Informing Interventions: The Importance of Contextual Factors in the Prediction of Sexual Risk Behaviors among Transgender Women
Bibliographic record
Abstract
This study identifies contextual factors that predict risky sexual behavior among 153 transgender women who participated in a structured survey soliciting information on demographics, substance use, HIV status, risk behaviors, and other health and psychosocial factors. Multivariate logistic regression models were used to determine predictors. Inconsistent condom use was associated with stimulant use, unstable housing, and recruitment site. Substance use during sex was associated with unstable housing and stimulant use. Sex work was associated with hormone use, gender confirming surgeries, and younger age. When developing interventions for transgender women, it may be useful to focus on predictors of risk behavior rather than predictors of current HIV status (i.e., race/ethnicity as "risk factor"), because these behaviors are the target of interventions aimed at sexual risk reduction. Implications include potential benefits of context-specific interventions, structural interventions addressing barriers to housing and health care, and culturally specific substance abuse treatment programs for transgender women.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".