Validation of the Comprehensive ICF Core Set for Osteoarthritis (OA) in patients with knee OA: a Singaporean perspective.
Bibliographic record
Abstract
OBJECTIVE: To evaluate content validity and construct validity of the International Classification of Functioning, Disability and Health (ICF) Comprehensive Core Set for Osteoarthritis (OA) in Singapore. METHODS: Patients with knee OA completed case report forms, which included the SF-36, Self-administered Comorbidity Questionnaire (SCQ), and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Health professionals completed the ICF Comprehensive Core Set for OA. Content validity was evaluated using frequency and percentage of patients with a reported problem for each ICF category, while construct validity was evaluated using Spearman correlation between the ICF categories and SF-36 and the WOMAC. RESULTS: A consecutive sample of 122 patients completed this study. In body functions, 12 categories were documented as a problem by more than 10% of the patients, of which 7, 12, and 10 categories correlated significantly with the SF-36 Physical Component Summary (PCS), WOMAC pain, and physical function, respectively. Only s750 (Structure of lower extremity) in body structures was reported as a problem and correlated significantly with SF-36 and WOMAC. In activities and participation, 12 categories were reported as a problem by more than 10% of the patients, of which, 11, 11, and 12 correlated significantly with SF-36 PCS, WOMAC pain, and physical function, respectively. In environmental factors, 2 and 14 categories were documented as barrier and facilitator, respectively, by more than 10% of the patients, but none correlated significantly with SF-36 and WOMAC. CONCLUSION: The content and construct validity of the Comprehensive Core Set for OA could be supported. Some categories, especially in environmental factors, need to be studied further in different sociocultural contexts.
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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 | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".