An Evaluation of the Responsiveness and Discriminant Validity of Shoulder Questionnaires among Patients Receiving Surgical Correction of Shoulder Instability
Bibliographic record
Abstract
Health-related quality-of-life (HRQL) measures must detect clinically important changes over time and between different patient subgroups. Forty-three patients (32 M, 13 F; mean age = 26.00 ± 8.19 years) undergoing arthroscopic Bankart repair completed three validated shoulder questionnaires (Western Ontario Shoulder Instability index (WOSI), American Shoulder and Elbow Surgeons Standardized Shoulder Assessment form (ASES), Constant score) preoperatively, and at 6, 12, and 24 months postoperatively. Responsiveness and discriminant validity was assessed between those with a satisfactory outcome and those with (1) a major recurrence of instability, (2) a single episode of subluxation, (3) any postoperative episode of instability. Eight (20%) patients reported recurrent instability. Compared to baseline, the WOSI detected improvement at the 6- (P < 0.001) and 12-month (P = 0.011) evaluations. The ASES showed improvement at 6 months (P = 0.003), while the Constant score did not report significant improvement until 12 months postoperatively (P = 0.001). Only the WOSI detected differential shoulder function related to shoulder instability. Those experiencing even a single episode of subluxation reported a 10% drop in their WOSI score, attaining the previously established minimal clinically important difference (MCID). Those experiencing a frank dislocation or multiple episodes of subluxation reported a 20% decline. The WOSI allows better discrimination of the severity of postoperative instability symptoms following arthroscopic Bankart repair.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".