Infant malnutrition treatment in Kenya: Health worker and breastfeeding peer supporter experiences
Bibliographic record
Abstract
Acute malnutrition in infants under 6 months (u6m) is increasingly recognised as a global public health problem. The World Health Organisation (WHO) guidelines for inpatient nutritional rehabilitation of infants u6m is re-lactation: the re-establishment of exclusive breastfeeding. Evidence suggests these guidelines are rarely followed in many low-income settings. Two studies of infant nutritional rehabilitation undertaken in three public hospitals in coastal Kenya employed breastfeeding peer supporters (BFPSs) to facilitate WHO guideline implementation. To explore the acceptability of the strategy to health workers (HWs) and the BFPSs, in-depth interviews were conducted with 20 HWs and five BFPSs in the three study hospitals. The HWs reported that the presence of the BFPSs changed the way infant nutritional rehabilitation was managed, increasing efforts at relactation and decreasing reliance on supplemental milk. BFPSs were said to help address staff shortages and had dedicated time to support and assist the mothers. Key to the success of the BFPSs was the social relationships they were able to establish with the mothers due to the similarity in their experiences and backgrounds. Despite the success of the BFPSs, human resource management and infrastructure challenges remained. BFPSs can successfully be employed to facilitate the implementation of the WHO guidelines for the nutritional rehabilitation of acutely malnourished infants u6m in hospitals in Kenya, establishing supportive social relationships and trust with the mothers of the acutely malnourished infants and helping to address the issue of human resource shortages.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".