Validation of the Vietnamese version of the EORTC QLQ-SWB32: A measure of spiritual well-being in cancer patients
Bibliographic record
Abstract
Abstract Purpose : The quality of life of people with cancer can be improved by helping them discover meaning and purpose in life, even if they are faced with a potentially fatal illness. This study aimed to evaluate the reliability and applicability of the Vietnamese version of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Spiritual Well-being 32 (EORTC QLQ-SWB32) measurement in cancer patients. Methods : A total of 214 patients from four hospitals with cancer treatment facilities or having an oncology department were invited to participate in the study. The data were collected from November 2021 to April 2022 and analyzed for validation. Results : In this group of participants, the type of cancer with the highest prevalence rate was lung cancer (71%). The confirmatory factor analysis of construct validity with Chi-Square/df = 2.283, goodness-of-fit index = 0.846, comparative fit index = .742, and root mean square error of approximation = .078 confirmed the culturally distinguished model fit in Vietnamese people with cancer. The reliability of the instrument ranged from 0.604 to 0.749 for Relationship with Someone or Something Greater (RSG) and Relationship with Others (RO). In the group of patients who identified as having a religion, patients with no religion had lower RSG scores than Catholics or Buddhists. There were distinctions in the median Relationship with Self (RS) scores according to the severity of most Edmonton symptoms. Conclusion : The Vietnamese version of the EORTC QLQ-SWB32 tool was accepted and reliable, specifically for cancer patients in Vietnam.
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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 | 0.005 | 0.009 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".