Gender differences in the association between childhood sexual abuse and risky sexual behaviours: A systematic review and meta-analysis
Bibliographic record
Abstract
This meta-analytic review examines the association between childhood sexual abuse and risky sexual behaviours with sub-group analyses by gender. Systematic searches of electronic databases including MEDLINE, PubMed, EMBASE, and PsycINFO were performed using key terms. We used a priori criteria to include high quality studies and control for heterogeneities across eligible studies. The review was registered with PROSPERO and used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The final meta-analysis applied fixed-effects model to generate pooled odds ratio (OR). Subgroup analyses were conducted to identify potential methodological moderators. The meta-analysis included 8 eligible studies (N=38,989, females=53.1%). The overall syndemic of risky sexual behaviors at adulthood was 1.59 times more common in childhood sexual abuse victims. There was a similar association between childhood sexual abuse in general and subsequent risky sexual behaviors in both females and males. However, in cases of substantiated childhood sexual abuse, there was a greater odds of risky sexual behaviors in females (OR=2.72) than males (OR=1.69). The magnitude of association of childhood sexual abuse and risky sexual behaviors was similar for males and females regardless of study time, study quality score and method of childhood sexual abuse measurement. There were nonsignificant overall and subgroup differences between males and females. Childhood sexual abuse is a significant risk factor for a syndemic of risky sexual behaviors and the magnitude is similar both in females and males. More research is needed to explore possible mechanisms of association.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.023 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".