Sexual abuse and mental ill health in boys and men: what we do and don't know
Bibliographic record
Abstract
Summary The spectrum of adverse mental health trajectories caused by sexual abuse, broadly defined as exposure to rape and unwanted physical sexual contact, is well-known. Few studies have systematically appraised the epidemiology and impact of sexual abuse among boys and men. New meta-analytic insights (k = 44; n = 45 172) reported by Zarchev and colleagues challenge assumptions that men experiencing mental ill health rarely report sexual abuse exposure. Adult-onset sexual abuse rates of 1–7% are observed in the general population, but for men experiencing mental ill health, adult lifetime prevalence was 14.1% (95% CI 7.3–22.4%), with past-year exposure 5.3% (95% CI 1.6–12.8%). We note that these rates are certainly underestimates, as childhood sexual abuse exposures were excluded. Boys and men with a sexual abuse history experience substantial disclosure and treatment barriers. We draw attention to population health gains that could be achieved via implementation of gender-sensitive assessment and intervention approaches for this at-risk population.
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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 | 0.023 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".