Understanding the Intersections of IPV and HIV and Their Impact on Infant Feeding Practices: A Narrative Literature Review
Bibliographic record
Abstract
Intimate partner violence (IPV), particularly sexual and emotional violence, against Black mothers who acquire human immunodeficiency virus (HIV) during childbearing age is a significant health and social concern worldwide requiring targeted interventions and precautions. IPV against women increases the chances of early mixed feeding, putting infants at high risk of mother-to-child transmission of HIV and increased infant morbidities. Although violence complicates many Black mothers’ lives, there is limited research evidence about the critical intersections of violence, HIV, and Black motherhood. Women's fears associated with IPV make them less likely to disclose their positive HIV status to their partners which subsequently prevents them from using the recommended guidelines for safe infant feeding practices. This review aims to explore the critical intersections between IPV and HIV and the impact of both on the infant feeding practices of Black mothers living with HIV. Furthermore, the theme of IPV and how it overlaps with other factors such as HIV-positive status and gender dynamics to compromise the Black motherhood experience are the focus of this narrative review of existing literature. Understanding the intersection of IPV and other factors influencing infant feeding practices among women living with HIV will help inform programming and policy interventions for HIV-positive Black mothers who may be experiencing IPV during the perinatal period.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".