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Bullying is unwanted aggressive behavior by another person or group of people. In bullying, there is always an actual or perceived power imbalance, and the aggression is repeated multiple times or is highly likely to be repeated. Bullying also includes cyberbullying, a type of aggression that is carried out through electronic means, such as through the Internet, e-mail, or mobile devices. People of all ages can be bullied, and bullying may take place at home, school, or work. Because of cyberbullying, bullying can occur almost anywhere at any time.

About Bullying

Bullying is when a person or a group shows unwanted aggression toward another person. 1 To be considered bullying, the behavior in question must be aggressive. 2  The behavior must also involve an imbalance of power (e.g., physical strength, popularity, access to embarrassing details about a person) and be repetitive, meaning that it happens more than once or is highly likely to be repeated. 2

Bullying can be 2 :

• Physical: punching, beating, kicking, or pushing; stealing, hiding, or damaging another person's belongings; forcing someone to do things against his or her will
• Verbal: teasing, calling names, or insulting another person; threatening another person with physical harm; spreading rumors or untrue statements about another person
• Relational: refusing to talk to someone or making them feel left out; encouraging other individuals to bully someone

Bullying also includes cyberbullying and workplace bullying.

• Cyberbullying has increased with the increased use of the social media sites, the Internet, e-mail, and mobile devices. 3  Unlike more traditional bullying, cyberbullying can be more anonymous and can occur nearly constantly. 3  A person can be cyberbullied day or night, such as when they are checking their e mail, using Facebook or another social network site, or even when they are using a mobile phone. 3
• Workplace bullying refers to adult behavior that is repeatedly aggressive and involves the use of power over another person at the workplace. 4  Certain laws apply to adults in the workplace to help prevent such violence.  Read more from CDC about occupational violence and laws to prevent it .
• Centers for Disease Control and Prevention. (2014).  Featured topic: bullying research. Retrieved on January 28, 2014, from http://www.cdc.gov/violenceprevention/youthviolence/bullyingresearch/
• U.S. Department of Health and Human Services. (.). What is bullying?  Bullying definition.  Retrieved on August 7, 2012, from  http://www.stopbullying.gov/what-is-bullying/
• Eunice Kennedy Shriver  National Institute of Child Health and Human Development. (2010).  Taking a stand against bullying.  Retrieved on August 7, 2012, from http://www.nichd.nih.gov/news/resources/spotlight/092110-taking-stand-against-bullying
• U.S. Department of Health and Human Services. (n.d.).  Workplace bullying.  Retrieved on August 7, 2012, from  http://www.stopbullying.gov/what-is-bullying/related-topics/index.html#workplace

Who is affected and how many are at risk for bullying?

People of all ages can be bullied. Bullying may take place at home, school, or work.

• A 2013 survey from the National Center for Education Statistics found that bullying continues to affect many school-aged children 1 : Slightly more than 1 out of 5 students in middle and high school experienced “traditional” bullying at school during the 2012–2013 school year. Six percent of students ages 12 to 18 reported that they had been pushed, shoved, tripped, or spit on during the school year. Of these students, 22% reported being injured in the event.
• The 2013 survey found that, during the same school year, 7% of students reported being cyberbullied. 3
• Data from the 2015 Youth Risk Behavior Surveillance System from the Centers for Disease Control and Prevention indicate that about 20% of U.S. students in grades 9 through 12 experienced bullying on school property within the last year. 2
• National Center for Education Statistics. (2016). Indicators of school crime and safety: 2015. Retrieved September 1, 2016, from https://nces.ed.gov/pubs2016/2016079.pdf (PDF 2.8 MB)
• Centers for Disease Control and Prevention. (2016). Youth risk behavior surveillance system. Morbidity and Mortality Weekly Report, 65 , 6. Retrieved June 17, 2016, from http://www.cdc.gov/healthyyouth/data/yrbs/pdf/2015/ss6506_updated.pdf (PDF 2.91 MB)
• National Center for Education Statistics. (2015). Indicators of School Crime and Safety: 2014 . Retrieved June 17, 2016, from https://nces.ed.gov/pubs2015/2015072.pdf (PDF 4.14 MB)

What are common signs of being bullied?

Signs of bullying include 1 , 2 , 3 :

• Depression, loneliness, or anxiety
• Low self-esteem
• Headaches, stomachaches, tiredness, or poor eating habits
• Missing school, disliking school, or having poorer school performance than previously
• Self-destructive behaviors, such as running away from home or inflicting harm on oneself
• Thinking about suicide or attempting to commit suicide
• Unexplained injuries
• Lost or destroyed clothing, books, electronics, or jewelry
• Difficulty sleeping or frequent nightmares
• Sudden loss of friends or avoidance of social situations
• Eunice Kennedy Shriver National Institute of Child Health and Human Development. (2010). Taking a stand against bullying. Retrieved June 17, 2016, from http://www.nichd.nih.gov/news/resources/spotlight/092110-taking-stand-against-bullying
• U.S. Department of Health and Human Services. (n.d.). Who is at risk? Warning signs. Retrieved June 17, 2016, from http://www.stopbullying.gov/at-risk/warning-signs/index.html

How does bullying affect health and well-being?

Bullying can affect physical and emotional health, both in the short term and later in life. It can lead to physical injury, social problems, emotional problems, and even death. 1 Those who are bullied are at increased risk for mental health problems, headaches, and problems adjusting to school. 2 Bullying also can cause long-term damage to self-esteem. 3

Children and adolescents who are bullies are at increased risk for substance use, academic problems, and violence to others later in life. 2

Those who are both bullies and victims of bullying suffer the most serious effects of bullying and are at greater risk for mental and behavioral problems than those who are only bullied or who are only bullies. 2

NICHD research studies show that anyone involved with bullying—those who bully others, those who are bullied, and those who bully and are bullied—are at increased risk for depression. 4

NICHD-funded research studies also found that unlike traditional forms of bullying, youth who are bullied electronically—such as by computer or cell phone—are at higher risk for depression than the youth who bully them. 5 Even more surprising, the same studies found that cyber victims were at higher risk for depression than were cyberbullies or bully-victims (i.e., those who both bully others and are bullied themselves), which was not found in any other form of bullying. Read more about these findings in the NICHD news release: Depression High Among Youth Victims of School Cyberbullying, NIH Researchers Report .  

• Centers for Disease Control and Prevention. (2015). Fact sheet: Understanding bullying . Retrieved June 17, 2016, from https://www.cdc.gov/youth-violence/about/about-bullying.html .
• Smokowski, P. R., & Kopasz, K. H. (2005). Bullying in school: An overview of types, effects, family characteristics, and intervention strategies. Children and Schools, 27, 101–109.

• Eunice Kennedy Shriver National Institute of Child Health and Human Development. (2012). Focus on children's mental health research at the NICHD. Retrieved June 17, 2016, from http://www.nichd.nih.gov/news/resources/spotlight/060112-childrens-mental-health

What are risk factors for being bullied?

Those who are at risk of being bullied may have one or more risk factors 1 , 2 , 3 :

• Are seen as different from their peers (e.g., overweight, underweight, wear their hair differently, wear different clothing or wear glasses, or come from a different race/ethnicity)
• Are seen as weak or not able to defend themselves
• Are depressed, anxious, or have low self-esteem
• Have few friends or are less popular
• Do not socialize well with others
• Suffer from an intellectual or developmental disability
• U.S. Department of Health and Human Services. (n.d.). Who is at risk? Risk factors. Retrieved June 17, 2016, from http://www.stopbullying.gov/at-risk/factors/index.html
• U.S. Department of Health and Human Services. (n.d.). Who is at risk? Considerations for specific groups. Retrieved June 17, 2016, from http://www.stopbullying.gov/at-risk/groups/index.html

What can be done to help someone who is being bullied?

To help someone who is being bullied, support the person and address the bullying behavior. Other ways to help—including what to do if a person is in immediate danger—are listed below.

Support a child who is being bullied: 1

• You can listen to the child and let him or her know you are available to talk or even help. A child who is being bullied may struggle talking about it. Consider letting the child know there are other people who can talk with him or her about bullying. In addition, you might consider referring the child to a school counselor, psychologist, or other mental health specialist.
• Give the child advice about what he or she can do. You might want to include role-playing and acting out a bullying incident as you guide the child so that the child knows what to do in a real situation.
• Follow up with the child to show that you are committed to helping put a stop to the bullying.

Address the bullying behavior: 1

• Make sure a child whom you suspect or know is bullying knows what the problem behavior is and why it is not acceptable.
• Show kids that bullying is taken seriously. If you know someone is being a bully to someone else, tell the bully that bullying will not be tolerated. It is important, however, to demonstrate good behavior when speaking with a bully so that you serve as a role model of good interpersonal behavior.

The " Bullying: Be More Than a Bystander " resource, which includes a presentation and facilitator's guide , seeks to educate people about taking action against bullying. It suggests you can help someone who is being bullied in the following ways: 2

• Be a friend to the person who is being bullied, so they do not feel alone.
• Tell a trusted adult if you see someone being bullied.
• Help the person get away from the bullying without putting yourself at risk.
• Don't enable bullying by providing an audience.
• Set a good example by not bullying.

If you feel that you have taken all possible steps to prevent bullying and nothing has worked, or someone is in immediate danger, there are other ways for you to help. 3

Table modified from http://www.stopbullying.gov/get-help-now/index.html 3

• U.S. Department of Health and Human Services. (n.d.). Respond to bullying: Support the kids involved (Support kids who are bullied). Retrieved June 17, 2016, from http://www.stopbullying.gov/respond/support-kids-involved/index.html#support
• NICHD. (2015). Bullying: be more than a bystander (presentation). Washington, DC: U.S. Government Printing Office.
• U.S. Department of Health and Human Services. (n.d.). Get help now . Retrieved June 17, 2016, from http://www.stopbullying.gov/get-help-now/index.html

NICHD Bullying Research Goals

NICHD aims to understand the short- and long-term health effects of bullying, how the patterns of bullying have changed over time, and other information. NICHD’s research on bullying includes traditional bullying behavior (physical, verbal, and relational) as well as electronic aggression (“cyberbullying”).

Some of NICHD’s projects related to bullying include but are not limited to:

• Examining the co-occurrence of different types of bullying, including physical, verbal, social exclusion, spreading rumors, and cyberbullying, as well as their physical and psychological effects
• Determining the health and behavioral consequences of bullying, as well as the outcomes to those being bullied
• Identifying characteristics and other factors that increase a child’s risk for being bullied
• Determining the prevalence of bullying and being bullied among children from different countries and comparing rates across countries
• Identifying changes in bullying patterns and frequency over time and how these differ between and among different countries

Bullying Research Activities and Advances

NICHD supports and conducts a range of research on bullying. In addition to its own research, the Institute collaborates with other NIH Institutes and organizations to further our understanding of bullying.

Institute Activities and Advances

The following is only a summary of some of the Institute's efforts related to bullying.

Child Development & Behavior Branch (CDDB) research supports a number of projects related to bullying through its Social and Emotional Development/Child and Family Processes Program . Some of these include:

• Identifying Positive Aspects of Youth Internet Use: The Next Step in Prevention ( Michele Ybarra, Internet Solutions for Kids, Inc.)
• Social Aggression: Growth and Outcomes (Marion Underwood, University of Texas at Dallas)
• Bullying Prevention Intervention for Adolescent Primary Care Patients (Megan Ranney, Rhode Island Hospital)
• Reducing Problem Behaviors Through PYD: An RCT of Restorative School Practices (Joie Danielle Acosta, RAND Corporation)
• Development of the CABS: Child-Adolescent Bullying Screen (Judith Vessey, Boston College)

The CDBB is soliciting Small Business Innovation Research (SBIR) grants to develop and test games that address bullying and cyberbullying, such as games that raise awareness about bullying or help those being bullied cope.

Division of Intramural Population Health Research (DIPHR) research on bullying is aimed at understanding the prevalence and patterns in bullying and how they change over time. Some of the DIPHR projects related to bullying include:

• Examining cross-national health trends in children, including the prevalence of bullying
• Identifying bullying and victimization factors in school-aged children
• Characterizing the link between cyberbullying and depression in both bullies and those who are victimized by bullies

Other NICHD-supported studies include:

• Co-occurrence of victimization for several subtypes of bullying, including physical, verbal, social exclusion, rumor spreading, and cyberbullying
• Predictors of being bullied, such as weight status and race/ethnicity
• Likelihood of substance use among adolescents who have been bullied

Other Activities and Advances

• NICHD adapted materials from the stopbullying.gov website to create the "Bullying: Be More Than a Bystander" educational resource . The resource includes a presentation and facilitator's guide to educate students on how they can support someone who is being bullied.
• Research co-funded by NICHD and the National Institute of Mental Health to study the mental health effects of verbal victimization, the risk of self-harm after being bullied, and the genes that are associated with the development of emotional problems after being bullied
• Research co-funded by NICHD and the National Institute of Drug Abuse to study the effects of bullying on adolescent substance abuse
• Research co-funded by NICHD and the National Institute of Diabetes and Digestive and Kidney Diseases on sexual orientation and being bullied
• NICHD staff participated in planning the Federal Partners in Bullying Prevention Summit . Dr. Layla Esposito, director of the program on Process in Social and Emotional Development, serves on the Federal Partners in Bullying Prevention Steering Committee, an interagency effort that was launched in early 2010 to focus on the problem of bullying. Members of the committee help plan the Federal Partners in Bullying Prevention Summits.
• NICHD also participated in the Surgeon General's Workshop on Making Prevention of Child Maltreatment a National Priority: Implementing Innovations of a Public Health Approach . This workshop was convened to discover and elucidate effective strategies for preventing child maltreatment, including bullying, and promoting child well treatment.

• Research article
• Open access
• Published: 14 December 2021

Bullying at school and mental health problems among adolescents: a repeated cross-sectional study

• Håkan Källmén 1 &
• Mats Hallgren   ORCID: orcid.org/0000-0002-0599-2403 2  

Child and Adolescent Psychiatry and Mental Health volume  15 , Article number:  74 ( 2021 ) Cite this article

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To examine recent trends in bullying and mental health problems among adolescents and the association between them.

A questionnaire measuring mental health problems, bullying at school, socio-economic status, and the school environment was distributed to all secondary school students aged 15 (school-year 9) and 18 (school-year 11) in Stockholm during 2014, 2018, and 2020 (n = 32,722). Associations between bullying and mental health problems were assessed using logistic regression analyses adjusting for relevant demographic, socio-economic, and school-related factors.

The prevalence of bullying remained stable and was highest among girls in year 9; range = 4.9% to 16.9%. Mental health problems increased; range = + 1.2% (year 9 boys) to + 4.6% (year 11 girls) and were consistently higher among girls (17.2% in year 11, 2020). In adjusted models, having been bullied was detrimentally associated with mental health (OR = 2.57 [2.24–2.96]). Reports of mental health problems were four times higher among boys who had been bullied compared to those not bullied. The corresponding figure for girls was 2.4 times higher.

Conclusions

Exposure to bullying at school was associated with higher odds of mental health problems. Boys appear to be more vulnerable to the deleterious effects of bullying than girls.

Introduction

Bullying involves repeated hurtful actions between peers where an imbalance of power exists [ 1 ]. Arseneault et al. [ 2 ] conducted a review of the mental health consequences of bullying for children and adolescents and found that bullying is associated with severe symptoms of mental health problems, including self-harm and suicidality. Bullying was shown to have detrimental effects that persist into late adolescence and contribute independently to mental health problems. Updated reviews have presented evidence indicating that bullying is causative of mental illness in many adolescents [ 3 , 4 ].

There are indications that mental health problems are increasing among adolescents in some Nordic countries. Hagquist et al. [ 5 ] examined trends in mental health among Scandinavian adolescents (n = 116, 531) aged 11–15 years between 1993 and 2014. Mental health problems were operationalized as difficulty concentrating, sleep disorders, headache, stomach pain, feeling tense, sad and/or dizzy. The study revealed increasing rates of adolescent mental health problems in all four counties (Finland, Sweden, Norway, and Denmark), with Sweden experiencing the sharpest increase among older adolescents, particularly girls. Worsening adolescent mental health has also been reported in the United Kingdom. A study of 28,100 school-aged adolescents in England found that two out of five young people scored above thresholds for emotional problems, conduct problems or hyperactivity [ 6 ]. Female gender, deprivation, high needs status (educational/social), ethnic background, and older age were all associated with higher odds of experiencing mental health difficulties.

Bullying is shown to increase the risk of poor mental health and may partly explain these detrimental changes. Le et al. [ 7 ] reported an inverse association between bullying and mental health among 11–16-year-olds in Vietnam. They also found that poor mental health can make some children and adolescents more vulnerable to bullying at school. Bayer et al. [ 8 ] examined links between bullying at school and mental health among 8–9-year-old children in Australia. Those who experienced bullying more than once a week had poorer mental health than children who experienced bullying less frequently. Friendships moderated this association, such that children with more friends experienced fewer mental health problems (protective effect). Hysing et al. [ 9 ] investigated the association between experiences of bullying (as a victim or perpetrator) and mental health, sleep disorders, and school performance among 16–19 year olds from Norway (n = 10,200). Participants were categorized as victims, bullies, or bully-victims (that is, victims who also bullied others). All three categories were associated with worse mental health, school performance, and sleeping difficulties. Those who had been bullied also reported more emotional problems, while those who bullied others reported more conduct disorders [ 9 ].

As most adolescents spend a considerable amount of time at school, the school environment has been a major focus of mental health research [ 10 , 11 ]. In a recent review, Saminathen et al. [ 12 ] concluded that school is a potential protective factor against mental health problems, as it provides a socially supportive context and prepares students for higher education and employment. However, it may also be the primary setting for protracted bullying and stress [ 13 ]. Another factor associated with adolescent mental health is parental socio-economic status (SES) [ 14 ]. A systematic review indicated that lower parental SES is associated with poorer adolescent mental health [ 15 ]. However, no previous studies have examined whether SES modifies or attenuates the association between bullying and mental health. Similarly, it remains unclear whether school related factors, such as school grades and the school environment, influence the relationship between bullying and mental health. This information could help to identify those adolescents most at risk of harm from bullying.

To address these issues, we investigated the prevalence of bullying at school and mental health problems among Swedish adolescents aged 15–18 years between 2014 and 2020 using a population-based school survey. We also examined associations between bullying at school and mental health problems adjusting for relevant demographic, socioeconomic, and school-related factors. We hypothesized that: (1) bullying and adolescent mental health problems have increased over time; (2) There is an association between bullying victimization and mental health, so that mental health problems are more prevalent among those who have been victims of bullying; and (3) that school-related factors would attenuate the association between bullying and mental health.

Participants

The Stockholm school survey is completed every other year by students in lower secondary school (year 9—compulsory) and upper secondary school (year 11). The survey is mandatory for public schools, but voluntary for private schools. The purpose of the survey is to help inform decision making by local authorities that will ultimately improve students’ wellbeing. The questions relate to life circumstances, including SES, schoolwork, bullying, drug use, health, and crime. Non-completers are those who were absent from school when the survey was completed (< 5%). Response rates vary from year to year but are typically around 75%. For the current study data were available for 2014, 2018 and 2020. In 2014; 5235 boys and 5761 girls responded, in 2018; 5017 boys and 5211 girls responded, and in 2020; 5633 boys and 5865 girls responded (total n = 32,722). Data for the exposure variable, bullied at school, were missing for 4159 students, leaving 28,563 participants in the crude model. The fully adjusted model (described below) included 15,985 participants. The mean age in grade 9 was 15.3 years (SD = 0.51) and in grade 11, 17.3 years (SD = 0.61). As the data are completely anonymous, the study was exempt from ethical approval according to an earlier decision from the Ethical Review Board in Stockholm (2010-241 31-5). Details of the survey are available via a website [ 16 ], and are described in a previous paper [ 17 ].

Students completed the questionnaire during a school lesson, placed it in a sealed envelope and handed it to their teacher. Student were permitted the entire lesson (about 40 min) to complete the questionnaire and were informed that participation was voluntary (and that they were free to cancel their participation at any time without consequences). Students were also informed that the Origo Group was responsible for collection of the data on behalf of the City of Stockholm.

Study outcome

Mental health problems were assessed by using a modified version of the Psychosomatic Problem Scale [ 18 ] shown to be appropriate for children and adolescents and invariant across gender and years. The scale was later modified [ 19 ]. In the modified version, items about difficulty concentrating and feeling giddy were deleted and an item about ‘life being great to live’ was added. Seven different symptoms or problems, such as headaches, depression, feeling fear, stomach problems, difficulty sleeping, believing it’s great to live (coded negatively as seldom or rarely) and poor appetite were used. Students who responded (on a 5-point scale) that any of these problems typically occurs ‘at least once a week’ were considered as having indicators of a mental health problem. Cronbach alpha was 0.69 across the whole sample. Adding these problem areas, a total index was created from 0 to 7 mental health symptoms. Those who scored between 0 and 4 points on the total symptoms index were considered to have a low indication of mental health problems (coded as 0); those who scored between 5 and 7 symptoms were considered as likely having mental health problems (coded as 1).

Primary exposure

Experiences of bullying were measured by the following two questions: Have you felt bullied or harassed during the past school year? Have you been involved in bullying or harassing other students during this school year? Alternatives for the first question were: yes or no with several options describing how the bullying had taken place (if yes). Alternatives indicating emotional bullying were feelings of being mocked, ridiculed, socially excluded, or teased. Alternatives indicating physical bullying were being beaten, kicked, forced to do something against their will, robbed, or locked away somewhere. The response alternatives for the second question gave an estimation of how often the respondent had participated in bullying others (from once to several times a week). Combining the answers to these two questions, five different categories of bullying were identified: (1) never been bullied and never bully others; (2) victims of emotional (verbal) bullying who have never bullied others; (3) victims of physical bullying who have never bullied others; (4) victims of bullying who have also bullied others; and (5) perpetrators of bullying, but not victims. As the number of positive cases in the last three categories was low (range = 3–15 cases) bully categories 2–4 were combined into one primary exposure variable: ‘bullied at school’.

Assessment year was operationalized as the year when data was collected: 2014, 2018, and 2020. Age was operationalized as school grade 9 (15–16 years) or 11 (17–18 years). Gender was self-reported (boy or girl). The school situation To assess experiences of the school situation, students responded to 18 statements about well-being in school, participation in important school matters, perceptions of their teachers, and teaching quality. Responses were given on a four-point Likert scale ranging from ‘do not agree at all’ to ‘fully agree’. To reduce the 18-items down to their essential factors, we performed a principal axis factor analysis. Results showed that the 18 statements formed five factors which, according to the Kaiser criterion (eigen values > 1) explained 56% of the covariance in the student’s experience of the school situation. The five factors identified were: (1) Participation in school; (2) Interesting and meaningful work; (3) Feeling well at school; (4) Structured school lessons; and (5) Praise for achievements. For each factor, an index was created that was dichotomised (poor versus good circumstance) using the median-split and dummy coded with ‘good circumstance’ as reference. A description of the items included in each factor is available as Additional file 1 . Socio-economic status (SES) was assessed with three questions about the education level of the student’s mother and father (dichotomized as university degree versus not), and the amount of spending money the student typically received for entertainment each month (> SEK 1000 [approximately $120] versus less). Higher parental education and more spending money were used as reference categories. School grades in Swedish, English, and mathematics were measured separately on a 7-point scale and dichotomized as high (grades A, B, and C) versus low (grades D, E, and F). High school grades were used as the reference category.

Statistical analyses

The prevalence of mental health problems and bullying at school are presented using descriptive statistics, stratified by survey year (2014, 2018, 2020), gender, and school year (9 versus 11). As noted, we reduced the 18-item questionnaire assessing school function down to five essential factors by conducting a principal axis factor analysis (see Additional file 1 ). We then calculated the association between bullying at school (defined above) and mental health problems using multivariable logistic regression. Results are presented as odds ratios (OR) with 95% confidence intervals (Cis). To assess the contribution of SES and school-related factors to this association, three models are presented: Crude, Model 1 adjusted for demographic factors: age, gender, and assessment year; Model 2 adjusted for Model 1 plus SES (parental education and student spending money), and Model 3 adjusted for Model 2 plus school-related factors (school grades and the five factors identified in the principal factor analysis). These covariates were entered into the regression models in three blocks, where the final model represents the fully adjusted analyses. In all models, the category ‘not bullied at school’ was used as the reference. Pseudo R-square was calculated to estimate what proportion of the variance in mental health problems was explained by each model. Unlike the R-square statistic derived from linear regression, the Pseudo R-square statistic derived from logistic regression gives an indicator of the explained variance, as opposed to an exact estimate, and is considered informative in identifying the relative contribution of each model to the outcome [ 20 ]. All analyses were performed using SPSS v. 26.0.

Prevalence of bullying at school and mental health problems

Estimates of the prevalence of bullying at school and mental health problems across the 12 strata of data (3 years × 2 school grades × 2 genders) are shown in Table 1 . The prevalence of bullying at school increased minimally (< 1%) between 2014 and 2020, except among girls in grade 11 (2.5% increase). Mental health problems increased between 2014 and 2020 (range = 1.2% [boys in year 11] to 4.6% [girls in year 11]); were three to four times more prevalent among girls (range = 11.6% to 17.2%) compared to boys (range = 2.6% to 4.9%); and were more prevalent among older adolescents compared to younger adolescents (range = 1% to 3.1% higher). Pooling all data, reports of mental health problems were four times more prevalent among boys who had been victims of bullying compared to those who reported no experiences with bullying. The corresponding figure for girls was two and a half times as prevalent.

Associations between bullying at school and mental health problems

Table 2 shows the association between bullying at school and mental health problems after adjustment for relevant covariates. Demographic factors, including female gender (OR = 3.87; CI 3.48–4.29), older age (OR = 1.38, CI 1.26–1.50), and more recent assessment year (OR = 1.18, CI 1.13–1.25) were associated with higher odds of mental health problems. In Model 2, none of the included SES variables (parental education and student spending money) were associated with mental health problems. In Model 3 (fully adjusted), the following school-related factors were associated with higher odds of mental health problems: lower grades in Swedish (OR = 1.42, CI 1.22–1.67); uninteresting or meaningless schoolwork (OR = 2.44, CI 2.13–2.78); feeling unwell at school (OR = 1.64, CI 1.34–1.85); unstructured school lessons (OR = 1.31, CI = 1.16–1.47); and no praise for achievements (OR = 1.19, CI 1.06–1.34). After adjustment for all covariates, being bullied at school remained associated with higher odds of mental health problems (OR = 2.57; CI 2.24–2.96). Demographic and school-related factors explained 12% and 6% of the variance in mental health problems, respectively (Pseudo R-Square). The inclusion of socioeconomic factors did not alter the variance explained.

Our findings indicate that mental health problems increased among Swedish adolescents between 2014 and 2020, while the prevalence of bullying at school remained stable (< 1% increase), except among girls in year 11, where the prevalence increased by 2.5%. As previously reported [ 5 , 6 ], mental health problems were more common among girls and older adolescents. These findings align with previous studies showing that adolescents who are bullied at school are more likely to experience mental health problems compared to those who are not bullied [ 3 , 4 , 9 ]. This detrimental relationship was observed after adjustment for school-related factors shown to be associated with adolescent mental health [ 10 ].

A novel finding was that boys who had been bullied at school reported a four-times higher prevalence of mental health problems compared to non-bullied boys. The corresponding figure for girls was 2.5 times higher for those who were bullied compared to non-bullied girls, which could indicate that boys are more vulnerable to the deleterious effects of bullying than girls. Alternatively, it may indicate that boys are (on average) bullied more frequently or more intensely than girls, leading to worse mental health. Social support could also play a role; adolescent girls often have stronger social networks than boys and could be more inclined to voice concerns about bullying to significant others, who in turn may offer supports which are protective [ 21 ]. Related studies partly confirm this speculative explanation. An Estonian study involving 2048 children and adolescents aged 10–16 years found that, compared to girls, boys who had been bullied were more likely to report severe distress, measured by poor mental health and feelings of hopelessness [ 22 ].

Other studies suggest that heritable traits, such as the tendency to internalize problems and having low self-esteem are associated with being a bully-victim [ 23 ]. Genetics are understood to explain a large proportion of bullying-related behaviors among adolescents. A study from the Netherlands involving 8215 primary school children found that genetics explained approximately 65% of the risk of being a bully-victim [ 24 ]. This proportion was similar for boys and girls. Higher than average body mass index (BMI) is another recognized risk factor [ 25 ]. A recent Australian trial involving 13 schools and 1087 students (mean age = 13 years) targeted adolescents with high-risk personality traits (hopelessness, anxiety sensitivity, impulsivity, sensation seeking) to reduce bullying at school; both as victims and perpetrators [ 26 ]. There was no significant intervention effect for bullying victimization or perpetration in the total sample. In a secondary analysis, compared to the control schools, intervention school students showed greater reductions in victimization, suicidal ideation, and emotional symptoms. These findings potentially support targeting high-risk personality traits in bullying prevention [ 26 ].

The relative stability of bullying at school between 2014 and 2020 suggests that other factors may better explain the increase in mental health problems seen here. Many factors could be contributing to these changes, including the increasingly competitive labour market, higher demands for education, and the rapid expansion of social media [ 19 , 27 , 28 ]. A recent Swedish study involving 29,199 students aged between 11 and 16 years found that the effects of school stress on psychosomatic symptoms have become stronger over time (1993–2017) and have increased more among girls than among boys [ 10 ]. Research is needed examining possible gender differences in perceived school stress and how these differences moderate associations between bullying and mental health.

Strengths and limitations

Strengths of the current study include the large participant sample from diverse schools; public and private, theoretical and practical orientations. The survey included items measuring diverse aspects of the school environment; factors previously linked to adolescent mental health but rarely included as covariates in studies of bullying and mental health. Some limitations are also acknowledged. These data are cross-sectional which means that the direction of the associations cannot be determined. Moreover, all the variables measured were self-reported. Previous studies indicate that students tend to under-report bullying and mental health problems [ 29 ]; thus, our results may underestimate the prevalence of these behaviors.

In conclusion, consistent with our stated hypotheses, we observed an increase in self-reported mental health problems among Swedish adolescents, and a detrimental association between bullying at school and mental health problems. Although bullying at school does not appear to be the primary explanation for these changes, bullying was detrimentally associated with mental health after adjustment for relevant demographic, socio-economic, and school-related factors, confirming our third hypothesis. The finding that boys are potentially more vulnerable than girls to the deleterious effects of bullying should be replicated in future studies, and the mechanisms investigated. Future studies should examine the longitudinal association between bullying and mental health, including which factors mediate/moderate this relationship. Epigenetic studies are also required to better understand the complex interaction between environmental and biological risk factors for adolescent mental health [ 24 ].

Availability of data and materials

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HK conceived the study and analyzed the data (with input from MH). HK and MH interpreted the data and jointly wrote the manuscript. All authors read and approved the final manuscript.

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Källmén, H., Hallgren, M. Bullying at school and mental health problems among adolescents: a repeated cross-sectional study. Child Adolesc Psychiatry Ment Health 15 , 74 (2021). https://doi.org/10.1186/s13034-021-00425-y

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Committee on the Biological and Psychosocial Effects of Peer Victimization: Lessons for Bullying Prevention; Board on Children, Youth, and Families; Committee on Law and Justice; Division of Behavioral and Social Sciences and Education; Health and Medicine Division; National Academies of Sciences, Engineering, and Medicine; Rivara F, Le Menestrel S, editors. Preventing Bullying Through Science, Policy, and Practice. Washington (DC): National Academies Press (US); 2016 Sep 14.

Preventing Bullying Through Science, Policy, and Practice.

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5 Preventive Interventions

The research on bullying prevention programming has increased considerably over the past 2 decades, which is likely due in part to the growing awareness of bullying as a public health problem that impacts individual youth as well as the broader social environment. Furthermore, the enactment of bullying-related laws and policies in all 50 states has drawn increased focus on prevention programming. In fact, many state policies require some type of professional development for staff or prevention programming related to bullying ( Hatzenbuehler et al., 2015 ; Stuart-Cassel et al., 2011 ). Despite this growing interest in and demand for bullying prevention programming, there have been relatively few randomized controlled trials (RCTs) testing the efficacy or effectiveness of programs specifically designed to reduce or prevent the onset of bullying or offset its consequences on children and youth ( Bradshaw, 2015 ; Jiménez-Barbero et al. 2016 ). Moreover, the much larger body and longer line of research focused on aggression, violence, and delinquency prevention has only recently begun to explore program impacts specific to bullying. The focus of that research has typically been on broader concepts, such as aggression, violence, delinquency, externalizing problems, etc. Therefore, it is quite possible that there are several violence or aggression prevention programs that have substantial effects on bullying, but there is currently too little data available from most violence prevention studies that employ RCT designs to formulate a conclusion regarding impacts on bullying specifically ( Bradshaw, 2015 ).

In this chapter, the committee summarizes the current status of bullying prevention programming, while acknowledging both gaps in the extant literature and opportunities for future research. The committee first focuses more narrowly on bullying prevention and intervention programming for which there are data specifically on bullying behaviors; greater emphasis is placed on RCTs, as compared to nonexperimental, correlational, or descriptive studies. The committee then considers the broader literature on other youth-focused violence prevention and intervention programming, with particular attention to potential conceptual or measurement overlap with bullying, since such models may hold promise for reducing rates or effects of bullying ( Bradshaw, 2015 ; Hawkins et al. 2015 ). Although the committee was intentionally inclusive of the larger body of prevention programming literature, it acknowledges the caveats of such a broad focus, as findings from other violence prevention programs may not always generalize to bullying-specific outcomes (e.g., Espelage et al., 2013 ). Nevertheless, this review is not intended to be an exhaustive list of all evidence-based approaches to bullying or youth violence prevention; rather, the committee highlights particular models and frameworks for which there is a strong or emerging line of RCT studies suggesting promise for preventing or offsetting the consequences of bullying.

In an effort to organize the vast and somewhat disparate lines of prevention literature, the committee adopted the National Research Council's public health model of mental health intervention ( Institute of Medicine, 1994 ) as a framework for conceptualizing the various programs and models across increasing levels of intensity (see Figure 5-1 ).

Mental health intervention spectrum. SOURCE: Adapted from Institute of Medicine (1994, Fig. 2.1, p. 23).

This model includes three levels of prevention programming (i.e., universal, selective, and indicated), which are preceded by promotion-focused programming and followed by treatment and maintenance ( National Research Council and Institute of Medicine, 2009 ). Mental health promotion has been recognized as a key component of the mental health intervention continuum ( National Research Council and Institute of Medicine, 2009 ). Although prevention programming can occur in multiple settings and ecological contexts (see Figure 5-2 ; also Espelage and Swearer, 2004 ; Swearer et al., 2010 ; Weisz et al., 2005 ), the majority of research has been conducted within schools. As a result, the committee made an effort to also provide examples of programs that occur in settings other than school, even when the literature base was thinner as it relates to bullying-specific programming and/or outcomes. After summarizing various research-based prevention frameworks and programs, the committee concludes by highlighting lessons learned from the extant research as it relates to critical features of bullying prevention programming and identifying future research directions related to bullying prevention programming.

An ecodevelopmental model of prevention. SOURCE: Adapted from National Research Council and Institute of Medicine (2009, Fig. 4-1, p. 73).

• MULTI-TIERED PREVENTION FRAMEWORK

An increasingly common approach to the prevention of emotional and behavioral disorders is the three-tiered public health model that includes universal, selective, and indicated preventive interventions, as illustrated in Figure 5-1 ( Institute of Medicine, 1994 ; National Research Council and Institute of Medicine, 2009 ; Weisz et al., 2005 ). Similar frameworks have been proposed or articulated to conceptualize a multi-tiered system of supports (for a review, see Batsche, 2014 ). Although this continuum of preventive interventions can be applied to many behavioral, educational, mental health, and physical health problems, this report considers it primarily through the lens of bullying prevention among youth.

The Three Tiers

Specifically, universal prevention programs are aimed at reducing risks and strengthening skills for all youth within a defined community or school setting. Through universal programs, all members of the target population are exposed to the intervention regardless of risk for bullying. Using universal prevention approaches, a set of activities may be established that offers benefits to all individuals within that setting (e.g., school). Examples of universal or Tier 1 preventive interventions include social-emotional lessons that are used in the classroom, behavioral expectations taught by teachers, counselors coming into the classroom to model strategies for responding to or reporting bullying, and holding classroom meetings among students and teachers to discuss emotionally relevant issues related to bullying or equity. Universal interventions could also include guidelines for the use of digital media, such as youth's use of social network sites.

Most of the bullying prevention programs that have been evaluated with RCT designs have employed a universal approach to prevention ( Ttofi and Farrington, 2011 ; Jiménez Barbero et al., 2016 ). Although universal bullying prevention programs are typically aimed at having effects on youth, they may also yield benefits for the individuals implementing the programs. For example, recent findings from a RCT of a social–emotional learning and behavior management program indicated that the program substantially affected the teachers who implemented the program, as well as affecting the students ( Domitrovich et al., 2016 ). Similarly positive effects were observed in a randomized trial of a schoolwide Positive Behavior Support model, where implementation of the model demonstrated significant impacts on the staff members' perceptions of school climate ( Bradshaw et al., 2009a ). Consistent with the social-ecological model, these effects may be either direct—through the professional development provided to the teachers—or indirect through the improved behavior and enhanced organizational context of the setting in which the program is implemented. These types of secondary impacts on the broader school or community environment also likely occur in universal bullying prevention programs, many of which are intended to reduce bullying in conjunction with improving school climate ( Bradshaw, 2013 ).

Most school-based bullying prevention programs would fall under the universal category of largely preventive interventions, with limited articulation of specific programs, activities, or supports for students not responding adequately to the universal model. Even if the programs focus on the whole school or climate/culture changes, they often take the perspective that a universal approach is the most important and potentially most effective intervention because all children can benefit from attempts to enhance school climate, change attitudes or awareness about bullying, reduce aggressive behavior, or improve related social skills or behavior. Furthermore, some universal programs follow the assumption that all students are considered to be at risk at some level for bullying behavior, either as perpetrators, targets, or bystanders ( Rigby and Slee, 2008 ). In fact, there is a growing recognition that universal prevention programs do not equally benefit all individuals; rather, evidence is emerging that universal prevention programs may actually be more effective for higher risk students than those traditionally conceptualized as low risk ( Bradshaw et al., 2015 ; Eron et al., 2002 ; Kellam et al., 1994 ). As a result, there is a growing trend in prevention research to explicitly examine variation in responsiveness to universal prevention programs in order to better understand which youth may be most affected by a particular model ( Kellam et al., 1994 ; Lanza and Rhoades, 2013 ). This may also improve understanding of why some effect sizes of universal prevention programs are relatively modest when they are averaged across a large population, as a broader population may have a relatively low base rate for engaging in the behavior ( Biglan et al., 2015 ). On the other hand, investing in prevention on a national level has the potential to produce significant and meaningful behavior change for larger populations of youth across a broad array of outcomes, not just outcomes related to bullying behavior ( Biglan et al., 2015 ; Institute of Medicine and National Research Council, 2015 ).

The next level of the tiered prevention model is referred to as selective preventive interventions. These may either target youth who are at risk for engaging in bullying or target youth at risk of being bullied. Such programs may include more intensive social-emotional skills training, coping skills, or de-escalation approaches for youth who are involved in bullying. Consistent with a response-to-intervention framework, these Tier 2 approaches are employed to meet the needs of youth who have not responded adequately to the universal preventive intervention ( National Research Council and Institute of Medicine, 2009 ).

The third tier includes indicated preventive interventions , which are typically tailored to meet the youth's needs and are of greater intensity as compared to the two previous levels of prevention. Indicated interventions incorporate more intensive supports and activities for those who are already displaying bullying behavior or have a history of being bullied and are showing early signs of behavioral, academic, or mental health consequences. The supports are usually tailored to meet the needs of the students demonstrating negative effects of bullying ( Espelage and Swearer, 2008 ); they typically address mental and behavioral health concerns, often by including the youth's family. Such programs may also leverage expertise and involvement of teachers, education support professionals, school resource officers, families, health care professionals, and community members, thereby attempting to support the participating youth across multiple ecological levels. While a number of selective and indicated programs have demonstrated efficacy for a range of youth behavioral and mental health problems (for a review see National Research Council and Institute of Medicine, 2009 ), there has been considerably less research on selective and indicated prevention programs specific to bullying ( Swearer et al., 2014 ).

Integrating Prevention Programs across the Tiers

Consistent with the public health approach to prevention ( National Research Council and Institute of Medicine, 2009 ) and calls for multi-tier or multidisciplinary approaches to prevention, there is an increasing interest in layering components “on top of” or in combination with the universal intervention to address factors that may place youth at risk for being targets or perpetrators of bullying (universal plus targeted interventions). These combined programs often attempt to address at the universal level such factors as social skill development, social-emotional learning or self-regulation, which are intended to also reduce the chances that youth would engage in bullying or reduce the risk of further being bullied ( Bradshaw, 2013 , 2015 ; Merrell et al., 2008 ; Ttofi and Farrington, 2011 ; Vreeman and Carroll, 2007 ). These combined programs are often characterized as universal, whole school, or climate/culture changing programs that may have additional “benefits” for perpetrators or targets (e.g., help them be more effective in coping with the stress of bullying). However, few have easily identifiable components that specifically target youth at risk for involvement in bullying behavior or those already identified as perpetrators or targets. Therefore much of what is currently known about bullying prevention derives from studies of universal programs, with limited research on selective and indicated models for prevention.

Current research is limited in its ability to specifically tease out the effects of targeted elements embedded in whole-school universal programs ( Bradshaw, 2015 ; Ttofi and Farrington, 2011 ). For example, evaluators have not been able to assess whether it is the universal or targeted components (or the combination of the two) that leads to reductions in bullying behavior or improvements in social-emotional skills ( Ttofi and Farrington, 2011 ). In fact, few of the truly multi-tiered programs have been evaluated using randomized, controlled esperimental designs to determine whether they are effective or lead to sustained behavior change. Moreover, once a child or youth is identified as a target or a perpetrator of bullying, the individual is often referred to mental health or behavioral health services providers in the community—in part because few school-based mental health professionals are available to provide these specialized services ( Swearer et al., 2014 ).

In summary, despite calls for a layered public health approach to bullying prevention or calls for multicomponent, multilevel programs ( Leff and Waasdorp, 2013 ), few studies of school-based bullying prevention programs have simultaneously evaluated both universal and targeted components ( Bradshaw, 2015 ). Although many researchers encourage the use of a multi-tiered approach to address bullying, and there is conceptual research supporting the full integration of preventive interventions ( Bradshaw, 2013 , 2015 ; Espelage and Swearer, 2008 ; Hawley and Williford, 2015 ; Hong and Espelage, 2012 ; Swearer et al., 2012 ), relatively few large-scale RCT studies have examined the combined and tier-specific effects of multi-tiered programs on bullying. Yet, integrating the nested levels of support into a coherent, tiered framework could also reduce burden and increase efficiency of implementation ( Bradshaw et al., 2014a ; Domitrovich et al., 2010 ; Sugai and Horner, 2006 ).

Perspectives from the Field

Treatments could be better integrated: We could be doing more to integrate social services in schools with medical treatments, and we could also foster stronger relationships with varying organizations so we can make better referrals. Behavioral health counselors embedded in the school district as satellite offices could be helpful, particularly when they can work with pediatricians. Access to care is immensely important, as is supporting people in getting that access (particularly in seeking access without having to worry about stigma). Everyone needs to work together as a team with their own place on the pathway to preventing bullying. Another thing we've thought of is having mental health professionals in the room during pediatric visits to talk to the parent and conduct pre-screening.

—Summary from community-based providers focus group (See Appendix B for additional highlights from interviews.)

• PREVENTION PROGRAMS SPECIFICALLY IMPLEMENTED TO REDUCE BULLYING AND RELATED BEHAVIOR PROBLEMS

The sections that follow focus on the available efficacy and effectiveness research that has examined different bullying prevention programs, the vast majority of which have been implemented at the universal level and within schools. The committee first considers the evidence for the effectiveness of universal programs, many of which are whole-school efforts that may include some elements directed to youth at risk for bullying or those already engaged in bullying behaviors. 1 The committee also reviews the effectiveness of specific selective or indicated prevention programs, many of which were designed more broadly for youth with behavioral or mental health problems, rather than specifically for bullying.

The committee considered the broader literature on programs aimed at reducing youth aggressive behavior and those aimed at improving emotional and behavioral problems among youth. While most of these programs were not originally developed to address bullying behavior specifically, one may still learn much from them about means to reduce bullying-related behavior, or they may provide clues about how to improve resilience, social competence, or problem-solving skills that may lead to reductions in bullying perpetration or being bullied. In some instances, the committee has drawn upon literature from related fields, such as trauma exposure or research on how families can promote emotional resilience to being a target of bullying ( Bowes et al., 2010 ). Few of these studies, however, have assessed or examined the impact of these interventions on behaviors specific to bullying. Rather, they may assess behaviors such as fighting, threats, violence, aggressive, or delinquent behavior. If one takes the position that most bullying can be characterized as aggressive behavior but not all aggressive or violent behavior meets the narrower definition of bullying ( Farrington and Ttofi, 2011 ; Finkelhor et al., 2012 ; Leff and Waasdorp, 2013 ), then perhaps there are lessons to learn from interventions that have shown reductions in aggression and violence or improvements in social skills, even if bullying behavior was not the primary focus of the intervention. The same thinking applies to studies of peer victimization in that while being bullied may be characterized as a form of victimization, not all victimization by peers would be characterized as bullying, particularly with respect to the criteria of repeated targeting or a power imbalance ( Finkelhor et al., 2012 ).

We should pay attention to the bully, too: Appropriate consequences for bullying should happen, including punishment, but we also need to ask what kids are going through that makes them want to bully. We need to actually talk to everyone, not accepting bullying but accepting that everyone is going through their own challenges and has their own needs. Bullies should be part of the solution and should not be isolated or ignored.

—Summary from community-based providers and young adults focus groups discussing bullying

“Before you get angry, before you think of all the mean things you could say, just take time, take a breath, and think about what they're thinking. And that's how you solve it, that's how you help the bully. You ask them about it.”

—Quote from a young adult in a focus group discussing bullying (See Appendix B for additional highlights from interviews.)

Another reason the committee has considered the broader violenceprevention literature is that bullying often co-occurs with other behavioral and mental health problems, including aggression and delinquent behaviors ( Bradshaw et al., 2013a ; Swearer et al., 2012 ), and the risk factors targeted through preventive interventions are often interrelated. For example, aggressive youth are more likely to be rejected by their peers, to have associated academic problems ( Nansel et al., 2003 ), or to experience higher rates of family discord or maltreatment ( Shields and Cicchetti, 2001 ). Further, many preventive interventions seek to enhance positive or prosocial behaviors or improve social competence, in addition to reducing negative behaviors such as aggression and fighting ( Embry et al., 1996 ; Flannery et al., 2003 ).

For example, a meta-analysis of school-based mental health promotion programs found that they can improve social-emotional skills, prosocial norms, school bonding, and positive social behavior, as well as result in reduced problem behaviors, such as aggression, substance use, and internalizing symptoms ( Durlak et al., 2007 ; Durlak et al., 2011 ). An improvement in competence and social problem-solving skills may lead to reductions in bullying perpetration even if that was not the intended outcome of the intervention. Other studies have demonstrated improvements in youth coping skills and stress management ( Kraag et al., 2006 ), which can be helpful to children who are bullied even if such children were not the original population targeted by the intervention. In summary, many school and community-based programs were not originally designed to specifically reduce bullying, but because they target related behaviors, they may provide valuable lessons that can inform efforts related to bullying prevention.

Summary of the Available Meta-Analyses

A number of recent meta-analyses have been conducted in an effort to identify the most effective and promising approaches within the field of bullying prevention; for a review of the meta-analyses see Ttofi and colleagues (2014) . The most comprehensive review conducted to date was by Ttofi and Farrington (2011) , who applied the Campbell Systematic Review procedures in reviewing 44 rigorous program evaluations and RCTs. The majority of these studies were conducted outside the United States or Canada (66%), and over a third of the programs were based in part on the work of Olweus (1993) . Ttofi and Farrington (2011) found that the programs, on average, were associated with a 20-23 percent decrease in perpetration of bullying, and a 17-20 percent decrease in being bullied, as illustrated in Figures 5-3 and 5-4 . 2

Forest graph showing the measure of program effect sizes in logarithm of odds ratio (LOR) for bullying perpetration. SOURCE: Ttofi and Farrington (2011, Fig. 1, p. 38).

Forest graph showing the measure of program effect sizes in logarithm of odds ratio (LOR) for victimization. SOURCE: Ttofi and Farrington (2011, Fig. 2, p. 39).

As in other reviews and meta-analyses ( Bradshaw, 2015 ; Leff and Waasdorp, 2013 ), Farrington and Ttofi (2009) concluded that in general the most effective programs are multicomponent, schoolwide programs that reduce bullying and aggression across a variety of settings. However, as noted previously, these multicomponent programs are not always multi-tiered in the context of the public health model; rather, they may have multiple complementary program elements that all focus on universal prevention, such as a combination of a whole-school climate strategy coupled with a curriculum to prevent bullying or related behaviors. Furthermore, the designs of the studies precluded the researchers from isolating which program elements accounted for the program impacts. Nevertheless, Farrington and Ttofi (2009) concluded that parent training, improved playground supervision, disciplinary methods, school conferences, videos, information for parents, classroom rules, and classroom management were program components associated with a decrease in students being bullied.

The whole-school bullying prevention programs (mostly based on or modeled after the extensively studied Olweus Bullying Prevention Program model, which aims at reducing bullying through components at multiple levels) also generally demonstrated positive effects, particularly in schools with more positive student-teacher relationships ( Richard et al., 2012 ). In general, significant intervention effects have been demonstrated more often for programs implemented in Europe ( Richard et al., 2012 ) and Scandinavian countries ( Farrington and Ttofi, 2009 ; Salmivalli, 2010 ) than in the United States (also see Bradshaw, 2015 ). Some researchers and practitioners have suggested that interventions implemented outside the United States may be more successful because they involve more homogeneous student samples in schools that are more committed to implementing programs as intended ( Evans et al., 2014 ), compared with student samples and schools' commitment in the United States. Competing demands on student and teacher time, such as standardized testing, also limit U.S. teachers' perceived ability to focus on social-emotional and behavioral activities, as compared with traditional academic content. The challenges in designing and delivering effective bullying prevention programs in the United States may also include the greater social and economic complexities of U.S. school populations, including greater income disparities and racial/ethnic heterogeneity.

The meta-analyses, most notably the Ttofi and Farrington (2011) review, noted variation in program effects based on study design, as has been shown for most such intervention programs. For example, large-scale effectiveness studies (i.e., studies of taking an intervention program to scale) did not produce effects as strong as those in more tightly controlled efficacy studies, where the program is often administered with greater support and researcher influence ( Bradshaw, 2015 ; Ttofi and Farrington, 2011 ). Similarly, the effects generally were stronger in the non-RCT designs than in the RCTs, suggesting that the more rigorous the study design, the smaller the effect sizes ( Farrington and Ttofi, 2009 ). Moreover, as has been shown in several other studies across multiple fields (e.g., Domitrovich et al., 2008 ), poor implementation fidelity has been linked with weaker program outcomes (also see Durlak et al., 2011 ).

Another important finding from the Ttofi and Farrington review was that, generally speaking, there are more school-based bullying prevention programs that involve middle-school youth than those that target youth of high school age. Of the programs that have been evaluated with RCT designs, the observed effects were generally larger for older youth (ages 11-14) than for younger children (younger than age 10) ( Farrington and Ttofi, 2009 ; Ttofi and Farrington, 2011 ). However, this effect has not been consistent across all programs and all studies, as there is compelling developmental research suggesting that the earlier one intervenes to prevent behavior problems, the more effective the intervention is ( Kellam et al., 1994 ; Waasdorp et al., 2012 ). Unpacking this finding is likely to be complicated because different programs are often used at different age ranges, thereby confounding the child's age with the program used. However, more recently, some programs that were originally developed for a particular age group have been adapted for youth of a different age range (e.g., Promoting Alternative Thinking Strategies, Second Step, Coping Power; Olweus Bullying Prevention Program). Implementations of these programs span multiple age groups, with specific curricular or program activities that are developmentally appropriate for the target population (e.g., to address different developmental needs for a third grader than for an eighth grader).

Other meta-analyses of school-based bullying intervention programs have not been as positive as the Ttofi and Farrington (2011) review (e.g., Merrell et al., 2008 ; Vreeman and Carroll, 2007 ). Some of these mixed findings may be due to different inclusion criteria, such as where the study was conducted (e.g., in the United States or Europe) or who conducted it (i.e., the program developer or an external evaluator). For example, Merrell and colleagues (2008) reviewed 16 studies of over 15,386 kindergarten through grade 12 (K-12) students in six different countries from 1980 through 2004. They concluded that the majority of outcomes were neither positive nor negative and generally lacked statistical significance one way or the other (they found a meaningful positive average effect on bullying for about one-third of all outcomes). They further concluded that programs are much more likely to show effects on attitudes, self-perceptions, and knowledge than on bullying behavior. Only one of the reviewed studies specifically included an intervention for at-risk students; a program that assigned social workers to the primary school building to work with students at risk for perpetrating or being targets of bullying ( Bagley and Pritchard, 1998 ). Bagley and Pritchard (1998) assessed student self-reports of bullying incidents and showed significant declines in bullying among students who received intervention services from social workers. Merrell and his colleagues (2008) did not weight the 16 studies in the meta-analysis for sample size, degree of experimental rigor, or threats to validity when they computed effect sizes within the individual research studies. Overall, however, they concluded that while some intervention studies had positive outcomes, these were mostly for attitudes and knowledge rather than improving (lessening the frequency of) youth self-reports of being perpetrators or targets of bullying ( Merrell et al., 2008 ; Smith et al., 2004 ).

Vreeman and Carroll (2007) also conducted a systematic review of bullying preventive interventions, some of which combined programs across the tiers. They found that whole-school approaches with teacher training or individual counseling did better than curricular-only approaches. Of the 26 studies that met their inclusion criteria, only four included targeted interventions involving social and behavioral skills groups for children involved in bullying as perpetrators ( Fast et al., 2003 ; Meyer and Lesch, 2000 ) and two targeted youth who were victims of bullying ( DeRosier, 2004 ; Tierney and Dowd, 2000 ). According to Vreeman and Carroll (2007) , three of the four studies focused on youth in middle school (sixth through eighth grade) and one examined third grade students. The only social skills training intervention that showed clear reductions in bullying was the study of third grade students. The other three studies of older youth produced mixed results.

Another more recent meta-analysis of bullying prevention programs by Jiménez-Barbero and colleagues (2016) examined a range of effects of 14 “anti-bullying” programs tested through RCTs, comprising 30,934 adolescents ages 10-16. All studies were published between 2000 and 2013. They examined not only bullying frequency (ES = 0.12) and victimization frequency (ES = 0.09), but also attitudes favoring bullying or school violence (ES = 0.18), attitudes against bullying or school violence (ES = 0.06), and school climate (ES = 0.03). See details of the individual studies below in Figure 5-5 . This study was considerably smaller in scale than the Ttofi and Farrington (2011) meta-analysis, in large part because of stricter inclusion criteria. Furthermore, on average, these effect sizes were smaller than observed in the Ttofi and Farrington (2011) study. Because of the smaller sample size, it is difficult to formulate conclusions based on specific components (e.g., family, teacher) or youth subgroups (e.g., age of students). Taken together, the meta-analyses provide evidence that the effect sizes of universal programs are relatively modest. Yet these effects are averaged across a full population of youth; selective and indicated prevention approaches, which focus on youth more directly involved in bullying, will likely yield larger effect sizes, as has been seen in other studies of violence prevention programming (discussed later in this chapter).

Effect size for each outcome measurement. NOTE: For additional details about study design, population, measurement, variables included in analyses, etc., please refer to the original studies. SOURCE: Adapted from Jiménez-Barbero et al. (2016, (more...)

In contrast to the somewhat mixed findings on interventions specifically for bullying prevention, the larger body of universal youth violence prevention programming has generally had more favorable results, particularly for preschool and elementary school children ( Sawyer et al., 2015 ; Wilson and Lipsey, 2007 ). Systematic reviews and meta-analyses of school-based violence prevention programs (most that did not specifically address bullying behaviors) have shown many to be effective at reducing aggressive behavior and violence ( Botvin et al., 2006 ; Durlak et al., 2011 ; Hahn et al., 2007 ; Mytton et al., 2002 ). Whereas some of the reviews of programs focused on bullying have reported greater effects for older students in middle or secondary schools versus students in primary schools ( Mytton et al., 2002 ; Ttofi and Farrington, 2011 ), the programs focused on aggression and social competence have shown greater effects for younger children ( Kärnä et al., 2011a ). One factor may be variations in focus, such as reviews that cover secondary prevention trials for those at risk for aggression and violence ( Mytton et al., 2002 ) versus reviews that include universal and whole school violence prevention programs ( Hahn et al., 2007 ). For example, a review of violence prevention programs by Limbos and colleagues (2007) found that about one-half of 41 intervention studies showed positive effects, with indicated interventions for youth already engaged in violent behavior being more effective than universal or selective interventions.

Another comprehensive meta-review of 25 years of meta-analyses and systematic reviews of youth violence prevention programs concluded that most interventions demonstrate moderate program effects, with programs targeting family factors showing marginally larger effects compared to those that did not ( Matjasko et al., 2012 ). Strength of evidence was rated as small, moderate, or strong by the authors using data on reported effect sizes. This meta-review suggested that studies consistently reported larger effect sizes for reduction of youth violent behavior for programs that targeted selected and indicated populations of youth versus universal prevention. The authors also found that programs with a cognitive-behavioral component tended to have larger effect sizes than those without that component or with only a behavioral component ( Matjasko et al., 2012 ). These findings are generally consistent with a recent meta-analysis by Barnes and colleagues (2014) , who found that school-based cognitive behavioral interventions were effective (mean ES = −0.23) on reducing aggressive behavior, especially those delivered universally compared with those provided in small group settings ( Barnes et al., 2014 ).

Examples of Universal Multicomponent Prevention Programs to Address Bullying or Related Behavior

As noted above, many schoolwide bullying prevention programs include multiple components, both within and across the three prevention tiers. One such program is the Olweus Bullying Prevention Program ( Olweus, 2005 ), which is also the most extensively studied bullying prevention program. It aims to reduce bullying through components at multiple levels, including schoolwide components; classroom activities and meetings; targeted interventions for individuals identified as perpetrators or targets; and activities aimed to increase involvement by parents, mental health workers, and others. Some studies of the Olweus Bullying Prevention Program have reported significant reductions in students' reports of bullying and antisocial behaviors (e.g., fighting, truancy) and improvements in school climate ( Olweus et al., 1999 ). However, some smaller-scale studies of this model produced mixed results (e.g., Hanewinkel, 2004 ). Although other derivations of Olweus's model also have demonstrated promise at reducing bullying in North America (e.g., Pepler et al., 2004 ), these programs were generally more effective in Europe. Farrington and Ttofi (2009) found that programs that were conceptually based on the Olweus Bullying Prevention Program were the most effective, compared to the other programs examined ( OR = 1.50 versus OR = 1.31, p = .011).

Another multicomponent and multi-tiered prevention model is Positive Behavioral Interventions and Supports (PBIS) ( Sugai and Horner, 2006 ; see also Walker et al., 1996 ). PBIS aims to prevent disruptive behaviors and promote a positive school climate through setting-level change, in order to prevent student behavior problems systematically and consistently. The model draws upon behavioral, social learning, organizational, and positive youth development theories and promotes strategies that can be used by all staff consistently across all school contexts ( Lewis and Sugai, 1999 ; Lindsley, 1992 ; Sugai et al., 2002 ). Through PBIS, staff and students work together to create a schoolwide program that clearly articulates positive behavioral expectations, provides incentives to students meeting these expectations, promotes positive student-staff interactions, and encourages data-based decision making by staff and administrators. The model aims to alter the school environment by creating both improved systems (e.g., discipline, reinforcement, and data management systems) and procedures (e.g., collection of office referral data, training, data-based decision making) in order to promote positive change in student and teacher behaviors ( Kutash et al., 2006 ; Sugai and Horner, 2006 ). The PBIS model also emphasizes coaching to tailor the implementation process to fit the culture and context of the school. The PBIS framework acknowledges that there is no one-size-fits-all program or model, therefore, coaches work with the schools to collect data in order to identify needs and both local challenges and resources. They subsequently help the school choose the most suitable program to be integrated within the PBIS framework, and they provide support to staff to optimize implementation fidelity.

The PBIS model follows a multi-tiered prevention approach ( Institute of Medicine, 1994 ; National Research Council and Institute of Medicine, 2009 ), whereby Tier 2 (selective/targeted) and Tier 3 (indicated) programs and supports are implemented to complement the Tier 1 (universal) components ( Sugai and Horner, 2006 ; Walker et al., 1996 ). Recent randomized effectiveness trials of PBIS, largely focused on the universal, Tier 1 elements, have reported significant effects on bullying and peer rejection (effect sizes ranging from 0.11 to 0.14; see Bradshaw, 2015 ; Waasdorp et al., 2012 ), as well as school climate (effect sizes from 0.16 to 0.29; see Bradshaw et al., 2008 ; Horner et al., 2009 ), and discipline problems (effect sizes from 0.11 to 0.27; see Bradshaw et al., 2010 , 2012 , 2015 ). Other significant effects have been reductions in suspensions and office referrals (ES = 0.27; see Bradshaw et al., 2008 , 2009a , 2010 ; Horner et al., 2009 ; Waasdorp et al., 2012 ). Another randomized trial of PBIS combining Tier 1 and 2 supports in elementary schools also demonstrated significant improvements, relative to Tier 1 only, on teacher and student behaviors such as special education usage, need for advanced tier supports, and teacher efficacy to manage student behavior problems (Bradshaw et. al., 2012). An ongoing RCT of PBIS in 58 high schools, which combines other programs at Tiers 2 and 3, is currently under way; the preliminary findings from this trial suggest positive effects on bullying, violence, school climate, and substance use ( Bradshaw et al., 2014b ).

The KiVa Antibullying Program is another schoolwide, multicomponent program that has demonstrated promising effects. It has been implemented nationally in Finland for students in grades 1 through 9. Its universal elements include activities designed to increase bystander empathy and efficacy, teacher training, and more-targeted strategies for students at risk for or engaged in bullying as perpetrators or victims. It provides classroom training and materials to promote open discussions between teachers and students, peer support for students who are bullied, training for school staff in disciplinary strategies, and informational materials for families to prevent and appropriately respond to bullying. Computer games are also used to help students practice bullying prevention skills.

In their nonrandomized national trial, Kärnä and colleagues (2011a , 2011b ) showed that after 9 months of implementation, students in KiVa schools reported lower rates of bullying behavior compared to students in non-intervention control schools. Specifically, victimization rates decreased with age from grade 1 (25.9%) to grade 9 (9.3%), with the largest decrease occurring between grades 1 and 6. Compared to controls, students in the KiVa program reported lower rates of being targeted for bullying ( OR = 1.22; 95% CI [1.19, 1.24]) and perpetration of bullying ( OR = 1.18; 95% CI [1.15, 1.21]).

Previous evaluations of the KiVa Program have also found the greatest program effects for younger elementary age students (grades 1-6) and smaller effects for middle-school age children (grades 7-9). Generally, program effects increased through grade 4 but steadily declined from that point forward. Specifically, KiVa has demonstrated significant impacts on being a perpetrator or a target of bullying behavior among students in grades 4-6 (effect sizes from 0.03 to 0.33; see Kärnä, et al., 2011a , 2011b ), as well as for youth in grades 1-9 (odds ratios from 0.46 to 0.79; see Garandeau et al., 2014 ). In one evaluation of the KiVa Program, Veenstra and colleagues (2014) showed that for fourth to sixth grade students, their perception of teacher efficacy in decreasing bullying was associated with lower levels of peer-reported bullying. They argued that teachers play an important role in anti-bullying programs and should be included as targets of intervention. Ahtola et al., (2012) also found in their evaluation of the KiVa Program that teacher support of the program was positively related to implementation adherence, which in turn contributes to the potential for enhanced program effects. KiVa has only been tested in Europe, although there are currently efforts under way to adapt the model for use in other countries such as the United States.

A recent meta-analysis examining developmental differences in the effectiveness of anti-bullying programs provides some supportive evidence for significant declines in program effectiveness for students in eighth grade and beyond ( Yeager et al., 2015 ). Specifically, Yeager and colleagues examined hierarchical within-study moderation of program effects by age as compared to more typical meta-analytic approaches that examine between-study tests of moderation. Their findings are inconsistent with the findings of Ttofi and Farrington (2009) , in which larger program effect sizes (reductions in perpetrating and being a target of bullying) were found for programs implemented with older students (typically defined as students over age 11) compared to younger students.

A number of social-emotional learning programs have also been developed and tested to determine impacts on a range of student outcomes ( Durlak et al., 2007 , 2011 ). Some of these models have shown promising effects on aggression and bullying-related outcomes. One such model is Second Step: A Violence Prevention Curriculum. This classroom-based curriculum for children of ages 4-14 aims to reduce impulsive, high-risk, and aggressive behaviors while increasing social-emotional competence and protective factors. The curriculum teaches three core competencies: empathy, impulse control and problem solving, and anger management ( Flannery et al., 2005 ; Baughman Sladky et al., 2015 ). Students participate in 20-50-minute sessions two to three times per week, in which they practice social skills. Parents can participate in a six-session training that familiarizes them with the content in the children's curriculum. Teachers also learn how to deal with disruptions and behavior management issues. ( Flannery et al., 2005 ). In one study, children in the Second Step Program showed a greater drop in antisocial behavior compared to those who did not receive the program, behaved less aggressively, and were more likely to prefer prosocial goals ( Flannery et al., 2005 ; Frey et al., 2005 ). Other studies of Second Step have demonstrated significant reductions in reactive aggression scores for children in kindergarten through second grade and significant reductions in teacher-rated aggression for the children rated highest on aggression at baseline ( Hussey and Flannery, 2007 ).

In a RCT of 36 middle schools, Espelage et al. (2013) found that students in Second Step intervention schools were 42 percent less likely to self-report physical aggression than students in control schools, with aggression measured as incidents of fighting, but the authors reported that the program had no effect on verbal/relational bullying perpetration, peer victimization, 3 homophobic teasing, or sexual violence. In one of the first school-level RCTs of a violence prevention curriculum, Grossman and colleagues (1997) examined, via parent and teacher reports and investigator observation, the effects of the Second Step preventive intervention program on elementary student (second and third grade) aggressive and prosocial behavior. While they did not find changes over time in parent or teacher reports, behavioral observations of students in various school settings showed an overall decrease 2 weeks after the curriculum in physical aggression (–0.46 events per hour, p = .03) and an increase in neutral/prosocial behavior (+3.96 events per hour, p =.04) in the intervention group compared with the control group. One of the recurrent limitations faced by school-level analyses is that measures that have been validated as school-level constructs may not use measures that have only been validated for individual assessment. Similarly, analyses in many studies do not account for the nesting of students within classrooms or schools.

The Good Behavior Game is an elementary school-based prevention program that targets antecedents of youth delinquency and violence. It uses classroom behavior management as a primary strategy to improve on-task behavior and decrease aggressive behavior ( Baughman Sladky et al., 2015 ). Evaluations of the Good Behavior Game in early elementary school have shown it results in reduced disruptive behavior, increased academic engagement time, and statistically significant reductions in the likelihood of highly aggressive children receiving a diagnosis of a conduct disorder by sixth grade, as well as a range of positive academic outcomes ( Bradshaw et al., 2009a ; Wilcox et al., 2008 ). The effects were generally strongest among the most aggressive boys, who, when exposed to the program starting in the first grade, had lower rates of antisocial personality disorder when diagnosed as young adults ( Petras et al., 2008 ) and reduced rates of mental health service use, compared to those in the control group ( Poduska et al., 2008 ).

Good Behavior Game has also been tested in combination with other programs, such as Linking the Interests of Families and Teachers (LIFT), which combines school-based skills training with parent training for first and fifth graders. This program is implemented over the course of 21 one-hour sessions delivered across 10 weeks. LIFT uses a playground peer component to encourage positive social behavior and a 6-week group parent-training component. The Good Behavior Game is the classroom-based component of LIFT. LIFT also reduced playground aggression, reduced overall rates of aggression, and increased family problem solving ( Eddy et al., 2000 ; Baughman Sladky et al., 2015 ).

Raising Healthy Children ( Catalano et al., 2003 ), formerly known as the Seattle Social Development Project ( Hawkins et al., 1999 ), is a multidimensional intervention that targets both universal populations and high-risk youth in elementary and middle school. The program uses teacher and parent training, emphasizing classroom management for teachers and conflict management, problem-solving, and refusal skills for children. Parents receive optional training programs that target rules, communication, and strategies to support their child's academic success. Follow-up at age 18 showed that the program significantly improved long-term attachment and commitment to school and school achievement and reduced rates of self-reported violent acts and heavy alcohol use ( Hawkins et al., 1999 ). At age 21, students who had received the full intervention when young were also less likely to be involved in crime, to have sold illegal drugs in the past year, or to have received a court charge ( Hawkins et al., 2005 ).

Steps to Respect is another multicomponent program that includes activities led by school counselors for youth involved in bullying, along with schoolwide prevention, parent activities and classroom management. ( Frey et al., 2005 , 2009 ; Baughman Sladky et al., 2015 ). One RCT of Steps to Respect showed a reduction of 31 percent in the likelihood of perpetrating physical bullying in intervention schools relative to control schools (adjusted odds ratio = 0.609) based on teacher reports of student behaviors ( Brown et al., 2011 ). Brown and colleagues (2011) also showed significant improvements in student self-reports of positive school climate, increases in student and teacher/staff bullying prevention and intervention, and increases in positive bystander behavior for students in intervention schools compared to students in control schools (effect sizes ranged from 0.115 for student bullying intervention to 0.187 for student climate). They found no effects for student attitudes about bullying.

In a separate RCT of Steps to Respect, Frey and colleagues (2009) found, using teacher observations of student playground behaviors, statistically significant declines over 18 months in bullying ( d = 2.11, p < .01), victimization ( d = 1.24, p < .01) and destructive bystander behavior ( d = 2.26, p < .01) for students in intervention schools compared to students in control schools. While student self-reports of victimization declined across 18 months, student self-reports of aggressive behavior did not change.

One of the most comprehensive, long-term school-based programs that has been developed to prevent chronic and severe conduct problems in high-risk children is Fast Track. Fast Track is based on the view that antisocial behavior stems from the interaction of influences across multiple contexts such as school, home, and the individual ( Conduct Problems Prevention Research Group, 1999 ). The main goals of the program are to increase communication and bonds between and among these three domains; to enhance children's social, cognitive, and problem-solving skills; to improve peer relationships; and ultimately to decrease disruptive behavior at home and in school. Fast Track provides a continuum of developmentally sequenced preventive intervention spanning grades 1 through 10. It includes some of the program elements and frameworks mentioned above, such as a social-emotional learning curriculum developed in elementary school called Promoting Alternative Thinking Strategies, as well as a version of the Coping Power program for higher-risk students. Other elements include support to parents, which is tailored to meet the unique needs of the family and youth.

Thus, Fast Track is a combination of multiple programs across the tiers. It has demonstrated effectiveness in reducing aggression and conduct problems, as well as reducing associations with deviant peers, for students of diverse demographic backgrounds, including sex, ethnicity, social class, and family composition differences ( Conduct Problems Prevention Research Group, 2002 , 2010 ; National Center for Health Statistics and National Center for Health Services Research, 2001 ). In an examination of the longitudinal outcomes of high-risk children who were randomly assigned by matched sets of schools to intervention and control conditions, the Conduct Problems Prevention Research Group (2011) showed that 10 years of exposure to Fast Track intervention prevented lifetime prevalence (assessed in grades 3, 6, 9, and 12) of psychiatric diagnoses for conduct disorder, oppositional defiant disorder, externalizing disorder, and attention deficit hyperactivity disorder.

In addition, a recent RCT of Fast Track showed that early exposure to the intervention substantially reduced adult psychopathology at age 25 among high-risk early-starting conduct-problem children ( Dodge et al., 2015 ). Specifically, intent-to-treat logistic regression analyses showed that 69 percent of participants in the control condition displayed at least one externalizing, internalizing, or substance use psychiatric problem (assessed via self-report or peer interview) at age 25, compared to 59 percent of those assigned to intervention ( OR = 0.59, 95% CI [0.43, 0.81]; number needed to treat = 8). Intervention participants also received lower severity-weighted violent crime conviction scores (standardized estimate = −0.37). This study was a random assignment of nearly 10,000 kindergartners in three cohorts, who were followed through a 10-year intervention and then assessed at age 25 via arrest records, condition-blinded psychiatrically interviewed participants, and interview of a peer knowledgeable about the participant.

The above descriptions of the selected universal multicomponent programs that address bullying or related behavior and their tiered levels of prevention are summarized in Table 5-1 . The ecological contexts in which these programs operate are summarized in Table 5-2 .

Summary of Selected Universal Multicomponent Prevention Programs that Address Bullying or Related Behavior.

Summary of Ecological Contexts in which Selected Universal Multicomponent Prevention Programs Operate.

Examples of School-Based Selective and Indicated Prevention Programs to Address Bullying or Related Behaviors

As noted above, many of the schoolwide and universal prevention models included elements across the tiers, but here the committee considers programs that are largely focused at the selective and indicated level. Within schools, it is common for students who are involved in bullying to be referred for some type of school-based or community counseling services ( Swearer et al., 2014 ).

McElearney and colleagues (2013) reported that school counseling was an effective intervention for middle school students who had been bullied when the counseling focused on improving peer relationships. In their study, they collected longitudinal data from 202 students (mean age = 12.5) using the self-rated Strengths and Difficulties Questionnaire (SDQ). 4 In total, 27.2 percent of the student referrals to the intervention related to being bullied. Students who had been bullied had significantly higher initial status scores (LGC initial score = 1.40, p < .001) on the Peer Problems subscale of the SDQ and experienced a significantly more rapid rate of decrease on this subscale (LGC rate of change score = −0.25, p < .001) with each successive session of school counseling, compared with those students who had accessed the intervention for another reason. However, counseling sessions probably vary considerably in the services provided and the extent to which they employ evidence-based models.

A few studies have examined social workers or school mental health staff who provide intervention for youth involved in bullying, but the research in this area is rather weak, with relatively few systematic studies focused on assessing the impacts of selective and indicated programs on bullying ( Swearer et al., 2014 ). Moreover, given the difficulty of determining the efficacy of counseling as an intervention per se, the committee focuses here more specifically on particular structured preventive intervention models that have been more formally articulated in a curriculum, many of which are delivered by school-based counselors, social workers, or psychologists.

For example, Berry and Hunt (2009) found preliminary support for a cognitive-behavioral intervention for anxious adolescent boys in grades 7-10 (mean age of 13.04 years) who had experienced bullying at school. Fung (2012) assessed a group treatment for youth ages 11-16, provided by social workers in Hong Kong using a social information processing model. Students were selected for intervention based on their high levels of aggressive behavior rather than bullying specifically, but the author did find that after 2 years of the intervention, students reported a decrease in reactive aggression but not proactive aggression. Fung (2012) also found that cognitive-behavioral group therapy was effective in reducing anxious and depressed emotions in children who are both the perperator and target of bullying.

One of the few evidence-based targeted intervention programs for late preadolescent children is the Coping Power Program ( Lochman et al., 2013 ). Coping Power targets aggressive youth and their parents and is delivered by counselors in small groups over the course of a school year. Additional supports are provided to teachers to promote generalization of skills into nongroup settings. The program has demonstrated significant improvements in aggressive-disruptive behaviors and social interactions, many of which were maintained at 3-year follow-up for children from fourth through sixth grade ( Lochman et al., 2013 ).

Having available strategies to cope with stress has also been shown to reduce depression among older adolescents who were bullied ( Hemphill et al., 2014 ). Although originally developed for students in grades 4-6, there is currently an ongoing 40-school randomized trial testing a middle school version of this model; the trial has a particular focus on assessing outcomes related to bullying ( Bradshaw et al., in press ); a high school model of Coping Power is also currently in development and will soon be tested on 600 urban high school students ( Bradshaw et al., in press ).

DeRosier (2004) and DeRosier and Marcus (2005) evaluated the effects of a social-skills group intervention for children experiencing peer dislike, bullying, or social anxiety. In their study of third graders randomly assigned to treatment or to no-treatment control, DeRosier and Marcus (2005) showed that aggressive children exposed to the program reported greater declines in aggression and bullying behavior and fewer antisocial affiliations than aggressive children in the no-intervention control condition. The intervention resulted in decreased aggression on peer reports (Cohen's d = 0.26), decreased targets of bullying on self-reports (Cohen's d = 0.10) and fewer antisocial affiliations on self-reports (Cohen's d = 0.11) for the previously aggressive children ( DeRosier and Marcus, 2005 ).

A study of elementary school students exposed to the FearNot! virtual learning intervention to enhance coping skills of children who were bullied showed a short-term improvement on escaping being bullied ( Sapouna et al., 2010 ). In a separate evaluation of the FearNot! Program in the UK and German schools, exposure to the intervention was found to help non-involved primary grade children to become defenders of the target in virtual bullying situations, at least for youth in the German sample ( Vannini et al., 2011 ).

There are also a number of preventive interventions that aim to address mental health problems but may also prove to be helpful for youth who are involved in bullying. For example, a school-based version of cognitive-behavioral therapy is Cognitive Behavioral Intervention for Trauma in Schools (CBITS). This evidence-based treatment program is for youth ages 10-15 who have had substantial exposure to violence or other traumatic events and who have symptoms of posttraumatic stress disorder (PTSD) in the clinical range. The CBITS Program has three main goals: (1) to reduce symptoms related to trauma, (2) to build resilience, and (3) to increase peer and parent support. Based on a model of trauma-informed care, CBITS was developed to reduce symptoms of distress and build skills to improve children's abilities to handle stress and trauma in the future. The intervention incorporates cognitive-behavioral therapy skills in a small group format to address symptoms of PTSD, anxiety, and depression related to exposure to violence. CBITS was found to be more accessible to families who may not have been able or willing to participate outside of schools. CBITS was also found to significantly improve depressive symptoms in students with PTSD ( Jaycox et al., 2010 ).

Examples of Family-Focused Preventive Interventions to Address Bullying

A few family-focused preventive interventions have been developed that may also demonstrate promising effects on bullying. For example, the Incredible Years Program aims to reduce aggressive and problem behaviors in children, largely through supports to parents, as well as students and teachers. It focuses on social skills training components ( Webster-Stratton, 1999 ) and targets elementary school students with the aim of preventing further aggression and related behavior problems for youth with conduct problems but whose behavior would not yet be considered in the clinical range requiring treatment. Barrera and colleagues (2002) showed that high-risk elementary school children in the Incredible Years Program displayed lower levels of negative social behavior, including aggression, compared to control youth who did not receive the intervention. In another study, Webster-Stratton and colleagues (2008) showed that teacher training in combination with Dinosaur School in Head Start and first grade classrooms with at-risk students resulted in improved social competence and self-regulation and in fewer youth conduct problems. There is also a universal version of the Incredible Years Program delivered by teachers, which is currently being tested in two separate randomized trials. To the committee's knowledge, bullying has not been assessed as an outcome in prior studies of Incredible Years, although several impacts on other discipline and behavior problems have been observed in prior RCTs.

Another family-focused program is The Family Check-Up (also known as the Adolescent Transitions Program). This multilevel, family-centered intervention targets children at risk for problem behaviors or substance use. The Family Check-Up had historically been delivered in middle school settings, but more recent studies have extended the model to younger populations (e.g., 2-5 year olds in Dishion et al., 2014 ). Parent-focused elements of The Family Check-Up concentrate on developing family management skills such as using rewards, monitoring, making rules, providing reasonable consequences for rule violations, problem solving, and active listening ( Dishion and Kavanagh, 2003 ). Connell and colleagues (2007) found that The Family Check-Up resulted in significantly fewer arrests; less use of tobacco, alcohol, and marijuana; and less antisocial behavior for intervention youth, compared with control group youth.

Another targeted program that includes supports for families is the Triple P intervention. A RCT of Resilience Triple P for Australian youth 6 to 12 years old found significant improvements for intervention youth compared to controls on teacher reports of overt victimization ( d = 0.56), and child overt aggression toward peers ( d = 0.51) as well as improvements in related mental health such as internalized feelings and depressive symptoms. The intervention that combined facilitative parenting with social and emotional skills training worked best ( Healy and Sanders, 2014 ). An earlier study of Triple P for preschoolers at risk for conduct problems found that a version delivered by practitioners (clinical psychologists, psychologists, and psychiatrists) trained and supervised in the delivery of the interventions was more effective in reducing problem behaviors compared to a wait-list condition and a Triple P program that was self-directed ( Sanders et al., 2000 ).

In addition to the largely school- and family-based programs summarized above, there are several evidence-based interventions that are more typically provided in the community ( Baughman Sladky et al., 2015 ). Although these programs focus more generally on violence and aggression prevention, they may also produce effects on bullying related behaviors, such as conduct problems for perpetrators or those at risk for perpetration, or they may address the behavioral and mental health consequences of being bullied.

For example, a widely utilized intervention to address mental health issues for children and adolescents is Trauma Focused Cognitive Behavioral Therapy (TF-CBT) which has been shown to be effective in reducing mental health symptoms related to violence exposure ( Cohen et al., 2006 ). TF-CBT has been particularly effective in treating children who are victims of sexual abuse ( Cohen et al., 2005 ). While not specifically used to address being a target of bullying, TF-CBT can be used to treat complex trauma and has been shown to result in improvements to mental health issues related to peer victimization including PTSD symptoms, depression, anxiety, and externalizing behavior problems ( Cohen et al., 2004 ; Deblinger et al., 2011 ).

Programs that are delivered in the community often include supports for parents as well as the youth. For example, Functional Family Therapy (FFT) is a family-based intervention program that targets youth between the ages of 11 and 18 who are at risk for and/or presenting with delinquency, violent or disruptive behavior, or substance use ( Baughman Sladky et al., 2015 ). It is time-limited, averaging 8-12 sessions for referred youth and their families, with generally no more than 30 hours of direct service time for more difficult cases. FFT is multisystemic and multilevel in nature, addressing individual, family, and treatment system dynamics. It integrates behavioral (e.g., communication training) and cognitive-behavioral interventions (e.g., a relational focus). Assessment is an ongoing and multifaceted part of each phase ( Henggeler and Sheidow, 2012 ). Evaluations of FFT have shown significant improvements in delinquent behavior and recidivism ( Aos et al., 2011 ; Sexton and Alexander, 2000 ).

Brief Strategic Family Therapy (BSFT) is a short-term (approximately 12-15 sessions over 3 months) family-based intervention for children and youth ages 6-17 who are at risk for substance abuse and behavior problems ( Robbins et al., 2002 , 2007 ; Szapocznik and Williams, 2000 ). BSFT employs a structural family framework and focuses on improving family interactions. Evaluation results demonstrate decreases in substance abuse, conduct problems, associating with antisocial peers, and improvements in family functioning. In a small randomized trial of girls who were perpetrators of bullying, Nickel and colleagues (2006) found a decrease in bullying behavior (and expressive aggression) in the BSFT group, with improvements maintained at 1-year follow-up. Similar findings were observed in a separate study of BSFT for boys who were involved in bullying behavior. ( Nickel et al., 2006 ).

Wraparound/Case Management is a multifaceted intervention designed to keep delinquent youth at home and out of institutions by “wrapping” a comprehensive array of individualized services and support networks “around” young people, rather than forcing them to enroll in predetermined, inflexible treatment programs ( Bruns et al., 1995 ; Miles et al., 2006 ). Evaluations of Wraparound have found marked improvement in behavior and socialization, and youth in the intervention group were significantly less likely to reoffend compared to graduates of conventional programs ( Carney and Buttell, 2003 ; Miles et al., 2006 ).

Multisystemic Therapy (MST) targets chronic, violent, or substance-abusing male or female juvenile offenders, ages 12-17, at risk of out-of-home placement, along with their families. MST is a family-based model that addresses multiple factors related to delinquency across key socioecological settings. It promotes behavior change in the youth's natural environment, using a strengths-based approach ( Henggeler, 2011 ). Critical service characteristics include low caseloads (5:1 family-to-clinician ratio), intensive and comprehensive services (2-15 hours per week) and time-limited treatment duration (4-6 months) ( Henggeler et al., 1999 ). Treatment adherence and fidelity are key ingredients for achieving long-term, sustained effects and decreasing drug use. Evaluations of MST that examined delinquency rates for serious juvenile offenders demonstrated a reduction in long-term rates of re-arrest, reductions in out-of home placements, and improvements in family functioning, and decreased mental health problems for serious juvenile offenders ( Greenwood and Welsh, 2012 ; Schaeffer and Borduin, 2005 ). A recent meta-analysis of the effectiveness of MST across 22 studies containing 322 effect sizes found small but statistically significant treatment effects for its primary outcome of delinquent behavior, but the meta-analysis also found secondary outcomes such as psychopathology, substance use, family factors, out-of-home placements, and peer factors. For example, considering MST as an intervention that may affect bullying related behaviors, eight studies assessing peer relations showed improvements for aggressive youth treated with MST compared to youth treated via other modalities (mean effect size d = 0.213) ( van der Stouwe et al., 2014 ).

Another communitywide prevention model that holds promise for reducing violence and related behavior problems is the Communities That Care (CTC) framework. CTC is a system for planning and organizing community resources to address adolescent problematic behavior such as aggression or drug use. It has five phases to help communities work toward their goals. The CTC system includes training events and guides for community leaders and organizations. The main goal is to create a “community prevention board” comprising public officials and community leaders to identify and reduce risk factors while promoting protective factors by selecting and implementing tested interventions throughout the community. Based on communitywide data on risk and protective factors, schools may select from a menu of evidence-based programs, which includes some of the models listed above. Thus, CTC is more of a data-informed process for selecting and implementing multiple evidence-based programs. As a result, it is difficult to attribute significant improvements in youth behavior to any one specific program. However, randomized studies testing the CTC model have shown statistically significant positive effects on delinquency, alcohol use, and cigarette use, all of which were lower by grade 10 among students in CTC communities, compared to students in control communities ( Hawkins et al., 2011 ).

Descriptions of a subset of selective and indicated prevention programs that address bullying or related behavior and their tiered level of prevention are summarized in Table 5-3 . The ecological contexts in which these programs operate are summarized in Table 5-4 .

Summary of Selective and Indicated Prevention Programs that Address Bullying or Related Behavior.

Summary of Ecological Contexts in which the selected Selective and Indicated Prevention Programs Operate.

Examples of Preventive Intervention to Address Cyberbullying and Related Behaviors

In a review of interventions to reduce cyberbullying, Mishna and colleagues (2012) found some gains in knowledge about Internet safety, but psychoeducational interventions had little effect on changing risky online behavior. Ryan and Curwen (2013) noted the lack of evidence-based interventions for victims of cyberbullying in their review of evidence regarding the occurrence, impact, and interventions for targets of cyberbullying. Given that cyberbullying takes place online and that the vast majority of youth are online, online resources to prevent or address cyberbullying may have broad reach. At present, online resources exist that were created to address or provide support regarding cyberbullying; one example is the website STOP Cyberbullying. 5 There have also been social marketing campaigns tied to online resources that include resources to counter cyberbulling; one example is the It Gets Better Project. 6 To the committee's knowledge, none of these online programs has undergone empirical evaluation yet.

Across social media sites, there is no consistent information about bullying policies, resources, or tracking of behaviors. Facebook is the most popular social media site and provides a Webpage of bullying resources. 7 Instagram is also popular among teens and provides its own Webpage discussing cyberbullying. 8 Both of these sites provide links where bullying can be reported to site administrators, but there are no published reports of this information or empirical studies evaluating prevalence of what is reported. The committee found no studies of the effectiveness of these sites or of the resources they provide.

In the family context, however, recent correlational studies suggest that spending time together, such as through family meals, may provide an important context for disclosure of being a target of bullying, which in turn buffers some of the subsequent effects of bullying on social-emotional adjustment ( Elgar et al., 2014 ).

Some recent research, predominantly in Europe, has examined the effectiveness of preventive interventions specifically on cyberbullying. These programs are school based and were designed for students between the ages of 13 and 17. Many of these evaluation studies used randomized designs, including studies of Cyber Friendly Schools and the Viennese Social Competence Program. Cyber Friendly Schools is a whole-school, online cyberbullying prevention and intervention program that is based on a social–ecological approach and considers the many factors that influence students' vulnerability to cyberbullying at multiple levels ( Cross et al., 2015 ). The Viennese Social Competence Program is a primary preventive program that includes secondary preventive elements to reduce aggressive behavior and bullying and to foster social and intercultural competencies in schools ( Gradinger et al., 2015 ). These programs have been associated with declines, from program pretest to post-test, in both cyberbullying perpetration and being targeted.

The German program Medienhelden (“Media Heroes”), which was originally designed for traditional bullying, has also been used as a cyberbullying intervention. This program is a universal, modularized, and theoretically based preventive intervention for the school context that builds on previous knowledge about potential risk and protective factors such as cognitive and affective empathy. An evaluation of this program showed that while the intervention was associated with reductions in both traditional and cyberbullying perpetration for both short-intervention conditions (mean difference = −0.29, p = .00) and long-intervention conditions (mean difference = −0.32, p = .00), it was not associated with reductions in being targets of either kind of bullying ( Chaux et al., 2016 ).

Other studies used a quasi-experimental design. For example, an evaluation of the NoTrap! Program, which is a school-based intervention, and utilizes a peer-led approach to prevent and combat both traditional bullying and cyberbullying, showed a decrease over time in being targeted for traditional bullying or cyberbullying ( F (1, 457) = 5.379, p = .02; η 2 p = .012) and in perpetrating bullying ( F (1, 457) = 9.807, p =. 002; η 2 p = .021) ( Palladino et al., 2016 ). Evaluation of the ConRed Program ( Ortega-Ruiz et al., 2012 ), which is a theory-driven program designed to prevent cyberbullying and improve cyberbullying coping skills, showed that individuals who had been targets of cyberbullying reported decreased incidence of being bullied for both traditional bullying ( F = 7.33, p = .008, d = 0.46) and cyberbullying ( F = 7.73, p = .03, d = 0.56) ( Del Rey et al., 2015 ). Finally, a study focused on college students used the theory of reasoned action ( Ajzen, 1985 ) in a cyberbullying prevention program involving an educational video. One month follow-up found that the intervention group had increases in cyberbullying knowledge ( d = 0.85), as well as decreases in approving attitudes (.24 < ds < .48) toward online behaviors such as unwanted contact, public humiliation, and deception ( Doane et al., 2015 ).

As a whole, this body of research supports a finding that interventions designed to target one type of bullying can have spillover effects on another. This is not surprising, given the overlap between cyberbullying and traditional bullying ( Waasdorp and Bradshaw, 2015 ). A common issue and limitation of this body of work is that all the studies involved self-report by students. Future research opportunities include triangulating this data with reports from parents or teachers. All of the preventive interventions reviewed in this section, despite their focus on cyberbullying, are implemented in the offline world and specifically in schools.

• RECOMMENDED COMPONENTS AND CONSIDERATIONS FOR BULLYING PREVENTION

In the committee's broader reflections on the literature about and practice of bullying prevention, a number of core elements or critical features consistently emerged. In this section, we summarize those elements for which there is a converging body of supporting evidence. However, a challenge in this area is the limited documentation on the effectiveness of particular components or programmatic elements. Much of what has been reported about what works in bullying prevention comes from randomized trials of programs and meta-analyses summarizing effective models, with limited post hoc exploration into programmatic elements associated with the greatest effect sizes. Although few studies were appropriately designed to discern particular effective components or elements of an entire model, separate from other elements, the following frameworks and core components are among the most promising within the extant research.

As noted above, there is a growing emphasis on the use of multi-tiered approaches—those which leverage universal, selective, and indicated prevention programs and activities. For example, a tiered approach might include lessons on social-emotional skill development for all students—thus making it a universal program. In fact, research highlights the importance of providing class time to discuss bullying ( Olweus, 1993 ) and the use of lessons to foster skills and competencies, effective communication, and strategies for responding to bullying ( Farrington and Ttofi, 2009 ); such strategies can also have a positive impact on academic and other behavioral outcomes ( Durlak et al., 2010 ). Effective classroom management is also critical, as well-managed classrooms are rated as having a more favorable climate, being safer and more supportive, and having lower rates of bullying compared to less-well-managed classrooms ( Koth et al., 2008 ). At Tier 2, selective interventions may include social skills training for small groups of children at risk for becoming involved in bullying. Finally, an indicated preventive intervention (Tier 3) may include more intensive supports and programs tailored to meet the needs of students identified as a perpetrator or a target of bullying and the needs of their families ( Espelage and Swearer, 2008 ; Ross and Horner, 2009 ).

Consistent with the social–ecological framework ( Espelage et al., 2004 ), schools should address the social environment and the broader culture and climate of bullying ( Bradshaw and Waasdorp, 2009 ). Research documents the importance of schoolwide prevention efforts that provide positive behavior support, establish a common set of expectations for positive behavior across all school contexts, and involve all school staff in prevention activities ( Ross and Horner, 2009 ). Effective supervision, especially in bullying “hot spots,” and clear anti-bullying policies are essential elements of a successful schoolwide prevention effort ( Olweus, 1993 ). The playground appears to be a particularly important context for increasing supervision in order to prevent bullying ( Farrington and Ttofi, 2009 ; Frey et al., 2005 ). Collecting data on bullying via anonymous student surveys can inform the supervision and intervention process. These data can identify potential areas for intensive training of school staff, which is an essential element of successful bullying prevention efforts ( Farrington and Ttofi, 2009 ). Data are also critical for monitoring progress toward the goal of reducing bullying ( Olweus, 1993 ).

Families also play a critical role in bullying prevention by providing emotional support to promote disclosure of bullying incidents and by fostering coping skills in their children. Parents need training in how to talk with their children about bullying ( Johnson et al., 2011 ), how to communicate their concerns about bullying to the school, and how to get actively involved in school-based bullying prevention efforts ( Waasdorp et al., 2011 ). There also are important bullying prevention activities that can occur at the community level, such as awareness or social marketing campaigns that encourage all youth and adults—including doctors, police officers, and storekeepers—to intervene when they see bullying and to become actively involved in school- and community-based prevention activities ( Olweus, 1993 ).

It is also important to consider how schools can integrate prevention efforts with their other existing programs and supports. Research by Gottfredson and Gottfredson (2001) indicates that, on average, schools are using about 14 different strategies or programs to prevent violence and promote a safe learning environment. This can often be overwhelming for school staff to execute well, thereby leading to poor implementation fidelity. Therefore, schools are encouraged to integrate their prevention efforts so that there is a seamless system of support ( Domitrovich et al., 2010 ), which is coordinated, monitored for high fidelity implementation, and includes all staff across all school contexts. Instead of adopting a different program to combat each new problem that emerges, schools can develop a consistent and long-term prevention plan that addresses multiple student concerns through a set of well-integrated programs and services. Such efforts would address multiple competencies and skills in order to prevent bullying, while helping students cope and respond appropriately when bullying does occur. Programs should include efforts to enhance resilience and positive behaviors and not just focus on reductions in bullying perpetration. The three-tiered public health model provides a framework for connecting bullying prevention with other programs to address bullying within the broader set of behavioral and academic concerns.

Collectively, the extant research suggests that there are a number of universal prevention programs that are effective or potentially promising for reducing bullying and related behavioral and mental health concerns. With regard to selective and indicated prevention programs, the focus of the model tends to be more generally on other behavioral concerns, with relatively few programs at these levels being tested using RCT designs to determine impacts on bullying specifically. Additional research is clearly needed to better understand the impacts of programs across all three tiers, as well as the combined impacts of such programs.

• NONRECOMMENDED APPROACHES

There has been an emerging concern that some programs and strategies commonly used with the goal of preventing or stopping bullying may actually increase bullying or cause other harm to youth or the school community. For example, suspension and related exclusionary techniques are often the default response by school staff and administrators in bullying situations; however, these approaches do not appear to be effective and may actually result in increased academic and behavioral problems for youth. Encouraging youth to fight back when bullied is also not a recommended strategy, as it suggests that aggression is an effective means for responding to victimization and may perpetuate the cycle of violence. Furthermore, such an aggressive response may escalate the level of violence and the risk of harm for all parties involved. While there is still much to be learned about effective youth responses to bullying across the different age groups and social–ecological contexts, recommended responses may include deflecting, seeking peer and adult support, and avoidance of situations that may increase the likelihood of exposure to bullying ( Waasdorp and Bradshaw, 2011 ). Yet there are characteristics of some youth that may make some of these responses easier to display than others. For example, youth who have challenges regulating emotions and inhibiting aggressive responses are more likely to use violence when bullied.

Given that bullying is a complex peer behavior, it may seem wise to leverage peers in attempting to intervene in bullying situations. In fact, there is a large and growing literature supporting the potential effectiveness of bystander interventions ( Polanin et al., 2012 ). However, caution should be taken about the types of roles youth play in bullying prevention. Youth- or peer-facilitated programs, such as peer mediation, peer-led conflict resolution, forced apology, and peer mentoring may not be appropriate or effective in bullying prevention.

There are concerns about approaches based on forced apology or the use of peer-mediated conflict resolution within the context of bullying programs, in part because of the face-to-face interactions between the youth who have been perpetrators and those who have been targeted. Such approaches are rarely structured in a way to address peer abuse of power, as it occurs in bullying behavior, as compared to the original focus of such approaches on conflict ( Bradshaw, 2013 ). The systematic review and meta-analysis of school-based anti-bullying programs by Ttofi and Farrington (2011) found that programs that were peer-led often produced null or even iatrogenic effects. Some programs appeared to increase attitudes supportive of bullying, whereas others showed an increase in incidents of targeting rather than a reduction in bullying-related behaviors. There is also a large body of violence- and delinquency-related research (see Dodge et al., 2006 , for review) suggesting that grouping youth who bully together may actually reinforce their aggressive behaviors and result in higher rates of bullying. In these situations, a contagion process likely occurs, whereby the youth learn more aggressive and bullying behaviors from each other and are reinforced for their aggressive behavior. Furthermore, conflict resolution approaches, even when facilitated by adults, are not typically recommended in situations of bullying, as they suggest a disagreement between two peers of equal status or power, rather than an instance of peer abuse. These approaches also typically bring targets and youth who bully face to face, which may be especially hurtful for the youth who is bullied. It is important to note, however, that there may be other forms of delinquent and problem behavior, such as property offenses or threats toward staff, which may be more appropriate for these types of conflict resolution approaches. Although additional research is certainly needed to determine the appropriateness of these and other youth-facilitated practices in the context of bullying prevention, it is likely that structured and well-supervised youth leadership activities can have a positive impact on bullying prevention; however, more RCT-designed studies that document outcomes associated with these approaches are needed.

There is also little evidence that one-day awareness raising events or brief assemblies are effective at changing a climate of bullying or producing sustainable effects on bullying behavior ( Farrington and Ttofi, 2009 ). Some of these types of efforts have focused largely on instances of youth suicides, which may have been linked in some way with bullying. Given growing concerns about the potential association between bullying and youth suicide, and more generally issues related to suicidal contagion among adolescents ( Duong and Bradshaw, 2015 ; Romer et al., 2006 ), practitioners and researchers should be cautious in highlighting such a potential link, as it may result in confusion and misattribution among families as well as in the media. Rather, it is critical to state the epidemiologic evidence that suicide is extremely complex and generally associated more directly with mental health concerns such as anxiety and depression. Bullying could, therefore, serve as a risk factor for youth who are also experiencing mental health concerns ( Klomek et al., 2011 ). This underscores the importance of multicomponent programs that address social, behavioral, and mental health concerns.

• AREAS FOR FUTURE RESEARCH RELATED TO BULLYING PREVENTION PROGRAMMING

This final major section of the chapter identifies a number of areas that require additional research and focus in order to advance bullying prevention programming.

Implementation of Bullying Prevention Programming

There is a need for more implementation-focused research aimed at improving the adoption and implementation of evidence-based programs. Numerous studies have documented challenges with implementation fidelity of school-based programs, most of which suggest that the programs themselves are not difficult to implement; rather, constraints such as lack of buy-in, limited time to implement programs, competing priorities, lack of organizational capacity to coordinate the effort, and insufficient administrative support are all factors that may contribute to the relatively slow adoption of school-based programs and that compromise implementation fidelity ( Beets et al., 2008 ; Domitrovich et al., 2008 ; Vreeman and Carroll, 2007 ). Commitment not only to the implementation of a model but also to its sustainment and authentic integration with other efforts is needed for any such program to become routinized. For example, teacher attitudes about the potential effectiveness of the program, as well as school-related factors that support successful implementation with fidelity, have been shown to be important predictors of successful implementation of universal character education programs ( Beets et al., 2008 ).

A need also exists for sustained investment in data systems to guide the identification of strengths and gaps in implementation programming, as well as to track progress toward outcomes ( Bradshaw, 2013 ). Adequate time for ongoing quality professional development, coaching supports, and performance feedback are essential features of an implementation support system for achieving high-quality implementation of any evidence-based practice; positive effects cannot otherwise be expected ( Domitrovich et al., 2008 ; Fixsen et al., 2005 ).

Bullying prevention programming could also benefit from adopting practices and principles from the field of implementation science ( Fixsen et al., 2005 ). It may be that potentially effective programs already exist and that the field just needs to make a more sustained commitment to implementing the existing models with fidelity and testing them with RCT designs to better understand what works for whom, and under what conditions. This may be especially relevant when considering the broader set of youth violence prevention programs, which have rarely been evaluated to determine the impacts of these interventions on bullying specifically. The field of bullying prevention could benefit from the development and implementation of additional innovative and novel approaches that use emerging technologies and strategies. Furthermore, more research is needed to better understand the effective mechanisms of change and strategies to optimize the effect size of prevention programs.

The Role of Peers and Peer-Led Programming

There is no question that peers have a significant influence on youth development ( Collins et al., 2000 ; Dodge et al., 2006 ) including their involvement in and responses to bullying ( Paluck et al., 2016 ; Salmivalli, 2010 ). In fact, correlational studies have found that having more friends was associated with increased bullying perpetration but less risk of being bullied ( Wang et al., 2009 ), whereas other studies found that the way in which peers respond to witnessing bullying may help buffer the effects for the targeted youth ( Salmivalli et al., 1996 ). As a result, there is an increasing interest in leveraging these relationships and influences to prevent and intervene in bullying situations ( Paluck et al., 2016 ). However, the empirical findings on the role of peers in bullying prevention have been mixed, with some researchers suggesting the need for more peer-based interventions ( Paluck et al., 2016 ), such as friendship-making components ( Leff and Waasdorp, 2013 ), and others calling for more caution, particularly regarding implementation of selected or indicated interventions ( Dodge et al., 2006 ). Clearly, there is a need to distinguish between the role of peers as bystanders in bullying situations and peers as potential leaders or implementers of intervention programs.

Within group-based interventions, which is often a modality used for selective and some indicated preventive interventions, studies show that there is the potential for deviance training and a shift in attitudes that actually favor aggression and deviant behavior ( Dodge et al., 2006 ). While there are certainly structures and procedures that adult facilitators of such groups can put in place to try to mitigate these potentially iatrogenic effects, caution should be taken when implementing group-based programs for youth who are aggressive, such as those who bully.

One particular area of interest is intervention programs that operate through peer bystander behavior. This is a topic that is gaining attention, both within practice and within the research literature ( Cunningham et al., 2011 ; Polanin et al., 2012 ; Salmivalli, 2014 ). A bystander is defined as an onlooker who is present during the bullying event but remains neutral (passive), helping neither the victim nor the bully ( Salmivalli, 2010 ). A meta-analysis by Polanin and colleagues (2012) reviewed 12 school-based bullying prevention approaches that focused on bystanders' behaviors as a component of the intervention. They found that bystander-involved models were generally effective at reducing bullying (overall effect size as measured by Hedge's g = 0.20, p < .001, 95% CI [0.11, 0.29]). Although overall these programs were successful at increasing bystanders' intervention in bullying situations, Polanin and colleagues (2012) did not find any improvement in bystander empathy for the victims. This is consistent with other recent meta-analyses on a smaller set of studies that included bystander effects ( Merrell et al., 2008 ). Developmentally, Polanin and colleagues (2012) also found that bystander intervention effects were larger for older youth compared to younger children. Specifically, the effects were typically stronger in high schools (ES = 0.43) compared to students in younger grades (ES = 0.14; p < .05). Polanin and colleagues (2012) noted that their meta-analysis was limited to a relatively small number of studies, so they called for more research on the effects of peers on bullying, especially regarding the distinction between peers as bystanders and peers as leaders of intervention programming.

There are some potentially promising findings emerging from a few peer-led educational models that have been used successfully to address bullying and cyberbullying in Italy ( Menesini et al., 2012 ). Other youth-led programs have demonstrated some potentially promising effects in the context of bullying, sexual harassment, and dating violence prevention ( Connolly et al., 2015 ). However, a study by Salmivalli (2001) testing a peer-led intervention campaign against school bullying found that it produced mixed effects, with an increase in pro-bullying attitudes among boys. Additional research is clearly needed with larger samples and more RCT designs to determine the extent to which these and the other peer-led models are truly effective and robust against potentially iatrogenic effects. Other potentially promising findings are in the area of gay-straight alliances, which were discussed in Chapter 3 ( Poteat et al., 2013 , 2015 ). Such resources appear to be an important buffer for LGB youth and may contribute to a shift in the norms regarding stereotype-driven targeting of LGB youth. There is also growing interest in programming focused on issues related to equity in relation to both sexual and racial minorities ( Bulanda et al., 2014 ; Polanin and Vera, 2013 ). Similarly, there is increasing interest in the use of restorative practice-based models with the goal of preventing bullying and providing more equitable disciplinary practices in response to other behavioral violations ( Bradshaw, 2013 ). However, much of the work on this topic has been descriptive and conceptual, with few randomized and controlled studies assessing behavioral or bullying-related outcomes for youth. Additional research is needed to leverage findings from the extant research on equity and inclusion for subpopulations (e.g., minorities; youth with disabilities; lesbian, gay, bisexual, and transgender [LGBT] youth) to inform bullying prevention programming.

Role of Educators and School-Based Programming

Given the amount of time youth spend in school and the overall rates of school-based bullying, it is not surprising that teachers and other education support professionals play an important role in bullying prevention ( Bradshaw et al., 2013b ). Teachers often serve as implementers of programs as well as frontline interveners in bullying situations ( Goncy et al., 2014 ; Holt et al., 2013 ); however, they vary in their willingness to intervene and in their skills to intervene effectively ( Biggs et al., 2008 ; Bradshaw et al., 2009c ; Hektner and Swenson, 2011 ). In fact, there appears to be a disconnect between students' and educators' perceptions and experiences of bullying behavior. Several studies found that educators underestimated the impact and prevalence of bullying behavior ( Bradshaw et al., 2009c ), which in turn likely contributes to youth's hesitance to report bullying to adults at school. Furthermore, many adults lacked skills to intervene effectively, and potentially even overestimated their efficacy and ability to detect bullying-related problems. Studies have found that many youth perceived teachers as not effective in preventing or intervening in bullying situations ( Berguno et al., 2004 ; Bradshaw et al., 2009c ).

In contrast, teachers' perceived efficacy has been associated with an increased likelihood of intervening in a bullying situation, although this was also affected by perceived threat and the teachers' years of experience ( Duong and Bradshaw, 2013 ), as well as their feelings of connection to the school ( Bradshaw et al., 2013b ; O'Brennan et al., 2014 ). There is research to suggest that professional development can have a positive effect on teacher efficacy with respect to increasing teachers' willingness to intervene in bullying incidents ( Bell et al., 2010 ). Nevertheless, it is clear that more work is needed to better understand ways that educators can bridge with students to improve prevention and intervention in bullying situations.

Teachers are not the only adults working in schools or outside of schools who have a role to play in bullying prevention (see Box 5-1 ). There is emerging research on the important, but often overlooked, group of education support professionals (ESPs), including bus drivers, cafeteria workers, and other paraprofessionals, in bullying prevention ( Bradshaw et al., 2013b ). The U.S. Department of Education's Office of Safe and Healthy Students provides guidance on how bus drivers can effectively respond to and prevent bullying ( U.S. Department of Health and Human Services, 2015 ). These individuals are rarely provided training in bullying prevention and their school's policies related to bullying. They are seldom engaged in schoolwide bullying prevention efforts, despite witnessing rates of student bullying similar to teachers.

Who Are the Adult Professionals and Volunteers Who Work with Children and Adolescents?

School resource officers (SROs) are also an increasing presence in schools ( James and McCallion, 2013 ), but their engagement in prevention programming is rare. Most SROs are engaged primarily in law enforcement–related activities, such as patrolling school grounds, responding to crime/disorder reports, and investigating leads about crime ( Coon and Travis III, 2012 ; James et al., 2011 ). The SRO role is traditionally viewed as a triad of law enforcement, teacher, and counselor, so it makes sense that an officer can play a potentially important role on school safety teams and in bullying prevention efforts. However, few studies have examined their role in implementing anti-bullying policies and interventions ( James and McCallion, 2013 ; Robles-Piña and Denham, 2012 ). The limited research on this topic acknowledges a tension between two different perspectives. The first is that SROs should not be involved in bullying interventions because many acts that individuals report as bullying are not criminal matters ( Broll and Huey, 2015 ; Parr et al., 2012 ). In contrast, others view the SRO as not just a sworn law enforcement officer but also an important member of the school staff who can and should be trained to engage in teaching- and counselor-related activities ( Coon and Travis III, 2012 ; Robles-Piña and Denham, 2012 ). Although SROs are often called in when there is a problem, additional research is needed on how best to leverage their expertise and role to promote a positive school climate and prevent bullying.

The Role of Parents

Not surprisingly, parents play an important role in helping youth navigate social challenges and adapting to stress ( Collins et al., 2000 ). There is a large and growing body of research documenting the efficacy and effectiveness of preventive interventions that involve parents, particularly at the selective and indicated levels. However, the vast majority of these programs focus on youth violence prevention, social-emotional development, and academic outcomes, with virtually no RCT-design evaluations of programs that were developed specifically to prevent bullying. Yet, intervention research consistently highlights the importance of parents in shaping positive outcomes for youth. The meta-analysis by Ttofi and Farrington (2009) found that several family factors were important elements of effective bullying prevention programs, including parent training and informing parents about bullying. However, few of the evaluations of universal programs reviewed by the committee collected comprehensive data on the penetration or uptake of those parent-focused elements. For example, sending home information to parents and offering workshops is much easier than ensuring parents' engagement, program attendance, and actual use of those materials ( Bradshaw et al., 2009b ). It is quite possible that parent-focused programming for school-age youth is more efficient and effective at the selective and indicated levels than at the universal level ( Arseneault et al., 2010 ).

The notion that “violence begets violence” also applies to the need for interventions targeted to individuals who bully and are bullied by others. Espelage and colleagues (2012) examined the relationship between peer victimization and family violence in early adolescence and found that youth who were identified as poly-victims 9 or who reported relational bullying were more likely to also endorse witnessing domestic violence and being physically or sexually abused at home when compared to nonvictimized youth. Similarly, parents also need to be wary of behavior akin to bullying in the home, such as among siblings or cousins ( Jones et al., 2013 ), which speaks to the need for increased parent awareness of the signs and symptoms of bullying and its impact on the youth and family.

Hawley and Williford (2015) specifically called for the active and consistent involvement of parents in anti-bullying interventions, particularly with respect to the prevention of cyberbullying. In a study of late adolescent victims of bullying, Hemphill and colleagues (2014) found that having opportunities for prosocial involvement in the family lessened subsequent involvement in nonviolent antisocial behaviors. Wang and colleagues (2009) also found that parental support may protect adolescents from multiple forms of bullying, including cyberbullying, which makes parental involvement a potentially critical intervention target.

Health Care Professionals and Bullying Prevention and Intervention

Health care clinicians, including mental and behavioral health experts, can be important players in bullying prevention, especially when they can collaborate with teachers and other education professionals. Evidence of the physical, mental, and behavioral health issues of children who bully, are bullied, or observe bullying incidents ( Borowsky et al., 2013 ; Vessey et al., 2013 ; Wolke and Lereya, 2015 ) provides child health and mental health clinicians in community and acute care settings with knowledge to engage in bullying prevention interventions.

Child health care providers can address biological and psychological consequences of bullying in many ways ( Fekkes, 2006 ). Although their clinical roles and responsibilities may vary, community- and hospital-based child health care providers have opportunities to identify and support children, family members, and school personnel in need of care or advice. In addition to physicians and nurses, other health care providers, such as psychologists, dentists, social workers, physical therapists, occupational therapists, and speech and language professionals, may encounter children and youth who have been bullied, who bully, or who have been bystanders to bullying incidents.

Bullying raises complex issues for health care providers because of the associations among bullying and many physical, emotional, behavioral, and social issues such as depression, anxiety, suicide, psychosomatic complaints, substance abuse, school truancy and delinquency ( Borowsky et al., 2013 ; Dale et al., 2014 ; Gini and Pozzoli, 2009 ). Clinicians in schools, clinics, primary care practices, schools, and school-based health centers have opportunities to discuss bullying during visits for well-child care, annual school or sports exams, and routine acute care ( Magalnick and Mazyck, 2008 ). Because middle school students experience higher rates of being bullied than students in high school ( Robers et al., 2015 ), encounters with early adolescents might be especially important for prevention and anticipatory guidance. Because of possible long-term effects of bullying (and other early childhood adversity or toxic stresses) ( Lereya et al., 2015 ; Shonkoff et al., 2012 ), youth in high school might have emotional or mental health issues that relate to previous bullying incidents.

In addition to children and youth who have been bullied, those who bully may have specific health care needs. They might have family situations that are characterized by violence, abuse, neglect, low socioeconomic status, or other stressful issues. Perpetrating bullying might be the manifestation of other underlying issues, such as mental or behavioral health problems, alienation, homelessness, or undetected learning disabilities.

Because some children internalize victimization or emotional difficulties ( Adams et al., 2013 ; Borowsky et al., 2013 ), the physical or emotional impacts of bullying on children who bully, have been bullied, or have been bystanders to bullying might not be readily apparent to family members, educators, or health care professionals. Therefore, during child health encounters, clinicians might inquire about changes in behavior, appetite, and sleep and about children's attitudes toward school as ways of screening for involvement with bullying.

Given possible somatization of symptoms among children who have been bullied ( Gini and Pozzoli, 2009 ), health care professionals who see children for purported acute care problems that don't show evidence of illness might consider experience of being bullied among many other possible reasons for the symptoms claimed for the visit or for parents' or children's concerns. Children and youth with certain diagnoses and conditions might be at higher risk for being targets of bullying than others. This includes children with chronic illnesses (e.g., diabetes, obesity, or cerebral palsy), autism spectrum disorders, attention deficit disorders, learning disabilities, congenital anomalies, and behavioral or emotional illnesses ( Adams et al., 2013 ; Pittet et al., 2009 ; Storch et al., 2006 ; Twyman et al., 2010 ).

Health care professionals might also consider protective factors for youth involved with bullying and could provide guidance to parents and children regarding the importance of certain supports. For example, parent connectedness and perceived caring by friends and nonparental adults can be protective factors for some children and youth involved with bullying ( Borowsky et al., 2013 ).

Because most bullying occurs at school ( Robers et al., 2015 ), school nurses are often on the frontlines of caring for children and youth involved in bullying. They might be the first health care professional involved with children and youth who have been bullied in school settings, especially some groups of children who are particularly at risk. As noted above, counselors are often called upon to respond to bullying prevention situations, but they rarely use evidence-based bullying-intervention approaches when providing counseling services to youth who bully or who are victims of bullying. Additional research is needed on the selective and indicated mental health interventions referenced above (e.g., CBITS, MST, FFT, Wraparound/Case Management), as they, too, may be effective for youth involved in bullying. Moreover clinicians should inquire about bullying, even when the youth presents with symptoms that seem consistent with other mental health problems, as bullying may be a contributing factor.

Bullying prevention intervention presents inherent challenges to pediatric health care providers. For example, if a health care professional suspects or identifies a child who has been involved with bullying, effective mechanisms for referral and collaboration with education and other professionals are typically lacking. Appropriate counseling or other services may be in short supply in communities, especially in remote rural areas or other underserved areas. Sharing patient or student information across settings presents legal and logistical challenges. Involvement of parents may be difficult. Reporting mechanisms under state and local laws and other policies might not pertain to situations in which a child health professional detects that bullying has occurred. Finally, best practices or procedures for follow-up by health care professionals are lacking from the evidence-based literature.

Other challenges reside in integrating bullying prevention intervention into the daily responsibilities and realities of health care professionals, regardless of setting. Mechanisms to compensate for time spent on screening, referral, counseling, follow-up of bullying incidents among patients and school or community education may lack public or private sources of financing and reimbursement.

Organizations such as the American Academy of Pediatrics and the National Association of School Nurses have issued statements on the bullying prevention role of their respective members ( Committee on Injury, Violence, and Poison Prevention, 2009 ; DeSisto and Smith, 2015 ). Interdisciplinary collaboration in this area and identification of effective intervention for best child health outcomes need further study.

The Role of Media

As noted in previous sections of this report, the media serves as both a positive and negative influence on youth with respect to bullying behavior. There are relatively few RCT studies of social norm campaigns focused on bullying awareness and prevention, despite the large body of public health research suggesting such approaches may be effective at shifting norms, attitudes, and behavior ( Wakefield et al., 2010 ). For example, there have been programs that have delivered normative information as a primary tool for changing socially significant behaviors, such as alcohol consumption ( Neighbors et al., 2004 ), tobacco and drug use ( Donaldson et al., 1994 ), and gambling ( Larimer and Neighbors, 2003 ). Additional work is clearly needed to better understand both the risks and the opportunities associated with media-focused campaigns and social norms–based interventions in relation to bullying.

Social Media

Social media offers both intervention challenges and opportunities for cyberbullying. A challenge is that social media provides a platform on which bullying can occur. This may include bullying by private messages sent within a site, by posting public and embarrassing content about a peer, or by creating a “false” profile of the target and posting embarrassing or untruthful content. Because of the multimedia capacity of these sites, embarrassing content may include text, photos, or even video. Social media allows this content to be spread rapidly within a network, as well as shared through others' networks. Even if the original post is removed, content that has been shared may be difficult to locate and remove.

Social media also provides opportunities to prevent and intervene with bullying. Organizations dedicated to intervention for preventing and treating consequences of bullying may use social media to maintain a presence in those electronic communities where bullying is taking place and to use their platforms for positive messages. Social media may be used to promote prevention messages, such as the It Gets Better campaign, 10 although the committee recognizes that this use of social media, as well as many other intervention approaches, needs further evaluation to determine if it helps or harms children involved in bullying. Social media may also provide opportunities for those who have experienced bullying to directly communicate with an organization. While limited studies have evaluated these efforts, the platform of social media provides opportunities to test the effectiveness of these approaches.

Systematic reviews and meta-analyses over the past decade recommend that the most likely effective bullying prevention programs are whole school, multicomponent programs that combine elements of universal and targeted strategies ( Bradshaw, 2015 ; Rigby and Slee, 2008 ; Vreeman and Carroll, 2007 ). Yet, most meta-analyses of bullying programs show mixed effects and small to moderate effect sizes, at best. When the effects are positive, they are more likely to be effects on attitudes, knowledge, and perceptions, rather than effects on bullying behavior such as experience as a perpetrator or target of bullying. If a universal program does include elements intended to reduce related risk factors or enhance protective factors such as social competence, these elements tend to be embedded in the program so that it is not easy to discern which program components produce desired results for bullying-related behavior. The effects of preventive interventions tend to be greatest for the highest-risk youth, even for interventions in early elementary school ( Bradshaw et al., 2015 ; Limbos et al., 2007 ; Petras et al., 2008 ).

Few bullying programs include specific intervention components for youth at risk for involvement in bullying or for youth already involved in bullying, whether as perpetrators or targets (or both). Other school-based interventions tend to target behaviors associated with bullying (e.g., aggressive behavior, social skill development) or the mental health problems associated with being buillied (depression, anxiety, academic failure). Few of the selective and indicated preventive interventions for identified perpetrators (aggressive youth) or targets (youth with mental health issues or at risk for suicide) are school-based, so there needs to be stronger connections between schools, families, and community-based treatment programs. Moreover, these programs need to be further evaluated with regard to impacts on bullying behavior, as they were originally developed to address violence and mental health problems. Yet, many of these problems co-occur and have overlapping risk and protective factors, which suggests these other evidence-based selective and indicated violence prevention models may also demonstrate positive effects for youth involved in bullying.

There is still a dearth of intervention research on programs related to cyberbullying and on programs targeted to vulnerable populations such as LGBT youth, youth with chronic health problems, or youth with developmental disabilities such as autism ( Minton, 2014 ). The role of peers in interventions for at-risk students or for those who are perpetrators or targets needs further clarification, whether that is for peers as bystanders or peers as interventionists, or peers as fellow perpetrators, or targets. Despite increasing interest in programs aimed at increasing equity, shifting norms related to stereotypes, or the use of restorative practices, there are few fully developed models that target these issues, and virtually no randomized studies documenting outcomes associated with these approaches. Additional work is needed on these models to determine whether broader dissemination of these approaches is warranted.

Schools may want to consider implementing a multicomponent program that focuses on school climate, positive behavior support, social and emotional learning, or violence prevention more generally, rather than implementing a bullying-specific preventive intervention, as these more inclusive programs may reach a broader set of outcomes for students and the school environment. Tiered preventive interventions appear to be a promising model for schools, but the lack of rigorously tested selective and indicated preventive interventions focused specifically on bullying means that other violence and mental health prevention models should be leveraged and integrated to increase efficiency. Regardless of the model selected, issues related to implementation fidelity, spanning initial buy-in, and adoption through sustainability, need careful consideration and an authentic investment of resources in order to achieve outcomes.

• FINDINGS AND CONCLUSIONS

Finding 5.1: The most likely effective bullying prevention programs are whole school, multicomponent programs that combine elements of universal and targeted strategies. Finding 5.2: The findings from meta-analyses of bullying prevention programs have been mixed, with the largest effects observed for whole school programs implemented in Europe, as compared to programs tested in the United States. The challenge of designing and delivering effective bullying prevention programs in the United States may be due to the greater social and economic complexities, including greater income disparities and racial/ethnic heterogeneity in the United States, compared with European countries. More research is needed in the United States focusing on developing and testing novel models for bullying prevention programming and the identification of strategies for increasing fidelity of implementation and effect sizes. Finding 5.3: Research on the role of peers in bullying prevention interventions has been mixed, with some studies suggesting the need for more peer-based interventions, such as friendship-making components, and others calling for more caution because peer-based interventions have produced null or even iatrogenic effects. Finding 5.4: Few bullying programs include specific intervention components for youth at risk for bullying (e.g., ethnic minorities, sexual minorities, youth with disabilities), or for youth already involved in bullying as perpetrators or targets (or both), and the studies examining impacts of bullying prevention programs for these subpopulations are rare. Finding 5.5: Few of the selective and indicated preventive interventions for identified perpetrators (aggressive youth) or targets (e.g., bullied youth with mental health issues or at risk for suicide) are school-based, so there needs to be stronger connections among schools, families, and community-based treatment programs. Finding 5.6: There is a growing interest in research documenting the effectiveness of bullying and youth violence preventive interventions that involve parents, particularly at the selective and indicated levels. However, to date few such family-focused programs have been developed or tested in relation to impacts specifically on bullying. Finding 5.7: There is emerging international research that suggests a variety of models may be effective at reducing both cyberbullying and traditional bullying.

Conclusions

Conclusion 5.1: The vast majority of research on bullying prevention programming has focused on universal school-based programs; however, the effects of those programs within the United States appear to be relatively modest. Multicomponent schoolwide programs appear to be most effective at reducing bullying and should be the types of programs implemented and disseminated in the United States. Conclusion 5.2: Most of the school, family, and community-based prevention programs tested using randomized controlled trial designs have focused on youth violence, delinquency, social-emotional development, and academic outcomes, with limited consideration of the impacts on bullying specifically. However, it is likely that these programs also produce effects on bullying, which have largely been unmeasured and therefore data on bullying outcomes should be routinely collected in future research. Conclusion 5.3: There has been limited research on selective and indicated models for bullying intervention programming, either inside or outside of schools. More attention should be given to these interventions in future bullying research. Conclusion 5.4: The extant, empirically supported selective and indicated preventive interventions for violence and delinquency should also be leveraged to meet the needs of students involved in bullying, or those experiencing the mental and behavioral health consequences of bullying. These programs should be integrated into a multi-tiered system of supports for students at risk for engaging in or experiencing the consequences of bullying. Conclusion 5.5: The role of peers in bullying prevention as bystanders and as intervention program leaders needs further clarification and empirical investigation in order to determine the extent to which peer-led programs are effective and robust against potentially iatrogenic effects. Conclusion 5.6: The role of online resources or social marketing campaigns in bullying prevention or intervention needs further clarification and empirical investigation in order to determine whether these resources and programs are effective. Conclusion 5.7: Since issues of power and equity are highly relevant to bullying, fully developed prevention models that target these issues as an approach for preventing bullying should be conducted using randomized controlled trial designs. Conclusion 5.8: Additional research is needed on the effectiveness of programs targeted to vulnerable populations such as lesbian, gay, bisexual, and transgender youth, youth with chronic health problems such as obesity, or those with developmental disabilities (e.g., autism), as well as variation in the effectiveness of universal programs for these subpopulations. Conclusion 5.9: There is a strong need for additional programming and effectiveness research on interdisciplinary collaboration with health care practitioners, parents, school resource officers, community-based organizations (e.g., scouts, athletics), and industry to address issues related to bullying and cyberbullying. Conclusion 5.10: Regardless of the prevention program or model selected, issues related to implementation fidelity, spanning initial buy-in and adoption through taking programs to scale and sustainability, need careful consideration and an authentic investment of resources in order to achieve outcomes and sustained implementation.

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Clinicians and policy makers define efficacy trials as trials that determine whether “an intervention produces expected results under ideal circumstances” and effectiveness trials as trials that “measure the degree of beneficial effect under ‘real world' clinical settings” ( Gartlehner et al., 2006 ).

The committee includes details of studies where possible, in particular if the study employed a RCT design and where effect sizes are reported or control groups were used. We encourage the reader to refer to the original studies for additional details about study design, population, measurement, variables included in analyses, etc.

Peer victimization was assessed using the three-item University of Illinois Victimization Scale (Espelage et al., 2013).

The SDQ is a brief behavioral screening questionnaire that asks about 25 attributes, some positive and others negative ( Goodman, 1997 ).

See http://www ​.stopcyberbullying.org [April 2016].

See http://www ​.itgetsbetter.org/ [April 2016].

See Put a Stop to Bullying at https://www ​.facebook.com/safety/bullying [February 2016].

See Learn How to Address Abuse at https://help ​.instagram ​.com/527320407282978/ [October 2015].

The term “poly-victim” for individuals who experience multiple types of victimization is discussed in Chapter 4 .

The It Gets Better Program employs user-generated media to reach LGBT youth and ameliorate depression and suicidal thoughts among these individuals during their adolescent years. See http://www ​.itgetsbetter.org [April 2016].

• Cite this Page Committee on the Biological and Psychosocial Effects of Peer Victimization: Lessons for Bullying Prevention; Board on Children, Youth, and Families; Committee on Law and Justice; Division of Behavioral and Social Sciences and Education; Health and Medicine Division; National Academies of Sciences, Engineering, and Medicine; Rivara F, Le Menestrel S, editors. Preventing Bullying Through Science, Policy, and Practice. Washington (DC): National Academies Press (US); 2016 Sep 14. 5, Preventive Interventions.
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9 facts about bullying in the U.S.

Many U.S. children have experienced bullying, whether online or in person. This has prompted discussions about schools’ responsibility to curb student harassment , and some parents have turned to home-schooling or other measures to prevent bullying .

Here is a snapshot of what we know about U.S. kids’ experiences with bullying, taken from Pew Research Center surveys and federal data sources.

Pew Research Center conducted this analysis to understand U.S. children’s experiences with bullying, both online and in person. Findings are based on surveys conducted by the Center, as well as data from the Bureau of Justice Statistics, the National Center for Education Statistics and the Centers for Disease Control and Prevention. Additional information about each survey and its methodology can be found in the links in the text of this analysis.

Bullying is among parents’ top concerns for their children, according to a fall 2022 Center survey of parents with children under 18 . About a third (35%) of U.S. parents with children younger than 18 say they are extremely or very worried that their children might be bullied at some point. Another 39% are somewhat worried about this.

Of the eight concerns asked about in the survey, only one ranked higher for parents than bullying: Four-in-ten parents are extremely or very worried about their children struggling with anxiety or depression.

About half of U.S. teens (53%) say online harassment and online bullying are a major problem for people their age, according to a spring 2022 Center survey of teens ages 13 to 17 . Another 40% say it is a minor problem, and just 6% say it is not a problem.

Black and Hispanic teens, those from lower-income households and teen girls are more likely than those in other groups to view online harassment as a major problem.

Nearly half of U.S. teens have ever been cyberbullied, according the 2022 Center survey of teens . The survey asked teens whether they had ever experienced six types of cyberbullying. Overall, 46% say they have ever encountered at least one of these behaviors, while 28% have experienced multiple types.

The most common type of online bullying for teens in this age group is being called an offensive name (32% have experienced this). Roughly one-in-five teens have had false rumors spread about them online (22%) or were sent explicit images they didn’t ask for (17%).

Teens also report they have experienced someone other than a parent constantly asking them where they are, what they’re doing or who they’re with (15%); being physically threatened (10%); or having explicit images of them shared without their consent (7%).

Older teen girls are especially likely to have experienced bullying online, the spring 2022 survey of teens shows. Some 54% of girls ages 15 to 17 have experienced at least one cyberbullying behavior asked about in the survey, compared with 44% of boys in the same age group and 41% of younger teens. In particular, older teen girls are more likely than the other groups to say they have been the target of false rumors and constant monitoring by someone other than a parent.

They are also more likely to think they have been harassed online because of their physical appearance: 21% of girls ages 15 to 17 say this, compared with about one-in-ten younger teen girls and teen boys.

White, Black and Hispanic teens have all encountered online bullying at some point, but some of their experiences differ, the spring 2022 teens survey found. For instance, 21% of Black teens say they’ve been targeted online because of their race or ethnicity, compared with 11% of Hispanic teens and 4% of White teens.

Hispanic teens are the most likely to say they’ve been constantly asked where they are, what they’re doing or who they’re with by someone other than a parent. And White teens are more likely than Black teens to say they’ve been targeted by false rumors.

The sample size for Asian American teens was not large enough to analyze separately.

During the 2019-2020 school year, around two-in-ten U.S. middle and high school students said they were bullied at school . That year, 22% of students ages 12 to 18 said this, with the largest shares saying the bullying occurred for one day only (32%) or for between three and 10 days (29%), according to the most recent available data from the Bureau of Justice Statistics (BJS) and the National Center for Education Statistics (NCES).

Certain groups of students were more likely to experience bullying at school. They include girls, middle schoolers (those in sixth, seventh or eighth grade), and students in rural areas.  

The most common types of at-school bullying for all students ages 12 to 18 were being made the subject of rumors (15%) and being made fun of, called names or insulted (14%).

The classroom was the most common location of bullying that occurred at school in 2019-2020, the BJS and NCES data shows. This was the case for 47% of students ages 12 to 18 who said they were bullied during that school year. Other frequently reported locations included hallways or stairwells (39%), the cafeteria (26%) and outside on school grounds (20%).

Fewer than half (46%) of middle and high schoolers who were bullied at school in 2019-2020 said they notified a teacher or another adult about it, according to the BJS and NCES data. Younger students were more likely to tell an adult at school. Around half or more of sixth, seventh and eighth graders said they did so, compared with 28% of 12th graders.

Students who reported more frequent bullying were also more likely to notify an adult at school. For instance, 60% of those who experienced bullying on more than 10 days during the school year told an adult, compared with 35% of those who experienced it on one day.

In 2021, high schoolers who are gay, lesbian or bisexual were about twice as likely as their heterosexual counterparts to say they’d been bullied, both at school and online, according to the Centers for Disease Control and Prevention . In the 12 months before the survey, 22% of high school students who identify as gay, lesbian or bisexual – and 21% of those who identify as questioning or some other way – said they were bullied on school property. That compares with 10% of heterosexual students. The data does not include findings for transgender students.

The trend is similar when it comes to electronic bullying through text or social media: 27% of high school students who identify as lesbian, gay or bisexual say they experienced this in the 12 months before the survey, as did 23% of those who identify as questioning or some other way. That compares with 11% of those who identify as heterosexual.

• Online Harassment & Bullying

Katherine Schaeffer is a research analyst at Pew Research Center .

72% of U.S. high school teachers say cellphone distraction is a major problem in the classroom

U.s. public, private and charter schools in 5 charts, a quarter of u.s. teachers say ai tools do more harm than good in k-12 education, most americans think u.s. k-12 stem education isn’t above average, but test results paint a mixed picture, about 1 in 4 u.s. teachers say their school went into a gun-related lockdown in the last school year, most popular.

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What Are the Different Types of Bullying?

Cynthia Vinney, PhD is an expert in media psychology and a published scholar whose work has been published in peer-reviewed psychology journals.

Ann-Louise T. Lockhart, PsyD, ABPP, is a board-certified pediatric psychologist, parent coach, author, speaker, and owner of A New Day Pediatric Psychology, PLLC.

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What Is Bullying?

Mental health effects of bullying, types of bullying.

Bullying is most often recognized as a form of physically and verbally aggressive behavior that school children endure from their peers. However, there are actually six different kinds of bullying: physical, verbal, relational, cyber, sexual, and prejudicial.

These types of bullying overlap and a bully may use more than one form to abuse a victim. Moreover, bullying isn't limited to kids and teenagers. Adults can also be guilty of bullying.

This article will start by providing a general definition of bullying and discuss its prevalence and consequences. It will then explain each of the six types of bullying.

Bullying is defined as any intentional, repeated aggressive behavior directed by a perpetrator against a target in the same age group.

Power Imbalances

One of the most noteworthy components of bullying is an imbalance of power between the bully and their victim.

Sometimes the power imbalance is obvious when, for example, a bigger, stronger kid bullies a weaker, smaller kid or when a group of people bullies a single individual. However, sometimes the power imbalance is more difficult to discern because it involves less obvious factors, such as differences in popularity, intelligence, or ability, or knowledge of the information the victim finds embarrassing.

Bullying Statistics

Bullying is widespread and can negatively impact both bullying victims and the bullies themselves.

A 2019 survey by the Centers for Disease Control and Prevention (CDC) found that 19.5% of ninth through twelfth graders were bullied on school property in the 12 months prior to completing the questionnaire.

Moreover, a study by the World Health Organization (WHO) conducted in 2013 and 2014 in 42 countries in Europe and North America found that, on average, 14% of 11-year-old boys and 11% of 11-year-old girls were bullied at least twice in the previous two to three months.

People who are bullied can experience a plethora of short- and long-term problems , including depression and anxiety, social withdrawal , substance abuse, difficulties at school or work such as underachieving and poor attendance, and even suicide .

If you are having suicidal thoughts, contact the National Suicide Prevention Lifeline at 988 for support and assistance from a trained counselor. If you or a loved one are in immediate danger, call 911.

For more mental health resources, see our National Helpline Database .

In addition, children who are targets of bullying may become victims or perpetrators of violence later in life. Meanwhile, those who bully others are more likely to get into fights and vandalize property, abuse drugs and alcohol, have criminal convictions in adulthood , and abuse their romantic partners and children .

Even people who simply observe bullying can experience issues, including mental health difficulties and increased substance use.

Bullying falls into six categories, some of which are more obvious than others. They include:

• Physical bullying
• Verbal bullying
• Relational bullying

Cyberbullying

• Sexual bullying
• Prejudicial bullying

Physical Bullying

Physical bullying is the most obvious type of bullying and what many people think of when they imagine this kind of aggression .

Physical bullying involves any assault on a person's body, including hitting, kicking, tripping, or pushing. It can also extend to inappropriate hand gestures or stealing or breaking a victims' belongings.

Physical bullying is perpetrated by an individual or group of individuals who are bigger or stronger than the individual being targeted.

If a physical altercation happens between two people of similar size and strength, it's not considered physical bullying.

Studies have shown that males are more likely to be involved in physical bullying than females. For example, a study of children between 7 and 14 years old found that boys were more likely to be hit, punched, or kicked and to have their belongings taken than girls.

Another study of children between 7 and 10 years old showed that boys were more likely to be the perpetrators of physical bullying than girls.

Verbal Bullying

Verbal bullying involves using spoken or written words to insult or intimidate a victim. It includes name-calling, teasing, and even threats.

Research indicates that verbal bullying using insults is the most common form of bullying experienced by 7- to 10-year-old children and that boys are more likely to be verbally bullied than girls.

Verbal bullying isn't always easy to recognize because it often takes place when authority figures aren't around. Moreover, a bully can pass it off as good-natured ribbing between friends. As a result, it can be difficult for the victim to prove. Therefore, this form of bullying can become a long-term source of stress and anxiety.

Relational Bullying

Relational bullying, which is also referred to as relational aggression or social bullying, involves actions intended to harm a victim's reputation or relationships. It can include embarrassing the victim in public, spreading rumors, purposely leaving them out of social situations, or ostracizing them from a group. Unlike more overt types of bullying, it is especially sly and insidious because it involves social manipulation.

Relational bullying is often associated with so-called "mean girls." However, while research has shown girls are more often the victims of relational bullying than boys, both boys and girls are equally likely to be perpetrators.

On the other hand, studies suggest that girls who engage in relational bullying have worse adjustment problems , including issues maintaining fulfilling and positive relationships.

Relational bullying can lead to isolation, loneliness, depression, and social anxiety, yet research indicates that school counselors tend to feel relational bullying is less serious and have less empathy for victims of relational bullying than victims of physical and verbal bullying. This may be because the severity of relational bullying is more challenging to detect.

Cyberbullying is bullying that happens via electronic devices like computers, smart phones, and tablets. It can take place over text messages, social media, apps, or online forums and involves posting or sending harmful content, including messages and photos, and sharing personal information that causes humiliation.

Research by the Cyberbullying Research Center shows that 15% of 9- to 12-year-olds and 37% of 13- to 17-year-olds have experienced cyberbullying at some point in their lives.

In-person bullying is still more prevalent than cyberbullying but cyberbullying is a growing problem. Not only are perpetrators of cyberbullying less likely to be caught, but the online nature of cyberbullying can also be especially damaging to victims.

People have their devices on them all day, every day, so if they're being cyberbullied, they never get a break, even in their homes.

Similarly, targets of cyberbullying may be constantly reminded of the online bullying they've endured because, even if they block the cyberbully, others may see and share the evidence.

Sexual Bullying

Sexual bullying is online or in-person bullying that involves sexual comments or actions, including sexual jokes and name-calling, crude gestures, spreading sexual rumors, sending sexual photos or videos, and touching or grabbing someone without permission.

Sexual bullying and harassment are remarkably widespread. A 2019 study found that 81% of women and 43% of men experienced sexual harassment or assault at some point in their lifetime.

Meanwhile, sexting, sending or receiving sexually explicit messages or images between electronic devices, is becoming increasingly common.

Research shows that among kids between the ages of 11 and 17, 15% of them sent sexts and 27% received sexts; the prevalence of the behavior increases as adolescents age.

When sexts are sent without consent, such as when private nude photos or videos of an individual are widely shared among a peer group, it can lead to sexual bullying and even sexual assault .

Prejudicial Bullying

Prejudicial bullying involves online or in-person bullying based on the target's race, ethnicity, religion, or sexual orientation . It is based on stereotypes and is often a result of the belief that some people deserve to be treated with less respect than others.

Though prejudicial bullying has been studied less than other types of bullying, research indicates that ethnic and sexual minorities are more likely to be bullied than their peers.

However, ethnic minorities that attend more ethnically diverse schools experience less bullying than those in schools that are more ethnically homogenous.

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Jacobsen KE, Bauman S. Bullying in Schools: School Counselors’ Responses to Three Types of Bullying Incidents .  Professional School Counseling . 2007;11(1):1-9. doi:10.1177/2156759x0701100101

StopBullying.gov. What Is Cyberbullying?

Patchin JW, Hinduja S. Tween Cyberbullying in 2020 . Cyberbullying Research Center. 2020.

Patchin JW. 2019 Cyberbullying Data . Cyberbullying Research Center. 2019.

Graber D. Raising Humans in a Digital World: Helping Kids Build a Healthy Relationship with Technology . HarperCollins Leadership; 2019.

Stop Street Harassment. National Studies .

Madigan S, Ly A, Rash CL, Van Ouytsel J, Temple JR. Prevalence of Multiple Forms of Sexting Behavior Among Youth: A Systematic Review and Meta-Analysis .  JAMA Pediatr . 2018;172(4):327-335. doi:10.1001/jamapediatrics.2017.5314

Menesini E, Salmivalli C. Bullying in Schools: The State of Knowledge and Effective Interventions .  Psychology, Health & Medicine . 2017;22(sup1):240-253. doi: 10.1080/13548506.2017.1279740

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Warning Signs for Bullying

There are many warning signs that may indicate that someone is affected by bullying—either being bullied or bullying others. Recognizing the warning signs is an important first step in taking action against bullying. Not all children who are bullied or are bullying others ask for help.

It is important to talk with children who show signs of being bullied or bullying others . These warning signs can also point to other issues or problems, such as depression or substance abuse. Talking to the child can help identify the root of the problem.

Signs a Child Is Being Bullied

Look for changes in the child. However, be aware that not all children who are bullied exhibit warning signs.

Some signs that may point to a bullying problem are: 

• Unexplainable injuries
• Lost or destroyed clothing, books, electronics, or jewelry
• Frequent headaches or stomach aches, feeling sick or faking illness
• Changes in eating habits, like suddenly skipping meals or binge eating. Kids may come home from school hungry because they did not eat lunch.
• Difficulty sleeping or frequent nightmares
• Declining grades, loss of interest in schoolwork, or not wanting to go to school
• Sudden loss of friends or avoidance of social situations
• Feelings of helplessness or decreased self esteem
• Self-destructive behaviors such as running away from home, harming themselves, or talking about suicide

If you know someone in serious distress or danger, don’t ignore the problem. Get help right away .

Signs a Child is Bullying Others

Kids may be bullying others if they:   

• Get into physical or verbal fights
• Have friends who bully others
• Are increasingly aggressive
• Get sent to the principal’s office or to detention frequently
• Have unexplained extra money or new belongings
• Blame others for their problems
• Don’t accept responsibility for their actions
• Are competitive and worry about their reputation or popularity

Why don't kids ask for help?

Statistics from the  2018 Indicators of School Crime and Safety - PDF  show that only 20% of school bullying incidents were reported. Kids don’t tell adults for many reasons:

• Bullying can make a child feel helpless. Kids may want to handle it on their own to feel in control again. They may fear being seen as weak or a tattletale.
• Kids may fear backlash from the kid who bullied them.
• Bullying can be a humiliating experience. Kids may not want adults to know what is being said about them, whether true or false. They may also fear that adults will judge them or punish them for being weak.
• Kids who are bullied may already feel socially isolated. They may feel like no one cares or could understand.
• Kids may fear being rejected by their peers. Friends can help protect kids from bullying, and kids can fear losing this support.

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How is Bullying Defined?

60-second answer.

Bullying is when someone aggressively uses their “power” to target another individual with repeated, unwanted words or actions. Those targeted are hurt either physically or emotionally and have a hard time stopping what is happening to them.

Students often describe bullying as when “someone makes you feel less about who you are as a person.”

Note: Definitions vary greatly. These are not legal definitions. Find your state’s law and definition at StopBullying.gov

What is bullying? At first glance, it might appear that this behavior is easy to define. A common image of bullying might be of a physically intimidating teen beating up a smaller classmate or one child shoving another inside a hallway locker. While these examples are still considered bullying, it's important to know that bullying behavior can be much more complex and varied than historical stereotypes.

• hurts or harms another person physically or emotionally,
• those targeted by the behavior have difficulty stopping the action directed at them and struggle to defend themselves, and
• the student demonstrating the bullying behavior can have more “power” in ways such as higher social status, is physically larger, has access to embarrassing information, or is emotionally intimidating, and
• the behavior is repeated or has the potential to be repeated
• The types of bullying: The behavior can be overt and direct, with physical behaviors such as fighting, hitting, or name calling, or it can be covert with emotional-social interactions such as gossiping or leaving someone out on purpose. Bullying can also happen in person or through technology on digital devices like phones, computers, and tablets; and in apps, texts, social media, or gaming.
• Distinction about amount and duration: Many definitions indicate that bullying is repeated or chronic with the behavior directed at an individual over a period of time. However, the reality is that bullying can also be circumstantial, the result of a single situation, such as a social media post reaching thousands.
• Perception of aggression: Aggressive behavior can be defined as forceful words or actions. For bullying, it is important to note not all bullying behavior will be immediately evaluated as “aggressive.” Acts such as physical fighting and name calling are easy to recognize while acts that exhibit more covert and subtle behaviors are often difficult to assess but no less aggressive in their impact on the target (e.g., manipulation of how someone is perceived, damaging someone’s reputation or status, or spreading false information).
• Intent versus impact: Some definitions may include that behavior is considered bullying if the intent is to willfully and knowingly cause hurt or harm. However, in some instances intent can be difficult to identify and assess by those involved in the situation: the person doing the bullying, the target, the witnesses, or even adults who receive the reports of bullying. While it is important to address the intention or purpose behind the bullying behavior, it is equally important to look at the impact of the behavior on the target. Focusing on impact verses intent can be useful in situations where the person bullying indicates that, for example, “it was just a joke” or that the target “took it the wrong way.”
• The implications for all students: It’s important to note that bullying is not just about the implications for those targeted by the behaviors, but is also about the behavior’s impact on all students in the school including those who witness the behavior and those that engage in the behavior.
• Additional factors: These can include the differentiation between bullying and harassment, enumeration of protected classes, statements around the use of technology, how the behavior impacts educational performance, and the physical locations that would fall under the jurisdiction of school sanctions.

Students often describe bullying as when “someone makes you feel less about who you are as a person.”

Note: This is not a legal definition, but rather a way to help understand and identify bullying. For your school’s definition, check the district’s bullying prevention policies. For a legal definition, consult your state’s law on bullying at StopBullying.gov .

Posted November, 2016

How is Bullying Defined? 60 Second Response | PACERTalks About Bullying | Season 3, Episode 1

Welcome to Season 3 of PACERTalks About Bullying, our weekly video series all about bullying prevention – including informational content, interviews, and more! To kick off this season, we begin with the basics by answering in 60 seconds or less the question “How is bullying defined?”

How is Bullying Defined? 60 Second Response | PACERTalks About Bullying | Season 3, Episode 2

Students respond to the question, “How do you define bullying?”

PAPER BAG LOVE | Anissa Yu

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What Is Bullying | Mrs. McBride’s Kindness Club at Mapleshade School

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Bullying | Grade 5 Class at Empire Public School; Waterloo, Ontario, Canada

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Bullying: A Module for Teachers

• Schools and Classrooms

Sandra Graham, PhD, UCLA

Children's social lives — and their academic lives go hand in hand, whether or not they have friends, whether they are accepted or rejected by their peers, or whether they are victims or perpetrators of aggression. This means that we cannot fully understand the factors that lead to academic achievement without knowing about the social environment of children in school. For example, children who have few friends, who are actively rejected by the peer group, or who are victims of bullying are unlikely to have the cognitive and emotional resources to be able to do well in school (Juvonen & Graham, 2014).

Bullying can have long-term effects on students' academic achievement. Commonly labeled as peer victimization or peer harassment, school bullying is defined as physical, verbal, or psychological abuse of victims by perpetrators who intend to cause them harm (Olweus, 1993). The critical features that distinguish bullying from simple conflict between peers are: intentions to cause harm, repeated incidences of harm and an imbalance of power between perpetrator and victim. Some examples of an imbalance of power are physically stronger youth picking on weaker peers, older students harassing younger students, or numerical majority group members deriding numerical minority members. Hitting, kicking, shoving, name-calling, spreading of rumors, exclusion and intimidating gestures (e.g., eye rolling) by powerful peers are all examples of harassment that is physical, verbal, or psychological in nature. Some definitions of bullying state that the harassment must be repeated over time. However, even a single traumatic incident of peer victimization can be painful and raise fears about continued abuse.

This definition of school bullying does not include more lethal sorts of peer-directed hostilities. Although some widely-publicized school shootings may have been precipitated by a history of peer abuse, they remain rare events (Indicators of School Crime and Safety: 2012). The focus of this module is on more typical and widespread types of bullying that affect the lives of many children and that have been labeled as a public health concern by the American Medical Association.

How widespread?

According to national surveys (e.g., Center for Disease Control, 2012; NCES, 2013):

• 70 percent of middle and high school students have experienced bullying at some point.
• 20-40 percent report having bullied or been part of bullying during the school year.
• 27 percent report being harassed for not conforming to sexually stereotypical behavior.
• 5-15 percent of youth are chronic victims.
• 7-12 percent are chronic bullies.

How serious?

• 60 percent of elementary and secondary school students rate bullying as a major problem affecting their lives.
• Most 5th-12th graders are more concerned about emotional maltreatment and social cruelty from peers than anything else including academic achievement.
• Some recent school shootings have been traced back to a history of peer abuse.
• Peer harassment is designated as a Public Health Concern by The American Medical Association.
• In light of such statistics and growing public concern, it is important that teachers have a better understanding of bullying and what they can do to both prevent it and intervene when it occurs.
• Respond to any bullying incident that you witness. Most bullying takes place in "unowned spaces" like hallways, playgrounds and restrooms where adult supervision is minimal (Astor, Meyer, & Behre, 1999). It is important for teachers to be more visible in these places and to respond to all bullying incidents that they witness. A response by a teacher communicates to bullies that their actions are not acceptable and it helps victims feel less powerless about their predicament. The frequent presence of teachers in all areas of the school helps give students a feeling of safety. Teachers should also keep an eye on students who are physically smaller than their peers, or who behave or look different from others, since these variables often serve as risk factors for bullying (Jvonen & Graham, 2014).
• Use witnessed bullying incidents as "teachable moments." Teachable moments are defined as situations that open the door for conversations with students about difficult topics (CITE?). These may include: why many young people play bystander roles and/or are unwilling to come to the aid of victims, how social ostracism can be a particularly painful form of peer abuse, and why bullies are sometimes popular among their peers. An effective way to send the message that bullying will not be tolerated is to engage students in these difficult dialogues rather than to quickly and harshly punish the perpetrator.
• Seek outside help when needed. Most teachers do not have the training to deal with students who have serious problems as either perpetrators or victims of bullying. Hence, they should request professional assistance when it is needed either from the principal, a school counselor or the school psychologist. Although bullying in American schools affects the lives of many youth, about 10 percent of students are chronic bullies or victims and they may be at risk for long-term adjustment difficulties (Juvonen, Graham, & Schuster, 2003; Nansel et al., 2001).
• Set an example with your own behavior. Unfortunately, peer bullying also occurs among educators and between educators and students (e.g., Brendgen, Wanner, & Vitaro, 2006). It is critically important that adults in school settings refrain from targeting each other and from targeting students.
• Never ignore a student who reports being victimized by peers. Victims of peer bullying are often reluctant to tell their teachers about their experiences because they fear retaliation. Others who avoid disclosure believe that their teachers do not care or are unwilling to come to their aid. Because so many victims of school bullying "suffer in silence" it is important that teachers follow up on every reported incident.
• Do not rely too heavily on a zero tolerance approach to disciplining bullies. Zero tolerance approaches that advocate suspension or expulsion of school bullies are sometimes preferred because they presumably send a message to the student body that bullying will not be tolerated. However, research suggests that these policies do not always work as intended and can sometimes backfire (APA Task Force on Zero Tolerance, 2008). Before deciding on a discipline strategy, teachers need to give careful thought to the scope of the problem, where change should be targeted, who will be affected by those changes, the fairness of the strategy, and the kinds of messages that are being communicated to students.
• Do not adopt a "one size fits all" model for intervening in school bullying. Because bullying can take many forms (e.g., psychological vs. physical), it may be temporary or chronic. Because bullies and their victims have different challenges, teachers need to tailor their intervention approaches to the specific needs of each child.
• Do not let the peer group off the hook. Bullying involves more than perpetrators and victims. Students are often witnesses to bullying incidents and may take on roles of bystanders or reinforcers who encourage bullies (Salimalvalli, 2010). Peers need to learn that there is no such thing as an innocent bystander and how their group behavior can indirectly encourage bullies.

School bullying is associated with a host of adjustment difficulties (see Juvonen & Graham, 2014, Sanders & Phye, 2004). Students who are chronic victims of bullying are often the same children who are rejected by their peers; have low self-esteem; and feel depressed, anxious and lonely. Part of this psychological distress may revolve around how victims think about the reasons for their plight. For example, repeated encounters with peer hostility or even a single isolated, yet especially painful experience, might lead that victim to ask, "Why me?" In the absence of contrary evidence, such an individual might come to blame their predicament on their own shortcomings. Victims often conclude, for example that "I'm someone who deserves to be picked on" (Graham, Bellmore, & Mize, 2006; Graham & Juvonen, 1998). It is as if the victim is saying to himself or herself: "It's something about me; things will always be that way, and there is nothing I can do to change it"). Self-blame can lead to many negative psychological outcomes because individuals who make this attribution tend to feel both helpless and hopeless.

In addition to psychological challenges, some victimized children also have real physical symptoms that lead to frequent visits to the school nurse and absenteeism (Nishina, Juvonen, & Witkow, 2005). It is not difficult to imagine a chronic victim of bullying who becomes so anxious about going to school that she or he tries to avoid it at all costs. Victims of bullying can also develop negative attitudes toward school, which then can lead to poor performance. The academic problems associated with bullying begin as early as kindergarten and extends into the adolescent years (e.g., Schwartz, Gorman, Nakamoto, & Toblin, 2005).

Many beliefs about school bullying are not supported by current research. These are among the most common myths that even some teachers have been known to endorse:

Bullies are rejected by their peers and have no friends.

Many people believe that everybody dislikes the class bully. But in truth, research shows that many bullies have high status in the classroom and lots of friends (e.g., Rodkin, Farmer, Pearl, & Van Acker, 2000). Particularly during the middle school years, some bullies are actually popular among classmates who perceive them as "cool" (Juvonen et al., 2003). Many classmates admire their toughness and may even try to imitate them.

Bullies have low self-esteem.

Just as it has been incorrectly assumed that bullies are rejected by peers and have no friends, there is a general belief that such youths have low self-esteem. That myth has its roots in the widely accepted view that people who bully others must act that way because they think poorly of themselves. Some readers may remember the self-esteem movement of the 1980s when many people argued that raising self-esteem was the key to improving the outcomes of children with academic and social problems (Baumeister, 1996). But, there is little evidence that bullies suffer from low self-esteem. To the contrary, many studies report that bullies perceive themselves in a positive light, perhaps sometimes displaying inflated self-views (Juvonen et al., 2003; Zariski & Coie, 1996). Therefore, just focusing on self-esteem enhancement will probably not improve the outcomes of youths who pick on others.

Being a victim builds character.

Another misconception is that bullying is a normal part of the childhood and adolescence experience, and that surviving peer harassment builds character. In contrast to this view, research findings clearly show that being bullied increases the vulnerabilities of bullied children. For example, we know that children who are passive and socially withdrawn are at a heightened risk of getting bullied and these children become even more withdrawn after incidents of harassment (Schwartz, Dodge, & Coie, 1993).

Many childhood victims of harassment become violent as teens.

The portrayal of bullying victims lashing out in anger at their tormentors in school shooting incidents has been reinforced by the media over the past few years. However, most victims of bullying are more likely to suffer in silence than to retaliate. As indicated above, many victims experience psychological adjustment problems like depression and low self-esteem that encourage them to turn their anger inward rather than outward (Juvonen & Graham, 2014).

Bullying involves only perpetrators and victims.

Many parents, teachers and students view bullying as a problem that is limited to bullies and victims. Yet, bullying involves more than the bully-victim dyad (Salmivalli, 2010). Studies based on playground observations found that in 75 percent of bullying incidents, at least four other peers were present as witnesses, bystanders, assistants to bullies, reinforcers, or defenders of victims (O'Connel, Pepler, & Craig, 1999). Assistants to bullies take part in ridiculing or intimidating a schoolmate. Reinforcers, in turn, encourage the bully by showing signs of approval (e.g., smiling when someone is bullied). In contrast to the pro-bully participants, those who defend victims are rare. One observation study found that in more than 50 percent of observed incidents of bullying, peers reinforced bullies by passively watching. In only about 25 percent of the incidents did witnesses support the victim by directly intervening, distracting or discouraging the bully (O'Connel et al., 1999). Bystanders often ignore the bullying incident because they are either afraid that they might be next or they blame the victim fro his or her plight and feel no moral obligation to intervene (Pozzoli & Gini, 2010).

Understanding facts versus myths about bullies and victims is important for intervention. The problems of victims and bullies are not the same. Victims of harassment need interventions that help them develop more positive self-views and learn not to blame themselves for their experiences with harassment (Graham et al., 2006). Bullies need to acquire strategies that help them control their anger and their tendency to blame other people for their problems. And peers need to learn that bullying is a whole school problem for which everyone is responsible.

There are many intervention strategies to combat and deal with bullying in schools. Some interventions come in the form of whole school programs, others focus on classroom curricula, and still others target at-risk individuals (typically bullies). Certain programs focus on skill building (e.g., fostering pro-social skills, conflict-mediation strategies), whereas others rely on the punishment of undesirable behavior (e.g., zero tolerance policies). Data on program effectiveness are limited at this time; especially limited are evaluation studies that compare different approaches (Hyman, Kay, Yabori, Weber, Mahon, & Cohen, 2006; Samples, 2004; Smith, Pepler, & Rigby, 2004).

Differences between victims, bullies and bully-victims

What is it like to be a victim of peer harassment during early adolescence? What is it like to be a bully? Are there some youths who have characteristics of both victims and bullies? Researchers have been studying the similarities and differences between middle school students who have reputations as victims, bullies, or both bullies and victims (Graham, Bellmore, & Mize, 2006; Juvonen, Graham, & Schuster, 2003). Table 1 shows the differences found among victims, bullies, bully-victims, and a well-adjusted group on psychological, social and academic adjustment.

Table 1. Psychological profiles of early adolescents

Note: adapted from Juvonen, Graham, & Nishina (2003) and Graham, Bellmore, & Mize (2006).

Notice in the first column that early adolescents with reputations as victims share many psychological and social adjustment problems. Compared to the normative group, victims are more depressed, anxious, lonely, and they report low self-esteem. Research shows that victims have a tendency to blame themselves for their experiences with harassment; they are more likely to believe that "it is something about me, things will always be that way, and there is nothing I can do to change it." Self-blame and its accompanying negative demeanor make it more difficult for victims to cope with challenging social experiences (Graham & Juvonen, 1998). As might be expected in light of their other self-perceived vulnerabilities, victims perceive their schools as unsafe. Yet, victims do not perceive the school rules as unfair in the sense that they do not feel mistreated by teachers or administrators.

What about bullies? Compared to victims and the well-adjusted "normal" group, bullies appear to have healthy mental lives. They are no more depressed, anxious, or lonely than the well-adjusted group and they have high self-esteem. These findings are at odds with the widely held belief in our society that people who aggress against others must act that way because they think poorly of themselves. But in fact, there is very little indication in the research literature that aggressive youths suffer from low self-esteem (Juvonen & Graham, 2014). Also, bullies are least likely to blame themselves for any conflicts they have with their peers. That finding is consistent with the large body of literature in developmental psychology which reports that it is common for aggressive youths to blame the hostile intentions of others for their difficulties with peers rather than blame their own characteristics or behaviors (Dodge, Coie, & Lynam, 2006). And consistent with this low self-blame, bullies are more likely to believe that the school environment is safe, but teachers and administrators treat them unfairly.

Another noteworthy finding reported in Table 1 is that bullies, compared to victims, enjoy high social status. This may help to explain their positive self-views. Bullies are often perceived as especially "cool," where coolness captures both popularity and possession of traits that are admired by early adolescents. As early adolescents exercise their need for autonomy and independence, it seems that bullies enjoy popularity as their better-adjusted peers attempt to imitate their anti-social tendencies.

In the third column you will see the profiles for youths with reputations as both victims and bullies. Are they more similar to victims, to bullies, or to a distinct subgroup with its own unique characteristics?

In comparing columns 1 and 3, it seems that bully-victims are somewhat unique and they exhibit the worst characteristics of both categories. They report psychological maladjustment as high as that of victims, yet they do not enjoy any of the social benefits of bullies because their peers overwhelmingly reject them. In some cases, bully-victims turn inward and feel bad about themselves; in other cases, they turn outward and aggress against perpetrators. But with few friends, bully-victims have little social support to help them ward off potential retaliation. Like victims, bully-victims feel unsafe at school; but like bullies, they judge the school rules as unfair.

This suggests that bully-victims suffer from multiple risks. They also do more poorly in school than any of the other groups.

Considering all of the adjustment outcomes examined here, bully-victims may be the most troubled and vulnerable of the behavioral subgroups (Unnever, 2005).

School-wide interventions

A school-wide approach targets all students, their parents and adults within the school, including administrators, teachers and staff. Such programs operate under the assumption that bullying is a systemic social problem and that finding a solution is the collective responsibility of everyone in the school. Systemic prevention requires changing the culture of the whole school rather than (in addition to) focusing on the behavior of individuals or groups actually involved in bullying incidents. This approach requires increased awareness of the nature of the problem, heightened monitoring, and systematic and consistent responses to incidents of bullying. For example, students are asked to create their own rules about bullying and they are provided with information about strategies for dealing with bullying and opportunities for classroom discussions about their experiences. Teachers and school staff receive training that includes strategies for preventing problems associated with bullying.

Evaluations of school-wide interventions have yielded somewhat disappointing findings (e.g., Baldry & Farrington, 2007). Actual bullying behavior often does not decrease very much and in some cases bullying increased, suggesting that the intervention may have backfired. It is evident that staff buy-in is essential to make these school-wide programs work. Research on decision making about program adoption reveals that many teachers and administrators in American schools are reluctant to embrace whole-school interventions because they either believe that there is not enough time and space in the curriculum or that developing anti-bullying attitudes is primarily the responsibility of parents (Cunningham et al., 2009). The best examples of successful school-wide interventions (see Juvonen & Graham, 2014) enjoy broad-based support from school districts, teachers, administrators, parents and students.

Targeted intervention programs

Unlike school-wide approaches that address the needs of everyone, most interventions target the known dysfunctional thoughts and behaviors of those children who aggress against others. One very well documented research finding is that bullies have a tendency to believe that peers are intentionally causing them harm, particularly in ambiguous situations (Dodge et al., 2006; also see Castro et al., 2002 for a meta-analysis). This tendency has been called hostile attributional bias. Imagine, for example, that you are standing in line and unexpectedly receive a push from the person behind you. Although it may be unclear whether the person intended the push or not, bullies are more likely to infer that the push was instigated "on purpose" (i.e., the person is responsible) and to respond with anger and aggression.

Hostile attributional bias may be only one part of a larger set of deficits that interferes with the adaptive social information processing. For example, Crick and Dodge (1994) proposed a five-step social cognitive model that has become very influential in the bullying intervention literature. In that model, the information processing difficulties of bullies begin when they inaccurately interpret social cues associated with interpersonal dilemmas (e.g., the hypothetical push while waiting in line) and continues as they formulate goals accessed from a repertoire of possible behavioral responses (e.g., should I retaliate or just ignore it?), and finally choose a response.

One of the best-known bullying interventions that includes these kinds of social information processing skills is Fast Track (Conduct Problems Prevention Research Group (CPPRG), 2011). Implemented at four sites (Durham, North Carolina, Nashville, Tennessee, Seattle and a rural community in central Pennsylvania), Fast Track identified a sample of 890 high-risk kindergarten children based on parent and teacher reports of conduct problems at home and at school. These children were then randomly assigned to either an intervention group or to a no-treatment control group. Those in the intervention group participated in a yearlong curriculum with weekly meetings that included training in social information processing, social problem solving, emotional understanding, communication and self-control. When it was needed, the social-cognitive component was accompanied by individualized academic tutoring, and there was also a parent-training component. Intervention activities continued to grade 10, but with heavier concentration in the first two years of elementary school and during the transition to middle school. Other examples of targeted approaches for elementary school students are Brainpower (Hudley, 2008) and Promoting Alternative Thinking Strategies (PATHS) (Greenberg, Kushche, & Mihalic, 1998).

School-wide bullying prevention and targeted interventions, although complementary, represent different schools of thought and each has advantages and disadvantages. School-wide programs aim to build resiliency in all children and to create a more positive school climate, whereas targeted approaches focus on the underlying causes of bullying behavior in the individual bully. Fidelity and sustainability, two important components of good interventions, are likely to be differentially achieved in the whole-school versus targeted approaches. Fidelity, or the consistency with which all of the components of the intervention are implemented, is easier to both monitor and achieve in targeted approaches because there are fewer adults (trainers) and children to track. With school-wide programs, there are multiple activities at multiple levels involving multiple stakeholders and it is more difficult to monitor treatment fidelity. On the other hand, sustainability may be easier to achieve in the school-wide programs. Systemic changes in peer, classroom, school and community are needed to build the foundation for long-term prevention of bullying. Targeted interventions, typically imported from the outside and implemented by researchers or school staff working with those researchers, usually are too short-lived to achieve that kind of support base.

Are there gender differences in the experience of bullying?

Yes and no. The answer to this question emerges in discussions of different types of peer victimization — that is, physical, verbal and psychological. Psychological or relational victimization , usually involves ostracism or attempts to damage the reputation of the victim. Some research suggests that girls are more likely to engage in this relational type of bullying (e.g., Zimmer-Gembeck, Geiger, & Crick, 2005). Because a whole popular culture has emerged around relationally aggressive girls (so-called queen bees, alpha girls, etc. ) and their victims, it is important to put these gender findings in proper perspective. First, in some studies, physical, verbal and relational victimization tend to be correlated, suggesting that the victim of relational bullying is also the victim of physical and verbal bullying (e.g., Bellmore & Cillessen, 2006). Second, if relational bullying is more prevalent in girls than boys (and the results are mixed), then this gender difference is most likely confined to middle childhood and early adolescence (see reviews in Archer & Coyne, 2005; Card et al., 2008). By middle adolescence, relational bullying becomes the norm for both genders as it becomes less socially accepted for individuals to physically attack peers. In surveys of high school students, for example, both boys and girls report that they are more likely to engage in emotionally abusive behavior, such as ridicule and ostracism, than physically abusive behavior (Harris, 2004).

Are there ethnic differences in the experience of bullying?

No, the question is more complicated than that. There is no persuasive research evidence that ethnicity in and of itself is a risk factor for victimization. A more critical variable is whether one's ethnic group is the numerical majority or minority in a particular school. Because bullying occurs when there is an imbalance of power between perpetrator and victim, being a member of the minority group can lead to more victimization because one's group is less powerful in the numerical sense (e.g., Graham & Juvonen, 2002). It could be that the best situation is an ethnically diverse context where no one group holds the numerical balance of power (Juvonen, Nishina, & Graham, 2006). Shared power may reduce incidents of bullying that, in turn, affect perceptions of vulnerability. Thus, it is not so much ethnicity per se as it is the ethnic composition of classrooms and schools that shape the experience of victimization.

Is it true that "Once a victim, always a victim"?

No. Some findings suggest that victim status is moderately stable across a one-year school period for elementary students (Korchenderfer & Wardrop, 2001). In research with early adolescents, however, only about a third of students who had reputations as victims in the fall of sixth grade maintained that reputation at the end of the school year (Juvonen, Nishina, & Graham, 2000). Although certain personality characteristics (e.g., the tendency to be shy or withdrawn) place children at higher risk for being bullied, a host of changing situational factors (e.g., being a new student in school, being a late maturer) affect the likelihood of a child being bullied or continuing to be bullied. These situational factors explain why there are more temporary than chronic victims of bullying.

Are some students both bullies and victims?

Yes. A growing research literature has described the psychological profile of bully-victims — that is, students who are both perpetrators and targets of peer harassment. These students appear to be overwhelmingly rejected by their peers, while not enjoying any of the social benefits that sometimes accrue to aggressive youth (e.g., Graham, Bellmore, & Mize, 2006; Unnever, 2005). With multiple behavioral and social risks, bully-victims are considered to be more troubled and vulnerable than either bullies or victims.

What is the main reason that students get picked on by their peers?

Although there are many causes of bullying, one meaningful factor that consistently predicts victimization is being different from the larger peer group. Thus, having a physical or mental handicap or being highly gifted in a regular school setting, being a member of an ethnic or linguistic minority group, suffering from obesity, or being gay or lesbian are all risk factors for bullying because individuals who have these characteristics are often perceived to deviate from the normative standards of the larger peer group. A 2011 report on school bullying by the U.S. Commission on Civil Rights confirms these characteristics as risk factors. After examining a compendium of school district data, legal briefs and testimony of experts, the commission concluded that "…bullying based on students" identities 3 such as their sex, race, ethnicity or national origin, disability, sexual orientation or gender identity, or religion — can be particularly damaging. Unfortunately these forms of bullying are all too common in American schools" (U.S. Commission on Civil Rights, 2011, p. 8).

With so many bully-reduction interventions on the market, how can teachers know which one to choose?

Three questions are important to consider. First, how the problem of bullying defined? If the intervener believes that bullying is the collective responsibility of everyone in the school community, then a school-wide approach is called for. However, if one's primary focus is on the needs of chronic bullies and/or victims (the 7-15%), then a more targeted program would be more appropriate. Second, how sustainable is the intervention among staff who may already be overwhelmed with responsibilities? In all cases, interventions with independent evaluation data supporting their effectiveness should be considered. Third, what age group is the intervention targeting? Children undergo major cognitive, emotional, social and biological changes from pre-K through high school, and intervention activities must be sensitive to different needs of various age groups. In addition, with multiethnic student populations, program activities should reflect the life experiences and cultural heritages of the participants.

What is cyberbullying?

Cyberbullying is peer harassment that takes place online: texting via cell phone, emailing or instant messaging (IM), and posting messages on social networking sites and in chatrooms. It can be either direct (i.e., threats or nasty messages are sent to the target) or indirect (i.e., malicious comments, pictures and private messages are spread much like rumors). Cyberbullying often results in emotional distress much like in-person (offline) bullying (e.g., Nixon, 2014), but it also has distinct features. One unique feature is its speed and spread: degrading messages can quickly reach not only the target, but also a vast number of individuals. Another feature is anonymity. When screen names (that can be easily created and changed) are used to send instant messages or to take part in discussions in chatrooms, the identity of the bully can be easily concealed. Anonymity combined with very limited social controls (i.e., monitoring) makes it easy to send a hostile message or post embarrassing pictures of someone. Youth who report being targets of traditional bullying also report being the targets of cyberbullying (Patchin & Hiduja, 2006), so many students may be at risk for both types of harassment.

Developmental differences

Bullying has been documented in children as young as preschool, but tested interventions for very young children are rare (Alsaker & Valkanover, 2001). Research suggests that physical bullying increases throughout childhood and early adolescence, and then begins to level off by middle school (e.g., Nansel et al., 2001). By middle adolescence it becomes less acceptable to engage in physical bullying and more acceptable to employ covert psychological tactics such as social ostracism and spreading rumors (Archer & Coyne, 2005). Most intervention strategies, both school-wide and targeted, have been developed for use with elementary age children and the types of bullying most prevalent during those years.

Puberty, the onset of romantic relationships, and easy access to technology during early and middle adolescence bring new forms of bullying, including cross-gender sexual harassment (Pepler, Connolly, & Henderson, 2001), harassment of gay and lesbian youths (Toomey et al., 2010) and cyberbullying. Because early adolescence is a developmental period of heightened concern about finding one's niche, "fitting in," and peer approval, middle school students who are targets of bullying might be particularly vulnerable to adjustment difficulties (Juvonen & Graham, 2014).

Contextual factors

School contextual factors, (i.e., school and class size, teacher-student ratio, location and distance from home, racial/ethnic composition and organizational structure) change from childhood to adolescence, but very little is known about the effects of these changes on bullying or on its prevention. For example, one might hypothesize that bullying will be more extensive in larger schools where there are more "unowned spaces" with minimal adult supervision; or that students are more likely to be victimized going to and from school when they travel longer distances. It would also be important to know whether small learning communities (e.g., schools within schools) decrease the amount and seriousness of bullying; and whether academic tracking — which limits the mixing of students — affects bullying behavior during non-tracked classes. Contextual variables that increase students' sense of belonging are presumed to result in a more positive school climate, which includes less bullying (Payne & Gottfredson, 2004). But, we do not have enough research about the psychological mechanisms that may or may not explain contextual school effects.

Additional resources

• Stopbullying.gov A federal government website managed by the U.S. Department of Health & Human Services.
• UCLA Center for Mental Health in Schools/School Mental Health Project This website provides access to a clearinghouse of resources for enhancing mental health in schools. Resources include: consumer information outlets, national organizations with missions that focus on mental health in schools, relevant government agencies, listservs, electronic journals and newsletters.

For further reading

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Juvonen, J., & Graham, S. (2014). Bullying in schools: The power of bullies and the plight of victims. Annual Review of Psychology, 65 , 159-185. This article is an up-to-date review of scientific research on bullying in schools. There is a section that may be most useful to teachers on interventions to reduce bullying.

Alsaker, F. D. & Valkanover, S.  (2001).  Early diagnosis and prevention of victimization in kindergarten. In J. Juvonen & S. Graham (Eds.), Peer harassment in school: The plight of the vulnerable and victimized (pp. 175-195). New York: Guilford Press.

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Examining the Effectiveness of School-Bullying Intervention Programs Globally: a Meta-analysis

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• Published: 21 February 2019
• Volume 1 , pages 14–31, ( 2019 )

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• Hannah Gaffney   ORCID: orcid.org/0000-0001-9677-0218 1 ,
• David P. Farrington 1 &
• Maria M. Ttofi 1  

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This article presents results from an extensive systematic and meta-analytical review of the effectiveness of school-based bullying prevention programs. Its main aim is to explore the results of this meta-analysis specifically in regard to variations in the effectiveness of school-bullying programs globally and the effectiveness of specific anti-bullying programs. Our meta-analysis included 100 independent evaluations, and found that, overall, programs were effective in reducing school-bullying perpetration and victimization. In the present paper, we focused on 12 countries (e.g., Italy, Norway, USA, UK), three regions (i.e., Europe, North America, and Scandinavia) and four anti-bullying programs (i.e., KiVa, NoTrap!, OBPP, and ViSC) with multiple evaluations. Our results showed that anti-bullying programs evaluated in Greece were the most effective in reducing bullying perpetration, followed by Spain and Norway. Anti-bullying programs evaluated in Italy were the most effective in reducing bullying victimization, followed by Spain and Norway. Evaluations conducted in North America were the most effective in reducing bullying perpetration, and evaluations conducted in Scandinavia were the most effective in reducing bullying victimization. Evaluations of the Olweus Bullying Prevention Program produced the largest effect sizes for bullying perpetration outcomes, but the NoTrap! Program was the most effective in reducing bullying victimization. We also systematically review the core components of the intervention programs and make recommendations for researchers, practitioners, and policy makers.

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Introduction

Bullying remains a ubiquitous problem internationally and is an important topic for effective intervention and empirical research. Bullying is characterized by three core elements, namely (1) an intention to harm; (2) repetitive in nature; and (3) a clear power imbalance between perpetrator and victim (Centers for Disease Control and Prevention 2014 ; Farrington 1993 ; Olweus 1992 ). In other words, a bully is an individual who intends to cause harm to a victim, or victims, repeatedly, over a long period of time. Additionally, victims of bullying will feel that they cannot easily defend themselves against a bully, either due to a physical or social power imbalance.

Recent research has highlighted the various forms that bullying can take, not only amongst school children and adolescents but also between adults too, particularly within the workplace environment (Kowalski et al. 2018 ). Moreover, bullying can include relational, verbal, or physical behaviors. Most recently, online aggressive behaviors that are consistent with definitions of school bullying have been defined as cyberbullying (Bauman 2013 ; Betts 2016 ). The present review, however, is concerned only with school-bullying, specifically, bullying that occurs in schools involving children and adolescents, typically aged between 4 and 18 years old. School bullying is a complex social phenomenon and can commonly involve the whole peer group (Salmivalli 2010 ).

Outcomes of School Bullying

The negative outcomes of school-bullying perpetration and victimization are well documented in the research literature. These outcomes highlight the need for effective intervention and prevention programs to reduce school-bullying amongst children and adolescents around the world. Cross-sectional studies have found that bullying perpetration and victimization experiences are associated with worrying mental health outcomes, such as increased suicidal ideation (e.g., Hinduja and Patchin 2010 ; Holt et al. 2015 ; Klomek et al. 2010 ). In addition, adolescent victims of school bullying have been found to report higher levels of social anxiety (e.g., Hawker and Boulton 2000 ) and depression (e.g., Ttofi et al. 2011a ) in comparison to their non-victimized peers. Bullies, on the other hand, are more likely to carry weapons (e.g., Valdebenito et al. 2017 ) or use drugs (e.g., Ttofi et al. 2016 ; Valdebenito et al. 2015 ).

A recent review of systematic reviews concluded that the outcomes of school-bullying behaviors can occur not only concurrently with these experiences but also during adulthood (Zych et al. 2015 ). For example, longitudinal studies have suggested that individuals who bully others in childhood are more likely to be violent (e.g., Ttofi et al. 2012 ) and offend (e.g., Ttofi et al. 2011b ) as adults. While there is limited understanding of how these outcomes may vary between bullies and victims in different countries, researchers have suggested that experiences of school bullying may function as stepping stones towards many undesirable life outcomes (Arsenault et al. 2010 ). Thus, bullying is not only a concern for parents and educators but it is a public health concern also (Masiello and Schroeder 2013 ), and it is imperative that effective intervention efforts are put in place (Ttofi 2015 ).

Internationally, Due et al. ( 2005 ) reported that the risk of physical and psychological symptoms increased with higher levels of exposure to bullying across 28 countries. More recently, Fry et al. ( 2018 ) conducted an extensive meta-analysis across 21 countries to examine the relationship between childhood violence and educational outcomes. Predictors included school-bullying perpetration and victimization, as well as cyberbullying and peer-to-peer victimization (Fry et al. 2018 ). This study concluded that experiences of bullying in childhood were significantly related to higher rates of school dropout and absenteeism. Bullying was also related to a decrease in school graduation and lower academic achievement overall, although, the latter relationship was not statistically significant (Fry et al. 2018 ).

International Prevalence of School Bullying

A recent report published by the United Nations Educational, Scientific, and Cultural Organization (UNESCO 2018 ) proposes that creating educational spaces that are free from violence and safe learning environments for all children remains a global priority. This report outlines that bullying and other forms of violence affect approximately one-third of children and adolescents, but the rates of bullying victimization vary between regions. Using international self-report data (e.g., Health Behavior of School Children survey; HBSC), this report suggests that reports of bullying victimization are highest in regions such as the Middle East (41.1%), North Africa (42.7%), and sub-Saharan Africa (48.2%). Additionally, reports of bullying victimization were comparatively low in North America (31.7%) and lowest in Europe (25%), the Caribbean (25%), and Central America (22.8%).

An extensive meta-analysis reported that the mean prevalence of involvement in school bullying was 35% across 80 different countries (Modecki et al. 2014 ). Recent analyses of the Health Behaviour in School-aged Children (HBSC) study found interesting trends in bullying victimization across male and female schoolchildren (aged 11, 13, and 15 years old) from 33 countries (Chester et al. 2015 ). The authors suggested that, overall, occasional school-bullying victimization had decreased from 33.5% in 2001–2002 to 29.2% in 2009–2010, while chronic school-bullying victimization had also decreased from 12.7% in 2001–2002 to 11.3% in 2009–2010. This report also found that, while reports of school-bullying victimization were declining in one-third of countries included in the analysis, there are still large variations in bullying victimization across countries.

Researchers have attempted to identify factors that may explain these geographical differences. Elgar, Craig, Boyce, Morgan, and Vella-Zarb ( 2009 ) concluded that school-bullying prevalence varied according to rates of income inequality across 37 countries. Specifically, higher income inequality was associated with more reports of school bullying amongst adolescents. After controlling for income inequality, family and school support were associated with lower levels of school-bullying perpetration (Elgar et al. 2009 ). However, the relationship between income inequality and school-bullying victimization was not consistent across each of the countries included in the analysis.

Definitions of school bullying, and behaviors that constitute bullying, can also differ between countries. Previous research conducted by Smith, Kwak, and Toda ( 2016 ) showed that school bullying in Eastern cultures manifests more often as exclusion or isolation of an individual victim. Specifically in Japan, ijime involves a group excluding or isolating one student. In comparison, school bullying in Western cultures comprises a wider range of physical, verbal, and relational forms of aggression (e.g., Toda 2016 ). Thus, standardized international surveys may be insufficient at detecting different manifestations of bullying in different cultures which may in turn influence prevalence rates.

Regardless of international variation, bullying behaviors remain very frequent. One in four schoolchildren in Europe to nearly one in two children in sub-Saharan Africa report bullying victimization (UNESCO 2018 ). It is imperative, therefore, that practitioners should implement effective anti-bullying programs in their schools to protect students from bullying and its potential negative outcomes. From the perspective of international human rights law, the right to be safe at school and not be subjected to the aggression and victimization associated with bullying should be afforded to all children (Olweus and Limber 2010 ; Convention on the Rights of the Child 1989; Universal Declaration of Human Rights 1948).

Effectiveness of School-Bullying Intervention Programs

There have been many previous attempts to establish what works in bullying intervention and prevention. Farrington and Ttofi ( 2009 ) found that school-based anti-bullying programs were effective in reducing bullying perpetration by approximately 20–23% and bullying victimization by approximately 17–20%. This report identified that evaluations conducted in Norway were significantly more likely to report desirable results in comparison to evaluations conducted in other locations (Farrington and Ttofi 2009 ). The authors also reported the difference between evaluations conducted in Europe and elsewhere, but the difference in the odds ratio mean effect sizes was not statistically significant (p. 140).

More recent analyses have found that anti-bullying programs are effective in reducing both school-bullying perpetration and victimization, but these reviews are limited in various ways. For example, some previous systematic reviews have failed to conduct a meta-analysis to quantify the effectiveness of school-bullying intervention programs (i.e., Cantone et al. 2015 ; Chalamandaris and Piette 2015 ; Evans et al. 2014 ). Therefore, we cannot adequately quantify and judge the objective effectiveness of included anti-bullying programs.

Some previous meta-analyses have over-restricted their analysis to include only randomized controlled trials (i.e., Jiménez-Barbero et al. 2016 ), or evaluations published after 2000 and conducted with participants between the ages of 6 and 16 years old (i.e., Jiménez-Barbero et al. 2012 ). These restrictive inclusion criteria may unnecessarily exclude studies that used non-randomized quasi-experimental designs or younger/older children and adolescents. Often in school-based evaluation research, randomized controlled trials are not feasible and thus, high-quality non-randomized quasi-experimental designs are an appropriate alternative evaluation design. Furthermore, although forms of bullying may change with age, bullying behaviors have been reported in kindergarten-aged students and adolescents over the age of 16 (UNESCO 2018 ).

Objectives of the Current Report

A recent comprehensive systematic review and meta-analysis of the effectiveness of school-based bullying prevention programs found overall that anti-bullying programs are effective (Gaffney, Ttofi, and Farrington 2019a ). This meta-analysis found that anti-bullying programs were collectively effective in reducing school-bullying perpetration by around 19–20% (odds ratio = 1.309) and school-bullying victimization by around 15–16% (odds ratio = 1.244). This study included evaluations of many different anti-bullying programs from across the world. However, as you would expect, there was significant heterogeneity in the results (see Gaffney et al. 2019b ).

Thus, the objective of the present report is to explore some possible explanations for the variations in results between evaluations of anti-bullying programs. We use the data collected for the aforementioned review and evaluated the effectiveness of anti-bullying programs according to moderator variables. The present report explores variables such as the location of the evaluation and the particular intervention program that was evaluated. We aim to establish the effectiveness of existing anti-bullying efforts globally, to better inform ongoing research and potential translation of existing programs between countries. We also aim to identify and review existing anti-bullying programs that are widely disseminated or have been implemented across different settings and populations.

We suggest that the results of this analysis will be useful to researchers, policy makers, and practitioners (e.g., teachers, principals, school counselors/psychologists). It is important for all parties involved in anti-bullying work to understand the mechanisms of change underlying effective anti-bullying programs, and also to appraise the existing evidence on “what works” in bullying prevention. Therefore, we hope that this review will inform practitioners, such as school staff or counselors/psychologists, when deciding what anti-bullying program to implement in their schools.

Systematic Review

In order to locate studies for our review, we conducted a series of extensive systematic searches of the literature. Boolean searches were conducted using combinations of the following keywords: bully* ; victim *; bully-victim ; school ; intervention ; prevention ; program *; evaluation ; effect *; and anti-bullying . We searched several online databases, including, but not limited to, Web of Science, PsychINFO, EMBASE, ERIC, DARE, Google Scholar, and Scopus. Databases of unpublished reports (e.g., ProQuest) were also searched to include gray literature in this review. The inclusion of unpublished studies should reduce any potential publication bias (Easterbrook et al. 1991 ; McAuley et al. 2000 ).

In addition, studies both included and excluded by previous meta-analyses and systematic reviews (i.e., Cantone et al. 2015 ; Chalamandaris and Piette 2015 ; Evans et al. 2014 ; Jiménez-Barbero et al. 2016 ; Jiménez-Barbero et al. 2012 ) were reviewed to identify any potentially includable studies for the present review. In total, 49 studies that were included in a previous systematic review (i.e., Farrington and Ttofi ( 2009 )) were included in our updated analysis. New searches were conducted for studies published from 2009 to the end of December 2016.

To be included in the updated meta-analysis, primary studies were measured against a set of pre-determined inclusion criteria. Namely, studies must (1) describe an evaluation of a school-based anti-bullying program that was implemented with school-age participants; (2) utilize an operational definition of school bullying that coincides with existing definitions (e.g., CDC 2014 ; Farrington 1993 ; Olweus 1992 ); (3) measure school-bullying perpetration and/or victimization using quantitative measures, such as self-, peer-, or teacher-report questionnaires; and (4) use an experimental or quasi-experimental design, with one group receiving the intervention and another (control group) not receiving the intervention.

Search Results

Our searches of the literature produced approximately 20,000 reports that were screened for eligibility. Based on titles and abstracts, 474 of these results were retained for further screening. The majority of these studies were excluded for various reasons. Our initial wave of screening excluded 107 studies that did not actually evaluate a specific anti-bullying program, 108 studies that reviewed several anti-bullying programs, and 43 studies that did not report empirical quantitative data.

Following more in-depth screening of the methodologies and results of the remaining studies, 133 studies were excluded because they (1) reported irrelevant outcomes; (2) did not have an adequate control group; or (3) did not meet the specified methodological criteria. For a detailed description of the screening process and how we determined which studies were included, please see Gaffney et al. ( 2019b ). Following screening, 83 studies published after 2009 were eligible for inclusion in the systematic review.

In total however, 141 studies were eligible for inclusion in the present systematic review. This number includes 83 studies identified in the searches described here, five studies identified after searches were completed, and 53 studies that were included in the previous systematic review by Farrington and Ttofi ( 2009 ). However, only 100 primary evaluations were included in our meta-analysis, as a number of studies were excluded for a number of different reasons. For example, 10 studies lacked statistical information (needed to estimate effect sizes), 26 reported outcomes of evaluations conducted with the same sample (i.e., non-independent studies, repeat publications, or follow-up studies), and the remaining studies used an “other” experimental-control design (i.e., non-randomized with no before and after measures).

Included evaluations used one of three experimental methodologies: (1) randomized controlled trials; (2) quasi-experimental designs with before and after measures; and (3) age cohort designs. Randomized controlled trials are considered the gold standard in experimental evaluations (Weisburd et al. 2001 ) and involve the random assignment of individuals, or clusters of individuals, to experimental and control conditions. Quasi-experiments are conceptually similar to randomized controlled trials but do not use random assignment. As such, the validity of results may be reduced so in our meta-analysis, we only included quasi-experiments that measured school bullying before and after the implementation of an intervention. Age cohort designs involve students of a particular age assessed for relevant outcomes in the first year of the intervention and this data acts as a control for students in the same school and the same age tested after the intervention has taken place. For detailed descriptions of these 100 evaluations, please refer to Gaffney et al. ( 2019b ), for studies published after 2009, and to the original systematic review by Farrington and Ttofi ( 2009 ), for studies published before 2009.

• Meta-analysis

From the 100 evaluations, we estimated 103 independent effect sizes for the effectiveness of anti-bullying programs in reducing bullying perpetration and bullying victimization. The majority of effect sizes were corrected for the effect of clustering (i.e., the allocation of groups, classes, or schools, rather than individuals, to experimental conditions) which is a common approach in school-based evaluation studies (Donner et al. 2001 ). Our meta-analysis included evaluations that were conducted using randomized-controlled designs ( n  = 45 effect sizes), quasi-experimental designs with before and after measures of bullying outcomes ( n  = 44 effect sizes), and age cohort designs ( n  = 14 effect sizes).

The Comprehensive Meta-analysis software was used to conduct our analysis of the effectiveness of anti-bullying programs. Gaffney et al. ( 2019b ) presented the results of this analysis using three different models of meta-analysis and highlighted the strengths and weaknesses of each approach. For the present report, the results will be presented only using the multiplicative variance adjustment model (MVA; Farrington and Welsh 2013 ). This model of meta-analysis overcomes the problems associated with both the fixed-effects model (i.e., the assumption of a normal distribution of studies, even though homogeneity between primary studies is rare) and the random effects model (i.e., the additive adjustment for heterogeneity resulting in disproportionate weight given to smaller studies, which is undesirable).

We also translated odds ratio effect sizes to percentages to more effectively communicate the effectiveness of school-based anti-bullying programs. A clear example is provided by Ttofi and Farrington (2011), but this process involves assuming equal allocation of participants to experimental and control conditions in primary evaluations. For example, if there were around 55 bullies and around 145 non-bullies in the control condition ( n  = 200) and approximately 45 bullies and approximately 155 non-bullies in the experimental condition ( n  = 200), the OR would be about 1.3. This relates to a reduction in bullying perpetration of approximately 19–20%. Following this logic, we were able to translate ORs to approximate percentage decreases in bullying behaviors.

Coding Moderator Variables

For the purpose of the present report, we coded each of the 100 evaluations according to three moderators. Firstly, the country in which the evaluation took place was recorded (e.g., Australia, Sweden, or the USA). Secondly, for comparison, we coded the world region in which this country lies. For example, studies conducted in Italy, France, Spain, etc. were coded as the region “Europe,” and studies conducted in the USA or Canada were coded as “North America.” Evaluations conducted in Finland, Norway, or Sweden were coded as the region “Scandinavia,” but, an additional category (named EU) was created to encompass all European studies (i.e., inclusive of Scandinavian countries).

Both the country and regional information of all was coded all except one country. Sapouna et al. ( 2010 ) evaluated the FearNot! Virtual-learning intervention program in both the UK and Germany. Therefore, this study was not included in either the UK or German evaluations but was included in regional analysis as a European study. Thirdly, we also recorded the specific intervention program evaluated in each primary study. For example, some anti-bullying programs are widely disseminated and have been evaluated repeatedly in different locations and samples (e.g., KiVa or the Olweus Bullying Prevention Program).

Systematic Review Results

Evaluations globally.

Of the 100 evaluations included in our meta-analysis of school-based anti-bullying programs, the majority (80 for perpetration, 84 for victimization) were conducted in one of 12 different countries (i.e., Australia, Canada, Cyprus, Finland, Germany, Greece, Italy, Netherlands, Norway, Spain, UK, USA). We also identified singular evaluations conducted in Austria (Yanagida et al. 2016 ); Brazil (da Silva et al. 2016 ); China (Ju et al. 2009 ); Czechoslovakia (modern day Czech Republic and Slovakia; Rican, Ondrova, and Svatos 1996 ); Hong Kong (Wong et al. 2011 ); Ireland (O’Moore and Minton 2004 ); Malaysia (Yaakub et al. 2010 ); Romania (Trip et al. 2015 ); Sweden (Kimber et al. 2008 ); South Africa (Meyer and Lesch 2000 ); Switzerland (Alsaker and Valkanover 2001 ); and Zambia (Kaljee et al. 2017 ).

Repeatedly Evaluated Anti-bullying Programs

We found that very few specific anti-bullying programs had been implemented and evaluated more than once using independent samples. Sixty-five different school-based bullying intervention and prevention programs were included in our meta-analysis, but only eight were repeatedly evaluated (i.e., Bully Proofing Your School; the fairplayer.manual; KiVa; NoTrap!; OBPP; Second Step; Steps to Respect; ViSC). Moreover, of these programs, only four were evaluated more than twice across different locations with different evaluators (i.e., KiVa, OBPP, NoTrap!, and ViSC). The following sections of this report outline the key features of these programs. These four studies are outlined in Table 1 .

KiVa Anti-bullying Program

The KiVa anti-bullying program was developed and widely disseminated in Finland from 2007 to the present (Kärnä et al. 2013 ). The program was developed on the basis on several theoretical models of human social behavior, such as Bandura’s (1989) social-cognitive theory and the complex involvement of peers in school-bullying scenarios (e.g., Salmivalli 2010 ). Thus, the KiVa anti-bullying program targets bystanders in bullying situations, with the aim of reducing the social rewards for bullies and in turn reducing their bullying behaviors (Kärnä et al. 2013 ). The program is composed of three age-appropriate curriculum materials that focus on enhancing empathy, self-efficacy, and anti-bullying attitudes of bystanders.

Kärnä et al. ( 2011a , b , 2013 ) reported that trained teachers implement the KiVa intervention program in their classrooms and are provided with detailed lesson plans, which include various activities, such as group discussion, role-play, and short anti-bullying videos. Classroom anti-bullying rules are also devised throughout lessons. The KiVa program also includes a virtual-learning element, with primary school students playing an anti-bullying computer game both during and between lessons. Secondary school students are introduced to “KiVa Street” which is an online forum, providing vast information on bullying-related topics. Kärnä et al. ( 2011a ) state that the KiVa program includes many features identified by a previous review (Farrington and Ttofi 2009 ) as being significantly effective intervention components. For example, it includes disciplinary methods, improved playground supervision, teacher training, classroom rules, a whole-school anti-bullying policy, information for parents, videos, and cooperative group work (Kärnä et al. 2011a , p. 797).

Our systematic searches identified 16 potentially includable evaluations of the KiVa anti-bullying intervention (i.e., Ahtola et al. 2012 , 2013 ; Garandeau et al. 2014a , b ; Haataja et al. 2014 ; Hutchings and Clarkson 2015 ; Kärnä et al. 2011a , b , 2013 ; Nocentini and Menesini 2016 ; Noland 2011 ; Sainio et al. 2012 ; Salmivalli et al. 2012 ; Williford et al. 2012 ; Williford et al. 2013 ; Yang and Salmivalli 2014 ). Of these 16 studies, only four met our inclusion criteria and were included in our meta-analysis (i.e., Kärnä et al. 2011a , b , 2013 ; Nocentini and Menesini 2016 ). These studies presented the results of nationwide evaluations of the KiVa anti-bullying program using an age cohort design (i.e., Kärnä et al. 2011a ) and a randomized controlled trial (i.e., Kärnä et al. 2011b , 2013 ). Additionally, Nocentini and Menesini ( 2016 ) reported the results of the implementation and evaluation of the KiVa anti-bullying program in Italy using a randomized controlled trial design.

Noncadiamointrappola (let us Not Fall Into a Trap), or NoTrap!, is a web-based anti-bullying program that has been developed and evaluated in Italian high schools (Menesini et al. 2012 ). The intervention involves actively engaging students in the development of a website to promote anti-bullying. In addition, a number of participating students are enrolled as peer-educators throughout the intervention. These students act as moderators of the online anti-bullying forum, regulating discussion threads and responding to users’ questions and concerns (Menesini et al. 2012 ).

Additionally, peer-educators hold workshops offline with participating students to highlight the key issues surrounding both school- and cyberbullying (Palladino et al. 2016 ). Offline activities incorporate several elements that focus on (1) victims’ roles and victim support; (2) involving bystanders in bullying; (3) greater involvement of teachers; and (4) creation of a Facebook group to supplement online forum materials (Palladino et al. 2012 ). Classroom workshops target empathy and problem-solving skills (Palladino et al. 2016 ).

Our meta-analysis included four independent evaluations of the NoTrap! program in Italian secondary schools using quasi-experimental designs with before and after measures of school- and cyberbullying. Menesini et al. ( 2012 ; Study 1), implemented the program with 386 9th to 13th grade students during the December 2009 to June 2010 academic year. Palladino et al. ( 2012 ) and Menesini et al. ( 2012 ; Study 2) reported the results of the implementation and evaluation during the December 2010 to June 2011 academic year. Finally, Palladino et al. ( 2016 ) reported the results of two trials of the NoTrap! program with 9th grade students from 15 secondary schools, for the 2011/12 (Trial 1) and 2012/13 (Trial 2) academic years.

Olweus Bullying Prevention Program

It can be argued that the Olweus Bullying Prevention Program (OBPP; Olweus 1993a , b ) was the original whole-school anti-bullying program. This program aims to improve the school environment in order to reduce existing bullying problems and prevent further instances of bullying (Olweus et al. 1999 ). The program includes elements at many levels, specifically, school, classroom, individual, and community levels (Olweus et al. 2007 ). Intervention components are guided by four key principles, namely, adults, both at school and home, should (1) show warmth and positivity towards students; (2) set strict limits and restrictions on unacceptable student behavior; (3) apply consistent and non-aggressive consequences; and (4) act as positive and authoritative role models (Olweus and Limber 2010 , p. 126).

Olweus and Limber (Olweus and Limber 2010 , p. 127, see Table 1 ) specify that, at the school-level, the OBPP intervention involves establishing a Bullying Prevention Coordinating Committee (BPCC) that is comprised of school staff, parents, and members of the wider community. Intensive training is also provided for staff, and regular staff discussion groups are held. School rules against bullying are implemented at the whole-school and classroom levels, and a school-wide “kick off” event is held to launch the start of the intervention. At the individual level, intervention components include “hot-spot” supervision (i.e., increased staff presence at locations around the school where bullying is known to occur). The intervention also targets specific individuals who are recognized as bullies and victims, and their respective parents. Individual-specific intervention strategies are also designed for students involved in bullying.

Our meta-analysis of school-based anti-bullying programs included 12 independent evaluations of the OBPP intervention, largely implemented in Norway and the USA (e.g., Finn 2009 ; Limber et al. 2018 ; Losey 2009 ; Purugulla 2011 ). We also identified one evaluation of the OBPP in Malaysia (i.e., Yaakub et al. 2010 ). The OBPP was largely evaluated using quasi-experimental designs with before and after measures, or age cohort designs. The OBPP can be implemented with children and adolescents of a range of ages. For example, Finn ( 2009 ) implemented and evaluated the program with elementary schoolchildren, Purugulla ( 2011 ) implemented the program with middle school students, and Losey ( 2009 ) and Yaakub et al. ( 2010 ) implemented the program with secondary school students. Several of the OBPP evaluations that were included in our meta-analysis were implemented with students from a range of grades (e.g., Limber et al. 2018 ).

Viennese Social Competence Program

The Viennese Social Competence (ViSC) intervention program approaches bullying prevention from a socio-ecological perspective (Bronfenbrenner 1979 ; Swearer and Espelage 2004 ). This intervention targets not only individual students but also includes teachers, parents, and school staff, from a social learning theory (Bandura 1977 ) perspective. The ViSC program ensures that teachers have a shared responsibility to prevent bullying perpetration and victimization amongst students. The aim of the ViSC program is to reduce aggressive and bullying behaviors and also to create social and intercultural competencies within the school environment (Gradinger et al. 2015 ).

Designed to be implemented with secondary school students, the ViSC program is a 1-year program and adopts a “train-the-trainer” model. In other words, experts train teachers, who in turn train their students (Gradinger et al. 2015 ). The first semester of the program incorporates school-level intervention components, implemented with teachers and school staff. Participants are trained in how to recognize and tackle bullying scenarios and implement preventative measures at the school- and class-levels. Participating students also complete 13 lessons that follow a student-centered approach. Lessons one to eight focus on bullying behaviors and require students to actively work together to develop ways to prevent aggressive behavior in their respective classes. In the remaining five lessons, students work together on a class project to achieve a positive common goal and practice their social skills (Atria et al. 2007 ; Gradinger et al. 2015 ).

Our systematic review included five evaluations of the ViSC program, implemented in Austria (Gradinger et al. 2015 ; Yanagida et al. 2016 ); Cyprus (Solomontos-Kountouri et al. 2016 ); Germany (Gollwitzer et al. 2006 ); and Romania (Trip et al. 2015 ). One evaluation (i.e., Trip et al. 2015 ) of the ViSC program also implemented additional cognitive-behavioral intervention lessons, based on Rational Emotive Behavioral Education (REBE).

Meta-analysis Results

Overall, our meta-analysis found that anti-bullying programs were effective in reducing both school-bullying perpetration (OR = 1.324; 95% CI 1.27–1.38; p  < 0.001) and school-bullying victimization (OR = 1.248; 95% CI 1.27–1.38; p  < 0.001) outcomes. We estimated that this result corresponds to an approximate reduction of 19–20% and 15–16% for bullying perpetration and victimization respectively.

While the mean effect sizes suggest that anti-bullying programs are effective, there was significant heterogeneity for both bullying perpetration ( Q  = 323.39; p  < 0.001) and bullying victimization ( Q  = 387.26; p  < 0.001) outcomes. This result is not surprising in light of the large number of studies included in our meta-analysis, and the wide array of countries and intervention programs represented. Therefore, the aim of the present report is to explore variations in the effectiveness of intervention programs between countries and regions and specific anti-bullying programs.

School-Bullying Perpetration

Table 2 presents the effectiveness of anti-bullying programs across 22 different countries for bullying perpetration outcomes. Table 2 shows that, amongst international locations where more than one evaluation was conducted, evaluations carried out in Greece were the most effective in significantly reducing bullying perpetration, followed by Norway, Italy, the USA, and Finland. When singular evaluations were included, the anti-bullying program implemented in the former Czechoslovakia had the largest effect size for bullying perpetration, followed by Ireland. Effect sizes for bullying perpetration across all 22 countries included in our meta-analysis are represented graphically in Fig.  1 .

Forest plot of weighted mean odds ratios for bullying perpetration outcomes across 22 different countries. Odds ratios are shown on a logarithmic scale

School-Bullying Victimization

Table 2 also summarizes the effectiveness of anti-bullying programs across 21 different countries for bullying victimization outcomes. Amongst international locations where more than one evaluation was conducted, evaluations conducted in Italy were the most effective in significantly reducing bullying victimization, followed by Spain, Norway, the USA, and Finland. Additionally, evaluations conducted in Germany and the UK were significantly effective. When singular evaluations were included, the anti-bullying program implemented in Austria had the largest effect size for bullying victimization, followed by Switzerland. Effect sizes for bullying victimization across all 21 countries included in our meta-analysis are represented graphically in Fig.  2 .

Forest plot of weighted mean odds ratios for bullying victimization outcomes across 21 different countries. Odds ratios are shown on a logarithmic scale

Comparing Regional Effectiveness

In addition to exploring the effectiveness of anti-bullying programs conducted in individual countries, we also estimated effect sizes for different regions. Table 3 shows the weighted mean effect sizes across seven different geographical regions for school-bullying perpetration and victimization outcomes. We were able to code effect sizes for seven regions: Africa, Asia, Australia, Europe (excluding Scandinavia), North America, South America, and Scandinavia. The majority of studies were conducted in either Europe, North America, or Scandinavia. We also estimated a weighted mean effect size for studies conducted in Europe (including Scandinavia).

In regard to school-bullying perpetration outcomes, evaluations conducted in North America were the most effective, followed by Scandinavian studies, and then European studies. For school-bullying victimization outcomes, evaluations conducted in Scandinavia were the most effective. Evaluations conducted in Europe were the second most effective, followed by North American studies. When weighted mean effect sizes were estimated for European and Scandinavian countries collectively, they were significantly more effective in reducing bullying victimization outcomes than North American studies. However, the effect size in North American studies for bullying perpetration outcomes was not significantly different from the weighted mean for European and Scandinavian studies.

Effectiveness of Specific Anti-bullying Programs

Table 4 summarizes the effectiveness of specific anti-bullying programs in reducing school-bullying perpetration and victimization. Eight programs (i.e., Bully Proofing Your School, fairplayer.manual, KiVa, NoTrap!, OBPP, Second Step, Steps to Respect, and ViSC) could be studied in relation to bullying perpetration outcomes. The same programs, with the exception of the fairplayer.manual program, were studied in relation to bullying victimization outcomes. The effectiveness of these programs varied greatly. For both perpetration and victimization outcomes, we also report effect sizes for evaluations of the OBPP conducted in Norway ( n  = 5) and the USA ( n  = 6) separately. Overall, there were 12 evaluations of the OBPP included in our analysis, which includes one evaluation conducted in Malaysia.

In relation to school-bullying perpetration outcomes, overall the OBPP was the most effective intervention program. In addition, evaluations of the OBPP in Norway and in the USA were the most effective individually, in comparison with other included anti-bullying programs. The difference in the magnitude of OBPP evaluations conducted in Norway and in the USA was not statistically significant for school-bullying outcomes. Other programs were also significantly effective in reducing school-bullying perpetration behaviors, including KiVa, Second Step, and Steps to Respect, although their effect sizes were markedly lower in comparison to the OBPP. Positive effect sizes (i.e., OR > 1) were also observed for the BPYS and NoTrap! programs, but these effects were not statistically significant. Surprisingly, negative effects were found for two anti-bullying programs, the fairplayer manual and ViSC, although these effects were not statistically significant.

In relation to school-bullying victimization outcomes, NoTrap! was the most effective anti-bullying program, followed by the Bully Proofing Your School Program. Our analysis found that other anti-bullying programs were also significantly effective in reducing school-bullying victimization, including Steps to Respect and KiVa. The OBPP intervention program was the third most effective anti-bullying program for reducing victimization. Effect sizes for the OBPP varied significantly between evaluations conducted in Norway and evaluations conducted in the USA. Our analysis also found negative effects of the Second Step program in relation to victimization. Evaluations of the ViSC program also had a negative effect on bullying victimization, although this effect was not statistically significant.

Overall, the results of our meta-analysis are consistent with previous findings and show that school-based anti-bullying programs are effective in reducing bullying perpetration and victimization. Our meta-analysis included evaluations of anti-bullying programs from a wide range of countries and specific intervention programs, far more than in any previous meta-analysis (e.g., Cantone et al. 2015 ; Chalamandaris and Piette 2015 ; Evans et al. 2014 ; Jiménez-Barbero et al. 2012 ; Jiménez-Barbero et al. 2016 ). We conclude that school-based anti-bullying programs are effective in reducing both school-bullying perpetration and victimization globally and across different school-based programs.

Global Effectiveness

In Greece, where evaluations included in our meta-analysis were highly effective, school-bullying perpetration was reduced by approximately 40%. Evaluations conducted in the Norway, Italy, and the USA were effective in reducing bullying perpetration by approximately 21–25%. Anti-bullying programs implemented and evaluated in Italy were also very effective in reducing victimization in our meta-analysis, with the odds ratio effect size corresponding to an approximate reduction of 31%. Evaluations conducted in Spain and Norway reduced victimization by approximately 28% and 23%, respectively. Evaluations conducted in Finland, Germany, and the UK were also significantly effective in reducing victimization by approximately 8–12%.

We also identified regional differences in the effectiveness of anti-bullying programs. Specifically, intervention programs conducted in Europe significantly reduced bullying perpetration by around 13%, while interventions conducted in Scandinavian countries significantly reduced bullying perpetration by around 20%. Evaluations conducted in North America (i.e., the USA and Canada) significantly reduced bullying perpetration by around 21% and bullying victimization by around 11%. Comparatively, anti-bullying programs that were implemented and evaluated in Scandinavia and Europe reduced victimization by a larger percentage, 18% and 15% respectively. However, no clear pattern of statistically significant differences between regional effect sizes was identified in our analysis.

Limitations and Future Research

While the results of our further analysis in relation to the location of evaluations are interesting, the findings are limited in explaining why heterogeneity occurs between mean effect sizes. The current report highlights that anti-bullying programs are effective and are largely effective worldwide. The results are consistent with previous findings such as the recent UNESCO ( 2018 ) report on bullying. The majority of anti-bullying programs were evaluated in regions where the prevalence of bullying is already comparatively low, for example, Europe and North America. Our systematic review further highlights the lack of existing anti-bullying programs in areas where UNESCO report worryingly high levels of bullying, such as sub-Saharan Africa and the Middle East.

The lack of a clear pattern in relation to the regional effectiveness of anti-bullying programs may be explained by several factors. Firstly, there are a large number of potential confounding factors that could be influencing the overall results. When comparing the effectiveness of anti-bullying programs in a meta-analysis such as this, other moderators need to be considered. For example, previous analyses have found that anti-bullying programs are more effective with older participants (i.e., over age 11) than they are with participants aged 10 years old and younger (Farrington and Ttofi 2009 ). The relationships between participant age and overall effectiveness are not consistent, with prominent researchers disagreeing with this finding (e.g., Smith et al. 2012 ; Smith 2010 ).

Other potential confounding variables include the type of measurement, the specific intervention components, or the evaluation methodology used. Gaffney et al. ( 2019b ) showed that evaluations conducted using an age cohort design consistently resulted in the largest effect sizes. This may also serve to explain why the OBPP program and evaluations conducted in Norway/Scandinavia are found to produce larger effect sizes as this evaluation method is predominantly used to evaluate this program in Norwegian schools (Gaffney et al. 2019b ).

Previous research has indicated that there are cultural differences in bullying behaviors amongst adolescents (e.g., Smith et al. 2016 ). Therefore, an anti-bullying program that is designed to reduce these behaviors should reflect these differences. This is particularly evident when we observe the variations in effect sizes for the Olweus Bullying Prevention Program (OBPP; Olweus 1993a , b ). This program was originally designed and implemented in Norway, and it is therefore not surprising that the OBPP program was more effective in reducing both perpetration and victimization when evaluated in Norway, compared to evaluations in the USA (see Table 4 ). While the program was still significantly effective in the USA, the percentage decrease in school-bullying perpetration was 25% and in victimization was 11%. These figures are low in comparison to the decreases in bullying seen in Norwegian evaluations (35% perpetration; 29% victimization). These differences could be attributed to different evaluation methodologies (see Gaffney et al. 2019b ), but they could also reflect cultural and societal differences between youth in Norway and youth in the USA.

Moreover, when the OBPP was evaluated in six Malaysian secondary schools, with a sample size of approximately 3816 students, the program was not significantly effective in reducing school-bullying victimization (Yaakub et al. 2010 ; OR = 1.09, p  = 0.28). This may be a result of the different manifestations of school-bullying victimization in Eastern societies. As previously stated, researchers (e.g., Smith et al. 2016 ) have outlined that bullying manifests differently in Eastern and Western cultures. This may explain why in Malaysia, the OBPP was seemingly ineffective at reducing bullying victimization. It may be that the program itself was not tailored to the specific experiences and/or behaviors demonstrated by Malaysian students.

Future research is needed to better explore the potential factors that may explain heterogeneity observed between mean effect sizes of anti-bullying evaluations. For example, such research could incorporate the type of intervention implemented, the age of participants, the sample size, timeframe of measurement (i.e., bullying experienced in past 3, 6, 9 months), and the type of report (i.e., self-, peer-, or teacher-reported bullying).

Specific Interventions

We also explored the effectiveness of the four most widely disseminated anti-bullying programs that were included in our review (i.e., KiVA, NoTrap!, OBPP, ViSC). For the purpose of this analysis, we only included programs that had been evaluated on three or more independent occasions. The OBPP was the most effective in reducing school-bullying perpetration. Across 12 evaluations, the OBPP reduced bullying perpetration by approximately 26%. In relation to victimization outcomes, the NoTrap! program was the most effective, reducing victimization by around 37%. NoTrap! also reduced bullying perpetration by a considerable amount, approximately 22%, but this effect was not statistically significant. The KiVA program significantly reduced school-bullying perpetration by approximately 9% and school-bullying victimization by approximately 11%. The ViSC program was the only program to increase bullying perpetration (by roughly 4%) and bullying victimization (by roughly 4%), although these effects were not statistically significant. Again, these results may have been influenced by the particular evaluation methods used (see Weisburd et al. 2001 ).

Intervention Components

As Table 1 shows, the KiVA, NoTrap!, OBPP, and ViSC programs incorporated quite similar intervention components. Specifically, the KiVA, OBPP, and ViSC programs are very similar in practice, with the NoTrap! program being the most different of the four programs. As the effectiveness of these programs also varied, it may be possible, by exploring these different components, to better inform future research, practice, and policy decisions.

The Whole-School Approach

With respect to these programs, it is not surprising that three of the four adopted a “whole-school” approach (i.e., KiVA, the OBPP, and ViSC). This approach to anti-bullying programs was first introduced and implemented by Dan Olweus in Norway (i.e., OBPP, Olweus 1991 ), and it is undeniably the most common approach to bullying prevention. Other programs (i.e., KiVa or ViSC) have implemented this approach and applied a socio-ecological theoretical framework to explain any potential changes that occur as a result of the implementation. The whole-school approach to bullying prevention incorporates individuals involved in every aspect of students’ lives, for example, not only the students involved in bullying but also their peers, parents, teachers, and the wider community.

In relation to effectiveness, our meta-analysis suggests that the whole-school approach was not always the most effective. The OBPP was very effective in reducing both bullying perpetration and victimization, but the KiVa program was only marginally effective (approximately 9% and 11% decreases in perpetration and victimization respectively), and the ViSC program had an undesirable effect. Although the effect sizes for the ViSC program were not statistically significant, the odds ratios correspond to roughly a 4% increase in both bullying perpetration and victimization. Moreover, the non-whole-school program NoTrap! was the most effective intervention in reducing bullying victimization, with a decrease of 37% approximately. NoTrap! involved creating an online forum where trained students acted as moderators, responding to participants’ questions and concerns about bullying.

This suggests that, while school bullying may very well be a complex social peer-group phenomenon, the whole-school approach might not be effective for every individual student. This observation is consistent with previous research. For example, in the context of the KiVa anti-bullying program, Kaufman et al. ( 2018 ) recently characterized participants into different trajectories of victimization. This study found that high-trajectory (for victimization) participants (i.e., those who reported high levels of peer rejection, internalizing problems, and lower quality parent-child relationships) reported lesser decreases in victimization following the intervention, in comparison to participants in the decreasing and low/no victimization trajectories. The universal approach commonly includes school- and class-level components that focus on raising awareness about bullying-related issues. It may be the case that, by raising awareness, and focusing on highlighting bullying issues amongst students, the effect sizes may be influenced by a social desirability bias. This might explain why greater reductions are seen for whole-school programs for bullying perpetration in comparison to decreases for bullying victimization. To explore this result further, future research should aim to compare effect sizes based on participants’ self-reports to teacher- or peer-reports of bullying victimization and perpetration.

Peer Involvement

Gaffney, Ttofi, and Farrington ( 2019a ) previously found that the intervention component “work with peers” was associated with an increase in bullying victimization. However, this finding was not widely accepted by other researchers in the field who champion the peer-led approach to bullying prevention (e.g., Smith et al. 2012 ). In the four most widely disseminated programs, the peer group was involved in intervention activities in various ways. For example, the OBPP program involved actively working with participants to engage bystanders in order to encourage them to prevent, or respond accordingly to, bullying situations in their daily lives. Moreover, the OBPP involved in-class group exercises and discussions, as did the KiVA and ViSC programs. In comparison, the NoTrap! program is a peer-led program.

The NoTrap! program includes a peer-led online forum for participants to discuss bullying victimization experiences. It may be that the anonymity and protection of an online environment encourages participants to truly open up about bullying victimization, whereas in classroom settings, they may feel uncomfortable about disclosing their experiences. Previous research has shown that a number of factors, including trust and perceived privacy, can influence disclosure in online settings, in relation to sensitive issues (Joinson et al. 2010 ).

Furthermore, the overlap between offline and online bullying perpetration and victimization will increase amongst adolescents, as the Internet has become a part of our daily lives rather than an abstract place where different social norms apply (Rooney, Connolly, Hurley, Kirwan, and Power 2015 ). Previous studies have shown that the greatest risk factor for cyberbullying is school bullying (Baldry et al. 2015 ), and that the factors involved in both online and offline bullying regularly overlap (Tzani-Pepelasi et al. 2018 ). Therefore, it may be that moving from the classroom to online peer-led forums may be a way in which practitioners can improve intervention programs to better reduce bullying victimization. This may also be a practical and cost-effective method, to get students actively involved in anti-bullying work while also highlighting key issues.

Parent and Teacher Involvement

The NoTrap! program was the only program of these four widely disseminated programs that did not formally include teachers or parents in prevention activities. While this intervention focused on peer-led online forums (in conjunction with peer-led offline anti-bullying activities), the OBPP, KiVa, and ViSC programs each included the involvement of both parents and teachers. As previously stated, the involvement of teachers and parents is a key feature of the ecological, whole-school approach to anti-bullying programs. In both the KiVa and OBPP programs, parents received leaflets or letters at home that provided them with information about bullying and about the intervention program. Parents were also invited to information nights held at participating schools.

Similarly, the KiVA, OBPP, and ViSC programs trained teachers to implement the detailed anti-bullying curricula that were specific to the intervention programs. In the KiVA program, teachers were trained to implement either the “confronting approach” or the “no blame approach” when dealing with bullies. Both the KiVA and OBPP programs required teachers to engage with “hot-spot” supervision, which has been found to be an effective intervention component (Farrington and Ttofi 2009 ). Hot-spot supervision involves identifying locations within the school premises where bullying occurs frequently and increasing teacher presence in these areas. These elements are missing in the NoTrap! and ViSC programs, and this may be one potential reason why the KiVa and OBPP programs are more effective in reducing bullying perpetration.

Implications for Schools and Researchers

Our meta-analysis provides practitioners with useful insights into the effectiveness of anti-bullying interventions in a number of countries worldwide. Our results show that the effectiveness of school-based interventions for bullying perpetration and victimization varies between locations, and this should be something practitioners should take into account. Effectiveness also varies across different intervention programs, and particular components of anti-bullying programs have differential effectiveness in reducing bullying perpetration and victimization. The results of the present report lead to many recommendations and implications for teachers, schools, and practitioners who deal with school bullying amongst children and adolescents.

Recommendations for teachers and schools:

If implementing an existing anti-bullying program, practitioners should consider:

Previous evaluations of the effectiveness of anti-bullying programs in the same country, region, or culturally similar setting, as these factors may influence effectiveness.

The location and population for which the program was developed and evaluated initially, and whether this impacts previous measures of its effectiveness and its particular approach to tackling bullying.

A pre-intervention survey to explore the specific manifestations of bullying in their respective schools, to evaluate whether or not one particular program may address these issues better than another.

If implementing a new anti-bullying program, practitioners should consider:

Existing research reports and meta-analyses that assess specific intervention components and their effectiveness.

That whole-school anti-bullying campaigns can be effective, but they may not be the best strategy to combat bullying victimization; additional intervention components may also be needed.

That comprehensive anti-bullying programs should include intervention elements at multiple levels, including the school, class, parent, peer, and individual level. Targeted interventions are needed to help individual children that are particularly vulnerable to bullying victimization.

A pre-intervention survey to explore the specific manifestations of bullying in their respective schools to evaluate which components are the most effective, and practical, methods of reducing bullying victimization and perpetration.

That online forums, moderated by trained students, may be an efficient and cost-effective way to tackle bullying victimization.

That hot-spot supervision and specific strategies for dealing with bullying scenarios when it occurs are effective methods for preventing school-bullying perpetration and victimization.

Practitioners should take a number of factors into consideration when choosing an anti-bullying program. It is important to initially evaluate the nature, presence, and frequency of bullying in the relevant school. Bullying behaviors will not necessarily manifest in the same way in different countries, regions, communities, or schools, and thus may impact the effectiveness of any intervention program implemented. For example, the cross-national Health Behaviour in School-Aged Children (HBSC) study showed that greater income inequality predicted higher levels of bullying perpetration and victimization (Elgar et al. 2013 ). Therefore, implementing a program developed in a region with low-income inequality may not have the same level of effectiveness in an area of greater income inequality, as the causal roots of bullying are different.

The NoTrap! program was particularly effective, in comparison with other studies included in our meta-analysis, in reducing bullying victimization. This specific program was developed through several iterations and multiple evaluations in the same schools, but with different participants each year (Menesini et al. 2012 ; Palladino et al. 2012 , 2016 ). This suggests that schools should evaluate anti-bullying efforts on an ongoing basis and adapt programs according to the specific needs of the students, staff, and parents. Our meta-analysis did include several programs that adopted this approach, but they have not yet been repeatedly evaluated, and so are not included in the present report.

Practitioners should also consult the wealth of research and literature that exists in relation to effective anti-bullying programs. Research reports and meta-analyses of bullying intervention and prevention programs (e.g., Gaffney et al. 2019b ) can give practitioners a detailed overview about what works overall. Experts in the field have also produced a number of accessible handbooks and guides in relation to bullying issues (e.g., Patchin and Hinduja 2016 : Bullying today: bullet points and best practices ; Smith 2013 : Understanding School Bullying: Its Nature and Prevention Strategies ). Furthermore, journals such as this one, and interdisciplinary conferences such as the World Anti-Bullying Forum (next meeting in Dublin, June 2019), are key resources for teachers, school personnel, policy makers, and researchers to share and discuss important issues relating to bullying and its prevention.

Our results not only have important implications for teachers and schools. The results of our meta-analysis can have implications for researchers also. For example, 41 studies published between the years of 1983 and 2016 that reported the effectiveness of an anti-bullying program did not report enough statistical information. Frequently, authors included complicated advanced statistics to demonstrate the effectiveness of an anti-bullying program, but this information is not useful to meta-analysts. In addition, using advanced statistical methods may reduce the accessibility of evaluation studies for teachers and practitioners.

Thus, when reporting the evaluation data of an anti-bullying program, it is important to include basic descriptive statistics, such as the mean, standard deviation, and sample size. Alternatively, the frequency or prevalence of bullying perpetration and/or victimization should be reported as percentages to easily convert to odds ratio effect sizes. The second recommendation we would make is that more replication of scientific evaluations of anti-bullying programs is needed. Replication is essential in designing effective intervention programs. Yet our meta-analysis included 100 evaluations of approximately 65 anti-bullying programs, and only four of these programs had been evaluated three or more times.

We included roughly 65 different programs, as there was quite a bit of overlap in some of the intervention strategies included. For example, Trip et al. ( 2015 ) evaluated the ViSC program, yet also included elements of REBE. Therefore, the evaluated intervention is slightly different from the ViSC program evaluated by other researchers. The same can be said for the impact of implementation fidelity and quality on effect sizes. Previous studies in criminology, psychology, and other social sciences have found strong evidence to support the positive correlation between implementation quality and effect sizes for multiple outcomes (e.g., Farrington, Ttofi, and Losel 2016 ). Also, researchers could consider cost-benefit analysis of anti-bullying programs as a core aspect of evaluations. The few studies included in our meta-analysis that did conduct a cost-benefit analysis found desirable results (e.g., Bonell et al. 2015 ). Moreover, prominent researchers in the field have highlighted how using a metric to convert effect sizes to monetary values is a convincing way to communicate research findings to policy makers, government departments, and practitioners (Farrington and Koegl 2015 ).

Finally, the current paper is limited in its ability to inform on the effectiveness of intervention programs to reduce other forms of bullying, such as cyberbullying. Gaffney et al. ( 2019b ) recently reported that interventions are largely effective in reducing cyberbullying perpetration and victimization. However, more research needs to be conducted in this area as cyberbullying is a growing phenomenon amongst children and adolescents worldwide.

Concluding Remarks

This paper presents key findings and further analyses of a large-scale meta-analysis that explores the effectiveness of school-based anti-bullying programs (i.e., Gaffney et al. 2019b ). Overall, while school-bullying prevention programs are effective, there are significant differences between countries, regional areas, and existing intervention programs. Specifically, there is a lack of existing anti-bullying work in areas that report high levels of bullying behaviors and repeated evaluations of existing programs. We make several recommendations for practitioners and researchers and suggest that future research can be conducted to better understand what works in anti-bullying programming.

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Gaffney, H., Farrington, D.P. & Ttofi, M.M. Examining the Effectiveness of School-Bullying Intervention Programs Globally: a Meta-analysis. Int Journal of Bullying Prevention 1 , 14–31 (2019). https://doi.org/10.1007/s42380-019-0007-4

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EDITORIAL article

Editorial: advances in youth bullying research.

• 1 Department of Psychology, Social Science Research Center, Mississippi State University, Starkville, MS, United States
• 2 Social Science Research Center, Mississippi State University, Starkville, MS, United States

Editorial on the Research Topic Advances in Youth Bullying Research

Bullying amongst youth is a worldwide concern. Globally, as many as 246 million children reported experiencing bullying and school violence annually [ United Nations Educational Scientific Cultural Organization (UNESCO), 2019 ]. In the UNESCO report, 32% of children reported bullying victimization with the most common type being psychological or verbal aggression. This special issue highlights the prevalence as well as some of the predictors and buffers of types of bullying occurring among youth from a variety of countries. Specifically, this issue can speak to bullying concerns in Peru, China, Chile, Portugal, Spain, Poland, Russia, Mexico, and the United States.

Variation in Youth Bullying Statistics

Rates vary across samples in the present special issue. For example, contrasting current bullying statistics in the U.S. where bullying and other forms of victimization appear to be on the decline ( Musu-Gillette et al., 2018 ), researchers have found that the bullying prevalence in Peru has increased, as has the social, emotional, and behavioral impacts of victimization ( Arhuis-Inca et al. ). Also, in contrast to North American samples, where ~20% of students report bullying victimization, lower rates—16%—were reported in a Russian sample of 6,249 students ( Avanesian et al. ). These contributions alone demonstrate the importance of examining cultural differences in bullying.

Consequences of Youth Bullying Behavior

All authors recognized the significant harms of bullying. Research by Peng et al. examined these potentially devastating consequences. In their study of 4,241 7th to 12th grade students in China, they examined the relationship between bullying and self-harm. Their results indicated that different forms of bullying (physical, relational, verbal, and cyber) are associated with different harmful behaviors (self-harm, suicide attempts, and suicidal ideation). Most forms of bullying—except verbal—posed a significant risk for suicide attempts ( Peng et al. ). This is particularly troubling as the World Health Organization reports suicide as the fourth leading cause of death in 15–19-year-olds worldwide ( World Health Organization, 2021 ), and rates appear to be rising ( Zohuri and Zadek, 2020 ).

Individual Differences Associated With Bullying Perpetration

Understanding the individual difference variables that affect the experience of bullying and responses to bullying can help guide the implementation of more effective intervention strategies. Zhang et al. conducted a study of 1,631 middle and high school students, analyzing individual differences (i.e., Big Five personality, loneliness, and self-concept) and their influence on bullying behaviors via self-report measures. The links between personality variables and bullying behavior was mediated by loneliness, thus indicating the importance of addressing relational variables as a route for intervention.

Indeed, relationship variables were identified as important in other studies featured in this issue. For instance, Vagos and Carvalhais surveyed 375 youth between 15 and 19 years old to examine the relationship between their attachment quality with parents/peers and their likelihood of engagement in aggressive vs. prosocial behaviors. They found that peer attachment had an indirect effect on prosocial behaviors and quality maternal relationships indirectly resulted in a decrease in overt aggression and delinquency.

Stubbs-Richardson et al. tested the Multimotive Model (MMM), which measures prosocial, asocial, antisocial responses to bullying victimization in a sample of 605 American high school students. Relational variables were key to predicting whether victimized youth would choose a prosocial path over an antisocial response. Students who perceived having fewer supportive relationships were least likely to choose prosocial responses. Relatedly, those seeking help when bullied were more likely to report strong peer connections and family communication ( Sitnik-Warchulska et al. ).

Further research in Silesia is consistent with this relational narrative. Children engaging in bullying perpetration often reported low quality parental relationships ( Sitnik-Warchulska et al. ). Low quality family relationships were also linked to bullying victimization as revealed by a study of 2,415 Mexican youth (9–15 years old), where familial child abuse (i.e., emotional, physical, and sexual) was strongly linked to peer victimization (i.e., direct, indirect, and cyberbullying; Martin-Babarro et al. ).

Impact of School Climate on Youth Bullying

Youth bullying is also embedded in school culture. Researchers examining the validity of the Dual School Climate and School Identification Measure—Student (SCASIM-St15) in 2,044 Chilean school-aged children found that negative school climate is associated with tolerance of antisocial behavior ( Gálvez-Nieto et al. ). Students who hold a more positive perception of their school climate were less likely to break the rules; those who positively identify with their school may view authority figures more positively and thus be more willing to seek help.

Other aspects of school climate included examined how much students perceived having help and how well-equipped they were to deal with bullying. A study consisting of 75 Silesian students analyzed the relationship between the probability of help-seeking behaviors and bullying risk factors ( Sitnik-Warchulska et al. ). They found that the majority of participants exhibited help-seeking behaviors, most of which was directed toward family followed by peers ( Sitnik-Warchulska et al. ). This perceived presence of support proved to be vital in reducing bullying prevalence in schools.

Researchers in Russia, consistent with past work on school climate variables, noted that “Bullying…tends to develop more frequently in a competitive environment” ( Avanesian et al. , p. 1). They encourage schools to foster a less competitive context to decrease bullying.

In another study by Montero-Carretero et al. of 629 Spanish students between the ages of 12 and 14 years old examined the relationship between school climate and bullying behaviors. Results indicated that when students perceived greater teacher support and rule clarity, they experienced more positive perceptions of school climate and lower levels of victimization ( Montero-Carretero et al. ). Thus, across cultures, various improvements in school climate appear promising for reducing the harm of bullying, if not reducing the bullying behavior itself.

Additional Considerations for Interventions

Some of the papers featured herein tested specific interventions whereas others identified additional routes for intervention beyond what was discussed above. For example, researchers examining the effects of the “Zero Violence Brave Club” as a prevention effort among young children found that, after its implementation, participants became more aware of the problem, were less favorable toward aggression, valued kindness, and increased bystander peer intervention ( Roca-Campos et al. ). Compellingly, this research involved a diversity of school environments and showed effects across contexts.

Outside of the school walls, Stives et al. point to the importance of interventions involving more than just the children. They examined parental perspectives of bullying. Results showed that most parents find bullying to be problematic but feel that their children under-reported to them about instances of bullying. The researchers recommend the greater inclusion of parents in anti-bullying efforts as there was a strong interest among parents interviewed in addressing the problem.

Beliefs about bullying are also influenced by societal values. When examining the relationship between Belief in a Just World (BJW) Hypothesis and responses to bullying, researchers found that higher global BJW, instead of personal BJW, was correlated with minimization of perpetrator actions ( Voss and Newman ). Therefore, belief in a just world may constitute victim blaming which is counterproductive to bullying prevention efforts. Thus, countering these attitudes could be means to improve assistance afforded to victims.

What is consistently shown, no matter the cultural context, is that bullying hurts, carrying significant negative outcomes for bullies, victims, and bully-victims. Research evidence collected here also revealed factors that may be helpful for intervention purposes. Namely, the research shows how changes to school climate—such as reducing competition—and the involvement of the community—such as parents and peers—can reduce the impact of bullying and bullying prevalence, as well as enhance prosocial behavior. In particular, the importance of social connection for curbing antisocial behavior was a consistent theme cross-culturally. As bullying is a worldwide problem it requires cross-cultural research to address the associated problems and outcomes. The present special issue addresses this need.

Author Contributions

KW focused on article summaries. MS-R on the introduction, fact-checking, and references. HS on conclusion, editing of the entirety, checking against results, cutting to meet word limits, refinement, and flow. All author contributed to the writing, editing, summaries, and fact-checking of the material within this manuscript.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

We wish to thank all of the authors and reviewers who contributed to bringing this special issue to fruition.

Musu-Gillette, L., Zhang, A., Wang, K., Zhang, J., Kemp, J., Diliberti, M., et al. (2018). Indicators of School Crime and Safety: 2017 (NCES 2018-036/NCJ 251413) . National Center for Education Statistics, U.S. Department of Education, and Bureau of Justice Statistics, Office of Justice Programs, U.S. Department of Justice.

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United Nations Educational Scientific and Cultural Organization (UNESCO). (2019). Behind the Numbers: Ending School Violence and Bullying . Paris: United Nations Educational, Scientific and Cultural Organization.

World Health Organization. (2021). Suicide Worldwide in 2019: Global Health Estimates . Geneva: World Health Organization.Licence: CC BY-NC-SA 3.0 IGO.

Zohuri, B., and Zadek, S. (2020) Global suicide rate among youngsters increasing significantly. J. Neurol. Disord. doi: 10.32474/OJNBD.2020.03.000175. [Epub ahead of print].

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Keywords: bullying, adolescence, prevention, cross-cultural, child psychology, aggression

Citation: Sinclair HC, Wilson KJ and Stubbs-Richardson M (2022) Editorial: Advances in Youth Bullying Research. Front. Psychol. 13:860887. doi: 10.3389/fpsyg.2022.860887

Received: 23 January 2022; Accepted: 21 February 2022; Published: 07 June 2022.

Reviewed by:

Copyright © 2022 Sinclair, Wilson and Stubbs-Richardson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: H. Colleen Sinclair, csinclair@ssrc.msstate.edu

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

All of the Following Are True About a Pure Bully

Question 25

All of the following are true about a pure bully, except:

A) has never been the victim of a bully B) has very poor self-esteem C) bullies to establish power D) chooses victims who are easy to intimidate E) often not even angry with the victim

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Q21: Mrs. Morales said, "Mark, I know you

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Q24: Sam teases William. What has Sam engaged

Q26: All of the following are true of

Q27: The bully/victim: A) has bullied others B) has been

Q28: A bystander: A) is a witness to bullying B)

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Q30: Unresponsive parents often: A) fail to meet the

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Anonymous messaging app targeting teens: Read the disturbing allegations in FTC and Los Angeles DA action against NGL

An anonymous messaging app marketed to kids and teens: What could possibly go wrong? A lot, allege the FTC and the Los Angeles District Attorney’s Office . A complaint against NGL Labs and founders Raj Vir and Joao Figueiredo alleges violations of the FTC Act, the Children’s Online Privacy Protection Rule (COPPA), the Restore Online Shoppers’ Confidence Act (ROSCA), and the California Business and Professions Code. The company also made AI-related claims the complaint challenges as deceptive. The $5 million financial settlement merits your attention, but it’s the permanent ban on marketing anonymous messaging apps to kids or teens that’s particularly notable. 

Among the most downloaded products in app stores, the NGL app is named for the text shorthand for “Not Gonna Lie,” but based on the complaint allegations, it could stand for “Not Gonna be Legal.” The app purports to allow users to receive anonymous messages from friends and social media contacts. The defendants expressly pitched it as a “fun yet safe place” for “young people” to “share their feelings without judgment from friends or societal pressures.” For parents wary of their kids’ use of an anonymous messaging app, the defendants assuaged their concerns by touting “world class AI content moderation” that enabled them to “filter out harmful language and bullying.” Consumers who downloaded the app were prompted to create an account that collected a substantial amount of personal information, but NGL didn’t ask how old they were and didn’t use any form of age screening. 

You’ll want to read the complaint for details, but in general terms, app users could post pre-generated prompts to their social media accounts like “Send me a pickup line and I’ll tell you if it worked” or “Share an opinion that’ll get you cancelled” which allowed viewers of the prompts to write an anonymous message in response. In addition, many users received anonymous messages like “are you straight?” “I’ve had a crush on you for years and you still dont know lmao,” and “would you say yes if I asked you out – A.” When a recipient opened the message, a button appeared inviting the person to find out “Who sent this?” with a paid NGL Pro subscription. Eager to learn the sender’s identity, many recipients clicked on that button. 

That’s the briefest summary of what NGL told users and parents, but a closer look at the six-count complaint reveals what the FTC and the Los Angeles DA’s Office say was really going on behind the scenes.

The FTC challenges the defendants’ marketing of its anonymous messaging app to children and teens as an unfair practice. According to the complaint, defendant Figueiredo urged employees to get “kids who are popular to post and get their friends to post” and noted that the “best way is to reach out” on Instagram “by finding popular girls on high school cheer pages.” As another NGL executive observed, “We need high schoolers not 20 something[s].” But for any parent of a teenager – or anyone who’s been a teenager – the inevitable consequences of an anonymous messaging app targeting teens wouldn’t be hard to predict. As one high school assistant principal told the defendants, students were using the app to send “threatening” and “sexually explicit content” that was “significantly affecting the mental health and well-being of our students.” According to the complaint, NGL received numerous reports of cyberbullying, harassment, and self-harm and yet chose not to change its marketing strategy or how its product operated. 

In addition, the FTC and the Los Angeles DA’s Office allege the defendants used multiple misrepresentations to push their app. For example, many of those anonymous messages that users were told came from people they knew – for example, “one of your friends is hiding s[o]mething from u” – were actually fakes sent by the company itself in an effort to induce additional sales of the NGL Pro subscription to people eager to learn the identity of who had sent the message. But even after receiving numerous complaints describing the anonymous messages as “invasive,” “anxiety inducing,” and “hateful,” NGL’s in-house response was nothing short of gleeful. The complaint cites the following comment from defendant Figueiredo: “These ppl addicted . . . there’s people sharing the [NGL App link] EVERY day and all they get is fake questions 😂.” 

The FTC and the Los Angeles DA’s Office say NGL’s promise to parents to protect kids through the use of “world class AI content moderation” proved misleading, too. According to the complaint, the company’s much vaunted AI often failed to filter out harmful language and bullying. It shouldn’t take artificial intelligence to anticipate that teens hiding behind the cloak of anonymity would send messages like “You’re ugly,” “You’re a loser,” “You’re fat,” and “Everyone hates you.” But a media outlet reported that the app failed to screen out hurtful (and all too predictable) messages of that sort.

What’s more, even if users upgraded to NGL Pro, they still wouldn’t be told who sent the message, rendering that claim deceptive, too. But that wasn’t the only problem with the defendants’ practices. According to the complaint, consumers who clicked on the "Who sent this?" button were not clearly told that this was a recurring negative option – not a one-time purchase – and that defendants would charge them $9.99 (and later $6.99) per week for NGL Pro.

The defendants were well aware of consumer complaints about unexpected charges and the ineffectiveness of the “Who sent this?” feature. Even Apple warned the defendants that their product “attempts to manipulate customers into making unwanted in-app purchases by not displaying the billed amount clearly and conspicuously to the users.” How did the defendants respond? In a text discussion with defendants Vir and Figueiredo, NGL’s Product Lead succinctly summarized the company’s reaction to consumer complaints: “Lol suckers.” According to the FTC, the defendants’ use of an online negative option to hype sales of their NGL Pro app violated ROSCA , which requires companies that sell products online with negative options to clearly and conspicuously disclose all material terms of the transaction before obtaining the consumer’s billing information and to get the consumer’s express informed consent before making the charge.

The FTC also says the company collected and indefinitely stored users’ personal data, including their Instagram and Snapchat usernames and profile pictures, information about their location, and their browsing history. The lawsuit alleges the defendants violated the  COPPA Rule by failing to provide proper notice to parents, failing to get verifiable parental consent, and failing to provide a reasonable way for parents to stop further use of or delete the data of kids under 13.

The complaint also alleges multiple violations of California consumer protection laws. 

The proposed settlement includes a $5 million financial remedy – $4.5 million for consumer redress and a $500,000 civil penalty to the Los Angeles DA’s office. But most importantly, the order bans the defendants from offering anonymous messaging apps to kids under 18. How long will that ban be in place? Forever. 

Among other things, the settlement requires the defendants to implement an age gate to prevent current and future users under 18 from accessing the app and mandates the destruction of a substantial amount of user information in the defendants’ possession. In addition, the defendants must get consumers’ express informed consent before billing them for any negative option subscription, must provide a simple mechanism for cancelling those subscriptions, and must send reminders to consumers about negative option charges.

What guidance can other companies take from the settlement?

The FTC will use all of its tools to protect both kids and teens. Certainly COPPA is (and will remain) an important tool for protecting kids under 13 and for ensuring that parents – not tech companies – remain in control of children’s personal information. But this action also reinforces the FTC’s concern about information practices that pose a risk to teenagers’ mental and physical health.

Don’t tout your company’s use of AI tools if you can’t back up your claims with solid proof. The defendants’ unfortunately named “Safety Center” accurately anticipated the apprehensions parents and educators would have about the app and attempted to assure them with promises that AI would solve the problem. Too many companies are exploiting the AI buzz du jour by making false or deceptive claims about their supposed use of artificial intelligence . AI-related claims aren’t puffery. They’re objective representations subject to the FTC ‘s long-standing substantiation doctrine.

There’s nothing “LOL-worthy” about ROSCA violations. For decades the FTC has used both the FTC Act and the  Restore Online Shoppers’ Confidence Act to fight back against illegal negative options. According to the complaint, the defendants enticed teens with anonymous questions like “would you say yes if I asked you out” and then presented them with that hard-to-resist “Who sent this?” button without clearly explaining that the company was enrolling them in a negative option subscription and charging them every week. That the defendants used this illegal bait-and-switch tactic against teens and then laughed about it adds brazen insult to the financial injury they inflicted.  

• Consumer Protection
• Bureau of Consumer Protection
• Online Advertising and Marketing
• Advertising and Marketing Basics
• Payments and Billing
• Children's Privacy
• Consumer Privacy
• Artificial Intelligence

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What possible good or benefit could derive to people from using this--to adults, to teens, to children--to ANYONE except to line the pockets of the scornful, amoral developers of this horrible technology?

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