Contextually appropriate nurse staffing models: a realist review protocol
Bibliographic record
Abstract
Introduction Decisions about nurse staffing models are a concern for health systems globally due to workforce retention and well-being challenges. Nurse staffing models range from all Registered Nurse workforce to a mix of differentially educated nurses and aides (regulated and unregulated), such as Licensed Practical or Vocational Nurses and Health Care Aides. Systematic reviews have examined relationships between specific nurse staffing models and client, staff and health system outcomes (eg, mortality, adverse events, retention, healthcare costs), with inconclusive or contradictory results. No evidence has been synthesised and consolidated on how, why and under what contexts certain staffing models produce different outcomes. We aim to describe how we will (1) conduct a realist review to determine how nurse staffing models produce different client, staff and health system outcomes, in which contexts and through what mechanisms and (2) coproduce recommendations with decision-makers to guide future research and implementation of nurse staffing models. Methods and analysis Using an integrated knowledge translation approach with researchers and decision-makers as partners, we are conducting a three-phase realist review. In this protocol, we report on the final two phases of this realist review. We will use C itation tracking, tracing L ead authors, identifying U npublished materials, Google S cholar searching, T heory tracking, ancestry searching for E arly examples, and follow-up of R elated projects (CLUSTER) searching, specifically designed for realist searches as the review progresses. We will search empirical evidence to test identified programme theories and engage stakeholders to contextualise findings, finalise programme theories document our search processes as per established realist review methods. Ethics and dissemination Ethical approval for this study was provided by the Health Research Ethics Board of the University of Alberta (Study ID Pro00100425). We will disseminate the findings through peer-reviewed publications, national and international conference presentations, regional briefing sessions, webinars and lay summary.
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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 | 0.228 | 0.291 |
| Meta-epidemiology (narrow) | 0.007 | 0.008 |
| Meta-epidemiology (broad) | 0.019 | 0.014 |
| Bibliometrics | 0.024 | 0.022 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.073 | 0.019 |
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".