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Chapter 4. Cyberbullying in the United States
Dorothy L. Espelage, Ph.D.
University of Florida
Jun Sung Hong, Ph.D.
Wayne State University & Sungkyunkwan University
Alberto Valido, B.S.
University of Florida
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Introduction
Cyberbullying is recognized as a critical public health concern in the United States
(Centers for Disease Control and Prevention, 2009; Srabstein, Berkman, & Pyntikova, 2008;
Ybarra & Mitchell, 2004a) and is broadly conceptualized as a digital version of peer-based
aggression. Technological advances have significantly increased adolescents’ use of social media
and online communication platforms, such as Facebook and Twitter. According to Hinduja and
Patchin (2009), cyberbullying is defined as “willful and repeated harm inflicted through the use
of computers, cell phone, or other electronic devices” (p. 5). Definitions and forms of
cyberbullying vary, but some common examples include flaming, harassment, stalking,
impersonation, outing, trickery/phishing, as well as exclusion. Utilizing technology, the
perpetrator can send or post humiliating or threatening messages or photos of the victim, to a
third party, or to a public forum where many online participants visit (Hinduja & Patchin, 2009).
Similar to face-to-face bullying and peer victimization (Patchin & Hinduja, 2012; Kulig,
Hall, & Kalischuk, 2008), cyberbullying is found to be associated with a variety of poor
psychological and behavioral outcomes, including depressive symptoms, anxiety, risky
behaviors, self-injury, and suicidal thoughts and behaviors (Bauman, Toomey, & Walker, 2013;
Gamez-Guardix, Orue, Smith, & Calvete, 2013; Hinduja & Patchin, 2010; Hoff & Mitchell,
2009; Patchin & Hinduja, 2010; Price & Dalgleish, 2010; Schneider, O’Donnell, Stueve, &
Coulter, 2012; Ybarra, Espelage, & Mitchell, 2007). One meta-analytic study (Van Geel, Vedder,
& Tanilon, 2014) reported that both peer victimization and cybervictimization were associated
with suicidal ideation and attempts. Interestingly, cyberbullying was found to be more strongly
related to suicidal ideation relative to face-to-face peer victimization.
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Prevalence of Cyberbullying and Cybervictimization
According to the Pew Research Center, 92% of U.S. children and adolescents report
going online daily, and 71% use more than one type of social media (Lenhart, 2015), which
increase their exposure to cyberbullying. According to the U.S. Department of Justice,
approximately 7% of students in U.S. public schools nationwide reported being cyberbullied in
2013 (Zhang, Musu-Gillette, & Oudekerk, 2016). Although the rate of cyberbullying is lower
than the rate of face-to-face peer victimization (22%), the report also found that cyberbullied
students were less likely to notify an adult than face-to-face bullying victims (23% vs. 39%;
Zhang et al., 2016). Further, an online survey among 1,501 young regular internet users (age: 10-
17 years) revealed that 19% of adolescents were involved in online aggression in the past year
(Ybarra & Mitchell, 2004a). Twelve percent reported being perpetrators of online aggression, 4%
reported being victims/targets, and 3% reported being both perpetrator and targets. A systematic
review of cyberbullying prevalence among U.S. adolescents by Selkie, Fales & Moreno (2016)
also summarized that the rates of cyberbullying perpetration range between 1% to 41% based on
32 studies; the rates of cyberbullying victimization range between 3% and 72% based on 55
studies; and the rate of being both a perpetrator and a victim of cyberbullying range between
2.3% and 16.7% respectively based on ten studies.
Cyberbullying is also prevalent in many other countries, as estimated by a systematic
review and meta-analysis of 166 cyberbullying research studies from different countries. The
prevalence rates of cybervictimization around the world range approximately between 10% and
40% (Kowalski, Giumetti, Schroeder & Lattenner, 2014). In the U.K., the National Children’s
Home (NCH, 2005) surveyed 770 participants (age = 11-19 years) and found that 20% of the
study participants had been cyberbullied or threatened online, and 11% of the study participants
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had perpetrated cyberbullying. In a study among 11,227 students (age:11-15 years) in U.K.,
about 7% students reported that they had “received any nasty or threatening text messages or
emails” at least “once in a while” (Noret & Rivers, 2006). In Sweden, Slonje and Smith (2008)
surveyed 360 adolescents (age: 12-20 years), and found that 5.3% reported being cyberbullied
inside school in the last couple of months. In Canada, utilizing one-year longitudinal data (two
time points) among 1,972 adolescents from the Health Behavior in School-Aged Children Study,
Cappadocia, Craig, and Pepler (2013) found that 11.6 % of the study participants had been
involved in cyberbullying perpetration; 13.5% had been involved in cybervictimization; and
4.6% had involved in cyberbullying perpetration and victimization. Thus, it appears that US rates
of cyberbullying perpetration and victimization are more similar to U.K. statistics than Canada
statistics.
Issues in Reporting the Prevalence Rate of Cyberbullying
The reported prevalence rates are different not only across countries, but also within
countries. The variability in reported prevalence may result from several measurement issues in
studies on cyberbullying. First, the definition of cyberbullying is not consistent across studies.
When being asked whether they have ever been bullied, harassed, threatened or embarrassed by
someone using the internet, cell phone and other technologies, the same participants responded
differently from when they were asked about others “repeatedly [trying] to hurt you or make you
feel bad by e-mailing/e-messaging you or posting a blog about you on the internet.” The former
question generated a prevalence rate of 31% (Pergolizzi et al., 2011), while the latter generated a
prevalence rate of 9% (Bevans, Bradshaw, & Waasdorp, 2013). Second, there are discrepancies
in the time frame being assessed. For example, in a survey of middle school students, 9% of
students reported having ever been cyberbullied in their lifetime, whereas 9% reported being
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cyberbullied in the last 30 days. Finally, in terms of response options, some studies provided
binary responses while others used Likert-type scales. The cutoff points in studies with Likert
scales to decide whether participants had experienced cyberbullying were oftentimes not
validated (Selkie et al., 2016). Despite the issues related to differential methods to assess
cyberbullying, the extant literature suggests that cyberbullying involvement is prevalent and
should be considered a public health concern.
Theories Explaining Cyberbullying and Cybervictimization
Compared to face-to-face bullying, theories providing empirical support for
cyberbullying and cybervictimization are sparse (Espelage, Rao, & Craven, 2012). As stated by
Tokunaga (2010), research on cyberbullying has largely been conducted in the absence of
theoretical frameworks, although theory can foster cohesiveness to a body of literature by
establishing an order to the variables that have already been tested (see also Dublin, 1978).
Tokunaga (2010) also argued that theories not only help to predict behaviors of bullies and
victims, but can possibly shed light as to why the effects of cyberbullying would be amplified
compared to those of face-to-face bullying. Nevertheless, several theories can provide insights
into our understanding of cyberbullying—social cognitive theory, routine activity theory, and
general strain theory are next reviewed.
According to Bandura (2001), social cognitive theory argues that attitudes and behaviors
are acquired directly through observing others in social interactions or other outside influences,
such as the media. For learning to occur, individuals need to (a) attend to the observed behavior,
(b) encode images of the observed behavior, (c) reproduce those images, and (d) be motivated to
perform the behavior (Bandura, 1978). Although the social cognitive theory is similar to
Bandura’s (1986) social learning theory, social cognitive theory places importance on cognitions
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in determining individual behavior (Bandura, 1978). In addition, moral values, moral emotions,
and moral justifications are important components of social cognitive theory (Perren &
Gutzwiller-Helfenfinger, 2012). Social cognitive theory has long been applied to examine
aggressive behavior (Bandura, 1978), and a limited number of studies have also applied this
theory to understand cyberbullying (Bauman, 2009; Perren & Gutzwiller-Helfenfinger, 2012).
Many study findings demonstrate an association between observing and experiencing bullying
and cyberbullying (e.g., Jang, Song, & Kim, 2014; Sticca, Ruggieri, Alsaker, & Perren, 2013).
Because the social cognitive perspectives involve learning, thinking and reasoning, it is
recognized as one of the most effective strategies in addressing bullying and cyberbullying
(Boxer & Dubow, 2002; Thorton, Craft, Dahlberg, Lynch, & Baer, 2000).
Routine activity theory can also provide a perspective on why certain adolescents engage
in cyberbullying. This theory does not attribute violence or crime to social causes, rather argues
that the prosperity of societies offers more opportunities for crime or violence. Routine activity
theory is an ecological approach to exploring the antecedents of cyberbullying, as it considers the
location, accessibility, and presence or absence of environmental characteristics and certain types
of individuals who are at risk for cyberbullying and cybervictimization. Proposed by Cohen and
Felson (1979), routine activities refer to generalized patterns of social activities, which can
provide opportunities for situations to emerge where perpetrators target victims (Wikstrom,
2009). For crime or cyberbullying to occur, spending time away from family or being
unsupervised can increase opportunities for cyberbullying and cybervictimization (Groff, 2007).
Cyberbullying occurs as an end result of the convergence of a motivated offender (cyberbully), a
suitable target (cybervictim), and a lack of guardianship or parental monitoring (control; e.g.,
parents or teachers; Wikstrom, 2009). Cyberbullies need to be a motivated individual in order to
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perpetuate bullying online. The cybervictim is a suitable target that draws the motivated offender
because the victim might be vulnerable for reasons such as having a limited social support
network or low parental monitoring of their technology use (Felson & Boba, 2010). Although
this theory is highly criticized, it has been found to predict cyberbullying among adolescents and
young adults (Marcum, Higgins, & Ricketts, 2010; Navarro & Jasinski, 2011, 2013).
Robert Agnew’s general strain theory has received significant empirical attention over
the years. Although the strain theory dates back to early 20th century through the work of Edwin
Sutherland and Robert Merton, it was later modified by Robert Agnew who developed the
general strain theory. The general strain theory holds that individuals who experience strain and
negative emotions are at a heightened risk for engaging in deviant behavior, such as
cyberbullying (Hinduja & Patchin, 2010). According to the general strain theory, strain originates
from (a) failure to achieve valued goals, (b) removal of stimuli with positive values, and (c)
introduction of negative stimuli which results in negative emotional responses (Agnew, 2001).
Strain and stressors do not directly cause deviant behavior; rather, they can increase the risk of
negative emotions, such as anger and frustration, which can lead to the development of negative
or aggressive emotions (Agnew, 2001). As a result, youth experiencing strain may release their
frustration out on others through verbal abuse or insulting others (Agnew, 2001)—both online
and offline. As expected, the general strain theory has received wide empirical support for
explaining why certain youth are predisposed to cyberbullying and cybervictimization (Hay,
Meldrum, & Mann, 2010; Paez, 2016; Patchin & Hinduja, 2010). For instance, Paez’s (2016)
study, which utilized a nationally representative sample of children, explored whether individual
and social factors associated with general strain theory was associated with cyberbullying.
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Supporting the general strain theory, their results showed that students who experienced strain
were more likely to engage in cyberbullying.
Factors Associated with Cyberbullying Perpetration and Victimization
Risk Factors
The social-ecological model of human development serves as a conceptual framework to
understand how bullying and cyberbullying can emerge. It focuses on understanding how
individual characteristics of children interact with environmental contexts or systems to promote
or prevent bullying victimization and perpetration (Bronfenbrenner, 1977; Espelage, 2012; Hong
& Espelage, 2012). These structures include peer groups, families, and schools among other
settings.
Individual factors. Researchers are divided about whether boys or girls engage in higher
level of cyberbullying (Kowalski et al., 2014). In some studies, boys were more often
perpetrators of cyberbullying whereas girls were more frequently victimized (Kowalski et al.,
2014; Sourander et al., 2010). Other studies have found no significant effect of gender on
cyberbullying perpetration or victimization (Li, 2006; Ybarra & Mitchell, 2004b). Studies also
offer conflicting reports of age as a risk factor for cyberbullying perpetration or victimization
(Slonje & Smith, 2008). For example, Ybarra and Mitchell (2004b) reported a higher incidence
of cyberbullying in students fifteen years old or older, while Kowalski and colleagues (2012)
reported higher prevalence among younger adolescents. Moreover, Smith, Mahdavi, Carvalho, &
Tippett, (2006) found no change of cyberbullying rates from early to late adolescence.
Other individual level risk factors include low affective empathy, or an inability to feel
other’s emotions; low cognitive empathy, or an inability to understand other’s emotions; and
narcissistic personality traits (Kowalski et al., 2014). Moreover, depression, anxiety, and low
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self-esteem were also found to be associated with cyberbullying victimization in one study
(Kowalski et al., 2014). Interestingly, permissive attitudes toward cyberbullying, a desire to
control others, and a sense of superiority have been positively related to cyberbullying
perpetration (Kowalski et al., 2014; Gradinger, Strohmeier, & Spiel, 2011).
School. Lower levels of school belonging, lower academic achievement, and higher
unexcused absences were found to be linked to cyberbullying victimization in several studies
(Hinduja & Patchin, 2008; Ybarra & Mitchell, 2004a). Furthermore, a negative perception of
school climate was associated with higher engagement in cyberbullying (Williams & Guerra,
2007).
Peer. Peer victimization in the forms of verbal, physical, or relational aggression
exacerbate cyberbullying perpetration and victimization (Kowalski et al., 2014; Ybarra &
Mitchell, 2004a). For example, Twyman, Taylor, and Comeaux (2010) found that children who
were involved in cyberbullying were more likely to have suffered from previous peer
victimization. Additionally, lower peer support, substance use, and bullying perpetration were
found to be related to higher cyberbullying victimization and perpetration (Espelage et al., 2012;
Ybarra & Mitchell, 2004a).
Family. Low parental support has been associated with cyberbullying perpetration and
victimization in one study using a nationally representative sample of adolescents (Wang,
Iannotti, & Nansel, 2009). Among the family level predictors, those with higher cyberbullying
perpetration and victimization also had higher socioeconomic status, and greater access to
technology and higher internet usage (Walrave & Heirman, 2011; Ybarra & Mitchell, 2004b).
Additionally, cyberbullying victims also report lower levels of connection with their parents and
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lower parental monitoring of internet activities (Kowalski et al., 2014; Ybarra & Mitchell,
2004a).
Protective Factors
Relative to risk factors, protective factors have been less well-studied in the field of
adolescent behavior. More recently, however, scholars have begun to realize the importance of
considering factors that operate in individual, peer, family, and school domains that may insulate
youth from problem behavior or mitigate the effects of risks (Dekovic, 1999). In their review and
meta-analysis of cyberbullying studies, Kowalski, Giumetti, Schroeder, and Lattanner (2014)
identified several protective factors. Protective factors associated with cyberbullying perpetration
included empathy, parental monitoring, peer support, school climate, and school safety
(Kowalski et al., 2014). For victims of cyberbullying, protective factors included social
intelligence, school safety, parental monitoring, perceived support, empathy, school climate, and
parental control of technology (Kowalski et al., 2014).
Certain psychological variables reportedly insulate adolescents from being involved in
cyberbullying. One notable protective factor is empathy, which has been considered in research
on bullying. Empathy is defined as an “emotional response that stems from another’s emotional
state or condition” (Eisenberg & Strayer, 1987, p. 5). There is strong evidence that low levels of
empathy are associated with greater cyberbullying perpetration (Renati, Berrone, & Zanetti,
2012; Steffgen, Konig, Pfetsch, & Melzer, 2011). Also considering the developmental literature
that females are more likely to display empathy than males (Rueckert & Naybar, 2008), studies
have examined whether empathy can explain gender differences in both offline and online
bullying (Topcu & Erdur-Baker, 2012). Topcu and Erdur-Baker (2012) found, for example, that
boys tend to bully others more frequently as they are seen as less empathic than females. The
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study also found that both affective and cognitive empathy indirectly mediated the association
between sex differences and cyberbullying. Interestingly, Ang and Goh’s (2010) study, using a
sample of 396 Singaporean adolescents found that youth with low level of cognitive empathy
scored higher on cyberbullying than those with high levels of cognitive empathy, irrespective of
gender.
Variables representing family level protective factors may include parental monitoring
and support, which have been implicated in research on cyberbullying. Although cyberbullying
occurs primarily in the home, parents are often excluded from many of their children’s online
activities, and youth rarely tell their parents about their involvement in cyberbullying (Mishna,
Saini, & Solomon, 2009; Subrahmanyam & Greenfield, 2008). As a result, parents are often
unaware of their children’s involvement in cyberbullying (Dehue, Bolman, & Vollink, 2008).
However, parents are recognized as having a very strong influence on the behavior of their
children, and a strong bond between parent and child can insulate youth from engaging in
deviant activities (Hinduja & Patchin, 2013). Given this, it is not surprising that parental
monitoring and support have been a major focus of cyberbullying intervention and prevention
efforts (Beale & Hall, 2007). Numerous studies consistently demonstrate that children who are
involved in cyberbullying as perpetrators and victims receive limited parental monitoring and
supports than those who do not (Low & Espelage, 2013; Fanti, Demetriou, & Hawa, 2012;
Mesch, 2009; Wade & Beran, 2011; Wang, Iannotti, & Nansel, 2009; Ybarra & Mitchell, 2004b).
From a nationally representative sample of U.S. students in grades 6-10, Wang and colleagues
(2009) reported that higher parental support was related to less involvement in online and offline
bullying and peer victimization. Using a large U.S. sample of youth internet users, Ybarra and
Mitchell’s (2004b) study also revealed that youth engaging in internet-based bullying reported
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experiencing poor parent-child relations in the home. A more recent study conducted by Low and
Espelage (2013) found that lower levels of parental monitoring predicted higher levels of
cyberbullying among a sample of racially diverse early adolescents in fifth through seventh
grades in four US Midwestern middle schools.
School districts have been challenged to develop ways to prevent and to intervene in
bullying and cyberbullying situations. Educators and schools have an important role in
promoting positive youth development and preventing students from engaging in deviant
behaviors (Torney-Purta, 2002). This is particularly true when considering the amount of time
students spend in their school (Hinduja & Patchin, 2013). Students’ positive perceptions of the
school climate, teacher support, and teacher involvement are some examples of school level
protective factors that have been found to be related to not only less face-to-face bullying, but
also cyberbullying in one study (Sourander et al., 2010). Casas, Del Rey, and Ortega-Ruiz (2013)
found that students who perceive their teachers as supportive are less likely to report
cyberbullying. Smokowski, Evans, and Cotter (2014) also reported from a rural adolescent
sample that teacher support was inversely related to both face-to-face bullying and cyberbullying
victimization. Likewise, according to Hinduja and Patchin’s (2013) findings, students (6th-12th
grade) who perceived that adults in their life (e.g., teachers) are involved and impose
consequences on them for cyberbullying were less likely to participate in such behavior.
Teachers are potential source of social support and play a critical role in helping students make
sense out of confusing and dangerous situations. Teachers can also serve as a role model and
refuge for students who are confronted with situations that they perceive as beyond their
understanding and control (Bowen, Richman, Brewster, & Bowen, 1998).
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Are the Factors associated with Face-to-Face Bullying and Cyberbullying Similar?
As noted previously, compared to traditional bullying, the incidence of cyberbullying is
generally less frequent (e.g., Espelage et al., 2012; Smith, Mahdavi, Carvalho, Fisher, Russell, &
Tippett, 2008; Slonje & Smith, 2008). Extant research has demonstrated a close relation between
traditional bullying and cyberbullying. Experiencing traditional victimization increases the risk
for being a victim of cyberbullying (e.g., Juvonen & Gross, 2008; Nansel et al., 2001;
Raskauskas & Stoltz, 2007). But there is evidence that a small portion of adolescents who are
perpetrators or victims of cyberbullying do not experience tradition forms of bullying (Olweus,
2012; Raskauskas, 2010).
Studies that have contrasted different forms of bullying perpetration (with individual and
family correlates) suggest areas of both overlap and uniqueness. For example, David-Ferdon and
Hertz (2009) posit that “like perpetrators of other forms of aggression, perpetrators of electronic
aggression were more likely to believe that bullying peers and encouraging others to bully peers
are acceptable behaviors” (p. 8). Findings from this study also suggested that cyberbullies were
more likely to engage in other forms of aggression, implying shared underlying risk factors.
Wang and colleagues (2009) found that cyberbullying (as well as physical, verbal and relational
bullying) was similarly related to low parental support; however, unlike other forms of bullying,
cyberbullying was not related to having more friends. These authors assert that further research is
needed to clarify shared and non-shared features across various forms of bullying in order to
begin placing cyberbullying in a larger theoretical framework.
However, findings from a recent longitudinal study of U.S. middle school students
revealed that cyberbullying is more distinct than other forms of aggression, as one study found a
greater overlap between non-physical bullying and fighting perpetration than associations with
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cyberbullying perpetration (Low & Espelage, 2013). This study also found that predictors of
cyberbullying varied as a function of gender and race. More specifically, cyberbullying was less
stable than other forms of aggression, and continuity appeared to be limited to White youth and
females. Differences in stability are noteworthy and warrant further investigation. The study data
also implied that cyberbullying is a relatively low-frequency behavior and arguably more
sporadic than other forms of bullying, though less so for females.
Prevention and Intervention Approaches & Programs
Legal & Policy Considerations in the U.S.
Given the bullying is a public health concern, schools need to take actions to reduce both
cyberbullying and bullying inside and outside of school building. Schools that choose to seek
legal action against students suspected of cyberbullying may face difficult legal battles. Vague
court decisions, and the changing environment of cyberbullying laws in different states often
thwart school’s obligations towards student’s safety (Hinduja & Patchin, 2011).
One of the first cases questioning the ability of schools to govern student’s actions came
with Tinker v. Des Moines Independent Community School District in 1969. Des Moines School
district pressed charges against a student protesting against the Vietnam War on school grounds
(Tinker et al. v. Des Moines Independent Community School District et al., 1969). The court
decided that the student’s freedom of expression had to be respected and not subjected to
disciplinary actions unless the school could prove significant disruption to educational activities
(Hinduja & Patchin, 2011). In other words, if school officials could not prove that the incident
was sufficiently disruptive, they were unable to limit student’s communication. Later court cases
also decided that students were free to act if it happened away from school.
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Although well intentioned, the Tinker standard limited the ability of schools to deter
students from cyberbullying. Cyberbullying can deprive the victim of an environment conducive
to learning. But if the cyberbullying occurred outside of the school, most likely, school officials
are unable to follow any type of legal action against students. Later court cases created further
precedents limiting schools’ authority to follow legal actions against students (Hinduja, &
Patchin, 2011). For example, in Klein vs Smith (1986) the court decided in favor of a student
who showed the middle finger to a teacher outside of school, despite claims from the school that
the action was specifically directed at a school official. These rulings complicate intervention
and prevention efforts because schools have traditionally been focused on behavior within
school. Cyberbullying by definition can happen anywhere outside the jurisdiction of the school.
More recently many states have enacted laws that address cyberbullying specifically.
Notar and colleagues recommend schools to consult with trained lawyers to handle these cases
given student’s First Amendment rights in the U.S. (Notar et al., 2013). Administrators are
advised to proceed with caution when disciplining students for behavior that may have occurred
outside of class (Wong-Lo, 2009). Tragic incidents have occurred where children who are
cyberbullied have committed suicide and schools have been in legal battles with the families.
(Notar et al., 2013). Given this complexity, it is ideal to develop and implement clear pre-
emptive policies and programs that aim to reduce cyberbullying (Willard, 2011).
The dynamic nature of digital media and inexperience of school officials offer another
complication in addressing cyberbullying. That is, it is unreasonable to monitor several, often
changing, social media platforms in an attempt to manage cyberbullying behavior (Lane, 2011).
This is especially true given the autonomy or privacy offered by numerous platforms. Schools
cannot fully control behavior that happens via digital devices, but school-based programs that
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educate and advise children could be beneficial. The report offers guidelines and implications for
school personnel who work on developing programs (Twyman, Saylor, Taylor, & Comeaux,
2010).
Schools have been advised to incorporate some of the abovementioned factors into their
programs designed to eliminate cyberbullying. Schools should define cyberbullying, have strong
policies, and solid training as well implementation. Kowalski and colleagues (2012) offered nine
intervention tips: save the evidence, ignore minor offenses, report the offense to the digital
platform, investigate further, communicate perpetration with school officials, get parents
involved, seek legal advice, report to law enforcement, and get the students mental health care.
Online Resources/Guidance for Youth, Parents, Teachers, & Administrators
Although most agree that something should be done to change the culture of
cyberbullying in schools, the research lacks empirical consensus regarding preventive strategies
or intervention programs (Bauman, 2013). Nevertheless, an approach that many programs do
agree upon is the involvement multiple stakeholders, curriculum programs in the U.S often
involve students, parents, and school staff (Couvillon & Ilieva, 2011; Notar et al., 2013)
Programs focus on definitions of cyberbullying and strategies to prevent children from becoming
victims (Cassidy, Faucher, & Jackson, 2013; Pearce, Cross, Monks, Waters, & Falconer, 2011)
Schools often employ websites, tip sheets, and other online resources to disseminate
cyberbullying information and increase awareness (e.g.,
http://www.stopbullying.gov/cyberbullying/index.html,) (Keith & Martin, 2005) In a meta-
analysis of 17 cyberbullying prevention websites, Ahlfors found that 14 of the 17 websites were
directed to parents, seven were constructed for elementary aged children (6-10 years old), eight
of the programs addressed tweens (11-12 years old), and 11 included information specifically
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created for adolescents (ages 13 to 18) (Ahlfors, 2010). Websites created for healthcare
providers who often have to treat victims of cyberbullying were absent from the list of resources.
Some of the websites reported were based in a commercial intervention or curriculum and only
ten offered citations to the research (Ahlfors, 2010).
Many of these websites are directed to parents. Many researchers point to parents as an
essential component of any productive cyberbullying campaign (Aboujaoude, Savage, Starcevic,
2015). It has been observed that parent involvement leads to considerable reductions in bullying
victimization (Farrington & Ttofi, 2009). Although students may not go to their parents for help
when they are cyberbullied, parents should be prepared to answer decisively to any
cyberbullying incident (Juvonen & Gross, 2008). Additionally, youth should have access to
online resources that offer them a way to protect themselves online without supervision from
their parents. It is noteworthy to mention that although many online resources are based on
recommendations from the scientific literature, many commercial products that offer school
prevention strategies may not be based on empirical findings.
Scholars have suggested several guidelines for youth who are been cyberbullied, and to
support parents and school staff who deal with cyberbullying (Beale & Hall, 2007; Couvillon &
Ilieva, 2011; Feinberg & Robey, 2009). Some recommend that the victim do not read the
messages sent by the cyberbullies (Keith & Martin, 2005), parents are encouraged to find
information (Beale & Hall, 2007), and schools are advised to demand adherence to Student
Internet Policies, perform professional development trainings, and subscribe to school-wide
interventions that address cyberbullying specifically (Peace et al., 2011; Couvillon & Ilieva,
2011).
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Moreover, Ortega-Ruiz, Del Rey, and Casas (2012) recommends the following tactics to
develop a successful prevention program: ”(1) Proactive policies, procedures, and practices; (2)
Raising school staff’s and youth’s individual awareness and online social competence; (3)
Promoting protective school environment; and (4) School-family-community partnerships to
promote cooperation between school staff, families, and local organizations.”
Students’ and Educators’ Awareness, Attitudes, and Perceptions of Cyberbullying
School preventive efforts have expanded to include assemblies, software programs, and
student lead campaigns to increase awareness of the negative consequences of cyberbullying.
The research is still in its infancy, since no more than a handful of studies have assessed the
effectiveness of these programs. One of the studies exploring the effectiveness of assembly style
presentations was carried by Roberto and colleagues (2014) with the “The Arizona Attorney
General’s Social Networking Safety Promotion and Cyberbullying Prevention” presentation.
The 45 minutes long session tried to shift student’s online safety attitudes (Roberto, Eden,
Savage, Ramos-Salazar; Deiss, 2014). Some of the topics covered during this training ranged
from cyberbullying prevention to Internet Safety (Roberto et al., 2014). An analysis of the
effectiveness of the presentation revealed that students who received the training were more
engaged in Internet safety activities than those in the control group (Roberto et al., 2014). The
results also showed that they were more likely to keep their account information private, and stay
away from people they didn’t know online. However, the study had limited validity due to the
short follow up after the presentation. Therefore, further longitudinal research is needed to
evaluate the effectiveness of these programs.
School-based Programs
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There have been a variety of programs implemented in the U.S. The Seattle Public
School District developed their own program that focused on debunking misperceptions about
digital behavior, building empathy, teaching online safety, and empowering victims (Holladay,
2011). This program also emphasized parental and teacher engagement. Other curriculum-based
program aimed at addressing cyberbullying have been designed: iSafe Internet Safety Program,
Cyber Bullying: A Prevention Curriculum (Kowalski et al., 2012), Sticks and Stones:
Cyberbullying (Wilson, 2007), Lets Fight It Together: What We All Can Do to Prevent
Cyberbullying (Juvonen & Gross, 2008), and The Second Step Violence Prevention Program
(Craig, Pepler, & Atlas, 2000). Often these programs involve videos, websites, resources, and
scripted lessons. There are also numerous online programs such as www.stopcyberbullying
which offer similar resources and curriculum. Although this list is not comprehensive, it
illustrates the scope of programs available in the U.S. (see Notar, Padgett, & Roden, 2013).
Table 1 also shows some of the leading prevention approaches and programs in the U.S.,
their intended goals, and audience. Among the most prominent we find the Olweus Bullying
Prevention Program (OBPP), the Second Step Bullying Prevention Program, and the I-SAFE
Curriculum.
The Olweus Bullying Prevention Program (OBPP) was one of first anti-bullying
programs in the world. In the U.S., the intervention has been adopted across elementary, middle,
and high school settings in virtually every state (Olweus & Limber, 2010). The hallmark of the
Olweus Bullying Prevention Program is the restructuring of the school environment to “shift
bullying norms” with the help of parents, school staff, and teachers. Although the intervention
has yielded significant reductions in bullying and peer victimization in many countries, studies in
the US have found mixed results (Olweus & Limber, 2010). For example, the first randomized
20
clinical trial conducted in South Carolina schools had such poor implementation that the data
were never published (Olweus & Limber, 2010). Also, Bauer, Lozano, and Rivara, (2007)
conducted a controlled trial of the OBPP and found that there were mixed effects varying by
gender, ethnicity, and grade but no school-wide effect. These studies indicate that transporting
programs from other countries into the U.S. must consider implementation issues more
diligently.
The Second Step: Student Success through Prevention Program (Committee for Children,
2008) uses a Social Emotional Learning Framework to decrease bullying, and cyberbullying
perpetration. In a clinical trial testing the efficacy of the Second Step Program, Espelage and
colleagues found reductions of self-reported delinquency, bullying, and cyberbullying over a 3-
year period for schools following the program. Although The Second Step Program was not
designed specifically to address cyberbullying, reductions in cyberbullying were found through
the reduction of delinquency (Espelage, Van Ryzin, Low, & Polanin, 2015). These findings lend
some support to the general strain theory discussed earlier. The prevention curriculum capitalizes
on current knowledge of risks and protective factors by targeting disruptive classroom behaviors,
violence, and impulsivity (Espelage et al., 2015). The lessons are divided according to the grade
level and include topics that teach students to control their own emotions, cope with stress,
develop problem solving skills, and substance use prevention (Espelage et al., 2015).
Another noteworthy prevention program is the I-SAFE curriculum. Mishna and
colleagues (Mishna, Cook, Saini, Wu, & McFadden, 2009) studied the impact of U.S.-developed
I-SAFE curriculum (Chibnall, Wallace, Leicht, & Lunghofer, 2006). The program’s main module
includes five lessons (60 minutes) on Internet safety, cyberbullying, social networking, and cyber
etiquette. The lessons of the I-SAFE program are taught by teachers during school hours. The
21
target population were students from 5 to 8 years old. Mishna and colleagues report
improvements of student’s knowledge on internet safety following the intervention (Mishna et
al., 2009).
The Help-Assert-Yourself-Humor-Avoid-Self-Talk-Own tactic address the needs of middle
school students (ages 10-12) by developing social skills to navigate cyberbullying episodes
(Mishna, Cook, Saini, Wu, & McFadden, 2009). The program improved the knowledge of e-
safety issues, but did not have an effect on online behaviors (Salvatore, 2006; Mishna et al.,
2009). Moreover, Salvatore (2006) found that the program resulted in small improvements in the
levels of cyberbullying victimization (g = .32).
Summary & Future Directions
Prevention programs are only now being developed and evaluated to address
cyberbullying and cybersafety issues among youth and their families. Websites, tip sheets, and
other online resources might be where parents and teachers are receiving information about how
to best protect their children. However, it appears that these online resources are often promoted
by organizations who are selling products and are rarely evidence-based. Thus, parents, teachers,
and school administrators should be cautious when reviewing information at these sites, and
should focus on online resources that are provided by the federal agencies and advocacy groups
that use research to guide their recommendations.
Researchers have also turned to educator’s awareness and perceptions of cyberbullying to
understand how intervention program can be improved upon (Cassidy, Brown, & Jackson, 2012;
Beale & Hall, 2007). Cassidy and Colleagues studied the experiences, knowledge of social
media, and attention that teachers give to cyberbullying issues. The authors found that most
teachers were unfamiliar with the avenues where children can be cyberbullied, and that schools
22
lacked specific programs to address the problem of cyberbullying in their schools (Cassidy et al.,
2012). These findings highlight the need for new programs supporting research based
interventions catered to educators and focused in identifying warning signs of cyber bullying
victimization and perpetration.
Few school-based programs in the U.S. have been developed and evaluated to reduce
cyberbullying specifically, however, it appears that many efficacious bully prevention and
intervention programs or approaches could be extended to include outcomes focused on
cyberbullying (Paul, Smith, & Blumberg, 2012; Slonje, Smith, & Frisén, 2013). Scholars who
are evaluating bully prevention programs should at the very least add cyberbullying outcome
measures and where possible, bully prevention programs should add lessons on cybersafety and
cyberbullying. However, schools need to be supported to implement these programs through
stronger legislation that addresses cyberbullying. Finally, much more guidance is needed for
school practitioners to talk to parents about limiting screen time, monitoring their children’s use
of the technology, talking to their children about internet safety and privacy, and encouraging
open communications when they do experience cyberbullying.
Further, more longitudinal research needs to be conducted to understand the
developmental trajectories associated with traditional bullying and cyberbullying, and the risk
and factors associated with simultaneous change of these behaviors. Measurement issues plague
the bullying scholarship which has largely been focused on traditional, face-to-face bullying, and
it appears that when bullying involves social media and technology, these measurement issues
become even more complex. Thus, it will be critical for scholars to conduct systematic and
multi-method and multi-informant studies on cyberbullying.
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36
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37
Table 1. Cyberbullying prevention programs and Interventions in the United States.
38
Program/Intervention Type Target
Population
Length State Program
Targets
Research
Evidence
Olweus Bullying Prevention Program (OBPP) 2
The OBPP is a school wide intervention
bringing together staff, parents and the
community. The training integrates multiple
levels of prevention.
Curriculum
Professional
development
K-12 Students,
Teachers,
Community
members
Long term US-wide Prosocial
behaviors, school
climate, social
support
Research
based,
efficacious3
Nationally
Recognized
The Second Step Bullying Prevention Program
The program is based on Social Emotional
Learning skills and attitudes that help prevent
cyberbullying. Encourages helpful bystander
behavior1
Curriculum
Professional
development
5-12 years
Student, parents,
teachers
13 – 15
lessons
US-Wide Empathy,
emotion
management,
social problem
solving skills
Research
based,
Efficacious.4
I-SAFE
Prevention oriented lessons based on peer
networks and student leadership. Educate
students in cyberbullying, social networking,
cyber etiquette, and e-safety.
Curriculum,
Digital resources,
Professional
development
5-8 years
Students,
School, Staff,
Parents
5 lessons US-wide Cyber Privacy,
prevention, e-
safety
Not research
based
Seattle curriculum
School sponsored cyberbullying prevention
program. Four main areas: Breaking myths
about digital behavior, create empathy and
understanding, learning online safety skills, and
strategies to reject abusive behavior online.1
Curriculum,
professional
development
5-8 years
Students,
Teachers,
Parents
9 lessons Washington
State
Awareness,
Parent
involvement,
Research
based
Help-Assert Yourself-Humor-Avoid-Self-Talk-
Own it
Offer students strategies to deal with
cyberbullying on their own. The words on the
title are steps to follow when bullied.
Curriculum 10-12 years. 5 lessons US-wide Social emotional
learning.
Moderate
reductions in
Cyberbullying,
Cyberbullying prevention engine
Aim to protect children from cyberbullying and
risky online behavior by filtering content
delivered to mobile devices. Monitor
communications by keywords.
Monitoring
software
Parents, school
staff,
Adults.
Not
Applicable
US-Wide Cyber security,
privacy.
Not research
based.
Stop Bullying.gov
A federal government website with information
about cyberbullying prevention. Offer advice
of what to do if someone is been cyberbullied.
Website Students,
Parents,
School Staff,
Not
Applicable
US-Wide Awareness,
Prevention,
Online
Resources
Not Research
based.
39
1 http://www.cfchildren.org/about-us/enewsletter/the-second-step-program-and-the-bullying-prevention-unit-a-powerful-combination
2 Olweus D. Bullying at School: What We Know and What We Can Do. Cambridge, MA: Blackwell Publishers; 1993.
3 Bowllan, N. M. (2011). Implementation and evaluation of a comprehensive, school‐wide bullying prevention program in an urban/suburban
middle school. Journal of School Health, 81(4), 167-173.
4 Notar, C. E., Padgett, S., & Roden, J. (2013). Cyberbullying: Resources for Intervention and Prevention. Universal Journal of Educational
Research, 1(3), 133-145.
5 http://www.athinline.org/about
6 Snakenborg, J., Van Acker, R., & Gable, R. A. (2011). Cyberbullying: Prevention and intervention to protect our children and youth. Preventing
School Failure: Alternative Education for Children and Youth, 55(2), 88-95.
Table 1 (continued). Cyberbullying prevention programs and Interventions in the United States.
