Prevalence and correlates of physical and sexual intimate partner violence among women living with HIV in Uganda
Bibliographic record
Abstract
BACKGROUND: Intimate partner violence (IPV) is a significant global health problem. Women who experience IPV have increased HIV incidence, reduced antiretroviral adherence, and a lower likelihood of viral load suppression. There is a lack of evidence regarding how to effectively identify and support women living with HIV (WLWH) experiencing IPV, including uncertainty whether universal or targeted screening is most appropriate for lower-resourced settings. We examined physical and sexual IPV prevalence and correlates among WLWH in Uganda to understand the burden of IPV and factors that could help identify women at risk. METHODS: We utilized data from women receiving ART and enrolled in the Uganda AIDS Rural Treatment Outcomes (UARTO) cohort study between 2011 and 2015. Bloodwork and interviewer-administered questionnaires were completed every 4 months. IPV was assessed annually or with any new pregnancy. Multivariate models assessed independent socio-demographic and clinical factors correlated with IPV, at baseline and follow-up visits. RESULTS: 455 WLWH were included. Median age was 36 years, 43% were married, and median follow-up was 2.8 years. At baseline 131 women (29%) reported any experience of past or current IPV. In the adjusted models, being married was associated with a higher risk of baseline IPV (ARR 2.33, 95% CI 1.13-4.81) and follow-up IPV (ARR 2.43, 95% CI 1.33-4.45). Older age (ARR 0.96, 95% CI 0.94-0.99) and higher household asset index score (ARR 0.81, 95% CI 0.68-0.96) were associated with lower risk of IPV during follow-up. CONCLUSION: There was a high prevalence of physical and sexual IPV amongst WLWH, and many women experienced both types of violence. These findings suggest the need for clinic-based screening for IPV. If universal screening is not feasible, correlates of having experienced IPV can inform targeted approaches.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".