Intimate Partner Violence and Health Outcomes Among Women Living With HIV/AIDS in Ghana: A Cross-Sectional Study
Bibliographic record
Abstract
Intimate partner violence (IPV) is known to have negative health consequences for victims. For women living with HIV/AIDS, whose health may be compromised, exposure to IPV can be devastating. Yet few (if any) studies have explored the health implications of exposure to IPV among HIV-positive women. We begin to fill this gap by examining the effects of various dimensions of IPV (physical, sexual, psychological/emotional, and economic) on the cardiovascular, psychosocial, and sexual reproductive health outcomes of HIV-positive women in Ghana. Data were collected from a cross-section of 538 HIV-positive women aged 18 years and older in the Lower Manya Krobo District in the Eastern Region. We used logit models to explore relationships between IPV and health. The findings indicate high prevalence of IPV in our sample: physical violence (61%), sexual violence (50.9%), emotional/psychological violence (79.6%), and economic violence (66.8%). Generally, participants with experiences of IPV reported cardiovascular health problems, unwanted pregnancies and pregnancy loss, and poor psychosocial health. Our findings suggest the importance of screening for IPV as part of HIV care in Ghana.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".