A Systematic Review of the Relationships between Intimate Partner Violence and HIV/AIDS
Bibliographic record
Abstract
BACKGROUND: Intimate partner violence (IPV) is a significant health problem that has been associated with HIV infection in numerous studies. We aimed to systematically review the literature on relationships between IPV and HIV in order to describe the prevalence of IPV in people with HIV, the prevalence of HIV in people experiencing IPV, the association between IPV and HIV, and evidence regarding mechanisms of risk and interventions. METHODS: Data sources were 10 electronic databases and reference lists. Studies were included if they reported data on the relationship between IPV and HIV. All records were independently reviewed by two authors at the stages of title and abstract review and full text review. Any abstract considered eligible by either reviewer was reviewed in full, and any disagreement regarding eligibility of full texts or data extracted was resolved by discussion. RESULTS: 101 articles were included. Experiencing IPV and HIV infection were associated in unadjusted analyses in most studies, as well as in adjusted analyses in many studies. The findings of qualitative and quantitative studies assessing potential mechanisms linking IPV and HIV were variable. Few interventions have been assessed, but two identified in this review were promising in terms of preventing IPV, though not HIV infection. CONCLUSIONS: Experiencing IPV and HIV infection tend to be associated in unadjusted analyses, suggesting that IPV screening and linkage with relevant programs and services may be valuable. It is unclear whether there is a causal association between experiencing IPV and HIV infection. Research should focus on defining parameters of IPV which are relevant to HIV infection, including type of IPV and period of exposure and risk, on assessing potential mechanisms, and on developing and assessing interventions which build on the strengths of existing studies.
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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 | 0.015 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.024 | 0.026 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".