Original articleLongitudinal Predictors of Cyber and Traditional Bullying Perpetration in Australian Secondary School Students
Section snippets
Predictors of cyberbullying
Few studies have examined predictors of cyberbullying perpetration and compared these with traditional bullying. Williams and Guerra (2007) found that shared predictors of Internet bullying, physical bullying, and verbal bullying include normative beliefs that accept bullying behavior, a negative school climate, and perceived lack of peer social support [15].
Research on predictors of cyberbullying can be guided by the extant literature on traditional bullying and youth violence. Predictors are
Participants
This article draws on data from the International Youth Development Study, a longitudinal study of the development of students from Victoria, Australia and Washington State, United States who were recruited through schools in grades 5, 7, and 9 in 2002. To obtain state representative samples from the two states, a two-stage cluster sampling approach was used. In the first stage, within each state and grade level, public and private schools containing grades 5, 7, or 9 were randomly selected
Rates of bullying perpetration
Table 2 shows the distribution of cyber and traditional bullying perpetration at grade 9 in 2006. Approximately 15% of students reported that they had engaged in cyberbullying and 21% of students had engaged in traditional bullying. Further analyses revealed that 7.3% of students had cyberbullied others and engaged in traditional bullying. Traditional bullying was more prevalent in boys than girls; however, there were no gender differences for cyberbullying perpetration.
Correlations between all risk factors and bullying variables
Intercorrelations
Discussion
Cyberbullying is a recent phenomenon raising many concerns for adolescents, parents, and educators. There are few studies that provide longitudinal data on the predictors of cyberbullying perpetration, particularly with detailed information about established risk factors for traditional bullying and related behaviors. This study is unique in examining whether the longitudinal predictors of cyberbullying perpetration are the same as those of traditional bullying perpetration. The results show
Conclusions
This study is unique in examining the longitudinal factors that influence cyber and traditional bullying perpetration using comprehensive measures of risk factors. The results of this study underline the importance of further theoretical and conceptual development of “bullying” and the subtypes of bullying. Further longitudinal research of the predictors of cyber versus traditional bullying is warranted. This information can then inform the development of prevention programs and strategies
Acknowledgments
The authors are grateful for the financial support of the National Institute on Drug Abuse (R01-DA012140) for the International Youth Development Study initial data collection. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Drug Abuse or the National Institute of Health. Continued data collection in Victoria, Australia, has been supported by two Australian Research Council Discovery Projects (DPO663371
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