Demoralization Syndrome Among Elderly Patients with Cancer Disease
Bibliographic record
Abstract
Background Demoralization is distinctive psychological distress that involves hopelessness, helplessness, loss of purpose and meaning, and existential distress. Cancer patients' demoralization has been well documented, but little is known regarding older cancer patients and the related factors. Therefore, this study evaluated demoralization syndrome in older cancer patients. Methods Cancer patients over 61 years old ( n = 113, female 59.3%, mean age 65.7 years, range 61–80) diagnosed with heterogeneous types of cancer were recruited. They completed questionnaires in a hospital's inpatient and outpatient units. Their demoralization was measured using the Demoralization Scale-Mandarin Version (DS-MV). The Patient Health Questionnaire-9 (PHQ-9), Distress Thermometer (DT), Beck Scale for Suicide Ideation (BSS), and Posttraumatic Growth Inventory (PTGI) were used to measure other psychological statuses and the association with demoralization. Results The mean DS-MV score was 28.1 ( SD = 16.3). In this sample, 57.7% had moderate to high demoralization (18.6% had moderate demoralization, and 38.1% had high demoralization). Twenty-three percent reported a DT score of five and above, 5.5% reported a PHQ-9 score of 10 and above, and 23.9% reported a BSS score greater than zero. Demoralization was associated with suicide ideation, depression, distress, lower education, and the cancer site. Demoralization was not associated with posttraumatic growth, gender, work status, or religion. Conclusion More than half of older cancer patients have moderate to high demoralization and it is associated with depression, suicide ideation, and distress. Screening and interventions that are better tailored to older cancer patients could improve the quality of care in cancer treatment.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".