Associations of prognostic awareness/acceptance with psychological distress, existential suffering, and quality of life in terminally ill cancer patients' last year of life
Bibliographic record
Abstract
PURPOSE: Whether prognostic awareness benefits terminally ill cancer patients' psychological-existential well-being and quality of life (QOL) is unclear because of lack of well-controlled longitudinal studies. This study longitudinally evaluated the associations of accurate prognostic awareness and prognostic acceptance with psychological distress, existential suffering, and QOL while comprehensively controlling for confounders in Taiwanese terminally ill cancer patients' last year of life. PATIENTS AND METHODS: A convenience sample of 325 cancer patients was followed until death. Psychological distress and existential suffering were assessed by severe anxiety and depressive symptoms and high self-perceived sense of burden to others, respectively. Dichotomized and continuous (QOL) outcome variables were evaluated by multivariate logistic and linear regression modeling with the generalized estimating equation, respectively. RESULTS: Accurate prognostic awareness was not associated with the likelihood of severe anxiety or depressive symptoms but significantly increased the likelihood of high self-perceived sense of burden to others and was associated with poorer QOL in participants' last year of life. Participants who knew and highly accepted their prognosis were significantly less likely to experience severe anxiety symptoms than those who were unaware of or knew their prognosis but had difficulty accepting it. CONCLUSION: Knowing one's poor prognosis and confronting one's impending death without full acceptance and adequate professional psycho-spiritual support may harm more than benefit terminally ill cancer patients' psychological state, existential well-being, and QOL. These findings highlight the importance of tailoring psycho-spiritual support to cancer patients' psychological and existential needs when prognostic information is disclosed.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".