Palliative and end of life care communication as emerging priorities in postgraduate medical education
Bibliographic record
Abstract
BACKGROUND: Reliance on surveys and qualitative studies of trainees to guide postgraduate education about palliative and end of life (EOL) communication may lead to gaps in the curriculum. We aimed to develop a deeper understanding of internal medicine trainees' educational needs for a palliative and EOL communication curriculum and how these needs could be met. METHODS: Mixed methods, including a survey and focus groups with trainees, and interviews with clinical faculty and medical educators, were applied to develop a broader perspective on current experiences and needs for further education. Quantitative descriptive and thematic analyses were conducted. RESULTS: Surveyed trainees were least confident and least satisfied with teaching in counseling about the emotional impact of emergencies and discussing organ donation. Direct observation with feedback, small group discussion, and viewing videos of personal consultations were perceived as effective, yet infrequently identified as instructional methods. Focus groups and interviews identified goals of care conversations as the highest educational priority, with education adapted to learner needs and accompanied by feedback and concurrent clinical and organizational support. CONCLUSIONS: Our work expands on previous research describing needs for postgraduate education in palliative and EOL communication to include the importance of support, culture change, and faculty development, and provides insight into why such needs exist.
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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 | 0.001 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".