Incarceration and Sexual Risk Behavior and Incident Sexually Transmitted Infection/HIV in HIV Prevention Trials Network 061: Differences by Study City and Among Black Sexual Minority Men Who Have Sex With Men, Black Sexual Minority Men Who Have Sex With Men and Women, and Black Transgender Women
Bibliographic record
Abstract
BACKGROUND: Black sexual minority men (BSMM) and Black transgender women face a disproportionate risk of incarceration and sexually transmitted infection (STI)/HIV, yet research on the longitudinal association between incarceration and STI/HIV risk in these groups is limited. METHODS: We used data from the HIV Prevention Trials Network (HPTN) 061 study conducted among BSMM and Black transgender women in Atlanta, Boston, Los Angeles, New York City, San Francisco, and Washington, DC, restricting analyses to those who returned for the 6-month follow-up visit when recent incarceration was measured (n = 1169). Using inverse probability of treatment weighting, we measured associations between incarceration and next 6-month multiple partnerships; selling or buying sex; condomless anal intercourse; and incident chlamydia, gonorrhea, syphilis, and HIV. We explored differences by study city, and among BSMM who had sex with men only, BSMM who had sex with men and women, and Black transgender women. RESULTS: Approximately 14% reported past 6-month incarceration. Incarceration was associated with next 6-month selling sex (adjusted risk ratio [ARR], 1.80; 95% confidence interval [CI], 1.12-2.87) in the overall sample and multiple partnerships among BSMM who had sex with men and women (ARR, 1.34; 95% CI, 1.10-1.63) and transgender women (ARR, 1.77; 95% CI, 1.22-2.57). There is evidence suggesting that incarceration may predict gonorrhea (ARR, 2.35; 95% CI, 0.95-5.77), with particularly strong associations observed in Los Angeles (ARR, 6.48; 95% CI, 1.48-28.38). CONCLUSIONS: Incarceration may increase STI/HIV risk among BSMM and Black transgender women. Additional mixed-methods research is needed to validate associations and understand pathways.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".