Computers in Human Behavior 28 (2012) 631–641

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Computers in Human Behavior

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A videosharing social networking intervention for young adult cancer survivors

Margaret McLaughlin a,⇑, Yujung Nam b, Jessica Gould b, Courtney Pade b, Kathleen A. Meeske c,Kathleen S. Ruccione d, Janet Fulk e

a Annenberg School for Communication & Journalism 301D, University of Southern California, Los Angeles, CA 90089-0281, USAb Annenberg School for Communication & Journalism G6, University of Southern California, Los Angeles, CA 90089-0281, USAc Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USAd Center for Cancer and Blood Diseases, Children’s Hospital Los Angeles, 4650 Sunset Blvd., Mailstop #54, Los Angeles, CA 90027, USAe Annenberg School for Communication & Journalism 324E, University of Southern California, Los Angeles, CA 90089-0281, USA

a r t i c l e i n f o a b s t r a c t

Article history:Available online 6 December 2011

Keywords:Cancer survivorshipMobile social networkSocial supportSocial capital

0747-5632/$ - see front matter � 2011 Elsevier Ltd. Adoi:10.1016/j.chb.2011.11.009

⇑ Corresponding author. Tel.: +1 213 740 3938.E-mail addresses: mmclaugh@usc.edu (M. McLau

Nam), jessicjg@usc.edu (J. Gould), cmschult@usc.educ.edu (K.A. Meeske), kruccione@chla.usc.edu (K.S. Ruc

Clinicians interested in taking a proactive approach to healthy cancer survivorship might consider the useof a social networking and videosharing platform tailored specifically for young adult cancer survivors.This study examines six key factors that may influence a childhood cancer survivor’s participation in asocial networking and videosharing intervention program tailored to their needs: (1) the individual’ssocial capital, defined as resources accessed by individuals through a broad range of social connections,(2) social support, (3) family interaction, (4) self-efficacy, (5) depression, and (6) self-reported quality oflife. Fourteen healthy childhood cancer survivors participated in a social networking and videosharingintervention program, LIFECommunity, over a period of 6 months. Young adult cancer survivors withweak ‘‘bonding’’ social capital with other cancer survivors, little social support from friends and family,and lower family interaction participated in the social networking intervention more than those withstronger social capital and larger bases of support. The findings suggest that cancer survivors used thesocial network as a way to fulfill needs that were not being met in their ‘‘offline’’ lives. The study providesa deeper understanding of the factors that contribute to the success of social networking interventions foryoung cancer survivors.

� 2011 Elsevier Ltd. All rights reserved.

1. Introduction

A recurring concern of health care organizations with respect tochildhood cancer patients who have completed treatment is help-ing them manage the transition from the pediatric to the adulthealth care system, and to provide them with the resources re-quired for healthful survivorship. To do so has proven to be partic-ularly challenging with adolescents and young adults from thelow-income, largely minority populations who constitute the bulkof the patients in many metropolitan pediatric emergency and ter-tiary care hospitals. Keeping these former patients connected tothe resources of the hospital and helping them to understandand deal with potential long-term effects of their illness and treat-ment is a high priority.

In the following pages, we describe a project whose goal was toprovide a proactive approach to healthy cancer survivorship focus-ing on helping survivors overcome some of the challenges theyface through the use of a mobile social networking platform

ll rights reserved.

ghlin), yujungna@usc.edu (Y.(C. Pade), kmeeske@chla.us-

cione), fulk@usc.edu (J. Fulk).

designed specifically for young adult cancer survivors. In the pres-ent study, we examine a variety of factors including a survivor’s so-cial capital, social support, patterns of family interaction, self-efficacy, and depression in order to gain a better understandingof the key determinants that may influence a survivor’s participa-tion in such a program. Findings from this study can help us to tai-lor future programs and interventions so as to reach the greatestnumber of survivors, and to increase participant engagement. First,we provide a brief overview of some of the key challenges faced byyoung adult cancer survivors, and describe our interventional vid-eosharing and social networking program. Next, we provide anoverview of extant literature on the factors we expect to influenceparticipation in such an intervention. We conclude with methods,results, and a discussion of our findings.

1.1. Challenges faced by young adult cancer survivors

In 2007 there were 10,400 new cases of cancer diagnosed inchildren (ages 0–15 years) (National Cancer Institute, 2008). Asof 2006, there were approximately 330,000 survivors of childhoodcancer living in the United States (Oeffinger, Mertens, Sklar, et al.,2006). Once childhood cancer survivors have completed treatment,

632 M. McLaughlin et al. / Computers in Human Behavior 28 (2012) 631–641

they are still faced with a multitude of challenges, some of whichthey will have to cope with for their entire lives (Geenen et al.,2007; Hudson et al., 2003). Over two-thirds of adolescent cancersurvivors will have some cancer-related physical or psychosocialproblem that will develop within 5 years of their initial diagnosis(Hewitt, Weiner, & Simone, 2003; Oeffinger, Mertens, Hudson,et al., 2006). However, the number of cancer survivors who actu-ally participate in specialized survivorship programs that, whenfollowed, can help to reduce or eliminate the complications associ-ated with these late effects is quite low (Oeffinger, Eshelman,Tomlinson, & Buchanan, 1998). This situation is exacerbated bythe fact that many survivors do not have a highly accurate knowl-edge of their own cancer history. Even when they are able to pro-vide an accurate history and know that their history may have putthem at risk for future health problems, this knowledge is not nec-essarily predictive of health behaviors (Tyc, Hadley, & Crockett,2001).

Having a network of supportive and understanding peers is par-ticularly important for encouraging survivors to abstain from un-healthy behaviors, and instead to foster behaviors which willpromote successful and healthy survivorship (Decker, 2006). Re-search has indicated that young survivors are largely satisfied withthe support they receive from family members, but are not as sat-isfied with the support they are receiving from friends (Decker,2006). Satisfactory support from peers who are also cancer survi-vors may be important in facilitating a smooth transition to a suc-cessful cancer survivorship and validating survivors’ emotional andcognitive needs.

1.2. A mobile social networking program

In an effort to address some of these challenges young adultcancer survivors are faced with after they have finished treatment,we developed a mobile social networking site for young adult can-cer survivors. Recent research indicates that mobile social net-works can be used to build relations and social support amongmembers of a community (Ankolekar et al., 2009) and can serveas a platform for the dissemination and exchange of information(Chou et al., 2008). Research also has shown that virtual environ-ments that support relationships with peers and mentors withsimilar medical experiences can assist young persons in making asmooth transition after overcoming illness and improving adher-ence to treatment regimens and follow-up guidelines (Cantrellet al., 2010). In the present research, we developed a social net-work to assist in the development of social capital and support net-works among a group of young adult cancer survivors. We alsoused this network as a platform for providing access to survivor-ship-related events, resources, and information. The network wasdesigned to provide survivors with emotional and informationalsupport, to increase their awareness of key medical concerns, suchas long-term effects of treatment, environmental hazards andstressors, and to facilitate their transition to the adult healthcaresystem, informing them of the options and opportunities availableto them.

We made a determination to make the social networking appli-cation available through mobile devices to facilitate ready, around-the-clock access. In order for benefits to be realized, however, indi-viduals from the target population must also be inclined to logonand participate. We used extant theory on social support, familyinteraction, and social capital, and the individual level factors ofdepression and self-efficacy to explore potential factors that mightlead participants to participate in a survivorship social network.The following sections provide an overview of theory and researchon these factors, along with hypotheses linking them to participa-tion in a mobile social network.

2. Literature review

2.1. Social capital and health

The first theory that gives some insight into motivations for on-line social network participation is social capital theory. Putnam(2001) defines social capital as ‘‘features of social organization,such as trust, norms and networks, that can improve the efficiencyof society by facilitating coordinated actions’’ (Putnam, 2001).Communication, in particular, is viewed as a way for people todetermine whom to trust, help, and cooperate with in order to en-gage in productive network ties (Sirianni & Friedland, 1955).

Recently, researchers in the realm of health communicationhave explored social capital’s impacts in many different domains.One such area is an individual’s efficacy in finding health-relatedinformation. For example, Kawachi, Kennedy, and Glass (1999) be-lieve that the formal and informal social networks associated withhigh social capital stimulate health efficacy because they providepeople with access to health education including information onpreventative measures. Individuals with high social capital willhave more networks from which to seek out health information.Basu and Dutta’s (2008) work substantiates this conclusion, findingthat high community participation (social capital) is correlatedwith high health information efficacy, defined as the feeling thatone is able to find health information. Both the ability and willing-ness of an individual to remain healthy are dependent on thehealth of the community that surrounds the individual. Our studyis unusual compared to those cited in that we examine domain-specific social capital, that is, social capital within a communityof other survivors of childhood cancer. These findings linking com-munity participation to both health information efficacy andhealth information orientation provide some insight into how off-line social capital predicts participation in online healthcommunities.

Two different types of social capital may be important whenexamining online community participation. First, bonding socialcapital refers to resources that are accessed within social groupswhose members are close social ties, such as family and friendswho are very similar with respect to interests and experiences.Bonding social capital is a source of cohesion, which can createconditions for supportive interactions. Bonding social capital, how-ever, does not often tap into novel ideas and information, becauseclosely connected individuals communicate frequently with eachother, thus sharing the same information. Bridging social capital re-fers to the resources accessed by individuals through connectionsthat cut across boundaries of social identity (Kawachi, Subramani-an, & Kim, 2008; Williams, 2006). Bridging capital provides accessto new information, ideas and persons, but these persons do nottypically offer supportive interactions, because bridging relation-ships tend to be more arms-length. Thus, because individualswho are strongly embedded in social networks are more healthefficacious and more knowledgeable about health behaviors, it ishypothesized that both offline bridging and bonding social capitalwill be positively related to online community participation.

H1. Bonding social capital with other cancer survivors is positivelyrelated to level of participation in a social networking intervention.

H2. Bridging social capital with other cancer survivors is positivelyrelated to level of participation in a social networking intervention.

2.2. Social and familial support

2.2.1. Social supportBoth social and familial support are critical variables to consider

in the context of health and online participation. Social support,

M. McLaughlin et al. / Computers in Human Behavior 28 (2012) 631–641 633

broadly defined as the ‘‘resources provided by other persons’’ (Co-hen & Syme, 1985), has been shown to have a wide range of ben-eficial effects on physical and emotional health (Seeman, 1996;Uchino, 2004). For example, social support has been linked to rat-ings of quality of life (Helgeson, 2003), increases in compliancewith medical treatment (DiMatteo, 2004; Guidry, Aday, Zhang, &Winn, 1997), and enhanced abilities to cope with both day-to-day (Bolger & Amarel, 2007) and illness-related stress (Decker,2006; Nichols, 1995). In contrast, a lack of social support can leadto detrimental effects. Low levels of social support have beenlinked to increased risk of mortality (Berkman & Syme, 1979;Blazer, 1982; Kroenke, Kubzansky, Schernhammer, Holmes, &Kawachi, 2006). Social support is a related but distinct constructfrom social capital, in that the latter refers most specifically tothe individual’s networks of connections while social support re-fers more specifically to the potential or active provision of help,such as comfort, information, or material resources. Here we con-ceptualize social support in terms of the active provision of helpfrom individuals occupying different roles, such as friends, family,or relevant professionals.

2.2.2. Social support and online participationIn recent years, researchers have begun to examine provisions

of social support in online contexts (Eastin & LaRose, 2005; Lewan-dowski, Rosenberg, Parks, & Siegel, 2011). However, what has lar-gely been overlooked is how social support may influencebehaviors and interactivity in online spaces, particularly in onlinespaces pertaining to health. Research indicates that individualswho have high levels of social support offline reap greater benefitsfrom online interactions than those who have lower levels of socialsupport offline. In addition to reaping greater benefits from onlineinteractions, individuals with high levels of offline social supportare also more likely to have higher levels of participation online.For example, Birnie and Horvath (2002) found that students whohave a greater number of offline social contacts and engage inhigher levels of socialization offline will also tend to have more so-cial contacts and engage in higher levels of socialization online. Lee(2008) also found that teens who had strong offline social relation-ships were more likely to engage in higher levels of online commu-nication than were teens who did not have strong offlinerelationships. In light of these findings, we predict that offline so-cial support will be predictive of rates of participation in a mobilesocial networking site for cancer survivors.

H3. The social support level of participants is positively related tothe level of participation in a social networking intervention.

2.2.3. Family support and interactionWhile offline social relationships may lead individuals to inter-

act more with their peers online, support from family membersmay have the opposite effect. It is clear that family members area key source of emotional support for cancer survivors (Gottlieb& Wagner, 1991). However, survivors may not always receive thesupport they need from their families and thus may have to lookelsewhere. For example, participation in face-to-face cancer sup-port groups was highest among those who did not get sufficientemotional support from their families (Pilisuk, Wentzel, Barry, &Tennant, 1997). Also, in an offline support group study, those withless familial support showed a greater propensity for participation(Grande, Myers, & Sutton, 2006). In addition, a study on breast can-cer patients found that Internet use was associated with a low de-gree of family support, but had no association with peer support(Winefield, Coventry, Pradhan, Harvey, & Lambert, 2003). Overall,these studies add to the argument that social support groups aresought as a way to complement deficiencies in emotional support

provided from close family relationships. Thus, building on thesestudies, if cancer survivors are satisfied with their level of familysupport, they will be less inclined to use the features on the mobilesocial networking site.

H4. The family interaction of participants is negatively related tothe level of participation in a social networking intervention.

2.3. Survivorship self-efficacy

Self-efficacy, a central variable in Bandura’s (1986, 1997) socialcognitive theory, refers to peoples’ judgments of their capabilitiesto perform certain actions (Bandura, 1997). Bandura argues thatself-efficacy influences many aspects of individual behaviors, suchas the acquisition of new behaviors, inhibition of existing behav-iors, and disinhibition of behaviors (Bandura, 1997; Stretcher, DeV-ellis, Becker, & Rosenstock, 1986). The impact of self-efficacybeliefs has been demonstrated in a range of contexts includinghealth behavior (Bandura, 1986, 1997; Jerusalem & Schwarzer,1992) and Internet and computer use (Cassidy & Eachus, 2002;Ginossar & Nelson, 2010). Thus, it has been argued that in orderfor individuals to obtain Web-based health information effectively,it is essential that they have high levels of self-efficacy (Ginossar &Nelson, 2010). We propose that survivorship self-efficacy, the abil-ity of cancer survivors to manage their post-treatment health careand access relevant informational resources as needed, may be animportant predictor of online health information seeking behaviorincluding participation in online communities and networks de-voted to cancer survivorship.

Recent studies have indeed found a link between self-efficacyand Internet usage. In fact, a survey found that 92% of cancer pa-tients believe the Internet empowers them to make health deci-sions (Eysenbach, 2003). In a study of newly diagnosed cancerpatients, Bass et al. (2006) found a significant positive relationshipbetween the amount of Internet usage and self-efficacy of the pa-tient. In addition, this study found Internet use was also signifi-cantly associated with other self-efficacy variables such asconfidence in actively participating in treatment decisions, askingphysicians questions, and sharing feelings of concern (Bass et al.,2006). Therefore, extending these findings, we predict that thereis a positive relationship between survivorship self-efficacy andparticipation in a social network intervention.

H5. The survivorship self-efficacy of participants is positivelyrelated to their level of participation in a social networkingintervention.

2.4. Depression

It has been noted that cancer survivors continue to face a vari-ety of challenges even after they have completed treatment andtime has passed. Some of these challenges pertain to physicalhealth, but others relate to mental health. One key psychologicalchallenge faced by survivors is depression (Schultz et al., 2007;Zebrack, 2000; Zebrack & Chesler, 2002; Zebrack et al., 2002).

Individuals who are depressed or lonely may seek solace andsupport online (Houston, Cooper, & Ford, 2002; Morahan-Martin& Schumacher, 2003). For example, Houston, Cooper, and Ford(Houston et al., 2002) found that for depressed individuals, partic-ipation in an online support group was linked to decreases indepression. Other studies have echoed this finding, revealing thatthe social support derived from online community participationcan lead to decreases in depression (Powell, McCarthy, & Eysen-

634 M. McLaughlin et al. / Computers in Human Behavior 28 (2012) 631–641

bach, 2003) and increases in overall psychological well-being (Rod-gers & Chen, 2005).

Depressed individuals may exhibit higher levels of Internet usethan individuals not suffering from depression. For example, Shep-ard and Edelman (Shepard & Edelmann, 2005) found a positiverelationship between depression and Internet use. Specifically,they found that depressed individuals use the Internet as a toolfor coping with social anxieties. Bansil, Keenan, Zlot, and Gilliland(2006) found that adults suffering from depression are more likelyto seek out health-related information on the Web. While both ofthese studies examined adults, we expect their findings will alsohold true for adolescents and young adults, who have even higherrates of internet use (Lenhart, Purcell, Smith, & Zickuhr, 2010).Therefore, in light of these findings, we predict that among usersof an online social network for cancer survivors, depressed individ-uals will exhibit higher rates of participation.

H6. Participants’ level of depression is positively related to theirlevel of participation in a social networking intervention.

2.5. Quality of life

Individuals may seek out interactions online when they havedeficits in their personal lives. One such deficit may be in an indi-vidual’s overall rating of his or her quality of life. Many years ofsuffering from a devastating illness, and coping with both the psy-chological and physical late effects of treatment even after recov-ery, have been linked to decreased ratings of overall quality oflife (Ganz et al., 1996; Meeske, Ruccione, Globe, & Stuber, 2001;Schag, Ganz, Wing, Sim, & Lee, 1994; Zebrack & Chesler, 2002).Spending time on the Internet and engaging in social activities on-line is linked to increases in ratings of quality of life, particularlyfor individuals who are suffering from isolating illnesses, or believethey do not have the offline support they need. In her study oflong-term cancer survivors, Klemm (2008) found that survivorsgrappling with late effects of treatment often do not believe theyare receiving the support or information they need regardinghealthy survivorship, and that Internet support groups can be aneffective means of filling these voids. Meier, Lyons, Grydman, Forl-enza and Rimer (2007) have also found that online groups can be akey source of both informational and emotional support for cancersurvivors. Therefore, we predict:

H7. The self-reported quality of life of participants is negativelyrelated to the level of participation in a social networkingintervention.

3. Method

The pre- and post-intervention within-subject design consistedof 14 participants each completing a 6-month long mobile-basedsocial networking program. A private mobile social networkingsite, LIFECommunity, was designed and launched by the researchteam. The project was affiliated with an established program ofthe same name at a large metropolitan children’s hospital on thewest coast. LIFECommunity offered many of the functionalitiesavailable in well known social networking sites such as Facebook.Participants had the ability to create a profile, post pictures, sendmessages, and share videos and stories with one another. Theseactivities could all be conducted via a smartphone, which the par-ticipants were provided with as part of the study, or via computer.This paper focuses on the pre-intervention and intervention timeperiods; the hypotheses are centered on how preintervention so-

cial and personal situations influence actual use of the social net-working site.

3.1. Participants

Fourteen participants were recruited from the children’s hospi-tal cancer registry. A research assistant reviewed each patient’smedical record to determine eligibility. Inclusion criteria were thatparticipants were diagnosed with cancer between 1/1/1980 and12/31/2003; that all cancers were eligible and that patients withcentral nervous system (CNS) cancers might participate so longas the attending physician had determined that the patient wasnot cognitively impaired; that the participant must have been offtreatment for a minimum of 2 years, and disease free for a mini-mum of 5 years; that the participant was between the ages of 18and 29 at enrollment; and finally that the participant was able toread and write at an 8th grade level in English. Participants wererecruited by sending a letter on hospital letterhead to them at theirlast known home address, with a reply card included. One hundredtwenty-two former patients met the inclusion criteria and werecontacted by mail to assess their interest in participating. Thosewho returned a card indicating that they might be interested werecontacted via phone and/or email to follow up. Among 29 partici-pants who were contacted for follow-up via phone and mail, 19showed interest in the study. Five people were excluded on the ba-sis that they did not live in Los Angeles and could not attend theorientation session. All study activities including recruitment strat-egies and data safety management plans were approved by theinstitutional review boards of both the hospital and the university,as the research team was composed of both academic researchersand clinical personnel from the hospital through which partici-pants were accrued (Table 1).

3.2. Procedure

Upon completion of the design and implementation of the LIFE-Community site, we conducted a trial orientation session for thestudy with student volunteers. The goals of the orientation sessionwere to provide participants with instructions regarding how touse the new mobile phones we issued to them, to provide themwith an overview of the functionalities of the LIFECommunity siteand to administer a pretest. Feedback was solicited from the stu-dent volunteers regarding the structure and content of the phoneand site instruction periods, and wording of items in the pre-testquestionnaire.

After the trial orientation session, we launched an actual inter-vention program with the fourteen recruited subjects. Three orien-tation sessions were required to accomplish recruitment of all ofthe participants, owing to scheduling and other conflicts; partici-pants began the intervention in roughly two cohorts of size tenand size four. Participants were invited to an orientation sessionon the university campus. After signing all consent documentsand completing a pre-questionnaire, they participated in aninstructional session where they learned the basic functionalitiesof the mobile phone and key components of the LIFECommunitysite. Participants were told that use of the mobile phone was com-pletely free to them for 6 months, and that after completion of theproject in 6 months they would be permitted to keep the phoneand to transition to a monthly payment plan if they chose to keepusing the phone. Once completing the face-to-face orientation, allintervention activities and contact with the researchers were con-ducted via web and mobile access only. In accordance with thedata safety monitoring plan, the use of the LIFECommunity wasclosely monitored daily by two researchers, one from the academicprogram and one from the hospital, with particular attention to thecontent of blog posts and videos.

Table 1Participant characteristics

Characteristic (N = 14) Value, n (%)

SexMen 9 (64.3%)Women 5 (35.7%)

Race/ethnicityHispanic or Latino 12 (85.7%)Asian or Pacific Islander 1 (7.1%)Native American 1 (7.1%)

Education10th grade 2 (14.3%)12th grade 2 (14.3%)GED 3 (21.4%)Some college or Technical/vocational school 7 (50%)

Father’s educationLess than high school 4 (28.6%)High school or GED 6 (42.9%)Do not know 4 (28.6%)

Mother’s educationLess than high school 8 (57.1%)High school or GED 1 (7.1%)Some college or technical/vocational school 3 (21.4%)College graduate 1 (7.1%)Do not know 1 (7.1%)

EmploymentPart-time student 13 (92.9%)Work full-time 11 (78.6%)

Primary language spoken at homeSpanish 7 (50%)Both Spanish and English 4 (28.6%)English 2 (14.3%)

Primary written languageBoth Spanish and English 4 (28.6%)English better than Spanish 7 (50%)Only English 2 (14.3%)

Primary spoken languageBoth Spanish and English 5 (35.7%)English better than Spanish 7 (50%)Spanish better than English 1 (7.1%)Only English 1 (7.1%)

US bornParticipants 11 (78.6%)Mothers 3 (21.4%)Fathers 1 (7.1%)

M. McLaughlin et al. / Computers in Human Behavior 28 (2012) 631–641 635

Users were invited to attend a wrap-up session after the 6-monthlong mobile intervention. At the face-to-face meeting, they wereasked to complete a paper and pencil post-test questionnaire andshare their thoughts about the intervention efforts in a focus group.

3.3. Multimedia narrative assignments

In conjunction with the network-building approach we em-ployed a method known as Video Intervention/Prevention Analysis(Rich, Lamola, Gordon, & Chalfen, 2000), a technique based on vi-sual anthropology in which short self-produced video narrativesand interviews with significant others, in our case to be taken withcell phone cameras, are used to increase self-awareness and sensi-tize individuals to the stressors which contribute to poor medicalself-care. Throughout the duration of the study, participants re-ceived periodic text messages from the research coordinators thatencouraged them to share open-ended and unstructured videonarratives with other LIFECommunity participants. Narrativeassignments covered a wide range of topics such as familiar sur-roundings, coping skills, communication with healthcare care pro-viders, and reflection on cancer survivorship in general. Anexample of a periodic text message that encouraged participants

to share their interests and backgrounds is, ‘‘Introduce yourselfto the group! Post a photo of yourself to share with the othersand make a video in which you tell the group a little bit aboutyourself.’’ An example of survivorship related topic is, ‘‘Pretendthat you are talking to someone that you did not know before.Make a video in which you tell him/her about your experience withcancer.’’ Video narrative assignments also consisted of educationalcomponents that were intended to increase self-awareness andpreparation for the potential stressors and risky behaviors suchas, ‘‘Make a video about how you might deal with the temptationto do things that are risky to your health, such as smoking or lyingin the sun without skin protection.’’

3.4. The LIFECommunity site

A mobile and web-based social networking site, the LIFECom-munity, was created specifically for the purposes of the presentstudy. It was designed and implemented on an open source-basedmobile/web platform (Drupal) that provided participants with theability to create a personal profile, share pictures and videos, createa blog, create a group discussion, and send private messages toother participants. Site membership was available only to partici-pants in the study. Any video recordings or multimedia entries,blog posts, discussion forum activity, private messages, or FAQswere posted to the LIFECommunity site and were available to con-nected buddies depending on their privacy settings (Table 2). Fig. 1is a composite of pc screen captures of various features of the LIFE-Community site.

3.5. Measures

Responses to questionnaires were collected from the partici-pants at the orientation session. The measures used were thefollowing.

3.5.1. Social supportSocial support was derived from the Social Support for Adoles-

cents Scale (Cauce, Felner & Primavera, 1982). A composite index ofemotional support from close friends, parents, and healthcare pro-viders assessed social support in participants’ lives on a 5-pointscale (‘‘1 = No support’’, ‘‘5 = Most support’’). The obtained valueof Cronbach’s alpha for the scale was .93.

3.5.2. Bridging social capitalThe bridging social capital scale was adapted from Williams

(2006). The instructions were modified to pertain specifically tocancer survivors. The scale was composed of the following items:There are several other cancer survivors who make me: (1) inter-ested in things that happen outside of my town; (2) want to trynew things; (3) interested in what people unlike me are thinking;(4) curious about other places in the world; (5) feel like part of alarger community; (6) feel connected to the bigger picture; (7) re-minded that everyone in the world is connected; (8) want to spendtime to support general community activities; (9) connected tonew people to talk to; (10) informed about new things to try,and (11) connected to useful information and resources. Responseswere given on a 1–5 point scale (‘‘1 = Strongly disagree’’,‘‘5 = Strongly agree’’). Cronbach’s alpha for this scale was .98.

3.5.3. Bonding social capitalBonding social capital was also adapted from Williams (2006).

Responses were given on a 5-point scale (‘‘1 = ‘‘Strongly disagree’’,5 = ‘‘Strongly agree’’). The scale was composed of the followinginstructions and items: There are several other cancer survivorsthat (1) I trust to help solve my problems; (2) I can turn to for ad-vice about making very important decisions; (3) I can talk to when

Table 2LIFECommunity functionality.

Function Activities

Buddy list Displays a list of connected friends and groups of participantsManages buddy lists, pending requests, and group membershipHighlights buddies who were online to encourage real-time interactions among participants

Multimediablog

Shares any photo or video blog entries with connected buddiesAllows video clips of up to 10 min taken with participants’ smartphonesAllows participants to take photos with their phones and upload them directly to the siteConnected buddies receives an immediate notification on their wall upon entry of a new postInteracts with buddies through posting or reading comments on a blog post or attaching a text or multimedia file in comments

Forum Shares specific topics and invited other members to engage in discussionFirst page shows a list of the most recent forum conversationsWhen a forum topic is selected, a thread of the conversation is expanded in descending orderAllows adding comments or sharing multimedia files

FAQ Provides questions and answers to health and lifestyle related questions that were relevant to survivorsA team of medical experts from the childrens’ hospital reached an agreement on the most important information that should be provided tochildhood cancer survivorsAmong the topics covered were long-term treatment effects, coping strategies, obtaining a copy of medical records, persisting in follow-up treatment,communicating about cancer with friends and family, and dealing with emotional effects from cancer

Privatemessaging

Composes or responds to a message from a specific recipient or a group

Fig. 1. LIFECommunity social networking site.

636 M. McLaughlin et al. / Computers in Human Behavior 28 (2012) 631–641

I feel lonely; (4) would put their reputation on the line for me; (5)would be good job references for me; (6) would share their lastdollar with me; and (7) would help me fight an injustice. The ob-tained value of Chronbach’s alpha was .86.

3.5.4. DepressionIndividual depression was measured using the Center for Epide-

miologic Studies (CES-D) depression scale (Radloff, 1977). Thescale is composed of 20 items. Participants were asked to ratehow they had felt in the past week using the following responses:‘‘rarely or none of the time (<1 day)’’, ‘‘Some or a little of the time’’(1–2 days)’’, ‘‘Occasionally or a moderate amount of the time(3–4 days)’’, ‘‘Most or all of the time (5–7 days).’’ Examples of theitems include, ‘‘I was bothered by things that don’t usually botherme’’, ‘‘I felt that I was just as good as other people,’’ and ‘‘I felteverything I did was an effort.’’ The obtained value of Chronbach’salpha was .90.

3.5.5. Survivorship self-efficacySelf-efficacy was measured by adapting and extending Jerusa-

lem and Schwarzer’s (1992) 16-item scale. Responses were given

on a four point scale (‘‘1 = Not at all true’’, ‘‘2 = Barely true’’,‘‘3 = Moderately true’’, ‘‘4 = Exactly true’’). Sample items included:‘‘I am confident as a cancer survivor that I can find the health infor-mation I need’’; ‘‘I am comfortable asking my doctor/nurse ques-tions about my body and health’’; and ‘‘I am confident I canaccess the resources I need to stay healthy.’’ The obtained valueof Chronbach’s a was .89.

3.5.6. Family interactionFamily interaction was assessed using three items adapted form

Wilkin, Katz, and Ball-Rokeach’s (2009) family interaction scale.Participants were given the stem, ‘‘Thinking about talking to yourfamily. . .’’ and were asked to respond to items using a five-pointscale (1 = ‘‘Very comfortable’’ to 5 = ‘‘Very uncomfortable’’). Sampleitems are (1) How comfortable would you be to talk to your familyabout the things you share with your friends/other cancer survi-vors? (2) How comfortable would you be to talk about the thingsyour friends/other cancer survivors have shared with you? (3)How comfortable are you taking about the treatment plan the doc-tors gave you? The obtained value of Chronbach’s alpha was .73.

Com

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ups

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1 .764

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1

M. McLaughlin et al. / Computers in Human Behavior 28 (2012) 631–641 637

3.5.7. Quality of lifeQuality of life was measured using the SF-12 (Ware, Kosinski, &

Keller, 1996). Sample items included: (1) During the past 4 weeks,how much of the time has your physical health or emotional prob-lems interfered with your social activities like visiting with friends,relatives, etc.? (2) During the past four weeks, how much did paininterfere with your normal work, including both work outside thehome and housework? The obtained value of Chronbach’s alphawas .77.

In addition to the questionnaire data collected at the orientationsessions, log files of the LIFECommunity site were used to obtainautomated records of participant site activity. These included:number of login times, number of blog posts, number of imagesposted, number of forums created, number of comments made,number of private messages sent and received, number of groupscreated, number of profile views, and number of views of theFAQ. All requests for page access and all input data (e.g., videos,forum posts) on the site were recorded and timestamped. A com-posite measure of participants’ global participation on the sitewas created from the individual participation metrics.

Tabl

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4. Analysis and results

The hypotheses were tested using OLS regression of the predic-tor variables on the global indicator of site participation. Thismethod provides a very conservative test, since the relatively smallsample size reduces the likelihood of finding a significant relation-ship (Cohen, Cohen, West, & Aiken, 2002). Hypothesis 1 proposedthat bonding social capital was positively related to participation.Results revealed a marginally significant relationship, lending mar-ginal support to Hypothesis 1 (b = .40, t(12) = 1.54, p = .07).Hypothesis 2 posited that the bridging social capital of participantswould also be positively related to participants’ level of participa-tion. This hypothesis was supported (b = .52, t(12) = 2.10, p < .05).

Follow-up analyses with activity types on the site revealed thathigher bridging social capital was positively related with sharingvideo stories (b = .50, t(12) = 1.97, p < .05) and exchanging informa-tional and empathy support through sending (b = .57, t(12) = 2.39,p < .05) and receiving more private messages (b = .59, t(12) = 2.29,p < .05). Higher bridging social capital was also significantly relatedto more frequent visits to other participants’’ profile walls (b = .51,t(12) = 2.10, p < .05).

Hypothesis 3 proposed that the social support from friends,family, physicians, teachers and relevant professionals experiencedby participants would be positively related to site participation.Contrary to predictions, however, a trend in the opposite directionwas observed, with decreased levels of support linked to increasesin participation (b = �.65, t(12) = �2,28, p < .05). Participants whoscored lower in face-to-face social support were significantly morelikely to participate in the online activities during the 6 months’LIFECommunity intervention (R2 = .60, F (1, 12) = 17.9, p < .01).Therefore, H3 was not supported.

In a follow-up analysis, participants with lower social supportlogged in to the LIFECommunity more frequently (b = �.79,t(12) = �4.42, p < .001), shared significantly more video narratives(b = �.68, t(12) = �2.87, p < .05), posted more comments in re-sponse to other participants’ entries (b = �.75, t(12) = �3.97,p < .05), and sent out more private messages to their buddies(b = �.84, t(12) = �5.34, p < .05) compared to those with higher so-cial support levels.

Hypothesis 4 addressed family interaction. We predicted thatincreased levels of interaction with and ability to talk candidlywith family members would be associated with lower levels of par-ticipation on the site. Results provided support for this hypothesis,indicating that participants who were closer to family members

638 M. McLaughlin et al. / Computers in Human Behavior 28 (2012) 631–641

and could discuss things more freely with them were less likely tobe involved in the mobile social networking program (b = �.55,t(12) = �2.30, p < .05).

Hypotheses 5 and 6 posited that the depression and survivor-ship self-efficacy would be positively related to participation onthe site, while Hypothesis 7 proposed that quality of life was neg-atively related to participation on the site. These hypotheses werenot supported. Further analyses indicated that there was a negativecorrelation between the predictors and individual participationactivities on the site. Lower survivorship self-efficacy, poorerassessment of general well-being, and higher depression predictedactive participation in blogging and private group-related activitiesin the LIFECommunity. For example, participants with lowersurvivorship self efficacy (b = �.54, t(12) = �2.19, p < .05) andlower evaluation of their own general well-being (b = �.52,t(12) = �2.07, p < .05) were significantly more active in postingblog entries on the site. Similarly, a higher depression level indi-cated more activity in blog posting (b = .47, t(12) = 1.83, p < .05).Participants who were more depressed (b = .61, t(12) = 2.70,p < .05) or appraised their quality of life more negatively(b = �.53, t(12) = �2.20, p < 05) also created significantly moreprivate on-site groups in the LIFECommunity. Summary data onmeans, standard deviations, and correlation coefficients areprovided in Table 3.

5. Post-hoc qualitative analysis

Our results indicated that participants with low social support,strong bridging – not bonding – ties, and little family interactionactively participated in the LIFE social networking website. Takentogether, these results suggest that individuals with few strongnetworks in ‘real’ life used the site more than those who had astronger offline support system. In order to further examine thisrelationship, an additional analysis was performed on the qualita-tive survey data. Specifically, we focused on the responses given toKuhn and McPartland’s (1954) Twenty Statements Test (a.k.a. the‘‘Who Am I’’ test). Participants were asked to provide up to 20words or phrases that described them. The statements were thencoded as being either ‘socially’ valenced or ‘individually’ valenced.Descriptors were coded as ‘socially’ valenced if they either explic-itly or implicitly referenced some interaction or relationship withother individuals. Example ‘social’ descriptors were ‘‘caring’’, ‘‘reli-able’’, ‘‘loyal’’ and ‘‘friendly.’’ Descriptors were coded as ‘individu-ally’ valenced if they made reference to unique individualattributes, and did not imply any relationship or interaction withothers. Example ‘individual’ descriptors were ‘‘observant’’, ‘‘un-ique’’, ‘‘different’’, and ‘‘healthy’’. Two coders independently codedthe adjectives, and an agreement rate of 94% was obtained.

Comparing participants’ descriptions of themselves to their lev-els of site participation, a trend emerged that mirrored our quanti-tative findings. Participants who were more active on the sitetended to list more individual descriptors, whereas individualswho had lower levels of participation had a higher volume of socialdescriptors. For example, the participant who was the most activein the site also listed the greatest number of individual-centeredwords like ‘different’ and ‘unique’, while only listing one socialword, ‘understanding’. This finding suggests that she may not haveseen herself as a social person with strong external ties. On theother hand, a participant who was not very active on the site listedalmost twice as many social words (e.g. fun, outgoing, exciting,friendly) as individual words (e.g. healthy, smart). The small sam-ple size prevents us from making generalizable conclusions. How-ever, the consistency of our results across both qualitative andquantitative methodologies provides further support for ourfindings.

6. Discussion

The study reported here tested the relationship between char-acteristics of childhood cancer survivors and participation in theLIFECommunity, a mobile social networking site designed to pro-vide connections, support and information to young adult cancersurvivors. In order to obtain an understanding of the factors thatcontribute to the success of such a program, we examined how avariety of factors influence participation. We examined social sup-port from friends, family and significant professionals (clergy, phy-sicians, teachers), social capital from other cancer survivors, familyinteraction patterns, depression, survivorship self-efficacy, andquality of life. An intervention with 14 healthy childhood cancersurvivors each completing a 6-month long mobile-based socialnetworking program produced several significant findings relatedto program participation.

The first two hypotheses proposed a relationship between twotypes of social capital built on relations with other cancer survivors– bridging and bonding – and overall participation in the LIFECom-munity program. H1, which hypothesized that the bonding socialcapital of participants would predict their level of activity on the site,was not supported, although the trend was in the predicted direc-tion. H2, which explored the link between bridging social capitaland participation, was positively related to participants’ level of gen-eral activity in the mobile social networking intervention. This find-ing is notable because bridging social capital is developed through‘‘weak ties,’’ which are loose connections between individuals whomay provide useful information but typically not emotional support(Granovetter, 1982). Thus, unlike those with strong ties to other sur-vivors (high bonding social capital) individuals with a large span ofdiverse connections are more inclined to participate in the site,perhaps to get the emotional support they need. Alternatively, theymay participate more actively in the site because their offlineexperiences with other cancer survivors and the resources theycan connect to through them have proved rewarding in the past.

We also hypothesized that the offline social support of partici-pants from friends, family and significant professional contactswould be positively related to the level of activity on the social net-working site. However, we found that participants who scored lowerin face-to-face social support were actually more active in the socialnetworking community during the 6 months of the intervention.The results indicated that participants who do not have a satisfac-tory level of social support from their face-to-face ties were morelikely to be actively engaged in the mobile social networking site.

H4 predicted a negative correlation between the level andquality of interaction with family members and participation inthe LIFECommunity. The results provided support for this hypoth-esis, indicating that childhood cancer survivors who communi-cated less with family members were more involved in themobile social networking program than those who are able to dis-cuss things frequently and openly with their families. Again, thesefindings are in line with the negative correlation found betweenthe level of face-to-face social support and level of engagementin the mobile social networking program.

Finally, H5, H6, and H7 hypothesized that depression, self-efficacy, and quality of life of participants would predict thegeneral level of online activities in the mobile social networkingintervention. The correlation between these three predictors andthe overall participation level was not significant. However, furtheranalyses confirmed a general trend in the findings and showed thatparticipants who scored lower in their survivorship self-efficacy,general quality of life, or higher depression participated more inblogging and private group-related activities in the LIFECommunity.

The findings from this study provide a deeper understandingof the relationship between social networking participation and

M. McLaughlin et al. / Computers in Human Behavior 28 (2012) 631–641 639

individual, environmental, and relational attributes. In particular,one consistent thread throughout our findings is that individualswith little social support from friends and family, and weak familyinteraction all participated in the mobile social network more thanthose with stronger ties and larger bases of support. However, hav-ing strong bridging ties offline with other cancer survivors washighly predictive of site activity. Thus, these cancer survivorsmay have used this social network as a way to fulfill ‘‘bonding’’needs that they were not getting in their offline life and extendingthe gratifications afforded offline through bridging networks ofother, weak-tie cancer survivors.

A body of literature suggests a possible explanation for whyyoung cancer survivors who lack an existing support network seekit out online. The uses-and-gratifications approach posits that peo-ple actively use media to gratify their needs and desires (Katz,Blumler, & Gurevitch, 2003). When a channel for individuals’ needsis unavailable or ineffective, people take further steps and turn to afunctional alternative (Papacharissi & Rubin, 2000). Cancer survi-vors will evaluate available face-to-face support and speculateabout the potential benefits of a mobile networking program.Therefore, a lack of existing social support and expected supportoutcomes will function as motivations to use a peer support net-working program. Perceived offline social support and participa-tion in social support groups become important when face-to-face support is unavailable or inaccessible for medical or logisticalreasons (Craig Lefebvre, Tada, Whifiker & Baur, 2010; Dutta, Pfister,& Kosmoski, 2010; Han et al., 2010; Lee & Hawkins, 2010).

The findings on family interaction confirm the relationship be-tween support needs and active engagement in an alternative sup-port option for cancer survivors. For some individuals, attainingsupport from their immediate social circle of close ties maybecome difficult, because family members ‘‘don’t understand’’ orbecause the survivor does not wish to burden them. Previous stud-ies have shown that less support from family and friends was asso-ciated with frequent and intense participation in offline socialsupport groups (Gottlieb & Wagner, 1991; Grande et al., 2006;Schaefer, Coyne, & Lazarus, 1981). Papacharissi and Rubin (2000)also suggested that evaluation of offline support as unsatisfyingor inappropriate for personal needs often leads to more engage-ment in online support group use.

Cancer patients and survivors often turn to close friends andfamily members for necessary medical information and emotionalsupport. It is becoming increasingly clear that the most prominentmotivational drive for turning to online support resources is to col-lect information and seek and share encouragement (Buchanan &Coulson, 2007; Maloney-Krichmar & Preece, 2005). Accurate andrealistic information about available treatment regimens, side ef-fects of treatments, and determinants of prognosis is critical forcancer patients and survivors for effective coping (Barnett et al.,2006; Dutta et al., 2010; Grande et al., 2006) but may not availablethrough offline support resources, leading survivors to seek outother resources.

Cancer survivors also need to express negative emotions includ-ing fear, anxiety, worry, anger, and feelings of shame and worth-lessness (Barnett & Hwang, 2006; Montazeri et al., 2001). Whensurvivors lack opportunities to alleviate such feelings of vulnerabil-ity, uncertainly and stress, they may actively participate in suchintervention programs in order to enhance a sense of control andwell-being.

7. Limitations and directions for future research

Taken together, this study’s findings suggest that, when facedwith few strong bonding ties, weak social support, and little familyinteraction, cancer survivors are more likely to participate in an

online mobile social network. This finding underscores the impor-tance of interventions like LifeCommunity; these services may pro-vide contact and support for those cancer survivors who need it themost.

While this finding adds both theoretical and practical insightsinto cancer survivorship, the study does have some limitations.First, despite an intensive recruiting effort, there were only 14 par-ticipants. It is apparently not uncommon for hospitals, especiallyhospitals that serve urban, often highly migratory populations, tolose touch with patients treated in childhood. But clearly future re-search should involve a larger group of participants. Confirmingthe present results in a larger sample would allow for generaliza-tions to a larger population.

Second, in this study, we are unable to report post-test datafrom the conclusion of the intervention in significant numbers tomake statistical analysis meaningful. Arranging for participantsto return to the research site to engage in a post-intervention fol-low up proved to be extremely challenging. The value of post-testmetrics cannot be underestimated, and therefore future researchshould look for new and innovative ways to secure participationin follow-up testing, including incentives. In this study the incen-tive value of a free smartphone and cellular service was providedat the beginning of the study only.

Third, the sample had some bias in that it included volunteerswho agreed to participate in a social networking study with othercancer survivors. In this sense, the participants were already biasedto participate in the online venture. It is unknown if stronger re-sults would have been obtained if we had been able to study thesocial capital, social support, self-efficacy, depression, quality oflife and family interaction of those less likely to participate in suchan online forum. In essence, the patterns found in this study re-lated to degree of participation for those already positively predis-posed to participate, although clearly we found considerablevariability in intensity of participation even among these volun-teers. Although there are limitations, this study takes the first stepin exploring the factors that motivate cancer survivors to use on-line social networks, and has provided an understanding of someof the factors that promote and influence participation.

Acknowledgments

Partial support for this research was provided by the AnnenbergProgram on Online Communities. We express gratitude to SusanGantan and Jackie Gilberto who assisted in monitoring of the LIFE-Community activities and Carey Numoto for assisting with partic-ipant postcard responses. In addition, we would like toacknowledge Eric Qi for his support for the project as the leaddeveloper of the LIFECommunity, along with Bin Feng and MinWang, who worked as site programmers. Ernest Katz, Matt Weber,Li Xiong, Scott Sanders, Hayeon Song and Vikki Katz contributed tothe assessment design, revision of the LIFECommunity program,and the broader implementation support.

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