[The nursing practice informed by research: leader training in health organizations, a promising path].
Bibliographic record
Abstract
PROBLEM: Despite the recognition by nurses of the importance of supporting their experiential knowledge on scientific data, evidence-based nursing research is seldom integrated in their practice. An important limitation is the nurses' general lack of basic abilities to use research to better inform their clinical decision making. The objective of this pilot study was to evaluate a leader training intervention on research results integration in nursing practice. INTERVENTION: Seven advanced practice nurses and 12 clinical nurses from six care specialties jointly participated to training activities on knowledge transfer and exchange. METHOD: Nineteen nurses went through a 20-day training internship and 14 participated to two interviews, before and after the intervention. RESULTS AND CONCLUSION: Overall, nurses were very positive about their participation to the training. Difficulties encountered during the internship and the prior negative perception about the research process, were largely offset by the acquired capabilities and the clinical results of the intervention. Furthermore, the beginning of change in the organization and in relations with some health professionals were noted and seen as positive.
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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 | 0.039 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".