Mentoring as a Knowledge Translation Intervention to Inform Clinical Practice: A Multi-Methods Study
Bibliographic record
Abstract
Background: Mentoring is an intervention for implementing evidence into practice, but little is known about this intervention. The overall aim of this dissertation was to examine mentoring as a knowledge translation (KT) intervention to inform clinical practice. Methods: 1) A systematic review was used to determine the effectiveness of mentoring as a KT intervention. 2) An interpretive descriptive qualitative study was conducted to explore the use of mentoring in the Registered Nurses' Association of Ontario’s Best Practice Guidelines Implementation/ Knowledge Transfer Fellowship program. Findings: 1) Of 10,669 citations from 1988 to 2012, 10 studies were eligible. Findings showed that mentoring alone (n = 1 study) improved one behavioral outcome. When mentoring was used as part of a multi-faceted intervention (n = 9), there were various effects on knowledge, beliefs/attitudes, use of research evidence in clinical practice, and the impacts on healthcare professionals, patients and organizations. 2) Qualitative interviews with 6 fellows, 8 mentors and 4 program leaders revealed that mentoring involved building relationships, establishing a learning plan, and using teaching and learning activities. Mentors were described as accessible, dedicated, and having expertise; fellows were described as dedicated, self-directed, and having mixed levels of expertise. Mentoring was described as positively impacting upon mentoring relationships, fellows, mentors, and organizations. Participants reported no negative outcomes. Conclusion: Mentoring was used as a KT intervention to support the implementation of evidence into clinical practice. The systematic review and qualitative study findings informed the Mentoring for Guideline Implementation model. Mentoring involved mentees selecting more experienced mentors who provided individualized support based on mentees’ learning needs, which resulted in mutual benefits for mentees and mentors. Future research is required to validate this new mentoring model, develop an instrument to measure the mentor-mentee relationship, and evaluate the effectiveness of mentoring as a KT intervention for guideline implementation in nursing.
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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 | 0.035 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".