Evidence Rating for Outcomes
Juvenile Problem & At-Risk Behaviors | Bullying |
Victimization | Overall bullying victimization |
Victimization | Relational bullying victimization |
Victimization | Physical bullying victimization |
Victimization | Bystander intervention |
Mental Health & Behavioral Health | Empathy for the victim |
Victimization | Verbal bullying victimization |
Date:
The practice includes programs designed to reduce bullying perpetration and victimization and to increase positive bystander behavior in bullying situations. The practice is rated Effective for reducing bullying perpetration (e.g., overall and physical), reducing bullying victimization (e.g., overall and relational), and increasing positive bystander behavior. The practice is rated No Effects for increasing bystander empathy for bullying victims and reducing verbal bullying victimization.
Practice Goals/Target Population
The goals of bullying prevention programs are to reduce all types of bullying perpetration and victimization and to increase positive bystander behavior in bullying situations. Although varying definitions of bullying exist, to distinguish bullying from other types of aggression or violence these definitions often include the following aspects: 1) the behavior stems from an intent to cause fear, distress, or harm; 2) the behavior is repeated over time; and 3) there is a real or perceived imbalance of power between the individual who engages in bullying and the individual who is victimized (Ferguson et al. 2007; Merrell et al. 2008; Nansel et al. 2001). The Centers for Disease Control and Prevention developed a definition of youth bullying that encompasses all three of these elements, characterizing bullying as any unwanted aggressive behavior (or behaviors) 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. 2014). Further, bullying may be physical, verbal, or relational. Physical bullying is a direct type of bullying that involves physical aggression such as hitting, pushing, or kicking. Verbal bullying is also a direct form of bullying that can involve teasing, threatening, and name calling but does not include physical aggression. In contrast, relational bullying is defined as indirect nonphysical aggression that can include social rejection, rumor spreading, and exclusion (Kennedy 2020).
Finally, youths can be involved in bullying, not only through perpetration and/or victimization but also as "bystanders." A bystander is defined as an individual who lacks participation in bullying scenarios as either through perpetration or victimization. The role of the bystander is often described in relation to sustaining or preventing the bullying behavior such as reinforcer (e.g., laughing or seeing what is happening), assistant (e.g., follower of the individual engaged in bullying behavior), defender (e.g., being supportive of the victim), or outsider (e.g., remaining away from the bullying situation (Salmivalli et al. 1996). Significantly, observational research has found that when bystanders intervene on behalf of the victim, they successfully abate victimization more than 50 percent of the time (Craig, Pepler, and Atlas 2000).
Thus, the goals of bullying prevention programs are to 1) prevent or reduce bullying perpetration, 2) prevent or reduce victimization, and/or 3) increase bystander intervention in bullying situations. Correspondingly, bullying prevention programs typically target individuals engaged in bullying behavior, victims of bullying, and/or bystanders.
Practice Components
Bullying prevention programs can be implemented in grades K through 12 and in various settings, including community settings and through schoolwide, classroom-based, small-group, and individualized approaches. As programs vary in implementation, they also vary in methods, scope, objectives, and whether they target individuals engaged in bullying behavior, victims of bullying, and/or bystanders (Wong 2009).
Further, program elements generally vary by the targets of the intervention. Bully- and victim-focused programs target those directly involved in the bullying incident. Some examples of program elements for these types of programs are classroom-based or schoolwide bullying prevention rules, bullying prevention curriculum material, teacher trainings, individual work with individuals engaged in bullying behavior or victims of bullying, school conferences or informational assemblies, parent informational meetings, cooperative group work among experts (teachers, counselors, and interns), and improved playground supervision (Farrington and Ttofi 2009; Wong 2009).
Bystander interventions target witnesses of bullying incidents. Examples of elements in these types of programs are classroom-based dramatizations, videotaped reenactments, and interactive computer software to track students’ progress within social scenarios and provide feedback on effective bystander behavior (Polanin, Espelage, and Pigott 2012).
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Juvenile Problem & At-Risk Behaviors | Bullying
Gaffney, Ttofi, and Farrington (2019) reported a statistically significant reduction in bullying perpetration (OR=1.24) based on the findings from 36 randomized controlled trials. Wong (2009) also reported that the bullying prevention programs made a statistically significant impact on reducing bullying perpetration (d=0.11), based on the findings from 22 effect sizes across 19 studies. This means that youths who participated in bullying prevention programs were less likely to bully, compared with youths who did not participate. |
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Victimization | Overall bullying victimization
Gaffney, Ttofi, and Farrington (2019) report a statistically significant reduction in overall bullying victimization (OR=1.2), based on 33 randomized controlled trials. Wong (2009) also reported that bullying prevention programs had a statistically significant effect on reducing overall bullying victimization (d=0.19), based on 19 studies. This means that youths who participated in bullying prevention programs were less likely to be the victims of bullying, compared with youths who did not participate. |
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Victimization | Relational bullying victimization
Across 18 effect sizes, Kennedy (2020) found that bullying prevention programs had a statistically significant effect (OR=1.26) on relational bullying victimization outcomes. This means that youths who participated in bullying prevention programs were less likely to be the victims of relational bullying, compared with youths who did not participate. |
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Victimization | Physical bullying victimization
Across 17 effect sizes, Kennedy (2020) found that bullying prevention programs had a statistically significant effect (OR=1.38) on physical bullying victimization outcomes. This means that youths who participated in bullying prevention programs were less likely to be the victims of physical bullying, compared with youths who did not participate. |
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Victimization | Bystander intervention
One meta-analysis looked at the impact of bullying prevention programs on bystander behavior. Based on 12 studies, Polanin, Espelage, and Pigott (2012) found that these programs increased positive bystander intervention in bullying situations (g=0.20), meaning students were more likely to intervene in situations when they witnessed another student being bullied. This finding is statistically significant. |
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Mental Health & Behavioral Health | Empathy for the victim
One meta-analysis looked at the impact of bullying prevention programs on the bystanderâs empathy for the bullying victim. Based on eight studies, Polanin, Espelage, and Pigott (2012) found that the programs had no statistically significant effect on bystander empathy. |
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Victimization | Verbal bullying victimization
Across 13 effect sizes, Kennedy (2020) found that bullying prevention programs had no statistically significant effect on verbal bullying victimization outcomes. |
Literature Coverage Dates | Number of Studies | Number of Study Participants | |
---|---|---|---|
Meta Analysis 1 | 1983-2016 | 100 | 101615 |
Meta Analysis 2 | 1980-2010 | 12 | 12874 |
Meta Analysis 3 | 1996-2002 | 22 | 25361 |
Meta Analysis 4 | 1990-2018 | 33 | 0 |
Gaffney, Ttofi, and Farrington (2019) conducted a new review of the literature to update the meta-analysis by Farrington and Ttofi (2009) that looks at school-based programs designed to reduce bullying and victimization. The new search covered literature available from 2009 through December 2016 and was added to literature captured in the Farrington and Ttofi (2009) search from 1983 through May 2009. Using the same systematic search process as the original meta-analysis, the 2019 meta-analysis included primary studies that 1) described an evaluation of a school-based antibullying program implemented with school-age participants (between 4 and 18 years of age); 2) used an operational definition of school bullying that coincides with existing definitions (that is, Gladden et al. 2014; Farrington 1983); 3) measured school-bullying perpetration and/or victimization using quantitative measures such as self-, peer-, or teacher-report questionnaires; and 4) used an experimental or quasi-experimental design, with one group receiving the intervention and another (control group) not receiving the intervention. To facilitate a search for such programs, Boolean searches were conducted on several online databases. Databases of unpublished reports (e.g., ProQuest) also were searched to include gray literature in the review. Further, primary studies (both included in and excluded by previous systematic reviews) were scanned for any additional evaluations that we may have missed in the systematic searches. There was no sample-size limitation. The search included English and non-English studies and published articles and unpublished manuscripts.
Ultimately, the researchers identified 65 studies published since 2009 and combined them with the 35 studies from the previous meta-analysis, resulting in 100 studies with a total of 103 independent effect sizes. The types of study designs were randomized control (n = 45), quasi-experimental (n = 44), and age cohort (n = 14). There were 101,615 participants in the randomized controlled and quasi-experimental designed studies. The authors provide information on the racial/ethnic and gender breakdown of individual studies when that information is available. The studies involved both male and female students and included students from prekindergarten through high school. Race/ethnicity was not provided for most studies. The included studies looked at programs implemented in the United States and internationally throughout North America, South America, Europe, Asia, Africa, Australia, and New Zealand.
Cohen's d was estimated for primary studies when results were reported in the form of continuous data. For primary studies that presented results as percentages or frequencies of participants identifying as either perpetrating bullying or being victimized, the odds ratio (OR) effect size was estimated. All effect sizes were converted to odds ratios. Further, because clustering is a common phenomenon in educational evaluations, effect sizes were corrected for the inclusion of clusters in primary studies. The results of the meta-analysis were presented using three different models: 1) a random effects model that weights studies in proportion to the between-study variance, 2) a fixed effects model, which assigns greater weight to larger evaluations; and 3) a multiplicative variance adjustment to account for the heterogeneity of effect sizes.
Meta Analysis 2Polanin, 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 be in English and be peer-reviewed and published or conducted between 1980 and 2010. Additionally, the studies needed to be based solely within a school system and intended purposefully to modify bystander behavior. 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 8 studies.
Meta Analysis 3Wong (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 quasi-experimental designs with no pretest measure. Additionally, studies had to evaluate a program, intervention, or policy in a primary, secondary, or K–12 school, had to assess at least one outcome variable that represented bullying behavior or victimization, and each experimental group had to be at least 20 students. The author searched 14 electronic databases from the inception of the database through April 2008, and the bibliographies of retrieved documents, including 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 studies) and Europe or Australia (11 studies). 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.
Meta Analysis 4Kennedy (2020) conducted a meta-analysis to examine the effectiveness of bullying prevention programs on subtypes of traditional bullying victimization (relational, physical, and verbal victimization). A systemic search of literature published from 1990 to 2018 was conducted using three academic databases: PsycINFO, Academic Search Ultimate, and ERIC. Additionally, the reference lists of other meta-analyses on bullying prevention programs were reviewed. Studies were included if they conducted at least one evaluation of a bullying prevention program implemented on youths under age 18 and were published from 1990 to 2018. Additionally, the studies had to be published in English. Research designs included experimental designs, quasi-experimental designs, and nonexperimental designs that used pretests and posttests only. These nonexperimental designs were included to increase sample size. (Note: This CrimeSolutions review includes those analyses that examined only experimental and quasi-experimental designs.) Finally, studies were required to have reported outcomes that related to at least one bullying subtype (relational, physical, or verbal).
Thirty-three individual studies with 87 effect sizes were identified in the search. Thirty-three of the effect sizes were for relational bullying victimization (38 percent), 31 effect sizes were for physical bullying victimization (36 percent), and 23 effect sizes were for verbal bullying victimization (26 percent). The majority of studies (56 percent) were experimental or quasi-experimental, and the remainder (44 percent) were pretest/posttest design. Most studies (76 percent) examined bullying prevention programs for eighth grade and below, 18 percent were for ninth grade and above, and 6 percent had an overlap in age groups. Additionally, 59 percent of the studies took place in the United States, and 68 percent were published in 2010 or later.
All analyses were conducted using comprehensive meta-analysis software Version 3 (Borenstein et al. 2013). The primary method of analysis was a meta-analysis, using an approach that takes into account multiple outcomes from each study. The effect size statistic is an odds ratio. To minimize variance, the mean effect size was computed by weighting the individual effect sizes, assigning the weights by using the sum of the variance within and between studies. A random-effects model was used. A moderator analysis was conducted to analyze the impact of different study-level moderators.
Moderator Analyses
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, Polanin, Espelage, and Pigott (2012) 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. Wong (2009) also found no significant correlation between the magnitude of effect size and program 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).
These sources were used in the development of the practice profile:
Gaffney, Hannah, Maria M. Ttofi, and David P. Farrington. 2019. “Evaluating the Effectiveness of School-Bullying Prevention Programs: An Updated Meta-Analytical Review.” Aggression and Violent Behavior 45:111–33.
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.
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.
http://www.rand.org/pubs/rgs_dissertations/RGSD240.htmlKennedy, Reeve S. 2020. “A Meta-Analysis of the Outcomes of Bullying Prevention Programs on Subtypes of Traditional Bullying Victimization: Verbal, Relational, and Physical.” Aggression and Violent Behavior 55:1–12.
These sources were used in the development of the practice profile:
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.
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.)
Farrington, David P., and Maria M. Ttofi. 2009. “School-Based Program to Reduce Bullying and Victimization.” Campbell Systematic Reviews 2009:6
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.
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.
Zych, Izabela, David P. Farrington, Vicente J. Llorent, and Maria M. Ttofi. 2017. Protecting Children Against Bullying and Its Consequences. New York, NY: SpringerBriefs in Behavioral Criminology.
Salmivalli, Christina, Kirsti Lagerspetz, Kaj Björkqvist, Karin Osterman, and Ari Olavi Kaukiainen. 1996. “Bullying as a Group Process: Participant Roles and Their Relations to Social Status Within the Group.” Aggressive Behavior 22(1):1–15.
Borenstein, Michael, Larry V. Hedges, Julian Higgins, and Hannah R. Rothstein. 2013. Comprehensive Meta-Analysis Software Version 3 [Computer Software]. Englewood, New Jersey: Biostat.
Craig, Wendy M., Debra Pepler, and Rona S. Atlas. 2000. “Observations of Bullying in the Playground and in the Classroom.” School Psychology International 21(1):22–36.
Farrington, David P. 1983. “Randomized Experiments on Crime and Justice.” Crime and Justice 4:257–308.
Following are CrimeSolutions-rated programs that are related to this practice:
This practice review has been updated to reflect findings from more recent meta-analyses. In 2013 the practice was called School-Based Bullying Prevention Programs and was reviewed with the meta-analyses by Farrington and Ttofi (2009), Wong (2009), and Polanin, Espelage, and Pigott (2012). Merrill and colleagues (2008) was also reviewed but did not meet CrimeSolutions criteria for inclusion in the overall practice rating. In 2019 an updated version of Farrington and Ttofi (2009) replaced it in the review (Gaffney, Ttofi, and Farrington (2019). In 2022 an additional meta-analysis (Kennedy 2020) was reviewed, and the name of the practice was changed to Bullying Prevention Programs.
Age: 3 - 18
Gender: Male, Female
Setting (Delivery): School, Other Community Setting
Practice Type: Bullying Prevention/Intervention, Classroom Curricula, Conflict Resolution/Interpersonal Skills, Parent Training, School/Classroom Environment, Victim Programs, Violence Prevention
Unit of Analysis: Persons
1325 G Street, NW, Suite 900
Josh Polanin
American Institutes for Research
Washington, DC 20005
United States
Email