Psychometric properties of the Japanese version of the Demoralization Scale‐II (DS‐II) in cancer patients
Bibliographic record
Abstract
Abstract Aim Demoralization, which is characterized by helplessness, hopelessness, and the loss of meaning, has gained increasing attention in psychiatry and palliative care. Robinson et al. developed the Demoralization Scale‐II (DS‐II) to assess this construct in a brief and reliable format. However, a validated Japanese version has not been developed to date. The purpose of this study was to develop a Japanese version of the DS‐II (DS‐II‐J) and to evaluate its psychometric properties in cancer patients. Methods A total of 147 cancer patients from 3 acute care hospitals in Japan were included in the study. Participants completed the DS‐II‐J, Patient Health Questionnaire‐9 (PHQ‐9), Generalized Anxiety Disorder 7‐item Scale (GAD‐7), and Edmonton Symptom Assessment System Revised Version (ESAS‐r). Internal consistency was assessed using Cronbach's α . Convergent validity was evaluated by examining correlations with the PHQ‐9, GAD‐7, and ESAS‐r. Confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) were conducted to assess factor structure. Results The DS‐II‐J demonstrated high internal consistency ( α = 0.92). Strong positive correlations were found between DS‐II‐J scores and PHQ‐9 and GAD‐7 scores, and moderate correlations with selected ESAS‐r physical symptoms, supporting convergent validity. CFA results showed a suboptimal model fit for both a one‐factor model and the original two‐factor model proposed by Robinson et al. EFA supported a two‐factor structure, but with a different item composition, suggesting cultural influences. Conclusion The DS‐II‐J is a valid and reliable tool for assessing demoralization in Japanese cancer patients.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".