Rural Mentorships in Health Care: Factors Influencing Their Development and Sustainability
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The need to recruit and retain health care providers remains a concern in rural communities. This project aimed to better understand what health care providers and senior leaders value in mentorship and determine the best way to implement a mentorship program in rural western Canada. METHOD: Health care providers and senior leaders from a rural health region were recruited through convenience and snowball sampling. Participants were interviewed using a semistructured interview guide, and data were analyzed using thematic analysis. RESULTS: Two main themes were revealed: rural mentorship challenges and facilitators. Challenges included administrative, scope of practice, and interpersonal, whereas facilitators included mentorship as a recruitment and retention strategy, openness and commitment, structured mentorship programs, and community influence. CONCLUSION: This information will enable administrators and educators to more successfully implement mentorship programs for a variety of health care professionals working within rural environments and facilitate staff development, recruitment, and retention. J Contin Educ Nurs. 2018;49(7):322-328.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it