Attitudes of the General Population, Cancer Patients, their Family Caregivers, and Physicians toward Dying and Death: A Nationwide Survey
Bibliographic record
Abstract
Little is known about people’s attitudes toward death. We aimed to examine attitudes toward death and to investigate their associations with health status in various participant groups. We administered nationwide questionnaires to a total of 4, 107 individuals including general Korean population, cancer patients, family caregivers, and physicians. Association of attitudes toward five aspects of dying and death—the ending of life, fearing death because it is painful, anticipating an afterlife, preparing to practice charity and being remembered—and physical, mental, social, and spiritual health status were also analyzed. Attitudes differed. Most (63.4%-76.2%) accepted that death is the ending of life, 45.6%-58.8% feared a painful death, 47.6%-55.0% anticipated an afterlife, 88.5%-93.0% expected to forgive, and 89.9%-94.1% expected to be remembered after death. The general population, cancer patients, and family caregivers had similar attitudes but had more positive attitudes than physicians on the ending of life, fearing a painful death, and anticipating an afterlife. Accepting death as the ending of life and fear of death pain were inversely associated with mental, social, spiritual, or general health status, but participants anticipating an afterlife, expecting to forgive, or expecting to be remembered showed better social, spiritual, or general health status. This nationwide study of various participant groups shows that attitudes toward dying and death were associated with mental, social, spiritual, or general health, but not physical health status. These data suggest that sensitive and skillful discussions of death and dying might contribute to peaceful end of life.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".