Psychometric Properties and Factorial Analysis of the Arabic McGill-QoL Questionnaire in Breast Cancer
Bibliographic record
Abstract
Purpose: This study aimed to assess the psychometric properties of the Arabic McGill Quality of Life Questionnaire-Revised (MQOL-R) in breast cancer survivors. Patients and Methods: One-hundred-forty breast cancer survivors were recruited and completed the questionnaire. The construct validity was assessed using confirmatory factor analysis (CFA). MQOL-R scores were correlated with Global Health Status/QoL and functional subscales of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (EORTC QLQ-C30) for convergent validity. Reliability was estimated using Cronbach's alpha and intraclass correlation coefficients (ICC). Results: CFA reproduced a four-factor model (ie, physical, psychological, existential, and social) with good fit indices (comparative fitting index = 0.980; root mean square error of approximation = 0.091), with all items significantly loading on their respective subscales. The total MQOL-R scores were correlated with the global health status/QoL and functional subscales of the EORTC QLQ-C30 (r = -0.172, P < 0.01). Known-group validity was proven by different MQOL-R scores according to functional status (50.62 ± 6.35 vs 45.98 ± 7.19, P < 0.01). Reliability was supported by good internal consistency and high test-retest correlation coefficients for the Arabic MQOL-R and its subscales (ICC range, 0.83-0.95). Conclusion: The Arabic MQOL-R demonstrated adequate construct validity, factor structure, excellent test-retest reliability, and good internal consistency. This tool is valuable for assessing the quality of life in research and physical therapy rehabilitation settings among Arabic-speaking breast cancer survivors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".