A short screen for lifetime sexual victimization experiences: Expanding research on the Sexual Abuse History Questionnaire (SAHQ) across cultures, genders, and sexual identities
Bibliographic record
Abstract
The Sexual Abuse History Questionnaire (SAHQ), a widely used screening tool for childhood sexual abuse (CSA) and adolescent/adult sexual assault (AASA) experiences, has limited examination of its psychometric properties in diverse populations. Our study assessed the SAHQ's psychometric properties (i.e., structural validity and measurement invariance across demographic groups, know-group validity, and internal consistency) and estimated the frequencies of various types of sexual victimization across 42 countries and in diverse gender-, trans-status-, and sexual-identity-based groups that were previously missing from measurement-focused studies. We used a large, non-representative sample ( N = 81,465; 57 % women, 3.4 % gender-diverse individuals, M age =32.34 years, SD =12.48) from the International Sex Survey, a 42-country cross-sectional, multi-language, online survey. The SAHQ demonstrated excellent structural validity in all country-, gender-, sexual-identity-, and trans-status-based groups, as well as acceptable reliability and known-group validity. Occurrence estimates for six CSA and AASA types were reported across sociodemographic groups, corroborating previous evidence that women and gender- and sexual-minority individuals are at greater risk of CSA and AASA. Pansexual and queer individuals emerged as a particularly vulnerable group. Associations between different types of CSA and AASA revealed that participants who experienced any form of CSA were at least twice as likely to experience AASA. The findings have significant implications for policy and interventions, especially for marginalized groups.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".