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

Abstract

BackgroundParalleling 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.MethodsIn 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.ResultsOf 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.ConclusionsThis 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.

Internet Addiction: A Systematic Review of Epidemiological Research for the Last Decade

“…Moreover, the following Internet use variables were found to be associated with Internet addiction in adolescents: age of first exposure to the Internet [195], Internet use for entertainment purposes [63], frequency and length of Internet use [45,63,64,76], Internet access at home [61], Internet usage at an Internet café [70,78], the use of online gaming [46,52,69,196], social applications [45,46,52], and other Internet applications [69]. In addition to this, parental guidance with regards to Internet behaviours was reported to be associated with Internet addiction, specifically little parental communication about Internet use, rules about Internet times [41], and a lack of rules regarding Internet use [50].…”

“…Sung and colleagues [51] used the Internet Addiction Proneness Scale -Short Form (KS-Scale) [88] in a sample of 73,238 adolescents in South Korea and reported that 3.0% and 11.9% of adolescents were at high risk and at potential risk for developing Internet addiction in South Korea, respectively [51]. On the other end of the spectrum, Xu et al [45] used the DRM 52 Scale of Internet use in a random sample of 5,122 adolescents in Shanghai, China with the result that 8.8% of adolescents in this sample were classified as Internet addicts. The only cross-cultural study of Internet addiction prevalence included two separate samples of 1,761 high school students in China and 1,182 students in the USA who were used in a longitudinal study by Sun et al [47] using the (CIUS), and showed that the prevalence rates were 5.8% in Chinese females, 15.7% in Chinese males, 9.7% in US females, and 7.3% in US males.…”

“…In addition to the prevalence estimates reported, the studies have found that in adolescents, Internet addiction is associated with the following sociodemographic variables: higher family income levels [61,63], male gender [45, 61-63, 65, 66, 81, 83], female gender [48], being left behind (i.e., abandoned), and migrant [68], living in rural areas [81], being in senior high school, and having a monthly spending over 100 RMB [45]. The discrepancy between findings concerning associations between Internet addiction and gender can possibly be explained by the measures utilised, i.e., Liu et al [48] found that a higher percentage of girls reports excessive usage behaviours, which might be indicative of their increased problem awareness relative to boys.…”

“…A total of 21 studies were identified that used miscellaneous criteria. Of these, 14 studies used miscellaneous criteria to identify Internet addiction in adolescents [40][41][42][43][44][45][46][47][48][49][50][51][52]. In addition to the adolescent samples, miscellaneous classification criteria for Internet addiction have been used in adult samples, including a total of eight studies [53][54][55][56][57][58][59][60].…”

“…A total of 13 studies used miscellaneous criteria to identify Internet addiction in adolescents [40][41][42][43][44][45][46][47][48][49][50][51][52]. Sample sizes varied from including 1,098 adolescents in Singapore [43] to 73,238 adolescents in South Korea [51].…”