Psychological vulnerability, resilience, and subjective well-being:
The mediating role of hope
Seydi Ahmet Satici
Artvin Coruh University, Faculty of Education, Department of Psychological Counseling and Guidance, 08000 Artvin, Turkey
a b s t r a c ta r t i c l e i n f o
Article history:
Received 7 March 2016
Received in revised form 20 June 2016
Accepted 22 June 2016
Available online 2 July 2016
The present study examined the mediating role of hope on the association between psychological vulnerability,
resilience, and subjective well-being. Participants include 332 undergraduates (195 females and 137 males) from
two universities in Turkey. Data were collected using the Psychological Vulnerability Scale, the Brief Resilience
Scale, the Dispositional Hope Scale, the Satisfaction with Life Scale, and the Positive and Negative Affect Schedule.
Structural equation modeling results indicated that hope fully mediated the impact of resilience on subjective
well-being and that hope partially mediated the impact of psychological vulnerability on subjective well-being.
Moreover, bootstrapping procedure revealed signiﬁcant links from psychological vulnerability and resilience to
subjective well-being through hope. Alternative models indicated mixed support for the variable ordering in
the structural model. These ﬁndings contribute to the complex nature of the relationship between psychological
factors and subjective well-being. The possible explanations and limitations are discussed.
© 2016 Elsevier Ltd. All rights reserved.
Keywords:
Subjective well-being
Hope
Resilience
Psychological vulnerability
Students
1. Introduction
The scientiﬁc study on subjective well-being has been of interest in
the last three decades with the remarkable rise of the positive psychology
movement which focuses on the human strengths and virtues and
also building the best qualities in life (Seligman, 2002). As a human
strength, subjective well-being can be deﬁned as being satisﬁed with
life, experiencing long term affect of pleasure and feeling less negative
emotions. In other words, subjective well-being is a multidimensional
concept which refers a global appraisal of individuals' own life in
terms of cognitive dimensions including general life satisfaction and affective
dimensions which refer to the presence pleasant affect, and absence
unpleasant affect. Happy individuals experience high levels of
satisfaction with their lives, greater positive emotions, and less negative
emotions (Diener, 2000; Diener, Lucas, Oishi, 2002).
A bulk of research examined demographic variables that may predict
subjective well-being such as age, sex, socioeconomic status, educational
level, marital status, income (Vera-Villarroel, et al., 2012). Some
other researches have also focused the association between subjective
well-being and internal factors and human strengths like gratitude,
self-esteem, self-efﬁcacy, optimism, forgiveness, hope, meaning in life,
social self-efﬁcacy, loneliness and shyness (Hombrados-Mendieta,
Garcia-Martin, & Gomez-Jacinto, 2013; Li, Shi, & Dang, 2014; Snyder &
Lopez, 2007). In a longitudinal study, it was yielded that positive psychological
constructs, positive emotions, stress and anxiety may be signiﬁcant
predictors of well-being (Avey, Wernsing, & Mhatre, 2011).
Previous studies have indicated that resilience that can be accepted
as a human strength may have a substantial impact on subjective
well-being (Doyle et al., 2015; Liu, Wang, & Lü, 2013). Resilience has
been deﬁned broadly and variously over the years. While Thornton
and Sanchez (2010, p.455) deﬁned resilience as a “dynamic process
that enables the individual to respond or adapt under adverse situations”,
Connor and Davidson (2003, p.76) deﬁned it as “as the personal
qualities that enable one to thrive in the face of adversity”. People who
are resilient are more persistent in the face of adversity, can struggle
better with threatening circumstances, deal effectively with stress and
hardship, have more capacity to respond life stressors and cope better
with everyday difﬁculties (Mandleco & Perry, 2000; Smith, 2006).
Resilience involves positive patterns of adaptation in deﬁance of adversity
and this adaptation process develops over time (Wright, Masten,
& Narayan, 2013). Connor and Davidson (2003) have discussed resilience
as an important target of treatment in maladaptive situations
such as anxiety and depression. Ong, Bergeman, Bisconti, and Wallace
(2006) suggested over time high-resilient individuals may recover effectively
from daily stress. Therefore, resilience can be seen as an important
predictor to enhance subjective well-being. Similarly, studies
indicated that resilience was positively related to mindfulness, positive
affect, and life satisfaction, happiness, extraversion and negatively related
to negative affect and neuroticism (Bajaj & Pande, 2015; Lü, Wang, &
Zhang, 2014).
Personality and Individual Differences 102 (2016) 68–73
E-mail address: sasatici@anadolu.edu.tr.
http://dx.doi.org/10.1016/j.paid.2016.06.057
0191-8869/© 2016 Elsevier Ltd. All rights reserved.
Contents lists available at ScienceDirect
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journal homepage: www.elsevier.com/locate/paid
Contrary to resilience that has also been termed as “invulnerability”
psychological vulnerability can be seen as a negative predictor of subjective
well-being. The vulnerability can be deﬁned as at risk for developing
psychopathology and susceptibility to undesirable outcomes
(Wright, et al., 2013). Sinclair and Wallston (1999, p.102) suggested
that psychological vulnerability refers to cognitive structures which
make individuals more fragile to stress and described it as a “pattern
of cognitive beliefs reﬂecting a dependence on achievement or external
sources of afﬁrmation for one's sense of self-worth”.
Psychological vulnerability is a natural result of being human and
each individual was endowed with a degree of vulnerability which
may cause psychological problems in cases of experiencing stressful
conditions (Zubin & Spring, 1977). Previous literature on psychological
vulnerability indicated that there was a positive relationship between
psychological vulnerability and negative affect and depressive symptoms.
On the other hand, the psychological vulnerability was negatively
correlated with positive affect, life satisfaction, dispositional optimism,
and self-efﬁcacy (Sinclair & Wallston, 1999). Additionally, some research
suggests that there is a link between the psychological vulnerability
and adaptive constructs which are closely associated with
subjective well-being such as life satisfaction, social safeness and
ﬂourishing (Satici, Uysal, Yilmaz, & Deniz, 2016; Uysal, 2015).
1.1. Hope as a mediator
Hope as a human psychological strength is the cognitive process that
helps people to have positive expectation to reach desired goals and to
perceive that these goals can be met. Hope has been deﬁned as “a cognitive
set that is based on a reciprocally derived sense of successful
agency (goal-directed determination) and pathways (planning to
meet goals)” (Snyder et al., 1991, p.571). Therefore, hope consists of
three components: (a) goals which refer anything that an individual
has a wish to get or reach, (b) pathway thinking which refers producing
different or possible ways and planning routes to reach these goals and
(c) agency thinking that refers tendency to develop and maintain motivation
to meet desired goals, and having energy to use pathways to
achieve goals (Snyder, 2002; Taysi, Curun, & Orcan, 2015).
Snyder (2002) suggested that hope is an important factor for people
with lower well-being and is positively related to psychological wellbeing,
and physical health. Findings from recent studies have also revealed
that hope is a signiﬁcant predictor of life satisfaction, positive affect,
negative affect and ﬂourishing (Demirli, Türkmen, & Arık, 2015).
High-hope individuals evaluate stressful situations as challenging rather
than threatening and judge situations generally in positive ways (Rubin,
2001). These individuals are also conﬁdent, energized, and experience
lower levels of depression (Snyder, 1999). Additionally, hope was
found positively linked with increased self-esteem, positive thoughts,
optimism, psychological well-being, physical health and resilience and
negatively linked with depression and externalizing behaviors
(Karaırmak, 2007; Snyder, 2002; Snyder & McCullough, 2000). In their
study which has a longitudinal conceptual framework, Meeks et al.
(2016) proved that hope may be related to quality of life, social support,
and anxiety. Valle, Huebner, and Suldo (2006) indicated that individuals
who state higher levels of hope were more likely to report higher levels
of life satisfaction a year later. Hope was also found as a factor that promotes
resiliency and a positive inner source for both future and presentoriented
life (Granek et al., 2013). Additional studies indicated that
hope may act as a mediator between adaptive variables like life satisfaction
and maladaptive variables like psychological distress (Rustoen,
Cooper, & Miaskowski, 2010). Therefore, hope might play a signiﬁcant
role in the inﬂuence of resilience and psychological vulnerability on
subjective well-being.
In this paper, it was aimed to investigate the possible mediating role
of hope in path analyzes and it was hypothesized that hope would mediate
the relationships between resilience, psychological vulnerability,
and subjective well-being on cross-sectional data. In other words, it
was proposed that while resilience may facilitate the development of
hopeful thinking, psychological vulnerability may inhibit hope, and
hopeful thinking may lead to high or low levels of subjective wellbeing.
Although most previous studies indicated that hope may mediate
the relationships between different variables, to our knowledge, no
study has compared the relationships of resilience, psychological vulnerability
and subjective well-being in a Turkish sample.
2. Method
2.1. Participants and procedure
A cross-sectional survey was conducted between October 2015 and
December 2015 with 332 [195(58.7%) female, 137(41.3%) male] voluntary
university students in Istanbul and Eskisehir, two large-sized cities in
the northwest and middle part of Turkey. The mean age of the participants
was 20.96 years (SD = 2.01). Participants were attending classes
in one of the four grades of higher education (26.2, 22.9, 21.7 and 29.2%
were in the ﬁrst, second, third and fourth year, respectively). Table 1
shows detailed demographic and socioeconomic variables. We excluded
14 participants from the analyzes due to missing data. The questionnaires
were administered to classroom groups (40 to 60 students) in
paper-and-pencil based format in the classroom. The participants
were not given any promise of reward. The questionnaires were
counterbalanced to control for sequential effect. 8 booklets were designed
in a way which each questionnaire can appear at the beginning
and/or at the end of the booklet. Since the questionnaires were anonymous,
individual participants could not be identiﬁed. We explained
that participants could withdraw from the study whenever they want.
Each participant took about 15 to 20 min to complete the measures.
2.2. Measures
2.2.1. Subjective well-being
Subjective well-being was measured by Positive and Negative Affect
Schedule (PANAS; Watson, Clark, & Tellegen, 1988) and Satisfaction
with Life Scale (SWLS; Diener, Emmons, Larsen, & Grifﬁn, 1985). The
PANAS is designed to assess affective dimension of the subjective
well-being. The PANAS consists of two 10-items scales; positive affect
(PA) and negative affect (NA), rated on a 5-point Likert scale (1 =
very slightly or not at all to, 5 = extremely). Possible scores range
from 10 to 50 with higher scores reﬂecting positive or negative affect.
The Turkish version of PANAS was adopted by Gencoz (2000). Gencoz
reported that Cronbach alpha coefﬁcient 0.83 and 0.86 for PA and NA,
respectively. The SWLS is designed to assess cognitive dimension of
the subjective well-being. The SWLS consist of ﬁve items (e.g. If I
could live my life over, I would change almost nothing). Responses
Table 1
Participant characteristics.
Variable n Valid %
Gender
Female 195 58.7
Male 137 41.3
Academic majors
Psychological Sc. 54 16.3
Educational Sc. 69 20.8
Sciences 35 10.5
Arts/Humanities Sc. 67 20.2
Economics Sc. 74 22.3
Engineering Sc. 33 9.9
Perceived socio-economic status
Very poor 19 5.7
Poor 77 23.2
Moderate 139 41.9
Good 72 21.7
Excellent 25 7.5
69S.A. Satici / Personality and Individual Differences 102 (2016) 68–73
were made on a 7-point Likert scale (1 = Strongly disagree and 6 =
Strongly agree). Higher scores indicate greater satisfaction with life.
The Turkish version of SWLS was adopted by Durak, Senol-Durak, and
Gencoz (2010). Durak and colleagues reported that Turkish version of
the SWLS has acceptable reliability (Cronbach alpha: 0.81) and validity
(CFA: χ2
/df = 2.026, IFI = 0.99, TLI = 0.99, CFI = 0.99, SRMR = 0.020,
and RMSEA = 0.043). In the present study, the SWLS and PANAS have
acceptable Cronbach alphas; 0.81, 0.79, 0.80, for SWLS, PA, and NA,
respectively.
2.2.2. Hope
Hope was measured by Dispositional Hope Scale (DHS; Snyder, et al.,
1991) which is designed to assess an individual's general or characteristic
level of hope. The DHS is a 12-item including four ﬁller items questionnaire
that generates scores based on two subscales: agency (e.g.
my past experiences have prepared me well for my future) and pathway
(e.g. I can think of many ways to get the things in life that are important
to me). Responses were made on an 8-point Likert scale (1 = Deﬁnitely
false and 6 = Deﬁnitely true). Higher scores indicate greater hope. The
Turkish version of DHS was adopted by Tarhan and Bacanlı (2015).
Tarhan and Bacanli reported that Turkish version of the DHS has acceptable
reliability (Cronbach alpha: 0.84) and validity (CFA: GFI = 0.96,
AGFI = 0.92, NNFI = 0.94, RFI = 0.90 CFI = 0.96, and RMSEA =
0.077). In the present study, the DHS have acceptable Cronbach alphas;
0.75, 0.81, for agency and pathway, respectively.
2.2.3. Resilience
Resilience was measured by Brief Resilience Scale (BRS; Smith, et al.,
2008) which is designed to assess the ability to bounce back or recover
from stress. The BRS is a 6-item (I tend to bounce back quickly after hard
times). Responses were made on a 5-point Likert scale (1 = Strongly
disagree and 5 = Strongly agree). Higher scores indicate greater resiliency.
The Turkish version of BRS was adopted by Doğan (2015).
Dogan reported that Turkish version of the BRS has acceptable reliability
(Cronbach alpha: 0.83) and validity (CFA: χ2
/df = 1.83, NFI = 0.99,
NNFI = 0.99, CFI = 0.99, IFI = 0.99, RFI = 0.97, GFI = 0.99, AGFI =
0.96, RMSEA = 0.05, and SRMR = 0.03). In the present study, the BRS
have acceptable Cronbach alpha (0.87).
2.2.4. Psychological vulnerability
The psychological vulnerability was measured by Psychological Vulnerability
Scale (PVS; Sinclair & Wallston, 1999). The PVS is 6-item (e.g.
I tend to set my goals too high and become frustrated trying to reach
them). Responses were made on a 5-point Likert scale (1 = Unsuitable
to me and 5 = Suitable to me). Higher scores indicate greater psychological
vulnerability. The Turkish version of PVS was adopted by Akın
and Eker (2011). Akin and Eker reported that Turkish version of the
PVS has acceptable reliability (Cronbach alpha: 0.75) and validity
(CFA: NFI = 0.97, GFI = 0.99, AGFI = 0.98, RFI = 0.95, SRMR =
0.025, and RMSEA = 0.00). In the present study, the PVS have acceptable
Cronbach alpha (0.70).
2.3. Data analysis
First, an initial correlational analysis was used to examine the relationships
between subjective well-being, resiliency, psychological vulnerability,
and hope measures. Descriptive statistics (mean, standard
deviations, skewness, and kurtosis) were also tested via IBM SPSS Statistics
version 20.
The mediation role of hope was tested using the two-step structural
equation analysis procedure. Firstly, the measurement model
was calculated to assess whether each of the latent variables was
represented by its indicators. If the measurement model turns out
satisfactory, then the structural model can be tested using the maximum
likelihood estimation in the AMOS Graphics. To evaluate the
overall ﬁt of the model to the data, several indices recommended
by Hu and Bentler (1999) was calculated in the current study: χ2
/df
ratio, SRMR, RMSEA, CFI, GFI, and TLI. We also calculated AIC and
ECVI in order to ﬁnd the best model. For AIC and ECVI, smaller values
represent a better model ﬁt.
We estimated bootstrapping procedure with 10,000 bias-corrected
bootstraps 95% conﬁdence intervals (CIs). Bootstrapping procedure includes
the creation of an empirical representation of the population by
continuously resampling from the empirical sample for mimic the original
sampling process (MacKinnon, Lockwood, & Williams, 2004). They
recommended the use of the percentile bootstrap, which provides a CI
and has been shown to provide both reasonable controls of type 1
error and good statistical power. Applying this procedure, an indirect
role was signiﬁcant if zero was not included in the computed CIs.
3. Results
3.1. Correlation and descriptive statistics of variables
Descriptive statistics and bivariate correlations are displayed in
Table 2. Inspection of the skewness and kurtosis indices for all variables
in the study proved normal (skewness ranged from −0.81 to 1.05, and
kurtosis from −0.58 to 0.75). All the variables revealed signiﬁcant associations
with each other. As expected, positive affect and life satisfaction
were positively associated with hope and resilience and negatively associated
with psychological vulnerability. Conversely, negative affect
was positively associated with psychological vulnerability and negatively
associated with hope and resilience. These results provide a solid
foundation for structural equation model analysis.
3.2. Measurement model
There are four latent variables (subjective well-being, hope, resilience,
and psychological vulnerability) and 17 observed variables in
the measurement model. The ﬁt indices for the measurement model
were as follows: χ2
(113, N = 332) = 230.84, p b 0.001; CFI = 0.93;
GFI = 0.92; TLI = 0.92; SRMR = 0.056; RMSEA = 0.056 C.I. [0.046,
0.066]. Values of the ﬁt indices showed that the measurement model
had an adequate ﬁt. All indicators loaded signiﬁcantly their corresponding
latent constructs (ranged −0.52 to 0.88, p b 0.001), indicating that
latent variables were adequately operationalized by the observed
variables.
3.3. Structural model
First, the role of hope as a full mediator between resilience/psychological
vulnerability and subjective well-being (Model I). This model revealed
an acceptable ﬁt to data: χ2
(115, N = 332) = 244.42, p b 0.001;
CFI = 0.93; GFI = 0.92; TLI = 0.91; SRMR = 0.063; RMSEA = 0.058
C.I. [0.048, 0.068]; AIC = 320.42; ECVI = 0.97. Then, we added links
(from resilience to subjective well-being and from psychological vulnerability
to subjective well-being). When these relationships were
added (Model II), the ﬁt was good: χ2
(113, N = 332) = 238.40,
p b 0.001; CFI = 0.93; GFI = 0.92; TLI = 0.92; SRMR = 0.057;
RMSEA = 0.056 C.I. [(0.046, 0.066)]; AIC = 314.82; ECVI = 0.954,
however, only the link from psychological vulnerability to subjective
well-being was statistically signiﬁcant, while the other added link
from resilience to subjective well-being was not signiﬁcant (β = 0.16,
p N 0.05). When this non-signiﬁcant link was removed (Model III), the
resulting model showed an satisfactory ﬁt to data: χ2
(114, N = 332) =
234.25, p b 0.001; CFI = 0.93; GFI = 0.92; TLI = 0.92; SRMR = 0.057;
RMSEA = 0.056 C.I. [0.046, 0.067]; AIC = 312.25; ECVI = 0.943.
According to Model III, consistent with it functioning as a mediator
resilience may have an indirect role on subjective well-being through
hope and psychological vulnerability both direct and indirect roles on
subjective well-being. The statistics associated with the path
coefﬁcients can be seen in Fig. 1.
70 S.A. Satici / Personality and Individual Differences 102 (2016) 68–73
3.4. Bootstrapping
The mediating role of hope between resilience, psychological vulnerability
and subjective well-being was tested for signiﬁcance using
the bootstrapping procedure. Table 3 shows the direct and indirect
roles and their associated 95% conﬁdence intervals. The indirect role involving
resilience as the predictor was statistically signiﬁcant (bootstrap
estimate = 0.25, 95%CI = 0.13, 0.40), indicating that hope signiﬁcantly
mediated the relationship between resilience and subjective well-being.
Moreover, the indirect role involving psychological vulnerability as the
predictor was statistically signiﬁcant (bootstrap estimate = −0.19,
95%CI = −0.32, −0.09), indicating that hope signiﬁcantly mediated
the relationship between psychological vulnerability and subjective
well-being.
3.5. Alternative models
We examined various alternative models due to the cross-sectional
nature of the data. These various models consisted of varied associations
among the study variables. If these various models supported lower ﬁts
to the data, they would further promote the present theoretical model.
The ﬁrst alternative model (Model IV) that include hope as an exogenous
variable, resilience, and psychological vulnerability as mediator
variables, and subjective well-being as separate outcome variables
was tested. Results revealed that Model IV was not satisfactory ﬁt to
the data χ2
(115, N = 332) = 280.35, p b 0.001; CFI = 0.90; GFI = 0.90;
TLI = 0.88; SRMR = 0.068; RMSEA = 0.066 C.I. [0.056, 0.076]; AIC =
356.35; ECVI = 1.08.
In the second alternative model (Model V), hope was exogenous
variable, subjective well-being was a mediator variable, and resilience
and psychological vulnerability were outcome variables. Model V was
also low ﬁt to the data especially CFI = 0.89, GFI = 0.89, and TLI =
0.88; χ2
(116, N = 322) = 296.10, p b 0.001; SRMR = 0.71; RMSEA =
0.068 C.I. [0.059, 0.078]; AIC = 370.10; ECVI = 1.12. In respect to all
models' AIC and ECVI values, Model III had smaller AIC and ECVI values
than the other models (see Table 4). Also, Model III had the better ﬁt to
the data. In conclusion, the preferred ﬁnal model suggested that hope
fully mediated the role of resilience on subjective well-being and that
partially mediated the role of psychological vulnerability on subjective
well-being with cross-sectional data.
4. Discussion
Hope that helps individuals cope with various life challenges and
may serve to drive well-being of people can be deﬁned as a “unidimensional
construct involving an overall perception that goals can be met”
(Snyder, et al., 1991, p.570) and involves two interrelated cognitive
components: agency and pathways (Snyder, 2002). Research has
established that hope directly associated with positive outcomes,
Table 2
Correlations and descriptive statistics of the study variables.
Variable
Bivariate correlations Descriptive statistics
1 2 3 4 5 6 M SD Skewness Kurtosis
1. Positive affect – 30.56 6.74 −0.03 −0.09
2. Negative affect −0.25⁎⁎ – 20.74 6.71 1.05 0.75
3. Life satisfaction 0.32⁎⁎ −0.29⁎⁎ – 21.62 6.27 −0.36 −0.58
4. Agencyh
0.41⁎⁎ −0.28⁎⁎ 0.23⁎⁎ – 24.86 4.46 −0.81 0.30
5. Pathwayh
0.47⁎⁎ −0.30⁎⁎ 0.34⁎⁎ 0.68⁎⁎ – 23.32 4.27 −0.67 0.50
6. Resilience 0.31⁎⁎ −0.34⁎⁎ 0.19⁎⁎ 0.40⁎⁎ 0.40⁎⁎ – 18.90 4.85 −0.15 −0.29
7. Vulnerability −0.16⁎⁎ 0.37⁎⁎ −0.24⁎⁎ −0.25⁎⁎ −0.30⁎⁎ −0.34⁎⁎ 16.27 4.34 0.28 −0.21
Note. h
subscales of the hope.
⁎⁎ p b 0.01.
Fig. 1. Standardized factor loading for the ﬁnal structural model. Note. N = 332; **p b 0.01; PA positive affect; NA negative affect; LS life satisfaction; RItem items of the Brief Resilience Scale;
VItem items of the Psychological Vulnerability Scale
71S.A. Satici / Personality and Individual Differences 102 (2016) 68–73
adjustment and subjective well-being (Snyder, 2002). On the other
hand, lower levels of hope are connected with aversive variables
(Rustoen, et al., 2010). In this regard, the main goal of the present
study was to identify whether hope mediates the relationships between
resilience/psychological vulnerability and subjective well-being.
The full mediating role of hope was identiﬁed in the relationship between
resilience and subjective well-being based on cross-sectional
data which means that this result of the current study in concordance
with feeling high level of resilience may provide experiencing high
hope which helps to report more positive evaluations about cognitive
and affective dimensions of life. Although, to date, the bulk of research
have examined the link between resilience and subjective well-being
(i.e., Liu et al., 2013; Lü, Wang, Liu, & Zhang, 2015) no other study has
investigated the possible mediator role of hopeful thinking in this relationship.
Our ﬁndings may consistent with the ﬁndings of Magaletta
and Oliver (1999) who reported that hope as a cognitive set “might reﬂect
a positive orientation toward experience and that might thus contribute
to well-being (p.549)”. The research stated that hope may be an
essential component of resilience and helps individual to alleviate the
effects of stress on health (Werner, 1993). According to Wu (2011) resilience
is positively related with hope and both of these constructs
have a direct positive inﬂuence on life satisfaction. Similarly, Gillespie,
Chaboyer, and Wallis (2007) claimed that hope may be identiﬁed as a
deﬁning attribute of resilience. McCullough (2002) propounded that
hopeful individuals experience more positive emotions like zest and
evaluate stress as an opportunity to reach their goals. Additionally, several
studies found hope may be predictors of subjective well-being and
indicators of subjective well-being such as positive affect, negative affect,
forgiveness, quality of life and ﬂourishing (Demirli, et al., 2015;
Taysi et al., 2015; Wu, 2011). Thus, it can be said that this result of the
study is parallel with earlier studies.
Results which are also based on cross-sectional data indicated that
hope acted as a partial mediator of the relationship between psychological
vulnerability and subjective well-being. In other words, the ﬁndings
are consistent with individuals who have higher levels of vulnerability
being more likely to develop lower hopeful thinking, which in turn contributes
to lower subjective well-being. However, there may be models
that were not examined that would also be equally consistent with the
data. This result seems parallel with Rustoen and colleagues' (2001)
study that reported that hope mediated the relationship between psychological
distress and life satisfaction in a community sample of cancer
patients. Halama (2010) also remarked that hope acts as a partial mediator
between neuroticism which is signiﬁcantly associated with being
vulnerable to psychological problems and life satisfaction which is the
cognitive part of subjective well-being. Some additional studies revealed
that hope was negatively linked with maladaptive variables
such as depression, anxiety and loneliness (Arnau, Rosen, Finch,
Rhudy, & Fortunato, 2007; Lackaye & Margalit, 2008) and adaptive variables
such as optimism, coping styles, positive affect and self-efﬁcacy
(Lackaye & Margalit, 2008; Karaırmak, 2007). Hence, these ﬁndings
also seem to be consistent with previous literature.
As it was expected, correlational results showed that both resilience
and hope had positive relationships with subjective well-being. In addition,
the psychological vulnerability was found negatively associated
with resilience, hope, and subjective well-being. These ﬁndings are in
line with numerous studies that have examined the link between
these variables. Sinclair and Wallston (1999) demonstrated that psychological
vulnerability was positively related to negative affect and depressive
symptoms and negatively related to positive affect and life
satisfaction. Taysi and colleagues (2015) found that hope was negatively
related to anger and depression. Hope was also found as a signiﬁcant
predictor of subjective well-being (Şahin et al., 2012). Similarly, Tomas
et al. (2012) stated that resilience is also an important indicator of well-
being.
4.1. Limitations
Several limitations of the present study should be addressed. The
ﬁrst limitation of the current study is that the data was collected only
via self-report measures that may reduce the internal validity. Using
multiple methods to collect data may help to reduce the effect of subjectivity.
Besides, using different methods (e.g., observation and peer evaluation)
may be essential to measure the level of resilience and
vulnerability level. The second limitation is that the participations of
the study were university students living in two cities in Turkey. So, it
is limited to generalize of ﬁndings of the current study. The third limitation
is that this study has a cross-sectional design which makes cause
and effect interpretations difﬁcult. The relationship between hope and
resilience might be reversed with hope leading to resilience. Similarly,
some sort of reciprocal relationship might be found between hope and
psychological vulnerability. In order to overcome this limitation of the
study and to clarify the causal order, future research should use longitudinal
designs that permit stronger conclusions regarding the causal direction
of the variables. In addition, while it was seen that the best
well-ﬁtted model the model which examined in this study, it should
be considered the ﬁt indexes of alternative models were not low.
Thus, as suggested by Maxwell and Cole (2007) longitudinal data may
be used to examine mediation role which can provide a better understanding
of these variables. Clariﬁcation of timing and possible causal
order may also be clariﬁed with experimental studies. The last limitation
is that the mediating role of hope has been tested in the present
study, but other possible mediators need to be identiﬁed.
4.2. Implications
Despite the limitations mentioned above, the present study presents
some important contributions to the existing literature on positive psychology
through examining constructs like subjective well-being, hope,
and resilience. Counseling services and other professionals should consider
the role of hope and develop psycho-educational programs including
hope to increase well-being. Additionally, resilience is an
improbable and learnable trait (Luthar, Cicchetti, & Becker, 2000).
Therefore, counseling programs which aim to increase resiliency can
be an effective method to reduce psychological vulnerability and to enhance
subjective well-being.
Table 3
Parameters and 95%CIs for the paths of the ﬁnal model.
Model pathways Estimated
95%CI
Lower Upper
Direct link
Resilience➔Hope 0.380 0.226 0.507
Psychological vulnerability➔Hope −0.286 −0.443 −0.122
Psychological vulnerability➔Subjective
well-being
−0.308 −0.543 −0.078
Hope➔Subjective well-being 0.666 0.447 0.854
Indirect link
Resilience➔Hope➔Subjective well-being 0.253 0.125 0.403
Psychological vulnerability➔Hope➔Subjective
well-being
−0.190 −0.322 −0.088
Table 4
Fit indices among competing models.
Model χ2
CFI GFI TLI SRMR RMSEA AIC ECVI
I 244.42 0.93 0.92 0.91 0.063 0.058 320.42 0.97
II 238.40 0.93 0.92 0.92 0.057 0.056 314.82 0.95
III 234.25 0.93 0.92 0.92 0.057 0.056 312.25 0.94
IV 280.35 0.90 0.90 0.88 0.068 0.066 356.35 1.08
V 296.10 0.89 0.89 0.88 0.710 0.068 370.10 1.12
72 S.A. Satici / Personality and Individual Differences 102 (2016) 68–73
4.3. Conclusions
Analysis of the study proved the mediational role of hope between
resilience/psychological vulnerability and subjective well-being in a
sample of Turkish university students. Given that positive psychology
set out to determine the factors that may contribute subjective wellbeing,
the current study has provided more understanding for both
practitioners and researchers.
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