Psychometric testing of the Spiritual Well-Being Scale–Mandarin version in Taiwanese cancer patients
Bibliographic record
Abstract
OBJECTIVE: The spiritual well-being of terminally ill cancer patients is an important indicator of the quality of their lives and of the quality of hospice care, but no validated tools are available for assessing this indicator in Taiwan. METHOD: The present cross-sectional study validated the Spiritual Well-Being Scale-Mandarin version (SWBS-M) by testing its psychometric properties in 243 cancer patients from five teaching hospitals throughout Taiwan. Construct validity was tested by factor analysis and hypothesis testing. Patients' spiritual well-being and quality of life were assessed using the SWBS-M and the McGill Quality of Life Questionnaire (MQoL), respectively. RESULTS: Overall, the SWBS-M had an internal consistency/reliability of 0.89. Exploratory factor analysis showed that the SWBS-M had an underlying two-factor structure, explaining 46.94% of the variance. SWBS-M scores correlated moderately with MQoL scores (r = 0.48, p < 0.01). Terminally ill cancer patients' spiritual well-being was inversely related to their average pain level during the previous 24 hours (r = -0.183, p = 0.006). Cancer patients' spiritual well-being also differed significantly with their experience of pain (t = -3.67, p < 0.001); terminally ill cancer patients with pain during the previous 24 hours had a lower sense of spiritual well-being than those without pain. SIGNIFICANCE OF RESULTS: Our findings support a two-factor model for the SWBS-M in terminally ill Taiwanese cancer patients. We recommend testing the psychometric properties of the SWBS-M in different patient populations to verify its factorial structure in other Asian countries.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".