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      Effectiveness of Virtual/Augmented Reality–Based Therapeutic Interventions on Individuals With Autism Spectrum Disorder: A Comprehensive Meta-Analysis

      systematic-review

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          Abstract

          In recent years, the application of virtual reality (VR) for therapeutic purposes has escalated dramatically. Favorable properties of VR for engaging patients with autism, in particular, have motivated an enormous body of investigations targeting autism-related disabilities with this technology. This study aims to provide a comprehensive meta-analysis for evaluating the effectiveness of VR on the rehabilitation and training of individuals diagnosed with an autism spectrum disorder. Accordingly, we conducted a systematic search of related databases and, after screening for inclusion criteria, reviewed 33 studies for more detailed analysis. Results revealed that individuals undergoing VR training have remarkable improvements with a relatively large effect size with Hedges g of 0.74. Furthermore, the results of the analysis of different skills indicated diverse effectiveness. The strongest effect was observed for daily living skills ( g = 1.15). This effect was moderate for other skills: g = 0.45 for cognitive skills, g = 0.46 for emotion regulation and recognition skills, and g = 0.69 for social and communication skills. Moreover, five studies that had used augmented reality also showed promising efficacy ( g = 0.92) that calls for more research on this tool. In conclusion, the application of VR-based settings in clinical practice is highly encouraged, although their standardization and customization need more research.

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          Bias in meta-analysis detected by a simple, graphical test

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            Robust variance estimation in meta-regression with dependent effect size estimates.

            Conventional meta-analytic techniques rely on the assumption that effect size estimates from different studies are independent and have sampling distributions with known conditional variances. The independence assumption is violated when studies produce several estimates based on the same individuals or there are clusters of studies that are not independent (such as those carried out by the same investigator or laboratory). This paper provides an estimator of the covariance matrix of meta-regression coefficients that are applicable when there are clusters of internally correlated estimates. It makes no assumptions about the specific form of the sampling distributions of the effect sizes, nor does it require knowledge of the covariance structure of the dependent estimates. Moreover, this paper demonstrates that the meta-regression coefficients are consistent and asymptotically normally distributed and that the robust variance estimator is valid even when the covariates are random. The theory is asymptotic in the number of studies, but simulations suggest that the theory may yield accurate results with as few as 20-40 studies. Copyright © 2010 John Wiley & Sons, Ltd.
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              Basics of meta-analysis: I(2) is not an absolute measure of heterogeneity.

              When we speak about heterogeneity in a meta-analysis, our intent is usually to understand the substantive implications of the heterogeneity. If an intervention yields a mean effect size of 50 points, we want to know if the effect size in different populations varies from 40 to 60, or from 10 to 90, because this speaks to the potential utility of the intervention. While there is a common belief that the I(2) statistic provides this information, it actually does not. In this example, if we are told that I(2) is 50%, we have no way of knowing if the effects range from 40 to 60, or from 10 to 90, or across some other range. Rather, if we want to communicate the predicted range of effects, then we should simply report this range. This gives readers the information they think is being captured by I(2) and does so in a way that is concise and unambiguous. Copyright © 2017 John Wiley & Sons, Ltd.
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                Author and article information

                Contributors
                Journal
                Front Psychiatry
                Front Psychiatry
                Front. Psychiatry
                Frontiers in Psychiatry
                Frontiers Media S.A.
                1664-0640
                23 June 2021
                2021
                : 12
                : 665326
                Affiliations
                [1] 1School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM) , Tehran, Iran
                [2] 2Cognitive Neuroscience Laboratory, German Primate Center , Goettingen, Germany
                [3] 3School of Medicine, Shahid Beheshti University of Medical Sciences , Tehran, Iran
                [4] 4Behavioral Science Research Center, Shahid Beheshti University of Medical Sciences , Tehran, Iran
                [5] 5Department of Psychology, Faculty of Psychology and Education, University of Tehran , Tehran, Iran
                [6] 6Control and Intelligent Processing Center of Excellence (CIPCE), Cognitive Systems Laboratory, School of Electrical and Computer Engineering, College of Engineering, University of Tehran , Tehran, Iran
                Author notes

                Edited by: Raz Gross, Sheba Medical Center, Israel

                Reviewed by: Yoon Phaik Ooi, University of Basel, Switzerland; Diogo Morais, Lusophone University of Humanities and Technologies, Portugal

                *Correspondence: Abdol-Hossein Vahabie h.vahabie@ 123456ut.ac.ir

                This article was submitted to Child and Adolescent Psychiatry, a section of the journal Frontiers in Psychiatry

                Article
                10.3389/fpsyt.2021.665326
                8260941
                34248702
                bc6ebfc0-d079-4772-9c2e-5c5d9df31758
                Copyright © 2021 Karami, Koushki, Arabgol, Rahmani and Vahabie.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 07 February 2021
                : 12 May 2021
                Page count
                Figures: 6, Tables: 5, Equations: 5, References: 106, Pages: 25, Words: 14741
                Categories
                Psychiatry
                Systematic Review

                Clinical Psychology & Psychiatry
                autism spectrum disorder,virtual reality,rehabilitation,technology,augmented reality

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