Comprehensive mapping of NICU developmental care nursing interventions and related sensitive outcome indicators: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Neurodevelopmental outcomes of preterm infant are still a contemporary concern. To counter the detrimental effects resulting from the hospitalisation in the neonatal intensive care unit (NICU), developmental care (DC) interventions have emerged as a philosophy of care aimed at protecting and enhancing preterm infant's development and promoting parental outcomes. In the past two decades, many authors have suggested DC models, core measures, practice guidelines and standards of care but outlined different groupings of interventions rather than specific interventions that can be used in NICU clinical practice. Moreover, as these DC interventions are mostly implemented by neonatal nurses, it would be strategic and valuable to identify specific outcome indicators to make visible the contribution of NICU nurses to DC. OBJECTIVES: The overarching objective of this review is to identify the nature, range, and extent of the literature regarding DC nursing interventions for preterm infants in the NICU. The secondary twofold objectives are to highlight interventions that fall into identified categories of DC interventions and suggest nursing-sensitive outcome indicators related to DC interventions in the NICU. INCLUSION CRITERIA: Papers reporting on or discussing a DC nursing intervention during NICU hospitalisation will be included. METHODS AND ANALYSIS: The Joanna Briggs Institute's methodology for scoping reviews will be followed. CINAHL, MEDLINE, Embase, PubMed, Web of Science, Scopus, ProQuest and PsycInfo databases from 2009 to the present will be searched. Any type of paper, published in English or French, will be considered. Study selection and data extraction will be conducted by pairs of two review authors independently. A qualitative content analysis will be conducted. ETHICS AND DISSEMINATION: No Institutional Review Board ethical approbation is needed. Results of this review will be presented in scientific meetings and published in refereed papers.
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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 | 0.083 | 0.074 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.016 | 0.013 |
| Bibliometrics | 0.029 | 0.021 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.059 | 0.011 |
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".