Attention-deficit/hyperactivity disorder as a risk factor for being involved in intimate partner violence and sexual violence: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Intimate partner violence (IPV) and sexual violence (SV) are significant problems world-wide, and they affect women disproportionally. Whether individuals with attention-deficit/hyperactivity disorder (ADHD) are at an increased risk of being involved in these types of violence is unclear. METHODS: We carried out a systematic review and meta-analysis (PROSPERO registration CRD42022348165) of the associations between ADHD and being the victim or perpetrator of IPV and SV. Ratios of occurrence of violence were pooled in random-effects models and study risk of bias was evaluated using the Newcastle-Ottawa Scale. RESULTS: A search on multiple databases, carried out on 7 October 2022, yielded 14 eligible studies (1 111 557 individuals). Analyses showed a higher risk of ADHD individuals being involved in IPV as perpetrators (six studies, OR 2.5, 95% CI 1.51-4.15) or victims (four studies, OR 1.78, 95% CI 1.06-3.0). Likewise, individuals with ADHD were at increased risk of being perpetrators (three studies, OR 2.73, 95% CI 1.35-5.51) or victims of SV (six studies, OR 1.84, 95% CI 1.51-2.24). Results were overall robust to different analytical choices. CONCLUSIONS: Individuals with ADHD are at an increased risk of being involved in cases of violence, namely IPV and SV, either as victims or perpetrators. Although the causal path or mediating variables for these results are still unclear, this increased risk should inform evidence-based psychoeducation with individuals with ADHD, their families, and partners about romantic relationships and sexuality.
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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 | 0.012 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.036 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 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".