Sociocultural factors influencing infant-feeding choices among African immigrant women living with HIV: A synthesis of the literature
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The World Health Organizations (WHO) strategy is to eliminate pediatric HIV. HIV prevention guidelines in high-income countries recommend mothers living with HIV avoid breastfeeding. Yet, breastfeeding is promoted as the normal and unequalled method of feeding infants. This creates a paradox for mothers coming from cultures where breastfeeding is an expectation and formula feeding suggests illness. Therefore, the purpose of this literature review is to examine the context influencing infant feeding among African immigrant women living with HIV to develop interventions to reduce the risk of HIV mother-to-child transmission. METHODS: Using the PEN-3 cultural model as a guide, we selected 45 empirical studies between 2001 and 2016 using 5 electronic databases on the sociocultural factors influencing infant-feeding choices and practices among African women from HIV endemic countries. CONCLUSIONS: Findings are congruent with the importance of culture when developing guidelines. Our review provides support that culture-centered interventions are crucial toward achieving the WHO's strategy to eliminate pediatric HIV. IMPLICATIONS FOR PRACTICE: Understanding the sociocultural determinants of infant-feeding choices is critical to the development of prevention initiatives to eliminate pediatric HIV.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".