Childhood sexual abuse in boys and men: The case for gender-sensitive interventions.
Bibliographic record
Abstract
OBJECTIVE: To review the literature on the experiences of boys and men exposed to childhood sexual abuse, and to assess the implications of this literature for trials of interventions and tailored services for this population. METHOD: We conducted a narrative review of papers pertaining to boys and men exposed to childhood sexual abuse. Implications of this literature for treatment were critically appraised. RESULTS: Boys and men suffer the negative sequelae of childhood sexual abuse to the same (and sometimes greater) extent as girls and women. Boys and men also experience a number of unique challenges, as the abuse experience may undermine masculine identities and relations. This conflict may contribute to the underreporting of childhood sexual abuse among boys and men. Boys and men are less likely to disclose their abuse experience and wait longer to disclose compared to girls and women. Existing estimates therefore likely underestimate the prevalence of childhood sexual abuse among boys and men. Additionally, to date, intervention trials for individuals exposed to childhood sexual abuse have included a disproportionately low number of boys and men, even based on existing prevalence estimates. CONCLUSIONS: Further investigation into the treatment needs of boys and men exposed to childhood sexual abuse is critically important. To facilitate a better understanding of their needs, intervention studies for this cohort should include a greater proportion of boys and men. Studies should also assess the influence of boys' and men's alignments to masculine norms for moderating treatment outcomes as a means to guide gender-sensitive treatments. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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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 | 0.041 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 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".