Transformative medical education: must community-based traineeship experiences be part of the curriculum? A qualitative study
Bibliographic record
Abstract
BACKGROUND: There are shortcomings in medical practitioners' capacity to adapt to the particular needs of people experiencing circumstances of social vulnerability. Clinical traineeships create opportunities for the acquisition of knowledge, competencies, attitudes, and behaviors. However, some authors question the learnings to be made through classical clinical training pathways. This article explores the learnings gained from a traineeship experience within a community-based clinical setting intended for patients experiencing social vulnerability and operating under an alternative paradigm of care. To our knowledge, there is little research intended to identify and understand what medical trainees gain from their experience in such contexts. METHODS: This exploratory qualitative study is based on twelve interviews with practicing physicians who completed a traineeship at La Maison Bleue (Montreal, Canada) and three interviews conducted with key informants involved in traineeship management. Based on Mezirow's theory of transformational learning, data were analyzed according to L'Écuyer's principles of qualitative content analysis. NVivo software was used. RESULTS: The main learnings gained through the traineeship are related to (1) greater awareness of beliefs, assumptions and biases through prejudice deconstruction, cultural humility and critical reflection on own limitations, power and privileges; (2) the development of critical perspectives regarding the health care system; (3) a renewed vision of medical practice involving a less stigmatizing approach, advocacy, empowerment, interdisciplinarity and intersectorality; and (4) strengthened professional identity and future practice orientation including confirmation of interest for community-based practice, the identification of criteria for choosing a future practice setting, and commitment to becoming an actor of social change. Certain characteristics of the setting, the patients and the learner's individual profile are shown to be factors that promote these learnings. CONCLUSIONS: This article highlights how a traineeship experience within a clinical setting intended for a clientele experiencing circumstances of social vulnerability and operating under an alternative paradigm presents an opportunity for transformative learning and health practice transformation toward renewed values of health equity and social justice. Our findings suggest medical traineeships in community-based clinical settings are a promising lead to foster the development of fundamental learnings that are conducive to acceptable and equitable care for people experiencing social vulnerability.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".