Risk factors for involvement in cyber bullying: Victims, bullies and bully–victims

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Abstract

Objectives

The purpose of the current study was to examine the frequency of cyber bullying among youth by distinguishing among the three categories of involvement in cyber bullying: victims, bullies, and bully–victims, to compare these to a fourth category of students who are not involved in the three categories of cyber bullying and to explore the factors that contribute to involvement in cyber bullying.

Method

This study utilized a large and diverse sample of 2186 middle and high school students, who completed self report questionnaires during class time. We performed a Multinomial Logistic Regression to examine the relationship between the cyber bullying categories and our independent variables (gender, age, technology use, parental involvement and safety).

Results

Over 30% of the students in this study identified as involved in cyber bullying, as victims or perpetrators, and one in four of the students (25.7%) reported having been involved in cyber bullying as both bully and victim during the previous three months. Students who were involved in cyber bullying were more likely than others to report perpetration of violence toward peers, to use computers for more hours a day, and to give their password to friends. Other risk factors, such as gender, age and safety, were found to be specific only for one category of cyber bullying.

Conclusion

The findings revealed that students are highly involved in cyber bullying. Several unique characteristics emerged regarding the frequency and risk factors of students' involvement in cyber bullying. In traditional bullying the category of bully–victims represents the smallest and most vulnerable group of children, whereas in the current study the bully–victims category emerged as common. In addition, females were more likely than males to be bully–victims, in contrast to research on traditional bullying, in which more males than females are typically involved as bully–victims. In addition, several risk factors were common among the three groups of children, including the amount of hours per day students use the computer, and giving passwords to a friend. These results point to the need for further examination and to focus on the risk factors for students' cyber bullying involvement in each of the three categories.

Highlights

► We compare cyber bullying: victims, bullies, bully–victims, no involvement. ► We explore the factors that contribute to involvement in cyber bullying. ► One quarter reported involvement as both bully and victim in previous three months. ► In traditional bullying bully–victims represent the smallest most vulnerable group. ► In the current study the bully–victims category emerged as more common.

Introduction

Evidence indicates that 98% of Canadian youth access the Internet and communication technologies on a daily basis (e.g., social networking sites, instant messages) (Cassidy et al., 2009, Mishna et al., 2010). Similarly, 93% of American youth between the ages of 12 to 17 go online occasionally, and nearly two thirds (63%) go online daily (Lenhart, Purcell, Smith, & Zichuhr, 2010). Three of four American teenagers own a cell phone, with 88% of these individuals text messaging (Lenhart, Ling, Campbell, & Purcell, 2010).

The cyber world provides young people with unprecedented opportunities for communication with others both in and out of their existing face-to-face social networks (Cassidy et al., 2009, Gross, 2004, Lenhart and Madden, 2007, Mishna et al., 2010) and with unparalleled opportunities for learning and self-exploration (Blais et al., 2008, Brown et al., 2006). Despite the many benefits of cyber interactions such as social support, identity exploration, and cross-cultural interactions (Jackson et al., 2006, Valkenburg and Peter, 2007), there are risks for youth, in particular the risk of bullying involvement (Berson et al., 2002, Gasser et al., 2010), as youth spend more time online than ever before (Li, 2007, Shariff, 2009).

Students who are cyber bullied report feeling sad, anxious, afraid and unable to concentrate on school (Beran and Li, 2005, Juvonen and Gross, 2008) and may report social difficulties, drug and alcohol use, and eating disorders (Dehue et al., 2008, Fosse and Holen, 2006, Ybarra and Mitchell, 2007). Victimized youth are more likely to skip school (Wolak et al., 2006, Ybarra et al., 2007), to have detentions or suspensions, or to take a weapon to school (Mitchell, Ybarra, & Finkelhor, 2007). Youth who cyber bully are likely to engage in rule-breaking and to have problems with aggression (Ybarra & Mitchell, 2007). A longitudinal study found that involvement in cyber bullying as perpetrator or as victim affects the wellbeing of youth, over and above traditional bullying. More specifically, perpetrating online bullying predicted a significant increase in substance use whereas online victimization predicted decreased quality of life related to sense of wellbeing and belonging (Blais, 2008).

Cyber bullying often occurs in the context of social relationships (Hoff and Mitchell, 2008, Mishna et al., 2009b, National Children's Home, 2002) which challenges the commonly held assumption that it is anonymous (Hinduja and Patchin, 2008, Hinduja and Patchin, 2009, Kowalski and Limber, 2007, Shariff, 2009) and is consistent with understanding bullying as a relationship issue (Craig & Pepler, 2007). Previous research found that one quarter of cyber bullying occurs in the presence of witnesses (Mishna et al., 2010) corresponding with evidence that most traditional bullying occurs in the presence of peers who play key roles (Atlas and Pepler, 1998, Craig and Pepler, 2007). The possible number of online observers is unlimited (Kowalski & Limber, 2007).

Long considered a school-based problem (Craig & Pepler, 2008), electronic communication tools have extended bullying into the realm of the cyber world. There is not a universally accepted definition of cyber bullying however, or a strong theoretical model for how this phenomenon compares with traditional bullying. Both are necessary to establish (Vaillancourt et al., 2008, Vandebosch and Van Cleemput, 2008). Still, several definitions and elements have been used in order to study the phenomenon. Similar to traditional bullying, cyber bullying has been defined as “willful and repeated harm inflicted” (Hinduja & Patchin, 2009, p. 5) towards another. What makes cyber bullying distinct is the use of electronic communication technology as the means through which to threaten, harass embarrass, or socially exclude (Hinduja and Patchin, 2009, Patchin and Hinduja, 2006, Williams and Guerra, 2007). Cyber bullying can encompass the use of an electronic medium to sexually harass (Hinduja and Patchin, 2008, Shariff and Johnny, 2007), including distributing unsolicited text or photos of a sexual nature or requesting sexual acts either online or offline (Schrock & Boyd, 2008). What constitutes repetition in cyber bullying is complex. As it occurs in the public domain (Wendy Craig, personal communication, February 25, 2009), by its very nature cyber bullying involves repetition because material such as email, text, or pictures can be viewed far and wide, can be distributed not only by the perpetrator but by anyone who has access (Campbell, 2005, Slonje and Smith, 2008), and can be difficult or indeed impossible for the victimized child or youth to remove (Wolak, Mitchell, & Finkelhor, 2007). There is increasing research and academic literature devoted to this new form of bullying (Berson et al., 2002, Hinduja and Patchin, 2009, Lenhart and Madden, 2007; Wolak et al., 2006, Ybarra and Mitchell, 2004a, Ybarra and Mitchell, 2004b) including large surveys to determine normative data on the prevalence and character of cyber bullying.

The purpose of the current study was twofold: 1) to study the prevalence of cyber bullying among youth by distinguishing among the three categories of involvement in cyber bullying: victims, bullies, and bully–victims and to compare these to a fourth category of students who are not involved in cyber bullying; and 2) to examine factors that contribute to involvement in each of the cyber bullying categories in comparison to students that are not involved in cyber bullying.

Previous research examining cyber bullying has primarily focused on two categories of involvement, those who are victims and those who are perpetrators. These studies typically found prevalence rates of cyber bullying to range from approximately 10 to 35% (Hinduja and Patchin, 2008, Kowalski and Limber, 2007, Agatson et al., 2007, Li, 2007, Patchin and Hinduja, 2006, Williams and Guerra, 2007), whereas others have found significantly higher rates (Juvonen and Gross, 2008, Mishna et al., 2010, Raskauskas and Stoltz, 2007).

Much of the previous research has attempted to identify risk factors for cyber bullying focusing on demographic and behavioral factors. Inconsistent findings have been reported regarding gender and age difference (Hinduja and Patchin, 2010, Smith et al., 2008). Examining the behavioral factors, research has shown that intensive use of Internet emerged as a risk factor for child cyber harassment (Wolak et al., 2007). Furthermore, the location of the computer in the home was found to be a predictive factor of cyber victimization. Children who use the Internet in private places at their home (e.g., bedroom) were at higher risk to be victimized than children who used computers in a public space in their home (Sengupta & Chaudhuri, 2011). Installing a monitoring system in the computer however, was not associated with level of cyber harassment or bullying (Sengupta & Chaudhuri, 2011). In addition, children who are involved in cyber bullying have been found to be less aware of the risks involved in particular uses of the Internet, such as sharing passwords with others or talking with individuals they did not know in their offline lives (Hinduja and Patchin, 2009, Sengupta and Chaudhuri, 2011).

An additional risk factor that has been discussed in previous research refers to a child or youth's involvement in school violence and bullying. Ybarra and Mitchell (2004a) found that students who were physically victimized at school were more likely to be perpetrators of Internet harassment. These findings were not supported by Raskauskas and Stoltz (2007), who found that traditional victims were not more likely to bully electronically, but rather to also be victimized by electronic means. They found that youth who were considered traditional bullies were more likely to be bullied and to bully through cyber means.

To the best of our knowledge previous studies have distinguished youth who are victims from those who are perpetrators of cyber bullying, but have not focused on youth who are both victims and perpetrators of cyber bullying as a distinct group. Children who both bully and are victimized in traditional bullying are the most severely rejected by peers and have particularly serious adjustment problems (Pellegrini, 1998, Perry et al., 1988). They have also been found to be easily angered and provoked (Olweus, 1978, Schwartz et al., 1997) and to be more victimized by school staff (Khoury-Kassabri, 2009). Consequently this group might also be targeted more for maltreatment by peers (Dodge, 1991). Thus, relying on these finding the purpose of the current study was to examine risk factors for cyber bullying involvement among students who are in the bully–victim category, in addition to those students who are bullies and who are victims.

Section snippets

Method

This study employed an exploratory, cross-sectional survey design to examine cyber bullying among students in grades 6, 7, 10 and 11, attending schools in a large Canadian city. These grades were chosen to reflect middle/junior and high school students, respectively, as the participating school boards believed that sampling from grades five to twelve would prove too unwieldy for participating schools. The study received approval from the University of Toronto Research Ethics Board and the

Cyber bullying

Over 50% of the students in this study identified themselves as involved in cyber bullying, as victims, perpetrators or both (see Table 2). Almost one quarter of the students (23.8%) reported being victimized, 8% reported cyber bullying others, and one in four students (25.7%) reported having been involved in cyber bullying as both bully and victim during the previous three months. Boys reported bullying others more than girls, whereas girls reported being victimized and both bullying and

Discussion

This paper reports on a survey of cyber bullying with a sample of 2186 middle and high school students, in a large urban setting. The aim of the study was to examine the frequency of students' involvement in cyber bullying and to explore the factors that contribute to their involvement in this phenomenon. We report the findings of this study, which we compare with research results on traditional bullying.

Since the 1990s there has been greater focus in research on identifying aggressive victims

Conclusion

This study is unique in examining not only the frequency of youth's self-reported involvement in cyber bullying, but also the ways in which youth are involved. Almost one quarter of the students reported being victimized alone, and one quarter reported being involved as both bully and victim. It is striking that the category of bully–victim emerged as one that included a sizeable percentage of youth, whereas in traditional bullying this category represents the smallest and most vulnerable group

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    We would like to acknowledge Bell Canada for providing support for this research.

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