Strengthening family medicine through coaching-informed peer support: a pilot program evaluation
Bibliographic record
Abstract
BACKGROUND: Primary care physicians are facing elevated levels of burnout and often struggle to find joy in their work, with fewer physicians choosing primary care as a career. Peer coaching offers a way to enhance professional fulfillment and job satisfaction by fostering connection and support among physicians. In this study, we evaluated a pilot coaching-informed peer support program for family physicians in Ontario. Our evaluation explored whether the program helped increase joy in practice, strengthen professional well-being, and reduce burnout. METHODS: In the Peers for Joy program, physicians are trained to be "Guides" and support fellow physician "Learners" across 3 meetings to identify their goals and find ways to create joy in their work. To evaluate this pilot program, we used a multi-methods approach including surveys, interviews, and focus groups to explore whether the program increased joy in practice and reduced burnout, as well as its potential impacts on the guides. The primary outcome focused on satisfaction and joy in practice, assessed through the survey question: "How likely are you to recommend this job as a family physician?". Surveys were analyzed with Anova for continuous variables, Fisher's exact tests for categorical variables and the weekly one question surveys were analyzed with the Mann Kendall trend tests. Interviews were transcribed and analyzed using thematic analysis. RESULTS: 32 peer learners and 27 peer guides participated in the pilot from January-April 2024. After participation, both peer learners and peer guides were more likely to recommend their job as a family physician to a friend or colleague (learners increased from 5.5/10 to 7.0, P = 0.004 and guides from 6.4/10 to 7.5, P = 0.003). Peer learners reported they joined the program due to burnout and because they wanted to find joy and connection. Peer guides wanted to help their colleagues regain their passion for family medicine. Peer learners described various benefits from participating in the program, including feeling validated, receiving advice on workflow improvements, and encouragement to shift their perspective on their role as a family physician. Peer guides also felt that the experience was fulfilling, that it helped shift their perspective on their role as a family physician, and that they learned valuable coaching techniques that could be applied in their clinical encounters. CONCLUSION: The pilot demonstrated an acceptable and potentially helpful approach to improve family physician resiliency from burnout, promote togetherness, and improve joy in work. As such, the program could be a sustainable approach to peer support for family physicians.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".