HINDI TRANSLATION, CROSS CULTURAL ADAPTATION, VALIDATION AND TEST RE-TEST RELIABILITY OF CHEDOKE MCMASTER STROKE ASSESSMENT(CMSA) SCALE: A CROSS-SECTIONAL STUDY
Bibliographic record
Abstract
This Data Contain Hindi translation, cross cultural adaptation , validation and test retest reliability of Chedoke McMaster stroke Assessment scale Stroke is one of the leading causes of death and long-term disability worldwide, emphasizing the need for effective rehabilitation strategies. CMSA is a reliable and valid measure developed in Canada. The widespread use of Hindi, there is no Hindi translation of the CMSA. Developing a culturally and linguistically appropriate version of the CMSA for Hindi speakers could enable rehabilitation personnel to evaluate change in the patient’s motor control and functional ability. This study translated and adapted the CMSA into Hindi for effective stroke assessment in Hindi-speaking patients. We obtained permission from the original author of the CMSA to translate the tool into Hindi. The translation process adhered to recognized guidelines for cross-cultural adaptation. Two bilingual experts, one with a medical background and the other a linguistic specialist, independently translated the CMSA into Hindi. The translations were combined and back-translated into English by independent translators to ensure consistency with the original tool. To ensure content validity, we used the Delphi method to assess the relevance of each item in the scale. The experts evaluated each item on a 4-point scale, and the Item-Level Content Validity Index (I-CVI) and Scale-Level Content Validity Index Average (S-CVI/Ave) were calculated. 51 stroke patients were chosen using a suitable sample technique based on the selection criteria in order to estimate concurrent validity and test re-test reliability. The content validation process demonstrated a high degree of linguistic and cultural equivalence. The Hindi CMSA achieved an I-CVI of 0.98985, an S-CVI/Ave of 0.98985, and an S-CVI/UA of 0.881944, indicating strong evidence of its validity. Reliability results demonstrated Cronbach's alpha 0.999 and ICC 0.998 values were calculated for test-retest reliability The results were analysed, evaluated, and compared using the statistical software package for social sciences (SPSS) version 20.0, with a total of 51 participants assessed for the study. The normality of the data was assessed using the Shapiro-Wilk Test. During the comprehensive assessment of test-retest reliability, Spearman's ρ yielded a remarkable value of 0.998, indicating a high degree of This study evaluated that there was strong relationship showed by the spearmen rho value that was 0.998 along with 0.000 P value. The Hindi CMSA has been culturally adapted and validated for evaluating stroke-related impairments and functional activity in Hindi-speaking healthcare environments. This study gave a strong evidence which proves Hindi version of CMSA is Highly reliable and valid. This version will enhance the ability of rehabilitation personnel in conducting clinical assessments and customizing rehabilitation strategies for this population
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".