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Open Access Research article

Personal characteristics related to the risk of adolescent internet addiction: a survey in Shanghai, China

Jian Xu1, Li-xiao Shen1, Chong-huai Yan1*, Howard Hu26*, Fang Yang3, Lu Wang4, Sudha Rani Kotha37, Li-na Zhang5, Xiang-peng Liao1, Jun Zhang1, Feng-xiu Ouyang1, Jin-song Zhang1 and Xiao-ming Shen1

Author affiliations

1 Xinhua Hospital, MOE-Shanghai Key Laboratory of Children’s Environmental Health, Shanghai Institute for Pediatric Research, Shanghai Jiao Tong University School of Medicine, Shanghai, China

2 Environmental Health Department, School of Public Health, University of Michigan, Ann Arbor, MI, USA

3 Center for Global Health, University of Michigan, Ann Arbor, MI, USA

4 Biostatistics Department, School of Public Health, University of Michigan, Ann Arbor, MI, USA

5 Biostatistics Department, Shanghai Jiao Tong University School of Medicine, Shanghai, China

6 DALLA LANA School of Public Health, University of Toronto, Ontario, Canada

7 Center for Global Health, University of Toronto, Ontario, Canada

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Citation and License

BMC Public Health 2012, 12:1106  doi:10.1186/1471-2458-12-1106

Published: 22 December 2012



Paralleling the rapid growth in computers and internet connections, adolescent internet addiction (AIA) is becoming an increasingly serious problem, especially in developing countries. This study aims to explore the prevalence of AIA and associated symptoms in a large population-based sample in Shanghai and identify potential predictors related to personal characteristics.


In 2007, 5,122 adolescents were randomly chosen from 16 high schools of different school types (junior, senior key, senior ordinary and senior vocational) in Shanghai with stratified-random sampling. Each student completed a self-administered and anonymous questionnaire that included DRM 52 Scale of Internet-use. The DRM 52 Scale was adapted for use in Shanghai from Young’s Internet Addiction Scale and contained 7 subscales related to psychological symptoms of AIA. Multiple linear regression and logistic regression were both used to analyze the data.


Of the 5,122 students, 449 (8.8%) were identified as internet addicts. Although adolescents who had bad (vs. good) academic achievement had lower levels of internet-use (p < 0.0001), they were more likely to develop AIA (odds ratio 4.79, 95% CI: 2.51-9.73, p < 0.0001) and have psychological symptoms in 6 of the 7 subscales (not in Time-consuming subscale). The likelihood of AIA was higher among those adolescents who were male, senior high school students, or had monthly spending >100 RMB (all p-values <0.05). Adolescents tended to develop AIA and show symptoms in all subscales when they spent more hours online weekly (however, more internet addicts overused internet on weekends than on weekdays, p < 0.0001) or when they used the internet mainly for playing games or real-time chatting.


This study provides evidence that adolescent personal factors play key roles in inducing AIA. Adolescents having aforementioned personal characteristics and online behaviors are at high-risk of developing AIA that may compound different psychological symptoms associated with AIA. Spending excessive time online is not in itself a defining symptom of AIA. More attention is needed on adolescent excessive weekend internet-use in prevention of potential internet addicts.

Adolescent; Internet addiction; Risk factors; China