Effects of the computer-assisted rehabilitation environment on patient rehabilitation: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Computer-assisted rehabilitation environment (CAREN) integrates virtual reality, motion capture systems, and real-time feedback mechanisms to enhance patient rehabilitation results. This study aimed to determine the potential benefit of CAREN in increasing balance, cognition, and mental health in patients with neurological and musculoskeletal disorders. Methods Systematic searches were carried out across PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), and Web of Science databases for relevant studies published up to November 2025. The review comprised randomized, non-randomized controlled trials and single-arm studies evaluating the rehabilitative outcomes of CAREN treatment compared with standard therapy or no intervention in patients. The primary outcomes comprised balance function, cognitive functions, and mental health status; the secondary outcome was the incidence of adverse events. The quality of studies included in the review was evaluated using the Newcastle–Ottawa Scale, and the pooled effect size was computed using standardized mean differences (SMDs) or mean differences (MDs) for continuous outcomes. Statistical analysis was performed using Stata 18.0. Results The database search yielded 3,553 records, of which 15 studies were included, and 9 had sufficient data for meta-analysis. CAREN training significantly improved balance, as indicated by higher Berg Balance Scale scores (SMD = 1.12; 95% CI = 0.08 to 2.16; p = 0.03; I 2 = 92.64%), and cognitive function, as shown by increased Montreal Cognitive Assessment scores (MD = 0.44; 95% CI = 0.11 to 0.76; p = 0.01; I 2 = 0.00%). Changes in fear of falling, assessed with the Falls Efficacy Scale-International (MD = −0.05; 95% CI = −0.36 to 0.27; p = 0.76; I 2 = 0.00%), and depression, evaluated with the Beck Depression Inventory or Hamilton Depression Rating Scale (MD = −0.20; 95% CI = −0.62 to 0.22; p = 0.35; I 2 = 70.64%), were non-significant. Additionally, adverse events were rare, with no serious cases reported. Conclusion CAREN training appears to improve balance and cognitive function, while its effects on mental health are relatively limited. However, these findings should be interpreted with caution. Systematic review registration PROSPERO, identifier (CRD420251172390).
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.032 |
| Bibliometrics | 0.007 | 0.007 |
| 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".