Death Anxiety and Correlates in Cancer Patients Receiving Palliative Care
Bibliographic record
Abstract
Background: Death anxiety is powerful, potentially contributes to suffering, and yet has to date not been extensively studied in the context of palliative care. Availability of a validated Death Anxiety and Distress Scale (DADDS) opens the opportunity to better assess and redress death anxiety in serious illness. Objective: We explored death anxiety/distress for associations with physical and psychosocial factors. Design: Ancillary to a randomized clinical trial (RCT) of Dignity Therapy (DT), we enrolled a convenience sample of 167 older adults in the United States with cancer and receiving outpatient palliative care (mean age 65.9 [7.3] years, 62% female, 84% White, 62% stage 4 cancer). They completed the DADDS and several measures for the stepped-wedged RCT, including demographic factors, religious struggle, dignity-related distress, existential quality of life (QoL), and terminal illness awareness (TIA). Results: DADDS scores were generally unrelated to demographic factors (including religious affiliation, intrinsic religiousness, and frequency of prayer). DADDS scores were positively correlated with religious struggle ( p < 0.001) and dignity-related distress ( p < 0.001) and negatively correlated with existential QoL ( p < 0.001). TIA was significantly nonlinearly associated with both the total DADDS ( p = 0.007) and its Finitude subscale ( p ≤ 0.001) scores. There was a statistically significant decrease in Finitude subscale scores for a subset of participants who completed a post-DT DADDS ( p = 0.04). Conclusions: Findings, if replicable, suggest that further research on death anxiety and prognostic awareness in the context of palliative medicine is in order. Findings also raise questions about the optimal nature and timing of spiritual and psychosocial interventions, something that might entail evaluation or screening for death anxiety and prognostic awareness for maximizing the effectiveness of care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".