Why do new-borns die? Perspectives of community members and health care providers in the Lawra municipality of the Upper West Region, Ghana
Bibliographic record
Abstract
Neonatal deaths contribute significantly to under-five mortality and serve as a crucial indicator of a country’s socioeconomic development, quality of life, and health status. These deaths occur both at home and in health facilities. Therefore, the perspectives of community members and healthcare providers are essential in defining neonatal survival. This study explored the perceived causes of neonatal deaths among healthcare professionals and community members at the Lawra Municipality in the Upper West Region, Ghana. This study employed a qualitative descriptive approach. A purposive sample of 30 participants including 18 community members and 12 healthcare providers, was selected. Data were gathered using Focus Group Discussion (FGD), transcribed verbatim, coded and analysed using thematic-content analysis. Three themes were constructed to describe the factors leading to newborn deaths both at health facilities and in the community. These factors included: (1) personal factors related to newborns, mothers/families and health staff; (2) physical factors related to hospital facilities and equipment; and (3) logistical factors related to transport, referral and presentation delays. The study identified differences in perspectives between healthcare providers and community members, which can affect interventions in neonatal care. Health authorities are encouraged to develop a shared vision to engage communities by addressing geographic-specific factors causing neonatal deaths. This approach can help in understanding how collective actions can contribute to reducing neonatal deaths.
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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) | 0.001 | 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 | 0.001 |
| 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".