Evidence map›Paper›PMID 34636735›Full record

SynthesisJournal of medical Internet research2021

Effects of Virtual Reality Training on Upper Limb Function and Balance in Stroke Patients: Systematic Review and Meta-Meta-Analysis.

Jinlong Wu, Aihua Zeng, Ziyan Chen, Ye Wei, Kunlun Huang, Jiafeng Chen, Zhanbing Ren

Registry-linked trialOpen access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07520253 (Effect Of Virtual Reality On Cortical Reorganization And Upper Extremity Functional Recovery In Patients With Subacute Stroke), which is not on this map. Cited by 54 papers, 21 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 21 pooled it
8.0field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT07520253 nanot yet recruitingnot on this mapstarted 2026, after this paper: background citation

Effect Of Virtual Reality On Cortical Reorganization And Upper Extremity Functional Recovery In Patients With Subacute Stroke

TypeinterventionalSponsorCairo UniversityRan2026 to 2026Enrolled40ConditionsStrokeArmsVirtual Reality, Conventional physical therapy program
3 · Its place in the literature

Who cites it

54 citing papers in PubMed, 21 syntheses or guidelines pooled it, 93 citations in OpenAlex.

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  7. Virtual Reality Therapy for Upper Limb Motor Impairments in Patients With Stroke: A Systematic Review and Meta-Analysis.Physiotherapy research international : the journal for researchers and clinicians in physical therapy · 2025
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  13. Combined noninvasive brain stimulation virtual reality for upper limb rehabilitation poststroke: A systematic review of randomized controlled trials.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Jinlong Wu *Department of Physical Education, Shenzhen University, Shenzhen, China.ORCID 0000-0002-0694-3144
Aihua Zeng *Shanwei Polytech, Shanwei, China.ORCID 0000-0002-9922-1297
Ziyan ChenDepartment of Physical Education, Shenzhen University, Shenzhen, China.ORCID 0000-0003-1406-8068
Ye WeiNanshan District Culture, Radio, Television, Tourism and Sports Bureau, Shenzhen, China.ORCID 0000-0001-9805-1241
Kunlun HuangDepartment of Physical Education, Shenzhen University, Shenzhen, China.ORCID 0000-0002-7339-4050
Jiafeng ChenDepartment of Physical Education, Shenzhen University, Shenzhen, China.ORCID 0000-0003-4988-1622
Zhanbing RenDepartment of Physical Education, Shenzhen University, Shenzhen, China.ORCID 0000-0002-2999-9239
Shenzhen University · CNHuawei Technologies (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVirtual reality (VR) training is a promising intervention strategy that has been utilized in health care fields like stroke rehabilitation and psychotherapy. Current studies suggest that VR training is effective in improving the locomotor ability of stroke patients.

objectiveThis is the first meta-meta-analysis of the effects of VR on motor function in stroke patients. This study aimed to systematically summarize and quantify the present meta-analyses results of VR training and produce high-quality meta-meta-analysis results to obtain a more accurate prediction.

methodsWe searched 4 online databases (Web of Science, Scopus, PubMed, and Chinese National Knowledge Infrastructure) for meta-analysis studies. After accounting for overlap, 10 studies (accounting for almost 550 stroke patients) were obtained. Based on the meta-meta-analysis of these patients, this study quantified the impact of VR training on stroke patients' motor performance, mainly including upper limb function, balance, and walking ability. We combined the effects under the random effect model and pooled the estimates as standardized mean differences (SMD).

resultsThe results of the meta-meta-analysis showed that VR training effectively improves upper limb function (SMD 4.606, 95% CI 2.733-6.479, P<.05) and balance (SMD 2.101, 95% CI 0.202-4.000, P<.05) of stroke patients. However, the results showed considerable heterogeneity and thus, may need to be treated with caution. Due to the limited research, a meta-meta-analysis of walking ability was not performed.

conclusionsThese findings represent a comprehensive body of high-quality evidence that VR training is more effective at improving upper limb function and balance of stroke patients.

Indexed as

StrokeStroke RehabilitationVirtual RealityHumansUpper Extremitydigital interventionhealth caremental healthmeta-meta-analysismotor functionmotor skillsrehabilitationreviewstrokestroke patientsvirtual reality

Identifiers

PMID34636735
PMCPMC8548971
OpenAlexW3195766124

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.