The Iranian version of Angina Pectoris characteristics questionnaire: reliability assessment
Bibliographic record
Abstract
AIMS: To evaluate internal consistency and test-retest reliability of the Iranian version of the Angina Pectoris characteristics questionnaire. BACKGROUND: To evaluate symptoms in patients with Angina Pectoris, the Iranian version of the Angina Pectoris characteristics questionnaire was created by combining items from Modified Rose Questionnaire, Short Form-McGill Questionnaire and the Accompanying Symptom Checklist. The Angina Pectoris characteristics questionnaire has been developed and validated recently although it required assessment of its reliability. DESIGN: Reliability study using test and retest. METHOD: One hundred and ten coronary heart disease patients with Angina Pectoris were included. The test-retest reliability of the instrument was estimated for measurement after 15 days. RESULT: The analysis of the result indicated that internal consistency was found adequate at both assessments (Cronbach's alpha = 0.65) for test and retest. There was no significant difference between test and retest. The intra-class correlation coefficient ranged from 0.76-0.98. CONCLUSION: The Angina Pectoris characteristics questionnaire is a reliable instrument for the assessment of Angina Pectoris characteristics in a Persian population. RELEVANCE TO CLINICAL PRACTICE: The Angina Pectoris characteristics questionnaire can be used with confidence in Iranian coronary heart disease patients for Assessing Angina Pectoris symptom.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".