The Degree of Shoulder Involvement in Sports (DOSIS) scale is a valid and responsive instrumentation for shoulder assessment in patients after surgery for anterior instability
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to evaluate validity and responsiveness of the Degree of Shoulder Involvement in Sport (DOSIS) scale. METHODS: A web-based survey was developed to test the construct validity of the DOSIS scale. Fifty-three patients with a median age of 33 years (range 17-59) were included in the study. Convergent validity was evaluated by external correlation (Spearman's rank correlation coefficient, r) of the DOSIS with the Brophy-Marx and Tegner activity scales, the Western Ontario shoulder instability index (WOSI), the Simple Shoulder Test (SST), and the Short-Form 36 (SF-36). Responsiveness was analysed by relative efficiency calculation of the DOSIS versus the Brophy-Marx and Tegner activity scales. RESULTS: The DOSIS showed strong correlation with the Brophy-Marx and Tegner activity scales, a moderate correlation with the WOSI and SST scores, and a moderate correlation with the physical functioning, role physical and role emotional subscores of the SF-36. The distribution of the DOSIS scores had no serious ceiling or floor effects. The DOSIS demonstrated lesser responsiveness when compared to the Brophy-Marx and Tegner activity scales. CONCLUSION: The DOSIS showed an adequate validity and responsiveness. The clinical relevance of this study is that the DOSIS scale can be used for sport-specific shoulder assessment in patients after surgery for anterior instability. LEVEL OF EVIDENCE: III.
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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 | 0.003 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".