Intersecting Stigmas among HIV-Positive People Who Inject Drugs in Vietnam.
Mai DoHien Thi HoHa Thu DinhHa Hai LeTruong Quang TienTrung Vu DangDuong Duc NguyenKatherine AndrinopoulosPublished in: Health services insights (2021)
HIV-related stigma remains a barrier to ART adherence among people living with HIV (PLWH) globally. People who inject drugs (PWID) may face additional stigma related to their behavior or identity; yet, there is little understanding of how these stigmas may co-exist and interact among these key populations. This study aims to explore the existence of multiple dimensions of HIV-related stigma, and how they may intersect with stigma related to drug injection. The study took place in Vietnam, where the HIV epidemic is concentrated among 3 key population groups; of those, PWID account for 41% of PLWH. The vast majority (95%) of PWID in Vietnam are male. Data came from in-depth interviews with 30 male PWID recruited from outpatient clinics, where they had been receiving ART medications. Deductive, thematic analysis was employed to organize stigma around the 3 dimensions: enacted, anticipated, and internalized stigma. Findings showed that HIV- and drug use-related stigma remained high among participants. All 3 stigma dimensions were prevalent and perceived to come from different sources: family, community, and health workers. Stigmas related to HIV and drug injection intersected among these individuals, and such intersection varied widely across types of stigma. The study revealed nuanced perceptions of stigma among this marginalized population. It is important for future studies to further investigate the influence of each dimension of stigma, and their interactive effects on HIV and behavioral outcomes among PWID.
Keyphrases
- hiv aids
- antiretroviral therapy
- hiv positive
- mental health
- hiv infected
- mental illness
- human immunodeficiency virus
- social support
- men who have sex with men
- hiv testing
- south africa
- drug induced
- healthcare
- hepatitis c virus
- single cell
- social media
- electronic health record
- emergency department
- physical activity
- health information
- insulin resistance
- risk assessment
- depressive symptoms
- drinking water
- primary care
- machine learning
- current status
- deep learning