Is virtual reality beneficial for dual-task gait training in patients with Parkinson's disease? A systematic review
Bibliographic record
Abstract
This systematic review examined the evidence about the effects of virtual reality (VR) on dual-task gait training in Parkinson's disease (PD). METHODS: this study (PROSPERO registration CRD42019114736) aimed to answer the question: "Is VR beneficial for dual-task gait training in patients with PD?" We searched for studies from 2008 to 2018 on Medline/PubMed and Web of Science/Web of knowledge databases. The keywords were Parkinson AND gait training AND virtual reality OR Parkinson AND gait training AND game. A total of 55 articles were retrieved, of which 11 systematic reviews, 11 opinions, letters to the editor, posters or conferences abstracts and 17 studies not evaluating the effects of VR gait training were excluded. Three further studies addressing VR dual-task gait training in PD (found in references of studies selected) were also included. Therefore, 19 studies were included and analysed. RESULTS: all studies reported gait improvement after VR training. Many clinical scales were used, hampering comparison of the effects of each protocol. CONCLUSION: VR dual-task gait training should be part of rehabilitation protocols for PD. The studies showed that VR training was effective, although specific guidelines have not yet been established.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".