Translation, cultural adaptation, and validation of the duke activity status index in the hindi language
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Bibliographic record
Abstract
Background: The Duke Activity Status Index (DASI) is a validated questionnaire in English to assess the functional capacity (FC) of patients with cardiovascular disease (CVD). Aim: The aim of the study is to translate, cross-culturally adapt, and validate the DASI in Hindi. Settings and Study Design: Observational validation study. Methodology: Different translators translated the DASI into Hindi and then back-translated it into English. Validation for feasibility and psychometric properties of translated questionnaire was done on 200 adults, Hindi-speaking patients with CVD, who were advised exercise testing by a cardiologist. Statistical Analysis: Internal consistency (Cronbach's α) and test-retest reliability (Pearson's correlation coefficient) were calculated. Construct (correlation with the Canadian Cardiovascular Society Classification [CCSC] for angina and exercise capacity with treadmill testing [TMT]) and content validity (time taken to fill the questionnaire, ease of understanding the questionnaire items, and comprehensibility) were calculated.P < 0.05 was considered significant. Results: The Cronbach's α for internal consistency was 0.78, which indicates adequate relatedness among the items of questionnaire, and the test-retest reliability was 0.65 (P < 0.05). A significant correlation between CCSC (r = -0.60) and TMT (r = 0.56) was found. The median time taken by the respondents to fill the questionnaire was 4 min. Of all the respondents, 95.74% of the respondents agreed that the Hindi questionnaire was easy to comprehend and 97.87% patients correlated the translated items to their daily physical activity. Conclusions: The Hindi translated and culturally adapted version of the DASI is reliable, valid, and feasible to assess the FC in the Hindi-speaking CVD patients.
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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 | 0.000 | 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