Health effects associated with exposure to intimate partner violence against women and childhood sexual abuse: a Burden of Proof study
Bibliographic record
Abstract
The health impacts of intimate partner violence against women and childhood sexual abuse are not fully understood. Here we conducted a systematic review by comprehensively searching seven electronic databases for literature on intimate partner violence-associated and childhood sexual abuse-associated health effects. Following the burden of proof methodology, we evaluated the evidence strength linking intimate partner violence and/or childhood sexual abuse to health outcomes supported by at least three studies. Results indicated a moderate association of intimate partner violence with major depressive disorder and with maternal abortion and miscarriage (63% and 35% increased risk, respectively). HIV/AIDS, anxiety disorders and self-harm exhibited weak associations with intimate partner violence. Fifteen outcomes were evaluated for their relationship to childhood sexual abuse, which was shown to be moderately associated with alcohol use disorders and with self-harm (45% and 35% increased risk, respectively). Associations between childhood sexual abuse and 11 additional health outcomes, such as asthma and type 2 diabetes mellitus, were found to be weak. Although our understanding remains limited by data scarcity, these health impacts are larger in magnitude and more extensive than previously reported. Renewed efforts on violence prevention and evidence-based approaches that promote healing and ensure access to care are necessary.
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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 | 0.040 | 0.164 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".