Cross-cultural Psychometric Evaluation of the Dutch McGill-QoL Questionnaire for Breast Cancer Patients.
Bibliographic record
Abstract
AIM OF THE STUDY: Assessing the cross-cultural psychometric properties of the Dutch-MQoL for breast cancer patients. METHODS: 26 patients were recruited at the Antwerp University Hospital. Eligible patients filled in the MQoL on different moments in time in order to evaluate clinimetric properties. To determine the validity; MQoL was correlated to the EORTC QLQ-C30. Internal consistency was analysed using Cronbach's and test-retest reliability was determined by ICC. For statistical responsiveness, S.E.M and MDC were calculated. RESULTS: A strong correlation was found between the 'QoL score' of the MQoL and the domain 'existential well- being' of the EORTC QLQ-C30 (r = 0.72). An excellent test-retest reliability (ICC (1,1)) was demonstrated with intraclass coefficients ranging from 0.82 to 0.92. A MDC in total score of only 1.22 (12%) was seen, needed to detect a factual change within a patients' QoL. Psychometric properties of the Dutch MQoL were found comparable to the properties of the original questionnaire. CONCLUSION: The Dutch version of the MQoL is a valid and reliable questionnaire for breast cancer patients and shows statistical responsiveness. Due to the strong to excellent reliability, this version of the MQoL is useful in clinical as well as scientific setting.
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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 | 0.006 | 0.018 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".