Fostering Reflexivity in Medical Students: Is Patient Engagement a Promising Avenue? A Qualitative Case Study
Bibliographic record
Abstract
Background: Reflexivity enables individuals to analyze a situation based on past experience to develop other ways of thinking and perspectives for action. Reflexivity is therefore crucial for the improvement of professional practice. In medical education, recent studies have identified patient engagement as a promising strategy for fostering reflexivity in students; however, few evaluative studies have explored such a link. This article describes the reflexive effects of an intervention that engages patients in small-group discussion workshops about ethical, moral, and social issues arising from practice (as part of an undergraduate medical course at Université Laval) and presents the main processes involved in producing these effects. Methods: The study subscribes to a qualitative case study design. Cases are three groups that received the intervention in winter 2021. Data collection involved semi-structured interviews and non-participatory observation. Analysis entailed within-case and cross-case analysis. The study mobilizes Sandars' proposition of a three-stage reflexive process which is enhanced with other models of reflexivity. Results: The main reflexive effects and processes involved: (i) better understanding disembodied theoretical content, (ii) awareness of the limits of the clinical view for grasping complex situations, (iii) questioning one's convictions about the self and the profession, and (iv) awareness of the patient-doctor social distance. When considering concrete implications for action, reflexive effects refer to a patient-centered approach, implying other ways of doing, being, and thinking as a physician. Conclusions: This study was an opportunity to identify patient engagement in discussion workshops as a promising avenue to foster medical students' reflexivity and to better understand its whys and hows. It sheds new light on patient engagement's relevance and value in medical education. By identifying factors influencing the reflexive process, it also provides concrete support to medical schools wishing to commit to transformative educational postures and approaches involving patients.
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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 | 0.056 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.016 | 0.021 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".