A concept map of death-related anxieties in patients with advanced cancer
Bibliographic record
Abstract
OBJECTIVES: Fear of death and dying is common in patients with advanced cancer, but can be difficult to address in clinical conversations. We aimed to show that the experience of death anxiety may be deconstructed into a network of specific concerns and to provide a map of their interconnections to aid clinical exploration. METHODS: We studied a sample of 382 patients with advanced cancer recruited from outpatient clinics at the Princess Margaret Cancer Centre, Toronto, Canada. Patients completed the 15-item Death and Dying Distress Scale (DADDS). We used item ratings to estimate a regularised partial correlation network of death and dying-related concerns. We calculated node closeness-centrality, clustering and global network characteristics. RESULTS: Death-related anxieties were highly frequent, each associated with at least moderate distress in 22%-55% of patients. Distress about 'Running out of time' was a central concern in the network. The network was organised into two areas: one about more practical fears concerning the process of dying and another about more psychosocial or existential concerns including relational problems, uncertainty about the future and missed opportunities. Both areas were yet closely connected by bridges which, for example, linked fear of suffering and a prolonged death to fear of burdening others. CONCLUSIONS: Patients with advanced cancer may have many interconnected death-related fears that can be patterned in individual ways. The bridging links between more practical and more psychosocial concerns emphasise that the alleviation of death anxiety may require interventions that integrate symptom management, advance care planning and psychological treatment approaches.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".