Development of a Palliative Care Education Program in Rural Long-Term Care Facilities
Bibliographic record
Abstract
In North America, people 85 years and older are the fastest growing age cohort and long-term care homes are increasingly becoming the place of end-of-life care. This is especially true in rural communities where services are lacking. Staff in long-term care homes lack education about palliative care, but in rural areas, accessing education and the lack of relevant curricula are barriers. The focus of this paper is to describe an approach to developing and delivering a research-based palliative care education curriculum in rural long-term care homes. The approach included conducting a detailed assessment of staffs' educational needs and preferred educational formats; developing a 15-hour interprofessional curriculum tailored to the identified needs; and delivering the curriculum on site in rural long-term care homes. Staff confidence and participation in delivering palliative care increased. Based on work in northwestern Ontario, Canada, this approach can serve as a model for palliative care education in other rural areas.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".