Which patients with osteoarthritis of hip and/or knee benefit most from behavorial graded activity?
Bibliographic record
Abstract
Our objective was to investigate whether behavioral graded activity (BGA) has particular benefit in specific subgroups of osteoarthritis (OA) patients. Two hundred participants with OA of hip or knee, or both (clinical American College of Rheumatology, ACR, criteria) participated in a randomized clinical trial on the efficacy of BGA compared to treatment according to the Dutch physiotherapy guideline (usual care; UC). Changes in pain (Visual Analog Scale, VAS), physical functioning (Western Ontario and McMaster Universities Osteoarthritis Index, WOMAC, and McMaster Toronto Arthritis Questionnaire, MACTAR), and patient global assessment were compared for specific subgroups. Subgroups were assigned by the median split method and were analyzed using analysis of covariance. Beneficial effects of BGA were found for patients with a relatively low level of physical functioning (p?0.03). Furthermore, beneficial effects of BGA in patients with a low level of internal locus of control were marginally significant (p = .05). Patients with a relatively low level of physical functioning benefit more from BGA compared to UC. Compared to UC, BGA is the preferred treatment option in patients with a low level of physical functioning. (aut. ref.)
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".