Abstract
The increasing presence of gaming disorder in recent years has led to major efforts to identify the specific predictors that have a high impact on the profile of people seeking treatment for this mental condition. The purpose of this study was to explore the network structure of the correlates of gaming disorder considering sociodemographic features and other clinical symptoms. Network analysis was applied to a sample of patients who met clinical criteria for gaming disorder (n = 117, of ages ranging from 15 to 70 yrs-old). Variables considered in the network included sex, age, socioeconomic position, global emotional distress, age of onset and duration of the gaming disorder, personality traits and the presence of other addictive behaviors (tobacco, alcohol and behavioral addictions). The central nodes in the network were global psychological distress, chronological age, and age of onset of gaming related problems. Linkage analysis also identified psychopathological status and age as the variables with the most valuable information in the model. The poorest relevance in the analysis was for the duration of gaming problems and socioeconomic levels. Modularity analysis grouped the nodes within four clusters. Identification of the variables with the highest centrality/linkage can be particularly useful for developing precise management plans to prevent and treat gaming disorder related problems.
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