of the
long 18th century. The article contends that each of these revolutions initiated significant changes in
humanity’s experience and understanding of happiness. And though we are still living in the shadow of the
last of these three great revolutions, it may be that humanity stands on the cusp of another.
Keywords: happiness, history, Paleolithic, Axial Age, revolution in human expectations
The tools available to social scientists hoping to measure the happiness of the living are now many and
varied. They range from the detailed scales and questionnaires that assess subjective well-being around the
globe, to methods of experience sampling, to a variety of physical measures that capture the brain and
body’s response to stimuli both internal and external. It is true, as Dan Gilbert has remarked, that the nature
of subjective experience is such that there will never be a “happyometer,” a perfectly reliable instrument
that allows us to measure another person’s well-being with complete and total certainty. But the
alternatives to perfection are still pretty good. Gilbert invokes the wisdom of the builder. “Imperfect tools
are a real pain, but they sure beat pounding nails with your teeth” (Gilbert, 2006).
From the perspective of a historian who would hope to measure the happiness of the dead, however,
the prospect of broken teeth is real. Try asking a skeleton to meditate in an MRI machine and you will
begin to see the problem. The dead, most often, are unresponsive. You can’t do experience sampling with
a corpse. And though it may be that we are now bequeathing enough survey data to our descendants to
enable future historians one day to ask questions of the departed that we currently ask the living—“Did you
experience happiness during a lot of the day yesterday?” “On the whole, would you describe yourself as
very happy, pretty happy, not so happy?”—for the time being such questions, when posed to people in the
past, tend to fall on deaf ears.
Yet if historians’ questions, like their instruments, must necessarily differ to some extent from those of
their social-scientific colleagues who work with subjects still among us, they needn’t throw up their hands
in complete despair. A variety of methods and approaches are at their disposal to aid inquiries about
happiness in the past. Historians might, for instance, follow the lead of the Marquis de Chastellux, who in
the 18th century undertook to write the world’s very first history of happiness by means of proxy data.
Lower levels of slavery, say, or war, or famine, Chastellux reasoned, ought to correspond to higher levels
of what he called “public felicity.” By aggregating such data, Chastellux hoped to sketch the broad
outlines of the history of social happiness (Chastellux, 1772). And although more recent historians have
not, to my knowledge, attempted such an undertaking, they surely can. So too can they undertake
conceptual histories of happiness, examining how different cultures have imagined and understood this
complex phenomenon at different times (McMahon, 2006). There is a particular need to devote energy to
this work in non-western and comparative settings. Finally, historians can draw on the tools developed by
their colleagues in the sub-discipline of the history of emotions, who ask how emotions are channeled and
expressed under different affective or “emotional regimes” (Reddy, 2001; Stearns, 2012; McMahon,
2013). Although any one of these approaches might be pursued separately, this article draws on elements
of each of them in order to sketch, in broad terms, three crucial turning points or “revolutions” in the long
history of human happiness. Insight into the different ways that human beings have conceived,
experienced, and defined happiness in the past, it is hoped, may be of service to those who think about
happiness in the present, and pursue it in the future.
The Deep History of Happiness
How happy were our earliest human ancestors? The question, of course, admits of no easy answer,
and yet it is striking how many cultures of the world seem intent on attributing an original happiness to the
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very first human beings. Myths of a lost paradise or a vanished golden age are virtually universal in
human culture, and their consistent accounts of teeming abundance and ease are striking. At the very least,
such accounts can offer clues into how human fortunes have changed over time, to say nothing of men and
women’s capacity to imagine circumstances better than their own.
For the men and women who first fashioned these myths may have been onto something.
Archeologists and anthropologists today emphasize that early human existence was surprisingly prosperous
—if not a paradise, then perhaps an “original affluent society,” to cite the well-known formulation of the
anthropologist Marshall Sahlins (1972). In this view, the hunter-gather bands that roamed the earth for
much of the Paleothic era prior to the advent of agriculture roughly 12,000 years ago enjoyed a number of
comparative advantages that their later, myth-fashioning descendants did not. For one, what we now style
the “paleo” diet—rich in protein and fibers and free of refined carbohydrates—was abundant, varied, and
nutritious. Our hunter-gatherer ancestors, it seems, were relatively well-fed. Evidence from fossilized
skeletons and dental remains, for example, suggests that early foragers were less likely to experience
starvation or malnutrition than their farmer-peasant counterparts of later periods, and that they were, on the
whole, of superior stature (Harari, 2015). Average life-expectancy, though brought down by a high
incidence of infant-mortality, was, for those who survived the first years after childbirth, surprisingly high,
upwards of sixty years, which compares favorably to most human societies up until the time of the
industrial revolution. The absence of infectious diseases born of high-density populations and domesticated
livestock, moreover, meant that the curse of large-scale epidemics was unknown. With only 5 to 8 million
foragers inhabiting the earth on the eve of the Agricultural Revolution there were ample resources and
room to move about, which meant that tensions both within and between bands could be diffused by simply
moving on. An alternative to war was flight, and a strategy for dealing with excessive coercion was to
leave the group and strike out on one’s own. As a number of scholars have concluded, this meant that
early hunter-gatherers likely enjoyed a significant degree of freedom, and, in the absence of accumulation
and private property, equality (Maryanski & Turner, 1992; Sanderson, 1995; Boehm, 2001; Veenhoven,
2005). Certainly their fortunes were superior in these respects to those of the vast majority of men and
women born into the highly stratified and coercive societies that followed in the wake of the Agricultural
Revolution, in which slavery was common and inequality the norm (Scheidel, 2017). Finally, foraging
peoples had the luxury of time. Rough calculations suggest that the average “work week” of huntergatherers—measured
in the hours necessary to ensure the supply of food and to perform essential tasks—
was considerably less than that of modern workers, leaving ample opportunity for leisure, recreation, and
social interaction in settings that were favorable to close interpersonal interaction (Sahlins, 1972; Harari,
2015).
Of course, it is important not to substitute our own myths for the myths of old, imagining the huntergatherer
past as some sort of sylvan idyll before humanity’s corruption and fall. Modern observers, it is
true, have not always avoided that temptation. But clearly life in the Paleolithic period was never a golden
age. Even after our Homo sapiens ancestors rose, with the help of fire, tools, and teamwork to the top of
the food chain within the last 100,000 years, they still were susceptible to attack by a variety of fierce
predators—not least, other members of the genus Homo. The evidence of mass grave sites in the
Paleolithic period—replete with shattered skulls and severed limbs—belies any easy assumption that our
ancestors lived in uninterrupted peace and harmony. And however abundant their streams, forests, and
savannahs, eking out an existence—above all in the long winters of the long ice age—was never an easy
task. In the end, the life of foraging peoples in the Stone Age was, just as it has been for the great majority
of those who came after, a struggle.
Still, when we compare this earlier period with the settled societies that began to spring up in the wake
of the Agricultural Revolution, we can understand how later observers might have looked back with a
certain elegy. For the broadly egalitarian existence of hunter-gatherers, with their relative freedom and
prosperity, gave way to societies of a very different sort, characterized by a far greater degree of hierarchy,
inequality, and oppression, as well as the persistent threat of famine, war, and disease. The paths to these
destinations, of course, varied considerably, and they frequently doubled-backed. Yet in their circuitous
ways, they led across the threshold of what the scholar Walter Scheidel has called “the great
disequalization,”, the “transition to new modes of subsistence and new forms of social organization that
eroded forager egalitarianism and replaced it with durable hierarchies and disparities” of income, wealth,
and power (Scheidel, 2017). Agriculture was an important (though not the only) driver in this process,
permitting accumulation and surplus, which could then be transmitted to one’s offspring, perpetuating
status and power. Concentrated state power was another (Scott, 2017). Inequalities followed in turn, and
were gradually rendered hereditary, setting humanity on a road to “monarchy, slavery, and empire,” and the
incessant wars needed to create and defend these institutions (Flannery & Marcus, 2012).
To be sure, there were winners in this process. Those who were able to concentrate the surplus
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wealth generated by farming—most often in close concert with emergent states—did far better than their
forager ancestors could ever have dreamed—so much so that this early elite has been styled the “original
1%” (Scheidel, 2017). But for the vast majority, lowly peasants and laborers now tied to the land and
crowded in settled communities, the tradeoffs were extensive. Although agriculture meant a greater sum
total of food (and so expanding populations), the end result was to keep more people alive in worse
conditions than they had known before. Diets were increasingly less varied and nutritious, as the shift to
agriculture favored carbohydrate-heavy foods such as rice, grains, corn, and potatoes that were high in
calories but low in essential nutrients. The labor required to tend to them, moreover, was backbreaking and
monotonous, and the reliance on a limited number of staples rendered populations susceptible to crop
failure and famine. When combined with the parasites and epidemic diseases spread by domesticated
livestock and communicated via concentrated populations, and the war, violence, raiding, and social
conflict that attended territorial competition, the picture that emerges is far from pretty. On a range of
indices from life-expectancy to stature many human beings around the world would not obtain the levels of
their hunter-gather ancestors until after the industrial revolution, if then (Clark, 2007). It may be an
exaggeration to say, with Jerrod Diamond, that the transition to agricultural societies was “the worst
mistake in the history of the human race” (Diamond, 1987). But the point is well taken. At the very least
it reminds us that history is not an inevitable march of progress. Some “advances” actually set us back.
The first revolution in the history of human happiness, it seems likely—our exit from our hunter-gatherer
past—was an unhappy one.
Why, then, did men and women leave? Hindsight, of course, is 20-20, and the first agriculturalists
had no way of foreseeing the human future. Some were coerced, and others tempted into settlement,
seeking security in greater numbers. But the broader answer is that evolution is not interested in the fate of
individuals, but in the perpetuation of species. Agriculture, for all its drawbacks, enabled Homo sapiens to
expand exponentially, even when the quality of individual lives suffered (Harari, 2015). From an
evolutionary standpoint, greater population was a victory in itself.
It is true that an evolutionary account also suggests that human beings must be happy enough to want
to reproduce and carry on. Darwin himself posited an adaptive role for happiness, observing that the
“vigorous, the healthy, and the happy survive and multiply,” and evolutionary psychologists have further
developed that insight (Darwin, 1859; Buss, 2000; Grinde, 2002; Hill, DelPriore, & Major, 2013). If
happiness as positive affect is often good for us, they reason, it was also good for our ancestors, who did us
the favor of passing on their genes. Good feelings could serve as a carrot to induce adaptive behaviors and
a reward for acts that contributed to our fitness, such is social bonding, the search for nourishing food, and
sex. Then again, negative affect in the form of jealousy, anxiety, and fear, could serve as a powerful stick,
ensuring that we never got too happy for our own good. The picture that emerges from such accounts is
one of human beings inclined to adapt quickly to their pleasures, so that they will then set off in search of
more. Restless creatures, we are rarely satisfied for long. And it may be that our long evolution in the
conditions of the Stone Age has given us a reward system (and anxieties and fears) that are maladapted to
the conditions of the modern world.
But if consideration of the early human past can provide material for speculation about our subsequent
psychology, it may also help historians understand why so many cultures that developed in the aftermath of
the Agricultural Revolution looked with longing to that time long ago, imagining an Arcadian golden age of
plenty and ease in contrast to their own experiences of uncertainty and periodic privation. It is altogether
telling that the earliest recorded words for “happiness” in virtually every human language are cognate with
fortune or luck (McMahon, 2006; Oishi, Graham, Kesebirm, & Galinha, 2013). For cultures regularly
subject to upheavals and twists of fate—from the descent of plague to the appearance of a marauding army
to the onset of famine or the wrath of one’s betters—it was difficult to imagine happiness as something that
could endure, still less as something that one could control. Happiness, rather, was in the hands of the gods,
meted out by fortune, or forged in the crucible of fate. And though the prosperous might better hedge
against uncertainty than the poor, even they were not immune to the upheavals and sudden reversals that
inevitably threatened us all. As ancient Chinese sages cautioned, misfortune (huo) was fortune’s ( fu)
twin. That reflection figures in some of the earliest extant writings of China, and it was repeated down
through the ages. As the Daoist philosopher Lao Tsu observed around 500 BCE: “Misfortune (huo) is that
which beside fortune (fu) lies” (Keping, 2001). Artabanus of Persia, as interpreted by the Greek historian
Herodotus in the 6th century BCE, echoed this wisdom, but in even darker tones, voicing assumptions that
were shared in many cultures.
Short as [the human life] is, there is not a man in the world, either here or elsewhere, who is happy
enough not to wish – not once only but again and again – to be dead rather than alive. Troubles
come, diseases afflict us, and this makes life, despite its brevity, seem all too long (Herodotus,
2003).
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The reckoning was grim, reflecting a view of the world as at once hostile and unpredictable, in which
suffering was the norm. It was a world governed by forces beyond our control. And in such a world,
happiness must be elusive and fleeting. To conceive of it otherwise—as something that could endure in a
world of change—would be to imagine a supreme, even superhuman, achievement, happiness as something
divine.
Happiness in the Wisdom Traditions of the Axial Age
In the aftermath of the Second World War, the German philosopher Karl Jaspers published his Vom
Ursprung und Ziel der Geschichte (1949), “The Origin and Goal of History.” An audacious work, the
book departed from what Jaspers characterized as an article of faith: that mankind has one single origin and
goal. And it advanced the view that world history, as a consequence, possesses a coherent meaning,
structure, and end. Few practicing historians are liable to share that view today. And yet scholars,
particularly those of world religions, continue to draw on one of Jasper’s central themes: the formative
influence of what he called the “Axial” age, through which ran the axis of history (Bellah & Joas, 2012). It
was this period, Jaspers argued, spanning roughly the first millennium BCE, that witnessed the emergence
of the world’s great religious and wisdom traditions: from the Confucian and Daoist teachings of China to
the doctrines of the Upanishads and the Buddha in India, to the Hebrew prophets in Palestine and the great
philosophers of Classical Greece. And though other major traditions were to follow—most notably
Christianity and Islam—they built on spiritual foundations already established. The Axial Age, Jaspers
contended, bequeathed to humanity a store of spiritual values on which it has continued to draw. “Until
today mankind has lived by what … was thought and created in that period” (Jaspers, 2010).
Jaspers himself did not consider the subject of happiness or human flourishing directly. But students
of religion who have addressed the impact of the Axial Age have. And in the opinion of one of them, the
noted philosopher Charles Taylor, the “most fundamental novelty” of the Axial revolution was precisely its
“revisionary stance toward the human good.” “More or less radically,” Taylor maintains, “all of [the Axial
religions] call into question the received, seemingly unquestionable understandings of human flourishing”
that had reigned previously (Taylor, 2012). The Axial religions, in short, reconceived and redefined human
happiness.
Each did this, of course, in unique ways. But there were, nonetheless, striking commonalities. Most
importantly, the wisdom traditions explicitly challenged purely worldly or mundane understandings of
happiness as plenty, prosperity, pleasure, or power. Fantasies of freedom and abundance of the type that
had likely drawn the imaginations of the poor and powerless since the advent of the Agricultural
Revolution (and continued to do so long after) were not always rejected outright: milk and honey might
still be seen on the horizon. And it is also true that the various Axial creeds adopted differing perspectives
on the instrumental value of material prosperity—with some, Confucians say, or Aristotelians, arguing that
a certain degree of wealth was a prerequisite to the pursuit of the higher aspirations of the good life, and
others emphasizing the inherently corrupting nature of pleasure and affluence. In most cases, however,
moderate worldly prosperity was seen, at best, as a means to higher ends, never as an end in itself. To
pursue wealth for wealth’s sake, all agreed, was to succumb to one of the many dangerous temptations that
common understandings of happiness dangled before us, as if mere riches, power, or sensual satisfaction
could fulfill us. Genuine happiness required something more—a connection to the transcendent, to God or
the gods, to the Good or the True. It involved, as Taylor asserts, a “going beyond” ordinary human
flourishing, however such flourishing might be conceived locally (long life, prosperity, freedom from
disease, drought, natural catastrophe, etc. (Taylor, 2012). For the Axial traditions, human happiness must
always entail something else.
The Daoist philosopher Zuhang Zi expressed this nicely in the 4 th century BCE with the seemingly
paradoxical assertion that “Perfect happiness is without happiness” (zhi le wu le), by which he meant that
true happiness did not depend on those things that people in the world often considered to be valuable
sources of (ordinary) happiness, such as easy living, good food, wealth, longevity, and the like (Keping,
2001). Indeed, those who devoted themselves solely to such worldly goods and pleasures were “upside
down people,” whose priorities had been inverted (Ivanhoe, 2013). Genuine happiness required devotion
to the Dao or Way, the true order and harmony of the universe that transcended the self. Similarly, in this
respect, the master Kongzi, known as Confucius in the West, taught that living well went far beyond
ordinary pleasures and comforts. Rather, it involved knowing how to find joy in the right things in the
right ways. Kongzi emphasized the importance of good conduct to others and the value of family and
friends, while praising behaviors, rituals, and rites that took us beyond ourselves, connecting us to the
deeper structures and patterns of the universe. It was in this alignment, he believed—between the
individual and the transcendent, between right conduct and right order—that true harmony, peace, and joy
could be found.
24
In their common rejection of “ordinary” happiness, conceived largely in hedonic terms, Axial
understandings of happiness were thus invariably “eudaimonic,” concerned less with good feeling and
enjoyment for their own sake, than with living optimally, living well. The very term (eudaimonic), of
course, emerged in the context of the Axial wisdom traditions of Classical Greece, employed by Socrates
and Plato in explicit contrast both to good fortune (eutychia) and to sensual pleasure (Nussbaum, 1986). As
described by their acolyte Aristotle, eudaimonia was the “highest good,” a characterization of a life lived
fully in its entirely. Neither a fleeting feeling nor an ephemeral emotion, eudaimonia was the product of
discipline, dedication, and craft. Eudaimonia, in short, required what Aristotle and the Greeks called arête
(virtue).
Regardless of the word used to describe it, however, the insight that human flourishing demanded the
development of human excellence—the cultivation of particular strengths of character and mind—was
another common assumption of Axial understanding of happiness. Moses and the Buddha, Aristotle and
Confucius, the author of the Upanishads and the Stoics were of one mind on the matter. To learn to live
well required preparation, training, and perseverance, a discipline of the body and of the mind. We were
not born into the world knowing how to live at the highest level of excellence. This was a skill to be
acquired, practiced, and perfected. Living well was a way of life, and it was never easy.
The various traditions took different stances on the role played by the divine in this process. Was
revelation necessary for enlightenment? Did human perfection require grace or the direct assistance of the
gods? Or did we all, as the Buddhists maintained, have within us the full potential to live happy lives?
Regardless of the individual positions taken on these and a range of related questions, none of the Axial
traditions denied the importance of the human element in realizing human perfection. Happiness, in other
words, did not just happen by chance. It was a product of our characters, of who we were and of who we
chose to be. To live well was to make choices about how best to live, and about what kinds of virtues to
cultivate in the service of a flourishing life.
Once again, the range of recommendations on these matters put forth by the various wisdom traditions
was extensive. And though it may be that there are certain basic character strengths that are lauded
universally across cultures, to enumerate them in any detail here would be to go beyond the scope of the
present inquiry (Peterson & Seligman, 2004; Haidt, 2006). Still, it is useful to call attention to a number of
key virtues and insights extolled by the Axial traditions that have drawn commentary in the more recent
scientific literature in relation to human flourishing. Virtually all of the wisdom traditions, for example,
reinforce the virtues of gratitude and forgiveness, urging us to express thanks for what we have, and to treat
with indulgence those who have done us wrong. Virtually all of the wisdom traditions, likewise, cultivate
the virtues of optimism and hope, recommending that we make an effort to see the good in the world, to
keep alive its possibility, and to trust that it is there, even (especially) when it is hard to see. Virtually all of
the wisdom traditions, furthermore, cultivate the importance of friendship, fellowship, and loving kindness,
extolling compassion, love, and human understanding as among the highest expressions of the soul. And
so virtually all foster the insight that magnanimity and charity to others are not only good in their own
right, but good for oneself, recommending the injunction later voiced by Jesus: Give and you shall receive.
Finally, virtually all the wisdom traditions operate on the assumption that there are powerful forces at work
in the human mind (and flesh) that militate against the cultivation of every one of these virtues (and others
besides), meaning that to craft a flourishing life will inevitably be a challenge—a difficult one—a process
of self-mastery that demands continual attention and training.
The upshot of these prescriptions for pursuing a flourishing life is that many—indeed most—will not
be up to this challenge. The Buddha, who maintained that all human beings have the capacity for
happiness, acknowledged as much when he asserted that all life is suffering, misery, and pain. Most people,
that is, live lives of ignorance, illusion, and craving. They could change this by seeking enlightenment, but
alas most don’t. The other Axial traditions tend to agree: those virtuosi who successfully devote
themselves to cultivating genuine human flourishing are necessarily an elite. The happy, as Aristotle says,
are the happy few.
Although the great Post-Axial faiths of Christianity and Islam developed their own variations on these
themes—while accentuating the importance of the afterlife, where the inevitable sufferings of this world
would be overcome—they did not depart essentially from the basic perspectives on human flourishing
elaborated here. Many might be called, but few would be chosen. True happiness, whether of this life or
the next, remained an extraordinary achievement.
And so humanity plodded on, taking its pleasures where it could, while accepting that happiness—
both of the ordinary and extraordinary kind—was more the exception than the rule, the provenance of the
lucky, the privileged, and the powerful, on the one hand, and the chosen, the enlightened, and the saved on
the other. This is not to say that human beings were less happy (or more) in those times than their later
25
descendants. In the absence of surveys and direct reports, that question, to repeat, can only be addressed by
proxy. Chastellux, for his part, thought that his own age (the 18th century) was the happiest in the history
of the world, and there are those among us today who would be inclined to say the same about our own day
on the basis of other metrics (average life expectancy for one), building a case for progress over time
(Veenhoven, 2005). Then again, we know that human adaptation is a powerful force, and in the absence
of direct comparisons, it may be that people of previous times and economic fortunes were just as happy as
we are now (Clark, 2007). Historians should devote more attention to the matter.
What we can say here, however, is that regardless of how men and women of the past may have felt,
experientially, from day to day, their expectations about how they should feel were very different from our
own. That was as true in China as it was in Africa or Europe. For until at least the 18th century, men and
women across the globe lived in societies that regarded, with good reason, suffering and scarcity as the
norm. In societies such as these, happiness might be a hope or a dream, an aspiration or an achievement, or
a turn of the wheel of fortune. But it was seldom an expectation, and rarely, even for the most privileged,
was it assumed. That would only begin to change—and with powerful consequences—with the dawning of
the great revolution in human expectations of the long 18th century.
The Revolution in Human Expectations
It is a striking fact that in 1800 the economic condition of the average human being in the world was
no better than it had been in the Stone Age (Clark, 2007). Life expectancy was no better either, and
average stature was actually worse. Despite impressive outliers—soaring cathedrals, great pyramids,
palaces, and sprawling estates for the landed and wealthy—very little had changed in the economic history
of the world.
But change was on the horizon, and indeed had already begun in Western Europe and its North
American possessions, preparing the way for the tremendous economic takeoff of the Industrial Revolution
and what historians now refer to as the “Great Divergence,” the unprecedented economic gap that began to
open up between the West and the rest in the late 18th century (Pomeranz, 2000). To look at a graph of
average income since 1800 is to watch fortunes soar.
What was the place of happiness in this development? Some economic historians answer that it was
considerable (McCloskey, 2016). They point out, for example, that towards the end of the 17th and the
beginning of the 18th century, one can detect an important shift in Christian theological reflection, which
began to speak less of deferring our happiness until the next life and more of making it here below. Deemphasizing
sin and the fires of hell, Christians stressed instead God’s benevolence and desire for our
well-being during our earthly sojourn. Did not God want us to be happy? By mid-century, an erstwhile
Calvinist like Benjamin Franklin was expressing amazement that Christians could reflect any other way.
“‘Tis surprising to me that men who call themselves Christians,” he observed, “should say that a God of
infinite perfections would make anything our duty that has not a natural tendency to our happiness”
(Franklin, 1960). Increasing numbers of his contemporaries on both sides of the Atlantic were becoming
convinced that the Creator would not. As the historian Roy Porter (2000) has aptly observed, the old
question “How can I be saved?” was gradually giving way to the new question “How can I be happy here
below?”
These changes in religious reflection, which increasingly sanctioned the pursuit of happiness on earth,
were accompanied by a new rhetoric and apology for pleasure put forth by thinkers associated with the
Enlightenment (McMahon, 2006). Inspired by the thought and example of Isaac Newton, they drew the
conclusion that the universe was not random and chaotic, but ordered and predictable, governed by rational
principles that could be ascertained through human reason. And if human beings could know and
understand the natural world, then they could certainly know and understand the human world, a world of
their own making. Setting themselves that task, they labored not only to understand, but to improve.
Surely it was no sin to seek greater comfort in life, and to work to better our condition? And why should it
be taboo to enjoy our own bodies and the pleasures of the world? Were not human beings constructed so as
to pursue pleasure and to flee pain? Pleasure was natural and nature intended us to be pleased. Human
beings, in short, were meant to be happy.
Thus, a growing Enlightenment confidence that humans being could control their fate was
accompanied by a frank apology for pleasure and happiness. The two, in fact, were increasingly spoken of
as one and the same. When the great English utilitarian philosopher Jeremy Bentham recommended that
the “greatest happiness of the greatest number” be the standard by which we judge, he understood this to
mean the maximization of pleasure and the minimization of pain (Bentham, 1996). Pleasure was good,
26
pain was bad. We should work to spread the one and mitigate the other. That belief, in the 18 th century,
was widespread (McMahon, 2006).
And so the Enlightenment apology for happiness worked to undermine both the perennial view that
saw happiness as a function of fortune—something we cannot ultimately control—and the longstanding
assumption common to Christianity and the wisdom traditions that happiness was a product of superior
virtue or grace, a rare and special achievement in a world in which suffering was the norm (McMahon,
2004). “Does not everyone have a right to happiness according to his whims?”, asked one 18th-century
observer in that bible of the Enlightenment, the French Encyclopédie. Judged by historical standards, the
question was remarkable: a right to happiness?! And yet it was by no means an isolated claim, reflecting a
growing belief that justice demanded the happiness of all. Since human beings were meant to be happy, it
followed that when they were not, there must be a reason—injustice or false belief, oppression or
individual failure. Governments, accordingly, should work to provide the conditions in which human
beings could flourish. “The happiness of society is the first law of every government,” declared the
American founding father James Wilson (2007). The French Jacobin constitution of 1793 imbedded the
assumption in its very first article: “The goal of society,” it declared, “is common happiness.” Here was a
creed for a new age.
It was also a creed for a new economy. For regardless of the precise role played by Enlightenment-era
discussions of happiness in fostering the economic take off that ensued, clearly an apology for earthly
happiness and material improvement was conducive to economic growth. And clearly economic growth—
with a new culture of consumption proffering luxury items, comforts, and pleasures to expanding segments
of the population—was conducive to the belief that suffering need not be an unfailing law of the universe.
As the 18th-century French economist and administrator Anne Robert Turgot observed, in modern
commercial society men and women “buy and sell happiness” in the form of discrete packets of pleasure.
Modern economies, it seemed, lent themselves perfectly to happiness’s pursuit.
Whether they lent themselves to happiness’s attainment was another matter. That claim, of course,
would be hotly contested in the 19th and 20th centuries, with socialist and Marxist critics of capitalism,
among others, charging that it did no such thing. But what united all parties in the dispute was the common
assumption that happiness is, and ought to be, the human due. This was the novel consequence of the
revolution in human expectations of the long 18th century. The dramatic economic growth that followed,
however imperfectly distributed between countries and classes, only fed those expectations, spreading the
demand for happiness ever wider. Already, in the middle of the 19 th century, the Scottish critic Thomas
Carlyle could draw attention to this remarkable transformation, noting that “Every pitifulest whipster that
walks within a skin has had his head filled with the notion that he is, shall be, or by all human and divine
laws ought to be, ‘happy.’” Carlyle was a skeptic, a dissenter to the new creed of happiness as our “being’s
end and aim … not yet two centuries old in the world” (Carlyle, 1965). Yet he had put his finger on the
way in which that creed had a tendency to crowd out other organizing principles of life, as well as to spread
downward and outward to formerly marginalized segments of the population. Notwithstanding two world
wars and the incalculable tragedies of the 20th century, it has continued to do so, hastened since the 1960s,
as the philosopher Pascal Bruckner has argued, by the expansion of personal credit and an ascendant
individualism that has further licensed an ethic of personal fulfillment and non-delayed gratification.
Happiness, today, Bruckner (2011) observes, constitutes “the only horizon of our modern democracies.”
Meanwhile, globalization in the wake of decolonization, notwithstanding its other effects, has begun to
narrow the economic gap that opened up with the Great Divergence, exposing hundreds of millions more
(above all in China, India, and the emerging Asian economies) to the prospect that happiness on this earth
might be more than good fortune or a millenarian dream. The fact that today the United Nations, along
with Gallup, the OECD, and other international organizations, collect data on happiness in every country of
the world is a sign of this expansion, an indicator of the aspiration that all might be happy one day and that
we should work to make it so. The overall significance of this expansion, however, in historical terms, and
the “meaning” of the rise of a global conversation about happiness is not yet clear (McMahon, 2010).
Conclusion
In this brief essay, I have examined three major developments in the history of human happiness,
presenting the departure from our hunter-gatherer past at the time of the Agricultural Revolution, the
emergence of the wisdom traditions of the “Axial Age” of the first millennium BCE, and the “Revolution in
Human Expectations” of the long 18th century as crucial turning points in humanity’s experience and
understanding of happiness. Judging by a number of indicators, there is reason to conclude that the first
revolution was on balance detrimental to the happiness of the many, even as it provided new opportunities
27
to the few. In hostile and unpredictable environments of relative scarcity and insecurity, suffering was
regarded as the human norm, while happiness was represented as largely beyond our agency and control, a
fortunate condition bestowed by the gods or luck, and seldom lasting or assured.
Yet this prevailing and perennial conception—common to virtually all early societies and kept alive in
the folk cultures of many peoples to this day—was profoundly challenged by the great religious and
philosophical traditions of the Axial Age. Taking up the problem of human suffering, they sought means to
address it, asserting collectively that human beings do not live by bread alone. True happiness, they
agreed, involved a “going beyond” conventional prosperity and the ordinary conditions of life in the pursuit
of a higher happiness predicated on the cultivation of human virtue and excellence. Retaining the view
that happiness was a rare exception and human suffering the norm, they nonetheless wrested human
flourishing away from the clutches of fortune, making it in large measure the product of human will and
action aligned with what were deemed the transcendent forces of the universe.
In a very general way, these were the basic orientations on human happiness that held sway in most
parts of the world until the 18th century, when a revolution in human expectations began to alter
perspectives on the prospects for happiness in this life. Forthrightly hedonic in their equation of happiness
and good feeling, these new perspectives presented happiness neither as a matter of chance nor as a reward
for superior virtue. Happiness, rather, was treated as a natural endowment, whose pursuit and attainment
would follow from the mitigation of pain and the removal of “unnatural” barriers, such as injustice and
false belief, that stood in its way. Coinciding with the beginnings of a remarkable economic transformation
that continues to this day, this revolution had the effect of gradually eroding the older, eudaimonic
perspectives on happiness that had long equated human flourishing with virtue of character.
Needless to say, this revolution occurred only slowly and imperfectly. Yet the dominant ideological
systems of the 19th and 20th centuries helped to spread the prospect of happiness to ever wider segments of
the world’s population, radiating outward from Europe and the New World, so that today more people than
ever before are being raised in environments that inspire the pursuit of earthly happiness and encourage
expectations that it will be found.
Whether or not such pursuits and expectations correspond to actual increases in levels of happiness is
a matter of considerable debate within the contemporary social scientific community, which has pioneered
efforts in the last several decades to measure happiness around the world, and to analyze its causes and
correlates in relation to economic conditions and other variables. To a significant degree these efforts have
drawn on, and contributed to, the new “science of happiness” pioneered by positive psychologists, who
have also turned their attention of late to better understanding happiness’s foundations. Working together,
they hope to help not only individuals, but governments and policymakers, shape better policies and
prescriptions for the future.
From the perspective of the student of history, it is noteworthy that there have been significant
overlaps between the “modern truths” of the new science of happiness and “ancient wisdom,” particularly
the eudaimonic insights of the Axial traditions and their post-Axial successors (Haidt, 2006; McMahon,
2016). Research on gratitude, for example, or on charity and loving kindness, meditation and meaning,
forgiveness and hope has demonstrated the benefits of these “virtues” in encouraging flourishing lives.
Such research would suggest that those who spearheaded the revolution in human expectations initiated in
the long 18th century may have been too quick to denigrate and displace the older insights of the Axial
traditions. Whether those insights can now be updated with the imprimatur of science and adapted to
cultures that have largely accepted the hedonic and democratic consequences of the 18th-century revolution
in human expectations remains to be seen. The history of happiness, and in particular the first great
revolution examined here, cautions against any facile assumption that “progress” and happiness necessarily
go hand and hand. But it also makes room for the possibility that they can advance together. For those
hoping to use the knowledge about happiness being generated by researchers today to better guide the
policies and prescriptions of tomorrow, aligning the two will be the great challenge, and historians have a
role to play in this alignment by further clarifying the relationship between happiness and
progress/historical change in the past. Should we succeed in our collective endeavors, we may hope,
however modestly, to contribute to the beginnings of a new revolution in the happiness of the world.
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Religion and Well-being
By David B. Newman, University of Southern California; Jesse Graham, Eccles School of Business,
University of Utah
Citation
Newman, D. B., & Graham, J. (2018). Religion and well-being. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
Religion plays an important role in the lives of many people. To understand how religion relates to wellbeing,
it is important to consider the beliefs and practices of the world’s main religions. In the first section,
we begin by describing how various religions define well-being and how religions envision God. Next, we
outline various beliefs about the afterlife and key religious teachings that may affect well-being. In the
second section, we describe how religious practices such as prayer, meditation, and fasting could influence
one’s well-being. We conclude by arguing that it is crucial to consider the specific beliefs and practices of
religions to understand more fully how religion relates to well-being.
Keywords: Religion, Well-being, Overview
Religion is a central part of the lives of many people. According to one estimate, 68% of humans
claim that religion is an important part of their lives (Diener, Tay, & Myers, 2011). According to a 2016
Gallup poll, roughly 51% of Americans attend church or synagogue once a month or more frequently
(Gallup, 2016). Given the paramount role of religion in many people’s lives, it is important to understand
how religious beliefs and traditions could relate to individuals’ well-being.
Research suggests that people who engage in religious activities report higher levels of well-being
(Diener et al., 2011; Hackney & Sanders, 2003; Oishi & Diener, 2014). More specifically, religious
individuals report higher levels of life satisfaction and positive feelings in the US (Diener et al, 2011) and
lower levels of depression in the US and Europe (Smith, McCullough, & Poll, 2003). These effects tend to
be small and positive, and the effects also depend on the level of analysis (Tay, Li, Myers, & Diener, 2014).
For example, within countries, religion can fulfill needs such as a sense of belonging and community
affiliation, which promote well-being. Between countries, religious practices could increase volunteerism
and altruistic behaviors. The relationship between religiosity and well-being in non-western nations also
appears to be positive but weak (Tay et al., 2014).
In many of these studies, religiosity has typically been measured with a single item, such as “Is
religion an important part of your daily life?” or “Thinking about your life these days, how often do you
attend religious services, apart from social obligations such as weddings or funerals?” Although such
measures could be informative in predicting well-being, specific religious beliefs and practices could relate
to well-being in nuanced ways. In order to more fully understand the complex relationship between religion
and well-being, researchers should carefully consider what religions say about well-being. The goal of this
chapter is to provide an overview of these teachings, and of how the beliefs and practices of the major
world religions relate to well-being.
To provide an overarching framework to this chapter, we rely on the distinction of doxis vs. praxis
often used to define religions (e.g., Snoek, 1999). Doxis, from the Greek word doxa, refers to worldviews,
beliefs, and thoughts, whereas praxis refers to actions, rituals, and practices. Religions are often defined by
these two characteristics. Given these two dimensions, we believed it would be helpful to use this
distinction in framing our chapter.
To narrow our focus within each of these broad dimensions of religion, we rely on the
conceptualizations of religion developed by Ninian Smart (Smart, 1998, 1999). According to Smart, a
religious framework is composed of seven dimensions: narrative/mythological, doctrinal, ethical,
institutional, material, ritual, and experiential (Smart, 1999). These dimensions capture the broad and
encompassing nature of religion. The narrative dimension refers to the foundational stories of a religion,
passed down through history either orally or written. These stories often concern the religion’s founder.
The doctrinal dimension is related to the narrative dimension as it refers to the philosophical nature of the
religion, such as the nature of God. Next, the ethical dimension refers to the rules or laws of a religion. The
social or institutional dimension concerns the organization and gathering of a religious community, for
example in a church, mosque, or temple. Religions typically designate a particular day of the week for
worship in addition to particular days of celebration or remembrance during the year. Somewhat related, the
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material dimension refers to specific places and artifacts that are of particular importance to a religion. The
ritual dimension concerns the specific practices in which religions express themselves, such as prayer and
meditation. Finally, the experiential dimension refers to the strong emotional experience connected to the
rituals that provide them with meaning.
The advantage of such an organization and framework allows one to categorize and define a
religion. Of course, debate continues as to the best way to do this and whether it is even possible (cf.,
James, 1902). Putting this debate aside, we opted to use a common-sense approach by describing the main
world religions. Most individuals are familiar with the names used to define the world’s core religions, and
some scholars categorize religion using these common labels (e.g., Christianity, Judaism, Hinduism, etc.;
Smith, 1991). Similar to Smith’s categorization, we believed that fine distinctions between particular
religious denominations, such as the difference between Baptists and Presbyterians, would not be fruitful
for a concise overview. Therefore, we have opted to rely on Smart’s dimensions of religion to guide our
discussion of how religion relates to well-being while still referring to core religions. After discussing the
main topics and dimensions, we will provide examples from the major world religions, such as Christianity,
Judaism, Islam, Hinduism, and Buddhism.
In the first half of the chapter we cover doxis, religious beliefs and thoughts. First, we describe how
religions conceptualize well-being. Next, we discuss how various religions conceive God (e.g., as a
forgiving and loving father, as a harsh and powerful entity) and how these conceptions might relate to wellbeing.
Following this, we depict various beliefs of the afterlife and how these thoughts could influence
one’s current well-being. Finally, we outline various key rules and guidelines that religions endorse and
what role these rules play in influencing one’s well-being. Finally, in terms of Smart’s dimensions, doxis
covers the narrative, doctrinal, and ethical dimensions.
The second half of the chapter covers praxis, the rituals and practices of religions. We begin with a
description of many common rituals such as prayer, meditation, fasting, religious services, pilgrimages, and
festivals and holiday celebrations. In each of these sections, we discuss the emotional or experiential aspect
that accompanies these rituals. These rituals and practices overlap with Smart’s social, material, ritual, and
experiential dimensions. The chapter concludes with a section on implications for well-being research.
Doxis
The key beliefs and thoughts discussed in this section cover religious conceptions of well-being,
envisagement of God, beliefs about the afterlife, and ethical teachings.
Conceptions of Well-being
Before discussing how religions define well-being, it is important to delineate different types and
definitions of well-being used by researchers. One broad and helpful way of classifying well-being is
through the hedonic vs. eudaimonic distinction (Ryan & Deci, 2001). Hedonic well-being refers to pleasure
and positive feelings. The goal of striving for as much pleasure and hedonic well-being as possible was
even endorsed by the philosophers Aristippus, Epicurus, Hobbes, Locke, and Hume (Joshanloo, 2013a). In
contrast, eudaimonic well-being refers to a sense of meaning, purpose, and fulfillment in life. Plato,
Aristotle, and Fromm endorsed this type of well-being by suggesting that it was more worthwhile to strive
after virtue than hedonic happiness (Ryan & Deci, 2001).
Empirically, hedonic well-being typically includes measures of positive emotions, negative
emotions, and life satisfaction. Someone experiencing high levels of hedonic well-being is assumed to
experience high levels of positive emotions and life satisfaction, and low levels of negative emotions. A
common way of categorizing some of these measures is through the term subjective well-being, which
consists of positive emotions, negative emotions, and life satisfaction (Diener, 2000). Positive and negative
emotions define an affective well-being component, and life satisfaction defines a cognitive well-being
component.
Specific definitions and measures of eudaimonic well-being definitions often vary. Measures of
eudaimonic well-being include self-acceptance, positive relations with others, autonomy, environmental
mastery, purpose in life, personal growth (Ryff, 1989), meaning in life (Steger, Frazier, Oishi, & Kaler,
2006), vitality, and self-actualization (Ryan & Deci, 2001). Despite the many different measures used to
capture eudaimonic well-being, researchers tend to believe that eudaimonic well-being is some form of
well-being that extends beyond pleasant emotions and feelings.
A useful way of categorizing the well-being types is through the categories of evaluative,
experiential, and eudaimonic (Schwarz & Strack, 1999; Steptoe, Deaton, & Stone, 2015). Evaluative refers
to judgments of life satisfaction; experiential refers to emotions, often captured in real time through the use
of ecological momentary assessment techniques (Shiffman, Stone, & Hufford, 2008); and eudaimonic
refers to a sense of meaning and purpose in life. In terms of the broader distinction between hedonic and
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eudaimonia, evaluative and experiential would fall under the hedonic category.
With this categorization in mind, it is important to understand what happiness and well-being mean
in different religious contexts. Certain differences in relationships between religious practices and wellbeing
could stem from how religions define well-being. In Judeo-Christian traditions, two primary Hebrew
words are used to refer to happiness: ashrey and smh (Charry, 2010). Ashrey is often translated as “blessed”
or “happy” although it does not refer to a subjective pleasant state or feeling. This word is often found in the
Psalms and the book of Proverbs. Typically, this word is used in connection to God and God’s teaching.
Grammatically, ashrey always accompanies another noun to describe the meaning of the word. For
example, Psalm 1 begins with the word ashrey: “Blessed (ashrey) is the man who does not walk in the
counsel of the wicked….” One would not use the word ashrey as a self-descriptive adjective the way one
might use the word happy in contemporary language (e.g., “I am happy”).
In Greek, ashrey is translated as macarios, which could also be defined as happy or blessed. The
word macarios is the word used often in Jesus’ sermon on the mount. Here the word macarios is used in a
similar way to its use in the Old Testament, in connection to God’s commands (e.g., “Blessed ( macarios)
are those who hunger and thirst for righteousness…”; Matthew 5:6).
The word ashrey has been defined somewhere in between hedonic and eudaimonic well-being
(Charry, 2011). Although it is often translated as happy, its meaning is certainly different from a pleasant
emotional state one might experience at a party. Perhaps ashrey could be considered closer to eudaimonia
as it refers to a sense of “enduring pleasure, contentment, satisfaction…” (Charry, 2011, p. 244), but this
must be connected to a life characterized by obedience to God’s commands.
The Hebrew word smh also means happiness and is found often in the book of Psalms. In contrast
to ashrey, however, smh is more closely related to a positive feeling (Charry, 2010). Smh can also be used
self-referentially (e.g., “I am happy”) and would be categorized as a form of hedonic well-being. Thus,
happiness in the Old and New Testaments can refer to both hedonic and eudaimonic well-being.
The concept of happiness or well-being in Islam is also a complex one. It has often been defined in
terms of physical, social, mental, and spiritual health (El Azayem & Hedayat-Diba, 1994). Similar to
Christianity and Judaism, the concept of happiness is connected to having faith and practicing that faith,
i.e., by obeying commands (Joshanloo, 2013a). Furthermore, the Islamic culture views true happiness as
inner peace that comes from devotion to God (Joshanloo, 2013a). In terms of the hedonic vs. eudaimonic
distinction, the goal of Islam is not to maximize positive emotions or minimize negative emotions (Quran
7:169). Thus, this would seem to favor a eudaimonic goal. However, the Quran also says that Muslims who
follow customs, laws, and lifestyles will experience positive emotions, suggesting some hedonic benefits
of the devout life as well (Joshanloo, 2013a). Moreover, Islam values low arousal positive emotional states
over high arousal positive emotional states, a finding consistent with some cross-cultural research (Tsai,
2007). Thus, the concept of happiness or well-being in Islam consists of both low-arousal hedonic and
eudaimonic aspects.
In Buddhism, the concept of well-being is often connected to a practice and cultivation of an
equanimity mindset that is achieved through meditation. One must first realize that life is suffering (the first
Noble Truth). From this realization, there are multiple steps one should take, outlined in the Eightfold Path,
such as practicing mindfulness and compassion. One purpose of these steps is to detach oneself from the
desires of the world. In light of these teachings, happiness is sometimes defined as the state beyond bliss
that is achieved through right concentration and meditation. Thus, the type of happiness one should strive
to achieve does not refer to the hedonic definition of happiness described and sought after in many western
cultures.
In Hindu traditions, one of the key objectives is kama, which can be defined as pursuit of sensual
pleasures, broadly defined. That is, kama refers broadly to all senses involved in aesthetic experiences, such
as romantic love and the appreciation of beauty in music, art, and food. This concept relates to the notion of
hedonic and eudaimonic well-being. Furthermore, this pursuit of sensual pleasures should not be pursued
over other primary objectives, such as the pursuits of righteousness (dharma), economic prosperity (artha),
and release from sorrow (moksa). Thus, the concept of well-being may not be as highly prioritized as some
other values.
Finally, it is important to briefly describe the moral concept of pursuing happiness across religions.
In Christianity, for example, Jesus taught people to value the pursuit of a life with God rather than a pursuit
of hedonistic pleasures. Jesus once spent 40 days fasting to spend time with God. His teaching to pursue
God rather than pleasure evolved somewhat in the Middle Ages such that Christians believed the pursuit of
happiness to be morally corrupt. In Islam, the pursuit of hedonism has been discouraged since the original
writings of the Quran (Joshanloo, 2013b). Even modern Muslim teachings oppose the pursuit of hedonic
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well-being, although extreme asceticism and celibacy is also not advocated (Husain, 1998). The Buddha
denounced a life of pleasure after becoming aware of sickness and death; He led a life of asceticism until
receiving enlightenment. One of the Buddha’s teachings was that desire, including sensual desire, was a
cause of suffering. In sum, the main world religions do not teach their followers to pursue happiness as
characterized by a hedonistic lifestyle. Rather, they instruct their followers toward a pursuit of deeper
meaning, such as connection to God or a state of mindfulness through meditation. In this way the major
world religions, by urging against simple pursuit of pleasure but promising deeper meaning and purpose,
embody the hedonic/eudaimonic distinction in the modern science of happiness.
Conceptions of God/gods
The way in which one views God or other supernatural powers could potentially influence wellbeing.
For example, viewing God as a harsh, judging figure can lead people to cheat less (Shariff &
Norenzayan, 2011). This action may follow from a sense of fear of punishment that could lower one’s
well-being. The specific views that religions have about God -- from the metaphysical nature of God to
what God is like -- can affect people’s well-being as well.
In Christian and Judeo traditions, the nature of God is quite complex. On the one hand, God is
viewed as a powerful, judging God. For example, when God sends a flood to destroy mankind with the
exception of Noah and his family, God clearly shows power. He is also viewed as a judging God who does
not tolerate sin. Such patterns are seen in the Old Testament in various instances, such as the flood during
the time of Noah. On the other hand, the God of the Bible is also viewed as a loving father who cares for
His children and who forgives those who repent. This view is exemplified in particular in the New
Testament, as Jesus welcomes children to come to Him, places them in His arms, and blesses them (Mark
10: 13-16). In numerous occasions, Jesus also forgave those who had sinned (e.g., a paralyzed man,
Matthew 9; those who crucified Him, Luke 23).
These particular views of God can lead to different well-being outcomes. Imagining God as a
punishing God could lead to a sense of fear which could lower one’s well-being, particularly if one
believes the sins committed are not forgivable. In contrast, imagining a loving God who desires a personal
relationship with people could provide one with a greater sense of hedonic and eudaimonic well-being. The
mechanisms explaining how social relationships could increase well-being could be similar to the
mechanisms explaining how a relationship with a kind and loving God could increase well-being. This
likely improves both hedonic and eudaimonic aspects of well-being.
In Islam, God is viewed as a powerful creator who can judge and also as a merciful and
compassionate God. In a similar manner to the Christian view of God, this juxtaposition could have diverse
effects on well-being. In contrast to the Christian view of the Trinity (i.e., God as three persons in one),
Muslims believe in a monotheistic God, i.e., God as a single entity. They also believe that God cannot be
fully comprehended, but they believe it is possible to have a personal relationship with God. That is, no
intermediary is necessary to communicate with God.
The view of God in Hinduism and Buddhism is a bit less straightforward. There are various
different views in Hinduism about the nature of god, whether one even exists, whether multiple gods exist,
etc. Some Buddhists, such as those part of the Theravada school, follow the teachings of Buddha, but they
would not consider Buddha God in the same way that Christians refer to Jesus as God or the way Muslims
refers to Allah as God. Buddhists who are part of the Mahayana school, in contrast, consider Buddha as a
god. Among the various schools of Buddhism, a main focus seems to center on the practice of teachings
rather than on the nature of God. We will return to the effect of these teachings on well-being in a later
section.
Beliefs about the Afterlife
Another aspect of Smart’s doctrinal dimension concerns beliefs, specifically regarding views of the
afterlife. Similar to common values, these beliefs can have important and somewhat complex associations
with well-being.
A common belief among some of the main world religions is the belief that the afterlife consists of
some form of heaven and hell. In the US, for example, 85% of Christians and 89% of Muslims reported
believing in heaven; 70% and 76% of Christians and Muslims, respectively, believe hell exists (Pew
Research Center, 2014a). Islam describes heaven as a place filled with joy and happiness, also referred to
as paradise (Jannah). Christianity describes heaven as the dwelling place of God (Psalm 33), paradise
(Luke 23), and where the streets are paved in gold (Revelation 21). Hell, in contrast, is described in Islam as
a place of blazing fire. In Christianity, hell is often depicted as a place of weeping and gnashing of teeth.
According to Christian and Islamic traditions, people will face a day of judgment and their fate will
be determined, often by what they have believed or done while on earth. A common belief seems to follow
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the saying that one will reap what one has sown. Good deeds and actions will be rewarded, whereas bad
deeds will be punished.
This view of the afterlife and judgment can certainly influence well-being. One psychological
theory that pertains to these beliefs is systems justification theory (Jost, Banaji, & Nosek, 2004), which
states that individuals want to hold a favorable view of themselves and a positive attitude about the system
and how it is organized. Although the system often refers to current political and economic situations, it
can be applied to beliefs about the afterlife. Some empirical work suggests that the belief in a just world in
which one can rationalize inequality relates positively to life satisfaction (Napier & Jost, 2008).
Although Christianity and Islam believe in some sort of reward and punishment system, it is
important to make a distinction between different views about how one can enter heaven. According to
some denominations of Christianity, one enters heaven by committing good deeds or actions (e.g., going to
church/mass, giving money to the poor, etc.). When asked about whether one will go to heaven, this view
may cause some uncertainty, stress, and worry (e.g., “have the good deeds I have done outweighed the bad
ones?”), which could lower one’s well-being. In other Christian denominations, salvation is not earned by
deeds committed by the individual, but rather it is granted by grace, a sacrifice made by Jesus on behalf of
those who believe in God. This view of salvation by grace likely promotes a sense of calm, relief, and joy
which could increase well-being. This distinction between belief in salvation by grace vs. works -- and its
relationship to well-being -- remains a fruitful avenue for future research.
According to Islamic traditions of the afterlife, both notions of grace and works are important. On
the one hand, Muslims are instructed to pray daily, give to the poor, and fast; they are rewarded based on
these actions. On the other hand, entering Paradise is ultimately based on God’s grace. According to one
hadith by the Prophet Muhammed, “No one of you will enter Paradise by his deeds alone." They asked,
"Not even you, O Messenger of Allah?" He said, "Not even me, unless Allah covers me with His Grace
and Mercy." Some scholars believe that entering Paradise depends on God’s grace, and the level in
Paradise depends on one’s actions. Clearly, grace and action play important roles in understanding the
afterlife in Islam.
Related to the notion of the afterlife is the belief in karma, common in Buddhism and Hinduism.
According to these religious traditions, karma represents a cycle of suffering and rebirth. Actions and
events that occur in one’s life could be the result of the actions of one’s life, either in one’s own past or
from a past life. The general belief is that actions may have consequences in the future. The good deeds
could be rewarded by a higher being. In terms of one’s well-being, this belief could lead to exaggerated
reactions to positive and negative events. For example, when a negative event occurs, one might believe
that God is punishing them even though they did nothing wrong at the present time. Alternatively, when
positive events occur, one might receive a boost in momentary happiness if one believes that this positive
event is a reward for a previous action.
Ethical Teachings
There are certain teachings that are common across many or all of the main religions of the world.
These teachings express moral values, rules of conduct, and ethical principles. Here we describe a few of
these common rules and teachings and explain their relationship to well-being.
The first is the “golden rule,” which states that you should do to others as you would have others do
to you. Practicing this principle should increase one’s well-being in multiple ways. It could increase one’s
eudaimonic well-being by providing one with a closer sense of connection to another. It could also provide
a reciprocal effect in which the recipient of the kind act could become happier which could reflect
positively on the benefactor. Empirically, some research suggests that people tend to report greater wellbeing
on days when they engage in eudaimonic behaviors, such as volunteering, in comparison to days
when they engage in hedonistic activities, such as attending a party or getting drunk (Steger, Kashdan, &
Oishi, 2008). However, doing unto others as one would do unto oneself could also result in lower wellbeing
if these actions require one to sacrifice certain needs that would otherwise increase well-being, such
as autonomy. In fact, when Mother Theresa was engaged in helping the poor, she often felt sad, unhappy,
and lonely (Ward & King, 2016; Zaleski, 2003).
Related to golden rule, according to many religions, it is considered better to give than to receive. In
Islam, for instance, individuals are told that true enrichment comes primarily from the soul. Secondary
importance is placed on material wealth. In Christianity, money is listed as the root of all evil. Pursuing
money can be considered an idol and can lead to greed. Instead, individuals are told to give away a portion
of money back to God as a tithe. It is often said that it is better to give than to receive. In contrast,
according to the Hindu principle of Artha, one should actually pursue wealth or material well-being.
Buddhists believe that money is not intrinsically evil or wrong, but it could be used for the wrong reasons.
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Research has shown that there is a positive relationship between income and well-being, but the
positive effects tend to slope off around yearly salaries of $75,000, depending on the specific well-being
indicator (Kahneman & Deaton, 2010). The way one spends money, however, can influence one’s wellbeing
(Dunn, Gilbert, & Wilson, 2011). Spending money on others, for example, can actually increase
momentary well-being (Dunn, Aknin, & Norton, 2008). Presumably, the act of prosocial spending fosters
social relationships and can make one feel good about oneself.
Many of the world religions encourage its followers to express gratitude. Christians are called to
give thanks in all circumstances (1 Thessalonians 5:18) and express gratitude to God (Psalm 118). The
Quran mentions that the soul will profit by being grateful (Quran 31:12). The Buddha taught his followers
to express gratitude as well. Empirical research suggests that expressing and feeling grateful can increase
one’s well-being (e.g., Emmons & McCullough, 2003; Nezlek, Newman, & Thrash, 2017; Seligman, Steen,
Park, & Peterson, 2005). Relatedly, it is commonly taught that one should not worry. For example,
Christians are commanded to not be anxious about anything (Philippians 4:6). Removing worry can
alleviate stress and improve well-being.
Similarly, many of the world religions encourage or teach their followers to forgive one another of
their wrongdoings. The act of simply belonging to a religious group could even increase the likelihood that
one would forgive others (Wuthnow, 2000). Individuals who tend to forgive others report higher selfesteem
and lower anxiety and depression (Hebl & Enright, 1993). The process or act of forgiving someone
could increase one’s well-being by lowering grief, anger and anxiety (Coyle & Enright, 1997). In one study
examining forgiveness behaviors over time, benevolence toward an aggressor was positively related to
satisfaction with life, positive mood and was negatively related to negative affect (Bono, McCullough, &
Root, 2008). Thus, the teaching to forgive another of their wrong could help improve one’s well-being.
Moreover, one should not compare oneself with others, but rather should be content with what one
has. The Bible often warns people to not compare them with others, but to think about how God views
them. In Islam, individuals are actually encouraged to look at those below them, i.e., those less fortunate,
and not to look above them. Research suggests that comparisons can alter the standard to which one makes
a judgment (e.g., Bless & Schwarz, 2010).
In addition to these relatively straightforward ways of attaining happiness, some religious teachings
concerning well-being are actually counterintuitive. For example, one of the Beatitudes from Jesus’
Sermon on the Mount says, “Blessed are those who mourn, for they will be comforted.” As described
previously in this chapter, the word for blessed here is the Greek word macarios which is roughly
equivalent to the Hebrew word ashrey, meaning happy or blessed, but typically in reference to obedience
of God’s commands. Another counterintuitive Beatitude says, “Blessed are the meek, for they will inherit
the earth.” The second half of each of these verses provides some insight into how those who mourn and
those who are meek will be happy. Nevertheless, these teachings do not converge with commonsense views
of how to become happy. Finally, at the end of the Beatitudes, people are told to rejoice and be glad when
others insult and persecute them because of God. They are told that their reward in Heaven will be great.
These teachings actually overlap to some extent with the teachings concerning how one should
handle negative experiences. According to the Hindu principle of moksa, one can find liberation from
sorrow. The goal is to achieve a level of bliss or happiness by understanding one’s soul. This should help
one in the midst of life’s setbacks. That is, one can actually experience happiness in the face of tragedies.
Buddhist wisdom says that the mind should be balanced and that mental training can help one maintain a
level of happiness in the face of life’s difficulties. As discussed previously, Christians can expect to suffer
and those individuals should be considered blessed and happy if the suffering comes because of their faith.
In a similar manner, Islam preaches that God tests people through hardships. This knowledge can actually
help one cope with suffering and could increase one’s well-being in the long term.
Praxis
The second section of the chapter concerns religious practices and behaviors and how they relate to
well-being. The description of these practices and behaviors conceptually overlap with various dimensions
outlined by Smart, such as ritual, ethical, and institutional. We begin with a section on religious rituals.
The goal of this section is to provide a broad overview of some of the main rituals common across the main
world religions. It is beyond the scope of this chapter to cover every ritual, so we will focus on acts of
prayer, meditation, fasting, worship services, pilgrimages, and holiday festivals and celebrations.
Prayer
According to a Pew Research Center poll, 55% of Americans pray on a regular basis (Pew Research
Center, 2014b). Some form of prayer or communication with a higher being is described in many religions,
although the exact form of prayer may vary from religion to religion. In Islam, for example, prayer is a
36
mandated part of their religion as one of the five pillars of Islam. Muslims are required to pray five times a
day; parts of these prayers involve reciting sections of the Quran in Arabic. In addition to these obligatory
prayers, Muslims may pray voluntarily, and additional congregational prayers occur as well. Obligatory or
congressional prayers are also often performed in various Catholic and Anglican denominations. Many
Christian traditions have prayers that are recited from passages in the Bible, but there is also great emphasis
on voluntary prayers. These prayers occur at various times during the day. In fact, Christians are called to
pray without ceasing (Thessalonians 5:17). Prayers are often regarded as conversations with God. Specific
categories of topics such as adoration, confession, thanksgiving, and supplication are often taught as a
guideline for how one should pray. Prayers among Hindus and Buddhists are also important aspects of
their worship. Sometimes prayers occur in private in the face of a deity (e.g., an image or statue) or in
larger congregations.
Given the nuances and different types of prayer, the relationship to well-being could be complex.
Prayers should help one feel connected or closer to God, and this could influence well-being depending on
how one views God (e.g., as a loving father or as a judgmental ruler). The effects of obligatory prayer on
well-being may dissipate with time given the habitual nature. Voluntary prayers may have a stronger
influence on well-being or could be the result of some event which could have a strong influence on wellbeing
(e.g., a negative event occurs which causes one to feel sad and to pray). The content of the prayer
could influence well-being in different ways. Some research suggests that individuals who engage in
prayers of thanksgiving and adoration tend to be happier that those who do not, whereas those who engage
in obligatory prayers, and prayers of confession and supplication tend to report lower levels of well-being
(Whittington & Scher, 2010). Of course, further research is needed to understand the effect of these
processes on well-being. Additional research is required to understand the effect of prayer location (e.g.,
whether one is in isolation or with others) on well-being.
Meditation
Related to prayer, meditation and mindfulness techniques involve some type of quiet reflection, an
emptying of one’s thoughts, and a time in which one is not disturbed or distracted by external stimuli or
environmental factors. In Buddhist traditions, meditation involves a focus on a narrow or specific object,
such as one’s breath. Next, the goal is to be mindful of one’s environment and surroundings while still
remaining calm and focused on the narrow object. In Hindu traditions, the goal of meditation is to become
one with God. Although people commonly associate meditation and mindfulness to Buddhism, meditation
and mindfulness techniques are also practiced in Christian traditions. Christians are often called to meditate
on God’s Word (i.e., the Bible) by considering the commands and reflecting on them.
Research suggests that mindfulness can lower one’s stress and increase well-being (e.g., Brown &
Ryan, 2003). The exact mechanisms explaining how and why mindfulness techniques improve well-being
is an active area of research (e.g., Gu, Strauss, Bond, & Cavanagh, 2015). Future studies can examine
whether these processes exist within religious contexts as well.
Fasting
Another common ritual in many religions is fasting. Similar to meditation, the goal of fasting is to
become less focused on a particular external distraction. In Islam, fasting is one of the five pillars. Muslims
are called to fast from dawn to sunset each day during Ramadan. The goal is to feel more closely connected
to God, and this could increase a feeling of attachment to God. Because all Muslims are called to fast
during the same time, it could also promote a sense of belonging and connection to others which could
increase well-being. Hindus will often fast on particular days of the month or even specific days of the
week. It can also occur during religious festivals and holidays. Buddhists will often fast during spiritual
retreats and it accompanies meditation. In many Christian denominations, fasting involves not only
abstinence from food, but emphasis is placed on devoting oneself to God and Biblical commands. This
emphasis on a connection to God, similar to the other religions during fasting, likely increases one’s well-
being.
Of course, fasting could occur with more negative thoughts and feelings. In Judaism, for example,
fasting often occurs with sorrow. The two most common days of fasting are on Yom Kippur and Tisha
B’Av. Yom Kippur is known as the day of repentance or atonement. This is typically a sorrowful day as
one reflects on and repents for one’s sins. Tisha B’Av is a day meant for remembering tragedies that have
happened to the Jewish people. Thus, the act of fasting on these days likely occurs with lower levels of
well-being. Thus, the act of fasting may lead to increases or decreases in well-being depending on the
specific contexts.
Worship Services
Religious services and community worship are important ritualistic experiences that have important
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implications for well-being. In Christian and Jewish traditions, fellow believers gather together at a church,
cathedral, or synagogue for worship. At worship services, people hear the word of God, often through the
preaching of a pastor, priest, rabbi, or spiritual leader. Songs are often sung and passages of the Old
Testament or Scripture are read aloud. In some denominations, attendance is considered obligatory,
whereas attendance is voluntary in others. Muslims also gather together for worship, but the emphasis of
meeting at a mosque is typically for prayer and a reminder. An imam will deliver a homily or short speech
on Fridays, but the meeting or gathering follows a different format from Christian or Jewish worship
services. Hindus and Buddhists often meet together for temple worship even though emphasis is also
placed on private worship. Buddhist monks will often live together in intentional and/or monastic
communities.
Being together in community can fulfill needs for affiliation and belonging, which can increase
eudaimonic well-being. Community can also provide encouragement, laughter, and joy, which could
increase hedonic well-being. A gathering together for the purpose of worship provides individuals with a
sense of unity and it binds people together (Graham & Haidt, 2010). These gatherings also provide
individuals with a social support system that could increase well-being (Salsman, Brown, Brechting, &
Carlson, 2005).
Pilgrimages
An example of another community activity is a pilgrimage, a form of which is present in most of
the main world religions. In Islam, Muslims are obligated to take a pilgrimage to Mecca at some point in
their life as this is one of the five pillars of Islam. The pilgrimage involves sleeping in various desert plains,
walking around the Kaaba in Mecca, and walking between Mount Safa and Mount Marwah.
In other religions, pilgrimages are not required but are often undertaken by a substantial portion of
followers. In Hindu traditions, for example, various cities in India are visited which are considered to be
holy. Some Christians will take trips to the Middle East to visit important sites described in the Old and
New Testament. An important pilgrimage among Catholics is the Camino de Santiago (aka Way of St.
James), a route that culminates in a visit of the Cathedral of Santiago de Compostela in Spain. The
culminating purpose of this pilgrimage is to visit the remains of Saint James, who is believed to be buried
in Santiago de Compostela.
Pilgrimages, when done with other fellow believers, can have similar positive effects on one’s wellbeing
as worship services. These acts likely bind people closer together, providing them with a sense of
closeness and bonding. These pilgrimages can also instill experiences of awe and wonder, experiences that
often covary with well-being (e.g., Rudd, Vohs, & Aaker, 2012).
Celebrations of Holidays and Festivals
Festivals and holidays can be times of great celebrations and exuberance, times of somber
reflection, or some mix of the two. In Christian traditions, the celebrations of Christmas and Easter are
oriented around the birth and resurrection of Jesus. These days of celebration are joyous occasions
accompanied by food, presents, and friends and family. The Jewish New Year celebration of Rosh
Hashanah is also a festive and joyous occasion. Buddhist festivals are typically joyous occasions as well
that involve food and some sort of ceremony.
More somber holidays include Good Friday and Yom Kippur, days of remembering the death of
Jesus and the atonement of one’s sins, respectively. The two major holidays in Islam, Eid al-Fitr and Eid
al-Adha begin with the word Eid which translates to solemn festival. Eid al-Fitr occurs just as Ramadan
ends and means the “festival of breaking of the fast.” It is obligatory to give money to the poor, pray, and
display signs of happiness. Eid al-Adha is celebrated in remembrance of Abraham who was saved from
having to sacrifice his son Ishmael after being presented with a ram as a substitute. This festival is
sometimes referred to as the festival of the sacrifice.
In Hindu traditions, the word for festival comes from the Sanskrit word “utsava” which means
removal of worldly sorrow. Hindu religious festivals are typically joyous occasions (e.g., Pongal) but they
can also include time for fasting and serious reflections (e.g., Maha Shivaratri). The festival celebrations
can sometimes last for several days and often involve feasting with friends and family. This would
certainly seem to increase hedonic and eudaimonic aspects of well-being.
Clearly, festivals can have mixed effects on well-being. Most celebrations likely increase hedonic
and eudaimonic well-being as they involve a gathering of people with food and merriment. Somber
holidays and festivals likely do not increase hedonic forms of well-being at the moment, but they could
increase a sense of meaning and purpose in life by solidifying one’s belief or by enabling one to remember
a somber past.
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Conclusions
In this chapter, we have outlined various beliefs and practices of the main religions of the world.
These beliefs and practices could have important implications for well-being researchers and could
highlight avenues for future research. Although it has been shown that religious individuals report greater
well-being, the exact mechanisms are less well understood. Specific religious practices could potentially
mediate the relationship between religiosity and well-being. Moreover, certain religious beliefs may
moderate relationships between religiosity and well-being. For example, the belief about how one is
accepted into heaven (e.g., grace vs. works) could moderate the relationship between a specific act (e.g.,
committing a transgression) and well-being. Among those who believe they will earn salvation through
their actions, a transgression could cause one to worry about how that could potentially affect their eternal
destination, whereas those who believe in salvation by grace may not be as influenced by a transgression in
terms of the well-being. Furthermore, a greater understanding of the process from religiosity to well-being
could be achieved by building models that integrate beliefs and practices as moderators and mediators,
respectively. For example, social support found in community worship may mediate the relationship
between religiosity and well-being more strongly among Christians than other religious groups. The key
mediator among Hindus, on the other hand, may be related to a sense of peace or tranquility that occurs
through individual prayer. That is, a specific religious belief may moderate the mediation or indirect effect
from religiosity to well-being.
To examine such models and test these kinds of theories, it is critical to move past single item
measures of religiosity. One possible solution would be to ask participants to report their specific religious
belief. To make such statistical comparisons, it would require large and diverse samples. Of course, there is
often great heterogeneity of specific religious beliefs and practices within a particular religion,
denomination, or sect. For example, two individuals might report being Buddhist, but yet their beliefs and
practices may vary substantially. It would be important to ask participants to describe their actual beliefs
and to record their religious practices in real time.
Future research could utilize text analysis techniques to capture individual differences in religious
beliefs. Another avenue to address religious practices would be to utilize ecological momentary assessment
techniques by having participants record their religious experiences and well-being in the moment.
One limitation of this review is that we have not addressed all religious beliefs and practices.
Within each major religious group there are many specific denominations and sects, and these differences
should be considered when researchers examine the link from religiosity to well-being. There are also
individuals who identify as atheist or agnostic who nevertheless have spiritual beliefs and/or engage in
certain religious practices, such as meditation (e.g., Harris, 2014). Future research should try to disentangle
these individual differences. Our goal was to provide a useful overview of what the main world religions
say about well-being through their beliefs and practices. We hope that well-being researchers can use this
chapter as a guiding framework to address research questions concerning religion and well-being.
Acknowledgements
We would like to thank Ed Diener, Jamaal Diwan, Randy Newman, Shige Oishi, Varun Soni, and Louis
Tay for their helpful comments on an earlier draft of this chapter.
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2018 Ed Diener. Copyright Creative Commons: Attribution, noncommercial, no
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Well-Being Concepts and Components
By William Tov, Singapore Management University
Citation
Tov, W. (2018). Well-being concepts and components. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
Well-being is a broad, multifaceted construct. This chapter reviews different ways of defining and
measuring well-being and the implications this has for understanding the correlates and causes of wellbeing.
Hedonic well-being (HWB), eudaimonic well-being (EWB), and other conceptions of well-being are
discussed. Specific components and aspects of HWB are elaborated on. These include the distinction
between affective and cognitive well-being. Major aspects of affective well-being include valence,
frequency versus intensity, arousal, and interpersonal engagement. Major aspects of cognitive well-being
include life satisfaction, life evaluation, and domain satisfaction. Processes underlying the structure of
cognitive well-being are discussed including top-down versus bottom-up models, and the tendency to use
heuristics versus stable sources of information to evaluate one’s life. Trait versus state conceptions of wellbeing
are introduced. Different well-being assessment methods (online, recall, global) can be located on a
state-trait continuum. The distinction between state and trait measures of well-being has implications for
understanding the structure of affect, the relation between well-being and health, and cultural variation in
well-being. Future research is needed to clarify the distinct correlates of affective versus cognitive wellbeing,
as well as how positive and negative emotions are operationalized. In addition, a better
understanding of the components of EWB and how they are related to HWB and affective dimensions
beyond valence will shed light on the validity of the EWB construct. Finally, greater sensitivity to the statetrait
distinction will deepen our knowledge of the processes that shape both HWB and EWB.
Keywords: hedonic well-being, cognitive well-being, affective well-being, state versus trait, emotion,
satisfaction
The term well-being encompasses all the ways in which people experience and evaluate their lives
positively. What exactly it means to experience life positively can be understood in myriad ways. Some
equate well-being with happiness, but this can sometimes conjure up images of an immensely joyful,
cheerful person that many do not identify with. As a result, some prefer to view well-being as a prolonged
state of contentment. For others still, well-being is simply about wellness--as in having good physical and
mental health. None of these views is incorrect; but each perspective is incomplete in itself. A great
challenge for the science of well-being has been to define and measure this broad, encompassing construct.
An important development in this field over the past few decades is the recognition and growing acceptance
that well-being consists of many aspects--that it cannot be fully represented by any one measure. A person
who is depressed cannot be said to be well; however, to equate well-being with an absence of depression
misses much of what people strive for when they seek to enhance and preserve their well-being. In other
words, well-being includes the lack of suffering, but it is more than this (Diener, 1984; Seligman &
Csikszentmihalyi, 2000).
This chapter reviews various conceptions of well-being and how different components of well-being
have been measured and studied in the psychological literature. The variety of ways in which well-being
has been defined could be said to dilute the construct or render it meaningless. However, the causes,
consequences, and correlates of well-being may depend on how it is defined and measured. A single
intervention might improve some aspects of well-being but not others. Such an understanding is critical for
the design of policies aimed at improving well-being.
Conceptions of Well-Being
What does it mean to “be well”? Numerous scholars have answered this question in different ways,
resulting in a variety of well-being concepts. There are two major approaches to conceptualizing well-being
(Ryan & Deci, 2001). The first approach emphasizes a person’s evaluation of their own life--both
emotionally and cognitively. It has been referred to as hedonic well-being (HWB) and consists of (i)
frequent pleasant feelings, (ii) infrequent unpleasant feelings, and (iii) an overall judgment that life is
satisfying. This tripartite model is also referred to as subjective well-being (Diener, 1984) because it
prioritizes a person’s own assessment of how well their life is going and whether they are getting the
things they want in life--without specific concern for what these “things” actually are.
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The second approach includes several concepts that together have been referred to as eudaimonic
well-being (EWB). This approach takes as its starting point that there are certain needs or qualities that are
essential for one’s psychological growth and development; the fulfillment of these needs enables a person
to reach their full potential (Ryan & Deci, 2001). The concept of psychological well-being (Ryff, 1989) is
an example of the EWB tradition. Drawing on the theories of Erikson, Jung, Maslow, and Rogers (among
others), Ryff posited six key features of people who are functioning well in life. Such people should have
the maturity to be guided by internal standards (autonomy), be capable of trusting and loving others
(positive relations), be able to manage external stressors and leverage on opportunities (environmental
mastery), have a positive attitude toward themselves (self-acceptance), have important aims and goals
(purpose in life), and accept new challenges in life as furthering their development (personal growth).
Other EWB approaches emphasize living up to one’s personal potential--in line with Aristotle’s view of
eudaimonia as living in accord with one’s true nature (or daimon). From this perspective, EWB is rooted in
the pursuit of goals and activities that are consistent with one’s values and identity (McGregor & Little,
1998; Waterman, 1993).
Measures of HWB and EWB are highly correlated suggesting that positive feelings and positive
functioning tend to go hand in hand. Nevertheless, a number of studies suggest that the two sets of
measures are distinguishable from one another (Compton, Smith, Cornish, & Qualls, 1996; Keyes,
Shmotkin, & Ryff, 2002; Linley, Maltby, Wood, Osborne, & Hurling, 2009). Specifically, HWB measures
(e.g., pleasant feelings, unpleasant feelings, life satisfaction) often correlate with each other more strongly
than they do with EWB measures (e.g., meaning, growth, autonomy), and vice versa. Some studies have
found distinct correlates of HWB and EWB measures. For example, HWB is associated with the pursuit of
projects that are fun and likely to be successful; EWB is associated with projects that are closely aligned
with one’s values and identity (McGregor & Little, 1998). Challenging activities are associated with a
greater sense of EWB (personal expressiveness; Waterman, 1993) but can sometimes be associated with
less HWB (positive emotion; Moneta & Csikszentmihalyi, 1996). Enacting moral behavior toward others is
associated with EWB; receiving the same from others is associated with HWB (Hofmann, Wisneski,
Brandt, & Skitka, 2014). The amount of time spent imagining the future was associated with greater EWB
(meaning) but less HWB (happiness); in contrast, the amount of time spent thinking about the present was
associated with greater HWB but was unrelated to EWB (Baumeister, Vohs, Aaker, & Garbinsky, 2013).
Additional well-being concepts have been proposed that are not consistently included in either
hedonic or eudaimonic conceptions of well-being. Csikszentmihalyi (1990) described the state of flow, in
which a person is optimally engaged with what they are doing. Flow states require a delicate balance
between the challenges of a task and the person’s skill at meeting these challenges. Ideally an activity
should not be too easy or too difficult but challenge the person at a level slightly above their current skills.
This creates an opportunity for the expansion of one’s skill level if the challenge is met. Research suggests
that flow states involve higher levels of engagement and concentration than nonflow states, but are not
always accompanied by higher levels of pleasant feelings (Csikszentmihalyi & LeFevre, 1989; Moneta &
Csikszentmihalyi, 1996). Thus, flow states may be more closely related to EWB (growth and mastery) than
HWB.
Some accounts of well-being (Boehm, Peterson, Kivimaki, & Kubzansky, 2011; Diener, Wirtz et
al., 2010; Su, Tay, & Diener, 2014) include optimism--the general expectation that one wil experience more
positive than negative outcomes in life (Carver & Scheier, 2003). The disposition to be optimistic is
associated with greater satisfaction and happiness and lower levels of depression and stress (Scheier &
Carver, 1992), lower risk of health problems and faster recovery from illness (Boehm & Kubzansky, 2012;
Scheier & Carver, 1992; Seligman, 2013). Several of these studies show that optimism prospectively
predicts better health outcomes even after controlling for a range of demographic and personality
variables. These findings led Taylor and Brown (1988) to suggest that highly positive beliefs about one’s
future, oneself, and one’s ability to control outcomes, might be important hallmarks of mental health. In
particular, such “positive illusions” may be especially functional when facing adversity. Optimistic beliefs
tend to correlate strongly with measures of EWB (Diener, Wirtz et al., 2010; Su et al., 2014) and HWB
(Lucas, Diener, & Suh, 1996), but are not completely synonymous with either conception of well-being.
Other conceptualizations have been proposed that include mixtures of HWB and EWB. Keyes
(2002) offered the term flourishing to describe a condition characterized by high levels of both HWB and
EWB. Seligman (2013) presented a similar model of flourishing called PERMA: positive emotion,
engagement (flow), (positive) relationships, meaning, and achievement. According to Seligman, these five
elements of well-being are pursued for their own sake and not necessarily to increase other well-being
elements. Diener and colleagues (Diener, Wirtz et al., 2010; Su et al., 2014) also offered a conception of
flourishing, viewing well-being as social-psychological prosperity or capital. This might be thought of as a
set of beliefs or resources that not only enhance well-being but also strengthen mental and physical
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resilience in times of adversity. Such resources include those in the PERMA model, as well as optimism,
given its power to predict health behavior and recovery.
Kashdan, Biswas-Diener, and King (2008) raised a number of issues with the concept of EWB.
They noted that whereas HWB is consistently defined as the experience of pleasant affect, unpleasant
affect, and life satisfaction, EWB consists of a range of constructs that vary across researchers. As a result,
there is no unified operational definition of EWB, although certain components (e.g., growth, meaning,
authenticity, and mastery) appear in most conceptions of EWB (Huta & Waterman, 2014). The challenge
hinges on what theorists consider to be an optimally functioning person. Some components emphasize the
integrity of the person (e.g., authenticity, autonomy), others emphasize social functioning (positive
relationships), still others emphasize engagement with life and its challenges (growth, meaning, mastery,
striving for excellence). More work is needed to understand how and why specific components of EWB
are interrelated--with each other and with external outcomes.
Another theoretical issue concerns the very notion of EWB concepts as indicators of well-being
(Kashdan et al., 2008; Ryan & Deci, 2001). For example, Ryff (1989) views autonomy, mastery, and
positive relationships as defining elements of psychological well-being. A monk who lives alone in the
mountains and is happy and satisfied with his life would be well in terms of HWB, but might not be
functioning optimally in terms of EWB. In contrast, Ryan and Deci’s (2000) self-determination theory
posits autonomy, competence, and relatedness as universal needs that, if unfulfilled, may decrease HWB.
Thus, the elements of EWB are thought of as antecedents to well-being rather than as defining well-being.
A similar issue might apply to concepts such as flow and optimism. Are these defining elements of wellbeing
or should they be considered antecedents of well-being? An answer to this issue is not easily resolved
empirically, particularly when no single criterion of well-being exists. It also quite plausible that
bidirectional influences exist among components of HWB, EWB, and other related concepts. Ultimately,
the resolution of what constitutes well-being may depend on the theoretical perspective one chooses to
adopt. Readers interested in a deeper discussion of these issues, should refer to the excellent volume on
EWB edited by Vittersø (2016).
For remainder of this chapter, we elaborate on the components of HWB. The reason for this is that
there is a larger body of research in this area, as well as a fairly consistent operational definition of its
components (pleasant affect, unpleasant affect, and life satisfaction).
Affective Versus Cognitive Well-Being
HWB (subjective well-being; Diener, 1984) consists of an affective component and a cognitive
component. Affective well-being (AWB) refers to the experience of pleasant and unpleasant feelings. A
person with high AWB generally experiences a preponderance of pleasant over unpleasant feelings. Thus
AWB is typically assessed by asking respondents how often they have experienced specific emotions (e.g.,
happiness, joy, contentment, sadness, anger, worry, etc.). Cognitive well-being (CWB) is based on an
evaluation of how well one’s life is going relative to an ideal state of affairs. A person with high CWB
should judge that their goals, desires, and standards are largely met by the current conditions of their life.
CWB is most commonly assessed by measures of life satisfaction (Diener, Emmons, Larsen, & Griffin,
1985), but also includes satisfaction with specific areas of life such as health, work, and family (i.e., domain
satisfactions; Diener, Suh, Lucas, & Smith, 1999). AWB and CWB are strongly correlated. To a certain
extent, these interrelationships are expected. The fulfillment of valued goals and standards is often
accompanied by pleasant affect whereas the lack of fulfillment may result in unpleasant affect. Thus,
emotional experiences provide some information about how well one’s life is going and thus may factor
into one’s judgment of life satisfaction (Schwarz & Clore, 1983; but see Yap et al., in press). Nevertheless,
correlations between AWB and CWB are not so strong that they could be considered redundant. For
example, Lucas et al. (1996) observed concurrent correlations as low as -.30 between life satisfaction and
negative affect, and as high as .65 between life satisfaction and positive affect, on various self-report
measures of well-being.
Different processes are involved in the experience of AWB and CWB. Emotions are often
experienced in reaction to specific events. In contrast, satisfaction judgments may involve a range of
factors. This can include the specific standards one uses to judge whether life is going well, and how
satisfied one is with specific areas of life (e.g. work, relationships, health; Kim-Prieto, Diener, Tamir,
Scollon, & Diener, 2005). Compared with AWB, CWB tends to be based more on stable sources of
information such as global assessments about one’s life circumstances and domains of life, rather than
specific events or activities (Luhmann, Hawkley, Eid, & Cacioppo, 2012; see also Schimmack & Oishi,
2005). Thus, if one’s social relationships are generally supportive and enjoyable, a recent argument with a
friend is unlikely to reduce CWB as much as AWB. The implication of this finding is that CWB should be
more stable across time, whereas AWB should be more variable as it fluctuates with recent events.
45
Analyses by Eid and Diener (2004) support this hypothesis.
If CWB tends to be based on information that is more stable (relative to AWB), then it should be
more strongly associated with factors that stabilize or destabilize the general conditions of one’s life.
Indeed, income and unemployment correlate more strongly with CWB than with AWB (Diener, Ng,
Harter, & Arora, 2010; Howell & Howell, 2008; Luhmann, Hofmann, Eid, & Lucas, 2012; Schimmack,
Schupp, & Wagner, 2008; Tay & Diener, 2011). These factors are often related to the conditions of one’s
society more generally, and may explain why national differences tend to be larger in terms of CWB (Tay,
Chan, & Diener, 2014). Major life events such as bereavement and childbirth also seem to have greater
impact on CWB than AWB (Luhmann, Hofmann et al., 2012). Interestingly, whereas CWB decreased in
the months following childbirth, AWB increased. Perhaps the birth of a child creates opportunities for
pleasant social interactions, but the time spent caring for the baby and resulting lack of sleep negatively
affect other areas of life (and hence CWB). Positive social relationships correlate more strongly with AWB
than CWB. For example, social support is a strong predictor of positive emotions, and feeling respected is
one of the strongest predictors of both positive and negative emotions (Tay & Diener, 2011).
One caveat to the notion that CWB is based more on stable information relative to AWB is that
personality traits such as extraversion and neuroticism correlate more strongly with AWB (Schimmack et
al., 2008). Although AWB may respond more to recent events, there are stable individual differences in
mean levels of affect (see Trait versus State Well-Being). Covariation with personality traits may suggest
that AWB is partly influenced by heritable predispositions to experience certain kinds of emotion.
Extraverts may attend to positive stimuli more than introverts (Derryberry & Reed, 1994), and this
tendency may increase the likelihood that they experience pleasant emotions. Extraverts may also actively
seek pleasant social situations (Emmons & Diener, 1986). However, personality traits do correlate with
CWB. A meta-analysis by DeNeve and Cooper (1998) examined a range of traits and did not find
consistent differences in their association with CWB (life satisfaction) versus AWB. A key difference may
be that Schimmack et al. controlled for the effect of general evaluative biases (i.e, a tendency to rate oneself
positively on a range of traits) when comparing the effect of personality traits on AWB and CWB.
Additional studies suggest that although CWB is associated with extraversion and neuroticism, this
relationship is mediated by AWB (Schimmack, Diener, & Oishi, 2002; Schimmack, Radhakrishnan, Oishi,
Dzokoto, & Ahadi, 2002). That is, these traits are associated with CWB largely because they influence
levels of pleasant and unpleasant affect, which in turn influence how well people evaluate their lives.
Thus far, AWB and CWB have been discussed in a somewhat monolithic fashion to highlight the
differences between them. That said, each construct in itself can be understood in terms of more specific
components and processes that are important for understanding the causes and consequences of well-being.
Major Aspects of AWB
Valence. A basic feature of affective experience is the degree to which it is pleasant or unpleasant.
This quality is fundamental to the notion of AWB as the preponderance of pleasant over unpleasant
feelings. The distinguishability of pleasant (positive) affect versus unpleasant (negative) affect has been
debated and studied from many perspectives. The degree to which they are correlated with each other
depends on how they are measured--a point that will be revisited in this chapter. For now, it is generally
understood that positive (PA) and negative affect (NA) are separable though not completely independent.
In this section, the emphasis is on their distinct correlates and causes. The validity of the tripartite model of
subjective well-being (PA, NA, and life satisfaction) depends partly on the identification of factors that are
uniquely related to PA and NA (Busseri & Sadava, 2011). For example, the fulfillment of basic needs is a
strong predictor of NA but not of PA (Tay & Diener, 2011). Struggling to find food and shelter may induce
unpleasant emotions; however, having food and shelter in and of itself may not produce many pleasant
emotions.
A number of studies suggest that PA and NA are associated with distinct personality traits.
Extraversion is more strongly associated with PA, whereas neuroticism is more strongly associated with
NA (DeNeve & Cooper, 1998). These differences could be due to overlapping item content in that some
extraversion scales include subscales directly measuring positive emotion (e.g., the NEO-PI-R; Costa &
McCrae, 1992), and neuroticism by definition involves the tendency to experience negative emotion.
However, specific behaviors associated with extraversion (e.g., social activities) are also associated with
higher levels of PA but are not consistently related to NA (Clark & Watson, 1988). Moreover, acting
extraverted is associated with increases in momentary PA for both introverts and extraverts (Fleeson,
Malanos, & Achille, 2002). In contrast, neuroticism and dispositional negativity are associated with greater
sensitivity in regions of the brain that are associated with threat perception (e.g., the amygdala; Everaerd,
Klumpers, van Wingen, Tendolkar, & Fernandez, 2015; Shackman et al., 2016). This suggests that the
correlation between self-reported neuroticism and NA is not simply due to a tendency to endorse negative
46
items.
Both PA and NA predict health outcomes. Many studies have established that chronic levels of
negative emotion are associated with increased risk of health problems such as coronary heart disease
(Frasure-Smith, Lesperance, & Talajic, 1995; Russek, King, Russek, & Russek, 1990; Smith, 1992).
Negative emotions such as anger and anxiety activate the body’s stress response, which can impair immune
system functioning if such activation is chronic (O’Leary, 1990). Independently of NA, several studies
have found that PA predicts mortality and disease in the direction of lower risk (Diener & Chan, 2011;
Pressman & Cohen, 2005). In a classic study, Cohen, Doyle, Turner, Alper, and Skoner (2003) exposed
participants to the cold virus. Those who tended to experience PA were less likely to develop a cold than
those less inclined to experience PA; the tendency to experience NA was not associated with cold
susceptibility. In a world sample, Pressman, Gallagher, and Lopez (2013) found that both PA and NA were
uniquely associated with self-reported health. The size of these relationships were similar on average,
although the positive correlation between PA and health was larger in less wealthy countries. The processes
by which PA reduces the risk of illness require further study. Effects of PA on health may be related to
stronger immune system functioning, healthier behavior, or stronger social support (Pressman & Cohen,
2005). There is also some evidence that positive emotions quicken the recovery of cardiovascular activation
triggered by negative emotions (Fredrickson & Levenson, 1998), potentially offsetting the stress response.
Frequency versus intensity. The frequency of an emotion (how often it occurs) can be
distinguished from its intensity (how strongly it is felt). According to Schimmack and Diener (1997), mean
levels of affect reflect a combination of frequency and intensity. Suppose that each day for one week,
participants rated how happy they feel on a scale from 0 (not at all) to 10 ( extremely). Their mean level of
happiness across the week could be computed by averaging the seven ratings they made daily. Joe only
experienced happiness on two days, but both days were fairly intense (7). In contrast, Ted experienced
happiness every day of the week, but at a lower intensity (2). Both Joe (7 x 2 / 7 = 2) and Ted (2 x 7 / 7 =
2) would end up with the same mean level of happiness. However, both men clearly experience happiness
differently. Joe is happy less often, but when happy, he feels it intensely. Ted is happy often but at a mild
intensity. These differences can only be captured if we separate intensity from frequency. Specifically, the
average intensity is best understood as the magnitude or strength of an emotion when it is felt (Schimmack
& Diener, 1997). By this definition, the average intensity of Joe’s happiness is 7, whereas Ted’s is 2.
Frequency might be measured as the number of times happiness was experienced at all (i.e., a non-zero
rating was given). In that case, Joe’s frequency is 2, and Ted’s is 7. Thus, by one measure (intensity), Joe is
happier; but by another measure (frequency), Ted is happier. Are both statements correct? One way to
answer this question is to ask Joe and Ted to evaluate their lives more generally: how happy are they
overall? Diener, Sandvik, and Pavot (1991) found that measures of long-term, global well-being were better
predicted by the frequency of happiness rather than its intensity. (Diener et al. actually measured frequency
in terms of the proportion of time participants felt more positively than negatively).
Intense positive emotions may be less predictive of overall well-being because such experiences
tend to be uncommon (Diener et al., 1991). Their rarity implies that the occurrence of such intense
emotions may not adequately represent a person’s normal life circumstances. Furthermore, it appears that
people who experience intense PA are also likely to experience intense NA (Schimmack & Diener, 1997;
Diener, Larsen, Levine, & Emmons, 1985), which would seem to counteract the effects intense PA. Several
processes may contribute to the tendency to experience both intense PA and NA (Diener, Colvin, Pavot, &
Allman, 1991). One such process is highly valuing and investing in certain goals and events (Diener et al.,
1991; Pomerantz, Saxon, & Oishi, 2000; Schimmack & Diener, 1997). The goals that are extremely valued
will produce more intense PA if they are attained (e.g., winning a championship) but more intense NA if
are not.
The distinction between frequency and intensity may affect the interrelation between PA and NA.
Diener, Larsen et al. (1985) showed that over an extended period of time, mean levels of PA and NA are
only weakly correlated--suggesting that they are independent. However, mean levels of affect confound
frequency and intensity. When intensity is partialed out, PA and NA are negatively correlated. This is
because the remaining variation in mean level affect reflects the frequency of emotional experiences, which
tend to be inversely related. This finding is qualified by the definition of frequency that is used. When
frequency is defined as a proportion of time spent feeling positively versus negatively, a negative relation is
observed because time is inherently limited. More time spent feeling sad means less time to spend feeling
happy. However, if frequency is defined in more absolute terms--a simple count of how many times one
felt PA or NA--then frequencies are positively correlated (Schimmack & Diener, 1997; Schimmack, Oishi,
Diener, & Suh, 2000). This is consistent with the observation that people who experience many positive
events also tend to experience negative events (Magnus, Diener, Fujita, & Pavot, 1993).
Other dimensions of affect. In addition to their valence, frequency, and intensity, emotions may
47
also be characterized by their level of arousal (Barrett & Russell, 1998; Larsen & Diener, 1992). Pleasant
emotions may be low (e.g., calm) or high (e.g., enthusiasm) on arousal. Similarly, unpleasant emotions may
be low (e.g., boredom) or high (e.g., anxiety) on arousal. Arousal represents a dimension of affective
experience that is empirically distinguishable from intensity (Kuppens, Tuerlinckx, Russell, & Barrett,
2013; Schimmack & Diener, 1997). A person who is extremely calm may not be any more aroused than
one who is only somewhat calm. Although AWB primarily emphasizes the valence of affective experience,
the relation between emotions and other variables may also depend on arousal. In their review of the
literature, Pressman and Cohen (2005) observed that mild levels of PA tend to be associated with better
immune functioning; in contrast, highly arousing PA can be detrimental in a manner that is similar to
highly arousing NA. People with asthma may have more difficulty breathing when they experience
extreme NA or PA (Ritz & Steptoe, 2000), although it is unclear from this study whether arousal or
intensity is the key factor given that a mixture of high arousal and low arousal affects were combined in the
NA and PA scores. Given that depression and anxiety are often correlated, some researchers have
suggested that a general negative disposition may underlie the detrimental effects of high arousal (anger
and anxiety) and low arousal (depression) NA on health (Suls & Bunde, 2005).
The cultural value of certain emotions may depend on their level of arousal and not just their
valence. Although people generally want to feel more pleasant than unpleasant emotions, the specific types
of emotions they want to feel varies across culture. For instance, European Americans tend to value higharousal
PA (e.g., excitement) more than Hong Kong Chinese; the latter value low-arousal PA (e.g.,
calmness) more than the former (Tsai, Knutson, & Fung, 2006). Because East Asian cultures emphasize
attention and accommodation to the social environment, low-arousal PA may be especially functional in
this cultural context; in contrast, U.S. cultural norms tend to emphasize the agency of the individual and
high-arousal PA may facilitate the assertion of such agency. Tsai et al. found that European Americans
tended to be more depressed when they did not experience high-arousal PA as often as they desired; in
contrast, Hong Kong Chinese were more depressed when they did not experience low-arousal PA as often
as they desired.
Another dimension that may be culturally variable is the degree to which emotions are
interpersonally engaging (e.g., feeling close to someone) or disengaging (e.g., feeling proud or superior to
others). The frequency of disengaging emotions was a stronger predictor of general “good feelings” among
U.S. participants; in contrast, the frequency of engaging emotions predicted good feelings among Japanese
participants (Kitayama, Markus, & Kurokawa, 2000; Kitayama, Mesquita, & Karasawa, 2006). The
findings of Tsai et al. and Kitayama et al. are consistent with the general tendency for East Asians to value
collectivism and Westerners to value individualism (for a review, see Tov & Nai, in press).
Major Aspects of CWB
CWB judgments involve an evaluative assessment of one’s life as a whole (global measures) as
well as specific aspects of life (domain specific measures). Some researchers describe CWB as an attitude
(or evaluative belief) about one’s life (Schimmack, 2008). Most CWB concepts assume that a comparison
is made between one’s current state and a desirable state of affairs (Campbell, 1976; Diener et al., 1985).
Positive CWB (e.g., satisfaction) arises when the current state or circumstances meet or exceed what is
desired; otherwise, negative CWB (e.g., dissatisfaction) may arise. Measures of global CWB include life
satisfaction (Diener, Emmons et al., 1985) and Cantril’s (1965) self-anchoring striving scale, which is also
referred to as life evaluation (Kahneman & Deaton, 2010; Tay & Diener, 2011). Life satisfaction (LS) can
be assessed directly by asking respondents how satisfied they are with life, as well as additional questions
about whether they are getting the important things they want in life. The life evaluation measure asks
people to think about the best possible and worst possible life they could live, and to locate their current life
somewhere in between these two anchors. The two measures correlate strongly with each other (r = .57 and
.82 at the individual and nation levels, respectively; Diener, Kahneman, Tov, & Arora, 2010). People may
also have evaluative beliefs about specific areas of life (e.g., work, family, health, and leisure). These more
specific domain satisfaction (DS) judgments may be based on more specific standards (e.g., whether pay is
commensurate with job skills and hours). A key point is that the individual decides for himself or herself
the standards by which they judge their life and its domains.
Top-down versus bottom-up models. How does a person evaluate his or her life as a whole? The
target of judgment is extremely broad. One hypothesis is that people evaluate specific domains (DS) first.
Satisfaction across domains is then aggregated to arrive at satisfaction with life as a whole (LS; Campbell,
Converse, & Rodgers, 1976). This bottom-up model assumes that LS is derived from satisfaction with
important areas of life. Thus, conditions at work, the quality of relationships, health, and other relevant
domains each contribute to LS. One problem with this model is that LS judgments tend to be higher than
what would be predicted from a set of DS judgments (Diener, Napa Scollon, Oishi, Dzokoto, & Suh, 2000).
Moreover, this positivity bias is systematically related to cultural ideals regarding LS. That is, people who
48
live in cultures that strive for higher levels of LS tend to exhibit larger biases (i.e., larger LS given their DS
scores). This finding supports the plausibility of top-down models, in which the direction of causality runs
from LS to specific DS judgments. In these models, one is satisfied with life not so much because of
satisfaction with work and relationships; instead, satisfaction with these domains is the product of a general
tendency to be satisfied with life as a whole. A more extreme top-down model views personality traits such
as extraversion and neuroticism as causing both LS and DS. This model implies that correlations between
LS and DS are fully accounted for by personality traits. Heller, Watson, and Ilies (2004) found no support
for such a model. Although personality traits do correlate with LS and DS, the latter two remain strongly
correlated with each other even after accounting for personality. Instead, support was found for both topdown
and bottom-up processes. Personality traits can be viewed as influencing LS, which in turn influences
specific DS judgments (top-down process). Alternatively, traits can be viewed as causing both LS and DS
(top-down), with additional effects of DS on LS (bottom-up). It is likely that both processes operate
together (Schimmack, 2008). One way the relation between LS and DS could simultaneously reflect topdown
and bottom-up processes is in the weight that individuals place on specific domains. For example,
happy people place more weight on the domain they are most satisfied with when judging LS; in contrast,
unhappy people place more weight on the domain they are least satisfied with (Diener, Lucas, Oishi, &
Suh, 2002). Thus, the top-down process is reflected in how a person weights each domain, and the bottomup
process is reflected in the effect of that domain on LS.
Effects of heuristics versus stable sources of information. Schwarz and Strack (1999) noted that
the task of evaluating one’s life as a whole is actually quite difficult. There are a potentially large number
of important life domains so that a truly comprehensive assessment of one’s life should take hours. Yet,
people seem to answer LS questions fairly quickly. To account for this phenomenon, Schwarz and Strack
proposed a judgment model of well-being. They suggested that CWB judgments are largely constructed onthe-spot
from whatever information is currently on the person’s mind and deemed relevant. When the target
is broad (e.g., life as a whole), many kinds of information are deemed relevant. This includes current mood
as well as social comparison. The narrower the target is (e.g., as in DS judgments), the more selective the
use of information. The number of dates a person had in the past month could be relevant for judging LS
but not satisfaction with health. The judgment model implies that LS judgments are highly unstable--
susceptible as they are to momentary influences. However, Schimmack and Oishi (2005) showed that the
effects of momentary factors such as mood and priming are generally small (see also Yap et al., in press).
Instead, LS judgments are largely based on chronically accessible information--specifically, on how well
one is generally doing in important areas of life.
State versus Trait Conceptions of Well-Being
The scientific study of well-being (and happiness in particular) was once questioned on the grounds
that it referred to phenomena that were momentary and fleeting. The judgment model of well-being
(Schwarz & Strack, 1999), for example, assumes that people do not actually have enduring representations
of how happy and satisfied they are with life. However, Headey and Wearing (1989) provided evidence
that PA, NA, and LS were fairly stable across a six-year period (r’s were between .35 to .52; see also Lucas
& Donnellan, 2012; Schimmack & Oishi, 2005). These correlations suggest that HWB components contain
some stability, but not so much stability that they remain unchanged in response to life events (Lucas, 2007;
Luhmann, Hofmann et al., 2012). It is now recognized that well-being consists of both state-like variation
and trait-like stability (Eid & Diener, 2004). Trait levels of well-being refer to how a person feels or how
satisfied they are in general or on average (across time and situations). State levels of well-being refer to
feelings and satisfaction at a particular moment in time or within a restricted period of time (e.g., the past
week). Trait measures of well-being tend to be influenced by personality traits, cultural values, memory
biases, and general beliefs about the self (Robinson & Clore, 2002b). State measures of well-being may
reflect unstable factors such as the day of the week, temperature, or the nuances of a recent event or
activity. Thus, state and trait measures of well-being involve different processes; they are influenced by
different factors and are associated with distinct outcomes.
Measures of well-being can be placed on a continuum ranging from state-like to trait-like. It is
helpful to distinguish between online, retrospective/recall, and global measures of well-being (Kim-Prieto
et al., 2005; Scollon, Diener, Oishi, & Biswas-Diener, 2004). Online measures ask respondents to report
how they are feeling “right now”. Because respondents are often randomly alerted to complete a survey
(e.g., through smartphone), online measures may instruct participants to report how they were feeling just
before they were alerted to avoid effects of the alarm itself on their mood. Recall or retrospective measures
ask respondents to report how they felt over a specified period of time. The time frame can range from the
past hour to the past year. Finally, global measures typically ask respondents to report their well-being in
general. Whereas online measures capture well-being states and global measures capture well-being traits,
recall measures reflect a mixture of states and traits. Robinson and Clore (2002a) showed that people spend
49
increasingly more time assessing their emotion as the target period increases from the past hour to the past
few weeks. This is consistent with the idea that people are recalling the specific events that they
experienced: the longer the target period, the more events there are to recall. However, when the target
period concerned the past few months or longer, no further increase in time was observed. People spent
nearly as much time recalling their emotion over the past few years as they did over the past few weeks.
This suggests that at some point, people stop recalling specific events and rely on more general beliefs
about themselves. Such beliefs are more likely to reflect the influence of personality traits and cultural
values. Distinctions between online, recall, and global measures produce important insights about affective
structure, health, and cultural variation in well-being.
Structure of Well-Being
Diener and Emmons (1984) showed that state PA and NA tend to be inversely correlated at a single
moment in time. People rarely report feeling pleasant and unpleasant at the same time. However, when
reporting how they felt over the past year, levels of PA and NA were weakly correlated. Additional work by
Diener and Iran-Nejad (1986) clarified that state PA and NA tend not to co-occur at high levels of
intensity; however at lower levels of intensity, people can experience PA and NA in different combinations
(see also Tay & Kuykendall, 2017). The co-occurrence of low intensity state PA and NA, combined with
the inverse relation observed at high intensities may contribute to their reduced correlation at broader time
frames. Thus, PA and NA may diverge more from each other at trait levels than at state levels. Watson,
Clark, and Tellegen (1988) did not observe consistent effects of time frame on the correlation between PA
and NA--which were largely independent in their studies. However, their measures consisted of
predominantly high-arousal PA and NA terms (e.g., excited, distressed). Thus the typically inverse relation
between valenced states may have been offset by positive covariation due to high arousal levels (Barrett &
Russell, 1998).
Far less work has examined momentary measures of CWB and how these relate to AWB. Tov and
Lee (2016) examined daily satisfaction (a state-like measure of CWB) and its covariation with daily affect.
Daily satisfaction was more strongly correlated with daily PA than daily NA. The effect replicated when
participants reported their well-being over the past few days. A similar pattern has also been observed with
a time frame of the past two months (Luhmann, Hawkley et al., 2012) as well as among global, trait
measures of HWB (Lucas et al., 1996; Robinson, 2000). Thus, the relation between CWB and PA appears
to be similar at both state and trait levels--although more research is needed.
Relations Between AWB and Health
Most research findings that suggest a protective effect of PA and detrimental effects of NA on
health are based on trait measures of affect (Boehm & Kubzansky, 2012; Diener & Chan, 2011; Suls &
Bunde, 2005; Pressman & Cohen, 2005). These measures tend to reflect the frequency rather than intensity
of emotional experience (Schimmack & Diener, 1997). Thus, it is chronically experiencing these emotions
that appears to affect health outcomes. Such effects could reflect other personality traits or individual
differences that predispose people toward healthy or unhealthy behaviors. For example, conscientiousness
is associated with a variety of health protective behaviors (Bogg & Roberts, 2004) and is also correlated
with trait measures of well-being (DeNeve & Cooper, 1998). Interestingly, however, these effects often
hold when controlling for demographic factors such as age and income.
The relation between emotion and health is more complex when considering state PA and NA. As
noted earlier, state PA--particularly high arousal PA--can sometimes affect cardiovascular and pulmonary
functioning in a way that is detrimental for those already predisposed to suffer from asthma or heart attacks
(Pressman & Cohen, 2005). In contrast, although trait NA is associated with negative health outcomes,
there may be circumstances in which state NA is beneficial. Advertising campaigns that use fear to
promote healthy behavior (e.g., anti-smoking, vaccination) appear be more effective at inducing changes in
attitudes and behavior that non-fear appeals (Tannenbaum et al., 2015). Some studies also suggest that state
anxiety and guilt may motivate patients to better adhere to treatment protocols than those who do not
experience these emotions (Mayne, 1999).
Retrospective Well-Being
A concern with recalled or retrospective judgments of well-being is their susceptibility to memory
biases (Schwarz & Strack, 1999). They may also be vulnerable to heuristic biases such as peak-and-end
effects (Fredrickson, 2000)--the tendency to evaluate a past episode by its most intense experience as well
as its ending, with less weight placed on the overall duration of the episode. If recalled experiences are
inaccurate, what utility could they have for understanding a person’s well-being? Although retrospective
well-being assessments are far from a perfect recollection of past experiences, they do reflect actual
experiences (Scollon et al., 2004; Tov, 2012). Moreover, peak-and-end effects are not consistently
50
observed when emotions are recalled for time frames that involve several episodes (Miron-Shatz, 2009;
Parkinson, Briner, Reynolds, & Totterdell, 1995). Instead, the average level of affect experienced during
the period is a stronger predictor of retrospective well-being than either peak or end experiences. Finally,
retrospective well-being judgments mediate the effect of daily events on global well-being measures, even
after controlling for trait happiness and neuroticism (Tov, 2012). Thus, how we remember our well-being
over the recent past forms a bridge from momentary well-being to more stable forms of well-being.
Retrospective judgments have important implications for decision-making. For example, the
decision or desire to repeat a vacation was predicted by retrospective but not online measures of emotion
(Wirtz, Kruger, Scollon, & Diener, 2003). Cultural differences in well-being may also manifest in
retrospective measures more strongly than online measures. Oishi (2002) found that participants of Asian
descent tended to report lower retrospective well-being over the past week than European Americans.
However, the two groups tended not to differ on measures of online well-being during the same week. This
suggests that retrospective well-being may be influenced by cultural norms and values and is consistent
with Robinson and Clore’s (2002b) model of emotional self-report. More specifically, culture may shape
people’s beliefs about which emotions are desirable to experience (Tsai et al., 2006), and such beliefs may
influence how people remember and reconstruct their past emotional experiences (Scollon, Howell,
Caldwell, & Ito, 2009). On the other hand, cultural differences in online emotional experience have been
reported in other studies (e.g., Scollon et al., 2004; Kitayama et al., 2006). Such differences appear to be
larger for disengaged emotions (e.g., pride and anger) than for other emotions—with Asians tending to
report lower levels than European Americans. Thus, the extent to which culture influences retrospective
versus online affect may also depend on the particular emotional state examined.
On the whole, the above findings offer some insight into how global well-being can be stable in the
face of most events but still be responsive to change during major life events. Cultural values, personality
traits, and other individual differences may influence how we remember our recent past, and these
influences may act on global well-being in a similar manner. However, these factors may only shape
memory to a certain point. Actual experiences impose a reality constraint on recall biases. A person who is
injured in a car accident may not be able to recall the experience as a positive one no matter how inclined
they are toward positivity.
Future Directions
A great deal of research has examined the structure and correlates of PA, NA, and LS. This work
has advanced the field but there remains much to learn about well-being. First, many studies separately
examine AWB and CWB. Researchers have only recently begun to understand the processes that are
unique to these components. For example, Luhmann, Hofmann et al. (2012) find some evidence that
adaptation to life events occurs more quickly for AWB than CWB--but the findings depend on the
particular event (e.g., bereavement versus unemployment). Few studies have compared the unique effects
of PA, NA, and LS on health. Wiest, Schüz, Webster and Wurm (2011) observed that both PA and LS (but
not NA) independently predicted mortality. Additional research on the unique or divergent correlates of
HWB components provides important insights into how interventions can best enhance well-being, or why
some interventions and policies fail to obtain their desired effects. In addition to measuring AWB and
CWB, researchers should also attend more to how PA and NA are operationalized. Certain measures of
affect (e.g., Watson et al., 1988) measure high-arousal states, other measures are more valenced-based (e.g.,
SPANE; Diener, Wirtz et al., 2010).
More theoretical and empirical work is needed to understand how EWB should be conceptualized,
as well as the processes that contribute to convergence and divergence between HWB and EWB. Following
the recommendation of Kashdan et al. (2008), it will be extremely informative to study specific
components of EWB and how they relate to components of HWB. For example, although meaning and
satisfaction are highly correlated, they diverge more in response to negative experiences than positive
experiences (Tov & Lee, 2016). Although positive experiences are generally associated with greater
meaning and satisfaction, negative experiences (e.g., a romantic break-up) can be meaningful but
dissatisfying. In addition, the implications of an event for one’s future appears to be a predictor of meaning
but not satisfaction (see also Baumeister et al., 2013 for a related analysis).
Efforts to identify the unique correlates and processes underlying AWB, CWB, HWB and EWB are
likely to require large sample sizes to detect such differences. This is because these constructs tend to be
strongly correlated with each other so that the amount of unique variance (e.g., in EWB after controlling
for HWB) will tend to be small. For example, Tov and Lee’s (2016) observation that certain negative
experiences are negatively correlated with satisfaction but positively correlated with meaning is based on
thousands of events reported by over 2000 participants. These correlational differences amounted to a
Cohen’s Q of .05, which is a small effect. Realistically, many differences among well-being components
51
will be in the small to moderate range. Nevertheless, small effects can be theoretically and practically
important—particularly when they represent phenomena (e.g., daily experiences) that may cumulate over
time (Abelson, 1985). Well-being researchers who seek to uncover such effects will need to sample many
people and experiences to ensure that differences in well-being components are not simply due to noise or
random error. Large sample sizes also allow researchers to use more sophisticated statistical methods (e.g.,
structural equation modeling) to control for measurement error when they examine how different aspects of
well-being are related to other outcomes.
Occasionally, the contrast between HWB and EWB is described as “feeling good” versus “doing
good.” This contributes to the view that EWB is less affectively tinged than HWB. Indeed, certain elements
of EWB (e.g., mastery, growth, flow) are enhanced by activities that challenge the person. Such activities
may not be pleasant but contribute to a person’s development. However, other dimensions of affective
experience may be more relevant for EWB. For example, inherent in the experience of flow
(Csikszentmihalyi, 1990) is the notion of an optimal level of arousal. A task that is too easy (skills exceed
the level of challenge) induces boredom; a task that is too difficult (challenges exceed skills) induces
anxiety. Thus the balance between challenge and skills maintains a level of arousal that facilitates
concentration, interest, and engagement. Ryan and Frederick (1997) describe subjective vitality as a feeling
of positive energy that arises from the pursuit of activities that are personally expressive or self-actualizing-
a feeling of being alive. Subjective vitality correlated only modestly with high-arousal PA suggesting that
it reflects a distinct aspect of experience. Thus, similar to HWB, it may be possible to conceptualize EWB
as consisting of distinct affective and cognitive elements. This expanded view of EWB offers more avenues
to explore processes that link these two well-being conceptions.
A final related point is that divergences and similarities between state and trait measures of wellbeing
deserve more attention. Divergences are important to identify and understand because they prevent
inferential fallacies. For example, although chronic or trait NA is deleterious to health, it would be
erroneous to conclude from this that state NA is equally deleterious. Momentary anxiety could lead one to
take one’s symptoms seriously and seek early care, and thus be beneficial. Similarities are equally valuable
to identify. If trait-level relations are also mirrored at the state-level, this can guide intervention efforts
toward specific behaviors and experiences that enhance well-being. For example, if extraverted behavior
induces PA (mirroring the relation between extraversion and PA at the trait level), then well-being
interventions might teach skills to enact these types of behaviors with the idea that such tendencies over
time may contribute to higher but stable levels of PA. The state-trait distinction could also further the
understanding of EWB components--which have tended to be measured as traits rather than states
(Waterman, 2008).
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Reevaluating the Strengths and Weaknesses of Self-Report
Measures of Subjective Well-Being
By Richard E. Lucas, Michigan State University
Citation
Lucas, R. E. (2018). Reevaluating the strengths and weaknesses of self-report measures of subjective
well-being. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF
Publishers. DOI:nobascholar.com
Abstract
Subjective well-being, by definition, is a construct that relies on people's subjective evaluation of their lives
as a whole. The subjective nature of the construct makes self-report a natural method for assessing SWB.
However, the psychometric properties of these measures still must be questioned and assessed, both using
traditional techniques for evaluating reliability and validity, and using more targeted approaches for
understanding the processes by which respondents make these judgments. This chapter reviews the
evidence about the nature and psychometric properties of self-report measures of SWB, including
traditional global measures of life satisfaction and positive and negative affect, and more recently
developed experiential measures including experience sampling and the day reconstruction method.
Although specific questions remain about the processes underlying SWB judgments and certain limitations
exist, research shows that the psychometric properties of these measures are generally quite good.
Keywords: Subjective Well-Being, Self-Report, Measurement
There are many reasons why applied and theoretical researchers seek simple, well-validated measures
of the quality of a person's life as a whole. Such measures can help clarify which life circumstances or
individual-level characteristics are critical ingredients of "the good life," and these findings can in turn
reveal fundamental features of human nature. For instance, external circumstances that are reliably
associated with differences in well-being could provide information about basic needs that must be satisfied
for humans to flourish (Baumeister & Leary, 1995; Wilson, 1967). Similarly, individual-level
characteristics or personality traits that reliably predict well-being may point towards critical skills or
approaches to life that foster high levels of well-being. Such findings could be used by applied researchers
at the individual level to guide personal life decisions and at the societal level to guide public policy
(Diener, Lucas, Schimmack, & Helliwell, 2009).
A minimal amount of introspection reveals, however, that different life circumstances are likely to
affect different people in different ways. Although strong social relationships and a meaningful career may
both, on average, contribute to a good life, it also seems likely that the value that people place on these two
characteristics will vary across individuals; some people may be willing to sacrifice some degree of
relationship quality to obtain a successful career, whereas others may make the opposite choice. Thus, to
capture one's overall quality of life, some amount of subjectivity must be incorporated into this evaluation.
Subjective well-being (SWB) is a construct that focuses explicitly on these subjective evaluations.
Indeed, one simple, over-arching definition of SWB is that it represents "a person's subjective evaluation of
the quality of life as a whole." This definition acknowledges that the subject's own evaluation is prioritized,
which means that different people can evaluate the same objective life circumstance in different ways and
can weight different life domains differently. In addition, the focus on "life as a whole" means that the
totality of one's experiences and circumstances add up to an overall sense of quality of life, and that
different life circumstances may balance each other out in their impact on the overall evaluation. SWB can
be contrasted with objective list definitions of well-being, which typically identify a limited set of
measurable dimensions that must be considered, without input from the subject himself or herself, to obtain
an overall evaluation of the quality of life (see Diener et al., 2009, for a discussion). SWB researchers
typically object to such objective list approaches by pointing out both that it is difficult, if not impossible, to
develop uncontroversial lists of important domains, and that empirical evidence suggests that people do
weight domains differently.
One implication of this focus on subjective evaluations is that the study of SWB appears, necessarily,
to require the use of self-report measures. If researchers wish to capture a person's own evaluation of his or
her life, then it is difficult to think of alternatives to self-report measures. Unfortunately, self-reports have
known limitations (Lucas & Baird, 2006; Paulhus & Vazire, 2007), which can lead to concerns about the
psychometric properties of existing self-report well-being measures. Thus, it is especially important to
consider the evidence that exists for the reliability and validity of subjective well-being measures. Because
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there is no gold-standard measures against which self-reports can be compared (as there might be for other
constructs that can be assessed by self-reports, like height or one's grade point average), the process of
validating measures of SWB can be challenging. In general, the process proceeds by considering evidence
for reliability and construct validity, and also by addressing specific theoretical questions about how SWB
evaluations are made. In this chapter, I review the evidence for the reliability and validity of SWB
measures, along with the critiques of these measures and the alternatives that have been proposed.
Self-Report Approaches to Measuring Subjective Well-Being
Many different approaches to evaluating SWB have been developed, with the simplest consisting of
brief, self-reported evaluations of the quality of one's life as a whole. For instance, single-item life
satisfaction measures that ask "All things considered, how satisfied are you with your life as a whole" are
often included in large-scale panel studies and national surveys. Multiple-item versions of these measures
have also been developed, typically with similarly worded questions that tap into this overall sense that
one's life is going well (e.g., Diener, Emmons, Larsen, & Griffin, 1985; Lyubomirsky & Lepper, 1999).
Diener (1984) noted that these judgments of life satisfaction form a class of measures that he referred
to as being "cognitive" in nature. This term reflects the fact that answering such questions requires
respondents to reflect on their lives and consciously select a response that best reflects their overall
evaluation. Diener noted that such cognitive judgments could be contrasted with a separate class of
evaluations that are based in respondent's typical affective experiences (e.g., Watson, Clark, & Tellegen,
1988). The reasoning behind the use of such measures is that those whose lives are going well should
typically experience high and frequent levels of positive affect, along with low and less frequent
experiences of negative affect. Thus, an overall evaluation of life could be obtained by capturing a person's
typical levels of affect. Diener noted that these different components of SWB may ultimately result from
different causes, and thus, should be assessed separately to obtain a more complete evaluation of one's life
as a whole (though Busseri & Sadava, 2011, noted that there is some amount of conceptual ambiguity in
this tripartite model of SWB that could be clarified with additional theoretical precision; also see
Schimmack, 2008).
Traditionally, both the cognitive and affective components of SWB were assessed using global,
retrospective (or "evaluative") measures that required respondents to think back on their lives and the
characteristics of those lives to come up with judgments of life satisfactions or ratings of the frequency or
intensity of affective experiences over some extended period (Watson et al., 1988). However, there is
reason to believe that such retrospective evaluations of affective experience may not accurately capture the
actual experiences that people have in their daily lives. For instance, Robinson and Clore (2002) noted that
different processes are likely used to make judgments about one's current affective experience, one's very
recent affective experiences, and one's affective experience from far in the past. Specifically, they argued
that people can typically report with some degree of ease about their current affective experiences simply
through careful introspection, but that past experiences are rated by accessing episodic and semantic
knowledge. The more recent the experience, the more likely respondents are to rely on episodic memories
of the actual experience; the more distant, the more likely respondents are to rely on semantic knowledge or
stereotypes about how one typically feels in similar situations. Thus, they argued, different time lags lead to
differential accuracy, if the criterion is the actual emotional experiences that would have been reported in
the moment. In addition, some research suggests that when asked to aggregate over extended periods of
time, certain biases affect this aggregation process, leading to global evaluations that do not match with the
actual experiences as it occurred (Kahneman, Fredrickson, Schreiber, & Redelmeier, 1993; Redelmeier &
Kahneman, 1996).
Because of the potential for inaccurate reconstructions of one's affective experience at some earlier
point in time, some researchers have suggested that we should distinguish between measures that focus on
retrospective evaluations and those that capture people's emotional reactions to life as it is lived (Kahneman
& Riis, 2005). For instance, it is possible to use experience sampling methods, where respondents are
signaled multiple times per day (typically, using mobile phones) and asked to complete surveys about what
they were doing, who they were with, and how they were feeling (Mehl & Conner, 2013). Kahneman
(1999) argued that the benefits of these momentary---or experiential---reports (namely the fact that they
avoid problems with inaccurate memories and aggregation biases) makes them closer to a measure of
objective happiness than more evaluative, retrospective measures. Of course, this is an argument that must
be evaluated with empirical data, as this approach may introduce new methodological problems that do not
exist with more traditional retrospective methods (a concern I address below).
Finally, because methods like the experience sampling are extremely time- and resource-intensive,
both for the researcher and the participant, new methodologies that combine the strengths of these
experiential measures with the efficiency of more traditional questionnaire measures have been developed.
59
For instance, Kahneman, Krueger, Schkade, Schwarz, and Stone (2004) proposed a new technique, one
based in existing approaches to assessing time use, to assess affective experiences throughout the day.
Their Day Reconstruction Method involves respondents breaking their day down into distinct episodes that
represent coherent blocks of time that share some respondent-defined characteristic (e.g., "eating
breakfast," "walking the dog," or "cleaning the house"). Participants are asked to list all episodes they
engaged in throughout the day, to describe the features of these episodes (e.g., what the participants were
doing, who they were with, where they were), and to report the affect that they experienced during each
episode. The idea is that these day reconstructions, if completed relatively close in time to the actual
experience, will capture relatively accurate episodic memories of the recent events. Thus, they would have
many of the advantages of the experience sampling method, while only requiring a single, constrained
assessment occasion. Again, as with the experience sampling method, these reasonable assumptions can be
validated with empirical evidence.
The Reliability and Validity of Subjective Well-Being Measures
As I noted above, unlike certain self-report measures (such as those for height, weight, grade point
average, or even for some ratings of physical health), there is no gold standard against which self-report
measures of SWB can be compared. By definition, the evaluation is a subjective one, and thus, it captures
internal thoughts and feelings that are not visible to outside observers. This fact, however, does not mean
that self-reports themselves are unimpeachable sources of information about people's SWB. People may
misremember their affective experiences, may disproportionately weight certain irrelevant sources of
information when deriving a cognitive judgment of life satisfaction, may be unable to translate an internal
feeling to a meaningful response on an experimenter-provided scale, or may be unwilling to provide an
honest response when questioned about their well-being (see Schwarz, 1999, for a general discussion of
many of these issues). Thus, it cannot be taken for granted that any measures of SWB---self-report or
otherwise---reliably and validly captures the evaluation of interest.
In general, the quality of SWB measures has been assessed using traditional approaches to
understanding psychometric properties. For instance, indexes of reliability can be used to assess the extent
to which measures are free from measurement error. For multiple-item measures, this is typically assessed
using internal consistency coefficients, and for most measures, these coefficients tend to be high, reflecting
the fact that items that are typically included in well-being measures tend to be moderately to strongly
correlated (see, e.g., Diener et al., 1985). The reliability of single-item measures is slightly trickier to
assess, because internal consistency coefficients cannot be used to assess reliability. The reliability of these
measures is especially important, however, as single-item scales are often included in large-scale surveys.
Fortunately, because the conditions of people's lives tend to be relatively stable, at least over short periods
of times (e.g., most people's income, employment status, marital status, and health are stable in the short
term), one would expect measures that are based, at least in part, on these circumstances, to be relatively
stable, too. With this assumption in mind, short-term stability coefficients, or even longer-term stability
coefficients with varying intervals can be used to assess the reliability of the measures.
For example, Lucas, Freedman, and Cornman (in press) assessed the stability over the course of a onehour
interview in a group of participants who had also been assessed numerous times over the previous six
years. This research design allowed the authors to estimate stability over a very short interval, to assess the
extent to which the two measures of life satisfaction were related to measures of life satisfaction assessed in
prior years, and to test whether survey content administered between the two measures influenced the
ratings that respondents provided. Together, these analyses provide information about the reliability of
single-item measures and the extent to which any instability is due to systematic effects. Their results
showed that although stability over the hour-long interview was only .62, the measure assessed at the
beginning of the survey correlated just as strongly with prior years' assessments as did the measure
assessed at the end of the survey (with correlations in the range of .40-.50). Moreover, the intervening
survey content appeared not to have a major impact on the final life satisfaction rating.
Other research has used multi-wave data to estimate the reliability of these single-item measures of life
satisfaction (see Alwin, 2007; Kenny & Zautra, 1995 for general approaches to accomplish this goal). For
instance, Lucas and Donnellan (2007) used two long-running panel studies to separate stable trait variance,
reliable but slowly changing autoregressive variance, from unstable state variance in life satisfaction (which
can serve as an estimate of measurement error). They estimated the reliability of life satisfaction to be
approximately .67. Similarly, Lucas and Donnellan (2012) extended these analyses to four panel studies
and used measures of domain satisfaction to separate reliable state variance from measurement error, and
they found reliability estimates closer to .75. These estimates are also reasonably consistent with metaanalytic
analyses conducted by Anusic and Schimmack (2016) and Schimmack and Oishi (2005).
Together, these results suggest that single-item measures have a reasonable degree of reliability (for a more
detailed review of the evidence for the reliability of single- and multiple-item measures of SWB, see
60
Chapter 5 of Diener et al., 2009).
Assessing reliability is relatively straightforward, as this psychometric property can be described using
quantitative indexes. Validity, however, is more complex and more difficult to establish in any sort of
definitive way. Although validity is often simply defined as whether a test measures what it is supposed to
measure, providing evidence for validity has proven to be controversial (see Borsboom, Mellenbergh, &
van Heerdan, 2004, for a review and discussion). For instance, in contrast to the simple definition provided
above, Messick (1995) suggested that validity could be defined as "an overall evaluative judgment of the
degree to which empirical evidence and theoretical rationales support the adequacy and appropriateness of
interpretations and actions on the basis of test scores or other models of assessment" (p. 741). This
definition emphasizes that validity reflects a judgment that is based on theories of the underlying construct
that one hopes to assess.
Diener et al. (2009) reviewed evidence for four types of validity that could be considered when
evaluating self-report SWB measures. The weakest form is face validity, which simply refers to whether
the measure appears to measure what it is supposed to measure. Most SWB measures have high levels of
face validity, though it is possible to come up with reasons why face valid measures may not be desirable
or reasons why measures that lack face validity can serve as useful tools for assessing the construct. Thus,
researchers tend to focus on the other three forms of validity.
Content validity refers to the extent to which the measure in question captures the breadth of the
construct of interest, without including content that should theoretically be excluded. Diener et al. (2009)
noted that there are two types of measures where content validity is typically a concern. First, for
multifaceted measures of well-being, such as the Oxford Happiness Scale (Hills & Argyle, 2002), one
could raise concerns about the inclusion of irrelevant content. For example, this scale includes the item "I
think I look extremely attractive" which is not a face valid indicator of SWB. It is possible that happy
people are more likely to endorse this item, regardless of their objective appearance, in which case content
validity may not be affected by the item's inclusion. However, if the item truly taps the respondent's
objective appearance, then the item could shift the focus of the total scale score away from its desired
target.
The second type of scale for which content validity is typically a concern is for measures of the
affective components of SWB. For many years, debates have taken place about the number and nature of
affective dimensions that exist, and these debates shape the measures that are used to assess affective wellbeing.
For instance, the widely used Positive and Negative Affect Schedule (PANAS; Watson et al., 1988)
does not include items assessing face valid indicators of affective well-being such as happy or sad. This is
because the measure was designed to assess particular forms of positive and negative affect that are based
on underlying theories about the nature of affective experiences. Researchers who use affective well-being
scales should consider these existing theories and choose measures that best tap the content that they
believe is theoretically most relevant (for instance, alternatives to the PANAS like the Scale of Positive and
Negative Experiences [SPANE; Diener, Wirtz, Kim-Prieto, Choi, Oishi, & Biswas-Diener, 2009] may
provide a better match with some measurement goals).
Convergent and discriminant validity are complementary forms of validity that reflect the extent to
which a measure correlates strongly with other related measures (convergent validity) and correlates
weakly or not at all with measures to which it should be unrelated (discriminant validity). In terms of
convergent validity, it is especially important to show that different measures of the same construct cohere
even when assessed using different methods of assessment. This is because correlations between measures
can be inflated by shared method variance that may be independent of construct variance. Numerous
studies show that standard, widely used measures of SWB tend to show reasonable levels of convergent
and discriminant validity, even when different methods of assessment are used (Lucas, Diener, & Suh,
1996). For instance, Schneider and Schimmack (2009) reported a meta-analytic average correlation of .42
between self- and informant reports of well-being.
The final form of validity, and the most complicated to assess, concerns construct validity (Cronbach
& Meehl, 1955). This form of validity reflects the extent to which a measure behaves as it would be
expected to behave, given theories about the construct itself. Thus, to test construct validity, one must have
some idea about how a measure should relate to additional constructs. Diener et al. (2009) reviewed a
broad range of correlates of SWB, including income, social relationships, and relevant behaviors. They
conclude that widely used measures of SWB show relatively strong evidence for construct validity. For
instance, there is strong reason to expect that income would be related to well-being, given that money can
purchase many of the things that might be expected to cause high well-being; and indeed, income is
consistently related to measures of SWB (Lucas & Schimmack, 2009). Similarly, if low levels of life
satisfaction reflect a genuine evaluation of one's life as being of poor quality, one might expect scores on
61
life satisfaction measures to predict suicidal behaviors, which appears to be the case (Koivumaa-Honkanen
et al., 2001). Other studies show that domain-specific well-being measures predict relevant behaviors within
those domains (e.g., job satisfaction predicts turnover; Tett & Meyer, 1993). Although this is just a brief
overview of the type of evidence that can be used to assess validity, prior in depth reviews suggest that
established SWB measures show an impressive degree of validity (Diener et al., 2009).
Although reliability is often a concern with single-item measures, there can also be reasons to be
skeptical about the validity of such short measures. This is because psychological constructs are often
complex, and it may be difficult to capture this complexity in a single item. For instance, personality traits
like extraversion are often difficult to capture with a single-item because the construct itself is multifaceted.
SWB constructs like life satisfaction, however, are often much simpler. It may be more reasonable to assess
one's overall satisfaction with life with a single-item than it is to assess broad personality traits or attitudes.
Indeed, multiple-item measures of life satisfaction often have items that are very close in meaning to one
another, and those items that deviate often perform worse than the more straightforward items (Oishi,
2006). In any case, evidence suggests that when single- and multiple-item measures are compared, they
tend to perform similarly. For instance, Cheung and Lucas (2014) used data from large, representative
samples to compare the associations between various criterion variables and both single- and multiple-item
measures, and they found that correlations tended to be very similar in size. They concluded that there was
not a loss of validity when single-item measures were used.
The Judgment Model of Subjective Well-Being
One of the biggest challenges to the validity of SWB measures comes from the judgment model of
SWB (Schwarz & Strack, 1999). This model starts with the reasonable assumption that when asked about
their well-being, respondents do not have a response stored in memory that can simply be accessed and
reported. Instead, respondents must construct a response at the time of judgment. Researchers who work
from this judgment-model tradition consider the various steps that take place when such a judgment is
formed, and they investigate various sources of validity and invalidity that affect each step of the process.
For instance, because respondents may not have the ability or motivation to consider all relevant
domains of their lives when making a life satisfaction judgment, it is possible that they rely on various
heuristics to quickly derive an appropriate response to an experimenter's question. Most famously, Schwarz
and Clore (1983) suggested that respondents may rely on their current mood at the time of the judgments as
a proxy for how they feel about their life overall. To provide evidence for this possibility, Schwarz and
Clore (1983) manipulated mood (in one study, by having respondents write about positive or negative life
events, and in a second by contacting participants on days that varied in the pleasantness of the weather)
and then asked participants to report on their satisfaction with life (the experimenters made sure to present
the life satisfaction question as if it were part of an unrelated task so that participants would not make a
connection between the mood induction task and the well-being question). In accordance with their
predictions, Schwarz and Clore (1983) found that those who were exposed to the positive mood induction
procedures reported much higher life satisfaction than did those exposed to the negative mood induction
procedures.
Importantly, the authors included additional conditions in their design to provide support for the idea
that respondents heuristically rely on mood as a proxy for a broader life satisfaction judgment. Specifically,
in additional conditions, the authors drew respondents' attention to the fact that the mood they were
currently experiencing may have resulted from the prior induction. By making the cause of the mood
salient, the authors argued, respondents would be less likely to rely on this mood when making the life
satisfaction judgment. Again, results supported this hypothesis: the previously described mood effects on
life satisfaction judgments were eliminated when the cause of the mood was made salient. Subsequent
studies replicated these results with additional mood inductions, including having one's favorite soccer
team win or tie an important game or having participants complete the well-being questionnaire in a
pleasant or unpleasant room (Schwarz, Strack, Kommer, & Wagner, 1987).
In a related series of studies, Schwarz, Strack, and colleagues suggested that the specific sources of
information that are used when evaluating SWB can be influenced by contextual factors. Specifically,
people base their judgments about the quality of their lives on different life domains, depending on which
of these domains are salient at the time of the judgment. For instance, Strack, Martin, and Schwarz (1988)
asked respondents about their satisfaction with life and their satisfaction with dating in one of two
conditions: either with the dating question asked immediately prior to the global life satisfaction question or
immediately following the question. The idea was that if satisfaction with dating was made salient, then
respondents would be more likely to incorporate this specific life domain into their overall evaluation of
life than if the domain had not been made accessible. Again, the results supported this prediction, with
much stronger correlations between the two questions when the domain satisfaction rating was presented
62
prior to the life satisfaction question. Schwarz and Strack (1999) review additional studies that further
clarify how this information is used in global well-being judgments, along with other contextual factors
(such as information about social comparison or subtle features of questionnaire design) that can impact
global well-being judgments in ways that potentially affect the validity of the measures. This programmatic
line of research has had an important impact on perceptions of the validity of global self-reports of SWB
(e.g., Kahneman & Krueger, 2006).
Concerns About the Judgment Model
In recent years, broad concerns have been raised about standard research practices in the field,
especially within (though certainly not limited to) specific domains in social psychology (Bakker, van Dijk,
& Wicherts, 2012; Open Science Collaboration, 2015; Simmons, Nelson, & Simonsohn, 2011). These new
methodological critiques suggest that certain "standard operating procedures" within the field can lead to
high rates of false positive findings. These methodological practices include the reliance on very small
samples, which can increase the rates of false positives that make it in to the published literature (Bakker et
al., 2012); an aversion to publishing replication studies (Makel, Plucker, & Hegarty, 2012) and null results
(Ferguson & Heene, 2012); and flexibility in analyses, which, when combined with natural tendencies to
fall prey to confirmation bias, allow for capitalization on chance in support of a prediction (Gelman &
Loken, 2013; Simmons et al., 2011). Because most of the published findings that support the judgment
model were published at a time when these problematic methodological practices were the norm, it is worth
revisiting the findings to determine whether the evidence is as strong as its advocates claim.
Indeed, a close look at the studies that are typically cited in support of the judgment model suggest that
there is cause for concern. First, sample sizes from these studies are almost always extremely small (though
for an exception, see Deaton, 2012). For instance, Yap et al. (in press) reviewed as many studies as they
could find that examined the effect of mood on life satisfaction judgments and they reported that these
studies had an average of just 11 participants per cell---a sample size that could only detect very large
effects.
Second, the effect sizes that are typically found are arguably too large to be plausible given the
hypothesized processes that underlie these effects. The effect of a mood induction procedure on life
satisfaction judgments should result from the multiplicative effect of the induction on mood and the
subsequent effect of mood on life satisfaction judgments. In turn, this means that the effect of a mood
induction on life satisfaction judgments will necessarily be smaller than the effect of the induction on
mood or mood on life satisfaction. Furthermore, one could derive plausible expectations for effect sizes
from what we know about the typical effect sizes for mood induction procedures and for the association
between mood and life satisfaction. As Yap et al. (in press) showed, however, effect sizes for the effect of
mood induction procedures on life satisfaction judgments have typically ranged from ds of 1 to 2.5, which
are equal to or even exceed the typical manipulation check effect sizes for mood inductions themselves
(Westermann, Spies, Stahl, & Hesse, 1996)!
Finally, there is considerable evidence of analytic flexibility across studies, where different analyses
are used and different effects emphasized (e.g., interaction versus simple effects) even when very similar
designs were used. Together, these patterns suggest that large-sample replications would be needed before
strong conclusions about the replicability and robustness of effects from the judgment-model tradition can
be drawn.
Partly in response to these concerns, researchers have begun to reexamine classic effects from the
judgment-model tradition using much larger sample sizes than in the originals. For example, Yap et al. (in
press) conducted nine replication studies with sample sizes that were five to ten times as large as those
from the originals to examine the effect of mood on life satisfaction judgments. Effects were typically not
significant, and those that were significant were considerably smaller than those from the original studies.
Overall, meta-analytic estimates from the nine studies were less than one-tenth the size of the average
effect from the original work (with ds around .15). These studies suggest that mood has only weak effects
on life satisfaction judgments.
Moreover, these replication studies are consistent with other large sample studies investigating context
effects on SWB judgments. For instance, Lucas and Lawless (2013) used a sample of almost one million
U.S residents to examine the effect of current weather conditions on life satisfaction judgments. Even
though they had considerable power to detect ever very small effects, they found no evidence that weather
systematically influenced satisfaction judgments. In addition, in a study specifically designed to examine
the extent to which naturally occurring fluctuations in mood were associated with fluctuations in life
satisfaction judgments, Eid and Diener (2004) assessed both multiple times over a three-month period.
They showed that although mood fluctuated considerably across occasions, life satisfaction judgments did
not. Furthermore, the transient component of life satisfaction was only weakly associated with changes in
63
mood, confirming with a different designs the results from Yap et al. (in press).
Additional studies have examined other context effects predicted by the judgment model and have had
similar problems replicating the original findings. Most notably, Schimmack and Oishi (2005) conducted a
number of studies examining item-order effects, in which the association between satisfaction with a
specific domain and satisfaction with life as a whole varies depending on whether the domain was assessed
prior to or after the global judgment (e.g., Strack et al., 1988). Schimmack and Oishi failed to replicate the
large differences found in the original studies, and they showed in a meta-analysis that most studies that
have tested for item order effects show only small differences across conditions. Schimmack and Oishi
concluded that manipulating the order of items should, theoretically, not have large effects, as domains that
are likely to be considered in global judgments (such as health or romantic relationships) are typically
chronically salient, and thus will be included in global judgments even if the context does not make them
salient. On the other hand, domains that are not chronically salient (e.g., the weather, local public
transportation) are unlikely to be considered relevant for global life satisfaction, and thus will not affect
satisfaction judgments even when made salient. Thus, they argued, item order effects should not be
expected to be pronounced; a prediction that is supported by their large-sample studies and meta-analysis.
It is true that at least one large-sample context effect was found that had more than a modest effect
size. Deaton (2012) showed that in Gallup data, asking questions about politics before a question about
subjective well-being led to a moderate drop in life satisfaction, compared to a condition where these
political questions were omitted. Although the mechanisms underlying this effect have not been determined
(see, e.g., Lucas, Oishi, & Diener, 2016), the fact that this effect emerged in a large sample study must be
acknowledged. Importantly, however, Deaton also showed that the effect was eliminated very easily simply
by asking a buffer question that returned focus to the person’s life before asking the well-being question.
Future research can clarify when and how these effects emerge or can be prevented.
Research from the judgment model is valuable in that it pushes well-being researchers to consider the
processes by which respondents formulate and report responses to questions about their SWB. The theory
itself is straightforward and elegant, and it is likely that the processes identified by judgment-model
researchers can impact life satisfaction judgments (as they have been shown to affect judgments in a wide
range of circumstances). The important practical question, however, is not whether these processes exist,
but how much they affect the psychometric properties of well-being judgments. It is possible, for instance,
that the heuristics that the judgment-model researchers have identified represent just one of many processes
that people can use to formulate well-being judgments, and any problems for validity that these processes
introduce are outweighed by more straightforward and intuitive processes that positively impact the validity
of these measures. Thus, it is important not only to look for evidence of underlying processes posited by the
judgment model, but also to explicitly test the extent to which these processes undermine the validity of
these measures as typically used. The research reviewed above suggests that context effects predicted by
the judgment model tend to be very small; a conclusion that is supported by the considerable evidence for
reliability and validity of SWB measures.
Comparing the Psychometric Properties of Global and Experiential Measures
If the two main categories of self-report measures of well-being are global measures and experiential
measures, then a final issue to consider concerns the comparison between the two in terms of their
psychometric properties. Remember, the idea behind the latter experiential measures is that assessing
affective reactions at the time they occur (or very soon after) reduces memory problems and prevents
biases that result from aggregation. Thus, it is often argued that such measures will have more desirable
psychometric properties than global measures (Kahneman, 1999). However, it is possible that these
methods have unique psychometric problems that don't affect global measures. In addition, the relatively
high level of respondent burden means that respondents are often assessed over a very short period of time,
which can lead to concerns about the stability of results that are obtained. In other words, if respondents are
asked to complete a day reconstruction method report for a single day of their lives, will the affect they
experience generalize to other days and reflect a stable sense of well-being?
In their initial development efforts, the researchers who proposed the day reconstruction method did
not assess long-term stability, but recent efforts have begun to provide information on this topic. For
instance, Krueger and Schkade (2008) tested short-term stability and found that it was comparable to global
measures of life satisfaction, even when only a single day of experiences was sampled. Similarly, both
Hudson, Anusic, Lucas, and Donnellan (in press) and Hudson, Lucas, and Donnellan (2016) tested fourweek
stability of DRM measures, with results showing moderate stability, with correlations in the range of
.40 to .60. Hudson, Lucas, and Donnellan (2016) used four waves of data, each separated by a year-long
interval, to test the long-term stability of the day reconstruction methods. Again, even though just a single
day of experiences was sampled, year-to-year stabilities were moderate and only slightly weaker than those
64
from global measures like a single-item life satisfaction scale. Thus, it appears that relatively stable, traitlike
measures of well-being can be obtained even from a single day's worth of reports.
These studies have also begun to compare the convergent and construct validity of global and
experiential measures using large samples of participants. Anusic et al. (2017), for instance, used data from
a three-wave study to examine the correlations between global and day-reconstruction-based measures of
well-being and informant reports and relevant criteria (also see Hudson et al., 2016, for a similar study
with similar conclusions). These studies show that global self-reports typically correlate as strongly or even
more strongly with alternative measures and relevant criteria as compared to experiential measures derived
from the day reconstruction method.
Given the theoretical arguments for the superiority of experiential measures over global measures,
why don't experiential measures show enhanced validity when compared directly to global measures (at
least in these initial studies)? One possible reason is that the two types of measures assess two distinct
underlying constructs. For instance, Diener and Tay (2014) suggested that global measures are better at
tapping experiences that are contextualized within a person’s life schema, and that this allows these
measures to predict a wider range of meaningful outcomes than more experiential measures that lack such
contextualization.
Alternatively, it is possible that the unique demands of the experiential measures create specific
threats to validity that do not apply to global measures. For instance, Watson and Tellegen (2002) argued
that when respondents are asked to repeatedly respond to affect questions, unwanted response-style
variance can, because of aggregation, get amplified relative to the variance that taps the underlying
construct. Furthermore, additional research shows that asking respondents to repeatedly answer the same
question over and over again can change respondent's interpretation of the questions.
For instance, Baird and Lucas (2011) examined this issue in a different domain: the repeated
assessment of personality across different situations. They found that respondents reported more variability
and greater impact of situational features when they were asked to report their personality multiple times in
different situations than if they were asked to report on their personality in just one situation. In other
words, when asked how extraverted they were in a specific situation, respondents exaggerated the effect of
the situation when they were asked about multiple situations than when they were asked just about one. It
is possible that experiential measures like experience sampling or day reconstruction methods
communicate to respondents that they should emphasize the changes that occur from situation to situation
rather than the stability that they experience. If so, this may affect associations between experiential
measures and stable predictors of well-being. All in all, although experiential measures are especially
useful when assessing changes in affective experiences over short periods of time, they do not have a clear
advantage over global measures when used to assess stable levels of well-being. Of course, more research
that directly compares the psychometric properties of these two forms of measures is needed.
Conclusion
The domain of SWB, by definition, focuses on people's subjective evaluations of their lives. Thus,
there is a strong emphasis within SWB research on self-reports of the construct, as such subjective
evaluations may best be assessed by asking the subject themselves. However, the subjective nature of the
construct does not mean that self-reports are an unimpeachable source of information about the construct.
As with all measures, the psychometric properties of these instruments must be assessed.
Fortunately, existing research suggests that SWB measures typically have desirable psychometric
properties, including relatively high levels of reliability, convergent, discriminant, and construct validity.
To be sure, these measures, like all self-report measures, are not perfect. Research from traditions such as
the judgment model of SWB provide the means of testing some of the processes underlying well-being
judgments, and when combined with more traditional approaches to evaluating psychometric properties,
this research can help clarify the relative strengths and weaknesses of these approaches. Thus, research on
the properties of self-report measures can not only strengthen conclusions from research that uses those
methods, but can also help clarify what SWB is and how people go about evaluating their lives.
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Non-Traditional Measures of Subjective Well-Being and Their
Validity: A Review
By Christie Napa Scollon, Singapore Management University
Citation
Scollon, C. N. (2018). Non-traditional measures of subjective well-being and their validity: A review. In
E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
This chapter reviews a variety of methods for assessing subjective well-being beyond traditional global
self-reports. The chapter examines indicators of SWB such as brain activity, smiling, cognitions, memory,
and momentary experience. The author discusses the practical costs and benefits of each. Lastly, the
chapter reviews new forms of data such as social media and internet searches and how they can reveal
information about the subjective well-being of groups. While no single measure is perfect, this chapter aims
to equip researchers with the knowledge to make informed decisions in their research designs and projects.
Keywords: Measurement, Assessment, ESM, DRM, Twitter, Facebook
Traditionally, subjective well-being (SWB) has been measured with global self-reports. There are
good philosophical foundations for using self-reports of SWB. After all, the construct refers to subjective,
not objective well-being, and who is best to judge how someone feels about her life other than the person
herself? Global self-reports such as those captured by life satisfaction questions are especially relevant
because it is these broader cognitive evaluations of one’s life as a whole that are arguably at the heart of
SWB. Similarly, other self-reports such as frequency and degree of positive and negative emotions provide
information about the affect component of SWB. Nevertheless, there are good reasons to explore
alternative measures of SWB. For example, global self-reports of SWB can be vulnerable to memory
biases, social desirability, or focusing illusions. Another reason is that newer technologies may allow
scientists to collect SWB data through less burdensome, more economical means. No matter the case,
alternative measures of SWB can complement traditional self-reports. This chapter will explore these
alternative measures and their validity.
Brain Activity
Since the 1990s techniques such as functional magnetic resonance imaging (fMRI) and
electroencephalogram (EEG) have revolutionized the field of psychology. What can a window into brain
processes reveal about SWB? Specifically, can fMRI and EEG be used to measure SWB? In order to
address this question, we must first determine whether reliable patterns of brain activation exist for
happiness or other emotions. Feldman Barrett and Wager (2006) pointed out that conditions such as
consistency (i.e., activation that is not due to emotion induction procedures) and specificity (i.e., activation
patterns that are non-overlapping for various states) must be met in order to establish the validity of the
measures.
A handful of studies have used meta analytic techniques to examine the many fMRI and positron
emission tomography (PET) studies to identify neural profiles for happiness and other emotions.
Unfortunately, there remains no consensus among meta analytic studies. For example, Murphy, NimmoSmith,
and Lawrence (2003) identified the rostral supracallosal anterior cingulate cortex (ACC) and
dorsomedial prefrontal cortex (PFC) as highly involved in happiness, whereas Phan, Wager, Taylor, and
Liberzon (2002) identified the basal ganglia as consistently involved in happiness. More recently, Vytal
and Hamann (2010) used a more sensitive meta-analytic method to determine if any consistent activation
exists for specific emotions. For happiness, the most frequently activated structure was the right superior
temporal gyrus (STG).
Often it is difficult to separate activation due to the emotion itself and activation due to other
cognitive processes invoked during the emotion induction procedure. For example, Suardi, Sotgiu, Costa,
Cauda, and Rusconi (2016) reviewed 15 studies which used fMRI and PET on subjects who had been
asked to recall happy memories. They found that remembering happy autobiographical events was
associated with activation in the PFC, ACC, and insula. However, these structures were also implicated in
the experience of negative emotions. Indeed, autobiographical recall is a complex task that requires
memory retrieval, self-referencing, and cognitive processes such as appraisal. Not surprisingly, these very
regions (PFC, ACC, and insula) have also been identified as relevant to these complex processes.
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Similarly, Phan et al. (2002) identified the medial PFC as generally involved in emotion processes, and
activation of the ACC and insula as due to emotion recall procedures.
Despite the vast number of studies, neuroscience has yet to converge on any clear brain markers of
happiness or any other emotion for that matter. In fact, the most agreed upon finding is that the amygdala
is involved in fear (Murphy et al. 2003; Phan, et al. 2002), but even then, there is disagreement among
scientists. For instance, the conditions of consistency and specificity have been hard to meet. There are
conditions under which amygdala activation occurs which do not involve fear and sometimes even involve
positive stimuli (see Feldman Barrett & Wager, 2006).
Part of the challenge in identifying which brain structures are associated with happiness is that most
structures are involved in multiple emotions and serve multiple functions. Few distinct patterns exists that
characterize a particular state or trait. However, there is evidence to suggest neural correlates of broader
affective categories as there appear to be differences in brain activation in approach-related emotions (e.g.,
happiness, anger) as compared to avoidance-related emotions (e.g., fear, sadness). For instance, Richard
Davidson’s lab uses EEG to measure asymmetry of frontal lobe activation. His team has consistently found
that greater left than right PFC activity is associated with positive affect (Urry et al., 2004). Similarly,
Feldman Barrett and Wager (2006) noted that some studies found greater left-side activation for approachrelated
(as opposed to avoidance-related) affect. The findings are consistent with Gray’s (1970)
neurobiological theory which posits the existence of a Behavioral Activation System that governs
appetitive, reward seeking behavior, and a Behavioral Inhibition System that governs avoidance behavior.
Smiling
What can a smile reveal about a person’s SWB? Two detailed studies provide strong evidence that
smiling in photographs is a valid measure of SWB. Harker and Keltner (2001) examined yearbook photos
of women from the Mills College Study. Expert raters used the Facial Action Coding Scheme (FACS:
Ekman, Friesen, & Hager, 1978) to rate the photographs, including the extent to which the women
exhibited Duchenne smiles, or genuine smiles. Photographic ratings correlated with self-reports of
personality and emotion. Individuals who expressed more positive emotionality in their yearbook photos
reported less negative emotionality—and this relation held over time even when comparing self-reported
emotionality 20 years after the photographs were taken. Photographic expressions also correlated with
scores on the Well-Being Scale of the California Psychological Inventory (CPI: Gough, 1990) which
contains items about emotional and physical health and has been shown to be highly related to life
satisfaction.
Another study by Seder and Oishi (2012) compared photographs from Facebook profiles and selfreported
life satisfaction. Expert raters judged participants’ photographs for displays of positive
emotionality. Smile intensity not only correlated with concurrent life satisfaction, but it also predicted
changes in life satisfaction. Individuals with greater and more genuine smiles at Time 1 had greater
increases in life satisfaction over a two-year period than those with less intense or no smiles. Moreover, it
was demonstrated that the effect was not due to extraversion.
Abel and Kruger (2010) and Scollon, Sim, Shin, Koh, and Stevens (2016) also used smiling in
photographs as a measure of SWB, but these studies did not have self-reported data to validate their
measure. They did, however, find that smiling predicted longevity (Abel & Kruger, 2010) and teaching
performance (Scollon et al., 2016)—results which are consistent with a broader literature demonstrating the
links between positive emotionality and desirable life outcomes (e.g., Danner, Snowdon, & Friesen, 2001;
Lyubomirsky, King, & Diener, 2005). These authors have argued that the photographs indeed capture
stable individual differences in SWB.
Other research suggests a need for caution when making inferences about smiling. Labroo,
Mukhopadhyay, and Dong (2014) demonstrated that people differ in their lay theories about smiling.
Whereas some people smile when they are happy (emotion expression theory), others smile in an attempt
to become happy (emotion regulation theory). In a series of experiments, Labroo et al. (2014) found that
smiling made people with the expression theory feel happier (probably based on a facial feedback
mechanism) whereas smiling made people with the regulation theory feel worse. By this rationale, smiling
might be less informative about the SWB of a person who holds the emotion regulation theory, compared
to people who hold the expression theory. Labroo et al. (2014)’s study, however, was a laboratory
experiment where smiling was manipulated. Assessing smiling in photographs may be less of a problem
because there is a strong expectation to express how one feels, rather than regulate internal states at that
moment.
In short, smiling appears to be a valid indicator of SWB. Relative to other measures, smiling is not
widely used as a measure of SWB in research. However, as the technology for automatic coding of facial
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expressions improves, reducing or removing the need for human coders, the science of SWB may see more
studies using smiling in the future (see big data section).
Experience Sampling Methodology
Experience Sampling Methodology (ESM) involves participants answering questions about their
affect and activities in real-time several times a day over several days. For example, respondents in a
typical ESM study may receive 4-7 signals or alerts during the waking day. When respondents receive an
alert, they complete a brief questionnaire about what they are doing at that moment, how they are feeling,
etc., that typically takes less than a minute to complete. Technologies such as smart phones or personal
data devices (e.g., Palm Pilot) make it easy for scientists to sample affect, behaviors, and time use by
automatically sending alerts to participants and storing participants’ responses either directly on the device
or on a server. Smartphone technologies can even allow researchers to capture multimedia data and
location information as well. These advances have made ESM more convenient for participants and
reduced error and data loss leading to a greater response rate overall. Smart phones in particular are
convenient for both researchers and participants. A 2015 Pew Survey found that 68% of Americans now
own a smartphone. Among smartphone owners, 81% report that they keep their smartphone near them
almost all the time during waking hours, and more than 70% report checking their smartphone a minimum
of once per hour (Gallup, 2015). Never before in the history of social science research have scientists been
able to track daily lives so closely and frequently. For a comprehensive review of ESM see Scollon, KimPrieto,
and Diener (2003).
The advantage to using ESM is that respondents report on their feelings and activities in real-time
or close to real time. This reduces the memory biases that often plague retrospective or global reports of
well-being (Feldman Barrett, 1997; Oishi, 2002; Robinson, Johnson, & Shields, 1998; Scollon, Diener,
Oishi, & Biswas-Diener, 2004). The richness of the repeated measures also allows scientists to investigate
dynamic and within-person processes (e.g., Tov & Lee, 2016).
To examine the validity of ESM, we need to consider not only the psychometric evidence but also
the philosophical underpinnings of the construct of SWB and its measures. The studies that have measured
both ESM and global self-reports of SWB have shown there is a positive moderate correlation among the
measures (Scollon et al., 2004). The less than perfect correlation either means that ESM and global selfreports
are not exactly the same, or that one or both of these measures is poor. Because ESM relies on
repeated measures, the aggregated data yield high reliability estimates, typically in the .90s. Therefore, the
assumption is usually that ESM is the gold standard and that global self-reports are the fallible measure.
Assuming ESM is the gold standard, what can it be compared to for validation? Ultimately,
researchers need to look at the entire nomological network of measures. Wirtz, Krueger, Scollon, &
Diener (2003) examined ESM, global/retrospective ratings, and behavioral choice in their study which
tracked students before and after a Spring Break experience. Students reported on their feelings before,
during, and after the vacation. Three weeks after returning from their vacation, respondents reported the
extent to which they would like to have a similar Spring Break experience to the one they just had. Wirtz
et al. (2003) found the expected intercorrelations among all the SWB measures. However, and most
intriguingly, ESM reports during the vacation were completely unrelated to wanting to repeat the
experience. Only students’ memories of the vacation predicted wanting to repeat the same (or similar)
experience. At first glance, the findings may seem to defy conventional wisdom, not to mention
behaviorism which posits that human beings should seek to repeat experiences they enjoy and avoid
experiences they didn’t enjoy. However, the results highlight the fundamental difference between what
Kahneman (2010) calls experienced versus remembered utility. ESM captures experienced utility, the
enjoyment that occurs during an experience, whereas global and retrospective reports capture remembered
utility, how one remembers an experience. Whereas experienced utility is fleeting and lasts only as long as
short-term memory lasts, remembered utility remains and continues to influence behavior long after the
experience is over. The two types of utility are independent, and although ESM may have greater veracity
or accuracy for experience utility, it is not necessarily superior depending on the outcome measure.
Unlike global self-reports of SWB, ESM has a greater potential for reactivity effects. Because the
methodology draws attention to the respondent’s internal states, perhaps with high frequency and intensity,
ESM may actually change people’s well-being during the course of a study. For example, depressed
participants in a two-week experience sampling became less happy over time with greater frequency of
emotion reporting (Conner & Reid, 2012). By contrast, non-depressed participants showed the opposite
pattern and became happier over time with greater emotion reporting.
There are practical limitations to ESM as well. First, the methodology is intensive. Participants can
find the frequent questioning to be invasive, even irritating. For this reason, researchers must keep the
number of questions in each momentary assessment to a minimum. Second, the methodology requires
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considerable compliance from participants, which means some groups will be over-represented in ESM
studies (e.g., conscientious people with not too chaotic lives), and even then researchers must typically
offer good incentives for people to participate. Technological advances that make ESM more convenient
for participants (such as using a smart phone app on the participant’s own phone) will help narrow the gap
between those who can and those who cannot complete an ESM study, but there are some limitations
which will always remain. For scientists interested in starting their first ESM study, see Conner and
Lehman (2012).
The Day Reconstruction Method
The Day Reconstruction Method or DRM (Kahneman, Krueger, Schkade, Schwarz, & Stone, 2004)
has been heralded as offering the richness of ESM with the convenience of a single-time assessment. The
DRM guides respondents through a detailed moment-by-moment reconstruction of the previous day’s
activities. Participants record the location, duration, and affect experienced during each episode.
Experienced affect can be weighted as a function of duration, and researchers can estimate affect in specific
activities (e.g., childcare, commuting). The DRM is designed to minimize memory biases by being close in
proximity to the previous day’s experiences and by relying on cued recall. Several studies have now
examined its validity.
Individual Difference Studies
Responses on the DRM consistently correlate with individual difference measures in expected
ways. Depressed patients report more negative and less positive affect in the DRM compared to nondepressed
patients (Bylsma, Taylor-Clift, & Rottenberg, 2011). Likewise, the relation between PA and
Extraversion has been replicated using the DRM (Srivastava, Angelo, & Vallereux, 2008). Diurnal
patterns of affect using the DRM (Daly, Delaney, Doran, & MacLachlan, 2011; Kahneman et al., 2004)
mirror studies using ESM. Other studies have shown that the DRM can be used successfully and
meaningfully in a variety of cultures (Caballero et al., 2014; Mellor-Marsa et al., 2015). On the other hand,
Hoffenaar, van Balen, and Hermanns (2010) compared the DRM and global measures in a sample of
women pre- and post-partum and found only modest convergence among the two types of reports. The
authors concluded it is important to measure both global and experienced affect.
Is the DRM a Good Substitute for ESM?
In order to answer this question, researchers need to directly compare ESM data and DRM data.
Dockray et al. (2010) was one of the few studies to have done this, and they found consistent within-person
variation in affect across the two types of measures. Specifically, affect, especially reports of happiness, in
both the DRM and ESM corresponded with one other over the course of the day. Fisher R to Z correlations
were generally around .60, before adjusting for unreliability, lending strong support to the idea that the
DRM may, in fact, provide equivalent information to ESM. However, Diener and Tay (2014) pointed out
that completing the ESM together with DRM may inflate the convergence of measures. By drawing
attention to people’s emotions using ESM, responses on the DRM may be more accurate than usual.
Bylsma et al. (2011) found moderate to strong correlations among ESM and DRM measures in a
sample of depressed and non-depressed participants. They also tested for reactivity to events and found
reactivity effects replicated across the two methods. Srivastava et al. (2008) also tested for reactivity using
the DRM and found that extraverts do not display greater reactivity to social events. Srivastava’s study
replicated what Lucas and Baird (2004) established using ESM, lending further support to the DRM as a
decent substitute for ESM.
Abbreviated DRM
Although the DRM is significantly less time intensive than ESM, it still takes typically one hour to
complete, which makes it impractical for large scale studies. Anusic, Lucas, and Donnellan (2016)
examined the validity of a random sampling DRM. In this abbreviated format, respondents list the
previous day’s episodes or events, similar to the original DRM. However, instead of providing affect
ratings for all episodes, respondents rate a randomly selected subset of episodes. Most promising, the
shortened version of the DRM was shown to converge with other SWB measures and yielded results
comparable to the original DRM studies.
Caveats
At the heart of these validation studies lies a more fundamental question about what specific
measures mean within a theory of subjective well-being. In comparisons of the DRM with ESM, the
assumption is that ESM is the gold standard. As described earlier, ESM has been shown to be a poor
predictor of behavioral choices (Wirtz et al., 2003). If the DRM is supposed to yield ESM-like data, is
there any reason to suspect that the DRM would be any better at predicting behavioral choices?
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Another limitation of the DRM is the common practice of weighting affect by duration of the
episode. While there is a logic to this practice, it also presupposes that psychological duration can be
counted in the same units as time. Lastly, one of the chief advantages of the DRM over ESM is that the
DRM can provide nearly as much information as ESM without the time/resource intensity. However, smart
phone apps and more widely available passive data may erode this gap or at least narrow it.
Memory Measures
A memory task can be a subtle, yet powerful way to assess SWB as demonstrated by Sandvik,
Diener, and Seidlitz (1993). They gave subjects 2 minutes to recall all the positive things that had
happened in their lifetime, and later another 2 minutes to recall all the negative things that had happened.
The balance of frequency of positive memories over negative memories was shown to correlate with selfreports
of life satisfaction. In other words, happy people recalled a preponderance of positive events over
negative events compared to unhappy people. Seidlitz and Diener (1993) found this individual difference
was stable across samples, and the mechanisms behind the effect stemmed from differences in experience
and interpretation of events. Happy people simply experience more positive events than unhappy people in
general, and happy people interpret the same events as more positive than unhappy people. The belief that
happy people recall more positive events because they are in a happy mood at the time of recall was not
supported. There was also little evidence for the notion that happy people rehearse positive information
more, thereby strengthening their retrieval of happy events.
From a practical standpoint, memory measures have a lot to offer researchers with little cost.
Because they are an indirect indicator of SWB, they are not susceptible to social desirability artifacts the
way asking someone how happy they are can be. Memory measures can also be implemented easily,
cheaply, and quickly. To avoid priming effects, however, researchers should place memory tasks before
other items that may influence accessibility of positive or negative information. Relative to other types of
SWB measures, memory measures are underused in the literature, but the evidence shows they may be a
good alternative.
Cognitive Accessibility
Two studies suggest that people with higher SWB organize positive emotions differently from their
less happy counterparts, and this may point the way toward innovations in measurement. Robinson and
Kirkeby (2005) devised a method of measuring cognitive organization based on a reaction-time paradigm.
In their study, people with high life satisfaction were faster to report their positive emotions when the
question followed another question about positive emotion. For example, they were faster to report how
much joy they experience in general if this question followed a question about how much excitement they
experience in general. By contrast, when a question about negative emotion was followed by a question
about positive emotion, happy people were relatively slower to respond (e.g., how much anxiety do you
experience in general, followed by how much happiness do you experience in general). The decreased
reaction times suggest that positive emotions are organized in a tighter associative network for happy
people.
In an independent set of studies, Koo and Oishi (2009) adapted the classic Deese-RoedigerMcDermott
“false memory” paradigm to examine how people organize happiness-related concepts. For
example, participants learned several word lists, one of which included words related to happiness (e.g.,
excited, joy, smile). Importantly, each list omitted a critical word that was associated with the content of
the rest of the words. In the case of the happiness-related list, the word happiness (known as the ‘critical
lure’) was intentionally omitted so participants would not study it. Compared to unhappy people, happy
people falsely recalled “happiness” as being part of the studied word list. In other words, they were more
susceptible to having false memories but only for a category related to positive emotions. They were no
more likely to have false memories for other categories.
These two studies demonstrate that activation of happiness-related concepts may automatically lead
to activation of other parts of an associative network in happy individuals. Although no studies have used
cognitive accessibility or the false memory paradigm to capture stable individual differences in SWB, these
two studies show how they can be useful.
Informant Reports
Most theories of SWB hold that the individual is the best judge of his or her own happiness.
Nevertheless, can other people be a valuable source of information about a person’s happiness? Most
studies show modest to moderate correlations among self-reports and informant reports of SWB. For
instance, Zou, Schimmack, and Gere (2013) compared students’ self-reports of SWB with parents’ reports
of the student’s SWB and found convergent correlations of .30 to .36. In a meta-analysis, Schneider and
Schimmack (2010) found an overall correlation of .42 among self and informant reports of life satisfaction.
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Similarly, Koydemir and Schütz (2012) also found moderate convergence (rs .42 to .46) among informant
and self-ratings of life satisfaction. The highest convergence (in the .5s) was from Sandvik et al. (1993)
whose participants had a minimum of 7 informants each, including at least one parent and one friend.
Sandvik et al. (1993) noted that more informants and more items increase the convergence of self and
informant reports.
Informant reports have even been used to study the well-being of primates (Robinson et al., 2016;
Weiss, King, & Perkins, 2006). Of course, primates cannot supply self- report ratings to compare with the
informant reports. However, primate studies of SWB demonstrate the psychometric reliability of observer
measures. Weiss et al. (2006) reported an intraclass correlation (equivalent to Cronbach’s alpha) of .83 for
chimpanzee SWB when at least 3 raters provided judgments about the animal.
Importantly, however, the degree to which SWB is visible may vary by person and culture making
informant reports a better indicator for some than others. Saeki, Oishi, Maeno, and Gilbert (2014)
examined the convergence of self and informant reports of SWB and personality in Japanese and American
samples. While self and informant reports converged in general, the convergence was lower among
Japanese samples than among American samples. Self and informant reports of life satisfaction also had
lower convergence than traits such as extraversion. Their findings highlight the unobservable nature of
SWB, which appears to be less visible than say extraversion, and which may be more or less visible
depending on one’s culture.
Implicit Measures
The implicit association test (IAT) was first developed by Anthony Greenwald and colleagues
(1998) to measure implicit or unconscious racial bias. The IAT uses reaction times to measure the strength
of positive and negative associations towards a particular category, such as African Americans, the elderly,
women, obese people, the self, or even one’s own life. The Implicit Life Satisfaction (ILS: Kim, 2004)
measure adapts the original IAT framework by pairing “my life” with the evaluative categories of “good”
versus “bad” to measure an individual’s automatic evaluation of his or her life. Whereas self-reports of life
satisfaction often invite socially desirable responses, implicit measures of SWB can circumvent this
problem.
Kim (2004) reported that the ILS showed reasonable internal consistency ( rs ranging in the .70s and
.80s) and modest test-retest correlations (r = .41). Implicit life satisfaction did not correlate with selfreported
life satisfaction. In general, many of the IAT variants have low test-retest correlations, especially
in comparison to their explicit counterparts. In addition, within the IAT paradigm, implicit measures are
not necessarily expected to correlate with explicit measures as they are independent processes.
Interestingly, individuals who recently escaped North Korea had higher levels of explicit life
satisfaction compared to South Koreans or resettled North Korean defectors (Jang & Kim, 2011). The high
explicit life satisfaction was attributed to the recent dramatic and positive changes in defectors’ living
conditions. However, both recent and resettled North Korean defectors showed similar low levels of
implicit life satisfaction, which the authors attributed to chronic negative living conditions. Although
results from this unique study are consistent with theories of SWB and IAT research, more studies are
needed to confirm the validity of the ILS.
As to whether respondents can fake responses on the ILS, Kim (2004) found that respondents could
suppress their implicit life satisfaction scores when instructed to do so by slowing down their responses.
However, respondents could not enhance their responses to achieve higher life satisfaction scores by
responding faster. Thus, while the ILS may not be susceptible to socially desirable responding, it is not
entirely immune from conscious control.
Big Data
One of the most exciting areas to provide new insight and ways of measuring SWB is through big
data, particularly big data from social networking sites such as Facebook and Twitter or search engines
such as Google. Big data have been described as having high “volume, velocity, and variety,” (Laney,
2001) making them rich sources of information about human behavior. Information can be obtained
unobtrusively on millions of users, enabling social scientists to overcome methodological problems such as
under-powered designs, non-representative sampling, participant selection and fatigue, etc. This sounds
like a social scientist’s dream, but it may be worth taking a closer look at the validity of such measures. To
date, a handful of studies have examined the validity of Facebook status updates or Twitter tweets as
sources of information about a person’s SWB.
Facebook
Wang, Kosinski, Stillwell, and Rust (2014) correlated Facebook Gross National Happiness scores
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with daily life satisfaction scores from Facebook users in 2009 and found few significant correlations. The
authors concluded that Facebook status updates were not a valid way of measuring well-being or mood.
However, the daily FBGNH ratings were not necessarily derived from the same Facebook users who
provided the life satisfaction ratings, which may explain why Wang et al.’s results were inconsistent with
data reported by Facebook scientist Adam Kramer (2010).
Kramer (2010) also compared the SWLS with the FGNH in a group of over 1,000 of the same
respondents. According to Kramer (2010), life satisfaction correlated 0.17 with positivity in status
updates. Considering the sample size, the magnitude of the correlation was surprisingly weak. Lending to
its face validity, however, FGNH overall showed an increase during holidays and dips during national
tragedies. Also, consistent with traditional studies of SWB (Larsen & Kasimatis, 1990), FBGNH showed a
cyclical day-of-the-week effect where mood is highest on Fridays and lowest on Mondays.
Perhaps one explanation for the weak correlations between social media posts and life satisfaction
is that social media biases users to post positive content. Liu, Tov, Kosinski, Stillwell, and Qiu (2015)
postulated that self-presentation norms increase people’s desire to post positive status updates, rendering
positive updates less indicative of a person’s true SWB. However, negative emotions are more ‘honest’
reflections of SWB because they are not subject to self-presentational concerns. Indeed, they found that
negative, but not positive, emotion in Facebook status updates were related to life satisfaction. In addition,
only status updates from the past 9 months or earlier were related to life satisfaction, a finding which
corroborates Suh, Diener, and Fujita (1996) who found that only recent events contribute to SWB.
Twitter
Yang and Srinivasan (2016) directly sampled a subset of Twitter users who tweeted life satisfaction
content and completed the SWLS. People who made more life satisfaction tweets had higher life
satisfaction scores than those who tweeted dissatisfaction (e.g., “I hate my life”). High life satisfaction also
related to tweeting more positive and fewer negative words overall, and using fewer first-person singular
pronouns. Overall, the number of life satisfaction tweets was low compared to the total number of tweets
(only .13%). This is not surprising given that researchers have to rely on the spontaneous mention of life
satisfaction in tweets, which may make for unnatural language in the Twitter world. This may explain why
there are more Twitter studies using affect instead of life satisfaction, although life satisfaction and affect
tweets showed discriminant validity. Importantly, researchers need to select their words for searches
carefully when trying to examine SWB from tweets.
Yang and Srinivasan’s study (2016) also revealed that Twittered life satisfaction did not fluctuate
with events over two-year time frame, consistent with the stability of traditional life satisfaction measures.
Replicating the findings that religiosity contributes to SWB, Twitter users with high life satisfaction also
posted more about religion than unhappy ones. Like Kramer’s study, these findings indicate good face
validity of tweets as a source of information about SWB. Unfortunately, Yang and Srinivasan (2016) only
had a response rate of .46% in their study. Responders might conceivably be more consistent overall than
non-responders. In any event, there appears to be promising evidence that Twitter can be used to gather
meaningful data about life satisfaction.
Using a different approach, Schwartz et al. (2013) examined Tweets from over 1,000 U.S. counties
with at least 30,000 Tweets per county. Their data spanned a period of 14 months and compared the
Twitter data to surveys of life satisfaction from people in the same counties. Like Wang et al. (2014), the
Twitter users were not necessarily the same individuals who provided the life satisfaction data.
Nevertheless, the two sources were correlated, and Twitter word use predicted county level life satisfaction
above and beyond demographic variables such as median age and income. Moreover, topics that were
most strongly associated with life satisfaction—for example, physical activity, social engagement, and
prosocial activity—were the very ones that have consistently been found to be related to well-being using
more traditional data sources.
In addition to Facebook and Twitter, other platforms such as Instagram have potential as well
because the information posted by individuals are publicly available. Given the usefulness of smiling in
photographs (e.g., Seder & Oishi, 2012), researchers could easily gather smiling data from Instagram as a
measure of the user’s SWB. With improvements in machine learning technology, the extraction of
psychological information will become easier and easier, eventually removing the need for human coders
entirely. Some commercially available software already exists (e.g., Noldus). To give one example of
what can be done, Redi, Quercia, Graham, and Gosling (2015) identified the ambience of cafes using
profile pictures of the cafes’ customers. For example, a hipster café might attract more customers who
wear glasses. Cleverly, the researchers used machine learning to teach computers to extract visual
information from profile pictures that had previously been found to correlate with ambience. Other sources
of big data, even those that are outside the realm of social media or those that have yet to be invented, may
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also prove to be useful to SWB science. The possibilities are endless and only constrained by our
imagination.
Google Searches
Whereas Kramer (2010) described the Facebook status update as a “self-descriptive text modality,
optimized and designed to elicit updates about the self,” and the “strongest signal of the emotional wellbeing
of the poster,” Ruths and Pfeffer (2014) cautioned that social media distorts human behavior. Not
only are the platforms themselves explicitly designed to shape human behavior (e.g., social network sites
aim to increase homophily through the recommendation of friends and sites), but there is a heightened
sense of self-presentation in social media (e.g., Liu et al., 2015), which may lead to the data not accurately
reflecting people’s true thoughts and feelings. By contrast, when people conduct internet searches, they do
so in privacy, making the study of internet searches one of the rare glimpses into private behaviors that is
available to scientists. Furthermore, unlike self-reports internet searches do not require introspection.
Thus, by examining what people in a population are searching for on the internet, researchers may be able
to estimate the well-being of that population.
Ford, Jebb, Tay, and Diener (2017) were the first to examined Google search activity and its
relation to well-being. Indeed, regions with greater frequency of searches containing words such as
depression, afraid, or anxiety had lower self-reported affect and more incidences of coronary heart disease
and depression. This pattern emerged at both state and metropolis levels. Although internet searches are a
powerful and inexpensive way of capturing people’s deepest concerns, there are limitations on the capacity
of internet searches to represent SWB. Mainly, people whose search queries include words such as
depression are likely to be experiencing negative emotions and thus seeking ways to resolve them. By
contrast, someone with high life satisfaction is unlikely to Google positive emotion terms. Ford et al.’s
study, in fact, was limited to internet searches of negative terms.
Overall, big data have enormous potential for understanding SWB, and they are constantly being
generated with no incentives at all from scientists. Compared to surveys or ESM which can be very costly,
social media data and internet searches are potentially economical sources of information. Despite these
advantages, there are limitations. For instance, social media users will tend to be younger and more tech
savvy than the general population. In addition, Twitter only releases a small sample of tweets to the public.
Twitter also limits the number of words users can post. However, these limitations are small in comparison
to the enormous information big data can provide.
Skepticism and Caution
These new forms of data are already raising some novel and potentially serious ethical concerns for
scientists. Privacy, consent, and data ownership, are just a few of the known challenges, and these too are
constantly evolving. With just a bit of reflection on the amount of passive data generated by modern
individuals, it is easy to sense the “creep factor” of big data (Gumbus & Grodzinsky, 2016). Unlike in a
traditional survey design or laboratory experiment, when people generate social media content (such as
posts and likes), do they even realize they are providing data? Chances are not. Often no explicit consent
is obtained from those who provide data. In the case of internet searches, there is no way for potential
subjects to opt out, short of not searching for the information in the first place. Even if it is possible to
obtain consent from users for social media content, participants may not grasp the details of the research at
the time of consent because in some cases, the data precede the research questions. Even when data are
anonymized, people may be uncomfortable with their social media data being used for research purposes.
Scholars have warned of inequities in accessibility to big data and proprietary algorithms for public data
that may over represent or under represent some populations or behaviors (Ruths & Pfeffer, 2014) and
potentially widen disparities between groups (Gumbus & Grodzinsky, 2016). Not to mention, if big data
fall into the wrong hands, there is enormous potential for misuse. Even if there were a way to solve these
problems, there may remain broader implications of conducting research in a big data world. For instance,
does the datafication of our lives erode free will? For this reason and others, psychologists should forge a
dialogue with ethicists, social media experts, and ordinary users to understand how best to use big data,
especially as social norms evolve and new forms of data arise.
Conclusion
Thanks to advancements in technology researchers now have at their disposal many new methods
for measuring SWB. While neurological approaches to assessing SWB remain far from useful or practical
at present, other techniques such as big data and momentary assessments are growing more economical and
accessible each day. These non-self-report methods can, at times, reduce the social desirability and
introspection inherent in self-reports of SWB. However, it is important to consider that all the measures
offer different vantage points of the underlying phenomenon, and no single method is a direct measure of
76
SWB. A variety of methods allows researchers to triangulate on a picture of SWB, but they should not
entirely replace self-reports of SWB. After all, the construct is subjective well-being.
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2018 Ed Diener. Copyright Creative Commons: Attribution, noncommercial, no
derivatives
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What do Subjective Well-Being Judgments Mean? Sources and
Distinctions, Processes and Mechanisms
By Michael D. Robinson & Robert J. Klein, North Dakota State University
Citation
Robinson, M. D., & Klein, R. J. (2018). What do subjective well-being judgments mean? Sources and
distinctions, processes and mechanisms. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of wellbeing.
Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
How do people decide how happy they are? In principle, a number of models are possible and the current
chapter highlights three of them. People could subdivide their life into various domains, consider their
progress in these domains, and then integrate the results of this bottom-up activity. Alternatively, people
could omit such a systematic process and simply base their judgments on whatever information is currently
accessible. Finally, it is possible that people already know their happiness levels, in which case they could
directly retrieve such evaluations. The plausibility of these models is examined with respect to issues of
stability, change, and context in well-being judgment. People have fairly stable ideas about how happy they
are and well-being judgments seem somewhat resistant to priming. Nonetheless, well-being sometimes
changes in response to life events. Accordingly, some combination of judgment models might be necessary
to fully account for current findings.
Keywords: Happiness, Judgment, Heuristic, Systematic, Life Events
For most people, happiness is not just a pleasant occurrence. Rather, it is a guiding principle in their
lives. People want to be happy more than they want more specific things like love, wealth, or health and
happiness is the presumed goal of many of their other pursuits (Kim-Prieto, Diener, Tamir, Scollon, &
Diener, 2005). This emphasis on happiness is not misplaced in that there are many benefits to being happy,
including in the realms of love and work as well as physical functioning (De Neve, Diener, Tay, & Xuereb,
2013; Lyubomirsky, King, & Diener, 2005a). For example, happy people attract marital interest and they
are less likely to get divorced (Marks & Fleming, 1999). Even beyond the individual level, happiness can be
used to track societal changes (Frey & Stutzer, 2010) and to compare entire societies (Diener & Seligman,
2004).
Given the importance of happiness to individuals as well as societies, it is important to understand its
basis. A first point worth making here is that happiness is a subjective phenomenon. People make
judgments of happiness and we consider them happy to the extent that they report themselves to be happy,
potentially independent of the circumstances of their lives (Myers & Diener, 1995). A second point worth
making is that happiness, in the form of subjective well-being (SWB), encompasses both emotional
experiences and cognitive evaluations (Diener, 1984; Tay, Chan, & Diener, 2014). People are happy when
they have more frequent experiences of positive emotion, less frequent experiences of negative emotion,
and when they evaluate their lives more favorably (Myers & Diener, 1995). The present chapter is primarily
concerned with life evaluations rather than emotional experiences.
People have been asked to evaluate their lives in a number of ways. They have been asked to
choose rungs of a ladder or faces to represent how happy they are (Andrews & Withey, 1976). Another
commonly used happiness item asks people whether they are very happy, pretty happy, or not too happy
“these days” (Bradburn, 1969). Alternatively, people might be asked how satisfied they are with their lives,
“all things considered” (Wagner, Frick, & Schupp, 2007). Such single-item measures are used both
because they are convenient and because they seem to capture the construct in an efficient manner (Lucas
& Donnellan, 2011). In addition, though, a number of multi-item measures of life satisfaction exist. One
asks people to make several general life satisfaction ratings before rating satisfaction with more particular
domains like health and standard of living (Weinberg, Seton, & Cameron, in press). Another asks people
whether they agree or disagree with statements such as “I am satisfied with my life” (Diener, Emmons,
Larsen, & Griffin, 1985). These different measures tend to correlate fairly highly with each other (Kobau,
Sniezek, Zack, Lucas, & Burns, 2010), and constitute the primary data of interest.
In principle, people could engage in a number of different strategies in answering these questions.
Campbell, Converse, and Rodgers (1976) posited a somewhat complex mental calculus. When deciding
one’s overall level of happiness, one could enumerate the various domains of life, consider one’s progress
in those domains, compare that progress to multiple standards, and compute an overall well-being score
that averages across these efforts. Somewhat similarly, Michalos (1985) suggested that people make an
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extensive set of comparisons (e.g., between what one has and what one expects to have in 5 years, between
what one has and what one expected to have 3 years ago) and then integrate the results of these
comparisons before deciding what their well-being is. To us, these perspectives implicate a level of
thoughtfulness and extension that is unlikely to characterize the typical effort to determine one’s wellbeing.
That is, these perspectives seem inconsistent with modern views of decision making (Gigerenzer,
2015) and social cognition (Fiske & Taylor, 1991), which hold that people aim for efficiency when making
their decisions and judgments.
At another extreme, some social psychologists emphasize the malleability of attitude judgments in
general (Erber, Hodges, & Wilson, 1995) and life satisfaction judgments in particular (Deaton & Stone,
2016; Schwarz & Strack, 1999). On the basis of priming studies (Bargh & Chartrand, 1999), some of which
are reviewed below, the suggestion seems to be that people do not essentially know their levels of life
satisfaction. Rather, they construct such judgments on the basis of whatever information happens to be
accessible in the moment of judgment (Schwarz & Strack, 1999). Both survey researchers and well-being
researchers should be interested in these sorts of influences. However, the possible presence of priming
effects does not preclude the additional presence of more stable sources of information in well-being
judgment. The fact is that well-being judgments are fairly stable over time (Eid & Diener, 2004) and
priming perspectives on judgment seem insufficient in accounting for such sources of stability (Anusic &
Schimmack, 2016). People know a fair amount about their lives and are likely to retrieve this information
when deciding how happy they are (Eid & Diener, 2004).
Indeed, it is reasonable to propose that people think about their lives a lot of the time and they think
about happiness in this connection (Myers, 1992). This renders it possible that asking people about their
happiness is asking them to answer questions that they have already answered, for an internal audience. If
so, people may not need to construct an answer when they are asked about their life satisfaction. Rather,
they may be able to recall a pertinent answer more-or-less directly from memory. This perspective overlaps
with the accessibility model of attitude strength, which posits that previous experience evaluating an
attitude object (in this case, one’s life) changes the evaluation process in favor of direct attitude retrieval
(Fazio, 1995). For example, asking the novice coffee drinker how much they like coffee could lead to a
complex mental calculus. Asking the experienced coffee-drinker the same question, however, may lead to
the answer “a lot” without a great deal of deliberation. It is feasible that some people, if not many, think of
their lives in a way akin to an experienced coffee drinker.
To summarize, there are at least three perspectives on life satisfaction judgment that deserve
attention (see Table 1). Under some circumstances, people will think about their standing and standards in
various life domains before giving a life satisfaction judgment (Campbell et al., 1976). However, people are
efficient thinkers and may curtail some of this activity in favor of quicker, more heuristic ways of
answering the question (Gigerenzer, 2015). Under some circumstances, primed thoughts and feelings could
influence the life evaluation process (Schwarz & Strack, 1999). However, these contextual influences are
not likely to be strong because people know a great deal about their lives and are likely to consult this
information independent of priming influences (Schimmack & Oishi, 2005). Finally, we have suggested
that people who have thought about their lives extensively may be able to evaluate them somewhat directly,
thereby omitting a lengthy deliberation process at the time of judgment. The last perspective should assume
that life satisfaction judgments are stable, much as accessible attitudes are (Fazio, 1995). We will revisit
these three perspectives, in one way or another, throughout the course of the review.
Table 1
Three Models of Well-Being Judgment and Their Characteristics
Integrative Constructivist Direct Retrieval
Relevant Citation Campbell, Converse, &
Rodgers (1976)
Schwarz & Strack (1999) Fazio (1995)
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Description When making well-being
judgments, people
enumerate their life
domains, review their
progress in each life
domain, compare that
progress to standards, and
average across these
computations.
People do not know how
happy they are “in
general”. When they are
asked such questions, they
use whatever information is
currently accessible and are
therefore vulnerable to
temporary and irrelevant
priming factors.
People have thought about
how happy they are
previously. When making
well-being judgments, they
directly retrieve these prestored
evaluations.
Processing Mode Systematic Heuristic Heuristic
Retrieval Direction Bottom-Up Bottom-Up Top-Down
Strength 1 Can explain why life events
matter
Highlights potential
influences due to mood and
communication rules
Can explain the stability of
well-being judgments
Strength 2 Can account for well-being
change
Can account for contextual
influences
Is consistent with cognitive
miser perspectives
Weakness Presumes too much mental
calculus
Overemphasizes the
malleability of well-being
judgments
Does not specify the basis
of happiness levels
Do Life Circumstances Matter?
It is intuitive to think that life satisfaction judgments should be about life. That is, they should
reflect life’s circumstances and the situation in which one finds oneself. Demographic factors like sex,
race, and age should matter and social and economic factors like one’s income should matter as well.
Although there clearly are relationships between social-demographic factors and happiness, these
relationships can be surprisingly small (Diener, Suh, Lucas, & Smith, 1999). In an older but comprehensive
effort, Andrews and Withey (1976) concluded that demographic and life circumstance factors collectively
explained less than 10% of the variance in happiness judgments. Later, the figure rose to 15% or so
(Argyle, 1999), but the point remains that factors like age, race, income, and socioeconomic status explain
only a relatively small portion of variance in well-being judgments (Diener et al., 1999; Lykken &
Tellegen, 1996).
The relationship between age and well-being is an illustrative example. As we age, we lose
mobility, encounter disease more often, and lose fluid intelligence as well (Rook, Charles, & Heckhausen,
2011). Furthermore, people in America (including older people) hold a pessimistic view of aging
(Hummert, Garstka, Shaner, & Strahm, 1994). One could therefore expect some decreases in well-being
with age. Instead, the relationship between age and well-being seems puzzling. One contention is that both
positive and negative affect decrease with age (Diener, Sandvik, & Larsen, 1985). However, another
contention is that well-being increases with age (Carstensen et al., 2011), perhaps excepting a late-life
decline (Gerstorf et al., 2008). A third perspective, though, contends that there are curvilinear relations
between age and well-being, with the lowest levels in middle age (Blanchflower & Oswald, 2008). It is
difficult to make sense of these divergent ideas and the truth of the matter may be that aging effects are
either subtle or sample-dependent. Thus, the most general conclusion could be that age does not impact
well-being as much as one might think or even much at all (Lykken & Tellegen, 1996; Myers & Diener,
1995).
Further, there are data to suggest that even somewhat radical changes in life circumstances can have
surprisingly small effects on long-term well-being (Loewenstein & Schkade, 1999). Along these lines,
Gilbert and colleagues have conducted several studies showing that people quickly habituate to seemingly
terrible events such as tenure denial (Gilbert, Pinel, Wilson, Blumberg, & Wheatley, 1998). Under many
circumstances, they also seem to adapt to the positive features of their lives as well (Sheldon &
Lyubomirsky, 2007). In a famous study of this type, Brickman, Coates, and Janoff-Bulman (1978)
compared the happiness levels of lottery winners, controls, and people who had encountered fairly serious
spinal cord injuries. The authors concluded that the lottery winners were not happier than the control group
and the paralyzed accident victims had rebounded such that their happiness levels were surprisingly high.
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When combined with other life event/well-being studies (e.g., Headey & Wearing, 1989; Robinson, 2000;
Suh, Diener, & Fujita, 1996), the conclusion seems to be that happiness levels can often be insensitive to
bottom-up, life circumstance factors (Lykken & Tellegen, 1996). Such considerations led to a different,
top-down view of well-being judgment (Diener, 1984).
Are There Top-Down Influences?
Top-down influences are sources of belief, affect, or disposition that stabilize well-being judgments,
potentially in a way that is independent of objective life circumstances (Diener, 1984; Watson, 2000). There
are several basic properties of well-being judgment that seem consistent with top-down influences. First, the
average person does not have neutral levels of life satisfaction. Rather, the average person is more satisfied
than dissatisfied with his or her life and this is true across many measurement instruments and countries
(Cummins, 2003). The consistency of these findings suggests that there is a sort of default that favors nonneutral
levels of happiness for most people under most circumstances (Diener, Lucas, & Scollon, 2006).
Second, life satisfaction is stable over time (Eid & Diener, 2004) and consistent across situations (Watson,
2000). That is, people who are more satisfied with their lives tend to remain more satisfied with their lives
across time and circumstance (Watson, 2000).
Thus, there seem to be dispositional (stable, but person-varying) top-down influences on life
satisfaction judgments that warrant serious attention (Diener et al., 1999). These top-down influences could
reasonably be due to one’s personality traits. For example, Costa and McCrae (1980) maintain that
extraversion and neuroticism, two personality traits linked to affect, could determine one’s “set point” or
stable level of well-being. In support of these ideas, extraversion and neuroticism are good predictors of
well-being (Watson, 2000) and these personality traits tend to be more stable than life satisfaction or
emotion (Anusic & Schimmack, 2016). Alternatively, top-down influences could follow from self-esteem
given that a number of theories of well-being implicate processes concerning the self (e.g., Michalos, 1985)
and self-esteem is also a good predictor of well-being (Diener & Diener, 1995). These perspectives can be
combined when it is recognized that extraversion and neuroticism are loaded with self-evaluative variance
and this self-evaluative variance is highly correlated with self-esteem (Anusic, Schimmack, Pinkus, &
Lockwood, 2009).
The link to self-evaluative processes seems appealing in another way. There are pronounced cultural
differences in well-being (Diener, Oishi, & Lucas, 2003) and there are also pronounced cultural differences
in self-evaluation (Heine, Lehman, Markus, & Kitayama, 1999). In particular, people from Asian cultures
like China, Japan, and Korea tend to report lower levels of life satisfaction (Diener et al., 2003) and these
cultures also favor greater modesty in self-presentation (Heine et al., 1999). Processes concerning the self
(Markus & Kitayama, 1991) and self-evaluative tendencies (Suh, 2000) could therefore constitute a sort of
top-down influence on well-being judgments that diverges across cultures. Top-down influences should be
particularly apparent for global or retrospective reports of well-being (Tay et al., 2014) and there is some
evidence to suggest that these are the sorts of well-being judgments that display the greatest variations
across culture (Oishi, 2002; Saeki, Oishi, Lee, & Maeno, 2014). This model will not be sufficient in
accounting for all cultural differences in well-being, many of which can be ascribed to objective features of
the culture (Diener, Diener, & Diener, 1995), but it could account for some of them (Diener, Napa Scollon,
Oishi, Dzokoto, & Suh, 2000).
We are generally convinced that there are top-down influences on well-being judgment. However,
the framework is not entirely satisfactory. To ascribe well-being to personality traits, or to self-esteem, does
not explain where personality traits or self-esteem come from. Moreover, self-evaluative processes,
including those linked to personality or culture, may constitute some uncertain mix of style and substance
(Paulhus & John, 1998). This renders it possible that at least a portion of the link between personality and
well-being, or between culture and well-being, could be due to variations in self-presentation rather than
more substantive factors like temperament (Davies, Connelly, Ones, & Birklund, 2015). Finally, both
personality and well-being change over time (Anusic & Schimmack, 2016) and some consideration of
bottom-up factors seems necessary to account for these changes (Headey, Muffels, & Wagner, 2010). In the
context of top-down factors, we therefore revisit the question of whether life circumstances matter, this time
while considering the “set point” idea of well-being.
Are There “Set Points” for Well-Being?
In the well-being literature, the set point is a sort of happiness default that one might return to in the
absence of unusual events. For the vast majority of people, the set point seems to favor happiness over
unhappiness (Diener, Kanazawa, Suh, & Oishi, 2015). Consistent with this idea, Cummins (2003)
converted a number of happiness and life satisfaction measures to a 0 to 100 scale. The average life
satisfaction score was about 75, or roughly ¾ of the happiness/satisfaction maximum. The person’s set
point could vary by culture, in that cultures differ in their average ratings of happiness (by as much as 14 of
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100 points in Cummins, 2003). Of more pertinence, one’s set point would vary by personality traits such as
extraversion and neuroticism (Costa & McCrae, 1980). Events that are more pleasant (unpleasant) than
typical for one’s personality would temporarily shift happiness in a positive (negative) direction, but
happiness would return to one’s dispositional level thereafter (Headey & Wearing, 1989).
The set point idea seems somewhat necessary, both to cover the polarized nature of normative
happiness ratings (Cummins, 2003) and to cover marked individual differences (Watson, 2000) as well as
genetic influences (Lykken & Tellegen, 1996). Nonetheless, we may never know what a person’s set point
is because they are always interacting with the environment and therefore always in flux to a certain extent
(Headey & Wearing, 1989; Robinson, 2000). Further, it should be recognized that life satisfaction changes
over longer periods of time, though in different directions for different people (Anusic & Schimmack,
2016). This probably means that set points also slowly change, either due to maturation processes or
lifestyle choices that create new personal trajectories. Along these lines, Headey et al. (2010) estimate that a
sizeable minority of people (25-30%) had different apparent set points in the 1980s than they did in the
2000s.
To gain a more detailed perspective on set points and adaptation levels, recent research has
revisited the idea that life events typically fail to influence our happiness levels for any appreciable length
of time (McCrae & Costa, 1994). In contrast with classic research in this area (e.g., Brickman et al., 1978),
this more recent research has typically used longitudinal designs rather than quasi-experiments and has
sometimes employed sophisticated methods to deal with maturational trends (Anusic, Yap, & Lucas, 2014).
In one study of this type, Clark and colleagues (Clark, Diener, Georgellis, & Lucas, 2008) found that
people adapted to marriage and widowhood within about 3 years, but unemployment appeared to
undermine well-being for a longer period of time. Using a different sample and somewhat different
methods, Anusic et al. (2014) reported adaptation for marriage and childbirth, but a seeming permanent
change due to disability. Summarizing a number of studies of this type, Lucas (2007) suggests that people
adapt to changes in marital and family status, but may not be able to fully recover from periods of
unemployment or disability.
Thus, there could be an asymmetry with respect to positive and negative events. Positive events like
marriage or promotion (or winning the lottery: Brickman et al., 1978) can influence our happiness for a
period of time, but that influence will probably dissipate. On the other hand, some negative events – such
as unemployment or disability – can have a lasting impact (Lucas, 2007), possibly because they
permanently alter our capacity to pursue our goals. Cummins (2010) makes a related point when he
suggests that especially low levels of life satisfaction reflect homeostatic defeat rather than normal
fluctuations about one’s set point. Even within normal ranges, though, people fluctuate in their happiness
levels from time to time (Eid & Diener, 2004). These fluctuations suggest that it may be more accurate to
characterize the set point as a “set range” – a range of possible well-being scores for the individual rather
than one specific level (Sheldon & Lyubormirsky, 2007; Watson, 2000). Provided that one is not at the top
of this range, improvements in well-being may be possible (Sheldon & Lucas, 2014; Watson, 2000).
However, improving one’s well-being appears to be difficult. Seeking pleasure can backfire
(Schooler, Ariely, & Loewenstein, 2003) and mere behavioral change does not seem sufficient (Sheldon &
Lyubomirsky, 2007). Rather, one must engage in the right activities for the right reasons while varying
their form and timing so that hedonic adaptation is forestalled (Lyubomirsky, Sheldon, & Schkade, 2005b).
Also, positive events and activities, per se, do not seem to be sufficient. Rather, the positive events and
activities must contain elements of novelty and they must implicate core self-motives such as autonomy,
competence, and relatedness (Sheldon & Elliot, 1999). These perspectives suggest that we have the
opportunity to intentionally increase our well-being, but considerable skill may be necessary in doing so
(Lyubomirsky et al., 2005b; Sheldon & Lyubomirsky, 2007).
To summarize, well-being is conservative, such that it remains remarkably stable over time even as
our lives change (Anusic & Schimmack, 2016). Much of this stability seems to be due to global beliefs
about ourselves and to personality factors, both of which compel us to give similar answers about our
happiness over time (Lykken & Tellegen, 1996). Alternatively, people may develop fairly fixed ideas about
their happiness that they can retrieve whenever they are asked (Robinson & Oishi, 2006). In either case,
there are top-down influences that keep happiness judgments within acceptable, accustomed ranges
(Cummins, 2003). Yet, such fixed ideas about happiness are not entirely insensitive to recent life events
(Robinson, 2000) or to significant life changes (Lucas, 2007). Altogether, then, we suggest that there are
both top-down (dispositional) and bottom-up (event-based) influences on well-being judgment, though the
top-down influences tend to dominate (Anusic & Schimmack, 2016; Eid & Diener, 2004).
Are Life Satisfaction Judgments Plagued by Context Effects?
Experimental research conducted in the 1980s suggested that our judgments of life satisfaction can
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be biased by somewhat irrelevant and temporary factors such as finding a dime in the copy machine, the
weather, the outcome of a recent soccer match, or the order in which life satisfaction questions are
administered (Schwarz & Clore, 1983; Schwarz, Strack, Kommer, & Wagner, 1987; Strack, Martin, &
Schwarz, 1988; for a review, see Schwarz & Strack, 1999). Some of this research gave rise to a very
influential theory of mood (Schwarz & Clore, 1996) and the Strack et al. (1988) paper can be highlighted
for its fascinating analysis of the role of communication norms (such as to avoid redundancy) in the
potential inferences that people make when answering self-report questions (Schwarz, 1999). Yet, the
research adopted a puzzling view of well-being. The contention, more or less, was that people rarely
evaluate their lives as a whole and are therefore susceptible to a range of biases when making life
satisfaction judgments. This radical constructivist view does not seem consistent with the highly stable
nature of well-being (Pavot & Diener, 1993) or with the top-down factors that seem endemic to well-being
judgments (Cummins, 2003; Diener et al., 1999; Heller, Judge, & Watson, 2002).
The idea that people consult their affective states when deciding how happy they are (Schwarz &
Clore, 1983) has intuitive appeal. Moreover, this idea is clearly correct at some level. Personality traits like
extraversion and neuroticism predict happiness in part because they predict dispositional levels of positive
and negative affect (Costa & McCrae, 1980). Also, trait reports of affect are strong predictors of well-being,
even after controlling for personality traits and cognitive predictors (Blore, Stokes, Mellor, Firth, &
Cummins, 2011). Nevertheless, people can distinguish momentary affective states from their more general
tendencies to experience positive and negative affect (Watson, 2000) and they may discount the former
when making dispositional inferences (Lucas, Dyrenforth, & Diener, 2008). Consistent with these ideas,
Eid and Diener (2004) found that subjective well-being (SWB) was strongly trait-like over the period of 12
weeks and momentary mood states had small, largely inconsequential influences on SWB judgment (also
see Yap et al., in press). Similarly, Lucas and Lawless (2013) revisited the idea that transient weather
patterns can influence life satisfaction judgments (Schwarz & Clore, 1983). In a large-scale study, current
weather conditions did not predict life satisfaction judgments in any straightforward manner, and most
weather conditions did not predict them at all. Hence, life satisfaction biases due to current mood seem to
be slight (Lucas et al., 2008).
Turning to item-order effects, Strack et al. (1988) examined the correlation between dating
happiness and general happiness in three conditions. When the general happiness item was answered before
the dating happiness item, the correlation was r = .16, suggesting that people do not consider dating much
when rating their general happiness. When the dating happiness item preceded the general happiness item,
by contrast, the correlation rose to r = .55, such that participants may have based their ideas about their
happiness in general on primed information about their dating lives. In a third condition in which it was
made clear that there were two separate questions (one about dating and one about life in general), though,
the correlation dropped to r = .26 even when the dating item occurred first. These results indicate that it
may be possible to alter happiness judgments by priming more specific sources of information first (e.g.,
about dating), but that people may resist this influence when the two judgments seem different from each
other (also see Schwarz, Strack, & Mai, 1991).
In the domain of happiness judgments, it appears that priming effects can either take the form of
assimilation (increased use of primed information) or contrast (decreased use of primed information).
Moreover, it is often difficult to state, a priori, which sort of priming effect is more likely (Schwarz &
Strack, 1999). This has resulted in complicated findings. For example, Eiser and de Mey (1993) found
complex priming effects depending on whether positive or negative sources of information were first
recalled and whether the recalled information was vivid or not. The exact form of the results did not seem
expected. It is also not always obvious where priming effects end and communication effects begin or what
inferences people will make about the communication context (Tourangeau, Rasinski, & Bradburn, 1991).
Concerning the relationship between marital happiness and general happiness (Schwarz et al., 1991),
researchers have found assimilation effects (Smith, 1982), contrast effects (Schuman & Presser, 1981), or
no effects (Turner, 1984). Further, when priming effects are found, the results involving correlations and
means can differ. Thus, a wider reading of this literature suggests that item-order effects are confusingly
temperamental (Schuman & Presser, 1981; Tourangeau et al., 1991).
There are also reasons to wonder about the typical magnitude of item-order effects (Lucas et al.,
2008; Lucas, Oishi, & Diener, 2016). Theoretically, they can occur when (a) people do not know, ahead of
time, how happy they are, (b) the primed source of information is deemed relevant, and (c) the primed
source of information would not have been accessed in the absence of the priming manipulation
(Schimmack & Oishi, 2005). To the extent that people know how happy they are, or to the extent that they
would have retrieved the relevant information anyway, item-order effects would be considerably less likely
(Schimmack & Oishi, 2005). In speaking to this literature, Schimmack and Oishi (2005) conducted a metaanalysis
and several replication attempts. The meta-analysis revealed that item-order effects were
85
heterogeneous across 16 previous studies. Furthermore, several direct replication attempts failed to produce
significant findings and the authors concluded that item-order effects may typically be fairly small in effect
size. When these studies are considered in light of inconsistencies among previous studies (e.g., the
contrasting results of Smith, 1982, and Schuman & Presser, 1981), this seems a reasonable conclusion
(also see Weinberg et al., in press).
What Do People Think About When Making Well-Being Judgments?
Thus far, we have primarily examined how people make well-being judgments by examining
questions of process – stability, personality correlates, vulnerability to contextual influence, etc. However,
it might also be possible to ask people what they think about when making life satisfaction judgments.
Although the sources of knowledge mentioned might not overlap perfectly with those actually contributing
to their judgments (Nisbett & Wilson, 1977), this is a worthwhile type of data to consider.
A first point worth making is that people typically recall more positive than negative events from
their personal past (Seidlitz & Diener, 1993) and they also have more favorable than unfavorable thoughts
about their lives (Luhmann, Hawkley, & Cacioppo, 2014). This degree of positivity could follow from
factors like self-enhancement (Sedikides & Gregg, 2008) or it could follow from the fact that we typically
inhabit hospitable rather than hostile environments (Cacioppo, Gardner, & Berntson, 1997). In either case,
greater positivity in recalled events or in thoughts about our current life could partially explain why life
satisfaction tends to be polarized in a positive direction (Cummins, 2003).
With respect to time frames, Ross, Eyman, and Kishchuck (1986) found that people primarily
thought about their present lives when making life satisfaction judgments, suggesting that life satisfaction
judgments should display some sensitivity to recent life events (Robinson, 2000). Following a focus on the
present, people said they were focused on the future (Ross et al., 1986). This makes sense because wellbeing
is intimately related to our goals and goals are future-oriented entities (Sheldon & Lyubomirsky,
2007). Finally, people did not report thinking about the past as frequently when making life satisfaction
judgments (Ross et al., 1986).
The sorts of life domains that people report thinking about also make sense. Relationships are
important to well-being (Myers & Diener, 1995) and people report thinking about relationships (e.g., family
relationships, friendships) when making well-being judgments (Luhmann et al., 2014). They also report
thinking about their academic and career success and some mention their health (Luhmann et al., 2014). In
one study, for example, Schimmack, Diener, and Oishi (2002) asked people what they thought about while
making life satisfaction judgments and found that 33% mentioned family, 26% mentioned friends, 22.5%
mentioned romantic life, 20% mentioned academic life, and 12% mentioned health. Financial concerns and
social comparisons were not mentioned as frequently.
Schimmack and colleagues (2002) have reported additional intriguing evidence in favor of this
thought-listing method. What people report thinking about correlates highly (r = .67) with importance
ratings for the relevant source of information. This suggests that people tend to think about important
domains of their lives, rather than whatever happens to come to mind, when making life satisfaction
judgments (Schimmack & Oishi, 2005). Furthermore, people who report using a source of information
(“users”) display higher correlations between that source and general well-being than those who do not
(“non-users”). For example, Schimmack et al. (2002) reported that the correlation between family
satisfaction and life satisfaction was higher for people who reported thinking about family (r = .44) than for
people who did not mention this domain (r = .12).
There are clearly limitations to this method, though (Nisbett & Wilson, 1977). People do not
mention their personalities as a source of life satisfaction judgment despite the importance of personality
influences (Costa & McCrae, 1980). And they do not mention cultural norms, even though cultural norms
have been heavily implicated in life satisfaction judgment (Diener et al., 2003). Thus, people do not seem
aware of some of the important top-down influences that are guiding their judgments.
Some Distinctions in Well-Being Judgment
There are different ways of measuring well-being and some of these distinctions are important in
understanding what a given sort of judgment reflects. In that spirit, we review some useful distinctions,
particularly with respect to their ability to elucidate judgment processes. These distinctions can also be
useful, however, in thinking about personality and culture and in comparing different views of what
happiness should consist of.
Online Happiness versus Recalled Happiness. Online reports of happiness focus on current
emotional experiences and how they are influenced by factors such as social setting, events that have
recently happened, or time of day (Bolger, Davis, & Rafaeli, 2003). These emotions are typically in flux
and have a noticeably reactive character to them (Bolger et al., 2003; Conner, Tennen, Fleeson, & Barrett,
86
2009). They are also highly dependent on setting. Some settings and activities are more “fun” than others
and people tend to report greater happiness when they are engaged in leisure or socializing relative to work
or childcare (Kahneman, Krueger, Schkade, Schwarz, & Stone, 2004). In the short run, in fact, one could
be happier when unemployed than when not because unemployment can bring greater leisure (Knabe,
Rätzel, Schöb, & Weimann, 2010). In the long-run, by contrast, unemployment would tend to undermine
self-esteem and, perhaps because of this, life satisfaction (Clark et al., 2008).
Nonetheless, an advantage of online reports is that they are closely tied to both events and actual
experiences (Robinson & Clore, 2002a). This seems to render them, relative to retrospective or trait reports
of emotion, less prone to belief-driven top-down biases (Robinson & Clore, 2002a). For example, Oishi
(2002) observed that Asian/European American differences in happiness were greater for recall-based
measures than for online measures, and similar results have been found using Day Reconstruction methods
(Oishi, Whitchurch, Miao, Kurtz, & Park, 2009). One interpretation of this pattern of findings is that
Asians believe that they are less happy than European Americans and such beliefs differentially contribute
to retrospective and trait reports of happiness relative to online reports (Robinson & Clore, 2002a). If this is
true, one could actually study top-down factors in terms of the discrepancy between online reports of
happiness and retrospective reports.
Even so, online reports of happiness should not always be favored. They may focus too particularly
on the person’s ecological reactions to events, and on hedonic factors, relative to broader forms of wellbeing
such as meaning and purpose (Diener & Tay, 2014). Averaging a person’s happiness across moments
could therefore provide a somewhat misleading picture of a person’s global, more cognitive sense of life
satisfaction (Tay et al., 2014).
Domain Satisfaction versus Global Life Satisfaction. There are only 24 hours in a day and
people have limited capacities to achieve everything that they might wish to achieve (Baumeister,
Heatherton, & Tice, 1994). There can therefore be tradeoffs such that one succeeds in some life domains
(e.g., work) but not others (Heidemeier & Göritz, 2013). Despite these potential tradeoffs, there tend to be
positive correlations among life domains such that satisfaction in one life domain tends to predict
satisfaction in another (Campbell et al., 1976; Diener, 1984). These correlations can be small, though.
Along these lines, the correlation between marital satisfaction and job satisfaction may be as low as r = .16
(Heller, Watson, & Ilies, 2004). By averaging across a number of life domains, however, one can compute
a domain-derived life satisfaction measure that correlates highly with a more generic (domain-unspecified)
one (Campbell et al., 1976; Weinberg et al., in press).
Regardless, people consider different sources of knowledge when making domain satisfaction
ratings versus when rating their satisfaction with life in general. Developments within a particular domain
(e.g., a raise at work) are more likely to affect satisfaction with that domain (e.g., work) than satisfaction
with life in general, indicating the presence of bottom-up influences (Heller et al., 2004). Conversely, there
are top-down influences that matter more for global reports of well-being, even after controlling for
satisfaction with particular domains. Personality factors and dispositional positivity are among these
(Diener et al., 2000). Thus, one way to isolate dispositional positivity is to subtract domain-specific
satisfaction ratings from domain-general satisfaction ratings, with larger differences indicating greater
positivity (Diener et al., 2000).
Relatedly, happy people self-enhance. That is, they view their lives more positively than seems to
be justified (Wojcik & Ditto, 2014). Happy people also treat the domains of their lives differently than
unhappy people. They invest effort in the areas of their lives that are improving and divest effort from
other, more problematic life domains (Carver & Scheier, 2014). In related terms, happy people emphasize
the areas of their lives that are going well. This point was made in a set of studies by Diener, Lucas, Oishi,
and Suh (2002), who first isolated a person’s “best” (highest-rated) and “worst” (lowest-rated) life
domains. The best domains were more predictive of global well-being for happy people and the worst
domains were more predictive of global well-being for unhappy people. These results are consistent with
the idea that happiness biases the selection of life domains to consider when rating happiness in general.
One could avoid these biases somewhat by measuring life satisfaction in terms of the average of multiple,
more specific life domains (Weinberg et al., in press). Alternatively, biases such as these are central to
more global conceptions of life satisfaction (Tay et al., 2014).
Bottom-Up versus Top-Down Influences. Bottom-up models contend that happiness is built on the
particulars of life, including circumstances, events, and progress in specific life domains (Diener, 1984).
Top-down models instead emphasize factors like personality and self-enhancement, which are likely to
influence life satisfaction as a whole as well as life satisfaction in particular domains like work, marriage,
and leisure (Heller et al., 2002). Bottom-up factors will lead to changes in well-being when life
circumstances change; by contrast, top-down factors will tend to promote stability over time (Headey &
87
Wearing, 1989). These models are not mutually exclusive and one can find evidence for both bottom-up
and top-down influences in the same study, which Brief, Butcher, George, and Link (1993) did in the area
of health satisfaction. Similarly, job satisfaction is influenced by the circumstances of one’s job, but also
by personality factors like extraversion and neuroticism (Watson, 2000).
Consistent with top-down paths, personality traits have been linked to satisfaction with particular
life domains like one’s job or marriage (e.g., Heller et al., 2004). Moreover, controlling for personality
traits often reduces the correlation between satisfaction with a domain (e.g., one’s job) and life satisfaction,
suggesting that at least a portion of the relationship can be ascribed to personality (Heller et al., 2002).
Although it is intuitive to think of top-down influences in terms of judgmental biases like dispositional
positivity or self-enhancement (Wojcik & Ditto, 2014), top-down influences can also be more substantive.
Along these lines, several studies have shown that personality traits can predict the occurrence of positive
and negative life events (Headey & Wearing, 1989; Magnus, Diener, Fujita, & Pavot, 1993) and global life
satisfaction can prospectively predict latter success in particular domains like health and work
(Lyubomirsky et al., 2005a). Happy people, for example, attract marital partners, are happy in their
marriages, and are less likely to become divorced (Marks & Fleming, 1999).
Support for bottom-up paths can also be found, however. Changes in the relative proportion of daily
positive and negative life events can shift well-being in a corresponding direction, at least in the short term
(Robinson, 2000; Suh et al., 1996). And more serious changes in one’s life situation – such as
unemployment or disability – can have a lasting impact on well-being, even for multiple years (Diener et
al., 2006). Furthermore, there are age-related changes in life satisfaction that are consistent with bottom-up
rather than top-down influences (McAdams, Lucas, & Donnellan, 2012). Most notably, satisfaction with
health decreases with age while satisfaction with income increases (McAdams et al., 2012). We can also
alert the reader to more complex longitudinal models that either conclude that different life domains follow
different models (Headey, Veenhoven, & Wearing, 1991) or that there are both top-down and bottom-up
influences that are apparent in how people make domain satisfaction judgments (Lucas, 2004).
Future Directions
Both social psychology (e.g., Schwarz & Strack, 1999) and personality psychology (e.g., Eid &
Diener, 2004) have contributed to our understanding of how people make life satisfaction and happiness
judgments. Nonetheless, there are under-explored sorts of manipulations that may be useful in this
enterprise. As a way of studying motivational influences, Wojcik and Ditto (2014) told some participants
that happiness was linked to positive outcomes (e.g., better relationships), but told other participants that
happiness was linked to negative outcomes (e.g., unwarranted risk-taking). People tended to report greater
happiness in the positive outcome condition than in the negative outcome condition, though such trends
were particularly apparent at higher levels of self-enhancement. It seems to us that manipulations of this
type can be used to study some of the motivational factors that have been implicated in the personality and
culture literatures (Diener et al., 2003).
There are reasonable questions about whether people make life satisfaction judgments in more
heuristic or more systematic ways (Schimmack & Oishi, 2005; Schwarz & Strack, 1999). We would guess
that people use both sorts of strategies, and that the relative balance of the strategies may vary by person
(e.g., as captured by need for cognition) and situation (e.g., as captured by time of day or cognitive
busyness). Similarly, the relative influence of top-down (e.g., self-concept) and bottom-up (e.g., life events)
factors in life satisfaction judgment could vary by factors such as self-esteem (Diener & Diener, 1995) or
culture (Diener et al., 2003). Some clarity into these different routes to judgment could be achieved by
manipulating processing style, how much time people have to respond, or by manipulating cognitive
busyness (e.g., see Van Boven & Robinson, 2012). In an interesting study of this type, Trent and King
(2010) asked participants to make meaning in life judgments either rapidly or thoughtfully. Meaning in life
had different correlates under these different conditions and results of this type could be used to better
understand the typical process of judgment. For example, if the correlates of untimed happiness judgments
look more similar to a “rapid” condition than a “thoughtful” condition, one might conclude that heuristic
strategies tend to dominate (for related work, see Erber et al., 1995).
Perhaps most straightforwardly, reaction time (RT) methods could be used more extensively in the
happiness and well-being literature (Robinson & Compton, 2008). In one sort of paradigm, Robinson and
Clore (2002b) showed that people switched from a data-driven to belief-based (top-down) judgment
strategy when rating their emotions over the period of several weeks or longer. A similar relationship
between time frame and judgment speed could occur for life satisfaction or happiness judgments. Primingrelated
paradigms can also be used. Bottom-up theories would be supported if judging one’s satisfaction
with a specific life domain speeds judgments of life satisfaction in general; by contrast, top-down theories
would be supported if the opposite pattern is found (for one application of similar logic, see Schell, Klein,
88
& Babey, 1996). Finally, if life satisfaction is a type of attitude (Pavot & Diener, 1993), then cognitive
models of attitude strength (Fazio, 1995) could be used in understanding it. Faster life satisfaction
judgments are likely to implicate a top-down path to judgment that should be more particular to some
individuals than to others. Among other consequences, this literature would lead us to predict that people
making these judgments more quickly, in comparison to more slowly, should report levels of life
satisfaction that are more stable over time (Fazio, 1995).
Conclusions
In the introduction, we contrasted three different models of well-being judgment. According to a
bottom-up, systematic model, people may carefully consider their standing in a number of life domains
before making life satisfaction or happiness judgments (Campbell et al., 1976). According a second
constructivist model, people may lack solid ideas about their general levels of happiness and therefore seize
onto whatever happens to be accessible in the moment (Schwarz & Strack, 1999). According to a third
model, people might judge their lives in the same way that they judge very familiar objects – by direct
retrieval of their evaluations, potentially independent of corroborating evidence (Fazio, 1995). After
having reviewed multiple sources of evidence, we are inclined to think that some combination of these
models seems necessary, with strengths and weaknesses outlined in Table 1. People have very stable ideas
about their happiness, consistent with the third model, but they are also responsive to changes in their lives,
consistent with the first. Further attention to how people make these judgments could sharpen the models,
in turn allowing us to understand how variations in culture, personality, and life events get translated into
variations in well-being.
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2018 Ed Diener. Copyright Creative Commons: Attribution, noncommercial, no
derivatives
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The Cornerstone of Research on Subjective Well-Being: Valid
Assessment Methodology
By William Pavot, Southwest Minnesota State University
Citation
Pavot, W. (2018). The cornerstone of research on subjective well-being: Valid assessment methodology.
In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
This chapter focuses on the process of obtaining valid assessments of Subjective Well-Being (SWB) from
individuals, primarily with conventional self-report methodology. A brief review of the SWB construct
and its constituent facets is followed by a discussion of some of the factors, both stable and transient, that
may influence an individual’s response to questions about their SWB. Several examples of measurement
instruments, ranging from single-item measures to multi-faceted questionnaires, are briefly reviewed. The
issues of scale reliability and validity are considered. General design strategies for optimizing the “fit”
between assessment and the goals of the research follow. Some conclusions regarding SWB research, as
well as additional resources and guides that are available to researchers new to SWB assessment are in a
final section.
Keywords: Subjective Well-Being, Assessment, Self-report, Reliability, Validity
Research on Subjective Well-Being (SWB) continues to be a thriving inter-disciplinary interest
area. Even a brief examination of the chapter topics in this volume confirms the breadth and depth of
SWB-related investigation. This level of interest is quite remarkable for a topic that was almost unheard of
three decades ago. In the interim, an impressive database has been gathered in an attempt to discern the
structure, correlates, and sources of SWB.
Theoretical research focused on the structure and sources of SWB continues, but the application of
SWB research for the improvement of the quality of life has become an important additional growth area.
Many nations, for example, have begun to recognize that the assessment of the SWB of their citizenry can
provide an important social indicator for policy and decision making, over and above the more traditional
sources, such as economic indicators (Diener, 2000; 2006).
Despite the rich diversity of research related to SWB, some concerns are common: How accurate
are the observations upon which the conclusions of the investigator are based? What are the potential
strengths and weaknesses of the research design employed? Are the findings widely generalizable?
Regardless of the goals of the researcher, the fundamental building block continues to be dependable and
accurate data obtained from valid assessment methodologies. The present chapter will examine some of
the issues involved in the assessment of SWB, with a specific focus on traditional self-report measures.
The first section of this chapter will briefly discuss the major components of the SWB as they have
emerged from early research. The second section will review and discuss some of the measurement issues
that may influence the validity of self-reports of SWB. Examples of some of the best-known instruments
for the assessment of SWB are presented and discussed in the third section of the paper, and, in the fourth
section, issues of establishing the reliability and validity of assessment instruments are considered. Some
design considerations for future assessments of SWB appear in the following section, and some
conclusions and suggested resources are presented in the closing section.
The Structure of SWB
The structure of SWB can be conceptualized as having two, three, or four facets, depending on the
specificity required to address the research question(s) of interest. At a very fundamental level, SWB can
be divided into two facets: One facet would include the affective or emotional aspect of subjective
experience, and a second facet that would represent the cognitive, evaluative or reflective aspect. This
structure is intuitively appealing and straightforward. But early findings by Bradburn (1969), and later
confirmed by Diener and Emmons (1984) indicated that the experience of positive emotion and negative
emotion are largely independent of each other. As a result, most contemporary researchers tend to consider
positive emotion/affect and negative emotion/affect as separate facets, and tend to use a three-facet model
of SWB (e.g., Arthaud-Day, Rode, Mooney,& Near, 2005). Additionally, depending on the goals of the
researcher, the cognitive/evaluative/reflective component may sometimes be further divided as well.
Frequently, investigators are interested in an individual’s overall evaluation of their life as a whole, usually
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referred to as life satisfaction. However, if the research is focused on a particular aspect of a person’s life,
such as their employment or their marriage, it may be useful to examine the individual’s evaluation of a
particular domain of their life. Thus, the evaluative component can be divided into a judgment of overall
life satisfaction, or one or more specific aspects of life with domain satisfaction.
Issues in the Measurement of Subjective Well-Being
On the surface, the assessment of SWB may seem (perhaps deceptively) simple. In many cases, a
single, clear question is asked, such as “Overall, how happy are you in life?” The respondent is typically
asked to make a rating of their happiness using a Likert-type response scale (e.g., ranging from “1”,
indicating a low level of happiness to a “10” indicating a very high level of happiness). The researcher’s
assumption is that the response provided is an accurate reflection of the respondents overall and relatively
stable subjective experience. To an extent, a very large body of empirical evidence has supported the
validity of this assumption. But previous research has also revealed that a number of factors can, under
specific circumstances, exert influences on the response given, possibly biasing the response in a positive
or negative direction, and thereby reducing the validity of the data obtained.
Random transient influences on self-reports of SWB. A potential concern to researchers
attempting to assess SWB is the influence that relatively random, contextual and/or situational factors
might have on an individual’s response. These transient influences might include current mood, the
situation surrounding the assessment situation, or the influence of questions or items that are presented
prior to the SWB item(s) within a given questionnaire arrangement.
Transient affective/mood states. One well-known demonstration of the potential for current mood
to influence self-reports of SWB was provided by Schwarz and Clore (1983). Using induced positive or
negative mood states (e.g., memory searches for good or bad events; obtaining responses on sunny versus
rainy days) these researchers were able to influence respondents judgements of overall happiness and
satisfaction with life. Subsequent research (Pavot & Diener, 1993a; Eid & Diener, 2004; Lucas & Lawless,
2013; Yap et al., in press) has shown that these effects are generally minimal, if not nil, and can be further
reduced with methodological safeguards; nonetheless, the potential influence of current mood on selfreports
of SWB, while generally small, is noteworthy.
Transient situational/contextual factors. It is also possible for self-reports of SWB to be
influenced by transient factors in the situation or the context surrounding the response. A face-to-face
interview, for example, could yield reports of greater SWB, when compared to responses on an anonymous
survey, due to the effects of the social desirability of happiness. In situations where an item intended to
measure SWB is embedded in a larger survey, the content areas of the proceeding items in the survey might
influence the response to the specific SWB question. The order in which questions are presented can have
an influence on an individual’s response (Strack, Martin, & Schwarz, 1988).
While it is important to recognize and acknowledge that these random transient factors can
influence self-reports of SWB; it is also important to point out that these influences are generally limited,
and can be minimized with careful design and methodology. In very large survey designs, for example,
transient mood effects are likely to have minimal influence on group levels of reported SWB. Barring
some major crisis or world event with sweeping emotional impact, the effects of the transient negative
mood state of one individual is likely to be effectively cancelled by the transient positive mood state of
another. The effects of item placement on response can be minimized by presenting survey items in a
random order. In smaller scale studies specifically focused on an aspect of well-being, transient effects can
be minimized by assessing SWB on more than one occasion, and then computing an average score across
those occasions. While some transient effects will likely always be part of self-reported SWB, careful
methodological planning can substantially reduce their impact.
Stable situational /contextual factors. In addition to the potential influences of transient
situational and contextual factors may exert on self-reports of SWB, investigators must also be mindful of
more stable influences as well. A differential cultural perspective between respondents, for example, might
well be a source of consistent variation in assessments of SWB. Although several studies (e.g., Balatsky &
Diener, 1993; Scollon, Diener, Oishi, & Biswas-Diener, 2004) have indicated that SWB measures do have
a reasonable level cross-cultural validity, other reports (e.g., Vitterso, Roysamb, & Diener, 2002) have
indicated that the reliability and underlying factor structure of life satisfaction measures can vary across
cultures. Examining nations using a general individualist versus collectivist cultural categorization can
provide an illustration. Using two large international data sets, Suh, Diener, Oishi and Triandis (1998)
found life satisfaction more strongly correlated with emotions in individualist nations as compared to
collectivist nations. In collectivist nations, social norms were equally as strong as emotions in the
prediction of life satisfaction reports. Thus the sources of information that are accessed in the formulation
of life satisfaction judgments can vary across cultures.
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An additional factor, less clearly identified yet likely no less influential, is the potential for
differential “cohort effects” between age groups (Diener & Suh, 1997). Individuals of the same
chronological age (same “cohort”) share not only age-related physical developmental changes as they
progress through life; they have also experienced social change and major historical events together. These
shared experiences likely serve to help each cohort group develop its own “scale” of positive and negative
life events that is to some extent unique. For example, a cohort that has experienced severe economic
depression or a world-wide conflict likely has a somewhat different scale of negative events than members
of a cohort without these experiences.
Another factor that can influence responses to SWB measures is the particular facet of SWB that is
assessed by the measure. Measures of the evaluative facet of SWB (i.e., judgments of life or domain
satisfaction) appear to be influenced to a greater degree by contextual factors than measures focused on the
affective facets of SWB (Tay, Chan, & Diener, 2014).
Memory Issues and Biases
Another potential influence on self-reports of SWB involves the memory processes used by the
respondent in formulating their subjective report. “Traditional” self-report instruments for assessing SWB
rely on global retrospective reports from respondents. Unfortunately, human memory is not perfect, and a
number of factors may work to create biases in retrospective reports. For example, the data indicate that
people tend to formulate reports of emotion that are more strongly correlated with the amount of time they
have experienced an emotion, rather than on the intensity of the emotional experience (Diener, Sandvik, &
Pavot, 1991).
One methodological innovation intended to address the problems inherent in retrospective reports is
the Experiential Sampling Method (ESM; Csikszentmihalyi & Larson, 2014). This method involves
obtaining a large number of reports of emotion and SWB at random moments during each day, while the
respondents are having these subjective experiences. Such an approach can eliminate the retrospective
element of the self-report, and therefore presumably eliminate the problem of memory bias. The ESM
method is discussed in detail in another chapter of the volume.
Representative Examples of SWB Self-Report Instruments
Rutt Veenhoven has created a large and highly informative database of SWB research, the World
Database of Happiness. One section of this database focuses on existing measures of happiness, which
number more than eleven hundred catalogued examples (Veenhoven, 2017). It is not possible to review
these measures in detail; it is possible, however, to sort potential instruments into general groups, and
prominent examples of each general group are reviewed in this section.
Single-item broadband measures. Most of the measures that have been included and catalogued
in the World Database of Happiness are single-item measures, usually presented to respondents in a survey
format (Veenhoven, 2017). Many of these single-item measures are “broadband” in design; all facets of
SWB are assessed by this single item, in the form of a statement or question. Usually the stimulus item is
focused on the generic terms of “Happy” or “Happiness.” A prototypical example of this category is the
Fordyce’s Single-Item Happiness Question (1977). The Fordyce Scale offers 11 Likert-scale response
choices (ranging from “Extremely happy” to “Extremely unhappy”) to the query: “In general, how happy
or unhappy do you usually feel?”
Another single-item broadband measure of SWB is the Delighted-Terrible Scale (Andrews &
Withey, 1976). After prompting the respondent to think about their own life and about “life in this
country” over the past year, and their expectancies for the future, the respondent is asked to make one of
seven possible responses to the question: “How do you feel about how happy you are?” The responses
range from 1 (Terrible) to 7 (Delighted). The Delighted-Terrible scale has been used in conjunction with
the World Values Survey (1994), and has demonstrated good psychometric characteristics.
The brevity of single-item broadband measures is obviously a great asset to survey researchers.
But there is a significant trade-off involved; single item measures do not provide specific information
regarding the separate facets of SWB.
Single-item facet-focused measures. One of the most enduring and widely used single-item
measures is Cantril’s Self-Anchoring Ladder (SAL; Cantril, 1965). This instrument has been frequently
used in large-scale survey studies, perhaps most notably research conducted by the Gallup Organization,
both internationally (Helliwell, Layard & Sachs, 2014) and in the United States (Harter & Gurley, 2008) .
Data from the SAL is a primary source for the World Happiness Report, sponsored by the Organisation
(sic)for Economic Co-operation and Development (OECD). The instructions for the Cantril SelfAnchoring
Scale ask the respondent to imagine a ladder with the steps numbered from zero (the bottom
step) to 10 (the top step). Then the top and bottom step are identified as representing the best possible life
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and worst possible life, respectively, for the respondent. The respondent then chooses the step that is most
representative of their life as a whole. The time frame for the response can be adjusted to represent their
current life, their future life (i.e., five years from now), or both time-frames can be assessed separately.
Single item measures of Life Satisfaction have been demonstrated to have good reliabilities (Cheung &
Lucas, 2014), that are comparable to multiple-item scales.
Multi-item comprehensive scales. In some contrast to the single-item survey measures of SWB,
which are often used for a broad range of purposes and applications, multiple-item measures tend to be
used in research settings with a primary focus on SWB. Multiple-item measures can provide researchers
with a more detailed picture of the respondent’s SWB, and can be examined in more detail
psychometrically.
Most multi-item SWB scales are facet specific; they tend to assess either the affective facets or the
life satisfaction facet of SWB, but not both. Still, there are examples of multi-item, comprehensive
measures of SWB.
The Oxford Happiness Questionnaire (OHQ; Hills & Argyle, 2002), represents a revision of an
earlier instrument, the Oxford Happiness Inventory (OHI; Argyle, Martin, & Crossland, 1989). The OHQ
consists of 29 items, each a statement to which individuals can respond on a 6-point Likert-type scale. The
authors interpret the underlying factor as being uni-dimensional. Correlational comparisons indicate that
both the convergent and discriminant validity of the OHQ are somewhat improved over the OHI.
The Subjective Happiness Scale (SHS; Lyubomirsky & Lepper, 1999) is a brief (4-item) measure
that is also intended to assess global subjective happiness. Responses to the four items can be made on a 7point
Likert scale, with higher numbers indicating greater SWB. In early validation studies, correlations of
the SHS with informant reports were moderate to strong, and test-retest reliability was also strong. The
brevity of the SHS, combined with the encouraging initial psychometric data on the scale, suggest that the
scale should have good utility when a comprehensive measure is desired.
Multi-item affect scales. Several multiple-item measures have been developed with a specific
focus on the affective components of SWB. Although it would be possible to create a scale that was
focused on either positive affect or on negative affect exclusively, most of the scales in this category
measure both of these facets using separate subscales. This allows for the computation of an index of the
affective state of the respondent, commonly referred to as “affect balance” (Bradburn, 1969). The affect
balance score represents the difference between the amount of positive affect reported and the amount of
negative affect reported (e.g., positive affect – negative affect = affect balance). A positive affect balance
would indicate that the respondent has reported a greater amount of positive emotion that negative emotion
over a specified time frame and presumably has experienced SWB during that time. It is also possible, of
course, to focus on the subscale scores independently as well.
The Bradburn Affect Balance Scale (BABS; Bradburn & Caplovitz, 1965; Bradburn 1969) was the
first scale to use the affect balance approach as an assessment of SWB. The 10-item BABS includes PA
and NA subscales of five items each. In the original version of the BABS, the respondent is asked to
indicate, using a “yes” or “no” response, whether they have experienced any of the positive or negative
affects “during the past few weeks.” The BABS affect balance index is generally correlated (albeit
moderately) to other SWB indices.
The Affectometer 2 (Kammann & Flett, 1983) uses an approach that is similar to the BABS, but
incorporates an expanded array of 40 affect items, intended to assess ten facets of SWB. The Affectometer
2 also replaces the “yes” or “no” responses of the BABS with a frequency response scale for each item.
The combination of larger number of items and a frequency response scale are psychometrically appealing,
but the length of the Affectometer 2 might be an obstacle in some research designs.
Researchers have frequently used another multiple-item affect measure, the Positive and Negative
Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988), in recent years. The PANAS includes 10
affective adjectives in each of its two subscales. Respondents indicate the degree to which they have
experienced each emotion, using a 5-point scale. The time-frame can be adjusted to reflect the either the
current emotional experience of the respondent or a retrospective report (e.g., “over the past few days” or
“in the past few weeks”). Both the PA and NA subscales have good psychometric characteristics. The
PANAS tends to put emphasis on high activation emotions, and includes some adjectives (e.g., “strong”)
that may not necessarily reflect emotion exclusively. An expanded version of the original PANAS, the
PANAS-X, utilizing 60 items, is also available (Watson & Clark, 1999).
A relatively recently developed scale, the Scale of Positive and Negative Experience (SPANE;
Diener et al., 2010), has a number of desirable characteristics. The 12 items (emotion adjectives) of the
SPANE, despite the brief format, assess a broad range of both positive and negative affective experience.
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The 5-point frequency response scale, ranging from 1 = “Very rarely or never” to 5 = “Very often or
always” indicates the relative amount of time that the respondent was experiencing each emotional state.
And frequency of feelings, rather than intensity of emotion, tends to be related to other SWB measures,
such as life satisfaction measures.
Multi-item satisfaction scales. Probably the best known of the measures in this category is the
Satisfaction With Life Scale (SWLS; Diener, Emmons, Larsen, & Griffin, 1985). The satisfaction with life
scale has been used in thousands of studies and has been translated into more than 30 languages. The
SWLS has been cited in more than 17 thousand published scholarly articles (according to a 2017 Google
Scholar search). The SWLS consists of five statements, such as “In most ways my life is close to my
ideal,” and “I am satisfied with my life.” Typically, a seven-point Likert scale is provided for a response to
each item, ranging from “strongly disagree” (1) to “strongly agree” (7). The five-item SWLS has
demonstrated good internal reliability and moderate temporal reliability. It has been shown to be sensitive
to both positive and negative change over time (Pavot & Diener, 1993b; Pavot & Diener, 2008).
The 15-item Temporal Satisfaction With Life Scale (TSWLS; Pavot, Diener, & Suh, 1998) uses
essentially the same items as the SWLS, but presents them with three distinct temporal contexts, referring
to the past, the present, and the expected future satisfaction of the respondent. The TSWLS thus can be
used to gauge future expectancies of the respondent, as well as past and current perspectives.
Population / domain specific measures. Nearly all of the measures of SWB reviewed in this
chapter have good generalizability to a very wide range of populations. Most will provide valid SWB data
without concern for respondent age, or occupational, economic or other noteworthy social differences.
However, some researchers are interested in aspects of life that may be particularly relevant to the SWB of
a specific group or age range. Specialized measures of SWB and life satisfaction are available for a
number of specific populations. For example, researchers interested in the aging process have developed
several measures, such as multiple versions of a Life Satisfaction Scale (LSR, LSIA, LSIB; Neugarten,
Havighurst, & Tobin, 1961). Another well-known scale intended for older adults is the Philadelphia
Geriatric Center’s Morale Scale (PGC Morale Scale; Lawton, 1972, 1975). This scale appears to assess
several factors, including loneliness and attitudes toward aging. These scales are well-established and have
been used extensively in research focused on late adulthood.
Children and adolescents represent another population that has been the focus of attention for wellbeing
researchers, particularly in their role as students. The Student's Life Satisfaction Scale (Huebner,
1991) and the Brief Multidimensional Students' Life Satisfaction Scale (Seligson, Huebner, & Valois,
2003) are two examples of measures focused on the student population.
Many researchers are interested in assessing satisfaction with specific aspects of life, such as job,
marriage, income, religious orientation, government function, or some other specific life domain. Items
intended to assess specific domains are numerous (Veenhoven, 2017), and can be adjusted to whatever
situation or domain is of interest to the researcher.
Measures of constructs related to SWB. When designing a study focused on SWB, It is often
desirable to include additional assessment instruments that provide data on constructs that are related or are
believed to be related to SWB itself. An example of one such construct that has relevance for the
experience of SWB is Dispositional Optimism. Dispositional Optimism refers to a global generalized
tendency to believe that one will generally experience good vs bad outcomes in life (Scheier & Carver,
1985). One measure intended to assess dispositional optimism is the Life Orientation Test (L.O.T.; Scheier
& Carver, 1985). The L.O.T. includes eight construct-relevant items (four keyed in a positive direction,
and four in a negative direction), along with four “filler” items intended to disguise the specific focus of the
scale. Responses are made on a five-point Likert scale. A later version of the scale, the 10-item L.O.T. –
R., was developed by dropping two of the construct-relevant items, in order to more clearly distinguish
dispositional optimism from neuroticism (Scheier, Carver, & Bridges, 1994). Both versions have good
psychometric characteristics, and have been used extensively in research.
The Flourishing Scale (FS; Diener et al., 2010) is intended as a broadband measure of selfperceived
well-being across a range of important domains. The FS assess functioning in areas that are key
to psychological well-being such as relationships, feelings of competence, and a sense of meaning and
purpose in life. The FS includes eight items, and utilizes a 7-point Likert scale for responses.
Another recently developed broadband measure also focused on a range of well-being related
domains is the Comprehensive Inventory of Thriving (CIT; Su, Tay, & Diener, 2014). The CIT is
composed of 54 total items (18 subscales), and spans a very broad range of domains. For situations
requiring a quicker assessment, a 10-item version of the CIT, The Brief Inventory of Thriving (BIT), has
also been developed and is included in the same report. Both of these measures were evaluated with
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multiple samples with diverse demographics. The CIT and BIT demonstrated excellent psychometric
properties and good convergent validity (Su, Tay, & Diener, 2014)
Reliability and Validity of SWB Assessments
Reliability. Reliability refers to the degree to which an assessment instrument produces consistent,
dependable results. Several forms of reliability are commonly examined when evaluating an assessment
instrument or technique. For the present I will focus on three basic types of reliability. One gauge of
reliability is focused on the ability of assessment instrument to produce dependable results over a period of
time, and is often referred to as “test-retest” reliability. For example, if we asked an individual to complete
a measure of SWB today, and then asked them to complete the same measure one month from now, we
would expect that the results would be similar. The degree of agreement or correlation between the two
measurement occasions would represent an index of test-retest reliability. A second form of reliability is
referred to as “inter-rater” reliability. This form of reliability is an index of agreement between two or more
“raters” or “judges.” For example, we might ask two (or more) different raters to evaluate the emotion
content of a writing sample that a respondent has completed. The degree to which their evaluations agree
would serve as an index of inter-rater reliability. A third type of reliability is usually identified as internal
reliability or “Alpha” reliability. The “Alpha” identifier is a reference to Cronbach’s Alpha (Cronbach,
1951), which is a statistic that is usually computed and reported as an index of internal reliability. Internal
reliability is determined by the consistency of response to each of the items on a multiple-item measure.
That is, the tendency of individuals to respond consistently to all the items of the measure in a similar
way. Thus, the greater the consistency of response across the individual items of the scale, the larger the
Alpha statistic will be. There is no absolute standard regarding the minimum acceptable level of Alpha;
generally a range of .7 to .75 would be considered a minimal demonstration of internal consistency.
The reliability of most self-report measures of SWB is typically evaluated using either an index of
test-retest reliability or of internal reliability. For multiple-item measures, it is usually expected that
statistics depicting both indices will be presented. With single-item measures, the index of internal
reliability, or Cronbach’s Alpha, cannot be computed. In either case, an index of reliability is a critical
element in the evaluation of the assessment instrument or method.
Validity. Validity can also be understood from multiple perspectives. Many types of validity have
been identified, such as face validity and predictive validity. A full discussion of all forms of validity is
beyond the scope of this chapter; it is perhaps more efficient to focus on some central elements. A central
form of validity, construct validity, refers to the degree to which an instrument accurately measures the
construct it is intended to measure. In other words, a measure of SWB, when completed by a respondent,
should be an accurate depiction of that person’s experience. Establishing the construct validity of a SWB
measure is a complex process. A first step in the process usually involves establishing reliability, because
without dependable assessment, it is impossible for a measure to be considered valid. Thus, reliability is a
necessary, but not sufficient, condition for validity. Reliability is not sufficient for validity because,
unfortunately, it is possible to be reliably wrong. In addition to demonstrating reliability, it is critical that
an assessment instrument demonstrate that it is accurately measuring the construct it is intended to
measure. Accuracy (construct validity) can be evaluated by comparing the results yielded by the measure
to the results of both similar and dissimilar measures obtained from the same sample.
Convergence of similar measures. In order to go beyond reliability and establish the accuracy
(validity) of our measurement, we have to rely on established “benchmarks” that can help us determine
how well our measure is accurately assessing the intended construct. One type of benchmark is provided
by previously established indices that measure the same construct, or at least similar constructs to the one
we are interested in. We would expect that such indices would be positively correlated with our measure.
To demonstrate such correlations would represent establishing convergent validity. To gauge the
convergent validity of a SWB measure, it is necessary to include more than one such measure within a
particular sample, and then examine the strength of the correlations between the two (or more) measures of
SWB. Measures of other closely related constructs can also be examined. Thus, a measure of flourishing
would be expected to be positively correlated to a measure of life satisfaction from the same sample.
An additional advantage of including more than one measure of SWB within a research design is
the possibility of creating “composite” SWB scores. That is, if the convergence between separate measures
of SWB is high, it is possible, using standard scores such as “Z” scores, to combine the results of the
individual measures into one composite measure of SWB. The advantage to this strategy is that a
composite score or index tends to have greater stability and reliability than the scores on the individual
scales, thus strengthening the results of any further analysis. A potential drawback to this strategy,
however, is that the use of composite scores can obscure meaningful differences between measures at the
specific facet level. It is desirable, therefore, to report the results of basic analyses of the individual scales
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before combining them into composite scores.
Convergence of self-reports with other methodologies. In addition to demonstrating the
convergence of multiple self-reports of SWB, convergence can also be evaluated by comparing self-reports
of SWB to an index of SWB obtained by using another methodology. An often-used alternative
methodology is the use of “informant” reports. Informant reports are typically obtained from someone who
knows the research participant well, such as a spouse, parent, sibling, roommate, or co-worker. Informant
reports tend to increase confidence in the validity of the self-reported data, as they are obtained from an
independent source. The validity of self-reported measures of SWB, such as reports of life satisfaction, has
been demonstrated by the convergence of such reports with informant reports in a number of studies (e.g.,
Costa & McCrae, 1980; Pavot, Diener, Colvin, & Sandvik, 1991; Pavot & Diener, 1993b; Lyubomirsky &
Lepper, 1999).
Other alternative methodologies include rating based on clinical interviews, ratings based on writing
samples (Danner, Snowdon, & Friesen, 2001), and analysis of memory bias for positive and negative
events (Sandvik, Diener, & Seidlitz, 1993).
Divergence of dissimilar measures. Another set of benchmarks, in this case measures of
dissimilar constructs, could also support the validity of our measure. By demonstrating divergent validity,
we can show that our measure is an assessment of a construct that is distinct from other, dissimilar
constructs. In the case of divergent validity, we would expect to see either no correlation, or perhaps a
negative correlation in the case of a strongly dissimilar (perhaps opposite) construct. For example, a
measure of SWB would be expected to have a negative correlation with a measure of psychological
distress, such as depression or anxiety. Two often used measures of distress that can be useful in this
capacity are a depression scale, the CES-D scale (Radloff, 1977), and the SCL-90-R (Derogatis, 1992), a
broader assessment of nine primary symptom dimensions. Scores on measures of anxiety and neuroticism,
such as the neuroticism scale on the NEO-PI (Costa & McCrae, 1980).
Considerations for Designing Future Studies
For the researcher contemplating a study focused on SWB, the design and methodological
possibilities are many. Clearly, a wide array of self-report instruments for the assessment of SWB is
available. Choosing a measure, or a battery of measures, and the specific method of employing these
measures to best advantage are critical questions. The question of which, if any, additional dimensions to
add to a design is important as well. It may be useful to review some of these considerations.
In its most basic form, the assessment of SWB might be accomplished by a single question at one
point in time, such as an item embedded in a larger survey of social attitudes. Despite the simplicity of this
approach, useful data, albeit at a very general level, can be obtained in this way. This might be the only
feasible choice for very large -scale survey efforts, and has been used quite successfully in many such
situations, such as compiling the World Happiness Report. The difficulty with this approach is the lack of
specificity and detail in the assessment. As these surveys are generally not given to the same individuals at
an additional occasion, we have no sense of the stability or the dynamics of the respondent’s subjective
experience, nor do we know the specifics of the quality of the subjective experience. Still, the very general
snapshot of SWB might well be useful in monitoring the overall SWB of a large group, such as monitoring
the overall reaction to a recent change in public policy.
For those interested in a more finely grained assessment, more sophisticated measures may be in
order. Two or more SWB measures might be used in concert, and perhaps some additional variables (e.g.,
personality factors, measures of distress) could be included, to provide a system of benchmarks, to examine
convergence or divergence of the measures. If the SWB measures are multiple-item scales, information on
internal reliabilities can also be obtained.
Another level of complexity can be added to the analysis if the research participants are surveyed at
more than one point in time, with an interval of one or more months between. With assessment on multiple
occasions, we can obtain test-retest reliability data, and look for stability (or change) over time. For
example, a meta-analysis of such data has shown test-retest reliabilities for global SWB tend to range from
.70 over a one-year period, and then decrease to approximately .50 for a 5-year interval (Anusic, &
Schimmack, 2016). If the entire original sample cannot be retested, it may be possible to conduct a retest
on a subsample of the original group.
A still more sophisticated design might include the collection of informant reports, in addition to the
self-report measures of SWB. Informant reports that show good convergence with the self- reports of the
study serve to greatly increase the confidence in the findings of the research. A detailed discussion of the
sources of self-report and informant-report agreement is available in a meta-analysis by Schneider and
Schimmack (2010).
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Thus, a longitudinal research design with multiple measures of SWB assessed on multiple occasions
and including informant reports is likely to be desirable for those who want a complex, sophisticate data set
of the first order. Obviously the cost to achieve that goal, in terms of time, resources, and effort is going to
be high. Conversely, a single-item survey assessment can likely be obtained quickly and economically,
but will only provide a very general level of data. For many researchers, a design that falls somewhere
between these points is a likely solution. A gradual validation of a finding from a series of studies is as
valuable (if not more valuable) than a single “answers all the questions” effort. Replication of previous
findings is usually not sensational, but it is essential for building a strong empirical database. A
programmatic body of research, in which each study replicates and builds upon previous work, is a
valuable tool for advancement.
Summary and Additional Resources
Fortunately, there are many additional sources and examples of the topics briefly presented here. I
will list a few of the many options here; there are far too many to enumerate in any comprehensive way.
For those who are new to the study of SWB, and interested in obtaining some general background
information, a landmark review article by Ed Diener is a great start (Diener, 1984). After reading the 1984
paper (if you haven’t already) I would suggest Diener (2000) as an update, with a particular proposal for a
national index of SWB. An edited volume (Kahneman, Diener, & Schwarz, 1999) also provides much
greater depth on many of the issues raised in this chapter. For a review focused on the assessment of SWB,
Diener (1994) is a good choice; Pavot (2008) also discusses assessment issues. A more recent discussion
of the validity of life satisfaction scales is available in Diener, Inglehart and Tay (2013).
For those readers interested in developing and validating their own measures, it may be valuable to
review the work of others who have previously engaged in the process. For some good examples of the
scale validation process, I would suggest Lyubomirsky and Lepper (1999), Seligson, Huebner, & Valois,
(2003) or Diener et al. (2010). The article by Pavot, Diener, Colvin, & Sandvik (1991) is an example of
validation of a self -report scale with informant reports. Before you begin the complex process of
developing and validating a new measure of SWB, I would encourage you to access the World Database of
Happiness (Veenhoven, 2017) on the internet (website: http://worlddatabaseofhappiness.eur.nl). This is an
outstanding resource for anyone interested in any aspect of research on happiness or SWB. As noted
earlier in this chapter, more than eleven hundred measures have been catalogued and are listed in the
“measures” section of the database. It is possible that a previous researcher has already developed a
measure that may well suit your needs. Guidelines for researchers interested in using SWB assessments
for specific purposes (e.g., general assessment of well-being at the national level) are available (Diener,
2006).
There is no single “correct” way to assess SWB across all research situations and purposes.
Nevertheless, it is very possible to optimize the validity of assessment in any given study by a careful
consideration of the parameters of the research situation, the resources available, and the proximal and
distal goals of the particular research program.
It is important that future researchers continue to pursue both theoretical and applied questions
regarding SWB. The topics listed in the table of contents of this handbook are indicative of the many
possible directions a program of research might take. At the basic research level, questions from the
evolutionary, biological, cognitive, and social perspective are the subject of current study, and will continue
to be so for the future. Applied research ranges from the development of interventions at the individual
level to social policy at the national level. In terms of the assessment of SWB, future research could focus
on the further development of alternative methodologies to compliment the already extensive array of selfreport
measures that are available.
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2018 Ed Diener. Copyright Creative Commons: Attribution, noncommercial, no
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Statistical Approaches to Analyzing Well-being Data
By Michael Eid, Free University of Berlin
Citation
Eid, M. (2018). Statistical approaches to analyzing well-being data. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
This chapter gives an overview of modern latent variable models for well-being (WB) research. After a
short introduction into the importance of measurement error and methodological artifacts that can be
produced by measurement error, the basic principles of four types of latent variable models are described:
item response theory, latent class analysis, factor analysis, and latent profile analysis. Then, latent variable
models for multidimensional data structures are discussed and it is shown how the models can be used to
define general WB measures and facet-specific factors. It is pointed out how these models can be applied in
multimethod WB research and how the convergent and discriminant validity can be measured in this
context. Finally, a very general model for analyzing variability and change in WB is presented and it is
discussed how this model and special cases of this model can be applied in WB research.
Keywords: latent variable models, item response theory, classical test theory, latent class analysis,
latent profile analysis, confirmatory factor analysis, measurement error, g-factor, bifactor model,
longitudinal data analysis
Over the last decades, there has been an enormous progress in the development of advanced statistical
methods in the social and behavioral sciences. This chapter will give an overview of some important
methods that are relevant for well-being (WB) research. It will focus on measurement models that are
appropriate for representing the specific characteristics of WB measures. These measurement models can
be used in more complex models to analyze the causes and consequences of WB.
As the chapters of this handbook show there are many measures of WB that have been developed
over time. If a researcher uses, for example, two different measures in a study, she or he will realize that
these two measures will not perfectly coincide. It would not be possible to perfectly predict interindividual
differences in WB on one measure using another. Even if one measures the same individuals repeatedly
using the same WB measure it is likely that the results are not perfectly the same. To interpret the empirical
results of WB research appropriately, it is necessary to understand the reasons for the divergence of WB
measures, to estimate the degree of divergence, and to consider the sources for these degrees of divergence.
This can serve to avoid methodological artifacts that could lead to invalid conclusions.
There are several reasons why two well-being measures do not perfectly coincide. A first reason is
measurement error. Whenever we measure something in science we cannot avoid unsystematic influences
that affect the measurement process. For example, if we weigh ourselves in the morning repeatedly using
the same balance, the results might differ depending on how we stand on the balance. A second reason
might be method effects. If one measure is a self-report of WB and the other measure is an observational
method the measurements might differ because these assessment methods have peculiarities that are not
shared. A third reason can be that the two different WB measures assess different components of WB, for
example, cheerfulness and calmness. A fourth possible reason is that WB has changed between the two
measurements. In order to separate these different sources of variability in WB scores, measurement
models are required. This chapter gives an overview of measurement models that can be applied to analyze
WB data, and gives answers to the following questions:
1. Why is it important to consider measurement error?
2. How can measurement error be considered?
3. How can the multidimensional structure of WB measures be modelled?
4. How can method effects be measured?
5. How can change in WB be measured?
The approaches presented assume that a random sample is drawn from a population of interest. In
some research contexts, sampling is more complex. One example is cross-cultural WB research in which
random samples are taken from different nations. Another example is organizational WB research, in
which a multilevel sampling process is usual. In a two-level sampling process, for example, first
organizations (e.g., companies, schools, villages; level-2 units) are drawn from a population of
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organizations and then for each organization a random sample of individuals (level-1 units) is selected. At
the end of this chapter it is discussed how the approaches presented can be extended to these more complex
research designs.
Why is It Important to Consider Measurement Error?
Measurement error cannot be avoided in any empirical science. Because of measurement error one
would get different scores for the same individual even if one theoretically could measure the same
individual with the same instrument repeatedly at the same time. In measurement error theory (classical
psychometric test theory, Lord & Novick, 1968) one decomposes the observed score of an individual into a
true score and a measurement error score. The true score is the score of an individual one would get if one
could measure the individual repeatedly and calculate the mean score across all replications. Because it is
not possible to repeatedly measure the same individual at the same time, measurement models have been
developed to separate measurement error from true scores that are built on more viable research designs.
The separation of measurement error from true scores in these measurement models is important for
different reasons. First, it allows estimating the reliability of the measurements and judging whether
measurement error is low enough so that the measures can be trusted. Second, measurement error can cause
many methodological artifacts. Consider, for example, that a researcher has conducted an intervention
study to increase WB. She is interested in whether there is a correlation between the WB scores before the
intervention started (pre-scores) and the change of the WB scores (WB after the intervention minus WB
scores before the intervention). She finds a negative correlation between the change scores and the prescores
and is very happy about this result, because this indicates that individuals with a low pre-test WB
score have profited more than individuals with a high pre-test score. However, this could be a pure
methodological artifact as it can be shown that measurement error decreases the true correlation between
the change scores and the scores before the intervention (Rogosa, 1995). Even if the true change scores and
the true pre-scores are unrelated, measurement error will produce a negative correlation and can lead to
wrong conclusions.
Table 1. Types of latent variable models (Bartholomew & Knott, 1999)
Latent variables
Observed variables Metrical Categorical
Categorical Latent trait models Latent class models
Also in quasi-experimental research, measurement error can produce serious artifacts. Consider the
evaluation of a WB intervention in which random assignment was not possible but participants assigned
themselves to the intervention vs. control groups. People being high in WB might have chosen the
intervention group more often because they are more active and more interested in WB issues. In this case
of self-selection, a researcher has to correct for group differences in the pretests in order to evaluate the
intervention appropriately. Assume that there is a positive (but not perfect) correlation between the
observed pre-test and the post-test scores and that each member of the control and the intervention shows
exactly the same increase of true WB scores (no treatment effect). If this study is analyzed by a regression
analysis with the independent variables pre-test and group there could be a significant effect of the group
factor indicating a treatment effect that would be an artifact caused by measurement error (Lord, 1967). It
is important to note that this effect does not show up if a repeated measures analysis of variance is applied.
This difference between the two analysis methods is called Lord’s paradox (Lord, 1967). Lord’s paradox
shows that even the regression coefficient of an independent variable in a regression analysis that is
measured without error (group membership: intervention vs. control group) can be distorted if the
measurement error of another independent variable (WB pre-test scores) is not appropriately corrected for.
These two examples demonstrate why it is important to correct for measurement error in WB research.
How Can Measurement Error Be Considered?
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In order to consider measurement error psychometric models are necessary. In general, four types of
psychometric models can be distinguished (Bartholomew & Knott, 1999, see Table 1). This distinction is
based on the type of observed variables (categorical vs. metrical) and the types of latent (error-free)
variables (categorical vs. metrical). Models with metrical latent variables are dimensional models whereas
models with categorical latent variables are typological models. In dimensional models, it is assumed that
individuals as well as items can be ordered on one (or more) continuous variables, whereas this ordering is
not necessary for typological models. The basic ideas of these types of models are explained with respect to
one simple representative of each type.
Latent Trait Models
In Figure 1a the one-parameter logistic test model (also called the Rasch model; Rasch, 1960) is
shown. This model is a model for dichotomous observed variables (items) measuring a continuous latent
variable. Consider the (hypothetical) example that participants rated their momentary WB using the three
items well, cheerful and happy and a two-category response format (no, yes). In the Rasch model, it is
assumed that the probability to choose the category yes depends on a value of an individual on a
continuous WB dimension (see Figure 1a). The higher the value of an individual on the WB dimension
(latent variable) the higher is the probability to choose the category yes. However, the probability will
never be perfectly 1 (or 0) because of measurement error. Because the probability of the response no is 1
minus the probability of the response yes, it is sufficient to consider only one response probability.
Individuals differing in their WB will differ in their values on the latent WB variable and can be ordered on
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the latent dimensions. These values are not known but can be estimated given their responses to all items.
Also, the items can be ordered on the latent dimension according to their difficulty. The item happy in
Figure 1a is more difficult than the item well because an individual needs to have a higher value on the
latent WB dimension to obtain a high probability for the category yes than it is the case for the item well.
The item cheerful is located on the latent WB between the two other items. An item difficulty parameter is
defined as the value of the latent WB dimension that is linked to a response probability of 0.50. These
difficulty parameters are not known but they can be estimated given the response patterns of the
participants. The Rasch model assumes that the curves describing the response probabilities as functions of
the latent WB dimension (so-called item characteristic curves) do not differ in their forms between items.
Moreover, the model assumes that the latent dimension explains the observed associations (correlations)
between the items perfectly (assumption of local independence): The items are correlated because they are
measuring the same construct (latent variable). Their correlations, however, are not perfect because of
measurement error. The assumption that the items are fulfilling the assumptions of a Rasch model can be
statistically tested and there are several ways to relax the assumptions of this model. For example, it can be
allowed that the item characteristic curves differ in their steepness by integrating a discrimination parameter
in the model (so-called two-parameter logistic model or Birnbaum model; Birnbaum, 1968). Dimensional
models for categorical response variables have been extended to more than two response categories. There
are special models for items with ordered response categories (for an overview, see Nering & Ostini, 2010;
Ostini & Nering, 2006). In the partial credit model, for example, there is a probability function for each
category of an item (category characteristic curve) that describes the probability to give a response in this
category as a function of the latent dimension (Masters, 1982). As the latent dimension is also called latent
trait, this family of models is called latent trait models. Because the item responses are modelled in these
models, they are also called models of item response theory. Latent trait model also exist for items with
unordered response categories (e.g., nominal scale model; Bock, 1972).
Latent Class Models
An important property of the model in Figure 1a is that all items and individuals can be ordered on
the same continuum. This implies, for example, that the item happy is more difficult than the item well for
all individuals and items. The assumption that all items and all individuals can be ordered on a common
latent dimension might not be appropriate for all individuals. Consider, for example, the assessment of
domain life satisfaction with the three items marriage, leisure activities, and job and a dichotomous
response format (satisfied, dissatisfied). Applying the Rasch model, for example, to these three items
would require that the three domains are ordered for all individuals in the same way. For example, the
ordering marriage, leisure activities, and job would imply that all individuals would have a higher
probability to be satisfied with their marriage than with their job or leisure activities. However, there might
be individuals being happier with their job than their marriage and their leisure activities, and other
configurations are possible. In areas of research where it is theoretically and/or empirically not possible to
order items on a dimension in a way that is obligatory for individuals, a typological model with a
categorical latent variable is more appropriate. Latent class analysis (LCA) is a typological model for
observed categorical variables (Lazarsfeld & Henry, 1968). In Figure 1b, a (hypothetical) latent class model
for the three satisfaction items and two latent classes is presented. LCA assumes that the whole population
consists of subpopulations (latent classes) that differ in the response probabilities for the categories of the
observed items. Each individual of the population has to belong to one, but only one latent class. The
number of latent classes is not known but can be estimated given the observed response patterns of
individuals. The membership of an individual is also not known but the probability of belonging to the
different classes can be estimated for each individual (assignment probabilities) and individuals can be
assigned to the latent class for which the assignment probability is maximum. All members of the same
latent class show the same response probabilities for the item categories. The members of different latent
classes differ in the profiles of their response probabilities. The latent class structure explains the
associations (correlations) between the observed items perfectly. That means that within each latent class
the items are independent and observed response differences between individuals belonging to the same
class are due to measurement error. In the model in Figure 1b, the first class is characterized by high
probabilities for being satisfied with marriage and leisure activities and for being dissatisfied with the job.
Class 2, on the other hand, is described by high probabilities for being satisfied with the job and dissatisfied
with marriage and leisure activities. Whether a latent class model fits the data and how many latent classes
are necessary can be statistically tested.
LCA can be easily extended to items with more than two categories. In the case of multiple
categories, the class-specific response probabilities are estimated for all categories of an item. LCA can
also be applied to items with ordered response categories (e.g., Rost, 1985). An overview of LCA and their
applications is given by Hagenaars and McCutcheon (2002). Similarities and differences between latent
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class and latent trait models are discussed by Heinen (1996). Figures 1a and 1b show important differences
between dimensional and typological models. These models have different areas of applications and a
researcher has to decide which type of model is more appropriate for analyzing the research question and
data structure considered.
Models of Factor Analysis
Models for metrical observed variables are based on the same principal ideas as the models for
categorical observed models. In dimensional models for metrical response variables the item characteristic
curves are not curvilinear such as in latent trait models (see Figure 1a), but linear. In Figure 1c the item
characteristic curves for three items and one latent dimension is presented. In this model, the (conditional)
expected value of an items is considered as a function of the latent dimension (factor). The deviations of
the observed values from the item characteristic curves are due to measurement error. The observed values
(not shown) scatter around the line (item characteristic curve). The models are called factor analytic models
or factor models (e.g., Bartholomew & Knott, 1999). These models are applied to metrical variables such as
scale scores or response times. The model in Figure 1c is a one-factor model. The straight lines (upper part
of Figure 1c) differ in their slopes (factor loadings). In this model, an observed variable is decomposed in
one part that is predicted by the latent dimension (factor) and measurement error. The measurement error
variables are assumed to be uncorrelated. This implies that the factor explains the correlations of the
observed variables perfectly. As in latent trait models, the observed variables (e.g., scales) are correlated
because they measure the same construct but they are not perfectly correlated because of measurement
error. Factor analytic models are often depicted as path models (lower part of Figure 1c) in which the latent
variable (factor) is shown as a circle or oval having an influence on the observed variables (squares). The
error variables are denoted by the letters E.
Latent Profile Analysis
Typological models for metrical observed variables are called latent profile models (Lazarsfeld &
Henry, 1968). Like in LCA it is assumed that the population consists of different subpopulations. The
subpopulations, however, differ in the profiles of the mean values of the metrical observed variables. If the
three domain satisfaction items were measured on a continuous scale, the result of a latent profile analysis
can look like the result in Figure 1d. The first class is characterized by high expected mean values on the
items marriage and leisure activities and a low expected mean on the item job, whereas it is the other way
around in Class 2. In classical latent profile analysis, it is assumed that the observed variables are normally
distributed in all latent classes and that the observed variables are independent within latent classes.
Other Models
The four models presented in Figure 1 are prototypical models. Over the last years, the development
of psychometric models have made enormous progress and it is possible to extend and to combine these
models in different ways. LCA has been combined with other statistical models to detect subpopulations
that differ in the parameters of a statistical model (so-called mixture distribution models, e. g., Hancock &
Samuelsen, 2008). For example, LCA can be combined with latent trait or with factor models to scrutinize
whether there are subpopulations differing in item difficulty parameters or factor loadings. Factor analytic
models have also been extended in such a way that different types of observed variables (e.g., metrical,
ordinal) can be simultaneously analyzed (e. g., Jöreskog & Moustaki, 2001).
Computer Programs
There are many computer programs available for analyzing latent variable models. There are also
several packages of the computer program R that can be downloaded at no charge from the internet. The R
internet page Psychometric Models and Methods (https://cran.r-project.org/web/views/Psychometrics.html)
gives an overview of currently available R packages for latent variable modeling.
How Can the Multidimensional Structure of WB Measures Be Modelled?
Well-being is a construct consisting of different components. For example, subjective well-being
(SWB) typically comprises the three constructs life satisfaction (LS), positive affect (PA), and negative
affect (NA). How distinct are these three constructs? Is it necessary to consider them all in an empirical
study? How can their relationships be explained? How can the information that is represented by the three
traits be combined to predict dependent variables such as health and longevity? To scrutinize these
important research questions the models presented in Figure 1 have to be extended to multidimensional
models. The basic structure of these models will be explained only for metrical observed and latent
variables [models of confirmatory factor analyses (CFA)] but the basic idea of these models can be
transferred to other variable types (for multidimensional IRT models see, for example, Deboeck & Wilson,
2004; Reckase, 2009; for models of CFA for ordinal variables see, for example, Jöreskog & Moustaki,
2001; for multidimensional LCA, see, for example, Hagenaars, 1993).
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Figure 2. a) Model with correlated factors; b) Bifactor (S-1) model; c) Bi-factor model; d) Model
with common independent factor; e) Model with formative well-being factor. Models of confirmatory
factor analysis for multidimensional data structures. Yik: observed variables, i: indicator, k: facet. λ:
loading parameters. Eik: residual (measurement error) variables. LS: life satisfaction, PA: positive
affect, NA: negative affect, WB: well-being, DV: dependent variable, IV: independent variable, -S:
specific factor.
In Figure 2a, a multidimensional model with three latent variables (factors) for the three facets of
SWB is depicted. For simplicity, only two observed variables (indicators) for each latent variable (factor)
are presented. This model allows for analyzing the latent correlation between the three factors. These
correlations are higher than the correlations between the observed variables because they are not distorted
by measurement error. This model allows (a) to test whether the non-perfect correlation between the
observed variables is only due to measurement error or whether the three facets are distinct, (b) to estimate
the degree of discriminant validity [indicated by a (low) correlation coefficient], and (c) whether the
different indicators are distinct indicators of the different latent variables (indicated by no cross-loadings).
The parameters of the model can be estimated and the goodness-of-fit of this model – as all other models in
Figure 2 – can be evaluated by statistical tests and fit indices that have been developed for structural
equation models (SEM; for an overview see Hoyle, 2012; Mulaik, 2009; Schumacker & Lomax, 2010).
Several computer programs have been developed for analyzing SEM. One of them is the publicly available
R-package lavaan (Beaujean, 2014; Rosseel, 2012) that can be downloaded at no charge from the internet.
If the different components are distinct, researchers are often interested in the specific part of a
component that is not shared with the other components. Moreover, the causes of these differences can be
analyzed, and it can be investigated whether the components have a unique contribution to predicting and
explaining other dependent variables. There are several ways to define a specific part of a component. One
way is to select one component as a reference component and to define the specific part of another
component as that part that cannot be predicted by the reference component. This approach is depicted in
Figure 2b. In the model in Figure 2b, the latent LS variable is taken as reference factor that predicts all
other observed variables. That latent part of PA that cannot be predicted by LS is represented by the
specific factor PA-S that is uncorrelated with the LS factor. The PA-S factor is a residual factor like a
residual in traditional regression analysis and can be interpreted accordingly. It always has a mean of 0. A
positive value of an individual on the PA-S factor indicates that this individual shows a higher PA than one
would expect given the LS of this individual. A negative value indicates that the person’s PA is lower than
is expected for a person with this latent LS score. An analog interpretation is true for the specific factor
NA-S. The correlation between PA-S and NA-S is a partial correlation. It indicates that part of the
association between PA-S and NA-S that is not due to LS. The variance explained by the LS factor and the
specific factors can be compared. The proportion of variance of an observed variable by a factor (that is
uncorrelated with another one) equals the squared factor loading. The sum of the two squared factor
loadings equals the reliability of an observed variable in the model in Figure 1b. The larger the explained
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variance by a specific factor compared to the explained variance by the LS factor the larger is the
component specificity. The partial correlation is 0 if LS explains the total correlation between PA-S and
NA-S. The model depicted in Figure 2b is called bifactor-( S-1) model and is described in detail by Eid,
Geiser, Koch and Heene (2016).
If a specific factor had been defined for the indicators of the LS factor in Figure 2b, and if it had been
additionally assumed that all specific factors are uncorrelated, the model is called bi-factor model (see
Figure 2c; Holzinger & Swineford, 1937). The factor on the left-hand side would then not be the LS factor
but a general factor (G factor). In the case of components of a construct that are not interchangeable, the
application of the bi-factor model usually produces problematic results and the meaning of the G factor is
not well defined (see Eid et al., 2016, for a deeper discussion). The components of a construct, however,
are usually not interchangeable (LS is theoretically a different construct than PA and NA), and, therefore,
the bi-factor might not be appropriate for these types of applications.
The LS factor and the specific factors in Figure 2b can be correlated with other variables in an
extended model (not shown here). They can also be modelled as independent and dependent variables in a
latent regression analysis. If specific factors are taken as dependent variables in a regression analysis some
arrangements (e.g., transformations) have to be made to avoid methodological artifacts (see Koch,
Holtmann, Bohn, & Eid, in press, for a detailed discussion and some guidelines).
A second way to define specific factors is to regress all observed variables of SWB on another
independent variable (IV) as it is done in Figure 2d. Then, residual factors for all facets of SWB can be
defined indicating that part of a SWB facet that is not predicted by the IV. The values of the specific
factors and their correlations have a similar meaning as in the model presented in Figure 2b. Assume, for
example, that the IV in Figure 2c is flourishing. A positive value of LS-S would then indicate that the LS of
this person is higher than one expects for a person having such a flourishing score. Also in this model the
variance explained by the IV (flourishing) and by the specific factors can be compared to get a measure of
the degree of facets specificity. If the facet specificities in Figure 2d were large, this would indicate that
flourishing and SWB are quite different constructs.
In some studies, researchers are interested in combing the different facets to a general SWB score to
predict a dependent variable (DV) such as health or income. In Figure 2e such a model is presented. In this
model, the general WB factor is a linear combination of the three facets. This makes it necessary to fix the
variance of the residual of the WB factor in the latent regression to 0. Such a measurement model is called a
formative measurement model (e.g., Willoughby, Holochwost, Blanton, & Blair, 2014). An alternative is a
reflective measurement model of a general WB factor such as the bi-factor model (Figure 2c). To define a
general WB factor in a formative measurement model it is necessary that there is a dependent variable in the
model that is regressed on the WB factor. Defining a general WB factor in such a formative measurement
model has several advantages compared to a general factor in the bi-factor model. First, the bi-factor model
causes many application problems in typical application areas of psychology because it is misspecified for
the construct that are typically considered in multidimensional models (Eid et al., 2016). Second, the WB
factor in Figure 2e is always the best combination of the three facets LS, PA and NA for the DV considered.
That means that the meaning of the WB factor changes with changing DV. PA might, for example, having a
stronger impact on WB than NA when predicting creativity, whereas NA might have a stronger influence
on WB than PA when predicting reasoning tasks. Although formative factors are rare compared to reflective
factors in psychology, they are promising for future WB research.
How Can Method Effects Be Measured?
The most widely used assessment method in research on WB is self-report. WB refers to the inner
state of an individual and the individual is the person that might best know her or his WB. However, are
self-reports valid? Are there other assessment methods that provide important information about the WB of
an individual that goes beyond self-report? There are many studies on the validity of self-reports that are
summarized in Chapter 5 of this volume and their results will not be reiterated here. One important strategy
in validity research is to apply different methods and to analyze their convergent validity (Campbell &
Fiske, 1959). These multimethod studies typically show that there are strong method effects. Methods
effects, however, are not the “serpent in the psychologist’s Eden” (Cronbach, 1995, p. 145) but they
represent important substantive effects. Validity research typically focus on estimating the convergent
validity but not on understanding method effects. For example, peer ratings of WB are used to analyze
their correlation with self-reports but there is less research on the question why peer reports of WB differ
from self-reports. In order to get a deeper understanding of the results of WB research, method effects have
to be understood. How can method effects be analyzed? In recent research on method effects two types of
latent variable models are distinguished that define method effects in a different way (Eid, Geiser, & Koch,
2016). These models are the models presented in Figure 2b and Figure 2c for multidimensional data
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structures. These models can be applied to multimethod research by replacing the different facets by
different methods. The first model (Figure 2b) is appropriate for structurally different methods, whereas the
second model (Figure 2c) is appropriate for interchangeable methods (Eid, Geiser, & Koch, 2016). The
difference between these two types of methods can be explained with respect to multiple rater studies.
Multiple raters can be considered as multiple methods (Kenny, 1995). Interchangeable raters stem from the
same population of raters, for example, different peers rating a common friend, or different students rating
the same teacher. Structurally different methods do not stem from the same population. For example, if the
WB of a child is measured by a self-report, a parent report and a teacher report, the self, parent, and teacher
do not stem from the same population of interchangeable raters, they have different social roles and
experience the child in quite different contexts. Other examples of structural different methods are
observational methods, physiological measures, reaction time measures, etc. (see Eid et al., 2008; Koch,
Eid, & Lochner, in press, for a deeper discussion of these differences and their implications for modeling
multimethod data). In the multimethod model in Figure 2b a reference method (e.g., the child self-report) is
selected and contrasted with the other methods (e.g., parent report, teacher report). The method factors have
a similar meaning as the facet-specific factors. A method factor represents the over- vs. underestimation of
trait with respect to the value expected based on the reference method (e.g., self-report). The correlation
between two method factors shows whether two methods have something in common (e.g., common view
of different raters) that is not shared with the reference method. In the multimethod model in Figure 2c
there is a common factor underlying all interchangeable methods. If the three methods considered are, for
example, three peer ratings (three friends of a target) and the peers are randomly assigned to three groups,
the general factor measures the expected trait value of a target across all interchangeable raters. The
method factor represents the deviation of the single raters from the expected values across all raters, that
means, it represents the rater-specific view. Because the raters are interchangeable and nested within targets
the three method factors are uncorrelated (Nussbeck, Eid, Geiser, Courvoisier, & Lischetzke, 2009). In the
two models presented in Figure 2b und 2c, the variance explained by the factor on the left hand side
(squared standardized loadings of the general factor having an influence on all observed variables) is a
measure of convergent validity, whereas the variance explained by the method factors (squared
standardized method factor loadings) is a measure of method specificity. The general factor and the method
factors of the models can be related to other variables to explain individual trait differences and method
effects. The models presented in Figure 2d and 2e can also be applied in multimethod studies in order to
explain the convergence of different methods (Figure 2d) and to combine different methods (e.g., different
raters and/or different physiological variables) for predicting a dependent variable (e.g., health) in an
optimal way (Figure 2e).
The multimethod models in Figure 2b and 2c can be extended to multitrait-multimethod (MTMM)
models to estimate not only the convergent but also the discriminant validity (see Eid et al., 2008; Koch et
al., in press). A guide to more complex multimethod models is given by Eid, Geiser and Koch (2016).
MTMM models for ordinal variables are presented by Nussbeck, Eid and Lischetzke (2006), LCA MTMM
models are discussed by Nussbeck and Eid (2015) as well as Oberski, Hagenaars and Saris (2015).
How Can Change in WB Be Measured?
In the analysis of change two general change concepts are considered – variability and change in the
narrow sense (Nesselroade, 1991). Whereas variability refers to reversible short-term fluctuations, change
in the narrow sense characterizes change processes that are more long lasting and less reversible
(Nesselroade, 1991). The variability of WB measures is often analyzed in a state-trait model of WB.
Momentary WB states are considered as fluctuations around a stable WB trait (habitual WB level, set-point,
well-being trait, e.g., Eid & Diener, 2004). Several studies have shown that intraindividual variability itself
can be considered a personality trait as individuals differ in stable way in the variability of their well-being
states (e.g., Eid & Diener, 1999).
Examples of change in the narrow senses are developmental processes and trait changes caused, for
example, by interventions. The variability of WB states is often analyzed in longitudinal studies comprising
many repeated measurements in a relatively short period. Change processes in the narrow sense are often
analyzed with larger time lags between repeated measurements and long time periods. However, variability
and change (in the narrow sense) are not totally distinct processes, and it might be the more typical case
that they overlap. Even the measurement of stable personality traits take place in specific situations that
might cause a certain degree of variability (Deinzer et al., 1995; Eid & Diener, 2004). How can both types
of change be measured and separated from change due to unsystematic measurement error? Over the last
years, the development of latent variable models for analyzing change has been a major topic of
psychometric research and not all models can be presented (for an overview see, for example, Collins &
Sayer, 2001; Eid & Kutscher, 2014; Laursen, Little, & Card, 2012; Little, 2013; McArdle & Nesselroade,
2014; Mehl & Conner, 2012; Molenaar, Lerner, & Newell, 2014; Newsom, 2015; Singer & Willet, 2003).
114
Instead of presenting different models for specific purposes, the basic principles of latent change modeling
will be presented with respect to a very general longitudinal model for analyzing variability and change
(see Figure 3a) that contains various longitudinal models as special cases (Eid, Courvoisier, & Lischetzke,
2012). This model is a combination of latent growth curve models (Bollen & Curran, 2004; 2006; Curran &
Bollen, 2001; Duncan, Duncan, & Strycker, 2006) with latent state-trait models (Cole, Martin, & Steiger,
2005; Eid & Hoffmann, 1998; Steyer, Mayer, Geiser, & Cole, 2015).
a)
b)
Figure 3. a) Path model; b) Model for two individuals A and B and one period of time. The colors
correspond to the colors and variables in figure a).
General longitudinal model. Yikp: observed variables, i: indicator, k: occasion of measurement, p:
period. λikp, λIikp: loading parameters. Eikp: residual (measurement error variables). Ip: intercept
factor, Lp: slope factor, Skp: latent state variable; Rkp: occasions-specific residual, Ukp: occasionspecifc
residual indicating unpredictability. βk(k-1)p: autoregressive parameter. For reasons of clarity
not all parameter labels are included.
115
The model presented is a model for two time periods, for example, the periods before and after an
intervention or for two days of an experience sampling study. The model can easily be extended to more
than two time periods. Within each time period, there are multiple repeated measurements. For each
occasion of measurement there are two indicators of a latent state variable Skp characterizing the true WB
state on an occasion of measurement k in a period p. On the level of the latent state variables a latent
growth curve structure with a linear trend is specified. According to the linear growth model, the state
change of each individual can be characterized by a linear trend. The basic idea of this model for two
individuals is depicted in Figure 3b. The intercept and the slope of the linear trend can differ between
individuals. The individual intercept is a value of the latent intercept factor Ip. The larger the variance of
this factor, the larger are individual differences in the intercepts. The mean value of the intercept factor
represents the mean slope of the change process. The individual slopes are values of the slope factor Lp. A
large variance indicates large differences in the linear trends. The mean value of this factor is the mean
slope across all individual slopes. If the variance and the mean of the slope factor are 0, there is no linear
trend in the data and the growth factor can be removed. In this case, the model reduces to a so-called latent
state-trait model with autoregressive effects (Cole et al., 2005; Eid, Holtmann, Santangelo, & EbnerPriemer,
2017). The intercept factor is then the trait factor characterizing the individual WB level over time.
The linear curves do not perfectly determine the change of the state variables because there are residual
variables Rkp. These residuals indicate momentary deviations from the linear trend (or in the case without a
linear trend from the latent trait) are due to occasion-specific influences. In addition, there are
autoregressive effects on the level of residuals. These effects represent the inertia of the change process
(carry-over effects between two neighboring occasions of measurement. To test the hypothesis that the
autoregressive process is time homogeneous the autoregressive parameters can be set equal within and
between periods. Fixing the autoregressive parameters also helps to avoid estimation problems. The
residual variables (UPkp in Figure 3a) indicate that part of a momentary latent WB state variable that is
unpredictable by the intercept and slope factors as well as the state variables measured before. Finally,
there is an indicator-specific factor in the model on which the second indicators load. Such a factor is often
necessary because the two indicators are not perfectly homogenous (unidimensional). Like in the
multidimensional model in Figure 2b the number of indicators is one less than the number of indicators
considered (Eid, Schneider, & Schwenkmezger, 1999). If there are more than two indicators and, therefore,
more than two indicator factors within a period they can be correlated within and between periods. If the
indicators are unidimensional with respect to the latent state variable indicator-specific factors are not
necessary. In the case of unidimensionality the assumption of indicator-specific factors can cause
estimation problems (because they are not necessary and do not have substantive variance). Therefore,
researchers can start with a model without indicator-specific factors and add them if they are necessary
because a model without them does not fit the data.
Mean stability and mean change between periods can be analyzed with respect to the period-specific
intercept and slope factors. For example, after a WB intervention the mean values of the intercept factor
can differ indicating that the intervention might have changed the general WB level. A change of the mean
values of the slope factor would indicate that the intervention might have changed the developmental
process. For WB research, a model without linear change model might be the more typical model because
of adaptation processes that preclude a linear change. Therefore, stability and change of WB might be well
represented by a state-trait model (Eid & Diener, 2004).
Measurement Invariance
In longitudinal studies, different types of measurement invariance over time can be considered
(Millsap, 2011). Measurement invariance (MI) concerns the question whether the same WB states are
measured or whether there is a structural change in the link between the latent and observed variables
showing that the psychometric meaning of the WB measures has changed. The lowest level of MI is
configural invariance. That means that the number of latent variables do not differ between occasions of
measurement and time periods. Weak MI additionally assumes that the values of the loading parameters of
the latent variables do not differ between occasions of measurement and time periods. Weak MI is
necessary if one wants to relate the latent variables to other variables in extended models and to make sure
that the structurally the same WB factors are measured on each occasion of measurement. Strong MI
additionally requires that the intercepts of an observed variable do not change over time. The intercepts are
not shown in the path models presented in this chapter. Intercepts are additional constants that are specific
to an observed variable and mainly determine the mean value of the observed variables. Strong MI is
required when one wants to compare latent means over time, e.g., the means of the intercept factors before
and after an intervention. If strong MI is not given this would indicate that mean change was indicator
specific and is not well-captured by the means of the latent variables. Strict MI would additionally assume
116
that the variances of the error variables do not change over time. This is not required for relating latent
variables to other variables or testing for mean differences but it is interesting to see whether the quality of
WB measurements changes over time. Often it is also assumed that the autoregressive process is timeinvariant
with non-changing autoregressive parameters and residuals of the UP variables over time.
The measurement model that is shown for one construct in Figure 3a can be extended by including
other variables. For example, if there are multiple constructs, a measurement model can be specified for
each construct and the mutual influences of the variables over time can be analyzed (e.g., Wickrama, Lee,
O’Neal, & Lorenz, 2016). The model in Figure 3 assumes that the time lag between the occasions of
measurements is the same between all occasions and for all individuals. This assumption might be violated,
for example, in experience sampling studies in which occasions of measurements are individually selected.
In such studies, the loadings of the intercepts and the autoregressive parameters have to consider these
individual differences in time lags (Eid et al., 2012). This can be done, for example, in the context of
dynamic structural equation modeling (Driver, Oud, & Voelkle, 2017; Asparouhov, Hamaker, & Muthen,
2017).
How Can These Models Be Extended to Analyze Multiple Groups?
The models presented assume that a sample of individuals was randomly drawn from a population.
In WB research, the sampling process is sometimes more complex. Often, it is of interest to analyze
different groups, for example, nations, intervention groups, schools, companies, etc. There are two ways to
consider group differences – multigroup and multilevel analysis. In multigroup analyses different groups
are selected because the researcher is interested in exactly these groups. In a replication of a study, a
researcher would select samples exactly from the same groups. For example, the researcher might be
interested in comparing women and men, China and the US, or an intervention with a control group. In this
case, multigroup analysis is appropriate. In multigroup analysis a latent variable model is specified in each
group and several hypotheses about between group differences with respect to the parameters of a model
(e.g., factorial structure, mean differences, regression parameters) can be tested. The models considered in
this chapter can be easily extended to multigroup analysis (e.g., Bock & Zimowski, 1997; Brown, 2015;
Eid, Langeheine, & Diener, 2003). If there are many groups testing assumptions across groups (e.g., testing
measurement invariance across many nations) can become very cumbersome. In this case, recent
developments of methods for analyzing many groups can be applied (for an overview and comparison of
different approaches see Kim, Cao, Wang, & Nguyen, 2017).
In multilevel analysis, it is assumed that the groups themselves are randomly selected from a
population of groups. For example, a WB researcher might be interested in work satisfaction and randomly
select different companies (level-2 units) and employees within companies (level 1 units). The level-2
units are considered interchangeable. In a replication of such a study, the researcher would get a different
sample of level-2 units. Like in multigroup analysis, the level-2 units can differ in the parameters of a
model. In addition to multigroup analysis, however, the variations of the parameters between groups can be
explained by other variables. Because the level-2 units are randomly selected, the parameters of the model
have a distribution. It can be estimated how strong the variation of parameters is and to which degree level-
2 differences in the parameters can be predicted by other level-2 variables (e.g., the organizational climate
of a company). Multilevel extensions have been developed for the different types of psychometric models
in Table 1 (e.g., Adams, Wilson, & Wu, 1997; Heck & Thomas, 2015; Skrondal & Rabe-Hesketh, 2014;
Tay, Diener, Drasgow, & Vermunt, 2011; Vermunt, 2003; 2008).
Multigroup and multilevel analyses require that the group membership of an individual is known. If a
researcher has the hypothesis that the parameter of a model differ between subgroups but the subgroups are
not known, latent class analysis can be combined with the models presented so far resulting in mixture
distribution models (e.g., Hancock & Samuelsen, 2008). For example, latent variable models of
longitudinal research can be extended to latent growth mixture models (Wickrama et al., 2016) or mixture
distribution latent state-trait models (Courvoisier, Eid, & Nussbeck, 2007) to detect population
heterogeneity with respect to the change process (e.g. degree of variability, mean growth rates).
Conclusion
Latent variable models enable the estimation of unsystematic measurement error from systematic
sources of WB differences. This allows avoiding methodological artifacts and estimation biases that are
caused by measurement error. They also enable researcher testing theories about the measurement of WB as
well as its causes and consequences in a sophisticated way. Latent variable models have been developed
for different areas of application and can be combined and extended in manifold ways to fulfill the needs of
empirical WB research.
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Qualitative Approaches to Culture and Well-Being
By Neil Thin, University of Edinburgh
Citation
Thin, N. (2018). Qualitative approaches to culture and well-being. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
This chapter explores the distinct contributions of qualitative wellbeing research in relation to quantitative
research, and particularly concerning the many ways in which wellbeing phenomena are ‘cultural’. The
core contribution of qualitative approaches has been to highlight a ‘constructivist’ perspective, depicting
wellbeing not as a quantifiable essence but as a diverse, fluid, and elusive set of feelings and evaluations.
These meanings emerge from interactions among people, and between them and cultural resources.
Qualitative research is part of that construction process, not just a tool for extracting data. Its value may lie
more in the process - facilitating important conversations and debates - than in particular findings.
Keywords: Qualitative; wellbeing; happiness; culture; ethnography; humanistic; scientism; methodological
pluralism; mixed methods; social constructivism; narrative wellbeing; compositional wellbeing
Wellbeing is a Qualitative Cultural Process
Shortly before the rapid rise of happiness studies, the human geographer Yi-fu Tuan wrote that
‘culture makes it possible for people to be pleased with themselves: that is in fact one of its principal
functions’ (1986, p. 1). Since both society and culture are often blamed for many kinds of injustice and
suffering, Tuan’s observation offers a crucial corrective to pathologism. But in what ways are people
‘pleased with themselves’. Pleased relative to what or whom? Based on what criteria or reasoning? How
can we tell? And is this really a matter of ‘fact’ at all, let alone one generalisable across all cultures? Does
Tuan’s elegant but seemingly ad hoc presentation of evidence warrant such confidence?
Wellbeing research is now proliferating at an astonishing rate, becoming more multi-disciplinary,
more multi-cultural, and more diverse in its methods and approaches. At the same time, general publics,
administrators, employers, planners, and professional wellbeing promoters are engaging more explicitly
than ever before in public discussions about wellbeing worldwide, increasingly blurring the divisions
between scholarly research and public learning. At the same time, the kinds of clear and confident findings
produced by quantitative wellbeing research are increasingly being complemented by a diversity of
qualitative research approaches, most of which raise questions, stoke conversations, and provide
impressions and vignettes rather than confident findings. This makes it both increasingly important and
increasingly difficult to synthesise practicable lessons from wellbeing research around the world.
All wellbeing scholarship is mainly based on qualitative enquiry, and all the disciplines involved including
psychology and economics which are now mainly known as ‘quantitative’ and ‘positivistic’
disciplines - were constituted from qualitative research. But wellbeing scholarship, like most forms of
humanistic or anthropological study, has often sought public esteem as a ‘science’ by displaying signals of
rigorous control, expert detachment, and reduction of the objects of study to numerical representations of
reality. In late 20th century the rapid rise to prominence of happiness scholarship and positive psychology
was almost entirely unconnected to the ‘qualitative revolution’ (Camic, Rhodes, Yardley, & Bamberg,
2003; Wertz, 2011) that was belatedly spreading through psychology.
Nonetheless, qualitative enquiry also constitutes a socio-political and cultural movement (Wertz,
2011; p. 93). This movement has in common with happiness research a strong desire to promote empathy
across cultural and bureaucratic divisions, empowering people to articulate their own views on their own
wellbeing. Unfortunately, disciplines like sociology and anthropology with long histories of qualitative
research remained until recently oblivious to the wellbeing revolution that was sweeping through
psychology and economics (Thin, 2005; Veenhoven, 2006; Bartram, 2012). The same has been
paradoxically true of ‘liberation psychology’, which has explored cultural diversity, qualitative research,
and empowerment but from an entirely pathological perspective (Watkins & Shulman, 2008).
In wellbeing research, sometimes the push towards scientific rigour and quantification have resulted
in implausible pseudo-scientific claims concerning factual knowledge about elusive phenomena such as
‘meaning’ or ‘spirituality’ or ‘positivity’ that clearly aren’t matters of fact (Sink, 2000; Mathews &
Izquierdo, 2008a, p. 9; and see e.g. the 2013 critique by Brown, Sokal, and Friedman of Fredrickson and
Losada’s ‘positivity ratio’ paper, 2005). In quantitative wellbeing research, sophisticated and fine-grained
statistical techniques are commonly based on extremely blunt labels and fragile distinctions, such as those
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between ‘affective’ and ‘cognitive’ wellbeing, or between ‘hedonic’ and ‘eudaimonic’ wellbeing for
example (in real life, it isn’t actually possible to separate feelings from thoughts, or pleasures from
evaluations). Scientism in wellbeing research has also led to the neglect or denigration of qualitative or
participatory research. Insofar as expert-led approaches exclude citizens as active learners, the wellbeing
research movement may be missing opportunities for scholars to promote wellbeing directly through
inclusive collaboration (Gergen, Josselson, & Freeman, 2015).
Happiness surveys, which have produced important new understanding and - perhaps more
importantly - have captured the imaginations of publics and politicians worldwide, epitomise the
quantitative or ‘positivistic’ approach. Just as economists have since the 1930s persuaded people to believe
in ‘the economy’ as if it were a measurable thing, so quantitative happiness scholars are now persuading us
to imagine happiness as measurable entity that ebbs and flows at national level.
Qualitative researchers, by contrast, emphasise that it cannot be ‘scientific’ to apply more precision or
control than the subject-matter warrants. Their main contribution to the rapid growth and popularisation of
wellbeing scholarship has been to strengthen recognition of both the potential but also the limits of
systematic enquiry into ultimately elusive and partly ineffable experiences. A related contribution has been
the ‘cultural turn’, highlighting the many uncertainties about wellbeing that derive from its dependence on
culturally diverse forms of expression. Qualitative research de-emphasises the question of ‘how happy’
people say they are, and instead explores how people are happy, and how people think about and pursue
happiness (Kavedžija & Walker, 2017). It invites respondents to consider their own explanations and
experiences of various aspects of wellbeing, rather than extracting from them the inevitably artificial and
simplified answers that survey questions elicit.
Institutionalised downplaying or denigration of qualitative enquiry has been one of the most
disappointing aspects of happiness scholarship and positive psychology so far (Rich, 2017; Hefferon &
Boniwell, 2011; Gergen, Josselson, & Freeman, 2015). Lack of systematic attention to qualitative
dimensions of research is all the more surprising because wellbeing is primarily a qualitative and a cultural
concept. It signals evaluation and appreciation of how well people live. Most of the qualities implied are
cultural (they are conceived, produced, expressed, and expressed through culturally patterned terms and
idioms), interactive (they are produced and understood through interactions among people, not just by and
through individuals), contextually intertwined (inseparable from their physical and cultural lifeworlds) and
processual (they are dynamic, constantly changing as we observe and comment on them). When we judge
ourselves or someone else to be living well, we invoke cultural values and scripts, we discuss those with
other people, and those discussions influence the experience of wellbeing. Qualitative enquiry into
wellbeing mimics and intensifies the enquiries that all humans do everywhere.
The near-synonym ‘quality of life’ makes this qualitative assessment explicit: we want to know what
life is like for people, not just how long they live or how ‘high’ they would rate their temporary feelings or
self-evaluations. Surprisingly, however, most research on wellbeing or quality of life has emphasised
quantification, sometimes at the expense of robust qualitative analysis. Some statistics are relevant to this
appraisal in relatively unproblematic ways - longevity, morbidity rates, suicide and murder rates, for
example. Other statistics, such as those relating to happiness, cultural values, and poverty, are useful but
endlessly debatable. To appreciate their relevance and validity in wellbeing assessment, we need richly
qualitative investigations and analyses.
Unlike concepts such as ‘longevity’, ‘morbidity’, and ‘living standards’, which imply quantitative and
factual comparisons, both wellbeing and ‘quality of life’ imply mainly qualitative assessment. The elusive,
qualitative nature of wellbeing scholarship becomes particularly clear when we focus on happiness. This
term, for which the more scholarly term ‘Subjective Well-being’ (SWB) is a synonym, refers to
‘subjective’ or ‘inside-out’ appreciation of life as a whole. In research on wellbeing, the more emphasis
there is on a) subjectivity and b) interactions between personal and collective wellbeing, the more elusive
and provisional our findings become. Qualitative approaches are crucial because many important features
of the things being assessed (opinions, self-evaluations, self-expressions) are highly uncertain and subject
to interactive and situational variation.
Looking at wellbeing research over the past half century or so, we can observe four kinds of bias that
have restricted its usefulness and scope, but which conscious application of diverse qualitative approaches
to culture and wellbeing could rectify:
Scientism: most of the journals specialising in wellbeing have mainly published work by scholars
working mainly within ‘positivist,’ experimental, and/or quantificatory traditions that privilege facts
and numbers over more ‘humanistic’ or ‘interpretivist’ approaches emphasising qualitative
exploration and analysis (Michalos, 2004; Thin, 2014). Arguably, this has produced a research
tradition that steers our attention towards indicators (e.g. national ‘levels’ of self-reported happiness)
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rather than the phenomena themselves (the experienced qualities of people’s lives).
Western ethnocentrism: the subjects of wellbeing research have been disproportionately from
wealthier and particularly ‘western’ populations, with consequent risks of cultural bias (Christopher,
1999); it remains worryingly common for North American or British researchers to use the phrase
‘our culture’ on the assumption that all their readers are culturally homogeneous.
Oversimplification of crosscultural contrasts: insofar as researchers have tried to diversify the
cultural backgrounds of research subjects, too much of the crosscultural research has been based on
two naïve assumptions: that regional and international comparisons are the most interesting and
important forms of cultural contrast; and that such comparisons can be well represented by surveying
student populations (Oyserman, Sorensen, Reber, & Chen, 2009; Mathews, 2012; Tsai & Park,
2014).
Qualitative pathologism: insofar as qualitative researchers have explicitly addressed wellbeing
themes, they have predominantly done so through a pathological lens. Even the texts they have
labelled ‘wellbeing’ have tended to be mainly about illbeing (Thin, 2005, 2018).
Although these shortcomings are important and problematic, this chapter will demonstrate that many
able researchers have successfully adopted qualitative and approaches to exploring interactions between
culture and wellbeing. It is also true, although not explored here in any detail, that many primarily
‘quantitative’ researchers have drawn significant inspiration from qualitative research, and have done a
great deal to bridge the unhelpful ‘qual-quant’ cultural divide.
What is Qualitative Research?
There are two different senses in which wellbeing research can be ‘qualitative’. First, all wellbeing
research is ‘qualitative’ insofar as it relies heavily on careful consideration of the many qualities involved
in wellbeing assessment and of the interactions between them. For example, ‘good’ emotional quality
might mean excitement or calm, or it might be about relations between contrasting emotions through the
day or through the life course. Even so-called ‘quantitative’ researchers in practice put their most
significant efforts into qualitative thinking, and many confess that even the most sophisticated quantitative
methods are more art than science. It is therefore extremely unhelpful to take sides in the so-called
‘paradigm wars’ between quantitative and qualitative research, or to draw a stark division between
‘qualitative’ and ‘quantitative’ research. Careful scholars instead consider a variety of qualitative aspects of
all wellbeing research.
Second, the term ‘qualitative approaches’ more typically refers residually to those scholars who don’t
emphasise tight scientific control or the use of numbers in their pursuit of wisdom. Methods and analytical
approaches used by scholars working with the ‘qualitative’ tradition are extremely diverse, emphasising for
example interpretation, personal experience, debate, linguistic analysis, everyday in situ observation, and
story-telling as the routes to knowledge. This chapter follows mainly this second way of thinking, on the
understanding that other chapters here have much to say about qualitative aspects of more controlled
‘scientific’ research on wellbeing.
Although we should appreciate the many values of qualitative research, it is also important to be aware
of its limitations. For example, narratives and opinions can be biased, and in-depth qualitative interactions
such as open-ended interviews and focus groups tend to reach very small samples compared to the
representative samples reached by structured questionnaire surveys. And the kinds of ‘findings’ revealed
through qualitative analysis tend to be much less clear and confident than the factual findings from
experiments and statistical analyses. In addition, insofar as there remain significant gender differences in
methodological preference, both quantitative (‘masculine’) and qualitative (‘feminine’) research traditions
are prone to different kinds of gender bias (Oakley, 2000; Järviluoma, Moisala, & Vilkko, 2004).
A problem for anyone trying to consider qualitative methods as a system is that in some disciplines,
particularly those that welcome both ‘social science’ and ‘humanities’ approaches to research, remarkably
little is said or taught about methods or systems. In social and cultural anthropology, for example, an
‘anything-goes’ approach applies equally to the development of questions, empirical field research,
secondary research, literature reviews, data analysis, and writing up. Ask a sociocultural anthropologist
what their ‘hypothesis’ is and they will tend to respond with bafflement or laughter. Without hypotheses,
anthropologists can proceed iteratively and flexibly, but they are unlikely to develop a clear rationale for
how they manage different parts of their research effort. As the entry on ‘methodology’ in a popular
anthropological encyclopedia puts it:
Methodology is not a popular concern in anthropology …few researchers actually know any methods for
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collecting information, beyond hanging around with the folks and trying to figure out what is going on.
(Salzman 2010, p. 464)
Few anthropologists, even those trying to promote public use of their work, even pause to discuss
whether their assertions are ‘evidence-based’ (Liebow et al., 2013). ‘Method,’ for anthropologists, amounts
to being reasonably thorough and multidisciplinary in doing secondary research; being a good listener and
being interactive and observant during fieldwork; and writing up in honest and humanistic ways that bring
real lives and cultural diversities to the fore. While considerable gains can be made from so much flexibility
and reliance on individuals’ common sense, this makes it extremely hard to judge the quality of research
design, the thoroughness and rationale of secondary research, and the quality of data and validity of
interpretations.
Everything humans do is cultural, and all research on wellbeing is ‘qualitative’ insofar as it is based
on observations and analysis of qualities. We will focus here on the distinctive contributions of research
labelled as both ‘qualitative’ and ‘cultural’. Although in theory this might apply to all research, in practice
research is called ‘qualitative’ when it doesn’t make substantial use of either quantification or positivistic
experimental hypothesis-testing, and it is labelled ‘cultural’ when it pays explicit heed to patterned and
shared learning associated with a distinct population or activity. ‘Qualitative’ research tends to emphasise
exploration and interpretation rather than positive proof, and to employ methods such as participant
observation, discursive interviews, life narratives, secondary data analysis, and focus groups. ‘Cultural’
research may be about one particular cultural context (e.g. a North American school, a Korean business,
and African Church), or a religion, or an Internet space, or a community or nation. Or it may be about
broad crosscultural comparisons, such as Asia versus Europe.
This chapter will also focus on ‘happiness’, used here as a flexible term for the subjective experience
and evaluative interpretation of wellbeing. Though nowadays mainly associated with personal enjoyment
and positive self-evaluation, happiness does still retain broader meanings that were more emphasised in the
past, including the goodness and admirability of a person’s whole life. It is in common usage a synonym
for ‘subjective wellbeing’, though it can also quite reasonably serve as an extended synonym for ‘quality of
life’ and for ‘wellbeing’.
Purposes and Approaches of Qualitative Wellbeing Research
Figure 1 provides a thumbnail sketch situating the main focus of this chapter - empirical qualitative
research on wellbeing - within the broader encompassing categories of nonquantitative wellbeing
scholarship, wellbeing scholarship in general (all of which is mainly based on a substantial degree of
‘qualitative’ inquiry, analysis and theorising), and the broader public discourse on wellbeing (whose
boundary with ‘academic research’ is often blurred).
Figure 1: Varieties of qualitative learning about wellbeing
Qualitative approaches are a residual academic category that is in various ways contrasted with the
kinds of approach that emphasise hypothesis-testing and scientific rigour through either experimental or
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survey-based quantification. These are loose categories and many researchers would be unhappy to be
assigned to one camp or another. Even those who have some sympathy with seemingly anti-scientific
attitudes of the ‘postmodernist’ movement and who emphasise interpretive or narrative approaches also
consider their research to be empirical, and think of themselves as scientific realists.
Summarising the key arenas of debates between scientific modernists and postmodernism, Susen
(2015, p. 2) argues that there are three fault lines: truth versus perspective; certainty versus uncertainty;
and universality versus particularity. Referring these contrasts to wellbeing scholarship, we can usefully
outline the core assumptions or beliefs of scholars subscribing to qualitative-interpretive and/or
postmodernist approaches to learning about wellbeing:
truth versus perspective: many of the important things worth learning about wellbeing are a matter
of personal or cultural perspective rather than universal factual truth
certainty versus uncertainty: many of the important things about wellbeing are highly elusive and
uncertain
universality versus particularity: many of the important things about wellbeing aren’t universal
truths or universal values, but relate to particular situations, conditions, or places
Biological wellbeing - health and longevity - can be fairly adequately represented as facts and
captured in statistics. Subjective wellbeing - overall happiness, life satisfaction, self-esteem, or satisfactions
with particular domains of life such as home, leisure, and work - is far too complex to reduce to factual
representation. SWB statistics are useful, but they are facts about utterances and opinions, not hard facts
about the real world. Quantitative research also plays key roles in fostering clear definitions of concepts,
and analytical rigour in the development of causal theories. Still, the numbers only make sense in
combination with a lot of qualitative analysis.
To appreciate the distinct value of qualitative research, the first requirement is to recognize that it has
purposes that tend to be very different from the purposes of statistical or experimental research. Qualitative
scholarship tends to be more about ‘thinking or talking things through’ than about ‘finding things out’.
Summarising qualitative research purposes, it has been argued that they aim ‘to describe and possibly
explain events and experiences, but never to predict’ (Willig, 2013; p. 52). When we conduct qualitative
research on complex aspects of wellbeing, the research purpose is not to accumulate and compare facts so
as to prove or disprove hypotheses, but rather to enrich our conversations and our analytical tools so that we
understand one another better and appreciate the diversity of human experiences. Qualitative research
contributes to these objectives by strengthening our terminological sophistication, translating across diverse
languages and cultures, providing analytical tools, proposing interesting questions and causal theories, and
humanising the statistics by making them memorable and emotionally salient through real-life stories and
vignettes.
Research on wellbeing involves conceptualisation (what kinds of thing are we talking about when we
discuss wellbeing?); evaluation (how well do people live, and how and in what ways to they live well?);
correlation (what traits, activities, or events are linked with wellbeing?); explanation (is it plausible or
likely that those correlations may be causal?) and comparison (are people living better than before, better
than other people, better in some respects than others, better than expected, etc.?). Apart from
conceptualisation, which is purely a qualitative matter, all of these may involve a combination of
quantitative and qualitative approaches. All are also ‘cultural’ insofar as there are strong cultural patterns,
associated with social processes and institutions, that influences people’s attitudes and motivations
concerning wellbeing. For example, in one cultural context wellbeing may mainly be conceived as meeting
basic survival needs, and in another there may be more emphasis on existential meaning. Qualitative
cultural research, as well as the informal cultural knowledge of researchers, provides crucial background
analysis to contextualise all wellbeing research.
Given the diversity of qualitative enquiry, it is useful to consider significant variations in its
characteristics: the degree to which the approach is explicitly systematic or methodical; degree of emphasis
on empirical evidence versus intellectual analysis; primary versus secondary evidence (i.e. whether or not
data are by a researcher for specific research projects); study-specific versus research synthesis reports;
armchair theorising versus laboratory research versus ‘naturalistic’ research in everyday life. Although
most qualitative authors combine a variety of these characteristics, Table 1 offers a loose classification of
books on happiness by qualitative scholars.
Table 1: Varieties of qualitative approach to wellbeing research
Approach to qualitative enquiry Published examples
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Relatively unsystematic and free-flowing but rational exploration of
theories and/or evidence from mainly nonacademic writing (e.g.
historical accounts, personal documents, local archives, fiction)
Tuan (1986); McMahon (2006); Kosaka
(2006); Ehrenreich (2009); Thomas (2009);
Ahmed (2010); Pawelski and Moores
(2013); Hyman (2014)
Nonscientific but methodical armchair philosophical theorising on
wellbeing concepts, norms, strategies, and policies
Haidt (2006); Haybron (2008); S. Bok
(2010); Tiberius (2008); Martin (2012);
Badhwar (2014)
Interdisciplinary but relatively unsystematic synthesis of academic
(empirical and theoretical) studies
D. Bok (2010); Stebbins (2011); Steedman,
Atherton, and Graham (2010); Thin (2012);
McKenzie (2016)
Mixed-methods, e.g. empirical qualitative analysis of laboratory or
other controlled experiments, biographical interviews, and
supplementing surveys with secondary research
Baumeister (1991); Vaillant (2002); Gough
and McGregor (2007); Mischel (2014);
Estes and Sirgy (2017).
Scholarly or journalistic accounts based mainly on personal interviews
and/or primary ethnographic research in naturalistic settings.
Csikszentmihalyi (1992\2002); Mathews
(1996); Sternberg (1999); Adelson (2000);
Overing and Passes (2001); Low (2004);
Baylis (2006); Weiner (2008); Calestani
(2013); Fischer (2014); Snell-Rood (2015);
Sundararajan (2015); Cieslik (2016)
There are innumerable ways of doing qualitative research. Methods are not only extremely diverse, but
are also typically inexplicit. Qualitative research texts commonly have little or nothing to say about the
methods used (Goertz & Mahoney, 2012; p. 7). Rather than aligning to particular techniques, qualitative
researchers tend to follow general approaches or ‘traditions’. Five traditions are commonly distinguished
(Creswell, 1998, 2017):
narrative research (listening to and co-constructing stories - popular now in all social sciences other
than economics);
(an unnecessarily cumbersome term for mainly obscure, pretentious, and jargon-prone writing on
how experience happens - how it becomes meaningful through mental and bodily interactions with
particular kinds of sociocultural and physical context);
grounded theory (building theoretical understanding gradually through empirical exploration - an
approach common to many qualitative researchers although the term ‘grounded theory’ has rarely
been used outside of sociology and nursing research);
(embedded observation of social and cultural processes - a term originating in anthropology that has
recently become popular in many academic disciplines and non-academic corporate learning
strategies); and
case studies (getting into rich details of bounded examples of individuals, events, institutions, etc.).
Since these traditions overlap and many scholars draw on several of them, it is probably more useful
to consider broad-brushed differences between the cultural traditions of quantitative/positivistic and
qualitative/interpretive scholarship, as indicated in Table 2.
Table 2: quantitative versus qualitative approaches and methods
Quantitative/positivistic Qualitative/interpretive
Rooted in Enlightenment faith in rational
discovery of facts and explanations in a
largely determinate world
Rooted in counter-Enlightenment or postmodern interest in the
radical indeterminacy and uncertainty of many important aspects of
life
Deductive approach: hypothesis specified
based on theorising in advance of data
gathering
Inductive approach: hypothesis implicit, or no hypothesis, but
theories developed through engagement with data
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‘Realism,’ emphasising facts and on the
reliability and replicability of research; fear
of researchers’ ‘bias’
‘Interpretivist’ or ‘hermeneutic’ approaches, emphasising meanings,
feelings, experience, and on the relevance and validity of research;
welcoming researchers’ moral engagement and ‘reflexive self-
awareness’
Reductionist approach, studying specific
isolated variables
Holistic and/or narrative approach, studying individuals, institutions,
communities, event narratives, life stories, etc. as ‘wholes’
Small number of tightly specified research
questions, strict interview protocol, restriction
of responses e.g. to ‘forced choice’
Larger number of vaguer and open-ended questions, flexible
interviewing, scope for creative, elaborate, and surprising responses
‘Blueprint’ research design, strictly adhered to Flexible research design responsive to surprises and changing
circumstances
Laboratory or clipboard encounters ‘naturalistic’ settings and semi-natural encounters in everyday life
Larger samples and aggregate generalisation smaller samples, and/or detailed attention to individual case studies,
objects, places, or activities
Methods explicit and specific Methods implicit and typically diverse or nonspecific
Explicit and strict rules on selection and
presentation of evidence
Implicit, informal, optional, and typically nontransparent
Extractive and disengaged: Researcher as
detached and impartial expert; informants as
instruments who may be kept ignorant of
research purposes; scientific research strongly
distinguished from nonacademic and
everyday ‘commonsense’ learning
Engaged and participatory: researcher embedded and emotionally
involved, often explicitly committed to moral positions or partisan
politics; informants as research partners who understand and
appreciate research purposes; research only weakly distinguished
from normal learning
Standard research reporting structure, basic
functional writing style
Idiosyncratic research reporting, sometimes with experimental
‘poetic’ writing style
Cultural Construction of Wellbeing:
Concepts and Values
The most common and persuasive justification for qualitative wellbeing research is that it helps us
recognize the many ways in which wellbeing concepts, experiences, and expressions are ‘culturally
constructed’. Since we are all products of multiple cultural and social interactions, our sense of wellbeing
must be understood not as a definable thing but as a complex web of negotiated and provisional meanings
and values. No doubt most researchers working in ‘positivist’ and ‘quantitative’ traditions do recognize
this, yet in practice their scientific discipline require a degree of control and reductionism that steers people
towards ‘essentialism’ - imagining elusive entities such as happiness and cultural traits as if they were fixed
things. Scientific aspirations can also steer people towards ‘universalism’ - imagining human psychology to
be more unified than is actually the case.
A ‘constructivist’ approach to culture and wellbeing (or what might also be called an ‘ecological’
approach) leads to highlighting the following characteristics of wellbeing:
being culturally constructed rather than the result of a universal natural process, wellbeing concepts,
valuations, experiences, and expressions are extremely varied worldwide, and between different
institutions and situations within countries.
every aspect of wellbeing is dynamic, changing according to different cultural situations and
interactions.
given the diversity and fluidity of ways in which people think and talk about wellbeing, no-one can
have a totally secure sense of what wellbeing means to them or how happy they are.
being products of specific cultural contexts and situations, wellbeing meanings and experiences are
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best appreciated in situ and are ultimately untranslatable.
Since experiences are produced through interactions and narrations which usually involve other
people and which built on cultural scripts, wellbeing is best understood as co-constructed and public,
rather than pre-reflective and private. Thus, for example, if you ask someone about their happiness,
the self-report isn’t just an expression of a pre-existing self-evaluation, but is in part a product of the
question and of the social and physical environment in which it is asked. It is ‘elicited’ information
rather than just a ‘given’ piece of data.
Of all the personal and social goods that social researchers study, none seems to compare with
happiness in terms of its uncontroversially universal value. Not even the most popular of other goods - such
as economic growth, education, democracy, freedom, equality, or human rights - is universally valued.
While there have been plenty of attempts to denigrate some specific forms or versions of happiness, such
as selfish hedonism or idle contentment, it is hard to imagine a plausible sustained argument against the
valuation of happiness in general. It is therefore common for popular texts on wellbeing to assert that
everyone in the world wants to be happy and that all cultures value happiness.
Both of these claims are true in a rather circular and therefore vacuous sense: insofar as ‘happiness’
means pursuing, getting, and enjoying whatever it is you want, then by definition happiness is wanted and
valued. But the claims are also untrue in an important sense: since most people in the world don’t have
English as their first language, it isn’t ‘happiness’ that they want and value, it’s bound to be a slightly
different concept that they have their own labels for. And even in English, concepts and terms associated
with ‘happiness’ are extremely diverse: fine, fun, flourishing, flow, fulfilment, etc., and that’s just the
terms beginning with F. To assert that happiness is a cultural value really tells us little more than that value
is valuable and that people prefer to live well. It doesn’t tell us whether people think of happiness as a
personal or a collective thing; whether their concept includes afterlife bliss; whether it’s mainly about
pursuits or achievements; whether people believe they have a soul whose happiness matters; whether they
prefer excitement or quiet contentment; or whether progressive achievements are part of their idea of living
well.
It is hard to imagine a population lacking terminology for discussion wellbeing, but the ways people
conduct such conversations may be instructive, For example, in Bolivia ‘there is no local term in Aymara
for happiness’ but the goodness of life is discussed mainly in terms of either ‘Suma Jakaña’ (household
wellbeing) or ‘Suma Qamaña’ (communal or national wellbeing) (Calestani, 2013). The terminology of
wellbeing domains, too, varies widely by language and situation. What does ‘work’ mean, for example, for
people who aren’t employed with regular hours at a separate workplace? What does ‘spirituality’ mean to
an atheist? The language of comparison, too, is nuanced. For example the phrase ‘not too happy’
(commonly used in happiness surveys), depending on situations and cultural settings, may be taken
literally or may be a form of ironic understatement meaning ‘slightly or very unhappy’. And ‘very happy’
may seem dignified and desirable to some, and undignified to others.
So one of the key challenges for qualitative wellbeing research is to reveal and make sense of cultural
diversities in the meanings, valuation, and practical implications of different terms and concepts relevant to
the pursuit of happiness. Table 3 gives a structured overview of some of the key literature on these various
aspects of the cultural inflection of wellbeing.
Table 3: what aspects of wellbeing are culturally variable?
Aspect Elaboration Examples of qualitative literature
Concepts, terms and
metaphors
Diversity, overt meanings, and nuances of the
terminology used in talking and thinking about
wellbeing.
Kovecses (2000); Altarriba, Basnight,
and Canary (2003); Wierzbicka
(2004); Pflug (2009); Cheng et al.
(2011); Goddard and Wierzbicka
(2013); Ogarkova (2016); Boster
(2017)
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Valuations and
motivations
Salience of wellbeing in public and private
discourse; ideal affect and emotion norms in
general and in specific settings and relationships;
individualism versus collectivism
Stearns and Stearns (1988); Paul
(1990); Grima (1992) Lu, Gilmour,
and Kao (2001); Reddy (2001); Lu
and Gilmour (2004); Uchida,
Norasakkunkit and Kitayama (2004);
Tsai (2008); Tsai, Knutson, and Fung
(2006); Ehrenreich (2009); Joshanloo
(2014); Fischer (2014)
Facilitation or
inhibition of the
experience of wellbeing
Cultural variety in the degree to which basic
requirements for pursuit of wellbeing are supported
or restricted (material needs, security, autonomy,
opportunities, information)
Edgerton (1992); Hollan and
Wellenkamp (1994); Duncan and
Grazzani-Gavazzi (2004); Mathews
and Izquierdo (2008b); Johnson
(2013)
Expression/
narration
Encouragement to express, narrate, mask or selfregulate
emotions or self-evaluations in diverse
contexts
Wikan (1990); Hollan (1992); Ochs
and Capps (1996); Butler, Lee, and
Gross (2007); Yang (2013)
Cultural consonance/
mismatch
Variety in the degree to which cultural settings
achieve optimal balance between clarity and
flexibility, allowing people a sense that they ‘fit’
with their culture
Lu (2006); Oyserman, Sorensen,
Reber, and Chen (2009)
Wellbeing research is largely about evaluation - of selves, lives, situations, and cultural practices. For
all humans, evaluative dispositions are developed through personal and situational perspectives, and
through a variety of cultural values that are patterned by regional populations, social networks, religions,
organizations, classes, age cohorts, and so on. Most research that is explicitly about ‘culture’ tends to
reduce this versatile concept to broad-brushed generalisations about regional or national population. Much
of the quantitative research on cultural values has focused on contrasts between regional values,
particularly between ‘East’ and ‘West’, and/or between ‘communal’ and ‘individualistic’ cultures.
But rather than being bound to nations or regions, most cultural phenomena are actually associated
with other kinds of entity such as professions, activities, tools, built environments, corporations, schools,
religions, age cohorts, social media, and social networks. Insofar as wellbeing is ‘cultural’, it is influenced
through these cultural forces, not just through national traditions. Every human is therefore ‘multicultural’,
and qualitative research is needed to reveal the rich variety of ways in which values and preferences are
learned, chosen, experienced, and expressed through cultural media (Mathews, 2012; Knoop & Delle Fave,
2013; p. 1). Local ethnographic research helpfully explores these micro-level and situation-specific cultural
influences with which every human being interacts.
Culture influences every aspect of the pursuit of wellbeing, including: how wellbeing is conceived and
discussed; norms and expectations concerning the experience and expression of wellbeing; perceived
options for pathways to wellbeing; and the extent to which personal or collective wellbeing is emphasised,
and the extent to which individuals are seen as responsible for their own wellbeing.
Compositional Wellbeing:
Balance, Harmony, and Biographical Holism
Quantitative research both feeds off and promotes thinking about happiness and other phenomena in
hydraulic and altitudinal metaphors (‘how much’? or ‘how full?’ or ‘how high’?). These metaphors apply
not just to emotions and moods, but to ‘life satisfaction’ surveys which invite people to give a single rating
to their ‘life as a whole’. Qualitative researchers are less interested in the quantity or altitude of happiness
than in its splendid variety, messiness, elusiveness, and ultimate ineffability. Hence, they want to
understand better the contexts in which people talk and think about happiness - how it is dynamically
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composed, displayed and recognized in everyday life. They ask ‘how’, ‘why’, ‘where’, ‘when’ and ‘with
whom’ questions. And when they ask about lives as wholes, they are looking for holistic insights into how
people integrate various domains and life phases, and how they balance self-orientation with selftranscendent
concerns.
It is important to appreciate not just how happy people are, but how wellbeing is composed. Just as we
talk about the ‘compositional qualities’ of a picture or a piece of music, so too we can elucidate pursuits of
happiness by discussing the compositional qualities of good lives. Commonly, people talk about these
qualities, about the integration of various life domains, using metaphors of ‘balance’ or ‘harmony’ (Berzin,
1998; Bacon, 2009; Chen, 2009; Delle Fave, Massimini, & Bassi, 2011; p. 13; Ip, 2014; Kavedžija, 2015;
Sundararajan, 2015).
The expectation that good things such as positive emotions must be balanced by bad things, and that
we should accept such contradictions, has been described as a ‘dialectical’ theme that is prominent in
Chinese folk wisdom (Pen & Nisbett, 1999). But balance metaphors are probably a human cultural
universal, reflecting their basis in the bodily experiences of the ongoing challenge of postural correction in
response to challenges (Johnson, 1987; Kovecses, 2000). Biographical research on happiness in both USA
(McAdams, 2005) and UK (Cieslik, 2015, 2016) shows that most people make ample reference to personal
sacrifices and adversities when constructing narratives of the good life: what brings value and dignity is not
the avoidance or denial of unhappiness, but coping well with troubles, sharing them through story-telling,
and making sense of them.
In some cultural traditions, most notably in parts of Asia influenced by Taoism and Confucianism, it
has also been argued that people may value a sense of appropriate balance and moderation between
pleasures and pains, rather than valuing or expecting a life of maximum pleasure or happiness (Tsai &
Park, 2014). Consequently, people from cultures which value balance are likely to use ‘cultural scripts’ to
‘dampen’ their own experiences of positive emotion, as an emotion regulation strategy, in contrast to the
‘savoring’ of positive emotions commonly promoted in Western culture (Miyamoto & Ma, 2011). A more
stark East-West contrast has also been observed in responses to negative emotion, with Asians much less
likely to try to respond to adversity by deliberate positivity or denial (Miyamoto, Ma, & Petermann, 2014).
Evidently, such contrasting beliefs are very likely to influence the scores people award themselves in selfreports
on happiness or life satisfaction scales.
The related but more complex metaphor of ‘harmony’ refers to interactions between components,
rather than just to the proportionality. In a ‘harmonious’ life, or a ‘harmonious’ relationship or a
‘harmonious’ society, the different components complement each other in a pleasing or constructive way,
as in the ‘harmony’ of a piece of music or a picture. Liang and Luo’s research in China revealed a discourse
of ‘harmonious aging’, connected with the Yin-Yang philosophy, which contrasts with the western concept
of ‘successful aging’. Often associated with ageism and with a quantitative evaluation of levels of activity,
this western ideal can usefully be contrasted with the Chinese recognition of late-life wellbeing as a
complex negotiation of changing motives and experiences as the body ages and as some social connections
fall apart. A related metaphor of ‘conviviality’ emphasizes the cultural salience of harmony as a desirable
social quality which may be deliberately cultivated, for example, by ritualised laughter as has been
commonly observed for example in Amazonian and other Latin American populations (Overing & Passes,
2000; Calestani, 2013).
Qualitative research has shown how balance and harmony metaphors act as important correctives
against the implicit ‘more-is-better’ assumptions of quantitative evaluation, reminding of the possibly toxic
outcomes of overzealously pursuing any one activity or good. In many cultures worldwide, harmony and
balance metaphors also commonly allude to negotiations between care of the self and care of the
community, and between personal and relational wellbeing (Mccubbin et al., 2013; Delle Fave et al., 2016;
Arthur & Mair, 2017).
Ultimately the purpose of most wellbeing research is to evaluate people’s whole lives. Conceptually, a
‘life’ may seem to be a natural phenomenon, but both lives and selves are in fact a cultural and negotiable
phenomena, constantly being constructed and reconstructed through interactive story-telling. This universal
practice provides us with crucial qualitative data that beg to be analysed. Biographies are not only stories
about wellbeing (or illbeing), they also constitute wellbeing.
One of the foremost qualitative psychology researchers is Jerome Bruner, who has made unique
contributions to appreciation of the narrative construction and performance of personal identities (e.g.,
Bruner, 1984, 2003, 2008). Central to his work has been the idea that wellbeing is built up by culturally
scripted forms of ‘intersubjectivity’ - that is, people enjoy their lives if they succeed in everyday life in
telling one another stories that give them a comfortable sense of mutual appreciation - ‘being able to
''know'' and share each other's mental lives’, but also developing stories to enhance toleration of ‘deviations
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from shared ordinariness’ (Bruner, 2008; p. 35). The narrative dimension of social lives, therefore, involves
an ongoing dynamic process balancing comfortable convention with individual creativity.
Bruner’s work built on the inspiration of Gordon Allport, a leader of the ‘humanistic psychology’
movement and an important forerunner of positive psychology. In an influential early text on the use of
personal documents in qualitative psychology, Allport (1942) gave a persuasive account of the many ways
in which third-person accounts (such as medical records, case studies, and psychological novels or
historical accounts) as well as autobiographical materials (such as confessions, diaries, dream accounts,
and letters) could provide new empathic insights into subjective experiences, self-evaluations, and
motivations. Just as importantly, Allport addressed head-on the many warnings against allowing such
documents to support biased or deceptive conclusions, offering a full consideration of evaluative criteria by
which we might distinguish plausible from implausible use of personal documents: representativeness;
adequacy for a particular scholarly purpose; reliability crosschecked with independent sources; and validity
of the interpretations drawn. Although not much of his text is specifically about the study of wellbeing, he
did make the important observation that life writing may tendentiously steer our attention towards trouble
and suffering: ‘As a rule autobiographical writing seems to be preoccupied with conflict, with…the
"personality-making" situations of life. Happy, peaceful periods of time are usually passed over in silence.’
In recent years, the leading exponent and promoter of biographical research on happiness has
undoubtedly been Dan McAdams, whose work has largely been about the narrative development of
personal identities and sense of self-worth in the USA. More clearly than anyone else, McAdams (2005)
has demonstrated the intertwining of subjective wellbeing with cultural scripts that are interactively
performed by telling stories that enable people to build up a sense of who they are that is publicly affirmed
by listeners. Happiness, that is to say, is socially and culturally constructed through interactive self
narratives. Adults who are exceptionally ‘generative’ in midlife use biographical stories not just to record
their lives but to structure their lives and strengthen their motivation and sense of meaning. Such narratives
have distinct culturally variable flavours: in the USA, a dominant theme is ‘redemption’ - triumphantly
recovering from suffering and/or adversity to achieve a renewed and stronger self. This is important
because it shows how even in one of the most ‘positive’, pro-happiness cultures in the world, substantial
attention is paid to the critical roles of suffering and adversity in the good life. Also noteworthy is the
substantial use that McAdams makes of secondary cultural and historical research in linking present-day
self-narratives with historical figures, religious doctrine, and popular literature such as self-help texts.
A similarly rich synthesis of autobiographical accounts and cultural history is provided by Gordon
Mathews’ book What Makes Life Worth Living (1996), which was the first book-length ethnographic
account of happiness. Mathews organized his innovative work around paired mini-biographies of USA and
Japanese interviewees, and linked his interpretation of these with a full analysis of recent cultural and
socio-economic trends in both countries. In contrast to many of the quantitative East-West psychological
comparisons, Mathews offers a more subtle portrayal of cultural values which shows how there is plenty of
evidence for both ‘individualism’ and ‘collectivism’ in both countries, with individuals working out their
own unique ways of interacting with chosen cultural themes and values.
An intriguing portrayal of narrative identity is presented in the folklorist-ethnographer Bénédicte
Grima’s (1992) account of Paxtun women in Pakistan, who met regularly to compete with one another in
miserabilist self-narratives. The ethic is the exact opposite of the north American ethic of compulsory
positivity lambasted in Ehrenreich’s book Smile or Die [Bright-Sided]. For Paxtun women, dignity and
respect come from turning events of extreme suffering into a story shared with other women.
Appreciative Inquiry, Participatory Research, and
Action Learning: The Intrinsic Value of Wellbeing Enquiries
Like many activities, research can have both instrumental value and intrinsic value. Typically,
scientific research is seen as a means to an end - producing new information in order to take better
decisions. The emphasis is on the robustness of the findings rather than on the direct value of the research
process itself. Qualitative research that is less detached, more participatory, and more blended with
everyday public curiosities and conversations, is more likely to be recognized as having intrinsic or
processual value. It can and arguably should make more direct contributions through the more immediate
life enhancement that participation in research can provide.
This is particularly true of qualitative enquiries on wellbeing, including one-to-one applied work such
as life story elicitation and talk therapies, as well as focus group and organizational work that goes under
the general label ‘appreciative enquiry’ (Prilleltensky & Prilleltensky, 2006.) Lewis outlines a set of
principles of appreciative inquiry, which include promotion of a ‘constructionist’ recognition that we all
create one another’s realities, and ‘positive’, ‘anticipatory’ and ‘narrative’ approaches that build and stories
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based on successes and enjoyments to foster constructive hope and motivation (2016; p. 126-7). The
prospect of participatory research being directly beneficial is also particularly strong when working with
categories of people who otherwise lack opportunities for reflection and public self-expression, such as
children (e.g., Theron, Liebenberg, & Ungar, 2015; Nastasi & Borja, 2016; Fattore, Mason, & Watson,
2017), older people (Hoban, James, Pattrick, Beresford, & Fleming, 2011), and disadvantaged ethnic
minorities (White & Jha, 2014).
Provision of evidence about the benefits of appreciative enquiry tends to be impressionistic, anecdotal,
and far from impartial. Both researchers and participants have a vested interest in demonstrating that they
have been a force for good, and the research ethos of positivity points them in this direction (Bushe, 2007).
One fairly typical example is Wendy Penney’s work in three residential care facilities in rural Victoria,
Australia, which invited care staff to describe what they did well to improve residents’ lives. This is what is
called the ‘unconditional positive question’ (Ludema, Cooperrider & Barrett, 2008). Researchers found that
the process was enjoyable and energising for staff, that it resulted in more positive communication and
sense of pride in work, and in potentially beneficial changes to everyday practices. A more sophisticated
example is a comprehensive wellbeing enquiry and promotion programme in a USA school, involving a
psychology interest group; parent training courses on wellbeing; a formal wellbeing curriculum; a
wellbeing club including yoga, mindfulness and Tai Chi activities; and wellbeing courses. Researchers
noted the enthusiastic adoption of these activities and were optimistic about benign impacts but were not
able to offer evidence actual effects on objective or subjective wellbeing (Waters & White, 2015).
There clearly is potential for qualitative researchers to improve the plausibility of their arguments by
providing stronger and more impartial evaluative evidence of real-world changes brought about by
participatory research. But we need to be realistic about the inevitable limitations of participatory research
in this regard. And we mustn’t lose sight of the very plausible arguments about the direct benefits of
fostering positive discussion of strengths and enjoyments in diverse social contexts. Bearing this in mind it
can be argued, for example, that governments, corporations and civic organizations should support
participatory wellbeing research even if there is great uncertainty about the validity and usefulness of its
ultimate findings.
A good society, and a good organization, is one which takes the wellbeing of its stakeholders
seriously and encourages and enables them to voice their views on the matter. Of course, responsible
researchers should make sincere efforts to produce valid and useful findings, but they should also cherish
and enhance the values of the research process. Qualitative research approaches have much better potential
in this regard. They can encourage active citizen participation in all aspects of the research process,
whereas experimental and qualitative research tend to require alienating forms of expert control - even to
the extent of hiding the true nature of enquiries.
Toxic Culture, ‘Critical’ Perspectives,
and Pathological Detours
Since wellbeing themes are unavoidably evaluative, wellbeing researchers cannot escape the
responsibility to move beyond moral relativism and try to help people make sense of evidence that reveals
some cultural contexts and societies to perform much less well at facilitating wellbeing than others do
(Thin, 2005; Mathews & Izquierdo, 2008b). Quantitative survey research has revealed very strong
geographic patterns of self-reported happiness worldwide, unsurprisingly confirming that most people
don’t seem very happy in those countries that inhibit freedom or that fail to meet basic needs for food,
shelter, and physical security (Helliwell, Layard, & Sachs, 2017; Veenhoven, 2017). It has performed less
well at exploring in detail the many forms of cultural toxicity that severely curtails people’s ability to live
well in many parts of the world.
Sociocultural anthropology, the archetypal qualitative research discipline, has a weak record in
fostering explicitly evaluative cultural analysis. Like sociology, the discipline grew out of largely critical
approaches to western modernity. Unlike sociology it focused on nonwestern cultures, and until the late
20th century it tended to foster two main principles: ‘relativism’ (insisting that cultures should be
evaluated, if at all, only by their own criteria) and ‘adaptivism’ (assuming that cultural practices don’t
survive if they are maladaptive, i.e. bad for survival). As an antidote to colonial triumphalism, many
anthropologists have seen it as their moral duty to reveal the beauties and values of nonwestern culture and
to avoid ‘ethnocentric’ use of alien values to criticise aspects of culture. And the ‘adaptivist’ principle is
nonevaluative too, insofar as it is about mere survival, not about wellbeing. Hence the discipline has failed
to develop either theories of human flourishing or any sustained analysis or critiques of cultural harms.
The psychological anthropologist Robert Edgerton did produce an impressive collection of
crosscultural evidence of cultural harms around the world. In his book Sick Societies (1992) presents a
133
catalogue of social ills. He notes that most human cultures have allowed practices to persist which promote
physical and mental illness, poverty, unfair inequalities, avoidable suffering, and premature death. The
forms of toxic culture which anthropologists have habitually failed to criticise include: warfare; witchcraft;
‘honour’ killings; torture and severe corporal punishments and humiliations; dowry harassment; human
sacrifice; ritualised and sanctified sexual abuse of children; genital mutilation of children and other
harmful bodily mutilations; male dominance; dangerous health practices; poor nutrition; widow-burning;
and blood feuds.
Although Edgerton’s moral call to arms failed to ignite a new evaluative tradition in anthropology,
since the 1970s anthropologists have in general shifted their interests towards researching mainly
pathologies much as sociologists have always done. Sociologists, unlike anthropologists, were throughout
the 20th century mainly interested in social harms but in a highly restrictive way: for the most part, their
critical attention was directed towards western modernity, and by extension towards the metropolitan urban
cultures of poorer countries. This kind of bias is flagrant, for example, in a recent sociological text entitled
Social Harm (Pemberton, 2015), which directs its critical gaze only at those harms that the author believes
can be attributed to ‘neoliberal’ modernity.
A different but analogous kind of bias is evident in a feminist collection on Harmful Cultural
Practices around the world (Longman & Bradley, 2016), which similarly sounds global in scope but is
actually a collection of essays by women scholars who define ‘cultural harm’ solely in terms of the harms
done to female victims. From both an evaluative and a policy perspective, qualitative scholarship on
cultural harms would be greatly enhanced if scholars took seriously their responsibility to consider the
wellbeing of humanity in general in less partisan ways. In contrast to wellbeing scholars, who are quite
happy to generalise, it seems that scholars specialising in the study of harm feel a need to indulge in
dichotomous portrayals of victims and perpetrators.
Apart from the problem of selective bias in criticism of cultural and social harms, qualitative research
disciplines have also in general reduced their descriptive validity, their moral plausibility, and their ability
to achieve benign influence on the world, by failing to theorise or define the opposite of harms and
harmfulness, i.e. wellbeing and beneficence. There are innumerable ethnographic monographs on various
forms of suffering and injustice, but even apparently neutral or balanced texts such as Subjectivity:
Ethnographic Investigations (Biehl, Good, & Kleinman, 2007) or Contentment and Suffering (Hollan &
Wellenkamp, 1994) or Wellbeing in the Time of AIDS (Wallman, 1996) or World Mental Health (Desjarlais
Eisenberg, Good, & Kleinman, 1995) have shown relentless interest in adversities without any
complementary ethnography or theorising of wellbeing.
Methodological Pluralism, Mixed Methods,
and Research Synthesis
With the rapid proliferation of all kinds of wellbeing research output from an increasing variety of
disciplines and countries, the need for persuasive and reliable synthesis research becomes paramount. This
is also important as a way of addressing the collective weakness of much qualitative research that remains a
somewhat ad hoc collection of one-off local studies based on small samples and idiosyncratic methods.
Good synthesis research is needed to move towards viable generalisations and crosscultural comparisons.
Achieving plausible synthesis of qualitative research requires great ingenuity, flexibility, and patient
tolerance. Three main features make it extremely hard for scholars, planners, or interested public to draw
generalised conclusions from qualitative research:
The messiness and flexibility of idiosyncratic approaches makes it hard to discern the validity and
quality of specific studies.
The vagueness and uncertainty of research purposes, questions, and findings, and in some cases even
a total lack of ‘findings,’ means that much qualitative research is at best suggestive rather than
conclusive.
The diversity of methods and writing approaches makes it hard to develop any systems for
comparison or synthesis
If ‘pluralism’ is the key benefit that qualitative approaches add to wellbeing research (Gergen,
Josselson, & Freeman, 2015), those who try to help us make sense of this plurality must provide some
guidance regarding the comparative values of diverse methods. But whereas with quantitative research
there are clear and strict protocols for conducting and presenting ‘meta-analysis,’ qualitative researchers
have yet to come up with clear guidelines for synthesis, and secondary research analysis is in practice
mainly conducted without any clear system. Although improvements in transparent reporting of approaches
and rationales in qualitative synthesis research are possible and desirable, realistically the process is too
134
unwieldy to expect more than a loose set of explanations and justifications. Tight specification of inclusion
and exclusion criteria would result in too much loss of flexibility, steering attention towards a narrow
subset of those varieties of qualitative writing most amenable to comparison and synthesis.
‘Secondary’ research methods means using information that was generated for different purposes whether
for personal or bureaucratic record, or for other research purposes. When numerous quantitative
studies are synthesised, this is called a ‘meta-analysis’ or ‘synthesis’. But such research is dependent on
finding several studies that match rigorous inclusion criteria so that they are properly comparable. When
qualitative research is synthesised, scientifically valid generalisations aren’t possible. But this doesn’t
prevent the formation of useful insights based on high levels of plausibility as opposed to scientific near-
certainty.
Most qualitative synthesis takes the form of relatively ad hoc literature reviews (e.g. in the opening
paragraphs of articles or books) or introductions to thematic collections which both synthesis crosscutting
themes in the collection and link these with other literature. As published information proliferates, and as
the boundary between one-off scholarly research and ongoing public learning becomes blurred, future
qualitative research scholars can greatly add to the value of qualitative research by coming up with
approaches to research synthesis that are reasonably systematic and transparent, but without resorting to the
excessively restrictive and exclusionary approaches that dominate ‘meta-analysis’ in quantitative science.
Conclusions
We have reviewed here a small fraction of the increasingly copious qualitative research output on
wellbeing from anthropology, sociology, psychology, linguistics, history, development studies, literary
studies, human geography, political science, cultural studies, and philosophy. Most of these disciplines
have not made wellbeing as central or as explicit in their research agendas as they should have done, and
many have been either ethnocentric or somewhat culture-blind in their approaches. Though there
encouraging signs of rapidly increasing quantity and diversity of crosscultural wellbeing research but there
is a long way to go in terms of clarifying methods for conducting, synergising and synthesising this
research (Tonon, 2015; Bruni & Porta, 2016).
All researchers need to take culture seriously as the environment in which wellbeing develops. To do
this, we must pay systematic attention to language, learning, scripting, sharing and interactive display and
discussion of wellbeing. For ‘subjective’ wellbeing, i.e. happiness, this means exploring subjective
experience in its full complexity, looking well beyond not only the individual’s self-reports or laboratory
behaviors to examining the dialectic interactions of everyday life.
But addressing these important complexities in the qualitative dimensions of wellbeing research comes
at a high price. Qualitative research is in general slow, scrappy, extremely diverse in its disciplines and
methods. Its outputs come nowhere near the clarity and confidence that we see in the outputs from the
tactically reductionist research of experimental science and survey-based quantification. Collectively, the
persuasions and influences of qualitative research are achieved - if at all - indirectly rather than through
provision of clear conclusions from specific studies or research syntheses.
For funders and users of research on wellbeing, or for researchers trying to striking an optimal balance
between qualitative and quantitative aspects of their work, this creates difficult strategic decisions. Some
themes and questions - generally specific ones about particular kinds of behavior or correlation - can be
effectively answered by experimental or quantitative research. All of the most important questions,
however, require input from qualitative approaches. Decisions about research methods take place at
multiple levels, from the pico-level of specific topics and activities, through the micro-level of individual
researchers and projects, the meso-levels of programmes, institutions, and research areas, to the macrolevels
of whole academic disciplines and national or corporate research strategies. All we can ask is that all
researchers give respectful and intelligent consideration to judicious mixing of methods and approaches.
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THEORIES OF SUBJECTIVE WELL-BEING
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Cognitive Outlooks and Well-Being
By Seth Margolis & Sonja Lyubomirsky, University of California, Riverside
Citation
Margolis, S., & Lyubomirsky, S. (2018). Cognitive outlooks and well-being. In E. Diener, S. Oishi, & L.
Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
The top-down approach to well-being focuses on how people attend to and construe information in their
lives and how these processes affect their well-being. In this chapter, we review evidence that attention and
construal, broadly conceived, influence well-being. We then discuss specific types of attention and
construal (i.e., cognitive outlooks) that affect well-being. Such cognitive outlooks include gratitude, selfesteem,
optimism, locus of control/autonomy, competence, connectedness, attributional style, and
ruminative style. For each cognitive outlook, we review research that demonstrates an association between
the cognitive outlook and well-being. We then discuss evidence for causal effects and theoretical accounts
of these effects. We conclude with a brief discussion of questions that future research can explore.
Keywords: Cognitive outlooks, Well-being, Attention, Construal, Top-down approach
Research on the correlates and causes of well-being has yielded two approaches (Diener, 1984). The
bottom-up approach emphasizes the role of the objective environment on well-being. Specifically, the
bottom-up approach seeks to explain variance in well-being levels by examining the moment-by-moment
situations people face. For example, exploring the impact of daily hassles and uplifts on life satisfaction
(Lavee & Ben-Ari, 2008) fits squarely under the umbrella of the bottom-up approach to well-being.
In contrast to the bottom-up approach, a top-down approach focuses on subjective processing of the
environment to explain variation in well-being. From a top-down perspective, the effect of the environment
on well-being is heavily mediated by subjective construal. For example, research taking a top-down
approach to explore the effect of divorce on well-being might consider whether a partner views the divorce
as freedom from an unhealthy relationship or as the loss of a supposedly lifelong partner. Conversely, a
researcher who views well-being with a bottom-up approach may focus on certain features of the divorce,
such as its effects on one’s living situation and access to immediate family members.
As the science of well-being has grown and matured over the last several decades, most well-being
researchers have gravitated toward the top-down approach. This trend is likely the result of robust findings
indicating that life circumstances, which are emphasized in a bottom-up approach, explain a surprisingly
small amount of the variance in well-being, whereas personality, emphasized in a top-down approach,
explains a relatively large proportion of the variance in well-being. Although some researchers initially
believed life circumstances would have large impacts on well-being, reviews revealed that they account for
only about 10-15% of the variance in well-being (Andrews & Withey, 1976; Argyle, 1999; Campbell,
Converse, & Rogers, 1976). By contrast, a meta-analysis found that Big Five traits account for up to 63%
of the variance in well-being (Steel, Schmidt, & Shultz, 2008).
Further support for the top-down approach comes from research on general positivity, which has
primarily been measured in two ways. One method assesses the degree to which general satisfaction ratings
are more positive than the aggregate of specific satisfaction ratings. For example, an individual high in
general positivity would score higher on a measure of life satisfaction than measures of work and family
satisfaction. Other researchers have used a positivity scale, which contains items regarding optimism, life
satisfaction, and self-esteem (Caprara et al., 2012). With both approaches, general positivity is strongly
associated with well-being (Caprara, Eisenberg, & Alessandri, 2016; Diener, Scollon, Oishi, Dzokoto, &
Suh, 2000; Lauriola & Iani, 2015; Oishi & Diener, 2001).
In this chapter, we review specific cognitive outlooks that show how positive cognitions affect
well-being, which fits squarely within the top-down approach. We define a cognitive outlook as a pattern
of thinking that comprises one’s evaluation of the self and events in the world. Thus, cognitive outlooks are
a component of personality and are likely a major reason why personality accounts for a large proportion
of the variance in well-being. Consistent with the overwhelming support for the top-down approach, many
cognitive outlooks impact well-being.
Construal
Why do life circumstances account for a relatively small proportion of the variance in well-being?
Many researchers point to the role played by construal, or one’s subjective perception and evaluation of a
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situation. Construal research can be traced back to Henry Murray’s (1938) distinction between alpha press
and beta press. A “press” is an environmental influence on an individual. Alpha press is the objective
environmental influence, and beta press is the subjective or perceived environmental influence. For
example, Javier may repeatedly glance at Mary during their psychology class. This is the alpha press, as it
describes objectively the situation or event that is occurring. The beta press would represent Mary’s
thinking about why Javier keeps looking at her. Mary might believe that Javier is looking at her because
she looks weird today. Alternatively, she might guess that Javier is attracted to her.
As illustrated in this example, the beta press (i.e., construal) can vary widely. Many well-being
researchers point to this variability in explaining individual differences in the effects of life events or
situations on well-being. For example, Lyubomirsky (2001) argues that the effects of life events on wellbeing
are strongly mediated by cognitive processes. According to Lyubomirsky, situations affect wellbeing
not directly but through cognitive and motivational processes—that is, situations are “processed”
(i.e., evaluated, framed, remembered). The modal model of emotion (Gross & Thompson, 2007) offers a
very similar explanation. According to this model, situations lead to construals (via attention, as described
in the next section), which lead to an emotional response (see Figure 1). This idea can also be stated using
Murray’s terminology: The alpha press affects well-being via the operation of the beta press. Returning to
the example with Javier and Mary: Whether Mary interprets Javier’s glances as condemning or flattering
will affect how Mary feels.
As people go through their daily lives, they repeatedly form construals, which affect well-being.
For this reason, construal style (i.e., one’s pattern of construing situations in a particular way) predicts
well-being. For example, Lyubomirsky and Tucker (1998) found that happy individuals did not differ from
their unhappy peers in the number of stressful and negative life events they reported experiencing, but
rather, happier people employed different cognitive strategies than unhappy ones. Happier people rated
positive events as making them more happy than did unhappy people, and unhappy people rated negative
events as making them more unhappy than did happy people. In addition, when envisioning themselves in
hypothetical scenarios, happier people reported more positive evaluations overall—that is, rating the
scenarios as being more positive, less negative, bringing them more happiness, and improving their moods.
Although these results are correlational, they form a compelling argument for the effect of construal
on well-being. Two experiments tested a causal effect of construal on well-being (Lichter, Haye, &
Kammann, 1980). First, a small sample of participants met for eight 2-hour sessions over 4 weeks to
discuss a list of irrational/maladaptive thoughts with the aim of combating them (i.e., attempting to shift
their evaluations). After this period and at a 6-week follow-up, participants’ beliefs were more positive,
their affective well-being increased, and their life satisfaction increased more than those of participants in a
no-activity control. In a second experiment, participants were randomly assigned to either rehearse positive
statements for 2 weeks or to a no-treatment control. Participants who rehearsed positive statements
increased in well-being more than control participants. These findings support the above theories, which
state that construal causes well-being.
Few studies have focused on general construal and its effect on well-being, although the existing
work provides both correlational and causal evidence of this effect. Further evidence of the relatively large
effect of construal on well-being resides in research on specific cognitive outlooks. However, these
cognitive outlooks are not just characterized by construals, but also have attentional components.
Attention
The modal model of emotion (Gross & Thompson, 2007) indicates that one must direct attention to
particular elements of a situation before one construes that situation (see Figure 1). Attention refers to the
process by which people select a subset of perceivable information to concentrate on or cognitively process
further (i.e., construe). Thus, attention selects the information that is to be construed. This process is
necessary because people cannot attend to all the information they perceive. For example, imagine a
woman walking into a party with dozens of people and evaluating whether she should stay at the party or
leave. The woman cannot possibly attend to all the activity in the party (e.g., she cannot attend to each
person’s behavior). Instead, she must try to attend to the salient cues in the environment (e.g., the behavior
of people she knows, the music, etc.) and make her decision from that information. Although some human
universals drive people’s attention (e.g., people naturally attend to changes in their visual fields), there are
individual differences in what people habitually attend to (Isaacowitz, 2006). Some researchers point to
these individual differences to explain the large effect of personality on well-being. Indeed, individual
differences in attention are robustly associated with well-being levels. A meta-analysis of 33 studies
examined individuals with anxiety and/or depression with eye tracing methods (Armstrong & Olatunji,
2012). Relative to those without anxiety, participants with anxiety displayed increased vigilance for (i.e.,
attention to) threat during free viewing and visual search tasks, and had difficulty removing their attention
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from threat in visual search tasks. Furthermore, relative to those without depression, individuals with
depression oriented to positive stimuli less and attended to positive stimuli for shorter times than they
attended to negative stimuli.
Figure 1. The modal model of emotion. Adapted from “Emotion regulation: Conceptual
foundations,” by J.J Gross and R.A. Thompson, 2007. In J. J. Gross (Ed.), Handbook of emotion
regulation (pp. 3-24).
Research indicates that the link between well-being and attention is bidirectional: Well-being affects
attention and attention affects well-being. The broaden-and-build theory of positive emotions (Fredrickson,
2013) indicates one way in which well-being affects attention. According to this theory, positive emotions
serve a functional role in that they broaden awareness, which builds skills and resources. Conversely,
negative emotions narrow one’s focus. Negative emotions alert individuals that something is not well, and
narrowing their attention allows them to search for the problem and focus on solving it. In contrast,
positive emotions signal that all is relatively well. In the absence of threats, there is no need to search for
and resolve problems; instead, a person with positive emotions has the flexibility to broaden attention. The
broaden-and-build theory of positive emotions has held up to empirical testing using experimental
methods. For example, one study manipulated positive affect by randomly assigning participants to hear a
happy or sad song. Those induced to feel positive (rather than negative) emotions showed increased access
to remote semantic associates, as well as increased attention to stimuli outside their immediate focus of
attention (i.e., flanking “distractors” in the Eriksen flanker task; Rowe, Hirsh, & Anderson, 2007). In
another set of studies, participants randomly assigned to a positive mood induction attended relatively more
to reward words during a spatial probe task (Tamir & Robinson, 2007). In sum, a large body of evidence
supports the idea that well-being influences attention.
However, the opposite is also true: Attention affects well-being. Several methods of attention
modification, including dot-probe training methods, visual search training methods, clinical auditory
training tasks, and meditation (primarily mindfulness-based stress reduction), have been used to reorient
people to more positive and/or less negative stimuli. These attention-altering tasks appear to have
beneficial effects on affective well-being (Wadlinger & Isaacowitz, 2011). More recent research also
supports the notion that changes in attention can cause changes in well-being. For example, participants
experimentally induced to attend to positive information experienced more positive affect in response to
success (Grafton, Ang, & MacLeod, 2012). Furthermore, meditation seems to increase well-being via shifts
in attentional processes (Menezes et al., 2013; Pavlov et al., 2015). The well-replicated effect of attention
on well-being supports the modal model of emotion, because, according to that model, changes in attention
should have downstream effects on emotion and hence well-being.
Before turning to specific types of attention and construal, we would like to note that the effects of
attention and construal on well-being are also manifested in another cognitive process—namely, memory.
Although evidence that actual recall is affected by well-being is mixed (Lyubomirsky & Tucker, 1998;
Seidlitz & Diener, 1993; Seidlitz, Wyer, & Diener, 1997), positive construal of memories has been
associated with well-being. In one study, for example, people higher in well-being reflected more positively
on their memories than those lower in well-being (Liberman, Boehm, Lyubomirsky, & Ross, 2009). In
addition, turning one’s attention to positive memories can boost well-being. In one experiment, a small
group of participants randomly assigned to reminisce about positive memories increased in well-being,
relative to those assigned to simply think about a life event (Bryant, Smart, & King, 2005). Thus, wellbeing
may be associated with memory processes via attention and construal. Although a large literature has
examined the relationship between current affective states and memory (Blaney, 1986; Bower, 1981), there
is room for much more research on the link between memory processes and more general well-being.
Specific Types of Attention and Construal
As reviewed above, there is a great deal of evidence that attention and construal, broadly
conceptualized, impact well-being. However, most research on the links between cognitive outlooks and
well-being targets specific cognitive outlooks. These cognitive outlooks are organized in Table 1. With the
exception of attributional style, which refers to a specific type of construal, each of these cognitive
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outlooks has both attentional and construal components.
Table 1
Cognitive Outlooks Related to Well-Being
Evaluations of the Past
and Present
Evaluations of the Self Evaluations of the Future
Gratitude Self-Esteem Optimism
Locus of Control/Autonomy
Competence
Connectedness
Attributional Style
Ruminative Style
In this chapter, we review each of these cognitive outlooks. We begin by defining the specific
cognitive outlook and then review the research that supports its association with well-being. Next, we
examine research that suggests the cognitive outlook has a causal effect on well-being. Lastly, we discuss
the leading theories that explain the observed relationships.
Appreciation and Gratitude:
Evaluations of the Past and Present
Appreciation and gratitude are closely related conceptually. Generally, appreciation is viewed as a
more general form of gratitude. Gratitude has been defined as “the recognition of a positive outcome from
an external source, including a felt sense of wonder or thankfulness for benefits received” (Emmons &
McCullough, 2003; Nelson & Lyubomirsky, 2016; Roberts, 2004). Gratitude is “a component of
appreciation,” where appreciation is “acknowledging the value and meaning of something—an event, a
person, a behavior, an object—and feeling a positive emotional connection to it” (Adler & Fagley, 2005).
Both gratitude and appreciation involve recognizing a positive event. However, gratitude is directed
towards a specific source or cause. One may be grateful to one’s mother for providing support.
Appreciation differs in that it need not be directed towards a source or cause. One may appreciate a
beautiful natural scene without attributing the landscape to geological forces or a god. Following these
examples, gratitude typically occurs in interpersonal contexts, whereas appreciation can occur in any
context with a positive outcome.
Notably, researchers have overwhelmingly focused on investigating gratitude rather than
appreciation more generally. However, some factor analytic work suggests that gratitude and appreciation
are a singular construct (Wood, Maltby, Stewart, & Joseph, 2008). If this is the case, all conclusions about
the association between gratitude and well-being should hold true for appreciation and well-being. Because
gratitude is a part of appreciation and most research focuses on gratitude, we discuss the two constructs
together.
Unsurprisingly, those with higher levels of gratitude and appreciation tend to have higher levels of
well-being (Lambert, Fincham, & Stillman, 2012; Watkins, 2004; Wood, Joseph, & Maltby, 2008, 2009;
see Wood, Froh & Geraghty, 2010 for a review). This effect holds across a variety of positive outcomes
(e.g., positive emotions) and negative outcomes (e.g., depressive symptoms) in dozens of studies. Evidence
supporting a causal effect of gratitude on well-being comes from two longitudinal studies that measured
gratitude and well-being at the beginning and end of participants’ first semester of college (Wood, Maltby,
Gillett, Linley, & Joseph, 2008). Cross-lagged analyses suggested that gratitude leads to well-being and not
the other way around.
Experimental studies have provided stronger causal evidence. In these studies, participants typically
list things they appreciate or write a gratitude letter to a person towards whom they feel grateful. Those
performing one of these appreciation/gratitude activities tend to increase in well-being more than those in a
control condition, demonstrating that gratitude causes shifts in well-being (e.g., Boehm, Lyubomirsky, &
Sheldon, 2011; Emmons & McCullough, 2003; Froh, Sefick, Emmons, 2008; Layous, Lee, Choi, &
Lyubomirsky, 2013; Lyubomirsky, Dickerhoof, Boehm, Sheldon, 2011; Seligman, Steen, Park, &
Peterson, 2005; see Wood et al., 2010, for a review). The effect of appreciation/gratitude activities on wellbeing
tends to be meaningful in size, with Cohen’s ds typically between d = .2 and d = .6 (Wood et al.,
2010, Table 5).
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Why or how do appreciation and gratitude impact well-being? Gratitude may cause one to engage
in positive reframing (i.e., focusing attention on the positive aspects of a past events to construe the event
in a more favorite light), which, in turn, boosts well-being (Lambert et al., 2012). For example, a student
may reflect on a challenging English course and feel grateful towards the professor for substantially
improving her writing skills. Gratitude may also boost well-being via improved feelings about
relationships, particularly the relationship with the target of gratitude (Lambert & Fincham, 2011). These
positive relationship feelings may then boost well-being because feelings of connectedness are important
for well-being (Ryan & Deci, 2000). Lastly, gratitude seems to boost prosocial behavior (Bartlett &
Desteno, 2006; Tsang, 2006), and prosocial behavior increases well-being (Crocker, Canevello, & Brown,
2017). Because these two mediators (i.e., feelings about relationships and prosocial behavior) are inherently
social, they may be specific to gratitude’s effect on well-being and hence potentially not mediate the
relationship between appreciation and well-being. However, we expect that positive reframing would also
mediate the relationship between appreciation and gratitude.
Optimism: Evaluations of the Future
Those with an optimistic disposition expect future events to be positive. For example, an optimist
may believe that a trip to the DMV will be quick and easy, whereas a pessimist is more inclined to believe
that they will be stuck waiting for hours. Research shows that the former person is more likely to be happy
than the latter person.
A recent meta-analysis found that across various measures of well-being, optimism is positively
associated with well-being (Alarcon, Bowling, & Khazon, 2013). For example, across 50 studies including
19,831 participants, optimism, as measured by the Life Orientation Test (Scheier & Carver, 1985), was
correlated with life satisfaction at an average of r = .43. Interestingly, the same meta-analysis found that,
across 13,593 participants in 36 studies, optimism was positively associated with general physical health at
r = .28. Optimism may have such strong correlations with both physical and mental health because it offers
both physical and psychological resilience. For example, one study sampled middle-aged men before and
after coronary artery bypass surgery. The more optimistic men, compared to less optimistic men, used more
effective coping styles, recovered from the surgery faster, and reported a higher quality of life 6 months
after the surgery (Scheier et al., 1989).
Despite the plethora of correlational research on optimism and well-being, little direct evidence
exists for a causal effect of optimism on well-being. A few relevant experiments have had participants
envision their “best possible selves”—an exercise that prompts them to form optimistic thoughts about the
future—and found subsequent increases in well-being (Layous, Nelson, & Lyubomirsky, 2013;
Lyubomirsky et al., 2011; Peters, Flink, Boersma, & Linton, 2010; Sheldon & Lyubomirsky, 2006).
Longitudinal designs can also provide some evidence of causality. One study found that pessimism
predicted increases in depressive symptoms over 3 years (Bromberger & Matthews, 1996). In addition, a
few longitudinal studies suggest optimism predicts future well-being following or during a stressful period
(see Scheier & Carver, 1992, for a review).
Which theories can explain the beneficial effects of optimism? To our knowledge, no explicit
theory of how optimism impacts well-being has been put forward. This may be the case because it is rather
intuitive that those who believe more positive events will occur are happier. However, we still believe this
lack of theory represents a hole in the literature. Although the relationship between optimism and wellbeing
may seem self-evident, there are many distinct ways in which optimism could impact well-being. For
example, optimists may be less concerned than others about stressful future events. Alternatively, optimists
may experience anticipatory pleasure when thinking about future events. Or do optimists spend more time
thinking about the future, leading them to ruminate less about the past or present? Another possibility is
that optimists simply hold more positive construals (or appraisals) in general. Alternatively, perhaps it is
not optimists’ construals that differ from those of other people but rather their attention; in other words,
they attend to more positive information, particularly about the future. Lastly, optimists may be goaloriented,
which is associated with greater goal progress, which leads to greater well-being. One or several
of these hypotheses could be true. We encourage researchers to identify mediators between optimism and
well-being, and more broadly, develop theories that explain why optimism seems to have a causal impact
on well-being.
Self-Esteem: Evaluations of the Self
Self-esteem is typically conceptualized as an overall evaluation of one’s worth. Individuals with
high self-esteem are likely to believe that they are capable and deserve the positive outcomes they
experience. By contrast, those with lower self-esteem may believe they have little power to produce good in
the world and feel that praise directed towards themselves is unwarranted.
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Multiple studies have found a positive correlation between self-esteem and well-being (Cheng &
Furnham, 2003a; Cheng & Furham, 2003b; Emmons & Diener, 1985; Hills & Argyle, 2002; Joshanloo &
Afshari, 2011; Lyubomirsky, Tkach, & DiMatteo, 2006; Paradise & Kernis, 2002). This effect seems to be
quite robust: One study found a positive correlation between self-esteem and life satisfaction in each of the
31 countries sampled (Diener & Diener, 2009). These correlations were rather strong (average r = .45) and
depended on a country’s individualism: The correlation between self-esteem and life satisfaction was
greater in more individualistic countries.
Unfortunately, to our knowledge, no studies have used experimental methods to directly test for a
causal effect of self-esteem on long-term well-being. Presumably, researchers have judged self-esteem as a
stable construct that is very difficult to manipulate in the long-term. However, researchers have used tasks
that temporarily manipulate self-esteem as mood induction techniques. These tasks involve receiving
positive or negative feedback on some task (e.g., a social skills task or a game; see Martin, 1990;
Westermann, Spies, Stahl, & Hesse, 1996, for reviews). The impact of positive and negative feedback on
mood suggests that self-esteem causally impacts the affective component of well-being. However, these
studies manipulate self-esteem over short durations and the effects on affect are transient.
Some interventions may be effective at boosting self-esteem in the long-term, albeit indirectly. Selfaffirmation
interventions target self-integrity, which is the belief that one is a good and moral person
(Sherman & Cohen, 2006). Because self-integrity and self-esteem overlap conceptually, self-affirmation
interventions might boost self-esteem. In addition, self-affirmation interventions may have recursive effects
that last for months or even years (Cohen & Sherman, 2014). Thus, self-affirmation interventions may be
one way to boost self-esteem for a long duration and observe downstream effects on well-being. Indeed,
two studies found that such interventions did boost well-being (Nelson, Fuller, Choi, & Lyubomirsky,
2014; however, see Revord & Lyubomirsky, 2017 for a nonreplication). One should note that these effects
were not robust and were found with small sample sizes.
Self-compassion interventions, which teach people to accept their perceived shortcomings, may also
boost self-esteem for a relatively long duration. Like self-integrity, self-compassion is distinct from, yet
related to, self-esteem (Neff, 2003, 2011). A few small pilot studies and experiments suggest that selfcompassion
interventions boost well-being (Gilbert & Procter, 2006; Neff & Germer, 2013; Smeets, Neff,
Alberts, & Peters, 2014). Future studies can explore whether self-compassion and self-affirmation
interventions impact well-being via changes in self-esteem, which would suggest that self-esteem casually
impacts well-being.
The direction of causality between self-esteem and well-being has also been examined with
longitudinal designs (Ciarrochi, Heaven, & Davies, 2007; Lucas, Diener, & Suh, 1996; Orth & Robins,
2013). One of the largest studies to investigate this effect longitudinally sampled over 1,824 individuals
aged 16 to 97 five times over a 12-year period. Cross-lagged analyses suggested that self-esteem was a
cause, and not a consequence, of positive affect, negative affect, and depression (Orth, Robins, &
Widaman, 2012). Furthermore, a meta-analysis with 77 studies found that self-esteem predicted decreases
in depression (β = -.16) to a greater extent than depression predicted decreases in self-esteem (β = -.08,
Sowislo & Orth, 2013).
Which mechanisms link self-esteem and well-being? According to Beck’s cognitive theory of
depression (Beck, 1967), negative views of the self predispose one to experience depression. Although few
studies have tested mediators of the effect of self-esteem on well-being, one found rumination as a
mediator between self-esteem and depression (Kuster, Orth, & Meier, 2012). Alternatively, people with
high self-esteem may simply attend to more positive information about themselves. For example, one study
used a Stroop task with rejection (e.g., “neglected”) and acceptance (e.g. “included”) words and found that
participants with low self-esteem experienced more interference for (i.e., attended more to) rejection words
than acceptance words (Dandeneau & Baldwin, 2004). No such difference was found for participants with
high self-esteem. This attentional mechanism may account for another possibility—namely, that selfesteem
may lead an individual to have more positive construals of the self overall, boosting well-being.
One study found that participants with high self-esteem construed ambiguous attributes of themselves more
positively than did those with low self-esteem (Suls, Lemos, & Stewart, 2002). In addition, other studies
have found that those with low self-esteem feel like they do not deserve positive events and, thus,
experience less positive affect from them (Wood, Heimpel, Manwell, & Whittington, 2009; Wood,
Heimpel, & Michela, 2003). In sum, there are many potential avenues by which self-esteem could impact
well-being, and future studies can continue to explore the precise mechanisms by which this occurs.
Evaluations of Autonomy/Locus of Control, Competence,
and Connectedness: Evaluations of the Self
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Self-determination theory posits three needs that are fundamental for the well-being of an in
individual: connectedness, competence, and autonomy (Ryan & Deci, 2000). Connectedness, also called
relatedness, indicates the extent to which people feel they are close to others. Thus, a person high in
connectedness believes that he or she has meaningful social relationships. Conceptually, the construct of
connectedness requires only a perception of social connectedness and not objective connections, such as
number of friends. The construct of competence is similarly subjective. Competence is defined by the
degree to which people believe they possess mastery and can bring about desired changes in their lives.
People low in feelings of competence may lack confidence when trying to learn a new skill, for example.
Competence is certainly related to self-esteem and may be a component of it. Indeed, the State Self-Esteem
Scale (Heatherton & Polivy, 1991) has a performance subscale that closely resembles competence. Lastly,
autonomy indicates the degree to which people believe their actions are a result of their internal
motivations rather than pressure from other individuals. Autonomy is closely related to locus of control,
which reflects the degree to which people believe they, rather than external factors, control their life. Locus
of control, which is similar to the internal/external dimension of attributional style, also varies from internal
(i.e., one has great control over one’s life) to external (i.e., one has little control over one’s life). Due to the
heavy degree of overlap between locus of control and autonomy, we will discuss these two constructs
together.
According to self-determination theory, autonomy, competence, and connectedness are all necessary
for well-being. Thus, all three needs to be satisfied in order for a person to have high well-being. However,
research has simply used bivariate correlations between needs and well-being. Autonomy, competence, and
connectedness are each positively correlated with well-being (Deci et al., 2001; Kasser & Ryan, 1999;
Milyavskaya & Koestner, 2011). If these constructs are indeed needs, then these correlations should hold
across cultures and evidence supports this (Chirkov, Ryan, Kim, & Kaplan, 2003; Diener, Ng, Harter, &
Arora, 2010; Tay & Diener, 2011). Furthermore, longitudinal research has found significant correlations
among these constructs and well-being both between and within individuals (La Guardia, Ryan, Couchman,
& Deci, 2000; Reis, Sheldon, Gable, Roscoe, & Ryan, 2000; Sheldon, Ryan, & Reis; 1996). Lastly, people
with an internal locus of control tend to have higher levels of well-being than those with an external locus
of control (April, Dharani, & Peters, 2012; Cvetanovski & Jex, 1994; Krause & Stryker, 1984).
Clearly, research supports the idea that the needs posited by self-determination theory correlate with
well-being. But perhaps a stronger test of whether autonomy/locus of control, competence, and
connectedness increase well-being is to test them as causes of well-being. Unfortunately, experimental
research examining the effects of autonomy/locus of control, competence, and connectedness on well-being
is very limited. However, one study assigned participants to pursue goals related to connectedness,
competence, autonomy, or life circumstances (as a control) and tracked well-being over 6 months (Sheldon
et al., 2010). The main effect was not significant: Those who pursued the three goals related to selfdetermination
theory did not improve in well-being significantly more than those in the control condition.
However, this effect was present for participants who pursued goals with sustained effort and made
progress. This study serves as weak evidence for causal effects of autonomy, competence, and
connectedness on well-being. Future research can use experimental methods similar to the above study to
test for causal effects.
Attributional Style:
Evaluations of the Past, Present, Future, and Self
People naturally ascribe causes to events and these are referred to as attributions. According to
attributional models of depression, certain patterns of attribution can create a susceptibility to depression
(Abramson, Seligman, & Teasdale, 1978). Early attributional models of depression emphasized the
importance of attributions of negative events along three dimensions: internal-external (i.e., personal),
stable-unstable (i.e., permanent), and global-specific (i.e., pervasive).
Variation on each of these dimensions can be demonstrated by considering the attributions someone
can draw. For example, Susan may have failed a midterm exam during her first semester of college. If
Susan believed that she failed because she lacked the intelligence and dedication to do well on the exam,
she would be drawing an internal (i.e., personal) attribution. However, Susan might make an external
attribution by concluding that she failed because the exam was unusually difficult. Thus, the internalexternal
dimension indicates the degree to which one attributes an event to oneself rather than external
forces. Susan may further infer her failing is a stable characteristic of herself—she will continue to fail in
similar situations. Thereby, Susan would be using a stable attribution. Alternatively, Susan may believe this
instance of failing is not going to be typical for her, thus drawing an unstable attribution. Unstable
attributions indicate that future outcomes may be different, whereas stable attributions specify that a
negative outcome shows evidence of what the future holds. Lastly, Susan may view her failure as global by
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reasoning that failing in this one class indicates that she will fall short in other situations. For example,
Susan could believe that her failing an exam indicates that she will fail as a friend and as a mother.
However, Susan could also view the event as specific. Perhaps she believes her failure is limited to exams
of a certain format. The permanency of attributions indicates the extent to which one believes a negative
outcome in one domain indicates that negative outcomes will occur in other life domains.
One study provides evidence that explanatory style is a relatively stable trait. Burns and Seligman
(1989) examined the content of written text (e.g., letters, diaries, essays) of 30 participants. Each participant
provided text from early adulthood and late adulthood (the average age difference was 52 years). The
authors found that the attributional style used by participants in these texts was consistent over time.
However, this only demonstrates weak evidence of stability and the study had a small sample size.
Attributional models of depression posit that individuals who consistently draw internal, global, and
stable attributions for adverse events and external, specific, and unstable attributions for positive events are
at higher risk for depression. This style of attribution is often referred to as a pessimistic or depressive
attributional style. An optimistic attribution is the opposite: Drawing external, specific, and unstable
attributions for negative events and internal, global, and stable attributions for positive events.
Does evidence support this attributional model of depression? A meta-analysis of over 100 studies
found that internal, global, and stable attributions of negative events were each positively related with
depression measures, supporting this attributional model of depression (Sweeney, Anderson, & Bailey,
1986). Furthermore, internal, global, and stable attributions of positive events (i.e., an optimistic
attributional style) were each negatively related to depression measures. The same pattern of results has
also been found in more recent work (Cheng & Furnham, 2001, 2003a; Winefield, Tiggemann, & Smith,
1987). Furthermore, cross-lagged analyses from longitudinal studies demonstrate that attributional style
predicts changes in measures of depression (Firth & Brewin, 1982; Golin, Sweeney, & Schaeffer, 1981;
Seligman et al., 1984)
Unfortunately, this area of research suffers from a lack of causal studies. This is understandable, as
it seems it would be difficult to experimentally manipulate people’s habitual attributions. However, clinical
therapy may do just that. Indeed, one longitudinal study randomly assigned employees to a cognitivebehavioral
training program or waitlist control and assessed whether changes in attributions mediated
between condition and well-being outcomes such as job satisfaction, self-esteem, and psychological
distress (Proudfoot, Corr, Guest, & Dunn, 2009). Most mediation analyses did not yield significant results.
Although this is evidence that attributional styles do not casually impact well-being, one study cannot rule
out a causal path. Thus, researchers should conduct more longitudinal experiments to test whether clinical
therapy causes changes in attributional styles, which then cause changes in well-being.
Although this area of research lacks experimental longitudinal studies, longitudinal studies without
random assignment have been used to suggest a causal effect of attributional style on well-being. One
meta-analysis examined whether attributional style could predict subsequent changes in depression among
adolescents (Joiner & Wagner, 1995). Across seven studies, a pessimistic attributional style positively
predicted increases in depression.
Longitudinal studies in adults also suggest that attributional style has a casual impact on well-being.
One study assessed 143 Japanese undergraduates at three time points across 6 months (Sakamoto &
Kambara, 1998). In relatively negative environments, participants with a depressive attributional style
tended to be more depressed that those without such an attributional style. Another study that did not
consider the state of one’s environment found that a depressive explanatory style predicted increases in
depressive symptoms (Sanjuán & Magallares, 2009).
Interestingly, Sakamoto and Kambara (1998) found that participants with an internal, global, and
stable attributional style decreased in depressive symptoms more than those without that attributional style
in positive environments. Similarly, Needles and Abramson (1990) found that individuals with depression
experienced increases in well-being when they employed an internal, global, and stable attributional style
towards positive events. In sum, evidence suggests attributional models of depression are correct. That is,
an internal, global, and stable attributional style decreases well-being in negative contexts but increases
well-being in positive contexts.
Why are internal, global, and stable attributions maladaptive in negative contexts but adaptive in
positive contexts? Internal, global and stable attributions in negative contexts signal learned helplessness,
which is the process by which an organism learns that it is helpless when the environment contains threats
(Maier & Seligman, 1976). Internal, global, and stable attributions about negative events indicate that this
learned helplessness is a result of personal shortcomings, applies to more than the one context, and will
persist. This construal creates a grim outlook of one’s past, present, and future experiences, thus lowering
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well-being. However, internal, global, and stable attributions of positive events signal “learned optimism”
such that one believes positive events are the result of one’s personal capabilities and indicative of positive
events to come both in the situation in question, as well as other domains (Seligman, 2011). Thus, people
with learned optimism are thought to be higher in well-being because they are characterized by stronger
self-esteem and higher optimism.
Ruminative Style:
Evaluations of the Past, Present, Future, and Self
Drawing internal, global, and stable responses is not the only maladaptive way to respond to
negative events. A large body of research has explored the ruminative response style, which involves a
tendency to respond to negative events by repeatedly attending to the symptoms, causes, and consequences
of distress rather than focusing on possible solutions (Nolen-Hoeksema, 1991). Ruminative thoughts need
not contain negative content—their defining feature is their repetitive yet passive approach to negative
moods. Although rumination is highly correlated with worry (Fresco, Frankel, Mennin, Turk & Heimberg,
2002), the two are conceptually distinct in several ways (Nolen-Hoeksema, Wisco, & Lyubomirsky, 2008).
Rumination typically involves focus on the past, whereas worry involves focus on the future. In addition,
ruminative thoughts tend to contain themes of meaning, loss, and self-worth, whereas worried thoughts
regard potential threats. Lastly, ruminative thoughts are characterized by certainty, uncontrollability, and
insight-seeking, whereas worried thoughts are characterized by uncertainty, controllability, and threat-
preparation.
Ruminative style is associated with other cognitive outlooks we have discussed, including
maladaptive attributional styles, pessimism, and low self-esteem (Lam, Smith, Checkley, Rijsdijk, & Sham,
2003; Lyubomirsky & Nolen-Hoeksema, 1995; Lyubomirsky, Tucker, Caldwell, & Berg, 1999; Spasojevic
& Alloy, 2001). Importantly, rumination predicts depression even after controlling for these cognitive
styles (Flett, Madorsky, Hewitt, & Heisel, 2002; Nolen-Hoeksema, Parker, & Larson, 1994; Spasojević &
Alloy, 2001). Furthermore, multiple longitudinal studies demonstrate that the more people ruminate, they
more likely they are to develop depression and have longer periods of depression (Just & Alloy, 1997;
Kuehner & Weber, 1999; Nolan, Roberts, & Gotlib, 1998; Nolen-Hoeksema, 2000; Nolen-Hoeksema,
Larson, & Grayson, 1999; Nolen-Hoeksema, Morrow, & Frederickson, 1993; Nolen-Hoeksema, et al.,
1994; Sarin, Abela, & Auerbach, 2005; Segerstrom, Tsao, Alden, & Craske, 2000; Spasojević & Alloy,
2001; Wood, Saltzberg, Neale, Stone, & Rachmiel, 1990).
Researchers have sought to establish a causal effect of rumination on well-being—negative affect,
in particular—using a rumination induction task developed by Nolen-Hoeksema and Morrow (1993). In
this task, participants are told to focus on the meanings, causes, and consequences of their current feelings
for 8 minutes. Several studies have demonstrated that this seemingly benign task boosts negative affect
among dysphoric or depressed participants (Donaldson & Lam, 2004; Lavender & Watkins, 2004;
Lyubomirsky, Caldwell, & Nolen-Hoeksema, 1998; Lyubomirsky & Nolen-Hoeksema, 1993, 1995;
Lyubomirsky et al., 1999; Morrow & Nolen-Hoeksema, 1990; Nolen-Hoeksema & Morrow, 1993; Watkins
& Baracaia, 2002; Watkins & Moulds, 2005; Watkins & Teasdale, 2001).
Why does rumination exhibit consistent detrimental effects on well-being? Response styles theory
(Nolen-Hoeksema, 1991) argues that rumination can lead to depression through several paths. First,
rumination is thought to enhance negative thinking while one is in a negative mood. Indeed, dysphoric
participants experimentally prompted to ruminate reported more frequent negative life events than did those
prompted to distract themselves (Lyubomirsky et al., 1998). Using the same design, other studies have
found dysphoric individuals assigned to ruminate (versus to distract themselves) construe hypothetical
negative and positive events in a more negatively-biased, pessimistic manner (Lyubomirsky & NolenHoeksema,
1993, 1995). Rumination is also believed to impede problem solving. Dysphoric participants
induced to ruminate found problems more overwhelming and developed less effective solutions, compared
to participants induced to distract themselves (Lyubomirsky & Nolen-Hoeksema, 1995; Lyubomirsky et
al., 1999). Lastly, ruminators engage in less social support. Ruminators seem to avoid social interaction,
either to take time to think or write about their feelings or by repelling others with their negativity. In sum,
rumination has both behavioral and cognitive adverse consequences, which seem to account for its affective
ramifications.
Future Directions
All the cognitive outlooks we reviewed in this chapter have been found to relate to well-being.
These findings speak to the value of the top-down approach. Clearly, attention and construal, which are
manifested in each of the different outlooks, are both important to well-being. However, despite the
relatively sizable research literature on each of these cognitive outlooks, more work is needed in several
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areas.
Throughout this chapter, we have noted where we believe holes in specific literatures exist.
However, a broad overview of the literature highlights that most researchers tend to focus on a specific
cognitive outlook. However, these constructs have considerable overlap. What is the unique effect of each
construct on well-being? Furthermore, do any cognitive outlooks interact to predict well-being? For
example, self-esteem could moderate the effect of gratitude on well-being because one needs to feel
deserving of an act of kindness to appreciate it. Alternatively, a particular cognitive outlook might mediate
the association between another cognitive outlook and well-being. For example, a sense of autonomy might
boost self-esteem, which then affects well-being. These possibilities can be explored in future studies that
focus in concert on several cognitive outlooks and well-being. This type of research could utilize multiple
regression and path-analytic techniques to uncover unique, moderation, and mediation effects.
Another hole in the cognitive outlooks literature is the lack of causal evidence. The reasons that
little experimental work has been conducted in these areas are likely to vary widely—from relevant
researchers’ lack of interest or training in experimental methods to some constructs, like self-esteem, being
particularly difficult to manipulate experimentally. However, investigators may erroneously believe that
some constructs are difficult to manipulate. Thus, we encourage researchers to think creatively to design
studies that explore causal effects.
In sum, more research is needed on how to improve people’s levels of gratitude, optimism, locus of
control/autonomy, connectedness, competence, and optimistic attributional style. We know much more
about which cognitive outlooks impact well-being than about how to intervene on these constructs.
Determining the most effective ways to shift these cognitive outlooks could have profound implications for
individuals’ well-being.
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Affective Forecasting
By Jaime L. Kurtz, James Madison University
Citation
Kurtz, J. L. (2018). Affective forecasting. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of wellbeing.
Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
This chapter outlines the topic of affective forecasting, the process of predicting one’s future feelings
(Gilbert & Wilson, 2007). Although people are often fairly skilled at making these sorts of predictions,
examples of systematic errors in forecasting are laid out. Key topics related to this topic are defined and the
reasons underlying errors in forecasting are explored. Also considered are correctives to affective
forecasting errors, with the goal of offering advice on how to make better predictions of future feelings.
Keywords: Affective forecasting, hedonic adaptation, self-knowledge
“All decisions are based on predictions of future feelings ” (March, 1978).
Imagine being in the fortunate position of receiving two job offers. One is geographically close to
family and friends, yet the work sounds a bit dull and the job offers little opportunity for advancement. The
other would require a cross-country move to a new city, but the workplace sounds dynamic and the work
meaningful.
Which job do you choose? This decision requires a complicated line of reasoning. You have to
weigh the importance of social ties against the value of meaningful work. You have to project into a
foreign future, envisioning likely but inherently unknowable scenarios. Undoubtedly, at some point all of
this internal debate would take the shape of a seemingly simple question: Which of these two scenarios
would ultimately make you happier?
This sort of question is one we ask regularly—about large matters like job offers, but also about
everyday decisions. Will I feel better if I eat a salad or a bacon cheeseburger for lunch? Would a date with
Joe be fun, dreadful, or somewhere in between? Would that new piece of furniture bring me enough
happiness to justify the money I’m about to spend on it?
All of these questions require making an affective forecast, a prediction of your future feelings. They
require that we mentally create a hypothetical future, making our best guess not only of how a situation
will unfold, but exactly how we will feel as it does. Prospection, this process of thinking into the future in
this way, is a uniquely human experience and it provides numerous advantages (Gilbert & Wilson, 2007).
Without it, we’d be blindly guessing at our tastes and preferences. Choosing a job, a lunch, a date, or a
consumer purchase would be complete guesswork, and we’d be just as well off flipping a coin. The
question is, however, exactly how good are we at this process of affective forecasting? Do self-knowledge
and the power of prospection offer any advantages, or are we better off with a coin flip?
To be certain, humans have survived and thrived because of the power of prospection. We generally
can identify causes of pleasure and causes of pain. We very often learn from our mistakes. So, while it is
easy and fascinating to lay out the many mistakes we make, it is important to mention and keep in mind
that we must be reasonably good forecasters to function well in a complex world.
Indeed, while we are generally accurate when making crude predictions of emotional valence (for
example, ice cream will be good, dental work will be bad), systematic errors are more likely to occur when
making more nuanced predictions, such as when guessing just how intensely and for how long an
emotional reaction may last. Starting in the mid-1990s, this area of research has revealed systematic lapses
in self-knowledge. The basic paradigm of an affective forecasting experiment involves randomly assigning
participants to the role of either forecaster or experiencer (e.g., Gilbert, Pinel, Wilson, Blumberg, &
Wheatley, 1998; Wilson, Centerbar, Kermer & Gilbert, 2005; Wilson, Wheatley, Meyers, Gilbert, &
Axsom, 2000). Forecasters are asked to imagine a scenario playing out and predicting how they might feel
in that scenario. Experiencers, on the other hand, actually live out the scenario and report their actual
feelings about it. When comparing the reactions of the two groups and seeing no difference, we can
conclude there is no forecasting error: people’s predictions align with reality. But if there is a discrepancy
—in terms of intensity, valence, or duration—a forecasting error may be taking place.
Across a variety of situations, it has been demonstrated that we are poor predictors of our future
emotional states. From the outcomes of elections, promotions, romantic breakups, winning the lottery, and
losing a football game, we systematically mispredict the intensity and duration of our emotional reactions
to future life events (e.g., Wilson & Gilbert, 2008; Wilson, Wheatley, Meyers, Gilbert, & Axsom, 2000).
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Simply put, we don’t always know what will make us happy and for how long. Relatedly, then, we are also
poor at knowing what decisions will bring us the happiness that we seek (Mellers & McGraw, 2001): job
choices, romantic partners, meal preferences and more are prone to affective forecasting errors.
Key Concepts in Affective Forecasting Research
The impact bias refers to the pervasive tendency to overestimate both the intensity and duration of
an emotional reaction. As the term suggests, future events tend to be thought of as more powerful than they
are when they actually occur. Parsing further, duration neglect is defined as the common experience of
overestimating just how long something will be emotionally impactful (Gilbert, Pinel, Wilson, Blumberg,
& Wheatley, 1998). We may know that an unexpected romantic breakup will be painful, but as we predict
just how bad it will be, we expect the pain to linger for months or even years. In reality, it will likely start
to fade much faster. Note that while this is certainly desirable when it comes to negative life events—it has
a lot in common with the concept of resilience—it can be a challenge to lasting happiness when it comes to
positive events, as explained later.
A related concept, which helps to explain just why duration neglect occurs, is focalism or the
focusing illusion—the tendency to hone in on one isolated future event at the expense of everything else
that is likely to be going on around it. For example, when asked to imagine how they would feel if their
school’s football team won or lost an upcoming game, students overestimated how long their feelings
would linger, because they were failing to account for all the other things that would also be taking place in
their daily lives (Wilson, Wheatley, Meyers, Gilbert, & Axsom, 2000). Sure, they would be a little
disappointed if their team were to lose, but there will be exams to take, meals to eat, and friends to spend
time with. In another study (Schkade & Kahneman, 1998), a sample of Midwestern and Southern
Californian college students were asked to report on their own personal happiness, and also predict the
happiness of a typical student in the other location. While there was no significant difference between
groups, Midwestern college students thought that Southern Californians would be happier, because they
were focusing too much on unique and pleasant features of that location: sunshine and beaches, for
instance. They were missing so much of the everyday life things—classes, social life, housework—that
they have in common.
Exploring Possible Mechanisms
Why do affective forecasting errors exist? And why do they persist, even as we see the outcomes of
our errors in everyday life time and time again? Several potential underlying mechanisms offer explanations
why.
Misconstrual. One simple reason for affective forecasting errors is the fact that we often
erroneously imagine the future experience in question (Wilson & Gilbert, 2003). Prospection is rife with
errors; without a crystal ball, we cannot perfectly gauge what any future experience will truly be like. If a
vacationer predicts that her upcoming beach trip will be wonderful and it turns out terribly, this could be
because she was envisioning a deserted white sand beach and perfect weather, rather than a crowded, loud,
or rainy one. In this case, the root of the error is less psychological and more environmental.
Hedonic adaptation. It is difficult to discuss affective forecasting in depth without considering the
role of hedonic adaptation (Brickman, Coates, & Janoff-Bulman, 1978; Diener, Lucas, & Napa Scollon,
2006). Due to this process, over time and through repeated exposure, emotional events go from the
forefront to the background of our attention. This is a highly functional process. It is maladaptive to keep
attention focused on a past event and more adaptive to attend to immediate challenges. Adaptation happens
in very basic ways, for example, the tenth candy is seldom as enjoyable as the first. It can also operate on
major life events: getting into a dream college or falling in love is tremendously exciting at first, but it
gradually ceases to be so. Daily life takes over our attention and it becomes increasingly challenging to
attend to our past triumphs and defeats.
Importantly for accurate affective forecasting, it seems that we fail to realize the extent to which we
adapt to emotional events. This is part of why we make forecasting errors (Loewenstein & Schkade, 1999).
Instead, when we do experience short-lived joy or pain, we sometimes chalk it up to the object of our
forecast (“Dating Chris isn’t nearly as fun as I expected. I guess he’s not the Prince Charming I thought he
was.”) rather than to our “psychological immune systems” (Wilson, Meyers, & Gilbert, 2001). Gilbert,
Pinel, Wilson, Blumberg, and Wheatley (1998) use the term immune neglect to describe the behind-thescenes
inner workings of our mental and emotional systems. Because we don’t always have conscious
access to these neutralizing processes, we can be surprised when emotional experiences lose their power
over time.
Ease of explanation. In their AREA (attend, react, explain, adapt) model of hedonic adaptation,
Wilson and Gilbert (2008) posit that when something emotionally-relevant happens, it draws our attention
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and we respond with some experience of happiness or sadness. As is well-established, hedonic adaptation
will likely occur next. The critical next step, which determines the rate of adaptation, is sense-making. Why
did this event occur? In an effort to understand the whys and hows of what happened, we try our best to
explain the event. “He asked me out because we have a similar sense of humor and are both baseball fans”
or “I didn't get the job because I was less qualified than the other applicants.”
This satisfies our need to know but destroys a bit of the mystique. With any unexplained event, there
is a good deal of uncertainty and much material for reflection (“Why did this happen?”). Once we have an
explanation, we will move on to other, more pressing concerns. In short, life goes on.
It follows that if we can keep the mystery alive with a lack of explanation, we might be able to
inhibit adaptation and keep things a source of joy for a longer period of time. Several studies confirmed
this: when receiving compliments from a series of potential “dates,” participants were in an elevated mood
for longer when they didn’t know which date had paid them which compliment (Wilson, Centerbar,
Kermer & Gilbert, 2005). When entered into a raffle to win one of two desirable prizes, participants were
happier longer when they had to wait to find out which prize they won, as compared to finding out
immediately (Kurtz, Wilson, & Gilbert, 2007). Notably, forecaster participants (those who were asked to
simply predict their feelings) said they would prefer to have their curiosity satisfied rather than to remain
uncertain about the outcome, an intuition that actually seems to diminish enjoyment. In fact, to inhibit
hedonic adaptation, it helps to have an air of mystery or inexplicability about the event in question. It keeps
the event salient in mind as we mentally replay it to try to understand it better. (Naturally, the opposite is
true of negative life events. To promote recovery and resilience, understanding the negative event—
explaining it or making sense of it—is generally preferable.)
This concept has far-reaching implications. In the context of romantic relationships, the early stages
are often characterized by intense longing and all-consuming thoughts along the lines of, “Does this person
really like me?” As agonizing as this mindset can be, research by Whitchurch, Wilson, and Gilbert (2011)
revealed that this period of questioning may maintain the allure of a new potential partner. In an online
dating simulation, female participants who believed that a sample of men were interested in dating them
were more attracted to the men than women who thought the men liked them only an average amount (i.e.,
we like those who like us). However, the women who found the men the most attractive were the ones who
weren’t sure whether those men liked them or not. Their uncertainty led them to think about the men the
most, perhaps serving as a cue to their own level of interest, and this increased their attraction toward the
men.
For long-term relationships, Koo, Algoe, Wilson, and Gilbert (2008) adapted this idea into a
counterintuitive strategy for relationship satisfaction. Married participants were asked to vividly imagine
how they might not have met their spouse (and, by extension, how they wouldn’t have the life they have
currently). This “mental subtraction” seemed to make their marriages seem less explainable and inevitable
and more surprising. This increased their levels of appreciation and satisfaction, compared to a neutral
control group. Importantly, a sample of forecaster participants failed to see the advantages of mental
subtraction, believing that thinking about a life without their spouses would be more sad than it actually
was.
Projections across time. Affective forecasts, by definition, require a certain “psychological time
travel,” whereby we project into the future to estimate what our feelings might be. However, the present
(i.e., the time of the forecast) and the future can vary in critically important ways in ways we fail to realize.
The projection bias describes the tendency to falsely project current preferences onto a future event
(Loewenstein, O'Donoghue, & Rabin, 2003).
One well-documented temporal disconnect is known as the hot-cold empathy gap. Loewenstein,
O’Donoghue, and Rabin (2003), for instance, found that people who had just eaten dinner underestimated
how much they would enjoy the next day’s breakfast. In the moment of the forecast, they were feeling
satiated, and that distinct physical feeling couldn’t help but weigh into their judgment of how they would
feel the next morning. A similar experience can be found at the grocery store, where hungry shoppers often
buy more food than they want later, because their inner state is providing powerful—but erroneous—
suggestions of future desires. This gap can also occur interpersonally. Van Boven and Gilovich (2003)
found that one’s own level of thirst dictated how much they estimated another person would want a drink.
Past experiences can also color future forecasts. When looking back on a past positive experience,
such as when one’s preferred candidate won an election, participants recalled being happier in that moment
than they actually had reported as it was unfolding (Wilson, Meyers, & Gilbert, 2003).
A well-accepted fact that memory is a reconstruction of past events, prone to numerous biases and
errors (Schacter, 1989). What is less known is that certain kinds of life events are prone to a unique
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reconstructive bias known as the rosy view. Specifically, experiences that are generally positive, bounded
in time (they have a clear beginning and an end), and free from an evaluative outcome (there is no win or
lose) are often recalled as being better than they were when they were actually happening.
For example, Mitchell, Thompson, Peterson, and Cronk (1997) researchers surveyed cyclists on a
three-week tour of California. While their daily experiences were characterized by high points such as
pedaling along the Pacific coastline or making new friends, they also had a lot of neutral and negative
moments to deal with – rain, hills, traffic, and so on. When asked to think back and report on their overall
experience of the trip, however, they consistently reported it as being better than the sum of its reported
moments. Other studies found a similar pattern for both families on a Disneyland vacation and in a sample
of marathon runners (Lemm & Wirtz, 2013; Sutton, 1992). These gaps seem to get larger as the time
between forecast and experience widens (Gilovich, Kerr, & Medvec, 1993).
Incorrect lay theories. It is in the best interest of marketers to convince consumers that their
product or service will greatly enhance their lives. Romantic comedies send the message that a loving
relationship is the key to everlasting happiness. Messages such as this can easily become internalized. As a
result, it is easy to see how we might overestimate our future happiness when acquiring a new possession,
meeting a new potential partner, and more.
The power of rationalization. A final reason for the persistence of affective forecasting errors—
particularly the impact bias—is the misunderstanding of the power of rationalization. This is demonstrated
in Gilbert and Ebert’s (2002) study on reversible versus nonreversible decisions. At the end of a very
involved photography class, participants were told that they could keep only one photograph that they had
taken. Some were further told that they had a few days to change their minds, at which point they could
easily trade in their chosen photograph for a different one. Others were told that their decision was
nonreversible; whatever photograph they chose was the one they had to keep. Surprisingly, those who were
not allowed to change their minds made the best of things and came to like their photograph more than
those who were allowed to reconsider it. In short, we rationalize what we cannot change. Importantly, a
sample of forecasters expressed a strong preference for the opposite, preferring to have the freedom to
change their minds. This experiment has far-reaching implications for the surprising downside of an escape
clause, from decisions ranging from buying a new mattress to choosing a spouse. In a follow-up, Lieberman
and colleagues (2001) found that coming to love what you own is displayed even in retrograde amnesiacs.
They cannot overtly recall what objects they own, but somehow they know that it is superior to what they
don’t own.
Not all of life’s events are rationalized in the same way. In fact, it is often surprising how
catastrophes can be quickly explained away, while minor irritations linger. Imagine that you have a
squeaky door jam. Multiple times per day, you open the door, hear the annoying squeak, and feel minor
irritation. It bothers you, but not quite enough to act upon. Now, imagine instead that a tree falls through
your front window, causing major damage. You are on the phone immediately, arranging to get it fixed.
The surprising end result is that the accumulated annoyance will be greater for the squeaky door than for
the much bigger problem of the broken window. Gilbert, Lieberman, Morewedge and Wilson (2004)
posited that our emotional systems may work similarly. We are motivated to make sense of and recover
from extremely upsetting events—being insulted by a loved one, for one—but we are less motivated to
bounce back from, say, a seemingly minor insult from a stranger. Because that unconscious motivation is
lower, insults from strangers tend to linger. Again, people get it wrong, thinking that it would be far
preferable to be insulted by an irrelevant person than a significant one.
Individual Differences in Forecasting Ability
While affective forecasting errors are extremely common, some people tend to be more accurate
than others when predicting future feelings. While research on individual differences in forecasting ability
seems relatively limited, studies show that emotional intelligence—an awareness of one’s internal affective
state—allows people to make more accurate predictions of future feelings (Dunn, Brackett, Ashton-James,
Schneiderman, & Salovey, 2007; Hoerger, Chapman, Epstein, & Duberstein, 2012). Higher levels of
mindfulness have also been linked to more accurate forecasts (Emanuel, Updegraff, Kalmbach, & Ciesla,
2010). Both of these traits allow open, nonjudgmental access to one’s inner life. This information can be
helpful in promoting sound judgments of future feelings as well.
By contrast, certain dispositions bias us to particular kinds of information, which can cloud
judgments of future feelings. Those with depressive symptoms are especially likely to overestimate
negative emotional reactions but underestimate positive ones (Hoerger, Quirk, Chapman, & Duberstein,
2012; Marroquín, & Nolen-Hoeksema, 2015). Most people, but especially those with clinical panic and
anxiety disorders, tend to overestimate their future fear responses (Arntz, Hildebrand, & van den Hout,
1994; Rachman, 1994). A fear of anxiety-producing situations can perpetuate the disorder by reinforcing
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avoidance behaviors (Reiss, Peterson, Gursky, & McNally, 1986). In fact, mental illnesses have also been
framed as, in part, errors in affective forecasting.
Also, there is mixed evidence that older people are better at predicting certain kinds of emotional
experiences. Specifically, older adults seem better able to make refined judgments of future emotions
(Nielsen, Knutson, & Carstensen, 2008).
Interestingly, forecasters tend to downplay the role of their personality when making forecasts. For
example, those dispositionally high in optimism tended to underestimate the role this trait would play in
their affective reaction to receiving bad news (Quoidbach & Dunn, 2010). This “personality neglect”-- a
person’s tendency to overlook their personality when making decisions about their future emotions – can
be another source of blind spots in forecasting.
Implications for Long-Term Happiness and Well-Being
The ability to forecast well has many implications for happiness and health-related behaviors
(Loewenstein, 2007; Sieff, Dawes, & Loewenstein, 1999). In fact, as argued by Hsee and Hastie (2006),
many major life decisions from the short-term – resisting that carton of ice cream to the long -- saving for
retirement and staying up-to-date with health screenings assume that people are rational and accurate
forecasters.
It is clear that, contrary to these assumptions, affective forecasting errors can actually interfere with
the ability to make sound decisions for the future. We tend to overestimate our levels of self-control
(Stutzer & Frey, 2007).
Interpersonal relationships. Mallett, Wilson, and Gilbert (2008) conducted a series of studies that
have important implications for outgroup relations. When told that they would be interacting with students
outside of their racial or ethnic groups, participants overestimated the extent to which this interaction
would be unpleasant, relative to other participants’ actual experiences. This was because they focused on
the differences between themselves and the outgroup member when, in actuality, they were similar in many
ways (age, college student status, etc.). Importantly, though, it seemed that this bias could be partially
undone: interactions were expected to be more pleasant when participants were first asked to generate
reasons they were similar to the outgroup members. This took the spotlight off of their apparent differences
and reminded them of the many similarities that actually existed between them.
In the context of romantic relationships, affective forecasting errors play out in other important
ways. For instance, when coping with a romantic breakup, people tend to overestimate how long they will
take to recover. These errors occur because people initially overestimate the intensity of their emotional
reactions to the breakup (which may be accurate in the very early, very painful stages), but then they use
this intense reaction as a basis for judgment (Eastwick, Finkel, Krishnamurti, & Loewenstein, 2007). In
short, they underestimate their own levels of resilience.
Consumer behavior. Affective forecasting errors and a general lapse in self-knowledge have
serious implications for how consumers allot their money. In their review of the literature, Dunn, Gilbert,
and Wilson (2011) argue that a primary reason for the unimpressive correlation between income and
happiness is the fact the we do not always spend money in a way that reliably promotes happiness. Short of
true love and good health, money can buy most everything. So, as the authors argue, if money doesn’t
make you happy, you may not be spending it right. Well-documented spending habits that are related to
higher levels of happiness are: buying experiences rather than material possessions, making it difficult to
return a purchase, limiting options, spending money on others rather than on the self, and buying many
small pleasures instead of one large one. There is much evidence to suggest that consumers do not always
spend in accordance with these principles.
Improving Affective Forecasts
As long as the future remains uncertain, affective forecasting errors are likely to occur. And despite
how frequently they befall us, they have a tendency to be “sticky” – we do not learn from our mistakes as
much as we might think (Meyvis, Ratner, & Levav, 2008; Wilson, Meyers, & Gilbert, 2001). However,
some techniques do show promise at improving our accuracy.
Prospective diaries. After demonstrating the traditional affective forecasting errors (overestimating
how long their feelings would last after a football win or loss), Wilson and colleagues (2001) had
participants think ahead to all of the things that may happen in their lives on a typical day. This broadened
perspective seemed to pull focus from the football game that was so overarching in their forecasts. As a
result, they did not overestimate how long their emotional reactions would linger. In practice, then, when
grappling with a decision of how happy or sad something may make you, it may increase accuracy if you
think ahead and imagine an ordinary day in your life. In their study on social interactions with an outgroup
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member, Mallett, Wilson, and Gilbert (2008) used a short term version of this to remind participants that
there is more to a person than their outgroup status. Techniques that encourage more big-picture processing
show promise at reducing certain kinds of forecasting errors.
Imagining one’s future self. Thinking accurately about the future is key to sound decision making.
However, we often think of our future selves as distant strangers, more like members of an outgroup
(Burum, Gilbert, & Wilson, 2016), which can make sound decision making difficult. They find that people
who feel connected to their future selves tend to make better, more ethical decisions (Hershfield, Cohen, &
Thompson, 2012). They are more likely to consider long-term consequences of their behavior and show
fewer signs of delinquency. While this is thought to be an individual difference (i.e., conscientiousness),
they have also found that strengthening the accessibility and saliency of the future self can improve longterm
decision making.
In one study, for instance, those who wrote a letter to their hypothetical future self were less inclined
to make impulsive, delinquent choices, relative to a control group. In a second study, the researchers
created age-progressed photographs of participants using a computer program. After interacting with this
“future self,” participants were less likely to cheat on a subsequent task, relative to controls (Van Gelder,
Hershfield, & Nordgren, 2013). Envisioning one’s future self in a vivid way (again, viewing ageprogressed
photos of oneself) also motivates people to save more for retirement (Hershfield et al., 2011)
because the distant future seems more accessible and concrete.
Surrogation. One promising correction to forecasting errors is to rely less on our own assessments
of our future feelings, which are often rather uninformed, and to instead consult other people, particularly
those who have experienced something like it themselves. This strategy is known as surrogation. In one
study (Gilbert, Killingsworth, Eyre, & Wilson, 2009), a group of college women were given the facts about
someone they were about to meet on a five-minute speed-date. Each woman learned facts—his hometown,
age, height, and favorite movie, and they also saw his photograph. Armed with this information, she could
imagine what the date might actually be like. Other participants were given a different woman’s account of
how her date with him actually went. Note that only the other woman in the study knows what he was
really like (at least, what could be revealed in the span of five minutes). And, indeed, the study found that
the women’s actual impression of him, after meeting him, aligned with that of the surrogate – the woman
who had spent time with him previously. Importantly, participants failed to realize this, believing that their
own, relatively uninformed impressions would be much more useful. This can easily give rise to
overconfidence.
In short, we overestimate our ability to accurately imagine and predict our feelings about future
events, and undervalue the experiences of people in our social networks. However, relying on the opinions
of well-informed others, be they friends or strangers (Eggleston, Wilson, Lee, & Gilbert, 2015), can help
undo forecasting errors.
Issues of Replication
Recently, the replicability of well-known social psychological phenomena has been called into
question (Open Science Collaboration, 2015) and affective forecasting research has not been exempted
from this criticism. One particular debate surrounds the legitimacy of the impact bias itself. In four studies
and a meta-analytic review, Levine, Lench, Kaplan, and Safer (2012) argue that the tendency to
overestimate the emotional reaction we have to future events is merely a procedural artifact. Specifically,
they argue that a disconnect occurs when participants are asked to predict future feelings very broadly,
without being given something specific to focus on, and this is the reason why errors are demonstrated. In
essence, forecaster participants may be imagining something very different from what experiencers are
rating. Any disconnect in their affect ratings, then, are inflated by this difference in focus. The authors
suggest that clarifying the forecasting question (i.e., what are participants supposed to be focusing on,
exactly?) reduces errors. In a response, Wilson and Gilbert (2013) state that Levine’s argument was
artificially bolstered by a highly selective literature review and a series of coding and translational
problems. In their response, Levine and colleagues (2013) maintained that their procedural revision (i.e.,
that a slight change in forecasting instructions eliminated the typical affective forecasting effect) reduced
forecasting errors somewhat, but agree that it has not been completely eliminated.
What Remains Unknown?
There is considerable research establishing the existence of affective forecasting errors, as well as on
the underlying mechanisms that account for their existence. Considerably less is known about individual
differences in forecasting abilities. While research on certain traits, such as mindfulness and emotional
intelligence, suggests some people are more accurate than others, more work on this topic is needed. The
same is true for the external conditions that make it especially difficult for one to predict future feelings
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accurately. To what extent do marketers feed into the impact bias, for instance? Finally, cross-cultural
differences in forecasting ability is a relatively unstudied topic that is worthy of investigation (although see
Lam et al., 2005, who demonstrated that East Asians tend to make more accurate forecasts than
Westerners, particularly for positive events).
Another important future direction involves dissecting when people are most likely to make
forecasting errors. To be certain, there are times when we are quite good at knowing when a decision is
good or bad – survival requires this precision. When, then, do the errors make themselves known? Is it a
function of novelty, such that brand-new, foreign experiences are harder to predict than the familiar? Are
we often misled by the erroneous opinions of others, for example, marketers convincingly arguing that their
product will bring us far more joy than we can reasonable expect? Breaking down the nuances of the
forecasting process – when we are accurate and when we are not – is yet another avenue for future
research.
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Eudaimonia in the Contemporary Science of Subjective WellBeing:
Psychological Well-Being, Self-Determination, and
Meaning in Life
By Samantha J. Heintzelman, University of Virginia
Citation
Heintzelman, S. J. (2018). Eudaimonia in the contemporary science of subjective well-being:
Psychological well-being, self-determination, and meaning in life. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
The human pursuit of well-being occupies space that extends beyond simply seeking pleasure, feeling good,
and being satisfied. In philosophy, Aristotle introduced the concept of “eudaimonia” to reflect human
flourishing as a reflection of virtue and the development of one’s full potential, in contrast to pleasurecentered
hedonic well-being. Within psychological science, traditional conceptualizations of subjective
well-being have also been expanded to include constructs that capture a more holistic version of well-being.
The goal of this chapter is to provide a comprehensive overview of psychological theory and research
regarding eudaimonic well-being. I will first briefly review the philosophical underpinnings of eudaimonia.
I will then shift focus to the utilization of eudaimonia within modern psychology, first reviewing the
ranging definitions and operationalizations of this concept used across the field. Next, I will review
theoretical and empirical examinations of eudaimonic well-being in comparison to hedonic
conceptualizations of well-being and discussions of limitations to the existing work in this area. In the next
section of this chapter, I will provide an overview of the active debate in the field regarding the value vs.
costs of maintaining a distinction between eudaimonic and hedonic well-being within psychological
science. To end, I will highlight major areas of psychological research falling under the umbrella of
eudaimonic well-being, including psychological well-being theory, self-determination theory, and meaning
in life. Finally, I will discuss several areas of future research focusing on eudaimonic well-being.
Keywords: well-being, eudaimonia, psychological well-being, self-determination theory, meaning in
life
While the pursuit of happiness is a near universal, the means to this happiness and the contours of
attained happiness can differ widely across people and situations. While happiness can be conceptualized
as the presence of positive feelings, the minimization of negative feelings, and a sense of satisfaction with
one’s circumstances, the three pillars of subjective well-being, there seems to be more to it than this (Ryff,
1989). Engagement in important work, making valuable contributions to society, and living in alignment
with a set of moral virtues, are a few among many features of a happy life that aren’t represented within the
realm of positive affect and satisfaction. A holistic view of psychological well-being includes constructs
that extend beyond affect and life satisfaction.
A eudaimonic perspective offers a class of constructs to paint an expanded and more complete
picture of psychological well-being. In this chapter I will review early philosophical perspectives of
eudaimonia before discussing the use of eudaimonia within modern psychological science. Then, I will
review the ongoing debate regarding the use of a hedonic vs. eudaimonic distinction in the study of wellbeing.
Finally, I will outline key research areas in psychological science that follow from the eudaimonic
perspective including psychological well-being, self-determination theory, and meaning in life.
Philosophy of Eudaimonia, Briefly
The concept of eudaimonia pervades philosophical treatments of ethics, beginning with Aristotle’s
Nicomachean Ethics (4th century B.C.E./2001), in which he forwarded eudaimonia—“activity expressing
virtue”—as an objectivist theory of happiness. Eudaimonia is most traditionally translated as “happiness,”
though the alternate translation used in much of contemporary philosophy is “flourishing.” In modern
philosophy many interpretations of, and commentaries on, Aristotle’s eudaimonia have been offered
(Annas, 1993; Haybron, 2008; Kraut, 1979; Norton, 1976; Tiberius, 2013). Shared among these is the
notion that eudaimonia is a reflection of virtue, excellence, and the development of one’s full potential
(Huta & Waterman, 2014). Rooted in these philosophical origins, eudaimonia refers to that which is worth
pursuing in life—an objective standard of goodness (Huta & Waterman, 2014).
Eudaimonia in Modern Psychology
In addition to spurring much philosophical discussion, Aristotle’s concept of eudaimonia has also
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been deeply impactful in the psychological study of well-being. Similar concepts began emerging in
humanistic theories of personality including Maslow’s self-actualization (1968) and May’s daimon (1969).
Such thinking developed over time and eudaimonia has now been adopted widely into the psychological
science of well-being. Yet, in this transition, one key aspect of eudaimonia changed; in psychology,
eudaimonia is now treated as a subjective state and this subjectivity is a central defining feature of this
psychological construct. For example, early psychological treatments of eudaimonia position it as the
subjective experiences related to doing what is worth doing and having what is worth having (Norton,
1976; Telfer, 1980).
Defining and operationalizing eudaimonia. Building on philosophical and early psychological
thinking about eudaimonia, various conceptual definitions and operationalizations arose to describe the
psychological experience of eudaimonic well-being. One definition suggests, “Eudaimonia, as a subjective
state, refers to the feelings present when one is moving toward self-realization in terms of the developing
one’s unique individual potentials and furthering one’s purposes in living” (Waterman, Schwartz, & Conti,
2008, p. 42). However, there is little agreement among scholars in this area regarding any one conceptual
definition of eudaimonia, nor is there a shared methodological approach for its study (Huta & Waterman,
2014).
Huta and Waterman (2014) outline the basic conceptual and operational definitions of eudaimonia
employed by a number of leading scholars in the field. For instance, Waterman (1993) uses self-realization
and personal expressiveness as core, defining features of eudaimonia, and suggests that eudaimonia is
“activity expressing virtue” (Waterman, 1990). Alternately, Ryff and colleagues conceive of eudaimonia in
a broader, trait-like manner, suggesting that eudaimonia is to be fully functioning and successful despite the
existential challenges of life (e.g., Ryff & Singer, 2008). Keyes (2002) integrates a component of social
well-being into his conceptualization of eudaimonia, while Huta (2015) treats eudaimonia as a motive to
develop the best in oneself. Bauer, McAdams and Pals (2008) study eudaimonia from a narrative
perspective and consider it in terms of psychosocial integration, ego development, and personal growth.
Ryan and Deci (2001) suggest that eudaimonia is living a life in full accord with one’s potential, Delle
Fave, Brdar, Freire, Vella-Brodrick, and Wissing (2011) consider eudaimonia as flow experiences and
long-term meaning-making, and Seligman (2002) claims that eudaimonia is a product of one’s
characteristic personality traits or strengths.
To accompany these varied conceptualizations of eudaimonia, there are also many
operationalizations used in studying these concepts. Eudaimonia can be measured at the trait level. For
instance, Ryff’s (1989) Scales for Psychological Well-Being have been widely used in this area of study.
Additional trait assessments of eudaimonia exist. The Questionnaire for Eudaimonic Well-Being
(Waterman et al., 2010) taps six dimensions: self-discovery, perceived development of one’s best
potentials, sense of purpose and meaning in life, investment of effort in pursuit of excellence, intense
involvement in activities, and enjoyment of personally expressive activities. Alternately, Keyes’ (2002,
2006) Mental Health Continuum assesses psychological, social, and emotional well-being with a variety of
subscales. Eudaimonia has also been measured at the state level using scales such as the Personally
Expressive Activities Questionnaire (Waterman, 1993), which assesses engagement in self-defining
activities.
These scales also vary in their specificity, each targeting a different theoretical conceptualization of
eudaimonic well-being. In recent years, additional scales have been developed with an aim towards
capturing the broad range of concepts included in psychological success. First, the Flourishing Scale is an
8-item scale capturing various aspects theorized to be important to eudaimonia, including positive
relationships, feelings of competence, and meaning and purpose in life (Diener et al., 2010). An even
broader measure of psychological well-being conceptualizations can be found in the Comprehensive
Inventory of Thriving (Su, Tay, & Diener, 2014). This scale was developed in a theory-driven manner, first
identifying seven core theoretical dimensions of psychological well-being based on prominent theories
throughout the literature. These include: subjective-well-being, supporting and enriching relationships,
interest and engagement in activities, meaning and purpose in life, mastery and accomplishment, control
and autonomy, and optimism (Diener, 1984; Ryan & Deci, 2000; Ryff, 1995; Scheier & Carver, 1985;
Seligman, 2011), for a more holistic measurement approach towards well-being.
Comparing eudaimonic and hedonic well-being. One cross-cutting theme inherent in most
definitions of eudaimonia is the exclusion of an affective, or hedonic, component (Disabato, Goodman,
Kashdan, Short, & Jarden, 2016). Indeed, eudaimonic well-being is often discussed in contrast to hedonic
well-being (e.g., Ryan & Deci, 2001; Waterman, 1993). Contrary to eudaimonia, the ideas of hedonic wellbeing
philosophers such as Aristippus, Bentham, and Mill were centered on the notion that pleasure is the
highest good (Tatarkiewicz, 1976). Early work examining happiness from a psychological perspective did
not discuss a hedonia/eudaimonia distinction (e.g., Brickman & Campbell, 1971; Easterlin, 1974; Wilson,
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1967). However, more recently, research in this area has begun to distinguish, and contrast, these two
conceptualizations of happiness.
When comparisons are drawn between eudaimonic and hedonic well-being, the concept most
frequently used to indicate hedonic well-being is subjective well-being. Subjective well-being consists of
high levels of positive affect, low levels of negative affect, and the cognitive appraisal that one is satisfied
with the conditions of his or her life (Diener, 1984). Certainly, subjective well-being encompasses a
broader range of experiences than simple hedonic pleasure, including values, goals, and need fulfillment
(e.g., Ryan & Deci, 2001). Yet, eudaimonia scholars most frequently invoke subjective well-being as the
hedonic side of the dual-conceptualizions of well-being. Subjective well-being research has proliferated in
recent decades (Diener et al., 2017; Diener, Suh, Lucas, & Smith, 1999). Noting subjective well-being’s
seeming domination of well-being research, Ryff (1989) countered with an argument for a more inclusive
conceptualization of well-being that captured a broader range of what it meant to be well. As these two lines
of well-being research have grown, they are often compared and contrasted.
Empirical examinations. The distinction between eudaimonic and hedonic well-being has been the
focus of empirical investigation. First, there is a good amount of evidence that eudaimonic and hedonic
well-being are strongly related, and experienced simultaneously. For example, Waterman (1993) found that
the personal expressiveness reported for activities, an indicator of eudaimonia, related to the hedonic
enjoyment of that activity, with correlations ranging from .71 to .86 across activities and studies. In three
subsequent studies, similar relationships between feelings of personal expressiveness and hedonic
enjoyment have been found, ranging from .83 to .87, indicating that these two state-level measures
regarding one’s experiences during specific activities share a large variance overlap of about 68% to 76%
(Waterman et al., 2008).
While these concepts tend to be very closely related, factor analytic work has demonstrated a
statistical separation between hedonic and eudaimonic measures. Most research examining the factor
analytic separations of hedonic and eudaimonic constructs have utilized trait measures of each, diverging
from the more state-oriented measures utilized in the correlational work noted previously. For instance, in a
study including 18 trait-like mental health measures, separate, though correlated, subjective well-being and
personal growth factors emerged (Compton, Smith, Cornish, & Qualls, 1996).
Additional studies have utilized factor-analytic techniques to examine hedonia, following Diener’s
(1984) model of subjective well-being introduced earlier in this chapter, and eudaimonia, following Ryff’s
model of psychological well-being, which will be examined further in a subsequent section of this chapter.
First, Keyes, Shmotkin, & Ryff (2002) examined these relationships among U.S. adults. When forcing the
loadings to fit a theoretical two-factor structure with correlated eudaimonic and hedonic well-being, these
factors shared a very high correlation of .84. Furthermore, exploratory factor analyses revealed substantial
cross-loadings for some subscales meant to indicate eudaimonic well-being, onto a hedonic well-being
factor as well. These findings seem to indicate a lack of distinctiveness between these two versions of wellbeing,
though the authors conclude confirmation of their hypotheses for “related but distinct conceptions of
well-being” (Keyes et al., 2002, p. 1017). The two-factor structure with high correlations between latent
eudaimonic and hedonic factors was also found in a similar U.S. adult sample, r = .78, and was even
stronger in an undergraduate sample, r = .92 (Gallagher, Lopez, & Preacher, 2009). In similar analyses
utilizing samples from the UK, Linley et al. (2009) found clean two-factor loadings for hedonic and
eudaimonic measures of well-being in exploratory factor analyses. Furthermore, in a confirmatory model,
they found a correlation of .76 between the two factors (Linley, Maltby, Wood, Osborne, & Hurling, 2009).
A similar pattern pointing to the correlated distinction between measures of hedonic and eudaimonic wellbeing
measures has been replicated (e.g., Robitschek & Keyes, 2009) including within a variety of
populations including a South African sample (Keyes et al., 2008). Finally, Disabato et al. recently (2016)
examined the dimensionality of well-being in an international study with participants spanning over 100
countries, including a number of metrics for both hedonic and eudaimonic well-being. They compared a
one-factor model, with all measures indicating a single factor, against a two-factor solution, with the
hedonic measures indicating one factor and the eudaimonic measures indicating another. Both solutions fit
equally well and furthermore, in the two-factor solution, the factors correlated at r = .96 indicating a shared
variance of about 92% (Disabato et al., 2016). Clearly eudaimonia and hedonia are closely linked.
In developing the CIT measure discussed above to capture the breadth of the human experience of
thriving, Su et al. (2014) identified 18 facets of psychological well-being, including constructs from both
eudaimonic and hedonic traditions. They found excellent fit for a model with correlated latent factors for
each well-being facet suggesting correlated, yet distinguishable, psychological well-being constructs.
Furthermore, correlations among the facets were typically of moderate size, consistent with the conclusion
that these construct scales are relative but distinct. Still the more eudaimonia-oriented facets of the CIT
were highly correlated with subjective well-being measures, for instance, the CIT meaning facet shared a
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correlation of r > .80 with subjective well-being measures.
Using a more sophisticated analytic technique, Chen et al. (2012) utilized a bifactor model to
capture the shared variance between measures of eudaimonic and hedonic well-being as well as their
unique predictive contributions. They identified a strong general factor shared by the measures as well as
two specific factors that each demonstrated predictive power independent of their shared, general factor
variance (Chen, Jing, Hayes, & Lee, 2012).
Together, this body of work suggests that eudaimonic and hedonic well-being are strongly related to
one another, yet can be potentially differentiated statistically. However, there is certainly substantial
overlap between the two, leaving the discussion regarding their independence unresolved and indicating the
necessity of additional research to build a more thorough understanding of these concepts themselves and
together.
Beyond utilizing factor analytic techniques to examine the structure of happiness, this technique has
also been employed to examine the relationships between eudaimonic and hedonic factors and other
variables. In a series of studies, feelings of personal expressiveness in an activity, a eudaimonic indicator,
were more strongly linked to finding that activity to provide opportunities for the development of one’s
potential, self-realization, and feelings of being challenged, competent, and assertive, for example, whereas
hedonic enjoyment, on the other hand, was more strongly related to feeling relaxed, excited, content,
happy, and interested (Waterman, 1993; Waterman et al., 2008). Across a series of daily diary studies,
reported engagement in eudaimonic behaviors was more strongly and consistently related to feeling that life
is meaningful and satisfying than engagement in hedonic behaviors (Steger, Kashdan, & Oishi, 2008).
In additional cross-sectional and experience sampling studies examining hedonic and eudaimonic
pursuits both between and within persons, Huta and Ryan (2010) found hedonic pursuits to relate more
strongly to positive affect and carefreeness, while eudaimonic pursuits related more to meaning.
Furthermore, an experimental intervention study has been conducted in which participants were randomly
assigned to complete hedonic or eudaimonic activities for 10 days. Those in the hedonic activities
condition reported more well-being benefits immediately following the intervention, whereas those in the
eudaimonic activities condition reported greater well-being in a follow-up assessment 3 months later (Huta
& Ryan, 2010). It seems, then, that both hedonic and eudaimonic pursuits are important avenues to wellbeing,
albeit different aspects and with different time frames.
There is also some evidence supporting Telfer’s (1980) theoretical notion that eudaimonia is a
sufficient, but not a necessary condition for experiencing hedonic enjoyment. Examining events that were
rated as very high or very low on personal expressiveness and hedonic enjoyment, 4/5 of activities rated as
providing a great sense of personal expressiveness were also rated as very hedonically enjoyable, whereas
only about 1/3 of highly hedonically enjoyable activities were also associated with personal expressiveness
(Waterman et al., 2008). From this asymmetric finding, which was consistent across three samples, the
authors concluded that activities that bring about a sense of eudaimonia are a subset of those that lead to
hedonic enjoyment (Waterman et al., 2008). Similarly, Keyes and Annas (2009) found that while 48.5% of
individuals in the MIDUS sample reported high levels of hedonic well-being, only 18% were categorized as
“flourishing,” that is, expressing high levels of both hedonic and eudaimonic well-being. Furthermore, they
found that those who were not flourishing, but experiencing high levels of hedonic well-being with only
moderate or low levels of eudaimonic well-being, reported much greater rates of mental illness compared
with those who were high on both types of well-being (Keyes & Annas, 2009).
Limitations. The inconsistencies within the literature regarding the roles of eudaimonia and hedonia
in an individual’s well-being stem from a number of different sources. First, as mentioned, the diverse array
of conceptualizations of eudaimonia complicates comparisons with hedonic well-being and can account for
some differences in findings. Without systematic evaluations of these findings that take into account the
conceptualizations of each construct employed, these findings remain muddled. This is especially
problematic when comparisons are made between treating hedonia as a way of feeling and eudaimonia as a
way of behaving (Huta & Ryan, 2010; Huta & Waterman, 2014). Similarly, as Huta and Waterman (2014)
point out, some comparisons treat hedonia as cognitive-affective experiences while treating eudaimonia as
mental functioning or trait level orientations (Compton et al., 1996; Gallagher et al., 2009; Keyes et al.,
2002; McGregor & Little, 1998) and such asymmetrical treatments can make direct comparisons of their
relationships with each other and predictors and outcomes difficult. Finally, the strong correlation between
the two conceptualizations of well-being leaves questions regarding the nature of their differential
relationships with outside variables as these seem to represent only the extreme ends of both the eudaimonic
and hedonic sides of well-being, which seem to be poor representations of the concepts as they are
experienced in daily life.
Eudaimonia in Psychology: A Misleading or Valuable Distinction?
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The mixed evidence above regarding the divergence of eudaimonic well-being from hedonic wellbeing
and plentiful discussions of the limitations within this area, preview an ongoing debate within the
well-being literature regarding the utility of eudaimonia as a concept within the psychology of well-being.
The critique of eudaimonia that has generated the most discussion regarding these concerns was published
by Kashdan, Biswas-Diener, and King (2008).
In this piece, Kashdan and colleagues (2008) argue that the philosophical distinction between
hedonic and eudaimonic well-being does not carry over well into the psychological science of well-being
and present a number of critiques to support this argument. I have discussed a few of their criticisms
previously in this chapter. Namely, that the field of eudaimonic well-being lacks concise conceptual and
operational definitions and, furthermore, that the existing definitions and measurement strategies fail to
fully capture the concept of eudaimonia forwarded by Aristotle. In similar critique, Kashdan et al. (2008)
argue that the subfield of eudaimonia research suffers from not having a uniting theory to encompass its
many arms, and they suggest that such a theory would be problematic anyway given the diversity of the
field and the loss of information that would result from a single theory of eudaimonic well-being. This
“looseness” or vagueness of definitions and lack of unification has been discussed elsewhere as well (e.g.,
Huta & Waterman, 2014; Waterman, 2008), yet adequate solutions to these problems remain to be seen.
Kashdan et al. (2008) raise additional concerns regarding the appropriateness of drawing
comparisons between hedonic and eudaimonic well-being. First, they argue that this distinction promotes
the notion that the two conceptualizations of well-being exist on a moral hierarchy with eudaimonic wellbeing
claiming the superior position (Waterman, 2007). Narrowly, that subjective well-being, the most
commonly used conceptualization of hedonic well-being, occupies the lower ranks of this hierarchy is
questionable given the plentiful research pointing to the wide benefits of subjective well-being and success
in a host of life domains (Lyubomirsky, King, & Diener, 2005). More broadly, this hierarchy is problematic
if well-being is to be considered a subjective human experience. This highlights the stark distinction
between the psychological study of subjective eudaimonia and its roots in objectivist philosophy.
Arguments have been forwarded suggesting that the study of eudaimonic well-being is more about why
someone is happy rather than an accurate subjective assessment of whether someone is happy, which
conflates the experience of happiness with the common sources of this experience (Kashdan et al., 2008).
Kashdan et al.’s (2008) critique of eudaimonic well-being’s place within psychological science
opened a lively discussion about the merits and problems of eudaimonia throughout the well-being field,
even eliciting several direct responses (Delle Fave & Bassi, 2009; Keyes & Annas, 2009; Ryan & Huta,
2009; Waterman, 2008). For example, Keyes and Annas (2009) argued, “hedonism logically can’t be a
rival to eudaimonism on its own level. It is one of the options within eudaimonism” (p. 198). Even more
broadly, Waterman (2008) suggested that it is perhaps too early in the history of the psychological science
of eudaimonia to engage in such pointed critiques regarding the shortcomings of this work in the first place.
Eudaimonic Concepts in the Science of Well-Being
Both sides of this debate do share some common ground in finding value in many of the constituent
parts of the eudaimonic tradition. The concept of eudaimonia, regardless of its function within the study of
well-being in and of itself, provides an umbrella under which to discuss aspects of psychological well-being
that aren’t included in present psychological definitions of subjective well-being, or happiness, which
include only affective feelings and satisfaction with life. Kashdan et al. (2008) recommended referring to
specific constructs under this umbrella rather than discussing the broad categories of hedonia and
eudaimonia. Here, I will examine three major areas of study that align with a eudaimonic approach to wellbeing:
psychological well-being theory, self-determination theory, and the study of meaning in life. I will
also briefly mention several other concepts that also occupy a space within this literature.
Psychological Well-Being Theory. In response to the seeming takeover of well-being field by
research focused on the concept of subjective well-being, Carol Ryff (1989) argued that the state of this
area of study was suffering from a lack of theoretical grounding and definitional precision regarding the
essential features of well-being. To supplant this limitation, Ryff (1989) proposed an alternate, wider,
model of psychological well-being driven by diverse theoretical perspectives regarding positive human
functioning. Drawing upon some of the most well-known theories from developmental, clinical, existential,
and humanistic psychology (e.g., Allport, 1961; Erikson, 1959; Frankl, 1959; Jung, 1933; Maslow, 1968),
Ryff’s model of psychological well-being includes six central dimensions: self-acceptance, positive
relations with others, autonomy, environmental mastery, purpose in life, and personal growth.
To highlight the central features of each factor briefly: (1) self-acceptance refers to the awareness
and acceptance of one’s personal strengths and weaknesses; (2) positive relationships with others refers to
deep connections with significant others; (3) autonomy is living in accordance to one’s own convictions;
(4) environmental mastery is managing life situations; (5) purpose in life is the extent to which one’s life
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feels meaningful and purposefully directed; and (6) personal growth is achieved when one is using his or
her personal talents and potential (Ryff, 1989, 2014; Ryff & Singer, 2006). Four of these six dimensions of
well-being (positive relations, autonomy, purpose, and growth) had not been previously included in other
measures of well-being, despite their role in theories of positive functioning, highlighting the novel
contributions of this model (Ryff, 1989).
In the decades since the advent of this model of psychological well-being, much research has
developed following this widened conceptualization of well-being (Ryff, 2014). First, research regarding its
factor structure has been conducted, with numerous papers reporting replications of the theoretical sixfactor
structure of this model (e.g., Clarke, Marshall, Ryff, & Wheaton, 2001; Gallagher et al., 2009; Ryff
& Keyes, 1995). Still, elsewhere, this six-factor model has been challenged and the factor structure has not
always replicated (Kafka & Kozma, 2002; Springer & Hauser, 2006). More extensive discussions of the
factor-structure replications can be found elsewhere (Ryff, 2014; Ryff & Singer, 2006; Springer & Hauser,
2006).
In addition, work following the psychological well-being tradition has focused on examining age
and gender profiles in well-being (Ryff & Keyes, 1995; Springer, Pudrovska, & Hauser, 2011) and
additional psychosocial and sociodemographic correlates of eudaimonia (Keyes et al., 2002; Ryff & Singer,
2008). For example, findings suggest that adults with higher psychological well-being than subjective wellbeing
were younger, more educated, and were more open to experience (Keyes et al., 2002). Furthermore,
research examining the biological underpinnings of psychological well-being and its importance for health
has been growing in recent years (Ryff, 2013). Some initial findings point to connections between
eudaimonic well-being and lower salivary cortisol, decreased cardiovascular risk, and better sleep (Ryff,
Singer, & Love, 2004). Subsequent work has identified relationships between some factors of eudaimonic
well-being and important inflammation indicators (Friedman & Ryff, 2012; Morozink, Friedman, Coe, &
Ryff, 2010).
Much of the work highlighting the empirical comparisons of hedonic and eudaimonic well-being
utilized Ryff’s conceptualization of psychological well-being as an indicator of eudaimonia and note small,
yet predictive, differences compared to subjective well-being. Overall, research in this area highlights the
advancements made following a well-conceptualized theoretical approach to eudaimonic well-being.
Self-Determination Theory. Another broad theory that embraces a eudaimonic conceptualization
of well-being is self-determination theory. Self-determination theory considers self-realization, or
eudaimonia, as the key defining feature of well-being and focuses on specifying the processes through
which self-actualization can be achieved (Ryan & Deci, 2001). Ryan and Deci (2000) inductively identified
three basic psychological needs—autonomy, relatedness, and competence—essential for optimal growth
and integration and constructive social development (Ryan & Deci, 2000). As such, the satisfaction of these
three needs fosters eudaimonic well-being. Note that unlike psychological well-being theory reviewed
previously, which defines eudaimonic well-being in terms of principle factors similar to autonomy,
relatedness, and competence, self-determination theory posits that these needs foster, rather than define,
well-being (Ryan & Deci, 2001).
The extent to which the basic self-determination needs are satisfied also determines variability in
intrinsic motivation (Ryan & Deci, 2000), another concept central to self-determination theory and closely
tied to eudaimonic conceptualizations of well-being. Intrinsic motivation reflects positive human potential
and represents the inherent tendency to pursue novelty and challenge, explore, learn, develop, and grow
(Ryan & Deci, 2000), all central to well-being from a eudaimonic perspective. According to selfdetermination
theory, the satisfaction of the three basic needs and intrinsic motivation across the lifespan
are necessary for human thriving (Ryan & Deci, 2000).
Supporting these claims tying needs satisfaction and intrinsic motivation to the fulfillment of human
potential, researchers working within the self-determination theory framework have found that the pursuit
of some, but not all goals, satisfy these basic needs and, subsequently, enhance eudaimonic well-being
(Ryan, Sheldon, Kasser, & Deci, 1996). First, whereas intrinsically driven goals, such as affiliation,
growth, and community, satisfy these three basic needs directly, other more extrinsically motivated goals,
like wealth, fame, and image do not (Ryan et al., 1996). Additionally, focusing on intrinsic aspirations
relates positively to indicators of well-being central to the eudaimonic tradition, such as self-actualization,
or the fulfillment of one’s potential, while focusing on extrinsic aspirations shares an opposite, negative,
relationship (Kasser & Ryan, 1993, 1996; Ryan et al., 1999).
While self-determination theory has always aligned with eudaimonic thinking (Ryan & Deci, 2001),
this connection was taken a step further more recently, with the introduction of a formalized model of
eudaimonia based in self-determination theory (Ryan, Huta, & Deci, 2008). From a self-determination
theory perspective, this model categorizes eudaimonic living into four central motivational concepts: (1)
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pursuing intrinsic, rather than extrinsic, goals and values, (2) behaving in an autonomous and volitional,
rather than controlled, manner, (3) being mindful and acting with awareness and (4) behaving in need
satisfying ways (Ryan et al., 2008).
Much research in the area of self-determination theory has focused on the relationship between
goals, needs, and conceptualizations of well-being beyond the eudaimonic tradition, including, as well,
more hedonically oriented conceptualizations of well-being (Ryan & Deci, 2001). For instance, the
attainment of intrinsic goals was found to enhance hedonic well-being, measured with four items: happy,
joyful, pleased, and enjoyment/fun, while succeeding at extrinsically oriented goals does not (Sheldon &
Kasser, 1998). Similarly, goals that satisfy the three basic psychological needs, autonomy, competence, and
relatedness, contribute to hedonic well-being more than other goals (Sheldon & Elliot, 1999). Furthermore,
daily fluctuations in the satisfaction of the basic self-determination needs predicted daily fluctuations in
mood (Reis, Sheldon, Gable, Roscoe, & Ryan, 2000; Sheldon, Ryan, & Reis, 1996). This work suggests
that psychological needs satisfaction is not only relevant for living a eudaimonic life, but also for concepts
within the realm of hedonic well-being. Still, leading self-determination theory scholars maintain the
distinction between hedonic and eudaimonic well-being (Ryan and Deci, 2001), noting that there some
conditions that foster hedonic well-being that don’t promote eudaimonic well-being (Nix, Ryan, Manly, &
Deci, 1999).
Meaning in Life. A third large area of research under the umbrella of eudaimonic well-being
focuses on the experience of meaning in life. Feeling that one’s life is meaningful is a fundamental human
motivation (Baumeister, 1991; Frankl, 1984; Klinger, 1977; Maslow, 1968) that has been theorized to be an
essential indicator of eudaimonic well-being. While meaning and purpose in life are included as a factor in
Ryff’s psychological well-being model, an extensive body of work on this topic now exists independent of
that framework.
Like other eudaimonic concepts, meaning in life is somewhat difficult to define (e.g., Heintzelman
& King, 2013). Yet recent strides have been made in this literature towards a consensus definition of
meaning in life. One representative definition of meaning in life states that, “Lives may be experienced as
meaningful when they are felt to have a significance beyond the trivial or momentary, to have purpose, or
to have a coherence that transcends chaos” (King, Hicks, Krull, & Del Gaiso, 2006, p. 180). This definition
highlights three central aspects of the experience of meaning in life: purpose, significance, and coherence
(George & Park, 2016a, 2016b; Heintzelman & King, 2013; 2014a, 2014b; Martela & Steger, 2016).
Purpose refers to engagement in goal directed pursuits: Striving towards personally significant goals is
related to feelings that life is worth living (Battista & Almond, 1973; Emmons, 2003; McGregor & Little,
1998; McKnight & Kashdan, 2009; Vallerand, 2008). Significance is the feeling of mattering or making an
impact, and building a legacy that will transcend the self (George & Park, 2016a). Coherence is the degree
to which stimuli, events, and one’s life make sense and fit with expectations (Antonovsky, 1993; Battista
& Almond, 1973; Baumeister & Vohs, 2002; Heine, Proulx, & Vohs, 2006; Heintzelman, Trent, & King,
2013).
Meaning in life research has focused, in large part, on the antecedents and consequences of
reporting that one’s life is meaningful. Many aspects of life relate to, or causally lead to, feeling like that
life is meaningful. These sources of meaning in life include, but are not limited to, social relationships such
as family and friends (Lambert, Clark, Durtschi, Fincham, & Graham, 2010; Lambert, Stillman, Kamble,
Baumeister, & Fincham, 2013), religion (Hicks & King, 2008; Steger & Frazier, 2005), and regularities
(Heintzelman et al., 2013). In terms of consequences, high levels of meaning in life are associated with a
number of beneficial outcomes across a host of life domains, for example better physical health (for
review, see Roepke, Jayawickreme, & Riffle, 2014), mental health (Heisel & Flett, 2004; Mascaro &
Rosen, 2005; Owens, Steger, Whitesell, & Herrera, 2009; Steger & Kashdan, 2009), and social functioning
(Stavrova & Luhmann, 2016; Stillman, Lambert, Fincham, & Baumeister, 2011).
Some recent meaning in life research highlights some inconsistencies that emerge when maintaining
a traditional hedonic/eudaimonic distinction. First, a strong relationship (r ≈ .65) between meaning in life
and positive affect is consistently replicated across this literature, and furthermore, inducing a positive
mood also enhances meaning in life, suggesting positive affect is another source of meaning (King et al.,
2006). In addition, eudaimonic well-being is often situated as the morally superior form of well-being, in
part, because it is thought to be more difficult to attain than its hedonic counterpart. However, recent
research suggests that meaning in life is a very common human experience across populations
(Heintzelman & King, 2014a) that responds to momentary experience (Machell, Kashdan, Short, & Nezlek,
2015) and is related to automatic, default, intuitive cognitive processing systems (Heintzelman & King,
2016).
Additional eudaimonic concepts. In addition to growing research following each of the three
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traditions elaborated above, there is also an abundance of other psychological concepts following a
eudaimonic approach to well-being. I will review four such concepts, selecting those that have
comparatively larger surrounding research literatures among the battery of existing eudaimonic concepts.
First, well-being theorizing and research has engaged in efforts to conceptualize “the good life.”
King and Napa (1998) found that folk concepts of the good life nearly always include both happiness and
meaning in life, and additional work demonstrated the necessity of fulfilling personal relationships for a
“good life” (Twenge & King, 2005). Finally, effort also seems to play a role in beliefs about the good life
as participants rated a meaningful and effortful life as most morally good, while rating a happy and
effortful life as most desirable, happy, and meaningful (Scollon & King, 2004).
Another subarea of research within the domain of eudaimonic well-being is Csikszentmihalyi’s
(1975) concept of “flow” experiences. Namely, flow occurs when one exerts “voluntary effort to
accomplish something difficult and worthwhile,” typically at the intersection of task challenges and one’s
skill level (Csikszentmihalyi, 1990). Flow states are characterized by intense focus and a loss of reflective
self-consciousness and temporal awareness in which activity engagement is itself rewarding (Nakamura &
Csikszentmihalyi, 2014). The concept of flow has even merged into larger areas of study within the
eudemonic tradition, namely self-determination theory research (e.g., Schüler, Brandstätter & Sheldon,
2013).
Still another concept within the psychological science of eudaimonia is the human propensity for
growth, or ego development (Loevinger, 1976). Growth is often studied by examining the narrative
accounts people produce about their own lives and experiences, reconstructing the past and imagining the
future (McAdams, 2001). People who have high levels of eudaimonic well-being tend to emphasize
personal growth in their narratives and tend to frame difficult experiences as transformative (Bauer et al.,
2008). As such, growth seems to be another important aspect of eudaimonia.
Lastly, character strengths also occupy space in the realm of eudaimonic well-being concepts.
Character strengths can be defined simply as “positive traits reflected in thoughts, feelings, and behaviors”
(Park, Peterson, & Seligman, 2004, p. 603). Peterson and Seligman (2004) identified 24 ubiquitously
acknowledged strengths of character by examining core virtues shared by world cultures throughout
history. These strengths fit into six categories: wisdom, courage, humanity, justice, temperance, and
transcendence. In research regarding positive intervention activities, participants who identified their
character strengths and used them in new ways reported improvements in happiness, measured with items
tapping the pleasant life, the engaged life, and the meaningful life, that lasted over a six-month period
(Seligman, Steen, Park, & Peterson, 2005).
Conclusions & Future Directions
Recent decades of psychological science have certainly contributed much to the centuries-old
concept of eudaimonia. This approach has widened the scope of well-being research to include concepts
beyond simple pleasure seeking to encompass, as well, those parts of life that are virtuous and meaningful.
Still, examining eudaimonic well-being from a psychological science perspective as a subjective experience
is a fairly new area of study (Waterman, 2008). As such, many critiques remain yet to be fully overcome
(e.g., Huta & Waterman, 2014; Kashdan et al., 2008). Within the study of eudaimonia, more conceptual
clarity is needed to move the field forward in a unified manner (Huta & Waterman, 2014).
There remain many doors open for further research following the eudaimonic tradition. Of course,
research is currently thriving within subtopic areas in this field, including psychological well-being, selfdetermination
theory, and meaning in life, and the momentum within these areas will continue to propel
them forward in their own interesting and informative directions. In addition to research within these
subareas, there are also many lingering questions broadly regarding the roles of hedonia and eudaimonia
for overall human well-being. There now exists strong support that both hedonic and eudaimonic pursuits
lead to well-being (McGregor & Little, 1998; Ryan & Deci, 2001; Seligman, 2002). However, more work is
needed to understand how hedonic and eudaimonic variables affect one another (Kashdan et al., 2008). Su
et al. (2014, p. 4) stated, “Enrichment of other dimensions of psychological well-being (e.g. mastery or
social relations) can, through a dynamic and reciprocal relationship, enhance [subjective well-being].” The
question remains, however: Is eudaimonia a means to more hedonic states such as those captured by
subjective well-being, or is it, itself, an end? Perhaps this question and others like it are strictly
philosophical. However, psychological science now offers insight into a countless number of big questions
that were also once deemed too lofty to study empirically. Currently researchers from hedonic and
eudaimonic traditions limit their examinations the opposite conceptualization of happiness when trying to
distinguish their own ideas as unique (or superior). In order to make forward progress on such deep
questions, it will be important, and even necessary, for research to take a balanced approach to these
perspectives simultaneously.
175
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2018 Ed Diener. Copyright Creative Commons: Attribution, noncommercial, no
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Do It! Activity Theories and The Good Life
By Joar Vittersø, University of Tromsø, Norway
Citation
Vittersø, J. (2018). Do it! Activity theories and the good life. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
Ever since the Aristotelian conception of happiness as activity of the soul to modern perspectives on the
ever-active biological organism, the doing part of life has been considered essential for survival and
wellbeing. Humans must act in order to live—and live well. The basic assumption of activity theories of
wellbeing is that doing things in certain ways and for particular reasons constitute a kind of goodness in
itself. We can act in ways that are good for us, and we can act in ways that are bad for us. In the current
chapter, philosophical, economical and psychological theories are presented and critically analyzed in
order to clarify how activities can be regarded as a crucial ingredient of wellbeing. Possible mechanisms
accounting for the association between activities and the concept of goodness are introduced, and
theoretical disputes and empirical controversies between them are discussed.
Keywords: Happiness, Activities, Aristotle, Welfare, Internal motivation, Flow, Self-determination,
Functional wellbeing, Needs
It was Ed Diener, in his now classic 1984 article, who introduced the category of activity theories to
the taxonomy of wellbeing theories. In Diener’s scheme, the view that happiness is a “by-product” of being
active was named as activity theory and contrasted with telic theories of wellbeing. To illustrate the
concept, Diener used the example of ascending a mountain: the climbing itself might bring
greater happiness than reaching the summit. Telic theories are, according to the Diener classification, not
able to explain this kind of goodness, since they are restricted to account only for the pleasure of
accomplishing a goal—like reaching the peak of a mountain. Activity theories on the other hand, are able
to explain the pre-goal element of wellbeing, and in Diener’s article, Aristotle’s function argument and
Csikszentmihalyi’s writings on flow experiences were presented as examples of activity theories of a good
life.
Wellbeing 1 typically refers to a life that goes well 2, hence activity theories must clarify what it is that
can go well for a person during an activity. The critical question is how to categorize something as good
even if it does not include goal accomplishment or need fulfilled. The present chapter reviews some of the
theories aiming to explain this puzzle and it starts by investigating the notion of activity itself. It proceeds
by presenting some historical and philosophical ideas on the issue and moves on to examine the
contribution from welfare economics. The final part of the text critically discusses four psychologically
activity theories.
Being Active Is The Modus Operandi Of Human Life
To live means to be active and it is activity—not passivity— that is the modus operandi of our lives
(Mayr, 1982; Pross, 2016). In stark contrast to what some philosophers have speculated, like Jean-Jacques
Rousseau who argued that indolence was the natural condition of human life (see Ciulla, 2000), we must
continuously be active in order to keep our biological and psychological structures organized.
The importance of being active was recognized by the psychology pioneers, not at least among those
with a biological orientation (e.g., Allport, 1961; Angyal, 1941; deCharms, 1968; Deci & Ryan, 1985;
Elkind, 1971; Goldstein, 1939; Hebb, 1955; Henle, 1956; Loevinger, 1976; Rogers, 1963; von Bertalanffy,
1952/2014; White, 1959; Woodworth, 1918). The term organismic was introduced to explain how all living
systems are organized as parts of a unified whole, and how this holistic system seems to be continuously
active and self-regulated toward a two-folded goal of both preserving and expanding their organic
structure. Giants like Piaget and Vygotsky considered activity to be essential not only for basic life
regulation, but for all psychological actions, including the formation of cognitive structures (see Fischer &
Bidell, 2006). No wonder then, that a scholar such as Brandstätter (2006) argues that action is the center of
what people are and how they develop.
Philosophical and Historical Approaches
Aristotle
The significance of activity for human goodness was discussed long before the birth of scientific
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psychology, and, not surprisingly, Aristotle had an articulated opinion about it. Activities are important to
Aristotle’s theory on wellbeing, but he does not start his argument with that concept. He begins with the
notion of goals.
Aristotle paid close attention to the world around him and this led him to believe that all creatures were
driven by a goal. All forms of life, Aristotle realized, have a purposeful character. Based on this insight he
proposed the idea of a ‘summum bonum’ or ultimate goal. All things, living and non-living, searched
towards this goal. The Greek philosopher was wrong, however, in including non-living things in this telic
principle, but as far as biological organisms goes, his ideas about their goal-oriented nature was spot on.
Modern biologists no longer refer to it as telos, though, they call it ‘teleonomy’ (Pross, 2016).
Since Aristotle’s thinking is essentially telic, Diener’s categorization of it as an activity theory in
opposition to the telic theories might appear as somewhat misleading. However, the important ‘function
argument’ in Aristotelian theory articulates a close association between goals and activities (e.g.,
Korsgaard, 2008; Whiting, 1988). The theory is in a sense both a telic and an activity theory and one could
say with MacIntyre (2007) that it is “only because human beings have an end towards which they are
directed by reason of their specific nature, that practices, traditions, and the like are able to function as they
do.” Despite its telic grounding, Aristotelian happiness is often defined with reference to an activity, more
specifically the kind of activity that takes place “in the rational part of the soul performed well, which is to
say, in accordance with virtue.” (Korsgaard, 2008, p. 129). Aristotle conceived of virtues as “dispositions
not only to act in particular ways, but also to feel in particular ways.” (MacIntyre, 2007, p. 149).
MacIntyre has further interpreted Aristotelian happiness as a “state of being well and doing well in
being well” (MacIntyre, 2007, p. 148). He thus indicate that the doing well part refers to the practice of
actively pursuing the ultimate human goal, which, according to Aristotle, is one and the same for all of us,
as dictated by our human nature (e.g., Besser, 2016). Since we cannot escape our nature, including its final
goal, only proper activities that direct us toward the true goal will make us flourish.
This conceptualization of a unitary human nature diverges fundamentally from scientific perspectives,
which—since Darwin—typically focus on natural differences within each species. The idea of natural
variations makes it likely that many different kinds of goals and activities can do the trick of making us
happy, depending on the individual’s dispositions and environmental peculiarities. After all, Aristotle knew
nothing about evolution and it is understandable that he stumbled on the idea of a unitary goal/unitary
activity approach to happiness. A critical hand might also be astounded by Aristotle proposal that the only
life truly worth living is that of a philosopher, a statement that, according to Thin (2012) sounds
“embarrassingly smug.” More updated on how and why variations is a natural part of human lives,
Lyubomirsky and Layous’ writings on the “person-activity fit” suggest that a diversity of goals and
activities is exactly what we need to be happy. What is important, is the match between one’s dispositions
(and these vary across individuals) one the one hand, and the goals held and activities performed on the
other. A huge pool of goals and activities are equally potent as sources of happiness, given that the they fit
our more or less idiosyncratic dispositions (Lyubomirsky & Layous, 2013). Variations of the perspective
presented by Lyubomirsky are mainstream in modern psychology, and can be found in almost every goaloriented
approach in the discipline (e.g., Cantor & Sanderson, 1999; Dweck, 2000; Emmons, 1999;
Klinger, 1975; Little, 2016; Sansone & Harackiewicz, 1996; Sheldon, 2014).
A final point about the Aristotelian theory of happiness worth some pondering concerns the meaning
of the phrase “by-product.” Diener used it to describe activity theories of wellbeing, and other scholars use
it in order to explain how an activity can create a feeling state (e.g., Ryan & Martela, 2016). Aristotle
seems to have had at least two different opinions on the issue, and experts on interpreting his writings,
such as Nussbaum (e.g., Nussbaum, 2008), argue that in Book VII and Book X of the Nicomachean Ethics
Aristotle diverge. In Book VII Aristotle identified pleasure with unimpeded activity. As such, pleasure is
not a “by-product” of activities, in the sense of a by-product being “a result of making something else, or
something unexpected that happens as a result of something: Buttermilk is a by-product of making butter.
Illness is one of the by-products of overcrowded housing” (Cambridge English Dictionary Online;
https://dictionary.cambridge.org/us/dictionary/english/by-product). In Book X of the Nicomachean Ethics,
Aristotle speaks of pleasure a bit differently, as something that “supervenes on it, like red check in the
youth” (Nussbaum, 2008, p. S84). According to Nussbaum, pleasure in this second meaning is not
identified as unimpeded activity, but as a result of such activities. Nevertheless, pleasure as laid out in
Book X is “so closely linked to the relevant activities that it cannot be pursued on its own, any more than
bloom can be adequately cultivated by cosmetics. To get that bloom you have to pursue health.”
(Nussbaum, 2008, p. S85). Pleasures such perceived are not simply external rewards, but “achievements
and satisfactions available only in the activities of the practice” (Boyle, 1987). Similarly, Katz (2009) has
argued that Aristotle held a “Perfection in functioning view”, which, in the context of activity theories,
means that pleasure arises from being active, from the activity itself. Finally, Lazarus (1991) has pointed
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out that Aristotelian happiness is “not goal attainment that generated pleasure but the normal exercise of
any function.” (p. 92). Irrespective of the interpretations offered on Aristotle's view on the matter, modern
emotion theory clearly consider feelings as an integrated part of, and not a by-product of activities. In a
later section, the Functional wellbeing approach (FWB) will be offered as a possible explanation as to why
activities generates feelings by and in themselves.
The Utilitarian Turn
The Aristotelian idea that humans, by nature, are genuinely social and that our inborn moral
dispositions must be actively cultivated in order to develop good societies and lead happy lives was more
or less abandoned during the Enlightenment (MacIntyre, 2007). Instead, deontology (Kant),
utilitarianism/consequentialism (Bentham) and contractism (Hobbes) came to dominate the ethical debates.
Following these views, no connection between (moral) activities and the good life was proposed. Rather,
the idea of goodness that started out as utilitarianism and ended up as economic welfarism discarded the
distinction between goods internal to and goods external to an activity. Wellbeing, what many scholars hold
as the essence of economic welfare (e.g., Hausman, McPherson, & Satz, 2016; Jordan, 2008; Moore &
Crisp, 1996; Ringen, 1995; Sumner, 1996), became identical with money, and money was most efficiently
generated by the interaction between supply and demand as regulated by competitive markets. The
relevance of human activity for wellbeing was reduced to the behavior involved in producing a supply and
breeding demands. The logic goes something like this. Since people in a market act on a voluntary basis3,
prices will adjust until supply equals demand (the state of ‘market equilibrium’). “The resulting set of
prices makes everyone as well-off as possible. In other words, markets produce the best of all possible
worlds” (Kwak, 2017, Chapter 2).
Interestingly, the early economists had a much more sophisticated view on human wellbeing that what
we are left with in the extreme reductionism of modern versions of the discipline. Adam Smith, for
example, was concerned with the nature on human activities, although he, like many of his contemporaries,
held a generally negative view of it. To be active was to Smith a hostile necessity. “It is in the inherent
interest of every man to live as much at his ease as he can; and if his emoluments are to be precisely the
same whether he does or does not perform some very laborious duty, to perform it in as careless and
slovenly a manner that authority will permit” (Adam Smith, 1776, cited in Schwartz, 2015). Some years
later, Jeremy Bentham talked about “love of labour is a contradiction in terms” (cited in Skidelsky &
Skidelsky, 2013, Chapter 1). What is more, Bentham considered the activities involved in paid employment
to be so aversive—and poor people to be so lazy and unwilling to take part in it—that in order to motivate
them to work “the paupers should be kept in ‘wholesome horror’” (Dean, 2008, p. 61).
In contrast to economic welfarism, even a free market apologist like Adam Smith agreed that when it
comes to welfare, the negativity of hard work had to be subtracted from the monetary surplus generated by
the balancing forces of supply and demand. To Smith, activities like work simply had “negative utility.”
Not only did he realize that the division of labor meant that the work reduced welfare because it made the
life of the workers more boring, Smith also developed a pessimistic outlook on the prospect of capitalism
as a provider of welfare in the long run. He believed that the division of work among the assembly line
workers eventually would end in material decline and moral decay (Heilbroner, 1973). A person who loses
the opportunity to practice the skills of a trade or a craft, becomes, in Smith’s own words “as stupid and
ignorant as it is possible for a human creature to be” (cited in Schwartz, 2015, Chapter 4). A look at his
famous schedule for manufacturing pins illustrates how the division of labor might be good for business,
but bad for wellbeing. In order to produce pins efficiently, the task should be divided into more limited
tasks, such as drawing the wire, straightening the wire, pointing, cutting heads etc. And not only should the
initial craftsmanship involved in the making be chopped up into meaningless chunks of activities, the
different part of the process should be delegated to the cheapest possible employees. Women were paid less
than males, and girls less than boys. Such a scheme makes the surplus go up, but wellbeing, Smith feared,
will go down.
About a hundred years later, reports given to the Children's Employment Commission in England
could verify Smith’s prophecies about the alienation of factory workers. Here is a mother’s testimony on
the working conditions for her little son in London in 1863: “When he was seven years old I used to carry
him [to work] on my back to and fro through the snow, and he used to work 16 hours a day…. I have often
knelt down to feed him, as he stood by the machine, for he could not leave it or stop” (Marx, 1977, cited in
Hochschild, 1983, p. 3)
Based, in part, on these and similar observations, Marx developed his view on how capitalism
systemically prevents most people from having the requirements of a ‘good life’. Marx, who held a PhD in
the philosophy of Democritus and Epicurus (see McMahon, 2006) was familiar with the Aristotelian
concept of eudaimonia and when Marx wrote about good lives, it was, according to Miller (1992), in
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Aristotelian terms. Thus, Marx opposed utilitarianism and accused Bentham for failing to discriminate
among the different versions of ‘human nature’ (R. Miller, 1992, p. 280). As an alternative, Marx was
concerned with what he referred to as “species being”, his view on human nature and the essence of
humanity (Dean, 2016). Being active is an important element of this nature, in fact Marx considered
activities to be definitive of human essence and self-realization. A slogan-like summary of this idea is
known from his well-known wish "to do one thing today and another tomorrow, to hunt in the morning,
fish in the afternoon, rear cattle in the evening, criticize after dinner, just as I have a mind, without
becoming hunter, fisherman, cowherd, or critic” (cited in Hurka, 1987, p. 734).
The consequences of not letting people do “one thing today and another tomorrow” had more severe
consequences in the nineteenth century than it has today. Nevertheless, ignoring the importance of varied
and meaningful activities may still have devastating consequences to many people on the Globe. Not
comparable to the exploitation of child workers, though, a recent example from Norway may illuminate the
fundamental problem of ignoring the value of being active. A small group of handicapped people has for
years been employed to maintain parks in a city at the west coast. The crew show admirable commitment to
their job and being thus active helps structuring the lives and secure enjoyment and meaning for these
individuals. The chief municipal executive of this city was, however, dissatisfied with the situation: he
figured that the world would be a better placed if the handicapped group was fired and replaced by
professional gardeners. Expectedly, this arrangement would create a larger monetary surplus. To the chief
municipal executive, as to other believers of economic welfarism, what people do, and how they do it, are
irrelevant; economic surplus is the only thing that matters. Fortunately, the City Council voted the proposal
down (Lexberg & Frafjord, 2017).
Craftsmanship
The shortcomings of economic welfarism is a reminder, not only about the perils of shrinking the
complexity of human lives down to an imagined balance of demands and supplies, but also about the
dangers of doing science without theoretical guidance. A proper understanding of what it means for
humans to lead good lives can never be established without solid knowledge about what human being are
like. In order to live, humans must be active. In order to live well, they must be active in the right way. An
excellent illustration of this point comes from Sennett (2008) who, from a sociological and philosophical
perspective, has contributed a comprehensive analysis of the activities involved in craftsmanship.
Craftsmanship reflects a kind of work engagement characterized as a “desire to do a job well for its
own sake.” Working towards excellence under the right circumstances, Sennett tells us, creates a deep
satisfaction. Not only with regard to what one is doing and its material products, but also for the person’s
role as a citizen. In a society of functioning guilds and proper craftsmanship, “Learning to work well
enables people to govern themselves and so become good citizens” (Sennett, 2008, p. 268). The
nourishment of a fine rhythm between problem solving and problem finding is a crucial element of the
experience. Since skill development is an enduring process that involves a constant refinement of the
craftsman’s ability to perceiving crucial details in nuanced ways, solving one problem often points to
another. Such a dynamic generates a constant improvement in individual skills and in the knowledge
commonly held by a society of craftsmen. But this openness to improvement is, according to Sennett,
antagonistic to much of the modern work life, which is enforced upon a growing number of people by the
pressures of an impersonal market and an over-bureaucratic state. In contrast to the marked way of
thinking, with its focus on getting things done, craftsmanship operates in line with the ideal of getting it
right or making it beautiful. Managing complex activities require task-specific rhythms, and sometimes
these are slow and repetitive. Acting slowly and repetitively will in turn stimulate professional reflection
and self-criticism. These are critical elements of skill development, and if the internally driven struggle for
excellence is taken away by a top-down driven management regime, the opportunities for skilldevelopment
and professional reflection disappears. This essence of craftsmanship disappears if one push
for quick results.
Psychological Approaches
To a psychologist, craftsmanship sounds a bit like intrinsic motivation. For instance, a sense of craft
has been described as becoming “engaged in the work in and for itself,” and craftsmanship is supposed to
occur when “the satisfactions of working are their own reward” (Sennett, 2008, p. 27). These
characteristics resembles those typically listed to describe intrinsic motivation, as in Berlyne’s (1960)
definition of it as “motivation in which the rewards were inherent in the activity,” or in Ryan and Deci’s
terminology as “behavior done for its inherent satisfactions” (2008, p. 655). Moreover, since the term was
coined by Harlow (1950), the argument that intrinsically motivated behavior prompts learning and skilldevelopment
has been an integrated part of the concept.4 In other words, both craftsmanship and intrinsic
motivation have been presented as prototypical examples of the Aristotelian ideal about “being well and
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doing well in being well.” Hence, the concept of intrinsic motivation aspires to contribute the best
psychological account of the relationship between activities and wellbeing. From a variety of psychological
theories with relevance for intrinsic motivation, four will be presented in this section (for more
comprehensive reviews, see Deci, 1975; Deci, Koestner, & Ryan, 1999; Eccles & Wigfield, 2002; Eckblad,
1981; Eisenberger, Pierce, & Cameron, 1999; Gerhart & Fang, 2015; Lepper, Henderlong, & Gingras,
1999; Oudeyer & Kaplan, 2007; Renninger & Hidi, 2016; Ryan, 2012; Ryan & Deci, 2017).
Internal Motivation
The concept of internal motivation has clear overlaps with the idea of craftsmanship. For instance, it
shares with Sennett the idea that a well performed activity has a structure that associates it with the concept
of good. Although it is presented in slight opposition to the mainstream work on intrinsic motivation, the
theory of internal motivation is an activity theory, and at an overarching level, it might even be permissible
to categorize at as a kind of an intrinsic motivation theory.
The concept of internal motivation has been develop by Schwartz and colleagues, in the spirit of
Aristotelian eudaimonism (e.g., Schwartz, 2015; Schwartz & Wrzesniewski, 2016). Its approach to
wellbeing is based in the pursuit of excellent activities, and the authors argue that the traditional perspective
on intrinsic motivation is too narrow to properly explain the association between activities and wellbeing.
To improve this state of affairs, the theory of internal motivation appeals to the Aristotelian concept of
telos, and to MacIntyre’s (2007) concept of a practice. The theory argues that the Aristotelian ideal of
“doing the right thing, at the right time, in the right way, for the right reasons” provides a better framework
for analyzing good lives, than does the mainstream idea of intrinsic motivation. The latter is restricted to
activities for which a pleasant feeling is the very purpose of the activity—the pleasant experience becomes
an end in itself. In such a perspective, the important relationships between motives, actions and their
consequences are overlooked. This neglect has serious consequences for the understanding of wellbeing.
Here is a brief resume of what Schwartz and colleagues propose as an alternative.
Telos specifies what counts as excellence in an activity. For instance, the telos of a builder is to
produce excellent buildings and the telos of a doctor is to cure disease. The telos thus provides an activity
with meaning and direction. The theory of internal motivation is also indebted to MacIntyre and his
concept of practice. MacIntyre is a neo-Aristotelian who sticks with the idea that it is only because “human
beings have an end towards which they are directed by reason of their specific nature, that practices,
traditions, and the like are able to function as they do” (MacIntyre, 2007, Prologue). The concept of a
practice is further defined as “any coherent and complex form of socially established cooperative human
activity through which goods internal to that form of activity are realized in the course of trying to achieve
those standards of excellence which are appropriate to, and partially definitive of, that form of activity, with
the result that human powers to achieve excellence, and human conceptions of the ends and goods
involved, are systematically extended” (MacIntyre, 2007, p. 175).
Surely, this definition is quite a mouthful and it leaves the impression of a very abstract phenomenon.
But the concept of practice comprises a very promising and rather concrete idea. It is that the proper value
of an activity is only available through the achievements and satisfactions inherent to the practice that
defines the framework of the activity. Without goods internal the activity itself, behaviors become little less
than technical performances. In liberal democracies, for example, politics cannot be good unless it is
motivated by a genuine wish for societal improvement. Without this aim, politics declines to empty
rhetoric and cynical fights for power (Boyle, 1987).
Teaching is another example of how excellent activities cannot be guided by just any kind of goals.
For a teacher, making a salary can be important, but it will never be the telos of teaching—excellent
teaching cannot be measured by the income it produces. It can only be evaluated against the learning it
generates; what students learn and how they develop as human beings. Besides, there are many ways to
earn money, and teaching is only one among many option (and probably not a very efficient one either). It
seems clear to us, Schwartz and Wrzesniewski (2016, p. 130) summarize, “that some goods are only
attainable through the particular activity, some are attainable through the activity but also some others (they
are internal to success at a practice, but not unique to it), and some are completely arbitrary in their relation
to a practice.”
Flow Theory
Another theory of intrinsic motivation, broadly defined, is flow theory (Csikszentmihalyi, 1975, 2014).
It is the only example of a psychological activity theory of wellbeing mentioned in Diener’s 1984 review.
According to the description given in that article, a person who is involved in an activity that demands
intense concentration will typically experience a pleasurable feeling, a flow experience, as long as the
person's skills and the challenge of the task are roughly equal. After more than 40 years of research, this
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conceptualization has not changed much and Diener’s description still reflects the standard understanding
of a flow experience, although the term pleasurable is often replaced with the term enjoyment (e.g.,
Seligman & Csikszentmihalyi, 2000).
There are some links between Aristotelian eudaimonism and flow theory. For instance,
Csikszentmihalyi (1975) explains that flow represents optimal psychological states because when a flow
state occurs, people both develop their potentials and feel great at the same time. This idea shares some
conceptual territory with the “being well and doing well in being well” kind of eudaimonia defended by
MacIntyre (2007). However, Csikszentmihalyi is a bit unclear when it comes to the feeling quality of a
flow experience. Sometimes the feeling of flow is presented as intensely positive, like “pleasure, happiness,
satisfaction, enjoyment” (Csikszentmihalyi, 1992, p. 24). In other contexts, flow is depictured as a state
without any feelings at all: “Strictly speaking, during the experience people are not necessarily happy
because they are too involved in the task to have the luxury to reflect on their subjective states. Being
happy would be a distraction, an interruption of the flow. But afterward, when the experience is over,
people report having been in as positive a state as it is possible to feel.” (Csikszentmihalyi, 1999, p. 825).
The latter position indicates that the state of flow is thwarting rather than generating good feelings.
Scholars have also questioned the assumption that flow experiences contribute to skill development.
Detailed studies of learning in adults suggest that several of the criteria that are necessary for skills to
develop are in conflict with the principles of flow (e.g., Ericsson & Charness, 1994). For instance, tedious
repetitions and a constant and uncomfortable focus on the errors one makes are essential for skill
development but devastating for flow. Studies that compare low performers with high performers show that
the latter report fewer occasions of joyful experiences than the lower performers (Ericsson & Charness,
1994). Actually, Ericsson has declared the characteristics of flow to be inconsistent with the process
involved in the acquisition of high-level skills (Ericsson, 1996, p. 25).
Another knotty aspect of the flow theory relates to its motivational properties. The problem comes to
light in the model typically offered to account for how flow experiences are initiated and maintained (e.g.,
Csikszentmihalyi, 1975; Rathunde & Csikszentmihalyi, 2006). The model articulates a dynamics between
challenges and skills on the one hand, and the feelings of anxiety, boredom and flow on the other.
Graphically, this interplay is depicted in a two-dimensional diagram that can be likened to a stairway,
leading upwards from left to right. The horizontal dimension reflects a person’s skills, which increase as he
or she moves to the right. The vertical dimension reflects the challenge afforded by the situation (up means
more challenges). Moving horizontally denotes developing skills without increasing the level of
challenges. Moving straight up indicates increasing levels of challenges without increasing the level of
skills. In terms of feeling qualities, rightward movement creates boredom and upward movement creates
anxiety.5
A challenges-skills balance implies that a person is properly equipped to cope with the situation at
hand—learning, in other words, is not necessary. Consequently, the model suggests that skill improvement
only occurs when a person moves into the zone of boredom, and not really during flow. The boredom may,
however, motivates a search for higher challenges (an upward move), in which case a flow experience is
likely to occur. Note that this is a hedonic escape maneuver (avoiding a negative experience). Approaching
flow from a challenging situation imposes avoidance motivation as well. Being in challenges-higher-thanskills
position, which really is an opportunity to learn, creates anxiety in the flow model. It is this negative
feeling that pushes the individual away from its current position, either as a downward rescue away from
the learning opportunity, or rightwards towards skill development. Hence, skills may also be improved
during states of anxiety, but once a balance between challenges and skills is established and flow kicks in,
the development of skills stops. The only way to continue to learn, is by moving into a state of boredom.
An alternative idea would be that flow results, not from an equilibrium between challenges and skills,
but rather when challenges are somewhat higher than skills. Such an “imbalance model” of flow has been
proposed by Løvoll and Vittersø (2014). What is gained by an imbalance model is first, the possibility of
having a flow state that is motivated by the positive feelings inherent in the flow experience itself (this
model assumes that people are actually experiencing intense feeling during the flow state, and not just
afterwards). The imbalance model further assumes that it is the slightly higher level of challenges that
motivates a person to keep working to overcome the difficulty at hand. When a person is in flow, this urge
to cope with a challenge is experienced as something positive, something the person really wants to do.
Second, when a challenge is above one’s skills, a learning opportunity is immediately available, because
one’s skills must improve in order to cope with the situation.
A last limitation in flow theory worth mentioning, relates to the nature of activities that are familiar and
even repetitious. A series of theories point out that repetitions are not only important for skill development,
but also that they sometimes create good feelings and opportunities for reflection (e.g., Eckblad, 1981;
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Montessori, 1948; Piaget, 1952; Sennett, 2008; Whitehouse, 2004). Csikszentmihalyi claims that “Unless
people get better at what they are doing, they can't enjoy doing it any longer” (Csikszentmihalyi, 1992, p.
262). Several research paradigms have nevertheless convincingly documented how automatized and easy
activities are the ones we enjoy most (Hill & Schneider, 2006; Winkielman, Schwarz, Fazendeiro, & Reber,
2003; Zajonc, 1980). For instance, when a grown-up is introduced to a new leisure activity, he or she will
typically focus on skill-development for a rather short period of time. Normally, less than 50 hours will be
devoted to this phase of effortful exercises. As soon as an acceptable level of proficiency has been
established, the person will happily practice this activity without any skill improvement for the rest of his
or her life. At this “everyday skills” level, performance has basically become automated and individuals
will be satisfied by carrying out the activity with minimal effort, and without further learning (Ericsson,
1996).
Most of the activities we enjoy are automatized and do not facilitate learning. Thus, the interesting
question is not whether improvement is a prerequisite for doing something joyfully or not. We know
activities can be joyful even if they don't lead to any skill improvements. We also know that skill
development typically requires unpleasantly high levels of efforts. The promise of intrinsic motivation,
however, is that given the right circumstances, adults can sometimes enter a state in which they both feel
intensely positive and develop their skills at the same time. Two theories defending this view, although
offering different explanations as to why it happens, will be presented next.
Self-Determination Theory
A popular approach that meets the criteria for activity theories of wellbeing is the Self-determination
theory (SDT; Deci & Ryan, 1985, 2000; Ryan & Martela, 2016), a wellbeing theory that at least partly
draws on Aristotelian eudaimonism (Ryan, Curren, & Deci, 2013). An original idea in the SDT is that
humans have an inherent tendency toward organismic growth, and that this growth is regulated by three
psychological needs, known as competence, autonomy and relatedness. By organismic Deci and Ryan
mean “a fundamental human trajectory toward vitality, integration, and health” (Deci & Ryan, 2000, p.
229), and a need is defined as a psychological entity that “specify the necessary conditions for
psychological growth, integrity, and well-being” (Deci & Ryan, 2000, p. 227). The needs are not fulfilled
physiologically, but phenomenologically. For example, in order to satisfy the need for competence, a
person must feel competent. Similarly, feeling autonomy/relatedness is necessary and sufficient to satisfy
the need for autonomy/relatedness (Deci & Ryan, 2000; Ryan & Deci, 2008). The theory further suggests
that an individual who acts in certain ways toward certain goals will experience feelings of
competence/autonomy/relatedness. However, these feelings are not themselves a part of the concept of
wellbeing. They are causes of wellbeing. What count as wellbeing in the SDT is a different set of feelings,
such as satisfaction/a fuller sense of satisfaction/happiness/happiness in the fullest
sense/vitality/fulfillment/thriving/ wellness/integrity/wholeness, which is but a sample of the terms used to
describe wellbeing in Ryan and Martela (2016).
Although the SDT is inspired by Aristotle—Deci and Ryan argue that the principle elements of
Aristotle’s view are modeled in SDT (Ryan et al., 2013)—there are some confusing discrepancies between
Aristotelian ideas on wellbeing, and those proposed by the SDT. The next section discusses one of these
discrepancies.
In his search for a principal reasoning on the human good, Aristotle came up with the idea that arête,
or excellent functioning, could provide a framework for the conceptualization of goodness. An important
premise in his functioning argument is that if something functions in accordance with its natural telos, then
we can call that functioning good. A sharp knife is a good knife, just as an eye that sees well is a good eye.
On this basis it can be inferred that humans also can be categorized as good when they function excellently.
Some parts of the writings of Deci, Ryan and their many collaborators are in agreement with this
Aristotelian principle. For example, Ryan, Curran and Deci claim that “human potentialities whose
fulfillment is essential to well-being and happiness—potentialities whose fulfillment constitutes (italics
added) the good” (Ryan et al., 2013, p. 57). The authors continue: “the eudaimonist conception of wellbeing
or flourishing rests on the proposition that what is most subjectively satisfying over the course of a
life is activity that develops and expresses one’s most reflectively valued and well integrated human
potentialities. According to this view, pleasure accompanies activities that fulfill human intellectual, social,
and productive potentials in good and admirable ways, even though pleasure is not the aim of such
activities.” (p. 58). Both phrases clearly explain that activities that fulfill human potentials constitutes
wellbeing (“the good life”).
Somewhat later in the same chapter, however, the authors seem to have changed their minds. Now they
argue that eudaimonic activities are not really a part of wellbeing after all. Eudaimonia is just a precursor of
wellbeing, an antecedent of the good life. “Central to our considerations is distinguishing between
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eudaimonia as a way of living and positive affect as a hedonic outcome.” (Ryan et al., 2013, p. 60).
Optimal functioning is in other words not good in itself, it is just the cause of goodness. This split between
functioning and wellbeing is even more articulated in a more recent chapter by Ryan and Martela: “We
argue that eudaimonia should not be understood as referring to any kind of subjective experience or ‘richer
feeling of happiness’ but is rather about a good and valued way of living that can produce happiness,
vitality and wellness as its byproducts” (Ryan & Martela, 2016, the abstract). These authors also proclaim
that “eudaimonia is rather a depiction of the kinds of pursuits and a manner of living that would most
reliably give rise to (italics added) a life accompanied by a sense of wellness, vitality and thriving.” (p.
111).
In contrast to Aristotelian eudaimonism—in which the most essential argument is that wellbeing is the
endpoint or ultimate goal of all human activities—the SDT proposes that eudaimonia isn’t that endpoint at
all. It is just a mean to reach the endpoint. The endpoint itself, i.e., wellbeing, is, according to the SDT, a
broad set of positive feeling states.
Another controversy in the SDT concerns the use psychological needs to account for intrinsically
motivated behavior. The authors suggest that the concept of psychological needs is particularly useful
when it comes to explain how the introduction of a reward, lack of control or secure attachment seem to
undermine intrinsic motivation. However, there is a literature that goes against this position, on several
grounds. For example, the category of intrinsically motivated behaviors is much broader than typically
discussed by Deci and Ryan. Their focus was initially on relatively simple “free-choice” laboratory tasks
or some kind of self-reports behavior. Over the years, other kinds of intrinsically motivated behaviors have
been studies from the perspective of SDT (see Ryan & Deci, 2017, for an extended overview), but these
activities are still considered as means towards the goal of satisfying a need, and not as an end in
themselves. However, many of the most interesting intrinsically motivated behaviors are neither captured
by a free-choice laboratory test, nor conducted in order to satisfy a need. Rather, such activities occur
spontaneously, can last for long periods of time, and—importantly—they don’t seem to be regulated by
any kind of need or drive. For instance, in a seminal analysis Koch (1956) insisted that when it comes to
intrinsically motivated behavior, the concept of needs would maintain an artificial externality that never
could explain the true mechanisms of intrinsic motivation. Similarly, White (1959) showed in his wellknown
text on effectance motivation that the concept of needs (at least in the sense of states of deficiency)
cannot explain intrinsic motivation. White’s idea was that inherent feelings of competence came as a result
of effective functioning itself, not from the satisfaction of a particular need. Put simply, if an activity is
rewarding in and by itself, the concept of needs is redundant.
Actually, needs seem to make the explanation of intrinsic motivation unnecessary complicated, it is as
if a wedge has been driven in between activities and wellbeing. Rather than argue, as will be done below,
that wellbeing is an integrated part of being active, the concept of need implies a series of complicating
steps. First, only activities that are able to fulfill the psychological needs has the power to motivate people
intrinsically. Second, the activity will not be intrinsically motivating by the mere presence of positive
feelings such as pleasure, satisfaction, interest or curiosity. Actually, pleasant feelings can, according to the
SDT, terminate an intrinsically motivated behavior (see Deci, 1975). Finally, the feelings of autonomy,
competence, and connectedness are not signs of wellbeing in themselves; they are only triggering
something that later on will be experienced as positive affect, fulfillment, life satisfaction, happiness,
thriving, wellness, meaning, vitality, depth or any other of the many experiences that SDT holds as
indicators of wellbeing. A simpler explanation of intrinsic motivation is offered in the Functional
wellbeing approach to be presented next.
The Functional Wellbeing Approach
The functional wellbeing approach (FWA; Vittersø, 2013a, 2013b; Vittersø, 2016a) is an activity
theory of wellbeing in the sense that it proposes a set of mechanisms that identify activities with the state of
being well. The approach assumes that wellbeing is best conceptualized as an integrated part of human
psychology, particularly with regard to the adaptation and regulation of behavior. There are two major
processes of adaptation in living organisms; the regulation of stability and the regulation of change.
Accordingly, the FWA suggests that the wellbeing associated with these types of adaptation also come in
two forms, referred to as hedonic and eudemonic wellbeing respectively. This structure is depicted in
Figure 1.
Hedonic wellbeing (HWB) has to do with pleasure, which is a particular kind of subjective good-bad
evaluations. There are two important types of hedonic wellbeing felt pleasure and attitudinal pleasure.6
Attitudinal pleasure is the same as life satisfaction.7
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Felt pleasure and attitudinal pleasure have much in common, but they are also different enough to be
represented as separate categories at the third level of a wellbeing taxonomy. Felt pleasure is sometimes
referred to as being happy in your life, whereas attitudinal pleasure is referred to as being happy with your
life (Vittersø, 2016b). In terms of (optimal) functioning, the major role of HWB is to regulate stability
according to the general principles of homeostasis. Briefly, the principle suggests that biological,
psychological and social states of disequilibrium will produce feelings of displeasure, which initiate
behavior intended to reestablish equilibrium. When the homeostatic balance is regained, we feel pleased.
Pleasure is in other words the signal that evolution has developed to communicate to our minds that
equilibrium is reestablished and that we currently are well off. A similar mechanism works at the mental
level for striving towards, and reaching goals. Hence, HWB covers communication about both need
fulfillment and goal achievement. The fulfillment of needs and the accomplishment of goals are both
indicating good functioning, thus high HWB reflects a state of well-functioning stability.
The role of eudaimonic wellbeing (EWB) is to regulate change. All complex organisms must be
altered in order to survive and according to the FWA, these changes are regulated by a different
mechanisms and feelings than those associated with stability. For example, the phenomenology
characterizing the process of change can sometimes (but certainly not always) be positive. When that
happens, we feel engagement, curiosity, interest and sometimes awe rather than pleasure or satisfaction.
The function of eudaimonic experiences is to motivate departures from the comfort zone of pleasant
stability, and it operates through a feeling of being absorbed in the task of overcoming a challenge. This
allows for biological, psychological and social growth processes and explains why EWB sometimes is
described as being happy fulfilling your life (Vittersø, 2016b).
Growth processes include certain feeling states, but are not limited to these. Just as life satisfaction
reflects a trait element in HWB, there is a trait element in the EWB dimension as well. It facilitates learning
and development and is referred to as personal growth. The concept is undeniably a somewhat confusing
one (Vittersø & Straume, 2017), but hopefully, more research will make the idea more coherent. In the
FWA, personal growth includes some objective element, like moral development. The EWB part of the
Functional wellbeing approach thus comprises a combination of subjective and objective criteria, a pattern
that has been called a “sobjective” perspective (MacLeod, 2015). This implies that it is not entirely up to
the individual to judge whether he or she is growing as a human being. Consequently, self-reports will
never be able to fully capture the concept of personal growth. Note also that the growth processes in the
FWA include goals and plans for reaching these goals that appear more or less meaningful for a person,
which means that the concept of purpose or meaning in life is included in this category.
There are some principal similarities between the FWA and Aristotle’s conceptualization of goodness,
primarily related to the idea of developing one’s potentials qua human beings. Although the FWA does not
subscribe to the idea that every disposition that appears “natural” is good (e.g., Thin, 2016), it does agree
with the description of EWB as “man-as-he-could-be-if-he-realized-his-essential-nature,” in contrast to the
“man-as-he-happens-to-be” nature of HWB (cf. MacIntyre, 2007).
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The influence from Piaget. The FWA builds on Piaget (e.g., 1952, 1971). The influence comes in
particular from the connection identified by Piaget between activities and feelings, and from his ideas about
needs. General knowledge of biological structures and adaptation enabled Piaget to dissociate the concept
of needs from the performance of certain behaviors. It is because the movements involved in an activity
already are directed, Piaget pointed out (Piaget, 1952, p. 45), that they are set in motion in the first place.
Needs cannot fully account for human behavior because “a need does not explain how the movement
necessary for its satisfaction is directed” (Piaget, 1952, p. 44).
To further grasp what Piaget had in mind when he asserted that an activity could be initiated and
maintained without reference to the concept of needs, his theory on how activities are organized around a
schema is important. When an organism has a structure available, Piaget reasoned, there will be “a basic
tendency to exercise the structure, that is, to make it function” (Ginsburg & Opper, 1969, p. 30). The mere
acting on these structures had what Piaget referred to as functional meaning, which is to say that the act has
“a value for the subject himself. But whence comes this value? From functioning as such” (Piaget, 1952, p.
42). This perspective allows for activities to be reinforced by themselves. Note that Piaget also considered
repetition of an acting structure as a necessity for all forms of life, and that some repetitions had functional
meaning. Both Sennett’s work on craftsmanship (Sennett, 2008) and observations made by Montessori
(1948) corroborate Piaget’s view on repetitive activities.
A final Piagetian concept worth mentioning is the moderate novelty principle. It suggests that we feel
most interested when interacting with stimuli that bears some relevance to what we already know, but at the
same time is sufficiently novel to present incongruities and conflicts to the existing structures. Since these
new observations do not assimilate easily, they are met with “a resistance which is imposed by the reality
of the objects themselves” (Ginsburg & Opper, 1969, p. 59).
The influence from Eckblad. The idea that feelings could be generated directly from an activity that
has been initiated by a discrepancy between a cognitive structures and the resistance offered by the
circumstances was further developed by Eckblad (1981). By analogy to the Wundt curve—which suggests
that pleasure is a curvilinear function of arousal, with maximum pleasure produced at some optimal level of
arousal8— she developed a multi-curve model in which distinct feelings reached their most intense
expressions at increasingly higher levels of assimilation resistance. Thus, each feeling state has “a singlepeaked
preference function for any given complexity dimension” (Eckblad, 1981, p. 97). The idea is laid
out graphically in Figure 2, illustrating for instance how pleasure typically will be experienced at low levels
of assimilation resistance. Feelings of joy will kick in at somewhat higher levels, whereas the
phenomenological responses to high levels of assimilation resistance are those of interest, curiosity and
challenge. The assimilation resistance can also be overwhelmingly high, in which cases feelings like
frustration, chaos and perhaps anxiety will be prompted. A more detailed account of these processes is
provided by Eckblad (1981, Chapters 2 and 3).
The influence from appraisal theories. Piaget’s theory and the additions suggested by Eckblad
explains how an activity by itself can generate feelings of different qualities. This account is adopted by
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the FWA, into a model that also includes feelings generated according to the principles of appraisal theories
of emotions (Lazarus, 1991; Oatley, 1992; Scherer, Schorr, & Johnstone, 2001; C. A. Smith & Ellsworth,
1985).9 These theories hold the view that emotions are evaluative responses to challenges or opportunities
regarding goals that are important to us. As a part of the process, and approaching a novel situation, some
kind of a primary appraisal will take place, which is to say that a person will check if the situation is
relevant and congruent with his or her goals (Lazarus, 1991, p. 133).
Figure 3 illustrates what Piaget and Eckblad refer to as a “totality”, which includes both the ongoing
activity and the goal of that activity. The mid part of the figure reflects the ongoing activity, the
“throughput” in the Input-Throughput-Output (ITO) scheme. The input and output feelings involve
evaluations, whereas the throughput feelings do not. They follow the principles of functional assimilation.
To illustrate how this may be integrated in a totality, the classical Test-Operate-Test-Exit or TOTE scheme
may be of assistance (G. A. Miller, Galanter, & Pribram, 1960). The test procedure involved in TOTE is
illustrated in the black frame at the lower left part of Figure 3, and it is regulated by “some criteria
established in the organism, to respond if the result of the test is to show incongruity, and to continue to
respond until the incongruity vanishes, at which time the reflex is terminated.” (G. A. Miller et al., 1960, p.
26).
The idea proposed by the FWA is that as long as one’s attention is focused on the operation itself (oval
circle in the TOTE box) it is the feelings generated by the functional assimilation process that will be
phenomenologically dominant. Intense attentions at the ongoing activity prevents rapid shifts between
operation and testing to reach consciousness. Hence, the testing phase will not interfere with the focused
attention unless there is a dramatic shift in progress towards, or a retreat away from, the goal of the totality.
This lack of interference with the focused activity is the explanation offered for why the feelings of
intrinsically motivated behavior and flow can be very intense and lasting. The effect of shutting out
disrupting impulses to conscious awareness is referred to as stimulus gating (Elkind, 1971). It is also
described by Goffman (1961), who used the term “semipermeable membrane” to explain the phenomenon.
The Future of Activity Theories
The present chapter has discussed strengths and weaknesses of some activity theories of wellbeing. A
few possible directions for further research and theorizing are worth mentioning. Chief among these
concerns is the development of better concepts.
Some of the major concepts in the activity theories are somewhat outdated. Aristotle’s thinking runs
thousands of years back. They are difficult to operationalize scientifically and are hardly tested empirically.
Still, psychological theories on activity and wellbeing build, at least in part, on some of these ideas. And
even if modern activity theories have integrated more recent science into their bodies of knowledge, they
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still appear slightly segregated and theoretically old-fashioned. Many of their core concepts were developed
more than half a century ago. Hence, conceptual renovations, and in some cases even a theoretical restart,
will probably make the approaches more complete and better able to explain the dynamics between the
doing parts and the wellbeing parts of human lives. After all, scientific progress consists primarily in
refining one’s concepts and departing from the outdated ones (e.g., Mayr, 1982).
Economic welfarism is the approach that most urgently needs to change. Research and real life
episodes have revealed how this line of though suffers from overly reductionism and surprisingly high
levels of errors when making predictions (e.g., Chang, 2012; Ferguson, 2012; Jordan, 2008; Kwak, 2017;
Loewenstein, Rick, & Cohen, 2008; Scitovsky, 1992; Skidelsky & Skidelsky, 2013). Using the vocabulary
of Kuhn (1970), nothing less than a scientific revolution seems necessary in order to get the mainstream
thinking in economic welfarism straight.
Psychological theories need improvements as well. For example, the core concepts of FWA are vague.
The notion of a schema has rightfully been criticized for being too broad and imprecise (e.g., Neisser,
1994) and much of the empirical evidence in Piaget’s work comes from the study of children. In the years
to come, a better integration of general knowledge from cognitive and emotional sciences, including new
ways of measuring on-line mental states and feeling qualities will be help strengthening the assumptions
made by the FWA and move the approach forward. Another important challenge for future developments
on the FWA is to integrate recent attainments in research on the social and moral nature of human beings
into the cognitive-emotional framework of the theory.
Self-determination theory has a successful record of assimilating new knowledge into their theoretical
framework. It has been less progressive when it comes to accommodating its core concepts. The idea of an
organismic nature, or being naturally inclined towards growth, is an example in case. One of the unsolved
puzzles here concerns the specific meaning of a “natural inclination towards growth and integration”.
Another difficult concept is that of psychological needs. At a general level, the notion makes a lot of sense.
When needs are not met, we intuitively infer that something negative is about to happen. However, on a
more specific footing the notion runs into trouble. For instance, each of the three needs are sweeping very
broad, the criteria to have them satisfied are hard to measure with sufficient precision, and the potential
conflicts between them are not properly accounted for. The Self-determination theory will gain from
further clarifications of these issues.
After 40 years of research, the core concepts of flow theory have hardly changed. Terms like
challenges and skills and the balance between them were hard to pin down when the theory was born, and
they continue to be so. As a consequence, we still don’t know when and even if flow has been validly
measured. The proposal that a balance between challenges and skills prompts people to develop their skills
is also controversial, and research specifically tailored to back up this idea is needed. More work is also
required in order to understand what it really feels like to be in flow. Does it occur in a phenomenological
vacuum, or is it filled with intense experiences? Self-reports may not be precise enough to clarify the
problem, even when they are collected by the so-called “gold standard” of experience sampling methods.
Thus, the development of better methodologies is an important avenue for future research.
Finally, the Internal motivation theory offers important insights on how activities, wellbeing and good
societies are interrelated. However, it may fall short of explaining the psychology of intrinsic motivation as
classically defined. Occasionally humans act, sometimes even for substantial periods of time, without
keeping the aim of that activity in mind. It seems likely that these instances are important to many people,
they may even be essential for optimal functioning. These features of human lives call for a theoretical
account.
Conclusions
The idea that good living involves good acting is old. This way of thinking was, however,
outmaneuvered by the philosophies of deontology and consequentialism/ utilitarianism during the
Enlightenment. In the nineteenth century, utilitarianism advanced into economic welfarism, which seems to
be the hegemonic wellbeing ideology among politicians and decision makers today. Welfarism defines
wellbeing in terms of money and commodities, more specifically as the optimal balance between demand
and supply as these are regulated on a marked. In its most radical form, welfarism argues that this
equilibrium is all one needs to care about when it comes to wellbeing. As a consequence, human activities
are reduced to economic activities and insights into human nature are deflated to beliefs about commodities.
Against this background, the promise of activity theories is two-fold. First, by detailing how good
lives by necessity include opportunities to act in accordance with certain aims and rhythms, they contribute
general knowledge to the science of wellbeing. Second, by means of this knowledge, activity theories can
be precise in predicting how and why wellbeing will be reduced if the doing part of our lives are ignored or
193
reduced to economic performance.
Although much work remains in order to get the details straight, activity theories are well on their way
to give reliable descriptions of what states of wellbeing look like, to explain why these states are good for
us, and to predict the consequences of changes in the basic structure of these states. That is not a bad
accomplishment for a group of scientific theories.
Footnotes
1Terms like wellbeing and happiness are used in many different ways, but in compliance with the
mainstream literature on subjective wellbeing, I use them as synonyms in this chapter. In psychology,
happiness is also frequently use to denote a relatively brief feeling of intense joy or even “satisfaction in the
fullest sense”. In philosophical literature, the term happiness has a much broader meaning (Badhwar, 2014;
Bishop, 2015; Bradley, 2015; Haybron, 2017; Hurka, 2011)
2Philosophers sometime add the phrase “for the person who’s life it is” to this definition. They do this to
clarify that wellbeing is a so-called prudential value—and not a moral or other kind of value (e.g., Griffin,
1986). The prudential perspective might inflict an unnecessarily individualistic constrain on the concept of
wellbeing, though, since humans are such ultra-social and morally oriented animals that it is hard to
conceive of human goodness as a private property.
3Whatever that may imply. For instance, how “voluntarily” is the “demand” for food for a hungry person
and the “demand” for medicine for someone seriously ill? Roman law developed a term for this
illusionary idea of freedom; ‘coactus volui’. The English translation goes something like “Having been
forced, I was willing”, or more fully “though I would not have been willing had it been freely offered,
nevertheless, having been forced, I was willing.”
(https://en.m.wikibooks.org/wiki/Annotations_to_James_Joyce%27s_Ulysses/Wandering_Rocks/240)
4Elkind (1971) made a distinction between learning as the outcome of extrinsic motivation and
development as the outcome of intrinsic motivation. This distinction is not used in the present text.
5Given that the position held before the movement starts is a state of balances between challenges and
skills.
6Terms like cognitive or evaluative wellbeing are used more frequently than attitudinal pleasure to name
this dimension of wellbeing. But evaluations involve both affective and cognitive elements of information
processing, and they are also involved in many kinds of psychological processes. Some of these are very
brief and state like. Hence, the term attitude is preferred in the FWA to underscore the trait like nature of
overall good-bad evaluation. After all, the essential component of an attitude is an evaluation along an
affective good-bad dimension (e.g., Eagly & Chaiken, 1993).
7Satisfaction can be specified at a lower and more specific level in a taxonomy of wellbeing, typically
referred to as domain satisfaction (e.g., Diener, Scollon, & Lucas, 2009)
8Note that the Wundt curve is incommensurable with the affect circumplex (Russell, 1980). In Wundt’s
model, pleasure depends on the level of arousal whereas the circumplex model assumes that the two are
independent. Both models are consistent with the low correlation typically observed between pleasure and
arousal though, because a curvilinear relation between two variable will also comprise a zero correlation.
9In Eckblad (1981, p. 34) a dichotomy akin to the one I have proposed is presented as a division between
“spontaneous activity of schemes and disequilibrium proper”.
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The Way is the Goal: The Role of Goal Focus for Successful Goal
Pursuit and Subjective Well-Being
By Oliver J. Kaftan, University of Zurich, Dept. of Psychology; Alexandra M. Freund, University of
Zurich, Dept. of Psychology and University Research Priority Program Dynamics of Healthy Aging
Citation
Kaftan, O. J., & Freund, A. M. (2018). The way is the goal: The role of goal focus for successful goal
pursuit and subjective well-being. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt
Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
Goals are considered by some theories as essential for subjective well-being (i.e., telic theories, see Diener,
1984). In fact, achieving goals is beneficial for subjective well-being. However, just holding goals does not
bring about goal achievement. Therefore, this chapter highlights the importance of goal pursuit (autotelic
theories) in addition to goal achievement for a more comprehensive understanding of subjective well-being.
We address the question of whether goal progress and attainment are differentially related to subjective
well-being and examine how people best pursue their goals. Specifically, we posit that focusing more on
the means of goal pursuit (i.e., adopting a process focus) is more beneficial for goal progress and subjective
well-being than focusing more on its ends (i.e., adopting an outcome focus). There also exists some
evidence that suggests that adopting a process focus is adaptive when people face a particular type of
difficulty when intending to pursue a goal, namely procrastination. Given that procrastination hinders
successful goal pursuit and subjective well-being, this finding again highlights the importance of goal
focus for understanding how people best pursue their goals.
Keywords: Subjective Well-Being, Goals, Goal Pursuit, Goal Focus, Procrastination
Albert Einstein reportedly stated: “If you want to live a happy life, tie it to a goal, not to people or
things.” In fact, research shows that having a goal, even if we do not reach it, provides us with a sense of
direction and meaning (e.g., Emmons, 1996; Klinger, 1977; Little, 1989). This might be best illustrated by
another quote, this time from actor and martial arts master Bruce Lee: “A goal is not always meant to be
reached, it often serves simply as something to aim at.” Setting and pursuing long-term goals that go
beyond the immediate gratification of needs such as food or shelter seems central to humans: People live
by identifying desirable states they want to achieve (or undesirable ones they want to avoid) for themselves
and their lives, and ways of achieving (or avoiding) these states (e.g., Carver & Scheier, 1990; Emmons,
1996; Freund, 2007). In this chapter, we will explore some of the mechanisms by which goals affect
subjective well-being.
Goals and Subjective Well-Being
A goal can be defined as the cognitive representation encompassing the linking of means to desired
outcomes (Kruglanski et al., 2002). For example, the goal to get a college degree entails desired outcomes
(e.g., to get a job, to impress others) and means to attain these outcomes (e.g., to study hard, to resist
temptation). Because goals are comprised of means and ends, they might act as channels for new
knowledge and organize information in terms of means and ends (e.g., Woike, Lavezzary, & Barsky,
2001). As knowledge structures, goals follow similar principles of activation, change, and organization that
have been articulated in reference to knowledge representations in general (e.g., Higgins, 1996).
Goals have been described as building blocks for the accomplishment of a variety of developmental
tasks and their achievement is likely to foster long-term patterns of successful development (Freund &
Riediger, 2006; Heckhausen, 1999; Ryff, 1989). As pointed out above, goals imbue life with meaning and
provide structure and direction (e.g., Emmons, 1996; Klinger, 1977; Little, 1989). Against this backdrop,
successful goal pursuit can be linked to both cognitive and affective aspects of subjective well-being, which
represent distinct lower order constructs, but also load onto a single higher-order factor of subjective wellbeing
(Lucas, Diener, & Suh, 1996). According to Diener, Lucas, and Oishi (2002), subjective well-being
denotes “emotional reactions to events as well as cognitive judgments of satisfaction and fulfillment” (p.
63). There is no systematic investigation into a potential dissociation of affective and cognitive aspects of
subjective well-being in relation to goal pursuit and goal achievement. Therefore, we will review the
literature linking goals and subjective well-being as it is formulated in theories and with regard to the
aspects of subjective well-being that were included in the empirical studies. Note, however, that it would be
theoretically very interesting to systematically separate affective and cognitive aspects of subjective wellbeing
and their association with goal pursuit and achievement.
200
Goals are often seen as essential to the cognitive aspect of well-being, as this evaluation entails the
judgment of how well one is doing vis-à-vis important goals. In such telic conceptions of cognitive wellbeing,
satisfaction indicates the degree of goal achievement, which, in turn, is crucial for experiencing life
satisfaction (Diener, 1984). In other words: when people achieve goals, they experience satisfaction, when
they fail to achieve goals, they experience dissatisfaction (e.g., Brunstein, 1993; Emmons, 1986; Klug &
Maier, 2015). This is also in line with control theory of goals (Carver & Scheier, 1990) and goalsetting
theory (Locke & Latham, 1990), according to which goals are effective because they indicate the
level of performance that is acceptable.
With regard to the affective aspect of subjective well-being, prominent models such as the model of
goal-directed emotions (Bagozzi, Baumgartner, & Pieters, 1998) consider anticipatory emotions, as well as
emotions tied to the actual outcome of goal pursuit. Anticipatory emotions are elicited by the prospects of
goal success or failure (e.g., “If I succeed in achieving my goal of getting a degree, I will feel happy”).
Depending on their intensity, anticipatory emotions have a smaller or greater potential to motivate goaldirected
actions that are necessary for goal attainment. Goal attainment, in turn, elicits outcome-related
emotions (e.g. “Because I have now received the degree, I am happy”). Carver and Scheier (e.g., 1990)
assume that the velocity with which we approach desired end states (i.e., how fast we close the gap
between the actual and the desired state) is associated with positive affect (or, in the case of insufficient
speed of progress, negative affect).
Thus, goals have an important function for the regulation and evaluation of behavior and subjective
well-being. However, the link between goals and subjective well-being is complex. On the one hand,
evidence from longitudinal studies shows that successful goal striving can boost subjective well-being
(Sheldon & Houser-Marko, 2001). On the other hand, and according to the hedonic treadmill theory
(Brickman & Campbell, 1971), the positive effects of reaching goals are typically short-lived (Frederick &
Loewenstein, 1999). That is, people adapt quickly to good or bad outcomes and return to their baseline
levels of happiness (e.g., Bonanno et al., 2002; Bonanno, Wortman, & Nesse, 2004; Brickman, Coates, &
Janoff-Bulman, 1978; Lucas, Clark, Georgellis, & Diener, 2003; for limitations of the hedonic treadmill
theory, see Diener, Lucas, & Scollon, 2006). Goals can even be understood as having an inherent potential
for dissatisfaction. This is because setting goals creates a negative discrepancy between the actual and the
desired state. In the same vein, McIntosh and Martin (1992) argued that people who see goal attainment as
a prerequisite for their happiness might ruminate in the case of failure, which would lead to negative mood
and unhappiness.
In addition, some types of goals bring forth more subjective well-being than others. Two important
goal characteristics that affect subjective well-being are goal content and whether goals are approach or
avoidance goals (Carver & Baird, 1998; Kasser & Ryan, 1993). Regarding goal content: goals that satisfy
basic psychological needs (e.g., to belong) and that converge with underlying motives (e.g., affiliation) are
more likely to lead to emotional well-being (Brunstein, Schultheiss, & Grässman, 1998; Deci & Ryan,
2008). However, in the case of failure, they also have a stronger negative effect on subsequent subjective
well-being (Sheldon et al., 2010).
Beginning with William James (1890), there is a long and rich tradition of research on approach and
avoidance motivation and goals, that was reflected in learning theories (e.g., Hull, Thorndike, Skinner) as
well as in motivation theories (e.g., Atkinson, Higgins, Lewin, McClelland). A review of this literature is
beyond the scope of this chapter (for an entire handbook on this topic, see Elliot, 2008). Suffice it here to
summarize this research very roughly by stating that approach goals are generally related to higher positive
emotions and well-being, whereas avoidance goals are related to lower subjective well-being (lower
positive mood, less life satisfaction, more anxiety) and performance (e.g., Coats, Janoff-Bulman, & Alpert,
1996; Elliot & Sheldon, 1997; Elliot, Sheldon, & Church, 1997; Emmons, 1996). The lifespan
developmental literature has put forth a somewhat different yet related distinction between goals that are
oriented towards achieving gains, maintenance, or the avoidance of loss (Freund & Ebner, 2005). This
literature shows that adults become more maintenance and loss-avoidant with age, and that this shift seems
adaptive when considering the age-differential association of goal-orientation and subjective well-being
(for a summary, see Freund, Hennecke, & Mustafić, 2012).
Goal Pursuit and Subjective Well-Being
Despite the evidence for a positive relationship between simply holding goals and subjective wellbeing,
having the right kind of goals is not enough to bring about goal achievement and guarantee wellbeing
(Diener, Suh, Lucas, & Smith, 1999). Thus, important questions in the research on goals are: Are goal
progress and attainment differentially related to subjective well-being? How do people best pursue their
goals? We will address each of these questions in the next sections.
Differential Effects of Goal Pursuit and Attainment
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The idea that goal progress and attainment may be differently related to subjective well-being has its
historical roots in the question of whether subjective well-being is brought about by the attainment of
desired end states (telic theories) or by the movement toward such end states (autotelic theories). The
autotelic perspective has its roots in ancient Greek philosophy as for instance developed by Aristotle, who
suggested that positive human experience may lie in the nature of activity itself rather than in any end state
toward which such activity might be directed. This thought was seized upon by many classical theorists
(for an overview, see Diener, 1984; Omodei & Wearing, 1990) and has led more recent research to explore
unique effects of goal pursuit. As mentioned above, Carver and Scheier (1990) drew a direct link between
goal progress and emotional well-being by viewing emotions as indicators of distance-reducing processes
between actual and desired states. In line with this theory, Hsee and Abelson (1991) found that the rate of
progress toward one’s desired end states, rather than their attainment per se, was responsible for
differences in affect. Little (2005) posited that positive psychological functioning, which includes
subjective well-being, is contingent on the sustainable pursuit of core personal projects. Indeed, a recent
meta-analysis (Klug & Maier, 2015) has shown that the association between successful goal striving and
subjective well-being was larger when successful goal pursuit was defined as goal progress instead of goal
attainment. However, Wiese and Freund (2005) found that subjective progress in the pursuit of personal
goals was not (or only weakly) related to subjective well-being (positive and negative affect, satisfaction)
but that the degree to which people were involved in pursuing their goals was associated with an increase in
subjective well-being over the course of three years.
There is empirical evidence for qualitatively different subjective well-being experiences between
goal progress and attainment. Austin and Vancouver (1996) suggested that progressing toward a goal might
be associated with a unique “flow”-like (Csikszentmihalyi, 1990) type of affect that is not related to
outcome valence. Support for such distinct emotional experiences during goal pursuit and following goal
attainment is provided by brain research. For example, Davidson (1994) posited that approach-related
affect (e.g., enthusiasm) is usually generated when moving toward a desired goal and associated with an
activation of a specific brain region (i.e., the dorsolateral prefrontal cortex). In contrast, positive affect
experienced after goal attainment is phenomenologically experienced as contentment and not associated
with this brain region. In sum, then, goal pursuit and progress are beneficial to subjective well-being and
separate from goal attainment effects (see Wiese, 2007, for an overview). We will next elaborate more on
the issue of goal pursuit.
Successful Goal Pursuit
The question how people best pursue their goals concerns the factors that promote successful goal
pursuit. Different social psychological models such as the theory of reasoned action (Fishbein, 1980;
Fishbein & Ajzen, 1975), the theory of planned behavior (Ajzen, 1985, 1991), and protection motivation
theory (Rogers, 1975, 1983) propose that intentions to perform a behavior are the most immediate and
important predictor of actual behavior. However, although intentions (e.g., ‘‘I intend to get a degree’’) can
predict actual behavior, the intention-behavior consistency is far from perfect (see Sheeran, 2002). This so
called ‘intention-behavior gap’ can be the result of people not having the necessary resources, skills, or
cooperation needed to turn commitment into action (Sheeran, Trafimow, & Armitage, 2003).
Often, people fail to cope effectively with problems during goal striving. That is, they may have
problems detecting opportunities to act (Kruglanski et al., 2002), shielding goals from distractions
(Fishbach, Friedman, & Kruglanski, 2003) or competing goals (Shah, Friedman, & Kruglanski, 2002), and
monitoring progress toward goals (Liberman & Dar, 2009). Such difficulties in goal pursuit can be seen as
a function of both which goal is selected (i.e., a goal’s content) as well as strategies and plans associated
with how to pursue and achieve the goal (i.e., goal process). Important dimensions are the concreteness of
the goal (both, concerning the means and the ends) and the difficulty of goal pursuit and attainment. Locke
and Latham (2002) have summarized the core finding of more than three decades of research on goalsetting
theory as showing that specific and challenging goals are best suited to promote goal success as well
as subjective satisfaction. However, as Ordóñez, Schweitzer, Galinsky, and Bazerman (2009) have pointed
out, setting appropriate goals in this way may be a challenge itself: People may set goals that are too
specific or too challenging. Inappropriate goal setting, in turn, may have harmful effects on subjective
well-being. For instance, goals can focus attention so narrowly that people neglect other important
dimensions in life, or they might set goals that are so difficult that the likelihood of failure is very high.
Problems during goal pursuit might also be due to the use of inefficient means such as a poor
strategy to pursue a goal or to a poor implementation of the strategy. When goals are personally highly
important, such difficulties in goal pursuit are associated with lower subjective well-being (e.g., Diener,
1984; Emmons, 1986; Little, 1983; Omodei & Wearing, 1990; Palys & Little, 1983; Ruehlman & Wolchik,
1988; Snyder et al., 1996). The obvious question, then, is: What are effective strategies of goal pursuit?
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Effective strategies. Different strategies have proven effective to tackle problems during goal
pursuit and to positively influence subjective well-being. One of the strategies is mental contrasting of
vague positive fantasies of outcomes with the less positive actual state, thereby producing commitment to a
more reachable goal and the related involvement in goal pursuit (Oettingen et al., 2009). The actual
involvement in goal pursuit is related to the specification and concreteness of the representation of the
behavioral steps that have to be undertaken (i.e., implementation intentions; Gollwitzer, Fujita, &
Oettingen, 2004). In implementation intentions, people plan the when, where, and how of striving for a
goal in the format of “If I encounter situation Y, then I will perform goal-directed response Z.” A wealth of
evidence supports the effectiveness of implementation intentions (e.g., Gollwitzer, 1999; Gollwitzer &
Brandstätter, 1997; Parks–Stamm, Gollwitzer, & Oettingen, 2007). Combined with mental contrasting, the
formation of implementation intentions is even more effective than either of the strategies alone (Adriaanse
et al., 2010). Further factors that support goal progress and attainment that have been shown to increase
subjective well-being include persistence, self-efficacy, and optimism (e.g., Bandura, 1997; Carver et al.,
1993; Emmons, 1996; Freund & Baltes, 1998; Freund & Riediger, 2006; Scheier et al., 1989; Seligman,
1991).
Although goal progress enhances subjective well-being, being able to disengage from goals is also
important for the maintenance of subjective well-being (e.g., Brandtstädter & Greve, 1994; Heckhausen &
Schulz, 1995): When goals are beyond reach and cannot be attained, people are at risk of compromising
their subjective well-being if they do not protect emotional and motivational resources by disengaging from
these goals and reengaging in new meaningful goals (Brandtstädter & Renner, 1990; Heckhausen, Wrosch,
& Schulz, 2010; Wrosch & Miller, 2009; Wrosch, Miller, Scheier, & de Pontet, 2007; Wrosch, Scheier,
Miller, Schulz, & Carver, 2003).
As pointed out above, the representation of goals in terms of concrete goal-relevant actions in a
specific context (i.e., implementation intentions) as well as the specificity of outcomes (in contrast to vague
fantasies) is important for successful goal pursuit and subjective well-being. However, this research does
not address the consequences of focusing more on the process or the outcome of goal pursuit for successful
goal pursuit and subjective well-being. We will do so in the remainder of this chapter.
Goal Focus
At the beginning of this chapter, we defined goals as cognitive representations linking means to
outcomes of goal pursuit. The concept of goal focus denotes the salience of the means or the process (i.e.,
process focus) and the salience of the ends of goal pursuit (i.e., outcome focus) in the representation of a
given goal. In other words, process focus is the degree to which a person attends to the aspects of the goal
that are related to the means, whereas outcome focus is the degree to which a person attends to the desired
outcomes and consequences of goal pursuit (Freund et al., 2012).
As elaborated by Freund and Hennecke (2015), relative to outcomes, means (e.g., running) are
typically more proximal and concrete than their more distal and abstract outcomes (e.g., an increased
endurance; Carver & Scheier, 1998; Trope & Liberman, 2003; Vallacher & Wegner, 1989). Similarly, the
process of goal pursuit takes place in specific situational contexts, whereas outcomes tend to be more
decontextualized. For example, a runner must run in specific contexts (e.g., in the woods), while the desired
gain in endurance is not context-bound but hopefully generalizes to diverse situations. Another feature
distinguishing outcome and process focus is that outcome focus more likely provides a clear standard of
comparison between actual and desired states and therefore also for goal achievement: The appropriateness
of the means is measured according to the standard set by the outcome—the runner, for instance, is
successful only if the running results in the desired gain in endurance; the number of miles he or she is able
to run without a break reveals the discrepancy between the desired and the current state. However, different
to a focus on the process, outcomes do not offer guidelines for goal-relevant actions (e.g., Emmons, 1996;
Klinger, 1977; Little, 1989): Focusing on better endurance does not bring about this outcome (Oettingen,
1996), but focusing on how to achieve better endurance is more likely to lead to the necessary running
exercises (Gollwitzer, 1999).
Similarities and Differences Between Goal Focus and Related Constructs
In order to introduce the concept of goal focus more fully, the following sections place it in the
context of related psychological constructs.
Construal level and psychological distance. Construal level theory posits that the same event,
object, or goal can be represented at different levels of abstractness or generality (Trope & Liberman,
2003, 2010). A low-level construal conveys specific features of a stimulus, the implications of which are
often context-specific, whereas a high-level construal conveys a more global, de-contextualized
representation of the stimulus (e.g., Fujita, Trope, Liberman, & Levin-Sagi, 2006). Moreover, construal
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level theory assumes that people use increasingly high levels of construal to represent an object as their
psychological (i.e., temporal, social, spatial, or probabilistic) distance from the object increases. However,
whereas construal levels denote general mind-sets representing events or goals in more concrete/immediate
or abstract/delayed terms, goal focus refers to means-ends relations (Freund & Hennecke, 2015). For
example, when a dieter chooses between an apple and a candy bar as a snack, lower level construals would
lead the person to focus on the immediate hedonic value and concrete features of the choice (e.g.,
differences in taste). Therefore, a concrete construal of the two options likely leads to a choice of the candy
bar. In contrast, higher levels of construals would lead the dieter to consider the more abstract and delayed
health-related implications of each food option. Therefore, an abstract construal of the two options likely
leads to the choice of the apple (Fujita & Sasota, 2011). In contrast, goal focus refers to the salience of
means and ends within a given goal. Whereas the candy bar would likely be judged a good means if the
goal is to increase the hedonic enjoyment of food, it would not be considered a good means for a health
goal. For a health goal, an apple would likely be represented as a better means than a candy bar (Freund &
Hennecke, 2015).
Evidence for the idea that goal focus and concreteness are related but not redundant is also provided
by Freund and Hennecke (2012). Although there was a weak to moderate positive association between
goal focus and concreteness, goal focus explained unique variance over and above concreteness in a
health-related outcome. Moreover, according to construal level theory, people construe goals along a
unidimensional continuum from concrete to abstract. In contrast, process and outcome focus are
conceptualized as two dimensions. Empirical evidence supports this view: We investigated how process
and outcome focus change with an approaching deadline when pursuing an important goal (Kaftan &
Freund, 2017a), and found that they evolve asymmetrically over time. In addition, process and outcome
focus show a weak positive association, implying that outcome and process focus are two dimensions
rather than two opposite poles on one dimension.
Intrinsic and extrinsic motivation. When intrinsically motivated, people engage in activities
because they derive satisfaction from the engagement in the activity itself, without concern for its further
instrumentality. According to self-determination theory (SDT; Deci & Ryan, 2000), intrinsic motivation is
content-based because an intrinsically motivated action serves at least one of three end goals that are
essential for achieving and maintaining well-being: autonomy, competence, or relatedness. When
extrinsically motivated, people do not act out of interest but because they perceive them as being
instrumental to bring about more tangible and separable consequences like a material reward. When
extrinsic goals dominate over intrinsic goals, according to SDT, they can distract people from intrinsic
endeavors that support their subjective well-being (e.g., Deci & Ryan, 2008).
In contrast, goal focus is mute regarding the underlying reasons for engaging in goal pursuit as both
process and outcome focus can be associated with intrinsic or extrinsic motivation (Freund et al., 2012).
For example, while reading a paper, a student may focus on highlighting important passages (i.e., process
focus) or focus on acquiring new knowledge (i.e., outcome focus). When focusing on highlighting
important passages, the student might do so because he or she loves to structure texts with different colors
(i.e., intrinsic motivation) or because he or she is positively reinforced for doing so by being paid by
another student for highlighting the most important passages of the text (i.e., extrinsic motivation).
Similarly, when focusing on acquiring new knowledge, the student might do so because he or she is
autonomously interested in understanding new scientific discoveries (i.e., intrinsic motivation) or to
impress a teacher with his or her knowledge (i.e., extrinsic motivation).
Intrinsic motivation involves enjoyment of the activity – Rheinberg (1989) describes this as the
incentive that lies solely in engaging in the task – and is positively related to positive affect (e.g., Bye,
Pushkar, & Conway, 2007). Goal focus, in contrast, is affectively neutral in the sense that it takes on the
affective valence that people experience or anticipate when they focus on the process or outcome,
respectively. For instance, when a person focuses on highlighting important passages in a paper and
experiences this activity as fun, this would likely positively influence her affect, but if she experienced this
activity as boring, this would likely negatively impact her affect.
The meaning of the concept of goal focus dissolves in the structure-perspective on intrinsic
motivation by Shah and Kruglanski (2000). The authors maintain that intrinsic motivation occurs when an
activity (means) and the outcome of this activity (goal) are closely associated such that there is a sense of
inseparability between the two (i.e., a means-end fusion; Kruglanski et al., 2013). A case in point is the
goal to have a good time with friends where the means – doing something fun with friends – cannot be
separated from the ends. If the activity itself constitutes the desirable end state, as is the case in all
enjoyment goals (e.g., enjoying music, a good meal, or somebody’s company), the concept of goal focus
becomes vacuous as it presupposes separable means and ends.
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In sum, the concept of goal focus has some overlap with other motivational constructs such as
construal level as well as intrinsic and extrinsic motivation, but it also carries unique meaning that is not
covered by these constructs (for links between goal focus and mastery/performance goal orientation, see
Freund et al., 2012). Let us now turn to the adaptiveness of goal focus. Specifically, we first give an
overview of empirical evidence suggesting that a process focus (i.e., a ‘‘the way is the goal’’ attitude) is
related to a higher likelihood of achieving difficult goals and to affective well-being. Then, we will address
the underlying mechanisms that explain why focusing on the process is adaptive, and also consider
situations in which an outcome focus might be more adaptive.
Adaptiveness of Process Focus for Successful Goal Pursuit and Subjective Well-Being
There is growing evidence that adopting a process focus is more beneficial to successful goal pursuit
and achievement than adopting an outcome focus – particularly when goal pursuit is difficult. In a
longitudinal study with overweight women, Freund and Hennecke (2012) found that focusing on the
process (dietary behaviors) rather than on the outcome of dieting (weight loss) is associated with more
successful goal pursuit and achievement. Similarly, Hennecke and Freund (2014) examined how goal
progress during a diet (i.e., weight loss) impacts subsequent weight loss depending on whether success is
identified on the process level or the outcome level of dieting. They found that successful weight loss in
one week predicted less weight loss (or even weight gain) in the subsequent week – a well-known effect
from the literature on “self-licensing” (e.g., De Witt Huberts, Evers, & De Ridder, 2012). However,
identifying success on the process level (vs. the outcome level) attenuated this negative effect.
In the academic context, Pham and Taylor (1999) found that students who mentally simulate the
process of studying for an exam study more hours and obtain higher exam scores than students who
mentally simulate the feeling of receiving a good grade or that do not mentally stimulate anything at all
(i.e., a control group). In the same context, focusing on the process has also been found to be adaptive
when learning a new task such as acquiring writing revision skill (Zimmerman & Kitsantas, 1997, 1999).
Houser-Marko and Sheldon (2008) found that students who self-reported lack of goal progress framed in
terms of the outcome (which they termed “primary goal level”) reported lower levels of perceived
performance than students who framed lack of goal progress in terms of the process (which they termed
“sub-goal level”).
In other studies, a process rather than an outcome focus was positively related to dental flossing
(Fishbach & Choi, 2012) and exercising adherence (Fishbach & Choi, 2012; Freund, Hennecke, &
Riediger, 2010; Kaftan & Freund, 2017b). For example, Fishbach and Choi (2012) found that asking
participants to describe why (i.e., outcome focus) they were engaging in a particular activity (e.g., yoga)
resulted in a lower level of persistence than was observed when asking participants to describe their
experience of the activity (i.e., process focus). Goal persistence, in turn, is associated with subjective wellbeing
and good health (e.g., Bandura, 1986).
Similarly, in the study of Freund et al. (2010), participants with the goal to exercise regularly
reported greater persistence, a higher goal satisfaction, and higher affective well-being (i.e., positive affect)
over a period of 3 months when they focused on the means (vs. the outcomes) of achieving a goal. Further
evidence regarding links to subjective well-being suggests that goal focus might be indirectly related to
affective well-being through the ability to regulate one’s behaviors and thoughts (Freund & Hennecke,
2012). Thus, outcome focus might indirectly affect negative emotions through failures of self-control. This
is also supported by results from Houser-Marko and Sheldon (2008), who found that failure feedback had
stronger negative effects on mood when it pertained to the outcome compared to the process. When goal
pursuit is difficult, people who focus on the process are also more satisfied with their performance
(Vallacher, Wegner, & Somoza, 1989).
Underlying mechanisms. Why is adopting a process focus more adaptive than adopting an outcome
focus? As mentioned before, a process focus likely provides guidelines for goal-relevant actions (e.g.,
Emmons, 1996; Klinger, 1977; Little, 1989). In their study, Pham and Taylor (1999) investigated the
mechanisms by which process simulation exerts its positive effect on exam performance. They found that
the effect was mediated by enhanced planning and reduced anxiety. In a similar vein, Fishbach and Choi
(2012) explained their findings by arguing that experience weighs more than the outcome as soon as people
actually pursue an activity. In their study, an outcome focus not only negatively affected the positive
experience of pursuing a goal but also reduced participants’ motivation and adherence to goal-relevant
routines. Thus, when people adopt an outcome focus, they might be more likely to pursue an activity only
as a means to an end, which causes a devaluation of the intrinsic appeal of the activity. In contrast, focusing
on the process may counteract the tendency for complacency and to “slack” when making progress
towards goal achievement (Amir & Ariely, 2008; De Witt Huberts, Evers, & De Ridder, 2014). For
example, when people focus on the process, success and failure are followed by less intense affective
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reactions (Houser-Marko & Sheldon, 2008). That is, focusing on the process of successful goal pursuit less
likely generates a sense of achievement that can be followed by a period of decreased goal-related effort
than focusing on the outcome (Amir & Ariely, 2008). In contrast, a failure in goal pursuit less strongly
impairs mood, subsequent motivation, and expectancy for future goal performance when focusing on the
means instead of the outcome (Freund & Hennecke, 2012; Houser-Marko & Sheldon, 2008).
There are several reasons why focusing on the process may be particularly beneficial when people
learn a new task (Zimmerman & Kitsantas, 1997, 1999), a task is difficult (Vallacher et al., 1989), or the
goal demanding with respect to self-regulation (Freund et al., 2010). In these cases, a process focus helps
people to acquire the necessary goal-relevant means and make fewer errors. In the dieting study of
Hennecke and Freund (2014), process focus (but not outcome focus) predicted increases in self-efficacy
from baseline to after the diet. Self-efficacy, in turn, is known to adaptively influence the goal challenges
people set for themselves, the effort they invest in the endeavor, and how perseverant they are when facing
difficulties and setbacks (Bandura, 2013). In this line, several studies have documented that people who are
confident to achieve what they want (i.e., are high in self-efficacy) also experience higher subjective wellbeing
than people who are not (i.e., are low in self-efficacy; e.g., Caprara & Steca, 2005; Lent et al., 2005;
Luszczynska, Scholz, & Schwarzer, 2005). Similarly, it is likely that a higher process focus leads to higher
perceived behavior control, which entails both self-efficacy (dealing largely with the ease or difficulty of
performing a behavior) and controllability (the extent to which performance is up to the actor; Ajzen,
2002).
Moreover, when adopting a process focus, people more likely persist in a given activity (e.g.,
studying) if they experience this activity as rewarding (Freund & Hennecke, 2015). The reward might lie in
the intrinsic value of the means (e.g., an increased interest in the activity) or in their instrumentality for
achieving the desired outcome. When people perceive the means as particularly instrumental, this not only
positively influences their motivation to pursue a given goal but also how much effort they invest in goal
pursuit, and their performance (Bandura, 1997; Labroo & Kim, 2009). In turn, when people feel that they
invest effort in the process of goal pursuit, they also come to view the means as more valuable and
instrumental (Labroo & Kim, 2009). In contrast, an outcome focus may distract from practicing and
acquiring the goal-relevant means and thereby hinder successful goal pursuit.
A related reason for the adaptiveness of process focus is that people use effort as a heuristic: the
more effort they invest in goal pursuit, the more valuable they deem the outcome to be (Kruger, Wirtz, Van
Boven, & Altermatt, 2004). Higher value beliefs, in turn, are linked to a higher persistence (e.g., Eccles &
Wigfield, 2002; Wigfield & Eccles, 2000). Thus, when a person focuses on the means of goal pursuit, the
effort he or she has invested in goal pursuit as well as the value and instrumentality of the means should be
more salient compared to when the person focuses on the outcome. A process focus should therefore
intensify the described effects and contribute to greater persistence and better performance. A quote that
nicely encapsulates these effort-related benefits of a process focus comes from former supreme court
justice Benjamin Cardozo, who stated that: “In the end the great truth will have been learned that the quest
is greater than what is sought, the effort finer that the prize (or rather, that the effort is the prize), the victory
cheap and hollow were it not for the rigor of the game.”
Adaptiveness of Outcome Focus
At first sight, the reviewed evidence supporting the adaptiveness of process focus for successful
goal pursuit contradicts findings from other studies in the field. A first important contradiction seems to
exist between the work on goal focus and research on construal level. Research on goal focus favors the
adaptiveness of adopting a process focus, whereas research on construal level has shown that higher-level,
more abstract construals increase the adoption of both immediate (e.g., Magen & Gross, 2007; Schmeichel
& Vohs, 2009) and prospective (e.g., Fujita & Roberts, 2010) self-control strategies.
For example, Fujita et al. (2006) found that higher-level construals can improve self-control by
reminding people of the reasons why (i.e., their superordinate goals) they are engaging in a difficult
behavior (e.g., studying for an exam). Self-control, in turn, is related to positive affect as part of subjective
well-being (e.g., Hamama, Ronen, Shachar, & Rosenbaum, 2013). However, note that goal focus denotes
the salience of means and ends within a given goal, whereas the operationalization of construal level by
Fujita and colleagues induces a general cognitive mind-set of a more high-level (i.e., abstract) and a more
low-level (i.e., concrete) representation of events. This mind-set is induced using events that are unrelated
to the goals and self-reported self-control judgments that are subsequently assessed. This kind of
procedural priming does not target the relative salience of the means and ends within a given goal. For
instance, in Study 1, Fujita et al. (2006) asked participants to generate responses to “why” or “how” to
maintain good physical health. They subsequently assessed a variant of the delay of gratification scenarios
that are unrelated to physical health as a measure of self-control for various items (e.g., a DVD player),
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indicating a preference for immediate versus delayed rewards. In fact, Fujita and colleagues (2006, p. 355)
state that “preferences for immediate versus delayed outcomes do not capture a conflict between means and
ends but rather a conflict between what is primary and what is secondary.”
Another potential issue that challenges the supremacy of process focus over outcome focus is that
outcome focus may be adaptive in specific phases of goal pursuit. There are no studies that systematically
compare the adaptiveness of outcome focus and process focus in different phases of goal pursuit, however,
Freund et al. (2012; see also Krause & Freund, 2014b) suggested that process and outcome focus as well as
their adaptiveness may change over the course of goal pursuit. For instance, when a deadline is still far
away, a focus on the outcome may distract people from the implementation of goal-relevant actions. In
contrast, once the deadline is looming, an outcome focus might revive the importance of a goal and give a
final “boost” to motivation even if the means are unpleasant. If research were to show that the adaptiveness
of process and outcome focus dynamically varies over time, this would also have implications for
subjective well-being. One particular challenge that would have to be addressed in this research is the
separation of changes in subjective well-being tied to goal focus and goal pursuit from fluctuations of
subjective well-being due to independent factors such as diurnal rhythm (Chow, Ram, Boker, Fujita, &
Clore, 2005; Larsen, 2000; Luhmann, Schimmack, & Eid, 2011). Solving this issue necessitates the
assessment of both goal focus and indicators of subjective well-being repeatedly over time (see Diener,
Pressman, Hunter, & Delgadillo-Chase, 2017).
Similarly, Carver and Scheier (1998) argue that focusing on the outcome and comparing the current
with the desired state could motivate a person to move towards the goal. Especially when a task is
perceived negatively, being reminded of its importance (the abstract framing) may aid goal-pursuit and
achievement (Ferguson & Sheldon, 2010; McCrea, Liberman, Trope, & Sherman, 2008). Shah and
Kruglanski (2003) found that priming attainment means increases the cognitive accessibility of desired goal
states, which has a positive effect on persistence and performance during goal pursuit. However, the
activation of goals (i.e., outcomes) by their attendant means was moderated by the perceived effectiveness
of the means and it remains unclear to what extent participants consciously focused on means and
outcomes during actual goal-directed striving.
If a task at hand is relatively easy to master, an outcome focus might be more adaptive than a
process focus because people can better appreciate and consolidate their own motivations for striving,
which may then re-energize them towards the goal (Ferguson & Sheldon, 2010; Houser-Marko & Sheldon,
2008; Vallacher & Wegner, 1989; Vallacher et al., 1989). A person who focuses on the outcome or keeps
her “eyes on the prize” (Houser-Marko & Sheldon, 2008) might also be less distracted by alternative
activities. In contrast, a person who focuses on task details, could feel overwhelmed (Dewitte & Lens,
2000). Further evidence suggests that people can benefit from shifting from a process to an outcome focus
when they have acquired the necessary skills to master a task (Zimmerman & Kitsantas, 1997, 1999).
In summary, the existing research suggests that adopting a process focus (vs. outcome focus)
promotes successful goal-pursuit and subjective well-being. More research is needed to identify boundary
conditions and potential moderators and mediators of the relationship between goal focus, successful goal
pursuit, and subjective well-being. This includes the investigation of additive or synergistic effects of
process and outcome focus. A simultaneous focus on both process and outcome may lead to a recognition
of trade-offs between the desirability of a goal on the outcome level and its feasibility on the means level,
hence be beneficial for goal pursuit. For example, in their mental simulation study, Pham and Taylor
(1999) found that mentally simulating both the process and the outcome was more beneficial for motivation
than mentally simulating the process alone. Conversely, focusing on process and outcome may lead to
decision difficulty, that is, a greater willingness to postpone making a choice, and a lower commitment to
the chosen option (Escalas & Luce, 2004; Thompson, Hamilton, & Petrova, 2009).
The evidence reviewed above shows that goal focus predicts successful goal pursuit and subjective
well-being. Exploring the boundaries of the usefulness of this construct, the next section elaborates more
on the role of goal focus in the context of one of the highly prevalent failures in goal pursuit:
procrastination.
Goal Focus, Procrastination, and Subjective Well-Being
People typically do not pursue one goal in isolation but instead have multiple goals that compete for
goal-relevant resources such as time and energy. For instance, wanting to pass an exam might conflict with
the goal to make new friends. The presence of multiple goals thus poses challenges to goal pursuit. For
example, to the extent that alternative goals are accessible, they may interfere with the commitment to a
given goal. Accordingly, goals and means have to be defended or shielded by inhibiting alternative goals
(e.g., Shah et al., 2002; Shah & Kruglanski, 2008). In this sense, alternative goals represent temptations. A
temptation can be understood as an alternative goal, the pursuit of which hinders attainment of the focal
207
goal, and provides less important (though often more psychologically immediate) rewards than the focal
goal (Trope & Fishbach, 2000; Trope & Liberman, 2003).
Procrastination denotes the difficulty in protecting a given focal goal against alternative goals
(Dewitte & Schouwenburg, 2002; Dietz, Hofer, & Fries, 2007) and is defined as “the voluntary delay of an
intended and necessary and/or personally important activity, despite expecting potential negative
consequences that outweigh the positive consequences of the delay” (Klingsieck, 2013, p. 26). In other
words, a person has the intention to act but delays doing so to the point of discomfort (e.g., Howell &
Watson, 2007; Krause & Freund, 2014a; Solomon & Rothblum, 1984).
Procrastination and Subjective Well-Being
Over the past three decades, extensive research has provided a wealth of insights into the correlates
and consequences of procrastination for subjective well-being. This research has shown that procrastination
is associated with negative mood states such as depression and anxiety (e.g., Ferrari, 1991; Martin, Flett,
Hewitt, Krames, & Szanto, 1996; Senécal, Koestner, & Vallerand, 1995), shame and guilt (e.g., Blunt &
Pychyl, 2005; Fee & Tangney, 2000; Giguère, Sirois, & Vaswani, 2016), negative self-blame (Sirois &
Kitner, 2015), negative self-evaluations in general (Flett, Stainton, Hewitt, Sherry, & Lay, 2012; McCown,
Blake, & Keiser, 2012), low self-esteem (Ferrari, 1994, 2000), low levels of self-compassion (Sirois, 2014),
distress (e.g., Flett et al., 2012; Richardson, Abraham, & Bond, 2012), and poor overall mental health
(Stead, Shanahan, & Neufeld, 2010). At first glance, the many ties of procrastination to subjective wellbeing
may seem surprising because waiting to the last minute to get tasks done is often only immediately
stressful and seems to save the time of longer goal pursuit. In fact, when we give talks on procrastination
there is typically at least one person in the audience who proudly claims that he or she saves time by
procrastinating and gets the task done nevertheless. Obviously, the attribution we are to make is: The
person is simply a genius and gets everything done perfectly well at the very last minute. However, even if
this prototypical audience member is in fact a genius and an exception to the rule, the rule is that
procrastination leads to lower levels of subjective well-being and task performance (Steel, 2007). In fact, it
is likely that procrastination as a more enduring tendency leads to chronic stress, which is associated with
an increased risk for chronic illness that can create additional vulnerabilities and compromise subjective
well-being (for an overview and the procrastination-health model, see Sirois, 2016a, 2016b).
Linking Goal Focus to Procrastination
Procrastination research has predominantly focused on explaining procrastination as a dispositional
trait (Milgram, Mey-Tal, & Levison, 1998) and only little research has conceptualized and investigated
procrastination as a behavioral phenomenon that depends on situational or action-oriented factors
(Klingsieck, Grund, Schmid, & Fries, 2013).
We assume that the general mechanisms underlying the adaptiveness of process focus discussed
above also apply to procrastination. However, some additional mechanisms are helpful for understanding
procrastination. People who represent a goal more concretely (vs. abstractly) perceive goals as more urgent
and, thereby, are more likely to engage in goal pursuit and to procrastinate less (McCrea et al., 2008). In
contrast, a higher-level, distant construal of a task (i.e., outcome focus) might lead to the conclusion that the
task only needs to be completed in the distant future, thereby matching levels of construal.
Krause and Freund (2014b) argued that focusing on the means of goal pursuit might reduce
procrastination by directing one’s attention to the specific actions required during goal pursuit (e.g., exam
preparation) rather than to the – temporally more distant – outcome (e.g., good grade in an exam) that, in
addition, might be associated with fear of failure. Testing this hypothesis, Krause and Freund (2016) found
that process focus is negatively related to procrastination. In addition, a higher process focus reduced fear
of failure and task aversiveness that also contributed to procrastination. In a workout study (Kaftan &
Freund, 2017b), we found that people with a higher average process focus skip less workout sessions (i.e.,
procrastinate less), report a higher workout satisfaction, and improve more over time as measured by
objective fitness indicators (i.e., number of push-ups). Additionally, average process focus was positively
related to mood.
Similarly, research on implementation intentions has found that, compared to the consideration of
why one should pursue a given goal (i.e., outcome focus), the consideration of how to go about pursuing a
goal (i.e., process focus) leads people to faster identify opportunities to act (Parks–Stamm et al., 2007;
Webb & Sheeran, 2004), to initiate goal-relevant activities (Orbell & Sheeran, 2000; Parks–Stamm et al.,
2007), to anticipate action earlier (Gollwitzer, Heckhausen, & Ratajczak, 1990), and to engage in as well as
complete assigned tasks prior to a deadline (i.e., to procrastinate less; Bamberg, 2002; Gollwitzer &
Brandstätter, 1997).
Moreover, when people focus on small, manageable units of action, a process focus may not only
208
provide concrete guidelines for action (Carver & Scheier, 1998; Freund et al., 2010), but also circumvent
the problem of delay of gratification as it directs attention to the small, immediate steps toward goal
achievement (Steel & König, 2006), and thus reduces procrastination.
Goal Focus and the Immediate Experience of Activities
Goal focus may also have very immediate effects on how people experience or perceive activities
during goal pursuit. Particularly in the case of procrastination, reports of immediate experience are
important because they may differ from retrospective reports due to rationalization processes. For example,
students may not experience much guilt when procrastinating because they suddenly perceive cleaning as
very important, only to regret afterwards that they cleaned instead of studying for an exam. In line with this
reasoning, Krause and Freund (2014a) found a negative association between self-reported procrastination
and affective well-being (but see Pychyl, Lee, Thibodeau, & Blunt, 2000).
In our own experience sampling study (Kaftan & Freund, 2017c), we sent questionnaires to
participants at times they had planned to engage in goal pursuit (writing a thesis) and asked them to
indicate how they perceived the alternative activities they were currently engaged in when procrastinating.
One of the results was that a higher outcome focus on alternative activities was associated with a higher
perceived importance, lower pleasantness, and less guilt. These changes in the perception of activities were
also found in a second experience sampling study (Kaftan & Freund, 2017b) conducted in a different
context (i.e., the sports domain) and may have important consequences for further goal pursuit. On the one
hand, perceiving alternative activities as more important and less guilt-evoking can be maladaptive because
it may sustain procrastination. On the other hand, the lower pleasantness may serve as a stop signal to
procrastination. By affecting further goal pursuit, goal focus, then, might also affect subjective well-being.
Overall, these studies suggest that the relationship between goal focus and procrastination is complex and
that more research is needed to better understand the dynamics underlying procrastination.
Conclusion
Whether goal attainment leads to subjective well-being depends on different factors, such as what
goals are selected (e.g. approach or avoidance goals) and whether they meet basic needs (e.g., competence).
Although people usually experience a form of contentment when they attain their goals, they are trapped in
a hedonic treadmill running in vain for greater happiness as the effects of goal achievement are more shortlived
than they might wish. Given that we typically spend much longer on pursuing our goals than
experiencing their attainment, it seems crucial to investigate processes linking goal pursuit to subjective
well-being. We maintain that goal focus is a promising construct for understanding the mechanisms of how
goal pursuit may increase (or decrease) subjective well-being. Growing evidence supports the view that
adopting a process focus (i.e., focusing on the way of goal pursuit) is associated with positive affect and
subjective well-being, and leads to a higher persistence and goal attainment, even when encountering
difficulties or setbacks during goal pursuit.
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Hedonic Adaptation and the Set Point for Subjective Well-Being
By Maike Luhmann & Sabrina Intelisano, Ruhr University Bochum
Citation
Luhmann, M., & Intelisano, S. (2018). Hedonic adaptation and the set point for subjective well-being.
In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
Classical theories of hedonic adaptation assume that lasting changes in subjective well-being (SWB) are
not possible because one’s SWB inevitably returns to its baseline level, a phenomenon known as the
hedonic treadmill. This baseline level is sometimes referred to as the set point for SWB and is assumed to
be primarily determined by heritable factors. In this chapter, we review classical theories on hedonic
adaptation: adaptation-level theory, range-frequency theory, hedonic relativism and the hedonic treadmill,
opponent-process theory, the concept of the genetically determined set point, the distinction between
desensitization and shifts in adaptation levels, and dynamic equilibrium theory. We then review the
empirical evidence on these theories, with a focus on longitudinal studies on the heritability and stability of
SWB, on changes in SWB after life events, and on the effectiveness of SWB interventions. Together, the
empirical evidence suggests that although SWB is stable for most people, lasting changes are nevertheless
possible. Recent theoretical developments such as the revised set-point theory, SWB homeostasis theory,
and the hedonic adaptation prevention model offer different explanations for these findings. The chapter
concludes with a discussion of four central questions that need to be addressed in future research.
Keywords: Hedonic Adaptation, Hedonic Treadmill, Set Point Theory, Dynamic Equilibrium
Theory
A quick stroll through the self-help section of any average bookstore conveys a clear message:
Happiness is attainable anytime and for anyone, if one only chooses the right lifestyle. Although there is
considerable disagreement on which lifestyles are particularly good for happiness, with options ranging
from meditating to finding fulfilling relationships to achieving material success, the common theme of this
industry is that happiness and well-being can be changed.
For decades, scholars of happiness and well-being begged to differ. The science of happiness and
well-being was for a long time dominated by the notion that our individual level of well-being is primarily
determined by our genes, that we adapt to any changes in life circumstances rapidly and completely, and
that any attempts to improve our happiness are futile. This notion has been proposed under various labels,
including adaptation level (Helson, 1948, 1964), hedonic treadmill (Brickman & Campbell, 1971),
dynamic equilibrium (Headey & Wearing, 1989, 1992; Solomon & Corbit, 1974), set point (Lykken &
Tellegen, 1996), and hedonic adaptation (Frederick & Loewenstein, 1999), and became such a
fundamental part of this field of research that some likened it to a research paradigm (Headey, 2008b).
In the 2000’s, however, a series of longitudinal studies examining changes in life satisfaction after
major life events such as widowhood, marriage, divorce, or unemployment (summarized in Lucas, 2007a)
challenged the assumption that people can adapt to any circumstances and initiated a paradigm shift
(Headey, 2008b). It is now widely accepted that while most people experience stable levels of happiness
and well-being, significant and lasting changes can, and do, occur (Sheldon & Lucas, 2014).
The present chapter recounts this paradigm shift and provides an overview of past and current
theories and empirical research. It begins with a review of historical and philosophical accounts, followed
by a presentation of the main classical theories. We then review empirical evidence for these theories,
focusing on longitudinal studies, and discuss recent and current theoretical developments that have been
prompted by the empirical evidence. The chapter concludes with a discussion of open questions and
directions for future research.
Early Historical and Philosophical Accounts
In many cultures and languages, the word “happiness” appears as a synonym for luck and fortune.
This reflects an ancient view of the world as a place governed by an external power where there was little
human beings could do to improve their conditions (McMahon, this volume). The pursuit of happiness
consequently was a worthless task for humans. Since they are subject to the change of fate and fortune,
humans should not even strive for happiness. In accordance with this idea, the pursuit of happiness has
often been compared to Sisyphus’ task: No matter how hard we try to be happier, we will always go back
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to our previous level of happiness. Sisyphus, a figure in Greek mythology, was condemned to rolling an
immense stone up a hill, only to watch it roll down again and again for eternity.
Whether this notion is true has been a point of debate since the days of the religions traditions and
the Ancient Greece (McMahon, this volume). In contrast to the very early idea of happiness as merely
governed by luck, most Hellenistic philosophers believed that happiness and well-being can change but
differed in what causes these changes. For example, Democritus suggested that happiness does not depend
on fortune and external circumstances, but resides in people’s cast of mind. Epicurus was the first to
propose that the best way to improve our human lives is to have pleasure and to avoid pain. In contrast,
Seneca, as a Stoic, believed that virtue alone was sufficient for happiness. Aristotle thought that happiness
is achievable by anyone living a virtuous life but admitted that fortune and external circumstances play a
big role in human happiness. In sum, even if they differed on what happiness is and how it can be
achieved, all the great ancient school of philosophy agreed that the possession of certain material goods,
such as money, cannot guarantee that one’s well-being increases beyond a certain threshold. Most
importantly, they also agreed that the determinants of happiness lay within individuals, in that only one’s
moral and rational behaviors lead to happiness (Haybron, 2008a; McMahon, 2006; Tatarkiewicz, 1976).
Similar to Greek philosophers, Christian philosophers of the Middle Ages believed that virtue was
indispensable for happiness, but in contrast to Greek philosophers, they believed that happiness lays in the
hands of God and could only be attained by leading a life inspired by faith in God (McMahon, 2006).
The idea of happiness as something that humans have the power to achieve spread again in the Age
of Enlightment. The concept of happiness assumed a subjective connotation, and pleasure was all that
mattered for a happy life. At the beginning of 18th century, John Locke declared that happiness is the
utmost pleasure of which we are capable, thereby implying that we are able to change our happiness. In this
spirit, the United States Declaration of Independence of 1776 granted the pursuit of happiness as an
unalienable right. The notion that happiness (in terms of pleasure) was achievable was also unquestioned
by the Classical Utilitarians, Jeremy Bentham and John Stuart Mill, who argued that we ought to maximize
the total amount of happiness, that is, bring about ‘the greatest amount of happiness for the greatest
number’.
In sum, most of these philosophers agreed that lasting happiness is at least in principle attainable.
The concept of adaptation is, however, discussed in contemporary treatises on happiness and well-being
which usually integrate philosophical thinking with empirical research findings. A common notion in
contemporary philosophy is that even if there is a set level of happiness, there are still opportunities for us
to improve our level of happiness (e.g., Haybron, 2008b).
Classical Psychological Theories
Most psychological theories relate to aspects of happiness and well-being that can be counted as
components of subjective well-being (SWB), and we therefore focus on this construct for the remainder of
the chapter. According to Diener (1984), SWB comprises cognitive components such as life satisfaction
and satisfaction with specific life domains (also referred to as cognitive well-being) as well as affective
components such as the frequency of positive affect (PA) and negative affect (NA) (also referred to as
affective or emotional well-being and comprising both mood and specific emotions).
Adaptation-Level Theory
In general, adaptation describes a process through which systems change their sensitivity to
external stimuli. For example, our eyes are able to adapt to varying lighting conditions. When we enter a
dark room, we are almost blind at first, but within minutes, our eyes adapt to darkness and we are able to
perceive more and more details.
In his adaptation-level theory, Helson (1948, 1964) proposed a mathematical model of adaptation.
The main concept in this theory is the adaptation level, which is defined as the level at which a stimulus
evokes a neutral response. The adaptation level determines whether stimuli are experienced as positive
(above the adaptation level), neutral (at the adaptation level), or negative (below the adaptation level). For
example, an object is experienced as heavy if its weight is above a person’s adaptation level, and as light if
its weight is below a person’s adaptation level.
According to Helson (1948), the adaptation level is a function of the weighted geometric mean of
all past stimuli. A person who lifted primarily light objects in the past would therefore have a lower
adaptation level than a person who lifted primarily heavy objects in the past. Each new stimulus is factored
into this equation, which means that the adaptation level is not fixed but can change. A shift in the
adaptation level then influences how future stimuli are evaluated. For example, if a person with a low
adaptation level for perceiving weights is required to lift a number of heavy weights, his or her adaptation
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level should move upwards. This shift affects how objects lifted in the future are evaluated. Objects that
were initially above the adaptation level and therefore had been perceived as relatively heavy might then be
below the adaptation level and be perceived as relatively light.
Although adaptation-level theory was originally developed and tested with respect to perception,
Helson (1964) explicitly argued that his theory is generalizable to other psychological experiences. With
respect to SWB, the main implication of adaptation-level theory is that changes in stimuli lead to changes in
what is perceived as neutral (i.e., adaptation level) such that despite changing stimuli (i.e., circumstances),
people inevitably revert to a point of neutrality over time. On average, people should therefore experience
SWB that is neither positive nor negative.
Range-Frequency Theory
Similar to adaptation-level theory, range-frequency theory (Parducci, 1968, 1995) offers a
mathematical formulation of how people evaluate hedonic and non-hedonic stimuli. Just like adaptationlevel
theory, range-frequency theory assumes that novel stimuli are compared to past stimuli. In contrast to
adaptation-level theory, however, range-frequency theory predicts that a novel stimulus is not evaluated
against the mean of the value of past stimuli but with respect to two parameters of the distribution of the
value of past stimuli: range and frequency. The range principle posits that a stimulus is compared to the
minimum and maximum of the distribution of previous stimuli. The closer a novel stimulus lies to the
maximum of the range (i.e., to the most positive past stimulus), the more positively it is evaluated. The
frequency principle posits that a novel stimulus is evaluated with respect to the frequency of previous
stimuli below the novel stimulus. The more stimuli lie below the novel stimulus, the more positively the
novel stimulus is evaluated.
To illustrate these principles and to highlight the difference between adaptation-level theory and
range-frequency theory, consider an example where the value of past stimuli follows the positively skewed
distribution shown in Figure 1 and the value of a novel stimulus corresponds exactly to the mean of
previous stimuli. According to adaptation-level theory, this stimulus would be evaluated as neutral because
its value is equal to the adaptation level. According to the range principle, this stimulus would be evaluated
negatively because it lies in the bottom half of the range. According to the frequency principle, in contrast,
this stimulus would be evaluated positively because more than half of the previous stimuli were even more
negative. Hence, the range principle and the frequency principle can lead to divergent evaluations and
therefore have to be weighed against each other when evaluating new stimuli. In sum, range-frequency
theory differs from adaptation-level theory (Helson, 1948, 1964) in that it explicitly assumes that not all
past stimuli are equally important in predicting how people react to new stimuli.
Figure 1. Illustration of adaptation-level theory and range-frequency theory. The figure shows the
distribution of past stimuli which in this example is positively skewed. The solid vertical line
indicates the geometric mean (M) of past stimuli, i.e. the adaptation level as defined in adaptationlevel
theory. The dashed vertical line indicates the median (Md), i.e. the value that splits the
distribution into two equally-sized halves. The dotted vertical line indicates the midpoint of the entire
range of past stimuli. A novel stimulus with a value corresponding exactly to the mean (M) would be
evaluated as neutral according to adaptation-level theory because it is identical with the adaptation
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level. According to the frequency principle, it would be evaluated positively because it is more
positive than the median. According to the range principle, it would be evaluated negatively because
it is more negative than the range midpoint.
The Hedonic Treadmill
Brickman and Campbell (1971) were among the first to systematically apply adaptation-level
theory to hedonic experiences. They proposed that people experience pleasure and satisfaction when they
are confronted with stimuli that are more positive than their hedonic adaptation level, and they experience
pain and dissatisfaction when they are confronted with stimuli that are more negative than their hedonic
adaptation level. These stimuli are then integrated into the hedonic adaptation level, leading either to an
upward or a downward shift in what people experience as hedonically neutral. The satisfaction or
dissatisfaction elicited by a particular stimulus therefore fades over time, and people inevitably revert to a
level of hedonic neutrality. Permanent happiness or satisfaction can thus only be achieved through a
constant stream of novel positive stimuli – an endeavor that Brickman and Campbell described as a
hedonic treadmill.
Expanding Helson’s (1948, 1964) original ideas, Brickman and Campbell (1971) further proposed
that a new stimulus is not only compared to one’s past experiences (temporal comparisons), but also to
one’s experiences in other life domains (spatial comparisons) and to experiences made by other people in
one’s social network (social comparisons). Social comparisons are assumed to be particular powerful. For
example, whether receiving one’s monthly salary is experienced as hedonically positive, negative, or
neutral depends not only on one’s previous salaries (the salary would be experienced as positive if it were
higher than before) but also on the salary of similar people (e.g., the salary would be experienced as
negative if it were still lower than the salary of one’s co-workers).
Brickman and Campbell realized that the hedonic treadmill has serious individual and societal
implications. On the individual level, it implies that “subjective pleasure is, as a state, by its very nature
transient and, as a goal, an ever-receding illusion” (Brickman & Campbell, 1971, p. 289) unless one
manages to get off the hedonic treadmill by “abandoning all evaluative judgments” (Brickman & Campbell,
1971, p. 300). They also infer that high SWB would be easiest to attain for those with particularly low
hedonic adaptation levels because almost all stimuli would be experienced as positive. Thus, they conclude,
“the happiest adult is one who had a moderately unhappy childhood” (Brickman & Campbell, 1971, p.
293) and who remembers these unhappy moments occasionally in order to maintain a permanently low
hedonic adaptation level.
On the societal level, the hedonic treadmill implies that any policy interventions aimed at
improving a population’s SWB are doomed to fail because people adapt to any changes in their life
circumstances. This conclusion was backed up by the Easterlin Paradox which describes the observation
that national happiness levels remain constant across time despite rising income levels (Easterlin, 1974).
Opponent-Process Theory
Similar to the theories discussed thus far, opponent-process theory (Solomon & Corbit, 1974)
assumes that the hedonic impact of any stimulus on SWB is brief and that people eventually return to a
state of hedonic neutrality. The most important contribution of opponent-process theory lies in spelling out
how this return to baseline unfolds over time.
Solomon and Corbit (1974) propose that the standard hedonic response to a stimulus can be split
into five stages (Figure 2). (1) Stimulus onset is associated with an immediate pleasant or unpleasant
primary reaction, which peaks shortly after stimulus onset. (2) Over time, the intensity of the hedonic
reaction declines through adaptation, even if the stimulus remains present. (3) The hedonic reaction then
stabilizes on a non-neutral level as long as the stimulus remains present. (4) Once the stimulus is
terminated, an opponent process kicks in. This so-called affective after-reaction is opposite to the primary
reaction (e.g., negative if the primary reaction was positive) and peaks shortly after the stimulus is
terminated. This pattern is sometimes referred to as the overshoot effect. The opponent process is activated
automatically and indirectly through the primary reaction and constitutes a physiological response to the
primary reaction. (5) The opponent process weakens over time and the affective state returns to its initial
neutral level (hedonic equilibrium).
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Figure 2. Five stages of the hedonic response to a stimulus according to opponent-process theory
(Solomon & Corbit, 1974). Figure adapted from Solomon and Corbit (1974, p. 120, Figure 1).
To illustrate this pattern, imagine a young couple on one of their first dates. When they first see
each other, they experience intense joy and excitement (primary reaction). Over the next hours, the
intensity of these emotions declines (adaptation) but they remain in a generally positive hedonic state.
However, when they part ways, the automatic opponent process takes over, leaving them sad and longing
for each other’s company. These negative emotions are most intense immediately after the separation and
decline again over time until both return to their initial state of hedonic equilibrium.
The existence of opponent processes has several important implications. First, this theory is unique
among all classical theories discussed here in its emphasis of the role of time. Because the affective
reaction to a stimulus unfolds in a highly complex and dynamic pattern over time, its trajectory can only be
described adequately if multiple repeated measures that cover each of the five stages are available. Crosssectional
studies and longitudinal studies using inappropriate time points and intervals between
measurement occasions may lead to wrong conclusions because they may confound primary and opponent
processes. A study of the affective impact of a romantic date would come to vastly different conclusions if
the affective reactions of the couple were measured shortly after the date began, shortly after it ended, or a
few days later when both had returned to hedonic neutrality. Second, this theory implies that any stimulus
can cause both positive and negative reactions, either as the primary process or as the opponent process.
Although opponent-process theory has been developed to describe the short-term dynamics of affect, this
implication may also apply to more long-term dynamics of SWB, for example in the context of major life
events.
We conclude this section with highlighting additional differences between opponent-process theory
on one hand and adaptation-level theory and its spin-offs on the other. All of these theories assume that
stimuli are evaluated relative to the baseline level, which they refer to as adaptation level (adaptation-level
theory) or hedonic equilibrium (opponent-process theory). However, adaptation-level theory and related
accounts propose that this level can change as a function of previous related stimuli whereas opponentprocess
theory implies that this level remains unchanged (cf. Bowling, Beehr, Wagner, & Libkuman,
2005). Furthermore, only opponent-process theory explicitly assumes that the underlying processes are
automatic and physiological. Hence, while all theories assume that people experience, on average, hedonic
neutrality, they differ fundamentally in their assumptions about the underlying processes through which
hedonic neutrality is maintained.
Dynamic Equilibrium
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Headey and Wearing (1989, 1992) expanded previous theoretical accounts by adding personality to
the equation. According to their dynamic-equilibrium theory, each person has two types of equilibriums: a
SWB equilibrium and a life-events equilibrium. The term equilibrium is used in a similar sense as by
Solomon and Corbit (1974) and indicates that people’s levels of SWB as well as the frequency of positive
and negative life events fluctuate over time, but they do so around a stable baseline – the equilibrium.
Both equilibriums differ between individuals and are at least partly predicted by stable personality
traits. Specifically, Headey and Wearing (1989, 1992) predict that high levels of SWB are predicted by
high levels of extraversion and low levels of neuroticism—which is indeed one of the most robust findings
in SWB research (DeNeve & Cooper, 1998; Steel, Schmidt, & Shultz, 2008). Dynamic-equilibrium theory
therefore deviates from previous theoretical accounts in that it does not assume that all people experience,
on average, hedonic neutrality but posits that (a) the average level of SWB is positive and (b) there are
individual differences in SWB.
Dynamic-equilibrium theory further assumes that people differ in their typical patterns of life
events because life events are not completely random (i.e., exogenous), but at least partly driven by
personality characteristics (i.e., endogenous). Specifically, Headey and Wearing propose that high
extraversion is associated with experiencing more positive events, high neuroticism is associated with
experiencing more negative events, and high openness to experiences is associated with experiencing both
more positive and more negative events, relative to low levels on these three traits.
Personality therefore stabilizes levels of SWB through two pathways: through its direct impact on
people’s disposition to experience low or high SWB and through its indirect impact on what kind of life
events people experience. Headey and Wearing further predict that life events do not change people’s
levels of SWB per se but only if they deviate from the normal equilibrium of life events. For example, a
positive event should not have much impact on a person’s SWB who experiences positive events all the
time, but it should lead to a temporary improvement in SWB in a person who rarely experiences positive
events. Over time, however, people adapt even to these kinds of changes because their personality pulls
both their SWB and the frequency of events back to their respective equilibrium levels (Headey &
Wearing, 1992).
Dynamic-equilibrium theory differs from previous theories in three important aspects. First, this
theory allows and explains individual differences in both SWB and stimuli (here: life events). Second, it
drops the notion of a neutral baseline to which people revert. Finally, it includes personality as a major
driver of individual differences and adaptation. Headey and Wearing (1989) provided preliminary support
for their theory in a longitudinal study, but as we will see below, Headey (2008) later revised this theory
substantially to account for divergent empirical findings.
The Happiness Set Point
Despite their differences, the common notion of the theories discussed up to this point is that one’s
level of SWB always returns to some kind of baseline or equilibrium. To date, this baseline is usually
referred to as set point, a term suggested by Lykken and Tellegen (1996). Using twin data, Lykken and
Tellegen (1996) estimated that the stable component of SWB is 80% heritable. Although this seems like a
strikingly high estimate, it is important to keep in mind that this estimate refers to the heritability of the
stable component of SWB only. Lykken and Tellegen (1996) do in fact acknowledge that SWB can be and
should be expected to be highly volatile across time. Nevertheless, their conclusions centered on the high
heritability of SWB, and this paper was typically cited in this context.
In the same study, Lykken and Tellegen (1996) also found that the individual level of SWB was
better predicted by the twin’s level of SWB than by the individual’s sociodemographic characteristics,
leading them to the conclusion that the effects of life circumstances on SWB are negligible and that
individual differences in SWB are primarily determined by genetic factors. Although they were not able to
test this assumption in their study, Lykken and Tellegen (1996) assumed that how happy one can be
depends on one’s happiness set point, which they assumed to be heritable and stable across time. This term
was quickly adopted by others to describe theories of SWB that assumed that people adapt to any changes
in life circumstances.
Shifts in Adaptation Level versus Desensitization
Frederick and Loewenstein (1999) defined hedonic adaptation as “processes that attenuate the
long-term emotional or hedonic impact of favorable and unfavorable circumstances” (Frederick &
Loewenstein, 1999, p. 302). To describe and explain hedonic adaptation, they revived the mathematical
definition of the adaptation level (Helson, 1948, 1964) and extended it in two critical ways. Similar to
adaptation-level theory, they maintained that how a stimulus is perceived depends on past stimuli. For
example, a stimulus is perceived as positive if its valence is above the current adaptation level, which is
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defined as a function of past stimuli. However, unlike to Helson, they acknowledged that the intensity and
valence of these past stimuli can fade over time through adaptation. The adaptation level AL at time t is
then defined as
ALt = a Xt–1 + (1 – a) ALt–1 (equation 16.3, p. 306)
where Xt–1 is the valence of the previous stimulus, ALt–1 is the adaptation level at the previous occasion,
and a is the rate of adaptation. If there is no adaptation (a = 0), the current stimulus is compared to the
mean of all previous stimuli, as originally proposed by Helson (1948). Conversely, if the rate of adaptation
is maximal (a = 1), the current stimulus is compared to the previous stimulus only and past stimuli are
irrelevant. In addition, Frederick and Loewenstein (1999) proposed that the hedonic experience does not
just depend on the contrast between the current stimulus and the adaptation level, but that some stimuli are
inherently good or bad and therefore always trigger a positive or negative hedonic response, regardless of
past experiences. For example, starting a new romantic relationship with someone always feels good,
regardless of how many romantic relationships one might have had before. Formally, the hedonic response
(or, in their terms, experienced utility) u to a stimulus X at time t is defined as a function of the contrast
between the current stimulus Xt and the adaptation level ALt and a constant c that reflects the inherent
valence of the stimulus:
ut = c + f(Xt – ALt) (p. 307)
This function follows an S-shaped curve (Kahneman & Tversky, 1979) (see solid blue curve in
Figure 3A). The valence of the stimulus is depicted on the x-axis, with X = 0 corresponding to the
adaptation level, and the hedonic response is depicted on the y-axis. As the curve illustrates, the hedonic
response is particularly sensitive to differences in stimuli that are close to the adaptation level (steep slope
in the middle of the plot) and less sensitive to differences in stimuli that are far from the adaptation level
(flat slope at both ends of the plot). This phenomenon is known as declining marginal utility in economics
(Kahneman & Thaler, 2006; Kahneman & Tversky, 1979). The constant c is reflected in the intercept of the
curve (i.e., the hedonic response at X = 0): An inherently good stimulus with a positive value for c will
elicit a positive response even if its valence is exactly at the adaptation level.
Figure 3. Illustrations of the S-shaped hedonic response curve according and changes in the hedonic
response due to shifting adaptation levels (Panel A), and desensitization and sensitization (Panel B),
as proposed by Frederick and Loewenstein (1999).
This formalization of the relationship between a stimulus and the hedonic response allowed
Frederick and Loewenstein (1999) to distinguish two different processes of hedonic adaptation. First, the
hedonic response to a stimulus may become weaker because of shifting adaptation levels, as proposed by
Helson (1948), Parducci (1968, 1995), and Brickman and Campbell (1971). The shift in adaptation level
would result in an upward or downward shift of the hedonic response curve. For example, a downward shift
of the hedonic response curve would imply that a stimulus that once elicited a positive hedonic response
now elicits a neutral or even negative response (see black dashed line in Figure 3A). Second, the sensitivity
towards differences between stimuli may weaken. This desensitization would result in a flatter slope of the
hedonic response curve, and positive stimuli would elicit an attenuated hedonic response (dotted line in
Figure 3B). The slope of the hedonic response curve could also change in the opposite direction, leading to
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sensitization towards stimuli (dashed line in Figure 3B).
Note that there is some disagreement in the literature on whether both of these processes reflect
hedonic adaptation. Frederick and Loewenstein (1999) clearly think so, as they define hedonic adaptation
as “anything that reduces the subjective intensity of a given stimulus” (p. 303). Others, however, explicitly
draw a line between adaptation (i.e., shifts in adaptation levels) and desensitization (Armenta, Bao,
Lyubomirsky, & Sheldon, 2014; Cummins, 2014).
Summary
Classical theories on adaptation converge on the assumption that external factors do not have
lasting effects on SWB because people adapt to any changes in external factors. Hence, although observed
SWB can fluctuate, the average long-term level of SWB is stable. This long-term level of SWB has been
termed adaptation level (Brickman & Campbell, 1971; Helson, 1948, 1964), dynamic equilibrium (Headey
& Wearing, 1989, 1992; Solomon & Corbit, 1974), and set point (Lykken & Tellegen, 1996), which is the
term that we will use for the remainder of the chapter.
These basic assumptions lead to the following testable hypotheses. (1) Because the set point is
genetically determined, SWB should be highly heritable and be correlated more strongly with other
heritable factors such as personality than with presumably non-heritable external factors such as life
circumstances. (2) Because the set point cannot change, SWB should be highly stable across time both in
terms of rank-order stability and in terms of mean-level stability. (3) Because people always return to their
set points, external stimuli such as major life events or interventions should have only short-term effects on
SWB. In the following section, we review the empirical evidence for these hypotheses.
Empirical Evidence
Early studies of hedonic adaptation often relied on non-experimental cross-sectional data from
small samples. In this section, we first explain why hypotheses about adaptation cannot be tested
adequately with these kinds of studies, but only with studies using longitudinal studies. We then review
studies examining (a) the stability and heritability of SWB, (b) the association between changes in life
circumstances (e.g., life events) and changes in SWB, and (c) the effectiveness of interventions aimed at
improving individual SWB (for a similar comprehensive review, see Tay & Kuykendall, 2013).
Why Adaptation Should Be Studied Longitudinally
Before longitudinal data became widely available, researchers of hedonic adaptation usually relied
on two types of indirect evidence. The first type of evidence came from cross-sectional correlational studies
that tried to explain individual differences in SWB with various correlates. Such studies usually found that
personality accounted for a substantially higher proportion of the variance in SWB than life circumstances
such as marital status, employment status, or income, leading many to conclude that one’s level of SWB is
primarily determined by one’s personality and that the effects of life circumstances are negligible (for
reviews, see Argyle, 1999; Diener, Suh, Lucas, & Smith, 1999; Myers & Diener, 1995). Such a conclusion,
however, is problematic for several reasons. First, cross-sectional correlations only refer to momentary
rank-order differences between individuals. It is impossible to infer whether these differences are stable
across time and whether changes in the predictors (e.g., changes in life circumstances) are associated with
changes in SWB within individuals. Second, weak correlation coefficients may conceal practically
significant effects. For example, the correlation between individual income and individual SWB is typically
around .30 (Howell & Howell, 2008), which means that income explains about 9 % of individual
differences in SWB. This seemingly low figure conceals that the SWB differences between poor and rich
individuals can be substantial (Lucas & Schimmack, 2009). Finally, equating personality influences with
stability is misleading because personality can change across the entire life span (Roberts, Walton, &
Viechtbauer, 2006; Specht et al., 2014).
The second type of evidence came from studies that compared the average level of SWB among
groups that differed in whether they had recently experienced major changes in their lives. A citation
classic in this category is the study by Brickman, Coates, and Janoff-Bulman (1978). In this study, a group
of lottery winners and a group of paraplegic accident victims were compared to a control group that had not
recently gone through any major life changes. Lottery winners were not significantly happier than
participants in a control group. Accident victims were unhappier than both lottery winners and control
participants, but happier than “might have been expected” (Brickman et al., 1978, p. 921) because their
average happiness level was above the neutral midpoint of the scale. Together, these findings seemed to
suggest that major life events do not have any lasting effects on SWB, presumably because people adapt
quickly and completely. However, this interpretation is false: (a) The sample size was rather small (N = 22
for lottery winners, N = 29 for accident victims, and N = 22 for controls), so weak effects were unlikely to
be detected. (b) Despite these relatively small sample sizes, the mean-level difference between accident
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victims and controls was statistically significant and quite strong in terms of effect size (d = 0.75; Diener,
Lucas, & Scollon, 2006). (c) The study was cross-sectional, making it impossible to judge whether these
differences were caused by the event or had existed before.
The latter point reveals a more general problem with these types of cross-sectional studies. Meanlevel
differences in SWB after life events only allow conclusions about the impact of a life event if there
were no differences in SWB before the events. Without data on SWB collected before the event, this
assumption cannot be tested. In fact, multiple studies suggest that life events are not completely random but
at least partially associated with person characteristics such as personality (Headey & Wearing, 1989;
Kandler, Bleidorn, Riemann, Angleitner, & Spinath, 2012; Lüdtke, Roberts, Trautwein, & Nagy, 2011;
Magnus, Diener, Fujita, & Pavot, 1993) and even the previous level of SWB (Luhmann, Lucas, Eid, &
Diener, 2013).
In conclusion, non-experimental cross-sectional studies are inconclusive with respect to whether,
when, how fast, and for whom hedonic adaptation occurs. For this reason, the following review of the
empirical evidence focuses on longitudinal studies.
Heritability and Stability of SWB
A central hypothesis in set-point theory is that SWB fluctuates around a stable, genetically
determined set point (Headey & Wearing, 1992; Lykken & Tellegen, 1996). This hypothesis implies that
long-term levels of SWB should be highly heritable and stable across time. To probe to what extent these
predictions are confirmed in empirical studies, we first review the current state of research on the
heritability and then discuss studies on the rank-order and mean-level stability of SWB.
Heritability of SWB. Heritability refers to the proportion of the total variance of a variable (i.e.,
phenotype) that is accounted for by genetic factors and is usually estimated using behavioral genetic
designs such as twin studies (Plomin, DeFries, Craig, & McGuffin, 2003). Across studies, the average
heritability of SWB is between .30 and .40 (Bartels, 2015; Nes & Røysamb, 2016; Røysamb & Nes, this
volume), which is slightly below the heritability of personality which is estimated to be between .40 and
.50 (Bleidorn, Kandler, & Caspi, 2014).
However, some studies also found much lower and much higher heritability estimates. Specifically,
heritability estimates of momentary affect are typically lower (between .00 and .35; Eid, Riemann,
Angleitner, & Borkenau, 2003; Riemann, Angleitner, Borkenau, & Eid, 1998) and heritability estimates of
the long-term SWB are typically considerably higher (between .70 and .95; Lykken & Tellegen, 1996; Nes
et al., 2013; Nes, Røysamb, Tambs, Harris, & Reichborn-Kjennerud, 2006). Hence, fluctuations in day-today
affect appear to be mainly driven by environmental factors whereas long-term SWB appears to be
mainly influenced by genetic factors. The latter conclusion is consistent with set-point theory (Lykken &
Tellegen, 1996).
Several caveats of these studies need to be considered when interpreting these findings (Røysamb,
Nes, & Vittersø, 2014). First, estimates of heritability depend on a number of assumptions which are often
not met in reality. One of these assumptions is that the parents of twins are matched randomly. However,
several studies found evidence for assortative mating with regard to SWB such that spouses often have
similar levels of SWB (e.g., Hoppmann, Gerstorf, Willis, & Schaie, 2011; Schimmack & Lucas, 2010).
Moreover, estimates of heritability depend not only on the amount of genetic variance, but also on the
amount of environmental variance in a population. Estimates of heritability are higher in environmentally
homogeneous populations (e.g., populations with similar sociodemographic background) than in
environmentally heterogeneous populations (e.g., different cultures), even if the effect of the genetic factors
is identical (Røysamb et al., 2014).
Second, even if one accepts that the heritability of long-term SWB is as high as suggested by some
of the studies mentioned above, this figure does not automatically imply that we have genetically fixed set
points to which we return no matter the circumstances. As Røysamb et al. (2014) discuss in more detail,
even monozygotic twin pairs tend to differ from one another in their levels of SWB, suggesting that it may
be more appropriate to think of the set point in terms of a range of values rather than a single fixed value.
Life events or interventions may cause individuals to experience permanent levels of SWB that are above
or below the middle of the set point range. Adaptation, defined as a return to baseline, is therefore not
inevitable. Furthermore, gene expression changes over the life course, which means that different genes
might be effective in different circumstances and different life stages (Nes, 2010; Røysamb et al., 2014).
Even if the set point is genetically determined, it is not necessarily fixed to a specific value that remains the
same across the entire life span (Røysamb et al., 2014).
In sum, behavioral genetics studies suggest that SWB is at least partly influenced by genetic
factors, particularly if long-term SWB is considered, but these findings do not imply that hedonic
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adaptation is quick and inevitable.
Rank-order stability of SWB. Under the assumption that individual differences in SWB exist
(Headey & Wearing, 1989, 1992; Lykken & Tellegen, 1996), a further implication of the classical
adaptation theories is that the rank order of individuals should be stable across time. If Person A has a
higher set-point for SWB than Person B, then Person A should have higher observed levels of SWB than
Person B at any given point in time. This rank-order stability is estimated by the retest correlation between
observed SWB scores measured at Time 1 and observed SWB scores measured at Time 2. For most
psychological variables, the retest correlation is highest when the time lag between the two time points is
minimal and decays with increasing time lags until it reaches an asymptote that is typically above 0 (Fraley
& Roberts, 2005). The decay reflects the cumulative effect of changing environmental factors and the
asymptote reflects the effect of the stable component of the variable. Thus, the higher the asymptote, the
stronger is the influence of stable factors such as a genetically determined set point.
The rank order of SWB has been examined in multiple studies, with retest intervals ranging from a
few days to 10+ years. Meta-analyses of these studies found that both life satisfaction and affect follow the
pattern described above, with retest correlations decreasing over time until they reach an asymptote of
about r = .30 (Anusic & Schimmack, 2015; Schimmack & Oishi, 2005). For comparison, the asymptote for
retest correlations of personality is about r = .60 (Anusic & Schimmack, 2015), indicating that SWB is
substantially less stable than personality.
If more than two waves of data are available, the relative contribution of stable and changing
factors can also be estimated with structural equation models for longitudinal data (Cole, Martin, & Steiger,
2005; Kenny & Zautra, 1995). Such models allow decomposing the total variance into components that are
due to stable influences, occasion-specific (momentary) influences, and in some models, autoregressive
influences (i.e., effect of the SWB at the previous occasion on SWB at the following occasion). Using data
from representative panel studies, Lucas and Schimmack (2009) estimated that stable, autoregressive, and
occasion-specific influences each account for roughly one third of the total variance in life satisfaction. In
their meta-analysis, Anusic and Schimmack (2015) estimated that stable influences account for 42 % of the
variance in affect and 52 % of the variance in life satisfaction (see also Eid & Diener, 2004, for similar
estimates), compared to 83 % for personality.
In sum, these findings suggest that while a substantial proportion of the variance of SWB is due to
stable factors, which is consistent with the existence of a set point, SWB is also at least as much influenced
by changing environmental factors. Similar to the findings on heritability, these studies do not provide any
information on whether hedonic adaptation is indeed quick and inevitable. To examine whether people
return to a stable baseline regardless of the external circumstances, stability and change in mean levels of
SWB must be examined.
Mean-level stability of SWB. If the assumption that people always return to their stable set points
is correct, mean levels of SWB should be stable over longer time spans both on the population level and
within persons. With regard to the population level, a frequent finding is that national levels of SWB
change very little across long time spans, despite changes in sociodemographic circumstances such as
national income levels (Easterlin, 1974). However, this pattern has primarily been replicated in countries
that experienced relative stability in the past decades. By contrast, both upward and downward changes in
national levels of SWB can be found in countries that experienced significant economic and political
changes (e.g. Russia, Greece) (Veenhoven, 2014), indicating that stable population levels of SWB are not
universal.
Furthermore, classical theories of adaptation imply that SWB does not change across the life span.
Again, however, the empirical evidence does not fully support this assumption. Both affective well-being
(Charles, Reynolds, & Gatz, 2001; Lachman, Teshale, & Agrigoroaei, 2015) and life satisfaction (Baird,
Lucas, & Donnellan, 2010; Mroczek & Spiro, 2005; Steptoe, Deaton, & Stone, 2015; Stone, Schwartz,
Broderick, & Deaton, 2010) change over the life span (for a recent review on the development of SWB
across the life span, see Luhmann, 2017) and decline in the last years of life, suggesting that people do not
adapt fully to the cognitive and health-related decline that characterizes this period in life (Gerstorf et al.,
2008; Kunzmann, Richter, & Schmukle, 2013).
Together, these studies show that average levels of SWB can change over time, which is hard to
reconcile with the classical theories of adaptation. Note, however, that studies on average mean-level
change offer only limited insights into changes occurring within persons. In fact, moderately changing
mean levels of SWB can reflect (a) that most people experience moderate changes in their individual SWB
or (b) that most people do not experience any changes in their individual SWB but a significant minority
experience strong changes. Similarly, stable mean levels of SWB can reflect (a) that individuals do not
experience any changes in SWB or (b) that the number of individuals experiencing increases and decreases
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are roughly similar. Empirical studies considering interindividual differences in intraindividual change
suggest that both explanations are somewhat true. Using longitudinal data on life satisfaction spanning up
to several decades, several authors found that while most people experience stable levels of life satisfaction,
a substantial minority of about 20 % experience significant and lasting increases or decreases over the
multi-year period (Fujita & Diener, 2005; Headey, 2008b; Headey, Muffels, & Wagner, 2014).
Changes in SWB after Life Events
If hedonic adaptation is indeed inevitable, even major life events should not have any lasting
impact on SWB. Two general methodological approaches to study the relationship between life events and
SWB can be distinguished. In the first approach, the frequency of life events experienced over a specified
time frame is measured, often with life events checklists such as the Social Readjustment Scale (Holmes &
Rahe, 1967). For example, Headey and Wearing (1989) measured the frequency of positive and negative
events experienced over a period of two years and found that these frequency measures predicted life
satisfaction and positive affect over and above extraversion, neuroticism, and openness to experiences. In
addition, the frequency of negative events, but not the frequency of positive events, predicted negative
affect over and above extraversion, neuroticism, and openness to experiences.
In another study using the frequency approach, Suh, Diener, and Fujita (1996) regressed
momentary SWB on the number of positive and negative self-reported life events experienced in specific
time periods over the past four years. They found that positive affect was significantly predicted by the
number positive life events, negative affect was significantly predicted by the number of negative life
events, and life satisfaction was significantly predicted by both positive and negative life events. Crucially,
they also found that when the time point of the occurrence of these events was considered, only events
experienced in the past three months, but not more temporally distal events, were significantly associated
with SWB. Suh et al. saw their findings as consistent with Headey and Wearing’s (1992) dynamic
equilibrium theory and concluded that “it seems to be the case that SWB does react to external changes in
life but returns to a stable individual baseline rather quickly. More specifically, the results of our study
indicate that the impact of most life events on SWB diminishes in less than 3 months” (Suh et al., 1996, p.
1098). This conclusion, however, is unwarranted given the study design. In fact, this study did not provide
any evidence on whether people return to the set point at all nor on how quickly they do because the
intraindividual trajectories of SWB were not examined. Instead, this study merely shows that individual
differences in SWB cannot be predicted by the frequency of life events that occurred more than three
months ago. An additional limitation of the frequency approach is that life events that differ quantitatively
(in terms of their hedonic impact) and qualitatively (in terms of, for example, life domain or subjectivity)
are lumped together in one single score, which means that the impact of specific events on SWB cannot be
examined.
This limitation is resolved in the second methodological approach that focuses on single specific
events. Many studies focusing on single specific events compared individuals having experienced the event
with individuals not having experienced the event (e.g., Brickman et al., 1978, for more examples, see the
comprehensive review by Frederick & Loewenstein, 1999). However, as discussed above, these types of
cross-sectional group comparisons do not allow conclusions about the impact of life events nor about the
process of adaptation.
The strongest approach to testing whether and how adaptation to external stimuli unfolds over time
is therefore to examine intraindividual changes in SWB after life events using prospective longitudinal data.
Data are prospective if SWB is measured both before and after the event. Only prospective data permit
testing whether and how quickly people return to their pre-event (i.e., baseline) levels of SWB after the
event. Prospective studies on life events are hard to conduct because they require repeated measures of
SWB (to allow examining intraindividual change) from large samples (to ensure that a significant number
of people experienced the event of interest) tracked over long time periods (to ensure that both pre-event
and post-event data on SWB are available). Fortunately, such studies have increasingly become available.
For example, the German Socioeconomic Panel Study (SOEP) provides longitudinal data on life
satisfaction collected annually since 1984 in a large sample representative of the German population
(Wagner, Frick, & Schupp, 2007). This study and similar ones from other countries have been used
extensively to study changes in SWB in the context of family-related events such as marriage (Lucas,
Clark, Georgellis, & Diener, 2003), childbirth (Dyrdal & Lucas, 2013; Galatzer-Levy, Mazursky, Mancini,
& Bonanno, 2011), divorce (Lucas, 2005), widowhood (Lucas et al., 2003; Specht, Egloff, & Schmukle,
2011); work-related events such as unemployment (Galatzer-Levy, Bonanno, & Mancini, 2010; Lucas,
Clark, Georgellis, & Diener, 2004; Luhmann & Eid, 2009), job transitions (Lindfors, Hultell, Rudman, &
Gustavsson, 2014), and retirement (Pinquart & Schindler, 2007); and health-related events such as the
onset of disability (Lucas, 2007b; Pagán-Rodríguez, 2012). Reviews (Lucas, 2007a; Yap, Anusic, & Lucas,
2014) and meta-analyses (Luhmann, Hofmann, Eid, & Lucas, 2012) of this literature indicate that whether
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and how fast people adapt to life events depends on the specific event. On average, people appear to adapt
within a few years to marriage, childbirth, and divorce. Adaptation can also be found for widowhood and
bereavement, although the rate of adaptation is slower than for divorce. For some events, however, changes
in SWB are more permanent, for example after unemployment and disability. These results suggest that
while adaptation is common, it is neither automatic nor inevitable, particularly after negative life events.
Despite their many strengths, a number of limitations of these studies need to be considered. First,
most studies only included individuals who had experienced a particular event but did not include a control
group comprised of individuals who had not experienced this event. A control group is necessary to (a)
examine selection effects (e.g., people high in SWB are more likely to get married; Mastekaasa, 1992) and
(b) to disentangle event-induced changes from age-related normative changes. Ideally, individuals would
be randomly assigned to the event group and the control group, but with few exceptions (e.g., Galiani,
Gertler, & Undurraga, 2015), such a random assignment is ethically impossible. An alternative is
propensity score matching (Thoemmes & Kim, 2011), a statistical procedure that can be used to a create
control group that is matched with the event group. A study by Yap, Anusic, and Lucas (2012)
demonstrates how the conclusions can change by including a control group: While they replicated previous
findings that people return to their pre-event levels after marriage, they also observed similar declining
levels of life satisfaction in a matched control group, suggesting that while marriage did not change
people’s general downward trajectory of life satisfaction normal in this age period, it did give people a
boost that kept them permanently above the life satisfaction level of the unmarried control group.
Second, SWB was measured annually in most studies, which limits the possibility to detect shortterm
variations in SWB. As the meta-analysis on life events and SWB (Luhmann, Hofmann, et al., 2012)
shows, variability in SWB is particularly high in the first months after a significant event, suggesting that
the first weeks and months after an event may be particularly volatile. We return to this issue below when
we discuss open questions and future directions.
Third, most studies focused on life satisfaction. Only few longitudinal studies on changes in
affective well-being are available. Distinguishing between these components is important because life
satisfaction and affective well-being are differentially affected by life events (e.g., Knabe, Rätzel, Schöb, &
Weimann, 2010) and change at different rates and, for childbirth, even in different directions (Luhmann,
Hofmann, et al., 2012).
Finally, both the reaction to life events and the rate of adaptation to life events vary substantially
among individuals experiencing the same events and among different kinds of events. An active field of
research is to identify the person-related and event-related moderators that account for this variability. We
return to this issue below.
In sum, studies on life events and SWB paint a complicated picture: adaptation seems to occur
frequently for most events and most individuals, but not for everyone.
Effectiveness of SWB Interventions
Lykken and Tellegen (1996) famously stated that “it may be that trying to be happier is as futile as
trying to be taller” (Lykken & Tellegen, 1996, p. 189). Unfazed by this quote, a number of researchers and
practitioners have developed interventions that attempt just that: to improve people’s levels of SWB. This
volume includes several chapters reviewing these interventions (Layous; Ehlers, Salerno, Aguiñaga, &
McAuley; Stone & Parks; Chow; Holman, Johnson, & O’Conner, this volume), so we will not reiterate
them here. For our purposes, it suffices to say that the empirical evidence available to date suggests that
SWB can be improved through interventions (Bolier et al., 2013; Davis et al., 2016; Sin & Lyubomirsky,
2009) and through intentional activities (Layous, this volume), a finding that is inconsistent with classical
theories of adaptation.
Summary
In this section, we reviewed studies on heritability and stability of SWB as well as studies on the
impact of external stimuli (life events and interventions) on SWB. Together, these studies indicate that
SWB is relatively stable but nonetheless changeable. For most people, their SWB fluctuates around a stable
baseline that is partly heritable, which is consistent with classical theories of adaptation. However, a
significant minority experiences major increases or decreases in their SWB. In sum, adaptation is a real
phenomenon, but it may not be as pervasive and inevitable as classical theories suggest.
Recent Theoretical Developments and Current Debates
In reaction to the empirical evidence, Headey (2008b) announced a paradigm shift in this field of
research and called for a revision of the classical set-point theories. A comprehensive theory of SWB, he
states, needs to be able to explain both stability (which classical theories do) and change (which classical
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theories fail to do) (Headey, 2010). In this section, we review current theoretical developments that attempt
to achieve this goal.
Revisions to Set-Point Theory
Diener et al. (2006) and Headey (Headey, 2008b, 2010) independently argued that the classical
theories of adaptation need to be fundamentally revised. Diener and colleagues (2006) proposed five major
revisions. (1) Set points are not neutral, as assumed in some classical theories (Brickman & Campbell,
1971; Helson, 1948, 1964; Solomon & Corbit, 1974), but are, on average, positive (Diener & Diener, 1996;
Diener, Kanazawa, Suh, & Oishi, 2015). (2) People differ in their individual set points, and these
differences can partly be explained by heritable factors such as personality. (3) People may have multiple
set points for different components of SWB. (4) SWB can change, for example through the experience of
major life events. (5) People differ in the degree to which they adapt, and these individual differences can
partly be explained by differences in personality and coping strategies.
Headey was compelled to substantially revise his dynamic equilibrium theory (Headey & Wearing,
1989, 1992) which, in its original form, was able to explain stability but not lasting changes in SWB. Recall
that a central proposition of the original dynamic equilibrium theory was that people’s levels of
extraversion, neuroticism, and openness to experience predispose them to a characteristic pattern of life
events. SWB changes not when particular life events occur, but when the pattern of life events deviates
from the characteristic pattern of life events. For example, one would experience significant increases in
SWB not by experiencing positive events per se, but by experiencing more positive events than normal.
In his revision of this theory, Headey (2008b) suggests that such positive and negative deviations
from the normal pattern of life events are more likely for individuals with certain combinations of
personality traits. Specifically, he proposes that people who are at the same time high in extraversion and
low in neuroticism have an ‘upside risk’ of experiencing more positive events than normal and thereby
have a greater chance of experiencing lasting increases in SWB. Conversely, he proposes that people who
are at the same time low in extraversion and high in neuroticism have a ‘downside risk’ of experiencing
more negative events than normal and thereby have a greater risk of experiencing lasting decreases in
SWB (for preliminary empirical support, see Headey, 2008b). Moving even further away from the original
theory, Headey later proposed that lasting changes in SWB can also be due to people’s behavioral choices,
for example, who they choose as a partner, how they balance work and leisure, their degree of social
participation and volunteering, how physically active and healthy they live, and other life goals (Headey,
2008a; Headey, Muffels, & Wagner, 2010; Headey et al., 2014). This notion presents quite a dramatic shift
away from the classical theories that all converged on the idea that people cannot influence their SWB
because it is mainly determined by personality and by automatic adaptation processes.
Subjective Well-Being Homeostasis
In a stark contrast to Headey’s revised set-point theory, Cummins (2010, 2014) continues to
emphasize the role of automatic processes. In his theory of SWB homeostasis, Cummins posits that SWB,
particularly mood, can be described as a homeostatic system. He specifically focuses on what he calls
homeostatically protected mood (HPMood), a biologically determined and normally distributed
predisposition for certain positive mood states that influences people’s personality (not vice versa),
cognitive processes, and other aspects of SWB such as life satisfaction. HPMood is controlled by
homeostatic processes that keep HPMood within a narrow range, the so-called set point range. These
processes comprise internal processes such as automatic habituation and cognitive mechanisms such as
reframing and meaning making, and external resources such as wealth and social relationships.
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Figure 4. The SWB homeostasis system. The plot illustrates the association between HPMood (y-axis)
and the strength of challenges to the homeostatic system (x-axis). HPMood normally (a) fluctuates
within the set point range (here: between 70 and 80). For moderate challenges (b), HPMood moves to
the thresholds of this range, but a strong homeostatic defense keeps it within the set point range.
Only for very strong challenges (c) can the threshold be passed (homeostasis failure). Figure adapted
from Cummins (2010, p. 5).
The homeostatic system is illustrated in Figure 4. The more the current level of HPMood
approaches the thresholds of the set-point range, the harder the system works to keep HPMood within this
range. Under ordinary circumstances, the system will therefore ensure that people’s fluctuating HPMood
stays within their individual set point range, which explains why most people experience stable levels of
SWB over long time spans. Under extraordinary circumstances, however, homeostasis may fail and the
threshold may be exceeded, leading to significant changes in HPMood and, consequently, other aspects of
SWB. Cummins attributes findings on long-term changes in SWB after life events to this kind of
homeostasis failure. Over time, however, the homeostatic system regains control and HPMood returns to
the set point range. Importantly, the assumption that the set point is biologically determined does not imply
that it is fixed to a specific value or a specific range across the entire life span. Rather, just like other
physiological parameters, the biological foundations of the set point for HPMood can change with age.
In their attempts to reconcile the empirical evidence with a theory of SWB, Headey and Cummins
appear to come to widely divergent conclusions. At a second glance, however, it becomes clear that these
theories explain different phenomena. Although Headey typically refers to SWB, his empirical studies
focus on the cognitive component of SWB, that is, life satisfaction. Cummins, by contrast, explicitly
focuses on the affective component of SWB, that is, HPMood. Although correlated, cognitive and affective
well-being are structurally and functionally distinct (Lucas, Diener, & Suh, 1996; Luhmann, Hawkley, Eid,
& Cacioppo, 2012; Luhmann & Hennecke, 2017), and show divergent change trajectories over the life span
(Stone et al., 2010) and after life events (Luhmann, Hofmann, et al., 2012). It is therefore plausible to
assume that the mechanisms that account for stability and change are not the same for affective and
cognitive well-being, and that distinct theories might be necessary to explain stability and change in these
components of SWB.
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Hedonic Adaptation Prevention Model
Anyone invested in improving people’s SWB inevitably wonders how adaptation to negative
events can be expedited and how adaptation to positive events can be prevented or at least slowed down.
These questions can only be answered if the mechanisms and moderators of adaptation are well understood.
This is the goal of the Hedonic Adaptation Prevention Model (Lyubomirsky, 2011; Sheldon, Boehm, &
Lyubomirsky, 2013), a comprehensive model that distinguishes two central paths to adaptation and
identifies several moderators that affect the rate of adaptation. Similar to other presentations of this model,
we focus on adaptation to positive changes, but it should be noted that the model applies to adaptation to
negative changes as well.
Figure 5. The Hedonic Adaptation Prevention Model. The effect of positive changes on SWB is
attenuated by two separate processes. First, the emotional reaction to positive events associated with
the positive change becomes weaker over time. Second, aspiration levels increase. Variety and
appreciation of the positive events may moderate these pathways. Figure adapted from Armenta et
al. (2014, p. 64).
The full model is shown in Figure 5. A first basic assumption in this model is that major positive
changes (e.g., getting a pay raise) are associated with a number of positive events (e.g., dinner in a fancy
restaurant, an extended shopping spree, or simply being able to pay a bill on time). These positive events
have a positive effect on SWB, but this effect can wear off over time (hedonic adaptation). Two separate
pathways account for adaptation. First, positive events elicit positive emotions which in turn improve
SWB, but both the link between events and emotions and between emotions and SWB become weaker over
time. For example, a dinner in a fancy restaurant feels less and less special over time and is therefore
associated with less joy and pleasure the more often one experiences it. Furthermore, even if one continues
to experience positive emotions at the dinner, these positive emotions are less likely to have a lasting effect
on SWB because they become part of the normal pattern. This pathway resembles what Headey and
Wearing (1989, 1992) described as a dynamic equilibrium for events and SWB and what Frederick and
Loewenstein (1999) described as desensitiziation.
Second, experiencing a large number of positive events may raise people’s aspiration levels. The
higher the aspiration level, the more likely people experience a discrepancy between their current and their
desired state, which is experienced as negative affect and low life satisfaction (Carver & Scheier, 1990;
Michalos, 1985). For example, the quality of food and service experienced in the fancy restaurant might
soon feel normal, and restaurants that do not meet the new high standard are more likely to give cause for
negative affect and dissatisfaction. This pathway is similar to a shift in hedonic adaptation levels proposed
in some classical theories (Brickman & Campbell, 1971; Frederick & Loewenstein, 1999; Helson, 1948,
1964).
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In addition to describing the main processes of adaptation, the Hedonic Adaptation Prevention
Model identifies two central moderators of these processes. The first, variety, relates to how similar or
variable the positive events are. Specifically, the more variable the positive events, the slower the aspiration
level rises and the longer these events elicit positive emotions which in turn improve SWB. A person who
spends the new disposable income only on restaurant dinners will adapt to the pay raise more quickly than
a person who spends the disposable income on a variety of different things and experiences. The second
moderator, appreciation, relates to how much people appreciate the positive events. The more one is able
to savor a nice dinner at a fancy restaurant, the slower one’s aspiration level rises. A short-term
longitudinal study found initial support for the two pathways and the moderating effects of variety and
appreciation (Sheldon & Lyubomirsky, 2012).
The identification of these moderators has important practical implications. While changing
aspiration levels and dampening emotional reactions may be automatic, both variety and appreciation can
be controlled and might therefore be effective tools to speed up adaptation to negative events and slow
down adaptation to positive events.
Open Questions and Future Directions
We conclude this chapter by addressing four main open questions that need to be addressed in
future research: (1) How should we study adaptation? (2) How does adaptation work? (3) Why is
adaptation faster after some events than after others? (4) Why do some people adapt more quickly than
others?
How Should We Study Adaptation?
As we discussed repeatedly in this chapter, studies on adaptation are subject to a number of
methodological challenges. Here, we outline how an ideal study would deal with these challenges (for an
in-depth discussion, see Luhmann, Orth, Specht, Kandler, & Lucas, 2014).
The ideal study on adaptation should be longitudinal and focus on some discrete stimulus or event
that affects people’s SWB. SWB should be measured multiple times both before and after the event to be
able to determine whether and when people’s SWB returns to baseline after the event. Multiple
measurement occasions are necessary to model nonlinear change trajectories. The intervals between
measurement occasions are neither too short nor too long. If the intervals between occasions are too long,
short-term changes may be overlooked (Uglanova & Staudinger, 2013). Conversely, if the intervals
between occasions are too short and the study therefore ends too soon, it may not be possible to determine
whether adaptation continues beyond the last occasion. The ideal study furthermore includes a matched
control groups to disentangle changes caused by adaptation from normative changes and regression-to-themean
effects. Finally, the ideal study includes different generations, age groups, time periods, and cultures
to evaluate to what extent the observed adaptation patterns are influenced by age, cohort, period, and
cultural effects. Of course, no single study can meet all of these requirements. This field of research
therefore exemplifies the importance of cumulative research where multiple imperfect studies eventually
lead to a comprehensive picture of the frequency and time course of adaptation.
How Does Adaptation Work?
The theories discussed in this chapter propose a great variety of mechanisms of adaptation, ranging
from automatic, physiologically driven processes (Brickman & Campbell, 1971; Cummins, 2010, 2014;
Lykken & Tellegen, 1996; Solomon & Corbit, 1974) to stable personality differences pulling people back
to a set point (Headey & Wearing, 1992) to cognitive changes (Frederick & Loewenstein, 1999; Helson,
1948, 1964; Lyubomirsky, 2011; Sheldon et al., 2013) to behavioral choices (Headey et al., 2014). As
mentioned above, empirical studies suggest that the processes underlying adaptation may be distinct for
affective and cognitive well-being, with automatic, homeostatic processes more likely underlying
adaptation of affective well-being and cognitive processes more likely underlying adaptation of cognitive
well-being.
One frequently mentioned cognitive process is that the exposure to external stimuli leads to a
change in the standard of reference against which new stimuli are judged (Brickman & Campbell, 1971;
Frederick & Loewenstein, 1999; Helson, 1948, 1964; Lyubomirsky, 2011; Parducci, 1995; Sheldon et al.,
2013). How exactly this standard of reference is formed in the first place and changes over time is still
poorly understood. In particular, it is an open question to what extent the standard of reference used for
SWB judgments is determined by past experiences (temporal comparison; Helson, 1948, 1964; Parducci,
1995), by comparisons with other people (social comparison; Diener & Fujita, 1997; Festinger, 1954), or by
our ideal and/or ought selves (self-discrepancy; Higgins, 1987). A better understanding of how people
judge their SWB is necessary to fully understand how and why these judgments change over time.
Another cognitive mechanism is proposed in the AREA model by Wilson and Gilbert (2008).
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Wilson and Gilbert assume that events only impact SWB if people focus their attention on the event
(Attend), which is a prerequisite for an emotional reaction to the event ( React). Attention to an event
dissipates over time and thereby reduces the emotional reactions to the event. Furthermore, as a
consequence of attending and reacting to the event, people may be able to make sense of and assign
meaning to the event (Explain). Once an event is completely explained, no further attention is paid to the
event and the event cannot further impact SWB (Adapt). In their review of the literature, Wilson and
Gilbert (2008) provide empirical evidence for each link in this cognitive process, but to our knowledge, this
model has not yet been tested in its entirety.
Tasks for future research include (a) conducting rigorous tests of specific mechanisms of
adaptation, (b) distinguishing between affective and cognitive well-being when studying mechanisms of
adaptation, and (c) integrating these empirical findings into a comprehensive theory of hedonic adaptation.
Why is Adaptation Faster After Some Events Than Others?
The average reaction and rate of adaptation vary substantially across different life events. Based on
the notion that negative stimuli often have stronger effects than positive stimuli (Baumeister, Bratslavsky,
Finkenauer, & Vohs, 2001; Cacioppo, Gardner, & Berntson, 1999), a common assumption is that people
adapt faster to positive events than to negative events (Cummins, 2010; Larsen & Prizmic, 2008). Indeed,
those events that appear to have lasting effects on SWB (e.g., unemployment, widowhood, disability)
would be considered undesirable by most people. It is easy, however, to come up with counterexamples.
Adaptation is quick after divorce (Luhmann, Hofmann, et al., 2012), another rather undesirable life event.
Moreover, some studies find lasting positive changes in SWB after events such as cosmetic surgery
(Margraf, Meyer, & Lavallee, 2015) and moving to a greener urban area (Alcock, White, Wheeler,
Fleming, & Depledge, 2014). Furthermore, people might differ in how they evaluate the valence of a
particular event. For example, the death of the spouse might have some positive connotations if it marks
the end of enduring suffering. Finally, as suggested by opponent-process theory (Solomon & Corbit, 1974),
even events with a clear positive or negative valence may lead to opposite hedonic reactions due to
opponent processes. Thus, valence alone cannot explain the differences among life events.
Obviously, events differ on many other aspects besides valence. Easterlin (2005) speculated that
people only adapt to changes in economic factors such as income, but not to changes in non-economic
factors such as relationships. Wilson and Gilbert (2008) suggested that event characteristics such as
novelty, surprise, variability, and certainty about the nature of the event might account for differences
among events because they affect how well people can make sense of the event. A one-week laboratory
study on chocolate consumptions found that people savored eating chocolate more if they abstained from
eating chocolate for an entire week than if they did not abstain (Quoidbach & Dunn, 2013), suggesting that
adaptation to positive stimuli may be slowed down by deliberately reducing the exposure to these stimuli.
Some events may also be associated with specific consequences that mediate the impact of the event on
SWB. For example, the transition to parenthood is associated with a host of positive and negative changes
which jointly determine how people react and adapt to this event (Nelson, Kushlev, English, Dunn, &
Lyubomirsky, 2013). Exposure to a missile attack has been associated with increased avoidance motivation
which in turn was associated with lowered levels of SWB (Van Dijk, Seger-Guttmann, & Heller, 2013). In
sum, an open question for future research is which characteristics of events influence the rate of adaptation
and why.
Why Do Some People Adapt More Quickly Than Others?
The rate of adaptation does not just differ across different events, but also among individuals
experiencing the same event (Bonanno, 2004; Diener et al., 2006; Lucas, 2007a). Two general approaches
to explore these individual differences can be distinguished. The first approach focuses on specific
variables that are theoretically derived and examines whether these variables affect the reaction and rate of
adaptation to life events. Most studies in this domain have focused on the Big Five personality traits,
particularly extraversion and neuroticism. Results are mixed. Some studies found positive results. For
example, adaptation to unemployment appears to be more negative for people high in conscientiousness
(Boyce, Wood, & Brown, 2010; Hahn, Specht, Gottschling, & Spinath, 2015) and low in extraversion
(Hahn et al., 2015); the reaction to spousal bereavement was found to be stronger for people low in
extraversion and openness (Pai & Carr, 2010), adaptation to disability was found to be faster for people
high in agreeableness (Boyce & Wood, 2011), and fluctuations in income were more strongly associated
with life satisfaction among people high in neuroticism (Soto & Luhmann, 2013). However, these effects
cannot be consistently replicated in independent samples (Anusic, Yap, & Lucas, 2014; Yap et al., 2012)
and can vary even within samples, for instance between men and women (Boyce, Wood, & Ferguson,
2016). Other studies focused on more narrow personality variables and found protective effects of sense of
mastery (Marum, Clench-Aas, Nes, & Raanaas, 2014), humility (Krause, Pargament, Hill, & Ironson,
235
2016), perceived control (Infurna et al., 2016), and external locus of control (Specht et al., 2011), but no
significant moderating effects for perceived social support (Anusic & Lucas, 2014; Marum et al., 2014).
The second approach is more exploratory and descriptive and aims at identifying different patterns
of adaptation using latent growth mixture modeling (Muthén, 2006). This statistical procedure allows
identifying and describing different latent classes that differ in their average SWB trajectories. Latent
growth mixture models have been applied to various life events, including marriage (Mancini, Bonanno, &
Clark, 2011), childbirth (Galatzer-Levy et al., 2011), divorce (Mancini et al., 2011; Perrig-Chiello,
Hutchison, & Morselli, 2015), bereavement (Infurna & Luthar, 2017b; Mancini et al., 2011; Spahni,
Morselli, Perrig-Chiello, & Bennett, 2015), unemployment (Galatzer-Levy et al., 2010), and retirement
(Pinquart & Schindler, 2007). A typical result of these kinds of studies is that three to four latent classes
can be distinguished, one of which is characterized by a relatively flat trajectory. This so-called resilient
trajectory is often (but not always, e.g., Infurna & Luthar, 2017a) found to be the most common trajectory;
however, latent growth mixture models are highly complex methods with strict assumptions that are often
not met and, if violated, can lead to an overestimation of the prevalence of the resilient trajectory (Infurna &
Luthar, 2016).
In sum, more research is needed to identify variables that explain individual differences in reaction
and adaptation consistently across samples and methods.
Conclusion
After assuming for decades that SWB is highly stable, the field has recently made a significant turn
towards recognizing that lasting changes in SWB are possible. This turn was at first entirely data-driven,
ignited by the availability of large-scale longitudinal studies that track people’s SWB over long periods of
time. Theory is catching up, as several promising models that explain both stability and change have been
proposed in the past years. These models provide useful directions for future research, which is necessary to
arrive at a complete understanding of the mechanisms and boundary conditions of hedonic adaptation.
Acknowledgments
Preparation of this chapter was supported by grant #57313 awarded to Maike Luhmann by the Happiness
& Well-Being Project, a joint program by the St. Louis University and the Templeton Foundation. We
thank Nick Augustat and Vincent Beermann for their assistance in the literature search and formatting of
this manuscript.
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Well-Being, Self-Actualization, and Fundamental Motives: An
Evolutionary Perspective
By Douglas T. Kenrick & Jaimie Arona Krems, Arizona State University
Citation
Kenrick, D. T., & Krems, J. A. (2018). Well-being, self-actualization, and fundamental motives: An
evolutionary perspective. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake
City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
From an evolutionary perspective, feelings of subjective well-being signal progress toward adaptive goals.
We discuss life history theory and fundamental motives—integrating ideas from social psychology and
evolutionary biology that offer a potentially useful perspective on subjective well-being. We discuss some
preliminary research from this perspective, and outline implications for future research. In doing so, we
suggest that different people may have very different notions of which behavior evokes feelings of
subjective well-being, linked to their particular life history features (e.g., age, sex, relationship status). This
perspective also suggests predictable variations in what evokes subjective well-being across geography and
cultures. We end by addressing avenues for future work taking an evolutionary perspective to
understanding happiness and satisfaction—as well as the positive side of unhappiness and dissatisfaction.
Keywords: Fundamental motives, Evolutionary psychology, Well-being, Self-actualization, Life-
history.
At first blush, the pursuit of happiness and well-being sounds like a good thing. Indeed it accounts,
in good part, not only for the popular appeal of positive psychology, but also for a multi-million dollar
industry of personal fulfillment workshops, books, and magazines. It could be argued that goods and
experiences designed to enhance feelings of well-being account for the major portion of non-essential
consumer goods, as well as a large part of how people spend their leisure time.
From an evolutionary perspective, though, natural selection has not shaped human beings to feel a
blissful sense of well-being (Buss, 2000; Keltner, Haidt, & Shiota, 2006; Nesse, 2004; Nesse & Ellsworth,
2009). Although psychologists and laypeople may lament the hedonic treadmill (Brickman & Campbell,
1971; Diener, Lucas, & Scollon, 2006), which implies that achieving any form of emotional satisfaction is
soon followed by boredom and dissatisfaction, this treadmill might not be such a bad thing on an ultimate,
functional view. Once one of our ancestors had achieved an important goal, such as catching several fish,
or building a hut, redirecting his or her attention to other unmet goals, such as the annoying leak in the
hut’s roof or a potential threat to a romantic relationship, would have made more sense than smugly resting
content.
This is not to say that people are designed to desire unhappiness and agitated dissatisfaction rather
than happiness and contentment (or vice versa). It is also not to say that people consciously wish to hop
back on the hedonic treadmill as soon as they finish the next lap. However, we would argue that
unhappiness and dissatisfaction serve purposes equally as important as those served by happiness and
satisfaction. Without those negative affective states, our ancestors would not have survived, or, more
importantly from the perspective of their descendants (i.e., us), reproduced.
In this chapter, we consider subjective well-being in light of two related sets of ideas at the
interface of evolutionary biology and social psychology: Life history theory and fundamental motives.
From an evolutionary life history perspective, what constitutes “subjective well-being” would be expected
to vary in predictable ways across people and across contexts. Those variations would have made adaptive
sense in ancestral environments (though not always in modern society). After laying out some of the
theoretical rationale for our particular evolutionary life-history approach to well-being, we describe our
own previous work examining how evolved fundamental motives are connected in somewhat different
ways to subjective well-being (versus eudaimonic and hedonic wellbeing, or self-actualization), and present
some unanswered questions generated by an evolutionary approach to subjective well-being. We suggest
that: (1) feelings of subjective well-being may signal progress toward adaptive goals; (2) there is no
monolithic, one-size-fits-all path to achieving subjective well-being; rather, what evokes a sense of wellbeing
may differ sensibly for different people, and for the same person at different times, such that (3) life
history features (e.g., age, sex, relationship status, presence of children) may be able to predict what
behavior people believe will give rise to their feelings of subjective well-being; (4) ecological and cultural
factors might also affect what goal pursuits give rise to subjective well-being, such that there may be
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predictable and sensible variations in what causes subjective well-being across geographical and national
boundaries; and, finally, (5) because unhappiness and dissatisfaction are also of adaptive importance for
humans, it is important to understand the positive side of negative affect as well.
Fundamental Motives and Life-History Theory
A number of classical approaches to human motivation have attempted to explain human choices,
goals, and motivations in “domain general” terms. One example of a domain-general theory is the idea that
organisms are programmed to “seek reward,” another is that people are designed to “maximize benefits and
minimize costs.” These approaches aggregate all positive outcomes into a single coin, as in economic
approaches that ask how many dollars a given good or service is worth. Such domain-general approaches
have the advantage of parsimony. A domain-specific approach, however, assumes that different rules apply
to some categories of reward or benefit than to others (for example, that the cognitive and affective systems
dealing with costs and benefits for friendship are different from those dealing with amorous affairs or
relationships between parents and children; Kenrick & Griskevicius, 2013).
Domain-specific approaches have arisen partly because domain-general models have faced a
number of problems in accounting for human behavior. Harlow’s (1953) classic work, for example,
demonstrated that attachment in primates could not be explained through secondary association with food
rewards, but seemed to be associated instead with physical contact, and that attachment might be linked to a
separate desire for what he called “contact comfort.” In a related vein, Garcia and Koelling (1967)
demonstrated that the simple rules of classical conditioning did not apply cleanly to learning to avoid
nausea-inducing foods (which occurred after a single trial, and despite several hours passing between the
presentation of the taste and the consequence of nausea). Wilcoxon, Dragoin, and Kral (1972) suggested
that the mechanisms for conditioning nausea were even more complex, differing in species-specific ways
that made evolutionary sense. They found that rats, which use taste and smell cues to find food in their
natural environments, easily condition nausea to taste, whereas quail, which typically eat seeds that they
locate by vision rather than smell or taste, more easily condition nausea to visual cues than to taste cues.
Furthermore, neuroscientific findings, such as Sperry and Gazzaniga’s work with split brain patients (e.g.,
Gazzaniga, 2005), further suggested that the brain is not one monolithic processing unit, but consists of
multiple systems processing different types of information in parallel. In a review of diverse bodies of
evidence from comparative psychology, neuroscience, and learning, Sherry and Schacter (1987) built a
strong case that animals, including humans, required multiple distinct memory systems for different, and
sometimes incompatible types of learning (a bird learns its species single song at a critical early age, and
then never modifies it, but it may learn hundreds of places where it has stored food, which need to be
selectively remembered and forgotten depending on whether they have been used up, and it learns to avoid
poisonous foods throughout life, without ever forgetting them). All of these lines of evidence have led
many behavioral scientists to adopt a modular, or domain-specific, approach, which presumes that affective
and cognitive processes are not monolithic, but composed of multiple parallel sub-systems that function in
ways that are often specific to the particular types of threats and opportunities that each species confronts in
its typical social and physical environment.
Abraham Maslow (1943), a student of Harry Harlow, suggested an influential early model of
multiple human motivations. He postulated that motivations could be arranged into a “hierarchy of
prepotency,” and the hierarchical pyramid of human motivations has remained a highly appealing and
robust cultural meme (Ackerman, Nocera, & Bargh, 2010; Diener, 2000; Kenrick, Griskevicius, Neuberg,
& Schaller, 2010; Krems, Kenrick, & Neel, 2017; Peterson, Park, & Seligman, 2005). Maslow postulated
that distinct motivational systems unfold developmentally. Maslow also assumed that only once people had
achieved lower-tier physiological and social goals, such as affiliation, and esteem, they could they move on
to individual pursuits of self-actualization, or fully realizing one’s own unique potential. Maslow (1943)
used the term “self-actualization” to refer to: “the desire to become more and more what one is, to become
everything that one is capable of becoming” (p. 382). He wrote:
Even if all these [physiological, safety, and social] needs are satisfied, we may still often (if not
always) expect that a new discontent and restlessness will soon develop, unless the individual is doing what
he is fitted for. A musician must make music, an artist must paint, a poet must write, if he is to be ultimately
happy. What a man can be, he must be. This need we may call self-actualization. (1943, pp. 382-383).
Maslow’s (1943) model of motivation was a precursor of modern evolutionary perspectives on
domain specificity. However, modern developments have suggested a number of renovations to his
pyramid (Kenrick et al., 2010). For example, Maslow paid very little attention to reproductive motivations,
sweeping sexual desire in with basic physiological needs such as hunger and thirst.
Figure 1 presents a graphic illustration of a “renovated” hierarchy of needs (Kenrick et al., 2010).
Our model begins with the premise that, over the course of evolutionary time, humans have faced recurrent,
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distinct challenges. Successfully surviving, reproducing, and rearing reproductively viable offspring
required humans to meet these wide-ranging problems. Furthermore, because humans are a highly social
species, many of these challenges were social in nature, such as competing for and acquiring friends as well
as mates. We thus suggested a hierarchy of “fundamental human motives” that distinguishes between basic
physiological needs, self-protection, disease avoidance, affiliation, status, mate acquisition, mate retention,
and parenting (Kenrick, et al., 2010). Each of these motivational systems evolved in response to distinct
selection pressures. The particular decision-rules that would make adaptive sense when interacting with
one’s offspring would not be the same as those that make adaptive sense when dealing with friends, and
still different sets of decision-rules would be adaptive in dealing with romantic partners, strangers, and so
on (Kenrick & Griskevicius, 2013). Once a given motivational system is activated, it would direct attention
to different stimuli, weight those different stimuli in different ways, and produce distinct outputs, in ways
that would be likely to best avoid particular threats and approach particular opportunities.
One notable feature of the revised pyramid is that, unlike Maslow’s model, self-actualization is not
conceptualized as the pinnacle human motivation. From an evolutionary perspective, it is unlikely that our
ancestors would have evolved to solve the problems of protecting themselves from harm, acquiring friends,
and winning respect, only to go off on one’s own to play music and contemplate philosophical questions,
per se. It makes sense that such noble pursuits are easier for those who do not have to grapple with hunger
and physical danger, but from an evolutionary perspective, it seems likely that artistic and intellectual
creativity are not end in themselves but actually ways of winning respect and acquiring mates
(Griskevicius, Cialdini, & Kenrick, 2006; Miller, 2000; Krems et al., 2017). On this view, seeking a sense
of self-actualization is not a separate adaptive pursuit in and of itself, then, but a means of achieving other
adaptive goals. Likewise, subjective well-being would, on this view, be viewed not as a separate goal in
itself, but as a signal of adaptive progress toward functional goals.
Figure 1. Maslow’s (1943) pyramid of human motivation (left) and Kenrick et al.’s (2010) revised
pyramid of human motivation (right).
This renovation—and the general approach to thinking about happiness, self-actualization, and
well-being—is based on ideas from evolutionary life history theory (e.g., Stearns, 1992). Life history
theory is based on the general premise that all animals, including humans, must continually make decisions
involving economic trade-offs (e.g., Stearns, 1992). All living organisms, even the healthiest, wealthiest,
and most resourceful human beings, have limited resources of time and energy. At any moment, those
resources need to be allocated to one of several mutually exclusive tasks: developing and maintaining one’s
own body (including developing one’s brain), attracting mates, or parenting. Biologists refer to these tasks
as somatic effort, mating effort, and parenting effort. Whereas some animals invest very little effort in
parenting (e.g., many amphibians and fish lay hundreds of eggs, and do not care for them afterwards),
other species invest a great deal in parenting effort (e.g., elephants do not reach sexual maturity for well
over a decade, and then produce a very small number of offspring in which they invest a great deal of
energy for years). Compared to most other mammalian species -- and indeed most other living species --
humans are very slow-developing, not reaching sexual maturity for well over a decade after birth and
investing heavily in very few offspring.
This typical human life history trajectory has implications for how and when we pursue the various
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fundamental motives over the lifespan. On this view, a calorie devoted to pursuing one of these goals (e.g.,
seeking mates) is a calorie that cannot be invested in pursuing another (e.g., caring for one’s children).
Moreover, we must invest in growing our bodies before we can invest in finding a mate, and we must, of
course, successfully find a mate before we can invest in our own offspring. Allocating these finite resources
over the life span—and doing so in ways that make sense given one’s environmental surroundings—can
enhance one’s fitness. Whereas all humans are relatively slow developing—compared to many other
mammals, which can become sexually mature in several months and begin having large litters of offspring
early in life—there are individual differences within any species, humans included. We consider some of
these differences below.
Sex differences. One important difference in life history is linked to biological sex. Humans are
like other mammals in that females have a very high obligatory investment (gestation and lactation for
several years; Trivers, 1972). This, in turn, leads to a sex difference in desires for number of mates (males
benefit more from additional mates), as well as other myriad other features—not all of which are directly
linked to mating. For example, men have relatively high standards for long-term relationships, as do
women. However, when compared to women, men have relatively lower standards for short-term, lowcommitment
relationships (Kenrick, Sadalla, Groth, & Trost, 1990). Men and women also select mates
using somewhat different criteria (Li & Kenrick, 2006). Females prefer high-status males, and often choose
older males who have had a chance to gain social position, whereas males prefer women with features
indicating high fertility (e.g., Kenrick & Keefe, 1992). Humans are also unlike most other mammals in that
the male often does make a very high indirect investment (provision of resources for developing offspring;
Geary, 2000; Trivers, 1972). As a consequence, men are, compared to other mammalian males, more
selective in choosing longer-term mates.
Ecological influences. Different ecological factors—such as the availability and predictability of
resources, the prevalence of external mortality threats (e.g., violence), pathogen prevalence, and sex ratios
—are known to affect how an organism allocates its finite resources across the lifespan (Durante,
Griskevicius, Simpson, Cantu, & Tybur, 2012; Ellis, Figueredo, Brumbach, & Schlomer, 2009;
Griskevicius et al., 2011). For example, a number of researchers have found evidence that harsh and
unpredictable environments are associated with relatively “fast” strategies in human beings: earlier puberty,
earlier reproduction, emphasis on immediate rewards, more children, and less investment in any particular
child (e.g., Griskevicius, Tybur, Delton, & Robertson, 2011; Pollet, Nelissen, & Nettle, 2007). Although
people often moralize about such “fast” behavior, this calibration to the environment may have been
adaptive, allowing humans to reap all-important fitness rewards in harsh and unpredictable environments
(e.g., Ellis et al., 2009; Griskevicius et al., 2011; Williams, Sng, & Neuberg, 2016).
Implications of an Evolutionary Life History Perspective for the Subjective Well-being
Subjective well-being(s). Taking an evolutionary perspective means asking what functional,
fitness-relevant outcomes feelings of subjective well-being might generate. On our view, feelings of
subjective well-being might signal progress toward adaptive goals. Thus, from a general evolutionary
perspective, feelings of subjective well-being ought to be systematically calibrated to one’s fitness. That is,
I should feel subjective well-being when I am generally experiencing success in enhancing my fitness, and
not when I am experiencing failure.
However, humans are unlikely to have a general, all-purpose fitness calibration mechanism in our
brains (e.g., Barrett & Kurzban, 2006). Instead, we are likely to have a number of separate “systems” that
gauge success in particular domains that correspond to the recurrent challenges and opportunities our
ancestors faced. Considering the set of fundamental motives we discussed earlier, this might mean that we
gauge success separately for satisfying nonsocial physiological needs, protecting ourselves from physical
attacks, making and keeping friends, winning respect in our social groups, acquiring mates, keeping mates,
and successfully caring for our offspring and other relatives (Kenrick & Griskevicius, 2013; Kenrick,
Sundie, & Kurzban, 2008).
One implication of this is that people might have domain-specific subjective well-being s. For
example, a hedge fund wunderkind who achieved riches by working day and night during his 20s might,
once he reached his early thirties, lament not having a wife and kids. His financial successes might have
garnered him status and esteem, which might have evoked feelings of subjective well-being at the time, but
perhaps only in the status domain. By continuing to focus all of his finite time and energy on achieving
financial success, he would be unable to spend the necessary time and energy to acquire a mate and start a
family. Hence, his sense of subjective well-being regarding status achievements might be overshadowed
by his deficits in the mating and kin care domains. Getting back on the hedonic treadmill to erase these
deficits via pursuing a wife and having children would serve his reproductive fitness more than continuing
to relish his wealth and status achievements.
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Thus, the very same behavior (i.e., working overtime to achieve financial success) could constitute
success in one fundamental motive domain, but failure in another. As a consequence, at any one time, a
person might feel subjective well-being in one domain, but not in others. This notion of multiple, domainspecific
subjective well-beings is somewhat consistent with Diener’s (2000) assertion that subjective wellbeing
is composed of several separable components, including satisfactions with various important domains
(e.g., work, family life). This raises questions about how humans might aggregate across different types of
well-being in various functional domains when reporting their general, global sense of subjective wellbeing.
We return to this question later in the chapter.
Different outcomes evoke feelings of subjective well-being as a function of life history
features. In a related vein, we would also expect well-being to be differently linked to each of the goal
systems at different ages, and in different contexts, depending on which evolved fundamental motives are
currently salient. That is, we would expect that there are important individual differences in which
fundamental goals (e.g., seeking status, pursuing mates, caring for kin) are chronically active. Different
goals are likely to be differentially weighted depending on one’s gender and other life history features, such
as age, relationship status, and whether or not a person has (young and dependent) children. Some
preliminary support for that assumption comes from recent work by Neel, Kenrick, White, and Neuberg
(2016), who found, for example, that a mate-seeking motivation decreased with age, whereas kin care
increased among parents, especially those with younger children. This, too, is likely to have important
implications for which behavior generates feelings of subjective well-being across individuals.
Thus, achieving success in the domain that is most salient for a person at a particular phase of life
history should generate the greatest feelings of subjective well-being. For example, as in the example of the
successful hedge fund investor, well-being for a young adult male might be primarily linked to achieving
status and esteem. And at that point in his life, caring for a child might actually serve to decrease feelings
of subjective well-being. This is consistent with research by Diener and Fujita (1995), who found that
having resources in domains related to one’s salient goals (e.g., having social skills for people who want to
network, having physical attractiveness for people who want to find mates) is a better predictor of
happiness than resources unrelated to one’s salient goals. Similarly, people feel better on those days when
they make progress toward goals they highly value (Oishi, Diener, Suh, & Lucas, 1999).
Further, we can use typical life history trajectories to make informed guesses about what outcomes
might evoke feelings of subjective well-being in people, as a function of their ages and sex (and other life
history features). For example, caring for a young child might be especially likely to evoke feelings of
subjective well-being for somewhat older people who are in stable romantic relationships, whereas this
same behavior might be less likely to evoke feelings of subjective well-being for younger people, or those
lacking stable romantic partnerships. Similarly, we noted earlier that there tend to be differential levels of
mating versus parental investment in males and females, such that men tend to be generally higher in mateseeking
motivation, women tend to be generally higher in kin care motivation. Successfully pursuing mates
might be more likely to evoke feelings of subjective well-being among young men than among young
women, and caring for a young child might be more likely to evoke feelings of subjective well-being
among older women than among older men.
A recent series of studies provides preliminary support for the predictive value of life history
features as determinants of psychological well-being (Krems et al., 2017). We assessed which fundamental
motives were most strongly reflected in the behavior that people believed would garner them feelings of
subjective well-being (as well as other types of well-being). We also linked such assessments to people’s
life history features (such as age, sex, and parental status). Participants first read descriptions of several
different types of well-being, broadly defined: subjective well-being, eudaimonic well-being (meaning in
life), hedonic wellbeing (attaining pleasure and avoiding pain), and self-actualization (realizing fully one’s
own, unique potential). After reading one of these descriptions, participants were asked what they would
be doing if they were achieving each of these types of well-being (for subjective well-being, for example,
what would you be doing if you were maximizing the extent to which your life, work, health, and social
relationships are desirable, enjoyable, and valuable). Later, they asked to view their answers (e.g., “You
said that, if you were achieving subjective well-being at this point in your life, you would be doing…”);
people then rated the extent to which each of the fundamental motives (self-protection, disease avoidance,
affiliation, status-seeking, mate acquisition, mate retention, and kin care) was reflected in their responses,
using a 7-point Likert-scale (1 = not at all, 7 = very much). These same people gave information about
their life history features (age, sex, relationship status, presence of children, and children’s ages).
Table 1 provides illustrative examples of what people reported they would be doing if they were
achieving subjective well-being.
Overall, affiliation was the fundamental motive most strongly reflected in the behavior people
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believed would garner them subjective well-being (see Figure 2). By contrast, status-seeking was the
motive most strongly reflected for self-actualization. For hedonic well-being, on the other hand, selfprotection
and mate acquisition were relatively more strongly reflected. For eudaimonic well-being,
affiliation and kin care were strongly reflected.
Thus, laypeople view well-being as primarily linked to spending time with friends, and also view
the profile of motives associated with subjective wellbeing as somewhat distinct from other types of
happiness-linked outcomes (e.g., self-actualization).
Table 1
Samples of Lay Perceptions of Behaviors that Would Achieve Subjective Well-Being
Example Sex Age
“Writing, I'd have a book or two published with a few short stories; I'm in shape now but want to
be a bit more muscular; I'd be able to go out and socialize more, I love food and craft beer.”
Male 28
“Trying my best to have good hearted friends, spending time with close family, working out
and dieting, trying to climb the financial, educational, and work related ladders to the top”
Female 25
“Spending more time with my kids” Female 29
“Rescuing animals while taking care of my family” Female 43
“Probably sitting in the backyard at a friend’s house around a fire” Male 41
“Out to lunch with close friends.” Female 44
“My life has a whole would include work to keep my brain working, my relationships to keep
me grounded and to feel that I am wanted and needed and loved. And try to stay healthy and
life a long and happy life.”
Male 69
“Meeting new people, finding a job that actually means something, creating something” Male 56
These findings also supported the prediction that there would be systematic linkages between
people’s fundamental motives, their life history features (age, sex, relationship status, presence of children),
and their expectations of what pursuits would lead to subjective well-being. For example, people’s
emphasis on affiliation changed across the lifespan; both younger and older people reported that affiliation
was linked more to their anticipated subjective well-being than did middle-aged people. This is consistent
with what we know about socialization across the lifespan; whereas friends are highly important in youth
and young adulthood, romantic partners and one’s own children take up more time and energy later on.
When children are no longer highly-dependent, however, affiliative relationships again become prioritized
(e.g., Neel et al., 2016). Thus, age is one life history feature that affects what motives people believe they
are pursuing when they pursue subjective well-being.
Second, men reported that both status-seeking and mate acquisition were more strongly linked to
their anticipated subjective well-being than did women. This demonstrates that gender also affects what
motives people believe will maximize subjective well-being, and that these pursuits might truly reflect
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progress towards those different goals that are adaptive for different people, again as based on their
particular combination of life history features (e.g., Kenrick et al., 2010; Krems et al., 2017; Miller, 2000).
Figure 2. The extent to which men and women report each motive as being reflected in their pursuit
of subjective well-being. Error bars represent 95% standard errors. Data taken from Krems et al.
(2017).
Third, people’s relationship status (i.e., whether they were single or partnered) affected the extent
to which various fundamental motives were reflected in their anticipated subjective well-being, again in
ways consistent with predictions made from an evolutionary life history perspective. For example, single
men (but not women) linked seeking status and acquiring mates more strongly to their anticipated
subjective well-being than partnered men did, whereas partnered women (but not men) linked mate
retention and kin care more strongly to their anticipated subjective well-being than single women did.
Fourth, whether or not people had children also affected the extent to which various fundamental motives
were reflected in anticipated subjective well-being, again in ways consistent with an evolutionary life
history perspective. For example, both fathers and mothers linked kin care more strongly to their
anticipated subjective well-being than did men and women without children, respectively.
Taken together, these findings suggest that subjective well-being does not mean the same thing to
different people. What is required to achieve well-being varies for individuals in systematical predictable
ways. That is, subjective well-being looks somewhat different for people as a function of their ages, sexes,
and other life history features. This has implications for how people go about pursuing subjective wellbeing,
as well as for how health professionals and others instruct people to go about achieving this flavor
of happiness. Although it may seem obvious that giving a grandfather and a young single woman the same
advice about how to achieve subjective well-being is likely to make neither happy, it is worth exploring
further how this might be useful for mental health interventions. There may be no one-size-fits-all advice
for achieving this outcome. Our framework suggests that some features might help determine what
subjective well-being might look like for different folks.
Different outcomes evoke feelings of subjective well-being as a function of ecology and
culture. This perspective also leads to the expectation that behaviors evoking subjective well-being might
be systematically different in different environments, as a function of the ecological features of those
environments (e.g., resource availability, pathogen prevalence, sex ratio, local levels of violence).
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Consider a resource-scarce environment characterized by high levels of violence. In this
environment, self-protection is likely to be a chronic priority. Likewise, in an environment characterized by
high pathogen loads (e.g., high infectious disease), disease avoidance is likely to be a chronic priority. Selfprotection
might be more strongly linked to subjective well-being for people living in the violent
environment, whereas disease avoidance might be more strongly linked to subjective well-being for people
living in the high-pathogen environment. Thus, ecological conditions are likely to drive the functional
prioritization of the fundamental motives, meaning that people living in different ecologies might have
different conceptualizations of what constitutes their own subjective well-being.
Because these different motives direct attention, perception, cognition, and behavior in specific,
potentially functional ways, an ecologically-influenced prioritization of some motives over others could
have major implications for predicting what behavior would contribute to feelings of subjective well-being
in different environments. This might help explain why, for example, although people living in
ecologically-developed and relatively wealthy nations are among the happiest (e.g., Diener, Kahneman,
Tov, & Arora, 2010)—likely because their basic needs are met (Tay & Diener, 2011)—there is not a
monotonic relationship between income and reported subjective well-being across cultures (e.g., Diener &
Oishi, 2000) and why, within countries, rich people are only slightly happier than poor people (Diener,
Horwitz, & Emmons, 1985).
Environments characterized by high income inequality are also characterized by higher levels of
violence (e.g., Daly, Wilson, & Vasdev, 2001; Krems & Varnum, 2017; Varnum & Grossmann, 2017; see
also Helliwell et al.’s World Happiness Report, 2016, 2017). Thus, people living in environments with
high income inequality might also relatively prioritize self-protection on average. Likewise, some research
has also asserted that environments with female-biased sex ratios might have more male-male violence, but
that environments with male-biased sex ratios might have more male-female violence (e.g., Krems &
Varnum, 2017), implying that men in the male-biased environments and women in the female-biased
environments might also relatively prioritize self-protection. An implication of this is that some
environments might cause (certain) people to spend their finite time and energy on more “basic”
fundamental motives, meaning that these people cannot spend that time and energy on “higher” motives
such as seeking status, findings mates, and caring for kin. This is consistent with both Inglehart’s (1990)
and Maslow’s (1943) propositions that individuals only pursue self-fulfillment after they have met their
basic material needs.
In environments where meeting these needs requires constant vigilance, then, perhaps selffulfillment
seems like an impossible pursuit. Graham (2017) proposes that income inequality can lead to
inequality in people’s hopes, dreams, and happiness. In essence, she argues that the experience of daily
stresses can inhibit an individual’s ability to plan for the future (because he/she must instead be focused on
getting by day-to-day). This ecologically-necessitated present-focus prevents people from planning for the
future, and, therefore, from pursuing lives filled with pleasure and meaning.
Whereas these and other ecologically-evoked aspects of culture can affect the prioritization of
fundamental motives, there are also aspects of transmitted culture that are likely to do the same. That is, the
value system of any one culture (e.g., which achievements are prioritized) tells its people what is important
(and unimportant); achieving outcomes one’s own culture prioritizes might be especially likely to lead to
feelings of subjective well-being. Because cultures can differ in what they prioritize, this implies that what
gives rise to subjective well-being might also differ across cultures. In more individualistic and capitalistic
cultures, for example, people might link subjective well-being more strongly to achieving status, whereas in
more collectivistic and equalitarian societies, people might link subjective well-being more strongly to
affiliation. This prediction seems consistent with work by Diener and Diener (1995), which showed that
self-esteem was more strongly correlated with life satisfaction in individualistic than collectivistic societies.
Similarly, in more highly religious nations, higher religiosity was more strongly linked to happiness
(Diener, Tay, & Myers, 2011); and in richer countries, which presumably prioritize earning money, those
with higher incomes reported more life satisfaction (Tay, Morrison, & Diener, 2014).
Other Evolutionary Approaches to Well-Being
Several other social scientists have made interesting bridges between evolutionary psychology and
happiness, well-being, and self-actualization (e.g., Buss, 2000; Diener, Kanazawa, Suh & Oishi, 2015;
Grinde, 2002, 2005; Nesse, 2004). These authors have generally shared an assumption that positive affect
/feelings of well-being would be expected to occur when an individual is engaging in behaviors or facing
situations that would likely have enhanced fitness in the ancestral past. Since some situations pose more
threats than opportunities, negative emotions also have a positive side, in motivating avoidance of
situations that would have typically lowered fitness in ancestral fitness (e.g. Nesse, 2004). Diener, Oishi,
and Lucas (2015) go a step further, arguing that a chronically mild positive affect state might itself be
251
adaptive, in that people in a good mood are likely to engage in social and exploratory behaviors that
increase the odds of enhancing fitness. Several authors have also pointed out that an evolutionary approach
leads to a focus on situations as well (certain situations are more likely to pose opportunities, others to pose
threats). Buss (2000) points out, for example, that well-being is likely to be associated with being near
kinship support groups. Humans evolved in small, kin-based groups of about 50 to 150 individuals
(Dunbar, 1993), but live today is massive groups (e.g., the population of New York City is around 8.5
million individuals). Exposure to so many people might not only be daunting, in general, but it might also
affect us in unexpected and negative ways; for example, seeing many physically attractive women can
lower men’s commitments to their existing mateships (Kenrick, Gutierres, & Goldberg, 1989; Kenrick,
Neuberg, Zierk, & Krones, 1994), and can also affect women’s self-concepts, making them feel less
attractive and less happy (Gutierres, Kenrick, & Partch, 1999). Moreover, others have similarly linked
living in modern, anonymous cities can increase depression by removing the social supports associated
with ancestral living conditions (Nesse & Williams, 1994). The life history approach we have presented
here is largely compatible with these other evolutionary approaches, differing mainly in specifying the
different ways in which adaptive threats and opportunities would vary systematically with different life
history phases.
Some Unanswered Questions
As we noted, there is preliminary support for the heuristic value of thinking about psychological
well-being in an evolutionary life history perspective. Nevertheless, most of the research on this topic
remains to be done. We present some findings above, for example, that show U.S. adults perceive a
primary link between the fundamental motive of affiliation and feelings of subjective well-being, and also
that what these adults believe generates feelings of subjective well-being differs in ways, as systematically
predicted by their life history features (Krems et al., 2017). It would be interesting to extend this work to
compare perceptions of subjective well-being across cultures. For instance, future work may wish to
explore how fundamental motives interact with ecological and other cultural predictors of country-level
scores on the national index of subjective well-being (Diener, 2000).
Similarly, the empirical work we discussed presented findings on what people thought they would
be doing if they were achieving self-actualization, or various other types of well-being (Krems et al.,
2017). However, we do not yet know whether there is actually a relationship between anticipated wellbeing
and one’s success at satisfying different fundamental motivations. Perhaps achieving status would
actually lead to a higher sense of subjective well-being than engaging in affiliative behavior would. Further,
perhaps achieving success in parental goals does not actually lead to a sense of eudaimonic well-being.
Indeed, there is a controversy about how parenting is linked to happiness, with some authors suggesting
that parenting is actually linked to unhappiness while others suggest it is linked to meaning in life (e.g.,
Kahneman, Krueger, Schkade, Schwarz, & Stone, 2004; Nelson, Kushlev, English, Dunn, & Lyubomirsky,
2012). Perhaps using behavior-sampling methods might be useful for answering these questions.
Another avenue of work suggested by an evolutionary life-history approach would be to explore
the extent to which there are in fact multiple, domain-specific subjective well-beings linked to different
fundamental goals. Above, we suggested not only that different behavior might evoke feelings of
subjective well-being for different people (e.g., with some prioritizing mate acquisition and others kin
care), but also that a person might have multiple subjective well-beings simultaneously—one for each
fundamental motive. Perhaps it is only when the self-protection and disease avoidance subjective wellbeing
meters are at adequate levels can one pursue “higher” motives, for example. Moreover, this notion
raises the question of how people might aggregate across domain-specific subjective well-beings when
answering typical assessments of their global subjective well-being.
Some existing work might speak to this, suggesting that subjective well-being in some fundamental
motive domains might be of especially high importance. For example, whereas Suh, Diener, and Fujita
(1996) found that the effects of many major life events (e.g., being fired or promoted) on well-being had
waned almost entirely after three months, Winter, Lawton, Casten, & Sando (1999) found that romancelinked
life events (i.e., marriage and widowhood) were still effecting subjective well-being six to eight
months later. Similarly, other work suggests that, whereas people can rapidly adapt to some seemingly
crippling life events rather quickly, other events have potentially longer-lasting effects—and again, these
other events were linked to romance (Frederick & Loewenstein, 1999). This convergence might begin to
suggest that mating motives are highly important for subjective well-being, or at least that events affecting
mating motive-linked outcomes have particularly high and long-lasting impact on subjective well-being.
Or those findings may be linked to the age and parental status of the research participants in the different
studies.
Beyond replicating and extending work taking an evolutionary approach to understanding
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subjective well-being, future work may also wish to take advantage of the unique, generative power of this
approach to understanding subjective well-being (see, e.g., Buss, 2000; Nesse & Ellsworth, 2009). That is,
one of the interesting suggestions of an evolutionary perspective is that negative affect is as adaptive as
positive affect; a person’s unhappiness (or dissatisfaction, etc.) with his station in life can lead him or her
to pursue achievements that garner status and esteem, which can facilitate the acquisition of a desirable
mate, having children, and so on.
One implication of this perspective is that it might reframe the happiness gap discussed by Graham
(2017); she argues that perhaps poor Americans feel less subjective well-being because they are necessarily
more concerned with the day-to-day business of survival rather than making meaning, planning for the
future, and other activities that might typically lead to feelings of subjective well-being. On an evolutionary
view, whereas poor Americans might lack subjective well-being, they are nevertheless engaging in behavior
that, for their environment, may be adaptive. People for whom getting by day-to-day might would be
expected to have different conceptualizations of what behaviors give rise subjective well-being, as
compared to people from more privileged environments. Perhaps feelings of personal safety, for example,
generate phenomenologically similar feelings of subjective well-being for poor people as does pursuing
what might be considered by some to be “higher” motivations does for wealthier people. Ellis and
colleagues (2009) have made similar arguments about the “fast” life history strategies pursued by people
from ecologies characterized by harshness and unpredictability. Whereas middle-class people, such as
most highly educated researchers, frequently make moral judgments about fast strategists’ levels of risktaking,
earlier sexual debuts, and lesser investment across more children, this suite of behavior may be
adaptively calibrated to the environment which evokes it. Pathologizing the lack of subjective well-being
among the American poor may be akin to moralizing how they (ought to) spend their time.
A second implication of pointing out the possible functionality of unhappiness serves to underscore
the fact that the possible upsides of nonclinical levels of dissatisfaction, too, are worthy of study (e.g.,
Buss, 2000). For example, Buss (2000) cites how the negative emotion of jealousy, whereas it might feel
unpleasant, motivates adaptive behavior designed to counter threats to valued mateships (Daly, Wilson, &
Weghorst, 1982). Thus, negative feelings can generate functional outcomes. Nesse (2004), too, argues that
focus on reliving negative status and achieving positive states has left ‘diagonal psychology’ ignored; but
an evolutionary approach would emphasize the adaptive benefits of negative emotions. Further, just as we
argue above that progress toward adaptive goals makes people happy, thwarted progress toward those same
goals makes people unhappy. And just as the prioritization of goals is affected by one’s life history features
(e.g., age, sex, relationship status) and perhaps ecology/culture, what makes people unhappy in functional
ways may similarly vary across cultures in important ways. Identifying what behavior makes different
people happy—or functionally unhappy—and why, on an ultimate level, is an area ripe for future empirical
work. Indeed, what makes someone less happy is not necessarily the same thing that makes that person
unhappy; studying unhappiness and dissatisfaction merely as low scores on happiness and satisfaction
scales might obscure the distinct, important features of negative affect (especially if such scales have no
possible negative scale points for reporting unhappiness but rather start at 0 or 1 to indicate “”no” or “low
happiness”). From an evolutionary point of view, just because unhappiness is less pleasant than happiness,
this does not make it any less adaptive or any less worthy of study.
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Exploring the Associations Between Personality and Subjective
Well-Being
By Richard E. Lucas, Michigan State University
Citation
Lucas, R. E. (2018). Exploring the associations between personality and subjective well-being. In E.
Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
Decades worth of research on subjective well-being provides evidence for the idea that personality plays a
strong role reports of positive affect, negative affect, and life satisfaction. Specifically, this research shows
that subjective well-being, like personality traits themselves, is moderately stable over time and moderately
heritable. In addition, some of the strongest correlates of well-being reports are personality traits like
extraversion and neuroticism. In this chapter, I review evidence for the importance of personality in
explaining subjective well-being, focusing both on the strengths and limitations of existing research and
complexities in the interpretation of the empirical evidence that does exist. Ultimately, research on
personality and well-being can be seen as a model for how research on other predictors of subjective wellbeing
can proceed.
Keywords: Personality, Subjective Well-Being, Stability
Subjective well-being (SWB) reflects a person's overall evaluation of the quality of his or her life as a
whole. Presumably, when constructing life satisfaction judgments, people consider the various events and
circumstances in their lives (e.g., their income, their social relationships, their health, and the various
positive and negative life events that have occurred), weight these circumstances by importance, and then
aggregate to derive an overall evaluation. If this intuitive model of how SWB judgments are made is
correct, then one might expect the objective circumstances in one's life to be the primary determinant of his
or her SWB. Furthermore, people's behaviors are often guided by their beliefs about what external
circumstances will make them happy (Gilbert, 2006). Thus, psychologists and lay people alike often
express surprise about the relatively weak associations between specific external life circumstances and
well-being judgments (e.g., Gilovich & Eibach, 2001; Kahneman, 1999; Schwarz & Strack, 1999).
In contrast to the relatively small associations with life circumstances, decades of research show that
the strongest and most consistent predictors of SWB are typically the stable individual differences that
personality psychologists study (Diener, Suh, Lucas, & Smith, 1999; Lucas & Diener, 2015; Steel,
Schmidt, & Shultz, 2008). For instance, although research typically shows correlations around .20 between
SWB and intuitively appealing predictors like income (R. T. Howell & Howell, 2008; Lucas & Dyrenforth,
2006; Lucas & Schimmack, 2009), correlations with personality traits like extraversion and neuroticism are
often around .40 or .50 (Lucas & Fujita, 2000; Steel et al., 2008).
Indeed, the strong evidence for the stability and heritability of SWB, along with the relatively strong
associations between scores on SWB measures and various personality traits, have led some to suggest that
well-being judgments themselves are trait-like and may even be impervious to lasting effects of changing
external circumstances (Brickman & Campbell, 1971; Headey & Wearing, 1991; Lykken & Tellegen,
1996). Clearly, if SWB were so strongly determined by personality that external circumstances simply do
not matter, then this would have serious implications for research on SWB. Specifically, it would suggest
that the search for external predictors of the construct would ultimately be fruitless. Perhaps more
importantly, it would suggest that striving for improved well-being may be impossible, as personality
processes would inevitably return people to their genetically determined set points. In this chapter, I review
the evidence for the role that personality processes play in SWB, focusing on what we know about the links
between personality and well-being and what this means for our understanding of the role of external
circumstances for SWB.
Evidence for the Importance of Personality
Before addressing the role that personality plays in SWB judgments, it is important to define the
construct itself. As noted above, I start with the idea that SWB reflects a person's overall evaluation of the
quality of life as a whole (see Diener, Lucas, Schimmack, & Helliwell, 2009, for a more detailed
discussion). Researchers who study SWB acknowledge that such evaluations can be assessed in a variety
of ways. For instance, Diener (1984) noted that there are least two ways to evaluate SWB. First, one can
simply ask respondents to think about the features of their lives and to provide an overall rating of their
satisfaction with these conditions. Measures of life satisfaction or domain satisfaction assess this more
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cognitive approach to the evaluation of well-being. Alternatively, if one's life is going well, it is reasonable
to assume that that person would experience frequent positive emotions and infrequent negative emotions;
and thus, it is possible to use respondents' typical levels of affective experience as an indicator of how well
their lives are going (see Busseri & Sadava, 2011; Schimmack, 2008, for a discussion of these multicomponent
models of SWB).
It is also important to note that even for the same component of SWB, there are multiple ways to
obtain an assessment of the underlying construct. For instance, Kahneman and Riis (2005) noted that if we
want to assess the typical level of positive affect that a person experiences, researchers could either ask
respondents to reflect on their lives and report their typical experiences or they could assess these
momentary experiences using more intensive procedures such as ecological momentary assessment (Stone,
Shiffman, & DeVries, 1999) or the day reconstruction method (Kahneman, Krueger, Schkade, Schwarz, &
Stone, 2004). The various components of SWB and even the various measures of the same component can
show differential associations with predictors and outcomes, and thus, it is important to consider when and
why these various measures behave the same or differently. Thus, when possible, I will discuss how
personality differentially relates to different measures.
As reviewed elsewhere (Lucas & Diener, 2008, 2015), there are at least three main lines of evidence
that suggest that personality matters for SWB. First, SWB measures, like personality traits themselves, are
stable over time. Specifically, people exhibit rank-order stability, where those who are relatively happy at
one moment tend to be happier than average when assessed at a later time. Second, SWB is moderately
heritable, which suggests that something inside the person plays a role in the well-being that people report.
And finally (and most directly), SWB measures tend to be moderately strongly correlated with scores on
personality traits. Below I review some of the primary findings for each line of evidence.
The Stability of SWB
The importance of research on the stability of SWB is nicely summarized in a quote from an early
article by Costa, McCrae, and Zonderman (1987). They noted that the evidence for high levels of stability
that they found in their study "[points] out the need for caution in interpreting well-being scores as indices
of the quality of life, because well-being is strongly influenced by enduring characteristics of the
individual" (p. 299). In other words, if we assume that the circumstances of one's life change over time,
then evidence for strong stability means that these changing circumstances have little effect on SWB, and
that something internal to the person must be the primary determinant of individual differences in this
construct.
The article by Costa et al. (1987) is useful in highlighting some of the issues involved when
considering research on the stability of SWB. First, this early study, which used high quality data to
examine the test-retest stability of SWB, clearly shows that responses to SWB measures are stable over a
reasonably long period time. Specifically, in this 10-year longitudinal study, which included a nationally
representative sample of the United States with thousands of participants, the stabilities of positive and
negative affect were .44 and .43, respectively. As Costa et al. (1987) emphasized, these relatively high
stability coefficients contrast with the relatively weak correlations with demographic factors like income or
age. Furthermore, they showed that the correlations are equally strong for those who went through major
life transitions like a change in employment or marital status and those who did not. Thus it appears to
provide strong evidence that SWB judgments are impressively stable over time.
Although the early study by Costa et al. (1987) provides important evidence for the long-term stability
of SWB, there are a number of limitations that would need to be addressed by subsequent research. First,
the study used a simple two-wave design that results in just a single stability coefficient. This single
stability coefficient is difficult to interpret (Fraley & Roberts, 2005; Kenny & Zautra, 1995, 2001): Would
stability coefficients decrease with longer intervals, or do they remain impressively strong even over many
decades? Multi-wave studies can be used to assess the pattern of stability coefficients across varying
intervals, which provides clearer answers to the questions about the role of stable internal factors in
determining SWB.
Second, the study relies solely on global, self-report measures of SWB, and specifically on self-report
measures of the affective components of SWB. This limitation leaves open a number of questions: How
stable are other components, such as life satisfaction; how stable are non-self-report measures of SWB;
how much of the stability is due to the shared method variance that results from the reliance on a single
method or to stability in method factors such as response styles?
Finally, although Costa et al. acknowledge that stability in SWB could either be due to the influence
of personality or to the fact that important life circumstances tend to be stable over time, their methods for
dealing with this ambiguity (which focused on assessing stability separately among people who
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experienced a major life event versus those who did not) were quite limited. Thus, the question of whether
SWB can change after the experience of life events is mainly left unanswered by studies like this. Over the
subsequent decades, answers to these questions became much more clear.
More recent attempts to investigate the stability of well-being measures have led to clearer
conclusions about the degree of stability that exists. Specifically, more recent studies have used longrunning
panel studies or meta-analytic summaries from studies that vary in interval length to derive more
precise estimates of how stability coefficients change with increasingly long intervals and across different
types of measures (see Sheldon & Lucas, 2014, for an overview of issues related to the stability of SWB).
To clarify why these multi-wave studies are necessary, it is useful to discuss the conceptual underpinnings
of one model for analyzing multi-wave data, the Stable Trait-Autoregressive Trait-State (STARTS) model
(Kenny & Zautra, 1995, 2001).
The idea behind the STARTS model is that at any given occasion, there are three types of influences
that could affect responses to a measure. First, there are perfectly stable influences, those that impact
responses in the same way no matter the occasion. These can be considered stable trait influences. Second,
there are completely unstable influences that affect responses at one wave, but are completely independent
from responses at any other wave. These can be considered state influences.1 Finally, it is possible to
identify the influence of characteristics that change systematically over time in an autoregressive manner.
For instance, factors whose influence wanes with increasing time will lead to stronger correlations over
shorter intervals, and weaker correlations over longer intervals. These influences are reflected in an
autoregressive trait component.
Kenny and Zautra (1995) noted that each component implies a different pattern of stability
coefficients over time (also see Fraley & Roberts, 2005). For example, if responses to life satisfaction were
due entirely to the effects of unstable state influences, then responses should be completely uncorrelated
over time. In contrast, if life satisfaction judgments were due entirely to the influence of stable-trait factors,
then stability coefficients would equal one, no matter the interval that was chosen. Finally, if life
satisfaction ratings were due entirely to autoregressive factors, then stability coefficients should decline as
the length of the interval increased. Specifically, these coefficients should show an exponential decline. For
example, if the one-year stability was .75, then the two-year stability would be 0.56 (i.e., ) and the threeyear
stability would be 0.42 (i.e., ).
Of course, if all three sources of variance contribute to a person's score on a well-being measure, then
the pattern of correlations will not fall into one of these three ideal patterns. However, structural equation
modeling techniques can be used to decompose the pattern of correlations and to estimate the amount of
variance accounted for by the three sources. For instance, if a measure of SWB was influenced equally by
transient state influences, autoregressive trait influences, and stable trait influences, then the correlation
between two waves that were very close in time would be .66 (reflecting the fact that one-third of the
variance was completely transient), the correlation between two waves that were very distant would be .33
(reflecting the constant effect of the perfectly stable trait), and the correlation between waves of increasing
intervals would decline in a regular fashion (due to the impact of the slowly changing autoregressive trait;
the precise rate of decline would then depend on the wave-to-wave stability of this autoregressive
component).
Lucas and Donnellan (2007) and Lucas and Donnellan (2012) used these techniques with data from
four different long-running panel studies, including the German SocioEconomic Panel Study, the British
Household Panel Study, and the Household Income and Labour Dynamics in Australia study. Results
showed that approximately one-third of the variance was pure state variance (including measurement
error), one-quarter to one-third of the variance was purely stable trait variance, and approximately one-third
of the variance was moderately stable autoregressive variance. This leads to the expectation that year-toyear
stability will be about .60, stability coefficients will initially decline with increasing length of interval
(e.g., over interval lengths from 2 to 10 years), but that stabilities will eventually asymptote at around .25 to
.30, where they will remain even as interval lengths continue to increase. This pattern of results supports
the idea that there is a core, trait-like aspect to SWB judgments, but that this component accounts for only a
modest percentage of the variability in SWB judgments.
Complex analyses like this help address the ambiguities of early, two-wave longitudinal studies like
the one by Costa et al. (1987) described above because they can provide information about the causes of
the stability that is observed. For instance, the results from Lucas and Donnellan (2012) suggest that the
one-year stability will be considerably higher than the 20-year stability because the former is a result of
both the influence of a stable trait and slowly changing factors that lead to high stability over shorter
intervals. However, this slowly changing factors could be due to changes in personality or to external
factors. Further increases in complexity of design can help clarify these additional issues. For instance,
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Schimmack and Lucas (2010) expanded the use of latent state-trait models to incorporate information from
couples who were followed over time. This allowed them to examine how two members of a couple
change in similar or different ways over time. If, after accounting for initial similarity, two members of a
couple change in similar ways, then it suggests that shared environmental experiences are driving this
change. In addition, the models they used allowed them to test how much of the variance can ultimately be
explained by these external influences (though see the paper itself for some caveats about the strength of
conclusions that can be drawn). Their results suggested that sizable component of the variance in life
satisfaction judgments is due to the accumulating effects of external circumstances. This design is
important because it can help clarify the relative importance of person factors and situational factors even
without direct measures of either.
Although the studies reviewed used above rely on very large, long-running panel studies that include
nationally representative samples, it is also possible to use alternative methods for assessing stability of
SWB measures. Anusic and Schimmack (2016) meta-analytically combined results from many different
studies that reported stability estimates across varying intervals to isolate stable and changing components
from SWB measures. Importantly, they were able to expand their analyses beyond life satisfaction to focus
on both cognitive and affective components of SWB. Their meta-analytic results showed results that were
quite similar to those from the panel studies, with reliabilities ranging from .58 for affect to .67 for life
satisfaction. Furthermore, they found that approximately half of the reliable variance was due to stable
factors and half due to changing factors. Results were somewhat similar for affect and life satisfaction,
though the contribution of the stable component was slightly lower for affect than satisfaction. Importantly,
Anusic and Schimmack were also able to compare the results for SWB measures to those from personality
traits, and they found that the stable component accounted for a much larger percentage of variance in
personality traits than for SWB measures (also see Fujita & Diener, 2005). For instance, the stable
component accounted for about 40-50% of the variance in well-being measures, compared to about 80% of
the personality measures. Thus, by decomposing stability coefficients in this way, it is possible to provide a
very nuanced understanding of the stability of well-being measures; and these analyses strongly suggest
that SWB measures are quite different from personality traits in terms of the levels of stability they exhibit.
The results reported above relied primarily on global assessments of well-being to derive estimates of
stability. As noted previously, however, there are different ways to assess the various components of wellbeing,
including the use of more experiential measures that track SWB over time. Because of the increased
burden on respondents, experiential measures have been used much less frequently in large-scale studies
that track representative samples over long periods of time, and thus, there is not as much information
available about the long-term stability of such measures. One might expect stability to be weaker, as these
experiential measures track immediate reactions to ongoing experiences, typically over at most a few days.
Recently, some studies have begun to test the stability experiential measures, including some largescale
panel studies. This provides important initial information about the longer-term stability of such
measures. For instance, Baird, Le, and Lucas (2006) examined the six-month test-retest reliability of
multiple measures of SWB, including life satisfaction and both global and experience-sampling-based
measures of positive and negative affect. They found quite high stability (rs around .75) for all the
measures they assessed. However, this study focused entirely on student samples. Krueger and Schkade
(2008) examined the two-month test-retest stability of a day-reconstruction-based measure and found a
correlation of .64, which was comparable to that for a life satisfaction measure assessed twice over the
same period of time.
More recently, Hudson, Lucas, and Donnellan (2016) used day-reconstruction-method data from the
German Socio-Economic Panel study over a three-year period. Even though the day reconstruction method
used in this study sampled just a single day at each wave, one-year latent stability coefficients ranged from
.30 for negative affect to .47 for positive affect; and two-year stabilities were approximately the same size.
These stabilities were lower than the stability of a single-item life satisfaction measures, which ranged
from .50 to .59 in this sample (because just a single-item was used, these could not be adjusted for
measurement error; thus comparisons between the measures must take this difference into account).
Together with the results from Anusic and Schimmack (2016), this suggests that both experiential and
global measures of affect exhibit moderate stability over time, and that this stability tends to be somewhat
weaker than that for global life satisfaction measures.
The results reviewed above suggest that there is some degree of stability in SWB measures, regardless
of which component is assessed and which type of measure is used. At the same time, long-term studies
and meta-analytic evidence suggests that stabilities decline with increasing intervals, eventually leveling
out to asymptote at long-term stability coefficients around .25 to .30, or .40 to .50 after correcting for
measurement error. Together, this suggests that some truly stable personality factors contribute to wellbeing
judgments, but that real change, including change that could potentially be linked to external
260
circumstances, does occur. However, an important piece of evidence in early arguments for the role of
personality as a determinant of SWB was the fact that well-being scores remained stable in spite of
changing life circumstances (Brickman & Campbell, 1971; Costa et al., 1987). Thus, to fully address
questions about the relative role of personality and external circumstances, it is necessary to review studies
that explicitly focus on change that occurs following the experience of changing life circumstances.
Early evidence was interpreted as support for the idea that life circumstances simply do not matter.
Most famously, Brickman, Coates, and Janoff-Bulman (1978) examined the SWB of a small group of
patients with spinal cord injuries, a group of matched controls, and a group of lottery winners. Although the
authors' conclusion was simply that scores of the patients with spinal cord injuries were not as low as one
might expect (rather than that there were no differences at all), this study has had a strong impact on
perceptions of people's ability to adapt. As Lucas (2007b) noted, the differences between groups was, in
fact, quite large, and the extent of adaptation that occurred has been overstated. More recent studies that
rely on large samples of participants with similar spinal cord injuries consistently show that the differences
between these participants and those without such injuries are medium to large in size.
Simple cross-sectional studies like this are difficult to interpret. Better evidence for the impact of
changes in life circumstances comes from studies that follow individuals before and after such changes
occur. Of course, such studies are hard to conduct, as it is difficult to predict when rare events like the onset
of a disability will occur. However, researchers have again relied on large-scale panel studies that follow
large samples of participants for many years to examine these questions. With large enough samples and a
long enough period of time, some small percentage of participants will experience an event. As long as
SWB has been tracked throughout the study, pre-event levels can be estimated and compared to post-event
levels to examine the effects of the changing circumstances.
Many studies have now been conducted that use this approach (see Lucas, 2007a, for a review). These
studies show that changing life circumstances can have lasting effects on SWB, but the extent to which
lasting changes occur depend on the specific event in question. For example, Lucas, Clark, Georgellis, and
Diener (2003) found evidence that people quickly adapt to marriage (though see Anusic, Yap, & Lucas,
2014a, 2014b for complications regarding the interpretation of these effects), but that widows seem to be
affected by the loss of their spouse for much longer. Similarly, Lucas, Clark, Georgellis, and Diener (2004)
found evidence that life satisfaction permanently changes after a bout of unemployment, and Lucas
(2007b) found evidence for large and permanent effects of the onset of disability on life satisfaction,
especially for more severe conditions. Taken together, this evidence from longitudinal studies provides
relatively clear support for the idea that life circumstances do matter for SWB and that personality is not
the sole determinant of long-term individual differences (see Luhmann, Hofmann, Eid, & Lucas, 2012, for
a meta-analytic review).
In summary, there is now considerable empirical evidence about the stability of subjective well-being
measures over time. These studies reveal that in the short term, all components and measures of well-being
are reasonably stable. As the test-retest interval increases, stability declines. Eventually, however, stability
coefficients asymptote, and it appears that approximately one-third to one-half of the reliable variance (or
one-quarter to one-third of the total variance) in these measures is truly stable trait variance that does not
change even over very long periods of time. There is some indication that stability is slightly higher for life
satisfaction than affect, but this may be due to differences in the measures (Anusic & Schimmack, 2016).
Most studies that examine stability rely on self-report measures, which means that stability estimates may
be inflated by stability in method factors such as response styles; thus future research should take a
multimethod approach. Finally, studies that directly assess whether subjective well-being changes following
major changes in life circumstances shows that such changes can and do occur, even though some amount
of adaptation happens. Again, however, these studies of life events typically focus on life satisfaction as an
outcome, and there are fewer studies looking at the effects of life events on experienced affect.
The Heritability of SWB
The research reviewed above focused on the stability of SWB over time. One reason that this research
has been used to support the idea that personality matters is that personality itself is thought to be stable,
which leads to the idea that evidence for stability in SWB is evidence that personality matters. Of course, it
is possible that situations and life circumstances are also quite stable over time, which would provide an
alternative explanation for any stability in SWB that is observed. In addition, research that directly assesses
the impact of stable situations on SWB is limited in its ability to clarify these issues because it is difficult to
consider and assess all aspects of the situation and environment that may matter. Thus, researchers have
turned to other designs to help clarify whether stability in well-being that is examined is truly due to the
influence of internal factors versus stability in external, environmental features. One powerful set of
techniques for answering these questions comes from behavioral genetic studies (also see Røysamb, this
261
volume).
Although behavioral genetic studies represent a broad set of research designs, here I focus on evidence
from the most common of these: the twin study and its variants (see Røysamb, Nes, & Vitterso, 2014, for a
detailed review of these issues as they apply to research on SWB). Twin research takes advantage of the
fact that identical twins have identical DNA, whereas fraternal twins share on average 50% of their genes.
Thus, it is possible to estimate the influence of genes on SWB (or other observable characteristics) by
comparing the similarity of identical twins to the similarity of fraternal twins. A simple estimate of
heritability can be derived multiplying the difference between the identical twin correlation and the
fraternal twin correlation by two.
Some of the earliest studies that examined the associations among twins found heritabilities close to
.50 (Tellegen et al., 1988). However, the specific measures that were included were actually measures of
stable personality traits, even though the traits that were examined had an affective focus. Since these initial
studies were conducted, many additional studies have been reported, and these studies also find moderate
heritabilities, even for traditional measures of subjective well-being such as the Satisfaction With Life
Scale (Diener, Emmons, Larsen, & Griffin, 1985) or single-item measures of life satisfaction. For instance,
Stubbe, Posthuma, Boomsma, and De Geus (2005) examined the broad heritability of life satisfaction in a
sample of over 5,000 participants from the Netherlands Twin Registry, and they found a heritability
estimate of .38. Bartels and Boomsma (2009) found heritabilities between .40 and .50 for different
measures related to SWB, including a measure of life satisfaction. Indeed, enough studies have been
conducted that Bartels (2015) was able to conduct a meta-analysis of heritability estimates for well-being
measures, resulting in an average effect of .38 for general well-being and .32 for life satisfaction measures.
Studies focused on the heritability of SWB can be controversial because there is a tendency to
interpret these studies as providing direct evidence about the extent to which SWB can change.
Specifically, it is sometimes assumed that if something is highly heritable, then that means that change is
not possible, or even that early interventions are doomed to failure. This mistaken assumption can even
occasionally be reinforced by behavioral genetic researchers, such as when Lykken and Tellegen (1996)
suggested that "It may be that trying to be happier is as futile as trying to be taller and therefore is
counterproductive" based on their analysis of a longitudinal twin study. As Røysamb et al. (2014) point out,
there are no clear and direct implications for the potential for change from heritability estimates on their
own. Heritability estimates reflect a sample-based estimate of the variance that can be accounted for by
genes, and this estimate can vary across populations. They note that in modern industrialized nations, the
heritability of height is above 80%; but in the past, it presumably was much lower. This is because the
environmental factors that may have caused appreciable variation in height in the past are now much more
consistent, at least among individuals living in industrial nations. As a particularly salient example of this,
Cheung et al. (2017) showed that overall levels of life satisfaction have declined by more than two standard
deviations in Syria as the nation has descended into civil war; the severe environmental conditions clearly
impacted global well-being despite the influence of any personality characteristics. These results show that
caution is needed when drawing conclusions about the implications of high heritabilities for SWB.
Røysamb et al. walk through a number of important caveats about the interpretation of heritability studies
of SWB.
Ultimately, behavioral genetic studies of SWB are useful because they begin to constrain the possible
explanations for individual differences in SWB that are observed. If meta-analytic estimates suggest that
approximately one-third of the variance in life satisfaction is heritable (Bartels, 2015), then it will be
necessary to develop theories that incorporate mechanisms that can account for such effects. The consistent
result emerging from decades of behavioral genetic studies with many thousands of twins is that SWB is
moderately heritable, suggesting that some inborn features of people's personality have an influence on the
stable levels of SWB that they experience. It is up to future investigations to clarify exactly how these
processes work and how these inborn tendencies are translated into the individual differences in well-being
that we observe.
Associations with Personality Traits
The most direct evidence for the importance of personality in SWB comes from studies that examine
the association between specific personality factors and SWB. A quick review of the research that has been
conducted on SWB shows that there is considerable empirical evidence for this idea. Even in one of the
earliest reviews on the topic, Wilson (1967) stated that the happy person is best described as a "young,
healthy, well-educated, well-paid, extroverted, optimistic, worry-free, religious, married person with high
self-esteem, job morale, modest aspirations, of either sex and of a wide range of intelligence" (p 294).
Although this description emphasizes what is known about demographic predictors of SWB, it is clear that
personality factors like extraversion, optimism, high self-esteem, and even constructs related to goals and
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aspirations play a role. Since the time of Wilson's review, these early impressions have been confirmed
with increasingly sophisticated research designs.
In one of the earliest systematic investigations of the links between personality and subjective wellbeing,
Costa and McCrae (1980) specifically tested whether two personality traits---extraversion and
neuroticism---were uniquely linked to specific SWB variables. Costa and McCrae argued that extraversion
was associated with positive affect, neuroticism was related to negative affect, and together these
dimensions formed the affective core of the broader SWB construct. Interestingly, the associations between
personality traits and the affective dimensions were not especially strong, generally falling in the range of
.20 to .30. However, this early study provided a precedent for later work on the topic. Subsequent studies
focused on the structure of affect and the personality underpinnings of these dimensions often linked the
independent traits of extraversion and neuroticism to separable positive and negative affect dimensions
(e.g., Tellegen, 1985).
Perhaps because of the "disappointing" associations between SWB and objective life circumstances,
along with the consistently larger correlations between SWB and personality traits; research on personality
predictors of SWB flourished in the 1980s and 1990s (Diener & Lucas, 1999; Diener et al., 1999).
Researchers examined the association of hundreds of trait/well-being combinations. For instance, DeNeve
and Cooper (1998) conducted a meta-analysis of associations between various SWB components and 137
different personality traits. The traits that were most strongly associated with well-being were: "repressivedefensiveness,
trust, emotional stability, locus of control-chance, desire for control, hardiness, positive
affectivity, private collective self-esteem, and tension" (p. 197). DeNeve and Cooper also noted that wellbeing
components of satisfaction, happiness, and positive affect were predicted equally well from
personality traits, but that the association with negative affect tended to be weaker. Importantly, the overall
estimates that they arrived at were relatively small, typically below .20.
The meta-analysis by DeNeve and Cooper (1998) illustrates a number of issues that must be taken into
account when evaluating the associations between personality traits and SWB variables. First, the fact that
they were able to include 137 different traits in their meta-analysis makes the entire endeavor somewhat
overwhelming. Although 137 different measures can be identified, do these measures truly reflect 137
different constructs that need to be considered, each on its own? One goal of personality research over the
past decades has been to reduce the number of constructs that are examined so that more parsimonious
models can be developed (John, Naumann, & Soto, 2008). Indeed, of the traits that exhibited the strongest
correlations in DeNeve and Cooper's meta-analysis, many are not widely studied.
Perhaps even more problematic is that by necessity, meta-analyses often aggregate across scales that
have the same or similar names, but that reflect somewhat divergent content. For instance, Lucas and Fujita
(2000) suggested that by aggregating across very different types of measures of extraversion, DeNeve and
Cooper (1998) underestimated one association that, theoretically, should be quite strong: that between
extraversion and the specific component of positive affect. Lucas and Fujita conducted a more targeted
meta-analysis, which found much stronger associations between extraversion and positive affect, with an
average correlation of .37. Furthermore, their analyses showed that the size of this correlation varied
depending on which measures of extraversion and positive affect were used, supporting the idea that more
targeted analyses provide important information about the nature of this effect.
In a related, but much larger investigation, Steel et al. (2008) updated the meta-analysis of DeNeve
and Cooper (1998), focusing only on established measures of the Big Five personality traits and their
associations with well-being components. Like Lucas and Fujita (2000), Steel et al. found much larger
associations when these established measures were used. Importantly, their study showed that traits beyond
extraversion and neuroticism showed substantial associations with SWB. For instance, although in their
analyses extraversion showed an average correlation of .44 with positive affect and neuroticism showed an
average correlation of .54 with negative affect, even the traits of agreeableness and conscientiousness
showed moderate correlations with some well-being components (with correlations in the range of .20 or
.30). This meta-analysis confirmed that extraversion and neuroticism are especially important for SWB; but
it also showed that additional traits may play a role and should not be ignored when considering the impact
of personality on well-being.
Given these results, it is reasonable to ask what we should do about the rest of the 137 variables that
DeNeve and Cooper (1998) examined. For instance, Wilson (1967) highlighted traits such as optimism and
self-esteem as being particularly important for SWB, a finding that has been confirmed in subsequent
systematic research (e.g., Lucas, Diener, & Suh, 1996). Furthermore, these traits have a long history of
being studied independently from the Big Five (even if they are clearly related), and there are strong
theoretical reasons to expect them to be linked with well-being, perhaps even having an effect beyond traits
like extraversion and neuroticism. One recommendation for researchers interested in traits other than those
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in the Big Five is to (a) consider prior evidence like that included in DeNeve and Cooper's meta-analysis,
(b) think carefully about the psychological mechanism that would link the trait to SWB, (c) include
measures of extraversion and neuroticism in studies that examine the associations between the narrower
trait and the well-being outcomes to ensure that there is incremental validity.2 As the DeNeve and Cooper
meta-analysis makes clear, there is a danger that personality researchers will continually be "reinventing
the wheel" as they study related traits with different names as predictors of well-being outcomes. This is
particularly important given that many "positive" characteristics tend to go together, just as many
"negative" characteristics tend to correlate. Thus, it will be important to focus on personality-SWB
relations that provide unique information about the role that personality plays in SWB.
The idea that good things tend to go together raises one additional issue that must be addressed when
interpreting correlations between measures of personality traits and measures of SWB. That is, as typically
assessed, these two types of measures share method variance, which may inflate correlations substantially.
Remember, a critical part of the argument for the importance of personality traits as predictors of SWB is
that the correlations between personality and well-being variables tend to exceed correlations between
objective factors and SWB. However, if the former are inflated by shared method variance, then this
comparison may not be fair.
For example, Lucas and Fujita (2000), in their meta-analysis, separately examined correlations
between extraversion and positive affect that used the same method of assessment for both variables and
those that used different methods of assessment. Not surprisingly, the correlation was significantly larger
when the same method was used (r = .37) than when different methods were used ( r = .25). Indeed, the
correlation when different methods were used was only slightly larger than the correlation between SWB
and income (Lucas & Schimmack, 2009), a correlation that has often been dismissed as being very small
(Myers, 2000). Lucas and Fujita's meta-analysis confirmed that the association is not due solely to shared
method variance, but it does highlight the role that shared method variance plays. Few systematic
investigations of the role that shared method variance plays in other personality-SWB associations have
been conducted, but it is highly likely that the effect is similar in these different domains. Thus, we
encourage researchers to consider using alternative methods of assessment when examining the links
between personality and well-being to separate the substantive associations from those due to shared
method variance.
A final issue regarding the associations between personality traits and SWB concerns the extent to
which specific personality traits (or even specific facets of personality traits; Sun, Kaufman, & Smillie,
2017) exhibit differential associations with different components and measures of SWB. The meta-analysis
by Steel et al. (2008) showed that indeed, extraversion correlated most strongly with positive affect
(compared to other components of SWB) and neuroticism correlated most strongly with negative affect.
These results are consistent with the idea first raised by Costa and McCrae (1980) that extraversion and
neuroticism affect global well-being through their unique associations with positive and negative affect,
respectively. In support of this idea Schimmack, Oishi, Furr, and Funder (2004) showed that the facets of
extraversion and neuroticism that were most closely linked to positive and negative affect accounted for
most of the association between these traits and life satisfaction. This also suggests that future work
examining the associations between traits beyond extraversion and neuroticism and well-being related
outcomes such as life satisfaction can focus specifically on mechanisms that link these constructs
independently from extraversion and neuroticism.
Some research has also begun to investigate the links between personality and alternative measures of
well-being variables. For instance, Lucas and Fujita (2000) showed that self-reports of extraversion
predicted more experiential measures of well-being, such as daily reports of positive affect, somewhat less
strongly than they predict global measures of well-being (r = .28 versus r = .39). Similarly, Lucas, Le, and
Dyrenforth (2008) found larger correlations with extraversion for global reports of positive affect (r = .53)
than for aggregated daily or experience-sampling-based reports (rs = .39 and .31, respectively). More
recently, Anusic et al. (2017) compared self and informant reports of personality to global and experiential
(day reconstruction method) measures of subjective well-being. Across two student samples, global
measures of affect were at least as strongly, if not more strongly correlated with both self and informantrated
personality than the day-reconstruction-based measures. This result was replicated in a community
sample by Hudson et al. (2016). These results indicate that experiential measures based on experience
sampling or the day reconstruction method tend to correlate somewhat less strongly with personality
measures than do traditional measures of affect.
Overall, this review confirms the importance of personality traits as correlates of various components
of SWB, while also pointing to some substantial caveats. First, meta-analytic summaries show that
personality traits do show some of the strongest associations with SWB, with the associations between
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extraversion and positive affect and between neuroticism and negative affect being particularly strong. A
close look at the literature, however, suggests that these associations are inflated somewhat by shared
method variance, meaning that the associations between personality and well-being outcomes are not as
much larger than correlations between SWB and external circumstances as it might first appear. The metaanalytic
evidence is rich enough to show that the associations themselves do not result entirely from
method variance, but future research should take concerns about method variance more seriously when
examining these effects. The research also shows that correlations do vary across different components and
measures of well-being, with somewhat weaker associations for experiential measures like the day
reconstruction method or experience sampling method, as compared to global reports of affect. Future
research can help clarify whether these discrepancies are due to differences in the underlying processes or
to psychometric differences across measures.
Why Does Personality Matter?
The literature reviewed above provide clear evidence that the stable individual differences that
personality psychologists typically study are related to the SWB that people report. SWB scores are
somewhat stable over time, even in the face of changing life circumstances; this stability appears to be due,
at least in part, to in born genetic factors; and there are robust and moderately strong associations between
specific personality traits and SWB measures. Thus, an important question concerns the mechanisms that
may underlie these associations. Once the empirical links are established, research can proceed to explain
why these effects exist.
In terms of general mechanisms, may different approaches have been considered. For instance, one
class of mechanisms suggest that the behaviors that result from stable individual differences in personality
traits can directly or indirectly lead to well-being related outcomes. Decades of research has now shown
that personality can predict consequential outcomes, often with effect sizes that are larger than other widely
studied predictors such as intelligence or socioeconomic status (Ozer & Benet-Martinez, 2006; B. Roberts,
Kuncel, Shiner, Caspi, & Goldberg, 2007). It is possible that the associations between personality and wellbeing-related
outcomes flow through the different behaviors that individuals with different personalities
exhibit or different environments that they choose.
Alternatively, a different class of explanations focuses on the way that people perceive the world
around them. The fact that different people respond differently to the same external circumstances suggest
that there may be fundamental differences in outlook and perception that contribute to individual
differences in well-being. For example, early work by Rusting (1998) focused on basic cognitive processes
that may differ across individuals and that could promote greater or lesser well-being. Some people may
attend more to positive things in their environment, whereas other people's attention may be naturally
drawn to threats in the environment. Some people may find it easier to remember positive life events,
whereas for others, negative experiences may more easily come to mind. Even the interpretation of the
same event may differ across individuals; Diener, Lucas, Oishi, and Suh (2002) suggested that there are
stable individual differences in whether people use information about who is better or worse than they are
when evaluating their standing on a domain. These fundamental, low-level processes could add up to stable
individual differences in the well-being that people experience and report (see Robinson & Compton, 2008,
for a review).
Currently, there is no single, comprehensive model that clarifies how either a specific personality trait
or a set of individual differences affect SWB outcomes. However, there are good examples of what such a
theory would look like. Therefore, in the next section, I focus on one example where considerable
theoretical and empirical work has been done to investigate a specific personality/SWB association: The
link between extraversion and positive affect.
An Example: Extraversion and Positive Affect
As noted above, even in the earliest reviews, the importance of extraversion for SWB was emphasized
(e.g., Wilson, 1967). Costa and McCrae (1980) suggested that extraversion directly influenced one of two
major affective dimensions (positive affect), and these affective dimensions formed the core individual
differences underlying reports of SWB. Later factor analytic work confirmed and clarified the links
between extraversion and an activated form of positive affect (Depue & Collins, 1999; Lucas, Diener,
Grob, Suh, & Shao, 2000; Tellegen, 1985; Watson & Clark, 1997).
Attempts to clarify the mechanisms underlying these effects have proceeded in a number of different
directions. For instance, McCrae and Costa (1991) posited two broad classes of explanations that could be
considered: an instrumental explanation, which focuses on well-being as an indirect outcome of the
behaviors that extraverts tend to do; and a temperament model, which focuses on the direct links between
underlying physiological systems and the affective experiences that people have.
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In regard to the former class of explanations, many researchers have looked closely at what extraverts
do differently than introverts that might explain why they are happier. For instance, Diener, Larsen, and
Emmons (1984), Emmons, Diener, and Larsen (1986), and Pavot, Diener, and Fujita (1990) used daily
diary and experience sampling studies to assess whether extraverts participated in social activity more than
introverts or enjoyed that experience more, as a way of explaining extraverts' greater positive affect. Later,
a number of researchers followed up on this work with larger samples and more sophisticated sampling
designs (Lucas et al., 2008; Oerlemans & Bakker, 2014; Srivastava, Angelo, & Vallereux, 2008). These
studies consistently showed that extraverts do participate in greater amounts of social activity and that
social activity is associated with higher levels of positive affect, but that these differential experiences
cannot fully account for extraverts' greater positive affect. A related line of research focuses on
experimental evidence linking extraverted behaviors with experiences of positive affect. Specifically,
Fleeson and his colleagues have shown that asking people to act in an extraverted manner increases levels
of experienced positive affect (Fleeson, Malanos, & Achille, 2002).
Other researchers have more directly examined the temperament-based explanations. Many of these
investigations are at least loosely based on a model of personality developed by Gray (Gray, 1970, 1991;
Gray & McNaughton, 2000), in which different physiological systems regulate responses to rewarding or
punishing stimuli in the environment. For instance, one possible mechanism underlying extraversion is an
underlying sensitivity to reward, such that extraverts have stronger responsiveness to reward, which could
manifest in the form of increased wanting for potential rewards or increase liking of achieved rewards (see
Smillie, 2013, for a recent review). Some have posited that the precise system that underlies these effects
relates to individual differences in dopamine function (Depue & Collins, 1999), though evidence for
specific hypotheses related to this possibility is mixed (Wacker & Smillie, 2015).
A variety of specific research questions follow from the idea that extraverts may be more sensitive to
rewards than introverts and that this difference is responsible for their greater happiness. For instance, early
studies suggested that extraverts, when exposed to positive emotional stimuli (e.g., a positive mood
induction procedure in the lab), would respond more positively than introverts (Larsen & Ketelaar, 1991).
However, this initial effect frequently failed to emerge in laboratory studies (Lucas & Baird, 2004), and
more naturalistic studies rarely found support for the idea that extraverts respond more positively to
positive experiences or events (Anusic et al., 2014a; Lucas et al., 2008; Yap, Anusic, & Lucas, 2012).
More recently, however, Smillie and colleagues found support for a possible resolution to the contradictory
evidence, showing that extraverts appear to respond more strongly to appetitive stimuli, rather than simply
pleasant stimuli. This distinction fits with the underlying reward sensitivity and may explain
inconsistencies in past research.
Together, the studies from this large literature provide ample avenues for future research on the
association between extraversion and positive affect. To be sure, existing studies do not yet provide a
complete answer about why these constructs are related. However, the various approaches that have
focused on behaviors, cognitive factors, emotional reactions, etc., provide a clear model for how research
on personality and well-being variables can proceed. These studies posit various mechanisms by which one
can get from relatively basic, low-level mechanisms that can be tested in the lab or in more naturalistic
studies. It is likely that research on extraversion and positive affect will provide useful information not just
for understanding this pair of constructs, but for researchers who are beginning to think about mechanisms
that may link other trait/well-being associations.
Summary
Research on the links between personality and SWB is important partly because the strong
associations have been so surprising to lay people and scientists alike, partly because of the amount and
breadth of evidence that has accumulated for the robustness of these effects across different constructs and
methods of assessment, and partly because of the rich theories that have emerged to explain the
correlational findings that alerted early well-being researchers to the stable individual differences in wellbeing
that exist. Incredible progress has been made on all of these questions, so much so that perhaps more
than any area in psychology, researchers are able not only to specify that some degree of stability or
heritability exists, or that some personality traits predict well-being variables, but also to make relatively
precise point predictions about the size of these effects. Thus, research on personality and well-being can
serve as a model for how research on the factors underlying well-being can proceed.
That being said, there is still considerable work to be done. This area of research, like many areas
within SWB more broadly, suffers from an over-reliance on self-report methods. This makes comparisons
between various predictors of SWB somewhat difficult to make, as personality predictors often share
method variance. Future work that relies on multiple methods of assessment, both of the personality
predictors and the well-being outcomes, will help further clarify these associations. And, as with most areas
266
of well-being research, greater emphasis on the processes that underlie these associations will advance not
only theories of SWB, but basic theories of personality themselves.
Footnotes
1It is also important to note here that random measurement counts as a state-like influence that leads to
instability from one occasion to the next.
2It is also important to use techniques for testing incremental validity that provide a conservative test of the
importance of the new construct; see Westfall and Yarkoni (2016) for a discussion.
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Hedonomics: On Subtle Yet Significant Determinants of
Happiness
By Yanping Tu, University of Florida; Christopher K. Hsee, University of Chicago
Citation
Tu, Y., & Hsee, C. K. (2018). Hedonomics: On subtle yet significant determinants of happiness. In E.
Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
One way to pursue happiness is to improve the objective levels of external outcomes such as wealth; that is
an economic approach. Another way to pursue happiness is to improve the arrangement of and choices
among external outcomes without substantively altering their objective levels; that is a hedonomic
approach. This chapter reviews research adopting the latter approach. Specifically, we present a list of
subtle yet significant determinants of happiness from four perspectives: (1) pattern of consumption, (2)
procedure of consumption, (3) (mis)match between the choice phase and the consumption phase, and (4)
type of consumption. Although far from comprehensive, these factors offer implications for “choice
architects”—government, companies, and individual consumers—on improving happiness.
Keywords: hedonomics, happiness architecture, judgment and decision making, consumption
It is almost truism to say that happiness is the ultimate pursuit—or, at least, one of the ultimate
pursuits—of life. Hence, “formulas” for improving happiness have always been of interest not only to
academics (Diener & Seligman, 2004; Gilbert, 2006; Huppert, Baylis, & Keverne, 2005; Seligman, 2002;
Seligman & Csikszentmihalyi, 2000), but also to policy makers and individuals. Intuitively, happiness
correlates with wealth—people in affluent countries are happier than those in poor countries, and people
with higher annual incomes are happier than those with lower annual incomes, presumably because
wealthier individuals have access to more and better material goods (e.g., more and tastier food, larger and
better houses, appliances and technologies that liberate them from labor). Indeed, research generally finds a
reliable positive link between wealth and happiness (Diener & Oishi, 2000; Lucas & Schimmack, 2009).
Yet, the impact of wealth on happiness has its boundaries—their relationship follows a concave curve,
such that an increase in wealth ceases to increase experienced happiness in daily life once wealth reaches a
certain point (Diener & Biswas-Diener, 2002; Kahneman & Deaton, 2010).
Then, are there non-economic approaches to increase daily affective well-being? In this chapter,
we review research on hedonomics (Hsee, Hastie, & Chen, 2008), which studies how to increase happiness
(and minimize unhappiness) by improving the arrangement of and choices among external outcomes
without substantively increasing the objective levels of the external resources. Hedonomics involves many
factors. In this chapter, we focus on four perspectives: (1) the pattern of consumption, (2) the procedure of
consumption, (3) the (mis)match between the choice phase and the consumption phase, and (4) the type of
consumption. We also explain the corresponding psychological underpinnings. These factors may seem
subtle, but can produce significant impacts on happiness.
We should note that “happiness” has different meanings, and this chapter focuses on only one type
of happiness: valenced (positive or negative) hedonic experiences with external stimuli. We do not study
specific emotions such as anger and excitement, nor do we study overall life satisfaction or meaning in life.
Pattern of Consumption
A fixed amount of consumption resources can be divided into several chunks and consumed
sequentially on separate occasions. The characteristics of these chunks, including the number of chunks,
the size of each chunk in the sequence, and the change in the sizes of chunks, can influence happiness.
Segregating Gains
Prospect Theory’s value function (Kahneman & Tversky, 1979) posits that gains confer a
subjective utility along a concave curve, with diminishing marginal utility. Therefore, a large quantity of
consumption resources can be divided into a few chunks and treated as distinct consumption units,
increasing happiness by taking advantage of the steep utility gain from “zero consumption” to “some
consumption” (i.e., the region close to the reference point). Indeed, segregating gains is one of the four
hedonic editing rules formally proposed by Thaler (1985). It suggests that, for example, a person who plans
to eat in a fancy restaurant and get a relaxing massage should arrange these two activities on separate days,
rather than on the same day, to derive greater overall happiness from these two activities. Similarly, a
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person who receives a notification that a new season of her favorite sitcom is available on Netflix should
spread her viewing experience over two weeks, rather than binge-watching all the episodes in two days, to
maximize the overall pleasure obtained from watching the entire season. (For other hedonic editing
principles, see Thaler, 1985.)
Note that usually segregation inevitably means introducing non-consumption periods into the
consumption sequence and lengthening the overall consumption duration. This way, people have more time
to recover from satiation or hedonic adaption (see “ Adding Delays” and “ Adding Interruptions and
Slowing Down” in this chapter for more information), in addition to taking advantage of the high marginal
utility of a small portion of consumption resources. Then, will the segregation principle be effective above
and beyond the satiation account when the total length of consumption is held constant? Redden (2007)
offers supporting evidence by merely having participants mentally segregate their consumption (i.e., a
manipulation of perceived segregation). In one study, participants ate several jelly beans of different
flavors. They either sorted these jelly beans into one broad category (e.g., jelly beans) and treated their
eating experience as one unit, or sorted the same amount of jelly beans into several specific categories
(e.g., orange jelly beans, banana jelly beans) and treated their experience as a combination of several
distinct units. Redden (2007) found that participants reported greater happiness over the course of eating
jelly beans in the latter condition, even though their eating experience was only mentally segregated and
the total duration of consumption was fixed.
Improving Sequence
Without a doubt, people desire a happy ending, but do they prefer that happy ending at the cost of
inferior experiences early in the sequence? Loewenstein and Prelec (1993) find that, for a constant
objective amount or value of consumption resources, people prefer a course with progressively increasing
quality of experience, compared with a course with stable or declining quality of experience. In one study,
when scheduling a dinner at a fancy French restaurant and a dinner at a local Greek restaurant, people
preferred the “Greek first, French second” sequence over the “French first, Greek second” sequence. In a
similar vein, Prelec and Loewenstein (1998) show that people preferred the decoupling of payment and
consumption, and were willing to incur losses (i.e., payment) before gains (i.e., consumption experience).
Outside the lab, panel data on British employees’ wage change and well-being supports this principle
(Clark, 1999)—employees who experienced a positive wage change were happier and more satisfied with
their job, regardless of the absolute amount of salary. To illustrate this in a stylized way, the annual income
stream “$50k, $60k, and $70k” generated greater overall happiness than the stream “$60k, $60k, and $60k”
or the stream “$70k, $60k, and $50k,” despite all income streams achieving the same average of $60k
annually.
Noticeably, this preference contradicts the economically rational solution that calculates the present
value of a flow of future values via discounting. Specifically, because both future gains and future losses
“deflate” in value when evaluated at the present, expediting future gains (to increase their present utility)
and postponing future losses (to decrease their present disutility) can maximize the present value of the
consumption flow. Nevertheless, this economically optimal arrangement is sub-optimal for happiness.
In addition, not only are people sensitive to the change of the sizes of the consumption chunks, as
reviewed in “Improving Sequence,” but also they are sensitive to the velocity of the change (i.e.,
acceleration; Hsee & Abelson, 1991). Specifically, a sequence of consumption resources that increase in
quantity or value faster and faster will generate greater happiness than does a sequence of consumption
resources that increase in quantity or value at a constant rate (Hsee, Salovey, & Abelson, 1994). For
example, a video game player will be happier and more motivated to continue playing if the game score
increases in an accelerating pattern (e.g., 10, 20, 40, 80, 160, 320,….) than if it increases in a uniform
pattern (e.g., 100, 200, 300, 400, …), even if the score does not correspond to any external rewards and is
spurious (Shen & Hsee, 2017).
Procedure of Consumption
The same amount of consumption resources can be consumed in different ways. The characteristics
of the procedure—delays, interruptions, speed, and curiosity towards the experience—influence overall
happiness.
Adding Delays
Obviously, people get pleasure from their moment-to-moment experiences with the consumption
stimuli, but can they get pleasure outside the consumption phase? Research shows that, by imagining
positive experiences prior to the actual occurrence, people can get anticipated utility or savoring value, too
(Kahneman, 1999). It follows that delaying consumption can generate additional “free” happiness. Indeed,
in one study, participants either waited 30 minutes before eating two chocolate candies or ate them
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immediately, and those who waited reported greater overall enjoyment of the chocolate candies (Nowlis,
Mandel, & McCabe, 2004). This principle suggests that, for example, families should book vacations in
advance, and online shoppers should not select expedited shipping (especially when it costs extra) to get
higher overall enjoyment. (Relatedly, the opposite is true for negative experiences, such as waiting to get a
surgery. In these situations, one should expedite the experience to reduce unhappiness from anticipation.)
Despite evidence that an externally imposed delay can produce a hedonic boost, do people choose
to delay consumption? It is possible that, because waiting requires self-control and people tend to act on
impulsive desires immediately (Frederick, Loewenstein, & O’Donoghue, 2002; Mischel, Shoda, &
Rodriguez, 1989), people may not opt for it when given the choice. However, a few studies document that,
at least in some contexts, people can choose optimally. For example, Loewenstein (1987) finds that when
people could choose to enjoy a fancy dinner or get a kiss from their favorite movie star either now or later,
they preferred later. Similarly, Lovallo and Kahneman (2000) show that gamblers were more inclined to
delay learning about their outcomes when the potential reward was larger, thereby deriving greater
savoring value from imagining winning the reward.
However, the delaying principle should be applied with caution because it runs against a few other
accounts. First, the waiting period is usually unpleasant, which may result in anxiety and stress (Houston,
Bettencourt, & Wenger, 1998; Osuna, 1985). Second, the negative experience during waiting is likely to be
transferred to the target consumption, and hence may reduce overall satisfaction (e.g., Dellaert & Kahn,
1999). Third, from an economic perspective, waiting decreases the present value of the consumption
experience. Fourth, because imagined experience sometimes can substitute for real experience
(Morewedge, Huh, & Vosgerau, 2010), the anticipation period may lead to adaptation and thus decrease
pleasure from the actual consumption.
Interrupting and Slowing Down
Whereas the previous section (“Adding Delays”) deals with the procedure of consuming a single
unit, this section is about improving overall happiness in consuming a single stimulus repeatedly (e.g.,
listening to one’s favorite song 10 times) or a series of similar stimuli (e.g., watching 10 episodes of a TV
show), a process in which people generally experience hedonic adaption, get satiated, and enjoy the stimuli
less and less (Frederick & Loewenstein, 1999; Kahneman & Snell, 1992). In these situations, adding
interruptions (i.e., introducing “breaks” into the course of consumption) can boost happiness by giving
people time to recover naturally from satiation. Indeed, Nelson and Meyvis (2008) find that adding a short
break to a massage or a pleasant song elevated the participants’ overall enjoyment of the period, as
compared with no interruption. Moreover, adding an interruption can help even when the interruption itself
is somewhat negative. For example, Nelson, Meyvis, and Galak (2009) show that TV commercials (i.e.,
not-so-pleasant distractors) can help “reset” a person’s feelings toward the TV program, restore the
intensity of the positive experience, and increase overall enjoyment. However, people usually do not
foresee the benefit of adding interruptions, and do not choose to break up positive experiences (Nelson &
Meyvis, 2008; Nelson, Meyvis, & Galak, 2009).
Relatedly, these findings suggest that people will benefit from slower consumption when
experiencing repeated, similar stimuli, since a slower pace means more and longer intervals between
consumption periods. Indeed, Galak, Kruger, and Loewenstein (2012) provide empirical support for this
proposition. In one study, they had participants eat six Hershey’s Kisses while watching a 20-minute video.
In the forced-slow-rate condition, participants were instructed to eat each of the chocolates when prompted
by the computer, once every 200 seconds. In the self-paced condition, participants were instructed to eat at
a rate that they thought would maximize their overall enjoyment of the Hershey’s Kisses. All of the
participants then ate the chocolates and rated their enjoyment of each piece after consumption. At the end
of the study, they also rated their overall happiness retrospectively. Participants in the self-paced condition
ate faster than those in the forced-slow-rate condition. More importantly, enjoyment of each chocolate
declined much faster and enjoyment of the entire eating experience was lower in the self-paced condition
than in the forced-slow-rate condition. These results confirm the hedonic benefit of slowing down, and also
suggest that people do not seem to anticipate how quickly they may get satiated from repeated
consumption. As a result, people consume too rapidly when they have control over the consumption pace.
Inducing Curiosity
Curiosity is conceptualized by Loewenstein (1994) as the desire to “close an information gap,” and
is a form of “cognitively induced deprivation.” Just as deprivations of sleep, sex, and food lead people to
seek restoration, the deprivation of a cognitive state can also result in a natural resolution—in this case, the
desire to resolve curiosity can be a goal in and of itself, beyond the practical benefits such as information
(Litman, 2005) and entertainment (e.g., gossip; McNamara, 2011). For example, in one study (Hsee &
Ruan, 2016), participants saw ten pens and learned that five were regular pens, while the other five were
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prank electric-shock pens that would deliver a painful (yet harmless) shock. In one condition, the prank
electric-shock pens were labeled to avoid evoking curiosity, whereas in the other condition, the prank
electric-shock pens were unlabeled and therefore curiosity-inducing. Participants then entered into a
waiting period (purportedly for another study) during which they could click these pens if desired. Hsee
and Ruan (2016) find that participants clicked more of the pens (and as a result, received more unpleasant
electric-shocks) in the curiosity-inducing condition. Coined the Pandora Effect—that curiosity leads people
to opt for expectedly negative outcome—this counterintuitive phenomenon provides evidence that people
can get positive hedonic value through curiosity resolution.
It follows that one can increase overall happiness by adding a curiosity-induction stage prior to the
target consumption period, in which the curiosity will resolve. Ruan, Hsee, and Lu (in press) provide
empirical support for this possibility. In one study, participants learned that they would read a biography of
Einstein. Prior to the reading period, those in the curiosity-inducing condition read ten questions about the
life of Einstein and were prompted to think about the answers, whereas those in the control condition
viewed 10 pictures of Einstein and were not prompted to think about anything related to the biography.
Participants then rated their experiences in the prior-to-reading period, read the biography, and rated their
experiences in the reading period. The authors find that participants in the curiosity-inducing condition
were happier than those in the control condition during the experiment as a whole (i.e., considering
happiness ratings from the prior-to-reading phase and the reading phase together). Importantly, the greater
overall happiness in the curiosity-inducing condition was driven mainly by a boost in happiness during the
reading period. In other words, participants who thought about the questions obtained greater satisfaction
from reading the Einstein biography, but thinking about those questions per se did not decrease their
happiness in the first stage. Importantly people do not seem to be aware of the hedonic benefit of inducing
curiosity and do not choose optimally—when given a choice between viewing questions about Einstein or
pictures of Einstein before reading the biography, participants did not prefer the curiosity-induction
method.
(Mis)Match Between Choice Consumption
Because people possess malleable (i.e., context-dependent and time-dependent) preferences, they
are prone to choosing sub-optimally if the circumstance under which they choose a consumption option
mismatches with the circumstance under which they ultimately consume the option. Therefore, happiness
can be improved by matching the choice phase with the consumption phase, in terms of visceral state (hot
or cold), evaluation mode (joint or separate), and focus (wide or narrow).
Matching Visceral States
Loewenstein (1996) made the distinction between two visceral states: a “cold” state, in which
people are rested, satiated, sexually unaroused, or intellectually satisfied, and a “hot” state, in which people
are tired, hungry, sexually aroused, or intellectually curious. Individuals in one state usually cannot
accurately anticipate or predict their preferences and experiences in the opposite state—there is an empathy
gap. For example, a person who just had dinner will have difficulty imagining how hungry she will feel the
next morning.
People’s visceral states change over time. Therefore, people who make decisions about future
consumption too far in advance may experience a mismatch in visceral states between the choice phase and
the consumption phase. People tend to make predictions about their future state by projecting their current
state (Loewenstein, O’Donoghue, & Rabin, 2003; see also Loewenstein, 1996; Van Boven, Dunning, &
Loewenstein, 2000; Van Boven & Loewenstein, 2003); this projection bias leads to sub-optimal decisions.
For example, a grocery shopper who just had dinner may not buy enough for her upcoming breakfast,
impairing her satisfaction the next morning; a grocery shopper who just finished work at 5pm, feeling
hungry and thirsty, may add an unplanned dessert item (e.g., a big carton of ice cream) to her shopping
cart, only to find herself too full to eat anything after dinner (Nisbett & Kanouse, 1969; Gilbert, Gill, &
Wilson, 2002; Read & Van Leeuwen, 1998). Similarly, right after visiting an art museum, one may be
particularly curious (i.e., intellectually aroused) about the stories behind the artwork, so she purchases
related books or DVDs. However, she later finds the books and DVDs gathering dust on her bookshelves,
as her curiosity about the artwork faded quickly after the visit. To optimize choice and increase
consumption happiness, one should either engage in more deliberative projection of future states or reduce
the temporal interval between the choice phase and consumption phase.
Matching Evaluation Modes
All decisions and judgments are made in the joint evaluation mode (JE), the single evaluation
mode (SE), or some combination of the two (Hsee, 1996). In the joint evaluation mode, two or more
options are juxtaposed and evaluated comparatively; in the single evaluation mode, each option is
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presented in isolation and evaluated in an absolute sense, without comparison to alternatives. These two
modes can systematically shift people’s attention to different attributes of the options and influence their
evaluations. Specifically, when attributes differ in terms of “evaluability”—that is, the extent to which
people can judge the value of the attribute when it is presented alone—easy-to-evaluate attributes receive
more attention and more decision weight in the single evaluation mode, while difficult-to-evaluate
attributes receive more attention and more decision weight in the joint evaluation mode (Hsee, 1996; Hsee,
Loewenstein, Blount, & Bazerman, 1999; Hsee & Zhang, 2004). Take 4K TVs: the size of the screens is
more difficult to evaluate (since they are all very big) than the aesthetic design. Thus, people who evaluate
different 4K TV models one by one (in the single evaluation mode) will give more weight to aesthetic
design than size, whereas people who evaluate these models together (in the joint evaluation mode) give
more weight to the size dimension. It is therefore possible that a consumer prefers the TV model with a
larger size in the store (joint evaluation) but the TV model with a better aesthetic design at home (single
evaluation). (Note that the evaluability of an attribute differs across individuals. In general, expertise or
familiarity with the attribute will improve its evaluability. For example, although the size of a 4K TV might
be a difficult-to-evaluate attribute for most consumers, it might be an easy-to-evaluate attribute for Best
Buy personnel.)
Importantly, people often make choices in the joint evaluation mode, as they compare various
options, yet they often consume in the single evaluation mode, experiencing only the option they
purchased. Because people value difficult-to-evaluate attributes more in the joint evaluation mode and
easy-to-evaluate attributes more in the separate evaluation mode, they may make suboptimal choices for
consumption. For example, one may spend a large sum of money to obtain the bigger 4K TV, only to find
that day-to-day, she does not enjoy looking at the TV in the living room. To alleviate the impact of such a
mismatch, one should try to adopt the single evaluation mode in the choice phase, evaluating options one
by one and forming holistic impressions of each of them.
Widening Focus
When predicting future experiences, people tend to focus narrowly on the target stimuli and ignore
the impact of contextual factors, such as ambient environment, mood fluctuations, and other life events.
Consequently, this focalism bias leads people to overestimate both the intensity and the duration of the
focal stimuli’s impact (i.e., the impact bias; Gilbert, Pinel, Wilson, Blumberg, & Wheatley, 1998; Wilson &
Gilbert, 2003; Wilson, Wheatley, Meyers, Gilbert, & Axsom, 2000;). For example, college football fans
thought the victory of their favorite team would make them happier in the moment and cause them to
remain happy for a longer time than it actually did.
In the context of making choices for future consumption, the mismatch of attention span between
the choice phase and the consumption phase may lead people to overvalue the focal option in the choice
phase, resulting in regret and dissatisfaction in the consumption phase. For example, when a new iPhone
comes out, a consumer may be drawn to the new or better features it offers (e.g., a faster chip, a more
sensitive 3D touch system, a brighter and more clear screen with retina display). She may overestimate its
hedonic impact in her daily life and willingly pay a high price to purchase the new iPhone. However, once
she owns the new iPhone, it will gradually lose its attentional prominence because it has become one of
many things—such as mundane activities (e.g., laundry), work duties, and environmental factors (e.g.,
good or bad weather)—that influence her overall happiness. As a result, this consumer may feel unsatisfied
and regret the purchase. To alleviate the impact of a mismatch, one may deliberatively widen the span of
focus in the choice phase, perhaps by actively considering other factors that may contribute to future
happiness, to estimate the hedonic impact of the target option more accurately.
Type of Consumption
Different types of consumption produce happiness with different intensity and durability.
Experiential consumption generates greater happiness and more durable happiness than material
consumption; consumption that satisfies an inherent preference (i.e., a preference formed early in
evolution) generates greater happiness and more durable happiness than consumption that satisfies a
learned preference (i.e., a preference that was formed recently).
Distinguishing between Experiential and Material Consumption
In their seminal research, Van Boven and Gilovich (2003) defined material consumption as
“spending money with the primary intention of acquiring a material possession—a tangible object that you
obtain and keep in your possession,” and experiential consumption as “spending money with the primary
intention of acquiring a life experience—an event or series of events that you personally encounter or live
through.” Research generally finds that compared with material consumption, experiential consumption
generates more intensive happiness and more durable happiness. For example, in terms of the intensity of
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happiness, one study (Van Boven & Gilovich, 2003) asked participants to recall either a recent material
purchase or a recent experiential purchase of similar price, and to rate the enjoyment they got from the
purchase. Results show that experiential purchases generated greater enjoyment than material purchases. In
terms of the durability of happiness, one study (Nicolao, Irwin, & Goodman, 2009) asked participants to
make a purchase from either a set of experiential options (e.g., watching videos, listening to songs, playing
video games) or a set of material options (e.g., a ruler, a keychain, a picture frame), all of which were
priced the same in the lab. Researchers tracked participants’ happiness with their purchases for an extended
period of time. Happiness decayed more slowly in the experiential purchase condition than in the material
purchase condition, suggesting that happiness engendered by experiential purchase is more resistant to
hedonic adaptation.
The different hedonic impacts of experiential and material consumption have three major
psychological underpinnings. First, experiential consumption is more important than material consumption
to one’s identity; specifically, experiences constitute a larger proportion of, and are more central to, one’s
identity. As the saying goes, we are what we do, not what we have. Carter and Gilovich (2012) offered a
straightforward test of this notion by asking participants to first list five most significant experiential
purchases and five most significant material purchases they had made in their lives, and then write a
summary of their “life story” in which they could incorporate their significant purchases. Participants
weaved their experiential purchases into their life stories more often than their material purchases,
suggesting that experiential consumption contributes more than material consumption to one’s identity.
Besides, when asked to draw a large circle to represent the self, and a few small circles to represent their
material and experiential consumptions, participants drew the circles representing experiential
consumption closer than the material consumption circles to the “self” circle, suggesting that people view
their experiential consumption as more central to their personal identity. Second, people are less likely to
engage in potentially invidious, alternative-wise and social comparisons after making experiential
purchases than material purchases (Carter & Gilovich, 2010; Howell & Hill, 2009). This is because
experiences (a) are more inherently evaluable, making comparison unnecessary (Carter & Gilovich, 2010),
and (b) have a lot more variation among experiencers than material possessions have among owners,
making comparison difficult (Van Boven, 2005). Third, experiential consumption is more satisfying than
material consumption because the former enhances social relationships. Specifically, people more often
share experiences than material possessions (Caprariello & Reis, 2013), making experiential consumptions
inherently more social. Besides, experiential consumptions are better conversation topics, and people
prefer a conversation partner who talks about experiences over material goods (Van Boven, Campbell, &
Gilovich, 2010).
Distinguishing between Inherent Preference and Learned Preference
Preferences can be categorized by the timing of their formation in human evolution—a million
years ago, a millennium ago, or a year ago (Tu & Hsee, 2016). Preferences that formed earlier in evolution
are “inherent”. Examples include our preference for a warm ambient temperature (e.g., 70 °F) over a cold
ambient temperature (e.g., 40 °F), for high-calorie food (e.g., French fries) over low-calorie food (e.g., kale
salad), for a good night’s sleep over sleep deprivation, and for being socially accepted over being socially
excluded. These preferences are hard-wired, derived from our basic biological and psychological needs,
and persist regardless of time and contexts. Preferences that formed later in evolution are “learned.”
Examples include our preference for genuine diamonds over synthetic diamonds, for a $3000 Gucci bag
over a $300 Coach bag, for French wine over California wine, and for Crocs’ hole-filled shoes over
normal-looking shoes. These preferences are malleable and vary with time and contexts. There is certainly
a continuum of inherent preference (IP) to learned preference (LP), but for ease of exposition, we treat
these as distinct categories here.
Based on this distinction, Tu and Hsee (2016) propose that happiness derived from IP attributes
needs no social comparisons and is absolute, whereas happiness derived from LP attributes requires social
comparison and is relative. Therefore, an improvement on an IP attribute will always increase happiness,
whereas an improvement on an LP attribute does not necessarily increase happiness. A field study
supported this proposition by comparing happiness derived from ambient temperature in winter (a
representative IP attribute) and happiness derived from the value of one’s jewelry (a representative LP
attribute) within and across 31 major cities in China (Hsee, Yang, Li, & Shen, 2009). Specifically,
researchers interviewed residents in these cities via phone and asked four questions: (1) the participant’s
present room temperature, (2) how happy they were with their present room temperature, (3) the value of
the participant’s jewelry, and (4) how happy they were with their jewelry. Because social comparison is
more likely to happen among people within the same city than between different cities, the researchers
compared the impacts of temperature value and jewelry value on happiness both within cities and across
cities. For room temperature, people with higher room temperature were happier both within each city
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(within-city effects) and between cities (between-cities effect) (see Figure 1). However, jewelry value had
only within-city effects (see Figure 2). These results suggest that happiness derived from room temperature
—an inherent-preference attribute—increased as the value of this attribute increased, whereas happiness
derived from jewelry value—a learned-preference attribute—increased only when the value of this attribute
was higher than the values held by other people.
Figure 1. The impact of room temperature on happiness within cities and across cities. The slope of
each small line indicates the effect of temperature within a particular city, and the slope of the long
(trend) line indicates the effect of temperature across all the cities. The graph shows a positive effect
of temperature within most cities (within-city effects), and also a positive effect across cities
(between-city effect).
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Figure 2. The impact of jewelry value on happiness within cities and across cities. The slope of each
small line indicates the effect of jewelry value within a particular city, and the slope of the long
(trend) line indicates the effect of jewelry value across all the cities. The graph shows a positive effect
of jewelry value within most cities (within-city effects), but not have a positive effect across cities
(between-city effect).
The second proposition based on this distinction is that the durability of happiness differs between
IP and LP attributes. Because inherent preferences have a stable and hard-wired internal reference scale, an
improvement on an IP attribute will likely be permanent and long-lasting. On the contrary, because learned
preferences do not have a stable reference scale and instead rely on external reference points (e.g., a prior
status or the status of others), an improvement on an LP attribute will likely disappear once the external
reference points lose salience or change. For instance, social acceptance (an IP) confers an increase in wellbeing
that will endure regardless of whether other people get socially accepted. Meanwhile, a luxury bag
(an LP) confers an increase in well-being that will fade when other people also purchase similar (or better)
bags, or when the consumer forgets the experience of not owning a luxury bag in the past.
Two empirical studies by the present authors (Tu, Hsee, & Li, 2017) lend support to this
hypothesis. In both studies, participants first learned the definitions and examples of IP and LP and then
passed a comprehension test before answering further questions. Noting that IP and LP fall on a
continuum, we created comprehension questions in relatively obvious contexts. For example, we asked
participants to indicate whether “the preference for a warm ambient temperature to a cold ambient
temperature in winter” or “the preference for earning $100,000 a year to earning $80,000 a year” is more
inherent. The former is the correct answer. We find that the correction rates are generally high, suggesting
that people can intuit and identify the distinction between IP and LP. This approach is similar to what was
used in studying material and experiential consumption (Van Boven & Gilovich, 2003). Next, in one study,
we asked participants to think about a purchase they had made with the intention of satisfying an inherent
or learned preference. We specified the time frame (“more than two years ago”), the cost (“between $50–
$500”), and the durability of the purchase (“something you still have and are still using”). Participants
recalled such a purchase, described the type of preference they tried to satisfy, and then rated their
immediate happiness and current happiness due to the purchase. We find that, although happiness
decreased over time with both types of purchases, the decline was greater for LP-oriented purchases than
for IP-oriented purchases. In the second study, we replicated this effect in the context of life events while
controlling for immediate happiness. Specifically, we asked participants to recall two improvements in
their life within the past 5 years—one satisfying an inherent preference, the other satisfying a learned
preference—that had similar immediate impacts on their happiness. Participants described two such
improvements and rated whether the improvements had a long-lasting effect on happiness. Supporting our
prediction, participants reported longer-lasting effects of happiness from improvements that satisfied an
inherent preference than from those that satisfied a learned preference.
Together, we aim to make two related contributions from this program of research (Hsee et al.,
2009; Tu & Hsee, 2016; Tu, Hsee, & Li, 2017). First, we draw a distinction between inherent preferences
and learned preferences—a distinction that has potentially profound implications for both theory-building
and policymaking. Second, we provide empirical evidence suggesting that improvements related to
inherent preferences produce more sustainable gains in happiness than do improvements related to learned
preferences. This insight is important, in light of the fact that most improvements that have been made over
the years are only about learned preferences and not about inherent preferences.
Conclusion
In this chapter, we review research on hedonomics. We present a representative, but not
comprehensive, list of determinants of happiness, mainly drawing upon research on judgment and decision
making. These factors are subtle but can significantly influence happiness. More importantly, they offer
implications for “choice architects”—governments, companies, and individual consumers—who seek to
design better consumption patterns and procedures, to offer proper timing of choice and consumption, to
produce and stimulate the right type of consumption experiences, and ultimately, to improve daily
happiness without significantly increasing the possession or consumption of external materials.
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derivatives
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BIOLOGY
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The Genetics of Well-being
By Espen Røysamb & Ragnhild Bang Nes, University of Oslo, Norwegian Institute of Public Health
Citation
Røysamb, E., & Nes, R. B. (2018). The genetics of wellbeing. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
Research into the genetic and environmental origins of human wellbeing has made tremendous progress
over the last two decades. Genetic effects on subjective wellbeing (SWB) are well established, and metaanalyses
reveal average heritabilities in the 32-41% range. Behavior genetic studies also provide strong
evidence for the causal role of environmental factors in SWB. In this chapter we review exciting
developments within the intersecting fields of wellbeing and genetically informative research. We start by
elaborating on the concept of heritability and the basics of twin studies. The beauty of the twin study lies in
the potential to examine causal factors, without observing them, by the logic of a research design. Next, we
review findings of genetic and environmental influences on SWB, and the role of such influences in the
multivariate associations between different types of wellbeing, between wellbeing and ill-being, and
between personality and wellbeing. We also outline recent developments within molecular genetics, and
strategies to identify specific genes. A separate section addresses the issue of gene-environment interplay,
and we discuss concepts such as vantage sensitivity and differential susceptibility. Throughout the chapter,
we will seek to elaborate on what is known – and what is yet to be known.
Keywords: Genetic, Twin, Molecular genetics, Heritability, Wellbeing
To what extent, and in what ways, is wellbeing influenced by genes? What is the role and interplay
of genetic and environmental factors in wellbeing and illbeing? Is the genetic effect on wellbeing due to
personality-related genes? Which specific genes influence wellbeing? These are among the questions that
researchers have addressed in recent years – and for which we do have some answers and are searching for
more.
Recent meta-analyses have documented that the weighted average heritability of subjective wellbeing
(SWB) is in the range of 32-41% (Bartels, 2015; Nes & Røysamb, 2015; Vukasovic, Bratko, & Butkovic,
2012). Heritability is, however, not a fixed statistic. There is considerable heterogeneity across population
groups, measures and methods (Nes & Røysamb, 2015). There is also evidence of substantial heritability
for personality traits, and the genetics of wellbeing appear to be partly about personality genes (Keyes,
Kendler, Myers, & Martin, 2015; Weiss, Bates, & Luciano, 2008). Similarly, the genes that influence
wellbeing appear to be partly the same as those protecting against depression (Haworth, Carter, Eley, &
Plomin, 2017; Kendler, Myers, Maes, & Keyes, 2011; Nes, Czajkowski, Røysamb, Reichborn-Kjennerud,
& Tambs, 2008; Nes et al., 2013).
Behavior genetic studies reporting heritability estimates also provide strong evidence for the
substantial environmental effects involved. Causality of specific variables (e.g., life events) is generally
hard to prove in correlational studies, but genetically informative studies reporting a heritability of 40%
imply that 60% of the variance in wellbeing is caused by environmental factors, and random measurement
error. Despite considerable progress in estimating genetic influences on wellbeing, several pieces of
knowledge are still missing. Whereas behavior genetic studies, using twin, family and adoption designs,
have been able to estimate total genetic effects (heritability), molecular genetic studies have so far had
limited success in identifying the specific genetic variants involved (Okbay & al., 2016; Weiss et al., 2016).
However, with collaborative efforts, extensive sample sizes and new technology for analyzing DNA, the
field of molecular genetics is moving ahead at high speed.
In this chapter we aim to review some of the exciting recent findings on the role of genetic and
environmental factors in wellbeing. We start by clarifying the concept of heritability, and move on to
outline the logic involved in estimating heritabilities from twin and adoption studies. Next, we review
findings pertaining to the role of genes and environment in wellbeing, and in the associations between
wellbeing, illbeing and personality traits. Are the observed relationships between such phenotypes due to
shared genes, shared environments or both? Next, we outline recent findings and prospects from molecular
studies, and finally we address various types of interplay between genes and environment.
Heritability - What it is (Not) About.
What is the heritability of the number of fingers of human hands? Most of us have two hands and ten
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fingers, and we know that these features are genetic in origin. Without genes coding for hands and fingers
in the developing fetus, we would not have any. Yet, the heritability of the number of fingers on human
hands is probably quite low. How can that be? To understand the scientific concept of heritability ( h2) we
need a simple formula:
where Vg equals genetic variance, Ve is the environmental variance and Vtot represents the total variance
(sum of all genetic and environmental effects). Thus, heritability is the proportion of the total variance that
is due to genetic variance.
Now, returning to the number of fingers, in general there is not much variance in this figure. If
everybody have ten fingers the variance is zero and it would not be meaningful to estimate the heritability
(also, mathematically, division by zero is undefined). However, some people do not have ten fingers. This
is usually due to accidents, which mostly are environmental in origin. The genetic variance in number of
fingers is minimal. With the exception of rare mutations that generate other numbers of fingers, varying
finger-numbers are due to environmental factors. Thus, the larger part of the total variance is
environmental, rather than genetic, in origin – and therefore the heritability is low. This also implies that if
the environmental variance for any trait is reduced in a population (e.g., less social inequalities or less
accidents), the heritability increases, and with rising environmental variance (e.g., by introduction of an
intervention), heritability will be reduced.
As heritability is about variance we need to keep in mind that it is a population statistic. It is not
meaningful to translate a heritability estimate directly into an estimate of the genetic contribution to a single
person’s traits – regardless of whether the traits are wellbeing, personality, body height or number of
fingers. For example, human body height has a heritability around 80% (Bergin et al., 2012; Silventoinen,
Kaprio, Lahelma, & Koskenvuo, 2000; Yang et al., 2010). However, that does not mean that a person with
height 170 cm has received 136 cm (170x80%) from her genes and 34 cm (170x20%) from the
environment. Correspondingly, if the heritability of wellbeing is about 40% it does not mean that 40% of
your wellbeing is genetic and 60% is environmental. In each one of us, the genetic and environmental
factors have operated together in creating a unique blend that cannot be partitioned into percentages of
effects.
In this sense, heritability is an estimate of explained variance in the same way that we can estimate
the variance of wellbeing accounted for by personality traits or life events. When we obtain explained
variance (R2) in a multiple regression analysis, this parallels the estimate of heritability – the variance
accounted for by genetic factors. It does not make sense to say that a certain life event explains for example
30% of a single individual’s wellbeing. The same holds for genetic factors.
How then, may we envision the genetic effects on individuals without partitioning a person into
genetic and environmental effects? One useful thought experiment includes imagining a person with 99
other identical twins, that is, in total 100 genetically identical persons. All differences between these 100
people would necessarily be due to environmental differences, and this group of people would have a
certain mean, variance and total range of scores. Thus, the hypothetical wellbeing range among the 100
clones would represent the potential wellbeing range for each individual. In this sense, we all have a
genetically based wellbeing set-point (in the sense of the average of our own clones), and a range to
operate within (the range of our clones). Although this perspective involves a genetically based set-point,
note that most of the 100 people will not be at this exact point: roughly half will be above and half below.
This example may function as a basis for thinking about a person’s wellbeing range as rather wide, with
potential for both upward and downward movements. However, without the 99 other clones available, we
cannot know whether a particular person is actually below or above her own genetic midpoint.
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Figure 1 illustrates the effect of genetic and environmental factors on wellbeing. The latent factors
(ovals) represent additive genetic effects (A) and environmental effects (E), and the observed (rectangular)
variable represents wellbeing. In this illustration, all three variables are standardized (with mean=0 and
sd=1). The effect of the genetic factor is set to 0.60, implying a heritability of 36% (0.6x0.6=.36), and the
effect of the environmental factor is set to 0.80. Thus, in this scenario a person’s wellbeing is given by the
formula:
Wellbeing=0.60xA+0.80xE
A certain person X with a genetic disposition to happiness of -0.5 (i.e., 0.5 sd below the mean on
the latent genetic variable A) but a favorable environment of +0.5 would end up with a wellbeing score of
+.10 (i.e., 0.6x-0.5 + 0.8x0.5), whereas a person Y with a happy disposition of +1.0 but a total negative
environmental load of -1.0 would have a wellbeing score of -0.20 (0.6x1.0 + 0.8x-1.0). Now, this
illustration represents a basic model as it only includes an additive genetic and a non-shared environmental
variable, and have disregarded potential correlations and interactions between them. We will return to the
notions of gene-environment interplay later.
How to Estimate Heritability
The elegance of twin studies lies in their potential to estimate genetic and environmental effects by
the logic of a design, without necessarily measuring any specific genes or given environments (Plomin,
DeFries, Knopik, & Neiderhiser, 2013; Røysamb & Tambs, 2016). In the classic twin design we collect
data from monozygotic (MZ) and dizygotic (DZ) twins, and the observed similarity within pairs among MZ
versus DZ twins represent a core element of information. MZ twins share 100% of their genes, whereas DZ
twins share on average 50% of segregating genes, and we use this knowledge to test hypotheses about the
influence of four major types of factors: Additive genetic factors (A) are correlated at unity among MZ
twins and at 0.5 in DZ twin pairs. Non-additive genetic influences (D) also correlate 1.0 in MZ twins, and
0.25 (or below) in DZ twins. The non-additive effects include dominance (hence D), interaction at a certain
locus whereby one allele (genetic variant) is dominant, and epistasis, which involves interaction between
alleles at different chromosomal loci. Shared or common environmental factors (C) are per definition
shared by the twins in a pair, for both MZ and DZ twins, and correlate at unity. C effects are often, but not
necessarily, expected to reside within the family. Note that C factors reflect environmental influences
leading to similarity among twins. A certain parenting style or event in a family may or may not represent a
C factor, depending on whether the effect on the twins is the same or different. Finally, non-shared
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environmental influences (E) include all factors that contribute to twin differences (including random
error), and are therefore uncorrelated between twins in a pair (Plomin et al., 2013).
Broad-sense heritability (H2) includes both additive (A) and non-additive (D) genetic effects,
whereas narrow-sense heritability (h2) includes additive effects only. A crude estimate of the heritability
(disregarding D-effects for now) can be calculated based on the difference in observed twin-cotwin
correlations across zyosity groups:
h2 = 2(rMZ – rDZ)
Thus, the heritability equals two times the difference between the MZ and DZ correlations.
Correspondingly, the shared environmental variance (C) is given by the formula
c2 = 2rDZ – rMZ,
and non-shared environmental variance (E) is resolved by
e2 = 1– rMZ.
These formulas can give important information about the magnitude of various effects, but more
sophisticated methods are used to test specific models and obtain measures of uncertainty.
Figure 2 illustrates a basic biometric model with the four latent factors, A, D, C and E, and one
observed wellbeing variable. Correlations between latent factors are shown for MZ and DZ twins. This is a
univariate twin model, in the sense that only one observed variable is analyzed, but measured in two twins.
The model can be tested as a structural equation model (SEM) in software such as Mplus, Mx or OpenMx
(Boker et al., 2011; Muthen & Muthen, 2017; Neale, 1996). The twin-cotwin correlations for the latent
factors, as shown in the figure, are fixed at the depicted values, for example in a two-group model with MZ
and DZ twins, and the paths a, d, c and e are estimated. Typically, nested submodels (e.g., an AE model)
are compared to full models (e.g., ACE) and the presence of the various latent factors is determined by the
fit and the comparison of the different models. Note that the full ADCE model is underidentified in the
classic twin design, which includes only MZ and DZ twins reared together. Therefore, the full model is
typically an ACE, or ADE, model – depending on the structure of correlations.
The basic univariate model may be extended along several lines. First, sex-differences may be
examined by testing for quantitative (different magnitude of effects for women and men) or qualitative
(partly different genes operating for women and men) effects (Neale, Røysamb, & Jacobson, 2006;
Røysamb, Harris, Magnus, Vitterso, & Tambs, 2002). Testing of quantitative sex-differences can be
performed in samples including only same-sex twins, whereas qualitative differences require opposite-sex
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DZ twins as well. Second, the univariate model may be extended into different multivariate models,
including two or more phenotypes. The multivariate models comprise several subtypes, such as
independent factor models, common factor models, phenotypic causality models, and Cholesky models
(Neale et al., 2006; Røysamb & Tambs, 2016), which partly differ in their underlying assumptions.
However, all may be informative regarding the shared and unique contributions of genes and
environmental factors to a set of variables. For example, we know that wellbeing (e.g., life satisfaction) and
illbeing (e.g., depression, anxiety) are negatively correlated in the population (Haworth et al., 2017; Nes et
al., 2008; Nes et al., 2013). Twin studies may help resolve the question about whether this association is
due to shared genetic factors or shared environmental factors (more about this below).
Genetically informative designs comprise twin (including MZ and DZ twins), family (including
relatives of varying genetic relatedness, and step-relatives) and adoption (with or without twins involved)
studies. The classic twin study represents the core logic and is the most widely used design. It has been
criticized for limitations in distinguishing genetic and common environmental effects that contribute to
similarity between twins, but a number of findings have been replicated in for example adoption studies,
thus lending support to the general twin study findings (Plomin et al., 2013).
A recent meta-analysis of heritability estimates in Nature Genetics (Polderman et al., 2015) covered
more than 2700 twin studies based on altogether 14,558,903 twin pairs, published during the last fifty
years. The study included more than 17,000 phenotypes or traits and reported almost all of these to be
heritable. Although genetic effects vary across traits, substantial heritabilities have been reported for
phenotypes such as height and weight, metabolic functions, blood pressure, longevity, educational
attainment, personality traits, drug use, mental disorders and wellbeing (Boomsma, Busjahn, & Peltonen,
2002; Plomin et al., 2013; Plomin, DeFries, Knopik, & Neiderhiser, 2016; Polderman et al., 2015). Thus,
wellbeing is a human condition that falls into a widely-observed pattern of both substantial genetic and
environmental origins.
Heritability Findings – What Do We Know?
A fair number of studies have reported on the genetic and environmental influences on SWB. The
heritability estimates commonly range between 25 and 50% across the different studies (Bartels &
Boomsma, 2009; Eid, Riemann, Angleitner, & Borkenau, 2003; Nes, Czajkowski, & Tambs, 2010; Nes,
Røysamb, Tambs, Harris, & Reichborn-Kjennerud, 2006; Røysamb et al., 2002; Røysamb, Tambs,
Reichborn-Kjennerud, Neale, & Harris, 2003; Schnittker, 2008; Stubbe, Posthuma, Boomsma, & De Geus,
2005; Tellegen et al., 1988). The remaining variation tends to be accounted for by nonshared, rather than
shared environmental influences. Table 1 gives a selection of estimates of genetic and environmental
influences on SWB and closely related phenotypes.
Three meta-analyses have reported weighted average heritability estimates for wellbeing. First,
Vukasovic et al. (2012) examined nine independent studies and reported an average heritability of 39%.
Second, Bartels (2015) analyzed ten independent samples including a total of 55,974 individuals and
obtained a general heritability estimate of 36% for SWB. She also constrained a set of analyses to life
satisfaction, obtaining an estimate of 32%. Finally, Nes and Røysamb (2015) included 13 unique studies
from seven countries, and used structural equation modelling to estimate average heritability. The best
fitting model yielded a heritability of 40% in the total sample, and 41% in a more restricted sample (e.g.,
excluding outliers). These three meta-analyses varied in the inclusion criteria used, the studies included,
and the statistical approaches adopted. Yet, they converge on finding average heritabilities in the range of
32 to 41%.
Notably, Nes and Røysamb (2015) also examined the variability of heritability estimates across
studies, and found a significant and substantial deviation from homogeneity. Heritabilities varied beyond
the level expected by random fluctuations, with roughly 70% of the variability due to true heterogeneity.
Thus, the study confirmed the theoretical notion that heritability is not a fixed statistic, but can vary across
populations and groups, and will depend on the range of environmental factors involved and the measures
studied. This finding also accords with several studies reporting evidence of heritability-environment
interaction (Johnson & Krueger, 2006; Nes, Røysamb, Harris, Czajkowski, & Tambs, 2010; van der Aa,
Boomsma, Rebollo-Mesa, Hudziak, & Bartels, 2010).
Some of the biometric studies have shown the heritability of SWB to primarily reflect additive
genetic effects (Nes et al., 2006; Røysamb et al., 2003; Schnittker, 2008). Other studies have indicated
mainly non-additive genetic effects (Lykken & Tellegen, 1996; Stubbe et al., 2005). Perhaps the largest
biometric study of SWB to date, combining data from 6,600 twins and 54,450 nuclear family members,
reported both additive and non-additive genetic influences. Broad-sense heritabilities were estimated to be
36 and 33 percent for males and females, respectively (Nes, Czajkowski, et al., 2010). This large-scale
study also suggested additional effects such as assortative mating and a shared twin environment, the latter
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accounting for 8% of the total environmental variation.
Table 1.
Selected key twin studies of genetic and environmental influences on subjective wellbeing
First
author
Year Phenotype Measure N Age h2
c2
e2
Tellegen 1988 WB MPQWB 804 .40-.48 .13-.22 .38-.40
Røysamb 2003 SWB SWB-index 6576 18-31 .44 - .56
Stubbe 2005 LS SWLS 5668 14-88 .38 - .62
Nes 2008 LS LS-item 8045 18-31 .17-.35 .00-.11 .66-.71
Schnittker 2008 Happiness PA-scale 2330 25-74 .36 .06 .57
Weiss 2008 SWB SWB-index 1946 25-74 .22 - .78
Caprara 2009 LS SWLS 856 23-24 .59 - .41
Bartels 2009 SWB SWLS, Cantril, SHS 5024 13-28 .36-.47 - .53-.64
Keyes 2010 Emo.WB PA-index, LS 1386 m=45 .50 - .50
DeNeve 2012 LS LS-item 1098 .33 - .67
Franz 2012 LS, WB LS-item, MPQWB 1226 51-55 .19-.35 .02 .63-.79
Haworth 2017 Happiness
LS
SHS, BMSLSS 9463 16 .34-.44 .06-.11 .45-.60
BMSLSS=Brief Multidimensional Student Life Satisfaction Scale; SWLS=Satisfaction With Life Scale;
SHS=Subjective Happiness Scale; MPQWB=Multidimensional Personality Questionnaire Well-being scale;
PA=Positive Affect; WB=Wellbeing; SWB=Subjective wellbeing; LS=Life satisfaction; h 2=heritability;
c2=common/shared environment (C); e2=non-shared environment (E).
(Bartels & Boomsma, 2009; Caprara et al., 2009; De Neve, Christakis, Fowler, & Frey, 2012; Franz et al., 2012;
Haworth et al., 2017; Keyes, Myers, & Kendler, 2010; Nes et al., 2008; Røysamb et al., 2003; Schnittker, 2008;
Stubbe et al., 2005; Tellegen et al., 1988; Weiss et al., 2008)
The collective findings thus indicate that SWB is moderately heritable with differences in the
magnitude of the heritability estimates likely to be related to the specific constructs explored, the
psychometric qualities and the given research design, including the number and type of respondents (i.e.,
relative classes) – and the environmental context.
As noted above, the non-genetic influences on SWB primarily reflect non-shared environmental
effects, and when not accounted for; measurement error (Bartels & Boomsma, 2009; Nes et al., 2006;
Røysamb et al., 2003). Shared environmental influences appear to be minor, or entirely negligible. Thus,
family resemblance for SWB appear to be mainly due to shared genes, and not to shared environments. It is
important to note, however, that family factors might still impact on SWB. Rather than undermining the
importance of family features, the biometric findings imply that environmental influences do not generally
operate in a family-by-family fashion (e.g., parenting styles or socioeconomic conditions do not have
general effects), but rather on an individual-by-individual basis (i.e., affect the different siblings in a family
differently). Importantly, negligible influences from shared environments may primarily indicate that
shared environmental influences are very small and smaller than the non-additive genetic effects.
How do the findings of heritability fit with findings of substantial national differences in wellbeing
(Diener, Helliwell, & Kahneman, 2010; Helliwell, Layard, & Sachs, 2017; Morrison, Tay, & Diener, 2011;
Oishi & Schimmack, 2010; Tay & Diener, 2011)? It should be noted that heritability is a statistic referring
to a variance component within a certain population, and as such has no say on differences across
populations. It seems reasonable to assume that national differences in wellbeing are mainly environmental
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in origin (e.g., economy, governance, health care, education, culture, peace and safety). Thus, when
including the cross-national differences in the equation, the total environmental variance will increase, and
the ‘global heritability’ of wellbeing should consequently be reduced. Today there is also limited
knowledge about systematic interaction effects between cultural and societal factors on the one hand and
genetic factors on the other. Future studies should aim to disentangle how genetic expression is moderated
by environmental factors also at the national and cultural level.
Multivariate Findings: Shared and Unique Factors
The same set of genes and environmental factors may underpin several correlated characteristics
simultaneously. In fact, most genes involved in complex traits (e.g., SWB) tend to have pleiotropic effects affecting
a number of different characteristics, for example due to coding for “endophenotypic”
neurobiological mechanisms (e.g., neurotransmitter systems) involved in different characteristics.
Multivariate biometric designs permit us to decompose the correlation between variables (e.g., SWB and
extraversion) into genetic and environmental sources. They also allow us to quantify the extent to which the
genetic and environmental variation is specific to one characteristic only (e.g., SWB), and the extent to
which it is shared by other characteristics (e.g., extraversion, depression). Such commonality or specificity
is reflected in the genetic (rg) and environmental (re) correlations between the given characteristics. The rg
and re may differ substantially from the genetic and environmental contributions to the covariance. For
example, the genetic influence on two given traits may be minor (i.e., low genetic covariance). Yet, the
genetic correlation could be very strong, indicating that the same genetic sources affect both traits (although
weakly).
Partly overlapping genetic factors have been indicated for different wellbeing indicators. For
example, by means of an extended twin-sibling design, Bartels and Boomsma (2009) reported correlations
between four common SWB indicators (quality of life in general, quality of life at present, life satisfaction,
subjective happiness) to largely reflect shared genes (i.e., the same genetic core). Partly overlapping sets of
genes have also been reported for emotional, social, and psychological wellbeing (Keyes et al., 2010), and
for self-esteem, SWB, and optimism (Caprara et al., 2009). In the latter study, the genetic correlations ( rg)
were estimated to range from 0.80 (self-esteem and SWB) to 0.87 (SWB and optimism). The environmental
influences were considerably more distinct, with environmental correlations (re) ranging from 0.18 to 0.32.
What about the association between SWB and psychopathology? Can SWB inform us about
vulnerability to mental illness? The correlations between SWB and mental illness tend to be moderate and
inverse, typically around -0.50 (Franz et al., 2012; Kendler, Myers, Maes, et al., 2011; Nes et al., 2008; Nes
et al., 2013; Okbay et al., 2016). Moreover, a meta-analysis reported an average heritability of depression
of 37% (Sullivan, Neale, & Kendler, 2000), thus paralleling that found for SWB. However, similar
magnitudes of heritability for different characteristics do not per se inform us about the degree of shared
genetic factors.
Biometric studies have indicated a partly different genetic and environmental etiology for positive
and negative affect (Baker, Cesa, Gatz, & Mellins, 1992) as well as for optimism and pessimism (Plomin et
al., 1992). A few studies have examined the genetic and environmental sources underpinning the negative
associations between mental health problems and SWB and closely related constructs. Most of these
studies are based on adult samples with mental health problems such as internalizing problems or disorders
(i.e., anxiety and depression). For example, Vinberg, Bech, Kyvik, and Kessing (2007) investigated quality
of life in first-degree relatives of patients with affective disorder, finding quality of life to be impaired in
twins with an affected co-twin. Nes and colleagues examined the etiology underpinning the covariance
between SWB (i.e., life satisfaction) and self-reported symptoms of anxiety and depression (Nes et al.,
2008), and later on the association between dispositional SWB and life time major depression (Nes et al.,
2013). In addition, Kendler, Myers, Maes, et al. (2011) examined the generality and specificity of
etiological influences on the association between internalizing psychopathology (MDD, generalized anxiety
disorder, panic attacks) and mental well-being (MWB), comprising emotional, psychological, and social
well-being. All of these studies show a moderate inverse correlation between SWB and internalizing
mental health problems, a substantial but far from complete overlap in genetic factors, and modest
commonality of environmental influences (Kendler, Myers, Maes, et al., 2011; Nes et al., 2008). Thus, the
genes that contribute to wellbeing are only partly the same as those protecting against depression. However,
environmental influences with a long-term impact on vulnerability to internalizing problems seem to
influence SWB to a greater extent than environmental influences with mainly transient effects (Kendler,
Myers, Maes, et al., 2011).
Although most studies to date are based on adults, a recent study of 4,700 pairs of 16-year-old
twins reported similar findings (Haworth et al., 2017). This recent study has also indicated different
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patterns of overlap for life satisfaction and subjective happiness. More specifically, the phenotypic
correlations between the constructs were highly similar. Yet, the authors observed stronger genetic links
between life satisfaction and depression, than between subjective happiness and depression. About 45% of
the genetic influences on life satisfaction and 70% of the genetic influences on subjective happiness were
independent of the genetic factors underpinning internalizing symptoms. In line with previous studies, nonshared
environmental influences were also in this study largely specific to each particular trait. Thus,
certain environmental factors influence illbeing, whereas another, mostly independent set of environmental
factors contributes to (low) wellbeing. The multidimensional nature of the etiological influences on
wellbeing, and the overlap with mental health problems, has also been reported in a smaller study based on
613 pairs of middle-aged male twins (Franz et al., 2012).
Overall, the biometric studies thus indicate that SWB do not merely constitute the “other end” of a
genetic liability to internalizing problems such as anxiety and depression. Some genetic factors for SWB
convey protection against internalizing psychopathology, but high levels of SWB also reflect independent
genetic sources associated with healthy, or salubrious psychological functioning. This specificity in
etiological influences on SWB and internalizing problems suggests that different interventions might be
needed for healing problems and promoting wellbeing, and that interventions may need to target partly
different biological pathways.
The etiology underpinning associations between SWB and other mental health problems, is
scarcely studied. Nevertheless, one study investigated common risk factors for (low) mental wellbeing and
externalizing psychopathology (EP), the latter measured as a history of alcohol-related problems and
smoking behavior last year (Kendler, Myers, & Keyes, 2011). The two latent constructs (i.e., EP and
mental wellbeing) were modestly correlated (r = -0.28) in this study. The genetic and environmental risk
factors for EP were negatively associated with wellbeing, and accounted for 7% and 21% of its genetic and
environmental influences, respectively. Of note, when adding recent (last year) internalizing
psychopathology (IP) to the model (i.e., controlling for genetic risk factors common to IP and EP), the
genetic factors related only to EP (5% of the total genetic variation) were associated with higher wellbeing,
while the unique environmental risk factors for EP were related to lower wellbeing. One tentative
explanation of the positive genetic association between the unique EP factor and wellbeing could involve
an underlying genetic disposition to for example extraversion that might contribute to both characteristics.
Further, the authors suggested that shared genetic risk factors to EP and IP reflect genetic risk for EP
associated with the negative consequences of substance use commonly decreasing wellbeing – such as
anxiety and depression. The corresponding environmental influences were suggested to reflect
psychosocial adversities that contribute to drug use and misuse, and in turn compromise wellbeing.
Personality and Wellbeing
What is the relationship between personality traits and wellbeing? To what extent do people’s
extraversion and neuroticism influence their happiness and life satisfaction? And what is the role of genetic
and environmental factors in these associations?
Personality psychology focuses on a number of different tendencies and traits. Within the trait
perspective, the five factor model (FFM) of personality has obtained a dominant role. The Big Five factors
comprise five broad personality traits, including neuroticism, extraversion, openness to experience,
agreeableness and conscientiousness. A number of studies have examined relations between these
personality traits and wellbeing, and already in 1998, a meta-analysis concluded that in particular
neuroticism is a strong (negative) predictor of life satisfaction and happiness (DeNeve & Cooper, 1998). In
addition, extraversion and partly conscientiousness show substantial relations to wellbeing whereas the
findings involving agreeableness, and in particular openness, are mixed and mainly indicate weak or
negligible associations (DeNeve & Cooper, 1998; Lucas & Diener, 2008; Vitterso, 2001).
The importance of personality for wellbeing contrasts findings of the limited effect of demographic
and background variables. In general, age and sex differences in wellbeing are usually minor or totally
absent, and variables such as educational level, income or geographical location appear to explain
considerably less variance in wellbeing than personality traits do (Diener, Suh, Lucas, & Smith, 1999;
Lucas & Diener, 2009). Also, whereas the impact of negative and positive life events (e.g., divorce,
accidents, winning a lottery) are mostly short-lasting, the associations between personality and wellbeing
tend to be enduring.
Personality traits are influenced by genetic factors, and studies have shown substantial heritabilities
(Boomsma et al., 2002; Jang, Livesley, & Vernon, 1996; Vassend, Røysamb, Nielsen, & Czajkowski,
2017). Given the genetic influence on both personality traits and wellbeing, and the phenotypic
associations between them, it seems pertinent to address the question of what role genes and environment
play in generating relations between the two sets of characteristics. Is the heritability of wellbeing due to
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personality related genetic factors? Are there unique genetic influences on wellbeing, independent of
personality? Are there environmental factors that influence both personality traits and wellbeing?
A few recent studies have addressed these questions. Weiss et al. (2008) found that both genetic and
environmental factors contributed to the relations between wellbeing and three of the Big Five traits,
namely neuroticism, extraversion and conscientiousness. However, the authors found no unique genetic
effects on wellbeing. That is, the entire heritability of wellbeing was accounted for by genetic factors in
personality. Correspondingly, Hahn, Johnson, and Spinath (2013) reported shared genetic factors for
personality and wellbeing. Associations were found for extraversion and neuroticism, but not
conscientiousness, and the personality-related genetic factors explained the entire heritability of wellbeing.
Finally, Keyes, Kendler, Myers, and Martin (2015) studied a global latent factor of flourishing, finding
substantial genetic overlap with personality. However, contrasting the two previous studies, the authors also
found a unique genetic influence on wellbeing, unrelated to personality traits.
Some studies have also moved beyond the general level of the five broad factors and examined
associations between personality facets and wellbeing. For example, given that extraversion is related to
wellbeing, researchers have investigated which particular facets (e.g., warmth, sociability, novelty seeking,
assertiveness, positive emotions), are the most important drivers of this association. One study found the
facet of positive emotions in extraversion, and the facet of depression in neuroticism to be consistent
predictors of life satisfaction (Schimmack, Oishi, Furr, & Funder, 2004). More recently, Quevedo and
Abella (2011) reported depression, but not positive emotions, to be important, and also found a unique
association for the facet of achievement striving in conscientiousness. Next, Albuquerque, de Lima, Matos,
and Figueiredo (2012) replicated the finding of depression and positive emotions as central, but also found
an effect from the facet of vulnerability in neuroticism.
Whereas these studies examined associations between personality facets and wellbeing at the
phenotypic level, ongoing efforts try to disentangle the role of genes and environment in the facetwellbeing
relations. A recent study identified four facets that were particularly important for wellbeing,
namely anxiety and depression in neuroticism and positive emotions and activity in extraversion
(Røysamb, Nes, Czajkovski, & Vassend, 2017; Røysamb, Nes, & Vassend, 2014). These four facets
accounted for the larger part of the genetic variance in life satisfaction, but there was also a unique genetic
factor in wellbeing. Environmental factors also contributed to the associations between personality facets
and wellbeing, and were the major source of unique variance in wellbeing.
The studies on personality facets and wellbeing are somewhat divergent on which specific factors
that contribute uniquely to wellbeing, and this divergence is probably partly due to different measures
being used, different levels of facets, and different populations being sampled. Still, the studies seem to
replicate and converge on pointing to the depression facet of neuroticism and positive emotions in
extraversion as important. It is noteworthy that out of 30 facets in the NEO-PI model, these two basic
emotional tendencies seem more important for wellbeing than facets such as sociability (gregariousness),
competence, warmth, excitement seeking, self-discipline and trust.
Stability and Change
Our levels of wellbeing fluctuate, but tend to be relatively stable over time, with substantial variance
shared with personality traits. The stable variance in wellbeing typically amounts to approximately 50% of
the total variation, and the heritability of this stable component is usually high – in the 70% to 90% range
(Lykken & Tellegen, 1996; McGue, Bacon, & Lykken, 1993; Nes et al., 2013; Nes et al., 2006). As such,
the heritability of stable, or dispositional wellbeing resembles that of strongly heritable characteristics like
human body height (Silventoinen et al., 2003) and adult intelligence (Haworth et al., 2009). Biometric
studies have also shown the genetic influences on wellbeing to be fairly stable, reporting cross-time
correlations between the genetic factors (rg) in the 0.8 to 0.9 range. By contrast, corresponding correlations
for environmental factors (re) are reported in the 0.2 to 0.3 range (Nes et al., 2006; Paunio et al., 2009).
How do findings of (genetic) stability fit with evidence of changeability? National comparison
studies have indicated quite substantial population changes over time (Diener, Tay, & Oishi, 2013;
Helliwell et al., 2017; Veenhoven, 2009). Wellbeing levels also change in response to formative events
(Dyrdal, Røysamb, Nes, & Vitterso, 2011; Luhmann, Hofmann, Eid, & Lucas, 2012; Nes et al., 2014),
psychotherapy and interventions (Bolier et al., 2013; Lyubomirsky & Layous, 2013; Seligman, Steen,
Park, & Peterson, 2005). Longitudinal twin studies show that environmental factors account for the major
share of change variance, in the 80-90% range (McGue et al., 1993; Nes et al., 2006). Interestingly, as the
remainging change is due to genetic factors, these findings suggest that partly different genes affect
wellbeing at different ages and life stages.
Interventions have proved effective despite substantial heritability and stability. A recent twin study
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by Haworth et al. (2016) showed significant improvements in wellbeing along with reductions in
internalizing problems over a 10-week intervention involving kindness and gratitude tasks. The authors
reported increased wellbeing despite high heritability (48%) and the same genetic influences were operating
throughout the intervention. The overall magnitude of environmental influences also remained stable, but
new non-shared environmental influences emerged over time in response to the intervention. In summary,
wellbeing is both heritable and changeable (Røysamb, Nes, & Vitterso, 2014), and whereas genetics play a
major role in the stability of wellbeing, environmental factors play an equally important role in generating
change.
Molecular Genetic Findings
Development and refinement of molecular genetics in the 1990s led many to assume that specific
genes with causal effect on happiness, health and illness would be easily identified. These expectations
have not been met, perhaps primarily due to such traits being multi-factorial and polygenetic (i.e., many
genes with differing effects are involved in genetic variation) with risk and protective factors acting in a
complex, probabilistic fashion. Additionally, complex characteristics like wellbeing are likely to be
pleiotropic (i.e., the genes are involved in multiple functions such as biochemical processes throughout the
brain). Due to very modest effects, genetic heterogeneity, and intricate patterns of interplay with
environmental influences - as well as psychometric challenges; the relationship between the genotype (i.e.,
genetic constitution) and the phenotype (i.e. observed characteristic) is far from understood. Nevertheless,
molecular genetics have made immense progress over the past few years, and wellbeing is now clearly
placed on the molecular genetic research agenda and examined by means of a number of different
strategies and techniques.
Molecular genetics examine the structure and function of specific genes, aiming to trace the causal
pathways from the DNA to a given phenotype (e.g., SWB) using a multitude of research strategies.
Traditionally, molecular genetics employed linkage analyses and candidate gene association studies, and
SWB has been studied using these methods. For example, by means of a linkage design, Bartels et al.
(2010) reported a signal at the end of the long arm of chromosome 19 and a second suggestive linkage
peak at the short arm of chromosome 1 for SWB measured with the Subjective Happiness Scale. However,
the sample was fairly small and the linkage peaks were not clearly significant.
Several candidate gene studies have focused on the 5-HTTLPR (associated with decreased
availability of the serotonin transporter protein) and suggested a link between the neurobehavioral effects
of the 5-HTTLPR and enhanced sensitivity to motivationally relevant stimuli. Recent reports also suggest
that the short 5-HTTLPR variant is likely to confer heightened sensitivity to both negative and positive
stimuli (Beevers et al., 2011; Belsky et al., 2015; Belsky & Pluess, 2009b; Fox, Zougkou, Ridgewell, &
Garner, 2011). The “short” variant might therefore constitute a plasticity factor rather than a risk factor,
coding for a general sensitivity to the environment.
Genome-wide association studies (GWAS) constitute a widely-used approach. GWAS are not
hypothesis driven and commonly sequence all or most of the genome, usually focusing on correlations
between particular traits (e.g., SWB) and common gene variations (i.e., polymorphisms), or structural
variations in the DNA such as copy number variations (CNVs). GWAS usually test for a million genetic
markers and permit scanning the whole genetic sequence with simplicity and low cost, and may thus
include a large number of participants. In a recent GWAS of SWB (n = 298,420), depressive symptoms (n
= 161,460), and neuroticism (n = 170,911), Okbay et al. (2016) identified three variants associated with
SWB, two associated with depressive symptoms, and 11 associated with neuroticism. These findings
support the view that GWAS may successfully identify genetic associations with large sample sizes.
However, mixing of different measures make the discovered associations somewhat difficult to interpret.
The heritabilities estimated in this study were based on specific genetic variants, or single-nucleotide
polymorphisms (SNPs) - and were also quite low (0.04 for SWB, 0.05 for depressive symptoms, and 0.09
for neuroticism). Overall, the effect sizes reported in this GWA study imply that to account for even a
moderate share of the heritability estimated in twin studies, hundreds - or perhaps more likely thousands of
genetic variants will be required.
High genetic correlations (rg > .75) between SWB, positive affect, neuroticism, and depressive
symptoms suggest a common, or partially shared etiology. By means of a multivariate genome-wide metaanalysis
(n= 958,149) of these four traits - collectively referred to as “the well-being spectrum”, the authors
reported 63 significant independent signals, of which 29 were not previously identified (Baselmans et al.,
2017).
Genetic influences for SWB have also been examined using Genome-wide Complex Trait Analysis
(GCTA), which allows for estimation of the variance accounted for by all the common SNPs on the
genome. Using this method, Rietveld et al. (2013) reported that up to 18% of the variance in SWB can be
293
explained by cumulative additive effects of genetic polymorphisms that are frequent in the population.
Other contemporary methods include the use of polygenic scores, resembling a sum or factor-score for
multiple genetic loci and their associated weights. Polygenic scores may allow us to test genetic overlap
between different dimensions of wellbeing, to detect and control for genetic confounding in the outcomes,
and to explore gene-environment interaction (Plomin, 2013; Weiss et al., 2016).
Yet another molecular genetic strategy using RNA transcripts as outcomes (i.e., “expression
profiling”, “transcriptome profiling”) has been used to examine SWB. Genes which are transcribed from
genomic DNA (i.e., transcriptome) constitute an important determinant of cellular function. Using such
procedures, Fredrickson et al. (2013) have reported divergent transcriptional response to adversity (CTRA;
pro-inflammatory, anitviral and antibody-related genes) for hedonic and eudaimonic wellbeing despite the
two constructs being highly correlated, suggesting that the two types of wellbeing engage distinct gene
regulatory programs despite similar effects on overall wellbeing. These findings have been subject to
heated debate however (Brown, MacDonald, Samanta, Friedman, & Coyne, 2014), but have been partly
replicated (Fredrickson et al., 2015).
In summary, different genetically informative designs have provided somewhat divergent estimates
of the genetic influence on wellbeing. First, twin studies (and adoption/family studies) typically yield
heritability estimates in the 25-50% range. Second, genome-wide complex trait analysis, examining
genome similarities in unrelated individuals, report heritabilities based on common polymorphisms up to
18% (Rietveld et al., 2013). Third, genome wide association studies, so far have only identified specific
genetic variants that explain 4% of the variance in wellbeing (Okbay et al., 2016). The apparent
discrepancy between quantitative genetic studies and molecular genetic studies is often referred to as
missing heritability (Manolio et al., 2009; Plomin, 2013; Yang, Zeng, Goddard, Wray, & Visscher, 2017).
Why do molecular genetic studies not find the same heritabilities as twin studies? Notably, only
quantitative genetic studies (twin/adoption/family studies) are able to capture the entire genetic effects,
including rare genetic variants, epistasis and dominance effects – and there is a general consensus that the
estimates from such studies are mostly valid (Manolio et al., 2009; Polderman et al., 2015; Visscher, Yang,
& Goddard, 2010). Possible explanations for the lower estimates found in molecular genetic studies include
the limited ability to examine non-additive effects, rare mutations, epigenetics, and a high number of tiny
effects. Note that the genome wide significance level is typically set at p<0.00000005, instead of the
ordinary p-levels of 0.05, 0.01 and 0.001. This is due to the excessive multiple testing involved, and
implies that huge sample sizes, in the range of hundreds of thousands of participants, are required to
identify small effects (Manolio et al., 2009; Okbay et al., 2016). Note also that missing heritability has a
certain parallel in ‘missing environment’. Although we know from twin studies that environmental factors
in total account for roughly 60% of the variance in wellbeing, and numerous studies have identified
correlates of wellbeing, we have limited evidence about which specific factors that are truly causally
related to wellbeing and thereby add up to this percentage.
The recent interest in the molecular genetic underpinnings of wellbeing testifies to the importance
of these fields. However, there are still few published studies, most findings have not, yet, been replicated,
and the scientific understanding of the molecular genetic mechanisms in SWB is rather limited, thus
awaiting new discoveries. Based on the combined findings from molecular and quantitative genetics it
seems fair to conclude that the total genetic effect on wellbeing is substantial. Yet there is no major
happiness gene that explains most of the heritability, but rather a high number of genetic variants, each with
very tiny effects, which appear to operate and interact in complex ways.
A Structural Model of Wellbeing and Illbeing
As outlined above there are substantial negative correlations between wellbeing and illbeing, and
genetic factors contribute to these associations (Franz et al., 2012; Nes et al., 2008). Yet, wellbeing and
illbeing are not necessarily polar opposites and a nuanced picture of relationships is emerging. Illbeing
comprises various conditions such as depression, anxiety, drug abuse, eating disorders and psychoses – and
the relations to wellbeing vary across disorders (Keyes, 2007; Nes et al., 2008; Ryff et al., 2006; Røysamb
et al., 2011).
Moreover, as the general field of wellbeing research has moved forward, a number of concepts and
terms have been launched. In addition to examining SWB, researchers have proposed terms such as
psychological wellbeing (Ryff, 1989; Ryff & Singer, 1996), mental wellbeing (Keyes et al., 2010), social
wellbeing (Keyes, 1998; Shapiro & Keyes, 2008), and a general distinction between hedonic and
eudaimonic wellbeing (Disabato, Goodman, Kashdan, Short, & Jarden, 2016; Goodman, Disabato,
Kashdan, & Barry, 2017; Ryan & Deci, 2001; Waterman, 2008). Here, we mainly refer the interested reader
to the relevant literature for these different concepts and types of wellbeing. Yet we see it fitting to
integrate some of the current knowledge into a general structural model, in order to illustrate some of the
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mechanisms of environmental and genetic factors.
Figure 3 shows a structural model of wellbeing and illbeing , also termed the Well/IllStaying/Moving
(WISM) model (Røysamb & Nes, 2016). This model is partly based on the circumplex
model of affect (Posner, Russell, & Peterson, 2005; Russell, 1980) and recent findings of relationships
between mental disorders and different types of wellbeing (Kendler, Myers, & Keyes, 2011; Nes et al.,
2013; Ryff et al., 2006).
The model involves two basic dimensions: One positive-negative dimension and one of stabilitychange.
Environments can be (or perceived to be) positive or negative to us, and may represent continuity
and stability, or development and change – with all shades of grey in between. Central to the model is the
notion that humans have various ideals, needs or goal states (Emmons & Diener, 1986; Lyubomirsky,
Sheldon, & Schkade, 2005; Oishi & Diener, 2001; Ryan, Huta, & Deci, 2008). We may experience the
presence of an obtained goal state (e.g., a university grade, a good relationship, or a home), in which we
are satisfied, happy and in harmony. This condition is termed well-staying. Sometimes we are not yet in
this state, but nevertheless moving towards it (e.g., climbing a mountain, applying for a job, dating a
wonderful person); we are in a process involving excitement, growth and fulfilling of potentials – thus we
are well-moving. In other situations we realize there are threats to our goal states (e.g., a potentially failed
exam, a dream-date meets someone else, or serious illness emerges); we experience fear, anxiety or anger,
and are basically ill-moving. Note that both well-moving and ill-moving are partly future-oriented. Finally,
when a goal state is lost or has vanished (e.g., failed exam, lost job, relationship break-up), we might
experience sadness, depression and hopelessness – a situation of ill-staying.
In this model, wellbeing comprises both well-staying and well-moving. Illbeing correspondingly
involves ill-staying and ill-moving. As we face life’s challenges and opportunities, we perceive and
respond to environmental factors (e.g., events, people, circumstances) that are seen as good or bad, and as
involving continuation of the current situation, or change. We all have a repertoire of evolutionary based
tendencies (e.g., fear, sadness, joy) with which we respond (Belsky & Pluess, 2009a; Hill & Buss, 2008;
Izard, 2009). However, there are also individual differences in the threshold for activation and in the
strength of response, and these differences seem to be partly genetic. Thus, finding a heritability of 40% for
SWB tells us about the genetic contribution to individual differences in seeking, creating and responding to
environmentally based life challenges and opportunities. As life happens, and is constructed, mastered and
celebrated, we all move around in this space of illbeing and wellbeing with the help of our genetic makeup.
A good life may involve movement mainly between the well-staying and well-moving areas. However,
some inevitable trips to the illbeing side might result in important turning-points, contrasts and sources of
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meaning, and thereby a potential return into the wellbeing sphere.
Gene-Environment Interplay
It is increasingly acknowledged that genetic and environmental factors are neither independent nor
static. Rather, the genetic and environmental factors transact and interplay throughout development.
Several types of gene-environment interplay are likely to be important for wellbeing. Heritabilityenvironment
interaction constitutes one type of such interplay and refers to environmental moderation of
genetic effects. This type of interaction has been indicated in several biometric studies of SWB. The
heritability of SWB has for example been shown to vary across gender (Nes, Czajkowski, et al., 2010;
Røysamb et al., 2002), socio-economy (Johnson & Krueger, 2006), marital status (Nes, Røysamb, et al.,
2010), and parental divorce (van der Aa et al., 2010). In one study, the genetic and environmental
contributions to SWB were indicated to vary across marital status in both men and women, with lower
heritability observed among the married (Nes, Røysamb, et al., 2010). Marriage or marital-like
relationships are thus associated with greater impact of environmental influences on SWB.
Another type of interplay is gene-environment interaction (GxE), which refers to interaction
between specific DNA variants and specific measured environments. A number of GxE studies and metaanalyses
(Karg, Burmeister, Shedden, & Sen, 2011; Kim-Cohen et al., 2006; Risch et al., 2009) have found
that individuals often differ quite markedly in how they respond to their environment depending on
whether they carry specific genes. Most such studies have investigated associations between specific
polymorphisms (e.g., 5-HTTLPR) and vulnerability to negative health outcomes (e.g., depression, conduct
disorder) given negative life circumstances (e.g., abuse, maltreatment) (Caspi et al., 2003; Moffitt, Caspi, &
Rutter, 2006). Recently more salubrious phenotypes have also been explored. The concept of vantage
sensitivity (Pluess & Belsky, 2011) indicate that some people for genetic reasons may benefit more than
others from positive life experiences. The related construct of differential susceptibility (Belsky, 1997;
Belsky & Pluess, 2009a) refers to some individuals being disproportionally susceptible to both negative
and positive environmental influences – thus they are particularly malleable or plastic. So, differential
susceptibility pertains to situations in which given factors - like specific genetic polymorphisms, may
increase risk of adversity (e.g., depression, anxiety) given a harsh environment, but may contribute to
particular benefits (e.g., optimism, wellbeing, self-esteem) given a positive and supportive environment.
The concept of gene-environment match-making (Røysamb, Nes, & Vitterso, 2014) builds on geneenvironment
interplay and suggests a pathway to increased wellbeing through pursuing and creation of
environmental conditions that allow for flourishing of genetic potentials. People have various (genetically
influenced) potentials, and these may be nourished and allowed to develop when matched with an
appropriate environment. For example, a person with a genetic talent for creativity or musicality would
benefit from creating and seeking environments that are conducive to these potentials. Such match-making
occurs naturally, for example when we choose to go into sports or academia or get new friends. However,
acknowledging the phenomenon also provides a basis for developing interventions and exercises that build
on the importance of such match-making. The notion of gene-environment match-making is a new concept,
awaiting further exploration. But it corresponds to the well-established diathesis-stress model of mental
disorders (Belsky & Pluess, 2009a; Monroe & Simons, 1991), which postulates that disorders occur as a
result of a genetically influenced vulnerability in combination with stressful life events. The diathesis-stress
model can be seen as focusing on gene-environment mismatch, and as such the match-making perspective
represents an antidote to this model.
Gene-environment interplay will commonly be concealed in the standard variance components (i.e.,
A, C, E). The same goes for another common type of gene environment interplay, namely geneenvironment
correlation (rGE), known as social selection in the developmental sciences and reverse
causation or confounding in epidemiology and refers to the fact that genetic factors tend to imply exposure
to a non-random selection of environments (i.e., the nature of nurture). rGE is usually classified as passive,
active, and evocative (Scarr & Weinberg, 1983). Individuals tend to inherit their parents’ genes and
environment and these are likely to reinforce each other (passive rGE): children of happy and optimistic
parents inherit “positivity” genes and experience positive and supportive parenting (i.e., double
advantage). Individuals also actively select and shape their environments (active rGE), and in turn, these
environments reliably respond to their behavior (evocative rGE), amplifying or strengthening genetic traits
and dispositions. Happy, sociable, and optimistic children actively seek situations matching their partly
genetic positivity disposition (active rGE) - and tend to evoke more positive and supportive responses in
others (evocative rGE). Such active and evocative rGE will be incorporated in the heritability estimate.
That is, the effect is genetic in origin but the mechanism in play can be environmental. Consequently,
heritability reflects more than direct genetic effects.
Most biometric studies on wellbeing have not examined such niche building and co-responsive
296
processes explicitly (Johnson & Krueger, 2006; Krueger & Johnson, 2008). However, Krueger and
colleagues have shown that youths with high levels of positive emotionality tend to elicit positive regard in
their parents (Krueger, South, Johnson, & Iacono, 2008). Additionally, Kandler, Bleidorn, Riemann,
Angleitner, and Spinath (2012) have reported genetic factors to mediate associations between personality
traits (i.e., Extraversion and Openness) and controllable positive life events - and shown that genetic factors
play a major role in continuity and repetition of controllable positive events. The nature of nurture, and the
nurture of nature suggest fascinating ways in which genes and environments interact and correlate, and we
are only beginning to understand the processes involved.
Conclusion
Subjective wellbeing is influenced by genetic factors. There is solid evidence of substantial
heritability for different wellbeing components. Correspondingly, there is evidence for equally strong, or
stronger, causal effects of environmental factors. Nevertheless, despite these replicated findings (Bartels,
2015; Nes & Røysamb, 2015), heritability is not a fixed statistic. Rather, as a representation of explained
variance, heritability is found to vary significantly across studies – probably due to differing constructs and
measures, differing demographics, and differing environmental and cultural conditions.
Genetic factors seem to play an important role for associations between different aspects of
wellbeing, including life satisfaction and positive affect, as well as eudaimonic components. Likewise,
associations between wellbeing, illbeing and personality are also substantially influenced by genetic factors.
The genes that protect against depression are partly overlapping with those that contribute to wellbeing.
Despite exciting progress in studies of genetic and environmental effects on wellbeing, this is also a
field where new questions arise continuously. Future research is needed to identify specific genes, and
specific environments, involved in components of wellbeing and illbeing – and in their associations. We
need a more profound understanding of the mechanisms at play and the way the underlying factors interact.
As such, the intersection of genetics and wellbeing promises to be a tremendously exciting research area in
the years to come.
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Neuroscience and Well-Being
By Sanda Dolcos, Matthew Moore, & Yuta Katsumi, University of Illinois at Urbana-Champaign
Citation
Dolcos, S., Moore, M., & Katsumi, Y. (2018). Neuroscience and well-being. In E. Diener, S. Oishi, & L.
Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
Abundant evidence highlights the important role of personality traits, age, and social relationships in the
experience of subjective well-being. Experiential factors influence well-being, and evidence shows that
specific forms of training, such as physical exercise and mindfulness meditation, can produce strong and
enduring beneficial effects on well-being. These factors also shape the structure and function of our brains
throughout the lifespan, with fascinating implications for our well-being. However, understanding how
well-being is created (and changed) by our brains has only recently become the focus of neuroscientific
investigations. In this chapter, we review recent neuroscientific evidence revealing how the
neurocircuitries underlying personality traits (i.e., optimism, negative bias, self-esteem, extraversion, and
neuroticism), successful emotional aging, and social relationships (i.e., love and loneliness) contribute to
well-being, and how these circuits and systems are altered in chronic stress, anxiety, and depression.
Identifying the neural correlates of well-being can illuminate the processes that cause higher levels of wellbeing,
which, in turn, can inform promising training interventions that can induce neuroplastic changes and
help people live happier, healthier, and more successful lives.
Keywords: Affective biases, Neuroplasticity, Prefrontal cortex, Amygdala, Orbitofrontal cortex,
Ventral striatum.
The study of well-being has deep philosophical roots dating back to Aristotle, who proposed that
well-being has at least two components: hedonia and eudaimonia (Aristotle, 2009; Seligman, Steen, Park,
& Peterson, 2005). The term “hedonic” originates in the ancient Greek word “Hedone”, which means
pleasure. Hedonic well-being is exemplified in Ed Diener’s concept of subjective well-being, which
encompasses a combination of positive affect and life satisfaction. Thus, hedonic well-being highlights
positive affect as a defining feature of well-being. Eudaimonic well-being emphasizes aspects of a life
experienced as meaningful (with purpose, growth, etc.), and may or may not be accompanied by positive
affect. Studying the neural substrates of eudaimonic well-being is more challenging, as it is harder to define
life meaning and to link it to specific brain regions or networks. Therefore, in this chapter we will focus
mostly on the hedonic component of well-being.
Subjective well-being is influenced by a combination of individual characteristics, such as genetics,
personality traits (Lucas & Diener, 2008), and age (Carstensen et al., 2011), by psychosocial factors, such
as having a reasonable income (Diener & Oishi, 2000; Luhmann, Schimmack, & Eid, 2011), being married
(Diener, Gohm, Suh, & Oishi, 2000), or having meaningful social relationships (Cacioppo & Patrick,
2008), as well as by lifestyle-related factors, such as exercise (Hassmén, Koivula, & Uutela, 2000) and
engagement in mindfulness meditation (Carmody & Baer, 2008). Although a large amount of evidence
accumulated during the last decade has advanced our understanding of the roles of these factors in the
experience of subjective well-being, a number of essential issues remain unclear. Among these, a key issue
refers to the brain mechanisms supporting well-being, which could help clarify why some people experience
greater well-being than others, what might go wrong in affective disturbances, and how different types of
interventions can enhance brain function and well-being. Recent brain imaging advances enabling the
investigation of the neural correlates of positive emotions and overall well-being have provided essential
contributions to answering these fundamental questions.
The goal of this chapter is to review recent neuroscientific evidence revealing how the different
brain regions and systems contribute to well-being, how these are different in affective disturbances, and
how this knowledge about the brain can inform interventions aimed at helping people lead happier,
healthier, and more successful lives. We start with a general overview of the brain and how it works, while
also introducing some of the main brain regions typically involved in general emotion processing and in
positive emotions associated with well-being (pleasure, reward). Then, we examine how the structure and
function of these regions is different in people experiencing low levels of well-being, such as in stress and
affective disorders (anxiety and depression). Next, we review evidence pointing to links between various
brain regions and factors that contribute to well-being, including individual differences (i.e., personalityand
age-related) and psychosocial factors (i.e., social connectedness). Finally, we conclude with evidence
highlighting changes in the brain resulting from interventions focused on increasing well-being.
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Neural Correlates of Well-Being
Brief Introduction to How the Brain Works
All of our mental life—our thoughts, emotions, memories, and decisions—is brought about by the
physical substance of the brain. To understand how the brain enables well-being, it is necessary to first
understand the basics of its organization (or structure), function, and modes of communication. All brain
activity depends on the workings of neurons—cells that carry information from one place to another
through a combination of electrical and chemical signals. Information is transferred between neurons at
synapses, and is typically mediated by chemical signaling molecules, called neurotransmitters. The most
relevant neurotransmitters that facilitate the enjoyment of a wide range of experiences and the desire to
engage in these experiences are dopamine and opioids (the endogenous brain variety of opiates)
(Kringelbach & Berridge, 2010). The outer layer of the brain forms the cerebral cortex, which is
responsible for many of the attributes that we consider inherently human, like language, reasoning, and
imagination. The cerebral cortex is divided into four lobes. The frontal lobe, the front section of the brain,
is involved in the planning, guidance, and evaluation of behavior. The parietal lobe, located in the middle
section of the brain, is involved in integrating information from multiple sensory modalities within the
body, and information from memory. The temporal lobe, located in the bottom section of the brain, is
associated with auditory processing, memory, visual item recognition, and emotion. Finally, the occipital
lobe, located at the back of the brain, is mainly involved in processing visual information. Below the cortex,
in the center of the brain, are the subcortical structures, which contain many of the core areas involved in
emotion and reward processing, and contributing to the experience of well-being. An abundance of
neuroscientific evidence indicates that the subjective experience of happiness, pleasure, rewards, and
general well-being depends on shared or overlapping networks of interacting subcortical and cortical
regions. These networks involved in processing emotions and rewards include subcortical structures such
as the amygdala, ventral tegmental area, nucleus accumbens, and ventral pallidum, and portions of the
prefrontal cortex regions, including the medial prefrontal cortex, orbitofrontal cortex, anterior cingulate
cortex, and insula.
Neural Correlates of Emotion
Emotion processing has been associated with a wide range of interacting brain regions (Lindquist,
Wager, Kober, Bliss-Moreau, & Barrett, 2012). In this review we focus on regions that have been typically
associated with well-being. A region that plays a critical role in the detection of emotional information and
in learning the emotional significance of the information is the amygdala (AMY), a small, almond shaped
subcortical region located deep in the brain, in the temporal lobe. Traditionally, the AMY was linked
exclusively to processing negative emotions, such as fear and anger. However, current views also highlight
the AMY’s role in processing positive emotions, and more generally in detecting salient stimuli (Adolphs,
2008, 2009; Dolcos, Iordan, & Dolcos, 2011; Whalen, 2007). Positive experiences increase the release of
dopamine, the most important neurotransmitter for the experience of reward or pleasure, which makes the
AMY react stronger to positive events and experiences, and send signals to the nearby hippocampus (HC)
to remember such experiences.
The main cortical areas involved in emotion processing are located in the frontal lobe, which
consists of a number of regions. The most relevant for well-being are the prefrontal cortex regions
(especially its medial and orbital parts), the inferior frontal cortex, and the anterior cingulate cortex. The
prefrontal cortex (PFC), which comprises the anterior regions of the frontal lobe, takes part in the more
complex aspects of planning, organizing, and executing behavior. The medial PFC (mPFC) plays
important roles in processing information about the self and others, emotion regulation, and emotional
decision making. The orbitofrontal cortex (OFC), the most ventral part of the PFC, is especially involved
in the experience of pleasure, happiness, and well-being. Located just above the orbits, this region receives
input from the external senses (vision, hearing, touch, smell, and taste), as well as input related to the
internal states of the body (via the insula, described below). By comparing the properties of an external
stimulus (e.g., sweet, friendly) with the body’s current internal state, the OFC (especially its mid-anterior
part) computes the current emotional value of a stimulus at a particular moment, and tracks changes in the
subjective pleasure or reward. The inferior frontal cortex (IFC)1 is involved in a diverse range of
processes, such as basic processing of emotional and salient information, response inhibition, and emotion
regulation. Another frontal lobe structure, the anterior cingulate cortex (ACC) is connected to many brain
areas, including the PFC and AMY, which allows this region to have an important integrative role in
emotion, self-monitoring, and reward anticipation. The ACC is involved in assessing the value of
responses; that is, whether an action is likely to elicit a reward or punishment, which is different from the
role of the OFC, which computes whether a stimulus is currently rewarding or punishing. Overall, there is
also evidence that the left PFC plays a more specialized role in positive affect and approach-driven
305
behaviors, whereas the right hemisphere is involved in negative affect and withdrawal/avoidance-driven
behaviors, but this evidence is not discussed in details here (Davidson, 2004; Eddington, Dolcos, Cabeza,
& Strauman, 2007; Eddington et al., 2009; Herrington et al., 2010).
Another brain region involved in emotion processing is the insula, which is an area of cortex tucked
between the frontal and temporal lobes. Commonly known for its role in disgust, the insula actually has a
wider role in emotional processing, being involved in monitoring the internal states of a body. The more
complex whole-body sensations associated with emotional states, like feelings of happiness, sadness, or
elation, are processed in the anterior insula, whereas basic visceral sensations like pain, temperature, or
fatigue are processed in the posterior insula. Figure 1 highlights these brain regions and their main roles.
Figure 1. Neural circuitry of well-being emphasized in the present review. The areas circumscribed
by dotted lines shown in the left panel illustrate brain regions located deep inside the brain. Note that
the highlighted regions are meant to give a general idea of the locations in the brain, whereas
delineations used for analysis might target specifically gray or white matter and use nomenclature
specific to one or the other.
Neural Correlates of Reward
Neuroscientific evidence has shown that positive experiences engage a set of reward brain centers,
which paint a “hedonic gloss” on some of our experiences. Before talking about these reward centers, we
need to define the concept of reward. Reward consists of three components (Berridge & Kringelbach,
2015). The first component is the one most associated with reward, which is the actual pleasure or liking.
The second component is the motivation for reward, or wanting. The third component is learning about
future rewards based on past experiences. “Liking” is the core process of hedonic pleasure, whereas
“wanting” refers to the motivation to obtain the reward, or the incentive salience. “Liking” is a presentmoment,
interoceptive feeling of well-being, whereas “wanting” is a future expectation of well-being. In
addition to these psychological dissociations, “liking” and “wanting” can be also dissociated at the
neuroanatomical and neurochemical levels. “Wanting” is generated by more widely distributed subcortical
brain circuits, especially by the mesolimbic dopamine system, which connects the dopamine-rich ventral
tegmental area to the nucleus accumbens (see Figure 1). The ventral tegmental area contains many neurons
that produce dopamine. The nucleus accumbens (NAcc), a subcortical structure located deep inside the
brain, contains many dopamine receptors. Dopamine released from the mesolimbic system into the NAcc
regulates the incentive salience of the stimuli. In addition to dopamine, other neurotransmitters, including
opioids (natural brain neurochemicals similar to opiate drugs), also contribute to the incentive salience or
“wanting” (reviewed in Berridge, 2009). “Liking” is generated by more restricted brain regions than
“wanting”, and is also more restricted neurochemically. “Liking” is enhanced by opioid stimulation in
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opioid hotspots such as the NAcc and the ventral pallidum. Although dopamine was considered by many as
playing a role in sensory pleasure, recent evidence suggests that dopamine is only involved in “wanting”
something, but not necessarily in “liking” it (Berridge & Kringelbach, 2015). Therefore, “liking” and
“wanting” are different aspect of pleasure, and they involve different neurotransmitters. Opioids are the
ones causing people to enjoy the experience, and dopamine keeps them coming back for more. While the
“liking” component of reward is relatively understudied, the “wanting” part is very well studied, especially
in the form of addiction.
In summary, no single brain area is responsible for the experience of emotion, pleasure, and reward.
Rather, a number of brain regions interact to produce the different types of emotional experiences that
accompany well-being.
When Things Go Wrong: Stress, Anxiety, and Depression
As described above, the experience of positive emotions, pleasure, and well-being is supported by
the normal functioning of a number of brain regions and their interconnections2. Disturbances in the
structure and function of these regions can reduce the ability to experience positive emotions and pleasure,
which is commonly seen in chronic stress, anxiety, and depression.
Stress and the Brain
Everyone experiences stress in their life—from minor stressors such as a traffic jam or financial
difficulties to major stressors such as divorce or the loss of a loved one. Stressors can cause a wide range of
emotional responses, from mild alertness, to a sense of being overwhelmed and literally feeling stressed
out. However, not all stress is bad. Acute or moderate stress (eustress), or what we commonly refer to as
basic fight-or-flight response, not only helps people get out of danger in unexpected emergency situations,
but can also have beneficial effects on people’s health, strengthening the immune and cardiovascular
systems. However, chronic stress, that is stress extending over longer periods of time, with no end in sight,
can have deleterious effects on brain structure and function, and on people’s health and well-being, leading
to increased incidence of disease, such as generalized anxiety disorder, major depressive disorder, and
post-traumatic stress disorder (PTSD) (Dohrenwend & Dohrenwend, 1974; Kendler, Gardner, & Prescott,
1999; Monat, Lazarus, & Reevy, 2007). Before describing the effects of stress on the brain, we need to
understand how stress works.
Exposure to stressors activates the body’s stress response (the fight-or-flight response), which
involves the production of hormones and neurochemicals in the brain. Two key hormones are cortisol,
which helps activate our brain and senses to increase alertness to better deal with emergency situations, and
adrenaline, which gets the body immediately activated and aroused for action. Cortisol hard-wires the
pathways between the AMY, which is important for emotions and for learning about aversive stimuli, and
the adjacently located HC, which is critical for episodic memories. The hippocampal cells have the largest
number of cortisol receptors in the brain, making the HC highly receptive to any change in cortisol levels.
Short exposure to cortisol improves hippocampal activity and memory, but prolonged exposure to high
levels of cortisol damages hippocampal cells. Patients with conditions associated with long-term stress
exposure, such as depression and PTSD, have significantly shrunken HC (Arnone, McIntosh, Ebmeier,
Munafo, & Anderson, 2012; Bonne et al., 2008; Koolschijn, van Haren, Lensvelt-Mulders, Hulshoff Pol, &
Kahn, 2009; McEwen, Nasca, & Gray, 2016), suggesting that long-term cortisol exposure has destroyed
their hippocampal cells. They also show changes in the size and connectivity of the AMY (Hamilton,
Siemer, & Gotlib, 2008; McEwen et al., 2016; Morey et al., 2012). Increased stress in patients with these
conditions puts the AMY into overdrive, and the increased AMY activity is accompanied by reduced
activity in the PFC (Bremner, 2006).
Anxiety, Depression, and the Brain
Anxiety and depression are associated with symptoms of reduced well-being, such as negative
affective biases (Cisler, Bacon, & Williams, 2009; Eysenck, Derakshan, Santos, & Calvo, 2007; Gotlib,
Krasnoperova, Yue, & Joormann, 2004), and enhanced encoding of negative stimuli (Hamilton & Gotlib,
2008; Russo et al., 2006). In addition, structural and functional neuroimaging evidence indicates that brain
regions implicated in emotion and reward processing are altered in anxiety and depression. For example,
individuals with anxiety and depression tend to show decreased volume in frontal lobe regions such as the
OFC and ACC (Arnone et al., 2012; Koolschijn et al., 2009; Shang et al., 2014; Talati, Pantazatos,
Schneier, Weissman, & Hirsch, 2013), as well as in medial temporal regions such as the HC and AMY
(Alemany et al., 2013; Arnone et al., 2012; Fisler et al., 2013; Hayano et al., 2009; Irle et al., 2010;
Koolschijn et al., 2009; Meng et al., 2013), suggesting that these conditions are linked to structural changes
in key regions engaged during processing and integration of emotional and motivational signals.
Furthermore, anxiety and depression have been linked to reduced integrity of the structural
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connections between these brain regions, including between the frontal lobe and the AMY (Cullen et al.,
2010; de Kwaasteniet et al., 2013; Kim & Whalen, 2009; Zhang et al., 2012), supporting the idea that the
structure within and between key brain regions involved in emotion and reward processing are altered in
anxiety and depression. Moreover, anxiety and depression are associated with aberrant brain activity,
including communication between brain regions when the brain is “at rest” (i.e., resting state functional
connectivity). For instance, anxiety is characterized by reduced resting state connectivity between PFC and
the AMY (Hahn et al., 2011; Kim et al., 2011), and depression by increased resting state connectivity
within a network of brain regions implicated in autobiographical memory, and decreased connectivity
within a network implicated in cognitive control, relative to healthy individuals (Rayner, Jackson, &
Wilson, 2016). These findings suggest that maladaptive cross-talk between brain regions occurs in anxiety
and depression even when not engaged in a particular task. During tasks, individuals with anxiety or
depression tend to show enhanced response in AMY to negative stimuli compared to control groups (Etkin
& Wager, 2007; Groenewold, Opmeer, de Jonge, Aleman, & Costafreda, 2013), consistent with the idea
that anxiety and depression influence the mechanisms subserving emotion processing.
Together, these findings identify brain mechanisms underlying chronic stress and reduced mental
health, which are key factors in understanding the neuroscience of well-being, and highlight potential
targets for preventive and therapeutic interventions aimed at decreasing susceptibility and increasing
resilience against affective conditions to support improved well-being.
Factors Influencing Well-Being:
The Role of Individual Differences and Social Relationships
Important insight into understanding well-being has been offered by research clarifying the neural
substrates of individual differences that play a role in promoting enhanced well-being and protecting
against symptoms of reduced well-being. Among these, the most studied are individual differences in
personality and age, which are discussed here. The role of social relationships is also discussed, with a
focus on love and loneliness.
Personality, the Brain, and Well-Being
Personality influences many aspects of our lives, including our emotions, thoughts, and ultimately
our well-being. Although a breadth of personality characteristics can be considered in the context of wellbeing,
the present discussion focuses on several key factors that emerge from the literature, including
optimism, negative bias, self-esteem, and Big 5 traits.
Optimism, a deep-rooted mindset defined as the dispositional tendency for people to hold
generalized favorable expectancies about their future (Carver, Scheier, & Segerstrom, 2010), has been
shown to be associated with coping behavior (Nes & Segerstrom, 2006), to be beneficial in times of
adversity (Carver et al., 2010), and to promote psychological well-being (Andersson, 1996; Carver et al.,
2010). Optimism is not just feeling good or thinking positively—it also helps us stay engaged in important
tasks with important rewards (Scheier & Carver, 1985). Optimism leads to increased well-being because by
expecting to do well, people will increase their engagement and persistence, being therefore more likely to
achieve their goals.
Emerging evidence shows that optimism is associated with the structure and function of the brain.
Structurally, trait optimism has been associated with greater volume in reward-related (Grabenhorst &
Rolls, 2011; Kringelbach & Berridge, 2009; Phelps, Lempert, & Sokol-Hessner, 2014) and approachoriented
(Eddington et al., 2007) processing regions, such as the OFC (Dolcos, Hu, Iordan, Moore, &
Dolcos, 2016). Moreover, optimism has been shown to mediate the relation between the OFC and
symptoms of reduced well-being, thus demonstrating that increased volume in this brain region can play a
protective role against anxiety through increased optimism (Dolcos et al., 2016). In addition to the OFC,
trait optimism has also been associated with a region of the ACC (rostral anterior cingulate cortex, rACC)
when imagining future positive events vs. future negative events (Sharot, Riccardi, Raio, & Phelps, 2007).
This region, known to be involved in self-reflection (Moran, Macrae, Heatherton, Wyland, & Kelley, 2006;
Paulus & Frank, 2003) and assessing the salience of emotional and motivational information (Bush, Luu, &
Posner, 2000), has also shown increased functional connectivity with the AMY when imagining future
positive events compared to imagining negative events (Sharot et al., 2007).
Research examining the brain chemistry associated with optimism (Fox, 2013) posits that the
optimistic mindset is rooted in the “sunny brain”, the pleasure center of the brain, whereas the pessimistic
mindset is rooted in the “rainy brain”. The sunny brain consists of neurons in a core reward region, the
NAcc, that forms links with neurons in particular areas of the PFC, and seems to be left lateralized
(Davidson & Irwin, 1999). Converging evidence from healthy and clinical studies support these
lateralization findings, suggesting that the two hemispheres are differentially engaged in these fundamental
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approaches to life (reviewed in Hecht, 2013).
Overall, the reviewed evidence highlights the role of the OFC, rACC, and NAcc in supporting
optimism, and points to brain-personality mechanisms promoting enhanced well-being as well as protecting
against reduced well-being.
Negative Bias. Another important aspect of understanding the neural correlates of well-being is
clarifying the links between individual differences in affective biases that influence well-being. Positive
affective biases tend to be observed in optimistic individuals and are associated with indicators of improved
well-being (Segerstrom, 2001), whereas negative affective biases tend to be observed in individuals with
emotional disorders and are associated with indicators of reduced well-being (Cisler et al., 2009; Eysenck
et al., 2007; Gotlib et al., 2004). Negative affective biases are often expressed as enhanced sensitivity to
negative or threatening information (Bar-Haim, Lamy, Pergamin, Bakermans-Kranenburg, & van
IJzendoorn, 2007), and likely reflect compromised executive control of attention (Cisler et al., 2009) and
impairment of the ability to inhibit prepotent responses and to resist interference to task-irrelevant
distracters.
Negative attentional biases can be captured by tasks like the Affective Go/No-Go, in which
participants are asked to respond to target stimuli and withhold from responding to distracter stimuli, while
targets and distracters differ in affective valence. A negative affective bias can be detected by an increased
speed and/or accuracy in participant responses when attending to negatively (vs. positively) valenced
information (Schulz et al., 2007). This pattern is typically shown by patients with affective disorders,
whereas the opposite pattern is typically shown by healthy participants (Erickson et al., 2005). Together,
these results support the idea that negative biases in attention can be targeted to clarify potential links
between impaired control mechanisms and affective disorders. Structural and functional imaging evidence
has linked the IFC with performance in Go/No-Go tasks (Brown et al., 2015; Brown et al., 2012; Liddle,
Kiehl, & Smith, 2001; Swick, Ashley, & Turken, 2008, 2011). Structural damage to the IFC is associated
with higher error rates (Swick et al., 2008), and greater IFC activity has been seen in no-go trials (Liddle et
al., 2001), particularly for negative emotional contexts (Brown et al., 2012), consistent with the idea that
IFC helps to inhibit prepotent responses and is differentially engaged by emotional stimuli. Furthermore,
the IFC responses to affective stimuli seem to be modulated by trait anxiety (Fales, Becerril, Luking, &
Barch, 2010). More specifically, Fales et al. (2010) showed that higher anxiety was associated with greater
activation within the left IFC in response to fearful (vs. neutral) targets, while lower anxiety was associated
with greater activation to happy (vs. neutral) targets. Extending these previous findings, a recent study (Hu
& Dolcos, 2017) showed that trait anxiety was negatively correlated with left IFC volume, and positively
correlated with a negative bias in reaction time. Furthermore, trait anxiety mediated the negative association
between the IFC volume and the negative bias measure, thus demonstrating that decreased volume in this
brain region is linked to negative affective bias through anxiety.
Overall, extant evidence highlights the influence of negative affective bias in attention, and points
to the IFC as a region both structurally and functionally associated with executive control. Available
evidence shows that negative affective bias tends to be associated with enhanced sensitivity to negative or
threatening information, possibly linked to compromised executive control of attention, and subserved by
alterations of underlying brain mechanisms. In turn, negative affective bias plays a key role in
understanding the neurophysiological substrates of well-being.
Self-Esteem is another important factor that has been shown to greatly predict well-being (Diener,
2009). Self-esteem typically refers to one’s global attitudes about oneself (Rosenberg, 1965). Interestingly,
evidence suggests that when happiness decreases, self-esteem decreases as well (Laxer, 1964; Wessman &
Ricks, 1966), suggesting that the relation between these factors might be bidirectional (Diener, 2009).
At a neural level, self-esteem has been shown to be associated with both the structure and function
of the brain. Structurally, self-esteem has been linked to greater HC volume, in both younger and older
adults, suggesting a potential protective role against challenges such as stress (Pruessner et al., 2005). Selfesteem
is also associated with the structural connections between regions, such as the white matter integrity
between the mPFC and the ventral striatum (Chavez & Heatherton, 2015), consistent with the role of these
brain regions in processing information about the self and positive affective processes such as reward,
respectively. Functionally, self-esteem has been linked to modulation of brain activity both at rest and
during tasks. Greater self-esteem was associated with greater resting state functional connectivity between
the ventral mPFC and the HC (and between the cuneus/lingual gyrus and right dorsolateral PFC and ACC)
(Pan et al., 2016), consistent with the idea that brain networks supporting self-referential, memory, and
cognitive control-related processes support self-esteem. Furthermore, tasks involving social exclusion or
social feedback have shown that self-esteem modulates the engagement of ACC and mPFC responses
(Onoda et al., 2010; Somerville, Kelley, & Heatherton, 2010). For instance, individuals with lower self-
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esteem relative to a high self-esteem group reported greater social pain in response to social exclusion, and
had both greater response in ACC and greater connectivity between ACC and PFC (Onoda et al., 2010).
These findings are consistent with the idea that self-esteem influences brain mechanisms engaged for
interpretation of social signals and can lead to differential outcomes relevant to well-being.
Together, extant evidence suggests that self-esteem and the associated neural correlates influence
factors of well-being. Self-esteem appears to be greatly linked to indices such as happiness, and is
supported by both the structure and function of the brain. Hence, continuing research on these relations will
refine and improve understanding and promotion of well-being.
Big 5 Traits . Yet another important aspect of understanding individual differences and the brain
regions subserving well-being is the role of general personality factors. The link between the brain and
well-being is complex, and might be better understood if individual differences in general personality traits
are also taken into account. Personality is commonly studied using the Big 5 model, which includes the
dimensions of extraversion, neuroticism, agreeableness, conscientiousness, and openness to experience
(Costa & McCrae, 1992). Whereas the Big 5 have been shown to be linked to measures of well-being,
most findings focus on extraversion and neuroticism, which are also the focus of this review (for details
about agreeableness, conscientiousness, and openness to experience, see DeNeve & Cooper, 1998;
Gutierrez, Moreno-Jimenez, Garrosa, & Puente, 2005; Hayes & Joseph, 2003). Extraversion is typically
defined as a trait reflecting sensitivity to reward and positive affect, whereas neuroticism generally
encompasses sensitivity to punishment and negative affect. Extraversion is linked to indicators of increased
well-being, such as positive affect (DeNeve & Cooper, 1998; Gutierrez et al., 2005), enhanced recall of
positive memories (Mayo, 1983; Rusting, 1999) and maintaining a positive mood after retrieval of positive
personal memories (Denkova, Dolcos, & Dolcos, 2012). In contrast, neuroticism is associated with
indicators of decreased well-being, such as negative affect, reduced life satisfaction, reduced happiness,
and a tendency to recall negative information (Bradley & Mogg, 1994; DeNeve & Cooper, 1998; Gutierrez
et al., 2005).
Available evidence links extraversion and neuroticism to the structure and function of the brain. For
example, extraversion is positively associated with the medial OFC (DeYoung et al., 2010). Neuroticism is
negatively linked to AMY volume (Hu et al., in press), and positively linked to the volume of regions
engaged by sensitivity to punishment, negative emotion, and emotional dysregulation (mid-cingulate gyrus
and caudate) (DeYoung et al., 2010). These traits have also been linked to other structural aspects such as
cortical thickness (Riccelli, Toschi, Nigro, Terracciano, & Passamonti, 2017), and the structural
connections between brain regions (i.e., white matter) (Xu & Potenza, 2012), as well as to the function of
the brain. For instance, resting state functional connectivity measures have shown that extraversion and
neuroticism are differentially associated with activity in networks of brain regions while at rest (Adelstein
et al., 2011; Sampaio, Soares, Coutinho, Sousa, & Goncalves, 2014), consistent with the idea that these
traits are linked to regions engaged in processes such as emotion regulation, self-evaluation, and reward
(Adelstein et al., 2011; Andrews-Hanna, Reidler, Sepulcre, Poulin, & Buckner, 2010). Moreover,
extraversion and neuroticism influence brain responses, especially in the AMY and HC, during tasks that
involve emotional learning (Haas & Canli, 2008; Hooker, Verosky, Miyakawa, Knight, & D'Esposito,
2008). Overall, the reviewed evidence highlights the role of general personality factors as possible targets
for better understanding susceptibility, and improving resilience, against emotional disturbances.
Successful Aging, the Brain, and Well-Being
Healthy aging is generally associated with improved emotional functioning and well-being
(Carstensen et al., 2011; Mather, 2012; Scheibe & Carstensen, 2010). Brain imaging findings parallel this
behavioral evidence, suggesting that healthy aging is associated with relatively preserved structural
integrity in regions typically involved in the processing and valuation of emotional information (AMY,
mPFC), whereas it is associated with marked anatomical (Fjell et al., 2009; Raz, Ghisletta, Rodrigue,
Kennedy, & Lindenberger, 2010; Raz et al., 2005) and physiological (Fabiani, 2012; Reuter-Lorenz &
Park, 2014) losses in specific brain structures typically involved in executive control and emotion
regulation (lateral PFC). Of note, given that the mPFC is also involved in some forms of emotion regulation
(Roy, Shohamy, & Wager, 2012) and does not seem to show significant age-related cortical volume loss, it
is possible that older adults may rely more on this structure in controlling their emotional responses
(Mather, 2016).
In the context of overall preserved emotional functioning and well-being in aging, considerable
evidence supports the idea of an age-related positivity effect in emotional perception, attention, and
memory, by which older adults tend to pay greater attention to and remember more positive information
(Charles, Mather, & Carstensen, 2003; Isaacowitz, Wadlinger, Goren, & Wilson, 2006; Knight et al., 2007;
Mather & Carstensen, 2003) and show reduced processing of negative information (Grühn, Scheibe, &
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Baltes, 2007; Wood & Kisley, 2006), compared to younger adults (see also Mather, 2016; Reed &
Carstensen, 2012; Reed, Chan, & Mikels, 2014). In order to explain this age-related positivity effect and its
impact on well-being, a few models of emotional aging have been proposed. According to the
Socioemotional Selectivity Theory (SST; Carstensen, Fung, & Charles, 2003), older adults’ preference for
positive over negative information is driven in part by their prioritization of more present-focused
motivational goals related to emotional meaning and satisfaction, which in turn enhances their well-being.
The SST model interprets the positivity effect as a consequence of enhanced top-down modulation by the
PFC/ACC influencing AMY response (Dolcos, Katsumi, & Dixon, 2014; St. Jacques, Dolcos, & Cabeza,
2010), thus emphasizing the role of motivational goals in emotion regulation (Carstensen et al., 2003).
Another influential model called the Aging Brain Model (ABM; Cacioppo, Berntson, Bechara, Tranel, &
Hawkley, 2011) interprets it as a consequence of impaired bottom-up processing of negative arousing
stimuli by the AMY in older adults, considering that its response to positive stimuli may be relatively
unimpaired by advancing age (Cacioppo et al., 2011). It is important to note, however, that there is
evidence identifying activation of overlapping areas of the AMY between younger and older adults in
processing negative stimuli (Dolcos et al., 2014; St. Jacques et al., 2010). Therefore, it is unlikely that the
age-related reduction in AMY activity can be explained by impaired functioning of this region, as posited
by the ABM.
In addition to reduced processing of negative stimuli, available evidence points to the link between
enhanced processing of positive/rewarding stimuli and increased psychological well-being in aging. For
instance, among a sample of middle-aged and older adults, those who showed sustained activity in the
striatum, which is typically involved in the processing of various types of reward, over time in response to
viewing positive pictures also reported overall greater levels of well-being (Heller et al., 2013). Moreover,
striatal activation related to the viewing of positive stimuli mediated the relationship between well-being
and daily levels of the stress hormone cortisol. In particular, greater levels of well-being were associated
with increased activation in the striatum during positive picture processing, which in turn was associated
with decreased levels of cortisol (Heller et al., 2013). Overall, these findings suggest that sustained
engagement of the striatum in positive emotion processing is a key factor associated with well-being and
adaptive regulation of stress necessary for maintaining health (see also Ryff, Heller, Schaefer, Van
Reekum, & Davidson, 2016).
Taken together, these findings suggest that healthy aging is associated with an age-related positivity
effect in emotion processing, as reflected in reduced processing of negative stimuli and enhanced
processing of positive stimuli. This age-related positivity effect appears to be subserved by brain regions
involved in basic/bottom-up processing (e.g., AMY, striatum) and those involved in higher-order/top-down
processing and control (e.g., PFC, ACC) of emotional information. Successful engagement of these regions
may in turn lead to improved subjective well-being in older adults.
Social Relationships, the Brain, and Well-Being
Humans are fundamentally a social species, sharing a strong need to interact with others. Social
relationships can provide enjoyment and can feel rewarding (Kahneman, Krueger, Schkade, Schwarz, &
Stone, 2004). They give people access to the benefits of shared resources, security, and social support
(Baumeister & Leary, 1995), and have a protective role, being associated with a variety of positive
outcomes ranging from lower rates of mortality (House, Landis, & Umberson, 1988) and increased survival
from heart attacks (Seeman, 1996) to physical (Holt-Lunstad, Smith, & Layton, 2010) and
mental/subjective well-being across the lifespan. On the flip side, however, the perceived absence of social
relationships, or loneliness, makes people feel more unsafe and threatened in social contexts (Cacioppo et
al., 2011; Cacioppo & Patrick, 2008), and is associated with increased risk of depression (Cacioppo,
Hawkley, & Thisted, 2010; Cacioppo, Hughes, Waite, Hawkley, & Thisted, 2006) and other negative
outcomes.
Interactions with others are so critical for our survival that we developed larger brains and complex
neural networks to be able to understand other people and to predict their intentions. Interestingly, when at
rest, the brain’s pattern of activity looks very similar to when people are thinking about others, oneself, and
the relation of oneself to other people (Mars et al., 2012). This has led some scientists to believe that “our
brains are built to practice thinking about the social world and our place in it” (Lieberman, 2013). As such,
it should not be surprising that a lack of interactions with the social world, and especially perceived
loneliness, has deleterious effects on health through its effects on the brain (Cacioppo & Hawkley, 2009).
The neural substrates supporting social cognition/behavior consist of many cortical and subcortical regions,
each involved in several distinct processes. Most of the structures that we have talked about as being
important in processing emotions and rewards are also important for social behavior. These include the
AMY, the OFC, and the ventral striatum (especially the NAcc, caudate nucleus, and the putamen).
Additional brain regions are also involved in social relationships. The next paragraphs review structural and
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functional changes in the brain associated with the involvement in dyadic or more extended social
relationships (i.e., love and social networks), and the perceived absence of social relationships (i.e.,
loneliness).
Love is a complex and rewarding mental state involving cognitive and goal-directed behavioral
components (Bianchi-Demicheli, Grafton, & Ortigue, 2006). The different kinds of love (e.g., passionate,
maternal) are important predictors of positive emotions, happiness, and satisfaction (Myers, 1992).
Evidence indicates both common and dissociable circuits for different kinds of love (e.g., romantic vs.
maternal). Functional brain imaging evidence (Bartels & Zeki, 2000; Bartels & Zeki, 2004) shows that all
types of love engage subcortical dopaminergic reward-related brain systems (involving dopamine and
oxytocin receptors), which play an important role in goal-directed motivation, reward, and pair-bonding
(Ortigue, Bianchi-Demicheli, Patel, Frum, & Lewis, 2010). However, the different types of love also
involve distinct neural networks inside and outside the dopaminergic network (Bartels & Zeki, 2004;
Fisher, Aron, & Brown, 2005). For instance, passionate love engages the ventral tegmental area (part of the
brain’s reward circuit, associated with the motivation to pursue rewards) and the caudate nucleus
(associated with reward detection and expectation). Maternal love recruits similar brain areas, with a
specific involvement of the periaqueductal gray matter, an area that receives direct connections from the
limbic emotional system, and contains a high density of receptors (vasopressin) that are important in
maternal bonding and in pain suppression during intense emotional experiences like childbirth.
Interestingly, the presence of a loved one is not only rewarding, but it may act as a buffer against
pain or stress. Showing female participants pictures of a loved male while receiving painful stimulation
was associated with reduced reported pain intensity (Master et al., 2009), and such an analgesic effect
correlated with activity in the reward-related NAcc (Younger, Aron, Parke, Chatterjee, & Mackey, 2010).
Holding a partner’s hand, relative to holding the hand of a stranger or squeezing a ball, produced similar
effects (Master et al., 2009). Moreover, love also reduces critical social assessment of others. For instance,
when people look at their loved partners, the neural circuits that are normally associated with critical social
assessment (AMY, temporo-parietal junction, and mPFC) of other people are suppressed, whereas regions
involved in reward and attachment (caudate nucleus, putamen, medial insula, ACC) are activated (Bartels
& Zeki, 2000). In sum, love facilitates positive emotions, by connecting the NAcc with the PFC, and
reduces negative emotions, such as social judgment, by connecting the NAcc to the AMY.
Loneliness has been linked to a number of psychological states that contribute to morbidity and
mortality, including increased depression (Booth, 2000; Cacioppo et al., 2010; VanderWeele, Hawkley,
Thisted, & Cacioppo, 2011) and lower subjective well-being (Kong, Zhao, & You, 2013; VanderWeele,
Hawkley, & Cacioppo, 2012). Loneliness also influences individuals’ perception and appraisal of the world.
There is behavioral and neural evidence that loneliness increases attention to potential threats from the
social world (Cacioppo & Hawkley, 2009), and is associated with increased worry about being evaluated
negatively, as well as with higher levels of perceived threat in social situations (even when there is no
increased likelihood of being rejected; Jones, Freemon, & Goswick, 1981). Lonely people also tend to feel
more unsafe, compared to non-lonely people. They tend to appraise other individuals as more threatening,
and to isolate themselves when confronted with stressors, rather than actively looking for the help and
support of others (Berscheid & Reis, 1998; Cacioppo & Hawkley, 2005).
Loneliness involves multiple brain mechanisms, and produces significant changes in both brain
structure and function. Recent structural brain imaging studies have identified relationships between
loneliness and the density of gray and white matter in different regions of the brain. Loneliness was
negatively correlated with the gray matter density in the left posterior superior temporal sulcus (pSTS), an
area involved in processing biological motion and social perception (Kanai et al., 2012); the pSTS size was
also related to poorer performance in a social perception task. Loneliness has also been associated with
widespread reduction in white matter density in areas related to self- and social-cognition (bilateral inferior
parietal lobe, the right anterior insula, and left posterior temporo-parietal junction), as well as areas
associated with empathy (the left pSTS and right lateral PFC) and self-efficacy (dorsomedial PFC)
(Nakagawa et al., 2015). In addition to these structural changes, neuroimaging evidence also reveals
functional changes associated with perceived loneliness in a number of brain regions involved in the
detection of threat (AMY, ACC, the ventrolateral PFC, and the insula; Cacioppo et al., 2013; Eisenberger
& Lieberman, 2005; Eisenberger, Lieberman, & Williams, 2003), and managing the demands of complex
social contexts (OFC, mPFC, STS, temporo-parietal junction; Bickart, Hollenbeck, Barrett, & Dickerson,
2012; Cacioppo, Norris, Decety, Monteleone, & Nusbaum, 2009; Cacioppo et al., 2016; Eisenberger &
Cole, 2012; Klumpp, Angstadt, & Phan, 2012).
Overall, the evidence reviewed in this section illustrates the essential role of social relationships for
our happiness and well-being. Our brains are wired to be social, and this wiring of our brains motivates us
to engage in relationships with others, which in turn, increases positive emotions, enjoyment, and feelings
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of reward. The fact that by simply enhancing social connections in our everyday lives we can enhance our
well-being highlights the need to develop interventions focused on educating the social brain.
Enhancing Well-Being through Brain Building Interventions
The brain is a dynamic system, which responds to environmental demands and generates goals and
actions, and hence its anatomical structure and physiology continuously change throughout our life. This
ability to physically change and to maintain this change is known as neuroplasticity. Neuroplasticity has
fascinating implications for our well-being! A growing body of evidence suggests that neuroplasticity is
associated with variations in brain activity, which might come from experience (May, 2011),
training/learning (Draganski & May, 2008), clinical status (Cahn et al., 2002), or injury (Sidaros et al.,
2009). Plasticity allows our brains incredible flexibility, and evidence shows that our experiences can make
real changes in the structure and function of our brains. This means that we have the power to change our
brains for the better. Although the mechanisms underlying neuroplasticity are still an area of active
research, it may describe a result of Hebbian learning, which posits that repeated patterns of neuronal firing
lead to increased synaptic connectivity (Hebb, 1949), and suggests that these alterations might lead to
changes in brain structure, such as gray matter volume (Boyke, Driemeyer, Gaser, Buchel, & May, 2008;
Draganski et al., 2004; Draganski et al., 2006) and white matter connections between brain regions (Tang,
Lu, Fan, Yang, & Posner, 2012), as well as brain function (Dayan & Cohen, 2011). Notably, extant
evidence points to the possibility that interventions can be performed to improve well-being and the
underlying structure and function of the brain (Davidson & McEwen, 2012). This idea has led to new and
emerging research targeting different forms of training interventions to improve well-being and the brain.
Areas in this domain include physical training and mindfulness training.
Physical Activity, the Brain, and Well-Being
Physical activity has been consistently associated with profound benefits for brain structure and
function, and overall well-being. Engaging in physical activity might be enjoyable, and is associated with
increased positive mood (Steptoe, Kimbell, & Basford, 1998; Yeung, 1996) and decreased negative mood
(McIntyre, Watson, & Cunningham, 1990; Raglin & Wilson, 1996; Steptoe, Kearsley, & Walters, 1993).
More important than these transient effects on mood are the more enduring effects of physical exercise,
reflected in reduced stress and symptoms of anxiety and depression (Blumenthal et al., 2007; Silveira et al.,
2013), prevention of the onset of depression (Schuch et al., 2016), and overall improved well-being
(Penedo & Dahn, 2005). How is physical activity relieving the detrimental effects of stress and improving
mood and well-being? Physical exercise changes the way the brain processes the information, and even
more importantly, it changes the brain, having a positive effect on the structure and function of a number
of brain regions (Foster, 2015), including the HC and the PFC. Although the exact mechanisms underlying
the beneficial effects of physical activity on the human brain and well-being are not clear, extant research
attributes these advantageous effects to a number of factors, including changes in neurotransmitters and
neurogenesis – that is, the capability to recruit, in some specific areas of the adult brain, more neurons,
showing cellular and synaptic plasticity abilities (Garcia-Segura, 2009). We will review these effects in
turn below.
A possible neurobiological mechanism underlying these beneficial effects of exercise is the
increased synthesis and release of neurotransmitters and neurotrophins, which could result in neurogenesis
and neuroplasticity (Dishman et al., 2006). A critical mechanism involved in depression seems to be the
depletion of a category of neurotransmitters called monoamines, including serotonin and norepinephrine
(López-Muñoz & Alamo, 2009). Animal models provide evidence that, similar to the effects of
antidepressants, regular aerobic exercise increases serotonergic and noradrenergic levels in the brain
(Chaouloff, 1989; de Coverley Veale, 1987; Meeusen & De Meirleir, 1995; Van Praag, 1982). For instance,
treadmill training and wheel running have been linked to increased levels of norepinephrine in the HC and
frontal cortex in rodents (Dishman, 1997; Dunn, Reigle, Youngstedt, Armstrong, & Dishman, 1996).
Exercise has also been associated with increases in the synthesis of serotonin (Chaouloff, 1997; Dunn &
Dishman, 1991; Meeusen & De Meirleir, 1995; Wilson & Marsden, 1996).
Accumulating evidence shows that physical exercise has a strong influence on inducing
neuroplasticity (Voss et al., 2013), increasing the levels of the brain derived neurotrophic factor (BDNF).
Research in rodents has shown that 20 days of voluntary wheel running increased BDNF levels in the HC
and caudal neocortex (Meeusen & De Meirleir, 1995; Russo-Neustadt, Beard, & Cotman, 1999). The
increase in BDNF increases functioning in the serotonergic system and may promote neuronal growth.
Research in humans confirms the beneficial effects of physical exercise on neurogenesis. A 3‑month fitness
training (Pereira et al., 2007) study in a small group of middle-aged participants showed increases in
measures of cerebral blood volume (CBV) in a region of the HC (i.e., the dentate gyrus). The location of
the CBV changes in the dentate gyrus is interesting, given that previous animal evidence has shown
313
neurogenesis in these very specific regions.
Physical activity interventions have also been shown to have positive effects in children, producing
changes in brain structure and function. Research shows that more active children have greater HC volume
(Chaddock, Erickson, Prakash, Kim, et al., 2010), along with greater basal ganglia volume (Chaddock,
Erickson, Prakash, VanPatter, et al., 2010), and greater white matter integrity (Schaeffer et al., 2014). In
addition, they show increased and more efficient patterns of brain activity (Voss, Nagamatsu, LiuAmbrose,
& Kramer, 2011), and superior executive and cognitive control performance (Chaddock et al.,
2012; Davis et al., 2011; Hillman et al., 2014).
Most studies on the effects of exercise in humans have been done in the elderly. These studies have
demonstrated that exercise improves older adults’ cognitive abilities in various domains (and the associated
neural mechanisms), or more directly, subjective well-being (reviewed in Bamidis et al., 2014; Gajewski &
Falkenstein, 2016; Hillman, Erickson, & Kramer, 2008; Kramer & Erickson, 2007). Greater physical
activity and cardiorespiratory fitness have been associated with reduced age-related cognitive declines and
a lower risk for dementia in older adults (Buchman et al., 2012; Sofi et al., 2011). Furthermore, mounting
evidence suggests that aerobic exercise interventions, such as those involving walking or dancing, lead to
enhanced cognitive abilities and subjective well-being in older adults (Awick et al., 2017; Awick et al.,
2015; Colcombe & Kramer, 2003; Kattenstroth, Kalisch, Holt, Tegenthoff, & Dinse, 2013; Netz, Wu,
Becker, & Tenenbaum, 2005). Recent brain imaging studies in this population have shown that physical
exercise induces both structural and functional changes in a variety of brain regions. For instance, weekly
aerobic walking was associated with increased volume of the anterior HC in older adults, which was in turn
positively associated with improvements in spatial memory performance due to exercise (Erickson et al.,
2011). Similar beneficial effects of exercise have also been identified with respect to neural functioning. In
particular, older adults who had undergone aerobic training for six months showed increased activity in the
lateral PFC and parietal cortex and decreased activity in the ACC during a challenging task involving
conflict resolution and selective attention; these participants also showed improvements in behavioral
performance on the task (Colcombe et al., 2004). Overall, these findings suggest that exercise interventions
can enhance the ability of the aging brain to effectively allocate neural resources, which in turn leads to
improved performance on a cognitively challenging task (see also Voss et al., 2011).
In summary, exercise has beneficial effects by increasing the production of neurotransmitters such
as serotonin and noradrenaline, by stimulating the growth factor and blood flow, and by stimulating adult
neurogenesis.
Mindfulness Training, the Brain, and Well-Being
In recent years, there has been growing interest in the use of mindfulness-based training and
intervention programs to improve well-being and to identify the underlying brain mechanisms associated
with such improvements (Chiesa & Serretti, 2010; Fox et al., 2014; Gotink, Meijboom, Vernooij, Smits, &
Hunink, 2016; Lomas, Ivtzan, & Fu, 2015). Mindfulness generally refers to “the awareness that emerges
through paying attention on purpose, in the present moment, and non-judgmentally to the unfolding of
experience moment by moment” (Kabat-Zinn, 2003). Training programs focusing on mindfulness typically
target skills aimed at reducing distressing symptoms, including those associated with psychological
disorders and somatic conditions.
Behaviorally, mindfulness training tends to mediate improved indices of well-being, such as
decreased stress, rumination, and trait anxiety, as well as increased positive states of mind, psychological
well-being, quality of life, and self-compassion (Branstrom, Kvillemo, Brandberg, & Moskowitz, 2010;
Carmody & Baer, 2008; Nyklicek & Kuijpers, 2008; Shapiro, Brown, & Biegel, 2007; reviewed in Visted,
Vollestad, Nielsen, & Nielsen, 2015). Notably, mindfulness training has been targeted in many different
populations. For example, mindfulness interventions have been tested in healthy and clinical populations
(Chiesa & Serretti, 2010; Fox et al., 2014; Gotink et al., 2016; Lomas et al., 2015), including groups with
psychological conditions such as anxiety (Vollestad, Nielsen, & Nielsen, 2012; Vollestad, Sivertsen, &
Nielsen, 2011) and depression (Jain, Walsh, Eisendrath, Christensen, & Cahn, 2015; Kuyken et al., 2016;
van der Velden et al., 2015). Mindfulness-based interventions have also been tested in different age groups,
such as children and adolescents (Kallapiran, Koo, Kirubakaran, & Hancock, 2015), young and middleaged
adults (Fox et al., 2014), and older adults (Ehrenbrusthoff, Ryan, Schofield, & Martin, 2012).
Although there is much heterogeneity of the practices and goals of mindfulness interventions when applied
to these various groups, available evidence generally points to improvement in intervention outcomes
(Quaglia, Braun, Freeman, McDaniel, & Brown, 2016; Visted et al., 2015).
At a neural level, mindfulness interventions have been shown to induce changes in both the
structure and function of the brain. Structural studies have associated mindfulness training with increased
gray matter volume or density in the cingulate cortex (Hölzel et al., 2011), insula (Murakami et al., 2012),
314
and HC (Hölzel et al., 2011). Evidence for structural changes in the AMY seems a bit less clear (Hölzel et
al., 2010; Murakami et al., 2012; Pickut et al., 2013), and is perhaps influenced by other factors such as
sample demographics. However, overall, available evidence appears consistent with the idea that
mindfulness engages brain regions that are key for body awareness, memory, and emotion (Fox et al.,
2014). Mindfulness and meditation practice have also been associated with modulation of structural
connectivity between brain regions. For example, meditation practice has been linked to changes
suggesting enhanced connectivity within and between hemispheres of the brain (Luders et al., 2012; Tang
et al., 2010), which is consistent with the idea that mindfulness and meditation training can improve the
underlying connections in the brain that support attentional self-regulation processes (Luders et al., 2012).
At the functional level, mindfulness training was associated with changes in the resting state functional
connectivity between the so-called default mode and salience networks (Doll, Hölzel, Boucard,
Wohlschläger, & Sorg, 2015), consistent with the idea that interactions between brain networks support the
ability to attend to current experience without judgment. Moreover, mindfulness training appears to also
influence brain responses when engaged in tasks, such as paradigms that involve responding to, or
regulating response to, emotional stimuli. A study by Creswell and colleagues (2007), for example,
showed that when labeling emotions, the AMY was negatively associated with lateral PFC activation in
more mindful individuals. This evidence seems consistent with the idea that mindfulness training
modulates the neural mechanisms involved in emotional processes.
Although how mindfulness interventions alter brain structure is still an open question that is being
investigated, a number of possible mechanisms have been proposed (reviewed in Tang, Hölzel, & Posner,
2015). An account referred to as “use-dependent plasticity” (Bütefisch et al., 2000; Kleim et al., 2002;
Kleim, Barbay, & Nudo, 1998; Nudo, Milliken, Jenkins, & Merzenich, 1996; for reviews of relevant studies
in humans see Draganski & May, 2008; May, 2011) suggests that there is a relation between the structure
of the brain and its level of use. This account may describe a result of Hebbian learning as mentioned above
(Hebb, 1949), and suggests that these structural changes might lead to alteration in brain structure
(Draganski et al., 2006). Consistent with the Hebbian learning model, it is possible that repeated
engagement in mindfulness affects brain structure through expansions of existing synapses and dendrites,
or creation of new synapses. It is also possible that engaging in mindfulness induces the formation of new
neurons or myelin sheaths that help insulate the connections between neurons. Another possibility is that
mindfulness influences autonomic and immune activity, which might help preserve or restore neurons.
Alterations in these mechanisms at the level of brain cells might contribute to overall changes in the volume
of brain regions and the integrity of the connections between them.
In sum, extant evidence on mindfulness training and the brain suggests that mindfulness
interventions can enhance well-being, and modulate the structure and function of the brain. Available
evidence highlights the benefits of mindfulness training, and further research in this area will continue to
refine understanding of the effective practices and underlying neural mechanisms, in order to better
promote well-being.
Conclusion
Taken together, the diverse body of neuroscientific evidence reviewed in this chapter reveals that
factors known to play critical roles in well-being, such as personality traits, age, and social relationships,
are influenced by subtle differences in the volume, function, and connectivity of a network of emotion- and
reward-related regions. Our mind is highly plastic, and what we think, feel, and do changes the physical
structure of the brain, and the function of different brain circuits. Given that the brain circuits supporting
positive emotions and rewards are remarkably malleable, we have the amazing ability to reshape our
brains, to change our affective mindsets, and to improve our well-being. One way to enhance well-being is
to address the rising tide of chronic stress, anxiety, and depression, conditions that have negative impacts
on the life and well-being of an increasing number of people worldwide. Another way is to engage in
activities that have positive impacts on our minds and bodies. Being physically active and engaging in
mindfulness meditation are known to produce many physiological changes in our body, but they can also
produce striking changes in the structure, function, and communication between the brain regions
supporting well-being, helping us to lead happier and healthier lives. This suggests that well-being might be
enhanced through training. Future research is needed to tap further into the enormous potential benefits of
these training activities and to determine whether such training can produce changes with long-lasting
consequences.
Endnotes
1It is important to consider the distinction between cortices and gyri when discussing neural correlates.
Anatomically, cortex usually refers to gray matter in particular, while gyrus might refer to both gray and
white matter. Depending on the goal of a study, the focus might be specifically on the gray matter of a
315
particular region, in which case it is referred to as cortex (e.g., inferior frontal cortex, IFC), or the focus
might be on a region of interest that does not distinguish between gray and white matter, and thus it is
referred to as gyrus (e.g., inferior frontal gyrus, IFG). Hence, in the text and Figure 1 both cortical and
gyral terms appear.
2Current brain imaging techniques allow noninvasive mapping of the anatomical and functional
connections among distant brain regions. Structural connectivity refers to the “integrity” of the anatomical
connections linking sets of neuronal elements. These connections refer to the white matter fibers linking
different areas of the brain, and are often measured using a special magnetic resonance imaging approach
called diffusion tensor imaging, or DTI. Functional connectivity evaluates the interconnections between
spatially separated brain regions that occur at rest (resting state functional connectivity), or when a subject
is performing an explicit task.
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Stress, Development, and Well-being
By Carrie E. DePasquale & Megan R. Gunnar, Institute of Child Development, University of Minnesota
Citation
DePasquale, C. E., & Gunnar, M. R. (2018). Stress, development, and well-being. In E. Diener, S. Oishi,
& L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
Typically, when we experience stress, our physiological and social resources allow us to regulate and adapt
effectively, which tends to prevent maladaptive outcomes associated with those experiences. A complex
network of stress response systems maintains physiological and behavioral allostasis, or stability through
change in their activity. The social relationships we have, particularly those with attachment figures, allow
us to maintain this balance even if the stress would otherwise be outside our regulatory capacity. This is
particularly critical early in life when we cannot regulate on our own. When these social relationships are
absent, inconsistent, or of low quality, chronic activation of stress response systems can result in
dysregulated stress reactivity and regulation. This puts children at increased risk for poor physiological and
psychological outcomes and overall lower well-being across the life span.
Keywords: Stress Response, Physiology, Social Relationships, Regulation, Development
The experience of stress is a normal part of life. Therefore, humans possess mechanisms both
“under the skin” and in the environment that function to support processing, responding to, and recovering
from stressors while preserving physical and psychological well-being. During development, these stress
systems are adapted to our individual context based on personal characteristics, early experiences, and
social relationships. When faced with chronic stressors, the body makes continuous adjustments that may
come at a cost to future well-being. When stressors become too intense or overwhelming, or when one of
these mechanisms breaks down and can no longer function properly, there can be detrimental effects on
physiological, behavioral, and emotional health. Up to a point, it is not the presence of stressors in your
life, but the capacity to regulate reactions to them, that influences their impact on physical and
psychological well-being. These impacts vary over time as the stress systems develop from infancy into
adulthood.
Throughout this chapter, the ‘stress response’ is defined as the body’s network of physiological
and behavioral processes that are activated in order to restore homeostasis following an encounter with a
real or imagined threat to our well-being. Stress responses are moderated by actual and/or perceived
controllability and predictability of the stressor, the presence of social support, and the extent to which the
stressor threatens physiological or behavioral stability (Koolhaas et al., 2011). It is important to note that
stress is neither always negative nor does it always have negative consequences. Stressors within the
regulatory capacity of the individual that result in moderate activation of stress response systems can
actually aid in learning (Lucas, Chen, & Richter-Levin, 2013). We experience stress at all stages of life, for
example after separation from a caregiver, when there is a physical or emotional threat to the self, or during
the anticipation of social evaluation. By mobilizing available physiological and social resources when
necessary, humans have an incredible capacity to regulate in response to stress. In fact, even in the face of
severe, chronic stress, a sizable portion of individuals show resilient functioning. This may be due in large
part to the buffering effect of stable, high-quality caregiving and social relationships.
Physiological Building Blocks of Well-being
There is a complex array of physiological systems involved in the stress response. This neurosymphony
of stress mobilizes particular resources in order to deal with stressors. While these systems work
in concert, they do not all respond the same way to the same stressors. Perhaps the most critical, and most
frequently studied, system involved in the stress response is the hypothalamic-pituitary-adrenal (HPA) axis.
The HPA axis response begins in the paraventricular nuclei (PVN) of the hypothalamus, a brain region that
is a central regulator of a wide range of homeostatic, autonomic and neuroendocrine processes. Multiple
neural signals regulate the activity of these PVN neurons according to signals from higher brain regions,
including the amygdala, hippocampus and prefrontal cortex (PFC; Ulrich-Lai & Herman, 2009). The
hypothalamus secretes corticotropin-releasing hormone (CRH) which activates the anterior pituitary to
secrete adrenocorticotropic hormone (ACTH) into the bloodstream. ACTH travels to the adrenal cortex,
which sends the HPA axis end-product cortisol throughout the body (Charmandari, Tsigos, & Chrousos,
2005). Circulating cortisol binds to its receptors that reside in most cells, facilitating its wide-ranging
influence on multiple systems. Once bound to its receptor, this glucocorticoid hormone is transported to the
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cell nucleus where it regulates protein synthesis for various genes. Peak cortisol levels are achieved 20-40
minutes after activation of the system. Cortisol operates by regulating the transcription of genes into
protein, processes that take minutes to hours to be achieved and whose effects may last days (Kirschbaum
& Hellhammer, 1994). The HPA axis is reliably activated by psychosocial stressors, but not necessarily to
stimuli like exercise, which results in non-social homeostatic disruption (Ulrich-Lai & Herman, 2009).
Circulating cortisol is regulated by its own negative feedback loop, reducing activity at all levels of
the HPA axis, to prevent excess amounts of cortisol that may have detrimental effects on physical and
mental health (Chrousos, 2009). However, in the context of severe, prolonged stressors, activating signals
override negative feedback and elevated levels of cortisol continue which may result in poorer well-being
(Strüber, Strüber, & Roth, 2014). Even in healthy individuals, increases in cortisol production seen
approximately 30 minutes following wake-up (cortisol awakening response), have been negatively
associated with trait well-being when they get too large (Smyth et al., 2015). In some cases, after a long
period of elevated cortisol, negative feedback mechanisms can overcompensate and result in lower than
normal cortisol production (i.e. hypocortisolism), which is also associated with poorer health and behavior
outcomes (Fries, Hesse, Hellhammer, & Hellhammer, 2005; Strüber et al., 2014).
The effects of the HPA axis are generally slow and long lasting. In contrast, the sympatheticadrenomedullary
(SAM) system responds rapidly and supports fight/flight. This system is a component of
the sympathetic nervous system (SNS) and is more reliably activated by any (internal or external)
environmental stimulus that disrupts the body’s physiological homeostatic balance and, to a lesser extent,
psychosocial stressors (Ulrich-Lai & Herman, 2009). The SAM system involves innervation of chromaffin
tissue in the adrenal medulla via the splanchnic nerve, which then releases epinephrine (Epi) and some
norepinephrine (NE) into circulation to act on systems throughout the body (Gunnar & Quevedo, 2007).
SAM activity amplifies the effect of the SNS which releases NE at synapses on many of the same target
organs (e.g. heart, lungs, pupils, blood vessels; Charmandari et al., 2005; Gunnar & Quevedo, 2007). In a
matter of seconds, heart rate and respiration increase to prepare the body for an immediate stress response.
The SNS is also influenced by the opposing branch of the autonomic nervous system, the
parasympathetic nervous system (PNS), which operates synergistically with the SNS and promotes ‘rest
and repair’ functions like digestion and bodily maintenance. Typically, the PNS suppresses or inhibits the
activity of organs involved in fight/flight, for example causing the heart to beat slower, or the pupils to be
less dilated. Upon detection of a stressor, the PNS usually releases its influence (i.e., ‘lifting the vagal
brake’), allowing organs under tonic inhibition (e.g., the heart) to rapidly increase their activity. This is
enhanced seconds later as the actions of the SNS take effect, resulting in large increases in heart rate and
blood pressure (Porges, 2007). Epi and the CRH produced outside of the hypothalamus act as positive
feedback mechanisms for the SNS (Chrousos, 2009); however, PNS activation dampens the effects of SNS
activity and returns the body to its resting state (Quas et al., 2014). In the context of chronic stress, the SNS
tends to be hyperreactive, and autonomic regulation shifts away from balanced activation of SNS and PNS
to an SNS-dominant system (Del Giudice, Ellis, & Shirtcliff, 2011).
These peripheral systems have upstream influences by widespread brain regions involved in
detecting and responding to real or imagined threats in the environment. The HPA axis is regulated by
CRH released by the hypothalamus, which is in turn regulated by the PFC, hippocampus, and amygdala
(McEwen, 2007; Ulrich-Lai & Herman, 2009). Given that the hypothalamus also plays a role in autonomic
functioning (Porges, 2007), neural regulation of the hypothalamus can have wide-ranging effects on the
stress response. Generally, the medial PFC and hippocampus have inhibitory effects on the hypothalamus
and are involved in the reduction or termination of the stress response (Ulrich-Lai & Herman, 2009), while
the amygdala has excitatory effects (McEwen, 2007). Cortisol alters the activity of the structures that
regulate its own production and, in doing so, alters thresholds for perceiving and responding to threat.
Large and/or chronic increases in cortisol reduce hippocampal and medial PFC functioning, weakening
their ability to terminate the HPA axis stress response and inhibiting learning and memory. Chronic cortisol
production also increases the activity of the amygdala, which may lower the threshold for responding to
threats and increase HPA axis activation (McEwen, 2007; Ulrich-Lai & Herman, 2009). All of these
consequences may result in impaired well-being across domains (Davidson & McEwen, 2012).
There are a number of hormones and neuropeptides that are neuromodulators of stress, beyond
CRH and NE. Oxytocin tends to reduce the HPA stress response, potentially through reduced expression of
hypothalamic CRH (Jurek et al., 2015; Zheng et al., 2010). CRH produced in the central nucleus of the
amygdala has widespread influence on neural systems that orchestrate fear responses and fear learning
(Gafford & Ressler, 2015). Serotonin has been shown to reduce the sensitivity of the adrenal cortex to
ACTH (Chen & Miller, 2012). Similarly, direct activation of serotonin receptors (5-HT1A) in the rat
hypothalamus reduces the amount of corticosterone (the rodent equivalent of cortisol) produced in response
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to restraint stress, a common rodent stressor that involves extended immobilization and restricted limb
movement (Stamper et al., 2017). Additionally, serotonin transporters in the adrenal medulla function to
reduce the SAM response in rats (Brindley, Bauer, Blakely, & Currie, 2017). These patterns may partially
explain why selective-serotonin reuptake inhibitors are a common treatment for anxiety and depression
(Hirschfeld, 2001). Dopamine may also be a critical modulator of the stress response. When activated,
CRH receptors in the ventral tegmental area release dopamine throughout the brain (Wanat, Hopf, Stuber,
Phillips, & Bonci, 2008). The ventral tegmental area has bidirectional connections with the PFC, and
increased levels of circulating dopamine produced by the nucleus accumbens are seen following acute (i.e.,
short-lived) stressors. However, exposure to chronic stress in infancy has been found to downregulate
dopamine expression (Gatzke-Kopp, 2011). Additionally, rats exposed to restraint stress showed an
increase in prefrontal NE followed by an increase in dopamine in the nucleus accumbens and PFC that does
not occur in the absence of increased NE (Pascucci, Ventura, Latagliata, Cabib, & Puglisi-Allegra, 2007).
Coordination Between Stress Systems
Clearly, these systems are highly interdependent and each system responds based on activity of
other systems. Additionally, genes influence the rate and amount of production of neuromodulators, their
receptors, and other molecules involved in the transmission of neural signals (Charmandari et al., 2005).
Every person has two copies of each gene (termed ‘alleles’) that may be identical to or different from each
other and those of another person. Particular alleles influence stress system regulation; for example, alleles
of the glucocorticoid receptor gene NR3C1 confer differential sensitivity to HPA axis negative feedback
(McEwen, 2007). Similarly, allelic variation impacts psychiatric outcomes associated with these stress
systems; for example, an allele of the monoamine oxidase A ( MAOA) gene that produces inefficient
MAOA functioning increases the risk for antisocial behavior following abuse (Caspi et al., 2002).
While the genes a person possesses are permanent, the capacity of genes in a specific cell to be
transcribed into protein (i.e., gene expression) is subject to change via numerous processes, including
epigenetic modifications. Epigenetic modifications are alterations to chromatin structure that do not change
the DNA sequence, but still can influence gene expression. Chromatin is comprised of the genes and their
packaging proteins (called ‘histones’). The more tightly the histones “package” the genes, which is
influenced by epigenetic modifications, the less likely that gene will be transcribed into protein. These
modifications are a key mechanism through which the environment and experiences produce lasting
changes on gene function (Boyce & Kobor, 2015). Rodent studies have found that epigenetic alterations of
the glucocorticoid receptor gene, NR3C1, are a function of the quality of early maternal care, and mediates
early care’s impact on stress responsivity in adulthood (Zannas & West, 2014). In humans, epigenetic
processes are mechanisms through which children who have experienced maltreatment are at higher risk
for various types of psychopathology (Lutz & Turecki, 2014). While epigenetic changes can be longlasting
and even transgenerational, they can also be reversible (Boyce & Kobor, 2015). This is promising
for the success of interventions and treatment following adverse early experiences.
Although there is a wide range of stress systems and neuromodulators that allow the body to
respond to diverse challenges, they tend to overlap in their functions (Joëls & Baram, 2009). There is
extensive cross-talk and coordination between systems, such that each system cannot truly be understood
except in the context of the rest. Countless studies have explored the link between HPA and sympathetic
activity in rodents, primates, and humans (for a review, see Schumacher, Kirschbaum, Fydrich, & Ströhle,
2013). Petrullo et al. (2016) found attenuated cortisol reactivity, but unchanged salivary a-amylase
reactivity (a peripheral marker of SNS activity), in juvenile rhesus macaques exposed to maternal abuse.
Gordis and colleagues (2006) found that attenuated cortisol reactivity was associated with increased
aggressive behavior in the context of lower, but not higher, a-amylase reactivity. Thus, it seems that
attenuated cortisol reactivity is associated with aggression; however, it is still unclear whether and how
SNS activity plays a role in this association. More research into the biological mechanisms underlying
these associations is also needed to investigate whether this is a causal relationship. Coordination between
these systems may also be associated with subjective stress and anxiety when discussing a conflict with a
romantic partner (Laurent, Powers, & Granger, 2013). Other studies have explored SNS/PNS activity
patterns (Blechert, Michael, Grossman, Lajtman, & Wilhelm, 2007; Winzeler et al., 2016), and their
relation to HPA activity (Quas et al., 2014). El-Sheikh and Erath (2011) found that coactivation or
coinhibition of the SNS and PNS, diverging from their typical asymmetry, presents greater susceptibility to
externalizing problems for children experiencing marital conflict. Rash et al. (2016) suggest that maternal
stress response profiles of HPA, SNS, and PNS activity may predict their child’s dysregulation of the same
systems. They propose that children with asymmetrical SNS/PNS activity and SNS/HPA activity are at the
lowest risk for behavioral problems and psychological well-being.
With the emergence of cross-system research, some have put forth theories that include activity of
multiple systems (Del Giudice et al., 2011; Joëls & Baram, 2009; Korte, Koolhaas, Wingfield, & McEwen,
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2005; Porges, 2007). However, many questions remain unanswered. These systems operate on different
time scales, and thus it is difficult to assess multiple systems within the same study. Similarly, while we are
often interested in brain activation of these systems, practical and technological limitations sometimes force
us to measure peripheral endpoints in blood, saliva, or activity of downstream systems (i.e. heart rate, skin
conductance). These measures may only be modestly correlated with activity of the brain regions
orchestrating the stress response. Moreover, responses are highly context-dependent and small
manipulations such as the presence of a caregiver can alter the stress response (Conner et al., 2012).
Finally, many studies have sought to find linear relationships between stress response systems. However,
some systems, the HPA axis in particular, have non-linear relationships with well-being, such that both too
much and too little activity are associated with poor outcomes (Chrousos, 2009). There is also reason to
believe that relationships between stress systems are non-linear. Future studies should address the
coordination between multiple systems using the most direct measures as possible, and acknowledge that
their interactions are likely complex and non-linear.
Developmental Processes in Well-being
In addition to interrelations between stress systems, there are many changes occurring with
development. Again, the most studied stress system in this regard is the HPA axis. Beginning in the
prenatal period, a child’s HPA axis develops in the context of the mother’s cortisol production which
impacts activity in the placenta (Gunnar, Doom, & Esposito, 2015). While the majority of the mother’s
cortisol is broken down by the enzyme 11b-HSD2, some cortisol still reaches the fetus intact and this
prenatal exposure may influence the child’s future HPA axis regulation (Oberlander et al., 2008).
Moreover, maternal cortisol stimulates the placenta to produce CRH which may activate the fetus’ own
HPA axis. Infants exposed to higher levels of cortisol in utero were less able to mount a sufficient cortisol
response to the Strange Situation, a maternal separation stressor paradigm, which may signify that fetal
programming of the HPA axis can have maladaptive effects on later stress regulation (O'Connor, Bergman,
Sarkar, & Glover, 2013). In the first few months after birth, infants typically start to develop a stable
diurnal rhythm. During the preschool period, with the end of regular daily naps, this rhythm starts to
resemble an adult-like pattern (Gunnar & Quevedo, 2007). There is some evidence to suggest that the
cortisol awakening response tends to increase across the entire lifespan (Miller et al., 2016).
The other stress response systems have much less research delineating normative developmental
changes. There is some evidence that heart rate, a measure of SNS activity, decreases with age and vagal
tone, a measure of PNS activity, increases with age (Alkon et al., 2003; Gunnar & Quevedo, 2007). An
increase in PNS activity may be associated with the development of emotion regulation, via the increased
ability to modulate physiological and behavioral responses to a stimulus (Gunnar & Quevedo, 2007).
Neuromodulators like serotonin are present at relatively high levels very early in fetal development, and
during this period serve as neurotrophic (i.e., nerve growth) factors that stimulate brain development.
Serotonin levels remain high for the first two years of life before gradually declining in childhood
(Whitaker-Azimitia, 2001). Further research should address developmental changes in all stress response
systems and their interactions in more detail.
The normative development of stress regulatory systems may vary by sex. These differences,
particularly in the HPA axis, tend not to be present until puberty (Doom & Gunnar, 2013). When
differences are found, males tend to have lower diurnal cortisol levels compared to females of the same age
(Miller et al., 2016). With puberty, differences in gonadal hormone production tends to facilitate
differential neural and HPA axis regulation (Del Giudice et al., 2011; Ordaz & Luna, 2012). Adolescent
females begin to have larger cortisol awakening responses that peak at 45, rather than 30, minutes
following wake-up (Schlotz, Hellhammer, Schulz, & Stone, 2004). Males begin to react to stressors more
strongly than females, however not all studies have found these sex differences (Doom, Hostinar,
VanZomeren-Dohm, & Gunnar, 2015; Ordaz & Luna, 2012). This inconsistency may depend on the type
of stressor (e.g. social evaluation, pain, performance, Del Giudice et al., 2011). Studies assessing sex
differences in autonomic reactivity have not always shown consistent effects either (Kelly, Tyrka,
Anderson, Price, & Carpenter, 2008); however, some studies have found that females tend to have
increased autonomic reactivity (Ordaz & Luna, 2012). Cortisol reactivity patterns may be a mechanism
through which females, particularly adolescents, are at heightened risk for depression and anxiety, however
the direction of these effects has been inconsistent (Natsuaki et al., 2009; Powers, Laurent, GunlicksStoessel,
Balaban, & Bent, 2016). For males, on the other hand, suppressed HPA and autonomic reactivity
may be associated with substance abuse (Fox et al., 2009).
Temperament is associated with stress regulation and reactivity and affects how children respond
to stressors. Temperamental fearfulness is associated with increased HPA axis activity to unavoidable
social challenges in non-human primates and preschool children (Kalin, Shelton, & Davidson, 2000; Talge,
Donzella, & Gunnar, 2008). Talge et al. (2008) also examined associations between fearfulness and
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autonomic activity but found no consistent relation. Infant surgency (low fearfulness, high impulsivity) is
also associated with elevated HPA and sympathetic reactivity (Laurent, Ablow, & Measelle, 2012);
however, this may be dependent on the social context (Gunnar, Sebanc, Tout, Donzella, & van Dulmen,
2003). In fact, several studies have shown that associations between temperament and stress reactivity
depend on the quality of the parent-child relationship or the child’s attachment to their primary caregiver
(Nachmias, Gunnar, Mangelsdorf, Parritz, & Buss, 1996; Smeekens, Riksen-Walraven, & Van Bakel, 2007)
with similar patterns emerging when predicting behavioral and emotion regulation (Kim & Kochanska,
2012; Thomas et al., 2017). Interestingly, the effect seems to be bidirectional – one study found that low
parent-child relationship quality predicted increases in negative emotionality across childhood but only
when the child also exhibited higher cortisol reactivity (Kopala-Sibley et al., 2015).
Social Relationships and Well-being
The parental figure is a primary example of how powerfully social relationships regulate stress
response systems. Better parenting quality has been consistently associated with healthier HPA axis
regulation (Albers et al., 2008; Martin, Kim, Bruce, & Fisher, 2014) and parasympathetic tone (Hinnant,
Erath, & El-Sheikh, 2015). Secure attachment relationships and higher quality parenting are effective
buffers from maladaptive stress outcomes for young children experiencing a wide variety of adversities
(poverty: Blair, Raver, Granger, Mills-Koonce, & Hibel, 2011; foster care, Fisher, Gunnar, Chamberlain, &
Reid, 2000, Oosterman, De Schipper, Fisher, Dozier, & Schuengel, 2010; maltreatment, Cicchetti,
Rogosch, Toth, & Sturge-Apple, 2011; international adoption, Pitula, DePasquale, Mliner, & Gunnar, in
press). Parenting quality may sometimes moderate the association between physiological regulation and
maladaptive behavioral outcomes, such that the poor outcomes only occur when the child also experiences
lower quality parenting (Barrios, Bufferd, Klein, & Dougherty, 2017; Bubier, Drabick, & Breiner, 2009).
Furthermore, the dysregulation of a parent’s own stress response systems may hinder their ability to
provide high quality parenting (Skowron, Cipriano-Essel, Benjamin, Pincus, & Van Ryzin, 2013).
The presence of a sensitive caregiver often reduces the reactivity of a child’s stress response
systems, particularly the HPA axis (i.e. parental social buffering, Gunnar & Quevedo, 2007). In rat pups, by
about 10 days of age the stress-hyporesponsive period ends and their HPA axis responds to aversive
stimuli, except (for approximately the next 10 days) in the presence of the mother (Sullivan & Perry, 2015).
This is similar to the capacity of the parent to buffer HPA axis responses by the end of the first year of life
in humans and is most prominent in secure attachment relationships (Gunnar, Brodersen, Nachmias, Buss,
& Rigatuso, 1996). Oxytocin, a critical neuromodulator involved in attachment and affiliative behavior,
may play a role in this phenomenon (Strüber et al., 2014). In one study, children who completed the Trier
Social Stress Test (TSST), a common social-evaluative stressor, and had full contact with their parent
immediately after showed both the lowest cortisol reactivity and the highest spike in oxytocin (Seltzer,
Ziegler, & Pollack, 2010). Even for adult males, having a best friend provide social support during TSST
preparation resulted in a smaller cortisol response, a larger increase in oxytocin, and less subjective stress
and anxiety (Heinrichs, Baumgartner, Kirschbaum, & Ehlert, 2003).
Still, there are developmental changes in the social buffering of stress reactivity. Parents essentially
block the entire stress response in infants (Gunnar et al., 1996). They are also more effective buffers for
children compared to adolescents. The loss of parental effectiveness as a stress buffer likely corresponds to
pubertal maturation (Gunnar & Hostinar, 2015). Who, then, takes over as the primary source of social
support? It turns out, it is not friends – at least not for social-evaluative stressors (Doom, Doyle, & Gunnar,
2016). In this study by Doom and colleagues, adolescents ages 15-16 showed a larger cortisol response to
the TSST when preparing with their caregiver compared to that of younger children ages 8-9. Adolescents
showed an even larger response when preparing with their best friend. Whether friends can be social
buffers under other conditions during this developmental period or whether the quality of the friendship
matters is not yet known. Certainly, by adulthood social partners can be effective buffers (Heinrichs et al.,
2003). The ability to utilize social partners to buffer the stress response in early development is likely
important for healthy physiological and brain development. It is possible that the apparent loss of this
ability in adolescence helps the body learn to independently self-regulate and develop more mature patterns
of stress system activity, however more research is needed to directly test this claim. Additionally, a
limitation to this body of research is the disproportionate use of decontextualized stressors. The TSST,
while a reliable way to activate the HPA axis, is one of many laboratory stressors that may not reflect how
a person would respond in the real world. Future research should delve further into the developmental
patterns of parental social buffering in more naturalistic contexts.
Nevertheless, it seems clear that the presence of a sensitive caregiver at particular points in
development is critically important for physical and psychological well-being. Positive parenting in
childhood can influence future HPA axis regulation and how children react to stressors years later (Hagan
et al., 2011; Shirtcliff, Skinner, Obasi, & Haggerty, 2017). Early parenting, over and above later parenting,
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is especially important for healthy physiological development (Loman & Gunnar, 2010; Sroufe, 1979).
During early development, rapid changes in neurological and physiological systems are the building blocks
for healthy functioning. The environment a child experiences during this time of heightened plasticity is
highly influential for how those systems develop (Luecken & Lemery, 2004). Early experiences set the
stage for physical, physiological, and psychological well-being across the lifespan.
Impact of Absent, Low Quality, and Inconsistent Relationships
Because early caregiving relationships have the potential to be a strong positive influence on
children’s development, they can also cause great harm when those relationships are absent, of low quality,
or inconsistent. The negative influence of early caregiving has been powerfully demonstrated in “natural
experiments” where children were exposed to extremely stressful or deprived environments early in life but
were later removed from those environments. For example, children who have been adopted from or
fostered out of orphanages/institutions have typically experienced unstable, inadequate care. In institutional
care children have multiple rotating caregivers with whom they have no real opportunity to form
relationships and little developmentally appropriate stimulation (Gunnar, Bruce, & Grotevant, 2000).
However, once adopted or fostered into families, their environments drastically change. Still, many postinstitutionalized
children have lingering physiological and behavioral deficits for several years following
adoption (Koss, Mliner, Donzella, & Gunnar, 2016; McLaughlin et al., 2015) and these deficits increase
their risk for psychopathological outcomes (Slopen, McLaughlin, Fox, Zeanah, & Nelson, 2012). Increased
caregiving quality following institutionalization has been shown to improve outcomes, however,
particularly in the HPA axis (DePasquale, Raby, Hoye, & Dozier, under review; McLaughlin et al., 2015).
Even in more typical circumstances, breakdowns in early caregiving are detrimental to a child’s
well-being. Children who have experienced maltreatment exhibit dysregulated HPA and autonomic stress
response systems and poorer socioemotional outcomes (McLaughlin, Sheridan, Alves, & Mendes, 2014).
Children in foster care, particularly those placed several times, also show HPA axis dysregulation (Fisher,
Van Ryzin, & Gunnar, 2011). Maternal depression and cumulative risk associated with poverty have been
associated with more negative parenting and thus dysregulated HPA axis and autonomic functioning (Evans
& Kim, 2007; Oberlander et al., 2008; Zalewski, Lengua, Kiff, & Fisher, 2012). In all of these instances –
maltreatment, foster care, and poverty – the very people who should be a child’s primary source of support
and positive experiences may become the source of extreme stress and neglect. This may enhance the
maladaptive consequences of those experiences, and significantly impact children’s ability to adapt
effectively over time. What remains to be studied in sufficient detail are the bidirectional effects between
the parent and child on child physiological development, and the dyad’s relationship quality and
physiological, behavioral, and emotional well-being over time.
Because of the powerful role of caregivers in children’s development, it is not necessarily the
presence of stressors, but the capacity of the parents to buffer and regulate stress that affects a child’s
physical and psychological well-being. Depending on the developmental time period, when buffering
systems fail stressors can have profound impacts on the entire network of stress response systems, which
drastically reduces a person’s ability to effectively adapt despite adverse experiences. Some stressors, like
early institutionalization, are powerful enough to offset the protective effect of a sensitive caregiver
encountered after adoption or foster placement. Institutionalization also highlights the specific importance
of experiences during the first few years of life when the stress response systems are developing rapidly.
Caregivers can affect well-being for better or for worse, and there are critical neurobiological mediators
involved in the experience of stress and the impact of caregiving throughout development. The timing and
nature of caregiving influences and adverse experiences may affect how these factors impact physiological
reactivity and regulation and, as a result, psychological well-being. While timing is central to understanding
development, it is precisely this area where we lack definitive answers. The question of sensitive periods
and periods of opportunity to recalibrate stress-responsive systems is at the cutting-edge of research on
stress reactivity, regulation and well-being.
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Foods, Sex, and Drugs: Appetitive Desires and Subjective Well-
Being
By Wilhelm Hofmann, Katharina Diel, & Magdalena Seibel, University of Cologne
Citation
Hofmann, W., Diel, K., & Seibel, M. (2018). Foods, sex, and drugs: Appetitive desires and subjective
well-being. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF
Publishers. DOI:nobascholar.com
Abstract
In their everyday environments, people spend a lot of time experiencing and dealing with appetitive desires
of all kinds, including those for foods, sex, and drugs. In this chapter, we review the concept of appetitive
desire and spell out its multifaceted link with subjective well-being. Our main conclusions are that,
oftentimes, appetitive desires are quite unproblematic and adaptive, and enacting them is typically a source
for affective and cognitive well-being. However, desires sometimes conflict with important long-term goal
or moral values, and their mere experience can be aversive. More importantly, the enactment of such
unproblematic desires appears to result in diminished hedonic gains, and is related to reduced cognitive
well-being. Having identified motivational conflict as the main source for the sometimes problematic
nature of appetitive desire, we conclude by discussing various ways through which individuals faced with
the dilemma of problematic desire may be able to optimize their subjective well-being.
Keywords: Desire, Self-Control, Well-Being, Motivational Conflict, Morality
Consider the last couple of hours before you started reading this chapter: Did you desire to
consume or acquire something? Perhaps getting a good-looking donut when passing that bakery? Perhaps a
coffee, if you are a regular coffee drinker, or a cigarette, if you are a smoker? Or did you desire to be close
to someone¾be it psychologically, or even physically? In their everyday environments, people spend a lot
of time experiencing and dealing with appetitive desires of all kinds. These include innate desires such as
for food, water, sex, and sleep, but also acquired desires such as for alcohol, cigarettes, and other (more or
less harmful) drugs. Typically, such appetitive desires are quite unproblematic and adaptive. And so,
enacting them is typically a source for short-term pleasure and happiness.
Things, however, can easily get more complicated: Sometimes a given desire conflicts with an
important long-term goal or moral value. Consider the alcoholic spouse who is fully aware of the fact that
giving in to the desire for another drink at the barbecue party will likely impair his ability to drive home
safely (putting him/her and other people at danger), or make him/her more flirtatious (putting his/her
spousal faithfulness to the test). The example illustrates that poor desire regulation may not only involve
possible personal costs (e.g., being fined for drunk driving or getting divorced, respectively), but also costs
to other people involved.
On an aggregate, societal scale, the consequences of poor desire regulation can be enormous.
According to an influential study, 40% of deaths in the United States each year have been estimated to be
attributable to behaviors that , directly, or indirectly, have to do with poor desire control, such as with
regard to unhealthy foods, tobacco, alcohol, unprotected sex, aggressive urges, and illicit drugs (Schroeder,
2007). Therefore, it seems important to both gain a better understanding of the antecedents that contribute
to successful and unsuccessful desire regulation, as well as of the consequences for health and well-being
that result from the way people deal with their appetitive desires.
The present chapter, therefore, is centered on the concept of appetitive desire. We will begin with a
brief definition of desire and desire regulation. In doing so, we will also touch on the neuropsychological
literature on appetitive desires, as well as on some of the key antecedents of poor desire regulation. This
will lead over to our main question in this chapter: how is the enactment or non-enactment of appetitive
desires such as for food, sex, and drugs linked to well-being?
Desire: Definition, Neuropsychological Basis, Similarity to Emotion
In colloquial language, the term desire can refer to all kinds of wishes and wants. Therefore, it is
important to more clearly define what we mean by desire in the context of this chapter: We use the term
“desire” here to refer to the more narrow sense of appetitive desire. Appetitive desire can be defined as a
“feeling of wanting that propels us to approach and consume objects or otherwise engage in activities that
satisfy a need and, in doing so, yield a gain in immediate pleasure (or relief from discomfort)” (Hofmann &
Nordgren, 2015, p. 5). Typically, appetitive desires are based in physiological need states; However, they
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can also be acquired through processes of reinforcement learning as in the case of drugs, media addiction,
spending urges, etc. (Martin-Soelch, Linthicum, & Ernst, 2007). Moreover, we use the term “craving” to
refer to desires across domains that are particularly high-intensity (e.g., drug craving, food craving).
How are desires represented in the brain? From a neuroscientific perspective, an often-replicated
finding is that the emergence of desire appears to be rooted in activity in largely subcortical neural regions
in the limbic system of the brain. The key region that lights up in dozens of desire-related studies is
commonly referred to as the reward center in the brain. The reward center is part of the so-called
mesolimbic dopamine system (Kelley, Schiltz, & Landry, 2005). Of particular interest is the so-called
nucleus accumbens (NAcc) in the ventral striatum. This structure seems to be implicated in the generation
of wanting experiences (Berridge, Robinson, & Aldridge, 2009; Peciña & Berridge, 2005). For instance,
one study connecting laboratory brain data and everyday life desire experiences, showed that individual
differences in NAcc activity during exposure to food cues in the scanner were reliably related to the average
strength of food desires in people’s everyday environments, as measured via experience-sampling (Lopez,
Hofmann, Wagner, Kelley, & Heatherton, 2014). Likewise, individual differences in NAcc responsivity to
food and sexual pictures have been shown to be predictive of subsequent weight gain and sexual activity 6
months later (Demos, Heatherton, & Kelley, 2012).
In sum, appetitive desire experiences appear to have its roots in deep-seated structures in the brain
that we share with most animals. However, the desire (i.e., reward-related) signals emanating from these
structures are then integrated, cognitively enriched and regulated in higher-order, prefrontal structures in
the brain, as the system needs to decide which course of action from the available options to take. This then
becomes an issue of desire regulation which we will touch on below.
From a conceptual perspective, a parallel can be drawn between the concept of desire and the
concept of an emotion (Hofmann & Kotabe, 2013). That is, like emotions, desires have an affective,
motivational, and cognitive dimension. Regarding the affective dimension, both desires and emotions are
accompanied a certain phenomenological feeling (the feeling of “wanting” in the case of desire). Regarding
the motivational component, desires as well as emotions prepare and motivate behavior. Desiring
something means wanting to have, consume, or do something that is expected to yield pleasure (or reduce
discomfort).
Regarding the cognitive component, both desire and emotions are subject to appraisal processes
and can thus be intricately linked to cognition (as reflected, for instance, in the affect-cognition debate of
emotion). The most prominent theory linking desire to cognition is the so-called elaborated intrusion theory
of desire (Kavanagh, Andrade, & May, 2005). According to this theory, desire is typically accompanied by
intrusive thoughts (including fantasies) about the object of desire. Moreover, desire and cognition can
reinforce each other in a dynamical way (see Hofmann & Van Dillen, 2012, for a related dynamical model
of this process): As a person engages in more and more cognitive elaboration of a given desire, the strength
of the desire typically increases. As the strength of desire increases, it captures more and more attention and
thus more mental resources are allocated to it in working memory. This is one explanation for why desires
can sometimes escalate to the point where, metaphorically, common sense goes out of the window. In other
words, the sometimes all-consuming, highly ruminative nature of intense cravings makes it increasingly
more difficult for conflicting goals and values to gain the upper hand in the struggle for limited working
memory resources (Hofmann, Friese, Schmeichel, & Baddeley, 2011; Hofmann & Van Dillen, 2012;
Kavanagh et al., 2005).
Desire Regulation (or, the Killjoy Society)
Whereas many desires are unproblematic and adaptive, more often than we may wish, desires
conflict with important self-regulatory or moral standards, goals, and values. This notion of intrapsychological
conflict turns a given desire into a special subclass, temptation (or problematic desire),
defined as a desire that stands in conflict with an important higher-order goal, standard, or moral value.
Examples include food (dieting; not eating animal food), sex (sexually transmitted diseases; remaining
faithful), and drugs (health, doing something illegal). It is thus clear that “desire” and “temptation” are not
synonymous terms (Hofmann & Kotabe, 2013; Hofmann & Van Dillen, 2012). Rather, “temptations” can
be conceptualized as a subset of desires, namely those that conflict with an important higher-order goal or
value. To put it in the words of philosopher Alfred Mele (2001), to say someone is “tempted” requires that
the person desires to do X and simultaneously has a good reason not to do X. Whether a person has good
reason not to do X will typically hinge on the “baggage” the person brings with him- or herself in terms of
endorsed self-regulatory goals, internalized or introjected values, or other competing motives and goals
(Kotabe & Hofmann, 2015).
At a general level, the unrestrained enactment of desire can either be self-harming or interfere with
the well-being of fellow citizens (or both). For instance, excessive alcohol consumption may not only harm
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one’s own body, but also have a disintegrating effect on one’s family members (e.g., impulsive acts of
family violence, failing to maintain a job). The capacity to regulate desire can thus be regarded as an
important prerequisite for participating in society. Ignoring this necessity can be quite costly. As Sigmund
Freud (1930) has so aptly put it in his seminal essay, Civilization and its Discontents, “An unrestricted
satisfaction of every need presents itself as the most enticing method of conducting one’s life, but it means
putting enjoyment before caution, and soon brings its own punishment.” Societies everywhere have
developed multiple mechanisms to deal with those who repeatedly fail at controlling desires. For instance,
repeated sexual offenders are typically removed from free society and confined to prison.
It is thus clear, that most people, most of the time, harbor good reasons against enacting
problematic desires. But where do these “good reasons” come from? Not surprisingly, many of these
reasons have become institutionalized as norms of proper conduct. That is, legal, religious, and educational
systems have always played an active part in the regulation of desires as these norms are passed onto (most)
members of society and ultimately internalized through the process of socialization. Presumably, the ideal
goal of such regulative attempts is to establish a consensual balance between individual liberty and
collective interests¾including public safety, order, and health, even if it comes at the cost of sacrificing
some individual pleasures (see Freud, 1930, for a classic treatment of this tradeoff).
In fact, the regulative power of morality runs deep, even beyond institutionalized normative
influence. According to the well-established moral foundations theory (Graham et al., 2013), morality is
based on several core moral principles: Care (i.e., “don’t harm other people”), Fairness (i.e., “don’t pursue
your own advantage in disproportionate ways”), Loyalty (i.e., “don’t betray your in-group”); Authority
(i.e., “don’t disrespect laws, rules, and authority figures”), and Sanctity (i.e., “don’t do something
“impure” or “indecent”). Another, separable core moral principle may be Honesty (i.e., “don’t manipulate
the truth”; Hofmann, Wisneski, Brandt, & Skitka, 2014). Each of these principles can serve as a moral
reason of desire regulation in the sense of a moral “ought” (i.e., proscriptive morality; Janoff-Bulman,
Sheikh, & Hepp, 2009). Accordingly, self-control goals often appear to be moralized (e.g., Haidt & Hersh,
2001; Mooijman et al., in press; Rozin & Singh, 1999). For instance, it is easy to see how harm (e.g., rape),
disloyalty (e.g., infidelity), disrespect of authority/law (e.g., sex with a minor), impurity/disgust (e.g., sex
with a sibling), or dishonesty (e.g., pretending to be a star when you are not) can all serve as good reasons
or moral principles for why (people think) a person should think twice about advancing and enacting a
given sexual urge.
Appetitive Desire and Well-Being
Having thus laid the foundation for the concept of appetitive desire, as well as its tension with
societal affordances that require the motivation and capacity for the control of certain desires, we now turn
to the even more complex issue of how appetitive desires such as food, sex, and drugs relate to subjective
well-being. To better understand this complex picture, and introduce some meaningful demarcations, we
will distinguish between (a) affective (i.e., hedonic) well-being and cognitive well-being (i.e., life
satisfaction), (b) the experience and the enactment of desire (and its consequences), and (c) between
unproblematic and problematic desires (i.e., temptations). The resulting organizational scheme is presented
in Table 1. In a nutshell, we distinguish between affective and cognitive well-being to acknowledge the
well-established fact that these two facets of subjective well-being can be clearly separated, and have
different predictors and consequences (Diener & Chan, 2011; Lucas, Diener, & Suh, 1996; Luhmann,
Hofmann, Eid, & Lucas, 2012). This opens up the possibility that the two major dimensions of well-being
may be differentially affected by appetitive desires and their regulation. We distinguish desire experience
and enactment to suggest that even the experience of desire may, under certain conditions, be aversive and
thus reduce affective well-being. And we distinguish unproblematic and problematic desire because
problematic desires may pose quite different challenges for well-being than unproblematic ones.
Table 1. Organizational Scheme of the relationship between appetitive desire and well-being. The
taxonomy distinguishes between desire experience and enactment, affective and cognitive well-being,
and unproblematic and problematic desire. Parts printed in gray font are only briefly discussed in
the present chapter.
Desire Experience Desire Enactment
Affective Well-Being Unproblematic Desire Unproblematic Desire
Problematic Desire Problematic Desire
Cognitive Well-Being Unproblematic Desire Unproblematic Desire
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Problematic Desire Problematic Desire
Experiencing Desire and Affective Well-Being:
The Role of Ambivalence and Conflict
How does the experience of appetitive desires such as for food, sex, and alcohol relate to in-themoment
affective well-being? As mentioned above, desires are characterized by a phenomenological state
of wanting. This state has often been described as ambivalent (Kavanagh et al., 2005): On the one hand,
there is tantalizing enchantment from anticipating pleasure (“imaginary relish”). On the other, there is
frustration from not (yet) having had the opportunity to consume the source of the desire ("exquisite
torture"; Kavanagh et al., 2005). So, even in the case of an unproblematic desire, the combined effect of
experiencing a given desire on affective well-being may depend on the relative strength of the positive and
negative ingredients of this “mixed” (ambivalent) emotional state (Larsen, Coles, & Jordan, 2017). If the
positive ingredient of the anticipated reward is relatively larger, desire is likely to be positive in tone.
However, note that in the case of unproblematic desire, the ambivalence emerges entirely within one given
motivational stream of action (e.g., “longing for one’s partner”).
In the case of problematic desire, however, the ambivalence is arguably much more intense. The
reason is that a major source of additional negativity enters the psychological scene: As mentioned above,
problematic desires imply intra-psychological conflict between motives. There is the literal struggle
between “two souls” within oneself: One part wants something and pushes for action, but another part
inside urges caution and voices “good reason” for why one should not (Hofmann, Friese, & Strack, 2009;
Milkman, Rogers, & Bazerman, 2008). Such motivational conflict has consistently been shown to be an
aversive, unpleasant affective experience in a large body of research (e.g., Emmons & King, 1988;
Nordgren, Van Harreveld, & Van Der Pligt, 2006; van Harreveld, Nohlen, & Schneider, 2016). Further
evidence comes from the literature on cognitive conflict and error-related brain activity which likewise
suggests that experiencing motivational conflict is aversive in nature (see Inzlicht & Legault, 2014, for a
review). In a related vein, of course, the literature on cognitive dissonance has long suggested that holding
conflicting thoughts in mind is an affectively negative experience (Festinger, 1957; Proulx, Inzlicht, &
Harmon-Jones, 2012). A paper from a large experience-sampling project on self-control (Hofmann,
Baumeister, Förster, & Vohs, 2012) has directly compared momentary levels of affective well-being for
(non-enacted) unproblematic desires and (non-enacted) problematic desires (Hofmann, Kotabe, &
Luhmann, 2013). The study found that the no-enactment baseline for problematic temptations was
substantially lower than the no-enactment baseline for unproblematic ones, suggesting that the fact of being
in a tempting, conflicting situation was experienced as considerably more aversive than when self-control
demands were absent.1
In summary, the relation between experiencing appetitive desire and momentary well-being may
depend on how problematic the desire is, that is, how much motivational conflict it entails. The available
evidence consistently suggests that the experience of a desires that conflict with important self-regulatory
goals or values is accompanied by higher levels of ambivalence and, hence, reduced affective well-being as
compared with the experience of unproblematic desires. It was recently hypothesized that motivational
conflict in desire control may be a function of desire strength, opposing goal strength, and their degree of
incompatibility (Kotabe & Hofmann, 2015). Future research manipulating these or other aspects of
motivational conflict may arrive at a more fine-grained picture of this relation.
Throughout this section, we have avoided discussing the relationship between in-the-moment
desire experiences and cognitive well-being/life satisfaction, a decision that was motivated by the absence
of a substantial amount of literature that would speak to this possibly more remote connection. Perhaps the
(repeated) mere experience of unwanted desire intruding into consciousness and sticking around may lower
one’s life satisfaction via self-attributions of low control and perceived helplessness as mediating
mechanisms. Future research will have to clarify this largely unknown territory.
Enacting Appetitive Desire and Affective Well-Being
What is the effect of enacting appetitive desires on affective well-being? The standard answer from
motivation science is that the pursuit of pleasure (and avoidance of pain) is one of the most fundamental
principles of motivation (Carver & Scheier, 1990; Hull, 1943; Lewin, 1935). That is, humans generally
experience a temporary gain in affective well-being by fulfilling millennium-old basic needs such as the
need to eat, rest, and reproduce, or acquired appetitive desires such as those for drinking alcohol or
receiving likes on facebook.2 For instance, large surveys as well as daily diary studies from relationship
research have consistently found a positive effect of sexual activity on indicators of affective well-being
(Blanchflower & Oswald, 2004; Hofmann, Finkel, & Fitzsimons, 2015; Muise, Schimmack, & Impett,
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2016). Using the daily diary method, Oishi, Schimmack, and Diener (2001) found that people felt happier
on days when they fulfilled physical desires such as for food or sex compared to days when they did not.
Likewise, across several thousand observations from more than a dozen desire domains sampled from
everyday life, a positive enactment gain on in-the-moment affective well-being was obtained,
corresponding to a large effect size of about d = .90 (Hofmann et al., 2013). With regard to unproblematic
desire, the equation thus seems straightforward: enacting appetitive desire boosts affective well-being, at
least in the short run.3
Concerning problematic desires, however, motivational conflict enters the scene, and a highly
interesting question emerges: What gain in affective well-being does enacting problematic desire bring
about? Scholarly and public opinions about the instant utility of giving in to temptation run deep among
political, religious, and cultural divides (Veenhoven, 2003). Overall, four quite different “lay” hypotheses
about the outcome of such a comparison can be found. Their respective predictions are summarized in
Figure 1 (see Hofmann et al., 2013).
The pure hedonism hypothesis holds that the gain in affective well-being resulting from enacting a
tempting desire would be no different from the gain in momentary happiness resulting from enacting a
comparable unproblematic desire: A cake is a cake. Take two people, one harboring no dieting goal
whatsoever, the other being hard-pressed to diet: in both cases, the basic principle of need satisfaction
would predict that consuming the object of desire sets free the same amount of pleasure units (for cake,
these are sometimes also referred to as “calories”). According to this view, temptations have their
downside, or course, but these negative effects lie in the delayed and uncertain future.4 The forbidden fruit
hypothesis suggests that enacting problematic desires is accompanied by a special allure that may add an
additional boost for affective well-being. In contrast, both the spoiled pleasure hypothesis and the backfire
hypothesis predict that enacting problematic desire yields a reduced hedonic payoff when compared with
the unproblematic desire case. This reduction may be due to the impact of self-conscious emotions: Humans
are not only equipped with basic emotions but also subject to emotions of self-assessment, such as guilt,
regret, and pride (Taylor, 1985; Tracy, Robins, & Tangney, 2007). Thus, according to this view, affective
well-being results from the combination of primary, basic and secondary, self-conscious emotional
experience. Yielding to temptation may thus be like a “mixed blessing” for affective well-being: a feeling
of pleasure that adds to affective well-being, but at the same time a constellation of self-conscious emotions
(e.g., heightened guilt) that subtracts from it. The resulting net effect differs for the spoiled pleasure and
the backfire hypothesis. In the former, the pleasure derived from enactment still outweighs the effect of
self-conscious emotions; in the latter, the net effect is negative (see Figure 1), hence, from a happinessmaximization
perspective, temptations are not even worth it in the “here and now”.
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Figure 1. Four hypotheses regarding the extent of gain or loss in affective well-being due to the enactment
of problematic appetitive desire in comparison with the enactment of unproblematic appetitive desire.
Reprinted/adapted by permission from Springer: Copyright Springer; Journal: Motivation and
Emotion, Authors: Hofmann et al., 2013, Figure 1.
First empirical evidence seems to support the spoiled pleasure account (Hofmann et al., 2013). That
is, enacting problematic desires resulted in a considerably smaller, but still positive, gain in affective wellbeing
(only a small positive effect of d = .13) as compared to unproblematic desires. Furthermore, the
effect was not moderated by whether the desire domain in question is generally assumed to be addictive or
not (Hofmann et al., 2013).
In sum, whereas there is strong evidence for a general boost in affective well-being for desire
enactment, this effect has mainly been researched without a clear distinction between unproblematic and
problematic desires. Given that the majority of appetitive desires are rather unproblematic in nature
(Hofmann et al., 2012), this general positive effect is not surprising. However, distinguishing among
unproblematic, and problematic (i.e., motivationally conflicting) desires reveals a considerably reduced
hedonic gain for the latter type of desire. This novel finding from the field challenges the long-standing
assumption underlying the ‘‘pure hedonism’’ hypothesis, according to which giving in to temptation would
produce similarly rewarding immediate hedonic payoffs as the fulfillment of unproblematic desires, and
would thus incur only delayed costs. Future experimental research will have to more closely investigate this
intriguing possibility.
Enacting Appetitive Desire and Cognitive Well-Being
The final question we want to address is how the enactment of appetitive desires relates to
cognitive well-being. Cognitive well-being refers to global or domain-specific evaluations of life. The most
central and important aspect is global life satisfaction (“life satisfaction” henceforth), a cognitive judgment
about how well one’s life is going in general. The concept of life satisfaction is thus very similar to the
Aristotelian notion of eudaimonic well-being, a sense that one is leading the “good” life, that one’s life is
“well-lived.” So, in contrast to affective well-being which is experiential in nature, cognitive well-being
requires that people “take a step back” to view and evaluate the way they lead their life (over larger timespans)
and cognitively weigh and integrate various sources of information.
Because the frequent fulfillment of unproblematic needs and desires adds to affective well-being,
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and since there is little reason to question whether enacting these desires is time and effort well spent, it is
straightforward to assume that the evaluation of one’s frequent rather than infrequent enactment of
unproblematic desires would generally be positive and thus contribute as one (out of many) sources for life
satisfaction. Accordingly, the above-mentioned diary study by Oishi and colleagues (2001) also found that
the average pleasure from fulfilling basic, physical desires positively contributed to life satisfaction (see
also Tay & Diener, 2011). Moreover, because what is judged to be good is ultimately a value judgment, it
is possible, that the fulfillment of basic appetitive needs may receive a stronger relative weight in those
who prioritize the value of hedonism over and above other values in life (such as, for example, security,
power, or achievement; Schwartz & Bilsky, 1987). Some evidence for this conjecture comes from the
finding that people high in sensation seeking showed a stronger relationship between physical pleasure
fulfillment and daily social life satisfaction (Oishi et al., 2001). In plain terms, if you value the pleasures of
life a lot, seeing yourself harvest many of them will generally give you the sense that you are living your
life in an optimal, authentic way. The desire to experience pleasure and happiness is also one focus of
consumer research: Hedonic consumption is defined as the purchase of products that fulfill fantasies and
satisfy emotions (Hirschman & Holbrook, 1982). In contrast to utilitarian consumption, which is
characterized by the purchase of functional and necessary products, hedonic consumption has the essential
feature of simply bringing pleasure or fun (for a review, see Alba & Williams, 2013). Consuming hedonic
products improves satisfaction with the relevant life domains, and thus, increases cognitive well-being,
based on a longitudinal study (Zhong & Mitchell, 2010).
Again, since most desires are unproblematic, the above general findings may somewhat cloud what
can be gleaned with regard to problematic desires. Note that, with regard to affective well-being, our
conclusion was that enacting problematic desire results in spoiled pleasure, but still a positive gain in
affective well-being. In contrast, there is converging evidence from multiple areas of research suggesting
that things take on a more negative spin when it comes to the cognitive evaluation of one’s life: First, as
discussed in length above, problematic desires are problematic for a good reason, and their - repeated or
just one-time - enactment may wreak considerable havoc such as serious or even lethal health problems
due to overweight, sexually transmitted diseases, continuous substance abuse or drug overdoses, or other
problems such as poor social integration (Moffitt et al., 2011; Mokdad, Marks, Stroup, & Gerberding,
2004; Schroeder, 2007; Shoda, Mischel, & Peake, 1990). One of the key insights from work on self-control
and weakness of will is that lack of awareness of/knowledge about these negative consequences is often not
the key issue – rather motivational and volitional problems are central (Kotabe & Hofmann, 2015); hence,
it can be supposed that most people who are low in self-control, most of the time, are well aware of the fact
that their giving in to temptation may have negative long-term consequences. Second, from the perspective
of dual motive conflicts, temptations can be regarded as obstacles with regard to making progress on the
competing long-term goal; Hence, overly frequent indulgence that goes beyond people’s ideal balance
between the two motives may go along with the perception of insufficient progress towards important goals
and aspirations (Hofmann, Luhmann, Fisher, Vohs, & Baumeister, 2014a; Wiese et al., in press). Third,
there is the social environment: People who overindulge in problematic desires may receive frequent
negative feedback from close others, doctors and caretakers, observers, including negative moral judgment
directed towards oneself (Nordgren, van der Pligt, & van Harreveld, 2007). And fourth, the repeated
enactment of desires one better ought to control may give rise to the sense that one is lacking internal
control of one’s inner driving forces (i.e., desires) that instigate the problematic behavior. Lack of
perceived control is a well-known negative correlate of life satisfaction (e.g., DeNeve & Cooper, 1998),
and research in problem populations such as obese people (e.g., Greeno, Jackson, Williams, & Fortmann,
1998) or teenagers experimenting with cigarettes and alcohol (Adalbjarnardottir & Rafnsson, 2001)
supports the role of perceived control as one possible mechanism.
In sum, knowledge about negative consequences, insufficient long-term goal progress, negative
social feedback, and perceived lack of control over one’s behavior may all contribute to a negative
evaluation of the way one conducts one’s life. Accordingly, there is strong and often replicated evidence
that individuals who describe themselves as low in self-control, as typically measured via the brief trait selfcontrol
scale (Tangney, Baumeister, & Boone, 2004), score higher on life satisfaction than those who
describe themselves as high in self-control (Hofmann et al., 2014a; Wiese et al., in press), and alternative
measurement approaches in more specific domains such as obesity support this view (Stutzer & Meier,
2016).
Is the relationship between self-control and subjective well-being a monotonic, linear function, or
can there be too much of a good thing? Recently, Wiese and colleagues (in press) have scrutinized the
theoretical possibility that too much self-control may have harmful implications for subjective well-being
which might be due to overregulation of cognition, emotion, and behavior or obsession with
accomplishment of long-term goals at the expense of happiness; However, across multiple studies,
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methods, and measures there was no support for an inverted-U effect of self-control on subjective well-
being.
Summary and Outlook
In this chapter, we have reviewed the link between appetitive desires such as for food, alcohol, and
sex on subjective well-being. We set out by noting the dilemma between the ubiquity of appetitive desires
as internal driving forces and the necessity for the regulation of “problematic” desires both for individual
(e.g., health-related) reasons and for societal welfare. How individuals solve this dilemma appears to have
important implications for subjective well-being. Our review of the connection between desire and
happiness was guided by our proposal that a fine-grained analysis of this link needs to distinguish, at
minimum, between affective and cognitive well-being, unproblematic and problematic desires, and the
experience and enactment of desire. Our main conclusions from surveying the available evidence are that
(1) the experience of problematic (as compared to unproblematic) appetitive desire seems to be associated
with a temporary drop in affective well-being, (2) the enactment of problematic (as compared to
unproblematic) appetitive desire provides only “spoiled” pleasure, that is, a substantially reduced boost in
momentary affective well-being, and (3) the frequent enactment of problematic (as compared to
unproblematic) appetitive desire is associated with reduced cognitive well-being (i.e., life satisfaction). A
lot of empirical effort is still needed, however, to better understand the mechanisms that give rise to these
effects, such as the mechanisms that mediate between repeated self-control failures and low life
satisfaction.
From a practical perspective, the present analysis identified problematic desire as the main culprit.
This view suggests that happiness may be optimized by either becoming a master at inhibiting the
enactment of problematic desires through interventive self-control or by avoiding or even eliminating
problematic desire experiences as much as possible through preventive strategies of self-control which,
ultimately, may be more successful. (Fujita, 2011; Hofmann & Kotabe, 2012). Note, however, that
problematic desires may also be eliminated through changes to one’s mental landscape, i.e., the types of
goals, moral values, and viewpoints one endorses. Though existing ideologies and moral systems typically
offer such viewpoints (for free), one need not necessarily buy into them. Luckily, as people keep
questioning and reasoning about moral values, there is overall moral progress (Shermer, 2015). One of the
major, continuing challenges of societies, therefore, is to identify and demarcate the truly morally
problematic forms of desire enactment from those that may be in need of revision and, possibly,
unmoralization. As the moral landscape changes, new and better equilibria for balancing individual
happiness and societal welfare may emerge.
Footnotes
1 As an aside, an interesting question, inspired by Buddhist philosophy, is whether, given the ambivalence
of desire, a life with substantially reduced desire or even without experiencing desire at all may be the peak
of happiness? We believe that the answer may depend on the type of desire experienced: Desiring
something unproblematic and attainable may be associated with levels of momentary affect that may lie
above the “Buddha” baseline of no desire experience; such a finding would also be consistent with research
on the lack of motivational drive, or anhedonia (Treadway, 2015); However, experiencing a problematic
desire (temptation) may lie below that baseline for the above reasons of introducing aversive intrapsychological
conflict.
2 Even though not the focus of the present chapter, this general principle also entails the satisfaction of
basic psychological needs (Tay & Diener, 2011), as spelled out, for instance, by self-determination theory
(Ryan & Deci, 2000).
3 Of course, such effects are temporary, as inherent in the idea that desire (needs) and desire fulfillment
(need satisfaction) are parts of the cycle of homeostatic regulation. There is some dearth of longitudinal
studies involving substantially longer time spans which would allow drawing conclusions about the extent
to which being able to regularly fulfill important basic, hedonic needs is causally linked to increased
general levels of affective well-being.
4 Note that this is the standard utilitarian explanation for why people (sometimes) yield to temptation: They
expect the immediate reward resulting from temptation enactment to outweigh the (temporally discounted)
long-term reward resulting from resistance (Ainslie, 2001; Thaler & Shefrin, 1981).
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Hormones and Well-being
By Jerrald L. Rector & Elliot M. Friedman, Purdue University
Citation
Rector, J. L., & Friedman, E. M. (2018). Hormones and well-being. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
The growing evidence that positive psychological functioning is linked to favorable health outcomes has
led to a search for biological mechanisms that may underlie these salubrious effects. Although there is
interest in biological processes that are uniquely related to positive psychological functioning, most work to
this point has centered on those with known associations with adverse psychological experiences, such as
stress and depression. This chapter reviews the existing literature on the ways in which psychological wellbeing
(broadly defined) is linked to hormone systems in the body (endocrine and neuroendocrine). The
chapter is structured by hormone system. Given the newness of the field, this literature is understandably
limited, and conclusions about such links are consequently tentative. Nonetheless, the overall picture is
promising, and links between hormone systems and psychological well-being should be a vibrant area of
future research with critical implications for physical and mental health.
Keywords: well-being, optimism, HPA axis, cortisol, catecholamines, metabolic hormones, oxytocin,
prolactin
Psychological well-being has been linked to a broad range of health outcomes, most notably
reduced risk of diverse forms of morbidity and general mortality (Chida & Steptoe, 2008; Giltay, Geleijnse,
Zitman, Hoekstra, & Schouten, 2004; Hill & Turiano, 2014; Pressman & Cohen, 2005), and there is a large
and growing literature devoted to illuminating the biological mechanisms that may underlie these health
effects. Although there is interest in identifying biological processes that may be unique to positive
psychosocial functioning (Kubzansky, Boehm, & Segerstrom, 2015), the bulk of existing research has
examined the ways in which well-being affects and is affected by well established biological responses to
adversity, including those related to immune and endocrine function (Friedman, 2012; Steptoe, Dockray, &
Wardle, 2009). The focus of this chapter is on connections between well-being and endocrine biology,
including bi-directional influences.
The construct of well-being can be operationalized in a variety of different ways. There exists, for
example, two broad categories of well-being measures – hedonic and eudaimonic – reflecting different
ideas of what it means to lead a good life, a debate that stretches back to Greek philosophical disputes.
While hedonic well-being comprises various elements of emotional life (such as positive and negative
affect and satisfaction with life), eudaimonic well-being focuses more on the realization of individual
potential through meaningful engagement (Ryan & Deci, 2001; Waterman, 1993). While the two are often
correlated, they are distinct in a number of relevant ways, including how they change with age and how
they relate to a range of outcomes, including health (Cole et al., 2015; Friedman, 2012; Ryff, 2014; Ryff &
Keyes, 1995). There are additional indicators of positive psychological functioning, such as optimism, that
do not fit neatly into one category. In this chapter we define well-being broadly and consider links between
diverse endocrine systems and multiple aspects of well-being.
An important point to make at the outset is that this chapter focuses on research featuring explicit
measures of well-being, not ill-being. That is, there is a large and long-standing body of research on the
endocrine, neuroendocrine, and autonomic correlates of clinical and sub-clinical mental illness, chronic
stress, and the like. But there is substantial evidence that well-being is not merely the absence of ill-being
(Keyes, 2002; Pressman & Cohen, 2005; Ryff et al., 2006). For example, studies in which more
advantageous profiles of endocrine function are observed in those with lower levels of stress or depression
have not necessarily demonstrated the biological impact on well-being. For this reason, with only a few
exceptions we constrain our review to research assessing indicators of well-being. See Table 1 for an
overview of the hormones, their function, and a brief summary of evidence in relation to well-being.
Table 1
Hormone function and summary of associations with well-being
Function Summary
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Adrenal hormones
Cortisol Elevates blood glucose levels; activates
anti-stress and anti-inflammatory
pathways.
Well-being is linked to optimal daily cortisol
regulation and buffering of adverse
experiences.
DHEA(S)* Androgen; intermediate in sex steroid
biosynthesis; binds to neurotropin
receptors.
Supplementation in older adults increases well-
being
Catecholamines Initiates cascade of physiological
changes, mobilization of resources in
response to stressors.
Studies linking catecholamines and well-being
are mixed and inconclusive.
Sex hormones
Testosterone Controls expression and maintenance of
male-specific characteristics; regulates
sexual differentiation and behavior.
Weak evidence linking testosterone to wellbeing
in older adults. Studies lacking in younger
adults.
Estrogen Controls expression and maintenance of
female-specific characteristics;
regulates sexual differentiation and
behavior.
Evidence linking estrogen to well-being is
largely absent. Studies across wider age ranges
are needed.
Metabolic hormones
Insulin-like growth
factor
Involved in neuronal survival,
neurogenesis, angiogenesis,
neurotransmission, regulation of food
intake, and cognition.
Inversely associated with well-being; binding
protein directly linked to well-being.
Associations likely age- and sex-specific.
Insulin Regulates macronutrient metabolism by
promoting absorption of glucose into
tissues.
Intranasal insulin improves mood and attenuates
reactivity to social stress; association may be
dependent on age and ethnicity.
Thyroid hormones Regulates physiological functions,
including growth and development,
metabolism, body temperature, and
heart rate.
Generally positively linked to well-being, but
evidence is mixed; age, sex, and thyroid
function contribute to these associations.
Other hormones
Oxytocin Facilitates labor during pregnancy;
promotes maternal bonding, sexual
behavior, and affiliation
Intranasal administration has inconsistent
associations with mood; links to well-being
appear to be moderated by receptor genotype.
Anti-diuretic hormone Stimulates water retention and
vasoconstriction; promotes pairbonding
behavior
Limited evidence suggests positive relationship
to happiness; receptor type may influence
associations in a sex-specific manner.
352
Prolactin Regulates water and salt balance, breast
milk production, cell proliferation and
differentiation, T-cell immunity,
pancreatic β cell function,
hematopoiesis, and adipogenesis
Limited number of studies suggest sex-specific
positive associations with well-being. Positive
behavior patterns during conflict were also
associated with higher levels among women.
*DHEA(S) – Dehydroepiandrosterone (sulfate)
Adrenal Hormones
The adrenal glands, located above the kidneys, are composed of an inner medulla and an outer
cortex that together produce a number of hormones, including cortisol, dehydroepiandrosterone (DHEA),
epinephrine and norepinephrine, among others. These hormones play key regulatory roles across multiple
physiological systems. Most notably, the hormones produced by the hypothalamic-pituitary-adrenal (HPA)
axis and the sympathetic-adrenal-medullary (SAM) axis help coordinate whole-body adaptive responses to
acute and chronic stressors and other environmental challenges encountered in daily life. For a more
detailed treatment of the HPA axis, the SAM axis and their role in the stress response and well-being, see
DePasquale and Gunnar in this volume (Chapter 22).
Dysregulated levels of adrenal hormones have marked negative consequences for diverse
physiological functions, and numerous syndromes and disorders characterized by aberrant hormone
production are well-documented (Charmandari, Nicolaides, & Chrousos, 2014; Lacroix, Feelders,
Stratakis, & Nieman, 2015; Zografos, Perysinakis, & Vassilatou, 2014). Conversely, the maintenance of
efficient regulation of these hormones, not only day-to-day but across the life course, corresponds to
optimal functioning and health. In addition, steroid hormones such as cortisol and DHEA can cross the
blood-brain barrier (Banks, 2012) where they have marked influences on both neurophysiology and
subjective psychological experience; these influences are observed in the context of stressors and during
normal daily activity. The ability of adrenal steroids to influence the brain directly highlights bidirectional
influences that are relevant for this chapter: well-being affects the regulation of adrenal hormones, and
circulating adrenal hormones can affect subjective experiences of well-being.
Cortisol. The steroid hormone cortisol is the main downstream effector of the HPA axis. Cortisol
serves to elevate blood levels of glucose, by liberating existing stores or initiating glucose synthesis, to be
used by muscles and the brain for daily activity and responses to environmental challenges. It also activates
potent anti-stress and anti-inflammatory pathways.
Cortisol is present in diverse tissues, including blood, urine, saliva, and hair, and cortisol levels
from these different sources provide information on different aspects of HPA function. To illustrate,
cortisol levels in blood and saliva can change over the course of minutes and hours, providing a lens into
acute changes in the physical and psychological state of the organism. Levels in urine and hair, in contrast,
reflect longer-term accumulation, and analysis of cortisol in these tissues can inform about chronic patterns
of HPA activity. Importantly, cortisol concentrations determined from different tissues within the same
person often show weak inter-correlations, emphasizing the distinct aspects of HPA functioning that
different modes of assessment provide (Rector, Tay, Wiese, & Friedman, unpublished data).
In general, cortisol has been used to study the impact of negative subjective experience (e.g. stress,
depression) on health via dysregulated HPA axis activation. There are, however, associations between
cortisol and well-being that are distinct from these links to ill-being. To this point, cortisol is the beststudied
hormonal correlate of well-being.
A currently popular mode of assessing HPA regulation involves tracking fluctuations in cortisol
across the day. Cortisol has a strong diurnal pattern, with a peak soon after awakening and a nadir right
before the onset of sleep. To assess diurnal cortisol, 4 samples are typically collected: one upon awakening,
a second 30 minutes later, a third before lunch, and the fourth before bedtime. The timing of these samples
makes it possible to capture several important parameters of the diurnal cortisol rhythm: the waking value,
the cortisol awakening response (CAR) – the rise from waking to 30 minutes later, during which cortisol
concentrations increase by around 50% – the decline to mid-day, which is usually the steepest part of the
daily decline, and the concentration approaching the typical nadir, which both allows for calculation of the
cortisol slope, or rate of decline across the entire day, and the value of the nadir, which has been shown to
be meaningful for mental health in itself. Cumulative cortisol production across the day can also be
estimated as the cortisol area under the curve (AUC). Diurnal cortisol regulation is a particularly attractive
focus for research as many of these parameters are stable across measurement occasions (i.e., trait-like)
while also being sensitive to acute life challenges (i.e., state-like).
353
There are at least two major features of the diurnal cortisol profile that show distinct patterns in
relation to positive psychosocial functioning: the CAR and the slope (of cortisol levels over the day). In a
study of 80 healthy Chinese adults aged 19-55 years, greater positive affect was associated with a steeper
diurnal slope, but was unrelated to the CAR (Lai et al., 2005). Conversely, a later study using participants
from the Family Heart Study (mean age: 31 years) found that greater positive affect was associated with a
less pronounced CAR, but was unrelated to the diurnal decline (Brummett, Boyle, Kuhn, Siegler, &
Williams, 2009). Notably, the Chinese study used median splits to determine high and low positive affect,
suggesting that the relationship between positive affect and diurnal cortisol slope may not be linear across
all levels of positive affect. That is, associations with the cortisol slope within the high positive affect group
may be stronger than in those in the low positive affect group. Moreover, positive affect comprises
dimensions of both emotional valence and degree of arousal. Calm and excitement, for example, are both
positive emotions, but the latter is associated with higher levels of arousal. Along these lines, Hoyt, Craske,
Mineka, and Adam (2015) found that high but not low arousal positive affect was associated with a steeper
cortisol slope (and lower bedtime cortisol levels) among adolescents. The steeper slope seems to have been
in part a function of lower levels of bedtime cortisol in those with the highest levels of high arousal positive
affect (Hoyt et al., 2015). These results suggest a multi-dimensional representation of positive affect, which
captures both valance and arousal, may be critical for a precise account of the relationship between positive
affect and cortisol, and possibly help to explain prior mixed results.
There are more consistent findings for dispositional optimism. For example, among 543 healthy
adults aged 53-76 years from the Whitehall II cohort study, a more robust CAR – a larger increase in
cortisol from waking to 30 minutes later – was associated with lower optimism, but not the diurnal decline
(Endrighi, Hamer, & Steptoe, 2011). A similar pattern of associations between optimism and the CAR was
reported in Chinese adults. However, this relationship may be sex- and/or ethnicity-specific, as some
associations were found only among men in the Chinese sample (Lai et al., 2005).
Smyth and colleagues (2017) assessed the relationship between global life satisfaction, measured
by a single item, momentary affect (from ecological momentary assessment), stress, and diurnal cortisol
slopes among 115 working aged adults (aged 19-63). Multi-level models revealed a trend (p<.10) towards
greater global life satisfaction and steeper slopes, indicating a stronger diurnal rhythm, on each of the 3
sampling days. Interestingly, after averaging the slopes across the days, life satisfaction was actually
associated with flatter cortisol slopes (Smyth, Zawadzki, Juth, & Sciamanna, 2017). The authors note that
the initial measurements of cortisol did not begin until a few hours after waking, and likely missed
important information from the early hours of the day needed to adequately assess the daily slope.
However, Ryff and associates (2006) also reported an association between flatter cortisol slope and higher
scores on the eudaimonic well-being domains of personal growth and purpose in life in 52 women aged 75
and older. These authors note that upon further examination, those with higher personal growth and
purpose in life started the day with lower levels of salivary cortisol and stayed lower across the day,
compared to those with lower scores on these domains (Ryff et al., 2006). These observations underscore
the importance of considering absolute levels of cortisol and diurnal slope in tandem; flat slopes may result
in different absolute levels of cortisol exposure depending on waking levels. Thus, one should also consider
interactions between components in associations with well-being.
Well-being has also been studied as a buffer against the impact of stress on HPA responses. For
example, in 135 community-dwelling adults aged 61 or older, Jobin and colleagues (2014) assessed stress
perceptions and four indicators of diurnal cortisol (AUC, awakening, afternoon/evening, and CAR levels)
on 12 different days over six years. When considering absolute levels of stress across participants,
optimism was associated with a reduced CAR among those experiencing high stress levels. Compared to
pessimists, optimists were protected against elevations in cortisol AUC, awakening levels, and
afternoon/evening levels on days they perceived higher-than-average stress levels (Jobin, Wrosch, &
Scheier, 2014). Conversely, in a double-blind, randomized study, Koelsch et al. (2016) exposed 143
participants to a CO2 stress test (inhalation of 35% CO2) and measured the impact of positive moodinducing
music on cortisol recovery. They found that compared to a neutral music control group the music
intervention was associated with more positive mood and stronger cortisol responses to the acute stressor.
The authors suggest that the lower cortisol among those with more negative mood is associated with a
suboptimal (i.e. less robust) stress response, similar to HPA hypoactivity observed in patients with
depression (Koelsch et al., 2016). The differences in the results of these two studies also illustrate the
nuances associated with different types of analyses. In the context of acute stressors, a robust response is
often linked to favorable outcomes, whereas in the context of daily function higher levels of cortisol
typically indicate greater ongoing stress and poorer outcomes.
Overall, cortisol is a sensitive biomarker of psychological experience. Although a relatively recent
line of work, research on positive psychological functioning and cortisol suggests that cortisol regulation
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may be one biological pathway by which well-being has its beneficial effects on health. This effect is seen
in direct links between markers of positive psychological functioning (e.g. positive affect; optimism) and
daily cortisol regulation. Well-being also buffers the impact of adverse experiences.
Dehydroepiandrosterone (DHEA). The steroid hormone DHEA (and its longer lived sulfated
form, DHEA-S) is one of the most abundant circulating steroids. Like cortisol, the majority of DHEA is
produced and secreted by the adrenal cortex under the control of adrenocorticotropic hormone (ACTH). In
addition to functioning as a metabolic intermediate in the synthesis of sex steroids and as an androgen in its
own right, DHEA binds to and activates receptors of neurotrophins like nerve growth factor (NGF) and
brain-derived neurotrophic factor (BDNF) with high affinity, and is thus capable of signaling neurons to
survive, differentiate and grow (Lazaridis et al., 2011; Prough, Clark, & Klinge, 2016). DHEA levels begin
to decline in the early thirties at a rate of about 5% per year – DHEA is sometimes referred to as the “antiaging”
hormone – although the decline is highly variable and is driven by unknown factors. The various
negative effects of this age-related decline are particularly robust in women, since DHEA is their only
source of sex steroids after menopause. Such a decrease in DHEA-derived sex steroid availability could be
partially responsible for numerous symptoms of hormone deficiency observed after menopause, including
vaginal atrophy, bone loss, fat accumulation, type 2 diabetes, skin atrophy, cognition problems, memory
loss, and possibly Alzheimer’s disease (Labrie, 2007, 2010).
Observational studies associating DHEA(S) levels with various measures of well-being have been
conducted primarily among older adults (Berr, Lafont, Debuire, Dartigues, & Baulieu, 1996; Lebrun et al.,
2006; Petros, Opacka-Juffry, & Huber, 2013). Along with other physiological outcomes, Berr and
colleagues (1996) found that among 622 community-dwelling adults aged over 65 years, DHEA levels were
significantly lower in females with depressive symptoms, poor subjective health, and poor life satisfaction.
A later study involving 402 post-menopausal women aged 56-73 years found that none of the hormonal
parameters measured, including DHEA and DHEA-S, were related to quality of life (Lebrun et al., 2006).
In an opportunistic sample of 32 individuals (63% women; mean age 29), Petros and associates (2013)
found that salivary DHEA-S and resilience were positively associated after adjustment for age and sex.
However, well-being was not significantly correlated with DHEA-S, cortisol, or the DHEA-S/cortisol ratio
(Petros et al., 2013). These studies suggest that lower levels of DHEA(S) may be indicative of lower levels
of well-being, although the results to this point are limited and mixed.
The potential importance of DHEA to health in older age has led to a number of studies aimed at
boosting DHEA levels by supplementation. These studies provide the opportunity to examine the
consequences of the manipulation of DHEA for well-being. The duration of administration in most
placebo-controlled supplementation studies range from 7 days to 4 months. A 3-month randomized, doubleblind
placebo cross-over DHEA replacement trial among 30 men and women (aged 40-70 years) resulted
in restoration of DHEA levels to those of young adults, a 2-fold increase in androgens in women and a
small rise in androstenedione for men. These were accompanied by increased perceptions of physical and
psychological well-being in men (67%) and women (84%) after 12 weeks, including improved sleep
quality, feeling more relaxed, and having increased energy to better handle stress, as reported in openended
questions (Morales, Haubrich, Hwang, Asakura, & Yen, 1998). Another randomized double-blind
cross-over trial in men aged 62-76 found no significant differences in well-being between treatment and
control groups in a 13-week DHEA supplementation trial. However, correlation analyses showed that
higher morning DHEA levels were associated with lower confusion, while higher evening levels were
associated with lower anxiety and lower current negative mood in the morning (van Niekerk, Huppert, &
Herbert, 2001). These are relatively short administration periods, and studies assessing the impact of
DHEA supplementation across longer periods of time are rare. As part of a 1-year DHEA supplementation
trial in 225 men and women aged 55-85, cognitive functioning, life satisfaction, and quality of life were
measured at 3, 6, and 12 months. This study found increases in cognitive function in the treatment group
compared to the placebo control. Depression scores also decreased in both men and women. Women
additionally showed increases in life satisfaction (Kritz-Silverstein, von Muhlen, Laughlin, & Bettencourt,
2008).
DHEA supplementation also has effects on brain regions relevant for well-being. A study involving
24 healthy young men (aged between 18 and 40 years), examined the impact of 7 days of DHEA
supplementation on episodic memory and assessed potential neural correlates for its effects, specifically
event-related potentials (ERPs). DHEA administration led to reduced evening cortisol and improved mood
and memory. The authors linked these results to neuronal recruitment in the steroid-sensitive anterior
cingulate cortex (ACC) that may be involved in pre-hippocampal memory processing (Alhaj, Massey, &
McAllister-Williams, 2006). This neuronal recruitment by DHEA may be of particular importance to the
issue of well-being, as the ACC as well as the prefrontal cortex and insula have been implicated in the
regulation of happiness and well-being (Berridge & Kringelbach, 2011; Lewis, Kanai, Rees, & Bates,
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2014; Suardi, Sotgiu, Costa, Cauda, & Rusconi, 2016).
In addition to the direct effects of DHEA supplementation on well-being, researchers have also
examined the role of DHEA supplementation as a buffer against the adverse effects of stress exposure. For
example, in a study by Kudielka et al. (1998), 75 healthy older males and postmenopausal women
participated in a 2-week double-blind, placebo-controlled study of DHEA supplementation. Afterwards,
they underwent an acute psychosocial stressor, the Trier Social Stress Test (TSST). Women treated with
DHEA showed similar ACTH stress responses to men, but they were significantly enhanced compared to
women on the placebo. As noted above, robust responses to acute stressors are considered markers of
health.
There may also be a 3-way association among stress, well-being, and DHEA-S. A recent study
focusing on caregivers of individuals with dementia and use of adult daycare services examined salivary
levels of DHEA-S and their relationships to positive mood and depressive symptoms in the caregivers.
This study found that DHEA-S levels in caregivers were significantly higher on the days after the
individuals for whom they were caring used daycare services. These results suggest potential restorative
effects of a brief respite from providing care and thereby protection against the physiological effects
associated with caregiving stress. Furthermore, DHEA-S levels co-varied with daily positive mood, but not
with depressive symptoms (Zarit et al., 2014).
Overall, observational studies suggest that DHEA links specifically to well-being are more readily
discernible among older adults than their younger counterparts. Randomized control trials involving DHEA
supplementation generally suggest a positive impact of DHEA supplementation on well-being, although
null findings have also been reported. One difficulty in comparing study results is variability in the
experimental protocols used: DHEA dosage protocols and well-being measures assessed vary from study to
study. Studies with comparable dosages of DHEA covering longer supplementation durations and wider
age ranges may provide further information about age- and sex- and dose-specific associations. Likewise, a
common set of well-being measures to compare across studies would be informative. Evidence also points
to DHEA(S) acting as a buffer against acute stress or as a restorative agent during recovery from chronic
stress, although the range of well-being measures assessed in these studies has been limited.
Catecholamines. Norepinephrine and epinephrine are the two main chemical messengers released
from the adrenal medulla via sympathetic nervous system activation, and they are responsible for the socalled
‘fight-or-flight’ response to threatening environmental stimuli. [Note: While the adrenal medulla is
the sole source of epinephrine in the periphery, norepinephrine is released in multiple other parts of the
body from sympathetic neurons]. Generally their release initiates a cascade of physiological changes and
mobilization of resources needed to respond to a stressor, including elevations in heart rate, cardiac output,
blood pressure and blood glucose levels. Not surprisingly, given this role in the stress response, studies of
links between well-being and catecholamines tend to focus on well-being as a modifier of hormonal
reactivity and recovery following stressors.
A range of measures has been used to assess well-being in the context of autonomic function, the
latter usually in response to an experimental stressor. For example, in participants of the Family Heart
Study mentioned above, Brummett et al. (2009) found that during a sadness and anger recall protocol,
positive affect was inversely related to the mean level of norepinephrine. However, positive affect was
unrelated to reactivity or recovery after. The study of 90 newlywed couples focused on behaviors during a
real-time marital conflict as predictors of epinephrine and norepinephrine responses, measured as the
composite of hourly blood samples across the day. The tendency of husbands to withdraw from the conflict
(‘negative-withdrawal’ pattern) was associated with higher norepinephrine levels in the wives, whereas
more positive behaviors (‘validation-facilitation’ pattern) were associated with lower epinephrine levels
(Kiecolt-Glaser et al., 1996). In the study by Koelsch and colleagues (2016), norepinephrine exhibited the
fastest and strongest response to the CO2 stress test. However, norepinephrine was not significantly
different in the positive mood-inducing music stimulus group compared to the neutral control group.
Further analyses, comparing those who increased and decreased mood in response to the stress, showed that
positive mood did not affect norepinephrine response to or recovery from the CO2 stress.
Cancer tumors are able to synthesize and release hormones, and one interesting area of study is the
impact of the host environment on tumor hormone processes. In a clinical sample of 353 adult ovarian
cancer patients, Davis et al. (2015) used latent factors to represent eudaimonic well-being (personal growth,
purpose in life and self-acceptance), positive affect, and psychological distress, and assessed their
relationship with norepinephrine levels in tumor samples. Increased eudaimonic well-being was related to
reduced tumor norepinephrine levels (Davis et al., 2015).
Taken together, the studies associating epinephrine and norepinephrine with measures of well-
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being are mixed, although there have been few such studies, and larger epidemiological studies that could
provide information about broad, population-level patterns of association between circulating or
experimentally-induced levels of catecholamines and diverse measures of well-being are lacking.
Sex Hormones
Steroidal sex hormones, also called gonadal hormones, are produced in the gonads, i.e. the testes
and ovaries of males and females, respectively. Their synthesis is under the control of the hypothalamicpituitary-gonadal
(HPG) axis, and is crucial for the proper development and function of the body.
Testosterone and estrogens, present at higher levels in males and females, respectively, control the
expression and maintenance of secondary sex-specific characteristics, and regulate sexual differentiation
and sexual behavior patterns.
Some studies have measured the psychological impact of testosterone replacement (usually to
restore sexual function) in males with abnormally low levels of testosterone, for reasons of hypogonadism
or marked declines with age (e.g. adrenopause). Such studies have documented increases in anger, hostility,
and aggressive behavior, with variable effects (Bassil, Alkaade, & Morley, 2009). Among those with
normal functioning (eugonadal) additional testosterone administration may have a minor impact on mood
(O'Connor, Archer, & Wu, 2004). In females, the rise and fall of levels of estrogen with the menstrual cycle
have been suggested to play a major role in the fluctuation of mood and emotions. Over the life cycle, the
decline in estrogen levels among women (e.g. perimenopause and menopause) has been suspected to
modulate the increased rate of depression and mood disorders, compared to men. While the underlying
mechanisms are not known, evidence points to the neurological effects of estrogen, which are directly
relevant to mood symptomotology (Wharton, Gleason, Olson, Carlsson, & Asthana, 2012). Varying levels
of testosterone and estrogen are often examined in conjunction with sexually dimorphic phenomena.
However, few studies have directly investigated their relationship with well-being. The following section
discusses findings relevant to the correspondence of levels of these hormones and various measures of
well-being.
Testosterone. Studies relating testosterone to well-being have focused on older adults, in part
because there is a gradual, age-related decline of serum levels after age 30 (Bassil et al., 2009), and
generally these studies have not found links between testosterone and well-being. Castanho et al. (2014),
studying 120 Portuguese community-dwelling adults aged 51-87 years, identified four participant clusters
based on performance in cognitive functioning (executive functioning, memory), depressive mood and
well-being. These clusters were compared for their serum concentrations of various hormones, including
testosterone. In males, higher testosterone was generally associated with lower odds of membership in the
poorest performance cluster, characterized by poor cognitive functioning, low well-being, and high
depression, although testosterone was not significantly associated with the well-being or quality of life
measures for either sex (Castanho et al., 2014). An earlier study by Lebrun and associates (2006) among
402 post-menopausal women aged 56-73 years did not find an association between testosterone levels and
health-related or general life satisfaction. Similarly, in 466 men aged 64-97 years from the Lieto Study,
Eskelinen and associates (2007) found that total testosterone and free testosterone levels were associated
with higher self-rated health after adjustment for age; however, these associations were no longer
significant after further adjustment for body mass index (Eskelinen, Vahlberg, Isoaho, Kivela, et al., 2007).
In general, given the above studies, the evidence that testosterone is related to well-being among
older adults is weak. Importantly though, there are relatively few studies of testosterone that have assessed
well-being. There are also few studies involving younger samples (e.g. around the time when testosterone
levels first begin their decline). Well-being might, for example, affect trajectories of changes in
testosterone over time. In addition, other measures of well-being, such as eudaimonic well-being, positive
affect, and optimism, have not been investigated thoroughly.
Estrogen. Changes in estrogen levels occur naturally throughout the life course, and fluctuations,
sudden withdrawal, or sustained deficits in estrogen have been linked with significant mood disturbance.
Studies specifically examining the link between estrogen and well-being are inconsistent and appear to
implicate lower estrogen levels in the progression of negative mental health instead of improvements
associated with higher levels.
In their study of Portuguese community-dwelling adults, Castanho and colleagues (2014) found
that in males lower levels of estradiol (a major form of estrogen) predicted significantly higher odds of
membership in the poorest performance cluster, characterized by poor cognitive functioning, low wellbeing,
and high depression. In the individual linear regression analysis, estrogen was not significantly
associated with the well-being or quality of life measures (Castanho et al., 2014). Lebrun and associates
(2006) failed to find an association between estrogen and health-related or general life satisfaction in postmenopausal
women. However, there was a negative relationship between estrogen and health, seen only in
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the highest quintile of estrogen. This association was no longer significant after adjustment for fat mass
(Lebrun et al., 2006).
Estrogen appears, at least in older adults, not to be directly related to well-being. There may a sexdependent
association, whereby males generally perform worse than females with lower levels of estradiol.
However, this association does not appear to be specific to well-being, but more likely reflects an overall
reduction in mental functioning. There have been few observational studies of estrogens that include
measures of eudaimonic well-being, optimism, or positive affect; such efforts would complement existing
findings and allow for meaningful comparisons across studies.
Metabolic Hormones
Metabolism refers to a complex network of continuous biochemical processes that allow for the
efficient breakdown of food into energy for carrying out activities of daily life (catabolism) or for
conversion into usable components for building and repairing the body (anabolism). In addition to age, sex,
body composition, diet, and physical activity, metabolism is greatly influenced by hormone function.
Metabolic hormones, such as growth hormone, insulin, insulin-like growth factor, and thyroid hormones,
provide signals that regulate catabolic and anabolic processes within the body. The structure provided by
anabolic processes supports the proper functioning of the body. Consequently, dysregulation of metabolism
can be associated with a wide range of diseases and disorders. For example, abnormal cellular structure and
function of neuronal circuits in the brain has been implicated in the development and progression of
neuropsychiatric disorders, including neurodegenerative diseases like Alzheimer’s. Importantly, these
disorders frequently co-occur with metabolic disturbances, such as insulin resistance, diabetes, and obesity
(McIntyre, Mancini, & Basile, 2001). Individuals with major mental illnesses, such as schizophrenia and
bipolar disorder, also have an increased prevalence of metabolic syndrome (Newcomer, 2007). Although,
associations among these populations may be due to non-disease-related factors such socioeconomic status
or adverse metabolic side effects from medications. In non-clinical populations, these metabolic hormones
are likewise suggested to have an impact on cognitive functioning and mood. These observations highlight
the potential role of metabolism in general well-being.
Insulin-like growth factor 1 (IGF-I). Insulin-like growth factor is a hormone whose production is
regulated by growth hormone, nutrition, and insulin. These insulin-like peptides are involved in a variety of
biological activities, including neuronal survival, neurogenesis, angiogenesis, excitatory and inhibitory
neurotransmission, regulation of food intake, and cognition (Werner & LeRoith, 2014). Across the life
course, IGF-I follows an age-dependent pattern with serum levels peaking around puberty and declining
thereafter with increasing age. Most IGF-I in the blood is produced by the liver (Roelfsema & Clark, 2001).
The majority of studies involving IGF-I and well-being are among individuals with growth hormone
deficiency undergoing growth hormone replacement therapy. The few studies in non-deficient populations
suggest an association between IGF-I (and its binding proteins) and well-being.
In a study of individuals aged 20-74, Unden and associates (2002) measured several domains of
well-being (social well-being, mental well-being, self-esteem, social support, and self-rated health) and
found that they were positively correlated to IGF-I in those aged 20-44 years. Overall, age was found to
account for 40% of the variation in IGF-I levels. In multivariate analyses controlling for this decline with
age, social well-being was important in predicting IGF-I concentrations in the younger age group. In the
older two age groups (i.e., 45-59 years and 60-74 years), associations were limited to physical factors, such
as sex hormone binding globulin, low density lipoprotein, and lipoprotein(a), as well as education and
physical health (Unden, Elofsson, Knox, Lewitt, & Brismar, 2002). These results suggest that in older
adults age-related changes in health and physical function may dominate and diminish the potential links
between psychosocial factors and IGF-I. Of note, these analyses were completed using stepwise selection
of independent variables for the linear regression model. This variable selection method has since been
found to have inherent reliability issues (Whittingham, Stephens, Bradbury, & Freckleton, 2006). However,
this null association was also observed in the above study by Lebrun and colleagues (2006) that found no
consistent associations of well-being with IGF-I, nor with two major binding proteins, among the postmenopausal
women. More recently, Emeny et al. (2014) found that among 985 Cooperative Health
Research in the Region Augsburg (KORA) study participants aged 64-93 years, IGF-I was inversely
associated with well-being and directly linked to depressive symptoms in women. On the other hand, the
binding protein IGFBP-3 was positively associated with well-being in women. IGFBP-3 serves to shuttle
IGF-I around the body, but its affinity for the IGF receptor means that it may also act as an antagonist,
preventing IGF from binding and causing changes within the cell (hence the opposing effects of IGF-I and
IGFBP-3 in this study). There were similar trends in men, but not statistically significant (Emeny et al.,
2014). This study suggests that the previous studies may have failed to observe an association in older
adults because it may be sex-specific. Further studies using the quality of life instruments utilized in these
earlier studies with stratification by sex would be needed to confirm this possibility.
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Overall, these findings show that in older adults, IGF-I may be inversely associated with wellbeing,
while levels of its binding protein (IGFBP-3) were directly related to well-being. Importantly, these
associations may be limited to older females. The menopausal status of these women may also be an
important discriminating factor for these associations.
Insulin. Insulin is a peptide hormone produced by beta (β) cells of the pancreatic islets. Insulin
helps to regulate the metabolism of carbohydrates, fats, and protein by promoting the absorption of glucose
from the blood into fat, liver, and skeletal muscle cells. Under normal physiological functioning, the release
of insulin into the circulation is closely linked to glucose concentrations in the blood. High glucose
concentrations stimulate β cells to secrete insulin. Conversely, low glucose levels inhibit the secretion of
insulin (Sonksen & Sonksen, 2000). Like steroid hormones, insulin can cross the blood-brain barrier where
it appears to play an important role in neuronal survival (Werner & LeRoith, 2014). Research linking
insulin levels and well-being has largely investigated the effect of insulin therapy either directly on mood
or as a buffer of stress. These studies have generally found that intranasal insulin improves mood and
attenuates HPA reactivity to social stress (Lee, Zabolotny, Huang, Lee, & Kim, 2016).
Observational studies have generally reported inverse associations between insulin levels and wellbeing.
Oreskovic and Goodman (2013) investigated the relationship between dispositional optimism and
insulin levels measured 6-7 years later among adolescents aged 12-19 years. In bivariate analyses, insulin
was negatively correlated to scores on optimism and positively correlated with scores on pessimism. In
analyses adjusted for a range of potential confounders, an inverse association was found among nonHispanic
black, but not white adolescents, whereby a one unit increase in unidimensional optimism
corresponded to 2.2% lower insulin levels (Oreskovic & Goodman, 2013). A study of 402 post-menopausal
women found that insulin was not related to health-related life satisfaction. There were negative
associations between insulin and life satisfaction which were present only in the highest quintile of insulin,
but these were attenuated by adjustment for fat mass (Lebrun et al., 2006).
Lee et al. (2016) recently summarized the results of numerous experimental studies involving
insulin administration to human and animal subjects. A set of four studies specifically examined the impact
of intranasal insulin on well-being and psychological responses to stressors, including social evaluative
stress. The studies have generally found that intranasal insulin improved mood and attenuated HPA
reactivity to social stress (Lee et al., 2016).
Thyroid hormones (TSH/T4/T3). Thyroid stimulating hormone (TSH) is an integral part of the
hypothalamic-pituitary-thyroid axis. Specifically, the hypothalamus releases thyrotropin-releasing hormone
(TRH) to stimulate the anterior pituitary to produce TSH. TSH then stimulates the thyroid gland to produce
thyroxine (T4), which is in turn converted to active triiodothyronine (T 3). T3 affects almost every
physiological process in the body, including growth and development, metabolism, body temperature and
heart rate. T3 and T4 levels provide negative feedback to the hypothalamus and pituitary gland to regulate
the release of TRH and TSH, respectively.
Alterations in the levels of thyroid metabolites occur normally with age and are also present in
conditions that often result in lower levels of thyroid hormones (hypothyroidism), such as Hashimoto’s
Thyroiditis, thyroidectomy, or other thyroid deficiency. In non-patient populations, subclinical
hyperthyroidism is characterized by lower-than-normal TSH in the presence of normal levels of free
thyroxine (fT4). Subclinical hypothyroidism is characterized by elevated TSH in the presence of normal
fT4. Subclinical hypothyroidism is often accompanied by increased levels of thyroid autoantibodies
(thyroid peroxidase; anti-TPO).
Thyroid hormone status has predominantly been studied in relation to depression. Whereas most of
the patients with primary depression have normal thyroid function, some patients with hypothyroidism or
hyperthyroidism manifest features of depression, the latter presenting with a wider spectrum of
neuropsychiatric symptoms (Hage & Azar, 2012). However, some studies have investigated the
relationship of thyroid hormones with health-related quality of life (HR-QOL) and well-being, though not
all studies are in agreement. Comparing 93 Hashimoto’s Thyroiditis patients with 31 euthyroid (normally
functioning thyroid) controls, Yalcin et al. (2017) found that depression and anxiety scores were higher and
scores on subscales of the SF-36 (physical functioning, general health, and mental health) were lower in the
patients. Larger studies outside of clinical populations tend not to find any associations of TSH and T4
levels with life satisfaction, self-rated health, and quality of life in healthy control populations, nor any
differences in those with hypothyroidism undergoing thyroxine replacement therapy (Eskelinen, Vahlberg,
Isoaho, Lopponen, et al., 2007; Kelderman-Bolk, Visser, Tijssen, & Berghout, 2015). In a large study of
9,491 individuals of the LifeLines Cohort Study aged 18-90 years old, Klaver et al. (2013) compared to
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euthyroid individuals, there was no difference between those with elevated or suppressed TSH or fT4 levels
in HR-QOL. There was a sex-specific effect whereby women with suppressed TSH scored significantly
lower on domains of ‘physical functioning’ and ‘general health’ compared to euthyroid women (Klaver et
al., 2013). Similarly, a later study among 8,214 Danish General Suburban Population Study participants
aged 20 or older (55 years on average) found no difference in well-being between subclinical
hypothyroidism and euthyroid individuals with or without high levels of anti-TPO. One exception is that
euthyroid women with high anti-TPO had better well-being than euthyroid women with anti-TPO in the
reference range; although this association may have arisen by chance (Fjaellegaard, Kvetny, Allerup, Bech,
& Ellervik, 2015).
The literature on links between thyroid hormones and well-being generally show associations in the
expected directions, but as with catecholamines, more large-scale studies are needed to document
population-level associations.
Other Hormones
The hormones discussed below include posterior pituitary hormones, oxytocin and vasopressin,
and prolactin. These hormones are important messengers that potently influence inter-personal interactions,
including in-group affiliation and out-group discrimination, mating preferences and pair-bonding, parental
behavior, and pro-social behavior (Olff et al., 2013; Shamay-Tsoory & Abu-Akel, 2016; Sobrinho, 1991;
Walum et al., 2008), and as such may have considerable bearing on social well-being. These hormones also
coordinate a number of other processes important for physiological and mental health, such as pain
perception, wound healing, and reward circuits in the brain. Thus, these hormones may work across
multiple levels to impact the subjective experiences of the individual.
Oxytocin. Oxytocin is a neuropeptide produced by the hypothalamus and stored in the posterior
pituitary where it is released into the circulation. It can also be released from specific neural projections to
other structures in the brain where it modulates the activity of other neurochemical systems. In addition to
its physiological role during pregnancy – increasing uterine tone, promoting uterine contractions, and
inducing labor – oxytocin is also involved in maternal bonding, sexual behavior, and affiliation (Ishak,
Kahloon, & Fakhry, 2011). Recently, oxytocin administration has gained increased attention for its ability
to promote positive social behavior and stress regulation, and for its potential as a therapeutic intervention
for alleviating symptoms of various psychiatric disorders. However, the observed effects are not uniformly
beneficial. Accumulating evidence suggests that contextual and inter-individual factors, such as presence
of a stranger versus a friend, sex, attachment style, or the presence of psychiatric symptoms, moderate the
effects of oxytocin, as well as absolute levels in the periphery (Olff et al., 2013). Specifically, these factors
are thought to interact with oxytocin to influence the salience of social and environmental cues. Depending
on the context, oxytocin can induce pro-social, anti-social or even aggressive behavior (De Dreu, 2012; De
Dreu, Greer, Van Kleef, Shalvi, & Handgraaf, 2011; Shamay-Tsoory & Abu-Akel, 2016). Thus, oxytocin
effects are not uniformly pro-social, as has been thought (it has been popularly referred to as the “cuddle”
hormone), but rather is highly sensitive to social context.
Studies specifically relating oxytocin to well-being are rare. Those that have been done have tended
to focus on the potential beneficial effects of intranasal administration. There is also interest in the oxytocin
receptor, which has a number of polymorphisms that may be linked to well-being to different degrees.
Barraza et al. (2013) studied the impact of 10 daily doses of intranasal oxytocin on mood among 41
residentially housed older adults (mean age of 80) in a randomized, double-blind, placebo-controlled study.
No changes in mood were observed across the 10-day period. However, dispositional gratitude improved in
the treatment group compared to controls. Saphire-Bernstein and colleagues (2011) investigated the link
between the oxytocin receptor genotypes (with or without the A allele) and psychosocial resources
(optimism, mastery, self-esteem) among 344 university students and employees aged 18-36 years. This
study found that carriers of the A allele had lower levels of these resources, compared to G/G
homozygotes. These resources were also found to mediate the relationship between oxytocin receptor type
and depression (Saphire-Bernstein, Way, Kim, Sherman, & Taylor, 2011). These findings are in line with
an earlier study by Lucht et al. (2009) among 285 adults that found individuals with the oxytocin receptor
A/A genotype had lower scores for positive affect. However, this effect was only observed in males (Lucht
et al., 2009).
Oxytocin has also been suggested to predict positive affective responses to acute socio-evaluative
stress. Using the TSST among 172 participants aged 18-35 years, Moons, Way, and Taylor (2014) found
that post-stress oxytocin levels interacted with oxytocin receptor polymorphisms to predict positive
affective responses to the stressor. This effect was sex-specific whereby higher levels of oxytocin in
females with the G/G genotype had more positive affect compared to the carriers of the A allele (Moons et
al., 2014).
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Anti-diuretic hormone/arginine vasopressin (ADH/AVP). Vasopressin is a hormone released
from the posterior pituitary gland. Release of vasopressin in the blood increases water retention in the body,
and in higher concentrations, produces vasoconstriction. Vasopressin also acts on reward circuits in the
brain to promote pair-bonding behavior during partner preference formation in prairie voles. Similar effects
of vasopressin receptor activation have been found in studies of marital discord in men (Walum et al.,
2008). Studying the impact of intranasal vasopressin administration on musical working memory, Granot
and associates (2013) found that compared to those in the placebo group, those receiving vasopressin had
higher scores on happiness (Granot, Uzefovsky, Bogopolsky, & Ebstein, 2013). Moons et al. (2014) found
an interaction between vasopressin and its receptor in predicting anger responses to the TSST. This effect
was gender-specific whereby men, but not women, with high post-stressor vasopressin levels who were
also carriers of a particular vasopressin receptor polymorphism had more post-stressor anger compared to
non-carriers (Moons et al., 2014).
Prolactin. Prolactin is a potent hormone secreted mainly from the anterior pituitary gland with a
broad range of biological effects, including water and salt balance, breast milk production, cell
proliferation and differentiation, T-cell immunity, pancreatic β cell function, hematopoiesis, and
adipogenesis. It acts via binding to prolactin receptors and cytokine-like receptors located in many tissues
throughout the body (Bole-Feysot, Goffin, Edery, Binart, & Kelly, 1998). Creative approaches have been
used in the study of prolactin responses to stressors. In one study, for example, women with anger
responses to hypnosis-evoked experiences of humiliation showed elevated prolactin (Sobrinho, 2003).
Additionally, more passive coping mechanisms in real-life situations have been associated with chronic
elevations in prolactin (Sobrinho, 1991, 2003).
Studies assessing levels of prolactin and measures of well-being are limited. Castanho et al. (2014)
found sex-specific associations among 120 Portuguese participants aged 51-87 years. In males, higher
prolactin was associated with higher odds of membership in the poorest performance cluster, characterized
by poor cognitive function, higher depression and lower well-being, compared to the best performance
cluster. Similarly, in males only, linear regression analyses showed that higher prolactin predicted less
depressive mood and greater well-being (Castanho et al., 2014). Kiecolt-Glaser et al. (1996) also measured
prolactin among 90 newlywed couples during marital conflict and found that the more positive ‘validationfacilitation’
behavior pattern, but not the ‘negative-withdrawal’ pattern, was associated with higher
prolactin levels, in women only. No such associations between the behavior patterns and endocrine
responses during marital conflict were observed in the men.
Conclusion
The existing literature points to associations of some, but not all, hormones with well-being that are
not merely the mirror image to those of ill-being. There are some features of the current literature that limit
the conclusions we can draw about the relationship between hormones and well-being. First, the measures
of well-being used across the above studies are diverse – some focused on emotions, others on meaningful
engagement with life pursuits, others on optimism – and not all are used in any single study. Null findings
in particular are thus difficult to interpret: is there no association with well-being, or with the specific
measure of well-being used in a specific study? Second, the impact of basic but influential characteristics,
such as age and sex, has not been considered explicitly in most studies and may have marked consequences
for the outcomes studied. Even if there is a robust association between a particular hormone and wellbeing,
it may change with age, for example, along with normative changes in biological functioning.
Moreover, for many of the hormones considered here there has been evidence of sex-specific associations
that should be clarified and replicated in future studies. Third, there are still open questions regarding the
nature of the hormones themselves. In particular, the complexity of diverse cortisol assessments (c.f. Clow,
Hucklebridge, Stalder, Evans, & Thorn, 2010) necessitates the systematic testing of the links between
positive functioning and these measures. It may not be reasonable to expect that all of these different
measures of cortisol will be linked to the same aspects of well-being to the same degree. Lastly, this chapter
has considered studies looking specifically at the association of single isolated hormones with well-being. It
is well-known that these hormones all have some degree of stimulatory or inhibitory function in relation to
other hormones. For example, testosterone has been found to enhance the effects of growth hormone
(Meinhardt & Ho, 2006) and norepinephrine to strongly inhibit insulin release (Nakaki, Nakadate, & Kato,
1980). There are practical reasons that no studies have included measures of all these various hormones
and investigated their interactive associations with well-being, but the existence of such complexity must
be acknowledged and assessed wherever possible. The few studies that did assess multiple hormones in a
single sample did not specifically investigate their interactions in predicting well-being, but the results
nonetheless suggest that complex interactions may exist with sex-specific effects (Castanho et al., 2014;
Kiecolt-Glaser et al., 1996; Lebrun et al., 2006).
In sum, research on the associations between hormones and well-being appears to be in its infancy
361
compared to the vast body of work characterizing hormone associations with ill-being (e.g., depression,
stress). Thus, this represents a fertile area of research with great promise to illuminate the physiological
pathways by which well-being affects physical and mental health.
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DEMOGRAPHICS
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A Lifespan Perspective on Subjective Well-Being
By Jennifer E. Lansford, Duke University
Citation
Lansford, J. E. (2018). A lifespan perspective on subjective well-being. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
This chapter provides a lifespan perspective on subjective well-being. First, evidence for stability and
change in subjective well-being across the lifespan is considered with attention to both set-point theory and
evidence regarding whether life events and choices can alter individuals’ well-being in the long-term. Next,
the chapter describes mean levels of cognitive and affective components of well-being and considers
predictors and consequences of well-being at different points in the lifespan, including gender, culture and
country, and socioeconomic factors that are important for the understanding of well-being. The chapter
then summarizes aspects of cognitive and social development that affect subjective well-being from infancy
to childhood, adolescence, early adulthood, middle adulthood, and late adulthood. Finally, the chapter
suggests directions for future research.
Keywords: Infancy, Childhood, Adolescence, Adulthood, Lifespan, Subjective Well-Being
Subjective well-being is often conceptualized as encompassing meaning and purpose in life; life
satisfaction; and feelings of happiness, sadness, and other positive and negative emotions (Kahneman,
Diener, & Schwarz, 1999). Together, these components capture both cognitive and affective aspects of
well-being (Diener, Lucas, & Scollon, 2006). This chapter begins with an overview of evidence for stability
and change in subjective well-being across the lifespan and then describes mean levels of different aspects
of well-being during specific life stages. The chapter then summarizes predictors and consequences of wellbeing
that are applicable across the lifespan as well as specific to particular developmental stages and
attends to gender, country or culture, and socioeconomic status, which are important considerations in the
study of well-being. Next, the chapter traces the development of well-being from infancy through early
childhood, middle childhood, adolescence, early adulthood, and middle adulthood to late adulthood, with a
particular focus on factors related to cognitive and social development in each life stage that have
implications for subjective well-being. The chapter concludes by suggesting directions for future research.
Stability and Change in Subjective Well-Being
across the Lifespan
Theory and empirical research suggest evidence for both stability and change in subjective wellbeing
across the lifespan (Sheldon & Lucas, 2014). Stability is promoted by heritability and personality
correlates such as neuroticism and extraversion, which have been found to be stable over long
developmental periods, especially after age 30 (McCrae & Costa, 1994, but see Roberts, Walton, &
Viechtbauer, 2006, for an alternative perspective). Furthermore, individuals’ environments are also largely
stable over time, promoting stability in well-being as well. Change can be brought about by environmental
stressors or welcome events (Clark, Diener, Georgellis, & Lucas, 2008) in addition to choices about one’s
life goals and priorities, time spent working and in leisure, healthy lifestyle, social participation, religion,
and intimate partners (Headey, Muffels, & Wagner, 2010).
On the one hand, set-point theories of well-being suggest that because of genetic (Lykken &
Tellegen, 1996) and personality predispositional (Headey & Wearing, 1992) factors, subjective well-being
is stable over the long term. There is some evidence for homeostatic adaptation, meaning that because of
genetically programmed dispositions for a set level of happiness, individuals tend to bounce back to this
preset level, even after major positive or negative life events (Cummins, 2010). Although transitory factors
as minor as the weather might influence individuals’ reports of subjective well-being (Schwarz & Strack,
1999, but see Lucas & Lawless, 2013, for evidence to the contrary with respect to reports of life
satisfaction), well-being is influenced by temperament and personality in addition to life circumstances. In
studies that have compared the stability of well-being in individuals going through major life changes such
as divorce or widowhood (e.g., Costa, McCrae, & Zonderman, 1987) or increases or decreases in income
(Diener, Sandvik, Seidlitz, & Diener, 1993), changes in well-being have been brought about temporarily by
major life events but then return to a baseline level after a brief adjustment period. Stability characterizes
reports of positive and negative affect in addition to life satisfaction and is found even when different
people report on a target individual’s affect at different time points (Costa & McCrae, 1988).
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On the other hand, subjective well-being is less stable than personality over time (Fujita & Diener,
2005). In a 17-year longitudinal study, 24% of respondents experienced a significant change in life
satisfaction from the first five years to the last five years of the study (Fujita & Diener, 2005). Even after
several years, individuals do not always bounce back following major life events such as widowhood
(Lucas, Clark, Georgellis, & Diener, 2003) and unemployment (Lucas, Clark, Georgellis, & Diener, 2004).
Individuals may also differ in the extent to which they return to set points of well-being after positive or
negative life events. For example, marriage increased the life satisfaction of a subgroup of individuals over
the long-term but decreased the life satisfaction of a different subgroup of individuals over the long-term;
attending just to population averages may falsely inflate the apparent stability of life satisfaction because
individual differences would be masked (Lucas et al., 2003). In a longitudinal study of a nationally
representative sample of German adults assessed annually from 1984 to 2008, personal and economic
choices were related to long-term changes in life satisfaction, contradicting set-point theory (Headey et al.,
2010).
Life satisfaction may be less stable than positive and negative affect over time to the extent that the
former relies on cognitive evaluations of one’s present circumstances, whereas affect may be more
strongly related to personality traits such as neuroticism and extraversion. Support for the differential
stability of these different aspects of well-being was found in a meta-analysis of longitudinal studies that
examined both cognitive and affective well-being in relation to eight family and work related life events
(marriage, divorce, bereavement, child birth, unemployment, reemployment, retirement, and
relocation/migration; Luhmann, Hofmann, Eid, & Lucas, 2012). Affective well-being generally returned
more quickly to baseline than did cognitive well-being, although the magnitude of the change and rate of
adaptation depended on the specific event. Furthermore, there was more variability in the effects of life
events on affective well-being than cognitive well-being (Luhmann et al., 2012), perhaps because affective
well-being is more strongly related to personality, social support, coping strategies, and emotional
regulation that may affect how individuals adapt to life events (Diener et al., 2006).
Mean Levels of Well-Being at Different Ages
In comparisons of well-being at different ages, a frequently described pattern is characterized by a
U-shaped curve in which well-being is higher earlier and later in the lifespan than during mid-life, a pattern
that holds for life satisfaction as well as positive emotions and lack of negative emotions (Stone, Schwartz,
Broderick, & Deaton, 2010). The Gallup World Poll conducted in over 160 countries, however, suggests
that this pattern is most common in high-income countries, with the nadir of well-being in the range of 45 to
54 years. By contrast, in sub-Saharan Africa, few mean differences in well-being are found at different
ages, and in Latin America and Eastern Europe, well-being decreases progressively with age (Steptoe,
Deaton, & Stone, 2015). Different components of well-being also show somewhat different patterns with
age. For example, anger and stress decrease after early adulthood, and worry decreases after middle
adulthood, so by later adulthood negative affect is low (Stone at al., 2010).
Mean level changes with age are not inconsistent with demonstrations of stability in well-being over
the lifespan. Stability and change can come in different forms. For example, rank-order consistency refers
to how individuals in a group compare to one another over time, whereas mean-level change refers to
whether individuals, on average, increase or decrease on a particular dimension over time (Roberts et al.,
2006). Thus, even if there are developmental patterns whereby adults during mid-life, on average, have
lower well-being than they do at earlier or later points in the lifespan, the happiest children may remain the
happiest teenagers and the happiest adults, reflecting rank-order consistency as well as normative
developmental change. Test-retest stabilities in global self-reported well-being are approximately r = .70,
.60, .50, and .35 over 1-, 2-, 5-, and 10-year intervals with a lower-bound of approximately .20 to .35 over
longer intervals (Anusic & Schimmack, 2016; Schimmack & Oishi, 2005). Average changes in mean levels
of well-being with age, of course, do not necessarily reflect the experience of everyone in the group. For
example, although negative affect decreased from adolescence to early adulthood for most individuals, a
subgroup increased in negative affect (Roberts, Caspi, & Moffitt, 2001).
Predictors of Well-Being
Many predictors of well-being are consistent across the lifespan. For example, material deprivation,
living in a dangerous neighborhood, and interpersonal violence are related to lower subjective well-being,
whereas supportive family relationships and friendships are related to better subjective well-being for
children and adults alike (e.g., Currie et al., 2012; Siedlecki, Salthouse, Oishi, & Jeswani, 2014). In
representative samples from 155 countries, having social relationships, having a sense of purpose, feeling
pride, and being treated with respect predict well-being consistently from early to late adulthood (Morrison,
Jebb, Tay, & Diener, 2017). For children, living in a higher-income (and safer) neighborhood is related to
more opportunities to play outside (Carver, Timperio, & Crawford, 2008), access to positive adult role
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models (Galster, 2014), and freedom from the chronic stressors associated with crime and violence
(Finkelhor, Turner, Shattuck, Hamby, & Kracke, 2015), all of which contribute to indicators of better wellbeing
in both the short- and long-term. In a randomized housing mobility study, low-income adults who
were randomly assigned to move from a low-income to a higher-income neighborhood showed
improvements in subjective well-being 10-15 years following the move, even though the move did not
affect personal economic self-sufficiency (Ludwig et al., 2012).
Other predictors of well-being are more salient at specific points in the lifespan. For example, being
bullied is a more common experience during childhood and adolescence than during adulthood and,
therefore, a more salient contributor to lower well-being earlier in life (Olweus & Breivik, 2014), although
bullying in the workplace does occur during adulthood, predicting worse well-being for adults as well
(Verkuil, Atasayi, & Molendijk, 2015). By contrast, romantic partnerships do not become developmentally
normative until adolescence, at which point experiences in romantic partnerships begin predicting wellbeing
(Collins, 2003). Having a job is a more important predictor of well-being in middle adulthood than in
early or later adulthood (Morrison et al., 2017). Generativity (An, Cooney, & An, 2006) and wisdom
(Ardelt, 2016) are important contributors to subjective well-being during later life. The link between
behaving prosocially and subjective well-being strengthens from early to late adulthood (Morrison et al.,
2017). Thus, predictors of well-being are sometimes tied to temporally proximal, developmentally salient
experiences.
However, some experiences continue to predict well-being even years later. For example, physical,
emotional, and sexual abuse during childhood have long-lasting detrimental effects on subsequent
development (e.g., Draper et al., 2008). Adults who were abused as children are at greater risk for
depression, anxiety, and other psychiatric disorders; have higher suicide rates; and report being less
satisfied with their lives than do adults who did not experience childhood abuse (e.g.,
Fergusson, McLeod, & Horwood, 2013). Other adverse childhood experiences such as exposure to
substance abuse in the home or having a mentally ill or incarcerated family member also can have longterm
detrimental effects on well-being that persist into adulthood (Nurius, Green, Logan-Greene, & Borja,
2015). By contrast, warm, sensitive, responsive caregivers promote secure attachment relationships with
their children, which can have protective effects throughout childhood, adolescence, and into adulthood
(Schoenmaker et al., 2015). Social connections during adolescence are better predictors of well-being in
adulthood than are academic achievements (Olsson, McGee, Nada-Raja, & Williams, 2013). The extent to
which specific life events are related to long-term changes in subjective well-being depends on the event in
question. For example, individuals adapt more quickly to marriage (Lucas et al., 2003) than to divorce
(Lucas, 2005) or unemployment (Lucas at el., 2004).
In addition to life experiences, one’s own choices can have long-term effects on well-being. Headey
et al. (2010) identified several types of choices and preferences that are related to long-term changes in life
satisfaction. Marriage to a partner low in neuroticism improves well-being over time, above and beyond an
individual’s own low neuroticism (Headey et al., 2010). Placing relatively greater emphasis on altruistic
goals (helping other people and being involved in social and political activities) and family goals (having
good relationships with one’s spouse and children) over goals related to material success and one’s own
career predicts increases in life satisfaction over time, whereas prioritizing goals related to career and
material success predicts decreases (Headey et al., 2010). For women, having a partner who prioritizes
family goals also contributes to an increase in life satisfaction over time (Headey et al., 2010). Long-term
increases in life satisfaction also are predicted by regular church attendance, working the desired number of
hours per week rather than being over- or under-worked (with being under-worked having worse
consequences than being over-worked), social participation with friends, and regular exercise (Headey et
al., 2010).
Consequences of Well-Being
Well-being is an important outcome in its own right. In surveys of what adults desire for their
children’s futures, happiness is highly ranked across diverse countries (Diener & Lucas, 2004). The
importance of subjective well-being has been recognized by governments around the world and has been
added as an indicator of how nations are faring, along with more traditional measures of gross domestic
product, infant mortality, and the like (Helliwell, Layard, & Sachs, 2017). Happiness is now regarded as an
indicator of social progress at a national level, in addition to a desired outcome at an individual level.
Subjective well-being is also related to several other desired outcomes. Individuals higher in
subjective well-being maintain better physical health and even live longer than individuals lower in
subjective well-being (Diener & Chan, 2011; Diener, Pressman, Hunter, & Chase, 2017). In addition, better
subjective well-being is related longitudinally to better outcomes in several domains such as higher
educational achievement, better performance at work, and less work-family conflict (De Neve, Diener,
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Tay, & Xuereb, 2013; Matthews, Wayne, & Ford, 2014; Suldo, Gormley, DuPaul, & Anderson-Butcher,
2014). Associations between subjective well-being and other aspects of adjustment are bidirectional and
transactional over time. For example, well-being in one year predicts more community participation in the
next year, and more community participation in one year predicts better well-being in the next year,
controlling for continuity in both well-being and community engagement as well as potential confounds
(Ding, Berry, & O’Brien, 2015). Taken together, previous research supports the conclusion that better wellbeing
predicts future adjustment in other areas, even after controlling for prior adjustment in those areas.
Several studies have investigated mechanisms through which well-being could affect other
outcomes. For example, in the education domain, brain imaging studies have demonstrated that positive
emotions are related to more effective cognitive processing (Hinton, Miyamoto, & Della-Chiesa, 2008),
which promotes success in school. Positive emotions also are related to more critical and flexible thinking,
which helps students handle academic challenges (Fredrickson, 2001). Negative emotions such as anxiety
and depression, by contrast, interfere with memory and efficiency of learning (see Valiente, Swanson, &
Eisenberg, 2012). The “Broaden and Build” theory (Fredrickson, 2001) suggests that positive emotions
promote academic success by encouraging exploratory, broadening thoughts, whereas negative emotions
narrow students’ focus, making them less engaged in school (Reschly, Huebner, Appleton, & Antaramian,
2008).
Taken together, extant findings suggest that consequences of well-being are tied to developmentally
salient outcomes at particular points in the lifespan. For example, links between well-being and academic
achievement are more salient during childhood and adolescence, whereas links between well-being and less
work-family conflict are more salient during adulthood. Because early development sets the stage for later
development, consequences of well-being during early childhood may be especially important for setting in
motion developmental cascades predicting future well-being and positive outcomes in other domains
(Masten & Cicchetti, 2010). Indeed, prevention science has demonstrated greater returns on investments
made in early childhood than in later childhood or subsequent developmental periods (Heckman, 2006).
Sociodemographic Considerations in Relation to
Subjective Well-Being across the Lifespan
Gender
In the adult literature, common findings are that women report higher life satisfaction than men but
also more negative affect, including anxiety and depression (Senik, 2015; for a detailed discussion of
gender differences in subjective well-being, see Batz & Tay chapter in this volume). Gender differences
appear more pronounced at some points in the lifespan than others. Prior to adolescence, boys and girls
have similar levels of well-being, but with the onset of puberty, gender differences begin to emerge,
especially marked by increases in anxiety and depression for girls (Hankin & Abramson, 2001). Gender
differences in well-being also have been reported in late adulthood. A meta-analysis of 300 studies found
that in later life, women reported lower life satisfaction and happiness than men; the magnitude of the
effects was small, accounting for less than 1% of the variance, but remained significant after controlling for
widowhood, socioeconomic status, and physical health (Pinquart & Sörensen, 2001). Biological factors
may account for some of the documented gender differences, but environmental factors such as gender
equality at a societal level also play a role (e.g., Meisenberg & Woodley, 2015).
Culture or Country
International research has demonstrated that countries differ in their average level of subjective
well-being and that subjective well-being is related to country-level factors such as individualism, equality,
human rights, and income (Diener, Diener, & Diener, 1995). According to surveys conducted in 135
countries in 2013, countries in Latin America fare the best, and countries in sub-Saharan Africa fare the
worst on a number of indicators of subjective well-being (Standish & Witters, 2014). Some of these
differences have been attributed to cultural factors such as focusing on the positives in life in Latin
America, and others may result from dire living situations involving civil war and extreme poverty
(Standish & Witters, 2014).
Using data from representative samples of over 1.2 million adults in 155 countries, life satisfaction
and negative affect were found to be slightly higher whereas positive affect was slightly lower in older than
younger age groups (Morrison et al., 2017). However, there were regional differences. Compared to older
adults in regions with negative attitudes toward aging, older adults in East and Southeast Asia, where older
adults are more respected, showed levels of well-being more comparable to those of younger adults.
Indicators of subjective well-being have become an important part of assessing how countries are
faring with respect to a wide range of factors that historically included primarily economic and physical
health considerations (Helliwell et al., 2017). Historically, assessments of well-being at a national level
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were based on external observations (e.g., poverty, material deprivation), but individuals who are poor can
still be happy. Asking individuals to report on their own well-being provides a different perspective that
may or may not align with external indicators. Assessing the subjective well-being of children and
adolescents has become a way to give young people a voice and promote their participation rights
(Martorano, Natali, De Neubourg, & Bradshaw, 2013).
Socioeconomic Status
Poverty and severe economic deprivation are related to low subjective well-being (Howell &
Howell, 2008). There has been debate regarding whether there is a certain level of financial security
beyond which additional economic resources do not predict further increases in well-being (see Stevenson
& Wolfers, 2013). At a national level, after gross domestic product per capita exceeds $10,000, some
research has reported that no additional increases in life satisfaction are found (Layard, 2005). For a family
with an annual income of $10,000, an additional $10,000 would constitute a doubling of the family’s
financial resources for the year and have more substantial benefits in terms of being able to provide food
security and pay for basic necessities, whereas a family with an annual income of $100,000 may also enjoy
an additional $10,000, but this amount represents a smaller percent increase and would likely be used for
more discretionary purposes rather than basic necessities. However, other research has not found a satiation
point beyond which subjective well-being ceases to improve with further increases in income (Stevenson &
Wolfers, 2013). As individuals’ income rises, so do their expectations and reference points (Wolbring,
Keuschnigg, & Negele, 2013). On a day-to-day basis, higher income is associated with more anger,
hostility, anxiety, and tension, but not with happiness (Schnall, Schwartz, Landsbergis, Warren, &
Pickering, 1998), perhaps in part because higher income is related to spending more time at work and in
compulsory non-work activities that are related to tension and stress, but not with time in leisure activities
that are related to happiness (Kahneman, Krueger, Schkade, Schwarz, & Stone, 2006). The relation
between income and well-being is stronger for cognitive (life satisfaction) than for emotional (happiness)
measures of well-being (Howell & Howell, 2008).
Subjective Well-Being during Different Life Stages
Infancy
Underlying positivity or negativity may be expressed in similar or different ways at different ages.
During infancy, negativity is generally reflected in descriptions of fussy or difficult temperaments, whereas
positivity is reflected in descriptions of easy temperaments (Bates, Schermerhorn, & Petersen, 2014).
Temperamental differences during infancy can persist into adulthood (Schwartz, Wright, Shin, Kagan, &
Rauch, 2003). In the first year of life, infants do not yet have internal representations of mental states that
are the foundation of cognitive aspects of subjective well-being (e.g., judgments regarding life satisfaction;
Siegler, 2017). However, infants experience positive affect, as expressed through smiles, laughter, and
positive vocalizations such as cooing, as well as negative affect as expressed through crying and fussing.
Social smiles that begin in response to someone else’s smile emerge between the age of four to eight weeks,
and laughs begin by three to four months, increasing in frequency when interacting with familiar people by
about six months (Gerber, Wilks, & Erdie-Lalena, 2010).
At this young age, caregivers play a more central role in emotion regulation than will be the case
later in development. Sensitive caregivers will anticipate infants’ needs to promote positive affect and will
respond quickly to reduce negative affect. Through these interactions with caregivers, infants develop
internal working models of relationships that set the stage for future interpersonal interactions (Bretherton
& Munholland, 2008). Infants who have sensitive, responsive caregivers come to expect that their needs
will be met by others and regard the world as a caring and reliable place; being securely attached to
caregivers during infancy then predicts the development of more trusting social relationships in later
developmental periods, including through late adulthood (Consedine & Magai, 2006). In contrast, infants
whose emotional needs are not met by caregivers develop internal working models of relationships
characterized by distrust, foreshadowing problems in future social relationships and decreasing well-being
(Bretherton & Munholland, 2008).
Childhood
Cognitive developments during early childhood lead to the emergence of more sophisticated forms
of subjective well-being as children become increasingly able to understand their own and other people’s
mental states. Theory of mind, which refers to the understanding that other people have thoughts and
beliefs that can differ from one’s own, typically emerges between the ages of three and four years.
Although the development of theory of mind has advantages in terms of promoting children’s perspective
taking and ability to show empathy and provide support to others, the development of theory of mind is
also associated with a decrease in self-esteem (Chaplin & Norton, 2015). Between early and middle
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childhood, children become increasingly self-critical as they develop a more nuanced perspective on their
own strengths and weaknesses relative to other people (Markus & Nurius, 1984).
During middle childhood, self-concept, self-esteem, self-efficacy, and self-worth emerge as
increasingly important constructs (Harter, 2012), all of which are related to subjective well-being. These
developing conceptions of the self all relate to cognitive aspects of well-being as children become more
reflective and able to evaluate how they regard themselves and their lives. Play also has an important role in
subjective well-being during childhood. Pretend play characterized by more emotion has been found to
predict more subsequent life satisfaction and positive affect in real life, perhaps because through pretend
play children are able to practice expressing and regulating emotions and coping flexibly (Fiorelli & Russ,
2012).
Beyond these cognitive and emotional developments, children who have positive relationships with
family members and peers are also more satisfied with their lives and happier. As in infancy, parent-child
relationships are among the most important predictors of well-being during childhood (Khaleque & Rohner,
2002). Dyadic friendships as well as acceptance (as opposed to rejection) by larger peer groups are
important sources of fun and positive affect (e.g., Holder & Coleman, 2015). Thus, social relationships
during childhood are directly associated with well-being because they provide opportunities for moment-tomoment
enjoyment and positive affect as well as indirectly associated with well-being through mediators
such as a sense of belonging and self-worth that enhance children’s satisfaction with life. Social
relationships continue to be importantly related to subjective well-being in adolescence and adulthood.
Adolescence
The onset of puberty marks the beginning of adolescence and a turning point in some aspects of
subjective well-being. During adolescence, girls begin experiencing more negative affect than boys, which
manifests in higher rates of internalizing disorders such as depression and anxiety that begin to emerge at
this time and persist into adulthood (Nolen-Hoeksema & Girgus, 1994). As in childhood, relationships with
parents and peers are related to well-being during adolescence, with friends becoming increasingly
important confidantes (Markiewicz & Doyle, 2012). In addition, individuals often form their first romantic
partnerships during this developmental period, with attendant risks and benefits for well-being (Collins,
2003).
Early theories and empirical studies focused on adolescence emphasized “storm and stress”
characterized by conflict and negative emotions (for a review, see Arnett, 1999). However, the more recent
positive youth development movement attends to more positive aspects of adjustment. For example, the
Five Cs model focuses on caring/compassion, competence, character, connection, and confidence (Lerner,
Almerigi, Theokas, & Lerner, 2005). During adolescence, character strengths that build connections to
other people (e.g., teamwork, kindness) and that contribute to a sense of purpose beyond the self (e.g., love,
meaning) are related to an increase in subjective well-being over time, including an increase in life
satisfaction and a decrease in depressive symptoms (Gillham et al., 2011).
Early Adulthood
Early adulthood is characterized by major changes in family relationships as individuals transition
from their families of origin to families of their own creation, yet relationships with parents continue to be
related to well-being during early adulthood (Trzcinski & Holst, 2008). Intimate partnerships become
increasingly important in early adulthood. A widely replicated finding is that men and women who are
married are happier and more satisfied with life than non-married men and women (e.g., Waite & Lehrer,
2003). Even with marked demographic changes in the average age of marriage and the proportion of adults
choosing to remain unmarried (e.g., Settersten & Ray, 2010), married individuals show better well-being
than unmarried individuals in both low- and high-income countries, although the marriage benefit appears
to be shrinking for men, particularly in high-income countries, as the life satisfaction of unmarried men has
increased over time from 1981 to 2009 (Mikucka, 2016). Furthermore, despite these demographic changes,
marriage continues to confer benefits for well-being that exceed those of cohabitation, although the
difference is smaller in countries that are more accepting of non-traditional family forms (Vanassche,
Swicegood, & Matthijs, 2013).
In addition to intimate partnerships, family formation during early adulthood often involves the
transition to parenthood. Conclusions about how parenthood is related to well-being have been inconsistent
and appear to depend largely on how the analyses are conducted (e.g., with or without control variables that
differentiate who becomes a parent in the first place) and on who the reference group is (comparing parents
to non-parents or comparing an individual to him or herself before and after becoming a parent). A metaanalysis
of prospective longitudinal studies found that the transition to parenthood is associated with a
decline in life satisfaction (particularly tied to a decline in satisfaction with the intimate partnership) but an
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increase in positive affect (Luhmann et al., 2012). After this initial transition, controlling for marital status,
religion, income, education, and health, some research has found that adults who live with a child are less
satisfied with life and have higher levels of both positive and negative affect (Deaton & Stone, 2014).
Other findings suggest that compared to non-parents, parents have higher levels of life satisfaction,
moment-to-moment happiness, and feel more positive when taking care of their children than their daily
average of positive emotion (Nelson, Kushlev, English, Dunn, & Lyubomirsky, 2013). However, these
findings are moderated by gender, with men who are parents generally reporting more happiness than men
who are not parents but no differences in happiness for women (Nelson et al., 2013), which the authors
suggest may reflect the greater burden of housework and childcare experienced by mothers than fathers
(Nomaguchi & Milkie, 2003). In addition, the findings depend on the circumstances of parenthood with
individuals who were younger and unpartnered at the time they became parents reporting less satisfaction
and happiness (but more meaning in life) than their counterparts who are not parents (Nelson et al., 2013).
Early adulthood also is characterized by education and work transitions related to completing
schooling and joining the workforce, tasks that have become more prolonged in recent years than in the
past (Settersten & Ray, 2010). Having employment problems that necessitate moving back in with parents
is related to more depressed affect in early adulthood (Copp, Giordano, Longmore, & Manning, in press).
In support of a value-as-moderator model, there is evidence that activities that are valued by an individual
exert greater influence on well-being than activities that the individual does not value as strongly (Oishi,
Diener, Suh, & Lucas, 1999). For example, receiving good grades at school is related to life satisfaction
more strongly for individuals who place high value on achievement than for those who do not (Oishi et al.,
1999). These findings suggest that in early adulthood, psychological well-being will be associated with
engaging in roles and activities that have personal value and meaning.
Middle Adulthood
Middle adulthood is the time of life that is at the nadir of subjective well-being for individuals from
high-income countries (Stone et al., 2010). At this time of life, individuals juggle many family, work, and
community roles, contributing to stress and fatigue that can take their toll on well-being (Scheibe & Zacher,
2013). This developmental period is sometimes known as the “sandwich generation” to refer to the period
roughly between the ages of 45 and 65 years in which adults are sandwiched between demands of caring
for children and aging parents while still working in the paid labor force (Burke, 2017). Women continue to
provide the majority of care to both children and aging parents, and providing extensive care is related to
more depression and lower subjective well-being (Hammer & Neal, 2008). Demographic changes with an
increase in the proportion of adult children who return home to live with their parents might also contribute
to stress during middle adulthood. Relationships between parents in middle adulthood and their young adult
children are generally positive, but parents feel more ambivalent about these relationships when their adult
children are not attaining autonomy milestones (Fingerman, Cheng, Tighe, Birditt, & Zarit, 2012).
Late Adulthood
Subjective well-being is related to health and longevity (Diener & Chan, 2011), considerations that
become especially salient later in life. In longitudinal analyses with an average follow-up of 8.5 years,
controlling for demographic factors as well as baseline measures of physical and mental health, 29% of
individuals in the lowest quartile of well-being died during the follow-up period compared to only 9% of
individuals in the highest quartile (Steptoe et al., 2015). Well-being has been found to remain relatively
stable during late adulthood until shortly before death, when it drops precipitously (Gerstorf, Ram, Goebel,
Schupp, Lindenberger, & Wagner, 2010). The drop in well-being is more pronounced for individuals who
die after the age of 85 (about three times as steep a decline in the four years before death than prior to that
point) than for those who die between the ages of 70 and 84 (about two times as steep a decline), perhaps
because of the accumulation of health problems and the loss of loved ones over a longer period of time
(Gerstorf, Ram, Röcke, Lindenberger, & Smith, 2008).
Socioemotional selectivity theory posits that as individuals age, they selectively prune their social
networks to focus on a smaller group of family members and friends to whom they are emotionally close
rather than larger groups of acquaintances or individuals with whom they have distant or contentious
relationships (Carstensen, Isaacowitz, & Charles, 1999). The theory has garnered considerable empirical
support (for a review see Charles & Carstensen, 2010). Early in life when individuals perceive themselves
as having a long future, they prioritize goals related to meeting new people, gathering information, learning
new things, and maximizing achievement, whereas in late adulthood when individuals perceive their
futures to be shorter, they prioritize short-term goals related to positive emotions and activities that are
meaningful to them (Carstensen, 2006). Taken together, this body of research suggests that higher wellbeing
during late adulthood is related to this narrowing of the social network and focusing on goals that
promote positive affect.
374
Future Directions
As the study of subjective well-being advances, three directions for future research might be
especially useful. First, future research in neuroscience offers the potential to understand brain mechanisms
involved in subjective well-being across the lifespan (see biology chapters in this volume). Early research in
this area provides some intriguing insights into structural and functional aspects of the brain that could help
delineate the neural underpinnings of well-being. For example, compared to adults not in a romantic
relationship, adults with a romantic partner not only report more happiness but also show less gray matter
density in the right dorsal striatum, a region of the brain important in processing social rewards
(Kawamichi et al., 2016), suggesting one mechanism through which social relationships could affect wellbeing.
Better understanding the biological substrates of well-being also offers the potential to intervene in
targeted ways to enhance the well-being of individuals who are at risk for a variety of reasons. For
example, treating mothers at risk of postpartum depression with oxytocin, a neuroendocrine hormone that
promotes adjustment to motherhood, shows promise both in reducing postpartum depression and in
promoting mother-infant bonding (Kim et al., 2014).
Second, future research on genetic factors and gene x environment interactions that shape subjective
well-being across the lifespan will be important for understanding stability, change, and individual
differences in subjective well-being. Estimates vary depending on features such as study design and
measures used, but a recent meta-analysis found that approximately 32% of the variability in life
satisfaction can be accounted for by genetic factors (Bartels, 2015). However, environmental factors have
been found to both weaken and strengthen genetic effects on well-being. For example, being married has
been found to weaken heritability estimates (Nes, Røysamb, Harris, Czajkowski, & Tambs, 2010), whereas
increasing income has been found to strengthen heritability estimates (Johnson & Krueger, 2006).
Conceptual models have come to recognize that it is not just that particular genetic markers can serve as
risk factors in the face of certain environments but that particular genetic markers can make individuals
more susceptible to both positive and negative environments, either enhancing or limiting prospects for
well-being (Ellis & Boyce, 2008).
Third, the most consistent predictor of better subjective well-being across the lifespan is positive
social relationships (Siedlecki et al., 2014). New technology has brought about many changes in social
relationships that might affect well-being for the better or worse. On the one hand, texting, Skype, and
social networking make it possible to stay in touch with family and friends who are not in close
geographical proximity, which might contribute to enhanced well-being (Grieve, Indian, Witteveen, Tolan,
& Marrington, 2013). On the other hand, online communication may not confer the same benefits for wellbeing
as spending time with friends and family in person, especially if the online communication is not with
people to whom individuals have strong ties or if the communication involves general posts rather than
personal, dyadic communication (Burke & Kraut, 2016). Early research suggested that within the first one
to two years that families began using the Internet, their social networks narrowed, they communicated less
with other members of the household, and their depression and loneliness increased (Kraut et al., 1998).
More recent research has yielded mixed findings (e.g., Best, Manktelow, & Taylor, 2014, for a review).
Future research will benefit from trying to elucidate the ways that subjective well-being is related to social
relationships in new, ever-changing technological contexts.
Conclusions
Adopting a lifespan perspective on subjective well-being facilitates understanding of the
development of well-being over time. A large body of research has demonstrated that well-being is fairly
stable over time as well as that, on average, individuals have lower mean levels of well-being during
middle adulthood than earlier or later in the lifespan (particularly in high-income countries). In every stage
of development, family relationships are central to well-being. During infancy, secure attachment
relationships with parents set the stage for trusting, supportive relationships throughout life. During
childhood and adolescence, parents remain important, but peer relationships take on increased importance
in relation to well-being. In adolescence and early adulthood, romantic partnerships become
developmentally salient and important sources of well-being. With the transition to parenthood,
relationships with children bring well-being full circle to the next generation. Cognitive development across
the lifespan enables the emergence of a sense of self during infancy that supports cognitive aspects of wellbeing,
and during adulthood a future orientation and perceptions of time remaining in life are related to
selective narrowing of social networks in ways that promote positive affect and life satisfaction. Life events
and life choices can have both short- and long-term effects on well-being. Subjective well-being is
important throughout life both in its own right as an important outcome as well as because better subjective
well-being predicts other desirable outcomes including longevity.
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Gender Differences in Subjective Well-Being
By Cassondra Batz & Louis Tay, Purdue University
Citation
Batz, C., & Tay, L. (2018). Gender differences in subjective well-being. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
Results regarding whether men and women differ in terms of their well-being levels have been highly
inconsistent. To more conclusively understand the past research regarding on the relationship between
gender and subjective well-being (i.e., life satisfaction, positive affect, and negative affect), we summarize
the current body of the literature on the subject including both large, nationally representative empirical
papers as well as past meta-analyses. Next, we review explanations behind the presence of gender
differences in subjective well-being as well as explanations behind the lack of gender differences in
subjective well-being. We conclude by addressing current limitations of the present research and propose
important future directions to further disentangle the remaining questions regarding gender differences in
subjective well-being
Keywords: Gender Differences, Sex Differences, Subjective Well-being, Affect
Pundits, policy-makers, and lay people alike are captivated by differences between men and
women. Questions of gender differences inundate both the popular press and academic journals: how, are
men and women different, and why? It is not uncommon to see gender comparisons as a main emphasis in
research on different psychological characteristics or drawn on as a moderator of interest. The role of
gender and gender differences in well-being has also been of longstanding interest. Intriguingly, results
regarding well-being differences in gender have often been inconsistent. While at times research fails to
find a significant difference between men and women’s well-being (e.g., Okun & George, 1984), others
demonstrate significant differences between the genders in opposing directions (e.g., Stevenson & Wolfers,
2009; Haring, Stock, & Okun, 1984; Fujita, Diener, & Sandvik, 1991). Complicating matters, there are
different aspects of well-being (e.g., positive affect, negative affect) that one can make comparisons on and
different sub-populations within which gender comparisons are made (e.g., age, nation) (e.g., Shmotkin,
1990). Given an ongoing interest in gender differences in well-being, and the inconsistent results found in
the past, there is a need to synthesize the well-being literature and provide conceptual grounding for when
we might see gender differences in well-being, when we may not, and why.
In this chapter, we summarize the present state of research on gender differences in well-being.
Specifically, we focus on subjective well-being (SWB) among the different possible conceptualizations of
well-being. We begin by reviewing past research on gender differences on the three components of SWB
(e.g., life satisfaction, positive affect, and negative affect). Next, we will discuss the findings of several
large-scale meta-analyses and samples on the different SWB components. After which, we present the
conceptual underpinnings that have been proposed as to why we would, or would not, expect to find
differences in well-being between men and women. Drawing on the above, we conclude with limitations of
current research and future directions to help address remaining unanswered questions.
Past Research on Gender Differences in Subjective Well-being
Subjective Well-being
Given widespread interest in gender and well-being, gender differences in SWB has been
repeatedly examined over time. In a landmark review of the SWB literature, Wilson (1967) concluded that
one’s sex was not associated with happiness – though this conclusion was based on only two studies. One
study was commissioned by the US congress to examine the mental health of 2,460 American adults 21
years old and older (Gurin, Veroff, & Feld, 1960), and the second was a study that included data from 450
households from various social-economic statuses (Bradburn & Caplovitz, 1965). Since more research has
been conducted on this issue, re-examining the initial conclusion of a lack of gender differences in SWB is
necessary.
Across broader and larger samples, there have been mixed findings on whether there are gender
differences in SWB. Whereas some research has found that men have significantly higher levels of SWB
(e.g., Stevenson & Wolfers, 2009; Haring, Stock, & Okun, 1984), other studies have shown that women
have significantly higher levels of SWB (e.g., Fujita et al., 1991). Complicating matters further, many
studies have found no significant differences (Okun & George, 1984), particularly after controlling for
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Table 1.
Summary of Large Scale, Nationally Representative Studies on Life Satisfaction
Study Sample Characteristics (Number
of Nations)
Sample Size Findings
Clemente & Sauer (1976) US representative sample (1) 1,347 No significant gender
difference in life satisfaction
Inglehart (2002) International representative
sample (65)
~150,000
Young women have higher
levels of life satisfaction than
young men; Older women
have lower levels of life
satisfaction than older men.
Blanchflower & Oswald (2004) US and UK representative
samples (2) 94,574
Women have higher levels of
life satisfaction than men.
other relevant demographic factors (e.g., age, marital status) (e.g., White, 1992; Inglehart, 1990; Shmotkin,
1990; Warr & Payne, 1982; Larson, 1978).
It has been proposed that these inconsistent and conflicting reports are in part due to SWB being
comprised of three components: (1) positive affect, (2) negative affect, and (3) life satisfaction (Diener,
Lucas, & Oishi, 2002; Diener, 1984). The magnitude and direction of the gender differences diverge for
each component and conflating them in the analysis may reduce any observed differences – or it may lead
to empirical confusion when not distinguished conceptually (Diener, Suh, Lucas, & Smith, 1999; Parker &
Brotchie, 2010).
The idea that there are differences within these components has been supported by several studies
that have examined the components of SWB independently. For instance, a large-scale international study
by Lucas and Gohm (2000) found that in most of the nations examined, women experienced more negative
affect than men. Other studies have reported similar findings that negative affect is more prevalent among
women (Nolen-Hoeksema & Rusting, 2003). This is supported by research within the clinical domain that
has found women experience greater levels of depression, anxiety, and mood disorders than men (Eaton et
al., 2012; Grant & Weissman, 2007). Furthering the support of this explanation is the fact that women are
also reported to experience higher levels of positive affect, or happiness, than men (Wood, Rhodes, &
Whelan, 1989; Lee, Seccombe, & Shehan, 1991). Therefore, it is likely that the inconsistent findings may
be in part attributable to conflating different dimensions of SWB – such as positive and negative affect. To
avoid this potential pitfall, we will review past research on life satisfaction, positive affect, and negative
affect separately.
Additionally, apart from conflating the different components of SWB, there may also be sampling
variability leading to differences in observed gender SWB differences. To minimize this potential, we
focus our review drawing on large-scale nationally representative studies and previous meta-analyses.
Life Satisfaction. Broadly, large-scale, nationally representative studies on life satisfaction have
found somewhat mixed results on gender differences in life satisfaction. An early study by Clemente and
Sauer (1976) found no significant differences between men and women on life satisfaction in representative
sample of over 1,000 individuals from the United States. A study by Inglehart (2002) in using data from
the World Values Survey that spanned more than 60 nations found that the direction of the gender
difference was dependent upon on the age group, whereas younger (e.g., 18-44) women had higher levels
life satisfaction than younger men, but older women (e.g., 44-65+) had lower levels of levels of life
satisfaction than older men. A later study by Blanchflower and Oswald (2004) that compared over 20,000
individuals from both the United States and Great Britain, cited a small effect with women reporting higher
levels of life satisfaction than men in both Great Britain and the United States. The most recent study by
Tay, Ng, Kuykendall, and Diener (2014) used the Gallup dataset to examine this question for full-time
workers across the United States and over 150 other countries. For the United States, they found very small
effect size differences, but found larger differences across other included nations in which full-time
working women had higher life satisfaction than full-time working men (Tay et al., 2014).
383
Tay, Ng, Kuykendall, & Diener
(2014)
International representative
sample (156)
172,949 Women have higher levels of
life satisfaction than men.
Notes. US= United States; UK = United Kingdom; ~ = approximate as reported by author
Consistent with large-scale representative samples, past meta-analyses have also been conducted on
the question of gender differences in life satisfaction and have resulted in mixed findings as well. One of
the first large scale reviews conducted on the subject was done by Haring, Stock, and Okun in 1984.
Haring and colleagues (1984) looked at empirical studies from the US that examined gender and social
class as predictors of subjective well-being. The studies included were conducted prior to 1980 and had to
include “life satisfaction, happiness, morale, quality of life, and subjective well-being” as keywords. Based
on the studies that met the above criteria, their results showed that men had slightly higher levels of
subjective well-being, which included life satisfaction, than women, but the magnitude of this difference
was small (r = .03; d = .06).
A few years later, Wood, Rhodes, and Whelan (1989) conducted another meta-analysis on sex
differences in positive well-being with attention paid to marital status and emotional style. They drew upon
85 studies from both US and international samples that provided a comparison between men and women on
measures of life satisfaction, happiness, morale, positive affect, or general well-being. In terms of life
satisfaction, it was found that men had lower levels of life satisfaction than women (d = - .03).
Another meta-analysis conducted by Pinquart and Sörensen (2001) investigated differences
between men and women over the age of 55 in psychological well-being. They included 174 studies from
the developmental and gerontological literature that looked at gender differences in life satisfaction. They
found that older men, as compared to older women, reported slightly higher levels of life satisfaction (g =
.08; d = .08).
Most recently, Batz, Tay, Kuykendall, and Cheung (under review) conducted a meta-analysis that
examines gender differences in life satisfaction and the influence of gender inequality on the size of this
difference. Across the 281 included samples, which included over a million individuals, Batz and
colleagues (under review) found that, after accounting for publication bias, men and women significantly
differed in their levels of life satisfaction such that men report higher levels of life satisfaction than women
(d = .03).
Table 2.
Summary of Meta-Analyses on Gender Differences in Life Satisfaction
Meta-Analysis Sample Characteristics Sample Size Findings Effect Size**
Haring, Stock, & Okun
(1984)
US samples (k=146) 52 Men have higher levels
of life satisfaction.
.06
Wood, Rhodes, &
Whelan (1989)
US and international
samples (k= 85)
1,505* Women have higher
levels of life
satisfaction than men.
-.03
Pinquart and Sörensen
(2001)
US sample; Over age 55
(k= 174)
27,186 Men have higher levels
of life satisfaction.
.08
Batz, Tay, Kuykendall,
& Cheung (under
review)
US and international
samples (k= 281)
1,001,802 Men have higher levels
of life satisfaction.
.03
Notes. US = United States; k = number of samples; a positive effect size indicates men having greater life
satisfaction; * = median number of participants among all included studies, total was not reported; **All effect sizes
converted to Cohen’s d for interpretation
Taken together, the majority of the results from meta-analyses on this subject favor the conclusion
that men and women do significantly differ in life satisfaction, such that men have higher levels of life
satisfaction than women, though the size of the difference is small.
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Positive Affect. Across large, nationally representative samples, the discrete emotion of ‘happy’ or
‘happiness’ is often the operationalization of positive affect. An example of this is first seen in Inglehart’s
(2002) examination of the World Values Survey of individual from over 60 nations. Inglehart (2002) found
that gender differences in happiness levels were dependent upon age, whereas young (18-44) women are
happier than young men, middle aged (45-54) women and men do not differ in terms of happiness, but
older (55+) women are less happy than older men. Another example of this is research by Easterlin (2003)
who looked at gender differences in happiness using the internationally representative sample from the
General Social Survey. Easterlin’s results (2003) mirrored that of Inglehart (2002), finding that younger
women are happier than younger men, while older women are less happy than older men. A more recent
study Zuckerman, Li, and Diener (2017) examined gender differences in positive affect, measured by using
a range of positive emotions beyond just happiness, using data from the Gallup World Poll, a globally
representative data set of over 150 countries. Their results indicated that men and women did not
statistically differ in terms of positive affect.
Table 3.
Summary of Large Scale, Nationally Representative Studies on Positive Affect
Study Sample Characteristics
(Number of Nations)
Sample Size Findings
Inglehart (2002) International representative
sample (65)
~150,000 Young women have higher levels
of happiness than young men;
Middle aged women and men do
not significantly differ in levels of
happiness; Older women have
lower levels of happiness than
older men.
Easterlin (2003) International representative
sample (Not reported)
Not Reported Young women have higher levels
of happiness than young men;
Older women have lower levels of
happiness than older men.
Zuckerman, Li, & Diener
(2017)
International representative
sample (162)
455,104* No significant difference between
men and women.
Notes. US= United States; ~ = approximate as reported by author; * = total sample size for study overall
Meta-analyses have strived to summarize the rather large body of empirical studies that focus on
both happiness and positive affect. For example, Wood, Rhodes, and Whelan (1989) conducted a metaanalysis
based on 96 studies from both US and international samples. They found that women reported
higher levels of happiness (d = -0.07), but that when examined more broadly, there was not a nonsignificant
gender difference for positive affect overall. Another meta-analysis conducted by Pinquart and
Sörensen (2001) used 58 studies to investigated differences between men and women over the age of 55 in
happiness. They found that older women, as compared to older men, reported slightly lower levels of
happiness (g = .06; d = .06).
Table 4.
Summary of Meta-Analyses on Gender Differences in Positive Affect
Meta-Analysis Sample Characteristics Sample Size Findings Effect Size**
Wood, Rhodes, &
Whelan (1989)
International samples
(k= 85)
1,505* Women have higher
levels of happiness
than men; No gender
difference in positive
affect overall.
-.07; n.s.
385
Pinquart and Sörensen
(2001)
US sample; Over age 55
(k= 58)
53,197 Men have higher levels
of happiness.
.06
Notes. US = United States; k = number of samples; a positive effect size indicates men having greater life
satisfaction; * = median number of participants among all included studies, total was not reported; **All effect sizes
converted to Cohen’s d for easy interpretation
Collectively, the results from meta-analyses on this subject come to different conclusions, whereas
one finds that women report higher levels of happiness than men and the other finds the opposite to be true.
One reason for this variation may be two very important differences in the studies themselves: the inclusion
of international samples (Wood, Rhodes, & Whelan, 1989) versus the inclusion of samples only over the
age of 55 years old (Pinquart & Sörensen, 2001). Additionally, the analyses were done over a decade apart.
As such, one may conclude that the samples are so different that it is unfair to deem these results
inconsistent with one another and instead address the question of gender differences in positive affect for
different subsets of the population. Future work should examine this question further.
Negative Affect. Very few researchers have examined gender differences in negative affect on a
large-scale or meta-analytically. This is likely due to the overwhelming interest in gender differences in
mental health, particularly the experience of depression. Which, while related to negative affectivity, is
viewed as a distinct concept from negative affect in the context of subjective well-being (Luhmann,
Hofmann, Eid, & Lucas, 2012). However, one large-scale study by Zuckerman, Li, and Diener (2017) did
examine gender differences in negative affect using data from the Gallup World Poll, a globally
representative data set of over 150 countries. Their results indicated that men and women did significantly
differ in negative affect, such that women had higher levels of negative affect than men.
Table 5.
Summary of Large Scale, Nationally Representative Studies on Negative Affect
Study Sample Characteristics
(Number of Nations)
Sample Size Findings
Zuckerman, Li, & Diener
(2017)
International representative
sample (154)
455,104 Women have higher levels
of negative affect than men.
Notes. * = total sample size for study overall
This large analysis conducted by Zuckerman and colleagues (2017) suggests that men and women
significantly differ in negative affect, such that women have report higher levels of negative affect than
men. While this study provides a baseline in which examine this question using a large and representative
sample, one must avoid viewing this finding as conclusive. Future work must be done to examine this
question further – including future meta-analyses that seek to examine this question across more samples to
provide greater confidence in these results.
Reasons for Gender Differences in Overall Well-being
When attempting to explain gender differences in well-being, there are several themes that emerge
from the literature, including structural factors (i.e., differences in institutional arrangements and
opportunities between men and women), socio-cultural factors (i.e., differences in societal expectations
and norms for men versus women), and biological differences (i.e., physical and physiological differences)
(e.g., Stevenson & Wolfers, 2009; Wood et al., 1989; Tesch-Römer, Motel-Klingebiel, & Tomasik, 2008;
Landers, 1988; Fujita et al., 1991; Russo & Green, 1993). These differences are summarized in Table 6. We
recognize that there are likely complex interactions between these factors, but we seek to discuss them as
main effects for parsimony.
Table 6.
Explanations for Gender Differences in Subjective Well-being
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Category Psychological/Physiological
Mechanisms
Posited Outcome
Structural factors:
Access to educational,
economic, political, and social
resources, opportunities, and
power structures
Need fulfillment Women have lowered SWB due to limited
opportunities to fulfill basic and
psychological needs from current structural
inequalities between men and women
Social factors:
Societal expectations and norms
Gender role fulfillment
(prescription & description)
Violations of gender roles lead to lowered
SWB where women seeking to move into the
workplace or traditionally male-dominated
industries have lower SWB.
Emotional expressiveness is more acceptable
for women rather than men meaning they are
more willing to display and report higher
levels of positive affect and negative affect
than men.
Biological factors:
Physiological Hormones
Genetics
Hormonal differences, both in the type and
fluctuation, between men and women lead to
variations in the experiences of both positive
and negative emotions
Genetic differences between men and
women may led women to develop
personality types that make them more
susceptible to the experience of positive and
negative affect.
Structural Factors: Gender Inequalities & Need Fulfillment
One potential key to undersanding gender differences in SWB is Need Fulfillment theory. This has
often been implicitly, or explicitly, invoked in the examination of gender differences particularly for the
evaluative components of SWB (e.g., Diener & Lucas, 2000; Tay & Diener, 2011). Substantively, this
theory posits that SWB levels are dependent on the extent an individual’s physical and psychological needs
(e.g., autonomy, competence, relatedness) are fulfilled (Ryan & Deci, 2000; Ryff & Keyes, 1995; Maslow,
1943). This theory considers not only external, objective structural realities that influence the ability to meet
one’s needs, but also personal perceptions that physical and psychological needs are being met.
Based on this theory, gender differences in SWB may be understood in terms of the variation in
men and women’s experiences of global inequality within economic, educational, political, and social
structures. More specifically, differences in access to opportunity structures (e.g., access to education),
resources (e.g., income differences), and power systems (e.g., representation in government) for men and
women would lead to difference in their respective perceptions of their ability to meet their needs. Such that
women would not only be less able, but also feel less enabled to meet their needs as compared to men.
Subsequently this would result in gender differences in SWB, but the size of this difference likely would be
dependent upon the degree of inequality within these societal structures. Specifically, in nations and
communities where there is equality within these structures (i.e., opportunity, resource, power) there will
likely little to no difference in gender SWB but where inequality is high there will likely be greater
differences between the sexes.
A substantial amount of research has shown support for the idea that a greater provision of human
rights (e.g., civil, political) and greater equality (e.g., education, income) is related to higher levels of SWB
(Diener, Diener, & Diener, 1995; Oishi, Kesebir, & Diener, 2011; Oishi & Diener, 2014). Similarly, it has
been found that in societies with greater gender equality, individuals have higher levels of overall
happiness (e.g., Bjørnskov, Dreher, & Fischer, 2007; Inglehart & Welzel, 2005; Inglehart, Foa, Peterson, &
Welzel, 2008; Jorm & Ryan, 2014; Ruth & Napier, 2014; Schyns, 1998). This prior work is supportive of
the proposition that variations in the experiences of inequality may improve well-being for women and so
387
enhance overall well-being nationally.
More direct evidence has been found in an empirical study that examined whether gender
differences in life satisfaction were explained by variability in the experiences of gender inequality. The
study, conducted by Tesch-Römer and colleagues (2008), examined the influence in differences of cultural
inequality on the magnitude of gender differences in SWB in over 50 countries. They found that the greater
societal gender inequality, the greater the difference between men and women on levels of SWB, but only
in countries that valued gender equality.
However, some studies have found the opposite to be true to some degree. A study using data from
over 90 countries by Meisenberg and Woodley (2015) found that although some indicators of gender
equality and female status are related to higher life satisfaction for women, some indicators, including
women’s involvement in gainful employment and prolonged schooling, are negatively related to women’s
well-being. This may be explained by the fact that along with increases in opportunities and rights,
women’s aspirations and responsibilities have also increased, particularly in the workforce (Patten &
Parker, 2012; Regan & Roland, 1982). These shifting standards and increased demands may cause gender
differences in SWB to persist despite equality. The expansion of opportunities may have come at a cost for
women, and ended up benefiting men more than women (Stevenson & Wolfers, 2009). This idea is
consistent with work by Blanchflower & Oswald (2004) who found that women’s happiness decreased over
time in the United States and Britain despite women’s rise in resources, opportunities, and power.
Therefore, policies aimed at equality may have had an inadvertent negative impact on women’s levels of
SWB. Also, as women have taken on additional roles that were once reserved for only men, their
comparison group may have expanded, and thus their perception of their relative success possesses a more
negative connotation (Stevenson & Wolfers, 2009). Clearly, the relationship between culture, equality, and
need fulfillment may be complex and will require future research to disentangle why we do not see vastly
different effects despite these sometimes large disparities between men and women in terms of
opportunities and resources
Social Factors: Societal Expectations and Norms
Social factors may also help explain gender differences in SWB via the differences in the norms
and expectations for men and women, referred to in the literature as ‘gender roles.’ Gender roles are
socially held, descriptive and/or prescriptive stereotypes regarding the characteristics of each sex as well as
the subsequent acceptable, expected behaviors for men and women (Eagly & Karau, 2002). These
expectations and norms in gender roles influence the perceptions regarding the appropriate occupations for
men and women, the type of traits men and women should possess, and even the type of emotions that are
acceptable to experience and demonstrate for men and women. Researchers have explored the
consequences of violating gender role expectations and find that men and women who engage in behaviors
counter to these expectations often face backlash from others, which can subsequently have a negative
impact on both their successes and well-being (e.g., Eagly & Karau, 2002; Blazina & Watkins, 1996; Good
& Wood, 1995). For instance, research has shown that women experience backlash that impacts their job
satisfaction when they take on roles in organizations that are not traditionally feminine or require them to
behave in traditionally masculine ways (Garcia-Retamero & López-Zafra, 2006).
A significant part of gender role expectations is that it is more acceptable for women than men to be
emotionally expressive, which may also help explain why women report experiencing both positive and
negative affect more often than men (e.g., Simon & Nath, 2004; Plant, Hyde, Keltner, & Devine, 2000).
Men may be more reluctant than women to report the degree to which they feel specific positive and
negative emotions, which may influence the self-report based findings on gender differences in positive
and negative affect (Nolen-Hoeksema & Rusting, 2003). Moreover, these expectations may impact the
degree to which men and women allow themselves to actually feel and express these emotions (NolenHoeksema
& Rusting, 2003).
Research by Grossman and Wood (1993) has supported this idea, finding that women report more
extreme emotions than men without being prompted. However, when emotional responses were
manipulated for a person to be either more, or less, emotionally expressive, no sex differences were
obtained, which may be indicative of initial conformity to gender role expectations. Other research has
examined this question and found that women engage in more non-verbal expressions of positive emotions
(e.g., smiling, laughing) than men particularly when gender was made more salient (LaFrance, Hecht, &
Paluck, 2003). Similarly, a study by Fujita, Diener, and Sandvik (1991) examined the case for emotional
intensity further, finding that gender alone accounted for less than 1% in the variance in the valence
dimension of happiness-sadness, whereas gender accounted for approximately 13% of the variance on the
emotional intensity dimension, suggesting that women are more open to intense emotional experiences than
men.
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Biological Factors: Hormones and Genetics
There has also been research done regarding biological factors, such as hormonal or genetic
differences between men and women, that may contribute to men and women’s differing levels of the
affective components of SWB (e.g., Hyde, Mezulis, Abramson, 2008; McRae, Ochsner, Mauss, Gabrieli, &
Gross, 2008).
First, this idea has been supported by studies that have looked at relationships between genetics and
well-being. For example, a study by Weiss, Bates, and Luciano (2008) cited substantial evidence for a
genetic component to well-being and happiness. Røysamb and colleagues (2002) conducted further
exploration to test the hereditability of happiness. In this exploration, they used a classic twin-studies
design with over 5,000 individuals. Results indicated a significant gender difference in the heritability of
happiness. Further, they found that women have a greater genetic determination in their happiness level as
compared to men (Røysamb, Harris, Magnus, Vittersø, & Tambs, 2002). Additionally, research has
revealed that there might be different sets of genes that influence women’s happiness as compared to men’s
happiness. Research has attempted to dive further into this by identifying specific genes, such as the
monoamine oxidase A (MAOA) gene that is involved in mood regulation. Researchers postulate that the
presence of this gene, via its impact on mood regulation, lead women to experience moods more intensely
and lead to more frequent mood shifts than women with low expression of this gene, while the gene has no
impact on men (e.g., Chen et al., 2013). This may lend some insight as to why women report greater levels
of both positive and negative affect than men for instance However, when examined meta-analytically the
results remain unclear as to whether there are gender differences in the genetic architecture of well-being
(Bartels, 2015).
There is also some evidence that women’s hormones, including estrogen and progesterone, may be
tied to women’s fluctuations in positive and negative affect, particularly around times which those
hormones also fluctuate greatly such as their premenstrual period (Nolen-Hoeksema & Rusting, 2003).
However, other studies have reported that these shifts in hormones around a woman’s menstruation
influence on negative affect levels is inconclusive (Golub & Harrington, 1981), though substantial work has
shown that most women report mood shifts prior to menstruation (Johnson, 1987). Other work has looked
at the influence of these gonadal hormone fluctuations across a woman’s lifespan influence on their
neurochemistry and their neuroendocrine system, which has a large impact on one’s moods and mood
regulation (Steiner, Dunn, & Born, 2003). The evidence from these studies support that gender differences
in mood disorders, such as depression, are not as prevalent pre-puberty as they are post-puberty when these
hormonal shifts are occurring and may lead to these affective differences in men and women (Kessler &
Walters, 1998).
Additional work has looked at gender differences in the influence that well-being, including both
affective and psychological, has on the physical and hormonal health outcomes of men and women. This
line of works has found that there may be distinctive patterns of health-related outcomes from well-being in
men and women, such that well-being leads to different outcomes in the male body versus female body
(Steptoe, Demakakos, de Oliveira, & Wardle, 2012). For example, for men, well-being is associated with a
smaller waist circumference, and women it led to fewer inflammatory markers in their body, yet both men
and women had improved lung function (Steptoe et al., 2012).
Broadly, researchers conclude that while there is substantial evidence that men and women’s
anatomy and physiology differ, the implications of this on the experience well-being is not well-established
(Savic-Berglund, 2010). So, while biological differences are commonly believed to be a contributing
factor, more work needs to be done to provide greater supporting evidence.
Reasons for Lack of Gender Differences in Overall Well-being
We note that it is important to explain why we might not expect gender differences in SWB due to
the number of large-scaled studies we reported with null effects. There is a line of research that proposes
why we should not expect many, if any, differences between men and women based on the gender
similarity hypothesis proposed by Hyde (2005). This hypothesis proposes that many gender differences are
extremely small, if not totally non-existent. Hyde (2005) proposes than men and women are more similar
than they are different. She bases this conclusion on a review of many meta-analyses on gender differences
across a wide array of outcomes and characteristics. In this review, she finds that most mean difference
effect sizes are small, if not non-significant, on the outcomes of interest. She states that these overly
endorsed claims harm men and women by propagating expectations of differences that can have
detrimental impact on the lives of men and women, and as such people should be wary of making these
conclusions (Hyde, 2005). We propose that it may not necessary be the case that these effects are inherently
small, but rather are potentially minimized by other psychological processes that contribute to a rather
static baseline of well-being and influence the evaluations one makes in determining their well-being
389
levels. These psychological processes are summarized in Table 7.
Table 7.
Explanations for Lack of Gender Differences in Subjective Well-being
Category Psychological/Physiological
Mechanisms
Posited Outcome
Return to Baseline Adaptation
Habituation
Men and women adapt to their respective
surroundings leading to little gender
differences in well-being overall.
Men and women are not impacted as greatly
by aspects of life that become habitual in
nature (e.g., inequality or stereotypes)
leading to little gender differences in wellbeing
overall.
Basis of Evaluation In-Group Social Comparisons Values
Men and women may not consider one
another part of their in-group and compare
they life to others of their same sex leading
to little gender differences in well-being
overall.
Men and women may value different aspects
of life such leading to little gender
differences in well-being overall.
Return to Baseline
Adaptation. Adaptation is another phenomenon difficult to address in our measurement of SWB
that may contribute to seemingly null effects. Adaptation, also labeled the hedonic treadmill (Brickman &
Campbell, 1971), is the theorized reason behind the lack of large, long-lasting influences of major life
events (e.g., loss of a job, marriage, winning the lottery) on a person’s levels of well-being (Luhmann,
Hofmann, Eid, & Lucas, 2012; Brickman & Campbell, 1971). More specifically, researchers have found
that despite major life events that intuitively one would suspect would have large, long-lasting impacts on
one’s well-being levels, it appears instead that individuals tend to adapt to their new-found situations and
return to their original baseline levels of well-being (Luhmann, Hofmann, Eid, & Lucas, 2012; Brickman &
Campbell, 1971). If men and women are not biologically predisposed to experience vastly different levels
of SWB, this idea may be one reason behind why we do not see consistent or persistent differences in
SWB between men and women in all samples we study. While in the moment stereotypes or restricted
resources may impact women more negatively, decreasing their levels of SWB, relatively quickly – due to
adaptation – women return to their baseline which may not be much different, if at all, from men’s baseline
levels of well-being.
Habituation. Habituation proposes that constant stimuli begin to fade into the background due to
an evolutionary benefit of protecting our limited cognitive resources (Helson, 1948; 1964). This applies to
the idea of well-being too, such that well-being is less dependent upon the desirability of the constant, everpresent
circumstances (e.g., stereotypes, inequalities), but are more so reflective of changes in the
important circumstances of life (Carver & Scheier, 1990). As such, once women become accustomed to life
circumstances, such as inequalities, these circumstances may end up having less of an influence on their
well-being levels. Thus, potentially diminishing differences between men and women in SWB that would
have been present had this state not become habitual in nature.
Basis of Evaluation
In-group social comparison. Another challenge of self-reported well-being measures is the
inability to determine the extent to which in-group versus out-group comparisons are being made. While
some samples may find no difference between men and women, this may be due to women’s in-group
comparisons being comprised of only other women. Thus, it may be likely that they do not perceive
390
themselves to be any worse off that other women, leading to relatively high levels of well-being. However,
in some samples (e.g., working samples) where we do see gender differences in SWB, women’s in-group
social comparison may include men too, and then comparatively, due to inequalities or social expectations,
they may have decreased levels of well-being from making this comparison. Unfortunately, current
measures of SWB do not include a way for people to report when these sort of in-group comparisons are
being made and how they go about defining their in-group members.
Values. Another critical issue that also needs to be considered in comparing the levels of SWB
between men and women is that they may derive happiness from different sources. There has been
substantial work on differences in what men and women value most in life and their sources of happiness.
Past research has suggested that men and women’s values differ (e.g., Beutel & Marini, 1995), which may
influence the degree to which different aspects of life impact their respective levels of SWB. Work by
Beutel and Marini (1995) found that women reported valuing the well-being of others and finding purpose
and meaning in life more than men and value materialism and competition less than men. More
specifically, some research has explored differences in perceived sources of happiness for men and women,
reporting some differences among the sexes. While men reported sports, sexual activity, being liked, and
having a quality social life significantly more influential on their happiness than women did. Women
reported helping others, being close to family, and being loved as significantly more influential on their
happiness levels than men (Crossley & Langdridge, 2005).
Some work has looked directly to differences between the sexes in terms of the influence of life
factors have on their subsequent happiness. For example, in a meta-analysis by Pinquart and Sörenson
(2001) found that income, education, and SES were more impactful on men’s well-being levels as
compared to women’s, and that social networks were more impactful on women’s well-being levels as
compared to men’s. Subsequently, women and men may go about basing their responses on SWB measures
on different value structures, subsequently nullifying differences. If measures instead left less up for
interpretation on what aspects of life one should be rating, or considering, in this evaluation, we may see
greater gender differences in SWB.
Future Directions
While work addressing the question of gender differences in well-being is not rare, there are several
limitations in current research that can be addressed by future work on this subject. As is true in most areas
of research, there is a concern that the literature is inundated with only results that are significant, and those
that are not significant are relegated to a “file-drawer” either literally or metaphorically (Rosenthal, 1979).
While this is by no means a new problem, or an issue only relevant to the study of gender differences in
well-being, it is an issue that should be paid particular attention to in an area of research most interested in
differences by the very nature of the question being asked. Results that do not find significant differences
should be equally valued if we are to have a balanced and complete perspective on this issue and
significant results should be replicated to increase confidence in these findings (Pashler & Harris, 2012;
Hyde, 2007).
Along these same lines, there is a need for further empirical work on specific theoretical reasons
proposed for why gender differences exist rather than simply relying on secondary analyses to answer this
question. Theory is critical in providing a foundation for research questions, and it is critical to then test the
theory in an empirical manner to further develop an understanding of gender differences in well-being. This
may include pinning two theoretical perspectives against one another in an attempt to empirically validate
one over the other as has been done some previously (e.g., Mason, 1995). Additionally, research that is
more causal in nature may be beneficial to further understand why and when environmental factors, such as
inequality, contribute to gender differences in well-being. This may be done by manipulating situations of
perceived inequality in a laboratory setting to provide some additional evidence of a cause and effect
relationship rather than relying exclusively on correlational-based theory.
Other methods may also be beneficial to incorporate further to develop our understanding of wellbeing
differences among the sexes such as longitudinal investigations. While presently there is work that
compares gender differences across age groups (e.g., Pinquart & Sörenson, 2001; Diener, & Suh, 1997),
variations in the magnitude of gender differences in well-being in these studies may be reflective of
generational differences rather than differences across the lifespan. Past research has also suggested that
longitudinal work may help to distinguish between the frequency by which men and women experience
positive and negative emotions versus the intensity that these emotions are experience by men and women
respectively (Diener, Sandvik, & Larsen, 1985). There may be differences in well-being patterns overtime
dependent upon whether one is interested in the frequency the emotions are experienced versus the
intensity by which they respond to the same or similar emotional stimuli. As such, understanding the
fluctuation across both the short-term and long-term using methods such as experience sampling method
391
will provide additional insights that are critical to further understand well-being across time and help
untangle the question of gender differences in well-being over time in ecological settings (Tay, Chan, &
Diener, 2014).
Additionally, integrating both person-centered (e.g., looking at differences among clusters of
individuals on outcomes) and variable-centered approaches in research on this subject may be beneficial to
provide further insight as to why there are gender differences in well-being for some samples and not
others. Integrating the adaption of a person-centric perspective on well-being will help to preserve the
integrity of the person overall in order to understand the way that they shape, feel about, and understand
their own well-being (Weiss & Rupp, 2011). This focus would emphasize the experience of the subjective
states and experiences at both a momentary level (e.g, positive and negative affect) as well as more
cumulative evaluations (e.g., life satisfaction). This would requires relying more heavily on both
quantitative and qualitative methods such as gathering the histories and narratives individuals create about
their lives.
In adopting these methods, we will likely have an increased understanding of gender’s relationship
to well-being and develop ways to enhance SWB for both men and women. Lyubomirsky (2001) proposed
that the greater understanding of why some people, or sexes in this case, are happier may provide the
foundation for interventions to increase happiness of the less happy group by drawing on the developable
traits, behaviors, and environmental factors of the happier group. Because happiness has been shown to
relate to and precede numerous important life outcomes (Lyubomirsky, King, & Diener, 2005), the ability to
do this could subsequently improve the long-term success of both men and women in numerous areas of
life.
Beyond understanding the causes of gender differences in well-being levels, it is also important to
further explore the subsequent repercussions of these differences. Substantial amounts of research have
examined the numerous positive outcomes that are believed to be a result of high SWB, but research has
failed to examine if these outcomes differ for men and women. This would be important for understanding
further the impact differences in well-being has on the lives of men and women. As such, we believe that
exploring the differential validities of SWB for the outcomes of men and women separately may be
beneficial to having a more complete picture of the impact of these differences in SWB.
Concluding Remarks
Despite the question’s popularity in research and the work that has already been done, there is still
substantial work that can, and should, continue on the subject in an effort to further our understanding of
gender and well-being. While the question of whether men and women differ in levels of well-being is a
seemingly straight-forward one, there are numerous complexities involved in answering it. First, it is
important to consider the different types, and components, of well-being as a construct. Second, it is
important to understand that depending on numerous biological, individual, and environmental factors the
difference in SWB may be more or less apparent. Third, one must consider the present limitations in the
research and act on the necessary future directions to provide further clarity and understanding. Thus, we
hope that taken together these considerations paint a vivid picture of the complex nature of a seemingly
simple question. Do men and women differ in levels of SWB? As cliché as it sounds, the answer appears to
be, at least for now, “it depends.”
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Race and Subjective Well-being: Critical Race Perspective and
Empirical Review of Key Predictors
By Hyung Chol Yoo, Arizona State University, Adam Y. Kim & Richard M. Lee, University of Minnesota,
Twin Cities
Citation
Yoo, H. C., Kim, A. Y., & Lee, R. M. (2018). Race and subjective well-being: Critical race perspective
and empirical review of key predictors. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being.
Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
The purpose of this chapter is to clarify what is currently known about subjective well-being (SWB) for
racial groups in the United States, with a focus on common racial struggles and resilience in people of
color. We organize the chapter by first summarizing the between-group and within-group studies of culture
and SWB. We then provide a Critical Race perspective on studying SWB across racial groups with
particular attention to how we define race, followed by a comprehensive review of empirical literature on
four common race and ethnic specific predictors related to SWB: racial-ethnic discrimination, racial-ethnic
identity, acculturation and enculturation, and racial-ethnic socialization. We conclude with suggestions for
future research to advance theory and methodology in the study of race and SWB.
Keywords: Race, Racism, Critical Race Theory, Subjective Well-being
Subjective well-being (SWB) describes how individuals feel and think about their own life (Diener,
2000). It has gained increased popularity in psychology, including growing interest and study across
cultures and nations (Diener, 2000; Diener, Oishi, & Lucas, 2003). In the United States, understanding how
race contributes to the experience of SWB seems pressing, as some of the major issues affecting minority
communities today are tightly linked to race (e.g., Deferred Action for Childhood Arrivals program repeal,
Charlottesville white supremacy march and murder of an anti-protester, anti-Muslim bans, Standing Rock,
Black Lives Matter, Flint water crisis). How is SWB defined and maintained in these communities? How
do they promote resilience and increased SWB in face of adversities? How is SWB shaped by history of
race and racism in the United States?
The purpose of this chapter is to clarify what is currently known about SWB for racial groups in
the US. We narrowly focus this review on race in the US as the construction of race informed by history
operates differently within and across nations (Omi & Winant, 2014). We approach our review from a
Critical Race theory perspective (Delgado & Stefancic, 2012), drawn from the interdisciplinary field of
Ethnic Studies (Banks & Banks, 2009; Hu-DeHart, 1993), in order to critically advance the study of race
and SWB. We organize the chapter by first briefly summarizing the between-group and within-group
studies of culture and SWB. Second, we provide an Ethnic Studies perspective on studying SWB across
racial groups with attention to how we define race, in particular. Third, we present a review of empirical
literature of four common race and ethnic specific predictors related to SWB, including racial-ethnic
discrimination, racial-ethnic identity, acculturation and enculturation, and racial-ethnic socialization.
Finally, we conclude by providing suggestions for future research to advance theory and methodology in
the study of race and SWB.
Between- and Within-Group Studies of Culture and SWB
Cross-cultural studies have primarily examined mean-level differences on SWB across many
different proxies for culture, including country, income, wealth and other economic factors, and between
individualistic and collectivistic societies (see Diener, 2000; Diener, Oishi, & Lucas, 2003; and Dolan,
Peasgood, & White, 2008; for more detailed review). Many interpretations are provided for these
differences including “tangible” resources (e.g., food, shelter), individual-level characteristics (e.g.,
approach and avoidance style, personality traits), measurement biases (e.g., self-serving biases), and broad
cultural values (mainly focused on individualism and collectivism) (Diener, 2012; Diener & Diener, 1995;
Kitayama, Markus, & Kurokawa, 2000; Suh, 2007). For instance, Dolan et al. (2008) reviewed economic
factors contributing to SWB and found evidence that poor health, separation, unemployment, and lack of
social contact are all strongly negatively associated with SWB. Diener et al. (2003) reported that
differences in mean levels of SWB appear due to objective factors like wealth, to norms dictating
appropriateness of feelings and importance of SWB, and to the relative approach versus avoidance
tendencies of societies.
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In particular, the role of individualistic and collectivistic values on thoughts, feelings, and
behaviors associated with SWB has been extensively studied (e.g., Fulmer et al., 2010; Oishi & Diener,
2001; Oishi, Krochik, & Akimoto, 2010; Suh, 2007; Uchida & Kitayama, 2009); including, feeling and
expressing positive emotions (Eid & Diener, 2001), differences in social support (Oishi & Schimmack,
2010), and differences in positivity (Diener, Scollon, Oishi, Dzokoto, & Suh, 2000). For instance, Diener
and Diener (1995) investigated 31 countries and found that self-esteem is less strongly correlated with
subjective well-being in those that were rated to be more collectivistic (e.g., East Asian) than in those rated
to be more individualistic (e.g., European American).
When more closely examining racial group differences in the US (i.e., Asian American, Pacific
Islander, Native American, African American, White, and Latinx) on SWB, there appear to be some group
differences. For instance, Oishi and Diener (2001) found that European Americans were significantly more
satisfied with their lives than Asian Americans. Crocker, Luhtanen, Blaine, and Broadnax (1994) found
differential effects on the relationship between collective self-esteem components (private, public,
membership, and identity) and well-being (personal self-esteem, life satisfaction, depression, and
hopelessness) of African American, White, and Asian American college students. Some studies more
broadly compare predictors and experience of SWB across White and “non-White” samples (e.g., Dush &
Amato, 2005; Seder & Oishi, 2009).
There is growing literature and debate on interpreting racial group differences in self-esteem.
Studies generally find African Americans tend to report higher levels of self-esteem than Whites. This has
led some authors to raise doubts about the validity of the internalization of stigma perspective for racial
minorities in the US (Gray-Little & Hafdahl, 2000). However, in a more thorough literature review of racial
differences in self-esteem (including Latinx, Asian American, and Native American), Twenge and Crocker
(2002) found levels of self-esteem differed widely between racial groups - varying by type of self-esteem
measured, year of data collection and age, sex composition, and SES of the sample. Given this cross-racial
group heterogeneity, they argued that future research should move away from asking why racial group
differences exist, and instead ask how SWB is constructed within these different racial groups.
Overall, there is a wide range of cultural differences in the experiences and predictors of SWB.
Causal interpretation of these differences, however, can be problematic for a number of reasons. For
instance, in their review of economic factors associated with SWB, Dolan et al. (2008) cautioned against
drawing firm conclusions about the causes of SWB. Their review identified contradictory evidence, a lack
of certainty on the direction of causality, and concerns regarding the impact on findings of potentially
unobserved variables.
Also, the level of cultural analysis (e.g., national, socioeconomic, income/wealth, race, ethnicity,
general cultural values, etc.) is often either unclear or terms are used interchangeably in these studies. This
is related in part to the complexity and challenge in finding agreed upon, operationalized, and differentiated
meaning in terms broadly captured by culture (Giraldeau, Lefebvre, & Morand-Ferron, 2007). Still, this
leads to a challenge in drawing any meaningful conclusion regarding cross-cultural differences on SWB.
For instance, there is growing research on the role of broad cultural values on SWB. Many cross-cultural
studies compare SWB between individualistic and collectivistic societies, often interchangeably using
North American and East Asian countries, respectively. Not only does this hinge on outdated stereotypes
(Matsumoto, 1999; Takano & Osaka, 1999), but it also ignores the evidence of greater heterogeneity within
than between these national (rather than cultural) groups (Oyserman, Coon, & Kemmelmeier, 2002). It
further limits our understanding of culture to individualism and collectivism (Hofstede’s (2001) cultural
dimensions additionally include instrumental and expressive, uncertainty avoidance and tolerance, for
instance).
In addition, the group comparison in these studies often overemphasizes cross-cultural differences
in SWB, ignoring heterogeneity of cultural and racial groups. For instance, although there are many studies
that examine SWB across nations, there are few that examine differences within nations, including racial
group differences within the US. An exception is a study conducted by Tay and colleagues (2014) that
found racial differences in well-being among African American, White, Latinx, and Asian American in
their workplace and in general (Tay, Ng, Kuykendall, & Diener, 2014). These racial differences in wellbeing
measures, however, were not consistent. Further, studies that do assess SWB within nations often
over-represent some racial groups and group comparisons (Whites, White and Asian, White and Black),
while other groups and respective comparisons are under-represented (e.g., Native American, Latinx).
Finally, and most importantly, cross-cultural comparisons ignore the possibility that individual
interpretations of SWB are unique to each culture, making it difficult to study across cultures. Cultural and
indigenous psychology emphasize how all psychological phenomena (like SWB) are embedded within a
particular cultural setting based on unique values, traditions, and history (Shweder, 1991). Further they are
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critical of the imposed etic research approach where culture-specific ideas (such as SWB) may be wrongly
imposed on and generalized to other cultures (Berry, 1989; Pike, 1967). Lastly, White and WEIRD samples
(Western, Educated, Industrialized, Rich, and Democratic) are overly represented in viewpoint, cultural
biases, and generalizability (Henrich, Heine, & Norenzayan, 2010). We therefore focus our review on the
experience of SWB for separate racial minority groups and evaluate their common, uniquely racialized
risks and resilience. Our focus is further framed by an analytical lens offered by Ethnic Studies that
emphasizes complexity and agency of racialized groups.
Ethnic Studies and Critical Race Perspectives on SWB
Inspired by the 1960s U.S. Civil Rights movement, a joint coalition of Black, Latinx, Asian
American, and Native American student groups led one of the longest student strikes in U.S. history in 1969
to demand fundamental changes in higher education (Banks & Banks, 2009). They challenged the
prevailing academic power structure and the Eurocentric curricula of colleges and universities. They
demanded for more scholarly programs, faculty, and staff who focused on the under-represented and understudied
histories and experiences of diverse racial minority groups, which led to the birth of Ethnic Studies
(Maeda, 2009).
There are many ideas and debates of what Ethnic Studies is or should be, and conceptualizations
can differ from campus to campus and change over time (Hu-DeHart, 1993). What is clear in its
scholarship, however, is the specific or comparative focus on marginalized groups in America that often
lacked equity, representation, and privilege. In particular, the field continually documents and emphasizes
the self-determination, autonomy, and empowerment of racial minority groups, often in resistance and
opposition to structural systems of oppression, colonialism, and inequity.
Today, Ethnic Studies pushes race-related scholarship, including more theories and methods to
examine relations and intersections of power in race, class, gender, and sexuality (Hu-DeHart, 1993). It
further expands across fields, level of education including K-12, and broadens the framework to include the
effects of migration, assimilation, and accommodation of people moving between nations and borders. It
considers new spaces, community, and identity forged by migrants across national boundaries (Basch,
Glick-Schiller, & Szanton-Blanc, 1994).
Drawing on these principles, Critical Race theory can be helpful in clarifying and framing how
race should be understood in the study of SWB. This theory developed in the early 1980s in response to the
failure of critical legal studies to adequately address the impact of race and racism in the US jurisprudence.
Legal scholars, including Derrick Bell, Richard Delgado, and Alan Freeman, initially helped contribute to
advancing this theory. They critiqued the system of racial oppression and emphasized need for agency and
activism; ultimately, the end goal focused on structural change and social justice (Bell, 1992; Delgado &
Stafancic, 2012). Critical Race theory has now expanded across disciplines including history, women’s
studies, education, psychology, sociology, and political science. Central tenets of Critical Race theory
include the significance of racism, racialization, intersectionality, and agency.
Racism. Race is a socio-political and legal construct based on perceived physical differences (e.g.,
skin color, facial features, and hair type), rather than inherent biological differences. It differs from
ethnicity, which emphasizes the traditions, values, language, and history attached to a particular social
group (Cokley, 2007). More importantly, race and racial differences were created and maintained to
promote power and privilege attached to “whiteness.” Whiteness is a racial ideology that is interchangeably
used with what is normal, beautiful, and American (Devos & Banaji, 2005; Sue, 2005). It uses false
narratives of biological and “cultural” inferiority of “non-Whites” to rationalize genocide, slavery,
exclusion, and colonization of Black, Native, Pacific Islander, Latinx, and Asian Americans in the past
(Miller & Garran, 2008; Takaki, 1993). Racism is systemic and maintains the racial status quo on an
interpersonal, cultural, and institutional level, always seeking white supremacy and exclusion (Jones,
1997). Today, racial inequities continually persist as people of color are systematically disadvantaged
compared to Whites across multiple domains of life, including health, education, work, and legal systems
(Alvarez, Liang, & Neville, 2016; Lui, Robles, Leondar-Wright, Brewer & Adamson, 2006). Therefore,
race and racism—a system of privilege and oppression based on racial hierarchy—are inextricably linked
today and throughout history. Relevant to the study of SWB, racism raises questions, for instance, who gets
to ask the questions? From what vantage point is the research conducted? Are studies of SWB comparably
represented across racial groups? What groups are left out?
Racialization. Science has now debunked any notion of meaningful and distinct racial group
differences, finding more within-group than between-group variations in phenotypic and biological
characteristics (Betancourt & López, 1993; Carter & Pieterse, 2005; Smedley & Smedley, 2005).
Nevertheless, invariably conceptualized within historical contexts, individuals are racialized as race shapes
group membership, meaning, experiences, and treatment of others (Helms, 1990; Helms & Cook, 1999;
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Omi & Winant, 2014). Further, the meaning and classification of race and racial groups is ever-changing,
continually deconstructing and reconstructing to reinforce a power structure of systemic privilege that
benefits Whites (Omi & Winant, 2014). For instance, the U.S. Supreme Court used varying definitions of
race (e.g., biological vs. social) to deny citizenship to Asian Americans (e.g., regarding cases Takao Ozawa
v. US and Bhagat Singh Thind v. US; López, 2006). Multiracials were classified and treated as non-Whites
based on racist, legislative policies associated with the “one-drop rule” in efforts to maintain “racial purity”
(Root, 2003). Irish, Italian, and Jewish immigrants were once considered racial “others” (non-White) and
subjected to blatant forms of racism (Guglielmo & Salerno, 2003). However, their experiences were
different compared to other racial minority groups in the US given their phenotypic proximity to whiteness.
Further, these ethnic groups were later assimilated as part of whiteness. European immigrants of second
and later generations subsequently had more opportunity to either choose or not choose to integrate their
ethnicity into their daily lives without penalty (e.g., celebration of St. Patrick’s Day), a privilege not
afforded to people of color (Gans, 1979). With the end of World War II and the beginning of the U.S. Civil
Rights movement in the 1960s, expressions of racism grew from “old-fashioned” blatant, overt, and
intentional expressions of white racial superiority to include “modern” color-blind, subtle, ambiguous, and
unintentional reinforcement of the racial hierarchy (Devine, 1989; Dovidio & Gaertner, 1986; Plous, 2003;
Sue, 2005). Relevant to the study of SWB, racialization raises questions such as what are the unique
racialized experiences of people of color that shape their experiences of SWB? How do roles of power and
privilege, including structural inequities, influence how SWB is studied or interpreted with racial minority
groups?
Intersectionality. Intersectionality highlights that oppressive systems–including but not limited to
racism, sexism, classism, heterosexism, xenophobia, and ableism–are interconnected and not merely
hierarchical or additive; as such, they should not be examined separately (Crenshaw, 1991). As a
framework for understanding how multiple interlocking systems of oppression and privilege operate at a
structural level, it has now been applied to understand individual-level processes and outcomes (Cole,
2009). Illustrating this framework, Le Espiritu (2008) uses an intersectional lens to analyze how roles of
race, class, gender, and sexuality of Asian Americans have been used throughout US history to maintain
racial hierarchy of Whites and to justify structural racism against Asian Americans. In particular, Asian
men and women are often cast in contrasting images to help define and maintain White male
heteronormativity. Over the course of U.S. history, Asian men have been racialized as both hypersexual
and more recently asexual, while Asian women have been viewed as both masculine and more recently
super-feminine (Le Espiritu, 2008; Sue, Bucceri, Lin, Nadal, & Torino, 2009; Takaki, 1989). Relevant to
the study of SWB, intersectionality raises questions about how multiple identities are categorized and who
is included. How do power and privilege shape multiple identities, their intersectionality, and what is their
link to SWB?
Agency. Racism has been both intentionally and unintentionally violent towards racial minority
groups both past and present (Alvarez et al., 2016; Lui et al., 2006). It is maintained by false beliefs in a
natural order of biological and cultural differences, as Whites are assumed superior to people of color
(Smedley & Smedley, 2005; Takaki, 1993). Despite the injustice, people of color have protested, resisted,
and contributed to building a stronger, more equitable society in the US (Takaki, 1993). Critical Race
points out that people of color are active agents creating their own personal narratives and directing their
present and future lives (Lee, Kim, & Zhou, 2016). This theory proposes practices of counter-storytelling to
reveal and contest the identity-infused base of everyday society. Relevant to the study of SWB, agency
raises questions about whether cultural deficit models (including stereotype consistent models) are used to
interpret racial differences. Do SWB studies include vantage points based on the unique perspectives and
voices of racial minority groups? For people of color, what are unique forms of racialized resilience and
their relation to SWB? How do critical consciousness and social activism relate to SWB?
Empirical Review of Race- and Ethnicity-Specific
Predictors of SWB
Operationalized Definitions
There is a wide range of meaning in race and SWB in the psychological literature. Historically,
scholars have differentiated race and ethnicity: race emphasizes a socio-political and legal construct based
on perceived physical differences (e.g., skin color, facial features, and hair type) and ethnicity emphasizes
the traditions, values, language, and history attached to a particular social group (Cokley, 2007). However,
the use of these terms is often based on social convention rather than empirical definition. For instance,
African American is typically thought of as racial while Latinx is typically thought of as ethnic - regardless
of the context of the research question (Umaña-Taylor et al., 2014). Further, operationalization and
measurement of racial and ethnic constructs often overlap such that they can be difficult to distinguish
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(Cokley, 2007). Thus, we follow recent arguments for using the term “racial-ethnic” to capture this broad
construct, and when possible, we use terms for specific aspects of each (Hughes et al., 2006; UmañaTaylor
et al., 2014). Similarly, there was a wide range of interpretation in operationally defining well-being,
often using a broad collection of “positive” outcome measures including self-esteem, happiness, positive
self-perceptions, life satisfaction, and positive and negative affect (e.g., Pascoe & Richman, 2009; Smith &
Silva, 2011). Given many definitions of well-being, we focus our review on studies that used “positive”
psychological adjustment outcomes such as those listed above. We also do not focus on broader negative
outcome or mental distress (e.g., depression, anxiety, stress) measures in our review as they are extensively
reviewed elsewhere (e.g., Lee & Ahn, 2011, 2012, 2013). Finally, from a Critical Race perspective,
interpreting racial group differences may lead to essentializing racial groups or worse, to reinforcing racist
conceptions of human behavior (Zuckerman, 1990). Emphasizing agency in people of color as they create
personal narratives during both struggles and resistance, we focus our review on some of the most
commonly studied racialized psychological risks and resilience that may affect their experience of SWB.
These include: racial-ethnic discrimination, racial-ethnic identity, acculturation and enculturation, and
racial-ethnic socialization. Our review provides a broad and brief summary of related definitions and
theories, empirical review as it relates to SWB, and limitations for each construct.
Racial-Ethnic Discrimination
Racial-ethnic discrimination (RED) refers to the biased behavior and treatment of individuals
based on their racial or ethnic background (Dovidio & Gaertner, 2010; Ong, Burrow, Fuller-Rowell, Ja, &
Sue, 2013; Paradies, 2006). It is one of many ways in which racism occurs at the individual level, along
with racial stereotype that emphasizes cognitive overgeneralizations and racial prejudice that emphasizes
emotions attached to the overgeneralization (Fiske, 1998; Paradies, 2006). Racism also functions on a
cultural and institutional level: cultural, institutional, and legal practices operate and are structured in ways
to benefit the dominant group (Jones, 1997). Although many operationalized definitions and measures of
racism are provided in the literature (Essed, 1991; Jones, 1997; Harrell, 2000), most emphasize the
centrality of power and privilege attached to whiteness. The experiences of RED for people of color
consequently are often chronic and wide ranging, including direct or indirect, intentional or unintentional,
and subtle or blatant, to name a few (Harrell, 2000). The empirical work on the experience and impact of
RED for people of color started after the 1960s U.S. Civil Rights movement (Winston, 2004), as
psychology shifted from predominantly studying the perpetrator’s experience of RED to including the
target’s experience as well (see Fiske, 1998, for review). There is now a large body of research that focuses
on the perceptions and psychological correlates of RED for people of color.
RED has been theoretically and empirically linked to mental health and SWB for people of color.
According to the racism-related stress theory, a popular and often cited framework in this area, perception
and experience of racism can be stressful, taxing an individual’s coping resources and consequently leading
to higher distress and lower well-being (Harrell, 2000). This theory has been largely supported by empirical
studies as multiple dimensions and domains of racism have been linked to a wide range of psychological
distress and SWB outcomes. Although studied less frequently than maladjustment outcomes (Lee & Ahn,
2011, 2012, 2013), RED has been linked to a lower SWB (including lower self-esteem, life satisfaction,
control and mastery, positive affect, and general well-being) for Asian, Latinx, and African heritage
samples living the US and abroad. Similar results were found in one of the largest meta-analyses on the
subject to date (293 studies from 333 articles) by Paradies et al. (2015) for African American (37%), Latinx
(19%), Asian American (9%), and Native Americans, Arab Americans, or international students (less than
1% combined). Pieterse and colleagues (2012) also found this link in their meta-analyses focused on the
SWB of African Americans. Finally, the RED-SWB link for people of color seems to vary considerably by
the type of racism (e.g., subtle or blatant, Crocker, Voelkl, Testa, & Major, 1991; personal or group, Taylor,
Wright, Moghaddam, & Lalonde, 1990), as well as a host of ecological factors (e.g., identity, family,
school/work, society) (Bronfenbrenner, 1979; García Coll et al., 1996).
From a Critical Race perspective, there are few limitations and gaps that if addressed could
strengthen this area of research. Most of the sample and related measures of RED focused on African
Americans, and less was clear on the unique socio-political and historical circumstances of RED that
shaped the SWB of other racial minorities, particularly Native Americans. Also, despite the theoretical
importance of structural racism, most measures and research in this area focus on individual-level
perceptions and outcomes of racism. More research is needed to evaluate the impact of objective cultural
and institutional forms of racism, including anti-race policies. For instance, Gee (2002) found individual,
self-perceived racism and institutional racism of segregation and redlining differentially related to health
outcomes in a large community sample of Chinese Americans.
Racial-Ethnic Identity
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Racial-ethnic identity (REI) is a broad construct associated with meaning, behaviors, and
attachment towards a particular racial or ethnic group, although efforts to differentiate between the two are
made (Helms, 2007). Ethnic identity is defined as the subjective sense of ethnic group membership that
includes self-labeling, sense of belonging, knowledge, attitude, and group participation (Phinney, 1996).
Racial identity is defined as the collective identity of any group of people socialized to think of themselves
as a racial group (Helms & Cook, 1999). When researchers are interested in cultural beliefs, values, and
behaviors on an individual, Cokley (2007) encourages the study of ethnic identity; when researchers are
interested in response to an oppressive and highly racialized society, Cokley (2007) recommends the study
of racial identity. Still, Umaña-Taylor et al. (2014) argued that the distinction between the ethnic and racial
phrasing seems more artificial than intentional, and therefore a meta construct comprising both racial and
ethnic identity should be used. REI is a multidimensional construct that taps into a variety of dimensions
including, but not limited to, public regard, private regard, salience, pride, resolution, search, and
participation (Lee & Yoo, 2004; Phinney, 1992; Roberts et al., 1999; Sellers, Rowley, Chavous, Shelton, &
Smith, 1997; Umaña-Taylor, Yazedjian, & Bámaca-Gómez, 2004). Most common theories used to study
REI and SWB include developmental models (Phinney, 1990), social identity theory (Tajfel & Turner,
1979), and schema models (Helms, 1990).
REI is believed to be important to the development and resilience of racial minorities in the US, a
proposition supported by numerous empirical studies. In a meta-analysis on the link between REI and
mental health for people of color in North America, Smith and Silva (2011) found a positive relation
between REI and general well-being (r=.19; k=32), and mental health more broadly defined ( r=.17; k=184).
This finding is supported by Rivas-Drake et al.’s (2014) meta-analysis that found a positive relation
between REI and well-being (r=.20; k=8), and positive adjustment more broadly ( r=.26; k=27), including
positive social functioning (6 studies), self-esteem (21 studies), and well-being (8 studies). Although fewer
studies focus on “positive” outcomes in comparison to “negative” outcomes, REI seems comparably
important to the SWB of people of color. Further, these findings held similarly across racial minority
groups (i.e., African, Asian, Latinx, Native) in both reviews; one limitation is that half of the 51 sample
studies focused on African Americans, roughly 15% on Asian Americans and Latinx, and only 6% on
Native Americans (Rivas-Drake et al., 2014). Finally, although there is a wide range of racial and ethnic
identity measures (Cokley, 2007), most studies reviewed here relied on the Multi-group Ethnic Identity
Measure (MEIM; Phinney, 1992) and the Multidimensional Inventory of Black Identity (MIBI; Sellers et
al., 1997).
From a Critical Race perspective, there are few limitations and gaps that if addressed could
strengthen this area of research. Although there are a large number of studies that focused on African
Americans, there are fewer that focused on other racial minority groups, particularly Native Americans.
Consequently, little is known about the effects of REI on SWB for Native Americans, particularly the
unique meaning attached to REI based on values, resilience, and history. Furthermore, there are limited
measures of REI that focuses on uniquely racialized experiences of specific racial minority groups
grounded in their history and interlocking oppression. An exception is the number of Black measures that
consider these larger historic and system factors, including the MIBI (Sellers et al., 1997) that measures the
salience of identity; the centrality of the identity; the ideology associated with the identity (including
subscales: Nationalist, Assimilation, Minority, and Humanist); and the regard in which the person holds
African Americans (including subscales: Private Regard and Public Regard).
Acculturation and Enculturation
Acculturation is a broad term that involves the process of one cultural group coming in contact with
another cultural group and the associated change involved (Redfield, Linton, & Herskovits, 1936).
However, in the field of psychology, for racial minorities and immigrants, acculturation is most often
viewed as the process of adapting and learning about the dominant, mainstream culture. Enculturation, in
contrast, is the process of retaining and learning about one’s culture of origin (Yoon et al., 2013). The
literature long debated whether the process and adaptive outcome of psychological acculturation was either
unidimensional (i.e., individual reject their heritage culture to adapt to the host culture) or bidimensional
(individuals reject/retain their heritage culture while also rejecting/retaining their host culture). Current
evidence indicates that acculturation is bidimensional (Flannery, Reise, & Yu, 2001; Ryder, Alden, &
Paulhus, 2000). Berry and colleagues further theorized and empirically supported four acculturation
strategies that individuals engage in while negotiating between two cultures (Berry, 1997; Sam & Berry,
2010). They include assimilation (rejecting the heritage culture, adopting the host culture), integration
(retaining the heritage culture, adopting the host culture), separation (retaining the heritage culture,
rejecting the host culture), and marginalization (rejecting both the heritage and the host cultures). These
strategies neither represent the totality of acculturation strategies, nor are they all equally valid across
groups (for a more thorough review of the acculturation literature, see: Schwartz, Unger, Zamboanga, &
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Szapocznik, 2010).
Acculturation and enculturation have been repeatedly linked with positive mental health outcomes.
Yoon et al. (2013) examined unilinear measures of acculturation and enculturation, along with bilinear
measures of acculturation in a meta-analysis of 325 individual studies. Unilinear measures of acculturation
were unrelated to positive mental health, while bilinear measures of acculturation were positively related to
positive mental health (r=.18; k=42). Further analyses found that only the integration strategy was related
to positive mental health (r=.10; k=10), and that positive mental health was significantly better for the
integration strategy than assimilation (d=.33; k=9) and marginalization (d=.92; k=9). Lastly, enculturation
was positively related to positive mental health (r=.14; k=57). These findings are similar to Nguyen and
Benet-Martínez’s (2013) meta-analysis that suggested a positive relation between biculturalism (similar to
the integration strategy) and psychological adjustment (high self-esteem and low anxiety; r=.11; k=52).
Although these studies were conducted with different racial minority groups, no significant or meaningful
group differences were found between acculturation/enculturation and SWB (e.g., Yoon et al., 2013).
Furthermore, Latinx and Asian American populations were studied more often than African Americans and
other minority groups (e.g., Middle-Eastern/Arab Americans).
Acculturation theory has made advances over the last few decades, such as the incorporation of
bilinearity and an increased emphasis on context. Nevertheless, from a Critical Race perspective,
limitations and gaps exist in the literature. While integration of two cultures is assumed to be most adaptive
(Berry, 1997), it can be complicated and context dependent (e.g., proportion of similar racial in-group
members in the community) (Nguyen and Benet-Martínez, 2013). Furthermore, future research should
examine beyond individual-level factors (e.g., personality) that shape the relationship between
acculturation/enculturation and SWB, focusing on broader social context and institutional factors (e.g.,
redlining, segregation, race-related policies). Solely focusing on an individual’s acculturation strategies in
relation to mental health and SWB can place undue responsibility and blame on individuals (Yoon et al.,
2013).
Racial-Ethnic Socialization
In psychological and developmental literature, parental racial-ethnic socialization (RES) generally
refers to the transmission of information from adults to children regarding race and ethnicity (Hughes et al.,
2006). While the two aspects of “racial” (i.e., tapping into the racialized experiences of people of color)
and “ethnic” (i.e., tapping into the dissemination of cultural knowledge) parental socialization have been
well-studied for African American youth and families (Priest et al., 2014), scholars have only more
recently begun to differentiate between racial and ethnic socialization processes for other racial minority
families (Juang, Shen, Kim, & Wang, 2016). Racial socialization refers to the ways in which parents teach
their children about the meaning that is associated with being from a certain race, for example, when one’s
racial group may be devalued in society, preparing children for challenges due to stereotyping and racism.
Ethnic socialization, in contrast, refers to the preservation and transmission of cultural values, practices,
traditions, language, and history. Hughes and Chen’s (1997) most popular racial-ethnic socialization model
and measure comprise of three dimensions that collectively describe the transmission of information
regarding race and ethnicity. Preparation for bias emphasizes discussions about racism and how to cope
with it. Promotion of mistrust emphasizes warning about interactions with racial out-group members.
Cultural socialization emphasizes messages about the history, values, and pride of one’s own racial and
ethnic groups. Alternative terminologies have also been used for these RES strategies (Smith, Jacobson, &
Juarez, 2011; Stevenson, Cameron, Herrero-Taylor, & Davis, 2002), which further complicates
understanding and comparison of results between studies.
Research in this area emphasizes the importance of RES in developing SWB and preparing
children to cope with barriers and inequalities present in American society (Hughes et al., 2006). Empirical
studies, however, suggest the link between RES and SWB may be more complicated. It has been found to
vary across a wide range of factors including the selected dimensions of RES and SWB, racial groups,
agents of RES (e.g., parents, peers, mentors), and child characteristics (e.g., age, gender, skin color)
(Hughes et al., 2006; Priest et al., 2014; Telzer & Vazquez Garcia, 2009). For instance, depending on
domains of SWB measured, Constantine and Blackmon (2002) reported preparation for bias and cultural
socialization were associated with higher family self-esteem, cultural socialization was associated with
higher peer self-esteem, and mainstream socialization was associated with lower school self-esteem. Recent
studies also found differential effects of RES dimensions on well-being for people of color. Cultural
socialization for instance is generally positively related to well-being (Bynum, Burton, & Best, 2007; Juang
et al., 2016; McHale et al., 2006; Rivas-Drake, 2011). Interestingly, preparation for bias seems to have a
curvilinear relationship to adjustment, with low and high levels relating to poor adjustment and moderate
levels relating to positive adjustment (Harris-Britt, Valrie, Kurtz-Costes, & Rowley, 2007; Seol, Yoo, Lee,
403
Park, & Kyeong, 2016). In other words, too little or too much discussion about racial bias may relate to
poor well-being with moderate amounts being most adaptive.
There are several gaps and limitations in this research area. There is an inconsistent use of
terminology referring to racial and ethnic socialization messages and behaviors. For instance, often “racial
socialization” is used almost exclusively with African Americans, while “ethnic and cultural socialization”
is used more often with Latinx and Asian Americans (Hughes et al., 2006). The inconsistent use of different
terms and definitions make it challenging for researchers to tease apart specific psychological effects and
integrate findings from past research. RES is also extensively studied and measured with African
Americans, while less attention is given to other racial minority groups (Priest et al., 2014). Finally, more
studies are needed to examine the multiple social and environmental factors (e.g., family, school,
neighborhood) and multiple influential agents (e.g., parents, teachers, peers, online) that may influence
RES and its relationship to SWB.
Conclusion and Recommendation for Future Research
Our review of the race and SWB literature (focusing on key predictors, racial-ethnic
discrimination, racial-ethnic identity, acculturation and enculturation, and racial-ethnic socialization)
highlights both the importance and challenges of studying this topic. Although at times, racial groups were
compared with each other (e.g., comparing Latinx and Asian immigrants’ experience of acculturation), the
majority of these studies focused on a specific racial minority group. Even though this literature is smaller
in comparison to that of key predictors related to negative mental health outcomes (see, Lee & Ahn, 2012,
2013), our review finds that these racial risks and resilience are important to the SWB of people of color.
Furthermore, by going beyond simple racial group comparison–that may further reinforce stereotypes of
racial minority groups living in an oppressive system of racism (Zuckerman, 1990)–these studies illustrate
that the contribution of race to SWB is complicated and there are many important, uniquely racialized risks
and resilience that are multidimensional. We conclude our review by providing suggestions for future
research to advance theory and methodology in the study of race and SWB. Grounded in Critical Race
theory, they focus on the significance of racism, racialization, intersectionality, and agency.
Significance of Racism
Given the system of racism that privileges Whites, our review narrowly focused on the racialized
risks and resilience of racial minorities living in the US. That said, there were racial minority groups that
were over-represented in some areas and under-represented in others. Research that focuses on “race”
(including study of racial-ethnic discrimination, racial-ethnic identity, and racial-ethnic socialization) was
conducted more frequently with African Americans while focus on “ethnicity” (including
acculturation/enculturation) was studied more frequently with Latinx and Asian Americans. Native
Americans, multiracials, and other marginalized minority groups (e.g., Arab Americans) were largely
absent in this literature. Together, our review draws attention to these understudied groups and the
accompanying stereotyped assumptions of significance in topic to specific racial minority groups (e.g.,
importance of race to primarily African Americans or ethnicity to Asian Americans or Latinx) that should
be avoided.
Also, operationalization and measurement of racial and ethnic constructs often overlap, making it
difficult to distinguish between them (Cokley, 2007) and easy to conflate results in regard to SWB. For
instance, the same measures of identity and socialization may be defined as racial identity or racial
socialization if studied with African Americans, but ethnic identity or ethnic socialization if studied with
Latinx or Asian Americans (Juang et al., 2016; Umaña-Taylor et al., 2014). Therefore, research questions,
measures, and sample selection should be based on whether researchers are interested in ethnic-related
constructs that emphasize cultural beliefs, values, and behaviors or race-related constructs that emphasize
response to an oppressive and highly racialized society (Cokley, 2007). Hence, a study might use a sample
of Asian Americans when studying effects of racism-related stress, but specific Asian ethnic groups (e.g.,
Filipino American, Vietnamese, Asian Indian) when studying effects of acculturation gap. Similarly,
operationalization and measurement of well-being was not consistent in this literature, often relying on a
collection of “positive” psychological adjustment outcomes (e.g., self-esteem, positive affect). There is
debate about whether there is a meaningful and measurable difference between SWB and psychological
well-being (Chen, Jing, Hayes, & Lee, 2013); more importantly, few studies focused on understanding
factor structure and invariance of SWB across racial groups or developing new theories and measures of
SWB based on distinct racialized history and experiences of particular racial minority groups.
Finally, there are limited studies that investigate how the relationship between race-related
risks/resilience and SWB is influenced by system-level factors (e.g., family, community, state). Most
studies focused on individual-level factors (e.g., personality, coping strategy). Interestingly, many theories
in this area of research (Bronfenbrenner, 1979; Garcia-Coll et al., 1996; Harrell, 2000; Phinney, 1990)
404
already emphasize the role of community and larger system factors (e.g., anti-race policies) on the
individual. Incorporation of system-level factors in this area of research is needed to further understand
how individuals and structures of oppression interact on SWB. Also, more studies are needed in
understanding how race and SWB link relate to activism and ways that individuals engage in transforming
a racist society (Klar & Kasser, 2009).
Significance of Racialization
Racial groups are distinctly categorized and their unique process of racialization leads to different
trajectories in maintaining white racism (Omi & Winant, 2014). For instance, Asian Americans are
simultaneously viewed as hard-working (i.e., model minority) but un-American (i.e., perpetual foreigner);
in contrast, African Americans are viewed as lazy and aggressive but more American (Kim, 1999). This
calls for more attention to studies focusing on uniquely racialized experience of each racial minority group,
many of which were missing across the reviewed risks and resilience factors. Research on race and SWB
should also provide more relevant, historical, and socio-political context of race-specific constructs (Lee et
al., 2016). Also, absent from the literature were many other marginalized racial minority groups (e.g.,
multiracials, Arab Americans) and their unique racialization processes. For example, Shih and Sanchez
(2009) point out that studies on multiracials in psychology often rely on a cultural-deficit view, despite the
many ways they successfully navigate between multiple racial identities and racism (Yoo, Jackson,
Guevarra, Miller, & Harrington, 2016). Lastly, as racism is ever-evolving to maintain power and privilege
attached to whiteness, new roles of migration shaped by colonialism and imperialism need to be examined.
For instance, studies often operationalize migration histories in terms of acculturation, generational
differences, or immigration status, failing to account for alternative migration histories including
transnationalism and diaspora (Huber, 2010; Lee et al., 2016).
Significance of Intersectionality
Research on the link between race and SWB would benefit from a broader framework that
examines multiple and intersecting forms of oppression and identities (Cole, 2009; Crenshaw, 1991).
Intersectionality is a lens that critique how multiple social systems interlock to produce and sustain
complex inequalities (Crenshaw, 1991). In psychology, there is a growing interest and body of work using
intersectionality lens to examine how multiple identities is associated with a wide range of psychological
outcomes; although there is growing concern that psychological outcomes of multiple social identities are
being examined without critiquing systems of inequality or ways in which oppression is challenged
(Moradi, 2016; Shin et al., 2017). Other scholars have examined unique experiences of intersecting
multiple identities and how they adaptively cope with discrimination. For instance, Seaton, Caldwell,
Sellers, and Jackson (2010) examined how combinations of ethnicity, gender, and age moderated the
relationship between perceived discrimination and psychological well-being (depressive symptoms, selfesteem,
and life satisfaction) in a nationally representative sample of African American and Caribbean
Black adolescents. Szymanski and Lewis (2016) applied intersectionality framework to study how African
American women in an institution of higher education cope with gendered racism. There is also a growing
number of empirically validated measures of unique experiences across multiple intersecting identities and
oppression, such as the LGBT People of Color Microaggressions Scale (Balsam, Molina, Beadnell, Simoni,
& Walters, 2011), Gendered Racial Microaggressions Scale for Black women (Lewis & Neville, 2015),
and Foreigner Objectification Scale (Armenta, Lee, Pituc, Jung, Park, et al., 2013). Examining intersections
of race, class, gender, and/or sexuality on SWB may also require methods that capture more nuanced
relationships, including qualitative or mixed-method designs.
Significance of Agency
Critical Race theory emphasizes the role of people of color as active agents creating their own
personal narratives within an interlocking, structural system of oppressions. The practice of counterstorytelling
is encouraged to reveal and contest the identity-infused base of everyday society. Huber (2010),
for example, uses the counter-storytelling method to explore intersectionality of race, gender, and
migration on the educational experiences of undocumented Chicana college students. In addition,
community-based participatory research designs (Minkler & Wallerstein, 2011) involve community
members as part of the research team to help inform the study questions, designs, interpretation, and
dissemination of research. This design allows for self-determination and safeguards against the imposition
of dominant narratives. For instance, Okazaki, Kassem, and Tu (2014) argued how community-based
participatory research with Asian Americans can counter the homogenized portrait of Asian American
communities by disaggregating populations, increasing cultural competence in service providers,
improving mental health literacy, and decreasing stigma.
Final Thoughts
405
Our review of race and SWB from a Critical Race perspective illustrates the significant and
dynamic relationships among unique racial challenges, racial resilience, and SWB of people of color. It is
important to remember that this relationship is situated within the broader system of racism, as advantages
attached to whiteness and disadvantages attached to being a person of color manifests on individual,
cultural, and institutional levels (Harrell, 2000; Jones, 1997). Today, racial inequities continually persist as
people of color are systematically disadvantaged compared to Whites across multiple domains of life,
including health, education, work, and the legal system (Alvarez et al., 2016; Lui et al., 2006). Research
and policies that promote SWB for racial minority groups should also emphasize the need to dismantle
these systems of interlocking oppression. However, the burden of responsibility in deconstructing racism
should not only weigh on people of color. Although not reviewed here, there is a simultaneously growing
field of Critical White studies (Delgado & Stefancic, 1997) that examines how to deconstruct roles of
power and privilege attached to whiteness by examining its mechanisms (e.g., color-blind racial attitude;
Neville, Lilly, Duran, Lee, & Browne, 2000), evaluating emotional and behavioral costs of White racism
(Spanierman & Heppner, 2004), developing critical consciousness, and helping deconstruct systems of
interlocking oppression related to race, class, gender, and sexuality (Shin, Ezeofor, Smith, Welch, &
Goodrich, 2016). Studies could examine how this awareness and engagement in developing a broader
social justice identity for Whites may also contribute to their SWB (Klar & Kasser, 2009; Waters, 2010).
Similarly, the study of race and SWB should not be a separate discipline from the general study of SWB.
Rather, Ethnic Studies can provide multiple analytical frameworks (e.g., Critical Race theory) that can be
applied to all research studying SWB–thereby, advancing the field of SWB with more rigorous and rich
research that carefully examines the role of race.
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Intersection of Religion and Subjective Well-Being
By Chu Kim-Prieto & Leanne Miller, The College of New Jersey
Citation
Kim-Prieto, C., & Miller, L. (2018). Intersection of religion and subjective well-being. In E. Diener, S.
Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
This chapter reviews the body of research investigating the effect of religion and religiosity on subjective
well-being (SWB). First, we provide a broad overview of the relation between religiosity and SWB, with
specific attention to cultural factors and circumstances that moderate this effect. Then, we review the
research on four specific process variables that have been considered in the past as mediating the relation
between religiosity and well-being. Meaning in life, coping, social support, and emotion regulation are
considered in examining whether these variables can account for, and explain away, the effect of religiosity
on SWB.
Keywords: Religion, Spirituality, Subjective Well-Being
Religion is a directed and active search for a sacred universal truth. The inclusion of the sacred is
what makes religion different from other searches for universal truth (Pargament, 1999). The search – and
the experiences, feelings, and beliefs that accompany the search – as well as the destination, are both part of
the religious experience. For example, the search might include attendance at religious events, whereas
destination might include experiences of the sacred. The sacred, in turn, has been defined broadly to
include concepts about higher powers, the divine, and the transcendent. These beliefs about the sacred can
be transferred to objects as well as people, thus turning ordinary objects, such as a bowl, a bead, or a statue,
into sacred objects, and people into saints and other spiritual beings (Pargament, 2002). In addition, as an
institution, religion includes not just the objects and edifices, such as codified texts, places of worship,
methods of teaching and learning, but also the set of beliefs, values, norms, mores, and rituals that are
observed, taught, and practiced. For the purposes of this chapter, we include all three of these aspects when
we refer to religion or religiosity.
And it is through these institutions, practices, and experiences that religion can lift adherents to
heights of ecstasy and serve as a bulwark against distress, anxiety, and loneliness – we examine the ways in
which religion promotes well-being and lay out the research evidence linking religion and subjective wellbeing
(SWB). Of course, this is not to say that religion has not served to justify heinous crimes and
conflict. History is rife with such examples. However, the goal of this chapter is to examine the benefit of
religion and evaluate the research evidence related to the intersection of religion and SWB.
Overall Findings about Religion and SWB
Much research supports the positive relationship between religion and SWB. In a nationally
representative US Gallup poll, respondents were twice as likely to be in the “very happy” group if they had
reported religious faith as being most important, as opposed to least important (Myers, 2000). Indeed, in
their review, Koenig and Larson (2001) found that of the 100 studies that they considered, 79 found a
positive relationship, including 10 of the 12 which included prospective cohort studies. When the criterion
was depression, 60 of 93 found lower rates of depression and fewer symptoms (for a brief review, see also
Seybold & Hill, 2001). In addition to broad reviews, several meta-analyses have also found support for
this relationship. For example, Hackney and Sanders (2003) found an overall positive effect (r = 0.10) of
religiosity on psychological adjustment. A more recent meta-analysis by Smith, McCullough & Poll
(2003) also found similar results, in that they found a negative relation (r = -.096) between religiosity and
depression. But as can be seen from the effect sizes, the impact at first glance appear to be small, at best.
A closer look at the relationship, however, raises the possibility that the size of the effect may be slightly
larger than that shown by overall means. Even though the overall effect found by Smith, McCullough &
Poll (2003) in their meta-analysis was small, they also found that the strength of the relationship was
stronger for those who were experiencing distress due to recent life events, such that those studies that
considered severe life stress found weighted mean r = -.152, compared to minimal life stress ( r = -.071).
Similarly, Hackney and Sanders (2003) also found that depending on the operationalization of well-being
and religiosity, average effect sizes varied from 0.11 to 0.32.
Of course, the above effects are still not large. However, what makes religion an important factor in
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considering SWB is that this relation appears to hold across multiple situations, religions, and cultures.
While much of the evidence supporting religion’s role in SWB stems from research with Christians from
Western and relatively wealthy and industrial nations, research examining the effect across different
religions have similarly found that religion predicts SWB. For example, Abdel-Khalek (2006) found that
for Kuwaiti Muslim undergraduate students, religiosity accounted for 15% of their variance on happiness.
And for Kuwaiti participants, the predictive power of religiosity held even during and subsequent to Iraq’s
invasion of Kuwait (Figley, Chapman, Ashkanani, al-Naser, & Donnelly, 2010). Rosmarin, Pargament, &
Mahoney (2009) found that trust in God was associated with greater happiness and lower levels of anxiety
and depression for Jewish participants, and Krause, Ingersoll-Dayton, Liang, & Sugisawa (1999) found that
for elderly Japanese participants, religiosity predicted better health. Ng & Fisher (2016) also found that
religiosity predicted SWB for Hong Kong Christian Chinese participants. In addition to research that
focuses on specific religions or populations, investigations that consider large multi-national samples have
also found similar results. For example, Diener & Clifton (2002) found that religiosity was positively
associated with positive feelings and negatively associated with negative feelings across Buddhism,
Christianity, Hinduism and Islam, controlling for demographic variables of age, gender, and life
circumstances at the individual and societal level.
A caveat, however, exists in that while religion might predict SWB, the strength of the predictive
ability, as well as overall mean levels of SWB, do vary across religions as well as denominations within
religions. For example, some research has found that adherents of more fundamentalist denominations
compared to liberal denominations across different religions self-reported greater happiness, life
satisfaction, as well as optimism (Ellison, Gay, & Glass, 1989; Green & Elliott, 2010; Sethi & Seligman,
1993). But the findings are mixed, with other research not finding such differences across different
denominations (e.g., Diener & Clifton, 2002; Ellsworth & Ellsworth, 2010). And because it is not always
possible to consider solely religious or denominational affiliation while eliminating the effect of other
variables, such as individual and national wealth, majority vs. minority status, intra-individual changes in
religiosity and value of religiosity, as well as other cultural values and beliefs, this research contains
multiple confounds.
The culture-level variable that has garnered much research focus is whether the culture values
religion or not. For example, Graham & Crown (2014) found an overall positive relation between
religiosity and SWB using a large-scale dataset that includes about 160 nations. This relation was
moderated by culture, specifically the religiosity of the culture itself. In cultures with high levels of
religiosity, being religious had a greater impact on SWB, compared to cultures with low levels of
religiosity. In addition, using the European and World Values Studies datasets, Stavrova, Fetchenhauer, &
Schlosser (2013) found that the predictive power of religiosity on life satisfaction was greater in highly
religious cultures, whereas the relation was negative in cultures that valued atheism (c.f. Pirutinsky, 2013,
who replicated the main effect, but not the interaction of religiosity at the nation level, using European
Social Survey). Lun & Bond (2013) also found that across nations, the impact of religiosity on well-being
was further moderated by support for spiritual practice, as well as societal hostility towards religion. For
nations with low support for socialization, spiritual practice and happiness were not related. Similary,
Diener, Tay, & Myers (2011) found that while religiosity was associated with higher SWB generally, it was
mediated by social support, feelings of respect, and meaning in life. These, in turn, were moderated by
difficult life circumstances. That is, when life circumstances were difficult, greater religiosity predicted
greater SWB, via greater social support and meaning in life. But if circumstances were not as difficult,
religiosity did not provide much benefit to SWB.
Thus, it appears that overall, and generally, religiosity provides some benefits for SWB. The
extent of the benefit varies, however, and are circumscribed by culture-level and individual-level
variables. In addition, much of the effect appear to be mediated by third variables that may perhaps
account for much, if not most, of the effect of religiosity on SWB.
Processes that Explain the Relation between Religion and SWB
What might explain the relationship between religiosity and SWB and further clarify the boundary
conditions of this effect? Lewis and Cruise (2006) argue that by definition, religion provides “existential
certainty,” a meaning in life. They further argue that it provides mechanisms for social support,
emphasizing the social implications of religious involvement (see also Myers, 2000). Indeed, much
research have borne out this theory. In addition, others have noted that religion serves as a bulwark
against distress by providing various ways of coping, whether it be through social services or through
religious belief. Last, a growing body of research investigates the role of religion in emotion experiences
and emotion regulation, both of which are implicated in SWB. Below, each of the process variables are
discussed in turn and evaluated in terms of the research evidence.
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Meaning in life. Religions, by definition, provide an explanation for the world and the rationale
for existence within it. Most religions also provide a goal or a standard by which that existence should be
measured. These edicts provide meaning and purpose to adherents, and research evidence bears out the
importance of meaning in life as a mediator. For example, French & Joseph (1999) found that meaning in
life fully mediated the relation between religiosity and happiness. Others have found similar results, even
when meaning in life has been operationalized slightly differently as coherence or importance of meaning,
or when religiosity was measured as attendance at religious service (e.g., Ellison, 1991; Yoon et al., 2015;
see George, Ellison & Larson, 2002 for review of research on meaning as mediator for relation between
religiosity and physical health). In addition, a prospective research study measuring adjustment and wellbeing
pre- and post- a major natural disaster also found that sense of purpose, as well as optimism,
mediated pre-disaster religiosity and post-disaster well-being (Chan, Rhodes & Perez, 2012). And as was
the case for the body of research on religion and SWB in general, while much of the research is based on
Christian adherents, the findings replicate across religions (i.e., Steger & Frazier, 2005; Vilchinsky &
Kravetz, 2005).
Coping. Not all coping strategies, whether they be religious or non-religious, are effective.
Similarly, not all religious coping strategies provide comfort. However, positive religious coping
strategies, similar to positive coping strategies in general, provide access to heightened well-being. For
example, Mickley, Pargament, Brant & Hipp (1998) found that for hospice caregivers, religious appraisals
that were positive vs. negative (death as punishment from God vs. dying process as a benevolent act from
God) predicted meaning in life, anxiety, depression, and spiritual well-being (see also Koenig, George &
Siegler, 1988; Pargament et al., 1990). Indeed, a meta-analysis of 147 studies on the relation between
religiosity and depressive symptoms found that while the overall strength of relation was r = -.09, when
positive religious coping, intrinsic religious orientation and positive regard of God were separated from
external religiosity and negative coping, the effect size was as high as r = -.20 (Smith, McCullough, & Poll,
2003). Similarly Ano and Vasconcelles (2005) found mean r = .33 for positive religious coping and
positive psychological outcomes. Similar findings have been noted for Lebanese college students in Beirut
(Moussa & Bates, 2011), and Muslim participants (Abu-Raiya, Pargament, & Mahoney, 2011). And while
not as numerous as cross-sectional research, prospective studies have also confirmed the positive effect of
positive religious coping on SWB. Chan & Rhodes (2013) found that positive religious coping predicted
posttraumatic growth following a large-scale natural disaster, while negative religious coping predicted
symptoms of post-traumatic stress disorder.
It is important to note, however, that much of the research on religious coping conflate several
variables. For example, an often used positive religious coping strategy might be cognitive reappraisal, but
also prevalent are forms of emotional and social support, such as seeking support from members of the
religious congregation or religious leader (e.g., Pargament et al., 1994). Thus, below, we further
investigate the different ways in which social support may be a crucial mediator in the relation between
religiosity and SWB.
Social support. A robust body of research indicates that strong and close social relationships may
be one of the most important predictors of SWB (for brief review, see Myers, 2000). For many religious
traditions, regular attendance at religious services and/or membership in a congregation is a large
component of adherence to the religion. A strong indication that social support may indeed account for
much of the effect of religiosity lies in the fact that in many of the above research studies, religiosity has
been operationalized as frequency of church attendance. When religiosity is measured in multiple ways,
research have found that it is church attendance that best predicts well-being outcomes. For example,
Strawbridge, Shema, Cohen, Roberts, & Kaplan (1998) measured private/individual religious acts and
beliefs, such as prayer, importance of religion, as well as church attendance, and found that it was church
attendance that best predicted well-being (see also Levin & Chatters, 1998).
Research indicates that frequent churchgoers not only have larger social networks, but also more
frequent contact with members in the network, both in person and by telephone. Frequent attenders also
received greater social support, and rate their social relationships as more favorable compared to those who
do not attend religious congregations as frequently (Ellison & George, 1994). In addition, this relation
held when personality variables, such as extraversion, were controlled for (Bradley, 1995).
The social support appears to provide benefits to adherents in two ways: As a buffer against
adverse life events; and as source of social capital and status. For example, Williams, Larson, Buckler,
Heckmann & Pyle (1991) found that religious attendance moderated the effect of stress on mental health,
such that for low frequency attenders, stressful life events negatively impacted metal health, whereas high
frequency attenders were less debilitated by negative life events (see also Ellison, Burr & McCall, 1997;
Salsman, Brown, Brechting & Carlson, 2005). And in the aftermath of tragic events, such as the sudden
death of an infant, parents who were frequent attenders received greater social support, and that social
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support in turn predicted better adjustment three weeks later (McIntosh, Silver, & Wortman, 1993). As a
source of social capital, Shkolnik, Weiner, Malik & Festinger (2001) found that religiosity predicted social
status, which in turn led to social capital among elderly Jewish participants (see also King & Furrow,
2004).
The benefits of social support can also be discerned by holding the benefit of shared doctrine
constant. Unitarian Universalism does not have a creed; instead, each member is responsible for seeking
their own spiritual path, which means that the benefit of a cohesive principle or belief may be missing.
Even in such cases, adherents benefited from social support of the congregation and derived strength and
comfort (Elliott & Hayward, 2007). Researchers found, however, that the extent of benefit depended on
whether being a Unitarian Universalist was central to their identity. The role of identity as a member of a
religious group seems to be an important element of social support in other religions as well. Using a
national probability sample, Greenfield & Marks (2007) found that social identity mediated the effect of
church attendance on SWB. In addition, Hayward & Elliott (2009) found that degree of congruence with
the congregation predicted having spiritual needs met, as well as help with daily living. Indeed, Hogg,
Adelman and Blagg (2010) go as far as to posit religion as a social group, and religiosity as the extent to
which one adheres to the norms, beliefs, and mores of that social group, with the difference between
religions and other social groups being that religion’s beliefs are existential.
But if social support mediates the effect of religiosity on SWB, and religion is yet another social
group, then is religion necessary? That is, is religious social support something that provides benefits for
the adherent above and beyond social support received from non-religious sources? Some research seems
to indicate that while social support from non-religious sources also serves to buffer and provide social
capital, religious social support provides unique benefits to well-being. For example, while church based
emotional support appeared to buffer against the negative impact of financial stain, support from secular
networks did not (Krause, 2006; see also Krause & Bastida, 2009). In addition, while spiritual support
predicted positive religious coping in adherents, emotional support did not (Krause, Ellison, Shaw,
Marcum, & Boardman, 2001).
And of course, one can be a strong adherent of a religion without being a member of a
congregation. And in many religions, communal worship or membership in a congregation is not a
codified part of religious adherence, or a valued aspect of religiosity. This was seen in Krause, IngersollDayton,
Liang, & Sugisawa (1999), who found that for elderly Japanese participants, the aspect of
religiosity that mattered was not attendance at religious functions, but daily at-home religious practices.
Thus, while social support explains much of the link between religiosity and SWB, it cannot fully explain
the effect of religiosity on SWB.
Emotion. In searching for additional processes that might explain the impact of religion on SWB,
Fredrickson (2002) suggested positive emotions as a mediator. Indeed, emotions are an integral part of
religion, such that religions provide guidelines for experiencing, or not experiencing, specific emotions
(Kim-Prieto, 2014; Kim-Prieto & Diener, 2009). Thus, the experience of specific emotions, as well as
regulation of that experience, might indeed help explain religion’s impact on SWB.
A robust body of research indicates that religious emotions play a key role in promoting SWB.
Religious services, prayer, sermons, reading religious texts, serve as triggers of positive religious emotions
(Argyle & Hills, 2000). Emotions such as awe, gratitude, love and peace, as well as optimism, have been
found to fully mediate religiosity and well-being (van Cappellen, Toth-Gauthier, Saroglou, & Fredrickson,
2016; Salsman et al., 2005). Religious people who practice forgiveness report lower stress, depression, and
anxiety (Spilka, Hood, Hunsberger, & Gorsuch, 2003; Worthington, Berry, & Parrott, 2001), and those
who practice Loving Kindness meditation, a Buddhist meditation practice, reported increased positive
emotions, which in turn predicted increased social support (Fredrickson, Cohn, Coffey, Pek, & Finkel,
2008; see also Philippot, Chapelle & Blairy, 2002). In addition, even on social media platforms, presumed
Christians showed greater use of positive emotions words compared to presumed atheists (Ritter, Preston,
& Hernandez, 2013).
In addition to emotion elicitation, religious traditions regulate emotions in additional ways.
Disclosure of emotion has been found have positive benefits for well-being, and religious practice often
serves as a way by which trauma or negative experiences can be disclosed (described in Pizarro & Salovey,
2002). In the Roman Catholic tradition, for example, describing transgressions is expected to absolve sin,
thus providing a way of ameliorating guilt. In addition, while prayer, meditation, and other similar rituals
can serve to elicit positive emotions, they can also promote the regulation of other emotions. A growing
body of research on mindfulness-based meditation, a Buddhist meditation technique, has established a
robust set of evidence showing the benefits of meditation on emotion regulation (for review, see Lykins,
2014). For example, Goldin & Gross (2010) found that participants with social anxiety disorder who
416
participated in an 8-week mindfulness based stress reduction meditation session experienced reduction in
anxiety, depression, and rumination.
Conclusion
Thus, as reviewed above, evidence points to religion as a factor in SWB. Much of the effect,
however, is mediated by other intervening variables, such as meaning in life, coping, social support, and
emotion regulation. While research evidence shows that some of these intervening variables fully mediate
the effect of religiosity on SWB, additional evidence also indicates that some of these mediating factors
may be unique to religion. In addition, some of these variables may also serve as moderators. For
example, benefits of religious coping would accrue in response to distressful events, but not in the absence
of such events. Last, additional context variables moderate the role of religion on SWB. For example, as
reviewed above, the extent to which a culture values religiosity or provides supports for the practice of
religion, along with the experiences of hardship at the individual and society level, impact the effect of
religion on well-being.
Freud (1929) believed religion to be a form of neurosis. He considered religion to be an infantile
search for bliss, merely an attempt to resolve the Oedipal complex and resolve feelings of helplessness.
We have provided evidence that religion provides benefits to the individual and perhaps society. But we
also cannot ignore the evidence that religion is not always beneficial. At the individual level, religiosity is
linked with greater out-group hostility and prejudice, support for suicide attacks, unwillingness to forgive,
and discrimination (e.g., Cohen, Malka, Rozin, & Cherfas, 2006; Ginges, Hansen & Norenzayan, 2009;
Hunsberger & Jackson, 2005). Exline (2002) also points out that religion can serve as a source of
interpersonal discord and strain, especially group-level violence. And when adherents struggle with
disbelief, experiencing disappointment regarding the ineffectiveness of God, experiencing God as distant,
or doubts about the existence of God, these experiences predict negative outcomes, with the impact being
strongest for those who are most devout (Ellison, Fang, Flannelly, & Steckler, 2013; Exline, Yali, & Lobel,
1999; Exline, Yali, & Sanderson, 2000; Krause & Wulff, 2005; Pargament, 2002; Smith, McCullough, &
Poll, 2003).
What are some other variables that might further bolster or attenuate the effect of religion on wellbeing?
Are there specific types of religious activity that may be more or less beneficial than others?
Additional research is needed on various mind-body practices, including yogic and other forms of posture
based meditation, as well as other bodily practices, such as walking meditation and prayer, spiritual dance,
or religious flagellation. And while the body of research investigating the effect in non-Christian and nonWestern
contexts is growing, additional research is needed to better understand whether some of the effects
are merely the effects of those better-researched religions, or can be assumed to be generalizable to
religions at large. In addition, while a few sets of research provide experimental data, where religion or
religiosity have been experimentally manipulated or made salient (e.g., Kim-Prieto & Diener, 2009), most
research are cross-sectional. More experimental research, as well as longitudinal investigations, would
allow for stronger evidence of the causal direction of the impact of religion on SWB.
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Married...With Children: The Science of Well-Being in Marriage
and Family Life
By S. Katherine Nelson-Coffey, Sewanee: The University of the South
Citation
Nelson-Coffey, S. K. (2018). Married...with children: The science of well-being in marriage and family
life. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF
Publishers. DOI:nobascholar.com
Abstract
As some of the most important relationships in people’s lives, marriage and parenthood offer many
opportunities for people to experience great joy or to suffer incredible disappointment. In the current
chapter, I review current understanding of whether, how, and why marriage and parenthood are associated
with well-being, drawing on evidence from cross-sectional, longitudinal, and daily experience studies. I
also consider the implications of family structure for the associations between marriage and well-being, and
parenthood and well-being, respectively. Current evidence provides relatively robust support for the
association between marriage and well-being; however, the association between parenthood is much more
complex. I conclude with a number of suggestions for future research.
Keywords: Family, Marriage, Parenthood, Well-Being, Happiness
For many people, getting married and having children represent the ideals of the American dream.
Indeed, family relationships are some of the most important aspects of people’s lives, influencing their dayto-day
experiences, decisions, and broad evaluations of their lives (Gerson, Berman, & Morris, 1991). Not
surprisingly, these relationships hold important implications for people’s overall happiness and well-being
(Nelson, Kushlev, & Lyubomirsky, 2014; Saphire-Bernstein & Taylor, 2013). Drawing on literature from
psychology, economics, and sociology, this chapter focuses on how marriage and parenthood are
associated with happiness and well-being, along with the psychological factors that magnify and minimize
the happiness gained from these relationships.
What is Happiness?
The most common scientific approach to defining happiness (also referred to as subjective wellbeing)
includes cognitive (high life satisfaction) and affective (frequent positive emotions and infrequent
negative emotions) components (Diener, 1984; Diener, Suh, Lucas, & Smith, 1999). According to this
definition, happy people evaluate their lives positively overall (i.e., high life satisfaction), and they
experience frequent positive emotions (e.g., love, joy, contentment) and infrequent negative emotions (e.g.,
anger, frustration, sadness). Other researchers distinguish happiness from meaning in life, which is
theorized to include three components—coherence (i.e., the evaluation that life makes sense), significance
(i.e., belief in one’s value, worth, and importance), and purpose (i.e., feeling that one has important goals
and life direction; King, Heintzelman, & Ward, 2016; Martela & Steger, 2016). Despite these distinctions,
however, happiness and meaning in life are highly correlated (Kashdan, Biswas-Diener, & King, 2008;
King, Hicks, Krull, & Del Gaiso, 2006). Many studies also examine how family life is related to symptoms
of psychological illnesses, such as anxiety or depression. In the current chapter, I focus primarily on studies
that measure subjective well-being or one of its components (life satisfaction, positive emotions, or
negative emotions) and meaning in life as they relate to family; however, I also draw on studies measuring
symptoms of depression and anxiety, particularly when the well-being literature is sparse. I use the terms
happiness and subjective well-being interchangeably but refer to specific constructs when discussing
findings of individual studies.
Methodological Approaches to Studying Family and Well-Being
Studies of family relationships are remarkably interdisciplinary, drawing on multiple areas within
psychology (e.g., developmental psychology, social psychology, clinical psychology), as well as economics
and sociology. Moreover, because marriage and parenthood cannot be randomly assigned, drawing causal
conclusions about their effects on well-being is difficult. In the absence of experimental approaches, three
primary methodologies have been used to investigate the links between family and well-being—each with
their own strengths and limitations.
Cross-Sectional Studies
First, research has investigated whether marriage and parenthood are associated with well-being by
employing cross-sectional designs comparing the well-being of married participants with unmarried
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participants (e.g., Diener, Gohm, Suh, & Oishi, 2000), or parents with nonparents (e.g., Nelson, Kushlev,
English, Dunn, & Lyubomirsky, 2013; McLanahan & Adams, 1989; Umberson & Gove, 1989). These
studies often rely on large, nationally representative surveys, thus avoiding potential sampling biases. In
addition, these datasets often include respondents from young adulthood to very old age and provide indepth
demographic information on each respondent. These features allow researchers to thoroughly
investigate the associations between family relationships and well-being across the lifespan and in light of a
variety of demographic factors (e.g., gender).
Despite these strengths, studies relying on cross-sectional designs should be interpreted in light of a
few limitations. Most notably, these studies cannot determine whether getting married or having children
causes changes in well-being. Indeed, some evidence suggests that happiness precedes both getting married
and having children (Kim & Hicks, 2016; Luhmann, Lucas, Eid, & Diener, 2013; Lyubomirsky, King, &
Diener, 2005; Cetre, Clark, & Senik, 2016). In an effort to address this limitation and determine whether
marriage and parenthood cause changes in well-being, some studies include many demographic factors
(e.g., age, gender, income) as covariates in their analyses (e.g., Bhargava, Kassam & Loewenstein, 2014);
however, few studies include similar covariates in their analyses, making it difficult to compare across
studies, and causality is still impossible to determine in the absence of random assignment or time
separation among variables. A more informative approach may be to examine these covariates as
moderating variables that may alter the links between marriage or parenthood and well-being, respectively
(for a full discussion of this issue as it relates to parenthood and well-being see Nelson, Kushlev, Dunn, &
Lyubomirsky, 2014; Nelson, Kushlev, & Lyubomirsky, 2014).
Longitudinal Studies
Second, studies have examined whether well-being changes before and after getting married or
having children using longitudinal designs (for a meta-analysis, see Luhmann, Hofmann, Eid, & Lucas,
2012). By relying on a within-person approach, these studies partially address selection biases (that happy
people are more likely to get married and have children; Cetre et al., 2016; Kim & Hicks, 2016;
Lyubomirsky et al., 2005). In addition, like the cross-sectional studies described above, many longitudinal
studies examining the transition to marriage or parenthood rely on large, nationally representative samples
(e.g., Dyrdal & Lucas, 2013; Lucas, Clark, Georgellis, & Diener, 2003).
These longitudinal studies are primarily limited by the timing of well-being assessments
surrounding marriage and childbirth. A recent meta-analysis of the transition to parenthood, for example,
revealed that the average timing of baseline well-being measurement was just 2 months prior to childbirth
(Luhmann et al., 2012)—a time likely filled with excitement, anticipation, and celebration in preparation
for a new child. Given evidence that well-being begins to change prior to experiencing major life events
(Luhmann et al., 2012), these studies should be interpreted in light of when baseline well-being was
measured. Furthermore, many couples have children within a few years of getting married (Claxton &
Perry-Jenkins, 2008), and marriage itself is associated with a boost in happiness that typically lasts for 2
years (Lucas et al., 2003). Thus, changes in happiness in response to childbirth ought to be interpreted in the
context of responses to other life events, such as marriage.
Daily Experience Studies
Finally, studies have investigated the links between family and well-being using methods to capture
individuals’ daily experiences—namely, by employing experience sampling methodology (Hektner,
Schmidt, & Csikszentmihalyi, 2007), the Day Reconstruction Method (Kahneman, Krueger, Schkade,
Schwarz, & Stone, 2004), and other daily diary procedures (Bolger, Davis, & Rafaeli, 2003). In these
studies, participants typically provide information about their daily activities and emotions, either in realtime
(experience sampling), at the end of the day (daily diary), or the following day (Day Reconstruction
Method). Using these approaches, studies could compare the daily experiences of married with unmarried
participants, or parents with nonparents (e.g., Nelson et al., 2013, Study 2). Alternatively, some studies
focus on within-person comparisons—for example, by contrasting parents’ emotions during caregiving
relative to their other daily activities (e.g., Nelson et al., 2013, Study 3; Nelson-Coffey, Borelli, & River,
2017), or by examining how daily behaviors (e.g., daily sacrifice) are related to relationship satisfaction
and well-being (e.g., Impett, Gable, & Peplau, 2005). Thus, one benefit of this methodological approach is
its flexibility to address a variety of research questions. In addition, daily experience studies can capture
people’s feelings while they are spending time with their spouse or children (in contrast to reports of global
well-being, which may reflect feelings during other moments of the day). Finally, because these studies
typically rely on in-the-moment reports of emotion, they may be less susceptible to response biases.
Notably, however, daily experience studies also have their limitations. Like the other
methodological approaches discussed above, these studies do not provide information about the causal
influence of getting married or having children on well-being. In addition, because these studies typically
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capture reports of momentary emotions, they do not provide insight into how marriage and parenthood are
related to global well-being; however, evidence suggests that emotions—especially positive emotions—are
important predictors of global well-being (Kuppens, Realo, & Diener, 2008). Finally, daily experience
studies may provide a limited portrait of marriage and parenthood, dependent on the type of activity or
other influences on people’s days.
Summary
In sum, a variety of methodological approaches have been implemented to better understand how
family relationships—namely marriage and parenthood—are related to well-being. One of the great
challenges in this line of work involves the desire to understand whether these relationships cause people to
be happier. Although social scientists may not be able to directly answer the question of causality, they can
draw on the methodological approaches described here to understand whether married people and parents
are happier than unmarried people and nonparents, respectively, in a randomly selected group of people
(cross-sectional studies); whether people become happier after getting married and having children, and for
how long (longitudinal studies); and how marriage and parenthood are related to the emotions felt in daily
life (daily experience studies). Furthermore, the strongest evidence supporting links between marriage or
parenthood and well-being draws on multiple methodologies and demonstrates replicability. In the
remainder of this chapter, I review the current literature on family relationships and happiness, turning first
to the links between marriage and happiness and next to parenthood and happiness. In this review, I note
areas of consensus and contradiction in the research findings and offer suggestions for future research.
Marriage
Is Marriage Associated with Happiness?
The majority of the evidence investigating the claim that marriage is associated with happiness
comes from cross-sectional and longitudinal studies examining objective marital status and well-being.
Cross-sectional studies indicate that married people tend to be happier than unmarried people (Coombs,
1991; Diener et al., 2000; Easterlin, 2003; Haring-Hidore, Stock, Okun, & Witter, 1985; Kamp Dush &
Amato, 2005; Lee & Ono, 2012; Myers, 2000; Williams, 2003; Wood, Rhodes, & Whelan, 1989). These
findings are robust and consistent across studies and cultures (Diener et al., 2000; Haring-Hidore et al.,
1985; Lee & Ono, 2012). In one study, for example, the association between marriage and subjective wellbeing
was examined in 42 nations. Across countries, married participants reported greater life satisfaction
and positive emotions and lower levels of negative emotions, relative to both cohabiting and divorced
participants (Diener et al., 2000). Additionally, in a meta-analysis of this literature, married respondents
reported significantly higher levels of subjective well-being than unmarried respondents (average r = .14;
Haring-Hidore et al., 1985).
An important consideration in evaluating cross-sectional studies examining the association between
marriage and happiness is whether changes in happiness precede marriage. Evidence suggests that happy
people have rich and satisfying social relationships (Diener & Seligman, 2002), which may increase their
likelihood of getting married. In one classic study on this topic, women’s positive emotional expression in
their college yearbook photographs was associated with greater likelihood of being married at age 27 and
greater marital satisfaction at age 52 (Harker & Keltner, 2001). Another study found that life satisfaction
significantly predicted the likelihood of getting married within 5 years (Luhmann et al., 2013). Thus, the
findings from cross-sectional studies may be partially explained by the fact that happier people are more
likely to get married.
One way to address these selection biases is to examine whether and how happiness changes before
and after getting married with longitudinal designs. Longitudinal research also suggests that getting married
is associated with a boost in happiness, which diminishes over time. In one study drawing from the German
Socioeconomic Panel, people reported their life satisfaction and a variety of demographic information
annually for 15 years. Researchers were then able to track changes in respondents’ life satisfaction after
getting married. This study found that people reported an increase in life satisfaction the year they got
married, which was followed by a return to their pre-marriage baseline happiness within 2 years (Lucas et
al., 2003). In addition, a meta-analysis of this literature found that cognitive well-being (life satisfaction),
but not affective well-being (positive and negative emotions), increased after marriage, followed by a
subsequent decline (Luhmann et al., 2012). Thus, existing longitudinal evidence suggests that, on average,
getting married is associated with a boost in well-being, which typically dissipates by a couple’s second
anniversary.
Another approach to understanding whether and how marriage is related to well-being is to
consider how relationship quality predicts happiness, over and above objective marital status. These studies
suggest that the quality of marriage is a more important predictor of happiness than simply being married.
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One study on this topic found that people who were in the happiest relationships—whether those were
marriages, cohabiting, or dating relationships—reported the highest levels of subjective well-being (Kamp
Dush & Amato, 2005). Another study examined how changes in marital status and marital quality were
related to changes in life satisfaction and symptoms of depression over 5 years. In this study, low marital
quality (as indicated by high levels of marital stress and low levels of marital harmony) predicted decreases
in life satisfaction and increases in depressive symptoms. In addition, this study found that people who
remained in unhappy marriages reported lower levels of well-being than those who remained unmarried
(Williams, 2003). Furthermore, in an examination of changes in marital quality and happiness over the life
course, participants with the highest marital satisfaction also reported high levels of happiness over the
course of 20 years (Kamp Dush, Taylor, & Kroeger, 2008). Thus, extant evidence—drawing on both crosssectional
and longitudinal designs—suggests that the quality of a person’s relationship is an important
predictor of well-being, perhaps more important than objective marital status. Indeed, a meta-analysis of 93
studies found that marital quality was significantly associated with well-being (average r = .37 for crosssectional
studies and average r = .25 for longitudinal studies; Proulx, Helms, & Buehler, 2007).
Individual differences. Marriage may be associated with greater well-being for some people than
it is for others. Indeed, a number of demographic and psychological factors moderate the association
between marriage and happiness. Although a full discussion of the many individual differences in the
association between marriage and happiness is outside the scope of this chapter, below I consider two
factors—gender and attachment style—that are important predictors of the association between marriage
and happiness.
Gender. Some evidence suggests that the link between marriage and subjective well-being differs
for men and women. In cross-sectional studies investigating the link between relationship status and wellbeing,
marriage was more strongly associated with well-being for men than for women (Coombs, 1991;
Haring-Hidore et al., 1985). Similarly, in one longitudinal study investigating gender differences in
reactions to divorce, men experienced a greater drop in well-being following divorce than did women
(Lucas, 2005). Notably, however, a meta-analysis of longitudinal studies examining reactions to getting
married (rather than divorced) did not find any gender differences in reactions to marriage (Luhmann et al.,
2012). One explanation for these gender differences suggests that men benefit more from the social support
they receive from their spouses, whereas women—who tend to have stronger social ties outside of marriage
—do not rely as heavily on social support from their spouse (Antonucci & Akiyama, 1987; Coombs, 1991;
Gurung, Taylor, & Seeman, 2003).
Conversely, other studies have examined gender differences in the association between marriage
and well-being by focusing on relationship quality rather than relationship status. In these studies,
relationship quality tends to be more strongly associated with happiness for women than for men (Proulx et
al., 2007; Saphire-Bernstein & Taylor, 2013). For example, in one study of older married couples,
perceptions of social support from one’s spouse was more strongly associated with greater marital
satisfaction and well-being among women than men (Acitelli & Antonucci, 1994). Together, this evidence
suggests that marriage is differentially associated with well-being for men and women. For men, simply
being married seems to be sufficient to improve well-being; for women, however, being in a high quality
marriage is associated with greater well-being.
Attachment . Attachment style is thought to develop based on individuals’ early experiences
receiving care from attachment figures (e.g., their parents) and shapes people’s feelings, beliefs, and
expectations about relationships across the lifespan (i.e., internal working models; Bowlby, 1969).
Attachment styles are commonly measured along dimensions of anxiety and avoidance, with secure
attachment characterized by low levels of both anxiety and avoidance (Mikulincer & Shaver, 2007).
Attachment avoidance is characterized by distrust of relationship partners along with a desire for
independence; attachment anxiety is characterized by fear of rejection and desire for extreme intimacy; and
finally, secure attachment is characterized by trust, comfort, and ease in close relationships (Mikulincer &
Shaver, 2007, 2016).
Investigations of attachment style and subjective well-being suggest that, relative to those with
insecure attachment orientations (i.e., high attachment anxiety or high attachment avoidance), individuals
with secure attachments experience greater subjective well-being overall and within their close
relationships (Mikulincer & Shaver, 2013). For example, in one study, wives high in attachment anxiety
and avoidance expressed fewer positive emotions after reuniting with their husbands following an extended
separation (Medway, Davis, Cafferty, Chappell, & O’Hearn, 1995). Similarly, another study found that
people high in attachment avoidance expressed fewer positive emotions when discussing positive aspects
of their relationship with their partner (Tucker & Anders, 1998). Finally, in a daily experience study of
attachment, relationship behaviors, and gratitude, people with secure attachments reported more gratitude
in response to their partner’s positive behaviors, whereas people high in attachment avoidance reported less
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gratitude in response to their partner’s positive behaviors (Mikulincer, Shaver, & Slav, 2006). Although this
work does not directly test whether attachment style moderates the association between marriage and
happiness, it suggests that individuals with secure attachment styles would experience the greatest
happiness in response to marriage.
Why is Marriage Associated with Happiness?
Why is marriage associated with happiness? The bulk of research addressing this question focuses
on the importance of relationships, and processes within those relationships, for happiness more generally,
rather than the specific importance of marriage. From this perspective, theory suggests that human beings
have a fundamental need to belong (Baumeister & Leary, 1995) and to feel connected to others (Ryan &
Deci, 2000). Thus, marriage—especially highly satisfying marriages—may offer people opportunities to
feel that they belong and that they are connected to others. In addition, a large body of research suggests
that social support is beneficial for both physical health and subjective well-being (Cohen, 2004; Siedlecki,
Salthouse, Oishi, & Jeswani, 2014). Indeed, receiving adequate support from one’s spouse is associated
with greater life satisfaction (Wan, Jaccard, & Ramey, 1996), as well as reduced depressive symptoms and
perceived stress (Beach, Sandeen, & O’Leary, 1990; Brown, Andrews, Harris, Adler, & Bridge, 1986;
Dehle, Larsen, & Landers, 2001).
To my knowledge, an integrated model explaining the association between marriage and happiness
does not exist. Drawing on the substantial body of research demonstrating that relationships are beneficial
for happiness, future researchers may wish to integrate this literature to develop a unifying theory
explaining the links between marriage and happiness. Notably, such a model would help distinguish the
extent to which marriage is associated with happiness due to selection effects (e.g., Luhmann et al., 2013),
along with psychological processes beneficial to well-being after marriage, such as feelings of
connectedness, social support, and others.
Family Structure and Changing Societal Norms
Notably, the majority of past research examining the association between marriage and happiness
focused on comparing legally married, opposite-sex couples with those who were never married,
divorced/separated, or cohabiting, with variations in comparison groups across studies. Understanding these
distinctions is important, given rising rates of cohabitation (Bumpass & Lu, 2000; Lichter, Turner, &
Sassler, 2010) and the legalization of same-sex marriage.
Cohabitation. In general, studies offer consistent evidence that being married is associated with
benefits to well-being in comparison with those who have never been married (Easterlin, 2003; Lee & Ono,
2012; Myers, 2000; Williams, 2003), those who were divorced or separated (Diener et al., 2000; Myers,
2000; Williams, 2003) or those who were widowed (Haring-Hidore et al., 1985; Williams, 2003). The
evidence comparing marriage with cohabitation, however, is mixed. Some studies found that marriage was
associated with greater happiness relative to cohabitation (Diener et al., 2000; Lee & Ono, 2012), whereas
others found no difference in happiness levels of married and cohabiting individuals (Kamp Dush &
Amato, 2005). Furthermore, cross-cultural evidence suggests that marriage is associated with a larger boost
in happiness relative to cohabitation in cultures with stronger religious and social norms against
cohabitation (Lee & Ono, 2012; Soons & Kalmijn, 2009). In addition, a 1985 meta-analysis of the link
between marriage and well-being found smaller effect sizes among more recent studies (Haring-Hidore et
al., 1985)—a time also marked by increasing favorability towards cohabitation (Thornton & YoungDeMarco,
2001). To my knowledge, a more recent meta-analysis of the association between relationship
status and well-being has not been conducted. An updated meta-analysis including studies from the last 30
years is warranted to determine if effect sizes have continued to shrink.
Other research has examined how cohabitation prior to marriage is related to relationship quality
and stability after marriage. Early evidence suggested that premarital cohabitation was associated with
lower marital quality and increased risk of divorce (Axinn & Thornton, 1992; Schoen, 1992; Thomson &
Colella, 1992), but more recent work has suggested that this “cohabitation gap” is moderated in part by
social context (e.g., gender climate and religious context; Lee & Ono, 2012; Soons & Kalmijn, 2009;
Stavrova, Fetchenhauer, & Schlosser, 2012; Stavrova & Fetchenhauer, 2015). For example, in one study of
30 European countries, the cohabitation gap was larger in countries that were less accepting of cohabitation
(Soons & Kalmijn, 2009). Additionally, another study found that women who cohabited only once prior to
marriage (with their eventual spouse) did not demonstrate increased risk of divorce (Teachman, 2003),
further pointing to inconsistency in the association between cohabitation and marital satisfaction.
Three explanations have been offered to clarify why cohabiters may be less happy and less satisfied
in their relationships. First, studies finding that the size of the cohabitation gap depends in part on societal
norms for cohabitation, gender, and religion (Lee & Ono, 2012; Soons & Kalmijn, 209; Stavrova et al.,
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2012; Stavrova & Fetchenhauer, 2015) suggest that people may be less happy due to their violation of these
social norms. Second, people who choose to cohabit prior to marriage may be unique in ways that
undermine their happiness and relationship satisfaction. For example, cohabiters may have relatively less
favorable attitudes towards marriage and more favorable attitudes towards divorce (Axinn & Thornton,
1992), which may increase their likelihood of divorce. Third, the experience of cohabiting may alter
people’s attitudes in ways that undermine marital quality. One study found that people were more accepting
of divorce after cohabiting than they were prior to cohabiting (Axinn & Thornton, 1992), which in turn
predicts declines in relationship quality (Amato & Rogers, 1999). Ultimately, research has supported each
of these three possibilities, suggesting that they are not mutually exclusive.
Same-sex marriage and partnerships. Same-sex marriages are legally recognized in 23 countries
worldwide (Pew Research Center, 2015). Notably, however, the majority of research on romantic
relationships (marriage or otherwise) and well-being focus on opposite-sex partnerships. Evidence suggests
that the factors that predict relationship quality in same-sex couples are the same as those that predict
relationship quality in opposite-sex couples (e.g., trust, communication, conflict-resolution styles; Balsam,
Beauchaine, Rothblum, & Solomon, 2008; Kurdek, 2005). In addition, one study compared lesbian, gay,
and heterosexual couples on five domains expected to be indicative of relationship health: psychological
adjustment (including life satisfaction), personality traits, relationship styles, conflict resolution, and social
support. This study found no difference in reported life satisfaction between same-sex and opposite sex
couples and that the only area in which same-sex couples fared worse than opposite-sex couples was in the
amount of support they received for their relationships from others (Kurdek, 2004). More research
incorporating same-sex couples in understanding the links between relationship status, relationship quality,
and well-being is needed.
Summary
In sum, married people tend to be happier than single, divorced/separated, and widowed
individuals, with the most consistent evidence from cross-sectional studies of opposite-sex couples.
Longitudinal research suggests that getting married is associated with a boost in happiness that diminishes
over time. Furthermore, despite these overarching trends in the association between marriage and
happiness, little work has explained why marriage is associated with happiness.
Parenthood
Is Parenthood Associated with Happiness?
Is parenthood associated with happiness? This simple question assumes that there is a simple
answer—parents are either happy or not. Notably, however, parenthood is a complex and dynamic role,
involving multiple people (e.g., co-parent, one or more children) and many changes throughout the life
course (e.g., parenting a toddler vs. a teenager). Accordingly, parenthood may be better understood as a
fluid process that changes over time, and its association with well-being depends on many different factors
(see Nelson et al., 2014 for a review).
Highlighting the complexity of parenthood, cross-sectional studies comparing the happiness levels
of parents with nonparents have reached conflicting conclusions. Research has indicated that (a) parents
report greater well-being than nonparents (Balbo & Arpino, 2016; Nelson et al., 2013); (b) parents report
lower well-being than nonparents (Evenson & Simon, 2005; McLanahan & Adams, 1987, 1989); and (c)
parents and nonparents do not differ in their reported well-being (Rothrauff & Cooney, 2008). Further
adding to this confusion, another recent study found that parents reported both more positive emotion and
more negative emotion than nonparents (Deaton & Stone, 2014).
Evidence regarding the association between parenthood and well-being from longitudinal studies
appears to be more consistent than evidence from cross-sectional studies; however, this work also supports
the idea that parenthood is complex and dynamic. Studies of the transition to parenthood have found that
becoming a parent is associated with a rise in well-being followed by a decline (Dyrdal & Lucas, 2013;
Margolis & Myrskyla, 2015). Moreover, this pattern is not consistent for all parents: Men and people with
higher socioeconomic status (people with higher income, more education, and who are employed) have an
easier transition to parenthood (Margolis & Myrskyla, 2015). Finally, a meta-analysis of this literature
confirms the overarching trend—the transition to parenthood was associated with an initial rise in life
satisfaction with a subsequent decline. This meta-analysis also revealed that parents reported greater
positive emotion after their child was born than they did prior to becoming a parent (Luhmann et al.,
2012).
These findings regarding positive emotion are also consistent with evidence from daily experience
studies. In an experience sampling study comparing parents’ and nonparents’ emotions in their daily lives,
parents reported significantly more positive emotion and meaningful moments than nonparents (Nelson et
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al., 2013). Providing a conceptual replication of these results, other work found that parents report more
positive emotion and meaning in life during their time spent with children relative to their other daily
activities (Musick, Meier, & Flood, 2016; Nelson et al., 2013; Nelson-Coffey et al., 2017). These findings
may seem contradictory to a classic finding that childcare ranks relatively low in positivity (Kahneman et
al., 2004). In this study, a sample of working women (including both parents and nonparents) completed
the Day Reconstruction Method, recording all of their activities and emotions for an entire day. When
activities were rank-ordered by average positivity across the entire sample, childcare ranked close to the
bottom—below having sex, relaxing, and watching TV, among others, but above housework, working, and
commuting (Kahneman et al., 2004). Notably, however, this study included both parents and nonparents in
their analysis and did not account for whether or not people actually engaged in each of the given activities.
Thus, although this study provides preliminary insight regarding people’s feelings during childcare, it does
not provide conclusive evidence that childcare is significantly associated with lower emotional well-being
among parents. In subsequent studies including only parents, their emotions during childcare were
compared with their emotions during their other daily activities. In each of these studies, childcare was
associated with elevated positive emotion and meaning in life (Musick et al., 2016; Nelson et al., 2013;
Nelson-Coffey et al., 2017).
In sum, longitudinal and daily experience studies provide consistent support that parenthood could
be associated with elevated well-being—albeit temporarily. Conversely, the evidence from cross-sectional
studies is much less consistent. The conflicting evidence could be in part due to differences in statistical
approaches and sample characteristics. Indeed, evidence suggests that the association between parenthood
and well-being is moderated by a number of parent demographic (e.g., parent gender; Margolis &
Myrskyla, 2015; Musick et al, 2016; Nelson et al., 2013) and psychological (e.g., attachment style; NelsonCoffey
et al., 2017) characteristics, which may shed light on these conflicting findings (see Nelson et al.,
2014).
Individual differences. The happiness associated with parenthood depends in part on parents’ age,
gender, marital status, as well as their personality and attachment orientation. Indeed, a number of
demographic (e.g., gender) and psychological (e.g., attachment style) factors moderate the association
between parenthood and well-being. Although a full review of the many moderators of the association
between parenthood and well-being is outside the scope of this chapter, in this section I consider gender
and attachment style as important factors predicting parents’ well-being.
Gender. Evidence suggests that parenthood is more strongly associated with greater well-being for
fathers than for mothers. In one study of a nationally representative sample from the U.S., fathers were
happier than men without children, but mothers were no more or less happy than women without children
(Nelson et al., 2013). Consistent with these findings, other studies have found fatherhood to be associated
with well-being (Keizer, Dykstra, & Poortman, 2010; Kohler, Behrman, & Skytthe, 2005). Conversely,
studies comparing the relative well-being of mothers with women without children tend to find no
differences or a relative well-being deficit among mothers. In one study of Norwegian mothers over the
transition to parenthood, self-esteem decreased during pregnancy, increased around childbirth, followed by
a gradual decline over the course of 3 years (van Scheppingen, Denissen, Chung, Tambs, & Bleidorn, in
press).
One explanation for the gender differences in parents’ well-being may involve the nature of
mothers’ and fathers’ interactions with their children. Women tend to spend more time—and more time
alone (i.e., solo parenting)—with their children (Musick et al., 2016; Nelson-Coffey et al., 2017). In
addition, when mothers spend time with their children, they are relatively more likely to engage in basic
childcare, childcare management, cooking, and cleaning with their children, whereas fathers are more
likely to engage in play and leisure with their children (Musick et al., 2016). These gender differences in
how parents spend time with their children have implications for happiness as well. In this study, for
example, play (more common among fathers) was associated with the highest levels of well-being across
activities, whereas basic childcare and solo parenting (more common among mothers) were associated with
low levels of well-being (Musick et al., 2016). Other work suggests that mothers experience more guilt,
particularly in juggling caregiving and employment (Borelli, Nelson, River, Birken, & Moss-Racusin,
2017; Borelli, Nelson-Coffey, River, Birken, & Moss-Racusin, in press), suggesting another potential
pathway explaining mothers’ relatively lower levels of well-being.
Attachment. In addition to shaping people’s expectations and experiences in romantic
relationships, attachment style also shapes people’s experiences caring for their children (Jones, Cassidy, &
Shaver, 2015; Mikulincer & Shaver, 2016). Attachment avoidance is associated with greater stress in the
transition to parenthood (Rholes, Simpson, & Friedman, 2006), less reported closeness with children
(Rholes, Simpson, & Blakeley, 1995; Wilson, Rholes, Simpson, & Tran, 2007), and lower parenting
satisfaction (Cohen, Zerach, & Solomon, 2011; Rholes et al., 2011). Furthermore, two daily experience
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studies found that parents high in attachment avoidance reported fewer positive emotions while spending
time with their adult (Impett, English, & John, 2011) and young (Nelson-Coffey et al., 2017) children.
Together, this work suggests that attachment avoidance would be associated with relatively lower levels of
well-being among parents. In addition, attachment anxiety is associated with greater parent-child conflict
(Selcuk et al., 2010), greater parenting stress (Fernandes, Muller, & Rodin, 2012), and greater negative
emotion in parent-child interactions (River, Borelli, & Nelson-Coffey, 2016). Notably, however, in a daily
experience study, attachment anxiety did not differentially predict positive emotion, negative emotion, or
meaning during caregiving relative to parents’ other daily activities (Nelson-Coffey et al., 2017). Thus,
existing evidence more consistently indicates that parents’ high in attachment avoidance may experience
lower levels of well-being; however, more work is needed to disentangle the moderating role of attachment
anxiety in parents’ well-being.
Why is Parenthood Associated With Happiness (and Unhappiness)?
Drawing on evidence from cross-sectional, longitudinal, and daily experience studies, my
colleagues and I developed a model of parents’ well-being to illuminate the psychological factors that
predict happiness and unhappiness among parents (Nelson et al., 2014). According to this model, parents
report greater happiness when they experience elevated feelings of meaning in life, positive emotions,
psychological need satisfaction (i.e., autonomy, competence, and connectedness), and fulfillment of social
roles. Conversely, parents report less happiness when they experience elevated negative emotions, financial
strain, sleep disturbance, and lower relationship satisfaction.
Notably, not all pieces of this model have been thoroughly tested. Supporting the path to parents’
greater well-being, research reliably indicates that parents report elevated meaning in life (Nelson et al.,
2013; Nelson-Coffey et al., 2017; Umberson & Gove, 1989) and positive emotion (Deaton & Stone, 2014;
Musick et al., 2016; Nelson et al., 2013; Nelson-Coffey et al., 2017). Fewer studies have directly tested the
links between parenthood and psychological need satisfaction and fulfillment of social roles, although
indirect evidence supports that they would be important predictors of parents’ well-being. For example, one
study found that parenting efficacy, authenticity, and satisfaction with friendships and partner were
correlated with life satisfaction among mothers (Luthar & Ciciolla, 2015), providing suggestive evidence
for the importance of competence, autonomy, and connectedness, respectively. Furthermore, research
suggests that holding more social roles (Barnett & Hyde, 2001; Thoits, 1992) and feeling called to fulfill
those roles (Bellah, Madsen, Sullivan, Swidler, & Tipton, 1985) promotes well-being. Thus, parenthood
may be associated with improved well-being by providing parents with an additional social role or calling
to contribute to their identities.
Supporting the path to parents’ lower levels of well-being, research consistently indicates that
parents report relatively lower levels of relationship satisfaction (for meta-analyses see Luhmann et al.,
2012; Twenge, Campbell, & Foster, 2003), along with greater financial strain (Bird, 1997; McLanahan &
Adams, 1987; Ross & Van Willingen, 1996; Umberson & Gove, 1989; Zimmermann & Easterlin, 2006)
and sleep disturbance and fatigue (Chalmers & Meyer, 1996; Gay, Lee, & Lee, 2004; Lee, Zaffke, &
McEnany, 2000; Yamazaki, Lee, Kennedy, & Weiss, 2005). The evidence regarding parents’ experiences
of negative emotions, however, is somewhat inconsistent. Some evidence suggests that parents report
greater stress (Deaton & Stone, 2014), anger and frustration (Ross & Van Willingen, 1996; Simon & Nath,
2004), and depression (Evenson & Simon, 2005) compared with nonparents; however, another recent study
found that parents did not report greater negative emotion while they were spending time with their
children relative to their other daily activities (Nelson-Coffey et al., 2017). Notably, more work is needed to
better understand parents’ experiences of negative emotions, as well as replication of this latter finding.
Furthermore, the parents’ well-being model was developed based on a comprehensive review of the
literature and has therefore not been tested extensively. Future work investigating the predictors of parents’
happiness and unhappiness in a single study would be informative. In particular, such a study would
illuminate whether some factors are more important for parents’ happiness than others. For example, past
research indicated that positive emotions more strongly predict long-term well-being than negative
emotions (Coffey, Warren, & Gottfried, 2015; Cohn, Fredrickson, Brown, Mikels, & Conway, 2009;
Kuppens et al., 2008; Nelson, Layous, Cole, & Lyubomirsky, 2016). Accordingly, understanding whether
these patterns persist among parents is an important direction for future research.
Family Structure
Families come in all shapes and sizes, including biological, adoptive, and blended families, in
addition to parents in opposite-sex or same-sex partnerships. Accordingly, it is important to consider the
association between parenthood and well-being in light of the variety of family structures (Caballo,
Lansford, Abbey, & Stewart, 2001).
429
Adoptive and blended families. Little research focuses on understanding how the well-being of
adoptive and step-parents compares with parents in other family structures. Adoptive parents may be
coping with infertility, managing intrusive adoption screening, and perhaps even coping with societal
discrimination and stigmatization (Bird, Peterson, & Miller, 2002; Caballo et al., 2001), which might
predict lower levels of well-being among this group of parents. Notably, however, existing studies do not
provide conclusive evidence for differences in the psychological well-being of adoptive and biological
parents (Caballo et al., 2001; O’Brien & Zamostny, 2003). For example, one study compared a group of
adopted children and their parents with a matched sample of biological children and parents from the
National Survey of Families and Households. In this study, biological and adoptive parents did not differ in
their reports of happiness or depressive symptoms (Borders, Black, & Pasley, 1998). In addition, other
studies found no differences between biological and adoptive parents in stress, health, or self-esteem
(Mainemer, Gilman, & Ames, 1998; Ternay, Willborn, & Day, 1985).
Research comparing stepparents to other family structures is similarly inconclusive. For example,
one study found that stepparents reported lower parenting satisfaction than biological parents (Rogers &
White, 1998), but another study found no differences between stepparents and biological parents in
symptoms of depression, life satisfaction, and self-esteem (Lansford, Ceballo, Abbey, & Stewart, 2001).
Finally, research comparing the well-being of biological, step-, and adoptive parents indicates that factors
associated with family processes (e.g., family cohesion) are stronger predictors of well-being than objective
family structure (Lansford et al., 2001).
Same-sex partnership. Most research on parents’ sexual orientation has focused on child
outcomes. These studies generally do not find any harmful consequences of being raised by parents in
same-sex relationships in terms of children’s gender behavior and preferences, sexual behavior and
preferences, or mental health (Stacey & Biblarz, 2001). Very few studies have investigated the relative
happiness of parents and nonparents in same-sex marriages or partnerships. Parents in same-sex
partnerships may face stigmatization, difficult adoption proceedings, or other challenges in becoming
parents that might indicate low levels of well-being. However, existing research suggests the reverse:
Parents in same-sex partnerships tend to report relatively high levels of well-being. One review of this
literature noted that lesbian mothers reported fewer depressive symptoms and greater self-esteem than
heterosexual mothers (Stacey & Biblarz, 2001). Similarly, one study of fatherhood in Israel found that gay
fathers reported higher levels of life satisfaction than heterosexual fathers (Erez & Shenkman, 2016).
Another study found that the self-perceived parental role—which involves multiple aspects of parent
identity, including investment, competence, integration with other life domains, and satisfaction—was
associated with meaning in life among gay, but not heterosexual, fathers in Israel (Shenkman & Shmotkin,
2016). Finally, psychological need satisfaction within one’s relationship was associated with greater levels
of personal growth among lesbian mothers, but not heterosexual mothers (Shenkman, in press). These
studies provide preliminary evidence that parents in same-sex relationships do not report reduced wellbeing,
and may even experience elevated well-being in comparison to heterosexual parents. Notably,
however, much of this research relied on Israeli samples (where same-sex marriage is not legally
recognized and attitudes towards same-sex relationships may differ from other cultures). Accordingly,
more work is needed to evaluate how sexual orientation is related to parents’ well-being in other cultures.
Summary
In sum, researchers have drawn on a variety of methodological approaches to investigate the
association between parenthood and well-being. Cross-sectional studies have reached conflicting
conclusions about whether parents are more or less happy than nonparents, but longitudinal and daily
experience studies have more consistently indicated a happiness benefit (albeit temporary) for parents. In
addition, recent work has focused more on understanding why and for whom parenthood is associated with
happiness (e.g., Nelson et al., 2014). Furthermore, despite changing trends in family structures, evidence
does not suggest that parenting in the context of adoptive, blended, or same-sex partnerships is associated
with detriments to parents’ well-being.
Concluding Remarks
As some of the most important and significant aspects of people’s lives, family relationships—
particularly marriage and parenthood—have important implications for individuals’ happiness. However,
much remains to be learned about how and why marriage and parenthood are related to well-being. In this
chapter, I suggested potential mechanisms linking marriage and parenthood to well-being, and provided
suggestions for future research on these topics. In particular, studies aiming to understand how and why
marriage is associated with happiness would be informative. Furthermore, an important direction for
research on parenthood and well-being will be to consider parenthood as a dynamic process that unfolds
over time, rather than a static identity. Finally, research considering strategies people can use to improve
430
their marriages and relationships with their children, along with whether and how such strategies improve
happiness, would be illuminating. Thus, nurturing one’s family relationships may offer people
opportunities to live happy and fulfilling lives.
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2018 Ed Diener. Copyright Creative Commons: Attribution, noncommercial, no
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LIFE DOMAINS
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Work, the Work-Family Interface, and Subjective Well-being
By Michael Ford, Yi-Ren Wang, & Youjeong Huh, University of Alabama
Citation
Ford, M., Wang, Y.-R., & Huh, Y. (2018). Work, the work-family interface, and subjective well-being.
In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
Work is a significant contributor to subjective well-being (SWB) among working people and their
families. Chronic, structural work conditions and discrete emotionally-charged events have potential to
influence SWB via job satisfaction, affective states experienced at work, and spillover of work into family
life. In this chapter we review cumulative empirical findings on the relationship between SWB and a)
characteristics of the work that people perform, b) social support and leadership at work, c) fairness and
mistreatment at work, d) perceived characteristics of one’s employing organization, and e) the work-family
interface. Also considered are emerging research questions about the dynamics and causal directions
among work and SWB, the integration of and recovery from work and other life roles (e.g., family),
empirical findings taking a global perspective on work and SWB, and the role of precarious employment
arrangements and unemployment in worker SWB. Empirical results indicate that factors from each of
these areas correlate with SWB, although some are more predictive than others, and results vary across
dimensions of SWB. Furthermore, questions remain about causal relationships and temporal dynamics
among work and SWB and differences across cultures and regions of the world. As science continues to
accumulate on SWB, the role of work will continue to be better understood alongside other life factors.
Working people spend the majority of their waking hours on the job, and the characteristics of their
jobs and work situations vary in systematic ways that contribute to their quality of life and well-being.
Work also tends to spill over into other areas of life, which has additional implications for well-being and
functioning in family and other life domains. Relatedly, there is increasing pressure in many societies to
sacrifice family and leisure in order to respond to work-related pressures. Thus, a complete understanding
of subjective well-being needs to incorporate the experiences and chronic conditions that characterize work
life. What are these experiences and working conditions that contribute to subjective well-being (SWB)
and which are most important? And how are these structured and organized?
Fortunately, there is large literature with many replicable findings on the work-related factors that
contribute to SWB. In this chapter we review major models and empirical findings on the relationship
between work and SWB. We also consider the spillover of work into other areas of life, especially family.
To be comprehensive, we will start by describing the structure of empirical models linking work to SWB.
This will be followed by a discussion of specific findings on the relationship between SWB and job
characteristics, the work context, and the work-family interface. Finally, empirical findings and
unanswered questions on emerging topics will be considered.
The primary focus of our review across these topics will be on the effects of the work situation on
SWB. With that said, there are many variables at the individual level such as personality traits, coping
behaviors, and appraisal processes that may moderate the effects of work-related factors. These are
covered extensively in other chapters within this handbook and can be applied to work as well as to other
life domains. Because income and finances are covered in detail in other chapters within this volume, our
chapter will focus mainly on nonfinancial factors, and will address financial factors only to the extent that
they influence SWB via other mechanisms (e.g., perceived fairness, supportiveness, precarious
employment). Finally, unless otherwise noted, the core sections of this review will focus on evidence that
has accumulated over many studies and has been reported in meta-analyses. The section on new and
emerging topics will also discuss a mixture of evidence from meta-analyses and individual studies.
Empirical Approaches to Work and Subjective Well-being
Before delving into the specific work-related factors in SWB, it is important to consider the general
structure of these factors and linkages to more general models of SWB. As noted in other chapters of this
Handbook, the basic structure of SWB includes overall summary evaluations of one’s life, such as life
satisfaction and satisfaction with specific life domains (e.g., health, work, family), as well as one’s
emotional experiences, such as positive and negative affective states (Diener, 2013). There is general
support for the notion that these three dimensions, namely satisfaction, positive emotions, and negative
emotions, are related but also distinct (Diener, 2013).
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Similar to overall SWB, work-related SWB is structured into overall summary evaluations of one’s
job and emotional states experienced in response to work. Accordingly, the contributions of work to
overall SWB are primarily through their influence on a) job satisfaction, and b) emotional experiences at
work. Affective Events Theory (AET) (Weiss & Cropanzano, 1996) specifies this distinction and its
implications for work-related antecedents. From the perspective of AET, structural work conditions that
are relatively stable from day to day, such as one’s job duties, organizational procedures, and pay and
benefits, influence the stable component of one’s job satisfaction. This stable component of job
satisfaction tends to change primarily as a function of major changes to one’s work situation, such as a pay
raise, promotion, or a reorganization of one’s job duties. On the other hand, there are discrete work events
that come and go on a daily level. These might include interactions with customers or supervisors, task
accomplishments and failures, or layoffs in the organization. Discrete events trigger positive and negative
emotions that also vary daily, and in turn contribute to daily variance in job satisfaction. Thus, the
determinants of job satisfaction include chronic features of work that are relatively stable over time as well
as discrete work events that vary from day to day or even from moment to moment. Likely for this reason,
there is extensive evidence that job satisfaction and work-related affect are partially stable and partially
variable over time (Ilies & Judge, 2002; Judge & Ilies, 2004).
The primary contribution of work to general SWB is through job satisfaction, which represents an
overall psychological response to one’s job, comprises cognitive and affective components (Hulin & Judge,
2003), and reflects the extent to which work meets the values and needs that are important to the worker
(Locke, 1976). The correlation between job and life satisfaction has been found to be approximately .40
(Bowling, Eschleman, & Wang, 2010; Michel, Mitchelson, Kotrba, LeBreton, & Baltes, 2009; Erdogan,
Bauer, Truxillo, & Mansfield, 2012), while correlations between job satisfaction and general positive and
negative affect are estimated at .38 and -.27, respectively (Bowling, Eschleman, & Wang, 2010). Thus, the
factors at work that contribute to job satisfaction should in turn influence overall life satisfaction. Work can
also contribute to SWB independent of job satisfaction through its direct influence on other areas of life. In
particular, work can influence family life in negative and positive ways (Ford, Heinen, & Langkamer,
2007; Greenhaus & Powell, 2006), and this influence on family life should further contribute to overall
SWB (Michel et al., 2009; Erdogan et al., 2012). The effects of work on one’s health should also play a
role in SWB. There is extensive evidence that working conditions correlate with and predict self-reported
physical symptoms (Nixon, Mazzola, Bauer, Krueger, & Spector, 2011), which in turn contribute to SWB.
Thus, work can contribute to SWB via job and family satisfaction as well as through one’s health.
With empirical models of work and SWB in mind, we now consider established empirical findings
on the relationship between SWB and a) the work itself, which refers to the features of the tasks that
individuals perform; b) the work context, which refers to the social context of work and the employeeorganization
relationship; and c) the work-family interface, which refers to the influence of work on family
life.
Established Research Findings
Research on work and SWB has yielded a large body of cumulative knowledge about the predictors
of SWB from the work domain and the work-family interface. The research findings that have been
synthesized in meta-analyses will be the focus of this section. These findings are primarily based on crosssectional
correlations between self-reported working conditions and experiences and self-reported
measures of job satisfaction, life satisfaction, and/or indicators of affective well-being such as positive
affect, negative affect, stress, emotional exhaustion, or fatigue. Concerns about causality and endogeneity
in these effects warrant consideration and will be visited later in this chapter. However, when possible, we
will also discuss available evidence from individual studies on specific effects that have been studied
longitudinally.
The Work Itself
Some of the most robust predictors of job satisfaction, and in turn overall SWB, are characteristics
of the work itself that workers perform. Much of the initial research on the work-related predictors of job
satisfaction was inspired by the human relations approaches to management that emerged in the 1960s and
1970s (e.g., McGregor, 1960) as alternatives to the rigid specialization, division of labor, and chain of
command characteristic of traditional bureaucratic approaches to work organization. Human relations
approaches emphasized the importance of enjoyable, interesting, and enriching work for developing a
satisfied and motivated workforce. Around the time of this change in thinking among management
scholars, knowledge and theory were also being developed on employee workload and its impact on work
role stress (Kahn, Wolfe, Quinn, Snoek, & Rosenthal, 1964).
The most influential of the human relations approaches was the job characteristics model
(Hackman & Oldham, 1976), which specified five characteristics of work that improve motivation and
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satisfaction. These are as follows: a) job autonomy, or the freedom to decide what to do and how and when
to do it; b) skill variety, or the opportunity to perform different types of tasks and use one’s different
capabilities; c) task significance, or the chance to perform work that is personally meaningful and
contributes to important outcomes; d) task identity, or the opportunity to create discrete products that one
has ownership over; and e) feedback, or information about how one is doing that comes directly from the
job itself rather than from someone else such as a supervisor. The opportunity to work with others is also
sometimes considered within this framework. Early meta-analytic estimates of the correlations between
each of these factors and job satisfaction ranged from .20 to .34 (Loher, Noe, Moeller, & Fitzgerald, 1985;
Fried & Ferris, 1987). More recent estimates are similar, ranging from .23 for task identity to .37 for
autonomy (Humphrey, Nahrgang, & Morgeson, 2007). With respect to affective subjective well-being,
results for these dimensions are less clear. Job autonomy (r = -.18), feedback ( r = -.15), and task identity ( r
= -.13), have been found to predict lower job stress, whereas skill variety (r = -.10, ns) and task
significance have not (r = .04) (Humphrey et al., 2007). Anxiety has also been found to be negatively
related to autonomy (r = -.08) and feedback ( r = -.26), but not to the other dimensions. As such, it appears
that the job characteristics are better predictors of job satisfaction than of affective well-being at work.
There has also been surprisingly little research investigating the direct relationship between these job
characteristics and life satisfaction, although a moderately positive relationship might be inferred via
relationships with job satisfaction.
Some individual studies have investigated the effects of job characteristics and SWB
longitudinally. This work has usually either a) examined reciprocal relations among the job characteristics
and SWB via multi-wave panel design, or b) investigated the effects of job characteristics via intervention
and quasi-experimentation. Individual studies have found that increases in some of these job
characteristics were followed by increases in job satisfaction and affective well-being (Holman & Axtell,
2016; Morgeson & Campion, 2002), although such job enrichment can also increase training requirements
and workload. Results from longitudinal panel designs have been more mixed (e.g., de Jonge, Dormann,
Janssen, Dollard, Landeweerd, & Nijhuis, 2001; Mauno, Kinnunen, & Ruokolainen, 2007), suggesting that
the effects of job characteristics on subsequent change in SWB are not as well understood.
Another prominent feature of the work itself that is worth considering is workload, which has been
the subject of hundreds of individual studies. Workload generally refers to the amount and difficulty of
one’s work (Bowling & Kirkendall, 2012) and is treated as a subjective, continuous variable. Workload
has been found to be negatively correlated with job satisfaction (r = -.18) and positively correlated with
distress, depression, fatigue, and emotional exhaustion (r = .21, .17, .10, and .38, respectively), but
unrelated to life satisfaction (r = -.01) (Bowling, Alarcon, Bragg, & Hartman, 2015). Because workload is
sometimes associated with higher pay and status, the negative effect of workload on life satisfaction via
lower job satisfaction may be offset to some degree. Still, there is a robust relationship between workload
and negative affective states. As discussed later in this chapter, workload has been shown to predict
subsequent increases in negative affective states in longitudinal panel studies (Ford, et al., 2014), although
these effects have been found to vary substantially across studies.
In summary, it is clear that enriching job characteristics are associated with more positive levels of
job satisfaction, which likely results in more positive levels of life satisfaction. Job enrichment
characteristics are less consistently related to the negative affective components of SWB, however. On the
other hand, workload is associated with negative affective states and lower job satisfaction, but not with
overall life satisfaction, perhaps because of the pay and status that accompanies high workloads in many
jobs. Individual studies also suggest that job enrichment and workload are associated with some changes in
well-being, although these longitudinal effects do not appear to be as robust.
The Work Context- Leadership and Social Support from Others at Work
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Although the work itself is a strong determinant of job satisfaction and affective well-being at work,
the social context within which the work is performed has received as much, if not more, empirical research
attention. By social context, we are referring to the support workers received from others and the
organization at large, the fairness and respect with which individuals perceive they are treated, and
qualities of leadership in the organization.
Social support at work refers to instrumental (e.g., receiving help with work tasks) and emotional
(e.g., having someone to talk with about personal or professional problems) assistance from others, usually
supervisors or coworkers. Supportive supervisors can be important for well-being because they have
control over resources and decisions that affect an employee, while supportive coworkers can be important
because of the frequency with which workers interact with them in many jobs. Meta-analyses indicate that
social support at work is a moderately strong predictor of job satisfaction (r = .24), and a weaker, but
significant predictor of life satisfaction (r = .14) (Viswesvaran, Sanchez, & Fisher, 1999). A more recent
review separating the sources of support suggests an even stronger relationship between coworker support
and job satisfaction, after correcting for unreliability in the measures (r = .40) (Chiaburu & Harrison,
2008). Supportive supervision or leadership, which comprises several specific forms of leadership, has
shown similar cross-sectional effects (r = .42) (Chiaburu & Harrison, 2008). When comparing types of
social support, emotional or affective support from coworkers has been found to be a stronger predictor of
job satisfaction (r = .34) than is instrumental support (r = .24) (Chiaburu & Harrison, 2008). Regarding
affective well-being, there is meta-analytic evidence that supervisor support (r = -.28) and coworker
support (r = -.23) are negatively related to emotional exhaustion or fatigue, suggesting supervisor support
has a slightly stronger protective effect against negative emotions than does coworker support
(Halbesleben, 2006). Individual longitudinal studies have also suggested that social support at work
predicts increases in SWB, particularly when stressor levels are high (de Lange, Taris, Kompier, Houtman,
& Bongers, 2004; Dormann & Zapf, 1999; ter Doest & de Jonge, 2006).
Leadership, which overlaps some with social support but includes several distinct constructs, is also
an important factor in worker SWB. The most prominent leadership models that have been studied in
predicting SWB at work are those involving leader behaviors, transformational/charismatic leadership
phenomena, and the exchange relationship between leaders and their subordinates.
Behavioral approaches to leadership focus on the behaviors that leaders engage in, usually in
reference to the supervisor. Most leader behaviors that are directly relevant for subordinate well-being fall
within two general dimensions: a) relational, sometimes referred to as “consideration”, and b) taskoriented,
sometimes referred to as “initiating structure” (Fleishman, Mumford, Zaccaro, & Levin, 1991;
Yukl, Gordon, & Taber, 2002). Relational behaviors, which involve showing concern for the subordinate’s
well-being, are moderately strong predictors of subordinate job satisfaction (r = .40), well-being (r = .28),
and negative affective states (r = -.20 to -.21), whereas task-oriented behaviors, which involve providing
clear instructions and guidance, are also positively, but not as strongly, related to job satisfaction (r = .19)
and show small but significant negative relationships with negative affective states (r = -.09 to -.17) (Judge,
Piccolo, & Ilies, 2004; Montano, Reeske, Franke, & Huffmeier, 2017). Such correlations in longitudinal
studies have generally been smaller in size but still significant (Judge et al., 2004), although there is not a
strong body of research on behavioral leadership and subsequent changes in subordinate SWB. Other
leader behaviors that facilitate team processes, coordination, and cohesion may also contribute to SWB
(Zaccaro, Rittman, & Marks, 2001), as may strategic behaviors by which leaders organize work tasks, but
empirical results linking these behaviors to SWB have yet to be systematically structured and compiled.
Research on transformational/charismatic leadership focuses more on the inspirational processes
through which leaders influence followers to meet and exceed expectations (Bass & Avolio, 1994). This
work has differentiated transformational leadership from transactional leadership. Transformational
leadership involves behaviors and processes that provide a purpose and vision for subordinates, stimulate
followers intellectually, consider the needs of individual subordinates, and provide a role model that
followers want to identify with. By contrast, transactional leadership involves providing clear expectations
and rewards for meeting those expectations, and intervening to correct problems before they escalate.
Research has found that both forms of leadership are strong predictors of worker job satisfaction, with
correlations corrected for unreliability of .58 for transformational leadership and .64 for the dimension of
transactional leadership involving the provision of contingent rewards (Judge & Piccolo, 2004). By
contrast, laissez-faire leadership, which refers to the leader being absent from important leadership
functions, is negatively correlated with job satisfaction (r = -.28). Transformational leadership is also
positively related to psychological well-being (r = .27) and negatively related to negative affective states ( r
= -.16 to -.18) (Montano et al., 2017). Longitudinal research on these leadership factors and subordinate
SWB has been sparse, however, and some individual studies have found little effect of transformational
leadership on subsequent well-being after controlling for baseline effects (Nielsen, Randall, Yarker, &
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Brenner, 2008; Nielsen & Munir, 2009; Tafvelin, Armelius, & Westerberg, 2011). Thus, although people
who report having transformational leaders also report better SWB, it is not clear that transformational
leadership predicts increases in SWB.
The quality of the dyadic exchange relationship between workers and their leaders or supervisors,
termed leader-member exchange, is also an important factor in job satisfaction, and thus in SWB. Lowexchange
relationships between workers and their supervisors are characterized by the formal exchange of
pay for performance, whereas high-exchange relationships involve trust, social support, respect, and
mutual obligation between leader and follower that goes beyond formal role requirements (Graen & UhlBien,
1995). Not surprisingly, leader-member exchange quality as reported by the subordinate has been
found to correlate strongly with job satisfaction (r = .42) (Dulebohn, Bommer, Liden, Brouer, & Ferris,
2012) and is also a predictor of subordinate well-being (r = .39) and negative affective states (r = -.25 to .27)
(Montano et al., 2017). Leader-member exchange from the perspective of the subordinate has also
been found to predict increases in job satisfaction longitudinally (Volmer, Niessen, Spurk, Linz, & Abele,
2011). Recent meta-analytic work has shown leader-member exchange to be highly correlated with leader
behavioral dimensions (Gottfredson & Aguinis, 2016), suggesting that leader behaviors may influence
SWB in part through high quality leader-member exchange relationship. One notable characteristic of this
research is that it has primarily focused on leader-member exchange from the perspective of the
subordinate. Leader perceptions of leader member exchange have been found to also be correlated with
subordinate job satisfaction, although not nearly as much so (Cogliser, Schriesheim, Scandura, & Gardner,
2009).
In summary, supportive and task-oriented leader behaviors, inspirational leadership processes, and
high quality trusting and respectful relationships between leaders and subordinates are relatively strong
contributors to job satisfaction and should in turn relate to life satisfaction and general affect. As with the
work itself, we lack cumulative evidence about the direct relationships between leaders and SWB,
including life satisfaction and general life affect, but an effect can likely be inferred via the sizeable
observed relationships with job satisfaction and work-related affective states. Individual longitudinal
studies also suggest that social support and LMX predict future SWB after controlling for baseline levels.
The Work Context- Fairness, Civility, and Mistreatment
Some of the most powerful emotional experiences at work involve situations in which workers are
mistreated in some way. This mistreatment could be in the form of unfair policies, procedures, or pay;
rude, uncivil, or aggressive interactions with customers, coworkers, or supervisors; or even abusive
supervision. Because these experiences are so affectively charged, they have been studied more
extensively at the event level and as predictors of affective well-being, although there is also a substantial
body of research linking these factors to job satisfaction.
Fairness has received a large amount of empirical attention as a predictor of worker satisfaction and
affect. This work has most commonly drawn from theory on organizational justice, which has a variety of
historical and scholarly origins (Rupp, Shapiro, Folger, Skarliki, & Shao, 2017). Although debates about
the structure of organizational justice remain, there has been general convergence on at least three
dimensions of justice in organizations, namely distributive justice, procedural justice, and interactional
justice.
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Distributive justice refers to the fairness of pay and other valued outcomes, and is heavily influenced
by principles of equity (Adams, 1965), which suggest that rewards should be distributed in a manner
proportionate to one’s value. Procedural justice refers to fairness of the procedures by which decisions in
the organization are made. Procedural justice incorporates factors such as the control that workers have
over decision-making processes, the consistency, lack of bias, and ethics in decision-making processes, and
the opportunity to correct inappropriate decisions (Leventhal, 1980; Thibaut & Walker, 1975).
Interactional justice refers to the disclosure of information and explanations to workers about decisionmaking
processes as well as the treatment of employees with respect and dignity (Bies & Moag, 1986).
Interactional justice has also been empirically differentiated into informational justice, which refers to the
sharing of information, and interpersonal justice, which refers to treatment with respect and dignity
(Colquitt, 2001).
Distributive ( r = .39 to .46), procedural ( r = .40 to .51), and interactional ( r = .44) justice have all
been found to be strong correlates of job satisfaction (Cohen-Charash & Spector, 2001; Colquitt, Conlon,
Wesson, Porter, & Ng, 2001). Regarding affect, recent meta-analyses have found correlations of
procedural, distributive, interpersonal, and informational justice with positive affect of .39, .34, .29, and
.32, respectively, and correlations with negative affect of -.30, -.32, -.27, and -.23, respectively (Colquitt et
al., 2013). Other meta-analyses found similar relationships between perceived unfairness and stress (r =
.27), burnout (r = .30), and negative affective states (r = .31) (Robbins, Ford, & Tetrick, 2012). Still,
individual longitudinal studies on the effects of fairness on subsequent changes in SWB have resulted in
mixed findings. In one study, low SWB (depressive symptoms) predicted subsequent reductions in
fairness perceptions, but fairness did not predict subsequent changes in SWB (Lang, Bliese, Lang, & Adler,
2011). However, two other studies (Elovainio et al., 2015; Ybema & van den Bos, 2010) found the
opposite, with perceived fairness having stronger effects on subsequent changes in SWB.
Interpersonal mistreatment from others at work has also been studied as a predictor of SWB. This
research can generally be divided into three broad and related constructs: workplace aggression, incivility,
and harassment (sexual or otherwise), although there is still some debate about this structure (Hershcovis &
Barling, 2010). Aggression refers to intentional efforts by individuals in organizations to harm others in
the organization (Neuman & Baron, 1998). Aggression from supervisors is a stronger predictor of job
satisfaction (r = -.32) than is coworker aggression ( r = -.20) (Hershcovis & Barling, 2010), although both
are predictive. Supervisor and coworker aggression also predict distress (r = -.28 and -.21, respectively)
and depression (r = .24 and .18, respectively) (Herscovis & Barling, 2010). Workplace incivility refers to
behavior that is disrespectful but unclear in its intent (Anderson & Pearson, 1999; Cortina, Magley,
Williams, & Langhout, 2001). There has not been a meta-analysis of cumulative findings on incivility and
SWB, but coworker antagonism, which combines incivility and aggression, shows effects similar to those
for aggression (r = -.23) (Chiaburu & Harrison, 2008). Destructive leadership, which encompasses a
variety of related constructs involving leader behavior that is harmful to followers such as abusive
supervision, social undermining, and petty tyranny, is negatively related to follower job satisfaction (r = .34)
and is also related to positive affect (r = -.09), negative affect (r = .34), stress (r = .24), and overall
well-being (r = -.35) (Schyns & Schilling, 2013). Other reviews have found that workplace harassment,
which has been defined as rather similar to workplace aggression and refers to interpersonal behavior that
intentionally harms another at work, is related to job satisfaction (r = -.32), life satisfaction ( r = -.18),
anxiety (r = .25), depression (r = .28), positive emotions (r = -.21), and negative emotions (r = .38)
(Bowling & Beehr, 2006), while sexual aggression has been found to also predict lower job satisfaction (r =
-.32). Research has suggested that some types of civility training can improve job satisfaction and reduce
burnout (Leiter, Laschinger, Day, & Gilin-Oore, 2011), but longitudinal research on interpersonal
mistreatment and SWB has been relatively uncommon (Cole, Shipp, & Taylor, 2016).
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In summary, experiences by workers that violate norms of fairness, respect, and the avoidance of
harm tend to trigger dissatisfaction and negative emotions, and thus represent a significant contributor to
SWB when they occur. These experiences can include unfair pay and procedures as well as various forms
of interpersonal mistreatment. Still, longitudinal research in this area has been relatively uncommon and
has yielded some mixed findings on the temporal precedence of mistreatment and SWB.
The Work Context- The Organization
Some work experiences are driven by policies, procedures, and practices that originate at the
organizational level. These include more formal human resource (HR) policies, practices, and procedures,
as well as those that are more informal in the organization. These policies, practices, and procedures give
rise to employee perceptions about the organization’s climate and priorities. Furthermore, experiences that
are attributed to the organization at large influence attitudes and beliefs about the organization that also
predict well-being.
Human resources practices that are relevant for employee SWB include training adequacy,
compensation level, grievance processes, performance appraisal systems, reward and incentive systems,
participation in decision-making, employment security, and the sharing of information with employees
(Combs, Liu, Hall, & Ketchen, 2006). These practices influence the extent to which workers have the
knowledge, skill, ability, and motivation to perform their work at a high level (Combs et al., 2006), and
have been found to correlate with indicators of SWB at the collective level (r = .25 to .33 with a
combination of motivation, commitment, and job satisfaction) (Jiang, Lepak, Hu, & Baer, 2012). Another
meta-analysis found a similar relationship between HR practices and job satisfaction at the individual level
(r = .27) (Kooij, Jansen, Dikkers, & de Lange, 2010), although there has been little longitudinal research on
these effects. Job insecurity alone has been found to predict job satisfaction (r = -.32) and mental health ( r
= -.19) as well (Sverke, Hellgren, & Naswall, 2002). One study also found that job insecurity predicted
increases in mental health complaints over time (Hellgren & Sverke, 2003). Family-friendly HR practices
have also been studied more extensively and will be discussed later in the context of the work-family
interface.
Other research has focused on organizational or group climate, which refers to shared perceptions of
the organization’s (or group’s) policies, practices, and priorities (Schneider, Ehrhart, & Macey, 2013).
These perceptions can emerge as a function of HR practices, shared experiences, leader behavior, and
interactions among workers (Gonzalez-Roma, Peiro, & Tordera, 2002; Rogg, Schmidt, Shull, & Schmitt,
2001; Zohar, 2000). Organizational climates usually have a referent such that organizations have a climate
“for” something. Some referents are broad (e.g., social relations, empowerment) while others are more
specific (e.g., safety, customer service, mistreatment, justice). Organizational or group climate variables
can be operationalized at the collective level by taking the average of individual perceptions, or at the
individual level by using each worker’s individual ratings as a predictor or outcome. The latter of these is
sometimes referred to as psychological climate because it technically is not an organizational-level
variable. Accordingly, climate can be studied as a predictor and determinant of SWB at the individual or
collective level, dependent on the study’s level of analysis.
Research has found that climate for broad factors such as positive social relationships, involvement
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in employees in organizational processes, employee development and autonomy, rewards, and freedom
from organizational formality and constraints correlate strongly with job satisfaction (r = .33 to .46), but
not as strongly with direct indicators of well-being (r = .07 to .17) (Carr, Schmidt, Ford, & DeShon, 2003).
More specific climate dimensions also predict indicators of SWB. Climate for civility (r = .53) and climate
against mistreatment/aggression (r = .43 to .52) are strong predictors of job satisfaction (Yang & Caughlin,
2017). Climate for employee safety also predicts job satisfaction (r = .34) and general well-being (r = .30)
(Clarke, 2010), while climate for customer service has been found to be a strong predictor of job
satisfaction at the unit (i.e., work group) level (r = .51) (Hong, Liao, Hu, & Jiang, 2013). It should be noted
that unit-level correlations tend to be stronger than those at the individual level. There has been very little
longitudinal research on organizational climate and SWB from an individual or group level of analysis.
Beliefs about and toward one’s employer, which theoretically are in part the result of work
experiences and policies, are more proximal predictors of worker SWB. Perceived organizational support,
which reflects one’s descriptive belief about the extent to which the organization values employee
contributions and cares about their well-being (Eisenberger, Huntington, Hutchison, & Sowa, 1986), is a
strong predictor of job satisfaction (r = .57) as well as stress (r = -.38) and emotional exhaustion ( r = -.42)
(Kurtessis et al., 2017). Affective commitment toward the organization, which refers to an emotional
attachment to one’s employer, is a very strong predictor or correlate of job satisfaction as well (r = .65,
corrected), and a weaker but significant predictor of stress (r = -.21) (Meyer, Stanley, Herscovitch, &
Topolnytsky, 2002). By contrast, organizational cynicism is a strong negative predictor of job satisfaction
(r = -.50) (Chiaburu, Peng, Oh, Banks, & Lomeli, 2013). There has been very little longitudinal research on
the relationship between these variables and SWB, perhaps in part because they are often both considered
outcomes of the working conditions described earlier.
In summary, the perceptions of and beliefs about the organization that employees develop tend to be
strong predictors of job satisfaction and in turn significant predictors of SWB. The quality of the job itself
and the social context of work, which were discussed earlier, help to inform these perceptions and beliefs.
Thus, beliefs and feelings about the organization represent potentially more proximal factors of job
satisfaction and SWB, helping to explain the influence of more distal factors. Still, there has been very
little longitudinal research on relationship between perceptions of the organization and SWB.
The Work-Family Interface
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The interface between work and other areas of life, especially family, contributes to worker SWB
beyond what happens at work. Work and family are to some degree mutually incompatible for many
workers. The hours spent at work detract from the time workers can spend at home, and stressful work
experiences can spill over and influence the quality of family life. At the same time, work can provide
positive affective experiences, skills, and self-beliefs that are instrumental toward a better family life.
Therefore, via the work-family interface, work can influence both job satisfaction and family satisfaction,
thus further contributing to overall SWB.
Work-family conflict, which refers to the mutual incompatibility of work and family (Greenhaus &
Beutell, 1985), has been theorized and shown to be bidirectional, with work stressors and demands making
family life more difficult (i.e., work interference with family or WIF) and family stressors and demands
making work life more difficult (family interference with work or FIW) (Frone, Russell, & Cooper, 1992).
Role stressors from work such as workload, long hours, and stressful social situations, predict higher levels
of WIF, whereas family stressors and demands such as childcare responsibilities or marital discord predict
higher levels of FIW (Byron, 2005). Furthermore, support from coworkers, supervisors, and the
organization predicts lower levels of WIF, while that from family members predicts lower FIW (Byron,
2005).
Work-interference with family in turn predicts lower family satisfaction ( r = -.18 to -.20) and job
satisfaction (r = -.25 to -.26), as does family interference with work ( r = -.21 to -.22 for family satisfaction
and -.11 to -.14 for job satisfaction) (Amstad, Meier, Fasel, Elfering, & Semmer, 2011; Ford, Heinen, &
Langkamer, 2007; Shockley & Singla, 2011). Furthermore, WIF and FIW predict life satisfaction, with the
effects of WIF (r = -.30) stronger than those of FIW ( r = -.20) (Michel et al., 2009). Work-family conflict
also predicts the affective components of SWB, including psychological strain (r = .35 for WIF and .21 for
FIW), depression (r = .23 for WIF and .22 for FIW), stress ( r = .54 for WIF and .39 for FIW), and anxiety
(r = .14 for WIF and .19 for FIW) (Amstad et al., 2011). Interestingly, WIF has been shown to predict life
satisfaction independent of its relationships with job and family satisfaction (Michel et al., 2009),
suggesting the work-family interface predicts overall SWB beyond satisfaction with specific life domains.
Individual analyses have also found work-family conflict to predict life satisfaction over a 9-year period
after controlling for baseline life satisfaction, with these effects mediated by job and marital satisfaction
(Cho & Tay, 2016).
The positive spillover among work and family, often labeled as work-family enrichment
(Greenhaus & Powell, 2006), is also bidirectional. Theory on the work-family interface suggests that
skills, knowledge, self-beliefs, social capital, and material resources gained from each life domain benefit
other life domains, giving rise to work-family and family-work enrichment (Greenhaus & Powell, 2006).
Research has shown that work-to-family enrichment predicts higher job satisfaction (r = .27 to .37), family
satisfaction (r = .11 to .18), and overall life satisfaction ( r = .26), while family-to-work enrichment also has
significant effects on job satisfaction (r = .16 to .22) and family satisfaction ( r = .31 to .34) (McNall,
Nicklin, & Masuda, 2010; Shockley & Singla, 2011). In the longitudinal study cited earlier (Cho & Tay,
2016), family-to-work enrichment was also found to predict life satisfaction 9 years later after controlling
for baseline levels.
Given the apparent importance of the work-family interface, results have accumulated from studies
on supportive work-family policies in organizations. Such policies include flexible work arrangements,
dependent care assistance, and family-supportive supervision and organizational climates. It has been
found that flexible work arrangements (e.g., flextime, telework availability) are only modestly related to
lower work interference with family (r = -.11) and unrelated to family interference with work ( r = -.03)
(Allen, Johnson, Kiburz, & Shockley, 2013). Work-family policy availability is also significantly, but
modestly, related to job satisfaction (r = .13) (Butts, Casper, & Yang, 2013). The extent to which the
organization is perceived to support one’s family life is a stronger predictor of job satisfaction (r = .36)
(Butts et al., 2013). This perceived organizational support for family life reflects the informal policies and
norms that signal whether people and the organization care about one’s life at home.
In summary, workers’ perceptions of the work-family interface predict job satisfaction and family
satisfaction. The effects of work-family interface variables on job satisfaction tend to be weaker than the
effects of variables within the work domain covered earlier. However, perceptions of the work-family
interface appear to be stronger predictors of life satisfaction than those work domain-specific variables
discussed earlier. Research also suggests that perceptions of informal organizational support from the
organization are stronger predictors of job satisfaction than are the availability of formal family-friendly
policies, although both do contribute to higher job satisfaction. On the whole, these findings indicate that
the extent to which work fits with family life seems to be uniquely important for SWB among workers.
Unanswered Questions and Emerging
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Research Findings in Work and SWB
Beyond the content covered thus far, there are some notable areas of recent growth in empiricallybased
knowledge about work, the work-family interface, and SWB. Furthermore, there remain some
important unanswered questions that have been addressed to some degree in individual studies but for
which cumulative, robust knowledge is not currently established. Here we summarize some of these areas
with new and emerging questions and findings relevant to work and SWB.
Causal Inferences and Multilevel, Dynamic Perspectives on the Work-SWB Relationship
Aside from references to a few individual longitudinal studies, most of the correlations described
thus far in this chapter are based on studies that report correlations between self-reported working
conditions and experiences and subjective well-being, with all variables measured at the same time. This
of course raises questions about the extent to which actual working conditions cause levels of subjective
well-being. It could also be that a) subjective well-being causes the perceived working conditions, and/or b)
a third variable such as affect at the time of the survey influences responses to all questions, thus resulting
in misleading or artifactual correlations.
While it is not possible to randomize people across working conditions, one approach to address the
order of causality among work and SWB is to conduct longitudinal studies that assess the extent to which
work variables predict SWB over time. Cumulative knowledge on these effects is still emerging, although
two meta-analyses have addressed aspects of this issue. One review (Ford et al., 2014) examined the
relationships between work stressors and psychological strain (e.g., exhaustion/fatigue, anxiety, depression,
distress) in which work stressors and psychological strain were measured at one point in time and
psychological strain was measured again at a later point in time. Controlling for time 1 levels of
psychological strain, the average standardized effect of stressors at time 1 predicting strains at a later point
in time, or the “cross-lagged effect”, ranged from .05 to .08, with the strongest effects for lags of 2-3 years
and weaker effects for longer or shorter lags. The reciprocal or “reverse causation” effects ranged from .03
to .09, with stronger effects for longer time lags. A similar review of studies on work-family conflict and
strain (Nohe, Meier, Sonntag, & Michel, 2015) found that the average lagged effect of work interference
with family on psychological strain was .08, whereas the average lagged effect of family interference with
work on psychological strain was .03.
The weakness with this approach to assessing causal effects is that it only assesses effects of work
on SWB that a) have not yet occurred, and b) have a delayed onset. If an individual has a job that they
perceive as autonomous or a supervisor that they perceive as fair, this may have an immediate influence on
satisfaction and affective well-being. Lagged effects only capture the effects on well-being beyond this
immediate concurrent effect. Unfortunately, theoretical and empirical approaches to work and SWB are
not well established to account for the development of SWB as a function of work. As we know from
other research, SWB has considerable stability over time, suggesting individual personality variables and
dispositions explain some of SWB and could also contribute to spurious correlations with perceived work
characteristics. Random intercept cross-lagged models may help to address this issue (Hamaker, Kuiper, &
Grasman, 2015).
Research on stability in SWB should also take into account that work situations have stability as
well, and so the stability in SWB may in part have a situational explanation. Furthermore, individuals may
adapt to unfavorable work situations such that their SWB improves after initial exposure and stabilizes. Is
the observed stability in SWB a function of individuals adapting to their work situations, underlying
personality or dispositions, or the fact that work situations often do not change much over time? The
answers to this question in the work domain are currently not clear. Recent research has begun to
incorporate latent change score models to account for reciprocal effects among work and SWB that also
incorporate adaptation (Ritter, Matthews, Ford, & Henderson, 2016), but this is an area that needs further
empirical and theoretical development.
Relatedly, most of the research findings that have accumulated over the years have addressed
correlations between chronic work situations and SWB. Many individual studies in recent years have
investigated daily events and the extent to which these correlate with changes in affect or job satisfaction.
While no published research to date has quantitatively synthesized these findings, a recent and currently
unpublished meta-analysis (Pindek, Arvan, & Spector, 2017) analyzed correlations from diary studies that
differentiated between- and within-person effects. Between-person correlations are those that are based on
the mean of daily reports of stressors (e.g, demands, conflict) and the mean of daily reports of
psychological strain (usually an indicator of affective well-being). Within-person correlations are those
based on daily deviations from each person’s mean on each variable being correlated. Results suggest that
between-person correlations (r = .29) are stronger than within person correlations (r = .23), although not
dramatically so; interestingly, this analysis found that within-person effects on affect were stronger than
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those on other indicators of strain, which included work attitudes. These results suggest that within-person
daily experiences have a stronger influence on daily variations in affective SWB than on daily variation in
job or life satisfaction, which if true would be consistent with Affect Events Theory as discussed earlier
(Weiss & Cropanzano, 1996).
Daily work experiences also likely give rise to chronic perceptions of the work situation, in turn
influencing chronic levels of job satisfaction and SWB. The time course and contingencies on which this
process occurs are currently unknown. For example, do repeated daily experiences of an abusive
supervisor cause a lasting perception of that supervisor? Does this perception and/or any effect on SWB
go away after the stressor is removed, or is there some semi-permanent effect? Answers to these questions
are needed in order to determine when and why SWB may or may not change as a function of changes in
work experiences.
A final issue that falls within this general domain of causal inferences is the use of self-reported
measures of working conditions and experiences. The use of self-reported measures raises questions about
the extent to which self-reports of the work situation are biased by SWB, thus inflating observed
correlations. Alternatives to self-reported working conditions or questionnaires have limitations as well,
but they do exist. For example, the Occupational Information Network (O*NET) (Peterson et al., 2001)
includes publicly available ratings on a variety of important dimensions related to SWB, including job
autonomy, several types of job demands, and occupational values. Other methods are available to analyze
jobs that deviate from traditional survey instruments. Examples of alternative methods include the
collection of task statements in which people describe what they do at work, observations that allow
observers to rate jobs on relevant dimensions, interviews with workers to build deeper knowledge about the
context and processes involved in SWB at work, and critical incident questionnaires in which people
describe in their own words situations and events that influenced their SWB. These alternative approaches
have promise to advance our knowledge of how work influences SWB.
Work-Family Boundary Characteristics and Recovery
A burgeoning area of interest among researchers studying employee well-being involves the
boundaries that individuals maintain, or fail to maintain, between work and nonwork. Also of interest in
this work is what individuals do with their off-work time. Technological changes that have blurred
traditional work-nonwork boundaries along with the work intensification that has been driven by
competition and globalization have likely inspired much of this research. Two important sets of variables
in this domain are a) work-family role integration, and b) recovery and leisure experiences.
Work-family role integration is the extent to which people construe aspects of their work and
family life as part of the same domain or of separate life spheres (Allen, Cho, & Meier, 2014). Workfamily
boundaries refer to factors such as time and place that limit a person to a particular role, whether it
be one’s work or family role. Boundaries can vary in their permeability and flexibility, which influence the
extent to which a worker might have to switch life roles from work to family or family to work without
crossing a temporal or physical boundary (Ashforth, Kreiner, & Fugate, 2000). There have been a number
of individual studies on work-family role integration and boundary characteristics and these have produced
some notable results. First, role integration and permeable boundaries tend to be associated with more
work-family conflict (Kossek, Ruderman, Braddy, & Hannum, 2012). Furthermore, integrated roles tend to
increase the relationship between work-related mental states (e.g. thoughts and emotions) and those
experienced outside of work (Ilies, Wilson, & Wagner, 2009). Thus, permeable work-nonwork boundaries
and highly integrated work and family roles should increase the similarity in satisfaction specific to these
domains, for better or worse. So, for example, someone with highly integrated work and family roles and
that has high (low) job satisfaction will be more likely to have high (low) family satisfaction than would
someone with more segmented roles. Furthermore, research suggests there are meaningful individual
differences in preference for work-family role integration, and that people often take action to manage
these boundaries to their liking (Kossek & Lautsch, 2012).
Recent years have also spurred an interest in telecommuting (i.e., working from home at least some
of the time), which has been found to have mixed associations with factors relevant for SWB. For instance,
telecommuting has been found to be associated with less work interference with family but more family
interference with work (Golden, Veiga, & Simsek, 2006). People who telecommute tend to have slightly
higher job satisfaction (r = .09) and lower role stress (r = -.11) than those who do not, but these bivariate
relationships are relatively weak (Gajendran & Harrison, 2007). Other work suggests that this relationship
is curvilinear such that small-to-moderate amounts of telecommuting, up to 15 hours per week, are
associated with higher job satisfaction, but telecommuting beyond this length of time has little benefit for
SWB, perhaps because of the professional isolation that ensues among high-intensity telecommuters
(Allen, Golden, & Shockley, 2015).
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An additional related factor that has received considerable attention in recent years as a determinant
of well-being is recovery from work. There is considerable variance in what people do during their time
away from work, and this contributes to how satisfied people are with their work and family life as well as
how they feel and think about their life overall. Important off-work recovery experiences include
relaxation, psychological detachment from work, and off-job mastery experiences such as exercising or
performing challenging mental tasks (Sonnentag, Binnewies, & Mojza, 2008). Although no quantitative
meta-analysis has been published on these recovery experiences, a sizeable literature has developed
suggesting that psychological detachment from work during off-work time (e.g., not thinking about work) is
associated with lower levels of stress and fatigue and higher levels of life satisfaction, whereas
relationships with positive emotions and affect are less consistent (Sonnentag & Fritz, 2015). These effects
have generally held up in cross-sectional, longitudinal, and diary or experience sampling studies. A related
area of study looks at leisure engagement, which captures some of these same recovery experiences. A
recent meta-analysis suggests that engagement in leisure activities is related to life satisfaction (r = .22) and
positive affect (r = .29), and less so to negative affect ( r = -.10), with significant longitudinal effects on
SWB as well (Kuykendall, Tay, & Ng, 2015). More recently, the concept of telepressure, or a felt
obligation to respond to work-related interruptions while at home, has also emerged. Telepressure is an
impediment to detachment from work and may have an additive effect on SWB (Barber & Santuzzi, 2015).
In summary, there is a growing body of literature suggesting that boundaries, work-family role
integration, and recovery experiences outside of work have potential for additive effects on SWB beyond
the work-domain factors discussed earlier, and may in some instances moderate the relationship between
work-domain stressors and SWB by influencing the opportunity to recover from work. With the
continuing pressure for workers to be available and flexible, we can expect more cumulative findings and
questions on the implications of work-nonwork boundaries and recovery activities for SWB to emerge in
the coming years.
A Global Perspective
As in many research areas of psychology and organizational behavior, the vast majority of the
research on work and SWB has been conducted in traditionally Western settings and in relatively wealthy
economies such as the U.S., Canada, Western Europe, and Australia. This raises questions as to whether
the observed effects generalize across the world, particularly to workers in developing economies and more
traditionally non-Western cultures. There have been a number of review papers describing theoretical
frameworks and models for comparing the effects of work on SWB across nations and cultural settings
(e.g., Powell, Francesco, & Ling, 2009), but individual studies and empirical evidence have been relatively
sporadic, perhaps because of the practical difficulties in conducting and publishing cross-cultural research.
Thus, cumulative evidence is still emerging. Nonetheless, there have been some meta-analyses that have
included cross-national comparisons, and we report on some of these here.
In a few instances, empirical results from meta-analyses have suggested differential effects of
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work-related factors on SWB across national settings. For example, in one analysis, the relationship
between perceived unfairness and worker distress was found to be stronger in the U.S. (r = .36) than outside
of the U.S. (r = .25) (Robbins et al., 2012). A narrative review of the cross-cultural work-family conflict
literature found some individual studies that hypothesized a stronger relationship between work-family
conflict and attitudinal work outcomes in individualist than in collectivist countries (Shockley, Douek,
Smith, Yu, Dumani, & French, 2017), but it is not clear if these differences are large or reliable.
Individuals from collectivist nations have also been found to report higher levels of family interference with
work (Allen, French, Dumani, & Shockley, 2015). And organizational identification has been found to be
a better predictor of job satisfaction in collectivist than in individualist countries (Lee, Park, & Koo, 2015).
Some relationships have been found to be similar across national or cultural settings. In one
analysis, the quality of the leader-member (subordinate) exchange relationship was found to be similarly
associated with job satisfaction in individualist (r = .46) and collectivist (r = .42) countries (Rockstuhl,
Dulebohn, Ang, & Shore, 2012). An analysis of mean differences across studies found no mean differences
in work interference with family between individualist and collectivist nations (Allen et al., 2015). Abusive
supervision was also found to have similar relationships with job satisfaction, job tension, emotional
exhaustion, and depression within and outside of the U.S. (Mackey, Frieder, Brees, & Martinko, 2017).
Furthermore, work interference with nonwork had similar relations with emotional exhaustion and other
burnout symptoms across regions of the world (Reichl, Leiter, & Spinath, 2014).
Despite this sampling of findings, questions remain about robust differences or similarities across
the world in the direct relationships between work-related variables and SWB. Several individual multinational
studies have compared effects of work-related variables on SWB across nations and cultures.
Furthermore, a large number of studies in the past 15 years have been conducted outside of traditionally
Western or developed countries and could be assembled and compared in future meta-analyses across a
number of cultural and economic variables at the national or regional level. Constructs that are indigenous
to different parts of the world might shed light on new predictors of SWB as well. Thus, there is further
work to be done on the work-SWB relationship from a global perspective.
Precarious Employment and Unemployment
Changes in employment arrangements, job insecurity, and unemployment rates in recent years have
also generated increased interest in the implications of these arrangements for well-being. In particular,
there has been considerable growth in part-time, nontraditional, temporary and/or contingent work with low
levels of job security. Such work arrangements offer employers flexibility but result in jobs that are not
permanent and often do not offer the benefits of more traditional permanent employment. Some have
labeled this type of nontraditional or contingent work precarious employment and have identified it as a
social determinant of health (Benach et al., 2014).
There has been some meta-analytic work relevant to precarious employment as it relates to SWB.
As noted earlier in our discussion of human resource practices, job insecurity is a significant predictor of
job satisfaction and mental health (Sverke et al., 2002). Beyond the effects of job insecurity, unemployed
workers also have significantly poorer mental health (d = .52), life satisfaction (d = .44), and family
satisfaction (d = .20) than do employed workers (McKee-Ryan, Song, Wanberg, & Kinicki, 2005).
Reemployment among workers who were previously unemployed has been shown to substantially improve
mental health (d = .82) and life satisfaction ( d = 2.79), while job loss has the reverse effect on mental
health, although the size of the effect is not as strong (d = .35) (McKee-Ryan et al., 2005). It has even been
found that unemployment rates are negatively related to job and life satisfaction (Tay & Harter, 2013).
Contingent workers (e.g., contractors, temporary workers, direct-hire workers) also tend to report lower job
satisfaction than permanent workers (d = .21), although this difference is primarily found for temporary
workers (d = .37), whereas the satisfaction deficit for contractors or direct hires has been found to be much
smaller or nil (Wilkin, 2013). Perhaps surprisingly, little difference has been found in job satisfaction
between part- and full-time workers (Thorsteinson, 2003), although this may be in part because many parttime
workers choose such an arrangement.
As precarious employment arrangements continue to be increasingly prevalent, more work will be
needed on the implications for subjective well-being over time. Some of this work can likely be informed
by related research on the relationship between income and SWB, but precarious employment goes beyond
income in its influence on security, benefits, control, and power over one’s work and life situation,
rendering it a potentially important variable in social gradient approaches to health and well-being.
Conclusion
In this review, we provided information about the structure of empirical models linking work to
SWB, well-established research findings on the relationship between work and SWB, and findings from
450
more recently emerging areas of scholarly and societal concern. Together these results show that workrelated
variables, particularly the work people do, their interactions with others, the perceptions they form
about their employers, and the work-family interface contribute significantly to SWB. The effects of work
on SWB are likely primarily through job satisfaction and affective states experienced at work, but may also
occur via spillover to family life. Still, more work is needed on causal relationships and dynamics among
work and SWB, the relationship between SWB and precarious work over time, and SWB among workers
from a more global perspective than has traditionally been taken in the literature. As the science of SWB
moves forward, a consideration of work and the work-family interface will continue to inform our
understanding of the situational factors that contribute to SWB among workers and their families
throughout the world.
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The Importance of Leisure for Subjective Well-Being
By Lauren Kuykendall, Louis Boemerman, & Ze Zhu, George Mason University
Citation
Kuykendall, L., Boemerman, L., & Zhu, Z. (2018). The importance of leisure for subjective well-being.
In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
This chapter reviews what is known about how leisure contributes to subjective well-being (SWB). We
review evidence documenting the importance of leisure for SWB and point to psychological need
fulfillment as the main mechanism through which leisure promotes well-being. We discuss why individuals
often do not fully experience the beneficial effects of leisure, focusing on intrapersonal, interpersonal, and
structural constraints to leisure participation, and review differences in the degree and type of constraints
experienced by different demographic groups. Finally, we review research on the cognitive and behavioral
strategies individuals employ to overcome leisure constraints, and highlight the need to understand how
societal and institutional policies influence leisure participation and quality. Throughout, we identify
important questions for future research.
Keywords: Leisure, Subjective well-being, Leisure constraints
The role leisure plays in facilitating well-being is a timeless topic. For many, leisure has been
regarded as essential for a satisfying life. The ancient Greek philosopher Aristotle wrote about the
centrality of leisure for a satisfying life, emphasizing that—unlike work—leisure activities are particularly
worthwhile because they are done for their own sake (trans. 1980). Echoing these ideas, the 19th to 20th
century playwright George Bernard Shaw (1971) commented that “leisure…is not idleness. It is not even a
luxury: it is a necessity, and a necessity of first importance.” More recently, the German philosopher Josef
Pieper—in his critique of the culture of overwork and busyness (1952)—celebrated leisure as an essential
element of a happy life and a necessary escape from the busyness of the working world. Yet, for others,
leisure is regarded as an aspect of life that must be sacrificed to achieve higher, more useful ends or as a
luxury that must be forgone until retirement.
On balance, however, people do value leisure and to consider it important for a satisfying life. In
fact, in a recently nationally representative survey of the U.S., 43% of working adults said that leisure is
very important to their lives—a number slightly greater than the 38% who considered work very important
to their lives (World Values Survey, 2016). Yet, while people value leisure and while leisure is an ideal
context for engaging in activities to promote well-being, people often do not use their leisure to engage in
the types of activities that are most conducive to promoting well-being. In fact, recent U.S. nationally
representative time use data showed that people spend over 50% of their free time watching television—an
activity that is likely very limited in its potential for psychological need fulfillment—and very little time
pursuing activities that are likely to fulfill a wider range of social needs such as social activities (13% of
free time) and sports (6% of free time; Bureau of Labor Statistics, 2017). Together, these features of leisure
—that it is commonly highly valued for a satisfying life yet seemingly not commonly utilized to promote
well-being—bring it to the forefront as a domain that is potentially very important for promoting individual
and societal well-being (Kuykendall, Tay, & Ng, 2015).
With these broader issues in mind, the current chapter reviews the psychological literature on the
role leisure plays in promoting well-being. First, we define leisure and important aspects of leisure (i.e.,
leisure engagement, leisure satisfaction). Then, drawing on bottom-up perspectives on SWB, we explain
whether and when leisure satisfaction contributes to SWB and review the available evidence. Next, we
introduce psychological need fulfillment as the main mechanism through which leisure influences SWB,
focusing on evidence that leisure promotes SWB when leisure activities fulfill a broad range of
psychological needs and when leisure is used to compensate for needs and values that are unmet by other
life domains. Following the evidence for the role leisure plays in facilitating SWB, we then discuss what is
known about the intrapersonal, interpersonal, and structural constraints that prevent people from engaging
in and experiencing high-quality leisure, the constraints that are experienced by specific demographic
groups, and the processes through which people attempt to overcome those constraints. In each section, we
identify important questions for future research.
Defining Leisure
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In conceptualizing leisure, researchers distinguish between leisure engagement (also called leisure
participation) and leisure satisfaction. Leisure engagement refers to the extent to which people participate
in leisure and is measured based on time spent in leisure or the breadth and/or frequency of participation in
leisure activities. Within measures of leisure engagement, researchers distinguish between residual
definitions and experiential definitions of leisure (Haworth & Veal, 2004). Residual definitions define
leisure as all activities other than paid work or other obligatory activities. In contrast, experiential
definitions of leisure define leisure based on characteristic experiential features. The experiential approach
is exemplified in Neulinger’s (1981) work on pure leisure, which defines pure leisure as activities that are
freely chosen and intrinsically motivated. Leisure satisfaction refers to the degree to which individuals
derive enjoyment or satisfaction from their leisure activities.
Why Leisure Influences Well-Being
Bottom-up models of well-being have been commonly used to explain how and when leisure
influences SWB. Bottom-up models posits that individuals judge their overall life satisfaction based on
their satisfaction in specific life domains, with the greatest weight given to the most valued domains. While
the bottom-up mechanism is not the only mechanism linking domain satisfaction to SWB, it has been
supported by a wide range of empirical findings (see Schimmack, 2008 for a review) and specifically as
applied to leisure with meta-analytic findings on the relationship between leisure satisfaction and subjective
well-being (Kuykendall et al., 2015). In the bottom-up model, leisure satisfaction (rather than leisure
engagement) most proximally influences SWB, with leisure engagement being an important antecedent of
leisure satisfaction (Kuykendall et al., 2015; Newman, Tay, & Diener, 2014).
Evidence for bottom-up effects of leisure on SWB. This bottom-up account suggests that
improving the satisfaction with leisure is important for improving overall SWB. Supporting this prediction,
a recent meta-analysis of experimental studies showed that interventions targeting the quality of leisure
experiences improves SWB, providing further support for bottom-up mechanisms as applied to leisure,
albeit limited generalizability, as the samples were largely older adults (Kuykendall et al., 2015).
In addition to directly influencing well-being, leisure experiences can also indirectly impact wellbeing
through bottom-up mechanisms by affecting satisfaction with other domains (e.g., job satisfaction,
family satisfaction). The few rigorous studies that have examined this mechanism have provided initial
support for this mechanism for some types of leisure engagement. For instance, in a short-term (two-week)
longitudinal study of Canadian university employees, Hecht & Boies (2009) found that volunteering (but
not sports activities or membership in nonwork organizations) was associated with increased job
satisfaction, career satisfaction, and life satisfaction. One study has also shown positive effects of
volunteering on work-domain well-being. In a two-week daily diary study of working adults, Mojza,
Sonnentag, & Bornemann (2011) found that the amount of time spent volunteering was associated with
lower levels of negative affect (but not positive affect) during the following workday.
One longitudinal study has also examined how leisure experiences impact marital satisfaction.
Crawford, Jackson, & Godbey (1991) used a 13-year longitudinal study to examine whether marital leisure
patterns influence marital satisfaction or whether marital satisfaction influences marital leisure patterns and
found support for a bi-directional relationship. That is, low-quality leisure patterns (i.e., engaging in leisure
activities that the husband enjoyed but the wife did not) both influenced—and were influenced by—marital
satisfaction. In sum, this research establishes that participation in leisure activities can influence the quality
of one’s work and family experiences, though the effects may depend on certain features of leisure
activities (e.g., type of activity, enjoyment of activity). Future research should focus on identifying the
types of activities that are most conducive to positive effects on the quality of others domains and the
mechanisms responsible for these positive effects, taking into account that the most conducive activities
may vary depending on features of the job and the person.
Are the effects of leisure moderated by its subjective value? Regarding the question of when
leisure most strongly impacts well-being, bottom-up theory—specifically, the values-as-moderator
hypothesis—predicts that leisure satisfaction will have a stronger impact on SWB to the extent that it is a
valued life domain. While the values-as-moderator hypothesis was supported initially (Oishi, Diener, Suh,
& Lucas, 1999), it has recently been suggested that the values-as-moderator effect may operate differently
for different life domains. In a recent study examining this issue, some domain satisfactions were important
for well-being only if they were valued, whereas others were important regardless of whether they were
valued (Tiefenbach & Kohlbacher, 2015).
One implication of this research is that the values-as-moderator hypotheses may need to be assessed
for specific domains. Regarding the domain of leisure, very few—if any—studies have examined whether
the impact of leisure on well-being is moderated by how strongly leisure is valued. However, in research
recently conducted in our lab, we found that leisure role salience—a concept very similar to how strongly
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leisure is valued—did not moderate the effects of leisure satisfaction on workers’ SWB (Kuykendall et al.,
2017). That is, leisure satisfaction was generally important for workers’ SWB regardless of how strongly it
was valued. While additional research is needed to understand why this pattern emerged, one possibility is
that individuals are not fully aware of the benefits of leisure. That is, leisure may provide certain unique
benefits (e.g., relaxation, autonomy) that cannot be provided—and are often obstructed—by other, more
subjectively valued domains such as work and family, yet individuals may fail to fully recognize or
subjectively value these benefits. Thus, satisfying leisure may be important for predicting well-being even if
individuals are unaware of its value.
While very little research has explicitly assessed the values-as-moderator hypothesis for the effects
of leisure on well-being, a substantial body of research has indirectly addressed these questions by
assessing whether leisure is more strongly associated with SWB in specific populations that are thought to
place greater value on leisure (e.g., people in specific life stages). Specifically, developmental life stage
theorists posit that well-being hinges on pursuing and achieving progress with respect to one’s central life
tasks (Sanderson & Cantor, 1999; Super, 1990). In working adulthood, these central life tasks tend to
revolve around work and family, with leisure being less important. However, as one ages and has fewer
work and family-related central tasks, leisure should become increasingly important. As such, comparing
the impact of leisure on well-being for different life stages provides an indirect test of the values-asmoderator
hypothesis. A recent meta-analysis comparing the effects in cross-sectional studies did find
support for these predictions, revealing that leisure satisfaction is more strongly related to SWB for retired
individuals than for workers (Kuykendall et al., 2015). However, it is worth noting that—even though the
effect was stronger for retired individuals than for workers—the relationship between leisure satisfaction
and life satisfaction did remain significant for workers, suggesting that leisure satisfaction is still important
for workers’ well-being, albeit less important than it is for retired individuals.
In addition to life stage, another demographic factor thought to the impact the value of leisure is
cultural values. Specifically, Schwartz (1999) has suggested that leisure is less important in societies where
mastery values and hierarchy values are important, and leisure is more important in societies in which
affective autonomy values, egalitarian values, harmony values, and conservatism values are important.
These predictions have been supported indirectly by research showing that individuals in European
countries (with values corresponding to those that should predict valuing leisure) value work less and work
fewer hours (Schwartz, 1999; Organisation for Economic Cooperation and Development, 2009) and—by
extension—value leisure more. However, in a recent meta-analysis, the effect of leisure satisfaction on
well-being was not significantly different across European and U.S. samples (Kuykendall et al., 2015),
though the European sample included more worker studies than the U.S. sample, preventing a precise and
more conclusive test of the hypothesis that teased apart the effects of life stage and cultural values.
In sum, while the main prediction of bottom-up theories is strongly supported for leisure—namely,
that leisure satisfaction impacts overall SWB—the prediction that the size of the effect varies based on how
important leisure is has not yet been fully resolved, with some research showing that leisure satisfaction is
important for well-being regardless of whether it is valued and some research showing—albeit indirectly—
that it is more important in life stages when it is likely more strongly valued.
If future research replicates the finding that leisure is important for well-being regardless of the
extent to which it is valued, it will be important to understand why this is the case. Specifically, research
should consider the possibility that leisure provides unique benefits (i.e., autonomy, rest) that are typically
not sufficiently afforded by other life domains. Additionally, research could consider the possibility that
seeking satisfaction and need fulfillment across numerous life domains is more beneficial than seeking
concentrated need fulfillment in one domain (e.g., seeking mastery only at work)—an idea that has been
raised recently in the literature on balanced need satisfaction (Milyavskaya et al., 2009). Addressing these
questions would help further clarify the types of leisure participation that are most likely to enhance SWB.
What Facilitates High-Quality Leisure?
Given that leisure is generally very malleable compared to other life domains (i.e., individuals can
typically choose what to do with their leisure time), that leisure satisfaction predicts well-being across a
range of life stages and cultures, and that the effects of leisure satisfaction on well-being have been
supported across cross-sectional, longitudinal, and experimental studies, leisure satisfaction is likely an
important target for enhancing well-being. Accordingly, it is important to understand the experiential
aspects of leisure that are most likely to facilitate satisfaction and enhance SWB. In this section, we
highlight psychological need fulfillment as the main mechanism through which leisure influences SWB.
Need-based perspectives. Needs-based perspectives posit that leisure activities are most likely to
be satisfying and to facilitate SWB when they fulfill fundamental psychological needs. Integrating needs
posited by prominent needs-based theories, Newman et al. (2014) recently proposed the DRAMMA model
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to delineate how leisure facilitates SWB through specific needs. Drawing from a number of needs-based
theories, their framework includes Detachment-Recovery, Autonomy, Meaning, Mastery, and Affiliation
(DRAMMA) as the distinct needs through which leisure engagement can facilitate need fulfillment and
subsequently overall SWB. In what follows, we provide an overview of each of these needs, review the
evidence linking fulfillment of these needs through leisure to SWB, and discuss any known interventions
that help people fulfill each need through leisure.
Detachment-recovery. Detachment occurs when people refrain from job-related activities and
thoughts during nonwork time (Sonnentag & Fritz, 2015). Detachment is an important prerequisite for
facilitating recovery, which is the “process during which individual functional systems that have been
called upon during a stressful experience return to their prestressor levels” (p. 205; Sonnentag & Fritz,
2007). Detachment and recovery are necessary for protecting well-being on a daily basis from the shortterm
consequences of exposure to demands and stressors and from the long-term consequences of
cumulative exposure to stressors without sufficient rest. After periods of exerting effort to address demands
and stressors, individuals feel exhausted and desire a break from continued effort (Meijman & Mulder,
1998). This experience has been called the need for recovery (Sonnentag & Zijlstra, 2006). Without
restorative breaks that facilitate detachment and recovery, SWB suffers (Fritz, Sonnentag, Spector, &
McInroe, 2010; Siltaloppi, Kinnunen, & Feldt, 2009; Sonnentag & Fritz, 2007).
Detachment and recovery are increasingly difficult for working adults, as many workers feel
pressure to respond to work-related emails during non-work hours—a phenomenon recently coined
“telepressure” (Barber & Santuzzi, 2015). Research has shown that high levels of smartphone usage during
nonwork time impair psychological detachment and subsequently harm well-being (Derks, van Mierlo, &
Schmitz, 2014). Learning to detach from demands during the evening is difficult, but possible. In the first
attempt at a psychological detachment intervention, an intervention designed to facilitate recovery
experience during leisure (i.e., detachment, relaxation, mastery, and control) educated participants about
the benefits of detachment, presented different strategies for detaching from work (e.g., engaging in
absorbing activities, using “transition rituals” to separate work and nonwork time), and asked participants
to set personal goals for promoting better detachment (Hahn, Binnewies, Sonnentag, & Mojza, 2011). This
intervention resulted in improved psychological detachment compared to the experimental group one week
and three weeks after the training and decreased state negative affect three weeks after the training. Other
approaches to improve psychological detachment have used mindfulness interventions and have yielded
inconsistent results with one study effectively increasing psychological detachment (Michel, Bosch, &
Rexroth, 2014) and the other not (Hülsheger, Feinholdt, & Nübold, 2015), highlighting the need for
additional research about whether and when mindfulness interventions can help improve detachment.
Given that the types of activities that most effectively facilitate detachment likely depend on the
person and his or her job characteristics, interventions like the Hahn et al. (2011) intervention that educate
people about how different activities might facilitate detachment and encourage individuals to reflect on
and set goals for activities that would be most conducive will likely be more effective than encouraging
specific types of leisure activities. To support the design and refinement of such interventions, future
research is needed to determine the personal and contextual factors that impact the effectiveness of
different types of activities for facilitating detachment. For instance, people with ruminative tendencies may
benefit more from effortful and absorbing activities than from more relaxing activities that don’t
necessarily demand one’s full attention. Additionally, in line with the recent emphasis on well-being
interventions addressing both the person and organization (Hammer & Sauter, 2013), interventions should
be expanded to include what organizations, not just individuals, can do to facilitate detachment, as workrelated
variables such as time pressure and long work hours are associated with poor detachment (see
review in Sonnentag & Fritz, 2015).
Autonomy. Autonomy refers to the sense that one’s actions are freely chosen and reflect what one
wants to do. Autonomy and similar concepts (e.g., control, perceived freedom, autonomous motivation) are
highlighted as essential psychological needs in numerous theoretical models of well-being (e.g., Ryan &
Deci, 2000; Ryff & Keyes, 1995; Su, Tay, & Diener, 2014). Because leisure is a domain that is typically
characterized by greater freedom of choice than other life domains (e.g., work and household activities;
Graef, Csikszentmihalyi, & Gianinno, 1983), it is an ideal context for promoting autonomy and thereby
contributing to well-being. Accordingly, autonomy (or control) plays a central role in several leisure
frameworks that explain the importance of leisure for well-being (e.g., the leisure and well-being model;
Carruthers & Hood, 2007; the recovery experiences framework; Sonnentag & Fritz, 2007). In fact, several
researchers consider autonomy (or related concepts) to be a defining feature of leisure (Iso-Ahola, 1999;
Kelly, 1972; Neulinger, 1981). While different theories provide different reasons for why autonomy is
important for subjective well-being, most explanations emphasize that people have desire to feel that their
lives are predictable and within their control and that their actions are a reflection of their values and
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desires rather than controlled or coerced by external influences. When this sense is threatened, well-being is
diminished. Although autonomy is generally higher in leisure than in other life domains (Graef et al.,
1983), individuals do differ in the extent to which their leisure activities fulfill their needs for autonomy,
and those who experience greater autonomy have higher levels of well-being (Derous & Ryan, 2008;
Sonnentag & Fritz, 2007).
Given the importance of leisure autonomy for well-being and the unique opportunity leisure affords
for promoting well-being, interventions designed to facilitate leisure autonomy are likely very important for
facilitating well-being, particularly when experiences in other life domains (e.g., work and family) are less
malleable. In the previously discussed Hahn et al. (2011) intervention, one module focused on leisure
control and involved educating participants about its importance for well-being, facilitating a reflection to
help participants identify the activities during which they experience control, deciding on changes to make
to their leisure, and providing goal-setting, implementation intention, and time management strategies for
accomplishing changes. This intervention resulted in improved control during leisure when comparing the
experimental group to the control group one week and three weeks after the training and decreased state
negative affect three weeks after the training. Future interventions should continue to build upon and refine
this model.
Mastery. Needs for mastery are fulfilled when individuals have opportunities to utilize or increase
their skills or learn something new. Mastery and similar concepts such as accomplishment and competence
are needs emphasized in numerous theories of well-being (i.e., Csikszentmihalyi, 1990; Diener, 1984; Ryan
& Deci, 2000; Ryff & Keyes, 1995; Seligman, 2011) and also in leisure-specific well-being frameworks
(i.e., Sonnentag & Fritz, 2007). Mastery plays a central role in the literature on serious leisure (Stebbins,
1992; 1997)—a particular type of leisure defined as “the systematic pursuit of an amateur, hobbyist, or
volunteer activity sufficiently substantial and interesting for participants to find a career there in the
acquisition and expression of a combination of its special skills, knowledge, and experience” (p. 3,
Stebbins, 1992). Stebbins suggests that serious leisure promotes life satisfaction and attributes its effects on
well-being largely to sense of skill development and accomplishment that can be derived from serious
leisure pursuits.
Empirical research supports these predictions, as experience-sampling studies have shown that
engaging in leisure activities that facilitate mastery is associated with well-being (Sonnentag & Fritz, 2007),
and daily mastery experiences in leisure predict high levels of momentary well-being (Sonnentag,
Binnewies, & Mojza, 2008). Further, the pursuit of serious leisure, which has a large mastery component,
is generally positively associated with leisure satisfaction and life satisfaction—a finding that has been
replicated across a number of specific populations (e.g., older adult volunteers in Taiwan: Chen, 2014;
older adult competitive athletes in the United States: Heo, Lee, McCormick, & Pedersen, 2010; Heo,
Stebbins, Kim, & Lee, 2013; participants in arts groups in a Chinese university: Liu, 2014; recreational
event volunteers in Taiwan: Pi, Lin, Chen, Chiu, & Chen, 2014). However, future research is needed on the
potential negative well-being consequences of sustained serious leisure, given that it may give rise to role
conflicts (Stebbins, 1997).
In the Hahn et al. (2011) intervention, the module focused on leisure mastery educated participants
about the importance of mastery for well-being, facilitated a reflection to help participants identify the
types of challenging leisure activity that could provide mastery, provided a short exercise to boost selfefficacy
for engaging in challenging activities, and asked participants to identify changes to make to
improve their leisure. This intervention resulted in improved leisure mastery one week but not three weeks
after the training and decreased state negative affect three weeks after the training. Future interventions
should continue to build upon and refine this model to determine ways to facilitate longer lasting changes in
leisure mastery.
Meaning. Another need that is frequently emphasized in theories of well-being is meaning, which
is also sometimes referred to as purpose in life. Meaning has been emphasized as an important
psychological need for fulfilling well-being in general well-being theories (Diener et al., 2009; Ryff &
Keyes, 1995; Seligman, 2011) as well as leisure-specific perspectives (Carruthers & Hood, 2007; Iwasaki,
2008), and is an important antecedent of life satisfaction, especially when affect is non-optimal (Diener,
Fujita, Tay, & Biswas-Diener, 2012). Specifically, Iwasaki (2008) has focused on leisure as a key domain
of life for meaning-making and has begun to investigate the common ways that meaning in life can be
facilitated through leisure activities (see Iwasaki, 2016 for a review). Iwasaki’s research has suggested that
a variety of leisure activities can be used for meaning-making, and has identified several specific ways that
people engage in meaning-making through leisure, including cultivating a positive group or individual
identity, engaging in creative expression, cultivating connectedness with others or nature, experiencing
harmony/balance that is not necessarily available through other demanding domains, and experiencing
growth/transformation. Similarly, Petrou, Bakker, & van den Heuvel (2017) found that weekly leisure
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crafting, defined as “the proactive pursuit of leisure activities targeted at goal setting, human connection,
learning, and personal development” (p. 129), was associated with meaning-making in a sample of Dutch
employees.
Affiliation. The need for social connection—often called affiliation or relatedness—is emphasized
in nearly all theoretical models of well-being (Diener et al., 2009; Ryff & Keyes, 1995; Seligman, 2011).
Because many leisure activities are social, leisure is an important context for fulfilling the need for
affiliation and subsequently enhancing well-being. As expected, social leisure activities are positively
associated with well-being (Kelly, Steinkamp, & Kelly, 1987; Reyes-Garcia et al., 2009), including in an
experience-sampling studies of working adults (Sonnentag, 2001; Sonnentag et al., 2008; Sonnentag &
Ziljstra, 2006) and a short-term longitudinal study of working adults (Fritz & Sonnentag, 2005).
Compensatory benefits of fulfilling needs through leisure. While much research focuses on the
ways that leisure directly promotes SWB, other research focuses on how leisure activities can protect wellbeing
when used to compensate for the lack of need fulfillment in other life domains. Because people tend
to have high levels of freedom to choose their leisure activities, leisure can be used as an opportunity to
fulfill needs and desires that are not met in other domains such as work. Such compensatory use of leisure
should protect well-being in general and possibly also in the domain for which need fulfillment is
obstructed by substituting for need fulfillment in that domain (Heine, Proulx, & Vohs, 2006; Petrou &
Bakker, 2016; Petrou et al., 2017; Vogel, Rodell, & Lynch, 2016; Vallerand, 2000).
Studies have shown that leisure activities are important for protecting well-being when those
interests or values are not congruent with one’s job. For instance, in a study of working professionals,
Melamed, Meir, and Samson (1995) found that engaging in leisure activities was beneficial to a wide range
of well-being indicators, particularly for workers whose jobs were not congruent with their interests. More
recently, in a sample of working adults from a variety of industries, Vogel et al. (2016) found that
involvement in leisure activities lessens the negative effects of working in an organization that has values
incongruent with the subjective quality of one’s work experiences. Similarly, Petrou and Bakker (2016)
found that weekly leisure crafting (i.e., “the proactive pursuit and enactment of leisure activities target at
goal setting, human connection, learning, and personal development” p. 1) is most strongly related to
weekly well-being when opportunities for job crafting are low. Along the same lines, within counseling
psychology, leisure-based interventions have been suggested for increasing the life satisfaction of
individuals who are situationally constrained from leaving dissatisfying jobs (Hansen, Dik, & Zhou, 2008)
and also for increasing the well-being of other special populations such as unemployed adults (Liptak,
1991), college students (Lengfelder, 1987), older adults (Munson & Munson, 1986), and individuals coping
with mental health issues (Juniper, 2005).
While several theoretical models assume that people will adaptively seek need fulfillment in leisure
for needs that are not met in other domains (Guest, 2002), inconsistent support for these compensatory
models—as well as the prevalence of passive forms of leisure—raises doubts about how commonly people
engage in these adaptive compensatory processes and highlights the need to understand the motivational
processes that drive leisure decisions and to identify the processes and situational factors that would
facilitate participation in activities that would compensate for needs that are insufficiently fulfilled by other
domains (Petrou & Bakker, 2016; Petrou et al., 2017).
One question that emerges when considering the compensatory benefits of leisure is whether leisure
activities that fulfill one’s needs and values are important for well-being even if those needs and values are
met by other domains. Research relevant to this issue has yielded mixed findings, with at least one study
(Melamed et al., 1995) finding that engaging in leisure congruent with one’s personality was associated
with higher levels of well-being, even for workers with congruent jobs, and other studies have failed to find
effects of leisure congruence on well-being for workers with congruent jobs (e.g., Kabanoff, 1980;
Loscocco & Roschelle, 1991; Spreitzer & Snyder, 1987; Staines, 1980; Surber, 1983). Given these mixed
results, future research is needed to resolve the issue of whether leisure need fulfillment benefits well-being
even when needs are met in other important domains. On the one hand, for specific populations (e.g.,
“happy workaholics” who invest intensely in highly need-fulfilling jobs), engaging in activities that fulfill
only a small subset of needs such as detachment and recovery, which are not fulfilled by work, may be the
main benefit of leisure for well-being. Alternatively, balanced need satisfaction perspectives would suggest
that seeking satisfaction and need fulfillment across numerous life domains is more beneficial than seeking
concentrated need fulfillment in one domain (Milyavskaya et al., 2009). Given the mixed findings and
divergent theoretical perspectives on this issue, future research is needed to untangle whether and when
broad need fulfillment in leisure is important for well-being. That is, is broad need fulfillment in leisure
important only when work does not fulfill a wide range of psychological needs, or would individuals
benefit from broadly need-fulfilling leisure even when work fulfills a wide range of psychological needs?
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Summary of need-based perspectives. In sum, research has shown that people have higher wellbeing
when they engage in leisure activities that fulfill the needs for detachment-recovery, autonomy,
meaning, mastery, and affiliation. While much research in this area has been cross-sectional, the
longitudinal, experience-sampling, and experimental work conducted has also been largely supportive of
the effects of need-fulfilling leisure on well-being. While fewer studies have focused on whether and how
each of these needs uniquely relates to well-being, research in the general well-being literature has shown
that needs tend to have an additive effect on well-being—that is, fulfillment of each need contributes
beyond the fulfillment of other needs (Tay & Diener, 2011). Accordingly, the best way to optimize leisure
with respect to promoting well-being may be to prioritize activities that fulfill multiple needs, particularly
those needs that are not fulfilled through other domains. Unfortunately, however, this does not appear to be
how people make leisure choices. Recent U.S. nationally representative time use data showed that people
spend over 50% of their free time watching television—an activity that is likely very limited in its potential
for need fulfillment—and spend very little time pursuing activities that are likely to fulfill a wider range of
needs such as social activities (13% of free time) and sports (6% of free time; Bureau of Labor Statistics,
2017). These trends have been documented not only in the United States but also in all eighteen countries
surveyed by the Organisation for Economic Cooperation and Development (2009). As such, increasing the
amount of time people spend in leisure activities that are more broadly need-fulfilling and that fulfill needs
that are obstructed by other domains may be an important target for enhancing societal well-being across
the world. Future experimental research is needed to assess whether and for whom such approaches would
be effective for enhancing well-being.
Future research should also examine whether leisure provides the opportunity for fulfillment of
some needs that typically are not emphasized in general models of well-being. For instance, play is a
psychological state that has been recently highlighted as essential for well-being but is not included in
typical need-based models of well-being (Brown, 2009).
Barriers to Leisure Engagement and Satisfaction
Given the documented importance of leisure for well-being, a substantial body of research has
focused on understanding the barriers to leisure engagement and satisfaction. In what follows, we review
the most prominent model of leisure barriers—the hierarchical leisure constraints model. We review several
contributions of this model, including its emphasis on the important types of leisure constraints, the ways
people negotiation or overcome leisure constraints, and demographic differences in leisure constraints. We
also briefly mention the literature on leisure affordances—factors that facilitate interest in leisure. Finally,
we review research on barriers to leisure time physical activity—a specific type of leisure activity that
received substantial attention due to its importance for health and well-being
Types of leisure constraints. Given the documented importance of leisure for well-being, a
substantial body of research has focused on understanding the barriers to leisure engagement and
satisfaction. Within this stream of research, the most prominent organizing framework has been the
hierarchical leisure constraints model (Crawford et al., 1991; Crawford & Godbey, 1987; Godbey,
Crawford, & Shen, 2010), which has focused on specifying the most common types of leisure constraints
(i.e., factors that limited the desired level or quality of leisure participation) and understanding the process
through which people negotiate or fail to negotiate these constraints. Their model specifies three types of
leisure constraints. Intrapersonal constraints are internal states such as feelings of guilt or beliefs about
one’s capabilities that act as barriers to developing leisure interests. Interpersonal constraints are social
factors such as a lack of activity partners or a spouse’s leisure preferences that influence one’s own
preferences and the level of participation in one’s preferred leisure activities. Structural constraints are
contextual or environmental factors such as a lack of local recreational opportunities, lack of financial
resources, or inflexible/highly demanding work schedules that interfere with participation in a preferred
activity.
The hierarchical leisure constraints model posits that, of the three types of constraints, intrapersonal
factors most strongly and proximally influence leisure interests and preferences, whereas structural
constraints primarily influence the relationship between preferences and participation and interpersonal
constraints influence both preferences and acting on preferences (Crawford et al., 1991). The model further
specifies that encountering and negotiating leisure constraints should occur in a sequential fashion (Jackson,
Crawford, & Godbey, 1992), with people first encountering intrapersonal constraints (and possibly also
interpersonal constraints) and then experiencing structural constraints as salient primarily after
intrapersonal barriers have been addressed and leisure preference have been formed. While the model has
not been completely and consistently supported, the supportive evidence that does exist (e.g., Raymore,
Godbey, & Crawford, 1994; Raymore, Godbey, Crawford, & von Eye, 1993) has sustained its prominence
as the leading model of leisure constraint negotiation. Importantly, the hierarchical leisure constrains model
has been influential in suggesting that a focus on structural constraints is likely to be effective only insofar
463
as preferences are formed, and such formation requires first overcoming intrapersonal (and often
interpersonal) constraints.
Overcoming leisure constraints. More recently, researchers have also sought to understand the
specific strategies individuals employ to negotiate or overcome leisure constraints. In some cases, when
leisure constraints are sufficiently severe, people abandon the pursuit of a leisure activity or settle for low
levels or quality of participation. Jackson et al. (1992) have suggested that abandonment of leisure interests
is often a result of cognitive dissonance processes in which people devalue an activity when participating in
it seems unfeasible. These processes can have positive or negative impacts on well-being. On the one hand,
abandoning the activity and devaluing unattainable activities can help people to be more satisfied with the
activities they can pursue (Wrosch, Scheier, Miller, Schulz, & Carver, 2003). However, in abandoning the
activity, they may be prematurely foregoing other strategies that would allow them to retain the activity and
thereby missing out on the benefits of the activity (Kleiber, Walker, & Mannell, 2011). For instance,
abandoning one’s interest in physically active leisure would likely come at a cost to health and well-being.
However, in other cases, even sometimes in cases where constraints are severe, people can
overcome interpersonal or structural constraints that are preventing them from pursuing a preferred leisure
activity (Kleiber et al., 2011). Both behavioral and cognitive negotiation strategies have proven useful for
overcoming leisure constraints in ways that allow people to sustain participation in desired leisure activities.
Behavioral strategies include actions individuals engage in to overcome leisure constraints. These actions
can be directed toward the leisure activity or toward other aspects of life. Examples of leisure-directed
behavioral strategies include choosing alternative sites for participating in leisure that are more affordable in
order to overcome financial constraints or changing the timing of participation to overcome work-related or
family-related barriers to participation. Examples of nonleisure-directed behavioral strategies include
rearranging one’s work schedule to better accommodate leisure participation or reducing other expenses to
overcome financial leisure constraints (Lyu & Oh, 2015). Cognitive strategies include changes in the way
one thinks about barriers to leisure participation. For instance, intrapersonal barriers related to competence
may be overcome by persuading oneself that high levels of skills are not necessary for leisure participation
or quality. Similarly, barriers related to guilt may be overcome by persuading oneself that leisure
participation will help a person be a better employee or family member. Several studies have shown that
people tend to use both strategies jointly (Jun & Kyle, 2011; Jackson & Rucks, 1995), though behavioral
strategies are often used as the first option. Understanding when decisions to abandon leisure activities are
adaptive or harmful to well-being and what factors drive these decisions is an important area for future
research.
Demographic differences in leisure constraints. Another important contribution of the
hierarchical leisure constraints model is the emphasis on demographic differences in leisure constraints,
which has proven useful for guiding research on leisure constraints experienced by specific subpopulations.
The model posits that social privilege influences the experience of leisure constraints and subsequently
leisure participation and quality. Crawford et al. (1991) argued that individuals with lower income and
education would experience more severe leisure constraints, and similar arguments have also been
expanded to include women as a less privileged group. Supporting these predictions, studies have shown
that leisure is more constrained (Jackson & Henderson, 1995) for women than for men, and has documented
leisure constraints that are unique to women, particularly working mothers, such as intrapersonal constraints
related to caring behaviors and a lack of sense of entitlement to leisure and structural constraints such as
time scarcity and fewer opportunities to participate in sports (Shaw & Henderson, 2005). Research has also
shown that individuals with lower levels of income and education experience overall higher levels of
leisure constraints than do affluent and highly educated individuals (McCarville & Smale, 1993;
Alexandris & Carroll, 1997; Raymore et al., 1994). Research in this framework has also considered leisure
constraints for racial minorities (Shinew & Floyd, 2005) and immigrants (Stodolska & Yi-Kook, 2005).
While not necessarily under the scope of social privilege, research has also examined how leisure
constraints differ across the life span (Jackson, 2000), highlighting that the leisure experiences of young
people tend to be constrained by a lack of money, opportunities for participation, and participation partners.
In contrast, in middle adulthood, the barriers that are typically present for young people decrease and time
commitments become a salient barrier to leisure. For older adults, time commitments are typically no
longer a barrier, but skills and isolation more commonly constrain leisure.
Moving forward, research on demographic differences in leisure constraints would likely benefit
from understanding how national and local policies influence demographic differences in leisure
constraints, seeking to identify any policies that alleviate leisure constraints—and enhance leisure
participation and satisfaction—for disadvantaged or vulnerable populations.
Leisure affordances. While research on the causes of leisure engagement has focused primarily on
464
factors that impede participation, researchers have recently emphasized the need to focus on leisure
affordances, defined as “the environmental conditions that elicit motivation (e.g., interest, enthusiasm,
approach) in conjunction with felt needs” (p. 239, Kleiber, Wade, & Loucks-Atkinson, 2005). Emphasizing
how positive motivational forces (e.g., enjoyment) work in conjunction with constraints and negotiation
strategies to influence participation, Hubbard and Mannell (2001) tested multiple conceptual models and
found that positive motivational components increase engagement in negotiation strategies and in leisure
participation, and contribute uniquely to participation beyond the effects of constraints. These findings
motivated subsequent research, which is still in very early stages, examining how structural and
environmental conditions can elicit these positive motivational forces. Along these lines, future research
should focus on understanding how communities and institutions can better design environments to elicit
interest in beneficial leisure activities.
Barriers to leisure time physical activity. Within the literature on antecedents to leisure
participation, one particular leisure activity that has received substantial attention is leisure time physical
activity (LTPA)—a leisure activity that has been of particular interest because of its importance for health
and well-being (Sofi, Capalbo, Cesari, Abbate, & Gensini, 2008; Wiese, Kuykendall, & Tay , 2017) and
because the increasing prevalence of sedentary work makes leisure the most prominent context for pursuing
physical activity (Church et al., 2011). Because physical activity is at lower than ideal levels for much of
the U.S. population (National Center for Health Statistics, 2017), increasing LTPA is a major societal
concern. Though much of the research on barriers to LTPA has been guided by the Theory of Planned
Behavior (Ajzen, 1991)—an influential social psychological theory commonly used to explain healthpromoting
behaviors—rather than the hierarchical leisure constraints model, the findings can still be
summarized based on intrapersonal, interpersonal, and structural factors.
In a recent systematic review of determinants of adults’ physically active leisure, Wendel-Vos,
Droomers, Kremers, Brug, & Van Lenthe (2007) found that the most important interpersonal predictors
were having social support for leisure and having a companion for physical activity. Structural factors were
also important, as availability of physical activity equipment was associated with vigorous physical
activity/sports, and connectivity of trails was associated with active commuting. Yet, this systematic
review was limited in that it focused exclusively on cross-sectional studies.
More recently, reviews have focused on barriers to physically active leisure using more rigorous
studies, albeit in narrower populations. A more recent meta-analysis (Prince et al., 2016) that focused
specifically on the determinants of physically active leisure of adult women based on prospective cohort
studies—a much stronger design than cross-sectional designs—found evidence for both intrapersonal,
interpersonal, and structural determinants. Intrapersonal factors that were most commonly and consistently
associated with physically active leisure were intentions, perceived behavioral control, self-efficacy, selfrated
health, and quality of life. The interpersonal factor most commonly negatively associated with
physically active leisure was having children.
In a recent systematic review assessing the determinants of physical activity and exercise in healthy
older adults, similar findings emerged. Specifically, change in exercise self-efficacy was associated with
exercise (Koeneman, Verheijden, Chinapaw, & Hopman-Rock, 2011). The most important interpersonal
determinants were social capital and spousal physical activity, and the most important environmental factor
was the season of the year. As many of the factors shown to be associated with leisure time physical activity
across these studies are modifiable, they serve as promising targets for enhancing physically active leisure.
In the literature on physically active leisure, the emphasis has been primarily on intrapersonal and
interpersonal determinants, with less emphasis on environmental determinants. Specifically, one of the
most salient needs for future research is papers that examine how policies (e.g., workplace policies such as
subsidies for gym memberships, enforced breaks or governmental policies such as active commuting
incentives) influence physically active leisure (Prince et al., 2016), as very few—if any—studies have
examined how national or workplaces policies influence physically active leisure.
Conclusion
To summarize, while much research is needed to more fully understand the role leisure plays in
promoting SWB, the current literature does suggest that leisure is important for well-being across a wide
range of cultures and life stages and that leisure oriented toward fulfilling psychological needs and
compensating for needs or values that are not fulfilled in other domains is particularly important for SWB.
While a variety of intrapersonal, interpersonal, and structural constraints prevent people from being
interested in and engaged in the types of leisure activities that would enhance their well-being, specific
behavioral and cognitive strategies can be employed to help facilitate leisure engagement and leisure
quality. Research has not yet identified the types of societal and institutional policies that can help promote
high-quality leisure, and understanding these factors—and how to design interventions that remove both
465
personal and contextual barriers to high-quality leisure—should be an important priority moving forward.
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Well-being and Psychopathology: A Deep Exploration into
Positive Emotions, Meaning and Purpose in Life, and Social
Relationships
By Fallon R. Goodman, James D. Doorley, & Todd B. Kashdan, George Mason University
Citation
Goodman, F. R., Doorley, J. D., & Kashdan, T. B. (2018). Well-being and psychopathology: A deep
exploration into positive emotions, meaning and purpose in life, and social relationships. In E. Diener,
S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
For decades, researchers and practitioners have theorized psychological disorder and health as opposite
ends of a single continuum. We offer a more nuanced, data driven examination into the various ways that
people with psychological disorders experience well-being. We review research on the positive emotions,
meaning and purpose in life, and social relationships of people diagnosed with major depressive disorder,
bipolar disorder, social anxiety disorder, schizophrenia, and trauma-related disorders. We also discuss
when and how friends, family members, and caregivers of these people are adversely impacted in terms of
their well-being. Throughout, we highlight important, often overlooked findings that not all people with
mental illness are devoid of well-being. This review is meant to be illustrative as opposed to
comprehensive, synthesizing existing knowledge and inspiring explorations of unclear or undiscovered
territory.
Keywords: Well-being; positive emotions; meaning; purpose; social relationships
Well-being is associated with a broad range of positive outcomes, including strong work
engagement, performance, creativity, strong social connections, effective coping and problem solving
strategies, physical health, and life longevity (e.g., Diener, Pressman, Hunter, & Delgadillo-Chase, 2017;
Lyubomirsky, King, & Diener 2005). By definition, people with mental disorders experience significant
distress and/or impairment in everyday life (Widiger & Clark, 2000). The grammatical conjunction
“and/or” is of paramount importance in defining a psychological disorder, as this indicates that a person
can experience frequent, intense, enduring distress with the potential of minimal functional impairment
(McKnight & Kashdan, 2009a; McKnight, Monfort, Kashdan, Blalock, & Calton, 2016).
Researchers and practitioners often assume a linear association between the number of mental
illness symptoms present and a person’s overall functioning. Meta-analyses suggest these correlations are
modest to weak and vary across disorders (Cacioppo & Bernston, 1999; Clark, Watson, & Mineka, 1994).
Further, the presence of negative emotions in psychological disorders does not negate the possibility of
positive emotions. Research suggests that positive and negative emotions are not on opposite ends of the
same continuum, but rather, operate relatively independent of one another (e.g., Bradburn, 1969; Carver,
2001; Tellegen, Watson, & Clark, 1999; Watson & Tellegen, 1985). Other research suggests that positive
and negative emotions are bipolar ends of the same spectrum (e.g., Russell & Carroll, 1999), but people
perceive that they co-occur when their emotional state is close to the middle of this spectrum (Tay &
Kuykendall, 2017). What is clear is that negative and positive emotions are not mutually exclusive even in
psychopathology. For example, individuals with eating disorders and bipolar disorder may experience an
escalation in negative emotions while positive emotions remain, similar to healthy adults (e.g., Gruber,
Dutra, Eidelman, Johnson, & Harvey, 2011; Overton, Selway, Strongman, & Houston, 2005).
Research on mental illness has historically focused on the presence of aversive experiences.
Diagnostic categorizations of psychological disorders contain a near exclusive focus on negative emotions
and thoughts, and the avoidance of these unwanted experiences. Treatment of mental disorders extended
this approach with a focus on symptom reduction (e.g., Hollon & Beck, 1993). More recently, treatments
have emerged to promote the experience and savoring of positive emotions, instill strategies to satisfy
psychological needs for belonging, competence, and autonomy, and assist toward the clarification of values
and construction and pursuit of goals aligned with them (e.g., Fava, Rafanelli, Cazzaro, Conti, & Grandi,
1998; Ryan & Deci, 2008; Seligman, 2002; Seligman, Rashid, Parks, 2006).
In these interventions, people with psychological disorders acquire skills to move beyond
“normative” functioning in the pursuit of life success and fulfillment. Since initial trials to treat emotional
disorders (e.g., Fava et al., 1998; Seligman et al., 2006), quality of life interventions have been tailored for
a variety of community (e.g., Abbott, Kline, Hamilton, & Rosenthal, 2009; Feldman & Dreher, 2012;
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Lyubomirsky, Dickerhoof, Boehm, & Sheldon, 2011) and clinical populations (Fava et al., 2005; Gander,
Proyer, Ruch, & Wyss, 2012; Grant, Curtayne, & Burton, 2009; Ryan, Patrick, Deci, & Williams, 2008). If
practitioners wish to successfully enhance well-being among people suffering from psychological distress,
it is important to understand both the disorder-specific pathways that compromise well-being and the areas
of well-being that remain intact and even enhanced in the presence of disorder. Below, we review research
on the presence and absence of three key domains of well-being (positive emotions, meaning and purpose
in life, and social relationships) in various psychological disorders (depression, bipolar disorder, social
anxiety disorder, schizophrenia, and trauma-related disorders). This chapter is not an exhaustive review,
and due to space constraints, not every disorder is reviewed in every section. This chapter is intended to
highlight and synthesize key findings across disparate literatures to illustrate the ways in which
psychopathology interferes with well-being, and in other cases, co-exists with elements of a happy,
meaningful, and socially connected life.
Positive Emotions
Besides being subjectively pleasurable, even mild positive emotions serve an everyday purpose. A
growing body of research suggests that the experience of positive emotions fosters helpful and generous
behavior toward other people, increases open-mindedness and reduces defensiveness in social situations,
and broadens considerations when making decisions (Fredrickson, 1998; Isen, 1987). Of most relevance to
psychological disorder, positive emotions enhance people’s ability to choose targeted, effective coping
strategies to deal with stressful events (Fredrickson & Branigan, 2005; Fredrickson, Mancuso, Branigan &
Tugade, 2000; Tugade & Fredrickson, 2004). When people experience positive emotions, their attentional
resources broaden such that efforts are devoted toward aspirational life aims (instead of merely safety and
security) (Fredrickson, 2001). Of course, it is important not to overgeneralize these benefits, as discrete
types of positive emotions inspire variable behaviors and goal pursuits: love, interest, joy, amusement,
contentment, compassion, gratitude, awe, pride, admiration, hope, and relief (Roseman, 2011). Minimal
attention is given to discrete positive emotions and their relation to psychopathology because the small
body of research available tends to rely on the larger category of positive versus negative emotions.
Extreme positive emotional experiences are poorly understood. At one extreme, the relative
absence of positive emotions is associated with apathetic reactions to potentially rewarding events,
behavioral inhibition, and disengagement (Pizzagalli, 2014). At the other extreme, a hyperactive pleasure
system stuck in an appetitive phase is often an indicator of uncontrollable, manic episodes (Johnson, 2005).
We first review evidence for the former extreme (positive emotion deficits) among individuals with major
depressive disorder and social anxiety disorder. We then explore the latter extreme (positive emotion
excess) among individuals with bipolar disorder.
Major Depressive Disorder
Recent research challenges the assumption that being depressed leads to greater negativity in
response to stressful events and less reward responsiveness to positive events. Based on evolutionary
theory and strong methodological studies, it appears that when a person crosses the threshold from feeling
depressed to being diagnosed with major depressive disorder, two things occur (Bylsma, Morris, &
Rottenberg, 2008; Rottenberg & Gotlib, 2004). First, people are less emotionally reactive to negative
events. This appears counter-intuitive to everything written in biographies, scientific journal articles, and
popular media. But in fact, depressed individuals respond to negative events with less distress than healthy
adults. Second, depressed individuals are less emotionally reactive to positive events. They are insensitive
to environmental changes, regardless of whether events are positively or negatively valenced. They shut
down. Across contexts, people with depression show emotional inertia or a resistance to change.
People with depression tend to have a diminished capacity to experience positive emotions or
pleasure (i.e., anhedonia). When they encounter pleasant events or experiences, depressed people often
respond by dampening or suppressing positive emotions (Feldman, Joormann, & Johnson, 2008). They
might tell themselves that their streak of good luck will end soon or that pleasurable emotions will be
short-lived. They are less likely to mentally elaborate on positive mood states, such as savoring an
experience by replaying the highlights or identifying moments they are grateful for (Eisner, Johnson, &
Carver, 2009). This means that people who are depressed are reacting to positively appraised real-life
events by downplaying and resisting them.
Laboratory studies have showcased how adults with depression respond to a variety of rewarding
stimuli with blunted reactions (for review see Bylsma, Morris, & Rottenberg, 2008). For example, after
watching an amusing film clip, participants with depression felt less amusement than healthy controls
(Rottenberg, Kasch, Gross, & Gotlib, 2002). In another study, after viewing a series of pleasant pictures,
participants with depression reported diminished emotional responses and displayed less frequent and
intense positive facial expressions than healthy controls (Sloan, Strauss, & Wisner, 2001). In an
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autobiographical interview, adults with and without depression were videotaped talking about their happiest
memory. Participants with depression took longer to retrieve their happy moments and recalled fewer
specific details compared with healthy adults (Rottenberg, Hildner, & Gotlib, 2006).
Results from experience sampling studies offer a more mixed picture of emotional insensitivity. One
study found that people with greater depressive symptoms experienced less intense positive emotions in
response to daily positive events compared to people with fewer depressive symptoms (Carl, Fairholme,
Gallagher, Thompson-Hollands, & Barlow, 2014). They also tried to suppress or dampen their positive
emotions more frequently. While this pattern of results indicates emotion insensitivity, other studies have
found that depression is associated with increased reactivity. In one study, people with elevated depression
experienced greater emotional reactivity in response to both negative and positive events (Nezlek & Gable,
2001). A similar pattern of results were found in a study of social interactions; following both positive and
negative social interactions, depressed people reported greater emotional reactivity than less depressed
peers (Steger & Kashdan, 2009). The authors interpreted these results within evolutionary theory,
suggesting that social contexts might evoke a different response than reflecting on prior events, observing
movies and pictures, and other intrapersonal events. Depressive symptoms help people determine whether
their social value is declining, putting them at risk of being insecurely attached to a tribe, isolated, and
deprived of the psychological, physical, and social resources derived from group membership (Allen &
Badcock, 2003; Watson & Andrews, 2002). Because social acceptance is central to the basic tenets of
evolutionary survival and reproduction, it makes sense that depressed adults reported fewer occurrences of
positive social interactions but experienced greater well-being benefits when they occurred; these events
are cause for relief, as they are indicators that they are valued, cared for, and part of the tribe. It also makes
sense that depressed adults, chronically concerned about their precarious social standing, react to negative
social events with particularly strong emotions and experience diminished well-being due to the fear of
being ostracized and banished.
Research is needed to determine the extent to which disparate findings are a function of
methodology or phenomenology. In terms of methodology, it is possible that highly controlled laboratory
environments do not accurately reflect everyday experiences. Simulated threats and aversive stimuli may
be less stressful in laboratories, where a person can dampen their response by reminding themselves they
are not in real danger, compared with real-world, real-time threats. In terms of phenomenology, it is
possible that laboratory studies capture a limited subset of stimuli in which people with depression display
emotional insensitivity. Laboratory studies have primarily used emotion-eliciting images with little
consideration of more complex, naturally occurring situations (e.g., stressful social interactions, romantic
relationship break-ups, academic failures).
The emotional complexity of people with depression goes beyond the intensity of emotions
experienced. Depressed people are characterized by emotional inertia, in which prior emotions are strongly
predictive of future emotions to the point of being rigid or frozen in time, irrespective of what is occurring
around them (Kuppens et al., 2012). Another way to study emotional complexity is by examining the
density of emotion networks. Rather than focusing on a single emotion (e.g., sadness), density analyses
allow a group of emotions to be examined at once (e.g., sadness, anger, guilt). In one such study,
depression was associated with a greater density of negative emotions, but not positive emotions (Pe et al.,
2015). A density-distribution approach to emotions suggests that the positive emotions experienced when
depressed are fewer in type and less predictable. Still, it is unclear which positive emotions fail to arise in
particular situations. Moral emotions that are closely aligned to social activity such as gratitude,
compassion, and love might be deficient during depressed states, serving as potent targets for interventions
designed to enhance well-being.
These findings support a conceptualization that deficits in key areas of positivity such as positive
affect and behavioral activation confer risk for depression in addition to negative risk factors such as
pessimistic attributional styles, which have received more attention. Future research is needed to
disentangle the strength and temporal sequence of attenuated positivity and depression. Does depression
lead to a lack of motivation and sensitivity to potential positive rewards in a person’s environment, or does
diminished reward responsiveness increase risk for depression? A recent meta-analysis of longitudinal
studies offers support for a bidirectional effect (Khazanov & Ruscio, 2016). Self-report measures of
positive emotionality (positive affect, extraversion, and behavioral activation) prospectively predicted
increases in depression, and depression predicted subsequent decreases in positive emotionality. Finegrained
analyses that target discrete positive emotions will offer insight into the behaviors and goals that
depressed children, adolescents, and adults are being pulled toward and away from. By identifying which
positive emotions possess the strongest ties to depression, interventions can be developed that target
specific positive emotions such as gratitude, compassion, amusement, and love (e.g., Gander, Proyer,
Ruch, & Wyss, 2013; Hofmann, Grossman, & Hinton, 2011; Stellar et al., 2017).
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Bipolar Disorder
Positive emotional experiences are a defining feature of bipolar disorder. The consequences of the
intense euphoria, impulsivity, and grandiosity during manic episodes often lead to significant personal
damage including financial disarray after spending sprees, relationship problems after infidelities, physical
damage after excessive drug use, and risky sexual behavior. But in some cases, individuals with bipolar
disorder have the unique capacity to experience pronounced positive emotions in a broader range of
circumstances relative to healthy individuals. Past research has focused on positive emotions and
experiences during manic episodes. When manic, people with bipolar disorder are more reactive to positive
compared with negative stimuli (e.g., Johnson, 2005). They recall three times the amount of positive
memories as negative memories, whereas healthy controls tend to remember about 10% more positive than
negative memories during a typical good mood (Eich, Micaulay, & Lam, 1997). They are also more likely
to remember positive descriptive words about themselves compared to psychologically healthy adults (Van
der Gucht, Morriss, Lancaster, Kinderman, & Bentall, 2009).
Enhanced positivity is not confined to manic episodes, however. Research suggests that people
diagnosed with and at risk for bipolar disorder tend to display persistent positive emotion across contexts
(Johnson, Gruber, & Eisner, 2007). People with bipolar disorder exhibit a greater degree of positive
emotions in response to, in anticipation of, and following rewarding stimuli, even when in remission
(Gruber, 2011). Self-reports of positive emotions have been substantiated by physiological data showing
cardiac and respiratory states indicative of positive emotionality (Gruber, Harvey, & Johnson, 2009;
Gruber, Johnson, Oveis & Keltner, 2008). Neurological data converge on a similar conclusion that people
with bipolar display elevated reactivity to multiple types of rewards (Dutra, Cunningham, Kober, & Gruber,
2015). While this positive emotionality may not seem problematic, research suggests that people with
bipolar disorder show high levels of positive emotions (with self-report and physiological data) in
situations that not only lack reward potential but are objectively neutral or aversive (from sad and
disgusting film clips to hostile physical gestures by strangers; Gruber, et al., 2008; Piff, Purcell, Gruber,
Hertenstein, & Keltner, 2012). This positive emotion persistence extends to self-regulatory difficulties
when working toward meaningful life goals. Whereas healthy adults show a reduction in effort expenditure
after making goal progress, people with bipolar disorder continue to persist (as if achievement is irrelevant)
with sustained, high levels of positive emotions related to goal pursuit (joy, pride) (e.g., Fulford, Johnson,
Llabre, & Carver, 2010).
When considering theory and research on positive emotions in bipolar disorder, it makes sense that
these individuals are suspected to be more creative than the average population (Johnson et al., 2012).
Research suggests that people in highly positive mood states (e.g., those that activate approach behavior, as
seen in bipolar disorder) access more unusual and diverse information and in turn, show evidence of greater
flexibility and creativity in their ideas and decision-making compared to behavior in other mood states
(Baas, De Dreu, & Nijstad, 2008; Isen, 1999). Indeed, historical analyses of highly creative musicians,
writers, poets, and politicians identify a meaningful number who likely experienced bipolar disorder at
some point in their lives: Ernest Hemingway, Ludwig von Beethoven, Sylvia Plath, Georgia O'Keeffe,
Vincent Van Gogh, Robert Schumann, and Winston Churchill, among others (Jamison, 1989; Weisberg,
1994).
Early writings on the association between mania and creativity spawned interest in testing this
theory empirically. One early study found that people with bipolar disorder showed levels of creativity
similar to creative writers when sorting objects into different categories (Andreasen & Powers, 1975).
Another study found that lithium treatment for people with bipolar disorder dampens expansive, creative
thinking (Shaw, Mann, Stokes, & Manevitz, 1986); offering a reason why medical compliance is difficult.
A number of studies have examined the prevalence of bipolar spectrum disorders in creative professions.
One study used structured diagnostic interviews to assess bipolar symptomatology among students at the
prestigious University of Iowa Writer’s Workshop (Andreasen, 1987). Results showed that 43% of students
met criteria for bipolar spectrum disorders compared to 10% of a non-creative control group. Other studies
suggest that bipolar disorder is more common among individuals in creative professions such as writers
(Ludwig, 1992) and artists (Akiskal, Savino, & Akiskal, 2005). Beyond creative professions, bipolar traits
may be more common among those with more daily creative hobbies (Batey, 2007). While potential links
between creativity and bipolar disorder are compelling, it is unclear whether, and under what
circumstances, bipolar symptomatology actually fosters creativity. With an excessive focus on creative
professions, studies have neglected to measure creative activity with validated self-report and behavioral
measures. More research is needed to clarify the directionality of findings and uncover ways of harnessing
creativity to improve the quality of life for people with bipolar disorder.
Despite upticks in creativity and expansive thinking, positive emotions pose a dilemma for people
with bipolar disorder because they can signal the onset of a manic episode. They are forced to balance
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natural desires for pleasure and achievement with staving off manic-induced impairment. As they learn
from their prior experiences, mania is more likely to occur after achieving important goals (Johnson et al.,
2000). As a form of self-intervention, people with bipolar disorder intentionally try to dampen positive
experiences. In one study, nearly 80% of people diagnosed with bipolar I disorder reported engaging in at
least one strategy to avoid something rewarding in order to prevent mania, such as avoiding hobbies,
limiting creative pursuits, and choosing not to have children (Edge et al., 2013). When people with bipolar
disorder experience positive emotions, they are more likely to respond to positive experiences with
thoughts that curb emotion intensity (e.g., “I do not deserve to feel this good”) compared with healthy
adults. Unfortunately, emotion dampening is associated with lower self-reported quality of life. This means
that in an effort to prevent the onset of mania, people with bipolar sometimes avoid some of life’s most
rewarding, pleasurable experiences. Emotion regulation strategies such as mindfulness that keep people
rooted in the present without any attempt at altering ongoing experiences may be a more adaptive
alternative (e.g., Gilbert & Gruber, 2014). Future research can examine iterative decision-making processes
among people with bipolar disorder to discover strategies that minimize chances of mania while
maximizing the ability to fully engage with personally meaningful pursuits.
Social Anxiety Disorder
People with social anxiety disorder believe their personal characteristics are deficient, flawed, or
contrary to perceived social norms. Upon having their personal flaws exposed to others, they worry about
being evaluated unfavorably and ultimately rejected (Clark & Wells, 1995; Heimberg, Brozovich, & Rapee,
2010; Moscovitch, 2009). In hopes of preventing rejection, people with social anxiety disorder avoid social
situations or endure them with considerable distress. As a result of their distorted beliefs and avoidant
strategies, they are less likely to enjoy and pursue potentially pleasurable activities.
Unlike other anxiety disorders, social anxiety disorder is characterized by persistent low positive
affect and curiosity (for a meta-analysis, see Kashdan, 2007). Specific positivity deficits in social anxiety
disorder include the tendency to disqualify or reject positive feedback, difficulty recalling positive
memories, lack of approach-oriented behavior when in neutral, non-threatening situations (Cacioppo &
Berntson, 1999), and an impoverished quality of life (e.g., Eng, Coles, Heimberg, & Safren, 2005;
Moscovitch, Gavric, Merrifield, Bielak, & Moscovitch, 2011; Weeks, Menatti, & Howell, 2015). One study
examined how people with social anxiety disorder anticipate positive events by reading descriptions of
situations such as receiving a love letter from a longtime crush or receiving much needed help from a
coworker (Gilboa-Schechtman, Franklin, & Foa, 2000). Compared with non-anxious peers, people with
social anxiety disorder rated positive social events as less likely to occur in their lives. If positive social
events were to occur, they anticipated experiencing stronger negative reactions. These findings suggest that
two biases exist, the first being a belief that positive events are unlikely to occur and the second being that
if they do, rewards will be ignored and some level of pain/punishment will be recognized and ruminated
on.
Positivity deficits appear to be driven in part by frequent and intense self-regulatory efforts
(Kashdan, Weeks, Savostyanova, 2011). As an act of self-protection, people with social anxiety disorder try
to conceal perceived deficiencies and refrain from expressing intense emotions that might draw unwanted
attention (Heimberg et al., 2010; Moscovitch & Huyder, 2011). When people direct their limited attention
to reducing their anxiety, appearing less anxious, and making a positive impression, they exhaust the
energy necessary to extract rewards from their ongoing environment (Goodman, Larrazabal, West, &
Kashdan, in press; Hayes, Luoma, Bond, Masuda, & Lillis, 2006).
When analyzing face-to-face social interactions in everyday life over the course of two weeks, the
two characteristics that best distinguished people with social anxiety disorder from healthy controls were
the infrequency of positive emotions and reliance on avoiding anxious thoughts and feelings (Kashdan et
al., 2013). Notably, people with social anxiety disorder could not be distinguished from healthy controls
based on their experience of anxiety or negative emotions during social interactions. The implication is that
to understand social anxiety disorder, the action is not with anxiety in social situations, but rather the
relative absence of positive social experiences and the sheer amount of effort exerted to feel something
other than anxiety.
Experience sampling studies offer insights into how and when individuals with social anxiety
disorder experience diminished positivity. Socially anxious people tend to experience the fewest positive
events on days when they feel more socially anxious and devote considerable effort to suppress these
emotions (Kashdan & Steger, 2006). Irrespective of how anxious a person tends to be across situations
(trait social anxiety), participants in this study reported the most intense positive emotions on days when
they felt minimal social anxiety and comfortable expressing their emotions openly. Interestingly, people
with higher levels of social anxiety experience low doses of positivity regardless of whether they are
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socializing with other people or spending time alone (Kashdan & Collins, 2010).
An interesting paradox for people with social anxiety disorder is that in addition to a fear of being
evaluated negatively, they fear being evaluated positively (Weeks & Howell, 2012). People with social
anxiety disorder tend to interpret positive social interactions as a signal of future anxiety-provoking social
interactions (Alden, Mellings, & Laposa, 2004). Even if they receive positive feedback, they believe future
social interactions will be negative because they will fall short of rising expectations. With higher
performance standards, there is a higher probability of failure. They also worry that overly favorable
impressions might in some way be construed as threatening to other group members. For instance, they
might worry that if their senior director publically compliments their work on a project, their manager will
perceive them as threatening. When someone with social anxiety disorder ends up in a rare positive social
interaction, they tend to dismiss good news or accomplishments (Weeks, 2010). For example, they might
attribute a pleasant conversation to the other person being interesting rather than their social competence in
asking good questions. If someone acts friendly towards them, they might assume the other person feels
bad or is simply trying to be nice. By being hyper-focused on minimizing and concealing anxiety, people
with social anxiety disorder ignore potentially rewarding social cues, such as someone self-disclosing an
intimate detail about themselves (Kashdan et al., 2014).
These concurrent fears of positive and negative evaluation work in concert to contribute to positive
and negative emotional suppression (Turk, Heimberg, Luterek, Mennin, & Fresco, 2005). Suppressing
positive emotions helps a person with social anxiety disorder minimize attention directed towards them. On
days when people high in social anxiety tended to suppress the expression of positive emotions, fewer
positive social events and less positive emotions occurred the next day (Farmer & Kashdan, 2012). People
generally want to get rid of or downregulate negative emotions and savor or upregulate positive emotions.
For people with social anxiety disorder, the choice of which emotions to regulate spans the emotion
spectrum. There has yet to be systematic longitudinal studies on how the avoidance and suppression of
anxiety and positive emotions influences the development of friendships, romances, interests/passions, and
work-related prospects, engagement, performance, and innovation. It will be important for future research
to clarify the downstream consequences of decisions to avoid instead of approach over the course of months
and years.
To understand the problems inherent to social anxiety disorder, you need to simultaneously consider
personality, emotional experiences, how people react to these emotions, and beliefs about emotion display
rules. Ignore any of these elements and you will be misled about how they operate together. For instance,
there is a subgroup of people with social anxiety disorder (as high as one out of five diagnosed with the
condition; Kashdan, McKnight, Richey, & Hofmann, 2009) who instead of trying to escape anxious
situations and experiences, tend to be novelty seeking, impulsive, and risk-prone (Kashdan & McKnight,
2010). These people might take over a conversation to demonstrate social dominance or engage in risky
sexual behavior to control, instead of being controlled by, their anxiety. Do people in this subgroup have
similar positivity deficits, tendencies to conceal the expression of positive emotions, and fears of being
positively evaluated as people in the more timid, prototypical group? As for interventions, how can
individuals with social anxiety disorder organize their lives in ways that influence the probability of
positive experiences? How can they reverse their tendency to ruminate on blunders instead of savor the
moments of connection in the aftermath of social encounters? As a condition that affects approximately 7-
12% of the population (Fehm, Beesdo, Jacobi, & Fiedler, 2008; Kessler et al., 2005), sufficient basic
research exists to begin exploring translational interventions that address the positivity deficits. With the
tradeoff made such that people with social anxiety disorder meet their short-term goals of alleviating
anxiety and avoiding rejection, at the expense of building positive experiences, much needs to be learned
about the ways that well-being interventions require refinement to improve life outcomes beyond symptom
reduction.
Meaning and Purpose In Life
Purpose in life has been defined as a central, self-organizing, life aim. Those who acknowledge and
live in accordance with their purpose derive a deep sense of meaning in life via the pursuit and attainment
of valued goals (Kashdan & McKnight, 2009). A strong sense of purpose is associated with greater
meaning in life along with greater happiness and self-esteem, viewing goal pursuits as challenges instead of
threats, greater resilience when confronted with emotional difficulties and traumatic events, and longevity
(Bonebright, Clay, & Ankenmann, 2000; Boyle, Barnes, Buchman, & Bennett, 2009; McKnight &
Kashdan, 2009b; Ryff, 1989). On the other extreme, people who lack a sense of purpose are at greater risk
for mental health difficulties (Kashdan & McKnight, 2009; Ryff & Singer, 1996). Emotional distress
obstructs awareness of one’s purpose and inhibits the mobilization of effort toward one’s purpose (e.g.,
Berenbaum, Raghavan, Le, Vernon, & Gomez, 2003). With less research on the interface of meaning and
purpose and psychopathology compared to positive emotions and social relationships, the available review
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is streamlined.
Depression
Depression is characterized by a poverty of meaning and purpose (Beck, 1967). Beck’s early
writings on the subject describe people who are depressed as “having no goals,” “having nothing to look
forward to,” and “seeing no point in living” (Beck, 1967; see Westgate, 1996). In addition to hallmark
symptoms found in the DSM, some measures include items about meaninglessness as a specific symptom
of depression (e.g., Lovibond & Lovibond, 1995). Meaninglessness may stem from an unfulfilling social
support network (Stillman et al., 2009). Given that loneliness and depression frequently co-occur (e.g.,
Weeks, Michela, Peplau, & Bragg, 1980), it is unsurprising that a lack of meaning may indicate depression.
Factor analyses have also suggested that hope about the future is an important component of meaning
(Feldman & Snyder, 2005). Since hopelessness is one of the core features of major depression (Abramson,
Metalsky, & Alloy, 1989), a lack of hope may underlie deficiencies in meaning and purpose among
individuals with depression.
While a lack meaning in life is intertwined with the core features of depression, a strong sense of
meaning can play a protective role in the onset and maintenance of depression. In one study, nearly 800
people from 43 countries completed self-report measures of meaning in life and depression five times
throughout the year (Disabato, Kashdan, Short, & Jarden, 2017). People with higher meaning in life at the
start of the study experienced a decrease in depression three months later. This relationship was partially
mediated by positive life events people experienced over the three-month period, such as earning more
money or doing something exciting with a friend. These findings suggest that meaning in life can decrease
depressive symptoms by generating positive life events. Such findings coincide with the theoretical
rationales of interventions that target well-being indicators as outcomes (rather than symptom reduction),
which posit that deficient meaning in life is not merely a consequence or correlate of depression but rather,
meaning plays a causal role in the development and maintenance of the disorder. As such, enhancing
meaning, purpose, and related phenomena should be effective in preventing and treating depression.
Treatments such as Acceptance and Commitment Therapy (ACT) help people with depression clarify
personal values, and work toward goals that offer the greatest potential for meaning and purpose in life
(Hayes, Strosahl, & Wilson, 1999; Zettle, 2007). This is achieved not by eliminating depressive symptoms,
per se, but by disengaging from unproductive internal dialogue, acknowledging and accepting
uncomfortable emotional experiences while not acting on their behalf, staying in touch with the present
moment, and increasing goal-directed behavior irrespective of the presence of distress (Zettle, 2007).
Bipolar Disorder
While mood disorders generally obscure one’s sense of meaning and purpose, some people are able
to derive meaning from altered emotional states. This is especially evident in bipolar disorder. One
qualitative study examined ways in which people with bipolar disorder derive a sense of meaning from
their illness (Rusner, Carlsson, Brunt, & Nystrom, 2009). Participants described bipolar disorder as “an
illness that is intertwined with one’s whole being.” They reported an overall intensity of experience that can
at times be rich and profound. Participants alluded to a “daily battle” to understand themselves and
uncover what is helpful in life, and the distinction between reality and internal fiction. Results suggest that
while bipolar disorder creates a challenging existence for those affected, finding meaning within this
complexity is achievable.
While some individuals with bipolar disorder struggle to make sense of their often chaotic
emotional lives, others are able to derive a coherent sense of meaning with the help of spirituality and/or
religion. One study found that 78% of adults with bipolar disorder surveyed held strong spiritual or
religious beliefs (Mitchell & Romans, 2003). Theory and research suggest that people with strong religious
beliefs and practices are better able to control, monitor, and regulate the self and thus, are more skilled at
organizing, prioritizing, and achieving goals (McCullough & Willoughby, 2009). Religious and spiritual
beliefs may be particularly beneficial for people with bipolar disorder who have difficulty regulating their
emotions in the context of disorganized goal pursuit (Johnson, 2005). Spirituality may also boost well-being
among people with bipolar disorder, as research suggests that feeling connected with a higher power is
associated with greater well-being at the trait (Pargament & Mahoney, 2009) and daily level (Kashdan &
Nezlek, 2012). Many people with bipolar disorder endorse a direct link between religious beliefs and a
willingness to manage their illness (e.g., Galvez, Thommi, & Ghaemi, 2011; Mitchell & Romans, 2003),
suggesting that meaning derived from spiritual and religious systems may improve the course of bipolar
disorder. Some evidence suggests that people with psychological disorders can exhibit excessive religious
and spiritual engagement, but this is not the norm (Koenig, 2009). Spirituality and religion should be
further explored as a potentially useful paradigm to initiate coping and meaning making among people
with bipolar disorder; with the caveat that more attention is needed to the types of beliefs and behavioral
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practices that are helpful and unhelpful.
Social Anxiety Disorder
Compared to other anxiety disorders, people with social anxiety disorder are more apt to make
decisions that involve avoiding errors, mistakes, and failures than approaching rewards (Kashdan et al.,
2011; Rodebaugh & Heimberg, 2008), interfering with the ability to behaviorally commit to goals aligned
with a purpose in life. Theory substantiates this notion, as social anxiety is thought to be part of a
biologically based avoidance system designed to alert and protect against potential social exclusion (Leary,
2001). Research points to the hypothesis that a coherent sense of purpose and committed effort towards
that purpose may act as a powerful antidote for the emotional suffering experienced by people with social
anxiety disorder.
One study found that people with social anxiety disorder endorsed lower meaning in life and lower
drive toward a life purpose on a daily basis compared to psychologically healthy adults. Yet, on days when
people with social anxiety disorder made progress toward a purpose in life, they endorsed greater meaning
in life and positive emotions, and their self-esteem was indistinguishable from psychologically healthy
adults (Kashdan & McKnight, 2013). Results suggested that strong effort – rather than progress – toward
one’s purpose was the mechanism driving these benefits for individuals with social anxiety disorder.
Although this is only one study, this work suggests that if you give people with social anxiety disorder a
reason for getting through the day, there is a reduction in the unhelpful influence of anxious thoughts and
feelings. Further evidence for this alternative model of intervention (that does not make anxiety reduction a
goal) stems from effective clinical trials of ACT for people with social anxiety disorder who are given the
skills to be in the present moment, with a curious attitude, pursuing what they care about most despite the
presence of pain (Craske et al., 2014; Dalrymple & Herbert, 2007; Kocovski, Fleming, Hawley, Huta, &
Antony, 2013).
Schizophrenia
Conventional wisdom suggests that people with schizophrenia have obstructed views of the world
around them, resulting in significant functional impairment and thus, a diminished sense of meaning (e.g.,
Roberts, 1991). However, even people diagnosed with psychotic disorders can experience profound
meaning in life. Qualitative data suggest that there are at least five sources of meaning that can remain
intact despite the presence of severe psychological disorder: social relationships, meaningful work, physical
health and vitality, nostalgia for life defining moments, and positive experiences (Eklund, Hermansson, &
Håkansson, 2012). A greater sense of meaning and purpose can be therapeutic for people with
schizophrenia. Inpatients with schizophrenia who have a greater sense of meaning and purpose in life
endorse greater adherence to their medical regimen and are less likely to be depressed during their hospital
stay (Tali, Rachel, Adiel, & Marc, 2009). Despite difficulties deriving meaning from external sources,
research suggests that some people with schizophrenia construct meaning from their delusions and
hallucinations - integrating these experiences into a coherent framework of who they are. This allows these
individuals to better understand and accept their aberrant and otherwise disturbing experiences, which may
ultimately improve their symptomatology and well-being. One study found that people with schizophrenia
reported decreased meaning in life from pretreatment to posttreatment (Roberts, 1991). For those who
successfully integrated delusions and hallucinations into their sense of self, the loss or reduction of these
symptoms precipitated confusion and the fear and sadness of a lost identity. If delusions and hallucinations
are reduced or altered, this research suggests that treatment must go beyond symptom reduction to aid in the
reformulation of their self-concept.
Rich, descriptive studies of people with schizophrenia are needed to gain a deeper understanding of
their perspectives on life-sustaining sources of meaning. Notably, a fundamental sense of personal
meaning - which offers explanatory power to make sense of one’s life, exists at the core of one’s identity,
and allows one’s existence to be significant and of value to the world - appears to be invariant across people
with and without schizophrenia. Treatments such as ACT have been tailored toward people with
schizophrenia, showing promise in reducing the believability of hallucinations and delusions while
simultaneously reconstructing lives to revolve around commitment toward goals aligned with a person’s
central values (Gaudiano & Herbert, 2006; Gaudiano, Herbert, & Hayes, 2010; Veiga-Martínez, PérezÁlvarez,
& García-Montes, 2008). For example, one study compared ACT to enhanced treatment as usual
(Gaudiano & Herbert, 2006) for inpatients with psychotic disorders. Upon discharge, the ACT group
exhibited improvements in affective symptoms, distress related to hallucinations, and social impairment.
More patients in the ACT group experienced significant symptom reduction at discharge compared to those
receiving enhanced standard care. Notably, reductions in the believability of hallucinations were only seen
in the ACT group, and these reductions were strongly associated with decreased distress. It appears that
changing people’s attitudes toward delusions and hallucinations – rather than trying to eradicate them– is
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particularly important in helping individuals with schizophrenia live meaningful lives.
Trauma-Related Disorders
Meaning and purpose play a complex role in trauma-related disorders such as PTSD (Fontana &
Rosenheck, 2004). Trauma has been referred to as a “crucible of meaning” in which one’s sense of
meaning is tested, transformed, and often torn asunder, with the potential for a new meaning system to
emerge with the explanatory power to make sense of both losses and discoveries (Landsman, 2002). It is
not uncommon for survivors to search for meaning in the wake of their trauma, as traumatic events disrupt
assumptions about the self and world (Janoff-Bulman, 1989). For some, this search for meaning allows for
a re-examination of life and opportunities for growth in various domains including personal strength,
interpersonal relationships, appreciation of life, and a sense of possibility (e.g., Joseph & Linley, 2006;
Tedeschi & Calhoun, 1996).
Some people report positive changes in their self-perceptions and feel they improved as a person
for having experienced a traumatic event (e.g., Andreasen & Norris, 1972; Tedeschi & Calhoun, 1996). To
be clear—these are the subjective experiences of trauma survivors and any data on post-traumatic growth
should be interpreted cautiously (Jayawickreme & Blackie, 2014). After all, researchers are unable to
explore an alternative life trajectory without the trauma. Perhaps the majority of trauma survivors would
have achieved equal or even greater personal growth over the course of time without the presence of
trauma. Perhaps the subjective experiences are a strategy to cope with the difficulties that arise from
experiencing a traumatic life disruption. As scientist-practitioners, we are less interested in the veracity of
trauma survivors statements that their life trajectory has been significantly improved as a result of lessons
learned and more interested in the multiple paths to acquiring well-being, dissecting the mechanisms that
increase the possibility of positive change.
A study of adults with a recently deceased parent found that approximately 50% experienced a
strengthening of their relationships with others, as they reported more fully appreciating the transience of
meaningful connections with others (Malinak, Hoyt, & Patterson, 1979). Another study of survivors of a
sinking cruise ship found that 94% of people reportedly “stopped taking life for granted” and 71% noted
that they now strive to “live each day to the fullest” (Joseph, Williams, Yule, 1993). In some cases, positive
changes can manifest rapidly after traumatic events. One study of sexual assault survivors found that many
participants reported positive changes including increased empathy, stronger relationships, and a greater
appreciation of life as early as two weeks following the assault (Frazier, Conlon, & Glaser, 2001). Another
caveat is warranted, as this research does not suggest that any traumatic event is good/positive/healthy or
the cause of positive changes; rather, this research describes the psychological management of the
emergent distress and change (Coyne & Tennen, 2010).
Data suggest that two reasons that combat veterans seek services through the VA are weakened
religious faith and a search for meaning in purpose, rather than the severity of PTSD symptoms (Fontana &
Rosenheck, 2004). In some cases, traumatic exposure appears to strengthen religious faith (e.g., Calhoun,
Cann, Tedeschi, & McMillan, 2000). While the exact mechanisms are unclear, theories suggest that people
suffering from and working to overcome traumatic events may view their suffering as a form of
redemption - a common theme emphasized by many religions (e.g., Frankl, 1962; McAdams & McLean,
2013). A strong sense of purpose may lead to healthier, more resilient trajectories following traumas (e.g.,
Bonanno, Papa, Lalande, Zhang, & Noll, 2005). Purpose leads to greater psychological flexibility, which
allows individuals to adapt more effectively to changing environmental demands and thus experience fewer
psychological symptoms in the wake of trauma (McKnight & Kashdan, 2009b). As a whole, the above
research points to the paradoxical effect of traumatic events. While these experiences can shatter
assumptive views that the world is a safe and benevolent place (Janoff-Bulman, 1989), they also can offer
people a renewed sense of meaning and purpose as they rebuild their lives.
Social Relationships
Social alliances have served as important, life-sustaining resources throughout human history. If
obtained, social support has allowed individuals to not only survive, but also expand their resources,
perspectives, strengths, and skills by including other people within their self-concept (Aron & Aron, 1996).
With this more expansive self, goal pursuits are more efficient and effective, and it becomes easier to fulfill
basic psychological needs for belonging, competence, and autonomy (Deci & Ryan, 2000). To build a
strong social support network, one must possess sufficient social competence and be driven to develop,
negotiate, and maintain satisfying, meaningful social relationships. It is at this juncture that
psychopathology can impede social functioning and dampen well-being. Psychological disorders cast a
wide net of suffering affecting not only the individual, but also their friends, family, and caregivers (e.g.,
Maurin & Boyd, 1990). And in the same vein as every other human being, anyone with a mental illness can
benefit from social support. Research suggests that greater social support and community integration can
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lead to better social functioning and life satisfaction among people with severe mental illness (e.g., Lam &
Rosenheck, 2000; Rosenfield & Wenzel, 1997). Below, we review research in social functioning among
people with depression, bipolar disorder, social anxiety disorder, schizophrenia, and trauma-related
disorders.
Depression
Evolutionary theories offer insights into the interpersonal nature of depression (e.g., Allen &
Badcock, 2003; Watson & Andrews, 2002). These theories state that when confronted with the threat of
being viewed unfavorably by important people, one views their social value as systematically declining,
increasing the risk of rejection, ostracism, and isolation. Sadness, anhedonia, loss of appetite, psychomotor
retardation, and other forms of disengagement offer a moratorium on social activity. Energy is consolidated
for future interactions whereby one’s social attractiveness can be showcased via hard work, intelligence,
humor/wit, or other desirable behaviors. Concerns about social risk and the depressive symptoms evoked
impact communication, as a depressed person sends behavioral signals of withdrawal and elicits safe forms
of support from others within the social group. Long ago, these behaviors were life-sustaining, as social
exclusion almost certainly resulted in death. In modern times, these risk-management strategies are less
effective and can shut off opportunities to fully engage with loved ones, form new social bonds, and derive
positive emotions from one’s social world.
Depressed mood may have an adverse impact on others via emotional contagion effects. A large
body of evidence suggests that people with depression can socially transmit their depressed mood and other
depressive symptoms to those with whom they interact (e.g., Joiner & Katz, 1999). Interestingly, face-toface
interaction may not be necessary to transmit negative mood states. A large-scale study of Facebook
users found that when intentionally trying not to read the positively valenced posts of friends, people in turn
produced fewer positive and more negative posts (Kramer, Guillory, & Hancock, 2014). More research is
needed to explore the social behaviors of individuals who effectively “catch” negative moods from others,
and how this relationship unfolds within social media platforms. Irritability is another unhelpful social
behavior found among nearly half of patients with major depressive disorder (e.g., Fava et al., 2010; Perlis
et al., 2005). Animal studies suggest that neurotransmitters implicated in the pathophysiology of
depression, such as serotonin, play a role in inhibiting aggressive behavior (Carrillo, Ricci, Coppersmith, &
Melloni, 2009), which may partially explain this heightened irritability. Other studies suggest that
antidepressants targeting serotonin reduce quarrelsome behaviors and promote cooperation during group
tasks (Knutson et al., 1998; Tse & Bond, 2006). Together, these studies offer an illustration of the potential
neurobiological underpinnings of social deficits among people with depression.
Caring for people with depression can be particularly challenging for romantic partners or spouses,
who must take on new roles and responsibilities that formerly belonged to their depressed partner, thus
restricting their own social activities and leading to high subjective burden (Fadden, Bebbington, &
Kuipers, 1987). One study of 260 spouses and relatives of depressed patients found that 20-50% of
caregivers worried about the depressed person’s general health, treatment, safety, and future. Caregivers
also reported strained relationships with the depressed person and often reported seeking mental health
treatment themselves (Van Wijngaarden, Schene, Koeter, 2004). Interestingly, the stage at which the
depressed person is at in the trajectory of their illness can influence caregiver burden. Data suggest that
families tend to have marked difficulties at one year and 3-4 years after the onset of depression - due to
lost hope about their loved one returning “back to normal” (Muscroft & Bowl, 2000). These may be
important intervention junctures to offer support and foster hope. Research shows promise for family-based
interventions aimed at alleviating distress and enhancing knowledge among those caring for patients with
Alzheimer’s disease (e.g., Brodaty, Green, & Koschera, 2003; Eisdorfer et al., 2003), but research is
lacking in the domain of caring for those with depression. Much can be learned from interventions targeting
those who care for patients with other illnesses (such as schizophrenia, detailed in the section below).
Well-being interventions must move beyond the individual to the family unit and even the community for
managing psychological disorders that affect such a sizeable minority of the population.
Bipolar Disorder
Emotion dysregulation is a hallmark of bipolar disorder. One might assume that the positive
emotion persistence characteristic of bipolar disorder leads to deeper social relationships, but research
suggests that this persistence only encompasses positive emotions related to reward and achievement, not
those related to prosocial behaviors (e.g., love and compassion; Shiota, Keltner, & John, 2006). It is now
understood that people with bipolar disorder have difficulties processing and understanding other people’s
emotions as well as their own. Data suggest that people with bipolar disorder are equally skilled as healthy
controls at recognizing faces, but are significantly less skilled at recognizing and accurately labeling
emotional facial expressions (Getz, Shear, & Strakowski, 2003). Issues with facial emotion recognition
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among this population may underlie difficulties in recognizing and resolving interpersonal problems (Getz
et al., 2003). Research supports the notion that deficits in social perception predict poor social functioning
(e.g., Penny, Mueser, & North, 1995), an issue that extends to children and adolescents with bipolar
disorder. Relationships between people with bipolar disorder and their families are often strained. People
with bipolar disorder are more likely to be separated, widowed, or divorced relative to healthy adults
(Sanchez-Moreno et al., 2009). One explanation for this is potential stigma and rejection from family
members due to misinformation and/or lack of understanding about the disorder (Elgie & Morselli, 2007).
Caring for someone with bipolar disorder can be burdensome. Caregivers of people with bipolar disorder
(relative to those with unipolar depression) show higher levels of expressed emotion (i.e., being overly
critical, hostile, and over-involved). Caregiver burden is associated with depressive symptoms, which
negatively impact the prognosis for the person with bipolar disorder and creates a strained home
environment (for a review, see Ogilvie, Morant, & Goodwin, 2005).
Social Anxiety Disorder
People with social anxiety disorder experience marked impairments in virtually every relationship
domain, from friends (Rodebaugh, 2009) to family (Schneier et al., 1994) to romantic relationships
(Sparrevohn & Rapee, 2009). People with social anxiety disorder tend to have fewer friends and are less
satisfied with their friendships (Schneier et al., 1994), even more so than people with major depressive
disorder (Rodebaugh, 2009). These individuals have persistent fears of evaluation when in social situations
or performance settings (Rapee & Heimberg, 1997). While studies suggest that these fears are largely the
product of negative biases regarding one’s social performance (e.g., Alden & Wallace, 1995), these
individuals may actually perform poorly in social interactions and thus garner negative evaluations from
others (e.g., Kashdan & Wenzel, 2005). It may be that negatively biased perceptions of one’s social
performance are not initially founded, but carrying such beliefs into social interactions leads to a selfdirected
focus (e.g., to monitor one’s own performance and protect the self from social threat; Wells &
Papageorgiou, 1998) and a subsequent inability to attend to interaction partners.
Behaviorally, people with social anxiety tend to be less dominant and appear less well-adjusted
according to informant reports (Rodebaugh et al., 2014). They are also less likely to disclose personal
information with others, hindering intimacy development. One study found that socially anxious people
were less likely to reciprocate in a role-play interaction with escalating personal disclosures (Meleshko &
Alden, 1993). Instead, socially anxious participants continued to disclose at a moderate level despite the
magnitude of their partner’s disclosures. Of course, the onus of intimacy building does not fall on one
individual. Data suggest that in dyads, the presence of at least one highly socially anxious individual alters
the quality of an interaction. In a lab-based social interaction, researchers found that during a personal
disclosure condition, closeness was ranked highest when two strangers, both high in social anxiety, were
paired together (Kashdan & Wenzel, 2005). In a small-talk condition, however, greater closeness was
reported when two strangers, both low in social anxiety, were paired together. Across conditions, partners
with marked discrepancies in their levels of social anxiety reported less closeness than those with similar
levels of social anxiety (Kashdan & Wenzel, 2005). This study suggests that socially anxious individuals
may be comforted by mutual anxiety when making personal disclosures, while less socially anxious people
are better able to navigate awkward small talk and still form close bonds.
Positivity deficits among people with social anxiety disorder are evident in their difficulty engaging
in intimacy-building behaviors with romantic partners. One correlational study found that men and women
with social anxiety disorder reported less emotional expression, self-disclosure, and intimacy with their
romantic partners compared with psychologically healthy adults from the community (Sparrevohn &
Rapee, 2009). People with social anxiety disorder also struggle to be curious and enthusiastic in their
support when romantic partners disclose positive events that happened to them. When a partner is curious
and enthusiastic, the partner who disclosed the good news experiences more intense and enduring positive
emotions, attributed to the attentive partner and the relationship (Gable, Reis, Impett, & Asher, 2004). In a
laboratory study of 174 heterosexual couples, people high in social anxiety provided less support for their
partner’s disclosed positive events as measured by self-, partner-, and observer-report. Interestingly, people
high in social anxiety also received less support for their own positive events. Longitudinally, partners of
people high in social anxiety who received less support for their positive event disclosures experienced a
decline in relationship quality and were more likely to terminate the relationship six months later (Kashdan,
Ferssizidis, Farmer, Adams, & McKnight, 2013).
Social anxiety also impedes physical expressions of intimacy in romantic relationships. One daily
diary study followed 150 college students over a 21-day span and found that social anxiety was inversely
associated with feelings of pleasure and connection during sex (Kashdan et al., 2011). In terms of
directionality, stronger feelings of intimacy during sexual activity on a given day led to less socially
anxious feelings the following day; an effect that was particularly true for people suffering from greater
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dispositional social anxiety (Kashdan et al., 2014). Beyond sexuality, recent evidence suggests that
romantic partners with greater levels of social anxiety are less comfortable physically touching someone
else and more frequently avoid physical contact with other people (Kashdan, Doorley, Stiksma, &
Hertenstein, in press). Together, these studies suggest that socially anxious individuals have difficulty
connecting with partners during sex, but stand to benefit the most in terms of anxiety reduction after
positive sexual experiences. Touch discomfort and avoidance may be one barrier to enhanced sexual
intimacy among people with high social anxiety.
Cognitive-behavioral and pharmacological treatments have received much attention for the
treatment of social anxiety disorder (e.g., Rodebaugh, Holaway, & Heimberg, 2004), but other, more
nuanced approaches also show promise in directly targeting the social deficits characteristic of social
anxiety disorder. Social effectiveness therapy (SET) is a multi-component behavioral treatment for
children and adolescents with social anxiety disorder. SET aims to reduce social anxiety and avoidance,
increase interpersonal skills, improve self-concept, and increase the frequency of socially enjoyable events
(Turner, Beidel, Cooley, Woody, & Messer, 1994). The most innovative element of SET is the recruitment
of “super-normal” kids who aid clinicians in helping peers with social anxiety disorder face their social
fears, shape social skills, ensure initial positive social experiences, and serve as role models (Turner et al.,
1994). Studies suggest that SET is an effective treatment for people with severe social anxiety disorder,
teaching crucial skills that maintain high levels of social functioning at a 5-year follow-up assessment
(Beidel, Turner, & Young, 2006). The innovative idea of bringing socially intelligent role models into
psychological interventions is worthy of exploration in adults with social anxiety disorder. Prior work
suggests that engaging family members or romantic partners in therapy improves the outcome of
psychological conditions such as obsessive-compulsive disorder (Abramowitz et al., 2013; Renshaw,
Steketee, & Chambless, 2005). Possible people to include in an intervention for social anxiety disorder
should extend beyond family and romantic partners to anyone with high-level social skill and investment in
therapeutic gain. If what a person requires to improve their emotional and social intelligence is deliberate
practice with everyday social interactions with high-quality feedback, then an allied health professional
alone is insufficient. Interventions can be optimized with access to people who can serve as a guide and
role model. As a promising line of research in strength development, people with and without social anxiety
disorder might benefit from access to role models who encapsulate behaviors that exemplify courage,
curiosity, creativity, compassion, or other ideal personality profiles.
Schizophrenia
Schizophrenia leads to severe and wide-ranging deficits in social functioning (e.g., Hooley, 2010).
These deficits become prominent early in the course of disorder, when symptoms have not yet fully
manifested (i.e., the prodromal phase) (Ballon, Kaur, Marks, & Cadenhead, 2007). Interpersonal problems
are evident among people at heightened risk for developing schizophrenia (Hans, Auerbach, Asarnow,
Styr, & Marcus, 2000), suggesting social problems are not simply a result of disorder symptoms,
medications, or hospitalizations. People with schizophrenia are often ostracized and avoided by others,
making it extremely challenging to form close friendships (Hooley, 2010). One study paired research
assistants with people with schizophrenia and tasked them with forming friendships over a two-week span.
By the end of the study, there was a considerable increase in negative comments by research assistants
directed toward patients with schizophrenia (Nisenson, Berenbaum, & Good, 2001). This study reflects
broader relationship impairments; people with schizophrenia are six times less likely to get married than
the general population (MacCabe, Koupil, & Leon, 2009). They are much less likely to enter into
meaningful, long-term relationships, even when compared to others with severe mental illnesses (Hooley,
2010).
Research suggests that deficits in theory of mind may underlie social dysfunction among people
with schizophrenia, as they are less able to reason about and appreciate other people’s mental states
compared to healthy individuals (Corcoran, Mercer, & Frith, 1995; Frith & Corcoran, 1996). In addition to
duration of illness, poor verbal fluency, and the presence of both negative and positive symptoms, deficits
in theory of mind is one of the strongest predictors of poor social and community functioning (Roncone et
al., 2002). People with schizophrenia have difficulty perceiving social cues; deficits that are unrelated to
age, gender, or medication usage (e.g., Kline, Smith, & Ellis, 1992; Poole, Tobias, & Vinogradov, 2000).
Most studies have focused on deficits in facial and vocal affect recognition. For example, data suggest that
people with schizophrenia perform worse than healthy controls on tasks that require accurate perceptions of
facial emotional expressions. These deficits may be indicative of broader perceptual problems concerning
human faces (e.g., Kerr & Neale, 1993). People with schizophrenia also struggle to perceive emotional
prosody in speech compared to controls (e.g., Murphy & Cutting, 1990). Again, this may be a function of
overarching impairments in vocal recognition (Kerr & Neale, 1993). Various studies suggest that deficits in
facial and vocal perception may be driven by both negative symptoms such as alogia and avolition (e.g.,
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Kohler et al., 2003) and positive symptoms such as hallucinations and delusions (Kohler, Bilker,
Hagendoorn, Gur, & Gur, 2000; Schneider, Gur, Gur, & Shtasel, 1995). Despite general facial and vocal
recognition deficits, one study found that only facial and vocal affect recognition was positively associated
with social dysfunction (Hooker & Park, 2002). Taken together, people with schizophrenia have significant
difficulties perceiving facial cues, emotions, and changes in vocal tone. As a result, they are more likely to
miss the subtleties in social conversations that facilitate intimacy and foster strong interpersonal
connections.
The social environment in which people with schizophrenia live influences their symptomatology.
Data from several large-scale surveys by the World Health Organization (e.g., Jablensky et al., 1992;
Harrison et al., 2001) have offered a tantalizing finding - individuals with schizophrenia in developing
countries exhibit fewer symptoms with a better prognosis than people with schizophrenia in first-world
countries. Prognosis differences are partially explained by the quality of daily social interaction. Families
and caregivers of people with schizophrenia tend to communicate using overly critical and intrusive
comments, also known as high expressed emotion (EE). High EE often leads to negative, emotionally
intense experiences for people with schizophrenia. When a person with schizophrenia shows signs of
recovery and moves from inpatient hospitalization to outpatient or community care, high EE is one of the
strongest predictors of relapse (e.g., Butzlaff & Hooley, 1998). While social interactions characterized by
high EE clearly play a role in schizophrenia, the quality of data collected on EE in the developing world is
much lower than in Western first-world countries (Bhugra & McKenzie, 2003). Thus, it is unclear the
degree to which family EE is a factor in the course of schizophrenia in different countries; an alternative
explanation is that EE findings are primarily a research methodology artifact.
High levels of EE and caregiver burden often go hand-in-hand (e.g., Barrowclough & Parle, 1997;
Scazufca & Kuipers, 1996; Tarrier et al., 2002). Given the debilitating nature of schizophrenia, the high
burden experienced by caregivers is unsurprising. Burden tends to be especially high for caregivers who
are mothers, have less education, and care for younger patients (Gutiérrez-Maldonado, Caqueo-Urízar, &
Kavanagh, 2005). In addition to objective indicators, caregivers’ perceptions of the person’s symptoms
influence their perceived level of burden. Interestingly, caregivers’ perceptions of negative symptom
severity are associated with caregiver burden, while perceptions of positive symptom severity are not
(Provencher & Mueser, 1997). One explanation is that positive symptoms are more commonly viewed as
uncontrollable whereas negative symptoms are viewed as more malleable and manageable by the person.
Family interventions for people with schizophrenia and caregivers aim to reduce EE, improve caregiver
coping abilities, and enhance caregiver knowledge (including correcting misbeliefs) (Pharoah, Mari,
Rathbone, & Wong, 2010). These interventions have shown promise in alleviating caregiver distress and
stigmatizing beliefs and behaviors (e.g., Szmukler, Herrman, Bloch, Colusa, & Benson, 1996); these
interventions appear to be less effective at improving caregiver coping abilities (Szmukler et al., 1996;
Szmukler et al., 2003). More research is needed to tease apart what works and what should be changed with
regard to family-based interventions in an effort to better support patients with schizophrenia, aid family
members, and promote positive social communication and functioning.
Trauma-Related Disorders
Post-traumatic stress disorder (PTSD) is associated with a wide range of social problems including
social anxiety (Crowson, Frueh, Beidel, & Turner, 1998), anger (Jakupcak et al., 2007), sexual dysfunction
(Cosgrove et al., 2002), family discord (Galovski & Lyons, 2004) and strained romantic relationships
(Renshaw & Caska, 2012; Renshaw, Allen, Carter, Markman, & Stanley, 2014). Social support plays a
critical role in the onset, course, and severity of trauma-related symptoms. A lack of social support has
been cited as a risk factor for PTSD among war veterans (e.g., King, King, Fairbank, Keane, & Adams,
1998; Schnurr, Lunney, & Sengupta, 2004) and survivors of disasters and violent crimes (Johansen, Wahl,
Eilertsen, & Weisaeth, 2007; Zoellner, Foa, & Brigidi, 1999). One study found that negative reactions from
other people following a traumatic event were strongly associated with PTSD symptoms and partially
explained the association between victim-blame and PTSD (Ullman, Townsend, Filipas, & Starzynski,
2007). Strong social support networks can bolster resilience and reduce PTSD severity in the aftermath of
traumatic events (Pietrzak, Johnson, Goldstein, Malley, & Southwick, 2009; Schumm, Briggs-Phillips, &
Hobfoll, 2006).
Data suggest that male veterans with chronic PTSD self-disclose less frequently, are less
emotionally expressive with romantic partners, and have more intimacy problems compared to veterans
without PTSD (Carroll, Rueger, Foy, & Donahoe, 1985; Riggs, Byrne, Weathers, & Litz, 1998). Veterans
with, compared to without, PTSD report higher divorce rates (Cook, Riggs, Thompson, Coyne, & Sheikh,
2004). Of greater concern, male veterans with PTSD compared to without PTSD are more likely to be
emotionally and/or physically abusive toward partners and children (Monson, Taft, & Fredman, 2009).
Research has explored possible mechanisms underlying the association between PTSD and relationship
483
dysfunction. One study of Iraq/Afghanistan and Vietnam veterans found that romantic partners’
perceptions of withdrawal and numbness symptoms were associated with greater relationship distress,
while partners’ perceptions of re-experiencing symptoms were associated with less relationship distress
(Renshaw & Caska, 2012). These findings suggest that PTSD symptoms that are less overt and cause
individuals to pull away from partners (e.g., an inability to express loving feelings, withdrawal) may be
particularly detrimental to relationship functioning, while symptoms that are more directly related to the
trauma (e.g., physiological reactions to trauma-related cues) minimize partner distress and pull for
supportive responses. Other research suggests that re-experiencing is associated with wives’ perceptions
that a veteran’s PTSD symptoms are out of his control (i.e., external attributions), while withdrawal and
numbness are associated with wives’ perceptions that the veteran is responsible for his symptoms (i.e.,
internal attributions) (Renshaw et al., 2014).
Qualitative interviews with veterans suggest that harnessing strong military friendships are effective
in navigating the difficult re-integration from combat zones back to the day-to-day family affairs of civilian
life (Hinojosa & Hinojosa, 2011). Integrating families and relationship partners into treatment for returning
veterans and others suffering from PTSD may be crucial in reducing emotional dysfunction and improving
relationship communication, satisfaction, and commitment (Monson, Fredman, & Adair, 2008).
Concluding Thoughts
Generally, people with psychological disorders experience significant impairments in well-being.
But this byline fails to capture the complexity of associations between particular disorders and particular
dimensions of well-being. Several theoretically meaningful paradoxes exist. People with depression
respond to negative events with less distress than healthy adults. People with bipolar disorder experience
greater positive emotions than psychologically healthy adults and devote considerable effort to dampen
potentially rewarding experiences. People with social anxiety disorder experience chronically low levels of
positive emotions in both social and non-social situations; psychological difficulties that can be reduced by
the presence of extremely positive sexual experiences or effort towards a purpose in life. People with
schizophrenia construct meaning from their hallucinations and delusions, and often treatment leads to a
painful reduction in meaning in life. Trauma survivors often derive stronger, appreciative, purposeful lives
upon coping with their stressful experiences. The present chapter reviews research that highlights
significant impairment across psychological disorders, but also illustrates that across three domains of wellbeing—positive
emotions, meaning and purpose in life, and social relationships—a careful consideration of
contextual influences offers new insights and intervention targets. Only by exploring the interplay between
psychopathology and well-being will scientists and practitioners meet the demanding challenge of reducing
suffering and improving the human condition.
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Subjective Well-Being and Physical Health
By Marie P. Cross, University of California, Irvine; Lauren Hofschneider, University of California, Los
Angeles; Mikaela Grimm, California State University, Fullerton; Sarah D. Pressman, University of
California, Irvine
Citation
Cross, M. P., Hofschneider, L., Grimm, M., & Pressman, S. D. (2018). Subjective well-being and
physical health. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT:
DEF Publishers. DOI:nobascholar.com
Abstract
In this chapter, we review the literature on the connections between various facets of the broad construct of
subjective well-being (SWB) and physical health. We aim to highlight which variables have been explored
most, which need more research, and to examine possible overlap or similarities among these variables.
We divide these positive psychological constructs into six separate categories: hedonic constructs,
eudaimonic constructs, well-being practices, social well-being, motivation and efficacy, and future-oriented
constructs. Each construct will be defined and explored in terms of its association with various health
outcomes such as morbidity and mortality, and we discuss both the strengths and weaknesses of the
literature on each construct. Next, we discuss some possible pathways that may underlie the association
between SWB and physical health. Finally, we end with a discussion of the literature as a whole and
suggest future directions for research in this area to take.
Keywords: Well-being, Health, Positive affect, Optimism, Mindfulness
To be both happy and healthy is a common goal among many individuals. However, some might
not know the extent to which these variables are intricately connected. This chapter details the growing
science connecting physical health to subjective well-being (SWB) and, more specifically, the various
positive facets within this broad construct. Each positive psychological measure will be defined and
explored in terms of its association with various health outcomes such as disease incidence, morbidity, and
mortality. We then move to a discussion of possible pathways through which these connections may occur,
followed by a general summary about the state of the literature as a whole. First, however, we begin by
describing what we mean when we refer to SWB and physical health.
What is Subjective Well-Being?
Happiness is dependent on a number of psychological factors, as demonstrated by an original
review of the literature conducted by Wilson (1967). The study of SWB flourished in response to this initial
work and has since incorporated research on evaluations of the self, indices of life satisfaction, and
emotional responses to life events, among other topics (Diener, Suh, Lucas, & Smith, 1999; Kozma, Stone,
& Stones, 2000; Lyubomirsky, King, & Diener, 2005). Life satisfaction and positive—rather than negative
—aspects of psychology are the primary focus of SWB, although in some cases, low negative affect (NA)
may be considered an indicator of SWB as well (Diener et al., 1999; Ryff, 1989).
What is Physical Health?
While difficult to define, physical health can be broadly described as the systems of the body
carrying out physiological functions properly, with “good” physical health frequently indicated in research
by the lack of illness or disease (Breslow, 1972; Idler & Kasl, 1991), as opposed to the preferred World
Health Organization definition that health is more than the absence of disease (World Health Organization,
1948). Objective physical health outcomes are characterized by measures that can be confirmed by medical
tests such as the presence of a disease like cancer or a disability like a traumatic brain injury. Furthermore,
there are a number of health-related risk indicators, such as binge drinking or not exercising, which can be
measured in order to attain an estimate of physical health. Many of these physical health outcomes,
however, do not typically encompass mental health variables like depression (Howell, Kern, &
Lyubomirsky, 2007). To correct for this, physical health can also be assessed subjectively and with selfreport.
For example, subjective health is frequently assessed by an individual’s interpretation of symptoms
of illness or perceptions of pain. Unlike objective health outcomes that rely on medical testing to determine
classification, subjective health outcomes are classified by self-reports. In addition to objective and
subjective health outcomes, studies also investigate physiological parameters such as hormone levels or
blood pressure. It is important to note that while current physiological parameters may be connected with
future health outcomes (Pressman & Cohen, 2005; Steptoe, Wardle, & Marmot, 2005), physiology is not a
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health outcome in its own right and should be considered separately from outcomes such as morbidity and
mortality.
Review
The goals of this chapter are to examine how different positive psychological constructs within the
broad umbrella of SWB relate to physical health outcomes. We begin our review with a discussion of
hedonic constructs, that is, factors that are associated with the affective component of SWB, including
positive affect (PA) and life satisfaction. Next, we go over eudaimonic constructs, or constructs that are
associated with the self-realization component of SWB, including autonomy, self-esteem, perceived control,
and life purpose. Following this section are constructs that are well-being practices, including mindfulness,
self-affirmation, and gratitude. Although some of these constructs have aspects that are dispositional, we
chose to categorize them in this section because they are often studied as alterable states. We then move to
constructs that are associated with social well-being, including social support and networks and social
control, and constructs that are associated with motivation and efficacy, including self-efficacy,
determination and grit, and hardiness. The final section of the review focuses on future-oriented constructs,
including optimism and hope, and a quick discussion of under-researched positive constructs. While low
NA can be considered an aspect of SWB, we focus only on positive constructs given our interest in
elucidating the connections between these and physical wellness as opposed to the effects of the absence of
negativity. We end our chapter with a discussion of possible pathways connecting SWB to physical health,
as well as a number of suggestions for future directions in this area of research.
Hedonic Constructs
The distinction between hedonia and eudaimonia originates from Aristotle’s philosophy regarding
what constitutes “the good life,” and this distinction is still seen in the SWB literature today. Hedonic
constructs are driven by the search for pleasure and happiness, whereas eudaimonic constructs are focused
on cultivating well-being through long-term emotional processes that focus on meaningful life pursuits
(Waterman, 2007; Waterman, 2008). We begin this review by focusing on hedonic constructs, and then
move to eudaimonic constructs.
Positive Affect
One of the largest literatures connecting SWB to physical health outcomes is that focusing on PA
(for a review, see Pressman & Cohen, 2005). PA varies in time duration and can be assessed as a brief state
(positive emotion felt “in the moment”) or a dispositional trait. Although state and trait affect are highly
correlated, state affect is more variable, easier to manipulate in the lab, and less likely to be tied to longterm
health outcomes given the brevity of the experience. Both state and trait affect are almost exclusively
measured by self-report with popular scales like the Positive and Negative Affect Schedule (Watson, Clark,
& Tellegen, 1988). Only occasional health oriented studies use other PA assessment methods such as facial
coding (e.g., Abel & Kruger, 2010; Cross & Pressman, in prep) or positive emotion word usage (Danner,
Snowdon, & Friesen, 2001; Pressman & Cohen, 2012).
Overall, both state and trait PA have been connected with a number of physical health outcomes.
The area with the most research has shown that healthy individuals with higher levels of PA live longer (see
review by Chida & Steptoe, 2008). PA has also been linked to decreased mortality within a number of
diseases that have longer prognoses, such as coronary heart disease and diabetes (Moskowitz, Epel, &
Acree, 2008; van Domburg, Pedersen, van den Brand, & Erdman, 2001). In well-designed exposure to
infectious illness studies, people high in PA are less likely to develop a cold or flu after being infected
(Cohen, Alper, Doyle, Treanor, & Turner, 2006; Cohen, Doyle, Turner, Alper, & Skoner, 2003). One area
in which the literature is more mixed, however, is for diseases with short-term prognoses, such as end-stage
renal disease and advanced cancer, where sometimes benefits are not found or disease survival is reduced
(Cassileth, Lusk, Miller, Brown, & Miller, 1985; Devins et al., 1990), although in some cases, PA does
help (e.g., Svebak, Kristoffersen, & Aasarød, 2006). One explanation for this is that high levels of PA in the
face of life threatening disease may lead to not adhering to medical regimens or seeking help as frequently
due to the concomitant reduced perceptions of threat or negativity. Finally, it is clear that there are many
subjective benefits of high PA. Individuals with high PA report fewer symptoms of illness and less pain in
chronic and experimental studies (Pettit, Kline, Gencoz, Gencoz, & Joiner, 2001; Zautra, Johnson, & Davis,
2005). However, it is not clear to what extent these differences are biological versus perceptually based.
On top of the known objective and subjective connections between PA and health, much work has
been done examining plausible pathways that might be responsible for these associations. As outlined by
Pressman and Cohen (2005), there are ample connections between PA and immune, endocrine, and
cardiovascular function that might underlie health effects, in addition to behavioral and social pathways that
might also be responsible. PA is also known to ameliorate the negative consequences of stress, which may
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also lead to better health (Fredrickson & Levenson, 1998; Pressman & Cohen, 2005).
More work in this area is needed to understand the precise timeline and diseases most helped by
PA. While there are many mortality studies of healthy samples, research investigating morbidity (incidence
of disease) and survival needs to be replicated within specific diseases. Another important aspect in this
work is how NA is treated. Recent work has begun to control for NA within analyses in order to allow
researchers to isolate the unique impact of PA on health (e.g., Pressman, Gallagher, & Lopez, 2013).
However, in some cases, measures such as depression are also used due to high PA-NA overlap, leaving the
question of what the appropriate statistical and theoretical approach might be. As alluded to above, there is
also overuse of self-report as a method to assess PA, which may be a problem due to biases in selfpresentation
(Wojcik, Hovasapian, Graham, Motyl, & Ditto, 2015), and an overreliance on white North
American and Western European samples, leaving many important directions for this area.
Life Satisfaction
Life satisfaction is a measure tapping into a cognitive evaluation of one’s life; all things being
considered, is it satisfactory? We chose to classify life satisfaction as a hedonic construct in this chapter
because of its role in overall SWB (discussed in the earlier section defining SWB), but it is important to
note that the cognitive component of life satisfaction can also be considered a eudaimonic construct
(Kashdan, Biswas-Diener, & King, 2008). Higher life satisfaction has been connected to better subjective
outcomes such as higher levels of perceived health and reductions in self-reported pain (Einvik, Ekeberg,
Klemsdal, Sandvik, & Hjerkinn, 2009; Kreitler, Chaitchik, Rapoport, Kreitler, & Algor, 1993; Laborde &
Powers, 1985), in addition to differences in objective health outcomes (see review by Strine, Chapman,
Balluz, Moriarty, & Mokdad, 2008) such as asthma prevalence in clinical populations (Huovinen, Kaprio,
& Koskenvuo, 2001) and longer life span (Collins, Glei, & Goldman, 2009; Kimm, Sull, Gombojav, Yi, &
Ohrr, 2012; Lacruz, Emeny, Baumert, & Ladwig, 2011). There are, however, some inconsistencies in the
literature. For example, despite relative consistency in the longevity literature, one study of Finnish
participants found that life satisfaction was only protective for men (Koivumaa-Honkanen et al., 2000), and
other studies found no relationship between cancer survival rate and life satisfaction, despite measurements
using multi-item scales (Cassileth, Walsh, & Lusk, 1988; Lillberg et al., 2002). Two additional studies
observed that life satisfaction failed to significantly predict better recovery from physical disability
(Corrigan, Bogner, Mysiw, Clinchot, & Fugate, 2001; Dijkers, 1999). Further research is needed to
disentangle these disparate findings. Is it the case that some measures of life satisfaction (e.g., single item
assessments with poorer reliability) predict differently than more validated measures (e.g., the Satisfaction
with Life Scale; Diener, Emmons, Larsen, & Griffin, 1985)? Are certain populations such as older samples
or individuals with certain illnesses helped more by life satisfaction? Finally, what is the pathway by which
life satisfaction could improve physical health? Do individuals with more life satisfaction feel happier, and,
in turn, is it the PA-associated physiological and behavioral benefits driving these associations?
Eudaimonic Constructs
Autonomy
Autonomy is defined as the freedom to be self-determined and to act upon intrinsic motivations
(Ryan & Deci, 1987). Health psychologists are mostly concerned about the environmental or social cues
that facilitate and support autonomy. For example, the Health Care Climate Questionnaire (Williams,
Grow, Freedman, Ryan, & Deci, 1996) asks (typically adult) participants to rate whether their practitioner
acted in ways that supported their autonomy. Increased feelings of practitioner autonomy support can lead
to better health outcomes, possibly through patients feeling personally motivated to improve their own
health. Diabetic patients who reported greater levels of personal motivation and greater levels of
practitioner support had improved blood glucose levels over time. Moreover, personal motivation appeared
to explain the relationship between practitioner autonomy support and health outcomes (Williams,
McGregor, King, Nelson, & Glasgow, 2005). Practitioner autonomy support alone, however, does not
necessarily always lead to better glucose levels across diabetic samples (e.g., Lee & Lin, 2010; Ng et al.,
2012). Thus, research on autonomy must determine whether health outcomes are driven by supportive
systems or by personal motivation.
Few studies have examined how parental autonomy support can influence blood glucose levels in
diabetic children (Hanna & Guthrie, 2003). While results favored positive outcomes, Wysocki and
colleagues (1996) note one limitation to supporting child autonomy: adolescents who were excessively
responsible for their self-care reported more hospital visits, poorer blood glucose control, and worse
treatment adherence compared to adolescents with parents who shared diabetes management responsibilities
and adolescents with parents who were more controlling of their child’s diabetes management
responsibilities. Sociological factors such as cultural ideology are also important in this area. Women’s
autonomy exemplifies this interdisciplinary approach and is usually measured as a woman’s ability to
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make decisions in her household or her cumulative years of education. Lower levels of this construct have
been linked to higher rates of infant mortality and undernutrition in South Asia (Adhikari & Sawangdee,
2011; Shroff et al., 2011). While autonomy has succeeded in incorporating cultural and developmental
considerations in its construct measures, the research examines a narrow range of objective health outcomes
and should diversify its reach given the likely importance of perceptions of autonomy on any disease that
requires a high level of self-management or behavioral change.
Self-Esteem
Self-esteem, almost exclusively measured with the Rosenberg Self-Esteem Scale (Rosenberg,
1965), is the subjective evaluation of a person’s self-worth. Despite the age of this established scale, the
scope of literature examining the relationship between self-esteem and physical health is neither extensive
nor consistent. Whereas higher levels of self-esteem have been connected to better self-rated health (Cott,
Gignac, & Badley, 2014) and functional status (Blake, 1991; Chang & Mackenzie, 1998), self-esteem has
failed to predict improvements in blood glucose levels for diabetics (Bryden et al., 2001; Johnston-Brooks,
Lewis, & Garg, 2002) and has not been singularly predictive of all-cause mortality. One study found that
feelings of hopelessness, among other negative psychosocial factors, appeared to confound the protective
potential of self-esteem (Stamatakis et al., 2004). For example, Weaver and colleagues (1997) observed that
depressed moods mediated the relationship between self-esteem and functional status for individuals with
chronic obstructive pulmonary disease. Another study demonstrated that the relationship between selfesteem
and the risk of mortality attenuated after adjusting for feelings of hopelessness (Stamatakis et al.,
2004). To develop a clearer understanding as to how self-esteem can influence physical health, future
studies should account for the influence of both positive and negative emotions and examine whether selfesteem
in its own right has a health effect independent of affective pathways.
Perceived Control
Perceptions of control are surprisingly important to medical outcomes. While multidimensional,
control is typically assessed as either “locus of control” (i.e., do people explain events as due to internal or
external reasons; Rotter, 1966) or as a perception that one has control over certain aspects of one’s life.
Behaviorally, control can also be assessed or manipulated in the laboratory by allowing participants to
manipulate a stimulus, allowing participants to choose between alternatives (Averill, 1973), or removing
the ability to control a stimulus (e.g., noise bursts; Pennebaker, Burnam, Schaeffer, & Harper, 1977).
Control has an overwhelmingly positive effect on chronic conditions. For example, lower
perceptions of control are predictive of poorer reports of health (e.g., Bobak, Pikhart, Hertzman, Rose, &
Marmot, 1998; Lachman & Weaver, 1998), higher incidences of cardiac-related events (Bosma, Marmot,
& Hemingway, 1997; Siegrist, Peter, Junge, Cremer, & Seidel, 1990), and reduced blood glucose control in
diabetics (e.g., Band & Weisz, 1990; Broadbent, Donkin, & Stroh, 2011). These benefits may be partially
attributed to the effects of control on stress, given findings showing that the use or feeling of control is
related to lower blood pressure and heart rate during stressful laboratory tasks (e.g., DeGood, 1975;
Hokanson, DeGood, Forrest, & Brittain, 1971; Peters, Godaert, & Ballieux, 1998).
A seminal study by Rodin and Langer (1977) found that nursing home residents who were
manipulated to feel more personal control were less likely to die at a one-year follow-up, a conclusion
corroborated by a number of prospective longitudinal studies on control (e.g., Infurna, Gerstorf, Ram,
Schupp, & Wagner, 2011; Penninx et al., 1997; Turiano, Chapman, Agrigoroaei, Infurna, & Lachman,
2014). While the presence of control is associated with a longer life, the loss of control may also have
severe consequences. For example, a study of nursing home residents found that those who previously had
control over the frequency and duration of visits from student volunteers were more likely to die at followup,
when the study manipulation ended and the control was lost (Schulz & Hanusa, 1978). Altogether, the
connections between control and health have been subject to extensive research, in both naturally occurring
and experimental settings. Stress reduction is likely one pathway to these benefits, although further research
on the mechanisms is warranted, as is continued work on how control can benefit different types of illness
and at what points in time.
Life Purpose
Life purpose is defined as the ability to find life meaningful and is most frequently measured with
the Purpose in Life subscale in the Psychological Scale of Wellbeing (Ryff & Keyes, 1995). Overall, a
greater sense of life purpose has been positively associated with objective indicators of physiological
function and physical health. For example, those with greater life purpose report better glucose control
(Kim, Sun, Park, & Peterson, 2013), lower cholesterol (Ryff, Singer, & Dienberg Love, 2004), and fewer
disabilities (Cohen, Bavishi, & Rozanski, 2015; Kim, Sun, Park, Kubzansky, & Peterson, 2013; Schleicher
et al., 2005; Smith & Zautra, 2004). Life purpose has also been associated with increased longevity (e.g.,
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Boyle, Barnes, Buchman, & Bennett, 2009; Cohen, Bavishi, & Rozanski, 2015), even after accounting for
factors connected to life purpose such as social relationships and NA (Hill & Turiano, 2014). However,
there may be important sex differences in the connections between life purpose and health. For example,
elderly women with greater life purpose show lower inflammatory cytokine responses, which are related to
better physical health outcomes (Friedman, Hayney, Love, Singer, & Ryff, 2007; Ryff et al., 2004), and
men with greater life purpose have fewer incidences of cardiovascular-related deaths (Koizumi, Ito,
Kaneko, & Motohashi, 2008). In sum, the current research on life purpose provides strong evidence that it
is largely beneficial for physical health, and, if sex differences do persist, it is important to question how life
purpose is unique to men and women.
Well-Being Practices
Mindfulness
Mindfulness is the ability to direct attention to the physical and mental processes that occur in daily
life (Epstein, 1999) and can be studied as a malleable behavior or disposition. Dispositional mindfulness, an
inherent ability to practice mindfulness, is measured through self-report scales such as the Five Facet
Mindfulness Questionnaire (Baer, Smith, Hopkins, & Toney, 2001). The little research connecting
dispositional mindfulness to physical health is unconvincing at this point due to its overreliance on nonobjective
self-reports (e.g., Bränström, Duncan, & Moskowitz, 2011; Tamagawa et al., 2013) and
insufficient evidence in any one disease. However, there is a move towards more research on this topic,
including new studies examining connections to detrimental cardiovascular events (Loucks et al., 2015)
and diabetes (Loucks et al., 2016). Furthermore, measures of dispositional mindfulness have been
criticized for lacking content validity. Researchers argue that without a reliable and predictable measure of
mindfulness, assertions of the health benefits of mindfulness are weak (Park, Reilly-Spong, & Gross, 2013).
Increased attention to objective indicators of physical health and improvements to existing mindfulness
scales may remedy this issue.
In contrast, mindfulness as a learned skill is a subject of prolific research and yields a number of
positive results for chronic conditions (see reviews by Bonadonna, 2003; Chiesa & Serretti, 2011; Merkes,
2010). A frequently cited mindfulness intervention program, mindfulness-based stress reduction (MBSR;
Kabat-Zinn, 1982), uses breathing and yoga exercises (partnered with mindfulness skill instruction, such as
a focus on productive coping mechanisms) to engage patients. As reviewed by Grossman and colleagues
(2004), there is evidence that this program benefits a wide array of psychological and physical conditions,
from depression to cancer, by teaching patients proper coping skills. Impressively, studies have also
demonstrated that HIV-positive individuals who complete MBSR programs show improvements in
immune system functioning, including critical T-cell numbers (Creswell, Myers, Cole, & Irwin, 2009;
Robinson, Mathews, & Witek-Janusek, 2003). While these outcomes are promising, future research should
distinguish between the effects of psychological well-being manipulations that result from engaging in
mindfulness versus the effects of engaging in the physical activities and behaviors used to facilitate
mindfulness practices (e.g., yoga, muscle relaxation, breathing exercises).
Self-Affirmation
When one’s self concept is threatened, self-affirmation, or the affirmation of areas that emphasize
one’s strengths (e.g., values, beliefs, roles), can occur in order to reestablish positive self-worth, integrity,
and self-concept (Sherman & Cohen, 2006). Most self-affirmation studies have participants either complete
a scale such as the Allport-Vernon-Lindzey Scale (Allport, Vernon, & Lindzey, 1960) that aims to establish
how highly one views their personal strengths or manipulate affirmation by having participants write an
essay about a value that is important to them (McQueen & Klein, 2006). Studies that utilize scales such as
the Allport-Vernon-Lindzey Scale do so in order to determine whether participants can be categorized as
having high, moderate, or low self-affirmation, while studies that employ manipulations such as essay
writing aim to induce feelings of high self-affirmation.
Most studies that look at a possible relation between self-affirmation and physical health focus on
the health-mediating physiological stress response and have repeatedly shown that self-affirmation alters
stress trajectories (Creswell et al., 2005; Sherman, Bunyan, Creswell, & Jaremka, 2009). For example,
Creswell and colleagues (2005) revealed that higher levels of self-affirmation and personal identification
with values were associated with lower cortisol levels after being exposed to stress. Self-affirmation has
also been used as a tool to promote behavioral change that could lead to better health. One study found that
after three months, women in the self-affirmation condition weighed less, had lower body mass indexes,
and had smaller waist measurements versus those in the control group (Logel & Cohen, 2012). Other
studies have shown benefits of self-affirmation on smoking cessation (Harris & Epton, 2009). One possible
explanation for these behavioral changes is the connection between self-affirmation and self-control,
making this tool potentially relevant to many other negative health behavior change programs. However,
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this research area is still in its infancy and longer follow-ups are needed to determine the downstream
health impact of these behavioral effects, as well as studies examining the objective impact of selfaffirmation
on illness and disease.
Gratitude
Gratitude is a popular construct in well-being research, and while frequently studied in the context
of interventions (e.g., gratitude diaries; Emmons & McCullough, 2003), it can also be conceptualized as a
dispositional tendency to recognize and appreciate the benevolence of another person or being (Krause,
Emmons, & Ironson, 2015; McCullough, Emmons, & Tsang, 2002). Positive associations between
gratitude and physical health are disparate and largely limited to self-report data, such as single item
measures of overall health (Krause & Hayward, 2014) or evaluations of physical health symptoms
(Emmons & McCullough, 2003; Krause et al., 2015) and functioning (Hill, Allemand, & Roberts, 2013;
Millstein et al., 2016). Furthermore, there are some mixed findings, such as one study that found no benefit
for neuromuscular disorder related pain (Emmons & McCullough, 2003). Hill and colleagues (2013)
suggest that gratitude may impact physical health through mediating factors, such as mental health status
and participation in health-promoting behaviors (e.g., exercise and good nutrition). Indeed, past work has
found connections between gratitude exercises and better sleep (Emmons & McCullough, 2003).
Surprisingly, only one study to date has examined the effects of gratitude on objective physiological and
physical health outcomes (i.e., inflammatory biomarkers and hospital visits), but failed to provide any
conclusive evidence for the benefits of gratitude (Huffman et al., 2016), demonstrating a clear need to do
more research connecting both dispositional gratitude and interventions to non self-report health outcomes.
Social Well-Being
Social Support and Networks
While too large a literature to review here, connections between social relationships and health are
some of the strongest and most consistent psychosocial correlates of health in the medical literature. Effect
sizes are large, with the negative effect of social isolation on mortality comparable to that of regular
smoking (see reviews by Holt-Lunstad, Smith, & Layton, 2010; House, Landis, & Umberson, 1988; Tay,
Tan, Diener, & Gonzalez, 2013). This literature also boasts a diverse range of study samples, including
healthy and ill participants, minorities, and pet owners (e.g., Barth, Schneider, & von Kanel, 2010; Cohen,
Kaplan, & Manuck, 1994; Ford, Tilley, & McDonald, 1998; Reblin & Uchino, 2008; Schaefer, Coyne, &
Lazarus, 1981; Shumaker & Hill, 1991; Tang, Brown, Funnell, & Anderson, 2008; Uchino, 2006).
SWB definitions frequently include “good relationships” as a component of this broad construct. In
the health literature, “good relationships” can be assessed in numerous ways. Social support is broadly
defined as the resources provided by one’s social sphere (Cohen & Syme, 1985), such as emotional support
(e.g., a shoulder to cry on) or objective resources (e.g., being lent money). This type of social wellness is
most typically implicated in relation to stress and its ability to reduce the negative sequelae associated with
negative experiences (Cohen & Wills, 1985; Thoits, 1982), but is also more generally related to an array of
health outcomes such as cardiovascular disease, cancer, and overall mortality, as well as an array of
possible physiological and behavioral mechanisms (see reviews by Barth et al., 2010; Cohen et al., 1994;
Holt-Lunstad et al., 2010; Lett et al., 2005; Pinquart & Duberstein, 2010; Uchino, Cacioppo, & KiecoltGlaser,
1996). Structural measures of relationships have also been thoroughly connected to health (e.g.,
marital status, total number of relationships; Holt-Lunstad et al., 2010; House et al., 1988; Kiecolt-Glaser
& Newton, 2001). To complicate things further, subjective characteristics of relationships beyond support,
such as emotional feelings of love (see reviews by Green, Shellenberger, & Siegel, 1996; Traupmann &
Hatfield, 1981) or cognitive assessments of relationship satisfaction (Krause, 1987; Woloshin et al., 1997),
may also matter. Thus, while it is clear that positive relationship characteristics are beneficial for us, one
important remaining question is how they are related to or distinct from the effects of other positive
psychological factors. PA and related positive constructs are intricately connected to social relationships
(i.e., happy people have better relationships, relationships make us happy), making it somewhat difficult to
disentangle the effects of these variables.
Social Control
One way that relationships are good for us is via the social control inflicted on us by our
relationship partners, that is, the strategies used to regulate and influence another person to adopt positive
health practices (Thoits, 2011). Social control might include behaviors such as efforts to manage a specific
illness, alter health behaviors, or even promote medication adherence (e.g., August & Sorkin, 2010; Berg et
al., 2013). Research has indicated that attempts at social control can be related to positive health behavior
outcomes such as a reduction in smoking habits and an increase in physical activity (Umberson, 1992), yet
its direct influence on disease outcomes is marginal and has received mixed support (Thorpe, Lewis, &
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Sterba, 2008; Tucker & Anders, 2001). One critical aspect of social control is how the strategies are
received. In most cases, when social control is received positively, it leads to better adherence to medical
and dietary regimens (August & Sorkin, 2010; Berg et al., 2013; Stephens, Rook, Franks, Khan, & Iida,
2010). Alternatively, unwarranted social control may be perceived as criticism and hinder the development
or continuation of positive health behaviors (Lewis & Rook, 1999). Future studies should consider how this
aspect of relationships could directly relate to physical health outcomes, as well as variations in populations
and methods that might influence when social control is helpful versus harmful for physical well-being.
Motivation and Efficacy
Self-Efficacy
Self-efficacy is defined as one’s perceived ability to set and complete goals to achieve a specific
outcome, and it has been linked to better overall health and coping in studies ranging from cancer to health
promoting behaviors (see review by Strecher, McEvoy DeVellis, Becker, & Rosenstock, 1986). Beyond
studying self-efficacy as a perception, a rich area of research introduces self-efficacy interventions to those
who are seeking to change a health behavior (Stuart, Borland, & McMurray, 1994). For example, one study
found that individuals who successfully completed a self-efficacy smoking cessation program were less
likely to relapse a year after completion (O’Leary, 1985). Studies such as this have been replicated and
have produced consistent results that link high self-efficacy with successful smoking cessation (Stuart et
al., 1994). Self-efficacy is effective at helping individuals institute and maintain change and is also an
effective tool to help individuals complete short-term and long-term health oriented goals (Strecher et al.,
1986). Unfortunately, while the health promoting behavior literature is strong, much less work has taught us
what self-efficacy can do for long-term health due to the focus on this construct as a coping and behavior
altering mechanism (e.g., Schwarzer & Renner, 2000). Thus, there is a need for intervention studies that
alter behavior with long-term follow-ups examining the downstream effects on disease as well as behavior
change.
Determination and Grit
Determination, or one’s ability to initiate and maintain a desired behavior or outcome, is
understudied in relation to health but has recently begun to attract attention due to its possible use in health
behavior change (Deci & Ryan, 2008; Ryan, Patrick, Deci, & Williams, 2008). Therefore, similar to selfefficacy,
studies in this area emphasize health behaviors rather than objective health outcomes (e.g., goal
adherence and maintenance of health promoting behaviors; Deci & Ryan, 2008; Ryan et al., 2008;
Williams, Rodin, Ryan, Grolnick & Deci, 1998). Similar to determination is the relatively new construct of
grit, defined as the ability to persevere to pursue one’s long-term goals in spite of challenges (Duckworth &
Gross, 2014). It is not hard to imagine that these constructs will have downstream impacts on health due to
their ability to increase and maintain positive health behaviors, even when willpower is low or behavior is
difficult, but this area is in its infancy. Furthermore, some investigators challenge the claim that grit is a
positive trait for certain underrepresented populations such as African American students because the
construct ignores the toll that societal racism can take on these individuals (e.g., McGee & Stovall, 2015).
Thus, future research on this topic should investigate grit within different ethnic groups in order to
understand for whom it is beneficial and for whom it is not.
Hardiness
Hardiness is a personality type that consists of three elements thought to aid individuals to
successfully cope with stress: commitment, control, and challenge (Ouellette Kobasa, Maddi, Puccetti, &
Zola, 1985). Those high in hardiness are able to commit to a goal, feel they have control over their
environment, and will likely engage in situations or activities that challenge them. Thus, this construct
overlaps with other previously discussed measures such as control, determination, and efficacy. Research
has confirmed that high hardiness is linked to less stress related chronic illness (e.g., cardiovascular
conditions; Kobasa, Maddi, & Kahn, 1982) and less stress related acute illness (Nowack, 1989), even in
studies accounting for possible alternative explanations like high social support or more exercise (Kobasa
et al., 1982). Despite the clear benefits for stress and stress-related illness, little research has connected
hardiness to objective disease outcomes (see Okun, Zautra, & Robinson, 1988, for an exception examining
arthritis symptoms). Thus, like many other constructs in this section, for hardiness to be considered
important in the medical realm, research will have to determine its impact on disease and other objective
health outcomes and physiological and behavioral pathways. Due to its conceptual overlap with many other
constructs, future research also needs to determine to what extent it predicts above and beyond other
measures more thoroughly examined in the health arena.
Future-Oriented Constructs
Optimism
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Many studies have sought to determine the relationship between optimism and various health
conditions, ranging from cancer to chronic pain. While optimism can be specific to a given situation, what
is most commonly studied in health research is dispositional optimism, or the general tendency to believe
that good things happen more frequently than bad things (Scheier & Carver, 1985) as assessed by selfreport
(e.g., the revised Life Orientation Test; Scheier, Carver, & Bridges, 1994). This literature has
previously been reviewed (Rasmussen, Scheier, & Greenhouse, 2009), and typically focuses on the effects
of optimism for individuals who have already been diagnosed with a particular illness or health condition,
for example, cancer or heart disease. Studies follow patients longitudinally to determine whether those with
higher optimism are less likely to face complications with their disease, show better disease prognosis, and
better overall health outcomes, with many studies showing positive outcomes (see review by Rasmussen et
al., 2009). There are limits to the benefits of optimism, however. For example, to the best of our knowledge,
no study has found optimism to aid in cancer remission (De Moor et al., 2006; Schofield et al., 2004;
Schulz, Bookwala, Knapp, Scheier, & Williamson, 1996). The cardiovascular literature is perhaps more
consistent, with many studies revealing faster recovery rates after surgery (e.g., fewer days in the hospital)
and better disease prognosis (Conway, Magai, Springer, & Jones, 2008; Matthews, Räikkönen, SuttonTyrrell,
& Kuller, 2004; Scheier et al., 1989). In addition to these chronic illnesses, other studies have
found benefits for chronic pain patients (Costello et al., 2002), as well as patients with diabetes and carotid
atherosclerosis (Fournier, de Ridder, & Bensing, 2002; Matthews et al., 2004).
Mechanisms that might lead to better health outcomes for those high in optimism overlap with some
of the previously discussed pathways (e.g., alterations in immune function, behaviors). However, there are
some differences. People high in optimism may be more confident that they can successfully engage in
healthy behaviors, which may be why past studies have found optimistic university students to be more
likely to engage in health promoting behaviors, recover more quickly from the flu, and actively attempt to
prevent the flu compared to those who were pessimistic (Hamid, 1990). Optimism may also partially
operate via the pathways influenced by positive emotion, and, thus, may not be entirely independent from
affect (Segerstrom, 2007). Optimism also differs from other positive constructs in an important way in that
it can be harmful when unrealistic. For example, a study of law students (a high stress sample) found that
immunity was either strengthened or compromised depending on the students’ current outlook on their law
school experience. When students were more optimistic about a period of law school where their studies
were going well, their immunity improved, while when these students were experiencing difficult periods
during their studies, their immunity would plummet (Segerstrom, 2007). Few studies of positive constructs
show harm, but it is important to consider how and when SWB levels may have a cost rather than a benefit
in future work. In general, replication is also a problem in the study of optimism and physical health, and
there is a need for more research on the same physical outcomes.
Hope
While colloquially hope is often conflated with optimism, in positive psychology research, hope is
defined by an emphasis on determination that is goal-oriented, characterized by planning and perceived
controllability (Snyder, Irving, & Anderson, 1991). Hope has rarely been connected to physical health, but
there are some relevant self-report studies. For example, studies have investigated the relationship between
hope and cancer with the idea that high hope might enable better coping with the stress of this threatening
disease. One large study of individuals with either gastrointestinal, breast, head and neck, or hematologic
malignancy cancer found that those with high hope were able to successfully cope with their disease as
indicated by self-reported data collected using the Herth Hope Scale and the Jalowiec Coping Scale
(Felder, 2004). This finding, while distinct from objective health outcomes, is important, as coping with a
disease can result in better quality of life (Manne et al., 1994; Osowiecki & Compas, 1998; Stanton et al.,
2000). Interestingly, several studies have also linked hope to faster rates of healing, for example, after
spinal surgery (Elliott, Witty, Herrick, & Hoffman, 1991) and after getting burned (Barnum, Snyder,
Rapoff, Mani, & Thompson, 1998). This is possibly due to better adherence to medical instruction and selfcare,
which is echoed in work showing the connection between hope and preventive health behaviors (e.g.,
doctor check-ups and medical screenings; Salovey, Rothman, Detweiler, & Steward, 2000). Together, the
literature on hope is exciting but very small. Outcomes need replication, and there should be a focus on
outcomes most likely to be influenced such as healthy behavior change (and diseases most likely influenced
by this change). Many studies in this area use convenience samples; thus, future work should include power
analyses and utilize targeted and meaningful participant samples.
Under-Researched Positive Constructs
There are a number of additional positive constructs that are under-researched in the domain of
physical health, including factors like courage, creativity, and passion. Researchers need to investigate the
relationship between these constructs and physical health more closely, as it may be the case that not all of
these constructs are beneficial for physical health. For example, obsessive passion may lead people to
503
engage in risky behaviors at a higher rate, hence leading to negative outcomes such as injury (Vallerand et
al., 2003). As we have emphasized in this chapter, it is important to research each positive psychological
construct separately in its relation to physical health, as not all constructs will have the same beneficial or
detrimental effects.
Pathways Connecting Subjective Well-Being with Health
Throughout this chapter, we have discussed outcomes that are more appropriately described as
pathways to health as opposed to health in their own right. These include factors like cardiovascular and
circulatory physiology (e.g., blood pressure, cholesterol), immune function (e.g., wound healing, antibody
levels), endocrine activity (e.g., cortisol), and other less studied physiological pathways. While many
positive factors are known to induce change in these variables experimentally (e.g., PA inductions alter
physiology; Dockray & Steptoe, 2010), any SWB measures might influence these physiological pathways
via alterations in health behaviors (e.g., sleep, exercise, diet). Furthermore, SWB, by definition, includes
social relationships, which can influence physiological function, health behaviors, and more. For example,
as described in the social control section, relationships serve an important role in encouraging medical care
and adherence.
What may also be a common mechanism for altering health in many SWB-health connections is the
indirect effect of SWB on preventing downstream negative effects of stress. As described in many sections
above, SWB components may have effects on stress perceptions, reactivity, or recovery. Social support has
long been implicated in reducing the negative effects of stress (Cohen & Wills, 1985), and, more recently,
PA has been posited to play a similar role (Fredrickson & Levenson, 1998; Pressman & Cohen, 2005).
While not all SWB components may play a role here, and certainly the research is not deep in many of
these areas, conceptually, many components could help with stress. For example, hope and the goal setting
that goes with it may prevent future stress from occurring. Perceptions of control, efficacy, determination,
and grit might enable reduced reactivity during a stressful period, as might feelings of mindfulness or social
support that change stress and coping appraisals. Finally, recovery from stress is aided by positive
emotions, and even a simple positive behavior like smiling has been shown to help in this context
(Fredrickson & Levenson, 1998; Kraft & Pressman, 2012). Other positive facets may help as well; for
example, self-affirmation or stable self-esteem might enable a person to get over the stress faster, as might
the ability to focus on a positive future with dispositional optimism. Unfortunately, at this point, studies
specifically testing associations between SWB components and the different components of stress are rare,
as are studies that contrast different SWB measures against each other to determine their relative and
possibly unique effects.
Work on possible pathways continues to progress and develop, especially with the advent of
cheaper assays and easier to assess samples (e.g., saliva), new and interesting biomarkers with plausible
SWB connections (e.g., telomeres), and growing interest in health relevance. Behavioral and physiological
pathways are also getting easier to sample with the advent of new technologies for mobile assessments such
as motion sensors, portable heart rate variability, and even facial expressions, which may also play a role
in health via their influence on physiology and social relationships. Together, there is a far way to go
before we have a thorough understanding of how, when, and why SWB can influence health, but with a
conscientious effort to probe this question and attention to new methods (see review by Diener, Pressman,
Hunter & Delgadillo-Chase, 2017), this literature will grow and improve our understanding of this area as
well as inform future intervention design.
Discussion
Research on the connections between SWB and physical health has drastically increased over the
past twenty years, demonstrating a surge of interest in this topic. Overwhelmingly, SWB is positively
connected with physical health, revealing an impressive diversity of wellness benefits related to positive
states and traits. While it is important to take an omnibus approach in some cases to document the breadth
of these findings (e.g., Boehm & Kubzansky, 2012), future work will need to search for specificity.
Different constructs might be related to health and physiology in unique ways and should therefore be
investigated separately to inform interventions and/or provide precision in our knowledge of this area. It is
also important for researchers to know the extent to which certain constructs overlap, such as PA with life
satisfaction or hardiness with determination and grit. It may be the case that more specific definitions or
advanced measurement tools are needed to capture the distinctness of different SWB constructs, given the
high degree of overlap between many of them. To this end, one direction for future research is to determine
whether overlapping constructs have separate effects on physical health. For example, the PA and social
support literatures are the largest literatures connecting specific SWB constructs to physical health. It is
likely, however, that these literatures are connected, since happy people tend to have more and better social
relationships, and relationships confer well-being in many ways. Furthermore, studies need to focus on
504
determining the unique versus common variance of all positive constructs as they predict physical health.
However, this requires large samples and longitudinal designs, two methodological strengths that do not
appear in much of the SWB and physical health literature. Investigating both the separation and overlap of
positive psychological constructs will help clarify the sometimes conflicting literature involving different
SWB constructs and physical health and inform targeted health intervention designs.
While making distinctions among SWB constructs, it is also important to separate state and trait
constructs. Some SWB constructs, such as state PA and mindfulness, are more state-like in that they can be
manipulated readily. For example, state PA can be induced in the lab through various methods like videos
and writing exercises. However, other SWB constructs such as self-esteem and optimism are more trait-like
and, thus, are less readily and meaningfully altered within a short experimental session. Researchers should
be cognizant of how long it takes to alter the specific construct in which they are interested and plan their
experiments or interventions accordingly. They should also consider that state and trait constructs influence
physical health differently. While state constructs may influence quick moving physiological processes
(e.g., cardiovascular reactivity and recovery), trait constructs may be more likely to influence far off health
outcomes such as morbidity and mortality. This is likely due to the increased opportunity over years for
lasting SWB factors to influence behaviors, relationships, and physiological systems that influence long
term health. There are many experimental studies that manipulate SWB constructs and examine physiology
or other health-relevant outcomes in the short term, but longitudinal studies are much more rare. There are a
number of reasons for this, such as difficulty in following up with participants years later, but this does not
change the fact that longitudinal studies are desperately needed to understand how and if changes in SWB
influence disease processes versus whether only stable traits underlie future health.
There are a number of additional important new directions for this area of work. One key
consideration is how negative constructs (e.g., NA, depression, stress) should be factored into analyses on
SWB and health. Early reviews on this topic (e.g., Pressman & Cohen, 2005) highlighted the importance of
adjusting for NA so that findings can be attributed to the presence of the positive rather than the absence of
the negative. However, how to appropriately include negative constructs in analyses is still an open
question in the field. Because of the overlap between PA and NA, many researchers opt to utilize other
assessments (e.g., depression) as a covariate in their analyses, but this may not have the same meaning.
Alternatively, is it appropriate to adjust for negative factors when part of the reason SWB constructs may
be helpful is due to their ability to ameliorate the negative effects of these measures (e.g., the stress
buffering hypothesis of PA)? Thus, how to analyze and treat negative psychosocial measures in these
studies is still an important and understudied area. Another methodological issue within this literature that
we have referred to within this chapter is the overreliance on self-report, sometimes with single item
assessments. Questions about SWB are often thrown haphazardly into existing medical studies, and the
most appropriate measures are sometimes not used. Thus, more studies should be specifically designed with
the main goal of determining the effects of SWB constructs on health so that there is a rationale behind the
measures that are chosen.
As this chapter has demonstrated, SWB and physical health are intimately linked. Many different
SWB constructs have been investigated in this context, but much more work within each construct is
necessary. When examined as a whole, many associations between SWB and physical health are found, but
a number of SWB constructs have only a handful of studies. Are there truly replicable effects of some of
these measures on health outcomes? Would these effects withstand more rigorous adjustments for factors
like NA or related positive constructs? To date, many of the research areas are in their infancy and, thus,
replication, expansion, and a more thoughtful approach to study analyses and designs are needed. The
ultimate goal of many researchers in this area is to better understand how to keep the populace healthy.
While this area is clearly promising, we encourage researchers to hold a magnifying glass to the broad
construct of SWB to unpack what types of well-being are most helpful for certain individuals, certain
illnesses, and certain constructs.
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RESOURCES
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Time, Money, and Subjective Well-Being
By Cassie Mogilner, Anderson School of Management at UCLA; Ashley Whillans, Harvard Business
School; Michael I. Norton, Harvard Business School
Citation
Mogilner, C., Whillans, A., & Norton, M. I. (2018). Time, money, and subjective well-being. In E.
Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
Time and money are scarce and precious resources: people experience stress about having insufficient time,
and worry about having insufficient money. This chapter reviews research showing that the ways in which
people spend their time and money, the tradeoffs that people make between having more time or having
more money, and the extent to which people focus on each resource can have a significant impact on
happiness. Considering subjective well-being (or “happiness”) as a combination of high positive affect, low
negative affect, and high feelings of life satisfaction, we explore when, how, and why time and money
impact peoples’ anticipated, momentary, and lasting happiness.
Keywords: Time, Money, Trade-offs, Happiness, Subjective well-being
Time and money are both precious resources that matter for happiness. Many people feel
temporally and financially constrained in their day-to-day lives (Goodin, Rice, Bittman, & Saunders, 2005;
Perlow, 1999; Rheault, 2011), wishing that they had more time and more money (Hershfield, Mogilner, &
Barnea, 2016). Having more money is associated with experiencing greater daily happiness up to
approximately $75,000 of household income per year, with additional gains in life satisfaction beyond that
amount (Kahneman & Deaton, 2010). Having more spare time is also associated with greater happiness and
life satisfaction, even after controlling for income, and even amongst people who say they like being busy
(Kasser & Sheldon, 2009).
Beyond the absolute amount of free time and money they have (Kahneman & Deaton, 2010;
Kasser & Ryan, 1993; Kasser & Sheldon, 2009), the extent to which people value each resource and the
ways people spend their discretionary time and money can significantly impact their well-being. For
example, recent findings show that even after controlling for the amount of time and money people have
available, those who value time over money report greater happiness (Hershfield et al., 2016; Whillans,
Weidman, & Dunn, 2016).
Still, there are many related open questions pertaining to the relationships between time, money,
and happiness—such as when and how valuing time over money impact happiness, as well as the meaning
that each resource assumes in people’s daily experiences and their lives more broadly. For instance,
research suggests that inexpensive, everyday pleasures, such as drinking a cold beer on a warm day, may
predict happiness beyond major life events, such as winning the lottery or starting a new job (Gilbert,
2006). It has been similarly argued that the key to unlocking long-lasting changes in happiness involves
spending time on activities that do not require a lot of money, but do provide small frequent boosts in
mood, such as exercise and religious practice (Mochon, Norton, & Ariely, 2008). More specifically, the
extent to which people prioritize time versus money within each day or in their broader life decisions might
have important yet differential effects for subjective well-being. Similarly, the happiness that follows from
decisions about how to spend each resource may depend on when happiness is measured.
Using a definition of subjective well-being (i.e., “happiness”) as a combination of high positive
affect (i.e., feeling happy in the moment), low negative affect (i.e., not feeling sad in the moment), and high
life satisfaction (i.e., evaluating one’s overall life as positive; Diener, 1994; Diener et al., 2017; Diener &
Lucas, 1999; Sheldon, 2013), this chapter will explore when, how, and why time and money impact
people’s momentary and lasting happiness.
Some Differences between Time and Money
Benjamin Franklin encouraged people to equate time and money in his adage, “Time is money.”
Yet, mounting research shows that people think about time and money in vastly different ways. Moreover,
the ways that people think about these resources can have significant implications for how people behave,
with consequences for their daily and overall happiness.
In particular, money has a readily exchangeable market and can be saved and borrowed across time
periods, which is not true of time. Whereas a loss of $100 today has the potential of being earned back
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tomorrow, a lost hour cannot be recuperated, and the 24 hours comprising each day renews every morning.
Because money is more fungible than time (Leclerc, Schmitt, & Dube, 1995; Soster, Monga, & Bearden,
2010; Zauberman & Lynch, 2005), people are more prone to carefully plan their temporal expenditures
than their financial ones (particularly for the short run; Lynch, Netemeyer, Spiller, & Zammit, 2009), and
are more averse to the risk of losing or wasting their time than their money (Leclerc et al., 1995). For
instance, people are less likely to select the chance of waiting 90 minutes over waiting 60 minutes for sure
than they are to select the chance of losing $15 over losing $10 for sure (Leclerc et al., 1995).
It is also harder to account for expenditures of time than money (Saini & Monga, 2008). Because
time is more ambiguous than money, people pay less attention to sunk costs involving time than money
(Soman, 2001; Soster et al., 2010), and people can more easily rationalize poor or excessive investments of
time than of money (Okada, 2005; Okada & Hoch, 2004). As a result, people prefer to invest time rather
than money to acquire hedonic goods (Okada, 2005). Similarly, people have greater difficulty predicting
future temporal obligations than monetary ones, which makes people more prone to overcommit their
future time than their future money (Zauberman & Lynch, 2005).
While these attributes differentiate time and money as resources, time and money also differ in
their perceived connection to people’s self-concepts. People view their temporal expenditures as more
reflective of who they are as a person than they do their monetary expenditures (Gino & Mogilner, 2014;
Mogilner & Aaker, 2009). Consequently, people view donations of time as more moral and self-expressive
than donations of money (Reed, Aquino, & Levy, 2007), and people often prefer to make donations of time
versus money, even when these donations are less effective (Olivola & Shafir, 2013). People also like
products more when they think about the time they have spent with that product versus the money they
have spent (Mogilner & Aaker, 2009).
Not only are people’s experiences more critical to their personal narrative than material goods
(Carter & Gilovich, 2012), but the ways people spend their time literally sum up to the days and the life
they live (Mogilner, Hershfield, & Aaker, 2017). So, even though people can buy goods to express aspects
of their identity (Belk, 1988; Richins & Dawson, 1992), expenditures of money do not constitute people’s
lives in the same way that expenditures of time do. People who prioritize the accumulation of material
goods (materialism) thus typically report lower subjective well-being (Belk, 1985; Kasser & Ryan, 1993,
1996; Richins, 1994; Richins & Dawson, 1992; Van Boven, 2005).
Focusing on Time versus Money
Partly because of these differences between time and money, the extent to which each resource is
salient can influence behaviors that have implications for subjective well-being. For example, the extent to
which people are focused on time versus money influences moral behavior. In the context of charitable
giving, those led to consider giving time (vs. money) give more time and more money, because they
imagine the happiness they would feel from engaging with the cause (Liu & Aaker, 2008). Being primed
with time (vs. money) also reduces people’s tendencies to cheat in games that award money or pride (Gino
& Mogilner, 2014). Investigations into the effects of focusing on money confirm its deleterious influence
on ethicality. Situational reminders of money (and wealth) lead to unethical behavior, particularly when the
decision to act unethically has personal benefits (Dubois, Rucker, & Galinsky, 2015; Gino & Pierce, 2009;
Kouchaki, Smith-Crowe, Brief, & Sousa, 2013; Miller, Kahle, & Hastings, 2015).
Though ethicality has consequences for subjective well-being (Borgonovi, 2008; Steger, Kashdan,
& Oishi, 2008), focusing on time versus money also impacts subjective well-being by motivating behaviors
that are directly linked to happiness. Namely, when time (vs. money) is made salient, people become
motivated to socialize more and to work less (Mogilner, 2010)—activities that are often tied to immediate
happiness and unhappiness, respectively (Kahneman, Krueger, Schkade, Schwarz, & Stone, 2004).
Furthermore, people who are chronically focused on time rather than money (measured by their likelihood
to choose time over money) report feeling happier and more satisfied with life (Hershfield et al., 2016;
Whillans et al., 2016). Time-focused individuals exhibit greater social inclinations, preferring to spend their
time and money with or on others rather than on themselves (Hershfield et al., 2016; Whillans & Dunn,
2017).
The vast literature on the consequences of money salience similarly reveals anti-social, yet
productive, effects of focusing on money. Though not every finding involving money primes has been
replicated (Caruso, Shapira, & Landy, 2017; Caruso, Vohs, Baxter, & Waytz, 2013; Rohrer, Pashler, &
Harris, 2015), a review of over 150 studies supports two robust categories of effects (Vohs, 2015):
compared to neutral primes, reminders of money make people less interpersonally attuned they become
unhelpful, stingy, and disinterested in social interaction (Gasiorowska, Zaleskiewicz, & Wygrab, 2012;
Vohs, Mead, & Goode, 2006, 2008). On the other hand, reminders of money do motivate people to work—
they exert more effort on challenging tasks, work longer, demonstrate better performance, and feel more
517
efficacious (Vohs et al., 2006, 2008).
When people are led to equate time and money by putting a price on their time (by calculating their
hourly earnings or receiving hourly vs. salary pay), their behavior changes. They become less willing to
spend their time on uncompensated activities, such as volunteering and engaging in pro-environmental
behavior (DeVoe & Pfeffer, 2007, 2011; Whillans & Dunn, 2015), they experience greater feelings of
psychological and physiological stress (Pfeffer & Carney, 2017), and there is some debated evidence to
suggest they become more impatient and less likely to slow down and enjoy leisure activities, such as
listening to music (DeVoe & House, 2012; cf. Connors, Khamitov, Moroz, Campbell, & Henderson, 2016).
The vast money priming literature allows the meaning of money to emerge through the
conglomeration of findings. The sparser literature on priming time leaves the various meanings of time yet
to be fully explored or understood. Future research is needed to identify when and why reminders of time
influence behavior and emotional well-being. What features of time reminders lead people to think about
their daily schedule (which might be associated with the stress of immediate time pressures) versus their
time on Earth (which might motivate more meaningful pursuits; Mogilner et al., 2017)? Thinking about the
hours or days that remain before a task is due would likely have different emotional consequences than
thinking about the years remaining in one’s life. Also, time might mean different things to different people
—perhaps varying by culture, geography, or employment. More than money, time is a rich construct that
would benefit from further investigation and understanding.
When People Focus on Time versus Money
While the priming findings highlight how people’s focus on time or money is subject to situational
influence, the extent to which people are focused on time or money also varies by individual (Hershfield et
al., 2016; Whillans et al., 2016) and more stable circumstances—such as how much of the resource people
have. Having less of a resource, whether it be time or money, makes people focus on it more (Shah,
Mullainathan, & Shafir, 2012; Shah, Shafir, & Mullainathan, 2015; Spiller, 2011). Consistent with this
theory of scarcity, having less actual or perceived time (or money) increases people’s likelihood to choose
that resource over the other (Hershfield et al., 2016; Whillans et al., 2016). One study found low income
Americans to exhibit similar behavioral intentions as those primed with money, which suggests that money
is already highly salient among people who are financially constrained (Mogilner, 2010).
However, in the case of money, abundance also seems to increase its salience. Not only is money
more valued (showing a stronger relation to subjective well-being) in richer nations (Tay, Morrison, &
Diener, 2014), but very wealthy individuals exhibit similar behaviors as those exposed to reminders of
money: savoring simple pleasures less (Quoidbach, Dunn, Petrides, & Mikolajczak, 2010), deriving less
meaning from taking care of their children (Kushlev, Dunn, & Ashton-James, 2012), and being less
altruistic (Miller et al., 2015).
Though both scarcity and abundance increase people’s focus on money, only scarcity draws
people’s attention to time and its ultimate value. That said, the psychological and behavioral consequences
of time scarcity depend on whether time is construed more concretely (e.g., in terms of day-to-day
scheduling) or abstractly (e.g., in terms of one’s time to be alive; Trope & Liberman, 2010).
The feeling of being pressed for time in people’s day-to-day lives (Goodin et al., 2005; Robinson &
Godbey, 2010) has been described as a “time famine” (Perlow, 1999). It plagues people of both high and
low income (Hamermesh & Lee, 2007), and is particularly acute among working parents (Gimenez-Nadal
& Sevilla-Sanz, 2011; Goodin et al., 2005; Strazdins et al., 2011; Sullivan & Gershuny, 2001). Not only
does this form of time scarcity produce feelings of stress (Carroll, 2008; Roxburgh, 2004; Strazdins, Welsh,
Korda, Broom, & Paolucci, 2016), it also elicits behaviors that undermine subjective well-being. People
who feel time-constrained become less helpful, less active, and less physically healthy (Banwell, Hinde,
Dixon, & Sibthorpe, 2005; Darley & Batson, 1973; Jabs et al., 2007; Mogilner, Chance, & Norton, 2012;
Strazdins et al., 2011).
In contrast, awareness that one’s overall time in life is limited improves subjective well-being by
encouraging people to find greater enjoyment in life’s ordinary pleasures and close relationships
(Bhattacharjee & Mogilner, 2014; Carstensen, Isaacowitz, & Charles, 1999; Cozzolino, Sheldon,
Schachtman, & Meyers, 2009; Cozzolino, Staples, Meyers, & Samboceti, 2004; Kurtz, 2008; Mogilner,
Aaker, & Kamvar, 2012; Mogilner, Kamvar, & Aaker, 2011). For instance, when people perceive their
future time as more limited (which tends to happen with age; Carstensen et al., 1999), they derive greater
happiness from ordinary experiences, such as eating a piece of chocolate, basking in a sunny morning, or
receiving a text from a friend (Bhattacharjee & Mogilner, 2014). Additionally, the salience of limited time
left in life leads people to feel greater happiness from feeling calm than from feeling excited (Mogilner et
al., 2011), to pursue emotionally relevant goals (Fung & Carstensen, 2006), to behave more generously
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(Cozzolino et al., 2004), and to prioritize close interpersonal connections (Carstensen et al., 1999). It is in
realizing that one’s time in life is limited that people become more deliberate in how they spend their time
and extract greater happiness from those activities.
Happier Ways to Spend Time
Though happiness is partly influenced by inherited temperament (Lykken & Tellegen, 1996; Nes &
Røysamb, 2015) and circumstances (Fujita & Diener, 2005; Lucas, 2007), the way people choose to spend
their time within and across days is also a substantial determinant of happiness (Lyubomirsky, Sheldon, &
Schkade, 2005).
To promote daily happiness, people should consider spending more time engaging in activities that
elicit positive vs. negative mood (e.g., Krueger, Kahneman, Schkade, Schwarz, & Stone, 2009). To identify
what activities promote positive (and negative) mood, researchers have conducted studies using the Day
Reconstruction Methodology (DRM). In DRM studies, respondents are asked to reconstruct the activities
filling their last 24 hours, episode by episode. Respondents are then asked to report their mood during each
episode. Through these studies, researchers have found initial evidence that, on average, people feel more
positive emotion when they are engaged in leisure activities, such as exercising and socializing, than when
they are engaged in commuting, work, and housework (e.g., Kahneman, Krueger, Schkade, Schwarz &
Stone, 2004, 2006). Yet, it is worth noting that in one of the seminal DRM studies on this topic (Kahneman
et al., 2006), some respondents reported feeling happier at work (vs. leisure or other activities), suggesting
there are individual differences in which time-use activities promote happiness.
Using more sophisticated data collection methods, such as experience sampling and mobile
sensing, researchers have further expanded on these DRM findings by exploring what kind of leisure
activities people should engage in to reap the greatest happiness. In experience sampling studies,
respondents are asked to report how they feel “right now” during randomly selected episodes throughout
the day (Csikszentmihalyi & Hunter, 2003; Csikszentmihalyi & Larson, 2014; Hektner, Schmidt, &
Csikszentmihalyi, 2007; Napa Scollon, Prieto, & Diener, 2009). In mobile sensing studies, cell phone
technology stealthily records participants’ activities. Meanwhile, participants respond to messages
throughout the day indicating their current mood (Berke, Choudhury, Ali, & Rabbi, 2011; Killingsworth &
Gilbert, 2010; Lane et al., 2010; Lathia, Sandstrom, Mascolo, & Rentfrow, 2017; Ma, Xu, Bai, Sun, &
Zhu, 2012; Maisonneuve, Stevens, Niessen, & Steels, 2009; Rabbi, Ali, Choudhury, & Berke, 2011).
These state-of-the-art methodologies suggest that more active forms of leisure, such as exercising
and volunteering, are linked to greater daily positive mood compared to more passive forms of leisure, such
as watching TV, relaxing, and napping (Lathia et al., 2017; see also: Smeets, Whillans, Bekkers, & Norton,
2017; Richards et al., 2015; Wang et al., 2012). For example, new research using a mobile app that
measures activity level through smart phones shows that people feel happier when they have been moving
in the past 25 minutes than when they have been sitting or lying down, regardless of the activity they were
engaging in (Lathia et al., 2017). Most participants’ movement involved gentle walking, light jogging, and
casual cycling, suggesting that even minimal physical exertion can enhance daily mood.
Cultivate social connection. Another time-use activity that can promote happiness is spending time
with others: Time spent connecting with others tends to be the happiest part of most people’s day
(Kahneman et al., 2004; Mogilner, 2010), and experiences that are shared produce greater happiness than
those experienced alone (Caprariello & Reis, 2013). High quality social relationships are essential for
mental and physical health (Diener & Seligman, 2002). Meta-analyses suggest that the health benefits of
social connection are comparable to those of exercising regularly and not smoking (Holt-Lunstad, Smith,
Baker, Harris, & Stephenson, 2015; Holt-Lunstad, Smith, & Layton, 2010). Even fleeting social
interactions, such as chatting with one’s Starbucks barista or a fellow commuter on a bus, can make people
feel connected and therefore bolster happiness (Epley & Schroeder, 2014; Sandstrom & Dunn, 2013).
Help others. Spending time helping others is another activity that can enhance mood and physical
health (Dunn, Aknin, & Norton, 2008; Gimenez-Nadal & Molina, 2015; Liu & Aaker, 2008; Weinstein &
Ryan, 2010; Whillans et al., 2016, cf. Whillans, Dunn, Smeets, Bekkers & Norton, 2017). One way that
helping others can promote subjective well-being is by reducing the stress associated with feeling timeconstrained.
Study participants who spent time helping someone else (vs. who spent time on themselves)
reported feeling like they had more time, in part because it made them realize all they could accomplish
with their time (Mogilner et al., 2012).
Be active. As already discussed, engaging in active leisure activities seems to reliably promote
happiness (Lathia et al., 2017). Consistent with these findings, people also report greater happiness when
they are busy, especially when they can justify their busyness (Hsee, Yang, & Wang, 2010). In North
America, busyness is now a status symbol (Bellezza, Paharia, & Keinan, 2016). Idleness, on the other hand,
519
is extremely upsetting. People would rather shock themselves than be left alone with their own thoughts
(Wilson et al., 2014). These findings might help to explain why people who are unemployed (despite their
abundance of free-time) report lower levels of daily happiness than those who are employed (Young &
Lim, 2014). Notably however, once busyness transforms into feelings of time stress, people experience
lower positive mood and life satisfaction—and this effect holds even among people with a stated
preference to be busy (Kasser & Sheldon, 2009).
Increase variety. Across the activities that fill people’s lives, greater variety increases excitement
and engagement (Etkin & Mogilner, 2016), which helps to offset the threat of hedonic adaptation
(Lyubomirsky et al., 2005). Notably, however, though filling one’s day or week with highly varied
activities increases happiness, fitting highly varied activities into shorter time periods (e.g., an hour)
reduces happiness by making people feel like they have accomplished less (Etkin & Mogilner, 2016).
These findings provide initial evidence that multitasking can undermine feelings of productivity and
happiness.
Variety across emotional experiences can also have benefits for overall subjective well-being.
“Emodiversity”—the variety and relative abundance of the emotions that people typically experience—
predicts decreased depression and doctor’s visits, over and above mean levels of positive and negative
emotion (Quoidbach et al., 2014). Other research has shown that experiencing moderate variability in one’s
emotional experiences (vs. too much or too little variability) positively predicts happiness and is associated
with improved physical health (e.g., Human et al., 2015; Kashdan & Rottenberg, 2010). Too much
variability in positive emotion predicts lower life satisfaction and greater depression (Gruber, Kogan,
Quoidbach, & Mauss, 2013).
Relatedly, current research suggests that spending too much time engaging in social activity can
undermine well-being (Kushlev, Diener, Heintzelman & Oishi, 2017). In light of this possibility that overinvesting
in “positive” time-use pursuits can come at a cost to well-being, more research is needed to
understand individual differences and social/cultural factors that determine people’s happiness from
working versus leisure, as well as the optimal amount of time that people should spend at work versus
engaging in social and leisure activities.
Savoring Time Spent
In addition to what people spend their time doing, the extent to which people are mentally engaged
in those activities can influence resulting happiness (Nakamura & Csikszentmihalyi, 2009). This speaks to
the importance of savoring daily experiences. One strategy for savoring daily experiences is turning them
into rituals. For example, study participants rated a chocolate as more flavorful and worth savoring when
they had completed a ritual prior to consumption (e.g., by unwrapping the chocolate in a specific way;
Vohs, Wang, Gino, & Norton, 2013). Also, engaging in the creation of products can make the experience of
those products more satisfying—an observation called “the IKEA effect” (Norton, Mochon, & Ariely,
2012).
Another strategy to help people savor experiences includes taking photos of the experience. Taking
photos enhances enjoyment of positive experiences by increasing people’s engagement with the experience
(Diehl, Zauberman, & Barasch, 2016). Notably, however, taking photos with the intent of posting them on
social media pulls people out of the experience and reduces enjoyment of the experience (Barasch,
Zauberman, & Diehl, 2017). Photos taken during such events as concerts and nights out with friends
facilitate rediscovery of previously experienced events, which enhances positive mood (Zhang, Kim,
Brooks, Gino, & Norton, 2014).
When people are aware their time is running out, they are more likely to savor whatever time they
spend. For instance, people imagining it is their last month in their current city derive greater enjoyment
from their day-to-day experiences (Layous, Kurtz, Chancellor, & Lyubomirsky, 2017); college students
focused on the imminence of graduation engage more in their typical college-related activities and
experience greater happiness from them (Kurtz, 2008); and people who temporarily give up something
pleasurable derive greater pleasure from it the next time it is consumed (Quoidbach & Dunn, 2013). While
extraordinary experiences produce high levels of happiness regardless of the amount of time left in life,
ordinary experiences produce high levels of happiness among older people and younger people who
perceive their future as limited (Bhattacharjee & Mogilner, 2014). Realizing the preciousness of time
encourages people to extract greater happiness from even the most mundane activities.
Extracting Meaning from Time
Thus far, we have reviewed findings identifying ways to spend time that promote positive mood
and immediate feelings of happiness. Yet, a more lasting sense of purpose and meaning in life is also an
important factor in subjective well-being (Catapano, Quoidbach, Mogilner, & Aaker, 2017; Diener et al.,
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2010; Ryan & Deci, 2001). Therefore, in addition to understanding how people should spend their time to
maximize their daily mood, it is also important to clarify what activities help to maximize a sense of
meaning.
Time-use activities that are rated as low in positive affect (e.g., working or spending time with
young children; Kahneman et al., 2004) can be rated high in meaning (Nelson, Kushlev, English, Dunn,
Lyubomirsky, 2013; White & Dolan, 2009). These “objectively unpleasant” daily activities can indirectly
contribute to greater well-being by enhancing meaning in life (White & Dolan, 2009). People presumably
spend their time to satisfy various components of well-being. For instance, they may watch TV seeking
pleasure, but they may volunteer at a food bank to feel a greater sense of meaning. To advise people how
they should spend their time to maximize subjective well-being, it is therefore important to understand why
people are engaging in a given task, in addition to what people are doing and how they feel while doing
it.
Collectively, these findings highlight important areas for future research. More research is needed
to understand how best to spend time to maximize daily happiness, as well as life satisfaction. Since
moment-to-moment happiness does not simply sum up to one’s memory of the experience or one’s overall
evaluation of the experience (e.g., Diener, Wirtz, & Oishi, 2001; Fredrickson & Kahneman, 1993; Wirtz,
Kruger, Scollon, & Diener, 2003), an important question then becomes which source of well-being should
be optimized to translate into greater well-being each day and over the course of people’s lives (Mogilner &
Norton, 2017). Relatedly, more research is needed to understand when it is best to prioritize one form of
well-being over another. For example, research on psychological flexibility suggests that changing one’s
goals to meet the needs of the current situation will likely produce the best results (Kashdan & Rottenberg,
2010).
Happier Ways to Spend Money
One way to change how people spend their time is to change how they spend their money. The
products and services that people purchase (or not) are essentially purchases of time: buying a television is
buying time watching TV, paying for housecleaning is buying several hours of free time, and saving for
retirement is buying improved future time. Therefore, research identifying what uses of money “pay off” in
the most happiness focuses on ways to spend money—such that people spend their time in happier ways
(Dunn & Norton, 2013). More specifically, mounting research suggests that the material purchases people
make for themselves—from cars to houses to gadgets—often fail to pay off in increased happiness (Dunn
& Norton, 2013; Van Boven & Gilovich, 2003). Yet, spending money on others (instead of on the self) and
buying experiences (the opposite of tangible possessions) can promote happiness. Finally, a third area of
research explores the benefits of using money to directly buy more free time.
One caveat to note is that people who lack discretionary money and are struggling to make ends
meet will not often confront decisions for whether and how to spend their money to maximize happiness.
Still, many people do have some discretionary income, which makes these insights relevant for a
significant portion of the population. Indeed, a large proportion of people living in developed countries
have non-trivial discretionary income (OECD Economic Survey of Canada and the United States, 2016),
with the average North American household taking home approximately $30,000 of discretionary income
each year (Statistics Canada, 2016; US Census Bureau, 2015).
Spend on others. Dunn, Aknin, and Norton (2008) conducted a simple experiment designed to test
whether spending on the self or spending on others leads to greater happiness. On a university campus in
Canada, people were given either $5 or $20 and instructed to either spend it on themselves or on others by
the end of the day. When contacted that night, those assigned to spend on others were happier than those
assigned to spend on themselves, regardless of the amount. The happiness from prosocial spending is not
limited to wealthier countries: Large-scale survey data assessing the link between charitable giving and
well-being in 136 countries reveals a directionally positive link in 120 of the 136 countries, and a
significant correlation in a majority of the sampled countries (Aknin et al., 2013).
In general, prosocial behavior is most apt to positively influence personal well-being when the
behavior satisfies at least one of three basic needs: relatedness, competence, and autonomy (Weinstein &
Ryan, 2010; see also Dunn, Aknin, & Norton, 2014). Perhaps not surprisingly, then, prosocial spending
produces more happiness when the giving is conducted face-to-face (e.g., when people buy a friend a
coffee at Starbucks and accompany them there; Aknin, Dunn, Sandstrom, & Norton, 2013) and when
people spend on strong ties (such as family) rather than weak ties (such as acquaintances; Aknin,
Sandstrom, Dunn, & Norton, 2011). In addition, perceiving the prosocial impact—such that people feel
their giving is making a difference in the lives of others—heightens the happiness gained from prosocial
spending in both their personal lives (Aknin, Dunn, Whillans, Grant, & Norton, 2013) and their
professional lives (Grant & Sonnentag, 2010).
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Buy experiences. An impressive body of research suggests that when spending on the self, it is
better to buy experiences than material possessions to maximize subjective well-being (see Gilovich &
Kumar, 2015 for a review). In a seminal paper, Van Boven and Gilovich (2003) defined an experiential
purchase as “an event or series of events that one lives through” and a material purchase as “a tangible
object that is kept in one’s possession.” In the associated series of studies, people who recalled experiential
purchases were happier and felt that their money was better spent than those who recalled material
purchases.
There are several reasons for the greater happiness from experiential purchases than material ones.
For one, people are slower to hedonically adapt to experiences than possessions. In one study, the
happiness of participants who purchased experiences decreased more slowly over the ensuing days and
weeks than the happiness of people who had purchased material goods (Nicolao, Irwin, & Goodman,
2009). In another study, happiness with experiential purchases even increased over time (Carter &
Gilovich, 2010). Another reason for the greater happiness from experiential purchases is that experiences
tend to be more emotionally acute and socially connecting than material goods (Chan & Mogilner, 2017).
Recipients of experiential gifts therefore feel more connected to their gift-giver than do recipients of
material gifts (Chan & Mogilner, 2017). Moreover, whereas material purchases are more likely to be
consumed alone, experiential purchases are more likely to be enjoyed with others (Caprariello & Reis,
2013), and the associated feelings of relatedness are at least partly responsible for the ensuing happiness
(Howell & Hill, 2009). Furthermore, experiential purchases are more tightly tied to people’s sense of
identity, creating happy memories that give people a sense of “who they are” (Carter & Gilovich, 2012).
This is yet another reason why people go to great lengths to collect (Keinan & Kivetz, 2011) and protect
(Zauberman, Ratner, & Kim, 2009) memories of experiences, and why people find rediscovering those
memories so pleasurable (Zhang et al., 2014).
It is worth pointing out that experiential purchases do not always enhance happiness more than
material purchases. For example, while experiential purchases produce more intense feelings of happiness
(Chan & Mogilner, 2017), material purchases produce more frequent feelings of happiness (Weidman &
Dunn, 2016). More research is needed to identify exactly when material versus experiential purchases are
more effective at increasing subjective well-being—particularly when looking to maximize happiness in the
moment, rather than anticipated or retrospective happiness. More research is also needed to understand
whether some material purchases—such as a new car or a home with a view—can promote lasting
happiness by helping facilitate positive daily experiences.
Buy time. An emerging body of research has explored the benefits of using money to buy more
free time. Whillans et al. (2017) document three primary findings. First, people are surprisingly unlikely to
report using money to buy time (e.g., paying to delegate common household chores like cleaning, shopping,
and cooking), which suggests that buying time is not a common use of money. Second, large-scale surveys
of countries ranging from the United States to Denmark to the Netherlands involving both representative
samples as well as samples of millionaires demonstrate that buying time is correlated with well-being.
Third, an experiment in which people were given $40 and asked to make a time-saving purchase versus
buy a material good showed that buying time led to greater happiness, and these results were driven by the
buffering role that buying time played in alleviating time stress. Across studies, the least wealthy
participants benefitted the most from spending money on time-saving purchases. These results suggest that
people who are pressed for money might also be more likely to be pressed for time, potentially because
they must commute farther to work or are single parents. More research is needed to further understand
when and why buying time produces greater levels of well-being.
This review of findings identifies an exploration into the correct balance in spending across the
multitude of domains as one clear avenue for future research. Taking just the four spending categories
reviewed here, research suggests that while material purchases typically do not pay off in happiness,
prosocial spending, experiential purchases, and buying time do. Yet, people clearly must make some
material purchases (e.g., they need clothing). So the question remains: What percentage of spending should
be allocated across these categories? Second, the research reviewed offers several mediators of the moneyhappiness
link, but which is most important? And even if we assume, for instance, that relatedness is most
critical, what spending category best increases feelings of relatedness? Is it spending directly on an
experience with someone else, or giving to charity, or even buying time to free up more time to spend with
family and friends? More research is needed to compare the relative benefits of different methods for using
money to buy happiness. More research is also needed to understand who stands to benefit most from
spending money in each category. Recent research suggests that personality can moderate the benefits of
spending on others and on material purchases (Matz, Gladstone & Stillwell, 2016). Thus, future research
should seek to understand how both personality factors and available income interacts to predict the
benefits of various spending choices.
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Conclusion
This chapter reviews how thinking about and spending time and money shapes subjective wellbeing.
Notably, many of the effects depend on the temporal context of subjective well-being—is happiness
being optimized in the moment or when remembering the past or anticipating the future? Going forward,
researchers should more precisely delineate the role of time and money in day-to-day feelings of happiness,
forward- and backward-looking feelings of happiness, as well as assessments of living a happy life overall.
Researchers should also increase the representativeness and generalizability of the time-use and happiness
findings reported in this chapter by conducting research among non-Western samples and respondents from
both lower and higher income brackets (Henrich, Heine & Norenzeyan, 2010).
Also, though we focused on individuals’ happiness as the unit of analysis, future research should
consider the implications of time and money for the happiness of relationship pairs, families, organizations,
and societies. For example, how do various means of managing, sharing, and giving time and money
impact relationship satisfaction? Findings in the relationship literature on shared novel experiences (Aron,
Norman, Aron, McKenna & Heyman, 2000), expressions of gratitude (Algoe, Gable, & Maisel, 2010), and
rituals (Sezer, Norton, Gino, & Vohs, 2016) highlight this as a ripe area for research. From an
organizational perspective, companies might similarly consider how compensating employees with time
(e.g., vacations, sabbaticals, flex hours) versus money (e.g., salary, 401k options) translates into job
satisfaction.
Time and money are arguably life’s most precious resources. Continuing to understand how people
spend, think about, and value their time and money will help to answer the broader and more fundamental
question of how to maximize individual and societal well-being.
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Income and Subjective Well-Being: Review, Synthesis, and
Future Research
By Louis Tay, Purdue University, Michael Zyphur, University of Melbourne, & Cassondra L. Batz, Purdue
University
Citation
Tay, L., Zyphur, M., & Batz, C. L. (2018). Income and subjective well-being: Review, synthesis, and
future research. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT:
DEF Publishers. DOI:nobascholar.com
Abstract
To advance research on income and subjective well-being (SWB), we review and synthesize the research
on this topic. There is robust evidence showing a substantial association between income and SWB.
However, addressing the question of whether income leads to happiness requires an explication of the
underlying processes for how income may enhance or undermine happiness. A symbolic view of income
(e.g., signaling status) proposes that income has little relation to SWB. On the other hand, a functional view
of income (e.g., resource-buffer and a means for need fulfillment) proposes a stronger relation to SWB. In
seeking to integrate this literature, we present a multilevel model of symbolic and functional views of
income and SWB accounting for: (a) different levels of analysis; (b) income expenditure/distribution; and
(c) the income generation context. The purpose is to provide an overarching conceptual model that captures
the key factors influencing income and happiness that requires greater clarity and precision in order to
advance future scientific endeavors.
Keywords: Income, Well-Being, Happiness, Money
Although both societies and individuals strive toward material progress, with income being one of
the key indicators, there is considerable debate on whether income leads to, or is substantially associated
with, happiness. This has arisen in part due to different deeply held philosophical, religious, and ethical
viewpoints. Value judgments on materialism and money notwithstanding, burgeoning empirical research
on this issue from the fields of economics and psychology appear poised to resolve this debate. Yet
surprisingly, scientists are similarly divided, with some holding up evidence that little relation holds while
others point to a strong association.
In our review of the literature, there is robust evidence showing a substantial association between
income and subjective well-being (SWB). However, addressing the question of whether income leads to
happiness requires an explication of the underlying processes for how income may enhance or undermine
happiness. To this end, we review contrasting psychological and economic mechanisms that have been
proposed to explain how income may (or may not) enhance happiness and clarify key moderators that need
to be accounted for when empirically assessing this issue. By doing so, we shed greater light into the
conditions for when income may or may not exert effects on SWB.
In seeking to integrate this research, we present a multilevel model of income and SWB accounting
for: (a) different levels of analysis; (b) income expenditure/distribution; and (c) the income generation
context. The purpose is to provide an overarching conceptual model that captures the key factors
influencing income and happiness which requires greater clarity and precision in order to advance future
scientific endeavors.
Origins of Debate and Beyond: Key Factors for Consideration
Seminal work by Easterlin (1974) found that although in the cross-section income is associated with
happiness within nations, it was not associated between nations. Further, rising national income was not
associated with rising levels of national happiness. To explain these findings, it was posited that an
individual’s happiness level is contingent on the standard based on one’s society rather than an absolute
standard across the world. Therefore, as evidenced, relative income within a nation has greater bearing on
happiness than between nation income or increases in national income over time.
The relative happiness hypothesis was challenged in a re-examination of the between-nation
Easterlin data (Veenhoven, 1991). It was demonstrated that the between-nation correlation for income and
SWB in the two data sets were not trivial with magnitudes of .51 (N = 14) and .59 ( N = 9), respectively;
when a larger number of countries were considered, the correlation was .84 (Veenhoven, 1991). It was
argued that national happiness was highly correlated with national income and unlikely to be based solely
on relative standing within the nation. Instead, it is more likely that happiness is based on the fulfillment of
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basic and psychological needs afforded by income, which is an absolute standard, rather than one’s
relative income standing within a nation.
This debate between the two viewpoints – relative versus absolute standards – has continued to the
present day. However, the scope of the debate has narrowed as accumulated evidence shows that there is a
substantial correlation at the nation level between income and happiness at above .80 (Deaton, 2008; Sacks,
Stevenson, & Wolfers, 2012), with little to no evidence of satiation (Stevenson & Wolfers, 2013). Further,
time-series and panel analyses of a large number of nations have shown a positive relationship between
income and happiness over time (Diener, Tay, & Oishi, 2013; Sacks et al., 2012; Veenhoven & Vergunst,
2014). Currently, it is acknowledged that while in the short run income and happiness may be associated, it
is argued that this association does not hold in the long run (10 years or more) as shown in 34 nations
(Easterlin, McVey, Switek, Sawangfa, & Zweig, 2010). Different pieces of evidence point to valid
arguments from both viewpoints: while there is strong evidence that absolute income contributes to
happiness; it suggests that relative income plays a role in happiness over time.
Another source contributing to the debate has stemmed from studies on individual-level income and
happiness. Initial work on a small sample of lottery winners showed no long-term increases in happiness
and this has been thought to show that individual income does not enhance happiness (Brickman, Coates, &
Janoff-Bulman, 1978). Furthermore, meta-analytic evidence revealed a small effect size of .18 (k = 38)
between household income and SWB (Howell & Howell, 2008). Despite these initial findings suggesting
little to no relation between income and SWB, more recent work proposes otherwise. A longitudinal study
with a random sample of about 33,000 individuals, has shown that after two years, lottery winners
exhibited greater SWB as compared to non-lottery winners (Gardner & Oswald, 2007). Furthermore, it has
been proposed that the correlational effect size between income and SWB can be misleading as it masks
actual mean level differences between the rich and poor. Correlations as small as r = .09 correspond to a
mean difference of d = .40 between the richest and poorest in representative nation samples; and a low
correlation of r = .32 corresponds to a mean level difference of d = 1.23 between the richest and poorest
(Lucas & Schimmack, 2009).
Apart from debates on the predictor side of the equation, that is, whether income exerts changes to
SWB, debates have also occurred on the outcome side of the equation; that is, whether SWB is changeable
in the long-run. A key landmark heritability study on SWB demonstrated that test-retest correlations of
SWB over 5 to 10 years has a heritability estimate of 80%, thereby supporting the claim that SWB is fairly
immutable (Lykken & Tellegen, 1996). By extension, income effects would have little influence on SWB.
Nevertheless, the heritability estimate of 80% is based on the stable variance over time which is around
50% of the total variance. Therefore, around 60% of the total variance in SWB has changed over time and
the conclusion of immutability is too strong (Tay & Kuykendall, 2013). Overall, there is evidence that
while SWB has some degree of stability, it is also malleable and can systematically change over time
(Diener, Lucas, & Scollon, 2006; Tay & Kuykendall, 2013).
In general, the evidence on balance is supportive of a robust relation between income and SWB
(Frank, 2012; Veenhoven, 1991; Veenhoven & Hagerty, 2006). Yet, on many accounts, income does not
seem to be as strongly related to happiness over time as we would intuitively suppose (Aknin, Norton, &
Dunn, 2009). We propose that this is the consequence of concomitant contrasting effects. The relative
viewpoint exemplifies the negligible effect of income on happiness (Clark, Frijters, & Shields, 2008;
Easterlin, 1974; McBride, 2001) whereas the absolute viewpoint exemplifies the strong positive effect of
income (Hagerty & Veenhoven, 2003; Sacks et al., 2012; Veenhoven, 1991; Veenhoven & Vergunst,
2014). Pointing to coexistent and concomitant effects, research has shown that adaptation occurs
(attenuated income-SWB relation) in the long-run although income increases with happiness (Hagerty &
Veenhoven, 2003). This example suggests that contrasting effects can both hold, but there may be instances
or situations when one of these contrasting effects may be stronger or weaker (e.g., short-term versus long-
term).
Based on the debate and findings, we highlight several aspects that need to be recognized in
organizing this integrative conceptual model. It is important to consider the contrasting posited mechanisms
for how income may or may not lead to SWB. Critically, because this debate has emerged from primarily
two different levels of analysis (viz. national-level and individual-level), the processes of how income may
exert effects on SWB would require specificity at different levels. For instance, the issue of income
distribution exerting effects on SWB pertains to communities and nations rather than individuals (Oishi &
Kesebir, 2015). Moreover, it will also be critical to understand the moderating effects of national-level
income on the relation between individual-level income and SWB (Tay, Morrison, & Diener, 2014).
Beyond this debate, there is growing recognition that the way income is spent also contributes to
whether individuals achieve SWB (Dunn, Aknin, & Norton, 2008). This issue of how income is spent and
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redistributed in society is also relevant at the national level (Diener et al., 2013). Finally, another key factor
that has not been thoroughly considered is the context in which income is earned. It has been proposed that
the cost of earning income is that it has to be earned and the work context may serve as a source of
dissatisfaction (Kaun, 2005; Pouwels, Siegers, & Vlasblom, 2008). However, this issue appears to be more
complex as organizational psychologists have shown that work can also be a major source of satisfaction
depending on the job attributes (Hackman, Pearce, & Wolfe, 1978). By extension, at the national level, the
type of labor market needs to be considered as well as a key confounding variable in the income-SWB
model.
Based on aforementioned issues, we propose that key factors for inclusion in the conceptual model
include: (a) different levels of analysis; (b) income expenditure; and (c) the income generation context. A
multilevel framework of the key mechanisms and moderators is presented in Figure 1. We will expound on
aspects of these framework in the following sections. Specifically, we discuss the different contrasting
mechanisms, income expenditure, and income generation context at both the individual and national level.
Figure 1. Integrative multilevel framework linking income and subjective well-being
Mechanisms Underlying Positive and Nonpositive Effects of Income on SWB
In this section, we provide an organizing framework for understanding the differences in the relative
versus absolute viewpoints of income and SWB. Instead of using the terms relative and absolute, which
emphasizes social-cognitive mechanisms, we use the terms positive and nonpositive because these terms
cover a broader array of mechanisms. We review and compare the contrasting mechanisms posited by the
opposing viewpoints. In doing so, we consider what potential mediators and moderators may underlie the
differences in perspective. This can serve to elucidate differences and enable a more rigorous examination
of the income-SWB relation. Before presenting the specific mechanisms, however, it is useful to describe
different views of income as this is pertinent understanding the proposed mechanisms.
Views of income. We propose that that it is helpful to consider that income has both symbolic and
functional properties. Income is symbolic because it can demonstrate social standing (e.g., socioeconomic
status) and is a symbol of control, and even viewed as a symbolic resource to obtain love (De Vries, 2007).
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Income viewed in this manner corresponds to the first arrow in Figure 1 where income is primarily viewed
in a symbolic manner (and high status goods are purchased to signal high income). Generally, a symbolic
view of income corresponds to the idea that income does not have positive effects on SWB. Having more
income increases SWB, comparison effects reduce the positive effects to nugatory in the long run.
The functional property of income is demonstrated in two ways: (1) as a resource that buffers against
major life events (e.g., illnesses, unemployment), daily life hassles, and inconveniences (e.g., purchase of
help); and (2) as a means to obtain goods and services that are need fulfilling (Diener et al., 2013; Tay &
Diener, 2011). Generally, an emphasis on the functional view of income is often tied to a positive
perspective where income enhances SWB. Points (1) and (2) correspond to the “Resource” and “Need
Fulfillment” arrows in Figure 1, respectively. Generally, a functional view of income corresponds to the
positive view of income on SWB.
Uncovering these viewpoints about income will serve as a focal point linking the different
mechanisms outlined. In the following, we discuss the three mechanisms of status, resource, and need
fulfillment. The moderators for status and resource mechanisms are comparison processes and negative life
events, respectively. These variables are presented in Figure 1.
Status. Income has direct positive effects on SWB through its symbolic value such that, in
comparison to the poor, individuals with higher income would be happier. Apart from the raw value of
income, this could also occur through the purchase of status-building commodities. For instance,
conspicuous consumption is primarily meant to signal high income and greater social status (Corneo &
Jeanne, 1997). However, it has been argued that the symbolic value of income can be unhinged from the
objective value of income because of inherent subjectivity. This is because happiness is fundamentally
dependent on the extent objective income is higher than subjective standards for income, but these
subjective standards continually change with context and income level (e.g., Easterlin, 1974). Specifically,
the potentially positive status effect of income is substantially moderated by comparison processes such
that any positive effects on SWB are negated.
How are comparison processes enacted over different contexts and income levels? With regard to
context, a key driver of changing standards is social comparison. It is proposed that the proximal social
context in which an individual is situated provides the referent point for acceptable levels of income. For
example, the standard of income may be dependent on one’s living context so that the affluence of
neighborhoods may have negative effects on SWB over and above individual income (e.g., Luttmer, 2005).
Nevertheless, proximal social contexts may exert different effects from macro-contexts. It has been shown
that the affluence of nation contexts have positive effects on life satisfaction over and above individual
income (Tay, Morrison, et al., 2014).
With regard to income, it has been proposed that the higher the income, the higher the aspiration.
Therefore, the gap between levels of income and aspired levels of income hinders the extent happiness can
be increased through a rise in income (Frey & Stutzer, 2002). Moreover, as income rises, the referents for
social benchmarking changes. Indeed, Duesenberry (1949) proposed that individuals tended to compare
their own income to the income of others with a similar or higher status. Corresponding research shows that
income comparison effects are asymmetric and primarily upward (Ferrer-i-Carbonell, 2005). Finally, as
income rises, consumption habits may also change, leading to appetites for better goods and services,
thereby raising standards for income (Hudders & Pandelaere, 2011).
The status effect and the moderating comparison processes discussed so far pertain to the individual
level as they are psychological in nature. At the nation level, the direct relation between income and SWB
is complex. On one hand, it has been proposed that income comparisons occur within a nation leading to
positive within-country income-SWB relations but a negligible income-SWB relation between countries
(Easterlin, 1974). This assumes that residents within a country have a common national standard by which
to compare income to. On the other hand, the rationale for limited direct effects because of changing
standards implies that individuals use more proximal standards (i.e., high income individuals use other high
income individuals) or more personal standards (i.e., personal aspiration based on income level), with
research showing that there is diversity in the reference group (Oswald & Senik, 2010). If such specific
proximal/personal standards are used, when aggregating to the nation level, we would expect the effects of
income to be limited. Yet, empirical studies show that the between-country income-SWB relation is
estimated at r = .84 (Veenhoven, 1991). This suggests that comparisons may even occur on a common
global standard due to globalization and media access (Diener et al., 2013).
Resource. Apart from its symbolic value, income can also be viewed as a resource. Drawing on
Conservation of Resource theory (Hobfall, 1989, 2002), individuals seek to acquire and maintain
resources. The possession of resources can exert positive effects on well-being and buffer against negative
life events; a reduction in resources however can exert negative effects on well-being. Therefore, income
535
can generate well-being and buffer against stress generated from negative events (e.g., accidents,
unemployment). On the other hand, having low income or experiencing a loss of income will be
detrimental to well-being. Past research has shown that having the resource of money was predictive of life
satisfaction (r = .30) and its magnitude not far behind social resource (r = .40) (Diener & Fujita, 1995). As a
resource, income can also serve to overcome inconveniences and hassles thereby improving or maintaining
happiness as individuals can engage in more enjoyable activities and obtain paid help for less enjoyable
activities such as chores (cf. Kahneman, Krueger, Schkade, Schwarz, & Stone, 2004).
A key moderator of income from a resource-buffering perspective would be the degree to which
individuals experience negative life events. High income individuals who have a large pool of financial
resources are protected from life “shocks” by maintaining or compensating for negative life events or
conditions. For instance, Philippe Pozzo di Borgo became a paraplegic after a car accident. However, due
to his wealth, he was able to maintain his quality of life by obtaining the service of a full-time domestic
assistant. As such, the resource view of income is indicative of an ameliorative function (i.e., a safety net)
such that downturns more visibly reveal the relation between income and happiness.
A further consideration when viewing income as a resource is that the strength of effects may be
modulated by the level of income. At higher levels of income, where income serves primarily as a
resource-buffer, the accumulation of wealth may not exert strong direct effects as these effects are
contingent on the occurrence of negative life events and serve an ameliorative function. Therefore, at the
upper range of income levels, we may not see robust income effects. On the other hand, at low levels of
income, individuals would constantly experience stress and lowered SWB because of the insecurity of
insufficient financial resources according to Conservation of Resource theory. This may even be
compounded with negative life events. As such, at lower levels of income, we would observe stronger
direct effects of income on SWB.
At the national-level, national income can serve to buffer against national and local negative events.
For example, in the event of a natural disaster, nations have greater economic capacity to mobilize
necessary financial aid and provide material needs for individuals affected by the event. Income serves as a
buffer. From an analysis of how disasters affect poor and rich countries, United Nations Secretary General
Ban Ki Moon underscores this point in the 2016 International Day for Disaster Reduction, “High-income
countries suffer huge economic losses in disasters, but people in low-income countries pay with their lives.”
Need fulfillment. From both organismic (Maslow, 1943) and evolutionary perspectives (Kenrick,
Griskevicius, Neuberg, & Schaller, 2010), money can be viewed as a means to obtain payment for goods
and services and possessing higher income can enable individuals to fulfill physical and psychological
needs. The idea that need fulfillment is tied to well-being has been borne out in multiple studies (Oishi,
Diener, Lucas, & Suh, 1999; Sheldon, Elliot, Kim, & Kasser, 2001). Strong evidence for this idea was
demonstrated in a global study of 124 nations, where the effects of income were fully mediated by the
fulfillment of basic and psychological needs (Tay & Diener, 2011).
At the national-level, it has been shown using cross-lagged analyses that national income predicts
SWB, but not the converse. Importantly, when income rises along with national need fulfillment, there is a
greater increase in SWB (Diener et al., 2013). This suggests that income increases SWB via need
fulfillment at both the individual and nation level.
Comparison of perspectives and mechanisms. Differences in the perspectives and the mechanisms
provide an integrative view of how income may lead to happiness – and the moderators that potentially
affect the causal strength. There appears to be a weaker proposed effect of income when viewed as
symbolic compared to functional. The symbolic view emphasizes status is a means for enhancing SWB, but
comparison effects reduce the positive effects. Although if comparison effects are based on global
standards due to globalization, income may still be linked to SWB. The functional view espouses income as
a potential resource that could provide security and buffer against potential negative events, and as a means
to fulfill fundamental human needs. Between the mechanisms of resource and need fulfillment, stronger
arguments can be made for need fulfillment as exerting more robust effects on SWB. Resources
fundamentally serve to provide some level of basic security and ameliorative function in hardship but do
not address a range of psychological needs that would lead to greater happiness.
Spending and Distribution
While past work has often focused on whether income is associated with or leads to SWB, a critical
mediator of how income is spent – as shown in Figure 1 – has recently attracted more attention (Dunn,
Gilbert, & Wilson, 2011). We believe that this variable is crucial because it specifies how income is
allocated among the different mechanisms (e.g., status, resource, need fulfillment) – which may or may not
have strong promotional effects on SWB.
536
At the individual level, when income is symbolically used and allocated toward increasing status, its
effects on SWB are weaker compared to allocating to as a resource or toward need fulfillment. An
experimental study has shown that reminding individuals of wealth reduces the extent individuals savor
experiences, which refers to the enhancement or prolongment of positive emotional experiences
(Quoidbach, Dunn, Petrides, & Mikolajczak, 2010). On the other hand, when income is allocated as a
resource, its effects are made especially manifest by buffering against negative events. The salutary effect
on SWB of the resource mechanism is not as pronounced as when it serves to protect decrements in SWB.
Finally, when income is allocated toward need fulfillment, positive effects are likely to hold. The current
literature on spending demonstrates that prosocial spending can promote happiness (Dunn et al., 2008).
This relationship between autonomous prosocial behaviors – which would include prosocial spending – has
been shown to be mediated through psychological need satisfaction (Weinstein & Ryan, 2010).
In our model, values are a potential moderator of spending patterns. Individuals who have greater
values and identity placed on prestige would allocate income toward conspicuous consumption (Ottmar &
Wicklund, 1989). Emphasizing appearances of financial success could be lead to habitual compulsive
purchases that do not promote SWB in the long term (Roberts & Pirog, 2004). By contrast, individuals who
place less value in these would place more emphasis the functional aspects of income rather than the
symbolic aspect of income. As a resource, individuals who develop values toward thrift would likely
allocate income into savings (Anderson & Nevitte, 2006). Further, prosocial values would direct
individuals toward spending on others that can fulfill needs of autonomy, relatedness, and competence
which promote SWB (Weinstein & Ryan, 2010).
We note that values themselves provide an implicit or explicit weighting of what matters to
individuals for their well-being. Individuals with higher levels of extrinsic work motivation (i.e., working
for pay and rewards) exhibited a strong relation between income and SWB than individuals with intrinsic
motivation (Malka & Chatman, 2003). Further, individuals living in richer nations, which likely emphasize
income, demonstrated a stronger association between personal income and SWB (Tay, Morrison, et al.,
2014). While this may reduce some of the effects of allocation between income and SWB, this does not
completely negate the effects.
At the national level, values can also guide how nations spend and distribute the financial resources
which in turn has effects on SWB. In a review of inequality and SWB (Tay, Oishi, & Diener, 2017), crosssectional,
and longitudinal evidence revealed associations between income inequality and lower life
satisfaction. An analysis of the Gallup World Poll of 163 nations (2005 to 2013) showed that the GINI
index calculated from annual household income correlated -.44 with national life satisfaction (Diener &
Tay, 2015). Moreover, a cross-national study found that greater national progressive taxation was related to
higher life satisfaction and this association was in part mediated by availability of affordable housing,
public transportation system, education system, and even air quality (Oishi, Schimmack, & Diener, 2012).
This strongly suggests that how nations spend and distribute their financial resources will matter for SWB.
Income Generation Context
A key issue that is often neglected in understanding the relation between income and SWB is the
income generation context. At the individual level, for a large proportion of people, full-time or part-time
employment is the primary means by which they earn their income. At the same time, these same
individuals spend a large proportion of their waking hours at work. Therefore, it is important to examine
how this income generation context can possibly lead to both income and (un)happiness. This is analogous
to the idea that individual differences may lead to the association between both wealth and SWB
(Luhmann, Schimmack, & Eid, 2011).
From the context of work, income and SWB may be positively related because the types of jobs that
pay more also provide greater psychological need fulfillment. From the perspective of the Job
Characteristics Model (Hackman & Oldham, 1976), high-paying professional and management-level jobs
often have characteristics such as skill variety, task significance, task identity, autonomy, and feedback,
resulting in greater fulfillment of psychological needs and hence SWB. In this sense, it may be that income
and SWB are reflections of the type of work one engages in. This is not to suggest that higher income
would not lead to greater job satisfaction and overall SWB, as pay satisfaction and pay equity are important
components of overall satisfaction (Hulin, 1991).
Higher income jobs may also be tied to higher prestige occupations. In seeking to disentangle the
effects of income and work status, Di Tella and colleagues (2010) found that status change in terms of
occupational prestige had more robust and longer lasting effects on happiness as compared to income
change (Di Tella, Haisken-De New, & MacCulloch, 2010). This suggests that to the extent that income and
occupational prestige are tied together, we would observe a stronger relation between income and
happiness. It also suggests that the prestige of the occupation may be more proximal to happiness than
537
income itself.
Conversely, there alternate reasons to suspect that income may also be detrimental to SWB. This is
because income as an extrinsic reward of work has been argued to be ultimately dissatisfying for
individuals according to Self Determination Theory (Ryan & Deci, 2000). Further, having goals for
financial success at work can undermine more important needs such as relatedness (Kasser, 2002). Another
reason for why income does not lead to happiness is framed from a motivational perspective whereby the
narrow pursuit of income-generation activities through work may be at the expense of other key happiness
inducing life domains such as leisure and family. It has been proposed that because of higher opportunity
costs of time use, individuals often forsake relationships and even health (Becchetti, Trovato, & Bedoya,
2011; De Vries, 2007). For example, it has been shown that individuals primed with money spent more
time working rather than socializing (Mogilner, 2010); they also spent less time savoring experiences
(Quoidbach et al., 2010).
At the national level, the income generation context may be represented by the national labor force
(i.e., participation in labor, and the types/levels of occupations) and types of industries (i.e., broad
occupational contexts) in which most individuals within the national economy are in. In addition, there
needs to be a consideration of employment rates within the population as these labor market conditions also
predict national SWB (Tay & Harter, 2013). Future research needs to consider whether controlling for
these factors will show a similarly robust and strong relation between GDP per capita and SWB at the
national level (Diener, Ng, Harter, & Arora, 2010).
Future Issues to Consider
The review and synthesis of the literature has also led to new questions that we have about income
and SWB both methodologically and conceptually. We note several issues to consider for future research.
Foremost, while most of the research has been on income and SWB, there has been a recognition that
income is only one aspect of wealth, more broadly reflecting the economic circumstance of individuals and
societies. Some research has now shown that both income and wealth predict SWB (Headey & Wooden,
2004), although it appears that the relation between broader economic status variables have a greater
relation to SWB (Howell & Howell, 2008). This suggests that research should consider the wealth-SWB
relation (e.g., Fischer, 2007) and other types of economic status variables such as consumption (Headey,
Muffels, & Wooden, 2007), debt (Tay, Batz, Parrigon, & Kuykendall, 2016), and spending (Dunn et al.,
2011).
Given the multilevel context of income and SWB, an important aspect to consider in examining
national, community, or group level income is the distribution of income among members. The way income
is distributed or skewed can have differential effects over and above the average level of income on SWB
(Berg & Veenhoven, 2010; Diener & Tay, 2015). The other implication is in deciding whether the mean or
median is a better representation of group level income. In an examination of the neighborhood income, it
was presented that median rather than mean level income was a better proxy for studying the effects of
neighbor income effects on personal happiness (Firebaugh & Schroeder, 2009). Others have conceptualized
the importance of the range and skew of income within a community as affecting personal happiness
(Hagerty, 2000). The idea of income distribution should also lead to care when targeting specific groups of
individuals as the relation between income and SWB may be attenuated due to range restriction. For
example, research has shown that the relation between income and SWB is low in extremely poor and
moderately poor groups (Lever, 2004).
A multilevel understanding of income and SWB should also help researchers to consider the national
and community contexts in moderating the effects of income and SWB. Past research has shown that
national income boosts life satisfaction in wealthier nations beyond personal income (Tay, Morrison, et al.,
2014). This is likely because national income provides infrastructure and conveniences that poorer nations
do not have. However, at the level of communities, higher levels of community income appear to lower
SWB due to social comparison effects (Firebaugh & Schroeder, 2009; Luttmer, 2005). More research will
need to further examine the extent national or community contexts exert positive or negative effects on
SWB beyond personal income.
As suggested in Figure 1, a multilevel context implies a consideration of culture as well. This may
moderate the effects that are found in the relation between income and SWB. For instance, Caporale and
colleagues (2009) found that the income reference group effect on happiness was negative for Western
Europeans, but it was positive for Eastern Europeans (Caporale, Georgellis, Tsitsianis, & Yin, 2009). This
may be because Eastern Europeans may regard a higher income within their reference group as a source of
inspiration. This parallels a more recent finding that hope mediates that link between a positive relation
between inequality and happiness in rural China, but not urban China (Cheung, 2015).
538
The strongest effects found for income and SWB are primarily for life satisfaction as compared to
the affective components of SWB, which include positive and negative emotions (Diener et al., 2010). In
part, this may be because of income satiation effects on the affective dimensions of SWB as compared to
the evaluation dimension of SWB (Kahneman & Deaton, 2010). Further, evaluations may be more closely
linked to external global conditions as opposed to personal daily circumstances which are more closely
linked to affect (Tay, Chan, & Diener, 2014). More research needs to examine how income can be
effectively used in daily circumstances to promote SWB, including prosocial spending (Dunn et al., 2008)
and experiential spending (Van Boven, 2005; Van Boven & Gilovich, 2003) to even investing in structural
changes that can reduce daily hassles and increase conveniences (e.g., reducing commuting time).
Finally, another important aspect to consider is the valence of income and SWB as a possible
moderator. Given that people are loss averse (Kahneman & Tversky, 1979), income gains over time may be
less likely to raise SWB to the same degree as compared to losses in income. Indeed, there is now evidence
that there is an asymmetry between the impact of economic gains and economic declines at the national
level over time, with economic declines exerting twice the effect of economic gains (De Neve et al., 2015).
Future research should seek to further validate this at the level of individuals over time. In addition, one
can examine whether the impacts are similar depending on the valence of SWB indicators (e.g., positive vs.
negative affect). Using a single measure of life satisfaction, there is some evidence that income is not as
strongly related to high satisfaction, but more related to reducing dissatisfaction (Boes & Winkelman,
2010).
Conclusion
Interest and research on income and SWB has grown over the decades and we expect that this trend
will continue to grow. Understanding and explicating when and how income will give rise to SWB will
strengthen scientific knowledge and policy implications. We hope that this review and synthesis into a
multilevel conceptual framework will advance research and understanding of this domain.
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derivatives
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Beggars do not Envy Millionaires: Social Comparison,
Socioeconomic Status, and Subjective Well-Being
By Michael W. Kraus, Yale University, School of Management
Citation
Kraus, M. W. (2018). Beggars do not envy millionaires: Social comparison, socioeconomic status, and
subjective well-being. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City,
UT: DEF Publishers. DOI:nobascholar.com
Abstract
In this chapter I review theory and evidence linking socioeconomic status in society to subjective wellbeing.
Research on this topic includes studies across countries and cultures and two primary theoretical
perspectives that make predictions about the direction and strength of the relationship between SES and
subjective well-being—need theory and social comparison theory. This chapter suggests that both need
theory and social comparison theories can explain some of the patterns of associations between SES and
SWB but that both theories are underspecified to fully predict the ways in which associations between SES
and SWB shift as a function of situation, culture, and context. Notably, social cognitive tendencies and
cultural definitions of the self that arise from SES, may elicit differential bases for SWB and constrain
researchers’ ability to make complete conclusions about how SES relates to SWB. The chapter closes with
an examination of lay beliefs about links between SES and SWB and their capacity to elicit future
directions in research in this important domain of inquiry. This added complexity is an important next step
in understanding the bidirectional relationships between money and happiness.
Keywords: Subjective Well-Being, Happiness, Social Class, Socioeconomic Status, Inequality
“It’s a kind of spiritual snobbery that makes people think they can be happy without money.” – Albert
Camus (1956)
“I don’t know what they want from me. It’s like the more money we come across the more problems we
see.” –Christopher Wallace, Sean Combs, and Mason Betha (1999)
Earlier this year I was teaching a classroom of 65 first year MBA candidates at Yale University
about the evidence linking high social status to reduced stress and greater well-being. Usually I discuss the
famous Whitehall II studies, the examination of well-being and longevity of British civil service workers
that has been ongoing since 1967. The work itself is perhaps the best available evidence that positively
links social status with health and well-being because of the meticulous social status ranking system that the
civil service uses, the huge sample size (i.e., ten thousand), the longitudinal nature of the design, and that
the sample individuals all have government provided health benefits (Marmot et al., 1991). Links between
higher social status at work and better outcomes with respect to stress, health, and mortality clearly suggest
the role of social status in predicting well-being outcomes over time. Despite the strength of this evidence I
often get vigorous pushback from the students, who will soon be entering into 60-hour work weeks at jobs
in consulting, finance, and law. In these jobs, the monetary rewards are high but so is the stress: Many
newly minted MBAs will burnout from these firms within the first couple of years working there, and face
stiff travel demands, pressure filled deadlines, and long hours throughout their first years (Rivera, 2016).
My experience in the MBA classroom underscores why research on socioeconomic status and
subjective well-being captivates the attention of scholars and lay people alike. How precisely does social
status, defined based on position in society due to socioeconomic indicators like income, education, and
occupational prestige, influence feelings of happiness and life-satisfaction? Is there any evidence
suggesting that the anecdotes from MBAs are indicative of broader trends in large scale empirical studies?
What should we make of the size of the association between social status and subjective well-being?
In this chapter I consider these questions and others related to the ongoing science linking
socioeconomic status to subjective well-being (Lyubomirsky, King, & Diener, 2005). I start with a review
of the basic empirical evidence suggesting links between socioeconomic status (SES) and subjective wellbeing
(SWB) are positive and small to moderate when compared against traditional effect size metrics
(Cohen et al., 1994). I approach this literature from two fundamental theoretical perspectives, the first based
on resource needs and the second based on social comparisons (Diener, 1984; Diener & Biswas-Diener,
2002; Diener, Diener, & Diener, 1995; Diener, Tay, & Oishi, 2013; Ng & Diener, 2014; Pinquart &
Sorensen, 2000). Finally, I return to a consideration of the initial questions that launched this chapter:
Specifically, I draw on research and theory on the psychological experience of SES (Kraus, Piff, MendozaDenton,
Rheinschmidt, & Keltner, 2012) to answer the question: Why might people high in SES believe
their lives are worse in terms of well-being? In particular I am concerned in this final section with
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attempting to understand what scholars might be missing from examinations of SES and SWB, in order to
anticipate new areas of future research.
SES, SWB, and Individual Needs
Theoretical arguments for links between SES and subjective well-being are numerous and varied
(Diener, Ng, Harter, & Arora, 2010; Diener, Oishi, & Lucas, 2003). Here we provide a detailed summary
of the arguments that suggest how large SES and subjective well-being associations can be expected to be,
and in turn, what factors might moderate these associations.
Links between SES and subjective well-being may depend in part on whether people’s basic needs
are being met by their available resources. As the argument goes, as people are able to afford the resources
necessary to meet the demands and threats inherent in their environments, the impact of SES on well-being
should be diminished. This theoretical argument was originally discussed by Easterlin (1974; 1995; 2001),
and finds similar logic in recent work in psychology (Diener & Biswas-Diener, 2002; Diener & Lucas,
2000; Veenhoven, 1988; 1991). Importantly, this needs based explanation for links between SES and
subjective well-being elicits an expectation that links between SES and well-being will be smaller in
developed countries like the USA relative to developing countries where basic resource would be used to
obtain physical needs, such as food, sanitation, and shelter (c.f., Maslow, 1974).
Admittedly, there is only mixed support for this needs-based explanation of links between
subjective well-being and SES. Several studies conducted across different countries have provided support
for this needs-based explanation (e.g., Biswas-Diener & Diener, 2001; Camfield, Choudhury, & Devine,
2009; Diener, Oishi, & Lucas, 2003; Fuentes & Rojas, 2001; Kim, 1998; Zavisca & Hout, 2005). For
instance, within country analyses tended to produce smaller associations between SES and subjective wellbeing
(r = .06 to .15; Diener & Oishi, 2000; Diener, Sandvik, Seidlitz, & Diener, 1993; Easterlin, 1974;
1995; 2001; Rojas, 2004) than do studies in developing nations (r = .10 to .36; Howell & Howell, 2008). In
more recent work, surveys of 123 countries found that reports of need fulfillment accounted for income
associations with SWB (Tay & Diener, 2011). However, these patterns are not always observed: A recent
meta-analysis updating these findings with a far larger database of research finds no moderation by
development status and a small association (r = .11; Tan, 2016). This meta-analysis is notable because of
its total sample size (N = 3,249,838) and number of independent samples ( k = 144).
Overall, then we find only mixed support for need based explanations of associations between SES
and SWB. The evidence is not yet definitive and thus more work needs to be conducted in this domain of
research. One point of contention appears to be how people might define needs. For instance, cross-national
comparisons involve a complex calculation of whether or not an individual’s needs are being met, without
potentially thinking critically about how need is culturally bounded and situated (Henrich, Heine, &
Norenzayan, 2010). That is, both the costs of fulfilling ones needs might shape the strength of association
between SES and SWB as well as how an individual defines those needs, or sees them as central to living
(e.g., Diener, Suh, Lucas, & Smith, 1999). Relatedly, the detail at which researchers assess subjective
experiences of need might explain some of the inconsistency in research testing need theory. Studies that
examine individual differences in daily experiences of need might be better equipped to answer the
question of need-based influences on SWB. Such studies would also be a remarkable advance on prior
research because such fine-grained analyses of need could show associations with SWB in longitudinal
designs that could delineate the directionality of associations between SES and SWB.
Aligning with this perspective on obtaining finer detail in need experiences, the second perspective
on SES links with SWB relies on understanding daily experiences in comparisons between self and others.
How these experiences of economic comparison shape basic feelings of subjective well-being is a rich and
growing area of research.
Beggars and Millionaires: Social Comparison and SWB
“Beggars do not envy millionaires, just other beggars who are more successful.” –Bertrand Russell (1930)
A second theoretical perspective indicates that links between SES and subjective well-being may
depend on the relevant comparisons people make to others, to past circumstances or selves, or to some
fluctuating standard of living. Theories that rely on some form of social comparison make a few different
predictions about SES and subjective well-being links. First, expectancy based arguments would indicate
that the strength of the association between SES and SWB depends on changing standards, such that
individuals are higher in SWB when their current level of economic resources is greater than what they
expect it to be based on an assessment of their current social group (Clark, Frijters, & Shields, 2008; Clark
& Oswald, 1998; Diener & Fujita, 1997).
Several lines of evidence find both direct and indirect support for this expectancy argument. For
instance, Black Americans, a low status racial group in America, might have lower standards for how much
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resources they can attain in society due to prejudice and discrimination. Thus, they may derive higher SWB
from lower levels of SES (Diener et al., 1993). In support of this assertion, data from the general social
survey finds that Black people tend to report higher self-esteem than other racial groups in America, despite
having lower levels of income and education (Cohen et al., 2017).
Expectancy effects may also lead individuals to feel enhanced SWB if their achievement outstrips
some objective standard. Consistent with this prediction, higher income levels are likely to predict
increased happiness only in conditions where income changes are rapid enough to outstrip people’s
expectations (Diener et al., 1993; Graham, 2005). Similarly, the discrepancy between current and future
desired resource levels tends to predict SWB more than the discrepancy between current and actual
resource levels (Stutzer, 2004). All told, this research indicates that expectations based on future selves
play a role in shaping links between SES and SWB.
Social comparisons may influence SWB with respect to comparisons to others in one’s relevant
social groups (Festinger, 1954). Comparisons of resources between the self and others are a frequent and
unavoidable part of social life. Several studies suggest that aspects of wealth and social status are visible in
the clothes people wear (Kraus & Mendes, 2014; Gillath, Bahns, Ge, & Crandall, 2013), in nonverbal
behaviors (Kraus & Keltner, 2009) and physical characteristics of individuals (Mast & Hall, 2004;
Bjornsdottir & Rule, 2017). More recent work finds that people can provide others with information about
how much money they make and their educational attainment based on paralinguistic cues in speech
(Kraus, Park, & Tan, 2017; Labov, 1972). Certainly, societal segregation based on schools and
neighborhoods is also a source of accurate perception of SES (Desmond, 2016; Massey & Denton, 1993).
All told, there are many means by which individuals can compare on SES dimensions, and thus,
these comparisons can influence SWB in a variety of ways (Bourdieu, 1979). For instance, nurses who
made frequent comparisons to colleagues at work about income and status tended to be less satisfied with
their jobs than did those who made fewer comparisons (Buunk, Schaufeli, & Ybema, 1994). As well, in the
aforementioned meta-analysis, subjective perceptions of social class which require participants to compare
and rank themselves relative to other community members tend to predict SWB at twice the magnitude (r =
.21) of objective indicators of income and educational attainment (r = .11; Tan, 2016), though common
method variance (i.e., self-reports of both social class and SWB) may be a potential source of the size
difference in this association (Cohen et al., 2008; Adler, Epel, Castellazzo, & Ickovics, 2000; Kraus,
Adler, & Chen, 2013).
The Whitehall II data can also be thought of as evidence for social comparisons influencing wellbeing.
In these data, civil service workers differ in rank much more than they do in terms of income and not
at all in terms of health benefits (Marmot et al., 1991). And yet, even with these stark similarities of needs
being met, higher ranked civil services workers have much more positive health outcomes in terms of selfreports
related to SWB, and objective health indices such as heart disease and mortality rates.
Other indirect evidence in the realm of economic inequality is indicative of the influence of
comparison processes on SWB. For instance, even when controlling for objective material resources,
several studies find that unequal resource sharing predicts increases in broad societal problems related to
poor health care practices, delinquencies, and societal dissatisfaction (Wilkinson, 1992; Wilkinson &
Pickett, 2006), as well as reports of lower SWB (Oishi, Kesebir, & Diener, 2011; Cheung & Lucas, 2015a;
2015b). Related work finds that living near wealthier neighborhoods is associated with poorer health
among people living in less wealthy neighborhoods (Pellowski, Kalichman, Matthews, & Adler, 2013), and
living around wealthier neighbors is associated with lower levels of SWB (Luttmer, 2005).
Studies more directly testing comparison accounts of associations between SES and SWB yield
similar converging evidence. Boyce and colleagues (2010) used more than 86,000 respondents from the
British Household Panel Survey to calculate a ranking based on whether an individual had higher income
relative to others. The researchers then compared this ranking metric’s association with life-satisfaction to
the association between absolute income level and life-satisfaction. The results showed that relative ranking
predicted life-satisfaction more strongly than did absolute income (Boyce, Brown, & Moore, 2010).
In more directly related work examining social comparisons, Anderson and colleagues (2012)
examined associations between SWB and sociometric status, defined as prestige and respect within ones
important social groups. Sociometric status, the logic goes, is a locally defined form of social status that is
determined through interactions with people and groups that an individual cares about and spends a great
deal of time with. Across the studies, sociometric status with friends, co-workers, and class mates tended to
predict SWB more strongly than did absolute SES (Anderson, Kraus, Galinsky, & Keltner, 2012).
Despite this consistent evidence there are a few studies where comparisons do not predict SWB
(e.g., Diener & Fujita, 1997). For instance, among a sample of county employees in Wisconsin, social
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comparisons contributed virtually nothing to pay satisfaction ratings after accounting for equity concerns,
occupation type, past employment, and noneconomic job standing (Berkowitz, Fraser, Treasure, &
Cochran, 1987). Whether social comparison effects emerge after accounting for related constructs like
social status, occupation type, and equity concerns is a topic of future research. Related to this point, that
people high in trait neuroticism compare more than others is also an area of future research (Gibbons &
Buunk, 1999), in that social comparison effects related to SWB may emerge in part because of the elevated
trait anxiety levels of the people doing most of the comparing.
Overall, there is systematic and fairly consistent evidence linking social comparison perspectives to
patterns of associations between SES and SWB, and this theoretical perspective remains promising in
helping researchers to predict these relationships. Still, there is sufficient work that needs doing in this
research. Notably, social comparison theories are not particularly specific about which comparisons are
likely to be most important or most active in predicting SWB, and thus, thinking critically about how
cultures and position influence these comparisons is a topic of future research. As some studies suggest,
cultural beliefs about the importance of objective standards of social judgment might influence whether
people compare their resources to objective criteria about wealth (e.g., median income) or to more
subjective criteria (e.g., status symbols, educational prestige, dress). For instance, in one study objective
standards of SES predicted well-being reports more in Japan than they did in the USA, where subjective
reports of social class were a better predictor (Curhan et al., 2014). That Japanese participants relied more
on objective standards of economic standing rather than their own subjective assessments potentially
illustrates a cultural differences in the sorts of economic and social comparisons that people may value
(e.g., Choi, Kim, & Park, 2015; Chung & Mallery, 1999; Hofstede, 1984; Markus & Kitayama, 2003;
2010).
Lay Beliefs about SES and SWB
Popular narratives in the USA tend to associate hard work with success, and in fact, the American
Dream of equal opportunity and the possibility of prosperity for all is predicated to an extent on
individuals obtaining valued economic and psychological states based on their merits alone. This narrative
is a powerful influence on the ways in which individuals explain the structure of society. For instance,
beliefs in the American Dream tend to lead people to see societal inequalities as more fairly and justly
determined than they could possibly be given the sheer magnitude of inequality in society. That is, despite
wide disparities between CEO pay relative to the average worker (Kiatpongsan & Norton, 2014), or the
accumulation of wealth in the top income decile (Norton & Ariely, 2011), people tend to see societal
inequality as fundamentally determined by effort, talent, and merit (Jost, Banaji, & Nosek, 2003; Kay &
Jost, 2003; Kraus & Tan, 2015). In some ways these beliefs in meritocracy motivate striving and
achievement (Anderson, Brion, Moore, & Kennedy, 2012; Johnson, Blumstein, Fowler, & Haselton,
2013), whereas they also obscure real trends in inequality—that society is much more unequal than we
want it to be or that we realize (Norton & Ariely, 2011), or that intergenerational mobility is low (Davidai
& Gilovich, 2015). How these beliefs systems may shape beliefs about links between SES and SWB is the
topic of this third section.
Just as narratives of mobility and the American Dream are inconsistent with reality so too are
narratives about stress and work-related well-being: With only a cursory examination of articles in leading
business magazines (e.g., Petrie, 2017) and books (e.g., Seppala & King, 2017) one finds a wealth of advice
about how CEOs and managers can cope with the tremendous amount of stress their jobs place them under.
In fact, popular lists of stressful jobs indicate jobs as military personnel and firefighter have similar stress
levels as higher SES jobs such as broadcaster, public relations executive, and senior corporate executive
(Renzulli, 2016). However, despite these lay beliefs about job stress, empirical investigations of
associations between SES and subjective well-being, many of which we have reviewed above, clearly
delineate a positive association between SES and SWB.
Research on stress finds an even stronger positive relationship: In an examination of high level
corporate managers and their subordinates, managers consistently felt less anxiety and showed lower levels
of glucocorticoids in their saliva, a measure of physiological stress (Sapolsky, 2004), than did their
subordinates (Sherman et al., 2015). As well, all-cause mortality is consistently higher among lower,
relative to higher, SES people (Adler et al., 1994; Kawachi & Kennedy, 1997; Kennedy, Kawachi, &
Prothrow-Stith, 1996) even in studies like Whitehall II where all participants share the same health benefits
(Marmot et al., 1991).
Where does this disconnect between lay beliefs about links between stress or SWB and SES and
the actual associations come from? Critically, we contend that beliefs suggesting that it is more stressful
and less satisfying at the top serve to promote adherence to the American Dream and increase tolerance for
inequality in society. In effect, lay beliefs that CEOs face stress feed into beliefs about the merit-based
546
organization of society and suggest that success is built primarily based on hard work and effort.
Inequalities, even ones of huge scale, are justified given the theoretical magnitude of the physiological toll
they might take on the highest status individuals. In effect, if CEOs suffer high stress lives, non-CEOs might
not begrudge their 300 to 1 salary advantage relative to the average factory worker (Kiatpongsen & Norton,
2014).
This explanation aligns with recent work suggesting that individuals tend to highlight the
headwinds they tend to experience in their lives, which serve these ideologies of merit and deservingness.
For instance, empirical work finds that people have a much easier time of bringing to mind the things they
struggle with (i.e., headwinds) rather than the advantages they have benefited from in the past (Davidai &
Gilovich, 2016). In related work, a recent ethnography of elite business hiring in law, consulting, and
finance, successful job applicants tended to perform better to the extent that they crafted relatable stories
about their capacity to overcome significant personal obstacles (Rivera, 2016).
This disconnect between lay beliefs and actual connections between SES and SWB also highlights
the importance of future research providing finer detail assessments of both daily experiences of SES and
of SWB. On the side of SES, linking shifts in attainment of basic needs or in comparisons with important
others to fluctuations in experiences of SWB, particularly through the use of experience sampling methods,
is likely to provide significantly greater understanding of lay beliefs about SWB. For instance, it is possible
that the job stressors experienced by high SES individuals do lead to reductions in well-being for these
individuals that are temporary or that significantly change moods or cognitive assessments of lifesatisfaction
in enduring and persistent, but these shifts nevertheless stay higher on average, than the SWB
reports of lower SES individuals. Likewise, it might be the case that the monetary rewards received by
higher SES workers account for the satisfaction of needs that then reduces the psychological impacts of
any stress experienced at work. An experience sampling methodology that takes into account both need
fluctuations and the comparisons one experiences in important social situations might highlight how
differential correlates of SWB operate in opposition versus in unison. Along similar lines, high SES jobs
may disproportionately expose workers to opportunities for job crafting and autonomy that predict
enhanced SWB (Wrzesniewski & Dutton, 2001; Wrzesniewski, McCauley, Rozin, & Schwartz, 1997).
Lastly, it is possible that lay beliefs are disconnected from the reality of links between SWB and
SES because people tend to discount the role of power and autonomy in experiences of SWB. In short,
there is a wealth of research indicating that having some control over life outcomes, even if it is mundane
or illusory, can have positive benefits on feelings of happiness and well-being. In survey research, feelings
of power and control are strongly related to feelings of authenticity and autonomy (Kifer, Heller,
Perunovic, & Galinsky, 2013), which are also strongly correlated with subjective well-being (Kraus, Chen,
& Keltner, 2011). For instance, in the aforementioned study on high ranking manager stress, a sense of
control tended to explain why managers felt less anxiety than their subordinates (Sherman et al., 2012). In
the research on sociometric status and SWB, people who were higher in sociometric status tended to
experience heightened SWB in part due to its correlation with heightened sense of power and autonomy
(Anderson, Kraus, Galinsky, & Keltner, 2012). Given these data, it is likely that individuals do not account
for their elevated control and autonomy relative to others, nor do they account for how much this freedom
plays a role in eliciting positive SWB. In fact, prior research indicates higher SES individuals tend to
overemphasize the controllability of everyday life events and circumstances relative to their lower SES
counterparts (Kluegel & Smith, 1986; Kraus, Piff, & Keltner, 2009; Kraus, Piff, Mendoza-Denton,
Rheinschmidt, & Keltner, 2012; Varnum, 2015; Varnum, Shi, Chen, Qiu, & Han, 2014). Based on this
work, a lack of understanding of cultural or positional differences in control beliefs may account for some
of the discrepancy in lay beliefs about SES and SWB.
Caveats and Future Directions
Overall then, this chapter has examined prior theory and research linking SES and SWB.
Importantly this is a rich and influential empirical literature with a number of direct and conceptual
replications that allow us to get a clearer picture of the magnitude and direction of associations between
SES and SWB. Uniquely, statistical examinations of publication bias in the SES and SWB literature,
conducted in the aformentioned meta-analysis show low levels of publication bias (Tan, 2016)—which
suggests that this literature allows for a tighter fit between the empirical evidence and reality than many
psychological literatures can muster. With that as backdrop, the evidence indicates that SES and SWB
show small to moderate positive associations. This chapter makes the point that social comparison
processes play a central role this association whereas the role of need fulfillment is less clear based on the
literature.
Despite the considerable amount of knowledge that has been accumulated linking SES to SWB
more work is necessary. For instance, both SES and SWB are broad bundle variables that encompass a
547
number of social and psychological correlates that are hard to pin down in any large scale study with a goal
of comprehensive data collection using large samples. This means that researchers may still be decades of
study away from truly describing the intricacies of connections between SES and SWB, their cultural
variations, and the role of daily fluctuations in SES related variables and their causal influence on SWB.
Experience sampling methods offer a way forward, although these methods might lead to a
conscientiousness sampling bias or might bias mood reports (Scollon, Prieto, & Diener, 2009).
Nevertheless, these methods allow for more fine-grained analysis of local comparison processes that, in
prior research, are linked most strongly to SWB (Anderson, Brion, Moore, & Kennedy, 2012). Daily
experience sampling may also provide a window into how cultural differences shape SWB in that cultures
may not shift SWB itself but may instead, shift according to unique types of comparisons (Curhan et al.,
2014).
Lastly, our understanding of lay beliefs about the American Dream and societal opportunity are
rarely invoked when examining links between SES and SWB, and this dearth of connection in the literature
is an important point of potential theoretical advancement. In short, how individuals theorize about
happiness and well-being may differ from how they actually experience happiness and well-being. These
differences have implications for how people think about health care and health benefits and their
availability to all members of society, as well as, potentially providing justifications for the levels of SES
disparities in society. Broadly, improving lay belief accuracy in associations between SES and SWB has a
number of direct benefits—most directly, that it uncovers the real impact that economic advantages have
on the subjective experiences, mood, and meaning of the lives of individuals.
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Healthy social bonds: A necessary condition for well-being
By Shelly L. Gable & Christopher Bromberg, University of California, Santa Barbara
Citation
Gable, S. L., & Bromberg, C. (2018). Healthy social bonds: A necessary condition for well-being. In E.
Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
Do individuals need relationships with others to thrive? We begin this chapter with a review of the
evidence that the formation and maintenance of positive social bonds contributes to mental and physical
health and conclude that people need social bonds not only to thrive but to merely survive. This conclusion
is based on the well-established empirical links between physical health and interpersonal relationships and
the equally well-established links between subjective well-being and interpersonal relationships. We then
turn our attention to the question of how relationships might contribute to well-being. Processes such as the
reduction of negation emotion, shaping the self-concept, support for personal goals, and eliciting positive
emotions are highlighted as mechanism through which social partners have the potential to enhance wellbeing.
We then turn our attention to areas in the literature that we see as ripe for future attention.
Keywords: Close relationships, well-being, loneliness, interpersonal processes
In the seventeenth century when John Donne wrote that “no man is an island” he was observing that
human beings do not seem to thrive in isolation from one another. Similarly, psychologists have asked the
question of whether human beings need social bonds not only to thrive but also to survive. A nifty feature
of the human mind is that it is has motives that prompt individuals to act to obtain the goods we need. For
example, the experience of hunger and thirst prods us to seek food and water. Although it has long been
evident that people are motivated to form and maintain social relationships (e.g., Murray, 1938), early
theory and research viewed humans’ social motivation as a derivative of other basic needs, such as the
behaviorists’ view that social bonds are rewarding because of leaned associations created when others
provide rewards, such as food. However, this view did not hold up to empirical testing, perhaps the most
famous demonstration coming from Harlow’s (1958) findings that baby monkeys preferred a soft cloth
mother “monkey” that offered no additional rewards over a hard one that fed them. Indeed, a mountain of
empirical data indicates that people’s motivation to form (and keep) social relationships is basic in that it is
not a derivative or byproduct of other motives or needs (e.g., Deci & Ryan, 2000). Of course, just because
humans are built to want social bonds does not in and of itself mean that they need them to survive and
thrive. However, there is overwhelming historical and empirical evidence that there are substantial negative
health and well-being consequences if social needs are not met, especially in the long term. (e.g., Akerlind,
Hörnquist, & Hansson, 1987; Durkheim, 1897; Holt-Lunstad, Smith, & Layton, 2010).
Physical Well-Being, Mortality and Social Bonds
Large scale epidemiological studies on predictors of mortality have consistently revealed that social
isolation is a substantial risk factor for death (e.g., Berkman & Syme, 1979). In fact, in their 1988 review
House, Landis, and Umberson concluded that a lack of strong social ties carried a mortality risk that was
similar to that of smoking. A more recent meta-analysis of 148 longitudinal studies by Holt-Lunstad, Smith,
and Layton (2010) came to strikingly similar conclusions. The authors found that high quality connections
were as robust predictors of death (or in most cases, more robust) as other well-established mortality risks
such as excessive alcohol use, obesity, and failure to treat hypertension. Studies that measure disease and
health symptoms show similar patterns such that disease instance is higher, recovery longer, and relapse
greater in those who are socially isolated (e.g., Steptoe, Owen, Kunz-Ebrecht, & Brydon, 2004; Hawkley &
Cacioppo, 2003).
The question of how social relationships “get under the skin” is the focus of much current research
and several physiological processes and systems linking social isolation to health have been documented.
Studies have linked loneliness to disruptions in health restorative processes such as sleep (e.g., Hawkley &
Cacioppo, 2010). Threats of negative evaluation by others are associated with a heightened stress response.
Such responses, while adaptive in the short-term as a response to stress, have a host of negative
physiological implications when chronically activated, as is the case of those who are socially isolated or
lonely (e.g., Dickerson & Kemeny, 2004; Uchino et al., 2001). These findings are consistent with Cole and
colleagues (2007) who found that people who suffer from chronic loneliness also have elevated proinflammatory
activity, which is a risk factor for a host of inflammation-related disease, including
cardiovascular disease. In short, being socially isolated and having a lack of supportive social bonds is
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associated with elevations in problems across a host of cardiovascular, endocrine, and immune systems (for
review see Hawkley & Cacioppo, 2003; Uchino, Cacioppo, and Kiecolt-Glaser, 1996; Wilson et al., 2007).
In addition to the empirical evidence linking a lack of social ties to mortality and disease, there is
also good evidence that the quality of social relationships, not their mere existence is linked to health. In
the Holt-Lunstad and colleagues’ meta-analysis cited above people who reported having poor social
connections had a 40% higher mortality rate at follow-up than those who reported having positive and
supportive connections to others (Holt-Lunstad, Smith, & Layton, 2010). Other work has supported the
conclusions that conflictual, cold, or uncaring social bonds have negative health consequences (e.g.,
Kiecolt-Glaser & Newton, 2001; Miller, Rohleder, & Cole, 2009). For example, marriages characterized by
hostile conflict and a high degree of negative emotion are a risk factor for cardiac disease and death (Eaker,
Sullivan, Kelly-Hayes, D’Agostino Sr, & Benjamin, 2007; Wilcox, Kasl, & Berkman, 1994). Pathways for
this risk lie in dysregulation of immune functioning and impaired cardiovascular reactivity (Kiecolt-Glaser,
1999; Uchino, Holt-Lunstad, Uno, & Flinders, 2001). Finally, another direct pathway linking relationships
to mortality and physical health is violence at the hands of abusive relationship partners (e.g., Ellsberg,
Jansen, Heise, Watts, & Garcia-Moreno, 2008).
In summary, the empirical literature examining the links between social ties and health reveal two
major themes. First, loneliness and social isolation are associated within increased mortality and disease
incidence. Second, the presences of social ties in and of itself is not sufficient to lower these risks. Social
relationships that are high in conflict, rejection, exploitation, or coldness do not offer protection from the
risks and in fact add to them. On the contrary warm, caring, and supportive ties are associated with
increased physical health, recovery from disease, and lower mortality. Of course, any one social bond can
have both rewarding and costly components and have positive and negative effects on health (see also
Gable & Gosnell, 2013; Uchino et al., 2013).
Psychological Well-being and Social Bonds
Mirroring the findings that link social ties to physical health, the literature examining social ties and
psychological health and well-being also finds strong associations. For example, social isolation and
loneliness are correlated with depression, schizophrenia, personality disorders, substance abuse and
subjective well-being (e.g., Akerlind, Hörnquist, & Hansson, 1987; Helliwell & Putnam, 2004; Neeleman
& Power, 1994; Overholser, 1992). Once again, the quality of social ties, beyond the mere existence of
them, predicts well-being. For example, studies consistently find that people who have rewarding social
and family relationships have higher overall life satisfaction than those with less rewarding social and
family ties. In one study, the distinguishing feature separating those who were very happy (e.g., top 25% of
sample) from those who are less happy (e.g., bottom 25% of sample) is the quality of their social ties
(Diener & Seligman, 2002). Relationships that are hostile, conflictual, insecure, or cold are associated with
low self-esteem, depression, anxiety, and substance abuse (e.g., Davila, Bradbuy, Cohan, & Tochluk, 1997;
Holmes, 2002; Whisman, Uebelacker, & Settles, 2010).
The social domain is a better predictor of well-being than other domains of life which have long been
assumed to drive well-being such as career and financial attainment (e.g., Campbell, Converse, & Rodgers,
1976). The link between relationship quality and well-being has been documented across the stages of
human development, consistently showing strong and positive correlations in children, adolescents,
younger adults, and older adults (e.g., Chen & Feeley, 2014; Sherman, Lansford, & Volling, 2006;
Bradshaw, Hoelscher, & Richardson, 2007). Some recent evidence has also shown that relationship quality
in early life (e.g., maternal sensitivity towards infants) is associated with later (i.e., adult) health and wellbeing
(Farrell et al., 2017).
Much of the evidence on well-being reviewed above concerns subjective reports of well-being and
happiness or what has been referred to as hedonic well-being. However, theories of eudaimonic well-being
inevitably include high quality social relationships in their very definition. For example, Ryff & Keyes’
(1995) model contends that having positive relationships with others is one of six components of wellbeing.
Deci & Ryan (2000)’s theory of self-determination states that well-being is contingent on meeting
three fundamental human needs, one of which is feeling connected to other people. Models of well-being
that place healthy social bonds at the core are consistent with Bowlby’s (1969; 1988) model of attachment.
He outlined a theory in which attachment figures (caregivers for infants and later in development peers,
friends, and romantic partners) serve several functions necessary for survival—providing a safe haven to
return to in times of stress and being a secure base from which to launch explorations into the world.
Bowlby’s model ties the attachment system closely to psychological well-being and stress reaction.
Although in the remainder of this chapter we focus on the role of healthy social bonds for subjective
well-being, it is important to note that by definition, most models of eudemonic well-being include the
criteria of positive interpersonal relationships and thus this review is relevant to both conceptualizations of
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well-being. Of course, as anyone who has taken an introductory statistics courses can tell you, correlations
such as the ones reviewed in the previous section do not tell us whether social relationship quality
contributes to well-being, or vice versa. Luckily there is substantial evidence from longitudinal studies that
shows that both pathways occur (e.g., low well-being leading to later social isolation and social isolation
leading to later lowered well-being; e.g., Whisman & Bruce, 1999). In this chapter, we focus much of our
remaining attention on the pathways and mechanisms through which social relationship contribute to and
detract from well-being, however we note that we could write an entire other chapter on pathways linking
how well-being/ health to relationship functioning.
Mechanisms Linking Social Bonds to Well-Being
As the above sections hopefully make clear, our main theme is that warm, supportive, and trusting
relationships that are low in hostility and insecurity are associated with high well-being. While this is
certainly a two-way street, there is sufficient longitudinal and experimental evidence to conclude that at
least part of this association can be explained by the fact that high quality social relationships contribute to
an individual’s overall health and well-being (e.g., Holt-Lunstad et al., 2010; Hawkley et al., 2009). In the
next section, we turn our attention to a discussion of how social relationships contribute to or detract from
well-being. That is, we review and critique the specific aspects of relationships that researchers have
suggested link our social bonds to well-being. Three major themes emerged in our review of these
mechanisms. First, social relationships help buffer individuals from the negative events and stressors in
life. Second, social relationships can facilitate or hinder goals pursuit and growth of one’s sense of self.
Finally, social relationships provide rewards independent of reduction of threats or facilitation of goals.
Social Relationships Buffer Against Threats
Negative emotions are functional with clear implications for survival (e.g., Tooby & Cosmides,
2008). For example, the fear response to a predator can mobilize our physiological fight or flight responses;
feeling guilty for standing up a friend can help motivate us to repair the fractured relationship (Keltner &
Haidt, 1999; Tooby & Cosmides, 2008). Thus, the experience of negative emotions per se is healthy.
However what is not physically or psychologically healthy is the chronic experience of negative emotions
or experiencing negative emotions repeatedly in conditions where they are not warranted (e.g., Adler &
Matthews, 1994; Repetti, Taylor, & Seeman, 2002). This work generally falls under the topic of threat or
stress responses and research suggests that social relationships can play a role in people’s experience of and
reactions to stress (e.g., Hawkley, Thisted, & Cacioppo, 2009; Saxbe & Repetti, 2010). For example, there
is evidence that the mere presence of social relationship partners can have an impact on our biological
stress system as indicated by increases in the hormone cortisol. Saxbe and Repetti (2010) found evidence
that spouses regulated one another’s cortisol response such that when one spouse was experiencing
negative emotions (and had a spike in cortisol) the other spouse experienced a corresponding spike in
cortisol. Interesting, the less satisfied spouses were with each other in general the greater the synchronistic
response. In the following sections we outline two general pathways that social relationships can reduce (or
exacerbate) an individual’s experience with stress--through influencing the exposure to stressors and
through influencing the reaction to negative stimuli.
Exposure to negative events. Social relationships can increase or decrease the number of negative
events that people are exposed to through several routes. In order to experience an event or stimuli as
negative or threatening it needs to be noticed. In their Social Baseline Theory, Beckes and Coan (2011)
have made an evolutionary argument that the presence of benevolent social partners reduced our vigilance
to threat through a process they have called risk distribution. Specifically, they posit that in ancestral time
that the number of people in a social group increases, the statistical distribution of environmental risks (e.g.,
attack by predators) for any one of the individuals in a group goes down. Therefore people can adjust their
own vigilance to threat because the social partners literally provide more eyes and ears on the environment.
This reduced threat vigilance can mean smaller or more distant threats do not register when in a group of
benevolent social partners. The flipside is that isolation or being part of a hostile social group likely
increases vigilance and lowers the threshold of threat detection such that small or distant dangers are
noticed and interpreted as threats. Social Baseline Theory is intriguing and while there is evidence
supporting aspects of the model (e.g., Coan, Schaefer, & Davidson, 2006), there is a need for additional
empirical evidence as to whether risk distribution influences attention per se, or rather has an influence on
the interpretation of ambiguous or mildly threatening stimuli.
Other research has however shown that social relationship partners can serve as a context in which
ambiguous or neutral events are appraised as benign or raise a stress response. For example, people who
have been trained to seek out a smiling face in an array of disapproving faces on a previous task were less
likely to show interference from negative words in a subsequent Stroop task (Dandeneau, Baldwin, Baccus,
Sakellaropoulo, & Pruessner, 2007). Social partners can also directly influence exposure to unambiguously
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negative stimuli. Social partners can take on the responsibility of (or add to) some of life’s tasks (e.g.,
paying bills), thus diffusing daily hassles, which are comparable to major life events in terms of their
contributions to stress (Kanner et al., 1981). Interactions with social partners themselves can be potentially
negative events (e.g., conflict, rejection) and thereby actually increase exposure to stress directly (e.g.,
Veroff, Douvan, & Kulka, 1981).
Responses to negative events. Research also shows that social partners can mitigate or exacerbate
one’s response to negative events and stimuli. For example, Eisenberger and colleagues (2011) found that
simply viewing a close relationship partner while receiving mildly painful stimuli led to reductions in selfreported
pain ratings as well as less activity in pain-related areas of the brain. Although recent work such as
this has shown that the mere presence of close others can influence reactions to negative events, by far most
of the evidence that social partners contribute to the stress reaction comes from the social support literature.
Numerous studies have shown that simply perceiving that social partners would be available to help if
help were needed is closely tied to well-being (e.g., Kaul & Lakey, 2003). However, actually receiving
emotional or tangible support from social partners, which is called enacted or received support shows are
more nuanced association between well-being and social bonds (e.g., Dakof & Taylor, 1990). This literature
has shown that when social partners offer support for stressors sometimes it leads to a decrease in
recipients’ negative emotions and other times it is associated with increases in the recipients’ negative
emotions, and still studies show that there is no association between the two (see Rafaeli & Gleason, 2009;
Gleason, Iida, Bolger, & Shrout, 2003). Confounding the picture even further, the perception that others
will be available in the future if needed (perceived support) is not strongly correlated with experiences of
actually receiving support (Haber, Cohen, Lucas, & Baltes, 2007). The disconnect between perceived and
actual support leads to confusing results. For example, Krause (1997) found that greater perceived
availability of support was associated with decreased depression, but receiving actual support was
associated increases in depression.
In this literature it is often difficult to account for the confound that stress and well-being are likely
linked, such that those who are under more stress (and lower in well-being) may receive more support.
However, studies that are able to tease apart these factors still show that received support has a negative
impact on outcomes beyond this confound (e.g., Rini, Schetter, Hobel, Glynn, & Sandman; 2006).
Researchers have hypothesized that receiving support can have a detrimental effect on well-being because
of potential inadvertent consequences of receiving support even while contributing to the perceptions of
future support availability (Rafaeli & Gleason, 2009). Receiving support may lead the recipient to feel
indebted or incompetent (Gleason, et al., 2003; Shrout, Herman, & Bolger, 2006); be a blow to self-esteem
because a vulnerability or weakness has been made salient, or even just draw more attention to the problem
(e.g., Bolger, Zuckerman, & Kessler, 2000).
In short, receiving support may be helpful for reducing negative emotions associated with stressful
events but those same actions from a social partner can create negative emotions. One intriguing line of
research by Bolger and colleagues (2000) has suggested that the best type of support is that which is
provided without the recipient even noticing, known as invisible support. In addition, support is difficult to
provide effectively which can exacerbate these problems. The research shows that when relationship
partners are responsive to one’s needs they can provide support that is associated with increases in wellbeing
in the recipient, while those who provide support that is unresponsive to one’s needs can actually
decrease well-being one helpful and positive social bonds (Maisel & Gable, 2009). However, the bottom
line is that social bonds can have a strong effect on well-being through social support, but this effect can be
either positive or negative.
Social Relationships, Goals, and the Self
As noted above, social support contributes to subjective well-being by buffering against stress
(Cohen & Wills, 1985). However, social support has also been found to be associated with subject wellbeing
in the absence of threats (Lakey & Orehek, 2011). One reason for this appears to be the importance
of support from social partners for the pursuit of personal goals and for continued shaping of the selfconcept.
In this section we describe research focused on how social partners contribute to goal pursuit and
the self-concept as two mechanisms through which social others contribute to well-being. We then turn to a
third mechanism, how individuals incorporate their social partners’ well-being into their own goal pursuit.
Social partners’ support for personal goals. Recent research has suggested that support for
personal growth, exploration, and goal striving by one’s romantic partner is another mechanism by which
social relationships influence subjective well-being. For example, Overall, Fletcher, and Simpson (2010)
found that greater romantic partner support lead to greater self-improvement and relationship satisfaction
over the course of a year, whereas those who had less supportive partners had worse self-improvement and
relationship satisfaction. Molden and colleagues (2009) demonstrated that perceptions that one’s personal
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goals are supported by a romantic partner are associated with subjective and relational well-being. These
results are further supported by a recent meta-analysis of goal progress and subjective well-being,
demonstrating that successful progress towards one’s goals is robustly associated with subjective wellbeing
(Klug & Maier, 2015).
Although there is evidence that social support for goal pursuit is important, the conditions and ways
in which such support functions still require elaboration. One theoretical perspective that endeavors to
explore this function of support is Feeney and Collins’ (2015) model of thriving through relationships. This
theoretical model proposes that support for the pursuit of personal goals and challenges is one pathway
through which social support can help individuals thrive. Thriving is defined by the presence of five
components of overall well-being; eudaimonic well-being, subjective well-being, social well-being,
psychological well-being, and physical well-being. This type of support, that which aids recipients in their
pursuit of challenges and personal goals, is called relational catalyst support because it may serve as a
catalyst for personal growth and thriving (Feeney & Collins, 2015, Feeney, Van Vleet, Jakubiak, &
Tomlinson, 2017).
Relational catalyst support is rooted in attachment theory, specifically exploration and the caregiver
function of a secure base (Feeney & Collins, 2015). The innate motive to explore one’s environment is
interwoven with a desire for security and the minimization of risk. One function of caregiving is to provide
a secure base to recipients from which they can venture forth and explore, secure in the knowledge that aid
is available if difficulties are encountered (Bowlby, 1982, 1988). In providing a secure base, the recipient’s
needs are met through the knowledge that support will be available if needed. This notion of a secure base
is expanded upon in relational catalyst support by changing the role of the support provider from largely
passive to active. Relational catalyst support is provided when the caregiver actively encourages and
facilitates the pursuit of challenges and opportunities that the recipient has expressed interest in or have
been presented in the environment (Feeney & Collins, 2015, Tomlinson, Feeney, & Van Vleet, 2016). This
form of support enables participants to accept greater risks and to embrace opportunities and challenges
that they might not otherwise pursue. Feeney and Collins (2015) propose that this pursuit of personal goals
and opportunities leads to immediate outcomes relevant to personal and relational well-being, which in turn
influences long-term well-being and thriving.
While research on relational catalyst support is quite recent, preliminary evidence has been
provided for the immediate and long-term benefits of receiving this form of support. Tomlinson, Feeney,
and Van Vleet (2016) found that married individuals who were provided greater relational catalyst support
in a laboratory setting by their partners possessed greater immediate perceived capability than those whose
partners did not provide relational catalyst support. One year later, those provided such support had greater
self-esteem, reported more goal progress, and greater self-growth than those who weren’t. Similarly,
Feeney, Van Vleet, Jakubiak, and Tomlinson (2017) found that married couples were more likely to accept
a challenging opportunity in a controlled setting when one partner provided relational catalyst support. The
married couples that chose the challenging opportunity reported greater eudaimonic, subjective,
psychological, and relational well-being six months later than those couples that declined the opportunity.
While both studies are observational, they do provide evidence for the importance of relational catalyst
support for immediate and long-term outcomes that are relevant to well-being.
Secure base support (a component of relational catalyst support) functions similarly in regards to
well-being. Observational studies of romantic couples have found that those who receive greater secure
base support have better immediate outcomes such as greater self-esteem and positive mood (Feeney,
2004, Feeney & Thrush, 2010) than those who receive less support. Goal directed behaviors such as greater
perception that one is likely to achieve one’s goals (Feeney, 2004) and better performance and persistence
on a laboratory task (Feeney & Thrush, 2010) have also been associated with secure base support. In
addition, daily diary studies conducted by Jakubiak and Feeney (2016) found that daily spousal secure base
support predicted both same day and next day goal progress as well as psychological, physical, and
relational well-being. Subsequent mediational analyses found that goal progress indirectly mediated the
relationship between spousal support and the different types of well-being.
While the majority of this research does not allow for causal inferences, Feeney (2004) has
experimentally manipulated the provision of secure base support. An experimental study was conducted in
which participants believed they were chatting online with their partner while performing a fun and
challenging puzzle activity. Participants either received intrusive and controlling messages, intrusive and
supportive messages, nonintrusive and supportive messages, or no messages at all that were sent by the
experimenter posing as the participant’s romantic partner. Those in the nonintrusive and supportive
condition found the messages significantly less frustrating and insensitive and perceived their partner as
less intrusive and interfering than those in the two intrusive conditions. In turn, those who felt more
supported by their partner (measured by a composite of perceptions of the partners messages and
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perceptions of the partner) experienced greater self-esteem and positive affect.
It is important to note that relational catalyst support is only effective when it is responsive to one’s
partner (Feeney & Collins, 2015). When the support provided is intrusive, it disrupts exploration and is
associated with negative outcomes in children (Ainsworth, Bell, & Stanton, 1974) and attachment
insecurity in adults (Feeney & Collins, 2001). Indeed, Feeney (2004) found that participants in the intrusive
and supportive condition perceived their partner as less supportive overall, reacted with greater hostility and
rejection, and had lower self-esteem and positive mood than participants in the nonintrusive conditions.
This is consistent with findings by Feeney and Thrush (2010), who observed that more intrusive support
from spouses was associated with worse performance and less persistence on a task as well as lower self-
esteem.
The current evidence suggests that relational catalyst support acts as a mechanism through which
close relationships influence well-being. Relational catalyst support has been shown to facilitate goal
striving, exploration, and the pursuit of challenges (Feeney, 2004, Feeney & Thrush, 2010, Feeney, Van
Vleet, Jakubiak, & Tomlinson, 2017, Tomlinson, Feeney, & Van Vleet, 2016) which, in turn, facilitate
subjective well-being (Klug & Maier, 2015). Furthermore, provision of relational catalyst support is
connected to immediate outcomes such as self-esteem and positive mood, both of which are relevant to
overall well-being (Feeney, 2004, Feeney & Thrush, 2010, Tomlinson, Feeney, & Van Vleet, 2016). Future
research should continue to examine long-term outcomes and overall well-being while performing
experimental work that can establish causality between this type of support and well-being.
Social partners’ influence on the self-concept. Social relationships can also influence well-being
through changes to one’s self-concept independent of their influence on goal strivings. Self-expansion
theory argues that people are motivated to continually expand the self to increase perspectives and
resources (e.g., Aron, Aron, Tudor, & Nelson, 1991). Self-expansion in relationships, refers to the process
of including a close other in one’s conception of the self and includes taking in a close other’s “resources,
perspectives and characteristics” as part of the self-concept (Aron et al., 1991, p. 243). The theory of selfexpansion
is supported by empirical evidence such that in close relationships, mental models of the self and
other are seem to overlap with one other. Moreover, the closer the relationship, the greater this degree of
overlap. With increasing closeness, a social partner’s personal qualities and resources can become less
distinguishable from the personal qualities and resources of the self.
Importantly, the theory states that the act of self-expansion is, in itself, rewarding and creates positive
emotions. Experimental studies have demonstrated that creating opportunities for self-expansion in the lab
by having couples participate in a novel and physiologically arousing task together leads to increases in
positive affect and satisfaction (Aron et al., 2000). Aron and colleagues have argued that there is a
naturally occurring rapid expansion of the self at the beginning of relationships, which at least partially
accounts for the intense positive emotions experienced when falling in love (Aron et al., 1991).
The self-expansion process is a basic interpersonal process and seems to occur even among looser
social ties. For example, Fraley and Aron (2004) found that closeness between strangers was increased
through a shared humorous experience. On the other side of the coin, other work has shown the that selfexpansion
processes also can work in the reverse temporal order. Specifically, Slotter and Gardner (2009)
found that when people are motivated to be close to another they can employ self-expansion. That is, when
people desire social connection with another person, they integrate aspects of the other person into their
own self-concept. This type of strategic self-expansion may be more weakly tied to well-being.
Another line process through which relationships can contribute to the self-concept is through what
has been called The Michelangelo Phenomenon (e.g., Drigotas, Rusbult, Weiselquist, & Whitton, 1999,
Drigotas, 2002; Rusbult, Kumashiro, Kubacka, & Finkel, 2009). This work has shown that social partners
are also active participants in each other's personal development. That is, social partners can promote (or
hinder) one’s pursuit of the ideal self. The ideal self can be an explicit, clearly defined set of goals, or a
more vague set of dreams or aspirations. Empirical work on Michelangelo Phenomenon has found evidence
that partners help (or hinder) the growth toward the ideal self though partner affirmations. That is, partners
who see their partners as already possessing the attributes of their ideal self and treat their partners as if
they are (already) that ideal self, actually can elicit aspects of the ideal self from the partner through these
interactions (Rusbult et al., 2009). Partner affirmations are associated with the partner feeling more similar
to his or her ideal self and higher personal well-being and relationship quality (Drigotas, 2002; Drigotas, et
al., 1999; Rusbult, et al., 2009).
Individuals’ goals toward social partners. The types of goals that individuals choose, in regards to
their social relationships, serve as mechanisms that influence relationship quality, relational well-being,
personal outcomes, and ultimately, subjective well-being. Research by Crocker and Canevello (2008) has
examined two types of interpersonal goals, compassionate goals and self-image goals, that reflect distinct
558
perspectives and systems of motivation. Compassionate goals are supportive of others and are motivated
by concern for the well-being of others, while self-image goals focus on constructing and maintaining
desirable public and private images of the self and are motivated out of a concern for one’s own needs and
desires (Crocker & Canevello, 2008, 2012, Canevello & Crocker, 2015). Compassionate goals reflect an
ecosystem perspective of relationships in which the self is connected to others, the well-being of the self
and others is viewed equally, and others care about one’s well-being (Canevello & Crocker, 2015). This
perspective supports the ideas that actions towards others will harm or aid the self because of the
interconnected nature of relationships and that cooperation with others can lead to the fulfillment of one’s
needs (Crocker & Canevello, 2008, Crocker & Canevello, 2015). In contrast, self-image goals reflect an
egosystem perspective in which others cannot be trusted to help fulfill one’s needs and that others do not
care about their well-being (Crocker & Canevello, 2012). In the egosystem, individuals view relationships
as zero-sum affairs in which they can only gain benefits if others pay costs and others are only considered
in terms of how they might help meet one’s own needs and desires (Crocker & Canevello, 2008, Crocker,
Canevello, & Lewis, 2017, Canevello & Crocker, 2015).
Compassionate and self-image goals lead to patterns of behavior that reflect these underlying
systems of motivation. Those pursuing self-image goals attempt to use tactics such as persuasion,
ingratiation, manipulation, and intimidation to control others in order to gain benefits for themselves
(Crocker & Canevello, 2015) and to maintain their desirable public image to help in the pursuit of further
benefits (Canevello & Crocker, 2015, Crocker & Canevello, 2012). Those pursuing compassionate goals
show greater consideration of others needs in their decision making, are more constructive in how they
address relationship problems (Canevello, Crocker, Lewis, & Hartsell, 2014), and are more supportive
(Crocker & Canevello, 2008) and responsive (Canevello & Crocker, 2011a) to others.
These behaviors associated with compassionate and self-image goals lead to distinct relational and
personal outcomes. Crocker and Canevello (2008) found that greater support provision by those who adopt
compassionate goals leads to greater perceptions of perceived support from family, friends, and romantic
partners as well as the receiving of more support from roommates. Those with self-image goals provided
less support and, in turn, received and perceived less support from others. The greater responsiveness of
individuals with compassionate goals has similarly been found to predict responsiveness from others
(Canevello & Crocker, 2010, 2011a). In turn, the responsiveness of close others has been found to predict
greater self-esteem (Canevello & Crocker, 2011a) and greater relationship quality (Canevello & Crocker,
2010). Those who have self-image goals are less responsive to others and others were less responsive to
them in turn, leading to lower relationship quality and lower self-esteem. Furthermore, those with
compassionate goals have greater relationship growth belief (Canevello & Crocker, 2011b) and
relationship security (Canevello, Granillo, & Crocker, 2013), whereas those with self-image goals show
greater relationship insecurity.
The associations between compassionate and self-image goals and interpersonal outcomes are
consistent with findings that the quality of close relationships is highly relevant for subjective well-being
(Diener & Seligman, 2002). This research elaborates upon how compassionate goals serve as a mechanism
within relationships by which relevant interpersonal and personal outcomes can be improved (Crocker &
Canevello, 2008, Canevello & Crocker, 2011a), but also reveal how, in the case of self-image goals,
relationships can lead to worse relationships and overall well-being (Canevello & Crocker, 2011a,
Canevello & Crocker, 2010). Future research should endeavor to make explicit connections between this
past research and subjective well-being.
Social Relationships Provide Rewards
The final set of mechanisms we consider here are how social relationship partners provide rewards
above and beyond the mitigation of threats and contributions to goal pursuit and the self-concept.
Specifically, social relationships often provide the context in which people experience positive emotions.
Social partners can create, maintain, or increase positive affective states in others (conversely they can
thwart them). Positive affective states are part and parcel to well-being and the degree to which
relationships enhance or decrease positive emotions likely contributes a great deal to well-being (e.g.,
Fredrickson, 1998). We consider two specific positive emotions that an interpersonal in nature, love and
gratitude, and then a process through which social partners enhance positive emotions that occur outside of
the interpersonal relationship called capitalization.
Love. Love has been the topic of poems, songs, and plays for as long as there have been poems,
songs, and plays. Theorists such as John Bowlby (1969) proposed that love and attachment bonds were
part of the mind’s architecture and critical to human development, and contemporary psychologists are
trying to understand the biological systems involved in the experience of love (e.g., Bartels & Zeki, 2004).
Empirical research has identified and focused on two kinds of love: passionate love and companionate love
559
(e.g., Sprecher & Regan, 1998). Passionate love is the feeling of excitement for and attraction towards
someone else. Companionate love is the warmth and liking we feel for someone else. Feelings of love of
both kinds are closely tied to the reward system. For example, brain activity in areas associated with the
reward motivation is higher when people are cured with photos of people for whom they feel passionate
love (Aron et al., 2005). Communal relationships, which are social bonds characterized by mutual
expectations that each will respond to the other’s needs are closely entail companionate love (Clark &
Mills, 2013). Love in both forms is an emotional state that is experienced as positive and rewarding and by
definition occurs in the context of social bonds.
Gratitude. Feelings of gratitude enhance well-being (for review see Emmons & Mishra, 2011).
Algoe (2012) has proposed that gratitude is fundamentally a social emotion and describes the “Find,
remind, and bind” model of gratitude in which gratitude has social functions. Specifically, gratitude
promotes relationship formation and maintenance by signaling which people would make good social
partners and then reminding us of their generosity and promoting behaviors that facilitate bonding and
intimacy (Algoe, 2012). The empirical support for this model supports the premise that gratitude is
experienced frequently in the context of social bonds (e.g., Algoe, Gable, & Maisel, 2010). The empirical
evidence also supports the notion that the emotion of gratitude functions to find, remind, and bind others
closer to us. For example, Algoe and Haidt (2009) found that participants who were assigned to recall
events that evoked feelings of gratitude were more likely to report that they noticed new positive qualities
about the person to whom they felt grateful (i.e., find/remind) and that they wanted to spend more time with
that person (i.e., bind) in the future than those who recalled events that evoked happiness (but not gratitude)
with another person. Thus there is good evidence that gratitude occurs in social bonds (and helps maintain
bonds) and gratitude is associated with well-being. However, what is not yet clear is whether it is gratitude
per se that contributes to well-being or whether gratitude’s contribution to the quality of social bonds
influences well-being.
Capitalization. It is obvious that almost by definition, when good things happen people experience
positive emotions. What may not be as obvious is that people often respond to positive events by telling
someone else about the event, a process called capitalization (Langston, 1994). Early research on
capitalization (Gable, et al., 2004) found that people experience benefits beyond the original positive event,
such as increased daily positive affect and daily well-being, when they talk about those events with other
people. The empirical data also make it clear that when people capitalize they do so with those with whom
they have existing close social bonds, not strangers. (Gable et al., 2004). Moreover, similar to the work
reviewed above on social support, the response of the person with whom the event is shared influences
well-being.
There are four prototypical responses to capitalization attempts: active–constructive responses,
passive–constructive responses, active–destructive responses, and passive–destructive responses (Gable et
al., 2004/2006). Active-constructive responses entail excitement and enthusiasm for event and interest in
the interaction. Passive-constructive response are pleasant but show restrained interest in the interaction. An
active-destructive response is one that conveys interest in the interaction but is mainly negative in terms of
diminishing the positive event. A passive-destructive response fails to acknowledge the positive event
disclosed often by steering the conversation to something else.
When disclosers receive active-constructive and not passive or destructive responses to capitalization
attempts, they gain additional positive personal outcomes such as positive affect, well-being, and a sense
of connection to others (Gable, et al., 2012). The data also indicate that that active constructive responses
signal understanding and caring and thereby have the additional benefit of strengthening the social bond
with the responder (e.g., Maisel & Gable, 2009). Passive or destructive responses on the other hand are
associated with reduced relationships quality and lower well-being. The process of capitalization is a
common occurrence in social relationships and thus is mechanism that is strongly associated with well-
being.
Gaps in the Literature and Future Directions
One promising pathway through which close relationships may also influence subjective well-being
is through facilitating a sense of meaning and purpose in life. Research over the past decade has shown that
social relationships are positively correlated with the experience of meaning in life (Krause, 2007, Steger,
Kashdan, Sullivan, & Lorentz, 2008, Hicks & King, 2009). Experimentally induced social ostracism has
also been found to decrease meaning in life (Zadro, Williams, & Richardson, 2004, Stillman, et al. 2009).
Self-reports also lend support for the importance of relationships for meaning in life, as demonstrated in a
study by Lambert and colleagues (2010) in which participants ranked family as the top source of meaning
in their lives. Closeness to one’s family was further found to predict a greater sense of meaning in life.
While the evidence for a connection between social relationships and meaning in life is considerable
560
(Hicks & King, 2009, King, Heintzelman, & Ward, 2016), the exact nature of that connection and the
mechanisms by which it acts are currently unknown. Future research should aim to uncover how specific
relationship processes, such as those associated with personal growth (Drigotas, et al., 1999, Aron, Aron, &
Smollan, 1992), may relate to perceived meaning in life.
Another area we see as ripe for future research is interpersonal emotion regulation more broadly.
We already reviewed work suggesting that social partners can reduce negative affect after its onset
following a negative event (i.e., social support) and increase positive affect even further after a positive
event (i.e., capitalization). However, work on intrapersonal emotion regulation suggests that there are
likely many other routes for interpersonal emotion regulation. Specifically, Gross (1998) has outlined
several different strategies employed by individuals that range from the selection of situations that have a
high probability of eliciting certain emotions (e.g., going to an amusement park for excitement) to the
suppression of the outward signals of an emotion once it is experienced (e.g., smiling while receiving
hurtful criticism). Gross’s model of emotion regulation separates emotion regulation strategies that are
focused on the antecedents of an emotional experience—situation selection, situation modification,
attentional deployment, cognitive change—from the strategies employed in response to the experience of
the emotion—experiential modulation, behavior change, physiological modulation (Gross, 1998). To date,
the vast majority of work in this area has focused on what individuals do personally to regulate their own
emotions. Given the commonness of social support and capitalization, there are great reasons to suspect
that social partners engage in many of these strategies to influence others’ emotions (with or without a
target’s awareness) as well. Research aimed at more fully understanding these processes will provide a
clearer picture of how close others contribute to well-being through emotion regulation.
Conclusions
We began this chapter with asking whether people can thrive without social bonds. The answer
seems to be not only can they not thrive without interpersonal relationships, they cannot survive without
interpersonal relationships. After all, historically the punishment reserved for the worst offenders in a
prison has been solitary confinement. However, pathways through which social bonds have an impact on
well-being may not be as obvious. Three general pathways were identified; buffering the impact of
negative situations, contributions to intrapersonal goals and the self-concept, and increasing the experience
of positive emotions. Through these processes, and likely additional processes, social relationships have
great potential for increasing or decreasing individual well-being.
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Social Capital and Prosocial Behaviour as Sources of Well-Being
By John F. Helliwell, University of British Columbia; Lara B. Aknin, Simon Fraser University; Hugh
Shiplett, University of British Columbia; Haifang Huang, University of Alberta; & Shun Wang, KDI
School of Public Policy and Management
Citation
Helliwell, J. F., Aknin, L. B., Shiplett, H., Huang, H., & Wang, S. (2018). Social capital and prosocial
behavior as sources of well-being. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt
Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
This chapter surveys evidence documenting positive linkages among social capital, prosocial behaviour,
and subjective well-being. Whether in the workplace, at home, in the community, or among nations, better
and deeper social connections, and especially higher levels of trust are linked to higher subjective wellbeing,
even beyond the effects flowing through higher incomes and better health. Prosocial behaviour is
also shown to be a robust predictor of well-being in both correlational and experimental contexts. These two
lines of research are connected, as prosocial acts are most likely to increase well-being when they are
delivered in ways that improve social capital, and reflect intentional generosity free of either compulsion or
personal gain. We infer that these deep links between prosocial acts and well-being have an evolutionary
benefit in maintaining the quality of social capital and thereby delivering cooperative human responses in
times of crisis.
Keywords: Social capital, Prosocial behavior, Happiness, Well-being
Humans are extremely social creatures, spending much of their lives in the company of others.
Indeed, social connections are one of the greatest sources of human well-being (Diener & Seligman, 2002;
Lyubomirsky, Sheldon & Schkade, 2005) and, as such, this chapter surveys a range of studies showing
positive linkages running from social connections, trust, and prosocial behaviour to higher subjective wellbeing.
Although the magnitude of these effects can, at times, be difficult to establish because happier
individuals are more likely to make friends, marry, and help others, this type of positive feedback loop is
desirable for human welfare because it amplifies the well-being consequences of positive interventions.
The reported results are primarily based on research in which we have been involved, but also set within a
broader range of related studies.
That humans should gain happiness from social and prosocial behaviour has been doubted by some
who think that evolutionary fitness requires a sharper sense of self-interest than is implied by the evidence
we survey. To resolve these doubts requires an evolutionary theory that provides greater evolutionary
fitness for individuals, groups and societies that adopt and prefer prosocial behaviour. Humans are
generally more social and co-operative than other mammals and their own ancestors. Such exceptional
levels of social and prosocial tendencies have been linked to rapid growth of the pre-frontal cortex, the size
of which has been matched to the capacity and willingness to adopt social and prosocial behaviour (Shultz
& Dunbar, 2007). The ‘social brain hypothesis’ (Adolphs, 2009; Dunbar, 1998) suggests that across
mammalian species, and especially among anthropoid species, pre-frontal cortex size is linked both to
social group size and pair-bonding, both of which are argued or presumed to require the evaluative powers
conferred by the larger neo-cortex. One evolutionary puzzle is that the neo-cortex (the ‘slow brain’;
Kahneman, 2011) requires more energy than the more instinctive ‘fast brain’. Thus planning for the long
term, with the required intelligent attention to the interests of others, uses more energy, placing survival at
risk when times are tough.
It is precisely at this point where we see an evolutionary role for social connections and prosocial
actions. Social and prosocial activities provide psychological benefits, evidenced by positive emotions and
higher life evaluations, beyond those directly attributed to the material rewards they enable. These
additional psychological rewards help to sustain their energy costs, and hence favour the survival of
societies that can combine high trust and benevolence even in the face of scarce resources and prevalent
risks. Social connections can come in many forms, of course, but we focus primarily on social capital,
which is defined by the OECD as “social networks, together with shared norms, values and understandings
that facilitate cooperation within and among groups” (OECD, 2001, p.41).
In the review that follows we summarize the existing evidence for social capital and prosocial
behaviour as sources of well-being. We divide our review of the evidence as follows. First, we provide
examples of the well-being benefits of social capital at work and at home, followed by discussion of results
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at the community, regional, and national levels. Second, we turn to the specific areas of health, the
provision of public services, and the special role of trust. Finally, we conclude with a brief review of the
burgeoning literature, based on both survey and experimental evidence, of the emotional benefits of
prosocial behaviour.
Social Capital at the Individual Level of Analysis
At work. Many people spend a large portion of their waking hours at work (Schor, 2008),
suggesting that social connections in the workplace may be an important predictor of well-being. And they
are. Canadian data has shown that to work where trust in management is one point higher on a ten-point
scale has an effect on life satisfaction equal to that from a one-third increase in household income
(Helliwell & Huang, 2011). Workplace social capital seems to be more important for women than men;
women attach more value to trust in management and less to income than do male employees (Fortin, 2008;
Helliwell & Huang, 2009). These differences combine to make the income-equivalent value of workplace
trust in Canada twice as high for women as for men. The Gallup-Healthways Daily Poll in the United
States shows that happiness reports differ by day of week, while evaluative questions about life as a whole
do not. For most workers, weekends and holidays are significantly happier than weekdays. However, for
workers who think of their immediate superior as a partner rather than a boss, and who report a high level
of workplace trust, the weekend effects are very small, falling to zero for those who manage to achieve the
same number of social hours on weekdays and weekends (Helliwell & Wang, 2014; 2015).
The impact of social connections in the workplace may even help explain large age-related
differences in life satisfaction. While life evaluations typically follow a U-shaped curve, peaking in one’s
20s and 60s and dropping in between, employees who regard their superior as a partner show no such dip
in middle age in the Gallup Healthways Daily Poll. Figure 1 shows that for workers of all ages the quality
of social capital on the job, as measured simply by how one’s immediate supervisor is perceived, has a
large and highly significant relation to life satisfaction. For workers under 30, the effect is about 0.2 points
on the 10-point scale, rising to 0.4 points for older workers. Note that for workers in high social capital
workplaces, with partner-like supervisors, the middle-age drop in life evaluations is absent, with average
ladder scores being the same for those aged between 45 and 54 as they are for workers under the age of 30.
Figure 1. Average life satisfaction reported by individuals seeing their immediate supervisor as a
boss, as a partner, and combined for ages <30, 45-54, and >65. Error bars depict 95% confidence
intervals.
At home. Relationships with family and friends are among the most powerful correlates of
happiness all over the world. Answering “yes” to the question ‘If you were in trouble, do you have relatives
or friends you can count on to help you whenever you need them, or not?’ is the single most important
variable explaining differences in life satisfaction among individuals from more than 100 countries
(Helliwell, Huang & Harris, 2009). To have that basic amount of social capital in the form of family and
friends has, for a sample of 68,000 observations from the first three waves of the Gallup World Poll, the
same value as a five-fold increase in household income (Helliwell et al, 2009).1 That is an average across
the globe. When the same relationship was fitted for each country separately, having someone to count on
was strongly significant in every global region, and almost every country (Helliwell et al., 2009).
Similar findings emerge on more detailed measures of social capital assessing the size of and
reliance upon one’s social networks. Indeed, individuals with larger and more widely used networks
provide more positive life evaluations. Interestingly, however, the beneficial impact of large social
568
networks may be limited to in-person friendships. Few surveys ask respondents parallel questions about the
sizes of their networks of real and on-line friends, but one survey that has done so found that life
satisfaction increases with the size of the network of face-to-face friends, but not with the existence and
size of their networks of on-line friends, even in a large sample of on-line respondents (Helliwell & Huang,
2013).
The relationship between marital status and subjective well-being has been widely studied. Crosssectional
correlations between marriage and life satisfaction in western nations are almost uniformly
positive. To some extent these correlations are likely due to selection effects, because individuals in good
circumstances, or with genetic makeup favouring happiness, may also be more likely to find and attract
marriage partners (De Neve, Diener, Tay, & Xuereb, 2013; Stutzer & Frey, 2006). Studies using individual
fixed effects in longitudinal datasets have been used to avoid this risk, and have sometimes shown
happiness after marriage to revert to baseline levels within a few years (Clark & Georgellis, 2013, Lucas,
2007; Lucas, Clark, Georgellis, & Diener, 2003). But subsequent research has shown that, when due
account is taken of a happiness U-shape that is deeper for the unmarried than the married (Anusic, Yap &
Lucas, 2014a; 2014b; Yap, Anusic, & Lucas, 2012), marriage can protect against the midlife blues. It is
also important to compare happiness within marriage to that of a period sufficiently far in advance of the
marriage to remove the pre-marital happiness boost (Zimmerman & Easterlin, 2006) from the baseline.
These adjustments fully restore the positive well-being effects of marriage, at least for those industrial
countries with longitudinal surveys suitable for such analysis. The positive impact of marriage on wellbeing
also depends on the comparison group, since alternatives are quite diverse, including those who are
separated, divorced, widowed, single, and or living as a cohabitating couple. The last category is
substantial and growing in many western countries, and non-existent in some other cultures. Where it is
prevalent, non-married but cohabitating couples rate their well-being only slightly below that of married
individuals, suggesting that the happiness benefits of marriage may be due to its provision of social capital
more than to its legal structure.
Looking across world regions, the value placed on marriage as an institution differs considerably,
and so do its correlations with life evaluations. When the data from the Gallup World Poll (GWP) are
divided into the 10 global regions used in the World Happiness Report series, separate estimation using
individual-level cross-sections for each global region shows significant positive effects of marriage
(relative to all other alternatives) in most regions, with notable exceptions: the effects are significantly
negative in Latin America and Sub-Saharan Africa, while there are no significant correlations in South and
South-East Asia (Grover & Helliwell, 2014). This diverse relationship between marriage and life
satisfaction deviates from what is found for the effects of having family or friends to count on in times of
trouble, which are strongly positive in all global regions. We hypothesize that cross-cultural differences in
the role of marriage as a social institution are at least partly responsible for the diversity of results. If so,
then we would expect to find that the well-being effects of marriage are greater in circumstances where
marriage contributes to the quality of an individual’s social capital. This possibility is supported by results
from a UK survey where respondents were asked to locate their best friend from a number of categories,
including “spouse” as an option. The results show that although marriage and friends are both important
sources of subjective well-being, the effects of marriage on life evaluations are twice as large for those who
also regard their spouse as their best friend (Grover & Helliwell, 2014).
Social Capital at the Community Level of Analysis
The interpersonal relationships that form the basis of an individual’s social connections exist within
the larger social context of neighbourhoods, cities, regions and nations. Here, we review how the quality of
social connections at the community level affect subjective well-being. This is sometimes done by
comparing average well-being for communities and nations, both across communities and over time, and
sometimes by two-level modelling that attempts to separate the individual-level and contextual effects that
are lumped together when the analysis is done using aggregated data.
Comparison effects - “keeping up with the Joneses”- are generally believed to generate negative
spillovers which undermine the well-being effects of income (Easterlin, 1974, 1995; Kingdon & Knight,
2007; Luttmer, 2005; Stevenson & Wolfers, 2008). By contrast, the inherently collective nature of social
capital can induce positive spillovers, thereby increasing the benefits to local and national communities
(Helliwell & Putnam, 2004). Indeed, the effects of social trust on life satisfaction at the national level have
sometimes been found to be more pronounced in wealthier countries (Bjørnskov, 2003; Ram, 2010).
Nonetheless, positive aggregate effects of various forms of social capital have been found throughout the
international income distribution (Delhey & Dragolov, 2016), as well as within countries over time
(Bjørnskov, 2008; Helliwell, Huang, & Wang, 2014; 2017).
The role of social capital in explaining aggregate well-being at the national level is also substantial
569
and extends well beyond its effects on health and economic outcomes. In a study of 158 countries sampled
by the Gallup World Poll, Helliwell, Huang, and Wang (2015) found that measures of social support and
generosity collectively explain 37% of the variation in national average life evaluations after controlling for
GDP per capita, healthy life expectancy, and perceptions of freedom and corruption. Using data from the
GWP, European Social Survey (ESS), and World Values Survey (WVS) to estimate wealth-equivalent
values of social capital, Hamilton, Helliwell, and Woolcock (2016) estimate that social capital, as measured
by trust, comprises approximately 20% of total national wealth. Across regions, estimates range from as
low as 12% for Latin American countries, to as high as 28%, for OECD countries.
In the important case of social trust and other self-report assessments of social capital, the validity of
these international results requires that measured social capital reflect the quality of the underlying social
fabric, rather than cultural biases in reporting. Providing some direct evidence for the former, Knack (2001)
finds that average answers to the standard trust question across 14 European and 12 US cities in the WVS
were highly correlated with the actual probability of a stranger returning a wallet in the region in question.
Lending further support to this view, social trust among first-generation immigrants tends to reflect the
levels of natives in the host country more closely than stayers in the source country (Dinesen, 2012;
Helliwell, Wang, & Xu, 2016; see Dinesen & Sønderskov, 2017, for a recent review), suggesting that
levels of trust respond to the local context. The importance of the social context may also explain why new
immigrants to Canada report means and distributions of life satisfaction similar to those of Canadian-born
respondents (Helliwell, Bonikowska, & Shiplett, 2016). The smaller differences that remained could come
from cultural ‘footprint’ effects, or from differences in the social capital available to immigrants. In support
of the latter view, others have found that gaps between the life satisfaction of immigrants and natives in
developed countries can be explained by lower social support (De Vroome & Hooghe, 2014), by natives’
perceptions of immigrants (Hendriks & Bartram, 2016), and by immigrants’ own perceptions of
discrimination (Safi, 2010).
While international differences in social capital clearly play a large role in well-being, social capital
also accrues and influences well-being through more local channels. Investigating sub-national variation in
well-being can help to illuminate these channels while holding the national context fixed. Using the large
samples of life satisfaction available in the Canadian Community Health Survey and General Social
Survey, Shiplett, Helliwell, and Barrington-Leigh (2017) estimated levels of life satisfaction across more
than 1,200 Canadian communities. In the happiest dozen communities (the 99th percentile in the sample of
1,215 communities) average life satisfaction is above 8.5, compared to less than 7.5 in the dozen least
happy communities, a difference of 1.0 points on the 10-point scale. Comparing the happiest and leasthappy
communities in Figure 2, salient differences are apparent in residents’ reported sense of belonging to
the local community, a direct measure of the level of local social connectedness, as well as inequality in life
satisfaction (the within-community dispersion of life satisfaction, measured by the standard deviation of the
distribution of individual life satisfaction responses), and residential tenure2, both of which provide
plausible support for social capital.
Figure 2. Life satisfaction is higher in communities where more people feel a sense of belonging.
Multi-level models, in which measures of social capital are entered at both the individual and
regional levels, provide an opportunity to separate individual and contextual effects of social capital. Thus,
570
it is possible, for example, to separate the benefits of trusting others from those of living in a trusting
environment. Using this approach, Bjørnskov (2008) finds strong effects of social trust, formal sociability,
and informal sociability at the individual level, as well as contextual effects for social trust of a similar
magnitude to the individual effects in regressions of residuals at the state-level in cross-section and in a
region-level panel in the United States. Aslam and Corrado (2012) find similar regional benefits of general
and institutional trust for European regions, and Han, Kim, and Lee (2013) find local contextual effects for
organizational membership and social support at the local level in Seoul, South Korea. In the latter two
cases, the contextual effects were actually larger than the already substantial individual effects. Having
controlled for the potentially confounding effects of optimism through the individual responses, these
significant contextual effects also provide stronger support for a causal role of social capital, especially
through social trust.
When measuring contextual effects in a multi-level framework, results may be sensitive to the
geographic scale at which contextual variables are measured (Flowerdew, Geddes, & Green, 2001). If, for
example, the contextual effects of social connectedness operate primarily through the social context in local
neighbourhoods, a regression including individual and state-level measures of social connectedness may
show effects for both variables to the extent that they serve as two imperfect measures of the same
underlying, but omitted, neighbourhood characteristic, the first potentially imprecise but correctly scaled,
the second incorrectly scaled but more precisely measured. This type of scale effect may partially explain
why Bjørnskov (2008) and Aslam and Corrado (2012) do not find significant contextual effects for formal
or informal sociability measured at coarser geographic scales, while Han, Kim, and Lee (2013) do find
contextual effects for formal sociability in the form of organizational memberships measured at a much
finer level of geographic detail.
The evidence presented so far supports the positive effects of social capital on well-being, both
individually and collectively. But the benefits of living in a trusting and socially cohesive environment
extend even further. In addition to providing support to individuals facing adversity, as we have seen,
social capital provides a resource that can be tapped into collectively in times of need, supplementing or
even standing in for more formal institutions. Helliwell and Huang (2014) showed in a panel of US cities
that the contextual effect of aggregate unemployment was reduced by approximately one third in cities
where levels of broad engagement were one-standard deviation above average, compared to those where it
was one standard deviation below average. Furthermore, Helliwell, Huang and Wang (2014, 2015) argue
that the small effect of the 2008 financial crisis on life evaluations in hard-hit Ireland and Iceland3 when
compared to the large decreases observed in Spain, Italy, and Greece, can be explained by the exceptionally
high levels of social capital in the former.4
Communities with high social capital, particularly social trust, have also been documented to
recover more quickly from natural disasters, such as the Tokyo earthquake of 1923 (Aldrich, 2012) and the
2004 tsunami in southern India (Aldrich, 2011). Coping with natural disasters, which requires cooperation,
has been shown to be associated with subsequent increases in social trust (Toya & Skidmore, 2014), at least
when it is not initially too low (Dussaillant & Guzmán, 2014). For instance, Yamamura and colleagues
(2015) also show that following the Great East Japan Earthquake of 2011, the effect of trust on happiness
approximately quadrupled in areas that were damaged by the earthquake. This large change can be
accounted for both by the benefits of support during the disaster, but also by increases in trust, generosity,
and the value placed on social connections in the wake of the disaster (Uchida, Takahashi, & Kawahara,
2014; Yamamura, Tsutsui, Yamane, C., Yamane, S., & Powdthavee, 2015).
Social Capital and Health
The epidemiological literature mainly uses social capital at the individual and community levels to
explain the incidence of ill-health (Berkman & Glass, 2000; Berkman & Syme, 1979; Evans, Barer, &
Marmor, 1994; Kawachi & Berkman, 2000; Kawachi, Kennedy, Lochner, & Prothrow-Stith, 1997;
Marmot, 2005; Marmot, Ryff, Bumpass, Shipley, & Marks, 1997). For an example at the individual level,
experimental research demonstrates that individuals with robust social connections are less likely to be
affected by an experimentally delivered virus (Cohen, 2004; Cohen et al., 1997, 1998). A different line of
research emphasizes how building positive social identities helps people achieve better health status, or
speedier recovery times (Haslam et al., 2008; Haslam, Cruwys, Haslam, Dingle, & Chang, 2016). Yet
another branch shows how the quality of the social context shapes the effectiveness of different health
treatment strategies, ranging from the operating room to elder care. These latter studies are worth special
attention, partly because they have not previously been seen through the lens of social capital, and partly
because they provide a good link to the next section, where parallel evidence is considered for other
aspects of public service delivery.
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The operating room and elder care are two areas where growing demands and complexity are
leading to increasing pressures on budgets, hospital capacity, and the supply of trained professionals.
Gawande (2014) has shown that these stresses are linked, and that giving more attention to the well-being of
those receiving care would not only benefit patients, but would increase the well-being of providers as well.
To this end, the surgical checklist developed by Gawande and others (Gawande, 2010; Haynes et al., 2009)
for the World Health Organization has been widely adopted and credited with making significant
improvements in patient outcomes. The role of social capital becomes clear only when researchers analyze
how the guidelines are used, and where and why they are most effective. This emerging research has shown
that typical application of the checklist procedures may not be enough to significantly improve outcomes
(Urbach, Govindarajan, Saskin, Wilton, & Baxter, 2014). What may be most important are improvements
in team training (Neily et al., 2010), team involvement (Rydenfält, Johansson, Odenrick, Åkerman, &
Larsson, 2013; Walker, Reshamwalla & Wilson, 2012) and teamwork and communication in the operating
room (Russ et al., 2013). An important element in building teamwork and improving communications is the
timeout, where all members of the team drop their masks, introduce themselves, and discuss the case,
thereby achieving the closer connections and flatter structures shown earlier to add to the happiness of team
members and the quality of their work.
Gawande (2014) has also argued for the need to rethink elder care by paying more attention to the
quality of life of the elderly, their caregivers, and those playing both roles. Gerontologists have spelled out
the need for a revolution in elder care (Theurer et al., 2015) with a well-being focus. There is increasing
evidence that here, as in the operating room, providing people with social capital and prosocial
opportunities is a key ingredient to improving well-being. For example, experiments in an elder care
facility in Exeter, in the United Kingdom, showed that enabling residents to take even a small collaborative
role in designing their own future social spaces produced improvements in health and well-being greater
than those from facilities designed for them by professionals (Knight, Haslam, & Haslam, 2010). Tellingly,
these improvements were accompanied by more positive feelings about fellow residents and staff, as well
as more prosocial behavior. As such, providing elders with an opportunity to build social capital through
interaction in meaningful and helpful ways can yield important subjective well-being benefits.
Social Capital in the Provision of Public Services
In this brief section we look beyond the overall quantity and quality of public services to consider
the ways in which the services are designed and delivered. Indeed, if the social context matters in a firstorder
way for well-being, then we would expect both the sociality and prosociality of the design and
delivery of public services to have important consequences for well-being outcomes.
Much of the literature analyzing the quality of government, including trust in public services has
focused on the integrity and efficiency of the public services (Charron & Rothstein, 2016; Kaufman, Kraay,
& Mastruzzi, 2009; see Holmberg & Rothstein, 2011 for health outcomes), and on the effects of those
characteristics on the subjective well-being of the general population. A principal conclusion from this
literature is that well-being depends more on the quality of the services provided than on the funds devoted
to their provision. Whether the political process itself is democratic appears not to increase subjective wellbeing
unless or until the efficiency and integrity of service provision achieves certain levels (Helliwell &
Huang, 2008; Ott, 2010; see Helliwell, Huang, Grover, & Wang, 2014 for review).
We have already seen how flatter workplace structures (where supervisors are seen as partners
rather than bosses) are happier places to work. We shall also show later that people are more inclined to
generous acts, and happier to do them, where the beneficiaries are known and local. There is some parallel
evidence for the design and delivery of public services. For example, people have been found to have
higher life satisfaction in those Swiss cantons that rely more heavily on referenda, giving the citizens more
direct and immediate participation in government decisions (Frey, Benz, & Stutzer, 2004). It can also be
argued that the success of the Singapore prison reforms of 1998 was due in large measure to the efforts
made to involve all parties directly in the planning and delivery of services, thereby creating trust and new
social norms, permitting not just reductions in recidivism, but also better lives for inmates, employees,
families and the community at large (Helliwell, 2011). And a collaborative experimental effort to use
workplace training to deliver essential skills (Gyarmati et al., 2014) showed significant gains, especially in
higher trust environments, thereby showing the synergy between social capital and the delivery of more
effective public services.
Two more examples may help to show how social capital can be created almost anywhere, in ways
that improve the well-being of all parties. At least two music schools have partnered with elder-care
facilities to provide free accommodation for a small number of music school students, who then live,
practice, socialize and perform in the facility, thereby improving lives for all parties (The National, 2016,
Farooqui, 2017). To show that these experiments in co-living are not successful just because of the magic
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of music, co-housing of women soccer stars in an elder care facility was found to deliver better lives for the
athletes and their elderly housemates (Gutnick, 2013). What is needed to broaden the scope and prevalence
of such successes? First, it requires inspired commitment to see the opportunities and over-ride the
administrative and supposedly risk-avoiding hurdles that often stand in the way of mixing ages, skills, and
interests in untraditional ways. Second, the music school examples show the importance of success stories
being told, as the Canadian example (Farooqui, 2017) was inspired by a CBC story (The National, 2016)
on the earlier experiment in Cleveland. Although the co-living examples involve social experiments in the
field of elder-care, and thus could have been recounted in the health care section of the chapter, we include
them here to emphasize that opportunities for the creation of happiness-inducing social capital exist in all
institutions, communities and workplaces, whether public or private, large or small.
Trust and Well-Being
Trust is sometimes treated as a part of social capital and sometimes as independent but codetermined,
with causal arrows running from high trust to other forms of social capital, and from other
forms of social capital to high trust. We do not think there is any need to prefer one or the other of these
two definitional approaches, as long as the various types and dimensions of trust are distinguished, and
their links to well-being established. Analysts are slaves to what is measured, and that applies especially to
trust, where measurement is often absent or rudimentary.
The most long-standing measure of trust, often referred to as ‘social trust’, is based on answers to the
question “Do you think that other people can generally be trusted, or (alternatively) that you cannot be too
careful in dealing with people?’ Social trust, measured using this question, has been found to be highly
correlated with subjective well-being in previous studies (Helliwell, Huang, & Wang, 2014; Helliwell &
Wang, 2011). It has become and remains the canonical survey question on trust partly because of its longstanding
use (since Almond & Verba, 1963), and partly because, as we show below, it is a reasonable but
under-stated proxy for a wider range of more specific measures of trust.
Some large surveys have begun to include more detailed measures of the different dimensions of
trust. For example, the ESS (Huppert el al., 2009) asks a number of trust questions (unfortunately not yet
including the neighbourhood and the workplace) on a 0 to 10 response scale that provides a more
information-rich set of responses than are available from the binary response scale frequently used for the
social trust question. Using the ESS data, Helliwell, Huang and Wang (2017) recently found significant
individual-level partial correlations with life evaluations for five separate trust measures, even when they
were all simultaneously included. These included social trust, trust in police, trust in the legal system, trust
in parliament and trust in politicians. The two largest effects were for social trust and trust in police, with
each providing an effect larger than the sum of effects provided by the other three variables. Social trust, if
entered on its own, and hence standing in for the other forms of trust, attracts a significantly higher
coefficient than when entered in parallel, reflecting the ability of the general measure to capture some of the
missing measures. But it is not a complete substitute for the other measures, since social trust used on its
own delivers an estimated well-being effect that is only half as large as the combined effect of an
improvement in all five measures of trust, as shown in Figure 3.
Figure 3. Social trust captures only some of the well-being effects of trust. Estimated life satisfaction
effects from an increase of 1 point on ESS 10-point trust scale. Error bars depict 95% confidence
intervals.
Earlier sections have already shown how workplace and neighbourhood trust levels provide
additional subjective well-being above and beyond that due to their impacts on incomes5 and health. We
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also showed how high trust communities demonstrate more resilience in the face of natural and other
community-level shocks. In addition, individuals living in what they feel to be a high-trust environment are
more resilient to shocks that are specific to them (Helliwell, Huang, & Wang, 2017). By way of example,
ESS data allow this to be shown for three quite different unfortunate circumstances faced by individuals:
unemployment, ill-health, and feeling subject to discrimination. Figure 4 depicts three pairs of bars, each
showing the loss in SWB from one of three adversities- discrimination, ill-health and employment, with
two bars for each condition, one with and one without high social trust. Being subject to any one of these
circumstances is associated with significantly lower life evaluations. But the effects are smaller, by about
14% for unemployment, and up to 38% for discrimination, for those who rate the trustworthiness of others
at 7 or above on the 0 to 10 scale used for the ESS trust question.
Figure 4. Resilience is higher for individuals reporting higher levels of social trust.
Much of the preceding evidence is correlational, or makes use of natural experiments. There is also
an extensive literature (Ostrom, 2000) documenting the prevalence (but not universality) of prosocial and
trust-building behavior in the context of prisoner’s dilemma games and in the development of co-operative
solutions to common property management problems. Although the outcomes are typically not measured
directly in terms of subjective well-being, they include improved trust, better social norms, more effective
solutions for water-management, and other important collective action problems. Two features of this large
literature are especially relevant in the context of this chapter. First, face-to-face personal communications
have been repeatedly found (Balliet, 2010) to increase the probability of co-operative behavior in prisoner’s
dilemma games and resource management problems. Second, rules for cooperative management developed
internally by co-operating groups have been shown to be more efficient than are externally developed and
imposed rules, despite the greater enforceability of the latter (Bardhan, 2000; Frohlich & Oppenheimer,
1996; Cardenas, Stanlund & Willis, 2000). Both findings show how important it is for people to participate
in the design and improvement of the social norms and institutions governing their lives.
Both of these strands of experimental evidence show that social trust and co-operation can be
created and employed in ways that improve well-being. There are many policy areas where these lessons
can be applied – but they require more attention to the social context of decision-making, and the need to
build upon the innate human capacities for social and pro-social behaviour.
Generosity and Other Prosocial Behaviour
If humans are extremely social beings and meaningful connections with others are one of the most
reliable predictors of happiness (Diener & Seligman, 2002; Lyubomirsky et al., 2005), how do people
manage to create, maintain and strengthen social connections with other people? One way is by assisting
others through prosocial action. Indeed, engaging in acts of kindness and generosity can improve
connections with others and thereby promote the well-being of all parties, including the giver.
Consistent with this logic, a large and growing body of research demonstrates that giving leads to
greater well-being for the giver. For instance, data from nearly 30,000 people across 29 states in the United
States demonstrates that people who volunteer more frequently are both healthier and happier than those
who do not volunteer, even after controlling for well-known predictors of well-being, such as age, gender,
relationship status, education, and income (Borgonovi, 2008). This association between volunteerism and
happiness extends beyond the United States and has been documented in several countries around the
globe. Data from over 30,000 people in 12 countries indicates that individuals who have volunteered within
the last month reported higher life satisfaction and lower depression than those who did not volunteer
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(Haski-Leventhal, 2009). Beyond volunteerism, providing informal care or support to one’s spouse, family,
and friends yields benefits for the care provider. Indeed, in a sample of older married adults, Brown and
colleagues (2003) found that mortality rates were lower for individuals who provided instrumental support
to family, friends, and neighbours as well as emotional support to their spouse (also Schwartz & Sendor,
1999; Thomas, 2009). Interestingly, receiving support did not predict morality rates when support
provision was controlled for along with other demographic variables. Finally, using one’s financial
resources to help others, called prosocial spending, is associated with higher well-being as well. For
instance, individuals who donated money to charity reported higher levels of life satisfaction, in most
countries around the globe, than those who did not (Aknin, Barrington-Leigh et al., 2013).
Critically, the impact of prosociality on well-being is causal. For instance, Lyubomirsky and
colleagues (2005) found that participants randomly assigned to engage in five acts of kindness in a single
day weekly for six weeks reported higher subjective well-being relative to a control group who did not
engage in prosocial behavior. More recently, Nelson, Layous, Cole, and Lyubomirsky (2016) report that
participants randomly assigned to one of two prosocial conditions, completing kind acts for other people or
for the world, reported greater positive emotions and decreased negative emotions over a 6-week span than
individuals randomly assigned to do a nice thing for themselves or keep track of their daily activities.
Experimental evidence also demonstrates the benefits of support provision. Individuals randomly assigned
to hold their romantic partner’s hand while the partner received electric shocks displayed greater activation
in pleasure centers of the brain, such as the ventrial striatum and septal area, than individuals not able to
support their partners (Inagaki & Eisenberg, 2012). Finally, engaging in prosocial spending yields hedonic
rewards (Dunn, Aknin & Norton, 2008; 2014). For instance, when students were randomly assigned to
spend a windfall of either $5 or $20 on themselves or someone else by the end of the day, those who spent
the money on someone else were happier, regardless of the dollar amount (Dunn et al., 2008). Similar
experimental findings have been demonstrated in rich and poor countries (Aknin, Barrington-Leigh et al.,
2013), and in small-scale traditional villages (Aknin, Broesch, Hamlin & van de Vondervoort, 2015). Thus,
even though the prevalence of pro-social behavior has been shown to depend on genes (Kitayama et al.,
2014), culture (Bell, Richerson & McElreath, 2009), environmentally shaped differences in farming crops
(Talhelm et al., 2014) and interactions among them, the emotional rewards appear robust, emerging in a
variety of different cultural contexts. Even toddlers under the age of two smile more when giving away
edible treats than when receiving treats themselves (Aknin, Hamlin & Dunn, 2012).
When is prosociality most likely to promote well-being? Four key factors have been identified.
First, prosocial behavior yields the greatest emotional rewards when it facilitates social connection. For
instance, individuals randomly assigned to engage in prosocial spending were happiest at the end of the day
when their actions allowed for time spent with the recipient (Aknin, Dunn, Sandstrom & Norton, 2013). If
giving with social connection is more emotionally rewarding, this may help explain why people prefer to
support local causes and charities to which they have a personal connection (Small & Simonsohn, 2008).
Moreover, social connection may also explain why giving items that are closely tied to oneself, such as a
previously owned item or blood, leads to greater commitment and subsequent generosity than giving gifts
with minimized personal connection (Koo & Fischbach, 2016).
Prosocial action is also more likely to promote subjective well-being when generosity is motivated
by altruistic, as opposed to selfish, motives. Supporting this claim, correlational research reveals that
volunteering is associated with lower mortality risk in older adults, but only when volunteering is
motivated by other-oriented (as opposed to self-oriented) motives (Konrath, Fuhrel-Forbis, Lou, & Brown,
2012). Similarly, other-oriented motives reported by a sample of volunteer healthcare workers predicted
life satisfaction, but self-oriented motives did not (Veerasamy, Sambasivan & Kumar, 2015). Experimental
evidence points to similar conclusions. For instance, participants randomly assigned to recall a time they
engaged in helping behavior motivated by concern for others reported higher positive emotions than
participants assigned to recall a time they engaged in helping behavior to benefit themselves (Wiwad &
Aknin, under review). This may be why introducing opportunity for self-benefit undermines the emotional
rewards of giving. Indeed, Wang and Tong (2015) found that people report greater happiness after making
private (as opposed to public) donations, potentially because public donations are more likely to be
motivated by self-focused concerns.
Two final factors that make the benefits of giving more likely are volition and impact. When people
feel that their kind acts are compelled by others, giving does not translate into well-being benefits
(Weinstein & Ryan, 2010). This may be at least part of the reason why required volunteer work, such as
community service learning programs, have no detectable benefits on subjective well-being in experimental
tests (Whillans et al., 2016); making prosocial actions mandatory undermines an actor’s volition, which is
important for experiencing the emotional rewards of giving. Finally, feeling as if one has made a positive
impact on others also enhances the well-being benefits of giving. When donors know how their dollars will
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be used to help others, larger donations lead to greater well-being. Importantly, however, when information
about impact is absent, larger donations do not predict greater well-being (Aknin, Dunn, Whillans, Grant, &
Norton, 2013). This offers another, complementary explanation for why people prefer to give to local
charities – because they are more likely to see the impact of their gift and experience emotional rewards as
a result (Touré -Tillery & Fischbach, 2017).
The warm glow of giving not only offers an immediate reward for prosociality, but may prompt
subsequent generous action. Indeed, consistent with classic research demonstrating that positive affect
predicts helping behavior (Isen, 1970; Isen & Levin, 1972), more recent work has shown that positive affect
experienced after recalling a previous prosocial spending purchase predicts future generous spending
(Aknin, Dunn & Norton, 2011). To the extent that emotions serve to signal and promote adaptive behavior,
this positive feedback loop makes sense. Giving allows us to create and maintain meaningful relationships
with others. Since relationships are so essential to our survival and well-being, positive emotions serve to
make this prosocial action more likely in the future.
Concluding Summary
This chapter shows how the quality of the social fabric can affect subjective well-being. Whether in
the workplace, in the home, in the community, or among nations, tighter and more reliable social
connections are linked to happiness, whether measured by positive affect or higher life evaluations.
Governments were shown to enable higher life evaluations when they develop and deliver policies in ways
that build social capital in the process. Our review of prosocial acts showed them to be most effective at
increasing happiness, and therefore most likely to be repeated, in situations where social capital, as
measured by trust and shared social norms, is high. This synergy linking social capital, prosocial behaviour
and subjective well-being both underlies and supports our presumption that such a combination is likely to
be successful, even on an evolutionary time scale, wherever it is found.
Footnotes
1In Table 4 of Helliwell et al. (2009), the coefficient on the log of household income is 0.54, compared to
0.91 on the availability of family and friends. Hence the income multiple to offset the absence of helpful
family and friends is 5.4 (=exp(0.91/0.54)).
2While residential tenure has also been found to have a positive effect on subjective well-being by Shields,
Price, and Wooden (2009), at least for males, the aggregate effects may differ according to scale and
context. Talhelm and Oishi (2014), for example, find that rates of residential mobility are positively
associated with happiness in states with more extroverted populations, but negatively for states with more
introverted populations, suggesting that the balance between the benefits of variety and stability may
depend on the social context.
3See also Gudmundsdottir (2013) for an account of the well-being effects of the financial crisis in Iceland.
4Based on GWP data, Spain Italy and Greece ranked among the largest decreases in life evaluations from
2005-2007 to 2012-2014, while Iceland and Ireland rank at the top of the distribution in terms of the
proportion of individuals who reported having someone to count on in times of adversity.
5Evidence linking social trust with the levels and rates of growth of GDP is reported by, among others,
Algan & Cahuc (2010), Bjørnskov (2012), Helliwell & Putnam (1995), Knack & Keefer (1997) and Zak &
Knack (2001).
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Meaning and Well-Being
By Michael F. Steger, Colorado State University, Fort Collins; USA North-West University,
Vanderbijlpark, South Africa
Citation
Steger, M. F. (2018). Meaning and well-being. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of
well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
The topic of meaning in life is coming to the fore in well-being research. From an arcane existential idea to
a cornerstone of wellbeing, the path from obscurity to recognition was established through empirical
research. This chapter summarizes the development of theory and of measurement in meaning scholarship
over the past 70 years, and highlights replicated research results. Among the relationships that have been
found repeatedly in the literature are positive correlations between meaning and happiness, life satisfaction,
positive emotions, hope, self-esteem, autonomy, positive relationships with others, competence,
extraversion, conscientiousness, health, and longevity. Negative correlations have been replicated between
meaning and negative emotions, depression, anxiety, stress, hopelessness, neuroticism, substance use
problems, and suicidality. The body of evidence regarding meaning is large and growing quickly, and
appears to reliably demonstrate the importance of meaning to human wellbeing and flourishing
Keywords: Meaning, Meaning in Life, Purpose in Life, Well-Being, Meaningfulness
Conceive yourself, if possible, suddenly stripped of all the emotion with which your world now inspires
you, and try to imagine it as it exists, purely by itself, without your favorable or unfavorable, hopeful or
apprehensive comment… No one portion of the universe would then have importance beyond another; and
the whole collection of its things and series of its events would be without significance, character,
expression, or perspective. Whatever of value, interest, or meaning in our respective worlds may appear
endued with are thus pure gifts of the spectator’s mind.
William James, The Varieties of Religious Experience
William James, like scores of psychologists since, sought to understand the psychological nature of
humanity’s most profound and deep experiences. By speculating on the role of emotions in giving life its
savor and significance, he presaged modern interest in how the seemingly fleeting and earthly (emotions)
contributes to the seemingly enduring and transcendental (meaning). Emotions, of course, seem
fundamental to well-being (Diener, 1984). However, despite being proposed to be a defining feature of
well-being nearly 30 years ago (Ryff, 1989), meaning only recently has been a serious and common part of
conversations and research about well-being. Given that meaning is supposed to be a path to living well
and enjoying rich, fulfilling lives, it is important to examine how consistently and reliably meaning relates
to a variety of well-being variables. In this chapter, I will summarize research on meaning in relation to
well-being. By the end of this chapter, I believe it will be apparent that many studies have found, and
replicated, close ties between meaning and other variables that are used to indicate well-being. In fact, the
weight of this research seems to make clear that asking whether meaning is related to well-being is no
longer an interesting research question. Instead, a better question may be whether it is possible for people
to experience well-being without meaning.
To help support this conclusion, this chapter will present the psychological approach to
understanding meaning in life, including the most popular and recent theories and tools for measuring
meaning in life. This chapter also will review empirical research on meaning in life, with a particular
emphasis on results that have been found again and again, showing that many ties between meaning and
wellbeing are reliably repeatable.
Meaning in Life in Psychology
Although there is evidence that people’s concern for whether ‘life, the universe, and everything’ has
any meaning is quite old, modern meaning in life scholarship does not draw its inspiration from ancient
sources that touch on topics at the heart of meaning, such as the Judeo-Christian Bible or The Epic of
Gilgamesh. Instead, in one form or another, most scholars trace the inspiration for studying our human
attraction to meaning to Viktor Frankl. As we will see, Frankl really personalized the idea of meaning,
rooting it in each individual’s experience.
Earlier existentialist philosophers had argued that the failure of religion, governments, and other
human institutional collectives to prove their authority over moral truth and righteousness led to the
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inescapable conclusion that there really was no valid external entity that had dominion over these topics.
There was no person, text, or tradition one could point to in life to say “OK, so that’s what this is all
about.” Moral sources relied on an accumulation of authority and the weight of absolute conviction.
Governmental sources relied on their ability to steward the needs of those they governed. Over centuries of
war and exploitation, particularly the World Wars of the mid-20th Century, the capacity for these moral and
governmental agents to represent moral truth and righteousness was in doubt. “Trust us” no longer seemed
adequate to the task. Rational sources of moral authority did not fare any better. Brilliant and persuasive
people could argue both sides of every issue from violence and human rights to the existence of God. The
loss of these official sources of meaning left a vacuum, devoid of sense and direction. This realization
struck many as alarming. Without being able to rely on millennia of teachings, dogmas, and laws to point a
way toward how we are supposed to live our lives, we are forced to improvise. One person might determine
that life is about helping others but another person might determine that life is about exploiting and
dominating others, and our simple species couldn’t say who was right because no one was right. The
universe did not care. Life did not have moral rules. There was no absolute truth. Life and the universe
were random, and in a meaningless universe, meaning is impossible.
Frankl had a different perspective. Frankl (1963) argued that there was, in fact, some kind of
meaning out there for each of us, and that our primary job was to discover it and give it life. Meaning
became a personal pursuit of purpose in Frankl’s view, and the desire for meaning was put forward as
essential to being human. Where earlier meaning was in the hands of an inert and uncaring universe, in the
middle of the 20th Century meaning was positioned as a core part of who we are, manifested through our
relationships, actions, and attitudes. This shift created the possibility that we could actually study
something as abstract as meaning. We cannot test whether the universe has meaning, but we can test
whether people have meaning, one person at a time. Thus, meaning in life—as a psychological variable—
does not bother with what people think about where life came from, why bad things happen to good
people, or whether there is a soul. None of their answers can be proven or disproven according to scientific
methods. Such questions are about a different level of meaning. They are about the meaning OF life. In
contrast, psychology cares about whether a person feels that there is meaning IN life, from her or his
perspective.
From this critical pivot—from the vast universe to the lone individual—meaning in life became a
human quality that psychologists could research. Not that they necessarily started to research meaning right
away. About less than 100 papers were published per year in the 1970s, 1980s, and 1990s. However,
beginning in 2006, interest in meaning took off. In 2015, 1,900 papers were published on the topic, and a
large proportion of these papers presented empirical data, extending in small and large ways what we know
about how people experience meaning in their lives and what that experience of meaning provides.
Essentially, as many papers are published each and every year on this topic now as were published in the
first 60 years of the field combined. This chapter draws on that large body of research to identify what we
are confident we know about meaning in life as well as to identify key areas where we still do not know
enough. We will begin by discussing definitions and theories concerning meaning.
Definition and Measurement of Meaning in Life
At a basic level, “meaning” itself is widely used to refer to how meaningful people perceive their
lives to be. People who regard their lives to be very meaningful are said to “have meaning,” or that their
lives have the “presence of meaning.” Meaning in this sense exists at a medium level of abstraction. At a
more cosmic level is the meaning that the universe might or might not have (known as cosmic meaning).
For example, people’s belief or disbelief in religion are concerned with cosmic meaning. At a more specific
level is the meaning any one of us might attribute or draw from a particular life event (known as situational
meaning). Most interest in situational meaning concerns the way in which people interpret or try to make
sense of trauma, tragedy, or adversity they encounter in life. For example, losing one’s job can be
interpreted as a rebuke or diminishment of worth, in which case the situational meaning is one of hardship
and defeat. The meaning you perceive your life to have is more formally known as personal meaning. To
some degree personal meaning includes the ways in which cosmic meaning and situational meaning are
relevant to your life, but only insofar as they impact whether you feel your own individual life overall is
meaningful. Throughout this chapter, and in most of the research people conduct, “meaning” is used in this
manner.
A couple of additional distinctions are made in the field. First, although two people might both
perceive similar levels of meaning in their lives, their sources of meaning may differ. Person A might get
the most meaning from hard work, trying to achieve goals, and pursuing success, and Person B might get
the most meaning from family time, being a good friend, and volunteering. Sources of meaning are those
parts of life from which people draw meaning and in which they invest their energy. Generally, research
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suggests that the most common sources of meaning are relationships and the types of activities we are
engaged in (e.g., Steger et al., 2013). Not a lot of research has examined whether it makes a difference what
sources of meaning people have, but studies often find that people who get their meaning from selfcentered
or materialistic sources are less happy and experience less meaning than people who get their
meaning from self-transcendent and altruistic sources (Schnell, 2009).
Second, Person A and B might have very different orientations to meaning itself. Person A might
go through life never thinking about meaning unless she or he is asked, whereas Person B might think about
meaning much more, trying to get a deeper understanding of the nature of existence and being a good
person, looking for more meaning all the time. Person B would be more likely to engage in the search for
meaning. The search for meaning refers to how actively and intentionally people are oriented to meaning
in terms of their interest to find more or deeper understandings of meaning in their lives. Research shows
that people who are searching for meaning are a little more likely to be anxious and unhappy, but also are
more likely to be open-minded and interested about the world around them (e.g., Steger, Kashdan, Sullivan,
& Lorentz, 2008). The rest of this chapter is about the presence of personal meaning in a person’s life, or,
simply, meaning.
Theories of Meaning
Why should meaning be such an important part of well-being? Why should people experience
meaning in the first place? There are few theories that tackle both of these questions. Frankl (1963)
proposed that deep within humans is an innate need, or will, for meaning. In motivational need theories
like this one, people experience well-being if they meet the need and distress if they do not. People
successful at meeting needs are in their natural states, and look happy overall, particularly in contrast to
people who are frustrated in their efforts to meet their needs. It still might be somewhat unclear as to why
people would have a need for meaning. Frankl argues that humans are spiritual creatures, though not in any
religious sense. As spiritual creatures, we need to address our built-in desire for living out our values in a
meaningful way. In contrast to this spiritual explanation for why we might have an intrinsic orientation to
meaning,
Klinger (1977) felt that as living creatures we have a natural inclination to set goals to attain those
materials we need to stay alive. Klinger implies that this motivational drive transfers to meaning and
purpose because we humans are able to conceive of big abstract notions about what our lives should be
like. According to these two scholars, meaning is important as a motivational drive, perhaps rooted in our
animalistic needs to seek out nutrition, warmth, water, and other life-giving resources, which then gets
transferred to higher aspirations for having a life worth living. Battista and Almond (1973) suggested that
people also need to have a mental framework they can use to understand what that life worth living might
be like. In these theories, feeling the presence of meaning is the marker that we are doing a good job of
pursuing good aspirations. Baumeister (1991) argued that meaning occurs when a specific set of needs are
met: purpose (having big goals), self-worth (feeling good about one’s self), value (having some way to
justify decisions and actions), and efficacy (feeling competent to act effectively in the world). There are
two studies that provide some evidence that these four needs are correlated to people’s levels of meaning in
the context of thinking about one’s family (Lambert, Baumeister, Stillman, & Finchman, 2012) or under
experimental ostracism conditions (Stillman et al., 2009). However, purpose has been viewed as central
and even definitional to meaning since at least Frankl’s work in the 1940s and 1950s, and self-worth,
efficacy, and having a system of values or philosophies to guide one’s actions are each part of models of
general well-being in their own right. These close associations among meaning, well-being, and the
proposed needs makes it difficult to tease apart whether they are needs, or whether those elements are part
of meaning versus well-being. However, bridging these early theories of meaning’s origin suggests that
people have some level of primal motivational drive to act in the world that must be satisfied to create
meaning in their lives.
A different account of where meaning comes from focuses more on the nature of our mental
processes, rather than our motivational processes. Steger (2009, 2012, in press) argued that meaning is
similar to other mental processes the people have, that making sense of important stimuli gave us an
evolutionary competitive advantage. For example, making sense of the facial expressions of a new group
of people you encounter helps you navigate possible conflict. Making sense of the landscape around where
one lives helps identify dangers and resources. Making sense of the sounds and gestures produced by other
members of your species helps preserve and spread knowledge. This information processing and
integration capacity is very similar to the way in which meaning works. Meaning incorporates people
knowledge about their selves, other people, and the world around them into maps or meaning systems,
preserving and linking information, both concrete and abstract. People’s meaning systems help them
conceive of grand goals and aspirations for their lives, giving them a sense of purpose. Several other
scholars have emphasized the cognitive sense-making nature of humans in relation to meaning (e.g., Heine,
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Proulx, & Vohs, 2006).
Beyond motivation and cognition, some scholars have developed ideas about how people
experience meaning through emotional means (e.g., Reker & Wong, 1988). People seem to decide whether
their lives have meaning by using, in part, their gut feelings or emotions (Heintzelman & King, 2014). In
fact, all else being equal, people rate their lives as more meaningful when they are in a positive mood
(King, Hicks, Krull, & DelGaiso, 2006). That is, if I asked you how meaningful your life felt while you
were watching a funny movie, you might rate it higher than if you were just sitting at home reading.
However, some scholars feel that positive feelings are more important when they happen at a higher level
of abstraction. While feeling good might make life seem more meaningful for a few minutes, it may be
much more important to feel positively about your life as a whole, seeing that your life matters (George &
Park, 2014). Thus, “meaning in life necessarily involves people feeling that their lives matter, making sense
of their lives, and determining a broader purpose for their lives” (Steger, 2012, p. 177). More formally,
meaning emerges “from the web of connections, interpretations, aspirations, and evaluations that (1) make
our experiences comprehensible, (2) direct our efforts toward desired futures, and (3) provide a sense that
our lives matter and are worthwhile” (Martela & Steger, 2016, p.538, italics added), which are known as
comprehension (also known as coherence), purpose, and significance, respectively.
Tools for Measuring Meaning
Meaning research consists of two parts that are not very well connected. The first part, which we
have just examined, is the background of theory that defines meaning to have three main parts. The second
part is the empirical research tradition, which has established hundreds of links between meaning and living
a life marked by happiness and well-being. This second part usually uses formal tools for measuring
meaning, none of which really measure comprehension, purpose, and significance separately. Beginning in
the 1960s, a series of measurement tools were developed. Early tools (i.e., Purpose in Life Test;
Crumbaugh & Maholick, 1964; Life Regards Index, Battista & Almond, 1973), were criticized as having
problems with their internal structure, item wording, and inclusion of unrelated content, among other issues
(e.g., Dyck, 1987; Steger, 2006; 2007).
The two most widely used measurement tools today both benefitted from sophisticated statistical
techniques that were not practical until somewhat recently, which produced psychometrically robust
instruments. Ryff’s (1989) Purpose subscale is a part of a larger measure of psychological well-being. This
subscale assesses people’s levels of energy, activity, worthwhile things to do, and goals that they can
pursue. It is quite commonly used in health-related research. The Meaning in Life Questionnaire (Steger,
Frazier, Oishi, & Kaler, 2006) is more of a generic measure of meaning, asking people directly if they feel
their lives have meaning and purpose. It also measures how much people are searching for meaning. These
two subscales are quite commonly used in psychological and educational research. New tools continue to
be developed, usually with the aim of helping researchers understand the different dimensions and
components of meaning in life (e.g., George & Park, 2014).
Review of Research Assessing Relationships
between Meaning and Well-Being
Particularly within the last 10-15 years, many studies have been conducted providing extensive
knowledge about the connections between meaning and well-being. As you might expect from the title of
this chapter, the overwhelming conclusion is that meaning is closely tied to a vast array of well-being
indicators. In this section, the most-replicated results will be reviewed, broken into three categories:
subjective or hedonic well-being indicators, psychological or eudaimonic well-being indicators, and
general quality of life indicators. Although the general pattern will be to report only a single citation for
each finding, all of the results discussed here have been replicated. The importance of replication of results
across multiple studies is a central foundation of science, and especially for a variable with its roots in
philosophy and theology, knowing that different researchers have found the same phenomena several times
gives solidity to meaning research. This is not a meta-analysis, however, so only one reference is provided
for each finding, and it is not possible to provide an estimate of how many null findings it would take to
outweigh the significant ones. In some cases, this chapter will highlight areas where singular results
suggest an intriguing new angle that requires further research.
Subjective of Hedonic Well-Being Indicators
Subjective well-being (SWB) is a somewhat broad term for people’s appraisals that their life is
good with no particular boundaries or criteria imposed upon their responses. It is sometimes equated with
hedonic well-being, which is an older philosophical idea that more or less boils down to the idea that if
someone says she is happy, then she is happy, regardless of what information she uses to make that
determination. SWB has been proposed to include variables such as happiness, life satisfaction, and
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positive and negative emotions (Diener, 1984).
Meaning is positively correlated with experiencing positive affect and emotions (Chamberlain &
Zika, 1988), such as love, joy, vitality (Steger et al., 2006), curiosity (Kashdan & Steger, 2007), and hope
(Mascaro & Rosen, 2005). In fact, so much of this line of research has been published that a meta-analysis
among older adults was feasible, identifying a near-large effect size between meaning and diverse
measures of positive emotions (Pinquart, 2002). Further, experimental evidence from one set of studies
shows that increasing positive emotional states raises people’s perceptions of meaning (King et al., 2006).
As one might expect, meaning is inversely correlated with negative affect and emotions (e.g., Steger et al.,
2006).
Meaning also is positively related to broader indicators of SWB, such as happiness (Debats, van der
Lubbe, & Wezeman, 1993), general well-being (Reker, 2002), psychological adjustment (O’Conner &
Vallerand, 1998), and life satisfaction (Ryff, 1989). This latter finding includes one of the rare long-term
longitudinal studies, demonstrating that meaning and life satisfaction are positively correlated over one
year’s time (Steger & Kashdan, 2007). However, many of these results have been demonstrated over
shorter periods of time such as one month (e.g., Steger et al., 2006) or 2-3 weeks (Steger & Frazier, 2005).
Psychological or Eudaimonic Well-Being Indicators
Psychological well-being (PWB) is a more narrowly focused term for a specific set of variables that
are deemed by some expert source as being necessary for human flourishing. It is generally associated with
eudaimonic well-being, which draws inspiration from Aristotle’s philosophy. PWB variables are often
viewed as being critical for the full development of human potential, and do not always include the kinds
of information someone might use to judge if she or he is happy. PWB variables focus on personal growth,
persistence, virtue, morality, and so on. Meaning itself is often put forward as a PWB or eudaimonic wellbeing
indicator (e.g., Ryff, 1989), although it certainly can be considered to be both hedonic and
eudaimonic (Steger, 2016). Many characterizations of PWB suggest that people should have a positive
view off their selves. Accordingly, meaning positively correlates with self-esteem (Ryff, 1989), self-worth
(O’Conner & Vallerand, 1998), and self-actualization (Phillips, Watkins, & Noll, 1974). PWB also is
associated with Self-Determination Theory (Deci & Ryan, 2000), which posits that humans must meet three
needs in order to flourish psychologically: Autonomy, Positive Relationships, and Competence. Meaning
has been positively correlated to these three needs in several studies and cultures (Church et al., 2014).
Meaning also has been positively correlated with having a sense of personal control over one’s life, or
locus of control (Ryff, 1989), as well as positive perceptions of the world itself (Sharpe & Viney, 1973).
Quality of Life Indicators
The final category of well-being indicators is a diverse group of variables that can be lumped under
the umbrella term, quality of life (QOL). QOL is most often associated with health and health research and
includes factors such as whether people are free of illness or disease, physical impairments or symptoms,
and mental health. It may bear recalling that the heritage of meaning research lies in clinical theory on how
people develop and recover from disorders, like depression and anxiety. Although well-being often has
been separated from research on disorders, several models of overall psychological flourishing argue that it
is important to consider both distress and well-being (e.g., Keyes, 2002). Thus, this section includes
indicators of positive QOL, such as health, as well as negative QOL, such as disorders.
Among the most common results in this area of research is the inverse relationship between
meaning and depressive symptoms (Kleiman & Beaver, 2013). As with positive emotions, enough research
has been done on this link that a meta-analysis was able to estimate a near-large effect size of -.46 among
older adults (Pinquart, 2002). Although no meta-analysis has been conducted, inverse correlations between
meaning and anxiety symptoms are of similar size and also are frequently reported (Steger, Mann, Michels,
& Cooper, 2009). People who have high levels of meaning report lower levels of perceived stress (Flannery
& Flannery, 1990) and fewer symptoms of stress-related disorders, such as PTSD (DeViva, Sheerin,
Southwick, Roy, Pietrzak, & Harpaz-Rotem, 2016).
One idea of early existentialists like Frankl was that people who cannot find meaning may give up
on life, and indeed research has found that those low in meaning report more hopelessness (Edwards &
Holden, 2001), a higher degree of drug and alcohol-related problems (Nicholson et al., 1994), and even
stronger tendencies to want to end their own lives through suicide, known as suicidality (Henry et al.,
2014). On the flip side, those who do feel their lives have meaning report more effective coping (Debats,
Drost, & Hansen, 1995) and are more likely to say that they not only have survived trauma and tragedy but
even have grown psychologically, spiritually, or socially as a result of those experiences (Steger, Frazier,
& Zacchanini, 2008).
Finally, those who report having more meaning not only feel they are in better health than others
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according to their subjective health ratings (Battersby & Phillips, 2016), but they also live longer lives
(Boyle, Barnes, Buchman, & Bennett, 2009).
Personality. Although not directly considered to be QOL variables, some personality traits
consistently are linked to better health and well-being outcomes, so they are considered here. Meaning is
positively related to extraversion (e.g., Pearson & Sheffield, 1974) and conscientiousness (e.g., Steger et
al., 2008), and negatively related to neuroticism (e.g., DeViva et al., 2016). Finally, meaning has been
positively linked to several ways of measuring a person’s commitment to religious beliefs (e.g., Steger &
Frazier, 2005), which, though not a dimension of personality often is related to dimensions of personality
(e.g., conscientiousness) and well-being.
Discussion
Although there is appreciable breadth in the research that has been done on the many ties between
meaning and well-being, there are several important areas where the field is reliant on one study (or less).
Three areas in particular demand further study to clarify and expand upon tantalizing early research results.
These areas are understanding mechanisms by which meaning helps create broader well-being, identifying
how meaning impacts health, and exploring how meaning is construed or created in diverse cultural
contexts.
How does meaning create well-being? While we may be at the point where we can assume that
most people who have meaning also experience greater well-being, we do not know why that is so. One
hypothesis is that meaning supports other parts of people’s lives known to impact well-being. For example,
positive relationships with other people are critical to people’s psychological functioning and well-being,
and as reviewed here people with meaning in their lives report better relationships. If meaning helps people
establish better relationships, then that would provide one avenue for boosting well-being. There is
evidence that people prefer to interact with those who have high levels of meaning, and even judge them to
be more likeable, have greater potential as a friend, and even that this effect reduces the well-known impact
of physical attractiveness on these markers of interpersonal appeal (Stillman, Lambert, Fincham, &
Baumeister, 2011). There also is evidence that those high in meaning care more about helping and
benefitting others (Martela, Ryan, & Steger, in press). Thus, the arrow seems to run both ways: better
interactions and relationships foster meaning, and meaning creates better interactions and relationships.
A second hypothesis is that people with meaning engage in different activities, but very few studies
have established these links. One of the only ones that has been conducted showed that levels of meaning
were higher among people who tended relationships, did volunteer work, worked toward their goals, and
persevered through challenge to a greater degree than other people (Steger, Kashdan, & Oishi, 2006). Both
of these hypotheses require more research in order to identify what people with meaning seem to be doing
differently than other people. It may simply be that meaning is part of well-being, but greater possibilities
for improving people’s lives are suggested if meaning additionally is viewed as a path to well-being.
How does meaning lead to health? Similar to the case of well-being, we know that meaning is
linked to a longer, healthier life, but the number of studies implicating biological or behavioral mediators is
still small. Studies have found that people high in meaning engage less often in behaviors such as smoking
cigarettes, or abusing substances, which would reduce risks to their overall health, particularly over time
(e.g., Nicholson et al., 1994; Steger, Fitch-Martin, Donnelly, & Rickard, 2015; Steger, Mann, Michels, &
Cooper, 2009). Other research has targeted biological mediators between meaning and health, focusing on
people’s levels of stress-related hormones and immune cells. These studies find that people with greater
meaning have less evidence of potentially toxic levels of stress and immune response, as marked by such
things as inflammatory cytokines and killer T-cell levels (e.g., Bower, Kemeny, Taylor, & Fahey, 2003;
Krause & Hayward, 2012). Thus, meaning seems to play a role in protecting people from the risk for
physical harm, whether through their own behaviors or through the impacts of life and stress on their
immune and hormone system functioning, but more research is needed to show that meaning really does
predict these behavioral and biological precursors to health in longitudinal and experimental settings.
How is meaning construed in diverse cultures? Meaning, like much of the rest of psychology,
draws its origins from Western European-influenced cultures. This limited cultural scope leaves open the
possibility that meaning is to some degree a cultural artifact. Research strongly suggests that meaning and
well-being are linked together in all of the couple of dozen countries where it has been studied (e.g.,
Church et al., 2014). The issue is that when cross-cultural research is conducted, what is learned is
restricted to the questions that are asked. For meaning, we can say that when the MLQ is used, people say
their lives have meaning regardless of which country they come from (at least in the countries studied so
far). What we cannot say is whether we are asking the right questions about meaning. We are not able to
estimate whether studying meaning requires asking totally different kinds of questions in New York versus
New Guinea, New Zealand, or New Caledonia. Research is needed that builds from the ground up in many
588
different cultures and nations.
Meaning is somewhat unique among psychological variables because of the historic emphasis on
sources of meaning. This interest in where people find meaning lends itself to more open-ended inquiries
than do methods that require people to simply answer a list of validated survey items. It should be
reasonably straight-forward to ask people from diverse cultures and backgrounds where meaning comes
from in their lives. However, even studies that look at sources of meaning around the world favor Europe
and North America and tend to aggregate results rather than explore possible differences (Fave, Brdar,
Wissing, & Vella-Brodrick, 2013). One intriguing exception comes from a study of both Arab and Jewish
residents of Israel, in which rankings of the importance of sources of meaning differed by respondent’s
ethnicity (Bar-Tur, Savaya, & Prager, 2001). While it is interesting to know that cultural context may affect
how people prioritize sources of meaning, even better would be to conduct research in such a way as to
enable each culture’s unique assemblage of sources of meaning to be revealed.
Conclusion
From some of our species’ earliest writings to large scale scientific research conducted around the
world, meaning has presented a compelling set of questions. Some of these questions continue to evade the
field, such as how meaning helps foster well-being and health, and how much of the richness of the human
striving for meaning remains unexplored. Given the explosive pace of meaning research, these topics
undoubtedly will be tackled in the near future. Until then, it is clear that a great deal of research links
meaning with well-being, that these links generally represent large effects, and despite some gaps in
research coverage, meaning in life is justified in its position as a cornerstone resource for human well-being
and flourishing.
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2018 Ed Diener. Copyright Creative Commons: Attribution, noncommercial, no
derivatives
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Multiple Levels in Job Demands–Resources Theory: Implications
for Employee Well-being and Performance
By Arnold B. Bakker, Erasmus University Rotterdam, The Netherland, & Evangelia Demerouti, Eindhoven
University of Technology, The Netherlands
Citation
Bakker, A. B., & Demerouti, E. (2018). Multiple levels in job demands-resources theory: Implications
for employee well-being and performance. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of wellbeing.
Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
This chapter uses the most recent version of Job Demands–Resources (JD-R) theory to explain how
working conditions influence employees, and how employees influence their own working conditions. We
show how employee self-undermining activates a loss cycle of job demands, strain, and negative behaviors
over time, whereas employee job crafting activates a gain cycle of job resources, work engagement, and
positive behaviors. Moreover, we argue that employee well-being and organizational behavior is a function
of factors located at different levels (i.e. organization, team, individual level), which influence each other
within and over time. We propose cross-level interaction effects of organization-level initiatives and
leader/employee behaviors on team and individual well-being and performance. Although JD-R theory
provides answers to many questions regarding employee well-being and performance, we discuss several
issues that deserve research attention. The chapter closes with practical implications. We discuss how
managers and supervisors can help employees to avoid health problems and flourish at work.
Keywords: JD-R theory; work engagement; multilevel; teams; HR practices
Occupational well-being is gaining momentum because managers, policy makers, and employees
have started to realize that occupational well-being is a crucial determinant of human functioning and job
performance (De Neve, Diener, Tay & Xuereb, 2013). Our knowledge about well-being at work comes
from thousands of studies among the various stakeholders in organizational life: employees, their
supervisors, HR managers, work teams, and clients. High-quality studies use multiple sources of
information to investigate the predictors and outcomes of occupational well-being. In the past decades, we
have created a rich knowledge base about the psychosocial factors in the work environment that are
responsible for the experience of job stress or well-being, as well as organizational behavior. We know
now which job demands and resources predict employee well-being and have an impact on performance
(e.g., financial returns, absenteeism, client satisfaction) (e.g., Bakker, Demerouti, De Boer & Schaufeli,
2003; Xanthopoulou, Bakker, Demerouti & Schaufeli, 2009a). However, one important problem of the
current literature is that the vast majority of studies in occupational well-being follow a relatively simplistic
stimulus-response model; assuming that employees are passive and simply react to the working conditions
they are exposed to.
In the present paper, we use the most recent version of Job Demands–Resources theory (Bakker &
Demerouti, 2014; 2017) to explain how working conditions influence employees, and how employees
actively influence their own working conditions. We argue that organizational life should be modeled at the
various levels (organization, team, individual), which influence each other within and over time. In this
way, we can start to understand the stable and dynamic properties of occupational well-being. Moreover, it
is important to model the cross-level interaction effects of organization-level initiatives and
leader/employee behaviors on team and individual well-being and performance. Using this multilevel
approach, we can explain how managers and supervisors can help employees to avoid job stress, and
enhance well-being and job performance.
Job Demands–Resources Theory
Since the end products of modern labor are so diverse that they range from the optimization of
search engines to the provision of personal health care, it is obvious that working conditions can differ
dramatically between organizations. Despite these differences, Job Demands–Resources theory (Bakker &
Demerouti, 2014; 2017; Demerouti, Bakker, Nachreiner, & Schaufeli, 2001) proposes that all job
characteristics can be classified in two main categories – namely job demands and job resources – that have
unique properties and predictive value (Proposition 1). Job demands are the aspects of work that cost
energy, like workload, complex tasks, and conflicts. Whereas workload and complexity can be qualified as
challenge demands that help to perform well, conflicts are hindrance job demands that undermine
performance (LePine, Podsakoff, & LePine, 2005). Job resources are the aspects of work that help
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employees to deal with job demands and achieve their goals. For example, performance feedback, social
support and skill variety are motivating job characteristics that provide meaning to employees, and satisfy
employees’ basic psychological needs, namely the needs for competence, relatedness, and autonomy (Deci
& Ryan, 1985).
Job demands and resources have unique and independent effects on employee well-being
(Proposition 2). As already proposed in the original version of the JD-R model (Demerouti et al., 2001), job
demands may initiate a health-impairment process if exposure to daily workload transforms into chronic
overload over a long time period. In this case, job demands lead to chronic exhaustion and may eventually
result in physical health problems (including cardiovascular diseases). In contrast, job resources initiate a
motivational process. Since job resources provide meaning and satisfy people’s basic needs, job resources
are motivating and contribute positively to work engagement (i.e. a fulfilling state of vigor, dedication, and
absorption; Schaufeli & Bakker, 2004).
Proposition 3 of JD-R theory is that job resources can buffer the impact of job demands on negative
strain. Thus, even though job demands and job resources have clear and independent main effects, they
also work in concert (see Figure 1). Job resources are instrumental in that they arm employees with the
means it takes to cope with the job demands. Whereas some scholars have argued that job resources should
match the specific job demands – for example, that emotional job demands need to be matched with
emotional job resources (De Jonge & Dormann, 2006), our research has shown that various job resources
can buffer the impact of various job demands on negative strain (e.g., Bakker, Demerouti & Euwema,
2005; Bakker, Van Veldhoven & Xanthopoulou, 2010; Xanthopoulou et al., 2007).
Figure 1. The Job Demands–Resources model.
Proposition 4 brings the JD-R theory one step further as it suggests that job resources particularly
influence motivation and work engagement when job demands are high. Thus, autonomy, skill variety,
performance feedback, and task identity become particularly important when the job demands are very
challenging. This idea is consistent with Hobfoll’s (2001) notion that all types of tangible or psychological
resources gain importance and become particularly useful when needed. Particularly when employees are
confronted with a high workload and with emotionally demanding clients, they can use their autonomy,
skills, and sense of prosocial impact to deal persistently with these demands and choose the right approach.
Indeed, our research among Finnish teachers and dentists (Bakker, Hakanen, Demerouti & Xanthopoulou,
2007; Hakanen, Bakker & Demerouti, 2005) has shown that job resources such as appreciation,
innovativeness, and skill variety are most predictive of work engagement when job demands (e.g., pupil
misbehavior, unfavorable physical working environment) are high. Thus, job resources are particularly
useful and motivating when needed.
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Proposition 5 is that personal resources such as optimism and self-efficacy play a similar role as job
resources (see Figure 1). Personal resources refer to the beliefs people hold regarding how much control
they have over their (work) environment. Individuals who are high in optimism and self-efficacy believe
that good things will happen to them, and that they are capable of handling unforeseen events. Such beliefs
help employees to actively approach their job demands and deal with them in an effective way. For
example, our research has shown that health care nurses who feel optimistic and self-efficacious can
translate emotionally demanding interactions with their patients into challenges so that they feel engaged in
their work (Bakker & Sanz-Vergel, 2013). Additionally, when nurses realize they have many personal
resources, they are better able to deal with possible hindrance job demands, such as bureaucracy and
conflicts.
JD-R theory puts employee well-being center stage, but an important goal of the theory is to predict
employee behavior and organizational outcomes (absenteeism, productivity, organizational citizenship,
client satisfaction). Proposition 6 is that motivation has a positive impact on job performance, whereas job
strain has a negative impact on job performance. Whereas motivation helps employees to be goal-directed
and to focus all their energetic and cognitive resources on the tasks at hand, job strain impairs performance
because it undermines the ability to focus. Employees who are exhausted or feel anxious at work are more
likely to make mistakes, which have a negative impact on performance (Bakker, Van Emmerik, & Van
Riet, 2008). In recent experimental studies (Hopstaken, Van der Linden, Bakker, & Kompier, 2015;
Hopstaken, Van der Linden, Bakker, Kompier, & Leung, 2016), we have found that engaged individuals
perform better on demanding tasks because they focus all their attention to the task, as indicated by pupil
diameter data, brain activity, and self-report data. Furthermore, combining daily diary reports with objective
financial data, Xanthopoulou et al. (2009a) showed that employees working in fast-food restaurants had
better financial results on the days they were highly engaged in their work. =
Employees Influence their Own Job Design
As indicated in the opening paragraphs, most research in the domain of occupational health and
well-being follows a stimulus-response model, thereby implicitly assuming that employees are passive and
simply react to their working conditions. For example, the well-known demands-control model, effortreward
imbalance model, and job characteristics model (for a brief discussion, see Bakker & Demerouti,
2014) all assume that work characteristics influence employees, but do not explicate how employees may
influence their own work environment. However, there is considerable evidence for the idea that
employees play an active role in interpreting and modifying their working conditions. JD-R theory (Bakker
& Demerouti, 2014, 2017) proposes that depending on their occupational health and well-being, employees
may influence their own job design in one of two ways: (1) employees are stressed and influence their
working environment in a negative way, inducing a loss cycle of job demands and strain; or (2) employees
are engaged in their work and influence their working environment in a positive way, inducing a gain cycle
of job resources and work engagement. These propositions are discussed in more detail below.
Loss Cycles in JD-R Theory
In his conservation of resources theory, Hobfoll (1989) proposes that people who lack various types
of resources (e.g., a home, time, money, knowledge) are susceptible to losing even more resources. The
assumption is that resources are related to each other in a ‘web-like’ nature, and that resource loss occurs in
spirals. Loss spirals will follow initial losses, with each loss resulting in depletion of resources for
confronting the next threat or loss (Hobfoll, 2001). For example, in a study on coping with traumatic
stressors, Heath, Hall, Russ, Canetti, and Hobfoll (2012) found that exposure to political violence resulted
in the loss of important personal and social resources. Resources loss predicted psychological distress,
which predicted further resource loss. It is important to note that resource loss also prevents the switching
of the situation into gain cycles, because there are not enough resources to invest in order to gain new
resources. For example, in the context of work, one could invest knowledge, energy, and time to learn new
skills in order to qualify for a new job. JD-R theory refers to loss cycles, because loss spirals eventually
imply a complete depletion of resources. In most work organizations, people always have access to some
resources. However, they may end up in a vicious cycle of resource loss in which one problem leads to
another that aggravates the previous problem.
There is considerable evidence for loss cycles in an occupational context. Bakker, Schaufeli, Sixma,
Bosveld, and Van Dierendonck (2000) found that general practitioners who had lost their enthusiasm and
were more cynical towards their patients (cynicism) at the first wave of data collection faced more patient
demands (complaints, threats) at the second wave five years later. In a similar vein, Ten Brummelhuis, Ter
Hoeven, Bakker, and Peper (2011) found that financial consultants who had lost their enthusiasm and
showed more burnout complaints reported a stronger increase in work overload, work hours, and workhome
barriers over a period of two years. In a recent study, Frins, van Ruysseveldt, Van Dam, and Van den
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Bossche (2016) found that older employees who lost their energy, felt exhausted and wished to retire at an
earlier age reported more time pressure and more hectic work one year later.
Employees who experience high levels of job strain (e.g., chronic exhaustion) communicate poorly,
make mistakes, and create conflicts, which add up to the already high job demands. Bakker and Costa
(2014) have coined the term self-undermining to refer to “behavior that creates obstacles that may
undermine performance” (p. 115). Proposition 7 in JD-R theory is that negative job strain leads to selfundermining
behaviors, which result in higher levels of job demands, and even higher levels of job strain.
Bakker and Wang (2016) showed that employees who engaged in self-undermining behaviors (i.e., created
stress, confusion, and conflict) reported higher levels of work pressure and emotional demands, were more
exhausted, and scored lower on supervisor-ratings of job performance. Thus, self-undermining seems the
consequence of high levels of job strain, and is the fuel of a loss cycle of high job demands and job strain
(see Figure 1).
Gain Cycles in JD-R Theory
Longitudinal studies carried out in the past decade have also provided convincing evidence for gain
cycles of job resources, well-being, and outcomes. For example, Hakanen, Perhoniemi and ToppinenTanner
(2008) found that task-level job resources (craftsmanship, pride in the profession, and positive
feedback from the results of work) predicted dentists’ work engagement, and that work engagement
predicted personal initiative over a period of three years. In addition, there was evidence for reversed
causal effects. Among others, personal initiative positively influenced work engagement, and work
engagement had a positive impact on future job resources, suggesting a gain cycle. Similarly, Reis, Hoppe
and Schröder (2015) followed psychotherapists over a period of five months, and found that work
engagement was a predictor and outcome of job resources such as autonomy, task variety, and learning
opportunities. In addition, they found that the relationship between work engagement and mental health
was reciprocal. Thus, those who felt generally cheerful, active, rested, and interested at time 1 (T1) were
more likely to be engaged at work at T2, and those who were engaged at work at T1 were more likely to
report a better general mental health at T2.
In their longitudinal study among engineers, Xanthopoulou, Bakker, Demerouti and Schaufeli
(2009b) found that job resources predicted personal resources (self-efficacy, optimism, and self-esteem)
and work engagement. They also found evidence for reversed causal effects from personal resources and
work engagement to job resources – suggesting that those who were more self-efficacious, optimistic and
enthusiastic at work gained more job resources over time. Finally, using a sophisticated study design with
three waves of data collection, Weigl and his colleagues (2010) found that hospital physicians with higher
levels of job control and active coping, and better work relationships at T1, felt more engaged at T2 (one
year later). Work engagement, in turn, was a predictor of job control, active coping and high-quality work
relationships at T3 (eighteen months later). Thus, T2 work engagement functioned as a mediator in the
longitudinal relationship between T1 and T3 resources, suggesting a gain cycle of job resources. Taken
together, these studies suggest that individuals who are engaged in their job are also motivated to stay
engaged, and create their own resources (e.g., autonomy, feedback, support) over time. This idea is again
consistent with conservation of resources theory (Hobfoll, 1989; 2001). Individuals are motivated to
conserve their resources, and will try to expand these resources if possible. The question is how employees
manage to optimize their own work environment.
JD-R theory acknowledges employees as active creators by modeling the loss and gain cycles
employees initiate at work. We already saw that employees who are too strained by their job demands will
become exhausted and initiate a loss cycle. Their exhaustion increases the likelihood of self-undermining
behaviors, which further increase job demands and exhaustion. In contrast, employees who are engaged at
work are motivated to stay engaged. We suggest that these employees will proactively search for
challenges in their work and for the resources needed to perform well. The latter behavior is called job
crafting.
Job crafting. According to Wrzesniewski and Dutton (2001), job crafting refers to the proactive
changes employees make in their work tasks and their working relationships (e.g., with clients, colleagues,
and their supervisor). The authors argue that job crafting may also refer to a cognitive process in which
employees try to alter their view of work to make it more meaningful. In JD-R theory, we propose a
behavioral approach, and argue that job crafting can take the form of proactively optimizing job demands
and job resources (Tims, Bakker & Derks, 2012). More specifically, we propose that employees may
increase their challenge job demands, increase their social and structural job resources, and decrease their
hindrance job demands. A recent series of studies has indicated that job crafting can indeed lead to more
job and personal resources and indirectly contribute to work engagement and job performance (see Figure
1; Demerouti, 2014, for an overview).
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Proposition 8 in JD-R theory is that employees who are motivated by their work are likely to use
job crafting behaviors, which lead to higher levels of job and personal resources, and even higher levels of
motivation. Research of the past five years has provided convincing evidence for this process. For example,
Tims, Bakker and Derks (2013) found that job crafting in the form of seeking challenges and resources
predicted an increase in job resources, and indirectly related to increases in work engagement and job
satisfaction. Vogt, Hakanen, Brauchli, Jenny and Bauer (2016) showed with a longitudinal study that
employees who proactively built a resourceful and challenging work environment for themselves, increased
their own psychological capital (hope, resilience, self-efficacy, and optimism) and work engagement.
Demerouti, Bakker, and Gevers (2015) showed that job crafting (particularly increasing job
resources) was positively related to supervisor-ratings of contextual performance (i.e. helping others),
through employee work engagement. In addition, job crafting was positively related to supervisor-ratings
of creativity through work engagement and flourishing. Moreover, recent studies have shown that job
crafting interventions in the form of training and self goal-setting can have favorable effects on employee
well-being and job performance (Gordon et al., 2016; Van den Heuvel, Demerouti & Peeters, 2015; Van
Wingerden, Bakker & Derks, 2016). Thus, employees can create their own ‘gain cycle’ of resources and
work engagement by learning to craft their job. Unfortunately, however, most research seems to suggest
that (self-initiated) job crafting in the form of reducing job demands is not an effective strategy to stop the
loss cycle of high job demands and job strain (Demerouti, 2014).
Multiple Levels in JD-R theory
JD-R theory outlines the processes through which job demands and resources influence
occupational health, organizational behavior, and job performance. Most JD-R research has investigated
these processes at the individual, employee level. Thus, employees are asked to report about their own job
demands and resources and well-being, and this is then related to (self- or other-ratings of) individual
performance. When managers know which specific job demands and resources need attention, they may
take strategic and structural measures so that the work process is optimized for the employees in a topdown
fashion which results in a better quality of working life. In addition, we have seen that employees
influence their own working conditions. Employees can be reactive and undermine themselves by creating
more job demands, or they can be proactive and optimize their own job demands and resources. This
bottom-up perspective does not replace but rather complements existing top-down approaches.
Acknowledging the active roles of various stakeholders raises the question how the various stakeholders
interact. Therefore, it is essential that scientists distinguish between various levels, namely the level of the
organization at large or management, the leader, the team, and the individual. In what follows, we illustrate
how organizations, leaders and teams influence individual employees (cross-level main and mediation
effects), and how the various levels interact to enhance employee well-being and organizational
performance (cross-level interaction effects). Figure 2 gives an overview of the multilevel processes that
may play a role here.
Organizational Level
In a recent paper, Albrecht, Bakker, Gruman, Macey and Saks (2015) have outlined how
organizations may influence employee work engagement and performance through human resource (HR)
practices. They argue that four key engagement-related HR practices (employee selection, socialization,
performance management, and learning and development; see number 1 in Figure 2) influence the
organizational climate (number 2) and the job demands and resources experienced by employees in their
work roles (number 5 and 8), and indirectly influence work engagement and performance outcomes
(number 6 and 9). Research has indeed provided evidence for this cross-level process. For example, Alfes,
Shantz, Truss and Soane (2013) found that human resource practices such as employment security,
extensive training, decentralization of decision-making, and sharing of financial and performance
information (number 1) were positively related to individual organizational citizenship behaviors through
work engagement (number 9). Dollard and Bakker (2010) found that when Australian teachers and
administrators perceived a psychological climate in their organization signaling that management takes care
of their employees (i.e., psychosocial safety climate; number 2), employees reported more job resources
and endurable job demands (number 8) – which resulted in higher levels of work engagement (number 9).
In a similar vein, Idris, Dollard, and Yulita (2014) found in their study in the Malaysian private sector that
psychosocial safety climate (number 2) had cross-level effects on employee perceptions of job design
(emotional job demands; number 8) and indirectly reduced psychological problems (exhaustion and
depression; number 9).
Figure 2. Multiple levels in JD-R theory. Note. WB = Well-being. Feedback loops are not included to
avoid overly complex modeling.
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Furthermore, Van Wingerden et al. (2016) showed that job crafting training initiated by the HR
department (number 1) had consistent positive effects on employee job crafting behaviors (number 7), and
indirectly influenced job demands, resources (number 8) and work engagement (number 9). In a similar
vein, Gordon et al. (2016) showed that job crafting training (number 1) influenced nurses’ and surgeons’
job crafting behaviors (number 7), and improved job demands and resources (number 8), as well as
objective ratings of job performance (number 9). As a final example, in an impressive study among more
than 15,000 employees from more than 1200 workplaces, Croon, Van Veldhoven, Peccei and Wood (2015)
found that job enrichment HR practices (number 1) indirectly influenced organizational productivity
(number 3) through employee perceptions of job resources (job control; number 8) and job satisfaction
(number 9). These findings indicate that organizations can use HR practices to optimize the design of the
jobs they offer. HR practices such as performance development and skills training create an abundance of
challenging job demands and job resources that fuel employee well-being and performance.
Leader Level
How do leaders influence employees’ job demands and resources? According to transformational
leadership theory (Bass, 1985), effective leaders are able to inspire their followers to invest effort in
common goals. By using inspirational motivation, individual consideration, and intellectual stimulation,
leaders can motivate their followers to use their personal strengths. In a series of studies, Breevaart and her
colleagues investigated how leaders may influence the working environment of their employees and in this
way indirectly influence employee work engagement and job performance. In one study, Breevaart et al.
(2014) followed naval cadets during their 34-day voyage from Northern Europe to North America by sail
ship. The results showed that transformational leaders (number 4) had a positive influence on cadets’ daily
work engagement (number 9) because these leaders created abundant job resources for their followers
(number 8). Naval cadets could use these resources to deal with the daily job challenges (e.g., hurricanes,
complex exercises at sea).
In a follow-up study among a heterogeneous sample of white-collar workers, these findings were
expanded. Breevaart, Bakker, Demerouti, Sleebos, and Maduro (2014) found that transformational
leadership (number 4) contributed to followers’ work engagement and leader-ratings of job performance
(number 9) through job resources (autonomy, feedback, opportunities for growth; number 8). Similarly,
Fernet, Trépanier, Austin, Gagné, and Forest (2015) investigated the impact of leadership on follower
performance in their study among nurses and school principals. Consistent with JD-R theory, they found
that transformational leadership (number 4) resulted in fewer job demands (cognitive, emotional and
physical demands) and more job resources (e.g., participation in decision-making, job recognition, and
quality of relationships; number 8), and indirectly contributed to more positive work attitudes and better
job performance (number 9).
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Team Level
In their study among Portuguese research teams, Costa, Passos and Bakker (2015) found that
performance feedback, social support from co-workers, support from the supervisor, and information acted
as team job resources (number 5) that predicted team work engagement (number 6) and objective research
output (e.g., number of publications, number of oral presentations in conferences, organization of
seminars/conferences, patents; number 6 and 9). Relationship conflict undermined the link between team
resources and team work engagement, whereas task conflict aggravated the link between team work
engagement and performance. These findings and the literature on teams clearly suggest that individual
employees in work teams influence each other’s engagement and performance.
There is indeed evidence for the crossover of work engagement between co-workers (e.g., Bakker,
Van Emmerik & Euwema, 2006; Bakker & Xanthopoulou, 2009; link from number 5 to 8). Moreover, in
their study among teams of occupational health professionals, Tims, Bakker, Derks, and Van Rhenen
(2013) found that team work engagement (number 6) was related to individual performance through
individual work engagement (number 9). Moreover, the latter study showed that employees were more
likely to be proactive and improve their own job demands and resources, if they worked in teams where
most others engaged in job crafting behaviors (see also Leana, Appelbaum, & Shevchuk, 2009). Bakker,
Rodriguez Munoz and Sanz Vergel (2016) argue that employees imitate each other’s job crafting behaviors
and therefore influence each other’s work engagement. The results of their study among dyads of
employees from various companies showed indeed a reciprocal relationship between dyad members’ job
crafting behaviors. Moreover, employee’s job crafting was related to colleague’s work engagement through
colleague’s job crafting, suggesting a modeling process.
Interactions between Various Levels
As we saw in this review, it is important to differentiate between different organizational levels
(organization, leader, team, individual), because the various stakeholders in organizations influence each
other. Unfortunately, most research in organizational psychology is conducted at the individual level.
Organizations are usually interested in average scores on job demands-resources, well-being, and
performance at the team or departmental level. Therefore, researchers often aggregate individual scores to
the group level. However, the aggregate of individual work engagement is phenomenologically different
from team work engagement (Costa, Passos & Bakker, 2014). In addition, we have just seen that
organizational life can better be explicitly modeled at various levels. This also offers the opportunity to
investigate how the various levels statistically interact to produce occupational health and organizational
performance (cross-level interaction effects).
Studies in the area of human resource management have investigated the cross-level interaction
between HR practices and job demands/job resources. Boon and Kalshoven (2014) found that highcommitment
HR practices (number 1) such as continuous training, high job security, empowerment, job
rotation, a focus on learning and developmental feedback, variable pay, and an extensive benefits package
were positively related to work engagement and organizational commitment (number 9), when task
proficiency was low – that is, under the condition that employees lacked the resources to handle their tasks
(number 8). This suggests that HR practices can help to overcome a lack of resources. However, Jensen,
Patel, and Messersmith (2013) found that high-performance work systems, which are aimed at creating a
competitive advantage for organizations, do so at the expense of workers. Using a multilevel sample of
1,592 government workers nested in 87 departments, they found that HPWS had several negative
consequences when implemented with low levels of job control. Specifically, Jensen and colleagues
showed that HPWS contributed positively to employee role overload (number 8) and anxiety (number 9)
when job control (number 8) was low. These findings clearly indicate that if the implementation of HPWS
practices is not coupled with an appropriate increase in autonomy among individual employees, simply
instating a bundled set of integrated HR practices may have undesirable effects on employee job demands
and well-being. These results point at the interplay between factors from different levels.
Using a general population sample of 2,343 Australian workers from a wide range of sectors, Hall,
Dollard, Winefield, Dormann, and Bakker (2013) tested the buffering role of psychosocial safety climate as
a macro-level resource in the health impairment process of the JD-R model. PSC refers to shared
perceptions of organizational policies, practices, and procedures for the protection of worker psychological
health and safety (Dollard & Bakker, 2010). When employees collectively believe that management takes
good care of their health and safety, there is a high PSC. Hall and his colleagues found that PSC (number 2
in Figure 2) moderated the effects of (emotional and psychological) job demands (number 8) on depression
(number 9), also after controlling for the impact of specific job resources (job control and social support).
In a similar vein, Garrick et al. (2014) investigated the impact of general PSC in Australian schools on the
link between teachers’ daily job demands and well-being. They found that PSC (number 2) buffered the
599
impact of daily job demands (number 8) on fatigue (number 9), and boosted the impact of daily job
demands (number 8) on work engagement (number 9). PSC also exerted a negative main effect on fatigue
and a positive main effect on engagement. These findings suggest that organizations may be able to
prevent worker depression and fatigue and foster work engagement when they focus on the development
of a consistent PSC that signals a work environment conducive to worker psychological health and positive
organizational behaviors.
Breevaart and Bakker (in press) hypothesized that daily transformational leadership behavior boosts
employee work engagement on days characterized by high challenge job demands, and protects work
engagement on days characterized by high hindrance job demands. Teachers filled out a short online
questionnaire at the end of each workday during a two-week period. Results showed that teachers’ daily
challenge demands (workload and cognitive demands; number 8) had a positive relationship with work
engagement (number 9) on the days transformational leadership (number 4) was high (vs. low). In addition,
teachers’ daily hindrance demands (role conflict; number 8) had a negative relationship with work
engagement (number 9) on the days transformational leadership (number 4) was low (vs. high). These
findings suggest that leaders use inspiration, intellectual stimulation and individual consideration to help
followers to deal with their daily job demands.
Wang, Demerouti, LeBlanc, Bakker and Jiang (2017) investigated how Chinese leaders empower
their followers so that they optimize their own working conditions and feel well (i.e. job crafting). They
conducted a diary study among 106 leader-follower dyads (HR managers, consultants, engineers, and
programmers) that had work contact on a daily basis. Wang and colleagues found that proactive leaders
were most likely to show empowering behaviors, by consulting, delegating, enabling, and informing their
followers. Further, the results showed that on the days leaders used more empowering behaviors (number
4), followers were more likely to engage in job crafting – i.e. to seek job challenges and resources, and to
reduce hindrance demands (number 7). Moreover, daily empowering behaviors of leaders were particularly
important for follower job crafting on the days followers had limited autonomy (number 8). These findings
highlight that the interplay between leaders’ behavior and individual job characteristics influences
individual employee outcomes.
Future Outlook on JD-R Theory
Although JD-R theory provides answers to many issues regarding (occupational) well-being, there
are several issues that need further attention. We will zoom in on three of these issues. First, although we
know that job characteristics and well-being are related in the form of cycles or spirals (Salanova,
Schaufeli, Xanthopoulou, & Bakker, 2010), we do not really know why this is the case. Why do individuals
who are exhausted continue to find themselves in a negative cycle and not turn the negative cycle into a
positive cycle? Similarly, how do individuals who are engaged in their job manage to remain in a positive
cycle? Do such cycles lead to increases or decreases in the levels of well-being (i.e. higher levels of
exhaustion or engagement), or do cycles generally keep the levels of well-being constant? We also do not
know whether it is possible, and, if so, how individuals may change the progress of a negative cycle and
turn it into a positive one. These questions not only require longitudinal data that allow testing cycles and
spirals over time, but also advanced theory.
Second, we suggest in JD-R theory that well-being and performance are the outcomes of factors at
the individual (job function) level but also at the team or even the organizational level. Several studies have
provided evidence for such a claim. However, the empirical evidence is still scarce and scattered. We need
more empirical evidence regarding whether a factor at the organizational level consistently acts as buffer or
exacerbator of the effects on lower levels, or whether main effects are more important, for instance that a
HRM policy directly influences the well-being of an individual. In addition, and in line with Bakker (2015),
multilevel theories may differentiate between trait and state variables, integrate employee personality in the
model, and outline how stable and dynamic variables interact. From a theoretical point of view, multi-level
constructs result in a better understanding of psychological phenomena unfolding within organizations.
From a practical point of view, knowledge gathered by following a multi-level approach can help guide the
development of more effective interventions. We do not only need more systematic research on cross-level
effects, but we also need better theoretical arguments explaining why and how factors at the higher level of
the organization are important for processes occurring at the lower level.
Third, we have recently integrated employee behaviors in JD-R theory and have shown how
employees may modify their job demands and resources through job crafting and self-undermining. In this
chapter, we focused explicitly on self-undermining (involved in the negative cycle) and job crafting
(involved in the positive cycle). Demerouti (2015) suggests that individuals may use various strategies –
methods or plans that people choose to achieve a goal or solve a problem, which generally involve some
planning or marshaling of resources for their most efcient and effective use. According to Demerouti,
600
examples of such strategies are coping, recovery from work-related effort, as well as selection,
optimization, and compensation. Additionally, strength use (van Woerkom, Oerlemans, & Bakker, 2016)
and proactive vitality management (Op den Kamp, Tims, Bakker, & Demerouti, 2017) may be important
for the development of well-being. Integrating individual strategies into JD-R theory has both theoretical
and practical implications and may uncover which behaviors help individuals to function well in a specific
work context. These behaviors can then be stimulated or trained (see also, Bakker, 2017).
Implications for Practice
JD-R theory has been shown to be particularly influential in organizational practice as it helps
practitioners and organizations to recognize the factors related to well-being (health and motivation) and to
optimal functioning. Given the complexity of contemporary jobs, recognizing the demands and resources
that may harm health or diminish motivation is one important but not sufficient step for improving wellbeing.
Based on JD-R theory, we think that several steps are necessary in order to influence organizational
life positively.
First, regular monitoring of the prevailing job demands and resources as well as of well-being is
essential in order to recognize possible problems that require action. Second, as suggested, organizational
level factors (HR practices, organizational climate) but also team-level factors (leaders’ behavior, team
demands and resources) may influence processes at the lower level. Therefore, constantly improving work
processes and introducing employee friendly and high performance practices represent top-down
interventions that can be beneficial for both the individual employee and organizational performance. In
addition, training of supervisors to help them generate resources for their employees and teams to be
resourceful to each other is a possible intervention at the middle level.
Third, we showed that in addition to managers also individual employees influence the conditions at
work such that these conditions are optimized. Training employees to redesign their own jobs such that
these jobs are better tailored to employees’ preferences and abilities (through job crafting trainings; Van
den Heuvel et al., 2015; Van Wingerden et al., 2016) may complement top-down approaches and make
them even more effective. In order to achieve this, organizations need to enhance the relevant skills of their
employees (through training or role modeling), and give employees the decision-authority to engage in job
crafting.
Conclusion
In this chapter, we presented JD-R theory, which is appropriate to specify the factors that are
related to the well-being of individual employees. Central in this theory are the prevailing job demands and
job resources, which are responsible for health and motivational outcomes, respectively. However, we also
provided evidence that the well-being of individuals triggers them to influence their job demands and
resources (cf. job crafting and self-undermining), and these bottom-up influences operate next to the topdown
changes initiated by the organization or its leaders. Moreover, we discussed that these processes
occur over time in the form of positive or negative cycles, and that factors from different levels of the
organization are involved in these processes. Although further research is needed to test its propositions,
JD-R theory has clear implications for practice. We hope that JD-R theory will continue to inspire
researchers and practitioners in organizations who aim to improve employee well-being and effective
organizational functioning.
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Wisdom and Well-Being
By Hannes Zacher, Leipzig University, & Ursula M. Staudinger, Columbia Aging Center, Columbia
University
Citation
Zacher, H., & Staudinger, U. M. (2018). Wisdom and well-being. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
The literature that has investigated the association between wisdom and well-being has yielded conflicting
results ranging from positive associations through zero to even negative associations. After defining and
explaining the central constructs, the chapter will provide a review of this literature. While it seems
intuitively right that wisdom should be positively associated with well-being, researchers have argued that
the association depends on the type of definition and measurement of wisdom and well-being. The chapter
will review and discuss the association between wisdom and well-being as a function of the notion and
assessment of these constructs and will interpret the seemingly contradictory findings accordingly.
Furthermore, the distinction between two types of positive personality development, that is, adjustment and
growth, is used to help clarify the relationship between wisdom and subjective and psychological wellbeing.
We conclude with a discussion of directions for future research on wisdom and well-being.
Keywords: Wisdom, Well-Being, Adjustment, Growth
Wisdom, “the pinnacle of insight into the human condition and about the means and ends of a
good life” (Baltes & Staudinger, 2000, p. 122), has been a topic of rapidly growing interest among
psychological scientists studying human development, potential, and well-being (Bangen, Meeks, & Jeste,
2013; Karelitz, Jarvin, & Sternberg, 2010; Staudinger & Glück, 2011). The goal of this chapter is to review
and discuss the relationship between wisdom and subjective well-being (SWB) and psychological wellbeing
(PWB). To this end, we first outline different definitions and operationalizations of wisdom.
Importantly, in this chapter we focus on what has been called explicit theories of wisdom (i.e., how to
conceptualize and measure wisdom of individuals based on psychological theorizing) and not on implicit
theories of wisdom (i.e., how ordinary people perceive and define wisdom and wise people; cf. Staudinger
& Glück, 2011). Next, we describe important indicators of SWB and PWB, the distinction between these
constructs, as well as two types of positive personality development (i.e., adjustment and growth;
Staudinger & Kunzmann, 2005). Third, we present the results of a review of empirical studies on wisdom,
SWB, and PWB published over the past two decades. We conclude the chapter by integrating the findings
of our review with the concepts of adjustment and growth, and we outline directions for future research.
Wisdom
Psychological scientists have investigated the ancient notion of wisdom for nearly 40 years (e.g.,
Baltes & Staudinger, 1993; Clayton & Birren, 1980; Sternberg, 1990). In their comprehensive review of the
psychological wisdom literature, Staudinger and Glück (2011) broadly distinguished between general and
personal wisdom. While general wisdom entails insights into life in general, without personal concern,
personal wisdom involves people’s insights into their own lives, including personal problems (Staudinger,
2013; Staudinger, Dörner, & Mickler, 2005).
General Wisdom
Research on general wisdom is based on cognitive research on expertise (i.e., expert knowledge
and judgment), and adopts a performance-based view on wisdom in that wise people are assumed to
possess and demonstrate greater knowledge and better judgment about fundamental life matters compared
to less wise people. The most prominent approach to general wisdom is the Berlin wisdom paradigm. The
Berlin wisdom paradigm defines wisdom as expertise in the fundamental pragmatics of life, that is,
exceptional knowledge and judgment about the human conditions as well as life planning, management,
and understanding (Baltes & Smith, 1990; Baltes & Staudinger, 2000, see Staudinger & Glück, 2011, for a
review of other approaches to general wisdom). With regard to well-being, Baltes and Staudinger (2000)
argued that wisdom “involves good intentions. It is used for the well-being of oneself and others” (p. 123).
The paradigm proposes five wisdom criteria, including rich factual knowledge, rich procedural knowledge,
lifespan contextualism, relativism of values and life priorities, and recognition and management of
uncertainty. Wisdom is assessed by scoring participants’ responses to difficult and existential life problems,
such as the potential suicide of a friend. The validity of the Berlin wisdom paradigm has been demonstrated
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in numerous studies (e.g., Baltes, Staudinger, Maercker, & Smith, 1995; Staudinger, Lopez, & Baltes,
1997; Staudinger, Maciel, Smith, & Baltes, 1998; Staudinger, Smith, & Baltes, 1992). These studies have
shown that performance-based wisdom is typically normally distributed, with mean values below the midpoint
of the measurement scale. With regard to the association with well-being, the paradigm predicts that
SWB is a necessary but not sufficient condition in terms of predicting general wisdom-related performance.
Personal Wisdom
Research on personal wisdom is typically based on scholarship in the fields of personality
psychology and personality development, and both performance-based and self-report measures have been
developed to assess personal wisdom (see Staudinger & Glück, 2011, for a review of different approaches).
Mickler and Staudinger (2008) define personal wisdom as the realization of one’s own potential while
considering the well-being of others and society. Based on the Berlin wisdom paradigm, they developed
and validated a performance-based measure of personal wisdom that involves scoring participants’ answers
to a difficult personal problem according to five criteria (i.e., self-knowledge, growth and self-regulation,
interrelating the self, self-relativism, and tolerance of ambiguity). With regard to well-being, Mickler and
Staudinger (2008) proposed that SWB is a necessary but not sufficient precondition with regard to
predicting personal wisdom.
The most prominent self-report measures of personal wisdom were developed by Ardelt (2003)
and Webster (2003). Ardelt (2004) defines wisdom as the combination of cognitive (e.g., desire to
understand the truth), reflective (e.g., taking multiple perspectives), and affective (e.g., an empathetic
attitude) personality characteristics. She developed a self-report scale, the Three Dimensional Wisdom
Scale (3D-WS) to measure these wisdom dimensions. Webster (2007) defines wisdom as “the competence
in, intention to, and application of critical life experiences to facilitate the optimal development of self and
others” (p. 164). He developed the Self-Assessed Wisdom Scale (SAWS) to measure five dimensions of
wisdom (i.e., experience, emotion regulation, reminiscence and reflectiveness, openness, and humor). As
personal wisdom is a socially desirable characteristic, scores on these scales are typically highly skewed
toward the positive end of the measurement scales. Theoretically, both Ardelt (2004) and Webster (2007)
predict that their measures of self-reported wisdom are positively associated with indicators of SWB.
Consistently, both measures have demonstrated a substantial association with measures of SWB. A
common criticism of self-report scales of wisdom concerns their validity, in that wisdom involves critical
self-reflection and, therefore, wise people may not rate themselves higher on these scales than less wise
people (Staudinger & Glück, 2011). Moreover, when the same individuals are asked to rate both their
personal wisdom and their SWB, common method bias (or single source bias) is likely to be a problem, as
this approach can lead to artificially inflated correlations between self-reported constructs (Podsakoff,
MacKenzie, & Podsakoff, 2012).
Subjective and Psychological Well-Being
SWB (also sometimes referred to as “happiness”) involves individuals’ cognitive judgments and
affective reactions when they think about and evaluate the quality of their lives (Diener, 1984, 2000;
Diener, Suh, Lucas, & Smith, 1999). In empirical studies, the cognitive component of SWB is typically
operationalized as life satisfaction (Diener, Emmons, Larsen, & Griffin, 1985), and the affective
component of SWB is operationalized as the balance between experiences of positive and negative affect
(Watson, Clark, & Tellegen, 1988). Life satisfaction and affective balance SWB have been distinguished
from psychological well-being (PWB), which involves feelings of autonomy, growth, environmental
mastery, positive social relations, self-acceptance, personal growth, and purpose in life (Keyes, Shmotkin,
& Ryff, 2002; Ryff, 1989). This distinction is very similar to that the one between hedonic and eudaimonic
well-being (Ryan & Deci, 2001). Ryff and Keyes (1995) developed a self-report inventory of PWB to
measure the six dimensions of PWB just mentioned.
Building on research on personality development and well-being, Staudinger and Kunzmann
(2005) proposed two dimensions of positive personality development across the lifespan (see also
Staudinger & Kessler, 2009). In this approach, personality development toward adjustment entails
increases in life satisfaction, affect balance, as well as increases in the big five personality characteristics of
conscientiousness, agreeableness, and emotional stability (see Digman, 1990). Moreover, the PWB
dimensions of environmental mastery, positive relations, and self-acceptance are part of a broader
personality adjustment factor (Wink & Staudinger, 2015). Personality adjustment is conceived as the result
of individuals coping with normative developmental tasks and it enables individuals to function effectively
within societies. The second dimension, that is, personality development toward personality growth,
involves increases in openness to experience and the PWB dimensions of autonomy, personal growth, and
purpose in life (Wink & Staudinger, 2015). Personality growth involves experiences that go beyond societal
requirements, expectations, and structures. According to Staudinger and Kunzmann (2005), a certain level
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of adjustment is necessary, but not sufficient for growth to occur.
Researchers have argued that wisdom is conceptually closer to the notions of
psychological/eudaimonic well-being and personality growth than to subjective/hedonic well-being and
personality adjustment (Staudinger & Glück, 2011). Next, we review the empirical literature on wisdom
and well-being, with particular attention to specific operationalizations of both wisdom and well-being
across studies.
Review of the Empirical Literature
We conducted a literature review to identify empirical studies on wisdom and well-being. We
searched four common databases (i.e., Ebscohost, Google Scholar, PsycInfo, Web of Science) using the
following keywords in different combinations: wisdom, wise, well-being, wellbeing, psychosocial,
satisfaction, affect, and happiness. We screened out irrelevant studies based on the title and abstract (e.g.,
abstract that simply referred to “established wisdom in the field”). We also excluded non-empirical book
chapters and review articles (e.g., Ardelt, 2011; Ardelt & Ferrari, 2014; Baltes, Glück, & Kunzmann, 2002;
Knight & Laidlaw, 2009; Kramer, 2000). Overall, our search resulted in 28 relevant empirical studies.
These studies and their most important findings regarding wisdom and well-being are summarized in Table
1.
Table 1
Empirical Studies on Wisdom and Subjective Well-being (in the Same Order as Reviewed in the Text)
Authors and
Year
Sample and Design Operationalization
of Wisdom
Indicators of
Subjective Well-
Being
Main Results
Performance-Based Wisdom and Well-Being
1. Staudinger
et al. (1997)
125 adults between 19 and
87 years (mean age = 45.4
years); cross-sectional
design
Performancebased
general
wisdom (Berlin
wisdom
paradigm)
Psychological
well-being (Ryff
& Keyes, 1995)
Wisdom was associated with
personal growth, but not the
other indicators of
psychological well-being.
2. Kunzmann
and Baltes
(2003)
293 participants from
three age groups (93
young adults, 93 middleage
adults, and
107 older adults); crosssectional
design
Performancebased
general
wisdom (Berlin
wisdom
paradigm)
Positive and
negative affect,
positive affective
involvement
Wisdom was negatively related
to both positive and negative
affect, and positively related to
positive affective involvement.
3. Mickler and
Staudinger
(2008)
83 younger adults (ages
20–40) and 78 older adults
(ages 60–80); crosssectional
design
Performancebased
personal
wisdom (Berlin
wisdom
paradigm)
Life satisfaction,
positive and
negative affect,
agreeableness,
conscientiousness,
psychological
well-being
(composite of
autonomy,
mastery, and self-
acceptance)
Personal wisdom was unrelated
to indicators of subjective
well-being.
4. Glück et al.
(2013)
47 wisdom nominees and
123 control participants
between 26 and 92 years;
cross-sectional design
Self-reported
wisdom (3D-WS
and SAWS) and
performancebased
general
wisdom (Berlin
wisdom
paradigm)
Psychological
well-being (Ryff
& Keyes, 1995):
personal growth
and self-
acceptance
Both measures of self-reported
wisdom were positively related
to both indicators of wellbeing;
performance-based
wisdom was not significantly
related to well-being.
607
5. Wink and
Staudinger
(2015)
163 participants between
68–77 years of age; crosssectional
design
Performancebased
general
(Berlin wisdom
paradigm)
Personality
growth and
adjustment
Wisdom was positively related
to personality growth,
personality adjustment, and
generativity. The association
between wisdom and
adjustment/generativity were
mediated by growth.
6. Wink and
Helson (1997)
94 adults at age 54; crosssectional
design
Self-reported
wisdom (practical
wisdom scale
based on
adjective check
list) and observer
ratings of
transcendent
wisdom
Life satisfaction Wisdom measures were not
significantly associated with
life satisfaction.
7. Helson and
Srivastava
(2002)
92 participants at ages 21
and 61, and 201
participants at age 60;
longitudinal design
Wisdom
composite
consisting of selfreported
practical
wisdom, as well
as observer
ratings of
transcendent
wisdom and a
wisdom task
based on the
Berlin Wisdom
paradigm
Well-
being/adjustment
(feeling optimistic
and in good
health),
psychological
well-being (Ryff
& Keyes, 1995)
Wisdom was not significantly
related to wellbeing/adjustment,
and
positively related to personal
growth and positive relations
with others.
8. Grossmann
et al. (2013)
241 adults from three age
groups (25-40, 41-59, 60-
90 years); cross-sectional
design
Performancebased
general
wisdom (wise
reasoning)
Positive and
negative affect,
life and
relationship
satisfaction,
rumination,
longevity,
emotional
discourse patterns
Wise reasoning was associated
with greater life satisfaction,
less negative affect, better
social relationships, less
depressive rumination, more
positive vs. negative words
used in speech, and greater
longevity.Wise reasoning
mediated age-related
differences in well-being.
9. Shi, Ardelt,
& Orwoll
(2016)
66 wisdom nominees, 84
creativity nominees, and
92 controls (age range =
53-92 years, mean age =
71.3 years); crosssectional
design
Nominations Life satisfaction Wise and creative nominees
reported higher life satisfaction
than controls, even after
controlling for subjective
health.
Self-Reported Wisdom and Well-Being
10. Ardelt
(1997)
120 older women and men
from the 1968/69
Berkeley Guidance Study;
cross-sectional design
Self-reported
wisdom (3D-WS)
Life satisfaction Wisdom was associated with
life satisfaction above and
beyond objective conditions.
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11. Ardelt
(2000)
82 older women from the
1968/69 Berkeley
Guidance Study; crosssectional
design; same
sample as [10]
Self-reported
wisdom (3D-WS)
Life satisfaction Wisdom was associated with
life satisfaction above and
beyond objective conditions.
12. Le (2011) 123 community-dwelling
adults (age range = 39-96
years, mean age = 64
years); cross-sectional
design
Self-reported
wisdom (3D-WS)
Life satisfaction Wisdom was positively related
to life satisfaction.
13. Bergsma
and Ardelt
(2012)
7,037 respondents who
participated in an internet
survey; cross-sectional
design
Self-reported
wisdom (3D-WS)
Hedonic
happiness
Wisdom, particularly reflective
wisdom, was positively related
to hedonic happiness
(especially among people with
lower levels of education).
14. Mansfield
et al. (2010)
85 community members
(age range = 18-71 years,
mean age = 39.8 years);
cross-sectional design
Self-reported
wisdom (3D-WS)
Psychological
well-being (Ryff
& Keyes, 1995)
Wisdom was not significantly
related to psychological well-
being.
15. Taylor et
al. (2011)
176 participants ranging in
age from 18-68 years (M
= 36.60); cross-sectional
design
Self-reported
wisdom (3D-WS;
SAWS)
Life satisfaction,
forgiveness
Both wisdom scales were
positively related to life
satisfaction and forgiveness.
16. Ardelt et
al. (2013)
144 community residents,
nursing home residents,
and hospice patients
between 56-98 years;
cross-sectional design
Self-reported
wisdom (3D-WS)
Life satisfaction,
cheerfulness,
absence of
depressive
symptoms, death
fear
Wisdom was combined with
measures of mastery and
purpose in life. This
psychosocial strengths
measure predicted SWB above
and beyond objective life
conditions.
17. Ardelt and
Edwards
(2015)
156 older community
residents (mean age = 71
years) and 41 older
hospice patients and
nursing home residents
(mean age = 77 years);
cross-sectional design;
sample overlap with [16]
Self-reported
wisdom (3D-WS)
Life satisfaction,
cheerfulness,
absence of
depressive
symptoms
Wisdom was positively related
to SWB, especially in the
nursing home and hospice
sample; the relationship was
partially mediated by purpose
in life, both directly and via a
sense of mastery.
18. Ardelt
(2016)
123 older community
residents (mean age = 72
years); two-wave study
over 10 months
Self-reported
wisdom (3D-WS)
Subjective wellbeing,
mastery,
purpose in life,
and physical well-
being
Wisdom was positively related
to subjective well-being,
mastery, purpose in life, and
physical well-being at Time 2.
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19. Ardelt and
Jeste (2016)
994 adults aged 51–99
years (M = 77) from the
Successful AGing
Evaluation (SAGE) study;
cross-sectional design
Self-reported
wisdom (3D-WS)
Positive mental
health, happiness,
and life
satisfaction
Wisdom, in particular
reflective wisdom, was
positively related to subjective
well-being and buffered the
negative relationship between
adverse life events during the
previous year and current well-
being.
20. Etezadi
and Pushkar
(2013)
360 retired older adults
(mean age = 61 years,
range = 45–79 years);
cross-sectional design
Self-reported
wisdom (3D-WS)
Positive and
negative affect
Coping strategies, perceived
control, and life engagement
mediate the positive
relationships of wisdom with
positive and negative affect.
21. Zacher et
al. (2013)
175 university students
(age range = 17-41 years,
mean age = 21 years) and
400 online workers (age
range: 16-74 years, mean
age = 31.6 years); crosssectional
designs
Self-reported
wisdom (3D-WS)
Life satisfaction,
positive and
negative affect
Positive relationships of
wisdom with life satisfaction
and positive affect (but not
negative affect) became
weaker and non-significant
when emotional intelligence
was controlled.
22. Webster et
al. (2012)
512 adults (age range =
17-92 years; mean age =
46.46 years); crosssectional
design
Self-reported
wisdom (SAWS)
Mental health
(emotional,
psychological,
and social well-
being)
Wisdom was positively related
to mental health, above and
beyond certain demographic
and personality characteristics.
23. Webster et
al. (2014)
512 adults (age range =
17-92 years, mean age =
46.46 years); crosssectional
design; same
sample as [22]
Self-reported
wisdom (SAWS)
Mental health
(emotional,
psychological,
and social well-
being)
Wisdom was positively related
to mental health.
24. Proctor et
al. (2011)
135 undergraduate
university students; crosssectional
design
Self-reported
wisdom (Values-
In-Action
strengths
classification
system)
Life satisfaction,
positive and
negative affect
General strengths use is
positively associated with
subjective well-being, but
wisdom is one of the leastendorsed
strengths.
25. Moraitou
and Efklides
(2012)
446 adults (age range =
20-80 years); crosssectional
design
Self-reported
wisdom (Wise
Thinking &
Acting
Questionnaire)
Positive and
negative affect
Wisdom was positively related
to positive affect and not
significantly related to negative
affect.
26. Krause and
Hayward
(2015a)
1,535 older adults who
participated in a
nationwide survey (mean
age = 63.3 years); crosssectional
design
Self-reported
practical wisdom
(newly developed
7-item scale)
Life satisfaction Practical wisdom was
positively related to life
satisfaction.
610
27. Krause and
Hayward
(2015b)
1,535 older adults who
participated in a
nationwide survey (mean
age = 63.3 years); crosssectional
design; same
sample as [26]
Self-reported
practical wisdom
(newly developed
7-item scale)
Self-esteem, hope Practical wisdom is positively
related to self-esteem and hope.
28. Krause
(2016)
1,535 older adults who
participated in a
nationwide survey (mean
age = 63.3 years); crosssectional
design; same
sample as [26, 27]
Self-reported
practical wisdom
(newly developed
7-item scale)
Life satisfaction Wisdom and humility relate
positively to life satisfaction;
the relationship between
humility and life satisfaction is
stronger for wise people.
Note. 3D-WS = Three-Dimensional Wisdom Scale (Ardelt, 2003); SAWS = Self-Assessed Wisdom Scale
(Webster, 2003).
Performance-Based Wisdom and Well-Being
We identified five studies based on the Berlin wisdom paradigm that investigated relationships
between performance-based wisdom and indicators of well-being (Table 1). First, Staudinger et al. (1997)
recruited a diverse sample of 125 participants that were assessed using measures of general wisdom-related
performance, fluid and crystallized intelligence, personality (including the big five and Ryff’s six
indicators of PWB), and constructs at the intelligence-personality interface (e.g., creativity, cognitive
style). Results showed that of the six PWB indicators, only personal growth was positively related to
general wisdom-related performance at the bivariate level. Using backward regression analysis, openness to
experience and psychological mindedness, but none of the PWB indicators remained significant predictors
of wisdom.
Second, using a sample of nearly 300 participants from three age groups, Kunzmann and Baltes
(2003) found that people scoring high in general wisdom-related performance experience both positive and
negative affect less frequently than people scoring lower. These researchers suggested that wise people
have a more realistic and less positively biased views on life, and that they also possess greater emotionregulation
skills. Furthermore, Kunzmann and Baltes (2003) also reported that people with high levels of
wisdom-related performance had a higher degree of affective involvement, which involves experiences
such as being interested and feeling inspired, as well as values related to greater personal growth, life
insight, societal engagement, others’ well-being, and ecological protection.
Third, using a sample of 83 younger and 78 older adults, Mickler and Staudinger (2008) examined
associations of performance-based personal and general wisdom with several indicators of SWB. They
found non-significant relationships between personal wisdom-related performance and life satisfaction,
positive and negative affect, and personality adjustment (i.e., conscientiousness, agreeableness,
environmental mastery, self-acceptance, and autonomy). General wisdom-related performance was also not
significantly related to the SWB indicators, with the exception of a moderate positive relationship with life
satisfaction (with and without controlling for age). Mickler and Staudinger (2008) concluded that SWB is
not a sufficient condition to attain personal wisdom. In contrast, they suggested that critical self-reflection
and coping with negative events and emotional states which often are linked with lowering subjective wellbeing
are more important for achieving personal wisdom.
Fourth, Glück et al. (2013) included 47 wisdom nominees and 123 control participants in their
study on relationships between different well-established measures of wisdom including both self-report
and performance measures. Their analysis showed that performance-based general wisdom as measured
with the Berlin Wisdom paradigm was not significantly related to Ryff’s PWB indicators of personal
growth and self-acceptance.
Fifth, Wink and Staudinger (2015) investigated the relationship of performance-based general
wisdom with personality adjustment and growth as well as generativity (i.e., the concern for establishing
and guiding the next generation; Erikson, 1950) in a sample of 163 older men and women. They found
positive correlations between wisdom and personality growth, personality adjustment, and generativity.
Personality growth was operationalized as a composite including openness to experience, psychological
mindedness, and a sense of well-being derived from growth, purpose in life, and autonomy. Personality
adjustment was a composite of life satisfaction, high agreeableness and conscientiousness, low neuroticism,
and a sense of well-being derived from positive relations with others, self-acceptance, and environmental
mastery. Using latent path analysis, Wink and Staudinger (2015) further showed that the associations
611
between personality adjustment and wisdom and between generativity and wisdom were mediated by
personality growth. According to the authors, these findings suggest that wise people are capable of
balancing different personal strengths and interests, and that this integration takes place by pursuing
personality growth via personality adjustment.
We identified four additional studies that used interview ratings by trained observers and a
nomination procedure to measure wisdom. In an early study, Wink and Helson (1997) found no significant
relationship of life satisfaction with self-reported practical wisdom and transcendent wisdom ratings by
trained observers. A later longitudinal study by Helson and Srivastava (2002) examined how wisdom
related to well-being at ages 21 and 60, and to change in well-being from age 21 to age 61. The researchers
created a wisdom composite by averaging scores on self-reported practical wisdom, as well as observer
ratings of transcendent wisdom and responses to a wisdom task based on the Berlin Wisdom paradigm.
SWB was measured in terms of adjustment (i.e., feeling optimistic and in good physical and mental health)
with the California Psychological Inventory, and PWB was measured with the Ryff scales. Results showed
that wisdom was unrelated to SWB at age 21 and change in SWB between ages 21 and 61. In contrast,
wisdom was positively associated with Ryff’s PWB indicators of personal growth and positive relations
with others at age 60.
A study by Grossmann, Na, Varnum, Kitayama, and Nisbett (2013) with 241 adults from different
age groups measured performance-based wisdom as the extent to which people use pragmatic reasoning to
solve social conflicts. The researchers found that wise reasoning was positively related to life and social
relationship satisfaction, the use of more positive vs. negative words in speech, and longevity, and
negatively related to negative affect and depressive rumination (correlations ranged from .17 to .33). The
pattern of relationships remained the same when socioeconomic factors, verbal abilities, and personality
traits were statistically controlled. Wise reasoning further mediated age-related differences in participants’
well-being, particularly among older adults. Finally, a recent study by Shi, Ardelt, and Orwoll (2016)
examined personal wisdom and creativity using nominations by others. These researchers included 66
wisdom nominees, 84 creativity nominees, and 92 control participants in their study. Results showed that
people nominated as wise and creative reported higher life satisfaction than control participants, even after
controlling for subjective health.
In summary, performance-based general as well as personal wisdom do either show none or only
weak associations with SWB in the sense of a necessary but not sufficient condition for wisdom. The same
holds true for the adjustment-related component of PWB. In contrast, the growth-related component of
PWB shows substantial associations with performance-based wisdom measures.
Self-Reported Wisdom and Well-Being
The vast majority studies in our literature review examined associations between wisdom and wellbeing
using self-report scales of wisdom (see Table 1). This outcome is likely due to the ease and
practicability of administering self-report wisdom scales (Staudinger & Glück, 2011). Of the 22 studies
using self-report scales, 13 studies used Ardelt’s (2003) 3D-WS, four studies used Webster’s (2003) SAWS
(note that one study included both the 3D-WS and the SAWS; Glück et al., 2013), and six studies using
other self-report scales (e.g., practical wisdom scale, the values-in-action strengths classification system,
wise thinking and acting questionnaire).
Ardelt’s 3D-WS and well-being. In two early studies, Ardelt (1997, 2000) used the 3D-WS to
examine the relationship between self-reported wisdom and life satisfaction in samples drawn from the
1968/69 Berkeley Guidance Study. Both studies showed that self-reported wisdom was positively
associated with life satisfaction, above and beyond other factors such as age, self-reported physical health,
socioeconomic status, financial situation, physical environment, and social involvement. Subsequent studies
using the 3D-WS have largely reported consistent results for life satisfaction. Specifically, using a sample
of 123 community-dwelling adults, Le (2011) found that self-reported wisdom was positively related to life
satisfaction. Similarly, Bergsma and Ardelt (2012) reported that self-reported wisdom was positively
related to a measure of “hedonic happiness” in a large sample of over 7,000 adults who completed an
online survey (9.2% explained variance). Contrary to the authors’ expectations, a study with 85 community
members by Mansfield, Mclean, and Lilgendahl (2010) did not find a significant relationship between selfreported
wisdom and a composite of the PWB scales by Ryff and Keyes (1995). This finding may be due
to the PWB scales measuring both personality adjustment and growth (cf. Wink & Staudinger, 2015), and
an aggregate score does not take this important distinction in to account. However, a study by Taylor,
Bates, and Webster (2011) with 176 adults found positive associations between the 3D-WS and both PWB
and a measure of forgiveness.
Glück and colleagues (2013) found positive and moderate relationships between self-reported
wisdom measured with the 3D-WS and Ryff’s PWB indicators of personal growth and self-acceptance. In
612
a study with 144 community residents, nursing home residents, and hospice patients, Ardelt, Landes,
Gerlach, and Fox (2013) found that a psychosocial strengths measure (including self-reported wisdom,
mastery, and purpose in life) predicted various indicators of SWB (i.e., life satisfaction, cheerfulness,
absence of depressive symptoms, and low fear of death), above and beyond demographic variables (i.e.,
age, gender, race, and marital status) and objective life conditions (i.e., physical health, socioeconomic
status, financial situation, social involvement). In a later article using a similar sample, Ardelt and Edwards
(2015) reported that self-reported wisdom (3D-WS) was positively associated with the same composite of
SWB, and that this relationship was partially mediated by purpose in life, both directly and via a sense of
mastery.
Ardelt (2016) conducted the only longitudinal study on self-reported wisdom and SWB to-date.
Using a sample of 123 community residents who provided data at two measurement points separated by 10
months, she found that self-reported wisdom measured at Time 1 was positively related to SWB, mastery,
purpose in life, and physical well-being measured at Time 2. In another recent study, Ardelt and Jeste
(2016) found that self-reported wisdom, and especially the reflective component, was positively related to
SWB (i.e., life satisfaction, happiness, and positive mental health). Moreover, high levels self-reported
wisdom buffered the negative association between adverse life events during the previous year and current
SWB.
Two studies examined variables that may account for positive relationships between self-reported
wisdom (as assessed by the 3D-WS) and SWB. In a sample of 360 older adults, Etezadi and Pushkar
(2013) found that coping strategies, perceived control, and life engagement mediated the positive
relationship between self-reported wisdom and positive affect, and perceived control and life engagement
mediated the negative relationship between self-reported wisdom and negative affect (controlling for social
desirability, health, and sociodemographic variables). Zacher, McKenna, and Rooney (2013) examined
self-reported wisdom, emotional intelligence (i.e., the perceived ability to perceive and regulate emotions
in oneself and others; Law, Wong, & Song, 2004) in two samples of 175 university students and 400 online
workers. They reported that the positive associations of self-reported wisdom with life satisfaction and
positive affect (but not negative affect) became weaker and non-significant when controlling for emotional
intelligence in the analyses.
In summary, research using the 3D-WS has generally found positive associations between selfreported
wisdom and various indicators of well-being. Taking into account, however, that self-reported
wisdom, as measured by the 3D-WS, do not differentiate wisdom nominees from matched controls (Glück
et al., 2013), limits the meaning of this finding for improving our understanding of the association between
wisdom and well-being. Also, research on the potential explanations for these relationships (e.g., coping,
emotional intelligence) is still in its infancy, and the vast majority of studies are based on cross-sectional
instead of longitudinal designs.
Webster’s SAWS and well-being . Four articles using Webster’s (2003) SAWS found positive
associations between self-reported wisdom and well-being. Specifically, Taylor et al. (2011) found that the
SAWS was positively related to both PWB and forgiveness. In two articles using the same large sample of
512 adults, Webster, Westerhof, and Bohlmeijer (2012) and Webster, Bohlmeijer, and Westerhof (2014)
reported that the SAWS was positively related to mental health (operationalized as emotional,
psychological, and social well-being), above and beyond several demographic (i.e., age, gender, education)
and personality characteristics (i.e., neuroticism, extraversion, and openness to experience). Finally, Glück
and colleagues (2013) found small positive relationships between the SAWS and Ryff’s PWB indicators of
personal growth and self-acceptance.
Wisdom as values-in-action and well-being. Research using self-report measures of wisdom
other than the 3D-WS has also generally found support for positive associations between self-reported
wisdom and indicators of well-being. First, using the values-in-action strengths classification system
(Peterson & Seligman, 2004), Proctor, Maltby, and Linley (2011) examined the association between
endorsement of strengths, including wisdom, and SWB indicators in a sample of undergraduate students.
While more endorsement of strengths was positively associated with life satisfaction and positive affect,
and negatively associated with negative affect, wisdom was one of the least-endorsed strengths and,
therefore, its unique association with SWB was not assessed. Second, Moraitou and Efklides (2012)
assessed self-reported wisdom with the “wise thinking and acting questionnaire,” which they developed for
their study. The items of the questionnaire ask participants to rate their practical wisdom, integrated
dialectical thinking, and awareness of uncertainty in life. Using a sample of 446 adults, the authors found a
positive relationship with positive affect, but no significant relationship with negative affect.
Practical wisdom and well-being. In a series of articles based on the same sample of 1,535
middle-aged and older adults, Krause and Hayward examined relationships between a newly developed
613
self-report measure of practical wisdom and various indicators of well-being. Practical wisdom was
conceptualized as a higher-order factor comprising self-beliefs regarding learning from mistakes,
understanding others, forgiveness, helping others, tolerance of ambiguity, and perspective taking. Krause
and Hayward (2015a) found that frequency of church attendance was associated with greater self-reported
practical wisdom which, in turn, was positively associated with life satisfaction, experienced awe of god,
sense of connectedness with others, and life satisfaction. Krause and Hayward (2015b) reported that selfreported
practical wisdom was positively associated with self-esteem and hope. Krause (2016) showed that
self-reported wisdom is positively associated with humility values and life satisfaction, and that the
relationship between humility and life satisfaction is boosted by greater levels of self-reported wisdom.
In summary, most research on self-reported wisdom and well-being has found positive
relationships, independent of the specific operationalizations of self-reported wisdom and SWB. With
regard to PWB the findings are mixed as some studies use an average across the six scales and other studies
use individual subscales. It seems that personal growth and self-acceptance, indicators of personality
maturation towards growth, show moderately positive associations with self-reported wisdom.
Discussion
We reviewed empirical research on the association between wisdom and well-being as a function
of the wisdom and the well-being measures under study. In this section, we discuss the five main
conclusions of our review. First, performance-based measures of wisdom show a small but significant
association with SWB. More specifically, it is general wisdom scores that demonstrate this relationship
whereas personal wisdom does not seem to be related with SWB. This pattern of results may highlight the
fact that while being better able to provide advice to others may be associated with better SWB, higher
levels in self-related insight and wisdom seem to come at a cost in terms of SWB. This interpretation is
supported by the finding that the maturity aspects of psychological wellbeing are more strongly linked with
personal than general wisdom (Mickler & Staudinger, 2008).
Second, self-reported wisdom measures show a substantial positive relation with well-being. While
research using performance-based measures of wisdom found no significant or only weak associations with
SWB, most research using self-report questionnaires to assess wisdom found moderate to strong positive
relationships with SWB. There appear to be some differences between self-report measures of wisdom with
regard to their associations with well-being (cf. Glück et al., 2013). However, further research using reports
from multiple sources (e.g., friends, coworkers) as well as a broad variety of well-being indicators is
needed to better understand the reasons for these initial results. The same applies to the association between
wisdom and PWB. In particular, it seems that the scales of self-acceptance and personal growth show a
positive association.
Third, the distinction between personality maturation toward adjustment and/or growth (Staudinger
& Kunzmann, 2005) may be useful to clarify the seemingly contradictory findings on wisdom and SWB.
As noted earlier, personality adjustment includes not only personality characteristics such as
conscientiousness and agreeableness, but also common indicators of SWB (i.e., life satisfaction and
affective balance). In contrast, personality growth includes openness to experience and certain dimensions
of psychological well-being (i.e., autonomy, personal growth, and purpose in life; Ryff & Keyes, 1995).
Wisdom researchers have argued that valid measures of wisdom should be more strongly related to
personality growth than to personality adjustment, and that personality adjustment may be only a necessary
but not sufficient precondition for the development of wisdom (Staudinger & Glück, 2011; Sternberg &
Jordan, 2005; Wink & Staudinger, 2015). Indeed, consistent with this assumption, Wink and Staudinger
(2015) found that personality growth mediated the association between personality adjustment and
performance-based general wisdom.
Fourth, the validity of self-report measures of wisdom may be problematic, as truly wise
individuals may not rate themselves particularly high on these instruments (Staudinger & Glück, 2011).
And indeed, in a nomination study of wisdom, the self-report measures were not able to differentiate the
wisdom nominees from matched controls (Glück et al., 2013). Instead, individuals scoring high on selfreported
wisdom may be those who respond in a socially desirable way, which is consistent with
personality adjustment. This may explain why most studies reported positive relationships between selfreported
wisdom and various indicators of SWB, whereas relationships between self-reported wisdom and
PWB, and particularly the growth-oriented dimensions of Ryff and Keyes’ (1995) PWB measure, where
mixed. Future research assessing performance-based wisdom, self-reported wisdom, personality maturation
towards adjustment and towards growth is needed to verify these assumptions.
Finally, our review of the literature showed that most studies relied on cross-sectional designs.
Thus, it is important that researchers conduct more longitudinal studies to examine the causal direction of
relationships, as well as the (co-)development of wisdom and well-being over time.
614
In conclusion, researchers have argued for a long time that wisdom does not necessarily come with
happiness, but is an indicator of personality growth and a meaningful life (Staudinger & Glück, 2011;
Weststrate & Glück, in press). Indeed, gains in wisdom, in particular personal wisdom, may result from
overcoming negative challenging life events (Mickler & Staudinger, 2008; Staudinger et al., 2005). Our
review showed that performance-based measures of general wisdom are weakly related to indicators of
SWB and this association is fully mediated by personality maturation towards growth. Thus, in future
research on wisdom and well-being, it will be important to distinguish, both conceptually and empirically,
between self-report and performance measures of wisdom as well as between general and personal
wisdom. The distinction between personality maturation toward growth (represented by performance-based
wisdom measures) and personality maturation toward adjustment (which is represented by most of the selfreport
wisdom scales) seems to be helpful in understanding some of the seemingly conflicting evidence in
the literature.
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What’s Love Got to Do With it? Romantic Relationships and
Well-Being
By Jessica Kansky, University of Virginia
Citation
Kansky, J. (2018). What's love got to do with it?: Romantic relationships and well-being. In E. Diener,
S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
Social relationships are one of the most important facets of well-being and one of the strongest links with
both physical and psychological health. Romantic relationships specifically may have a particularly intense
impact on well-being due to heightened emotions and cognitions within these close relationships. Prior
research has identified the importance of romantic relationships and relationship status for well-being and
psychological adjustment, yet less has considered the specific qualities that play a role in this link. I will
consider the specific relationship qualities that may particularly benefit or damage well-being. Intimate
relationships become increasingly important as individuals transition from dating in adolescence,
cohabitating in emerging adulthood, and ultimately marriage in adulthood. I review the extensive literature
on the benefits of healthy romantic relationships on well-being, highlighting how each influences the other
during different developmental stages of relationships from initiation to dissolution adjustment. I also point
to the increasing diversity of understudied romantic experiences (i.e., online, casual, polyamory, arranged
versus self-selecting marriages, sexual minority) and highlight important unanswered questions this
proliferation leaves open. Future directions for further understanding the unique role of romantic
experiences in its association with well-being will be discussed.
Keywords: Romantic relationships, relationship quality, well-being
One of the strongest links to subjective well-being is the quality of one’s social relationships (Frisch,
2005; Oishi, Diener, & Lucas, 2007). The happiest people report having the most satisfying social lives.
Specifically, people with high positive affect and life satisfaction are more likely to engage in more social
activities including spending more time talking to others, have more friends, and feel closer to their friends
(Diener & Seligman, 2002; Mehl, Cazire, Holleran, & Clark, 2010). Those with strong social ties reap
myriad benefits beyond its critical link to well-being. For example, those with healthy social relationships
tend to live longer and have better physical health (House, Landis, & Umberson, 1988; Umberson & Karas
Montez, 2010), have greater job satisfaction and work performance, academic competence (Resnick et al.,
1997; Chambel & Curral, 2005; Cotton, Dollard, & de Jonge, 2002), and are more creative (Perry-Smith,
2006). Psychological health including depression, anxiety, substance use, and feelings of self worth and
self esteem has been strongly tied to social relationships (Cutrona & Russell, 1987; Diener & Seligman,
2002; Kawachi & Berkman, 2001; Richards, Hardy, & Wadsworth, 1997; Taylor, Doane, & Eisenberg,
2013).
There are several theories as to why happy individuals benefit from having strong ties with others.
Developing social resources has evolutionarily been beneficial for survival (Buss, 2000). Those in a
supportive group have been able to live longer and provide for their offspring in ways that living in solitude
could not provide. Humans at their core have needs to belong and to develop close social relationships
(Baumeister & Leary, 1995). Therefore, it is unsurprising that meeting these needs and having close social
ties is linked to well-being. An alternate perspective is that happy people attract social resources and can
also build relationships with others when in positive moods. This is most similar to Fredrickson’s broadenand-build
model (1998, 2001), which proposes that positivity allows one to expand resources including
one’s social network and relationships because they already have a strong foundation of met needs
(Fredrickson, Cohn, Coffey, Pek, & Finkel, 2008). Being in a positive mood allows individuals the
flexibility and freedom to explore and invest in social relationships because they do not have concern over
immediate or imminent survival. Happy individuals can devote more time towards building close social
relationships increasing their social capital that is especially useful in future times of stress.
Yet another perspective lies in a functional account of emotions, which proposes that affect guides
behaviors through a series of rewards and punishments, and that social relationships and interactions can
be especially important influences in generating informative and evocative functions (Keltner & Haidt,
2001; Keltner & Kring, 1998). Positive emotions indicate that a particular interaction or behavior is going
well and sends a reward signal to the individual to reinforce that behavior. This in turn leads to a greater
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likelihood of repeating the behavior in the future. Rather than simply providing feedback as information,
positive feelings can also evoke positive feedback from others through pleasant conversations, activities, or
games which all serve to continue building healthy relationships.
Rather than simply having a large social network, social relationship quality may contribute to
well-being in important ways. Social support specifically refers to the sense of being taken cared of,
listened to, loved, and appreciated. Social support has been identified as a critical driver of both physical
and mental health benefits (Cohen, 2004). Not only is the presence of social relationships important for
well-being, but the quality, especially the perceived satisfaction and level of support, from these
relationships influences our psychological health as well.
Romantic Relationships:
Similarities and Differences with Other Relationships
While social relationships in general have been extensively studied and linked to well-being, the
focus for this chapter will be on one specific type of relationship. In particular, romantic relationships may
be uniquely and powerfully related to subjective well-being. Romantic relationships differ from general
social relationships in important ways, yet researchers have acknowledged the difficulty in defining a
romantic relationship. One primary feature distinct between friendships and romantic relationships is a
marked difference in intimacy (Moss & Schwebel, 1993). While close friends share intimate details of their
lives, the role of intimacy involved in romantic relationships is typically deeper and more pervasive.
Combined with intimacy, passion and commitment are two additional features central to romantic
relationships (Sternberg, 1986). Ultimately, Sternberg proposes that the total amount of love depends on the
overall sum of the three components, and the type of love depends on the strength of each component
relative to each other. Depending on the relative strength of each feature, a relationship may be classified
by different types of love including romantic, companionate, empty, infatuation, and consummate.
Further, all three components (i.e., intimacy, passion, and commitment) are associated with
relationship satisfaction and their links to satisfaction vary over time as relationships evolve. All three
components increase over time as couples transition from casual dating to monogamous dating to
engagement (Gao, 2001). However, passion and intimacy tend to decline while commitment increases for
married couples over time (Acker & Davis, 1992). Although all three components are associated with
relationship satisfaction, commitment has the strongest association (Acker & Davis, 1992). Greater
mismatches among the three qualities within couples are associated with greater relationship dissatisfaction
(Sternberg, 1986; 1988; Sternberg & Barnes, 1985).
In addition to Sternberg’s triangular theory of love, many other researchers have attempted to define
and conceptualize love in order to empirically study this important relational quality. Many theorists have
identified two major types of love: passionate and companionate (Fehr, 1988; Fischer, Shaver, &
Carnochan, 1990; Hatfield & Rapson, 1993; Hatfield, Rapson, & Martel, 2007). Passionate love is often
referred to as infatuation, erotic love, or romantic love. It is usually characterized by sexual feelings and
intense emotions such as jealousy, passion, and anxiety. Alternatively, companionate love typically
involves less intense emotions and is characterized by attachment, intimacy, trust, closeness, and
commitment. Companionate love has also been referred to as storgic love (Lee, 1988). While theorists
have proposed that passionate love declines over time and companionate love remains stable, empirical
work has generally found a small decline in both types over time for married couples (Sprecher, 1999;
Hatfield, Pillemer, O’Brien, & Le, 2008). Each type of love has an important role in a successful marriage
and may account for different relationship and well-being qualities. For example, passionate love more
strongly predicts positive and negative affect, while companionate love more strongly predicts life
satisfaction (Kim & Hatfield, 2004). Hendrick, Dicke, and Hendrick (1988) found that passionate and
companionate love are both positively related to relationship satisfaction.
In addition to the two main types of love, Lee (1977) defined six types of love styles. The three
main love styles are eros (i.e., rooted in strong physical attraction), ludus (i.e., viewing love as a game,
noncommittal), and storge (i.e., friendship evolving into a romantic relationship). The next three styles are
combinations of the three main love styles including mania (i.e., possessive, jealous, anxious attachment to
a partner reflected via the combination of eros and ludus), pragma (i.e., practical approach reflected via the
combination of ludus and storge), and agape (altruistic love reflected via the combination of eros and
storge). Hendrick and Hendrick (1986) developed a 42-item Love Attitude Scale that categorizes
individuals into one of these six love styles. Subsequent analyses have linked the eros and agape styles to
higher commitment and relationship satisfaction, while ludus is negatively associated with satisfaction and
commitment (Frazier & Esterly, 1990; Hendrick, Hendrick & Adler, 1988; Morrow, Clark, & Brock,
1995). Individuals within couples who have different love styles tend to report lower quality relationships
and satisfaction (Davis & Latty-Mann, 1987). In a cross-cultural study, the storge love style predicted
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subjective well-being in the United States and Portugal while eros and mania predicted well-being in the
Mozambican sample (Galinha, Oishi, Pereira, Wirtz, & Esteves, 2014). Cross-cultural interpretations of
love styles and their impact on well-being remain a vastly understudied area, but early findings point to
important potential differences. Overall finding suggest that although there are many different types of love
for romantic partners, those with eros and agape styles and those who have similar love styles tend to
report better relationship quality and higher satisfaction.
The many different definitions and conceptualizations of love complicate attempts to assess the role
of love in romantic relationship stability, quality, and satisfaction. Yet, the intimacy and intense feelings of
love continue to be cited as qualities that make romantic relationships from other types of social
relationships. In addition to these potentially unique aspects, romantic relationships typically include a
sexual component as well, which set this type of relationship apart from others. Indeed, romantic love
includes passion, exclusiveness, sexual intimacy and physical attraction, all of which are typically absent in
other forms of love such as platonic or companionate (Gooch, 1989, Kaplan & Keys, 1997; Monsour,
Betty, & Kurzweil, 1993). Although sexual attraction may be present in platonic love, it is typically not
acted upon compared to the frequent utility of sexual attraction and intimacy in romantic love (Davis &
Todd, 1982; Monsour et al., 1993). However, more recently there has been a rise of nonromantic sexual
relationships (i.e., hookups; friends with benefits) especially common among emerging adults,
complicating attempts to define a romantic relationship (see Garcia, Reiber, Massey, & Merriwether, 2012
for a review; Furman & Shaffer, 2011; Paul, McManus, & Hayes, 2000).
A primary framework for understanding romantic relationships comes from attachment theory
(Bowlby, 1973; 1980). A crucial extension of Bowlby’s attachment theory, which originally was proposed
to explain parent-child relationships, is that adults may develop analogous attachment patterns to romantic
partners. Similar to a mother being seen as the primary attachment figure in childhood, a romantic partner
may be seen as the primary attachment figure in adulthood (Hazan & Shaver, 1987; Prager, 1995). The
quality of interactions with an attachment figure when in distress helps shape the attachment style one is
likely to adapt. A secure base, proximity seeking, and safe haven, which are characteristics of a strong and
secure attachment figure, are transferred from parents to romantic partners. Eventually, a romantic partner
will replace a parental figure as the primary attachment figure (Hazan & Shaver, 1994). When an
attachment figure is perceived as emotionally unavailable or unreliable, one may be more prone to feel
insecure and have doubts about the relationship; when a close other is perceived as available, reliable,
trustworthy, and willing to provide support when needed, one is more likely to feel a sense of secure
attachment, intimacy, support, and nurturance (Cassidy, 2000; Hazan & Shaver, 1994; Mikulincer, Shaver,
& Pereg, 2003). Thus, adults in romantic relationships form a unique attachment to their romantic partner
as compared to their level of commitment and engagement with other social partners.
Beyond attachment style, romantic love, intimacy, and passion, there are myriad other
characteristics that might define a romantic relationship. Researchers have disagreed about what constitutes
a romantic relationship, especially for unmarried couples. This is in part due to the changing norms of how
people are defining their own relationships in the gray area of dating prior to a committed marriage during
an era of proliferation of dating terms. I also want to acknowledge that this chapter will mainly focus on
heteronormative relationships – mainly heterosexual populations that hold the Westernized view of
relationship development towards self-selecting marriages. This is partially due to a lack of well-being
research on alternate forms of relationships as well as due to lack of space to consider all relationship
forms in the scope of this chapter. I will very briefly describe an overview of the research, and lack thereof,
on “nontraditional romantic relationships” such as polyamory, online dating, arranged marriages, and
sexual minority groups. Therefore, for the purposes of this chapter, a romantic relationship will be
considered to be one, monogamous, self-selecting, committed relationship between two individuals. In the
sections that follow, I will expand on the idea of attachment, intimacy, commitment, passion, and others as
important characteristics of romantic relationships and how they may relate to individual well-being and
relationship satisfaction.
The Basics: Are Romantic Relationships Linked to Well-Being?
In general, research has identified romantic relationships specifically as being uniquely related to
subjective well-being. Marriage has been cited as one of the leading sources of both support and stress for
adults (Walen & Lachman, 2000). Specifically, marriage has been linked to lower psychological distress
and higher well-being in adulthood as well (Diener, Gohm, Suh, & Oishi, 2000; Efklides, Kalaitzidou, &
Chankin, 2003; Glenn & Weaver, 1979; Holder, 2012; Wu & Hart, 2002). Even prior to marriage, romantic
relationships are linked to one’s overall sense of subjective well-being (Campbell, Simpson, Boldry, &
Kashy, 2005; Dush & Amato, 2005; Keyes & Waterman, 2003). It is not simply the involvement in a
romantic relationship that may account for the link to well-being, but the quality of that relationship as well
(Myers, 2000).
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In late adolescence, teens report feeling the greatest levels of support but also perceiving the
greatest amount of conflict from their romantic partners as compared to from their peers or parents (Furman
& Shomaker, 2008). While social relationships across the lifespan are important for well-being, romantic
relationships gain in importance and salience as a major aspect of one’s identity steadily throughout late
adolescence, young adulthood, and eventually adulthood (Giordano, Longmore, & Manning, 2001; SeiffgeKrenke,
2003; Umberson & Karas Montez, 2010). It will be critical to discuss how romantic experiences
influence well-being and vice versa as individuals’ needs, goals, and values in a relationship
developmentally change over time. Additionally, there are developmental differences in romantic
relationships across the lifespan, which can also change the strength of the link between intimate
relationships and well-being. The developmental differences of romantic experiences and their association
with well-being will be discussed.
Given the developmental perspective of the centrality of maintaining intimacy within a romantic
relationship in young adulthood, it is not surprising that one’s relationship status and quality of their
romantic partnership are linked to physical and mental health. Prior findings consistently point to the
marriage benefit in terms of less mental illness, distress, substance abuse, physical health complaints,
mortality, and morbidity (Gove, 1972; Horwitz, White, & Howell-White, 1996; Umberson, 1987; Waite,
1995). Romantic relationships generally are sources of high well-being, intimacy, companionship, and
happiness for emerging adults prior to marriage as well (Berry & Willingham, 1997; Demir, 2010; Diener
et al., 2000; Johnson, Kent, & Yale, 2012).
Let’s Get Specific:
What Qualities are Linked to Well-Being?
We see growing evidence that it is not simply relationship status that accounts for the benefits for
well-being. The quality of a romantic relationship as well as how satisfied one is with their relationship
and partner are both essential to assess as well. Subjective well-being encompasses affect and global life
satisfaction judgments; however, it can also include subjective evaluations of specific life domains
including social relationships, work performance, or citizenship. Prior findings suggest that global
subjective well-being and domain-specific relationship satisfaction are highly correlated, which one would
expect given the strong link between well-being and relationships. Relationship quality has been found to
positively correlate with well-being in terms of more satisfied individuals reporting higher levels of
happiness, life satisfaction, and positive affect and lower levels of negative affect (Dush & Amato, 2005;
Dyrdal, Roysamb, Nes, & Vitterso 2011; Love & Holder, 2015). Importantly, relationship satisfaction is
associated with higher levels of subjective well-being regardless of relationship status (Dush & Amato,
2005). Indeed, feeling satisfied with one’s relationship status, regardless of what that relationship status is,
predicts higher life satisfaction but is less tied to emotional and psychological well-being (Adamczyk,
2017). Interestingly, relationship satisfaction has been linked to idealistic, rather than realistic, views of a
romantic partner (Murray, Holmes, & Griffin, 1996) pointing to a potential positivity bias towards partners
among those high in relationship satisfaction.
Relatedly, sexual satisfaction has been another relationship domain that is linked to relationship
quality, satisfaction, and well-being. In a review, Sprecher and Cate (2004) found that sexual satisfaction is
significantly related to relationship stability and quality. Prior findings also indicate that changes in sexual
satisfaction are linked to changes in relationship satisfaction, love, and commitment to a partner in
unmarried couples (Sprecher, 2002). Key components of the link between sexual and relationship
satisfaction is likely communication and sexual expression (Sprecher, Metts, Burleson, Hatfield, &
Thompson, 1995). Given the importance of intimacy that is a hallmark and defining feature of romantic
relationships compared to its role in other social relationships, it is not surprising that sexual satisfaction is
an important characteristic. Being able to communicate with a partner about sexual needs and to receive
what one desires are both important aspects of high levels of sexual and relationship satisfaction, and this
communication is likely highly linked to overall intimacy.
Many other important qualities beyond intimacy emerge as essential factors for overall well-being.
Poor marital quality has been linked to poor immune and endocrine functioning, depression, anxiety, and
problem behaviors (Kiecolt-Glaser & Newton, 2001; Sampson, Laub, & Wimer, 2006; Umberson &
Williams, 1999). High conflict and hostile relationships are linked to poor mental health reflected in greater
rates of depression, anxiety, aggression, and substance abuse (Hawkins & Booth, 2005; Horwitz,
McLaughlin, & White, 1998; Umberson, Williams, Powers, Liu, & Needham, 2006; Whisman, 2007).
Demir (2008) found that for emerging adult couples, emotional security and companionship were the
strongest predictors of happiness and when combined with the qualities of reliable alliance, help, selfvalidation,
and intimacy, accounted for 13% of the variance in happiness. In adulthood, commitment, trust,
and intimacy in romantic relationships emerge as being especially highly related to subjective well-being
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(Drigotas, Rusbult, & Verette, 1999; Mehta, Walls, Scherer, Feldman, & Shrier, 2016; Uysal, Lin, Knee, &
Bush, 2012). We begin to see that while there are common qualities that are beneficial across
developmental stages, it is worthwhile to assess which qualities may be more influential and important than
others for unmarried versus married couples.
Another key mechanism that acts as a moderator between many relationship qualities and overall
well-being is attachment style. A secure attachment style is strongly linked to high quality romantic
relationships (Banse, 2004; Simpson, 1990) and securely attached individuals report relationships with
greater commitment, trust, and satisfaction (Simpson, 1990) which are qualities that have previously been
identified as critical to relationship satisfaction and well-being. Secure attachment has been linked to higher
levels of subjective well-being, while insecure attachment styles (i.e., avoidant and anxious) are negatively
related to well-being (La Guardia, Ryan, Couchman, & Deci, 2000; Li & Fung, 2014; Schiffrin, 2014; Van
Buren & Cooley, 2002). Attachment security can also predict relationship stability, or whether unmarried
couples tend to remain together or break up (Duemmler & Kobak, 2001) as well as whether one chooses to
enter into a committed relationship (Schindler, Eagundes, & Murdock, 2010). Specifically, attachment
anxiety is associated with a strong desire to commit while attachment avoidance is related to lower levels of
commitment and willingness to enter a committed relationship (Morgan & Shaver, 1999; Schindler et al.,
2010).
Those with secure attachment styles may feel most comfortable and confident in themselves and the
relationship which allows the healthy qualities of trust, communication, intimacy, and others to foster more
naturally and to a greater extent compared to individuals who are avoidant or anxious in their attachment
styles. Indeed, Leak and Cooney (2001) found that secure attachment was positively related to self
determination and that together they both related to higher well-being and mental health. Further, the link
between secure attachment and satisfaction was mediated by commitment and intimacy, again pointing to a
strong link between attachment styles and other romantic qualities (Madey & Rodgers, 2009). Following
from above, insecure attachment styles were related to lower levels of sexual satisfaction (Butzer &
Campbell, 2008).
Finally, what many people may consider to be crucial in romantic relationships, in addition to
support, sexual intimacy, and healthy conflict management, love is also a component of relationship and
individual well-being and satisfaction. Married couples tend to identify love as being the most important
quality that makes them feel close, connected, and committed to their spouse (Riehl-Emde, Thomas, &
Willi, 2003). Even in unmarried couples, love emerges as strongly linked to satisfaction (Hendrick et al.,
1988). Love, romance, and intimacy are all positively associated with well-being but this link may be
stronger for females than males (Love & Holder, 2015). While beyond the scope of this chapter, gender
differences in romantic experiences are important to consider in relationship research, which I will
highlight in the concluding section on future directions.
Overall, it is clear that intimate partnerships greatly impact one’s physical and emotional health in
both positive and negative ways depending on relationship status and quality. It is also evident that many
of these relationships are bidirectional – higher quality relationships can benefit well-being while higher
levels of well-being foster qualities that can enhance relationship satisfaction and functioning. Although
many couples report love as being the most important aspect of their relationship satisfaction, findings also
point to the qualities of attachment, support, intimacy, companionship, and sexual satisfaction as being
critical to relationship satisfaction and well-being as well.
The Mechanism: Why are Romantic Relationships
Linked to Well-Being?
Romantic relationships may uniquely contribute to well-being for several reasons. First, successfully
navigating romantic relationships is identified as a primary developmental task of emerging adulthood
(Arnett, 2000; Roisman, Masten, Coatsworth, & Tellegen, 2004). Happiness has been associated with
success in different life domains, especially the domains that are most pertinent to the appropriate
developmental stage (Lyubomirsky, King, & Diener, 2005). Thus, failure to meet the goal of maintaining
intimacy with a romantic partner during early adulthood may be linked to poorer well-being, self-esteem,
and psychological health. Indeed, abstaining from dating until early adulthood has been linked to a host of
negative outcomes including poor psychosocial functioning (Lehnart, Neyer, & Eccles, 2010; Rauer, Pettit,
Lansford, Bates, & Dodge, 2013).
One possible mechanism for the link between relationship status and well-being is that maintaining
a romantic relationship is seen as a socially appealing marker of success during early adulthood. Those
unable to form close relationships with others by adulthood in the form of a committed, monogamous
relationship may be more likely to experience lower well-being and greater levels of mental distress.
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Evidence for this mechanism is suggested by cultural findings on the link between marriage and wellbeing.
Diener and colleagues (2000) found that the benefit of being married was smaller in collectivist
nations and in nations where there was a high tolerance of divorce. They argue that in cultures where
divorce is considered taboo, unmarried individuals’ well-being may be impacted in a greater magnitude as
compared to nations where divorce is more common and acceptable (Gibbs, 1969; Glenn & Weaver, 1988;
Stack, 1990). Thus, in societies where committed romantic relationships are valued as a cultural norm,
failing to meet this goal may lead to poor psychological health and well-being. Related to developmental
goals, one’s well-being may be more impacted by failing to meet the intimacy goal during young adulthood
as compared to earlier in adolescence. Thus, the context and cultural expectations for romantic
relationships are likely powerful influences on the link between intimate relationships and well-being.
Beyond the socially constructed need to find one committed romantic partner in adulthood,
marriage may serve a more general and universal human need: social support. Recall that evolutionarily,
developing social support and resources is beneficial for survival (Baumeister & Leary, 1995; Buss, 2000).
Prior researchers have suggested that marriage can fulfill this need via providing companionship and thus
fighting against loneliness (Glenn, 1975; Glenn & Weaver, 1979; Rook, 1984). Indeed, Fromm (1956)
suggested that the concept of love developed over time as a way to combat loneliness and emotional and
social isolation. Thus, the evolutionary benefit of general social support may naturally extend to the
positive outcomes associated with having a strong, supportive marital partner (for a review see Eastwick,
2016). Happy people may be more likely to attract and maintain a healthy romantic relationship while
unhappy individuals struggle to find a suitable partner or to maintain a stable relationship over time (Diener
& Diener McGavran, 2008). Further, mate selection theorists have identified a preference for pleasant
personality characteristics (Buss & Barnes, 1986) indicating those with high well-being may be more
desirable mates. Successful romantic relationships may have also provided the financial, emotional, and
social support associated with greater likelihood of successful reproduction as well. Married individuals
benefit from having a partner to share life’s burdens, problems, and struggles with which can help boost
trust and intimacy between partners and decrease the distress linked to life’s hardships (Gove, Style, &
Hughes, 1990; Williams, 1988). Not only are partners beneficial for providing support when one is
undergoing stress, but they also provide the opportunity to reciprocate with support as well. Providing care,
love, and support for a spouse may boost one’s self-esteem, provide greater purpose in one’s life, and
increase sense of mastery over a salient developmental task (Gove et al., 1990).
Providing instrumental support via division of labor in the home may also be beneficial for
individuals as they share the burden of everyday tasks rather than solely providing everything for
themselves. Blumstein and Schwartz (1983) found couples who agree on a suitable division of labor for
financial and household responsibilities report the highest relationship satisfaction. Further, marital
happiness and conflict were both related to satisfaction with division of labor (Suitor, 1991). One’s own
hours and perception of partner’s hours spent on housework and paid work all seem to influence marital
satisfaction (Stevens, Kiger, & Riley, 2001). Sharing of household and work tasks is an ongoing discussion
and negotiation for many couples, highlighting the importance of communication. The perception of why
partners provide help is also linked to well-being and satisfaction. For example, sacrifices and helping with
approach motives (i.e., focusing on increasing positive outcomes) is associated with greater well-being and
higher relationship quality, while those with avoidance motives (i.e., focusing on decreasing negative
outcomes) is linked to lower well-being, relationship quality, and relationship stability (Gable & Reis,
2001; Impett, Gable, & Peplau, 2005). Thus, agreeing on division of labor and interpretation of partner’s
motives are important for relationship and individual well-being. With more dual-income families
becoming the common family dynamic, more research regarding division of labor and subsequent
satisfaction for relationship and individual well-being is warranted.
Beyond the role of a romantic partner in providing social support when conflict, distress, or other
negative events arise, the utility of sharing positive news and confiding in a romantic partner may also help
explain the link between relationship status and well-being. While friends can also provide social outlets to
share good news, a romantic partner is often someone of greater trust, intimacy, emotional connection, and
importance. Thus, romantic partners may particularly benefit from sharing and responding to positive news.
Gable, Gonzaga, and Strachman (2006) found that how partners respond to good news is more closely
related to relationship stability and well-being than how they respond to bad news. In particular,
responding in an active-constructive manner as compared to passive-constructive, passive-destructive, or
active-destructive, is important for individual and relationship well-being and satisfaction (Gable, Reis,
Impett, & Asher, 2004). Thus, capitalizing on the positive experiences and events a romantic partner
discloses may boost relationship functioning and well-being.
Yet another potential mechanism that explains the well-being and romantic relationship link is felt
understanding. Feeling understood by others generally is associated with higher well-being (Reis, Clark, &
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Holmes, 2004; Reis, Lemay, & Finkenauer, 2017). Related to capitalizing on sharing positive news with a
romantic partner, perhaps feeling heard and understood also helps boost well-being between individuals in
a relationship. The impact of feeling understood by a romantic partner may be particularly salient for wellbeing,
relationship satisfaction, and conflict management between partners (Gordon & Chen, 2016). In
general, knowing a partner well is linked to greater intimacy and relationship satisfaction (Gottman, 1994;
Gottman, Coan, Carrere, & Swanson, 1998; Swann, De la Ronde, & Hixon, 1994). Knowing a partners’
attitudes and well-being is associated with greater relationship satisfaction, perceived support from partner,
and life satisfaction and lower negative affect and depression (Moore & Diener, in press; Moore, Uchino,
Baucom, Behrends, & Sanbonmatsu, 2017). Thus, feeling understood by a partner may provide greater
emotional support, intimacy, and other important mental health and relationship benefits that lead to greater
well-being overall. A romantic partner may be the closest, most intimate relationship someone has in his or
her adult life. The felt understanding one perceives from this romantic partner may thus especially impact
well-being, as feeling understood by the person one is closest too seems to carry more weight than felt
understanding from strangers, friends, or other social relationships. A successful, healthy romantic
relationship in which both partners perceive great understanding and familiarity with each other is likely to
have psychological and relationship benefits.
Alternative explanations exist that may account for the link between romantic involvement and
well-being that focus on the quality of these partnerships. Happy individuals may be able to provide for
their partner in terms of support, intimacy, and emotional expressivity compared to individuals lower in
well-being. Positive affect has been linked to greater feelings of intimacy and warmth toward a partner
while negative affect is linked to decreased feelings of intimacy (Berry, Willingham, & Thayer, 2000;
Demir, 2008; Gleason, Iida, Shrout, & Bolger, 2008; Prager, 1995; Sprecher, 1999; Williams, Connolly, &
Segal, 2001). While intimacy is one example, it is likely that affect may play a role in the development of
trust, sexual satisfaction, support, communication, and companionship which have all been identified as
important relationship qualities linked to well-being.
Romantic Developmental Differences:
Adolescence, Emerging Adulthood, and Adulthood
Adolescence
Although research on romantic relationships and well-being have largely focused on marriage in
adulthood, it is widely recognized that romantic experiences come online much earlier and that these
experiences are influential to concurrent well-being and romantic development over time. Adolescents
begin experimenting with dating as early as 12 years old when about 25% report involvement in some type
of romantic relationship with an average relationship duration of 5 months (Carver, Joyner, & Udry, 2003).
Nearly half of adolescents report being involved in a romantic relationship by the age of 15; by age 18,
more than three quarters of adolescents report engaging in romantic involvement and on average, these
relationships last much longer – on average 20 months (Carver et al., 2003).
Per a review of romantic development theories by Meier and Allen (2014), normative romantic
exploration begins in early adolescence, which typically involves group dating and is relatively short in
duration. In mid-adolescence, multiple short-term relationships with an increased emphasis on sexual and
emotional intimacy become common. By late adolescence and into adulthood, one exclusive, sexual,
committed relationship becomes the normative experience. Early adolescent romantic experiences are
characterized as being more affiliative and companionate as compared to late adolescent romantic
relationships which tend to be more committed, supportive, and loving (Shulman & Kipnis, 2001; Shulman
& Scharf, 2000).
While maintaining intimacy within romantic relationships is not considered a primary
developmental goal until emerging adulthood, teens personally consider navigating intimate relationships
as important for their psychosocial lives. The majority of teenagers report at least one exclusive
relationship experience by the end of adolescence and the prevalence and importance of engaging in
intimate relationships increases during the transition into young adulthood (Carver et al., 2003; Furman &
Shomaker, 2008; Giordano, Manning, Longmore, & Flanigan, 2012; Reis, Lin, Bennett, & Nezlek, 1993).
Romantic relationships have been linked to both negative behaviors and poor psychological health and
well-being (Davies & Windle, 2000; Furman & Collins, 2009; Neemann, Hubbard, & Masten, 1995;
Thomas & Hsiu, 1993; van Dulmen, Goncy, Haydon, & Collins, 2008; Zimmer-Gembeck, Siebenbruner, &
Collins, 2004).
However, romantic exploration is common and normative among adolescents, and thus teen dating
also been linked to positive developmental outcomes as well in terms of later well-being and future
romantic relationships. Evidence suggests that while romantic experiences in early adolescence are more
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strongly linked to problematic behaviors, the link decreases in magnitude for romantic experiences that
occur in late adolescence (Neemann et al., 1995). Instead, adolescents who were involved in romantic
relationships by the end of high school were more likely to marry and cohabitate in early adulthood (Raley,
Crissey, & Muller, 2007). High quality adolescent romantic relationships have been linked to positive
relationships and a range of psychosocial benefits including positive commitment in relationships in early
adulthood, fewer externalizing problems, higher levels of social support, and greater social competence,
self-worth, and self-esteem (Collibee & Furman, 2015; Collins, 2003; Connolly, Craig, Goldberg, &
Pepler, 1999; Connolly & Konarski, 1994; Furman, Low, & Ho, 2009; Masten et al., 1995; Raley et al.,
2007; Seiffge-Krenke, 2003; van Dulmen et al., 2008). Specifically, support and self-disclosure have been
identified as essential predictors of successful adolescent relationships (Hansen, Christopher, & Nangle,
1992). Overall, we see that romantic relationships begin during adolescence and that these early
experiences can have important links to well-being and romantic trajectories over time.
Emerging Adulthood
Successfully navigating intimate relationships is recognized as a primary developmental task of
early and emerging adulthood (Barry, Madsen, Nelson, Carroll, & Badger, 2009; Clark & Beck, 2010;
Erikson, 1982; Roisman et al., 2004). Indeed, recent societal changes have delayed the age of first marriage
for young adults, which has led to the relatively new conceptualization of emerging adulthood as a distinct
developmental stage ranging from ages 18 through 29 (Arnett, 1998, 2000). Especially common during this
time is a period of exploration as individuals aim to blend romantic, personal, and career lives together
which partially accounts for the delayed entrance into long-term stable relationships (Shulman & Connolly,
2013). Thus, emerging adulthood can be characterized by a series of romantic relationships that vary in the
extent of commitment, intensity, and intimacy (Cohen, Kasen, Chen, Hartmark, & Gordon, 2003).
However, the trend for emerging adults to explore several romantic options during the 20-something
years does not necessarily mean that these romantic experiences are not as important or influential for
development and well-being. Remaining single or engaging in a series of various types of non-committal
romantic relationships (i.e., hooking up, friends with benefits, casual dating) is often a conscious,
intentional decision for these young adults (Katz & Schneider, 2013; Paul, McManus, & Hayes, 2000;
Puentes, Knox, & Zusman, 2008; Shulman & Connolly, 2013). Emerging adults may place career, travel,
or friendship priorities ahead of finding “the one” and as such the characteristic romantic exploration is a
choice rather than due to a deficit in connecting with a partner for a monogamous relationship. Shulman
and Connolly (2013) argue that young adults may deliberately choose to pursue work or school goals rather
than continue or initiate a long-term, monogamous, committed romantic relationship. Other researchers
have an optimistic view of this romantic exploratory period. For example, Marcia (2002) suggests that it is
healthy to explore available options prior to making a decision and this can extend to romantic exploration
for a marriage partner as well.
Perhaps paradoxically, emerging adults are still placing a high value on romantic relationships
during this time frame. Schulenberg, Bryant, and O’Malley (2004) found that emerging adults report
stronger ties between their well-being and successfully meeting the goal of romantic exploration and
intimacy, than between well-being and progress in reaching other developmentally-salient goals such as
avoiding substance use, maintaining close friendships, reaching educational achievements, or achieving
financial independence. For those in a romantic relationship, their partner is often identified as a greater
influence on well-being compared to parents or friends (Demir, 2010; Meeus, Branie, van der Valk, & De
Wied, 2007). Compared to in adolescence, high quality romantic relationships in emerging adulthood are
more strongly linked to well-being and relationship satisfaction, indicating a developmental shift in
centrality of intimate relationships to well-being (Collibee & Furman, 2015; Meeus et al., 2007). There is
some evidence suggesting that college students who are in committed relationships report higher levels of
well-being compared to their single peers (Braithwaite, Delevi, & Fincham, 2010) and that those young
adults who get and stay married report higher levels of well-being compared to their single peers (Horwitz,
White, & Howell-White, 1996). Further, college students often report their romantic relationship as the
closest and most meaningful type of relationship they have (Snyder, Berscheid, & Omoto, 1989). However,
others have found little to no difference in long-term impacts on well-being between those who have casual
hook up relationships and those in committed romantic relationships (Furman & Collibee, 2014;
Vrangalova, 2014).
Given that emerging adulthood is a relatively new developmental stage, it is not surprising that we
see mixed findings for whether and to what extent the characteristic romantic exploration is related to
concurrent or long-term well-being. One particularly interesting area of open research will be to further
assess whether different types of romantic relationships (casual relationships, open relationships, friends
with benefits, hooking up) impact individual and interpersonal development and well-being to different
degrees.
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Adulthood
Historically, research on romantic relationships has focused on married couples. As outlined above,
prior findings consistently point to what may be referred to as the marriage benefit. Namely, that being
married serves a positive function in general such that those who are married tend to reap benefits in terms
of both physical and mental health (Dush & Amato, 2005; Wu & Hart, 2002). However, even in adulthood,
we see varying relationship stages and transitions taking place that are each related to well-being in
different ways. Those who are married are happier than those who are cohabitating, casually dating,
monogamously dating, or rarely date (Dush & Amato, 2005). Even after controlling for relationship
satisfaction, relationship status in adulthood was found to remain linked to well-being. Further, with each
increase in relationship commitment level, there was an increase in subjective well-being. It is hypothesized
that it is this growing level of commitment and stability that accounts for the differences in well-being
(Brown, 2000; Dush & Amato, 2005)
In addition, married adults report greater levels of happiness compared to those who are single,
divorced, separated, or cohabitating (Dush, Taylor, & Kroeger, 2008; Glenn & Weaver, 1979; Gove et al.,
1990; Mastekaasa, 1994; Myers, 2000; Proulx, Helms, & Buehler, 2007; Stack & Eshleman 1998).
Helliwell (2003) found that being married is associated with the highest subjective well-being while being
separated is linked to the lowest ratings of well-being with the divorced and widowed falling in between. In
a meta-analysis, Proulx and colleagues (2007) found a moderate link (r = .37) between marital quality and
well-being.
The relationship between high quality romantic relationships and well-being becomes stronger with
age (Segrin, Powell, Givertz, & Brackin, 2003; Simon & Barrett, 2010). Interestingly, married couples tend
to experience a decrease in life satisfaction over the course of their marriage; however those couples with
high marital happiness reported the smallest declines (Dush et al., 2008). Whether individuals report high
general life satisfaction and happiness was strongly linked to whether the marriage was classified as high,
middle, or low in marital happiness indicating that individuals who have a high baseline well-being carry
over their happiness into their marriage with potential lasting effects. While it was well documented that
married individuals are happier, more recent research calls for attention to be shifted from relationship
status to relationship quality in explaining the potential for a marriage benefit to exist.
Romantic Dissolution and Divorce: Implications on Well-Being
Thus far, I have presented research suggesting the benefits of having a healthy marriage, yet there
are many societal changes that complicate the “simple,” Westernized notion of choosing a marriage partner
for life and assuming that this choice would relate to high levels of well-being. In emerging adulthood,
romantic exploration is key, which brings along a series of relationships including breakups. In adulthood,
the divorce rate is steadily climbing adding to the challenge of redefining romantic relationships in mid to
late adulthood as well. Therefore, it is worthwhile to consider the opposing situation and its impact on
well-being. It seems obvious that divorce or a breakup would be stressful, but how much of an impact does
dissolution have on well-being?
A romantic breakup has been cited as one of the worst types of traumatic experiences (Frazier &
Hurliman, 2001). Yet, it is relatively common during emerging adulthood such that nearly 40% of young
adults report at least one breakup over a 20-month period (Rhoades, Dush, Atkins, Stanley, & Markman,
2011). Romantic dissolutions have been linked to serious negative outcomes including anxiety, depression,
posttraumatic stress, substance abuse, self esteem, poor physical health, and finally low life satisfaction
(Chung et al., 2002; Fine & Harvey, 2006; Fleming, White, Oesterle, Haggerty, & Catalano, 2010;
Lewandowski, Aron, Bassis, & Kunak, 2006; Monroe, Rohde, Seeley, & Lewinsohn, 1999; Rhoades et al.,
2011). Given the normative process of romantic exploration during young adulthood, researchers have
begun exploring the possible benefits of nonmarital dissolutions. The scarce findings begin supporting the
idea that individuals can experience post-traumatic growth, personal growth, and positive emotions
following a breakup (Lewandowski & Bizzoco, 2007; Tashiro & Frazier, 2003). Further, they may report
increased satisfaction and higher relationship quality in their next romantic relationship (Kansky & Allen,
2017).
While in emerging adulthood, dissolutions are considered to be common and there are mixed
findings regarding their detriment to psychological well-being, breakups in adulthood in the form of
divorce may have more significant negative impacts. Indeed, adults cite divorce as one of the most stressful
events they may encounter in their lifetime (Kitson & Morgan, 1990). Compared to those married,
individuals who are divorced or separated report lower levels of psychological well-being, greater alcohol
abuse, and greater use of psychological treatment (Fine & Harvey, 2006; Gove & Shin, 1989; Kitson &
Morgan, 1990; Waite, 1995). Further, individuals who had previously divorced report lower levels of wellbeing
even if they remarry indicating the potential for long-term negative impacts on psychological health
627
(Richards et al., 1997). Interestingly, individuals report similar decreases in well-being following
dissolution whether they were married or only cohabitating in adulthood (Wu & Hart, 2002). This indicates
that dissolution of adult committed relationships even outside the context of marriage may impact wellbeing
similarly, even though the benefits of being in a marriage compared to cohabitating have differential
impacts on well-being.
However, other findings indicate that divorce may not alone account for the lower reports of wellbeing.
Rather, individuals tend to report greater distress and lower well-being over several years prior to
the divorce compared to those in happy, stable relationships (Mastekaasa, 1995). This indicates that prior to
filing for divorce, there may be a difference between those who stay married and those who part ways in
terms of their pre-transition stress and well-being levels. Rather than individuals suffering from divorce or
separation, their well-being may be negatively impacted from conflict, poor communication, and distress
related to a low quality relationship prior to the actual event of a divorce.
Attachment is an important moderator of many relationship qualities and satisfaction, and again we
see evidence for its role as a moderator in post divorce adjustment. Divorced individuals report greater
distress compared to their married counterparts, but only if the divorced report insecure attachment styles
(Birnbaum, Orr, Mikulincer, & Florian, 1997). Another dimension that moderates the relationship between
divorce status and well-being may be how quickly one finds a new, fulfilling, committed relationship. For
example, those who cohabitate with a new partner during the first year following the initial separation
report higher well-being compared to those who choose to live alone (Mastekaasa, 1994). Yet another
moderator may be cultural acceptance of divorce. As mentioned earlier, the impact of being unmarried or
divorced on well-being may be greater in cultures where divorce is less socially acceptable (Diener et al.,
2000; Glenn & Weaver, 1988). While in general it has been accepted that married individuals are happier
than divorced adults, many qualities and adjustment behaviors may paint a more complex picture.
The New Normal? Diverse
Romantic Relationships and Well-Being
As indicated previously, most research on romantic relationships and well-being has focused on
Western, heteronormative relationships. In particular, adult married populations are often the focus of
research in this realm. However, romantic experiences exist in many alternate forms, and recent empirical
attention has attempted to capture the range of romantic relationships and how it relates to well-being.
Sexual Minority Status
For example, sexual minority relationships have increasingly gained empirical support to
understand their similarities and differences with heterosexual romantic relationships. Given the finding of
a marriage benefit for heterosexual couples, it is important to consider whether this exists for sexual
minority couples as well. Because legal recognition of homosexual couples is not uniform, whether
relationship status (i.e., committed versus married) for homosexual, as compared to heterosexual,
individuals impacts well-being differently is important to consider.
In a study of lesbian, gay, and bisexual individuals, those in committed or legally recognized
relationships reported higher well-being and less psychological distress as compared to single participants
(Riggle, Rostosky, & Horne, 2010). Further, those in legally-recognized relationships reported higher wellbeing
compared to those in committed relationships pointing to a possible marriage benefit for nonheterosexual
couples as well. Lesbians, gay men, and bisexuals experience a higher prevalence of mental
disorders and distress compared to heterosexuals (Gilman et al., 2001; Meyer, 2003; Sandfort, de Graaf,
Bijl, & Schnabel, 2001). Findings also suggest that sexual minority youth report greater negative affect and
concern over romantic relationships and friendships compared to their heterosexual peers (Diamon &
Lucas, 2004).
Nonmonogamy and Polyamory
Beyond sexual orientation as a defining feature of “nontraditional” relationships, we are seeing an
increasing diversity of types of relationships based on other features as well. Individuals are increasingly
engaging in alternative relationship categories such as polyamory or open relationships. In a recent review
of nonmonogamous relationships and well-being, Rubel and Bogaert (2014) found little evidence for
differences in well-being based on monogamist or nonmonogamist status. Relationship qualities, not
overall well-being, based on this status may differ. For example, polyamorous individuals reported greater
levels of intimacy compared to monoamorous participants (Morrison, Beaulieu, Brockman, &
O’Beaglaoich, 2013). Because polyamorous relationships are characterized by emotional intimacy,
openness, and honesty rather than sexual intimacy, it is not surprising that higher levels of general intimacy
are reported (Barker, 2005; Fierman & Poulsen, 2014; Klesse, 2006). Overall, there is still little research
identifying how nonmonogamous, compared to monogamous, relationships may differentially relate to
628
well-being, and whether these unique relationship types differ in terms of qualities or experiences from the
traditional, committed marital relationship that has been the focus of romantic relationship research
historically.
Online Dating
Now that the Internet is almost constantly at one’s fingertips, the invention of online dating
websites and mobile dating applications together are an increasingly important facet of romantic
experiences that has yet to be fully tapped by researchers. A Pew Research Center study found that 38% of
“single and looking” American adults have used online dating sites themselves and almost 50% report
knowing someone who has been an online user (Smith & Duggan, 2016). One recent study found that onethird
of marriages from 2005 to 2012 began online such as through online dating websites (45%), social
networking platforms (21%), chat rooms (10%), online community forums (6%), and other avenues as
compared to meeting offline through work (22%), friends (19%), school (11%), social gatherings (10%),
bars (9%), family (7%) or other conventional means (Cacioppo, Caccioppo, Gonzaga, Ogburn, &
VanderWeele, 2013). There is also some evidence suggesting that those couples who begin their
relationship online report higher relationship quality, higher marital satisfaction, and were less likely to
experience a marital breakup as compared to those who met offline (Cacioppo et al., 2013; Rosenfeld &
Thomas, 2012), yet other studies find few differences (see Finkel, Eastwick, Karney, Reis, & Sprecher,
2012 for a review). Thus, there is continued debate as to whether online dating is beneficial or detrimental
to relationship formation, stability, and satisfaction.
Research identifying who may be more likely to use online avenues to find a romantic partner is
also limited but begins pointing to older adults and sexual minority individuals as being especially likely
candidates to take their dating efforts online (Rosenfeld & Thomas, 2012; Stephure, Boon, MacKinnon, &
Deveau, 2009). Yet, other studies identified the mid-20s through mid 40’s group as being most likely to use
online dating tools (Smith & Duggan, 2016). Given the proliferation of online dating avenues (i.e., general
and niche dating websites, mobile dating applications, chat rooms, gaming websites), lumping online dating
into one single category may neglect the heterogeneity of this recent trend. For example, older adults are
more likely to use email to meet potential spouses online while younger adults prefer mobile applications
and social networking sites (Caccioppo et al., 2013). The increased utility of online means for individuals
looking to connect with potential partners who may otherwise not form romantic relationships through
more conventional means highlights the significant potential impact online avenues may have for boosting
well-being. Despite the challenges the quickly changing online dating scene poses for researchers, evidence
begins pointing to similarities and differences between online versus offline relationships especially how
the access point of individuals meeting may influence relationship satisfaction and stability. Given the
continued increase in reported online dating use (Smith & Anderson, 2016), it is essential to more clearly
understand how romantic relationship quality, satisfaction, and well-being may be affected by this virtual
trend.
Arranged Marriages
Yet another category of relationships that we did not extensively review thus far is that of nonWestern
traditional forms of marriage. In non-Western cultures, such as India and areas of China,
marriages of choice are considered risky and frowned upon as they may detract from family obligations
(Medora, Larson, Hortacsu, & Dave, 2002). Instead, an estimated 90% of all Indian marriages are arranged
(Gautam, 2002). Even within westernized societies, subcultures exist that favor arranged marriages. For
example, in orthodox Judaism, it is relatively common to use a matchmaker, a Shadchan, to assist in
bringing couples together (Rockman, 1994). The traditionalist view on marriage suggests that free choice
marriages start off with high satisfaction which decreases over time, while arranged marriages have the
opposite pattern in which initial satisfaction is low but increases with time (see Xiaohe & Whyte, 1990 for a
discussion). However, in a pivotal study Blood and Wolfe (1960) found that for both self-selecting and
arranged marriages in Tokyo, satisfaction and love expression decreased over time. Husbands in arranged
marriages showed a more gradual decline than self-selecting husbands, while wives in arranged marriages
reported more dissatisfaction and lower love expression compared to self-selecting wives. In a partial
replication study in Chengdu, China, Xiaohu and Whyte (1990) found that wives in self-selecting marriages
reported greater relationship satisfaction compared to women in arranged marriages.
More research on these diverse marriage typologies has compared arranged marriages in Indian
cultures to self-selecting, or love, marriages in the United States. Findings suggest that there are differences
in the importance that arranged versus love or self-selecting married individuals place on relationship
characteristics that may ultimately influence marital satisfaction. For example, Yelsma and Athappilly
(1988) found that communication was less tied to marital satisfaction for arranged marriages as compared
to love marriages; yet those in arranged marriages reported higher marital satisfaction than those in self-
629
selecting marriages. Others have found differences in importance of qualities such as love and loyalty
between arranged versus love marriages but failed to find that this ultimately led to differences in
relationship satisfaction (Myers, Madathil, & Tingle, 2005). In a recent comparison, Madathil and Benshoff
(2008) found that arranged Indian married individuals place greater importance on finance and shared
values, while self-selecting American married individuals consider loyalty to be more important and tend to
report higher satisfaction overall.
Where Do We Go From Here?
Future Research Directions and Literature Gaps
In this chapter, I have reviewed the broad physical and mental health benefits stemming from social
relationships and highlighted how romantic relationships specifically are related to well-being. I want to
again acknowledge that the chapter focuses on heteronormative relationships – mainly heterosexual
populations that hold the Western traditional view of relationship development and marriage. As noted
previously, the choice to focus on this working definition of relationships was partially due to the majority
of relationship research focusing on this traditional relationship type. In addition, space limitations for this
chapter prevented discussion of all relationship forms, many of which accordingly fall outside the scope of
this chapter.
Again, most research on romantic relationships and well-being has focused on Western,
heteronormative relationships, especially adult married couples. Thus, more research should consider the
unique influences of diverse romantic relationships on psychological well-being and mental health. In
recent years, there has been an increase in research on sexual minority relationships, but this is still a
relatively open area for future research as it relates to well-being. More research regarding the unique
stressors for sexual minority individuals on their relationship satisfaction and experiences as well as their
well-being is needed.
Beyond sexual orientation, the diversity in romantic experiences based on commitment (polyamory
and nonmonogamy versus monogamy), avenue of meeting potential partners (online versus offline), and
freedom in selecting a marriage partner (arranged versus self-selecting) provides a plethora of alternative
relationships that may relate to well-being differently as compared to the link between well-being and
Western, monogamous, self-selecting married relationships. In particular, long-term outcomes for
psychological health and well-being associated with nonmonogamous relationships is needed, as only
recently have these alternative lifestyles been the subject of empirical attention. Further research on
whether well-being and other individual characteristics are related to the use of technology-assisted dating
will add to our limited understanding of this societal trend. In addition, whether online versus offline dating
differentially impacts relationship satisfaction and well-being is a challenging open area of research yet to
discover. The quickly changing online dating scene complicates efforts to assess long-term outcomes
linked to this relatively recent trend. Further, longitudinal studies of couples who met online compared to
offline, or who engage in online-only romantic relationships are needed to more clearly understand the
unique impacts of these alternative relationships on well-being. Finally, just as there is heterogeneity
within committed, self-selecting marriages that leads to different impacts on well-being, there also exists a
broad range of arranged marriages in which many factors influence a couple’s marriage decision and
trajectory including family and cultural influences or perceived input on the decision making process.
Given such discrepant and scarce findings of well-being and love versus arranged marriages, future
research on the differences between marriage types for relationship satisfaction and well-being is needed.
While I discussed love as an important characteristic of Western romantic relationships, this may
not apply cross-culturally, especially in societies in which traditional, arranged marriages are more
common. Indeed, college students in Western nations report love as being more important to a successful
marriage compared to students in Eastern nations (Levin, Sato, Hashimoto, & Verma, 1995). Further, love
may be defined or expressed differently in various cultures (de Munck, Korotayev, de Munck, &
Khaltourina, 2011; Karandashev, 2015; Nadal, 2012). Different qualities may be tied to relationship
investment and satisfaction cross-culturally as well (Karandashev, 2015; Madathil & Benshoff, 2008;
Schmitt, 2006; Schmitt et al., 2009; Yelsma & Athappilly, 1988). I reviewed evidence suggesting that there
are cultural differences regarding which love styles are related to well-being and satisfaction, yet this
remains a relatively understudied area. Because the concept and definition of love may vary crossculturally,
more research on universal and culture-specific relationship qualities (including love) for wellbeing
is warranted.
Another complication for assessing romantic relationships and well-being is that the definition of
what constitutes a romantic relationship is ever changing. While there is a wealth of research of marital
relationships, there is a societal trend in creating different categories of a relationship based on
commitment and intimacy levels. This is especially common among emerging adults who are exploring
630
romantically and delaying making “the one” decision for much longer than in the past. In addition to an
increase in nonmonogamous relationship subtypes in Western society, sociosexuality is another
relationship dimension that has recently received empirical attention. Sociosexuality is defined as one’s
willingness to engage in sexual encounters and experiences with others without the commitment, intimacy,
emotional connection, and closeness that traditionally accompanied sexual engagement (Gangestad &
Simpson, 1990; Simpson & Gangestad, 1991). Sociosexuality exists on a continuum ranging from
restricted (sex is accompanied by commitment and closeness) to unrestricted (sex in the absence of
emotional connection or commitment). Because up to 80% of college students report casual sexual
experiences and hooking up may replace traditional dating development (Garcia & Reiber, 2008; Bogle,
2008), assessing whether unrestricted sociosexuality impacts well-being or romantic satisfaction is
warranted. Research regarding hook up culture and positive versus negative impacts on well-being has thus
far been mixed (Fielder & Carey, 2010, Grello, Welsh, & Harper, 2006; Grello, Welsh, Harper, &
Dickson, 2003; Owen, Quirk, & Fincham, 2013; Vrangalova, 2015). Thus, considering how sociosexuality
and each distinct category of nonmarital dating (casual, monogamous, cohabitating, hooking up, friends
with benefits, etc.) relates to well-being is an important area of future study.
Another area lacking in sufficient research is identifying the beneficial aspects of early teen dating
and the possible benefits associated with the normal process of romantic exploration during adolescence
and emerging adulthood. Historically, research on adolescent romantic relationships has focused on its
negative correlates and risky behavior. More recently, researchers have begun to identify its utility for
overall mental health and successful future relationships, but there is much more that can be uncovered.
While there has been an uptick in research that looks at teen and young adult romantic involvement, this is
an area that deserves more attention especially given how potentially formative our early relationships can
be for future individual and interpersonal functioning.
Relatedly, I reviewed potential mechanisms that account for the strong link between romantic
relationships and well-being. Specifically, the social, emotional, and instrumental support a romantic
partner can offer in healthy relationships has been commonly cited as a key mechanism of this link.
Providing and receiving support in both distressing and positive events with a romantic partner may be a
crucial factor in predicting overall well-being. Beyond the general support hypothesis, others have
attempted to identify additional explanations for the relationship benefit. Feeling understood by others, and
in particular by romantic partners, is linked to higher well-being and relationship satisfaction (Gordon &
Chen, 2016; Reis, Lemay, & Finkenauer, 2017). Open communication to convey what one needs from a
partner and, in turn, understanding a partner’s needs and perspective may boost relationship benefits for
well-being. The familiarity, trust, understanding, and support romantic partners can provide all seem to
benefit individual well-being. Research on qualities unique to romantic relationships as compared to social
relationships and their impact on well-being continues to be limited. Further, more research on the specific
mechanisms that account for the link between romantic experiences and overall well-being is needed.
Finally, gender differences are often considered when discussing romantic relationships. Prior
research concerning the impact of romantic relationship transitions and experiences suggest that there may
be different implications for men and women. Early research on potential gender differences found that
males tend to benefit more from marriage and suffer more from divorce compared to women (Bloom,
White, & Asher, 1979; Gove, 1972). However, more recent findings suggest relatively few to no gender
differences in the marriage benefit for physical health or well-being (Kiecolt-Glaser & Newton, 2001;
Simon, 2002; Strohschein, McDonough, Monette, & Shao, 2005; Umberson, Chen, House, Hopkins, &
Slaten, 1996; Williams, 2003). Future research that addresses the conflicting findings regarding potential
gender differences would be beneficial.
Overall, there has been a wealth of research considering the link between romantic relationships and
well-being, but the vast majority has focused on the idea of identifying the marriage benefit and its
mechanisms. Many prior findings also linked well-being solely to relationship status without considering
more discrete qualities of those relationships. Moving forward, it will be critical to assess the
characteristics of romantic relationships that are most closely linked to well-being and relationship
satisfaction. It is evident that there are many more relationship qualities that impact well-being in addition
to love and that the concept of love varies across cultures, time, and development. Given the changing
definition of a romantic relationship and importance of different relationship qualities over time, more
research focusing on a greater variety of relationship types – whether it be varying degrees of commitment,
number of partners, or gender – and their link to well-being and relationship satisfaction is warranted.
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Resilience and Well-Being
By P.D. Harms, University of Alabama; Lisa Brady, University of Alabama; Dustin Wood, University of
Alabama; Anthony Silard, California State University, San Bernardino
Citation
Harms, P. D., Brady, L., Wood, D., & Silard, A. (2018). Resilience and well-being. In E. Diener, S.
Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
In this chapter we provide an overview of how resilience has been defined and measured with a particular
emphasis on the relationship between resilience and well-being. Specifically, we distinguish between
resilience defined as a trait and resilience defined as a pattern of psychological well-being over time. We
provide a review of the developmental origins of resilience and summarize recent research regarding
interventions designed to increase resilience in adults. We also differentiate resilience from closely related
constructs such as hardiness, grit, character strengths, and psychological capital. Finally, we provide
guidance on potential future directions for the study of resilience.
Keywords: Resilience, Well-being, Stress, Development
An observer taking a look through an airport bookstore or even the business leadership section of
the local book shop could be forgiven for thinking that “resilience” is just another big fad being pushed by
self-help gurus and consultants. And although there may be some truth in this assessment, the actual
science of resilience, its antecedents, and its effects are fairly well-established. In fact, the question as to
what makes an individual resilient in the face of trauma goes back many thousands of years.
That said, the boom in popular press books has largely reflected a similar explosion in research
about resilience itself over the past two decades and there are many excellent reviews of the topic in the
clinical, education, workplace, and social psychological literatures (e.g. Bonanno, Westphal, & Mancini,
2011; Britt, Shen, Sinclair, Grossman, & Klieger, 2016; Luthar, Cicchetti, & Becker, 2000; Windle, 2011;
Vanhove, Herian, Harms, & Luthans, 2015). Estimates of how many people are resilient range from 25-
84% (Vanderbilt-Adriance & Shaw, 2008). But what exactly does that mean? In the following sections,
we will define resilience, describe how it is modeled and measured, explain its relationship with wellbeing,
delineate how it is developed, and review closely related constructs. At the end, we will discuss
some major remaining issues for research and practice in the study of resilience.
Models of Resilience
Defining Resilience
One persistent problem in the resilience literature is understanding its meaning. Specifically,
resilience tends to have two somewhat distinct meanings. On one hand, resilience can mean the ability to
resist being damaged or deformed by traumas or destructive forces. On the other hand, resilience can also
mean readily “bouncing back” or recovering from those traumas or destructive forces. The first definition
perceives resilience as a trait an individual needs to survive. The second definition instead emphasizes
resilience as a means of thriving. This distinction is important, as an individual facing adversity can go
further than merely coping by finding meaning in the trauma-inducing events and utilizing this meaning to
enhance their well-being. Such an individual experiences post-traumatic growth, a process in which one
cognitively associates benefits with the situations or events that have generated the experienced trauma
(Elder, 1998; Feeney & Collins, 2014; Jayawickreme & Blackie, 2014).
These dueling definitions have resulted in the development of two somewhat independent streams
of research, each of which claims to be studying resilience. One on side, there are researchers who look at
resilience as something that an individual possesses. On the other side are those who believe that resilience
can only be demonstrated through one’s reactions to adverse events.
Resilience as a trait or capacity. There are several models and measures of resilience that treat the
construct as something that an individual has and can report on based on prior experience (Britt et al.,
2016). These models approach resilience either as a single construct (e.g. Brief Resilience Scale, Smith et
al., 2008) or a composite of several distinct traits or capacities. Across measures, a wide variety of
candidate traits have been suggested for inclusion in resilience measures as either antecedents or
components of resilience. For example, the Connor-Davidson Resilience Scale (CD-RISC, Connor &
Davidson, 2003), widely considered the “gold standard” of resilience measures, is a 25-item measure of
resilience assessing acceptance of change, control, personal competence, spiritual influences, and trust in
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one’s instincts. The more recently developed Five-by-Five scale (DeSimone, Harms, Vanhove, & Herian,
2016) is also a 25-item measure with five dimensions, but it assesses adaptability, emotion regulation,
optimism, self-efficacy, and social support. A more extreme version of this approach is the Global
Assessment Tool or GAT (Peterson, Park & Castro, 2011; see also Lester, Harms, Herian, & Sowden,
2015), a 105-item, multidimensional instrument used by the U.S. military in order to provide
developmental feedback for soldiers and reservists participating in resilience development programs. The
GAT assesses resilience in terms of four “fitness” dimensions (Emotional, Social, Family, and Spiritual).
Each higher-order dimension can in turn be broken down into subdimensions. For example, Emotional
Fitness consists of adaptability, good and bad coping, catastrophizing, character, depression, positive and
negative affect, and optimism. The GAT consists of a mixture of antecedents and outcomes of well-being,
leading to some concerns surrounding whether scores for the higher-order dimensions themselves are
interpretable (Harms, Wood, & Spain, 2016). That said, the instrument does not provide an overall
“resilience” score since the intention is to encourage soldiers to think of resilience in a multi-faceted
manner.
Protective Factors
In general, it is accepted that resilience is inherently related to the resources that an individual can
draw on to overcome adversity (e.g. Richardson, 2002; Werner, 1995). These protective factors come in a
wide variety of forms that combine to make a person resilient. Various researchers tend to focus on the
study of resilience at one level of analysis, often with the goal of developing resilience interventions
targeted at that level.
Individual factors. It is with this level that psychologists are typically concerned. It involves the
psychological and neurobiological factors that can play a role in maintaining and recovering well-being
after traumatic events or setbacks. This level of resilience typically involves investigations of personality
and coping styles described in the preceding section that mediate the relationship between adversity and
well-being (Luthar et al., 2000; Masten, 2007), but it can extend to include investigations of physical and
cognitive abilities as well as neurocognitive structures and neural responses to stressors (Feder, Nestler, &
Charney, 2009; Reinelt et al., 2015).
Social factors. These factors concern the social relationships one has and whether an individual
can call on and expect support in times of crisis. These can involve family, friends, coworkers, or really
anyone in one’s social network who could provide social, emotional, and even financial support to the
individual. Research has demonstrated that having such relationships can be an important determinant of
whether an individual can cope with major stressors such as the loss of a job, the dissolution of a marriage,
or chronic physical illness. Social support is widely construed to contain both affective and instrumental
components. Adams, King, and King et al. (1996; p. 412) note that “there is a growing consensus that
social support can come from both work and non-work sources and that this support is primarily in the
form of either emotional support (e.g., listening and providing empathy) or instrumental support (e.g.,
tangible assistance aimed at solving a problem).”
Community factors. The discussion of resilience has even moved beyond the realm of individualfocused
psychology to include resilience at the community or national level. This type of resilience goes
beyond individual capacities and takes into account economic, institutional, ecological, and infrastructure
capacities when evaluating which communities are most likely to be resilient in the face of tragedies such
as terrorist attacks, natural disasters, or even economic downturns (Cutter et al., 2008; Norris, Stevens,
Pfefferbaum, Wyche, & Pfefferbaum, 2008; Murphy, 2007). For instance, it might not only be necessary to
know whether or not a given area has emergency services, but also how well integrated the services are in
terms of communication and coordination. Importantly, community resilience need not be limited to
government institutions. For example, in the aftermath of Hurricane Katrina, Wal-Mart famously was able
to reach beleaguered areas with supplies before the federal and state governments because they had
contingency plans in place for just such an event and adapted their plans as events unfolded.
Resilience as a process. Simply put, the process approach to studying resilience looks more at how
individuals cope with hardship and, in particular, is often associated with assessing patterns of well-being
over time to determine who is resilient in periods of stress (Luthar, Cicchetti, & Becker, 2000; Windle,
2011; Becker & Ferry, 2016). It has been suggested that there are three general patterns that reflect
resilience: 1) functioning well under adverse conditions; 2) a relatively quick recovery to normal
functioning after facing adverse conditions; and 3) developing in the face of adversity (Bonanno, 2004,
2005; Masten, Best, & Garmezy, 1990).
Figure 1. Patterns of Recovery from Trauma
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Figure 1 provides an overview of these different patterns. In this figure, the first three patterns all
represent a form of resilience. The first two patterns, which have been labeled stress resistant resilience
and “bouncing back” resilience, reflect the most common forms of resilience (Bonanno, 2005). In the case
of stress resistance (blue), individuals do not appear to display any adverse reaction to the stressor or
negative event. Rather, they continue on with their lives in spite of it. In the case of the “bouncing back”
pattern (red), the individuals experience a loss but quickly adapt to it. The post-traumatic growth pattern
(green) largely parallels the ‘bouncing back’ pattern, but additionally reflects the idea that positive
development can occur after stressors – and importantly, because of exposure to these stressors – although
this does not necessarily occur quickly. The final three patterns all reflect individuals who are not
considered high in resilience. The basic recovery to set point pattern is meant to indicate that some
individuals will eventually return to levels of well-being similar to those that they experienced pre-trauma,
but that it will take an extended period of time to recover. The delayed reaction pattern (pink) represents
individuals who initially appear to be healthy, but eventually begin to display signs of distress. The final
pattern, lack of recovery (purple), reflects an individual who displays chronic problems caused by the
stressor or trauma that are never fully dealt with or resolved.
Developing Resilience
Life History
There is an extensive literature showing that resilience in adulthood can be traced to childhood
experiences (e.g. Masten, 2001; Masten & Tellegen, 2012; Obradovic et al., 2009; but see also Ong,
Bergeman, & Boker (2009) for a review of later life events impacting resilience). Specifically, a history of
poverty, disease, or abuse is typically associated with lower levels of resilience later in life (Schibli, Wong,
Hedayati, & D’Angiulli, 2017; Windle, 2011). At the same time, there are those who argue that harsh
environments can help individuals develop resilience since these early experiences provide the opportunity
to develop the skills necessary to overcome setbacks (e.g. Crane & Searle, 2016; Duckworth, 2016;
Goldstein, 2008; Rutter, 1999). In other words, experiences of stress and hardship can, for some people, be
an opportunity to learn and grow and become more ready to meet the next challenge. Individuals who
never experience challenges may experience high well-being on a regular basis, but they may also be more
likely to fall apart when they finally do face adversity (Davydov, Stewart, Ritchie, & Chaudieu, 2010).
That said, it has also been pointed out that individuals may also develop strategies for overcoming hardship
that could be grossly inappropriate in non-threat environments (Schibli et al., 2017). For example, upon
becoming a parent, an individual who had developed a detachment strategy for dealing with interpersonal
conflict is likely to discover that this strategy is inappropriate for dealing with infants.
Resilience-Training Programs
Resilience-training programs have utilized several different approaches to increasing individual
levels of resilience (Yost, 2016). These include encouraging a growth mindset, deliberative practice,
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meditation, teaching coping strategies, and providing social support.
One of the most famous developmental interventions for children is the Penn Resiliency Program
(Gillham, Reivich, Jaycox, & Seligman, 1995). This program is based on cognitive behavioral therapy
approaches and is usually implemented in school or group settings. At its core, the program attempts to
help participants develop cognitive and emotional skills that they can utilize when encountering setbacks.
For example, one cognitive skill that is taught is decatastrophizing or “putting things in perspective”. That
is, participants are instructed to step back and evaluate how important a failure event or embarrassing
situation may be. Such a response is a form of cognitive reappraisal, widely considered the most effective
form of emotion regulation (Gross, 2015). Cognitive reappraisal is an antecedent-focused strategy that
occurs when an individual changes his or her subjective evaluation of the situation or event that has
stimulated the emotion in order to change the emotion that they feel (Fisher, Minbashian, Beckmann, &
Wood, 2013). As such, cognitive reappraisal allows the individual to avoid overreacting to negative events.
One of the most popular resilience interventions in the research literature is the Penn Resiliency
Program. While meta-analytic work has shown the program produced some positive effects, its results were
highly variable and, in general, it was not more effective than other active control conditions or other
interventions designed to improve mental health and well-being (Brunwasser, Gillham, & Kim, 2009).
Beyond classroom settings, resilience-training initiatives are now becoming more popular in
corporate and government environments. Although it is believed that almost anyone can benefit from such
programs, there is also a consensus that resilience may be most important for occupations such as firstresponders
(i.e. police, firefighters, etc.) or medical personnel where high levels of stress are common and
exposure to secondary trauma—which is concerned with the intrapersonal emotive responses a person can
experience during or following an interaction(s) with another individual who shares their personal stories of
disempowerment, trauma, or abuse (Williams, Helm, & Clemens, 2012)—is frequent (Britt et al., 2016).
Consequently, military organizations have been on the forefront of developing resilience-building
programs (Harms, Krasikova, Vanhove, Herian, & Lester, 2013). Of particular note has been the
Comprehensive Soldier and Family Fitness (CSF2) program by the U.S. Army, which is based on the Penn
Resiliency Program and has been implemented at every level of the Army. CSF2 entails not just regular
self-assessments of resilience, but also includes online modules to address particular concerns of the
soldiers and embeds Master Resilience Trainers (MRTs) in units across the force to implement group-based
training of cognitive and behavioral skills that are associated with higher levels of resilience and wellbeing.
The CSF2 program proved to be more effective at developing resilience in younger soldiers than in
older soldiers (Lester, Harms, Herian, Krasikova, & Beal, 2011) and has also been shown to be related to
lower levels of substance abuse in units which receive the training (Harms, Herian, Krasikova, Vanhove, &
Lester, 2013).
A recent meta-analysis of organizational resilience interventions (Vanhove, Herian, Perez, Harms,
& Lester, 2016) has shown that not all resilience programs are created equal and not all people respond in
the same way to such programs. For example, although the benefits of resilience-development programs
tend to wear off for most people over time, there was evidence that for the most at-risk populations, the
benefits tended to accrue over time. Analyses also revealed that computer-based interventions were the
least effective medium for resilience training while one-on-one training was the most effective. Overall,
the results of these studies have suggested that social factors that promote resilience can interact with
individual factors and that well-designed interventions should target resilience development across levels in
order to achieve the best results.
The Relationship Between Resilience and Well-Being
Resilience and well-being are fundamentally related and, as noted above, in some instances
resilience is even measured using well-being instruments (Davydov et al., 2010; Windle, 2011). This
conflation creates problems with where to position resilience in models of well-being. First, it should be
pointed out that although meta-analyses have demonstrated that there are robust relationships between
measures of resilience and measures of well-being (Hu, Zhang, & Wang, 2015; Lee et al., 2013), there is
evidence that self-report measures of resilience are not simply redundant with indices of well-being (Burns
& Antsey, 2010; Martínez-Marti & Ruch, 2017). At the same time, the relationship between resilience and
well-being is not straightforward.
Some researchers have argued that higher levels of well-being serve as an antecedent of resilience
(e.g. Kuntz, Näswall, & Malinen, 2016). In particular, there has been extensive work showing that positive
emotions facilitate resilience (e.g. Fredrickson, Tugade, Waugh, & Larkin, 2003; Ong, Bergeman, Bisconti,
& Wallace, 2006; Ong, Zautra, & Reid, 2010; Tugade & Fredrickson, 2004). Research suggests that
positive emotions can promote greater resilience because they promote flexible thinking (Isen, Daubman, &
Nowicki, 1987) and facilitate both adaptive coping (Folkman & Moskowitz, 2000) and the maintenance of
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social relationships (Keltner & Bonanno, 1997).
Others have suggested that the relationship between well-being and resilience can also work in the
opposite direction. For example, several researchers have used resilience to directly predict a number of
well-being outcomes including depression (Loh, Schutte, & Thorsteinsson, 2014), job satisfaction
(Luthans, Avolio, Avey, & Norman, 2007), and subjective well-being (Cohn, Fredrickson, Brown, Mikels,
& Conway, 2009; Liu, Wang, Zhou, & Li, 2014). Still others have argued that resilience and related
constructs can serve as moderators between stressors and well-being outcomes (e.g. Flinchbaugh, Luth, &
Li, 2015; Min, Kim, & Lee, 2015).
That said, there is nothing inherently wrong with acknowledging that all of these theoretical
positions are potentially true. Positive individuals may ultimately be more resilient because they approach
situations expecting better outcomes and tend to elicit more positive responses (Wood, Harms, & Vazire,
2010). And although it is probably correct to position resilience indicators (the individual, social, and
community factors mentioned earlier) as moderators between stressors and well-being, that does not mean
that studies showing a direct path cannot infer that resilience is moderating several unmeasured stress
events over a long period of time and that the direct path simply captures the general trend across events.
A challenge, however, to conflating resilience and well-being is that the abilities honed by resilient
individuals may be more generative of self-efficacy, and in fact may actually hinder well-being. For
example, an individual cast away by his or her only family at a young age may learn how to navigate very
challenging environments to succeed. An individual’s resilience may lead to high self-efficacy and a
successful approach to his or her career, yet may also produce an “it’s all about me and getting what I
deserve” attitude that can undermine well-being. Considering that longitudinal research has found that
receiving social support is an antecedent of well-being (Elder, 1974, 1998), such an individual may isolate
him or herself from sources of such support.
Additionally, some individuals who experience high levels of well-being may lack the focus that
produces resilience. The positive emotions associated with well-being, such as joy and calmness, tend to
generate a diffuse contentment rather than the sharp, vivid focus on challenges associated with resilience
(Fredrickson, 1998; Silard, 2016). In fact, the action tendencies produced by positive emotions—such as
inactivity from contentment and free activation from joy—are often less specific (in terms of goal
orientation) and lacking in autonomic reactivity (Fredrickson & Branigan, 2005). It may be possible that
some antecedents of well-being and resilience diminish the attainment of the other. Future research might
better uncover these potential disparities.
Other Related Constructs
As noted above, a lack of strong theory surrounding resilience has meant that its position in the
nomological network can often be confusing and seemingly contradictory. The same issue applies to other
closely related personality characteristics. Recent reviews of resilience have suggested a number of
constructs that conceptually appear very similar to resilience (e.g. King, Newman, & Luthans, 2016;
January, 2016). The following section identifies some major constructs that are closely related to
resilience.
Psychological Capital
Psychological capital (PsyCap) is argued to be a set of four psychological factors associated with
overcoming obstacles that together form a higher-order construct (Luthans et al., 2007; Youssef & Luthans,
2007). Specifically, these psychological factors are self-efficacy, optimism, hope, and resilience.
Resilience in this model is often simply described as the capacity to adapt in the face of adversity. Because
of the self-report nature of the instrument and the limited number of questions typically asked, PsyCap
assessment tools generally have to assume that the resilience component is unidimensional, that
respondents have experienced appropriate setbacks in order to make informed judgments, and that they are
able to meaningfully average across the responses to multiple adverse events. Because of these potential
issues, there have been recent efforts made to create implicit measures of PsyCap that better reflect the
individual’s actual levels of resiliency (Harms & Luthans, 2012). Both the explicit and the implicit
instruments have been shown to predict health and well-being across multiple domains (Avey, Reichard,
Luthans, & Mhatre, 2011; Harms, Vanhove, & Luthans, 2017; Luthans, Youssef, Sweetman, & Harms,
2013). For example, one recent study found that PsyCap was predictive of both mental health and
substance abuse in a large sample of U.S. soldiers (Krasikova, Lester, & Harms, 2015). That said, although
there has been a great deal of research using PsyCap measures to predict important outcomes both in and
out of the workplace, there is still an ongoing debate as to whether combining the components of PsyCap
into a single score is appropriate or whether they are best considered independent of one another. In
particular, it could be argued that resilience should not be included in the set of PsyCap factors because it is
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theoretically positioned as an outcome of the other three.
Character Strengths
Character strengths are conceived of as “naturally recurring patterns of thought, feeling, or behavior
that can be productively applied” (Hodges & Clifton, 2004, p. 257). In other words, they are a broad array
of personality characteristics distinguishable from other traits because they are associated with high levels
of functioning both behaviorally and psychologically (Peterson & Seligman, 2004). In practice though,
they tend to be assessed as efficacies or self-appraisals of ability to function well on particular activities or
in specific domains. High levels of character strengths have been suggested to be key antecedents of
resilience (Martínez-Marti & Ruch, 2017; Peterson, Park, & Castro, 2011; Peterson & Seligman, 2004) or
as potential indicators of resilience itself (Goodman, Disabato, Kashdan, & Machell, 2017). However, the
empirical evidence of this assertion is somewhat mixed in terms of which strengths are associated with
well-being (Goodman et al., 2017; Park, Peterson, & Seligman, 2004). That said, there is fairly good
evidence that self-assessments of character strengths are useful predictors of mental health outcomes (e.g.
suicide and substance abuse; Lester, Harms, Bulling, Herian, & Spain, 2011). There are, however,
numerous criticisms of strengths measures in terms of their construct definitions, their theoretical structure,
the way they are scored, and their interpretation (Kaiser & Overfield, 2011; Kaplan & Kaiser, 2013).
Consequently, although the relationship between strengths and resilience looks promising, further
refinement of character strengths instruments is needed before it can be determined whether strengths are
antecedents of resilience or whether “resilience” as a trait should simply be considered redundant with
specific characteristics already contained in existing strengths measures.
Grit
Popularized by Duckworth (Duckworth, Peterson, Matthews, & Kelly, 2007), grit is conceived of as
perseverance in the face of challenges and experiencing passion in the pursuit of long-term goals. The
relationship with resilience is immediately apparent based on this definition in that one component of grit,
perseverance, seems to reflect a resilient personality and even the “passion” component might be
considered a possible antecedent of resilient behavioral patterns. However, meta-analytic evidence
suggests there is a trivial relationship between measures of resilience and grit even though grit appears to
be related to well-being outcomes such as depression and life satisfaction (Credé, Tynan, & Harms, 2017).
That said, once again measurement issues limit the degree to which firm conclusions can be drawn about
grit. First, the combination of the two factors of grit is not supported by either theory or empirical
evidence. Moreover, the current measures of grit have been demonstrated to largely overlap with existing
measures of trait conscientiousness (Credé et al., 2017). Consequently, little can be meaningfully said
about overall “grit” at this point and further scale refinement is necessary before any firm conclusions can
be drawn.
Hardiness
Of the closely-related constructs, hardiness probably comes closest in terms of conceptual similarity
to resilience. Individuals high in hardiness are described as being “unshakeable,” and they tend to attack
problems directly and willingly (Kobasa, 1979). Specifically, hardiness itself is conceived of as a
cognitively-based personality trait consisting of three characteristics that shape how hardy individuals view
events in their lives: control, commitment, and challenge (Bartone, 2006; Maddi, Kahn, & Maddi, 1998).
Control reflects the degree to which one believes that they have a high level of influence over their lives.
Commitment refers to the tendency or ability to find purpose in one’s life or to attach meaning to one’s
efforts. Challenge reflects a tendency to see difficult circumstances as an opportunity for growth as
opposed to nuisances or threats. Further, meta-analytic evidence shows that individuals with high trait
hardiness tend to have higher levels of psychological well-being, better coping skills, higher levels of
health, and more well-developed social support networks (Eschleman, Bowling, & Alarcon, 2010). The
primary difference between resilience and hardiness at the measurement level is that hardiness has a very
concrete theoretical model both in terms of structure and rationale. Resilience models have not yet arrived
at a consensus as to what should be included in the measures and what the specific antecedents are.
Future Directions
Not to belabor the point, but there is a real need for construct clean-up in the domain of resilience.
Not only are there several related constructs that need to be differentiated from resilience, but it is unclear
as to whether many measures of resilience are even measuring the same construct (Britt et al., 2016).
Further, as noted in the above sections, one important future direction for resilience and related measures is
to further refine their theories and measurement tools. Too often, resilience measures combine antecedents
and outcomes of resilience along with overall assessments in their measures and then try to infer a trait
based on structuralist logic that because variables are correlated, they must necessarily go together.
648
Particularly problematic is the inclusion of items that refer to well-being outcomes in the resilience
measures themselves as this tendency tends to create spuriously high correlations between constructs
(Wood & Harms, 2016). Instead, it would be preferable to embrace a functionalist approach to assessing
resilience (see Harms & Wood, 2016; Wood, Gardner & Harms, 2015), that is, to tease out the antecedent
psychological components of resilience and investigate how they interact to produce behavioral and
emotional resilience. Another fruitful approach may be to move away from questionnaire-based
approaches altogether and attempt to develop assessments of resilience based on neurological
measurements (e.g. Quisenberry, 2015), implicit measures (e.g. Harms & Luthans, 2012), or situational
tests (e.g., Kirschbaum, Pirke, & Hellhammer, 1993).
At the same time, it may not be necessary to completely eschew self-report measures if the goal is to
assess resilience as process or pattern. There have been many calls for more longitudinal research to
investigate resilience as patterns of well-being rather than the cross-sectional, retrospective studies which
tend to dominate in the literature (Britt et al., 2016; King et al., 2016). Recent work by Welbourne (2014)
has shown that even asking a single question concerning well-being repeatedly over several days can
produce enlightening results in terms of determining an individual’s overall resilience. Taking this logic a
step further is recent research by Sotak (2015), who has demonstrated that daily and weekly patterns in
emotions and well-being can be removed from such assessments in order to garner a more accurate view of
fluctuations in response to stressors.
Hand-in-hand with the development of new instruments and techniques is the need to validate those
instruments and techniques. A recent review of resilience measures showed that almost none of them had
gone through rigorous validation procedures and the overall validity of most resilience measures was
questionable at best (Windle, Bennett, & Noyes, 2011). Without appropriate tools, it is hard to see how we
can put much faith into much past research or how we are to move the field forward.
Beyond the need for new measures is a real need for theoretical development in the field of
resilience. In particular, it is reasonable to expect a little more precision in predictions than simply that
resilience should be positively correlated with good outcomes and negatively correlated with bad
outcomes. Clinical psychologists are fairly clear about what they expect in terms of outcomes of
resilience. When bad things happen, resilience is established by how one recovers from stress. However,
researchers in the positive psychology movement have been inconsistent in terms of what to expect from
resilience interventions. For them, the goal is or should be to see if they can promote individual
flourishing. At the same time, it is acknowledged that the degree to which programs based on positive
psychology are deemed effective is the extent to which they reduce mental illness (Seligman & Fowler,
2011). Likewise, industrial psychologists attempt to tie resilience to all manner of work outcomes with
little regard for theory (Britt et al., 2016). Having more clearly defined constructs and models would help
prevent this shotgun approach to science and save precious resources and time.
Conclusions
Resilience is more than just a buzz word used to sell books in airports. It is a valuable framework
for understanding how individuals cope with stress and maintain their levels of well-being. The past few
decades of research have revealed a great deal in terms of what factors are most important for driving
resilience and how interventions can be designed to facilitate growth and recovery in the face of adverse
events. Nonetheless, challenges remain in terms of the theory surrounding resilience, its measurement, and
its meaning. However, new approaches to assessing resilience show great promise for the study of
resilience in the future.
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2018 Ed Diener. Copyright Creative Commons: Attribution, noncommercial, no
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OUTCOMES
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Living Healthier and Longer Lives: Subjective Well-Being’s
Association with Better Health
By Julia K. Boehm, Chapman University
Citation
Boehm, J. K. (2018). Living healthier and longer lives: Subjective well-being's association with better
health. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF
Publishers. DOI:nobascholar.com
Abstract
To fully understand how psychological functioning is related to health and longevity, it is important to not
only consider psychological distress, but also subjective well-being (i.e., the presence of positive thoughts
and feelings). This chapter reviews the most recent and highest quality evidence for whether and how
subjective well-being is linked with living healthier and longer lives. Accumulating evidence has begun to
suggest that initially healthy individuals with higher versus lower levels of subjective well-being are less
likely to be diagnosed with incident disease including coronary heart disease, stroke, diabetes, arthritis, and,
to a lesser extent, cancer. The reoccurrence of disease in individuals who have already been diagnosed
shows a similar although less robust pattern. Associations are comparable for mortality, with fairly
persuasive evidence demonstrating that higher levels of subjective well-being in initially healthy
individuals are associated with longevity, but a somewhat less compelling body of work supporting the
association among cohorts of patients. Underlying pathways for these associations are discussed –
including mechanisms related to stress buffering and physiological and behavioral processes – and
suggestions for future research are provided.
Keywords: health, longevity, morbidity, mortality, subjective well-being, life satisfaction, positive
emotions
The notion that psychological states and physical states are connected has endured across the ages.
Most empirical research on this topic has focused on how psychological distress is related to poor health
outcomes. For example, compared to people with low levels of depression, anxiety, and stress, people with
high levels have an increased risk of incident coronary heart disease and mortality (Nicholson, Kuper, &
Hemingway, 2006; Pratt, Druss, Manderscheid, & Walker, 2016; Richardson et al., 2012; Roest, Martens,
de Jonge, & Denollet, 2010; Rugulies, 2002; Steptoe & Kivimaki, 2013). However, most people are not
psychologically distressed. In fact, most people report feeling happy most of the time (Diener & Diener,
1996; Diener, Kanazawa, Suh, & Oishi, 2015). Thus, to understand how the full range of psychological
functioning is related to health and longevity, it is important to not only consider psychological distress, but
also the presence of positive thoughts and feelings.
The frequent experience of positive thoughts (like satisfaction with life) and feelings (like positive
emotions) comprise the construct of subjective well-being (Diener, Suh, Lucas, & Smith, 1999). Subjective
well-being – which is colloquially known as happiness – inherently feels good. Moreover, evidence
suggests that subjective well-being is also associated with beneficial outcomes in a variety of life domains
such as in the workplace and in social relationships (Boehm & Lyubomirsky, 2008; Lyubomirsky, King, &
Diener, 2005). In the last decade or so, an explosion of research has explored whether the benefits of
subjective well-being are apparent with regards to health and longevity as well. Thus, this chapter reviews
the most recent and highest quality evidence for whether and how positive thoughts and feelings are linked
with living longer and healthier lives.
The strongest evidence for associations between subjective well-being and health-related outcomes
come from studies that are methodologically rigorous, as indicated by the following characteristics: 1)
prospective longitudinal design that takes baseline health into account and follows individuals across many
years; 2) assessment of subjective well-being with a well-validated and multi-item questionnaire or an
objective measure; 3) objective assessment of a health outcome (e.g., via medical records); 4) analyses that
control for confounding variables (e.g., socioeconomic status); 5) analyses that consider possible
underlying pathways (e.g., health behaviors); and 6) analyses that test whether subjective well-being’s
associations are independent from psychological distress (e.g., depression, anxiety). The selective review
that follows describes studies that are characterized by most or all of these criteria. I first describe evidence
linking subjective well-being with a variety of disease outcomes, then I describe evidence linking subjective
well-being with mortality. Because correlates and underlying processes may differ for people who are
initially free from disease and those who have been diagnosed with a medical condition, I review evidence
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for both groups separately. This chapter ends with a discussion of the mechanisms by which subjective
well-being may be linked with better health and longevity, as well as considerations for future research.
Note that although evidence also exists regarding how other indicators of positive psychological
functioning are associated with health outcomes – such as purpose in life or optimism (e.g., Cohen,
Bavishi, & Rozanski, 2015; Rasmussen, Scheier, & Greenhouse, 2009) – here I focus exclusively on the
positive indicators that comprise subjective well-being (i.e., life satisfaction and positive affect) to maintain
a manageable scope. In addition, low levels of negative emotions are sometimes included as part of
subjective well-being’s conceptualization, but I do not consider negative emotions here because there is a
very large and separate literature that has focused on the relationship between various negative emotions
and poor health (see selected references above).
Morbidity
In Initially Healthy People
Evidence is accumulating to suggest that happy and satisfied people have lower risk for being
diagnosed with a variety of medical conditions. Cardiovascular disease has been the most frequently
studied outcome, in part because it is a well-defined disease with objective indicators (Boehm &
Kubzansky, 2012). For example, 1,700 Canadian men and women over 18 years old had their positive
affect assessed via the facial expressions they displayed during a clinical interview (Davidson, Mostofsky,
& Whang, 2010). Relative to people showing fewer positive emotions in their faces, people showing more
positive emotions had a 22% reduced risk of being diagnosed with coronary heart disease across 10 years.
These findings were robust to adjustment for a variety of confounders and possible behavioral mechanisms,
as well as to adjustment for hostility and symptoms of depression and anxiety. Another study reported
similar findings based on a cohort of nearly 8,000 British civil servants. Individuals with greater initial life
satisfaction across a variety of domains (including satisfaction with work, family, and one’s sex life) tended
to have a reduced risk of incident coronary heart disease (Boehm, Peterson, Kivimaki, & Kubzansky,
2011). This study had a follow-up period of approximately 5 years and controlled for a range of variables
including sociodemographic characteristics, health behaviors, blood pressure, lipids, body mass index,
diabetes, and psychological ill-being.
However, positive affect was not related to incident coronary heart disease in the same cohort of
British civil servants followed across a mean of 12 years (Nabi, Kivimaki, De Vogli, Marmot, & SinghManoux,
2008). The null association between positive affect and heart disease was evident regardless of
which covariates were included in the models. With nearly 9,000 participants and more than 600 cases of
heart disease, statistical analyses were adequately powered to detect associations. Yet, there has been some
criticism of the Affect Balance Scale (Bradburn, 1969), which was used to assess baseline positive affect.
Reliability is relatively low (e.g., alpha less than .70), some of the items may be outdated or otherwise
problematic (e.g., feeling “on top of the world”), and there is a focus on personal accomplishment rather
than pure positive feelings (McDowell, 2006). Thus, null findings could have been due to a relatively poor
assessment of positive affect.
Other work has also reported a null association between subjective well-being and coronary heart
disease though (Feller, Teucher, Kaaks, Boeing, & Vigl, 2013). In one prospective study that followed
more than 6,000 Dutch men and women over age 55 for a dozen years, neither positive affect nor negative
affect were significantly associated with incident cardiovascular disease in minimally-adjusted models and
fully-adjusted models (Freak-Poli et al., 2015). Null associations persisted when stroke, heart failure, and
coronary heart disease were investigated separately, as well as after stratification by age and gender. One
possible explanation for the null findings in both the British and Dutch studies was the relatively
homogenous cohort of participants. In both cases, socioeconomic status did not vary much and participants
were relatively well off. Notably, however, the study with British civil servants found an association
between negative affect and heart disease whereas the Dutch study did not. The null findings for negative
affect are inconsistent with other work (e.g., Kubzansky, 2007).
Another possibility in the latter study is that the measure of positive affect – a 4-item composite of
positive emotions derived from the Center for Epidemiologic Studies-Depression [CESD] scale (Radloff,
1977) – did not adequately capture positive emotional experience. Although deriving indicators of
subjective well-being from measures originally designed to assess psychological distress is not ideal
(Boehm & Kubzansky, 2012), other studies have used this approach and found evidence for an association
between positive affect and cardiovascular disease. For example, positive affect derived from the CESD
scale was related to reduced risk of incident stroke among nearly 2,500 people over the age of 65 (Ostir,
Markides, Peek, & Goodwin, 2001). These participants were followed for 6 years, and associations were
evident for men and women and blacks and whites. Moreover, the inverse association between positive
affect and stroke risk held after accounting for sociodemographic characteristics, body mass index,
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smoking status, and other health conditions (all participants were free from stroke at baseline). (For other
stroke-related findings, see also Feller et al., 2013; Lambiase, Kubzansky, & Thurston, 2015). Another
study using the positive affect items from the CESD scale also reported inverse associations with
hypertension in a cohort of older Mexican Americans (Ostir, Berges, Markides, & Ottenbacher, 2006). For
individuals who were not on antihypertensive medication, every unit increase in positive affect was
associated with 9% reduced odds of belonging to a higher blood pressure category, controlling for
sociodemographic factors, health behaviors, diabetes, and even negative affect. The association between
well-being (specifically, emotional vitality) and hypertension has since been replicated in a British cohort
(Trudel-Fitzgerald, Boehm, Kivimaki, & Kubzansky, 2014).
Apart from cardiovascular-related outcomes, other health conditions have been investigated in
relation to subjective well-being. For example, one review of the literature has suggested that well-being is
tied with diabetes (Celano, Beale, Moore, Wexler, & Huffman, 2013). A study of almost 100 older women
who were initially free from diabetes demonstrates this. Women with higher levels of baseline positive
affect tended to have healthier levels of glycosylated hemoglobin – a marker of glycemic control in recent
months – two years later, controlling for negative affect and depression diagnosis (Tsenkova, Love, Singer,
& Ryff, 2007). More recently, a prospective study of nearly 8,000 British civil servants showed that higher
levels of both life satisfaction and emotional vitality were associated with reduced odds of self-reporting a
physician diagnosis of diabetes (Boehm, Trudel-Fitzgerald, Kivimaki, & Kubzansky, 2015). These findings
held after adjusting for demographic characteristics, health behaviors, blood pressure, and body mass
index, but were attenuated for emotional vitality after adjusting for depressive symptoms (findings were
maintained for life satisfaction when adjusting for depressive symptoms). No gender differences were
reported in the study, although a separate study of more than 50,000 German participants followed across 8
years found an association between life satisfaction and incident diabetes among women but not men
(Feller et al., 2013). More specifically, women who were unsatisfied with their lives had a 17% increased
risk of developing Type II diabetes compared with their very satisfied counterparts.
In addition to examining incident diabetes in the very large German cohort, incident cancer was also
considered. Cancer outcomes are less frequently investigated in connection with psychological predictors
because of the numerous different types of cancer and somewhat less precise way to define diagnoses.
However, in this case, an association was apparent between life satisfaction and cancer across 8 years.
Unsatisfied women had a 45% increased chance of incident cancer relative to satisfied women (Feller et al.,
2013). These findings held when controlling for sociodemographic factors and health behaviors, but not
when controlling an indicator of psychological distress. Moreover, there was no association between life
satisfaction and incident cancer in men. In a different study of approximately 12,000 Finnish women, the
relationship between life satisfaction and breast cancer was investigated. No relationship existed between
life satisfaction and incident breast cancer across 21 years in age-adjusted and multivariable-adjusted
models (Lillberg et al., 2002). Such null findings for cancer have been reported in other studies as well
(Bai et al., 2016; Okely & Gale, 2016).
Nonetheless, subjective well-being has been found to be related to incident arthritis. In one 9-year
study of more than 13,000 older adults throughout Europe, higher levels of well-being were associated with
reduced risk of reporting a doctor diagnosis of arthritis (Okely, Cooper, & Gale, 2016). Other studies have
also investigated the extent to which subjective well-being is related to functional status. In one example of
this, more than 3,000 older men and women from England responded to a baseline questionnaire about
how much they enjoyed life, and then were followed for 8 years (Steptoe, de Oliveira, Demakakos, &
Zaninotto, 2014). Relative to those with high levels of enjoyment, those who reported low levels of
enjoyment had increased odds of experiencing impaired physical functioning, as indicated by self-reported
activities of daily life and objective assessment of gait speed. Findings were robust to statistical adjustment
for sociodemographic characteristics, health-related factors including behaviors, and depression. To extend
these results even further, another group of researchers investigated how well-being was associated with
incident frailty, which tends to be preceded by impaired physical function. Using the same cohort of older
English men and women, models adjusting for a variety of confounders (including depressive symptoms)
indicated that those people with higher versus lower baseline levels of well-being were less likely to
experience incident frailty across a 4-year follow-up period (Gale, Cooper, Deary, & Aihie Sayer, 2014).
These findings have been replicated in another study of elderly caregivers (Park-Lee, Fredman, Hochberg,
& Faulkner, 2009).
In People Already Diagnosed with Disease
A meta-analysis has reported that well-being is related to recovery among people who have been
diagnosed with disease (Lamers, Bolier, Westerhof, Smit, & Bohlmeijer, 2012). Another meta-analysis
specific to cardiovascular disease showed that well-being appears to be associated with reduced risk of
hospitalization and mortality in cardiac patients (DuBois et al., 2015). For example, more than 800 patients
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undergoing percutaneous coronary intervention with stent implantation had their positive affect assessed.
Those with low versus high levels of positive affect were more likely to experience myocardial infarction or
death 2 years later (Denollet et al., 2008). There is some conflicting evidence though. For example, in ageadjusted
analyses that followed more than one thousand individuals diagnosed with coronary heart disease
for 7 years, there was only a marginally significant relationship between positive affect and cardiovascular
events (heart failure, myocardial infarction, stroke, or transient ischemic attack; Hoen, Denollet, de Jonge,
& Whooley, 2013). Moreover, positive affect in patients who had undergone cardiac rehabilitation was not
associated with hospitalizations or all-cause mortality an average of approximately 3 years later (Meyer,
von Kanel, Saner, Schmid, & Stauber, 2015). However, negative affect was also included in statistical
models and the two types of affect were very strongly correlated.
In cohorts of individuals with non-cardiovascular diagnoses, subjective well-being also appears to
be related to healthier outcomes. Among elderly patients who experienced a hip fracture, those with high
levels of positive emotion demonstrated better physical performance (i.e., walking speed and chair stands)
during a 2 year follow-up period than their peers with high levels of depressive symptoms (Fredman,
Hawkes, Black, Bertrand, & Magaziner, 2006). Similarly, increases in positive emotions in the 3 months
following a stroke were associated with improved functional performance in the patients (Seale, Berges,
Ottenbacher, & Ostir, 2010).
Mortality
In Initially Healthy People
Beyond whether happier people have lower risk for disease, reviews of prospective studies indicate
that happier people tend to live longer than less happy people (Chida & Steptoe, 2008; Diener & Chan,
2011; Martin-Maria et al., 2017). For example, one meta-analysis synthesized findings through 2008 and
reported that higher levels of well-being were associated with 18% reduced risk of mortality in initially
healthy cohorts (Chida & Steptoe, 2008). Such findings have been replicated in more recent research as
well. In one case, more than 31,000 U.S. adults ages 18 and over responded to the question: “Taken all
together, how would you say things are these days – would you say that you are very happy, pretty happy,
or not too happy?” (Lawrence, Rogers, & Wadsworth, 2015). Compared to those people who reported
being very happy, those who reported being not happy were 14% more likely to die during as many as 30
years of follow-up. These findings accounted for sociodemographic characteristics, geographic region, and
religious attendance, but not psychological distress. Similar results have been replicated in more than 9,000
men and women representative of those over 50 years old living in England (Steptoe & Wardle, 2012).
Individuals who reported the highest versus lowest levels of life enjoyment had a 28% reduction in
mortality risk across an average of 7 years of follow-up, accounting for sociodemographic factors, disease
diagnoses, health behaviors, and depression.
In the same cohort of older English men and women, subjective well-being was assessed with
ecological momentary assessment in nearly 4,000 participants (Steptoe & Wardle, 2011). This type of
measurement asked participants to report on their positive feelings at four points throughout the day to
capture “experienced” subjective well-being rather than the more conventional retrospective assessment.
Across an average of 5 years, individuals with the highest level of positive affect had a 35% reduction in
mortality risk compared to those with the lowest levels of positive affect. Notably, these analyses
statistically controlled for sociodemographic factors including education and wealth, as well as negative
affect, depressive symptoms, presence of disease, cigarette smoking, physical activity, and alcohol intake.
Moreover, negative affect was not related to increased risk of mortality in this study, but depressive
symptoms were (although positive affect’s association with mortality persisted when statistically
controlling for depressive symptoms).
The work reviewed thus far indicates that there is a consistent relationship between subjective wellbeing
and longevity in Western participants, but does the relationship generalize to other groups? Work on
this topic with diverse samples of participants is limited, but one notable study followed more than 5,000
older Taiwanese adults across 10 years (Collins, Glei, & Goldman, 2009). Individuals who were more
satisfied at baseline had lower risk of mortality than their less satisfied peers, controlling for
sociodemographic factors, indicators of health and health behaviors, and depression. This initial evidence
suggests that the association between subjective well-being and longevity exists for other cultural groups as
well (see also Kimm, Sull, Gombojav, Yi, & Ohrr, 2012; Yiengprugsawan, Seubsman, & Sleigh, 2014).
Other moderators of the association between subjective well-being and longevity have been
increasingly explored, including the extent to which subjective well-being remains stable over time.
Although subjective well-being – in particular, life satisfaction – is often thought of as being relatively
consistent across time, it can change due to life circumstances such as divorce or unemployment (Lucas,
Dyrenforth, & Diener, 2008). Thus, single assessments of subjective well-being at one point in time may
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not capture the whole story of a person’s sense of well-being. Several studies have now investigated how
fluctuations in subjective well-being are related to longevity. In one study, more than 9,000 older men and
women living in England reported their life enjoyment on three separate occasions across 6 years
(Zaninotto, Wardle, & Steptoe, 2016). Those who reported enjoying life at all three occasions had a 24%
lower risk for death up to 7 years later compared to those who reported not enjoying life at any occasion.
Furthermore, there was a graded relationship such that those who reported enjoying life at only two
occasions had a 17% reduced risk of death relative to those who did not enjoy life at any occasion.
Findings held after controlling for demographic factors, health, and depression.
Another study of more than 4,000 Australian men and women ages 50 and over used a different
approach to conceptualize maintenance of subjective well-being across time (Boehm, Winning, Segerstrom,
& Kubzansky, 2015). A single item of life satisfaction was assessed annually across as many as nine years.
The mean and standard deviation of each person’s life satisfaction ratings were then calculated to get a
sense of the stability and variability of life satisfaction across time. Consistent with past research, higher
versus lower mean levels of life satisfaction were associated with reduced risk of mortality during the
follow-up period. However, the variability in satisfaction that a person experienced across time modified
the relationship such that the least satisfied people who also had fluctuating levels of life satisfaction had
the highest risk of mortality. These results further confirm that sustaining high levels of SWB across time
are important to associations with longevity, while variability may be detrimental. Moreover, these studies
highlight the importance of looking at subjective well-being across time rather than as a static phenomenon,
as most studies do (for another example that considers time-varying subjective well-being, see Collins et
al., 2009).
Although the vast majority of studies have assessed subjective well-being via self-reported
questionnaires – including single item ratings or multi-item questionnaires that have been validated such as
the Satisfaction With Life Scale (Diener, Emmons, Larsen, & Griffin, 1985; Pavot & Diener, 2008) –
sometimes subjective well-being is assessed via indirect methods. Such studies also point to an association
between subjective well-being and longevity. For example, one group of researchers evaluated the intensity
of smiles that Major League Baseball players displayed in their photographs (Abel & Kruger, 2010). Those
players with Duchenne, or genuine smiles, were half as likely to die when compared to those players
without a smile. Likewise, another study assessed the subjective well-being of nuns in their twenties by
evaluating autobiographies the nuns had written for content related to positive emotions (Danner,
Snowdon, & Friesen, 2001). There was a 2.50-fold difference in the relative risk of mortality between nuns
who wrote with great positive emotion and those who wrote with little positive emotion, controlling for
age and education. In short, nuns who expressed more positive emotions early in life lived longer than
those who expressed fewer positive emotions. In other work, the use of activated positive emotion words
(e.g., lively, vigorous) but not less activated positive emotion words (e.g., calm, peaceful) were related to
longevity in famous psychologists (Pressman & Cohen, 2012).
Lest it seem that all studies have reported associations between subjective well-being and longevity,
there is one notable and well-publicized study that reported conflicting evidence (Liu et al., 2016). More
than 700,000 women from England and Scotland (median age of 59 years) were asked about their
happiness with the single item: “How often do you feel happy?” Responses ranged from “most of the time”
to “rarely/never.” Mortality was assessed during a follow-up period across an average of nearly 10 years. In
models adjusting for sociodemographic characteristics, body mass index, health behaviors, and religious
participation, women who were unhappy had an increased risk of mortality compared with women who
were happy most of the time. However, when self-rated health was also included in the analytic models,
happiness was no longer associated with mortality. The authors attribute the null association to the fact that
bad health can foster both less happiness and increased risk of death.
Yet other researchers have noted limitations in this study, the primary one being that the statistical
analyses adjusted for too many variables (Diener, Pressman, Hunter, & Delgadillo-Chase, 2017;
Kubzansky, Kim, Salinas, Huffman, & Kawachi, 2016). In particular, self-reported happiness and selfreported
health are known to be robustly correlated, and judgments of one may be informed by judgments
of the other (Benyamini, Idler, Leventhal, & Leventhal, 2000). To compound matters in this study, selfrated
happiness and health were assessed at the same time with similar, single item self-report questions (so
they not only shared common variance due to methodology, but were also less reliably measured). Thus, it
is not surprising that self-reported health attenuated the association between happiness and longevity.
Nonetheless, this study provides a helpful reminder for researchers to be thoughtful about which covariates
are included in analyses when examining associations between subjective well-being and longevity, with a
particular caution about how to interpret attenuation that could occur as a result of including highly
correlated variables or potential pathway variables (Diener et al., 2017). Moreover, optimal analyses would
incorporate repeated, reliable assessments of both the exposure and covariates that allow for consideration
660
of mechanistic relationships more explicitly (Stringer & Veldkamp, 2016). Such causal modeling has not
yet been done in this area of research but is greatly needed (Diener et al., 2017).
In People Already Diagnosed with Disease
Consistent with findings in initially healthy populations, happy people who have been diagnosed
with a disease seem to have a reduced risk of mortality compared with unhappy people diagnosed with a
disease. Notably, however, the effect seems to be smaller. One meta-analysis estimated that on average,
there was a 2% reduced risk of mortality for happy versus unhappy patients (compare that with the 18%
reduced risk for initially healthy people; Chida & Steptoe, 2008). A second, more recent meta-analysis
came to a similar conclusion that a small but meaningful relationship existed between well-being and
survival in people with existing disease (Lamers et al., 2012). However, both meta-analyses note the
heterogeneity in the studies with patient cohorts – for example, different patient populations with varying
types and severity of disease, follow-up periods, and quality – all of which could contribute to smaller
effects.
As an example, one year-long study found an association between a single item about enjoying life
and reduced risk of all-cause mortality (Scherer & Herrmann-Lingen, 2009). Participants were medical
inpatients, and statistical models controlled for physicians’ estimate of the patients’ prognosis, primary
diagnosis, and comorbidity. In another study of more than 400 men who were HIV positive, those with
higher baseline levels of positive affect – as assessed by the CESD – had a reduced risk of mortality
compared to those with lower levels of positive affect (Moskowitz, 2003). Results were robust to statistical
adjustment for indicators of illness progression, as well as negative affect. The same researcher has
reported similar findings for people diagnosed with diabetes. That is, in more than 700 individuals who
reported having a physician-diagnosis of diabetes, those with higher levels of positive affect had a reduced
risk of mortality across 10 years (Moskowitz, Epel, & Acree, 2008). However, the association was
attenuated when negative affect was simultaneously included in the models.
Among individuals with stable coronary heart disease, positive affect was associated with a 13%
reduced risk of death across an average of 7 years (Hoen et al., 2013). These findings held when adjusting
for baseline disease severity, as well as depression. However, when health behaviors – particularly physical
activity – were added to the models, the association was attenuated to non-significance. Similar findings
were evident in a study of six hundred Danish individuals with ischemic heart disease. People with higher
versus lower levels of positive emotions had a lower risk of all-cause mortality across as many as five
years, however, that relationship was mediated by physical activity (Hoogwegt et al., 2013). In contrast,
baseline positive affect was not related to mortality within 3 years in nearly six hundred Dutch patients
with implantable cardioverter defibrillators (van den Broek et al., 2013).
Pathways Linking Subjective Well-Being
With Morbidity and Mortality
Given subjective well-being’s apparent associations with health and longevity, it is worth
considering the mechanisms by which it may operate to influence morbidity and mortality. Past work has
identified three primary pathways: 1) buffering against the harmful effects of stress on physiological
processes, 2) directly affecting physiological processes, and 3) impacting behavioral processes (Boehm &
Kubzansky, 2012; Ong, 2010; Pressman & Cohen, 2005). With regards to stress buffering, evidence
suggests that subjective well-being can help ameliorate the physiological effects of stress (Fredrickson &
Levenson, 1998; Papousek et al., 2010; Tugade & Fredrickson, 2004). For example, during acute stressor
tasks in the laboratory, higher levels of positive emotions hasten blood pressure recovery and attenuate
cortisol responses (Bostock, Hamer, Wawrzyniak, Mitchell, & Steptoe, 2011). This buffering effect may
occur outside of the laboratory as well. In one study, cardiac patients with high levels of negative emotions
and high levels of positive emotions did not have the same increase in mortality risk as those with high
levels of negative emotions and low levels of positive emotions, which suggests that positive emotions
may buffer against the detrimental effects of negative emotions (Meyer et al., 2015).
Numerous studies have also established that subjective well-being has links to underlying
physiological processes that have implications for disease (Ryff et al., 2006; Steptoe, Demakakos, de
Oliveira, & Wardle, 2012; Steptoe, Wardle, & Marmot, 2005). For example, in the cardiovascular domain,
life satisfaction has shown protective associations with cardiometabolic markers of risk including blood
pressure, lipids, glycosylated hemoglobin, waist circumference, and C-reactive protein (which is an
indicator of inflammation; Boehm, Chen, Williams, Ryff, & Kubzansky, 2016). Other work has also
reported that subjective well-being is associated with lower levels of inflammation (Prather, Marsland,
Muldoon, & Manuck, 2007; Stellar et al., 2015; Steptoe, O'Donnell, Badrick, Kumari, & Marmot, 2008), as
well as healthier heart rate variability, which indexes sympathetic and parasympathetic activation
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(Bhattacharyya, Whitehead, Rakhit, & Steptoe, 2008; Oveis et al., 2009; Shiota, Neufeld, Yeung, Moser, &
Perea, 2011; Wang, Lü, & Qin, 2013). Notably, most of this work has examined linear relationships
between subjective well-being and biomarkers, although limited work suggests that not all relationships
between subjective well-being and physiological processes may be linear in nature (Kogan, Gruber,
Shallcross, Ford, & Mauss, 2013).
In the behavioral domain, accumulating evidence has also shown that subjective well-being is linked
with preventive behaviors that protect against disease (Grant, Wardle, & Steptoe, 2009; Sin, Moskowitz, &
Whooley, 2015; Strine, Chapman, Balluz, Moriarty, & Mokdad, 2008). Moreover, often subjective wellbeing
precedes the healthy behavior (although healthy behavior sometimes precedes subjective well-being
too, e.g., Mujcic & Oswald, 2016). For example, greater levels of subjective well-being are tied with more
frequent exercise (Baruth et al., 2011; Kim, Kubzansky, Soo, & Boehm, 2017; Lathia, Sandstrom,
Mascolo, & Rentfrow, 2017; Melin, Fugl-Meyer, & Fugl-Meyer, 2003; Rangul et al., 2011; Schnohr,
Kristensen, Prescott, & Scharling, 2005; Schwerdtfeger, Eberhardt, Chmitorz, & Schaller, 2010), healthier
diets comprised of fruits, vegetables, and whole grains (Lengyel, Tate, & Obirek Blatz, 2009; van Loon,
Tijhuis, Surtees, & Ormel, 2001; Yamasaki, Nagai, & Uchida, 2007), reduced likelihood of cigarette
smoking (Kaprio & Koskenvuo, 1988; Leventhal, Ramsey, Brown, LaChance, & Kahler, 2008), higher
quality sleep (Lacruz et al., 2016; Ong et al., 2013; Steptoe, O'Donnell, Marmot, & Wardle, 2008), and
more preventive health care visits (Kim, Kubzansky, & Smith, 2015; Kim, Park, Sun, Smith, & Peterson,
2014).
Conclusions and Future Directions
The reviewed evidence suggests that there is a consistent association between subjective well-being
and both incident disease and longevity such that people with greater life satisfaction and positive emotions
have healthier outcomes in adulthood. Protective effects for subjective well-being often remain when
psychological distress is taken account, which indicates that subjective well-being has independent
associations above and beyond those already known for distress. Furthermore, associations in initially
healthy people often persist when taking into account confounders like socioeconomic status. The
associations between subjective well-being and disease progression and survival in people with existing
disease are not quite as consistent or strong. This group of studies tended to be more diverse with numerous
different types of diseases and studies taking place at different points in the disease process. Disease
severity, in particular, may be an important moderating factor because as severity increases, more powerful
effects are needed to overcome entrenched disease processes and other factors such as treatment become
relevant (Tay, Tan, Diener, & Gonzalez, 2013). Nonetheless, overall findings seem to indicate modest
relationships between subjective well-being and disease prognosis, but these are often attenuated when
statistical analyses are adjusted for covariates such as psychological distress or health behaviors. Until more
empirical evidence is available with similar patient types, firm conclusions about links with subjective wellbeing
in patient populations may not be warranted.
Relatedly, it is also important to consider the extent to which findings from both the healthy and
patient populations generalize to more diverse groups of people (Diener et al., 2017). For the most part, the
available evidence to date has focused predominantly on white, older adults from Westernized countries
(cf. Collins et al., 2009). Although some evidence suggests that positive emotions may be important to
health for people from a wide variety of countries (Pressman, Gallagher, & Lopez, 2013), future research is
needed to consider the extent to which the associations described here generalize to individuals from other
countries, cultural groups, ages, and generations.
In addition to considerations regarding who associations between subjective well-being and health
may be relevant for, it is critical to consider how subjective well-being is measured. Because much of the
work to date has relied on epidemiological cohorts in which participant burden is a concern, indicators of
subjective well-being have often been single items or derived from existing depression inventories (Boehm
& Kubzansky, 2012). Although such measures may be better than nothing, the time has come to move
away from less reliable single items or conceptually unclear scales that were originally designed with
another purpose. More purposeful selection of which subjective well-being measure to include in cohort
studies will shed light on conceptual issues as well. For example, does experienced subjective well-being,
as assessed via ecological momentary assessment, show stronger associations with health outcomes
compared with trait assessments of subjective well-being? Does the cognitively oriented facet of life
satisfaction matter more for health than the affectively oriented facet of positive emotions? Are there
specific positive emotions – whether high arousal ones like excitement or low arousal ones like calm – that
are especially relevant for health? To date, such comparisons have rarely been made because well-being
indicators have typically been selected based on convenience. Future research is ripe for such
considerations though. Moreover, moving beyond assessment of subjective well-being at a single point in
time to consider changes in well-being over time may provide further insight into health processes. As
662
noted earlier, the stability in subjective well-being across substantial periods of time may itself be an
important predictor of both physical and mental health (Boehm, Winning, et al., 2015; Gruber, Kogan,
Quoidbach, & Mauss, 2013; Zaninotto et al., 2016). Another outstanding issue is under what circumstances
too much subjective well-being could be bad for health. High levels of positive emotions are not adaptive in
every circumstance (Gruber, 2011; Gruber, Mauss, & Tamir, 2011), so a more precise look at the exact
levels that are beneficial may be warranted.
Another consideration in the association between subjective well-being and health is the size of the
relationship that is reported. Although effect sizes are typically in the small to moderate range, these effects
are comparable with other well-established risk factors for disease. Moreover, the determinants of coronary
heart disease, diabetes, cancer, and other diseases are numerous, so any one factor (whether subjective
well-being, cigarette smoking, or family history) is likely to contribute rather modestly. However, at the
population level, such associations can have a measurable impact, especially if effects of subjective wellbeing
compound over time to further strengthen effects (Abelson, 1985; Friedman & Booth-Kewley, 1987).
Although the evidence reviewed in this chapter primarily assumed that subjective well-being
precedes and leads to healthier outcomes, it is also possible that poor health negatively impacts subjective
well-being (Diener et al., 2017). For example, one study of older adults followed across 8 years found that
self-reported health predicted life satisfaction, but that life satisfaction did not predict health (Gana et al.,
2013). Although this study was limited by a subjective assessment of health, it is likely that the relationship
could go in either direction or is bi-directional. Nevertheless, the prospective longitudinal studies described
in this chapter provide some of the strongest possible evidence available to support the idea that subjective
well-being comes before and brings about healthier outcomes. The only other stronger evidence available
would be a randomized experiment; however, such designs come with their own drawbacks (Diener et al.,
2017). Although perhaps not feasible over the years or decades that are usually seen in prospective designs,
accumulating evidence suggests that interventions designed to improve subjective well-being are effective,
at least in the short-term (Bolier et al., 2013; Weiss, Westerhof, & Bohlmeijer, 2016). Moreover, well-being
interventions are being developed to impact downstream health-related outcomes for healthy individuals
(Jackowska, Brown, Ronaldson, & Steptoe, 2016) and individuals diagnosed with chronic conditions
(Huffman et al., 2015; Moskowitz et al., 2017; Moskowitz et al., 2012; Nikrahan, Laferton, et al., 2016;
Nikrahan, Suarez, et al., 2016; Ogedegbe et al., 2012; Peterson et al., 2012; Sanjuán et al., 2016). Although
future research is necessary to determine whether or not well-being interventions can translate into
improved health outcomes over the long-term, a large body of evidence reviewed here indicates that
among initially healthy people – and to a lesser extent in people who have already been diagnosed with a
disease – robust associations exist between higher levels of subjective well-being and healthier and longer
lives. As the empirical evidence continues to grow, the boundary conditions and mechanistic pathways by
which such associations occur will also come into clearer focus.
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2018 Ed Diener. Copyright Creative Commons: Attribution, noncommercial, no
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Using Multiple Methods to More Fully Understand Causal
Relations: Positive Affect Enhances Social Relationships
By Shannon M. Moore*, University of Utah; Ed Diener, University of Utah, University of Virginia, and
The Gallup Organization; Kenneth Tan, Singapore Management University *Now at the U.S. Army
Research Lab
Citation
Moore, S. M., Diener, E., & Tan, K. (2018). Using multiple methods to more fully understand causal
relations: Positive affect enhances social relationships. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
We review research indicating that higher levels of positive affect help produce better social relationships
for that person and those around him or her. By better relationships we mean those that are experienced as
more pleasant and less aversive, are closer and more supportive, and are long-lasting. We review
longitudinal, experimental, experience-sampling, cross-cultural, and other types of evidence that suggest
that not only do good relationships produce positive affect, but that positive affect can lead to them as
well. We also focus on the mediators that create the association going from positive affect to sociability
and high-quality relationships. Finally, we review the unknowns in this area and the types of future
research still needed.
Keywords: Positive affect, subjective well-being, relationships, relationship quality
Is it self-evident that those with the most positive affect would be more socially successful? We
think not. For one thing, many consider happiness to be a hedonistic endeavor, which focuses the person
on pleasures, often selfish ones. In popular writing, authors such as Ehrenreich (2009) have argued that
happiness can lead to problems rather than to success. Thus, we find it implausible that the causal
connection we review in this paper is common knowledge, making it even more important to ensure there
is a wide range of literature that supports the conclusion that successful social relationships follow from
positive affect.
In the following article, we review evidence that indicates that positive feelings do not simply
follow from quality social relationships, but in turn increase their likelihood. Most importantly, we point
out the holes still remaining in this research area since the earlier review by Lyubomirsky, King, and
Diener (2005). Positive affect includes the moods and emotions that people experience as desirable and
pleasant. While people who experience more frequent positive feelings tend to have stronger and more
supportive social relationships, certain types of studies are still needed to further understand when and why
positive affect is beneficial to social relationships. We review the correlational, longitudinal, and
experimental evidence that suggests a causal arrow moving from positive affect to quality social
relationships (as first proposed by Lyubomirsky et al., 2005). We will also review the mediating
mechanisms that help explain the causal connections, as well as the moderators that influence the strength
of the connections. Our review focuses on positive feelings as a variable that is separable from low
negative affect, and which has a causal influence that goes beyond predictions from negative feelings.
Defining Quality Social Relationships
Before we define what we mean by quality social relationships, we would like to start by
introducing several theories of emotion that might predict why positive feelings may benefit social
relationships. First, functional approaches to emotion hypothesize that a major function of emotion is to
guide behavior, as well as reinforce behaviors through feelings of reward or punishment (Keltner & Haidt,
1999; Keltner & Kring, 1998). Positive emotions have informational value, telling the individual that the
activity is worth repeating, and the pleasant feelings of the positive emotions reinforce the behaviors
leading to them. Thus, positive emotions can reinforce social activities such as games and conversation,
which are often rewarding, leading people to seek out these activities in the future.
A related conceptual explanation of the connection between positive affect and sociability is in
terms of the approach versus avoidance motivational systems (Gable, 2006). Human beings have a
fundamental need to belong, and possess a powerful motivation to form and maintain strong and stable
interpersonal relationships (see Baumeister & Leary, 1995; Reis, Collins, & Berscheid, 2000 for reviews).
Social relationships have the propensity to provide rewards that fulfill interpersonal needs, but also threaten
punishments that leave us feeling vulnerable and hurt. As such, individuals are motivated to both approach
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rewards and avoid the punishments inherently found in social relationships. Positive affect may trigger the
approach system, which Gable finds is related to greater relationship satisfaction and less loneliness. The
idea is that the behavioral activation system, which underlies positive feelings, should trigger approach
tendencies toward others. This is supported by work by Girme, Overall, Simpson, and Fletcher (2015); they
studied a New Zealand sample and found that people reported greater life satisfaction when they reported
higher approach goals (r = .28 & .3), and this association was stronger for people in romantic relationships.
A third theoretical explanation for the link between positive feelings and better relationship quality
is Fredrickson’s broaden-and-build model (1998, 2001; Fredrickson, Cohn, Coffey, Pek, & Finkel, 2008).
Fredrickson suggests that the reason we experience positive emotions is to broaden and build our resources
for the future, and one key type of resource is social support. We experience positive emotions when we
have been successful and there are no imminent threats. It is in these situations that people have more
freedom to build resources and skills for the future. Therefore, positive feelings allow us to form tighter
bonds with others by doing rewarding activities with them, and by helping others in a way that they are
likely to reciprocate in the future.
What are high-quality social relationships?
1. The relationships are pleasant and rewarding. People enjoy the relationships and do not experience
chronic negative thoughts and feelings in them.
2. The relationships are close and supportive. People can rely on the other person for emotional
support, physical support, and understanding. Here, we will also rely on prosocial behavior as
outcomes suggesting more supportive relationships. In that prosocial behavior (e.g., donations, aid)
are signs of support, we feel that these findings can stand in as proxies of interpersonal support as
such tendencies would likely extend to closer relationships as well.
3. The relationships tend to be long-lasting. Relationships that last longer help build predictability and
security into people’s lives. Although, short-term relationships can be rewarding, they usually do not
provide an ongoing basis for achieving goals and providing support and security.
Thus, these are the three characteristics of high-quality social relationships that we concentrate on in
this review, and we examine how positive affect increases each of them.
Causal Analysis
Beyond simply reviewing evidence that makes it plausible that there is a causal arrow pointing from
positive affect to better social relationships, we plan to also describe research still needed to establish this
association. Thus, to understand how positive affect improves social relationships in the natural world, we
review various methods, each providing distinct information about the causal system that could provide
insight as to whether positive affect causally influences subsequent improvements in social relationships.
We examine simple correlational evidence because it can quickly reveal where associations exist
and do not exist. The correlational studies reveal that there is a connection between the two variables in
many different groups, including in the many nations that have been studied so far. These data indicate the
ubiquity of the association between the two variables. However, it is important to note that correlational
research does not on its own indicate causation.
We also describe longitudinal research where we can examine whether a possible cause precedes a
hypothesized outcome and whether a change in a causal variable over time precedes a change in the
outcome. Although longitudinal studies do not have the same internal validity as formal experiments in
terms of inferring causality, more external validity is usually present because longitudinal methods help
establish not just that X can cause Y, but that it actually seems to do so in everyday settings where there are
a host of interacting forces. Short-term longitudinal studies such as those using the experience-sampling
method help to establish whether two variables move up and down together in short time periods. Longterm
longitudinal research reveals the development of the connection over time—its dynamic unfolding.
Formal experiments can manipulate both short-term positive moods and enhance long-term positive
affect and examine the short and long-term effects, respectively, on improvements in social relationships.
Experiments are thus seen as the strongest evidence of causality due to high internal validity.
Experimentation has limitations, despite its internal validity, that the other methodologies can complement
with their strengths. For example, experiments usually are relatively low on external validity, and are
focused on relatively small samples of participants. Furthermore, experimental manipulations are often not
“clean,” in the sense that factors are often manipulated beside the concept intended. For example, mood
manipulations frequently include social content in the induction. Thus, the researcher cannot be certain that
the outcomes are due to the positive affect aspect of the manipulation per se or to the priming of social
cognitions. In addition, laboratory experiments are subject to biases such as demand characteristics.
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Finally, experiments must be so carefully focused on controlling the context of the situation that we often
gain little insight into the conditions that must be in place for the causal connection to occur. Fortunately,
the other methods, although possessing less internal validity, tend to not have the same limitations, and thus
are likely to expand understanding beyond that provided from experimentation. Taken together, these
methodologies can indicate causal direction and help us understand how the dynamic system functions.
Thus, when considering the link between positive affect (PA) and positive social outcomes, it is important
to determine the types of studies that are lacking, as the conclusion that positive affect leads to better
relationships requires comprehensive evidence.
Beyond these methodologies, scientific understanding of causality also requires understanding of
mediators and moderators. The mediators explain the processes that link X to Y, and the moderators place
boundaries on the causal sequence. Establishing the moderators allows us to know when the causal
sequence will be stronger and weaker, and when it does not occur at all. In sum, several approaches are
needed in understanding causal influences in the dynamic networks that psychologists study, such as
positive mood causing sociability and social success.
Positive Affect is Linked to Positive and Rewarding Relationships
We first look at research showing how positive affect is linked to what we offered as our first
definition of quality relationships, that they be positive and rewarding.
Correlational research. Based on environmental and genetic influences, sociability has been found
to correlate with positive emotionality (Eid, Riemann, Angeitner, & Borkenau, 2003; r’s = .27 to .57). In
one study, participants filled out daily reports for six weeks, which were then averaged across days. While
extraversion and positive affect were found to be separable, they were highly related (r = .380). These
results cannot be attributed to self-report biases, as observer reports were also used to assess the variables
(r’s = .293 to .577) (Fujita, 1991).
Correlational research also supports that positive affect is linked to more rewarding relationships.
One study found that extraversion (which is highly related to PA; Fujita, 1991) was associated with making
more friends (Feiler & Kleinbaum, 2015; r = .34). However, no correlational research appears to directly
link positive affect and the propensity to make friends. Moreover, it has been found that those with high PA
are liked more by others. This may be due to the fact that they are judged as more rewarding to spend time
with (Harker & Keltner, 2001; r = .70). Diener and Seligman (2002) studied the happiest 10% of students
and found that they experienced better romantic relationships (η2 = .24 to .44). In this study, happiness was
determined by examining satisfaction with life, global self-reported affect, informant affect balance, and
daily affect balance over 51 days. Affect balance refers to the prevalence of positive affect over negative
affect and is used to define “happiness” (Diener, 1984). Thus, because of the important role PA plays in
affect balance, here and at other times, we refer to results addressing affect balance because they are
important leads and point to a need for additional research, especially when affect balance is the only
measure currently available (i.e., little or no evidence in terms specifically of positive affect). Those who
experience greater positive feelings also exchange more often during negotiations (Lawler, Thye, & Yoon,
2000; β = .58), suggesting that when people interact with those who have higher levels of positive affect,
they can expect more favorable outcomes. Individuals higher in PA can be expected to have more friends,
to be rated more positively by others, and to report more positive interactions.
Another correlational finding that can be explored in terms of PA is its relation to sex. While
measures of subjective well-being are strongly correlated with frequency of sexual activity (Blanchflower
& Oswald, 2004, p. 402; “a large effect”), to the best of our knowledge, this has not been explored a great
deal in terms of its relationship to positive affect. For example, Muise, Schimmack, and Impett (2015) did
find that there were curvilinear associations of sexual frequency with PA; specifically, having sex once a
week was associated with greater happiness, especially for those currently in romantic/married
relationships. However, no additional effect was found for people having sex more than once a week (β =
.09 & .35). Thus, while there is minimal research on the association, work suggests PA is positively related
to sexual activity.
The specific social skills and traits exhibited by those with high or low PA also needs to be studied
in further detail. Depression is highly relevant in this regard, where a key feature of depression is low
positive affect (Watson, Clark, & Carey, 1988; r’s = -.41 to -.37), not simply high negative affect. For
example, in a review, depression was associated with a variety of poor social skills (Segrin, 2000) in areas
such as paralinguistic behaviors, speech content, posture and gestures, etc. Specifically, the review
indicated that the depressed are more verbally aggressive and discuss more negative verbal content.
Moreover, low positive affect is accompanied with feeling unsociable, being bored, as well as lacking in
energy (Diener, Kanazawa, Suh, & Oishi, 2015), which might detract from maintaining good relationships
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and engaging in social interactions. Interestingly, anhedonia (i.e., diminished interest/pleasure in response
to previously rewarding stimuli) is a symptom of depression (Feighner et al., 1972). Anhedonia has itself
been linked to social impairment, and the association between anhedonia and social impairment was
partially mediated by poorer attentional control, such that deficits in the ability to engage in self-regulation
negatively impacted social functioning and social relationships (Tully, Lincoln, & Hooker, 2014; r = .66).
Thus, it is possible that less happy people are generally less skilled at maintaining social relationships.
Anhedonia has also shown to be associated with lower than normal positivity offset (i.e., mild positive
moods when no strong emotional events occur; Strauss, Visser, Lee & Gold, 2017). This might be
particularly relevant because prior research has suggested that the positivity offset is beneficial for social
relationships (Diener et al., 2015). However, the research on why low positive affect specifically is
associated with poor social outcomes is still in the preliminary stages, and these effects need to be specified
in future research.
Long-term longitudinal data. Studies show that over time, those with higher levels of positive
affect have relationships that are more rewarding. One study suggests that positive affect may be able to
compensate for low social skills in marriages. For those with low social skills and low PA, the decline in
satisfaction is approximately 20+ points over 4 years, but with high PA, this decline is reduced to
approximately 10+ points over 4 years (Johnson et al., 2005, p. 23). While the influence of marriage on PA
has not been studied, this has been examined for life satisfaction, which we will use here as a proxy as they
are closely related (e.g., Lucas, Diener, & Suh, 1996; r’s = .28 to .52). A meta-analysis indicated that
getting married is initially positive for life satisfaction (b0 = .26), though on average it tends to return
toward baseline levels over time (Luhmann, Hoffman, Eid, & Lucas, 2012). While one might expect PA to
show a similar course, it would be prudent to study this directly and see how positive affect specifically
rises or falls after marriage.
Experience sampling longitudinal data. Experience sampling indicates that positive moods are
related to more interactions with others and feeling more sociable. PA/extraversion is related to the
frequency (β = .34 & .23) and pleasantness of interactions (β = .32), even after controlling for the related
variables of negative affect-neuroticism, openness to experience, conscientiousness, and agreeableness
(Berry & Hansen, 1996). As mentioned earlier, correlational research shows that when people are in a
naturally occurring positive mood, they also feel more sociable and this result is replicated in longitudinal
experience sampling data as well (Diener et al., 2015). Feeling sociable is associated with positive affect
over time within individuals. The authors signaled 42 respondents at random moments twice a day for 42
days. In a reanalysis of these data, they found the mean within-persons correlation was r = .48 between
positive affect and feeling sociable. Importantly, this correlation was significant and positive for 41 of the
42 respondents (see Diener & Larsen, 1984, for a description of this data set). A similar relationship was
found between-subjects (r = .39).
What the experience sampling studies indicate is that not only do trait levels of positive affect lead
to sociability, momentary state levels of positive affect are also associated with feeling sociable. They also
reveal that this association is found within most individuals. The within-subject data are important in
revealing the effects of momentary mood, but are also pivotal in terms of indicating that the findings in this
field are not just due to between-persons response styles.
Experimental—short-term moods. Experimental studies indicate that inducing positive moods in
the laboratory can also lead to greater sociability and better social skills. A positive mood induction led
people to feel more social (ηp
2 = .07 & .10) and prefer social situations (η p
2 = .04 & .06) (Whelan &
Zelenski, 2012). Those put in a positive mood also showed greater interest in social activities compared to
those in a neutral mood (Cunningham, 1988a) as well as those in a depressed mood (Cunningham, Shaffer,
Barbee, Wolff, & Kelley, 1990; r = .23). Interactions also appear to proceed more favorably when one is in
a positive mood. Inducing positive moods in child psychiatric patients led them to show better social skills
compared to those in the neutral condition (Kazdin, Esveldt-Dawson, & Matson, 1982). Another relevant
finding is that the implementation of a positive musical mood induction led to both objectively and
subjectively greater sexual responses compared to baseline and negative mood inductions (Mitchell,
DiBartolo, Brown, & Barlow, 1998). Studies focused on positive mood inductions indicate that positive
moods lead individuals to feel more social, exhibit better social skills, and experience greater sexual
arousal.
Experimental—inductions that alter long-term PA. Experimental research has also found that
manipulating a change in long-term positive affect can lead to lasting interpersonal changes, contributing to
more pleasant and rewarding relationships. Loving-kindness meditation is intended to improve relations
with others and increase warmth and caring for the self. In one study, those assigned to the loving-kindness
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meditation condition became more positive (i.e., calm, happy, loving; ηp
2 = .12) and less negative (i.e.,
angry, anxious, unhappy; ηp
2 = .04). Those in the loving-kindness meditation condition also experienced
increased positivity toward others (ηp
2 = .03) (Hutcherson, Seppala, & Gross, 2008). Other studies, such as
Fredrickson, Cohn, Coffey, Pek, and Finkel (2008), indicate that we can expect these effects to last at least
up to nine weeks. In Fredrickson et al. (2008), loving-kindness meditation increased daily positive
emotions. These positive emotions were in turn linked to increases in personal resources, such as positive
relations with others. Overall, it was concluded that the increase in personal resources led people to become
more satisfied with their lives.
A study by Kemeny et al. (2012) also found long-term social benefits as the result of a meditation
intervention. The researchers used a meditation and emotion regulation training intervention to determine
how it influenced participants emotionally and socially. The intervention incorporated concentration
practices, mindfulness practices, and attempted to promote empathy and compassion and the understanding
of the features of emotions and their consequences in one’s self and others. Female schoolteachers were
randomly assigned to a training group or a control group. Those who received training reported feeling less
negative emotion (r = -.51), less depression (d = .81), and increases in positive affect and mindfulness ( r =
.37) compared to the control group. This was still true five months after the training (e.g., depression: d =
.90). Those who received training showed greater feelings of compassion, better recognition of others’
emotions, and when asked to discuss an upsetting issue with their significant other, they were less hostile
during that interaction. This indicates that the intervention helped create closer and more supportive
relationships.
One issue with mindfulness interventions is that social feelings tend to be included in the treatment.
Thus, it is difficult to determine from these studies alone whether positive feelings alone will lead to
improvement in relationships. However, the studies reviewed above have seen encouraging and lasting
results. Though additional work is needed, the existing studies suggest that long-term changes in SWB also
lead to better relationships and that those benefits persist over time.
Positive Affect is Linked to Closer, Supportive Relationships
We next look at research showing how positive affect is linked to what we offered as our second
definition of quality relationships, that they would show evidence of being closer as well as being more
supportive.
Correlational research. Relationships with those who have higher positive affect appear to be
closer, characterized by holding relational values, experiencing greater liking, and having more meaningful
conversations. Positive affect is correlated with having social values, such as placing importance on
intimacy and social approval (Kunzmann, Stange, & Jordan, 2005; r = .27). Positive affect is also positively
associated with friendship, assessed by measuring “liking” for a close friend (Cheng & Furnham, 2002; r =
.31). Happiness, assessed with an affect balance score, is negatively related to discrepancies between ideal
and actual best friendships (Demir & Orthel, 2011; r = -.21), indicating that happier individuals are more
likely to experience the quality of friendships that they desire. In a study of call center employees, greater
verbal fluency during calls (i.e., minimal pausing, fumbling, or use of fillers) was positively associated with
their own positive affect after the call (Rothbard & Wilk, 2011), suggesting that higher positive affect is
associated with better conversations. Gable, Reis, Impett, and Asher (2004) found that when people shared
their positive events with each other, they experienced higher positive affect. Another study by Gable,
Gonzaga, and Strachman (2006) established that in discussing positive events together, a phenomenon
called “capitalization”, couples rated their partners as more responsive when they also perceived that their
partner was more excited by the event that they were discussing (r = .41 & .31). Thus, the display of
positive emotions during conversation may make one appear more responsive.
Additional correlational evidence indicates that those with higher PA also experience more
supportive relationships. George (1991) found in the workplace that positive mood was linked to helpful
behavior, both for actions included (i.e., customer service; r = .26) and not included (i.e., altruism; r = .24)
in one’s job. However, the study did find that trait positive affect was not correlated with those behaviors.
One possible reason for this finding may be evident in a study by Organ and Ryan (1995). They found that,
in a review of 55 studies, self-ratings (vs. ratings by others) are associated with higher correlations within
the organizational citizenship behavior literature (r = .14). This could be relevant as George (1991) used
supervisor ratings of tendency toward behaviors. Additionally, Siedlecki, Salthouse, Oishi, and Jeswani
(2013) found that provided support predicts positive affect (β = .13). Though PA was not linked to other
types of social support in this study (i.e., enacted or perceived), other aspects of subjective well-being such
as life satisfaction were (β = .13 & .18). In this study, enacted support constituted emotional, tangible, and
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informational support received from others, yet these individual types of support could also be examined
separately for their relations to positive affect. This appears to be a fairly unexplored area, and much
research could still be conducted on how positive affect is correlated with specific types of support.
Long-term longitudinal research. Another sign of closeness in relationships is the experience of
certain important life events, such as having children, getting separated, or getting divorced. While this has
not been studied specifically in regard to PA, those with higher life satisfaction also have a greater
likelihood of having children (OR: 1.05 - 1.37 to 1) and a lower likelihood of becoming separated (OR: .58
- .85 to 1), controlling for socioeconomic status (SES) and personality (Luhmann, Lucas, Eid, & Diener,
2013). Positive affect still needs to be studied long term in order to determine how it relates to the major
events experienced in close relationships.
Other longitudinal work found PA was linked to less loneliness, stronger friendships, and a
decreased likelihood to interact with deviant peers, all factors suggesting the presence of greater available
support. Kansky, Allen, and Diener (2016) conducted a longitudinal study of individuals from early
adolescence (age 14) to young adulthood (age 25), using a measure of positive affect at Time 1 to predict
social outcomes at Time 2. Early positive affect predicted mean levels of later loneliness (r = -.29) and
sociability (r = .30), as well as desirable changes in these over time. Data gathered from friends, a parent,
and the romantic partner supported these predictions. Friend reports of attachment (r = .17), as well as
improvements in this over time, were predicted by positive affect at Time 1. The father’s reports of low
association with deviant peers (r = -.38), as well as decreases in this across time, were predicted by levels
of positive affect at age 14. Kansky et al. (2016) controlled a major potential third-variable explanation of
the findings, family income, in all their analyses. Thus, this study provides evidence that the effects of
positive affect on later quality social relationships emerges early in life, is confirmed by data beyond selfreport,
and is not due to family resources such as income that might influence both affect and relationships.
Longitudinal research also supports the association between PA and prosocial behavior. Positive
affect in Korean teens predicted greater prosocial attitudes and behavior months later, even after controlling
for baseline prosociality (Shin, Choi, Suh, & Koo, 2013). Thoits and Hewitt (2001) found that those more
satisfied with their lives reported spending more hours volunteering when interviewed three years later.
However, to the best of our knowledge, the examination of PA long-term and its relation to prosocial
behavior is very rare. This appears to be an area left largely unexplored. This tendency toward helpful
behavior in general should have positive effects on one’s relationships with others as it indicates an overall
greater willingness to provide support. Research suggests that PA should continue to be associated with
prosocial actions over longer periods of time.
Experience sampling longitudinal data. Positive moods are also associated with spending more
time with others. Specifically, positive moods over time are strongly correlated with time spent in
fun/active (i.e., joking with friends; r = .23) and necessary/informational types of social interactions (i.e.,
meeting the job supervisor; r = .13), controlling for the dependency in measurement over time (Vittengl &
Holt, 1998).
Other work finds a link between happiness and greater empathy toward others. An interesting study
by Strayer (1980) consisted of preschool children being observed for eight weeks. Children showing happy
displays (versus sad, angry or hurt) were more likely to give empathic responses to others (r = .59). This is
something that should also be examined for positive mood more specifically. Such research could examine
whether this is an association that exists even at a young age. It could be that experiencing positive moods
more frequently as children helps establish one’s first friendships, and this could lead to more experience or
greater ease at socializing when one is older. This potentially greater ability to experience empathy may
also help people better support others.
Experimental—short-term moods. Positive mood inductions also lead people in the laboratory to
act closer, engaging in more self-disclosure, and more supportively, such as feeling more interested in
prosocial activities and being more cooperative. In regards to discourse, males in a positive mood
communicate and self-disclose more to females than those in a negative mood (Cunningham, 1988b; r’s =
.27 to .37). Individuals show greater interest in prosocial activities compared to those in a neutral mood
(Cunningham, 1988a). Inducing positive moods in the laboratory has been linked to more helpful behavior
(Aknin, Dunn, & Norton, 2012). Those in an elation condition versus a depression condition are more
likely to volunteer for a future unpleasant task (Aderman, 1972). Children induced to feel a positive mood,
by thinking of happy experiences, donate more money to other children than those in the control or sad
conditions (Rosenhan, Underwood, & Moore, 1974). Once again, prosocial behavior as a way of providing
support and help to others can be a method of fostering social bonds and increasing closeness in
relationships. Thus, we use prosocial outcomes here as a proxy for support in relationships. Another
finding is that participants induced with positive moods are more cooperative, using less contentious
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bargaining strategies (e.g., Carnevale & Isen, 1986). Thus, we see that manipulating positive mood in the
lab has been found to cause greater self-disclosure, as well as more prosocial behavior and cooperation.
Experimental—inductions that alter long-term PA. Most of the long-term experimental emotion
interventions focus on alleviating depression rather than directly on raising PA in normal populations.
Research suggests these interventions can make relationships closer and more supportive. Treatment for
depression has been associated with significant increases in one’s perceived social support (η2= .27),
utilized social support (η2= .27), and satisfaction with support (η2= .09) (Mohr, Classen, & Barrera, 2004),
where changes in social support were fully explained by changes in depression. Those in complete
remission for depression show less social functioning impairment compared to those in partial remission
(Romera et al., 2010). Additionally, Whisman (2001) found improvements in marital adjustment after
individuals were treated for depression (η2= .55), and this change was mediated by changes in depression.
Prior research has established that positive affect rises when patients are treated for depression, but only
when those patients show a significant decline in depression over time (Kring, Persons, & Thomas, 2007).
Overall, research shows that the treatment of depression is linked to better social outcomes over time.
Positive Affect is Linked to Long-Lasting Relationships
Finally, we look at research showing how positive affect is linked to what we offered as our final
definition of quality relationships in terms of relationship stability. That our review showed that there was a
lack of correlational or experimental evidence should not be surprising, as longitudinal data would be the
gold standard in examining the link between positive affect and relationship stability.
Long-term longitudinal research. From the perspective of longitudinal research, those with
higher positive affect appear to be in longer lasting relationships. For example, positive expressions in
photos predicted future favorable marital outcomes (Hertenstein, Hansel, Butts, & Hile, 2009: r’s = -.10 to .28;
Seder & Oishi, 2012: r’s = .25 to .44; see Freese, Meland, & Irwin, 2007 for a non-replication).
Similarly, Harker and Keltner (2001) found evidence that more positive facial expressions in photographs
predicted better marital outcomes up to 30 years later (r = .20), which was little changed when controlling
for physical attractiveness (r = .16) or social desirability (r = .18). While research on subjective well-being
has linked it to a greater likelihood of getting married (Marks & Fleming, 1999; OR: 1.5 to 1), this has not
yet been studied for the specific construct of positive affect. Thus, while we cannot yet say this
conclusively, it is likely married people have higher PA because these individuals are also more likely to
get married.
Mediators Established
How do those with greater positive affect experience better relationships? Understanding the
mediators of an association between two variables is essential to scientific understanding—what are the
processes connecting the cause to the effect? For example, if those with higher PA have better marriages,
why is this so? Do they tend to overlook the faults of their partner, do they have more fun with their
partner, or do they spend more time with their partner? In order to fully understand causal connections, we
need to establish the processes that mediate this connection. For the effects of positive affect on the quality
of social relationships, researchers have uncovered a number of mediators.
Sociability
Several studies point to the fact that positive affect is tied to both feeling more motivated to socialize
and to actually engaging in more social behavior. It may be this propensity toward sociability which helps
drive positive interpersonal outcomes. In a study examining reports of affect balance, those with higher
levels of subjective well-being were more social (Diener & Seligman, 2002; η2’s = .24 to .44). Positive
affect is linked to more time engaging in social activities (r = .19) and with friends ( r = .18) (Lucas, Le, &
Dyrenforth, 2008). A lack of positive affect is associated with feeling unsociable (Watson et al., 1995; r =
.19). As indicated before, extraversion is correlated with PA (Fujita, 1991). Thus, it makes sense that
research indicates that introversion is correlated with feeling less positive affect (partial η2 = .05) and
holding less positive attitudes (partial η2= .04) about an imagined group discussion (Besner, 2009).
Positive affect appears to be linked to feeling more sociable, as well acting on those feelings by actually
being more social. As a result of these interactions going well, people may come to expect good outcomes
in future interactions. This is supported by a study on customer service. This study found that in
salespeople, extraversion (r = .194) and conscientiousness ( r = .111) predicted better sales performance,
which appeared to be because those individuals also had higher self-efficacy. This then made them more
motivated to interact with customers and to have favorable interactions (Yang, Kim, & McFarland, 2011).
This area of research could be strengthened by relying less on a related measure (i.e., extraversion) and
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focusing on positive affect and its direct links to feeling or acting sociable.
It is More Rewarding to Interact with High Positive Affect Individuals
Not only are those with higher PA more sociable, but a number of studies also suggest that their
social interactions are actually more rewarding for them and their partners, which may be another factor
causing better relationship quality. Others are more satisfied when interacting with those with higher PA,
which may be because they too end up experiencing more positive emotions as a result of those
interactions. Individuals who exhibit more positive emotions are viewed as more attractive social partners
(as opposed to emotional downers). They are more popular and well liked (see review by Diener & Tay,
2012). The strength of employees’ smiles has been found to be positively associated with customers’
satisfaction with their interactions (Barger & Grandey, 2006; r = .20). Chi, Chung, and Tsai (2011) found
that leaders’ positive moods were related to better team performance (r’s = .31 to .38), and emotional
contagion was one of the factors mediating this relationship. Thus, spending time with more positive
individuals is likely to make a person more positive too. In a longitudinal study, Fowler and Christakis
(2008) found that individuals with higher levels of subjective well-being in a social network were arranged
in clusters, and this appeared to be due to SWB spreading throughout the network. For example, “a person
was 15.3% more likely to be happy if a directly connected alter was happy” (p. 5). For both a short-term
positive mood and more long-term positive affect, PA appears to be contagious. Others will find it
rewarding to be around those with high PA because they will also end up experiencing more positive
affect.
Cooperation and Prosociality
It may also be that those with higher PA are more cooperative and engage in more prosocial
behavior and that it is this greater generosity and helpfulness that leads to their interpersonal success. In a
longitudinal study from age 14 to age 25, Kansky, Allen, and Diener (2016) found that positive affect in
early adolescence predicted lower levels of conflict in relationships in young adulthood (r = -.27), as well
as a greater decrease in conflict over the intervening years. These trends were supported both by self-report
measures and by partner-report assessment (r = -.25). Several studies indicate that positive affect reduces
the tendency to use contentious strategies when bargaining (Barsade, 2002: r’s = -.11 to .39; Baron, Rea, &
Daniels, 1992; Baron, 1990: ω2 = .02; Carnevale & Isen, 1986). Specifically, those in a positive mood
condition made more concessions in negotiations (e.g., Carnevale, 2007). Even at a young age PA appears
to be linked to more cooperative behavior that persists over time, and extensive negotiations research
supports this finding. There are many articles indicating PA is linked to more cooperation in negotiations,
but future researchers should move beyond this area and explore links to cooperative behavior in other
types of social situations.
In general, these individuals also tend to feel more prosocial (Carlson, Charlin, & Miller, 1988:
Mean effect size = .54; George, 1991: r = .24; Priller & Schupp, 2011: 1-2% more frequent donations). In
an experimental study, those placed in an elated mood were more likely than those in a neutral mood to
help with both high-interest and low-interest tasks. This was true when they simply offered to help
someone else who was volunteering on his or her own and when that person encouraged participants to
assist (Cunningham, Shaffer, Barbee, Wolff, & Kelley, 1990). In the workplace, George (1991) found that
positive mood was positively associated with helpful behavior, both for behaviors related (r = .26) and not
related to one’s job (r = .24). Thus, the finding that PA is linked to prosocial behaviors is not only true in
the laboratory, but also in a work setting. This tendency to provide help and support is not limited to only
fun or interesting tasks, nor does it appear to only be the result of outside pressure.
Empathy, Compassion, and Perspective Taking
Positive affect is related to feeling interested, caring, and in harmony with others (Diener et al.,
2015). Yet another possibility is that the ability of PA to enhance a person’s compassion for others may be
a factor that benefits them in their relationships. An experimental study found that being in a positive mood
helps people show greater compassion, perspective taking, and sympathy for someone in distress (Nelson,
2009). Induced positive affect increases the likelihood that one will mirror the actions of another person
(Kuhbandner, Pekrun, & Maier, 2010; d = .64). Positive affect then not only makes us feel more interested
and invested in others, it also helps us take on their perspective, feeling greater sympathy for them and
unconsciously mimicking them in a potential effort to facilitate this desire. However, research is still
needed in this area. Other than self-reporting that they feel more compassionate (e.g., Nelson, 2009), it also
needs to be determined whether people actually act in a more compassionate manner. In addition to
mimicking others (e.g., Kuhbandner et al., 2010), taking a more situational perspective (versus
dispositional) when viewing another’s behavior, or assessing if another’s emotional reaction was
appropriate (e.g., Nelson, 2009), we need to investigate in what other ways people with higher levels of
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positive affect attempt to take on others’ perspectives. Some research has found that individuals with
compassionate goals want to be more supportive (r’s = .23 to .56) as they have goals to contribute to others’
well-being (Crocker & Canevello, 2008). Perhaps future researchers could explore this avenue: do those
with higher levels of positive affect show evidence of wanting to contribute to others’ well-being? For
example, do they report this as a goal or work toward this goal? This could be another way to assess
compassion.
Trust and Respect
Other work suggests that PA is tied to the values of trust and respect. Perhaps a focus on these key
qualities helps relationships thrive. In the Gallup World Poll we found a positive association between
positive affect and both trusting others (r = .06) and feeling respected (r = .36), both at the individual and
national levels. Across cultural regions positive emotions are associated with social and respect needs (Tay
& Diener, 2011). PA is linked to being more trustful and feeling and desiring respect. There may be
something about these qualities that leads to better interactions. Perhaps the need for respect or feeling
respected is also linked to showing others more respect. In that case, it would be clear as to why PA is
linked to better relationships: because those with higher levels of positive affect treat people with more
respect and are more trusting. However, a direct link between PA and treating others with more respect will
need to be established. PA also appears to be linked to giving one’s trust wisely. Researchers have found
that being in a positive mood helps us adjust our level of trust in another person in response to
corresponding cues (Lount, 2010; d = 1.21). Thus, this does not appear to be a tendency toward reckless
trust. Replications should be conducted to further establish trust as a mediator though.
More Substantive Interactions
Higher PA is also associated with a higher quality of interactions when meeting others. Those with
higher trait positive affect experience better interaction quality during first meetings (Berry & Hansen,
1996: r’s = .27 to .38). More specifically, over time positive emotionality has been found to broaden our
feelings of self-other overlap within new relationships (Waugh & Fredrickson, 2006; r = .21 & .27). These
studies suggest PA is associated with a higher quality of interactions in new relationships. More work
should be conducted on this topic, but it is possible that PA provides a boost when forming relationships
that could have long-term positive consequences.
Beyond initial first encounters, other research points to a promising area to further explore: PA and
substantive interactions. Research links PA to deeper conversations and positive relationship goals. A
study examining satisfaction with life found that those more satisfied spend less time alone (r = -.36), talk to
others more (r = .31), and have more meaningful conversations ( r = .26) (Mehl, Vazire, Holleran, & Clark,
2010). Determining that this is also true for positive affect would lead to stronger evidence that PA leads to
better relationships due to its influence on more meaningful interactions. Another way to assess deeper
interactions may be to examine one’s relationship goals. Referring back to Crocker and Canevello (2008),
they found that those with compassionate goals wanted to be more supportive of others. Perhaps by
measuring the goals those with PA have for their relationships (or that their friends/partners have for
them), we could examine another way in which those with high positive affect may be experiencing more
meaningful relationships and interactions. For example, if those with higher levels of positive affect are
more likely to have compassionate goals for their relationships than those with lower positive affect, this
would be additional evidence of their more substantive interactions.
Accurate Self and Person Perception
Those with greater levels of positive affect may also be better understood by others, which likely
enhances their social interactions. Research by Human and Biesanz examined the “well-adjusted” who are
identified using measures of self-esteem, satisfaction with life, positive relations with others, depression,
etc. The well-adjusted are more “judgeable” by others (Human & Biesanz, 2011a: r’s = .09 to .77),
probably because they act more genuinely (Human, Biesanz, Finseth, Pierce, & Le, 2014: d = .59). The
well-adjusted also accurately understand what other people are typically like (Human & Biesanz, 2011b:
d’s = -.72 to .58). While not directly focused on measures of positive affect, this does point to one
possibility as to how those with higher levels of PA experience better social relationships—by being more
readable and by more easily reading others. Initial research supports this, where a sad mood induction
caused participants to exhibit significantly lower accuracy in social judgments compared to those in the
happy or control group (Ambady & Gray, 2002; r = -.42). Future studies should be conducted to further
confirm that positive affect makes one a more accurate judge and to explore whether PA makes one more
judgeable.
Coping: A Buffer Against Stress
Positive affect may help people create a reserve of rewarding times or experiences with others,
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which they can draw upon to serve as a buffer during negative times, protecting their relationships from the
negative consequences of stress. For example, Gottman (1994) found that in stable marriages, couples have
more positive interactions when trying to resolve conflicts. Their ratio of positive to negative interactions
was 5 to 1, in comparison to a ratio of .8 to 1 in unstable marriages. The ability to create more positive
moments, even during a conflict, could be one of the ways that positive affect helps people buffer their
relationships from the ill effects of stress, but this has not yet been thoroughly tested. This is a particularly
interesting area for future research though as we also know that visible emotional support can be helpful for
individuals who are highly distressed, but costly for nondistressed recipients (Girme, Overall, & Simpson,
2013). Thus, the creation of these positive moments to help create a buffer against future stress will likely
have limitations or may need to be initiated in certain ways so as not to be detrimental to the relationship
instead. Another promising line or research regarding this has focused on shared leisure time. Couples were
interviewed prior to becoming parents and then were followed up with afterwards. It was found that when
wives and husbands reported more shared leisure time prenatally, they experienced more love one year
later (Claxton & Perry-Jenkins, 2008). It may be that shared leisure time is one way in which couples build
positive moments.
The broaden-and-build theory created by Fredrickson (1998) proposes that positive emotions, such
as interest, contentment, and joy, help broaden our thoughts and behavior. Specifically, in a social context,
we exchange social smiles, engage in social play, and are more likely to help others. In this way positive
emotions help us accumulate lasting social resources. Other research links better social support to more
effective coping as well. For example, when people feel they do not have others with whom to share their
thoughts and feelings, it can lead to distress, such as rumination and intrusive thoughts (Lepore, 2001). At
times, people may also feel that there are limits to what they can share about their stress with others. These
feelings are also associated with greater distress and poorer adjustment (e.g., Lepore & Helgeson, 1998; β =
-.14 & -.18). Furthermore, poor coping is linked to social interactions that are briefer, including the
tendency of others to distance themselves from the person in need (Silver, Wortman, & Crofton, 1990).
Thus, while this should be more directly examined, it appears that positive affect is likely associated with a
greater reservoir of social resources; these resources may help buffer them from the negative effects of
stress, allowing their relationships to remain stable.
Mediator Conclusions
Not all of the above mediators contribute to all three of the qualities of a good relationship that were
listed previously: pleasant and rewarding, closer and more supportive, and long-lasting. Studies should be
conducted that directly test the proposed mediators and to which of the three outcomes they contribute. On
the one hand, if a person with high PA is also more sociable, does that sociability lead to a more rewarding
relationship? On the other hand, being more sociable may be less likely to contribute to a long-lasting
relationship. All of these avenues should be directly explored in future research.
The Need for Moderators Research
Moderators tell us when a causal sequence does and does not occur. Moderators also describe when
the relation is stronger or weaker. Understanding the moderators of causal connections is essential to
scientific understanding, as these boundaries are needed for complete understanding. Not only do we want
to know, as laboratory experimentation can show, that a causal connection can occur, but whether it
actually does so in everyday life, and under what conditions. To draw an analogy from medicine, it is not
enough to know that a bacterium can make people sick, but that it does so in everyday life, and under what
conditions. For example, the bacterium Clostridium difficile can lead to severe gastrointestinal symptoms
and even death, but tends to do so primarily when a person’s natural gastrointestinal bacteria have been
depleted by antibiotics. To understand and control this infection, one must understand the conditions in
which the disease-causing bacteria can thrive. Fecal transplants that reintroduces healthy bacteria have thus
been much more effective in curing c. difficile than antibiotic treatments. It is not enough to simply know
that one factor can cause another; it is also essential to know when and why it does so in the natural world.
While there is evidence that some of the links exist across an array of cultures, a few studies point to
possible limitations to the relationship between subjective well-being and social outcomes. Forgas (2007)
found that those in a negative mood actually created better, more effective persuasive interpersonal
messages (β’s = .288 to .401). Tan and Forgas (2010) also established that positive moods led to more
selfish distribution of resources in a game, which may be due to a possible increase in internal focus.
Casciaro, Carley, and Krackhardt (1999) found that while positive affect improved accuracy when
assessing one’s friendship network structure (r = .21), it hindered accuracy in terms of perceiving one’s
local ties (r = .02), in that they had more unrealistic assessments of those ties. These studies suggest that
positive moods may not always lead to more cooperation and prosocial behavior, though the specific
reasons for these findings are not yet clear. It also indicates that the benefits of a positive mood may not
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extend to persuasive communication and that trait positive affect may lead to unrealistic assessments of
one’s personal ties. Thus, it is clear that negative emotions can help relationships in some cases and
positive moods are not invariably beneficial. Thus, we need more systematic research on the circumstances
and activities where positive versus negative moods will be most beneficial.
Lucas, Diener, Grob, Suh, and Shao (2000) found that although extraversion and positive affect
were related across cultures of the world, this association was stronger in some cultures. Specifically, the
correlation between extraversion and positive affect was weaker in collectivist nations (r = .59 vs. .77).
Related to this, Fulmer et al. (2010) found that extraverts reported higher life satisfaction if living in an
extraverted versus introverted culture (R2 = 3.30%).
Another interesting moderator may involve the manner in which one seeks subjective well-being.
Materialism, or the pursuit of happiness/success based on acquisition of social status and goods, is linked to
a decreased desire for interpersonal relationships, including negative attitudes toward marriage and
children (Li, Lim, Tsai, & O, 2015: β’s = -.26 to -.27). Thus, it may be that when one’s positive affect is
tied to certain sources, the link between positive affect and good interpersonal outcomes will not occur.
It is also possible that the link between positive affect and good relationship outcomes could be
more complicated depending on the attachment style of the person with whom you are interacting. For
example, avoidantly attached individuals exhibit negative responses to low or moderate levels of practical
support, but they exhibit positive responses to high levels of practical support, showing a curvilinear effect
(Girme et al., 2015: r = -.12).
Finally, partner aggression may play a part as well. Arriaga, Capezza, Goodfriend, Rayl and Sands
(2013) found that individuals see themselves as being less happy if they were to leave their aggressive
relationship. However, they are actually happier compared to their forecast when they finally do exit the
aggressive relationship. It could be the case that if positive affect keeps individuals in aggressive
relationships, then partner aggression may also eliminate the association we have typically observed
between positive affect and relationships.
However, much more research needs to be conducted to clarify the above findings so that we
understand when positive affect does not enhance relationships.
Causal Conclusions
An earlier review on subjective well-being and success by Lyubomirsky, King, and Diener (2005)
focused on the link between SWB and relational success. This review provided initial evidence (crosssectional,
longitudinal, experimental, etc.) that the causal arrow appeared to go both ways. After examining
a greater body of research, the current review focused on positive affect supports their initial conclusion.
So far, the literature indicates that positive affect does not just result from good relationships but
can also cause them. The most powerful evidence comes from experimental and longitudinal research,
which shows that manipulating subjective well-being in the lab can influence social outcomes and that the
naturally occurring association is evident over time, with positive feelings at Time 1 predicting better
relationships at Time 2, often controlling for Time 1 relationships (e.g., Kansky et al., 2016). Not only do
positive emotions predict better quality social relationships, but they can, at least in some cases, predict
relationships that improve over time. Long-term research indicates that often both state and trait positive
affect are linked to better relationship outcomes over time. For example, positive moods from moment to
moment are linked to more pleasant interactions, and trait PA is also linked to better marital outcomes. The
experimental literature also makes a strong case for a link between positive affect and better social
relationships. It has been found that inducing a positive mood in the laboratory can positively affect one’s
interest in social and prosocial activities. We hope that this article can serve as a model for reviewing what
evidence exists in a field and what additional evidence is needed.
Conclusions
We have presented compelling evidence that positive affect is likely to be a benefit to high quality
social relationships. Several complementary methodologies all point to this conclusion. Although each
method has limitations, they tend to converge in their conclusions and not suffer from identical limitations.
Another fact that adds to our confidence that positive affect can enhance relationships is that the findings
are based on a variety of mood manipulations in the experimental studies and on a variety of types of
measures of both positive moods and relationships. Thus, our conclusion is not based solely on correlations
found in global self-report measures.
Psychologists have long maintained that supportive social relationships are one key to
psychological health and well-being (e.g., Frisch, 2005; 2014; Seligman, 2011). Thus, the fact that positive
affect leads to higher quality social relationships has a number of applied implications. First, raising PA
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and lowering feelings of ill-being has the potential to substantially improve people’s social relationships,
and such interventions might be useful in both clinical and organizational settings. Alleviating depression
and other negative states is likely to lead to both increases in positive affect and to improvements in social
relationships. Similarly, raising the positive affect of workers has the potential of improving relationships
within the organization, with coworkers, customers, and supervisors.
An important implication of our review is that researchers must be cautious in interpreting
correlations that show a relationship between PA and social outcomes. Often it is assumed that the social
outcomes have caused higher levels of PA, but our review suggests that PA could be the cause of better
relationships.
Despite the extensive research in this field, there is still a need for more studies in many areas, for
example experimental treatments to raise long-term levels of positive affect. There is also a need for much
more research to determine the moderators, the bordering conditions, in which positive affect enhance
relationships. Very little is currently known. Thus, although a connection going from affect to social
relationship quality now seems likely, there is much we do not yet understand, and this area continues to
be a very promising area of research.
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Wellbeing and Work Performance
By Peter Warr & Karina Nielsen, Institute of Work Psychology, University of Sheffield
Citation
Warr, P., & Nielsen, K. (2018). Wellbeing and work performance. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
This chapter reviews research into the happy worker-productive worker thesis, which suggests that
individuals and groups with raised wellbeing perform better in their jobs than do those with lower
wellbeing. We examine different types of context-free and job-related wellbeing, and explore work
performance in terms of in-role and extra-role behaviors and through specific activities such as being
creative or proactive. In studies of individual workers, small-to-moderate cross-sectional and longitudinal
associations with performance are demonstrated, for example when focusing on wellbeing in the form of
job satisfaction or certain types of affect. We also review research into potential moderators of these
associations, finding that the magnitude of correlation depends, for example, on the opportunity for
personal discretion, occupational grade, and expected benefits from good performance. However, in the
absence of adequately controlled experiments in working organizations it is impossible to determine causal
direction. Turning to group-level wellbeing, we find that group affective tone is also moderately related to
performance. Some group characteristics, such as the number of members, have been suggested as
important moderators, but group-level research into possible moderators has been extremely rare. We
finish the chapter by suggesting some desirable developments in research, and offering an overall
speculation about causal influences in this area.
Keywords: Performance, Wellbeing, Jobs, Affect, Satisfaction, Engagement, Groups
Performance in paid work has for many years been studied as an important form of individual and
group behavior, with researchers and practitioners often aiming for its enhancement through job design,
staff selection and development, or shaping managerial style and organizational culture. In parallel with
this interest in performance, psychologists in employment settings have also worked to understand the
sources and consequences of wellbeing, and the two variables will be examined together in this chapter.
A substantial association between wellbeing and job performance is widely envisaged. For
example, as many as 92% of Australasian employees in Fisher’s (2003) study believed that ‘a happy
worker is likely to be a productive worker’. Although academic researchers are cautious about the direction
of causation, many lay-people emphasize the impact of wellbeing on performance. Ledford (1999) notes
that this belief in the productive power of happiness fits comfortably with the hopes of all parties involved –
employers, employees and academic researchers. Employers can value worker wellbeing as a possible
source of good performance; employees recognize wellbeing as desirable in itself; and for researchers the
prospect of jointly optimizing both variables can support claims that neither management nor labor is being
favored by their research. As Ledford (1999, p. 27) points out: ‘If interventions based on our theories lead
to outcomes that are good both for organizations and individuals, who can complain?’.
Types of Wellbeing
In thinking about and measuring wellbeing, it is important to differentiate between its various
forms. In respect of scope, the broadest wellbeing is ‘context-free’ – in terms of life in general rather than
concerned with a particular setting. Wellbeing of that broadest scope has been measured through
satisfaction with life, global happiness, and similar constructs. Next, medium-scope wellbeing is that which
is experienced within one segment of a life-space, focused on one’s family, health, leisure, or other
domains. In the present chapter, domain-specific wellbeing concerns a person’s job, being referred to as
‘job-related’ wellbeing and measured through job satisfaction, job strain and similar variables. Most
narrowly, we might examine wellbeing experienced in respect of one particular element. This can be
termed ‘feature-specific’ wellbeing, in terms of positive or negative feelings about a particular thing,
person, group, episode, or idea. Much studied in job settings is ‘facet-specific’ job satisfaction – with one’s
pay, supervisor or other elements.
Studies have varied in the wellbeing scope under investigation, and have also differed in their
emphasis on longer-term versus shorter-term experiences. Longer-term wellbeing, that which extends
across time, has sometimes been viewed as a trait or disposition, and must be distinguished from wellbeing
within a short period – ‘state’ or ‘situational’ wellbeing. Dispositional forms may be viewed as aspects of
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personality; they are sometimes referred to as ‘affectivity’ in contrast to shorter-term ‘affect’.
It is also important to examine separately two types of wellbeing indicator, either in terms of a
compound of thoughts and feelings or directly through particular feelings. Cognitive-affective compounds
of wellbeing have been investigated through multi-item questionnaires about satisfaction, engagement,
strain, burnout, depression and the like, bringing together thoughts, recollections, expectations, and mental
networks. As illustrated in this chapter, workers’ wellbeing has been measured through compounds
indexing job satisfaction, or work1 engagement as well as life satisfaction. Self-assessments of wellbeing in
these compound terms call for more reflection and mental processing than do assessments through specific
feelings – attending to and remembering particular elements and episodes, interpreting, evaluating and
integrating what is recalled, and perhaps making comparisons with other people or other settings (e.g., Staw
& Cohen-Charash, 2005; Warr, 2013).
Wellbeing measures of the second kind, in terms of feelings, often ask about core affect – pleasant
or unpleasant experiences that are ‘primitive, universal, and simple, irreducible on the mental plane’
(Russell, 2003, p. 148). Illustrated by ‘happy’, ‘relaxed’, ‘anxious’ and ‘sad’, feelings range along a
positive-negative continuum and also occur within emotions, moods, values, attitudes, orientations, and
ideologies.
However, as well as in positive or negative direction, affects and cognitive-affective compounds
also differ in other respects, one of which is particularly important here. In addition to their direction, the
circumplex model introduced by Russell (1980) characterizes feelings through the degree to which they are
physiologically and/or psychologically activated, being in an elevated ‘state of readiness for action or
energy expenditure’ (Russell, 2003, p. 156). Positive feelings of high versus low activation have been
studied in terms of, for instance, enthusiasm and elation (high activation) versus calmness and relaxation
(low activation) (e.g., Warr, Bindl, Parker, & Inceoglu, 2014), and a lower level of activation is tapped in
many compound scales of life or job satisfaction; ‘satis’ derives from the Latin word meaning ‘enough’. On
the other hand, raised activation in job tasks is central to compounds of job engagement (e.g., Bakker,
Albrecht, & Leiter, 2011). That is a combination of positive orientation and raised motivation, so ‘is
fundamentally a motivational construct that represents an active allocation of personal resources towards
the task’ (Christian, Garcia, & Slaughter, 2011, p.91), whereas the notion of satisfaction implies merely
acceptance of a situation.2
Types of Work Performance
Wellbeing thus takes several forms which need to be distinguished in reviewing associations with
other variables. It is also essential to differentiate between kinds of performance3, and researchers in job
settings have concentrated on the five types outlined below (e.g., Borman & Motowidlo, 1993; Griffin,
Neal, & Parker, 2007; Koopmans et al., 2011; Viswesvaran & Ones, 2000). Objective indicators of
individual workers’ performance (their output, sales, etc.) are rarely available, for example because output
is recorded for groups rather than individuals or because job activities are not readily quantifiable. Many
researchers have therefore investigated subjective assessments of performance – either ratings by
supervisors, colleagues or customers, or self-descriptions by research participants themselves. Performance
ratings by other people can be problematic, because observers may lack adequate knowledge or because
target behaviors depend on mental processes which are unobservable; furthermore, self-descriptions might
err towards positive assessment. In this and other fields, published results can powerfully depend on
researchers’ operationalization of variables so that reported findings from different studies are not
necessarily comparable with each other.
Of the principal aspects of performance, task performance, sometimes referred to as ‘in-role
performance’ or ‘proficiency’, has been of primary interest. Focusing on behaviors which are formally
required to meet organizational goals, research has investigated either overall indicators of a person’s
effectiveness in a job or the summation of separate behavioral assessments.
Second, specific job behaviors have been examined without setting those in the overallperformance
category above. Examples have included work quality, adaptability, innovativeness,
proactivity, participation in learning, and technical competence.
Organizational citizenship behavior (OCB), also referred to as ‘extra-role’. ‘contextual’, or ‘prosocial’
activity, is that which goes beyond formally prescribed job goals (‘task performance’ above), for
example through helping colleagues, guiding new workers, or choosing to take on additional tasks.
Counterproductive work behavior has negative value to an organization, violating accepted
conventions, for example through damaging equipment, stealing property, bullying subordinates or other
people, avoiding effort, and abusing drugs.
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Workers’ absenteeism, another key negative variable in this area, can create difficulties for team
colleagues and for wider organizational success, especially when a person’s non-attendance is unexpected
or long-lasting. Research problems can arise in separating medically-prescribed periods of (‘involuntary’)
absence from those which might result more from a worker’s personal choice (e.g., Johns, 1997; Johns &
Miraglia, 2015).
Research into these five types of work performance has mainly focused on individual workers, and
the chapter will first review research of that single-person kind. However, many job activities involve
collaboration within a group, and we will also examine the smaller number of studies on group-level
performance and wellbeing.
Individual-level Research
Considerable non-occupational research has identified positive relationships between individual
wellbeing and success in diverse areas of life. Cross-sectional, longitudinal and experimental studies have
pointed to possible benefits of wellbeing for health, longevity, family and social relationships, social
relationships, cooperativeness, creativity, self-evaluation, and self-regulation (De Neve, Diener, Tay, &
Xuereb, 2013; Diener et al., 2017; Lyubomirsky, King, & Diener, 2005; Tenney, Poole, & Diener, 2016).
In job settings, research has explored associations of performance with different aspects of wellbeing as
follows.
Wellbeing Measured as Job Satisfaction
Partly-overlapping meta-analyses by Petty, McGee, and Cavender (1984), Iaffaldano and
Muchinsky (1985), Judge, Thoresen, Bono, and Patton (2001), and Harrison, Newman, and Roth (2006)
have yielded average uncorrected correlations between overall job satisfaction and task performance of
.23, .25, .18 and .18 respectively. A subsequent study by Halbesleben and Wheeler (2008) found a
correlation with supervisor-rated performance of .22, Edwards, Bell, Arthur, and Decuir (2008) reported a
correlation of .15, and Schleicher, Watt, and Greguras (2004) found correlations of .15 and (averaged from
two satisfaction scales in two samples) .28.
Researchers into job satisfaction have often examined task performance as rated by supervisors or
(less often) by colleagues, but a small number have obtained self-ratings by workers themselves. Only
rarely have satisfaction-performance associations been directly compared between self-ratings of
performance and parallel ratings by other people, with apparently similar findings (Iaffaldano &
Muchinsky, 1985).4
Moving on to the second type of performance introduced above, specific job behaviors, personal
innovation in a job was investigated by Ayala, Peirό Silla, Tordera, Lorente, and Yeves (2016). They found
that young workers’ job satisfaction was correlated .41 with their self-reports of innovation at work.
Significant associations have also been found between job satisfaction and organizational
citizenship behavior (OCB). A meta-analysis by Organ and Ryan (1995) identified uncorrected average
cross-sectional correlations of .23, .20, and .38 with altruism, generalized contribution and overall
citizenship, and the review by Harrison et al. (2006) recorded average correlations of .26 (concurrent
analyses) and .22 (predictive, with satisfaction measured before OCB). Later cross-sectional research by
Edwards et al. (2008) found a correlation of .15 with supervisor-rated citizenship. A two-week diary study
by Fisher (2002) revealed workers’ average job satisfaction to be correlated .23 with self-reported
citizenship behavior, and for average satisfaction across three weeks that correlation was .52 in the study
by Ilies, Scott, and Judge (2006).
Job satisfaction has been found to be negatively correlated with counterproductive work behavior,
for example -.33 and -.25 with self-reports and peer-reports in the study by Penney and Spector (2005). For
employee absenteeism, negative correlations have also been found, for example -.20 and -.25 in research
by Johns (1997) and -.14 in the meta-analysis by Harrison et al. (2006). Almost all studies in this field have
recorded absence from work at a time before wellbeing is measured, but Hardy, Woods, and Wall (2000)
studied job satisfaction in advance of information about absence frequency; the correlation was found to be
-.23. Focusing only on intrinsic aspects of job satisfaction (for instance, with opportunity to learn new
skills) and subsequent short-term absence, Mirvis and Lawler (1977) recorded a correlation of -.81.
Task performance as a function of different facets of job satisfaction has less often been studied.
However, it appears that satisfaction with the work itself and with one’s supervisor are significantly
associated (around .20) with task performance (Edwards et al., 2008; Petty et al., 1984), but smaller
correlations are found with other facet satisfactions – concerning pay, promotion, co-workers and so on.
Slocum (1971) reported that managers’ task performance was more strongly correlated with the satisfaction
of self-actualization needs than, for instance, with security needs.
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Wellbeing Measured through Other
Cognitive-Affective Compounds
In addition to examining associations with job satisfaction, research into work performance has also
explored links with other forms of wellbeing. This section will review compound cognitive-affective
indicators beyond job satisfaction, before associations with wellbeing in terms of a worker’s affect are
considered in the next section.
In recent years, increasing attention has been devoted to the construct of job engagement, a
motivated state of positive wellbeing characterized by vigor, dedication, and absorption in one’s work (e.g.,
Bakker et al., 2011; Schaufeli, Salanova, González-Roma, & Bakker, 2002; Warr & Inceoglu, 2014). Metaanalyses
of findings by Rich, Lepine, and Crawford (2010) and Christian et al. (2011) drew on thenavailable
(fewer than ten) studies to report mean correlations of job engagement with task performance of
.35 and .36 respectively5, and mean correlations with organizational citizenship behavior of .35 and .26. In
addition, Christian et al. (2011) showed through incremental analyses for both kinds of behavior that job
engagement accounted for significant additional variance over and above job satisfaction.
Studying a wide range of jobs, Halbesleben and Wheeler (2008) found a correlation of .32 between job
engagement and supervisor-rated task performance. Among employees in a fast-food company,
Xanthopoulou, Bakker, Demerouti, and Schaufeli (2009) reported a correlation of .34 between day-level
job engagement and that day’s branch income. A significant association with engagement was also found
in a broader sample of workers by Demerouti, Bakker, and Halbesleben (2015) for self-reports of day-level
task performance and (negatively and less strongly) for self-reported counterproductive work behavior.
Bakker and Bal (2010) similarly observed in a weekly diary study that teachers’ self-rated performance covaried
with their level of job engagement. Among self-employed entrepreneurs (individuals who founded
or owned a private company), Gorgievski, Moriano, and Bakker (2014) observed a correlation of .56 with
self-described innovative behavior. In another sample of entrepreneurs, job engagement was found by
Djkhuizen, Gorgievski, van Veldhoven, and Schalk (2016) to be significantly associated with subjective
personal, but not financial, success. Overall, it appears that job engagement is more strongly associated
with task performance than is job satisfaction, but a meta-analysis of comparative levels in the same sample
is still required.
Negative forms of wellbeing have been investigated through reports of job-related emotional
exhaustion6, sometimes treated as a component of job burnout. For example, Taris (2006) brought together
the few studies of emotional exhaustion available at the time of writing (16 of them, with different measures
and samples), and reported mean correlations with task performance and citizenship behavior of -.19 and .17.
Subsequent findings about emotional exhaustion and task performance include a nonsignificant
association in the study by Demerouti et al. (2015) and significant correlations of -.13 (Janssen, Lam, &
Huang, 2010), -.27 (Demerouti, Bakker, & Leiter, 2014), -.19 and -.18 with self- and other ratings
(Mastenbroek et al., 2014), and (across time) -.28 (Petrou, Demerouti, & Schaufeli, 2015). In respect of
organizational citizenship, Janssen et al. (2010) obtained r’s of -.19 and -.23 with two measures, but that
association was insignificant in the study by Mastenbroek et al. (2014).
Finally in this section on compound measures of wellbeing, we turn to context-free indicators.
Examining senior managers’ life satisfaction in relation to their self-rated job performance, Zelenski,
Murphy, and Jenkins (2008) found an intercorrelation of .25, very similar to their finding for job-related
satisfaction (.22). Bringing together an unspecified number of publications, Erdogan, Bauer, Truxillo, and
Mansfield (2012) reported an average correlation between life satisfaction and task performance of .14, and
in a parallel analysis by Ford, Cerasoli, Higgins, and Decesare (2011) the average r was .16 from six
studies. Other context-free research has focused on negative forms of wellbeing. For example, in the metaanalysis
by Ford et al. (2011, above) generalized anxiety and depression were on average correlated -.15
and -.14 (uncorrected) with measures of job performance. Hardy et al. (2000) studied context-free
psychological distress in relation to subsequent lost-time absence, finding a correlation of .25.
A wellbeing indicator combining job-specific and context-free measures (job satisfaction, job
engagement, and life satisfaction) was studied by Djkhuizen, Gorgievski, van Veldhoven, and Schalk
(2017). They described how the wellbeing of entrepreneurs predicted reports of subjective personal and
financial success after an interval of two years; however, the lagged association with business performance
(annual profit, financial turnover and number of employees) was non-significant.
Wellbeing Measured as Job-related Affect
Given that all compounds of wellbeing contain some positive or negative feelings, the patterns
illustrated above are expected in general to be paralleled by findings about affect. Affect research outside
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employment settings has been summarized by, for instance, Isen and Baron (1991) and Barsade and
Gibson (2007), and also within organizations by Forgas and George (2001). This section will instead
examine research into workers and their job-related feelings.
Applying the Multiple Affect Adjective Checklist (MAACL) to feelings at work, Motowidlo,
Packard, and Manning (1986) obtained nurses’ reports of job-related negative and positive affect. They
recorded depression through self-descriptions of feeling miserable, sad, enthusiastic, inspired, etc., and
assessed anxiety in terms of feeling tense, worrying, cheerful, happy, and so on. Feelings which can be
viewed along an axis from job-related depression to enthusiasm were significantly correlated (-.31 and -.21)
with supervisors’ ratings of interpersonal and cognitive/motivational effectiveness, but feelings of anxiety
were unrelated to performance in those terms. Staw, Sutton, and Pelled (1994) also investigated supervisor
ratings of task performance in relation to job-related feelings along the depression-enthusiasm axis (which
they referred to as ‘positive emotion’), finding an overall concurrent correlation of .30 and a predictive r of
.16 over 18 months. Activated positive affect was found by Eisenberger, Armeli, Rexwinkel, Lynch, and
Rhoades (2001) to be correlated .16 with supervisor-rated task performance. For citizenship behavior (here,
supervisor-rated altruism), George (1991) recorded a correlation of .24 with activated positive affect,
although the correlation with subsequent sales was only .10. In the diary study by Zelenski et al. (2008),
positive affect was concurrently associated .36 with self-rated productivity, but correlations with negative
affect were around zero.
For self-reported citizenship behavior, a stronger association with positive than with negative
affect was also found by Fisher (2002) in analyses of average job feelings across two weeks (r’s = .48 and .01
respectively). Average diary levels of activated positive affect across three weeks were found by Ilies et
al. (2006) to be correlated .61 with self-reported organizational citizenship behavior. Examining
momentary feelings, self-reported allocation of job effort was found by Foo, Uy, and Baron (2009) to be
correlated on average .20 with positive affect but only .06 with negative affect. Two diary studies by Dalal,
Lam, Weiss, Welch, and Hulin (2009) yielded significant concurrent associations between job-related
affect and self-reported citizenship and counterproductive behavior, such that positive affect was typically
related to citizenship but not to counterproductive behavior, and negative affect was more often related to
counterproductive activity than to citizenship7.
Some research has directly compared activated versus non-activated positive affect. Studying a
range of self-reported task and citizenship behaviors in six different samples, Warr, Bindl, Parker, and
Inceoglu (2014) showed that work performance is principally associated with positive job feelings that are
activated, as did Madrid, Patterson, Birdi, Leiva, and Kausel (2014) in a single-sample diary study of selfreported
work innovation.
Positive mood at work was found by George (1989) to be correlated -.28 with subsequent
absenteeism, but negative mood was unrelated (-.03). In research by Hardy et al. (2000), feelings of jobrelated
anxiety and depression were correlated .30 and .25 with subsequent absenteeism.
Wellbeing Measured as Context-free Affect
Work behaviors are also moderately associated with wider-ranging feelings, those which are
context-free. For example, Tsai, Chen, & Liu (2007) found that the context-free8 activated positive moods
of insurance sales agents were correlated .46 with their supervisors’ ratings of task performance and .36
with their self-assessments. Reviewing organizational citizenship behaviors across 23 previous
investigations, Dalal (2005) found average correlations of .28 and -.08 with varied measures of positive
affect and negative affect. For counterproductive work behavior, those average values were -.28 and .34.
A few investigations of context-free affect have focused on specific aspects of work performance.
For instance, Fritz and Sonnentag (2009) asked about proactive work behavior as a function of context-free
activated positive and negative affect, finding average correlations of .36 and .13 respectively. Other
studies obtaining significant correlations between proactivity and positive affect (but mixed results for
negative affect) have been reviewed by Cangiano, Bindl, and Parker (2017).
Links with creativity at work have been investigated longitudinally by Amabile, Barsade, Mueller,
and Staw (2005) and considered non-empirically by James, Broderson, and Eisenberg (2004). Amabile and
colleagues studied 222 members of innovation-tasked teams at the end of a day for the duration of each
individual’s personal project extending up to 38 weeks. A person’s creative contribution was assessed
through researchers’ coding of that individual’s daily accounts of experiences and through monthly ratings
by colleagues. Both performance indicators were modestly but statistically-significantly associated with a
day’s positive feelings.
What Do the Correlations Mean?
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This summary of empirical research has revealed a consistently positive but small association
between individual workers’ wellbeing and performance. Many studies have additionally controlled for
potentially-distorting demographic and other variables, and a modest cross-sectional association seems to
be well established across many work behaviors. How might it be explained?
Perhaps greater wellbeing causes better performance. For that causal pattern to be inferred from
empirical findings, a minimum requirement is for wellbeing to be measured before performance. The field
has been dominated by single-occasion research9, but a few publications have considered longitudinal
associations across time, finding that lagged patterns are similar to, but can be reduced from, those crosssectional
associations (e.g., Riketta, 2008).10 It is certainly desirable to investigate patterns in which
wellbeing is measured in advance of performance. However, even when greater job satisfaction, for
instance, has been shown to precede better performance, causal impact from satisfaction cannot be inferred.
For example, influence might instead flow in the reverse direction, from good performance to, say,
job satisfaction (e.g., Lawler & Porter, 1967). Successful task performance could lead to intrinsic rewards
(for instance positive feelings linked to self-esteem) and/or extrinsic rewards such as promotion or an
increase in pay. The two sequential directions between wellbeing and performance have been compared by
Harrison et al. (2006) and Riketta (2008), in both cases showing that average longitudinal correlations are
almost identical irrespective of direction. In the meta-analysis of across-time studies by Harrison and
colleagues, longitudinal correlations between job satisfaction and task performance averaged .17 when job
satisfaction was measured before task performance and .19 when performance preceded satisfaction.
Riketta analyzed a smaller number of panel studies, and reported average correlations of .11 between job
satisfaction and subsequent task performance and .10 when performance was measured before satisfaction.
For organizational citizenship behavior, Riketta found that the two average correlations with job
satisfaction were .23 and .22 respectively.
A third possible causal interpretation combines the previous two. Influence might be reciprocal,
flowing in both directions, so that wellbeing causes good performance and good performance causes
wellbeing. Personal experiences lead many people to suspect that this is often the case, even though
processes within a single individual cannot be generalized to the between-person analyses which make up
the bulk of the empirical literature. However, assuming that some causal influence is reciprocal in that way,
we might also expect that the relative weight of each varies between situations and the operation of other
variables and processes.
However, an additional causal possibility has special merit. In some cases, both wellbeing and
performance may be influenced by omitted, unmeasured features, sometimes labeled as a study’s ‘third
variables’.11 Such potentially causative variables may operate either as short-term ‘occasion factors’ or as
longer-term, continuing influences (e.g., Zapf, Dormann, & Frese, 1996). Thus, concurrent short-term
impacts on both wellbeing and behavior might derive from characteristics of a setting occupied only briefly
or from immediately preceding events; and more extended influences can include continuing supervisor
behavior, support from colleagues, equipment limitations, particular stressors, etc. or from dispositional
worker characteristics such as ability, gender, personality, value preferences, and so on. Although
researchers have sometimes statistically controlled a number of these possible ‘third’ variables, other
potential influences of this kind can be envisaged in all published investigations.
It is logically impossible to be certain that no other features or groups of features also require
consideration as potentially important omitted variables.12 More generally, it is widely recognized that
learning about causality requires some form of experimental manipulation. Within a working organization,
tightly controlled experiments are almost always unacceptable to managers, non-managers or both, and any
organizational experiments which may be undertaken in this area are likely to be fatally flawed.
Researchers into wellbeing and behavior have therefore turned to laboratory experiments to
examine the impact of induced positive or negative feelings. Affect-induction procedures in this research
have included watching a film clip, receiving an unexpected small gift, reading about positive occurrences,
or being exposed to an attractive scent, and research participants have almost always been university
students. Laboratory experiments which induce affect have revealed several consequential changes in
cognition and behavior (e.g., Baas, De Dreu, & Nijstad, 2008; Baron, 1990; Barsade & Gibson, 2007; Erez
& Isen, 2002; Fredrickson & Branigan, 2005). For instance, increases in positive affect have been shown to
give rise to significantly more speedy and more comprehensive mental processing, more positive
judgments about neutral material, greater persistence, and more positive expectancy motivation, enhanced
optimism, increased creativity and self-esteem, and more cooperation with other people.13 Oswald, Proto,
and Sgroi (2015) described three laboratory comparisons of arithmetic task productivity, finding that the
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output of participants with induced positive-mood exceeded control groups by an average of 12%.
Experiments of this kind have yielded consistent findings in comparisons between positive and
neutral affect14 (induced positive affect yields positive behaviors), but it is of course uncertain how readily
those findings can be generalized to organizational settings. Laboratory effects are unlikely to endure
beyond about 20 minutes, and a range of additional variables and social processes also operate in
organizations. Furthermore, activities in a job and elsewhere often bring together behaviors of several
different kinds and embody sequences of experiences that shift between evaluatively negative and positive
and perhaps back again. Nevertheless, although laboratory-derived patterns cannot be directly applied to a
workplace, published causal evidence from experimental research together with personal experiences in
everyday life suggest to many people that wellbeing has some influence on performance. Furthermore,
measured compounds of wellbeing such as job satisfaction or life satisfaction derive from the accumulation
of feelings throughout life, many of which are themselves only brief; short-term affects are cumulatively
important in the long term when combined with other short-term affects (e.g., Diener, 1984; Diener, Suh,
Lucas, & Smith, 1999; Fisher, 2000; Kim-Prieto, Diener, Tamir, Scollon, & Diener, 2005). However, other
causal influences on performance are also probable, outlined above, and multiple causal routes should often
be envisaged. In general, patterns of influence are likely to vary between different feelings, events and
situations.
Varied Associations between Wellbeing and
Performance: Possible Moderators
Given that observed correlations between wellbeing and job performance can differ between
studies, it is important to examine possible moderator variables. Furthermore, by learning about the
conditions under which an association between wellbeing and performance is either larger or smaller, we
can form hunches about the causes of that association. There is a sense in which moderator analyses,
contrasting high and low levels of a possibly moderating variable, can be viewed as notionally
manipulating that variable – a form of ‘thought experiment’.
Early research into moderators in this area focused on the level of constraints on personal decisionmaking
and action. In some jobs, a person is free to decide how work is done, but in other cases external
constraints, such as instructions from a supervisor, strong social norms, or control of behavior by machine,
reduce personal autonomy so that associations between individual characteristics and behavior are then
likely to be reduced. Herman (1973) studied attitude-behavior links in the absence of situational pressures –
when voting for or against trade union representation in one’s company. In that low-constraint setting,
voting in favor of union representation was strongly negatively correlated (-.57) with satisfaction with the
company. Across a range of constraint levels, Bhagat (1982) examined external restrictions on departmentstore
managers in terms of perceived organizational pressure for high performance; correlations between
job satisfaction and supervisor-rated task performance averaged .56 among managers reporting low
organizational pressure, but were only .01 among high-pressure employees. For reported time pressure, the
low- and high-constraint sub-group correlations were .49 and.06 respectively.
The continuum between external and internal influences on behavior was viewed by Mischel (e.g.,
1977) in terms of ‘situational strength’, a major component of which is the degree to which an environment
acts to constrain self-initiated behavior (e.g., Bowling, Khazon, Meyer, & Burrus, 2015; Meyer, Dalal, &
Hermida, 2010). The opportunity to use personal discretion is limited in situations of high constraint –
‘strong’ situations in terms of Mischel’s model, A meta-analysis by Bowling et al. (2015) revealed a
correlation of -.34 between the magnitude of constraints in a job and the association between job
satisfaction and task performance; that is, stronger associations between wellbeing and performance were
found when jobs impose fewer constraints. From structural equation analyses of six sets of data, Warr et al.
(2014) observed substantial associations more widely among discretionary (i.e., low-constraint) forms of
job behavior. This theme was central to George and Brief’s (1992) model of positive mood at work, which
was viewed as having ‘the most effect on behaviors that are performed of one’s own free will’ (p. 324).
Some researchers have examined a second possible moderator – the degree to which good
performance yields personal benefits for an individual. In those terms, associations between wellbeing and
performance are predicted to be stronger when good performance brings the potential for some personal
reward. That was seen to be the case in a laboratory experiment by Cherrington, Reitz, and Scott (1971),
comparing the presence versus absence of performance-based payment, and among salespeople and
managers by Jacobs and Solomon (1977), who found that associations between job satisfaction and
supervisor-rated task performance were moderated by the perceived presence or absence of organizational
performance-reward contingencies.
In the same vein, Schwab and Cummings (1970) emphasized the assessed instrumentality of good
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performance – the degree to which it provides a path to personally-important goal achievement. Intrinsic
rewards, rather than those which are extrinsic such as pay or better work conditions, were central to the
models of Lawler and Porter (1967) and Slocum (1971) and to the perspective of Hochwarter, Perrewé,
Ferris, & Brymer (1999) on workers’ attainment of outcomes which are consistent with their personal
values. Perceived distributive justice (an acceptable balance between personal effort and reward) has been
shown by Janssen et al. (2010) to significantly affect the association of emotional exhaustion with
supervisory ratings of both task performance and organizational citizenship: Emotional exhaustion was
negatively associated with performance when justice was perceived to be high, but unrelated for workers
experiencing low justice.
Some moderators of these kinds are reflected in differences between organizational grades.
Managers and professional staff have more freedom than others to determine their own activities and
wellbeing. It might therefore be expected that correlations between wellbeing and work performance will be
greater among managers and professional staff than among lower-grade workers. In Sheridan and Slocum’s
(1975) study in a steel company, wellbeing-performance correlations were found to average .23 and .10 for
managers and machine operators respectively.15 Doll and Gunderson (1969) contrasted scientists against
enlisted naval personnel on Antarctic assignments, finding correlations between job satisfaction and
supervisor-rated performance of .34 and .05 respectively. The review of overall job satisfaction in relation
to task performance by Petty et al. (1984) found average correlations of .31 and .15 for
professional/managerial versus other workers, and the meta-analysis by Judge et al. (2001) identified
average correlations of .26 for jobs rated as highly complex and .18 for low-complexity work.
Social pressures provide another potential constraint on discretionary behavior, for example through
the operation of work-group norms about acceptable performance. In cases where a work group has
established a normatively prescribed level of acceptable performance, it may be that a person’s own
feelings and values will less determine behavior than in the absence of a strong norm. Early research in this
area emphasized that work-group cohesiveness is likely to promote norms of either low or high productivity
(e.g., Seashore, 1954), and parallel themes have been developed in terms of social identity theory by van
Knippenberg (e.g., 2000) and Tanghe, Wisse, and van der Flier (2010); individuals who more strongly
identify with a group are thought more likely to accept the group’s norms so that their behavior is more
likely to be shaped by them.
That between-person variation might also be construed in terms of an individualist versus
collectivist orientation, some aspects of which have been examined through peoples’ tendency to
experience guilt when deviating from the expectations of others. Guilt-prone workers are likely to be
particularly troubled if they break the norms of a reference group, and those who are more driven by
individualist rather than collectivist motives might be expected to experience less guilt when deviating
from socially-prescribed norms. That difference was observed in two studies of absenteeism from work by
Schaumberg and Flynn (2017). They predicted from the positive value placed by colleagues and superiors
on attendance in a work-role that job satisfaction would be more strongly associated with low absenteeism
among workers who were less prone to guilt than among those who were more guilt-prone. Full-sample
correlations in the two studies between job satisfaction and subsequent absenteeism were found to be
around zero, but in both cases the predicted interaction was statistically significant. At lower levels of
guilt-proneness, personal feelings were more associated with attendance behavior than among guilt-prone
individuals.
Bowling (2007) emphasized the role of personality characteristics, drawing on earlier metaanalyses
to show that associations between job satisfaction and task performance are reduced after the
introduction of Big Five traits such as conscientiousness, extraversion, and neuroticism, and after separate
inclusion of core self-evaluations and organization-based self-esteem. However, as he pointed out, the
satisfaction-performance correlation ‘remained statistically significant after employee personality was
controlled’ (p. 177).
Other personal attributes might also contribute to this pattern. For instance, impaired health reduces
the number and kind of options that are available to a person, and individual differences in skill level can
overwhelm any possible importance of variation in wellbeing. Similarly, certain personal value and
motivational systems are likely to have a wide-ranging impact on links between wellbeing and
performance. For example, workers who wish to avoid excessively stressful inputs from their job, perhaps
more valuing their activities outside paid work, can intentionally limit their work output (‘taking it easy’),
so that for them high wellbeing can be associated with moderate or even low task performance.
Reviews by Lyubomirsky et al. (2005) and others have stressed the role of social behavior and
interpersonal relationships. High-wellbeing individuals tend to be more socially involved than others, and
links between raised wellbeing and organizational citizenship behavior are widely found (above). Given the
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operation of norms of reciprocity, such that help given to others is accompanied by help in return (e.g.,
Bowling, Beehr, Johnson, Semmer, Hendricks, & Webster, 2004), it is possible that correlations between
wellbeing and performance are in some cases partly attributable to task assistance from colleagues (e.g.,
Tsai et al., 2007). Such interpersonal assistance varies between settings and is of course only possible in
jobs which permit interaction and collaboration with others.
Steers (1975) drew attention to the possibility that workers with higher need for achievement are
likely to more strongly value the successful attainment of job objectives, so that for them high task
performance would be especially strongly linked with job satisfaction. In a study of office staff, he found
that supervisor-rated performance was correlated .32 with job satisfaction in the sub-set of high-need
workers but only .10 among low scorers.
In overview, a small number of studies have pointed to environmental and personal variables which
might influence the strength of an association between worker wellbeing and performance. Also important
is the aspect of wellbeing under consideration. For example, Lawler and Porter (1967) and Slocum (1971)
showed that associations with supervisor-rated task performance varied between different needs, with selfactualization
satisfaction being most strongly related to performance.
Some characteristics of wellbeing also influence the magnitude of association with performance.
For instance, in the few studies which examined both positive and negative indicators of affect, positive
feelings have consistently been found to be more important than negative feelings, at least in respect of
positive performance. In addition, the activation level of wellbeing has a particular impact on observed
correlations. Only a few investigations have measured affects of both low and high activation, instead
recording feelings which are all activated16, so that much of the research literature reports significant
associations between wellbeing and performance which are in fact restricted to activated forms of
wellbeing. However, Warr et al. (2014) found in structural equation analyses of findings about a variety of
job behaviors across six investigations that activated job feelings were substantially more strongly
associated with self-reported behavior than were low-activation feelings – average path coefficients of .48
and -.17. In respect of creativity, the meta-analysis by Baas et al. (2008) contrasted more versus less
activated affect, finding average correlations of .17 and .01 respectively.
Associations between wellbeing and job performance are also likely to be influenced by aspects of
research design. For example, the size of observed correlations depends in part on the range of values
examined. Many projects in work settings have used five-point response scales when obtaining
performance ratings; that small range of scores is further truncated by the fact that few retained employees
are rated as low performers. And longitudinal studies have differed in their interval between measuring
wellbeing and performance, so that results from longitudinal research can vary between studies using
different intervals.
In addition, evidence from earlier research does not always meet today’s more rigorous
methodological requirements. For example, reported comparisons between wellbeing-performance
correlations among high- and low-scorers on a possible moderating variable often lack supporting tests of
statistical interaction or incorporate controls for demographic and other features. It is important now to
apply current criteria to new studies in the areas outlined here.
Group-level Research
Although organizations depend heavily on the performance of individual people, recent years have
seen increased attention to the operation and effectiveness of teams. This section will examine research into
wellbeing and performance at the level of groups. Group wellbeing has typically been computed by
aggregating individual scores, but a few studies have instead used items asking about the team as a whole
(e.g., Mäkikangas, Aunola, Seppälä, & Hakanen, 2016). Occasionally, collective wellbeing has been
viewed as group ‘morale’ – positive feelings linked to a desire to contribute to effective performance (e. g.,
Bowles & Cooper, 2009; Peterson, Park, & Sweeney, 2008).
Social contagion theory (Hatfield, Cacioppo, & Rapson, 1994) builds on the fact that emotions arise
not only internally but also from social interaction with others; we share emotions with other people, and
our own emotions are influenced by their emotions. Group-level wellbeing is thus partly the result of social
exchanges as we share our work experiences with other people and are affected by the experiences of
others (e.g., Barsade, 2002). In addition, individuals in a group can be exposed to common external
conditions which can provoke similar affective reactions.
Convergence in groups has been shown to be affected by several moderating influences. For
example, studies have pointed to the importance of stable membership and interdependence between
individuals (Bartel & Saavedra, 2000), and differences between people are influenced by a person’s
individualism or collectivism – the preference for individual versus communal activity; collectivistic group
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members have been found to be more susceptible to affective influences than are individualistic members
(Ilies, Wagner, & Morgeson, 2007). Drawing on social identity theory, Tanghe et al. (2010) showed across
71 teams that members’ stronger identification with their group was associated with more homogeneous
levels of group affect, and that members’ identification with the group was correlated .33 with selfperceived
task performance.
Despite a growing research interest in social dynamics, there have been relatively few
investigations into links between group-level wellbeing and work performance (Barsade & Knight, 2015).
In this section, we give an overview of the literature in this area, looking first at compound indicators of
wellbeing and then at group affective tone.
Group-level Job Satisfaction, Job Engagement,
and Other Wellbeing Compounds
In a meta-analysis of previous research into job satisfaction, Whitman, van Rooy, and Viswesvaran
(2010) reported average sample-size-weighted correlations of group-level satisfaction with task
performance and citizenship behavior of .29 and 34 respectively. They also recorded an average correlation
between group-level job satisfaction and absenteeism of -.37, and an average of .25 with customer
satisfaction. In addition, Whitman et al. (2010) found that the relationship was stronger for specific work
groups than at the branch level and also in work groups with fewer than ten members. They observed that
group-level associations with job satisfaction were stronger when scores within a collective were more
similar to each other, emphasizing the importance for links with performance of shared rather than
fragmented wellbeing. In general, more interdependent activities and experiences within a group are likely
to give rise to more similar experiences.
In a sample of retail stores, Brown and Lam (2008) found a corrected mean correlation between
group-level job satisfaction and customer satisfaction of .29. Furthermore, the relationship between store
satisfaction and customer satisfaction was stronger at the group level than at the individual level – as
confirmed in the wider examination by Whitman et al. (2010).17 Across 328 stores, Grandey, Goldberg,
and Pugh (2011) observed a significant association (r = .28) between store-level job satisfaction and
customer satisfaction, and found that store busyness (the number of sales transacted) significantly reduced
that association, suggesting that in busier stores employees had less time to identity and respond to
customers’ need for help.
Work engagement has traditionally been measured as an individual-level construct, but has also
received some attention at group level (Schaufeli & Salanova, 2011). Group-level work engagement has
been positively associated with supervisors’ ratings of groups’ task performance among office and similar
workers (McClelland, Leach, Clegg, & McGowan, 2014; Torrente, Salanova, Llorens, & Schaufeli, 2012).
Similarly, among hotel and restaurant staff Salanova, Agut, and Peiró (2005) found that group-level work
engagement predicted a positive service climate which in turn predicted group performance measured as
service provided to customers. Gracia, Salanova, Grau, and Cifre (2013) observed that group work
engagement was related to good service through staffs’ greater empathy and extra assistance to customers.
Extending that theme, García-Buades, Martínez-Tur, Ortiz-Bonnín, and Peiró (2016) found that group-level
work engagement in hotels was positively related to service performance, measured through customer’s
positive reports of experience and intentions to return. The association between work engagement and
service climate was reinforced by groups’ high climate for innovation.
Studying 102 work-groups, Mäkikangas et al. (2016) recorded a correlation of .86 between
members’ perception of group-level job engagement and their perceptions of group performance.
Examining possible moderation by personal job crafting (informal shaping of one’s job to better meet
individual needs) (e.g., Tims & Bakker, 2010), they found that crafting to increase self-development and
support from others strengthened the relationship between group-level work engagement and performance.
In a study of joviality (viewed as the extent to which individuals are enthusiastic, excited, and
enjoy what they do), O’Neill and Rothbard (2017) found that firefighters who worked in groups high on
joviality spent less time coordinating their response to calls, so could be seen as more effective, but when
outcomes were measured two months later they also had more vehicle accidents and property loss,
probably because they took more risks. For low wellbeing measured as group-level emotional exhaustion,
Leiter, Harvie, and Frizell (1998) found a strong negative correlation (-.73) across 16 medical units between
emotional exhaustion and patient satisfaction with their care.
Group Affective Tone
This section moves on from cognitive-affective compounds to examine group wellbeing in terms of
positive or negative feelings. Work-group affective tone is usually assessed through the average of
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members’ feelings that are ‘consistent or homogeneous’ (George, 1995, p. 108; George & King, 2007, p.
98). Research has pointed to moderate associations between group affect and aspects of performance. For
example, the positivity of group affective tone has been shown to be significantly associated with selfperceived
group performance (Tanghe et al., 2010) and with specific behaviors such as group coordination
(Sy, Côté, & Saavedra, 2005) and cooperation (Barsade, 2002). Totterdell (2000) described how collective
mood in cricket teams was related to individual players’ match performance, and Hmieleski, Cole, and
Baron (2012) reported that the performance of new venture companies is better when group affective tone
is more positive. Across 26 work-groups George (1995) found that negative aspects of group affective tone
were associated with poorer self-rated customer service ‘in your work group’, but correlations with positive
affective tone were not significant.
Negative group tone has been linked to lower levels of citizenship and customer service behavior
by George (1990); and Cole, Walter, and Bruch (2008) found that more negative group moods in
manufacturing work groups were related to poorer performance as rated by supervisors. Examining
possible moderators of this relationship, Cole and colleagues (2008) found that the inverse relationship
between group-level negative tone and performance was weaker when group members’ nonverbal behavior
was openly negative towards each other.
The meta-analysis by Knight and Eisenkraft (2015) suggested that when negative group affect
stemmed from a source outside the group, groups with more negative affect were better performers,
possibly because external threats make group members coordinate their actions and direct attention
towards tackling that threat. On the other hand, when the source of a negative group tone was internal to the
group (such as unpleasant interpersonal behavior), more negative affect was related to poorer group
performance, possibly because negative feelings in that case are associated with members viewing the
group in a negative light or because the source of the negativity has not been modified (Knight &
Eisenkraft, 2015).
Knight (2015) explored the importance of group affective tone during different phases of a project
in military teams on training exercises, and found that a shared positive mood at the middle of the project,
but not at other stages, was related to better group performance, as group members were more focused on
their collective task. On the other hand, a shared negative mood hindered team performance, as members
continued to explore alternative ideas even as the deadline for the project drew nearer. Stephens and
Carmeli (2016) found that groups in which members felt able to express negative emotions reported better
group performance, that was associated with greater adherence to project budgets and increased
knowledge-sharing.
Group affective tone has also been considered in relation to creativity. Barsade and Knight (2015)
drew attention to the possibility that positive group affect can enhance creativity because group members
who share positive feelings and associated ideas may collectively become better at innovation and problem
solution. However, Tsai, Chi, Grandey, and Fung (2012) failed to find that relationship with group
creativity. They observed that in groups where interpersonal trust was high a positive group affective tone
was related to lower creativity, and suggested that this atypical finding could be explained in terms of
group-centrism (George & King, 2007): If group members trust each other, they are more likely to gravitate
towards to the center of expressed opinions and to reject novel ideas and suggestions, thus reducing the
group’s creativity.
In addition to average wellbeing, the diversity in affect between members is important. For
example, Barsade, Ward, Turner, and Sonnenfeld (2000) found that, where members’ affect in senior
management groups was more varied, the groups performed less well, perhaps because of more internal
conflict and reduced cooperation. George and King (2007) argued that homogeneity in group members’
affect is likely to be most beneficial when tasks are routine and when homogeneity encourages a single
appropriate shared reality. On the other hand, some between-person heterogeneity in feelings can be
particularly desirable in complex or novel tasks to promote multiple perspectives and associated
suggestions for action.
Some Desirable Research Developments
The two-variable possibility that happy workers are more productive than others has long attracted
researchers and the general public, and no doubt will continue to do. However, it is important also to look
beyond those two variables on their own. Most behaviors have multiple causes, and a person’s wellbeing is
usually only one of many possible influences. Models and empirical studies of wellbeing and performance
should therefore also include other continuing or transient conditions, in the environment and/or within the
person. Inputs from a job situation (task demands, supervisor behavior, the availability of feedback,
relations with colleagues, etc.) and from within-person variables, such as values, traits, health, and taskrelevant
ability, may contribute to observed patterns as ‘third’ variables which are often unmeasured in
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studies of wellbeing and performance. A primary research need in this area is thus for the conduct of
multiple-variable investigations to broaden the focus beyond wellbeing and performance alone. For
example, does measured wellbeing account for additional variance in task performance over and above
specified job conditions?18
Another pressing need is for increased attention to possible moderator variables. In what
circumstances is the association of behavior with an investigated form of wellbeing likely to be higher or
lower? As summarized above, a small number of studies have examined this question, but research in
earlier decades can sometimes be questioned on methodological or conceptual grounds. Furthermore,
published moderator studies tend to be disconnected from each other, lack replication, and be conducted in
the absence of overarching theories. It is essential to place new moderator research in a conceptual
framework which includes other variables which can influence the strength of an association.
Some studies should focus on sets of individual workers. The happy-productive worker hypothesis
expects people on average to be either happy and productive or unhappy and unproductive, but the fact that
observed positive correlations are only moderate indicates that many workers do not fit that pattern. We
need to learn more about individuals who are outside the hypothesized pattern. Recognizing that, Ayala et
al. (2016) used data from a study of young employees to place workers in one of four categories: happy
and productive, unhappy and unproductive, happy and unproductive, and unhappy and productive.
Indicators of the two variables were job satisfaction and self-reported job innovation, and almost 15% of
the sample fell outside the two groups expected by the hypothesis; around 9% were classified as unhappy
and productive, and about 5% were defined as happy and unproductive. Average levels of educational
qualification, proactivity and job self-efficacy were found to differ between sets of workers. Further
research along these lines is now desirable, investigating additional measures of wellbeing and
performance and identifying situational and personal features associated with membership of each cluster.
Moderators require particular attention at the work-group level. Research questions and methods
have differed considerably between studies of group wellbeing and performance, and we need to learn
whether principal differences have affected findings. For instance, what is the impact of group size on
associations between wellbeing and performance? Tanghe et al. (2010) studied work-groups containing two
to four workers, but those examined by Mäkikangas et al. (2016) had four or more members; George
(1990) investigated as groups people who worked for the same departmental manager. We do not know
whether size differences of that kind are influential. Also potentially important are dimensions of task
complexity and uncertainty. Perhaps in routine work effectiveness is more linked to homogeneous positive
affect, whereas more complex and uncertain tasks are better performed by groups with more diverse
wellbeing. ‘Group-think’ is likely to be especially dangerous in uncertain and unpredictable conditions
(e.g., George & King, 2007).
Behavior of all kinds is sometimes brought about by external pressures which generate unhappiness
as well as action. When provoked into action by physical, economic, or social threats, people can
experience low wellbeing but generate behavior which is effective; ‘necessity is the mother of invention’.
Occupational research needs to identify situations of this kind and trace extra- and intra-person
developments across time. Zhou and George (2001) focused on job creativity, and showed that job
dissatisfaction was associated with greater creativity when continuance commitment (a perceived need to
remain in post) was accompanied by support for creativity from a worker’s colleagues and organization.
These and associated ideas about the occurrence of zero or negative correlations between wellbeing and
performance now deserve further investigation.
A general requirement is for additional qualitative research in this field, through interviews,
observation, group discussion, video-recording, analysis of company records, and similar procedures. In
many cases, particular behavior sequences can embody both negative and positive experiences, as a
problem first generates strain when solutions are sought and applied and then yields satisfaction or pleasure
after progress has been made. Many personal projects, in a job and elsewhere, are of that threat-thenresolution
kind, and these are poorly served by current research approaches.
Two research designs are conventional to investigate sequential possibilities. Diary studies obtain
research material on several occasions across one or a few days19, and more extended longitudinal research
gathers information on discrete occasions often separated by a period of months. Time intervals have
varied between different longitudinal studies, and study-specific periods of lag have rarely been justified
explicitly in relation to a project’s hypotheses.
It is particularly desirable to develop qualitative research across time 20 in addition to studies of
those kinds. For example, partially structured interviews can be conducted on repeated occasions to learn
more about perceptions of and reactions to evolving situations, possibly seeking the occurrence of self-
697
sustaining spirals and evidence relevant to Fredrickson’s ‘broaden and build’ developmental model (e.g.,
Fredrickson, 2001; Fredrickson & Branigan, 2005). That model envisages positive emotions broadening the
scope of attention, cognition and action, with benefits accumulating across time. In studying possible
changes of those kinds, it is desirable to explore mental processes and actions in depth through a series of
detailed discussions. Similarly, qualitative investigations into processes of job crafting, as workers shape
their job activities to enhance wellbeing, can benefit from personalized, continuing information-gathering.
Social contagion theories are based on individuals interpreting verbal and non-verbal cues in faceto-face
interaction, but work environments increasingly involve virtual team and remote working, where
direct interaction is replaced by text-based services, email, messaging, and several types of social media. In
those cases, emotions and affect are communicated less directly, and it is important to incorporate that
change in our research methods (Barsade & Gibson, 2007). Does the development of group affective tone
differ between face-to-face and virtual groups?
Research in this field has usually measured group affective tone as the average of individual scores,
and the conceptual and methodological bases and implications of this procedure also need examination
(van Mierlo, Vermunt, & Rutte, 2009). It is important to examine the degree of heterogeneity between
different group members (e.g., Barsade et al., 2000; Bliese, 2000; Cole, Bedeian, Hirschfeld, & Vogel,
2011; George & King, 2007), perhaps in terms of measured variance in individual scores, the number of
extreme-scoring members, or average deviation from the overall mean (Burke & Dunlap, 2002)21. For
example, it is likely that a small number of individual group members who are in a particularly negative
mood have an overall disruptive impact on processes within the group (Felps, Mitchell, & Buyington,
2006). Other methodological studies should compare the factor structure of compound indicators between
individual and group levels (van Mierlo et al., 2009).
It is also important to expand thinking about the concept of wellbeing. Traditionally, research has
examined hedonic forms of the kind illustrated in this chapter, but it is possible also to envisage additional
aspects which are loosely based on Aristotle’s (384-322 BC) ideas of ‘eudaimonia’ – a good, virtuous or
fulfilled life. This notion has been developed by some psychologists into wellbeing as personal
‘flourishing’, variously considered by different scholars to embrace an active engagement in the world,
experienced meaning or purpose in life, autonomous self-regulation, perceived competence in personally
important activities, having vitality, and relating positively to others (e.g., Baumeister, Vohs, Aaker, &
Garbinsky, 2013; Huta & Waterman, 2014; McGregor & Little, 1998; Ryff, 1989; Seligman, 2011;
Waterman, 2008). As an aspect of wellbeing beyond traditional hedonic indicators, flourishing deserves
more attention in the area of this chapter. For instance, for workers who flourish in terms of a high sense of
personal accomplishment in their work, a strong association appears likely between job performance and
that aspect of wellbeing. Previously applied hedonic measures of worker wellbeing do not cover all of that
construct, and flourishing should be included in future studies.
Another desirable research development is an increased concern for non-linear relationships
between wellbeing and performance (e.g., Tenney et al., 2016). For example, a curvilinear pattern might
reflect the fact that above a moderately high level of wellbeing the two variables are negatively rather than
positively associated with each other, parallel with Warr’s (2007, 2017) Vitamin Model. Or perhaps job
performance is not associated with wellbeing across higher levels of wellbeing, but the two are positively
intercorrelated at low to moderate levels.
Academic research into possible influences on wellbeing and performance has failed to investigate
practical processes of their joint optimization. Concern has often been directed at enhancing either
wellbeing or performance, but rarely at improving the two together. There is now a great need for research
into the processes and outcomes of interventions in work settings which are aimed to enhance both of them,
rather than merely one alone. For example, interventions in terms of self-management training can build
mental effectiveness in goal-setting, self-assessment and self-evaluation (Frayne & Geringer, 2000) in
addition to improving task performance. These changes can yield personal rewards and positive
experiences, linked to reduction in anxiety, improvement in mental health, and perhaps to improved job
wellbeing (Richardson & Rothstein, 2008).
At the group level, social support and collective job crafting have been found to be associated with
wellbeing and performance (Nielsen et al., 2017), and interventions to increase mutual support or collective
job crafting may yield increases in both wellbeing and performance. Such interventions aim to increase
resources widely within a group through knowledge-sharing, helping behaviors, and working towards
overall group benefits, rather than merely gains for an individual. Whereas one individual worker’s job
crafting may have consequences which are negative, for instance from avoiding disliked tasks or
competing with colleagues for activities which are most interesting, explicitly collective job crafting can be
of wider benefit to the work-group as a whole, in terms perhaps of both wellbeing and performance.
698
Speculation about Cause and Effect
The chapter opened by noting that a positive association between worker wellbeing and job
performance is widely expected. Subsequent sections have shown that across principal forms of wellbeing
and performance the association is indeed positive, although it is small and depends on the operation of
moderating factors.
We have stressed that it is not appropriate to draw conclusions about causal processes from the
evidence presented here. Firmly controlled experiments are required, but those have proved impossible
within organizations, which must maintain their financial viability throughout the months or years of an
experimental period. In any case, the limited experimental control which might be achieved is insufficient
to rule out the impact of potential ‘third variables’, which can be responsible for observed associations
between wellbeing and performance even despite statistical control of a limited number of variables.
Although cross-sectional and longitudinal research are both important to map out a current or extended
situation, they cannot provide the basis for causal interpretation.
Nevertheless, positive findings from laboratory experiments indicate clearly that changed
wellbeing can modify behavior in the short term. Short-term experiences and activities are essential
building-blocks of longer-term wellbeing, as multiple short-term feelings become aggregated across time,
repeatedly recalled, and perhaps elaborated (e.g., Diener et al., 1999; Fisher, 2000; Kim-Prieto et al.,
2005): life satisfaction is based on thousands of earlier short-term experiences stretching across years.
Furthermore, positive wellbeing tends to be associated with traits of optimism, confidence, sociability and
other dispositions which encourage goal-orientation and active involvement in situations which can
themselves generate wellbeing. In subjective terms, personal experiences suggest to many people that
wellbeing can sometimes make a difference to their job performance, as they observe how their positive or
negative moods appear to be shaping their behavior. Both conceptual argument and personal introspection
thus argue for some causal impact from wellbeing.
Many perspectives and decisions in daily life are based on imperfect evidence, and in those terms it
is our belief that wellbeing does often influence performance. However, this influence can be relatively
small, other variables are also causally important, and causality may run in other or multiple directions.
Footnotes
1Although the term ‘work’ often refers to a job, it is widely used in other settings – in respect of
housework, social work, voluntary work, and so on. Researchers differ in their use of either ‘work
engagement’ or ‘job engagement’.
2In practice, that conceptual distinction is not always maintained in scales used to measure satisfaction,
which can include items reflecting activated positive reactions rather than mere acceptance.
3The label ‘performance’ is usually applied to behaviors of a particular kind – those which are considered
important and desirable within the investigated setting, in this case behaviors which are desirable in a job.
4Correlations with job satisfaction and job engagement were very similar between supervisor-, colleagueand
self-ratings of task performance in research by Halbesleben and Wheeler (2008). For job engagement,
Christian et al. (2011) reviewed the few available associations with task performance and organizational
citizenship. Mean correlations across the two types of performance together were .31 for self-reports and
.29 for other-reports. For emotional exhaustion, Mastenbroek, Jaarsma, Scherpbier, van Beukelen, and
Demerouti (2014) found correlations with task performance of -.19 and -.18 respectively.
5Their two data-sets were very similar.
6Measured for example by ‘I feel emotionally drained by my work’.
7However, longitudinal affect-behavior associations were generally non-significant in these studies.
8We are grateful to Wei-Chi Tsai for the unpublished information that mood ratings were context-free
since participating sales agents can work at any time of day.
9A high proportion of publications fail to provide precise details of when information was collected. It
appears that in most cases (apart from in longitudinal studies) behavior has been investigated through
information about a period (often of unspecified duration) in the past. Analyses of cross-sectional findings
therefore often concern current wellbeing in relation to behavior at an earlier time.
10In part, the smaller size of longitudinal associations might be attributed to the duration of interval
699
between measurement of the two variables, since correlation sizes are found to be smaller as time lag
increases (e.g., Riketta, 2008).
11‘Third’ variables in the sense that they are additional to the two in a bivariate study. Taking a nowunfashionable
behaviorist view, Skinner (e.g., 1969) argued that feelings are mere accompaniments of
behavior, and that both are the products of common environmental variables.
12However, knowledge often expands through the accumulation of slightly different sets of findings, each
of which lacks some important controls but which as a whole widen the possible confounds that have been
held constant.
13Although these processes are desirable in many job situations, that is not always the case. For instance,
more rapid mental activities often rely on the use of simple heuristics which can be inappropriate in many
detailed tasks.
14On the other hand, negative manipulations have resulted in more variable outcomes (e.g., Davis, 2009).
15This comparison may be confounded by the use of different indicators of performance – supervisorratings
for managers and actual output for non-managers.
16The chapter’s account of affect studies has sometimes described a measure as ‘activated‘, although
activation level was not explicitly discussed in the published report. In those cases, the ‘activated’ label has
been applied after studying the items presented in the source publication.
17One possibility is that measurement reliability is increased by aggregating individual scores.
18Several variables treated in one publication as correlates of performance in addition to wellbeing might
for different purposes also be viewed as mediators (e.g., Tenney et al., 2016).
19However, diary studies have rarely focused explicitly on within-person changes during their period of
study.
20Qualitative approaches can also be justified on wider grounds as well as in this particular respect (e.g.,
Pratt & Bonaccio, 2016).
21Researchers into organizational culture have emphasized the notion of culture ‘strength’ – the level of
agreement between members of an organization (e.g., Schneider, Ehrhart, & Macey, 2013).
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Optimal Levels of Happiness
By Robert Biswas-Diener, Portland State University and Noba, & Christopher W. Wiese, Purdue
University
Citation
Biswas-Diener, R., & Wiese, C. W. (2018). Optimal levels of happiness. In E. Diener, S. Oishi, & L.
Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
In the post-material era, people are increasingly focusing on the pursuit of happiness. This popular interest
has been met by a growing number of authors and interventionists who promise routes to happiness. In
large part, these avenues to the good life are anchored in the results of scientific studies. Here, we offer the
caution that there may be an optimal level of happiness. While it is true that happiness is widely beneficial,
there is also a growing body of research suggesting that it is not always beneficial for all people. In this
chapter, we define happiness and review the literature suggesting that more nuance discussion is needed.
We focus on three ways that happiness might be sub-optimal, including mood dysregulation (being happy
regardless of circumstance), complacency (curtailing effort), and affect imbalance. We conclude by
discussing three contexts that interventionists and policy makers ought to consider when promoting
happiness. These include attention to happiness in specific life domains, distinguishing between short and
long-term happiness, and a deeper appreciation of how cultural factors affect the pursuit and experience of
happiness.
Keywords: Optimal levels; happiness; well-being; interventions
Everyone makes attributions. We believe our neighbor is a jerk, our spouse is generous, and that our
pet dogs are loyal. Nowhere are these attributions more prevalent, perhaps, than in the context of happiness.
Someone on holiday in Jamaica? Happy. Someone recently divorced? Unhappy. Someone whose team just
won the championship? Happy. Someone who was in a minor collision on the way home from work?
Unhappy. Interestingly, there is an unspoken assumption that happiness is the preferred emotional mode.
Most of us would prefer to see more Jamaican vacations and sports wins and fewer divorces and fender
benders. Simply put, we all want to be happy (Lomas, 2016). In fact, people—especially those living in
Western or industrialized cultures-- treat happiness largely as they treat money: with an appetitive attitude.
Indeed, Hobbes described happiness as the fulfillment of our human appetites (Kitanov, 2011). Just as
people tend to desire more money, so too do they tend to desire more happiness. But, should they?
The money metaphor is instructive. Results of research on economic conditions suggest that
national wealth is associated with better environmental policy, infrastructure, education, and social justice
(Biswas-Diener, Diener, & Lyubchik, 2015). Similarly, very wealthy individuals appear to experience a
high quality of life (Diener, Horwitz, & Emmons, 1985). Despite the appeal of money, it should be noted
that it is not the wealth itself that confers benefits but the possibilities it represents. Money can, for
example, be used to purchase rewarding experiences (Van Boven & Gilovich, 2003) or can be used
altruistically (Aknin et al., 2013). On the other hand, materialism—placing too heavy an emphasis on the
importance of money—appears to be toxic to happiness. We can see, therefore, that it is not that having (or
not having) of money, itself, that is good, but—rather—the potential psychological benefits are to be found
in our perceptions of money and in how we use it (Diener & Biswas-Diener, 2008). It may be that
happiness represents a similar case. It may be that happiness is generally, but not perfectly, beneficial.
Hence, it makes sense to wonder if a person can have “too much happiness.”
The question of optimal levels of happiness is important in the modern context. We live in a postmaterialist
era in which large numbers of people are able to focus on happiness as important areas for
personal development. This trend can be seen in the rise in popularity of the positive psychology movement
(Seligman & Csikszentmihalyi, 2000) both among researchers and consumers. The sales of happiness
related self-help books are further evidence that many people view happiness as highly desirable (Bergsma,
2008). This behavioral trend is echoed in survey results showing that people from widely differing cultures
all believe that happiness is an important life outcome (Diener & Oishi, 2000). Further, there is increasing
evidence that happiness is directly malleable – either through designed interventions (Tay & Kuykendall,
2013) or through deep brain stimulation (Synofzik, Schlaepfer, & Fins, 2012). We are entering an age
where happiness is both highly valued and can be easy induced. Therefore, it is important to take a step
back and question: Is there a downside to happiness?
In this chapter, we begin by stepping back – Defining first what is meant by happiness. There are a
708
variety of definitions of happiness and it is important that we define the boundary conditions of our
discussion. Next, we elaborate upon what is meant by ‘optimal levels.’ Specifically, optimal levels of
happiness may or may not result in detrimental outcomes and we discuss the forms in which these
relationships can take. We build upon this foundation by examining what is currently know about optimal
levels of happiness and present considerations for those looking to take the next steps in this endeavor. It is
our hope that this chapter may be informative to those looking to understand the potential downsides of
happiness and provide important considerations to those looking to extend the existing literature.
What is Happiness?
The question of whether there can be “too much happiness” hinges, in large part, on definitions of
this elusive concept. There are a variety of research traditions that address happiness. Perhaps the most
widely known is that of subjective well-being (SWB; Diener, 1984). SWB is comprised of three separate
but related elements. These are positive affect, negative affect, and life satisfaction. At the heart of SWB is
the notion that happiness is a subjectively experienced phenomenon, and that it includes both affective and
cognitive appraisals of life. A happy person, according to the SWB framework, would be someone who
feels generally satisfied with her life, experiences a preponderance of positive emotion and only occasional
and appropriate negative emotion.
By contrast, there are a number of lines of research that focus more broadly on well-being, and
which include what are, arguably, more objective phenomena. Perhaps the best-known example is
psychological well-being (PWB; Ryff & Singer, 1998). Psychological well-being includes mastery,
autonomy, relatedness, growth, self-acceptance, and meaning. A happy person, according to this
framework, would be someone who has a sense of competency, balances autonomy with high quality
relationships, experiences opportunities for personal growth, accepts herself, and enjoys a sense of being
engaged in meaningful goals.
Recently, it has become en vogue in the field to classify these two types of approaches to studying
happiness as if they represent 2 distinct happiness concepts. These include “hedonic” happiness, which
emphasizes the affective dimension, and “eudaimonic” happiness, which emphasizes the objective
functioning of the individual (Ryan & Deci, 2001). For an in-depth discussion of this topic see Keyes and
colleagues (2002) and Kashdan and colleagues (2008). For our purposes in this chapter, we will largely
confine our discussion of optimal levels of happiness to the subjective, emotional aspects of the topic. In
part, we do this because a comprehensive coverage of every model of well-being is beyond the scope of
any single work. That said, we will give brief coverage to both, including attention to life satisfaction (a
cognitive dimension of happiness).
Regardless of the specific definition, it is important to note that research from all traditions support
the idea that happiness does not just feel good; it is good. That is, happiness confers tangible benefits in a
wide range of domains. Reviews examining the hedonic tradition show that, across different study types
(cross-sectional, experimental, longitudinal) and across different domains (health, work, and relationships),
those experiencing more positive emotions tend to live longer and healthier lives (De Neve, Diener, Tay, &
Xuereb, 2013; Lyubomirsky, King, & Diener, 2005; Pressman & Cohen, 2005). Similarly, Ryan and Deci
(2001) argue that eudaimonic experiences of happiness are, by definition, beneficial. When people
experience growth, self-acceptance, or connectedness with others, for example, they are experiencing high
functioning. As evidence, Ryan and Deci (2001) review research linking physical health to eudaimonic
states. In both eudaimonic and hedonic frameworks these benefits appear to be consequences of happiness
as well as causes. Thus, happiness can be seen as a means as well as an end.
What is Optimal?
The aforementioned literature on the benefits of happiness are from studies that assume the
relationship between happiness and other outcomes are exclusively linear. It is only recently that
researchers have explored the potential downsides of happiness and employ the analytic techniques that
could detect such a relationship. Non-linear relationships can take on many forms; however, we are
concerned with only two in our discussion of optimal levels of happiness. First is what is commonly
referred to as the inverted-U shaped curve. This curve (Figure 1) represents the ‘too much of a good thing’
hypothesis, where happiness is beneficial for an outcome only until a certain point, after which happiness
actually becomes detrimental. Figure 1 also shows a less severe version of the curve in which there are
diminishing returns. With the diminishing returns curve, happiness reaches an optimal level, but higher
level of happiness do not necessarily detract significantly from the outcome of interest. Both theoretical
curves indicate optimal levels of happiness, however, they differ in terms of what happens after happiness
reaches an optimal level.
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How Can Happiness Be Bad?
For as popular a topic as happiness is, there appears to be a conspicuous absence of cautionary
restraint regarding the topic (Kashdan & Biswas-Diener, 2015). Although happiness feels good, and is
associated with a variety of benefits, we know little about how much happiness is optimal, and for whom,
and when. As noted earlier, the research evidence seems to indicate that happiness is always beneficial, and
this is also true of popular press books. An example of this can be seen in Achor (2010), “We can all reap
the benefits of the happiness advantage if we work hard enough at it. Remember, happiness is not just a
mood—it’s a work ethic” (p. 50). This view of happiness leads one to question: How can happiness be bad?
To answer that, we discuss three different possibilities that bring the unilateral goodness of happiness into
question.
Affect-as-Information Theory. Among the most highly cited theories in emotion research is
“mood as information” (Carver, 2003; Schwarz & Clore, 1983). This theory emphasizes the idea that mood
states offer useful information to those experiencing them on how to respond to their environment. Anger,
for example, is a signal that an individual’s person, group, property, ideals, or love ones are under
immediate threat (Kashdan & Biswas-Diener, 2015). Similarly, happiness can be a signal that no such
threats are present and that it is safe for a person to be more sociable, exploratory, or relaxed (Ito &
Cacioppo, 1999; Fredrickson, 2001). When modern self-help gurus advocate more happiness, they often
miss the informational value of emotion. They operate from the premise that negative moods feel bad,
should be avoided, and can be side-stepped through mental and behavioral intervention. By the same token,
positive moods can be amplified and extended through similar intervention. In both cases—positive and
negative moods—the idea of artificially promoting one state, regardless of context, may be encouraging a
process that divorces people from an important channel of information about the world. Hence, individuals
who are ‘too happy’ may be overlooking important information, dampening their ability to function
personally and socially.
Valuing Happiness. Another way happiness can be bad is if individuals place too much value on
it. Mauss and colleagues (2012) present the case that individuals who value happiness too much may set
unrealistic happiness goals. Ultimately, when they fail to achieve these unreachable goals, they experience
feelings of disappointment and sadness. In a series of two studies, Mauss and colleagues (2011) found
evidence for this effect such that those who valued happiness actually experienced less positive emotions
and more negative emotions. Valuing happiness too much may also come at a price to one’s social
relationships. Mauss and colleagues (2012) demonstrated that when individual value happiness (defined as
personal gains) too much, they a bound to destroy social connections leading to feelings of loneliness. They
found evidence of this through both self-report and salivary measures. Taken together, these studies offer
potential nuance to the “happiness is beneficial” narrative.
Affective Forecasting. The last way through which happiness could have adverse consequences is
through errors in affective forecasting. When projecting future emotional states, individuals tend to
underweight the potential impacts of negative events, believing instead that tomorrow will hold a bright
710
future (Schacter & Addis, 2007; Sharot, 2012). This optimism is, in part, functional – as it helps individuals
persevere through difficult times in hopes for a better tomorrow. However, much like valuing happiness
too much, these expectations could act as a double-edged sword (O’Brien, 2013). Individuals tend to hold
onto an optimistic attitude even when there are several signs to the contrary. Hence, when that better future
does not come, they are often left discouraged and frustrated.
Evidence of Optimal Happiness
With these three possibilities in mind, we now move to reviewing the existing evidence for optimal
levels of happiness. Although research on this topic is relatively new, we believe that there are three clear
trends attempting to tackle this issue: Mood dysregulation, nonlinear happiness, and balanced happiness.
Mood Dysregulation. There is a substantive rationale for inquiring about a potential optimal level
of happiness. The most obvious point of reflection on this topic is to be found in instances of mood
dysregulation. People suffering from bi-polar disorders, for instance, often experience intense positive
affect in a disruptive way (Gruber, Mauss & Tamir, 2011). People experiencing mania may be likely to
take risks or act in inappropriate ways that are damaging to themselves or those they care about. In a review
of clinical research literature Gruber and colleagues (2011) conclude, “I argue that troubled emotional
functioning in bipolar disorder might be explained by an unrelenting experience of heightened positive
emotions regardless of the external context…. In fact, feeling ‘too good’ may actually be detrimental” (p.
362). However, evidence of mood dysregulation is not limited to those with clinically diagnosed
psychological disorders.
Another line of research on affect regulation comes from Diener and colleagues (1991). They
examined the effects of various cognitive strategies on affect regulation across five studies. They
discovered that the mental strategies people use to amplify happiness might have a psychological price. For
example, cognitively amplifying positive affect can also have a spillover effect such that it amplifies
negative affect as well. This dovetails with research showing that people with clinical depression who
attempted to dampen negative emotions also showed diminished capacity to react expressively to
amusement (Chentsova-Dutton, Chu, Tsai, Rottenberg, Gross & Gotlin, 2007; Chentsova-Dutton, Tsai &
Gotlib, 2010). Although the research on this topic is relatively small, it appears that effortful regulation
strategies such as dampening and amplification are “blunt instruments” in that people may not be able to
regulate either positive or negative affect without also regulating the other.
Unbridled Happiness. Researchers have also begun to investigate the potential nonlinear
relationship between happiness and several interesting outcomes. To the best of our knowledge, Oishi and
colleagues (2007) were the first to directly raise the issue of linear versus non-linear benefits of happiness.
They provide analyses of social survey and quasi-experimental data on the association of happiness with a
variety of outcomes. The lion’s share of their scholarly attention is found in two areas: income and
academic performance.
With regards to the former, they reviewed a wide range of evidence showing that moderate, but not
consummate, happiness is associated with higher income. For example, using data from a long-term
longitudinal study of Australians they found that people who were a 4 out of 5 on a measure of life
satisfaction enjoyed higher outcomes than did those who were a 5 out of 5. This same finding was
replicated in a longitudinal study of students attending the University of Illinois. In this case, students who
were a 4 out of 5 on cheerfulness made more money two decades later than did their happier counterparts.
This trend—that happy people make more money than do very happy people—emerged again and again in
nationally representative samples in Germany and in the United Kingdom.
In addition to income, amount of positive affect also appears to be associated with academic
performance. Specifically, Oishi and colleagues (2007) evaluated a variety of academic, social and
psychological variables among University of Illinois students. To do this, they computed an affect balance
score by dividing positive emotional experiences such as joy, affection, and contentment by negative
emotional experiences such as anger, sadness and guilt. They found that those who were in the top quintile
for affect balance (“very happy”) reported the highest levels of gregariousness, close friendships, selfconfidence,
energy, and spent the most time on romantic dates. By contrast, those who were in the 4th
quintile (“happy”) had the highest grade point averages, the best class attendance, had the best balance of
positive to negative life events, and were the most conscientious.
Although Oishi et al (2007) represents a large-scale attempt to demonstrating the nonlinear
relationship of happiness, several smaller scale studies have also attempt to answer this question. Recently,
there has been increased interest on this topic in the organizational sciences. Baron, Tang, & Hmieleski
(2011) showed that entrepreneur’s positive emotions could eventually lead to a downturn in firm
performance. Interestingly, the severity of the downturn was more significant for smaller firms than larger
711
firms. Relatedly, Lam Spreitzer, and Fritz (2014) found an inverted-U shape curve between positive
emotions and prosocial behaviors at work. These researchers subscribe to the idea that too much happiness
leads to complacency. If the perception is that things are going well, there is no need to be more financially
successful or engage in prosocial behaviors. Hence, some have argued that the key to avoiding this
downturn is a balance of the positive and the negative.
Affective Balance. Could the key to optimal levels of happiness be a mix between positive and
negative feelings? Many researchers have tangentially touched on this issue by examining the effects of
ratios of positive to negative experience (e.g., Meeks, Van Haitsma, Kostiwa, & Murrell, 2012; Fredrickson
& Losada, 2005; Gottman & Levenson, 1992). Rather than charting boundary conditions, however, these
researchers were primarily interested in the finding that ratios need to favor positivity in order for people to
function well. However, there have been some notable exceptions. A study conducted by Friedman and her
colleagues (2002) assessed outcomes, such as self-deception, aggressiveness, and hypomanic symptoms, of
72 people who had above average emotional balance ratios and determined there was little support for “too
much happiness.” Even so, this is only a single study, and not without its limitations. It could be that the
average affect balance score was not sufficiently high to reach a threshold for “too happy.” Alternatively, it
might be that the outcome variables of interest were not those most likely to capture the “too much
happiness effect.” Specifically, the researchers were looking for instances in which happiness is actually
negative for the person experiencing it. It may be that high levels of happiness remain beneficial, but less
beneficial than are moderate levels of happiness.
Hence, it is not too surprising to find other studies using affective balance have found significant
effects. Specifically, Regu, Sousa, Marques, and Pina e Cunha (2012) were concerned with testing whether
a balanced positivity ratio is necessary for creativity such that if one is too positive, they may not be
creative. Indeed, they did find that this was the case – those with an excessively positive ratio were less
creative than those with more balanced ratios. Although Barker, Howard, Galabos, and Wrosch (2016) did
not use a positivity ratio, they found the happiest students who experienced some negative emotions had
the highest GPAs. In fact, during semesters when negative emotions were below average, the happiest
students had lower GPAs than those with lower positive emotions.
Considerations
Thus far, we have laid down the conceptual underpinning of why happiness could be a detrimental
and reviewed the existing evidence on the topic. In this next section, we take a look to the future and
provide several considerations for those interesting in optimal levels of happiness. Specifically, we discuss
how optimal levels may depend on life domain, short- vs. long-term happiness, intensity vs. frequency, and
culture.
Life Domain. Oishi and colleagues (2007) conducted many analyses whose results suggest that
there may be an optimal level to happiness. Interestingly, the majority of their results point to achievement
oriented domains as being likely contexts in which the advantages of additional happiness are non-linear.
In their examination of university students, for example, the happiest students seem to have the highest
scores for social relationships, confidence and energy, while the next happiest group showed superior
academic achievement. This is in line with prior research suggesting that the variable that best distinguishes
the happiest and least happy people is the presence of high quality social relationships (Diener & Seligman,
2002).
In fact, Oishi and colleagues (2007) analyzed data from the World Values Survey and found an
optimal happiness effect (non-linear) for achievement domains but not for social domains. A variation of
their findings is presented in Table 1. As can be seen, happiness appears to be generally beneficial but the
very happiest people do not perform quite as highly as do happy people. This effect holds for both men
and women.
Table 1. Outcomes by Level of Satisfaction
Highest
Income
Highest
Education
Most
Political Action
Most
Volunteerism
Highest
Relationship Satisfaction
Life Satisfaction
(1-10)
9 8 8 10 10
These points raise the issue of one possible way that too much happiness might interfere with
functioning in achievement oriented domains. Namely, through cognition. Researchers have noted stark
712
differences in the thinking styles of happy and unhappy people (Lyubomirsky & Ross, 1997). Baumeister
and colleagues (2007) noted that emotions can deleteriously influence behavior by interfering with optimal
cognitive processing. For example, researchers have found that happy people are more likely to perceive
less risk (Haase & Silbereisen, 2011) and more likely to be susceptible to false memories (Storbeck &
Clore, 2005). Further, research reveals that people in a good mood perform worse than others on tests of
moral reasoning (Zarinpoush, Cooper & Moylam, 2000) and make worse estimates of correlation (Sinclair
& Marks, 1995).
It is possible that the potentially negative impacts of positive affect on cognition are less relevant to
the social arena. Indeed, Oishi and colleagues (2007) did not report an optimal level of happiness for social
domains. Although the strong link between high quality relationships and happiness is often reported in
research, little is known about how the quantity of relationships relates to happiness. It may be that very
high levels of happiness have a direct and causal influence on relationship maintenance. Happy people
appear to be more sociable and connected with others (Lyubomirsky, King, & Diener, 2005). This does not
mean, however, that more time socializing is associated with greater happiness dividends in a linear
fashion. In fact, Diener and colleagues (2008) found evidence for diminishing marginal utility of time spent
socializing.
Short- vs. long-term happiness. Another consideration in the context of optimal levels of
happiness is the trade-offs between short-term and long-term happiness. The recent focus on hedonic
(emotional) and eudaimonic (non-emotional) aspects of well-being may have distracted from attention to
timeframe. Historically, researchers have examined momentary happiness (Scollon, Diener, Oishi, &
Biswas-Diener, 2004), frequency of happiness (Schimmack & Diener, 1997), and a continuum of happiness
that includes the past, present and future (Pavot, Diener, & Suh, 1998). For instance, Wirtz and colleagues
(2003) examined anticipated, experienced, and recalled happiness among college students during and
around the period of their spring break.
It may be that the answer to the question of whether there can be too much happiness depends upon
whether one is referring to short term or long term happiness, or to the trade-offs inherent between them.
For instance, a person experiencing high satisfaction with her grades may choose to study less than
someone with only moderately high satisfaction. In essence, she would be counterbalancing short term
happiness (current level of satisfaction) with estimated future levels of happiness. The way that people
allocate resources and make decisions in the short and long term is likely of crucial importance to the idea
of optimal happiness in achievement oriented domains. Initial research is suggestive that people
differentially preference pleasure in the short term, and meaning in the long term (Kim, Kang & Choi,
2014).
Intensity vs. Frequency. One important consideration in the question of optimal happiness is
related to the question of “what is happiness?”. Indeed, if happiness is defined as meaning in life then the
idea of too much meaning may be less sensible than if happiness is defined as emotion. As happiness
research was becoming established in the 1980s and 1990s researchers were interested in which aspects of
emotionality appeared to capture this elusive concept best. Research revealed, for instance, that people who
experience intense negative emotions are also more likely to experience intense positive ones (Diener et al.,
1985; Larsen, Diener & Emmons, 1986). However, positive and negative affect does not often co-occur at
high rates of intensity (Diener & Iran-Nejad, 1986). Diener and colleagues (1991) concluded that frequency
(but not intensity) of positive affect is both necessary and sufficient to produce high scores on a wide range
of happiness measures. Pressman and Cohen (2005) suggested those experiencing high arousal positive
affect might experience decrements in their physical health. This leaves open the question of whether—
when considering optimal levels of happiness—it might be possible that happiness is “too intense” and/or
that happiness might be “too frequent.” Both considerations need further investigation.
Culture. Another consideration involves the question of who, specifically, is experiencing the
happiness. Cultural factors may moderate the relationship between happiness and its benefits.
Psychologists often research culture as divided into two broad categories: individualist and collectivist
cultures (Triandis, 1998) and these roughly map onto so-called Eastern and Western societies. There is also
a robust research literature on the ways that culture affects the experience of emotion (see, for example,
Tsai, 2007; Suh, 2000). Researchers gave especially identified the ways that cultural leanings in cognition
can affect emotional processes. For example, Lam and colleagues (2005) examined differences between
individualists and collectivists with regards to affective forecasting (predicting future emotional states.
They found that people from Eastern cultures (collectivists) were less likely to cognitively focus and were,
therefore, less likely to experience the types of affective forecasting biases common in individualists. Other
studies have shown striking cultural differences in the experience of emotion itself. For instance,
Chentsova-Dutton and her colleagues (2010) investigated the emotional reactivity of Eastern and Western
people diagnosed with clinical depression. They found that Westerners with depression showed dampened
713
responses to amusing films whereas their depressed Eastern counterparts did not. This suggests that
Westerners have a different predisposition to distress tolerance and attempt to suppress their negative
emotions. In doing so, they also suppress positive emotions. A similar pattern was not seen among the
participants from Eastern cultures. Relatedly, the consequence of expression emotions may depend on the
culture. Kitayama et al. (2015) found that expression of anger led to higher health risk in American
samples, but lower health risk in Japanese samples.
Given these stark cultural differences in emotion, it makes sense to wonder whether a possible
optimal level of happiness would be similar across cultural groups. In a related study, Ford and colleagues
(2015) investigated whether motivation to pursue happiness produced different results for people from
various cultures. They found that for people from the United States, high motivated to pursue happiness
experience lower well-being but this was not the case with people from East Asia. The authors posit that
the how of happiness pursuit may be implicated. Specifically, East Asian may be more likely to pursue
happiness through social connectivity. This is important in the context of social relationships discussed
above. It may be that Americans rely more heavily on cognitive strategies (those most likely to be affected
by high levels of positive emotion) and that they are more likely to treat happiness as an achievement (a
stance with, possibly, a greater link to optimal levels of happiness). Although there is no definitive study or
line of research linking cultural factors to optimal happiness it is a worthwhile area of focus for future
study.
Conclusion
In the end, charting the boundary conditions at which happiness is beneficial is an important
undertaking. A small but growing body of research suggests that there may, indeed, be an optimal level of
happiness. Our preliminary understanding of this threshold suggests that this might especially be true for
achievement oriented life domains but not necessarily for social ones. In addition, it may be that the
answer to the question of optimal happiness depends, in part, on type of happiness as well as on cultural
factors. Differences in cultural background may be not be the only between-group factor influencing what
is considered optimal. For example, Diener, Nickerson, Lucas, and Sandvik (2002) show that cheerfulness
predicts job outcomes differently depending on financial background. Further, these differences were found
with regards to a discrete emotion (cheerfulness) as opposed to evaluating general happiness, which is the
focus of most of the existing research. Additional research is needed to sufficiently explore these areas and
graduate students, especially, are encouraged to look to this as a largely unexplored area for investigation.
Regardless of specific thresholds, domains, or intrapersonal factors involved, it should be noted
here that we are not suggesting overtly deleterious consequences of happiness. Indeed, a robust literature
points to the conclusion that happiness is widely beneficial. We are merely arguing that there may not be a
linear relationship between happiness and its many dividends. Rather, in some cases the very happiest
people may fare slightly less well than do their moderately happy counterparts.
This area of happiness research is especially important in an era of increasing attention to happiness
intervention and policy. As clinicians, coaches, and policymakers offer training programs and allocate
resources to enhance well-being the cautionary note of optimal levels is worth consideration. This is
especially true in the context of mood as information. Lay people ought to be encouraged to promote
happiness when it is contextually appropriate. Too strong an emphasis on the pursuit of happiness or the
experience of happiness when other emotions are more appropriate may, in fact, be deleterious. Further
research on the question of optimal happiness will ultimately lead to more sophisticated, more
individualized, and more effective interventions and policies.
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Affective Ingredients: Recipes for Understanding How Affective
States Alter Cognitive Outcomes
By Karen Gasper & Lauren A. Spencer, The Pennsylvania State University
Citation
Gasper, K., & Spencer, L. A. (2018). Affective ingredients: Recipes for understanding how affective
states alter cognitive outcomes. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt
Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
This chapter provides a guide to help people understand the complex effects that affect, a component of
subjective well-being, might exert on various cognitive processes, including the use of abstract information,
heuristics, stereotypes, and the effect of affect on persuasion and creativity. It reviews a number of
different theories about how affect alters processing and suggests recommendations for future work to
address current knowledge gaps. The key argument within this chapter is that affective states provide
people with information. This information, when relevant, shapes how people think. Much of the research
on this topic has focused on how happy or sad moods might shape processing by providing affective
information. Specifically, happy moods indicate that one should feel safe, which results in people using
more top-down, abstract information processing strategies. Sad moods indicate that one should be wary,
which results in people using more bottom-up, detail-focused strategies. This view is helpful; however, it is
an over-simplification. In particular, affective states are like basic ingredients. Just as the taste of an
ingredient can change from one recipe to another, affective states can provide a range of different types of
information depending on the context. This versatility is highly adaptive, but results in a greater need for
specificity when it comes to understanding how affect alters thought.
Keywords: Affect, Mood, Persuasion, Creativity, Abstraction, Heuristics, Stereotypes
“To have a basic ingredient that can be prepared a million different ways is a beautiful thing.”
~ Chef Alice Waters (as quoted in Baker, 2013)
When it comes to understanding how affect influences thought, people often ponder questions such
as — Are people who feel happy easier to persuade? Does sadness foster creativity? Will anger result in
people relying on derogatory stereotypes? Typically, people desire “yes” or “no” answers, but the truth is
often not that simple. This chapter discusses how everyday affective experiences alter some common
information processing tasks, including persuasion, creativity, and reliance on abstract concepts, heuristics,
and stereotypes. The chapter reviews basic findings, different theoretical explanations for them, and the
debates within the literature. It also provides recommendations for future research, in order to address some
of the knowledge gaps. Throughout this process, we argue that many of the contrasting ideas within the
literature can be resolved by viewing affective states as akin to basic ingredients in a recipe. Follow one
recipe and affect will produce one outcome; but change the recipe, and it might produce another. As Alice
Waters notes in the quote above, this is a beautiful thing – for such ingredients are highly versatile and
functional.
Before discussing how affect influences thought, we want to first discuss what affect is. Affect is a
key component of subjective well-being, in that subjective well-being includes “…specific feelings that
reflect how people are reacting to the events and circumstances in their lives” (Diener et al., 2017, p. 87).
This affective component is comprised of both positive and negative affect (Diener, Lucas, & Oishi, 2002).
Two kinds of affective states are moods and emotions. Moods are diffuse, long-term affective states that
generally have no salient cause; whereas emotions are more specific, short-term affective reactions that
have a specific source (see Beedie, Terry, & Lane, 2005). Two core dimensions of affect are: valence
(positive or negative), which signals whether something is good or bad; and arousal (activated or
deactivated), which signals urgency (Russell, 2003; Storbeck & Clore, 2008). Much of the work on how
affect alters processing centers on how commonly experienced, mild positive/happy and negative/sad
moods alter thought. Given this focus, we will concentrate on this work, occasionally mentioning research
on more specific emotional states when they are relevant.1
Background
Researchers have proposed a range of theories to explain why and how affect alters thought. If
affect is akin to an ingredient, then these different theoretical approaches are akin to different styles of
cooking (e.g., Italian, Mexican, Ethiopian). These theories have different flavors, but often share some core
assumptions about how affect might operate as an ingredient. First, many theories assume that affect alters
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information processing because it provides people with information that is experienced as being relevant to
the task at hand (Schwarz, 2012; Schwarz & Clore, 1983, 2003). Second, if affect is experienced as
irrelevant to the task, then affect exerts no influence. Thus, feelings are not constantly shaping thought.
Third, variations in context can shape the meaning of this affective information (Martin, Ward, Achee, &
Wyer, 1993). In sum, affect is not in every recipe, but when it is relevant to the recipe, the flavor that it
adds will depend on what else is in the mix.
Theories about affect and information processing generally fall into one of three categories. These
categories are theories that focus on affect as (1) interfering with people’s mental capacity, which alters
people’s ability to think about the task, (2) providing a hedonic cue, which alters the extent to which
people feel that they can cope with the affective consequences of the task, and (3) informing the task,
which alters how people think about the task.
Affect: Interfering with Mental Capacity
In the 1980s and 1990s, researchers often argued that affect altered thought because it occupied
working memory, thereby reducing people’s cognitive capacity or mental resources (Ellis & Ashbrook,
1988; Mackie & Worth, 1989; Oaksford, Morris, Grainger, & Williams, 1996). Since then, research has
cast substantial doubt on this idea (Bless, Clore, et al., 1996; Isen, 2001). For instance, positive affect,
which was often thought to reduce capacity (Mackie & Worth, 1989), might not reduce it and could even
enhance it (Gasper & Hackenbracht, 2015; Van Dillen & Koole, 2007; Yang, Yang, & Isen, 2013).
Moreover, as this review will reveal, the effect of affect on thought often is context-dependent, with both
positive and negative affects potentially inhibiting and promoting thought – something that would not
happen if these effects solely were due to capacity deficits. Thus, capacity arguments are akin to a style of
cooking that has gone out of favor.
Affect: Providing a Hedonic Cue
Some theories focus on the idea that affect shapes processing because it signals whether or not one
can handle the affective consequences associated with performing the task. These theories, such as the
hedonic contingency hypothesis (Wegener, Petty, & Smith, 1995) and the mood-as-resource model
(Raghunathan & Trope, 2002) assume that when people perform a task, they might be concerned with how
that task will make them feel. Affective states shape whether people are willing to endure the affective
costs associated with performing the task (e.g., people in happy states might be less likely than those in sad
states to perform a task that could dampen their good mood). The hedonic consequences of doing the task
thus are the chief determinant of how affect will influence performance. Therefore, in this style of cooking,
the concern is whether the outcome will result in too much or too little of a particular type of affective
flavor.
Affect: Informing the Task
According to the affect-as-information approach, affective states provide people with information
about their environments (Schwarz, 2012; Schwarz & Clore, 1983, 2003; see also mood-as-input, Martin et
al., 1993). Happiness and some positive states indicate that the situation is safe and all is well; thus, people
are free to explore and have fun (see Ashby, Isen, & Turken, 1999; Fredrickson, 1998). Sadness and some
negative states indicate that the situation is problematic; thus people should be wary and diligent. Building
on this idea, the mood-as-general-knowledge approach (Bless & Burger, 2017; Bless, Clore, et al., 1996;
Bless, Schwarz, & Kemmelmeier, 1996), the dual force model, (Fiedler, Nickel, Asbeck, & Pagel, 2003;
Fiedler, Renn, & Kareev, 2010) and the cognitive-tuning account (Schwarz, 2012) generally propose that
because happy states signal safety, people in them feel that they can trust generalized knowledge structures
(e.g., schemas, scripts, categorical information, procedural knowledge) as a means to organize and think
about information. Happy states therefore encourage people to assimilate new information into their prior,
generalized knowledge. Conversely, because sad states signal something is problematic, people in them
feel that they should be wary of what they already know and focus on the current situation’s details and
data as a means to solve the problem. Sad states therefore encourage people to accommodate/update what
they already know to adapt to the new information (see: Schwarz & Clore, 2007). This logic often underlies
researchers’ arguments that happy and sad mood states, respectively, promote the following processing
strategies: top-down vs. bottom-up (Bless & Burger, 2017), loose vs. tight (Fiedler, 1988), assimilative vs.
accommodative (Fiedler et al., 2010), global vs. local (Gasper & Clore, 2002), heuristic vs. systematic,
abstract vs. concrete/detailed (Schwarz & Clore, 2007), satisficing vs. optimizing (Kaufmann & Vosburg,
2002), and knowledge driven vs. stimulus driven (Fiedler, et al., 2003). This view differs from the hedonic
view in that affect informs how information is processed rather than shapes the degree to which people
think that they can cope with the affective consequences associated with doing the task.
The hypothesis that happiness promotes reliance on general strategies and sadness promotes
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reliance on detailed strategies is akin to a chef’s go-to style of cooking – it is a theoretical view that is
commonly employed and seems to work well for most occasions. But like all good styles of cooking, other
versions of it have developed, including the motivational dimensional model, the mood-congruent
expectancies approach, and the affect-as-cognitive feedback account. Each of these approaches has a
different take on what type of information affect provides. We will discuss these views, as well as the
hedonic views, in more depth below. In the process, we will review how affect influences various cognitive
outputs, such as the use of abstract information, heuristics, stereotypes, and its effects on persuasion and
creativity.
Cognitive Outputs
Abstract Information
Consistent with the view that happy states promote reliance on abstract/global concepts, numerous
studies indicate that happy moods encourage a focus on the forest (i.e., abstract/global information);
whereas sad moods encourage a focus on the trees (i.e., concrete/local information; Basso, Schefft, Ris, &
Dember, 1996; Curby, Johnson, & Tyson, 2012; Derryberry & Reed, 1998; Johnson, Waugh, &
Fredrickson, 2010; Moriya & Nittono, 2011; Rowe, Hirsh, & Anderson, 2007). For instance, relative to sad
moods, happy moods encourage people to focus on the global shape of an image more so than the local
elements that comprise it (Fredrickson & Branigan, 2005; Gasper, 2004a; Gasper & Clore, 2002). Similar
preferences occur in language use with people in positive moods using more abstract than concrete
language (Beukeboom & Semin, 2006; Forgas, 2011a; Isbell, McCabe, Burns, & Lair, 2013), framing
actions in terms of why (abstract) rather than how (concrete) they were done (Beukeboom & Semin, 2005;
Labroo & Patrick, 2009; Watkins, Moberly, & Moulds, 2011), and focusing on more abstract, idealistic
rather than concrete, pragmatic arguments (Burger & Bless, 2016). Furthermore, these links might be bidirectional,
in that construing action at abstract levels also can lead to positive affect (Freitas, Clark, Kim,
& Levy, 2009).
Valence, however, might not be the sole determinant of these mood effects. According to the
motivational dimensional model of affect , these effects might stem from the motivational qualities of the
affective states (Gable & Harmon-Jones, 2008; Gable & Harmon-Jones, 2010a; Gable & Harmon-Jones,
2010b; Harmon-Jones & Gable, 2009). Affective states vary in the degree to which they are low or high in
motivational intensity. In the motivational dimensional model of affect, affective states that are low in
motivational intensity (affect that does not focus people on obtaining a goal, such as amusement),
regardless of whether they are positive or negative, promote global processing because these states signal
that one is free to explore. In contrast, affective states that are high in motivational intensity (e.g. affect that
focuses people on obtaining a goal, such as desire or fear) promote local processing because they signal
that one should focus on the goal (for a review see: Gable & Harmon-Jones, 2010b). Yet, there is
disagreement concerning this view, in that others argue that motivational intensity might not be key, and
instead one should focus on differences in affective activation to understand how affect alters attentional
scope (Friedman & Förster, 2010, 2011). Regardless of which view one endorses, the key point is that
affective valence, although important, is probably insufficient to capture how affect influences these
processes. This work reveals that a more nuanced approach, which considers the many ways that affect can
inform thoughts, is needed.
The finding that affective states can influence people’s use of abstract information provides a
crucial stepping-stone, in that it helps incorporate affect into a wide number of theories that discuss the
importance of abstraction for both information processing and motivation (see Burgoon, Henderson, &
Markman, 2013; Förster & Dannenberg, 2010; Fujita & Carnevale, 2012). For instance, abstract
information plays a large role in construal level theory, which has implications for prediction, preference,
and action (Trope & Liberman, 2010; for discussion see Bless & Burger, 2017). By establishing these
connections, it becomes apparent that affect could serve as a key ingredient within a wide range of
psychological processes.
Heuristics
Heuristics are rules of thumb that people employ to solve problems. If happy moods promote
reliance on generalized knowledge, then happy moods should increase the use of heuristic reasoning
strategies. Indeed, relative to sad and neutral moods, happy moods promote the use of the following
heuristics: the fundamental attribution error (Forgas, 1998; Stalder & Cook, 2014), the halo effect (Forgas,
2011b; Sinclair, 1988), the ease of retrieval heuristic (Greifeneder & Bless, 2008; Ruder & Bless, 2003),
the conjunction fallacy (Gasper, 1999; but see Jundt & Hinsz, 2002), and the use of processing fluency as
well as other cues as judgmental heuristics (Forgas, 2015; Koch & Forgas, 2012; Wyland & Forgas, 2010).
Happy moods also reduce the degree to which people use systematic strategies. For instance,
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happy moods can decrease reliance on clear, logical decision rules (de Vries, Holland, Corneille, Rondeel,
& Witteman, 2012; Elsbach & Barr, 1999), lessen one’s ability to accurately estimate correlation
coefficients from graphic data (Sinclair & Mark, 1995), reduce reliance on Grice’s principles for
conversations (Koch, Forgas, & Matovic, 2013; Matovic, Koch, & Forgas, 2014), hurt syllogistic reasoning
(Gasper, 1999; Melton, 1995; for exception see Radenhausen & Anker, 1988), and lessen the extent to
which people use theory of mind when making judgments about others’ mental states (Converse, Lin,
Keysar, & Epley, 2008).
These differences in processing strategies also shape how mood alters evaluations of fairness
(Hertel, Neuhof, Theuer, & Kerr, 2000). Sinclair and Mark (1991) proposed that happy moods promote
attention to equality (50/50), whereas sad moods promote attention to equity (you get out what you put in)
because equity is determined by systematically attending to the details. Indeed, when people learned that
they had done 60% of the work, 84% of those in happy moods and 90% of those in neutral moods paid
their partner using the equality norm; whereas only 33% of those in sad moods did so because they
followed an equity norm (Inness, Desmarais, & Day, 2005). This focus on fairness also is evidenced by sad
moods being associated with lower acceptance of unfair offers in the ultimatum game (Chung, Lee, Jung, &
Kim, 2016; Harlé, Chang, van’t Wout, & Sanfey, 2012; Harlé & Sanfey, 2007; Riepl, Mussel, Osinsky, &
Hewig, 2016) and with making fairer offers relative to happy moods (Forgas & Tan, 2013). It should be
noted that others did not find that sadness lowered acceptance of unfair offers, but rather disgust (Moretti &
di Pellegrino, 2010) and anger (Srivastava, Espinoza, & Fedorikhin, 2009) did, presumably because these
emotions signaled a negative view of the unfair offer (see also Harlé & Sanfey, 2010; for a meta-analysis
on affect and justice, see Barsky & Kaplan, 2007).
At first glance, these effects suggest that positive affect might not be ideal, for it encourages the use
of simple, heuristic strategies. This view, however, is a mischaracterization. First, reliance on heuristics
does not always lead to poor decisions. Heuristics generally serve people well and are efficient (Ambady &
Gray, 2002; Baron, 1990). For instance, happy moods promote reliance on small samples, which can be
beneficial because it can lead to faster and more correct decisions (Fiedler et al., 2010). Heuristics also are
a type of mental habit that allows people to devote their attention to other challenges (see Lyubomirsky,
King, & Diener, 2005). Second, not all heuristics are promoted by happy moods. For instance, the
anchoring heuristic occurs when individuals extensively think about the possibility that the anchor is
correct. Research indicates that sad moods encourage people to think about the anchor, thereby increasing
the anchoring bias relative to happy moods (Bodenhausen, Gabriel, & Lineberger, 2000; Englich & Soder,
2009; Estrada, Isen, & Young, 1997; for non-replication see Jundt & Hinsz, 2002). Third, as we will
discuss later, when the situation is important and demands attention, happy moods promote complex
thought (Isen, 2001; Schwarz & Clore, 2007). Thus, it might be best to view this work as indicating that
compared to sadness, happiness promotes greater acceptance of generalized knowledge in relatively benign
situations.
Persuasion
Research on mood and persuasion also suggests that happy moods promote less systematic
processing strategies than sad moods. Numerous studies indicate that respondents in happy moods are less
likely to be influenced by the strength of the persuasive agreements than those in neutral (Mackie & Worth,
1989; Worth & Mackie, 1987) and negative moods (Bless, Bohner, Schwarz, & Strack, 1990; Bless,
Mackie, & Schwarz, 1992; Bohner & Weinerth, 2001; Schwarz, Bless, & Bohner, 1991; Sinclair, Mark, &
Clore, 1994; for meta-analysis see Hullett, 2005). Moreover, when asked to write their own arguments,
respondents in happy moods even produced less persuasive arguments than those in sad moods (Forgas,
2007; Forgas, East, & Chan, 2007). Thus, these data suggest that relative to neutral and sad moods, happy
moods decrease the use of systematic processing strategies.
Yet, it is important to keep in mind that valence alone is not the sole determinant of these effects.
Other characteristics of the state might matter. For instance, happy moods could have these effects because
they signal certainty. Tiedens and Linton (2001) found that certainty emotions (anger, contentment, and
sadness with certainty) resulted in people relying less on the quality of the message than uncertainty
emotions (worry, surprise, and sadness with uncertainty; see also Rydell et al., 2008). If so, affective states
are flexible ingredients, providing a range of information that could alter the processing of persuasive
communications.
Moreover, there are contextual factors that also shape how affective states might provide
information during the persuasion process. First, the effects of affect can depend on people’s motivation
and ability to process the persuasive communication. Research indicates that affect may alter how people
process the message when people possess moderate levels of motivation and ability to pay attention to the
message. However, when people possess either low motivation and ability or high motivation and ability,
721
then affect alters how much people like the message (for reviews see Petty, Fabrigar, & Wegener, 2003;
Petty, Wheeler, & Tormala, 2003). That is, instead of affect altering how people think about the message,
affect alters their evaluation of the message (see Petty, Schumann, Richman, & Strathman, 1993).2 Not all
research supports this view, however (see Albarracín & Kumkale, 2003; Batra & Stayman, 1990; Smith &
Shaffer, 1991), but the findings bring up a critical issue – when does affect alter how a message is
processed vs. how a message is evaluated?
Second, another key element to consider concerns the hedonic implications of the message.
According to the hedonic contingency hypothesis, people in happy moods are motivated to sustain their
positive feelings, resulting in them being uninclined to process mood-threatening messages that might make
them feel bad (Wegener et al., 1995). In contrast, people in sad moods already feel bad. Hence, they are less
concerned about processing mood-threatening messages because these messages would have limited
affective consequences. Indeed, positive affect promotes message scrutiny when messages are hedonically
rewarding (e.g. positive content, likeable source), but not when they are mood-threatening (Sinclair,
Moore, Mark, Soldat, & Lavis, 2010; Turner, Underhill, & Kaid, 2013; Van Kleef, van den Berg, &
Heerdink, 2015; Wegener & Petty, 1994; Wegener et al., 1995; see also Handley & Lassiter, 2002, for
meta-analysis see Hullett, 2005). Similar findings also arise when the message is framed using a more
positive, promotion-focused frame (e.g., attaining positive outcomes) than a more negative, preventionfocused
frame (e.g., avoiding negative outcomes; Baek & Reid, 2013; Van Kleef et al., 2015). Thus, happy
moods can promote message scrutiny as long as doing so is hedonically rewarding and not mood
threatening.
Third, people in happy moods do not always focus on sustaining their mood. According to the moodas-resource
model (Das & Fennis, 2008; Das, Vonkeman, & Hartmann, 2012; Raghunathan & Trope,
2002; Trope, Ferguson, & Raghunathan, 2001), positive moods can operate as a resource that allows people
to better cope with negative, self-relevant information (Lazarus, 1999). Specifically, people in happy states
might be better equipped to cope with negative, self-relevant messages, because they have more positive
affective reserves to draw upon to feel good when receiving negative feedback than those in negative
moods. Consequently, positive moods increase the processing of self-relevant, negative information (Das &
Fennis, 2008; Raghunathan & Trope, 2002). This effect is thought to occur because, when a negative
message is highly self-relevant, the need for accuracy and knowledge can overpower the need to feel
positively about one’s self, thereby encouraging people to more thoroughly process the negative
information.
At first glance, the mood-as-resource model seems to contradict the hedonic contingency
hypothesis. The two views, however, operate under very different contextual situations. The mood-asresource
model predicts that happy states should encourage acquiring negative information because it is
needed; whereas the hedonic contingency hypothesis suggests that happy states might encourage avoiding
negative information when it is not needed. Indeed, Gasper and Zawadzki (2012) found that when help was
needed, positive moods increased seeking out critical information in order to improve; whereas when help
was not needed, negative moods increased seeking out critical information in order to ward off potential
future problems (see also Albarracin & Hart, 2011; Trope & Pomerantz, 1998). Thus, positive affect can be
a highly adaptive ingredient. It focuses people on acquiring negative information when it is needed, but
ignoring it when it is not needed and perhaps mood threatening.
Lastly, mood can also influence persuasion by creating expectancies. According to the moodcongruent
expectancies approach (Ziegler, 2010, 2013, 2014; Ziegler & Diehl, 2011; Ziegler, Schlett, &
Aydinli, 2013; see also work on affective coherence, Huntsinger, 2013b; DeSteno, Petty, Rucker, Wegener,
& Braverman, 2004), one’s mood state creates an expectancy for what should happen. Happy moods
encourage people to expect the world to be a good place; whereas sad moods encourage people to expect it
to be a bad place. When people encounter a message that is congruent with their expectations (e.g., happy
moods and a trustworthy source, sad moods and an untrustworthy source), they are less likely to scrutinize
that message than when they encounter a message that is incongruent with their expectancies (e.g., happy
and untrustworthy source, sad and trustworthy source; Ziegler & Diehl, 2011). Thus, mood still provides
information, but this information shapes what one expects, which in turn alters processing, rather than
mood directly informing how one should process the information.
Clearly, there are many ways that affect can alter persuasion. As in the previous sections,
researchers need to consider carefully how affect informs these processes. They also need to understand the
context. Is the context promoting a moderate desire to process the information? Creating concerns about
sustaining one’s feelings? Activating concerns about learning negative and self-relevant information? Or
altering one’s expectancies? The answers to these questions should help determine how affective
ingredients will influence persuasion.
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Stereotyping
When people rely on a stereotype, they are using a pre-existing knowledge structure (specifically,
information about a group or category) to judge a group member rather than relying on individuating
information. Because positive affect often promotes the use of generalized knowledge structures, it should
promote reliance on stereotypes. Indeed, numerous studies indicate that people in happy moods are more
likely to rely on stereotypes to make judgments than those in neutral or sad moods (e.g., Bless, 2000; Bless,
Clore, et al., 1996; Bless, Schwarz, & Kemmelmeier, 1996; Bless, Schwarz, & Wieland, 1996;
Bodenhausen, 1993; Bodenhausen, Kramer, & Süsser, 1994; Curtis, 2013; Forgas, 2013; Huntsinger,
Sinclair, Dunn, & Clore, 2010; Isbell, 2004; Park & Banaji, 2000; Stroessner & Mackie, 1992). For
example, Bodenhausen, et al., (1994) had participants in positive or neutral moods read an alleged
misconduct case and make judgments of guilt. Half of the participants learned that the person belonged to a
stereotyped group. Participants in a happy mood judged the target as more guilty when the stereotype was
activated than when it was not, but participants in a neutral mood did not differentially judge the target.
Additionally, some negative moods seem to counteract processes associated with stereotyping, for they can
promote concrete thought, accommodation of new information, or a focus on local, individuating, or
behavioral information (e.g., Bless, Schwartz, & Wieland, 1996; Bodenhausen, Kramer, et al., 1994;
Bodenhausen, Sheppard, et al., 1994; Isbell, 2004; Krauth-Gruber & Ric, 2000; Unkelbach, Forgas, &
Denson, 2008).
As noted in the previous sections, affect is a versatile ingredient. These effects might not stem from
the valence of the affective information, but rather from other qualities associated with the affective
information. For example, Tiedens and Linton (2001) argued that people might rely on stereotypes more
when they feel certain rather than uncertain. They found that disgust, a certainty-based emotion, promoted
greater reliance on stereotypes than fear, an uncertainty-based emotion. Similarly, anger, another certaintybased
emotion, also increased reliance on stereotypes compared to sad and neutral moods (Bodenhausen,
Sheppard, et al., 1994).
In addition to considering the information the affect provides, one also needs to consider how the
meaning of that information might be context dependent. For instance, Dasgupta, DeSteno, Williams, and
Hunsinger (2009) found that the effects of anger and disgust on bias depended on whether the out-group’s
stereotype was one that typically aroused anger or disgust. They found that disgust, but not anger, elevated
implicit outgroup bias when the targets were gay (an outgroup that was more associated with disgust than
anger). Moreover, anger, but not disgust, elevated implicit outgroup bias when the targets were Arab (an
outgroup that was more associated with anger than disgust). Thus, emotions provide information about the
degree to which an outgroup is a threat, but only if the emotion is applicable to one’s existing knowledge
about that group. Another example comes from Unkelbach et al. (2008). They asked respondents in happy,
angry, or neutral moods to play a game in which respondents decided whether to shoot an un/armed person;
some targets wore an Islamic headdress. Happy participants exhibited a bias toward selectively shooting
more Muslim targets, and angry participants had an increased tendency to shoot all targets. This finding
suggests that happy moods might promote reliance on stereotypes; whereas anger increases the general
tendency toward aggressive responses. Additionally, it is possible for affective states to shape evaluations
of in/out group members via the mood-congruent expectancies model. Ziegler and Burger (2011), for
example, found that people engaged in more effortful processing when the outgroup’s membership was
incongruent, rather than congruent, with one’s mood-based expectancies. Together, this work underscores
how the characteristics of the task can shape the way in which affective ingredients function.
In addition to examining whether stereotypes are applied, researchers have examined how affect
alters the extent to which respondents perceive groups as being homogenous. Compared to neutral or sad
moods, happy moods often increase perceptions of group homogeneity (Park & Banaji, 2000; Queller,
Mackie, & Stroessner, 1996; Stroessner & Mackie, 1992; Stroessner, Mackie, & Michalsen, 2005). This
finding might occur because positive moods either decrease systematic thought, thereby preventing people
from noticing differences, or because happy moods promote assimilation, which encourages seeing
connections within the group. Indeed, positive moods promote broader inclusion of others into one’s
ingroup (Dovidio, Gaertner, Isen, & Lowrance, 1995; Ensari, Stenstrom, Pedersen, & Miller, 2009; Urada
& Miller, 2000). This inclusion effect is interesting for it suggests that even though happy states might
increasing stereotyping, they also increase the inclusion of others into one’s in-group.
In sum, happy moods generally promote stereotype use, perhaps by conveying that it is fine to rely
on generalized knowledge or by signaling certainty in one’s existing knowledge. Along these lines, anger,
another certainty emotion, also can promote stereotype use, especially with regards to groups that often
spark feelings of anger. Yet, even though happy moods increase reliance on stereotypic knowledge, they
also encourage people to be more inclusive and more likely to assimilate others into one’s group. Thus, an
interesting avenue for future research is to explore when people will rely on stereotypes and when they will
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instead focus on connections and similarities between oneself and others.
Creativity
Numerous researchers have examined whether mood influences creativity (for meta-analyses see
Baas, De Dreu, & Nijstad, 2008; Davis, 2009; Lyubomirsky, et al., 2005). Much of this work indicates that
happy states promote creative thought. The idea being that because happy states encourage a focus on
abstract information, people in them are better able to make higher-order connections and links promoting
novel thought (Ashby et al., 1999; Estrada, Isen, & Young, 1994; Isen, 2001; Isen & Daubman, 1984; Isen,
Niedenthal, & Cantor, 1992). This idea is supported by the broaden and build theory of positive emotions
(Fredrickson, 1998), which argues that positive states might promote creativity because they signal safety,
and hence one is free to play and explore (Friedman, Förster, & Denzler, 2007). Indeed, people in happy
moods tend to perform well on tasks that are interesting and fun (Hirt, Devers, & McCrea, 2008). In
support of these views, three meta-analyses revealed that, compared to neutral moods, experimentally
induced positive moods increase creativity, effect sizes: d = .30 (Baas, De Dreu, & Nijstad, 2008), d = .52
(Davis, 2009), d = .32 (weighted; Lyubomirsky, et al., 2005). Moreover, the link might be bidirectional, in
that creativity and inspiration also promote well-being and happiness (Thrash, Moldovan, Oleynick, &
Maruskin, 2014).
The effect of negative moods on creativity is more complicated. In his meta-analysis, Davis (2009)
concluded that positive moods promote more creativity than negative moods. However, Baas et al., (2008)
concluded that there were no differences between positive and negative moods. Additionally, both metaanalyses
found no significant difference between negative and neutral moods. These null effects could stem
from the fact that research on positive mood often focuses mainly on happy/amused mood states; whereas
research on negative moods often encompasses a wider range of states, such as sadness, fear, anger, and
boredom. These negative states vary dramatically in terms of the types of information they provide, which
could obscure an overall meta-analytic effect.
One promising approach to address the role of affect in creativity is to move beyond valence and
consider other relevant affective elements, such as whether the affective states reflect an approach or
avoidance orientation (Baas et al., 2008; Friedman & Förster, 2010). Approach states, such as excitement,
might foster creativity because they signal that it is safe to explore; whereas avoidance states, such as fear,
might dampen creativity because they signal the need for vigilance, especially when they are high in
activation. Indeed, Baas et al., (2008) found a meta-analytic effect indicating that fear hampered creativity
(r = -.12, 95%CI: -.22 to -.02), and later, Byron and Khazanchi (2011) found meta-analytic effects
indicating that both state (rcorrected = -.028, 95%CI[-.051, -.012]) and trait ( rcorrected = -.166, 95%CI[-.186, .147])
anxiety hindered creativity. Part of the problem Baas et al., (2008) ran into testing the role of
approach/avoidance in creativity is that they could find studies that examined high, but not low, activation
states. Since then, more research has been conducted using low activation states, and it too suggests that
even these states might differentially alter creativity depending on whether they activate approach or
avoidance motivations (Bench & Lench, 2013; Gasper & Middlewood, 2014; Mann & Cadman, 2014;
Middlewood, Gallegos, & Gasper, 2016). Furthermore, a recent meta-analysis on the association between
psychopathology and creativity also supports this view (Baas, Nijstad, Boot, & De Dreu, 2016; but see also
Taylor, 2017). Thus, what makes affect an influential ingredient in the creative process might be whether it
signals approach/avoidance rather than its valence.
In addition to understanding which moods promote creativity, another key question concerns how
they do so. One argument is that the abstract thought promoted by happy moods facilitates connections and
links, encouraging the production of creative ideas (Ashby et al., 1999). Additionally, mood might alter the
likelihood of accepting creative ideas. Affective states that signal caution and vigilance might indicate that
creative ideas or strategies are inappropriate, undesired, or too risky to employ. For instance, individuals in
sad moods are creative when it is clear that creativity is appropriate and desired (Friedman et al.,
2007; Gasper, 2003; Gasper, 2004b; Yamada & Nagai, 2015). Thus, some moods could have detrimental
effects not because they influence the production of creative ideas, but rather because they influence the
acceptance of them (de Vries et al., 2012).
In sum, approach states might promote more creativity than avoidance states, but clearly, more
research needs to be done to confirm this hypothesis. In addition, research would benefit from employing
an approach that considers not only what information the state is providing, but also how that information
might shape the types of processes are involved in various types of creative tasks. That is, just as it matters
in cooking when one adds an ingredient, so too might it matter at what stage of the creative process affect
is operating.
Affect-as-Cognitive Feedback: Everything is Reversible
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There is one last view of how affect alters processing that we want to discuss — the affect-ascognitive
feedback account (also called the cognitive malleability approach, for reviews see Huntsinger,
Isbell, & Clore, 2014; Isbell, Lair, & Rovenpor, 2013; Ray & Huntsinger, 2017). This newer theoretical
perspective argues that happy and sad moods do not directly promote the use of one processing strategy
over the other. Instead, affect provides information that signals whether one should use the accessible
strategy. Happy moods signal all is well and operate like a go-signal, providing information indicating that
it is okay to use whatever strategy is accessible. Sad moods signal that there is a problem and operate like a
stop-signal, providing information that one should be wary of and not use whatever strategy is accessible.
Proponents of this view argue that happy moods have promoted the use of abstract knowledge, heuristics,
and stereotypes not because they promote these strategies per se, but because these global strategies are
typically the accessible, default strategy.
To test this idea, researchers primed various processing strategies (global vs. local, heuristic vs.
systematic) to make one strategy more accessible than another. When global/abstract/heuristic strategies
were accessible, relative to sad moods, happy moods promoted the effects that were typically found in the
literature, such as increased out-group homogeneity effects (Isbell, Lair, & Rovenpor, 2016), greater
attention to global features (Huntsinger et al., 2010, Huntsinger, 2013a), increased use of category
information as a basis for judgment (Hunsinger, Isbell, & Clore, 2012), greater adoption of accessible goals
(Huntsinger & Sinclair, 2010), engaging in more creative thought, greater use of the conjunction fallacy,
but less use of the anchoring heuristic (Huntsinger & Ray, 2016). More importantly, when
detailed/local/systematic process strategies were accessible, ALL of these effects reversed. That is, when
detailed processing strategies were primed, people in happy moods used less global, abstract processing
strategies than those in sad moods did.
This work has at least two interesting implications. First, prior work that found reversals in mood
effects (e.g. happy moods promoting local strategies and sad moods promoting global strategies), which
might seem to contradict current wisdom, could have found these effects because the studies activated
local, rather than global, strategies as a means to complete the task. Second, this work also provides an
interesting explanation for why null results might occur. Specifically, null effects might arise when no clear
processing strategy is accessible, for when this happens, happy and sad moods do not differentially alter
processing (Isbell et al., 2016). Thus, affect might shape the extent to which people use accessible
strategies, and if no strategy is accessible, then affect might not alter information processing.
A key question is whether this view really challenges past work – is it a revolutionary way of
cooking? In the affect-as-cognitive feedback experiments, researchers first prime a processing strategy (e.g.
global vs. local). In doing so, they actually might be activating procedural knowledge about how to perform
the task. According to Bless & Burger (2017), accessible prior knowledge can include procedural
knowledge. Thus, one could argue that these studies are merely changing what type of procedural/prior
knowledge (e.g., global vs. local procedural knowledge) is accessible. Happy moods therefore are still
increasing reliance on prior knowledge; it is just that the priming manipulation changes what kind of prior
knowledge is accessible. If so, it is unclear if affect provides a signal about relying on prior, generalized
knowledge or if it provides a signal about relying on accessible knowledge (as the affect-as-cognitive
feedback account proposes). Regardless of one’s take on this issue, the affect-as-cognitive feedback
account makes the important point that the effect of affect on processing is highly malleable. That is, affect
is a wonderfully flexible ingredient that adapts to the situation, producing a range of outcomes depending
on the how it informs the context.
When the Effects Disappear
Lastly, it is important to keep in mind that all of these effects depend on whether affect is
experienced as providing relevant information. When affect is irrelevant, it should not influence
processing. Greifeneder, Bless, and Pham (2011) provide an excellent review of the factors that determine
when feelings are experienced as relevant to various judgments. Presumably, many of these factors would
apply to understanding when feelings are experienced as relevant to processing, but a systematic review is
needed to confirm this hypothesis. In terms of when affect is irrelevant, research indicates that irrelevance
can be achieved by either (a) altering the perceived source or meaning of the affective cues or (b) changing
the situational or task cues in such a way to override the affective information (Albarracín & Kumkale,
2003; Bless et al., 1990; Bodenhausen, Kramer, & Süsser, 1994; Faraji-Rad & Pham, 2012; Friedman et
al., 2007; Gasper, 2004a; Isbell, McCabe, et al., 2013; Ruder & Bless, 2003; Sinclair et al., 1994; van
Reijmersdal, Lammers, Rozendaal, & Buijzen, 2015). In addition, the intensity of the affective state might
matter. If the affect manipulation is too mild, affective cues might not be noticed and not employed; if
affective cues are too salient, they might be viewed as task-irrelevant and not employed (Bohner &
Weinerth, 2001). Indeed, Davis’s (2009) meta-analysis revealed that mood effects were stronger for
moderately intense affective states compared to mild or very intense states. The mood effects also were
725
stronger when a cover story was present rather than absent, perhaps because a cover story enhanced the
degree to which affect was experienced as task-relevant. These factors are not minor considerations, for if
any of them are present, they can negate whether affective ingredients play a role in shaping thought.
Recommendations for Future Research
Recommendation 1: View Each Affective Ingredient as Providing Multiple Rather than Single
Sources of Information
When research on affect and information processing began, the key focus was on the state’s
valence, but affective states possess other key qualities that can provide information. These include such
factors as the state’s underlying appraisal dimensions (Arnold, 1960; Clore, Ortony, & Foss, 1987; Frijda,
Kuipers, & Ter Schure, 1989; Lazarus, 1991; Moors, 2009; Roseman, Spindel, & Jose, 1990; Smith &
Ellsworth, 1985; Smith, Tong, & Ellsworth, 2014), motivational orientations (e.g., approach/avoidance,
motivational intensity; Fischhoff, Gonzalez, Lerner, & Small, 2012; Gable & Harmon-Jones, 2008; Gasper
& Middlewood, 2014; Lerner, Li, & Weber, 2013; Tiedens & Linton, 2001) arousal/activation level
(Storbeck & Clore, 2008), and intensity (Hackenbracht & Gasper, 2013; Lench & Bench, 2015). In this
chapter, we only scratched the surface through our discussions of how motivational intensity,
approach/avoidance, and differences in certainty might underlie these effects. There are many other ways
that affective ingredients could shape thought. For instance, Griskevicius et al., (2009) used evolutionary
theory to hypothesize that fear would activate self-protection, resulting in one wanting to blend in and not
stand out among others in order to be safe; whereas romance would activate the desire to differentiate
oneself from others, resulting in one wanting to stand out among others in order to attract a mate. Using
this reasoning, they predicted and found that people in fearful moods were more persuaded by messages
about being part of the group; whereas those in romantic moods were more persuaded by messages about
differentiating oneself from others (see also, Griskevicius, Shiota, & Neufeld, 2010; Keltner, Haidt, &
Shiota, 2006; Ng et al., 2017; Sauter, 2010). This example nicely illustrates how other affective elements,
in this case the potential evolutionary functions of affect, might shape the information that affective
provides.
The fact that affect can have so many influences is a beautiful thing, but this versatility also creates
ambiguity concerning what cue is responsible for the effect. Fear, for instance, could signal negativity,
avoidance, uncertainty, a focus on the future, urgency, and need for protection. With so many dimensions
to consider, it becomes very important to delineate which of these possible signals underlies the effect.
Right now, researchers often theorize that if affective state “x” signals “y”, it should result in “z”. They
establish that “x” produces “z”, but often do not adequately test or acknowledge all the possible “y”s. The
field would benefit by trying to establish what piece(s) of information (the potential “y”s) underlie the
effect. It is only with this information that one can know when fear will function more like sadness (a
negative emotion), hope (an uncertainty emotion), or excitement (a high urgency emotion).
Recommendation 2: Consider How Affective States Might Operate in Conjunction with One Another
Researchers should consider how two or more affective states might operate together to alter
information processing. Affect inductions often create more than one state, such as when sad mood
manipulations elevate anxiety or disgust (Westermann, Stahl, & Hesse, 1996). Yet, researchers often
assume that only one state predominates, not taking into account other potential affective influences
(Gasper & Danube, 2016). Multiple affective states can interact with each other to alter thought
(Middlewood et al., 2016). For instance, emotional ambivalence (e.g., experiencing happiness and sadness
at the same time) has been found to benefit problem-solving. Happiness promotes the exploration needed
for creative solutions; whereas sadness promotes the systematic thought needed to evaluate them (George
& Zhou, 2007; Kaufmann & Vosburg, 2002; Moss & Wilson, 2014; Rees, Rothman, Lehavy, & SanchezBurks,
2013; Rothman, Pratt, Rees, & Vogus, 2016; van Harreveld, Nohlen, & Schneider, 2015). Even
though people might simultaneously feel multiple states, research is currently lacking concerning how these
complex states function together to shape thought.
Recommendation 3: Develop Models that Delineate When Affect Would Influence Processing,
Judgment, or Both
Researchers often distinguish between affect altering judgment (evaluations of some object) and
processing (how people think). This review focused on how affect alters processing, but a close
examination of this discussion reveals that sometimes affect might alter these various cognitive outputs via
judgment. For instance, affect might alter how people use a stereotype to process information about a
group-member or it could just alter one’s judgment of the group-member (e.g., I dislike members of group
x). Affect might alter the generation of creative ideas or it might influence the evaluation of the suitability
of those ideas. Affect also might alter how a persuasive message is processed or one’s liking of the
726
message. But when does affect alter processing, judgment, or both? In the persuasion domain, researchers
have begun to address this issue by arguing that affect alters how people process messages when
motivation and ability are moderate and how they judge the messages when motivation and ability are
either both low or high (Petty, Fabrigar, & Wegner, 2003; Petty, Wheeler, & Tormala, 2003). This model,
however, has not always worked, but at least it reflects an attempt to tackle this issue. The field desperately
needs more theorizing that focuses on how the role of affect might change depending on the various stages
and mechanisms that are involved within each of these various domains.
Recommendation 4: Examine to What Extent These Effects Extend to Naturally Arising Affective
States and Traits
Most of the studies reviewed here examined how some type of manipulated affective state altered
various cognitive outcomes. A few studies have examined how naturally arising state and trait affect might
influence these outcomes, especially with regards to the processing of abstract information (Basso et al.,
1996; Derryberry & Reed, 1998; Gable & Harmon-Jones, 2008) and creative thought (for meta-analysis
see: Byron & Khazanchi, 2011). But our literature search revealed very little work examining these affects
with regards to the use of heuristics (for exceptions see; Greifeneder & Bless, 2008, Hilbig, 2008; Riepl et
al., 2016; also work exists looking at justice, see Barsky & Kaplan, 2007), persuasion (for exception see:
DeBono, & McDermott, 1994), and stereotyping. Examining naturally arising state and trait affect is
important, for these states might differ from manipulated affects in terms of the degree to which they seem
relevant and salient – two qualities that could influence whether affect will alter thought (Gasper &
Danube, 2016; Greifeneder et al., 2011). In addition, trait affect might not only alter processing, but also
alter the meaning and relevance of state affect (Gasper & Clore, 1998). For instance, extroverted and
neurotic individuals tend to differ in how much positive and negative affect they experience, and they also
differ in how they view and use the information provided by positive and negative affective states
(Augustine & Larsen, 2011; Rusting, 1999).3 Thus, there is a clear need to consider how naturally arising
state and trait affective influences might operate independently and together to shape the way in which
information is processed.
Recommendation 5: Move Toward Greater Scientific Rigor and Openness
In reviewing this literature, another issue that deserves attention is replicability. There are many
conceptual replications (many researchers doing the same type of work), but not many “exact” replications
(conducting the same study), let alone preregistered replications (registering hypotheses and methods
before conducting the study). The only preregistered replication of mood and processing effects that we
could find was by Domachowska et al., (2016), which replicated the work of Gable and Harmon-Jones
(2008) on how positive affects high in motivational intensity narrow attentional scope. In terms of
judgment, Yap et al. (2016) sought to replicate the effect of mood on judgments of life satisfaction
(Schwarz & Clore, 1983). They found rather small effect sizes relative to the original work. Even though
there are many reasons why a replication study might fail to find an effect, these studies provide
information relevant to determining the strength and scope of these effects, which is needed to understand
the practical significance of these findings.
A related issue is that there is not a lot of work that clearly delineates the overall magnitude of
these effects. With the exception of research on affective influences on creativity, meta-analyses for some
of these effects are scarce and many were conducted prior to the availability of newer techniques to detect
bias. The affect and creativity meta-analyses revealed that the effect size for positive affect on creativity
ranged from d = .30 to .52 (see creativity section). Lench, Flores, and Bench (2011) conducted a metaanalysis
that estimated the effect size of affect on cognition to be Hedges g = .24. This knowledge is
important, for it suggests that many of the experiments on mood and processing might be underpowered. If
a medium effect size is assumed (d = .50), then for an experiment that compares happy vs. sad moods,
assuming 80% power, alpha = .05, two-tailed test, one needs a sample size of 128 people. If the effect size
is closer to d = .25, then the sample increases to 506 people. Many of the studies reviewed here had 20 to
50 participants per cell, resulting in studies that are either somewhat underpowered (if d = .50, then
estimated power is .70 assuming 50 participants per cell) to very underpowered (if d = .25, then estimated
power is only .24). If the original studies are underpowered, then they might be difficult to replicate. Of
course, it is important to keep in mind that because these meta-analyses examined very heterogeneous
samples, the true effect size could be higher or lower depending on the study’s characteristics.
Nevertheless, it would be fruitful if researchers increase their sample sizes, preregister their hypotheses,
and share their data, materials, scripts and laboratory practices given the extent to which individual
differences and contextual cues can shape these effects. In other words, researchers should clearly
document their affective recipes.
Concluding Remarks
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To answer the questions posed in the introductory paragraph: Yes, it might be easier to persuade a
person in a happy mood. No, sad moods do not necessarily foster creativity. And, yes, anger does seem to
increase reliance on derogatory stereotypes. However, the likelihood of finding these effects depends on
the context. Affective states are basic ingredients that can have a wide number of effects. This feature
makes them adaptive, versatile, and highly functional – but also can make their influence tricky to predict.
At this point, researchers have developed some sound basic principles for understanding these effects: (a)
affect provides information, (b) this information must be experienced as relevant to the task, and (c)
individual, situational, and task characteristics can change the meaning of this information. These
principles form a foundational recipe that people can use as a basis for understanding a range of different
ways to approach this work. To move forward, researchers need to refine their affective recipes by asking
questions that better assess and highlight the complex, interactive effects that affective states can have on
information processing.
Footnotes
1This review focuses on the effects of mild, everyday feelings, not on clinical affective reactions (e.g.
depression, mania, etc.). Everyday feelings sometimes produce effects akin to those found in clinical
populations, but sometimes they do not.
2When people think about the message, moods can also influence persuasion by increasing the confidence
people have in their thoughts (Briñol, Petty, & Barden, 2007; Petty, Briñol, & Tormala, 2002).
3In addition, there are many other individual and cultural factors that can shape how affect is experienced
and interpreted, which in turn influences how affect functions (see: Avnet, Pham, & Stephen, 2012; Gasper
& Bramesfeld, 2006; Gasper & Clore, 2000; George & Zhou, 2002; Kashdan, Barrett, & McKnight,
2015; Tamir, 2009; Tamir, Bigman, Rhodes, Salerno, & Schreier, 2014).
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INTERVENTIONS
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Malleability and Intentional Activities
By Kristin Layous, California State University, East Bay
Citation
Layous, K. (2018). Malleability and intentional activities. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
Whether people can sustainably change their level of happiness has been a topic of much debate in the
psychological literature, with some researchers suggesting that happiness change is futile and others
suggesting that it is quite possible, even if challenging. The current chapter reviews the literature on the
major sources of happiness including genetics, life circumstances, and intentional activities, pointing to
evidence of both stability and malleability in happiness over time. Although happiness is stable over time,
evidence suggests that changes in certain life circumstances and the effortful practice of intentional
happiness-increasing activities can shift happiness. Research also suggests that increases in happiness are
not only valuable because they make life more pleasurable, but also because they trigger successful
outcomes in other important life domains (e.g., improved relationships, work, and physical health).
Although research on the potential downsides of over-valuing happiness serves as a warning for the
excessive pursuit of happiness, research on prioritizing positivity paints a healthier version of happinessseekers
who organize their daily lives around opportunities for greater happiness. Finally, intentional
happiness-increasing activities—often called Positive Psychological Interventions—are discussed,
including their mechanisms, moderators, and areas for future research. In sum, the research suggests that
happiness change is possible, but not easy. Through persistent effort directed toward efficacious
interventions, people can intentionally boost their happiness.
Keywords: happiness change, happiness stability, hedonic adaptation, happiness interventions,
positive psychological interventions
Happiness is not something ready-made. It comes from your own actions – His Holiness the 14 th Dalai
Lama of Tibet
It may be that trying to be happier is as futile as trying to be taller and therefore is counterproductive –
Lykken & Tellegen, 1996
The two quotes above represent two schools of thought on the malleability of happiness. The first
quote, from the Dalai Lama, asserts that happiness is a result of people’s actions, providing hope that
happiness is as changeable as behavior. In contrast, the second quote, from two authors of a classic paper
on the genetic basis of happiness, asserts that trying to change people’s happiness is as futile as trying to
change their physical characteristics. A deep dive into the research on the various sources of happiness
(e.g., genetics, life circumstances, intentional activities) provides support for both perspectives. That is,
evidence suggests that happiness can change but that this change requires sustained effort and is difficult to
maintain over time. Nevertheless, the prognosis on the malleability of happiness does not seem quite as
grim as Lykken and Tellegen (1996) presumed. That said, even if people can become happier, questions
remain about whether and how they should pursue this happiness. Thus, recent research has sought not
only to answer the question “can people become happier?” but also “should people pursue happiness?” and,
if so, “how can people effectively increase their happiness?”
Can People Become Happier?
Researchers cite many different types of evidence to answer the larger question of whether
people’s happiness can change. First and foremost, researchers explored whether genetics influence
happiness (i.e., is happiness heritable?). The short answer is yes, but the longer and more nuanced answer is
covered below. Secondly, researchers explored whether life circumstances (e.g., being rich, being male, or
being married) are related to happiness. The resounding conclusion is that these types of circumstances are
related to happiness, but not as much as conventional wisdom might suggest. People tend to adapt to
emotionally evocative situations in their lives such that positive or negative events in people’s lives elicit
less intense positive or negative emotions, respectively over time, making any one event or circumstance
less likely to permanently affect happiness (i.e., hedonic adaptation). Of course, there are variations on this
theme that are discussed below. Even though genetics and life circumstances explain some differences in
happiness across people, they do not explain the total variance, leaving room for other explanations that
might be more under people’s control (i.e., intentional activities).
Genetics
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Most of the evidence pertaining to the genetic influence on happiness comes from behavioral
genetics studies. The most common design is one in which researchers calculate the correlation in
happiness scores between identical (monozygotic) twins reared together (those who share 100% of their
genes) and between fraternal (dizygotic) twins reared together (those who share about 50% of their genes).
If identical twins have a higher correlation in happiness scores than fraternal twins, a genetic influence of
happiness can be inferred (i.e., happiness is considered to be heritable). The twin designs and associated
analyses can be much more complex than the design just described and can yield more detailed
information, but they all rely on comparisons of correlations between twins or siblings who share a certain
amount of genes (see Genetics and Heritability chapters in this Handbook).
Across multiple studies in multiple samples, using multiple different measures of well-being,
researchers have consistently estimated that happiness is about 40 to 50% heritable (e.g., Bartels &
Boomsma, 2009; Røysamb, Tambs, Reichborn-Kjennerud, Neale, & Harris, 2003; Stubbe, Posthuma,
Boomsma, & de Geus, 2005). That is, after correcting for unreliability, about 40 to 50% of individual
differences in happiness across a population are due to genetics. Importantly, heritability is not
deterministic. In one illustrative example, Røysamb, Nes, and Vittersø (2014) calculated difference scores
between identical twins on an 11-point subjective well-being index. The absolute mean difference was
1.28, with 51.4% of twin pairs having at least a one point difference. This indicates that even two people
with an identical genotype can still vary substantially in happiness.
The aforementioned studies measured one’s global level of happiness at one time point and
calculated heritability estimates at that time point. Other studies measured happiness across time, up to 10
years apart and found a strong correlation between individual’s scores from time 1 to time 2 (.50 to .67,
depending on the age of the sample with the older sample being more stable). Across three samples,
researchers found that the stability of happiness (how correlated scores were from time 1 to time 2) was
highly heritable—80% was accounted for by genetics (Lykken & Tellegen, 1996; Nes, Røysamb, Tambs,
Harris, & Reichborn-Kjennerud, 2006). This stability could be interpreted to mean that any short-term
changes in happiness due to life events or intentional activities will be short-lived, as one will return to their
original happiness level over time (i.e., their “set-point”; e.g., Lykken & Tellegen, 1996). Notably,
however, a quarter of people do substantially change in well-being over time (Fujita & Diener, 2005) and,
despite the high genetic influence on the stability that does exist, there are still substantial within-twin-pair
differences across time (Røysamb et al., 2014). For example, Røysamb and colleagues (2014) isolated one
member of an identical twin pair who scored high (above 8.5 on a scale from 0 to 10) at time 1 and at time
2 six years later (showing stably high well-being). The means across this group of twins were 9.25 and
9.22 at time 1 and time 2, respectively. The means for their co-twins were 8.4 and 8.34, respectively. Thus,
at some point, an environmental influence had set these twin pairs on stable yet different well-being paths.
In sum, given the heritability estimates of happiness, there is empirical evidence to support the
contention that some people are born happier than others. That said, this so-called genetic “set-point” is not
deterministic and there are environmental factors or perhaps intentional behaviors that can set people on
different well-being trajectories. For example, Haworth and colleagues (2016) administered a multi-week
positive psychological intervention in a sample of identical and fraternal twins and found that average
well-being across the sample improved even though estimates of genetic effects remained consistent across
time points. Future intervention studies with genetically sensitive designs would continue to illuminate the
interaction effects between genes and environments on happiness.
Life Circumstances
If genetics do not completely predetermine happiness levels, environmental factors are likely at
play. Conventional wisdom may suggest that people who are younger, richer, and more attractive would be
far happier than those who are older, poorer, and uglier. Extensive research has explored how much stable
life circumstances (e.g., income, age, physical attractiveness, or marital status) are related to well-being.
Generally, these life circumstances do not explain as much of the individual differences in happiness as
people might expect—researchers typically find that about 10-15% of individual differences in happiness
are explained by their combined life circumstances (Diener, Suh, Lucas, & Smith, 1999). Notably, the
estimate may depend on what type of well-being is being measured. For example, in a worldwide sample,
24% of the variance in life satisfaction, but only 5% of the variance in affect, was attributable to countrylevel
differences (Tay, Chan, & Diener, 2014; Tay & Diener, 2011). Although people might consider 5 or
10% to be a nominal amount, it is not.
Correlations are difficult to interpret practically, and even small correlations can lead to meaningful
differences in happiness across people (see Rosenthal & Rubin, 1982). For example, the within-country
correlation between personal happiness and personal income is .17 (Lucas & Schimmack, 2009). Although
this may seem small, Lucas and Schimmack (2009) noted that this yields a difference in happiness of about
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0.75 standard deviations between people making $200,000 versus people making $10,000 a year and
people making $200,000 were still at least 0.50 standard deviations happier than those making about
$55,000 (the average income in the sample). Thus, although life circumstances do not explain as much of
the variance in individual differences in happiness as people might expect, that does not mean that they do
not meaningfully relate to happiness. In addition, much of the research is conducted on people who are
meeting basic needs and thus we likely do not have a good estimate of how much changing income from
poverty to subsistence may change someone’s well-being. Indeed, in developing countries with the lowest
incomes, the relationship between income and well-being is higher than it is in developed countries or even
in developing countries with higher incomes, indicating that the lower your income, the more income
increases will matter for your well-being (Howell & Howell, 2008). Likewise, we likely do not have a
good estimate on how much marriage could change the well-being of someone who was utterly lonely
before meeting their life partner. Thus, the effect of life circumstances likely varies across people and
situations.
Another piece of evidence to support the importance of life circumstances in explaining well-being
are consistent between-country differences in happiness ratings. If life circumstances did not matter much
for well-being, researchers would not find such vast differences in well-being between countries like
Denmark (high happiness) and Sierra Leone (low happiness; Diener, Ng, Harter, & Arora, 2010). Indeed,
even after controlling for individual income, societal levels of income predicted happiness in a sample of
132 countries, indicating that there may be something about a nation’s wealth beyond individual prosperity
that contributes to a sense of well-being (Diener et al., 2010). In time-series data, researchers found that
happiness rose in 45 of the 52 countries they studied and these increases were explained by the degree to
which a society allowed free choice (Inglehart, Foa, Peterson, & Welzel, 2008). Over time, countries that
became democratized, developed economically, and increased in social tolerance also showed increases in
their residents’ perceptions of free choice, which in turn fed into increased well-being (Inglehart et al.,
2008).
Notably, estimates of heritability largely come from twin samples within economically stable and
democratic countries (e.g., U.S., Netherlands, England, and Norway), thus do not have the cross-country
variety like Inglehart and colleagues’ (2008) sample included. With less variance in environmental factors
that may affect well-being, heritability (versus environmental) estimates may be over-estimated in these
samples. Similarly, the relative stability in well-being among people over time could be because the
research largely draws from countries in which the types of environmental factors that affect well-being
remain relatively stable. That said, even within the U.S., income inequality is related to lower happiness,
indicating that shifting circumstances within stable countries can also relate to well-being (Oishi, Kesebir,
& Diener, 2011). Specifically, in years with greater income inequality, happiness is lower in the U.S and
these changes are mediated by lower perceptions of fairness and trust in people.
Thus, life circumstances do contribute to well-being. That said, as many researchers have noted,
they do not contribute as much as we might expect. Most researchers explain the relatively low percentage
of the variance attributable to life circumstances as a result of the natural process of adapting to our
environments—hedonic adaptation.
Hedonic Adaptation
Hedonic adaptation is the process by which people adapt to the emotionally salient events or
circumstances in their lives—both negative and positive—such that they do not feel the emotions as
intensely over time as they did when the event or circumstance first occurred (Brickman & Campbell,
1971; Frederick & Loewenstein, 1999; Lyubomirsky, 2011; see also Luhmann & Intelisano, 2017 in this eHandbook
for a comprehensive review of theories and empirical evidence related to hedonic adaptation
and set-point theory). The process of hedonic adaptation is often used to explain why people fluctuate
around a stable level of well-being (i.e., a set-point or set-range; see Diener, Lucas, & Scollon, 2006 for a
review). Although there is evidence that people adapt to life events, there is also evidence that people vary
in the degree to which they adapt, that people vary in their rate of adaptation, and that different events have
different rates of adaptation (Diener et al., 2006; Lucas, Dyrenforth, & Diener, 2008).
The best way to investigate hedonic adaptation is with large panel studies that track individuals,
their life events, and their happiness levels over time. Fortunately, a few such panel studies exist, allowing
for this type of investigation. An oft-cited finding is that people experience a boost to their well-being
when they get married, but then return to pre-event levels of well-being about two years post-marriage
(Lucas, Clark, Georgellis, & Diener, 2003; Yap, Anusic, & Lucas, 2012). Notably, however, Lucas and
colleagues (2003) found substantial variability in adaptation to marriage with some people adapting more
or less quickly than the average two years, and some people never adapting. They concluded that although
on average there was evidence of adaptation to marriage, adaptation should not be viewed as an inevitable
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process as it did not happen for all and rates and trajectories of change varied across people.
Anusic, Yap, and Lucas (2014) offered yet another perspective to the puzzle of hedonic adaptation
in marriage when they compared changes in well-being over time to those who had been married to those
who had never been married. They found an age-related dip in well-being over time in the never-beenmarried
group and noted that marriage actually seemed to slow this dip. Thus, it is possible that the
declines in well-being seen after marriage are not due to hedonic adaptation to marriage, but just normative
age-related declines in well-being during mid-life as responsibilities ramp up.
Although adaptation seems to occur on average to positive events like marriage (see also childbirth;
Dyrdal & Lucas, 2013; Yap et al, 2012; Anusic et al., 2014 and job change; Boswell, Boudreu, & Tichy,
2005), adaptation to negative events is not as complete. Researchers have found that people do not adapt as
quickly or at all to negative events such as widowhood (Lucas et al., 2003; Yap et al., 2012), divorce
(Lucas, 2005), disability (Lucas, 2007), or unemployment (Lucas, Clark, Georgellis, & Diener, 2004; Yap
et al., 2012; but see Anusic et al., 2014 for normative age-related changes comparison). It is evolutionarily
adaptive for negative events to grab people’s attention so that they can address threat and promote survival
and it is likely also adaptive to remember the threat vividly as to avoid it in the future (Baumeister,
Bratslavsky, Finkeneauer, & Vohs, 2001). Thus, adaptation to positive and negative events is asymmetrical
—on average, people are quicker to adapt to positive than negative events.
Because adaptation varies across people and is often incomplete for negative events, there may be
characteristics of the events or how people handle them that could make people less likely to fully adapt to
positive events, therefore extracting greater well-being over time. Although negative events and the
memory of them naturally hold people’s attention, there could be intentional ways in which people forestall
their adaptation to positive events. Sheldon and Lyubomirsky (2012) note that as time passes, positive
events provide fewer positive emotions (see also Lyubomirsky, 2011). At the same time, people’s
aspirations for their lives increase, undermining happiness. In their Hedonic Adaptation Prevention model,
Sheldon and Lyubomirsky (2012) suggest that hedonic adaptation to positive events can be forestalled if
people actively focus on appreciating the positive events or experiences (therefore keeping them at the
forefront of the mind just like negative events are more naturally) and also infusing them with variety so
that positive events and experiences can stay fresh over time. For example, a marriage may cease giving as
much pleasure as the partnership gets more routine and less exciting over time. In addition, people may
come to expect that their partner will do certain things for them (e.g., wash the dishes) and may have
increasing aspirations for what they thing constitutes good partner behavior. The Hedonic Adaptation
Prevention model suggests that people should actively appreciate their partners and put effort into doing
new and exciting things with their partner, just as they would have in the beginning of the relationship.
These activities may slow hedonic adaptation or at least give much needed boosts of positivity into the
relationship along the way, allowing for marriage to be a continual source of well-being.
Intentional Activities
Suggesting ways in which people can intentionally forestall hedonic adaptation leads directly into a
discussion of ways in which people can intentionally increase their happiness in general—not only in
response to a positive life events or experiences. As mentioned before, research suggests that about 50% of
individual differences in happiness are likely due to genetics and about 10-15% are likely due to people’s
life circumstances. As Lyubomirsky, Sheldon, and Schkade (2005) pointed out, this leaves a great deal of
individual differences in happiness unexplained. They suggested that these unexplained differences may be
due to how people respond to the events in their lives and the activities that they choose to engage in.
Although behavior change is not easy by any means, intentional activities meant to boost happiness
provide a more optimistic route to sustained happiness change than genetics and life circumstances.
Furthermore, as noted above, intentional activities could also positively affect the degree to which life
circumstances explains individual differences in happiness, helping people extract more positivity out of
the favorable aspects of their lives. Thus, although the percentages of how each source of happiness affects
well-being (genetics, circumstances, and intentional activities) are not set in stone, the likelihood remains
that at least part of well-being can be alterable via intentional activities. Furthermore, heritability estimates
do not address the possibility that an entire population’s well-being could be raised by societal factors like
free choice or individual intentional happiness practices. I will address more about activities to intentionally
boost happiness later in this chapter, but I would be remiss not to mention them as evidence that happiness
can change. Two meta-analyses of dozens of randomized controlled studies concluded that intentional
activities can increase people’s happiness (Bolier et al., 2013; Sin & Lyubomirsky, 2009) and more
evidence is accumulating each year about what factors make these intentional activities most likely to
improve well-being.
Happiness Can Change Over Time
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Lastly, and perhaps most persuasively, we know that happiness can change over time because it has
changed for some people. Lykken and Tellegen (1996) asserted that they did not think happiness could
sustainably change, but they found that happiness scores in their sample across time were correlated at .50.
Although this is a strong correlation, it accounts for only about a quarter of the variance in happiness scores
over time, leaving room for the interpretation of substantial change. Part of the variance in happiness scores
over time could be attributed to measurement error, but the fact remains that real changes in happiness in
their sample are plausible. Indeed, in a separate study, Fujita and Diener (2005) found that 24% of people in
their sample changed in life satisfaction significantly over 17 years and 9% changed by two standard
deviations or more. One may argue (correctly) that Fujita and Diener’s (2005) findings indicate that over
half of respondents did not change in life satisfaction over the 17 years, providing strong evidence of the
stability of life satisfaction. Although this is true, exploring the lives of the quarter of people who did
change could provide insight into what factors lead to sustainable shifts in happiness. Furthermore, this
sample was not engaged in any sort of intentional practice to shift well-being—they were just going about
their daily lives. Even then, some people showed meaningful change, indicating that it is possible.
Should People Intentionally Pursue Happiness?
The evidence reviewed thus far demonstrates that changing one’s happiness is possible yet
challenging, but the question still remains whether pursuing greater happiness is worth the effort. For
example, are increases in happiness only for their own sake (i.e., greater positivity for the individual
experiencing greater happiness) or might they also stimulate better outcomes in a variety of ways—for
individuals, those close to them, and societies? If increases in happiness were only for greater pleasantness
of an individual’s life, the effort expended by the individual might be deemed selfish by some. However, if
greater happiness caused greater success for the individual in other ways, and better lives for those around
them, then pursuing greater happiness could be seen as a public good. In contrast, another possibility is that
pursuing happiness could undermine well-being by directing attention inward rather than outward to things
that may promote happiness (e.g., relationships or nature). Thus, researchers set out to explore what good
happiness can bring and whether intentional happiness pursuit could be detrimental.
Happiness and Success
The broaden-and-build theory of positive emotions sets out a strong, empirically supported,
argument that positive emotions promote many desirable outcomes beyond simply feeling good
(Fredrickson, 1998, 2001, 2013). As opposed to negative emotions, which are meant to narrow attention to
handle an immediate threat, Fredrickson argues that positive emotions signal to people that they are safe to
explore and expand their horizons. In a positive state, people are free to be curious and engage in
approach-oriented behaviors like meeting new people or learning something new that can potentially affect
their lives positively in the long-term via reciprocal processes (i.e., upward spirals).
Thus, although positive states are fleeting, they broaden people’s thinking and attention, allowing
them to take steps that might build durable cognitive, social, physical, or psychological resources
(Fredrickson, Cohn, Coffey, Pek, & Finkel, 2008). In one empirical test of this process, participants
engaged in a loving-kindness meditation training which boosted positive emotions, which in turn improved
important resources (e.g., mindfulness, social support, physical health; Fredrickson et al., 2008). These
personal resources also predicted greater life satisfaction, which will theoretically feed back into greater
positive emotions over time, setting Fredrickson’s proposed upward spiral into effect. Thus, positive
emotions provide an emotional backdrop that allows people to improve themselves in a variety of ways.
Corroborating the findings from the broaden-and-build theory, a meta-analysis of over 300
findings sought to answer whether happiness leads to success (Lyubomirsky, King, & Diener, 2005; see
also De Neve, Diener, Tay, & Xuereb, 2013). The findings overwhelmingly supported that happiness was
not only related to success cross-sectionally, but also preceded success in longitudinal studies, and caused
success when manipulated in the laboratory. The authors included many different indicators of success
across work, physical health, and social domains, finding that happy people performed better at work (both
in terms of productivity and social relationships), were physically healthier, had better relationships with
others, and were more likely to engage in community service. Collectively, these findings point to
happiness having benefits for the individual beyond simply feeling good, and also benefits for the people
close to them and their communities.
Potential Negative Consequences of Happiness Pursuit
Although successful increases in one’s happiness can hold benefits for the individual and their
community, it is still possible that actively pursuing happiness could be detrimental for some. Research has
demonstrated that people who value happiness may actually be less happy in positive situations because
they are more likely to feel disappointed if a situation does not match their high happiness expectations
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(Mauss, Tamir, Anderson, & Savino, 2011). Indeed, in one study, participants who valued happiness
relatively more, and were under relatively low life stress, reported less happiness than their counterparts
who either did not value happiness as much or did value happiness, but were under relatively higher stress
(Mauss et al., 2011). Furthermore, in a separate paper, Mauss and colleagues (2012) found that the more
people valued happiness, the lonelier they felt. Thus, the authors concluded that valuing happiness can have
some surprisingly negative consequences.
Importantly, Mauss and colleagues’ (2011) measure of valuing happiness does not explicitly
measure the pursuit of happiness, but rather valuing happiness to an extreme degree. Questions include
participants’ level of agreement with statements like “How happy I am at any given moment says a lot
about how worthwhile my life is,” “If I don’t feel happy, maybe there is something wrong with me,” and “I
am concerned about my happiness even when I feel happy.” Thus, their measure of valuing happiness may
be tapping into an unrealistic and possibly pathological valuing of happiness. Indeed, the valuing happiness
scale is related to depression and bipolar disorder (Ford, Mauss, & Gruber, 2015; Ford, Shallcross, Mauss,
Floerke, & Gruber, 2014). In a test of the psychometric properties of the valuing happiness scale,
Luhmann, Necka, Schönbrodt, and Hawkley (2016) found that only two of the items are meaningfully
related to lower well-being: “If I don’t feel happy, maybe there is something wrong with me,” and “I am
concerned about my happiness even when I feel happy.” These items demonstrate a worry about being
unhappy that undermines people’s happiness. Luhmann and colleagues (2016) found that the rest of the
items either did not relate to well-being or related positively, suggesting that only the excessive focus on
happiness or fear of unhappiness is related to lower well-being.
In contrast, Catalino, Algoe, and Fredrickson (2014) created the prioritizing positivity scale which
more directly measures the intentional pursuit of happiness. Specifically, they assess the degree to which
people organize their daily lives around opportunities for positive emotions by asking participants to rate
how much they agree with statements like “A priority for me is experiencing happiness in everyday life,”
“What I decide to do with my time outside of work is influenced by how much I might experience positive
emotions,” and “My major decisions in life (e.g., the job I choose, the house I buy) are influenced by how
much I might experience positive emotions.” This type of prioritizing positivity is related to higher positive
emotions, lower depression, and greater resources like self-compassion and ego-resilience (Catalino et al.,
2014). Importantly, Catalino and colleagues (2014) also explored Mauss and colleagues (2011) valuing
happiness scale and found that, although prioritizing positivity and valuing happiness were related (r = .25),
they had distinct relationships with positive affect, negative affect, and life satisfaction. Specifically, as
mentioned, prioritizing positivity was related to higher well-being and, replicating Mauss and colleagues
(2011) work, valuing happiness was negatively related to well-being.
People Should Pursue Happiness (Thoughtfully)
In sum, organizing your life around increased happiness is not inherently a bad thing (as evidenced
by the prioritizing positivity findings), but if you take it too far, it could have detrimental outcomes (as
evidenced by the valuing happiness findings). Other work supports the idea that the type of intentional
activities people engage in to become happier has implications on whether their happiness pursuit will be
successful. Specifically, if people are going to pursue happiness, they need to do it in ways that feel
authentic to them (i.e., person-activity fit; Lyubomirsky & Layous, 2013). In addition, most of the work on
the intentional pursuit of happiness has included relatively mentally healthy samples (i.e., not clinical
samples) and people who are having more severe issues would likely be better off with the professional
help of a clinician than with a self-guided pursuit of happiness (see Sin & Lyubomirsky, 2009). Lastly, how
happy one may seek to become may depend on their goals. For example, people at the very highest level of
happiness have the most satisfying relationships and engage in the most community service, but those who
are happy, but just below the highest level, are the most successful at work and school and more politically
engaged, suggesting that they need a little room to grow to keep that drive (Oishi, Diener, & Lucas, 2007).
How Can People Effectively Increase Their Happiness?
After Lyubomirsky, Sheldon, and Schkade’s (2005) seminal paper outlining the persuasive
argument that happiness can change, research on happiness interventions exploded. Early pioneers had
already provided some evidence that happiness could change in response to certain activities (Fordyce,
1977, 1983) and gratitude interventions as a path to happiness were just taking off in the literature
(Emmons & McCullough, 2003), but Lyubomirsky and colleagues’ (2005) paper provided the theoretical
basis for research on happiness interventions that helped the field expand. Given the processes of hedonic
adaptation outlined earlier, Lyubomirsky and colleagues (2005) stipulated that the best route to sustained
happiness change would be through intentional and effortful activities rather than changing life
circumstances. Of course the processes of hedonic adaptation can apply to intentional activities as well as
to life circumstances, but intentional activities lend themselves more readily to variety that can help sustain
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positive changes in well-being (Sheldon & Lyubomirsky, 2006).
Positive Psychological Interventions
Positive Psychological Intervention (PPI) is an umbrella term used to describe a treatment method
or activity designed to foster happiness. PPIs can be directed by a therapist or coach in an individual or
group session or self-guided. Lyubomirsky and Layous (2013) have also used the term positive activity
intervention (PAI) to exclusively focus on the self-guided type of PPI or simply “positive activity” to refer
to happiness-increasing activities practiced in daily life (i.e., not as part of a randomized controlled
intervention). Before testing PPIs in randomly controlled interventions, researchers sought to explore the
behaviors of happy people to answer the question—what do happy people do that might reinforce their
happiness? For example, across multiple studies, researchers found that happy people are grateful
(McCullough, Emmons, & Tsang, 2002), prosocial (Krueger, Hicks, & McGue, 2001), and optimistic
(Lucas, Diener, & Suh, 1996). Thus, researchers started designing studies to explore whether the intentional
practice of gratitude (e.g., writing a gratitude letter or counting one’s blessings), prosociality (performing
acts of kindness), or optimism (visualizing one’s best possible self) could boost happiness. Research has
now accumulated to demonstrate that intentionally engaging in the activities of happy people boosts wellbeing
(Bolier et al., 2013; Sin & Lyubomirsky, 2009).
PPIs can be viewed as a type of emotion regulation strategy in which one seeks to upregulate
positive emotions. Thus, Quoidbach, Mïkolajczak, and Gross (2015) wrote a helpful review of positive
interventions, integrating the different types of PPIs with the extant emotional regulation literature by
categorizing them according to the process model of emotion regulation (i.e., into the strategies of situation
selection, situation modification, attentional deployment, cognitive change, and response modulation;
Gross, 1998) and demonstrating how they may be applied before, during, and after positive emotional
events to enhance their effect. In addition, the review covered which PPIs have the most empirical support
and during what time frame, pointing toward areas of opportunity for further research within the field.
How Positive Psychological Interventions Increase Well-Being
As described by the positive activity model (Lyubomirsky & Layous, 2013; see also Layous &
Lyubomirsky, 2014), PPIs increase global well-being via increases in positive emotions, positive thoughts,
positive behaviors, and psychological need satisfaction (i.e., autonomy, competence, and relatedness; Ryan
& Deci, 2000). Although much research is still needed to support these mechanisms, they do have some
preliminary support. For example, a loving-kindness meditation intervention boosted positive emotions,
which in turn improved personal resources such as social relationships and physical health, which in turn
improved life satisfaction (Fredrickson et al., 2008). In another study, people who expressed gratitude and
optimism rated their weekly experiences as more satisfying over time even though independent coders rated
them as consistently satisfying over time (Dickerhoof, 2007). Thus, people engaging in the PPI construed
the events in their lives more positively over time even though they did not objectively change. PPIs can
also stimulate the performance of positive behaviors unrelated to the specific PPI. For example, in one
study, participants assigned to record their blessings (i.e., express gratitude) engaged in more exercise over
time than those assigned to record their hassles (Emmons & McCullough, 2003). Finally, students assigned
to imagine their time as scarce in their college town (a savoring manipulation) reported increases in
psychological need satisfaction, which in turn predicted increases in subjective well-being (Layous, Kurtz,
Chancellor, & Lyubomirsky, 2017). Thus, the positive activity model has preliminary support, but much
research is needed to explore when and under what conditions these interventions may work, as well as
other mechanisms that may be at play.
Moderators of the Success of Positive Psychology Interventions
The positive activity model (Lyubomirsky & Layous, 2013) posits some features of the PPI itself
that may increase its efficacy, some features of the person engaging in the PPI that might make them more
likely to benefit, and finally, the importance of matching the activity to the person (i.e., person-activity fit)
to optimize successful increases in happiness. For example, research has demonstrated that timing and
dosage of a PPI can affect its efficacy (Lyubomirsky, Sheldon, et al., 2005), as can the variety with which
its practiced (Sheldon, Boehm, & Lyubomirsky, 2012), and whether it is other- or self-focused (Nelson,
Layous, Cole, & Lyubomirsky, 2016). For example, participants prompted to perform kind acts for others
or for the world reported higher levels of flourishing than those who were prompted to be kind to
themselves (Nelson et al., 2016).
Research has also revealed that people who are more motivated to engage in PPIs and put more
effort into their practice have greater increases in well-being (e.g., Lyubomirsky, Dickerhoof, Boehm, &
Sheldon, 2011). In one study, people who self-selected into a happiness intervention study reported greater
gains in well-being over the 8-week intervention period than those who self-selected to “test cognitive
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exercises” (Lyubomirsky et al., 2011). These gains were the highest for self-selected participants who were
assigned to the intervention conditions (i.e., gratitude and optimism) versus the control condition indicating
that participants not only need motivation to improve their happiness, but also an appropriate PPI (i.e., a
will and a way; Lyubomirsky et al., 2011; see also Sin & Lyubomirsky, 2009). Lyubomirsky and
colleagues (2011) also found that participants who put more effort into completing the intervention
conditions, but not the control condition, saw greater increases in well-being. Thus, participant motivation
and effort, coupled with the efficacy of the activity, predict greater increases in well-being.
Although studying main effects of certain features of the activity or happiness-seeker on
intervention efficacy provides valuable information, perhaps most importantly, researchers should be
exploring the optimal fit between the activity and the person (i.e., person-activity fit). Indeed, in one study,
people who indicated that they enjoyed the activity, benefitted from it, and did not find it difficult, were
more likely to complete the activity and showed greater boosts in well-being (Schueller, 2010). Similarly,
in one study, people who responded that they liked the exercise, benefitted from it, completed the exercise
as instructed, showed early reactivity (i.e., change in well-being during the one-week intervention period),
and continued to practice the activity post-intervention, were more likely to sustain well-being benefits out
to the 3.5 year follow-up (Proyer, Wellenzohn, Gander, & Rush, 2015). Corroborating this finding, another
study found that people who showed early reactivity to the intervention were more likely to continue
practicing the intervention after the intervention period had ended, which was predictive of sustained
increases in positive emotions at a 15-month follow-up (Cohn & Fredrickson, 2010). These researchers
took their participants’ preference for the activity, early reactivity, and continued practice post-intervention
to be evidence of person-activity fit. In addition, evidence suggests that people show a pattern of
preference toward certain activities (e.g., activities that focus on the present versus the past; Schueller,
2010), and thus researchers may be able to look for these fit patterns and assign PPIs accordingly. Much
research needed regarding this more fine-tuned administration of PPIs, but early evidence suggests that
better matching of person and activity can stimulate long-term rewards in well-being.
Future Directions in Research on Intentional Happiness Pursuit
As PPIs become widely used, it becomes even more important to understand their boundary
conditions, including how to maximize the efficacy of the activity and how to ensure that people are not
engaging in an activity that does not fit them and their needs. For example, some evidence suggests that
specific types of PPIs do not work equally well across cultures. In one study, both gratitude and kindness
activities boosted well-being over the control group when exploring across the U.S. and South Korean
samples. However, the effect of the gratitude condition was moderated by culture such that people in the
U.S. benefited from practicing gratitude, but people in South Korea did not (Layous, Lee, Choi, &
Lyubomirsky, 2013). The researchers reasoned that maybe gratitude was not additionally beneficial for
South Koreans because they had already expressed gratitude and obtained some sort of well-being benefit
or perhaps because the gratitude exercise was a reminder that they had put someone out and perhaps upset
a delicate social harmony that is extremely valued in collectivistic societies. Furthermore, it is quite
possible that the appeal of happiness-increasing activities is a western—or even a U.S.—notion as not all
cultures pursue positivity like people in the U.S. (e.g., Tsai, 2007, but see Diener, 2000). Thus, future
research needs to explore culture-activity fit in the pursuit of person-activity fit and also continue to
explore how actively different cultures intentionally pursue happiness.
Another person-activity fit issue includes whether people with certain levels of well-being might
actually be harmed by practicing PPIs. Evidence suggests that PPIs can decrease depressive symptoms
(Fava & Ruini, 2003; Seligman, Rashid, & Parks, 2006; Sin & Lyubomirsky, 2009), but one study found
that listening to neutral music (a distracter activity) was more effective in decreasing depressive symptoms
than a gratitude letter writing activity among mildly depressed participants (Sin, Della Porta, &
Lyubomirsky, 2011). Importantly, many of the self-guided PPIs have not been tested in clinical samples.
Given that approximately half of happiness-seekers on the internet would qualify as clinically depressed
(Parks, Della Porta, Pierce, Zilca, & Lyubomirsky, 2012), more research needs to investigate whether there
are certain types of activities that could backfire among clinical samples. Likewise, given that most people
are above the midpoint on happiness (Diener, Kanazawa, Suh, & Oishi, 2015), it may be futile for some
people to pursue greater happiness if they are already at the top of the scale. Furthermore, depending on
someone’s goals (e.g., political or career) they may benefit from being slightly less happy than their most
happy peers (e.g., Oishi et al., 2007)
In addition, the sustainability of intentional happiness change needs to continue to be explored. As
researchers in the field of psychology well know, behavior change is difficult and making intentional
behavior change habitual requires great effort and persistence (Lally, van Jaarsveld, Potts, & Wardle, 2010;
Wood & Neal, 2007). Evidence across multiple studies suggests that well-being at a three to six month
follow-up is still significantly higher in the intervention group than the control group (Bolier et al., 2013),
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but few notable exceptions explore a lengthier follow-up (e.g., Cohn & Fredrickson, 2010; Proyer et al.,
2015). Proyer and colleagues (2015) have the longest follow-up of a PPI to my knowledge (3.5 years) and
unfortunately, they did not have enough retained participants in the control group to make betweencondition
comparisons. That said, they were able to explore within-intervention components that sustained
effects (e.g., continued practice, early reactivity, enjoyment of the intervention, and effort) and future
researchers would do well to continue exploring what factors promote sustained happiness after the
inevitable completion of the prescribed intervention period. For example, possibly the happiness
intervention teaches the participant a happiness-enhancing skill (e.g., keeping a gratitude journal), and the
continued practice of that skill is what sustains boosts in well-being (see Kushlev et al., 2017).
Finally, studies are starting to explore how changes in well-being as a result of PPIs affect other
downstream consequences like social relationships, productivity, and physical health (e.g., Fredrickson et
al., 2008; Moskowitz et al., 2017) and more such studies are needed to demonstrate not only that happiness
can be increased, but that increasing happiness has other positive benefits. One example is the Enduring
Happiness and Continued Self-Enhancement (ENHANCE) program, a comprehensive intervention
program that seeks to develop multiple happiness-enhancing skills to boost happiness and, in turn, trigger
positive changes in other domains of life (e.g., relationships and physical health; Kushlev et al., 2017). A
randomized controlled trial of ENHANCE is currently under way and preliminary results are quite
promising regarding ENHANCE’s ability to improve well-being and stimulate other positive benefits.
Conclusion
Borrowing another quote from the Dalai Lama, the research can be summarized as follows:
“Although bringing about inner change is difficult, it is absolutely worthwhile to try” (His Holiness the 14th
Dalai Lama tweeted this on May 30, 2017). As Lykken and Tellegen (1996) noted, it is undoubtedly easier
for people who are born relatively happier than others to engage in behaviors that reinforce their happiness.
That said, over the past two decades, a great deal of evidence has accumulated demonstrating that people
can increase their own happiness through intentional and effortful practices like expressing gratitude and
performing kind acts. Thus, although challenging, increasing one’s happiness is possible and the science of
well-being is continually advancing to offer people more efficacious ways of doing so.
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Physical Activity Interventions: Effects on Well-Being Outcomes
in Older Adults
By Diane K. Ehlers, Elizabeth A. Salerno, Susan Aguiñaga, & Edward McAuley, University of Illinois at
Urbana-Champaign
Citation
Ehlers, D. K., Salerno, E. A., Aguiñaga, S., & McAuley, E. (2018). Physical activity interventions:
Effects on well-being outcomes in older adults. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of
well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
A corpus of literature has documented the benefits of physical activity to well-being and quality of life in
older adults. However, this relationship has frequently been studied in the context of health-related quality
of life (HRQL), as opposed to global quality of life, and in clinical populations. While meta-analyses in this
area provide strong evidence of a positive effect of physical activity on HRQL in these populations,
systematic evidence is lacking in relation to well-being and global quality of life in healthy older adults. A
small number of randomized controlled trials suggest physical activity benefits global quality of life;
however, additional research using the global conceptualization of well-being is needed to confirm these
findings. There is strong evidence, on the other hand, of a positive influence of physical activity on the
proposed antecedents of HRQL and global well-being, including self-related function, or psychological
states (i.e., depression, anxiety, self-esteem, positive affect, self-efficacy), and cognitive function (e.g.,
executive function, working memory) in older adults. Despite this, less is known about the: (1) modes and
doses of physical activity that most effectively improve self-related function, cognitive function, HRQL,
and well-being; (2) mechanisms of change in well-being outcomes due to increased physical activity; and
(3) mediating roles of self-related function, cognitive function, and HRQL in the broader relationship
between physical activity and well-being. In this chapter, we present current evidence of physical activity’s
effects on well-being and its correlates, HRQL, self-related function, and cognitive function. We also
highlight limitations in this evidence base and provide recommendations for future research.
Keywords: Physical activity, subjective well-being, quality of life, older adults
There has been a rapid shift in the demographic landscape of the United States in the last few
decades, a result of adults now living longer than ever before (Vincent & Velkoff, 2010). However, older
adulthood is a period often fraught with the onset of comorbid conditions and disability, which can lead to
impaired well-being and quality of life (QoL; Ward, Schiller, & Goodman, 2012). Defined as an affective
cognitive judgment of one’s satisfaction with life, QoL is a global construct often used interchangeably
with subjective well-being and considered a significant predictor of long-term survival (Diener, Emmons,
Larsen, & Griffin, 1985). Thus, it has become an important priority for researchers and clinicians to
identify low-cost, effective methods of maintaining older adults’ well-being and QoL and to protect against
age-related health decline.
Physical activity may be an effective vehicle for improving well-being and QoL with increased
age. In this chapter we focus on physical activity’s effects on the psychological (e.g., satisfaction with life,
anxiety, esteem, affect, cognition) rather than the physical (e.g., functional performance, activities of daily
living) components of well-being. We also focus on QoL as a global judgement of well-being. However,
the physical activity literature has given limited attention to QoL following this definition. Rather, this
literature has focused primarily on health status, or health-related quality of life (HRQL), while
operationalizing it as QoL (Chou, Hwang, & Wu, 2012; Gillison, Skevington, Sato, Standage, &
Evangelidou, 2009; Motl & Gosney, 2008).
HRQL is a construct derived from behavioral medicine and biomedical science and is comprised
of physical and mental health domains (Ware Jr. & Sherbourne, 1992). It is distinct from well-being and
QoL and considered by some researchers to be a proximal outcome along the pathway between physical
activity and well-being. For example, McAuley and Morris (2007) proposed that physical activity has a
direct impact on self-related function (self-esteem, self-efficacy, affect), cognitive function, and physical
function, which impact HRQL (physical and mental health domains). In turn, improved HRQL directly
influences global QoL (Figure 1). As this follows theoretical suppositions of subjective well-being (Diener,
1984; Rejeski & Mihalko, 2001), our discussion herein is guided by this framework.
A compelling body of evidence has demonstrated the effectiveness of physical activity interventions
for improving health status, reducing negative psychological states (e.g., depression, anxiety), and
754
increasing positive psychological states (e.g., self-esteem; Arent, Landers, & Etnier, 2000; Barbour,
Edenfield, & Blumenthal, 2007; Clarke et al., 2005; Ensari, Greenlee, Motl, & Petruzzello, 2015).
Likewise, a number of studies have identified the efficacy of physical activity interventions for improving
cognitive health (Northey et al., 2017; Smith et al., 2010), a key component of successful aging and wellbeing
in older adults (Diener, 1984; Fiocco & Yaffe, 2010; Lehnert, Sudeck, & Conzelmann, et al., 2012).
Despite this, the final path to well-being and global QoL has rarely been tested in accordance with McAuley
and Morris’s (2007; see Figure 1) hypothesized model. In this chapter we present current evidence relative
to subjective well-being in the context of global QoL and HRQL, self-related function (i.e., psychological
states), and cognitive function; identify strengths and shortcomings (relative to design in particular,
theoretical underpinnings, measurement, mode and dose of activity, potential mechanisms and moderators);
and make recommendations for future research directions.
Figure 1. A conceptual model of the physical activity and quality-of-life relationship*
*Adapted from McAuley and Morris (2007)
Note: Physical function is presented in gray as it is included in the original model proposed by
McAuley and Morris (2007), but is not the focus of this book chapter.
Global Well-Being
A small number of randomized controlled trials (RCTs) have shown that aerobic and non-aerobic
modes of physical activity may improve subjective well-being (Awick et al., 2015, 2017b; Li et al., 2001).
Unfortunately, this limited literature, in addition to inconsistent conceptualizations of well-being, make it
difficult to synthesize findings across studies and conclude whether physical activity interventions improve
well-being in older adults (Rejeski & Mihalko, 2001). As such, meta-analytic studies and systematic
reviews examining older adults’ physical activity and well-being from the global perspective are scarce in
the literature. A further limitation of this evidence is that it has focused primarily on clinical populations,
thus making generalizations to healthy older adults difficult. In this section we discuss: the effects of
physical activity on HRQL; the small body of evidence focusing on global QoL; and future directions to
better understand the influence of physical activity on these constructs in older adults.
Physical Activity and Health-related Quality of Life
755
As noted above, physical activity and HRQL have largely been studied from the perspective of
clinical populations (Chou et al., 2012; Ferrer, Huedo-Medina, Johnson, Ryan, & Pescatello, 2011; Motl &
Gosney, 2008). To the best of our knowledge, only one meta-analysis has focused on healthy populations
and included adults aged 18 to 65+ years (Gillison et al., 2009). Motl and Gosney (2008) observed a small
to moderate effect (d =.34) of short-term (<3 months), aerobic physical activity interventions on HRQL in
individuals with multiple sclerosis (MS). Longer interventions and non-aerobic (i.e., yoga, resistance
training) or combined programs did not yield the same benefits. Ferrer and colleagues (2011) also observed
increases in cancer survivors’ HRQL after participation in aerobic physical activity interventions; however,
they found that studies of longer duration (>6 months) had a greater influence on HRQL, and these
improvements were maintained ~4.5 months after the interventions ended.
Gillison and colleagues (2009) also found that short-term (3-6 months) physical activity
interventions yielded significant, albeit small, improvements in the physical and mental domains of HRQL
in healthy adults, (d = 0.22, 0.21, respectively). Interestingly, the mental domain of HRQL improved more
after engaging in light intensity activity, whereas the physical domain improved only with moderate
intensity activity (Gillison et al., 2009). This suggests the HRQL domains may be differentially impacted
by physical activity intensities. This may be due in part to recruitment of healthy, yet unfit and inactive
individuals who may have perceived light physical activity as more achievable and enjoyable, thereby
improving the mental HRQL domain. While results from these meta-analyses suggest aerobic activity may
be a viable mode for increasing HRQL in clinical and healthy populations, more studies are warranted.
The implications of these findings are restricted by a number of limitations. First, the focus on
clinical populations and HRQL limits broad understanding of physical activity's effects on well-being in
older adults. For example, in the meta-analysis in MS patients by Motl and Gosney (2008), the effect of
physical activity on HRQL was statistically significant when using MS-specific HRQL measures, but nonsignificant
when using broad measures such as the Medical Outcomes Study 36-item Short Form Survey
(Motl & Gosney, 2008; Ware Jr. & Sherbourne, 1992). Moreover, the effect of physical activity on HRQL
and well-being may be greater in clinical populations when compared with the general older adult
population (Ferrer et al., 2011; Gillison et al., 2009). It is also possible that physical activity impacts
clinical populations differently or may work along different underlying pathways. Similarly, HRQL is a
proximal outcome of physical activity and thought to be more of an indicator of health status (Stewart &
King, 1991). As such, more research with a focus on global QoL and well-being in clinical and general
older adult populations may enable us to better quantify the effects of physical activity on subjective well-
being.
Additionally, more details are needed on the intervention characteristics, such as mode, frequency,
intensity, duration, and settings that are most effective for improving HRQL in older adults. The extant
literature suggests shorter interventions and light intensity exercise may have larger effects on HRQL, but
further research should be conducted to confirm these findings. Finally, HRQL domains may be
differentially sensitive to the effects of physical activity (Chou et al., 2012; Gillison et al., 2009); therefore,
research is needed to explain relationships among physical activity, physical and mental HRQL, and global
QoL. A few studies in the older adult literature have aimed to reduce these knowledge gaps (see below);
however, more work in this area is warranted.
Physical Activity and Global Quality of Life
A smaller, yet important body of literature has assessed the impact of physical activity on global
QoL and well-being, using satisfaction with life as the proxy measure. For example, Awick and colleagues
(2015) examined the effects of a walking intervention compared with a stretching/toning control
intervention on satisfaction with life in low-active older adults at mid-intervention (6 months) and postintervention
(12 months). Both groups reported increases in life satisfaction at 6 months; however, the
walking intervention continued to improve their life satisfaction throughout the 12 months, while the
stretching/toning group declined from months 6 to 12. Li and colleagues (2001) also observed a large effect
(d =.93) on satisfaction with life in older adults who participated in a 6-month Tai Chi intervention
compared to a no-treatment control group. Findings from these studies suggest aerobic and non-aerobic
(stretching, toning, alternative exercise) exercise modalities have the capacity to improve subjective wellbeing
in older adults, but aerobic activity may have a greater, long-lasting impact. Notably, participants of
both interventions were generally healthy, suggesting the benefits of physical activity programs to wellbeing
are not restricted to clinical populations or those with compromised HRQL or QoL.
Contrary to these findings, a meta-analysis that included satisfaction with life as an outcome of
QoL reported no significant differences between physical activity groups and controls (Netz, Wu, Becker,
& Tenenbaum, 2005). However, this meta-analysis had several limitations to be considered. For example, a
table of study characteristics was not included, methodological quality was not evaluated, and specific
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measures used to assess global QoL were not reported in the meta-analysis, thus making interpretation of
these findings difficult.
In keeping with the theoretical conceptualization of well-being as a global, distal outcome of
physical activity (Figure 1), researchers have also tested the indirect effect of physical activity. For
instance, in a prospective study of older women, McAuley and colleagues (2008) found that changes in
physical activity were associated with changes in self-efficacy, which was in turn significantly associated
with changes in HRQL. Changes in mental health status were then significantly associated with changes in
satisfaction with life. The authors suggested that lack of findings in the physical health domain may be due
to the observational design, as individuals are more likely to improve physical function (e.g., strength,
flexibility) within the context of an intervention. A cross-sectional study by Mudrak and colleagues (2016)
also found that increased participation in physical activity was associated with greater self-efficacy in 546
older Czech adults. Greater self-efficacy was associated with better HRQL, and HRQL was associated with
higher satisfaction with life. Together, these findings provide support for proposed relationships between
physical activity and global QoL. However, as our interpretations are limited by the study designs
(prospective and cross-sectional), further research in the context of an RCT is needed to test the
directionality and causality of the relationships. Despite this, a robust literature provides strong evidence in
support of physical activity's benefits to proximal outcomes associated with well-being, such as HRQL,
self-related function, and cognitive function.
Self-related Function
A considerable body of literature has highlighted the positive influence of physical activity
interventions on psychological outcomes in older adults, specifically for reducing negative symptomology
(i.e., depression, anxiety) and improving positive psychological states (i.e., esteem, positive affect; Arent
et al., 2000; Barbour et al., 2007; Clarke et al., 2005; Ensari et al., 2015). These effects have remained
relatively consistent across levels of exercise supervision (e.g., center- v. home-based) and mode (e.g.,
aerobic v. non-aerobic). However, the mechanisms underlying physical activity’s influence on these
factors, as well as their concurrent influence on the larger relationship between physical activity and
subjective well-being are still unclear. In this section, we present evidence of the influence of physical
activity on negative and positive psychological states in older adults, including findings related to doseresponse
and mode of exercise.
Negative Psychological States
Negative psychological states are important concerns for older adults and have been consistently
associated with increased risk of morbidity and mortality when left untreated (Blake, Mo, Malik, &
Thomas, 2009). Although McAuley and Morris (2007) defined self-related function in terms of positive
psychological states only, negative affective outcomes are an important component of subjective well-being
(Diener, 1984) and a robust literature provides evidence in support of physical activity interventions for
improving negative psychological symptoms (Arent et al., 2000; Barbour & Blumenthal, 2005; Blake et al.,
2009; Herring et al., 2010; Penedo & Dahn, 2005; Rosenbaum et al., 2011). Barbour and Blumenthal
(2005) reported physical activity to be more effective for reducing depressive symptoms when compared
with wait-list and social contact controls and antidepressant medications. Conn (2010) corroborated these
findings in a meta-analysis and noted that both supervised and unsupervised physical activity interventions
in older adults were comparable in reducing depressive symptoms. The magnitude of physical activity’s
effect on depression across studies was moderate (ds ~0.38).
Exercise interventions have also been shown to reduce anxiety levels in older adults (Arent et al.,
2000; Herring et al., 2010; Penedo & Dahn, 2005). In an update to a previous comprehensive review of the
anxiety-reducing influence of acute and regular exercise (Petruzzello, Landers, & Hatfield, 1991), Ensari
and colleagues (2015) confirmed the small, but significant, beneficial effect of acute bouts of physical
activity on anxiety. Indeed, some of the most robust effects of physical activity on psychological well-being
in older adults have been on anxiety symptoms (Netz et al., 2005). While more recent evidence examining
the influence of regular physical activity on anxiety is needed, the extant literature overall unequivocally
supports a beneficial effect of physical activity on negative affect in older adults. However, as the effects
are not entirely uniform, there are several considerations for maximizing the benefits of physical activity in
future trials. Specifically, further exploration of physical activity dose, mode, and underlying mechanisms
is warranted. This is further discussed later in the chapter in the Future Directions section.
Positive Psychological States
Other important determinants of health in old age are factors associated with positive psychological
states, such as self-esteem, self-efficacy, and positive affect. Self-esteem, one’s affective evaluation of
his/her worth, and self-efficacy, one’s situation-specific self-confidence, are two constructs that have been
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associated with successful aging (Orth, Robins, & Roberts, 2008; Orth, Robins, & Widaman, 2012; Rejeski
& Mihalko, 2001). Although meta-analytic reviews have consistently revealed significant, but small
improvements in self-esteem, self-efficacy, and positive affect with exercise training (ds =.16-.57;
standardized mean difference [SMD] = .50; (Ashford, Edmunds, & French, 2010; Ekeland, Heian, Hagen,
& Coren, 2005; Reed & Buck, 2009; Spence, Mcgannon, & Poon, 2005; Wiese, Kuykendall, & Tay, in
press), most have failed to include individuals over the age of 60. As there is a paucity of systematic
evidence focused on positive psychological states in older adults specifically, we focus here instead on
exemplar RCTs. For example, older adults randomized to a 12-month walking group versus flexibilitytoning-balance
control group reported similar improvements in physical self-worth, a domain of self-esteem
(Gothe et al., 2011). Similarly, Awick and colleagues (2017a) found that a home-based, DVD-delivered
flexibility/toning/balance exercise program helped older adults improve and maintain their physical selfworth
immediately post-intervention (6 months) and after a one year, no-contact follow-up period.
There is a demonstrative body of evidence highlighting the reciprocal relationship between
physical activity and self-efficacy in older adults, such that self-efficacy acts as both a determinant and
outcome of physical activity behavior (Anderson, Winett, Wojcik, & Williams, 2010; Bandura, 1997;
Chase, 2013; McAuley & Blissmer, 2000). As such, self-efficacy has become widely recognized as an
important intervention target in numerous physical activity studies in older adults (Amireault, Godin, &
Vézina-Im, 2013; Heath et al., 2012). In a meta-analysis by Ashford et al. (2010), the largest effects for
increased self-efficacy were evidenced in physical activity interventions that included a greater emphasis on
vicarious experience and performance feedback, making these important considerations for future
interventions. Elavsky and colleagues (2005) reported that, among individuals randomized to a 6-month
exercise intervention, those who remained more physically active at one-year follow-up reported higher
levels of self-efficacy, self-esteem, and positive affect. It should be noted that these effects were maintained
at 5-year follow-up for self-esteem and positive affect, further suggesting that physical activity
interventions can provide long-lasting improvements in positive psychological states responses.
Cognitive Health
Cognition and brain health have increasingly been recognized as important factors of successful
aging and may be considered significant components of older adults’ subjective well-being (Fiocco &
Yaffe, 2010; Kramer & Erickson, 2007; Lehnert et al., 2012; McAuley & Morris, 2007; Rowe & Kahn,
1997). A small number of studies have linked cognition with well-being (Gerstorf, Lövdén, Röcke, Smith,
& Lindenberger, 2007), and several have connected it with well-being correlates, including depression,
anxiety, self-esteem, and self-efficacy (Agroskin, Klackl, Jonas, Downs, & Caspi, 2014; Birch et al., 2016;
McAuley et al., 2011). A large body of research has provided evidence in support of regular physical
activity for slowing cognitive decline, improving brain health and cognitive function with advancing age,
and reducing risk of dementia and Alzheimer’s disease (Bherer, Erickson, & Liu-Ambrose, 2013; Blondell,
Hammersley-Mather, & Veerman, 2014; Colcombe & Kramer, 2003; Smith et al., 2010). While a smaller
number of studies have questioned the overall effectiveness of physical activity for preserving cognitive
function in older adults (Kirk-Sanchez & McGough, 2013; Young, Angevaren, Rusted, & Tabet, 2015),
physical activity is generally accepted as protective against age-related cognitive decline. It is less clear
which dimensions of activity (i.e., frequency, intensity, duration, mode) most effectively ameliorate
cognitive decline, mechanisms by which physical activity influences cognitive function, and the effects of
cognitive function on well-being. In this section, we review evidence of the effects of physical activity on
cognitive function in older adults and emphasize important areas of further scientific investigation.
A number of meta-analyses and systematic reviews have attempted to quantify the effects of
physical activity on cognitive function in older adults, with most focusing on aerobic exercise. In an early
meta-analysis of 18 randomized aerobic exercise trials, Colcombe and Kramer (2003) reported that aerobic
exercise was moderately effective for improving cognitive function in older adults (Hedge’s g = 0.48), and
these benefits were greatest for executive control processes (e.g., cognitive flexibility, inhibition, planning;
g = 0.68). More recent meta-analyses and reviews have corroborated these findings, but suggest aerobic
exercise’s effects on cognitive function may be somewhat smaller. Smith and colleagues (2010) found,
across 29 aerobic interventions in adults aged 18 years and older, that aerobic exercise consistently led to
modest improvements in attention and processing speed (g = 0.16), executive function ( g = 0.12), and
memory (g = 0.13). In the most recent meta-analysis, aerobic exercise (k=18) in adults aged 50 years and
older was associated with improvements in cognition compared with controls (SMD = 0.24; Northey et al.,
2017). Like Smith et al. (2010), the effects were similar across cognitive domains (i.e., attention, executive
function, memory, working memory; SMDs = 0.27-0.36; Northey et al., 2017). Despite these positive
findings, the most recent Cochrane review reported no evidence of an association among aerobic exercise
(compared to non-aerobic exercise or no intervention), cardiorespiratory fitness, and cognitive function in
cognitively intact older adults aged 55 years and older (Young et al., 2015). This is also in contrast to
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previous studies suggesting improvements in cardiorespiratory fitness brought about by increases in aerobic
physical activity may at least partially explain enhancements in cognitive function among older adults
(Erickson et al., 2011; McAuley, Kramer, & Colcombe, 2004).
It is important to note the limitations in this evidence base, particularly in relation to study design,
risk of bias, and poor reporting of methods (Colcombe & Kramer, 2003; Fiocco & Yaffe, 2010; Northey et
al., 2017; Young et al., 2015). In the Cochrane review, Young and colleagues (2015) acknowledged a
preponderance of cross-sectional and observational studies, unclear randomization schemes in RCTs, lack
of participant and trainer blinding to exercise protocols, per-protocol analytic procedures, limited number
of published protocols, poor reporting of attrition, no assessment of contamination bias, and limited
discussion of ceiling effects. These factors may have contributed to the small or null effects observed
across studies.
Although most studies have provided evidence of a positive main effect of aerobic exercise on
cognitive function, results of moderator analyses have been mixed. For example, Colcombe and Kramer
(2003) observed varied relationships with cognitive performance across dimensions of fitness including trial
length and bout duration. Long-term training programs (6+ months; g = 0.67) and bout durations of 31-45
minutes (g = 0.61) were associated with better cognitive performance. Contrary to this, Smith et al. (2010)
and Northey et al. (2017) observed similar cognitive effects across trials of varying lengths (Smith et al.
(2010): range 8-72 weeks; Northey et al. (2017) categorized: 4-12 weeks, 13-26 weeks, >26 weeks).
Additionally, the effect of exercise bout duration on cognitive function followed a quadratic trend in which
only medium duration exercise bouts (i.e., >45 to <60 minutes) led to improvements in cognitive
functioning (Northey et al., 2017).
A growing body of evidence also suggests the cognitive benefits of exercise are not restricted to
aerobic exercise. Combined aerobic exercise + strength training programs, while comprising only a small
number of studies examined by Colcombe and Kramer (2003), had greater effects on cognitive function
when compared with aerobic exercise only (g = 0.59 v. 0.41). The cognitive effects observed by Smith and
colleagues (2010) were evident regardless of training received (i.e., aerobic v. aerobic + strength).
Likewise, Northey and colleagues (2017) observed similar improvements in cognitive function across 41
exercise interventions of different modes (aerobic exercise [SMD = 0.24], resistance training [SMD =
0.29], combined training [SMD = 0.33], tai chi [SMD = 0.52]). Although much additional work is needed,
the evidence to date indicates cognition should be fundamental to the discussion of physical activity’s
effects on subjective well-being in older adults.
Future Directions
The extant literature suggests further research in a number of areas in order to better understand the
roles of physical activity and proximal outcomes, such as psychological health, cognitive health, and
HRQL, in improving subjective well-being in older adults. Research areas of particular interest include
examination of (a) alternate modes of physical activity; (b) dose-response relationships; and (c) the
mechanisms and moderators of change in these outcomes. In this section we detail recommendations for
future research, in addition to practical considerations (e.g., study design) for the examination of physical
activity’s effects on well-being.
Alternate Modes of Physical Activity
Although aerobic exercise interventions comprise the majority of studies included in meta-analyses
and systematic reviews of physical activity’s effects on psychological and cognitive health, results of a
growing number of non-aerobic exercise interventions (e.g., strength and flexibility training, Tai Chi)
suggest examination of alternate modes of physical activity is warranted. For example, meta-analyses have
suggested that resistance-based exercise may result in the largest reductions in depressive and anxiety
symptoms (Arent et al., 2000; Conn, 2010). In the cognitive literature, meta-analyses and RCTs have
observed cognitive benefits of non-aerobic exercise modes similar to those of aerobic exercise (Colcombe
& Kramer, 2003; Northey et al., 2017). For example, Voss and colleagues (2010) observed improvements
in brain functional connectivity and older adults’ performance on executive function tasks after 6 and 12
months of training in a non-aerobic, stretching and toning group.
Interventions targeting positive psychological states also suggest similar effects of aerobic (i.e.,
walking) and resistance training (i.e., toning/flexibility/stretching) programs on self-efficacy and physical
self-worth (Elavsky et al., 2005; Gothe et al., 2011). However, the physical self-esteem subdomains (i.e.,
physical condition, body attractiveness, physical strength esteem) may be differentially influenced by
physical activity modality. Gothe and colleagues (2011) noted that individuals randomized to a
flexibility/toning group reported greater improvements in body attractiveness and physical strength esteem,
likely due to the nature of the program and subsequent improvements in muscular strength. Individuals
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assigned to the walking group reported improvements in the physical condition and strength esteem.
Despite these variations between groups, older adults in both conditions reported improvements in overall
physical self-worth, suggesting various exercise modes may contribute similarly to more global perceptions
of physical self-esteem.
The effects of complementary exercise, such as yoga or Tai Chi, have also increasingly been
explored. Patel, Newstead, and Ferrer (2012) documented greater effects of yoga practice compared with
conventional exercise on mental health status (SMD = 0.65) across 18 studies (N=649 adults aged 60+
years). Although a non-significant effect of yoga was observed for depression (SMD = -0.57), findings
across the studies included in the review were mixed. Elavsky and McAuley (2007) also provided
preliminary evidence that yoga may be effective in enhancing certain aspects of self-esteem in postmenopausal
women. Women assigned to a walking condition reported improvements in physical condition,
strength, and body attractiveness esteem, and women in the yoga group reported improvements in body
attractiveness esteem after the 4-month intervention compared to a control condition. However, no
increases in global self-esteem or physical self-worth were observed in either group.
In in a meta-analysis on cognitive health by Gothe and McAuley (2015), yoga practice led to
improvements in attention, processing speed, executive function, and memory across 15 RCTs (g = 0.33)
and 7 acute bout studies (g = 0.56). Further, effects sizes were similar to those reported in relation to aerobic
exercise (Smith et al., 2010). In older adults specifically, Gothe and colleagues (2014; 2013) observed
greater improvements in working memory and executive function after an acute bout of yoga, compared to
aerobic exercise, and after 8 weeks of yoga practice, compared to a stretching-strengthening control.
Likewise, Eyre and colleagues (2016) observed improvements in brain functional connectivity and
visuospatial memory in a small sample of older adults assigned to 12 weeks of hatha yoga compared to a
memory enhancement training control. Taylor-Piliae and colleagues (2010) also provided evidence
suggesting Tai Chi may lead to greater improvements in cognitive functioning in older adults compared
with aerobic exercise. These findings have been supported by Northey and colleagues (2017) who
observed significant effects of Tai Chi on cognitive function across four studies included in their metaanalysis.
As findings are preliminary and generally diverse, researchers acknowledge that larger,
prospective studies examining the effects of alternative exercise modalities on correlates of subjective wellbeing
in older adults are needed.
Dose-Response
While dose-response relationships of exercise on negative psychological states and cognitive
function have been examined, findings are equivocal. In relation to depression and anxiety, evidence
suggests programs that are shorter in length (i.e., 3-12 weeks) and lower in intensity may have the largest
effects compared with longer programs (i.e., 12+ weeks) and those of moderate and vigorous intensities.
Barbour and Blumenthal (2005) found that in individuals aged 20-45 years, activity at a lower energy
expenditure failed to provide significant reductions in depressive symptoms. However, researchers contend
that older adults may respond differently to physical activity interventions compared to their younger
counterparts (Arent et al., 2000; Herring et al., 2010). Thus, exercise trials of low intensity and short
duration may be leveraged to provide the greatest reductions in negative symptomology in late life. While
it remains unclear as to why shorter and lower intensity programs may elicit larger improvements in older
adults’ negative symptomology, it is possible that adherence is higher (Herring et al., 2010). Studies have
also proposed that improvements may be due to participants being low-fit and previously sedentary,
making low intensity physical activity more enjoyable and a more achievable goal. However, maintenance
of these effects beyond the end of the intervention is unknown. Studies comparing the effects of various
doses of exercise on negative states and including long-term follow-up assessments after program cessation
may reduce these knowledge gaps.
Observational studies have consistently described a dose-response relationship between total
volume of physical activity and cognitive function in older adults (Blondell et al., 2014; Xu et al., 2011).
Fanning and colleagues (2017), using isotemporal substitution models, found that replacing 30 minutes of
sedentary time with 30 minutes of moderate-to-vigorous physical activity resulted in improvements in
performance on working memory and executive function tasks across 247 older adults. However, replacing
sedentary time with light intensity activity did not confer the same cognitive benefits. Meta-analyses have
provided more details on dose-response; however, findings have been mixed and are limited by design
issues across RCTs. Northey and colleagues (2017) provided important evidence in support of the
comprehensive physical activity guidelines including both aerobic exercise and resistance training.
Findings also indicated that exercise sessions of a moderate duration (i.e., >45 to <60 minutes) and
moderate or vigorous intensity may be most beneficial to older adults’ cognitive functioning. Smith and
colleagues (2010), on the other hand, observed positive cognitive outcomes across physical activity
intensity levels. These preliminary and contrasting findings across studies indicate the need for further
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research examining the effects of exercise duration and intensity on older adults’ cognitive functioning.
Moreover, Voss and colleagues (2014) have argued that daily moderate-to-vigorous physical
activity may not offset the negative impacts of prolonged sedentary behavior on brain health and cognitive
function. In this review, the authors provide compelling evidence of a common mechanistic pathway of
cognition between moderate-to-vigorous physical activity and sedentary behavior. Certainly, more research
examining the independent effects of sedentary behavior and interactive effects with light and moderate-tovigorous
physical activity is warranted. The conclusions drawn by Voss and colleagues (2014) suggest that
neither sedentary time replacement nor increased physical activity should be promoted in isolation, but that
combined efforts targeting the entire physical activity spectrum (e.g., light activity, moderate-to-vigorous
physical activity, breaking up sedentary time) may most effectively benefit older adults’ cognitive function.
Findings across these studies indicate a need for additional RCTs investigating how various doses of
physical activity are associated with different levels of cognitive function and, in turn, well-being.
As there has been little investigation of dose-response relationships between physical activity,
positive psychological states, HRQL, and subjective well-being more research in these areas is needed.
Studies have suggested that shorter interventions and light intensity exercise may have larger effects on
HRQL (Gillison et al., 2009; McAuley et al., 2008). Likewise, Martin and colleagues (2009), in one of the
few RCTs to examine the dose-dependent effects of exercise on HRQL, observed greater improvements in
mental health status among participants assigned to the lowest dose of exercise when compared with the
control group. However, more evidence is needed to verify the effects of lower volumes of physical activity
on psychological health and HRQL, as this study also observed increases in physical and mental health
status among participants in the highest dose group (i.e., exceeding physical activity recommendations).
Taken together, the evidence across the literature suggests the effects of various doses of physical activity
may differ across domains of well-being. Studies that aim to identify the physical activity dose or
combination of doses (i.e., intensity + bout duration + mode + trial length) that optimize psychological,
cognitive, and HRQL responses, and thereby subjective well-being, are need to reconcile these differential
effects.
Mechanisms and Moderators
Studies have tested a number of mechanisms thought to explain the effects of physical activity on
psychological states and cognitive function. Cardiorespiratory fitness is arguably the most studied mediator
in older adults, partially due to a focus on aerobic physical activity that predominates the literature (Blake
et al., 2009; McAuley et al., 2004; Prakash, Voss, Erickson, & Kramer, 2015). However, findings suggest
that change in cardiorespiratory fitness is an unlikely mechanism of exercise’s effects on well-being
responses.
Other potential physiological mechanisms of the physical activity—self-related function
relationship include physical activity-induced changes in neurotransmitters of the brain and endogenous
opioids that are known to be associated with depression, anxiety and other mood constructs (Antunes,
Stella, Santos, Bueno, & Mello, 2005; Morgan & O’Connor, 1988). While there is preliminary evidence
for these mediators in younger individuals and within the context of acute physical activity (Antunes et al.,
2005; Brosse, Sheets, Lett, & Blumenthal, 2002; Dinas, Koutedakis, & Flouris, 2011; Janal, Colt, Clark, &
Glusman, 1984), it remains unclear as to how these biomarkers relate to the influence of regular exercise on
psychological health in older adults.
Consistent with the model proposed by McAuley and Morris (2007), there is a body of evidence
that indicators of self-related function may themselves be mediators of the more distal relationship between
physical activity and subjective well-being (Awick et al., 2017b; Elavsky et al., 2005; McAuley et al.,
2006; Mudrak et al., 2016; Rejeski & Mihalko, 2001). Awick and colleagues (2017b) found that previously
sedentary older adults who increased their levels of moderate-to-vigorous physical activity after a 6-month
exercise program reported significant reductions in a latent conceptualization of psychological distress (i.e.,
depression, anxiety, stress, sleep disturbance). Reduced distress was in turn significantly associated with
improvements in satisfaction with life.
In relation to positive psychological states, Arent and colleagues (2000) discussed the use of
physical activity as a mastery experience through which individuals may increase their exercise selfefficacy
which, in turn, may contribute to more effective coping and better mood. Elavsky and colleagues
(2005) reported that increased physical activity was positively associated with physical self-worth, selfefficacy,
and positive affect in older adults 6 months after completing a 6-month physical activity
intervention. Increased self-efficacy and positive affect were, in turn, significantly associated with greater
satisfaction with life. Further, after a 4-year follow-up period (5 years from baseline), increases in physical
activity were related to improvements in physical self-worth and positive affect, and these improvements in
positive affect observed were directly associated with increased satisfaction with life. Importantly, the
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direct effect of physical activity on satisfaction with life was not significant at either time point. Thus,
positive psychological states may at least partially mediate the influence of physical activity on QoL, and
these effects may be maintained years after programs end. In the context of public health, these findings not
only highlight the capacity of exercise interventions for improving a host of negative and positive
components of self-related function, but also suggest these improvements may be at least partially
responsible for lasting improvements in subjective well-being and life satisfaction.
Mechanisms of cognitive change frequently explored include brain volume, brain activity and
connectivity, and neurogenesis (Bherer et al., 2013; Erickson & Kramer, 2008). Specifically, these
mechanisms are: white and gray matter volumes, structural integrity, synaptic plasticity, growth factors
(e.g., brain-derived neurotrophic factor [BDNF], insulin-like growth factor [IGF-1]), brain vasculature,
inflammation, and neuroendocrine function (Voss et al., 2014). For example, Erickson and colleagues
(2011) provided evidence relative to the effects of aerobic exercise and cardiorespiratory fitness on brain
volume, neurogenesis, and cognitive functioning. Hippocampal volumes after a one-year RCT increased in
older adults assigned to a walking program and decreased among those assigned to a stretching control
group. Further, increases in cardiorespiratory fitness (as measured by a maximal graded exercise test) and
serum BDNF were correlated with these increases in hippocampal volume. Although fitness and BDNF
were not associated with participants’ performance on a spatial memory task across the intervention,
increases in hippocampal volume in the walking condition were associated with improvements in
performance on the memory task.
Likewise, Voss and colleagues (2010) observed increased functional connectivity, which, was
correlated with improved executive function in older adults participating in 12-month walking and
stretching/toning programs. While these studies represent some of the few to comprehensively examine
relationships among exercise training, neural mechanisms, and cognitive function, findings represent
correlated change. The literature is rich with studies investigating causal relationships between physical
activity and brain structure and function (Prakash et al., 2015); yet, few have extended Erickson et al.
(2011) and Voss et al.’s (2010) findings using structural tests of mediation of the causal pathway from
exercise training to brain structure and function to cognitive function.
Despite growing knowledge of mediators along the pathway between physical activity and
subjective well-being, less is known about the moderators. In this chapter, we have suggested that
intervention (e.g., program length, activity mode) and population (i.e., healthy v. clinical) characteristics
may modify the effects of physical activity on well-being outcomes in older adults. However, less research
has focused on person-level moderators, such as gender, age, personality, and baseline well-being. Netz
and colleagues (2005) observed greater improvements in well-being in young-old adults (d = 0.20) when
compared with old-old adults (d = 0.11) across 36 studies. As fewer well-being outcomes were tested in
old-old adults (13 v. 159 in young-old), further investigation of physical activity’s effects on well-being in
the oldest old is critical. Although studies have provided evidence of physical activity’s effects on wellbeing
in older women and men separately (McAuley et al., 2008; Vallance, Eurich, Lavallee, & Johnson,
2012), the differential effects of physical activity on well-being by gender are equivocal (Netz et al., 2005).
Research has also shown that personality traits (e.g., neuroticism, extroversion, agreeableness) may predict
satisfaction with life, happiness, negative affect, positive affect, and physical activity (Artese, Ehley, Sutin,
& Terracciano, 2017; DeNeve & Cooper, 1998). Yet, how personality and physical activity may interact in
effecting change in well-being is unknown. We also might expect that individuals with lower levels of wellbeing
or physical activity at the beginning of an exercise intervention may stand to benefit most. For
example, Reed and Buck (2009) reported that improvements in positive affect across 105 aerobic exercise
studies was greatest in individuals with the lowest levels of positive affect at program initiation (d = 0.81
[lowest tertile] v. d = 0.26 [highest tertile]). Similarly, Netz and colleagues (2005) reported greater
increases in well-being in sedentary versus non-sedentary adults (d = 0.35, 0.17, respectively).
Unfortunately, most of these studies have not focused on moderators within older adults specifically even
though aging researchers have stressed that modifying factors, such as baseline perceptions, may be more
important in older adults compared with younger adults (Lehnert et al., 2012).
Other Considerations
In addition to the areas detailed above, there are other practical considerations for research
investigating relationships among physical activity, psychological health, cognition, and well-being. First,
studies suggest a positive relationship between physical activity and global well-being; however, due to a
lack of experimental studies, few meta-analyses and systematic reviews have focused on well-being or
global QoL in older adults. Therefore, more RCTs and reviews are warranted to provide more evidence of
physical activity’s influence on subjective well-being. Future research in this area should be explicit in their
definitions of well-being and QoL, and, as such, carefully consider the measures utilized.
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Similarly, design limitations noted across meta-analyses and reviews in psychological and
cognitive health warrant additional RCTs. For negative psychological states, it has become a challenge for
researchers to design adequate placebo/attentional control groups given that center-based exercise programs
may include other factors that facilitate reductions in negative symptomology (Hawley-Hague et al., 2014;
Hawley-Hague, Horne, Skelton, & Todd, 2015). For example, the level of social support inherent in many
exercise training interventions may be effective in and of itself for improving negative affective responses
(Ehlers et al., 2017; McAuley & Blissmer, 2000); therefore, it will be important to identify the individual
role of physical activity for improving psychological states independent of other psychosocial elements.
While previous research has demonstrated that a home-based (i.e., non-social) physical activity program is
capable of improving positive affect (Awick et al., 2017a), further comparisons of social vs. non-social
programs are warranted.
In relation to cognitive health, RCTs that test the effects of exercise against an active control
condition may be needed to provide more definitive evidence of physical activity’s effects on cognition
(Northey et al., 2017; Young et al., 2015). While some RCTs have observed positive effects of exercise
training compared to an active control (Kramer et al., 1999), Northey and colleagues (2017) found that
exercise training only improved cognitive functioning when compared with education and no contact
control conditions. No differences were observed when exercise was compared with active or social control
conditions. RCTs may also help us to better understand interactions among physical activity, self-related
function, cognition, health status, and well-being in older adults and to expand our knowledge of potential
mediators, as recommended by Etnier, Nowell, Landers, and Sibley (2006).
Further, as subjective well-being is in part a cognitive assessment of one’s life satisfaction (Diener,
Oishi, & Lucas, 2003; Rejeski & Mihalko, 2001), understanding well-being perceptions among older adults
with cognitive impairment or compromised health status represents a significant challenge (Logsdon,
Gibbons, McCurry, & Teri, 2002). Deficits in attention, memory, and communication, in addition to
psychological health symptoms such as depression and anxiety, can affect older adults’ ability to
understand questionnaire items and effectively communicate subjective states (Logsdon et al., 2002). The
development of measures that validly assess well-being in individuals with cognitive impairment and
dementia is needed (Thorgrimsen et al., 2003). Finally, although the temporal order of effects relative to
self-related function and well-being is well-established, the directionality of the association between
cognition and well-being is equivocal. Some studies suggest positive well-being is protective against agerelated
cognitive decline, while others argue the relationship may be reciprocal (Goveas et al., 2016).
Therefore, the question remains—does greater life satisfaction lead to preserved cognitive function with
aging, or does maintained cognitive function lead to greater perceptions of life satisfaction among older
adults? Studies that investigate interactions among demographic (e.g., education, income), clinical (e.g.,
disease states), psychological, and cognitive correlates along the pathway between physical activity and
well-being in older adults may help to answer this question, in addition to others relative to exercise mode,
dose-response, and mediators of change (Chodosh, Kado, Seeman, & Karlamangla, 2007; Goveas et al.,
2016; McAuley & Morris, 2007).
Similarly, evidence has suggested a bidirectional relationship between physical activity and the
psychological, cognitive, and global aspects of well-being. For example, although individuals who are
regularly active may be less likely to report depressive symptoms over time, individuals reporting fewer
depressive and anxiety symptoms may also be more likely to participate in regular physical activity
(Steinmo, Hagger-Johnson, & Shahab, 2014). Moreover, while a robust literature supports exercise in
ameliorating cognitive decline in older adults, McAuley and colleagues (2011) also found that older adults’
baseline self-regulation and executive function were predictive of their adherence to a randomized exercise
trial. Finally, the framework proposed by McAuley and Morris (2007) posits well-being as a distal outcome
of physical activity; yet, empirical studies have suggested that individuals with greater life satisfaction may
also be more likely to engage in health behaviors such as physical activity (Diener & Chan, 2011).
Unfortunately, most studies investigating these reciprocal interactions between physical activity and
subjective well-being have been conducted in the context of observational designs and in younger adult
cohorts. RCTs in older adults are needed to better understand the temporal nature of the relationship
between physical activity and well-being in this population.
Conclusion
The literature on physical activity and QoL, self-related function, and cognition provides a
compelling argument in support of physical activity for improving subjective well-being in older adults.
However, systematic, empirical evidence is lacking. Several factors outlined in this chapter have
contributed to a lack of synthesis in the evidence on well-being in older adults. First, there is a need to
better operationalize well-being and QoL in the context of physical activity interventions, as an array of
definitions and measures have been used when referring to well-being (e.g., HRQL). We further contend
763
that QoL and health status (i.e., HRQL) are distinct constructs and should, therefore, be measured and
interpreted as such.
Next, a robust literature has evidenced the effectiveness of physical activity for improving selfrelated
function and cognitive health, but few studies have linked these outcomes with well-being in older
adults. Studies examining the pathway of changes in physical activity to mediators (e.g., self-related
function and cognitive health) and global QoL in the context of RCTs are needed. The conceptual model
proposed by McAuley and Morris (2007) provides a useful framework for filling this knowledge gap.
Specifically, further scientific investigation in this area may help researchers to (1) define exercise
prescriptions that optimize well-being in older adults; (2) clarify the temporal order of effects along this
path; (3) better understand the mechanisms of change in well-being due to increased physical activity; and
(4) identify for whom and under what conditions subjective well-being is most amenable to physical
activity. Such knowledge may improve the design of interventions, programs, and health policies aimed at
increasing well-being and QoL in older adults.
Both the psychological health and cognition literatures suggest aerobic and non-aerobic exercise
programs may benefit well-being in older adults. The HRQL and psychological health literatures indicate
that lower intensity programs may result in larger improvements in negative and positive psychological
states. Findings within the cognition literature, on the other hand, suggest moderate-to-vigorous intensity
exercise may be needed to elicit meaningful improvements in older adults' cognitive function. Additional
research aimed at identifying the doses of physical activity that most effectively improve self-related
function, cognition, health status, and well-being is needed. This includes further examination of trial
length and type (e.g., home- v. center-based) and activity intensity, mode, and duration. Findings also
suggest that less studied biological mechanisms (e.g., neurotransmitters, brain structure), in addition to
cardiorespiratory fitness, warrant further investigation. Finally, although psychological factors, such as
depression and self-efficacy, are generally accepted as proximal outcomes of physical activity, less is
known about the temporal interaction between cognition and well-being (Goveas et al., 2016).
As medical technologies advance and the population continues to age, it is imperative to preserve
the quality of extended years of life. Physical activity has emerged as an effective and attainable method for
improving a number of important factors associated with well-being. While more research is needed to
improve our understanding of lifestyle behaviors and well-being with advanced age, it is clear physical
activity can be leveraged to improve subjective well-being in older adults.
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Cultivating Subjective Well-Being through Positive Psychological
Interventions
By Bryant M. Stone, Southern Illinois University, Carbondale; Acacia C. Parks, Hiram College
Citation
Stone, B. M., & Parks, A. C. (2018). Cultivating subjective well-being through positive psychological
interventions. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF
Publishers. DOI:nobascholar.com
Abstract
Positive Psychological Interventions are activities that have been demonstrated to cause a positive change
in a population by increasing a positive variable (e.g., optimism). Although these activities come in a
variety of forms and focus on a wide range of positive variables, researchers tend to concentrate their
efforts on seven popular and well-researched categories of PPIs that are as follows: meaning, gratitude,
strengths, savoring, optimism, empathy, and kindness. Collectively, the PPIs in these domains have been
shown to alleviate depressive symptoms, increase pro-social spending and social connectedness, reduce
suicidal ideation, increase subjective well-being or happiness, and many other positive changes across
diverse populations. Still, there are many questions that warrant discussion for future research such as sex
and cultural differences, long-term effects, and antithetical or unexpected reactions to activities. Along with
examining these benefits and critiques of PPIs, we discuss the background and state of replicability for
each domain.
Keywords: Positive Psychological Interventions, Subjective Well-being, Self-Help
The relatively new field of Positive Psychology has produced a great deal of clinically applicable
research through the study of Positive Psychological Interventions (PPIs). In both self-help, research, and
clinical practice, well-researched domains such as gratitude, savoring, and kindness encourage individuals
to shift their focus away from negative experiences, traits, and circumstances towards the positive (Parks &
Biswas-Diener, 2013). The idea of this approach is to strengthen the non-psychopathological qualities of an
individual so that one is less susceptible to future psychopathology, and so that distressing symptoms
become more manageable. PPIs have been designed and tested for those who are suffering from severe
mental or physical ailments (e.g., schizophrenia; cancer), but also for subclinical psychological symptoms
(e.g., mild levels of depression and anxiety; management of chronic conditions) and normally occurring
problems (e.g., bereavement, vocational anxiety, interpersonal conflict). Furthermore, PPIs enhance
individual’s lives that are not experiencing a problem (Seligman & Csikszentmihalyi, 2000). Essentially,
unlike other more traditional psychological interventions (e.g., cognitive-behavioral therapy), PPIs are
designed to benefit anyone who uses them, regardless of one’s mental state or circumstance.
Parks and Biswas-Diener (2013) proposed a set of criteria to determine which interventions fall
under the umbrella of “PPI.” First, the activity must target some positive variable (e.g., positive affect).
Thus, researchers typically design PPIs to serve a function through the targeting of a positive variable. For
example, some PPIs seek to improve happiness among those who are depressed. The second criterion is
that the intervention observably affects that positive variable through experimentation. This second
criterion distinguishes between interventions with an empirical basis and those disseminated without
research vetting (for example, certain self-help books and programs whose “evidence base” comes from
testimonials and public acclaim rather than data). Lastly, there must be empirical evidence that a positive
change in the tested population was caused by a change in the positive variable targeted by the
intervention. For example, if one were to aim to increase hope in employees who hold high-stress jobs,
there must be some evidence that increasing hope actually improves the ability of those employees to
persevere at work, reduce their stress, perform better, and so on.
PPIs designed to increase an individual’s happiness and wellbeing generally fall into seven wellresearched
domains. There are many other areas, such as creativity, courage, patience, and humor (see
Parks & Schueller, 2014 for chapters on these emerging areas and others), which have some research basis,
but less than those featured in this chapter. In no particular order, the well-researched domains are
meaning, gratitude, strengths, savoring, optimism, empathy, and kindness. In this chapter, we examine the
theoretical framework, as well as an overview of the interventions, limitations, and future directions, for
each of these domains with a particular emphasis on their effect on subjective well-being and happiness.
Meaning
Meaning-oriented interventions focus on clarifying an individual's sense of purpose – that which
gives one’s life importance. Research suggests that life is generally pretty meaningful and that having
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meaning may be an important element of good functioning (Heintzelman & King, 2014; Steger, 2012). Due
to the complex nature of the construct, there is debate within the field as to which approach, either
reductionist (e.g., measuring a single “meaning”) or multidimensional (e.g., measuring various aspects that
sum to make “meaning”), is appropriate. Many opt for the multidimensional approach consisting of two
parts; although, many people have broken it down further (Martela & Steger, 2016; Leontiev, 2006; Reker
& Wong, 1988). The first component is purpose, which is the aspirations or goals an individual possesses.
This first component applies to multiple meaning-oriented ideas such as reasons for being in certain
relationships or vocational ambitions. The second part is coherence – one’s comprehension about one’s
life. This second part relates to the consistency one feels when assigning meaning to one’s lives (i.e.,
prescribing circumstances and behaviors to one’s bigger picture). Writing in meaning-oriented activities
promotes this coherence aspect of meaning in life.
As previously mentioned, an individual can find meaning by examining one’s relationships. In
other words, one can find meaning by defining reasons one is in a relationship. Furthermore, one can find
meaning within one’s work life through a calling. A calling is a sense of having a religious purpose or
devotion to one's vocation. The difference between a career and a calling is that when someone possesses a
calling they experience motivation that is spiritual and does not solely come from the desire to earn money
or do a good job. Moreover, Dobrow-Riza & Heller (2015) found in a longitudinal study that individuals
who had a stronger early musical career calling were more likely to perceive their abilities as better, which
resulted in them pursuing musical careers. Perhaps, this sense of direction in one’s career may lead to well-
being.
Consequently, there is evidence to support the claim that there are many psychological benefits to
finding and practicing meaning in life. Duffy & Dik (2013) found that developing an understanding of
one’s calling leads to higher levels of career maturity. Career maturity deals with one’s ability to process
and make difficult vocational decisions. This benefit ultimately leads to better and more fulfilling work
outcomes. In a study done by Bassi, Bacher, Negri, and Delle (2013) a successful and a failing insurance
company were compared in terms of life satisfaction, well-being, and job-meaning scores. Interestingly,
job-meaning scores did not differ between the companies, suggesting that the success of the organization
one works at is independent from one’s vocational purpose. However, those at the thriving company
experienced higher levels of meaning, life satisfaction, environmental mastery, and autonomy at an
organizational level.
An example of a meaning-based PPI is goal-setting (Parks & Layous, 2015). In this activity,
individuals set up goals they plan on achieving along with a timeline of when to accomplish those goals.
This planning strengthens the purpose aspect of finding meaning in life by determining precise motivations
and steps towards progress. Another common meaning-based intervention is reflecting on one’s life as a
whole (e.g. Pennebaker’s writing paradigm; see Niles, Haltom, Mulyenna, Lieberman, & Stanton, 2014 for
a review). This activity can be used to focus on some of the more unexplainable or negative aspects of
one’s life (e.g., getting a divorce) by filling in or explaining the negative or confusing times with meaning.
Still, some argue that having a calling may not be beneficial to one’s subjective well-being. This
antithetical effect may be explained by the distress individuals feel if they do not live up to their calling;
which in some circumstances is probable if one’s career aspirations are particularly unrealistic or
challenging to accomplish. Future research should examine the long-term effects of meaning-based
interventions using longitudinal designs. A majority of studies on meaning-based interventions focus on the
immediate effects or cross-sectional, and thus concurrent, effects instead of the long term. Lastly, gender
differences may explain differences in how individuals feel towards their calling. Researchers should seek
to differentiate the psychological effects and benefits of having a calling between the genders.
Gratitude
The domain of gratitude consists of activities in which an individual exercises one’s appreciation
for the altruistic acts of another individual or individuals. Originally, the sociobiologist Trivers (1971)
proposed that the emotion of gratitude is dependent on the cost to benefit ratio one experiences in a
relationship. He argued that gratitude is a means of regulating the generous acts from the benefactor so that
the natural sensitivity to feeling cheated is controlled. Specifically, he proposed that there is system
between individuals called reciprocal altruism. This concept suggests that there are two types of behaviors
when giving and taking in a relationship. The first type comprises behaviors of altruism and the second
type are behaviors of cheating. He suggests that humans have the tendency to perform both types of
behaviors. If either one of these behaviors significantly exceed the other than an individual who is giving
more may feel that one is being taken advantage of, which adds tension to the relationship. However, other
variables play into controlling this dynamic such as, “friendship, dislike, moralistic aggression, gratitude,
sympathy, trust, suspicion, trustworthiness, aspects of guilt, and some forms of dishonesty and hypocrisy”
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(p. 35). Therefore, gratitude from the individual displaying cheating behaviors may reduce the altruistic
individual’s feelings of being cheated.
More recent studies argue that gratitude plays a more critical and complex role than merely
regulating the cost-benefit ratio between two individuals. Algoe, Haidt, & Gable (2008)’s Find-Bind-andRemind
Theory proposes that gratitude may also be a reaction to the kind acts of another individual; not
just to mediate the relationship. The reaction may occur because acts of altruism stand out in comparison to
other more common social interactions. This theory stands apart from traditional theories because the
duration and intensity of the relationship between the benefactor and the recipient may not affect the
expression of gratitude. This theory recognizes that the experience of gratitude can happen outside of
established relationships, where mediating the give-take ratio would be less important than in established
relationships.
With the role of gratitude for relationship success in mind, one of the most popular gratitude-based
intervention is the gratitude letter exercise. In this activity, individuals write a letter to someone who they
are very grateful for, even though they may have never fully expressed their gratitude to that individual.
When writing the letter for an appropriate amount of time and length, those taking part in this activity
demonstrated an increase in well-being after just ten minutes. Additionally, the benefits of writing a
gratitude letter occur regardless of whether the letter is delivered to its intended recipient (Seligman, Steen,
Park, & Peterson, 2005) or if it remains undelivered (Boehm, Lyubomirsky, & Sheldon, 2011;
Lyubomirsky, Dickerhoof, Boehm, & Sheldon, 2011). Moreover, expressing gratitude is common outside
of relationships where individuals are not necessarily grateful for other individuals rather, they are grateful
for positive circumstances and situations. One can exercise this kind of gratitude through the three good
things activity. In this intervention, individuals write or think about three good things that have happened
to them recently or during that same day. Along with being convenient and easy to do daily, this
intervention can decrease an individual’s negative affect after just two weeks.
Furthermore, gratitude may decrease stress and depressive symptoms while encouraging higher
perceived social support (Wood, Maltby, Gillett, Linley, & Joseph, 2008). This finding supports the idea
that practicing gratitude in clinical settings may be helpful in treating some depressive and anxiety
disorders. Additionally, gratitude promotes prosocial behaviors to strangers more than general positive
affect (Bartlett & Desteno, 2006). These helping behaviors may lead to other benefits typically experienced
from kindness and empathy interventions. In addition, Vieselmeyer, Holguin, and Mezulis (2017) found
that expressing gratitude after a school shooting (Seattle Pacific University) lead to a decrease in posttraumatic
stress symptoms and an increase in post-traumatic growth. This finding suggests that gratitude
may be an effective protective and coping mechanism for trauma-related disorders in clinical settings.
Lastly, Emmons and McCullough (2003) found that gratitude was able to increase one’s subjective wellbeing
on many on numerous psychological and physical measures.
There is some concern in the literature on the effects one’s cultural background has on the potential
benefits of the gratitude interventions. Boehm, Lyubomirsky, & Sheldon (2011) found that Anglo
Americans demonstrated a larger increase in life satisfaction than that of the Asian Americans completing
the same gratitude-based intervention. In addition, Layous, Lee, Choi, and Lyubomirsky (2013) presented
evidence that Koreans may benefit even less from these kinds of interventions. These findings suggest that
one’s cultural values affect the outcome of gratitude interventions. Some have also proposed that certain
depressive styles affect gratitude interventions. According to Sergeant and Mongrain (2011) self-critics
received more benefits from the gratitude intervention than needy individuals. In fact, the gratitude
intervention for needy individuals had a negative impact on their self-esteem.
Future research should examine whether or not gratitude affects one’s social support system. There
is debate as to whether having strong social support creates gratitude in an individual or if gratitude in an
individual causes more people to join one’s social network. Regardless, gratitude may increase perceived
social support (Wood, Maltby, Gillett, Linley, & Joseph, 2008). Lastly, researchers should focus on the role
of gender in the style of expressing gratitude (e.g., are women more likely to express gratitude? Are men
and women more likely to express gratitude to certain individuals?)
Strengths
An essential virtue of PPIs is focusing on the positive instead of the negative. Likewise, focusing
on one’s strengths, instead of one’s weaknesses, is an important area of research for PPIs. Researchers
have separated strengths into two types. The first kind are strengths of character (e.g., empathetic, kind, and
determined), which are qualities individuals possess as character traits or temperament. The second type of
strengths are talents (e.g., good friend or parent, exceptional football player, and natural musicianship)
which are qualities individuals possess as aptitude or skills (Park, Peterson & Seligman, 2004). Strengthbased
PPIs effectively use both types of strengths, although researchers tend to focus more on character
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strengths.
The general structure of strength-based interventions is a strength-based assessment brings
awareness to one’s strengths, and then a counselor or therapist will explore those findings with the client,
although the latter is not necessary. These interventions work by giving an individual feedback and
guidance to use those strengths more often, in a novel manner, or as a means of replacing negative or
harmful behaviors (Parks & Layous, 2015). For example, strengths assessments may reveal that someone is
an exceptionally caring person. One could take this information and try to focus one’s efforts on exercising
one’s caring demeanor by doing more volunteer work or taking care of family and friends through small
acts of kindness. Similarly, a strengths assessment may reveal that one is remarkably good at considering
the different perspectives of others. One may exercise this strength by serving on a college judicial board,
or volunteering to help with evaluating applications hiring in one’s department.
Importantly, using one’s talents and character attributes in a positive or novel manner is associated
with many benefits. A study by Seligman, Steen, Park and Peterson (2005) demonstrated that strengthbased
interventions are effective at increasing happiness and decreasing depressive symptoms after just one
month. These effects remained present for the 6-month follow-up. Moreover, Park, Peterson, and Seligman
(2004) found that certain types of character strengths (e.g., creativity or love of learning) were associated
with higher levels of subjective well-being. Generally, agreeableness and extraversion are positively
associated with life satisfaction. Similarly, character strengths have been found to be a more potent
promoter of resilience than positive affect, self-efficacy, optimism, social support, self-esteem, and life
satisfaction (Martínez-Martí & Ruch, 2017). However, an important caveat to strength-based interventions
is that one must actually use the identified strengths. Seligman et al. (2005) found that the group in which
participant’s strengths were only identified yielded very similar results to the control group. Taking an
assessment and talking about one’s strengths does not yield the same benefits as using those strengths –
particularly in a novel manner.
A potential downfall to using strength-based interventions is that the participants may be inclined to
feel as if the strengths are permanent, and therefore unchangeable (Biswas-Diener, Kashdan, & Minhas,
2011). This can be discouraging to individuals because they may believe that pursuing the strengths serves
no purpose because they are immutable. This defeating idea renders the strength assessment ineffective
because one must actively pursue and believe that they are able to grow the strengths to receive the benefits.
Moreover, there is concern over the inappropriate use of strengths, which may lead individuals into
harmful or dangerous situations. For instance, if some individuals discover they have the strength of “zest,”
they may apply their enthusiasm to maladaptive behaviors, or they may pursue stimulation-seeking or
substances in order to enhance their experience of zest.
One other concern regarding strengths has to do with strengths assessment, which is typically
lengthy and cumbersome. Although many real-world settings use more time-efficient workarounds to
strengths assessment such as a patient-endorsed checklist, research has not demonstrated whether this type
of assessment approach is equally valid. Research should examine the benefits of patient identified
strengths instead of assessment or clinician identified strengths. Some have suggested that there may be
benefits to simply having an individual assess oneself.
Savoring
When individuals choose to savor, they focus on neglected or forgotten details and experiences.
Savoring-based interventions direct individuals to focus on these details (e.g., the intricate tastes of food or
the way the air smells). Researchers divide savoring activities into four types. Sharpening perception
occurs when an individual focuses on sensory experiences, which can involve all of the senses. Memory
building occurs when an individual focuses on significant moments, which may work by inducing an
appreciation of the fleeting nature of the present moment (Kurtz & Lyubomirsky, 2012). Reminiscence
involves savoring non-sensual experiences (e.g., ridding a fun roller coaster in the past). Lastly, the fourth
type of savoring, related to gratitude, involves relishing the healthy aspects of one’s relationships (Borelli
et al., 2014).
There are many other benefits to savoring mentioned in the literature. First, Bryant, Smart, and
King (2005) found that a reminiscing intervention lead to greater levels of positive affect when compared
to the control group after one week post-study. Furthermore, savoring imaginary future positive
experiences (mental time travel) daily for a period of two weeks heightened levels of happiness when
compared to savoring negative or neutral imaginary future experiences (Quoidbach, Wood, & Hansenne,
2009). Some research also suggests that certain aspects of savoring (e.g., mindfulness, reappraisal, &
meaning) can be a potent buffer against stress (Bryant, 2003). Still, naturally savoring events (i.e., outside
of clinical interventions) may be effective. Gentzler, Palmer, and Ramsey (2016) demonstrated that
naturally savoring positive events was associated with a higher perception of one’s ability to savor and an
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increase in subjective well-being.
One of the most popular savoring-based PPIs is a slow and attentive experience of the senses (i.e.,
sharpening perception). This intervention involves consuming a certain food (e.g., a cookie) slowly and
with high levels of focus on the senses. Instead of eating the cookie at a normal rate, an individual
performing this intervention might start by smelling and inspecting the textures of the food before taking a
bite. Black & Areni (2016) demonstrated that this activity can decrease one’s appetite – filling people up
faster with smaller proportions of food. Another activity that uses savoring is focusing on the positive
memories an individual has shared with others. This activity involves a slow and concerted effort to
remember all the details by mentally re-experiencing the memory as if it were happening again. This type
of reminiscing activity may lead to higher overall relationship-satisfaction as well as an increase in positive
affect. This effect was particularly present in those whose baseline overall relationship-satisfaction was
naturally elevated (Borelli, Rasmussen, Burkhart, & Sbarra, 2015).
Future research should examine the role of everyday savoring on the efficacy of reminiscing-based
activities. Essentially, if one habitually savors during any given moment, then one’s recollection of that
moment would be more intense and detailed when compared to someone who was paying less attention.
Optimism
Optimism-based activities focus on developing a positive outlook of the future instead of a negative
one (Scheier & Carver, 1985). One way in which optimism may affect an individual is by creating a desire
to work towards predicted or expected positive outcomes. An important distinction is that optimism and
pessimism may not exist on a continuum to form a unidimensional trait. Segerstrom, Evans, and EisenlohrMoul
(2011) found that optimism and pessimism may be separate constructs; it is possible to be both
optimistic and pessimistic at the same time.
Optimism may also work by assisting an individual in forming a positive coherent life narrative
(different from a meaning-based coherent life narrative, which is not necessarily positive). Some suggest
that optimism creates an illusion of control for an individual in which one feels more secure about one’s
ability to control one’s life. In fact, Alloy and Abramson (1979) found that nondepressed individuals tend
to overestimate the control they have over their lives whereas depressed individuals tend accurately
estimate their control. This finding suggests that optimism may be linked to an overestimation of one’s
control over one’s life, which is an essential component to healthy functioning. Additionally, optimism
may increase positive and healthy self-serving biases in individuals, whereas depression and pessimism
may lead to negative biases (e.g., discounting positive character strengths) (Alloy & Ahrens, 1987).
Arguably, the most notable activity that captures the idea of forming a coherent positive life
narrative is the Best Possible Selves (BPS) activity. In this activity, participants write about a future in
which they fulfill every expectation and aspiration they desire. The benefits of this activity are effective
when completed twenty minutes a day over the course of four days (King, 2001). Another optimism-based
intervention is the Life Summary. In this intervention, individuals write about an ideal future in which
everything turns out as planned – or better. When combined, these interventions focus on creating a
positive coherent life narrative.
A known benefit of optimism-based interventions is an increase in positive affect and positive
future expectations, accompanied by a decrease in negative expectations (Enrique, Bretón-López, Molinari,
Baños, & Botella, 2017). Peters, Flink, Boersma, & Linton (2010) found that less catastrophizing is
associated with a decrease in pain sensitivity and an increase in one’s ability to adjust to painful stimuli.
Moreover, there is an association between high levels of optimism and a faster recovery from serious
surgeries along with a lower likelihood of recurring illnesses (Balck, Lippmann, Jeszen, Klaus-Peter, &
Kirschner, 2016). A proposed explanation for this health-related benefit is that individuals who are high in
optimism tend to address their health concerns in a more constructive way. Furthermore, optimism is likely
to increase one’s desire to protect one’s health, higher levels of engagement and coping, lower levels of
avoidance and disengagement, and better relationships (Carver, Scheier, & Segerstorm, 2010). One can
attribute this finding to optimism’s effects on preparing an individual to expect positive, instead of
negative, outcomes. Lastly, optimism may promote subjective well-being by minimizing the distress an
individual experiences over events and decreasing depressive symptoms (e.g., as measured in women with
postpartum depression) (Carver & Gaines, 1987).
Nonetheless, there is some concern over the malleability of optimism. When examining the
benefits of optimism, one has to consider the difference between state and trait optimism. If some
individuals are predisposed to optimistic thinking, then there is a possibility that those people may not
benefit as much as someone with less dispositional optimism. Likewise, for those less inclined to thinking
optimistically, practicing optimism through interventions may feel less natural. A distinction between the
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effects of state optimism affected by trait optimism (a possible moderator variable) need to be further
addressed in the literature. Second, researchers should further examine the effects and benefits of little
optimism compared to big optimism. Little optimism has to do with fleeting situational attitudes (e.g., “I
am going to make it to work on time!”). Whereas big optimism focuses on large-scale situations (e.g., “The
economy is about to flourish!”). Making an important distinction between these types of optimism could be
beneficial to future research (Peterson, 2000). Lastly, the literature on optimism-based interventions is
lacking in strong longitudinal studies where several interventions occur. As a result, researchers should
focus on the long-term effects of practicing optimism.
Empathy
Empathy-based interventions focus on taking another person’s perspective in order to develop a
deeper understanding of the feelings another is experiencing. There is a consensus that empathy is
multidimensional and composed of both an affective and cognitive component (Decety & Jackson, 2004).
The affective component has to do with the sensitivity one has towards experiencing other’s emotional
states, whereas the cognitive component has to do with the extent to which one is aware of the flexibility
and intricacy of others’ thoughts.
Cultivating empathy is beneficial on both an intimate and a professional level. Arriaga & Rusbault
(1998) demonstrated that accurately taking a partner's perspective during a conflict leads to a better
resolution of that conflict. Additionally, Sadri, Weber, & Gentry (2011) found that, in the workplace,
employers who exercised more empathy were more likely to receive positive evaluations and higher
productivity from employees. Lastly, in the book “Video Interaction Guidance” , authors Kennedy, Landor,
and Todd (2011) explain the benefit of increased well-being from practicing empathy through a
relationship-based intervention. A relationship-based intervention focuses on the quality of an individual’s
relationship with others as a measure and a means of promoting one’s subjective well-being and overall
happiness.
An example of an empathy-based PPI is loving-kindness meditation (LKM). LKM is similar to
mindfulness meditation; however, the focus is on building a strong love for others instead of awareness.
The love practiced in LKM is one that has no conditions and is not restricted to friends and family, but
extends to all living beings. The idea behind LKM is that anyone can practice to attain this particular
idealistic feeling of love for others. Additionally, LKM reliably increases subjective well-being (Galante,
Galante, Bekkers, & Gallacher, 2014; Hofmann, Grossman, & Hinton, 2011; Shonin, Gordon, Compare,
Zangeneh, & Griffiths, 2015). Another empathy-based PPI is self-affirmations – or having empathy for
oneself. Self-affirmations fall into two categories (Armitage & Rowe, 2011). The first is attribute selfaffirmations
which emphasis an individual’s positive attributes and skills. The second type is value selfaffirmations
which emphasize an individual's morals. Both type of self-affirmations may promote positive
behaviors (e.g., increased fruit intake and cessation of indoor tanning) (Fielden, Little, Sillence, & Harris,
2016; Mays & Zhao, 2016) and increase feelings of self-worth (Dijk, Koningbruggen, Ouwererk, &
Wessling, 2011).
Nonetheless, there are concerns within the field that need further investigation on how and when
perspective taking and empathy are not always positive. Hodges, Clark, and Myers (2011) discuss how
perspective taking when in a competitive environment where resources are limited might cause an adverse
reaction for both the empathizer and the target of the empathy. First, when an individual attempts to
empathize with someone considered a competitor, one may use that information to figure out the
individuals plans instead of trying to form a genuine connection. This misuse of empathy could lead to
increased aggression and selfishness if the empathizer finds that the targets perceived plans are threatening
(Caruso, Eply, & Bazerman 2006). Second, when a perceived competitor attempts to empathize with an
individual the actions of the empathizer may seem disingenuous and manipulative which increases mistrust
and competitiveness (Caruso, Epley, & Bazerman, 2007).
Kindness
Kindness interventions aim to promote altruistic behaviors towards others with the intention of
fostering positive emotions in the benefactor. One PPI that promotes kindness is prosocial spending – the
act of spending money to benefit others. Generally, those with more money tend to be happier than those
with less money; however, science on prosocial spending is revealing that how you spend your money also
affects happiness. Still, there are times when spending money on others does not increase happiness. Dunn,
Aknin, and Norton (2008) suggest that three criteria that allow prosocial spending to be beneficial. The first
is relatedness, in which the act of prosocial spending results in a feeling of being close to another
individual. This need satisfies individuals’ desires of acceptance and love from others. The second criterion
is competence, which deals with others knowing that the act of prosocial spending results in some positive
outcome. Essentially, the powerful benefits of prosocial spending are most potent when the benefits to the
775
receiving party are apparent to others. For example, donating to a charity fulfills this requirement well since
there is a clear positive outcome that is universally accepted. Lastly, one must feel autonomous in one’s
actions. The individual cannot feel as if they were coerced or forced to prosocially spend. If one fulfills
these three conditions, prosocial spending may increase happiness and well-being (Dunn, Ashton-James,
Hanson, & Aknin, 2010).
There are other guidelines to ensure that practicing acts of kindness is beneficial. First,
Lyubomirsky, Sheldon, & Schkade (2005) found that the amount of time in between the acts of kindness
affects the benefits to one’s emotional health and well-being. When participants performed single acts of
kindness once a day across a week, the benefits were not as strong as when participants performed five
acts of kindness in a single day. These activities have little to do with the behavior itself, rather, the
reflection of the behavior post-act (Parks & Biswas-Diener, 2013). Additionally, the acts of kindness must
have an element of novelty involved. For example, an individual who always holds the door for others
would not significantly benefit from holding the door for several people in a single day. However, if an
individual who does not hold the door for others suddenly held the door open for everyone they encounter
in a single day, they would experience the benefits of acts of kindness to well-being more intensely than the
former individual.
Acts of altruism may increase both the giver and receiver’s well-being. Pressman, Kraft, and Cross
(2014) concluded that acts of altruism were responsible for a significant increase in positive affect and a
decrease in negative affect among the givers in their study. Moreover, Windsor, Anstey, & Rogers (2008)
found an inverted U shape between hours spent volunteering and life satisfaction. Individuals who spent
little and too much time volunteering reported similar low levels of well-being. Whereas, individual who
reported a moderate amount of time volunteering reported the highest levels of well-being. Lastly, a study
by Schwartz, Keyl, Marcum, and Bode (2009) found that helping others within a person’s family was
associated with benefits to health and subjective well-being.
Nonetheless, there is argument within the field over the need for authenticity when helping others
and how the motivation affects the benefits. Future research should examine if having intrinsic motivation
is more potent than extrinsic motivation. Additionally, there are several other concerns when studying the
benefits of acts of kindness. First, studies should examine if knowing the individual, as opposed to
performing the acts of altruism on strangers, affect the benefits. Second, individuals should examine if
planned acts of kindness have a different effect than random acts of kindness. Lastly, future research
should examine if seeing the individual respond to the acts of kindness affect the benefits.
Conclusion
The study of PPIs has resulted in a wide breadth of scientific knowledge on what is involved in
promoting subjective well-being, happiness, and life satisfaction. Despite great strides in the science of
increasing subjective well-being – the specific techniques that improve subjective well-being and the key
features of interventions such as variability and dosage that result in optimal outcomes – researchers still
know little about the underlying theoretical mechanisms that drive well-being interventions. Although for a
variety of interventions, many have proposed positive emotion as a mechanism, conversations with other
researchers in the field indicate to the second author that more often than not, well-being interventions
affect variables like depression with much larger effects than for positive emotion, if there is an effect on
positive emotion at all. Other potential mechanisms should be tested and considered such as hope, selfefficacy,
and attention towards positive stimuli. Furthermore, it may be that the idea of a single mechanism
that underlies well-being interventions is a misnomer, because different techniques operate by different
mechanisms. Although seminal work by Fredrickson and colleagues on the Broaden-and-Build Model of
Positive Emotions provides an important foundation for understanding how it is beneficial to improve
subjective well-being, the search for other mechanisms should also continue.
There are a few other domains that are becoming popular areas of interest among researchers worth
mentioning, though they were beyond the scope of this chapter. First, forgiveness interventions are that
which focus on the decision to let go of the negative feelings of anger, resentment, and hurt towards
another individual for behaving in a way that was perceived as offensive (DiBlasio, 1998). Forgivenessbased
interventions may reduce negative thoughts and feelings and increase positive thoughts and feelings
about a transgressor, increase forgiveness self-efficacy (i.e., forgiving without external pressure), and even
increase the likelihood that forgiveness will generalize to new situations (Harris et al., 2006). Additionally,
forgiveness-based interventions may be effective in helping females who have survived abuse (Freedman
& Enright, 2017) and students who experience emotional breakdowns (Mohammadi & HajiAlizadeh,
2017). Secondly, hope interventions and Hope Intervention Programs (HIP) focus on decreasing an
individual’s feelings of helplessness, powerlessness, and despair while increasing feelings of self-esteem
(Shin & Park, 2007). Hope interventions may increase sexual satisfaction and perceived body image in
776
men who suffer from addiction (Koolaee, Eslamei, & Mohammadi, 2017) and increase the effectiveness of
self-care instructional programs for those suffering from multiple sclerosis (Anderson, Turner, & Clyne,
2017). Lastly, Chamodraka, Fitzpatrick, and Janzen (2016) focused on the effectiveness of hope in a
therapeutic setting and found that a good match between a client’s preferences and a clinician’s hope-based
input can result in a client having increased faith in the therapeutic process, which leads to an increase in
hope as a positive outcome. Overall, these domains of hope and forgiveness need much more research to be
on par with the other previously mentioned domains.
Finally, one rising area of interest among researchers and clinicians is the dissemination of PPIs in
these aforementioned domains. Although providing clients with worksheets and homework in a therapeutic
environment similar to Cognitive Behavioral Therapy (CBT) or Dialectal Behavioral Therapy (DBT) would
work, some are opting for a more user-friendly method of delivery to individuals who are not receiving
treatment from a licensed professional. This can be done using mobile technology (i.e., smart phone
applications), but new methodological considerations arise when conducting interventions over the internet
(see Parks, 2014). Nevertheless, technology is a promising avenue for the dissemination of well-being
interventions to scale.
In conclusion, PPIs have both theoretical value for the study of how human happiness works as
well as practical applications for both therapeutic settings and the general population. Although scientists
already have a good depth of knowledge on PPIs, the field is only getting started and has many questions
that will guide future research, especially when it comes to realistic dissemination.
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Psychology Therapies and Interventions that Raise Subjective
Well-Being
By Philip I. Chow, University of Virginia, Department of Psychiatry and Neurobehavioral Sciences
Citation
Chow, P. I. (2018). Psychology therapies and interventions that raise subjective well-being. In E. Diener,
S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
Research and practice in mental health has a long history of focusing on what is wrong with people. By
contrast, relatively little work has examined how to raise subjective well-being. This chapter provides a
general overview of some therapies and interventions shown to increase well-being. An underlying theme is
that despite recent progress, more work is needed to understand what therapies increase well-being and the
putative mechanisms involved. Well-being researchers should learn from the lessons of clinical psychology,
such as thinking carefully about issues regarding reach and accessibility.
Keywords: Clinical psychology, Subjective well-being, Therapies, Mental health
Dominic has struggled with debilitating anxiety for as long as he can remember. Over the years, he
has figured out ways to compensate for his extreme fears and negative thoughts. For example, he is good at
blending into the background at work and avoids eye contact with people he sees on his street. However,
Dominic recently decided that he wanted more out of life, so he sought out a local psychotherapist who
could provide anxiety treatment. Over the past three months, Dominic has acquired a set of skills to
manage his fears and negative thoughts. However, despite experiencing some relief from his symptoms,
Dominic feels his overall quality of life is not where he would like it to be. While he feels more at ease
contributing to projects at work and interacting with people in his neighborhood, Dominic does not
experience optimism in his day-to-day life, nor is he on the path to deep and fulfilling personal growth.
Unfortunately, Dominic’s experience is common for those who receive psychotherapy. Researchers are
recognizing that therapies delivered in clinical settings are focused on decreasing symptoms rather than
increasing subjective well-being (e.g., Seligman, 2002; Sin & Lyubomirsky, 2009). In the case of Dominic,
while anxiety treatment has allowed him to lead a less symptomatic lifestyle, the likelihood that his anxiety
symptoms will surface in the future remains relatively high (full remission occurs in a minority of
patients). Most importantly, anxiety treatment has not given Dominic the skills he needs to grow and
flourish.
Most theory and research in clinical psychology has focused on what is wrong with people. For
example, prominent theories and research in depression and anxiety highlight the cognitive, emotional, and
behavioral factors that contribute to the development and maintenance of symptoms (Beck, 1974; Clark &
Watson, 1991). For example, much research has examined the role of negative cognitive biases in the
development and maintenance of anxiety symptoms (Dodge & Frame, 1982; Foa, Franklin, Perry, &
Herbert, 1996; Mathews, Mackintosh, & Fulcher, 1997; Mineka & Sutton, 1992). By contrast, relatively
little work has examined psychological therapies that promote subjective well-being. Thus, the focus of this
chapter is on providing a brief overview of psychological interventions and therapies that increase
subjective well-being. This chapter begins by briefly discussing some historical trends in how mental
health is conceptualized, as well as how a dysfunction model of mental health contrasts with models of
well-being promotion. Next is a discussion of traditional and third wave cognitive behavioral therapies,
with an emphasis on components that have been empirically shown to raise subjective well-being. There is
also a brief discussion of humanistic therapies and how they relate to modern day well-being interventions.
Finally, the conclusion of this chapter will focus on some critical unanswered questions and
recommendations for future work.
Well-Being and Mental Health
The history of mental health is marked by efforts to identify weaknesses in people (Szasz, 1974).
For example, some of the earliest attempts to assess mental status in the United States led to discriminative
and exclusionary practices against refugees trying to enter the country (e.g., those labeled as
“Undesirables”). This early focus on people’s perceived shortcomings has had far-reaching implications
for how mental health is conceptualized and researched. For example, the Diagnostic and Statistical
Manual of Mental Disorders (DSM), now in its fifth revision, and the International Classification of
Diseases (ICD), currently in its tenth revision, are the two widely used classification systems that influence
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how we view mental health status. Both systems rely on symptom checklists to classify individuals based
on perceived weaknesses. This method of classifying mental health status has dominated the way
researchers and the public perceive mental health, which is to view mental health from a lens of harm and
dysfunction (Wakefield, 1992). This systematic bias has, in part, led to the vast majority of mental health
research being focused on how to alleviate distress rather than promote well-being.
Many prominent psychologists have questioned psychology’s focus on the negative aspects of life.
For example, influential figures such as Carl Rogers and Abraham Maslow argued that people should be
seen as more than the sum of their symptoms, and that individuals should strive to achieve their full
potential (these ideas would serve as the basis for humanistic therapies and an impetus for the positive
psychology movement, discussed later in this chapter). More recently, the field of positive psychology
(Seligman & Csikszentmihalyi, 2000) is focused on how to cultivate people’s strengths in order to achieve
greater life meaning and fulfillment.1 Although seemingly nuanced, the difference between models of stress
reduction and well-being promotion has far-reaching implications. Chief among them is the notion that
acquiring skills for symptom reduction is not a sufficient replacement for those needed to develop and
maintain healthy levels of social and emotional well-being. A tacit assumption among many mental health
providers is that focusing on symptom reduction will necessarily translate into higher levels of well-being.
However, a burgeoning area of research is proving this assumption to be misguided, as researchers are
developing interventions that specifically target well-being promotion (e.g., Seligman, Steen, Park, &
Peterson, 2005).
How people think and feel about their lives are core components of subjective well-being (Diener,
Lucas, & Oishi, 2002; for a more thorough discussion of definitions and components of well-being, the
reader is encouraged to visit the corresponding section and chapters “Introduction/Theory/Measurement” in
this handbook). Importantly, a high level of positive affect alone is not sufficient for a high level of
subjective well-being, as researchers have stressed the importance of conceptualizing subjective well-being
as a general area of scientific interest rather than as a single construct (Diener, Suh, Lucas, & Smith, 1999).
Thus, as discussed further below, therapies that raise well-being commonly target how people think, feel,
and behave in everyday life.
It is important to note that despite clinical psychology’s focus on mental disorders, much work has
been dedicated to understanding factors relevant to well-being. For example, literature on resilience has
uncovered a great deal regarding how people adapt to stressors in their environments (e.g., Betancourt &
Khan, 2008; Davydov, Stewart, Ritchie, & Chaudieu, 2010). Although psychologists interested in
pleasurable emotions have most frequently studied joy or happiness, researchers have uncovered numerous
discrete (or highly similar) pleasant emotions, such as joy, contentment, interest, pride, and love (e.g.,
Berenbaum, 2002; Berenbaum, Chow, Schoenleber, & Flores, 2016; Shiota, Neufeld, Yeung, Moser, &
Perea, 2011). Likewise, studies have found that how people think about different types of pleasurable
emotions, such as happiness and appreciation/gratitude, is linked to a range of important outcomes (e.g.,
Chow & Berenbaum, 2015; Mauss, Tamir, Anderson, & Savino, 2011). Although most studies on cognitive
biases have focused on negative or threat related biases, studies have also examined how positive cognitive
biases contribute to life satisfaction (e.g., Cummins & Nistico, 2002; Peeters, 1971). Importantly,
continued research on these types of psychological factors will enhance our ability to understand the
putative mechanisms through which therapies increase subjective well-being.
Cognitive Behavioral Therapies and Emerging Third Wave Therapies
Cognitive behavioral therapy (CBT) is based on a wealth of empirical research demonstrating
strong connections between cognitive, emotional, and behavioral processes (Butler, Chapman, Forman, &
Beck, 2006). Thus, CBT2 is a goal-oriented approach that targets the ways people think, feel, and/or
behave. For example, CBT changes maladaptive thoughts (e.g., “I am such a loser”) that cause emotional
distress (e.g., sadness) and interpersonal dysfunction (e.g., excessive reassurance seeking from peers). CBT
is typically conducted through face-to-face therapy sessions. A key component of CBT is homework,
focused on skill acquisition through repetition, that clients are expected to complete between sessions.
Compared to other types of psychotherapy (e.g., psychoanalysis), the length of CBT is usually shorter on a
scale of weeks. CBT is best thought of as a family of interventions rather than as a solitary treatment, and
therapists will tailor treatments depending on the patient’s background as well as the specific skills the
patient needs to acquire. Among all therapies, CBT is among the most effective in treating a range of mood
and anxiety disorders (Barlow, Gorman, Shear, & Woods, 2000; Covin, Ouimet, Seeds, & Dozois, 2008;
Hofmann, Asnaani, Vonk, Sawyer, & Fang, 2012).
Although CBT is typically employed in clinical populations, where the primary focus is on
reducing psychological distress, an undercurrent of research suggests that interventions targeting the way
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people think and behave can also increase aspects of well-being. For example, a robust body of literature on
gratitude interventions suggest that increasing the experience of gratitude influences well-being by
targeting the way people think (e.g., Emmons & McCullough, 2003; McCullough, Emmons, & Tsang,
2002; Wood, Froh, & Geraghty, 2010; Wood, Maltby, Gillet, Linley, & Joseph, 2008). These interventions
often involve engaging in some type of repetitive activity, such as counting one’s blessings or recalling
positive memories, which promotes positive thinking, feeling states, and prosocial behaviors.
Behavioral activation (BA) is another type of CBT intervention that is based on models of behavior
(for a review, see Jacobson, Martell, & Dimidjian, 2001). BA draws upon foundational learning principles,
whereby individuals are taught to understand how their environmental responses are linked to the way they
think and feel. Individuals are typically asked to schedule activities (e.g., starting up a conversation with a
stranger, exercising) that allow for reinforcement and introspection to occur. Importantly, because a key
component of BA is positive reinforcement, some of the first studies demonstrated that BA not only
reduced depressive symptoms, but also increased the frequency of both pleasurable activities and prosocial
interactions (Lewinsohn, Biglan, & Zeiss, 1976). Further, engaging in behavioral activities has also been
found to lead to an increase in positive affect (e.g., Jacobson & Gortner, 2000; Martell, Addis, & Jacobson,
2001).
Although CBT is one of the most widely studied therapies, more research is needed before
concluding that it can raise subjective well-being. One reason is that studies of CBT almost exclusively
focus on symptom reduction in clinical populations. In these studies, a between-groups design is usually
employed where one group receives CBT and the other receives either no treatment or a placebo.
Participants in these studies often have high symptom levels (e.g., depression, anxiety, alcohol use) and are
desperate for relief. Thus, the outcome of interest is almost always symptom level rather than variables
linked to well-being. Although CBT packages could be useful in boosting well-being among the general
population, such as cultivating an optimistic thinking patterns and behaviors that foster strong interpersonal
relationships, these issues require more attention from researchers.
A “third wave” (also referred to as “new wave”, “next generation”, and “third generation”) of CBT
has increasingly caught the attention of researchers and clinicians. While there is ongoing debate regarding
what qualifies as a third wave therapy (Hofmann, Sawyer, & Fang, 2010), newer therapies such as
acceptance and commitment therapy (ACT; Hayes, Luoma, Bond, Masuda, & Lillis, 2006) and mindfulness
based treatments (Segal, Williams, & Teasdale, 2002) largely aim to change how people respond to events,
rather than changing the events themselves. For example, third wave acceptance-based therapies encourage
individuals to develop a meta-awareness of recurring thoughts and feelings. With enough practice,
individuals learn to objectify their subjective experiences and to monitor their reactions. This allows people
to effectively distinguish between what is real and what is imagined. By contrast, traditional CBT aims to
teach skills that change the content of thoughts. Through repeated practice, individuals learn to identify
maladaptive thoughts and generate alternative, healthier thinking patterns.
Despite their shift in focus, third wave therapies have much in common with traditional CBT
approaches. A central component of all CBT approaches is a shared focus on how cognitive processes
relate to affective experiences and behavior. For example, as discussed further below, an important
mechanism of mindfulness is cultivating awareness and attention to experiences in the present moment.
Thus, mindfulness practice leads to desired outcomes by restructuring how people respond to the automatic
thoughts and feelings that arise in response to events (e.g., accepting and describing a thought or feeling,
rather than pushing it away). This is similar to a more traditional CBT approach that might target thoughts
(and their underlying connections with emotions and behavior) by identifying and untwisting distorted
thoughts that give rise to maladaptive feelings and behavior (e.g., the distorted thought of “I’m terrible at
everything” gives rise to the alternative thought of “I know I’m a responsible husband and father”).
Therefore, third wave CBT approaches can be seen as largely building on a traditional CBT framework.
Mindfulness is a third wave therapy that has received considerable attention in recent years (for
reviews, see: Chiesa & Serretti, 2009; Grossman, Niemann, Schmidt, & Walach, 2004; Hoffman, Sawyer,
Witt, & Oh, 2010; Hoffman et al., 2012; Khoury et al., 2013; Piet & Hougaard, 2011). In scientific
literature, mindfulness is thought of both as a trait, or a characteristic that varies between individuals and
that is relatively stable, as well as a skill that can be acquired through practice. Most studies examining the
effectiveness of mindfulness practice conceptualize it as the latter. As a skill, mindfulness involves the
capacity to purposefully attend to one’s present experiences while taking a nonjudgmental stance (KabatZinn,
2003).3 Relative to other therapies, a strong body of research supports the notion that mindfulness not
only decreases symptoms, but conveys numerous benefits to well-being (e.g., Brown & Ryan, 2003;
Carmody & Baer, 2008) and use of adaptive coping strategies (e.g., Weinstein, Brown, & Ryan, 2009). As
mindfulness was originally developed to promote spiritual growth in Buddhism (Shonin, Van Gordon, &
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Griffiths, 2014), relative to traditional CBT considerably more mindfulness research has been focused on
how mindfulness practice develops strengths rather than shores up weaknesses.
An emphasis of mindfulness interventions is on cultivating attention and awareness to present
moment experiences. Thus, in contrast to the many automatic behaviors (e.g., accepting thoughts as one’s
reality, dwelling on past mistakes or future threats, daydreaming) that prevent people from fully living their
day-to-day lives, practicing mindfulness leads to an enhanced vividness, clarity, and appreciation of the
present. Individuals learn to be an observer of their own lives, developing a capacity to self-regulate and
weigh options. For example, mindfulness is consistent with self-determination theory (Deci & Ryan, 2000),
whereby increasing awareness of the present leads to enhanced feelings of autonomy, competence, and
relatedness. Along these lines, cognitive researchers theorize that mindfulness may directly impact wellbeing
by allowing for more intense pleasure through connection with present moment experiences (for a
review of mindfulness and theories of well-being, see Brown & Ryan, 2003). Not surprisingly, mindfulness
overlaps with constructs such as emotional intelligence (i.e., clarity and attention to one’s emotional states;
Salovey, Mayer, Goldman, Turvey, & Palfai, 1995), self-consciousness (e.g., Fenigstein, Scheier, & Buss,
1975), and the personality trait dimension of openness to experience (Costa & McCrae, 1992).
Although studies examining mindfulness have been around for decades (e.g., Kabat-Zinn,
Lipworth, & Burney, 1985), recent years have seen a proliferation in research demonstrating that practicing
mindfulness4 leads to increases in factors of well-being. Noted increases in well-being have also been
documented in studies focused on symptom reduction. For example, short-term meditation training has
been found to increase levels of empathy and spirituality in medical students (Shapiro, Schwartz, &
Bonner, 1998) and levels of well-being in adults (Carmody & Baer, 2008). Research also indicates that
mindfulness training has other benefits, such as increasing positive affect and frequency of positive
thoughts (Garland, Geschwind, Peeters, & Wichers, 2015), job-related affect (e.g., optimism and selfefficacy;
Malinowski & Lim, 2015), and use of adaptive emotion regulation strategies (Hülsheger, Alberts,
Feinholdt, & Lang, 2013; Teper, Segal, & Inzlicht, 2013).
Meta-analyses have found that mindfulness practice leads to positive outcomes, in part, by
increasing levels of mindfulness and decreasing cognitive and emotional reactivity, as well as repetitive
negative thinking (Gu, Strauss, Bond, & Cavanagh, 2015). For example, researchers theorize that
mindfulness training leads to changes in thought processes and the ability to shift one’s perspective (for a
review, see Shapiro, Carlson, Astin, & Freedman, 2006). This in turn allows individuals to achieve a degree
of objectivity regarding their internal experiences, which is consistent with models of personal growth
outlined by developmental psychologists (e.g., Deikman, 1982; Kegan, 1982). Taken together, among all
empirically supported therapies, mindfulness-based therapies are some of the strongest ones found to
increase well-being.
Like literature on CBT, a drawback of mindfulness effectiveness literature, including meta-analyses
of mindfulness studies, is that the focus has primarily been on treating mental disorders in clinical
populations and settings, or symptom reduction rather than promotion of well-being (e.g., Khoury et al.,
2013; Brown & Ryan, 2003). Thus, despite an accumulation of studies demonstrating that mindfulness
training can enhance well-being, this issue has received relatively little attention. In addition, precisely
which factors of well-being (e.g., positive affect, positive appraisals) are most reliably influenced by
mindfulness-based interventions is still an open question.
Acceptance and commitment therapy (ACT; Hayes, Strosahl, & Wilson, 1999), a therapy that
counts mindfulness as one of its core components, has also received considerable attention from researchers
in recent years. ACT extends traditional behavioral models (for a more detailed discussion, see Hayes,
Luoma, Bond, Masuda, & Lillis, 2006), and is largely based on Relational Frame Theory (RFT; Hayes,
Barnes-Holmes, & Roche, 2001). RFT focuses on how people use language to relate to events. For
example, subjective experiences (e.g., thoughts) can cause distress because of the language that is used to
relate to them. Thus, a notable difference from traditional CBT is that ACT views cognitions as a type of
behavior, and seeks to change the function of those behaviors rather than the content. ACT teaches people
to accept their thoughts and feelings, rather than judging their acceptability, and to understand the
functionality of their responses. Another notable difference from traditional CBT approaches is that, like
mindfulness, ACT emphasizes contextual and experiential strategies to generate change, but only after
accepting one’s subjective experiences.
A primary aim of ACT is psychological flexibility, which encompasses an ability to connect with
the present moment as well as the ability to regulate one’s behavior in line with one’s values. This is done
through exercises focused on: acceptance, cognitive defusion (seeing thoughts as what they are, not as
what they say they are), being present, understanding the self as context (that we are more than the sum of
our subjective experiences), identifying and pursuing values, and committed actions (goals in accordance
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with one’s values; for a more thorough review, see Hayes et al., 2006). Indeed, several of these domains are
highly overlapping with core principles of mindfulness, such as those that involve cultivating acceptance,
objectivity, and present-oriented awareness. ACT also incorporates striving for values and goal-oriented
behaviors, components commonly found in traditional CBT. In addition, despite their different approaches,
like CBT, a core function of ACT is to address experiential avoidance, or attempts to avoid unpleasant
thoughts, feelings, and sensations, that contribute to long-term suffering.
Some research suggests that ACT can enhance aspects of well-being, although the bulk of this
literature highlights the importance of mindfulness-related components of ACT. For example, fostering
acceptance of thoughts, feelings, and sensations leads to enhanced ability to regulate one’s affect and
physiological response to events (e.g., Bishop, Duncan, & Lawrence, 2004; Kabat-Zinn, 2003). Other
active components of ACT, such as cognitive defusion, are usually centered on unpleasant subjective
experiences and therefore applications to raising subjective well-being have been largely ignored by
researchers. Given that research and meta-analyses focusing on ACT is relatively new (the bulk of metaanalyses
have occurred in the last decade), and the vast majority of research has been limited to examining
effectiveness of symptom reduction in clinical populations (Öst, 2008; Powers, Vording, & Emmelkamp,
2009), whereas direct applications of ACT on increasing subjective well-being is relatively unknown.
Humanistic Therapies
When evaluating the landscape of therapies that raise subjective well-being, it would be remiss to
not include humanistic therapies. Humanistic therapies have a rich history in the field of clinical
intervention, and prominent psychologists such as Abraham Maslow, Otto Rank, and Carl Rogers have
had a profound impact on how therapy is conducted in the present day. For example, common factors in
psychotherapy such as therapeutic alliance, understanding the client’s perspective, and positive regard for
client experiences are among the most robust predictors of therapy success (Ackerman & Hilsenroth, 2003;
Duncan, Miller, Wampold, & Hubble, 2010; Krupnick et al., 1996). At its core, humanistic approaches treat
the whole person, rather than reducing individuals to their symptoms. An emphasis is placed on
understanding the individual’s subjective experience, such as how they perceive and interpret events, and
an overriding assumption is that people are generally good and have a basic need for growth. However,
early humanists were skeptical of quantitative methods and chose instead to use approaches such as
unstructured interviews. However, it is generally accepted that humanistic psychology was a precursor to
the now burgeoning field of positive psychology, although considerable tension between these fields has
focused on the precise role humanism has played in positive psychology (see Friedman & Robbins, 2012;
Seligman & Csikszentmihalyi, 2000; Waterman, 2013). This is not surprising given that humanists were
among the first to advocate seeing people as composed of strengths and potential, whereas positive
psychology emerged out of concerns that clinical psychology was only concerned with amelioration of
distress. Using principles of humanism as a building block, positive psychology studies therefore have
been instrumental to understanding how to encourage growth, flourishing, and well-being. Mounting
evidence supports positive psychology interventions (for reviews, see Bolier et al., 2013 and Sin &
Lyubomirsky, 2009), such as gratitude interventions (e.g., Emmons & McCullough, 2003; Wood et al.,
2010) and well-being therapy (e.g., Fava & Ruini, 2003) in increasing well-being. For example,
ENHANCE is a 12-week positive psychology program that targets knowledge and skills acquisition to
improve subjective well-being in generally health community samples, with encouraging early findings
(Kushlev et al., 2017). What makes ENHANCE different from most other positive psychology
interventions is its use of a multi-pronged approach that targets ten principles of happiness (e.g., values and
roles, goals, gratitude, prosocial behavior) organized around themes of building the core self, experiential
self, and social self. As a sustainable intervention package, programs like ENHANCE will continue to
bridge the divide between research and application. In order to understand the modern day influence of
humanistic theories and models on well-being, the reader is encouraged to review the chapter on positive
psychology interventions in this handbook (Parks, 2018).
Effectiveness of Clinical Therapies on Subjective Well-Being
This chapter only covers some of the therapies employed in real-world settings, though careful
consideration was made to present therapies that had at least some empirical support. Major scientific and
government organizations are striving to set guidelines regarding what constitutes an evidence-based
therapy. For example, Division 12 of the American Psychological Association
(www.psychologicaltreatments.org), SAMHSA ( www.nrepp.samhsa.gov), and the National Institute for
Health and Care Excellence have all compiled such lists. However, it is important to note that these efforts
are primarily based on literature concerned with ameliorating distress (Cloninger, 2006). This is largely
driven by clinical psychology’s traditional focus on discrete categories of mental disorders. For example, it
is still rare to come across subjective well-being as a primary outcome in CBT studies. Instead, research
tends to focus on a mental disorder type, such as depression, anxiety, and alcohol dependence. By contrast,
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literature focused on therapies that increase subjective well-being is relatively sparse, although early
reviews are promising (e.g., Bolier et al., 2013; Goyal et al., 2014; Sin & Lyubomirsky, 2009). Thus, while
it is likely that at some point organizations will compile lists of empirically supported therapies that raise
subjective well-being, more work is needed.
Unanswered Questions
This is an exciting time for researchers and clinicians interested in raising subjective well-being.
This is a burgeoning area of research and many unanswered questions remain. This section will focus on
important issues that still need to be fully addressed by therapy and well-being researchers.
One critical issue is whether effectiveness of well-being interventions differs as a function of the
population in question. Much theory and research in clinical psychology has focused on cultural
considerations in therapeutic settings (e.g., Lin & Cheung, 1999; Helms & Cook, 1999; Sue & Zane, 2009),
trying to take into consideration a client’s cultural background when tailoring a treatment approach.
However, despite significant progress, serious concerns remain (e.g., Sue & Zane, 2009). For example,
there is confusion regarding to what degree one should factor in a client’s cultural background, since studies
have shown a large amount of variation within cultural groups. In addition, many guidelines for tailoring
interventions are overly vague and lack the degree of specificity necessary to be useful to treatment
providers. To date, very little research has focused on how to tailor interventions that raise subjective wellbeing.
For example, some studies suggest that gratitude interventions are less impactful among East Asians
than among Americans (Layous, Lee, Choi, & Lyubomirsky, 2013), and researchers are increasingly
targeting well-being interventions towards specific populations and settings (e.g., Hamar, Coberley, Pope,
& Rula, 2015; Siu, Cooper, & Phillips, 2014). However, this body of work is still relatively new and it will
be important for researchers to pursue this line of inquiry.
Another issue pertains to the precise mechanisms involved in therapies that raise subjective wellbeing.
While some evidence suggests that the average effect sizes of well-being interventions is comparable
to psychotherapy interventions targeting mental disorders (Sin & Lyubomirsky, 2009), the putative
mechanisms involved in well-being interventions are not well understood. Some reviews have identified
candidate factors in raising well-being. For example, Layous and Lyubomirsky (2012) proposed four
mediating variables (positive emotions, positive thoughts, positive behaviors, and need satisfaction) and
two moderating variables (characteristics of the activity and the person) in the link between positive
activity interventions and well-being. In a review of mindfulness-based studies, Gu and colleagues (2015)
found strong support for the mediating variables of cognitive and emotional reactivity, and moderate
evidence for mindfulness, rumination, and worry (as well as preliminary support for self-compassion and
psychological flexibility). Importantly, the authors found that many studies had key methodological
shortcomings that limited the conclusions that could be made. This highlights the importance of conducting
methodologically sound studies that can be connected to the broader literature. Efforts should be made to
standardize paradigms and measures. In addition, future studies should systematically isolate mechanisms
thought to play a role in well-being interventions. These efforts will allow for more reviews and metaanalyses
that are instrumental to understanding how and why well-being interventions work (and for
whom).
There is a great deal of overlap between well-being interventions and clinical psychology
interventions aimed at attenuating distress. For example, both types of interventions typically involve
changing underlying cognitive processes tied to emotions and behavior. Thus, it would appear that these
interventions could be used in tandem—while clinical interventions can be used to decrease distress, wellbeing
interventions could be used to promote thriving and a healthy lifestyle. To date, the vast majority of
studies have focused on either clinical interventions to alleviate distress or interventions designed to raise
well-being. Thus, it will be important for future work to understand how these approaches can be
integrated, ideally in single treatment packages. One way to facilitate this effort is for researchers to include
outcome measures assessing psychopathology and well-being. This will enhance understanding of how an
intervention or therapy can be used in the service of decreasing symptoms or increasing well-being. From a
systematic perspective, it may also be useful for graduate programs to include well-being interventions in
their standard training packages, since most programs (e.g., clinical psychology, social work) exclusively
focus on training students to assess and alleviate psychological distress.
Prominent models and theories of well-being should continue to play a key role in developing and
evaluating therapies that target well-being. Virtually all influential models of well-being identify
subcomponents that can be targeted through intervention. For example, hedonic models of subjective wellbeing
highlight the importance of increasing positive affect and minimizing negative affect. According to
Ryff’s model of eudaimonic well-being (Ryff, 1989), an effective intervention should seek to increase at
least one of multiple factors (self-acceptance, personal growth, life purpose, positive relationships,
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environmental mastery, autonomy), in order to allow individuals to strive to reach their full potential.
However, the existence of competing models of well-being may cause confusion among therapy
researchers and practitioners. Future work should focus on how to integrate different models of well-being
(e.g., Gallagher, Lopez, & Preacher, 2009) so that connections between interventions can be made more
readily.
An important issue is how to deliver well-being interventions in everyday life. It is noteworthy that
evidence-based psychological treatments for mental disorders have come under scrutiny for their lack of
reach (for reviews, see Barlow, Bullis, Comer, & Ametaj, 2013, and Harvey & Gumport, 2015) and
standardization in real-world settings (Chow, Wagner, Lüdtke, Trautwein, & Roberts, 2017. Despite yearly
increases in the prevalence of mental disorders, roughly half of individuals who need treatment do not have
access to adequate treatment (Kessler et al., 2003). Thus, despite solid empirical work showing that
evidence-based psychological treatments can be effective in attenuating psychological distress (Chambless
& Ollendick, 2001; Layard & Clark, 2014), therapies targeting well-being will need to overcome the same
barriers to treatment dissemination and standardization. Technology offers one potential solution. Many
therapies that were once limited to the clinician’s office can now be delivered remotely online, with many
online therapies having comparable effect sizes to those delivered face-to-face (e.g., Barak, Hen, BonielNissim,
& Shapira, 2008; White et al., 2010). For example, there is emerging empirical support for the
Happify app (www.happify.com) for increasing positive affect, which delivers a mindfulness-based
intervention via people’s personal smartphones (Howells, Ivtzan, & Eiroa-Orosa, 2016). Other apps such as
JOOL Health (www.joolhealth.com) target well-being by creating personalized plans through predictive
modeling, although the effectiveness of these apps are still being examined. Compared to face-to-face
therapy, technology delivered interventions are more cost-effective, are capable of reaching a wider
audience, and can be delivered where and when they are most needed (e.g., Nahum-Shani, Hekler, &
Spruijt-Metz, 2015; Ritterband & Tate, 2009). For example, research leveraging mobile technology is
enhancing our understanding of everyday life processes in psychopathology (e.g., Chow et al., 2017; Saeb
et al., 2015) so that researchers can begin developing interventions that are woven into people’s routines.
Similar efforts are being made to understand processes important to well-being (e.g., Bentley & Tollmar,
2013). Such work is critical to personalizing well-being interventions (e.g., dynamically adapting an
intervention to people’s changing states) and understanding where, when, and how to deliver them. For
example, traditional face-to-face CBT usually involves once a week hourly sessions. Thus, clinicians have
little understanding of how their clients are doing outside the therapy office. Technology based approaches
can allow therapists to monitor their client’s well-being, as well as deliver an intervention (e.g., using a
smartphone application) at critical times (e.g., when the client is alone) and locations (e.g., when the client
is at home). However, the majority of technology based work (and works in mobile technology, in
particular) is being done by engineers who have limited training in mental health models. Given the
ubiquity of technology in modern society, it is therefore imperative for well-being researchers to bridge the
divide in order to explore cutting-edge solutions to intervention development and dissemination.
Conclusion
The therapies and interventions covered in this chapter do not comprise an exhaustive list. A
primary aim of this chapter was to provide a general scope of therapies that can raise subjective well-being.
Although more work needs to focus on therapies and interventions that raise subjective well-being, this is
an exciting field that holds great promise for enhancing the lives of both clinical populations and the
general population. Ideally, well-being researchers can learn from the trials and successes of clinical
researchers, as individuals from these seemingly disparate fields continue to work towards a unifying field
that focuses on improving people’s lives.
Footnotes
1Because this book contains a separate chapter dedicated to positive psychology, interventions and
therapies directly relevant to positive psychology will not be discussed in this chapter.
2There are several therapies with strong empirical support that are based on a CBT framework, such as
Dialectical Behavior Therapy (DBT; Linehan, 2014), although those will not be discussed in this chapter.
Relative to CBT, DBT emphasizes the relational aspects of psychopathology through skills training in a
group format. People learn skills of interpersonal effectiveness, distress tolerance, emotion regulation, and
mindfulness.
3In literature, mindfulness has been examined as both a unidimensional and a multidimensional construct
(i.e., as a general factor versus one composed of several interrelated facets, respectively). As researchers
have become increasingly interested in examining how mindfulness is associated with various outcomes,
this has necessitated examination of mindfulness at the facet level (e.g., Baer et al., 2008; Desrosiers, Vine,
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Curtiss, & Klemanski, 2014). Research shows that mindfulness can be separated into five factors, which
are describing and labeling one’s experiences, acting with awareness and attending to one’s activities in the
present moment, non-judging of inner experiences, observing and noticing one’s experiences, and nonreacting
to unpleasant stimuli (for a review, see Baer, Smith, Hopkins, Krietemeyer, & Toney, 2006). For
simplicity, mindfulness is presented as a single construct in the current chapter.
4There have been several mindfulness-based programs developed, such as mindfulness-based stress
reduction (MBSR; Kabat-Zinn, 1990) and mindfulness-based cognitive therapy (MBCT; Teasdale, Segal,
& Williams,1995), that are all based on the foundational principles of cultivating attention and awareness
to present moment experiences.
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Stress Management Interventions: Improving Subjective
Psychological Well-Being in the Workplace
By Holman, D., Johnson, S., & O’Connor, E., University of Manchester
Citation
Holman, D., Johnson, S., & O'Connor, E. (2018). Stress management interventions: Improving
subjective psychological well-being in the workplace. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook
of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
In this chapter we provide an overview of stress management interventions (SMI) and review the evidence
for their effects on employee stress and well-being. We start by setting out a typology of SMI that classes
SMI according to level (i.e., the individual-level or organisation-level) and focus (i.e., a ‘primary’ focus on
altering the causes of stress or a ‘secondary’ or ‘tertiary’ focus on reducing stress itself). We then use this
typology to describe key types of SMI, after which we review the evidence for those SMI with the most
extensive evidence bases, namely secondary individual-level SMI that seek to reduce stress in employees
(e.g., relaxation techniques, cognitive-behavioral therapy, mindfulness training) and primary
organisational-level SMI that seek to remove the causes of stress by changing organisational practices (e.g.,
job redesign, changes to working time schedules). We conclude by suggesting that there is convincing
evidence for both of these SMI approaches. However, the evidence base needs strengthening through more
robust methodological designs (e.g., randomised control trials, broad based evaluations of intervention
processes) and a better understanding of the contexts and individuals in which SMIs are most effective,
how the implementation of SMIs affects outcomes, and the long-term impacts of SMIs.1
Keywords: stress management interventions, evaluation, review, cognitive-behavioral therapy,
mindfulness training, job redesign
Improving employee well-being and reducing stress can have a number of benefits for
organizations, from increasing performance, improving relationships, to reducing sickness and absenteeism
rates (De Neve, Diener, Tay & Xuereb, 2013; Warr, 2003). Stress management interventions refer to a
class of activities that are used by organizations to improve employee well-being and reduce stress,
principally by either addressing the causes of stress or by reducing the impact of stress on an individual.
The aim of this chapter is to review the literature on stress management interventions to establish what we
know about the effectiveness of different interventions in improving psychological well-being. It is split
into three main sections. First, we introduce a typology of stress management interventions (SMI) and
provide examples of the different types of intervention. Second, we discuss the evidence concerning the
effectiveness of SMI, although before this we will briefly discuss methodological considerations used when
evaluating interventions to provide the reader with some grounds for understanding the quality of evidence
in this area. Finally, we conclude the chapter with an overview of what works best.
When reviewing the literature, we use a broad definition of subjective psychological well-being
which enables us to include studies on burnout, anxiety, and depression, for example, as well as studies
focusing directly on positive psychological well-being. Furthermore, as we are interested in psychological
well-being we do not include studies that have looked at physical health or job attitudes, or those on wellbeing
related outcomes at the organizational-level such as sickness and absenteeism. However, it is worth
noting that these outcomes are related such that improvements in psychological well-being can lead to
improvements in health, job satisfaction and absenteeism rates.
Stress Management Interventions: A Typology and Description
The stress management literature typically classifies interventions according to the ‘focus’ of stress
management and according to the ‘level’ at which the intervention takes place (DeFrank & Cooper, 1987;
de Jonge & Dollard, 2002). With regard to the focus of stress management, interventions are categorized as
primary, secondary or tertiary. The aim of primary interventions is to prevent stress from occurring by
removing the sources of stress and enhancing the causes of well-being. Secondary interventions aim to
reduce the severity or duration of stress once it has occurred and to prevent the level of stress becoming
problematic. Tertiary interventions seek to rehabilitate and maximize functioning for those who are already
experiencing or suffering from psychological ill-health.
With regard to the level of an intervention, a common and simple distinction is between individual
and organizational levels. As the name suggests, individual-level interventions focus on helping
employees to develop skills to manage, cope with and reduce stress, whereas organizational-level
794
interventions make more systemic changes to organizational practices that either target all employees or a
specific group of workers. A third category, individual-organizational level interventions, is used in some
classifications. Such interventions are thought to differ from others in that they focus on changing the
relationship between the individual and organization, e.g., peer support groups. However, as the distinction
between organizational and individual-organizational level interventions is not always clear cut, we use the
more parsimonious categorization of individual-level and organizational-level interventions.
Classifying stress management interventions (SMI) according to their focus and level implies that
both individual and organizational-level interventions can be primary, secondary and tertiary in nature.
This is illustrated in Table 1, along with examples of the different types of intervention in each category.
Throughout the remainder of the chapter we describe the different types of SMI according to this
classification.
Table 1. A Typology of Stress Management Interventions
Intervention
type
Individual Organisational
Primary Selection & Assessment
Pre-employment medical examination
Job Redesign
Working time and schedules
Management training, e.g. mentoring
Secondary Mindfulness training
Health promotion, e.g., exercise
Cognitive behavioral therapy
Relaxation
Meditation
Personal and interpersonal skill training
Acceptance and commitment therapy
Psychosocial intervention training
Coping skills training
Resilience training
Improving communication and decision making
Conflict management
Peer support groups
Coaching & career planning
Tertiary Employee Assistance Programmes
Counselling
Posttraumatic stress assistance
Disability management
Vocational rehabilitation
Outplacement
Individual-Level Interventions
The aim of a primary individual-level intervention is to prevent stress from occurring in an
employee. One means of achieving this is through selection and assessment procedures that select
applicants who have the skills and abilities to manage the demands of the job and to screen out those who
might be susceptible to experiencing stress in the target role, particularly in highly-stressful occupations
(Bartone, Roland, Picano & Williams, 2008). Although such interventions are one way of managing stress
and promoting well-being, they are rarely used (Giga, Cooper & Faragher, 2003).
Secondary individual-level interventions seek to equip employees with the skills and abilities to
manage stress and promote well-being, and to provide employees with opportunities to engage in stressreducing
activities. They include techniques such as relaxation, meditation, cognitive behavioural therapy,
mindfulness training, and exercise programmes, as well as other techniques such as education and
interpersonal skill development. Drawing on the emotion regulation literature (Gross, 1998), these
techniques can be understood as promoting antecedent-focused emotion regulation strategies that seek to
reduce or remove the causes of stress, or response-focused emotion regulation strategies that seek to reduce
the level of stress experienced by individuals. It can also be noted that some individual-level interventions
are multimodal, e.g., a combination of relaxation, CBT and mindfulness exercises. Such an approach might
be used in the expectation that it will increase the likelihood of beneficial outcomes for both the individual
and organization, as it can enable employees to develop a wide set of skills that can be used across different
795
circumstances, provide employees with the opportunity to develop both antecedent and response-focused
emotion regulation strategies, and increase the chance of meeting employees’ needs. As secondary
individual interventions are one of the more commonly used SMI, and there is a stronger evidence base for
their effectiveness (which we outline later), we now detail the more widely used techniques.
Relaxation techniques are based on the assumption that states of relaxation and stress (i.e., highlyaroused
negative states of well-being such as anxiety, tension and anger) are antithetical (Russell, 1979). In
other words, you cannot be both relaxed and stressed at the same time, such that increasing levels of
relaxation will necessarily entail lower levels of stress. Various methods are used to induce relaxation but
all can be considered as response-focused emotion regulation strategies as they focus on reducing the
symptoms of stress. Progressive muscle relaxation involves tensing and then relaxing different muscles
throughout the body in a prescribed order. For example, a person might start by clenching and unclenching
one hand then the other, then focus on the muscles in one forearm and then the other, and so on. The
length, duration and range of muscles covered can vary but with practice employees can induce a deep
state of muscle relaxation in minutes (Murphy, 2003). Meditation is another relaxation technique but one
that focuses on a mental rather than physical process. Techniques typically involve sitting in a quiet place
and repeating a word or sound while maintaining a passive mental state that excludes intrusive thoughts.
Although meditation has its roots in religious practice, secular and standardized methods appropriate for
clinical trials have been developed (Carrington et al., 1980). Muscle relaxation and meditation can also
involve breathing techniques that focus on the inhalation and exhalation of breath as an additional means
of achieving relaxation, although some interventions use breathing techniques alone.
Cognitive behavioral therapies (CBT) assume that maladaptive cognitions contribute to the
maintenance of psychological distress and problematic behavioral responses to stress. CBT addresses this
by helping the person to identify misconceptions about the nature and causes of stress, to test the validity of
existing thoughts and understandings, and to develop new conceptions about stress. In addition, the
behavioral element of CBT encourages the person to develop new behavioral responses to stressful events.
CBT is thought to work by promoting antecedent-focused emotion strategies that help the person to
reappraise and restructure their understanding of stress and stressful events (Hofmann & Asmundson,
2008). For example, Cecil and Forman (1990) conducted an intervention amongst teachers based on a
method of CBT called stress inoculation training (Meichenbaum, 1977) that consists of three phases:
education about stress and its causes; acquisition and rehearsal of skills in cognitive restructuring (e.g.,
identifying irrational thoughts and replacing them with rational thoughts); and developing and practising
new cognitive, emotional and behavioral ‘scripts’ for responding to stressful events. Their evaluation
revealed that the CBT intervention decreased stress to a greater extent than a peer support group and a
passive listening group.
Mindfulness training is an increasingly popular SMI that aims to promote states of mindfulness
(i.e., paying attention to the experiences, thoughts and emotions occurring in the present moment in a nonjudgmental,
compassionate, accepting and non-reactive way) and new adaptive responses to negative
thoughts and emotions (Kuyken et al., 2010). Mindfulness is thought to foster psychological well-being by
primarily helping the person to dissociate negative thoughts and emotions from maladaptive behavioral and
emotional responses. Mindfulness training can therefore be understood as a method that develops
response-focused emotion regulation strategies. But mindfulness training has key differences from other
methods that also encourage response-focused emotion regulation strategies, such as relaxation and
meditation. In particular, in mindfulness training, negative thoughts and experiences are not avoided or
suppressed (which can have negative consequences for well-being, Richards & Gross, 1999) and there is an
emphasis on developing new and more adaptive responses.
Mindfulness therapies include acceptance and commitment therapy (Hayes, Luoma, Bond, Masuda,
& Lillis, 2004) and mindfulness-based cognitive therapy (MBCT) (Segal, Williams & Teasdale, 2002).
MBCT, for example, uses a range of methods, often conducted in groups with a trainer, such as body
scanning, yoga and meditation exercises. The initial emphasis in MBCT is cultivating states of
mindfulness. At later stages, the emphasis moves towards identifying how negative thoughts trigger
maladaptive responses, helping the person to accept those feelings, and encouraging the choice of more
adaptive responses. Although mindfulness training has grown in popularity, few empirical studies have
been conducted in organizational settings. An exception is a study by Hülsheger and colleagues who
conducted a two-week, self-directed mindfulness intervention, based on MBCT protocols, with employees
from a range of occupations. Their evaluation, using data collected from daily diaries completed by
participants, showed that employees in the mindfulness training condition reported higher levels of daily
mindfulness and lower levels of daily emotional exhaustion that those in a control group (Hülsheger,
Alberts, Feinholdt & Lang, 2013).
Other types of secondary individual-level interventions have also been developed. Two popular
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initiatives include educational programmes that inform employees about stress and how it can be managed,
and health promotion initiatives that are based on the assumption that a healthier lifestyle (e.g., more
exercise, better diet) will improve well-being (Anger et al., 2015; Rongen, Robroek, van Lenthe, &
Burdorf, 2013). In addition, personal skill development training in communication, goal setting and time
management all aim to reduce stress by helping employees to prevent stressful situations from occurring,
e.g., conflict, high workloads.
Lastly, tertiary individual-level interventions focus on individuals who are experiencing high or
chronic levels of stress that may be impairing their ability to work. For example, employee assistance
programmes (EAP) provide counselling and advice to those experiencing high-levels of stress or mental
health problems, whether these issues are related to work or not (Bhagat, Steverson & Segovis, 2007;
Csiernik, 2011; McLeod, 2008).
Organizational-Level Interventions
Primary organizational-level interventions aim to remove the causes of stress in organizations by
changing organizational practices and policies, such as those concerned with leadership, working time, and
occupational health and safety (Anger et al., 2015). The majority of primary organizational-level
interventions reported in the literature are job redesign interventions that aim to modify job characteristics
(e.g., job discretion, workload, ergonomic design) as a means of enhancing employee well-being, and they
have a strong theoretical and empirical grounding in studies of job design that show job characteristics to
be key antecedents of employee stress and well-being (Humphrey, Nahrgang & Morgeson, 2007;
Demerouti, Bakker, Nachreiner & Schaufeli, 2001). Job redesign interventions typically differ in scale,
with some seeking to change one job characteristic, such as job discretion (Bond & Bunce, 2001), whereas
others seek to change multiple job characteristics in the expectation that this will produce larger changes in
well-being (Holman & Axtell, 2016).
Secondary organizational-level interventions aim to make organizational-wide changes that help
employees cope better with stressful experiences. Such interventions include the introduction of peer
support groups that enable employees to discuss the difficulties they face (Peterson, Bergstrom,
Samuelsson, Asberg, & Nygren, 2008) and communication skills training courses that seek to improve the
ability of all employees to manage stressful situations through, for instance, improved conflict management
(Ghazavi, Lohrasbi, & Mehrabi, 2010; Leiter, Laschinger, Day & Oore, 2011). However, in practice, there
is not always a clear distinction between primary and secondary organizational level interventions,
particularly with regard to social support interventions which can remove a potential source of stress (i.e., a
lack of social support) whilst also improving the ability of employees to cope with stressful events.
Implementing organizational-level interventions can be difficult and complex. This means that an
important part of organizational-level interventions, particularly primary interventions that seek to change
organizational practice, is the efficacy of the implementation process. In particular, reviews suggest that
successful organizational-level interventions involve four key activities: preparation, i.e., securing support;
screening, i.e., identifying the psychosocial risks; action planning, i.e., developing change initiatives; and
implementation, i.e., embedding change initiatives within the organization (Nielsen, Randall, Holten &
González, 2010). Another important characteristic of organizational-level interventions is the level of
employee participation. For example, in a job redesign intervention conducted by Morgeson et al. (2006),
only managers and external consultants were involved in developing and implementing job redesign
changes. In contrast, in a job redesign intervention among knowledge workers in Denmark (Sørensen &
Holman, 2014), employees participated throughout the intervention process by identifying, developing and
implementing job redesign initiatives to reduce workload and modify work procedures. Employee
participation is thought to be advantageous as it can improve the quality of change initiatives by drawing
on employees’ expertise to make them more contextually appropriate, and because it can increase
commitment to implementing change initiatives, as employees have a greater sense of ownership of those
change initiatives (LaMontagne, Keegel, Louie, Ostry, & Landsbergis, 2007). Participation can also
increase the sense of job control and responsibility, which is beneficial for well-being in its own right
(Mikkelsen & Saksvik, 1998). But participation is not without risk: it can increase complexity by involving
a wider range of stakeholders who may have competing ideas and motivations, increase frustration with the
intervention process if employees are not experienced or skilled in participation, and raise costs by
removing front-line employees from their jobs.
Some multimodal SMI combine individual- and organizational-level interventions. For example,
‘total worker health interventions’ integrate organizational-level health and safety programmes with
individual level health promotion programmes (see Anger et al., 2015 for a review). An advantage of this
approach is that the organizational-level intervention can reduce the causes of stress, while the individuallevel
intervention can enhance employees’ ability to deal with stress. Such an approach can be particularly
797
important for employees exposed to higher demands, as they also tend to engage in more high-risk health
behaviors (Anger et al., 2015). Other multimodal interventions occur just at the organizational level. For
example, job redesign interventions have been implemented alongside changes to other organizational
practices, in the expectation that this will augment the effects of the job redesign intervention (Daniels,
Gedikli, Watson, Semkina, & Vaughn, 2017). Potential disadvantages of multimodal approaches are an
increase in implementation complexity and that one intervention may reduce the effectiveness of the other.
What Works? Evaluating the Effectiveness of
Stress Management Interventions
When selecting SMI it is clearly important to consider the evidence for their effectiveness in
reducing stress and promoting well-being. In this section, we review the findings for those SMI that have
a more substantial evidence base, namely secondary individual-level and primary organizational-level
interventions2. But before we do this, it is important to touch on the issues concerned with how best to
evaluate interventions, as this provides a better understanding of the nature and quality of evidence
available.
Based on the natural science paradigm, randomised control trial (RCT) designs are traditionally
considered to be the optimal methodology for evaluating interventions. RCTs randomly allocate
participants to experimental and control groups and then introduce the intervention to the experimental
group. Change in the focal outcome is measured in both groups before and after the intervention.
Randomization is used to control for the effects of context and participant differences, such that when
change in the outcome in the experimental group is significantly different to that in the control group, the
change is assumed to be caused by the intervention. RCTs are therefore thought to provide stronger
evidence for the causal effects of an intervention than methodological designs that do not randomize
individuals to groups, that do not have a control group, and those that do not have pre-intervention
measurement.
In addition to the evaluation of individual studies, meta-analyses are used to provide a quantitative
overview of multiple studies. A meta-analysis produces an overall effect size based on the individual
studies selected for review. More confidence can be placed in meta-analytic results, as they are based on a
larger sample that minimizes the likelihood of chance findings, and because the weaknesses of individual
studies are balanced out. To explain this further, the results of one study could be accidental or influenced
by something that was not investigated, whereas the results of a meta-analysis that combine data from
multiple studies are much more likely to be a true reflection of an intervention’s real impact. A key issue
in a meta-analysis is how to select studies for inclusion (e.g., RCT studies only), since the methodological
quality of the studies chosen affects the confidence that can be placed in the findings.
However, several authors have questioned whether RCTs provide a sufficient and appropriate
methodology for intervention evaluation (Cox, Karanika, Griffiths & Houdmont, 2007; Nielsen &
Miraglia, 2017). Specifically, it is argued that RCTs are not always feasible in organizational settings
where, for example, randomisation is not practical or ethical, or when an equivalent control group
(consisting of similar participants to the experimental group) is not available. Randomization can also be
considered a change in itself that may affect employee perceptions of the intervention and experiences of
work (Nabe-Nielsen et al., 2015). Furthermore, RCTs tend to focus on changes in outcomes and do not
evaluate how the quality of the implementation process or organizational context shapes the effects of an
intervention. In response to these concerns, alternative intervention evaluation frameworks have been
proposed. Cox et al. (2007) suggested a framework that covers both intervention outcomes and
implementation processes. Examples of implementation process variables include managers’ advocacy of
the intervention, workers’ engagement with the intervention, and the availability of resources to support
implementation. Cox et al. argued that consideration of process variables enables identification of the
mechanisms determining intervention outcomes. Indeed, failing to consider process variables could lead to
the erroneous conclusion that an intervention is ineffective when in fact the implementation was flawed.
Nielsen and Abildgaard (2013) built on these insights to propose a longitudinal evaluation framework in
which each of the intervention ‘stages’ (e.g., preparation, screening etc., as outlined earlier) are assessed
separately to identify how each stage may influence subsequent stages and ultimately the outcome of the
intervention. They also suggested that a range of intervention outcomes (e.g., changes in attitudes, working
practices and well-being) should be addressed at each stage on the basis that these changes may become
evident at different times.
Given the importance of intervention processes to the success of an intervention, and the limits of
RCTs in organizational settings, it has been argued that assessments of the effectiveness of SMI should
draw on systematic quantitative and qualitative evaluations and to include rigorous evaluations of SMI that
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do not meet the ‘gold standard’ of RCTs. Such an approach is thought to be particularly important in the
evaluation of organizational-level SMI because, in comparison with individual SMI that tend to use existing
techniques proven in other domains (e.g., CBT), organizational SMI are diverse in design and may be
tailored to the organization, increasing the likelihood of outcomes being influenced by process and context
variables. Indeed, in light of these issues, process evaluations are now more evident in SMI studies.
Evidence for Secondary Individual-Level Interventions
A number of meta-analyses and systematic reviews of the effects of secondary individual-level
interventions on stress and well-being have been conducted (see Bhui, Dinos, Stansfeld & White, 2012, for
a review of these reviews). Two of the more comprehensive meta-analyses are by van der Klink, Blonk,
Schene and Van Dijk (2001) and Richardson and Rothstein (2008) (Table 2). Both cover CBT and
relaxation interventions across all types of employees. The Richardson and Rothstein meta-analysis builds
on the van der Klink et al. study by covering an extra ten years of research and including unpublished
studies (accounting for publication bias towards significant findings) but has stricter inclusion criteria, as it
only selects RCT-based studies. A wide range of individual interventions are also covered by Kuoppala,
Lamminpää and Husman (2008) but their analysis focuses on ‘psychological’ (i.e., education,
biofeedback) and health promotion interventions (e.g., exercise), while the meta-analysis by Conn et al.
(2009) focuses exclusively on health promotion interventions, specifically exercise and physical activity.
Other meta-analyses focus on SMI in particular groups of workers. Ruotsalainen, Verbeek, Mariné and
Serra’s study (2015) covers CBT and relaxation methods in health care employees, while that by Regehr,
Glancy, Pitts and LeBlanc (2014) focuses on individual-level interventions in physicians.
A conclusion that can be drawn from these meta-analyses is that that there is good evidence that
secondary individual-level interventions are effective in reducing stress and promoting well-being (Table
2). Meta-analytic studies report significant medium and large effect sizes for cognitive-behavioral
therapies (d=0.52, van der Klink et al., 2001; d=1.00, Richardson & Rothstein, 2008), small and large
effect sizes for relaxation techniques (d=0.31, van der Klink et al., 2001; d=0.83, Richardson & Rothstein,
2008) and small effect sizes for health promotion methods (RR=1.25, Kuoppola et al., 2008; d=0.19, Conn
et al., 2009). These findings suggest that CBT has a comparatively larger effect on stress and well-being
and van der Klink et al., (2001) found that effect sizes for CBT were significantly greater than those for
relaxation methods. However, this finding must be treated with caution, as their analysis included effects
across all outcomes, including those unrelated to employee well-being. Furthermore, as there are no
comparisons between CBT, relaxation and other interventions, it is difficult to make claims about relative
effectiveness of secondary individual-level interventions at this juncture. It can also be noted that existing
meta-analyses of secondary individual-level SMI do not focus on mindfulness training as a separate
category, although mindfulness studies are included in some meta-analysis (e.g., Regehr et al., 2014). This
means that we lack a statistical summary of their effects and a comparison of mindfulness and other
methods. Promisingly, most primary studies report positive effects of mindfulness training on
psychological well-being (e.g., Cohen-Katz, Wiley, Capuano, Baker, & Shapiro, 2005; Hülsheger et al.,
2013), whereas only a few studies have failed to yield supportive evidence (e.g., Malarkey, Jarjoura &
Klatt, 2013; van Berkel, Boot, Proper, Bongers, & van der Beek, 2014).
Meta-analytic studies of multimodal secondary individual-level interventions report significant
medium effect sizes (d=0.48, van der Klink et al., 2001; d=0.60 and 0.42, Richardson & Rothstein, 2008).
These effect sizes are not substantially different to studies of single secondary individual-level SMI,
meaning that multimodal secondary individual-level SMI do not provide a clear advantage over single
secondary individual-level SMI. But it is worth noting that Richardson and Rothstein (2008) found that the
effects of multimodal SMI increase over time and their effects are longer lasting. One interpretation of this
finding is that employees take longer to learn stress management techniques in multimodal SMI but, once
learnt, their effects are stronger and more sustainable. Again, such a conclusion, while plausible, must be
treated with caution for present purposes, as the comparison by Richardson and Rothstein included wellbeing
and well-being related outcomes such as absenteeism and physiological responses.
Another important feature of research on secondary individual-level SMI is the heterogeneity and
direction of effect sizes. In particular, effect sizes vary significantly and, to the best of our knowledge,
almost all effects are positive in direction, even if they are non-significant. For example, in Van der Klink
et al.’s (2001) meta-analysis, effect sizes across CBT and relaxation interventions ranged from 0.0 to 2.2,
and 22 of the 35 studies reported non-significant findings. A similar heterogeneity in effect sizes is
reported in other meta-analyses of SMI and in the literature on mindfulness training. This implies that
although secondary individual-level SMI are not harmful to employee well-being, their positive effects are
not realised in all contexts. The heterogeneity in effect sizes therefore suggests that implementation
processes, contextual factors or participant differences (e.g., motivation, initial levels of well-being) may
impact on the efficacy of secondary individual-level SMI. However, a lack of research and contradictory
799
evidence prevent firm conclusions being drawn about the effects of context and implementation process on
secondary individual-level SMI effectiveness (Van der Klink et al., 2001; Richardson & Rothstein, 2008;
Rongen et al., 2013).
Table 2. Meta-Analyses of Stress Management Intervention Effectiveness
Intervention type Effect size
(Cohen’s d unless stated)
N Authors Date Outcome reported
Individual-Level
Cognitive-behavioral 0.52 Large 14 van der Klink et
al.
2001 Well-being
1.00 Large 5 Richardson &
Rothstein
2008 Well-being
-0.25 No effect 4 Ruotsalainen et
al.
2015 Stress (up to 1 month
follow up)
-0.28 Small 6 Ruotsalainen et
al.
2015 Stress (1-6 month follow
up)
Relaxation 0.31 Small 14 van der Klink et
al.
2001 Well-being
0.83 Large 5 Richardson &
Rothstein
2008 Well-being
-0.48 Medium 4 Ruotsalainen et
al.
2015 Stress (up to 1 month
follow up)
-0.49 Medium 13 Ruotsalainen et
al.
2015 Stress (1-6 month follow
up)
Health Promotion 1.25 (RR) Small 3 Kuoppala et al. 2008 Well-being
0.19 Small 12 Conn et al. 2009 Stress
Multimodal 0.48 Medium 8 van der Klink et
al.
2001 Well-being
0.60/0.42 Medium 5/12 Richardson &
Rothstein
2008 Well-being(low stress/low
anxiety)
Organizational-Level
All Organizational-
Level
0.08 No effect 5 van der Klink et
al.
2001 Well-being
-0.31/0.17 No effect 2/3 Richardson &
Rothstein
2008 Well-Being/Mental Health
Note: RR = Risk Ratio; Cohen’s d effect sizes, 0.2 = small, 0.5 = medium, 0.8 = large. Effect sizes are
uncorrected for reliabilities.
Evidence for Primary Organizational-Level Interventions
On the basis of existing meta-analyses, it could be concluded that primary organizational-level SMI
do not improve employee well-being or reduce stress. Drawing on small samples of primary and secondary
organizational-level interventions largely based on RCT designs, meta-analytic studies report small nonsignificant
effect sizes (d=0.08, Van der Klink et al., 2001; d= -0.31 for well-being and d=0.17 for mental
health, Richardson & Rothstein, 2008).3
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In contrast, qualitative reviews of organizational-level SMI, which draw on a wider range of
studies, including quasi-experiments without randomization, offer a ‘cautiously positive’ interpretation of
the effectiveness of well-designed organizational interventions (Bhui et al., 2012; Daniels et al., 2017;
Egan, Bambra, Thomas, Petticrew, Whitehead, & Thomson, 2007; LaMontagne et al., 2007; Semmer,
2006, p518). Moreover, since these reviews, other organizational interventions have been conducted that
further point to the positive effects of job redesign and social support interventions on employee well-being
(Ahola et al., 2012; Bourbonnais et al., 2006; LeBlanc, Hox, Schaufeli, Taris, & Peeters, 2007; Linzer et
al., 2015; Peterson et al., 2008; Sørensen & Holman, 2014). In particular, job redesign studies by Bond,
Flaxman and Bunce (2008) and Holman and Axtell (2016) show that job redesign interventions alter job
characteristics (e.g., job discretion, feedback) which in turn lead to improvements in employee well-being.
These studies therefore confirm theoretical proposals that changes in job characteristics are a mechanism
through which job redesign interventions influence employee well-being. Other studies point to the longterm
impact of job redesign interventions. Kawakami et al. (1997) and Bourbonnais, Brisson and Vézina
(2011) reported that improvements in job characteristics and well-being in the intervention group were
sustained, respectively, one and three years after the intervention.
For multimodal organizational-level SMI, qualitative reviews all conclude that there is some
evidence for their efficacy (Anger et al., 2015; Daniels et al., 2017; Egan et al., 2007; Kompier, Aust, van
den Berg & Siegrist, 2000). However, what is less clear is whether their different parts have combined or
additive effects on well-being, and whether they are more effective than potentially less-complex
organizational interventions that focus on changing one discrete practice (i.e., only job design).
Despite a growing evidence base for the positive effects of organizational-level interventions, the
continuing heterogeneity of their effects must be recognised, as some studies report no effect on well-being
(Ghazavi et al., 2010; Leiter et al., 2011; Logan & Ganster, 2005; Uchiyama et al., 2013) and a very small
number report negative effects (Ryan et al., 2005; Dahl-Jørgensen & Saksvik, 2005). One explanation for
this heterogeneity, as we have already noted, is that implementation processes and contextual factors
impact on the effectiveness of organizational SMI. In recognition of this, an increasing number of studies
of organizational SMI evaluate and report on the nature of the implementation process. For instance, a job
redesign study conducted by Dahl-Jørgensen & Saksvik (2005) across two different sites found that, in one
of the sites, emotional exhaustion increased in the experimental group six months after the end of the
intervention. Their qualitative process evaluation found that in this site the quality of the implementation
process was low (in part due to high work demands and low management support), that some employees
saw the intervention as a burden, and that other concurrent changes may have impacted negatively on
employee stress, such as increased workload.
More generally, the empirical literature on intervention implementation has helped to confirm
models of implementation processes outlined earlier (Cox et al., 2007; Nielsen et al., 2010). This literature
suggests that attending to and supporting process-related activities at key stages (e.g., preparation and
gaining support, screening for psychosocial risks, action planning, and implementation) can enhance the
quality of implementation processes by increasing implementation intensity (i.e., greater time spent on
intervention activities), providing support for employees (e.g., training in change process, communication
skills), securing the necessary resources and fostering the implementation of change (Daniels et al., 2017;
Kompier, Cooper & Guerts, 2000; Murta, Sanderson, & Oldenburg, 2007; Nielsen et al., 2010; Semmer,
2006; Sørensen, 2016), and fostering employee participation throughout all intervention activities
(LaMontagne et al., 2007; Nielsen, Randall & Albertsen, 2007).
In addition, evidence suggests that organizational and participant characteristics can shape SMI
effectiveness. For example, downsizing, poor management-employee relations and problematic HR
practices may reduce employees’ motivation to participate, prevent changes being implemented or
counteract the positive effects of an intervention, such that augmenting interventions with wider changes in
HR practices may be one means of reducing the risk of the organizational context impeding an SMI
(Daniels et al., 2017). However, a lack of research prevents firmer conclusions being drawn about the
effects of organizational context on SMI. With regard to participant characteristics (e.g., demographics,
traits and attitudes), although they might be expected to influence SMI outcomes, few studies have
systematically examined this issue (Egan et al., 2007; Rongen et al., 2013). The best evidence suggests
that work redesign interventions are more effective when participants have an openness and willingness to
change (Bond et al., 2008; Cunningham et al., 2002; Nytrø et al., 2000), make more positive appraisals of
the intervention itself (Nielsen et al., 2007), and have previous experience of participation in decisionmaking
procedures (Mikkelsen, Saksvik & Landsbergis, 2000). Motivated employees with the ability to
participate in change processes therefore appear important to the success of organizational-level SMI,
possibly because they are more likely to implement or respond positively to the types of change
underpinning these interventions.
801
Conclusion
Our review of stress management interventions shows that organizations and managers have at their
disposal a range of techniques and practices that can be used to reduce stress and promote the well-being of
employees. There is a relatively convincing evidence-base for the effectiveness of secondary individuallevel
SMI, especially CBT, relaxation techniques, and mindfulness training, and the strength of the
evidence base is growing for primary organizational-level interventions, particularly job redesign. Another
encouraging conclusion that can be drawn from existing research is that we are gaining a better
understanding of why interventions succeed, particularly that the success of organizational-level
interventions appears to depend on the quality of implementation processes and employee participation.
However, it is important to temper these positive conclusions with the fact that they may be skewed by
publication bias and that they are based on studies with a range of methodological limitations. Indeed,
there is a need to improve the quality of the evidence base on SMI by conducting more studies of higher
methodological rigour and not just RCT designs. Rather, studies are needed using broad evaluation
frameworks to assess quantitatively and qualitatively SMI outcomes and the effects of intervention
processes on SMI effectiveness. In addition, we also know relatively little about the contexts in which SMI
are most effective, particularly with regard to individual-level SMI, for which workers SMI are most
beneficial, and the relative effectiveness of interventions, particularly because studies do not use
comparable measures of well-being. Knowledge of these issues could help to target SMI more effectively
and provide practical support where needed. Finally, questions remain about the long-term impact of SMI,
as few studies assess the sustained benefits of SMI. Clearly, this has important implications for the
management of SMI. Do organizations conduct SMI infrequently and reap the long-term benefits, or is
sustained and continuing effort needed to ensure that well-being remains high?
Footnotes
1Authors' contributions were equal.
2For reviews of other SMI, such as tertiary individual-level interventions, see Csiernik (2011) and McLeod
(2008).
3Ruotsalainen et al. (2015) provide a meta-analysis of particular types of organisational intervention but the
sample sizes are very small and they provide no effect size based on all interventions.
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CULTURE
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Predictors of Subjective Well-Being Across Cultures
By Eunkook M. Suh & Soyeon Choi, Yonsei University
Citation
Suh, E. M., & Choi, S. (2018). Predictors of subjective well-being across cultures. In E. Diener, S. Oishi,
& L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
We provide an overview of well-documented factors that predict and explain national and cultural
differences in happiness. A brief history of the culture and happiness research is offered, followed by a
literature summary on how cultural variations in happiness is related with objective life conditions, lay
cultural beliefs of happiness, emotion patterns, characteristics of the self, and excessive concerns of social
evaluation in East Asian cultures. We also briefly comment on findings from the culture-person fit
research, and introduce recent biological and ecological papers that may point to new research directions
for the culture and happiness field.
Keywords: subjective well-being, culture, self, emotion
Culture, as famously remarked by Durkheim (1895), is in many ways like “air.” It permeates our
mind and has a profound influence on our beliefs, feelings, values, and concerns about tomorrow. Yet, like
air, culture rarely enters into our consciousness. It shapes our mind so thoroughly and naturally that being
aware of its omnipresent influence on our mind is usually difficult.
This “invisible” culture started to draw the attention of subjective well-being (SWB) researchers in
the early 1990s, the period that roughly overlapped with the publication of landmark papers on culture and
self (e.g., Markus & Kitayama, 1991; Triandis, 1989). Important empirical foundations were laid, raising
excitement and justifications for the study of culture and happiness. For instance, significant mean
differences in happiness found between nations could not be attributed to simple methodological artifacts
(Diener, Suh, Smith, & Shao, 1995), and longstanding determinants of happiness found in Western
samples, such as self-esteem, were surprisingly weak predictors in non-Western samples (Diener & Diener,
1995). An edited volume (Diener & Suh, 2000), an Annual Review of Psychology article (Diener, Oishi, &
Lucas, 2003), and a special issue of the Journal of Happiness Studies (Suh & Oishi, 2004) were devoted
exclusively to the topic of culture and SWB. These works, in a sense, sprayed color to the once invisible
culture, carving an exciting new niche in happiness research.
Now, most researchers find it quite obvious that culture plays a critical role in shaping virtually
every aspect of happiness—how happiness itself is conceptualized, which life experiences are prioritized,
how they are combined into an overall happiness judgment, preferred type of happiness state (low versus
high arousal), to name a few. In addition to the development of more sophisticated research questions,
lately, an unprecedented amount of large international datasets released by research organizations (e.g.,
Gallup, World Values Survey) have become available for happiness researchers. Thanks to these changes,
cultural and national difference has now become a vibrant research field in happiness.
Given the huge volume of accumulated studies, our review of this topic is inevitably selective.
While trying to maintain a balance between classic and recent research, this chapter focuses more on wellreplicated
cultural predictors of SWB that have been particularly informative for happiness researchers. We
also suggest possible future directions for the culture and SWB research to expand, including more
systematic consideration of ecological and biological factors.
Objective Conditions
One ongoing debate on cultural/national differences in happiness is whether growth in national
wealth leads to increase in happiness. The spark of this debate dates back to Easterlin (1974), who
proposed that while wealthier nations are generally happier than poorer nations, national income does not
directly translate into more happiness after a certain point (see Easterlin, McVey, Switek, Sawangfa, &
Zweig, 2010, for a review). In contrast, some researchers have shown opposing evidence that economic
growth and happiness do go together. For instance, Deaton (2008) found from the Gallup World Poll that
highest levels of well-being are found in Western European countries (especially Scandinavia), North
America, Australia, and New Zealand, countries characterized as having many desirable objective
conditions, such as wealth, good education, and political stability (e.g., for national differences, see Diener,
Kahneman, & Helliwell, 2010; Diener & Suh, 1999; Hagerty & Veenhoven, 2003; Helliwell, Layard, &
Sachs, 2016).
808
In response to this debate, recent studies that analyzed the Gallup World Poll data have suggested
that economic conditions are correlated discriminately with SWB measures. That is, some type of objective
measures correlate with some types of SWB but not with others. Across 132 countries, economic
conditions (such as national income and public resources) were positively associated with the cognitive
evaluation of one’s life, but only weakly associated with emotional well-being (Diener, Ng, Harter, &
Arora, 2010). In other words, people living in wealthier nations “think” they are happy, but not necessarily
“feel” more positive emotions than those in poorer nations. A follow-up study even found that for the same
level of personal income, people living in richer countries felt angry and worried more frequently (Tay,
Morrison, & Diener, 2014). Overall, emotional well-being was largely predicted by personal factors rather
than societal conditions. Positive feelings were dependent on psychosocial factors, such as social support,
respect, and autonomy. Negative feelings were explained by both societal and personal factors (Diener et
al., 2010; Ng & Diener, 2014; Tay & Diener, 2011).
Some researchers argue that both the volume of national wealth and the psychological factors that
accompany it matters (see Diener, Oishi, & Lucas, 2015; Diener, Tay, & Oishi, 2013; Oishi & Schimmack,
2010). For instance, Oishi & Kesebir (2015) found that economic growth prompts increase in happiness
when income is evenly distributed, but not when income inequality is high. They speculate that heightened
sense of unfairness and social comparison may be the reason behind this phenomenon (see also Eksi &
Kaya, 2017; Schröder, 2017). It is also found that progressive taxation is positively associated with SWB of
nations (Oishi, Schimmack, & Diener, 2012).
However, it should be also noted that economic indices might shadow the effects of various positive
social qualities on happiness that correlate with national wealth. It has been found in some dataset that
national affluence raises happiness only through its effect on freedom, individualism, or democracy (Dorn,
Fischer, Kirchgässner, & Sousa-Poza, 2007; Fischer & Boer, 2011; Inglehart, Foa, Peterson, & Welzel,
2008), prompting the need to “unpackage” wealth and find what precise elements of economic affluence
contribute to the SWB of nations.
Lay Beliefs of Happiness
What is happiness, and what are the ingredients of it? The popular answer held by the average
person varies much by culture. For instance, the definitions of happiness from dictionaries of 30 countries
showed that some cultures focused more on external conditions or fortune, whereas others put more
emphasis on positive internal feelings (Oishi, Graham, Kesebir, & Galinha, 2013).
Lay beliefs about happiness are often contrasted between collectivistic and individualistic samples.
For example, when asked to indicate important criteria of a good and worthy life, Chinese focused on
external and practical components, such as wealth and social status, whereas European Canadians chose
more internal and private concerns, such as the self’s positive impact on the world (Bonn & Tafarodi,
2013). There are also variations in the sense of agency. A thematic analysis revealed that collectivistic
South Africans described happiness more on a societal level, such as social harmony and family ties, while
Germans defined happiness more on a personal level, such as personal freedom and pleasure (Pflug, 2009).
Similarly, Japanese people associated happiness with social balance, whereas Americans associated it with
personal accomplishments and hedonic pleasure (Uchida & Kitayama, 2009).
Although cultural difference in lay beliefs of happiness has been examined by a wide array of
studies, one common methodological weakness is that most of the responses are obtained through a
structured questionnaire format. The questionnaire items in many cases are pre-selected by the researcher in
reference to existing theories or well-established empirical findings. Merely given the option of either
agreeing or disagreeing with questionnaire items, participants have little room to express their spontaneous
beliefs about happiness. Consequently, by design, such studies tend to obtain theory-confirming results
about happiness beliefs rather than novel insights.
To overcome this limit, in one recent study (Shin, Suh, Eom, & Kim, 2017), Korean and American
participants are asked to write three words that immediately come to their minds when they think of
“happiness.” Regardless of cultural background, individuals who mentioned more words related with social
relationships or relational concepts (friendship, love) were happier than others. However, interesting
cultural differences were also found at a more detailed level. For instance, the most commonly associated
word with happiness in Korea was “family” (13% of all responses), whereas affective states or expressions,
such as “smile,” and “laugh” topped the list (11% of responses) in the US. The most central type of
relationship linked with happiness also differed. Whereas ascribed, in-group relationships (family) were
nominated prominently in Korea, American respondents more often linked self-chosen social connections
(romantic partner, friend) with happiness. Although social experiences are believed to be commonly
important in both cultures, the type of relationships through which this need is fulfilled seems to show
cultural variation.
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Besides different beliefs on the content of happiness, cultures also vary in how desirable they think
happiness is. In the US, for instance, people generally hold a glowing view of a “happy” person. A happy
person, compared to a less happy person, is viewed not only to be more desirable, but even more likely to
go to heaven by Americans (King & Napa, 1998). However, not all cultures are as enthusiastic about
happiness. In some cultures, people are ambivalent about being overly happy, because happiness is
believed to be followed by unhappiness at the end (Ji, Nisbett, & Su, 2001).
Also, the common Western belief that happiness is an inalienable right and a product of an
individual’s action appears less strongly among those brought up in East Asian or Islamic cultures (Lu &
Gilmour, 2006; Joshanloo, 2013). Reflective of this contrasting cultural attitude, it has been suggested that
Western cultural members might implicitly feel a certain degree of “pressure to be happy” (Suh, 2000),
whereas some degree of “aversion to happiness” may exist in non-Western cultures (Joshanloo & Weijers,
2014).
Cross-cultural stereotypes about a “happy” person align with this difference. Choi, Suh, & Shin
(2017) asked respondents from 45 nations to imagine overhearing a person who claims to be extremely
happy and satisfied with life. Then, they were asked to guess how well various positive (e.g., warm, moral)
and negative (e.g., arrogant, selfish) personality traits might characterize this self-proclaimed happy person.
As expected, culturally held stereotypes about a happy person’s character differed considerably across
cultures. Although this stereotype was highly positive in cultures that report high levels of happiness (e.g.,
US, South America), in certain regions, people were underwhelmed about the happy person. For instance,
in Japan, a nation that reports low happiness in comparison to its economic level, people believed that the
imaginary happy person is more likely to possess negative (e.g., selfish, shallow) than positive personality
traits. Across countries, how positively people thought about a happy person (indexed by subtracting the
estimated likelihood of possessing negative from positive traits) significantly predicted the actual happiness
level of each nation. This correlation remained even after controlling for relevant factors, such as emotion
norms, resentment towards expressing happiness, individualism, and gross domestic product (GDP).
Most recently, an interesting argument has been proposed as to why cultures vary in their
desirability judgments about happiness. Koh and her colleagues (2017) claim that one factor that sets apart
cultures that strongly value happiness from those that value it less is the level of pathogen threat
historically present in the environment. The high social nature of a happy person, although it has various
positive assets in low pathogen regions, may inadvertently increase the chance of bringing infectious
diseases through active social interactions. In high pathogen regions, people might have been reinforced to
de-value traits or emotions (happiness) associated with exploration and contact of strangers. This
hypothesis was not only supported in laboratory experiments, but interestingly, even predicted the voting
pattern of nations in the United Nations (UN) General Assembly meeting regarding an international
happiness resolution (adopting happiness as a national guide for policy). As predicted, UN member states
that sponsored this resolution had a significantly lower level of pathogen than non-sponsoring states.
Studying lay beliefs of happiness across cultures goes beyond gratifying academic curiosity. Certain
beliefs held by the person about happiness, and how much she values it actually make a difference in how
happy she is. For instance, people’s belief on whether the total amount of happiness they will experience in
life is predetermined and “fixed” or “infinite” leads to divergent habits and choices related with happiness.
Importantly, the fixed-amount theorists were significantly less happy with their lives (Koo & Suh, 2006),
controlling for personality factors. There is also the finding that in countries where positive emotions are
highly valued, people report higher life satisfaction and experience more positive emotions (Bastian,
Kuppens, De Roover, & Diener, 2014).
Emotion
A defining aspect of emotional well-being is the relative frequency of positive over negative affect
(Diener, Suh, Lucas, & Smith, 1999), which has led to a heavy focus on the affective dimension of valence
(positive or negative) in happiness research. Thanks to cross-cultural research, psychologists now recognize
that there are other dimensions of positive affect that are relevant for understanding happiness (Tsai, 2007).
For instance, Euro-Canadians highly value high activation positive affect (HAP), such as excitement and
elation, whereas Chinese and Japanese value low activation positive affect (LAP), such as calmness and
serenity (Ruby, Falk, Heine, Villa, & Silberstein, 2012).
This cultural variation in ideal positive affect causes a difference in the link between positive
emotion and happiness. Researchers found that the discrepancies between ideal and actual HAP led to poor
mental health for European Americans and Asian Americans, but not for Hong Kong Chinese (Tsai,
Knutson, & Fung, 2006). By contrast, discrepancies between ideal and actual LAP led to poor mental
health for Asian Americans and Hong Kong Chinese, but not European Americans.
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In addition to valence and arousal, Kitayama and colleagues (e.g., Kitayama & Markus, 2000;
Kitayama & Park, 2007) suggest that the happiness of Japanese and Americans also relate differently with
another pole of positive emotion—Japanese centered more on socially engaged (feelings of closeness to
others, friendly feelings) emotions, whereas Americans rely more on socially disengaged (pride and
feelings of superiority) emotions. Related to this difference, it is reasoned that the pursuit of happiness
itself may lead to different outcomes between cultures. According to Ford et al. (2015), motivation to
pursue happiness predicted lower well-being in the US, whereas it predicted higher well-being in Russia
and East Asia. The authors attribute this difference to the possibility that collectivistic cultural members
tend to pursue happiness in more socially engaging ways than individualistic cultural members.
Cultures also differ in their beliefs about the relation between positive and negative affect. In
general, East Asians have a more dialectic view than Western cultural members; therefore, they are more
likely to believe that events or experiences that seemingly contradict can co-occur (Peng & Nisbett, 1999).
As a result, European Americans tend to have fewer mixed emotional experiences (feeling bad and good at
the same time) than East Asians (e.g., Miyamoto, Uchida, & Ellsworth, 2010; Shiota, Campos, Gonzaga,
Keltner, & Peng, 2010), a pattern mediated by dialectical beliefs (Spencer-Rodgers, Peng, & Wang, 2010).
Some have employed this dialectic script to explain cultural differences in emotion regulation, such as the
dampening or savoring of positive emotions (Miyamoto & Ma, 2011) or why people try to maximize
positive emotion and minimize negative emotion more strongly in one culture than another (Sims et al.,
2015).
Another widely replicated finding concerns cultural difference in the use of affect in overall
judgments of happiness (Kuppens, Realo, & Diener, 2008; Schimmack, Radhakrishnan, Oishi, Dzokoto, &
Ahadi, 2002; Suh, Diener, Oishi, & Triandis, 1998). The “affect-as-information” theory (Schwarz & Clore,
1983) has suggested that people use their momentary mood as a heuristic cue for making various
evaluative judgements, including life satisfaction. Research has found that this phenomenon occurs more
reliably among individuals who chronically view themselves as an independent being than those who
construe themselves as an interdependent person.
This pattern is found between cultures as well as within a culture as function of one’s self-view. For
instance, when Americans are primed of the relational aspects of self, they tend to base their life
satisfaction judgment quite heavily on others’ evaluations of their lives (the typical collectivistic pattern);
conversely, Koreans primed on their unique aspects of the self shifted their attention to inner emotions
(individualistic pattern) during life satisfaction judgment (Suh, Diener, & Updegraff, 2008). Thus, the type
of information used in constructing global self-judgments of happiness seem to systematically differ
between cultures, depending on whether the autonomous, unique aspects of the self versus the
fundamentally socially embedded nature of the self are stressed. This difference is also observed with
implicit measures. In an association-judgment task, European Americans who were satisfied with their lives
associated happiness with more positive emotion words, but this pattern was not found for Koreans and
Asian Americans (Koo & Oishi, 2009).
Emotion norms that have implications for both the experience and expression of happiness also vary
between cultures. In general, in non-Western cultures, positive emotions (happiness) are valued less,
whereas negative emotions are believed to have important functional values, compared to highly
individualistic cultures, (e.g., Eid & Diener, 2001; Joshanloo et al., 2014; Oishi et al., 2013). Although
national differences in SWB are not completely explained by difference in emotion norms, researchers
need to be aware of their influence. For instance, according to a recent finding by Sheldon et al. (2017),
Russians (compared to Americans) reported a greater inhibition in the expression of happiness to strangers.
Interestingly, the greater happiness inhibition to strangers was unrelated with the experienced happiness of
Russians, but negatively predicted the happiness level of American samples (see also, Soto, Perez, Kim,
Lee, & Minnick, 2011). In this study, the self-reported SWB level between the two cultural groups did not
differ, suggesting that the size of the discrepancy between experience and overt expressions of happiness
may differ across countries.
Importance of the Self: High Esteem, Consistency, and Clarity
Cultures also differ in how important the self is for SWB (for review, see Suh, 2000). Having a
positive belief about one’s overall self seems to matter more for the happiness of individualist than
collectivist cultural members. Following Diener and Diener’s (1995) groundbreaking paper on cultural
difference in self-esteem and life satisfaction, studies have repeatedly found that self-esteem is a stronger
predictor of happiness in Western than Asian cultures (Uchida, Kitayama, Mesquita, Reyes, & Morling,
2008; Yuki, Sato, Takemura, & Oishi, 2013). It appears that the positive aspects of the internal self strongly
determine the person’s overall happiness in the West, whereas the relational tone between the self and other
significant selves (e.g., family) seem to be more salient for the well-being of collectivist cultural members.
811
One of the first empirical demonstrations of this difference was by Kwan, Bond, and Singelis (1997), who
found that compared to the US, the relative importance of relationship harmony to self-esteem was greater
in Hong Kong.
Having a clear, and consistent idea of oneself also seems to matter more in individualistic than
collectivistic cultures. People who have an inconsistent self-concept across social situations have lower life
satisfaction and affective well-being, but this relationship is weaker in collectivistic cultures, where being
flexible to situational demands is highly appreciated by others (Bleidorn & Ködding, 2013; Church et al.,
2014; English & Chen, 2011). For instance, Suh (2002) found that Koreans are less consistent in rating their
personality across social roles, and this degree of inconsistency had a smaller association with SWB,
compared to North Americans. In Korea, a more important predictor of SWB than consistency was how
individuals believed their life was evaluated by significant others (perceived social appraisal). In a similar
vein, Oishi, Diener, Scollon, and Biswas-Diener (2004) found that the within-person variability of affect
across situations (e.g., the effect of being with a romantic partner versus stranger on positive affect) was
greater among Japanese and Hispanic students than European Americans. Also, it is found that the
relationship between clarity of one’s feelings (being able to describe one’s feelings accurately) and SWB
was stronger in more individualistic countries (Lischetzke, Eid, & Diener, 2012).
Broadly speaking, happiness in collectivist cultures seem to depend less on private and personal
aspects of the self, but more on relational and even distal societal factors. This might be because the inner
self seems to be a more pivotal anchor of psychological experience in individualistic than collectivistic
cultures (Suh, 2000). Conversely, how well one’s family, group or country might be doing might matter
more for collectivists. A study by Morrison, Tay, and Diener (2011) illustrates this point. Although
personal factors are prime predictors of happiness in Western countries, they found that the overlap
between satisfaction with one’s country (national satisfaction) and personal satisfaction becomes larger in
collectivist nations.
Concern for Social Approval and Conflict
If the inner state of the self is a crucial predictor of happiness in the West, how the self’s exterior
layer is evaluated and recognized by others is critical for the happiness of East Asians. This is because East
Asians and other collectivist cultural members, chronically vigilant of their value as a social member, are
far more likely to adopt a third-person perspective about themselves than European Americans (Cohen &
Gunz, 2002). How I am “seen” by others are in many cases more important to a collectivist person than
how the world subjectively appears to her. Such thinking extends to various realms of life, and creates
several cultural variations in link to happiness.
For one, the “good life” is visualized somewhat differently. For instance, the individual’s perceived
social image predicts life satisfaction beyond the effects of emotions and personal achievement in India and
Pakistan, but not among White British and European Americans (Rodriguez Mosquera & Imada, 2013). In
comparison of how the good life is viewed by mainland Chinese and European Canadians, Bonn and
Tafarodi (2013) conclude that one of the key difference is the “focus of concerns”—tending towards either
inner/personal versus socially defined goods. The Chinese sample, for instance, was more likely to
emphasize security, wealth, and social success (status) in their visions of a desirable life than the European
Canadians. The latter group focused on less concrete and practical factors, such as meeting one’s inner
potential.
Since being acknowledged by others is easier when the person possesses something easily visible or
quantifiable, collectivistic cultural members put much effort to embellish the external aspects of the self.
This explains why money is strongly believed to be critical for happiness, even in highly affluent East
Asian societies. In one study, Singaporeans, but not Americans, expected that a person with a higher
income would be more likely to have a high-quality life than a person with lower income (Wirtz & Scollon,
2012). Compared to the US, extrinsic goods (e.g., money, physical appearance) are stressed more by
Koreans, a pattern that partly explains the happiness difference between the two countries (Koo & Suh,
2015). In a similar line, objective social status (education) is more strongly associated with happiness
among Japanese than Americans, whereas subjective social status is more strongly associated with
happiness among Americans than Japan (Curhan et al., 2014). The authors’ interpretation is that the
Japanese trust objective markers that others can see more, while Americans trusted their own judgments.
Using a more common psychological term, the contingency of self-worth (Crocker & Wolfe, 2001)
seems to differ between cultures. It is found that between Eastern and Western cultures, other’s approval
contingency of self-worth (CSW) is notably different, which mediates the happiness difference between
Taiwan and US samples (Liu, Chiu, & Chang, 2017). It suggests the possibility that East Asian’s selfjudgments
of happiness could be more prone to fluctuations, depending on the tone of social feedback. This
appears to be the case. In one study, Korean and American college students were asked to describe a recent
812
pleasant event and rate how happy they felt during the experience (Choi, 2013). Several weeks later, the
participants rated once again how happy they felt about the same event they wrote earlier, after receiving
bogus feedback that other people either agreed (also thought the event was fun) or disagreed (thought the
event was rather boring) with them. Interestingly, the Koreans’ evaluations of the self-nominated happy
event changed as a function of others’ approval or disapproval, whereas Americans did not. It implies that
even the hedonic evaluation of a highly personal experience is affected by other’s evaluation in
collectivistic Asian cultures.
A flipside of this heightened social sensitivity is that East Asians are much more concerned about
potential damages to their social image than Western cultural members. As such, some active and
promotive social gestures that benefit happiness are less pursued, in fear that they may instigate negative
reactions. A good example is, contrary to what might be expected from cultural stereotypes, East Asians are
in general less likely to seek social support from others than European Americans (Kim, Sherman, &
Taylor, 2008). This is because Asians are more concerned about the negative relational consequences of
help seeking, such as stressing the support provider or being viewed as an incompetent person. One recent
cross-cultural paper finds a highly similar pattern occurring in the link between capitalization and
happiness (Choi, Oishi, Shin, & Suh, in press). Koreans, compared to Americans, were more hesitant to
celebrate positive events (capitalization attempts) with others because of possible relational costs (e.g.,
being seen as immature, inappropriate).
The East Asians’ excessive concern of other’s view might be a key psychological reason for why
their happiness level is lower than expected by economic indices (Suh, 2007; Suh & Koo, 2008). It may be
the common underlying cause of several interrelated phenomena that are known to be detrimental for
happiness: a) being more focused on external, materialistic aspects of happiness, b) not being able to create
and use idiosyncratic standards for self-judgment, which is an essential strategy for maintaining selfenhancing
views (cf. Dunning & McElwee, 1995), c) being oriented more towards preventive than
promotive decisions in everyday life.
Culture-Person Fit Issue
One popular conceptual framework employed in explaining happiness across cultures is the culturefit,
or the culture-person matching hypothesis. The key idea is that, other things equal, the person is happier
when her personal characteristics (personality, value, emotion) resembles the dominant practices or values
of the residing culture.
Because cultures differ in emotion norms, the degree to which an individual’s emotion experience
pattern fits with the social norm could matter (cf. Gruber, Mauss, & Tamir, 2011). Using an implicit
measure of cultural fit of emotions, De Leersnyder, Mesquita, Kim, Eom, and Choi (2014) recently found
across US, Belgium, and Korea that individual’s level of emotion fit with the culture’s average emotion
profile across social contexts (e.g., with family, friends) predicted relational well-being.
Fulmer et al. (2010) found that the relationship between an individual’s personality and SWB is also
strengthened when the individual’s personality matches the common personality type in the culture. In a
society where extraverts were prevalent, culture boosted the positive effect of extraversion on happiness.
Furthermore, researchers showed that while civic virtue is usually positively associated with happiness,
virtuous individuals were not happier than selfish individuals in cultures where transgressions are common
and easily justified (Stavrova, Schlösser, & Fetchenhauer, 2013). A similar pattern has been examined in
the domain of personal and national religiosity (Diener, Tay, & Myers, 2011).
Despite the popularity of the culture-person fit idea, strong versions of this argument may lead to
cultural relativism, possibly undermining the pan-cultural, universal elements of human happiness. Few
would recommend a person who lives in a highly totalitarian society, for the sake of culture-person fit, to
give up personal autonomy as a strategy for increasing happiness. In fact, there are findings that challenge
the fit notion. According to the fit theory, the happier Koreans should be the ones whose personal values
align with strong collectivistic ideals. This was not the case (Kim, 2012). Even in Korea, individuals who
valued autonomy and enjoyed typical individualistic experiences (e.g., feeling unique) were happier than
the more culturally fitting counterparts, especially among the affluent group.
Newcomers: Ecological and Biological Factors
Thus far, this chapter has reviewed cultural differences in predictors of happiness mainly using the
framework of individualism and collectivism. However, this dichotomous cultural contrast offers little
insight to why the different regions of the world came to adopt certain cultural values in the first place.
Before concluding, it is worth a brief overview of some emergent findings relevant with happiness that
explore the role of ecological and biological factors. This approach might offer some fundamental insight
about the origins of cultural variation, and how SWB is related to such non-psychological factors.
813
As for ecological factors, a group of scientists claim that the historic prevalence of pathogens in the
local environment leads to the emergence of individualism and collectivism (Fincher, Thornhill, Murray, &
Schaller, 2008; Murray & Schaller, 2010). The claim is that central features of collectivism, such as strong
in-group favoritism or conformity, developed as a group-level psychological response to inhibit the
transmission of pathogens. This parasite-stress is claimed to increase in-group assortative sociality, which
is culturally expressed in the form of strong family ties (Fincher & Thornhill, 2012). As mentioned, in line
with this argument, Koh et al. (2017) found through a series of studies that happy individuals are viewed
less positively in high pathogen regions, presumably because the behavioral features associated with
happiness (e.g., risk-taking, novelty seeking) increase the spread of disease.
Another ecological factor that may influence perceptions of happiness is resource scarcity. Being
somewhat complacent and optimistic about one’s surrounding is more acceptable when the environment is
safe and resource is abundant. However, this free-spirited attitude may become problematic when an
immediate change or improvement of the situation is required, as when food or other crucial survival
resources need to be replenished. Probably for this reason, a recent study finds that resource scarcity leads
to a more negative perception of a happy person (Shin & Suh, 2017).
Climate has also been associated with well-being (Rehdanz & Maddison, 2005). Harsh climates (hot
summers and cold winters) negatively predict SWB. In an analysis of 58 countries, Fischer and Van de
Vliert (2011) showed that demanding climates predict ill-being in poor nations but not in wealthy nations,
because resources buffer the negative effects of climate. Coming from a more evolutionary angle, Li &
Kanazawa (2016) found that population density is negatively correlated with life satisfaction. The authors
explain that when group size and population density becomes higher than what was common in our
ancestral environment, people are likely to be stressed out more easily.
One of the latest newcomers to the study of culture and happiness are recent work on genes. In one
study, researchers reported that people in collectivistic cultures are more likely to carry short allele of the 5HTTLPR
than individualist cultural members (Chiao & Blizinsky, 2010). Interestingly, a culture-gene
coevolution was found. That is, the frequency of short allele carriers lowered the prevalence of affective
disorders, and increased collectivism mediated this relationship. Another recent study reports that national
percentages of people with high positive affect were correlated with the national prevalence of the
rs324420 A allele in the FAAH gene (Minkov & Bond, 2017). Although most of the current findings on
genetic and ecological factors are highly tentative, they shed light on a host of new factors that were once
completely outside the attention span of happiness researchers.
Conclusion
Although cultural variations clearly exist, we would like to simultaneously stress that there are
undeniably universal aspects of well-being. So far, research has not yet found any single country in which
happiness correlates in a reverse direction with well-known predictors of happiness—income, extraversion,
positive affect, etc. Even in collectivist cultures where inner emotions seem to play a less defining role in
happiness, for instance, the correlational direction is similar to other countries. Hence, appreciating the
cultural variance in happiness is important, but not to the extent of obscuring the universal aspects of
human well-being.
One of the most pressing research needs is gaining a more in-depth understanding of how and why
the culture-specific beliefs and practices of happiness arise. This would require researchers to go beyond
cataloguing surface differences between regions, and make creative, theory-driven speculations on what
underlying adaptive functions the different cultural contours of happiness might serve. Culture is created
by humans, who are not exceptions to the basic evolutionary principles (Hill & Buss, 2008). Basic
evolutionary needs, such as safety or social belongingness, are pursued in a widely different manner by
two individuals who differ in personality, values, and habits. Likewise, the different cultural shades of
happiness, influenced by ecological constraints and historical factors, might merely be different scenes seen
from multiple paths. They are all likely headed toward a common destination—securing essential needs for
survival and reproduction (social respect, belongingness, resource).
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Subjective Well-Being in Nations
By Ruut Veenhoven, Erasmus University Rotterdam, Netherlands, Erasmus Happiness Economics
Research Organization and North-West University, South Africa, Optentia Research Program
Citation
Veenhoven, R. (2018). Subjective well-being in nations. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
Subjective well-being is a main goal in modern society, thus it is worth knowing 1) how subjective wellbeing
differs across nations, 2) how it develops over time, 3) what the determinants of subjective well-being
in nations are and 4) what the consequences of more or less well-being are. In this chapter, I focus on one
particular aspect of subjective well-being, that is, life-satisfaction. I take stock of the research on this
matter, drawing on the World Database of Happiness. This reveals the following patterns: a) lifesatisfaction
differs much across nations, b) average life-satisfaction has risen over the past decade in most
nations, while inequality in life-satisfaction in nations decreased, c) several societal determinants of lifesatisfaction
have been identified, many of which are part of modernity, and, d) high life-satisfaction in a
nation has several positive effects and pursuit of greater happiness fits as such with wider policy aims.
Keywords: happiness, life-satisfaction, subjective well-being, comparative, cross-national, policy
implication
Why This Topic?1
All humans want a satisfying life for themselves and their children and this appears in high
rankings of happiness in the value hierarchy of students all over the world (Diener, Suh, Smith, & Shao,
1995). Individually, people seek ways to a more satisfying life and, in Western societies, this quest
manifests in soaring sales of ‘how-to-be-happy books’, such as ‘The art of happiness’ by the Dalai Lama
(1998). It also reflects in the development of life-coaching businesses. Citizens in western societies call on
governments for improvement of what they consider to be required social conditions, 85% of the British
agree with the statement that ‘a governments prime aim should be achieving the greatest happiness of the
people, not the greatest wealth’ (BBC 2006, question 14).
Consequently, interest in subjective well-being is rising among policy makers; it is a new topic on
the political agenda, along with sustainability. The international conference on Happiness and Well-being
held at the UN headquarters in New York in April 2012 (Thinley, 2012) is a recent manifestation of this
trend. The subsequent decision of the General Assembly in June 2014, to celebrate an ‘International Day of
Happiness’ on March 20 every year, illustrates its importance.
Information Needs
This call for greater well-being creates a demand for information. Policymakers seek answers to the
following questions.
Is greater well-being in the country possible? Policymakers will hear some experts say that
pursuit of greater happiness for a greater number is pointless. A common argument is that subjective wellbeing
depends on comparison with compatriots, and that relative differences do not change when absolute
conditions improve for everybody in the country (e.g. Brickman & Campbell, 1971). Next, there is the
theory that subjective well-being depends very much on ‘national character’, which is rooted in historical
conditions, such as the many revolutions in France, which have created a cynical view on life among the
French, as Inglehart (1990, p. 30) suggests. The first thing a government needs to know is whether
subjective well-being in nations is immutable.
How does the country do well-being wise? Once it is clear that average subjective well-being in a
nation can change, the next step is to estimate the chances for creating greater well-being in one’s own
country. This requires a view on how well people currently feel in your country, which calls for survey
studies. The next step is comparison, both comparisons of present day sense of well-being with subjective
well-being in earlier times in one’s country and with subjective well-being in other countries. Governments
can then see how their country is doing well-being-wise on a range between the highest and lowest levels
ever observed in other nations.
Since most governments are also concerned about equality among their citizens, they are also
interested in dispersion of subjective well-being in their country, and how this compares to inequality in the
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sense of well-being in other nations.
Can governments do much about how well citizens feel? If the level of well-being in a country
lags behind the possible level, the next question is whether a government can change that situation for the
better. In this context, a first question is to what extent the differences in subjective well-being are in things
that are beyond the control of governments, such as a prevalence of depressive genes in the population,
poor climatic conditions or historical legacies.
If subjective well-being in a country appears to depend on things that can be changed, the next
question is whether a government can bring about that change. This is the question of limits to social
engineering. In this context, it is worth knowing how other governments have fared in their attempts to
improve subjective well-being in their countries: Have they made any difference or have attempts to create
a better society mostly resulted in the opposite as critics of utopian engineering suggest (e.g., Avery,
2000)?
What can governments do to foster subjective well-being? If a government decides to pursue
greater subjective well-being in their country, the next question is where to start. In this context, a
government typically wants to know whether there are pockets of misery in their countries, or actually,
whether there is any truth in the claims about subjective ill-being in particular categories of citizens
advanced by organized advocacy.
Taking a broader view, governments would like to know what the drivers of differences in
subjective well-being among citizens are: in particular, to what extent these correspond with things over
which a government has some control, such as income, schooling, health care and safety. Again, this
typically involves the sifting of competing claims of special interests, presented by lobbyists. Interior
struggles also call for information about winners and losers of particular policies, for example, whether the
emancipation of women will come at the expense of the well-being of men and children.
In an even wider perspective, which some governments take, questions about societal conditions
for happiness arise. What are the secrets of the happiest countries, such as Denmark? Are they in
institutional things such as a strong welfare state? Are they found in the political regime, such as interest
groups having much voice? Or is the high level of happiness due to particular policies, such as promotion
of equal rights for men and women? What is the role of the well-being professions, such as psychologists
and life-coaches?
How compatible with other policy aims? Subjective well-being is only one of the aims states
pursue and typically not a very prominent one. This begs the question of how well the pursuit of greater
subjective well-being fits major policy aims, such as economic competitiveness, political democracy and
social peace. In this context, one question is to what extent the things required for greater subjective wellbeing
will also add to these causes, such as schooling adding to both subjective well-being and economic
growth. Or, how the question is put most of the time, to what extent do the things government does anyway
for other causes also add to subjective well-being.
A related question is what will be the consequences of greater subjective well-being: will it foster
decadence and decay, as some prophets of doom predict, like Huxley (1932), who depicted happy citizens
as shortsighted consumption slaves. Or will a happy populace be more productive, democratic and peace
minded, as is now commonly assumed in positive psychology? These contradictory speculations call for
empirical assessment.
Plan of This Chapter
In this chapter I explore the knowledge required to answer these questions. I start with a conceptual
analysis and focus on subjective well-being in the sense of life-satisfaction in section 2. I describe how that
concept is measured in section 3. Next, I provide an overview of the research findings on differences in
life-satisfaction across nations in section 4. I review the determinants of these differences in section 5. I
consider the consequences of more or less happiness in nations in section 6 and present an agenda for
further research in section 7.
What ‘Well-Being’?
When used in a broad sense, the term ‘well-being’ is synonymous with 'quality of life' or with
'happiness’ when used in philosophy. In this meaning, well-being denotes that a life is good, but does not
specify what is good about that life. The word ‘well-being’ is also used in more specific ways, and these
meanings can be clarified with the help of the classification of qualities of life presented in Scheme 1.
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Four Kinds of Well-Being
Vertically in Scheme 1, there is a difference between chances for a good life and actual outcomes
of life. Horizontally, there is a distinction between external and internal qualities. Together, these two
dichotomies mark four qualities of life, all of which have been denoted by the term 'well-being'.
Livability of the environment. The left top quadrant denotes good living conditions. Economists
sometimes use the term 'welfare' to indicate this meaning. 'Livability' is a better word, because it refers
explicitly to a characteristic of the environment. Politicians and social reformers typically stress this quality
of life.
Life-ability of the person. The right top quadrant denotes inner life-chances. That is, how well we
are equipped to cope with the problems of life. This aspect of the good life is also known by different
names. In biology, the phenomenon is referred to as 'adaptive potential'. Elsewhere, it is denoted by the
medical term 'health'. Sen (1992) calls this quality of life variant 'capability'. I prefer the simple term 'lifeability',
which contrasts elegantly with 'livability'. This quality of life is central in the thinking of therapists
and educators.
Usefulness of life. The left bottom quadrant represents the notion that a good life must be good for
something more than itself. This presumes some higher value, such as ecological preservation or cultural
development. In fact, there is a myriad of values on which the usefulness of a life can be judged. Moral
advisors, such as your pastor, emphasize this quality of life.
Satisfaction with life. Finally, the bottom right quadrant represents the inner outcomes of life.
That is the quality of a life in the eye of the beholder. As we deal with conscious humans, this quality boils
down to subjective appreciation of life. This is commonly referred to using terms such as 'subjective wellbeing',
'life-satisfaction' and 'happiness' in a limited sense of the word. This is the kind of well-being I deal
with in this chapter.
Four Kinds Satisfaction
This brings us to the question of what 'satisfaction' is precisely. This is also a word with multiple
meanings and again we can elucidate these meaning using a simple scheme. Scheme 2 is based on two
distinctions; vertically between satisfaction with parts of life versus satisfaction with life as-a-whole, and
horizontally between passing satisfaction and enduring satisfaction. These two bi-partitions yield again a
four-fold taxonomy.
Pleasures. Passing satisfaction with a part of life is called 'pleasure'. Pleasures can be sensory, such
as a glass of good wine, or cerebral, such as the reading of this text. The idea that we should maximize
such satisfactions is called 'hedonism'.
Part-satisfactions. Enduring satisfaction with a part of life can concern a domain of life, such as
‘working-life’, and an aspect of life, such as its ‘variety’. Sometimes the word happiness is used for such
part-satisfactions, in particular for satisfaction with one’s career.
Peak-experience. Passing satisfaction can be about life-as-a-whole, in particular when the
experience is intense and 'oceanic'. This kind of satisfaction is usually referred to as 'peak-experience'.
822
When poets write about happiness, they usually describe an experience of this kind. Likewise, religious
writings use the word happiness often in the sense of a mystical ecstasy. Another word for this type of
satisfaction is 'enlightenment'.
Life-satisfaction. Enduring satisfaction with one's own life-as-a-whole is called 'life-satisfaction'
and commonly referred to as 'happiness'. Elsewhere I have delineated this concept in more detail and
defined happiness as 'the overall appreciation of one's life-as-a-whole' (Veenhoven, 1984).
Conceptual Focus of This Chapter
This paper is about subjective well-being in the sense of life-satisfaction that is, enduring
enjoyment of one’s life as a whole.
Measurements of Life-Satisfaction
Life-satisfaction is something we have in mind. Consequently, life-satisfaction can be measured
using questions, that is, by asking people how much they enjoy their life-as-a-whole. Questions on
happiness can be posed in various contexts; clinical interviews, life-review questionnaires and survey
interviews. The questions can also be posed in different ways; directly or indirectly, and by means of single
or multiple questions.
All questions on subjective well-being that have ever used were checked for fit with the above
definition of happiness2. About half failed that test for face-validity. Accepted questions are listed in the
collection ‘Measures of Happiness’ of the World Database of Happiness (Veenhoven, 2017c).
A common question3 reads as follows:
All things considered, how satisfied are you with your life as a whole these days?
0 1 2 3 4 5 6 7 8 9 10
Dissatisfied Satisfied
Many misgivings have been advanced about such self-report of life-satisfaction; it has been
doubted that responses validly reflect how people feel about their life, that responses are erratic and
incomparable across persons and cultures. Though plausible at first sight, these qualms have not been
supported by empirical research, see for example Diener & Oishi (2004), VanPraag & Ferrer-i-Carbonell
(2004) and Veenhoven (1984, 2008a). Other indications for the validity of happiness self-reports are: their
stability over time, fit with rating by others and correlation with various aspects of a good life, such as
reported in this paper. Particularly telling is that self-reported happiness predicts longevity (Veenhoven,
2008b).
Life-Satisfaction in Nations
Questions on life-satisfaction are commonly used in large-scale survey studies, such as the General
Social Survey in the USA and the Eurobarometer in the EU. This has taught us much about the differences
in life-satisfaction within and across nations.
823
Findings on Life-Satisfaction in Nations
Research findings on life-satisfaction in nations are gathered in the World Database of Happiness
(Veenhoven, 2017a-f). This ‘findings archive’ involves two kinds of research results: distributional findings
on how satisfied citizens are in particular times and places and correlational findings on things that go
together with more or less life-satisfaction in countries. To date (January 2018) the archive lists 85434
distributional findings on life-satisfaction in the general public in 173 nations in different years
(Veenhoven, 2017d), and some 1000 correlational findings about societal characteristics that correspond
with more or less life-satisfaction in a nation (Veenhoven, 2017e).
In this chapter, I use the World Database of Happiness as an online appendix. This allows me to
sketch the main trends, without going into detail, since the reader can check in the database. The findings
archive is continuously updated and this will allow the reader a view on research findings that have
become available after this chapter was published. An overview of the most relevant entries in the World
Database of Happiness to date (January 2018) is presented in scheme 3.
Scheme 3
Findings on life-satisfaction in nations in the World Database of Happiness
Distributional findings: frequencies, mean, SD
By nation 8543 nation/year observations
By measure type sorted in 52 measure types
Rank reports Rankings of 142 nations for which comparable data is available
Trend reports Trends in 25 nations for which at least 10 comparable data-points
over 20 years is available
Correlational findings: various measures of association
Attitudinal climate in nation 13 findings
National character 82 findings
Societal conditions 959 findings
Position of the nation 15 findings
Differences Within Nations
Happiness differs considerably within nations. The surveys show extremely satisfied and
dissatisfied people in all countries, as is illustrated in figures 1 and 2. In Denmark, responses cluster at the
positive end of the scale, which results in a mean of 8,4 and a standard deviation of 1,65. In Ukraine, most
responses are at the middle of the scale and the dispersion is greater, which results in a mean of 4.4 and a
standard deviation of 2.46
824
Differences Across Nations
Happiness has now been assessed in most countries of the world, a notable exception being North
Korea. A world map of happiness is presented in Figure 3. Differences in average happiness are indicated
by the shade of the green; the darker the green, the happier the people in the nation. One can now see that
the high average happiness in Denmark is typical for developed nations. One can also see that the low level
of happiness in Zimbabwe is no exception, since happiness is equally low in most African nations. Latin
America surprises us in this picture, with higher scores than one would expect based on the news reports
emanating from that region.
825
Trend of Life-Satisfaction in Nations
Survey research on life-satisfaction started in the late 1940s and took off in the early 1970s. Until
recently, it was difficult to discern a pattern in the data; changes over time tend to be small and our view of
a trend is often blurred by minor variations in sampling and questioning. Now that we have more and better
data, we can see that life-satisfaction has risen in most nations, though not in all (Veenhoven, 2014). Some
illustrative cases are presented on Figure 4. This rising level of life-satisfaction is accompanied by a decline
of inequality in life-satisfaction among citizens as measured by the standard deviation (Veenhoven, 2017g).
826
Determinants of Life-Satisfaction in Nations
As we have seen in section 4.2, there are large differences in average life-satisfaction across
nations and this has instigated much research on the causes of these differences. The findings can be
ordered using the different kinds of well-being presented in scheme 1; part of the findings concern
variation in external living conditions in nations and fits the livability quadrant upper-left in scheme 1.
Another part of the findings is about variation in inner characteristics and fits the upper-right life-ability
quadrant of scheme 1. Findings on the relation between average happiness in nations and livability factors
are presented in table 1 and findings on the relation between average happiness and modal life-ability of
inhabitants are presented in table 2.
The many dark shaded cells in these tables indicate that the subject is well -researched. In the
column ‘partial’, the dark shaded cells denote that many attempts have been made to clean the zero-order
correlation from spurious effects, typically using regression analyses involving many controls. Since
national characteristics are typically much inter-twined, this involves a risk of underestimation. The blank
cells indicate that no data is available yet.
Livability of Society
The main findings about the relation between external living conditions and average lifesatisfaction
in nations are summarized in table 1.
Wealth. People live typically happier in rich countries than in poor ones. This difference is at least
partly due to an effect of material affluence as such, since much of the correlation remains when other
nation characteristics, such as climate, are controlled. Analysis of change over time reveals that economic
growth goes together with rising happiness (Veenhoven & Vergunst, 2014). This contradicts the wellknown
‘Easterlin Paradox’, which holds that rising wealth in nations does not add to the happiness of
citizens (Easterlin, 1974). Economic growth adds more to happiness in poor nations than it does in rich
ones.
Freedom. People also live happier in nations that provide the most opportunities to choose.
Economic freedom adds more to happiness in developing nations than in developed ones, but political
freedom correlates stronger with happiness in developed nations. Data on private freedom are limited to
developed nations. A related finding is that people live happier in individualistic cultures than in
collectivistic ones (Veenhoven, 1999). Correlations between freedom and happiness are much reduced
when economic development is controlled. The rise of liberal values in Western nations (Inglehart &
Wetzel, 2005) goes together with a rise in average happiness (cf. section 4.3).
Equality. Gender-equality stands out as a strong correlate of happiness, but income-equality does
827
not. The positive correlation with gender-equality is largely due to a greater opportunity to choose. The
non-correlation with income equality is probably the result of both positive and negative effects that
balance out (Berg & Veenhoven, 2010).
Security. Surprisingly, there is no correlation between murder rate and average happiness in
nations, probably because of the small number of people affected. Below we will see a much stronger
correlation with corruption, which affects a greater share of the population. At first sight, social security is
positively correlated to average happiness in nations (Pacek & Radcliff, 2008), but analysis of change over
time does not show a decline in happiness in western nations following cuts in welfare expenditure
(Veenhoven, 2011).
Institutional quality. People live happier in well-organized societies, where they can count on rule
of law and where government organizations function properly. This pattern also appears in a negative
correlation with corruption. In the case of government effectiveness, the ‘technical’ quality of the
bureaucracy counts more than its ‘democratic’ responsiveness. The effect of quality of government on the
happiness of citizens is stronger in developed nations than in developing ones, among other things because
central coordination is more required for the functioning of complex modern societies (Ott, 2010).
Much of the correlation with institutional quality remains when wealth of the nation is controlled,
which is again a rather severe test, since institutional quality is an important determinant of economic
success. In this line, it is argued that institutional quality also facilitates success in individual lives, since it
provides us with a predictable environment in which we are not too dependent on kin and can safely invest
in our future. At this point, there is an important connection between institutional quality and freedom.
Irrespective of these effects on personal goal achievement, a solid institutional environment is
rewarding in itself, like playing a soccer match is more pleasurable when the rules of the game are
respected. Frey, Benz, and Stutzer (2004) refer to this effect as ‘procedural utility’.
Modernity. Most of the above-mentioned societal correlates are part of the 'modernity' syndrome
and more direct measures of modernity also show a strong correlation with average life-satisfaction, such
as urbanization and globalization. The more modern a country, the happier its citizens are. This finding will
be a surprise to prophets of doom, who associate modernity with anomie and alienation. Though
modernization may involve problems, its benefits are clearly greater (Veenhoven & Berg, 2013).
The macro-social conditions listed in Table 1 together explain about 75% of the differences in
average happiness in nations depicted on the world map on Figure 3. Since measurement error in all
variables is likely to have attenuated the coefficients, this is close to perfect correlation. Explained variance
is lower in individual level analysis when country characteristics are entered after personal characteristics.
Table 1
Societal correlates of average life-satisfaction in nations
Characteristics of nations Observed correlation with happiness
Across all nations Similarity across kinds of
countries
cross sectional longitudinal
raw partial
Wealth
GDP p/c ++ + + ≠
Freedom
Economic freedom ++ + ≈
Political freedom ++ + ≈
Private freedom + +
828
Equality
Income equality 0 0 ≈
Gender equality ++ + ≈
Security
Lethal accidents – – ≈
Murder rate 0 0
Social security + 0 0 ≈
Institutional quality
Rule of law ++ + ≈
Good governance ++ + ≈
Corruption -- - ≈
Modernity
Industrialization + + =
Informatization + + =
Urbanization + +/- =
Table 2
Psychological correlates of average life-satisfaction in nations
Modal personal characteristics in nations Observed correlation with happiness
Across all nations Similarity across kinds of
countries
cross sectional longitudinal
raw partial
Self-direction
Individualism (vs collectivism) ++
Internal locus of control +
Intrinsic motivation + + ≠
Self confidence +
Mental health
Anxiety –
Neuroticism – –
829
Psychoticism – –
Personality
Agreeableness 0
Competitiveness – –
Conscientiousness 0
Extraversion +
Openness +
Optimism ++
Trust
Tolerance + +
Trust in people + + + ≈
Trust in institutions + + ≠
Values
Hedonism +
Honesty + 0
Secularism +
Key to summary markers in Tables 1 and 2
Strength of observed correlations
++ very positive
+ positive
+/– mixed findings, both positive and negative
– negative
0 unrelated
Similarity of findings across people and nations
= similar
≈ similar direction, but difference in strength of correlation
≠ dissimilar
Shading of cells indicates availability of research findings
none
a few
some
considerable
a lot
Life-Ability of Inhabitants
Less research has been done on the relation of average happiness in nations with psychological
characteristics of the population. The following findings are listed in table 2.
Self-direction. Life-satisfaction is typically higher in nations where inhabitants take control over
their lives. This appears in positive correlations with measures of modal individualism, internal locus of
830
control, intrinsic motivation and self-confidence. Several of the national character traits mentioned below
are also indicative for the ability to take control over one’s life.
Mental health. Life-satisfaction is typically lower in nations where a greater share of the
population is in poor mental health, as appears in high rates of anxiety, neuroticism and psychoticism.
Personality. Life-satisfaction tends to be higher in nations where the following personality traits
are the most common: extraversion, and openness for experience. Life-satisfaction is lower in nations
where people are the most competitive. Average life-satisfaction in nations appears to be unrelated to modal
agreeableness and conscientiousness.
Trust. A lot of studies show that life-satisfaction is typically higher nations where people trust their
fellow citizens and public institutions, and where tolerance is high.
Values. Life-satisfaction appears to be higher in nations where people value enjoyment positively,
which contradicts with claims that that the pursuit of happiness is self-defeating (e.g. Schooler, Ariely, &
Loewenstein, 2003; Mauss, Anderson, & Tamir, 2012). Life-satisfaction is also higher in nations where
honesty is most valued and where secular values prevail. These latter findings fit earlier observations that
people tend to be less happy in the most religious countries (Berg & Veenhoven, 2009)
Key Variable: Choice
Most of the above findings support the view that happiness in nations depends to a great extent on
freedom of choice. This involves an external opportunity to choose and the internal capability to choose.
External opportunity to choose requires that there is something to choose, and modern affluent
societies typically offer more options than traditional and poor societies do, among other things in
occupations and marriage arrangements. A further requirement is that choice is not limited, by law or
informal pressures, e.g. that gay people can live a life that fits their sexual orientation. Though all societies
will set some restraints to free choice, the restraints are less in nations that score high on freedom and
tolerance.
Internal ability to choose requires awareness of alternatives, which will be higher in nations where
openness for experience prevails. It also requires an inclination to choose , which is reflected in the findings
on self-direction and a positive stance to pleasure. A further requirement is the mental strength to choose,
which will be higher in populaces in good mental health and with a rational outlook.
Together, these conditions allow people to choose a way of life that fits them best and to escape
from situations in which they feel unhappy (Abdur Rahman & Veenhoven, 2017; Brule & Veenhoven,
2014). Though choice involves costs, the benefits clearly prevail. That fact fits the view that human nature
tends to a preference for independence (Veenhoven, 1999).
Consequences of Life-Satisfaction in Nations
Above, we have discussed the observed correlates of average life-satisfaction in nations as causal
factors. Yet reversed causality is also possible, a happy populace can stimulate the economy in various
ways and can foster freedom and equality in a country. A happy population may also adopt socialization
practices that foster the development self-direction, mental health and trust. Research at the micro-level of
individuals has revealed effects of life-satisfaction that could work out this way (e.g. Lyubomirsky, King, &
Diener, 2005). At the macro-level of nations, considered in this chapter, we are not yet able to disentangle
causes and effects of subjective well-being.
Directions for Future Research
So much, for what we do know now. What do we need to know more about subjective well-being
in nations?
Follow-up. As noted above we cannot yet distinguish causes and effects of life-satisfaction.
Though this will always remain difficult at the macro-level of nations, we will be able to shed more light on
this issue when more trend-data become available for a greater number of countries. The many white cells
in the ‘longitudinal’ columns in tables 1 and 2 illustrate that there is still a long way to go.
Causal paths. Assessing the direction of causality is one thing. The next step is to assess how
causality works. Several mechanisms have been suggested in section 4.1, but yet it is difficult to
demonstrate such effects empirically and to assess their relative importance.
Specifications. Most cross-national studies have looked for effects of social conditions on the
happiness in the general public. Yet some effects are likely to be contingent on persons and situations, for
example, a high degree of freedom in a country may be more beneficial for higher educated citizens than
for their low educated compatriots and may add more to happiness in stable countries than in situations of
831
social turmoil. Research on such differences will allow governments to make more informed policy
choices. The many white cells on the right in the tables 1 and 2 illustrate that there is still a world to win.
Fit with wider policy goals. The available findings on determinants of average life-satisfaction in
nations suggest that the pursuit of greater happiness fits well with several current policy goals, such as
economic growth, freedom and good governance. The findings on consequences of happiness also suggest
synergy with several common goals, such as furthering civil participation. Yet we are not yet able to see
synergy and conflict in much detail. We need a better view on causes and consequences of life-satisfaction
in nations to include this aim in standard policy analysis.
Footnotes
1This chapter draws on several of my earlier publications, in particular on Veenhoven, 2015.
2Detail about this selection is found in the introductory text to the collection Measures of Happiness
(Veenhoven, 2017c)
3Question used in Gallup World Survey. Code in collection Measures of Happiness O-SWL-c-sq-n-11-a
4Among these are multiple findings in the same year in particular countries, often involving multiple
measures of happiness. Combined, the number of country/year observations is 2472.
5Data European Social Survey 2014
6Data European Social Survey 2005
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Culture and Subjective Well-Being: Conceptual and
Measurement Issues
By Shigehiro Oishi, Department of Psychology, University of Virginia
Citation
Oishi, S. (2018). Culture and subjective well-being: Conceptual and measurement issues. In E. Diener,
S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
The present chapter reviews conceptual and measurement issues related to culture and subjective well-being
(SWB). Historically, the concepts of happiness gradually shifted from good luck and fortune to the
satisfaction of desires and goals. There are still large cultural variations in the concepts of happiness (e.g.,
fragility). The majority of the popular scales (e.g., the Satisfaction with Life Scale, the Subjective
Happiness Scale) have been successfully translated into various languages. However, most scales have not
been subjected to sophisticated psychometric analyses (e.g., Item Response Theory). Cross-cultural mean
comparisons require some caution due to cultural differences in response style, self-presentational
concerns, and memory and judgmental biases. In addition to the use of advanced statistical techniques, the
use of qualitative and non-invasive measures is recommended.
Key Words: Culture, Subjective Well-Being, Measurement, Concepts of Happiness
Happiness is used to describe at least two distinct psychological states. The first common use is to
describe an individual’s momentary affective state (e.g., feeling happy at this very moment, which is
typically accompanied by a smile on the face). The second common use is to depict an individual’s
relatively permanent state of being well (e.g., feeling happy about one’s life in general or how one’s life is
going). Subjective well-being (SWB) researchers are typically interested in the latter happiness, as it reflects
one’s entire life more closely than the momentary affective state of happiness. Among researchers, the term
SWB has been used since Diener (1984) to refer to an individual’s relatively longstanding state of being
well. Since some researchers think that a relatively permanent state of well-being should include other
dimensions of human excellence, other terms such as psychological well-being (PWB) and eudaimonic
well-being have been used (Ryan & Deci, 2001; Ryff, 1989). Yet, other researchers have advocated that
meaning in life is another aspect of being well (Heintzelman & King, 2014; Steger, Frazier, Oishi, & Kaler,
2006).
Among psychologists, the main debate concerning the concepts of well-being has centered on
hedonic versus eudaimonic well-being (Kashdan, Biswas-Diener, & King, 2008; Ryan & Deci, 2001; Ryff,
1989). Among philosophers, the main debate has centered on the meaning of eudaimonia, the term ancient
Greeks used to describe a good life or living well. For some, eudaimonia means living a virtuous life, while
for others it is living a complete life with a sense that nothing is missing (Nussbaum, 1986/2001). Yet,
other philosophers attach non-moral excellence to the notion of eudaimonia. For instance, Haybron (2016)
argues that eudaimonia could be best described as nature-fulfillment in terms of capacity-fulfillment and
goal-fulfillment. Thus, there is not yet a consensus on the notion of eudaimonia among philosophers (see
41 definitions of eudaimonia in Vittersø, 2016). However, it is clear that most philosophers view
eudaimonia to capture living well in terms of virtues, excellence, and fulfillment of human potentials that
go beyond a much narrower notion of meaning or purpose in life.
In the current chapter, we will focus on cultural and historical variations in the concepts and
measurements of happiness and life satisfaction, as empirical research on SWB has focused on happiness
and life satisfaction (Diener, Oishi, & Lucas, 2015; see Oishi & Gilbert, 2016; Uchida & Oishi, 2016 for a
general review on culture and SWB). Then, we will discuss substantial measurement-related issues on
cross-cultural comparisons of SWB.
Historical and Cultural Variations in Concepts of Happiness
The historian Darrin McMahon (2006) provides a comprehensive review on historical changes in
the concept of happiness. The ancient Greek term eudaimon consists of eu (good) and daimon (god, spirit,
demon). Thus, the concept of eudaimonia “contains within it a notion of fortune-for to have a good daimon
on your side, a guiding spirit, is to be lucky” (McMahon, 2006, p .3-4). He went on to state that “happiness
is what happens to us, and over that we have no control” (p. 19). Similarly, the philosopher Martha
Nussbaum (1986/2001) argues that “events beyond our control may affect, for good or ill, not only our
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happiness or success or satisfaction but also central ethical elements of our lives; whether we manage to act
justly in public life, whether we are able to love and care for another person, whether we get a chance to act
courageously” (p. xiv). Whereas ancient Greek philosophers such as Socrates and Plato (but not Aristotle)
denied the role of luck in ethical understanding, Nussbaum observes that ancient Greek poets recognized
the central role of luck in human happiness. Nussbaum goes on to argue that “by ascribing value to philia
in a concept of the good life, we make ourselves more vulnerable to loss” (p. 361, philia = love). Overall,
the ancient Greek concepts of happiness centered on fortune and good luck, which are external and fragile.
According to McMahon (2006), the concept of happiness became less fragile and more controllable
in the 13th century. Specifically, McMahon describes that St. Thomas Aquinas proposed a new view on
happiness, namely that happiness was attainable via achieving theological virtues of charity, hope, and
faith. The result was a divine gift of being blessed. In the 16th century, with the rise of Lutheranism and
Calvinism, the concept of happiness became even more agentic in that not just the achievement of
theological virtues but also calling to engage in some economic activities would bring happiness. Over
time, the ancient concept of happiness that centers on being “beyond one’s control” has gradually
transformed to the agentic concept of happiness that is within one’s reach.
Although there is a historical change in the concept of happiness described by McMahon (2006), it
is also true that the luck and fortune notion of happiness has not completely disappeared. For instance,
dictionary definitions of happiness in 30 nations (Oishi, Graham, Kesebir, & Galinha, 2013) revealed that
24 of the 30 nations studied (Australia, Brazil, China, Estonia, France, Germany, Guatemala, Indonesia,
Iran, Israel, Italy, Japan, Kenya, Korea, Malaysia, Mozambique, Norway, Pakistan, Portugal, Romania,
Russia, Senegal, Singapore, and Turkey) had good luck and fortune as definitions of happiness.
Related to the cultural differences in the dictionary definitions of happiness, the linguist Anna
Wierzbicka (2004) observed that the English terms ‘happy’ and ‘happiness’ are broad and could describe a
minor positive event, whereas the French, Polish, German, and Russian terms are more specific and
describe only a rare positive event. Wierzbicka states, “Happy-unlike heureux, scastlivyj, and glucklich-is
not restricted to exceptional states (like bliss), but rather is seen as referring to states within everyone’s
reach. There is nothing exceptional about being happy” (p. 38). It is possible that the good luck and fortune
definition of happiness connotes a relatively rare state of bliss, whereas other definitions (e.g., satisfaction
of desires) imply that happiness is common.
Interestingly, earlier definitions of happiness in Webster’s Unabridged English Dictionary (e.g.,
1850, 1853, 1861, 1888, 1895, 1910) had good luck and fortune as the primary definition (Oishi et al.,
2013). However, in the 1961 edition, the definition of “good luck and good fortune” was denoted as
“archaic.” Oishi et al. (2013, Study 2) then analyzed the use of the terms happy and happiness in the State
of the Union addresses from 1790 to 2010 and found that the good luck and fortune use disappeared around
1920. In addition, the Google Ngram Viewer search of “happy nation” and “happy person” showed that
“happy nation” appeared more frequently than “happy person” in published books in the U.S. from 1800
until around 1920. However, since then, “happy person” has appeared more frequently in American books
(Oishi et al., 2013, Study 3). These analyses show that until around 1920, the terms “happy” and
“happiness” in American English might have been referring to lucky external conditions.
Several programs of empirical research have also revealed cultural variations in the connotation of
happiness. For instance, Lu and Gilmour (2004) found that Americans tend to associate excitement and
success with happiness, whereas the Chinese tend to associate peace and calm with happiness. Similarly,
Jeanne Tsai and her colleagues found that Taiwanese and Hong Kong Chinese value low-arousal positive
affect such as calmness, whereas Americans typically value high-arousal positive affect such as excitement
(Tsai, Knutson, & Fung, 2006). Interestingly, Taiwanese children’s books depicted a mild smile more often
than a wide smile, whereas American children’s books depicted a wide smile more often than a mild smile
(Tsai, Louie, Chen, & Uchida, 2007). Similarly, Christian texts often use high arousal positive emotions,
whereas Buddhist texts often use low arousal positive emotions (Tsai, Miao, & Seppala, 2007). Given that
American concepts of happiness center on achieving of one’s goals, it makes sense that the resulting
emotions are excitement and pride. In contrast, given that Chinese conceptions of happiness center on luck,
the resulting emotional state might not be excitement but rather akin to gratitude and satisfaction.
Uchida and Kitayama (2009) also explored Japanese concepts of happiness using free
associations. They found that Japanese spontaneously mentioned that happiness could disrupt interpersonal
relationships via evoking envy and jealousy in others. In contrast, Americans’ descriptions were concerned
mostly with personal achievement and positive hedonic experiences (e.g., joy, smiling). Whereas happiness
is construed among Americans as a bond between people (e.g., smile is a gateway to a new friendship),
happiness in Japan is a potentially dangerous emotion that could disrupt important social relationships.
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Interestingly, several studies showed that Chinese expect a bad thing after a series of good things,
whereas Americans tend to expect a good thing after a series of good things (Ji, Nisbett, & Su, 2001). This
particular Chinese thinking style, dialecticism, has an important implication for the concepts of happiness.
Namely, those who believe in dialecticism should be worried about their current happiness, as happiness is
likely to be followed by unhappiness. Indeed, when Joshanloo and colleagues (2014) explored the potential
pitfalls of happiness using the fear of happiness scale (sample items include “I believe the more cheerful
and happy I am, the more I should expect bad things to occur in my life,” “disasters often follow good
fortune” and “excessive joy has some bad consequences”), Hong Kong Chinese endorsed the fear of
happiness items far more than Brazilians and New Zealanders. Similarly, Koreans tend to hold the belief
that there is a fixed amount of happiness one can experience akin to a fixed amount of luck (Koo & Suh,
2007). Thus, if a Korean person feels happy (lucky) today, she is likely to say she might not be happy
(lucky) tomorrow because she is using up all her happiness (luck) today. Just like ancient Greek poets
(Nussbaum, 1986/2001), many East Asians today hold the fragile view of happiness (see also Miyamoto &
Ma, 2011).
Related to the fragility of happiness, the Hindu notion of happiness is dramatically different from
the American notion of happiness today. Srivastava and Misra (2003) argue that Hindu Indians view
happiness and sorrow as the results of past lives and not just the present ones. To the extent that one has no
control over past lives, Hindu concepts of happiness appear to be consistent with the ancient Greek view.
Furthermore, Srivastava and Misra observe that Hindu Indians tend to feel happiness when they sacrifice
their material possessions and/or respond to others’ needs. Like Buddhist traditions, Hindus see attachment
to objects as a cause of suffering. Thus, Hindu happiness is concerned with the attainment of ananda, or “a
transcendental journey from a lesser self fraught with hedonistic concerns to a greater self that involves
realization of connectedness or oneness” (Nagar, in press).
Islamic conceptions of happiness are also quite different from the American notion of happiness.
Joshanloo (2013) argues that Islamic conceptions of happiness are fundamentally anti-hedonic. He cites
Shiite writer Musawi Lari: “One who seeks happiness through the pursuit of pleasures will find nothing
except anxiety and bafflement…The more that we succeed in subduing our lusts and desires, the closer
shall we move to happiness” (p. 1862). In addition to stoicism, the Islamic view of happiness is squarely
centered on the fear of, total submission to, and worship of God. It also includes the concept of perishable
body and an everlasting soul.
Finally, in some cultures, the concepts of happiness are more physical in nature. For instance, the
Fante speakers of Ghana describe happiness/excitement literally as “eye-get” (“anigye”) and
joy/contentment as “eye-agree/reach” (“anika”), in contrast with shame as “eye-die” (“aniwu”) and guilty
as “eye-put” (“anyito” in Dzokoto & Okazaki, 2006). These descriptions suggest that among the Fante
speakers of Ghana, happiness and associated positive emotions are eye-catching and easy on the eyes,
whereas shame and guilt are hard on the eyes. Interestingly, Dzokoto and Okazaki (2006) found that the
Dagbani speakers of Ghana describe happiness as “white heart,” peace as “heart at rest,” anger as “agitated
heart,” and sadness as “destruction of the heart.” These descriptions suggest that for the Dagbani speakers
of Ghana, positive emotions are physically low arousal states, whereas negative emotions are physically
aroused, agitated states. These physical descriptions of happiness suggest that for the Fante and the
Dagbani speakers of Ghana, the concepts of happiness are tied to objective bodily reactions to external
events and less concerned with the satisfaction or fulfilment of one’s desires and goals, which tend to be
more subjective, internal, and mentally constructed.
In sum, good luck and fortune has been a dominant definition of happiness around the world since
antiquity (McMahon, 2006; Oishi et al., 2013). However, the meaning of happiness has expanded and
changed over time in different parts of the world (due in part to different religious beliefs and economic,
social, political, and physical conditions). The diversity in the concepts of happiness across cultures and
time poses a major challenge to empirical research on happiness (see below how scientists have approached
this issue). However, it is also important to note that the inquiry into diverse concepts of happiness using
diverse methods has enriched our understanding of what it means to be in a relatively permanent state of
being well.
Measurement of Happiness Across Cultures
One of the first happiness scales was developed by George Hartmann (1934). He asked respondents
to rate on the following single item: “If you compare yourself with others of the same sex and age, how
would you rate your own general happiness? Use this definition as a guide: ‘A relatively permanent state of
well-being characterized by dominantly agreeable emotions ranging in values from mere contentment to
positive felicity.’ Give due weight to both inner and outer factors or manifestations: most unhappy of all, a
great majority of persons are happier than you are, a slight majority of other people are happier than you
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are, about average, somewhat happier than the general run of mankind, far happier than the great majority
of human beings, the happiest of all” (p. 206). One-month test-retest reliability was .70, and the correlation
with informant reports was .34. In 1946, a 3-point happiness item (“Take altogether, how would you say
things are these days-would you say you are very happy, pretty happy, or not too happy”) was included in a
national survey (Easterlin, 1974). In 1965, Hadley Cantril used a single-item ladder scale (0 = the worst
possible life; 10 = the best possible life). Unlike Hartmann, Cantril’s scale was used to measure the
subjective evaluation of life accomplishments (more similar to life satisfaction than the feeling of
happiness). These single-item measures of happiness and life satisfaction have been used widely in large
international surveys such as the World Values Survey and the Gallup World Polls.
Multiple-item scales. Bradburn (1969) was the harbinger of positive psychology that emerged in
the late 1990s. He was already concerned that researchers in the 1950s and the 1960s were preoccupied
with mental illness and not paying enough attention to mental health. He used the conceptual model of
well-being similar to “older pleasure-pain or utility models that view an individual’s happiness or wellbeing
in terms of the degree to which pleasure predominates over pain in his life experiences” (p. 9). To
measure the degree to which pleasure predominates pain in life, Bradburn developed a 10-item scale called
the affect balance scale (ABS). The five positive items were as follows: (1) “Pleased about having
accomplished something?” (2) “That things were going your way?” (3) “Proud because someone
complimented you on something you had done?” (4) “Particularly excited or interested in something?” (5)
“On top of the world?” (answered in the Yes/No format). Bradburn overturned the prevailing assumption
about positive and negative affect being the opposite ends of one dimension and showed that positive
affect and negative affect are relatively independent; that is, there are people who are high in both positive
and negative affect, as well as those who are low in positive and negative affect. It is also noteworthy that
decades later the Gallup World Polls adopted the affect items similar to Bradburn’s ABS, using the yes-no
format.
Devins et al. (1997) explored cross-cultural equivalence of the affect balance scale with Chinese,
Vietnamese, and Laotian refugees to Canada (those who arrived in 1979-1981). The researchers could not
translate the item “Have you been feeling on top of the world?” into South Asian languages. Thus, they
used only 9 items that were translatable. Confirmatory factor analyses showed that the remaining 9 items
formed two factors (positive and negative affect), just like in an English-speaking Canadian sample. It
should be noted, however, that these items capture mostly high arousal positive emotions that are deemed
more ideal for North Americans than East Asians. Furthermore, MacIntosh (1998) analyzed the World
Values Survey data from 38 nations, and found that the full 10-item, 2-factor solution did not fit data in
most nations. (Curiously, the 2-factor model fit best in Nigeria, where CFI was .90 and RMSEA was .056,
and South Africa, where CFI was .94, and RMSEA was .061; in other nations, fit was worse.)
Watson (1988) criticized the affect balance scale for having relatively low internal reliability (alpha
= .54 for positive, .52 for negative affect) and poor convergent validity with other affect measures. Instead,
Watson, Clark, and Tellegen (1988) developed the 20-item Positive and Negative Affect Schedule
(PANAS). Like the ABS, the PANAS items focused on high arousal positive affect such as excited,
enthusiastic, and inspired. When Japanese psychologists, Tokihiro Ogawa and colleagues (Ogawa, Monchi,
Kikuya, & Suzuki, 2000), developed an emotion scale, they included items such as ゆ っ く り し た
(slow/relaxed), の ど か な (rustic/peaceful),　 静 か な (quiet/tranquil), and the low arousal positive affect
formed a distinct factor from general positive and negative affect. The general emotion scale created by
these Japanese psychologists did not include pride. Similarly, Hamid and Cheng (1996) asked Hong Kong
Chinese to nominate 10 emotion words and created the Chinese Affect Scale. This scale included low
arousal states such as comfortable, relaxed, and peaceful, as well as agreeable (more interpersonal affective
state). The Chinese Affect Scale also does not include pride. Therefore, it is not surprising that pride is not
a part of the positive affect factor among Asian samples (Scollon, Diener, Oishi, & Biswas-Diener, 2005),
nor does it correlate highly with general positive emotion (Kitayama, Markus, & Kurokawa, 2000). It is
also noteworthy that when Thompson (2007) created the international PANAS by testing out the original
PANAS items with culturally diverse samples, the resulting positive affect items were determined,
attentive, alert, inspired, and active (i.e., enthusiastic, strong, interested, excited, and proud dropped out).
Whereas the ABS, the PANAS, and other emotion scales were focused on happiness and other
positive emotional experiences as an indicator of emotional well-being, other researchers assessed an
evaluative dimension of a relatively permanent state of well-being, that is how an individual sees her/his
life to be. Lyubomirsky and Lepper (1999) developed the 4-item subjective happiness scale (SHS), which
is very similar to Hartmann’s (1934) scale. The SHS items are the following: (1) “In general, I consider
myself…1 = not a very happy person to 7 = a very happy person” (2) “Compared to most of my peers, I
consider myself…1 = less happy and 7 = more happy” (3) “Some people are generally very happy. They
enjoy life regardless of what is going on, getting the most of out of everything. To what extent does this
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characterization describe you?” and (4) “Some people are generally not very happy. Although they are not
depressed, they never seem as happy as they might be. To what extend does this characterization describe
you?” (reversed item). As the SHS focuses on a trait-like happy person, test-retest reliability was quite high
(one-month test-retest reliability, r = .85 to .90; one-year test retest reliability, r = .55). The SHS has been
successfully translated into Japanese (Shimai, Otake, Utsuki, Ikemi, & Lyubomirsky, 2004), Malay
(Swami, 2008), German and Tagalog (Swami et al., 2009).
Among many scales to measure a relatively permanent state of being well, the Satisfaction with Life
Scale (SWLS: Diener, Emmons, Larsen, & Griffin, 1985) is the most popular in psychology. The 5-item
scale of life satisfaction captures several aspects of being well: favorable objective external conditions
(Item 2: “The conditions of my life are excellent”), a small gap between reality and ideal (Item 1: “In most
ways my life is close to my ideal”), goal-fulfillment (Item 4: “So far I have gotten the important things I
want in life”), and positive evaluation of life (Item 3: “I am satisfied with my life,” Item 5: “If I could live
my life over, I would change almost nothing”).
Oishi (2006) evaluated the cross-cultural equivalence of the SWLS between Chinese and American
university student samples. First, when the one-factor model with free factor loadings was examined using
the multi-group structural equation model (SEM), the fit was acceptable (GFI = .981; RMSEA = .06). The
standardized factor loadings were all above .67 among the U.S sample, whereas they were high for the first
three items (.62, .66, .72) among the Chinese sample. The goal fulfillment item was .49, and the last item,
“If I could live my life over, I would change almost nothing,” was the weakest with .38 (see similar results
for Orang Asli, aboriginal people in Malaysia in Howell, Howell, & Schwabe, 2006). When factor loadings
were constrained to be the same between the two samples, Item 5: “If I could live my life over, I would
change almost nothing,” was the only item that showed an item bias (constraining this item to be
equivalence decreased the fit significantly worse). When Oishi (2006) used the differential item function
(DIF) analysis of the Item Response Theory (IRT), which models not only factor loadings but also item
difficulty, 4 of the 5 items showed a significant item bias. In particular, Item 4: “So far I have gotten the
important things I want in life” and Item 5: “If I could live my life over, I would change almost nothing”
showed large DIFs. It is interesting to note that the most equivalent item was explicitly concerned with
favorable external conditions: “The conditions of my life are excellent.” In contrast, two items regarding
the past accomplishments showed a large discrepancy. Namely, among Chinese students, those who
endorsed favorable external conditions were not necessarily those who endorsed goal fulfillment items.
Among American students, those who endorsed favorable external conditions were those who endorsed
past accomplishment items. Overall, the results of the IRT analyses were consistent with the conceptual
analyses discussed above (Lu & Gilmour, 2004; Tsai et al., 2006). Furthermore, given that the good luck
and fortune definitions are prominent in many cultures (Oishi et al., 2013), the first three items of the
SWLS might be the most appropriate, least biased life satisfaction items across many cultures (see Tay,
Huang, & Vermunt, 2016; Tay, Meade, & Cao, 2015 for the application of IRT in cross-cultural research).
It is also noteworthy that some researchers modified the SWLS to fit a local culture and education
levels of respondents. For instance, Biswas-Diener and Diener (2001) used the 7 faces (1 = frown to 7 =
extreme smile) instead of 1 = strongly disagree to 7 = strongly agree when they administered the SWLS to
slum dwellers and sex workers in Calcutta, India.
Alternative measures. Global, retrospective measures of SWB have been criticized on various
grounds (e.g., Kahneman, 1999; Schwarz & Strack, 1999). One issue is concerned with memory bias, in
that global measures might not capture everyday affective experiences. To address this issue, experience
sampling method (ESM), in which respondents were prompted to report their momentary mood at random
moments, has been used in cross-cultural research on SWB (e.g., Oishi, 2002; Oishi, Diener, Scollon, &
Biswas-Diener, 2004; Scollon et al., 2005). Some researchers used the time-contingent recording (e.g.,
noon, 3pm, 6pm, and 9pm in Mesquita & Karasawa, 2002). In addition, daily diary method has been
utilized to gather daily life satisfaction and positive emotional experiences (Kitayama, Mesquita, &
Karasawa, 2006; Oishi et al., 2007). Due to these methods often being taxing to participants, some
researchers relied on Day Reconstruction Method (DRM: Kahneman, Krueger, Schkade, Schwarz, &
Stone, 2004), in which respondents were asked to recall various episodes in the morning, in the afternoon,
and in the evening of the previous day (Oishi, Kurtz, Miao, Park, & Whitchurch, 2011; see Diener & Tay,
2014 for a review on DRM).
In addition to “online” measures, others have used informant reports to address some of the
judgmental bias issues. Saeki et al. (2014), for instance, used informant reports and found that Japanese
informants (the target’s friends) tended to view the target’s life satisfaction to be higher than the target
him/herself, d = .51. Although in terms of domain satisfaction, the differences were much smaller (e.g.,
satisfaction with weather, d = .10; satisfaction with love life, d = .02).
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With the rise of implicit measures (e.g., Implicit Association Test: IAT), several researchers have
attempted to develop an implicit, reaction-based measure of SWB. For example, Constantini et al. (in press)
developed the IAT-based positive orientation scale and found a small but positive correlation with the
SWLS, r = .24, p < .001 (however, it is equally strongly correlated with global self-esteem, r = .23, p <
.001, as well). Yamaguchi et al. (2007) found that Japanese reported lower levels of global self-esteem
explicitly than Americans, but their IAT-based self-esteem was as high as Americans. Thus, IAT-based
measures of SWB could be promising in future cross-cultural research (see however Falk & Heine, 2015;
Schimmack & Diener, 2003 for some cautionary notes).
More recently, researchers have started to use social media data such as Facebook and Twitter to
gather information regarding users’ state of the mind and feelings. Golder and Macy (2011) conducted the
linguistic analysis of 509 million tweets from about 2.4 million individuals across the world, though limited
to English speakers. They found that Indians were happier relative to North Americans in the morning,
whereas Africans were relatively happier than Indians in early evening hours. Within the U.S., Eichstaedt
and colleagues (2015) found that anger-related words used in Twitter predicted county-level heart disease
mortality. This means that in the counties where heart disease mortality is high, residents were more likely
to use anger in their Tweets than those living in counties where heart disease mortality is low. Similarly,
Facebook Data Team (2011) applied automated sentiment analysis to the status updates and created an
index of positivity and negativity. Techniques like this are extremely promising, as they capture a large
number of individuals’ everyday moods naturally (that is, without making them think about the purpose of
research). However, when Wang, Kosinski, Stillwell, and Rust (2014) compared daily, weekly, and
monthly Facebook’s Gross National Happiness Index with daily, weekly, and monthly aggregate scores of
self-reported life satisfaction (SWLS) among myPersonality Facebook application users, the Facebook
positivity score was negatively associated with the SWLS in all three time frames. It should be noted that
the linguistic analysis of Twitter updates also showed some discrepancies from self-reported SWB. For
instance, conservatives typically report higher levels of happiness than liberals. However, Tweets were
more positive and happier among the followers of the Democratic party than those of the Republican party
(Wojcik, Hovasapian, Graham, Motyl, & Ditto, 2015). In short, social media present unprecedented large,
ecological data. Although it is clearly promising in the context of cross-cultural research on SWB, it is also
important to further validate specific indices in the future (see Kern et al., 2016 a review on how to use
social media in psychological research).
Another way to measure SWB is to code the sign of positive and negative affective state from nonverbal
behaviors. For example, Harker and Keltner (2001) coded yearbook photos for genuine smile and
found that yearbook smiles predicted self-reported well-being over 30 years later (see Seder & Oishi, 2012
for smile intensity in the Facebook profile photos). Oettingen and Seligman (1990) observed bar patrons’
non-verbal behaviors unobtrusively and found that East Berlin workers (then living in the communist
country) smiled and laughed less and showed more slumped posture than did West Berlin workers.
As many surveillance cameras are placed in public space (e.g., 33 permanent cameras in
Washington DC), it might be possible to use scenes captured on these surveillance cameras for SWB across
cultures (Tay, Jebb, & Woo, 2017). For instance, MIT Media Lab researchers Javier Hernandez,
Mohammed Hoque, and Rosalind Picard (2012) set up a camera on 4 different locations on a university
campus and assessed the degree to which people who passed by were smiling for 10 weeks. The
researchers report that over the study period, thousands of people passed by the camera and showed the
pattern expected from academic schedules such as exam periods, holidays, and graduation day. The “mood
meter” like this could provide a naturalistic behavioral index of happiness that could be scaled up for crosscultural
comparison (e.g., Hernandez et al. (2012) calculated the average intensity of smile among people
present in an image, thus the mood meter ranges from 0% to 100%).
Finally, numerous researchers have attempted to identify biological markers of SWB. Richard
Davidson and his colleagues used electroencephalography (EEG) asymmetry during the resting period as
an indicator of SWB (Urry et al., 2004). Using EEG, Lun, Oishi, Coan, Akimoto, and Miao (2010) found
that East Asians showed greater left prefrontal cortex activation (than European Americans) when they felt
understood by others.
Some researchers have examined cortisol outputs and found, for instance, that anger and tension are
associated with higher levels of cortisol in the evening (Adam, Hawkley, Kudielka, & Cacioppo, 2006).
Yet other researchers have explored heightened expression of genes associated with NF-κB and underexpression
of genes associated with anti-inflammatory glucocorticoid response elements as indicators of
ill-being (e.g., Cole et al., 2007). More recently, Fredrickson and colleagues (2013) used 53 genes to
indicate the “conserved transcriptional response to adversity” (CTRA) and showed their associations with
hedonic and eudaimonic well-being (see Nickerson, 2017 for a critique). Kitayama, Akutsu, Uchida, and
Cole (2016) measured the same 53 genes’ expression status and found the similar patterns of correlations
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with self-reported hedonic and eudaimonic well-being. The central claim of Fredrickson et al. that
eudaimonic well-being is more strongly associated with CTRA than hedonic well-being has been
questioned due to the high correlation between two types of well-being (r = .79 in Fredrickson et al., 2013; r
= .70 in Kitayama et al.). However, the gene expression of the CTRA appears to be reliably associated with
self-reported well-being. Thus, CTRA and related RNA measures appear to be a promising biological
index of well-being that might be of use to cross-cultural comparison in the future.
Indigenous scales. Although the majority of cross-cultural research on SWB has taken the etic
approach (translate an original scale), several researchers have used the emic approach. For instance,
Hitokoto and Uchida (2015) developed the interpersonal happiness scale to capture the Japanese view on
happiness, which is characterized by interpersonal harmony, relational worth, stability, and being above the
minimum acceptable standard. Sample items include the following: “I believe that I and those around me
are happy,” “I feel that I am being positively evaluated by others around me,” “Although it is quite average,
I live a stable life,” and “I believe I have achieved the same standard of living as those around me.”
Similarly, Lee et al. (2013) developed the peace of mind scale to capture the Chinese way of being
well. Sample items include these statements: “My mind is free and at ease,” “I feel content and comfortable
with myself in daily life,” “My life style gives me feelings of peace and stability” and “I have peace and
harmony in my mind.” As expected, it is moderately correlated with the SWLS, r (135) = .54, p < .001.
Furthermore, Lee et al. found that Taiwanese college students scored higher on the peace of mind scale
than European American college students, t = 3.61, p < .001, d = .55.
Singh, Raina, and Sahni (2017) created the Sukha-Dukha scale to capture uniquely Indian concepts
of happiness. Sukha refers to favorable experiences, and Dukha refers to unfavorable experiences. The
ultimate level of happiness is thought to be achieved when “dualities of sukha and dukha cease to exist” (p.
118). The 23-item sukha scale resulted in 4 factors: happiness due to contentment (“khush” “saubhagya”),
happiness due to physical and mental well-being (“svastha” “sakaratmak”), happiness due to social wellbeing
(“Santosh” “hita”), and happiness due to spiritual well-being (”utsah,” “rasa”).
Finally, Wang, Wong, and Yeh (2016) created the dialectical coping scale to capture a uniquely
Chinese way of coping: Sample items include these sentiments: “When I experience difficulties, I remind
myself that misfortune coexists with blessings,” “I believe that the problems in my life don’t last forever,”
and “In understanding the obstacles in my life, I can see the interconnections between negative and positive
events.” Overall, indigenous scales might be able to capture aspects of SWB that cannot be adequately
assessed by existing mostly Western measures.
Qualitative approach. Because the concepts of happiness are diverse, some researchers have used
a qualitative approach (see also Biswas-Diener, this volume; Thin, this volume for the utility of the
qualitative approach). Kral et al. (2011), for instance, interviewed the Inuit people and asked them about
meanings of happiness, as well as health, sadness, healing, and social change. The Inuit’s happiness was
deeply intertwined with family. When asked about happiness, one respondent (male, age 47) said,
“Summer life. Family. Having a good family relationship with my wife and with my daughters” (p. 430).
Although family is often mentioned in the context of happiness across the globe, the second most frequently
mentioned category among the Inuit was being on the land. This indicates the Inuits’ deep attachment to
their land, which is very different from the residents of many developed countries.
When Galinha et al. (2016) interviewed extremely poor people in Maputo, Mozambique, by far the
most frequently mentioned happy events were concerned with family and weddings: “When I got married it
was a happy time with a great party with his family and mine. As my grandfather had oxen, he offered an
ox to me” (p.79). Whereas many focus exclusively on happiness or related concepts, others explore
respondents’ life stories overall. For instance, Cox, Casablanca, and McAdams (2013) used the life story
interview, asking interviewees to talk about their life overall, key events, challenges, beliefs, and future
prospects. The life story interview shows some common themes of unhappiness among sex workers in
Managua, Nicaragua: early family problems, early departure from home, difficult romantic relationships,
and financial difficulties. The interview contents could be coded in terms of positivity and negativity.
Substantive Measurement Issues
With the introduction of internet, cross-cultural research has become much easier than decades ago.
Yet, there still remain many challenges to cross-cultural research on SWB. In this chapter, we will focus on
the three main issues: response style, self-presentation concerns, and judgmental biases.
Response style. There appear to be cultural variations in the tendency to use a certain number in
responding to the survey questions. Some cultures are more acquiescent than others. For instance, when
asked “how introverted are you?” and “how extraverted are you?”, Koreans were more likely to agree with
both introversion and extraversion items than Americans were (Choi & Choi, 2002). The researchers
840
speculated that East Asians can think of the situations in which they felt introverted as well as extraverted
and thus tend to endorse both items. This tendency could easily have an impact on emotional items.
Namely, if East Asians are more likely than Americans to endorse both positive and negative emotion
items, then the positive-negative emotion correlation should be positive among East Asians, whereas it
should be negative among Americans. Indeed, Schimmack, Oishi, and Diener (2002) found that the
frequency of positive-negative emotional experiences correlation was positive among Hong Kong (r = .09)
and Japanese participants (r = -.07), whereas it was negative among Americans ( r = -.36) and Australians (r
= -.37). It is important to dissect the degree to which acquiescence affects SWB responses. For instance,
researchers can use two conceptually identical items worded oppositely: “It should be forbidden completely
to smoke in malls” and “It should ‘not’ be forbidden to smoke in malls” (Baron-Epel, Kaplan, Weinstein, &
Green, 2010).
Related to acquiescence, Chen, Lee, and Stevenson (1995) found that Americans use the extreme
response more and the middle response less than Taiwanese and Japanese. Similarly, several large-scale
cross-cultural surveys found systematic cultural variations in response styles (e.g., Smith et al., 2016).
These findings present a major concern for the observed mean differences in SWB across cultures. For
instance, when Americans report higher levels of life satisfaction than Japanese, would the difference be
driven by extreme responding (or extreme response avoiding)? As an initial test of the role of extreme
responding, Oishi (2010) re-coded the original 7-point scale of the SWLS to the 3-point scale (1 to 3 = 1; 4
= 2, 5 to 7 = 3). In this recoding, 5, 6, 7 responses were coded as the same. In the original 7-point scale, the
U.S-Japan difference was substantial, d = .81. When the 3-point scale was used, the difference was almost
identical, d = .79. To make sure this is not just specific to the U.S-Japan comparison, Oishi also tested the
Chile-Japan difference. The magnitude of the mean difference remained virtually unchanged: d = 1.24 in
the original 7-point scale, d = 1.25 in the 3-point scale.
In addition, when the IRT scoring method was utilized, the U.S-China difference in the SWLS
remained substantial, d = .71 (only 1 of the 5 items was equivalent, thus the IRT scoring weighed this one
item more heavily than other “biased” items), whereas the U.S.-China difference in the original scale (sum
score) was d = 1.18 (Oishi, 2006). These findings suggest that although extreme responding might affect
the mean score, the magnitude of the mean difference seems to be relatively unaffected (it should be noted,
however, that when a large number of respondents respond randomly or use extreme categories, the
conversion could result in a dramatically different result, see Vittersø, Biswas-Diener, & Diener, 2005 for
an example; see also Batz, Parrigon, & Tay, 2016 for the number conversion issue in cross-cultural
comparisons).
Related to the number use, self-presentation concerns could blur true mean differences. For instance,
Americans typically say “Good” or “Great!” to answer “How are you?” In contrast, many East Asians
typically say “OK” or “So-so.” It is not uncommon for Japanese to say “not so good” or “dying.” In the
U.S., there is a pressure to be positive, whereas elsewhere there is a pressure not to be too positive. Then,
the self-presentational concern (e.g., to appear modest) could be a serious issue. Kim, Schimmack, and
Oishi (2012) utilized informant reports and found that European Canadians were more positive overall
(positive toward themselves and positive toward others) than were East Asians. Once this general positivity
bias was statistically removed, the mean difference in self-reported SWB disappeared.
Although happiness is highly valued across cultures, there are cultural variations in the desirability
of happiness (Diener, 2000). Americans, Australians, and Argentine value happiness far more than Chinese
and Indian. It is noteworthy that when Americans are led to think that happiness is a particularly desirable
quality, they tend to exaggerate their current levels of happiness (Wojcik & Ditto, 2014). Kim and Lee
(2011) also found that American college students who are concerned about self-presentation (those who
post only happy photos on Facebook) also reported being a happier person (the SHS). These findings
present a possibility that observed mean differences in self-reports of SWB could be due to selfpresentational
differences rather than “real” differences.
To address the self-presentation issue, Oishi (2010) examined the U.S.-Japan differences in the
SWLS using informant reports as well as self-reports: In self-reports measured in two time points,
American students reported higher levels of life satisfaction than Japanese students (Mus = 23.08 vs. Mjapan
= 21.27, t [174] = 2.13, p = .035, d = .32 at Time 1, Mus = 23.78 vs. Mjapan = 20.77, t [174] = 3.74, p <
.001, d = .57 at Time 2. American students’ life satisfaction rated by their informants was also higher than
Japanese students’ life satisfaction rated by their informants, Mus = 23.15 vs. Mjapan = 21.77, t [174] =
2.06, p = .041, d = .31. Japanese informant reports were also similar to self-reports in terms of the means
cores. Thus, these results suggest that self-presentation concerns might not play a huge role in crosscultural
comparisons of the SWLS scores. However, Saeki et al. (2014) found that Japanese informant
reports were substantially higher than self-reports of the SWLS. It is unclear, however, whether the target’s
841
friend exaggerated the target’s life satisfaction, or the target downplayed their life satisfaction. In order to
ascertain the rater effect and the target effect, it is critical to have a Round Robin type measure (group
member providing self-reports as well as ratings of all other members; see Kwan, John, Kenny, Bond, &
Robins, 2004; Su & Oishi, 2011 for the use of Round Robin measure on culture and self-enhancement).
Memory and judgmental bias. A potential memory bias emerges when two individuals or two
groups of individuals do not differ in terms of daily experiences of happiness, yet they report different
levels of overall happiness. Oishi (2002, Study 1) found that the mean of daily satisfaction over 7 days did
not differ between European Americans and Asian Americans, yet European Americans evaluated the
whole week to be more satisfying than did Asian Americans. A regression analysis suggested that Asian
Americans took into account the best day and the worst day during the 7-day period when evaluating the
whole week, whereas European Americans took into account only the best day. Oishi (2002) replicated this
finding with an experience sampling method (Study 2) and the evaluation of life events. Furthermore, Oishi
and Diener (2003) used a performance task such as an anagram and a free throw task and measured online
emotional experiences, recalled emotional experiences, and replicated Oishi (2002).
However, the third study of this kind, Scollon, Diener, Oishi, and Biswas-Diener (2004), in which
online emotional experiences were assessed using an experience sampling method, did not replicate the
findings from Oishi (2002). Instead, Scollon et al found that Japanese reported lower levels of happiness
than Americans both online and retrospectively. Since Japanese reported less happiness online already,
Scollon et al. did not find cultural differences in memory bias. It should be noted, however, that Oishi et
al.’s (2007) 21-day daily diary study in the U.S., Japan, and Korea showed again that European Americans
reported higher levels of life satisfaction (the SWLS) than Japanese and Koreans. However, the average
daily satisfaction of European Americans was not different from Japanese. Oishi et al.’s (2011) DRM
study in the U.S. and Korea further replicated these findings (i.e., no cultural difference in the average
positive emotion felt across various episodes on the previous day, but difference in the SWLS). Kitayama et
al.’s (2006) 14-daily diary study on engaging and disengaging emotions also showed that Japanese and
Americans did not differ in the daily experience of socially engaging positive emotions (e.g., shitashimi
[friendly feelings], although Americans reported more socially disengaging emotions such as pride than
Japanese). Likewise, Oishi (2010) reports that the intensity with which Japanese and American respondents
reported positive moods at the time of completing a questionnaire was virtually identical (Mus = 6.12 vs.
Mjapan = 5.97, t [530] = .87, p = .38, d = .08), yet Americans reported being happier about their lives in
general than Japanese (Mus = 6.10 vs. Mjapan = 5.69, t [530] = 2.35, d = .20).
Overall, although some studies (e.g., Scollon et al., 2004) found cultural differences in online
positive emotional experiences, the degree of cultural differences in online positive emotional experiences
tends to be smaller than in global reports. Online reports are based on specific situations and events that
just happened. Thus, a general belief about the typical level of happiness (e.g., “I am a happy person”) or
cultural norm (“I should be happy”) play a relatively small role. In contrast, global reports are based on
events that are remembered (Tov, 2012), as well as a general belief about the typical level of happiness
(Robinson & Clore, 2002) and cultural norms. Therefore, global reports appear to magnify cultural
differences in everyday emotional experiences, especially when cross-cultural comparisons involve two
groups that differ in desirability of happiness (see Oishi, 2010 for more details).
A related issue is concerned with a positivity bias, or the degree to which global domains are more
positively evaluated than their corresponding, specific domains. For instance, overall satisfaction with
education should be comparable to the average satisfaction with professors, lectures, and textbooks. Diener,
Scollon, Oishi, Dzokoto, and Suh (2000) found that the positivity bias score (global domain ratings –
average specific domain ratings) was higher among the countries with higher mean levels of life
satisfaction measured by the SWLS, r = .57, p < .001. These findings suggest that countries where people
report higher levels of life satisfaction might be evaluating the overall life more positively. However, at this
point it is unclear whether it is fair to say this is a “bias” or a characteristic of a happy person/culture.
One way to address the issue of positivity bias is to use vignettes and see how people from different
cultures evaluate others’ lives. Angelini, Cavapozzi, Corazzini, and Paccagnella (2014) used such a method
and found that there are indeed large cultural differences. For instance, John was described to be 63-years
old, a widow, relatively poor, and with heart problems. However, his children and grandchildren visit him
regularly. Over 20% of Germans and Dane thought John was satisfied or very satisfied with his life. In
contrast, less than 10% of Italian respondents thought John was satisfied or very satisfied. Once researchers
controlled for the vignettes’ ratings, cross-national differences in self-reported life satisfaction between
Italy and Denmark disappeared. Like Diener et al. (2000), however, it is inconclusive whether vignette
ratings are capturing judgmental biases or naturally positive inclinations. In addition, cultural differences in
ratings of John’s life satisfaction might be shedding light on one’s values rather than positivity bias per se.
842
For example, this example might tell us that Germans and Dane consider children and grandchildren’s
visits more important than financial conditions. It is also possible to interpret the results as indicating that in
Denmark and Germany, one can live happily without much money thanks to better social welfare programs
and public goods, whereas in Italy one must have money to live a good life. It is important to discern
values from judgmental biases in the future by perhaps creating diverse vignettes (Angelini et al. used only
two vignettes).
Conclusion
The concepts of happiness are diverse across times and cultures (McMahon, 2006; Oishi et al.,
2013). They contain the notions of good luck and fortune, bliss, the satisfaction of desires, and a physical
sensation of “eye-get” (“anigye” in Fante, Ghana). At this point, however, the notions of happiness in
Africa, Middle East, and South Africa are still relatively unknown. It is critical to explore various concepts
of happiness in even more diverse cultural samples in the future.
Over the last twenty years, researchers have developed many ways to assess different concepts of
happiness using divergent terms (“on top of the world”, “calm,” etc.), assessing multiple concepts (e.g., the
SWLS items) or multiple life domains, using indigenous scales (e.g., the Sukha-Dukha scale), using
informant reports, assessing momentary moods, and analyzing non-invasive, social media (e.g., Twitter) or
camera data (e.g., “mood meter”).
Cross-cultural comparisons are challenging in many ways, ranging from conceptual and
measurement equivalence to potential differences in number use, self-presentational concerns, and memory
and judgmental biases. Researchers have access to ever more diverse and large cross-cultural datasets. The
conceptual refinement goes hand-in-hand with the refinement of measures. Researchers should be fully
aware of sophisticated statistical methods to test measurement equivalence (e.g., Eid & Diener, 2001; Kim
et al., 2012; Tay et al., 2016; Tay, Woo, Klafehn, & Chiu, 2010) in cross-cultural research on SWB. At the
same time, it should be recognized that qualitative approaches (e.g., life story interview, Cox et al., 2013;
free associations, Dzokoto & Okazaki, 2006) shed a new light on the concepts of happiness. The
advancement of culture and SWB research hinges largely on conceptual clarification and solid
measurement. To this end, SWB researchers must be aware of diverse methods and measurement issues
summarized above and strive to go beyond the extant “good enough” measures of SWB.
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The Subjective Well-Being of Small Societies
By Robert Biswas-Diener, Portland State University and Noba
Citation
Biswas-Diener, R. (2018). The subjective well-being of small societies. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
So-called “small societies” such as Amish communities and traditional tribal groups offer a unique
opportunity to chart the conceptual territory of subjective well-being (SWB). First, these groups offer an
alternative to standard cross-national comparisons that are so common in happiness research. Because of
their smaller size and relative isolation, each small society represents a relatively homogenous experience
of happiness that can shed light on the ways that social ties, community norms and practices might
influence SWB. This chapter explores both culture and methods as they relate to SWB. Three diverse “case
studies” are discussed including the Amish, Tonga Islanders, and the Maasai. Finally, recommendations are
given for improving SWB research.
Keywords: subjective well-being, happiness, small societies, traditional cultures, culture, Amish,
Tonga, Maasai, Research Methods
In recent years the study of subjective well-being has grown exponentially. Academic articles and
chapters on the topic have increased dramatically over the last two decades. This academic interest in
happiness has coincided, to some degree, with the advent of the modern positive psychology movement
(Seligman & Csikszentmihalyi, 2000). Subjective well-being has also experienced an uptick in academic
attention as it is increasingly legitimized as a field of study in a broad range of disciplines including law
(Posner & Sunstein, 2010), economics (Stevenson & Wolfers, 2008), philosophy (Haybron, 2008) and
anthropology (Thin, 2009). These trends are reflected in an increasing number of academic journals
devoted to well-being related topics including Journal of Happiness Studies, International Journal of
Wellbeing, Journal of Positive Psychology, and Psychology of Well-being.
One interesting subset of studies in this area has focused on the ways that cultural factors influence
subjective well-being. Frequently, national identity is used as a proxy for culture (e.g. Diener, Diener &
Diener, 1995). The emphasis in these types of studies is almost exclusively cross-cultural (examining
cultural similarities and differences) as opposed to cultural (seeking to understand concepts as they exist
within one culture; Jahoda & Krewer, 1997). Cross-cultural research has the advantage of allowing
comparisons between diverse groups. This has been helpful in business-related research (Hofstede &
Hofstede, 2005) as well as in understanding societal differences in social, material and environmental wellbeing
(Biswas-Diener, Diener, & Lyubchik, 2015). Unfortunately, an emphasis on contrasting cultures
necessitates the use of standard measurement, which usually translates to quantitative methods and the use
of surveys created in, by and for members of industrialized societies. Similarly, an emphasis on contrasting
also encourages the use of convenience sampling; especially through employing college student samples.
There has been a conspicuous absence of research attention to small societies and traditional
cultures. Traditional culture is a term used to describe the beliefs, norms, roles, and practices of people
whose traditions are anchored in a shared cultural heritage (Biswas-Diener & Thin, 2017). Specifically,
traditional culture is associated with historical practices that exist in the larger modern context. This concept
is often understood to be culture that is pre-industrial and pre-colonial. The cultures of indigenous people in
nations such as Canada and Australia are examples of traditional culture even though many of these people
have assimilated with more mainstream society or use modern technologies. Members of some small
societies, such as Amish farmers or hunter-gatherers, are especially likely to retain their traditional culture
because of their limited contact with mainstream or colonial cultures.
Conducting research with small societies with traditional cultures is difficult. Often, members of
these groups have experienced prejudice and discrimination and can be distrustful of researcher motives. In
addition, there are methodological complications including translation difficulties and the obstacles
presented by remote geographical locations in which these societies are located. Despite these hardships, I
argue that it is both wise and important to include traditional cultures in the larger research program of
subjective well-being research. Research with small or traditional societies adds a layer of specificity to a
topic—culture—that is plagued by fuzzy boundaries. In many cross-cultural studies in psychology, for
example, nationality is treated as being synonymous with culture (e.g. Suh, Diener, Oishi & Triandis,
1998). However, nations such as China, for example, are too diverse to realistically have some monolithic,
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unifying culture. Demarcating cultural boundaries by collecting data from smaller and more traditional
groups can help us understand cultural factors that are broad and regional versus those that are unique and
local.
In addition, the bulk of the research attention to culture in psychology has focused on broad cultural
concepts such as individualism and collectivism (Triandis, 1995). Individualistic cultures are those in
which the primary unit of measurement is the individual. These cultures emphasize uniqueness and
generally have greater social and geographic mobility. By contrast, collectivist societies are those in which
the unit of measurement is the family. These cultures tend to emphasize social harmony and social
obligation. Although individualism and collectivism are, arguably, the most researched dimensions of
culture in psychology, other conceptualizations of culture have also been studied. These include cultures of
honor (Nisbett & Cohen, 1996), indexical versus referential cultural (Landrine, 1992), cultures with
positivity biases (Diener et al, 2000), and independent versus interdependent self (Markus & Kitiyama,
1991).
The Measurement of Well-Being in
Cultural and Cross-Cultural Research
In this chapter, I generally use terms such as well-being, happiness, and subjective well-being
interchangeably. I do so out of linguistic convention and to promote a better experience for the reader. That
said, I also acknowledge that each of these concepts is distinct, and that—for research purposes—each can
be operationalized in unique ways (Diener, 1984). For a thorough discussion of definitions related to
happiness please see Haybron (2007) and Diener and Biswas-Diener (2008). Similarly, I treat the terms
small society as if it is synonymous with traditional culture. There are also instances in which these
concepts overlap with “non-western culture” and “non-mainstream culture.” While arguments can be made
for the distinctiveness of these concepts a careful parsing of these terms is beyond the scope of this chapter.
For a fuller discussion of this issues please see Mathews and Izquierdo (2009).
It is impossible to disentangle the findings of studies on the SWB of small societies from the very
methods used to conduct those societies. That is, small societies present unique opportunities to focus on
methodological difficulties even as they offer interesting possibilities for gaining new insights into
happiness. To explore this issue in detail I will discuss some of the common research practices in the crosscultural
study of SWB as well as outline their limits. Thereafter, I will argue for the importance of
enhancing current research practices with more attention to culturally sensitive data collection procedures
including interviewing and qualitative analyses.
Methods Common to Cross-Cultural Studies in SWB
Researchers have long been interested in the role that cultural factors such as norms and values play
in SWB. Studies have usually been structured around samples: their demographic categories and size.
Some studies have employed large international samples from many nations (egs. Diener & Diener, 1995;
Veenhoven, 2012). Other studies have targeted comparisons of samples from only a handful of nations
(e.g., Biswas-Diener, Vittersø & Diener, 2005; Wirtz & Napa-Scollon, 2012). A third class of SWB studies
uses analyses of data from only a single nation but using standard metrics that allow for comparison (e.g.
Biswas-Diener, Tay & Diener, 2012). Consumers of this research can be reassured by the fact that many of
these studies use longitudinal sampling or large samples of adults. Other studies have employed student
samples. Interestingly, this is an instance in which student sampling is defensible because it allows for
more direct cross-cultural comparison. Students samples, of course, limit the ability to generalize results to
there is an inherent trade-off in the costs and benefits of this method of sampling.
In cross-cultural research on SWB a standard—typically quantitative—measure is used. Perhaps
the most common of these is the Satisfaction with Life Scale (Diener, Emmons, Larsen & Griffin, 1985); a
five-item questionnaire using a 1-7 Likert scale that directs respondents to indicate their agreement with
each item. Although such methods offer the benefit of a standard medium of comparison these methods
have been criticized as insensitive to cultural norms and contexts, and therefore difficult to interpret
accurately (Thin, 2009). More recently, large samples such as the Gallup World Poll have attempted to
address this shortcoming by employing the Cantril Self-Anchoring Striving Scale (Cantril, 1965). This socalled
“Cantril Ladder” offers greater cultural sensitivity by anchoring life appraisals in the respondent’s
own experience, even those these are not made explicit. The ladders instructs, “The top of the ladder
represents the best possible life for you while the bottom of the ladder represents the worst possible life for
you.” This allows for differences in context: a rating of 6 offered by two separate respondents is assumed to
be comparable even though the best possible life might include menial employment for one and living in a
mansion for the other.
There are those, myself included, who also argue for a greater use qualitative measures in cross-
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cultural research. Qualitative measures allow for greater contextualization of data (Colby, 2009). This is
especially important when studying a highly subjective phenomenon like happiness. Qualitative methods,
such as structured interviews and ethnographic analyses, are generally more sensitive than are quantitative
measures to cultural differences in happiness. This is not to suggest, however, that such methods are
inherently superior. They are time consuming, can limit generalizability, and may be vulnerable to
researcher bias during analysis and interpretation. Even so, a combination of quantitative and qualitative
measures could be advantageous in this research. An example of this can be seen in a hypothetical study in
which the Cantril Ladder was used in conjunction with interview questions that probed respondents’
specific representation of the best and worst possible life. The subsequent interview information would
provide the basis for better understanding the numeric ratings. They might also help future researchers
understand just how comparable Cantril Ladder ratings truly are.
Case Studies
The bulk of this chapter will consist of case studies in research on the SWB of small societies.
There are, of course, too many such societies to allow comprehensive coverage in of the research in this
chapter. Instead, I have elected to focus on three small scale societies. I have chosen these specific three
examples because they meet the following criteria:
a. Existing high-quality research on SWB. Many small-scale societies have been the subject of
scientific scrutiny but this research attention has not focused explicitly on SWB or has been
methodologically limited by small sample sizes or similar problems.
b. Diversity. I have chosen these examples because they represent two distinct types of diversity. First,
they are societies with geographical diversity, located in the American Midwest, the South Pacific,
and East Africa. This is important because small scale societies give us the opportunity to examine
the ways that the natural environment influences daily psychological experiences. Second, these
examples represent diversity in “types” of culture. Each society is unique in its means of food
production, economy, language group, and spiritual beliefs.
c. Methodological lessons. Each of the example societies offers insights into the benefits and
limitations of existing research practices. The research I will report has been carried out using both
spanning qualitative and quantitative methods. I will argue that both types are necessary to ensure the
quality of SWB research.
Intentional Culture: The Amish
The Amish of North America are famous for their intentional rejection of modern technologies such
as electric light and motor vehicles. Because they live in close proximity to people who live an
industrialized lifestyle, they have become a source of media fascination. They are depicted, alternately,
with romanticism or vilification in movies and television shows. The Amish are a religious order and are
part of the Anabaptist tradition that grew out of the Protestant Reformation (Hostetler, 1993). Anabaptists
broke from the Catholic Church on the issue of baptism: the former group preferred baptism to occur in
adulthood when people are, presumably, able to make a more informed choice regarding the acceptance of
God. The Amish were persecuted in Europe and the earliest Amish immigrants to North America arrived
from Switzerland. Their descendants speak “Pennsylvania Dutch” (a bastardization of the word “Deutsch”)
which is a dialect of German. Their largest population is concentrated in Pennsylvania and Ohio (USA),
with smaller communities in Indiana, Illinois and other states. There are also communities living in Mexico,
Belize and Canada.
Amish culture is centered on the Christian religion. They believe in the concept of “gelassenheit.”
Although in modern German gelassenheit means “carefree” it has a different meaning among the Amish. It
indicates the unburdening that comes with submission to God (Kraybill, 1989). The Amish adopt a fairly
literal interpretation of Christian scripture, pray daily, and engage in community worship. They emphasize
community-based generosity and gratitude for their food, home, health and other material provisions
(which they see as blessings from God). The Amish aspire to be intentional in their behaviors. For
example, during the Vietnam War, a time when young males in the United States were drafted for military
service, military-aged Amish males chose to be “contentious objector.” As with many small societies, there
is a relative lack of privacy in Amish communities and individual behavior is monitored by the group. In
the most extreme cases, shunning (called “meidung” by the Amish) occurs as a social correction for wrong
action. One Amish man describes it this way: “Shunning works a little bit like an electric fence around a
pasture with a pretty good fence charger on it” (Kraybill, 1989, p.117).
Perhaps the most conspicuous aspect of their intentional approach to living is their rejection of
modern technologies. The Amish avoid the “perils of worldliness” assumed to be in automobiles, tractors,
electricity, the Internet and other technologies and conveniences. This separation from the world is based in
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scriptural passages that admonish non-conformity to the world and to avoid being yoked to non-believers
(Hostetler, 1993). As such, the Amish have gravitated toward a rural, agricultural lifestyle that allows for
the greatest degree of self-sufficiency. Within Amish culture are there further sub-divisions, such as the
distinction between Old Order and New Order Amish. The New Order Amish split from the Old Order in
the 1960s. The New Order generally are more permissive toward technology (e.g., commercial airline
travel, some electricity in the home) but share many conservative religious values with their Old Order
spiritual counterparts.
The very intentionality of their lifestyle is suggestive of the prospect that Amish people might enjoy
high levels of happiness. In past studies, researchers have found that people who engage in a voluntarily
simple lifestyle enjoy high levels of subjective well-being (Brown & Kasser, 2005). Further, the researchers
found that life satisfaction and affect balance were correlated with both the mindfulness and the intrinsic
values that underscore an intentional lifestyle.
The majority of research conducted with the Amish has been either anthropological or medical in
nature. The norm for inter-marriage among the Amish means that they have a relatively small gene pool
compared with “the English” (as they refer to all mainstream Americans). The small gene pool makes them
a useful group for the study of the genetic aspects of health and illness. One example of this type of
research that is directly relevant to happiness is a study of Bipolar Disorder among the Amish (Egeland,
1988). In the early 2000s, my colleagues and I also collected data on subjective well-being from 52 Amish
people (Old and New Order) living in 2 communities in Illinois (Biswas-Diener, Vittersø, & Diener, 2005).
The process of recruiting and sampling our Amish participants offers an important methodological
lesson for the study of subjective well-being outside of college student samples. Because of their desire to
separate from industrialized society the Amish must be approached with sensitivity and patience. I
originally contacted the Amish through a small, local museum of Amish culture. It was both coincidental,
and helpful, that my surname—Diener—is also a relatively common Amish surname. This curious point of
contact allowed me to introduce myself and my project. I spent 3 months visiting Amish households before
conducting my research. These social calls were often spent in silence or discussing genealogy, in order to
gain the trust of community members. During this time I had the opportunity to spend the night in Amish
homes, attend communal meals and festivities, and give public addresses in Amish primary schools. It turns
out that these public talks were the “tipping point” in my recruitment of participants. Because the Amish
have so little news of the non-Amish world they are curious about other cultures. My weekly talks on tribal
society in East Africa grew in attendance and led to a number of introductions to people who eventually
agreed to participate in our research.
We were able to recruit 52 Amish participants for our study of which 56 % were male and for
which the average age was 44. Interestingly, the average levels of life satisfaction as measured by the
SWLS (Diener et al., 1985) was 4.4; just above the neutral point. Above neutral scores are consistent with
the idea that “most people are mildly happy” (Diener & Diener, 1996), and that mild happiness is
evolutionarily advantageous (Fredrickson, 2001). Comparatively, the Amish satisfaction in our study can
be interpreted as meaning that the Amish fall lower than members of many other groups. In a study of more
than 13 thousand college students from 31 nations, for example, only students from Kenya (whose average
life satisfaction was 4.0) scored lower than the Amish (Diener & Diener, 1995).
Anecdotally, the Amish society in which we conducted our study was fraught with contrasts. On the
one hand, the Amish had a pronounced pro-social attitude. One man I interviewed, for example, had
donated tens of thousands of US Dollars toward the medical treatment of his neighbor’s son, with no
thought of repayment. Similarly, the Amish often helped one another in quilting, construction, and food
preparation. On the other hand, these neighborly behaviors were confined to in-group members. There was
a conspicuous degree of prejudice toward out-group members, especially ethnic or religious minorities.
One bishop, for example, asked me whether I thought the space shuttle Challenger exploded because there
was a Jewish person (Judith Resnick) aboard.
Another set of contrasts could be found in the relationship between the Amish and the larger
“English” society in which they live. While on the one hand there is a strong cultural push to remain
separate from industrialized society. The Amish I spoke with were highly invested in publicly conforming
to group norms related to abstaining from the use of industrial technologies and from remaining aloof from
broader society. Privately, however, the Amish revealed themselves to be as curious and as human as
people from any other society. One participant, for example, admitted that he used his workplace telephone
—an allowable technology—to phone a newspaper number that hosts recordings of the world’s news.
Another informant revealed that she had secretly flown on an airplane. These examples reflect the on-going
tension of a society that must—individually and collectively—continually re-negotiate its relation to the
larger society in which it exists. Where subjective well-being is concerned, the tension between retaining
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traditions and adapting to new circumstances is an interesting issue for research. Too often, we treat culture
as if it is a static phenomenon. The acknowledgment that culture is a dynamic system is, itself, a call for
more longitudinal data collection among small societies despite the hardship this may entail.
A closer examination of Amish satisfaction reveals some interesting cultural insights. In our study,
we measure global life domains (e.g., “self” and “social life”) as well as specific domains (e.g.,
“intelligence” and “family”). These satisfaction scores are shown in Table 1. Past research has revealed that
discrepancies between global and specific domains reflect the role cultural norms play in the construction
of satisfaction judgments (Diener, Napa-Scollon, Oishi, Dzokoto, & Suh, 2000; Oishi & Diener, 2001).
Specifically, global and specific domain satisfaction should, theoretically, be in agreement. For example, if
a person is satisfied with her romantic life, her friendships, and her family relationships—all specific
domains—she should, logically, report about the same amount of satisfaction with her overall social life
(the global domain). Diener and colleagues found that this correspondence occurred in some cultures, such
as Japan. In other cultures, however, they discovered an inflationary effect. People in Colombia and the
United States, for instance, are likely to inflate their global reports of satisfaction over that reported for
specific satisfaction. Diener and his colleagues explained that the tendency toward or away from inflation is
suggestive that—in the absence of clearly defined criteria for making a judgment—people default to a
cultural norm for positivity.
Table 1. Amish Satisfaction
Amish Satisfaction
Self-Satisfaction Social Satisfaction
Self 4.2 Social Life 5.7
Intelligence 4.7 Friends 6.1
Morality 5.3 Family 5.9
Physical Appearance 5.1 Romance 6.1
In the case of the Amish in our study, you can see that no such inflationary effect occurs. In fact, it
appears, at least in this instance, which the Amish tend toward a deflationary effect. It does not make
logical sense that Amish participants would report relatively high satisfaction with various aspects of the
self, but report significantly lower satisfaction with the self globally. In this case, the whole is less than the
sum of the parts. Although we cannot be certain, one possible explanation for this trend is to be found in
cultural norms for self-abnegation. It may be, for the Amish that experiencing “too much satisfaction” with
the self is akin to the perceived sin of pridefulness and too far from the virtue of humility.
In this respect, the Amish provide an interesting case study of small society happiness. They
appear, upon a close examination of their life satisfaction, to evaluate their lives positively. They seem
appreciative of their material circumstances and enjoy the benefits of living a values-congruent lifestyle.
On the other hand, their unique religious views give rise to cultural norms that, perhaps, dampen some of
this psychological positivity. It is here that the usefulness of more qualitative and ethnographic measures
can be easily seen. Rather than assuming an operational definition of happiness it makes sense to ask “what
is happiness for the Amish?” To some degree, it is not the upbeat emotional experience sought by many
mainstream Americans. Instead, it is a state of being “blessed by God” as the result of right thought and
behavior.
Social Roles in Small Society: Tonga Islanders
The South Pacific region and its Polynesian cultures are, perhaps, the least researched on the planet.
Their geographic isolation adds financial and time costs to any study of well-being among these
widespread island nations. One interesting exception to this is a study of the well-being of Tonga Islanders
(Moore & Younge-Leslie, 2005). Like many of its neighbors, Tonga is an archipelago of more than 100
islands although it has a population of only about 100 thousand people. Of these, about 70% live in the
“main island” of Tongatapu. Tongan society is a constitutional monarchy that has traditionally resisted
colonial incursions in the region. Approximately 70% of Tongans living in remote areas rely on subsistence
production, an activity that is largely governed by cultural prescriptions for male and female roles (food
production for men and text-tile production for women). In more populous areas approximately 37% of
people have full-time employment and are involved with fishing, agriculture, and tourist industries
(Younge-Leslie & Moore, 2012).
Moore and Younge-Leslie (2005) were interested in understanding aspects of Tongan happiness,
853
called fiafia, that were universal (similar to patterns found elsewhere) as well as those that were locally
unique. They recruited 227 respondents who completed written surveys on a wide range of constructs
related to well-being. They discovered trends that link their Tongan sample with the results of wider
research. For example, they found that the Tongans in their study were generally happy, a conclusion
reached by other researchers (eg. Diener & Diener, 1996; Biswas-Diener, Vittersø, & Diener, 2005). In
fact, the average satisfaction reported was comparable to that of people studied in the Dominican Republic
and Brazil. Specially, she found the average levels of general life satisfaction were 2.36 out of 5, indicating
reports just above the neutral point. This might reflect the generally adaptable quality of mild happiness
(Diener, Kanazawa, Suh & Oishi, 2014; Fredrickson, 2001). Moore and Younge-Leslie also discovered
strong collectivistic leanings in their sample. Using statistical regression, they found that social concerns
such as kinship duties were significant predictors of happiness while individualistic concerns were not.
As is the case in many small societies, Tongan culture places a heavy emphasis on social cohesion
(Younge-Leslie & Moore, 2012). This includes fulfilling social roles, social and kinship duties. Tongan
culture includes institutional practices to reinforce this point. The community gathers together in fono
meetings, during which matters of community concern are discussed. Similarly, Tongan society is
hierarchically organized and elders enjoy higher status than do younger people. Members of society are
assumed to fulfill specific roles including those that are status based, such as offering deference and respect
to elders, as well as material gifts. This can be seen reflected in the fact that elders, in general, reported
higher life satisfaction than did younger people in the study. Younge-Leslie and Moore offer a preliminary
psychological explanation for the higher well-being of older participants: their status affords them greater
autonomy to make personal decisions. This line of reasoning is supported by research from selfdetermination
theory (Ryan & Deci, 2000).
Tongan society offers a case study of the ways that social structure, and the cultural norms
surrounding it, can affect well-being. The formal social bonds and relatively fixed structure of society can
be seen reflected in many other studies of small societies. For example, Adelson (2009) reports that the
well-being of members of Cree society of Eastern Canada is similarly related to kinship ties and
obligations. Their concept of miyupimaatisiiun translates to “being alive well” and includes a heavy
emphasis on responsibility to kin, fulfilling prescribed social roles, and the maintenance of social networks.
These same emphases have been found by other researchers investigating the well-being of other cultures.
Kral and Idlout (2012), for example, found the theme of family was the single most important to the
happiness of more than 100 Inuit participating in their study. Although it is true that social relationships are
generally highly correlated with happiness (Tay & Diener, 2011) the Inuit in this study placed a special
emphasis on visiting with family—especially elders—and fulfilling prescribed social roles such as
parenting. Similarly, Galinha and colleagues (2013) found that subjective well-being is better predicted by
relationship satisfaction in a large sample of Mazambicans (relative to Americans). The emphasis on high
quality social bonds is a call for more sophisticated research on culture and subjective well-being. Future
researchers can parse the concept of relationships into constituent categories (e.g. fulfilling obligations,
number of friends, social status, size of family, etc.) to better understand which types of relationships
impact well-being.
Cultural understanding of Positivity and Negativity: The Maasai
The Maasai are an indigenous group living in East Africa. They are semi-nomadic pastoralists
(herders) and their language (Maa) is Bantu. Historically, the Maasai have resisted English and German
colonial rule in the region and have retained many of their traditional practices such as medicine men
(laibon), the ritual circumcisions of adolescent males and females, polygamy, and a period of warrior hood
for young males (morani). The Maasai are largely pre-literate and live in houses made of stick frames
supporting dried mud and cow dung for the walls and roof. The traditional Maasai diet consisted of cow
milk mixed with cow blood but in recent times they have supplemented this with ugali (corn meal), tea,
and chicken eggs. Roles such as gathering firewood and herding cattle are culturally prescribed by sex.
Social status is important to the Maasai. Traditionally, men enjoy the highest status. Among men, status is
conferred by wealth (having many cattle, wives, and/or a large family), leadership (being recognized as
wise and honest among one’s age peers; the Maasai have clear generational age groups), and bravery.
Women have lower status and children have no status.
Biswas-Diener, Vittersø, and Diener (2005) interviewed 127 Maasai living largely outside of the
tourist industry and world economy. Fifty-two per cent of our sample was female and the average age of
our sample was 32. The respondents were from 10 villages in the Megwerra (also, Megwara) region of
Kenya. Although the respondents in this study had no formal education they live near the border of the
Maasai Mara National Park. Tourists can be seen traveling to and from the park and approximately 20% of
the park fees are paid back to the Maasai to fund medical clinics and similar extra-cultural services.
Increasingly, Maasai children attend Christian missionary schools and some Maasai are beginning to live in
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homes with tin roofs.
Our study began with translating and back translating our measures into Maa using separate native
translators. During this process, we also conducted preliminary interviews aimed at better understanding
the local conceptualization of happiness. We were informed, in art, by earlier research suggesting that
cultural concepts are bound to specific language (Wierzbicka, 2004). For example, we identified a number
of distinct linguistic concepts related to happiness such as: 1) enchipai (general happiness; the state of
being in a joyful mood), 2) ashipai (literally to have a “bright heart,” this concept is deep contentedness),
and 3) ebiotishu (the state of being healthy and fit). Understanding local concepts of happiness is more than
simply a translation issue; it also an opportunity to place these happiness-related concepts in the context in
which they occur: event antecedents, cultural norms and values, individual appraisals and behavior
(Mesquita, 2001). Simply put, one limitation of current cross-cultural research on subjective well-being is
that reported mean levels of affect do not provide needed information about how these emotions are
interpreted, tolerated, or used.
The Maasai also enjoy a cultural pride that is common in many tribal societies. For example, they
believe that Ngai (God) endowed the Maasai with dominion over all the cattle on Earth. As pastoralists the
Maasai do not engage in hunting and generally harbor prejudices toward members of nearby tribal groups
who do. The Maasai collectively refer to these groups as Dorobo, which is a derogatory term. One Maasai
informant in our study said, “During Creation the Maasai were given all the cows. The Dorobo were given
other animals because there were no cows left. They [the Dorobo] are looked down on and are poor.
Sometimes we beat them up.”
The Maasai in our sample reported relatively high levels of happiness. For example, they reported
an average score of 5.4 out of 7 (where 4 is the neutral point) on life satisfaction (Biswas-Diener, Vittersø,
& Diener, 2005). Similarly, they reported frequent experiences of positive emotion including joy and pride.
They did report moderate amounts of worry and anger. Further, we were able to obtain two informant
reports of emotion for each of our respondents. There was a high degree of agreement across our peer
raters and all of the peer reports of affect balance (positive emotion divided by negative emotion) were
significantly greater than zero.
A better understanding of how the Maasai understand emotion can be found in our previously
unpublished qualitative data. We asked each of our respondents to list positive and negative memories from
the previous day (with the order of these two tasks counter-balanced across participants) and to repeat this
task for positive and negative memories for the prior year. We were able to collect this data from 111
individuals. In Table 2, we display the total number of events listed for each time period and for both
positive and negative valences. All but one of our respondents could list one or more positive events from
the previous day. This single exception—a 24-year-old woman—had had six goats killed by hyenas the
previous evening. Of our 111 respondents, 59 of them could not list a single negative memory from the
previous day. Of the remainder who did report a negative memory these included mentions of severely sick
or hungry children (N = 4), goats being killed by leopards and hyenas (N = 3), and sick or dying livestock
(N = 7). Interestingly, the health concerns of friends (e.g., miscarriage, illness) were mentioned with the
same frequency as personal health concerns.
Table 2. Maasai Memory Reports
Maasai Memory Reports
(N = 111)
Yesterday Last Year
Positive Events Reported 211 206
Negative Events Reported 59 162
Memory Balance Score 3.58 1.27
What could account for the highly positive memories of the Maasai in our study? It is interesting to
consider a number of culturally relevant factors. Culture could impact the way that the Maasai cognitively
process and use the information necessary for making life evaluations. Past research has shown that culture
can affect the ways that visual information is processed and retrieved (Nisbett, 2003) and the way that
norms are integrated into satisfaction judgments (Suh, 2000). Although it is speculative, these data are
suggestive of a number of interesting possibilities. First, the Maasai may have a culturally unique appraisal
system for negative events wherein only events meeting some critical threshold are encoded as negative.
For example, a minor illness may not be viewed as “complaint worthy” whereas losing livestock to a
855
predator is. In addition, the Maasai seem to have a relatively high threshold for what constitutes a negative
event. There were no events that were comparable to common daily complaints in industrialized society
(e.g., “I was stuck in a traffic jam,” “I was late for a meeting,” “I had a frustrating interaction with
customer service”). Instead, the Maasai complaints were more comparable to our more serious complaints
such as car accidents or major financial setbacks.
Both of these trends can be seen in the memory reports for negative events occurring during the
prior year. All but a small handful of respondents with whom we collected memory reports reported
negative events for the previous year. Of these, the overwhelming majority were specifically about the
drought that had plagued the region. Most of these reports mentioned livestock dying and many mentioned
outbreaks of illness. Only a handful of participants specifically mentioned a personal hardship such as
falling ill themselves. Of these personal hardships, four were complaints about money (all four were
tangentially involved with either tourism or the selling of cornmeal.
As with the memory reports for recent events the yearly memory reports offer an intriguing look
into Maasai psychology. First, it is noteworthy that so many of them reported the same negative event (the
drought). That is, the drought—for the Maasai—was on the scale that the 2006 Indian Ocean Tsunami or
Hurricane Katrina were for the regions those disasters impacted. It should be noted that there have been 12
such droughts since 1975, making them a far more frequent occurrence than their counterpart natural
disasters in other parts of the world. The wide agreement about the negative impact of the drought is
evidence that the Maasai experience their lives as linked to the natural environment and linked to one
another. This can especially be seen in the fact that very few mentioned a personal hardship (“I had to walk
15 kilometers to fetch water”) whereas many mentioned illness in other people or the death of livestock.
The way the Maasai conduct mental appraisals of past events is not well understood and is in need
of further study. These preliminary findings point, however, to new research questions. For instance,
researchers have found that memory of events is related to but not identical to the actual experience of
events (e.g., Wirtz, Kruger, Scollon & Diener, 2003). Further, research reveals that more global judgments,
such as yearly as opposed to daily judgments, are more likely to draw upon cultural norms (Diener et al,
2000; Suh, Diener, Oishi & Triandis, 1998). The Maasai offer a unique opportunity to test cultural
differences in appraisal thresholds for both types and frequency of events as well as into the shared nature
of appraisal.
Conclusion
Small societies offer well-being researchers a unique laboratory in which to improve our
methodology and gain new empirical insights. Regarding the first point, the lion’s share of international
study in the field of well-being is ensconced in cross-cultural approaches. While this approach offers a
standard by which to compare individuals and groups it is also limiting. Well-being researchers are advised
to expand their methodological approaches by increasing their focus on cultural, rather than cross-cultural,
understanding of key concepts. This typically means the collection and analysis of more qualitative data.
This is especially important in establishing a sensitive and comprehensive understanding of local
definitions of well-being (see Sell & Nagpul, 1992). This is a difficult challenge because, from a practical
standpoint, it means increased time in the field, longer duration of study, fewer participants, higher
expenses, more travel, and more complexities regarding linguistic translation. Despite these challenges it is
a worthwhile undertaking. In part, because small societies are, by their very definition, small and isolated.
This means that it is easier to get representative samples of the population and that the society itself can act
as a laboratory in which certain conditions are naturalistically controlled.
The methodological complexities of investigating the well-being of small societies also raises the
prospect of increased Interdisciplinary collaboration. Well-being researchers, and especially psychologists
and economists who gravitate toward cross-cultural approaches, might benefit from the expertise of those
who are oriented toward cultural approaches. Historically, disciplinary approaches to definition and
measurement have served as an obstacle to effective cross-disciplinary research. Even so, there are
examples in the well-being literature of interdisciplinary theory (Ahuvia et al, 2015) as well as empirical
study (Inglehart, Foa, Peterson & Welzel, 2008). Greater dialogue between academics could help
researchers improve methods, enrich their understanding, and bridge levels of analyses.
Small societies also offer unique opportunities to better understand well-being. It may be that,
historically, small societies have been treated as nothing more than curious case studies that are so small
and so culturally relativistic that results from their study are not generalizable. To the extent that this claim
is true it is likely more so in psychology than in anthropology. Rather than thinking of small societies as
interesting oddities, well-being researchers would do well to consider them as unique laboratories. In many
cases, the geographical isolation, possible in-group biases, and small populations mirror—to some extent
— the controlled conditions of the research laboratory. The linguistic and cultural challenges they present
856
also encourage researchers to reflect on their methodological assumptions and continue to innovate data
collection and analysis.
All cultures change, including those of small societies. In fact, as technology increases
globalization, it is small societies that face the most dramatic impacts and the most rapid potential change.
As some traditional practices and languages face extinction, research offers us an opportunity to investigate
how pace of change and type of change affect well-being. Embedded within our interviews, surveys, and
other small society data are invaluable insights into kinship, vulnerability, resilience, and the pursuit of
happiness.
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2018 Ed Diener. Copyright Creative Commons: Attribution, noncommercial, no
derivatives
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Materialism and Living Well
By Tim Kasser, Ph.D., Knox College
Citation
Kasser, T. (2018). Materialism and living well. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of
well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
Materialism is a psychological construct reflecting the extent to which an individual believes that it is
important to attain money, possessions, image, and status, relative to other aims in life. This chapter
reviews evidence showing that materialism is a fundamental aspect of the human value system that stands
in relative conflict with intrinsic values concerning personal growth, close interpersonal relationships, and
helping others. Meta-analytic results and longitudinal studies demonstrate that people report lower levels
of well-being when they prioritize materialistic values and goals. Because materialism is also negatively
associated with pro-social and pro-environmental attitudes and behaviors, a strong focus on such aims is
likely to undermine the well-being of other people, other species, and future generations. Recent studies
show that materialism can diminish when people receive interventions that encourage intrinsic values, that
involve deep inward reflections, or that lead them to disengage from and question the messages of
consumer culture.
Keywords: Materialism, Values, Goals, Well-being, Social Behavior, Ecological Behavior
This chapter has four main goals. First, it will show that the construct of materialism can be
understood as an aspect of the human value system. Second, it will review the substantial empirical
evidence which has documented that people experience lower levels of personal well-being to the extent
they place a relatively high priority on materialistic values and goals. Third, it will show that when people
prioritize materialistic values and goals, they are also likely to hold attitudes and engage in behaviors that
interfere with the ability of others to live well. Finally, the chapter will describe some interventions that
hold promise for decreasing materialism and increasing well-being.
Materialism as a Part of the Human Value System
Psychologists and consumer researchers who study materialism have conceived of the construct in
varying ways. Belk (1985) first introduced the construct empirically as a personality trait with facets of
possessiveness, non-generosity, and envy. Others have considered materialism to be a feature of people’s
identities (Dittmar, 2008; Shrum et al., 2013). Still others have thought of the construct as composed of a
set of attitudes about money and wealth (Forman, 1987; Tang, 1992). Most empirical work, however, has
followed Richins and Dawson (1992) and Kasser and Ryan (1993, 1996) by conceiving of materialism as a
set of values, goals, and/or strivings. That is, to say that a person is materialistic is to suggest that s/he
believes it is important to have money and possessions that convey status and a desirable image, and that
these aims in life are relatively high priorities compared to all the other aims for which a person might
strive.1
Support for a value-based conceptualization of materialism comes from research showing that such
aims consistently emerge as a fundamental set of values across cultures. For instance, Schwartz’s (1992)
cross-cultural work has identified a cluster of self-enhancing values that includes “wealth,” “preserving my
public image,” and “social power,” as well as being “ambitious,” and “influential.” Further, Burroughs and
Rindfleisch (2002) demonstrated that the Richins and Dawson (1992) measure of materialistic values is
highly positively correlated with these self-enhancing values (as well as with hedonistic values). Using a
measure of personal “aspirations” or goals, Kasser and Ryan (1996) similarly showed the emergence of an
extrinsic factor composed of aspirations for financial success (e.g., “I will be financially successful”),
image (e.g., “My image will be one others find appealing”), and popularity (e.g., “I will be admired by
many people”). Grouzet et al. (2005) demonstrated that these three extrinsic aims consistently cluster
together in the goals of college students from 15 nations.
This body of research suggests that people experience aims for money, possessions, power, status,
and image as being relatively compatible with each other. For example, one can relatively easily pursue
both financial success and image aspirations, given that image is usually expressed through possessions
(e.g., cars, handbags) that require some level of financial success to purchase. Similarly, wealth typically
brings access to power, and power typically provides opportunities to attain wealth.
The finding that certain values are compatible with each other carries with it a corollary: Certain
860
values are also in conflict with each other. In the late 1980s and early 1990s, Schwartz (1992) made the
important discovery that across cultures the human value system is organized in a remarkably consistent
fashion, such that to the extent a person prioritizes a particular value, s/he is also likely to prioritize certain
other compatible values and to de-prioritize certain other conflicting values. Schwartz represented the
statistical extent of compatibility and conflict between values via a “circumplex” model in which the aims
that people experience as relatively consistent with each other are next to each other in the circle, the aims
that are in relative conflict are on opposite sides of the circle, and the aims that are neither in conflict nor
compatible are approximately 90 degrees apart on the circle.
Figure 1 shows a circumplex model derived from the cross-cultural work my colleagues and I
conducted on the importance people place on personal goals (Grouzet et al., 2005). In the west and southwest
portion of the circle, the reader can see that goals for financial success, popularity, and image cluster
together; their nearness to each other represents their relative compatibility, i.e., that they are relatively easy
to pursue together. It can also be noted that financial success goals are relatively compatible with
hedonism (as Burroughs and Rindfleisch (2002) also found) and that image and popularity goals are
relatively compatible with conformity goals. These findings are intuitively sensible, as money is often used
to purchase sensually pleasurable products and services, and one usually has to conform somewhat to
others’ opinions in order to obtain their praises.
Figure 1. Circumplex model representing the relative compatibility of extrinsic, materialistic goals
(for financial success, image, and popularity) and their relative compatibility and conflict with other
goals (from Grouzet et al., 2005, Journal of Personality & Social Psychology). Reprinted by
permission of the American Psychological Association.
Note as well the aspirations on the opposite side of the circumplex from these extrinsic values. Here
the reader will find the intrinsic values for self-acceptance (e.g., “I will choose what I do, instead of being
pushed along by life”), affiliation (e.g., “I will feel that there are people who really love me”), and
community feeling (e.g., “I will help the world become a better place”). The arrangement depicted in
Figure 1 reflects that people tend to experience the intrinsic aims as in relative conflict with materialistic,
extrinsic aims. That is, these values stand in dynamic tension with each other, such that it is relatively
difficult to simultaneously pursue them. For example, the strong opposition between financial success and
community feeling goals reflects the rather obvious fact that it is difficult to be simultaneously greedy and
generous. Similarly, the opposition between image/popularity and self-acceptance aspirations reflects that
in order to be popular and praised for one’s image, one must be concerned with what others will approve
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of, an approach to life that is typically inimical to one’s own personal growth (Rogers, 1961). Notably,
goals for financial success and spirituality are also at opposite ends of the circumplex, reflecting the
conflict between these aims mentioned in most religious traditions (see e.g., Belk, 1983).
Parallel results occur with Schwartz’s (1992) values measure, in which the self-enhancing values of
money, power, and achievement stand in relative conflict with self-transcendence values of universalism
(e.g., “unity with nature,” “social justice”) and benevolence (e.g., being “honest” and “helpful”).
Burroughs and Rindfleisch (2002) similarly found that Richins and Dawson’s (1992) measure of
materialism was in relative conflict with these universalism and benevolence values, as well as with values
for community and religiosity.
In sum, this body of evidence strongly supports the validity of conceiving of materialism as a set of
values and goals that people have for money, possessions, power, status, and image. It further suggests
that prioritizing materialistic values comes at the cost of de-prioritizing certain other values. As will be
described below, this fact has important ramifications for well-being.
Materialism and Personal Well-being
One of the primary questions that researchers have asked about materialism is whether prioritizing
such values promotes or hinders people’s personal well-being. Since the earliest studies on this topic
(Belk, 1985; Cohen & Cohen, 1996; Kasser & Ryan, 1993, 1996; Richins & Dawson, 1992), dozens more
have been conducted. Dittmar, Bond, Hurst, and Kasser (2014) recently undertook a thorough search for
and subsequent meta-analysis of published and unpublished studies on the relationship between
materialism and well-being. The search yielded 175 studies using 258 distinct samples across which
researchers reported 749 associations between a measure of materialism and a measure of personal wellbeing.
Across the 749 effects, Dittmar et al. (2014) found the mean size of the correlation between
materialism and well-being to be -.15; when only a single effect was selected from each of the 258 distinct
samples (to control for non-independence), the effect was also -.15 (95% CI = -.18 to -.13). Thus, the
negative association between materialism and well-being appears to be quite robust, even if it is not large.
Dittmar et al. (2014) also examined whether the size of the effect depended on the type of
materialism measure that researchers had used; to test this, they categorized 143 distinct materialism
measures into eight basic types. Substantial variation in effect sizes was notable. Stronger associations
between materialism and well-being (rs between -.19 and -.16) occurred when researchers used multifaceted
scales that assessed materialistic values and beliefs (e.g., Richins & Dawson, 1992) or scales that
assessed the importance of goals for money, image, and popularity relative to other non-materialistic goals
(e.g., Kasser & Ryan, 1993, 1996). Weaker effects (rs between -.07 and -.11) were typically obtained when
researchers used measures of materialism that were quite brief, that assessed general beliefs about money
and wealth, or that assessed the value participants placed on money in absolute (rather than relative) terms.
The size of the association between materialism and well-being also depended on how researchers
measured well-being. Dittmar et al. (2014) placed 497 well-being measures into 12 distinct categories to
examine this issue. Significant effects were obtained for all 12 categories of well-being, but the size of the
effects varied substantially. In decreasing order of effect size, materialism was associated with more
compulsive consumption (r = .44), engaging more frequently in risky health-related behaviors (like
smoking cigarettes and drinking alcohol, r = .29), a more negative self-image (r = .28), less positive affect
(r = -.23), more depression (r = .19), lower overall subjective well-being (r = -.19), a less positive selfimage
(r = -.17), more anxiety (r = .17), more symptoms of a variety of DSM Axis I disorders (r = .16),
worse physical health (r = -.15), more negative affect (r = .15), and lower life satisfaction (r = -.13). It thus
appears that there are manifold types of well-being negatively related to materialism.
Dittmar et al. (2014) also tested 25 potential moderators of the association between materialism and
well-being; these included study, sample and cultural characteristics. 18 of these potential moderators were
non-significant, and seven were significant. Specifically, the negative relationship between materialism
and well-being was stronger: a) when well-being was assessed with questionnaires (rather than interviews);
b) when participants were under (rather than over) age 18 years; c) in samples that included large
percentages of women (rather than men); d) in samples that included relatively few (vs. many) business,
economics, and law students and practitioners; e) in samples from nations with less (rather than more)
economic inequality; f) in samples from nations with slower (rather than faster) economic growth; and g) in
samples from nations that place relatively high (vs. low) importance on pleasure and an exciting life.
Importantly, none of these significant moderators revealed any conditions under which the relationship
between materialism and well-being was positive; instead, the effects were more weakly negative.
In sum, the Dittmar et al. (2014) meta-analysis demonstrates that the relationship between
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materialism and well-being is small but consistently negative. Certain measures of materialism tend to
produce stronger results than do others, and certain types of well-being are more strongly related to
materialism than are others. Further, although some sample and cultural characteristics decrease the size of
the negative relationship, the association between materialism and well-being is consistently negative
across different sorts of people and cultural circumstances.
Longitudinal and experimental studies. A clear weakness of Dittmar et al.’s (2014) metaanalysis
is that it included only studies that were correlational and cross-sectional. A handful of studies
have used more sophisticated methodologies to test how materialism and well-being relate to each other.
One approach researchers have taken is to test how changes in materialism over time correlate with
changes in personal well-being over time. Studies of Canadian college students (Hope, Milyavskaya,
Holding, & Koestner, 2014) and of Chinese business and engineering students (Jiang, Song, Ke, Wang, &
Liu, 2016) demonstrate that well-being declines as materialistic values increase over the course of one year.
Kasser et al. (2014) also examined longitudinal associations in samples of at-risk U.S. young adults, recent
U.S. college graduates, and Icelandic adults over time frames ranging from 6 months to 12 years; in all
three samples, individuals who increased in materialism over the relevant time period reported decreases in
well-being. These person-level results are complemented by nation-level time-series analyses in Norway
(Hellevik, 2003) and the U.S. (Twenge et al., 2010) revealing that as materialism levels increase in cohorts
of citizens, their overall well-being declines.
A few experimental studies have tested whether focusing on materialistic values might cause
decreases in well-being. Notably, however, ethical and practical difficulties mean that these studies
typically involve briefly exposing study participants to relatively subtle materialistic primes (vs. control
materials) before state well-being is assessed; it seems doubtful that such designs can shed much light on
the types of well-being deficits that occur in people who dispositionally prioritize materialistic values and
goals. Nonetheless, it is worth noting that increases in negative affect and decreases in positive affect have
been observed after participants view luxury consumer goods (vs. neutral images; Bauer, Wilkie, Kim, &
Bodenhausen, 2012) and think about their time as money (vs. control activities; Devoe & House, 2012).
On the other hand, Solberg, Diener, and Robinson (2004) found no effects of other sorts of activations of
materialism on well-being.
Explaining the negative association. A variety of explanations have been proposed for the
consistent negative correlation between materialism and well-being. I will not attempt to review them all
here, but will instead focus on the four explanations that have received the most attention in the research
literature.
One possibility is that materialistic individuals experience decrements in well-being because they
are not fully successful at attaining their goals of making money and obtaining possessions; this can be
called the goal-attainment perspective. For example, Nickerson, Schwarz, Diener, and Kahneman (2003)
found that the correlation between materialism and general life satisfaction was relatively weak (or nonexistent)
for wealthy individuals. That said, however, Nickerson et al. found that personal wealth did not
moderate the negative correlation between materialism and satisfaction with relationships. Other research
has found that progress at and attainment of extrinsic goals for money, image, and popularity do not
improve well-being (Niemiec, Ryan, & Deci, 2009; Sheldon & Kasser, 1998); such results seem
inconsistent with a goal-attainment perspective. Further, Dittmar et al.’s (2014) meta-analysis found no
evidence that the association between materialism and well-being is consistently moderated by personal or
household income. Meta-analytic results also showed that materialism’s negative relationship with wellbeing
is stronger in more (vs. less) economically-developed nations (i.e., those characterized by more
income equality and slower economic growth); the goal-attainment perspective would seemingly predict a
weaker relationship in more (vs. less) economically-developed nations, given the relative ease with which
material possessions and wealth can be obtained in wealthier locales. In sum, while it seems premature to
discard the goal-attainment hypothesis, this explanation of why materialism is negatively related to wellbeing
has weak and relatively contradictory evidence.
A second explanation (Sirgy, 1998) suggests that people with strong materialistic values and goals
experience substantial financial dissatisfaction, given that someone else is almost always wealthier and has
nicer possessions, and given that marketplaces continually introduce new consumer goods that are
advertised as being better than what one already owns. This dissatisfaction is thought to spill over into a
more generalized dissatisfaction with one’s life. Dittmar et al. (2014) tested this intriguing hypothesis
using multi-variate meta-analysis for mediation on studies that reported relevant data; no support for the
spill-over hypothesis was forthcoming, however.
A third, environmental congruence, hypothesis (Sagiv & Schwartz, 2000), suggests that materialism
results in lowered well-being when people find themselves in environments that are at odds with their
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values, as this leads to interpersonal conflicts, feelings of alienation, and fewer affordances for one’s
goals. Sagiv and Schwartz supported this hypothesis by showing that self-enhancing values (for power,
status, money, etc.) were negatively correlated with well-being in psychology students but uncorrelated
with well-being in business students. Other studies, however, have found that the negative correlation
between materialism and well-being persists in business-oriented samples (e.g., Jiang et al., 2016; Kasser
& Ahuvia, 2002), and that married couples who are both high in materialism have lower quality marriages
than couples who are both low in materialism or couples with mismatched values (Carroll, Dean, Call, &
Busby, 2011). Dittmar et al.’s (2014) meta-analysis found mixed support for the environmental congruence
hypothesis. On the one hand, meta-analytic results showed that the negative association between
materialism and well-being is somewhat weaker in samples composed of a large (vs. small) percentage of
business, law, and economic students and practitioners. On the other hand, the association between
materialism and well-being was still negative in samples with many business, law, and economic students
and practitioners. Further, the negative association between materialism and well-being was stronger in
samples from cultures more (vs. less) focused on pleasure and excitement; such a finding is a problem for
the environmental congruence hypothesis because hedonistic goals are generally consistent with
materialistic strivings (see Burroughs & Rindfleisch, 2002; Grouzet et al., 2005).
A fourth explanation (Kasser, 2002) has been derived from the research literature on the
organization of value-systems (reviewed above), intrinsic and extrinsic motivation (Ryan & Deci, 2017),
and humanistic/existential theories (e.g., Fromm, 1976; Maslow, 1954; Rogers, 1961). This need-based
hypothesis suggests that people have inherent psychological needs to choose their own behavior
(autonomy), to feel connected and close to other people (relatedness), and to be efficacious at their valued
behaviors (competence). When these needs are well-met, well-being is high, but when these needs are
frustrated, lower well-being occurs (see Ryan & Deci, 2017). The need-based approach proposes two main
reasons why the strong prioritization of materialistic values and goals is associated with lower well-being.
First, as people pursue their materialistic values and goals, they are likely to have many experiences that
directly interfere with need satisfaction; for example, their strong pursuit of money likely leads them to
spend more time working long hours at relatively uninteresting tasks they feel forced to complete, thereby
interfering with the satisfaction of the need for autonomy. Second, because extrinsic values tend to be in
relative conflict with intrinsic values (see Figure 1), people who prioritize materialistic values are less
likely to spend time in the intrinsically-oriented pursuits that generally provide experiences of need
satisfaction; for example, a person might spend so much time working or shopping in pursuit of her
materialistic aims that she has less time for activities relevant to family or helping others, thereby interfering
with the satisfaction of the need for relatedness. Kasser (2002) reviewed a variety of types of studies
demonstrating support for this hypothesis, and Dittmar et al.’s (2014) meta-analysis showed that
(dis)satisfaction of needs for autonomy, competence, and relatedness each partially mediated the negative
association between materialism and well-being. In addition, Kasser et al. (2014, Study 2) found that the
negative association between changes in materialism and changes in subjective well-being over two years
was fully mediated by changes in need satisfaction, such that individuals who became more materialistic
over time reported decreasing levels of need satisfaction, which, in turn, explained their decreases in wellbeing;
see Wang, Liu, Jiang, and Song (2017) for similar results.
In sum, while there appears to be substantial empirical agreement that materialism is negatively
associated with well-being, a consensus has not been reached as to why that is the case. At present, the
need-based approach appears to have the most consistent empirical support of the four explanations
reviewed here, but more research is needed on other sensible explanations that have been put forth (e.g.,
that materialism is an expression of traits such as neuroticism or agreeableness (Otero-Lopez &
Villardefrancos, 2013; Roberts & Robins, 2000; Watson, 2014). In addition, a growing body of research
shows that materialism is negatively associated with financial well-being and academic performance (see
Kasser, 2016a); further research is also needed to examine materialism’s negative relationships with these
outcomes.
Materialism and “Living Well Together”
While living a happy, satisfying life free from depression, anxiety, compulsive consumption, and
substance abuse is clearly part of what it means to “live well,” from my perspective, it is only part.
Individuals exist in families, communities, and ecospheres in which their actions affect the lives, and thus
the well-being, of other people, other species, and future generations. Thus, it is theoretically possible that
some individuals could experience relatively high levels of personal well-being while also behaving in ways
that hinder the well-being of others. Such individuals would certainly not be “living well together”
(Deneulin & McGregor, 2010).
As will be shown next, materialistic values are associated with a variety of attitudes and behaviors
that are likely to undermine others’ well-being. This is probably due to the fact, reviewed in the first
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section of this chapter, that materialistic aims stand in relative opposition to values such as helping others,
being honest, having close and loving relationships, and caring about social justice, equality, and unity with
nature (see Figure 1). That is, as people place increasing priority on materialistic values, they tend to place
less priority on the very values that would orient them towards nurturing their interpersonal relationships,
contributing to the wider community, and behaving in ecologically sustainable ways.
In terms of their close interpersonal relationships, people who prioritize materialistic values and
goals have lower-quality romantic and friend relationships (Carroll et al., 2011; Kasser & Ryan, 2001;
Solberg et al., 2004). Perhaps this is because materialistic/extrinsic values are also associated with treating
others in less empathic ways (Sheldon & Kasser, 1995), acting competitively rather than cooperatively
(Sheldon, Sheldon, & Osbaldiston, 2000), and being more Machiavellian (McHoskey, 1999) and
narcissistic (Kasser & Ryan, 1996). None of these are characteristics likely to support high quality
interpersonal relationships.
Regarding potential effects on the well-being of the members of one’s community, materialism is
negatively associated with engaging in pro-social activities (Briggs, Landry, & Wood, 2007; Sheldon &
Kasser, 1995) and positively associated with engaging in anti-social behaviors (Cohen & Cohen, 1996;
Foulkes, Seara-Cardoso, Neumann, Rogers, & Viding, 2014, Kasser & Ryan, 1993). Individuals who
prioritize materialistic values also engage in more interpersonally deviant workplace behaviors (Deckop,
Giacalone, & Jurkiewicz, 2015) and care less about corporate social responsibility (Kolodinsky, Maden,
Zisk, & Henkel, 2010), compared to their less materialistic counterparts. The broader community can also
be negatively influenced by the anti-egalitarian, prejudicial, and socially dominant attitudes common in
people who prioritize materialistic values (Duriez, Vansteenkiste, Soenens, & DeWitte, 2007; Flanagan,
Gallay, Gill, Gallay, & Naana, 2005).
Ecological sustainability is another aspect of “living well together” with which materialism appears
to interfere. To test this idea, Hurst, Dittmar, Bond, and Kasser (2013) meta-analyzed published and
unpublished data from 13 independent samples that reported 26 different effects; results showed that
materialism was negatively associated with pro-environmental attitudes (r = -.22, 95% C.I. from -.33 to .11)
and behaviors (r = -.24, 95% C.I. from -.30 to -.17). Apparently the desire for more and more money
and stuff is one factor that leads people to treat the planet in ways that leave less for other people, other
species, and future generations to meet their needs.
The conclusions that can be drawn from the correlational studies reviewed thus far are strengthened
by experiments in which researchers momentarily activate materialistic values in study participants. After
being primed with money-relevant (vs. control) stimuli, adults and children distance themselves more from
others and behave in less pro-social ways (Gasiorowska, Zaleskiewicz, & Wygrab, 2012; Goldberg &
Gorn, 1978; Roberts & Roberts, 2012; Vohs, Mead, & Goode, 2006; Wierzbicki & Zawadzka, 2016).
Priming with money (vs. control) stimuli also leads to increases in social dominance orientation (Caruso,
Vohs, Baxter, & Waytz, 2013) and more selfish behaviors in community and environmentally-relevant
resource dilemmas (Bauer et al., 2012; Frey & Oberholzer-Gee, 1997).
Cross-national findings yield similar conclusions. Kasser (2011) obtained data on the extent to
which citizens of 20 economically-developed nations prioritized hierarchy and mastery cultural values (i.e.,
values for money, status, power, achievement, etc.; Schwartz, 1999) relative to egalitarian and harmony
values (i.e., self-transcendence and intrinsic values). After controlling for variations in national wealth,
results showed that, compared to nations less focused on wealth, status, etc., more materialistic nations had
children with lower levels of well-being, aimed more advertising per hour at children, had national
maternal leave policies that were less generous, and emitted more CO2 per capita (thus contributing to more
climate disruption).
In sum, the existing evidence consistently documents that the more that people (and cultures)
prioritize materialistic values and goals, the less kindly they treat other people and the planet. Such
behaviors almost certainly will undermine the well-being of other people, other species, and future
generations. Compared to work on materialism and personal well-being, the body of literature on
materialism and others’ well-being is still relatively new and under-researched. More work is needed in an
array of diverse cultures with people of varying ages to explore the generalizability of these results. Future
research is also required to test why materialistic values are negatively associated with pro-social and proenvironmental
attitudes and behaviors; while the conflicting values perspective outlined at the start of this
section seems a sensible hypothesis, it has not received sufficient direct empirical scrutiny.
Interventions to Decrease Materialism
Given the array of problems associated with highly prioritizing materialistic values and goals, it
seems worthwhile to develop ways to diminish their prevalence in people, organizations, and society. One
865
approach, of course, is to implement policies aimed at this end; I have written elsewhere about such
policies (see Kasser, 2016a, 2016b; Kasser & Linn, 2016) so will not discuss those types of
recommendations in the current chapter. Instead I will review three types of person-level interventions that
preliminary research suggests hold particular promise for decreasing materialism.
The first set of interventions is derived from research reviewed above on the human value system.
Recall that this body of work shows that materialistic values stand in relative conflict with intrinsic, selftranscendece,
and spiritual values (see Figure 1). As such, if people are encouraged to more highly
prioritize these latter types of aims, then their focus on materialistic values should diminish. Indeed,
several short-term experiments (Dechesne et al., 2003; Fritsche, Jonas, Kayser, & Koranyi, 2010; Stillman,
Fincham, Vohs, Lambert, & Phillips, 2012; Weinstein, Przybylski, & Ryan, 2009) have found just that:
Priming people with spiritual, pro-environmental, and pro-social values results in short-term decreases in
materialistic values and behavior. Similar results were also obtained in a more extensive, multi-week
intervention conducted by Lekes, Hope, Gouveia, Koestner, and Philippe (2012). In this study, college
students were randomly assigned to write about either their two most important intrinsic values or their
typical daily tasks (e.g., cooking). Participants in the intervention group received emails over the course of
the next month reminding them of their intrinsic values, inviting them to reflect on those values, and
providing them with inspirational quotes relevant to those values; participants in the control group received
parallel emails. Results showed that at the end of the study, the control group’s values were unchanged, but
those participants in the intrinsic-activation group who reported getting immersed in the study’s activities
shifted away from extrinsic, materialistic values and toward intrinsic values. Further, this shift in values
was associated with increases in personal well-being. Unfortunately, Lekes et al. did not follow the
participants for very long after the intervention ended, so we do not yet know whether this promising type
of intervention can have more sustained effects on people’s values and well-being; future research could
certainly investigate whether this is the case.
A second type of intervention shown to decrease materialism involves inward reflection. Sheldon,
Arndt, and Houser-Marko (2003) found that when people are merely asked to pause and reconsider the way
in which they have previously rated their values, they typically, on second thought, place less importance
on extrinsic and more importance on intrinsic values. Another type of inward reflection associated with
low levels of materialism is mindfulness, or a non-judgmental awareness of one’s experience (Brown &
Kasser, 2005); in fact, training in mindfulness can make people more satisfied with their current financial
situation, which, in turn, can increase their well-being (Brown, Kasser, Ryan, Linley, & Orzech, 2009).
Gratitude reflections also cause people to de-prioritize materialistic values (Lambert, Fincham, Stillman, &
Dean, 2009), as do deep reflections on one’s own death. That is, while brief reminders of one’s death
typically increase materialism (e.g., Kasser & Sheldon, 2000), a few studies have documented that
engaging in deep, sustained reflections about one’s death decreases materialistic values and behaviors
(Cozzolino, Staples, Meyers, & Samboceti, 2004; Lykins, Segerstrom, Averill, Evans, & Kemeny, 2007);
these effects are particularly strong for people high in the personality trait of Openness to Experience
(Prentice, Kasser, & Sheldon, 2017). Together, this literature suggests that interventions involving inward
reflection might decrease materialism, but the processes involved in this effect are not well-understood.
Does inward reflection address and alleviate the feelings of insecurity known to orient people towards
materialistic values (see Kasser, 2016a)? Does reflection help people get in touch with their psychological
needs, and thus orient them towards intrinsic values? Is mindfulness really the catalyst? These are
questions future research could address.
The third type of intervention addresses the well-established body of literature showing that,
compared to less materialistic children, materialistic children ingest more advertising through their frequent
exposure to commercial media (see Kasser, 2016a). These interventions therefore attempt to decrease
children’s exposure to, and acceptance of, social models proclaiming the worth of materialistic aspirations.
Some work shows that when parents actively teach their children about the purposes of advertising and
criticize ads’ intentions, children’s materialistic tendencies decline (Buijzen, 2007; Buijzen & Valkenburg,
2005). Kasser et al. (2014) integrated this work with ideas derived from the other types of interventions
described above by testing an in-depth intervention to decrease adolescents’ materialism. After completing
baseline measures of well-being and materialism, adolescents and one of their parents were randomly
assigned to a no-treatment control group or to an intervention adapted from an established financial literacy
curriculum. Over the course of three, 3-hour group sessions, adolescents and their parents engaged in a
variety of activities designed to help the adolescents question the messages they receive from consumer
society that encourage them to spend money and acquire stuff; adolescents were also encouraged to save
and share more of their money and to develop a values-based spending plan. Materialism and well-being
were then assessed again ~2 and ~10 months after the intervention concluded. Two important sets of
findings occurred. First, while adolescents in the control group increased in materialism over the course of
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the study, adolescents in the intervention group decreased in materialism; thus, the intervention was
successful and had lasting effects. Second, while adolescents who began the study high in materialism and
did not receive the intervention decreased in self-esteem across the course of the study, adolescents who
began the study high in materialism and received the intervention increased in self-esteem; thus, the
intervention helped “at-risk” adolescents improve their self-image, and these effects were long-lasting.
In sum, preliminary evidence suggests that materialism can be decreased through each of the three
types of interventions described above. More studies are needed, however, that include samples from a
wider range of backgrounds, that involve sustained interactions with study participants (as opposed to oneshot,
brief interventions), and that assess study participants’ materialism levels for some months (or years)
after the study has ended (as opposed to immediately afterwards). More tightly controlled intervention
studies with stronger, placebo-treatment control groups are also necessary to determine whether demand
characteristics might explain the apparent success of some interventions. Some evidence suggests that the
decreases in materialism that occur after successful interventions are associated with increases in wellbeing,
but more studies are needed to replicate such findings. Finally, no studies, to my knowledge, have
explored whether interventions that decrease materialism also decrease materialistic individuals’ tendency
to treat other people and the Earth in ways that undermine others’ well-being; research is needed to explore
these types of outcomes.
Conclusion
In conclusion, I hope this review has helped readers to see that empirical evidence supports the
conclusions that: a) materialism can be fruitfully understood as a fundamental aspect of the human value
system; b) the more that people prioritize materialistic values and goals, the lower their personal wellbeing;
c) the more that people prioritize materialistic values and goals, the more likely they are to treat other
people and the Earth in ways that undermine others’ well-being; and d) it is possible to intervene in
people’s lives in ways that decrease their focus on materialism and increase their well-being. While
substantial research supports each of these conclusions, I hope that readers also see that much empirical
work remains to be done to flesh out and better explain each of these conclusions.
End Notes
1Given this definition and these operationalizations of materialism, the current chapter does not review the
growing research literature on the associations between well-being and how people use their money, e.g., if
they spend it on experiences (Van Boven & Gilovich, 2003) or prosocially (Dunn, Aknin, & Norton,
2008). It would be interesting, however to connect these two literatures more explicitly, especially given
that experiential and prosocial spending might reflect a person’s attempt to incorporate intrinsic values into
their monetary behavior.
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2018 Ed Diener. Copyright Creative Commons: Attribution, noncommercial, no
derivatives
871
Values and Subjective Well-Being
By Shalom H. Schwartz, The Hebrew University of Jerusalem; Florencia M. Sortheix, University of
Helsinki and University of Jyväskylä
Citation
Schwartz, S. H., & Sortheix, F. M. (2018). Values and subjective well-being. In E. Diener, S. Oishi, &
L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
This chapter summarizes what we know about value—SWB relations and identifies some of what we do
not know but would like to know. We first discuss the nature of values and the structured system they form.
We draw on the ten values in the Schwartz (1992) theory that form a circular motivational continuum. We
note three theoretical perspectives on relations of values to SWB. The first perspective seeks to explain
direct relations between values and SWB. A second generation of direct relations research explains
variation in relations across samples by pointing to societal-level moderators. The second perspective
examines the congruence (or similarity) between people’s values and the values prevailing in their
environment as a determinant of SWB. The third perspective sees the attainment of valued goals as the
source of SWB. We present these perspectives and the literature based on them, and note ideas for future
research throughout.
Keywords: Values, Subjective Well-being, Cross-Cultural Variations, Value Congruence
Research on relations of personal values to subjective well-being has begun to flourish only
recently. This is surprising because our values represent what we consider important and worth pursuing in
life, and our subjective well-being (henceforth SWB) represents how happy and satisfied we are with the
life we are leading. This chapter summarizes what we know about value—SWB relations and identifies
some of what we do not know but would like to know. We first discuss the nature of values and the
structured system they form. We then note three theoretical perspectives on relations of values to SWB
(Sagiv & Schwartz, 2000; Sagiv, Roccas & Hazan, 2004). The first perspective seeks to explain direct
relations between values and SWB. The second examines the congruence (or similarity) between people’s
values and the values prevailing in their environment as a determinant of SWB. The third sees the
attainment of valued goals as the source of SWB. We present these perspectives and the literature based on
them. Throughout, we note ideas for future research.
What Values Are and How They Are Structured
Both psychologists and lay people view values as broad motivational constructs that express what is
important to people (e.g., Rohan, 2000; Rokeach, 1973; Schwartz, 1992). Based on their values,
individuals perceive acts, objects, people, and events to be more or less desirable (Feather, 1995; Schwartz,
1992). People’s values are central to their identities and concepts of self (Hitlin, 2003; Rokeach, 1973). Are
they also related to our sense of well-being?
Most theorists agree in defining basic values as desirable, trans-situational goals, varying in
importance, that serve as guiding principles in people’s lives (Schwartz, 1992; cf. Kluckhohn, 1951;
Rokeach, 1973). Each person holds numerous values (e.g., achievement, security, benevolence) with
varying degrees of importance. Schwartz (1992, 2006, 2015) summarized six defining features of basic
values found in the literature. (1) Values are beliefs, inextricably linked to affect. (2) Values refer to
desirable goals. (3) Values transcend specific actions and situations. (4) Values serve as standards to guide
selection and evaluation of people, events, actions, and policies. (5) Values are ordered in a hierarchy by
their relative importance. (6) It is the relative importance of the values relevant to any attitude or behavior
that motivates and guides that attitude or behavior.
The above features characterize all values. What distinguishes one value from another is the type
of goal or motivation that the value expresses. Recognizing that every language includes thousands of value
terms, researchers have proposed more inclusive basic values for studying value origins and consequences
(e.g., Rokeach, 1973). The most popular current classification is from the theory of basic values by
Schwartz (1992, 2015). This theory defines ten broad values according to the motivation that underlies each
one. We draw on this theory to frame our examination of direct relations between values and SWB.
Presumably, the ten values are universal. This is because the values are based on one or more of
three universal requirements of human existence: needs of individuals as biological organisms, requisites
of coordinated social interaction, and survival and welfare needs of groups. People cannot cope
872
successfully with these requirements of human existence alone. To cope with them, people must articulate
appropriate goals, communicate with others about these goals, and gain cooperation in pursuing them.
Values are the socially desirable concepts used to represent and communicate these goals.
Figure 1 presents the ten motivationally distinct values in the form of a circular continuum. There is
a wedge for each value. Values in opposing wedges in the circle conflict with one another motivationally
(e.g., stimulation vs. security). Values in adjacent wedges are compatible (e.g., conformity and tradition).
Two bi-polar, higher order dimensions summarize the relations among the ten values (Figure 1). Selftranscendence
versus self-enhancement describes a conflict between values that express concern for the
welfare and interests of others versus values that express concern for one’s own interests above those of
others. Openness to change versus conservation describes a conflict between values that emphasize
independence of action, thought, and sensations and readiness for change versus security, predictability,
and resistance to change. The theory proposes that this circular structure describes the pattern of conflict
and compatibility among values across cultures. Research in over 80 countries largely confirms the circular
motivational continuum of values (Schwartz, 2017). This suggests a universal organization of human
motivations.
Figure 1. The circular structure of ten basic values, four higher order values, and two underlying
motivational sources (adapted from Schwartz, 2015).
The outer two circles in Figure 1 specify two other principles that organize relations among the
values. We discuss these principles later in this chapter. There, we cite literature that uses them to explain
the associations of values to SWB.
Table 1 lists the ten values in their order around the circle. Each is defined in terms of its
motivational goal.1 Conceiving values as organized in a circular motivational continuum has an important
implication: Any variable that is especially congruent with one basic value (e.g., supporting immigration
with universalism) should also be relatively congruent with the adjacent values (benevolence and selfdirection)
but should conflict with the opposing values (power, security and achievement). As we shall see,
this pattern generally holds for associations of values with SWB.
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Table 1. Ten basic values and their motivational goals.
Value Motivational goals
Achievement Personal success, demonstrating competence according to social standards
Power Social status and prestige, control or dominance over people and resources
Security Safety, harmony and stability of society, of relationships, and of self
Conformity Restraint of actions likely to upset others and violate social expectations or norms
Tradition Respect, commitment and acceptance of the customs and ideas that traditional culture or
religion provide the self
Benevolence Preservation and enhancement of the welfare of people with whom one is in frequent personal
contact
Universalism Understanding, and protection for the welfare of all and the environment
Self-Direction Independent thought and action-choosing, creating, exploring
Stimulation Excitement, novelty and challenge in life
Hedonism Pleasure and sensuous gratification for oneself
Adapted from Schwartz (1992).
There are three main theoretical approaches to understanding relations between values and SWB.
One approach holds that the specific motivational content of a value determines its influence on SWB. This
approach postulates that inherent properties of particular values either promote or undermine SWB. That is,
some values are ‘healthy’ and others ‘unhealthy’ (Sagiv & Schwartz, 2000; Strupp, 1980). A second
approach emphasizes the congruence or similarity between a person’s values and the values prevailing in
the environment. A third approach emphasizes the extent to which the environment constrains or facilitates
people’s attainment of their valued goals. A third approach emphasizes the effects of successfully attaining
valued goals on SWB. We discuss each approach in turn.
Direct Associations of Values With SWB: Healthy and Unhealthy Values
Theorizing by psychotherapists about value-SWB associations identified values that emphasize
autonomy, responsibility, and fairness as healthy and those based on security, conformity, or status needs
as unhealthy (Bergin, 1991; Strupp, 1980). Bilsky and Schwartz (1994) were the first social psychologists
to identify healthy vs. unhealthy values. Building on Maslow (1943) and Rokeach (1973), they argued that
healthy values are cognitive transformations of growth needs and unhealthy values are cognitive
transformations of deficiency needs. They classified stimulation, self-direction, universalism, benevolence,
and achievement as transformations of growth needs. Success in attaining the goals of these self-actualizing
values leads people to attribute more importance to them. They classified conformity, security, and power
values as transformations of deficiency needs. Failure to attain the goals of these self-protective values and
thereby overcome deprivation and threat leads people to attribute more importance to them.
Self-determination theory (Deci & Ryan, 1995; Ryan & Deci, 2001) also links human well-being to
the satisfaction of innate psychological needs (see Heintzelman, this handbook). It specifies three needs
whose satisfaction promotes well-being: autonomy, competence, and relatedness. These needs are
transformed into intrinsic, self-actualizing goals or values. Parallels between the three intrinsic goals and
the Schwartz (1992) values are autonomy—self-direction, competence—achievement, and relatedness—
874
both benevolence and universalism (Sagiv & Schwartz, 2000). Self-determination theory also identifies
extrinsic goals that derive from the need to obtain other people’s approval, admiration, and praise and to
avoid social censure (e.g., financial success, popularity, social dominance). The Schwartz values parallel to
extrinsic goals include security, conformity, power, and, perhaps, tradition.
Sagiv and Schwartz (2000) noted three mechanisms through which values and SWB may be
associated. First, pursuing healthy values may lead to perceptions (e.g. people are kind), attitudes (e.g.,
tolerance), or behaviors (e.g., helping) that, in turn, increase well-being. Conversely, pursuing unhealthy
values may lead to perceptions (people are threatening), attitudes (intolerance), or behaviors (shunning
others) that, in turn, undermine well-being. Second, pursuing healthy values may lead directly to well-being
because it satisfies intrinsic, self-actualizing needs. In contrast, pursuing unhealthy values does not satisfy
intrinsic needs and may require stressful ego-protective activity.
These first two mechanisms posit that pursuing particular values causally influences SWB. A third
mechanism posits the reverse causal direction, the level of SWB influences value priorities. People who
feel safe and satisfied with life have the emotional and cognitive resources to pursue autonomy (selfdirection)
and excitement (stimulation) and to care for the welfare of close others (benevolence) or society
and nature (universalism). People who feel unsafe and threatened, in contrast, are preoccupied with their
own problems and lack the resources to pursue these values. They emphasize values whose realization
promises greater safety, certainty, and relief from anxiety (security, conformity, tradition, and power).
First Generation Studies
Sagiv and Schwartz (2000) published the first empirical study of associations between the ten
values and SWB. They drew upon the above ideas to hypothesize that self-direction, benevolence,
universalism, stimulation and achievement values promote SWB and that power, conformity, security, and
tradition values to undermine SWB. As the value theory implies, the five values they expected to promote
SWB are adjacent in the value circle as are the four values they expected to undermine SWB. They had no
expectation for hedonism values, which lie on the boundary between these two sets. Subsequent researchers
proposed similar or no hypotheses, simply examining the observed correlations.
We found eight studies of direct value-SWB associations in non-representative student or adult
samples from seven countries (see Table 2). The SWB index was life satisfaction in most studies and
positive affect in a few. Table 2 reveals a consistent, though not perfect, tendency across studies for power
values to relate negatively and for benevolence, stimulation, and self-direction values to relate positively to
SWB, as hypothesized.2 Hedonism also related positively. Considering only significant findings, there was
also a tendency for universalism values to relate positively and conformity values to relate negatively to
SWB. Findings for achievement, tradition, and security were inconsistent. These studies offer only partial
support for the initial theorizing. Although small sample sizes and cultural differences might account for
some inconsistencies, improved theorizing and more rigorous research were clearly needed.
Schwartz (2012) and Sortheix and Schwartz (2017) suggested a new theoretical model of direct
value-SWB associations. They proposed that relations of values to SWB depend upon the interplay
between two motivational underpinnings of values. Every value has a social or a person focus, but it also
expresses a self-expansive growth orientation or a self-protective, anxiety-based orientation (Schwartz,
2006, 2015). The self-protection concept improves on the earlier deficiency concept. Self-transcendence
and openness to change values express self-expansive, growth orientations. They oppose conservation and
power values, which express self-protective, anxiety-control orientations (the top vs. bottom values in the
outer circle of Figure 1). Achievement values can be both self-expansive (expressing competence) and selfprotective
(meeting social standards) as Figure 1 shows.
Table 2. Summary of Studies Examining the Relationships between Ten Basic Personal Values and
Well-being (Pearson Correlations)
Study Sample Measures PO ACH HED ST SD UN BEN TRA CO SE
Sagiv &
Schwartz
(2000)
Israeli &
German Adults
& Students
N=1261
SWLS -.02 .04 .00 .03 -.01 -.05 .05 .02 .02 -.01
PA -.06 .10* .05 .13* .12* -.03 .05 -.08* -.12* -.13*
Israeli Business
Students N=40
SWLS .27* .05 -.11 -.10
875
PA .17 .41* -.22 -.11
Israeli
Psychology
Students N=42
SWLS -.26* -.07 .03 .18
PA -.34* -.07 .03 .07
Oishi,
Diener,
Suh, &
Lucas
(1999)
US Students
N=256-271
SWLS -.07 .13* .06 .05 -.03 -.02 .03 -.01 -.04 -.06
PA .00 .24** -.03 -.03 .01 -.05 .04 -.07 -.01 -.05
Joshanloo
& Ghaedi
(2009)
Iranian Students
N=200
LS .04 .34** .12 .01 .06 -.15 .08 -.09 -.01 .02
Affect
balance
-.05 .18* .08 -.02 .02 -.03 .04 -.22** .06 -.02
Haslam,
Whelan, &
Bastion
(2009)
Australian
Students N=180
SWB -.04 .12 .13 .29** .18* .17* .16* -.10 .08 .00
Karabati,
&
Cemalcilar
(2010)
Turkish
Students
N=1120
SWLS -.05 -.07* -.03 -.12**
-.22**
-.10*
.13**
.12***
.24**
.16**
Bilbao,
Techio, &
Paez
(2007)
Samples of
Spanish and
immigrant
adults and
students
( a v e r a g e r)
N=3664
SWLS -.09** .01 .16** .04* .14** .07** .15** .05* .00 .07*
Happiness -.05* .03 .16** .11** .17** .12** .14** .04* .02 .15**
Bobowik
et al.
(2010)
Representative
samples from 22
ESS countries +
3 from Spain
N=26778/28042
LS -
.09**
-
.06**
.15** .07** .12** .03** .12** -.08** -
.06**
-
.19**
PANA -
.07**
-
.04**
.11** .07** .12** .03** .06** -.08** -
.05**
-
.14**
Sortheix &
Lönnqvist
(2014)
Representative
samples from 25
ESS countries
N=44106
LS -
.11**
-
.07**
-
.07**
.04* -.02 .08** .08** .12** .02 -
.06**
Sortheix &
Schwartz
(2017)
Representative
samples from 35
ESS samples
N=121495
LS -
.09**
-
.06**
-
.07**
.03* -.02 .06** .06** .11** .02 -
.05**
Note. *p <. 05, **p < .01. PO = power, AC = achievement, HE = hedonism, ST = stimulation, SD = self-direction,
UN = universalism, BE = benevolence, TR = tradition, CO = conformity, SE = security, SWLS = Satisfaction with
life scale, PA = Positive affect, LS = Life satisfaction, PANA = Positive and negative affect, SWB = Subjective
well-being (LS and PANA).
These authors argued that the growth orientation and the person focus both promote SWB (see
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Table 3). The growth orientation does so because it motivates self-actualizing, free expression of own
ideas, abilities, and feelings (openness to change) and self-expansion to include concern for the welfare of
others (self-transcendence). It satisfies intrinsic needs for autonomy and relatedness. The person focus does
so because it motivates expression of one’s ideas, abilities, and feelings (openness to change) and the
pursuit of personal success and gains (self-enhancement).
In contrast, the self-protective, anxiety-control orientation and the social focus both undermine
SWB. The self-protective orientation reflects a need to avoid threat and anxiety. It undermines well-being
because it motivates subordinating the self to socially imposed expectations (conservation) or asserting
control and dominance to overcome anxiety (self-enhancement). It is directed toward extrinsic needs for
approval and status. The social focus undermines well-being because it draws attention to needs and
problems of others that may arouse concern and worry (self-transcendence) and to social expectations and
obligations that limit autonomy (conservation).
Table 3. Theorized associations between values and SWB based on crossing two sets of motivations
underlying values: growth versus self-protection and person versus social focus.
Motivational Bases of Values and
their Effects on SWB
Growth—Positive (+) Self-Protection—
Negative (-)
Person Focus—Positive (+) Hedonism, Stimulation,
Self-Direction
(+ +)
Power
Achievement
(+ -)
Social Focus—Negative (-) Benevolence
Universalism
(+ -)
Security, Tradition
Conformity
(- -)
Note: (++) = positive associations; (--) = negative associations; (+-) and (-+) = complex associations
(Sortheix & Schwartz, 2017).
Based on this theorizing, Sortheix and Schwartz (2017) hypothesized: (a) Openness to change
values, which combine a growth orientation and person focus, relate positively to SWB. (b) Conservation
values, which combine a self-protection orientation and social focus, relate negatively to SWB.
The combinations of orientation and focus that underlie self-enhancement values and selftranscendence
values have opposing implications for SWB (see Table 3). For achievement values, Sortheix
and Schwartz (2017) expected no direct association with SWB across countries. They anticipated a tradeoff
between the self-protective interest in the extrinsic goal of approval by others and the person focus on
the intrinsic goal of developing one’s competence. They assumed that the opposing implications of the selfprotection
orientation and the person focus for SWB would be approximately balanced.
For power values, they expected a negative association with SWB because the negative
implications would outweigh the positive. The self-protection goal of overcoming threats to one’s status
implies a sense of anxiety and need to control that may undermine SWB. Moreover, the positive
implications of the person focus—free self-expression—would be neutralized by negative implications of
pursuing self-interested dominance and wealth. These are extrinsic goals (Ryan & Deci, 2001) whose
pursuit increases anxiety (Kasser & Ryan, 1996) and often elicit negative reactions from others.
For universalism values, they expected no association with SWB. They assumed that the negative
implications of concern for the often-intractable problems of vulnerable out-group members and the wider
society (social focus) would neutralize the positive implications of the self-expansive transcendence of
personal interests (growth).
For benevolence values, they expected a positive association with SWB. They assumed that the
negative implications of concern for the welfare of close others (social focus) are offset by its positive
outcomes. This concern often motivates actions that promote good relations with family and friends and
satisfy relatedness needs (Deci & Ryan, 1995). The positive implications of the self-expansive
transcendence of personal interests (growth) should outweigh any weak negative implications of concern
for close others (social focus).
Sortheix and Schwartz (2017) analyzed representative data from three rounds of the European
Social Survey. Multilevel analyses across 35 countries confirmed their expectations for the associations of
all ten values with a life-satisfaction index of SWB (Table 2). This supported their theorizing that what
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determines a value’s association with SWB is its combination of growth- versus protection-orientation and
person- versus social-focus.
Second Generation Studies: Contextual Moderation
Three recent studies sought to explain variation across samples in the direct relations of values with
SWB. These studies introduced contextual variables as moderators that might explain this variation. We
present each study in turn.
Sortheix and Lönnqvist (2014) analyzed data from 25 representative national samples of the
European Social Survey. They drew upon Schwartz’ (1992) distinction between the social and person focus
of values. Social-focused values (universalism, benevolence, tradition, conformity and security) primarily
regulate how we relate socially to others and affect their interests (on the right in Figure 1). Person-focused
values (self-direction, stimulation, hedonism, achievement, and power) primarily regulate how we express
personal interests and characteristics (on the left in Figure 1). Sortheix and Lönnqvist (2014) assumed that
values’ association to SWB depend on how well values function to help individuals cope with their
environment. Different environmental contexts provide different opportunities and impose different
affordances or constraints on the successful pursuit of valued goals (Gibson, 1977). They proposed that the
level of human development in a country (HDI: affluence, health, and education) moderates direct value—
life satisfaction (LS) relations.
For social-focused values, Sortheix and Lönnqvist (2014) argued that high HDI contexts (e.g.
Norway) provide more resources for and fewer constraints against attaining their goals (e.g., equality,
harmony). Moreover, these values motivate prosocial behavior and contribute to social capital and trust
(Helliwell & Putnam, 2004; Devos, Spini, & Schwartz, 2002). They further argued that low HDI contexts
(e.g., Ukraine) provide few resources for attaining social harmony and constrain people to look out for and
protect their own interests and the interests of close others. Sortheix and Lönnqvist (2014) noted two
exceptions. They argued that security values are primarily concerned with self-protection, despite their
social focus. Moreover, benevolence values express concern for close others that motivates people to help
family and friends and promote harmony under all conditions. They hypothesized: (a) In low HDI
countries, social focused-values (except benevolence) relate negatively to SWB. (b) In high HDI countries,
social-focused values (except security) relate positively to SWB.
For person-focused values, Sortheix and Lönnqvist (2014) distinguished between openness to
change and self-enhancement values. They noted that openness to change values satisfy autonomy needs
and consistently related to higher well-being. They argued that openness to change values motivate
behaviors that are especially instrumental for adapting to the difficult and unpredictable living conditions
of low HDI environments. They further argued that power and achievement values motivate competitive,
self-assertive behavior that conflicts with the values in high HDI contexts but could be especially
instrumental for coping with the limited resources in low HDI contexts. They, therefore, hypothesized: (a)
Openness to change values relate positively to SWB across countries, but more so in low HDI countries.
(b) Self-enhancement values relate negatively to SWB in high HDI countries but positively in low HDI
countries.
Across all countries, without considering moderation by HDI, Sortheix and Lönnqvist (2014) found
that benevolence, self-direction, stimulation, and hedonism related positively to life satisfaction whereas
power, security, and conformity related negatively (Table 2). They tested their two moderation hypotheses
using the cross-level interactions between HDI and values in predicting SWB. All interactions were
significant except for benevolence and hedonism values. They correlated positively with SWB across
countries, regardless of HDI levels. In low HDI countries, as hypothesized, the social-focused values
(except benevolence) related negatively to SWB. In high HDI countries, as hypothesized, the social-focused
values (except security) related positively to SWB, but the universalism and conformity correlations were
not significant. Openness to change values related positively to SWB across countries, more so in low HDI
countries, as hypothesized. Self-enhancement values related negatively to SWB in high HDI countries, and
achievement related positively in low HDI countries. Contrary to the hypothesis, power values related
negatively to SWB in low HDI countries. This study demonstrated that the socioeconomic context
moderated eight of the ten associations between values and SWB. However, several findings did not fit the
theorizing based on the social versus person focus, especially in high HDI contexts.
In their study presented above, Sortheix and Schwartz (2017; Schwartz, 2012) also addressed the
variation in direct value-SWB associations across countries. They proposed that the cultural values that
prevail in a society moderate the associations. Cultural values refer to society’s normative system of value
emphases. Specifically, they proposed Cultural Egalitarianism as the critical moderator. This cultural value
emphasizes cooperative behavior out of personal choice, thereby preserving the social fabric (Schwartz,
2006, 2014). In egalitarian cultures, people are socialized to engage voluntarily in collaborative, productive
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work, based on internalized commitments, and to view all people as morally equal.
Sortheix and Schwartz (2017) generated moderation predictions by combining an analysis of the
cultural context in societies low versus high in Cultural Egalitarianism with the implications of pursuing
person-focused versus social-focused values. They asked whether pursuing each basic value might help
compensate for what the cultural context fails to provide and whether the cultural context could compensate
for what individuals’ values cannot provide. They argued that person-focused values confer an advantage in
low egalitarian societies. Such societies provide few resources, so, in order to succeed, individuals must
exploit their own capacities and resources and take self-assertive initiatives. This can compensate, at least
partially, for what is lacking in the non-supportive and threatening circumstances of low egalitarian
societies. They, therefore, hypothesized: In low versus high Cultural Egalitarianism societies, (a) openness
to change values relate more positively to SWB and (b) self-enhancement values relate less negatively to
SWB.
In contrast, pursuing social-focused values is less likely to motivate behavior that can compensate
for the instability, uncertainty, and selfishness that characterize low egalitarian societies. Conservation
values, grounded in anxiety, are unlikely to motivate the energy, skill, and self-assertiveness to cope with
the prevailing difcult circumstances. The needs of others, the concern of self-transcendence values, are
liable to be more intense and disturbing in low egalitarian societies. Moreover, these values motivate
harmony rather than the assertiveness and competitiveness that can overcome a lack of resources. They
therefore hypothesized: In low versus high Cultural Egalitarianism societies, (a) conservation values relate
more negatively to SWB and (b) self-transcendence values relate less positively to SWB.
The cross-level interactions that tested these hypotheses were all significant, and they confirmed all
four hypotheses. This supported the theorizing about how person- versus social-focused values affect the
ability to cope with the difficult conditions in low egalitarian societies. Moreover, Sortheix and Schwartz
(2017) compared the strength of Cultural Egalitarianism versus HDI as contextual moderators of valueSWB
associations. The cultural variable of Egalitarianism was the stronger moderator for nine values,
though not for power.3
Boer (2017) proposed that cultural factors and environmental threats (e.g., disease, wars) may
singly or jointly moderate associations of values with affective well-being. She argued that economic,
climatic, or safety threats strengthen the associations between affective well-being and the values that
protect against threats (e.g., conservation values). Moreover, threat also interacts with culture. Adequate
cultural responses to threat (e.g., cultural embeddedness) can diminish the impact of threat on value–wellbeing
associations. Boer (2017) obtained some support for her views, using country as a proxy for the level
of threat and of the type of culture. She compared small student samples from four countries. To assess her
theorizing requires research that measures threat levels and types of culture directly and uses larger, more
representative samples.
Value-Environment Congruence and SWB
The second approach to understanding relations of values to SWB emphasizes the extent to which
people’s values are congruent with (i.e., similar to) those in their environment, whatever the motivational
content of their values. Sagiv and Schwartz (2000) proposed three mechanisms through which person–
environment value congruence influences SWB.
The first mechanism refers to the opportunities and constraints that the environment affords for
goal-attainment. Environmental affordances (Gibson, 1977) are likely to be more favorable to goalattainment
when a person’s values are congruent with those prevailing in the environment. The second
mechanism refers to the positive or negative social sanctions likely to be experienced in the environment.
When people share similar values, these values take on normative force. Expressing congruent values
promotes SWB because others validate them and provide social support. Expressing non-congruent values
undermines SWB because others disapprove or even punish. The third mechanism refers to internal value
conflict, conflict within one’s own value system that may diminish SWB. This happens if values
internalized from the environment contradict the values a person already espouses.
The studies of context as a moderator of direct value-SWB associations applied two of these
mechanisms to explain moderation effects. These studies hypothesized and tested how variation in aspects
of the context (HDI or Cultural Egalitarianism) affected the environmental affordances that constrained or
facilitated attaining the goals of particular values. The environmental affordances moderated the
associations of those values with SWB. In addition, Sortheix and Schwartz (2017) referred to the social
sanctions mechanism to explain why power values relate negatively to SWB regardless of cultural values.
Researchers have applied the mechanisms that account for the effects of value-environment
congruence on SWB to many environments (e.g., family, friends, organization, profession, and
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community). We discuss a selection of these.
Congruence with Reference Groups
Sagiv and Schwartz (2000) studied congruence between the values of business and of psychology
students with the values prevalent in the departments in which they had chosen to study. They assumed that
power values are more important than benevolence values in Israeli business schools, but the reverse is true
in psychology, an assumption supported in Gandal, Roccas, Sagiv, and Wrzesniewski (2005). As expected,
those who endorsed values congruent with the environment had higher well-being. Endorsing power values
related positively to SWB among business students, but not among psychology students. Endorsing
benevolence values related positively to SWB among psychology students, but not business students.
Studies of business students in Singapore (Kasser & Ahuvia, 2002) and Belgium (Vansteenkiste,
Duriez, Simons, & Soenens, 2006) did not show the congruence effect, however. These studies measured
extrinsic and materialist values in the self-determination theory tradition, not the power value. They found
that business students had lower well-being the more importance they ascribed to materialist values. The
opposing findings might reflect differences in the index of values, the actual values prevailing in the
various business schools, national cultures, or something else. Further research is needed to clarify this.
Later studies operationalized value congruence objectively, correlating individuals’ values with their
group’s average values. Sortheix and Lönnqvist (2015) found that students in Argentina, Bulgaria, and
Finland whose values were more congruent with students in their discipline (psychology or business) had
higher life satisfaction and positive affect and lower negative affect. Moreover, value congruence led to
better interpersonal relationships, which partially mediated the value congruence - SWB association. In a
longitudinal study, Sortheix, Olakivi, and Helkama (2013) found that Finns whose values were more
congruent with those of others in their small community had better psychological health.
In a Russian national sample, Khaptsova and Schwartz (2016) found greater life satisfaction among
those whose values were more congruent with others with similar socio-demographic characteristics (age,
gender, education, and ethnicity). Thus, the value congruence effect extended even to an implicit reference
group with which one did not interact directly.
Numerous organizational studies demonstrate beneficial effects on SWB of sharing values with
colleagues or with the organization. For example, perceived compatibility between individual and
organizational values was critical in predicting higher work well-being (Leiter & Maslach, 1999).
Congruence between personal values and the core values of one´s profession may also protect against poor
well-being. Social work is a profession that emphasizes benevolence and universalism values as opposed to
power and face (prestige) values (cf. NASW Code of Ethics, 2008). Tartakovsky (2016) found that the
more social workers endorsed benevolence and universalism values and the less they endorsed power and
face values, the less exhaustion and burnout they experienced.
Value Congruence Among Marital Couples
Research using difference scores and profile correlations to measure value congruence found that
Israeli couples’ overall value similarity correlated with their relationship satisfaction (Gaunt, 2006). A
study of Finnish couples examined similarity on each of the ten values separately (Leikas, Verkasalo,
Ilmarinen, Vartiainen, & Lönnqvist, 2017). The relationships between value similarity and relationship
satisfaction depended on gender. For men, similarity with their spouse in self-direction values related
positively to satisfaction. For women, similarity with their spouse in conformity values related negatively
to satisfaction. For both men and women, similarity with their spouse in hedonism values related positively
to satisfaction. However, value similarity mattered less for couples’ satisfaction than similarity in political
attitudes and religiosity, variables that are influenced by underlying values (Leikas et al., 2017).
Value Congruence with the Societal Culture
If individuals strongly identify with the society in which they live, we might expect that congruence
between their values and those in the society would affect SWB. Zilberfeld (2010) assessed this possibility
in a study of ultra-orthodox students in Israel. Ultra-orthodox society emphasizes the embeddedness of the
person in the group and rejects autonomous thought and action. As expected, SWB correlated positively
with endorsing conformity values and negatively with endorsing self-direction values. This pattern of
correlations did not replicate among students from the wider Israeli society that does not share the same
cultural value emphases.
On the broader societal level, however, there is little support for the hypothesis that similarity
between individuals’ values and those of their country promotes SWB. Schwartz (2012) tested this
hypothesis with data from representative samples from 32 European Social Survey countries. Contrary to
the hypothesis, congruence with the average value in the country increased the negative correlations of
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conservation values with SWB and decreased the positive correlations of openness to change values with
SWB. Research on cultural estrangement also questions the positive role of congruence between
individuals’ values and those in their society. Cultural estrangement is the inverse of congruence. It refers
to the discrepancy between personal values and perceived societal values (Bernard, Gebauer, & Maio,
2006). The congruence hypothesis would predict a negative association between cultural estrangement and
mental health indicators. However, Bernard et al. (2006) found no association between value discrepancies
and psychological outcomes.
Perhaps value congruence with one’s society enhances SWB only when individuals are aware of
the prevailing cultural values and identify strongly with the society. This is a topic for future research.
Caveat
A problem overlooked in some similarity studies is that apparent similarity effects may be due to
the value scores of the individuals and/or groups compared. To uncover unique effects of similarity
requires first controlling for the actual value scores. Such controls may eliminate similarity effects (e.g.,
Dyrenforth, Kashy, Donnellan, & Lucas, 2010) or leave them unchanged (e.g., Khaptsova & Schwartz,
2016; Sortheix & Lönnqvist, 2015).
Attaining Valued Goals and SWB
This third approach is concerned with the process through which values lead to SWB. It proposes
that the link between a value and SWB depends upon the successful attainment of the goals the value
motivates a person to pursue. Unlike the healthy values approach, it does not assume that holding particular
values (e.g., self-direction) is conducive to SWB. Rather, it assumes that people experience high SWB to
the extent they attain the goals they. Some evidence suggests that simply attaining a valued goal is
sufficient to enhance SWB (e.g., Oishi, Diener, Suh, & Lucas, 1999). Other evidence suggests that the
effect on SWB depends on the nature of the goal that is attained (e.g., Sheldon & Kasser, 1998).
In a study by Oishi et al. (1999), students reported daily for 23 days how satisfied they were with
their achievements and their social life. They also reported whether it was a good or bad day. Subsequently,
they completed a measure of the importance they ascribe to the ten basic values. Students’ goal attainment
(indicated by their daily satisfaction with their achievements and social life) predicted their daily wellbeing.
Except for achievement, their values did not (Table 2). But their values did moderate the effect of
goal attainment. Satisfaction with achievements predicted well-being more strongly for those high in
achievement values than for those low in achievement values. Likewise, satisfaction with their social life
predicted well-being more strongly for those high in benevolence values than for those low in benevolence
values.
Another analysis showed that various activities were more or less satisfying to the extent that they
were consistent with individual’s important values (Oishi et al. 1999). For example, the more people valued
power, the more satisfaction they gained from performing power-related activities (e.g., buying expensive
clothes). Findings were similar for the effects of achievement, universalism, benevolence, and
stimulation/hedonism values on the satisfaction gained from their related activities. Moreover, the more
importance individuals attributed to a value, the less satisfaction they gained from activities related to the
values on the opposite side of the value circle. For example, the more people valued universalism, the less
satisfaction they gained from power-related activities. The third analysis in Oishi et al. (1999) showed that
values also moderated relations between satisfaction in particular life domains and global life satisfaction.
For example, satisfaction with grades related more strongly to life satisfaction the more important
achievement values.
In sum, values led to increased SWB when the goals they motivated were successfully attained.
This process applied to all values in Oishi et al. (1999). However, other research suggests that not all goal
attainment is beneficial for SWB. Most of this research is grounded in self-determination theory and does
not measure the ten basic values explicitly, but we can nonetheless extrapolate from it.
In three studies of adolescents and young adults, Kasser and Ryan (1993) examined associations of
individuals’ aspirations with various indexes of well-being. Aspirations for financial success (i.e., power
values) related negatively to well-being, fitting the healthy values expectation. Significantly for the goal
attainment approach, anticipating attainment of the desired financial success also led to poorer well-being.
In a diary study of students, Sheldon and Kasser (1998) examined whether students’ goal progress during a
semester promoted their well-being. Those who made more progress toward their goals experienced
increased SWB over time. However, this occurred only if the goals they pursued were high in selfdetermination
and/or in intrinsic orientation. Such goals largely express growth values. Attaining extrinsic
(power-related) goals did not affect SWB. Kasser and Ryan (2001) reported similar findings. They found
that attainment of intrinsic goals related to increased well-being, but the attainment of extrinsic goals did
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not.
The different outcomes of attaining achievement and power-related goals in Oishi et al. (1999) and
the research based on the self-determination theory discussed above (see also, Kasser & Ahuvia, 2002;
Vansteenkiste et al., 2006) points to the need for further research. Such research could measure both the ten
basic values and the intrinsic/extrinsic values explicitly. It could identify the circumstances under which
each value motivates goals whose attainment does or does not promote SWB. It would also be instructive to
examine relations between the ten basic values and people’s intrinsic and extrinsic aspirations.
Future Research
Moderation and Mediation Studies
A clear message of this chapter is that value-SWB associations vary across contexts. We saw that
both a socioeconomic (HDI) and a cultural (Cultural Egalitarianism) characteristic of societies moderated
these associations. Other potential societal moderators also merit investigation. For example, researchers
might consider levels of democracy, social expenditure, corruption, and rural/urban differences, on the one
hand, and cultural values like embeddedness, hierarchy, and harmony, on the other. Studies in non-Western
societies might reveal other patterns of moderation. Theoretical analyses could suggest how espousing
each value might enhance or undermine successful coping with the environmental demands, constraints,
opportunities, and sanctions associated with variation on potential moderators.
Less research attention has been paid to characteristics of individuals that may moderate valueSWB
associations. One potential moderator for which there is some support is people’s social identities
(Sagiv, Roccas, & Oppenheim-Weller, 2015). Identities provide different opportunities and constraints for
attaining valued goals. Whether particular values are likely to promote SWB may depend, therefore, on
which of a person’s social identities he or she is enacting. For example, endorsing power values may
enhance SWB for a person when enacting her manager identity but undermine SWB when enacting her
friend identity. Identities may also mediate relations of values to SWB. Espousing values consonant with a
social identity (e.g., self-direction values, but not conformity values, with an artist identity) may enhance
SWB by validating the identity. Links between values, identities, and SWB are a fruitful domain for future
research. Studies of self-esteem suggest that internal conflict or confusion between the values one espouses
in different contexts may also damage SWB (e.g., Daniel, Boehnke, & Knafo-Noam 2016).
No research we found treated age or gender as possible moderators of value-SWB associations. We
analyzed data from the representative samples from 27 countries in the first three rounds of the European
Social Survey to assess whether considering these ubiquitous individual characteristics might be
worthwhile. We categorized age into four groups: 15-29, 30-45, 45-65, and 65+ years. Correlations of
values and SWB revealed monotonic trends across age groups for eight of the ten values. With increasing
age, openness to change values correlated more positively with SWB, whereas conservation and selfenhancement
values correlated more negatively. Although these findings are based on cross-sectional data,
they suggest that theorizing about why age acts as a moderator assessing possible explanations is
worthwhile. Findings for gender also revealed significant moderation. Openness to change and selftranscendence
values correlated more positively with SWB among women than among men, whereas
conservation and power values correlated more negatively. So, moderation by gender also deserves further
study.
Taken together, two cross-national studies suggest that emotions may mediate relations of values to
SWB. One study revealed that people’s values influence the emotions they desire to feel (Tamir, et al.
2016). For example, people who endorse benevolence values want to feel more empathy or love and people
who endorse power values want to feel more anger or hatred. The second study (Tamir, Schwartz, Oishi, &
Kim, 2017) found that people who experience the emotions they desire to experience, whether pleasant
(e.g., empathy or love) emotions or unpleasant (e.g., anger or hatred) emotions, are happier. Thus, people
are happier the more they experience the emotions that their own values promote, whatever the content of
their values.
We found only one study that examined both values and personality traits together as predictors of
SWB. Haslam, Whelan, and Bastian (2009) found that one or more Big 5 traits fully mediated relations of
four values to SWB in a sample of Australian students. For example, extraversion mediated relations of
stimulation and self-direction with SWB. Further studies should examine joint effects of values and traits in
larger and more representative samples. Might there be additive effects? Or might they interact in their
effects on SWB?
Causality in Value-SWB Relations
Throughout this chapter, we have spoken of relations or associations between values and SWB.
Long-term longitudinal studies are required to establish whether value change affects subsequent change in
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SWB and/or vice versa. Because values change quite slowly and only in response to major changes in life
conditions whereas SWB is more volatile, it seems more plausible to expect causality to flow primarily
from values to SWB. Three studies by Kasser et al. (2014) examined change in SWB and materialism
values (related to power value) in different age groups and cultures. In all three studies, decreases in
materialism values led to increased SWB whereas increases in materialism lead to decreased SWB.
Moreover, changes in well-being predicted changes in materialism. The SWB to materialism effect was
weaker, as our reasoning suggests, but it does indicate some reciprocal causality.
Experimental studies have examined causality in short-term relations between various types of wellbeing
and materialism values. Some primed materialist values and observed the impact on well-being (e.g.,
study 4 in Kasser et al., 2014), others manipulated well-being and observed the impact on state materialism
(e.g., Solberg, Diener, & Robinson, 2004). The findings support reciprocal causality between values and
SWB.
These studies all examined materialism values. It is important to study value-SWB causality for
other values both longitudinally and experimentally. The strength and direction of causality between values
and SWB may depend upon the specific values in question.
Different Aspects of SWB
In reviewing the various studies, we have not distinguished among different aspects of SWB.
Although values usually relate to most aspects of SWB similarly, there may be some systematic differences
worth studying. For example, social well-being, defined as a sense of integration, cohesion, acceptance,
and contribution to society (Keyes, 1998), correlated positively with conformity and negatively with selfdirection
among Iranian students (Joshanloo & Ghaedi, 2009). These findings may reflect unique
characteristics of this sample or of Iran. However, it also possible that the relationships of conformity and
self-direction values to the social aspects of SWB differ from relations to other aspects of SWB in some
conditions.
The studies of value-SWB associations we reviewed investigate satisfaction with life, happiness,
and positive and negative affect. These SWB indicators correlate positively with meaning in life, but the
association is far from perfect (Baumeister, 1991; Oishi & Diener, 2014). Meaning is an important aspect of
well-being. Research on relations of the basic values to meaning in life and on the environmental and
individual characteristics that moderate them would provide an important addition to our understanding of
how values affect the quality of life.
Recent Value Developments
We have focused on the ten basic values identified by Schwartz (1992). Recent theorizing and
research (Schwartz et al., 2012; Schwartz, 2017) has refined these values and introduced two others
(humility and face) that are recognized across cultures that may yield worthwhile new insights.
Implications for National SWB
National levels of SWB have become a tool to evaluate the progress of countries and to inform
public policy (Diener, Lucas, Schimmack, & Helliwell, 2009). Most countries with the highest levels of
SWB are in Scandinavia and West-Europe (Helliwell, Layard, & Sachs, 2012). These countries provide a
favorable context of high Cultural Egalitarianism and socio-economic level. Countries with low levels of
SWB tend to be low in Cultural Egalitarianism and socioeconomic level. Our findings imply that change in
basic values would have different consequences for national SWB in more versus less favorable contexts.
Increased emphases on self-transcendence and conservation values may enhance SWB in favorable
contexts but may weaken SWB in unfavorable contexts. Increased emphases on self-enhancement values
may weaken SWB in favorable contexts, but in less favorable contexts, achievement values could even
enhance SWB. It is, therefore, necessary to consider the context when anticipating the kinds of value
change that may help to improve people’s well-being.
Conclusion
The literature reviewed here suggests that some values are healthier than others, though not under
all circumstances. Theorizing based on combining the social- versus person-focus and the growth versus
self-protection orientation of values explains direct value-SWB associations well. However, these
associations vary across context. The context may refer to family, friends, neighborhood, organization,
demographic peers, society, and more. Sharing values (congruence) with those in close social contexts
enhances SWB. In both close and broad societal contexts, the opportunities and constraints the environment
provides for attaining valued goals moderate value-SWB associations. We can understand variation across
cultures and countries in the associations of particular values with SWB by identifying characteristics of
the context that promote or block attainment of these values. With the recent flourishing of research on
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value-SWB relations, we anticipate many new insights.
Footnotes
1Recently, Schwartz and colleagues (Schwartz, et al. 2012; Schwartz, 2017) split the same circle into 19
more narrowly defined values in their refined value theory.
2We discuss the exceptions for business and psychology students in Sagiv and Schwartz (2000) below,
under ‘value-environment congruence’.
3This study also examined associations between values and depressive affect. Hypotheses were the mirror
opposite of those for life satisfaction. All main effect hypotheses were confirmed. Cultural Egalitarianism
moderated the associations with depressive affect for only four values in the predicted manner, however.
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SOCIETAL DIFFERENCES AND POLICY
887
Happiness comes Naturally: Engagement with Nature as a Route
to Positive Subjective Well-Being
By Ethan A. McMahan, Western Oregon University
Citation
McMahan, E. A. (2018). Happiness comes naturally: Engagement with nature as a route to positive
subjective well-being. In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City,
UT: DEF Publishers. DOI:nobascholar.com
Abstract
Empirical research consistently indicates that contact with the natural world is associated with broad
psychological and physical benefit. Of particular interest are findings indicating that exposure to natural
environments improves subjective well-being, suggesting that interacting with nature may be one route by
which individuals may achieve and maintain a durable sense of happiness. In the current chapter, key
concepts and influential theories concerning the effects of nature on well-being are described. Empirical
research detailing the salutogenic effects of nature is then reviewed, with emphasis placed on four main
areas of inquiry: (1) exposure to natural environments; (2) connectedness to nature and well-being; (3)
physical proximity to nature; and (4) green exercise. Current limitations in the extant literature are
discussed, and priorities for future research are outlined. Based on the present state of research in this
domain, it is concluded that ample evidence documents the positive effects of nature on subjective wellbeing.
However, additional research examining group differences in responses to nature, causal
mechanisms accounting for the relationship between nature and well-being, and environmental factors
impacting the effects of nature on well-being, among other topics, is necessary to develop a comprehensive
and more nuanced understanding of the myriad ways in which happiness may be achieved through
engagement with the natural world.
Keywords: Nature, Natural environments, Subjective well-being, Happiness
A large body of literature examining subjective well-being now exists, and scholars and laypeople
alike are becoming more familiar with the factors that contribute to individual happiness. Of these factors,
contact with nature and natural entities seems to be a particularly powerful route by which subjective wellbeing
can be improved. For centuries, it has been observed that people experience happiness and, more
broadly, positive feeling and functioning through connection with nature. Indeed, the notion that engaging
with nature improves both psychological and physical well-being has been articulated in numerous ways by
many notable individuals across recent history (Selhub & Logan, 2012). For example, John Muir,
American naturalist and author, encouraged people to “Climb the mountains and get their good tidings,”
and by doing so “nature’s peace will flow into you,” (1901). Frederick Law Olmstead, architect of Central
Park in New York City, espoused the importance of nature for optimal psychological functioning, stating
that “the enjoyment of [natural] scenery employs the mind without fatigue and yet exercises it; tranquilizes
it and yet enlivens it,” (1865). Henry David Thoreau suggested that “we need the tonic of wilderness,”
(1854) explicitly recognizing the healing powers of nature, while Edward Abbey similarly articulated a
need for natural environments, noting that “wilderness is not a luxury but a necessity of the human spirit,”
(1968).
Complementing and building upon the qualitative sentiments provided by well-known authors,
scholars, and others regarding the importance of nature, a robust and growing body of scientific literature
also indicates that contact with nature has salutary value for individual well-being. This research indicates
that engaging with the natural environment is associated with increased positive affect and decreased
negative affect (McMahan & Estes, 2015), higher levels of satisfaction with life (Biedenweg, Scott, &
Scott, 2017), improved cognitive functioning (Berman et al., 2012), a sense of meaning in life (Passmore &
Howell, 2014a), improved physiological functioning and physical health (Bowler, Buyung-Ali, Knight, &
Pullin, 2010), and increased self-esteem (Zhang, Howell, & Iyer, 2014), among other positive outcomes.
Thus, although contact with nature is of course not a panacea for all ills, evidence suggests that engagement
with the natural environment exerts broad positive effects on human functioning, and further empirical
investigation of the effects of nature would thus seem to be an important area of positive psychological
inquiry.
Despite the seeming relevance of research on the beneficial effects of contact with nature for
positive psychology, development of these two areas has occurred largely in parallel with little systematic
exchange or explicitly identified connection between the two fields. Research on the effects of nature has
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been conducted largely within the areas of environmental psychology, public health, urban planning,
landscape aesthetics, and medicine (Bratman, Hamilton, & Daily, 2012), and has thus been guided by and
interpreted with reference to the dominant theoretical perspectives in those fields. And although positive
psychological research has focused heavily on interventions, activities, and behaviors that improve
subjective well-being (e.g., gratitude exercises, practicing mindfulness; see Sin & Lyubomirsky, 2009), a
dearth of this research recognizes contact with nature as a route by which individuals can increase wellbeing.
The current chapter emphasizes the relevance of nature research for positive psychology and, more
specifically, research on subjective well-being. By explicitly recognizing and integrating these two areas of
research, a more comprehensive, nuanced, and accurate understanding of the role that nature plays in
facilitating human well-being can be achieved.
In what follows, a brief overview of the primary theories regarding the effects of nature on
psychological functioning is provided. Existing empirical literature on the effects of nature on subjective
well-being is reviewed, with focus placed on four primary areas of inquiry: (1) exposure to natural
environments; (2) connectedness to nature and well-being; (3) physical proximity to nature; and (4) green
exercise. Limitations of the extant literature are then identified, and opportunities for research that will
move the study of the beneficial effects of nature forward are described. Before turning to the above,
however, working definitions of nature and subjective well-being are provided.
Definitions of Terms and Scope of Review
The concept of “natural” and the more narrow definition of what makes a natural environment differ
depending on history, culture, and the individual doing the defining (see Bratman et al., 2012; Proctor,
1998). Evidence suggests that what is considered to be natural is largely subjectively determined, and there
is no widely-agreed upon definition of this construct. Because of this lack of clarity, the majority of
research in this area has avoided explicitly labeling environments as natural versus unnatural in favor of a
comparative approach whereby one environment is compared to another, with one of these environments
being clearly more natural within the context of the research (e.g., a nature preserve versus a city center).
Thus, “naturalness” is typically operationally defined as a matter of degree, rather than being categorically
determined.
A common, perhaps key attribute of natural environments is that they contain elements of living
systems, including flora and fauna. Beyond this commonality, however, natural environments are a broad
and heterogeneous class of environments that can differ along several important dimensions (see Hartig,
Mitchell, de Vries, & Frumkin, 2014). Natural environments can vary in their degree of human contact,
management, and influence, with some natural environments being relatively free of human impact (e.g.,
wilderness areas) and others being created and heavily managed by humans (e.g., urban green spaces;
McMahan, Cloud, Josh, & Scott, 2016). Moreover, by incorporating natural elements within built
environments (e.g., placing potted plants within an office space), even artificial environments (i.e., those
created by humans) can be more or less natural. To accommodate this heterogeneity, a broad definition of
natural environments is adopted in the current review, where natural environments are defined as those that
include a relatively high concentration of living systems, including those of both human and non-human
origin, that exist across a range of scales and level of human development.
Whereas definitions of nature vary and are in some cases nebulous, definitions of subjective wellbeing
are widely agreed upon, consistent, and precise. Subjective well-being involves subjective
assessments of the nature and quality of individuals’ lives and includes both affective and cognitive
components (Diener, 1984). In practice, subjective well-being is typically defined as a combination of the
relative frequency of positive and negative affect and self-reported life satisfaction, with a preponderance
of positive over negative affect and high life satisfaction being indicative of high subjective well-being
(Diener, 2000; Diener, Suh, Lucas, & Smith, 1999). Notably, subjective well-being is domain-general in the
sense that it typically concerns the quality of one’s life as a whole, rather than being reflective of
satisfaction with a specific domain of functioning, and is often considered to be roughly synonymous with
the less formal term “happiness.”
Few studies have examined the effect of contact with natural environments on subjective well-being
per se and instead typically focus on the effects of contact with nature on the factors that constitute
subjective well-being (e.g., positive affect). Accordingly, the current review includes studies that have
addressed these factors, either as a sole indicator of well-being or in combination with other positive
outcomes. Additionally, while focusing on studies that assessed positive and negative affect and life
satisfaction, the current review also includes literature that assessed positive outcomes that are clearly
relevant to affective states (e.g., vitality), as well as cognitive assessments of well-being that are in some
way conceptually similar to life satisfaction (e.g., subjective happiness).
Contact with Nature and Well-Being: Primary Theories
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Three primary theories provide the foundation for the majority of research examining the effects of
contact with nature on well-being: the biophilia hypothesis, psychoevolutionary stress reduction theory, and
attention restoration theory. The biophilia hypothesis states that ancestral humans’ well-being was
integrally tied to engaging with the natural environment (e.g., for obtaining resources such as food and
water), and in result, the desire to be in contact with nature was selected during our evolutionary history
(Kellert & Wilson, 1995; Wilson, 1984). Despite the fact that modern humans no longer need to directly
interact with nature in order to ensure survival, it is believed that we retain this deeply-engrained,
biologically-based desire. Moreover, because the majority of human history took place in natural
environments and regular contact with built environments is only a relatively recent development, it is
predicted that people will tend to prefer and respond more positively to natural versus built environments.
A number of studies provide indirect support for the biophilia hypothesis, finding that people prefer visual
representations of natural environments over built environments (Kaplan, Kaplan, & Wendt, 1972; Ulrich,
1983; van den Berg, Koole, & van der Wulp, 2003) and that the preference for natural environments is
observed across cultures (Newell, 1997; Ulrich, 1993) and evident from an early age (Balling & Falk,
1982; Falk & Balling, 2010; Kahn, 1997).
Psychoevolutionary stress reduction theory (SRT) similarly posits that humans evolved to respond
positively to nature and states that contact with the types of environments that contain evolutionarily
significant resources (e.g., those with vegetation, water sources, and expansive views) elicits a
physiological and psychological response characteristic of stress reduction (Ulrich, 1979; 1981). Because
natural environments, relative to built environments, contain a greater concentration of features that signal
the presence of these resources, people should evince this response when in contact with nature. In support,
empirical research indicates that short-term exposure to natural environments is associated with increased
positive affect and decreased negative affect (Hartig, Evans, Jamner, Davis, & Garling, 2003), lower
heartrate, reduced cortisol levels, and improved immune functioning (Tsunetsugu, Park, & Miyazaki,
2010), and more rapid recovery from stress inductions (Ulrich et al., 1991). Further, evidence suggests that
these salutogenic effects of nature also operate over extended periods, as more positive health profiles are
observed among those with a history of regular and frequent contact with nature (Korpela et al., 2017a) and
those who have greater access to nature (Maas, Verheij, de Vries, Spreeuwenberg, Schellevis, &
Groenewegen, 2009; Maas, Verheij, Groenewegen, de Vries, Spreeuwenberg, 2006).
Finally, attention restoration theory (ART; Kaplan, 1995) focuses primarily on cognition and
proposes that modern urban environments tax directed attentional systems, which leads to cognitive fatigue
and higher levels of stress and irritability. In contrast, natural environments contain a high concentration of
elements that are inherently fascinating, draw on directed attentional systems only modestly, reducing
cognitive load and thus allowing for both cognitive and affective restoration (see also Kaplan, 2001). In
support, empirical work indicates that those exposed to natural environments show greater improvements in
various aspects of both cognitive and affective functioning relative to those exposed to urban environments
(Berman, Jonides, & Kaplan, 2008; Berman et al., 2012; Berto, 2005). ART also draws from evolutionary
perspectives and proposes that the well-documented human preference for natural over built environments
is the result of nature’s ability to reduce attentional fatigue, a process which would presumably aid in
survival (Joye & van den Berg, 2011).
Although the above theories differ in several respects, they each converge on the notion that
humans evolved to respond positively to nature. Notably, each of the theories predicts that contact with
nature either directly or indirectly impacts aspects of subjective well-being (e.g., by increasing positive
affect), suggesting that engaging and connecting with nature may be one route by which happiness can be
cultivated. Evidence supporting this suggestion is provided perhaps most directly by research examining
the effects of exposure to natural environments via nature interventions.
Empirical Findings
Exposure to nature and nature interventions. Much of the research examining the various
positive effects of nature has focused on the affective consequences of exposure to natural environments.
As indicated by a recent meta-analysis of over 30 experimental studies conducted within the last 50 years
(McMahan & Estes, 2015), exposure to natural environments, relative to built environments, is associated
with both moderate increases in positive affect (r = .31) and smaller, but consistent decreases in negative
affect (r = -.12). Similar findings were observed in a meta-analysis comparing the effects of exercise in
nature versus in built environments (e.g., a gymnasium), with consistently higher levels of positive affect
and lower negative affect observed among those exercising in nature (Bowler et al., 2010). More generally,
each of these meta-analyses, as well as several other systematic reviews (e.g., Barton & Pretty, 2010),
indicate that being in nature is associated with more positive emotional outcomes.
Importantly, findings from this area of research have been replicated under a variety of
890
experimental conditions and within a variety of contexts. For example, positive affective outcomes have
been observed following brief exposure to natural environments (Hartig et al., 2003; Mayer, Frantz,
Bruehlman-Senecal, & Dolliver, 2009; McMahan, Estes, Murfin, & Bryan, 2017; Nisbet & Zelenski, 2011),
as well as after longer-term exposure to nature (Korpela et al., 2017a; Passmore & Holder, 2017; Passmore
& Howell, 2014b). Similar effects have been observed among those exposed to both manicured natural
environments (e.g., parks, green spaces; Berman et al., 2008; Johansson, Hartig, & Staats, 2011) and
wilder, less managed environments (e.g., nature preserves; Lee, Park, Tsunetsugu, Kagawa, & Miyazaki,
2009; Lee et al., 2011). Findings further suggest that in addition to improving affective states in nonclinical
samples, nature may have a therapeutic effect among those diagnosed with depression (e.g.,
Berman et al., 2012). Moreover, empirical evidence indicates that technologically-mediated or virtual
exposure to nature (e.g., viewing images of nature or nature simulations) is also associated with improved
affect (e.g., McMahan et al., 2017; Valtchanov & Ellard, 2010), although effect sizes are generally smaller
than those observed following in-person exposure to real natural environments (see Kahn, Severson, &
Ruckert, 2009; McMahan & Estes, 2015).
Although the bulk of the research in this area has focused on the effects of exposure to natural
environments on affective state, several studies have examined other positive outcomes that result from
engagement with nature. For example, engagement in outdoor activity has been found to be positively
associated with satisfaction with life in multiple independent studies (e.g., Biedenweg et al., 2017; Mert,
Zurnacı, C., & Akgün, 2015; Wolsko & Lindberg, 2013). In a recent study utilizing experience sampling
methodology in a group of 20,000 participants, higher levels of subjective happiness were reported when
participants were in natural environments versus built environments (MacKerron & Mourato, 2013).
Additionally, Ryan and colleagues (2010) observed higher levels of vitality – subjective feelings of energy
and vigor – when participants engaged in activities that involved nature. Notably, Ryan and colleagues also
found increased vitality among participants who were instructed to simply imagine themselves in nature.
Further, participation in wilderness-immersion programs has been associated with increased self-esteem,
among other positive outcomes (e.g., Passarelli, Hall, & Anderson, 2010).
Given strong empirical support for the benefits of engaging with natural environments, nature-based
intervention programs have been developed recently, and initial evidence suggests these programs are
effective at promoting well-being. As one of the largest of such interventions, the David Suzuki
Foundation’s 30x30 Nature Challenge is a month-long program encouraging participants to spend 30
minutes per day in nature. Evaluations of this program indicate significant reductions in stress and
improved mood and vitality among participants (Nisbet, 2014). On a smaller scale, Passemore and Holder
(2017) found increased positive affect, sense of connectedness, and prosocial orientation among
participants in a two-week intervention program encouraging increased attention to natural environments.
The Mood Walks Initiative is a nature hiking program for older adults with serious mental illness, and
preliminary findings regarding the outcomes of the program indicate higher levels of happiness and
decreased anxiety among those participating in the program (Mood Walks, 2015). Additionally, a number
of nature-based youth development programs have been developed, and much of the evidence suggests that
these programs are effective at improving multiple facets of well-being (e.g., Collado, Staats, & Corraliza,
2013; Norton & Watt, 2014; Passarelli et al., 2010). In general, findings regarding the effectiveness of
nature-based intervention programs at improving well-being are promising. However, these programs are
relatively few in number, and a priority for future work should be to develop additional empirically-based
programs aimed at utilizing nature as a means for promoting well-being among multiple populations.
Connectedness to nature and subjective well-being. A great deal of research documents the
benefits of direct contact with the natural world. Complementing this research are findings indicating that
the degree to which individuals report feeling connected to the natural environment is also associated with
well-being. Nature connectedness is a trait-level construct reflecting the degree to which one feels this
subjective connection to the natural world (Capaldi, Dopko, & Zelenski, 2014). Like other trait-level
constructs, nature connectedness is relatively stable across time and situations (Mayer & Frantz, 2004) and
consistently predicts relevant outcomes, such as endorsement of pro-environmental attitudes and
engagement in pro-environmental behaviors (Mayer & Frantz, 2004; Nisbet, Zelenski, & Murphy, 2009;
Tam, 2013). Notably, the term nature connectedness is used broadly in the current chapter to refer to several
constructs that have been offered in previous literature, such as connectedness to nature (Mayer & Frantz,
2004), nature relatedness (Nisbet et al., 2009), inclusion of nature in self (Schultz, 2001), emotional affinity
towards nature (Kals, Schumacher, & Montada, 1999), connectivity to nature (Dutcher, Finley, Luloff, &
Johnson, 2007), and environmental identity (Clayton & Opotow, 2003), among others (see also Capaldi et
al., 2014). Although the above constructs differ in their specifics, there exists considerable conceptual
overlap, and empirical findings suggest an underlying common construct (Tam, 2013).
Numerous studies have found nature connectedness to be associated with higher levels of subjective
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well-being. For example, when developing the Connectedness to Nature Scale (CNS), Mayer and Frantz
(2004) found higher levels of life satisfaction among those who feel more connected to nature and, in later
work, that nature connectedness mediated the effects of contact with nature on positive affect (Mayer et al.,
2009). Zelenski and Nisbet (2014) found that after controlling for feelings of connectedness to other entities
(e.g., connectedness to family, to friends), nature connectedness was positively associated with multiple
indicators of well-being, such as positive affect, subjective happiness, satisfaction with life, and vitality.
Similarly, while Howell, Passmore, and Buro (2013) found higher levels of happiness and emotional wellbeing,
as well as greater meaning in life and psychological well-being, among those reporting feeling
strongly connected to nature, Tam (2013) observed that multiple indicators of nature connectedness (e.g.,
nature relatedness, emotional affinity toward nature, etc.) were positively associated with subjective
happiness, affect balance, and satisfaction with life. Indeed, the general finding that nature connectedness is
positively associated with indicators of positive feeling and functioning has been replicated multiple times
(e.g., Cervinka, Roderer, & Hefler, 2012; Korpela, Savonen, Anttila, Pasanen, & Ratcliffe, 2017b; Wolsko
& Lindberg, 2013), and correspondingly, a recent systematic review of the relevant literature found a
small, but significant association between nature connectedness and indicators of subjective well-being (r =
.18; Capaldi et al., 2014).
Given the connection between nature connectedness and subjective well-being, a number of
investigators have attempted to elucidate the factors that facilitate and contribute to the development of a
strong sense of connection to the natural world. One such factor seems to be early childhood experiences in
nature, as those who report spending more time in nature as children tend to show higher levels of nature
connectedness as adults (e.g., Ward Thompson, Aspinall, & Montarzino, 2008). For instance, research
indicates that those who grew up in rural environments report higher levels of nature connectedness than
their urban-raised counterparts (Hinds & Sparks, 2008). In fact, the consistently found association between
childhood nature experiences and nature connectedness has led some investigators to suggest that
childhood may be a sensitive period for the development of strong connections to the natural world (e.g.,
Orr, 1993). If this is the case, encouraging children to interact with nature and providing them with the
resources to do so may be an effective strategy to increase nature connectedness and, in turn, the positive
outcomes associated with feeling connected to nature.
However, the effect of frequent contact with nature on nature connectedness is not unique to earlier
developmental periods, and even brief exposure to natural environments has been found to temporarily
increase self-reported nature connectedness among samples of adults (e.g., Nisbet & Zelenski, 2011;
Schultz, 2001; Zelenski & Nisbet, 2014). Moreover, Mayer and colleagues (2009) found that the salubrious
effects of nature exposure are mediated by short-term increases in nature connectedness, indicating that
feeling that one is connected to the natural world may be one mechanism by which nature positively
impacts subjective well-being. Findings such as these highlight the importance of regular and frequent
contact with natural environments for the development and maintenance of a strong connection to nature
and, in turn, positive well-being. But, ready access to natural environments is not equally distributed, with
some areas providing greater access to nature while others less so (e.g., rural versus urban environments).
This disparity in nature accessibility is a critical factor in determining whether individuals can take
advantage of the benefits of nature exposure, a point we now turn to in the following section.
Nearby nature: Physical proximity to natural environments. For many years, it has been
believed that access to natural environments promotes well-being. Indeed, this belief was a primary factor
motivating the development of urban park systems in many Western nations during the 19th and 20th
centuries (Forbes & Kendle, 2013; Hamilton-Smith & Mercer, 1991; Walker & Duffield, 1983), and the
development of green spaces within built and urban environments in the 21st century is largely the result of
an increased understanding of the role that natural environments play in the facilitation of public health
(Ward Thompson & Travlou, 2007). Moreover, the idea that contact with nature promotes health, broadly
conceived, has been used as justification for the preservation of natural areas outside of cities as well
(Maller, Townsend, Pryor, Brown & St. Leger, 2006). In short, proposals for the development of natural
areas within built environments and the preservation of natural areas outside of built environments are
largely predicated on the notion that having access to and utilizing these environments will in some way
improve the quality of life of nearby populations.
Given the empirical research indicating that even brief contact with nature promotes well-being, a
number of studies conducted in multiple locations across the world have examined whether having ready
access to natural areas, such as green spaces, parks, and wilderness reserves, is associated with positive
outcomes (see Maller et al., 2006). Much of this research is epidemiological in nature and indicates in
general that people with access to nearby natural settings enjoy higher levels of well-being than those
without easy access to nature (Kaplan & Kaplan, 1989). For example, in a large sample of Dutch survey
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respondents, de Vries, Verheij, Groenewegen, and Spreeuwenberg (2003) found that percentage of
greenspace (e.g., urban greenspace, agricultural greenspace, nature areas) and ‘blue’ space (i.e.,
environments with a dominant natural water feature) within three kilometers of one’s residence was
positively associated with higher levels of perceived health and decreased psychiatric symptoms. Similarly,
physical distance from local greenspace has been found to predict self-reported stress and health, with those
living more than one kilometer away from the nearest greenspace reporting higher levels of stress and
decreased health-related quality of life than those who are closer to these resources (Stigsdotter et al.,
2010). Moreover, long-term relocation of one’s residence to an area with greater access to greenspace is
associated with increased health-related well-being, while, conversely, moving to a less green area has been
found to be associated with decreased well-being (Alcock, White, Wheeler, Fleming, & Depledge, 2014).
Not surprisingly given its epidemiological roots, the bulk of empirical research examining
associations between access to nature and well-being has focused primarily on physical health-related
outcomes, mortality, and indicators of negative functioning. However, recent work examining associations
between nearby nature and indicators of positive psychological functioning has generated results similar to
those presented above. For instance, data drawn from the large-scale British Household Panel Survey
(BHPS) indicates that those living in urban areas with more greenspace report high levels of life satisfaction
than their urban counterparts with less greenspace (White, Alcock, Wheeler, & Depledge, 2013). Similar
results were observed in Berlin, Germany (Bertram & Rehdanz, 2014) and Baltimore, Maryland (Vemuri,
Grove, Wilson, & Burch, 2011), with residents living in greener neighborhoods of these urban centers
reporting higher levels of life satisfaction. Thus, although research addressing associations between nearby
greenspace and indicators of subjective well-being is in its infancy, existing findings parallel those found in
health-related fields and suggest that people psychologically benefit from living close to nature.
Green exercise. The specific mechanisms that account for associations between access to
greenspace and improved well-being are as-of-yet unclear (see Lee & Maheswaran, 2011). However, many
outdoor recreation spaces are designed to promote physical activity, and existing empirical evidence
consistently indicates that regular physical activity promotes both physical and psychological well-being
(Biddle & Asare, 2011; Penedo & Dahn, 2005; Scully, Kremer, Meade, Graham, & Dudgeon, 1998). Those
living close to nature may therefore enjoy improved physical and psychological functioning, at least in part,
because they are more physically active than those who don’t have easy access to these environmental
resources (e.g., Coombes, Jones, & Hillsdon, 2010; Mytton, Townsend, Rutter, & Foster, 2012). Yet,
research examining whether physical activity mediates associations between greenspace access and wellbeing
has yielded mixed results (e.g., Maas, Verheij, Spreeuwenberg, & Groenewegen, 2008; Richardson,
Pearce, Mitchell, & Kingham, 2013), suggesting a more nuanced picture of this relationship, whereby the
effects of greenspace access on both physical activity and health depend on various characteristics of both
the environment (e.g., greenspace quality, safety) and the person (e.g., age, gender).
Despite this ambiguity, other research clearly indicates that simply being active in nature, whether
walking, jogging, or engaging in strenuous physical activity, improves feeling and functioning (e.g.,
Mitchell, 2013; Pretty et al., 2007). Further, green exercise (i.e., exercising in the natural environment) has
been found to yield greater benefits than exercising in built or synthetic environments (e.g., Pretty,
Peacock, Sellens, & Griffin, 2005), and among natural environments, higher degrees of perceived
environmental greenness are associated with more positive outcomes (Mackay & Neill, 2010). In one
recent meta-analysis, Bowler and colleagues (2010) found small to moderate effects of physical activity
environment on several distinct affective states (e.g., anger, sadness; d range = .23-.76), where exercising
in nature was associated with more positive affective outcomes than exercising in built environments.
Additionally, in a multistudy synthesis (n = 1252) of research examining the effects of physical activity in
nature using simple pretest-posttest designs, Barton and Pretty (2010) found that being active in nature was
associated with moderate improvements in both self-esteem (d = .46) and mood (d = .54). In yet another
systematic review, exercising in nature, relative to exercising indoors, was found to be associated with
increased feelings of revitalization, positive engagement, and energy, as well as decreased tension,
confusion, anger, and depression (Thompson Coon et al., 2011). Findings such as these suggest a
synergistic effect of exercise and exposure to nature, where being physically active and engaging with the
natural environment produces more positive outcomes than participating in either activity alone (see Pretty
et al., 2005).
Notably, the effects of green exercise on indicators of subjective well-being vary depending on
environmental and individual characteristics and the nature of the activity (e.g., duration). For example,
larger effects are observed in natural environments that include a prominent water feature, and some
evidence suggests that the effects of green exercise are more pronounced among younger adults, men, and
clinical populations (Barton & Pretty, 2010). Additionally, the effects of green exercise are particularly
pronounced after short visits to natural environments (approximately 30 minutes), although further but
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more modest improvements in well-being are observed for visits of longer duration (Barton & Pretty, 2010;
see also Shanahan et al., 2016). Despite requiring little time for marked improvements in well-being, those
who exercise outside, relative to those who primarily exercise in synthetic environments, report greater
frequency and duration of exercise (Hug, Hartig, Hansmann Seeland & Hornung, 2009). And, outdoor
exercise is associated with higher levels of enjoyment and lower levels of perceived exertion when
compared to indoor exercise, despite comparable levels of physiological activity (Akers et al., 2012;
Kinnafick & Thøgersen-Ntoumani, 2014). In short, being active in nature requires little time commitment,
is more enjoyable, and perceived as less physically taxing than exercising indoors. As a result, green
exercise may be a relatively expedient and self-reinforcing activity that effectively improves both physical
and psychological functioning, thus representing one promising avenue by which sustainable
improvements in well-being can be achieved.
Remaining Questions and Opportunities for Future Research
As the above review indicates, existing research now provides convincing evidence that contact
with natural environments promotes positive psychological functioning and higher levels of subjective
well-being. However, this area of inquiry suffers from several general limitations that should be addressed
in future research in order to gain a more accurate understanding of the ways in which contact with nature
produces its salubrious effects. These are (1) a lack of definitional clarity and measurement consistency of
major relevant constructs, (2) limited knowledge of group differences, and (3) unclear causal mechanisms.
Each of these limitations are described in turn below.
Definitions and consistent measurement. There is a lack of consensus with respect to defining of
the primary constructs under investigation, and correspondingly, there exists a high degree of variability in
how these constructs are manipulated and/or measured. This is perhaps most obvious, as noted previously,
when it comes to defining what it means when we use the terms “nature” or “natural,” as these concepts
have been defined in manifold ways. Although disagreements regarding appropriate definitions of these
constructs might seem like academic squabbling, the absence of broad consensus has allowed the use of
several different types of “natural” environments in the empirical literature (e.g., urban greenspace,
wilderness areas, campus gardens), and there exists both theoretical and empirical evidence suggesting that
exposure to different types of natural environments may differentially impact well-being (e.g., McMahan et
al., 2016). However, a paucity of research has explicitly recognized these differences, thus leading to a state
of relative ignorance concerning how different natural environments may impact well-being. Developing
agreed-upon definitions of “nature” and “natural” that clearly delineate the key factors that constitute these
concepts will facilitate more finely-tuned distinctions between different types of natural environments and a
higher level of precision when assessing the effects of these environments. In result, a more nuanced
understanding of what type of nature works best for improving well-being may be realized.
Relatedly, there exists a high degree of heterogeneity in how well-being and, in particular,
indicators of positive psychological functioning are defined and measured in the relevant literature. For
example, affective state has been assessed using a multitude of instruments, including the Profile of Mood
States (POMS; see Norcross, Guadagnoli, & Prochaska, 1984), the Positive and Negative Affective
Schedule (PANAS; Watson, Clark, & Tellegen, 1988), and the Zuckerman Inventory of Personal Reactions
(ZIPERS; Zuckerman, 1977), among others. Critically, these instruments differ with respect to their
emphasis on positive versus negative affect and the distinct affects assessed, and evidence suggests that
associations between nature exposure and affect varies depending on which instrument is used (Capaldi et
al., 2014; McMahan & Estes, 2015). This issue is compounded when examining broader constructs, such as
psychological functioning, which have been operationalized in many different ways. This state of affairs
introduces a high degree of variability in quantitative syntheses of the existing studies and precludes
accurate and precise estimates of the size of the effect of nature on a particular outcome. Accordingly,
future research should attempt to address this limitation by attempting to maintain consistency in the
measurement of specific outcomes.
Group differences. A second limitation concerns the origins and demographics of the samples that
are frequently used in this area of research. The majority of studies across all areas reviewed in the current
chapter have been conducted on those from relatively affluent, industrialized, Western nations. This is
problematic as evidence suggests that cultures differ in how they conceptualize the relationship between
humans and nature (e.g., Bang, Medin, & Atran, 2007; Unsworth et al., 2012), and nation-level mean
differences in nature connectedness have been observed (Tam, 2013). These culture-related differences no
doubt impact how individuals respond to the natural environment and suggest that the benefit of exposure
to nature may vary depending on cultural context. Accordingly, future research should attempt to replicate
the current findings using samples from diverse cultural and national backgrounds.
Additionally, much of the research, particularly experimental studies examining the effects of
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contact with nature (e.g., Mayer et al., 2009) as well as studies examining associations between nature
connecteness and well-being (e.g., Zelenski & Nisbet, 2014), has relied primarily on university student
samples that are quite homogenous in demographic characteristics, thus limiting the ability to generalize
corresponding findings to other populations. However, evidence from epidemiological research examining
the effects of greenspace access suggests that some demographic groups may benefit from provision of and
exposure to nature to a greater degree than others. For example, younger and older adults have been found
to benefit more from greenspace access than middle-aged adults (Kaczynski, Potwarka, Smale, & Havitz,
2009; Maas et al., 2009), associations between greenspace exposure and health are stronger for nonHispanic
Whites relative to other ethnic groups (Kerr, Frank, Sallis, & Chapman, 2007; Scott, Dubowitz, &
Cohen, 2009), greenspace access has a stronger impact on the health of lower income groups relative to
those with higher incomes (Babey, Hastert, Yu, & Brown, 2008; Maas et al., 2006), and those living in
urban areas seem to respond more positively to nearby nature than those living in rural environments
(Lachowycz & Jones, 2013). Although suggestive, the above findings are limited in their emphasis on
greenspace access, their correlational nature, and their focus on physical health-related outcomes, and
corresponding findings generated from experimental research examining potential group differences in the
effects of nature exposure on positive psychological outcomes does not exist. A priority for future research
in this area is thus to examine how contact with nature psychologically benefits individuals from varying
demographic groups.
Causal mechanisms. A dearth of research has addressed potential mechanisms that mediate the
effects of nature on well-being, and in result, we know relatively little about how nature exerts its
salubrious effects nor the routes by which it does so. Of course, the mechanisms by which nature might
affect well-being are numerous and synergistic, and the conditions under which specific mechanisms are
elicited and exert their effects likely varies depending on environmental context, an individual’s current
state of functioning, as well as personal dispositions. A key step moving forward is thus to investigate these
potential mechanisms and the situations in which they take on significance in order to develop a more
nuanced understanding of the ways in which nature does and doesn’t impact psychological well-being.
With that said, several factors represent likely candidates for mechanisms that bridge the divide
between nature and happiness. One such mechanism may be the emotion of awe. Awe is defined as an
emotional response to perceptually vast stimuli that overwhelm current mental structures (Keltner & Haidt,
2003), and exposure to nature, particularly extraordinary nature (e.g., one involving an expansive view of a
large mountain range) is suggested to be a key elicitor of this response (Shiota, Keltner, & Mossman,
2007). Critically, those who experience awe report higher levels of life satisfaction (Rudd, Vohs, & Aaker,
2012), and contact with natural environments may therefore improve life satisfaction via this emotional
response. Indirect support for this prediction comes from research examining the differential effects of
exposure to particularly beautiful or awesome natural scenes (i.e., those most likely to elicit awe) versus
more mundane natural environments, where those exposed to extraordinary nature responded more
positively than those exposed to mundane nature (Joye & Bolderdijk, 2015). However, additional research
specifically addressing whether awe mediates the association between nature exposure and well-being is
still needed.
A related potential mechanism is meaning in life. The experience of meaning in life involves an
understanding of who we are, what the world is like, and how we fit in to the grand scheme of things
(Steger, 2012) and is consistently associated with higher levels of multiple indicators of well-being (Steger,
2017; Zika & Chamberlain, 1992). Meaning in life results from transcendent experiences (Emmons, 2005)
and believing that one’s life fits in within a larger context or plan (Wong, 2010), and nature experiences
likely facilitate a sense of meaning by providing a salient reminder of one’s place in the world and a means
by which individuals can connect to something larger than the self. In support, experiences in nature have
been found to be a significant source of meaning among adults (O’Connor & Chamberlain, 1996; Reker &
Woo, 2011). Additionally, meaning in life has been found to mediate associations between dispositional
nature connectedness and well-being (Howell et al., 2013). However, to date, research has not addressed
whether the beneficial effects of contact with nature result, at least in part, from increased subjective sense
of meaning, and additional experimental research addressing whether brief nature experiences elevate sense
of meaning and, in turn, well-being should be pursued.
Positive social experiences are yet another likely mechanism mediating associations between nature
and well-being. Several lines of research indicate that natural environments are one context in which social
interactions are facilitated and existing relationships are strengthened (e.g., Coley, Kuo, & Sullivan, 1997),
and the cultivation and maintenance of positive relationships with others is considered to be a key
component of optimal human feeling and functioning (Keyes, 1998; Ryff & Singer, 1998). Indeed, feeling
connected to others has been suggested to be a psychological need (Ryan & Deci, 2000). Importantly, the
availability of high quality natural environments has been found to contribute to both social cohesion and
895
self-reported health (de Vries, van Dillen, Groenewegen, & Spreeuwenberg, 2013), and one study
conducted in the Puget Sound region of Washington State, indicated that positive social experiences
mediated associations between frequency of outdoor recreation and self-reported life satisfaction
(Biedenweg et al., 2017). Moreover, Zelenski, Dopko, and Capaldi (2015) found that brief nature exposure
increased cooperative behavior, potentially identifying one mechanism by which nature may promote
positive social interactions. Yet, as above, experimental research specifically examining whether positive
social experiences mediate associations between contact with nature and subjective well-being are lacking,
and addressing whether this is the case represents a potentially fruitful area of future inquiry.
Addressing the mechanisms that account for associations between greenspace accessibility and
well-being is a particularly complicated task, as these areas could potentially serve many different functions
for many different individuals. In fact, these spaces are often intentionally designed to serve a broad section
of the local population by providing a diversity of resources and affordances (Eysenbach, 2008). For
example, a greenspace may provide opportunities for physical activity (e.g., an extensive path system),
quiet places to relax (e.g., solitary benches next to a pond), places to engage in social interaction (e.g., a
picnic area), cultural experiences (e.g., a pavilion), and so forth. They may also provide less obvious but
beneficial resources, such as better air quality (see Hartig et al., 2014). Utilizing these resources may then
in turn positively influence both physical and psychological functioning to varying degrees, depending on
the nature of the activity in question. Additionally, it is likely that individual-level characteristics (e.g.,
dispositions, acute states of functioning) impact the significance and utilization of these resources. For
instance, a quiet place to relax may be particularly valuable for an individual who is experiencing
significant work-related stress, and utilization of this resource may be particularly important and impactful
for stressed individuals versus those who are not experiencing significant stress. In support, a number of
empirical studies indicate that the positive effects of passive nature exposure are particularly pronounced
for those in need of psychological restoration (see van den Berg, Hartig, & Staats, 2007). Taken together,
the above indicates that not only should research consider the mechanisms by which nature improves wellbeing,
but also the conditions under which it does so.
Other questions. The above identifies a few major limitations in the current literature concerning
the effect of natural environments on well-being. But, this is by no means an exhaustive account of these
limitations, and there exist many other questions that should be addressed in order to develop a more
complete understanding of the role that nature plays in the promotion of positive human feeling and
functioning. For example, most of the existing research has exposed participants to pleasant natural
environments (e.g., nature preserves) or natural environments specifically designed for human use (e.g.,
urban greenspaces), and in result, less is known about how unpleasant natural environments and those that
are not well-suited to human use and habitation affect well-being. Similarly, how individuals’ well-being is
affected by different natural environs (e.g., boreal forests, deserts, temperate rainforests) is unclear. While
a substantial amount of research documents preferences among different natural environments, finding that
individuals tend to prefer savannah-like environments, those that contain water features, and familiar
natural environments (e.g., Falk & Balling, 2010), little research has addressed whether exposure to these
environments differentially benefits individuals. In a related vein, a dearth of research examines variability
in outcomes associated with exposure to different built environments. Like natural environments, built
environments are a heterogeneous class of environments that differ in many respects (e.g., a parking lot
versus an outdoor mall). These differences are likely of practical import when investigating the manner in
which a given built environment may or may not impact psychological functioning.
While a great deal of research documents the short-term effects of nature exposure on indicators of
subjective well-being, limited research has addressed the potential long-term effects of repeated or frequent
nature exposure. That which does exist has done so using retrospective or cross-sectional research designs,
thus precluding firm conclusions regarding causality. Relatedly, at current, we know relatively little
regarding how long the effects of nature last, the ideal dose of nature, the degree to which person-related
factors impact the effects of nature, or how more specific elements within natural environments (e.g., lowlevel
visual features) enhance or perhaps hinder these effects. The rigorous investigation of these questions,
as well as those presented above, should take the forefront in future research in this area.
Final Remarks
Despite the above-listed gaps in relevant research, the existing empirical evidence unambiguously
indicates that contact with natural environments in some way positively impacts human feeling and
functioning. These findings thus validate the literary and artistic sentiments of those who have across
history espoused the importance of nature for our happiness. Relative to previous generations however,
people are now spending less time in nature (Clements, 2004; Hofferth, 2009; Soga & Gaston, 2016) and
the majority of their daily lives indoors (MacKerron & Mourato, 2013). In result, the myriad benefits of
interacting with nature go largely unrecognized and thus unrealized (see Nisbet & Zelenski, 2011). The vast
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majority of individuals have access to some form of nature, be it a local park, a large urban greenspace, or
a national forest, and utilizing these resources seems to be a relatively easy and low-cost means by which
subjective well-being can be improved. Indeed, mental health practitioners are becoming increasingly
aware of the potential clinical importance of natural environments, and applied research focusing on the
promotion of mental health via exposure to nature is therefore likely to be in increasing demand (Mantler &
Logan, 2015). Moreover, evidence suggests that interaction with nature promotes conservation-oriented
behaviors (e.g., Zelenski et al., 2015). Engaging the natural world and regularly visiting natural
environments may therefore promote positive behaviors aimed at improving the well-being of our planet, in
addition to providing an effective route by which individual happiness and positive human health can be
achieved.
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2018 Ed Diener. Copyright Creative Commons: Attribution, noncommercial, no
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Geographical Variation in Subjective Well-Being
By Peter J. Rentfrow, University of Cambridge
Citation
Rentfrow, P. J. (2018). Geographical variation in subjective well-being. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
Research on subjective well-being has shown that there are geographical differences in well-being. Drawing
on theory and research in social-personality psychology, economics, and geography this chapter reviews
research concerned with the geographical distribution of well-being, and how individual characteristics,
social institutions, and the physical environment influence that distribution. Findings from several studies
conducted at multiple levels of analysis strongly suggest that selective migration, social influence, and
ecological influence are key mechanisms responsible for the geographical clustering of subjective wellbeing.
Cross-national studies and analyses of regional differences in the U.S. indicate that the average level
of subjective well-being in geographical areas is related to a range of economic, social, and health
indicators. Moreover, evidence suggests that personality traits interact with features of the environment to
influence individual differences in subjective well-being. More work is needed to understand the causal
nature of the relations between subjective well-being and the macro environment.
Keywords: Regional Differences, Geographical Psychology, Well-being, Social Indicators
For decades, psychologists have been concerned with understanding the relations between the
environment and psychological health. Through the years, countless studies have investigated how features
of the social and physical environment affect various indicators of mental health, from depression to
happiness. Although that work has proven to be immensely valuable to our understanding of well-being,
researchers’ conceptualizations of the environment have typically been rather narrow and focused on
proximal environmental features. Consequently, considerably less attention has been given to the impact
that macro-level factors may have on well-being. However, a growing body of research that conceptualizes
environments in terms of geographical units is beginning to broaden our understanding of the links between
the environment and psychological well-being.
The relevance of geography for understanding social and behavioral processes has long been
recognized by geographers, political scientists, economists, sociologists, and epidemiologists. For example,
political scientists often examine geographical variation in polling data and their relationships to
demographic, educational, and economic indicators (Heppen, 2003; Hero, 1998); macro-economists
investigate geographical variation in labor statistics and how they relate to income, migration flows, and
human capital (Krugman, 1991; Martin, 1999); and epidemiologists study geographical variation in rates of
disease incidences and their associations with demographic, lifestyle, and economic indicators (Borhani,
1965; Glymour, Avendaño, & Berkman, 2007; Lanska, 1993). What is abundantly clear from research in
those fields is that people’s values, aspirations, and health are strongly related to features of where they
live. It therefore seems reasonable to expect geography to add to our understanding of subjective well-
being.
Indeed, a great deal of interest has emerged over the past few years concerned with geographical
variation in psychological phenomena and how that variation relates to various macro-level indicators
(Rentfrow, 2014). Much of the research in geographical psychology is concerned with mapping the spatial
organization of psychological characteristics, identifying the mechanisms responsible for their
organization, and understanding how the spatial organization of psychological characteristics relate to
political, economic, social, and health variables. This chapter reviews research concerned with
geographical variation in well-being.
The Geography of Subjective Well-Being
Subjective well-being is a psychological construct that reflects a person’s cognitive and affective
evaluation of the quality of their life (Diener, Suh, Lucas, & Smith, 1999; Diener, Lucas, Schimmack, &
Helliwell, 2009). Because it is based on people’s subjective perspectives, it can be measured easily and
reliably using self-report measures, and scores on such measures can provide valid information about the
extent to which people find their lives enjoyable, rewarding, and positive overall. The bulk of research on
subjective well-being aims to develop an understanding of basic human functioning. Indeed, research on
subjective well-being has greatly informed our understanding of the ways in which social, economic, and
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psychological factors interact to influence well-being. For example, subjective well-being is positively
associated with income, productivity, sociability, and physical health (Lyubomirsky, King, & Diener,
2005).
Although most research on subjective well-being has examined individual-level processes,
researchers are beginning to examine how it plays out at broader geographical units of analysis, such as
nations, states, counties, and cities (Diener, Helliwell, & Kahneman, 2010; Lawless & Lucas, 2011; Lucas,
Cheung, & Lawless, 2014; Oswald & Wu, 2010; Plaut, Markus, & Lachman, 2002; Rentfrow, Mellander, &
Florida, 2009). Interest in the geography of well-being is based, in part, on developing an understanding
how local and national culture, society, politics, and economics might feed into people’s subjective
evaluations of life quality. There is value for psychology and economics researchers to examine such issues
because it can reveal distal causes of subjective well-being, and there is also value for policy makers who
could use such information to guide decisions about policies. To that end, researchers have begun to
examine geographical variation in subjective-well-being by measuring individual differences in subjective
well-being using very large samples of people from around the world. The level of well-being in a place
(i.e., nation, state, county, or city) is typically based on the average subjective well-being score derived
from a sample of people who live in the same place. Thus, to say that the state of Utah is high in well-being
means that the average level of subjective well-being taken from a sample of people who live in Utah is
high compared to the average level of well-being in other states. In this way, researchers are able to make
comparisons of well-being between geographical regions. And the evidence indicates that well-being is not
uniformly distributed, but geographically clustered.
A considerable amount of research on geographical variation in subjective well-being has been done
at the national level (e.g., Inglehart & Klingemann 2000; Lynn & Steel, 2006; Steel & Ones, 2002;
Veenhoven, 1993). Findings from international studies consistently reveal mean differences in subjective
well-being across nations. For instance, results consistently show that residents of Canada, Denmark,
Switzerland and the US score near the top on measures of subjective well-being whereas residents of
Eastern European and African countries score near the bottom (Diener, 2000; Veenhoven, 1993).
National variation is not the only way to examine geographical variation. Within many nations,
including the U.S., there is considerable variation in the social, economic, and political landscape within
the country. Thus, mapping regional variation within nations has value for further understanding the nature
of subjective well-being and the factors that affect it.
Figure 1. Statewide differences in subjective well-being. Source: Rentfrow, P. J., Mellander, C., &
Florida, R. (2009). Happy states of America: A state-level analysis of psychological, economic, and
social well-being. Journal of Research in Personality, 43, 1073-1082.
Using well-being data collected by the Gallup Organization, Rentfrow et al., (2009) investigated
regional variation across states throughout the U.S. The results shown in Figure 1 display the state-wide
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well-being differences reported in that research. The map of state-level well-being clearly shows that wellbeing
is not uniformly distributed across the country, but geographically clustered. Specifically, states in
the mountain and west coast regions scored highest in well-being. In fact, most of the states that ranked in
the top-half on well-being were from the mountain and west coast regions. Well-being was comparatively
lower in states along the east coast, and well-being was lowest in states in the Midwest and deep south.
Figure 2. Map of county-level life satisfaction across the United States. Counties in white have no
data; darker shades of gray reflect higher levels of subjective well-being. Source: Lucas, R. E.,
Cheung, F., & Lawless, N. M. (2014). Investigating the subjective well-being of United States regions.
In P.J. Rentfrow (Ed.) Geographical Psychology: Exploring the interaction of environment and
behavior. American Psychological Association.
Many states in the U.S. are large and diverse. For example, California, is home to approximately 40
million people, with six cities with more than 500,000 residents and 286 towns with fewer than 1,000
residents. Thus, it is useful to consider whether well-being varies at even more granular geographical levels
of analysis. Using data from the Behavioral Risk Factor Surveillance System, administered by the Centers
for Disease Control and Prevention, Lucas et al., (2014) examined regional variation in well-being across
roughly 2,400 counties in the United States. The county-level maps of well-being are displayed in Figure 2.
Although the data source is different to the one used by Rentfrow and colleagues (2009) to map state-wide
well-being, the geographical pattern appears very consistent. Indeed, high levels of well-being appear
clustered in the mountain and west coast regions, and low levels of well-being appear in the Midwest and in
many counties in the south. Furthermore, close inspection of the map shows considerable variation within
states. For example, both Texas and California have counties that score very high and very low in well-
being.
In summary, there is compelling evidence from a number of large-scale studies that subjective wellbeing
varies between nations, states, and counties. These findings are important because they strongly
suggest that features of the environment may contribute to people’s levels of well-being. However,
understanding how the environment may influence well-being first requires consideration of how
geographical variation in well-being emerges in the first place. What are the causes responsible for
geographical differences in well-being?
What are the Mechanisms Responsible for Geographical Variation in Subjective Well-Being?
Recent work in geographical psychology has identified three mechanisms that could contribute to
geographical differences in psychological characteristics. Selective migration is one mechanism. Drawing
on interactionist theories, which posit that people seek out environments that satisfy and reinforce their
psychological needs (Buss, 1987), selective migration assumes that people selectively migrate to places that
satisfy their needs. Research on the links between personality and migration decisions indicates that people
high in Openness are likely to move away from their home state to a different state and that people high in
Extraversion are likely to migrate and that residential mobility has adverse health consequences for people
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low in Extraversion (Jokela, 2009; Jokela, Elovainio, Kivimäki, & Keltikangas-Järvinen, 2008; Oishi,
2010; Oishi, Miao, Koo, Kisling, & Ratliff, 2012; Oishi & Schimmack, 2010; Rentfrow, 2011). In addition,
work by Lucas et al., (2014) indicates that U.S. counties where residents are high in subjective well-being
experience significantly higher levels of population growth compared to areas where well-being is low.
Although the causal nature of the relationship is unclear, it raises important questions about what it is about
places undergoing high in-migration and where residents are high in well-being.
Another mechanism that contributes to geographical variation in psychological characteristics is
social influence. The conceptual basis of the social influence mechanism is essentially an extrapolation
from experimental social psychology research showing that people’s thoughts, feelings, and behaviors are
influenced by those around them. Although most of the evidence for social influence comes from
experimental investigations, there is considerable evidence contagion effects within large social networks
(e.g., Bourgeois & Bowen, 2001; Fowler & Christakis, 2008). For instance, results from the Framingham
Study shows that positive affect spreads through social relationships. More specifically, one’s levels of
happiness can be predicted by the happiness level of friends three times removed (Fowler & Christakis,
2008).
A third mechanism that could give rise to geographical variation in psychological characteristics is
ecological influence. Ecological influence is based on the assumption that aspects of the physical
environment influence behavior. More specifically, there is empirical evidence suggesting that
temperature, rainfall, green space, crowding, and pathogen prevalence can significantly influence many
aspects of human behavior, which over time, can influence the thoughts, feelings, and values of people in
the area. As such, the physical environment can influence the prevalence of particular psychological traits.
One example of ecological influence comes from work by Schaller and colleagues, which suggests that
national levels of Openness and Extraversion are low in parts of the world that have had historically high
levels of infectious disease (Schaller, 2006; Schaller & Duncan, 2007; Schaller & Murray, 2008). The
explanation for the associations is the high risk of spreading disease led people to become more closed off,
skeptical, and exclusive, so that traits associated with these qualities were reinforced. Another example
comes from work by Oishi, Talhelm, and Lee (2015), which suggests that there is a link between
geographical terrain and well-being. Specifically, people high in Extraversion appear to show a strong
preference for oceans whereas people low in the trait show a stronger preference for mountains. Moreover,
people appear more content when in their preferred environments. The explanation for the link is that the
ocean side is more conducive to socializing, which is desirable among extraverts, whereas mountains are
more conducive to reflection, which is more desirable among introverts.
Selective migration, social influence, and ecological influence are three mechanisms hypothesized
to contribute to geographical variation in psychological characteristics. Although there is limited direct
evidence that conclusively shows the impact that each mechanism has on geographical differences, there is
a wealth of indirect evidence, which makes it reasonable to maintain the view that the mechanisms are
important. It also seems highly likely that the mechanisms do not work independently but in combination.
One example of how the mechanisms might work in combination to affect geographical variation in
well-being comes from recent research on the psychological legacy of the Industrialization Revolution.
Industrialization had far-reaching social and economic effects, especially in the old coal regions of Britain,
where entire towns were built to mine the coal that fueled the factories. However, with technological
advances and shifting economic structures, the value of coal plummeted, leaving entire populations
unemployed. Today, the old coal regions continue to have high levels of unemployment and low income
and rank near the bottom on measures of well-being (Obschonka et al., in press).
To understand how the rise and fall of industrialization in coal regions influenced the well-being of
residents in coal regions, Obschonka and colleagues (in press) examined the links between the historical
employment share in large-scale coal-based industries and current levels of well-being. The findings
suggested that the prevalence of coal-based industries was significantly related to high anxiety and
depression, and low well-being. Analyses of the mechanisms responsible for these associations suggested
that a combination of selective migration (with people high in well-being leaving the coal regions) and
social influence (where persistent economic hardship restricted opportunities) played important roles.
Thus far, we know how well-being differs across geographical areas and we have good ideas about
the mechanisms that are responsible for the differences. But how important are geographical differences in
well-being? Are they related to important outcomes? Investigating the links between geographical
differences in well-being and various geographical indictors will not only inform our understanding of the
importance of these differences, it will also help us understand how features of the environment contribute
to well-being.
Are Geographical Differences in Well-being Linked to Important Outcomes?
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To understand if geographical levels of well-being are associated with important outcomes, it is first
useful to consider the processes through which psychological characteristics, such as subjective well-being,
become expressed on geographic social indicators. There are at least two ways through which macro-level
indicators of psychological characteristics and social indicators become linked. One way is through a
“bottom-up” process, in which the psychological characteristics lead to demonstrative behaviors, which are
then represented on conceptually relevant social indicators. This process implies that geographical
differences in social indicators are an additive effect of the psychological characteristics of residents.
Research on the behavioral manifestations of personality provides evidence for a bottom-up perspective
(Bogg & Roberts, 2004; Ozer & Benet-Martínez, 2006; Roberts, Kuncel, Shiner, Caspi, & Goldberg, 2007).
Another way psychological characteristics could become expressed in social indicators is through a “topdown”
process, in which structural and institutional factors influence the prevalence of psychological and
behavioral processes by shaping the experiences, opportunities, and expectations of residents. This process
implies that geographical differences in psychological characteristics are a result of social and institutional
differences. Support for this perspective comes from research in social and cultural psychology showing
that norms influence people’s attitudes and behaviors (e.g., Cohen, 1996; Hofstede, 2001; Triandis & Suh,
2002).
These processes are complementary and intended to provide insight into the ways in which
psychological characteristics become represented on social indicators. To date, research on the
geographical correlates of subjective well-being cannot pinpoint causality, so it is not possible to say that
certain associations are due to bottom-up processes while others are based on top-down processes.
Nonetheless, it is helpful to keep these processes in mind while interpreting the links between geographical
levels of subjective well-being and the social indicators.
National-level correlates of subjective well-being. To develop an understanding of why some
nations consistently score highly in well-being, it is helpful to examine the cultural correlates of well-being.
This approach has illuminated a number of important findings. Specifically, it appears that nations with
high levels of well-being are have more individualistic cultures where citizens place considerable value on
personal independence and autonomy (Diener, Oishi, & Lucas, 2003; Hofstede, 2001). One interpretation
of the association is that individualistic societies, compared to collectivistic societies, afford people more
opportunities to pursue personal interests and to express themselves, so people have a greater range of
opportunities and sense of freedom. There is also evidence that nations with high levels of well-being score
high on measures of human rights and social justice. These findings suggest that in nations where the rights
of all citizens, irrespective of gender, race, ethnicity, or sexual orientation, the population as a whole is
effectively able to enjoy the freedom to pursue a meaningful life.
Several studies have observed positive associations between national levels of subjective well-being
and median income, suggesting that residents of wealthy nations are more satisfied with their lives
compared to people in less affluent nations (Diener et al., 2003; Diener & Suh, 1997; Easterlin, 1995;
Schyns, 1998; Stevenson & Wolfers, 2013). The explanation for this association is that in wealthy nations,
basic needs, like electricity, plumbing, shelter, healthcare, and the like are, are available, so life is much
easier for residents than it is for people who live in nations where such needs are not easily met. Moreover,
there is evidence that the benefits of national wealth to subjective well-being is greater to citizens of lowincome
nations than it is to residents of post-industrial and high-income nations (Mellander, Florida, &
Rentfrow, 2011).
Cross-cultural studies of personality have also added to our understanding of national differences in
well-being. There is evidence that nations high in subjective well-being are also high in Extraversion,
Agreeableness, and Openness, and Emotional Stability (McCrae & Terracciano et al., 2005, Steel & Ones,
2002). These patterns of associations are generally consistent with individual-level research and raising
interesting ideas about the nature of national differences in well-being. One idea is that places where there
are disproportionate numbers of sociable, enthusiastic, friendly, and stable people causes people to feel
accepted, appreciated, and hence satisfied with their lives. Another idea is that cultural characteristics, like
individualism-collectivism, freedom, and social justice, interact with the personality traits with the people
in the culture to affect subjective well-being. At present, we lack the data to understand precisely how
culture, money, and personality interact to affect national variation in well-being.
Regional-level correlates of subjective well-being. Analyses of the correlates of regional
differences in well-being has identified a number of patterns of results that are consistent with nation-level
analyses and also offer more nuanced information. Studies concerned with regional variation across the
U.S. have shown that well-being is linked to a range of economic, occupational, social value, and
personality indicators.
Wealth is important for regional differences in well-being. Both states and counties that score high
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on measures of well-being also score high on various measures of wealth. Specifically, regional levels of
well-being are related to median income, per capita GRP, and house prices (Florida, Mellander, &
Rentfrow, 2013; Lucas et al., 2014; Rentfrow et al., 2009). However, the nature of the association between
well-being and income does not appear to be linear, as money generates diminishing returns for well-being.
That is, as regions become wealthier the benefits to well-being become marginal at best. Given the strong
association between wealth and well-being, it is customary for researchers to control for the effects of
wealth on well-being.
Regional differences in well-being are also related to many occupational indicators. Areas with large
proportions of educated and employed residents show high levels of well-being. There is also evidence that
regions with large shares of highly educated professionals- or what Florida (2002) refers to as the creative
class, also score highly in well-being. These patterns are consistent with the proportion of residents who
have working-class professions (i.e., construction and extraction, installation, maintenance and repair,
production, transportation and material moving occupations). Regions with comparatively large shares of
working class professions score low on well-being.
Just as nations that value freedom and tolerance score high in well-being, so too do states regions.
Indeed, Rentfrow et al. (2009) observed evidence that states with large amounts of social and cultural
diversity also score highly on measures of well-being. However, it is necessary to point out that these
results were not replicated at the county level (Lawless & Lucas, 2011; Lucas, Cheung, & Lawless, 2014).
In fact, it appeared that at the county level, sexual orientation and ethnicity were negatively related to well-
being.
Statewide differences in well-being are also linked to personality. Specifically, states that score high
in subjective well-being also score highly on Neuroticism, which is consistent with research at both the
individual and national levels of analysis (Lyubomirsky et al., 2005; Steel & Ones, 2002).
In their analyses of well-being across counties, Lawless and Lucas (2011) observed associations
between well-being and the prevalence of married couples. Specifically, areas with large proportions of
married couples were significantly higher in well-being, whereas the prevalence of residents who were
separated, divorced, widowed, and single were each associated with significantly low levels of well-being.
This pattern of results is consistent with research at the individual level (Ben-Zur & Michael, 2009; Gove,
Style & Hughes, 1990), and the results lend further support to the argument that social relationships are
very important for subjective well-being (Diener & Seligman, 2002).
It may not come as a surprise, but it is important to report that regional variation in subjective wellbeing
is also related to several physical health indicators (Lawless & Lucas, 2011). Specifically, the level of
well-being in U.S. counties is significantly related to rates of physical health, obesity, and deaths due to
cancer, heart disease, influenza, homicide, and others. These results hold even when the rates are adjusted
for age. Thus, it appears that regions where disproportionate numbers of people are physically unhealthy
are also places where subjective well-being is low.
Person-Environment Interactions and Subjective Well-being
Another aspect of research in this area concerns the impact that regional psychological
characteristics have on the social and psychological processes of individuals. Studies of geographical
variation can help us understand how social and physical aspects of the environment influence and interact
with various psychological processes and affect subjective well-being. One of the ways research in this area
can add to our understanding is by illuminating the choices people make about where to live and whether
those choices influence their well-being. What factors do individuals seek out when choosing places to
live, and do those choices relate to life satisfaction?
Using data from a Gallup Poll of Americans, Florida (2008) examined the factors that influence
people’s decisions about where to live. For some people, social relationships are very important and
provide a strong source of life satisfaction. Such people therefore rank proximity to friends and family
among the most important factors when deciding where to live. Other people derive a great sense of
meaning from their careers and structure their lives around work. For people who place such importance on
their careers, proximity to work ranks higher than living near loved ones. And for other people, a
significant source of pleasure in life comes from spending time in various cultural or natural spaces. For that
reason, some people place outdoor amenities, like access to trails, parks, or beaches highly, or urban
amenities, like museums, clubs, and restaurants highly. The fact that there are individual differences in
place preferences is not surprising, but does living somewhere that satisfies one’s preferences promote
subjective well-being?
To live in a place that offers opportunities to pursue one’s interests seems ideal, and it seems
reasonable to expect that living in such a place would contribute to well-being. For instance, living in a
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suburban area with quiet streets, good schools, and plenty of green space should enhance well-being for
people who value raising a family because such areas provide supportive environments fulfilling that goal.
In contrast, living in a big city with famous museums, galleries, and theaters should enhance well-being for
people who value cultural experiences because such areas are well equipped to provide them. There is
empirical evidence to support such reasoning. Specifically, in a large-scale of 216 London neighborhoods,
Jokela, Bleidorn, Lamb, Gosling, and Rentfrow (2015) examined whether subjective well-being is
associated with living in a neighborhood that has characteristics that complement people’s personalities.
The findings indicated that the degree to which personality and place characteristics complement each
other does influence well-being. Specifically, the findings showed that people high in Openness had high
subjective well-being if they lived in densely populated and culturally diverse parts of London, and that
people high in Agreeableness had high subjective well-being if they lived in neighborhoods with large
numbers of family-occupied homes, large gardens and parks, and low crime rates. These results suggest
that there may not be a single set of environmental factors that enhance well-being (once basic needs are
met), but instead that environmental factors differentially affect well-being depending on certain
personality traits.
Another way to conceptualize person-environment interactions on well-being is to consider the
degree to which people are psychologically similar to the people in their environment. It is abundantly clear
that loneliness and isolation have serious consequences for psychological and mental health, so it is not
surprising that feelings of belongingness are critical for self-esteem and contribute to subjective well-being
(Leary & Baumeister, 2000). Feeling a sense of belonging and connection to others facilitates the
development of a shared reality where people’s thoughts, values, and emotions are validated, which can
contribute to feelings of self-worth (Fulmer et al., 2010). Thus, we can consider the degree to which people
are psychologically similar to their neighbors as measure of person-environment fit, and examine whether
the degree to which people fit with their neighbors is linked to well-being. Bleidorn et al. (2016)
investigated this possibility by studying personality similarity between individuals and the modal
personality of the people living in their city. The results from their analyses small but statistically
significant fit effects on self-esteem. Specifically, the more similar people were to their city’s modal levels
of Openness, Agreeableness, and Conscientiousness, the higher was their self-esteem. Although small
effects, the results nevertheless suggest that people have a greater sense of self-worth when they share with
their neighbors similar levels of curiosity, friendliness, and self-discipline.
Sharing similar values to one’s neighbors is also important for well-being. As the level of political
polarization dividing regions of the U.S. increases, people are sorting themselves into areas where they will
be surrounded by others who share their beliefs. Indeed, regional differences in political ideology are
partially driven by people’s efforts to share spaces with like-minded others. And the evidence indicates that
living with others who have similar ideologies fosters a sense of belonging and group identity (Dixon &
Durrheim, 2003; McPherson, Smith-Lovin, & Cook, 2006). For instance, in an impressive series of studies,
Motyl, Iyer, Oishi, Trawalter, & Nosek (2014) investigated the consequences of ideological fit within a
regional context and found that ideological fit was linked to feelings of belonging, place satisfaction, and
the desire to stay in the area. In contrast, people who did not share political or religious values with their
neighbors were more likely to want to move and to actually move to another location.
In summary, the social and physical characteristics of places are important to subjective well-being.
Whether or not people live in areas that satisfy their needs and have neighbors who share their values and
beliefs is important for subjective well-being. Research in this area offers important insights for
understanding the complex factors that contribute to well-being and they also have implications for
researchers and policy makers concerned with developing programs and initiatives designed to promote
psychological well-being. However, it is important to acknowledge that all the research that has focused on
geographical variation in well-being is based on samples from predominantly WEIRD nations (white,
educated, industrialized, rich, and democratic). The fact is that people in many parts of the world, and in
industrialized nations, lack the opportunities or resources to choose where they live. This fact is a limitation
of the research and its implications.
Conclusion
Where we live matters: So many important events and all the seemingly trivial routines of daily life
occur in the communities, towns, cities, and states in which we live. These are the places where we learn
about who we are and what we believe. And finding the right place to live is among the most important life
decisions that people make. It should therefore come as little surprise that the study of geographical
differences has a lot to contribute to our understanding of subjective well-being. The research carried out
thus far provides several important insights about the nature of well-being and offers valuable clues about
the social and economic factors that might enhance it. Further investigating the scale and impact that
geographical factors have on individual-level subjective well-being has the potential to inform theory and
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research in psychology, as well as government and policy initiatives aimed at promoting healthy living.
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The Psychology of Life Balance
By M. Joseph Sirgy, Virginia Polytechnic Institute & State University & Dong-Jin Lee, Yonsei University
Citation
Sirgy, M. J., & Lee, D.-J. (2018). The psychology of life balance. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
Life balance is a state of equally moderate-to-high levels of satisfaction in important life domains
contributing to overall life satisfaction. Life balance can be effectively achieved through a set of interdomain
strategies. Two sets of inter-domain strategies are identified, namely strategies to prompt greater
participation of satisfied domains to contribute to life satisfaction and strategies to increase domain
satisfaction and decrease dissatisfaction. Inter-domain strategies designed to prompt greater participation of
satisfied life domains to contribute to life satisfaction include: (1) engagement in social roles in multiple life
domains (explained by the principle of satisfaction limits), (2) engagement in roles in health, safety,
economic, social, work, leisure, and cultural domains (explained by the principle of satisfaction of the full
spectrum of human development needs), and (3) engagement in new social roles (explained by the
principle of diminishing satisfaction). Inter-domain strategies designed to increase domain satisfaction and
decrease domain dissatisfaction include (1) integrating domains with high satisfaction (explained by the
principle of positive spillover), (2) optimizing domain satisfaction by changing domain salience (explained
by the value-based compensation principle), (3) compartmentalizing domains with low satisfaction
(explained by the segmentation principle), (4) coping with domain dissatisfaction by engaging in roles in
other domains likely to produce satisfaction (explained by the behavior-based compensation principle), (5)
stress management (explained by the principle of role conflict), and (6) using skills, experiences, and
resources in one role for other roles (explained by the principle of role enrichment).
Key words: Balanced Life, Life Balance, Work-Life Balance, Life Satisfaction, Subjective Well-being,
Quality of Life. Work-Family Conflict, Work-Family Interference
Much research has been documented about concepts related to the balanced life in the literatures of
organizational/industrial psychology and human resource management. These concepts include work-life
balance, work-family balance, work-family interference, and work-family interface (see literature reviews
of various concepts related to work-life balance by Allen, Herst, Bruck, & Sutton, 2000; Bulger & Fisher,
2012; Byron, 2005; Casper, Eby, Bordeaux, Lockwood, & Lambert, 2007; Danna & Griffin, 1999; Eby,
Casper, Lockwood, Bordeaux, & Brinley, 2005; Eby, Maher, & Butts, 2010; Greenhaus & Allen 2011;
Kalliath & Brough, 2008; Kossek & Ozeki, 1998; Lee & Sirgy, 2017; McNall, Nicklia, & Masuda, 2010;
Sirgy & Lee, 2016, 2017; Sirgy, Reilly, Wu, & Efraty, 2008; Yasbek, 2004). In the literature of subjective
well-being, only a few studies were found addressing life balance. For example, Diener, Ng, and Tov
(2008) reported a study involving a representative sample of the world to assess people’s affect balance
(positive versus negative affect) on the previous day and the various activities they have engaged in. The
study found that the most popular activity that most people engaged in is socializing with family and
friends. In this context, the study also found a decreasing marginal utility of this type activity. That is, to
ensure an optimal level of life satisfaction, people attempt to engage in a variety of activities because
satisfaction from one type of activity diminishes in time. Sheldon and Niemiec (2006) demonstrated that
life balance is achieved not only by the fulfilment of psychological needs (needs for autonomy,
competence, and relatedness) but a balanced effect among the satisfaction of these needs . Matuska (2012)
conceptualized life balance as congruence among both desired and actual time spent in activities and
equivalence in the degree of discrepancy between desired and actual time spent across activities that satisfy
basic and growth needs (needs related to health, relationship, challenge/interest, and identity). The author
was able to demonstrate a strong association between life balance and personal well-being. A similar
conceptualization was introduced by Sheldon, Cummins, and Kamble (2010). They defined life balance as
perceived low discrepancy between actual and ideal time-use profiles. The authors developed a life balance
measure based on this conceptualization and were able to demonstrate that life balance is positively related
to subjective well-being mediated by psychological need satisfaction.
The first author of this chapter made an attempt to address the concept of the balanced life in his
2002 book on the Psychology of Quality of Life (Sirgy, 2002). In Chapter 14 of the book, titled “balance,”
Sirgy proposed that people make attempts to create balance in their lives to optimize life satisfaction (i.e.,
achieve and maintain an acceptable level of life satisfaction). He made a distinction between two balance
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concepts: within-domain balance and between-domain balance. Balance within a life domain is achieved by
striving to experience both positive and negative affect. Positive affect reflects a reward function, namely
goals are attained and resources are acquired. In contrast, negative affect serves a motivational function.
That is, negative affect helps the individual recognize problems and opportunities for future achievement
and growth (cf. Kitayama & Markus, 2000). Balance between life domains can be achieved through
compensation (i.e., increasing the salience of positive life domains compensates for negative life domains;
and conversely, decreasing the salience of negative life domains helps reduce the influence of negative
affect from these domains on overall life satisfaction) (also see Sirgy, 2012). The same author with a
doctoral student at the time (Sirgy & Wu, 2009) published an article in the Journal of Happiness Studies
titled “The pleasant life, the engaged life, and the meaningful life: What about the balanced life?” In this
article the authors positioned the concept of the balanced life vis-à-vis other popular concepts of subjective
well-being, namely “the pleasant life,” “the engaged life,” and “the meaningful life” (as proposed by
Martin Seligman in his 2002 book, Authentic Happiness). Seligman has argued that life satisfaction stems
from three major sets of experiences in life, namely experiencing pleasantness regularly (the pleasant life),
experiencing a high level of engagement in satisfying activities (the engaged life), and experiencing a sense
of connectedness to a greater whole (the meaningful life). In response, Sirgy and Wu countered by
suggesting that having a balanced life is equally important to life satisfaction. The balanced life is
experienced when people are highly engaged in social roles in multiple domains. They explained the effect
of balance on life satisfaction using two concepts, namely satisfaction limits (i.e., people can derive only
limited amount of satisfaction from a single life domain; hence engagement in multiple domains is
necessary to optimize life satisfaction) and satisfaction of the full spectrum of human developmental needs
(i.e., people have to be involved in multiple domains to satisfy both basic and growth needs; both sets of
needs have to be met to induce a high level of subjective well-being). This article won the Best Paper in the
journal and was reprinted in Explorations of Happiness (edited by Delle Fave, 2013).
The goal of this chapter is to identify the major principles of life balance, and as such we introduce
to the reader a comprehensive construct of life balance reflective of these principles. We describe how life
balance contributes to subjective well-being (life satisfaction or perceived quality of life).
Life Balance
To follow the subsequent discussion, the reader needs to become familiar with some basic concepts
of subjective well-being, namely life domain, domain satisfaction, and the bottom-up spillover process of
life satisfaction. Let’s first define the concept of “life domain” and “domain satisfaction.” Then we will
tackle the concept of “balance.” Andrews and Withey (1976) and Campbell, Converse, and Rodgers (1976)
were the main proponents of the life domain approach to the study of quality of life and subjective wellbeing.
Andrews and Withey used multiple regression to predict subjects’ life satisfaction scores ("How do
you feel about life as a whole?" with responses captured on a 7-point delighted-terrible scale). They found
that satisfaction with various life domains explained 52-60% of the variance. These domains are
interpersonal relations, self, family, leisure/leisure-time activities, home, friends and associates,
neighborhood, job, education, services/facilities, community, economic situation, local government,
national government, and life in the U.S. today. Campbell, Converse, and Rodgers used a similar set of life
domains, namely leisure/nonworking activities, family, standard of living, work, marriage,
savings/investments, friendships, city/county, housing, education, neighborhood, life in the U.S., health,
religion, national government, and organizations. Many other quality-of-life/well-being researchers have
uncovered other variations of life domains (see literature reviews by Diener, 1984; Diener, Suh, Lucas, &
Smith, 1999; and Sirgy, 2012), and the notion of satisfaction in life domains contributing to a life
satisfaction judgment has come to be known as bottom-up spillover theory of life satisfaction.
Affective experiences are stored in memory in life spheres, and these spheres are organized in a
hierarchy of satisfaction. At the top of the satisfaction hierarchy is life satisfaction—a hot cognition
reflecting how the individual feels about his or her life overall. Second in line in the satisfaction hierarchy is
domain satisfaction. That is, people make judgments about how they feel in certain life domains such as
family life, social life, work life, material life, community life, etc. Satisfaction in these life domains
influences the life satisfaction judgment, which is at the top of the satisfaction hierarchy—the most abstract
hot cognition. At the bottom of the satisfaction hierarchy are concrete hot cognitions related to satisfaction
with life events (i.e., concrete and salient events that have occurred and are associated with positive or
negative affect). As such, satisfaction judgments related to life events (most concrete hot cognitions)
influence satisfaction judgments of life domains, which in turn influence satisfaction with life overall (most
abstract hot cognition). The reader should then note that the central tenet of bottom-up spillover theory of
life satisfaction is the carryover of affect from subordinate life domains to superordinate ones, specifically
from life domains such as leisure, family, job, and health to overall life. Thus, bottom-up spillover implies
that subjective well-being (or life satisfaction) can be increased by allowing life domains carrying positive
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feelings or satisfaction to spill over unto the most superordinate domain (overall life). The positive affect
accumulates in life domains as a direct function of satisfaction of human development needs—
physiological needs, safety needs, social needs, esteem needs, self-actualization needs, knowledge needs,
and aesthetics needs (Maslow, 1970).
Having explained the concepts of life domains and domain satisfaction, the reader is now ready to
appreciate the discussion concerning how people manipulate the interplay life domains and domain
satisfaction to increase life balance, which in turn contributes to life satisfaction. That is, to achieve life
balance people engage in behavioral strategies to increase life satisfaction by manipulating the interplay
among domain satisfaction to prompt greater participation of satisfied life domains to contribute to life
satisfaction and increase domain satisfaction and decrease domain dissatisfaction. Inter-domain strategies
designed to prompt greater participation of satisfied life domains to contribute to life satisfaction include:
(1) engagement in social roles in multiple life domains (explained by the principle of satisfaction limits),
(2) engagement in roles in health, safety, economic, social, work, leisure, and cultural domains (explained
by the principle of satisfaction of the full spectrum of human development needs), and (3) engagement in
new social roles (explained by the principle of diminishing satisfaction). Inter-domain strategies designed to
increase domain satisfaction and decrease domain dissatisfaction include (1) integrating domains with high
satisfaction (explained by the principle of positive spillover), (2) optimizing domain satisfaction by
changing domain salience (explained by the value-based compensation principle), (3) using skills,
experiences, and resources in one role for other roles (explained by the principle of role enrichment), (4)
compartmentalizing domains with low satisfaction (explained by the segmentation principle), (5) coping
with domain dissatisfaction by engaging in roles in other domains likely to produce satisfaction (explained
by the behavior-based compensation principle), and (6) minimizing role conflict (explained by the principle
of role strain and stress).
We will begin by discussing those principles related to prompting greater participation of satisfied
life domains to contribute to life satisfaction. See Figure 1.
Inter-domain Strategies Designed to Prompt Greater Participation of Satisfied Life Domains to
Contribute to Life Satisfaction
As previously mentioned, we will discuss three behavioral strategies people use to achieve life
balance by prompting greater participation of satisfied life domains to contribute to life satisfaction. These
are (1) engagement in social roles in multiple life domains (explained by the principle of satisfaction
limits), (2) engagement in roles in health, safety, economic, social, work, leisure, and cultural domains
(explained by the principle of satisfaction of the full spectrum of human development needs), and (3)
engagement in new social roles (explained by the principle of diminishing satisfaction).
Engagement in social roles in multiple life domains and the principle of satisfaction limits.
Much research has shown that engagement in social roles in work life and nonwork life (family, leisure,
social, community, etc.) serves to produce a positive, fulfilling, state of mind characterized as vigor,
dedication, and absorption (Schaufeli, Salanova, Gonzalez-Roma, & Bakker, 2002). Vigor reflects a high
level of energy and mental resilience in role engagement in multiple domains. Dedication refers to being
strongly involved in one’s roles at both work and nonwork by experiencing a sense of significance,
enthusiasm, and challenge. Absorption is characterized by being fully concentrated and happily engrossed
in the task at hand associated with the various roles across life domains (Schaufeli & Bakker, 2004).
Figure 1. Behavioral Strategies of Life Balance
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Individuals are likely to achieve a high level of satisfaction in life overall when they are fully
engaged in multiple roles in work and nonwork life. Further, they are likely to maximize their life
satisfaction if and when they become fully engaged in multiple roles. Doing so is essentially one way to
increase harmony among life domains. Increasing satisfaction in multiple domains ultimately serves to
increase life satisfaction at large. The effect of role engagement in social roles in multiple domains on life
satisfaction can be explained through the principle of satisfaction limits, which we now turn to.
The bottom-up spillover model of life satisfaction proposes that life satisfaction is determined by
cumulative satisfaction experienced in important life domains such as satisfaction in work life, family life,
social life, leisure life, spiritual life., community life, etc. (e.g., Andrews & Withey, 1976; Campbell,
Converse, & Rodgers, 1976). Mathematically speaking, the model states that a life satisfaction score of an
individual can be predicted by adding all the satisfaction scores of salient life domains. For example, if one
uses an 11-point satisfaction scale (-5=high dissatisfaction to +5=high satisfaction), then an individual (A)
registering satisfaction in work life (e.g., “+3”), family life (e.g., “+3”), leisure life (e.g., “+3”), social life
(e.g., “+3”), and material life (e.g., “+3”) should have a higher life satisfaction score than another
individual (B) who registers satisfaction in work life (e.g., “+5”), family life (e.g., “0”), leisure life (e.g.,
“0”), social life (e.g., “0”), and material life (e.g., “0”). This is due to the fact that the former individual has
a total domain satisfaction score of “15” [(+3) + (+3) + (+3) + (+3) + (+3)], whereas the latter has a total
domain satisfaction score of “+5” [(+5) + (0) + (0) + (0) + (0)]. Of course, this predictive equation assumes
that work life, family life, leisure life, social life, and material life are all equally salient to both individuals.
In other words, overall life satisfaction is accrued additively from satisfaction in multiple life domains.
Research has demonstrated that satisfaction from a variety of life domains contributes to unique variance in
life satisfaction, and that there is some validity to this compensatory model of life satisfaction (e.g., Hsieh,
2003; Rojas, 2006; also see reviews by Diener, 1984; Diener et al., 1999).
The principle of satisfaction limits (Sirgy & Wu, 2009) posits that the amount of contribution of
domain satisfaction from a single life domain to overall life satisfaction is limited. In the example of the
compensatory model described above the limit is +5 satisfaction units in each domain (scale = +5 to -5). In
other words, one can achieve only a limited amount of satisfaction from a single life domain (a maximum
of 5 satisfaction units). Using the example above, Person A is satisfied in work life (“+3”), leisure life
(“+3”), social life (“+3”), material life (“+3”), and family life (“+3”). His life satisfaction (15 units) is based
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on a moderate degree of satisfaction in five salient life domains. Person B is satisfied with work life (+5)
only. He is not satisfied in family life (“0”), leisure life (“0”), social life (“0”), as well as material life (“0”).
His life satisfaction score (“5” units) is based on satisfaction from 1 out of 5 salient domains. In sum, an
individual who is highly satisfied in multiple domains is likely to experience a higher life satisfaction
compared to an individual who is highly satisfied in a single domain. As such, role engagement in multiple
life domains produces an additive effect on life satisfaction (e.g., Andrews & Withey, 1976; Campbell,
Converse, & Rodgers, 1976: Eakman, 2016; Hsieh, 2003; Rojas, 2006; Sirgy & Lee, 2016; Sirgy & Wu,
2009). That is, high role engagement in a single life domain with little or no role engagement in other life
domains cannot contribute much to life satisfaction compared to high role engagement in multiple domains.
Consider the following study: Bhargava (1995) asked study participants to discuss life satisfaction
of others. Most participants inferred life satisfaction of others as a direct function of their satisfaction in
multiple domains. They calculated happiness by summing satisfaction across several important domains—
the more positive affect in multiple domains, the higher the subjective well-being. In a work context,
individuals engaging in various social roles in nonwork life domains, in addition to roles in work life, are
likely to experience a high level of life satisfaction compared to those who are highly engaged only in work
life (e.g., Greenhaus & Powell, 2006; Rice, McFarlin, Hunt, & Near, 1985).
In sum, this discussion can be captured as follows: Individuals who have a high level of role
engagement in multiple life domains are likely to increase life balance and experience higher life
satisfaction than those who have a high level of role engagement in a single domain. This effect may be
due to satisfaction limits. Specifically, compared to individuals who are engaged in a single domain,
individuals who are highly engaged in multiple life domains are likely to experience more satisfaction in
those domains, contributing to life satisfaction. Those who are engaged in a single domain can produce
only a limited amount of domain satisfaction (less that those who are engaged in multiple domains) that
spills over to life satisfaction. That is, compared to role engagement in multiple domains, role engagement
in a single domain is likely to be wholly insufficient to contribute significantly to life satisfaction.
Engagement in roles in health, love, family, material, social, work, leisure, and culture
domains; and the principle of satisfaction of the full spectrum of human developmental needs. People
try to optimize their life satisfaction (enhance their life satisfaction to an acceptable level) by actively
engaging in social roles in multiple domains. The question that arises based on the preceding argument is
“which domains?” Life satisfaction is significantly increased when the individual engages in roles in life
domains that can satisfy the full spectrum of human development needs (Maslow, 1970). As such, we
believe that life balance can be achieved through active engagement in social roles in multiple domains
serving to satisfy both basic and growth needs: health, love, family, and material domains serving to satisfy
mostly basic needs and social, work, leisure, and culture domains serving to satisfy growth needs. Let us be
more specific.
Sirgy and Wu (2009) have argued that subjective well-being is not simply cumulative positive
minus negative affect—irrespective of the source. It is the satisfaction of human developmental needs, the
full range of needs—not a handful of selected needs. In other words, one cannot substitute positive affect
related to one need with another need. To illustrate this point, let us consider the following example. Two
individuals, A and B. Person A has “+3” satisfaction units in each of the following domains related to basic
needs: health life, love life, family life, and material life. In other words, Person A is satisfied in domains
related to his basic needs, a total score of “+8” satisfaction units [(+2) + (+2) + (+2) + (+2)] and the same
person is similarly satisfied in life domains related to growth needs (social life, work life, leisure life, and
culture life), a total of “+8” [(+2) + (+2) + (+2) + (+2)]. Summing up Person A’s domain satisfaction
scores, we obtain a total amount of “16” units of domain satisfaction (+8 satisfaction units from domains
related to basic needs, and another +8 satisfaction units from domains related to growth needs). Now let us
compare this case with Person B who is highly satisfied with basic needs only. Person B is highly satisfied
in domains related to his basic needs, a total score of “+20” satisfaction units [(+5) + (+5) + (+5) + (+5)]
while is dissatisfied in domains related to his growth needs, a total of “-8” satisfaction units [(-2) + (-2) + (-
2) + (-2)]. As such, the total domain satisfaction score for person B is also “+12”. We predict that person A
is likely to report a higher degree of life satisfaction than person B because person A has balanced
satisfaction from life domains related to both basic and growth needs, whereas Person B has unbalanced
domain satisfaction (high satisfaction in domains related to basic needs but low satisfaction in domains
related to growth needs).
Let us delve deeper to understand the psychology underling this effect. We will do so by
discussing the principle of satisfaction of the full spectrum of human developmental needs . This principle
posits that individuals who are satisfied with the full spectrum of developmental needs (i.e., satisfaction of
growth needs as well as basic needs) are likely to have a high level of life satisfaction relative to those who
are less satisfied (e.g., Alderfer, 1972; Herzberg, 1966; Maslow, 1970; Matuska, 2012; Sheldon, Cummins,
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& Kamble, 2010; Sheldon & Niemiec, 2006). When people engage in multiple roles across life domains,
they are likely to obtain access to psychological and physical resources, which in turn increase
opportunities for satisfaction of many basic and growth needs. Seeking to satisfy a specific need in a single
life domain does not positively contribute much to life satisfaction (Sirgy et al., 1995). That is, when
people engage in multiple roles, they are likely to experience satisfaction of growth needs (i.e., social,
knowledge, aesthetics, self-actualization, and self-transcendence needs) as well as satisfaction of basic
needs (i.e., health, safety, and economic needs). Satisfaction of growth needs contributes to positive affect,
whereas satisfaction of basic needs contributes only to the reduction of negative affect (Herzberg, 1966).
Satisfaction of both sets of basic and growth needs contributes significantly and positively to life
satisfaction.
Specifically, Sirgy and Wu (2009) have described how people organize their lives to fulfil their
developmental needs. To satisfy their biological and health-related needs, people engage in a variety of
activities such as eating right, exercising regularly, getting regular check-ups, engaging in regular sex, and
so on. The events related to those activities and their outcomes generate a certain amount of satisfaction
and dissatisfaction. These affective reactions are organized and stored in memory in certain life domains
such as health, love, family, and economic. When a man is asked how he feels about his health life, he is
likely to reflect on his affective experiences in relation to health-related activities such as eating right,
exercising regularly, having regular check-ups, and so on. When the same person is asked about his love
life, he reflects about his affective experiences related to love, romantic relationships, and sex. When asked
about his family life, he reflects on those experiences related to the use of his significant others such as
spouse and children, his residence, his neighborhood, and community. Financial issues and experiences
related to money, income, standard of living, and material possessions also likely to be segmented in
material life and mostly related to basic needs. With respect to growth needs (e.g., social, esteem, selfactualization,
self-transcendence, aesthetics, and knowledge needs), experiences may be segmented in life
domains such as social life, work life, leisure life, and culture life. However, this is not to say that a variety
of developmental needs can be met in a single domain. Consider the work domain for example. Many
developmental needs, both basic and growth needs, can be met through work life. Through work life, both
basic (i.e., economic, health and safety, and family-related needs) and growth needs (i.e., social, esteem,
self-actualization, self-transcendence, knowledge, and aesthetics needs) can be met. To reiterate, in every
life domain a variety of developmental needs can be met. However, certain life domains are predisposed to
meet certain developmental needs more so than others. As such, we argue that health, love, family, and
economic domains are likely to reflect satisfaction resulting more from meeting basic than growth needs.
Conversely, social life, work life, leisure life, and culture life are domains likely to reflect satisfaction
resulting more from meeting growth than basic needs.
Suggestive evidence of this principle comes from a body of evidence showing that materialism is
negatively correlated with life satisfaction (see Wright and Larsen, 1993, for a meta-analysis of the
research findings). Specifically, materialistic people can be viewed as imbalanced in that they pursue
wealth and material possessions to the exclusion of other important goals in life. Materialistic people who
are successful hoarding material wealth may feel successful and happy with their material life. Placing
undue emphasis on making money (to satisfy basic needs such as biological and safety needs) is likely to
lead them to neglect other growth needs such as social, esteem, self-actualization, self-transcendence,
aesthetics, and knowledge needs. It is no wonder that the evidence shows that materialism is negatively
correlated with life satisfaction.
Furthermore, as previously discussed, Matuska (2012) conceptualized life balance as congruence
among both desired and actual time spent in activities and equivalence in the degree of discrepancy between
desired and actual time spent across activities that satisfy basic and growth needs (needs related to health,
relationship, challenge/interest, and identity). The author conducted a study that successfully demonstrated
a strong association between life balance and personal well-being.
In sum, the preceding discussion can be captured as follows: Individuals who have a high level of
role engagement in life domains related to both basic needs (e.g., health, love, family, and material
domains) and growth needs (e.g., social, work, leisure, and culture domains) are likely to experience
greater satisfaction among life domains contributing to higher life satisfaction than those who have a high
level of role engagement in domains related to only basic or growth needs. This effect may be due to the
effect of satisfaction of the full spectrum of human developmental needs. Specifically, compared to
individuals who are engaged in roles in select domains, individuals who have a high level of role
engagement in multiple domains addressing both basic and growth needs are likely to experience more life
satisfaction. Role engagement in health, love, family, and material domains are likely to satisfy mostly
basic needs (survival needs such as having enough resources to deal with health and safety issues), whereas
role engagement in social, work, leisure, and culture are likely to satisfy mostly growth needs (higher-order
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needs such as social, esteem, self-actualization, aesthetics, and knowledge needs). The combined and
balanced effects of satisfaction of both basic and growth needs serve to increase life satisfaction. That is,
satisfaction of the full spectrum of human developmental needs (balance between basic and growth need
satisfaction) produces the highest level of life satisfaction.
Engagement in new social roles and the principle of diminishing satisfaction. Much research in
variety seeking supports the notion that successful engagement in new roles is likely to produce more
positive affect than successful engagement in well-established roles (e.g., Kahn, 1995; Kahn & Isen, 1993;
Levav & Zhu, 2009; McAlister & Pessmier, 1982). That is, engaging and succeeding in new roles tend to
produce a jolt of positive affect much more so than engaging and succeeding in well-established roles.
Also, much research in industrial/organizational (I/O) psychology has demonstrated the effect of task
variety on job performance and employee well-being (e.g., Christian, Garza, & Slaughter, 2011; Pierce &
Dunham, 1976). That is, compared to workers who are engaged in repetitive tasks, workers engaging in a
variety of tasks tend to feel much more motivated to excel on their jobs, tend to do much better in relation
to job performance, and experience higher levels of job satisfaction. One can extrapolate from this research
that life balance is not only limited to engagement in social roles in multiple domains satisfying both basic
and growth-related needs but also new social roles. This may best be explained using the principle of
diminishing satisfaction.
This principle states that individuals with life balance are likely to continuously engage in new
roles to guard against diminishing satisfaction associated with well-established roles. Why? The intensity
of the positive affect in the context of a social role experienced in a given life domain tends to decay with
adaptation effects (Helson, 1964). Consider the following scenarios. Person A (woman) is right out of
college and starts a new job. She experiences success in her assigned roles. This success is likely to bring
much positive affect and satisfaction in work life—+4 units of satisfaction in the work domain—on a 11point
satisfaction scale varying from -5 (very dissatisfied) to +5 (very satisfied). Compare Person A
(woman) to Person B (man) who is a seasoned worker—has been on the job for a long time. He is equally
successful in his assigned work roles (perhaps a +2 units of satisfaction). That is, the man is not likely to
experience the same magnitude of satisfaction compared to the woman. This dampening of positive affect
and satisfaction for the man is due to an adaptation effect. That is, positive affect is dampened with
repeated successful performance. To guard against this dampening effect and to restore satisfaction in the
work life domain, the man has to engage in new roles to maintain the same level of domain satisfaction that
was once generated through old and well-established role performance. However, to increase positive
affect in the work domain (say from +2 units of satisfaction to +4 units of satisfaction), he needs to engage
in new work-related roles successfully.
Research has documented this phenomenon. Specifically, given successful role performance in a
particular life domain (e.g., work life) individuals who have not been feeling satisfied in that domain are
likely to experience a greater magnitude of domain satisfaction than individuals who are already satisfied in
the same domain (e.g., Ahuvia & Friedman, 1998; Diener, Ng, & Tov, 2008; Rojas, 2006). Put succinctly,
increases in satisfaction in a life domain serve to increase life satisfaction but at a decreasing marginal rate
with repeated experiences.
In sum, we can capture the preceding discussion as follows: Individuals become engaged in new
social roles to mitigate decreases in domain satisfaction and life satisfaction overall. This effect is due to
the diminishing satisfaction effect. Specifically, individuals who are engaged in social roles experience
diminishing satisfaction in a given life domain over time, which in turn detracts from life satisfaction
overall. To guard against this diminishing domain satisfaction, they engage in new social roles to generate
new satisfaction thereby compensating for the diminished satisfaction related to the old roles.
Inter-domain Strategies Designed to Increase Domain Satisfaction and Decrease Domain
Dissatisfaction
In this section we will discuss six behavioral strategies people use to achieve life balance by
increasing domain satisfaction and decreasing domain dissatisfaction. These are: (1) integrating domains
with high satisfaction (explained by the principle of positive spillover), (2) optimizing domain satisfaction
by changing domain salience (explained by the value-based compensation principle), (3)
compartmentalizing domains with low satisfaction (explained by the segmentation principle), (4) coping
with domain dissatisfaction by engaging in roles in other domains likely to produce satisfaction (explained
by the behavior-based compensation principle), (5) stress management (explained by the principle of role
conflict), and (6) using skills, experiences, and resources in one role for other roles (explained by the
principle of role enrichment).
Integrating domains with high satisfaction and the principle of positive spillover. Life balance
can also be achieved by integrating life domains that house high levels of positive affect or satisfaction.
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Doing so contributes to life satisfaction overall. Consider the owner of a mom and pop store whose family
residence is situated on the top floor of the store. His wife and children help at the store by staffing the
checkout stand, maintaining inventory, dealing with suppliers and customers, etc. In this situation, the store
owner’s work life is highly integrated with his family life, marital life, social life, material life, and perhaps
community life too. The store is highly successful in that it has a good stream of patrons, a good reputation
in the neighborhood, and it generates a decent income that supports his family and a few other jobs in the
community. Success in these varied roles translates into positive affect in work life, family life, marital life,
social life, material life, and community life. Thus, life satisfaction is increased by integrating both work
and family life, which serves to increase satisfaction in both domains. This phenomenon is essentially
known as “positive spillover.”
Let us further delve in this discussion of positive spillover. Experiences in work and nonwork life
may spill over. That is, affect may spill over from work life to nonwork life and vice versa. This is what I/O
psychologists commonly refer to as “affect spillover” (e.g., Edwards & Rothbard, 2000; Grzywacz &
Carlson, 2007). Affect spillover can be either positive or negative. Positive affect spillover refers to
positive mood that transfer from one life domain to another. Conversely, negative spillover refers to
negative mood spilling over from one domain to another. Affect spillover should be distinguished from
crossover effects. Affect spillover refers to feelings caused by experiences in one life domain influencing
another life domain. It is an intra-individual phenomenon (i.e., within an individual). In contrast, crossover
effect is an inter-individual construct. It refers to emotional contagion between individuals whereby
individuals are influenced by the emotions displayed by those around them (e.g., Demerouti, Bakker, &
Schaufeli, 2005; Hatfield, Cacioppo, & Rapson, 1994). Crossover effects are likely to be high when
individuals are in physical proximity and in close communications (Barsade, 2002; Neumann & Strack,
2000).
Consider the following case involving two individuals, Person A and Person B. Both individuals
experience “+1” units of satisfaction in work life and “+3” units of satisfaction in family life. However,
Person B decides to integrate work and family domains (e.g., by doing work at home and taking care of
family responsibilities at work). Person B was highly successful in integrating work and family domains.
Doing so increased his satisfaction in work life from “+1” to “+3,” whereas his satisfaction in family life
remained at “+3.” Person B achieved work life balance through positive spillover. In contrast, Person A did
not bother to integrate the two domains; hence, he remained experiencing “+1” satisfaction in work life and
“+3” in family life. In this case, positive spillover through domain integration resulted in greater
satisfaction in family life for Person B, and as a result higher subjective well-being.
Individuals are likely to experience spillover of positive affect from one life domain to another
when the life domains are interdependent and the roles are integrated (e.g., Greenhaus & Powell, 2006;
Ilies, Wilson, & Wagner, 2009). In regard to the direction of spillover of positive affect, individuals are
likely to experience spillover of positive affect from a life domain with a strong involvement to another life
domain with weak involvement (Frone, Russell, & Cooper, 1992). For instance, for those who are highly
involved with work, affect spillover from work-to-family seems to be stronger than family-to-work
spillover.
The principle of positive spillover posits that positive affect in two life domains that are highly
integrated amplify domain satisfaction, which in turn spills over to overall life satisfaction. That is, positive
affect that spills over between life domains increases the level of satisfaction in those domains. For
example, sharing of positive work experiences increases family satisfaction because sharing of positive
events facilitates positive mood among family members and family satisfaction (e.g., Gable, Gonzaga, &
Strachman, 2006; Heller & Watson, 2005). Furthermore, positive affect in one role can boost the level of
motivation and energy to engage in another role in a neighboring domain. Thus, positive affect in one
domain may increase the likelihood of successful performance in a different domain, resulting in increased
satisfaction in that domain, which in turn increases life satisfaction overall (Edwards & Rothbard, 2000). In
other words, increased satisfaction in the respective domains contribute additively to life satisfaction.
In sum, the preceding discussion can be captured as follows: Individuals who experience positive
spillover between two or more life domains through domain integration are likely to experience greater
satisfaction in those domains, compared to those who do not experience positive spillover. Such increases
in domain satisfaction contribute to increases in life satisfaction overall.
Optimizing domain satisfaction by changing domain salience and the principle of value-based
compensation. Consider the following scenario: Person A is satisfied with family life (+3 unit of
satisfaction units on a 11-point scale varying from +5 to -5) but not satisfied with work life (-3 satisfaction
units). Person A also believes that both family life and work life are equally important (0.8 importance
points to each domain on a 1.0-point importance scale varying from “0” as “not important at all” to “1.0”
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as “extremely important”). Hence, family satisfaction is “+2.4” [(+3) x (0.8)] and work satisfaction is “-
2.4” [(-3) x (0.8)]. Person B is also in the same boat—feels happy with family life but unhappy with work
life. Person B also believes that both domains are equally important. Note that in both cases, there is
marked satisfaction in family life (“+2.4”) and dissatisfaction in work life (“-2.4”). How do people
manipulate the interplay between/among the domains to enhance life satisfaction overall?
Person A makes a cognitive change by increasing the salience of family life—increasing
importance weight from “0.8” to “1.0,” resulting in “+3.0” satisfaction points [(+3) x (1.0)] in the family life
and decreasing the salience of work life—decreasing the salience weight from “0.8” to “0.1” resulting in “-
0.3” satisfaction units [(-3) x (0.1)] in work life. That is, satisfaction in family life increases—from “+2.4”
to “+3.0” [(+3) x (1.0)] and dissatisfaction in work life decreases from “-3.2” to “-0.3” [(-3) x (0.1)]. Person
B remains the same. Thus, Person A was able to increase satisfaction in family life and decrease
dissatisfaction in work life. Doing so serves to increase life satisfaction overall. Person B remains the same.
This prediction is in line with the research showing a significant correlation between domain
satisfaction and domain importance (Hsieh, 2003). That is, domains in which people express high levels of
satisfaction are likely to be treated as more salient than domains with low satisfaction (or dissatisfaction).
Consider the following study. Scott and Stumpf (1984) collected data on subjective well-being, domain
satisfaction, and domain importance using a population of immigrants to Australia. The data clearly
revealed a pattern of correlations in which most domain satisfaction scores were significantly correlated
with their corresponding domain importance scores—friendship, material possessions, family recreation,
and nation. Also consider research in social psychology showing that people report things they are not
proficient at to be less important than the things that they are proficient at (e.g., Campbell, 1986;
Harackiewicz, Sansone, & Manderlink, 1985; Lewicki, 1984; Rosenberg, 1979). These findings also are in
line with the positive correlation between domain satisfaction and domain importance.
The principle of value compensation provides an explanation for the association between domain
satisfaction and domain salience. People jack up the salience of domains they feel satisfied in and decrease
the salience of domains they feel dissatisfied in. Why? They do so to increase life satisfaction or at least
prevent life satisfaction from falling below an acceptable level (Sirgy, 2002). Wu (2009) attempted to
capture the value-based compensation effect by developing an index that reflects the correlation between
have-want discrepancy scores from 12 different life domains and perceived importance scores of these
domains—a correlation coefficient at the individual level. Individuals who engage in compensation are
those who perceive life domains with high satisfaction to be more important than others. Wu calls this
compensation phenomenon the “shifting tendency.” Correlations between the shifting tendency and life
satisfaction (as well as domain satisfaction scores) were positive suggesting that the shifting tendency may
be a strategy that enhances subjective well-being.
In sum, the preceding discussion can be captured as follows: Individuals increase domain
satisfaction by increasing salience of satisfied domains; and conversely, they decrease domain
dissatisfaction by decreasing salience of dissatisfied domains. Life satisfaction is increased by doing so.
Compartmentalizing domains with high dissatisfaction and the segmentation principle.
Consider the following scenario comparing two individuals (persons A and B) who are experiencing
dissatisfaction at work: -3 units of dissatisfaction on a 11-point scale varying from -5 (very dissatisfied) to
+5 (very satisfied). However, both individuals are satisfied with their family life (+3 units of satisfaction).
Both individuals are experiencing negative spillover of affect from work life to family life. That is, their
dissatisfaction at work (-3 units of satisfaction) is influencing their mood at home causing friction and
stress in family life. Person A decides to deal with the high dissatisfaction at work by compartmentalizing
his work life to prevent future negative spillover of negative affect from work life to family life. That is, he
decides that at home he will not think about work issues, speak of work issues, and do anything related to
work. Doing so, Person A manages to maintain his satisfaction in family life to the previous level (+3).
Person B does not segment and thus remains to experience decreased satisfaction in the family life as a
result of the negative spillover.
Negative affect in one life domain is likely to spill over to other life domains when there is a high
level of overlap across life domains in terms of time, space, effort, and resources. In order to prevent
spillover of negative affect to other life domains, individuals create and maintain psychological, physical,
or behavioral boundaries around their life domains (Ashforth, Kreiner, & Fugate, 2000; Edwards &
Rothbard, 2000; Judge et al., 2001; Sonnentag 2012). For example, workers can segment family life
domain from work life domain. At home, they do not converse about work experiences. Work-life issues
stay at work, and home-life issues stay at home.
Research by Lucas, Diener, and Suh (1996) has demonstrated that the global category of happiness
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is composed of separable well-being variables (e.g., work satisfaction, home satisfaction, and life
satisfaction). These variables sometime move in different directions over time (cf. Scollon & Diener, 2006).
This finding point to the possibility that some people at times are able to prevent spillover of negative
affect between life domains. Recent research found that increased use of mobile technologies blur the
boundaries between work and family, making segmentation difficult (Chesley, 2005; Park, Fritz, & Jex,
2011).
Let us now delve more into the psychological dynamics concerning the effect of segmentation on
life satisfaction in greater detail. Wilensky (1960), I/O psychologist, was the first to describe how people
use segmentation to enhance their subjective well-being. He argued that when people feel dissatisfied in
one life domain and they realize they have little control in changing that outcome, they make an attempt to
“seal off” the domain housing the dissatisfaction. They do so to maintain a certain level of overall life
satisfaction (i.e., to ensure that overall life satisfaction does not drop below an intolerable level). He
described how affect from one domain “spills over” unto other domains. He described how people
“segment” their affect in certain domains preventing affect from spilling over.
As such, the segmentation principle posits that individuals who segment life domains can prevent
spillover of negative affect across life domains. Segmentation of dissatisfying life domains from other life
domains contribute to overall life satisfaction because segmentation of dissatisfying life domain from other
life domains protects satisfaction in other life domains. Segmentation of a life domain with negative
experiences is important because it serves as a coping mechanism and a buffer for subjective well-being.
Much research in work-life balance has documented the segmentation effect (e.g., Edwards & Rothbard,
2000; Michel & Hargis, 2008; Sonnentag et al., 2008).
Based on the discussion, we can summarize the concept of segmentation as a behavioral lifebalance
strategy. Compared to individuals who do not compartmentalize their dissatisfied domains from
spilling over to other domains, those who manage to compartmentalize reduce the likelihood of decreases in
life satisfaction overall. That is, compartmentalizing negative affect in one domain serves to protect
neighboring domains from negative spillover, thus preventing the neighboring domains from slipping into
dissatisfaction, and doing so prevents declines in life satisfaction.
Coping with domain dissatisfaction by engaging in roles in other domains and the principle of
behavior-based compensation. Consider the following scenario. Person A is becoming increasingly
unhappy with family life—satisfaction in family life drops from +3 units to -2 units. This drop of
satisfaction in family life is likely to adversely influence his life satisfaction overall. Person B is similarly
unhappy with family life—satisfaction drops from +3 units to -2 units in the last few months. Person A
becomes more engaged at work by taking on more responsibility, socializing with his co-workers, and
getting more recognition from his boss. That is, his satisfaction in work life jumps from a mere +1 units of
satisfaction to +4, a whopping increase of +3 units. This increase of satisfaction in work life serves to offset
the decrease of satisfaction in family life. Person B does not do anything about his family situation (-2) and
his satisfaction at work is rated +1. Ultimately, Person A’s life satisfaction is maintained, while Person B’s
life satisfaction drops significantly.
Many seminal studies in I/O psychology have documented the fact that involvement at work is
negatively correlated with involvement in nonwork (e.g., Cotgrove, 1965; Clark, Nye, & Gecas, 1978;
Fogarty, Rapoport, & Rapoport, 1971; Goldstein & Eichhorn, 1961; Haavio-Mannila, 1971; Haller &
Rosenmayr, 1971; Rapoport, Rapoport, & Thiessen, 1974; Shea, Spitz, & Zeller, 1970; Walker & Woods,
1976). Other evidence suggests that individuals dissatisfied at work tend to increase their engagement in
nonwork roles (e.g., Furnham, 1991; Shepard, 1974; Staines, 1980). For example, individuals in low-status
jobs feel dissatisfied with their jobs. To compensate for this dissatisfaction, they become more involved in
leisure activities (Miller & Weiss, 1982). Specifically, they stress the importance of prize winning in leisure
activities related to organized league bowling.
Also consider the research on materialism. There is much evidence to suggest that materialism
(strength of financial aspirations) is negatively related to subjective well-being (see literature review by
Richins & Rudmin, 1994; Roberts & Clement, 2007). That is, those who score highly on measures of
materialism report lower levels of subjective well-being, and vice versa (e.g., Ahuvia & Wong, 2002;
Kasser & Ryan, 1993; Richins & Dawson, 1992; Sirgy, 1998). One explanation provided by Diener and
Biswas-Diener (2009) is the notion of shopping therapy. Those who do not have close friends and other
social resources tend to compensate by shopping. In other words, shopping becomes therapeutic.
According to the principle of behavior-based compensation , individuals experiencing
dissatisfaction in one life domain are more likely to compensate by engaging in satisfying roles in other life
domains. For example, individuals feeling dissatisfied with their jobs invest themselves in more satisfying
nonwork activities such as leisure, family, or religion (e.g., Brief et al., 1993; Freund & Baltes, 2002;
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Judge, Thoresen, Bono, & Patton, 2001; Tait, Padgett, & Baldwin, 1989).
Best, Cummins, and Lo (2000) conducted a study on the quality of rural and metropolitan life and
found that both groups report equivalent levels of life satisfaction. However, metropolitan residents
reported more satisfaction with family and close friends, while farmers reported more satisfaction with the
community and productivity. The authors explained this finding by suggesting that life satisfaction is
maintained through behavior-based compensation. That is, decreases in satisfaction in one domain are
compensated by increases in satisfaction in another through role engagement. Specifically, behavior-based
compensation occurs when an individual repeatedly experiences dissatisfaction in a life domain allocates
much time, energy, and other resources in another life domain to make up for the satisfaction deficiency.
In sum, we can capture the preceding discussion as follows: Individuals who feel dissatisfied in a
life domain and engage in successful role performance in another life domain are likely to experience
higher levels of life satisfaction than those fail to feel equally dissatisfied but do not engage in other life
domains. Engaging in successful role performance in the other life domain serves to increase satisfaction in
that domain to compensate for the decrease in satisfaction in the original domain. Doing so serves to
maintain an adaptation level of life satisfaction.
Stress management and the principle of role conflict. The compensatory model of life
satisfaction does not take into account the interaction of roles between life domains. Consider the following
scenario: Person A experiences a moderate level of satisfaction in both work life and family life (e.g., +3
units of satisfaction in each domain). The same person experiences conflict between roles in work life and
family life (e.g., family demand interferes with work demand and vice versa). Person B experiences the
same levels of domain satisfaction in both work life and family life (+3 units of satisfaction in each).
Additionally, Person B does not experience role conflict. The compensatory model of life satisfaction
would predict that both individuals are likely to experience the same the level of life satisfaction. However,
life balance dictates that role conflict be accounted for in the way domain satisfaction contributes to life
satisfaction. By taking into account role conflict we would predict that Person B should experience higher
levels of life satisfaction than Person A.
Research has shown that role conflict in life domains has an adverse effect on domain satisfaction
and overall life satisfaction (e.g., Kossek & Ozeki, 1998). A high level of psychological involvement in one
role is usually associated with increased amount of time and involvement devoted to that role, thereby
making it difficult to deal with role demand in other life domains (e.g., Greenhaus & Beutell, 1985).
Individuals experiencing role conflict across life domains are likely to experience stress, which in turn
reduces overall life satisfaction (e.g., Frone, Russell, & Cooper, 1992). Why would they experience stress?
To maintain successful performance in these roles they have to invest much more time and energy in the
same roles to maintain an acceptable level of life satisfaction. This allocation of more resources to maintain
successful performance in conflicting social roles is essentially induced by psychological stress commonly
manifested in terms of general psychological strain, somatic/physical symptoms, depression, substance
abuse, burnout, work-related stress, and family-related stress. Positive affectivity is negatively correlated
with stress (e.g., Brief et al. 1993; Judge, Locke, Durham, & Kluger, 1998; Watson, 2000; Watson, Clark,
& Tellegen, 1988).
Much research has shown that life balance can be achieved when social roles in work and non-work
life domains are compatible with minimal conflict (e.g., Greenhaus & Allen, 2011). That is, stress
management is typically a suggested approach to deal with the stress generated by role conflict. Role
conflict can take multiple forms (Greenhaus & Beutell, 1985). Time-based conflict refers to time pressures
from one role preventing individuals from meeting expectations in another role or creating a preoccupation
with one role while one is physically attempting to fulfil another role. Strain-based conflict occurs when
tension, anxiety, and/or fatigue from one role affects performance in another role. Behavior-based conflict
occurs when in-role behavior from one role is incompatible with behaviors expected in another role. As
such stress management can be viewed as involving three different set of techniques, techniques to reduce
stress from (1) time-based conflict, (2) strain-based conflict, and (3) behavior-based conflict. Examples of
stress management techniques dealing with time-based conflict is to plan ahead and schedule tasks and
events in ways that do not conflict. In doing so, the individual has to be time sensitive and punctual in
starting and completing tasks and attending events on time. Examples of stress management techniques
designed to reduce strain-based conflict include breathing exercises, meditation, physical exercise, among
others. An example of a stress management technique that can assist in reducing behavior-based conflict is
to become more conscious at identifying behaviors that may cause role conflict and to take action to change
those behaviors in ways to avoid role conflict.
In sum, the preceding discussion can be summarized as follows: Individuals who successfully
manage stress stemming from role conflict are likely to experience higher life satisfaction than those who
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fail to manage that stress. Specifically, role conflict brings about much stress—stress stemming from timebased
role conflict, strain-based role conflict, and behavior-based role conflict. Stress take a toll on life
satisfaction. Stress management to reduce time-based conflict, strain-based conflict, and behavior-based
conflict serves to reduce domain dissatisfaction. In doing so, life satisfaction is maintained at acceptable
adaptation levels.
Using skills, experiences, and resources in one role for other roles and the principle of role
enrichment. Consider the following scenario. A worker experiences imbalanced domain satisfaction in
work and family life. That is, his satisfaction at work is +4 units—on a 11-point satisfaction scale varying
from -5 (very dissatisfied) to +5 (very satisfied). A few months ago his satisfaction in family life was +3
but now it plummeted to -2 (moderate degree of dissatisfaction in family life). That is, his satisfaction in
family life has decreased significantly but his satisfaction at work remained constant. He is experiencing
diminished satisfaction in family life due to conflict with his adolescent children. He remembers using
conflict resolution strategies at work that were successful in resolving conflict within his project team. He
applies the same conflict resolution strategies at home to deal with the family conflict with positive results.
Doing so managed to change his satisfaction in family life from a -2 to a +3, thus increasing satisfaction in
family life.
There are many situations in which people use skills, experiences, and resources in one role for
other roles to enhance balanced satisfaction among life domains. Experiences in a social role can produce
positive experiences and outcomes in another other role. Similarly, skills and resources in one role can
improve or further enhance performance and satisfaction in another role. For example, work-to-family
enrichment occurs when work experiences serve to increase satisfaction in family life; and similarly,
family-to-work enrichment occurs when family experiences contribute to heightened satisfaction in work
life (e.g., Greenhaus & Powell, 2006; Voydanoff, 2004). Doing so helps workers enhance domain
satisfaction. That is, learning occurs in one life domain is easily transferred to other life domains allowing
the individual to generate more domain satisfaction through role engagement and goal attainment. And
such learning serves to enhance domain satisfaction.
Research has documented the effect of role enrichment on overall life satisfaction when two roles
are integrated (e.g., Olson-Buchanan & Boswell, 2006), when the skills and resource requirements are
similar (e.g., Greenhaus & Powell, 2006), and when role performance in one life domain becomes
increasingly interdependent with another (e.g., Hanson & Hammer, 2006; Ilies et al., 2009). High levels of
role enrichment serves to improve role performance in work and non-work domains, which in turn
contributes to balanced domain satisfaction. That is, skills, psychological resources, and material resources
generated in a life domain can be applied to roles in other life domains to improve role performance in those
domains (e.g., Hanson & Hammer, 2006). Furthermore, individuals with high role enrichment are less
likely to experience stress and anxiety from increased role demand. Such individuals apply their skills and
resources across social roles producing more positive outcomes—less psychological distress and anxiety in
performing multiple roles and a heightened sense of self-efficacy in those roles.
In sum, we can succinctly capture the preceding discussion as follows: Individuals who use their
skills, experiences, and resources in one role for other roles across life domains are likely to experience
greater domain satisfaction (in dissatisfied domains) than those who do not. That is, they use skills,
experiences, and resources in one domain to increase satisfaction in another domain (or mitigate decreases
in satisfaction in another domain), and doing so helps to increase (or preserve) life satisfaction overall.
Conclusion
The key goal of this chapter is to shed more light on the concept of life balance and its effects on
life satisfaction. We presented a concept of life balance involving nine behavioral strategies and linked
those strategies to subjective well-being and we explained how they impact life satisfaction through a set of
psychological principles. The first three of these strategies are designed to prompt greater participation of
satisfied domains to contribute to life satisfaction, whereas the remaining strategies are designed to increase
domain satisfaction and decrease domain dissatisfaction. As such we believe that there are two sets of
strategic requisites of life balance. One requisite is to prompt greater participation of satisfied life domains
to contribute to life satisfaction; the second requisite is to increase domain satisfaction and reduce
dissatisfaction. These two strategic requisites result in what we call “life balance.”
To reiterate, inter-domain strategies designed to prompt greater participation of satisfied life
domains to contribute to life satisfaction include: (1) engagement in social roles in multiple life domains
(explained by the principle of satisfaction limits), (2) engagement in roles in health, safety, economic,
social, work, leisure, and cultural domains (explained by the principle of satisfaction of the full spectrum of
human development needs), and (3) engagement in new social roles (explained by the principle of
diminishing satisfaction). Inter-domain strategies designed to increase domain satisfaction and decrease
926
domain dissatisfaction include (1) integrating domains with high satisfaction (explained by the principle of
positive spillover), (2) optimizing domain satisfaction by changing domain salience (explained by the
value-based compensation principle), (3) compartmentalizing domains with low satisfaction (explained by
the segmentation principle), (4) coping with domain dissatisfaction by engaging in roles in other domains
likely to produce satisfaction (explained by the behavior-based compensation principle), (5) stress
management (explained by the principle of role conflict), and (6) using skills, experiences, and resources in
one role for other roles (explained by the principle of role enrichment).
The reader should note that we have construed life balance in terms of two sets of conjoint
behavioral strategies. We identified at least three principles to capture the psychological dynamics of the
first set and six other principles capturing the psychology of the other set. Within each set there may be
more. We encourage researchers to make a concerted effort to identify more behavioral strategies of life
balance within each set. For example, one can argue that people who have a balanced life are adept in
organizing their lives. That is, they use organizational skills to help them do the best they can in various
social roles across a variety of life domains. This may be a principle involving the second set of interdomain
strategies—strategies designed to increase domain satisfaction and decrease dissatisfaction.
Another behavioral strategy that may involve the second set is efficiency. Perhaps people with a balanced
life tend to use efficiency skills. To be efficient is to try to generate as much output with as little input.
Efficiency skills require to be creative in engaging in tasks that manage to “kill two birds with one stone.”
For example, a person is efficient in planning to shop for office supplies (i.e., work life) and family meals
(i.e., family life) at the same time. How about making decisions in one social role in a particular life
domain by taking a whole-life perspective—by considering the effect of that decision on satisfaction in
other life domains? Could this be a behavioral strategy of life balance characteristic of the second set (interdomain
strategies designed to increase domain satisfaction and decrease dissatisfaction)?
Much of what we discussed in this chapter have focused on behavioral strategies of life balance in
relation to life satisfaction. Future studies should examine the relative efficacy of these strategies affecting
life balance and life satisfaction. Future studies should empirically test the conceptual model presented in
this study.
Understanding the dimensions of life balance and the theoretical mechanisms linking life balance
with life satisfaction should help practitioners and policy makers formulate programs that can enhance
subjective well-being. Armed with this greater understanding, therapists, life coaches, human resource
managers, and policy makers can develop better programs to help their own constituencies achieve greater
balance in their lives.
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Subjective Well-Being and the Law
By Peter H. Huang, University of Colorado Law School and Visiting Scholar, Loyola LA Law School
Citation
Huang, P. H. (2018). Subjective well-being and the law. In E. Diener, S. Oishi, & L. Tay
(Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
This chapter analyzes legal implications of subjective well-being (SWB) research. Law can and should
learn much from SWB research because the law can and should care about people’s SWB. An incomplete
list of legal doctrinal and subject areas in which law professors have applied SWB research includes
administrative law, alternative dispute resolution, business law, civil procedure, conflict resolution,
contracts, constitutional law, corporate law, criminal law, development law, employment discrimination
law, family law, immigration law, international law, negotiations, legal ethics, securities law, securities
litigation and enforcement, tax law, tort law, and trusts and estates. Some legal scholars have repeated or
contributed to existing concerns, debates, and disagreements among non-law scholars about how to
measure SWB. For example, some law professors continue to assume that SWB is one-dimensional,
despite the large amount of empirical psychological research finding that SWB is multi-dimensional and
has distinct components. Some law professors also continue to ignore the conceptual difficulties with
aggregation, interpersonal comparisons, and intertemporal comparisons of multi-dimensional SWB
measures. In addition, law often requires societies to make contested normative value-judgments over
which there lacks consensus. Some law professors and policy makers advocate using SWB metrics to
evaluate legal policies, procedures, and regulations. Others argue that hedonic adaptation implies legal
interventions have little, long-run SWB impact. This argument ignores short-run impacts which might be
irreversible or have spillover effects, including changing individual preferences and social norms. The
unique history and current sociology of the American legal academy has resulted in American legal
scholarship applying SWB research focusing perhaps unexpectedly primarily on legal education and law
practice. Perhaps quite surprisingly, at least to SWB researchers, is that law professors have applied SWB
research most, and by a quite far margin, to analyze how to utilize SWB evidence-based research to
sustainably improve the alarmingly, perennially, and persistently negative SWB of many law students and
lawyers.
Keywords: Law, Legal Scholarship, Law Professors, Legal Education, Law Practice
The United States Declaration of Independence stated in 1776 that a self-evident truth is that
people have the right to pursue happiness. It is notable the statement is a right of pursuing happiness
instead of a guarantee of achieving happiness (Schubert, 2012). Some American law professors have
applied SWB research to analyze legal rules and institutions. A partial inventory of the areas in legal
doctrine where law professors have written articles based upon SWB research includes administrative law,
alternative dispute resolution, business law, civil procedure, conflict resolution, contracts, constitutional
law, corporate law, criminal law, development law, employment discrimination law, family law,
immigration law, international law, negotiations, legal ethics, securities law, securities litigation and
enforcement, tax law, tort law, and trusts and estates. This is not and should not be a surprising collection
of legal topics because SWB research findings are relevant, for both descriptive and prescriptive reasons, to
law. Part of legal scholarship describes how law impacts human behavior. Another part of legal
scholarship considers how to design socially optimal legal rules and institutions. The notion of social
optimality requires a benchmark by which to measure and evaluate alternative legal arrangements. SWB is
one such yardstick. More precisely, SWB is a dashboard or portfolio of metrics, including life satisfaction,
positive affect, negative affect, and time use (Brulé & Maggino, 2017; Krueger, 2009; Wheatley, 2017).
There are also anticipated, experienced, and remembered SWB measures (Kahneman, 2013; Huang, 2014).
A natural area of legal scholarship based on SWB research is to analyze whether and if so, then
how law can foster economic development and growth. A common belief and folk theory is that acquiring
sufficient wealth causes happiness. People, countries, and the media therefore often use wealth as an
imperfect proxy for happiness. The numerous difficulties and problems with measuring countries’ wellbeing
using traditional economic indicators as Gross Domestic Product (GDP), or even Net Economic
Welfare (NEW), are well-known to economists (Fleurbaey, 2013; Jones & Klenow, 2016) and others,
including an oft-cited speech that Robert F. Kennedy (1968) famously made about some of the
shortcomings GDP has in measuring what matters.
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In the Report by the Commission on the Measurement of Economic Performance and Social
Progress, that President Nicolas Sarkozy of France commissioned, 2001 economics Nobel laureate Joseph
Stiglitz, 1998 economics Nobel laureate Amartya Sen, French economist Jean Paul Fitoussi, and other
leading economists (Stiglitz, Sen, & Fitoussi, 2010) advocated measuring social progress by SWB in place
of the more traditional GDP. Many countries, cities, and communities have adopted SWB measures to
inform policy decision-making. Anti-fracking ordinances, regional or city planning, environmental impact
regulations, land use restrictions, open space laws, water use limitations, and zoning laws are just some
examples where simply changing the criteria of policy evaluation from unfettered economic development
and growth to SWB measures has drastic implications. As 1972 economics Nobel laureate Kenneth Arrow
observed in discussing the importance of organizational agendas (1973, p. 47), placing full employment on
the United States federal government’s agenda, which the Full Employment Act of 1946 accomplished,
had real, albeit slow, social and policy consequences.
Many legal doctrinal areas have this common structure: law can change people’s incentives to take
certain relevant actions. Law can provide negative incentives, such as fines, imprisonment, penalties, or
taxes. Law can provide positive incentives, such as monopolies, rents, subsidies, or tax deductions. In
business law, relevant actions include choice of business organization, partnership dissolution, and
partnership formation. In corporate law, relevant actions include acquisitions, appropriation of corporate
opportunities by a company’s directors and officers, corporate oversight, incorporation, mergers, and selfdealing
of a company’s directors and officers. In contract law, relevant actions include breach of and
reliance on a contract. In civil procedure, relevant actions include the decisions to file, drop, continue, and
settle lawsuits. In criminal law, relevant actions include crime commission and crime prevention. In family
law, relevant actions include marriage, divorce, and having children. In immigration law, relevant actions
include legal immigration, illegal immigration, and immigration enforcement. In international law, relevant
actions include agreeing to and breaking accords, conventions, and treaties. In legal ethics, relevant actions
include awareness, care, record-keeping, and social media use. In negotiations, relevant actions include
offers and counteroffers. In property law, relevant actions include acquisition, development, innovation,
investment, pollution, and upkeep. In securities law, relevant actions include disclosures, insider trading,
and securities fraud. In tax law, relevant actions include compliance, fraud, and reports about income,
expenses, or profits. In tort (accident) law, relevant actions include care, precaution, and activity levels. In
trusts and estates, relevant actions include bequests and charitable donations.
Much of legal analysis determines how civil liability and criminal penalties can achieve socially
optimal magnitudes of relevant actions. Socially optimal monetary civil liability damages or criminal
penalties involve wealth reallocations to achieve socially optimal compensation, deterrence, and risk
allocation (Cooter, 1991). Such legal analysis hinges crucially on the notion of social optimality employed.
Wealth or more generally economic and financial metrics of social optimality are only proxies of what
people ultimately care about (Oswald, 1997). After all, money has instrumental, not intrinsic, value. Most
economists view money to have three functions: a medium of exchange, a store of value, and a unit of
account. Some anthropologists, communication scholars, marketing scholars, philosophers, political
scientists, psychologists, and sociologists view money to be much more in the sense of signals or symbols
expressing beliefs, class, connection, emotions, family, friendship, gratitude, hope, identity, intimacy,
meaning, morals, power, relationships, security, sentiments, status, success, and trust (Bandelj, Wherry, &
Zelizer, 2017; Zelizer, 2017). People, popular culture, and the media often conflate and confuse money
with SWB.
Changing the meaning of socially optimality to include or be SWB rather than some other more
traditional normative criteria such as wealth can dramatically change the design of legal rules and
institutions (Huang, 2010) and in the regulation of risk (Huang, 2008a). For example, current tax law is
based upon optimal tax theory, which utilizes a neoclassical welfare economics approach to assess and
evaluate policy (Kaplow, 2010). A key assumption of neoclassical welfare economics is that people exhibit
declining marginal utility of income. Modern American income tax law and arguments for progressive
taxation are premised on that assumption. There is empirical evidence that some individuals experience
increasing marginal utility of income, which would lead a tax policy based on welfare economics analysis
to redistribute income from poor to rich people (Lawsky, 2011). If tax analysis replaces the criterion of
maximizing social welfare, defined to be some weighted sum of individual welfare, with the criterion of
maximizing experienced SWB, then SWB research supports progressive taxation policies that redistribute
income from rich to poor people, because a study by psychologists of 54 countries found progressive
taxation is associated with higher SWB (Oishi, Schimmack, & Diener, 2012).
In business law areas, such as corporate law and securities regulation, for example, metrics used to
evaluate the social desirability of economic outcomes and legal interventions include corporate stock
market value and shareholder wealth. Huang (2005a, 2005b, 2008b, 2011) examines other possible metrics
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for evaluating business law and securities regulations, including career satisfaction, consumer confidence,
economic stress, financial anxiety, investor exuberance, market moods, meaning at work, shareholder
empowerment and participation, trust in financial markets, and work-life balance. People’s financial health
and mental health are interrelated and influence each other. Economist Graham (2017) draws on research
linking inequality and SWB to show how a growing prosperity gap leads to gaps in people’s aspirations,
beliefs, hopes, and optimism. Poverty has emotional costs in terms of depression, despair, desperation,
hopelessness, misery, insecurity, and stress.
Blumenthal and Huang (2009) propose and advocate the notion of positive parentalism to foster
more positive individual and social outcomes based on applying insights from positive psychology. For
example, governments can help people learn and develop their signature strengths so that individuals can
seek and craft work to be more fulfilling and view that work to be a calling instead of a career or job
(Huang, 2008c; Wrzesniewski, McCauley, Rozin, & Schwartz, 1997). If light paternalism is analogous to
therapy that corrects for and remediates cognitive and emotional disturbances that detract from individual
SWB (Loewenstein & Haisley, 2008), then positive paternalism is analogous to positive therapy (Leffert,
2017) that improves decision-making capabilities or processes via helpful thinking styles that raise
individual SWB. Positive parentalism is related to policies that boost people’s competencies to exercise
agency by making choices (Grune-Yanoff & Hertwig, 2016; Hertwig & Grune-Yanoff, 2017). Both
positive parentalism and boosts empower people to make better decisions (Huang, 2015b).
A famous area of SWB research concerns hedonic adaptation (Brickman & Campbell, 1971).
Natural applications to law of SWB research about hedonic adaptation include analysis of civil lawsuit
settlements (Huang, 2008d; Swedloff, 2008), economic development (Clark, 2012), emotional paternalism
(Blumenthal, 2005, 2007), roles of decision versus experience utility in public policy (Loewenstein and
Ubel 2008), and tort damages for pain and suffering (Swedloff & Huang, 2010). The debate over the legal
relevance and significance of hedonic adaptation is ultimately a disagreement over three sets of issues.
First, reasonable people differ over whether SWB is the only thing people and society care about and
should care about (Etzioni, 2016; Swedloff, 2014). Second, the robustness of hedonic adaptation varies
across contexts and individual demographic variables, such as age, ethnicity, and gender. Third, the
distributive, ethical, and normative implications of hedonic adaptation are complex and unresolved.
Another legal area where SWB research about hedonic adaptation has relevance is employment
discrimination damages (Moss & Huang, 2009). A psychological theory of affective adaptation due to
Timothy Wilson and Daniel Gilbert posits that people attend to unexplained events, react to them and if
they can explain them, adapt emotionally to and attend less to them (Wilson & Gilbert, 2008). People who
lose their jobs due to illegal discrimination are less likely to adapt to such losses than people who lose their
jobs for non-discriminatory causes because illegal discrimination is illegitimate, invidious, and results from
animosity and hatred. A legal implication of this, other happiness research, and the endowment effect is
that courts should award higher damages for illegal firing of a long-term employee than for illegal failure to
hire.
The strand of SWB research that has had the most impact in areas of law has been that about
mindfulness and the legal areas that have most whole-heartedly adopted SWB research about mindfulness
are those of conflict resolution: negotiations, meditations, and alternative dispute resolution (Huang, 2018a;
Riskin, 2002, 2010, 2012; Riskin & Wohl, 2015). Although practicing mindfulness can apply to every area
of law (and life), law professors and lawyers practicing in the areas of conflict resolution have been at the
forefront of applying the insights from SWB research about mindfulness. Why this has been the case is
unclear. Perhaps one reason is that conflict resolution is emotionally charged and mindfulness about
emotions can be seen to be a form of emotional intelligence.
Many law professors, law students, and lawyers view much of legal education and law practice as
being analytical, cognitive, and logical, instead of also being affective, emotional, and psychological
(Robbennolt & Sternlight, 2012). Many law professors, law students, and lawyers often use the phrase
“thinking like a lawyer” to describe the goal of legal education. Rarely do law professors, law students,
and lawyers talk about feeling like a lawyer or feelings in general. Yet many in the public view and many
clients view (even their own) lawyers as being aloof, arrogant, robotic, uncaring, and unfeeling. Huang and
Rosen (2015) borrow the popular culture metaphor of a zombie apocalypse to describe what happens to
many American law students in law schools and lawyers in practice. Many law professors are coming to
realize the competitive advantage and importance that emotional intelligence in the form of empathy,
compassion, emotional regulation, and mindfulness offers lawyers in their professional development
(Austin & Durr, 2016; Fruehwald, 2015; Kiser, 2017; Linder & Levit, 2014; Martin, 2014).
Practicing mindfulness in the form of developing and exercising self-compassion may increase
attorney SWB and gender diversity (Mangan, 2016). Mindfulness has now become pervasive in legal
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education and law practice (Huang, 2015a, 2016, 2017, 2018b; Martin, forthcoming). To fully appreciate
why this has become so, it helps to better understand the unique history and current sociology of American
law, legal scholarship, law professors, and the legal academy. Although American law professors, law
students, and lawyers know much of this information only all too well, professors who do not teach in law
schools are likely to find the next section surprising, if not shocking, because law schools differ so much
culturally and structurally from other parts of universities, including economics, psychology, and marketing
departments which are the academic homes of many SWB researchers. The next section also partially
explains what parts of SWB research law professors, law students, and lawyers find most fascinating and
useful.
Law, Legal Scholarship, and Law Professors
Law is often a blunt and crude instrument of social policy. Societies design and enforce laws to
achieve hopefully legitimate and worthy ends. Legal scholars approach the study of law from various
perspectives. For example, an economics approach to law may view law as creating incentives to avoid
anti-social behavior through a menu of civil liabilities and criminal penalties. An expressive approach to
law may view law as being aspirational in changing social norms, expressing shared value-judgments, and
fostering pro-social individual preferences. An approach to law as instruments or levers implies some
criterion or set of criteria to assess how well the law is doing. Neoclassical economic approaches to law use
the criterion of Pareto efficiency (Calabresi, 1991) or Kaldor-Hicks efficiency (Hicks, 1939; Kaldor, 1939)
to evaluate legal interventions. Modern legal theory and legal education has become infused with the
language of microeconomics and finance, including these concepts: adverse selection, compliance, costbenefit
analysis, deterrence, discounted present value, diversification, efficiency, error costs, expected
value, externalities, incentives, informational efficiency, insolvency, internalization, moral hazard, network
externalities, opportunity costs, public bad, public good, risk allocation, risk aversion, social welfare,
standardization, tradeoffs, transactions costs, and utility.
Because happiness and SWB are related to, although distinct from, the notions of utility and
welfare in modern economics (Benjamin et al. 2014a, 2014b), SWB offers a potential alternative
framework to evaluate how well the law is doing. Utilizing SWB as a legal metric requires the balancing of
simplicity against validity. For better or worse, the gatekeepers to policy are often economists and lawyers.
SWB researchers can influence economists through happiness economics. SWB researchers can influence
lawyers through happiness law and economics. Some legal scholars view SWB research as providing a
different and more realistic foundation than neoclassical economics for performing legal analysis. The
question some legal scholars analyze is whether a particular legal policy, procedure, or rule increases a
measure or a (weighted) set of measures of SWB. How to weigh distinct components of SWB is a concern
and something over which reasonable people can disagree.
Some legal scholars have reargued the debates over whether SWB is a one-dimensional or multidimensional
measure. Empirical research finds that SWB is multi-dimensional and includes evaluative,
experienced, and eudaimonic aspects of well-being (Stone & Mackie, 2013). The multiple dimensions of
SWB also raise the issues of incompleteness and intransitivity of making comparisons based upon SWB.
There also are all too familiar political economy concerns that policy makers have multiple opportunities
and powerful incentives to cherry pick and manipulate SWB measures (Frey & Gallus, 2013).
Because of the particular path-dependent history of American legal scholarship, some legal
scholars are suspicious that SWB is just economists’ old notion of utility or welfare dressed in
psychological garb. It is helpful to briefly review the history of American legal scholarship. The former
dean of Yale Law School, Anthony T. Kronman (1993, p. 167), expressed his opinion that law and
economics has been the intellectual movement with the greatest influence on American academic law in
last twenty-five years of the twentieth century. Today’s dominant “law and economics” movement started
with the work of economics Nobel laureates Ronald Coase and Gary Becker, Henry Manne, Guido
Calabresi, and Richard Posner. Economic analysis of law has now become a routine part of jurisprudence,
judicial opinions, and law school classes. In spite of, or perhaps because of, the influence of law and
economics, there have been and remain today many criticisms of the law and economics approach and
movement. Critics point out how “classical” law and economics pays little attention to human rights,
distributive justice, and the importance of situations in shaping human choice and behavior. More recent
incarnations or versions of law and economics incorporate considerations about cognition, fairness, and
contexts by drawing upon research from anthropology, neuroscience, psychology, and sociology. These
newer developments in economic analysis of law apply insights from behavioral economics, game theory,
neuroeconomics, and socio-economics. Behavioral economics and its application to law, known as
behavioral law and economics, are currently very popular analytical tools among many legal scholars.
The above historical backdrop explains why some law professors think of SWB research,
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particularly happiness economics, as just more of the same old law and economics. For these law
professors, the small difference is that happiness economics, instead of neoclassical economics, has now
become the analytical tool for evaluating legal rules and institutions. Some law professors view allusions to
happiness to be merely a way to make look modern Jeremy Bentham’s (1749/1948) old moral philosophy
of utilitarianism. Some law professors are understandably suspicious and wary of articles and popular trade
books that include the word “happiness” in their titles with scant discussion about positive psychology or
SWB in their books.
The above historical backdrop also explains why some other law professors view SWB research in
the form of hedonic psychology or positive psychology as challenging the prevailing law and economics
orthodoxy because of SWB research focusing on people’s anticipated, experienced, and remembered SWB
as opposed to neoclassical economics’ revealed preference theory, which assumes people have
unobservable preference orderings, which their observed choices reveal. For these law professors, SWB
research differs fundamentally and radically from behavioral economics. While behavioral economics finds
that many people have cognitive biases and utilize heuristics, SWB research finds that people may not
choose what maximizes their SWB (Benjamin et al., 2012) and people having high SWB may be
satisficing, instead of maximizing any objective function (Schwartz et al., 2002). These law professors
view SWB research to have pervasive and far-reaching legal policy implications, such as advocating for
changes in (tax) law and policies to reduce American consumerism (Ritzer, 2013) and materialism (Kasser,
2003).
It is also helpful to briefly review the sociology of American legal scholarship. Most American law
professors have a professional degree, namely the doctor of jurisprudence or juris doctor (J.D. or JD). Most
American law professors do not have a Ph.D. These two facts mean that most American law professors
have neither the knowledge involved with nor experience of writing a Ph.D. dissertation. These twin facts
also mean that most American law professors lack Ph.D.-level expertise in economics, psychology, or any
other discipline. Finally, most American law professors have little, if any, training in probability and
statistics. In fact, many American law professors, law students, and lawyers lack much numeracy (Cheng,
2014; Milot, 2013; Obama, 2011), though some law students have a surprisingly high amount of
mathematics skills (Rowell & Bregant, 2014). The significance of the above observations is that many
American law professors, law students, and lawyers are unable to directly evaluate the validity of empirical
and experimental SWB research. Certainly, most American law professors, law students, and lawyers are
consumers, not producers, of SWB research.
Most American law professors publish exclusively in American law reviews, which are not peerrefereed.
Instead, second-year and third-year law students decide which of the many article submissions
they receive to publish. American law professors make simultaneous and multiple article submissions.
Upon acceptance, American law professors typically try to trade up their accepted article to a higher-ranked
law review. American law schools have a flagship or general law review in addition to several other legal
subject matter specialized law reviews. There are several rankings of law reviews that generally track the
U.S. News & World Report ranking of law schools. Most law reviews also do not require anonymous
submissions.
Many American law professors often engage in over-claiming of the scholarly contributions of
their law review articles. Some law professors are notorious for repeatedly publishing multiple, yet only
slightly different, versions of essentially the same article. Because law reviews are mostly, if not
exclusively, run by law students, there is little institutional memory. There are two submission cycles or
seasons, one in mid-February after new law student editorial boards have been chosen and the other in midAugust
when law students return from their summer jobs. Law reviews typically publish a couple of issues
per annual volume with each issue consisting of a couple of articles. For those slots, most law reviews will
typically receive several thousand submissions because simultaneously submitting the same article to
multiple law reviews is the norm. Many law review editors have neither the desire, interest, motivation,
time, or training to read, let alone carefully and thoughtfully, that many unsolicited manuscripts, each
approximately 25,000 words or 50 double-spaced pages. Law review editors often choose which articles to
publish based on a catchy, pithy title and the first several pages of a manuscript. Some law review editors
use the name, affiliation, and past publications of authors as imperfect proxies of quality. Many authors
claim their article is the first and only one to address an undertheorized important legal topic. A recent law
review article provides a parody and satire of law review articles generally (Schlag, 2017).
This publication system perversely selects for publication many law review articles that are
grandiose, overly complex, and verbose. There is often a disproportionate number of law review articles
that draw upon interdisciplinary and multi-disciplinary research because such law review articles are more
complicated, impressive, and interesting than the traditional legal analysis of judicial opinions and statutes.
The above sociology of the legal academy partially explains what law review articles law student law
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review editors chose to publish. As to why law professors publish, there are many reasons, including
feeling pride, getting tenure, influencing policy, being invited to scholarly conferences, and experiencing
joy (Anaya, 2017).
Improving Legal Education Based on SWB Research
There is currently a well-known crisis in legal education on many levels (Lewinbuk, 2015, pp. 5-7;
Tamanaha, 2012). Since 2011, there have been historic lows in the number of American law school
applicants, students, graduates, and jobs that involve law practice or require the professional J.D. degree
(Bernstine, 2014). Legal education commentators and observers disagree over whether these changes are
cyclical or structural and temporary or permanent. An area of justifiable interest to law students and law
professors is legal education reform. Some other law school stakeholders, such as law school alumni,
administrators, and law student wellness specialists, also have understandable incentives to advocate for
legal education reform.
The portrayal of American legal education in popular culture is and has been usually very negative
with many films and television programs featuring a cruel, inquisitional version of the so-called Socratic
method of teaching in which law professors continually and unsympathetically question law students into
submission, crying, and/or throwing up (Papke et al., 2012b). Even prior to the current legal education
crisis, some law school administrators engaged in dishonest and fraudulent actions to get a higher position
in the highly influential and very competitive annual law school rankings the magazine U.S. News &
World Report publishes each spring (Huang, 2012).
Although most students entering American law school have slightly higher SWB than the
population average, by the end of the first semester of law school, many law students report statistically
significant lower SWB and mental health, with little recovery during law school or afterwards (Sheldon &
Krieger, 2004, 2007). A 2014 SWB study (Organ, Jaffe, & Bender, 2016) surveyed over 11,000 law
students at fifteen law schools and found that 37% screened positive for anxiety, 17% screened positive for
depression, 53% drank enough to become drunk at least once in the prior thirty days, 43% binge drank at
least once in the prior two weeks, 22% binge drank more than two times in the prior two weeks, and 14% in
the prior year used prescription drugs without a prescription. Sadly, the survey also found that over 60%
expressed concern that seeking help is a potential threat to bar admission or finding a job, about 23%
sought help for mental health problems, and only 4% of students had sought help for alcohol and drug
problems. These disturbing statistics may not even reveal the depths of the SWB crisis among American
law students because of underreporting and self-delusion.
Undoubtedly, many American law students are suffering mentally and emotionally throughout their
time in law school. To cope temporarily with precipitous declines in SWB, many law students are
developing bad and unsustainable strategies of drinking alcohol and self-medicating (Austin, 2013, 2015)
instead of learning to eat healthily (Austin, 2017). Many factors can account for the sharp drop in SWB in
the first semester of law school, including an exclusive focus on analytical and critical thinking, amorality
or value-neutrality of legal analysis, the mandatory, competitive, and hierarchical grading curve of many
law schools with required means, medians, or distributions (Heffernan, 2014), a dominant language of law
school (Mertz, 2007), or a shift from such intrinsic values as learning, helping others, and public interest to
such extrinsic values as class ranking, grades, and starting salaries (Peterson, 2014).
What is clear is that a SWB crisis exists in American legal education. Because unhappy students
are likely to become unhappy lawyers, a SWB crisis also exists in American law practice, as the next
section discusses. A nationwide task force (with representation from the American Bar Association,
Association of Professional Responsibility Lawyers, National Conference of Chief Justices, National
Conference of Bar Examiners, and National Organization of Bar Counsel) issued a 73-page report detailing
changes that bar associations, judges, lawyer assistance programs, law schools, legal employers, and
regulators each can undertake to promote SWB in legal education and law practice (National Task Force on
Lawyer Well-Being, 2017). Many of the recommendations of that report are based on positive psychology
research, including examples in Appendix B of that report discussing possible topics to teach law students
about how to sustainably increase SWB.
Law schools can increase law student SWB in many ways, including enabling law students to
make better academic and career choices based on a more realistic vision of the realities of lawyers’
professional lives, teaching students about different attribution styles (Felder, 2014; Rosen, 2011), and not
fostering learned helplessness (Levit & Linder, 2010). A law professor and his daughter, who earned a
master’s degree in applied positive psychology, co-authored an important article about how and what legal
educators can learn from positive psychology to slow the current epidemic of law student depression
(Peterson & Peterson, 2009).
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A new field of study, positive legal education, (Austin, forthcoming; Huang, Brafford, Austin, &
Knudson, 2018) proposes to apply research from positive psychology and positive education to transform
American legal education focusing on law students’ SWB. This project intends to analyze whether: (1)
current American legal education adversely alters brain structure and function; (2) current American legal
education impairs character development, compassion, and ethical decision-making; and (3) neuroscience
and positive psychology-based interventions can mitigate the harmful effects of current American legal
education. Ultimately, this project aims to develop sustainable positive legal education interventions that
cultivate and foster character development, compassion, and ethical decision-making by American law
students.
This project will be a longitudinal, multi-year study of law students that includes the collection of
spit samples to test for cortisol levels and the neuroimaging of law students in August, December, and May
of the first year of law school to test for structural and functional brain changes. This project also plans to
conduct brain scans while law students make decisions in ethical dilemmas and play economic trust games
(Huang, 2009) to determine if current American legal training encourages unethical behavior (Huang, 2013)
and impairs the quality of decision-making, as well as during memory tasks to discover whether current
American legal education harms law students’ memory (Austin, 2013). The team plans to investigate
whether such positive psychology interventions as mindfulness or compassion meditation can change law
students’ brain functioning, brain structure, and charitable donation behavior, as is the case for a study
involving non-law students (Ashar et al., 2016). The project also plans to investigate if teaching other
SWB interventions enhances law school academic performance, similar to related research about
improvements on standardized tests (Adler & Seligman, 2016).
Improving Law Practice Based on SWB Research
The practice of law in America today is less of the noble profession it once was and more of a
competitive, cutthroat, and pressure-filled business, like many other former professions, such as
accounting, advertising, and medicine. Automation, outsourcing, and rapid technological upheaval are only
happening at ever increasing rates. While there is no shortage of lawyers for those who can afford the best
legal representation that money can buy, there is and has been a chronic shortage of lawyers for people
who cannot afford to hire lawyers to vindicate their legal and human rights (Bok, 1983).
Many clients are unsatisfied with many aspects of law practice, including the billable hour system
of compensation. Many law firm junior associates are unhappy about work-life balance. Many law firm
partners are disillusioned by the unrelenting stresses of the business of law practice. Many in the general
public see lawyers as well-paid corporate lackeys and parasites profiting off of others’ misfortune and
miseries. Lawyers have many external public relations issues and internal quality-of-life problems.
Lawyers are often portrayed as flawed humans, if not outright villains, in movies (Asimow, 2000) and
popular culture (Papke et al., 2012a). Lawyer jokes are ubiquitous and seemingly never-ending (Galanter,
2005).
Many lawyers are prone to poor mental and physical health, alcoholism, anxiety, depression, drug
abuse, suicide, and unhappiness (Brafford, 2014, 2017). A 2016 study found that 20% of attorneys abused
alcohol and about 30% had symptoms of depression (Krill, Johnson, & Albert, 2016). Despite these and
many other depressing statistics about lawyer SWB (Krieger & Sheldon, 2015), there is hope for change
for the better at both the level of individual attorneys and the level of legal organizations (Brafford 2014,
2017; Huang & Swedloff, 2008).
Individual attorneys can employ many positive psychology strategies to boost their SWB. One such
strategy is to cultivating optimism as part of a larger strategy to boost an attorney’s “psychological capital”
or “PsyCap,” a positive mental capacity, which is akin to what is colloquially called mental toughness.
PsyCap consists of these four psychological resources: hope, optimism, resilience and self-efficacy
(Gruman & Saks, 2013; Knudson, 2015; Luthans, Youssef, & Avolio, 2006). Empirical research reveals
significant positive links among PsyCap and engagement, job performance, and job satisfaction and
negative links with anxiety, stress, and turnover (De Waal & Pienaar, 2013; Gruman & Saks, 2013). Other
positive psychology evidence-based strategies that individual attorneys can easily incorporate into their
daily lives include acts of kindness, gratitude activities, and savoring (Lyubomirsky, 2007). These activities
can help boost positive emotions, and in turn resilience and SWB.
Brafford (2014, 2017) offers a carefully designed, detailed blueprint for how law firms can become
positive organizations. Brafford (2014, 2017) makes a compelling business case for why positive law firms
are likely to enjoy competitive advantages: 1) higher profitability, 2) desirable, extra-financial business
outcomes, and 3) successfully recruiting and retaining Millennials. Brafford (2014, 2017) proposes creating
a law firm SWB index with metrics for lawyers, staff, clients, law firms, and communities. Such an index
would be a welcome counterpoint and supplement for the currently dominant and well-known profits-per-
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partner metric. Widespread adoption of a law firm SWB index would facilitate comparisons across law
firms and encourage law firms to raise their SWB index scores to attract like-minded talent and clients.
Some Concluding Thoughts
SWB research can and should inform law. Humans make laws, which means that humans can
change laws. Laws differ across countries at any one point in time. Laws differ across time in any one
country. People today are often shocked by some of the past laws in their country or other countries.
Examples abound involving laws that discriminated against people solely because of their age, ethnicity,
gender, sexual orientation, race, and religion. Because laws come and go, there is hope laws that decrease
SWB will be overturned and laws that increase SWB will stand the test of time. There is no guarantee of
course that will happen at all or quickly. Laws have their own inertia. Laws can thus be quite sticky.
This chapter has considered only some of the vast and growing body of legal scholarship based on
SWB research. Merely replacing economic notions of efficiency and metrics of welfare by SWB has
potentially radical implications for the optimal design of legal rules and institutions. For better or worse,
currently most of the legal applications of SWB research are devoted to improving legal education and law
practice. To those outside of the legal academy and legal profession, such a focus may seem to be selfabsorbed
and self-indulgent. Non-lawyers can legitimately ask why not study the SWB of psychologists,
economists, educators, adolescents, nurses, veterinarians, and many others?
There are, at least, twelve responses that come to mind. First, researchers can and should analyze
the SWB of all people. Second, researchers can and should analyze the SWB of all professions. Third, and
more on point, dramatic, rapid, and permanent declines in the SWB of law students can interfere with the
legal education of those students. Fourth, dramatic, rapid, and permanent declines in the SWB of law
students can interfere with the legal education of their peers. Fifth, and even more importantly, lawyers
with low SWB are less effective advocates for their clients. Sixth, and also importantly, lawyers today are
often powerful leaders in many societies. Seventh, and also significantly, lawyers can collaborate with nonlawyers
to address many of the critical domestic and international problems facing humanity, including
climate change, inequality, injustice, poverty, and prejudice. Eighth and perhaps most importantly, lawyers
can make a difference to individual and societal SWB in societies under the rule of law. Ninth, lawyers
who have high SWB have the power to do good and help those who cannot help themselves. Tenth and
conversely, lawyers who have low SWB have the power to do harm and hurt those who cannot help
themselves. Eleventh, because lawyers are gatekeepers to policy making in America, lawyers who have
high SWB can improve the quality of U.S. policy making. Twelfth and conversely, lawyers who have low
SWB can impair the quality of U.S. policy making.
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How Political Systems and Social Welfare Policies Affect Well-
being
By Robert MacCulloch, University of Auckland
Citation
MacCulloch, R. (2018). How political systems and social welfare policies affect well-being. In E.
Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
This chapter focusses on the question of how formal institutions, like those governing the level of freedom
and the generosity of the welfare state, affect self-reported well-being. The evidence suggests, for example,
that more freedom, as well as government structures which encourage civic engagement, participation and
trust, have positive effects. Many studies, however, use cross-sectional data with small sample sizes, often
due to institutions being measured at the country level with limited variation over time. As a consequence,
further work is needed to test robustness. Stronger results hold with respect to particular types of welfare
state institutions, like unemployment benefits, which are subject to quite frequent changes within nations.
Increases in unemployment benefits are associated with higher levels of well-being for all workers,
probably due to greater income security. However, doubt still persists as to their overall impact, due to the
extent to which well-being is adversely affected by the higher taxes needed to support a more generous
welfare state.
Keywords: Well-being, Freedom, Partisan Happiness, Welfare Benefits, Taxes.
This chapter is about how formal institutions in a nation affect the well-being of its people.
Douglass North (1990) defines institutions as “the humanly devised constraints that structure human
interactions. They are made up of formal constraints (rules, laws, constitutions), informal constraints
(norms of behaviour, conventions, and self-imposed codes of conduct), and their enforcement
characteristics”.
In North’s theory, formal rules are created by the polity, whereas informal norms maybe part of the
heritage that is often referred to as “culture” and includes characteristics like “social trust”. This chapter
focuses mostly on formal institutions, and we leave it to other authors in this book to discuss how informal
norms affect well-being.
The chapter is structured as follows. In section 2 we study how the nature of the political system in
a country affects well-being. Do the citizens of a country gain pleasure from having more political
freedoms and civil liberties? In addition to the degree of freedom of its citizenry, we ask whether the
quality of other government structures affect happiness. Does corruption of public officials lead people to
experience more negative feelings? Is there a relationship between the size and quality of the regulatory
state and well-being?
This section also emphasizes the importance of formal institutions that facilitate greater
engagement with the political process and reinforce social networks. Is it the economic outcomes that
systems yield, or the degree to which their decision-making processes are inclusive, which matter the most?
The section concludes with a discussion of the role of partisan politics. Is, for example, political
competition more like a team sport whereby one gets pleasure from being a supporter of the winning side,
aside from the policies which actually end up being implemented?
Section 3 focusses mostly on government spending and taxes. It seeks to answer questions like
whether or not countries with more generous welfare states and greater job security have higher well-being.
Do the ‘happiness studies’ on this topic take into account the fact that countries with high public spending
tend to tax their citizens more? On the other hand, can “sin taxes” like on cigarettes, actually increase wellbeing?
The final section concludes.
The Effect of Political Systems on Well-being
The Effect of Freedom on Well-being
First, we ask the question of how formal institutions governing the level of civil, political and
economic freedoms affect well-being in nations. Most of the institutions governing these kinds of freedoms
change only slowly over time which is probably why much of the work in this field has relied on exploiting
cross-sectional variation.
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Many authors have sought to test the hypothesis that freer countries have higher levels of selfreported
well-being (SWB).1 Greater choice is typically regarded as a good thing. In particular, democratic
freedoms are often viewed as being vital to monitor and control politicians, and to bring the decisions of
government closer to the wishes of the citizenry.
Of course, not all theories highlight the positive effects of freedom. For those who have selfcontrol
problems, like eating or smoking too much, constraints on behaviour may be helpful. It is often
argued that the ‘right to bear arms’ should be restricted. There are also many rules imposed on children,
which include not having the right to vote, even in western democracies. Some people may voluntarily
place restrictions on themselves by joining a strict religion, due a belief in the supernatural or desire to be a
member of a close-knit group.
It should also be noted that economic freedoms are nearly always regulated, usually in the name of
increasing social welfare. Free markets are not to be mistaken with unregulated markets. Even “unfettered
competitive markets are based on a set of laws and institutions that secure property rights, ensure
enforcement of contracts, and regulate firm behaviour and product and service quality” (see Acemoglu,
2009).
The “happiness studies” on this topic tend to use data at the national level and their findings are
still in need of greater validation. As an early example, Veenhoven (1993) uses a cross-section of 23
countries from the World Values Survey (WVS) in the 1980s. He argues that there “ is a clear
correspondence between average happiness in nations and the degree to which these nations provide
material comfort, social equality, freedom and access to knowledge” (pg 32). Freedom is measured, in this
instance, by the Estes Index of Political Participation and also the degree to which the country has a free
press.
In a later study, Veenhoven (2000a) used a cross-section of 38 countries and a single index
combining political, civil and economic freedoms to again argue that freedom and well-being are positively
correlated.
However, Inglehart and Klingemann (2000) found that their Freedom House democracy score was
not significant in a SWB regression, after controlling for other variables, when using a cross-section of 105
countries. This result led these authors to conclude that “the interpretation that democracy causes wellbeing
does not stand up: other factors – particularly the number of years of communist rule and the
society’s level of economic development – seem to play much more powerful roles” (pg 181).
The uncertainty underlying this debate is heightened by the controversy over whether even the
level of development itself influences well-being. The time-series of SWB data for many nations do not
appear to support this proposition (see Easterlin, 1974) and the growth rate of GDP has often been argued
to matter more (see Di Tella, MacCulloch & Oswald, 2003).
One approach to better identify the relationship between freedom and well-being has been to use
within-country data. For example, Frey and Stutzer (2000) study the role of direct democracy (via
initiatives and referenda) using a cross-section of 26 Swiss cantons between 1992 and 1994. A shift from
the canton with the lowest direct participation rights (i.e., Geneva) to the one with the highest (i.e., Basel
land) is associated with an 11 percentage point higher probability of declaring oneself completely satisfied
with life (on an eight point scale ranging from “completely dissatisfied” to “completely satisfied”).
These authors argue that the institutions of direct democracy have two effects on well-being. One
maybe to generate better policy outcomes. The other is to expand the possibilities of citizens to participate
in political processes and procedures.
The relative sizes of these two effects can be identified since their data set includes foreigners
living in Switzerland who can share in the outcomes of direct democracy, but who are not able to gain
utility from participation in the process, which is only available to citizens. Consequently Swiss nationals
are hypothesised to gain more from direct democracy, compared to foreigners. It turns out that about two
thirds of the total gain in SWB is due to a more favourable process in political decision-making whereas
one third is due to more favourable outcomes.
The robustness of the Frey and Stutzer (2000) results has, however, been questioned. For example,
Dorn, Fischer, Kirchgässner and Sousa-Poza (2008) use surveys conducted between 2000 and 2002 by the
Swiss Household Panel to re-evaluate the relationship between cantonal direct democracy and well-being.
Their study introduces new controls for cultural determinants of life satisfaction such as languages and
religion. Once these controls are included, these authors are unable to find a robust relationship.
Furthermore, Blume, Muller and Viogt (2009) are also unable to detect a correlation between direct
democracy and happiness scores, although they revert to using cross-country data with a sample of 54
947
observations taken between 1996 and 2005.
Another approach to help better identify the relation between freedom and SWB has been to bring
a time series dimension to the question. For example, Inglehart, Foa, Peterson and Welzel (2008) use
different waves of the World Values Surveys, taken between 1981 and 2007. They correlate changes in
SWB (measured by both self-reported happiness and life satisfaction) from the first to the last available
survey for each country, with changes in two proxies for freedom, as well as changes in GDP per capita.
One of their freedom proxies is the level of democracy, measured by the Polity IV project. The
other is a survey question taken from the WVS which asks, “Some people feel they have completely free
choice and control over their lives, while other people feel that what they do has no real effect on what
happens to them. Please use this scale where 1 means “no choice at all” and 10 means “a great deal of
choice” to indicate how much freedom of choice and control you feel you have over the way your life turns
out”.
Of these two proxies, the Polity IV measure of democracy is not significant. Inglehart et al (2008)
instead argue that their results do “show that a growing feeling that one has free choice was by far the most
important influence on whether SWB rose or fell”. The positive correlation which these authors report
between changes in SWB and changes in feelings of free choice is an important one, although its
implications are somewhat unclear.
First, there is a degree of ambiguity as to what the above survey question is capturing. For
example, people in many countries, including Qatar, reported higher average levels of “free choice” and
“control over their lives” than the United States (see WVS, 2010-2014). Yet Qatar is ranked as being “not
free” by Freedom House.
Second, the WVS survey period from 1981 to 2007 covers the end of the Cold War in 1989-90
when, for example, the threat of East-West conflict was believed to be falling. The positive emotions and
reduced fear around this time may have led people to both tick up their happiness scores and report feeling
freer.
Third, Stevenson and Wolfers (2009) report that the subjective well-being of women in the United
States fell between 1972 and 2006, both absolutely and relatively to that of men, notwithstanding a great
expansion of women’s opportunities over this time.
In summary, the heavy use of cross-sectional data sets, limited time-series evidence, small number
of observations and widely differing proxies for freedom used across different studies, taken together, point
to a need for more work to help better identify the relationship between freedom and self-reported well-
being.
The Effect of Government Quality and Processes on Well-being
In additional to the freedom of its citizenry, the quality of other government structures may affect
the well-being of a nation. For example, Italy achieved the top score of 1 (out of 7) for its Political Rights
and Civil Liberties in 2017 from Freedom House, yet many of its institutions are perceived to be mired in
corruption.
Helliwell and Huang (2008) exploit the cross-sectional variation in life satisfaction data from 75
countries taken between 1981 and 2000 by the World Values Survey to test the relationship between the
quality of government and well-being. The quality variable is measured by an average of four indices that
measure governmental effectiveness, regulatory quality, rule of law, and control of corruption.
Their results show that increasing the overall quality of government by about one standard
deviation would have a similar effect on life satisfaction, for a typical respondent, as moving at least
halfway up the income distribution within one’s own country (measured in deciles).
The World Happiness Report (Helliwell, Layard, & Sachs, 2016) uses a larger sample of 156
countries, surveyed between 2005 and 2015, from the Gallup World Poll. The results focus mostly on
cross-sectional variation. This report finds evidence of a significant and large negative correlation between
SWB and an index of corruption. Well-being is measured by the Cantril “ladder of life” survey question
which asks respondents to rank their lives on a 0 to 10 scale, where the worst possible life is a 0 and the
best possible life is a 10.
The argument found in Frey and Stutzer (2000) that formal institutions, like referenda, may
increase well-being due to the satisfaction that comes from the process of participating, aside from the
actual outcomes that are produced, has important implications.
For example, Helliwell (2011) uses a case study of Singapore’s Prison Service reforms which he
believes exemplifies lessons from well-being research that emphasizes the positive role of processes (such
948
as engagement in a shared purpose). The reforms which he studies were begun in 1998 and emphasized the
building of connections and trust so as to combine prisoners, staff and the public in collaborative
commitments to improve the lives of all.
The outcome of these reforms appear to have been impressive, having helped contribute to a onethird
drop in recidivism, as well as improved staff morale and better social connections between prisons
and the rest of society.
More generally, Helliwell and Putnam (2004) use the World Values, US Social Capital Benchmark
and Canadian “Equality, Security and Community” surveys to study the relationship between social
networks and well-being. Marriage and family, closeness to friends, workplace ties, civic engagement, trust
and trustworthiness are independently and robustly positively correlated with an individual’s happiness and
life satisfaction.
At the macroeconomic level, Aghion, Algan, Cahuc and Shleifer (2010) find that measures of trust
are negatively correlated with the level of government regulation whereas Djankov et al. (2002) find a
positive relationship between corruption and regulation.2 Hence, the above types of findings, taken
together, suggest that countries with a smaller regulatory state and higher levels of citizen participation in
decision-making, as well as a greater degree of social connectedness and trust, may experience higher
levels of well-being.
However, work on the topic of how specific regulations affect well-being is still quite scarce,
probably due to the difficulty of obtaining comparable measures of rules, both across nations, and even
within the same country over time.
The Effect of Political Affiliation and Political Parties on Well-being
Another question relates to how an individual’s political affiliation, whether it be left-wing or rightwing,
as well as the partisan stance of the government, affects well-being. Di Tella and MacCulloch (2005)
find that the same outcomes affect people’s life satisfaction differently, depending on which party they
support, and that these differences cannot be traced back to income differences. A panel of 10 countries is
used from 1975 to 1992 to help identify the results by exploiting the time series variation in the data.
This kind of evidence favours the partisan approach to modelling business cycles: right-wingers
tend to care more about inflation and left-wingers seem to be more concerned with unemployment. In other
words, the same economic outcomes that are associated with a particular set of institutions may be
associated with different levels of well-being across individuals, depending purely on their ideological
inclination.
Respondents also declare themselves to be happier when the party in power has a similar partisan
inclination to themselves, even after controlling for key economic performance indicators such as
unemployment, inflation and income.
The effect is quite large: a right-wing person living under a Socialist Party leader, like President
Hollande of France, would have been willing to put up with an increase of 11 percentage points in the
inflation rate in order to have a Conservative Party leader, like Prime Minister Theresa May, in the United
Kingdom. This trade-off is derived by regressing a measure of well-being on a set of explanatory variables
that include how far into the ideological right is the government and also the inflation rate, where the data
are divided into two sub-samples made up of those who identify themselves as being either right-wing or
left-wing.
One interpretation is that some non-economic variables may affect the two constituencies
differently. Examples in America may be a party’s position on gun control or abortion. Another
interpretation is that voters experience happiness when the party they support is in power, regardless of its
policies, due to the personal charisma of the leader (which maybe attractive only to the party’s
constituency). Alternatively, there could be a pure “victory effect”, whereby individuals care that the party
which they support is in power (regardless of the leader or the policies which he or she enacts).
Furthermore, Pierce, Rogers and Snyder (2016) use daily data on the SWB of over 300,000 people
before and after the 2012 US election which was won by (former Democratic) President Obama. The
happiness of those individuals who identified themselves as partisan losers (i.e., Republican supporters)
dropped significantly in the days immediately after the election. The drop in their in their SWB was twice
as large as respondents living in Boston experienced in the aftermath of the Boston Marathon bombings. On
the other hand, the SWB of the partisan winners (i.e., Democrat supporters) was not affected by the
election.
Not only do economic and political outcomes affect SWB, but causality may also work in the
opposite direction. Using an unbalanced panel of 15 European Union members from 1973 to 2012, Ward
949
(2015) finds a positive correlation between voters’ SWB and their propensity to re-elect incumbent
governments. He includes a range of macroeconomic control variables, like GDP growth, inflation and
unemployment, as well as country and year fixed effects. A one standard deviation increase in SWB is
associated with an 8.5 percentage point (86% of a standard deviation) swing in the vote share enjoyed by
the governing coalition.
Liberini, Redoano and Proto (2013) also find that a drop in a person’s SWB makes them less likely
to vote in favour of the ruling party, even if the reason is an event for which the government has no
influence. They use British Household Panel Survey Data on just over 4,200 individuals who were
interviewed between 1996 and 2008.
To summarize, these findings appear to lend more support to the idea that well-being is not driven
solely by the outcomes which formal institutions generate. The success of one’s own “team”, as well as
participation in the electoral process, increase well-being, independently of the policies actually
implemented. In addition, although there are still few studies on the topic, lower SWB may lead to a desire
to change the government, regardless of its political colour.
The Effect of the Welfare State and Taxes on Well-being
In this section we study how another set of formal institutions, namely those relating to the
government expenditure and taxation system, affect well-being in nations. We focus in particular on those
programmes that enhance income security.
The Welfare State and Well-being
An increasing body of work has explored whether certain forms of welfare state institutions, like
unemployment benefits, affect well-being. For example, Richard Easterlin (2013) states that “If society’s
goal is to increase people’s feelings of well-being, economic growth in itself will not do the job. Full
employment and a generous and comprehensive social safety net do increase happiness”.
Some people argue that the unemployed voluntarily choose not to find a job since they don’t find
work attractive. If this is the case then unemployment may not be associated with much mental distress,
leading policy-makers to opt for a less generous benefit system to reduce the attractiveness of being out-of-
work.
However, a large body of evidence from ‘happiness’ studies has now shown that the unemployed
are far less happy than those that have work. Becoming unemployed has a larger negative effect than
divorce, according to many data sets. This result has led some economists to argue that governments should
bias their policies toward providing a comprehensive social safety net.
Di Tella, MacCulloch and Oswald (2003) study the effect of unemployment benefits on national
well-being, as well as on different sub-groups, like the unemployed and employed. They use a sample of
271,224 people living in 12 nations between 1975 and 1992 who were surveyed by Euro-barometer. Their
“happiness regressions” exploit the time-series variation in these data by controlling for country and year
fixed effects, as well as country specific time trends.
People are willing to forgo GDP growth rates of 2.5% to see an increase in unemployment benefits,
as a proportion of wages, equal to 3 percentage points, ceteris paribus. This trade-off is derived by
regressing a measure of well-being on a set of explanatory variables that include GDP and unemployment
benefits. The above change in benefits is equivalent to a shift from the Irish level to the French level (i.e.,
from 0.28 to 0.31). The employed and unemployed experience an increase in SWB of similar magnitude.
However, doubt still persists as to the overall impact of more generous benefits, due to the potential adverse
effects on well-being of the higher taxes and unemployment which they may cause.
More generally, a number of political scientists have focussed on the question of whether the
welfare state facilitates higher levels of well-being due to its capacity to allow people to uphold a “socially
acceptable” standard of living, independent of market participation. In this spirit, Esping-Andersen (1990)
creates a “decommodification” index, which measures the extent of “emancipation” of labour from market
dependency summarized across three domains: pensions, income maintenance for the ill or disabled, and
unemployment benefits.
Pacek and Radcliff (2008) use Euro-barometer data from 1975 to 2002 for 11 nations to test
whether the “decommodification” index is correlated with SWB. In regressions controlling for country
fixed effects, they find that decommodification is positively correlated with life satisfaction, significant at
the 5 percent level. A shift from the minimum to maximum value of the former variable is associated with
three-quarters of a standard deviation increase in SWB. These authors conclude that the “welfare state
contributes to human well-being”.
The above kinds of studies appear to build a strong case supporting a positive association between
950
a social safety net and SWB. However, Veenhoven (2000b) argues that public welfare may crowd out
private provision by friends, families and private organizations, as well as lead to a loss in individual
freedoms. Due to the positive correlations noted in the previous section of this chapter between SWB and
participation in private networks, the possibility of adverse effects due to crowding out do need to be
investigated further.
Related to these concerns, there is still much debate regarding the question of the effect of overall
government size on well-being. For example, Bjørnskov, Dreher, and Fischer (2007) correlate general
government consumption spending, as a fraction of GDP, with life satisfaction using the third and fourth
waves of the WVS, taken between 1997 and 2001, which cover 120,000 individuals in 74 countries. These
authors find that SWB is negatively related to government consumption, although they mainly exploit
cross-sectional variation by only controlling for a set of region dummies (i.e., Sub-Saharan Africa, North
Africa, Middle East, Asia, Pacific and Latin America) rather than country dummies.
In summary, whereas the evidence is supportive of a positive relationship between particular
dimensions of the welfare state, such as unemployment benefits, and well-being, the effect of aggregate
government size is subject to much disagreement. One reason for the difficulty in assessing the overall
impact of government spending on SWB is discussed in the next section.
Taxes and Well-being
The papers discussed above seek to explain well-being using measures of the generosity of
government programmes. However they do not directly consider the impact of the higher taxes needed to
fund them. Akay et al. (2012) use 26 waves of the German Socio-Economic Panel, which has surveyed
about 25,000 individuals between 1985 and 2010, to correlate life satisfaction with each person’s net
income, as well as the level of taxes they pay. Individual and year fixed effects are included in their
regressions.
Net income is significantly positively linked with SWB whereas, conditional on net income, taxes
have a positive effect. The authors interpret these findings as meaning that taxes have separate two effects
on SWB: a negative effect to the extent they subtract from gross income; and a positive effect most likely
due to the benefits that tax revenues provide by helping to fund public goods and social insurance
programmes.
One of the few papers which correlates SWB with direct measures of both government spending
and taxes at the national level is Grimes, Ormsby, Robinson and Wong (2016). They use data on 171,804
people living in 35 nations between 1981 and 2012, collected in six waves of the WVS. Taxes are divided
into two categories: “non-distortionary”, defined as indirect taxes on goods and services; and
“distortionary”, which include income taxes, social security contributions, and property taxes. They control
for country and year fixed effects, GDP per capita, inflation, unemployment, and personal characteristics.
Higher taxes are found to be associated with lower SWB, whereas the reverse is true for public
expenditures. Grimes et al (2016) main result is that non-distortionary taxes lower well-being more than
distortionary taxes. Increasing the latter by 10 percent of GDP, funded by a same sized cut in the former,
leads to a rise in SWB of 25% of a standard deviation, similar to the effect of getting married in many
‘happiness regressions’. They also find that devolving central government expenditure to a more local level
leads to higher SWB.
Another paper which attempts to distinguish between different types of tax structures is Oishi,
Schimmack and Diener (2012). Their sample is a cross-section of 54 countries from the 2007 Gallup
World Poll in which the Cantril “ladder of life” question was asked to 59,634 people. These authors find
that countries with more progressive income tax systems (i.e., where the tax rate increases more steeply as
taxable income rises) tend to have higher levels of SWB. They argue that the mechanism occurs by virtue
of a “fairer distribution of wealth” and the provision of more “quality public goods”.
Aside from taxes which are used purely to help raise revenues for the government, some taxes may
instead be used to discourage addictive forms of behaviour. These are sometimes referred to as “sin taxes”.
Gruber and Mullainathan (2005) find that higher cigarette taxes increase the SWB of smokers, on average,
compared to non-smokers, presumably by helping them give up.
In summary, research determining the impact of taxes on SWB is still in its infancy. There is
already some evidence suggesting that different kinds of taxes affect well-being differently. Few, if any
papers, have been able to successfully identify the net effect of government programmes on SWB, taking
into account the full impact of the taxes needed to finance them.
Conclusion
The aim of this chapter is to describe how formal institutions, like the political system in a country,
951
as well as the rules surrounding the welfare state and taxes, affect well-being. There are many studies
suggesting that more freedom, as well as government structures which encourage civic engagement,
participation and trust, have positive effects. However since freedom-related variables have typically been
measured at the national level and often vary only slowly over time, further work is needed to test
robustness.
One theme of this research agenda is that processes may matter at least as much as outcomes. For
example, people appear to experience higher levels of well-being from the act of participation in a
referendum, regardless of the policies that actually get implemented. Similarly, the evidence points to
political competition being somewhat like a team sport in which one gets pleasure from supporting the
winning side. In other words, there appears to be a pure “victory effect”, whereby individuals care that
“their” party is the one holding power, regardless of the policies which are enacted.
A growing body of research using country level panel data also supports the view that a
comprehensive social safety net is associated with higher levels of well-being for all workers, both
employed and unemployed. However, doubt still persists as to the overall impact of a generous welfare
state, due to the extent to which well-being may be adversely affected by the higher taxes needed to support
it.
Topics regarding the impact of (slow-moving) formal institutions on well-being opens up the
question of the advantages, but also the limitations, of using happiness data to help evaluate public policies.
First, there is uncertainty about the time horizon used by people in framing their survey responses. Second,
since people may adapt over time, there is doubt as to the short-run versus the long-run effect of
institutions on well-being. Third, there is still much disagreement as to whether a person’s well-being can
even be summarized by a single number or whether there are different dimensions of well-being that cannot
be aggregated.
Footnotes
1Examples of survey questions that have been used to measure self-reported well-being and which will be
referred to in this chapter include the “happiness” question, which asks, “Taking all things together, would
you say you are: very happy; quite happy; not very happy; not at all happy?”, and the “life satisfaction”
question, which asks, “How satisfied are you with your life as a whole these days?”, with responses ranging
from “completely dissatisfied” to “completely satisfied”. Another example is the “ladder of life” question
which asks “Please imagine a ladder with steps numbered from zero at the bottom to 10 at the top. The top
of the ladder represents the best possible life for you and the bottom of the ladder represents the worst
possible life for you. On which step of the ladder would you say you personally feel you stand at this
time?”
2Aghion et al (2010) use a measure of trust from the World Values Surveys, collected between 1981 and
2003, which they correlate with the level of regulation (measured by the number of steps that an
entrepreneur must complete to open a business legally) across 57 countries. Respondents in the WVS were
asked, “Generally speaking, would you say that most people can be trusted, or that you can’t be too
careful in dealing with people? What would it be today?” and also “To what extent do you trust the
following institutions: government, banks, foreign companies?”
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Subjective Well-Being and Public Policy
By Reto Odermatt and Alois Stutzer, University of Basel
Citation
Odermatt, R., & Stutzer, A. (2018). Subjective well-being and public policy. In E. Diener, S. Oishi, & L.
Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers. DOI:nobascholar.com
Abstract
Measures of subjective well-being have gained substantial attention in economics as quantitative
approximations of individual welfare. They allow researchers to study relevant determinants of welfare on
an individual as well as on a societal level. These determinants might not to be easily detectable in
observable behavior. By referring to the recent well-being literature, we provide a selection of determinants
of well-being that are important for public policy and show how the analysis of subjective well-being is
applied as a complementary analytical tool for policy evaluation. We highlight the use of these measures
for guiding public policy in areas that might involve suboptimal behavior. We also discuss some challenges
for future research that are associated with the choice of evaluation metrics, the role of aspiration and
adaption in evaluations, and utility misprediction.
Keywords: Subjective Well-Being, Determinants of Welfare, Policy Evaluation, Bounded Rationality
It is self-evident that public policy should be oriented towards the well-being of the people. It is
similarly evident that views differ regarding what well-being means and what contributes to well-being.
Moreover, we see that public policy is used (but also abused) to affect the allocation and redistribution of
resources and thus well-being. In order to gain a better understanding of such normative and positive issues
regarding the relationship between public policy and subjective well-being, several questions need to be
addressed. First, there is the question of what well-being is. In an empirical context, survey research has
derived several measures of subjective well-being that capture facets of what people consider a good life.
Second, there is the question about the determinants of well-being. Third, we would like to know how these
measures of subjective well-being can be analyzed to learn about the welfare consequences of alternative
policy arrangements. From a constitutional perspective, we would like to understand what basic rules can
be implemented to secure well-being‑enhancing public policies and, thereby, create environments that make
people better off.1
In this chapter, we provide an overview of some recent reactions to these questions and illustrate how
insights from research on subjective well-being can provide guidance for a well-being evidence-based
public policy.2 Studying covariates of subjective well-being helps us to understand the critical determinants
of individual welfare, which involve both tangible and non-tangible (psychological) aspects. Based on
measures of subjective well-being, it is possible to uncover welfare consequences that are partly
unobservable when using traditional measures of economic and social progress such as national income.
However, even with a better understanding of the determinants of well-being, an institutional perspective
on public policy reminds us that it is not possible to simply trade-off the different contributors to wellbeing.
Instead, we advocate that subjective well-being measures should be applied in comparative analyses
in order to learn about the consequences of alternative institutional and policy arrangements.
In particular, we see two major benefits of well-being research for policy evaluation. First, it facilitates
evaluations which analyze numerous, potentially countervailing effects of policies, thus allowing the
researcher to study their net effects on individual welfare. Well-being research thus helps to identify
institutions that enable individuals to better meet their preferences. Furthermore, it offers a promising
alternative method (often called Life Satisfaction Approach) for directly evaluating the benefits provided
by public goods. Second, subjective well-being research provides an alternative approach for policy
evaluation in areas that might involve suboptimal behavior. With regard to the insight commonly applied in
behavioral economics (and also a popular adage) that people do not always behave in their own best
interest, we emphasize the need to weaken the assumption of consumer sovereignty in rational choice
analyses and the strong (or exclusive) reliance on observed behavior as a welfare criterion. If some
behavioral choices are suboptimal from an individual’s perspective, research can then seek to identify the
conditions under which such choices are less likely. Data on subjective well-being can provide a valuable
input for the discourse and people’s limitations in pursuing their ideas of the good life. This empirical
research on subjective well-being provides a tool for policy evaluation in areas where decision utility (as
reflected in behavior) systematically diverges from experienced utility.
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There are, of course, many open issues and challenges to the use of subjective well-being for public
policy. First, the well-being approach involves the choice of a concrete evaluation metric: the metric that is
used to elicit people’s judgments. Depending on the applied measure, different (policy) conclusions might
be inferred. Second, hedonic adaptation and the aspiration treadmill have potentially great consequences
for the assessment of the nexus between public policy and individual well-being. And third, studies in the
field of economics and psychology suggest that people systematically mispredict the utility they derive
from some circumstances in the future. This might lead to suboptimal decisions. However, up to now it is
rather difficult to derive policy implications from the results in the literature.
The remainder of this chapter is organized as follows. In section 2, we start with the measurement of
individual well-being for public policy and provide some examples of policy‑relevant covariates of
subjective well-being. Section 3 discusses different aspects and examples of policy evaluations based on
subjective well-being data, including the life satisfaction approach to value public goods. A separate
section 4 addresses the potential of individual ex post welfare judgements for policy evaluations in areas
that might involve suboptimal behavior. In section 5, we take up three challenges for well-being evidencebased
public policy. Section 6 offers concluding remarks based on a constitutional perspective.
Policy‑Relevant Determinants of Subjective Well-Being
Subjective Well-Being as a Complementary Welfare Measure
Over the past two decades, economists have rediscovered their interest in the concept of utility as a
measurable quantity, as it had been abandoned with the ordinal revolution in economics on the basis of
general skepticism regarding subjective measures. The same holds for most other social sciences, but not
for psychology where already in 1999 Diener, Suh, Lucas, and Smith reviewed “three decades of progress”
after a first review of the topic by Wilson in 1967. In this recent counter-movement of “happiness research”
(as termed colloquially), data on subjective well-being is used as an empirical approximation of utility and
individual welfare.3 This approach bases judgements of individual welfare on people’s self-evaluations of
the quality of their lives rather than on a decision utility that is inferred from observed choices (Kahneman,
Wakker, & Sarin, 1997). In contrast to the traditional choice-based approach, the experience or surveybased
approach explicitly adopts and makes reference to (unobservable) psychological content, such as a
person’s beliefs, desires, or emotional states (e.g., Hands, 2009). It can therefore be argued that the
experience or survey-based concept of utility captured by measures of subjective well-being is broader and
more accurate and appropriate in identifying what people care about.
Subjective well-being can also serve as a welfare indicator from an aggregated perspective. It has
various advantages over traditional measures of economic activity which reflect only the monetary value of
goods and services trades in formal markets. Subjective well-being goes beyond measuring market
transactions by incorporating non-material aspects, such as the welfare derived from social relationships,
the experience of autonomy and competence, the absence of insecurity, or grievance derived from
perceived inequality. Moreover, measures of happiness consider outcome aspects of components already
included in the gross national product (GNP) via input measures. This holds, in particular, for the vast area
of government activity (measured in GNP by the cost of material and labor). The statistics based on these
subjective well-being measures are generally used to complement the traditional measures of aggregated
welfare, such as GNP per capita.4
In sum, subjective well-being may serve as an alternative welfare indicator which allows the researcher
to directly study relevant determinants of welfare both on an individual and on a societal level. The
identification of the determinants of individual well-being can then provide some guidance when
considering basic rules and defining the relevant space for public policy. By referring to the recent wellbeing
literature, we highlight in the following examples for determinants of subjective well-being that
matter for public policy.
Examples of Policy‑Relevant Covariates of Subjective Well-Being
Unemployment and inflation. The view that considered unemployment to be a social bad changed
with the advent of the new classical macroeconomics perspective in which all unemployment is considered
to be voluntary. According to this view, the important reasons why people decide not to work are that
unemployment benefits are too attractive relative to the salaries achieved on the market, or simply that the
going market rate is below the reservation wage. However, the results of subjective well-being research
show that the scope of this position is too narrow.
First, unemployment reduces the individual well-being of those personally affected, even if the lower
income available to them is statistically taken into account. For example, Kassenboehmer and HaiskenDeNew
(2009) find that entering unemployment has a negative causal effect on life satisfaction. They
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identify this effect by studying a sample of people in Germany who experience an exogenous transition
into unemployment due to plant closure. Based on their findings, they conclude that the non-pecuniary
costs of unemployment are dramatic, particularly for women during their first year in unemployment.
Second, unemployment reduces the subjective well-being not only of the individuals who are actually
unemployed, but also of those who currently work. Luechinger, Meier, and Stutzer (2010), for example,
find that an increase in regional unemployment substantially reduces the reported life satisfaction of the
people who currently work. However, with regard to people who work in the public sector and who usually
enjoy extended protection from dismissal, the negative effect is about a third lower than for private sector
employees. The results suggest that general unemployment is accompanied by increased economic
insecurity and that this is an important component of the psychological costs of general unemployment.
Besides unemployment, inflation is another economic variable that affects individual welfare and has
strong policy implications. A one percentage point increase in inflation is often considered to result in the
same welfare loss as a one percentage point increase in the rate of unemployment (this view is reflected,
for example, in the so-called misery index). However, research has shown that the negative well-being
effects of inflation seem to be relatively less severe than those from unemployment (Di Tella &
MacCulloch, 2006). The size of this relation varies between studies, though. Using data for 12 European
countries over the period from 1975 to 1991, Di Tella, MacCulloch, and Oswald (2001) report that people
would trade off a 1 percentage point increase in the rate of unemployment for a 1.7- percentage point
increase in the rate of inflation. With data for a longer time period from 1975 to 2013 and for a larger set of
EU member countries, Blanchflower, Bell, Montagnoli, and Moro (2014) find the same direction of
relationship. However, their estimates imply that unemployment has a much stronger negative impact.
They report that a one percentage point increase in the rate of unemployment lowers well-being more than
five times as much as a one percentage point increase in the rate of inflation.
Income and income inequality. People obviously care about their income, but they also care about
others’ incomes, as well as income inequality within a society. Based on a repeated cross-section of
Americans over a 37-year period, Oishi, Kesebir, and Diener (2011) find a direct negative effect of income
inequality on happiness. Americans were, on average, happier in years when relative national income was
comparatively more equally distributed than in years when it was less equally distributed. They further find
that this relationship cannot be explained by lower household income, but that it is moderated by
psychological factors, i.e., a decrease of perceived fairness and trust.
Schwarze and Härpfer (2007) present evidence for Germany that people of all income classes report
lower life satisfaction when regional income inequality increases. This may be due to inequality aversion
and/or empathy for the poor. Similarly, if economic shocks increase unemployment, people may care about
the fate of the people who experience unemployment, reducing their own sense of well-being (over and
above the effect of the increase in economic insecurity discussed above).
Another explanation for the negative impact of income inequality is the importance of relative position
or status as a determinant of people’s well-being. The empirical well-being literature documents that an
individual’s well-being level is reduced when the average income of other individuals increases.5 For
example, Stutzer (2004) studies residential communities and finds that the average income level in the
community of residence is significantly positively related to people’s income aspirations and negatively
correlated with people’s life satisfaction. Luttmer (2005) reports a negative correlation between selfreported
happiness (and other indicators of well-being) and income in the neighborhood. Dynan and Ravina
(2007) confirm the general finding that beside the positive effect of an absolute income increase, there is a
positive relationship between people’s income positions relative to that of their neighbors and self-reported
happiness. In their study for the United States, they further show that this relationship is stronger for
individuals who have above-average incomes. This finding highlights the fact that an income-based
analysis of the evolution of aggregate welfare in a society might be insufficient.
Further aspects. Beside these prominent economic determinants of subjective well-being, recent
literature has identified a broad range of other relevant aspects that are directly or indirectly linked to public
policy. This includes aspects such as social capital and quality of social relationships, religious faith,
exposure to crime, and access to technology, as well as, of course, health and health care. Picking out an
example, van den Berg, Fiebig, and Hall (2014) provide evidence for a relationship between caregiving
and self-reported life satisfaction. Based on Australian panel data, they find that weekly informal care time
is associated with reduced life satisfaction for the care-giving person. As the authors argue, this finding is
important given that the development of sustainable long-term care systems is one of the main challenges
for public policy in high-income countries.
Subjective Well-Being for Policy Evaluation
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Inherent Risk of Premature Policy Proposals
If research provides information about outcomes linked to individual well-being, it is tempting to
suggest policy interventions that strengthen positive outcomes and diminish negative ones, by trading them
off to obtain an optimal policy mix that maximizes some empirical indicator of subjective well-being.
Unemployment may be a case in point. One might propose that to improve the lot of the unemployed,
transfers should be increased, and to reduce the economic insecurity of the employed during a crisis,
employment protection should be extended. However, such conclusions might be premature. Regarding the
first aspect, the personal psychological costs of unemployment due to a strong social work norm might be
functionally or even necessary in order to maintain a generous and financially sustainable social benefit
system. These costs help to limit moral hazard; namely, that citizens search less intently for re-employment
when receiving higher unemployment benefits. With regard to the aggregate level, increased job protection
might benefit those who already have a job (see, for example, Clark & Postel-Vinay, 2009). However, it is
also likely to make employers more reluctant to hire new workers, which is detrimental for the job
prospects for those who are unemployed. Thus stronger labor protection rights might lead to longer
individual unemployment spells and to higher general unemployment.
These classic arguments highlight the importance of equilibrium effects and potential (unintended) side
effects when thinking about policy interventions. In our opinion, these considerations highlight the
limitations of an approach that focuses on an optimal outcome mix. Instead, we recommend an approach
that uses a constitutional perspective which derives policy proposals by referring to basic institutions and
rules (see also Frey & Stutzer, 2012). This shift in perspective has implications for empirical research on
subjective well-being, because the focus is then on the evaluation of institutions. Regarding the important
social issue of unemployment, analyses then attempt to evaluate the consequences of labor market
institutions and the system of social insurance on the subjective well-being of all the people, irrespective of
whether they have the status of employed, unemployed or not in the labor force.
In the following, we try to elucidate these considerations and present examples of how well-being
research can be applied to evaluate policy rules and to assess outcomes for policy decisions.
Examples of Policy Evaluation Based on Subjective Well-Being
Labor market regulations. So far, little is known about the institutions that reduce the vulnerability
to shocks on the labor market measured by individual well-being. In a longitudinal sample of the European
Union, more generous unemployment benefits are found to correlate positively with subjective well-being
in the general population (Di Tella, MacCulloch, & Oswald, 2003). Based on the same data from the
Eurobarometer, the negative effects of individual and general unemployment on reported life satisfaction
are found to be larger in countries with lower job protection (Becchetti, Castriota, & Giuntella, 2010).
In a recent analysis for the United States, Aghion, Akcigit, Deaton, and Roulet (2016) analyze the link
between structural change and people’s subjective well-being measured based on Cantril’s ladder of life.
They focus on the moderating effect of a more or less generous unemployment insurance in terms of the
maximum weekly benefit amount. Structural change is captured at the level of the metropolitan statistical
area in terms of the rate of job creation as well as job destruction. They find that a higher job turnover rate
(i.e., the sum of the job creation and the job destruction rate) has a more positive effect on reported wellbeing
in states which have more generous unemployment insurances. This result is due to a much smaller
negative effect of job destruction on well-being: They write: “[A] one standard deviation increase in our
measure of UI generosity reduces the negative effect of the job destruction rate by 33 percent” (p. 3891).
Based on panel data for Germany from 1992 to 2004, Crost (2016) studies whether workfare
programs, as a key part of the active labor market policy in Germany, reduce the negative effect of
unemployment on subjective well-being. The analysis indicates that workfare employment offsets part of
the negative effect of unemployment on individual life satisfaction, at least in the short run. Based on a day
reconstruction survey among 1,080 participants in workfare schemes in Germany, Knabe, Schöb, and
Weimann (2017) draw the same conclusion. They find that the life satisfaction of people in workfare
employment is between that of employed and unemployed people and that their emotional well-being is
even the highest of these three groups. They argue that identity utility might account for part of the effect.
In environments with strong social work norms, unemployed people suffer more from their lot (Stutzer &
Lalive, 2004). So even workfare employment is able to restore some of the loss in identity from work. Of
course, many further applications are possible with regard to different labor market regulations (see, e.g.,
Alesina, Glaeser, & Sacerdote, 2005, on the regulation of working hours, Dräger, 2015, on employment
protection, and Charles, 2004, on the effect of mandatory retirement).
Taxation. Research on subjective well-being has produced different insights which have the potential
to inspire our views about taxation (see Weisbach, 2008, for an overview). However, the direct effect of
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taxation on well-being is difficult to identify, and there are only a small number of studies which consider
the well-being consequences of particular tax schemes. One example is the study by Oishi, Schimmack, and
Diener (2012) that finds a positive statistical association between a more progressive taxation regime and
subjective well-being in a cross-section of 54 countries, controlling for national income and income
inequality. An additional analysis suggests that this effect is mediated by citizens’ satisfaction with public
goods such as education and public transportation. Alpaslan et al. (2012) exploit exogenous variation in tax
rules over time and across demographic groups in Germany and find a positive tax effect on subjective
well-being. Importantly, this effect is measured conditional on net income. While they cannot identify the
relevant mechanism, they consider a better provision of public goods or more redistribution and insurance
through the social security system as potential channels through which higher taxes may promote citizens’
satisfaction levels.
Some insights from well-being research have been related to proposals for optimal taxation (see Frank,
2003, Layard, 2006, or Mujcic & Frijters, 2015). These studies refer to the importance of status or relative
position as determinants of people’s well-being. Individuals do not value simply the absolute level of their
income, but compare themselves with people who have higher incomes (see also section 2.2). From this
insight, it is inferred that the rise in one person’s income or status creates a positional externality if it
affects the utility of other people. For example, someone owning a fancy sports car imposes a negative
external effect on all other people who do not own such a good, but are motivated to strive for it.6 If
people pursue status competition by working and spending more money in order to gain an equal or a
higher social position relative to their peers, this strategy leads to a zero-sum or even a negative-sum
game. The tax proposal should aim to mitigate this effect by heavily taxing high-income earners (or
specifically the consumption of status/luxury goods).
However, the greater the induced distorting effects of taxation are (for example, tax evasion promoted
by tolerance towards shadow economies), the less successful taxation interventions are likely to be from a
welfare perspective (see also Weisbach, 2008). Even if the taxation of income and consumption were
successful in undoing the negative status externalities from income comparisons, status competition might
persist via other channels, because people have a natural urge to distinguish themselves from others.7 The
crucial question is whether the positional externalities in these other dimensions are weaker or stronger (see,
e.g., Clark, 2016, on social comparisons in different life domains).
While we are beginning to understand positional externalities as a phenomenon, we think that it is
premature to draw policy conclusions in terms of optimal income or consumption taxes. Instead, we should
engage in the complementary comparative institutional analyses of different governance structures
(capturing the revenue-generating side as well as the expenditure side) in terms of their effects on the
subjective well-being of different groups in society.
Public or non-tangible goods. In the current politico-economic process, government agencies
undertake some of their decisions based on cost benefit analyses (CBAs). CBAs are a corner stone of the
welfare economic approach to public policy. However, the benefits from public goods are difficult to
measure in monetary terms, as the marginal utility to consumers is not reflected in market exchanges.
Inspired by well-being research, a promising method used to quantify the costs and benefits of public goods
has been proposed, often called the “Life Satisfaction Approach” (see Frey, Luechinger, & Stutzer, 2010).
Taking reported subjective well-being as a proxy measure for individual welfare, it is possible to directly
evaluate the utility provided by public goods. The marginal utility of public goods (or the disutility of
public bads) is captured by correlating the amount of public goods (or public bads) by means of
individuals’ reported subjective well-being, controlling for many other determinants on happiness. By
comparing the marginal utilities of public goods to the marginal utility of income, the trade-off between
income and public goods can be calculated.
The Life Satisfaction Approach avoids some major difficulties of both the stated preference and the
revealed preference approaches.8 With the Life Satisfaction Approach, it suffices if respondents indicate
their own life satisfaction. As the collection of survey data on subjective well-being is not linked to a
specific policy goal, there is little reason to expect strategic answers.9
The Life Satisfaction Approach has, among other applications, been used to value airport noise
nuisance (van Praag & Baarsma, 2005), air pollution (Welsch, 2006; Luechinger, 2009; Levinson, 2012),
crime (Manning, Fleming, & Ambrey, 2016), flood hazards (Luechinger & Raschky, 2009), terrorism
(Frey, Luechinger, & Stutzer, 2009), or wind turbines (Krekel & Zerrahn, 2017).
Recent studies have reached a high standard of quality, and the preconditions for its application are
continually being refined and formulated. What so far was an academically driven development of a new
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method may soon become an empirical tool that meets the demands of the political process.
Policy Evaluation in Areas That Might
Involve Suboptimal Behavior
Considering Limited Willpower
From a behavioral economic perspective, policy evaluations need to consider the insight that people
are not always able to behave in a manner that serves their own best interests.10 This questions the standard
economic view that people are fully able to behave in a time-consistent manner and to commit to their
long-term consumption plans. In contrast to this view, the behavioral economics perspective allows for the
possibility that people might consume certain goods in excess of their (long-term) preferences due to
limited self-control (see, e.g., O’Donoghue & Rabin, 1999; or Ameriks, Caplin, Leahy, & Tyler, 2007). In
cases where suboptimal behavior occurs, the application of a choice-based concept of welfare is
insufficient for public policy evaluation, because it assumes that whatever people choose makes them, in
their expectation, best off (see, e.g., Bernheim & Rangel, 2007; or Loewenstein & Ubel, 2008). However,
the standard economic perspective that focuses on people's behavior as the benchmark for welfare analysis
can be complemented with data on subjective well-being. The latter offers an indicator for public policy
evaluations, particularly in areas that might involve suboptimal consumption choices resulting from, for
example, limited willpower.
With regard to the respective policy consequences, suboptimal consumption patterns due to limited
willpower are no cause for immediate government intervention. For instance, people who suffer from
limited self-control might search for commitment devices that help them to pursue their optimal
consumption path. Policies might then aim to offer individuals who are subject to self-control problems
ways of overcoming their weaknesses by proposing self-binding mechanisms (for a broader discussion see,
e.g., O'Donoghue & Rabin, 2006a).
A widely discussed policy intervention is the imposition of excise taxes on the consumption of goods
that people tend to overconsume. If such taxes support self-control, they might make consumers with
limited willpower better off. The regulation of risky health behavior such as smoking offers an excellent
example. Analogous to negative externalities, consumers with self-control problems suffer from a negative
internality, which could contribute substantially to the welfare costs of addiction (see, e.g., Jürges, 2004).11
In reference to excise taxes on tobacco products, O’Donoghue and Rabin (2003, 2006b) investigate
negative internalities and argue that “sin taxes” can be imposed in cases where people exhibit an overconsumption
of unhealthy goods. However, the degree to which such internalities (over and above
externalities) serve as a rationale for additional policy interventions is the topic of a lively controversy (see,
e.g., Sugden, 2008; Frey & Gallus, 2016; or Schnellenbach & Schubert, 2015).
Evaluation of Tobacco Control Policies as an Example
Tobacco control policies such as cigarette taxes or smoking bans are controversially discussed, as they
have a multitude of consequences that affect people’s health and welfare in various ways, sometimes with
a counteractive effect. In general, tobacco control policies aim at internalizing the social costs of smoking
by protecting people from second-hand smoke, as well as at lowering costs for publicly funded health care
by making smoking less attractive. A successful tobacco control policy should therefore lead to positive
net-welfare effects, overall. Smokers, are nevertheless predicted to be worse off, as the policies restrict their
behavior. However, if tobacco consumption involves time-inconsistent behavior, tobacco control policies
might also have a positive impact on the individual well-being of smokers, because they can serve as a
self-control device. Therefore, different predictions for the welfare consequences of anti-smoking policies
emerge, depending on the assumed time consistency in smokers' consumption behavior. However, all the
tobacco control policies are expected to make smoking less attractive and to reduce the prevalence of
smoking among people who have full self-control and those who have limited self-control. This makes it
difficult to assess the various welfare consequences of such policies when the evaluation is based on
observed consumption behavior.
To address these challenges, Odermatt and Stutzer (2015a) analyze the welfare consequences of
smoking bans and cigarette prices based on data on reported satisfaction with life. They use data from 40
countries and regions between 1990 and 2011 and exploit the staggered introduction of smoking bans and
the respective progressively increasing cigarette prices across Europe. They simultaneously analyze the netwelfare
effects of smoking bans and cigarette prices and differentiate between the effects not only for
likely smokers and non-smokers, but also for smokers who failed to stop smoking. The latter group
potentially captures people with limited self-control. Their estimates do not reveal any statistically
significant systematic changes in people's life satisfaction levels as a result of implemented smoking bans,
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on average. For cigarette prices, they show a negative partial correlation with life satisfaction. This latter
correlation is driven by a quantitatively relevant negative effect of higher prices on smokers. Furthermore,
the results indicate that for likely smokers who failed an attempt to quit smoking, smoking bans are
beneficial in terms of life satisfaction, while higher cigarette prices are not.12 The results show that the
capacity of cigarette taxes to serve as a self-control device might be limited, while the implementation of
smoking bans, in contrast, might help smokers to overcome their self-control problems. This is consistent
with models that emphasize temptation as being a driver of time-inconsistent behavior. According to these
models, cues trigger a temptation to smoke, leading smokers to overconsume the addictive good if they are
unable to resist it by exerting their willpower. The insights that some smokers show time-inconsistent
behavior and thus benefit from commitment devices that help them to align their actual consumption with
their desired long-term consumption-path are of relevance from a welfare perspective and can provide an
input for public policy with potential implications for any good that is subject to the risk of
overconsumption.
Challenges for Well-Being Evidence-Based Public Policy
Measurement
Many measures of subjective well-being have been analyzed in studies related to public policy. There
is no consensus on which measure is best (see Diener, 2006; Helliwell, 2006; Kahneman & Riis, 2005;
Dolan & Metcalfe, 2012). This is probably for good reason, as the researcher’s choice of the concept to be
used should depend on the specific study’s objective and research question. We briefly discuss three
aspects that might be considered.
First, the well-being approach obviously involves the choice of a concrete evaluation metric that is
used to elicit people’s judgments. For a measure of reported subjective well-being to serve as a good proxy
for individual welfare, one property seems particularly relevant. The evaluation metric should fit people's
self-evaluations of their quality of life. Second, in order for changes over time in reported subjective wellbeing
to have an informative value, individuals must be assumed to have stable evaluation standards. If this
assumption is violated, any observed changes in reported well-being scores might not be driven by true
changes in well-being, but instead potentially result from scale changes.13 One psychological mechanism is
that individuals do not rate their own situation in reference to an absolute standard, but in reference to a
relative standard, and that this relative standard might change over time (e.g., Kievit et al., 2010). However,
it is still a partly unresolved issue whether the change in the relative standard is associated with a real
change in the hedonic experience, i.e., true hedonic adaptation, or only with a change in the description of
the same hedonic experience, i.e., scale norming. Third, when using self-reported measures of well-being it
is assumed that people's reporting of their well-being does not systematically deviate from their actual
assessment. An obvious violation would be if people would have an incentive to systematically lie or to
actively manipulate their answers. A more subtle potential violation which is discussed in the literature is
distorted response behavior, which is due to context effects such as social desirability, i.e., the tendency of
subjects to attribute characteristics to themselves which are socially desirable (Edwards, 1957).14 It is thus
important that researchers are aware of potential design and context effects in their satisfaction data.
Adaptation and Aspirations
A central finding in happiness research is that many changes in life circumstances have only shortlived
effects on reported subjective well-being. While it seems self-evident that people’s well-being
changes in most instances when circumstances change, it is less clear to what extent such changes persist
when the new conditions stabilize.15 Overall, evidence suggests that there is adaptation to changes in
circumstances, for example due to major life events. This adaptation, however, differs across events and is
far from complete for some of them (for a discussion of the claim that changes in well-being are only
temporary, see Powdthavee & Stutzer, 2014, and the other chapters in Sheldon & Lucas, 2014).
The second, closely related phenomenon is the change in people’s aspirations due to changes in their
life circumstances. One exemplary finding is that people adjust to income increases by increasing their
material aspirations in that their new levels of income are considered “necessary” for them to make ends
meet (Stutzer, 2004; Di Tella, Haisken-De New, & MacCulloch, 2010). This process has become known as
the aspiration treadmill. Hedonic adaptation and the aspiration treadmill have important consequences for
the assessment of individual welfare depending on the degree to which they are considered.
One example of their relevance is the case where courts have to decide about compensation for losses
suffered in car accidents. For the same physical harm, should they award lower damages to people with a
strong capacity to adapt and higher damages to others? Or related to government taxation, should
materialists with high income aspirations who suffer a great deal from personal income taxes face lower tax
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rates than people who can easily adapt to whatever material living standard they are confronted with?
Moreover, if people’s aspirations or capacities to adapt were taken into account in policy-making, one
would have to deal with the incentives that these individualized criteria create; for example, when a person
claims to adapt slowly in order to obtain a higher compensation or claims to have high aspirations in order
to be taxed less heavily. People would be induced to “play the system” instead of revealing their true state
of subjective well-being. As a consequence, it is difficult, if not impossible, to determine an individually
optimized compensation that is considered fair by the persons involved.
An acceptable rule can possibly be found at the constitutional level behind the veil of uncertainty in
which nobody knows whether he or she will be the victim of an accident or whether he or she is a quick or
slow adaptor. This holds more generally – how adaptation and aspiration effects have to be dealt with in
public policy cannot be answered based on some well-being calculus, but requires to be dealt with in a
process of collective decision-making.
Utility Misprediction
The conception of individuals who engage optimally in forward-looking utility maximizing behavior is
part of the basis of the rational choice approach to human behavior, which is prevalent in economics as
well as other social sciences. Studies at the intersection of economics and psychology, however, suggest
that people for some circumstances systematically diverge from this view and do not accurately predict the
utility they derive from alternative conditions (see e.g., Loewenstein, O’Donoghue, & Rabin, 2003;
Kahneman & Thaler, 2006; and Frey & Stutzer, 2014). Odermatt and Stutzer (2015b) show that this also
applies after major changes in life circumstances due to widowhood, unemployment, marriage, or disability.
People tend to underestimate the degree to which the impact of the event on their life satisfaction declines
over time.
The finding that people, on average, do not accurately predict their subjective well-being has profound
implications for the modeling of human behavior. While it is in itself questionable whether observed
adaptation can be explained from a standard rational choice perspective in which stable preferences are
assumed, the finding of a systematic underestimation of adaptation is not compatible with the paradigm of
rational expectations, a cornerstone of expected utility theory. From a welfare perspective, mispredicted
subjective well-being is relevant for choice formation, where the choice relies on predicted subjective wellbeing.
Mispredicted subjective well-being could result in the misallocation of a person's resources, resulting
in a lower level of individual welfare than would be achieved with unbiased decisions.16
However, from the results in the literature so far, it is difficult to derive direct policy implications. A
better understanding is required on an individual level in order to provide a basis for advancing our
understanding of the welfare consequences of misprediction on a societal level. This could, for example,
comprise an investigation of the extent to which people’s misprediction is carried forward through the
political process with potentially biased outcomes on an aggregated level, such as a suboptimal amount of
public good provision (see Frey & Stutzer, 2006, for a discussion). Nevertheless, studies based on
subjective well-being can provide a source of information for people to improve their choices, both as
private individuals and participants in processes of collective decision-making.17 For example, people
equipped with such insights derived from research might decide to overcome behaviors which reduce their
well-being by resorting to collective arrangements. They might, for instance, turn to self-binding
mechanisms such as government-mandated maximum working hours and weeks of vacation. In this way,
well-being research can also contribute to (constitutional) public policy that is aimed at people who are only
boundedly rational.
Concluding Remarks
The analysis of people’s subjective well-being offers great opportunities for public policy. In this
chapter, we have emphasized the evaluation of particular policies as well as the valuation of public goods
based on well-being data as promising applications of well-being evidence‑based public policy. Based on
people’s (ex post) judgments of their well-being, it is particularly attractive to evaluate policies in areas of
life in which people might be boundedly rational. In these areas, observed behavior is potentially a poor
guide to learn about the effects of policies on individuals’ welfare.
The “new” approach in the study of public policy should – in our opinion – not be understood as a new
paradigm of public policy, though. Insights from this new science are, instead, a complementary – and
most valuable – source of evidence for the existing democratic process of political decision-making. While
it is tempting to adopt a social welfare maximization approach, this new science does not overcome the
criticism against it: It is faulted for disregarding citizens as ultimate decision-makers, and for seeing
governments as benevolent maximizers of social welfare, which it captures in terms of measured subjective
well-being. It neglects the fact that people differ in their evaluation about what measures they consider to
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reflect their normative preferences. Moreover, the role that the processes of adaptation and aspiration
should play in policy decisions has to be clarified. Finally, the social welfare maximization approach based
on subjective well-being neglects the negative incentives for manipulating empirical welfare measures.
Empirical well-being research is, however, well equipped to contribute to a constitutional perspective
of public policy by seeking basic rules that are conducive to the pursuit of individual well-being (Frey &
Stutzer, 2012). In this paradigm, the fundamental rules and institutions are set at the constitutional level
behind the veil of uncertainty. They determine the decisions taken in the current politico-economic process.
The legitimacy of political action finally rests on the voluntary agreements on these fundamental rules by
the citizens involved. In particular, the sovereignty of the individual includes the individual’s choice on
how to best pursue his or her personal well-being. This holds both for the private as well as the collective
realm.
Accordingly, the political process should be institutionally structured so that people’s interests become
the principal controlling force in politics. Fundamental institutions, or rules of the game, have to be
established which provide politicians and public bureaucrats with incentives and information to adequately
respond to people’s preferences. Well-being research provides insights about how and to what extent
institutions have systematic effects on indicators of subjective well-being. The focus is on rules and
institutions which include written constitutional rules, state laws, social norms, traditions and even selfbinding
mechanisms (for references to the respective literature see Frey & Stutzer, 2017).
According to this constitutional view, the results gained from well-being research will provide
productive inputs for the political decision-making process. These inputs then have to prove themselves in
political competition and in public and political debates. An ideal outcome is envisaged, where the
integration of this research in the political process will enable people to actively promote and realize their
idea of the good life, both individually and collectively.
Footnotes
1There is an enormous body of literature that is concerned with understanding subjective well-being. In
economics, there are a series of monographs including, e.g., Frey and Stutzer (2002a), Layard (2005), Frey
(2008), and Graham (2011), as well as review articles including, e.g., Frey and Stutzer (2002b), Dolan,
Peasgood, and White (2008), or Stutzer and Frey (2010). For articles from a psychological perspective,
see, e.g., Diener and Biswas-Diener (2008), or the collections in David, Boniwell, and Conley Ayers
(2013), or Sheldon and Lucas (2014). Good overviews about cross-country comparisons of well-being are
provided in the five World Happiness Reports published so far (Helliwell, Layard, & Sachs, 2017).
2Other sources that discuss many issues related to public policy and subjective well-being are Diener,
Lucas, Schimmack, and Helliwell (2009), Hämäläinen and Michaelson (2014), or the report of the
Legatum Institute (O’Donnell, Deaton, Durand, Halpern, & Layard, 2014). In this chapter, we draw on
previous work by Stutzer (2009), and Frey and Stutzer (2010, 2012, 2016, 2017) and develop it further.
3Subjective well-being is an umbrella term for different measures proposed in the literature, ranging from
affective measures such as experience of fear, happiness, joy, or sorrow to evaluative measures such as life
satisfaction or purpose in life. For a definition and description of different indicators, see, e.g., Kahneman
and Krueger (2006), Diener, Inglehart, and Tay (2013), Tay, Chan, and Diener (2014). For a recent
empirical comparison of different measures see, e.g., Clark (2015).
4The discussion and development of aggregate measures of personal well-being has recently been
promoted in many countries; for example, by the French Stiglitz-Sen-Fitoussi Commission in 2009, or the
Enquete Commissions on Growth, Prosperity and Quality of Life in Germany between 2011 and 2013
(Enquete-Kommission, 2013). Furthermore, new statistics divisions devoted to measuring well-being and
progress have been set up by the OECD and many countries, such as the UK, Australia, or Canada, now
prepare special reports based on subjective measures of quality of life.
5For a review about relative income and subjective well-being, see Clark, Frijters, and Shields (2008).
6For recent empirical evidence on position of externalities of consumption, especially of luxury goods, see,
for example, Winkelmann (2012) or Perez-Truglia (2013).
7Examples of other domains are political power, education, leisure, or status seeking in other activities
outside economics and politics, such as sports or the arts (see Frey & Stutzer, 2016, for a discussion).
8The contingent valuation method, for example, might overstrain individuals, because the questions asked
are hypothetical, and the valuation task is unfamiliar. The respondents tend to be “primed” to the particular
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issue in question, which might not otherwise concern them at all. Moreover, the respondents may disregard
their budget constraints and the substitutes available. The likely result is, thus, a symbolic valuation of
people expressing attitudes (Kahneman & Knetsch, 1992). Furthermore, the strategic behavior of
respondents may also bias the answers. Revealed preference approaches usually require the observation of
undistorted equilibrium prices.
9This and further methodological issues are, for example, discussed in Kahneman and Sugden (2005),
Welsch and Kühling (2009), and Frey et al. (2010).
10A growing body of research has developed in the interdisciplinary field of economics and psychology
that investigates systematic deviations from utility maximizing behavior (for reviews, see, e.g., Kahneman,
2003; Camerer, Loewenstein, & Rabin, 2004; Frey & Stutzer, 2007; DellaVigna, 2009; or Rabin, 2013).
Thereby, a closer link between the study of suboptimal choices and the research on subjective well-being
is, for example, established in (Hsee, Rottenstreich, & Stutzer, 2012).
11Allcott and Sunstein (2015) define negative internalities as being the costs individuals impose on
themselves by taking actions that are not in their own best interest. Examples are time-inconsistent behavior
due to self-control problems or a distorted allocation of resources due to utility misprediction (see Section
5.3).
12This finding is contrary to a prominent result published in the study by Gruber and Mullainathan (2005).
In two longitudinal analyses for the United States and Canada, they find that tobacco taxes are positively
related to smokers' happiness. Similarly, Leicester and Levell (2016) find a positive differential effect of
higher cigarette taxes on smokers compared to non-smokers in the United Kingdom. They also study
smoking bans. For the identification of their effect, they rely on the different introduction dates across the
four regions in the UK. They find no significant effects on mental well-being.
13These scale changes are discussed in the literature under different terms, such as scale norming
(Frederick & Loewenstein, 1999), response shift (Schwartz & Sprangers, 1999), or scale of reference bias
(Groot, 2000).
14Conti and Pudney (2011) provide an example as evidence of the relevance of social desirability. They
find that people report higher values of satisfaction with their job in a face-to-face interview than when
self-completing a questionnaire. For a recent review on the determinants of the social desirability bias, see
Krumpal (2013).
15This question is related to the prominent work by Brickman and Campbell (1971), which proposes the
idea of a hedonic set point which is regained after a process of adaptation: People become used to a new
situation or repeated stimuli and thereby return to their innate level of experienced well-being. Their
conclusions provoked substantial empirical research on adaptation.
16A distorted allocation primarily occurs if the bias is not uniform across all goods and activities, because
the individual preference ordering of alternatives is altered (see Frey & Stutzer, 2014, for a discussion of
the relevance of such an asymmetry for utility misprediction). The presence of an asymmetry is indicated
by a well-known claim by Tibor Scitovsky (1976), namely that people tend to overinvest in comfort to
which one adapts strongly and to underinvest in creative activities where less adaptation is involved. Along
this line of reasoning, Frank (1999) claims that, due to incomplete information about the extent to which
we adapt to different goods and experiences, we observe a misallocation towards working and consuming
too much.
17Ubel, Loewenstein, and Jepson (2005) report findings of experiments which suggest that asking people to
reflect on adaptation is sufficient to reduce potential systematic errors in affective forecasts when people
predict their quality of life with respect to disability or living in a better climate.
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Media Technology and Well-Being: A ComplementarityInterference
Model
By Kostadin Kushlev, University of Virginia
Citation
Kushlev, K. (2018). Media technology and well-being: A complementarity-interference model. In E.
Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
Media technology—from mass media to social media and from video gaming to computer-mediated
communication—plays an increasingly central role in people’s lives. Due to exponential increases in
computing power, people now carry incredibly powerful computers—their smartphones—everywhere they
go. This ever-greater access to media technology is generating an ever-greater conflict between media
activities and the unmediated activities critical for psychological well-being—from our face-to-face
conversations and family time to our down time and work lives. What are the costs and benefits of people’s
modern media technology use for psychological well-being? Using a complementarity-interference (CI)
framework, I review research to illuminate key psychological processes (i.e., mediators) and conditions
(i.e., moderators) of the relationship between media technology and psychological well-being. Based on
the existing evidence, I propose an initial theoretical CI model of the effects of media technology on
psychological well-being. I use this CI model to outline important directions for future research, providing
guidelines for an integrated, theoretically informed research on media technology.
Keywords: Media, Communication technology, Computer-mediated communication (CMC),
Subjective well-being, Human-computer interaction (HCI)
Imagine that you have a time machine that can transport you to the past for a day at a time. You set
the year you want to travel to before you go to bed, and you wake up on the same calendar day but as far
back in the past as you wanted to travel. You decide to use the machine go back to the time of cavemen. As
you wake up in your cave, what options are available to you? You can stay in bed a little longer under the
warm animal hide covers, walk around the cave inspecting the carvings, or perhaps take a walk and try to
find some food (while presumably avoiding being eaten by a wild animal). Notably, all these options are
limited to what’s available in your immediate physical environment. Several days later, you decide to take
another trip through time back to the time of the Renaissance in the Italy. Now, as you wake up in your bed,
you can do much the same things you did on the previous trip—think, eat, look around—but now, you also
have additional options. Thanks to developments in media technology, you can now pick up and read a
book, transporting yourself in a vivid virtual world that is not constrained by your immediate physical
environment. After all this time traveling, you wake up in your own bed in the present time. And you
notice that you now have an unlimited number of virtual worlds that you can engage with. You can check
your work email or social media feeds on your phone, you can video-call your partner to tell him or her
about your time-travel adventures, or you can travel to virtual worlds—past, present, and future—with a
few movements of your finger on the TV remote. The focus of this chapter is to explore when, how, and
why this vast array of virtual worlds can enhance versus compromise psychological well-being.
Scope and Definitions
Media technology. In this chapter, we will explore psychological well-being in the context of modern
media technology. In common parlance, we often think of the word ‘media’ as referring to mass media,
such as news media (e.g., TV, radio), and more recently, to social media (e.g., Facebook, Twitter,
Instagram). But media—the plural of medium—broadly refers to any technological tool that serves as a
bridge or conduit to stimuli not otherwise available in the immediate physical environment. Thus, media
technology refers to books and newspapers, radio and television, video and computer games—or to any
device or method people use to transcend the constraints of their immediate physical environment: from
yesterday’s dial-up telephone to the today’s smartphone, and from writing a hand-written letter to texting a
friend (c.f., Okdie et al., 2014). Related terms also exist in the literature including information and
communication technology, or ICT, as well as computer-mediated communication, or CMC. Most of the
findings discussed here apply to—and in fact come from—the literature on ICT and CMC.
While using the broad term, media technology, this chapter will focus primarily on the effects of
media technology developed in the past century or so, including television, video games, and, most
recently, mobile computers such as smartphones. In other words, we will be focusing on screen media
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technology. I will use the term mediated to refer to the stimuli afforded by the media technology, and the
term unmediated to refer to behavior that does not involve the use of media (e.g., face-to-face interactions).
Even though media technology itself is physical, I will use the term immediate physical environment to
refer to the environment in which the media technology use occurs.
Well-being. We will explore the effects of media technology on well-being, broadly defined. Because
subjective well-being has been defined as a combination of life satisfaction positive affect, and (low)
negative affect (e.g., Diener, 1984, 2000; Diener et al., 2017), I will use the term psychological well-being
to include not only subjective well-being, but also the factors inextricably linked to subjective well-being
such as basic human needs (Baumeister & Leary, 1995; Fiske, 2014; Kenrick, Griskevicius, Neuberg, &
Schaller, 2010; Ryan & Deci, 2000; Ryff, 1989). We will use the term emotional well-being to refer to the
affective components of subjective well-being (i.e., positive and negative affect).
Chapter overview. There are many excellent comprehensive reviews of research on specific media
technologies, such as television, video gaming, and social media (e.g., Howard-Jones, 2011; Wilson,
Gosling, & Graham, 2012). Rather than providing a comprehensive review of existing research, therefore,
the goal of this chapter is to provide an integrative, and theoretically-focused overview of the relationship
between media technology and psychological well-being, broadly defined. Thus, I will focus on findings
that illuminate key psychological processes (i.e., mediators) and conditions (i.e., moderators) of the
relationship between media technology and psychological well-being. This focused approach allows the
identification of gaps in the literature, thereby providing guidelines for key future directions in this fastevolving
area of research. Because no comprehensive reviews exist on the psychological effects of
smartphones—the latest media device to become part of people’s lives—I will focus on evidence about
smartphones whenever possible, drawing on insights from my own emerging research in that area. First,
however, I outline my theoretical approach—the complementarity-interference framework (c.f., Kushlev &
Heintzelman, in press)—which I then use throughout this chapter to construct an initial complementarityinterference
model of media technology on well-being (see Figure 1).
Figure 1. The Complementarity-Interference (CI) Model of the effects of media technology on
psychological well-being. Media technology complements the well-being affordances of the
unmediated physical environment by providing access to activities and information not otherwise
available to users. Media technology can also interfere with the sources of well-being through
attention costs and replacement/displacement of unmediated happiness-promoting activities.
Moderating factors govern the interplay between these complementarity and interferences processes,
including how and how much people use media technology and to what extent the concurrent
unmediated physical environment affords engagement in happiness-promoting activities.
A Complementarity-Interference (CI) Framework
The focus of this chapter is to explore how and when modern media technology—and the vast array
of virtual worlds it provides—impacts well-being. To answer this question, we need to take into account
the context in which such technology use occurs. Indeed, media technology use always occurs in the
context of the immediate physical environment—and the affordances of that environment for promoting
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well-being. The critical question, then, is when media technology use complements versus interferes with
the sources of well-being available in the immediate environment. Adopting this complementarityinterference
framework, I explore evidence for both complementarity and interference processes, and then
explore the factors that determine when technology enhances versus undermines psychological well-being.
Complementarity Processes
Media technology provides access to a theoretically unlimited number of virtual worlds. In contrast,
the activities afforded by the immediate unmediated environment are limited by people’s physical locale.
Generally speaking, then, the quantity of the digital affordances for increasing well-being is greater than the
quantity of the unmediated affordances. By providing more options for engaging in happiness-supporting
activities, media technology has the potential to contribute to higher well-being.
Source of positive emotions. Perhaps the clearest empirical demonstration to date of how media
technology can complement the unmediated environment comes from a study with patients who were
undergoing minor surgery under the waist (Guillory, Hancock, Woodruff, & Keilman, 2015). Each patient
was randomly assigned to one of four conditions: (a) a control condition in which patients received
standard perioperative management, or three experimental conditions in which patients were asked to
engage in one of several activities on their phones during the surgery: (b) text messaging with a companion
(e.g., a friend, family member), (c) text messaging with a stranger, or (d) playing an engaging mobile
phone game. All participants received an initial dose of analgesic (fentanyl); the researchers then recorded
whether patients asked for additional analgesic during the surgery, providing an objective measure of
physical pain. Compared to patients undergoing the standard procedure with no technology use, patients
who were texting with a friend were approximately 4 times less likely to seek supplemental fentanyl during
surgery. Interestingly, patients who were texting with a stranger were almost 7 times less likely to ask for
more fentanyl compared to standard treatment. People who played a video game were not significantly less
likely to ask for more analgesic compared to those under standard procedure.
The findings of Guillory and colleagues (2015) suggest that, above and beyond mere distraction,
mediated social interactions can reduce the intensity of negative experiences—even physical pain. But why
did texting with strangers have a more pronounced effect than texting with a companion? Linguistic
analyses of the text messages showed that while patients who were texting with a friend talked more about
the surgery itself, patients who were texting with a stranger were more likely to express positive emotions
in their texts. Thus, by affording mediated social interactions that promote the expression of positive
emotions, media technology may directly stimulate subjective well-being.
Source of basic need satisfaction. Another mechanism by which the additional affordances provided
by media technology can enhance well-being is by serving as a source of basic psychological need
satisfaction. A mother travelling out of town for work might not be able to cultivate a sense of
connectedness with her children in person, but she can exchange text messages, call, or even video call her
children. And while a skier visiting Los Angeles may not be able to cultivate a sense of competence by
skiing on the streets of LA, she could do so by playing a skiing game on her smartphone (“there is an app
for that”). Although skiing mediated through a screen might not be quite the same as skiing at Lake Tahoe,
research shows that mediated activities can and do satisfy basic psychological needs. Playing video games,
for example, has been shown to effectively satisfy people’s need for competence (e.g., Przybylski,
Weinstein, Murayama, Lynch, & Ryan, 2012; Ryan, Rigby, & Przybylski, 2006). Studies have also
provided some initial evidence that computer-mediated communication may stimulate teenagers’ sense of
social connectedness and subjective well-being (e.g., Desjarlais & Willoughby, 2010; Valkenburg & Peter,
2007).
Efficiency and convenience. One of the key benefits—and in fact, a key purpose—of technology is
making our lives easier. With the sources of the Internet at our fingertips, we no longer need to go all the
way to the library to find popular literature or scholarly work. And with smartphones in our pockets, we can
easily find out how to get to even the most obscure of places. Looking for a nearby café to get some work
done? No problem, just ask your phone’s personal assistant! Wondering where to find the best Italian
restaurant in this neighborhood? The answer is only a tap away through a search engine. Indeed, when
people were asked to describe what they like most about their phones, the most commonly used word in
their responses was their “convenience” (Smith, 2012).
By providing a convenient portal to information, media technology affords instant access to resources
not otherwise available in the unmediated environment. With access to a search engine and a GPS map via
the Internet, or to one’s family and friends via a quick message, people can more efficiently achieve
everyday goals and solve everyday problems. Imagine that your car breaks down on the way to an
important meeting. There are no taxis or public transit nearby, and you are going to be late unless you find a
solution quickly. Rather than feeling helpless, you can use your phone to call a cab or, perhaps, a friend
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who lives nearby. To be sure, more than half of US smartphone users report that they have relied on their
phones to get help in emergency situations—with 50% having used their phones specifically to deal with
car emergencies on the road (Pew Research Center, 2015).
Beyond emergency situations, media technology can help people solve more common daily problems,
such as finding directions on the go—whether it is to a restaurant for lunch, a gas station on the road, or a
café for a necessary cup of coffee. And by making problem solving more efficient, recent research suggests
that media technology may support psychological well-being. In one experimental study, for example, all
participants were asked to locate a building on a university campus, and were then randomly assigned
either to have access or no access to their phones during the search for the building (Kushlev, Proulx, &
Dunn, 2017). Participants who relied on their phones found the building faster, and, after finding it, felt
happier than those who could not rely on mediated information. By complementing the affordances of the
unmediated environment, therefore, media technology can increase emotional well-being.
Interference Processes
Media technology can sometimes promote well-being by affording access to positive emotional
experiences, psychological need satisfaction, and more efficient ways to solve everyday problems. But
these same desirable qualities of media technology could also compromise psychological well-being by
leading people to disengage from the affordances of the unmediated environment shown to promote wellbeing.
Put simply, engagement with a mediated environment often entails disengagement from the
unmediated environment—and the benefits it affords (e.g., Przybylski & Weinstein, 2013). Yet, the
unmediated environment is inextricably linked with human flourishing and well-being (e.g., Cacioppo et
al., 2006; Lyubomirsky & Boehm, 2010; Myers & Diener, 1995; Nelson, Kushlev, & Lyubomirsky, 2014;
Reis, Sheldon, Gable, Roscoe, & Ryan, 2000). I next explore several key mechanisms of interference.
Concurrent attention costs. People have limited cognitive capacities (Navon & Gopher, 1979), and
performing multiple tasks at once can lead to limiting the cognitive resources dedicated to each task. When
two tasks require the same cognitive resource, such as attention or working memory, people cannot perform
these tasks simultaneously and must instead switch between tasks (Garavan, 1998; Liefooghe, Barrouillet,
Vandierendonck, & Camos, 2008; Oberauer, 2003; Pashler, 1998). The very act of switching between tasks
also requires deployment of attention and working memory, further taxing people’s limited cognitive
resources (Liefooghe et al., 2008). Thus, the multitasking afforded by media technology likely reduces
attention, working memory, and other cognitive resources people can dedicate to the unmediated
environment. At the same time, research shows that distraction is one of the strongest predictors of lower
positive affect during positive events—more so than psychological tendencies, such as finding faults with
events and even directly suppressing positive emotions (Quoidbach, Berry, Hansenne, & Mikolajczak,
2010).
Although the human cognitive limitations described above apply to any media technology—from
books and newspapers to TV’s and social media—it is smartphones that have truly extended the realm of
technological distraction beyond our homes and into virtually everything else people do. It is hardly
surprising, then, that about half of Americans admit that their phones have made it harder to give others
their undivided attention (Smith, 2012). Indeed, research confirms that mobile phone use can dramatically
reduce people’s ability to pay attention to their immediate environment (e.g., Drews, Yazdani, Godfrey,
Cooper, & Strayer, 2010; Strayer & Drews, 2007). In a particularly notable study, for example, people who
were talking on a cell phone while walking were less likely to see a street entertainer—a unicycling clown
—than people not using electronics (Hyman, Boss, Wise, McKenzie, & Caggiano, 2009).
To date, little direct evidence exists on how the documented attention costs of media technology
might be impacting psychological well-being. In one of the few existing studies to test the role of attention
costs, participants were assigned to spend one week maximizing phone interruptions by keeping
notification alerts on and their phones within their reach/sight. During another week, the same participants
were assigned to minimize phone interruptions by keeping alerts off and their phones away from easy
reach as much as possible. Participants reported higher levels of inattention when alerts were on than when
alerts were off. Higher levels of inattention in turn predicted lower psychological well-being (Kushlev,
Proulx, & Dunn, 2016).
Delayed attention costs. In addition to compromising attention during other activities, media
technology may be changing people’s ability to pay and sustain attention at a later time. Children’s
television viewing habits, for example, have been linked to subsequent attentional problems (e.g.,
Christakis, Zimmerman, DiGiuseppe, & McCarty, 2004; Johnson, Cohen, Kasen, & Brook, 2007). And
playing video games might be an even bigger culprit in causing downstream attentional problems in
children. In a US longitudinal study of 6 to 12-year-old children, researchers assessed television viewing
and game playing as reported by both the children and their parents (Swing, Gentile, Anderson, & Walsh,
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2010). To assess attentional problems, the researchers obtained school teachers’ reports of difficulties with
paying and maintaining attention, as well as of children’s tendency to interrupt others in class. After
controlling for existing attentional problems in this longitudinal study, the researchers found that television
viewing and playing video games both predicted more attentional problems, but that video games were a
stronger predictor.
Media technology use has also been linked to negative academic outcomes in university students with
downstream consequences for subjective well-being. In one study, students who used their mobile phone
more had lower GPAs, while also experiencing greater anxiety (Lepp, Barkley, & Karpinski, 2014, 2015)
—even after controlling for high-school GPA, as well as demographics, addictive behavior, and relevant
personality traits. Though phone use was not directly related to life satisfaction, path analyses indicated that
phone use is indirectly related to lower satisfaction with life through lower academic performance and
higher anxiety directly associated with phone use. Of course, these correlational findings cannot establish
causality, underscoring the need for future research using, for example, longitudinal methodology.
One way in which media screen time might be resulting in such downstream attentional and
performance issues might be through the effect of screen time on sleep. The light emitted from a screen has
been shown to interfere with circadian rhythms and quality of sleep. Researchers have found, for example,
that looking at a screen before bed reduces melatonin—a neurotransmitter critical for regulating circadian
rhythms (Higuchi, Motohashi, Liu, Ahara, & Kaneko, 2003). Another possible, yet unexplored, mechanism
could be found in a more basic characteristic of media: Media experiences are not limited by the same
parameters that constrain experiences in the unmediated, physical environment. A scrawny kid might not
excel in the school gym, but he can easily become an incredibly strong and agile fighter in the game Street
Fighter or become a superhero in the elaborate universe of the World of Warcraft—a massively multiplayer
online role-playing game, or MMORPG. But after the rush of playing such video games, this same kid
might find it hard to focus on the much less exciting content of his biology textbook.
Clearly, future research is needed to explore these and other possible mechanisms through which
media technology consumers develop attentional problems. In addition, future experimental and
longitudinal research needs to explore the multiple pathways through which such attentional costs might
impact well-being—from directly interfering with engagement in activities associated with greater
emotional well-being (e.g., face-to-face social interactions) to having downstream consequences for life
satisfaction in the long-term by compromising learning, performance, and achievement.
Substitution. Media technology can tax attention, thus reducing engagement with potential sources of
well-being concurrently available in the unmediated environment. But media technology can also
completely replace or obviate engagement with the unmediated environment. Thus, people may incur
indirect emotional costs of using media technology by foregoing the benefits of happiness-supporting
activities available in the unmediated environment. Playing with other children at the playground can be
replaced by playing with other gamers while sitting in front of a computer (e.g., Attewell, Suazo-Garcia, &
Battle, 2003). Getting a full night’s sleep can be replaced by a late television show (Higuchi et al., 2003;
Oka, Suzuki, & Inoue, 2008). And getting directions from a friendly local has all but been forgotten since
smartphones made it so convenient to get directions on our phones (Kushlev et al., 2017).
Replacing unmediated social activities. Of all the activities that using media technology could
replace, the replacement of unmediated social behavior (e.g., social events, face-to-face social interactions)
is perhaps the most relevant to well-being. Interestingly, research suggests that media technology is
particularly likely to replace interactions with weak social ties (e.g., acquaintances, strangers) rather than
interactions with strong social ties (e.g., friends, family). Putnam, for example, famously showed that
participation in community bowling leagues decreased as television sets became a staple in Americans’
homes in the second half of the 20th century (Putnam, 1995). Importantly, he showed that this effect was
specific to participating in bowling leagues, rather than to bowling activity in general. Thus, even as TV
watching became more popular, people continued to play bowling with their families and friends, but not
with members of the broader community. Putnam thus argued that television might be replacing
community involvement, with negative consequences for social capital such as eroding sense of community
and trust. Consistent with Putnam’s theorizing, recent research shows that portable media technology could
also be eroding trust. Specifically, in an American sample from the World Values Survey, people who used
their mobile phones more to obtain information were less likely to trust strangers and neighbors (Kushlev &
Proulx, 2016).
Due to the advent of mobile computing, people can now take their media-producing screens anywhere
they go, thus potentially replacing, and even obviating a much broader array of social behaviors than more
stationary media technology, such as TV or computers. Why interact with our classmates or colleagues
before class or meeting when we can catch up on our social media feed? And why try to spark a
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conversation with a stranger on public transit, when we can safely entertain ourselves on our phones? Yet,
social interactions—even those with mere strangers—are an important source of social and emotional wellbeing.
In one study, for example, coffee shop customers were randomly assigned to either have a friendly
interaction with the barista while getting their coffee or to have an efficient interaction by minimizing
conversation. The friendly customers subsequently felt a greater sense of belonging than the efficient
customers. In other words, having a friendly interaction with a stranger helped people to satisfy their basic
need for relatedness (Sandstrom & Dunn, 2014).
Emerging evidence suggests that screen time spent on new media might indeed be replacing in-person
social interactions, with consequences for psychological well-being. In one experience sampling study,
researchers tracked how people felt several times a day for two weeks. They found that the more people
used Facebook earlier in the day, the less happy they felt later in the day, even when controlling for earlier
affect (Kross et al., 2013). Furthermore, the more people used Facebook, the less they interacted with others
in person. Importantly, controlling for the frequency of in-person interactions—which predicted higher
well-being—attenuated the negative relationship between Facebook use and emotional well-being. These
findings suggest that Facebook use might be linked to lower well-being (for a review, see Wilson et al.,
2012) at least in part because social media use replaces face-to-face social interactions.
In addition to providing alternative social activities such as Facebook, smartphones are an incredibly
powerful source of information. While undoubtedly convenient, this ease of information access can obviate
the need to rely on fellow humans for information, leading people to forgo opportunities to cultivate a
sense of community, social connectedness, and trust. In an experimental study I described earlier, people
were asked to locate a building, and then randomly assigned either to rely or not to rely on their phones.
Participants relying on their phones talked to fewer people to obtain directions and ended up feeling less
socially connected than participants who relied on the kindness of others (Kushlev et al., 2017). These
findings suggest that portable media technology can reduce sense of community, connectedness, and trust
by replacing unmediated, face-to-face social interactions—a key source of social capital.
Displacing sleep time. In addition to replacing activities that satisfy basic psychological needs, media
technology might be displacing activities that satisfy basic physiological needs. In a 10-day experience
sampling study of working adults, researchers measured late-night technology use (i.e., after 9 pm),
including watching TV, and using a computer, a tablet, and a smartphone specifically for work (Lanaj,
Johnson, & Barnes, 2014). The researchers found that each type of technology use had independent, withinsubjects
effects on sleep quantity—even when controlling for the previous night’s sleep quantity and
quality. Put simply, people slept less on evenings when they used media technology more. Notably, even
though people spent ten times fewer minutes using their smartphones than watching TV—4 min versus 40
min—smartphone use explained twice as much of the variance in sleep quantity (4% vs. 2%).
Exploring the link between phone use and sleep further, Lanaj and colleagues (2014) found that by
displacing sleep, phones had downstream consequences for how psychologically depleted people felt in the
morning: To the extent that phones interfered with sleep, people felt more drained and unable to concentrate
in the morning. Morning depletion in turn predicted lower work engagement (e.g., feeling completely
absorbed in a work task) as measured by the Utrecht Work Engagement Scale. Though Lanaj and her
colleagues did not measure well-being, robust evidence exists that work engagement is associated with
psychological need satisfaction (e.g., competence, autonomy) and, consequently, with subjective well-being
(e.g., Deci et al., 2001; Harter, Schmidt, & Hayes, 2002). Future research is needed to clearly establish the
relationship between media use and well-being as mediated by sleep, depletion, and work engagement.
Interplay Between Complementarity and Interference Processes: The Moderators
I have so far considered some key mechanisms through which media technology might complement
or interfere with people’s “default” source of psychological well-being: the unmediated physical
environment. But, of course, the more interesting theoretical question is under what conditions the benefits
of media technology outweigh its costs—and vice versa. Unfortunately, there is little research directly
exploring these moderating variables. Yet, given that the literature abounds with both positive and negative
findings about the effects of media technology on well-being, understanding the critical moderators
between complementarity and interference processes is perhaps the most important avenue for future
theoretical and empirical work. Accordingly, using the proposed CI framework, I next explore some of the
key possible moderators.
At the broadest level, the net effects of media technology on well-being in any given period should
depend on: (1) the nature of the media activities, that is what media technology people are using and how
they are using it; (2) the quantity of media activities, that is how much people are using media technology;
and (3) the well-being affordances within the unmediated environment, that is what opportunity costs
people are incurring when using media technology.
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Quality: Active versus passive use. Research has suggested that complementarity processes of media
technology use are potentiated when people use media actively rather than passively. Direct evidence for
the role of active versus passive use as a moderating factor comes from research on social media.
Compared to people who use Facebook passively by browsing through others’ content, people who use
Facebook actively by sharing content with others experience greater social capital and feel less lonely
(Burke, Marlow, & Lento, 2010). Active media use thus seems to be a more effective way of satisfying
basic psychological needs than passive use.
Quality: Relevance to the unmediated environment. I identified attention costs as one of the key
mechanisms through which media behavior interferes with the benefits of unmediated activities. But people
frequently use media technology in ways that directly support their unmediated activities. In a
representative poll, for example, seven in ten Americans reported having used their phones for purposes
directly related to their face-to-face social interactions (Rainie & Zickuhr, 2015).
In situations in which people use media technology to directly support their unmediated activities, the
interference process through attentional costs should not apply. Thus, for example, looking at one’s phone
to find pictures or a video to share with one’s dinner companions may result in net benefits to emotional
well-being, whereas checking work email might produce net loss for emotional well-being. And while
staying at home alone on Sunday to binge watch movies online on Netflix might lead people to forgo the
benefits of socializing with friends or family, gathering with friends to socialize and eat Nachos while
watching the Super Bowl might lead to greater benefits to well-being than would socializing (and eating
Nachos) alone, that is without the stimulating effect of the spectacle.
Only initial evidence exists to show that relevance of media use to concurrent unmediated activities
can determine well-being outcomes. In the only such study to-date, parents spending time with their
children at a museum were randomly assigned to use their phones a lot or to limit their phone use. Overall,
parents assigned to use their phones frequently—compared to those assigned to limit phone use—felt less
socially connected while spending time with their children. This overall negative effect on social
connectedness was mediated by the negative effect of phone use on attention. Further, the effect of phone
use on social connectedness held regardless of whether parents used their phones for social purposes (e.g.,
text messaging, social media) or work purposes (e.g., email). Thus, any type of phone use that was not
directly relevant to parents’ experiences with their children at the museum predicted lower social need
satisfaction. Notably, however, parents who used their phones specifically to obtain relevant information
about the exhibits (e.g., by using the museum’s app for information about the exhibits) felt a greater sense
of connection (Kushlev, 2015). In other words, relevant phone use predicted higher social need satisfaction.
While illuminating, this evidence is correlational and exploratory, underscoring the need for future
experimental work to directly manipulate the relevance of media technology use to the unmediated
environment.
Quantity. In addition to how people use media technology, the effects of media technology on wellbeing
should depend on how much people use this technology in any given period of time. Of course, the
excessive use of the media technology should be particularly likely to interfere with other behaviors that
can satisfy psychological needs. While even 4 minutes of phone use for work before bed predicts less time
sleeping at night (Lanaj et al., 2014), excessive phone use has been linked to complete inability to sleep
(Tavolacci, Meyrignac, Richard, Dechelotte, & Ladner, 2015). More broadly, spending excessive time
online has been linked to dramatic outcomes, such as job loss, marriage breakdown, and academic failure
(Whang, Lee, & Chang, 2003). In some cases, the consequences can even be fatal—literally. An 18-yearold
Taiwanese teenager died after a 40-hour marathon of playing an online video game. A Korean couple
spent so much time raising their virtual daughter in an online game that they neglected their own biological
daughter; the daughter (the real one) eventually died (Wallace, 2014). And a British man who regularly
played for 12 hours at a time developed a blood clot and died from pulmonary aneurism; he was only 20
years old at the time. On the opposite side of the spectrum, however, some media technology use should
theoretically be beneficial to well-being (see Figure 1). Even though excessive video gaming can be
detrimental to well-being—and even deadly—some video game playing can also satisfy basic
psychological needs (Przybylski et al., 2012; Ryan et al., 2006). This suggests that the relationship between
media technology use and psychological well-being may be characterized by a reverse U-shaped function.
Curvilinearity. Researchers have discovered that time spent watching television is curvilinearly
related to life satisfaction: Some TV watching predicts greater life satisfaction than both excessive TV
watching or no TV watching at all (e.g., Jegen & Frey, 2004). In the domain of video games, a study with
444 Iranian adolescents found that those who spent some time playing video games had better mental
health than both non-gamers and excessive gamers (i.e., those who played more than 10 hours a week;
Allahverdipour, Bazargan, Farhadinasab, & Moeini, 2010). Similarly, in the realm of social media, studies
have suggested that the number of Facebook friends has an inverse U-shaped relationship with subjective
976
well-being (e.g., Kim & Lee, 2011). And even though multiple studies have found a negative relationship
between Facebook use and subjective well-being (Wilson et al., 2012), recent research has suggested that
Facebook users are happier and more satisfied with their lives than Facebook nonusers (Brailovskaia, &
Margraf, 2016).
Despite this consistent evidence for curvilinearity, future research is needed to provide more nuanced
understanding of the curvilinear relationship between media technology use and psychological well-being.
In the domain of social media, for example, research could explore whether the documented curvilinear
relationship between Facebook use and well-being is driven primarily by passive users, or whether active
Facebook users can also get too much. In the context of video games, research is needed to illuminate
whether some video games are characterized by stronger curvilinear relationships with well-being than
others, as well as whether people are more likely to play some video games more excessively than others. It
is possible, for example, that video games with a strong social component—such as MMORPGs, where
players can play in online guilds, teaming up with other players in virtual quests—might be particularly
beneficial for well-being by satisfying social needs. But such games might also be more likely to result in
excessive use, thus compromising well-being.
Research is yet to explore curvilinearity in the relationship between smartphone use and well-being. In
examining curvilinearity in the case of smartphones, researchers might be well advised to focus on
frequency of use and number of notifications in addition to the total time spent on phones. In one study, for
example, phone notifications alone significantly disrupted performance on an attention-demanding task,
even though participants did not directly interact with a mobile device during the task (Stothart, Mitchum,
& Yehnert, 2015). The magnitude of observed effects on attention was comparable in magnitude to those
seen when users actively used a mobile phone (e.g., calling, texting). In other words, even though people
spent no time using their phones, they still incurred attention costs simply as a result of receiving
notifications.
Affordances of the unmediated environment. According to the CI model, key factors that should
determine whether media technology would have a net positive or a net negative effect on psychological
well-being should be the quantity and the quality of happiness-promoting activities afforded by the
unmediated environment. Indeed, evidence suggests that even though media technology use has
opportunity costs for well-being in the context of environments rich in actual and potential social partners
(e.g., Przybylski & Weinstein, 2013), media technology can be beneficial to well-being in more
impoverished social environments, such as when undergoing minor surgery (Guillory et al., 2015). And, as
we saw earlier, smartphone use has been shown to reduce parental well-being during a time when parents
were spending time with their children at a science museum (Kushlev, 2015). But would phone use have
enhanced parental well-being if the study were run not in the stimulating environment of a museum, but
rather in an impoverished environment such as while waiting to pick up one’s child from school? To date,
no research has explored the affordances of the unmediated environment as a moderating factor in the wellbeing
effects of media use, highlighting a fruitful area for future research.
Political, economic, and societal factors. In addition to the affordances of the immediate unmediated
environment, the broader context of one’s political, economic, and societal milieu is likely both important
and understudied moderating factors of media use. I have so far examined a range of psychological
mechanisms in depth, largely ignoring the effects of media technology on broader political, economic, and
societal factors that also have implications for well-being. Thus, for example, social media and mobile
Internet access have allowed an unprecedented ability of groups of people—particularly those in
developing or undemocratic countries—to quickly and easily organize and congregate to achieve desired
political and social changes. Indeed, three quarters of the people surveyed in India, China, Indonesia, and
South Africa agreed that wireless mobile technology has given citizens a greater voice in their country; in
the U.S. and the U.K., less than half think so (Qualcomm, 2013). And during the Arab Spring, for example,
social media was credited as a critical factor in the successful overthrowing of current regimes in countries
like Egypt and Tunisia (Howard et al., 2011). Presumably, the use of media in such critical historical and
political contexts fosters social interaction, builds social capital, and could produce happiness boosts that
dwarf any costs.
In addition to allowing the organizing of grassroots movements for political change, access to media
technology can produce economic benefits for users, particularly in poor and developing countries. For
example, small scale framers—who produce up to 80% of the food in developing countries—often sell
their produce for much less than market value because they cannot afford to travel by themselves to the
city markets. But a mobile phone platform is allowing small-scale farmers in Kenya to easily communicate
with each other, organize transportation to the city markets, and thus sell their produce to consumers for up
to four times as much profit as before (Al Jazeera, 2014). This economic benefit of technology goes beyond
small-scale farming: About three quarters of people in India, China, Indonesia, and South Africa, for
977
example, agree that wireless mobile technology has been instrumental in finding the highest price for
something they want to sell (Qualcomm, 2013).
Finally, the broader societal benefits of having easy access to the Internet through mobile media
technology cannot be overstated. Across the developed world, smartphones are being used to provide realtime
sharing of information between physicians and patients, thus helping to improve healthcare (World
Health Organization, 2011). Like the positive political and economic effects of mobile media technology,
however, these effects are more pronounced in developing countries. For example, 9 out of 10 people in
China and Indonesia think that mobile technology has made it easier for them to access information to
maintain their own and their family’s health; in the U.S., only about half think so (Qualcomm, 2013).
In short, the use of media technology in Western, educated, industrialized, rich, and developed—or
WEIRD (Henrich, Heine, & Norenzayan, 2010)—countries might have very different effects on well-being
from the effects this same technology has in the rest of the world. Just as with most other topics in
psychological science, however, research outside WEIRD countries is badly needed.
Future Directions
Theoretical issues. Throughout this chapter, I have been highlighting gaps in the literature, charting
important directions for future research. Specifically, guided by CI framework, I have highlighted the lack
of evidence for some of the critical mediating and moderating factors in the relationship between media
technology and psychological well-being. Mediating factors that need further evidence include, for
example, the long-term effects of media technology’s attention costs on well-being. Moderating factors that
need further research include the relevance of media technology use for unmediated activities, the quality
and quantity of the well-being affordances of the unmediated environment, the role of how much and how
frequently people are using media technology, and the broader economic and political conditions.
While highlighting these critical areas for future research, it is worth noting that all processes and
conditions outlined here can benefit from replication and additional evidence. Indeed, my broader goal in
integrating existing evidence in an initial theoretical model has been to stimulate more theoretically-driven
future research that could shed light on the critical factors at play. It is worth noting, however, that I view
the CI model proposed here only as a blueprint to be improved and refined in the future. Thus, for example,
future empirical and theoretical work can reveal other mediating and moderating factors to be added to the
model. Future theorizing and research could also increase the complexity of the model by considering how
the various processes and conditions interact with each other. Thus, for example, researchers can consider
additive and subtractive effects of the various mediating processes, or explore how some of the moderating
conditions might interact with one another.
My hope is that by sowing the seeds of a theoretical model, researchers working across disciplines
will be able join forces to understand the key factors in the relationship between media technology and
well-being. Thus, when new media technologies become an integral part of people’s lives in the future—as
print media, television, gaming, and mobile computing have done in the past—researchers will be able to
launch a focused, theoretically-grounded research program to understand how these new media
technologies are similar to—and how they are different from—existing technologies.
Methodological issues. At the methodological level, this review has revealed that even after many
decades of research, causal evidence for key factors and outcomes is often lacking. This is no doubt in part
due to the challenges of exploring causality when studying the effects of human behavior as it occurs
naturally “in the wild”. One such challenge is manipulating natural behavior by asking people to use their
media technology differently. Such field manipulations can be both practically and ethically problematic.
Because media use plays such an integral part in people’s daily lives, it could be practically difficult to
recruit samples willing to substantially reduce their media use, and even more difficult to make people
follow such experimental instructions. On the flip side, asking people to increase their media technology
use could be ethically problematic given the existing research on the detrimental—and in some cases fatal
—effects of excessive use.
Such legitimate ethical issues can be minimized by reducing the duration of the study—thus
minimizing any lasting effects on well-being or health—and by carefully choosing experimental situations
in which increased use of media technology is unlikely to produce any serious harm. For example, while it
might be ethically and practically unproblematic to study parents as they spend an afternoon with their
children in the safe, enclosed environment of a science museum, asking parents to maximize their phone
use for an entire week can be ethically problematic (e.g., because it can reduce necessary supervision of
children in more hectic and potentially dangerous environments, such as a busy street intersection).
When experimental work is impractical or unethical, researchers should employ alternative
methodologies that can give suggestive causal evidence. Some of the research reviewed in this chapter
978
illustrated the benefits of longitudinal research (e.g., Swing et al., 2010) and experience sampling, or ESM
(e.g., Lanaj et al., 2014). These methods can isolate causality by allowing controls for previous media
behavior and well-being, while also allowing disambiguation of within and between-subject effects, thus
controlling for any individual differences. Of course, only multi-method research program can provide clear
evidence for the key factors at play.
Coda
In 1889, the British Medical Journal warned readers of “aural overpressure”—a new malady due to
“almost constant strain of the auditory apparatus” in people who used telephones for long periods of time.
Symptoms of the condition apparently included nervousness, buzzing in the ears, giddiness, and neuralgic
pains (Marvin, 1988). More than a century later, and with a lot more phones around us, we seem to be all
but free of this supposed malady. This example highlights the fact that new technologies have always
generated concerns about the effect they may have on people’s subjective well-being (e.g., Turkle, 2011).
Far from endorsing unbridled concerns about the perils of media technology on well-being, I have begun to
identify the processes and conditions (Figure 1) that determine how and when media technology use could
boost or hurt psychological well-being. It is my hope the theoretical model proposed here would stir further
theory development and necessary empirical research in order to understand the costs and benefits of the
media technology of today and of the future.
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Accounts of Psychological and Emotional Well-Being for Policy
Purposes
By Bob Sim, University of Virginia; Ed Diener, University of Virginia and University of Utah
Citation
Sim, B., & Diener, E. (2018). Accounts of psychological and emotional well-being for policy purposes.
In E. Diener, S. Oishi, & L. Tay (Eds.), Handbook of well-being. Salt Lake City, UT: DEF Publishers.
DOI:nobascholar.com
Abstract
Diener (2000) proposed that indicators of subjective well-being should complement existing economic and
social indicators that reflect the quality of life in nations. In this chapter, we review the reasons for
including indicators of subjective well-being in national accounts, describe the policies that subjective wellbeing
measures could influence, and summarize the progress nations have made in implementing national
accounts of well-being. We also describe the characteristics of nations that are high in subjective well-being
and respond to some common objections towards implementing indicators of subjective well-being in
national accounts.
Policy-makers in government and business often guide their decisions by economic and social
indicators. These indices are often referred to as national accounts because the indices are often collected
using large-scale surveys from nationally representative samples and are thus often considered to accurately
represent the nation as a whole (Smith & Mackie, 2015). Nations first started collecting official statistics on
their economy, monitoring economic indicators related to the production, income, labor, and market
expenditure of the nation. As nations grew wealthier, national accounts also started to include noneconomic
indicators that monitor physical well-being. Recently, spurred by increasing interest in subjective
well-being among researchers, public policy makers, and the general public, national statistical offices have
also begun collecting statistics on subjective well-being. Given the increasing prominence of national
accounts of well-being, this paper attempts to summarize the types of policies that may be beneficial for
subjective well-being, and review the initiatives various countries and organizations implemented to
measure the subjective well-being of their constituents.
What is Subjective Well-Being?
Subjective well-being (SWB) is defined as an individual’s global evaluation across different aspects
of life (Diener, 1984). SWB is often colloquially described as “happiness”. However, scientists avoid the
term “happiness” in the scientific literature because happiness is a term that encompasses various concepts.
Happiness can represent a specific emotion that people feel in response to various life experiences (e.g., I
am feeling happy), but happiness can also describe a broad judgment of a person’s life (e.g., I have a happy
life). Instead, we examine subjective well-being – the extent to which an individual believes that their life is
going well.
Subjective well-being consists of two major dimensions – affect and life satisfaction (Diener, 1984).
Affect is the term used by psychologists to describe a person’s feelings and emotions and comprises of
both positive and negative affect. Positive affect includes emotions like happiness, contentment, and joy,
while negative affect includes emotions like sadness, anger and fear. Crucially, a person high in SWB often
reports experiencing frequent positive affect and less frequent negative affect. On the other hand, life
satisfaction involves a person’s cognitive appraisal of his or her life. These appraisals could include either
be broadly (global life satisfaction measures) or narrowly (satisfaction with specific life domains) defined.
However, regardless of the scope of the appraisal, a person high in SWB often reports being satisfied with
his or her life.
Reasons for Including Subjective Well-Being
in National Accounts
Given that governments and businesses already compile social and economic indicators to track the
well-being of their constituents, some critics question the need to include measures of subjective well-being
in national accounts. In this section, we briefly review several important reasons for including SWB in
national accounts of well-being.
People Believe SWB is Very Important
The strong emphasis on the importance of SWB could be observed throughout history. Aristotle
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considered eudaimonia, which was often translated as happiness, as the final and sufficient goal for
mankind (Aristotle, 1985), while utilitarians like John Stuart Mill and Jeremy Bentham focused their
theories around achieving and maximizing subjective well-being (Mill, 1863).
Besides the deep philosophical roots of subjective well-being, lay persons too place great
importance on SWB. For example, we would hardly rate a person who is depressed and dissatisfied with
his or her life as a successful person, regardless of the person’s economic or social status. The importance
we place on SWB could also be inferred from our responses to Mill’s classic rhetorical question asking
whether it is better to be a dissatisfied human or a satisfied pig. Although the correct choice may not be
evident to us, it is clear that most of us would prefer to be a satisfied human rather than an unsatisfied one,
and a satisfied pig than an unsatisfied one (Diener, Lucas, Schimmack, & Helliwell, 2009).
The importance lay persons place on SWB was also demonstrated empirically. King and Napa
(1998) found that happy people are judged more positively than unhappy people to the extent that happy
people are thought to be more likely to ascend to heaven after they die. In addition, college students in 41
nations rated life satisfaction and happiness as extremely important concepts, with an average rating of 6.21
and 6.39 (out of 7) for life satisfaction and happiness respectively (Diener, Sapyta, & Suh, 1998). Crucially,
the importance of SWB was reflected not only by Western, industrialized nations but also by less
economically developed nations. For example, happiness was rated 6.63 in Indonesia, 6.62 in Brazil, and
6.27 in Ghana. Although subjective well-being may not be the most important value for everyone, it is
likely to be a value that almost everyone, lay persons, and philosophers alike, endorses. Since governments
in modern democracies are instituted to serve the interests of the populace they govern, governments
should thus consider implementing SWB measures in their national accounts.
Current Indicators are Incomplete and Insufficient
Economically developed nations typically monitor quality of life in their societies using both social
and economic indicators (Smith & Mackie, 2015). Both measures provide important information about how
nations are functioning. However, both types of indicators each have their limitations that can often be
addressed by incorporating measures of subjective well-being in national accounts (Diener, Oishi, & Lucas,
2015).
Social indicators often provide relevant information for policy making. These indicators evaluate
diverse areas ranging from health outcomes (e.g., obesity rates), education outcomes (e.g., percentage of
college graduates), to environmental outcomes (e.g., PM2.5 levels). Governments track social indicators
because these indicators were presumed to reflect characteristics of a good society. By tracking these
indicators, nations and organizations should then be able to monitor these attributes and enact policies to
address insufficiencies in certain areas.
Unfortunately, there is no obvious method to identify characteristics of a good society (Diener et
al., 2009). Governments and organizations thus often rely on experts to identify these characteristics, which
represent the first limitation of social indicators – that there is often no consensus, even among experts, on
the indicators to be included (or excluded). For example, number of hobbies is included in the Living
Conditions Index of the Netherlands (Boelhouwer & Stoop, 1999), but is its inclusion justified? What about
people who do not have hobbies? Is it justifiable to infer that people without hobbies are not satisfied with
their lives? What if people do not have hobbies because they are spending their time on other meaningful
activities (e.g., taking care of their children, volunteering with charities)? Although there are certain items
that almost everyone would agree should be included as social indicators of well-being, the number of such
items is relatively small compared to the number of possible items that could be used as social indicators of
well-being. If experts cannot agree on the indicators to be included, then it is highly likely that the social
indicators selected to predict the well-being of a society are incomplete.
Even if we manage to accurately identify the characteristics of a good society, the use of social
indicators as predictors of well-being still face another limitation: How do we integrate the information
obtained? Few would argue that every indicator is equally important. For example, Maslow (1954) would
argue that the indicators relating to our physical needs (need for food and water) are more important than
the indicators relating to our need for safety (need for safe shelter) and thus should be weighed heavier.
However, beyond this basic rule, coming to an agreement on the importance of other indicators will be
difficult. As the list of indicators increases, the difficulty of weighing the indicators will also increase
exponentially, making an already difficult task almost impossible (Diener et al., 2009). For example,
Becker, Denby, McGill, and Wilks (1987) examined the quality of life in 329 metropolitan areas and found
that 59 of the 329 regions could be ranked anywhere from first to last depending on how the indicators that
make up the overall quality of life index are weighed. Thus, a metropolitan area’s quality of life rating
could differ drastically depending on a person’s weighting of the indicators. Similarly, a nation’s index of
well-being could also differ drastically, depending on the weights we assign to each indicator. If so, then
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how can we be certain that the index of well-being is accurate and complete?
There is no doubt that social indicators provide useful information, but they also have limitations
(see Diener et al., 2009 for a review). Social indicators reflect the values of the people compiling the list. In
addition, it is often difficult to integrate and weigh the indicators objectively. Due to these limitations,
indicators of subjective well-being such as life satisfaction are needed to complement social indicators to
provide a more complete understanding of quality of life. Since subjective well-being indicators are often
broad assessments of a person well-being, these indicators do not rely on the identification of a list of
characteristics. In addition, subjective well-being indicators could provide a common metric that can be
used to compare outcomes across domains. For example, a government might face trades-off when
deciding whether to boost healthcare spending or to devote more resources to improve the environment.
Although subjective well-being indicators cannot provide absolute answers, they can provide information
about the relative effect of improvements in each domain, allowing the government to compare the two
policy decisions.
Besides social indicators, nations also invest considerable resources to generate and monitor
economic indicators. These indicators often measure a nation’s labor and trade productivity with the
assumption that a nation with strong economic performance is also a nation that is flourishing. Some
common economic indicators include the Gross Domestic Product (GDP), inflation rates, unemployment
rate, and tax rates.
Needless to say, economic indicators are important to societies. Since industrialization, governments
have relied and continue to rely primarily on the information derived from economic indicators to inform
their policies. However, economic indicators also suffer from a number of important limitations. Similar to
social indicators, there is a concern about what economic indicators are to be included, and how to integrate
the information derived from economic indicators. Furthermore, governments and organizations should
recognize that economic indicators often have large blind spots, often omitting other aspects of life that are
important to well-being (Diener & Seligman, 2004). For example, GDP is used as a measure of material
well-being of a society because it is supposed to reflect the total goods and services produced and
consumed in a society. However, GDP often underestimates the levels of well-being in a society because
there often are other activities that may have economic value, but are still not included in GDP. Work (e.g.,
laundry, cooking), as well as child care that occurs in the home, are not included in GDP although such
work contributes significantly to GDP when they are purchased as part of a service outside the home
(Diener et al., 2009; Diener & Seligman, 2004).
Other than blind spots, economic indicators often inform policy makers that something is wrong,
but they often do not reveal what is driving the problem (Diener, Kesebir, & Lucas, 2008). For example,
economic indicators could inform policy makers on the number of lost workdays, or the productivity of the
economy. However, economic indicators alone will not explain why workers are taking more days off.
Workers may be taking more days off due to mental illnesses, physical illnesses, or even because they are
working in a miserable environment. Without additional information, it will be tough for policy makers to
identify and remedy the root cause.
Economic indicators are useful but do not provide governments and organizations with complete
information. Economic indicators often do not value non-market goods and services, and often do not
reveal the true cause of a problem. As a result, indicators of subjective well-being could complement
economic indicators by addressing the insufficiencies of economic indicators. For example, subjective
well-being measures could be used to help policy makers value the externalities incurred by economic
activity (Diener et al., 2009). Negative externalities like air pollution could be measured by the decrease in
SWB of the citizens within the area affected by air pollution, which in turn can help inform cost-benefit
analyses involving the activity that led to the air pollution. Obviously, much more work is needed to
evaluate the validity and effectiveness of such a method. Nonetheless, the example demonstrates how
policy makers could derive concrete values using indicators of SWB.
Subjective Well-being is Beneficial
Besides being a very important value to most people, research conducted in the past decade
demonstrates that subjective well-being is also associated with several positive outcomes at both the
individual and societal level (Diener & Chan, 2011). People high in SWB are often healthier, more
successful, and have better social relationships (De Neve, Diener, Tay, & Xuereb, 2013; Lyubomirsky,
King, & Diener, 2005).
Pressman and Cohen (2005) wrote a comprehensive review of the beneficial effects of positive
affect on health. In addition, several longitudinal and experimental studies demonstrated the beneficial
effects of SWB on health. For example, Danner, Snowdon, and Friesen (2001) examined the diary entries
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of Catholic sisters written at age 22 and found that sisters who used more positive emotional words in their
entries were more likely to live longer six decades later. A study examining a representative sample of
older people living in England also found that people who report enjoying life more frequent lived longer,
even after controlling for several health-related factors (Zaninotto, Wardle, & Steptoe, 2016). In addition,
participants who were experimentally infected with the cold virus, and who reported experiencing high
levels of positive affect were less likely to fall sick and even recovered faster compared to people who
reported experiencing low levels of positive affect (Cohen, Doyle, Turner, Alper, & Skoner, 2003). A
separate study also found that inducing a positive mood after a stressful experience led to a faster recovery
of the cardiovascular system (Fredrickson & Levenson, 1998).
People high in SWB also tend to be more successful than their peers. Dotson and Allenby (2010)
found that bank employees with higher job satisfaction produced more revenue on average, while customer
service representatives in a bad mood completed fewer calls per hour (Rothbard & Wilk, 2011). Individuals
higher in SWB were more likely to be re-employed after unemployment (Krause, 2013), and positive
moods were also associated with better performance for both sales managers and subordinates in customer
service (George, 1995). In addition, people high in SWB are more likely to earn higher incomes, more
likely to secure a job, and report higher job satisfaction (Diener, Nickerson, Lucas, & Sandvik, 2002).
People high in SWB are also beneficial to organizations, although the benefits of SWB on organizational
performances are often small (Tenney, Poole, & Diener, 2016). Companies with higher employee
satisfaction had higher rises in share prices (Edmans, 2011) while manufacturing plants with higher
employee job satisfaction were more also productive (Böckerman & Ilmakunnas, 2012).
People high in SWB are not only more likely to be more successful than their peers; they are also
more likely to have better social relationships than people low in SWB. A longitudinal study found that
children who report low life satisfaction were more likely to be victimized later in life, and were less likely
to be prosocial (Martin, Huebner, & Valois, 2008), while adolescents who reported high positive affect had
fewer relationship conflicts ten years later (Kansky, Allen, & Diener, 2016). People high in SWB were also
more likely to get married, remain married, and to report high marital satisfaction (Harker & Keltner, 2001;
Lucas, Clark, Georgellis, & Diener, 2004). In addition, Cunningham (1988) found that inducing a positive
mood led participants to become more talkative and more self-disclosing, while children induced with
positive moods also displayed better social skills and higher self-confidence (Kazdin, Esveldt-Dawson, &
Matson, 1982).
The bulk of the research has demonstrated that individuals high in SWB function better in various
domains from health, to social relationships. Given the benefits of SWB on individuals and societies,
subjective well-being is therefore not only a private affair involving the individual but should also be a
public affair because it is in the best interests of governments and organizations to ensure that their
constituents are doing well.
Indicators of Subjective Well-being are Easy and Inexpensive to Implement
National statistics are often computed by government statistical agencies. As a result, national
statistics often contain higher quality information since only governments and big organizations like Gallup
could devote the resources needed to ensure large and representative sample sizes, high response rates, and
the ability to collect the data over a long period of time. For example, in 2012, the Gallup opinion surveys
cost the company $10 million a year and generates little to no revenue (Boudway, 2012). At the national
level, the 2010 Census in the United States cost taxpayers $13 billion (The Economist, 2011), while the
2011 Census in Australia cost the nation $440 million (Australian Bureau of Statistics, 2011). Obviously, a
lot of resources has been and continues to be devoted to collecting national statistics. In addition, the cost
of conducting the US Census has been increasing exponentially over the years, from $12 million for the
1900 US Census to $4.5 billion for the 2000 US Census (Gauthier, 2002). With the burgeoning cost of
collecting national statistics, critics may be concerned that incorporating indicators of SWB into national
statistics will incur further cost that outweighs the benefits of including these indicators.
While it is not yet possible to evaluate the cost and benefits of including indicators of SWB into
national statistics, it seems unlikely that it would be exorbitantly expensive for governments and
organizations to include indicators of SWB in their survey. Indicators of SWB are often self-report
measures where we ask participants to report their satisfaction using a one to seven scale (Diener et al.,
2009; Smith & Mackie, 2015). Such measures are often easily administered verbally or on pen and paper,
and can often be completed within a short period of time. Therefore, governments and organizations that
opt to include such measures into their surveys should not experience much difficulty incorporating the
measures into the survey and neither should they report a significant increase in time taken to administer
the survey. Given the relatively low cost in collating indicators of SWB and the potentially valuable
information that governments and organizations could derive, governments and organizations should thus
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consider implementing indicators of SWB in their surveys.
Summary
There are multiple reasons for incorporating indicators of SWB into national accounts. First, people
believe that SWB is important, and strongly value SWB (Diener et al., 1998). Second, current social and
economic indicators omit important characteristics that are important to quality of life (Diener & Seligman,
2004). Third, SWB has beneficial outcomes for both individuals and societies (Diener et al., 2015). Fourth,
it is easy to implement indicators of SWB in national outcomes with little cost (Diener et al., 2009).
Although we have highlighted the limitations of social and economic indicators, we do not believe
that these indicators are problematic, or should be ignored. Neither are we suggesting that indicators of
SWB are better than social and economic indicators. Social and economic indicators obviously provide
governments and organizations with useful and important information about their constituents, and we do
not believe that indicators of SWB are in competition with social and economic indicators. Instead, social,
economic, and SWB indicators should be seen as complementary measures that work in tandem to provide
us with a better understanding of a nation's well-being. When considered together, these indicators allow us
to better predict a nation's well-being and enable policy makers to enact more effective policies that work
for the better of society.
What Types of Policies Could
Subjective Well-being Measures Influence?
Indicators of SWB provide us with a broad understanding of the factors contributing to a person’s
or a society’s well-being. However, national accounts are produced not only for descriptive purposes but
more importantly, are used to meet the needs of policy makers in planning and assessing the impact of
policy decisions. In this section, we review the type of policies that might be beneficial for well-being, and
how indicators of SWB could assist policy makers with policy decisions. In many of these areas we review,
there is only preliminary evidence, thus we are not suggesting that that policy makers should base their
policy decisions on the research we present. Instead, these are just some of the policy recommendations that
we could envision, and further research will be required to provide evidence for the effectiveness and
validity of these policy alternatives.
Economic
Researchers have found a robust, albeit complicated, relationship between income and SWB. There
is consistent evidence that rising income is often accompanied by rising SWB (Diener, Tay, & Oishi, 2013;
Gardner & Oswald, 2007). However, researchers have also observed satiation points and a declining
marginal utility of income on SWB, indicating that money is not everything (Diener, Sandvik, Seidlitz, &
Diener, 1993; Jebb, Tay, Diener, & Oishi, 2016). These findings present alternative methods for measuring
cost of living indexes and are useful for policy makers in policy areas relating to wage distributions. For
example, when deciding upon an appropriate minimum wage, policy makers often rely solely on economic
measures that take into account the cost of housing, transportation, and other services essential to survival.
Instead of relying exclusively on economic measures, however, policy makers can also take into account
the income satiation points of SWB – levels of income where SWB does not increase further and
determine an appropriate minimum wage. Doing so will ensure that characteristics not captured by
economic measures (e.g., child care, housework), will be taken into account, and given an appropriate
weightage.
Unemployment is another area where SWB measures could influence policy. Lucas et al. (2004)
found that unemployment is detrimental to SWB such that life satisfaction does not fully return to preunemployment
levels even after people were re-employed (Clark, Georgellis, & Sanfey, 2001).
Furthermore, a longitudinal study examining a nationally representative sample in the United States
between 2008 to 2011 found that unemployment rate was significantly associated with job dissatisfaction
over time (Tay & Harter, 2013). Even though unemployment is detrimental to SWB, there is evidence that
the negative effects of unemployment could be alleviated by welfare policies such as income security,
employment programs, and regulations that protect workers (Easterlin & Switek, 2014; Radcliff, 2013).
Besides providing policy makers with such information on which to base policies upon, policy makers
could also derive value estimates using SWB measures, and weigh the trade-offs between two competing
policies alternatives.
Besides governments, organizations and businesses could also use subjective well-being findings to
design policies for workplaces. Research examining well-being in the workplace has found several features
that are conducive to employee’s well-being. For example, a workplace that has strong social support
among employees is strongly associated with higher employee well-being (Humphrey, Nahrgang, &
Morgeson, 2007), while having a supervisor who is friendly and communicates clearly is also associated
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with higher workplace well-being (Colquitt, Conlon, Wesson, Porter, & Ng, 2001). These results suggest
that organizations and businesses could have a direct influence on their employee's well-being. For
example, by being more mindful in their hiring processes, organizations could foster a work environment
that is conducive to employee's well-being, which in turn spurs job productivity and increases profits.
Interestingly, some corporations already seem to understand that insuring employee’s well-being is
the key to increased productivity and profit. In companies like Google, Facebook, and Airbnb, it is
common to find workplaces equipped with gyms, a cafeteria with restaurant quality dishes, and amenities
like a nap room, massage therapists, and even a playground equipped with slides and swings. Although it
is commendable that companies are placing so much effort in insuring employee’s well-being, we question
if such initiatives are actually improving employee’s well-being since there have been no studies
examining the effectiveness of such initiatives. Companies looking to evaluate the effectiveness of their
initiatives could consider incorporating indicators of SWB into employee’s evaluations, allowing
companies to determine the effectiveness of such initiatives.
Environmental
People living in a clean and green environment often report higher SWB (Bird, 2007). For example,
a survey involving 10,000 individuals found that individuals living in urban areas with more green space
reported higher well-being and lower mental distress (White, Alcock, Wheeler, & Depledge, 2013). In
another study, participants who were instructed to take a walk along a nature reserve experienced an
increased in positive affect compared to participants who walked along an urban path (Hartig, Evans,
Jamner, Davis, & Gärling, 2003), a finding that was replicated by MacKerron and Mourato (2013), who
tracked participants using GPS locations to determine whether participants were in an and urban area, or in
an area surrounded by nature. These studies have implications for a wide variety of public policies. For
example, policy makers may want to consider providing more parks and green spaces within urban
environments or even attempt to increase the amount of greenery found along streets. Wider implications
include revising zoning laws and zoning areas to account for the benefits of green spaces.
Indicators of SWB could also be used to evaluate the negative effects of air pollution. When trying
to evaluate the cost of air pollution on society, we currently depend almost exclusively on economic
indicators, measuring the cost of medical care incurred as well as the cost to repair the damage that has
been done. Alternatively, we could consider using indicators of SWB and quantify the extent of the
damage done by referencing the drop in SWB reported by regions affected by the pollution. For example,
Luechinger (2009) examined, over a period of time, people living upwind or downwind from power plants
which were scheduled to have scrubbers (which removes a majority of the pollutants from the effluent)
installed. He found that people living downwind from the power plants report higher life satisfaction after
the installation of the scrubbers, whereas people living upwind from the power plants did not report a
change in life satisfaction, demonstrating that efforts to remedy pollution can be effective in improving
SWB. Indeed, we still cannot accurately quantify levels of SWB in monetary terms, however as indicators
of SWB becomes widespread, improved methodologies will also develop in tandem such that such
conversions may be possible.
An increase in urbanization around the world is associated with an increase in transportation and
commuting concerns as more people flock towards the suburbs and must commute to work. A large
amount of evidence now shows that long commutes tend to be detrimental to people’s SWB. For example,
Stutzer and Frey (2008) found that people with long commutes reported lower life satisfaction than people
with short commutes. Schwarz, Kahneman, and Xu (2008) also found that among a variety of different
activities, people reported lowest affect balance scores during commutes. Furthermore, the negative effects
of commuting do not appear to be limited to people who commute using private transport. Evans and
Wener (2006) demonstrated that New York rail commuters who had long commutes also reported higher
stress and had higher levels of cortisol on commuting days. Given that commuting is detrimental to wellbeing,
policy makers may need to re-evaluate the premise of working in a physical office, and consider
alternative work arrangements such as telecommuting, or flexible working hours such that employees could
avoid long commutes. Policy makers may also need to consider policies that could reduce the length of
commutes, or improve the experiences of commuting. Regardless of the policies being debated, indicators
of SWB will be able to assist policy makers in making informed decisions.
Health
As people live healthier and longer, health organizations have also shifted their focus away from
prolonging life and towards improving quality of life (Kurth, 2005). Diseases and illnesses inflict misery
and ill-being onto the patient. Therefore, modern nations often spend vast amounts of money on disease
treatment and prevention, in hope that proper treatment could alleviate patients’ ill-being. Unfortunately,
nations rarely have enough resources to meet the demand for healthcare. Thus, nations often need to ration
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healthcare spending through various means (Dolan, 2007). For example, governments will need to decide
which diseases and illnesses they should focus their attention on, which will inform their decision for the
allocation of funds. Currently, policy makers often based their decisions on two criteria – the seriousness of
the disease or the likelihood that treatment of the disease could ease suffering. However, policy makers
could also use indicators of SWB as part of the evaluative process. For example, Dolan (2008) suggested
examining the SWB of patients who are suffering the disease and use their reports to calculate Happiness
Adjusted Life Years (HALY), a measure that is similar to the Quality Adjusted Life Years. Policy makers
can then use this information to make an informed decision. As a further advantage, because measures like
HALY are calculated independent of the disease symptoms that vary across illnesses, these measures could
be used as a common metric, allowing policy makers to make comparisons across illnesses.
Besides physical health, indicators of SWB could also be used to monitor the mental health of
societies, and in particular, of youth and children. Monitoring the mental health of the young is important
because mental health problems have direct consequences for the well-being of children. Not only is
suicide the third leading cause of death among youth in the United States (Spencer, 2006), anxiety
disorders also predict dropping out of school (Kessler, Foster, Saunders, & Stang, 1995), while depression
predicted a decrease in educational achievements like school performance (Asarnow et al., 2005). The goal
of monitoring the mental health of young and old alike is to identify people who are suffering from illbeing
and in need of professional help. If such programs were linked to treatments, then it is easy to
imagine that such initiatives could prevent behavioral and psychological problems in the long run. To
monitor the health of children, policy makers could, for example, evaluate the mental health and well-being
of students as part of their health assessment in schools. Besides evaluating students’ mental health, these
reports of well-being could also be used as indicators of educational performance. Many governments
spend large amounts of money assessing the academic progress of children through standardized testing.
However, governments seldom assess whether students enjoy school, or whether they are actively engaged
with the material. Indicators of SWB could fulfill this role. By asking students about their well-being in
school, policy makers will be able to evaluate the effectiveness of the educational system and identify areas
that need improvement.
Social
Social capital, as a resource, is often defined as the quality of social networks within a community.
Societies with strong social capital are characterized by high levels of civic participant, high levels of trust,
and with strong norms for reciprocity (Putnam, 1993). Social capital is positively associated with SWB at
both the individual and societal levels (Putnam, 2001). Individuals reported higher SWB not only when
their own levels of social capital were higher, but also when the level of social capital of the community
they were residing within was higher. The positive relationship between social capital and SWB was also
replicated in a cross-national sample (Helliwell, 2006). Given the time end effort required to build social
bonds, changes in social capital often do not occur immediately. Thus, policy makers interested in
evaluating the short-term effectiveness of policies intended to increase social capital could use indicators of
SWB as effective proxies. For example, social capital could be increased by initiatives to increase social
interaction. Policy makers build communal areas (e.g., resident centers, parks) within neighborhoods;
encourage residential architectural designs that allow greater neighbor interaction, or even organize
frequent town meetings or events that bring residents together. In the long run, these initiatives could result
in an increase in social capital, but indicators of SWB could be used in the interim to evaluate the
effectiveness of such initiatives.
As the urban population continues to grow, indicators of SWB could also be used to assist city
planners in evaluating the aspects of a city that contributes to well-being. For example, Kansas City,
Missouri, conducted a survey of its citizens in 2006, examining their well-being and satisfaction with city
facilities and services. Results indicated that the residents of Kansas City did not report high levels of wellbeing
and were not satisfied with the facilities and services provided by the city. More importantly,
administrators in Kansas City were also able to determine which facilities or services Kansas City residents
were most dissatisfied with, and could then take steps to improve the situation. While administrators would
be able to infer that residents were generally not satisfied with the facilities and services provided by the
city using economic or social indicators, they would have a harder time pinpointing the specific areas for
improvement using economic or social indicators.
Characteristics of Nations High in Subjective Well-Being
Nations high in subjective well-being often demonstrate several characteristics (see Oishi, 2012 for
a review). First, nations high in SWB are often developed nations with relatively high wealth and national
income (Diener, Kahneman, Tov, & Arora, 2010). Second, nations high in SWB are often low in corruption
(Tay, Herian, & Diener, 2014), and have efficient, effective governments (Helliwell, Huang, Grover, &
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Wang, 2014) that emphasizes a strong rule of law (Diener, Diener, & Diener, 1995), a strong emphasis on
protecting human rights, and are often low in corruption. Third, nations high in SWB have progressive tax
structures (Oishi, Schimmack, & Diener, 2012) as well as income and employment security programs that
protect the less privileged (Di Tella, MacCulloch, & Oswald, 2003; Easterlin & Switek, 2014; Radcliff,
2013). Initial evidence also suggest that places high in SWB are also healthier (Lawless & Lucas, 2011),
have better healthcare coverage (Boarini, Comola, de Keulenaer, Manchin, & Smith, 2013), and are often
greener (White et al., 2013), although further research is required to determine if the relationship holds at
the national level.
A nation that exemplifies almost all of the characteristics of a society high in SWB is Denmark. Not
only are Danes frequently ranked among the happiest people in the world (Helliwell & Sachs, 2017), Danes
enjoy a high standard of living, and Denmark often rank among the highest in cross-national rankings of
performances. For example, Denmark is ranked fifth in the Human Development Index, which takes into
account indicators such as life expectancy, education attainment, and GDP per capita (United Nations
Development Programme, 2016). Denmark also rank among the highest in the Democracy Index
(Economist Intelligence Unit, 2016), an index that measures the state of democracy in a country by taking
into account various important indicators of democracy such as the protection of civil liberties, whether the
nation has democratic electoral processes, and the extent of political participation in a nation. Among the
nations surveyed, Denmark also has one of the highest per capita income (World Bank, 2016a); the highest
social mobility (Causa & Johansson, 2010), a high level of income equality (World Bank, 2016b), the
lowest perceived levels of corruption (Transparency International, 2016), and one of the highest personal
income tax rates (KPMG, 2016).
Denmark also ranks highest in the world for workers' rights and strong employment security
programs (International Trade Union Confederation, 2014). Denmark also has a universal healthcare
system, ensuring that almost all health care provision is free for Danes. In addition, Denmark is a very
environmentally conscious nation, relying on wind power to provide 42% of the nation’s electricity.
Unsurprisingly, Denmark also ranks among the highest in the Environmental Performance Index, which
measures how well individual countries implement the United Nations’ Sustainable Development Goals
(Yale University, 2016).
Costa Rica is another nation that reports high SWB despite its’ poor GDP per capita earnings. Costa
Ricans are also frequently ranked among the happiest people in the world (Helliwell & Sachs, 2017),
despite being a developing country, with a 2015 GDP per capita of only US$10,630 (World Bank, 2016a).
In contrast, Denmark had a GDP per capital of US$52,000 in 2015. In the 2017 World Happiness Report,
Costa Rica was ranked 12th among the nations surveyed, the highest among the nations surveyed in the
Americas (Helliwell & Sachs, 2017). The country has consistently performed well in the Human
Development Index, ranking 66th among the nations surveyed in the 2016 Human Development Index, the
highest among the Latin American nations (United Nations Development Programme, 2016). The United
Nations Development Programme (UNDP) also found that Costa Rica attained higher human development
standards compared to other countries at the same income levels (United Nations Development Programme,
2016).
Similar to Denmark, Costa Rica also employs a universal healthcare system and is also an
environmentally progressive nation. In 2015, it is the only country to meet all criteria established by the
UNDP to measure environmental sustainability (United Nations Development Programme, 2015). It was
also ranked 42nd in the 2016 Environmental Performance Index, only outranked by the USA and Canada
among the Americas nations surveyed (Yale University, 2016). Despite a lagging economy, Costa Rica has
a literacy rate of 96.3%, one of the highest in Latin America, and a high-quality education system, ranking
52ng in the 2016 Global Competitiveness Report, 3 rd among the Latin American Countries (World
Economic Forum, 2016).
Besides differences of SWB between nations, there are also significant differences in SWB within
nation. The United States overall reports pretty high SWB. However, using data the Gallup-Healthways
Daily Well-being Index, we also found significant differences in SWB between zip codes. For example,
residents living in Delaplane, Virginia are mostly white, middle-aged, report a median household income of
US$124,141, and do not attend church regularly. They report experiencing high SWB. In contrast,
residents living in Port Murray, New Jersey report similar demographic indicators, but often report
experiencing low SWB. Meanwhile, residents living in Denmark, South Carolina are majority black, young
adults earning a median household income of US$21,026 who attend church regularly, yet they report
experiencing high SWB. This example illustrates that although cross-national indicators are useful, we
should also not assume that national accounts of well-being are adequate in describing the well-being of
990
everyone living in the nation. Instead, the well-being of citizens living in different regions of a nation could
differ drastically, and indicators of SWB should be used to identify within nations differences too.
Progress on National Accounts of SWB
Diener (2000) first proposed that nations should adopt national accounts of well-being to
complement economic and social indicators. Since then, there has been significant discussion and
refinement of the idea among academics and scientists. For example, Diener and Seligman (2004)
published the influential article “Beyond Money: Towards an Economy of Well-being”, also arguing that
economic indicators are insufficient to reflect the quality of life in societies. Then, Diener (2005) published
a set of broad guidelines for measuring and implementing national accounts of well-being. From 2005 to
2007, Diener coordinated a program at the University of Pennsylvania to discuss and further refine the
ideas of national accounts of well-being with psychologists, philosophers, economists, and policymakers.
Subsequently, Diener et al. (2009) authored a volume presenting the reasons for national accounts of wellbeing,
and provided examples of policies that SWB measures could influence. Diener et al. (2015) then
published a follow-up to Diener (2000), reviewing the significant progress that has occurred within the last
fifteen years regarding the acceptance and implementation of national accounts of SWB by policymakers.
Smith and Mackie (2015) also outlined how national statistical offices could measure SWB measures, and
how SWB measures could guide policy.
As Diener et al. (2015) reviewed, there has been significant acceptance of the idea that national
accounts of SWB are beneficial to nations and organizations. For example, Diener presented findings on
SWB to the World Bank in 2003, to the United Nations Development Program in 2008, and again to the
World Government Summit in 2016, a meeting that was attended by government representatives from 130
nations. In addition, the 2009 report of the Commission of the Measurement of Economic Performance and
Social Progress (Stiglitz, Sen, & Fitoussi, 2009) recommended that government population surveys should
measure people’s well-being.
In 2012, the UN General Assembly adopted resolution 65/309, affirming that economic measures
alone do not adequately reflect the well-being of people, and broader measures of well-being should be
considered. In 2013, the National Academy of Sciences of the USA issued a positive review of well-being
measures. In the same year, the Organization for Economic Cooperation and Development (OECD), which
assist in the coordination and collection of statistics across nations, also published a positive discussion of
SWB measures and their uses in policymaking.
Not only has there been significant acceptance of the idea that national accounts of well-being are
beneficial, there has also been significant implementation of national accounts of well-being across
different nations. For example, in 2010, the prime minister of the United Kingdom announced that the UK
would measure SWB to assist policy decisions. In addition, Bhutan also conducted the first measurement of
the Gross National Happiness Index (GNH) the same year. The GNH is an index used to measure the
collective happiness of a nation. Furthermore, the United Nations Development Program also published a
report of SWB in nations around the world in 2010. To date, over forty nations have assessed SWB in
surveys conducted by the government or international organizations. Australia, Germany, Switzerland, and
the UK also have large ongoing longitudinal panel studies that examine well-being (Diener et al., 2009).
International organizations like Gallup also assess well-being through the Gallup World Poll as well as the
Gallup-Healthways Index of Well-being.
Besides implementing national accounts of well-being, several nations have also appointed
government officials to monitor and enhance the well-being of their citizens. For example, the United Arab
Emirates (UAE) has a Minister of State for Happiness, whose main role is to institute programs that
enhance the well-being of people living in the UAE. Ecuador also has a Minister of Good Living, who
occupies a post similar to that of UAE’s Minister of Happiness. As part of her goal to enhance the wellbeing
of people living in the UAE, Her Excellency Ohood Al Roumi has recently implemented a 100-day
program of positivity in schools, where children learn about and practice positive interactions with others.
In addition, the UAE also collaborated with the University of Pennsylvania’s Positive Psychology Center to
create the Happiness & Positivity Program for the Private Sector, which aims to equip UAE private sector
employees with intuitive and practical skills to become the drivers of happiness and positivity in their
respective organizations.
Some Objections Answered
Some skeptics have argued that well-being is an individual’s affair, and governments should not
interfere with such a personal issue by telling people how they should live. This objection disregards the
fact that governments already intervene in numerous aspects of their citizens’ lives through taxes, laws and
other policies. Furthermore, there are legitimate consequences of well-being beyond the individual level
991
that allow us to question whether well-being is only an individual concern. Besides the societal benefits of
well-being that we reviewed earlier, there is also evidence that an individual’s well-being (or ill-being) can
influence the well-being of people around them. For example, caregivers who were caring for family
members suffering from medical illnesses often report low levels of well-being and are often found to have
a higher risk for depression (Hooley, Butler, & Howlett, 2005; Visser-Meily et al., 2005). Moreover, what
has been perceived as private and beyond the interference of governments has varied over the years. For
example, the choice to smoke was once thought to be an individuals’ affair as well. However, as increasing
evidence suggests that smoking is detrimental not only to the individual, but to society as well, the
perception that smoking is an individual choice also begun to fade, and governments now often institute
policies to discourage smoking.
Another common objection raised against accounts of well-being has been that well-being is nothing
more than hedonism, the pursuit of pleasure and self-indulgence. Thus, striving for high well-being is a
luxury and not a basic need. This criticism is a misconception because a plethora of research has
demonstrated that high SWB is associated with positive outcomes. For example, SWB is substantially
increased when basic needs of citizens are met (Tay & Diener, 2011) and when gains in economic resources
are allocated to meeting the basic needs of people (Diener et al., 2013). Other than the outcomes observed
for health, social relationships, and other achievement-related outcomes that we previously reviewed, high
SWB is also beneficial for being prosocial, organizational citizenship, work performance and business
productivity (Tenney et al., 2016). For example, higher SWB is associated with volunteering more (Oishi,
Diener, & Lucas, 2007), more frequent blood donations (Priller & Schupp, 2011). People high in positive
affect also reported being more creative (Johnson, Waugh, & Fredrickson, 2010), and lower job turnover
(Griffeth, Hom, & Gaertner, 2000).
Conclusions
Economic and social indicators have long dominated national accounts. However, these indicators
have limitations and large blind spots, often omitting important characteristics that contribute to quality of
life. Therefore, indicators of SWB should be incorporated into national accounts, not to replace existing
economic and social indicators, but to complement them. By including indicators of SWB into national
accounts, we broaden the information available to policy makers and enable them to design more effective
policies that improve the lives of their constituents.
Since Diener (2000) first proposed the use of national accounts of SWB, there has been significant
acceptance and implementation of the idea by governments, organizations, and behavioral scientists alike.
Several nations now have parliamentary members overseeing initiatives to ensure the well-being of their
citizens. Over forty nations have assessed SWB in the surveys they conduct, and behavioral scientists have
also begun to analyze these data to determine the policy implications of specific research findings. Going
forward, we hope to convince more nations of the benefits in measuring SWB in national statistics and for
more collaboration between policy makers and scientists to examine the implications of research findings
on public policy. In particular, more evidence is required to confirm the hypothesis that adoption of
national accounts of SWB is beneficial for citizens’ well-being both in the short and long term.
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