Concurrent Validity of Virtual Reality-Based Assessment of Executive Function: A Systematic Review and Meta-Analysis

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Abstract

This meta-analysis investigated the concurrent validity between virtual reality (VR)-based assessments and traditional neuropsychological assessments of executive function, with a focus on subcomponents such as cognitive flexibility, attention, and inhibition. A total of 1605 articles were identified through searches of PubMed, Web of Science, and ScienceDirect from 2013 to 2023. After removing duplicates, 1313 articles were screened based on their titles and abstracts, with 77 articles selected for full-text eligibility review. Of these, nine articles fully met the inclusion and exclusion criteria for this study. The effect size for overall executive function was assessed, with subcomponents categorized based on the specific assessment tools used in the studies. The effect size for each subcomponent—cognitive flexibility, attention, and inhibition—was then analyzed to provide a more detailed understanding of their relationships with traditional measures. The results revealed statistically significant correlations between VR-based assessments and traditional measures across all subcomponents. Additionally, sensitivity analyses confirmed the robustness of the findings, even when low-quality studies were excluded. These results support the use of VR-based assessments as a valid alternative to traditional methods for evaluating executive function. Moreover, the study highlights the potential of VR-based assessments as a valid alternative to traditional methods, emphasizing the need to address variability in executive function subcomponents and integrate diverse cognitive and motor metrics for greater ecological validity.

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APA

Lee, S. A., Kim, J. Y., & Park, J. H. (2024, November 1). Concurrent Validity of Virtual Reality-Based Assessment of Executive Function: A Systematic Review and Meta-Analysis. Journal of Intelligence. Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/jintelligence12110108

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