The development of a short measure of physical function for hip OA HOOS-Physical Function Shortform (HOOS-PS): an OARSI/OMERACT initiative
Bibliographic record
Abstract
OBJECTIVE: To derive a cross-culturally valid, short measure of physical function using function subscales (daily living and sports and recreation) of the Hip disability and Osteoarthritis Outcome Score (HOOS). METHODS: Rasch analysis was conducted on data from individuals from multiple countries who had hip osteoarthritis (OA). Fit of the data to the Rasch model was evaluated by model chi(2) and item fit statistics (chi(2), size of residual, and F-test). Differential item functioning was evaluated by gender, age and country. Unidimensionality was evaluated by factor analysis of residuals. Individual data sets were analyzed and data pooled and re-analyzed for fit to the model. Regression modeling was conducted to derive a nomogram converting raw summed scores to Rasch derived interval scores. RESULTS: Seven data sets were included (n=2991), ages 19-96 years, male/female ratio was 1:1.23. The final model included five HOOS items. From the easiest to most difficult, the items (logit) were as follows: sitting (1.832), descending stairs (0.729), getting in/out of bath or shower (0.255), twisting/pivoting on loaded leg (-0.221) and running (-2.595). The separation index was 0.80. CONCLUSION: The daily activity and sports and recreational items of the HOOS were reduced to five items achieving a feasible, short measure of physical function with interval level properties. This tool has potential for use as the function component of an OA severity scoring system. Further testing of this measure is warranted.
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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 | 0.007 | 0.008 |
| 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 | 0.000 |
| 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 | 0.001 |
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".