The rural incentive: Why do Physician Assistants choose to work in rural medicine and what makes them stay?
Bibliographic record
Abstract
Introduction: Access to healthcare in rural and underserved communities has been a longstanding concern in the Manitoba healthcare system. One way to help alleviate this shortage may be the use of physician assistants in rural communities. Currently 24% of University of Manitoba MPAS graduates practice in rural locations. Objective: The purpose of this review was to identify the benefits and difficulties of physician assistant practice in rural locations in order to understand how rural communities in Manitoba can maximize the recruitment and retention of physician assistants. Methods: A comprehensive review of online databases Embase, PubMed, Google Scholar and Medline for survey and questionnaire based studies of physician assistants. Five American articles were identified and analyzed. Results: Rural physician assistants identified increased autonomy, wider scope of practice and good supervising physician relationships as reasons why they choose rural practice. Community factors such as recreational and cultural amenities, desire for rural living and working in an underserved community were also influential. Increased workload, long hours and salary were identified as difficulties. Conclusion: Rural health employers in Manitoba looking to recruit physician assistants should highlight the benefits of working rurally such as more autonomy and more varied job duties as well as the community specific amenities and attractions. Employers should also address the difficulties such as workload and hours in order to increase retention in the long run.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".