Gaming disorder and its association with depression, social anxiety, and risk perception during the COVID-19 pandemic: A study using a Gaussian graphical model and moderated network models

Abstract

During the COVID-19 pandemic, many scholars in the field of behavioral addiction examined the risk of gaming disorder (GD). The association between GD, depression, social anxiety, and risk perception toward COVID-19 among Chinese university students has remained largely uninvestigated, especially using network analysis. Therefore, the present study (N = 1794) examined the relationship between these variables during the pandemic using Gaussian graphical model (GGM) and Moderated Network Model (MNM) approaches. In the GGM and MNM, GD had a significant interaction with depression. Individual risk perception and public risk perception had stronger connections in the network, as did depression and social anxiety. In addition, ‘fatigue’ was identified as the core symptom of depression. Neither moderation effects (i.e., three-way interaction between GD, depression, social anxiety, and risk perception) nor gender differences in network comparisons were found. These results suggest that relieving negative emotional states may have helped prevent GD during the COVID-19 pandemic, while the influence of risk perception on GD and negative emotions needs to be further examined.