The psychometric properties of the Turkish version of Myocardial Infarction Dimensional Assessment Scale (MIDAS)
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to describe the psychometric properties of the Myocardial Infarction Dimensional Assessment Scale (MIDAS). METHODS: This is a methodological cultural adaptation study. The MIDAS consists of 35-items covering seven domains: physical activity, insecurity, emotional reaction, dependency, diet, concerns over medication, and side effects which are rated on a five-point Likert scale from 1: never to 5:always. The highest score of MIDAS is 100.Quality of life (QOL) decreases as the score of scale increases. Overall 185 myocardial infarction (MI) patients were enrolled in this study. Cronbach alpha was used for the reliability analysis. The criterion validity, structural validity, and sensitivity analysis approach was used for validity analysis. New York Heart Association (NYHA) and the Canadian Cardiovascular Society Functional Classifications (CCSFC) for testing the criterion validity; SF-36 for construct validity testing of the Turkish version of the MIDAS were used. RESULTS: The range of Cronbach alpha values is 0.79-0.90 for seven domains of the scale. No problematic items were observed for the entire scale. Medication related domains of the MIDAS showed considerable floor effects (35.7%-22.7%). Confirmatory Factor analysis indicators [Comparative Fit Index (CFI) =0.95 and Root Mean Square Error of Approximation (RMSEA) =0.075] supported the construct validity of MIDAS. Convergent validity of the MIDAS was confirmed with correlation of SF-36 scale where appropriate. Criterion validity results was also satisfactory by comparing different stages of the NYHA and the CCSFC (p<0.05). CONCLUSION: Overall results revealed that Turkish version of the MIDAS is a reliable and valid instrument.
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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 | 0.005 | 0.021 |
| 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) | 0.002 | 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".