Factor Structure of McGill Quality of Life Questionnaire in Patients with Heart Disease: Second-order Confirmatory Factor Analysis
Bibliographic record
Abstract
Background and Objectives: The effect of heart diseases on the quality of life is the issue needs attention of health care providers. Improving quality of life is considered as the goals of rehabilitative therapies. This study conducted to evaluate the McGill Quality of Life Questionnaire in patients with heart diseases. Methods: In this cross-sectional study, 500 patients with heart diseases were recruited from BooAli Sina Hospital and Velayat Hospital affiliated with Qazvin University of Medical Sciences from May to August 2016. The participants completed the McGill Quality of Life Questionnaire. The construct validity (including convergent and discriminant validity) and Reliability using the Cronbach’s alpha, theta, and McDonaldchr('39')s Omega of the McGill Quality of Life Questionnaire were evaluated. The structure of the Questionnaire was assessed using factor analysis. Results: Three factors, including overall view of the quality of life, physical aspect, and psychological dimension, were extracted. Model fit indexes confirmed a good fit of he McGill Quality of Life Questionnaire (Comparative of Fit Index: CFI=.918, incremental fit index: IFI=.919, Adjusted Goodness of Fit Index: AGFI=.844, RMSEA=.079, Minimum Discrepancy Function by Degrees of Freedom divided: CMIN/DF=2.97, Parsimonious Normed Fit Index: PNFI=.681, Parsimonious Comparative Fit Index: PCFI=.709). Convergent and divergent validity, internal consistency, and construct reliability of the questionnaire were confirmed. Conclusion: The findings revealed that the three-factor model of the McGill Quality of Life Questionnaire has satisfactory validity and reliability. Thus, this questionnaire can be used in future studies to assess the quality of life of patients with heart 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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".