Original article
Longitudinal Predictors of Cyber and Traditional Bullying Perpetration in Australian Secondary School Students

https://doi.org/10.1016/j.jadohealth.2011.11.019Get rights and content

Abstract

Purpose

Cyberbullying perpetration (using communication technology to engage in bullying) is a recent phenomenon that has generated much concern. There are few prospective longitudinal studies of cyberbullying. The current article examines the individual, peer, family, and school risk factors for both cyber and traditional bullying (the latter is bullying that does not use technology) in adolescents.

Methods

This article draws on a rich data set from the International Youth Development Study, a longitudinal study of students in Victoria, Australia and Washington State, United States, which began in 2002. In this article, data from almost 700 Victorian students recruited in grade 5 are analyzed to examine grade 7 (aged 12–13 years) predictors of traditional and cyberbullying perpetration in grade 9 (aged 14–15 years).

Results

Fifteen per cent of students engaged in cyberbullying, 21% in traditional bullying, and 7% in both. There are similarities and important differences in the predictors of cyber and traditional bullying. In the fully adjusted model, only prior engagement in relational aggression (a covert form of bullying, such as spreading rumors about another student) predicted cyberbullying perpetration. For traditional bullying, previous relational aggression was also predictive, as was having been a victim and perpetrator of traditional bullying, family conflict, and academic failure.

Conclusions

The use of evidence-based bullying prevention programs is supported to reduce experiences of all forms of bullying perpetration (cyber, traditional, and relational aggression). In addition, for traditional bullying perpetration, addressing family conflict and student academic support are also important.

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

References (40)

  • S. Keith et al.

    Cyber-bullying: Creating a culture of respect in a cyber world

    Reclaiming Child Youth

    (2005)
  • J. Raskauskas et al.

    Involvement in traditional and electronic bullying among adolescents

    Dev Psychol

    (2007)
  • P.K. Smith et al.

    Cyberbullying: Its nature and impact in secondary school pupils

    J Child Psychol Psychiatry

    (2008)
  • D. Olweus

    Bullying at school: What we know and what we can do

    (1993)
  • J.J. Dooley et al.

    Cyberbullying versus face-to-face bullying: A theoretical and conceptual review

    J Psychol

    (2009)
  • D.W. Grigg

    Cyber-aggression: Definition and concept of cyberbullying

    Aust J Guid Couns

    (2010)
  • M.E. Hamburger et al.

    Measuring bullying victimization, perpetration, and bystander experiences: A compendium of assessment tools

    (2011)
  • B. Spears et al.

    Behind the scenes and screens: Insights into the human dimension of covert and cyberbullying

    J Psychol

    (2009)
  • D.L. Hoff et al.

    Cyberbullying: Causes, effects, and remedies

    J Educ Adm

    (2009)
  • J.W. Patchin et al.

    Bullies move beyond the schoolyard: A preliminary look at cyberbullying

    Youth Violence Juvenile Justice

    (2006)
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