Evaluating Responsiveness of the Persian Version of the Western Ontario Meniscal Evaluation Tool (WOMET) in Iranian Patients with Meniscal Injury
Bibliographic record
Abstract
Abstract Background This study aimed to evaluate the responsiveness of Western Ontario Meniscal Evaluation Tool (WOMET) and specify its Minimal Clinically Important Difference (MCID) in patients undergoing physiotherapy intervention following undergoing a meniscal lesion or surgery. Our hypothesis was that the WOMET would have adequate responsiveness in patients with meniscal injury. method: 100 patients undergoing physiotherapy interventions filled the Persian version of the WOMET and a questionnaire of the Knee injury and Osteoarthritis Outcome Score (KOOS) at Session 1 and Session 10 (4 weeks later). They also filled the 7-point Global Rating of Change (GRC) scale at Session 10. Internal responsiveness was calculated using T test and effect sizes (standard response mean (SRM) and Cohen's d); and external responsiveness was calculated via receiver operating characteristic curve and correlation analysis. The inclusion criterion was the age of 18 to 70 years old for the patients who had the ability of filling the questionnaire. The exclusion criteria included ligaments injury, severe osteoarthritis, inability to complete the questionnaire due to the lack of sufficient knowledge, malignancy, infection, neuromusculoskeletal disorder, rheumatologic disease, knee surgeries for any other reasons, and dissatisfaction for being enrolled in the study. Results All the WOMET subscales (AUC = 0.7) had acceptable external responsiveness. SRM was Trivial, and the scores of Cohen’s d were moderate to large and t tests showed significant differences. Conclusion Our findings showed that all of the WOMET subscales had acceptable external responsiveness, and thus this questionnaire could be used to study the effects of physiotherapy interventions on patients undergoing a meniscal lesion or surgery.
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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 | 0.017 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".