Strategies and interventions that foster clinical leadership among registered nurses: a scoping review protocol
Bibliographic record
Abstract
OBJECTIVE: The objective of this scoping review is to identify and describe strategies and interventions aimed at fostering registered nurses' clinical leadership in any clinical setting, identify the theories and/or frameworks that guide registered nurses' clinical leadership development, and describe the types of research conducted on this topic. INTRODUCTION: Registered nurse clinical leaders may be defined as staff nurses in clinical settings who influence and coordinate patients, families, and health care team members for the purpose of integrating care for positive patient outcomes. They have been described as expert clinicians, effective decision-makers, and relationship-focused professionals who build trust among patients, families, and health care colleagues to ensure the best possible patient care. Clinical nursing is the cornerstone of the nursing profession. Registered nurses' clinical leadership is considered critical to the health of patients and to the advancement of nursing practice. Hence, it is important to understand strategies and interventions for fostering this leadership. INCLUSION CRITERIA: This scoping review will include any quantitative, qualitative, or mixed methods studies that have registered nurse participants practicing in any clinical setting globally and that examined strategies and interventions to foster registered nurses' clinical leadership. Besides primary research studies, we will also include reviews. METHODS: This scoping review will be conducted using JBI methodology. Academic databases and sources of gray literature will be searched for published and unpublished studies. Screening and full-text review of accessed records will be conducted to determine alignment with the inclusion criteria. For records that meet the inclusion criteria, data will be extracted, mapped, and presented in a table. A narrative summary will describe how the tabulated results addressed the review questions. SCOPING REVIEW REGISTRATION: Open Science Framework Registration: https://osf.io/hjfkd.
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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 | 0.116 | 0.089 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.012 | 0.013 |
| Bibliometrics | 0.026 | 0.019 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.050 | 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".