Social support and quality of life over time among adults living with HIV in the HAART era

Social support and quality of life over time among adults living with HIV in the HAART era

ARTICLE IN PRESS Social Science & Medicine 58 (2004) 1353–1366 Social support and quality of life over time among adults living with HIV in the HAAR...

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ARTICLE IN PRESS

Social Science & Medicine 58 (2004) 1353–1366

Social support and quality of life over time among adults living with HIV in the HAART era Robert Burgoynea,b,*, Rebecca Renwickc,d a

Immunodeficiency Clinic, Toronto General Hospital, 200 Elizabeth St., Toronto, Ont., Canada M5G2C4 b Department of Psychiatry, University of Toronto, 250 College St., Toronto, Ont., Canada M5T1R8 c Graduate Department of Rehabilitation Science, University of Toronto, 500 University Ave., 9th Floor, Toronto, Ont., Canada M5G1V8 d Quality of Life Research Unit, University of Toronto, 500 University Ave., 9th Floor, Toronto, Ont., Canada M5G1V8

Abstract Stability in perceived social support and associations between social support and health-related quality of life for a sample of 41 adult outpatients living with HIV/AIDS (PHA) in Canada were assessed longitudinally. Construct-specific dimensions of the Medical Outcomes Study Social Support Survey (SSS), the Physical and Mental components of the Short-Form-36 (SF-36) quality of life measure, as well as clinical factors (i.e., symptomatology, immunologic/virologic variables), were measured in three waves: initial consecutive registration (T1, 1997), 2-year (T2, 1999) and 4-year (T3, 2001) follow-up, and evaluated for changes using repeated-measures analysis of variance, supplemented by Friedman tests for SSS and SF-36 ratings. Proportions of the PHA sample with clinically significant SSS changes (i.e., greater than 0.5 standardized effect size) were also calculated. Effects of improvement versus deterioration in SSS ratings on SF-36 ratings, and vice versa, were explored. Associations between SSS and SF-36 ratings, as well as between changes in SSS ratings and SF-36 ratings, were assessed using multiple regression analyses controlling for clinical factors. Cross-lagged analyses were conducted to examine predictive potential between SSS and SF-36 ratings. Clinical outcomes suggested immunologic improvement tempered by symptoms and/or treatment side effects. SSS and SF-36 mean ratings were moderately stable over time, but clinically significant 4-year decrements in SSS ratings occurred for approximately 40% of patients. A trend occurred in which poorer SF-36 mental outcomes portended poorer emotional and informational support. Otherwise, relations between SSS and SF-36 ratings appeared to be reciprocal. Cross-sectional associations between SSS and SF-36 ratings were more pronounced at T2 compared to baseline and T3. Changes in SSS and SF-36 ratings were somewhat related over the consecutive 2-year periods but not over the long term. T1–T2 SSS changes were associated with changes in the SF-36 mental component. T2–T3 SSS changes were associated with changes in the SF-36 physical component. Cross-lagged analyses yielded little explanation concerning direction of causation in terms of associations between social support and quality of life for the PHA in this study. r 2003 Elsevier Ltd. All rights reserved. Keywords: Canada; Social support; Quality of life; Antiretroviral; HAART; HIV/AIDS

Introduction Previous research with respect to people living with HIV/AIDS (PHA) has highlighted social support as an *Corresponding author. Immunodeficiency Clinic, Toronto General Hospital, 200 Elizabeth St., Toronto, Ont., Canada CWG-315. Tel.: +1-416-340-4800x8609; fax: +1-416-3404890. E-mail address: [email protected] (R. Burgoyne).

important determinant of health outcomes. Perceived support has been found to be associated with adjustment and coping in relation to HIV diagnosis and its potentially chronic, disabling course (Britton, Zarski, & Hobfoll, 1993; Crystal & Kersting, 1998; Friedland, Renwick, & McColl, 1996; Grummon, Rigby, Orr, Procidano, & Reznikoff, 1994; Hays, Turner, & Coates, 1992; Leserman et al., 1999; Linn, Lewis, Cain, & Kimbrough, 1993; Pakenham, Dadds, & Terry, 1994; Patterson et al., 1996). In the context of highly active

0277-9536/$ - see front matter r 2003 Elsevier Ltd. All rights reserved. doi:10.1016/S0277-9536(03)00314-9

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antiretroviral therapy (HAART) treatment regimens, the focus has shifted somewhat from an emphasis on the psychoneuroimmunological effects of stress and the potential buffering aspects of social support. More recently, research has investigated social support as a potential mediator in terms of the degree to which such things as treatment adherence and resource accessibility influence clinical outcome (Catz, Kelly, Bogart, Benotsch, & McAuliffe, 2000; Gifford et al., 2000; Gordillo, Del Amo, Soriano, & Gonzalez-Lahoz, 1999; Roberts, 2000; Singh et al., 1999). Quality of life has also been identified as a key component of overall health among PHA (Badia, Podzamczer, Garcia, Lopez-David, & Consiglio, 1999; Copfer et al., 1996; De Boer, Sprangers, Aaronson, Lange, & Van Dam, 1994; Lamping, 1994; Lubeck & Fries, 1993; O’Keefe & Wood, 1996; Wu, 2000). Although social support and quality of life appear to figure as salient factors affecting overall health and wellness status for PHA, there is a dearth of research examining their interrelations. A recent review article cited social support as an important factor affecting quality of life among PHA, yet identified that there was scant research in which the relationship between social support and quality of life had been addressed for this population (Douaihy & Singh, 2001). Research related to this question has been more prominent during the latter part of the second decade in which HIV/AIDS has received attention (Bastardo & Kimberlin, 2000; Cederfjall, Langius-Eklof, Lidman, & Wredling, 2001; Gielen, McDonnell, Wu, O’Campo, & Faden, 2001; Heckman, Somlai, Sikkema, Kelly, & Franzoi, 1997; Singh et al., 1998; Swindells et al., 1999). Although the degree of social support stability over time or potential influence of perceived social support on quality of life outcomes for PHA has not been thoroughly examined, recommendations to explore causal relationships between social support and quality of life have been highlighted in previous HIV-related research (Friedland et al., 1996). Causal directionality of relations between social support and overall health for PHA is unclear. At issue is whether social support promotes psychological well-being or, alternatively, whether good health attracts positive social support and poor health leads to requirements for psychological adaptation that render social support more challenging to maintain (Green, 1993; Kaplan, Patterson, Kerner, & Grant, 1997). Exploring causality is complicated by the possibility of shifts over time in the direction of the relationship between support and health (Nott, Vedhara, & Power, 1995). Similar questions can be applied to consideration of the causal relationships between social support and health-related quality of life among PHA. Exploring the causal directionality between social support and health, including its quality of life component, requires a comprehensive and systematic

evaluation of the temporality, strength, consistency, gradient and plausibility of associations between the two variables of interest (Kaplan et al., 1997). The purpose of this study was to systematically assess social support stability as well as cross-sectional associations between social support and quality of life and longitudinal relations between changes in social support and quality of life for a sample of HIV-positive adults over an extended period of outpatient clinical care in the context of HAART. Social support and quality of life ratings obtained at the time of initial consecutive outpatient clinic registration of a cohort of adult PHA were compared to ratings available at 2- and 4-year follow-ups. In addition, predictive potential and causal directionality between social support and quality of life as well as changes in these factors over time were examined.

Methodology Sample characteristics The study sample consisted of PHA outpatients attending a tertiary-care HIV/AIDS ambulatory clinic located in an urban-core teaching hospital in Toronto, Canada. Selected demographic and medical characteristics of the sample are outlined in Table 1. The sample derived from an inception cohort of 75 outpatients based on consecutive new patient referrals over a 1-year period beginning shortly after the first widespread accessibility of HAART in Canada in 1997 (T1). Patients in this cohort maintained continuity of specialty care provided in the Clinic following initial assessment. Potential participants were approached by clinical staff in the context of initial orientation to clinic services and asked to complete an information form along with standardized measures of social support and quality of life. Approximately 11% of newly registering patients

Table 1 Clinic outpatient adults living with HIV/AIDS sample characteristics at baseline N ¼ 41 Gender Age Time since diagnosis Disease stage Mean CD4 count Mean viral load Mean symptom count

35 male (85%), 6 female (15%) Mean 38.8 years; range 22–61 years Mean 52 months; range 1–144 months 29% asymptomatic; 32% symptomatic; 39% AIDS 315 cells/ml 3.9 log10 copies/ml 1.8 symptoms; 1.9 for symptomatic, 3.0 for AIDS

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declined participation at the first interview as well as when offered arrangements for completion of the surveys at their subsequent follow-up visit. Other data collected included basic demographic information (age, gender, relationship status), medical history (time from diagnosis, disease stage), immunologic/virologic status (CD4 count, plasma viral load), opportunistic infections and HIV-related symptoms and/or treatment side effects. Disease stage incorporated three subsample groups as an ordinal variable. Participants were classified as ‘asymptomatic’ if they had no HIV-related constitutional symptoms, ‘symptomatic’ if they had at least one such symptom, and as having ‘AIDS’ if they were symptomatic with a history of opportunistic infection(s) and/or CD4 count less than 200 cells/ml. Serum HIV concentrations (absolute viral load) were log10 transformed in order to conform to the assumptions of normal distribution. Patients were also designated according to whether viral load was ‘detectable’, that is, whether the amount of virus was sufficient to reach the observable threshold on a standard HIV viremia assay (i.e., absolute viral load: 50 copies/ml). A minority of patients had commenced HAART prior to initial Clinic registration. For the purposes of the study, HAART was defined according to standard treatment guidelines (Carpenter et al., 1997), and comprised a combination of antiretroviral medications consisting of at least two nucleoside reverse transcriptase inhibitor (NRTI) drugs along with a minimum of one protease inhibitor (PI) drug or one non-nucleoside reverse transcriptase inhibitor (NNRTI) drug. NNRTI medications became more prevalent as the duration of the follow-up period progressed. The study was given approval by the research ethics review board of the hospital and the university with which it is affiliated. Informed consent was required and complete patient confidentiality was guaranteed. Throughout 1999 (T2), patients were approached to complete a second administration of the survey measures at a time coinciding with 2-year (71 month) anniversary dates of receiving clinic services. At that time, 56 patients participated. Among the 19 patients (25% of inception cohort) who could not be assessed at follow-up, two had died in the interim, two were too ill to participate, eight declined when approached, and seven could not be located. Data were again collected on medical and immune function factors for the 56 patients. The majority of participants at 2-year follow-up had been consistently taking HAART over the 2 years. One patient had discontinued medications due to adverse events during medication induction and four individuals had attended appointments but had held off commencing HAART due to stable immune system functioning. Data from a third wave were collected during 2001 (T3) in the same manner for 41 patients, coinciding with 4-year post-registration anniversary dates. Of the 15

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patients assessed at baseline and T2 but not at the 4-year endpoint, two additional patients had died, five patients were known to have moved to other cities, four patients declined participating, and four patients could not be located at follow-up subsequent to T2. Patients who could not be located at T3 had been medically stable at T2 and may have transferred to another specialty clinic or were possibly receiving sole medical management from one of several ‘HIV primary care’ general practice physicians in the community. The longitudinal analysis does not account for participant attrition. Missing data were not imputed for patients who did not participate at follow-up because there was no basis upon which to extrapolate from assessments conducted 2 years previously. Therefore, available data only were analyzed and no data were carried forward to subsequent study points in time. However, as a group those patients who were willing and able to participate at 2- and 4-year follow-ups were indistinguishable at baseline from follow-up non-participants on all study variables assessed at that initial point in time, as determined by w2 tests for categorical variables, independent samples t-tests for continuous variables, and deconstructed w2 tests for proportions of disease stage groups. The majority (83%) of study participants at final (T3) follow-up had been consistently taking HAART over the 4-year study period. One patient had a protracted medication discontinuation period due to adverse events during induction, but eventually resumed a HAART combination. One patient was on dual combination therapy only and two patients were in a planned treatment interruption period at the time of final follow-up. Of the four individuals not on HAART prior to T2 due to stable immune system functioning, one had commenced HAART by T3 follow-up. Social support and quality of life measurement Perceived social support was measured using three self-perceived qualitative functional support dimensions of the Medical Outcomes Study (MOS) Social Support Survey (SSS) (Sherbourne & Stewart, 1991), abbreviated herein as the SSS. The three multi-item dimensions represent types of support available ‘if needed’ from unspecified sources: Affectionate support (expressions of love and affection), Positive Social Interactional support (availability of others with whom to share enjoyable time), and Emotional–Informational support (understanding, encouragement, guidance and information). For items within the subscales, the raw score is measured on a five-point Likert scale ranging from ‘none of the time’ to ‘all the time’. The converted scores for each subscale (i.e., the average of subscale items) range from 0 to 100. Higher ratings reflect higher availability of social support. Normative scores of a comparison medical population are based on MOS

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survey results obtained from approximately 3000 adult English-speaking, mainly Caucasian (79%) ambulatory United States patients diagnosed with at least one of four treatable chronic conditions: hypertension, diabetes, coronary heart disease, or depression. Health-related quality of life was measured using the MOS Short-Form-36 (Ware, Snow, Kosinski, & Gandek, 1993), also known as the SF-36. The SF-36 is a generic health-related questionnaire consisting of 36 items representing eight dimensions of quality of life. Possible scores on each dimension range from 0 to 100. Higher scores reflect better quality of life and fewer role limitations. The eight dimensions are: physical functioning, body pain, role limitations due to physical problems, general health perception, vitality/energy, social functioning, mental health, and role limitations due to emotional problems. The SF-36 measure has normative values for the general population, including mean scores according to age categories, as well as reference scores for various outpatient medical populations (McHorney, Kosinski, & Ware, 1994; Ware et al., 1993). The SF-36 has been the instrument of choice in a number of previous HIV-related quality of life research studies (Bing et al., 2000; Burgoyne & Saunders, 2001; Hays et al., 2000; O’Keefe & Wood, 1996; Saunders & Burgoyne, 2002; Swindells et al., 1999; Tsevat et al., 1996). For confirmatory purposes, a statistical data reduction was applied, consisting of principal components factor analysis of the eight SF-36 subscales. A twofactor solution evolved, in which a physical component factor and a mental component factor were extracted. These findings were compared to previous results for larger samples reported in the MOS literature and found to be consistent. Therefore, SF-36 physical and mental summary scores were calculated in this study utilizing the standard algorithms as described in that literature (Ware, Kosinski, & Keller, 1994; Ware et al., 1995). The advantages of physical and mental scores relative to the specificity of the subscales are that they can be utilized to represent overall quality of life for the purposes of simplicity and to reduce greater potential alpha error posed by statistical analysis using all eight subscales as opposed to the physical and mental quality of life components. The physical and mental ratings are depicted as T-scores, with a score of 50.0 representing the general population normative reference value. As such, they tend to conform better to the assumptions of normal distribution for parametric tests and result in minimal tie ranks that might compromise the rigor of non-parametric tests. Analysis Data analyses were conducted using Version 10.0 of Statistical Products and Service Solutions (SPSS). Mean

values of clinical indicators (i.e. CD4 count, viral load, number of symptoms), as well as SSS ratings and SF-36 ratings for the total T3 follow-up study sample were evaluated for changes among the three study time-points using repeated-measures analysis of variance (ANOVA) with corresponding ‘post hoc’ one-sample paired t-tests. A deconstructed series of w2 (McNemar) tests was used to assess changes over time in proportions (nominal yes/ no) of the total sample of patients with ‘undetectable’ plasma viral load, the ‘‘gold standard’’ outcome of antiviral therapy. As the distribution of data showed some degree of skew (i.e., relatively asymmetrical for some variables or at various points in time measured), non-parametric tests were used as a supplementary way of checking for consistency of findings in terms of longitudinal changes. Therefore, differences longitudinally were also analyzed using Friedman tests for an omnibus evaluation across the three points in time, with corresponding Wilcoxon signed ranks tests for assessing changes over the two consecutive 2-year time frames and the total 4-year study period. Median scores were also calculated to evaluate changes in central tendency of SSS and SF-36 ratings. Finally, an overall impression of degree of stability of average SSS ratings and SF-36 component summary ratings was assessed by tallying the proportions of patients whose overall social support score (i.e., average of Affection, Positive Social Interaction, Emotional–Informational support) and SF-36 summary scores changed between baseline and final 4-year follow-up by more than 0.5 standardized effect size (SES), a magnitude of individual change that is conventionally viewed as potentially clinically significant in health research. Because social support was the independent variable of primary interest, z-tests were conducted to compare the final T3 mean ratings of the three SSS subscales with the available ambulatory medical population reference scores. The sample was stratified at T3 according to SSS outcomes and then according to SF-36 outcomes. The mean 4-year changes in SF-36 ratings of patient subgroups for which any degree of 4-year decrement in SSS ratings occurred were compared to those of subgroups whose SSS ratings were stable or improved. This analysis consisted of two independent samples t-tests of SF-36 changes for groupings according to outcomes on each of the three SSS subscales. Similarly, the mean 4-year changes in SSS ratings of patient subgroups for which a 4-year decrement in SF-36 ratings occurred were compared to those of subgroups whose SF-36 ratings were stable or improved. This analysis consisted of three independent samples t-tests of SSS changes for groupings according to outcomes on each of the two SF-36 summary components. Within-group 4-year changes in mean SF-36 ratings according to better versus poorer SSS outcomes and within-group 4-year changes in mean SSS ratings according to better

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versus poorer SF-36 outcomes were conducted using one-sample paired t-tests. Associations between SSS and SF-36 ratings crosssectionally as well as SSS changes and SF-36 changes were determined using regression analyses. Thus, a multivariate regression model was employed to determine cross-sectionally at the three study points the relative effects of clinical status (symptoms, CD4) and SSS ratings on physical and mental ratings. A similar regression model was used to assess the relative effects of symptom changes, CD4 count changes and SSS changes on physical and mental changes over time. The latter analyses were done for changes over the first 2-year period (T1–T2), the second 2-year period (T2–T3), and the total 4-year study period (T1–T3). These multiple regression analyses were done for each of the three SSS subscales (Affection, Positive Social Interaction, Emotional–Informational support) separately due to the unique aspects of social support they represent, with symptom count entered first, followed by CD4 count and, finally, the relevant SSS data. Previous HIV-related research has consistently suggested that symptom burden is a major clinical factor in terms of relations (i.e., negative) with a wide range of quality of life dimensions investigated (Badia et al., 1999; Burgoyne & Saunders, 2001; Cunningham et al., 1998; Justice, Rabeneck, Hays, Wu, & Bozzette, 1999; Murri et al., 1997; Vogl et al., 1999; Wachtel, Piette, Mor, Stein, & Fleishman, 1992; Wu et al., 1991). Although previous studies have found a less consistent relationship between CD4 count and quality of life, a positive association has been found to occur to some degree (Chan & Revicki, 1998; Kaplan, Anderson, McCutchan, Weinrich, & Heaton, 1995; Weinfurt, Willke, Glick, Freimuth, & Shulman, 2000). In the present study, log10 viral load was highly correlated with CD4 count, both in terms of cross-sectional associations and changes over time. Due to the size of the sample limiting the number of variables that could be entered in the regression model while maintaining robustness of the regression analysis, the general principle that CD4 count is a function of viral load and could be justified longitudinally as a surrogate marker for overall immunologic/virologic status, as well as the problems of multicollinearity posed by the addition of both CD4 count and viral load and the fact that log10 viral load changes are expressed as a ratio as opposed to than an absolute difference, the analyses were conducted with viral load excluded from the model. Standard regression diagnostics and scatterplots were employed to correct for the artifacts of data (i.e., outlier values) that could contribute to spurious statistical test results. In addition, for all tests of associations between SSS ratings and SF-36 ratings, as well as t-tests of 4-year differences in SF-36 ratings according to SSS outcomes and t-tests of 4-year differences in SSS ratings according to SF-36

SS T1

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SS T2

SS T3 E

A

C

D

B F QoL T1

QoL T2

QoL T3

2-yr. correlations 4-yr. correlations Fig. 1. Cross-lagged panels: three waves of data, Pearson product-moment correlation coefficients (A, B, C, D, E and F) between the three social support (SS) subscales and the two quality of life (QoL) summary components; T1 1997, T2 1999, T3 2001.

outcomes, the level of statistical significance was set at a more conservative threshold (i.e., Po0:01) due to the number of tests potentially inflating alpha error. Predictive potential between SSS and SF-36 ratings was examined by means of a set of cross-lagged analyses, the premise being that causal directionality between two variables can be theoretically verified by comparing the relative strength of association between each variable at one point with the other variable value at a later point in time. This method of evaluating causal pathways has been described and employed in previous HIV-related social support research (Kaplan et al., 1997). In the present study, associations were determined with a series of Pearson product-moment correlation analyses. Causal pathways were evaluated by examining the magnitude of association as well as asymmetries in the relations between the two variables, SSS and SF-36 ratings, in the correlation models. The cross-lagged panels are depicted in Fig. 1. As mentioned, attrition, illness and mortality factors that limited study participation at follow-up were not accounted for in the analyses. It is recognized that the results would, therefore, possibly be biased in favor of those who survived and were healthy enough to participate at follow-up, although there was no indication that T2–T3 attrition was attributable to failing health.

Results Changes in clinical variables, social support, and quality of life A statistically significant increase in mean CD4 count occurred from T1–T2 (147 cells/ml; Po0:0001) and from

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T1–T3 (196 cells/ml; Po0:0001). There was a concomitant reduction in mean viral load (i.e., T1–T3; 1:4 log10 copies/ml; Po0:0001) that followed the same pattern, confirmed by Wilcoxon signed ranks tests. Changes between T2 and T3 were non-significant, suggesting a peak in immunologic/virologic outcome at some point closer to T2, that is, an improvement subsequently maintained. The mean number of symptoms was significantly greater at T2 compared to T1 (+1.3; Po0:003). The increase in mean number of symptoms between T1 and T3 (+0.6) was also statistically significant (Wilcoxon, Po0:05) in spite of a decrease (0.7; Po0:02 for t-test and Wilcoxon) in mean number of symptoms between T2 and T3. This pattern suggests an overall rise in symptom burden that was eventually only slightly attenuated. The mean number of opportunistic infections was progressively significantly reduced over the 4-year study period: 1.3–0.9 from T1–T2 (Po0:03) and subsequently reduced to 0.1 (Po0:0001) at T3, corresponding to the occurrence of one opportunistic infection each for four patients at their final follow-up. A reduction in the proportion of the sample with ‘detectable’ viral load (McNemar w2 ; Po0:01) was found between baseline (68%) and T3 (39%). Taken together, these results suggest overall long-term clinical immunologic improvement and prevention of opportunistic infections, an outcome somewhat tempered by symptoms and/or side effects of treatment. Table 2a summarizes the changes in mean SSS ratings among the three measurement times. For the most part, slight but statistically non-significant reductions in SSS ratings occurred at both follow-ups compared to baseline. A within-group change in the Affection subscale (Friedman test, Po0:04) reflected a statistically significant T1–T2 reduction (Wilcoxon signed ranks test, Po0:05) in that particular dimension of social support, undetected by t-test analyses alone. Consistent with the above findings, the median scores (not shown) for

Positive Social Interaction and Emotional–Informational support were constant over time, while there was found a slight reduction in median score for the Affection subscale at 2-year follow-up, a reduction that held constant at final 4-year follow-up. However, when changes in SSS ratings for individual participants were further examined (not shown in illustrations), it was determined that approximately twice as many patients (i.e., 39%) of the sample reported a 4-year decrease in average SSS ratings as reported an increase (17% of patients), based on changes exceeding 0.5 SES in either direction. To put these results in perspective, nevertheless, mean scores for all three social support dimensions at T3 were consistent with the mean ratings reported by the ambulatory medical reference population; all z-tests were non-significant. In fact, SSS ratings were comparable to reference norms at all three points in time measured. Mean changes in SF-36 ratings among the three measurement times are presented in Table 2b. Changes on either of the components were statistically nonsignificant using both parametric and non-parametric tests. Differences in SF-36 mean ratings between T2 and final (T3) follow-up were negligible, in contrast to small but non-significant increases from baseline to T2 followup. The magnitude of change in median scores (not shown) mirrored these findings. Proportions of the sample with marked SF-36 changes were less pronounced on the physical dimensions. Approximately 13% of the sample reported a 4-year decrease (i.e., deterioration) in physical ratings that exceeded a 0.5 SES, and 28% had an increase (i.e., improvement) that exceeded 0.5 effect size. Degree of change for the more psycho-emotional dimensions, as represented in the mental score was more consistent with the SSS changes. Unlike the SSS ratings, however, there was a trend indicating change more in the direction of improvement than deterioration. The sample proportions with greater

Table 2 Mean (standard error) (a) social support and (b) quality of life at baseline and 2- and 4-year change Baseline

2-year change

4-year change

(a) Social support subscales Affection Positive social interaction Emotional–informational

72.2 (4.7) 72.1 (3.7) 73.5 (3.7)

7.8 (4.5) 1.4 (3.4) 2.6 (3.8)

5.5 (3.1) 5.5 (3.3) 3.0 (3.1)

(b) SF-36 summary scoreb Physical Mental

45.7 (1.9) 41.7 (1.7)

1.5 (2.0) 2.3 (2.1)

0.8 (1.5) 1.7 (2.0)

a

Within-group change in Affection (Friedman test, Po0:04) reflects a T1–T2 affection reduction (Wilcoxon signed ranks test, Po0:05). a Within-group changes (repeated-measures ANOVA; t-tests) are non-significant for all subscales. b Within-group changes (repeated-measures ANOVA; Friedman tests) are non-significant for both component summaries.

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than 0.5 effect size decrease and increase in mental ratings were 28% and 40%, respectively. These results suggest somewhat less stability over time within the psycho-emotional compared to physical aspects of quality of life for the PHA sample, a pattern that is obscured when examining mean changes alone over time.

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shown) were non-significant. For the regression models at all three points in time, where statistically significant associations between social support and quality of life were found, SSS ratings accounted for approximately 6%, on average, of the variance in SF-36 ratings. Longitudinal relations: social support and quality of life

Social support and quality of life changes based on quality of life and social support outcomes Differences in mean 4-year changes in SF-36 ratings of patient subgroups for which a 4-year decrement in SSS ratings occurred compared to those of subgroups whose SSS ratings were stable or improved were statistically non-significant. In contrast, the mean 4-year change in Emotional–Informational support ratings of the T3 patient subgroup for which a 4-year decrement in mental ratings occurred (N ¼ 15) reflected a reduction compared to the subgroup (N ¼ 26) whose mental ratings were stable or improved (Po0:005). The T1–T3 within-group mean change (i.e., reduction) in Emotional–Informational support ratings for the poorer mental outcome subgroup was also statistically significant (Po0:007). Cross-sectional relations: social support and quality of life SSS ratings were not significantly associated with SF36 ratings at baseline, controlling for number of symptoms and CD4 count. At 2-year follow-up (T2), controlling for number of symptoms and CD4 count at that time, ratings on all three SSS dimensions were associated with physical health ratings, while Emotional–Informational support ratings alone were associated with mental health ratings. These relationships are reported in Table 3, with corresponding nonstandardized (B) regression coefficients and P values indicated for statistically significant findings. An examination of scatterplots indicated that there was evenness in these associations; that is, higher and lower SSS ratings tended to correspond, respectively, to higher and lower SF-36 ratings. At 4-year follow-up (T3), controlling for number of symptoms and CD4 count, relationships between SSS ratings and SF-36 ratings (not

The results of multiple linear regression for the 4-year follow-up sample (N ¼ 41) over the first 2-year period of the study, with T1–T2 change in number of symptoms, change in CD4 count, and change in SSS ratings designated as independent variables and T1–T2 changes in SF-36 ratings designated as dependent variables indicated that changes in Affection ratings and Positive Social Interaction ratings were not independently related to changes in SF-36 ratings when CD4 changes and symptom changes were held constant. In contrast, changes in Emotional–Informational support ratings were positively related to changes in mental quality of life ratings, but not changes in physical ratings, as depicted in Table 4a. Again, there were indications of evenness, with positive and negative SSS changes ratings corresponding to positive and negative SF-36 changes. The results of multiple linear regression for the second 2-year period of the study, with T2–T3 change in number of symptoms, change in CD4 count, and change in SSS ratings designated as independent variables and T2–T3 changes in SF-36 ratings designated as dependent variables are presented in Table 4b. These findings are shown for changes in Affection and Positive Social Interaction ratings and their relations to changes in physical ratings, which were found to be statistically significant with CD4 changes and symptom changes held constant. As can be seen, changes in either of these two social support ratings were not significantly associated with changes in mental ratings. T2–T3 changes in Emotion–Information support ratings were not related to changes in either component of SF-36 ratings. Finally, associations between 4-year SSS changes and 4-year SF-36 changes, with 4-year change in number of symptoms and change in CD4 count held constant, were non-significant and are not reported in table format.

Table 3 Significance of non-standardized regression coefficients B for effects of social support on quality of life at T2, controlling for clinical (CD4 and symptom count) variables SF-36 summary score

Physical Mental

Affection

Positive social interaction

Emotional–informational

B

P

B

P

B

P

0.19 —

0.005 ns

0.21 —

0.006 ns

0.21 0.20

0.003 0.01

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Table 4 Significance of non-standardized regression coefficients B for effects of first 2-year period (T1–T2) and 2-year (T2–T3) social support changes on quality of life changes, controlling for clinical (CD4 and symptom) changes (N ¼ 41) SF-36 summary T1–T2 emotion-info score B P (a) T1–T2 physical T1–T2 mental

— 0.23

ns 0.01

(b)

T2–T3 physical T2–T3 mental

T2–T3 affection

T2–T3 Pos social

B

P

B

P

0.67 —

0.008 ns

0.84 —

0.009 ns

Emotion-info=emotional/informational social=positive social interaction.

support

and

Pos

Cross-lagged analyses revealed statistically non-significant associations between ratings of SSS subscales and subsequent ratings of SF-36 component summaries, and vice versa. For all analyses of tests of association between SSS and SF-36 ratings, for any given statistical test no more than 1 case was excluded as a result of outliers contributing to spurious results of statistical significance, minimizing adjustments that would necessitate sample size reduction.

Discussion The results of this longitudinal study of social support and quality of life among adults living with HIV/AIDS, most of whom were consistently on HAART, suggested slight 4-year reductions in social support perceptions and stability in quality of life ratings as measured, respectively, by three interpersonal dimensions of the SSS and the two component summaries of the SF-36. The apparent stability in social support ratings over time is consistent with 5-year findings in previous research within the general population (Kendler, 1997) and 1-year findings in research with chronic heart failure patients (Bennett et al., 2001) and recipients of bone marrow transplantation (Heinonen et al., 2001). In contrast, 1-year decrements in emotional support among cancer patients have been previously reported (Courtens, Stevens, Crebolder, & Philipsen, 1996). Our finding of general stability in social support, combined with that of mean SSS ratings that were similar to reference norms for other ambulatory medical populations (also in the 70/100 range), might have been encouraging in view of

the potential disenfranchising aspects of living with HIV disease. Examining social support from the perspective of the individual patient did suggest, however, a clinically significant decline for approximately 39% of the patients in the study. This finding would have been obscured if mean ratings alone had been analyzed. The results of the present study suggest some degree of interaction between immunologic outcome and change in symptom and/or side effect profile over time. Otherwise, improvements in quality of life might have been expected in the context of the general immunologic restoration and improved overall health that occurred over the study period. A greater degree of change in clinical factors appeared to occur over the first 2-year period, with CD4 levels showing the most reconstitution, concomitant with the largest change (i.e., increase) in number of symptoms. It is possible that immunologic restoration in terms of CD4 count repletion potentially offset the deleterious consequences of increases in symptoms and/or side effects on quality of life perceptions over time, yielding general 4-year stability in SF-36 ratings for the overall sample. On the whole, stability in quality of life represents a positive direction in the context of treatment advances, in contrast with the findings of earlier research conducted prior to the introduction of HAART that generally showed decrements in quality of life for PHA over follow-up periods ranging from 6 to 18 months (De Boer et al., 1994; Lenderking et al., 1994; Lubeck & Fries, 1994; Revicki, Wu, & Murray, 1995; Scott-Lennox, Mills, & Burt, 1998; Tsevat et al., 1996; Weinfurt et al., 2000; Wu et al., 1993). Cross-sectional relationships between perceptions of available social support and ratings of quality of life were inconsistent for our study sample. The strongest associations occurred at the first 2-year follow-up, while relations were minimal at the initial and final points in time. Where associations were found to be statistically significant, the proportion of variance in SF-36 subscale ratings that was, on average, attributable to the SSS ratings (i.e., 6%) was consistent with previous research in the area of chronic disease (De Ridder & Schreurs, 1996). Comparisons of our study results with the findings of previous HIV-related research are somewhat mixed. Our finding of relatively stronger associations between social support and quality of life at T2 are consistent with a number of prior cross-sectional studies. Bastardo and Kimberlin (2000) reported significant positive associations between tangible, appraisal, and emotional aspects of social support and most domains of health-related quality of life. Satisfaction with multiple sources of social support was found to be related to a composite SF-36 score, particularly for informational and tangible support domains and less so for emotional support satisfaction (Swindells et al., 1999). Social support was among the variables in a multivariate

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model that predicted general life satisfaction among PHA (Heckman et al., 1997). In contrast, tangible, appraisal/informational and emotional aspects of social support were not related to an index of well-being in which life satisfaction was emphasized, but emotional support was associated with behavioral and healthoriented aspects of quality of life (Friedland et al., 1996). Availability of social integration (i.e., social contacts, friendships, supportive contexts) was positively associated with overall well-being among men in one other HIV-related research study, but not among women, and for both there was no significant relationship between social integration and mental health (i.e., anxiety, depression) or energy (Cederfjall et al., 2001). As for the greater predominance of T2 associations between social support, particularly in terms of emotional and informational aspects of support, and quality of life in the present study, one possible explanation may lie in the relative importance of support at different stages of illness and treatment. The study sample was quite heterogeneous in terms of length of time from initial diagnosis of HIV seropositivity and in terms of the circumstances under which initial referral to the clinic occurred. The reasons for referral ranged from acute onset of AIDS-defined opportunistic infection, to diagnosis of HIV infection in the context of a stable immune function, to desire for exploration in terms of commencing an antiviral medication regimen, to need for consultation due to a pre-existing treatment regimen for which an alteration might be in order, and so on. In any event, associations between SSS and SF-36 ratings at the time of initial clinic registration were minimal. In contrast, for many patients at 2-year follow-up a relatively greater degree of transition, such as shifts in health status, immunologic function, and development of treatment side effects, may have led to greater similarity and commonality among patients. If so, this trend perhaps rendered emotional and informationalbased aspects of support more significant in terms of quality of life perceptions at that time. It is possible that these apparent status shifts were less prevalent or disruptive for patients by the time of 4-year follow-up, at which time minimal associations between SSS and SF-36 ratings were again found. Cancer-related research associations between social support and quality of life have also been found to be inconsistent across time, and generally to be more evident at times of relatively greater biopsychosocial crisis (Courtens et al., 1996). In our study of PHA, the association between social support and quality of life may have evolved in part due to emerging dynamics related to health-information needs and sources of support for those needs met. By 2-year follow-up, patients had familiarized themselves with various members of the clinic consultation team and may have obtained salient aspects of information, reassurance, and feedback that resonated

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with experiences of quality of life at that time. Other research has identified health care providers as important sources of social support that impact positively on patients’ sense of well-being in the context of living with cancer (Mathieson, Logan-Smith, Phillips, MacPhee, & Attia, 1996; Molassiotis, Van Den Akker, & Boughton, 1997). In our study, the stronger positive associations between social support and quality of life at T2, when the mean number of symptoms reported was 71% greater compared to T1 and 28% greater compared to T3, suggest that perceptions of social support had the potential to mitigate the negative consequences that symptoms and/or side effects conferred on quality of life perceptions at that time. At a time of relative uncertainty and transition in the history of this particular disease, the apparent mediating or buffering aspects of social support is particularly promising. From a service provision perspective, these results underscore the importance of attending to goals of buttressing social support for PHA at specific points in time where quality of life is compromised, particularly due to the trend over the longer term that, if left unchecked, could result in progressively deteriorating social support. The lack of evidence of strong relationships between changes in functional social support ratings and changes in quality of life ratings, particularly in the context of evidence of transitions in perceived support and wellbeing seen over time for some of the patients in the study sample, may be partly attributable to clinical factors that impact on quality of life and override the contributions that changes in social support confer on changes in quality of life perceptions. Our pattern of findings consisting of a positive association between T1–T2 changes in social support ratings and T1–T2 changes in mental quality of life ratings, as well as between T2–T3 changes in support ratings and T2–T3 changes in physical ratings is consistent with prior crosssectional health research. Maor, King, Olmer, and Mozes (2001) found that social support from friends accounted for 9% of the variance in SF-36 physical ratings among hemodialysis patients. Our results are also comparable to prior longitudinal research. For example, 1-year changes in SSS Positive Social Interaction and Emotional–Informational support were associated with changes in ratings of fatigue, emotional well-being, and overall quality of life among heart failure patients whose social support and quality of life ratings were also stable at 1-year post-hospitalization follow-up (Bennett et al., 2001). In that study, baseline social support did not predict quality of life ratings at 12 months, a finding that is similar to our study in terms of the consistent lack of predictive potential between SSS and SF-36 ratings in either direction over longer time periods. Nevertheless, the apparent potential for social support to contribute to some aspects of quality of life at least some of the time suggests the importance of

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endeavoring to maximize support for PHA. One major reason for this recommendation is that the initial promise held out by new treatments is not fully borne out. The immunologic restoration and concomitant extended length of life conferred by HAART regimens appears to keep quality of life deterioration in abeyance but has not shown major inroads in terms of improvements in self-perceived well-being. No apparent clues were provided as to the causal direction of the various relationships that were found between social support and quality of life crosssectionally and between changes in social support and quality of life longitudinally. The cross-lagged analyses in our study failed to substantiate any assumptions one might posit concerning the causal relations between perceived social support and quality of life in those areas where there was evidence of uni-directional or reciprocal responsiveness. In research conducted before HAART emerged in the developed world, a study utilizing a cross-lagged methodology found results suggesting that declining health among men living with HIV caused reductions in social network size rather than network size predicting immune status (Kaplan et al., 1997). In contrast, other research suggested that the likelihood of progressing to AIDS over a 5-year period was significantly higher among PHA reporting lower social support perceptions (Leserman et al., 1999). In another 5-year longitudinal study, informational social support was found to play a role in terms of time of symptom onset, progression to AIDS and mortality, but did not predict the time elapsed towards significant reductions in CD4 count (Patterson et al., 1996). The lack of consistent findings with respect to relationships between social support and health outcomes makes it difficult to strongly defend any assertions concerning the causal aspects of associations between social support and quality of life, an area that has received even less attention. The notion that certain aspects of quality of life precede social support perceptions arguably has some credibility due to our finding that participants with poorer SF-36 mental outcomes (i.e., 4-year decrements) reported poorer Emotional–Informational support outcomes compared to those with no change or an increase in mental ratings. In contrast, participants with poorer SSS outcomes reported changes in SF-36 ratings that were not significantly poorer compared to SF-36 changes reported by those with stable or improved SSS ratings. Poorer emotional health in terms of mood and outlook on life may have negatively influenced perceptions of the availability of others for provision of guidance and support. Consistent with our results, cancer patients with deterioration in quality of life (i.e., assessed using a measure of global well-being) tended to perceive a decrease in emotional support over a 1-year period (Courtens et al., 1996). Of course, it

could also be argued that the withdrawal or lack of availability of needed support would lead to a sense of isolation that would foster greater levels of depression and anxiety. The connection between social support and quality of life may be bi-directional, with a reciprocal influence between these two variables. Support for this assumption is provided by our finding that T1–T2 and T2–T3 changes in various aspects of social support as measured by the SSS were related to changes in quality of life as measured by the SF-36, together with the lack of results favoring causal directionality either way. However, the conclusion that social support causally influences quality of life, and vice versa, has limited plausibility, given the lack of other corroborating research examining these questions in the HAART era. Findings concerning social support and quality of life differed among previous studies, further confounding causal directionality arguments. Further speculation concerning causal relations between social support and quality of life among PHA should await additional study. The generalization of the study’s findings is limited by the modest size of the sample, its under-representation of women and heterosexual men due to demographic trends in Canada that persisted several years following the inception of the research study, and its underrepresentation of demographic groups in which the incidence and prevalence of HIV/AIDS is becoming more widespread in the post-millennium decade. The sample could be seen, perhaps, as a microcosm of patients who do not necessarily represent the majority of adults living with HIV disease. Five years following the initiation of the study planning, a major influx of referrals of men and women from sub-Saharan African nations, newcomers to Canada, represents a change in demographics of HIV-infected adults locally. Patients referred to the hospital-based clinic program are also possibly viewed by their family physicians as being more at risk for the consequences of HIV infection. Statements concerning trends in the relationship between social support and quality of life for HIV-positive women in Canada remain largely conjecture at this point, as the number of female patients in this study was quite small. Finally, the quality of life assessment approach was consistent with most health-related outcome research that emphasizes functioning. As a result, coverage of broader conceptualizations of quality of life that might resonate in particular with both historical and evolving profiles of the HIV-positive population was missing, including issues such as stigmatization, equal access to opportunities for employment and community integration. The study results may also be biased in favor of those who survived and were healthy enough to participate at follow-ups. Sample attrition is a methodological artifact that can potentially influence longitudinal study results.

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It is reasonable to assume that, following initial assessment, the small number of patients who became acutely ill or died had experienced decrements in wellbeing. Including this small group and imputing low quality of life ratings would perhaps result in decrements in mean scores for the overall sample. It would have been more difficult to impute social support ratings for those same patients, as support is less predictable in the context of increasing morbidity and impending mortality. Similarly, it is difficult to know much about the social support status of patients who were lost to followup, and maintaining contact with the clinic program may have been constrained by a dearth of support for some among that group. Although the total sample size is relatively small, statistical power appeared to be adequate for testing for changes in SSS and SF-36 ratings for the overall 4-year sample in this study. For the five social support, physical and mental scores analyzed, there was sufficient sample size to detect an SES of 0.5, the conventional threshold of change used to assess power, at an average level of power of 82% between baseline and T2, 92% between baseline and T3, and 89% between T2 and T3 (at Po0:05). However, while statistical power was adequate for tests of change in the study variables among the three study points, it was less robust for secondary analyses (i.e., independent samples t-tests, one-sample paired t-tests) in which the sample was stratified according to better versus poorer SSS and SF-36 outcomes. Although sample power appears to be technically sound, larger sample sizes more satisfactorily support the assumptions derived from the results of the analysis and enhance the degree to which a group of PHA reflects the larger constituency of those living with this disease. Given the propensity for sample attrition in this type of research, therefore, we advise that future studies aim for large enough inception cohorts for follow-up over long-term time frames of the magnitude chosen in this study. Social support in this study emphasized perceptions of accessibility to others with whom to express mutual loving and caring, share activities and openly discuss issues of concern. Support that could be seen as actually enacted by others and potentially measured behaviorally was not the means of social support assessment in this study. The focus was on quality and not on quantity, such as size of supportive network of family and/or friends. Finally, interpersonal rather than practical, instrumental aspects of social support were measured.

Conclusions Moderate stability in social support and quality of life, as measured by the Social Support Survey and the Short-Form-36, was found for a sample of adult PHA

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over a 4-year period in the context of HAART. For more than one-third of participants, however, there occurred a decline in social support ratings to a degree that would likely be clinically significant or meaningful from the perspective of the patient. Perceived social support appeared to contribute at some level, along with clinical factors such as symptoms and immunologic and virologic status, to perceptions of health-related quality of life. Perceptions of social support were likely influenced by availability of clinic staff. Social support may have varied relative to particular needs at times of uncertainty and transition in the context of effective but potentially stressful treatment regimens. Attempts to illuminate the direction of causation between social support perceptions and health-related quality of life perceptions met with limited success. Study results suggested a trend in which some aspects of quality of life outcomes portended poorer social support. It is not clear whether causal relationships between physical and mental well-being, on the one hand and perceptions of interpersonal, emotional and informational support, on the other hand, were unidirectional or reciprocal. However, the study findings suggest sufficient evidence for underscoring the importance of interventions aimed at maximizing social support for adults living with HIV disease. In the era of highly active anti-retroviral drug therapy (HAART), understanding the influence of interpersonal as well as informational and emotional social support on clinical outcomes is important for the purposes of service delivery in relation to the skills and knowledge required by patients to participate fully in their care plans and to adjust to the challenges of sustaining lifelong commitments to pharmacotherapy. This study provides a glimpse of current themes associated with social support and quality of life specific to adults living with HIV/AIDS in a relatively developed nation where antiviral treatment is readily accessible. As such, one obvious bias of the research herein reported is that it does not reflect the devastating consequences of HIV infection in terms of the growing global AIDS pandemic. Rather, the focus is on outcomes in the context of newly emerging changes that have developed following the initial optimism surrounding the introduction of HAART in western standards of HIV/AIDS treatment. Inclusiveness of new subgroups emerging in terms of incidence and prevalence of HIV infection (i.e., AfricanCanadian women and their partners and children) is advisable in the context of social science research in Canada and elsewhere. Social support remains an important area of exploration in terms of its potential as a buffer against the negative consequences of HIV infection on health overall and on various aspects of quality of life. If selfperceived quality of life is indeed mediated by social support, research aimed at determining the types and

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quality of social support that help to buttress well-being potentially clarifies the confluence of factors in which illness adaptation and treatment outcomes can be optimized. There is a need for continuing longitudinal research to more fully investigate the predictive relationships between social support and various desired clinical outcomes for people living with HIV/AIDS, including perceptions of life quality. Research designed to comprehensively explore theoretical causal criteria such as temporality of relations between variables, as well as the strength, consistency and plausibility of these associations helps to determine what strategies could be applied to improving clinical and well-being results for PHA.

Acknowledgements This paper represents a portion of research undertaken by the first author in the context of enrolment in the Institute of Medical Science, University of Toronto. Acknowledgement for contributions to the development of the overall study design is gratefully extended by the first author to the Master of Science program advisory committee, consisting of Dr. Irving Salit, Dr. Dean Behrens, and Dr. Sean Rourke.

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