Care Provider Perspectives on End-Of-Life Care in Long-Term-Care Homes: Implications for Whole-Person and Palliative Care
Bibliographic record
Abstract
This study holistically explores the experience of dying and end-of-life care for older persons with dementia in long-term care (LTC) from the perspective of care providers. Using a focused ethnography methodology, seven researchers interviewed LTC staff, residents' families, volunteers, management staff, and spiritual advisers/clergy over a five-day period. Research was guided by two key questions: What is the dying experience of people living in LTC from the perspective of different care providers? and, What are the salient issues in providing palliative care for elderly people dying in LTC? Based on a thematic analysis of verbatim data, three common themes were identified: tension between completing job tasks on time and "being there" for residents; the importance of family-like bonds between front-line staff and residents; and the importance of communication among staff and between staff and residents and their families at the end of life. Findings are discussed in relation to their implications for policies and practices that can support whole-person care and ultimately a good death for residents of LTC facilities.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".