Translation, adaptation and measurement properties of an electronic version of the Danish Western Ontario Shoulder Instability Index (WOSI)
Bibliographic record
Abstract
Objectives To translate and adapt the Western Ontario Shoulder Instability (WOSI) questionnaire into Danish and, to evaluate measurement properties of an electronic Danish WOSI version. Methods The Swedish WOSI version was used for translation and adaptation into Danish followed by examination of test-retest reproducibility (14-day interval) besides concurrent and construct validity. Concurrent validity was examined by comparing WOSI in paper version with an electronic version, whereas construct validity was examined by comparing WOSI with Numeric Pain Rating Scale (NPRS) and the Oxford Shoulder Score (OSS). Reproducibility was evaluated with Intraclass correlations (ICC), Standard Error of Measurement (SEM), minimal detectable change (MDC) and limits of agreement (LOA). Validity was evaluated with Pearson’s ( r) and Concordance Correlation Coefficients (CCC). Results 41 subjects (median age 34, range 18–57) were included in the analysis of reproducibility. An ICC of 0.97 (95% CI 0.95 to 0.99) for the total WOSI score was found. SEM was 100.1, resulting in an MDC of 277.5 and LOAs within the range of -246.4 and 308.6. 25 subjects (median age 34, range 18–72) were included in the analysis of concurrent validity obtaining a CCC of 0.96 (95% CI 0.91 to 0.98). Construct validity was investigated in 62 subjects (median age 31, range 18–72) obtaining correlations of 0.83 (95% CI 0.68 to 0.97) (NPRS) and 0.79 (95% CI 0.62 to 0.94) (OSS). Conclusions An electronic Danish version of WOSI presented excellent test-retest reproducibility and acceptable measurement errors. Also, concurrent validity between paper and electronic version was highly satisfactory as was the construct validity. Surprisingly, though, the NPRS correlated more with WOSI than OSS.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".