Minority Stress, Psychological Distress, Sexual Compulsivity, and Avoidance-Based Motivations Associated with Methamphetamine Use Among Sexual Minority Men Living with HIV: Examining Direct and Indirect Associations Using Cross-Sectional Structural Equation Modeling
Bibliographic record
Abstract
Objective Sexual minority men (SMM) living with HIV report significantly greater methamphetamine use compared with heterosexual and HIV-negative peers. Greater use may be related to stressors (e.g., HIV-related stigma) faced by SMM living with HIV and subsequent psychological and behavioral sequelae. We tested an integrated theoretical model comprised of pathways between stigma, discrimination, childhood sexual abuse, psychological distress, sexual compulsivity, and cognitive escape in predicting methamphetamine use among SMM living with HIV.Methods Among 423 SMM living with HIV, we tested a structural equation model examining factors hypothesized to be directly and indirectly associated with methamphetamine use. Analyses were adjusted for demographic covariates and sampling bias.Results The model showed good fit (CFI = 0.96, RMSEA = 0.01). Heterosexist discrimination was associated with psychological distress (β = 0.39, p < 0.001) and psychological distress was associated with sexual compulsivity (β = 0.33, p < 0.001). Sexual compulsivity was associated with cognitive escape (β = 0.31, p < 0.001), which was associated with methamphetamine use (β = 0.51, p < 0.001). Psychological distress was associated with methamphetamine use via serial indirect effects of sexual compulsivity and cognitive escape (β = 0.05, p < 0.05).Conclusions Heterosexist discrimination contributed to psychological distress among SMM living with HIV. Psychological distress is linked to methamphetamine use via sexual compulsivity and cognitive avoidance. Interventions seeking to reduce the likelihood that SMM living with HIV use methamphetamine should include coping strategies specific to heterosexism and related psychological distress.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".