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Abstract
External HIV-related stigma remains pervasive, and its effect debilitating among PLHIV in South Africa, even though the country has made many advances against HIV. External HIV-related stigma impedes both HIV prevention and access to health care and reduces the quality of treatment and care received. This study examined the prevalence of and factors associated with higher levels of HIV-related stigma among youth and adults 15 years and older in South Africa. The analysis used a nationally representative population-based household survey data collected using a multistage cluster random sampling design. Exploratory factor analysis was used to calculate the primary outcome (higher and lower HIV stigma index scores above and below the mean, respectively), based on the total number of factors retained from the 10 item self-reported questions relating to attitudes and beliefs against PLHIV. Bivariate and multivariate generalised linear models with a log link and binomial distribution were fitted to estimate crude and adjusted risk ratios (ARR) with 95% confidence intervals (CI) for factors associated with external HIV-related stigma. Of 38 919 respondents, 49% (49.8%; 95% CI: 48.6–51.1) were categorised as having higher levels of external HIV-related stigma. Higher levels of HIV-related stigma were significantly associated with those who had secondary level education than those with no education/primary education [ARR = 1.14 (95% CI: 1.05–1.24), p = 0.002], those employed than unemployed [ARR = 1.08 (95% CI: 1.02–1.14), p = 0.006], those in rural areas than urban areas [ARR = 1.15 (95% CI: 1.07–1.23), p<0.001], those who were aware of their HIV status than not aware [ARR = 1.34 (95% CI: 1.12–1.61), p<0.001], those who were HIV positive than HIV negative [ARR = 1.09 (95% CI: 1.02–1.17), p = 0.018], and those with no correct HIV knowledge and myth rejection than their counterparts [ARR = 1.09 (95% CI: 1.03–1.15), p = 0.002]. The findings highlight the need for peer-facilitated HIV-stigma reduction interventions targeting all types of educational institutions and the strengthening of work-based interventions. The findings emphasise the prioritisation of rural informal settings/tribal areas when developing and implementing HIV stigma reduction interventions. The study suggests that stigma reduction should be considered an important component of HIV testing and awareness. Addressing public misconceptions about HIV can mitigate externalised stigma.
Citation: Mehlomakulu V, Mabaso M, Jooste S, Cloete A, Moyo S, Simbayi L (2024) Prevalence and factors associated with external HIV-related stigma in the South African population: Results from the 2017 population-based household survey. PLoS ONE 19(9): e0309694. https://doi.org/10.1371/journal.pone.0309694
Editor: Matt A. Price, International AIDS Vaccine Initiative, UNITED STATES OF AMERICA
Received: October 5, 2023; Accepted: August 16, 2024; Published: September 3, 2024
Copyright: © 2024 Mehlomakulu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: Data used in this analysis are available from the Human Sciences Research Council’s public data repository (data set). South African National HIV Prevalence, HIV Incidence, Behaviour and Communication Survey 2017: Combined. Version 1.0. http://dx.doi.org/doi:10.14749/1585345902.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
HIV-related stigma is one of the biggest challenges facing people living with HIV (PLHIV) globally [1]. External HIV-related stigma is received and/or an enacted form of this social phenomenon that is associated with public blame for contracting HIV and refers to negative beliefs, feelings, and attitudes towards PLHIV [2, 3] Several studies have shown that a high proportion of PLHIV are stigmatised by the community members they share their lives with [2, 4, 5].
Evidence shows that despite continued widespread information, education, and communication campaigns to raise awareness about HIV, external HIV-related stigma is still highly prevalent in sub-Saharan Africa. A multicountry cross-sectional study using data from the Demographic and Health Surveys of 12 sub-Saharan African countries found that the prevalence of negative attitudes toward PLHIV was 36.2% [6]. The 2012 South African national HIV household survey reported that 38% of PLHIV portrayed HIV-related stigma attitudes towards PLHIV [7], and the national stigma index study in South Africa revealed that 36% of PLHIV experienced external HIV-related stigma [8].
External HIV-related stigma hinders accessibility to HIV-related services and support programmes [2, 3]. This has been shown to negatively affect adherence to antiretrovirals and viral load suppression resulting in poor health outcomes [9, 10]. External HIV-related stigma has also been associated with delaying diagnosis and non-disclosure among PLHIV and, therefore, reducing linkage to care and delaying achievement of the UNAIDS 95-95-95 goals [11].
External HIV-related stigma also impacts HIV prevention as PLHIV continue to engage in risky sexual practices such as having unprotected sex because discussions about the need for safer sex often lead to questions about a partner’s serostatus [12]. Similarly, fear of rejection and intimate partner violence may lead some to hide their positive HIV status from sexual partners [12]. Risk reduction, resilience, and coping interventions have been instrumental in reducing the negative impact of external HIV-related stigma on the lives of PLHIV [13]. However, many factors associated with external HIV-related stigma may also impact the effectiveness of stigma-reducing interventions [14]. Therefore, identifying factors associated with HIV-related stigma might help redesign or reinforce these interventions.
Externalised HIV-related stigma is underpinned by many factors, including socio-demographic factors such as race, sex, marital status, level of education, socioeconomic status, and place of residence [2, 6, 15]. Factors associated with externalised stigma also include poor HIV knowledge and misconceptions about HIV [16, 17]. The literature also suggests that there is a link between HIV-related knowledge, HIV serostatus awareness/disclosure, and stigma due to psychological and social stresses associated with a positive HIV test [16–21]. However, few studies have examined the drivers of HIV-related stigma at a population level.
South Africa has the largest number of PLHIV globally, and external HIV-related persists after more than 20 years of the fight against HIV despite efforts to address it [22, 23]. An improved understanding of the levels of external HIV-related stigma and associated factors at the population level is important for developing innovative and targeted interventions at a national level. Therefore, this paper examines the prevalence of external HIV-related stigma and associated factors in the general population in South Africa.
Methods
Ethical considerations
The original survey was approved by the Human Sciences Research Council ethics board under Ethics Clearance of HSRC Research Ethics Committee Protocol No REC4/18/11/15.
Data source and study sample
This study used data from the 2017 South African National HIV Prevalence, Incidence and Behaviour Survey, a nationally representative population-based household survey collected using a multistage cluster random sampling design described in detail elsewhere [22]. Data collection started on the 4th of December 2016 and ended on the 31st of January 2018. The data were collected using a complex multistage-stratified cluster sampling design. Using the 2015 national population sampling frame of 84 907 small area layers (SALs) developed by Statistics South Africa [24], 1000 SAL were randomly sampled across the country. A systematic random sample of 15 households was sampled within each SAL. All individuals living in a selected household were eligible for the survey.
Detailed questionnaires for the household and age-appropriate individual behavioural questionnaires were administered to all consenting eligible adults aged 18 years and older and all assenting eligible children aged 12–17 years old who also had parental or guardian consent. Parents or guardians completed the questionnaires on behalf of eligible children under the age of 12 years. Interview data was collected digitally using tablet computers with Census Survey Processing (CS Pro) software (US Census Bureau). In addition, dried blood spot (DBS) specimens were collected from consenting participants to determine, among other tests, HIV serostatus [22]. The sub-sample used in this study comprised youth and adults aged 15 years and older who responded to questions on HIV-related stigma.
Measures
Dependent variables.
The primary outcome measure of the HIV stigma scale was based on a question relating to attitudes and beliefs against PLHIV with 10 items listed below:
- If you knew that a shopkeeper or food seller had HIV, would you buy food from them?
- Would you buy fresh vegetables from a shopkeeper or vendor if you knew that this person had HIV?
- Would you be willing to care for a family member with AIDS?
- If a teacher has HIV but is not sick, should he or she be allowed to continue teaching?
- Is it a waste of money to train or give a promotion to someone with HIV/AIDS?
- Would you want to keep the HIV-positive status of a family member a secret?
- Are you comfortable talking to at least one member of your family about HIV/AIDS?
- A person would be foolish to marry a person who is living with HIV/AIDS?
- If a pupil has HIV but not sick, should he or she be allowed to continue to go to school?
- Do you think children living with HIV should be able to attend school with children who are HIV-negative?
The respondents had to answer “Yes”, “No” and “Don’t know”.
Responses were assessed using exploratory factor analysis to determine the factor structure and items to be retained. Cronbach’s Alpha was used to assess the reliability of individual items used in the analysis. A varimax orthogonal rotation assessed the underlying domains and reduced the number of items retained [25]. Eigenvalues were used to identify factors that account for most variance within the items. Variables with a factor loading of at least 0.4 and factors with an eigenvalue of at least one retained for item analysis [26]. HIV stigma index scores were constructed by adding the total number of factors of retained items. The index score was then calculated using the mean as the cut-off point to categorise scores into higher or lower [27]. This approach has been used in different contexts in several countries [28–32]. The respondents whose scores were above the mean were classified as having higher levels of HIV stigma, and respondents with scores below the mean were classified as having lower levels of HIV stigma. The dichotomised HIV index score was coded into a binary outcome measure of external HIV-related stigma (0 = lower levels of stigma and 1 = higher levels of stigma). Cronbach’s alpha coefficient for items used to measure higher external HIV-related stigma was 0.8.
Independent variables.
Explanatory variables included demographic factors were age groups in years (15–24, 25–49, 50 and above), sex (Male, Female), race groups (Black African, Other), marital status (Married, Never Married), educational level (No education/Primary, Secondary, Tertiary), employment status (Employed, Not employed), and locality type (Urban, Rural informal/Tribal areas, Rural/Farms). We also included HIV-related variables such as ever tested for HIV (Yes = tested for HIV, No = Never tested for HIV), awareness of HIV status (Yes = aware of HIV status, No = Not aware of HIV status), HIV status (Negative, Positive based in testing of survey sample), self-perception of the risk of HIV Infection (Low, High), and correct HIV knowledge and rejection of myths (Yes = correct knowledge, No = incorrect knowledge) based on the following questions: “AIDS can be cured; a person reduce the risk of HIV by having fewer sexual partners; a healthy-looking person can have HIV; a person gets HIV by sharing food with someone who is infected; a person reduce the risk of getting HIV by using a condom every time he/she has sex?”
Data analysis.
Data were weighted and benchmarked to the 2017 mid-year population in South Africa. All analyses were conducted using STATA 15.0 software (Stata Corporation, College Station, TX, United States). Descriptive statistics (frequencies and percentages) were used to summarise study characteristics and external HIV-related stigma. Pearson’s Chi-squared test assessed differences between categorical variables. Bivariate and multivariate generalised linear models with a log link and binomial distribution were used to estimate risk ratios (RR) for factors associated with high levels of external HIV-related stigma. All factors significantly associated with externalised HIV-related stigma in bivariate models (p-value less than 0.2) were entered into a multivariate model to evaluate the independent effect of these variables. In the final model, adjusted risk ratios (ARR) with 95% confidence intervals (CI) and a p-value < 0.05 were considered statistically significant.
Results
Sample characteristics
The study sample consisted of 38 919 participants (Table 1). Over half were aged 25–49 years (53.4%) and were males (51.7%). Most were Black African (79.2%), had completed secondary school education (66.8%), never married (68.0%), were unemployed (64.0%), and resided in urban areas (66.3%). The majority reported that they had tested for HIV (74%), were aware of HIV status (96.6%), were HIV negative (80.7%), had a low self-perceived risk of contracting HIV (83.4%), and had low correct HIV knowledge and myth rejection (63.7%).
Prevalence of external HIV-related stigma
Of 38 919 respondents, 49% (49.8%; 95% CI: 48.6–51.1) participants were categorised as having higher levels of external HIV-related stigma for our analysis. Table 2 shows higher levels of external HIV-related stigma by sample characteristics. The prevalence of higher levels of external HIV-related stigma were found among those aged 25–49 years, females, Black Africans, those who never married, those with secondary education, the employed, and those residing in rural informal/tribal areas. The prevalence of higher levels of external HIV-related stigma was also found among those who ever tested for HIV, those who were aware of their status, those who tested positive for HIV, those who perceived themselves as at high risk of HIV infection, and those with no correct HIV knowledge and myth rejection.
Factors associated with external HIV-related stigma
Bivariate logistic regression models.
Table 3 shows that higher levels of HIV-related stigma towards PLHIV were significantly more likely among those aged 24–49 years, females, Black Africans, those who never married, those with secondary and tertiary education levels, the employed, and those residing in rural informal/tribal areas. Higher levels of HIV-related stigma were significantly less likely among those who ever tested for HIV, those aware of HIV status, those who perceived themselves as at high risk of HIV infection, and those with correct HIV knowledge and myth rejection.
Multivariate logistic regression model.
Table 4 shows the final multivariate mode with adjusted risk ratios (ARR) for factors associated with higher levels of HIV-related stigma. Higher levels of HIV-related stigma were significantly associated with those who had secondary level education than those who had no education/primary education [ARR = 1.14 (95% CI: 1.05–1.24), p = 0.002], those who were employed than the unemployed [ARR = 1.08 (95% CI: 1.02–1.14), p = 0.006], those who resided in rural informal/tribal areas than those in urban areas [ARR = 1.15 (95% CI: 1.07–1.23), p<0.001]. Furthermore, higher levels of HIV-related stigma were significantly associated with who were not aware of their HIV status than those who were aware [ARR = 1.34 (95% CI: 1.12–1.61), p<0.00], those who were HIV positive than those who were HIV negative [ARR = 1.09 (95% CI: 1.02–1.17), p = 0.018] and with no correct HIV knowledge and myth rejection than their counterparts [ARR = 1.09 (95% CI: 1.03–1.15), p = 0.002].
Discussion
This nationally representative study examined the prevalence and factors associated with higher levels of HIV-related stigma among youth and adults 15 years and older. The results revealed that 50% of respondents were categorised as having had higher levels of external HIV-related stigma. The 2014 South African study on external HIV-related stigma reported a 38% prevalence among the adult population [7]. Similarly, in Ethiopia, the 2016 Demographic and Health Survey found a 36% prevalence of high levels of external HIV-related stigma [2]. Furthermore, a study conducted in 15 sub-Saharan African countries reported an overall prevalence of 47%, with the highest external HIV-related stigma of 79.8% reported in Malawi [33]. These observations show that in sub-Saharan Africa, external HIV-related stigma remains relatively high, and this has been attributed to a number of social, cultural and structural factors [33, 34].
In the current study, the prevalence of higher external HIV-related stigma varied by socio-demographic and HIV-related factors, as expected. The final model showed that those with secondary education were more likely to report higher levels of external HIV-related stigma than those with no education/primary education. On the contrary, others found that stigmatising attitudes were more likely among those with low levels of educational attainment [2, 6, 34]. In agreement with current findings, others showed that higher levels of HIV-related stigma were associated with post-primary education [35, 36]. While educational attainment may be an important source of information and knowledge, school may also be the most important social sphere related to HIV stigma, where youth experience HIV stigma related to their status [35]. This suggests a need for peer-facilitated HIV stigma reduction intervention targeting all types of educational institutions, including schools.
The model showed that being employed was associated with higher external HIV-related stigma. Others found that those who were unemployed reported more stigmatising attitudes towards PLHIV [36, 37], and this has been attributed to employment wellness programmes which provide HIV-related information towards reducing stigmatising attitudes in the workplace [37]. However, PLHIV Stigma Index data records on work-related stigma indicate that there has been little improvement since 2000 and that HIV-related stigma enacted by co-workers remains pervasive [38]. There is a need to continue to review and modify HIV programmes and interventions aimed at reducing work-based HIV-related stigma towards delivering supportive workplaces for PLHIV [38].
The final model also showed that higher levels of external HIV-related stigma were associated with residing in rural informal/tribal areas, and these findings are consistent with other studies [39, 40]. Evidence shows that HIV-related stigma in rural and tribal communities is influenced by sociocultural norms and power structures that associate HIV with immoral sexual behaviour [41, 42]. These observations underscore the need to consider sociocultural and structural factors in developing and implementing stigma-reducing interventions, especially in rural settings [41].
Furthermore, the model showed that higher levels of external HIV-related stigma were associated with awareness of HIV status. However, other studies found that those who tested and were, therefore, aware of their HIV status were less likely to endorse stigmatising attitudes towards PLHIV [37, 40]. In addition, the model showed that higher levels of external HIV-related stigma were associated with HIV-positive status. This suggests that external HIV-related stigma does not only emanate from the general population but may also arise from PLHIV towards not only themselves but their peers as well. This can be attributed to internalised or self-stigma wherein the external stigma becomes internalised [43], suggesting even stronger feelings about their HIV status or their peers who are living with HIV. A similar finding is reported in the study done in Morocco, wherein those who experienced external HIV-related stigma presented with higher internal stigma scores, alluding to an association between these two phenomena [44]. These observations emphasise the importance of empowering PLHIV to take the lead in advocacy activities against stigma.
Limitations
The items used to construct the external HIV-related stigma were based on self-report and may be affected by social desirability bias. The cross-sectional design makes it impossible to infer causation in any of the associations reported in this study. The measure of HIV-related stigma prevalence used in this analysis was limited to identifying higher levels of stigma above the mean score relative to lower levels below the mean, which may not allow for a suitable comparison with other measures of stigma. There may also be other unobserved and/or unmeasured factors that are associated with external HIV-related stigma that were not accounted for in the analysis. The modest but statistically significant findings reflect the strength of the observed relationship and represent a weak or small association. Nevertheless, this study provides insight into factors associated with the prevalence of HIV-related stigma and, therefore, contributes to the body of literature on this subject.
Conclusion
The findings revealed that the prevalence of higher external HIV-related stigma varied by selected socio-demographic and health-related factors. The findings suggest a need for peer-facilitated HIV stigma reduction intervention targeting all types of educational institutions, including schools, and a need to strengthen work-based interventions to provide a supportive environment for PLHIV. The findings also highlight the importance of prioritising rural areas and accounting for the sociocultural context when developing and implementing HIV stigma reduction interventions in rural settings. Based on the current findings, efforts to mitigate externalised stigma should involve addressing public misconceptions about HIV, and stigma reduction should be considered a vital component of HIV testing and awareness.
Supporting information
S1 Data. Data review URL.
http://dx.doi.org/doi:10.14749/1585345902.
https://doi.org/10.1371/journal.pone.0309694.s001
(DOCX)
Acknowledgments
The data used in this study was obtained from http://dx.doi.org/doi:10.14749/1517402043. We wish to thank the HSRC for the availability of the data free of charge.
References
- 1.
UNAIDS. The Gap report [Internet]. 2014. Available from: http://www.unaids.org/en/resources/campaigns/2014/2014gapreport/gapreport [cited 2020 Mar 11].
- 2. Feyasa MB, Gebre MN, Dadi TK. Levels of HIV/AIDS stigma and associated factors among sexually active Ethiopians: analysis of 2016 Ethiopian Demographic and Health Survey Data. BMC Public Health. 2022;22:1080. pmid:35641915
- 3. Letamo G, Letamo R. Prevalence of, and factors associated with HIV/AIDS-related stigma and discrimination attitudes in Botswana. J Health Popul Nutr. 2020;39(1):347–357.
- 4. Egbe TO, Nge CA, Ngouekam H, Asonganyi E. Stigmatization among People Living with HIV / AIDS at the Kumba Health. J Int Assoc Provid AIDS Care. 2020;19:1–7.
- 5. Sarkar T, Karmakar N, Dasgupta A, Saha B. Stigmatization and discrimination towards people living with HIV/AIDS attending the antiretroviral clinic in a centre of excellence in HIV care in India. Int J Community Med Public Health. 2019;6(3):1241–1246.
- 6. Zegeye B, Adjei NK, Ahinkorah BO, Ameyaw EK, Budu E, Seidu A, et al. Individual-, household-, and community-level factors associated with pregnant married women’s discriminatory attitude towards people living with HIV in sub-Saharan Africa: A multicountry cross-sectional study. Wiley Health Science Reports. 2021. pmid:34746443
- 7.
Mehlomakulu V. An assessment of external HIV-related stigma in South Africa: implications for interventions [dissertation]. Cape Town: University of Cape Town; 2021. Available from: https://open.uct.ac.za/handle/11427/33801
- 8. SANAC. The People Living With HIV Stigma Index: South Africa 2014 [Internet]. [cited 2018 Jan 4]. Available from: http://sanac.org.za/2015/12/01/the-people-living-with-hiv-stigma-index-south-africa-2014-summary-report/
- 9. Chambers LA, Rueda S, Baker DN, Wilson MG, Deutsch R, Raeifar E, et al. Stigma, HIV and health: A qualitative synthesis. BMC Public Health. 2015;15(1):848.
- 10. Seth P, Kidder D, Pals S, Parent J, Mbatia R, Chesang K, et al. Psychosocial functioning and depressive symptoms among HIV-positive persons receiving care and treatment in Kenya, Namibia, and Tanzania. Prev Sci. 2014;15(3):318–328. pmid:23868419
- 11. Logie CH, Lacombe-Duncan A, Wang Y, Kaida A, Conway T, Webster K, et al. Pathways from HIV-related stigma to antiretroviral therapy measures in the HIV care cascade for women living with HIV in Canada. J Acquir Immune Defic Syndr. 2018;77(2):144–153. pmid:29135650
- 12. Worede JB, Mekonnen AG, Aynalem S, Amare NS. Risky sexual behavior among people living with HIV/AIDS in Andabet district, Ethiopia: Using a model of unsafe sexual behavior. Front Public Health. 2022;10:1039755. pmid:36579063
- 13. Pulerwitz J, Michaelis A, Weiss E, Brown L, Mahendra V. Reducing HIV-related stigma: lessons learned from Horizons research and programs. Public Health Rep. 2010;125(2):272–281. pmid:20297756
- 14. Ajong AB, Njotang PN, Nghoniji NE, et al. Quantification and factors associated with HIV-related stigma among persons living with HIV/AIDS on antiretroviral therapy at the HIV-day care unit of the Bamenda Regional Hospital, North West Region of Cameroon. Global Health. 2018;14:56. pmid:29866206
- 15. Brown A. ’How did a white girl get AIDS?’ Shifting student perceptions on HIV-stigma and discrimination at a historically white South African university. South African Journal of Higher Education. 2016;30(4):94‒111.
- 16. Yang H, Li X, Stanton B, Fang X, Lin D, Naar-King S. HIV-related knowledge, stigma, and willingness to disclose: A mediation analysis. AIDS Care. 2006;18(7):717–724. pmid:16971280
- 17. Nabunya P, Byansi W, Sensoy Bahar O, McKay M, Ssewamala FM, Damulira C. Factors Associated With HIV Disclosure and HIV-Related Stigma Among Adolescents Living With HIV in Southwestern Uganda. Front Psychiatry. 2020;11:772. pmid:32848940
- 18. Vanable PA, Carey MP, Blair DC, Littlewood RA. Impact of HIV-related stigma on health behaviors and psychological adjustment among HIV-positive men and women. AIDS Behav. 2006 Sep;10(5):473–82. pmid:16604295
- 19. Mall S, Middelkoop K, Mark D, Wood R, Bekker LG. Changing patterns in HIV/AIDS stigma and uptake of voluntary counselling and testing services: the results of two consecutive community surveys conducted in the Western Cape, South Africa. AIDS Care. 2013;25(2):194–201. pmid:22694602
- 20. Sullivan MC, Rosen AO, Allen A, Benbella D, Camacho G, Cortopassi AC, et al. Falling Short of the First 90: HIV Stigma and HIV Testing Research in the 90–90–90 Era. AIDS Behav. 2020;24:357–362.
- 21. Khan R, Garman EC, Sorsdahl K. Perspectives on Self-Disclosure of HIV Status among HIV-Infected Adolescents in Harare, Zimbabwe: A Qualitative Study. J Child Fam Stud. 2023;32: 3775–3785.
- 22.
Simbayi LC, Zuma K, Zungu N, Moyo S, Marinda E, Jooste S, et al. South African National HIV Prevalence, Incidence, Behaviour and Communication Survey, 2017. Cape Town, South Africa: HSRC Press; 2019.
- 23.
Cloete A, Mabaso M, Maseko G, Jooste S, Mthembu J, Simbayi L, et al. Study Report: The People Living with HIV Stigma Index 2.0 in Six Districts of South Africa 2020–2021. Cape Town: Human Sciences Research Council; 2022.
- 24. Statistics South Africa. Mid-Year Population Estimates 2017. Pretoria, South Africa: Statistics South Africa; 2017.
- 25. Fabrigar L, Wegener D, MacCallum RSE. Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods. 1999;4(3):272–299.
- 26.
DeVellis RF. Scale Development: Theory and Applications (Applied Social Research Methods Series, Vol. 26). Newbury Park, CA: Sage Publications; 1991.
- 27. Ritsher JB, Otilingam PG, Grajales M. Internalized stigma of mental illness: psychometric properties of a new measure. Psychiatry Res. 2003 Nov 1;121(1):31–49. pmid:14572622
- 28. Barke A, Nyarko S, Klecha D. The stigma of mental illness in Southern Ghana: attitudes of the urban population and patients’ views. Soc Psychiatry Psychiatr Epidemiol. 2011;46(11):1191–202. pmid:20872212
- 29. Brohan E, Elgie R, Sartorius N, Thornicroft G. Group G-ES: Self-stigma, empowerment and perceived discrimination among people with schizophrenia in 14 European countries: the GAMIAN-Europe study. Schizophr Res. 2010;122(1–3):232–8.
- 30. Bifftu BB, Dachew BA. Perceived stigma and associated factors among people with schizophrenia at Amanuel Mental Specialized Hospital, Addis Ababa, Ethiopia: a cross-sectional institution based study. Psychiatry J. 2014;2014:694565. pmid:24967300
- 31. Datiko D.G., Jerene D. & Suarez P. Stigma matters in ending tuberculosis: Nationwide survey of stigma in Ethiopia. BMC Public Health 20, 190 (2020).
- 32. Lapham J, Martinson ML. The intersection of welfare stigma, state contexts and health among mothers receiving public assistance benefits. SSM Popul Health. 2022 May 9;18:101117. pmid:35620484
- 33. Teshale AB, Tesema GA. Discriminatory attitude towards people living with HIV/AIDS and its associated factors among adult population in 15 sub-Saharan African nations. PLoS ONE. 2022;17(2):e0261978. pmid:35120129
- 34. Ncitakalo N, Mabaso M, Joska J, Simbayi L. Factors associated with external HIV-related stigma and psychological distress among people living with HIV in South Africa. SSM—Population Health. 2021;14. pmid:34027011
- 35. Chory A, Nyandiko W, Martin R, Aluoch J, Scanlon M, Ashimosi C, et al. HIV-Related Knowledge, Attitudes, Behaviors and Experiences of Kenyan Adolescents Living with HIV Revealed in WhatsApp Group Chats. J Int Assoc Provid AIDS Care. 2021;20:1–11. pmid:33657911
- 36. Nyasulu PS, Tshuma N, Sigwadhi LN, Nyasulu J, Ogunrombi M, Chimoyi L. Factors associated with high HIV-related stigma among commuter populations in Johannesburg, South Africa. SAHARA-J: Journal of Social Aspects of HIV/AIDS. 2021;18(1):149–155.
- 37. Antabe R, Sano Y, Atuoye KN, Baada JN. Determinants of HIV-related stigma and discrimination in Malawi: evidence from the demographic and health survey. Afr Geogr Rev. 2022;42:594–606.
- 38. The Global Network of People Living with HIV. HIV Stigma and Discrimination in the World of Work: Findings from the People Living with HIV Stigma Index; 2018.
- 39. Iqbal S, Maqsood S, Zafar A, et al. Determinants of overall knowledge of and attitudes towards HIV/AIDS transmission among ever-married women in Pakistan: evidence from the Demographic and Health Survey 2012–13. BMC Public Health. 2019;19(1):793. pmid:31226969
- 40. Arefaynie M, Damtie Y, Kefale B, Yalew M. Predictors of Discrimination Towards People Living with HIV/AIDS Among People Aged 15–49 Years in Ethiopia: A Multilevel Analysis. HIV/AIDS (Auckland, NZ). 2021;13:283–292.
- 41. Akatukwasa C, Getahun M, El Ayadi AM, Namanya J, Maeri I, Itiakorit H, et al. Dimensions of HIV-related stigma in rural communities in Kenya and Uganda at the start of a large HIV ’test and treat’ trial. PLoS ONE. 2021;16(5):e0249462. pmid:33999961
- 42. Vlassoff C, Weiss MG, Rao S, Ali F, Prentice T. HIV-related stigma in rural and tribal communities of Maharashtra, India. J Health Popul Nutr. 2012;30(4):394–403. pmid:23304905
- 43. Turan B, Budhwani H, Fazeli PL, Browning WR, Raper JL, Mugavero MJ, et al. How does stigma affect people living with HIV? The mediating roles of internalized and anticipated HIV stigma in the effects of perceived community stigma on health and psychosocial outcomes. AIDS Behav. 2017;21(1):283–291. pmid:27272742
- 44. Moussa AB, Delabre RM, Villes V, et al. Determinants and effects or consequences of internal HIV-related stigma among people living with HIV in Morocco. BMC Public Health. 2021;21:163. pmid:33468093