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Differences in Proactive and ReactiveAggression in Traditional Bullies andCyberbulliesK. Alex Burton a , Dan Florell b & Jonathan S. Gore ba Department of Psychology, University of Alabama, Tuscaloosa,Alabama, USAb Department of Psychology, Eastern Kentucky University, Richmond,Kentucky, USA

To cite this article: K. Alex Burton , Dan Florell & Jonathan S. Gore (2013): Differences in Proactiveand Reactive Aggression in Traditional Bullies and Cyberbullies, Journal of Aggression, Maltreatment &Trauma, 22:3, 316-328

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Journal of Aggression, Maltreatment & Trauma, 22:316–328, 2013Copyright © Taylor & Francis Group, LLCISSN: 1092-6771 print/1545-083X onlineDOI: 10.1080/10926771.2013.743938

Differences in Proactive and ReactiveAggression in Traditional Bullies and

Cyberbullies

K. ALEX BURTONDepartment of Psychology, University of Alabama, Tuscaloosa, Alabama, USA

DAN FLORELL and JONATHAN S. GOREDepartment of Psychology, Eastern Kentucky University, Richmond, Kentucky, USA

This study examined how proactive and reactive aggressionrelated to traditional bullying and cyberbullying. Participants were851 students in Grades 6 through 8 who completed a surveythat assessed bullying behaviors, proactive aggression, and reac-tive aggression. Most of these students were Caucasian and from arural background. For both traditional bullying and cyberbullyinggroups, uninvolved students were found to have significantly lowerproactive and reactive aggression than bullies and bully-victims.Further, it was found that for traditional and cyberbullyinggroups, bully-victims had significantly higher proactive and reac-tive aggression than bullies. Implications and future directions arediscussed.

KEYWORDS aggression, bullying, cyberbully

Bullying in schools has been prevalent for many years and a considerableamount of the research on bullying has examined the impact on victims(Beaty & Alexeyev, 2008; Cook, Williams, Guerra, Kim & Sadek, 2010).However, it is also important to consider the bullies themselves. Therefore,this study focuses on bullies and bully-victims (i.e., those who are both abully and a victim), and how they compare to students who are uninvolvedin bullying.

Received 29 August 2011; revised 20 April 2012; accepted 23 April 2012.Address correspondence to K. Alex Burton, Department of Psychology, The University

of Alabama, Box 870348, Tuscaloosa, AL 35487–0348. E-mail: kaburton1@ua.edu

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Aggression and Cyberbullying 317

Traditional bullying has been conceptualized as a type of aggressionrepeatedly directed toward a person and is characterized by an imbalanceof power (Olweus, 1993). Recent technological advances have led to thedevelopment of cyberbullying, a type of aggressive behavior in which theperpetrator repeatedly utilizes the Internet, computers, or other forms oftechnology to harass a victim (Patchin & Hinduja, 2006). Henceforth, werefer to traditional bullying as offline bullying and cyberbullying as onlinebullying. Evidence suggests that offline bullying is related to aggression(Camodeca, Goossens, Terwogt, & Schuengel, 2002; Ireland & Power, 2004;Machek, 2006), but because cyberbullying is a new phenomenon, the con-nection to aggression is relatively unexplored. Furthermore, research rarelydistinguishes among the types of aggression bullies might exhibit.

This study focuses on two main types of aggression in bullying:proactive and reactive (Dearing, Hubbard, McAuliffe, Morrow, & Rubin,2007). Proactive aggression is usually planned with the goal of gainingsomething else; it is a means to an end (Fite, Colder, Lochman, & Wells,2008). Unprovoked bullying behaviors are an example of proactive aggres-sion where the gained reward might be attention, admiration, or status frompeers. In contrast, reactive aggression is defense-driven and is the result ofothers’ behaviors, particularly if those behaviors are threatening or perceivedas intentional; it is an end in itself (Fite et al., 2008). For example, reactiveaggression might take the form of physical or verbal retaliation such as push-ing or shouting toward an aggressor or bully. Thus, bullies can exhibit bothproactive and reactive aggression.

OFFLINE BULLYING

There are various participants in offline bullying such as the bullies, victims,bully-victims, and those who are uninvolved. Offline bullies, who often havehigh levels of aggression and are less prosocial and cooperative than oth-ers (Perren & Alsaker, 2006), are the active aggressors within the bullyingprocess, and the victims are the recipients of the bully’s aggression. Offlinebullying is highly comorbid with other problematic behaviors in youth. Forexample, offline bullies often use tobacco and intoxicants (Nansel et al.,2001). In addition, offline bullies are at a higher risk than other youth forbehavioral problems and later problems in adulthood, potentially includingcriminal activity (Eliot & Cornell, 2009).

Another type of bully is a bully-victim, who is both the recipient andperpetrator of bullying (Menesini, Modena, & Tani, 2009; Solberg, Olweus,& Endresen, 2007). Bully-victims often have the poorest outcomes in termsof social and emotional adjustment (Gradinger, Strohmeier, & Spiel, 2009;Nansel et al., 2001), the highest levels of aggression (Veenstra et al., 2005),and are bullied more than victims who do not bully (Dulmus, Sowers, &

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Theriot, 2006). In contrast, uninvolved students are those who do not par-ticipate, or are minimally involved, in bullying. These individuals often havebetter academic performance (Veenstra et al., 2005) and lower levels ofaggression than offline bullies (Perren & Alsaker, 2006).

Research suggests that aggression and bullying are interrelated. Forexample, offline bullies and offline bully-victims have been found to havehigh proactive and reactive aggression (Camodeca et al., 2002). In fact,offline bullying can be predicted by proactive and reactive aggressive traits(Machek, 2006). Typically, offline bullies have a higher degree of proactiveaggression than other students (Pellegrini, Bartini, & Brooks, 1999), whereasboth offline bullies and offline victims are more reactively aggressive thantypical students (Camodeca & Goossens, 2005). Reactive aggression tends topredict future proactive aggression (Salmivalli & Helteenvuori, 2007), whichsuggests that engaging in one type of aggression could lead to the other,more harmful, displays of aggression. Given the link between offline bully-ing and aggression, it is important to determine if such a connection existsbetween aggression and online bullying as well.

ONLINE BULLYING

Online bullying has several distinct features. First, the harm inflicted on thevictim is psychological in nature rather than physical. Generally, the home,rather than the school or social setting, is the environment in which onlinebullying occurs (Dehue, Bolman, & Völlink, 2008). This environment allowsonline bullies the opportunity to engage in harassing behaviors without adultsupervision at any time (Patchin & Hinduja, 2006). Another distinct featureof online bullying is anonymity, which results in an absence of account-ability and identifiability (Nogami & Takai, 2008), and promotes antisocialbehavior (Mathes & Guest, 1976). Although the identity of the bully isnot always hidden from the victim, anonymity does play a role in someinstances. For example, one study reported that over one fourth of onlinevictims were unsure of the identity of their cyberbully (Juvonen & Gross,2008). Essentially, the Internet and computer systems become environmentsin which masked aggression can thrive (Dehue et al., 2008). Online bullyingis thus a phenomenon distinct and separate from offline bullying, althoughoffline bullies are at risk to also engage in cyberbullying (Burton, Florell, &Wygant, 2013; Erdur-Baker, 2010).

Online bullying seems widespread because of the overall ease of accessadolescents have to new communication technology, which is easily usedfor verbal and other nonphysical forms of harassment (Abelman, 2007).These communication tools have options for copying and pasting materialand offer quick access to personal information (Juvonen & Gross, 2008).Furthermore, online bullying does not require that a bully be at the same

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location and time as the victim. This could result in a delay in the noti-fication of the online bullying, so the victim is not immediately aware ofthe harassment. Put simply, the characteristics of online bullying, such asasynchrony and anonymity, provide an environment conducive for suchbehaviors.

There is evidence of the relationship between aggression and onlinebullying that suggests aggression is closely linked to online bullying muchlike offline bullying. One study found that those who had higher normativebeliefs about aggression were more likely to be online and offline bullies(Burton et al., 2013). The aim of this study is to further elucidate the rela-tionship between online bullying and aggression by showing how groupstatus (e.g., online bully-victim) relates to proactive and reactive aggression.Another study found that online bullying was significantly associated withproactive aggression (Calvete, Orue, Estevez, Villardon, & Padilla, 2010).However, in addition to examining how online bullying relates to proactiveand reactive aggression, this study used a categorical approach to bullyingand included an online and offline bully-victim group in the analyses, whichexpands on the findings of Calvete et al. (2010). Therefore, this study offersa novel contribution to the online bullying literature.

THIS STUDY

The purpose of this study is to examine the relationship of proactive andreactive aggression to offline and online bullying. Because of the similari-ties between offline and online bullying, the predictions about proactive andreactive aggression for offline bullying will be the same as those for onlinebullying. It is predicted that offline uninvolved students will have significantlylower reactive and proactive aggression than offline bullies (Hypotheses1 and 2) and offline bully-victims (Hypotheses 3 and 4). It is also predictedthat online uninvolved students will have significantly lower reactive andproactive aggression than online bullies (Hypotheses 5 and 6) and onlinebully-victims (Hypotheses 7 and 8).

METHOD

Participants

Participants were 851 middle school students (337 males, 501 females,13 unspecified) in Grades 6 through 8, ages 10 to 16 years old (M = 12.93,SD = 0.92). Participants completed a questionnaire that contained demo-graphic information such as age, socioeconomic status (51.2% were on a freeor reduced-price lunch program), gender, county and state of residence, eth-nicity (91% Caucasian, 2.5% African American, 1.4% Hispanic, 1.2% American

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Indian, 1% Asian, and 2.4% unspecified), grade level, and grades typicallyreceived in school (the minority population in the sample corresponds withthe U.S. Census for that rural area). Additionally, the questionnaire con-tained the offline bullying, online bullying, reactive aggression, and proactiveaggression measures.

Materials

OFFLINE BULLYING

This scale was adapted from previous research (Jolliffe & Farrington,2006; Olweus, 1991; Whitney & Smith, 1993). The offline bullying scale(α = .813) contained seven statements such as “I spread rumors about some-one” or “I physically hurt someone” to measure the student as the perpetratorof bullying behaviors. Participants rated the statements on a 5-point scale(1 = never, 2 = once or twice this year, 3 = a few times this year, 4 =about one time every week, 5 = about a few times every week) to assess theprevalence and frequency of offline bullying. The greater the score on thismeasure, the higher the frequency of bullying behaviors.

ONLINE BULLYING

The online bullying scale (α= .894), which has been used in recent research(Ang & Goh, 2010), contains nine statements such as “I sent or posted crueland untrue things about someone” and “I kept on sending someone rude andinsulting messages” to measure the student as the online bully. Participantsrated the statements on a 5-point scale (1 = never, 2 = once or twice thisyear, 3 = a few times this year, 4 = about one time every week, 5 = abouta few times every week) to assess the prevalence and frequency of onlinebullying. The greater the score on this measure, the higher the frequency ofonline bullying behaviors (see the Appendix).

PROACTIVE AND REACTIVE AGGRESSION

Participants also completed the Reactive Proactive Aggression Questionnaire,Child Version (RPQ–C; Raine et al., 2006) to measure reactive and proactiveaggression among children and adolescents. Participants rated each state-ment such as “I yell at others when they annoy me” and “I have tempertantrums” on a 3-point scale (0 = never, 1 = sometimes, 2 = often). Thismeasure yields a total score, in addition to a score for 12 items assessingproactive aggression (α = .80) and 11 items for reactive aggression (α = .82).For the purposes of this study the total score is not used, only the scores onthe two subscales.

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Procedure

University institutional review board approval, school district, parentalconsent, and student assent were obtained before data collection. Aftercontacting schools in six rural public school districts about participat-ing, administrators collected consent forms from students they allowed toparticipate.1 The recruitment method varied among the schools, at the dis-cretion of the school’s administrators, but all participants were given a briefsummary of the purpose of the study prior to participation. In each school,participants were administered the questionnaires, which took approximately40 minutes to complete, in a large group setting. Prior to the testing ses-sion, participants met at a designated area to complete the questionnairesand were seated at tables with at least two empty seats separating eachstudent to reduce information sharing and response acquiescence. Theinvestigator remained present for the entire session to answer any ques-tions and, on completion of the instruments, students returned to theirclassrooms.

Offline and Online Bullying Groups

Offline bullying and online bullying groups were designated using a methodsimilar to Burton et al. (2013), Demaray and Malecki (2003), and Veenstraet al. (2005), which is based on a frequency of scores. The students whoscored at or above the 75th percentile on the offline bullying or online bul-lying scales and at or below the 50th percentile on offline victimization oronline victimization scales were designated as offline bullies or online bul-lies, respectively. Offline bully-victims were students who scored at or abovethe 75th percentile on both the offline bullying and victimization scales.Students who scored at or above the 75th percentile on both the online bul-lying and online-victimization scales were designated as online bully-victims.The uninvolved students were those who scored at or below the 50th per-centile on victimization and bullying measures. It is important to note thatthose who are designated as offline bullies and offline bully-victims are notnecessarily the same students as the online bullies and online bully-victims.

RESULTS

A multivariate analysis of variance (MANOVA) was conducted to determinethe effect of offline group status (offline bully, offline bully-victim, offlineuninvolved) and online group status (online bully, online bully-victim, onlineuninvolved) on proactive and reactive aggression. The omnibus test revealed

1 Each school made the decision of which grade levels and classrooms were allowed to participate.

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TABLE 1 Mean Scores on Dependent Variables by Offline and Online Group Status

Bully-victim Bully Uninvolved

Dependent variables Offlinea Onlineb Offlinec Onlined Offlinee Onlinef

Proactive aggression 7.15 6.68 3.26 4.57 1.22 1.24Reactive aggression 14.12 13.61 9.96 10.93 6.77 7.07

an = 104. bn = 142. cn = 53. dn = 75. en = 140. fn = 279.

significant main effects of offline group status, F(4, 570) = 7.48, p < .01,Wilks’s λ = .90, and online bullying group status, F(4, 570) = 4.86, p < .01,Wilks’s λ = .93. There was not a significant Offline Status × Online Statusinteraction effect.

Follow-up univariate analyses revealed significant differences amongoffline groups on proactive aggression, F(2, 285) = 9.80, p < .01, and reactiveaggression, F(2, 285) = 13.31, p < .01 (see Table 1 for descriptive statistics).A Tukey test of pairwise comparisons revealed significant differences amongall three groups on proactive and reactive aggression. The offline bully-victim group was significantly higher than the other two offline groups inboth forms of aggression, and the offline bully group was also significantlyhigher than the offline uninvolved group in both forms of aggression. Theresults confirmed all of the hypotheses regarding offline bullying.

Similar to the offline groups, follow-up univariate analyses revealed sig-nificant differences among online bullying groups on proactive aggression,F(2, 285) = 6.92, p < .01, and reactive aggression, F(2, 285) = 8.48, p < .01(see Table 1 for descriptive statistics). A Tukey test of pairwise comparisonsrevealed significant differences among all three groups on proactive andreactive aggression. Replicating the earlier results, the online bully-victimgroup was significantly higher than the other two online groups in bothforms of aggression, and the online bully group was also significantly higherthan the online uninvolved group in both forms of aggression. The resultsconfirmed all of the hypotheses regarding online bullying.

DISCUSSION

The purpose of this study was to examine the differences in proactive andreactive aggression among types of bullies. In support of the predictions,the findings suggest that those uninvolved in online and offline bullyinghave significantly lower proactive and reactive aggression than bullies andbully-victims. It was also found that both online and offline bully-victimshad higher proactive and reactive aggression than bullies. These results sup-port past research that offline bully-victims have high levels of aggression

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(Camodeca et al., 2002; Nansel et al., 2001) and contribute to the literatureby demonstrating that online bully-victims also have the highest proactiveand reactive aggression. This might provide some insight as to why bully-victims have poor adjustment (Gradinger et al., 2009; Nansel et al., 2001;Veenstra et al., 2005)

For offline bullies and offline bully-victims, this might suggest thatextended involvement in subcultures of aggression (where bullying is anormative behavior) could result in higher levels of proactive and reactiveaggression compared to uninvolved individuals, who have little experiencewith offline bullying. On the other hand, bully-victims, who are involved inbullying more often than others, had even higher aggression than bullies.Taken together, this provides support for the notion that involvement in bul-lying relates to proactive and reactive aggression, and that this aggression ismore pronounced among bullies who are also victims of aggression.

A more important aspect of this study regarded online bullying. As men-tioned before, only one study has examined how online bullying relatesto proactive and reactive aggression (Calvete et al., 2010). This study didnot address differences in aggression in bully-victims though, nor did itdemonstrate that online and offline bullying category membership relatesto proactive and reactive aggression. Additionally, this study expanded onresearch that found a relationship between normative beliefs about aggres-sion and online bullying (Burton et al., 2013) by showing that online bullyingrelates to aggression, rather than beliefs about aggression.

Limitations

There are some limitations to this study that should be addressed before fur-ther research is conducted on the topic. The use of self-report measures (e.g.,offline and online bullying scales) can be vulnerable to students respondingin a socially desirable manner. This is particularly the case with bullying, asthe perpetrators can sometimes find themselves in trouble for participatingin these behaviors. Thus, one would expect not every instance of bully-ing to be accurately reported, which would underestimate the frequency ofsuch behaviors (Eliot & Cornell, 2009; Seals & Young, 2003). Additionally,the sample was gathered in a rural setting and contained only a small num-ber of minorities, so the findings might not generalize to urban or minoritypopulations.

The groups by which the bullies, bully-victims, and uninvolved studentswere designated are arbitrary; some students can be offline bullies and onlinebullies simultaneously. To be classified as a bully, one would have to be ator above the 75th percentile on the bullying scale. Those who bully fre-quently, yet fail to meet this cutoff, are still bullies in the sense of the word,but they are not designated as such in this study. Therefore, this study didnot classify those who engage in bullying behaviors infrequently as bullies.

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Additionally, this study design does not provide information on potentialcausal relationships (and how those relationships are temporally ordered)between online bullying and aggression.

Future Directions and Conclusions

The findings demonstrate the need for additional research into differencesbetween offline bullying and the more recent phenomenon of online bully-ing. Online bully-victims have a high risk of depression (Patchin & Hinduja,2010) and decreased self-esteem (Wang, Nansel, & Iannotti, 2011), so theymight have the worst outcomes of all those involved. Increased proactiveand reactive aggression might also increase the likelihood of future involve-ment in online and offline bullying. Therefore, this study demonstrates theneed for future research on online bullying, especially in its relationship toaggression-related constructs.

An important aspect of this research is that it highlights the similari-ties between offline and online bullying. Such findings could be particularlyuseful in schools where this, and related online bullying research, could beutilized to inform students and teachers on ways of dealing with online bully-ing situations. Research has provided evidence of the effectiveness of offlinebully intervention programs in increasing social competence, peer accep-tance, and self-esteem (Merrell, Gueldner, Ross, & Isava, 2008). Programssuch as these might be equally effective for online bullies.

The two main types of aggression, proactive and reactive, might explainthe cycle of online and offline bullying. Once norms involving aggressionhave been established, it might be difficult to change them. It would beinteresting to see how online bullies and bully-victims enter this cycle.Longitudinal studies might help determine when and where the use ofaggression online begins and the outcomes of the students who use it. Thiswould provide additional insight into the origin and consequences of engag-ing in online bullying behaviors, as offline bullies tend to have increasedrisk for relationship problems later in life than others (Pepler, Craig, Jiang, &Connolly, 2008).

Although this study only focused on the aforementioned bullying cate-gories, three other categories have been outlined in the literature. Reinforcerswork to assist and reinforce the bullying behaviors, whereas defendersattempt to neutralize the bullying and defend victims against it (Salmivalli,2010; Salmivalli, Kaukiainen, & Voeten, 2005). Similar but distinct fromthe uninvolved students, outsiders are those who withdraw from bullyinginvolvement by pretending to be unaware of it. Future research shouldaddress how these bullying categories relate to bullies, bully-victims, andthose who are uninvolved in online bullying.

In sum, this study has shown that proactive and reactive aggressionis important to consider for online bullies in particular. Online bullying

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appears to be similar to offline bullying in the degree of proactive andreactive aggression. Furthermore, this research demonstrated that for onlineand offline bullying, bully-victims are particularly high in proactive and reac-tive aggression. This suggests that more research is needed to fully examinethe ways in which online bullying is similar to, and differs from, offlinebullying.

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APPENDIX

Online Bully Scale

1. I made fun of someone by sending/posting stories, jokes or pictures abouthim/her.

2. I purposely left someone out from an online group.3. I sent or posted cruel and untrue things about someone4. I entered or used someone’s e-mail, website, or computer without his/her

permission.5. I sent or posted messages to someone saying that I will hurt him/her.6. I pretended to be someone else and sent/posted messages to get that

person into trouble or make the person look bad.7. I kept on sending someone rude and insulting messages.8. I spread rumors or gossip about someone.9. I tricked someone to provide me secret or embarrassing information and

then I sent/posted it online to others.

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Online Victimization Scale

1. Someone made fun of me by sending/posting stories, jokes, or picturesto describe me.

2. Someone purposely left me out of an online group.3. Someone sent/posted cruel and untrue things about me4. Someone entered or used my e-mail, website, or computer without my

permission.5. Someone sent or posted messages saying that he/she will hurt me.6. A person pretended to be someone else and sent/posted messages to get

me into trouble or made me look bad.7. Someone kept sending me rude and insulting messages.8. Someone spread rumors or gossip about me.9. Someone tricked me to provide secret or embarrassing information and

sent/posted it online to others.

Have any of these things happened to you this year? Please circle the numberthat best describes you.

1 = Never2 = Once or twice this year3 = A few times this year4 = About one time every week5 = About a few times every week

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