Evaluating the reproducibility of the short version of the Western Ontario Rotator Cuff Index (Short-WORC) prospectively
Bibliographic record
Abstract
Background Recently, a shorter version of the Western Ontario Rotator Cuff Index (Short-WORC) was created to reduce patient response burden. However, it has yet to be evaluated prospectively for reproducibility (reliability and agreement) and floor and ceiling effects. Methods Patients (N = 162) with rotator cuff disorders completed the Short-WORC at baseline. From this cohort, 47 patients underwent measurement of test-retest reliability within 2 to 7 days. We used the Cronbach α to determine internal consistency and the intraclass correlation coefficient (ICC 2,1 ) to assess test-retest reliability. To evaluate parameters of agreement, the standard error of measurement, minimal detectable change (based on a 90% confidence interval), and Bland-Altman plots were used. Results The Cronbach α was 0.82 at baseline, and the intraclass correlation coefficient (ICC 2,1 ) was 0.87. The agreement parameter was 8.4 for the standard error of measurement of agreement, and the limits of agreement fell within the range of –22.9 to 23.8. The Short-WORC is reliable over time and reflective of a patient's true score after an intervention. Conclusions The Short-WORC demonstrated strong reproducibility parameters and can be used for patients with rotator cuff disorders. The Short-WORC indicated no systematic bias and was reflective of the true score of both individual patients and groups of patients at 2 time points.
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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 | 0.016 | 0.041 |
| 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 | 0.001 |
| 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".