Postgraduate palliative care education: Evaluation of a South African programme
Bibliographic record
Abstract
AIM: We aimed to assess the postgraduate palliative care distance education programme of the University of Cape Town (UCT) in terms of its perceived ability to influence palliative care delivery. METHODS: A mixed-methods approach, consisting of two surveys using open-ended and multiple-choice options, was conducted from January to December 2007 at the UCT School of Public Health and Family Medicine. All students registered in the programme from 2000 - 2007 were invited to participate; 83 (66.4% of all eligible participants) completed the general survey, and 41 (65.7%) of the programme's graduates completed the graduate survey. The survey scores and open-ended data were triangulated to evaluate UCT's palliative care postgraduate programme. RESULTS: General survey scores of graduates were significantly higher in 5 of the 6 categories in comparison with current students. The graduate survey indicated that curriculum and teaching strengths were in communication and dealing with challenging encounters. Graduates also stressed the need to develop a curriculum that incorporated a practical component. CONCLUSIONS: In addition to current postgraduate training, palliative care education in South Africa should be extended to undergraduate medical students, as the benefits of UCT's programme were limited to a small cohort of practitioners.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".