The Quality of Dying and Death in Advanced Cancer from the Perspective of Bereaved Caregivers
Bibliographic record
Abstract
There were two main research goals of this project: 1) to increase the interpretability of quality of dying and death measures by exploring how respondents generate their evaluations; and 2) to measure the quality of dying and death in advanced cancer patients and consider the influence of specialized palliative care and place of death on this outcome.To understand how respondents evaluate dying and death, 22 caregivers of deceased cancer patients were asked to take part in a cognitive interview protocol after formulating the 31 quality ratings that contribute to the total Quality of Dying and Death (QODD) questionnaire score. Qualitative content analysis was applied to transcribed interviews. Results suggested that evaluations were based on multiple different perspectives and standards of comparison. Findings highlighted that the family should be the targeted unit of end-of-life care and attention should be paid to helping families anticipate and prepare for the realities of the dying process. To measure the quality of dying and death of patients with cancer and examine its relationship to receipt of palliative care and place of death, 402 caregivers of deceased cancer patients were interviewed with the QODD. Overall quality of dying and death was rated in the "neither good nor bad" to "almost perfect" range by 99.8% of caregivers. The lowest QODD subscale scores assessed symptom control and transcendence over death-related concerns. Multivariate analyses revealed that late or no specialized palliative care was associated with poorer death preparation and that home deaths were associated with better symptom control, death preparation, and overall quality of dying and death. Findings suggested that while home death was best, institutional deaths could also be of good quality, and also highlighted that symptom control and death-related distress are areas most in need of clinical attention. Overall, this research contributes to our understanding of the quality of dying and death construct, how it is evaluated, and the significant although small influence of location and palliative care on this outcome. Future directions include examination of quality of dying and death in other settings and the development of interventions that specifically target death-related distress.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".