AUTHOR=Cioban Smaranda , Lazăr Adela Răzvana , Bacter Claudia , Hatos Adrian 

TITLE=Adolescent Deviance and Cyber-Deviance. A Systematic Literature Review

JOURNAL=Frontiers in Psychology

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2021.748006

DOI=10.3389/fpsyg.2021.748006

ISSN=1664-1078

ABSTRACT=Deviance is a complex phenomenon that influences aspects both at the macro and micro levels. The study of deviance concerns a variety of fields, with it being found at the intersection of several disciplines such as psychology, sociology, and criminology, among others. Grounded in Pickering’s and Byrne’s approach (2014) of elaborating literature reviews, the present systematic literature review aims to identify recurrent themes in 61 most-cited articles related to the concept of deviance from the database of Web of Science, as well as 488 abstracts of representative papers on the same topic. For the purpose of the study, we employed KH Coder, which is an open-source text analysis software that allows complex queries. The research shows that the application of text analysis techniques, such as hierarchical text analysis, co-occurrence network, and correspondence analysis on articles, generates consistent insights related to the main topics and theoretical frameworks. Regarding deviance, four main groups of topics emerged, namely, predictors of deviance, online deviance, socio-constructivist theories, and explanatory theories of the nature of deviant behavior. The findings highlight that researchers frequently use strain theory, social learning, self-control, and social control theories in their studies. Our systematic literature review reveals the most encountered predictors of deviance, which we have classified into five main categories: family patterns, socio-demographic aspects, socialization, victimization, and school and individual factors. For online deviance, family patterns, socio-demographic aspects, victimization, school and individual factors, and Internet and computer use have been determined to be the main groups of predictors.