Variations in and factors influencing family members' decisions for palliative home care
Bibliographic record
Abstract
The purpose of this paper is to describe the variations in and factors influencing family members' decisions to provide home-based palliative care. Findings were part of a larger ethnographic study examining the social context of home-based palliative caregiving. Data from participant observations and in-depth interviews with family members (n=13) providing care to a palliative patient at home, interviews with bereaved family members (n=47) and interviews with health care providers (n=25) were subjected to constant comparative analysis. Findings indicate decisions were characterized by three types. Some caregivers made uninformed decisions, giving little consideration to the implications of their decisions. Others made indifferent decisions, whereby they reluctantly agreed to provide care at home, and still others negotiated decisions for home care with the dying person. Decisions were influenced by three factors: fulfilling a promise to the patient to be cared for at home, desiring to maintain a 'normal family life' and having previous negative encounters with institutional care. Findings suggest interventions are needed to better prepare caregivers for their role, enhance caregivers' choice in the decision-making process, improve care for the dying in hospital, and consider the development of alternate options for care.
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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 | 0.005 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| 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".