To stay or leave: an integrative review of factors, personas, and recommendations for retaining family physicians in Canada
Bibliographic record
Abstract
INTRODUCTION: Family physicians are the cornerstone of primary health care in Canada. Yet, retention remains a growing concern. Challenges in retaining family physicians poses serious implications for healthcare accessibility, continuity, and equity across all practice contexts in Canada, including (but not limited to) rural, remote, urban, and underserved communities. Currently, 25% of Canadians do not have a primary care provider. While much attention has been given to recruitment, less is known about the multifaceted and intersecting factors that influence whether practicing family physicians and family medicine trainees (including Canadian Medical Graduates (CMGs) and International Medical Graduates (IMGs)), remain in sustained comprehensive practice in Canada. This review synthesizes the literature to identify key drivers of family physician retention and offers evidence-based recommendations. METHODS: We conducted an integrative review of peer-reviewed literature published between January 1, 2000, and March 30, 2025, following Whittemore and Knafl’s five-stage methodology. A systematic search was carried out across five electronic databases. Included studies were assessed for quality and thematically analyzed using a five-domain coding framework: personal, family, community, professional, and structural/systemic. Composite personas were developed to illustrate recurring physician retention trajectories and evidence-based recommendations were thematized across our five-domain coding framework. RESULTS: Of the 1,613 records screened, 23 studies met inclusion criteria. Factors influencing retention were identified across all five domains. Structural and professional barriers, including licensure restrictions, administrative burden, and limited autonomy, emerged as the most consistent deterrents. Facilitators included strong community ties, spousal support, team-based practice environments, and access to continuing professional development. We identified and developed seven physician personas to create a portrait of the diverse experiences of family physicians in Canada. Key recommendations included reforming licensure and payment models, enhancing mentorship and CME access, supporting spousal integration, and fostering culturally safe, community-rooted team-based practice models. CONCLUSION: Retaining family physicians in Canada is a relational challenge that requires collaborative, multi-level change. Tailored, context-specific retention strategies co-designed with physicians and communities can enhance sustainability and health equity especially in rural, remote and underserved communities.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".