Abstract
Gottfredson and Hirschi’s (1990) general theory of crime and Akers’ (1998) social learning theory have received strong empirical support for explaining crime in both the physical and cyberworlds. Most of the studies examining cybercrime, however, have only used college samples. In addition, the evidence on the interaction between low self-control and deviant peer associations is mixed. Therefore, this study examined whether low self-control and deviant peer associations explained various forms of cyberdeviance in a youth sample. We also tested whether associating with deviant peers mediated the effect of low self-control on cyberdeviance as well as whether it conditioned the effect. Low self-control and deviant peer associations were found to be related to cyberdeviance in general, as well as piracy, harassment, online pornography, and hacking specifically. Deviant peer associations both mediated and exacerbated the effect of low self-control on general cyberdeviance, though these interactions were not found for the five cyberdeviant types examined.
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Notes
We focused on the work of Higgins (2007) and Gibson et al. (2010) because they examined the construct validity of the original Grasmick et al. scale with four options ranging from strongly agree to strong disagree. Piquero, MacIntosh, and Hickman (2000) tested a revised version of the Grasmick et al. scale that had five options measuring how frequent someone acted in that fashion.
Pirating media, pirating software, and viewing offensive sexual materials online were measured with the following three items respectively: 1) knowingly used, made, or gave to another person “pirated” media (music, television show, or movie); 2) knowingly used, made, or gave to another person a “pirated” copy of commercially-sold computer software; 3) looked at pornographic, obscene, or offensive materials online. Peer harassment was computed by taking the average of the standardized scores for the following four measures (alpha = .919): 1) posted or sent a message about someone for other people to see that made that person feel bad; 2) posted or sent a message about someone for other people to see that made that person feel threatened or worried; 3) sent a message to someone via e-mail or instant message that made that person feel threatened or worried; and 4) sent a message to someone via e-mail or instant message that made that person feel bad. Peer computer hacking was created by averaging the standardized scores for the following three items (alpha = .832): 1) tried to guess another’s password to get into his/her computer account or files; 2) accessed another’s computer account or files without his/her knowledge or permission just to look at the information or files; and 3) added, deleted, changed or printed any information in another’s computer files without the owner’s knowledge or permission.
There are two statistically significant differences (Paternoster et al., 1998) between the three self-control measures in Model 2. First, the Gibson measure had a statistically significant stronger effect on cyberdeviance (b = .009; std. error = .001). Second, a statistically significant mediation effect is found in Model 2 when using the traditional Grasmick et al. scale and the Gibson scale, but not the Higgins scale. The standard error for low self-control using the Higgins scale is .002 rather than .001 as is found for the other two measurements.
In order to further verify this conclusion, a linear regression was conducted with peer deviance as the dependent variable (results not shown). This model indicated that low self-control, spending more time online for non-school related reasons, computer skill, and lower report card grades all increased the association with delinquent others.
Although there were no statistically significant differences between the three different measures of low self-control within the two subgroups, the Gibson et al. measure indicated a conditioning effect (z = −3.13), congruent with that of the unstandardized scale. The Higgins measure had no such effect (z = −1.58), though this was because of the larger standard errors.
We dichotomized the components because of heavy skew and little variation. Most students did not commit these offenses or performed them at lower levels (see descriptives Table 1). Therefore, we dichotomized software piracy, pornography, harassment, and computer hacking (0 = no; 1 = yes) in order to examine whether self-control predicted the probability of committing these acts. Media piracy (mean = 1.29; std. dev. = 2.05) was a partial exception to the trend, as 55.9% of the sample did not engage in this offense within the last year. Another 16.8% stated that they had pirated media once or twice in the last year. This total (72.7%) is similar to the percentages of students who had not committed any of the other offenses; thus we dichotomized media piracy based on students who engaged in piracy less than twice in the last 12 months (0) and those who committed it more often (1).
Z-tests indicate that there were no significant differences in the abilities of the Grasmick et al., Higgins, and Gibson scales in predicting the five types of cyberdeviance.
Since the individual peer deviance measures were five-point ordinal measures, we could not partition the models by medians. Instead, we partitioned on whether or not the person had deviant peer associations for that specific item (i.e. low = 0; high = all other options).
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Holt, T.J., Bossler, A.M. & May, D.C. Low Self-Control, Deviant Peer Associations, and Juvenile Cyberdeviance. Am J Crim Just 37, 378–395 (2012). https://doi.org/10.1007/s12103-011-9117-3
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DOI: https://doi.org/10.1007/s12103-011-9117-3