Comparative assessment of a virtual performance measure with self-report and performance-based outcomes in patients with hip osteoarthritis
Bibliographic record
Abstract
BACKGROUND: The purposes of this study were to examine the reliability and factorial and convergent validity of a virtual performance measure (VPM) in patients with osteoarthritis (OA) of the hip joint and to compare the known-group validity of the VPM with traditional self-report and performance-based outcomes. METHODS: The VPM score was based on the results of 10 videos showing increasing difficulty in performing specific functional tasks. Patients were requested to choose the video that best reflected their own level of function. Clinical presentation and radiological findings were documented. Self-report measures were the lower extremity functional score (LEFS) and pain scale. The performance-based measures were the 30- second Chair Stand Test (CST) and the 40-meter fast paced walk test (40 m FPWT) test. RESULTS: Data of 100 patients, 64 (64%) females, mean age: 67 ±10 were examined. The Cronbach's alpha coefficient that examined internal consistency of the VPM total score was 0.88. Factor analysis showed two distinct domains. Moderate correlations were observed between the VPM total score and the LEFS, pain score, and 40 m FPWT (r > 0.50). The VPM and the LEFS were able to differentiate between candidates and non-candidates for hip arthroplasty and between those with and without assistive walking devices. There was no statistically significant difference between the overall accuracy of the VPM and LEFS in the area under the curve value (0.72 vs. 0.71) with respect to candidacy for surgery. CONCLUSIONS: This study provides substantial evidence towards the validity and reliability of the VPM outcome measure in patients with moderate to severe OA of the hip joint. Digitally based outcome measures have the potential of enhancing remote measurement of functional difficulties in specific situations. CLINICAL TRIAL NUMBER: Not applicable.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".