An Approach to Leadership Development and Patient Safety and Quality Improvement Education in the Context of Professional Identity Formation in Pre-Clinical Medical Students
Bibliographic record
Abstract
Objectives: Leadership and patient safety and quality improvement (PSQI) are recognized as essential parts of a physician's role and identity, which are important for residency training. Providing adequate opportunities for undergraduate medical students to learn skills related to these areas, and their importance, is challenging. Methods: The Western University Professional Identity Course (WUPIC) was introduced to develop leadership and PSQI skills in second-year medical students while also aiming to instill these topics into their identities. The experiential learning portion was a series of student-led and physician-mentored PSQI projects in clinical settings that synthesized leadership and PSQI principles. Course evaluation was done through pre/post-student surveys and physician mentor semi-structured interviews. Results: A total of 108 of 188 medical students (57.4%), and 11 mentors (20.7%), participated in the course evaluation. Student surveys and mentor interviews illustrated improved student ability to work in teams, self-lead, and engage in systems-level thinking through the course. Students improved their PSQI knowledge and comfort levels while also appreciating its importance. Conclusion: The findings from our study suggest that undergraduate medical students can be provided with an enriching leadership and PSQI experience through the implementation of faculty-mentored but student-led groups at the core of the curricular intervention. As students enter their clinical years, their first-hand PSQI experience will serve them well in increasing their capacity and confidence to take on leadership roles.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 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".