The Handbook of the Psychology of Communication Technology, First Edition. Edited by S. Shyam Sundar.
© 2015 John Wiley & Sons, Inc. Published 2015 by John Wiley & Sons, Inc.
22
Computer-Mediated Support for
Health Outcomes: Psychological
Influences on Support Processes
Kevin B.Wright
Department of Communication, George Mason University, Fairfax,VA, USA
The growth and popularity of computer-mediated support groups and other, less
formal, types of online social support (i.e., social support that occurs within Facebook
and other social media) has gained the attention of social support researchers in recent
years who are interested in the underlying psychological processes of social support
within this context (e.g., Barrera, Glasgow, McKay, Boles, & Feil, 2002; Gustafson
et al., 2005; Lieberman & Goldstein, 2005; Tanis, 2008). Scholars have been intrigued
by the potential of online support networks to supplement or replace traditional
face-to-face social support networks (Rains & Young, 2009; Wright & Miller, 2010).
Communication scholars and other social scientists have begun to examine the
implications of these innovations in terms of their impact on the process of how and
why individuals obtain online support, advantages and disadvantages of computermediated
support, and the relationship between online support and health-related
outcomes (i.e., reductions in physical symptoms, stress, depression, etc.). More
recently, scholars have begun to focus on computer-mediated support interventions
(see Gustafson et al., 2005), particularly among individuals who may lack access to
adequate support for their health concerns in their traditional face-to-face support
networks. Despite great strides in research during the past 15 years, many questions
regarding the psychological predispositions of computer-mediated support group
participants, social support processes within this context, and the relationships among
social support, behavioral change, and key health outcomes remain to be explored.
The purpose of this chapter is to provide an overview of the state of research in the
area of computer-mediated support and health outcomes with a focus on key
psychological variables and processes. Toward that end, the chapter examines the
growth and prevalence of computer-mediated support in the past two decades,
research on the perceived advantages and disadvantages of computer-mediated
support, key variables, and theoretical frameworks that are useful for understanding
	 Computer-Mediated Support for Health Outcomes Psychological Influences	 489
psychological processes related to computer-mediated support, common methods for
studying computer-mediated support, limitations of this body of research, and suggestions
for future theoretical and applied work in this area.
Prevalence and Growth of Computer-Mediated Support
Over the past two decades, paralleling the growth of the Internet, mobile technologies,
and new communication applications, we have witnessed a tremendous growth
in online social support activity. In recent years, various types of social media have
changed patterns of communication by increasing individuals’ connectivity, interactivity,
and direct participation in computer-mediated support (see Chou, Hunt,
Beckjord, Moser, & Hesse, 2009; Wright & Bell, 2003).
Fifty-nine percent of US adults, constituting 8 in 10 Internet users, seek health
information on the Internet (Fox, 2011). Of those online health information seekers,
60% have performed at least 1 of 11 social media activities assessed related to health
and health care, such as reading someone else’s commentary or experience about
health issues (Fox, 2011). Moreover, in addition to formal, disease-specific, computer-mediated
support groups, social support appears to be a common activity that
occurs within social networking sites, such as Facebook and Twitter (Steinfield,
Ellison, & Lampe, 2008; Wright, 2012).
Motivations for Participating in
Computer-Mediated Support Groups
Researchers have found that people have a variety of different motivations for participating
in computer-mediated support groups and other types of online support
(McKenna, 2008; McKenna & Green, 2002; Wright, 2002). Uses-and-gratifications
theory (Katz, Blumler, & Gurevitz, 1974) is a helpful framework in terms of examining
motives for using various types of media, including online communities
(Courtois, Merchant, De Marez, & Verleye, 2009; Ebersole, 2006; Wright, 2002).
These researchers have found motives to be important antecedent variables in terms
of understanding cognitive processes behind various communication-related behaviors,
such as the amount of time individuals spent online, relational development and
maintenance activities, and they ways in which individuals communicate with others
in virtual communities.
Researchers have identified a number of motives for using computer-mediated
support groups as well as differences in interaction based upon a persons’ motives.
One such motivation is the amount/quality of health information available within
online support communities. According to Purcell, Rainie, Mitchell, Rosenstiel,
and Olmstead (2010), 39% of Americans say there is not enough coverage of
health and medical news. This may in part account for the increasing number of
people going online for health information. Perceived risk and efficacy (as they
relate to health issues) have been shown to motivate information-seeking ­behaviors
490	 Kevin B.Wright
(Rimal & Real, 2003), including online health information seeking (e.g., Cline &
Haynes, 2001).
A second motive that has been identified in the online support literature is the
desire for emotional support and relationship formation (Buchanan & Coulson,
2007; Coulson & Knibb, 2007; Leimeister, Schweizer, Leimeister, & Krcmar, 2008).
Leimeister et al. (2008) found that both informational motives and interpersonal
motives for joining a virtual cancer support community were linked to the formation
of virtual relationships, and subsequently receiving support. Butler, Sproull, Kiesler,
and Kraut (2007) found that individuals who value the social benefits of an online
community are more likely to engage in community building activities (e.g., posting,
providing encouragement) compared to those who turn to the community for informational
benefits. By contrast, Nonnecke, Andrews, and Preece (2006) found
that ­informational motives for joining an online support group in the absence of
­socio-emotional support motives were linked to “lurking” (i.e., reading but not
posting messages) in the online community. Wright (2002) found that interpersonal
and social integrative motives predicted increased interpersonal communication,
relational development and maintenance, and social involvement in online support
communities. These findings suggest that members who are motivated solely by a
strong desire for information will be less active in providing support to others.
Perceived Advantages and Disadvantages
of Computer-Mediated Support
Early studies of computer-mediated support largely focused on participant perceptions
of advantages and disadvantages of using these groups. While largely descriptive,
these studies helped to identify key variables and processes that were subsequently
investigated in later work. The following section provides a brief overview of the
­findings related to perceived advantages and disadvantages of obtaining social support
in computer-mediated contexts.
Perceived advantages
According to studies of individuals who seek support in computer-mediated environments,
the Internet (and related new technologies) provides several advantages over
traditional face-to-face support, including broad reach, 24-hr availability, increased
interactivity with others, international participation, multimedia capabilities, and
greater anonymity (Cline & Haynes, 2001; Neuhauser & Kreps, 2008; Wright, 2002).
Researchers have also identified many other advantages of computer-mediated
support, including (a) reduced feeling of being stigmatized due to one’s health
condition (which I will discuss in greater depth later in the chapter), (b) it allows
­participants to be evaluated on their contributions to the group rather than their
physical appearance or disabilities (Wright, 2000), (c) convenience, (d) increased
opportunities for social comparisons, and (e) access to in-depth and diverse information
about a health condition (Wright, 2002). Moreover, the greater anonymity in online
	 Computer-Mediated Support for Health Outcomes Psychological Influences	 491
social interaction allows people who are reluctant to seek support in a face-to-face
setting to communicate with others in a straightforward and honest way about their
conditions and concerns (Caplan & Turner, 2007; Tidwell & Walther, 2002), and
participation within online support groups enhances the possibility that individuals
get incidental exposure to health information in addition to their active information
seeking online (Kontos, Emmons, Puleo, & Viswanath, 2010).
Perceived disadvantages
However, computer-mediated support groups have also been found to suffer from a
variety of problems, such as off-topic discussion, flaming, sporadic membership, and
other negative aspects, such as deception and cyberstalking (Caplan & Turner, 2007;
Wright, 2002; Wright & Bell, 2003).
Essentially, there are risks involved with obtaining social support online that may
potentially undermine perceptions regarding the credibility of support providers and
ultimately lead to dissatisfaction with the support that is offered within computermediated
support groups. For example, the anonymity of participants within these
groups may lead to flaming and other forms of unsupportive behavior (Barak, BonielNissim,
& Suler, 2008) and can make it more difficult than in face-to-face settings for
individuals to detect deception, insincerity, and alternative motives for using the
group (Hancock, 2007; Wright, 2002). This includes people within the groups who
are voyeurs, profiteers who hope to sell health-related products to participants, or
people who may have other motives for using the group (besides giving and receiving
support). These factors, as well as others, can potentially undermine the credibility of
online support providers and the usefulness of computer-mediated support groups for
obtaining adequate support.
Key Variables That Influence Participation in
Computer-Mediated Support
Health-related stigma
One variable that appears to be an important predictor of participating in some form
of computer-mediated support is the degree to which individuals perceive they are
stigmatized because of the issues they face (particularly health-related issues). Healthrelated
stigma is a significant problem that many individuals facing health concerns
have to deal with on a daily basis (Herek & Glunt, 1988). It has been linked reductions
in the size of individuals’ support networks, problems discussing concerns with
others, dissatisfaction with one’s support network, reduced compliance with treatment
recommendations, and increased health problems (Rosman, 2004; Vanable, Carey,
Blair, & Littlewood, 2006). Individuals with stigmatized health issues report increased
stress and depression (Riggs, Vosvick, & Stallings, 2007; Wolitski, Pals, Kidder,
Courtenay-Quirk, & Holtgrave, 2008), both of which have been linked to a multitude
of health problems, including alcohol and substance abuse, increased usage of
492	 Kevin B.Wright
tobacco products, anxiety and related mental health problems, reduced immune
system functioning, and increased physical health problems (Duncan, Hart, Scoular,
& Bigrigg, 2001).
Computer-mediated support groups can provide people with stigmatized health
problems greater access to online weak ties and weak-tie support (Wright & Bell,
2003; Wright, Rains, & Banas, 2010). These weak ties offer several advantages relative
to strong ties including being less judgmental and more objective, offering unique
information, and a reduced potential for role conflict (Wright & Miller, 2010).
Applied communication researchers (and applied scholars from other disciplines) have
become increasingly interested in computer-mediated support groups as a way to supplement
(or replace) traditional face-to-face support networks in the development of
interventions for individuals facing a variety of health concerns (Houston, Cooper, &
Ford, 2002; Shaw, Hawkins, McTavish, Pingree, & Gustafson, 2006). McKenna
(2008) found that becoming actively involved in a virtual community that focuses on
a stigmatized or secret aspect of one’s identity that was previously kept hidden leads
individuals to become more self-accepting of this aspect of themselves and to feel
more comfortable sharing that identity with others, thus becoming less socially isolated
and more socially connected with their face-to-face community.
Homophily
A second variable that appears to influence participation in computer-mediated
support is homophily, or the degrees to which members of a social network are similar
to one another in certain attributes or characteristics. Homophily predisposes people
to more attraction, trust, and understanding than one would find in dissimilar individuals.
Close, personal networks tend to be homophilous, although weaker ties
online can exhibit situational homophily (Walther & Boyd, 2002; Wright, 2000) in
terms of stressful situations that online communicators have in common. Similarity
between a sender and receiver may increase the persuasiveness of messages, and may
be especially important when new attitudes and beliefs are formed. For example,
Wang, Walther, Pingree, and Hawkins (2008) showed that perceived similarity of
support group members influenced perceptions of their credibility and, in turn, the
evaluation of health information they provided. Moreover, Wright (2000) and
Campbell and Wright (2002) found that homophily was a key perception that influences
social support satisfaction and perceptions of credibility of support providers
within health-related online support groups.
Perceptions of support provider credibility
A third important set of variables is perceptions of online support provider credibility.
For example, Robinson, Patrick, Eng, and Gustafson (1998) argue that several characteristics
of the Internet influence perceptions of source/information credibility,
including (a) improved opportunity to tailor messages; (b) the increased possibility
for users to remain anonymous, which may increase their willingness to engage in
more honest discussions; and (c) increased access to information and support on
	 Computer-Mediated Support for Health Outcomes Psychological Influences	 493
demand. The increased interactivity of computer-mediated communication (e.g., the
ability to post comments and receive feedback within on-line communities, etc.) is
also important to consider since individual users are able to ask direct questions of
information sources, which is generally impossible with traditional media. In addition,
the ability of members within the larger online community to read and respond to
online posts provides an opportunity for increased quality control of information
(Esquivel, Meric-Bernstam, & Bernstam, 2006). For example, information that does
not resonate with the experiences of members of the larger community may be subject
to greater scrutiny (Rieh & Belkin, 2000), a process similar to peer review.
Research conducted to date has shown that perceptions of online support group
credibility are associated with several noteworthy outcomes. Wright (2000) found
that two dimensions of source credibility, perceived competence and character, were
associated with the perceived similarity of other online support group members,
online support group network size and satisfaction with the support they received.
Similarly, Campbell and Wright (2002) found that these dimensions of source
credibility were associated with perceptions of situational similarity among online
support group members. Moreover, both dimensions of source credibility were associated
with perceptions of social support providers’ receptivity and status equality
within these groups.
Coping strategy predispositions
Finally, a fourth variable that is likely to influence social support processes within
computer-mediated contexts is the coping styles/predispositions of individuals who
seek support within this context. Stemming from Lazarus and Folkman’s (1984)
theory of psychological stress and coping, coping styles have received a substantial
amount of scholarly attention, particularly as they relate to social support (Billings &
Moos, 1981; Kohn, 1996). Coping can be defined as a persons’ ongoing cognitive
and behavioral efforts to manage external or internal demands that are appraised as
taking or exceeding a person’s resources (Lazarus & Folkman, 1984). Studies suggest
that problem-focused coping, which is “directed at remedying a threatening or harmful
external situation” (Kohn, 1996, p. 189), is often linked with positive adaptation
to stressful situations (Heady & Wearing, 1990; Lazarus & Folkman, 1984), while
emotion-focused coping, which is defined as “ventilating, managing, or palliating an
emotional response to a situation” (Kohn, 1996, p. 189), is typically associated with
negative adaptation (Billings & Moos, 1981; Kohn, 1996). However, problemfocused
coping strategies are more likely to be used when a situation is appraised as
changeable whereas emotion-focused strategies tend to be used when a situation is
assessed as unchangeable (Folkman, Lazarus, Dunkel-Schetter, DeLongis, & Gruen,
1987). As a result, sometimes emotion-focused coping can lead to positive outcomes,
although to a lesser extent than we typically see with problem-focused coping. In the
context of research on computer-mediated support groups, Wright (1999, 2000)
found that support group participants who were more satisfied with the support
provided by other group members were more likely to use problem-focused coping
strategies than individuals who had lower support network satisfaction scores.
494	 Kevin B.Wright
Prominent Theoretical Frameworks in
Computer-Mediated Support Research
Theory plays an important role in terms of understanding social support processes
and outcomes within computer-mediated contexts. This section presents several theories
that have been applied to the study of computer-mediated social support. While
many early studies of computer-mediated support tended to lack strong theoretical
frameworks, more recent work has become more theoretically rich, with scholars testing
various hypotheses derived from theory in many studies of computer-mediated
support. These theories appear to have utility in terms of providing explanations of
online support processes as well as helping scholars to predict relationships among
variables.
Social support and the optimal matching model
One theoretical framework that has received a good deal of attention in the computer-mediated
support literature is the optimal matching model (Cutrona &
Russell, 1990). For many years, social scientists have known that people often differ
in terms of the types of support they find useful due to factors such as the context of
the stressful situation they are facing, their perceived coping skills, and their relationship
with the support provider (Cutrona & Russell, 1990). The optimal matching
model (Cutrona & Russell, 1990) suggests that matching the specific type of support
offered with the dimensions of a stressor (e.g., desirability, controllability, life
domain, and duration of consequences) produces the most positive outcomes. More
generally, the model is grounded in the notion that a match between the needs of
support seekers and the resources/abilities of support providers is important in
terms of coping with the many relational challenges associated with communicating
social support. For example, if an individual is seeking emotional support for a health
concern and he or she perceives that members of his or her support network
have competently listened, expressed empathy, and acknowledged the severity of the
issue, then this would be considered an example of an optimal match between the
support seeker and support providers.
People tend to make decisions regarding approaching potential supporters based
on the perception that members of their network will be able to meet their specific
need(s) for support as well as their relational needs. Goldsmith (2004) contends
that optimal matches in supportive episodes may lead to more positive perceptions
of relational partners and the type of support that is being offered, and this, in
turn, may ultimately influence positive health outcomes. Yet it is also possible that
a recipient of support may perceive some types of support negatively (which is
often the case among strong ties who react negatively to stigmatized health conditions),
and this may negate the positive effects of the supportive attempt or it
may actually have a negative impact on health or quality of life (Dakof & Taylor,
1990). There is evidence to suggest that weak ties accessed via ­computer-mediated
­communication might be particularly valuable when strong ties are unable or
unwilling to provide support.
	 Computer-Mediated Support for Health Outcomes Psychological Influences	 495
This perspective may help to provide important insights into the supportive needs
of individuals who seek computer-mediated support. For example, drawing upon an
optimal matching theory framework, Eichhorn (2008) found that informational
support through shared experiences was the most common type of support for members
of an online support groups for eating disorders (followed by emotional support).
Moreover, Sullivan (2003) found that men were more likely to seek informational
support within online support groups, whereas women were more likely to seek emotional
support and validation.
Social comparison theory
Social comparison theory (Festinger, 1954) has been useful in terms of examining
perceptions of people within our support networks and for understanding why
support from these individuals may not always lead to positive outcomes. According
to social comparison theory, individuals make assessments about their own health and
coping mechanisms by comparing them to others in their social network (Helgeson
& Gottlieb, 2000).
Helgeson and Gottlieb (2000) mention that lateral comparisons, comparisons to
similar others, may normalize people’s experiences and reduce uncertainty and stress
for those dealing with health concerns. However, when individuals compare ­themselves
to others, their self-assessment could be either positive or negative. For example, if a
person with cancer feels that he is coping with problems less effectively than others in
his network (such as a friend or relative who has or had cancer or a similar life-­
threatening illness), this may create upward comparisons, which could produce feelings
of frustration or serve as a source of inspiration to the person to cope more effectively
by emulating the successful behaviors of those other members. Conversely, downward
comparisons to others in the social network, such as when an individual feels that he or
she is coping better than other members, can lead to positive self-assessments and/or
to negative feelings about people if interaction with the other members is perceived as
being unhelpful.
Participants often glean information about the status of their health issues through
social comparisons that take place within supportive interactions (Davison, Pennebaker,
& Dickerson, 2000). According to Sarasohn-Kahn (2008), the second most popular
reason people seek health information through online social networks is to research
other participants’ experiences with a health condition. Such social comparison processes
do not even require actual participation in the online group; rather, individuals may
engage in these practices passively by reading the posted group discussions.
Social information processing theory
One computer-mediated communication theory that has been useful in terms of understanding
the effects of computer-mediated channels on the perceptions of individuals
who engage in online social support is social information processing theory (Walther,
1992; Walther, 2007). Walther (1992) asserts that within the context of computermediated
communication, message senders portray themselves in a socially favorable
496	 Kevin B.Wright
manner to draw the attention of message receivers and foster anticipation of future
interaction. Message receivers, in turn, tend to idealize the image of the sender due to
overvaluing minimal, text-based cues. Idealized perceptions and optimal self-presentation
in the computer-mediated communication process tend to intensify in the feedback
loop, and this can lead to what Walther (1996) labeled as “hyperpersonal interaction,”
or a more intimate and socially desirable exchange than in face-to-face interactions.
Hyperpersonal interaction is enhanced when no face-to-face relationship exists, so
that users construct impressions and present themselves “without the interference of
environmental reality” (Walther, 1996, p. 33), and it appears to skew perceptions of
relational partners in positive ways, and in some cases, computer-mediated relationships
may exceed face-to-face interactions in terms of intensity (King & Moreggi,
1998; Walther, 1996; Wright & Bell, 2003). Moreover, according to Walther (1996),
the reduced number of available nonverbal cues in CMC increases message-editing
capabilities, and the temporal features of CMC allow communicators to be more
selective and strategic in their in self-presentation, form idealized impressions of their
partners, and, consequently, engage in more intimate exchanges than people in
face-to-face situations. For instance, Walther, Slovacek, and Tidwell (2001) found
that individuals rated online interaction partners as more socially attractive and affectionate
when a photo was not present compared to those who did view a photo of the
interaction partner. In addition, dyads in computer-mediated settings also appear to
self-disclose more than face-to-face dyads (Tidwell & Walther, 2002).
Strength of weak ties
Several of the preceding theories suggest that some individuals may benefit from characteristics
of online networks in terms of obtaining optimal support. One theory that
links social support processes to social network characteristics is Granovetter’s Strength
of Weak Ties theory (1973). This theory posits that the spread of social support is
dependent upon the structure of communication networks in communities.
Specifically, personal networks are made up of strong ties (such as close friends and
family), weak ties (such as coworkers, acquaintances, and people with whom one has
infrequent contact), and absent ties. Small clusters made up of an individual and his
or her strong ties may be linked to other strong tie clusters by weak ties. Without
weak ties, communication can only flow among small clusters, and groups become
information saturated. Weak ties reach larger numbers of people, and longer distances
than strong ties. The strength of weak ties theory is essential in adding an element of
structure to understanding online supportive interactions and for distinguishing the
roles and relationships inherent in the different positions people hold within online
networks.
Individuals often seek support through weak tie networks instead of within their
strong tie network because weak tie networks can provide access to more diverse
points of view and information that may not be available within more intimate relationships
(Adelman, Parks, & Albrecht, 1987; Haythornthwaite, 2002). Typically,
individuals form close relationships with others who are similar to them in terms of
demographics, attitudes, and backgrounds. This homogeneous preference can limit
	 Computer-Mediated Support for Health Outcomes Psychological Influences	 497
the diversity of information and viewpoints obtained about topics, including health
concerns. Access to more diverse viewpoints about health problems can provide individuals
with more varied informational support about health issues, and interacting
with varied types of people increases the number of social comparisons a person can
make about his or her health condition vis-à-vis others (Adelman et al., 1987).
The advantage of weak tie sources are that there are more of them, they are more
likely to be different from the receiver and from one another, and there’s a greater
likelihood of being able to find an expert in a particular area in weak tie rather than
strong tie sources. Members of weak tie networks may be more willing to talk about
illness since these individuals tend to be less emotionally attached to a person (Adelman
et al., 1987). Weak tie network members are often able to provide more objective
feedback about a problem since they are less emotionally attached to a person with
health problems than family and friends. People with whom we have close relationships,
in an effort to spare our feelings when talking about a health problem, may be
more likely to “sugar coat” the advice they give us or not be completely honest when
discussing how they feel about our illness. According to Goldsmith and Albrecht
(2011), weaker ties tend to be perceived as helpful when a person is coping with an
issue that requires new information or skills (that may be limited within a close-knit
family or friendship social network).
In addition, studies have found that role obligations in close ties and reciprocity
issues can lead to problems with the provision of social support. Support for a
loved one who is ill in close ties can lead to increased conflict or negative feelings
toward the person due to role obligations (Albrecht & Goldsmith, 2003; LaGaipa,
1990), despite the fact that people may care deeply for the person. According to
LaGaipa (1990), “social obligations may override the positive effect of companionship
and social support. Such constraints can have a negative effect on mental
well-being that may not make up for the beneficial aspects of personal relationships”
(p. 126). All of these features of weak ties can be beneficial to people who
are coping with stressful situations that may be difficult to ameliorate in strong ties
due to lack of information and relational problems in close relationships, and access
to weak ties is facilitated by the features of computer-mediated communication
(Wright & Miller, 2010).
Health Outcomes Related to
Computer-Mediated Social Support
Decades of social support research have linked improved social support to a variety of
positive physical and mental health outcomes, such as increased health literacy,
reduced stress, increased coping abilities, lower depression levels, greater adherence
to treatment, and reduced morbidity and mortality rates (Barrera et al., 2002; Rains
& Young, 2009). Communication researchers have contributed to this body of literature
by providing a broader understanding of social support processes by examining
characteristics of supportive messages (Goldsmith, 2004), and the relationship between
social support processes and health outcomes among individuals living with a
498	 Kevin B.Wright
variety of health conditions (Braithwaite, Waldron, & Finn, 1999; Query & Wright,
2003), and by demonstrating how several key aspects of supportive relationships play
critical roles in both psychological and physical health.
Researchers have known for decades that perceived life stress is inversely related to
many physical and psychological health outcomes, including increased blood
pressure, reduced immune system response, cardiovascular disease, morbidity and
mortality rates, depression, and loneliness (Aneshensel & Stone, 1982; Berg &
McQuinn, 1989; Berkman & Syme, 1979; Houston et al., 2002). Perceived stress is
also associated with perceived quality of life and general physical/psychological
well-being.
In recent years, a growing number of studies have measured psychological and
physical health outcomes related to participation in computer-mediated support
groups (Barrera et al., 2002; Rains & Young, 2009; Wright, 2000). There is empirical
evidence that these groups provide a wide variety of health benefits for users (such as
individuals with cancer, diabetes, and substance abuse problems), including reduced
stress, increased positive coping, increased quality of life, increased self-efficacy in
terms of managing one’s health problems, reduced depression, and increased physical
health benefits (Beaudoin & Tao, 2007; Gustafson et al., 2005; Houston et al., 2002;
Jones et al., 2008; Owen, Klapow, Roth, Shuster, & Bellis, 2005; Rains & Young,
2009; Shaw et al., 2006; Wright, 1999, 2000).
Wright (2000) provided evidence that participation in a computer-mediated
support community for older adults predicted reduced stress and increased coping
skills. Owen et al. (2005) discovered that participation within an online support group
for cancer patients predicted higher quality of life and reduced stress. In addition, in
a recent meta-analysis of 28 computer-mediated support group studies, Rains and
Young (2009) found that participation in computer-mediated social support groups
led to increased social support, decreased depression, increased quality of life, and
increased self-efficacy in terms of managing health conditions. Two decades of
research on the Comprehensive Health Enhancement Support System (CHESS) has
demonstrated positive health outcomes for women with breast cancer and people
with HIV/AIDS, such as reduced stress, fewer healthcare visits and hospitalizations,
and fewer incidents of disease symptoms (Gustafson et al., 1999, 2001). Wright et al.
(2010) found that characteristics of weak-tie support network preference among
members of health-related, computer-mediated support groups were predictive of
reduced stress surrounding health problems. Other researchers have found similar
health benefits for individuals who obtain social support within social networking sites
(see Ellison, Steinfield, & Lampe, 2007; Kim & Lee, 2011; Manago, Taylor, &
Greenfield, 2012; Wright et al., 2013).
Finally, the act of helping others appears to be associated with reduced stress and an
increase sense of well-being. For example, Caplan and Turner (2007) contend that
effective comforting communication within computer-mediated support groups fosters
adaptive cognitive reappraisals of upsetting experiences, which in turn ameliorate
emotional distress. Caplan and Turner (2007) assert that comforting communication
helps on-line support group members to reduce stress by “discursively constructing”
adaptive, or less troublesome, cognitive reappraisals of a distressing experience or
situation during the process of comforting other members.
	 Computer-Mediated Support for Health Outcomes Psychological Influences	 499
Prominent Methods Used in
Computer-Mediated Support Research
Researchers have used a variety of methods to study computer-mediated social support,
including survey research, content analysis, experimental designs, and naturalistic
research. My own research and work with colleagues (Campbell & Wright, 2002;
Johnson et al., 2008; Wright, 1999, 2000, 2002; Wright et al., 2010) in this area has
been largely limited to survey research (with some content analysis and ethnographic
methods), as well as work by other online support group researchers (see Shaw & Gant,
2002; Walther & Boyd, 2002). While survey research has a number of limitations and it
lends itself to more descriptive types of research, it will likely continue to be a prominent
method of studying online support due to the convenience of online survey tools (such
as Qualtrics and SurveyMonkey) and the ability to use online surveys to reach large
numbers of individuals who share common characteristics despite being geographically
dispersed (Wright, 2005). However, many researchers have engaged in experimental or
quasi-experimental methods to examine several facets of computer-mediated social
support for people facing health concerns (see Barrera et al., 2002; Shaw & Gant, 2002;
Gustafson et al., 1999, 2001, 2005). These designs will continue to be important to our
understanding of causal relationships among exogenous variables, key online support
variables, moderating variables, and key health outcomes, which is particularly helpful in
terms of designing and evaluating support interventions.
Finally, researchers have also relied on content analysis and naturalistic methods in
the study of computer-mediated social support. For example, Preece (1999) contentanalyzed
postings in online support groups for people coping with serious health
­problems, such as diabetes and cancer, and she found that the highest percentage of
messages were some form of empathic discourse followed by personal narratives. Rains
and Keating (2011) used content analysis to assess supportive messages and selfreported
health outcomes within health-related blogs. Rains and Young (2009)
­conducted a meta-analysis of over 20 computer-mediated support interventions, and
they found moderate effect sizes when assessing the relationship between online
support and a variety of health outcomes. Ley (2007) used ethnographic methods to
study social support in an online pregnancy support group, and found that the groups’
technical features influenced patterns of social support and, in some cases, had contradictory
effects on the perceived helpfulness of support. Future computer-mediated
support research will likely benefit from other types of naturalistic research, particularly
studies that allow researchers to understand how meanings of supportive messages are
co-constructed through interactions within the groups.
Limitations of Computer-Mediated Support Scholarship
and Future Theoretical/Applied Directions for Research
Despite the promise of computer-mediated support, there are still many facets of
individual support predispositions, support processes, and links between computermediated
support and health outcomes that need to be investigated. This section
briefly discusses several of these issues.
500	 Kevin B.Wright
One issue concerns accounting for the influence of overlapping sources of social
support on key outcome variables, such as stress and depression. According to
Haythornthwaite (2002), both online and offline supportive exchanges influence
health outcomes. In short, it becomes difficult to separate online supportive influences
from offline influences. For example, we typically mix face-to-face contact with
e-mail, searching the Internet with asking friends and reading books, and sending
regular mail and e-mail with use of the telephone. Caplan and Turner (2007) contend
that future computer-mediated support researchers should pursue whether online
supportive communication employs messages that are more, less, or equally empathic
to those conveyed in similar face-to-face encounters.
Future research in this area would benefit from the development of theories and methods
that take into account a more ecological perspective of the influence of social support on
health outcomes, including the main effects and interaction effects of online and offline
sources of social support, psychological predispositions, mediated variables (i.e., the
influence of CMC channels, contexts), and key demographic and environmental variables
(such as whether a person lives in a city, rural location, etc.) on health outcomes.
Although computer-mediated channels are able to connect individuals with larger,
more diverse, networks of individuals who may be able to offer types of social support
that transcend the quantity and quality of support within traditional face-to-face networks
(i.e., weak tie support), less is known about potential negative aspects of weak tie
support, such as the potential for increased deception, manipulation, cybersurveillance,
and other problems that can occur when communicating with relative strangers (Barak
et al., 2008; Finn & Banach, 2000). Given the potential benefits of computer-mediated
support groups and the risks associated with seeking support online, it is critical for
computer-mediated support researchers to better understand how group members evaluate
the credibility of supportive providers and supportive messages within these groups.
As we have seen in this chapter, the bulk of research on computer-mediated support
has focused on more formal health-related online support groups, although everyday
types of online social support, such as support within social networking sites and
virtual organizations, have been studied more in recent years (Steinfield et al., 2008;
Wright, 2012). Future research would benefit from studies that increase our understanding
of the many types of daily, mundane social support people give and seek
online, and the cumulative effects of this support on health outcomes.
Finally, relatively little is known about how minority groups and other populations
facing health disparities use computer-mediated support groups. However, it appears
that members of minority groups engage in a variety of online social support activities,
and individuals within these groups may benefit from computer-mediated support
interventions. For example, Fogel et al. (2003) found that while African-Americans,
Hispanics, and Asian Americans tend to use the Internet less than whites, their
Internet use was associated with greater ability to talk with someone about problems
and to obtain other types of social support.
Researchers have also found that access to traditional face-to-face support networks
(such as close family ties) often deteriorates among members of certain low-income
and minority groups due to factors such as unemployment, transience, and substance
abuse (Roschelle, 1997), underscoring the need to develop interventions targeting
these groups. Weinert and Hill (2005) found that rural women (including a high
	 Computer-Mediated Support for Health Outcomes Psychological Influences	 501
percentage of minorities and individuals from lower socioeconomic backgrounds)
using a computer-mediated support intervention had lower levels of depression and
higher self-reported management of day-to-day chronic illness symptoms than a control
group of similar rural women living with chronic illness. Irrizary, Downing, and
West (2002) and Wright (2000) found that computer-mediated support communities
were helpful in terms of helping isolated older adults facing health concerns to become
better connected with other individuals with similar circumstances. In short, there is
great potential for researchers to develop and test computer-mediated support interventions
with underserved populations.
Conclusion
Paralleling the growth of the Internet and social media, computer-mediated support
has become a common online activity in recent years, and it has gained the attention
of many researchers interested in understanding the nature of social support processes
and outcomes within this context. Building upon initial descriptive studies, scholars
have identified a number of theoretical frameworks that help to explain computermediated
support processes and their relationship to positive health outcomes for
individuals who participate in computer-mediated social support. While early studies
relied on survey research to understand the nature of computer-mediated social
support, more recent studies have moved toward experimental designs and intervention
approaches. The findings from these studies provide support for the idea that
computer-mediated support interventions may benefit certain populations (e.g., people
coping with a stigmatized health condition, individuals who lack support resources
in the face-to-face world, etc.). Future research is certainly needed to gain a better
understanding of intervening variables that may influence the relationship between
computer-mediated social support and various outcomes, and more studies are needed
that examine computer-mediated support among more diverse populations.
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