Cross-cultural adaptation, validity and reliability of the Persian translation of the Western Ontario Shoulder Instability Index (WOSI)
Bibliographic record
Abstract
Abstract Purpose The Western Ontario Shoulder Instability Index (WOSI) is the most commonly used patient-reported outcome measure to record the quality of life in patients with shoulder instability. The current study aimed to translate the WOSI into the Persian language and evaluate its psychometric properties. Methods The translation procedure of the WOSI was performed according to a standard guideline. A total of 52 patients were included in the study and responded to the Persian WOSI, Oxford shoulder score (OSS), Oxford shoulder instability score (OSIS), and disabilities of arm, shoulder and hand (DASH). A sub-group of 41 patients responded for the second time to the Persian WOSI after an interval of 1–2 weeks. The internal consistency, test–retest reliability using intraclass correlation coefficient (ICC), measurement error, minimal detectable change (MDC), and floor and ceiling effect were analyzed. The hypothesis testing method was used to assess construct validity by calculating Pearson correlation coefficient between WOSI and DASH, OSS, and OSIS. Results Cronbach's alpha value was 0.93, showing strong internal consistency. Test–retest reliability was good to excellent (ICC = 0.90). There was no floor and ceiling effect. The standard error of measurement and MDC were 8.30% and 23.03%, respectively. Regarding construct validity, 83.3% of the results agreed with hypotheses. High correlations were observed between WOSI and DASH, OSS and OSIS (0.746, 0.759 and 0.643, respectively) indicating excellent validity for the Persian WOSI. Conclusion The current study results demonstrated that the Persian WOSI is a valid and reliable instrument and can be used in the clinic and research for Persian-speaking 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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".