Longitudinal comparison of the Health Assessment Questionnaire (HAQ) and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC)
Bibliographic record
Abstract
OBJECTIVE: To compare the measurement properties of the generic Health Assessment Questionnaire (HAQ) and the disease-specific Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). METHODS: Physical function, pain, and radiographic progression were assessed in knee or hip osteoarthritis patients (n = 271) who had 2 radiographs that were at least 6 months apart from 6 ARAMIS (Arthritis, Rheumatism, and Aging Medical Information System) databanks. Data were compared at baseline and after a mean of 3.2 (SE 0.10) years. Correlation coefficients and standardized effect sizes (SES) were used to assess their relationship and responsiveness. RESULTS: The majority of items in the 2 function and pain scales overlapped and were highly and significantly correlated with each other at baseline and last assessments (function at baseline rs = 0.71 and function at last assessment rs = 0.79, P < 0.0001; pain at baseline rs = 0.70 and pain at last assessment rs = 0.76, P < 0.0001). The HAQ disability index and total knee score were more sensitive to detection of disease progression than the WOMAC (SES for HAQ = 0.27; SES for WOMAC = -0.05). CONCLUSION: Both instruments showed favorable measurement properties, with the HAQ having the advantages of being more sensitive to change and adaptable to a wide variety of diseases and conditions, which contribute to the generalizability of findings.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".