ChapterPDF Available


Cyberbullying is recognized as a critical public health concern in the United States (Centers for Disease Control and Prevention 2009a, b; Srabstein et al. 2008; Ybarra and Mitchell 2004) 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 visited by many online participants (Hinduja and Patchin 2009).
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
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.
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
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
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
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
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
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.
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
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
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,
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
lower parental monitoring of internet activities (Kowalski et al., 2014; Ybarra & Mitchell,
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
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
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
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).
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
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.
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
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,
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.,,) (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
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,
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
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
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
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
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
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
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.
Aboujaoude, E., Savage, M. W., Starcevic, V., & Salame, W. O. (2015). Cyberbullying: Review
of an old problem gone viral. Journal of Adolescent Health, 57(1), 10-18.
Agnew, R. (2001). Building on the foundation of general strain theory: Specifying the types of
strain most likely to lead to crime and delinquency. Journal of Research in Crime and
Delinquency, 38, 319-361.
Ahlfors, R. (2010). Many sources, one theme: Analysis of cyberbullying prevention and
intervention websites. Journal of Social Sciences, 6(4), 515-522.
Ang, R. P., & Goh, D. H. (2010). Cyberbullying among adolescents: The role of affective and
cognitive empathy, and gender. Child Psychiatry & Human Development, 41, 387-397.
Bandura, A. (1978). Social learning theory of aggression. Journal of Communication, 28, 12-29.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory.
Englewood Cliffs, NJ: Prentice-Hall.
Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual review of
psychology, 52(1), 1-26.
Bauer, N. S., Lozano, P., & Rivara, F. P. (2007). The effectiveness of the Olweus Bullying
Prevention Program in public middle schools: A controlled trial. Journal of Adolescent
Health, 40(3), 266-274.
Bauman, S. (2009). Cyberbullying in a rural intermediate school: An exploratory study. The
Journal of Early Adolescence, 30, 803-833.
Bauman, S. (2013). Cyberbullying: What does research tell us?. Theory Into Practice, 52(4),
Bauman, S., Toomey, R. B., & Walker, J. L. (2013). Associations among bullying, cyberbullying,
and suicide in high school students. Journal of adolescence, 36(2), 341-350.
Beale, A. V., & Hall, K. R. (2007). Cyberbullying: What school administrator (and parents) can
do. The Clearing House, 81, 8-12.
Beale, A. V., & Hall, K. R. (2007). Cyberbullying: What school administrators (and parents) can
do. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 81(1), 8-
Bevans, K. B., Bradshaw, C. P., & Waasdorp, T. E. (2013). Gender bias in the measurement of
peer victimization: An application of item response theory. Aggressive behavior, 39(5),
Bowen, G. L., Richman, J. M., Brewster, A., & Bowen, N. (1998). Sense of school coherence,
perceptions of danger at school, and teacher support among youth at risk of school
failure. Child and Adolescent Social Work Journal, 15, 273-286.
Boxer, P., & Dubow, E. F. (2002). A social-cognitive information-processing model for school-
based aggression reduction and prevention programs: Issues for research and practice.
Applied & Preventive Psychology, 10, 177-192.
Bronfenbrenner, U. (1977) ‘Toward an experimental ecology of human development’, American
Cappadocia, M. C., Craig, W. M., & Pepler, D. (2013). Cyberbullying: prevalence, stability, and
Risk Factors during adolescence. Canadian Journal of School Psychology, 28(2), 171-
Casas, J. A., Del Rey, R., & Ortega-Ruiz, R. (2013). Bullying and cyberbullying: Convergent and
divergent predictor variables. Computer in Human Behavior, 29, 580-587.
Cassidy, W., Brown, K., & Jackson, M. (2012). ‘Under the radar’: Educators and cyberbullying
in schools. School Psychology International, 33(5), 520-532.
Cassidy, W., Faucher, C., & Jackson, M. (2013). Cyberbullying among youth: A comprehensive
review of current international research and its implications and application to policy and
practice. School Psychology International, 34(6), 575-612.
Centers for Disease Control and Prevention. (2009). Technology and youth: Protecting your child
from electronic aggression. Injury Prevention & Control: Violence Prevention Retrieved
April, 24, 2013.
Chibnall, S., Wallace, M., Leicht, C., & Lunghofer, L. (2006). I-safe evaluation. Final report.
Cohen, L. E., & Felson, M. (1979). Social change and crime rate trends: A routine activity
approach, American Sociological Review, 44, 588-608.
Couvillon, M. A., & Ilieva, V. (2011). Recommended practices: A review of schoolwide
preventative programs and strategies on cyberbullying. Preventing School Failure:
Alternative Education for Children and Youth, 55(2), 96-101.
Craig, W. M., Pepler, D., & Atlas, R. (2000). Observations of bullying in the playground and in
the classroom. School Psychology International, 21(1), 22-36.
David-Ferdon, C., & Hertz, M. F. (2009). Electronic Media and Youth Violence: A CDC Issue
Brief for Researchers. Centers for Disease Control and Prevention.
Dehue, F., Bolman, C., & Vollink, T. (2008). Cyberbullying: Youths’ experiences and parental
perception. CyberPsychology & Behavior, 11, 217-223.
Dekovic, M. (1999). Risk and protective factors in the development of problem behavior during
adolescence. Journal of Youth and Adolescence, 28, 667-685.
Dublin, R. (1978). Theory building. New York: Free Press.
Eisenberg, N., & Strayer, J. (1987). Critical issues in the study of empathy. In N. Eisenberg & J.
Strayer (Eds.), Empathy and its development: Cambridge studies in social and emotional
development (pp. 3-13). New York, NY: Cambridge University Press.
Espelage, D. L., Low, S., Van Ryzin, M. J., & Polanin, J. R. (2015). Clinical trial of second step
middle school program: impact on bullying, cyberbullying, homophobic teasing, and
sexual harassment perpetration. School Psychology Review, 44(4), 464-479.
Espelage, D. L., Low, S., Van Ryzin, M. J., & Polanin, J. R. (2015). Clinical trial of second step
middle school program: impact on bullying, cyberbullying, homophobic teasing, and
sexual harassment perpetration. School Psychology Review, 44(4), 464-479.
Espelage, D. L., Rao, M. A., & Craven, R. (2012). Theories of cyberbullying. In S. Bauman, D.
Cross, & J. L. Walker (Eds.), Principles of cyberbullying research: Definitions, measures,
and methodology (pp. 78-97). New York: Routledge.
Espelage, D.L. (2012). Bullying prevention: A research dialogue with Dorothy Espelage.
Prevention Researcher, 19 (3), 17 – 19.
Fanti, K. A., Demetriou, A. G., & Hawa, V. V. (2012). A longitudinal study of cyberbullying:
Examining riskand protective factors. European Journal of Developmental Psychology,
9(2), 168-181.
Farrington, D. P., & Ttofi, M. M. (2009). School-based programs to reduce bullying and
victimization. The Campbell Collaboration, 6, 1-149.
Feinberg, T., & Robey, N. (2009). Cyberbullying: Intervention and prevention strategies.
National Association of School Psychologists, 38(4), 22-24.
Felson, M., & Boba, R. (2010). Crime and everyday life (4th ed.). Los Angeles, CA: Sage
Gámez-Guadix, M., Orue, I., Smith, P. K., & Calvete, E. (2013). Longitudinal and reciprocal
relations of cyberbullying with depression, substance use, and problematic internet use
among adolescents. Journal of Adolescent Health, 53(4), 446-452.
Gradinger, P., Strohmeier, D., & Spiel, C. (2011). Motives for bullying others in cyberspace. In
Q. Li, D. Cross & P. K. Smith (eds.), Cyberbullying in the global playground: Research
from international perspectives. Oxford, UK: Wiley-Blackwell.
Groff, E. R. (2007). Simulation for theory testing and experimentation: An example using routine
activity theory and street robbery’ Journal of Quantitative Criminology, 23, 75-103.
Hay, C., Meldrum, R., & Mann, K. (2010). Traditional bullying, cyber bullying, and deviance. A
general strain theory approach. Journal of Contemporary Criminal Justice, 26, 130-147.
Hinduja, S., & Patchin, J. W. (2008). Cyberbullying: An exploratory analysis of factors related to
offending and victimization. Deviant Behavior, 29(2), 129-156.
Hinduja, S., & Patchin, J. W. (2009). Bullying beyond the schoolyard: Preventing and
Hinduja, S., & Patchin, J. W. (2010). Cyberbullying research summary: Cyberbullying and
Strain. Retrieved from
Hinduja, S., & Patchin, J. W. (2011). Cyberbullying: A review of the legal issues facing educators.
reventing School Failure: Alternative Education for Children and Youth, 55(2), 71-78.
Hinduja, S., & Patchin, J. W. (2013). Social influences on cyberbullying behaviors among middle
and high school students. Journal of Youth and Adolescence, 42, 711-722.
Hoff, D. L., & Mitchell, S. N. (2009). Cyberbullying: Causes, effects, and remedies. Journal of
Educational Administration, 47(5), 652-665.
Holladay, J. (2011). Cyberbullying. Education Digest, 76(5), 4-9.
Hong, J.S., & Espelage, D.L. (2012). A review of research on bullying and peer victimization
in school: An ecological systems analysis. Aggression and Violent Behavior, 17, 311 –
312. doi: 10.1016/j.avb.2012.03.003
Jang, H., Song, J., & Kim, R. (2014). Cyberbullying behavior among youths? Application of the
general strain theory. Computers in Human Behavior, 31, 85-93.
Juvonen, J., & Gross, E. F. (2008). Extending the school grounds? Bullying experiences in
cyberspace. Journal of School Health, 78(9), 496-505.
Juvonen, J., & Gross, E. F. (2008). Extending the school grounds?—Bullying experiences in
cyberspace. Journal of School health, 78(9), 496-505.
Keith, S., & Martin, M. E. (2005). Cyber-bullying: Creating a culture of respect in a cyber world.
Reclaiming children and youth, 13(4), 224.
Kowalski, R. M., Giumetti, G. W., Schroeder, A. N., Lattanner, M. R. (2014). Bullying in the
digital age: A critical review and meta-analysis of cyberbullying research among youth.
Psychological Bulletin, 140, 1073-1137.
Kowalski, R. M., Limber, S. P., Limber, S., & Agatston, P. W. (2012). Cyberbullying: Bullying in
the digital age (2nd ed.). John Wiley & Sons.
Kowalski, R. M., Limber, S. P., Limber, S., & Agatston, P. W. (2012). Cyberbullying: Bullying in
the digital age. John Wiley & Sons.
Kulig, J. C., Hall, B. L., & Kalischuk, R. G. (2008). Bullying perspectives among rural youth: A
mixed methods approach. Rural & Remote Health, 8(2), 1-11.
Lane, D. K. (2011). Taking the lead on cyberbullying: Why schools can and should protect
students online. Iowa Law Review, 96(5), 1791-1811.
Lenhart, A. (2015). Teens, social media & technology overview 2015. Pew Research Center, 9.
Li, Q. (2006). Cyberbullying in schools: A research of gender differences. School Psychology
International, 27(2), 157-170.
Low, S., & Espelage, D. (2013). Differentiating cyber bullying perpetration from non-physical
bullying: Commonalities across race, individual, and family predictors. Psychology of
Violence, 3, 39-52.
Marcum, C. D., Higgins, G. E., & Ricketts, M. L. (2010). Potential factors of online
victimization of youth: An examination of adolescent online behavior utilizing routine
activity theory. Deviant Behavior, 31, 381-410.
Mesch, G. S. (2009). Parental mediation, online activities, and cyberbullying. CyberPsychology
& Behavior, 12, 387-393.
Mishina, F., Saini, M., & Solomon, S. (2009). Ongoing and online: Children and youth’s
perceptions of cyber bullying. Children and Youth Services Review, 31, 1222-1228.
Mishna, F., Cook, C., Saini, M., Wu, M. J., & MacFadden, R. (2009). Interventions for children,
youth, and parents to prevent and reduce cyber abuse.
Mishna, F., Cook, C., Saini, M., Wu, M. J., & MacFadden, R. (2009). Interventions for children,
youth, and parents to prevent and reduce cyber abuse.
Nansel, T. R., Overpeck, M., Pilla, R. S., Ruan, W. J., Simons-Morton, B., & Scheidt, P. (2001).
Bullying behaviors among US youth: Prevalence and association with psychosocial
adjustment. Jama, 285(16), 2094-2100.
National Children’s Home (2005). Putting U in the picture: Mobile bullying survey. Retrieved
May 18th, 2011, from
Navarro, J. N., & Jasinski, J. L. (2011). Going cyber: Using routine activities theory to predict
cyberbullying experiences. Sociological Spectrum, 32, 81-94.
Navarro, J. N., & Jasinski, J. L. (2013). Why girls? Using routine activities theory to predict
cyberbullying experiences between girls and boys. Women & Criminal Justice, 23, 286-
Noret, N., & Rivers, I. (2006, March). The prevalence of bullying by text message or email:
Results of a four year study. In Poster presented at British Psychological Society Annual
Conference, Cardiff, April.
Notar, C. E., Padgett, S., & Roden, J. (2013). Cyberbullying: A review of the
literature. Universal Journal of Educational Research, 1(1), 1-9.
Notar, C. E., Padgett, S., & Roden, J. (2013). Cyberbullying: Resources for Intervention and
Prevention.Universal Journal of Educational Research, 1(3), 133-145.
Olweus, D. (2012). Cyberbullying: An overrated phenomenon?. European Journal of
Developmental Psychology, 9(5), 520-538.
Olweus, D., & Limber, S. P. (2010). Bullying in school: evaluation and dissemination of the
Olweus Bullying Prevention Program. American Journal of Orthopsychiatry, 80(1), 124.
Paez, G. R. (2016). Cyberbullying among adolescents: A general strain theory perspective.
Journal of School Violence. doi:
Patchin, J. W., & Hinduja, S. (2010). Cyberbullying and self-esteem. Journal of School Health,
80(12), 614-624.
Patchin, J. W., & Hinduja, S. (2010). Traditional and nontraditional bullying among youth: A test
of general strain theory. Youth & Society, 41, 727-751.
Patchin, J. W., & Hinduja, S. (2012). Cyberbullying prevention and response: Expert
perspectives. Routledge: Taylor & Francis Group.
Paul, S., Smith, P. K., & Blumberg, H. H. (2012). Revisiting cyberbullying in schools using the
quality circle approach. School Psychology International, 33(5), 492-504.
Pearce, N., Cross, D., Monks, H., Waters, S., & Falconer, S. (2011). Current Evidence of Best
Practice in Whole-School Bullying Intervention and Its Potential to Inform Cyberbullying
Interventions. Australian Journal of Guidance and Counselling, 21(01), 1-21.
Pearce, N., Cross, D., Monks, H., Waters, S., & Falconer, S. (2011). Current Evidence of Best
Practice in Whole-School Bullying Intervention and Its Potential to Inform Cyberbullying
Interventions. Australian Journal of Guidance and Counselling, 21(01), 1-21.
Pergolizzi, F., Pergolizzi, J., Gan, Z., Macario, S., Pergolizzi, J. V., Ewin, T. J., & Gan, T. J.
(2011). Bullying in middle school: Results from a 2008 survey. International journal of
adolescent medicine and health, 23(1).
Perren, S., & Gutzwiller-Helfenfinger, E. (2012). Cyberbullying and traditional bullying in
adolescence: Differential roles of moral disengagement, moral emotions, and moral
values. European Journal of Developmental Psychology, 9, 195-209.
Price, M., & Dalgleish, J. (2010). Cyberbullying experiences, impacts and coping strategies as
described by Australian young people. Youth Studies Australia, 29(2), 51-59.
Psychologist, 32: 513-531.
Raskauskas, J. (2010). Multiple peer victimization among elementary school students: Relations
with social-emotional problems. Social Psychology of Education, 13(4), 523-539.
Raskauskas, J., & Stoltz, A. D. (2007). Involvement in traditional and electronic bullying among
adolescents. Developmental psychology, 43(3), 564.
Renati, R., Berrone, C., & Zanetti, M. A. (2012). Morally disengaged and unempathic: Do
cyberbullies fit these definitions? An exploratory study. Cyberpsychology, Behavior, and
Social Networking, 15, 391-398.
responding to cyberbullying. Thousand Oaks, CA: Sage, Corwin Press.
Roberto, A. J., Eden, J., Savage, M. W., Ramos-Salazar, L., & Deiss, D. M. (2014). Outcome
evaluation results of school-based cybersafety promotion and cyberbullying prevention
intervention for middle school students. Health communication, 29(10), 1029-1042.
Rueckert, L., & Naybar, N. (2008). Gender differences in empathy: The role of the right
hemisphere. Brain and Cognition, 67, 162-167.
Salvatore, A. J. (2006). An anti-bullying strategy: Action research in a 5/6 intermediate school.
Hartford (CT): University of Hartford.
Schneider, S. K., O’Donnell, L., Stueve, A., & Coulter, R. W. S. (2012). Cyberbullying, school
bullying, and psychological distress: A regional census of high school students. American
Journal of Public Health, 102, 171-177.
Selkie, E. M., Fales, J. L., & Moreno, M. A. (2016). Cyberbullying Prevalence Among US
Middle and High School–Aged Adolescents: A Systematic Review and Quality
Assessment. Journal of Adolescent Health, 58(2), 125-133.
Slonje, R., & Smith, P. K. (2008). Cyberbullying: Another main type of bullying? Scandinavian
Journal of Psychology, 49(2), 147-154.
Slonje, R., Smith, P. K., & FriséN, A. (2013). The nature of cyberbullying, and strategies for
prevention. Computers in Human Behavior, 29(1), 26-32.
Smith, P. K., Mahdavi, J., Carvalho, M. & Tippett, N. (2006). An investigation into
cyberbullying, its forms, awareness and impact, and the relationship between age and
gender in cyberbullying. Research Brief No. RBX03-06. DfES, London.
Smith, P. K., Mahdavi, J., Carvalho, M., & Tippett, N. (2006). An investigation into
cyberbullying, its forms, awareness and impact, and the relationship between age and
gender in cyberbullying. Research Brief No. RBX03-06.DfES, London.
Smith, P. K., Mahdavi, J., Carvalho, M., Fisher, S., Russell, S., & Tippett, N. (2008).
Cyberbullying: Its nature and impact in secondary school pupils. Journal of child
psychology and psychiatry, 49(4), 376-385.
Smokowski, P. R., Evans, C. B. R., & Cotter, K. L. (2014). The differential impacts of episodic,
chronic, and cumulative physical bullying and cyberbullying: The effects of victimization
on the school experiences, social support, and mental health of rural adolescents.
Violence and Victims, 29, 1029-1046.
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.
Sourander, A., Klomek, A. B., Ikonen, M., Lindross, J., Luntamo, T., Koskelainen, M.,...Helenus,
H. (2010). Psychosocial risk factors associated with cyberbullying among adolescents.
Archives of General Psychiatry, 67, 720-728.
Srabstein, J. C., Berkman, B. E, & Pyntikova, E. (2008). Antibullying legislation: A public health
perspective. Journal of Adolescent Health, 42(1), 11-20.
Steffgen, G., Konig, A., Pfetsch, J., & Melzer, A. (2011). Are cyberbullies less empathic?
Adolescents’ cyberbullying behavior and emotional responsiveness. Cyberpsychology,
Behavior, and Social Networking, 14, 643-648.
Sticca, F., Ruggieri, S., Alsaker, F., & Perren, S. (2013). Longitudinal risk factors for
cyberbullying in adolescence. Journal of Community & Applied Social Psychology, 23,
Subrahmanyam, K., & Greenfield, P. (2008). Online communication and adolescent
relationships. The Future of Children, 18, 119-146.
Thorton, T. N., Craft, C. A., Dahlberg, L. L., Lynch, B. S., & Baer, K. (2000). Best practices of
youth violence prevention: A sourcebook for community action. Atlanta, GA: Centers for
Disease Control and Prevention.
Tinker v. Des Moines Independent Sch. Dist., 393 U.S. 503, 506 (1969).
Tokunaga, R. S. (2010). Following you home from school: A critical review and synthesis of
research on cyberbullying victimization. Computers in Human Behavior, 26, 277-287.
Topcu, Ç., & Erdur-Baker, Ö. (2012). Affective and cognitive empathy as mediators of gender
differences in cyber and traditional bullying. School Psychology International, 33(5),
Torney-Purta, J. (2002). The school’s role in developing civic engagement: A study of
adolescents in twenty-eight countries. Applied Developmental Science, 6, 203-212.
Twyman, K., Saylor, C., Taylor, L. A., & Comeaux, C. (2010). Comparing children and
adolescents engaged in cyberbullying to matched peers. Cyberpsychology, Behavior, and
Social Networking, 13(2), 195-199.
Van Geel, M., Vedder, P., & Tanilon, J. (2014). Relationship between peer victimization,
cyberbullying, and suicide in children and adolescents: a meta-analysis. JAMA pediatrics,
168(5), 435-442.
Wade, A., & Beran, T. (2011). Cyberbullying: The new era of bullying. Canadian Journal of
School Psychology, 26, 44-61.
Walrave, M., & Heirman, W. (2011). Cyberbullying: Predicting victimisation and perpetration.
Children & Society, 25(1), 59-72.
Wang, J., Iannotti, R. J., & Nansel, T. R. (2009). School bullying among adolescents in the
United States: Physical, verbal, relational, and cyber. Journal of Adolescent health, 45(4),
Wikstrom, P.O.H. (2009). Routine activity theories. Oxford Bibliographies. doi:
Willard, N. (2011). School response to cyberbullying and sexting: The legal challenge. Brigham
Young University Education & Law Journal, 1, 75-125.
Williams, K. R., & Guerra, N. G. (2007). Prevalence and predictors of internet bullying. Journal
of adolescent health, 41(6), S14-S21.
Wilson, E. (2007, February 7). As bullies go high-tech, lawmakers say schools should be fighting
back. The Seattle Times. Retrieved from
Wong-Lo, M. (2009). Cyberbullying: Responses of adolescents and parents toward digital
aggression (Unpublished Doctoral Dissertation). Denton, TX: University of North Texas.
Ybarra, M. L., & Mitchell, K. J. (2004a). Online aggressor/targets, aggressors, and targets: A
comparison of associated youth characteristics. Journal of child Psychology and
Psychiatry, 45(7), 1308-1316.
Ybarra, M. L., & Mitchell, K. J. (2004b). Youth engaging in online harassment: Associations
with caregiver-child relationships, Internet use, and personal characteristics. Journal of
Adolescence, 27, 319-336.
Ybarra, M. L., Espelage, D. L., & Mitchell, K. J. (2007). The co-occurrence of Internet
harassment and unwanted sexual solicitation victimization and perpetration: Associations
with psychosocial indicators. Journal of Adolescent Health, 41(6), S31-S41.
Zhang, A., Musu-Gillette, L., & Oudekerk, B. A. (2016). Indicators of School Crime and Safety:
2015. NCES 2016-079. NCJ 249758. National Center for Education Statistics.
Table 1. Cyberbullying prevention programs and Interventions in the United States.
Program/Intervention Type Target
Length State Program
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.
K-12 Students,
Long term US-wide Prosocial
behaviors, school
climate, social
The Second Step Bullying Prevention Program
The program is based on Social Emotional
Learning skills and attitudes that help prevent
cyberbullying. Encourages helpful bystander
5-12 years
Student, parents,
13 – 15
US-Wide Empathy,
social problem
solving skills
Prevention oriented lessons based on peer
networks and student leadership. Educate
students in cyberbullying, social networking,
cyber etiquette, and e-safety.
Digital resources,
5-8 years
School, Staff,
5 lessons US-wide Cyber Privacy,
prevention, e-
Not research
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
5-8 years
9 lessons Washington
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
reductions in
Cyberbullying prevention engine
Aim to protect children from cyberbullying and
risky online behavior by filtering content
delivered to mobile devices. Monitor
communications by keywords.
Parents, school
US-Wide Cyber security,
Not research
A federal government website with information
about cyberbullying prevention. Offer advice
of what to do if someone is been cyberbullied.
Website Students,
School Staff,
US-Wide Awareness,
Not Research
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, schoolwide 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.
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.
... At the same time, we need to understand this issue with a gendered lens, as data from U.S. high school students have found that 20% of girls compared with 11% of boys having experienced CV [7]. While cyberbullying can take many forms including incidents of insult, humiliation, threats, and blackmail [8][9][10], there are notable gender differences in the nature of these abuses. Cyberbullying of girls is more likely to be sexually aggressive in nature (e.g., calling the victim a "slut" or sharing of sexually explicit pictures) and linked to a male partner, where cyberbullying of boys is more likely to be homophobic or transphobic in nature, focused on physical threats and perpetrated by a male peer [11]. ...
Full-text available
Cyberbullying victimization (CV), a widespread experience in adolescence, is associated with increased depression and suicidality. However, few studies have taken a gender approach when investigating the association between CV and suicidality, despite research that indicates disparate experiences by gender for both CV and mental health. We conducted a secondary data analysis of the 2019 Youth Risk Behavior Survey (N = 10,309; 50.1% girls), a cross-sectional survey drawn from a representative sample of US high school students. We found that CV remained significantly associated with suicidality after controlling for emotional and behavioral risk factors, for both boys and girls. CV increased the odds of suicidality directly and indirectly by increasing risk for depression, for both boys and girls. Boys contending with both CV and sexual violence were particularly vulnerable to suicidality, and binge drinking was positively associated with CV for girls but negatively associated with CV for boys. Findings confirmed that CV is a pervasive issue among U.S. adolescents. A gendered approach is necessary in order to understand and address the effects of CV.
... Unfortunately, cyberbullying has become prevalent among school-age children [33]. In a recent nationally representative survey of teenagers, the Pew Internet and American Life Project found that approximately 60% of teens aged 12-17 years old have personally expe-Future Internet 2021, 13, 223 3 of 12 rienced abusive online behaviors [34]. ...
Full-text available
This manuscript examined the role trait verbal aggression plays in cyberbullying victimization and perpetration in adolescence. More than 400 middle school students (46.8% males and 52.2% females) completed a questionnaire on trait verbal aggression and their history of cyberbullying perpetration and victimization. Linear regression analyses revealed that trait verbal aggression was a statistically significant predictor of both cyberbullying perpetration and victimization, that cyberbullying perpetration and cyberbullying victimization are related, and that cyberbullying perpetration appears to increase with age, while cyberbullying victimization does not. Ideas and implications for future applications of verbal aggression and cyberbullying are discussed.
... Введение А ктивное развитие информационных технологий по всему миру создаёт условия для оживленных интернет коммуникаций, которые становятся неотъемлемой частью жизни подростка [30]. Исследование агрессивного поведения в среде Интернет и проблемы виртуального экстремизма в этой связи становятся крайне актуальными и важными задачами государственного уровня. ...
Full-text available
Introduction. Communication in adolescence is often accompanied by a manifestation of insecurity and increased levels of anxiety. The research urgency is caused by necessity of psychological-pedagogical study of the phenomenon of communication of adolescents with a high level of anxiety that will improve the work of specialists to ensure the optimal intellectual, emotional, and personal development in individuals in this age group. The purpose of the study is to compile psychological characteristics of "anxious" and "non-anxious teenagers" in the process of communication. Materials and methods of research. Empirical research was conducted in educational organizations in Kolomna and Orekhovo-Zuyevo, Moscow region, where students of grades 6-7 acted as respondents. Total sample size: 60 people: 30 girls and 30 boys. In the interests of studying the psychological and pedagogical characteristics of interpersonal communication of adolescents with an increased level of anxiety, we used the following empirical methods: the method "test of communicative skills of L. V. Michelson", which allows you to determine the level of communicative competence and the quality of formation of basic communicative skills in the study sample; the method of studying the level of communication and organizational abilities (CBS) Sinyavsky V. V., Fedoroshin V. A.); the method "Diagnostics of interpersonal relations" (DMO) T. Leary, which allows you to identify the features of interpersonal communication of adolescents; Phillips' method of diagnosing the level of school anxiety, which allows you to assess not only the overall level of school anxiety, but also the components of General anxiety associated with various areas of school life. In addition, we used statistical data processing methods: Spearman correlation analysis, Mann-Whitney comparative analysis, included in the statistical analysis package STATISTICA v. 6.0. Results. Our empirical study to identify the features of communication between adolescents with an increased level of anxiety, showed that this category of children is characterized by resorting to a dependent type of behavior in the process of communication, this indicator was found in 15 respondents (25%), which may be manifested depending on the opinion of others, the need for help and trust from others and excessive modesty, which is also characteristic of another type of communication of this category of teenagers – the submissive type. In addition, teenagers with an increased level of anxiety can choose an aggressive type in communication, this indicator was found in 9 respondents (15 % of the group), which can be expressed in intemperance, short temper and unfriendliness.
... Although the social cognitive theory has been used to explore aggressive behavior for decades (Bandura, 1978), it is just beginning to be applied in cyberbullying research since the phenomenon is relatively new (Bauman, 2009;Espelage et al., 2018;Perren & Gutzwiller-Helfenfinger, 2012;Swearer, Wang, Berry, & Myers, 2014). Yet social cognitive theory provides a strong basis for understanding cyberbullying, in part due to the theory's strength in conceptualizing in-person bullying and other forms of aggressive behavior. ...
Cyberbullying is a major health concern for today's youth and a pervasive stressor for adolescents and their families. This study offers qualitative insights into how parents perceive their children's technology use and engagement in cyberbullying based on gender. Eight focus groups were conducted with 48 parents of adolescents ages 10–17. Findings indicated parents perceived their children overuse technology and lack awareness of what cyberbullying is. Specific to gender, parents suggested their daughters use technology for social connection, and parents were more concerned about their daughter's technology use than their son's, which they believed was related to specific interests. In response to cyberbullying scenarios, parents encouraged females but not males to socialize with peers. This is the first qualitative study to obtain an in‐depth understanding of the ways in which parents perceive and socialize their children in regard to technology use and cyberbullying scenarios. These results may help school systems, school psychologists, researchers, and parents gain awareness of the gender‐stereotypical socialization process that unfolds in parental monitoring of technology use and cyberbullying situations. We conclude by offering suggestions for how school systems and personnel might intervene.
... Although the concept of cyberbullying is still in its infancy, a relatively robust vocabulary has been created to describe the phenomenon, including words and phrases such as flaming, cyber harassment, cyberstalking, denigration, masquerading, outing, trickery, and exclusion (Espelage, Hong, & Valido, 2018). The sheer number and nuanced meanings of the words suggest that scholars have given the topic a lot of thought. ...
School psychologists and school counselors can act as agents of social justice in schools to prevent cyberbullying, particularly among the most vulnerable populations. Cyberbullying is an emerging form of bullying that has shown an alarming increase in society within the last decade and in schools as microcosms of society. Cyberbullying among K-12 students has adverse social, physical, and emotional impacts for victims, perpetrators, and bystanders. Advocacy for prevention, intervention, and more effective policies from school psychologists and counselors is of paramount importance for student and school community well-being and safety. This article provides an overview of cyberbullying in schools as a social justice issue; explores advocacy, ethical, and practitioner roles of both school psychologists and school counselors to address this issue among students in schools; discusses empirically based psychotherapy techniques for intervention and risk assessment; and offers policy and practice options to address cyberbullying.
Full-text available
Online lynching targets all kinds of online activities carried out by a user and their presence in digital networks. Publicly-published posts or such different contents as leaked private messages-even an offline action-can be used as an excuse to start online lynching. Activists are one of the groups that are considered the victims of online lynching while interactively using SNWs to inform others, to provide them with skills on social issues, or to reveal their skills. Online lynchers are directly concerned with the activists themselves rather than the advocacy contents of the activists. The purpose of this research is to discuss the lynching experiences of activists on social media. Moreover, to reveal the underlying causes of lynching and its consequences from the perspective of the activists. In this context, a semi-structured interview was conducted with some vegan activists producing content on social media accounts that represents an individual or a group in Turkey. The activists for the interviews were reached by using the snowball sampling method. The research is outstanding in terms of making sense of the online manifestation of lynching, an offline concept, in the framework of activism. 2 will present that online lynching also has a role in the offline lives of the victims and the concept of online lynching is frequently associated with the concepts of power/potency/masculinity. Moreover, significant differences have been revealed between cyberbullying and online lynching in terms of repetition, anonymity and power imbalance.
Full-text available
The author of this chapter provided a comparison of cyberbullying-related issues across the diverse cyber laws of countries. A definition and distinction between cybercrime and cyberbullying and the impact of cyberbullying on individuals of various ages, socioeconomic, and sociocultural backgrounds were discussed. The cyberbullying provisions in national cyber laws of the top five cyberbullying victim countries were reviewed. Then they were compared to Bangladesh's Information and Communication Technology Act, 2006, and the Digital Security Act, 2018. The final section of the chapter compares the legislation governing cyberbullying in India, Brazil, the United States of America, Belgium, and South Africa to Bangladesh's acts. The comparisons of the crimes demonstrate why the acts are more infamous in Bangladesh than in other nations with a higher rate of cyberbullying victims. Some future recommendations for the Bangladeshi government by examining the country's legislation with the international community and identifying new research possibilities for the future were recommended.
Full-text available
Due to the prevalence of cyberbullying in adolescence and its association with a number of negative psychosocial consequences, there is a need to develop programs to prevent this phenomenon. In this study, the aim was to examine the effect of the Cyberbullying Awareness Program on adolescents’ awareness of cyberbullying and their coping skills. A total of 38 adolescents were included in the study, where 17 adolescents were assigned to the intervention group and 21 to the control group. The mean age of the adolescents was 13.8 (SD = 0.44). The Cyberbullying Awareness Program was administered to the intervention group in 10 sessions. The Cyberbullying Awareness Scale for Adolescents and Coping with Cyberbullying Scale were used as data collection tools in the study. As a result of the study, it was determined that the Cyberbullying Awareness Program was effective in increasing the awareness level of the adolescents in the intervention group about cyberbullying, as well the development of their skills to cope with cyberbullying. In line with the results of the study, suggestions are presented to educators and policy makers. It is recommended that policy makers include cyberbullying prevention programs in their national curriculums in order to increase the awareness of adolescents about cyberbullying and improve their coping skills, and these programs should be implemented by educators to children and adolescents nationwide.
Full-text available
The lack of research on cyberbullying among Indonesian adolescents has become one of the critical arguments of this research. This study aimed to discover the factors that contribute to cyberbullying. This study took samples of students from three schools. The sample was 112 junior to senior high school students. The findings of this study indicate that school climate, parent-child relationship, and empathy have a significant role that encourages cyberbullying. © 2020, Institute of Advanced Engineering and Science. All rights reserved.
Full-text available
This Campbell Systematic Review examines the effectiveness of cyber abuse interventions in increasing internet safety knowledge and decreasing risky online behaviour. The review summarises findings from three studies: one conducted in Canada and the other two in the USA. The participants were middle school students in grades five to eight between the ages of 5‐19 who use the internet or cell phones. A total of 2,713 participants were included in the studies. Cyber abuse interventions and preventions are associated with an increase in internet safety knowledge. Despite the increase in knowledge, students who received the intervention did not become less likely to engage in inappropriate online behaviour, such as disclosing one's name, participating in open chat rooms, or emailing strangers. The three studies were evaluations of the following cyber abuse interventions: I‐SAFE cyber safety program, the missing cyber safety program, and the in‐school cyber bullying intervention (HAHASO). The I‐SAFE cyber safety had the largest effect on internet safety knowledge. Both the missing program and HAHASO suggests that intervention did not significantly change internet‐related safety attitudes or reduce the number of reported cyber bullying experiences. Given the low number of studies available for rigorous cyber abuse prevention and intervention evaluations, the evidence base for these conclusions is weak. Executive summary/Abstract BACKGROUND The Internet has created a new communication tool, particularly for young people whose use of e‐mail, websites, instant messaging, web cams, chat rooms, social networking sites and text messaging is exploding worldwide. While there are many benefits that result from electronic based communication, the Internet is, however, concurrently a potential site for abuse and victimization, whereby young people can fall victim to sexual perpetrators, stalkers, exploiters, and peers who bully online. Interventions regarding cyber abuse have been developed in response to a growing emphasis on protecting children and youth from online dangers. OBJECTIVES To examine the effectiveness of cyber abuse interventions in increasing Internet safety knowledge and decreasing risky online behaviour. SELECTION CRITERIA The scope of this review is experimental and quasi‐experimental prevention and intervention strategies that target children ages 5 to 19 years old and/or their parents, utilize a control group, and examine an outcome related to cyber abuse such as Internet safety knowledge, risky online behaviour, or exposure to inappropriate online content. SEARCH STRATEGY We searched the following databases : Psychological Abstracts (PsycINFO, PsycLIT, ClinPsyc‐clinical subset); MEDLINE; EMBASE; Database of reviews of effectiveness (DARE online); ChildData (child health and welfare); ASSIA (applied social sciences); Caredata (social work); Social Work Abstracts; Child Abuse, Child Welfare & Adoption; Cochrane Collaboration; C2‐SPECTR; Social Sciences Abstracts; Social Service Abstracts; Dissertation Abstracts International (DAI). We also handsearched Youth and Society; Journal of Interpersonal Violence; Annual Review of Sex Research; Computers in Human Behavior; Computers & Education; and Journal of Adolescent Health. Additionally, we contacted experts in the field and searched for grey literature. DATA COLLECTION AND ANALYSIS Two screeners reviewed abstracts and full‐text of all articles. Three articles met all inclusion criteria, and effect sizes and z‐tests were calculated for all relevant outcomes. MAIN RESULTS Significant z‐tests were found between pre‐and post‐test scores on measures related to Internet safety knowledge such as managing online risk and identifying online predators. Most z‐tests related to pre‐ and post‐ measures of risky online behaviour were not significant, including disclosing one's name, participating in open chat rooms, or emailing strangers. REVIEWERS’ CONCLUSIONS Results provide evidence that participation in psychoeducational Internet safety interventions is associated with an increase in Internet safety knowledge but is not significantly associated with a change in risky online behaviour. The need for further research in this field is highlighted.
Full-text available
This report covers topics such as victimization, teacher injury, bullying and cyber-bullying, school conditions, fights, weapons, availability and student use of drugs and alcohol, student perceptions of personal safety at school, and criminal incidents at postsecondary institutions. Indicators of crime and safety are compared across different population subgroups and over time. Data on crimes that occur away from school are offered as a point of comparison where available.
Full-text available
Bullying is becoming an ever more pressing issue for schools, daycare centers, politicians and the public. Everyone agrees that bullying is a serious problem and initiatives are urgently called for to stamp it out. This Campbell Systematic Review studied the effects of anti‐bullying programs in schools. The conclusion is that programs generally work and bullying is reduced on average by around 20%. A total of 89 reports were of sufficient quality to be included in the systematic review. The 89 reports describe 53 different studies. However, nine studies did not provide enough data to allow the calculation of an effect size and were, therefore, not included in the final meta‐analysis. The overall analysis is therefore based on a total of 44 studies. The 44 different studies were carried out between 1983 and mid‐2009 and came from 16 different countries. The included studies were either randomized controlled trials, quasi‐randomized trials, age‐cohort studies or other controlled studies. Furthermore, the systematic review clearly states that future evaluations should measure the children's situation before and after an anti‐bullying program. This should apply to the experimental group as well as the control group to get the most accurate results possible. Executive Summary/Abstract BACKGROUND School bullying has serious short‐term and long‐term effects on children's physical and mental health. Various anti‐bullying programs have been implemented world wide and, more rarely, evaluated. Previous narrative reviews, summarizing the work done on bullying prevention, as well as previous meta‐analyses of anti‐bullying programs, are limited. The definition of school bullying includes several key elements: physical, verbal, or psychological attack or intimidation that is intended to cause fear, distress, or harm to the victim; an imbalance of power (psychological or physical), with a more powerful child (or children) oppressing less powerful ones; and repeated incidents between the same children over a prolonged period. School bullying can occur in school or on the way to or from school. It is not bullying when two persons of the same strength (physical, psychological, or verbal) victimize each other. OBJECTIVES This report presents a systematic review and meta‐analysis of the effectiveness of programs designed to reduce school bullying perpetration and victimization (i.e. being bullied). The authors indicate the pitfalls of previous reviews and explain in detail how the present systematic review and meta‐analysis addresses the gaps in the existing literature on bullying prevention. SEARCH STRATEGY In the present report, we go beyond previous reviews by: doing much more extensive searches for evaluations such as hand‐searching all volumes of 35 journals from 1983 up to the end of May 2009; searching for international evaluations in 18 electronic databases and in languages other than English; and focusing only on programs that are specifically designed to reduce bullying and not aggressive behavior (i.e. the outcome variables specifically measure bullying). Leading researchers in the area of school bullying were also contacted via e‐mail. SELECTION CRITERIA Studies were included in this review if they evaluated the effects of an anti‐bullying program by comparing an experimental group who received the intervention with a control group who did not. The word ‘experimental’ here refers to students who received the program and does not necessarily imply randomization. Four types of research design were included: a) randomized experiments, b) experimental‐control comparisons with before and after measures of bullying, c) other experimental‐control comparisons and d) quasi‐experimental age‐cohort designs, where students of age X after the intervention were compared with students of the same age X in the same school before the intervention. Both published and unpublished (e.g. PhD theses) reports were included. Reports concerning an evaluation of a program had to clearly indicate that bullying or victimization were included as outcome measures. Bullying and victimization could be measured using self‐report questionnaires, peer ratings, teacher ratings, or observational data. RESULTS We found a total of 622 reports that were concerned with bullying prevention. The number of reports on anti‐bullying programs and on the necessity of tackling bullying has increased considerably over time. Only 89 of these reports (describing 53 different program evaluations) could be included in our review. Of the 53 different program evaluations, only 44 provided data that permitted the calculation of an effect size for bullying or victimization. Our meta‐analysis of these 44 evaluations showed that, overall, school‐based anti‐bullying programs are effective in reducing bullying and victimization (being bullied). On average, bullying decreased by 20% – 23% and victimization decreased by 17% – 20%. The effects were generally highest in the age‐cohort designs and lowest in the randomized experiments. It was not clear, however, that the randomized experiments were methodologically superior in all cases, because sometimes a very small number of schools (between three and seven) were randomly assigned to conditions, and because of other methodological problems such as differential attrition. Various program elements and intervention components were associated with a decrease in both bullying and victimization. Work with peers was associated with an increase in victimization. We received feedback from researchers about our coding of 40 out of 44 programs. Analyses of publication bias show that the observed effect sizes (for both bullying and victimization) were based on an unbiased set of studies. AUTHORS’ CONCLUSIONS Results obtained so far in evaluations of anti‐bullying programs are encouraging. The time is ripe to mount a new long‐term research strategy on the effectiveness of these programs, based on our findings. The main policy implication of our review is that new anti‐bullying programs should be designed and tested based on the key program elements and evaluation components that we have found to be most effective. We recommend that a system of accrediting anti‐bullying programs should be developed, supervised by an international body such as the International Observatory on Violence in Schools.
Social-emotional learning programs are increasingly being implemented in U.S. schools to address a wide range of problematic behaviors (e.g., bullying, delinquency) and to promote academic success. The current study examined the direct and indirect impact of the Second Step Middle School Program (Committee for Children, 2008) on bullying, cyberbullying, homophobic name-calling, and sexual harassment perpetration over the course of a 3-year randomized clinical trial. Delinquency was examined as an intervening variable between treatment condition and aggression outcomes. Thirty-six schools in Kansas and Illinois were assigned to either a Second Step condition or a control condition, and 3,651 sixth-grade students completed self-reported surveys at four time points across 3 years. Students in the Second Step condition received a total of 41 lessons across the 3-year study. No direct intervention effects were found for multiple forms of aggression perpetration at the end of 3 years. However, as hypothesized, decreases in self-reported delinquency (intervening variable) over the first 2 years were significantly related to decreases in bullying, cyberbullying, and homophobic name-calling perpetration for Second Step schools across the 3-year study. Indirect effects of the Second Step program on bullying and aggressive behavior were statistically significant through reductions of delinquency.
This Note argues that schools are the best line of defense against the growing problem of cyberbullying and offers a guide for schools wary of First Amendment lawsuits by students punished for their cyberspeech. In many cases, a student engaging in cyberbullying of a classmate will create a substantial disruption at school or interfere with the right of the victim to an environment conducive to learning, thus justifying action by the school under the Tinker standard. Other Supreme Court cases regarding indecent or offensive speech and speech the Court viewed as promoting drug use may provide helpful arguments for schools accused of overstepping constitutional boundaries. This Note also suggests that schools may wish to argue that courts should show more deference to disciplinary decisions made by schools that have punished students for cyberspeech directed at another student as opposed to cyberspeech about a school official. Courts could make this distinction based on an analogy to defamation law.
Crime and Everyday Life, Fourth Edition, provides an illuminating glimpse into roots of criminal behavior, explaining how crime can touch us all in both small and large ways. This innovative text shows how opportunity is a necessary condition for crime to occur, while exploring realistic ways to reduce or eliminate crime and criminal behavior by removing the opportunity to complete the act. Encouraging students to take a closer look at the true nature of crime and its effects on their lives, author Marcus Felson and new co-author Rachel L. Boba (an expert on crime prevention, crime analysis and mapping, and school safety) maintain the book's engaging, readable, and informative style, while incorporating the most current research on criminal behavior and routine activity theory. The authors emphasize that routine daily activities set the stage for illegal acts, thus challenging conventional wisdom and offering students a fresh perspective, novel solutions for reducing crime … and renewed hope. New and Proven Features Includes new coverage of gangs, bar problems, and barhopping; new discussion of the dynamic crime triangle; and expanded coverage of technology, Internet fraud, identity theft, and other Internet pitfalls; The now-famous “fallacies about crime” are reduced to nine and are organized and explained even more clearly than in past editions; Offers updated research on crime as well as new examples of practical application of theory, with the most current crime and victimization statistics throughout; Features POP (Problem-Oriented Policing) Center guidelines and citations, including Closing Streets and Alleys to Reduce Crime, Speeding in Residential Areas, Robbery of Convenience Stores, and use of the Situational Crime Prevention Evaluation Database; Updated “Projects and Challenges” at the end of each chapter Intended Audience This supplemental text adds a colorful perspective and enriches classroom discussion for courses in Criminological Theory, Introduction to Criminal Justice, and Introductory Criminology.