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Practice Profile

School-Based Bullying Prevention Programs

Evidence Ratings for Outcomes:

Effective - More than one Meta-Analysis Juvenile Problem & At-Risk Behaviors - Bullying
Effective - More than one Meta-Analysis Victimization - Being Bullied
Effective - One Meta-Analysis Mental Health & Behavioral Health - Bystander Intervention
No Effects - One Meta-Analysis Mental Health & Behavioral Health - Empathy for the Victim

Practice Description

Practice Goals
The growing awareness of the problem of bullying has led to the development of numerous antibullying interventions, as well as the passage of state and local laws and policies on bullying. These efforts aim to reduce bullying and victimization (being bullied). Some interventions aim to increase positive involvement in the bullying situation from bystanders or witnesses.

Many definitions of bullying exist, but they often include the following aspects to distinguish bullying from other types of aggression or violence:

  • The behavior stems from an intent to cause fear, distress, or harm.
  • The behavior is repeated over time.
  • There is a real or perceived imbalance of power between the bully and victim (Ferguson et al. 2007; Merrell et al. 2008; Nansel et al. 2001).
In 2013,the Centers for Disease Control and Prevention (CDC) developed a definition of bullying that captures all three of these elements:  Bullying is any unwanted aggressive behavior(s) by another youth or group of youths who are not siblings or current dating partners that involves an observed or perceived power imbalance and is repeated multiple times or is highly likely to be repeated (Gladden et al. 2013).

Bullying can be physical (e.g., hitting, punching), verbal (e.g., name-calling, teasing), or psychological/relational (e.g., rumors, social exclusion). Typically, individuals involved with bullying are classified as bullies, bully–victims, victims, or bystanders.

Target Population
School-based bullying prevention programs are implemented in school settings, where students report bullying as a significant problem. The most recent data in the United States covers the 2010–11 school year, during which 27.8 percent of students ages 12–18 reported having been bullied at school. Of these youth,
  • Almost 18 percent reported having been made fun of, called names, or insulted.
  • About 18 percent reported being the subject of rumors.
  • Eight percent reported being pushed, shoved, tripped, or spit on.
  • More than 5 percent reported being excluded from activities.
  • Five percent reported being threatened with harm.
  • More than 3 percent reported being forced to do things they didn’t want to do.
  • Almost 3 percent had property destroyed.
  • Nine percent of students reported being cyberbullied. (Robers et al. 2013)
Across studies, the rates of students involved with bullying range from 10 percent to 50 percent of children and youths (Atria et al. 2007; Cook et al. 2010), and rates of students involved in cyberbullying range up to 30 percent (Mishna et al. 2012).

Practice Components
Typical types of interventions include the following (Limber 2003, “Misdirections” 2012).

Awareness-raising efforts. Efforts can consist of assemblies for students, parent meetings, or in-service training for teachers to make participants aware of the problem of bullying. While raising awareness is important, such efforts are insufficient to change cultural norms and bullying behaviors.

School exclusion. These efforts include “zero tolerance” or “three strikes and you’re out”–type policies. When schools identify a student as a bully, that student is excluded from school. Research suggests that school exclusion interventions do not work: they can decrease the reporting of incidents because the sanctions are so severe, and through suspension or expulsion they negatively affect the students who are most in need of prosocial involvement at school.

Therapeutic treatment for bullies. This approach might include classes in anger management or efforts to boost self-esteem and empathy. Again, these types of programs are unlikely to effectively address the problem of bullying because they are based on faulty assumptions about the motivating factors for most bullies. Moreover, if bullies are grouped for treatment, behavior may further suffer as students reinforce antisocial and bullying behavior.

Mediation and conflict resolution. These programs are often used to help school staff address aggressive and violent behavior between students. However, these types of programs can backfire when used to resolve bullying situations, because they imply that both parties (bully and victim) are to blame. Moreover, these interactions may further victimize the target.

Curricular approaches. Numerous curricula have been developed for use in schools. In general, these programs try to explain bullying and its effects, to teach strategies to avoid bullying or for intervening, and to build social cohesion among students. Many of these programs have been evaluated, and some have been found to be effective in improving desired outcomes (see Related Programs for a list of curriculum-based programs included on

Comprehensive approaches. These approaches include classroom-based programs. They target the larger school community in an effort to change school climate and norms. They acknowledge the need for a long-term commitment to addressing bullying specifically, but they often do so as part of a larger violence prevention effort (Limber 2003). These approaches need to be developed to address the needs of a particular school or community; simply dropping prefabricated programs into place rarely works (Seeley et al. 2011; “Misdirections” 2012).

Practice Theory
While numerous antibullying programs have been developed, most “seem to be based on common-sense ideas about what works in preventing bullying rather than on specific theories of bullying” (Ttofi and Farrington 2009, 21). Ttofi and Farrington argue that more work must be done to develop and test theories of how antibullying programs can work.

A review of childhood bullying literature by Liu and Graves (2011) resulted in the identification of four major frameworks for understanding bullying and its predictors.
  • Ethological perspective. This framework considers the advantages stemming from bullying and sees it as a “tool for achieving social dominance—particularly in adolescence” (560).
  • Ecological and socioecological theories. This framework focuses on the interactions between an individual and his or her social environment and considers how the closer and broader environments affect individual behavior. This framework attends to factors such as school policies, societal attitudes, and social norms.
  • Cognitive and social–cognitive theories. This framework is influenced by theories of cognition and neurobiology. The framework considers individual characteristics, such as emotional dysregulation, impulsivity, and antisocial disorders. These factors can affect the ways in which individuals process information.
  • Genetic and other biologic theories. This framework considers how biology (such as autonomic tone) and genetics (such as levels of hormones) influence aggression and violence.
These frameworks give a useful overview of the types of categorizations in the literature, although other categorizations can also be made. For example, Mishna (2012) identifies six frameworks: a) ecological systems, b) social learning, c) cognitive behavioral, d) attribution, e) lifestyles exposure, and f) resilience.

For information on program components that may affect the effectiveness of antibullying programs, please see “Other Information.”

Meta-Analysis Outcomes

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Effective - More than one Meta-Analysis Juvenile Problem & At-Risk Behaviors - Bullying
Two meta-analyses looked at the impact of bullying prevention programs on bullying. Both found that antibullying programs were effective in reducing bullying. Farrington and Ttofi (2010) report a positive, though nonsignificant, effect size for bullying (OR = 1.1). This effect size is based on the findings from 14 randomized controlled studies. Wong (2009) reports that the weighted mean effect size indicates that the programs had a small positive, significant impact in reducing bullying (d = .109). This effect size is based on 22 effect sizes for bullying outcomes from 19 studies involving 18,903 students.
Effective - More than one Meta-Analysis Victimization - Being Bullied
Two meta-analyses considered the outcome of being bullied. Both found that antibullying programs were effective in reducing victimization. Farrington and Ttofi (2010) reported a significant effect size for reducing victimization (OR = 1.17). This effect size is based on 11 studies. Wong (2009) also reported that the interventions had a small, positive effect in reducing victimization (d = 0.188). This effect size is based on 25 effect sizes for victimization outcomes from 22 studies involving 25,361 students.
Effective - One Meta-Analysis Mental Health & Behavioral Health - Bystander Intervention
One meta-analysis looked at the impact of antibullying programs on bystander behavior. Polanin and colleagues (2012) found that programs increased bystander intervention (g = .20), meaning students were more likely to intervene in situations when they witnessed another student being bullied. This finding is based on 12 studies and is statistically significant.
No Effects - One Meta-Analysis Mental Health & Behavioral Health - Empathy for the Victim
One meta-analysis looked at the impact of antibullying programs on the bystander’s empathy for the bullying victim. Polanin and colleagues (2012) found that the programs had a positive, but nonsignificant effect (g = .05). This finding is based on eight studies.
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Meta-Analysis Methodology

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Meta-Analysis Snapshot
 Literature Coverage DatesNumber of StudiesNumber of Study Participants
Meta-Analysis 11983 - 20095315777
Meta-Analysis 21980 - 20101212874
Meta-Analysis 31996 - 20022225361

Meta-Analysis 1
Farrington and Ttofi (2010) conducted a meta-analysis of school-based programs designed to reduce bullying and victimization (being bullied). They included studies that concentrated on programs explicitly designed to decrease bullying in K–12 and that explicitly measured bullying (some analyses include more general violence or aggression reduction programs). To facilitate a search for such programs, they used the following definition of bullying: “physical, verbal, or psychological attack or intimidation that is intended to cause fear, distress, or harm to the victim; and an imbalance of power, with the more powerful child (or children) oppressing less powerful ones” (2010, 15). This definition excludes the dimension of repetition that is often included in definitions of bullying.

To be included, studies needed a comparison group. Farrington and Ttofi divided the eligible studies into four categories: a) randomized control trials, b) before and after quasi-experimental designs (QEDs), c) other QEDs, and d) age-cohort designs. The search included English and non-English studies, as well as published articles and unpublished manuscripts. The search covered literature available from 1983 through May 2009. There was no sample size limitation.

The researchers identified 89 reports (of 53 evaluations). Nine of these evaluations did not provide enough information to calculate effect sizes. The report includes descriptions of all the programs that were evaluated. No information on the racial/ethnic breakdown of the studies’ samples is provided; the authors provide information on the gender breakdown of individual studies, when that information is available. Evaluations were included of programs in the United States, Canada, Western Europe, Czechoslovakia, Australia, New Zealand, and South Africa.

The measure of effect size used in this analysis is the odds ratio. The authors used a random effects model to calculate the weighted mean effect sizes. Because there was a significant difference between the weighted mean odds ratio effect sizes for randomly controlled trials (RCTs) and the other three designs, the effect sizes for bullying and victimization based on the RCTs were used for this review instead of the overall weighted mean odds ratio effect size. The number of participants in the RCTs totaled 15,777.  The odds ratio for program effect on bullying is based on findings from 14 studies, while the effect size for victimization is based on 11 studies.

Meta-Analysis 2
Polanin, Espelage, and Pigott (2012) focused their meta-analysis on the effect of school-based bullying prevention programs on increasing bystander intervention in bullying situations. They included studies of programs implemented in K–12 school settings that explicitly measured the behavior of bystanders (also known as passersby, observers, or witnesses). The measure of bystander intervention included intention to intervene, intention to stop bullying, direct intervention, or difficulty in responding assertively to a bullying situation. The researchers also included a measure of empathy for the victim, such as “feeling sad about students who are bullied” and “unpleasantness when another student is being bullied.

To be included in the analysis, studies needed to include a control group. The authors searched five electronic databases and bibliographies of retrieved documents for English-language studies published or conducted between 1980 and 2010. They identified 12 studies that included a total of 12,874 participants. No information is provided on the racial/ethnic or gender composition of the study participants. Programs were located in Western Europe and the United States.

The authors used the standardized mean difference to determine effect sizes for each study using a continuous scale for outcome measures; all effect size metrics were bias corrected using Hedge’s small sample correction (g). The authors calculated logged odds ratio effect sizes for studies that used a categorical outcome measure (which were converted into a standardized mean difference). They used a random effects model for their analysis.  The weighted mean effect size for bystander intervention is based on 12 studies; the weighted mean effect size for empathy (toward the victim) is based on eight studies.

Meta-Analysis 3
Wong (2009) conducted a meta-analysis of school-based bullying prevention programs for students K–12. To be included, studies had to use an experimental design or a pretest/posttest independent-groups design; the analysis excluded studies that used age cohort designs and QEDs with no pretest measure. The author searched 14 electronic databases from the inception of database through April 2008, as well as the bibliographies of retrieved documents, and included English-language published (journal articles and book chapters) and unpublished (dissertations and reports) studies. The studies needed to include a measure of bullying or victimization. Samples could be as small as 20 participants per group. Although there was no date limit for publication, all eligible studies were published between 1996 and 2008. Studies covered programs in North America (11) and Europe or Australia (11). No information is given on the racial/ethnic or gender composition of the samples included.

The standardized mean difference effect size was calculated for studies using continuous outcome measures. For one study, Wong converted the product moment correlation and used the Cox-transformed log odds ratio to calculate effect sizes for studies using dichotomous outcome measures. A cluster adjustment of the effect sizes and standard errors was made to take the nesting of students in classrooms and schools into account. The author used a fixed effects model to calculate the standardized mean effect size.

The weight mean effect size for bullying is based on 22 effect sizes for bullying outcomes from 19 studies involving 18,903 students. The effect size for reducing victimization is based on 25 effect sizes from 22 studies involving 25,361 students.
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There is no cost information available for this practice.
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Other Information

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Several meta-analyses included additional tests—called moderator analyses—to see whether any factors strengthened the likelihood that bullying prevention programs improved outcomes. The results of these analyses have produced mixed evidence. For instance, both Polanin and colleagues (2012) and Farrington and Ttofi (2010) found that programs had larger effects for older students than for younger students. However, Wong (2009) found there was no significant correlation between the magnitude of the effect size and mean participant age. Farrington and Ttofi (2010) found that certain program components were associated with decreases in bullying and victimization. These components included parent training/meetings, improved playground supervision, disciplinary methods, classroom management, teacher training, classroom rules, whole-school antibullying policy, school conferences, information for parents, and cooperative group work. Certain components were also associated with decreases in victimization (e.g., disciplinary methods, parent training/meetings, videos and cooperative group work, duration and intensity of the program for children and teachers). In contrast, Wong (2009) found no significant correlation between the magnitude of effect size and these components (e.g., level of implementation, program duration, curriculum, whole-school antibullying policy, classroom antibullying rules, teacher training, individual work with bullies and/or victims, peer mediation or mentoring, parent information or meetings).
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Evidence-Base (Meta-Analyses Reviewed)

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These sources were used in the development of the practice profile:

Meta-Analysis 1
Farrington, David P., and Maria M. Ttofi. 2010. School-Based Program to Reduce Bullying and Victimization. Campbell Systematic Reviews 2009:6.

Meta-Analysis 2
Polanin, Joshua R., Dorothy L. Espelage, and Therese D. Pigott. 2012. “A Meta-Analysis of School-Based Bullying Prevention Programs’ Effects on Bystander Intervention Behavior.” School Psychology Review 41(1):47–65.

Meta-Analysis 3
Wong, Jennifer S. 2009. No Bullies Allowed: Understanding Peer Victimization, the Impacts on Delinquency, and the Effectiveness of Prevention Programs. Dissertation submitted to the Pardee Rand Graduate School.
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Additional References

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These sources were used in the development of the practice profile:

Atria, Moira, Dagmar Strohmeier, and Christiane Spiel. 2007. “The Relevance of the School Class as Social Unit for Unit for the Prevalence of Bullying and Victimization.” European Journal of Developmental Psychology 4(4):372–87.

Cook, Clayton R., Kirk R. Williams, Nancy G. Guerra, Tia E. Kim, and Shelly Sadek. 2010. “Predictors of Bullying and Victimization in Childhood and Adolescence: A Meta-Analytic Investigation.” School Psychology Quarterly 25(2):65–83.

Ferguson, Christopher J., Claudia San Miguel, John C. Koburn Jr., and Patricia Sanchez. 2007. “The Effectiveness of School-Based Antibullying Programs: A Meta-Analytic Review.” Criminal Justice Review 3(4):401–14.

Gladden R. Matthew, Alana M. Vivolo-Kantor, Merle E. Hamburger, and Corey D. Lumpkin. 2014. Bullying Surveillance Among Youths: Uniform Definitions for Public Health and Recommended Data Elements, Version 1.0. Atlanta, GA; National Center for Injury Prevention and Control, Centers for Disease Control and Prevention and U.S. Department of Education.

Limber, Susan P. 2003. “Efforts to Address Bullying in U.S. Schools.” American Journal of Health Education 34(5):S–23–29.

Liu, Jianghong, and Nicola Graves. 2011. “Childhood Bullying: A Review of Constructs, Concepts, and Nursing Implications.” Public Health Nursing 28(6):556–68.

Merrell, Kenneth W., Barbara A. Gueldner, Scott W. Ross, and Duane M. Isava. 2008. “How Effective Are School Bullying Intervention Programs? A Meta-Analysis of Intervention Research.” School Psychology Quarterly 23(1):26–42. (This study was reviewed but did not meet CrimeSolutions criteria for inclusion in the overall practice rating.)

“Misdirections in Bully Prevention and Intervention.” 2012. Webpage at

Mishna, Faye. 2012. Bullying : A Guide to Research, Intervention, and Prevention. New York, N.Y.: Oxford University Press.

Mishna, Faye, Mona Khoury–Kassabri, Tahany Gadalla, and Joanne Daciuk. 2012. “Risk Factors for Involvement in Cyber Bullying: Victims, Bullies and Bully–Victims.” Children & Youth Services Review 34(1):63–70.

Nansel, Tonja R., Mary Overpeck, Ramani S. Pilla, W. June Ruan, Bruce Simons–Morton, and Peter Scheidt. 2001. “Bullying Behaviors Among U.S. Youth: Prevalence and Association With Psychosocial Adjustment.” JAMA 285(16):2094–2100.

Robers, Simone, Jana Kemp, Jennifer Truman, and Thomas D. Snyder. 2013. Indicators of School Crime and Safety: 2012. Washington, D.C.: U.S. Department of Education, Institute of Education Sciences, National Center for Education Statistics.

Seeley, Ken, Martin L. Tombari, Laurie J. Bennett, and Jason B. Dunkle. 2011. “Bullying in Schools: An Overview.” Juvenile Justice Bulletin. Washington, D.C.: U.S. Department of Justice, Office of Justice Programs, Office of Juvenile Justice and Delinquency Prevention.

Smith, Peter K., Helen Cowie, Ragnar F. Olafsson, and Andy P.D. Liefooghe. 2002. “Definitions of Bullying: A Comparison of Terms Used, and Age and Gender Differences, in a 14-Country International Comparison.” Child Development 73(4):1119–33.

Ttofi, Maria M., and David P. Farrington. 2009. “What Works in Preventing Bullying: Effective Elements of Antibullying Programs.” Journal of Aggression, Conflict, and Peace Research 1(1):13–24.
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Related Programs

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Following are programs that are related to this practice:

KiVa Antibullying Program Promising - More than one study
An elementary school-based program to reduce school bullying and victimization. The program was designed for national use in Finnish schools. The program is rated Promising. KiVa schools self-reported less bullying, victimization and peer-reported victimization; but not for peer-reported bullying (except for older student reports were lower).

Positive Action Effective - More than one study
The program is designed to improve youth academics, behavior, and character, and can be used by schools, families, or communities. The program is rated Effective. Treatment students reported less substance use, problem behaviors, and violent behavior than the control group. There was a 41 percent reduction in bullying behaviors. Findings regarding sexual activity and disruptive behaviors were not statistically significant.

The Leadership Program’s Violence Prevention Project Promising - One study
A school-based prevention program, targeting 12 and 16 year olds, designed to prevent violence by enhancing conflict-resolution skills. The program is rated Promising. At follow-up, participants were using more pro-social verbal skills and had positive growth rates of peer support. Students not receiving the curriculum grew more accepting of aggression over time, while program participants maintained aggression tolerance levels.

Second Step®: A Violence Prevention Curriculum for Elementary School (2002 Edition) Effective - More than one study
A prevention program designed to reduce impulsive and aggressive behavior in children and adolescents by increasing their social competency skills. The program is rated Effective. The intervention group showed significant gains in social competence at varying times. There were improvements among students in measures of anxiety. Girls appeared to have higher scores for some behavioral measures and sixth grade boys had a decrease in externalizing problem behaviors.

Steps to Respect® Effective - More than one study
A school-based antibullying program that teaches social and emotional management skills to elementary school students. The goal is to help improve relationships and buffer the detrimental effects of bullying. The program is rated Effective. There were lower levels of bullying outcomes in the intervention group relative to the control group (e.g., observed bullying behavior, nonbullying aggression, destructive bystander behavior and students involved in malicious gossip).

Success in Stages® Program Promising - More than one study
An anti-bullying program that incorporated all students’ involved—victims, passive bystanders, and bullies. The program is rated Promising. One study found the treatment groups’ results diminished over time for bullying and victimization; but a treatment showed the effect of no longer being a passive bystander. A second study found that middle and high school student treatment groups reported becoming non-bullies, no longer being victims or bystanders.

WITS Primary Program Promising - More than one study
A community-based, schoolwide intervention aimed at children in grades 1 through 3 that targets socially competent behaviors and risks for peer victimization. The program was rated Promising. The program was shown to have significant positive effects on physical and relational victimization and social competence, but not on social responsibility or physical aggression.

Stop School Bullying (Greece) Effective - One study
A preventative, school-based program for students in 4th, 5th, and 6th grades (ages 9–12) that sought to reduce rates of bullying and victimization within elementary schools. The program is rated Effective. Evaluation results suggest that the program significantly reduced bullying and victimization rates at schools that implemented the program compared with a control group of schools that did not.

Pre-K RECAP Promising - One study
A semi-structured, school-based intervention program developed for pre-kindergarten students seeking to improve emotional and behavioral problems and promote social skills development. The program is rated Promising. Evaluation results showed no significant differences regarding parent-rated behavioral problems or social skill, yet teacher ratings of child behavioral problems and social skills significantly improved in the intervention group.

Social Aggression Prevention Program (SAPP) No Effects - One study
This is a school-based, small group program designed to prevent social aggression and increase empathy, prosocial behavior, and social problem-solving skills among fifth-grade females. The program is rated No Effects. While program participants self-reported more pro-social responses to hypothetical scenarios, there were no significant changes in behaviors as described by teachers and peers.

Second Step: Student Success Through Prevention Middle School Program (2008 Edition) No Effects - One study
This is a universal, school-based social-emotional learning program aimed at reducing violence and encouraging academic success among middle school students. The program is rated No Effects. While the program had a statistically significant impact on reducing physical aggression, there was no statistically significant impact on sexual-violence victimization and perpetration, peer victimization, bullying victimization and perpetration, cyberbullying, or homophobic name calling.

Second Step for Elementary School (2011 Edition) No Effects - One study
This is a school-based, social–emotional learning program for elementary school students. Teachers incorporate 25-40-minute lessons within the usual classroom curriculum. The program is rated No Effects. The treatment group displayed a statistically significant reduction in hyperactivity; however, there were no statistically significant differences between the treatment and control groups on measures of conduct problems, peer problems, social–emotional competence, or disruptive behaviors.
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Practice Snapshot

Age: 5 - 18

Gender: Both

Settings: School

Practice Type: Bullying Prevention/Intervention, Classroom Curricula, School/Classroom Environment, Victim Programs

Unit of Analysis: Persons