Translation and validation of the Western Ontario Osteoarthritis of the Shoulder (WOOS) index – the Danish version
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The Western Ontario Osteoarthritis of the Shoulder (WOOS) index is a patient-reported, disease-specific questionnaire for the measurement of the quality-of-life in patients with osteoarthritis. The purpose of this study was to describe the process used to translate the WOOS into Danish and to test the translation in a Danish population, in terms of validity, reliability, and responsiveness. MATERIAL AND METHODS: The translation of the WOOS was done according to international standardized guidelines. The psychometric properties were tested in 20 consecutive patients. The eligibility criteria were: a diagnosis of osteoarthritis without symptomatic rotator cuff pathology and treated with primary shoulder replacement. Patients were excluded only in the case of other pathology of the upper extremity or in the case of cognitive or linguistic impairment compromising the ability to complete the questionnaires. RESULTS: The Pearson's correlation coefficient between the WOOS and the Constant-Murley score (CMS), preoperatively was 0.62 (P = 0.004) and the correlation between the changes of score for the WOOS and CMS was 0.73 (P < 0.001). The correlation coefficient between the WOOS and the CMS, SF-36, and the Oxford Shoulder Score postoperatively was 0.82 (P < 0.001), 0.48 (P = 0.03), and 0.82 (P < 0.001), respectively. There were no floor and ceiling effects. The Cronbach's alpha was 0.98. The intraclass correlation coefficient between test and retest was 0.96. The standardized response mean was 1.41, and effect size was 2.32. CONCLUSION: We have shown that the Danish version of the WOOS, translated according to international standardized guidelines, has substantial statistical and clinical psychometric properties at the same level as was described for the original version.
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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 | 0.013 | 0.023 |
| 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 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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".