Place of care and death preferences among recently bereaved family members: a cross-sectional survey
Bibliographic record
Abstract
OBJECTIVES: The aim was: (1) to investigate preferred place for end-of-life care and death for bereaved family members who had recently lost a person with advanced illness and (2) to investigate associations between bereaved family members' preferences and individual characteristics, health-related quality of life, as well as associations with their perception of the quality of care that the ill person had received, the ill person's preferred place of death and involvement in decision-making about care. METHODS: A cross-sectional survey with bereaved family members, employing descriptive statistics and multinominal logistic regression analyses. RESULTS: Of the 485 participants, 70.7% were women, 36.1% were ≥70 years old, 34.5% were partners and 51.8% were children of the deceased. Of the bereaved family members, 52% preferred home for place of end-of-life care and 43% for place of death. A higher likelihood of preferring inpatient palliative care was associated with being female and having higher education, whereas a lower likelihood of preferring a nursing home for the place of care and death was associated with higher secondary or higher education. Partners were more likely to prefer hospital for place of care and nursing home for place of death. CONCLUSIONS: Home was the most preferred place for end-of-life care and death. Bereaved people's experiences of end-of-life care may impact their preferences, especially if they had a close relationship, such as a partner who had a higher preference for nursing home and hospital care. Conversations about preferences for the place of care and death considering previous experience are encouraged.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".