Challenges for Family Medicine Residents in Attaining the CanMEDS Professional Role: A Thematic Analysis of Preceptor Field Notes
Bibliographic record
Abstract
PURPOSE: Among the roles of the competent physician is that of a professional, according to the Canadian Medical Education Directives for Specialists (CanMEDS) framework, which describes the abilities physicians require to effectively meet the health care needs of the people they serve. Through examination of preceptor field notes on resident performance, the authors identified aspects of this role with which family medicine residents struggle. METHOD: The authors used a structured thematic analysis in this qualitative study to explore the written feedback postgraduate medical learners receive at the University of Toronto Department of Family and Community Medicine. Seventy field notes written between 2015 and 2017 by clinical educators for residents who scored "below expectation" in the CanMEDS professional role were analyzed. From free-text comments, the authors derived inductive codes, amalgamated the codes into themes, and measured the frequency of the occurrence of the codes. The authors then mapped the themes to the key competencies of the CanMEDS professional role. RESULTS: From the field notes, 7 themes emerged that described reasons for poor performance. Lack of collegiality, failure to adhere to standards of practice or legal guidelines, and lack of reflection or self-learning were identified as major issues. Other themes were failure to maintain boundaries, taking actions that could have a negative impact on patient care, failure to maintain patient confidentiality, and failure to engage in self-care. When the themes were mapped to the key competencies in the CanMEDS professional role, most related to the competency "commitment to the profession." CONCLUSIONS: This study highlights aspects of professional conduct with which residents struggle and suggests that the way professionalism is taught in residency programs-and at all medical training levels-should be reassessed. Educational interventions that emphasize learners' commitment to the profession could enhance the development of more practitioners who are consummate professionals.
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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 | 0.025 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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 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".