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Effects of Virtual Reality Therapy and Range of Motion Exercise on Range of Motion in Stroke Patients: Meta-Analysis

2023· article· en· W4322707897 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIndonesian Journal of Medicine · 2023
Typearticle
Languageen
FieldComputer Science
TopicEducation and Learning Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsRange of motionStroke (engine)Range (aeronautics)Motion (physics)Physical medicine and rehabilitationMedicineVirtual realityMeta-analysisPhysical therapyComputer scienceArtificial intelligencePhysicsEngineeringInternal medicineAerospace engineering

Abstract

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Background: Stroke is a disease caused by interference with blood flow in the brain which is still a global problem today. Post-stroke care needs to be done to prevent the worsening of the condition. One of the right interventions that can be done is virtual reality therapy and range of motion exercise. This study aims to examine, analyze and estimate changes in the range of motion of stroke patients with virtual reality therapy and range of motion exercise. Subjects and Method: Metaanalysis was carried out according to the PRISMA flow chart and the PICO model (Population: stroke patients, Intervention: virtual reality therapy and range of motion exercise, Comparison: not performed virtual reality therapy and range of motion exercise Outcome: range of motion). The databases used are Google Scholar, PubMed, and Science Direct. The keywords used (“virtual reality” OR VR) AND (stroke OR CVD) AND (“range of motion exercise” OR ROM OR “motor exercise”) AND (stroke OR CVD) AND “Randomized Control Trial”. The inclusion criteria were full-text articles with RCT studies published in 2012-2022, articles in English, and bivariate and multivariate analysis. Analysis was performed using ReVman 5.3. Results: There were 20 articles with a randomized control trial design originating from Iran, Turkey, China, Egypt, Myanmar, South Korea, Spain, the Netherlands, Italy, Switzerland, and Canada involving 799 people. A meta-analysis of 10 RCT studies concluded that virtual reality therapy increased the range of motion of stroke patients by 2.77 units (SMD= 2.77; 95% CI = 1.29 to 4.24; p<0.001) compared to no virtual reality therapy. In addition, the range of motion exercise intervention can also increase the stroke patient's range of motion by 0.84 units (SMD= 0.84; 95% CI= 0.35 to 1.33; p<0.001) compared to not being given range of motion exercise. Conclusion: Virtual Reality Therapy and Range of Motion exercises can increase the range of motion of stroke patients. Keywords: virtual reality therapy, range of motion exercise, stroke, range of motion, meta-analysis. Correspondence: Septyan Dwi Nugroho. Masters Program in Public Health, Universitas Sebelas Maret. Jl. Ir Sutami 36A, Surakarta 57126, Central Java. Email: septyandwin@gmail.com. Mobile: 081804418933. Indonesian Journal of Medicine (2023), 08(01): 23-36 https://doi.org/10.26911/theijmed.2023.08.01.03

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.258

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.059
GPT teacher head0.321
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it