EEG- and VR- derived affective computing in excessive internet gamers with social anxiety

This retrospective cross-sectional study examined arousal and valence in students at high and low risk of internet gaming disorder (IGD) using a convolutional neural network (CNN)-based model applied to electroencephalographic (EEG) data. Sixty participants underwent virtual reality (VR)-based socioemotional stress and were classified into high-risk (HIGD) and low-risk (LIGD) groups based on IGD test scores.

Depression, social anxiety, and emotion regulation were assessed using self-report questionnaires. Between-group differences were examined using parametric tests and linear mixed-effects models; associations between EEG-derived indices and self-report measures were evaluated using Spearman correlations with false discovery rate correction. The HIGD group reported significantly greater depression and social anxiety but comparable emotion regulation strategies.