Cyberbullying in adolescents: Modalities and aggressors’ profile
Introduction
Violent behavior among adolescents and young people is a severe problem in many countries. In recent years, new forms of aggression based on information and communication technology (computers, cell phones, etc.) have been added to the traditional forms of violence. In this context, cyberbullying (CB) has been defined as an aggressive and deliberate behavior that is frequently repeated over time, carried out by a group or an individual using electronics and aimed at a victim who cannot defend him- or her-self easily (Smith, 2006). Patchin and Hinduja (2006) describe it as deliberate and repeated harm performed with some kind of electronic text. These violent behaviors can be carried out by means of a cell phone, electronic mail, Internet chats, and online spaces such as MySpace, Facebook, and personal blogs.
Although in many cases, CB implies acts of traditional aggression (for example, insulting, spreading rumors, or threatening), which are communicated electronically instead of face-to-face, CB can also include unique behaviors with no analogue in traditional bullying. For example, the phenomenon known as bombing occurs when the aggressor uses an automated program to collapse the victim’s e-mail with thousands of simultaneous messages, causing failure and blocking of the victim’s e-mail account (Burgess-Proctor, Patchin, & Hinduja, 2008).
As this phenomenon is new, there is as yet little agreement about the diverse categories of this form of violence, so that in the studies carried out, different classifications can be found (e.g., Burgess-Proctor et al., 2008, Smith et al., 2006, Willard, 2006, Willard, 2007). For example, according to Willard, 2006, Willard, 2007, some of the modalities that CB can adopt are (1) online fights, known as flaming, which imply the use of electronic messages with hostile and vulgar language; (2) slandering, a modality that implies online disparagement, for example, sending cruel images or rumors about others to spoil their reputations or social relationships; (3) impersonation (hacking) by infiltration into someone’s account in order to send messages that make the victim lose face, cause trouble for or endanger the victim, or harm the victim’s reputation and friendships; (4) defamation by spreading secrets or embarrassing information about someone; (5) deliberate exclusion of someone from an online group; (6) cyber harassment or the repeated sending of messages that include threats of injury or that are very intimidating.
The phenomenon known as happy slapping consists of recording with cell phone cameras images in which a person, who is often in a minority situation, is attacked. The image or video is later shared with friends, posted online, or distributed electronically. This phenomenon has recently been the object of attention by the mass media in many European countries.
Diverse studies warn about the high occurrence of CB. Table 1 shows a sample of some representative studies. For example, in one of the first studies of CB, Ybarra and Mitchell (2004) surveyed 1501 children and adolescents between ages 10 and 17 years by phone and found that 12% had participated in cyberbullying. Li (2006), in a sample of 264 high school students, found that 22% of the boys and 12% of the girls admitted having cyberbullied others. In a cross-cultural study, the same authoress found percentages of cyberbullies ranging between 15% and 7%, respectively, for Canada and China (Li, 2008). In a study carried out with Turkish students, 35.7% admitted performing CB (Aricak et al., 2008). In Spain, Ortega, Calmaestra, and Mora-Merchán (2008) found in adolescents that 5.7% admitted having performed CB occasionally, and 1.7% had carried out severe forms of CB. Although most of the research was carried out in schools, in some cases it was online (Hinduja & Patchin, 2008).
A limitation of many of the studies is that they assessed the occurrence of CB generically, without specifying in detail the modalities employed. For example, in some cases, they focused on providing a definition of CB and asking the participants whether they had carried out CB, and if so, to describe aspects such as the means employed (chat room, e-mail, cell phone). This perspective is valuable to address a new phenomenon about which relatively few studies have been carried out. However, as we discover more about the importance of the phenomenon, it becomes appropriate to develop more specific measures that include a broad array of CB modalities. Therefore, the first goal of this study consisted of developing a questionnaire to assess the performance of many types of CB by adolescents.
On the other hand, CB reveals a series of differences with the traditional types of maltreatment and bullying among schoolmates. Elements such as the perception of online anonymity and the safety of hiding behind a computer screen contribute to freeing individuals from traditional constraints and social pressures, as well as from moral and ethical misgivings (Hinduja and Patchin, 2008, Li, 2007a, Li, 2007b). Thus, adolescents who would not behave violently in a face-to-face situation can adopt different roles and perform this type of violence. Anonymity also implies the absence of consequences, because the aggressors frequently cannot be identified and, therefore, they avoid punishment. These characteristics make one wonder whether the psychological profile of the adolescents who carry out CB is similar to or different from the profile associated with traditional forms of violence. Therefore, the second goal of the study consisted of assessing the relation between CB, offline forms of violence, and associated risk factors.
Regarding the relation of CB to other violent behaviors in adolescents, CB should be associated with forms of proactive aggression and indirect aggression. Proactive aggression consists of deliberate and planned behavior with the intention of obtaining a reward and is differentiated from reactive aggression, which refers to a furious response to a perceived threat or provocation (Dodge, 1991). In fact, previous studies suggest that traditional bullying is more closely associated with proactive than with reactive aggressiveness (Roland and Idsøe, 2001, Schwartz et al., 1998, Unnever, 2005). On the other hand, indirect aggression, also called relational or social aggression, consists of harming someone by means of manipulating relationships (Björkqvist, 2001, Björkqvist et al., 1992, Crick and Grotpeter, 1995). In this type of aggression, covert strategies are used in order to exclude and isolate rivals in the peer group. These actions include spreading rumors about others, threatening to end personal relationships, and to reveal private information (Crick, 1995, Galen and Underwood, 1997). In this sense, certain forms of CB have the same characteristics as traditional indirect bullying (Dehue, Bolman, & Völlink, 2008) and CB has even been defined as a computer-mediated form of indirect aggression (Piazza & Bering, 2009).
One of the risk factors that have been traditionally associated with the above-mentioned forms of aggressive behavior, and with bullying in particular, are normative beliefs about the justification of violence. Adolescents’ experiences throughout their lives lead them to store in their memories certain knowledge structures that affect their future behavior. Cognitive-social theories have generally called such knowledge structures schemas or scripts (Huesmann, 1988). In the case of aggressive behavior, many studies have revealed the presence of schemas related to the justification of the use of violence. For example, various studies have detected that children and adolescents who believe that it is appropriate to attack others when they deserve it are more apt to be aggressive (Bentley and Li, 1995, Bosworth et al., 1999, Calvete, 2008, Calvete and Cardeñoso, 2005, Huesmann and Guerra, 1997). In fact, a recent study of Williams and Guerra (2007) found an association between justification of violence and CB. However, in their study, the measurement of CB was a single question that referred to spreading lies about classmates by e-mail or instant messaging, and other forms of CB were not included.
In addition, a series of contextual variables have been linked to violent behavior for a long time. Firstly, the role of exposure to violence was pointed out from the social learning model by Bandura (1986). Children who observe more positive consequences and fewer negative ones for aggression acquire the belief that aggressive behavior leads to good consequences. In general, diverse studies support the fact that aggressive behavior increases with exposure to violence at home, at school, in the neighborhood, and in the mass media (Baldry, 2003, Coyne and Archer, 2005, Flannery et al., 2004, Gorman-Smith et al., 2004, Harold and Conger, 1997, Huesmann et al., 2003, Schwartz and Proctor, 2000).
Lastly, among the contextual variables are experiences with peers, and rejection by peers is one of the most important factors (Laird, Jordan, Dodge, Pettit, & Bates, 2001). Numerous investigations have found a clear relation between aggressive behavior and rejection (see Dodge, Coie, & Lynam, 2006). However, the results have been mixed, depending on the type of aggressive behavior (Card and Little, 2006, Price and Dodge, 1989, Salmivalli et al., 2000), and, in general, suggest that rejection is positively associated with reactive aggression and negatively with indirect aggression.
Summing up, the goals of this study were (1) to develop a questionnaire to assess a variety of CB behaviors. This goal in turn implied the assessment of the measurement model of the instrument. (2) To study the relation of CB with other indicators of aggressive behavior such as the justification of violence and the frequency of proactive, reactive, direct, and indirect aggressive behaviors. And (3) to study the association between CB and diverse contextual variables such as exposure to violence and acceptance and rejection by peers.
Section snippets
Participants
The sample was made up of 1431 adolescents, between 12 and 17 years, high school students from 31 classrooms of 10 educational centers of Bizkaia (Spain). The measurements were taken between March and May of 2008. Of the sample, 726 were girls, 682 boys, and 23 did not indicate gender. The mean age was 14.09 years (SD = 1.33). The degree of representativeness of the sample was 3.82% and the sampling error 2.6%. A cluster-sampling method was used, and high schools were selected randomly. Of the
Factor analysis of the Cyberbullying Questionnaire
The Kaise–Meyer–Olkin index was .96, indicating that the correlation matrix was suitable for factor analysis. The parameters for confirmatory factor analysis were estimated using the polychoric and the asymptotic covariance matrixes of the CBQ items. We tested a one-factor model via Weight Least Squared estimation with LISREL 8.8 (Jöreskog & Sörbom, 2006). Following the recommendations from a number of authors (e.g., Hu & Bentler, 1999), goodness of fit was assessed by the comparative fit index
Discussion
The first goal of the study consisted of developing a questionnaire that included a broad array of CB behaviors. The CBQ includes 16 of such behaviors and has shown excellent psychometric properties insofar as concerns the factor structure and internal consistency.
The most frequent CB modalities were writing embarrassing rumors or comments about classmates on the Internet, sending this link to another person, deliberately excluding someone from an online group, and hacking a classmate in order
Acknowledgment
This research was supported by a Grant from the Ministerio de Ciencia y Tecnología, Reference SEJ2006-61720 (Spanish Government).
References (69)
Bullying in schools and exposure to domestic violence
Child Abuse & Neglect
(2003)New bottle but old wine: A research of cyberbullying in schools
Computers in Human Behavior
(2007)- et al.
Evolutionary cyber-psychology: Applying an evolutionary framework to internet behavior
Computers in Human Behavior
(2009) - et al.
Cyberbullying among Turkish adolescents
CyberPsychology & Behavior
(2008) Social foundations of thought and action. A Social Cognitive Theory
(1986)- et al.
Bully and victim problems in elementary schools and students’ beliefs about aggression
Canadian Journal of School Psychology
(1995) - et al.
Cyber-harassment: A study of a new method for an old behavior
Journal of Educational Computing Research
(2005) Different names, same issue
Social Development
(2001)- et al.
Do girls manipulate and boys fight? Developmental trends in regard to direct and indirect aggression
Aggressive Behavior
(1992) - et al.
Factors associated with bullying behavior among early adolescents
Journal of Early Adolescence
(1999)
Cyberbullying and online harassment: Reconceptualizing the victimization of adolescent girls
Justification of violence and grandiosity schemas as predictors of antisocial behavior in adolescents
Journal of Abnormal Child Psychology
Gender differences in cognitive vulnerability to depression and behavior problems in adolescents
Journal of Abnormal Child Psychology
Proactive and reactive aggression in childhood and adolescence: A meta-analysis of differential relations with psychosocial adjustment
International Journal of Behavioral Development
Desarrollo del Inventario de Creencias Irracionales para Adolescentes (Development of the irrational beliefs inventory for adolescents)
Psicología Conductual
Continuities and changes in children’s social status: A five-year longitudinal study
Merrill–Palmer Quarterly
The relationship between indirect and physical aggression on television and in real life
Social Development
Relational aggression: The role of intent attributions, feelings of distress, and provocation type
Development and Psychopathology
Te role of overt aggression, relational aggression and prosocial behavior in the prediction of children’s future social adjustment
Child Development
Relational aggression, gender, and social-psychological adjustment
Child Development
Cyberbullying: Youngsters’ experiences and parental perception
CyberPsychology & Behavior
The structure and function of reactive and proactive aggression
Aggression and antisocial behavior in youth
Peer rejection and social information processing factors in the development of aggressive behavior problems in children
Child Development
Research on school bullying and victimization: What have we learned and where do we go from here?
School Psychology Review
Impact of exposure to violence in school on child and adolescent mental health and behavior
Journal of Community Psychology
A developmental investigation of social aggression among children
Developmental Psychology
Exposure to community violence and violence perpetration: The protective effects of family functioning
Journal of Clinical Child and Adolescent Psychology
Marital conflict and adolescent distress: The role of adolescent awareness
Child Development
Cyberbullying: An exploratory analysis of factors related to offending and victimization
Deviant Behavior
Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives
Structural Equation Modeling
An information processing model for the development of aggression
Aggressive Behavior
Children’s normative beliefs about aggression and aggressive behavior
Journal of Personality and Social Psychology
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