Impact of virtual avatar appearance realism on perceptual interaction experience: a network meta-analysis

虚拟化身外观真实感对感知交互体验的影响:一项网络元分析

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Abstract

OBJECTIVE: As virtual avatars become increasingly embedded in social, educational, and commercial platforms, the virtual avatars appearance realism (VAAR) has emerged as a critical factor influencing user perceptual interaction experience. This study explores the impact of VAAR on users' perceptual interaction experiences. METHOD: We retrieved all relevant publications from the past decade (April 2015 to April 2025) across four major databases: Web of Science, Elsevier Science Direct, Springer Link, and Google Scholar. The analysis focused on three user perceptual interaction experience-related indicators: attractiveness, trustworthiness, and eeriness. A network meta-analysis (NMA) was conducted using Stata software, and the relative ranking of VAAR was determined based on the surface under the cumulative ranking curve. RESULTS: A total of 13 studies with 2,343 participants were included in the analysis. According to the results of the NMA, high VAAR were perceived as more attractive and more trustworthy than those with medium or low VAAR. In contrast, medium VAAR elicited the strongest feelings of eeriness. CONCLUSION: This study highlights the subjective impact of VAAR on user interaction experience. These findings provide meaningful guidance for the future development and design of virtual avatars. SYSTEMATIC REVIEW REGISTRATION: The network meta-analysis (NMA) was preregistered on the Open Science Framework (OSF) and is publicly available at https://doi.org/10.17605/OSF.IO/5TRG6.

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