Telehealth and the recruitment and retention of physicians in rural and remote regions: a Delphi study.
Bibliographic record
Abstract
INTRODUCTION: The availability of a medical workforce is a growing concern for rural and remote communities across Canada. In the last decade, various telehealth experiences have highlighted the potential impact of this technology on professional as well as organizational practices. But could telehealth be a strategy to attract and maintain physicians in rural and remote communities? The objective of this study was to identify a reliable list of recruitment and retention factors on which telehealth could have an impact. METHODS: We conducted 2 literature reviews and a Delphi study among 12 telehealth experts across Canada. RESULTS: The literature reviews identified 7 categories of recruitment and retention factors on which telehealth could have an impact: 1) individual, 2) familial, 3) contextual, 4) professional, 5) organizational, 6) educational, and 7) economic. CONCLUSIONS: Experts consulted through the Delphi study reached consensus on 31 out of 34 of the proposed statements about the impact of telehealth. This consensus can now be used as a conceptual model for further studies on the topic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 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".