Are family medicine residents adequately trained to deliver palliative care?
Bibliographic record
Abstract
OBJECTIVE: To explore educational factors that influence family medicine residents' (FMRs') intentions to offer palliative care and palliative care home visits to patients. DESIGN: Qualitative descriptive study. SETTING: A Canadian, urban, specialized palliative care centre. PARTICIPANTS: First-year (n = 9) and second-year (n = 6) FMRs. METHODS: Semistructured interviews were conducted with FMRs following a 4-week palliative care rotation. Questions focused on participant experiences during the rotation and perceptions about their roles as family physicians in the delivery of palliative care and home visits. Participant responses were analyzed to summarize and interpret patterns related to their educational experience during their rotation. MAIN FINDINGS: Four interrelated themes were identified that described this experience: foundational skill development owing to training in a specialized setting; additional need for education and support; unaddressed gaps in pragmatic skills; and uncertainty about family physicians' role in palliative care. CONCLUSION: Residents described experiences that both supported and inadvertently discouraged them from considering future engagement in palliative care. Reassuringly, residents were also able to underscore opportunities for improvement in palliative care education.
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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 | 0.003 | 0.024 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".