Knowledge Translation Strategies for Enhancing Nurses’ Evidence‐Informed Decision Making: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: Nurses are increasingly expected to engage in evidence-informed decision making (EIDM); the use of research evidence with information about patient preferences, clinical context and resources, and their clinical expertise in decision making. Strategies for enhancing EIDM have been synthesized in high-quality systematic reviews, yet most relate to physicians or mixed disciplines. Existing reviews, specific to nursing, have not captured a broad range of strategies for promoting the knowledge and skills for EIDM, patient outcomes as a result of EIDM, or contextual information for why these strategies "work." AIM: To conduct a scoping review to identify and map the literature related to strategies implemented among nurses in tertiary care for promoting EIDM knowledge, skills, and behaviours, as well as patient outcomes and contextual implementation details. METHODS: A search strategy was developed and executed to identify relevant research evidence. Participants included registered nurses, clinical nurse specialists, nurse practitioners, and advanced practice nurses. Strategies were those enhancing nurses' EIDM knowledge, skills, or behaviours, as well as patient outcomes. Relevant studies included systematic reviews, randomized controlled trials, cluster randomized controlled trials, non-randomized trials (including controlled before and after studies), cluster non-randomized trials, interrupted time series designs, prospective cohort studies, mixed-method studies, and qualitative studies. Two reviewers performed study selection and data extraction using standardized forms. Disagreements were resolved through discussion or third party adjudication. RESULTS: Using a narrative synthesis, the body of research was mapped by design, clinical areas, strategies, and provider and patient outcomes to determine areas appropriate for a systematic review. CONCLUSIONS: There are a sufficiently high number of studies to conduct a more focused systematic review by care settings, study design, implementation strategies, or outcomes. A focused review could assist in determining which strategies can be recommended for enhancing EIDM knowledge, skills, and behaviours among nurses in tertiary care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".