Cerniglia L, Zoratto F, Cimino S, Laviola G, Ammaniti M, Adriani W. Internet Addiction in adolescence: Neurobiological, psychosocial and clinical issues.
Neurosci Biobehav Rev 2016;
76:174-184. [PMID:
28027952 DOI:
10.1016/j.neubiorev.2016.12.024]
[Citation(s) in RCA: 159] [Impact Index Per Article: 19.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Revised: 12/05/2016] [Accepted: 12/16/2016] [Indexed: 12/24/2022]
Abstract
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, psycho-social 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.
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