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Cyber Bullying Behaviors Among Middle and High School Students

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Faye Mishna at University of Toronto
Faye Mishna
Charlene Cook
Charlene Cook
Charlene Cook
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Tahany Gadalla at University of Toronto
Tahany Gadalla
Joanne Daciuk at University of Toronto
Joanne Daciuk
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Abstract

Little research has been conducted that comprehensively examines cyber bullying with a large and diverse sample. The present study examines the prevalence, impact, and differential experience of cyber bullying among a large and diverse sample of middle and high school students (N = 2,186) from a large urban center. The survey examined technology use, cyber bullying behaviors, and the psychosocial impact of bullying and being bullied. About half (49.5%) of students indicated they had been bullied online and 33.7% indicated they had bullied others online. Most bullying was perpetrated by and to friends and participants generally did not tell anyone about the bullying. Participants reported feeling angry, sad, and depressed after being bullied online. Participants bullied others online because it made them feel as though they were funny, popular, and powerful, although many indicated feeling guilty afterward. Greater attention is required to understand and reduce cyber bullying within children's social worlds and with the support of educators and parents.
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Cyber Bullying Behaviors Among Middle and High
School Students
Faye Mishna, Charlene Cook, Tahany Gadalla, Joanne Daciuk,
and Steven Solomon
University of Toronto
Little research has been conducted that comprehensively examines cyber bullying with a
large and diverse sample. The present study examines the prevalence, impact, and differ-
ential experience of cyber bullying among a large and diverse sample of middle and high
school students (N= 2,186) from a large urban center. The survey examined technology
use, cyber bullying behaviors, and the psychosocial impact of bullying and being bullied.
About half (49.5%) of students indicated they had been bullied online and 33.7% indi-
cated they had bullied others online. Most bullying was perpetrated by and to friends and
participants generally did not tell anyone about the bullying. Participants reported feeling
angry, sad, and depressed after being bullied online. Participants bullied others online
because it made them feel as though they were funny, popular, and powerful, although
many indicated feeling guilty afterward. Greater attention is required to understand and
reduce cyber bullying within children’s social worlds and with the support of educators
and parents.
The exponential growth of electronic and computer-based
communication and information sharing during the last
decade has radically changed individuals’ social interac-
tions, learning strategies, and choice of entertainment. Most
notably, technology has created new communication tools. The
tools are particularly influential among young people, who
extensively utilize websites, instant messaging, web cams,
e-mails, chat rooms, social networking sites, and text messaging
(Boyd, 2008; Bryant, Sanders-Jackson, & Smallwood, 2006; Pal-
frey & Gasser, 2008). Youth spend an average of 2–4 hr online
each day (Media Awareness Network, 2005), and it has been
suggested that the majority of youth view electronic communi-
cation tools as essential for their social interactions (Kowalski,
Limber, & Agatston, 2008).
The Internet provides innumerable possibilities for growth
among children and youth, including benefits such as social sup-
port, identity exploration, and development of interpersonal
and critical thinking skills, as well as educational benefits gener-
ated from expansive access to knowledge, academic support,
and worldwide cross-cultural interactions (Blais, Craig, Pepler,
& Connolly, 2008; Jackson et al., 2006; Tynes, 2007; Valken-
burg & Peter, 2007). The Internet is, however, concurrently a
potential site for abuse and victimization (Mitchell, Finkelhor,
& Wolak, 2003a, 2003b).
The Internet and other forms of communication technology
place children and youth at risk of being bullied online. Cyber
bullying comprises ‘‘willful and repeated harm’’ (Hinduja & Pat-
chin, 2009, p. 5) inflicted toward another and includes the use of
e-mail, cell phones, text messages, and Internet sites to threaten,
harass embarrass, or socially exclude (Hinduja & Patchin, 2009;
Patchin & Hinduja, 2006; Williams & Guerra, 2007). Cyber bul-
lying further encompasses the use of electronic media to sexually
harass (Hinduja & Patchin, 2007; Shariff & Johnny, 2007),
including distributing unsolicited text or photos of a sexual nat-
ure or requesting sexual acts either online or offline (Schrock &
Boyd, 2008). The nature of what constitutes repetition with
respect to cyber bullying is complex. Occurring in the public
domain (W. Craig, personal communication, February 25,
2009), cyber bullying by its very nature involves repetition,
because material such as e-mail, text, or pictures can be viewed
far and wide, and can be distributed not only by the perpetrator
but also by anyone with access (Campbell, 2005; Slonje &
Smith, 2008), and can be difficult or impossible for the victim-
ized child or youth to eliminate (Wolak, Mitchell, & Finkelhor,
2007).
Recent large scale cross-sectional studies demonstrate that
cyber bullying is a significant problem (Berson, Berson, &
Ferron, 2002; Mitchell et al., 2003a; Ybarra & Mitchell,
This study was funded by Bell Canada. The authors acknowledge the
support of the teachers and administrators at the Toronto District
School Board and the Centre for Enhancement of Jewish Education
(Mercaz Toronto). The authors would also like to thank the students
and their parents for participating.
Correspondence concerning this article should be addressed to Faye
Mishna, Factor-Intwentash Faculty of Social Work, University of
Toronto, Toronto, ON M5S 1V4, Canada. Electronic mail may be sent
to f.mishna@utoronto.ca.
American Journal of Orthopsychiatry 2010 American Orthopsychiatric Association
2010, Vol. 80, No. 3, 362–374 DOI: 10.1111/j.1939-0025.2010.01040.x
362
... eating disorders), somatic symptoms, or substance use (Beckman et al., 2012;Bonanno & Hymel, 2013;Bucchianeri et al., 2014;Hinduja & Patchin, 2007;Puhl & Luedicke, 2012;Schultze-Krumbholz & Scheithauer, 2009;Sourander et al., 2010;Willard, 2007). Relationship problems such as loss of trust, withdrawal, and aggression have also been linked to online shaming (Schultze-Krumbholz & Scheithauer, 2009;Willard, 2007;Wong et al., 2014;Ybarra & Mitchell, 2004) and negative cognitions and emotions including depression, anxiety, social isolation, negative self-perception and suicidal thoughts (Bucchianeri et al., 2014;Hamm et al., 2015;Hinduja & Patchin, 2007;Kowalski & Limber, 2013;Mishna et al., 2010;Patchin & Hinduja, 2011;Puhl & Luedicke, 2012;Tokunaga, 2010;Willard, 2007;Ybarra & Mitchell, 2007). However, most studies have sought to examine the prevalence and consequences of cyberbullying as an aggressive, intentional act or behavior targeted on a specific person with the aim of causing harm (Moreno, 2014). ...
... Considering that the most frequent responses involved negative thoughts (like doubt, frustration, guilt, or embarrassment) and passive (e.g., despair, hurt, and sadness) and uncontrollable (anxiety, fear, helplessness, powerlessness, worry, or embarrassment) negative emotions, our results support previous findings that online shaming experience poses a risk particularly for the development of depressive and anxiety disorders associated with reduced self-esteem and socialization tendencies. Given that a quarter of teenagers even reported self-harm thoughts (self-harm or suicidal tendencies), which is consistent with several previous studies of the aftermath of cyberbullying (Bucchianeri et al., 2014;Hamm et al., 2015;Hay et al., 2010;Hinduja & Patchin, 2007;Kowalski & Limber, 2013;Mishna et al., 2010;Patchin & Hinduja, 2011;Puhl & Luedicke, 2012;Tokunaga, 2010;Willard, 2007;Ybarra & Mitchell, 2007), these findings indicate that even theoretically, low-intensity online shaming can be a risky and potentially life-and health-threatening factor. Pathological behavioral responses to online shaming were present at a lower rate of up to 15%, with psychosomatic problems and increased substance use being the most common. ...
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... The role of anonymity and geographic variations were also incorporated as important features in Mondal, Silva and Benevenuto (2017) to enhance the detection and prevention of online hate speech. Additionally, Mishna, Cook, Gadalla, Daciuk and Solomon (2010) used features like the prevalence of bullying among youth, relationships between perpetrators and victims, emotional responses, and motivations for bullying. These features enhanced the prediction of cyberbullying and provided a nuanced understanding of the problem. ...
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Despite the growing body of research tackling offensive language in social media, this research is predominantly reactive, determining if content already posted in social media is abusive. There is a gap in predictive approaches, which we address in our study by enabling to predict the volume of abusive replies a tweet will receive after being posted. We formulate the problem from the perspective of a social media user asking: ``if I post a certain message on social media, is it possible to predict the volume of abusive replies it might receive?'' We look at four types of features, namely text, text metadata, tweet metadata, and account features, which also help us understand the extent to which the user or the content helps predict the number of abusive replies. This, in turn, helps us develop a model to support social media users in finding the best way to post content. One of our objectives is also to determine the extent to which the volume of abusive replies that a tweet will get are motivated by the content of the tweet or by the identity of the user posting it. Our study finds that one can build a model that performs competitively by developing a comprehensive set of features derived from the content of the message that is going to be posted. In addition, our study suggests that features derived from the user's identity do not impact model performance, hence suggesting that it is especially the content of a post that triggers abusive replies rather than who the user is.
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... However, this gender disparity is moderated by developmental stages: females show higher rates of cyberbullying during early adolescence, while males demonstrate increased cyberbullying behavior in later adolescence (Barlett & Coyne, 2014). Gender differences are also evident in the manifestation of cyberbullying behaviors: boys typically engage in more direct forms of aggression such as online threats and harassment, whereas girls tend to employ indirect methods including social exclusion and rumor spreading (Mishna et al., 2010). ...
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Previous research has established that the quality of peer relationships significantly impacts adolescents’ physical and mental health. However, the relationship between peer conflict and cyberbullying perpetration remains insufficiently explored. Based on the General Aggression Model and the General Strain Theory, this study investigates the mediating role of depression and hostile attribution bias in the relationship between peer conflict and cyberbullying perpetration, as well as the moderating role of gender, aiming to offer a new perspective on understanding adolescent cyberbullying perpetration. Employing a two-wave survey design, the study encompassed 900 adolescents ( Mage = 13.45, girls = 452), collecting data on peer conflict, depression, hostile attribution bias, and cyberbullying perpetration through self-reported questionnaires. The findings revealed that peer conflict at Time 1 (T1) significantly and positively predicted cyberbullying perpetration at Time 2 (T2). Depression and hostile attribution bias at T2 acted both individually and in a bidirectional chain as mediators between peer conflict at T1 and cyberbullying perpetration at T2. Gender differences were observed in the paths “peer conflict T1 → cyberbullying perpetration T2” and “depression T2 → cyberbullying perpetration T2.” Specifically, compared to girls, boys who experienced peer conflict and depression were more likely to engage in cyberbullying perpetration. These findings not only theoretically expand the application of the General Strain Theory and the General Aggression Model, but also provide practical guidance for the prevention and intervention of cyberbullying perpetration among adolescents.
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... Females engage more with cyberbullying as both perpetrators and victims owing to their higher involvement in indirect forms of aggression 133,134 and more frequent use of social networking sites 135,136 . Their tendency to share more personal information online increases their vulnerability 137,138 . Furthermore, females may interpret online comments as hurtful more quickly than males 139 , contributing to higher reported levels of victimization and may, therefore, be overrepresented in cyberbullying research 140,141 . ...
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