There is growing interest in understanding factors that shape resilience among people living with HIV (PLHIV) around the world. PLHIV face disproportionate psychosocial (e.g., depression, substance abuse) and structural (e.g., discrimination) adversities [1,2], and HIV can have a substantial impact on quality of life even when PLHIV are asymptomatic . Evidence also suggests that resilience improves quality of life and health outcomes among PLHIV [3–5], including via facilitating uptake of and adherence to antiretroviral therapy (ART) . With the increasing availability of and advances in treatment, promoting resilience among PLHIV is crucial for enabling PLHIV to live longer, healthier lives [7,8]. Thus, it is critical to better understand what shapes resilience among PLHIV, within and across populations.
Existing literature has demonstrated that PLHIV report substantial resilience – often defined as ‘positive adaptation within the context of significant adversity’  – when facing HIV [8,10–13]. Factors associated with resilience, and the related phenomena of health-related quality of life (the impact of health on individuals’ perceptions of their wellbeing and level of functioning in important areas of their lives) [14,15], include individual, interpersonal and structural influences. At the individual level, adverse influences include socioeconomic adversity [15–17], mental health problems [15,18,19], internalized HIV-related stigma (i.e., self-stigma) [4,11,15,20], enacted/experienced HIV-related stigma [15,20–24]; and suboptimal health status [15,17,21,25] (e.g., presence of symptoms), whereas spirituality/faith has shown a positive influence [8,13]. At the interpersonal level, social support (comfort, assistance, and/or information received from individuals or groups ) is consistently found to be associated with higher resilience [5,15,21,23,25]. The few, mainly qualitative studies addressing contextual or structural-level factors [8,13,27] describe community processes of building greater resilience over time, characterized by cohesion, activism, and social/health system support structures.
Yet, several key gaps remain in our understanding of resilience. First, there is a dearth of research simultaneously examining the relative contribution of factors influencing resilience among PLHIV at multiple levels, including the structural/policy level, which may limit insights into effective interventions to build resilience [3,28,29]. Second, few studies on factors associated with resilience among PLHIV include data from more than one country or compare geographic locations within a country. Finally, to date, no HIV-specific measures of resilience existed. Most commonly, studies among PLHIV have used general measures of resilience or quality of life (i.e., with all or most scale questions not referring to HIV status).
To address these issues, we developed and evaluated the PLHIV Resilience Scale , a HIV-specific measure permitting an investigation of resilience specifically related to the experience of living with HIV . This scale was developed as part of a consultative process to update the People Living with HIV Stigma Index, a widely used survey tool implemented by and for PLHIV to track stigma and discrimination worldwide . The Stigma Index 2.0 was developed through an iterative process involving multiple stakeholders, including PLHIV networks and advocates, to respond to changes in global treatment guidelines, to more fully reflect the experiences of key populations , and to better capture resilience among PLHIV.
In this article, we present Stigma Index 2.0 data from Cambodia, the Dominican Republic, and Uganda, enabling comparisons between different continents, cultures, HIV epidemics and responses, as well as legal and advocacy environments. We sought to answer three questions: first, to what extent do levels of resilience vary, between countries and between different geographic areas within each country? Second, what factors shape resilience at the individual, interpersonal, and structural/policy levels, and are similar factors important across countries? Third, what is the relative importance of each level for resilience? We conclude with a discussion of implications of findings for future research as well as programmatic, policy and advocacy efforts.
We implemented the PLHIV Stigma Index 2.0 in Cambodia (2019), the Dominican Republic (2018) and Uganda (2017). Six provinces/districts were included per country. Two provinces in Cambodia and one district in Uganda were urban, and the rest were periurban or rural; all provinces in the Dominican Republic were urban. Overall adult HIV prevalence was 0.5% in Cambodia, 0.9% in the Dominican Republic, and 5.8% Uganda, with markedly higher prevalence in each country among key populations (e.g., female sex workers, MSM, transgender individuals, and people who inject drugs) .
In all three countries, a combination of two nonprobabilistic sampling methods, venue-based and snowball sampling, was used to capture a diverse group of PLHIV with different experiences. For venue-based sampling, PLHIV were recruited via formal PLHIV networks, community-based organizations serving key populations, or clinics providing HIV care. For snowball sampling, study participants invited their peers to be interviewed.
In accordance with Stigma Index implementation procedures, the survey was administered by PLHIV trained on the instrument. Uganda used a pilot version of the ‘Stigma Index 2.0’ survey instrument; Cambodia and the Dominican Republic used the final Stigma Index 2.0, which had been refined based on pilot results. Study protocols were reviewed and approved by the Population Council Institutional Review Board (New York, USA), the Cambodian National Ethics Committee for Health Research (Cambodia), Consejo Nacional de Bioética en Salud Dominican Republic, and Mildmay Research Ethics Committee (Uganda). All participants provided informed consent.
We developed a conceptual model of hypothesized relationships between individual, interpersonal, and structural variables and resilience (Fig. 1). We assumed that the relationship between most variables and resilience is likely to be bi-directional (and perhaps mutually reinforcing over time). In a few cases, however, we assumed it was more likely that the variable precedes and causes resilience, rather than vice versa: first, the sociodemographic control variables (which with little doubt preceded resilience); second, ever having experienced a human rights abuse (which likely preceded resilience, which was assessed in the last 12 months); and third, structural/policy-level factors, which represent an aggregate scores for all respondents from the province/district (i.e., it would be unlikely that the particular respondent's level of resilience affected that of his/her province/district's).
We grouped variables within the individual, interpersonal and structural/policy levels (Table 1 ). Four sociodemographic control variables (age, gender identity, level of education, and length of time knowing HIV status) were assigned as such because they are less amenable to change through intervention. Structural/policy level variables were ‘aggregated’ from individual respondents’ responses in each province/district, to create ecological variables . Each respondent was then assigned a value representing the proportion of the variable of interest for their district/province – for example the proportion with food/housing insecurity could be 0.14 for respondents in one district and 0.46 for respondents in another.
All analyses were conducted for each country separately using Stata v15 . We assessed intraclass correlation (ICC) to understand the proportion of variation in resilience that was explained by province/district (0.14 in Cambodia, 0.08 in the Dominican Republic, and 0.06 in Uganda). These relatively high ICCs (for geographic variation of psychosocial variables)  led us to include structural/policy-level variables in an effort to explain variation between province/districts. We used the SVY (survey) command to adjust for recruitment method in Cambodia and Uganda (recruitment method was not a variable in the Dominican Republic data set).
After ensuring that no multicollinearity was present for the independent variables (all variance inflation factor and tolerance values were, respectively, <4.5 and >0.2), we assessed associations between resilience and each variable in the model, controlling for the four sociodemographic variables to understand the unique contribution of each variable beyond the controls. We then conducted hierarchical multiple regression and calculated the increase in proportion of variance (R2) in resilience explained by each set of control, individual, interpersonal, and structural-level variables (Table 1 ).
Mean age of respondents was 45 years in Cambodia (n = 1207), 39 in the Dominican Republic (n = 891), and 36 in Uganda (n = 391), with mean time since learning HIV diagnosis ranging from 7 years in Uganda and the Dominican Republic to 11 in Cambodia (Table 2). Over 94% of respondents reported currently taking ART, and even more reported being in HIV care (data not shown). A majority in each country had not completed secondary school. Approximately 60% of respondents in each country were women and 56% of respondents in the Dominican Republic, 42% in Uganda, and 3% in Cambodia reported being members of key populations. The most common key populations were female sex workers, MSM, and people who inject drugs. In the Dominican Republic, 10% of respondents were of Haitian origin, a population disproportionately burdened by HIV in that country and thus considered a key population .
Mean resilience scores, on a scale of −10 to +10, were 1.50 in Cambodia, 0.25 in the Dominican Republic, and 0.69 in Uganda (Fig. 2), with SDs of about four in each country (data not shown). Mean scores also differed substantially by province/district within each country (Fig. 2). These differences were highly statistically significant (all p < 0.001), even when controlling for varying province/district-level makeup of key populations and gender identities.
Descriptive statistics for variables included in the regression models are also included in Table 2.
Mean levels of internalized stigma fell in the middle of the range (low of 0–high of 6), at 3.6, 2.6, and 2.1 in Cambodia, the Dominican Republic and Uganda, respectively. About one-third of PLHIV in Cambodia and the Dominican Republic, and almost two-thirds in Uganda, had experienced at least one type of HIV-related enacted stigma in the last year. Among key populations, 19% in Cambodia, 32% in the Dominican Republic, and 47% in Uganda had experienced key population-related stigma in the last 12 months. Twenty-nine percentage of respondents in Cambodia reported ever experiencing a human rights abuse, as did 14% in Dominican Republic and Uganda. Finally, over two-thirds (69%) of respondents in Uganda, and about 14% in Cambodia and the Dominican Republic, reported experiencing food/housing insecurity.
About half of respondents in each country were currently in an intimate partnership. About half in Cambodia (42%) and the Dominican Republic (56%), and three-quarters (74%) in Uganda, reported supportive disclosure experiences with family and friends, although HIV-related stigma from family was 32% in Uganda, 20% in the Dominican Republic, and 3% in Cambodia.
For the aggregated structural-level variables, enacted stigma ranged from 13 to 60% across provinces/districts in Cambodia, 14–54% in the Dominican Republic, and 40–83% in Uganda. Province/districts also varied in terms of prevalence of food/housing insecurity, from 4 to 34% in Cambodia, 4–37% in the Dominican Republic, and 46–78% in Uganda. On average, about two-thirds of respondents in Cambodia and the Dominican Republic, and one-third in Uganda, were aware that there are legal protections for PLHIV against discrimination; these levels also varied by province/district in each country.
Associations between single factors and resilience (adjusting for controls)
Results of regression analyses between single factors and resilience (adjusting for control variables) are presented in Table 3. At the individual level, higher resilience was associated with lower internalized stigma (all three countries), more HIV-related stigma (Cambodia and the Dominican Republic), not experiencing human rights abuses (Uganda), and not experiencing food/housing insecurity (Cambodia). At the interpersonal level, higher resilience was associated with supportive disclosure experiences with family/friends (Cambodia and Dominican Republic), not being in an intimate partnership (Cambodia), and not experiencing stigma from close family (Uganda). At the structural/policy level, higher resilience was associated with awareness of legal protections for PLHIV (all three countries), higher HIV-related enacted stigma in the community (Cambodia and the Dominican Republic), and food/housing insecurity (lower in Cambodia; higher in Uganda). In addition, longer time since diagnosis (a control variable) was associated with higher resilience in the Dominican Republic and Uganda, as was younger age in Uganda, higher level of education in the Dominican Republic, and male (vs. female) gender identity in Cambodia.
In multivariable analyses, at the individual level higher resilience was associated with lower internalized stigma (all three countries), not experiencing food/housing insecurity (Uganda), and, in the Dominican Republic, with not experiencing human rights abuses and experiencing more HIV-related stigma. At the interpersonal level, there were no significant associations with resilience. At the structural/policy level, higher resilience was associated with higher awareness of legal protections for PLHIV (Cambodia and Dominican Republic), HIV-related enacted stigma (lower in Cambodia and higher in the Dominican Republic), and higher food/housing insecurity (Uganda). Longer time since diagnosis remained associated with higher resilience in the Dominican Republic and Uganda, as did younger age in Uganda. Male (vs. female) gender identity was also associated with higher resilience in Uganda.
Proportion of variance explained
In Cambodia and the Dominican Republic, the set of structural/policy-level variables explained the largest percentage of variance in resilience (R2 of 10 and 3%, respectively, above and beyond the other sets of factors), followed by the individual, then interpersonal levels. In Uganda, the set of individual-level variables explained the largest percentage of variance (7%), followed by structural, then interpersonal. The total percentage of variance explained by the full regression models was 19% in Cambodia and Uganda, and 13% in the Dominican Republic.
We found that factors at multiple levels are associated with resilience among PLHIV in Cambodia, the Dominican Republic, and Uganda. The most consistent findings were that higher resilience was associated with lower internalized stigma and with living in contexts with greater awareness of legal protections for PLHIV. To our knowledge, this study is the first to investigate geographic differences in experiences of resilience among PLHIV, which also enables examination of structural/policy influences. Critically, levels of resilience varied substantially across provinces/districts within each country (all p < 0.001). ICCs were 0.06–0.14, relatively large magnitudes for geographic clustering of psychosocial variables . Given the robust sample sizes of all provinces/districts, it is unlikely that this variation was due to chance. The extent of this variation led us to ask what might be causing it, and hence to incorporate structural/policy-level variables (i.e., variables that vary at the province/district level) in addition to individual-level and interpersonal-level variables. Our results for Cambodia and the Dominican Republic indicated that, in fact, the set of structural/policy-level variables explained more variance than individual or interpersonal-level variables.
The most consistent finding across single variable and multivariable analyses was the strong inverse relationship between resilience and internalized HIV-related stigma – the personal shame associated with HIV/AIDS and fear of being discriminated against on account of the illness . Several studies have suggested that internalized stigma may be particularly critical to psychosocial wellbeing (similar to resilience in this study), whereas enacted HIV-related stigma may be more closely tied to health outcomes [5,20]. A recent study in India, for example, found that internalized stigma was twice as detrimental as enacted stigma to quality of life among PLHIV .
Another consistent finding was how direct a role the legal environment and human rights issues play in respondents’ lives. Such findings emerged to some extent in each country. Those living in contexts with greater awareness of legal protections for PLHIV against discrimination had higher resilience (although in Uganda, this was only significant in the single-variable analysis). In addition, individuals who reported experiencing human rights abuses had lower resilience in the Dominican Republic (multivariable analysis) and Uganda (in the single-variable analysis). It is unclear why experiencing a human rights abuse was not associated with resilience in Cambodia. Perhaps the high prevalence of such abuses in Cambodia (29%, compared with 14% for Dominican Republic and Uganda) has increased solidarity among PLHIV, buffering adverse effects of such abuses on resilience. Although there is a rich body of literature around the effects of human rights, policy and legal environments on PLHIV and key populations [39–43], most studies have focused on effects on HIV testing and care outcomes, with few assessing impact on resilience or quality of life. This is a much-needed area for continued research and programming.
Enacted HIV-related stigmas were also important in our study, although findings were less consistent than for internalized stigma. In the multivariate model, higher levels of enacted stigma in the community were associated with lower resilience among PLHIV in Cambodia. These findings are similar to the previous Cambodian implementation of the Stigma Index which found links between experiencing enacted HIV-related stigma and increased mental health problems (i.e., an adverse form of psychosocial wellbeing) . In the Dominican Republic, HIV-related enacted stigma, at the individual-level and community-level, was in fact linked to greater resilience. This may reflect a phenomena documented in recent qualitative research from that country – community processes that enable the collective reconstruction of identity among PLHIV as a means of challenging stigma . It could also be that more resilient respondents had greater awareness of/vigilance around enacted stigmas, and thus were more likely to report these experiences (although it is unclear why this would particularly be the case in the Dominican Republic). Significantly, in Uganda, in which nearly two-thirds of respondents reported experiencing enacted stigma related to HIV in the last year (vs. one-third in Cambodia and the Dominican Republic), there were no significant associations between resilience either at the individual or structural/policy levels. Perhaps the negative effects of such prevalent experiences with discrimination are in effect being counteracted by positive collective responses. Key population-related stigma and discrimination (assessed in the Dominican Republic and Uganda) was not associated with resilience. Although many studies have documented links between such stigma/discrimination and HIV treatment or health outcomes [45,46], few have examined it in relation to resilience and those findings have been mixed [21,47]. More research is clearly warranted around the complex ways in which reported stigma experiences are linked to resilience.
Although most findings were consistent across the three countries, in Uganda only, food/housing insecurity was associated with lower resilience, reflecting other recent research in that country [8,16]. Russell and Seeley  described how even as ART became more widely available, circumstances of poverty and vulnerability undermined the transition toward more positive living with HIV, and how strong social and health support systems became very important in this context. The existence of support systems for vulnerable populations in Uganda may help explain the association we found between higher structural/policy-level adversity and higher resilience, although it is curious that no factors related to interpersonal support were similarly associated.
We were surprised by the lack of significant associations between interpersonal-level factors and resilience in the multivariate model (although a few single-variable associations were significant), particularly given evidence for the importance of social support to resilience and quality of life among PLHIV [5,15,21,23,25]. However, because the Stigma Index 2.0 does not include a direct measure of social support (such as the Medical Outcomes Study Social Support Survey ), it may be that the variables we chose (having an intimate partner, supportive disclosure experiences with family and friends) have more complex associations with resilience . For example, in a study in China, Huang et al. found that the resilience-promoting effects of couple identity/commitment were diminished if the couple had experienced HIV-related stigma. Previous studies have also shown mixed findings regarding the effect of relationship status and disclosure experiences on resilience/quality of life among PLHIV [17,21,49,50].
Taken together, our findings suggest that to promote resilience among PLHIV, interventions are needed that simultaneously address key factors at different levels. In particular, we suggest that such interventions should incorporate efforts to reduce internalized stigma and promote supportive structural/legal environments including broader awareness of legal protections for PLHIV. There is a growing body of evidence showing what works to address such factors; this should be tailored to the unique country contexts and build on interventions and policies already in place. Promising approaches to reducing internalized stigma include group sessions that encourage social support and active learning [51,52], cognitive behavioral therapy [53,54] and individually-tailored motivational counseling at entry into care . The Joint United Nations Programme on HIV and AIDS (UNAIDS) has prioritized seven human rights programs for incorporation into HIV/AIDS responses, many of which are structural in nature [43,56], including HIV-related legal services; sensitization of lawmakers and law enforcement agents; and rights and legal literacy programs. In line with ‘rights and literacy programs’, our findings around the resilience-promoting effects of awareness of existing legal protections for PLHIV against discrimination in each country suggest that an intervention that promotes greater awareness of legal protections (e.g., via mass media) could be effective in promoting resilience. Finally, there are also effective interventions to reduce enacted HIV-related stigma and discrimination [43,57–60], many of which focus on social cohesion and support organizations for PLHIV, including via social media and other internet-based platforms [47,61,62]. Such approaches could be strengthened by involving mentors living with HIV for several years, given findings that such individuals reported higher resilience (in the Dominican Republic and Uganda, with an average of seven years since diagnosis, vs. 11 in Cambodia).
The study had several limitations. First, the cross-sectional nature of the data limits inferences about temporality of associations between the independent variables and resilience. Although some factors we examined temporally or logically precede resilience, some do not, and it could very well be that resilience in fact preceded and perhaps caused those factors. Second, there are potential limitations of our analysis methods. The relatively large ICCs for clustering of resilience by province/district, along with our interest in contextual factors influencing resilience, would normally benefit from multilevel/hierarchical modeling. However, the number of provinces/districts available in the samples precluded such analysis, given the minimum of ∼10 clusters required . Generalized estimating equations are similarly ill-advised with a small number of clusters , and adjusting for province/district was not possible given complete collinearity with the aggregate structural-level variables. Therefore, findings around the proportion of variance in resilience accounted for by the set of structural/policy-level factors may have been overestimated. However, we incorporated structural-level variables in the model that we hypothesized to be important in explaining cluster-level variation, included similar/parallel individual-level variables to those structural-level variables, and calculated the increase in variance explained for the structural/policy-level set above and beyond the other sets of factors. Third, whereas key population membership would normally be important to include as a control variable in the models, we were unable to do so (due to collinearity with key population-related enacted stigma, since none of the non-key-population members had experienced such stigma). Fourth, responses were based on self-report, which can lead to social desirability bias. Finally, while using a purposive sampling design enabled us to capture experiences of important subgroups such as key populations, it may also limit representativeness/generalizability of findings to all PLHIV living in the districts/provinces or countries in this study. In particular, the proportion of each key population in our sample is likely to overrepresent the true population proportion for the Dominican Republic and Uganda, and underrepresent it for Cambodia, per available data from UNAIDS . Furthermore, because most of the study participants were engaged in care and/or taking ART, their levels of resilience may be different from those not engaged in care or treatment.
Our findings support the growing consensus that resilience among PLHIV is fundamentally shaped by factors at multiple levels, and that multilevel interventions are required [28,29,65]. The PLHIV Stigma Index 2.0 allowed us to empirically explore a diverse set of factors at multiple levels, both those more conventionally investigated and understudied, within and across countries. Perhaps our most illuminating finding is the existence of geographic variation in resilience. Identifying structural and other drivers of this variation could pave the way for effective multilevel interventions.
We would like to sincerely thank the People Living with HIV Stigma Index 2.0 respondents and interviewers in Cambodia, the Dominican Republic and Uganda.
Members of the People Living with HIV Stigma Index 2.0 study group include the following. In Cambodia: Sotheariddh Sorn, Ashish Bajracharya, Tep Navuth, Molyaneth Heng, Steve Wignall, and Polin Ung. In the Dominican Republic: Dulce Almonte, Felipa García, Yordana Dolores, Angel Del Valle, Alejandra Colom, and Eileen Yam. In Uganda: Stella Kentusi, Prossy Nanyanzi, Richard Mugumya, Richard Batamwita, Enos Sande, Jerry Okal, and Arnold Asava.
We also acknowledge and thank the members of the PLHIV Stigma Index Small Working Group involved in the process of updating the Stigma Index 2.0 from 2016 to 2018, which included: Christoforos Mallouris, Scott Geibel, Laurel Sprague, Julian Hows, Laura Nyblade, Stefan Baral, Florence Anam, Ugochukwu Amanyeiwe, Alison Cheng, Aasha Jackson, Noah Metheny, and Cameron Wolf. Julie Pulerwitz and Barbara Friedland, coauthors on the present article, were also members of this group.
Author contributions: Study conception: A.G.; study design: A.G., B.F., J.P., PLHIV Stigma Index 2.0 Study Group; protocol development: B.F., PLHIV Stigma Index 2.0 Study Group; data analysis and article preparation: T.M., A.G.; article review and final version approval: A.G., T.M., J.P., B.F.
The work was supported by Project SOAR (Cooperative Agreement AID–OAA–A–14–00060) made possible by the generous support of the American people through the United States President's Emergency Plan for AIDS Relief (PEPFAR) and United States Agency for International Development (USAID). The contents of this article are the sole responsibility of the authors and do not necessarily reflect the views of PEPFAR, USAID, or the United States Government. Funding for the Cambodia study was provided by the USAID Cambodia through FHI360's Linkages project and the Joint United Nations Programme on HIV and AIDS (UNAIDS) in Cambodia.
Conflicts of interest
There are no conflicts of interest.
1. Aranda-Naranjo B. Quality of life in the HIV-positive patient: implications and consequences
. J Assoc Nurses AIDS Care
2. Gakhar H, Kamali A, Holodniy M. Health-related quality of life assessment after antiretroviral therapy: a review of the literature
3. Dulin AJ, Dale SK, Earnshaw VA, Fava JL, Mugavero MJ, Napravnik S, et al. Resilience and HIV: a review of the definition and study of resilience
. AIDS Care
4. Zhang L, Li X, Qiao S, Zhou Y, Shen Z, Tang Z, et al. The mediating role of individual resilience resources in stigma–health relationship among people living with HIV in Guangxi, China
. AIDS Care
5. Zhao Q, Mao Y, Li X, Qiao S, Zhou Y, Shen Z. Psychosocial correlates of health-related quality of life among people living with HIV in China: the mediating role of resilience
6. UNAIDS. The gap report
. Geneva: UNAIDS; 2014.
7. Deeks SG, Lewin SR, Havlir DV. The end of AIDS: HIV infection as a chronic disease
8. Russell S, Seeley J. The transition to living with HIV as a chronic condition in rural Uganda: working to create order and control when on antiretroviral therapy
. Soc Sci Med
9. Luthar SS, Cicchetti D, Becker B. The construct of resilience: a critical evaluation and guidelines for future work
. Child Dev
10. De Santis JP, Florom-Smith A, Vermeesch A, Barroso S, DeLeon DA. Motivation, management, and mastery: a theory of resilience in the context of HIV infection
. J Am Psychiatr Nurses Assoc
11. Garrido-Hernansaiz H, Murphy PJ, Alonso-Tapia J. Predictors of resilience and posttraumatic growth among people living with HIV: a longitudinal study
. AIDS Behav
12. Gottert A, Friedland B, Geibel S, Nyblade L, Baral S, Kentutsi S, et al. The people living with HIV (PLHIV) resilience scale: development and validation in three countries in the context of the PLHIV stigma index
. AIDS Behav
13. Hussen SA, Tsegaye M, Argaw MG, Andes K, Gilliard D, del Rio C. Spirituality, social capital and service: factors promoting resilience among expert patients living with HIV in Ethiopia
. Glob Public Health
14. Cooper V, Clatworthy J, Harding R, Whetham J. Emerge Consortium Collaborators. Measuring quality of life among people living with HIV: a systematic review of reviews
. Health Qual Life Outcomes
15. Degroote S, Vogelaers D, Vandijck DM. What determines health-related quality of life among people living with HIV: an updated review of the literature
. Arch Public Health
16. Stangl A, Wamai N, Mermin J, Awor A, Bunnell R. Trends and predictors of quality of life among HIV-infected adults taking highly active antiretroviral therapy in rural Uganda
. AIDS Care
17. Zeluf-Andersson G, Eriksson LE, Schönnesson LN, Höijer J, Månehall P, Ekström AM. Beyond viral suppression: the quality of life of people living with HIV in Sweden
. AIDS Care
18. Li H, Tucker J, Holroyd E, Zhang J, Jiang B. Suicidal ideation, resilience, and healthcare implications for newly diagnosed HIV-positive men who have sex with men in China: a qualitative study
. Arch Sex Behav
19. Monteiro F, Canavarro MC, Pereira M. Factors associated with quality of life in middle-aged and older patients living with HIV
. AIDS Care
2016; 28 (Supp1 1):92–98.
20. Earnshaw VA, Smith LR, Chaudoir SR, Amico KR, Copenhaver MM. HIV stigma mechanisms and well being among PLWH: a test of the HIV stigma framework
. AIDS Behav
21. Garrido-Hernansaiz H, Heylen E, Bharat S, Ramakrishna J, Ekstrand ML. Stigmas, symptom severity and perceived social support predict quality of life for PLHIV in urban Indian context
. Health Qual Life Outcomes
22. Holzemer WL, Human S, Arudo J, Rosa ME, Hamilton MJ, Corless I, et al. Exploring HIV stigma and quality of life for persons living with HIV infection
. J Assoc Nurses AIDS Care
23. Logie CH, Wang Y, Lacombe-Duncan A, Wagner AC, Kaida A, Conway T, et al. HIV-related stigma, racial discrimination, and gender discrimination: pathways to physical and mental health-related quality of life among a national cohort of women living with HIV
. Prev Med
24. Mitchell MM, Nguyen TQ, Isenberg SR, Maragh-Bass AC, Keruly J, Knowlton AR. Psychosocial and service use correlates of health-related quality of life among a vulnerable population living with HIV/AIDS
. AIDS Behav
25. George S, Bergin C, Clarke S, Courtney G, Codd MB. Health-related quality of life and associated factors in people with HIV: an Irish cohort study
. Health Qual Life Outcomes
26. Earnshaw VA, Lang SM, Lippitt M, Jin H, Chaudoir SR. HIV stigma and physical health symptoms: do social support, adaptive coping, and/or identity centrality act as resilience resources?
. AIDS Behav
27. Carrasco MA, Barrington C, Kennedy C, Perez M, Donastorg Y, Kerrigan D. ‘We talk, we do not have shame’: addressing stigma by reconstructing identity through enhancing social cohesion among female sex workers living with HIV in the Dominican Republic
. Cult Health Sex
28. Harrison S, Li X. Rebooting resilience: shifts toward dynamic, multilevel, and technology-based approaches for people living with HIV
. AIDS Care
2018; 30: (Suppl 5): S1–S5.
29. Thomas-Slayter BP, Fisher WF. Social capital and AIDS-resilient communities: strengthening the AIDS response
. Glob Public Health
2011; 6: (Suppl 3): S323–S343.
30. Global Network of People Living with HIV (GNP+). The People Living with HIV Stigma
Index. Available from: https://www.gnpplus.net/our-solutions/hiv-stigma-index-2/
31. Friedland BA MC, Gottert A, Hows J, Nyblade L, Baral S, et al.
Developing the People Living with HIV Stigma
Index 2.0: a community-driven process for change. AIDS; in press.
32. Joint United Nations Programme on HIV and AIDS (UNAIDS). Country Fact Sheets 2019. Available from: https://www.unaids.org/en/regionscountries/countries/
33. Hox JJ, Moerbeek M, Van de Schoot R. Multilevel analysis: techniques and applications
. Sussex, Great Britain: Routledge; 2017.
34. StataCorp. Stata statistical software: release 15
. College Station, TX: StataCorp LLC; 2017.
35. Bland JM. Sample size in guidelines trials
. Fam Pract
36. Kalichman SC, Simbayi LC, Cloete A, Mthembu PP, Mkhonta RN, Ginindza T. Measuring AIDS stigmas in people living with HIV/AIDS: the Internalized AIDS-Related Stigma Scale
. AIDS Care
37. Rojas P, Malow R, Ruffin B, Rothe EM, Rosenberg R. The HIV/AIDS epidemic in the Dominican Republic: key contributing factors
. J Int Assoc Physicians AIDS Care (Chic)
38. Brouard P, Wills C. A closer look: the internalization of stigma related to HIV
. Washington, D.C.: United States Agency for International Development (USAID); 2006.
39. Beyrer C, Baral SD, Collins C, Richardson ET, Sullivan PS, Sanchez J, et al. The global response to HIV in men who have sex with men
40. Beyrer C, Crago A-L, Bekker L-G, Butler J, Shannon K, Kerrigan D, et al. An action agenda for HIV and sex workers
41. DeBeck K, Cheng T, Montaner JS, Beyrer C, Elliott R, Sherman S, et al. HIV and the criminalisation of drug use among people who inject drugs: a systematic review
. Lancet HIV
42. Chen AJ. HIV-specific criminal law: a global review
2016; 9 (3):
43. Stangl AL, Singh D, Windle M, Sievwright K, Footer K, Iovita A, et al. A systematic review of selected human rights programs to improve HIV-related outcomes from 2003 to 2015: what do we know?
. BMC Infect Dis
44. Yi S, Chhoun P, Suong S, Thin K, Brody C, Tuot S. AIDS-related stigma and mental disorders among people living with HIV: a cross-sectional study in Cambodia
. PLoS One
45. Rao D, Feldman BJ, Fredericksen RJ, Crane PK, Simoni JM, Kitahata MM, et al. A structural equation model of HIV-related stigma, depressive symptoms, and medication adherence
. AIDS Behav
46. Dlamini PS, Wantland D, Makoae LN, Chirwa M, Kohi TW, Greeff M, et al. HIV stigma and missed medications in HIV-positive people in five African countries
. AIDS Patient Care STDS
47. Barry MC, Threats M, Blackburn NA, LeGrand S, Dong W, Pulley DV, et al. Stay strong! keep ya head up! move on! it gets better!!!!’: resilience processes in the healthMpowerment online intervention of young black gay, bisexual and other men who have sex with men
. AIDS Care
2018; 30: (Suppl 5): S27–S38.
48. Moser A, Stuck AE, Silliman RA, Ganz PA, Clough-Gorr KM. The eight-item modified medical outcomes study social support survey: psychometric evaluation showed excellent performance
. J Clin Epidemiol
49. Huang J, Zhang J, Yu NX. Couple identity and well being in Chinese HIV serodiscordant couples: resilience under the risk of stigma
. AIDS Care
2018; 30: (Suppl 5): S58–S66.
50. Huang J, Zhang J, Yu NX. Close relationships, individual resilience resources, and well being among people living with HIV/AIDS in rural China
. AIDS Care
2018; 30: (Suppl 5): S49–S57.
51. Kidd R, Clay S, Chiiya C. Understanding and challenging HIV/AIDS stigma: a toolkit for action. International Center for Research on Women, Academy for Educational Development (AED)
. Washington, DC: International AIDS Alliance; 2007.
52. Rao D, Desmond M, Andrasik M, Rasberry T, Lambert N, Cohn SE, et al. Feasibility, acceptability, and preliminary efficacy of the unity workshop: an internalized stigma reduction intervention for African American women living with HIV
. AIDS Patient Care STDS
53. Tshabalala J, Visser M. Developing a cognitive behavioural therapy model to assist women to deal with HIV and stigma
. South African J Psychol
54. Yang JP, Simoni JM, Dorsey S, Lin Z, Sun M, Bao M, et al. Reducing distress and promoting resilience: a preliminary trial of a CBT skills intervention among recently HIV-diagnosed MSM in China
. AIDS Care
2018; 30: (Suppl 5): S39–S48.
55. Yigit I, Modi, R., Weiser, S., Johnson, M., Mugavero, M., Turan, J. & Turan, B. An engagement in care intervention for individuals entering HIV care decreases internalized HIV-related stigma
; in press.
56. Joint United Nations Programme on HIV and AIDS (UNAIDS). Key programmes to reduce stigma and discrimination and increase access to justice in national HIV responses
. Guidance note
57. Nyblade L, Stangl A, Weiss E, Ashburn K. Combating HIV stigma in healthcare settings: what works?
. J Int AIDS Soc
58. Mak WW, Mo PK, Ma GY, Lam MY. Meta-analysis and systematic review of studies on the effectiveness of HIV stigma reduction programs
. Soc Sci Med
59. Stangl AL, Lloyd JK, Brady LM, Holland CE, Baral S. A systematic review of interventions to reduce HIV-related stigma and discrimination from 2002 to 2013: how far have we come?
. J Int AIDS Soc
60. Pulerwitz J, Michaelis A, Weiss E, Brown L, Mahendra V. Reducing HIV-related stigma: lessons learned from Horizons research and programs
. Public Health Rep
61. Muessig KE, Nekkanti M, Bauermeister J, Bull S, Hightow-Weidman LB. A systematic review of recent smartphone, internet and web 2.0 interventions to address the HIV continuum of care
. Curr HIV/AIDS Rep
62. Bauermeister J, Muessig K, LeGrand S, Flores D, Choi S, Dong W, et al. HIV and sexuality stigma reduction through engagement in online forums: results from the HealthMPowerment intervention
. AIDS Behav
63. McNeish DM, Stapleton LM. The effect of small sample size on two-level model estimates: a review and illustration
. Educ Psychol Rev
64. Hubbard AE, Ahern J, Fleischer NL, Van der Laan M, Satariano SA, Jewell N, et al. To GEE or not to GEE: comparing population average and mixed models for estimating the associations between neighborhood risk factors and health
65. Baral S, Logie CH, Grosso A, Wirtz AL, Beyrer C. Modified social ecological model: a tool to guide the assessment of the risks and risk contexts of HIV epidemics
. BMC Public Health