Palliative Care Models in Long-Term Care: A Scoping Review
Bibliographic record
Abstract
OBJECTIVE: The goal of this scoping review was to identify existing palliative models in long-term care (LTC) homes and differentiate between the key components of each in terms of training/capacity-building strategies; resident, family and staff support; and advance care planning (ACP) and goals-of-care discussions. METHODS: We conducted a scoping review based on established methods to summarize the international literature on palliative models and programs for LTC. We analyzed the data using tabular summaries and content analysis. RESULTS: We extracted data from 46 articles related to palliative programs, training/capacity building, family support, ACP and goals of care. Study results highlighted that three key components are needed in a palliative program in LTC: (1) training and capacity building; (2) support for residents, family and staff; and (3) ACP, goals-of-care discussion and informed consent. CONCLUSION: This scoping review provided important information about key components to be included in a palliative program in LTC. Future work is needed to develop a model that suits the unique characteristics in the Canadian context.
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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 | 0.016 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".