Learning professional ethics: Student experiences in a health mentor program
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The use of patient centred approaches to healthcare education is evolving, yet the effectiveness of these approaches in relation to professional ethics education is not well understood. The aim of this study was to explore the experiences and learning of health profession students engaged in an ethics module as part of a Health Mentor Program at the University of Toronto. METHODS: Students were assigned to interprofessional groups representing seven professional programs and matched with a health mentor. The health mentors, individuals living with chronic health conditions, shared their experiences of the healthcare system through 90 minute semi-structured interviews with the students. Following the interviews, students completed self-reflective papers and engaged in facilitated asynchronous online discussions. Thematic analysis of reflections and discussions was used to uncover pertaining to student experiences and learning regarding professional ethics. RESULTS: Five major themes emerged from the data: (1) Patient autonomy and expertise in care; (2) ethical complexity and its inevitable reality in the clinical practice setting; (3) patient advocacy as an essential component of day-to-day practice; (4) qualities of remarkable clinicians that informed personal ideals for future practice; (5) patients' perspectives on clinician error and how they enabled suggestions for improving future practice. DISCUSSION: The findings of a study in one university context suggest that engagement with the health mentor narratives facilitated students' critical reflection related to their understanding of the principles of healthcare ethics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.024 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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 it