Effect of atrial fibrillation on quality of life (AFEQT) questionnaire: A Turkish validity and reliability study
Bibliographic record
Abstract
OBJECTIVE: This study aimed to determine the validity and reliability of the atrial fibrillation effect on quality of life (AFEQT) questionnaire and evaluate the quality of life of patients with atrial fibrillation (AF). METHODS: This was a methodological study that included 204 patients with AF over the age of 18 who participated voluntarily in the study. Data were collected using a structured questionnaire, the AFEQT questionnaire, and the University of Toronto atrial fibrillation severity scale (AFSS). The AFEQT questionnaire was translated into Turkish and presented to an expert panel, after which a pilot study was carried out with 20 patients for linguistic equivalence and cultural adaptation. The reliability of the AFEQT questionnaire was determined using Cronbach's alpha and item-total correlation coefficient analyses. RESULTS: The Cronbach's alpha value was found to be 0.91, and the scale and subscale item-total correlation values ranged from 0.36 to 0.91. The validity of the AFEQT questionnaire was determined by construct, concurrent, and discriminant validity analyses. The factor loads of the AFEQT questionnaire ranged from 0.37 to 0.94 and the ratio was χ2/df=2.43 in the confirmatory factor analysis. A negative and highly significant relationship was found in concurrent validity between the AFEQT questionnaire and the AFSS. When AF risk factors were compared with the AFEQT questionnaire, it showed that AF-related risk factors negatively affected patients' quality of life. The AFEQT questionnaire was suitable in terms of discriminant validity. CONCLUSION: The Turkish AFEQT questionnaire was found to be reliable and valid; therefore, we recommend its use to evaluate the quality of life of patients with AF.
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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 | 0.003 | 0.007 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".