| Different Characteristics of Psychological and Sleep Symptoms Across Social Media Addiction and Internet Gaming Disorder in Chinese Adolescents- A Network Analysis |
Wanling Zhang1 
, Liwen Jiang1
, Minglan Yu1
, Rong Ma2
, Tingting Wang1
, Xuemei Liang1
, Rongfang He1
, Chun Xu1
, Shasha Hu1
, Youguo Tan3,4
, Kezhi Liu1
, Bo Xiang1,4,5
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1Department of Psychiatry, Fundamental and Clinical Research on Mental Disorders Key Laboratory of Luzhou, Medical Laboratory Center, Affliated Hospital of Southwest Medical University, Luzhou, China
2School of Pharmacy, Southwest Medical University, Luzhou, China
3Zigong Mental Health Center, Zigong, China
4Mental Health Research Center, Zigong Institute of Brain Science, Zigong, China
5Institute of Cardiovascular Research, Southwest Medical University, Luzhou, China |
Correspondence: Kezhi Liu ,Tel: +86-0830-3165019, Fax: +86-0830-3165019, Email: kingzliu@163.com
Correspondence: Bo Xiang ,Tel: +86-0830-3165019, Fax: +86-0830-3165019, Email: xiangbo@swmu.edu.cn
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Received: May 3, 2023 Revised: December 13, 2023 Accepted: May 15, 2024 Published online: July 24, 2024 |
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| Abstract |
Objective
Previous research has explored a variety of mental disorders associated with Internet Gaming Disoder (IGD) and Social Media Addiction (SMA). To date, few studies focused on the network characteristics and investigated mood and sleep symptoms across SMA and IGD of adolescence at a group-specific level. This study aims to identify different characteristics of IGD and SMA and further determine the group-specific psychopathology process among adolescents.
Methods
We conducted a cross-sectional study to recruit a cohort of 7,246 adolescents who were scored passing the cutoff point of Internet Gaming Disorder Scale-Short Form and Bergen Social Media Addiction Scale, as grouped in IGD and SMA, or otherwise into the control group. Patient Health Questionnaire-9, Generalized Anxiety Disorder 7-item, and Pittsburgh Sleep Quality Index were assessed for the current study, and all assessed items were investigated using network analysis.
Results
Based on the analytical procedure, the participants were divided into three groups, the IGD group (n=789), SMA group (n=713) and control group (n=5,744). The edge weight bootstrapping analysis shows that different groups of networks reach certain accuracy, and the network structures of the three groups are statistically different (pcontrol-IGD=0.004, pcontrol-SMA<0.001, pIGD-SMA<0.001). The core symptom of SMA is “feeling down, depressed, or hopeless”, while IGD is “feeling tired or having little energy”.
Conclusion
Although IGD and SMA are both subtypes of internet addiction, the psychopathology processes of IGD and SMA are different. When dealing with IGD and SMA, different symptoms should be addressed. |
| Key words
Internet gaming disorder; Social media addiction; Sleep quality; Anxiety; Depression |
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