Literature DB >> 31207886

Neurobiological Risk Factors for the Development of Internet Addiction in Adolescents.

Sergey Tereshchenko1, Edward Kasparov2.   

Abstract

The sudden appearance and spread of Internet addiction in adolescent populations, in association with the rapid escalation of consumed Internet content and the broad availability of smartphones and tablets with Internet access, is posing a new challenge for classical addictology which requires urgent solutions. Like the majority of other psychopathological conditions, pathological Internet addiction depends upon a group of multifactor polygenic conditions. For each specific case, there is a unique combination of inherited characteristics (nervous tissue structure, secretion, degradation, and reception of neuromediators), and many are extra-environment factors (family-related, social, and ethnic-cultural). One of the main challenges in the development of the bio-psychosocial model of Internet addiction is to determine which genes and neuromediators are responsible for increased addiction susceptibility. This information will herald the start of a search for new therapeutic targets and the development of early prevention strategies, including the assessment of genetic risk levels. This review summarizes the literature and currently available knowledge related to neurobiological risk factors regarding Internet addiction in adolescents. Genetic, neurochemical and neuroimaging data are presented with links to actual pathogenetic hypotheses according to the bio-psychosocial model of IA forming.

Entities:  

Keywords:  Internet addiction; adolescents; comorbidity; gene polymorphism; neurobiology; neuroimaging; neurotransmitters

Year:  2019        PMID: 31207886      PMCID: PMC6616486          DOI: 10.3390/bs9060062

Source DB:  PubMed          Journal:  Behav Sci (Basel)        ISSN: 2076-328X


  2 in total

1.  Prevalence and Clinical Correlates of Internet Addiction Symptoms and Their Association With Quality of Life in Adolescents With Major Depressive Disorder: A Multicenter Cross-Sectional Study.

Authors:  Song Wang; Lei Xia; Jiawei Wang; Xiaoping Yuan; Yudong Shi; Xixin Wang; Xiaoyue Li; Yu Hu; Yulong Zhang; Yating Yang; Feng Geng; Zhiwei Liu; Changhao Chen; Xiangwang Wen; Xiangfen Luo; Fei Gao; Huanzhong Liu
Journal:  Front Psychiatry       Date:  2022-04-25       Impact factor: 4.157

2.  Rich Get Richer: Extraversion Statistically Predicts Reduced Internet Addiction through Less Online Anonymity Preference and Extraversion Compensation.

Authors:  Shaozhen Zhang; Wenliang Su; Xiaoli Han; Marc N Potenza
Journal:  Behav Sci (Basel)       Date:  2022-06-16
  2 in total

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