Preparation for the end of life in patients with advanced cancer and association with communication with professional caregivers
Bibliographic record
Abstract
OBJECTIVE: Previous studies regarding patients' end of life (EOL) preparation have focused mainly on practical tasks, such as advance directives. In this study, we investigate the relational and personal aspects of EOL preparation, using a patient-completed questionnaire, and examine associations with clinician-patient communication (CPC) and other variables. METHODS: Patients with advanced cancer but with good performance status were recruited from 24 medical oncology clinics, to participate in a cluster-randomised controlled trial of early palliative care intervention. Measures included the Quality of Life at the End of Life preparation for EOL subscale, and measures of CPC, functional status, comorbidity, spiritual well-being and symptom severity. Using chi-squared tests, t-tests and multivariate regression analyses, we examined the variables associated with preparation for EOL. We also examined the frequency distributions of individual EOL preparation items and used logistic regression to examine their associations with adequacy of CPC. RESULTS: In the 469 patients, characteristics associated with better EOL preparation were better CPC, older age, living alone, less symptom burden and better spiritual well-being. Thirty-one per cent agreed that they worried 'quite a bit' or 'completely' about their family's preparation to cope with the future, and 27% agreed that they would be a burden to their family. All preparation items except regrets about life were associated with adequacy of communication. CONCLUSIONS: A substantial minority of patients with advanced cancer but with good performance status are concerned about EOL preparation, particularly in relation to their families. Better CPC may help patients prepare not only practically but also personally and socially in relation to the dying process and the welfare of their families.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".