Journal of Youth and Adolescence

, Volume 45, Issue 9, pp 1931–1945 | Cite as

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

Empirical Research

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.

Keywords

Cyberbullying Online communication Online risk behavior Adolescence Panel survey 

References

  1. 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
  2. Bandura, A. (2001). Social cognitive theory of mass communication. Media Psychology, 3(3), 265–299. doi:10.1207/S1532785XMEP0303_03.CrossRefGoogle Scholar
  3. 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.CrossRefGoogle Scholar
  4. 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.CrossRefPubMedGoogle Scholar
  5. 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.CrossRefGoogle Scholar
  6. 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.CrossRefGoogle Scholar
  7. 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
  8. 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.CrossRefGoogle Scholar
  9. 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.CrossRefGoogle Scholar
  10. 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.CrossRefGoogle Scholar
  11. 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.CrossRefGoogle Scholar
  12. 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.CrossRefPubMedGoogle Scholar
  13. 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.CrossRefGoogle Scholar
  14. 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.CrossRefGoogle Scholar
  15. 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.CrossRefGoogle Scholar
  16. 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.CrossRefGoogle Scholar
  17. 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
  18. Gauntlett, D. (2008). Media, gender and identity. An introduction. Abingdon, UK: Routledge.Google Scholar
  19. 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.
  20. 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.CrossRefGoogle Scholar
  21. 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.CrossRefPubMedGoogle Scholar
  22. 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.CrossRefGoogle Scholar
  23. Jessor, R. (1987). Problem-behavior theory, psychosocial development, and adolescent problem drinking. British Journal of Addiction, 82(4), 435–446.Google Scholar
  24. 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.CrossRefPubMedGoogle Scholar
  25. Kopecký, K. (2011). Sexting among Czech preadolescents and adolescents. New Educational Review, 28(2), 39–48.Google Scholar
  26. 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.CrossRefPubMedGoogle Scholar
  27. 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.CrossRefGoogle Scholar
  28. 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.CrossRefGoogle Scholar
  29. 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.PubMedGoogle Scholar
  30. 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.
  31. 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
  32. 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.CrossRefGoogle Scholar
  33. 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.CrossRefGoogle Scholar
  34. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  35. 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.CrossRefGoogle Scholar
  36. Milosevic, T. (2015). Cyberbullying in US mainstream media. Journal of Children and Media, 9(4), 492–509. doi:10.1080/17482798.2015.1089300.CrossRefGoogle Scholar
  37. 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.CrossRefPubMedGoogle Scholar
  38. 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
  39. 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.CrossRefGoogle Scholar
  40. Rosseel, Y. (2011). Lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36.Google Scholar
  41. 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.CrossRefGoogle Scholar
  42. 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.CrossRefGoogle Scholar
  43. 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.CrossRefGoogle Scholar
  44. 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.CrossRefGoogle Scholar
  45. 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.CrossRefPubMedGoogle Scholar
  46. 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.CrossRefGoogle Scholar
  47. Subrahmanyam, K., & Greenfield, P. M. (2008). Communicating online: Adolescent relationships and the media. The Future of Children, 18, 119–146.CrossRefPubMedGoogle Scholar
  48. 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.CrossRefGoogle Scholar
  49. 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.CrossRefGoogle Scholar
  50. 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.CrossRefGoogle Scholar
  51. 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.CrossRefGoogle Scholar
  52. 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.CrossRefGoogle Scholar
  53. Vanden Abeele, M. M. P. (2015). Mobile youth culture: A conceptual development. Mobile Media & Communication. doi:10.1177/2050157915601455.Google Scholar
  54. 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.CrossRefGoogle Scholar
  55. 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
  56. 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.
  57. 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.CrossRefGoogle Scholar
  58. 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.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Children and Child CareDeutsches Jugendinstitut e.V. (German Youth Institute)MunichGermany
  2. 2.Department of CommunicationUniversity of MünsterMünsterGermany

Personalised recommendations