Pooled analysis of the association between mental health and violence against women: evidence from five settings in the Global South
Bibliographic record
Abstract
OBJECTIVES: To describe associations between men's poor mental health (depressive and post-traumatic stress symptomatology) and their perpetration of intimate partner violence (IPV) and non-partner sexual violence (NPSV), and women's mental health and their experiences of IPV and NPSV in five settings in the Global South. DESIGN: A pooled analysis of data from baseline interviews with men and women participating in five violence against women and girls prevention intervention evaluations. SETTING: Three sub-Saharan African countries (South Africa, Ghana and Rwanda), and one Middle Eastern country, the occupied Palestinian territories. PARTICIPANTS: 7021 men and 4525 women 18+ years old from a mix of self-selecting and randomly selected household surveys. MAIN OUTCOME MEASURES: All studies measured depression symptomatology using the Centre for Epidemiological Studies-Depression, and the Harvard Trauma Scale for post-traumatic stress disorder (PTSD) symptoms among men and women. IPV and NPSV were measured using items from modified WHO women's health and domestic violence and a UN multicountry study to assess perpetration among men, and experience among women. FINDINGS: Overall men's poor mental health was associated with increased odds of perpetrating physical IPV and NPSV. Specifically, men who had more depressive symptoms had increased odds of reporting IPV (adjusted OR (aOR)=2.13; 95%CI 1.58 to 2.87) and NPSV (aOR=1.62; 95% CI 0.97 to 2.71) perpetration compared with those with fewer symptoms. Men reporting PTSD had higher odds of reporting IPV (aOR=1.87; 95% CI 1.44 to 2.43) and NPSV (aOR=2.13; 95% CI 1.49 to 3.05) perpetration compared with those without PTSD. Women who had experienced IPV (aOR=2.53; 95% CI 2.18 to 2.94) and NPSV (aOR=2.65; 95% CI 2.02 to 3.46) had increased odds of experiencing depressive symptoms compared with those who had not. CONCLUSIONS: Interventions aimed at preventing IPV and NPSV perpetration and experience must account for the mental health of men as a risk factor, and women's experience.
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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 | 0.027 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.015 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| 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".