Cyber Deviance among Adolescents and the Role of Family, School, and Neighborhood: A Cross-National Study

Abstract

IntroductionWith the advent of new technologies and the ubiquity of the Internet, the world is now more connected than ever. Internet access around the world is increasing rapidly and, at the moment, Internet access for household stands at an average of 71.6% for OECD countries (Organisation for Economic Co-operation and Development, 2012). The Internet has proven to be extremely helpful, but it doesn't come without a cost. Cyber crime, software piracy, illegal downloading, hacking, and cyber bullying among others have all become part of our daily lives. Both illegal downloading and hacking, each for its own reason, have attracted a lot of attention from researchers and media alike. While the main issue with illegal downloading is copyrights and the vast amounts of money that music and movie producers don't receive due to sharing (Navarro, Marcum, Higgins, & Ricketts, 2014), hacking poses a security risk and can be potentially devastating to individuals, companies or countries alike. Theft of personal and financial data through hacking can be used against individuals and at the same time critically damage the reputation of a company(Nelson, 2014). Younger generations have been shown to adopt new technologies faster, leading to the debate of digital natives and digital immigrants (Prensky, 2012), which makes adolescents the perfect sample to study the link between technology and behavior.Digital Piracy and Illegal DownloadingIllegal downloading of software, movies and especially music has become an increasingly contentious issue. Setting aside the moral and legal debate of what pertains lawful and unlawful downloading (for a good discussion see Cluley, 2013), a number of studies have tried explain downloading and online piracy. The two most widely used theoretical frameworks are social learning theory and self-control theory. In support of the social learning perspective Hinduja and Ingram (2009) found that real-life association with deviant peers was the biggest predictor of music piracy, although online peers and online media were also significant factors. Morris and Higgins (2010) employed vignettes and asked their respondents How likely would it be for you to [go on-line and find a copy of the movie and download it for free, download the CD illegitimately under these to have friends ask you to make a copy it] to measure the possibility of digital piracy. The results indicated at modest support for Aker's social learning theory (Morris & Higgins, 2010). Lastly, lending credence to the social learning approach, Navarro et al. (2014) found that associating with deviant peers increased an individual's likelihood of committing software, movie or music piracy.Research concerning digital piracy and self-control is sparse and oftentimes done in conjunction with the social learning theory. Higgins, Wolfe, and Marcum (2008) employed the full scale of self-control, which was developed by Grasmick, Tittle, Bursik, and Arneklev (1993). Their dependent variable was I would go to the web-site with the intention to download the CD under these circumstances, which does not specify if the CD is music, movies, or software (Higgins et al., 2008). In this way the authors encompass all the possible types of digital piracy, but at the same time it is impossible to differentiate between them. In light of the limitations of the study, the authors found that low self-control and especially the impulsivity subscale are significantly associated with the intention of digital piracy (Higgins et al., 2008). This is in line with Higgins and Wilson (2006) who examined the link between self-control, differential association and software piracy. Their findings supported low self-control and differential association, however the statistical significance was lost in the sub-sample group with high morals (Higgins & Wilson, 2006). Thus one's morals can possibly negate the influence of low self-control or differential association. …