ISSN 0439-755X
CN 11-1911/B
主办:中国心理学会
   中国科学院心理研究所
出版:科学出版社

心理学报 ›› 2023, Vol. 55 ›› Issue (9): 1465-1476.doi: 10.3724/SP.J.1041.2023.01465

• 研究报告 • 上一篇    下一篇

迷“网”的少年:网瘾风险青少年的症状演化*

陈诗韵1,2, 屈笛扬3, 卜禾4, 梁凯欣1, 张沛超5, 迟新丽1()   

  1. 1深圳大学心理学院, 深圳 518061
    2香港理工大学应用社会科学系, 香港
    3清华大学万科公共卫生与健康学院, 北京 100091
    4华东理工大学社会与公共管理学院, 上海 200237
    5武汉大学现代心理学研究中心, 武汉 430072
  • 收稿日期:2022-01-10 发布日期:2023-06-09 出版日期:2023-09-25
  • 通讯作者: 迟新丽 E-mail:xinlichi@szu.edu.cn
  • 基金资助:
    国家社会科学基金(16CSH049);广东省基础与应用基础研究基金自然科学基金面上项目(2021A1515011330)

Changes in the network association of Internet addiction among heterogeneous high-risk adolescents

CHEN Shiyun1,2, QU Diyang3, BU He4, LIANG Kaixin1, ZHANG Peichao5, CHI Xinli1()   

  1. 1School of Psychology, Shenzhen University, Shenzhen 518061, China
    2Department of Applied Social Science, The Hong Kong Polytechnic University, Hong Kong SAR, China
    3Vanke School of Public Health, Tsinghua University, Beijing 100091, China
    4School of Social and Public Administration, East China University of Science and Technology, Shanghai 200237, China
    5Research Centre for Modern Psychology, Wuhan University, Wuhan 430072, China
  • Received:2022-01-10 Online:2023-06-09 Published:2023-09-25
  • Contact: CHI Xinli E-mail:xinlichi@szu.edu.cn

摘要:

本研究对深圳市1279名初一学生进行连续3年追踪测量, 采用增长混合模型和网络分析方法, 识别网瘾风险青少年及其网瘾症状的演化规律。增长混合模型结果显示, 根据青少年网瘾的发展趋势可以将青少年区分为正常组和风险组。网络分析结果表明, 风险组青少年的网瘾在不同阶段呈现不同的核心症状:在初一时, “强迫性网络使用”、“满足感缺失”、“情绪失控”和“戒断反应”的中心性均较高; 在初二时, “满足感缺失”成为了该时间点中心性最高的核心症状; 在初三时, “戒断反应”成为了中心性最高的核心症状。本研究拓宽了对青少年网瘾动态变化性的认识, 扩充了识别网瘾风险青少年的方法, 为未来设计有针对性的干预方案提供实证依据。

关键词: 网瘾, 网络分析, 发展轨迹, 纵向研究, 症状演化

Abstract:

The China Internet Information Center reported that the internet addiction rate among Chinese adolescents has reached as high as 10%, indicating that this problem has become a major social health concern among adolescents in China. Previous studies have identified one or more subgroups of adolescents whose trajectory of internet use behaviors puts them at a high risk of addiction, but further research is needed to determine and understand these high-risk groups and fill research gaps. Furthermore, most previous studies have approached the problem from the perspective of the variables of internet addiction, but its symptomatology remains poorly understood. The current study combines a growth mixture model (GMM) with network analysis to identify heterogeneous groups of adolescents at a high risk of internet addiction and to explore the changes in symptomatology in these groups.

A three-year longitudinal study followed students from the time they entered junior high school. Three assessments were conducted yearly at identical intervals (T1: October 2016 to November 2016, T2: October 2017 to November 2017, and T3: October to November 2018). Ultimately, 1, 279 adolescents (662 boys and 617 girls) completed the assessments at each time point. Internet addiction was assessed using the 10-item Internet Addiction Test. Mplus 8.0 was used for the descriptive statistics, correlation analysis, and the GMM to estimate the development trajectories of various heterogeneous groups. An R package was used to estimate the network structure and core symptoms of internet addiction of each high-risk group at each time point.

The GMM showed a normal group and a high-risk group, which consisted of adolescents who were heterogeneous in terms of the development trajectory of internet addiction. Network analysis revealed that the core symptoms of Internet addiction among the adolescents in the high-risk group differed at each time point. In the first year of junior high school, “Compulsive Internet Use”, “Lack of Satisfaction”, “Emotional Outbursts”, and “Withdrawal Symptoms” were the core symptoms. In the second year, “Lack of Satisfaction” was the core symptom, and in the third year, “Withdrawal Symptoms” became the core symptom.

This study enhances the understanding of the symptomatology of Internet addiction among high-risk adolescents, indicating that targeted interventions must be developed based on the various stages of adolescence. From the first year of junior high school, strategies should be implemented to prevent the development of Internet addiction in high-risk groups. In the second year, adolescents in the high-risk group should be identified by focusing on their satisfaction deficits. In the last year of junior high school, interventions should target adolescents’ withdrawal symptoms of Internet addiction.

Key words: Internet addiction, network analysis, trajectory, longitudinal study, symptomatology

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