The Chinese version of the Coronary Artery Disease Education Questionnaire-II (CADEQ-II): translation and validation
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: It is necessary to assess disease-related knowledge in patients with coronary artery disease (CAD) for tailored patient education; however there is a lack of a well-validated measurement in China. The objective of this study was to translate and validate a Chinese version of the Coronary Artery Disease Education Questionnaire-II (CADEQ-II). METHODS: The Chinese version of CADEQ-II was translated and culturally adapted. Then, it was tested for psychometric properties through a convenient sampling. Content validity was examined based on a panel of five experts. The item difficulty index and item discrimination index were calculated to assess the item difficulty and item discrimination. Internal consistency reliability was measured with the Cronbach's alpha coefficient. Criterion-related validity was established through comparing scores in patients with different education levels. Construct validity was assessed through confirmatory factor analysis (CFA). RESULTS: The Chinese version of the CADEQ-II was finalized after deleting three items and modifying two items from the original version. Three hundred and sixteen participants completed the whole questionnaire. Content validity index of the whole questionnaire was 0.87. The Cronbach's alpha coefficient of the overall questionnaire was 0.907. The significant difference of the knowledge scores among patients with different education levels supported criterion-related validity. CFA confirmed the proposed four-factorial structure of the questionnaire. CONCLUSION: The Chinese version of CADEQ-II had an acceptable reliability and validity among Chinese patients with CAD. It could be used to develop individualized health education for Chinese patients with CAD. Also, it could serve as a suitable outcome measurement to evaluate the effectiveness of education interventions related to CAD.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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 it