A Systematic Review of Postgraduate Palliative Care Curricula
Bibliographic record
Abstract
BACKGROUND: Palliative care is part of comprehensive family practice; however, many physicians do not feel confident in the biomedical and psychosocial realms. Although improving residency training to address this is necessary, there is little consensus on the best education methods. OBJECTIVE: To conduct a systematic review of postgraduate curricula in palliative care to incorporate the most effective components into a family medicine education program. METHODS: Studies of palliative care curricula conducted in postgraduate medical training programs that contained an evaluative component and published since 1980 were systematically examined by investigator pairs using standard selection criteria and data collection forms. Discrepancies were resolved by consensus. The outcomes examined were communication skills, knowledge, attitudes, and comfort/confidence level. RESULTS: 28 studies were included after reviewing 174 abstracts. Most studies (n = 21) used survey pre-post design with no control group. Outcomes were grouped into communication skills, knowledge and attitudes and confidence. Workshops with simulated patients or role plays improved communication skills. Relatively brief strategies such as short workshops showed objective improvements in focused knowledge areas. Either clinical rotations or multi-faceted interventions were required to produce improvements more broadly in knowledge base. Only a few studies examined the sustainability of outcomes. CONCLUSIONS: An effective palliative care curriculum will need to use a multifaceted approach, incorporating a variety of intentional strategies to address the multiple competencies required. There is a need for more rigorous curricular evaluation.
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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 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".