The reliability and validity assessment of western Ontario and McMaster university osteoarthritis index scale applied with Kashin-Beck disease
Bibliographic record
Abstract
Objective To evaluate the applicability of western Ontario and McMaster university osteoarthritis index (WOMAC) on Kaschin-Beck disease (KBD). Methods Clinical degree I adult patients with KBD came from Yongshou and Linyou Counties in Shaanxi Province were investigated according to the historical diagnostic data andThe Diagnosis Standard of Kashin-Beck Disease (GB 16003-1995), exclusion of other chronic diseases. Reliability of WOMAC was measured by retest reliability, 1/2 coefficient and Cronbach'α reliability coefficient analysis; validity of the WOMAC was tested by the principal components, factor analysis and correlation analysis methods. Results Totally 200 adults patients with KBD were investigated, and 177 effective questionnaires were taken back (88.5%). Retest reliability was 0.754-0.853, 1/2 coefficient was 0.886-0.971, and Cronbach'α reliability coefficient was 0.878-0.956. In three dimensions of WOMAC scale extracted a common factor, the cumulative variance contribution rate was 81.238% through principal component factor. The pearson correlation coefficient between all items score of WOMAC and scale score and total score of WOMAC was more than 0.600. The differences of WOMAC score were not statistically significant in different ages, different grading of adult KBD patients (all P > 0.05). Conclusion WOMAC scale used in KBD has good validity and reliability, but has low degree of differentiation. Key words: Reliability; Validity; Kashin-Beck disease
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".