Effect of Digital Exercise Therapy on the Pain and Physical Function of Patients With Osteoarthritis: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Osteoarthritis (OA) is a chronic degenerative bone and joint disease that significantly impacts patients' quality of life and mental health, while also imposing a substantial economic burden on society. However, access to rehabilitation for patients with OA is challenging upon hospital discharge. Digital exercise therapy represents a promising telemedicine strategy for enhancing the management of OA, but its effect on OA is not yet clear. OBJECTIVE: This study aimed to systematically evaluate the therapeutic effects of digital exercise therapy on pain and physical function in patients with OA. METHODS: Databases including PubMed, Embase, Cochrane Library, Web of Science, and SPORTDiscus were searched for randomized controlled trials on using digital exercise therapy for OA until October 25, 2023. The primary outcomes included the measures of pain scores or physical function scores immediately after the intervention and at full follow-up. The risk of bias was evaluated using the Physiotherapy Evidence Database scale. Relevant data were extracted, and a meta-analysis was performed using RevMan5.3 software (Cochrane Collaboration). RESULTS: A total of 9 studies with 1604 patients were included in the final meta-analysis. Compared with the conventional treatment group, digital exercise therapy significantly reduced numerical rating scale pain scores (mean difference [MD]=-1.07, 95% CI -1.35 to -0.78; P<.001) and Western Ontario and McMaster Universities Osteoarthritis Index physical function scores (MD=-2.39, 95% CI -3.68 to -1.10; P<.001) in patients with OA immediately after the intervention. However, follow-up results revealed no statistically significant difference in numerical rating scale pain scores (MD=-0.20, 95% CI -0.59 to 0.20; P=.34), while Western Ontario and McMaster Universities Osteoarthritis Index physical function scores showed a significant improvement in the digital exercise therapy group compared with the control group (MD=-1.89, 95% CI -3.52 to -0.26; P=.02). These findings suggest that digital exercise therapy provides immediate benefits for both pain and physical function in patients with OA, with sustained improvements in physical function observed during follow-up, though pain relief may not persist long term. CONCLUSIONS: Digital exercise therapy can alleviate the pain and improve the physical function in patients with OA and can be used as an auxiliary means in the rehabilitation treatment of OA. It provides great convenience for patients with OA who need long-term treatment, allowing them to exercise at home for rehabilitation training. TRIAL REGISTRATION: PROSPERO CRD42023484819; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023484819.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.031 |
| 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 | 0.002 | 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".