Effects of immersive and non-immersive virtual reality-based rehabilitation training on cognition, motor function, and daily functioning in patients with mild cognitive impairment or dementia: A systematic review and meta-analysis
Bibliographic record
Abstract
ObjectiveTo examine the effectiveness of virtual reality (VR)-based rehabilitation training in improving cognition, motor function, and daily functioning in patients with mild cognitive impairment and dementia.Data sourcesA systematic review of published literature was conducted using PubMed, Web of Science, Elsevier, Embase, Cochrane, CNKI, Networked Digital Library of Theses and Dissertations.MethodsThe search period was from inception to 7 October 2023. Eligible studies were randomized controlled trials evaluating the efficacy of VR-based rehabilitation training in patients with mild cognitive impairment or dementia versus control subjects. Methodologic quality was assessed with the Cochrane risk of bias tool, and outcomes were calculated as the standard mean difference between participant groups with 95% confidence interval.ResultsA total of 21 randomized controlled trials with 1138 patients were included. The meta-analysis showed that VR-based rehabilitation training had significant effects on Montreal Cognitive Assessment (SMD: 0.50; 95%CI: 0.05 to 0.95; P = 0.030), Trail-making test A (SMD: −0.38; 95%CI: −0.61 to −0.14; P = 0.002), and Berg Balance Scale scores (SMD: 0.79; 95%CI: 0.13 to 1.45; P = 0.020). A subgroup analysis revealed that the type of VR, and duration and frequency of interventions had statistically significant effects on cognition and motor function.ConclusionVR-based rehabilitation training is a beneficial nonpharmacologic approach for managing mild cognitive impairment or dementia. Immersive VR-based training had greater effects on cognition and motor function than non-immersive VR-based training, but non-immersive VR-based training was more convenient for patients with limitations imposed by their disease. Also, an intervention lasting 5–8 weeks and for >30 min at a frequency of ≥3 times/week achieved the best results. It indicated that a longer intervention cycle may not achieve the best intervention effect and training duration and schedule should be carefully considered when managing patients.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.028 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".