A functional difficulty and functional pain instrument for hip and knee osteoarthritis
Bibliographic record
Abstract
INTRODUCTION: The objectives of this study were to develop a functional outcome instrument for hip and knee osteoarthritis research (OA-FUNCTION-CAT) using item response theory (IRT) and computer adaptive test (CAT) methods and to assess its psychometric performance compared to the current standard in the field. METHODS: We conducted an extensive literature review, focus groups, and cognitive testing to guide the construction of an item bank consisting of 125 functional activities commonly affected by hip and knee osteoarthritis. We recruited a convenience sample of 328 adults with confirmed hip and/or knee osteoarthritis. Subjects reported their degree of functional difficulty and functional pain in performing each activity in the item bank and completed the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Confirmatory factor analyses were conducted to assess scale uni-dimensionality, and IRT methods were used to calibrate the items and examine the fit of the data. We assessed the performance of OA-FUNCTION-CATs of different lengths relative to the full item bank and WOMAC using CAT simulation analyses. RESULTS: Confirmatory factor analyses revealed distinct functional difficulty and functional pain domains. Descriptive statistics for scores from 5-, 10-, and 15-item CATs were similar to those for the full item bank. The 10-item OA-FUNCTION-CAT scales demonstrated a high degree of accuracy compared with the item bank (r = 0.96 and 0.89, respectively). Compared to the WOMAC, both scales covered a broader score range and demonstrated a higher degree of precision at the ceiling and reliability across the range of scores. CONCLUSIONS: The OA-FUNCTION-CAT provided superior reliability throughout the score range and improved breadth and precision at the ceiling compared with the WOMAC. Further research is needed to assess whether these improvements carry over into superior ability to measure change.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".