Comparison of the responsiveness of the Brazilian version of the Western Ontario Rotator Cuff Index (WORC) with DASH, UCLA and SF-36 in patients with rotator cuff disorders.
Bibliographic record
Abstract
OBJECTIVE: To investigate the responsiveness of the Brazilian version of the Western Ontario Rotator Cuff Index (WORC) and compare it with the Disabilities of Arm, Shoulder and Hand questionnaire (DASH), the University of California Los Angeles Shoulder Rating Scale (UCLA), and the Short-Form 36 questionnaire (SF-36) in patients with rotator cuff disorders. METHODS: The four questionnaires were administered to 30 patients at baseline and 3 months after treatment (physiotherapy or surgery). The patients were divided into two groups: those who improved after treatment (n=20) and those who did not (n=10) based on an anchor-based strategy to distinguish between the two groups and assess responsiveness. The t-test, the t-value of the paired t-test, the effect size (ES), and the standardized response mean (SRM) were calculated. RESULTS: All four questionnaires registered statistically significant changes (p<0.05) in the "improved" group between baseline and 3 months after treatment, and no changes in patients who did not improve. All four instruments showed higher ES and SRM values for the patients who improved than those who did not. WORC registered moderate to high ES and SRM values for the "improved" group, as did the UCLA and DASH. The ES and SRM values measured by the SF-36 ranged from small to large, the physical subscales being more responsive than the other subscales. CONCLUSION: The Brazilian version of the WORC (like UCLA, DASH and SF-36 physical subscales) proved responsive to change and suitable for use in the short-term follow-up of patients after rotator cuff interventions.
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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 | 0.006 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".