A Stakeholder Analysis of the Strengthening a Palliative Approach in Long-Term Care Model
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to conduct a stakeholder analysis of the strengthening a palliative approach to long-term care (SPA-LTC) model and refine it based on feedback from long-term care (LTC) residents and their families, staff, researchers and decision makers. METHODS: We used a mixed-methods design to conduct a stakeholder analysis of the SPA-LTC model that consisted of two sequential components: qualitative focus groups with LTC staff followed by a quantitative survey with key stakeholders. RESULTS: Twenty-one LTC staff provided feedback about the SPA-LTC model after residents relocated to LTC, during advanced illness and at end of life and in the period of grief and bereavement. This feedback helped to guide revisions of the model. According to the survey results, the SPA-LTC model was well received by 35 stakeholders, but its feasibility was questioned. CONCLUSION: The Canadian SPA-LTC model is evidence based and endorsed by LTC staff and stakeholders. Efforts are needed to determine the feasibility of implementing the model to ensure that residents' needs are made a priority while in LTC.
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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 | 0.053 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".