Elevated Risky Sexual Behaviors Among Sexual Minority Girls: Indirect Risk Pathways Through Peer Victimization and Heavy Drinking
Bibliographic record
Abstract
Sexual minority girls (SMGs), compared with heterosexual females, are more likely to report negative sexual outcomes including earlier age of sexual intercourse debut, more lifetime and recent sexual partners, pregnancy involvement, and sex while intoxicated. Data describing the mechanisms related to these health disparities are limited. The purpose of this study was therefore to longitudinally assess the roles of sexual minority-related peer victimization and heavy episodic drinking (HED) as mediators of the relation between sexual minority status and sexual outcomes. The girls examined in this study were recruited into a longitudinal study of adolescent health from two large, urban adolescent medicine clinics affiliated with academic medical centers. The final sample for this analysis included 79 SMGs and a comparison group of 127 heterosexual girls aged between 14 and 19 years. Mediation models were run in the structural equation modeling framework. Our results provided evidence to support a serial multiple mediation pathway. SMGs were more likely to report sexual minority-related victimization, and sexual minority-related victimization predicted increased HED, which was subsequently found to prospectively predict increased sexual risk behaviors. Taken together, these novel findings indicate that both sexual minority-related victimization and HED may play important roles in explaining disparities in risky sexual behavior among SMGs.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".