Associations between sexual assault and suicidal thoughts and behavior: A meta-analysis.
Bibliographic record
Abstract
OBJECTIVE: The goal of the present study was to conduct a quantitative review to determine the degree to which specific forms of suicidality (i.e., lifetime and past-year suicidal ideation and attempts) are associated with sexual assault (SA). It also examined whether the strength of the association between SA and suicidality was moderated by sample characteristics or the type of suicidality assessed. METHOD: A subset of studies (25 samples and 36 effects, reflecting N = 88,376 participants) from a prior meta-analysis assessing associations between SA and psychopathology was examined. Included studies provided the prevalence of suicidality in subsamples that had and had not been exposed to SA and/or an odds ratio comparing the prevalence in these groups. Random effects metaregression models aggregated prevalence estimates and odds ratios for lifetime and past-year suicidal ideation and suicide attempts in individuals in SA and no-SA groups. Analyses also examined whether sample characteristics (i.e., percent women, college sample) or type of suicidality moderated the magnitude of odds ratios. RESULTS: Subsamples exposed to SA reported a substantially higher prevalence of suicidality (27.25%) compared with unassaulted subsamples (9.37%). There were significantly higher rates of lifetime and past-year suicidal ideation, and lifetime suicide attempts in assaulted subsamples than in unassaulted subsamples. No tested moderators had significant associations with the strength of the relationship between SA and suicidality. CONCLUSION: Findings underscore the robust relationship between SA and both suicidal ideation and attempts and suggest that identifying moderators and mediators that explain it is a key directive for future research. (PsycInfo Database Record (c) 2022 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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.027 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".