Newborn care behaviours and neonatal survival: evidence from sub‐<scp>S</scp>aharan <scp>A</scp>frica
Bibliographic record
Abstract
OBJECTIVE: To review evidence from sub-Saharan Africa for the association between the practice or promotion of essential newborn care behaviours and neonatal survival. METHODS: We searched MEDLINE for English language, peer-reviewed literature published since 2005. The study population was neonates residing in a sub-Saharan Africa country who were not HIV positive. Outcomes were all-cause neonatal or early neonatal mortality or one of the three main causes of neonatal mortality: complications of preterm birth, infections and intrapartum-related neonatal events. Interventions included were the practice or promotion of recommended newborn care behaviours including warmth, hygiene, breastfeeding, resuscitation and management of illness. We included study designs with a concurrent comparison group. Study quality was assessed using the Cochrane EPOC or Newcastle-Ottawa tools and summarised using GRADE. RESULTS: Eleven papers met the search criteria and most were at low risk of bias. We found evidence that delivering on a clean surface, newborn resuscitation, early initiation and exclusive breastfeeding, Kangaroo Mother Care (KMC) for low-birthweight babies, and distribution of clean delivery kits were associated with reduced risks of neonatal mortality or the main causes of neonatal mortality. There was evidence that training community birth attendants in resuscitation and administering antibiotics, and establishing women's groups can improve neonatal survival. CONCLUSION: There is a remarkable lack of robust evidence from sub-Saharan Africa on the association between practice or promotion of newborn care behaviours and newborn survival.
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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 | 0.013 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".