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

• Published in: Addiction (Abingdon, England) Vol. 118; no. 2; pp. 327 - 339
• Main Authors: Wang, Zi‐Liang, Potenza, Marc N., Song, Kun‐Ru, Dong, Guang‐Heng, Fang, Xiao‐Yi, Zhang, Jin‐Tao
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01.02.2023
• Subjects: Activation; Addictions; Addictive behaviors; Behavior modification; Behavior, Addictive - psychology; Brain; Brain - diagnostic imaging; Brain mapping; Brain Mapping - methods; Clustering; Cognitive behavioral therapy; Cognitive style; Computer & video games; Craving; Craving - physiology; Emotional regulation; Functional connectivity; Functional magnetic resonance imaging; Humans; Immunoglobulin D; Inhibition; Internet; Internet Addiction Disorder - diagnostic imaging; internet gaming disorder; Machine learning; magnetic resonance imaging; Magnetic Resonance Imaging - methods; Neural networks; Neuroimaging; Reactivity; Research subjects; Responsiveness; Resting; support vector machine learning; video games; Video Games - psychology; craving; magnetic resonance imaging; internet gaming disorder; support vector machine learning; Addictive behaviors; video games
• ISSN: 0965-2140; 1360-0443; 1360-0443
• DOI: 10.1111/add.16047

Aims 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. Design Secondary analysis of two functional magnetic resonance imaging (fMRI) data sets. Setting Zhejiang province and Beijing, China. Participants One hundred and sixty‐nine IGD and 147 control subjects. Measurements 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. Findings 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. Conclusions 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.