The recent cases of bullying in schools have been largely cases of cyberbullying (International Association of Chiefs of Police, 2012). According to the IACP (2012), 32% of online teens are suffering from online harassment. In addition, 26% of teens have suffered harassment through their cell phones either through voice calls or text messages. The report also showed that 33% of youth are bullied online and offline, usually by the same bullies (IACP, 2012). Indeed, cyberbullying has become increasingly important in order to understand and potentially reduce bullying incidents in schools (Heirman & Walrave, 2011).
Erdur-Baker (2010) claimed that a significant number of students today have experienced being both victims of bullying in the traditional sense and victims of cyberbullying. The researcher also found that as high as 26% of children have perpetrated bullying others, both in the traditional sense and through electronic devices. Erdur-Baker (2010), however, claimed that the phenomenon of cyberbullying cannot just be lumped with the phenomenon of bullying in the traditional sense. Cyberbullying also has its own unique characteristics that traditional bullying does not have (Erdur-Baker, 2010). Heirman and Walgrave (2011) claimed that the most common method that students carry out cyberbullying is by posting hurtful comments and spreading rumors online against someone. Heirman and Walgrave (2011) also found that cyberbullying is most prevalent among students in the middle school.
Some studies have also explored the association of school bullying and later offenses or later violent acts. For example, Ttofi, Farrington, Losel, and Loeber (2011) examined the extent to which bullying perpetration at school is a significant predictor of later offenses in life and whether this relationship is mediated by certain risk factors during childhood. It was found that bullying perpetration was a significant predictor for later offending. Moreover, there is a higher probability of school bullies than non-involved students to commit offenses for up to 11 years later.
This is consistent with the findings of Bender and Losel’s (2011) study about school bullying as a significant predictor of delinquency, violence, and anti-social behavior in adulthood. The results indicated that bullying was a significant strong predictor of almost all anti-social outcomes such as violence, drug use, aggressiveness, and impulsivity. The authors noted that physical bullying was more predictive of this result more than verbal or indirect bullying. When the authors controlled for the family risks and internalizing or externalizing problems, the effect sizes were only reduced but it was still significant. On the other hand, bullying victimization was not related to anti-social outcomes.
Lindenberg, Salmivalli, Sijtsema, and Veenstra (2009) addressed the goals behind bullying and victimization. Authors note that although attention may in fact be a goal of bullies, their friends who reinforce this behavior are not the roots of the problem. Researchers also find that most perpetrators of bullying come from broken families where there are many underlying problems. These findings are somewhat consistent with Swidey’s (2010) popular media article on bullying in that they say the act of bullying is an attention seeking, reinforcing behavior.
No doubt, many studies show that bullying between students can affect the physical, emotional, social, and psychological well being, as well as their learning ability and academic performance. Many researchers in the academe have found the extent of cyberbullying and its effects on students’ well-being, behavior, and scholastic achievement. And as locus parenti of students, it would be beneficial for teachers to have a firm grasp of this startling phenomenon.
References
Bender, D. ,., & Lösel, F. (2011). Bullying at school as a predictor of delinquency, violence and other anti-social behaviour in adulthood. Criminal Behaviour and Mental Health, 21 (2), 99–106.
Erdur-Baker, Ö. (2010). . Cyberbullying and its correlation to traditional bullying, gender and frequent and risky usage of internet-mediated communication tools. New Media & Society, 12(1), 109-125. DOI: 10. 1177/1461444809341260
Heirman, W. &Walgrave, M. (2011). Cyberbullying: Predicting victimisation and perpetration. Children & Society, 25(1), 59-72. doi: 10. 1111/j. 1099-0860. 2009. 00260. X
International Association of Chiefs of Police. (2012). Social media and crime prevention fact sheet.
Lindenberg, S. , Salmivalli, C. , Sijtsema, J. J. , & Veenstra, R. (2009). Empirical Test of Bullies’ Status Goals: Assessing Direct Goals, Aggression, and Prestige. Aggressive Behavior , 57-67. doi: 10. 1002/ab. 20282
Swidey, N. (2010, May 2). The Secret to Stopping Bullying? Boston Globe , pp. 1-5. Retrieved from http://www. boston. com/bostonglobe/magazine/articles/2010/05/02/the_secret_to_stopping_a_bully/
Ttofi, M. M. , Farrington, D. P. , &Lösel, F. (2012). School bullying as a predictor of violence later in life: A systematic review and meta-analysis of prospective longitudinal studies. Aggression and Violent Behavior, 17(5), 405-418. doi:10. 1016/j. avb. 2012. 05. 002
By: Jason A. Untalan
