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The present study investigated the relationships between adolescents' online communication and compulsive Internet use, depression, and loneliness. The study had a 2-wave longitudinal design with an interval of 6 months. The sample consisted of 663 students, 318 male and 345 female, ages 12 to 15 years. Questionnaires were administered in a classroom setting. The results showed that instant messenger use and chatting in chat rooms were positively related to compulsive Internet use 6 months later. Moreover, in agreement with the well-known HomeNet study (R. Kraut et al., 1998), instant messenger use was positively associated with depression 6 months later. Finally, loneliness was negatively related to instant messenger use 6 months later.

Background: Prevalence studies of Internet addiction in the general population are rare. In addition, a lack of approved criteria hampers estimation of its occurrence. Aims: This study conducted a latent class analysis (LCA) in a large general population sample to estimate prevalence. Methods: A telephone survey was conducted based on a random digit dialling procedure including landline telephone (n = 14,022) and cell phone numbers (n = 1,001) in participants aged 14-64. The Compulsive Internet Use Scale (CIUS) served as the basis for a LCA used to look for subgroups representing participants with Internet addiction or at-risk use. CIUS was given to participants reporting to use the Internet for private purposes at least 1 h on a typical weekday or at least 1 h on a day at the weekend (n = 8,130). Results: A 6-class model showed best model fit and included two groups likely to represent Internet addiction and at-risk Internet use. Both groups showed less social participation and the Internet addiction group less general trust in other people. Proportions of probable Internet addiction were 1.0% (CI 0.9-1.2) among the entire sample, 2.4% (CI 1.9-3.1) in the age group 14-24, and 4.0% (CI 2.7-5.7) in the age group 14-16. No difference in estimated proportions between males and females was found. Unemployment (OR 3.13; CI 1.74-5.65) and migration background (OR 3.04; CI 2.12-4.36) were related to Internet addiction. Conclusions: This LCA-based study differentiated groups likely to have Internet addiction and at-risk use in the general population and provides characteristics to further define this rather new disorder.

This study examined the associations between adolescents' daily Internet use and low well-being (i.e., loneliness, low self-esteem, and depressive moods). We hypothesized that (a) linkages between high levels of daily Internet use and low well-being would be mediated by compulsive Internet use (CIU), and (b) that adolescents with low levels of agreeableness and emotional stability, and high levels of introversion would be more likely to develop CIU and lower well-being. Data were used from a sample of 7888 Dutch adolescents (11-21 years). Results from structural equation modeling analyses showed that daily Internet use was indirectly related to low well-being through CIU. In addition, daily Internet use was found to be more strongly related to CIU in introverted, low-agreeable, and emotionally less-stable adolescents. In turn, again, CIU was more strongly linked to loneliness in introverted, emotionally less-stable, and less agreeable adolescents.

Aim of the present study was to examine whether the personality correlates sensitivity to reward and to punishment, and impulsivity predict compulsive internet use (CIU). Furthermore, the predictive value of these personality correlates was compared to the predictive value of factors relating to psychosocial wellbeing. The results showed that particularly rash spontaneous impulsivity predicts CIU and that this personality factor is more important than psychosocial wellbeing factors. Sensitivity to reward, which is supposed to play a role in craving processes associated with substance abuse and eating disorders, could not be related to CIU. The data suggest that internet users who are characterized by an impulsive personality feature, are less able to control their use of the internet, which makes them more vulnerable to develop CIU.

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A representative sample (n=1,000) of the Belgian population aged 18 years and older filled out an online questionnaire on their Internet use in general and their use of social networking sites (SNS) in particular. We measured total time spent on the Internet, time spent on SNS, number of SNS profiles, gender, age, schooling level, income, job occupation, and leisure activities, and we integrated several psychological scales such as the Quick Big Five and the Mastery Scale. Hierarchical multiple regression modeling shows that gender and age explain an important part of the compulsive SNS score (5%) as well as psychological scales (20%), but attitude toward school (additional 3%) and income (2.5%) also add to explained variance in predictive models of compulsive SNS use.

The addiction treatment system only reaches a small number of individuals suffering from Internet-related disorders. Therefore, it is important to improve case detection for preventive measures and brief interventions. Existing screening instruments are often time-consuming and rarely validated using clinical criteria. The aim of this study is to develop an optimized short screening for problematic Internet use and Internet addiction (IA). A regression analysis was conducted in random subsamples of a merged sample (N = 3,040; N = 1,209) to examine the item performance of the Compulsive Internet Use Scale (CIUS). Based on the results, a short version of the CIUS was developed and compared with the original CIUS. A fully structured diagnostic interview, covering the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria for the Internet gaming disorder with a broader focus on all Internet activities, was conducted. A five-item version of the short screening performed best across the samples. Comparing the area under the curve (AUC) of the receiver operating characteristic between the Short CIUS and the original test revealed no significant difference (AUC = 0.968; 0.977). A cutoff point of 7 turned out to perform best for case detection and yielded a sensitivity of 0.95 and a specificity of 0.87, Cronbach's alpha was 0.77. The analysis showed that the performance of the Short CIUS is just as good in detecting problematical Internet use and IA as the performance of the original CIUS. The Short CIUS provides an economical and valid instrument for the assessment of problematic Internet use and IA.