Efficacy and feasibility of virtual reality-based cognitive tele-rehabilitation in Parkinson's disease: A pilot randomized controlled trial on patients and caregivers
Bibliographic record
Abstract
Objective Parkinson's disease (PD) is a progressive neurodegenerative disorder that not only impairs motor functions but also may lead to significant cognitive decline, greatly affecting the quality of life for both patients and their caregivers. This study aims to evaluate the feasibility and potential effectiveness of cognitive tele-rehabilitation (TR) plus virtual reality (VR), compared to traditional home-based rehabilitation methods, focusing on cognitive outcomes, quality of life, usability, and the impact on caregiver strain in patients with PD. Methods In this pilot randomized controlled trial, 20 PD patients and their primary caregivers were randomly assigned to either a control group (CG) receiving traditional cognitive training or an experimental group (EG) undergoing cognitive TR using a VR rehabilitation system, with assessments conducted before and after the 8-week intervention. Results TR was rated as highly usable (System Usability Scale mean score: 84.3 ± 9.5). Post-intervention analyses showed significant improvements in global cognitive functioning (Montreal Cognitive Assessment (MoCA): p = 0.002) and quality of life (Parkinson's Disease Questionnaire (PDQ)-8: p = 0.002) in the EG. The CG also showed improvements in MoCA ( p = 0.008) and PDQ-8 ( p = 0.016), although to a lesser extent than the EG. A reduction in caregiver burden was observed in both groups but did not reach statistical significance. Analysis of Δ scores revealed a significantly greater MoCA improvement in the EG compared to the CG ( p = 0.019). Statistically significant differences were found between the groups in the Family Strain Questionnaire and PDQ-8 Δ scores. Conclusion These findings suggest that cognitive TR, particularly when integrated with VR, might be useful in improving cognitive function and quality of life in PD patients and could play a key role in future PD management strategies, potentially easing the burden on caregivers.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".