RAPID COMMUNICATION Factors Associated with Internet Addiction among Adolescents Lawrence T. Lam, Ph.D., 1 Zi-wen Peng, MBBS., 2,3 Jin-cheng Mai, M.D., 3 and Jin Jing, M.D. 3 Abstract This research examined factors associated with Internet addiction in adolescence using a population-based cross- sectional survey with self-reported questionnaires. Participants were recruited from high school students, ages 13 to 18 years, registered on the secondary school registry in Guangzhou city using a stratified random sampling technique. Internet addiction was assessed using the Internet Addiction Test (IAT). Information was also col- lected on demographics, health behaviors, and perception of personal condition. Depression was assessed by the Zung Self-Rating Depression Scale. The majority of respondents were classified as normal users of the Internet (n ¼ 1,392, 89.2%), with 158 (10.2%) moderately and 10 (0.6%) severely addicted to the Internet. Results from the multivariate logistic regression analyses suggested a 50% increased odds for males to be addicted to the Internet (OR ¼ 1.5, 95% CI ¼ 1.1–2.2) when compared to females. Other potential risk factors included drinking behavior (OR ¼ 1.7, 95% CI ¼ 1.1–2.8), family dissatisfaction (OR ¼ 2.4, 95% CI ¼ 1.3–4.3), and experience of recent stressful events (OR ¼ 10.0, 95% CI ¼ 6.5–12.2). Stress-related variables were associated with Internet addiction among adolescents as they are also related to other addictions. Clinicians need to be aware of potential comorbidities of other problems such as stress and family dissatisfaction among adolescent Internet addiction patients. Introduction I nternet addiction has been recognized since the mid- 1990s as a new type of addiction and a mental health problem that exhibits signs and symptoms similar to those of other established addictions. 1–3 It is described as uncontrol- lable and damaging use of the Internet and is recognized as a compulsive-impulsive Internet usage disorder, one of those in the spectrum of impulse-control disorders discussed in recent psychiatric literature. 4–6 Despite a growing volume of work on Internet addiction, the basic epidemiology of the disor- der remains unclear. 6 Unlike for well-established, traditional impulse-controls, information on the population-based prev- alence of Internet addiction has not been forthcoming. Recent studies in different countries suggest that the population prevalence of Internet addiction ranges from 0.3% in the United States to 1.0% in Norway. 7,8 Among adolescents, the prevalence has been estimated to be about 8% in Greece. 9 While studies have indicated that people suffering from Internet addiction are mostly young males with introverted personality, it has also been shown that the rates of exhibiting the disorder among females is increasing. 10–12 In recent years, with the greater availability of the Internet in most Asian countries, Internet addiction has become an increasing mental problem among adolescents. A growing incidence in adolescence has been reported by re- searchers in Taiwan and China from about 6% in 2000 to about 11% in 2004. 13 Many studies have reported associations between Internet addiction, psychiatric symptoms, and depression among adolescents. 14–17 Internet addiction is also detrimental to physical health. Research on patients who were addicted to the Internet, particularly to the mas- sively multiplayer online role-playing games (MMORPGs), demonstrated that these games induced seizures in 10 patients. 18 In terms of risk factors associated with Internet addiction among adolescents, information provided from the literature is scarce. Apart from the above-mentioned male predomi- nance, no other detailed information is available. Hence, the aim of this exploratory study is to expand the knowledge of potential risk factors associated with Internet addictions among adolescents. Materials and Methods This cross-sectional health survey was conducted in Guangzhou city of the Guangdong Province in Southeast China in July 2008. The sample consisted of adolescents from 13 to 18 years old and was generated using a stratified ran- dom sampling method with stratification according to the 1 School of Medicine Sydney, University of Notre Dame Australia, Darlinghurst, New South Wales, Australia. 2 School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong Province, People’s Republic of China. 3 Department of Psychological Education of Elementary School and Secondary School, Guangzhou City Ministry of Education, Guangdong Province, People’s Republic of China. CYBERPSYCHOLOGY &BEHAVIOR Volume 12, Number 5, 2009 ª Mary Ann Liebert, Inc. DOI: 10.1089=cpb.2009.0036 551