The challenge of providing palliative care in the nursing home: part 1 external factors
Bibliographic record
Abstract
Nursing homes are increasingly becoming the place of care and site of death for growing numbers of frail older people dying of chronic progressive illnesses. Despite this increase, empirical evidence suggests that providing palliative care in nursing homes is replete with challenges. In a previous publication, the authors examined challenges external to the nursing home that influence the provision of palliative care, and which may be beyond the nursing home's control (Wowchuk et al, 2006). This paper reviews the primary internal factors identified in the literature that affect the provision of palliative care and are, to some extent, under the nursing home's control. The internal factors include: i) lack of care provider knowledge about the principles and practices of palliative care; ii) care provider attitudes and beliefs about death and dying; iii) staffing levels and lack of available time for dying residents; iv) lack of physician support; v) lack of privacy for residents and families; vi) families' expectations regarding residents' care; vii) hospitalisation of dying residents. Suggestions for practice, education and research are provided.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".