A systematic review of reviews: Recruitment and retention of rural family physicians
Bibliographic record
Abstract
INTRODUCTION: The recruitment and retention of family physicians in rural and remote communities has been the topic of many reviews; however, a lack of consensus among them with regard to which factors are most influential makes it difficult for setting priorities. We performed a systematic review of reviews which helped to establish an overall conclusion and provided a set of fundamental influential factors, regardless of the consistency or generalisability of the findings across reviews. This review also identified the knowledge gaps and areas of priority for future research. METHODS: A literature search was conducted to find the review articles discussing the factors of recruitment or retention of rural family physicians. Results were screened by two independent reviewers. The number of times that each factor was mentioned in the literature was counted and ordered in terms of frequency. RESULTS: The literature search identified 84 systematic reviews. Fourteen met the inclusion criteria, from which 158 specific factors were identified and summarised into 11 categories: personal, health, family, training, practice, work, professional, pay, community, regional and system/legislation. The three categories referenced most often were training, personal and practice. The specific individual factors mentioned most often in the literature were 'medical school characteristics', 'longitudinal rural training' and 'raised in a small town'. CONCLUSION: The three most often cited categories resemble three distinct phases of a family physician's life: pre-medical school, medical school and post-medical school. To increase the number of physicians who choose to work in rural practice, strategies must encompass and promote continuity across all three of these phases. The results of this systematic review will allow for the identification of areas of priority that require further attention to develop appropriate strategies to improve the number of family physicians working in rural and remote locations.
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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 | 0.045 | 0.218 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.009 |
| Bibliometrics | 0.017 | 0.023 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".