Internet addiction patterns of rural Chinese adolescents: Longitudinal predictive effects on depressive symptoms and problem behaviors

被引:1
|
作者
Sun, Yadong [1 ]
Shao, JingJin [1 ]
Li, Jiamei [1 ]
Jiang, Yue [1 ]
机构
[1] Southwest Univ, Fac Psychol, Ctr Mental Hlth Educ, Chongqing 400715, Peoples R China
来源
关键词
internet addiction; latent profile analysis; depressive symptoms; problem behaviors; longitudinal research; DEVIANT PEER AFFILIATION; STRESSFUL LIFE EVENTS; GENDER-DIFFERENCES; MEDIATING ROLE; SCHOOL; MODEL; SELF; ATTACHMENT; STUDENTS; ASSOCIATION;
D O I
10.1177/18344909221105351
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Few studies have systematically investigated the internal heterogeneity of internet addiction to determine the longitudinal predictive effects on depressive symptoms and problem behaviors, especially among the rural adolescents. Via two waves of data collection, this study conducted a survey among 1,194 rural adolescents in China (M-age = 14.53, SD = 0.72). A latent profile analysis was conducted to explore the various patterns of behaviors and influential factors of internet addiction. These results were then used to predict the probability of depressive symptoms and problem behaviors. The findings are as follows: (1) According to the behavioral patterns uncovered, internet addiction among rural adolescents can be divided into four subgroups: normal internet use (41%), low internet addiction (39%), high internet addiction (9%), and overuse of online games (11%). (2) The distribution of internet addiction patterns among rural adolescents were significantly correlated with gender, deviant peer affiliation, and parental alienation. (3) Adolescents in the high internet addiction and overuse of online game categories generally had more depressive symptoms and problem behaviors than those in the normal-use category. These findings indicate considerable heterogeneity in internet addiction among rural adolescents in China. Specifically, gender, deviant peer affiliation, and parental alienation are the risk factors for the internet-addiction profiles.
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页数:13
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