Forms of social support and their relationships to mental health in HIV-positive persons

Forms of social support and their relationships to mental health

in HIV-positive persons

Warren A. Reicha*, David W. Lounsburyb, Soye Zaid-Muhammadc andBruce D. Rapkinb

aThe Family Center, 315 W. 36 Street, 4th Floor, New York, NY, USA; bDepartment ofEpidemiology and Population Health, Albert Einstein College of Medicine of Yeshiva University,New York, USA; cDepartment of Psychiatry and Behavioral Sciences, Memorial SloanKettering Cancer Center, New York, NY, USA

(Received 6 August 2009; final version received 14 January 2010)

A baseline assessment for an HIV health services study recruited 626 people livingwith HIV/AIDS (PLWHA) in New York city who participated in an interviewquerying social support, health status, substance use, and mental health. Datawere modeled using hierarchical classes (HICLAS) analysis. HICLAS discrimi-nated items reflecting general support and assistance vs. support from animportant person in one’s life who was named in addition to other familymembers and friends. HICLAS then identified respondents who reported thatthey had general support and assistance, support from an important person, bothtypes, or neither type of support. Having one or more important persons as partof the respondent’s social network was associated with more positive mental (butnot physical) health than having only general support and assistance, or nosupport at all. Results argue for differentiating support obtained through one’srelationship with an important person.

Keywords: social support; mental health; HIV/AIDS

Introduction

People living with HIV/AIDS (PLWHA) are known to be at substantially elevatedrisk for mental health problems, including depression, anxiety, and chronic stress(Bing et al., 2001; Brackis-Cott et al., 2007; Ciesla & Roberts, 2001; Pence et al.,2006). Although the causal relationship between HIV and mental health impairmentis complex (Ferrando et al., 1998; Rabkin, 2006), it is clear that dysphoria inhibitsthe capacity of PLWHA to maintain their health (Boarts et al., 2006; Gonzalezet al., 2004; Leserman et al., 1997; Murphy et al., 2002). This has public healthconsequences in that depressed PLWHA spend more on health care than do theirnon-depressed counterparts (Joyce et al., 2005), and indeed have a greater likelihoodof AIDS-related mortality if they do not seek mental health treatment (Cook et al.,2004). The risk to health care posed by mental health challenges is cause for concerninto the future with increasing longevity among PLWHA.

*Corresponding author. Email: [email protected]

Psychology, Health & Medicine

Vol. 15, No. 2, March 2010, 135–145

ISSN 1354-8506 print/ISSN 1465-3966 online

� 2010 Taylor & Francis

DOI: 10.1080/13548501003623930

http://www.informaworld.com

Countervailing this tendency is the well-documented positive impact of socialsupport for PLWHA. Negative correlations between social support and dysphoriahave been observed in diverse samples of HIV-positive individuals (Lam, Naar-King, & Wright, 2007; Mizuno et al., 2003; Remien et al., 2006; Simoni, Frick, &Huang, 2006). Conversely, a sizable body of literature reports positive correlationsbetween social support and improved mental health in terms of self-esteem, positiveaffect, life satisfaction, and subjective and health-related quality of life (Gonzalezet al., 2004; Heckman, 2003; Jia et al., 2005; Stewart, Cianfrini, & Walker, 2005;Zea et al., 2005). Social support would seem to be a clear mechanism through whichthe mental health needs of PLWHA could be addressed.

Social support: theoretical and measurement issues

Social support is an umbrella term for a complex, multidimensional construct(Helgeson, 2003; Thoits, 1986), and the research cited above has operationalized thisconstruct in several ways – support network size, received support, satisfaction withsupport, instrumental support, and emotional support, to name a few. Althoughthese facets are often correlated with one another (Simoni, Frick, & Huang, 2006),they are not identical, and do not always predict mental health equally well amongPLWHA. Silver, Bauman, Camacho, and Hudis (2003) found that psychiatricsymptoms were associated with lower adequacy, but greater receipt of socialsupport. Ingram, Jones, Fass, Neidig, and Song (1999) reported that well-being wasa function of satisfaction with social support, but not with the number of supportnetwork members, and McDowell and Serovich (2007) found that mental health wasmore closely associated with perceived than actual social support. The source ofsupport appears to have an impact as well. Crystal and Kersting (1998) found thatwhile friend support ameliorated depression under low-stress conditions, only familysupport was effective under high-stress conditions. Kalichman, DiMarco, Austin,Luke, and DiFonzo (2003) found that lower depression was associated with supportfrom father, brother, and extended family, but not from sisters and friends. Thisbrief sampling of research shows substantial variation in the ways social support isconceptualized and operationalized.

In the present study, we performed an exploratory analysis of binary (yes/no)items on a brief social support measure reflecting instrumental, emotional, andinformational support, using a clustering procedure that to our knowledge has notbeen applied to survey data from PLWHA. We modeled the data using a hierarchicalclasses procedure (HICLAS; De Boeck & Rosenberg, 1988) that makes no a prioriassumptions about the item clusters. HICLAS empirically arranges items into classesaccording to the subsets of respondents endorsing them. For example, if 10respondents answer ‘‘yes’’ to items A and B, and four of these respondents respond‘‘yes’’ to item C, then item C would be located in a separate class from A and B. Thetwo classes would, however, be linked to reflect the subset of four respondentsendorsing all three items. This approach differs from factor analysis, which findsunderlying orthogonal dimensions.

HICLAS simultaneously classifies respondents and items. Thus, we were able tocompare the self-reported mental health across respondent classes, i.e. among thosewho endorsed different sets of social support items. We hypothesized that socialsupport will be correlated with better mental health. Beyond this, our methodologyallowed us to determine whether mental health is better predicted by a unitary

136 W.A. Reich et al.

aggregate or by disaggregated subsets of these items – and if so, which item(s)comprise these subsets.

The present data come from the National Institute of mental health-fundedfamily access to care study (FACS). FACS assessed the feasibility of formingpartnerships between frontline AIDS service providers and health behavioralresearchers to disseminate evidence-based interventions to families affected by HIV(Lounsbury, Murphy, Robinson, & Rapkin, 2007).

Method

Participants

We sampled agencies by reviewing New York City HIV/AIDS service directories anda listing of Ryan White CARE Act Fund recipients. Eligible agencies includedprivate and public facilities with a caseload of at least 50 adult HIV/AIDS clients.Agencies had to have been in operation for at least three years and had to offer directmedical, mental health, or social services to clients. Based on these criteria, wegenerated a list of 160 community-based agencies serving PLWHA. To minimizebias, agencies were put into random sequence, then stratified according to whetheror not they offered primary care services. Of the 24 that were approached,16 community-based service agencies and clinics and six hospital-based clinics agreedto participate. They received $500 for their time.

Participants were recruited from these 22 sites between 2003 and 2005 throughflyers, face-to-face contact, and provider referrals. To be eligible for the study,participants had to be at least 18 years old, speak English or Spanish, and havereceived services for at least three months. Approximately 30 participants wererecruited from each agency, for a total of 626. The mean age was 47.16 years(SD ¼ 8.95, range 18–70). Most were heterosexual (68.8%) and typically had beenliving with HIV/AIDS for approximately 10 years.

Procedure

Individual respondents were interviewed either in their service agency or in thelaboratory at Memorial Sloan-Kettering Cancer Center. The interview elicited anarray of information about clients’ overall health, access to and satisfaction withhealth care and other supportive services, and information about health behaviors,health status (e.g. AIDS diagnosis), and substance use (e.g. current alcohol use).The interview also queried social network ties with questions taken from Baumanand Weiss’ (1995) measure (items are listed in Appendix 1). Each item includeda yes/no question and an open-ended follow-up (e.g. ‘‘Is there someone whowould lend you $50?’’ ‘‘If yes, who would lend you $50?’’). Respondents couldname multiple persons for each question. This egocentric method for collectingsocial network data reflected our concern with the effect of support on a focalindividual’s mental health.

Mental health

The interview also included the five-item Mental Health Index (MHI; McHorney &Ware, 1995), a general self-report measure of dysphoria (e.g. ‘‘Have you been a verynervous person?’’ ‘‘Have you felt downhearted and blue?’’). The mean score was 4.24

Psychology, Health & Medicine 137

(SD ¼ 1.07), and reliability was good, a ¼ 0.81. MHI was unrelated to respondentsex, t ¼ 0.16, p ¼ 0.86, and was marginally related to age, r ¼ 0.07, p 5 0.06.

Hierarchical classes analysis

HICLAS is a two-way clustering procedure for binary data (De Boeck & Rosenberg,1988). In the present study, we used HICLAS to model respondents’ answers to the13 yes/no questions in the interview (not the open-ended follow-up questions or theMHI). HICLAS forms classes of respondents (two respondents are located inthe same class if they endorse the same items), and classes of items (two items arelocated in the same class if they are endorsed by the same respondents). HICLASthen links respondent classes to item classes so that one can easily see whichrespondents answered which items affirmatively. Respondents and items that do notfit the structure are placed into an unclassified ‘‘residual’’ category.

Interview data were formatted into a binary matrix for HICLAS. Respondentswere represented in the rows of this matrix, and items represented in the columns.For example, row eight, column six was the eighth respondent’s answer to whether s/he had someone who would lend $50. Each cell contained a ‘‘1’’ (yes) or a ‘‘0’’ (no).We used the HICLAS output to examine the differential endorsement of socialsupport items and code variables for use in the prediction of mental health.

Results

HICLAS analysis

Since this methodology is new to interview research with PLWHA, we conducted asplit-half analysis to determine the reliability of the HICLAS-derived item classes.To this end we created two 313 (respondents) by 13 (items) matrices by an even–oddsplit, and performed a separate HICLAS analysis on each. Eleven of the 13 itemswere placed in the same structural location in both HICLAS outputs. Since theseanalyses were run independently, there was no guarantee that any two items wouldbe classified together both times. These 11 items are shown in the bottom half ofFigure 1 (respondents appear in the top half). The remaining two items weredropped from the analysis because they were not reliably placed in the structuresfrom two independent HICLAS runs, and because they were not central to the aimsof this study.1

HICLAS identified seven classes of respondents and five classes of items. Figure 1shows that Respondent Class 1 was linked to Item Classes A, D, and E; RespondentClass 2 to Item Classes B and E; and Respondent Class 3 to C, D, and E;Respondent Class 4 was linked to Item Classes A, B, D, and E (and so on forRespondent Classes 5, 6, and 7). Figure 1 also shows the mean MHI score withineach class of respondents.

Classifying social support items

Figure 1 shows that HICLAS located five social support items in Item Class E. It didso because these items were simultaneously endorsed by the same set of respondents,in fact by a larger proportion of the sample (91%) than any other items. Because thecontent of Class E reflected a range of social supportive functions, we assigned it thelabel ‘‘support and assistance.’’ HICLAS also indicated that a sixth item, located in


Item Class A (‘‘Are there other important people in your life?’’), was endorsed bysome, but not all respondents who responded ‘‘yes’’ to the Class E items (51% of thetotal sample). Those indicating an important person were more likely to have hadsomeone come to them for help in the previous four weeks (Class A and Class D arelinked).

Predicting mental health

Next, we sought to determine which combination(s) of item classes were associatedwith positive mental health. The first step was to create three indicator variablesfrom the HICLAS output. Respondents linked to Item Class A (Respondent Classes

Figure 1. HICLAS classification of respondents and items, with class-wise mental healthindex scores. Note: High MHI (Mental Health Index) scores reflect positive mental health.Respondent classes (top) are linked to Item classes (bottom) through the bold vertical lines.For example, respondent classes 1, 4, 5, and 7 are linked to Item classes A, D, and E throughthe leftmost vertical line.


1, 4, 5, and 7; n ¼ 318) were assigned a score of 1 for the variable important person; 0otherwise. Likewise, those linked to Item Class B (Respondent Classes 2, 4, 6, and 7;n ¼ 257) were assigned a score of 1 for AIDS dx, and those linked to Item Class C(Respondent Classes 3, 5, 6, and 7; n ¼ 223) were assigned a score of 1 for drinker (0otherwise). A multiple regression analysis (shown in Table 1) revealed that having animportant person was significantly associated with higher MHI scores.

Subsequent analyses with non-HICLAS variables revealed that having animportant person was associated with being female, r ¼ 0.11, older, r ¼ 0.09, andmore able to deliver help that was asked for in the last 4 weeks, r ¼ 0.11, p 5 0.05.Those who endorsed having an important person in addition to other supportersalready named in Class E items reported that the help they received met their needs,w2(1) ¼ 3.55, p ¼ 0.06, and experienced less interference with their own needs due toassisting others r ¼ 70.12, p 5 0.05. Yet, they were more likely to have a non-HIVmedical illness, w2(1) ¼ 38.75, p 5 0.001 and to have network members with seriousillness or psychiatric/substance abuse problems, r ¼ 0.09 and 0.11, p 5 0.05. Most(59.47%) of those named as ‘‘other important persons’’ were siblings, children, orother relatives, and another 18.67% were friends.

We then conducted a one-way ANOVA with three groups: those not linked tosupport and assistance (i.e. respondents in the residual), those linked to support andassistance but not to important person (Respondent Classes 2, 3, and 6), and thoselinked to both support and assistance and to important person (Respondent Classes1, 4, 5, and 7). The omnibus effect was significant, F(2, 623) ¼ 10.48, p 5 0.001, andDunnett’s test revealed that the important person group scored higher than the othertwo groups on the MHI, ps 5 0.04.2

Discussion

HICLAS led to observations about the structural relationships among social supportsurvey items, and to conclusions about their correlation with mental health. Thisnovel analytic strategy produced a hierarchical structure that distinguished supportfrom an important person, which was reported by an identified subset of respondentsendorsing other forms of support and assistance. The present results argue fordifferentiating this component of social support in theoretical models andmeasurement instruments. That most respondents reported at least some supportmay reflect our sampling strategy which ensured that all were receiving services froman HIV provider agency; thus our results can only be generalized to PLWHA in care.Yet many did not report having important persons in their lives beyond those namedfor their willingness to provide general support.

Table 1. Predicting mental health from HICLAS-derived indicator variables.

Cumulative R2 b

0.03*Sex 0.01Age 0.06Important person 0.14*AIDS dx 0.07Drinker 70.03

*p 5 0.01. A higher value on the outcome reflects more positive mental health.


Social support and mental health

Results confirmed the prediction that social support is correlated with better mentalhealth. Our findings build on the literature by demonstrating that receiving supportfrom an important person incrementally predicted mental health beyond receivingother forms of support. These findings, which are in line with the established benefitsof having a confidant (Baumeister & Leary, 1995; Rook, 1987), leave open questionsof why and how these social network members are beneficial to PLWHA. Extantresearch has demonstrated that supporters of PLWHA ward off hopelessness(Johnson et al., 2001), quell loneliness (Schneider, Taylor, Hammen, Kemeny, &Dudley, 1991), discourage avoidant coping (Weaver et al., 2005), and reinforcepositive states of mind (Gonzalez et al., 2004). Investigations of the manner in whichsupport is given and received would add to our knowledge of why ‘‘importantpersons’’ seem advantageous to PLWHA’s mental health. If network ties withimportant persons – in the present sample, primarily family members – arecommunal relationships, one would expect that these persons offer support based onjudgments of need, not fairness or normative pressure to return favors (Clark &Mills, 1979). If this support is offered in a non-directive manner, it might (unlikedirective support) foster the recipient’s sense of autonomy, hope, and optimism(Harber, Schneider, Everard, & Fisher, 2005). That all respondents with animportant person were also connected to other forms of support further suggeststhat these PLWHA enjoyed the advantages of both strong and weak social networkties, the latter affording them access to resources, expertise, and information notprovided by the more emotionally grounded close relationships (Granovetter, 1983).

Those with an important person were more likely to have recently been asked tohelp someone, and were more able to deliver that help without interfering with theirown needs. Yet they were also more likely to suffer from illness in addition to HIVand to have social network members with serious illness, psychiatric and/orsubstance abuse problems. These findings suggest that actively caring for someoneplays a role in promoting positive mental health, even in emotionally (and medically)difficult circumstances. Future research might profit from exploring the mentalhealth benefits for PLWHA of enacting supportive roles to others (Liang, Krause, &Bennett, 2001; Strazdins & Broom, 2007).

The one-shot correlational design of this study cannot rule out the possibilitythat positive mental health leads PLWHA to better maintain close relationships. Akey feature of dysphoria is the tendency to withdraw from or not function well insupportive relationships (Coyne et al., 1987; Thoits, 1983). Maher, Mora, andLeventhal (2006) found that depressive cognitions about self and others predictedsubsequent reductions in perceived social support. Yet social support has predictedreductions in depressive symptoms in those at risk for HIV/AIDS (O’Brien,Wortman, Kessler, & Joseph, 1993), and supportive interventions have been shownto ameliorate depression in PLWHA (Simoni, Pantalone, Plummer, & Huang, 2007).It seems likely that both causal paths exist.

Implications for intervention

Our results suggest that HIV service providers engage in targeted outreach to thosewithout an important person, especially to younger men. A subtle implicationemerging from our analyses is that many younger and male participants did have a


support network addressing a variety of needs. Their mental health might, however,represent a vulnerability as they did not name an additional important person suchas a family member when asked.

A logical next step for interventionists would be to develop ways of fosteringsupportive relationships for those who do not report having one. Complexities arise,however, when one grapples with issues of who this person should be, and what he orshe should be doing. For example, is it more effective to cultivate existing intimaterelationships, as Remien et al. (2005) have successfully done, than to find ways tocreate new ones? Perhaps – yet, HIV/AIDS presents concerns, such as HIVdisclosure, best addressed by a new and trusted member of one’s social network(Brackis-Cott, Mellins, Dolezal, & Spiegel, 2007; Kalichman et al., 2003). We need tounderstand more about the value of supportive relationships for the purpose offostering sustained health and wellness for PLWHA and for others in their lives.Whatever the purpose or arrangement might be, our results suggest that treatmentinterventions seek to create, build, and maintain close personal relationships.

Acknowledgments

This research supported by NIMH 5R01-MH063045 (Rapkin, B., PI). The authors wish tothank Jan Hudis for her comments on an earlier draft of this manuscript.

Notes

1. The two remaining items were being a smoker and experiencing HIV symptoms.2. A cluster analysis (Lounsbury et al., 2006) identified four groups of agencies. This

grouping was not related to MHI, F(3, 622) ¼ 1.34, p ¼ 0.26, or to important person,w2(3) ¼ 4.91, p ¼ 0.18.

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Appendix 1.

Binary social support items modeled using HICLAS

Is there someone who would take care of you if sick in bed?Is there someone who would lend you $50?Is there someone you can depend on to help you in an emergency?Is there someone who gives you information or advice?Is there someone you can talk to about HIV?Did anyone come to you for help in the last 4 weeks?Are there other important people in your life?


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