Secondary Logo

Journal Logo

Supplement Article

Microsocial Environmental Influences on Highly Active Antiretroviral Therapy Outcomes Among Active Injection Drug Users

The Role of Informal Caregiving and Household Factors

Knowlton, Amy R MPH, ScD*; Arnsten, Julia H MD, MPH; Gourevitch, Marc N MD, MPH; Eldred, Lois MPH, DrPH§; Wilkinson, James D MD, MPH; Rose, Carol Dawson PhD, RN; Buchanan, Amy MHS#; Purcell, David W JD, PhD** for the INSPIRE Study Team

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: November 1, 2007 - Volume 46 - Issue - p S110-S119
doi: 10.1097/QAI.0b013e31815767f8
  • Free


Research is needed to inform the development of more effective interventions to improve adherence to highly active antiretroviral therapy (HAART) among injection drug users (IDUs). Previous HIV adherence intervention approaches have focused on individual-level factors, with limited effectiveness.1 Research indicates that HAART is efficacious among IDUs2 and that a supportive social environment is one of the most consistent predictors of better HIV medical adherence, virologic outcomes, and reduced morbidity and mortality.3-5 Furthermore, causal links have been found between social support virologic outcomes of HAART.6 Interpersonal support may be especially important to the health outcomes of populations in high need of assistance, such as the low income, chronically ill, or disabled.7

Given the high risk of treatment failure among disadvantaged IDUs, the purpose of the present study was to identify factors predictive of successful versus unsuccessful treatment over time among a community sample of IDUs on HAART. The study examined individual-level factors, such as drug use and depression; microsocial factors, such as social support, stigma, and social isolation; and structural factors, such as health insurance, health service use, and housing. The study findings may aid in the development of improved psychosocial assessments of IDUs so that clinicians can better identify patients at high risk of treatment failure. The results may also inform appropriate targets and strategies of intervention to promote successful HAART among IDUs.

Individual-Level Factors

Prior literature emphasizes associations between individual-level factors and HAART adherence and virologic outcomes.8-14 Unsuccessful HAART is associated with active substance use as compared with prior substance use or not ever using substances.15,16 One study found that active drug use had a rapid detrimental effect on virologic outcomes on HAART.15 In studies of IDUs, cocaine use most consistently and adversely affects HAART adherence and virologic outcomes.15-19 Findings from longitudinal studies have been inconsistent regarding the role of demographic and cognitive behavioral factors, such as adherence self-efficacy, as predictors of virologic outcomes of HAART.8,20

Microsocial Environmental Factors

Few studies to date have examined microsocial environmental factors that may help to explain the effects of active drug use on IDUs' virologic outcomes. Research indicates that social support is one of the most consistent predictors of successful HAART, including among IDUs.21,22 Emotional support is the form of social support emphasized in the literature and has been found to be predictive of numerous health behaviors and health outcomes in addition to successful HIV treatment.3,23 In a prior cross-sectional analysis of IDUs on HAART, emotional support was found to be the strongest correlate of viral suppression.24

Yet, a previous meta-analysis across an array of chronic conditions indicated that instrumental, or practical, assistance is the type of social support most consistently associated with better medical adherence.3 Instrumental assistance or emotional support to chronically ill or disabled individuals is how informal caregiving is usually defined in the literature25 and how we define it here. Most care given to the chronically ill or disabled is provided informally by family, partners, and friends.26 A growing body of research indicates the importance of informal care to health outcomes among those living with HIV/AIDS.27-30

Few studies have examined informal HIV caregiving to IDUs.31 Some studies find that low socioeconomic status and chaotic lifestyles among some IDUs impede their access to informal care.32 Others studies suggest that many IDUs living with HIV/AIDS are able to mobilize social support and informal care within their social environments33 and that this informal care is related to their appropriate use of HIV medical services.34

Household Factors

Research indicates that IDUs are at high risk of homelessness or housing instability, which has been associated with unsuccessful HAART.24,35 Studies of Canadian and English samples suggest that living alone is associated with poor HAART adherence.36,37 Among IDUs in the United States, a study found that those living with a partner, family, or friends were more likely to enter drug abuse treatment, which has been found to correlate with IDUs' successful HAART.24,38

Social Comfort in Taking HAART

Comfort in taking HAART in front of others has been found to be associated with IDUs' treatment adherence.39 In a study of IDUs, those who said they wanted more privacy in taking their HIV medications were significantly less likely to adhere.39 Social discomfort in taking HAART may be an indicator of the perceived social stigma of HIV, concerns about possible HIV disclosure, or privacy concerns about one's HIV or other illness.40 Social stigma presents considerable obstacles to effective HAART use.41 Discomfort in taking HAART in front of others may also be attributable to reluctance to burden family or friends potentially by such reminders of illness.42,43

Patient-Provider Communication

Although better patient-provider communication has been found to be associated with successful HAART in cross-sectional studies,44-47 including among IDUs,24 it is not clear whether it differentiates among HAART outcomes for IDUs.

Structural Factors

Structural factors, such as drug abuse treatment attendance, stable housing, and health insurance, have been found to be associated with access to HAART.48,49 In a prior cross-sectional study of IDUs on HAART, outpatient drug abuse treatment and stable housing were associated with viral suppression.24

The present study examined individual-level, microsocial, and structural factors predicting the maintenance of successful versus unsuccessful HAART over time.


Study Population

Participants were enrolled in the Intervention for the Seropositive Injectors-Research and Evaluation (INSPIRE) study, a secondary HIV prevention intervention conducted at 4 sites (Baltimore, Miami, New York City, and San Francisco) from 2001 to 2005.50 Participants were recruited using active and passive strategies, including street-based recruiting and advertisement at AIDS service organizations, medical clinics, and methadone maintenance clinics.50 Eligibility criteria included confirmed HIV-positive serostatus, self-reported injection drug use in the prior year, sex with an opposite-gender partner in the prior 3 months, and willingness to engage in group educational sessions and to provide oral and blood specimens.

The sample comprised 133 study participants who remained on HAART between baseline and 12 months of follow-up from among 560 participants on recommended HAART at baseline of the INSPIRE study (Fig. 1).50 Current HAART use was defined as self-reported prescription for and taking for at least 1 day in the prior month any regimen that was recommended strongly or as an alternative according to current US Department of Health and Human Services guidelines.51 Participants who reported taking nonrecommended antiretroviral therapies or no therapies were excluded from the analyses.

Sampling flow chart for IDUs on recommended HAART enrolled in the INSPIRE study (2001 to 2005).

Among 560 participants who reported taking recommended HAART at baseline of the INSPIRE study, 154 (28%) reported at follow-up that they had stopped taking HAART, 125 (22%) were lost to follow-up, and 82 (15%) had missing data (see Fig. 1). Of the 199 participants who remained on HAART, 133 (67%) had maintained detectable viral loads, achieved viral suppression, or maintained viral suppression at 12 months of follow-up and were included in the analysis (see Fig. 1). The remaining 66 cases were excluded because of erratic viral load changes or worsening viral load changes (ie, having an undetectable viral load at baseline and a detectable viral load at 6 or 12 months follow-up [12% of the original sample]).

Assessments were administered by audio computer-assisted self-interview (A-CASI).50 Oral and blood specimens were obtained at the time of the baseline assessment for local testing to confirm HIV serostatus (OraSure; OraSure Technologies, Bethlehem, PA) and for CD4 cell count and viral assays, which were conducted at the Centers for Disease Control and Prevention (CDC) in Atlanta. The CDC and local human subject review boards approved the study protocol. Participants were reimbursed $30 for their time and effort at baseline, $45 at 6 months of follow-up, and $50 at 12 months of follow-up.


The outcome was the binary indicator of HIV-1 RNA plasma level as detectable (>400 copies/mL) or undetectable (Amplicor HIV-1 Monitor; Roche Molecular Systems, Branchburg, NJ). Participants were classified into 1 of 3 groups according to changes in their plasma viral loads between baseline and 12 months of follow-up (Fig. 2):

Group assignment rules based on change in HIV-1 RNA plasma viral load between baseline and 6 and 12 months of follow-up among IDUs on recommended HAART in the INSPIRE study (n = 133).
  • Group 1: maintained treatment failure; those who maintained a detectable viral load at all 3 assessments
  • Group 2: achieved successful treatment; those who had a detectable viral load at baseline and an undetectable load at follow-up
  • Group 3: maintained successful treatment; those who maintained an undetectable viral load at all 3 assessments

Individual-Level Variables

Independent variables included baseline CD4 lymphocyte count (×106/L) ≤350, length of time on the HAART regimen, and whether the regimen comprised a protease inhibitor (PI) or nonnucleoside reverse transcriptase inhibitor (NNRTI).

Depressive symptoms were assessed by the 7-item depressive symptom subscale of the Brief Symptom Inventory (BSI), which has demonstrated high validity and reliability, including among HIV-seropositive IDUs.52,53 The Cronbach α for internal reliability was 0.88 for this sample. For ease of interpretation, the median score was the cutoff used to construct the binary variable of high/low depressive symptoms.

Self-efficacy to adhere to HAART was measured by a 13-item scale. Items included “How sure are you that you can or will be able to take your HIV medications exactly the way the doctor tells you to…when the medicines have been making you feel bad?”, “…when you are high or on a run?”, and “…even when getting to your clinic appointment is a hassle?” The Cronbach α was 0.96.

Participants were asked about their use of a variety of illicit injection and noninjection drugs in the past 3 months. Current illicit drug use was defined in 3 ways: use of any versus none of 9 different types of noninjection substances, excluding marijuana; use of cocaine (yes/no); and injection of any of 7 substances. Alcohol use was defined as daily use versus less than daily use or not at all. Sociodemographic variables included non-Hispanic black race versus other and median age, income, and education.

Microsocial Factors

Informal care was defined as a combined score of having someone to provide instrumental assistance during illness or to provide emotional support. Instrumental assistance was queried as the degree of certainty of having “someone you could depend on to take care of you if you were sick and had to stay in bed.” Emotional support was assessed as the degree of certainty of having someone to talk to about something personal or private. Responses were based on a 4-point scale and recoded as a binary score of very certain (4) or less than very certain (1 to 3). Emotional support and instrumental assistance were highly correlated (χ2 test of independence = 48.3; P < 0.001). Approximately two thirds (66%) of the sample reported high certainty of having emotional or instrumental support, and 41% reported high certainty of having both. Therefore, a binary variable was created by combining the types of support, with the variable coded 1 for high certainty of having instrumental or emotional support and coded 0 for neither type of support. The variable was termed informal care, given that either form of assistance has been used to define informal caregiving in the literature.

Respondents were asked about their relationship and communication with their health care provider using the Engagement with Healthcare Provider Scale.45 The 13-item scale included such questions as “My healthcare provider or doctor…listens to me,” “…answers my questions,” and “…involves me in decisions.” The Cronbach α for the sample was 0.95. Social comfort in taking HAART was assessed by response on a 4-point scale to the question “How comfortable are you taking HIV medications in front of other people?” The variable was recoded as 1 (comfortable) or 0 (uncomfortable).

Other microsocial factors assessed included living alone (vs. living with others) and degree of comfort in taking HIV medications in front of other people, with response options on a 4-point scale ranging from very comfortable to very uncomfortable.

Structural Factors

HIV primary care service use was assessed as the number of such health care visits reported in the prior 6 months. Primary health care visits were defined as “a visit to a doctor or medical provider to have a check up on how you're doing with your HIV or AIDS, discussion about HIV or AIDS medications, or blood test results.”

Attendance at outpatient drug abuse treatment in the prior year was assessed. Medical coverage was defined as self-report of having any private or public sources of medical coverage or insurance (1) versus none (0). Homelessness in the prior year was also assessed.

Statistical Analyses Plan

The goal of the analyses was to identify, among those taking HAART, baseline predictors over a 12-month period of being in the groups that achieved or that maintained viral suppression relative to being in the reference group that maintained detectable viral loads.

Fischer's exact tests were used to compare, from among those on recommended HAART at baseline, those lost to follow-up and (separately) those who stopped taking HAART as compared with those retained in the study and included in the analyses. Fischer's exact tests were also used to test for possible selection differences by study condition, and χ2 tests were used to test for selection differences by study site.

To reduce the possibility of misclassification, cases were excluded if they were missing outcome data at the 6- and 12-month assessments. Those with erratic or worsening viral load changes were also excluded from analyses. Exploratory analyses indicated no major differences in the main predictor variables between participants with erratic or worsening viral loads versus participants included in the final sample. The single exception was that those with erratic or worsening viral load trajectories had higher levels of informal care at baseline compared with participants included in the final sample (P < 0.05; analysis not shown). This finding may reflect that those with worsening viral loads, by definition, had undetectable viral loads at baseline.

Multinomial regression was used to calculate the unadjusted relative odds of baseline characteristics predicting being in group 2 (achieving viral suppression) relative to being in group 1 (maintaining detectable viral loads) and predicting being in group 3 (maintaining viral suppression) relative to being in group 1 (the reference group).

Independent variables significant at P < 0.10 in the unadjusted analysis were included in the final multinomial regression analysis. The same independent variables were used in each regression model. In the final model, the odds ratios represent the adjusted relative odds of baseline characteristics predicting achieving successful treatment (group 2) relative to treatment failure (group 1) and of maintaining successful treatment (group 3) relative to treatment failure (group 1). Analyses used STATA 8 (StataCorp, College Station, TX) and SAS statistical software (SAS Institute, Cary, NC).


Description of the Sample

Compared with participants lost to follow-up, those in the present analysis were older, and had a trend toward being of non-Hispanic black race and having a higher income (Table 1). Compared with participants who stopped taking HAART, those included in the present analysis had a trend toward reporting at baseline more frequent HIV primary health care visits and better patient-provider communication (Table 1).

Comparison of Participants Retained on HAART and Included in the Present Analysis Versus Those Who Stopped Taking HAART and Versus Those Lost to 6 or 12 Months of Follow-Up Among IDUs on HAART at Baseline of the INSPIRE Study, 2001 to 2005*

Analyses failed to find statistical differences in participant selection by study condition or by study site. There was no difference in assigned study condition among those who stopped taking HAART or were lost to follow-up. Also, there were no differences in virologic changes by study condition or by study site. Therefore, we included control and intervention participants in the analyses.

Among 133 participants included in the analyses, 28% were female, 73% were non-Hispanic black, 25% were homeless in the prior year, and 40% had less than a high school education (Table 1). The median age was 43 (SD = 6.1, range: 25 to 58) years, and the median CD4 count was 311 cells/mL (SD = 240, range: 4 to 1050). Almost two thirds (66%) maintained detectable viral loads between baseline and 6 or 12 months of follow-up, 15% achieved viral suppression, and 19% maintained viral suppression.

Bivariate (Unadjusted) Analysis

Unadjusted analysis indicated that baseline measures predictive of achieving viral suppression relative to maintaining detectable viral loads were nonblack race, no cocaine use, and CD4 count >350 (Table 2). Predictors of maintaining viral suppression relative to maintaining detectable viral loads were lower income, CD4 count >350, longer time on the regimen, not living alone, informal care, and social comfort in taking HAART, and there was a trend of greater rates of self-reported adherence in predicting maintaining undetectable versus detectable viral loads (Table 2). Baseline reports of regimen type, depressive symptoms, and HAART adherence self-efficacy perceptions were not significant, and none of the structural factors was significant.

Comparisons Between Baseline Characteristics and Virologic Changes Between Baseline and 6 or 12 Months of Follow-Up Among Sexually Active IDUs on HAART in the INSPIRE Study, 2001 to 2005 (n = 114; Unadjusted Multinomial Regression Analysis)*

Multivariate Analysis

The results from adjusted multinomial regression analysis indicate that a high level of perceived informal care, not being of non-Hispanic black race, and CD4 count >350 at baseline were positively predictive of being in the achieving viral suppression group relative to the treatment failure group (Table 3). Maintaining viral suppression compared with treatment failure was predicted by informal care, not living alone, and a high level of comfort in taking medications in front of others. There was a trend toward lower income in predicting maintaining undetectable versus detectable viral loads. When the final model was rerun with the CD4 cell count variable excluded, results were statistically unchanged.

Adjusted Multinomial Regression of Individual-Level and Social Environmental Factors on Virologic Changes on Recommended HAART Between Baseline and 6 or 12 Months of Follow-Up Among 114 Sexually Active IDUs in the INSPIRE Study, 2001 to 2005*


Results validate findings from prior cross-sectional studies on the role of microsocial environmental factors on successful HAART among a disadvantaged population at high risk of treatment failure. Specifically, the study results indicate that among IDUs who remained on HAART, having informal care (ie, instrumental assistance when sick or emotional support) was predictive of 4.6-fold higher odds of successful versus unsuccessful treatment during 12 months of follow-up. Not living alone and comfort in taking HAART in front of others were associated with 3.47-fold higher odds of maintaining successful treatment relative to treatment failure. The study findings contribute to social theories of health and suggest potentially promising targets and strategies to a social environmental, home, and community caregiving-focused approach to adherence interventions for disadvantaged IDUs. The study results also demonstrate the importance of prospective community-based studies of HAART outcomes and the need for further research on factors affecting the high level of discontinued use of HAART found in the study sample.

Microsocial Pathways to Treatment Outcomes

The present prospective study findings expand on prior cross-sectional research suggesting a social pathway to IDUs' HIV treatment outcomes. In an earlier cross-sectional analysis of the INSPIRE study cohort, we found an interaction between social support, having an undetectable viral load, and drug use. Among IDUs on HAART with a high level of social support, 61% of those who were not currently using drugs compared with 30% of current drug users had an undetectable viral load (P = 0.001).24 Among IDUs with a low level of social support, drug use status was not statistically significantly associated with viral suppression.

Social influence theories of health behavior posit that supportive relationships (eg, family, partners, friends) may act directly or indirectly to influence medical adherence and treatment outcomes.54 Direct social influences may include instrumental assistance with obtaining or administering treatments or with facilitating engagement in the health care system.55 Indirect social influences on treatment outcomes may include promoting health protective routines and norms and providing coping assistance to minimize the impact of psychologically distressing situations on health protective behaviors.56,57 Instrumental or emotional support was significantly associated with treatment outcomes in the present study.

Informal caregiving is increasingly important to the health and well-being of persons living with HIV/AIDS (PLHAs), because the use of HAART has prolonged life expectancy with HIV and time living with impairment. Previous descriptive studies suggest that IDUs' informal HIV caregivers tend to be female; kin, partners, and friends; and similar to care recipients with respect to race, socioeconomic status, and illicit drug use history.31 Prior study findings provide evidence of the influence of instrumental support networks on IDUs' optimal HIV medical service use and of the influences of support networks and informal HIV caregivers on their psychologic well-being.34,58,59

The finding from the present study that informal care and living alone were independent predictors of treatment outcomes supports a prior observation that IDUs' informal caregivers did not necessarily live with them.31 This suggests the importance of assessing IDUs' potential informal caregivers not by role relation or coresidence but by key forms of social support (eg, instrumental assistance, emotional support).

Potential Adverse Microsocial Influences on Health Outcomes

Although research indicates the vital role of social support and informal HIV caregiving on IDUs' medical adherence and treatment outcomes, more research is needed to understand potential adverse influences of support networks and caregiver relationship factors on IDUs' HAART outcomes. In a prior study, a greater level of active drug use among IDU PLHAs' support network members, but not IDUs' own drug use status, was associated with their suboptimal utilization of emergency medical services.34 Furthermore, IDU PLHAs' psychologic distress has been found to be associated with their greater number of conflictive relationships with social network members and with their caregiver relationship factors, including caregivers' own psychologic distress.58,59

Potential Constraints on Sustained Informal HIV Caregiving

Research indicates that long-term informal caregiving often has adverse effects on informal caregivers' physical health and their psychologic, social, and financial resources.42,60-64 Caregiving is especially stressful if the care recipient exhibits disruptive behaviors and is particularly financially costly if the care recipient uses illicit drugs.60,63 Results from a previous study suggest that limited economic resources present constraints on main supporters' provision of instrumental assistance to IDU PLHAs.31 Given these findings, it is incumbent on investigators and public health practitioners to examine not only the health benefits of informal HIV care receipt but the stresses associated with informal care provision and resources that facilitate informal HIV caregiving. Such home and community caregiving-focused research may inform the development of programs to bolster informal HIV caregivers' resources for sustained HIV care provision and minimize their caregiving burdens.

Study Limitations

Potential limitations of this study include self-report biases in adherence, errors in recall of treatment regimens, and the fact that participants were on various HAART regimens and for varying lengths of time. The study results indicated no effects of drug class or length of time on HAART on viral suppression, however. Given that our definition of current HAART use was use in the month before assessments, misclassification of cases cannot be ruled out.

Results are also subject to possible bias of treatment duration in the categorization of participants. Although it did not retain statistical significance in multivariate analysis, there was a trend toward increasing time on the current regimen for the 3 groups assessed; those who failed to achieve viral suppression were on their regimen a somewhat shorter time compared with those who maintained viral suppression. Thus, it is possible that the treatment failure group was composed of newer entrants into HIV medical care or of individuals who had difficulties with their regimens. Conversely, the members of the successful treatment group may have had more consistent medical care and treatment, and therefore survived longer on their regimens.

Selection bias may limit the generalizability of the findings to other IDU populations. Study participants may not be representative of all IDUs, because the present sample was heterosexually active, had volunteered for an HIV prevention intervention, and had remained on recommended HAART. We excluded participants on second-line or salvage therapies, with lower expected HAART efficacy; thus, findings may not generalize to all HIV treatment among IDUs. Also omitted from the study were those lost to follow-up and those who stopped taking HAART because of nonadherence or having switched to less recommended therapies during the follow-up period. Indeed, those in the present analysis compared with those who stopped taking HAART had a trend toward better engagement in the health care system, and thus likely had greater access to HAART. The sample's underrepresentation of IDUs with low engagement in medical care may explain why structural factors were not significant in the analyses. Participants in the present analysis compared with those lost to follow-up had a trend toward being older, being of non-Hispanic black race, and having a higher income. Future studies are needed to examine factors associated with IDUs' maintaining access to medical care and HAART over time, particularly among younger IDUs with lower incomes.


The study findings suggest that an important approach to improving disadvantaged IDUs' HAART outcomes is to enhance the ability of IDUs' family, partners, and friends to provide sustained informal care. The findings also suggest the importance of promoting social comfort in medication taking within IDUs' social networks and promoting IDUs' housing with supportive family or friends. To promote IDUs' HAART outcomes, public health practitioners ought to be trained in methods of assessing the supportiveness and resources of HIV-seropositive IDUs' informal caregivers, social networks, and households. Intervening with IDUs and their informal caregivers and reducing the potential caregiving burden may be important ways to bolster and sustain IDUs' existing support systems and maintain long-term successful HAART.


This study was supported by the CDC and the Health Resources and Services Administration. The INSPIRE Study Team includes the following people: Carl Latkin, Amy Knowlton, and Karin Tobin (Baltimore); Lisa Metsch, Eduardo Valverde, James Wilkinson, and Martina DeVarona (Miami); Mary Latka, Dave Vlahov, Phillip Coffin, Marc Gourevitch, Julia Arnsten, and Robert Gern (New York); Cynthia Gomez, Kelly Knight, Carol Dawson Rose, Starley Shade, and Sonja Mackenzie (San Francisco); David Purcell, Yuko Mizuno, Scott Santibanez, Richard Garfein, and Ann O'Leary (CDC); and Lois Eldred and Kathleen Handley (Health Resources and Services Administration).

The authors acknowledge the following people for their contributions to this research: Susan Sherman, Roeina Marvin, Joanne Jenkins, Donald Gann, and Tonya Johnson (Baltimore); Clyde McCoy, Rob Malow, Wei Zhao, Lauren Gooden, Sam Comerford, Virginia Lo Cascio, Curtis Delford, Laurel Hall, Henry Boza, and Cheryl Riles (Miami); George Fesser, Carol Gerran, and Diane Thornton (New York); Caryn Pelegrino, Barbara Garcia, Jeff Moore, Erin Rowley, Debra Allen, Dinah Iglesia-Usog, Gilda Mendez, Paula Lum, and Greg Austin (San Francisco); Gladys Ibanez, Hae-Young Kim, Toni McWhorter, Jan Moore, Lynn Paxton, and John Williamson (CDC); and Lee Lam, Jeanne Urban, Stephen Soroka, Zilma Rey, Astrid Ortiz, Sheila Bashirian, Marjorie Hubbard, Karen Tao, Bharat Parekh, and Thomas Spira (CDC Laboratory).


1. Simoni JM, Pearson CR, Pantalone DW, et al. Efficacy of interventions in improving highly active antiretroviral therapy adherence and HIV-1 RNA viral load. A meta-analytic review of randomized controlled trials. J Acquir Immune Defic Syndr. 2006;43(Suppl 1):S23-S35.
2. Vlahov D, Galai N, Safaeian M, et al. Effectiveness of highly active antiretroviral therapy among injection drug users with late-stage human immunodeficiency virus infection. Am J Epidemiol. 2005;161:999-1012.
3. Di Matteo MR. Social support and patient adherence to medical treatment: a meta-analysis. Health Psychol. 2004;23:207-218.
4. Persson L, Ostergren PO, Hanson BS, et al. Social network, social support, and the rate of decline of CD4 lymphocytes in asymptomatic HIV-positive homosexual men. Scand J Public Health. 2002;30:184-190.
5. Leserman J, Petitto JM, Gu H, et al. Progression to AIDS, a clinical AIDS condition and mortality: psychosocial and physiological predictors. Psychol Med. 2002;32:1059-1073.
6. Burgoyne RW. Exploring direction of causation between social support and clinical outcome for HIV-positive adults in the context of highly active antiretroviral therapy. AIDS Care. 2005;17:111-124.
7. Van Servellen G, Lombardi E. Supportive relationships and medication adherence in HIV-infected, low-income Latinos. West J Nurs Res. 2005;27:1023-1039.
8. Anastos K, Schneider MF, Gange SJ, et al. The association of race, sociodemographic, and behavioral characteristics with response to highly active antiretroviral therapy in women. J Acquir Immune Defic Syndr. 2005;39:537-544.
9. Turner BJ, Fleishman JA, Wenger N, et al. Effects of drug abuse and mental disorders on use and type of antiretroviral therapy in HIV-infected persons. J Gen Intern Med. 2001;16:625-633.
10. Chesney MA, Morin M, Sherr L. Adherence to HIV combination therapy. Soc Sci Med. 2000;50:1599-1605.
11. Johnson MO, Catz SL, Remien RH, et al. Theory-guided, empirically supported avenues for intervention on HIV medication nonadherence: findings from the Healthy Living Project. AIDS Patient Care STDS. 2003;17:645-656.
12. Remien RH, Hirky AE, Johnson MO, et al. Adherence to medication treatment: a qualitative study of facilitators and barriers among a diverse sample of HIV+ men and women in four US cities. AIDS Behav. 2003;7:61-72.
13. Moore RD, Keruly JC, Chaisson RE. Differences in HIV disease progression by injecting drug use in HIV-infected persons in care. J Acquir Immune Defic Syndr. 2004;35:46-51.
14. Shapiro MF, Morton SC, McCaffrey DF, et al. Variations in the care of HIV-infected adults in the United States: results from the HIV Cost and Services Utilization Study. JAMA. 1999;281:2305-2315.
15. Lucas GM, Cheever LW, Chaisson RE, et al. Detrimental effects of continued illicit drug use on the treatment of HIV-1 infection. J Acquir Immune Defic Syndr. 2001;27:251-259.
16. Arnsten JH, Demas PA, Grant RW, et al. Impact of active drug use on antiretroviral therapy adherence and viral suppression in HIV-infected drug users. J Gen Intern Med. 2002;17:377-381.
17. Tucker JS, Burnam MA, Sherbourne CD, et al. Substance use and mental health correlates of nonadherence to antiretroviral medications in a sample of patients with human immunodeficiency virus infection. Am J Med. 2003;114:573-580.
18. Palepu A, Horton NJ, Tibbetts N, et al. Uptake and adherence to highly active antiretroviral therapy among HIV-infected people with alcohol and other substance use problems: the impact of substance abuse treatment. Addiction. 2004;99:361-368.
19. Moss AR, Hahn JA, Perry S, et al. Adherence to highly active antiretroviral therapy in the homeless population in San Francisco: a prospective study. Clin Infect Dis. 2004;39:1190-1198.
20. Purkayastha T, Wasi F, Shuter J. Factors associated with sustained virologic suppression in patients receiving antiretroviral therapy in an urban HIV care clinic. AIDS Patient Care STDS. 2005;19:785-793.
21. Carrieri MP, Chesney MA, Spire B, et al. Failure to maintain adherence to HAART in a cohort of French HIV-positive injecting drug users. Int J Behav Med. 2003;10:1-14.
22. Chesney MA. Adherence to HAART regimens. AIDS Patient Care STDS. 2003;17:169-177.
23. Rabkin JG, Johnson J, Lin SH, et al. Psychopathology in male and female HIV-positive and negative injecting drug users: longitudinal course over 3 years. AIDS. 1997;11:507-515.
24. Knowlton AR, Arnsten JH, Gourevitch MN, et al. Individual, interpersonal, and structural correlates of effective highly active antiretroviral therapy use among urban active injection drug users. J Acquir Immune Defic Syndr. 2006;41:486-492.
25. Pearlin LI, Mullan JT, Aneshensel CS, et al. The structure and functions of AIDS caregiving relationships. Psychiatr Rehabil J. 1994;17:51-67.
26. Arno P, Levine C, Memmott M. The economic value of informal caregiving. Health Aff. 1998;18:182-188.
27. Young J, De Geest S, Spirig R, et al. Stable partnership and progression to AIDS or death in HIV infected patients receiving highly active antiretroviral therapy: Swiss HIV cohort study. BMJ. 2004;328:15-20.
28. Wardlaw LA. Sustaining informal caregivers for persons with AIDS. Fam Soc. 1994;75:373-384.
29. Wight RG, LeBlanc AJ, Aneshensel CS. Support service use by persons with AIDS and their caregivers. AIDS Care. 1995;7:509-520.
30. Samet JH, Freedberg KA, Stein MD, et al. Trillion virion delay: time from testing positive for HIV to presentation for primary care. Arch Intern Med. 1998;158:734-740.
31. Knowlton A. Informal HIV caregiving in a vulnerable population: toward a network resource framework. Soc Sci Med. 2003;56:1307-1320.
32. Johnston D, Stall R, Smith K. Reliance by gay men and intravenous drug users on friends and family for AIDS-related care. AIDS Care. 1995;7:307-319.
33. Knowlton A, Hua W, Latkin C. Social support among HIV positive injection drug users: implications to integrated intervention for HIV positives. AIDS Behav. 2004;8:357-363.
34. Knowlton A, Hua W, Latkin C. Social support networks and medical service use among HIV-positive injection drug users: implications for intervention. AIDS Care. 2005;17:479-492.
35. Waldrop-Valverde D, Valverde E. Homelessness and psychological distress as contributors to antiretroviral nonadherence in HIV-positive injecting drug users. AIDS Patient Care STDS. 2005;19:326-334.
36. Godin G, Cote J, Naccache H, et al. Prediction of adherence to antiretroviral therapy: a one-year longitudinal study. AIDS Care. 2005;17:493-504.
37. Pratt RJ, Robinson N, Loveday HP, et al. Adherence to antiretroviral therapy: appropriate use of self-reporting in clinical practice. HIV Clin Trials. 2001;2:146-159.
38. Lloyd JJ, Ricketts EP, Strathdee SA, et al. Social contextual factors associated with entry into opiate agonist treatment among injection drug users. Am J Drug Alcohol Abuse. 2005;31:555-570.
39. Schroeder JR, Latkin CA, Hoover DR, et al. Social factors related to antiretroviral therapy use in injection drug users. AIDS Behav. 2001;5:363-369.
40. Siegel K, Schrimshaw EW, Raveis VH. Accounts for non-adherence to antiretroviral combination therapies among older HIV-infected adults. Psychol Health Med. 2000;5:29-42.
41. Golin C, Isasi F, Bontempi JB, et al. Secret pills: HIV-positive patients' experiences taking antiretroviral therapy in North Carolina. AIDS Educ Prev. 2002;14:318-329.
42. Folkman S, Chesney MA, Christopher-Richards A. Stress and coping in caregiving partners of men with AIDS. Psychiatr Clin North Am. 1994;17:35-53.
43. Parsons JT, Van Ora J, Missildine W, et al. Positive and negative consequences of HIV disclosure among seropositive injection drug users. AIDS Educ Prev. 2004;16:459-475.
44. Altice FL, Mostashari F, Friedland GH. Trust and the acceptance of and adherence to antiretroviral therapy. J Acquir Immune Defic Syndr. 2001;28:47-58.
45. Bakken S, Holzemer WL, Brown MA, et al. Relationships between perception of engagement with health care provider and demographic characteristics, health status, and adherence to therapeutic regimen in persons with HIV/AIDS. AIDS Patient Care STDS. 2000;14:189-197.
46. Demmer C. Relationship with health care provider and adherence to HIV medications. Psychol Rep. 2003;93:494-496.
47. Schneider J, Kaplan SH, Greenfield S, et al. Better physician-patient relationships are associated with higher reported adherence to antiretroviral therapy in patients with HIV infection. J Gen Intern Med. 2004;19:1096-1103.
48. Goldstein RB, Rotherman-Borus MJ, Johnson MO, et al. Insurance coverage, usual source of care, and receipt of clinically indicated care for comorbid conditions among adults living with human immunodeficiency virus. Med Care. 2005;43:401-410.
49. Clarke S, Delamere S, McCullough L, et al. Assessing limiting factors to the acceptance of antiretroviral therapy in a large cohort of injecting drug users. HIV Med. 2003;4:33-37.
50. Purcell DW, Metsch LR, Latka M, et al. Interventions for seropositive injectors- research and evaluation: an integrated behavioral intervention with HIV-positive injection drug users to address medical care, adherence, and risk reduction. J Acquir Immune Defic Syndr. 2004;37(Suppl):S110-S118.
51. Centers for Disease Control and Prevention. Guidelines for using antiretroviral agents among HIV-infected adults and adolescents. MMWR Morb Mort Wkly Rep. 2002;51:40.
52. Derogatis LR, Spencer PM. The Brief Symptom Inventory (BSI): Administration, Scoring, and Procedural Manual-1. Baltimore, MD: John Wiley; 1982.
53. Mizuno Y, Purcell DW, Dawson-Rose C, et al. Correlates of depressive symptoms among HIV-positive injection drug users: the role of social support. AIDS Care. 2003;15:689-698.
54. Ewart CK. Social action theory for a public health psychology. Am Psychol. 1991;46:931-946.
55. Pescosolido B, Levy J. The role of social networks in health, illness, disease and healing: the accepting present, the forgotten past and the dangerous potential for a complacent future. In: Levy J, Pescosolido B, eds. Social Networks and Health. Amsterdam, The Netherlands: JAI; 2002:3-25.
56. Wagner GJ, Ryan GW. Relationship between routinization of daily behaviors and medication adherence in HIV-positive drug users. AIDS Patient Care STDS. 2004;18:385-393.
57. Thoits PA. Stress, coping, and social support processes: where are we? What next? J Health Soc Behav. 1995;Spec No:53-79.
58. Knowlton AR, Latkin CA. Network financial support and conflict as predictors of depressive symptoms among a disadvantaged population. J Community Psychol. 2007;35:13-28.
59. Knowlton AR, Curry A, Wissow L, et al. Depression and social context: characteristics of primary supporters as correlates of depression among HIV positive drug users. J Commun Psychol. (in press).
60. Clark RE. Family costs associated with severe mental illness and substance use. Hosp Community Psychiatry. 1994;45:808-813.
61. Wight RG. Precursive depression among HIV infected AIDS caregivers over time. Soc Sci Med. 2000;51:759-770.
62. Joseph EB, Bhatti RS. Psychosocial problems and coping patterns of HIV seropositive wives of men with HIV/AIDS. Soc Work Health Care. 2004;39:29-47.
63. Pearlin LI, Aneshensel CS, LeBlanc AJ. The forms and mechanisms of stress proliferation: the case of AIDS caregivers. J Health Soc Behav. 1997;38:223-236.
64. LeBlanc AJ, London AS, Aneshensel CS. The physical costs of AIDS caregiving. Soc Sci Med. 1997;45:915-923.

adherence; highly active antiretroviral therapy effectiveness; HIV/AIDS; home and community care; illicit injection drug users; social support structures

© 2007 Lippincott Williams & Wilkins, Inc.