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The Role of Online Communication in Long-Term Cyberbullying Involvement Among Girls and Boys

  • Empirical Research
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Abstract

Digital media, especially mobile communication technologies, enable adolescents to explore and experiment with each other with only limited adult control. Conflicts between peers can be easily staged since nearly everybody can be reached at any time under the radar of authorities. Therefore, involvement in conflicts and bullying might depend on how adolescents use and behave online. In the present study, we provide a comprehensive picture of the role aspects of online communication play in long-term involvement in cyberbullying. We focused on a gender-specific perspective, as girls and boys were found to differ not only according to their online communication but also in their cyberbullying involvement. Using a two-wave panel survey of 1817 adolescents between 13 and 17 years (56 % female), we found that girls’ cyberbullying involvement (perpetration and victimization) could be traced back to more intensive online social activities and a higher amount of online contact with strangers. In contrast, for boys, only higher exposure to antisocial media content predicted higher levels of victimization over time. The findings indicate that certain patterns of online communication increase the cyberbullying risk over time. However, it needs to be noted that these risk factors vary between girls and boys.

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Notes

  1. In the German school system, pupils are usually separated after 4th grade and, according to their school achievements, distributed to different types of schools with a three-part ranking of educational levels (lower-track, intermediate, and higher-track education schools).

  2. We excluded two types of cyberbullying that Vandebosch and van Cleemput (2009) suggested due to conceptual difficulties.

  3. Of the original eight items (see den Hamer and Konjin 2015), we excluded the four items referring to sexual risk behavior and substance use since the focus of our study was on online exposure to antisocial activities. Additionally, the item “…people who shoot at another person” had to be excluded since invariance testing revealed that girls’ and boys’ response probabilities were different for this specific question.

References

  • Arbuckle, J. L. (1996). Full information estimation in the presence of incomplete data. In G. A. Marcoulides & R. E. Schumacker (Eds.), Advanced structural equation modeling (pp. 243–277). Mahwah, NJ: Lawrence Erlbaum Associates Inc.

    Google Scholar 

  • Bandura, A. (2001). Social cognitive theory of mass communication. Media Psychology, 3(3), 265–299. doi:10.1207/S1532785XMEP0303_03.

    Article  Google Scholar 

  • Barlett, C. P. (2015). Anonymously hurting others online: The effect of anonymity on cyberbullying frequency. Psychology of Popular Media Culture, 4(2), 70–79. doi:10.1037/a0034335.

    Article  Google Scholar 

  • Barlett, C. P., & Coyne, S. M. (2014). Meta-analysis of sex differences in cyber-bullying behavior: The moderating role of age. Aggressive Behavior, 40, 474–488. doi:10.1002/ab.21555.

    Article  PubMed  Google Scholar 

  • Bryce, J., & Fraser, J. (2014). The role of disclosure of personal information in the evaluation of risk and trust in young peoples’ online interactions. Computers in Human Behavior, 30, 299–306. doi:10.1016/j.chb.2013.09.012.

    Article  Google Scholar 

  • Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling, 14(3), 464–504. doi:10.1080/10705510701301834.

    Article  Google Scholar 

  • Chen, L., Ho, S. S., & Lwin, M. O. (2016). A meta-analysis of factors predicting cyberbullying perpetration and victimization: From the social cognitive and media effects approach. New Media & Society. doi:10.1177/1461444816634037.

    Google Scholar 

  • den Hamer, A., & Konjin, E. A. (2015). Adolescents’ media exposure may increase their cyberbullying behavior: A longitudinal study. Journal of Adolescent Health, 56, 203–208. doi:10.1016/j.jadohealth.2014.09.016.

    Article  Google Scholar 

  • den Hamer, A., Konjin, E. A., & Keijer, M. G. (2013). Cyberbullying behavior and adolescents’ use of media with antisocial content: A cyclic process model. Cyberpsychology, Behavior, and Social Networking, 17(2), 74–81. doi:10.1089/cyber.2012.0307.

    Article  Google Scholar 

  • Dittrick, C. J., Beran, T. N., Mishna, F., Hetherington, R., & Shariff, S. (2013). Do children who bully their peers also play violent video games? A Canadian national study. Journal of School Violence, 12(4), 297–318. doi:10.1080/15388220.2013.803244.

    Article  Google Scholar 

  • Dooley, J. J., Shaw, T., & Cross, D. (2012). The association between the mental health and behavioural problems of students and their reactions to cyber-victimization. European Journal of Developmental Psychology, 9, 275–289. doi:10.1080/17405629.2011.648425.

    Article  Google Scholar 

  • Dowell, E. B., Burgess, A. W., & Cavanaugh, D. J. (2009). Clustering of internet risk behaviors in a middle school student population. Journal of School Health, 79(11), 547–553. doi:10.1111/j.1746-1561.2009.00447.x.

    Article  PubMed  Google Scholar 

  • Fanti, K. A., Demetriou, A. G., & Hawa, V. V. (2012). A longitudinal study of cyberbullying: Examining risk and protective factors. European Journal of Developmental Psychology, 9(2), 168–181. doi:10.1080/17405629.2011.643169.

    Article  Google Scholar 

  • Festl, R., & Quandt, T. (2013). Social relations and cyberbullying: The influence of individual and structural attributes on victimization and perpetration via the Internet. Human Communication Research, 39(1), 101–126. doi:10.1111/j.1468-2958.2012.01442.x.

    Article  Google Scholar 

  • Festl, R., Scharkow, M., & Quandt, T. (2013). Peer influence, internet use and cyberbullying: A comparison of different context effects among German adolescents. Journal of Children and Media, 7(4), 446–462. doi:10.1080/17482798.2013.781514.

    Article  Google Scholar 

  • Festl, R., Scharkow, M., & Quandt, T. (2015). The individual or the group: A multilevel analysis of cyberbullying in school classes. Human Communication Research, 41(4), 535–556. doi:10.1111/hcre.12056.

    Article  Google Scholar 

  • Finney, S. J., & DiStefano, C. (2006). Non-normal and categorical data in structural equation modeling. In G. R. Hancock & R. O. Mueller (Eds.), Structural equation modeling. A second course (pp. 269–314). Charlotte, NC: Information Age Publishing Inc.

    Google Scholar 

  • Gauntlett, D. (2008). Media, gender and identity. An introduction. Abingdon, UK: Routledge.

    Google Scholar 

  • Heirman, W., & Walrave, M. (2008). Assessing concerns and issues about the mediation of technology in cyberbullying. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 2(2), article 1. Retrieved from http://cyberpsychology.eu/view.php?cisloclanku=2008111401&article=1.

  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. doi:10.1080/10705519909540118.

    Article  Google Scholar 

  • Hunt, C., Peters, L., & Rapee, R. M. (2012). Development of a measure of the experience of being bullied in youth. Psychological Assessment, 24, 156–165. doi:10.1037/a0025178.

    Article  PubMed  Google Scholar 

  • Hurrelmann, K., & Richter, M. (2006). Risk behaviour in adolescence: the relationship between developmental and health problems. Journal of Public Health, 14(1), 20–28. doi:10.1007/s10389-005-0005-5.

    Article  Google Scholar 

  • Jessor, R. (1987). Problem-behavior theory, psychosocial development, and adolescent problem drinking. British Journal of Addiction, 82(4), 435–446.

    Google Scholar 

  • Jessor, R. (1991). Risk behavior in adolescence: A psychosocial framework for understanding and action. Journal of Adolescent Health, 12, 597–605. doi:10.1016/1054-139X(91)90007-K.

    Article  PubMed  Google Scholar 

  • Kopecký, K. (2011). Sexting among Czech preadolescents and adolescents. New Educational Review, 28(2), 39–48.

    Google Scholar 

  • Kowalski, R. M., Giumetti, G. W., Schroeder, A. N., & Lattanner, M. R. (2014). A meta-analysis of factors predicting cyberbullying perpetration and victimization: From the social cognitive and media effects approach. Psychological Bulletin, 140(4), 1073–1137. doi:10.1037/a0035618.

    Article  PubMed  Google Scholar 

  • Krasnova, H., Spiekermann, S., Koroleva, K., & Hildebrand, T. (2010). Online social networks: why we disclose. Journal of Information Technology, 25(2), 109–125. doi:10.1057/jit.2010.6.

    Article  Google Scholar 

  • Kwan, G. C. E., & Skoric, M. M. (2013). Facebook bullying: An extension of battles in school. Computers in Human Behavior, 29, 16–25. doi:10.1016/j.chb.2012.07.014.

    Article  Google Scholar 

  • Lee, E., & Kim, M. (2004). Exposure to media violence and bullying at school: Mediating influences of anger and contact with delinquent friends. Psychological Reports, 95, 659–672. doi:10.2446/pr0.95.2.659-672.

    PubMed  Google Scholar 

  • Lenhart, A., Duggan, M., Perrin, A., Stelper, R., Rainie, L., & Parker, K. (2015). Teens, social media & technology overview 2015: Smartphones facilitates shifts in communication landscape for teens. http://www.pewinternet.org/files/2015/04/PI_TeensandTech_Update2015_0409151.pdf. Accessed 9 May 2015.

  • Livingstone, S., Haddon, L., Görzig, A., & Olafsson, K. (2011). Risks and safety on the internet: The perspective of European children. Full Findings. London: EU Kids Online.

    Google Scholar 

  • Livingstone, S., Hasebrink, U., & Görzig, A. (2012). Towards a general model of determinants of risk and safety. In S. Livingstone, L. Haddon, & A. Görzig (Eds.), Children, risk and safety on the Internet: Research and policy challenges in comparative perspective (pp. 323–338). Bristol: Policy Press.

    Chapter  Google Scholar 

  • Livingstone, S., Kirwil, L., Ponte, C., & Staksrud, E. (2014). In their own words: What bothers children online? European Journal of Communication, 29(3), 271–288. doi:10.1177/0267323114521045.

    Article  Google Scholar 

  • Mendle, J., Turkheimer, E., & Emery, R. E. (2007). Detrimental psychological outcomes associated with early pubertal timing in adolescent girls. Developmental Review, 27, 151–171. doi:10.1016/j.dr.2006.11.001.

    Article  PubMed  PubMed Central  Google Scholar 

  • Menesini, E., Nocentini, A., & Calussi, P. (2011). The measurement of cyberbullying: Dimensional structure and relative item severity and discrimination. Cyberpsychology, Behavior, and Social Networking, 14(5), 267–274. doi:10.1089/cyber.2010.0002.

    Article  Google Scholar 

  • Milosevic, T. (2015). Cyberbullying in US mainstream media. Journal of Children and Media, 9(4), 492–509. doi:10.1080/17482798.2015.1089300.

    Article  Google Scholar 

  • Modecki, K. L., Minchin, J., Harbaugh, A. G., Guerra, N. G., & Runions, K. C. (2014). Bullying prevalence across contexts: A meta-analysis measuring cyber and traditional bullying. Journal of Adolescent Health, 55, 602–611. doi:10.1016/j.jadohealth.2014.06.007.

    Article  PubMed  Google Scholar 

  • Notten, N., & Nikken, P. (2014). Boys and girls taking risks online: A gendered perspective on social context and adolescents’ risky online behavior. New Media & Society. doi:10.1177/1461444814552379.

    Google Scholar 

  • O’Brien, L., Albert, D., Chein, J., & Steinberg, L. (2011). Adolescents prefer more immediate rewards when in the presence of their peers. Journal of Research on Adolescence, 21, 747–753.

    Article  Google Scholar 

  • Rosseel, Y. (2011). Lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36.

    Google Scholar 

  • Sasson, H., & Mesch, G. (2014). Parental mediation, peer norms and risky online behavior among adolescents. Computers in Human Behavior, 33, 32–38. doi:10.1016/j.chb.2013.12.025.

    Article  Google Scholar 

  • Schultze-Krumbholz, A., Göbel, K., Scheithauer, H., Brighi, A., Guarini, A., Tsorbatzoudis, H., et al. (2015). A comparison of classification approaches for cyberbullying and traditional bullying using data from six European countries. Journal of School Violence, 14(1), 47–65. doi:10.1080/15388220.2014.961067.

    Article  Google Scholar 

  • Slonje, R., Smith, P. K., & Frisen, A. (2013). The nature of cyberbullying, and strategies for prevention. Computers in Human Behavior, 29(1), 26–32. doi:10.1016/j.chb.2012.05.024.

    Article  Google Scholar 

  • Smith, S. L., Lachlan, K., & Tamborini, R. (2003). Popular video games: Quantifying the presentation of violence and its context. Journal of Broadcasting & Electronic Media, 47(7), 58–76.

    Article  Google Scholar 

  • Smith, P. K., Mahdavi, J., Carvalho, M., Fisher, S., & Russell, S. (2008). Cyberbullying-its nature and impact in secondary school students. Journal of Child Psychology and Psychiatry, 49(4), 376–385. doi:10.1111/j.1469-7610.2007.01846.x.

    Article  PubMed  Google Scholar 

  • Sticca, F., Ruggieri, S., Alsaker, F., & Perren, S. (2013). Longitudinal risk factors for cyberbullying in adolescence. Journal of Community and Applied Social Psychology, 23(1), 52–67. doi:10.1002/casp.2136.

    Article  Google Scholar 

  • Subrahmanyam, K., & Greenfield, P. M. (2008). Communicating online: Adolescent relationships and the media. The Future of Children, 18, 119–146.

    Article  PubMed  Google Scholar 

  • Thornberry, T. P., Bjerregaard, B., & Miles, W. (1993). The consequences of respondent attrition in panel studies: A simulation based on the Rochester Youth Development Study. Journal of Quantitative Criminology, 9(2), 127–158. doi:10.1007/BF01071165.

    Article  Google Scholar 

  • Tokunaga, R. S. (2010). Following you home from school: A critical review and synthesis of research on cyberbullying victimization. Computers in Human Behavior, 26(3), 277–287. doi:10.1016/j.chb.2009.11.014.

    Article  Google Scholar 

  • Valkenburg, P. M., & Peter, J. (2009). The effects of instant messaging on the quality of adolescents’ existing friendships: A longitudinal study. Journal of Communication, 59, 121–127. doi:10.1111/j.1460-2466.2008.01405.x.

    Article  Google Scholar 

  • Valkenburg, P. M., & Peter, J. (2011). Online communication among adolescents: An integrated model of its attraction, opportunities, and risks. Journal of Adolescent Health, 48(1), 79–97. doi:10.1016/j.jadohealth.2010.08.020.

    Article  Google Scholar 

  • Vandebosch, H., & van Cleemput, K. (2009). Cyberbullying among youngsters: Profiles of bullies and victims. New Media Society, 11(8), 1349–1371. doi:10.1177/1461444809341263.

    Article  Google Scholar 

  • Vanden Abeele, M. M. P. (2015). Mobile youth culture: A conceptual development. Mobile Media & Communication. doi:10.1177/2050157915601455.

    Google Scholar 

  • Walrave, M., & Heirman, W. (2011). Cyberbullying: Predicting victimization and perpetration. Children and Society, 25(1), 59–72. doi:10.1111/j.1099-0860.2009.00260.x.

    Article  Google Scholar 

  • Wegge, D., Vandenbosch, H., Eggermont, S., & Pabian, S. (2014). Popularity through online harm: The longitudinal associations between cyberbullying and sociometric status in early adolescence. The Journal of Early Adolescence. doi:10.1177/0272431614556351.

    Google Scholar 

  • Wolak, J., & Finkelhor, D. (2011). Sexting: A typology. Crimes Against Children Research Center. http://www.unh.edu/ccrc/pdf/CV231_Sexting%20Typology%20Bulletin_4-6-11_revised.pdf. Accessed 9 May 2015.

  • Wolak, J., Finkelhor, D., & Mitchell, K. (2008). Is talking online to unknown people always risky? Distinguishing online interaction styles in a national sample of youth Internet users. CyberPsychology & Behavior, 11(3), 340–343. doi:10.1089/cpb.2007.0044.

    Article  Google Scholar 

  • Ybarra, M. L., & Mitchell, K. J. (2008). How risky are social networking sites? A comparison of places online where youth sexual solicitation and harassment occurs. Pediatrics, 121(2), 350–357. doi:10.1542/peds.2007-0693.

    Article  Google Scholar 

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Acknowledgments

We would like to thank the participating students and schools.

Funding

The research leading to these results has received funding from the German Research Foundation (DFG) under Grant agreement no. QU 260/9-1.

Author’s Contributions

RF participated in the study design, conducted the field phase of the study, performed the measurement and the statistical analyses, and guided the interpretation of the data, as well as the coordination and drafting of the manuscript; TQ authored the funding application, participated in the design of the study and the interpretation of the data, and revised the manuscript for important intellectual content. All authors read and approved the final manuscript.

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Authors and Affiliations

  1. Department of Children and Child Care, Deutsches Jugendinstitut e.V. (German Youth Institute), Nockherstraße 2, 81541, Munich, Germany

    Ruth Festl

  2. Department of Communication, University of Münster, Bispinghof 9-14, 48143, Münster, Germany

    Thorsten Quandt

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  1. Ruth Festl
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Correspondence to Ruth Festl.

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Ethical Approval

Before recruiting the schools, we checked that the study design and the questionnaire complied with valid ethical guidelines for school surveys and received approval from the federal Ministry of Education.

Informed Consent

Informed consent was obtained from parents as well as students. Students were informed about the aims of the questionnaire and that they could withdraw from participation at any time without negative consequences.

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Festl, R., Quandt, T. The Role of Online Communication in Long-Term Cyberbullying Involvement Among Girls and Boys. J Youth Adolescence 45, 1931–1945 (2016). https://doi.org/10.1007/s10964-016-0552-9

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