Cross-Cultural Validation of the McGill Quality of Life Questionnaire-Revised (MQOL-R), Korean Version; A Focus on People at the End of Life
Bibliographic record
Abstract
Purpose: The purpose of this study was to confirm the factor structure of the McGill Quality of Life Questionnaire-Revised (MQOL-R) in the context of Korean culture and to verify its reliability and validity. Methods: The participants comprised terminal cancer patients aged 25 or older, and data from 164 participants were analyzed. The study was conducted in the following order translation, expert review, reverse translation, preliminary investigation and interviews, and completion of the final version. Confirmatory factor analysis was applied to evaluate the validity of the instrument, and the Beck Depression Inventory, Korean version (K-BDI) was applied to confirm the criterion validity of the MQOL-R Korean version. The Cronbach's alpha coefficient, representing internal consistency, was measured to evaluate reliability. Results: Cronbach's alpha for all 14 questions was 0.862. The model fit indices for confirmatory factor analysis were within the acceptance criteria. The factor loadings of all four factors were over 0.50, and convergent validity and discriminant validity were confirmed. Regarding criterion validity, a negative correlation was found between the four factors of MQOL-R Korean version and the K-BDI. Conclusion: The MQOL-R Korean version, the reliability and validity of which were verified in this study, is a 15-item tool consisting of 14 items dealing with four physical, psychological, existential, and social factors and a single item evaluating the overall quality of life. The MQOL-R Korean version is an instrument that can more concisely and effectively measure the quality of life of patients with life-threatening diseases.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".