Using Hierarchical Multivariate Analysis to Examine Interactions Between Alternative Appraisals of Cancer and Virtual Health Support Among Middle-Aged and Older Internet Users

Abstract

The advent of online communication is transforming how older adults find social support with a community of peers who cope with similar health issues. This article explores whether participation in virtual health support groups demonstrates a significant interaction with users’ appraisal of their illness experience and predicts self-reappraisal among adults 50 years of age and older (N = 157). Hierarchical multiple regressions demonstrate the significance of the combined effect of virtual health support and its interaction with illness appraisal measures to predict the outcome variable of self-reappraisal. The results indicate that even though appraisal of cancer as a traumatic experience reduces positive self-reappraisal, those who appraised their illness to have been a traumatic experience perceived virtual support to be more influential on their sense of positive change after cancer. In contrast, perceived benefit of virtual support on positive self-appraisal is reduced if illness is appraised as an opportunity for personal growth.

Keywords

cancer Internet support appraisal trauma self-appraisal

Introduction

Social support communication within the computer-mediated environments is becoming a new focus of research as the number of older Americans that use the Internet grows (Mitzner et al., 2010; Yoon, Yoon, & George, 2011). One of the reasons is that the advent of computer-mediated communication is transforming how older adults find social support with a larger community of peers who cope with similar physical and health problems (Slaughter, Tjora, & Sandaunet, 2010; Wagner, Hassanein, & Head, 2010 Yoon et al., 2011). Godfrey and Johnson (2008) explored the use of the Internet by those who are in older demographic groups and found that current cohorts of older adults view online support as a resource to promote their health-related quality of life and psychological well-being in old age. It is reported that 70% of computer-connected older adults use the Internet for health purposes (McMillan, Avery, & Macias, 2009). In fact, adults aged 50 and older are the fastest growing Internet users (National Telecommunications and Information Administration, 2006).

LaCoursiere (2001 called online support networks formed by the aging baby boom generation, who are digitally connected to information and support sources, “the emerging frontier of cyberspace” (p. 60). She developed a theory of online support which suggested that these peer networks are especially helpful for individuals who are coping with health issues that are perceived as life threatening. Older adults are the main beneficiaries of the virtual health support for several reasons: First, they are usually more in need of information and emotional support due to health challenges they tend to experience. Second, decline in offline support network (e.g., loss of spouse and friends) increases the importance of the Internet as a resource for social support. Third, life transitions such as retirement may provide extra time to browse the Internet to meet other older cancer patients. Networking with others in support groups helps to reduce the risk of isolation, improve psychological well-being, and encourage active coping strategies (McMellon & Schiffman, 2002; McMillan et al., 2009; Wright & Query, 2004).

Even though previous research has established that supportive communication in face-to-face context is a very powerful factor in coping with health crises, relatively few scholars probed into the association between technology use and physical and psychological health outcomes in older demographics (Chung, Park, Wang, Fulk, & McLaughlin, 2010; McMillan et al., 2009). Furthermore, even though the importance of appraisal variables has been emphasized in the literature, they have not been adequately examined among older adults who participate in virtual health communities. Thus, this study investigates whether participation in virtual health support groups: (a) is significantly associated with alternative appraisals of illness experience (cancer), (b) demonstrates a statistically significant interaction with users’ appraisal of illness experience, and (c) predicts positive self-reappraisal postdiagnosis among adults 50 years of age and older.

Cancer, as a life-threatening illness, tends to be associated with sense of fear, uncertainty, and loss (Fife, 1994). It usually challenges one’s assumptions about self (Aldwin & Sutton, 1998; Cordova, Cunningham, Carlson, & Andrykowski, 2001; Janoff-Bulman, 1992; Lee, Cohen, Edgar, Laizner, & Gagnon, 2006; Linley, 2003; Reynolds & Turner, 2008). Fife (2005) notes that “the illusion of personal control is shattered, and diagnosed persons are frequently thought to have lost some degree of assumed competence. In addition, self-image as well as others’ perceptions of the individual are negatively affected. This is often due to the fact that [cancer] and [its treatment] results in physical changes that alter body image . . . Meanings associated with these changes relative to the self result in the question “who am I now that I have been diagnosed with this illness”?” (p. 2134).

Interestingly, benefit finding and positive self-reappraisal in cancer patients are also reported in the previous literature (Sears, Stanton, & Danoff-Burg, 2003; Tomich, Helgeson, & Nowak-Vache, 2005). Sears, Stanton, and Danoff-Burg (2003) found social support has positive psychological effects such as finding meaning, posttraumatic growth, and positive reappraisal in women with early-stage breast cancer. Widows, Jacobsen, Booth-Jones, and Fields (2005) also report that availability of emotional support and more talking about breast cancer were linked with greater self-growth among breast cancer patients. Brennan (2001) points out, “cancer brings on changes that are not always for the worse and may precipitate healthy personal growth” (p. 1). Various studies of cancer survivorship indicate that positive self- and illness appraisals have been associated with psychosocial outcome measures such as decreased levels of depression, anxiety, and worry, improved self-esteem and body image, less internalized stigma, and higher health quality of life (Ashing-Giwa et al., 2004; Bowman, Deimling, Smerglia, Sage, & Kahana, 2003; Deimling, Kahana, Bowman, & Schaefer, 2002; Mattlin, Wethington, & Kessler, 1990). This article uses the term positive self-reappraisal to indicate that the outcome of coping with cancer might result in self-discovery and perceived positive changes in sense of self (Bellizi & Blank, 2006; Koopman et al., 2009; Lee et al., 2006; Tomich et al., 2005; Widows, Jacobsen, Booth-Jones, & Fields, 2005).

One of the most important aspects of virtual health support is facilitation of positive cognitive appraisals of traumatic events through mutual understanding based on shared experiences of cancer (Gooden & Winefield, 2007; Pitts, 2009; Seçkin, 2011). These groups bring together individuals who seek collective intelligence, support, and experiential knowledge of others in order to be better prepared for demands and challenges of coping with cancer (Bass, 2003; Drenta & Moren-Cross, 2005). As Wright and Query (2004) posit “similarity is often a key component in the social support process, particularly when individuals communicate empathy or the ability to communicate an understanding of another person’s perspective when providing support.” (p. 510). Previous research also shows that support seeking is especially related to positive self-reappraisal for those events that are considered high threat (Major, Richards, Cooper, Cozzarelli, & Zubeck, 1998). It is also reported that supportive social interactions are more influential on self-identity at times of extreme stress, high uncertainty, and change (Janoff-Bulman, 1992; Parkes, 1971; Schaefer, Moos, 1992). Finding a positive value in a negative life experience through social support may render the experience less aversive and threatening to psychological well-being (Lev-Wiesel & Amir, 2003; Thornton, 2002). Accordingly, as cancer is appraised more traumatic, virtual health support is more likely to be influential on positive self-appraisal.

Even though social study of stress and coping has a long tradition of emphasizing the significance of supportive relationships in coping with high loss and/or threatening events, research has primarily examined face-to-face social support groups (Brennan, 2001; Kerr & Kerr, 2003; Pearlin, 1989). Given the paucity of research examining the relations between virtual health support and positive self-reappraisal, the present study addresses an important gap in understanding the utility of virtual support groups on self-reappraisal and possibly illness appraisal and the potential virtual support groups have for cancer care of aging adults 50 years of age and older. This topic has a special significance for middle-aged and older adults because the incidence of cancer dramatically increases in older population (Bowman et al., 2003; Deimling et al., 2002). Additionally, their use of virtual tools represents the future wave of digital health trends. Virtual support groups may be helpful for aging adults experiencing a debilitating and/or life-threatening illness like cancer.

This study hypothesizes that beneficial impact of virtual health support is positively associated with appraisal of illness experience as a traumatic experience or as a life challenge. It is also hypothesized that the beneficial impact of virtual health support on postdiagnosis positive self-reappraisal will be higher for patients who appraise their illness to have been a traumatic experience compared to those who perceive it as a life challenge or an opportunity for personal growth.

Method

Recruitment and Sample

The study is a cross-sectional study of a subsample of 157 adults 50 years of age and older living with cancer (M age = 57; age range: 50–79) from the total sample of 350 respondents who participated in the Virtual Health Networks for Cancer Patients of the 21st Century: Patient Empowerment, Psychological Well-being and Trauma Transcendence Study (Seçkin, 2007). Data were collected for a doctoral dissertation research to partially fulfill the requirements for the degree of Doctor of Philosophy. Participants were recruited by posting announcements for the study on cancer listservs and bulletin boards of virtual cancer support groups. Google was used to identify these sites, as it is a major search engine used by health consumers to find information and support for their health needs (Hara, 2010). The web links retrieved by Google were first examined to determine their suitability for sample recruitment. This is done in accordance with the guidelines of the Medical Library Association. This included whether the websites were current, provided credible information, and stated who the sponsors were (Medical Library Association, 2009). The invitations for participation in the research were announced on support groups’ websites upon approval of group moderators or website administrators. If a site did not have a moderator, an invitation message was posted after reading the relevant disclosure information on the website. Interested respondents completed an online consent form and then accessed the website hosting the research survey. Completed surveys were received as e-mails, which were stripped of the submitters’ e-mail address and transferred to a database for analysis. The first 150 respondents were offered an online five-dollar gift card from Amazon.com as a token of appreciation for their participation in the study. Respondents’ e-mail addresses were separated from research data or any other identifiers. Institutional Review Board approval was obtained before launching the data collection.

Measures

Sociodemographic measures

Age at cancer diagnosis was measured in number of years. Gender was coded (0) for male and (1) female. Marital status was coded (1) for married and (0) other. Education was coded (1) high school or less, (2) some college education, (3) college degree, and (4) postgraduate degree. Income was coded (1) $24,999 or less; (2) $25,000–$49,999; (3) $50,000–$74,999; and (4) $75,000 or more.

Self-reported medical information

Cancer stage was categorized as I (in situ), II (local), III (regional), or IV (distal). Somatic distress was assessed using the Functional Assessment of Cancer Therapy (FACT) Quality of Life Measurement System (Cella, Gray, & Sarafian, 1993). Cronbach’s alpha (α) is .70. The number of treatments summed the total number of cancer treatments received. These included surgery, chemotherapy, radiation, hormone therapy, and other. Time since cancer diagnosis was a continuous variable and measured in number of month, which enabled the researcher to calculate the years of survivorship.

Psychosocial measures

Virtual Health Support was measured with the 16-item Cyber Support Scale-Cancer¹ (CSS-C; Seçkin, 2007, 2009). Cronbach’s α is .93. Responses ranged from (1) not at all to 5 always. The scale is presented in Appendix A. Depression was measured with the 7-item version of the CES-D (Radloff, 1977). The items were (1) I felt depressed, (2) I felt that everything I did was an effort, (3) I felt hopeful about the future, (4) I felt fearful, (5) I enjoyed life, (6) I felt sad, and (7) I felt that I was just as good as other people. Items 3, 5, and 7 are reverse-coded. Cronbach’s α is .81. Offline Support was measured with an adaptation of the “emotional and informational support” subscale of the Medical Outcomes Study (MOS)-Social Support Survey. Cronbach’s α is .90 (Sherburne & Stewart, 1991). Religiosity/Spirituality was measured using religion subscale of the COPE scale (Carver, Scheier, & Weintraub, 1989). Cronbach’s α is .91. Appraisal of cancer was measured using 3 items from the Cancer Experience Stress Appraisal Questionnaire² (Bowman et al., 2003). Respondents were asked: (1) “To what extent do you consider your experiences of cancer to have been a traumatic”; (2) “To what extent do you consider your experiences of cancer to have been as challenges that life presents”; and (3) “To what extent do you consider your experiences of cancer to have been an opportunity for personal growth.” Responses ranged from (1) not at all to (4) very much. Combining these items into a composite scale resulted in Cronbach’s α value of .53. Because values over .70 are suggested in order for a scale to have a high internal consistency (Todman & Dugard, 2007), regression models were estimated by performing an item-based analysis. In other words, the items for appraisal of cancer were entered into regression estimations as separate measures, without combining them into a composite scale. Positive Self-Reappraisal was measured with 5 items from Tedeschi and Calhoun’s Posttraumatic Growth Inventory (Tedeschi & Calhoun, 2005). These items are (1) I discovered that I can handle difficulties; (2) I discovered that I am stronger than I thought I was; (3) I developed new interests; (4) My priorities about what is important in life have changed; and (5) I appreciate each day more. Responses ranged from (1) not at all to (5) a lot. Responses ranged from (1) not at all to (5) a lot. Cronbach’s α is .83.

Analytical Approach

Regression diagnostics were conducted on the residuals to make sure the underlying assumptions of multiple regression analysis (i.e., homoscedasticity) were met. Ordinary least squares (OLS) regression analyses were performed using the SPSS 19.0. Comparisons of regression models examined whether and to what extent differential appraisals of cancer experience were associated with virtual health support. OLS hierarchical regression analyses tested the independent and cumulative effects of blocks of variables on the outcome variable of self-reappraisal. The variables were entered in three blocks: (1) demographic, medical, psychosocial measures,^1,2 and virtual health support; (2) illness appraisal measures; and (3) interaction terms between virtual health support and appraisal measures. Within each block, the simultaneous entry procedure was used. The interaction terms tested whether the impact of virtual health on positive self-reappraisal is conditioned by illness appraisals. An interaction exists when the strength of the association between one predictor and the outcome variable changes due to impact of another predictor (Preacher, Curran, & Bauer, 2006).

Results

Respondents’ age ranged from 50 to 79. Most were married (76%) with reported income levels of $50,000 or more (68%), and nearly all of them were Caucasian (97%). Half of the sample had college a degree or higher (53%). Women represented 60% of the sample. Almost 70% had relatively early stage cancer (Stages I and II) and relatively low levels of somatic distress (M = 1.9, SD = 11.0). The number of years of survivorship ranged from 2 months to 14 years. Forty-two percent were diagnosed with breast cancer. Each of the other cancer diagnoses was 5% or less. Participants used virtual support groups approximately 6 times per week for 4 hr. The average number of groups used was two. Time since first participation was approximately 2 years (M = 24.5, SD = 21.5). Respondents, on average, appraised their illness experience to have been quite a bit traumatic and/or challenging experience, and a little opportunity for personal growth. Virtual support was perceived to have been helpful between “somewhat” and “quite a bit.” The results of descriptive analyses in detail are presented in Table 1.

Table 1.

Descriptive Statistics (N = 157).

	Mean (SD) or frequency (%)
Age at cancer diagnosis (range 50–79)	57.0 (6.9)
Gender (Female)	95 (60.5%)
Marital status (married)	120 (76.4%)
Education (range 1–4)	2.7 (1.0)
High school degree or less	20 (12.7%)
Some college education	54 (34.4%)
College degree	37 (23.6%)
Postgraduate degree	46 (29.3%)
Income (range 1–4)	3.0 (1.0)
$ 24,999 or less	12 (7.6%)
$ 25,000–$ 49,999	38 (24.2%)
$ 50,000–$74,999	44 (28%)
$ 75,000 or more	63 (40.1%)
Cancer stage at diagnosis (range 1–4)	2.2 (0.9)
I (In situ)	38 (24.2%)
II (Local)	70 (44.6%)
III (Regional)	24 (15.3%)
IV (Distal)	25 (15.9%)
Somatic distress (range 1–5)	1.9 (0.7)
Months since cancer diagnosis (range 2–168)	31.3 (28.0)
Number of cancer treatments (range 1–5)	1.4 (0.7)
Religiosity (range 1–4)	2.7 (1.0)
Depression (range 1–4)	2.0 (0.5)
Offline social support (range 1–4)	2.8 (0.9)
Perceived benefits of virtual health support (range 1–5)	3.6 (0.8)
Not at all	4 (3.5%)
A little	25 (15.4%)
Somewhat	79 (49.5%)
Quite a bit	46 (28.7%)
Very much	3 (2.9%)
Appraisal of cancer experience (trauma; range 1–4)	3.1 (0.8)
Not at all	5 (3.2%)
A little	34 (21.7%)
Quite a bit	61 (38.8%)
Very much	57 (36.3%)
Appraisal of cancer experience (challenge; range 1–4)	3.4 (0.7)
Not at all	3 (1.9%)
A little	13 (8.3%)
Quite a bit	67 (42.6%)
Very much	74 (47.1%)
Appraisal of cancer experience (growth opportunity; range 1–4)	2.7 (1.0)
Not at all	21 (13.4%)
A little	44 (28.0%)
Quite a bit	48 (30.5%)
Very much	44 (28.0%)
Positive self-reappraisal (range 1–5)	3.6 (0.8)
Not at all	4 (2.5%)
A little	29 (18.4%)
Somewhat	66 (42.0%)
Quite a bit	56 (35.8%)
Very much	2 (1.3%)

Pearson product–moment correlation coefficients showed virtual health support is significantly correlated with measures of illness appraisal (r = .24, p < .001 for personal growth appraisal; r = .29, p < .0001 for life challenge appraisal; and r = .16, p < .05 for trauma appraisal) and with positive self-appraisal after cancer (r = .32, p < .001).

Comparison of regression models (Table 2) indicates that even though both appraisals of cancer experience as a traumatic event and as a challenge that life presents are significant and positively associated with virtual health support (β = .18, p < .05 and β = .23, p < .01, respectively), the β for appraisal of cancer as an opportunity for personal growth has no significant association with virtual support (β = .10, p < .23). Hierarchical regression analyses (Table 3) estimated the effect of virtual health support and its interaction with illness appraisal measures on postdiagnosis self-reappraisal while controlling for the impact of demographic, medical, and psychosocial covariates. The results in Block 1 show that virtual health support is a significant predictor of positive self-transformation (β = .24, p < .01). In Block 2, this association remains significant after controlling for the appraisal measures (β = .17, p < .05). In Block 3, virtual support loses its unique significance when interaction terms were entered into the analysis. Instead, interaction terms between virtual health support and trauma appraisal of cancer (β = .95, p < .05) and between virtual health support and personal growth appraisal are significant (β = −.99, p < .05). A rerun of Block 3 analysis only with interaction terms without virtual support main effect yielded a similar pattern of results. Interaction between virtual health support and trauma appraisal of cancer (β = .78, p < .01) and interaction between virtual health support and personal growth appraisal are found to be significant (β = −.40, p < .04).

Table 2.

Regression of Alternative Appraisal Measures on Research Covariates (N = 157).

	Trauma appraisal	Challenge appraisal	Growth opportunity appraisal
Age at diagnosis	.145 (.012)	.142 (.010)	−.178* (.013)
Female	.140 (.147)	.084 (.146)	−.041 (.171)
Degree	−.080 (.075)	−.057 (.063)	.032 (.088)
Income	.064 (.081)	.012 (.068)	.000 (.095)
Married	.134 (.162)	−.011 (.135)	.345 (.075)
Cancer stage	.163* (.071)	.112 (.060)	.109 (.083)
Somatic distress	−.092 (.116)	−.055 (.097)	−.031 (.135)
Months since diagnosis	.126 (.002)	.011 (.002)	.032 (.003)
Number of treatments	.000 (.105)	−.100 (.087)	−.009 (.122)
Offline social support	.114 (.079)	.080 (.066)	−.015 (.093)
Religiosity	.050 (.069)	.215** (.058)	.212** (.081)
Depression	.242** (.138)	−.069 (.115)	−.252** (.161)
Virtual health support	.184* (.094)	.236** (.079)	.106 (.110)
Intercept	−.470	1.261	4.262
R² (Adjusted R²)	.148 (.07)	.179 (.105)	.208 (.136)
F	1.91*	2.41***	2.89***

Note: *p < .05. **p < .01. ***p < .001.

Table presents standardized parameter (β) estimates with standard errors in parentheses.

Table 3.

Regression of Postdiagnosis Self-reappraisal on Covariates (N = 157).

	Block 1	Block 2	Block 3
Age at diagnosis	−.057 (.011)	−.009 (.010)	.007 (.010)
Female	.152* (.134)	.148* (.124)	.150* (.120)
Degree	−.108 (.069)	−.111 (.063)	−.062 (.062)
Income	.045 (.074)	.041 (.068)	−.004 (.066)
Married	.064 (.148)	.087 (.137)	.094 (.135)
Cancer stage	.163* (.065)	.104 (.060)	.103 (.058)
Somatic distress	.119 (.106)	.140† (.096)	.150* (.094)
Months since diagnosis	.152* (.002)	.133† (.002)	.131* (.002)
Number of treatments	.023 (.096)	.035 (.088)	.037 (.086)
Offline social support	.047 (.073)	.040 (.067)	.026 (.065)
Religiosity	.137† (.064)	.036 (.060)	.018 (.058)
Depression	−.152† (.127)	−.063 (.122)	−.056 (.119)
Virtual health support	.248** (.086)	.179* (.081)	.522† (.344)
Cancer as a traumatic event		.049 (.077)	−.658* (.340)
Cancer as a life challenge		.086 (.095)	.493 (.406)
Cancer as a growth opportunity		.378*** (.061)	1.147*** (.252)
Virtual health support × trauma			.952* (.089)
Virtual health support × challenge			−.647 (.112)
Virtual health support × growth			−.998* (.069)
Intercept	2.186	.745	−.587
R² (Adjusted R²)	.286 (.221)	.425 (.360)	.474 (.401)
F	4.41***	6.48***	6.50***

Note: †p < .10. *p < .05. **p < .01. ***p < .0001.

Table presents standardized parameter (β) estimates with standard errors in parentheses.

In order to understand the nature of these significant interactions, simple slopes analyses (Preacher et al., 2006) were used to estimate the association between self-appraisal and virtual health support across three levels (i.e., not at all, a little, or very much) of trauma and growth appraisal groups (see Figures 1 and 2). A statistical program that helps decompose an interaction in a regression analysis (http://quantpsy.org/interact/index.html) was employed. Results suggested virtual support is significantly associated with positive self-appraisal, particularly among those individuals who reported being very traumatized by their cancer diagnosis (Figure 1), but not as useful for those who reported cancer as an opportunity for personal growth (Figure 2).

Figure 1.

Simple slope analysis of virtual health support × trauma.

Figure 2.

Simple slope analysis of virtual health support × growth.

Assessment of virtual health support and the interaction terms in explaining self-reappraisal are important because removing these measures from Block 3 reduces R² from .47 to .40, and decreases the explanatory capability by 17% ([.47–.40]/.40 = .17). Maintaining virtual support but removing the interaction terms, reduces R² in Block 3 from .47 to .42, which corresponds to a decrease in explanatory power by 12% ([.47–.42]/.42 = .12). If the interaction terms were excluded, the predicted increase in self-reappraisal as a result of using virtual health support would be an overestimate for those who reported positive illness appraisal (i.e., cancer as an opportunity for personal growth) and an underestimate for those who reported negative illness appraisal (i.e., cancer experience as a traumatic event).

Additional analyses to reexamine the associations reported above using the whole sample (N = 350; M = 47.7, SD = 10.8) revealed that even though virtual health support was significantly associated with positive self-appraisal (β =.84, p < .001), none of the interaction terms were significant. This suggests that interaction terms do not condition the association between virtual support and self-reappraisal, and virtual health support is influential on younger respondents’ self-appraisal irrespective of how cancer is appraised.

Discussion

Hierarchical multiple regression analyses reported above demonstrated the significance of the combined effect of virtual health support and its interaction with illness appraisal measures to predict the outcome variable of postdiagnosis self-reappraisal. The findings show that perceived beneficial impact of virtual health support increases with higher levels of appraising cancer as a traumatic experience or as a life challenge. The results also indicate that even though appraisal of cancer as a traumatic experience reduces positive self-reappraisal, those who appraised their illness to have been a traumatic experience perceived virtual support to be more influential on their sense of positive change after cancer. It is possible that experiences, survival stories, role modeling, and encouragement of other patients might be more influential for those who appraise coping with cancer to have been a traumatic experience than those who appraise it to have been a personal growth experience or as a life challenge. This is possibly because peer-to-peer support empowers older adults to be proud of themselves, and contributes to one’s perception of self as the kind of person who can deal with traumatic stressors of cancer, a kind of perception that might add to the individual’s armamentarium of coping skills. Feeling understood, receiving experiential advice, and insider perspectives due to shared illness identity may meet the needs of those who report trauma appraisal more and/or better. In fact, perceived benefit of virtual support on positive self-appraisal is reduced if illness is appraised as an opportunity for personal growth, possibly as a result of other factors such as personality dispositions (Linley & Joseph, 2004; Sears et al., 2003).

Interestingly, offline social support from relatives and friends was not significant predictor of positive self-reappraisal. This result is consistent with the results of prior research (Cordova et al., 2001). The crucial contingency regarding the impact of social support on positive self-reappraisal might be the compatibility of the support needs of the patient and the extent to which support providers are able to meet illness-specific support (Høybye, Johansen, & Tjørnhøj-Thomsen, 2005; Turner, 1966). Because virtual health support is provided by patients with experiential knowledge of cancer, mutual understanding of each others’ experiences, rather than companionship and availability of help, might be the reason that online, but not offline, social support was significant (Drenta & Moren-Cross, 2005; Janoff-Bulman, 1992). Support communication in online networks can thus be an effective resource for older people to draw upon when coping with a life-threatening chronic illness (Godfrey & Johnson, 2009).

The significance of this study is limited by several issues. First, the sample was predominantly upper middle class, almost completely Caucasian, and reflected the confluence of race- and class-based disparities in using virtual support technology. However, this is a commonly reported limitation in Internet-based data collection methodology (Cullen, 2006; Shaw et al., 2006). Because appraisal of illness experiences may differ by ethnic background, future studies should reexamine the associations with more diverse samples possibly by recruiting respondents from users of websites, which are designed to address health-related information and support needs of minority populations. Second, the study did not measure various aspects of illness experiences (e.g., social roles, sexuality, financial worries), which might be differentially appraised resulting in differential appraisal of perceived benefit of using virtual support. Third, personality variables, which might have led to reports of positive self-reappraisal, were not measured (e.g., dispositional optimism). Fourth, the data set did not have enough sample of older adults who were 65 years of age and older (n = 18) to permit a subsample analysis between middle-aged and older respondents (e.g., between 50–64 and 65 and older). Future research should perform a subsample analysis with a larger sample of older adults. Additionally, a randomized controlled trial might be conducted to compare the beneficial impact of virtual health support groups to face-to-face groups. Furthermore, probing interaction terms and decomposing conditional associations will yield additional insights into the nature of the relations observed between predictor variables (Preacher et al., 2006).

Despite these limitations, this study is among the first to include offline and online social support as separate measures in assessment of illness appraisal and self-appraisal. Moreover, this study includes alternative appraisals of illness experience together in the same study. Most studies inquire about the negative impact of cancer, and do not acknowledge the possibility of coexisting cognitive appraisal processes. Additionally, this study includes a comprehensive measure of virtual health support in order to examine how use of support communities on the Internet might affect illness appraisal in later life.

Conclusions

As Eysenbach (2005) stated “while little rigorous evidence exists on the effectiveness of virtual communities, virtual communities may well be the one Internet application area with the biggest impact on health outcomes” (p. 102). There are two major conclusions from this research: (1) virtual health support has a significant effect on positive self-reappraisal subsequent to cancer among older adults and (2) virtual health support is perceived to be differentially helpful depending on whether cancer is judged to be traumatic experience or an opportunity for personal growth. While the perceived positive impact of virtual support on positive sense of self is heightened if cancer is perceived to be a traumatic event, the strength of the association is reduced if illness experiences are perceived to be an opportunity for personal growth.

Given that computer-connected aging baby boomers will be main beneficiaries of information and communication technologies for health and medical purposes (Mitzner et al., 2010; Pfeil & Zaphiris, 2009; Wagnet et al., 2010; Yoon et al., 2011), and the decline in offline support networks in old age, the importance of the Internet-enabled social relationships further increases (Xie, 2007; Wright & Query, 2004). The present study addresses an important gap in understanding the potential online support groups have for cancer care of aging adults.

Footnotes

Appendix A

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

Author Biography

Gül Seçkin is a medical sociologist. She got her Masters degree from the University of Southern California in Los Angeles, California and her PhD from Case Western Reserve University in Cleveland, Ohio.

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