A Shortened Version of the Western Ontario Rotator Cuff Disability Index: Development and Measurement Properties
Bibliographic record
Abstract
PURPOSE: The objective of this study was to develop and examine the measurement properties of a shortened version of the Western Ontario Rotator Cuff Index (WORC), the SHORTWORC, in individuals with rotator-cuff pathology. METHODS: The study occurred in two stages, both using secondary analysis of existing data sets. The first stage used cross-sectional data from candidates for rotator-cuff surgery to develop the SHORTWORC. The second stage examined various measurement properties of the SHORTWORC by analyzing scores from the WORC, the American Shoulder and Elbow Surgeons questionnaire, and the Constant-Murley score obtained from patients before and after rotator-cuff surgery. Approaches to validating the SHORTWORC included calculating the standard error of measurement (SEM) at an instant in time, performing a confirmatory factor analysis, correlating findings among the questionnaires, and examining differences between men and women. Sensitivity to change was investigated using standardized response mean and relative efficiency. RESULTS: Data for 712 patients were used to develop the SHORTWORC, the final version of which consisted of 7 questions. Data for 166 patients (86 men, 80 women; mean age 57±11 years) were used for validation. The SEM based on internal consistency (SEMIC) was calculated as 7.43 SHORTWORC points. The SHORTWORC had similar convergent validity (r=0.72-0.82) and sensitivity to change (SRM=1.20 vs. 1.25, p>0.05) to the longer version. The relative efficiency of the SHORTWORC was 3.19 times that of the WORC (95% CI, 1.50-71.51) in discriminating men's from women's level of disability. CONCLUSIONS: The SHORTWORC has indicators of validity, relative efficiency, and sensitivity to change comparable to those of the original version but has a smaller response burden. The SHORTWORC has indicators of validity, relative efficiency, and sensitivity to change comparable to those of the original version but has a smaller response burden.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".