Use of questionnaire-based outcomes for the measurement of activities and participation in the physiotherapy management of hip osteoarthritis: a review
Bibliographic record
Abstract
Physiotherapy is an important management option in hip osteoarthritis. Its effectiveness can be evaluated with the use of valid and reliable outcome measures in research and clinical practice. Numerous outcome measures for use in hip osteoarthritis are available and the ICF classification can be used to guide decision making to ensure that all aspects of human functioning are represented. The activity and participation components of ICF are a vital part of assessment, but are traditionally under-utilised in physiotherapy. A number of questionnaire-based outcomes that measure activity and participation can be used in clinical or research practice with hip osteoarthritis patients such as The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Lequense Index of Severity, Harris Hip Score (HHS), Arthritis Impact Measurement Scale (AIMS), Short Form-36 (SF-36) and European Quality of Life scale (Euroqol). These are discussed with particular reference to their psychometric properties of reliability, validity and responsiveness. To date, the WOMAC has undergone the most psychometric testing of the disease-specific measures, whilst the SF-36 is the most widely tested generic measure. Both of these measures are recommended for use in hip osteoarthritis. Further psychometric testing is required of the other measures which will enable clinicians and researchers to decide which is the most appropriate measure for use in hip osteoarthritis.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".