Effects of group-based versus individual physical exercise programs for knee osteoarthritis: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: Knee osteoarthritis (OA) is the most common joint disease worldwide and is associated with a high rate of disability and poor quality of life. However, little is known about the therapeutic effects of group-based versus individual-based physical exercise protocols. Objective: To investigate the effects of individual versus group-based physical exercises on pain intensity and functional outcomes in people with knee OA. Methods: MEDLINE/PubMed, Cochrane, EMBASE, and PEDro databases were searched from the earliest date available to July 2023. Study quality was evaluated using the PEDro scale. Mean difference (MD), standardized mean difference (SMD), and 95% confidence interval (CI) were calculated using a random effect model. Results: Six studies, with 763 patients, met the study criteria. Group-based physical exercises improved pain intensity (VAS 0-100) MD -17.2 (95% CI: -22.2 to -12.3), the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale MD -0.54 (95% CI: -1.0 to -0.08), WOMAC function subscale MD -2.1 (95% CI: -4.1 to -0.08) compared to individual modality. No significant difference regarding muscle strength and exercise tolerance was found for participants in the group-based physical exercises compared with individual physical ones. Conclusion: Group-based physical exercise was more successful in reducing pain intensity and functional impairment in patients with knee OA than individual exercise programs. Both group-based and individual physical exercise programs enhanced muscle strength and 6-minute walk distance.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.036 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".