Incorporating leadership development into family medicine residency: a qualitative study of program directors in Canada
Bibliographic record
Abstract
This article was migrated. The article was marked as recommended. Background: To understand Canadian family medicine programs directors' perspective on the incorporation of leadership skills development in curriculum. Methods: Semi-structured interviews based on CanMEDS Leader role competencies were conducted and audio recorded. Recordings were transcribed and analyzed by two independent researchers using an interpretive approach to thematic analysis. Results: Eight interviews were conducted. All participants indicated that leadership development in family medicine residency education was important. There were varying levels of leadership development at all institutions. Barriers to incorporating leadership development included curricular time, suitable teaching skills of faculty and cost. Important factors to consider in developing curricula included approaching the subject collaboratively and offering a variety of levels of engagement. Of the 22 Key Concepts in the CanMEDS Leader Role, three were not referenced by participants: complexity of systems, effective committee participation, and information technology for healthcare. Participants offered three concepts that were not included in the CanMEDS list: communication, teamwork and research skills. Conclusions: There were varying levels of incorporation of leadership skills development into family medicine training. A clearer understanding of each of the leader competencies is needed by educational leaders in order to identify and prioritize the skills to include in family medicine residency programs. This study contributes to the knowledge of what leadership skills should be incorporated into family medicine programs.
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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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.021 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".