Building a Medical Undergraduate Palliative Care Curriculum: Lessons Learned
Bibliographic record
Abstract
Previous literature demonstrates that current palliative care training is in need of improvement for medical students in global, European and Canadian contexts. The training of medical undergraduates is key to ensure that the ongoing and increasing need for enhanced access to palliative care across all settings and communities is met. We describe building a comprehensive palliative and end-of-life care curriculum for medical undergraduates at our university. As with recent European and US studies, we found that the process of university curriculum renewal provided a critical opportunity to integrate palliative care content, but needed a local palliative care champion already in place as an energetic and tireless advocate. The development and integration of a substantive bilingual (English and French) palliative and end-of-life care curriculum over the 4-year medical undergraduate program at our university has occurred over the course of 14 years, and required multiple steps and initiatives. Subsequent to the development of the curriculum, there has been a 13-fold increase in students selecting our palliative care clinical rotations. Critical lessons learned speak to the importance of having a team vision, interprofessional collaboration with a focus on vision, plans and implementation, and flexibility to actively respond and further integrate new educational opportunities within the curriculum. Future directions for our palliative care curriculum include shifting to a competency-based training and evaluation paradigm. Our findings and lessons learned may help others who are working to develop a comprehensive undergraduate medical education curriculum.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".