Healthcare worker perspectives on mother’s insufficient milk supply in Malawi
Bibliographic record
Abstract
BACKGROUND: Human milk insufficiency is a significant barrier to implementing breastfeeding, and it is identified as a prevalent concern in 60-90% of mothers in low-and-middle-income countries. Breastmilk insufficiency can lead to hypoglycemia, hypernatremia, nutritional deficiencies, and failure to thrive in newborns and infants. Studies investigating the impact of breastfeeding interventions to improve milk production highlight inconsistencies between healthcare workers and mothers perceived support, as well as gaps in practical knowledge and training. The aim of this study was to determine perceptions surrounding human milk insufficiency from Malawian healthcare workers. METHODS: This study is a secondary analysis of 39 interviews with healthcare workers from one tertiary and three district hospitals in Malawi employing content analysis. Interviewed healthcare workers included nurses, clinical officers, midwives, and medical doctors. An inclusive coding framework was developed to identify themes related to human milk insufficiency, which were analyzed using an iterative process with NVivo12 software. Researchers focused on themes emerging from perceptions and reasons given by healthcare workers for human milk insufficiency. RESULTS: Inability to produce adequate breastmilk was identified as a prevalent obstacle mothers face in the early postpartum period in both district and tertiary facilities in Malawi. The main reasons given by participants for human milk insufficiency were mothers' perceived normalcy of milk insufficiency, maternal stress, maternal malnutrition, and traditional beliefs around food and eating. Three focused solutions were offered by participants to improve mother's milk production - improving education for mothers and training for healthcare providers on interventions to improve mother's milk production, increasing breastfeeding frequency, and ensuring adequate maternal nutrition pre- and post-partum. CONCLUSION: Health care workers perspectives shed light on the complexity of causes and solutions for human milk insufficiency in Malawi. This research highlights that a respectful professional relationship between health care workers and mothers is an essential bridge to improving communication, detecting human milk insufficiency early, and implementing appropriate interventions. The results of this study may help to inform research, clinical practice, and education in Malawi to improve human milk production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".