The recent and ever expanding use of technological devices in the daily lives of children and adolescents’ has led to the development of new bullying behaviors dubbed electronic bullying, or cyberbullying. In 2008, over 66% of school age children reported having internet access from their bedroom; today almost 83% have access, and this figure will likely continue to rise (ChildrenOnline, 2008). Increased access to the internet and advanced mobile phones has provided youth with a new world of valuable educational tools, interactive entertainment, and new ways to develop and maintain social identities, but it also exposes them to new forms of harassment. Given that adolescents are especially concerned with how others see them and figuring out where they fit in society, harassment in online venues used to form and maintain social ties has potential to disrupt identity formation (Erikson, 1963). While operational definitions of cyberbullying vary, it can be summarized as intentionally and repeatedly inflicting emotional, mental, or social harm through an electronic medium (Patchin & Hinduja, 2006; Tokunaga 2010). Cyberbullying is a relatively new phenomenon and accordingly, there has been little research published compared to traditional bullying, with the first article focusing specifically on cyberbullying having been published only eight years ago (Patchin & Hinduja, 2006; Snakenborg, Van Acker, & Gable 2011; Tokunaga 2010).
The scarce research available on cyberbullying has focused on assessing prevalence and distress, addressing legal issues, reviewing prevention and intervention possibilities, the similarities and differences of cyberbullying and traditional bullying, and a wide range of individual and systemic factors hypothesized to contribute to the problem (Tokunaga, 2010; Wade & Beran, 2011). Although there have been mixed findings regarding age and few studies focusing on adult populations, research generally shows cyberbullying peaks in middle school between the ages of 11 and 16, meaning youth are disproportionately affected (Calvete, Orue, Estevez, Villardon, & Padilla, 2010; Smith et al., 2008; Tokunaga, 2010; Wade & Beran, 2011; Williams & Guerra, 2007). As a group, youth have considerably less power than adults have, and are less able to access resources to help them solve their social problems. Thus, they are more vulnerable to harassment and marginalization. Non-heterosexual youth are a particularly vulnerable group, as they have been shown to be disproportionately victimized online compared to heterosexual youth (Schneider, O’Donnell, Stueve, & Coulter, 2012). In addition, youth rarely tell adults they have been harassed, which increases the likelihood that they will not receive adequate support, further increasing their vulnerability to lasting psychosocial harm (Juvonen & Gross, 2008; Li, 2006; Li, 2007; Li, 2010; Mishna, Cook, Gadalla, Daciuk, & Solomon, 2010; Slonje & Smith, 2008; Smith et al., 2008). Many youth may feel the adults in their lives are unaware, unwilling, or unable to help them stop cyberbullies, which may lead to a breakdown of relationships with their parents and teachers.
Many factors have been associated with cyberbullying including anonymity, being a traditional bully, frequency of internet use and technical knowledge, justification of and exposure to violence, less parental supervision and enforcement, low social support, narcissistic exploitativeness, negative school climate, normative beliefs displaying approval of aggression and bullying, poor caregiver relationships, and proactive and reactive aggression (Ang & Goh, 2010; Aricak et al., 2008; Calvete et al., 2010; Erdur-Baker, 2009; Hinduja & Patchin, 2008; Kowalski & Limber, 2007; Law, Shapka, Domene, & Gagne, 2012; Mason, 2008; Snakenborg et al., 2011; Tokunaga, 2010; Wade & Beran, 2011; Williams & Guerra, 2007; Ybarra & Mitchell, 2004). Smith et al. (2008) has suggested that entertainment and acquiring social prestige may be factors contributing to cyberbullying behaviors, and Ybarra & Mitchell (2004) have suggested that revenge seeking may be the motivation behind many cyberbullying acts. In contrast, there are few if any studies that have focused on the broader context and systemic factors that may be contributing to cyberbullying. For example, researchers have failed to examine what effects school policies, specific state legislation, or individualistic versus collectivist societies have on prevalence, severity, and types of cyberbullying behaviors.
The impact of cyberbullying ranges from the annoying, such as name-calling and insults which are common in youth peer interactions, to life-threatening actions such as death threats and the encouraging of suicide (Ang & Goh, 2010; Beran & Li, 2005; Diamanduros, Downs, & Jenkins, 2008; Mitchell, Ybarra, & Finkelhor 2007; Stewart & Fritsch, 2011; Tokunaga, 2010). Significant psychosocial distress associated with cyberbullying has been well documented and includes lower self-esteem, higher levels of depression, anger, significant life challenges, peer problems, headaches, recurrent abdominal pain, sleeping difficulties, substance abuse, detentions and suspensions, skipping school, not feeling safe at school, carrying a weapon to school, and even suicide in some cases (Ang & Goh 2010; Beran & Li 2005; Diamanduros et al., 2008; Mitchell et al., 2007; Juvonen & gross 2008; Patchin & Hinduja 2006; Raskauskas & Stoltz 2007; Schneider et al., 2012; Slonje & Smith 2008; Sourander et al., 2010; Stewart & Fritsch, 2011; Wolak, Mitchell, & Finkelhor 2006; Ybarra, Diener-West, & Leaf, 2007; Ybarra & Mitchell 2004). The potential for violent retaliation by victims of cyberbullying is a realistic consequence that must also be considered. Though the research does not adequately cover the effects of these harms on the broader community, individual psychosocial distress and the breakdown of parent-child and teacher-child relationships may negatively affect other domains.
Given the wide range of serious consequences for all parties involved in cyberbullying, it is clear that parents, legislators, law enforcement, school administrators, counselors, and psychologists in particular must take cyberbullying seriously. System wide prevention and intervention programs are necessary in order to ensure the ability of youth to socialize online without being harassed by their peers (Chibbaro, 2007; Diamanduros et al., 2008; Hinduja & Patchin, 2008; Mason, 2008; Patchin & Hinduja, 2006; Stewart & Fritsch, 2011; Wolak et al., 2006). Unfortunately, given that cyberbullying is a relatively new phenomenon, prevention and intervention programs that specifically target cyberbullying are based more on practical beliefs, logical approaches, and traditional face to face bullying programs than scientific evidence (Snakenborg et al., 2011; Mason, 2008; Diamanduros et al., 2008). Additionally, programs focus more on coaching individuals to avoid cyberbullying rather than addressing structural and systemic factors such as school climate, youth culture, or state legislation.
Review of the Literature
While many authors have decried the scarcity of research addressing cyberbullying, there is a growing body of literature focusing on contributing factors, psychosocial effects, and prevention and intervention programs (Patchin & Hinduja, 2006; Snakenborg et al., 2011; Tokunaga, 2010). Researchers generally use self-report surveys and semi-structured interviews to study this phenomenon. Age, gender, and other contributing factors have been the focuses of researchers while minimal efforts have been made to investigate other important factors, such as those needed for evidence based prevention and intervention programs (Mason, 2008; Snakenborg, 2011; Tokunaga, 2010). Several factors are responsible for the relative lack of significant findings in the literature including the rapidly shifting nature of technology use, the use of different definitions used by researchers, a lack of standardized measures and theoretical development, a lack of cross-sectional and longitudinal designs, and almost exclusive reliance on self-report surveys to collect data (Calvete et al., 2010; Erdur-baker, 2010; Juvonen & Gross, 2008; Mitchell et al., 2007; Stewart & Fritsch, 2011; Tokunaga, 2010). The constantly changing nature of technology is an especially tough obstacle given that data from as few as five years ago may now be obsolete.
There has been a wide range of different operational definitions used in the literature that contribute to inconsistent findings (Tokunaga, 2010; Stewart & Fritsch, 2011). Definitions range from very explicitly outlined terms that constitute cyberbullying to definitions that are more general and include a range of harassment behaviors. Various operational definitions cause participants to respond differently to survey items, and it is difficult if not impossible to develop reliable and valid methods to measure cyberbullying without a consistent definition (Tokunaga, 2010; Stewart & Fritsch, 2011). Snakenborg et al. (2011) noted that most definitions of bullying involve repeated physical or verbal behavior with intent to harm others who are less powerful than the bully is. However, in contrast to traditional bullying, cyberbullies do not require direct contact, and they frequently use their technological prowess, rather than physical power or strength, in order to achieve their means (Hinduja & Patchin, 2008; Williams & Guerra, 2007; Ybarra & Mitchell, 2004). Most authors agree that cyberbullying involves intentional harm through electronic means, but it is frequently difficult for researchers and teachers, let alone children, to distinguish between what pushes normative teasing and joking online across the threshold into cyberbullying (Snakenborg et al., 2011). If self-report surveys are to yield accurate information regarding cyberbullying, the participants need to be educated as to what exactly they are endorsing. Children’s relative lack of comprehension regarding what defines cyberbullying behaviors is another example of having less power than adults have to address their social dilemmas.
There is also debate over whether cyberbullying behaviors need to be repeated over time, because some instances of cyberbullying may occur only once, but still be psychologically or emotionally devastating to the victim (Snakenborg et al., 2011). Additionally, different authors measure cyberbullying behaviors retroactively with different times, i.e. whether participants have experienced cyberbullying in the past week versus the past year, which yields different findings in terms of prevalence (Tokunaga, 2010). In an overview of the literature, Tokunaga (2010) suggested that, “Any behavior performed through electronic or digital media by individuals or groups that repeatedly communicates hostile or aggressive messages intended to inflict harm or discomfort on others” (p. 278) should be adopted as an operational definition by all researchers in order to maintain consistency across research designs. Until researchers use consistent conceptual and operational definitions, findings will not be comparable across different samples and populations (Tokunaga, 2010; Stewart & Fritsch, 2011).
Researchers investigating the prevalence of cyberbullying have used many different sample sizes, populations, and operational definitions that have yielded differing results (Stewart & Fritsch, 2011). If researchers do not collaborate in order to use similar methods and definitions, it will be impossible to compare prevalence rates across populations. Schneider et al. (2012) is the largest study known to this author regarding cyberbullying. 20,406 high school students filled out surveys addressing prevalence and impact of cyberbullying as part of the Center for Disease Control and Prevention youth risk behavior survey and the Massachusetts youth risk behavior survey, and 15.8% of participants reported being a victim at one point. However, prevalence findings have ranged from as low as 6.5% found in a national telephone survey of approximately 1,500 internet users between the ages of 10 and 17 years old, to as high as 72% found in an anonymous web-survey of 1,454 participants between the ages of 12 and 17 years old (Juvonen & Gross, 2008; Ybarra & Mitchell, 2004). Differences in prevalence may be found between different types of communities and school structures, which have not been appropriately addressed. Juvonen and Gross (2008) suggested that low prevalence rates, such as those found in Ybarra and Mitchell (2004), may be underestimating the true prevalence because they require parental consent. They posit that fear of parental restriction of internet access may be motivating youth to underreport cyberbullying, especially if they believe they may not be anonymously responding. Smith et al. (2008) explored youth perceptions of cyberbullying and noted that underreporting may also occur because victims are afraid that their bullies will retaliate if they admit to being a victim. Additionally, Smith et al. (2008) found that cyberbullying was more prevalent outside of school, possibly because youth are supervised more closely when using technology when in school. In contrast, over reporting of cyberbullying likely occurs in some studies as well, due to self-selection bias. Patchin and Hinduja (2006), for example, noted that using a web site of a popular musical artist may have drawn participants that are more frequent internet users, a factor that is associated with increased involvement in cyberbullying (Erdur-baker, 2010).
In general, studies show that 20-40% of research participants report being a victim of cyberbullying, although they vary in terms of medium, frequency, severity, and definition of bullying behaviors addressed (Aricak et al., 2008; Dehue et al., 2008; Hinduja & Patchin, 2008; Kowalski & Limber, 2007; Li, 2006, 2007; Mitchell et al., (2007); Patchin & Hinduja, 2006; Smith et al., 2008; Tokunaga, 2010; Ybarra & Mitchell, 2008). E-mail, instant messaging, and chat rooms have previously been found to be the most common medium for cyberbullying, however as technology continually advances, cyberbullies will likely adopt the use of new technology to torment their victims (Beran & Li, 2005, Kowalski & Limber, 2007). Use of older mediums such as E-mail, instant messaging, and chat rooms for cyberbullying will likely decrease as the use of social networking sites and smartphones with picture and video recording replace the older technologies. Evidence for this shift has been found in recent research; mean messages and pictures posted on websites, phone call, and text-messaging bullying were identified as the most prevalent methods of cyberbullying with self-report surveys and semi-structured interviews (Law et al., 2012).
Supervision, Enforcement, and Legal Issues
Cyberbullying is becoming more prevalent due to technological advances, increased access to the internet and technological proficiency (Hinduja & Patchin, 2008; Williams & Guerra, 2007; Ybarra & Mitchell, 2004). Increased prevalence is also due to lack of parental supervision, poor caregiver relationships, a lack of legislation specifically devoted to cyberbullying, and the difficulty inherent in policing it also contribute to the problem (Hinduja & Patchin, 2008; Mason, 2008; Snakenborg et al., 2011; Ybarra & Mitchell, 2004). Ybarra and Mitchell (2004) found involvement in cyberbullying was significantly associated with higher frequency use of the internet and knowledge about technology, and that over 50% of participants that were victims or bullies reported poor parental monitoring. Poor parental monitoring may also be linked to a poor caregiver relationship, which has been shown to increase the risk of being a cyberbullying victim (Ybarra et al., 2007). Mason (2008) suggested that adults’ separation from the digital world may impede the relationship with their children, and this may create more distance and less supervision. Additionally, it is crucial for parents to remember their children desire and deserve a certain amount of privacy, and unreasonably strict technology policies at home may create a rift in the parent child relationship. Though parental monitoring and blocking software have a crucial role in preventing involvement in cyberbullying, determined youth have ways of circumventing restriction systems, and thus parental supervision is not enough to prevent cyberbullying (Patchin & Hinduja, 2006; Ybarra & Mitchell, 2004).
Unlike traditional bullying, cyberbullies are often very adept at hiding evidence of their harassment, which makes it very difficult for parents, educators, or law enforcement to intervene when victims come forward (Stewart & Fritsch, 2011). Although legislation to make cyberbullies criminally liable has been introduced in a number of states, the extremely large number of electronic communications being sent constantly makes it almost impossible to police; ethical questions regarding the monitoring of private messages are also raised (Snakenborg et al., 2011; Stewart & Fritsch, 2011). The fact that electronic communications may originate in a different state than they are received in only adds to the confusion. Mason (2008) listed a number of legal precedents pertaining to schools being allowed to punish students when their online speech causes a significant disruption on campus, but the threshold for legal action is less clear regarding comments from one youth to another off school grounds. Without a clear line designating normative internet use that often includes peers teasing each other from harassment that may cause emotional distress, systemic legal interventions will remain a difficult task (Snakenborg et al., 2011). The effect of this ambiguous line between normal peer social interactions and cyberbullying on legislation is another reason why a precise, consistent definition of cyberbullying is imperative.
Determining the age cyberbullying behaviors begin and peak is crucial in order to design effective prevention programs, because resources can be targeted at the most vulnerable age groups rather than broadly applied across age groups (Tokunaga, 2010). Although adults also participate in cyberbullying, research has focused almost exclusively on youth populations, perhaps because they are seen as more vulnerable and less capable of seeking assistance (Patchin & Hinduja, 2006). Adults may also be more aware than youth regarding what constitutes inappropriate behaviors, and aware that many systems exist to prevent illegal cyberbullying behaviors such as harassment and stalking laws (Stewart & Fritsch, 2011). Overviews of the literature on cyberbullying point out inconsistent results in terms of susceptibility to cyberbullying across the lifespan, and differing peak frequencies approximately between 11 to 16 years of age (Calvete et al., 2010; Schneider et al., 2012; Smith et al., 2008; Tokunaga, 2010; Wade & Beran, 2011; Williams & Guerra, 2007).
In an early investigation using school surveys of 432 Canadian students, Beran and Li (2005) found no significant age differences in agreement with later studies (Hinduja & Patchin, 2008; Patchin & Hinduja, 2006; Slonje & Smith, 2008). However, these authors identified their own use of small range of age groups, self-selection biases, and unclear definitions as potentially skewing their results. The use of larger age ranges might have yielded significant effects in regards to younger or older groups of children. Including a wider age range with adults in future studies is necessary to compare rates of youth versus adult participation, and determine whether youth are truly more vulnerable than adults are. The comparison of psychosocial effects on adults versus children may show that youth are more effected than adults are. If these effects are found, it may suggest that either the relative lack of power and access to resources that youth experience, or their higher valuing of social approval and prestige, may be to blame.
Findings on gender are very similar to the findings regarding age in that no consistent differences are found (Beran & Li, 2005; Patchin & Hinduja, 2006; Schneider et al., 2012; Tokunaga, 2010; Wade & Beran, 2011; Williams & Guerra, 2007), although several studies have found girls to be slightly more involved than boys and vice-versa (Aricak et al., 2008; Erdur-baker, 2010; Li, 2007). Approximately equal involvement of females compared to males participating in cyberbullying means that more girls are involved in cyberbullying than traditional bullying relative to boys, which may be due to the indirect nature of electronic harassment (Hinduja & Patchin, 2008; Smith et al., 2008). Although no differences were found in terms of prevalence between genders, the type of bullying has been shown to differ between the genders, in that boys are associated with higher rates of text message bullying, and girls are associated with higher rates of E-mail bullying (Slonje & Smith, 2008). Girls have also been found to be more likely to have rumors spread about them, to be impersonated online, and solicited for sex than boys, while boys have been found to be more involved in direct threats and carrying out real violence in person (Mishna et al., 2010; Wade & Beran, 2011). Calvete et al. (2010) also found that boys more frequently used ‘happy slapping,’ a specific form of cyberbullying where videos are posted of victims being slapped or otherwise physically assaulted, supporting the findings that boys are more involved in direct forms of electronic harassment. The difference in the form of bullying between male and female youth suggests that gender roles and within-gender peer culture effect how aggression is electronically expressed.
Relationship to Traditional Bullying
Cyberbullying appears to be closely linked to traditional bullying, in that both involve intent to cause harm or humiliation, are frequently perpetrated by youth for entertainment purposes, and are seen as attempts to obtain social status (Tokunaga, 2010). Unlike traditional bullying, however, cyberbullies have the ability to follow their victims into their homes, to remain anonymous, to be on an even playing field with victims that are physically more powerful than they are, and to access a much larger potential audience with less risk of punishment (Erdur-baker, 2010; Snakenborg et al., 2011 Tokunaga, 2010; Wolak et al., 2006; Ybarra & Mitchell 2004). Many cyberbullies appear to be adapting to new technology in order to extend face to face bullying into a digital medium (Hinduja & Patchin, 2008; Raskauskas & Stoltz, 2007). It is possible cyberbullies select their victims at school, and that an underlying vulnerability to any form of peer harassment is responsible for both forms of bullying (Raskauskas & Stoltz, 2007). Additionally, Smith et al., (2008) found that 30 out of 42 traditional victims were also cyberbullies, supporting the hypothesis that at least some traditional victims seek revenge through electronic means (Hinduja & Patchin, 2008; Kowalski & Limber, 2007, Snakenborg et al., 2011).
Indeed, most of the literature shows significant correlations between victims of traditional bullying also being victims of cyberbullying ranging from 32% to 85%, with an average of approximately 60% (Beran & Li, 2005; Erdur-baker, 2010; Hinduja & Patchin, 2008; Juvonen & Gross, 2008; Patchin & Hinduja, 2006; Raskauskas & Stoltz, 2007; Schneider et al., 2012; Slonje & Smith, 2007; Smith et al., 2008; Ybarra et al., 2007). These results were found only through self-report surveys, however, and thus should be interpreted with caution. Erdur-baker (2010), for example, noted that the relationship between the two forms of bullying is not clear because despite the strong correlations, overlap in traditional bullying and cyberbullying victimization may not be causally linked. Children that are victims of both traditional bullying and cyberbullying are affected in multiple social contexts, and have no safe haven from their tormenters. To date, the literature has not adequately addressed whether there are additive effects of traditional and electronic harassment, and how this may affect the broader community.
Characteristics of Cyberbullies
Identifying cyberbullies is often difficult because of the potential to remain anonymous online; however, researchers have found factors correlated with being a cyberbully that may help identify at risk youth. These factors include individual and systemic factors such as proactive and reactive aggression, normative beliefs about aggression and bullying, narcissistic exploitativeness, low social support, justification of violence, exposure to violence, negative school climate, negative peer support, and internet usage frequency (Ang, Tan, & Talib Mansor, 2010; Calvete et al., 2010; Erdur-baker 2010; Law et al., 2012; Williams & Guerra, 2007). Calvete et al. (2010) studied the relationship between cyberbullying, aggression, and justification of violence by administering a self-developed 16-item Cyberbullying Questionnaire to 1,431 youth in Spain between 12 and 17 years old. The authors found significant associations with justification of violence, exposure to violence, proactive aggression, and low perceived social support. While the development of a new, psychometrically sound measure for cyberbullying deserves recognition, the authors acknowledged they were reliant on self-report data, and that reports from peers, parents, and teachers would have strengthened their conclusions. Similarly, Ang et al. (2010) administered a 9-item Cyberbullying Questionnaire in addition to scales to assess narcissism and normative beliefs about aggression to 710 Malaysian adolescents and found that both were significantly raised in cyberbullies. These findings are consistent with Williams and Guerra (2007), as well as previous research on traditional bullying. While the authors reported the age, race, and gender of their samples, failure to consider socioeconomic status may be another confounding variable.
In addition to investigating characteristics of cyberbullies, researchers have hypothesized that anonymity, revenge, fun, and social prestige provided by the online world might be possible motivating factors that drive cyberbullies (Hinduja & Patchin, 2008; Li, 2010; Raskauskas & Stoltz, 2007; Smith et al., 2008; Ybarra & Mitchell, 2004). Several researchers have hypothesized that revenge may be a primary motivation for victims of traditional bullying because of the relative safety and anonymity of cyberbullying (Hinduja & Patchin, 2008; Ybarra & Mitchell, 2004). Youth less powerful than their peers may see the electronic world as more balanced, and thus an opportunity to strike back without fear of physical retaliation (Hinduja & Patchin, 2008; Ybarra & Mitchell, 2004). Raskauskas and Stoltz (2007) found evidence to support this theory in that being a school bully correlated positively with being a victim of web site and chatroom bullying. They explain that anonymity may provide bullied youth with the courage to strike back at the bullies that attack them in real life. Despite this link, they found that traditional bullying victims did not endorse using cyberbullying as revenge. This may be yet another negative consequence of self-report surveys, in that the participants may not have wanted to self identify as bullies, or may not have fully understood the survey items. Entertainment and gaining social prestige are possible alternatives to the revenge hypothesis, which is supported by Li (2010) in that the majority of participants reported that fun is a primary motivation for cyberbullies.
As described earlier, there are significant psychosocial effects on both victims and perpetrators of cyberbullying that range from mild to life threatening. Perpetrators have been shown to have increased likelihood of hyperactivity, conduct problems, low prosocial behavior, and youth who are both victims and bullies are significantly associated with higher severity of issues that affect both groups (Sourander et al., 2010). However, these correlations do not necessarily imply causation; these effects could also be due to emotionally distressed youth being more digitally connected, resulting in a higher likelihood of victimization (Juvonen & Gross, 2008). Nevertheless, these associations show that youth involved in cyberbullying are at increased risk, a fact exemplified by numerous media reports of victims that have apparently committed suicide as a result of cyberbullying (Ang & Goh, 2010; Diamanduros et al., 2008; Mitchell et al., 2007; Stewart & Fritsch, 2011; Tokunaga, 2010).
Though they are more expensive and time consuming than surveys, without controlled longitudinal designs, researchers will not be able to address the causal relationship between cyberbullying and harm. Additional limitations of these studies include selective sampling, excluding physically and mentally disabled children, using survey items that are descriptive but not diagnostic, and not considering contextual influences such as the behaviors and attitudes of peers, parents, and teachers (Sourander et al., 2010; Schneider et al., 2012). These issues are important to address because vulnerable populations are being ignored and may be at higher risk, studies may be overestimating harm due to a lack of diagnostic ability in surveys, and the influence of the social environment on cyberbullying and the aftermath has not been addressed.
Prevention and Intervention
Prevention and intervention are two areas where the research literature on cyberbullying is particularly lacking. Currently implemented programs are not specifically focused on cyberbullying and evidence based research, relying instead on practical and logical approaches based on traditional bullying programs (Mason, 2008; Snakenborg et al., 2011). Examples of these programs include the Stop, Block, and Tell program, which advocates youth who are targeted by cyberbullies end the interaction, block the bully from messaging or E-mailing them online, and tell a parent or teacher (Kowalski et al., 2008). One problem with programs that take a “just say no” approach is that they fail to take into account the extremely high percentage of youth that do not feel comfortable reporting cyberbullying to their parents or teachers. Youth instead choose to rely on their peers or deal with the issue themselves. Programs that do not acknowledge the tendency of youth to keep to themselves and underreport problems are not likely to succeed.
In one of the more detailed reviews of cyberbullying prevention education programs in the literature, Mishna, Cook, Saini, Wu, and MacFadden (2011), analyzed 96 studies that evaluated the I-SAFE program, 64 studies that evaluated the Missing program, and 10 studies that evaluated the HAHASO program, which stands for “Help, Assert Yourself, Humor, Avoid, Self-talk, Own-it.” I-SAFE is mostly off-line and taught to students in Grades 5-8 during five sessions lasting 40 minutes, the Missing program is a computer-based interactive game taught to students in Grades 6-7 during three to four sessions lasting 40 to 50 minutes, and the HAHASO program is a five class traditional anti-bullying program that also collects data relevant to cyberbullying (Mishna et al., 2011). The authors noted the psychoeducational prevention and intervention strategies in the I-SAFE program were associated with increased internet safety knowledge and likelihood to discuss online risks, however this did not appear to decrease risky behavior online. It appears having the appropriate knowledge did not inhibit the inappropriate behavioral response from participants. One potential explanation for these findings is that the limbic system, which controls sensation seeking, is more fully developed at this stage than the frontal lobe, which is responsible for impulse control (Kail & Cavanaugh, 2010). Youth may be aw