Abstract

BackgroundInternet addiction can seriously affect the social functioning and studies of college students in China but measures for addressing this problem have not yet been developed or tested.ObjectiveAssess the personality characteristics of college students with internet addiction.MethodsTwo self-report scales, the Tridimensional Personality Questionnaire (TPQ) and the Chen Internet Addiction Scale (CIAS), were administered to a stratified random sample of 697 college students from colleges and vocational schools in Wenzhou, China. The characteristics of 48 subjects who meet Chen's criteria for internet addiction (score of 64 or greater out of 100 on the CIAS) were compared to those of 649 subjects who did not meet criteria for internet addiction.ResultsThe prevalence of internet addiction in the sample was 6.9% (95% CI=5.1-9.1%). Compared to students without internet addiction, those with internet addiction were more likely to be male, of Han ethnicity, to have a history of substance use (primarily tobacco and alcohol), and to be a student at a technical college. Students with internet addiction had higher mean (sd) scores on the novelty-seeking subscale of the TPQ [17.9 (1.2) v. 13.0 (1.6), t=16.75 p<0.001] and on the harm-avoidance subscale [17.2 (1.9) v. 14.6 (1.1), t=15.14, p<0.001] but lower scores on the reward-dependence subscale [14.6 (1.4) v. 18.3 (1.7), t=-7.64, p<0.001]. Logistic regression found that the most important independent predictors of internet addiction were Han ethnicity (OR= 5.52, 95% CI=2.00-15.32), male gender (4.40, 1.97-9.81), and substance use (1.08, 1.02-1.15). After adjustment for other variables personality measures were not significantly associated with internet addiction.ConclusionThe prevalence of internet addiction among college students in Wenzhou is similar to that in other parts of China. Significant differences in the personality characteristics assessed by the TPQ between university students with and without internet addiction become non-significant after controlling for gender, ethnicity and substance use patterns.

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