Purpose of Review With increasing use of the Internet throughout our daily lives, Internet use disorders (IUDs) due to addictive behaviors are gaining recognition. As an umbrella term, IUD covers an array of online behaviors that are potentially addictive. The growing population of Internet and smartphone users also raised public health concerns over IUD in regard to adverse cognitive, developmental, psychosocial, and physical consequences. While scientific literature to date has tended to focus on specific forms of IUD such as gaming or pornography, confining our attention to only these specific areas may impede research on the combined effects of multiple online addictive behaviors-often the clinical reality in maladapted Internet use. Taking this broader approach may also facilitate prioritization in policymaking and more efficient allocation of public health and clinical resources. This paper discusses conceptual application of a public health model at the society level and an integrative model at the individual level in IUD intervention strategies. Current treatment modalities of IUD are also reviewed from a biopsychosocial perspective. Recent Findings We propose that the harms of IUD are mediated by (1) risky/harmful content, (2) excessive/maladaptive use, and (3) financial burden. Prevention strategies that reduce the potential negative effects of these mediators may be useful against IUD. Summary Prevention and intervention efforts against IUD should not only target the "host" (individual vulnerabilities) but also the "agent" (media-related risks) and "environment" risks to better address complexities in the phenomena. The current mainstream therapeutic modality is psychosocial intervention. Further studies on psychopharmacology and neuromodulation are needed to broaden our therapeutic options for IUD.tf

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To characterize young adulthood depression is complicated because it is entangled with a broad spectrum of symptoms as well as traumatic experiences during development. However, previous symptom network studies have focused on undirected transdiagnostic association among depression and anxiety symptoms. Our study investigated both undirected and directed connections among variables potentially associated with depression, such as anxiety, addiction, subjective distress caused by traumatic events, perceived emotional adversities, and support systems. Both the regularized partial correlation network analysis and Bayesian network analysis were applied to 579 subjects screened for depression. Anxiety-related symptoms played a role as a hub node in the partial correlation network and Bayesian network. The vulnerability analysis of the partial correlation network showed that verbal abuse, social anxiety, concentration problems, and suicidal ideation had the strongest influence on changes in the network’s topology. In the Bayesian network analysis, loss of interest, depressed mood, and parental verbal abuse were located as parent nodes in the directed acyclic graph. In the aspect of disease networks, more attention should be paid to certain variables encompassing various domains as well as depressive symptoms in young adults’ mental health management.