4.7 Article Proceedings Paper

Internet Addiction in adolescence: Neurobiological, psychosocial and clinical issues

Journal

NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
Volume 76, Issue -, Pages 174-184

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neubiorev.2016.12.024

Keywords

Neurobiology; Etiopathogenesis; Social withdrawal; Hikikomori; 'Instrumental' sociability; Human-machine interaction

Funding

  1. Department of Antidrug Policies c/o Presidency, Council of Ministries (Italy)
  2. European Community [603016]

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Despite it has not been formally included in DSM-5 as a disorder, 'Internet addiction (IA)' has become a worldwide issue. It can be broadly defined as a non-chemical, behavioral addiction, which involves human-machine interaction. We pinpoint it as an instrumental form of social interaction (i.e. mediated by machines), a notion that appears useful for the sake of possible preclinical modeling. The features of Internet use reveals as addictive when this comes at the expense of genuine real-life sociability, with an overlap towards the hikikomori phenomenon (i.e., extreme retreat to one's own room). Due to the specific neuro-developmental plasticity in adolescence, IA poses risks to youths' mental health, and may likely produce negative consequences in everyday life. The thwarted development of adolescents' identity, self-image and adaptive social relationships is discussed: the IA adolescents often suffer loss of control, feelings of anger, symptoms of distress, social withdrawal, and familial conflicts. Further, more severe clinical conditions are also associated to IA, such as dysthymic, bipolar, affective, social-anxiety disorders, as well as major depression. This paper overviews the literature on IA, from neuro-biological, psychosocial and clinical standpoints, taking into account recent debates on diagnostic criteria, nosographic label and assessment tools. Neuroimaging data and neurochemical regulations are illustrated with links to pathogenetic hypotheses, which are amenable to validation through innovative preclinical modeling. (C) 2016 Elsevier Ltd. All rights reserved.

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