Neonatal nursing research in low-and middle-income countries: A scoping review
Bibliographic record
Abstract
Neonatal outcomes contribute over 50% to under-five child mortality globally. Given that nurses in low- and lower-middle-income countries are often primary care providers, they are ideally positioned to impact outcomes. Our scoping review aims to explore how neonatal nurses in LMICs are represented in global health research. This review was constructed using Arksey and O'Malley's five-step framework. Five databases were utilized in the search, and grey literature was included. A total of 651 articles were yielded, with 31 included in our review. We constructed themes based on the philosophical conceptualization of nursing knowledge as knowledge about nursing, knowledge for nursing, and knowledge of nursing. Representation of neonatal nursing in LMIC in global health research is extremely limited. Literature that exists primarily describes challenges in neonatal nursing or provides practice-specific knowledge for nurses to utilize. Further, research exploring knowledge of nurses that does exist has been entirely driven by Western, non-nursing perspectives.
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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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.020 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".