PDF(Pubmed)
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\".
CONCLUSIONS: 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.
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\".
CONCLUSIONS: 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.
摘要：
目的：先前的研究已经探索了与互联网游戏障碍（IGD）和社交媒体成瘾（SMA）相关的各种精神障碍。迄今为止,很少有研究关注网络特征,并在群体特异性水平上调查了青春期SMA和IGD的情绪和睡眠症状.本研究旨在确定IGD和SMA的不同特征，并进一步确定青少年群体特定的精神病理学过程。
方法：我们进行了一项横断面研究，招募了7246名青少年，他们的得分通过了互联网游戏障碍量表的分界点-简表和卑尔根社交媒体成瘾量表，按IGD和SMA分组，或以其他方式进入控制组。患者健康问卷-9，广泛性焦虑症7项，匹兹堡睡眠质量指数进行了评估，所有评估项目均采用网络分析法进行调查.
结果：根据分析程序，参与者分为三组，IGD组（n=789），SMA组(n=713)和对照组(n=5,744)。边缘权重自举分析表明,不同的网络组达到一定的精度,三组的网络结构有统计学差异(pcontrol-IGD=0.004,pcontrol-SMA<0.001,pIGD-SMA<0.001)。SMA的核心症状是“情绪低落，沮丧,或绝望，“而IGD“感到疲倦或精力不足”。
结论：虽然IGD和SMA都是网络成瘾的亚型，IGD和SMA的精神病理学过程是不同的。处理IGD和SMA时，应该解决不同的症状。
方法：我们进行了一项横断面研究，招募了7246名青少年，他们的得分通过了互联网游戏障碍量表的分界点-简表和卑尔根社交媒体成瘾量表，按IGD和SMA分组，或以其他方式进入控制组。患者健康问卷-9，广泛性焦虑症7项，匹兹堡睡眠质量指数进行了评估，所有评估项目均采用网络分析法进行调查.
结果：根据分析程序，参与者分为三组，IGD组（n=789），SMA组(n=713)和对照组(n=5,744)。边缘权重自举分析表明,不同的网络组达到一定的精度,三组的网络结构有统计学差异(pcontrol-IGD=0.004,pcontrol-SMA<0.001,pIGD-SMA<0.001)。SMA的核心症状是“情绪低落，沮丧,或绝望，“而IGD“感到疲倦或精力不足”。
结论：虽然IGD和SMA都是网络成瘾的亚型，IGD和SMA的精神病理学过程是不同的。处理IGD和SMA时，应该解决不同的症状。
