Cross-cultural adaptation, validation and responsiveness of the Persian version of Western Ontario shoulder instability index questionnaire in Persian patients with shoulder instability
Bibliographic record
Abstract
Introduction To translate, cross-culturally adapt, and psychometric testing the Western Ontario Shoulder Instability index (WOSI) into PersianMethods Seventy-two patients diagnosed with shoulder instability participated in reliability, construct validity, and responsiveness analysis. All the patients filled out the WOSI with an interval of two weeks to assess reliability. The shortened Disability of Arm, Shoulder and Hand (Quick-DASH), Shoulder Pain and Disability Index (SPADI), and the 36-Item Short-Form Survey (SF-36) were assessed to evaluate construct validity. In order to assess responsiveness patients filled out WOSI before and after the physiotherapy and global rating of change scale at last session of physiotherapy. Reliability was assessed by intra-class correlation coefficient (ICC (1,2)), construct validity by two tailed Pearson (r), and responsiveness by longitudinal validity and receiver operating characteristics (ROC) curve analysis.Results The ICC (1,2) was 0.90 and correlation analysis revealed high level of correlation with: Quick-DASH (r = 0.82); SPADI (r = 0.72); physical SF-36 (r = −0.52); and mental SF-36 (r = −0.48). Responsiveness analysis demonstrated the area under curve was 0.90, with minimal clinical important difference 46.87.Conclusion We found the Persian-WOSI as a valid, reliable, and responsive questionnaire to evaluate quality of life of patients with shoulder instability.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".