Adverse childhood experiences and intimate partner violence: A meta-analysis
Bibliographic record
Abstract
Intimate partner violence (IPV) represents a significant public health concern. Adverse childhood experiences (ACEs) represent one risk factor for IPV, however, the results of existing research on the association between ACEs and IPV demonstrate mixed findings. The present research sought to meta-analytically examine the association between ACEs and (a) IPV perpetration and (b) IPV victimization. Moderator analyses were conducted to determine factors that may impact the association between ACEs and IPV involvement. Electronic searches were conducted in MEDLINE, Embase, and PsycINFO in August of 2021. One-hundred and twenty-three records were screened for inclusion. All studies included a measure of ACEs and IPV victimization or perpetration. Among the 27 studies and 41 samples included in the meta-analysis, 65,330 participants were included. The results of the meta-analyses demonstrated that ACEs were positively associated with IPV perpetration and victimization. Significant methodological and measurement moderators further inform our understanding of ACEs and IPV involvement. The present meta-analyses demonstrates that trauma-informed approaches to IPV screening, prevention, and intervention may be useful, given that individuals who are involved with IPV may be more likely to possess a history of ACEs exposure.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.052 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".