No abstract

No abstract

This study investigated childhood psychopathology and Internet addiction in adolescents. Initial assessment data were obtained from 1998 to 1999, and a follow-up assessment was performed in 2006, when the original subjects entered middle school. Personal information for the 524 male subjects was obtained from the original data. The subjects were evaluated with the Korean version of the child behavior checklist, which was administered to the children's parents. Demographic and psychosocial factors were also evaluated. Children were reassessed with the self-reported Korea Internet Addiction Scale. Our results indicated that 3.6 % of the subjects had Internet addiction, and revealed a significant relationship between withdrawal and anxiety/depression and future Internet addiction. The results suggest that withdrawal and anxiety/depression during childhood should be considered in the etiology of problematic Internet use in boys. Accordingly, clinicians should consider anxiety/depression and withdrawal during childhood to prevent Internet addiction.

This paper describes a semi-parametric Bayesian approach for estimating receiver operating characteristic (ROC) curves based on mixtures of Dirichlet process priors (MDP). We address difficulties in modelling the underlying distribution of screening scores due to non-normality that may lead to incorrect choices of diagnostic cut-offs and unreliable estimates of prevalence of the disease. MDP is a robust tool for modelling non-standard diagnostic distributions associated with imperfect classification of an underlying diseased population, for example, when a diagnostic test is not a gold standard. For posterior computations, we propose an efficient Gibbs sampling framework based on a finite-dimensional approximation to MDP. We show, using both simulated and real data sets, that MDP modelling for ROC curve estimation closely parallels the frequentist kernel density estimation (KDE) approach.

The smartphone has many attractive attributes and characteristics that could make it highly addictive, particularly in adolescents. The purpose of this study was to examine the prevalence of young adolescents in risk of smartphone addiction and the psychological factors associated with smartphone addiction. Four hundred ninety middle school students completed a self-questionnaire measuring levels of smartphone addiction, behavioral and emotional problems, self-esteem, anxiety, and adolescent-parent communication. One hundred twenty-eight (26.61%) adolescents were in high risk of smartphone addiction. This latter group showed significantly more severe levels of behavioral and emotional problems, lower self-esteem, and poorer quality of communication with their parents. Multiple regression analysis revealed that the severity of smartphone addiction is significantly associated with aggressive behavior (β = .593, t = 3.825) and self-esteem (β = −.305, t = −2.258). Further exploratory and confirmatory studies should consider different sites, demographics, technological mobile devices, platforms, and applications.