Are trained delivery assistants better than non-trained personnel in practicing essential newborn care in home deliveries? Evidence from a nationally representative survey in Bangladesh
Bibliographic record
Abstract
Background: In Bangladesh, the neonatal mortality rate has remained relatively high at 23 deaths per 1000 live births. Consistent adoption of essential newborn care (ENC) practices should lower this rate significantly. This study assessed whether the presence of skilled birth attendants (SBAs) in home deliveries improved ENC practices in Bangladesh. Methods: Data from the Bangladesh Demographic and Health Survey 2014 on mothers who reported home birth in the previous 3 y was utilized (n=2761 out of 4904 total births). SBAs include all types of healthcare providers who have received formal training in obstetric care. A generalized structural equation model was used to explore factors affecting (1) utilization of antenatal care, (2) choice of birth attendants and (3) adoption of ENC practices. Results: One-quarter (25.7%) of home births were delivered by an SBA. SBAs performed ENC practices more often than traditional birth attendants (thermal care, 15.0% of skilled deliveries vs 10.1% of unskilled; cord care, 71.6% vs 62.9%; early breastfeeding, 63.9% vs 58.6%). The presence of an SBA during delivery resulted in a greater likelihood of receiving ENC practices. Conclusion: Although SBAs performed the recommended activities at a higher rate than the unskilled across all outcomes, the proportion of SBAs performing ENC practices is still low. It is important for policymakers to identify strategies to improve the effectiveness of SBAs in home deliveries.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".