Gender differences in the interactions and inferred causal relationships between risk factors and gaming disorder: a network and structural equation modeling approach.
Fei Cheng, Lei Guo, Yawen Shi, Shujun Pan, Lei Zhang, Shiyan Qu, Chenxin Yuan, Ying Jiang, Dawei Huang, Tianzhen Chen, Jiang Du, Min Zhao
{"title":"Gender differences in the interactions and inferred causal relationships between risk factors and gaming disorder: a network and structural equation modeling approach.","authors":"Fei Cheng, Lei Guo, Yawen Shi, Shujun Pan, Lei Zhang, Shiyan Qu, Chenxin Yuan, Ying Jiang, Dawei Huang, Tianzhen Chen, Jiang Du, Min Zhao","doi":"10.1007/s00406-025-02075-z","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Gaming Disorder (GD) is linked to severe psychological distress and functional impairment, substantially affecting individuals' daily lives. Current researches have not fully clarified the complex, gender-specific risk factors that contribute to GD development. This study aims to uncover key risk factors, such as negative emotions, childhood trauma, social anxiety, personality traits, and GD symptoms, by utilizing network analysis and structural equation modeling to explore differences between genders.</p><p><strong>Methods: </strong>An online survey was conducted with 1,073 Chinese participants aged 18 to 35. The research assessed GD symptoms, childhood trauma, personality traits, impulsivity, social anxiety, depression, and anxiety through validated scales. The EBICglasso network model was employed to identify core factors and symptoms. Directed Acyclic Graphs (DAGs) were used to infer potential causal pathways among these variables, with results further validated using Structural Equation Modeling (SEM).</p><p><strong>Results: </strong>The EBICglasso network analysis revealed distinct gender-specific core factors across variable clusters. DAGs and SEM identified stable causal pathways to GD symptoms that differed by gender. Among males, GD symptoms were predominantly driven by negative emotions, with \"suicidal ideation\" and \"low energy\" emerging as primary contributors. For females, the pathway to GD symptoms was influenced by childhood trauma, which affected personality traits and negative emotions, ultimately contributing to the development of GD.</p><p><strong>Conclusion: </strong>This study emphasize the critical need for gender-specific intervention strategies in preventing and addressing GD. For males, interventions should prioritize emotional regulation and the reduction of suicidal ideation. For females, it is essential to target anxiety and depressive symptoms associated with childhood trauma.</p>","PeriodicalId":11822,"journal":{"name":"European Archives of Psychiatry and Clinical Neuroscience","volume":" ","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Archives of Psychiatry and Clinical Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00406-025-02075-z","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: Gaming Disorder (GD) is linked to severe psychological distress and functional impairment, substantially affecting individuals' daily lives. Current researches have not fully clarified the complex, gender-specific risk factors that contribute to GD development. This study aims to uncover key risk factors, such as negative emotions, childhood trauma, social anxiety, personality traits, and GD symptoms, by utilizing network analysis and structural equation modeling to explore differences between genders.
Methods: An online survey was conducted with 1,073 Chinese participants aged 18 to 35. The research assessed GD symptoms, childhood trauma, personality traits, impulsivity, social anxiety, depression, and anxiety through validated scales. The EBICglasso network model was employed to identify core factors and symptoms. Directed Acyclic Graphs (DAGs) were used to infer potential causal pathways among these variables, with results further validated using Structural Equation Modeling (SEM).
Results: The EBICglasso network analysis revealed distinct gender-specific core factors across variable clusters. DAGs and SEM identified stable causal pathways to GD symptoms that differed by gender. Among males, GD symptoms were predominantly driven by negative emotions, with "suicidal ideation" and "low energy" emerging as primary contributors. For females, the pathway to GD symptoms was influenced by childhood trauma, which affected personality traits and negative emotions, ultimately contributing to the development of GD.
Conclusion: This study emphasize the critical need for gender-specific intervention strategies in preventing and addressing GD. For males, interventions should prioritize emotional regulation and the reduction of suicidal ideation. For females, it is essential to target anxiety and depressive symptoms associated with childhood trauma.
期刊介绍:
The original papers published in the European Archives of Psychiatry and Clinical Neuroscience deal with all aspects of psychiatry and related clinical neuroscience.
Clinical psychiatry, psychopathology, epidemiology as well as brain imaging, neuropathological, neurophysiological, neurochemical and moleculargenetic studies of psychiatric disorders are among the topics covered.
Thus both the clinician and the neuroscientist are provided with a handy source of information on important scientific developments.