In recent decades, one area of research on media effects has shed extensive light on problematic behavior in the use of media, particularly the overuse or the maladaptive use of the Internet, which is commonly known as Internet addiction (IA). Previous research supported the notion that the excessive use of technology could be problematic. Young posited that IA could be defined as an impulse-control disorder that does not involve an intoxicant. Recent research in IA has given rise to heated discussions and debates about the definition and assessment of IA and its related causes and consequences. Because the Internet has been widely adopted relatively recently in China, whether IA exists among Internet users as well as the symptoms and characteristics of addicts has become a focus of researchers in many disciplines (e.g., communication, psychiatry, psychology, sociology, public health, and education). Most scholars have agreed that IA research has significant implications for both theory and policy.
Despite the existing debate about the nature of IA, most researchers have considered previous definitions of addiction and integrated potential new symptoms. Hence, although different terminologies have been proposed (e.g., Internet dependency, problematic Internet use, and pathological Internet use), they include similar criteria for the assessment of the basic symptoms. Although certain aspects of this complex psychosocial process remain unclear, recent studies have reported important findings on diagnosing addictive symptoms, identifying predictors, and recommending preventive measures and treatments. However, because the previous IA research was conducted mainly in Western countries, little is known about the status of Internet addiction research in China. Thus, the aim of this chapter is to provide an overview of the work done in this emerging field in China, which has 731 million Internet users.
Internet and Smartphone Penetration in China
With an internet penetration rate of 53.2%, the lives of Chinese are undergoing significant change. Among the new netizens in 2016, 80.7% used a mobile phone to go online. Moreover, research has shown a polarized trend in the age differences among netizens as increasing numbers of both youngsters and elders begin using the Internet.
The number of mobile phone users reached 695 million at the end of 2016, and the percentage of people who used the telephone to go online increased from 90.1% in 2015 to 95.1% in 2016. Instant messaging (IM), search engine, and online news, as fundamental Internet services, showed steadily increasing usage at rates above 80%. On mobile phones, the most often used application was IM. The survey revealed that up to 79.6% of netizens used WeChat the most often, followed by QQ (60%), Taobao, Baidu, and Alipay. In addition, Moments and Qzone, which are social services provided by WeChat and QQ, were also widely used at rates of 85.8% and 67.8%, respectively. The 2016 China Social Media Influence Report released by Kantar pointed out that over half of urban Chinese citizens were social media users. Moreover, compared with Americans, British, French, and Brazilian social media users, Chinese social media users ranked third in terms of activeness. Sixty-two percent of American interviewees reported using Facebook and/or Twitter, whereas 58% in Brazil and 56% in China (Weibo and/or WeChat) reported using these social media.
According to the report, there were 417 million online gamers in China, comprising 57% of the entire netizen population. There were 352 million mobile gamers, or 50.6% of all mobile phone users. The number of online shoppers reached 467 million, or 63.8% of all netizens. In particular, there were 441 million mobile-phone online shoppers, which was an annual increase of 29.8%.
Live video streaming services increased throughout 2016 as capital poured into this newly developed industry, which is gaining popularity among Chinese netizens. At the end of 2016, the number of live streaming users had rocketed to 344 million, comprising 47.1% of all netizens. The usage rates of sports live, game live, and live chatting were 20.7%, 20%, and 19.8%, respectively.
The 2015 Chinese Teenagers’ Online Behavior Report, released by the China Internet Network Information Center (CNNIC) revealed that at the end of 2015, there were 287 million teenage netizens in China, comprising 85.3% of the entire adolescent population, 90% of whom used mobile phone to access the Internet, whereas the percentages of personal computer and laptop users were 69% and 39.5%, respectively. The usage rates of IM, Weibo, and Bulletin Board System (BBS) were 92.4%, 37.6%, and 18%, respectively, all of which were higher than the average usage rate in China. At the end of 2015, the number of underage netizens reached 134 million, comprising 46.6% of all teenage netizens. It is worth noting that the usage rate of online gaming, which was 69.2%, was higher than that of the average rate of teenage netizens.
Theoretical Origin and Definition
Traditionally, the concept of addiction was based on a medical model that was specific to the bodily and psychological dependence on a physical substance. It was argued that the concept of addiction should be widened to cover a broader range of behaviors. Griffiths proposed the concept of “technological addiction,” which is nonchemical and behavioral, involving excessive human-machine interaction. Derived from the substance-dependence criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), Internet addiction disorder (IAD), the first listed Internet-related disorder, is defined as a behavioral addiction consisting of six core components: salience, mood modification, tolerance, withdrawal symptoms, conflict, and relapse. Griffiths suggested that the source of this addiction could originate in one or more aspects of Internet use, including the process of typing, the medium of communication, the lack of face-to-face contact, Internet content, and online social activities. Young characterized IA as staying online for pleasure largely in chat rooms for an average of 38 hours or more per week, concluding that IA could shatter families, relationships, and careers. Utilizing an adapted version of the criteria for pathological gambling defined by the DSM-IV, Young developed eight criteria to provide a screening instrument for addictive Internet use. To be considered an addict, the individual must meet five of eight criteria for IA: (1) preoccupation with the Internet; (2) the need for greater amounts of time online; (3) repeated attempts to reduce Internet use; (4) mood modification by Internet use; (5) staying online longer than intended; (6) loss of a significant relationship, job, or educational, or career opportunity; (7) deception about the time spent online; (8) use of the Internet as a way of escaping from problems .
Recent Internet Addiction Research in China
In this chapter, a review of the literature is conducted to provide a broad account of the latest IA research in China. We performed an extensive search of the Social Science Citation Index and the Science Citation Index Expanded (SCI-E) of the ISI Web of the knowledge database of all published works related to IA research in China. A total of 101 relevant empirical studies, mostly journal articles spanning 2008 to 2016, were located. Among these studies, the most relevant were selected for review. These studies were in communication, psychology, education psychology, sociology, information science, economics, business, and others.
The literature review is classified into six broad domains on IA research in China. The domains are national, regional, cross-cultural, mediating effects, Internet research in special groups, and studies using methods other than surveys.
National Internet Addiction Research in China
In 2009, a large-scale national survey of elementary and middle school students in 100 cities or towns in 31 provinces in China was conducted to investigate the prevalence of Internet addiction (IA). The study was based on a probability sample of 24,013 respondents. The results showed that only 54.2% of the participants had access to the national Internet. The prevalence of IA was 6.3% in the total sample (N = 1523) and 11.7% among Internet users. Among the Internet users, males (14.8%) and rural students (12.1%) reported IA more often than females (7.0%) and urban students (10.6%). As the frequency of Internet use and time spent online per week increased, the percentage of IA increased. The study also reported that Internet cafés (18.1%) were the most typical location for surfing, and that playing Internet games (22.5%) was the most common purpose for Internet use. What is more, the most recent statistics on Internet penetration in China shows that there might be 86 million Internet addicts in China. These indicate that IA has become an important social issue and has caught the attention of national policymakers.
In another national survey of Internet users, Jiang and Leung posited that IA was a health risk and examined the effects of individual differences, awareness/knowledge, and acceptance of IA on the willingness of Chinese Internet users to change their Internet habits. In 2009, data were collected from an online survey of Internet users in urban China. The results showed that 12.3% of the participants were at high risk for having IAD.
As an increasing number of Chinese users connect to the Internet via their mobile devices; they use their smartphones or tablets to engage in various activities online. Therefore, this review of the literature in IA research included smartphone addiction studies. In a national online study, Bian and Leung explored the roles of psychological attributes and smartphone usage patterns in predicting smartphone addiction symptoms and social capital. The results showed that those who scored higher in loneliness and shyness had a higher likelihood of being addicted to smartphone use. The results also indicated that loneliness was the most powerful predictor, inversely affecting both bonding and bridging social capital.
Regional Internet Addiction Research in China
In addition to national surveys, several IA studies were conducted in regional locations in China, especially economically well-developed urban areas. The literature review revealed that five major IA studies were conducted in Wuhan, which is a major city, that is, a first-tier city in China. The first study focused on the relationship between adolescent addictive Internet use (AIU) and drug abuse (DA). The participants were from 15 secondary schools and one university. The prevalence rates of IA and drug use (DU) were 5% and 4%, respectively. The analysis, which used structural equation modeling, found that adolescent DU and DA were significantly predicted by AIU. The second study investigated the prevalence of problematic Internet use (PIU) among college students and the possible factors related to this disorder. Students from eight universities completed a questionnaire survey. The results showed that 9.58% of the participants indicated PIU. Moreover, heavy Internet use habits, poor academic achievement, and lack of love from the family were found to be significantly related to PIU. The third study, which was also conducted in Wuhan, examined the prevalence and factors of IA among adolescents. The results showed that a prevalence rate of IA at 13.5%. Internet addicts scored significantly lower in parental relationships and higher in hyperactivity-impulsivity than the non-Internet addicts did. Furthermore, better parental relationships were related to significantly decreased risk of IA in younger students than in older students. The fourth study investigated the clinical characteristics of IA by using a cross-sectional survey and a psychiatric interview. A structured questionnaire was completed by students at two secondary schools. Subsequently, students with IAD were interviewed to confirm their diagnosis and evaluate their clinical characteristics. Among the respondents, 12.6% met the criteria for IAD. The results indicated that being male, in grades 7–9, having a poor relationship between parents, and higher self-reported depression scores were significantly related to the diagnosis of IAD. Finally, the last study examined the association between IA and stressful life events and psychological symptoms among a random sample of school students who were Internet users. The findings indicated a high prevalence of IA among adolescent Chinese Internet users, indicating the importance of the stressors of interpersonal and school-related problems as risk factors for IA, which were mediated mostly through a negative coping style.
Three IA studies were conducted in Guangdong Province. One study examined the relationship between IA and self-injurious behavior (SIB) in adolescence. The participants were high school students aged 13–18 years. The results showed that SIB was common among adolescence in this province. Addiction to the Internet was harmful to mental health and increased the risk of self-injury among adolescents. In a second study in the city of Guangzhou, Li and Wang examined the role of cognitive distortion in online game addiction among Chinese adolescents. Adolescents from two middle schools completed a questionnaire survey. In addition, adolescents from a local mental hospital diagnosed with excessive online game play were randomly divided into to a cognitive behavior therapy group and a clinical control group to measure the severity of online game playing, anxiety, depression, and cognitive distortions according to a baseline after a 6-week intervention. The results showed that rumination and short-term thinking were the greatest predictors of online game addiction, and males were at a high risk of developing online game addiction. The third study was conducted in Guangzhou by Tan et al. They explored the correlations between PIU, depression, and sleep disturbance. Their findings showed a high prevalence of PIU, depression, and sleep disturbance among the high school students, and PIU and depressive symptoms were strongly associated with sleep disturbance.
In a regional study of IA, the authors conducted an exploratory research on IM addiction among Chinese teenagers in Xiamen, Fujian. The results showed that shyness and alienation from family, peers, and school had significant and positive correlations with levels of IM addiction. Both the level of IM use and the level of IM addiction were significantly related to decreases in academic performance. In Wenzhou, Fujian Province, Jiang et al. conducted a cross-sectional survey to assess the personality characteristics of college students with IA. The results showed that 6.9% of the sample had IA. Furthermore, there were significant differences in the personality characteristics, gender, ethnicity, and substance use patterns between students with and without IA.
Recently, Yang et al. explored the dual effects of flow experience on high school students’ IA and exploratory behavior. They also examined the effects of parental interventions on dual causal processes. The data were collected at eight high schools in a city in Hubei Province. The results revealed that flow experience had a positive influence on both high school students’ IA and exploratory behavior. Moreover, parental support significantly reduced high school students’ IA and increased their exploratory behavior on the Internet.
In a comparative study of two cities, Nanjing in the east and Urumqi in the west, Tao and Liu explored the relationship between Internet dependence and eating disorders in a survey of secondary school and college students. The students were divided into Internet dependents and non-Internet dependents (control group). The results showed that the Internet dependents had significantly higher rates of symptoms of eating disorders than the control groups did. In a study of four cities in Guangdong Province (i.e., Shenzhen, Guangzhou, Zhanjiang, and Qingyuan), Wang et al. investigated the prevalence of PIU and the potential risk factors for PIU among high school students. Among the participants, 12.2% met the criteria for PIU. The results showed that high study-related stress, having social friends, poor relations with teachers and students, and conflictive family relationships were risk factors for PIU. Similarly, a school-based study was also conducted in four cities (i.e., Shenyang, Guangzhou, Xinxiang, and Chongqing), which aimed to assess the correlations between PIU and physical and psychological symptoms among Chinese adolescents. The results revealed that 11.7%, 24.9%, 19.8%, and 26.7% of the sample had PIU, physical symptoms, psychological symptoms, and poor sleep quality, respectively. Poor sleep quality was found to be an independent risk factor for both physical and psychological symptoms. The effects of PIU on physical and psychological symptoms were partially mediated by sleep quality.
In Hong Kong, Leung and Lee examined the degrees to which demographics, addiction symptoms, information literacy, parenting styles, and Internet activities predicted Internet risk in a probability sample of 718 adolescents and teenagers aged 9–19 years. They conducted face-to-face interviews with the participants. The results showed that adolescents who were often targets of harassment tended to be older boys with a high family income. The findings indicated that they spent a significant amount of time on social networking sites (SNSs) and preferred the online setting. The adolescents who encountered the unwelcome solicitation of personal or private information online tended to be older girls. Regarding information literacy, they were generally very competent in using publishing tools, but they were not structurally literate (i.e., especially in understanding how information is socially situated and produced).
Using the same dataset, Leung and Lee also examined the interrelationships among Internet literacy, IA symptoms, Internet activities, and academic performance. The regression results showed that the adolescent Internet addicts tended to be male, in low-income families, and lacking confidence in locating, browsing, and accessing information from multiple resources. However, they were technologically knowledgeable and frequent leisure users of SNSs and online games. Contrary to the hypothesis, Internet literacy, especially in publishing and technology, increased the likelihood of addiction to the Internet. As expected, Internet activities, especially SNSs and online games, were significantly and positively linked to IA as well as to all symptoms of IA. Furthermore, the higher the subjects scored on tool and social-structural literacy, the better their academic performance was. However, skills in technical literacy, such as publishing and technology literacy, were not significant predictors of academic performance.
Another study in Hong Kong was conducted to examine the correlations between heavy Internet use and various health risk behaviors and health-promoting behaviors in a university. The results showed that 14.8% of the participants reported heavy Internet use, and that they had lower potential for health-promoting activities. Heavy Internet use was related to various risk behaviors, such as ignoring meals and sleeping late, as well as negative health outcomes, such as being overweight and hypersomnia.