Modeling the Impact of Race, Socioeconomic Status, Discrimination and Cognitive Appraisal on Mental Health Concerns Among Heavy Drinking HIV+ Cisgender MSM.
David G ZelayaArryn A GuyAnthony SuraceNadine R MastroleoDavid W PantalonePeter M MontiKenneth H MayerChristopher W KahlerPublished in: AIDS and behavior (2022)
Prior research has attributed mental health disparities between marginalized and non-marginalized populations to socioeconomic differences (i.e., education, income, employment), stigma (e.g., HIV-related discrimination), and cognitive appraisal (i.e., optimism, hostility, satisfaction with life), but the relations among these variables have not been examined concomitantly. The current study utilized structural equation modeling to examine how race and socioeconomic status impact mental health outcomes through increased exposure to stigma and more negative cognitive appraisals. Data came from a randomized controlled trial of motivational interviewing to address heavy drinking in cisgender men with HIV who have sex with men (n = 180). We found that self-reported discrimination experiences related to race/ethnicity, sexual orientation, and HIV status significantly mediated the relation between socioeconomic status and mental health concerns, whereas cognitive appraisal did not. These findings suggest that, among heavy drinking men with HIV who have sex with men, having low socioeconomic resources may increase exposure to discrimination which, in turn, may worsen mental health. Interventions that address social determinants, like socioeconomic disadvantage, and that enhance coping resources related to stigma, may have positive effects on mental health.ClinicalTrials.gov Identifier NCT01328743. Date of Registration 09/09/2019.
Keyphrases
- mental health
- antiretroviral therapy
- hiv testing
- hiv positive
- mental illness
- hiv infected
- hiv aids
- human immunodeficiency virus
- men who have sex with men
- hepatitis c virus
- middle aged
- healthcare
- physical activity
- alcohol consumption
- social support
- machine learning
- fluorescent probe
- deep learning
- living cells
- health insurance
- affordable care act