Exploring the utility of the Nursing Role Effectiveness Model in evaluating nursing contributions in primary health care: A scoping review
Bibliographic record
Abstract
AIMS: To inform a discussion for the applicability of using the Nursing Role Effectiveness Model (NREM) in the primary health care setting through a synthesis of the literature that has used the model in all health care sectors. DESIGN: Scoping Review. METHODS: Articles were considered for inclusion if they discussed any aspect of the NREM in health care research that presented information related to any nursing regulatory designation, such as nurse practitioner (NP), registered nurse (RN), licensed/registered practical nurse (LPN/RPN) and considered both quantitative and qualitative study designs, including expert opinions and reports. RESULTS: A total of 22 articles that cited and/or used the NREM were identified in this review. Only two studies were focused in the primary health care setting. There is precedence for the use of the NREM to guide research in primary health care. The NREM should be modified to incorporate the unique characteristics of the primary health care setting.
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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 | 0.119 | 0.217 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.025 | 0.019 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".