Relationship between demoralization and quality of life in end‐of‐life cancer patients
Bibliographic record
Abstract
OBJECTIVE: To examine the relationship between demoralization and health-related quality of life (HRQoL) in a sample of end-of-life cancer patients with a life expectancy of 4 months or less undergoing palliative care, controlling for sociodemographic, clinical, and psychological variables. METHODS: Sociodemographic, clinical, and psychological data from 170 end-of-life cancer patients were collected using the following scales: Edmonton Symptom Assessment System for palliative care patients' symptoms; Patient Health Questionnaire-9 (PHQ-9) for depressive symptoms; Functional Assessment of Cancer Therapy Scale - General Measure (FACT-G) for HRQoL; Functional Assessment of Chronic Illness Therapy - Spiritual Well-Being for spirituality (FACIT-Sp); Demoralization Scale - Italian Version (DS-IT) for demoralization. RESULTS: The DS-IT showed that 51.8% of cancer patients were severely demoralized. In addition, 36.5% of the sample had clinically significant depressive symptoms and QoL was severely impaired (FACT-G). The result of regression analysis showed that demoralization (especially "Disheartenment" and "Sense of failure") was the strongest contributor for HRQoL, followed by ESAS_Lack of Well-Being and depression (PHQ-9), with the final model explaining 66% of the variance of the FACT-G. CONCLUSIONS: The results highlight a very high prevalence of severe demoralization in end-of life cancer patients. Moreover, demoralization was not only associated with patients' HRQoL, but it was also the most important contributing factor. This finding underscores the need to identify preventive or therapeutic psychological interventions that focus on preventing existential distress, and thus improve the QoL of dying patients in their last days of life.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".