Effectiveness of Nursing Interventions in Reducing Maternal Mortality in Resource-Limited Settings: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Objective: To assess the effectiveness of nurse-led or nurse-integrated interventions in improving maternal health outcomes, particularly antenatal care (ANC) attendance, in resource-constrained settings. Methods: A systematic review and meta-analysis were conducted following PRISMA guidelines. Databases including PubMed, Scopus, CINAHL and Web of Science were searched for studies evaluating the impact of nursing interventions on maternal health outcomes. Risk of bias was assessed using the Cochrane RoB 2 tool and Newcastle-Ottawa Scale. A random-effects meta-analysis was performed for studies reporting ANC attendance (4 and more visits). (PROSPERO CRD420251067253). Results: Of the 1038 records identified, 11 studies met the inclusion criteria, and 3 were eligible for meta-analysis. The pooled Odds Ratio for ANC attendance was 1.48 (95% CI = 1.06-2.08), indicating a statistically significant improvement. For facility use at birth, results also showed positive effects (OR=1.49, 95% CI = 1.21-1.77). Mortality-related outcomes showed a midwife-delivered postpartum hemorrhage bundle reduced a composite outcome including severe hemorrhage and death (RR = 0.40, 95% CI = 0.32-0.50) Narrative synthesis of other outcomes such as skilled birth attendance and maternal mortality also suggested a positive impact of nurse-led interventions. Conclusion: Nurse-led and nurse-integrated maternal health interventions significantly improve ANC utilization in low-resource settings. Policymakers should consider scaling these models as part of broader maternal health strategies.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".