Depressive symptoms and problematic alcohol and other substance use in 1476 gay, bisexual, and other MSM at three research sites in Kenya
Bibliographic record
Abstract
OBJECTIVE: Information on mental health and substance use challenges among gay, bisexual, and other MSM (GBMSM) is needed to focus resources on these issues and optimize services for HIV prevention and care. We determined factors associated with depressive symptoms and problematic alcohol and other substance use among GBMSM in Kenya. METHODS: Self-identified GBMSM in three HIV research studies in Kenya provided information on depressive symptoms [Patient Health Questionnaire 9 (PHQ-9)], alcohol use [Alcohol Use Disorder Identification Test (AUDIT)], and other substance use [Drug Abuse Screening Test 6 (DAST-6)]. Associations were evaluated using mixed effects Poisson regression. RESULTS: Of 1476 participants, 452 (31%) reported moderate-to-severe depressive symptoms (PHQ-9 ≥ 10), 637 (44%) hazardous alcohol use (AUDIT ≥ 8), and 749 (51%) problematic substance use (DAST-6 ≥ 1). Known HIV-positive status was not associated with these outcomes. Transactional sex was associated with hazardous alcohol use [adjusted prevalence ratio (aPR) 1.34, 95% confidence interval (CI) 1.12-1.60]. Childhood abuse and recent trauma were associated with moderate-to-severe depressive symptoms (aPR 1.43, 95% CI 1.10-1.86 and aPR 2.43, 95% CI 1.91-3.09, respectively), hazardous alcohol use (aPR 1.36, 95% CI 1.10-1.68 and aPR 1.60, 95% CI 1.33-1.93, respectively), and problematic substance use (aPR 1.32, 95% CI 1.09-1.60 and aPR 1.35, 95% CI 1.14-1.59, respectively). CONCLUSION: GBMSM in rights-constrained settings need culturally appropriate services for treatment and prevention of mental health and substance use disorders, in addition to human rights advocacy to prevent abuse. Mental health and substance use screening and treatment or referral should be an integral part of programs, including HIV prevention and treatment programs, providing services to GBMSM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".