Research utilization and clinical nurse educators: a systematic review
Bibliographic record
Abstract
BACKGROUND: Clinical nurse educators and other linking agents such as clinical nurse specialists, advanced nurse practitioners, and nurses working in research leadership positions are an important link in the facilitation of evidence-based practice in health care organizations. AIM: The purpose of this paper is to report the findings of a systematic review of the literature regarding clinical nurse educators and research utilization, using the Promoting Action on Research Implementation in Health Services framework as a backdrop for the analysis. FINDINGS: There is a positive relationship between research utilization and attitude toward research, higher levels of education, and reading professional nursing journals among clinical nurse educators. The authors suggest that not all clinical nurse educators have the necessary critical appraisal skills and research knowledge to use research effectively in practice. CONCLUSIONS: Few studies have examined clinical nurse educators and the determinants of their research utilization behaviour in clinical practice. Future research on clinical nurse educators needs to focus on the outcomes of research utilization, including the effectiveness of their role as facilitators and the contexts in which they practice.
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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 | 0.024 | 0.108 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.015 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".