Compliance with the “Baby‐friendly Hospital Initiative for Neonatal Wards” in 36 countries
Bibliographic record
Abstract
In 2012, the Baby-friendly Hospital Initiative for Neonatal Wards (Neo-BFHI) began providing recommendations to improve breastfeeding support for preterm and ill infants. This cross-sectional survey aimed to measure compliance on a global level with the Neo-BFHI's expanded Ten Steps to successful breastfeeding and three Guiding Principles in neonatal wards. In 2017, the Neo-BFHI Self-Assessment questionnaire was used in 15 languages to collect data from neonatal wards of all levels of care. Answers were summarized into compliance scores ranging from 0 to 100 at the ward, country, and international levels. A total of 917 neonatal wards from 36 low-, middle-, and high-income countries from all continents participated. The median international overall score was 77, and median country overall scores ranged from 52 to 91. Guiding Principle 1 (respect for mothers), Step 5 (breastfeeding initiation and support), and Step 6 (human milk use) had the highest scores, 100, 88, and 88, respectively. Step 3 (antenatal information) and Step 7 (rooming-in) had the lowest scores, 63 and 67, respectively. High-income countries had significantly higher scores for Guiding Principles 2 (family-centered care), Step 4 (skin-to-skin contact), and Step 5. Neonatal wards in hospitals ever-designated Baby-friendly had significantly higher scores than those never designated. Sixty percent of managers stated they would like to obtain Neo-BFHI designation. Currently, Neo-BFHI recommendations are partly implemented in many countries. The high number of participating wards indicates international readiness to expand Baby-friendly standards to neonatal settings. Hospitals and governments should increase their efforts to better support breastfeeding in neonatal wards.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".