Subgroups of internet gaming disorder based on addiction-related resting-state functional connectivity.

Abstract

To identify subgroups of people with internet gaming disorder (IGD) based on addiction-related resting-state functional connectivity and how these subgroups show different clinical correlates and responses to treatment. Secondary analysis of two functional magnetic resonance imaging (fMRI) data sets. Zhejiang province and Beijing, China. One hundred and sixty-nine IGD and 147 control subjects. k-Means algorithmic and support-vector machine-learning approaches were used to identify subgroups of IGD subjects. These groups were examined with respect to assessments of craving, behavioral activation and inhibition, emotional regulation, cue-reactivity and guessing-related measures. Two groups of subjects with IGD were identified and defined by distinct patterns of connectivity in brain networks previously implicated in addictions: subgroup 1 ('craving-related subgroup') and subgroup 2 ('mixed psychological subgroup'). Clustering IGD on this basis enabled the development of diagnostic classifiers with high sensitivity and specificity for IGD subgroups in 10-fold validation (n = 218) and out-of-sample replication (n = 98) data sets. Subgroup 1 is characterized by high craving scores, cue-reactivity during fMRI and responsiveness to a craving behavioral intervention therapy. Subgroup 2 is characterized by high craving, behavioral inhibition and activations scores, non-adaptive emotion-regulation strategies and guessing-task fMRI measures. Subgroups 1 and 2 showed largely opposite functional-connectivity patterns in overlapping networks. There appear to be two subgroups of people with internet gaming disorder, each associated with differing patterns of brain functional connectivity and distinct clinical symptom profiles and gender compositions.