HIV-related stigma and optimism as predictors of anxiety and depression among HIV-positive men who have sex with men in the United Kingdom and Ireland.
Patrick J MurphyHelena Hernansaiz-GarridoFiona MulcahyDavid HeveyPublished in: AIDS care (2018)
This study investigated the associations between forms of HIV-related optimism, HIV-related stigma, and anxiety and depression among HIV-positive men who have sex with men (MSM) in the United Kingdom and Ireland. HIV health optimism (HHO) and HIV transmission optimism (HTO) were hypothesised to be protective factors for anxiety and depression, while the components of HIV-related stigma (enacted stigma, disclosure concerns, concern with public attitudes, and internalised stigma) were hypothesised to be risk factors. Data were collected from 278 HIV-positive MSM using an online questionnaire. The prevalence of psychological distress was high, with close to half (48.9%) of all participants reporting symptoms of anxiety, and more than half (57.9%) reporting symptoms of depression. Multiple linear regressions revealed that both anxiety and depression were positively predicted by internalised stigma and enacted stigma, and negatively predicted by HHO. For both anxiety and depression, internalised stigma was the strongest and most significant predictor. The results highlight the continued psychological burden associated with HIV infection among MSM, even as community support services are being defunded across the United Kingdom and Ireland. The results point to the need for clinicians and policy makers to implement stigma reduction interventions among this population.
Keyphrases
- hiv positive
- men who have sex with men
- mental health
- hiv testing
- hiv aids
- antiretroviral therapy
- mental illness
- social support
- hiv infected
- healthcare
- human immunodeficiency virus
- risk factors
- south africa
- depressive symptoms
- public health
- sleep quality
- cross sectional
- emergency department
- primary care
- machine learning
- palliative care
- high resolution
- health information
- high speed
- deep learning