Evaluating the effectiveness of school-bullying prevention programs: An updated meta-analytical review

doi:10.1016/j.avb.2018.07.001

Aggression and Violent Behavior

Volume 45, March–April 2019, Pages 111-133

https://doi.org/10.1016/j.avb.2018.07.001 Get rights and content

Highlights

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This paper updates the results of one of the most recent comprehensive meta-analyses of anti-bullying programs.
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The meta-analysis included 100 evaluations of school bullying intervention programs and 103 independent effect sizes.
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The results suggest that anti-bullying programs effectively reduce school-bullying perpetration by approximately 19 – 20%.
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The results suggest that anti-bullying programs effectively reduce school-bullying victimization by approximately 15 – 16%.
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Further research is needed to explore which specific components of school-bullying intervention programs are effective.

Abstract

A comprehensive and extensive systematic review and meta-analysis of the effectiveness of bullying prevention programs is presented. This report updates earlier research conducted by Farrington and Ttofi (2009). Systematic searches of online databases (i.e., Web of Science, PsychARTICLES, PsychINFO, EMBASE, DARE, ERIC, Google scholar, and Scopus) were conducted for primary studies published from 2009 to December 2016. Searches were also conducted for unpublished reports. To be included in the systematic review, primary studies must: (1) describe an evaluation of a school-based anti-bullying program; (2) utilize an appropriate operational definition of school-bullying (e.g., Centers for Disease Control and Prevention, 2014; Farrington, 1993; Olweus, 1992); (3) measure school-bullying perpetration and/or victimization behaviors using quantitative measures; and (4) use an experimental or quasi-experimental design with adequate control group.

Following systematic screening of over 20,000 search results, a total of 100 evaluations (with 103 independent effect sizes) were eligible for inclusion in our meta-analysis. Most of the effect sizes are estimated from studies that used RCT designs (n = 45) or quasi-experiments (n = 44 effect sizes), with only 14 effect sizes from age cohort designs.

Anti-bullying programs significantly reduce bullying perpetration (random effects OR = 1.309) and bullying victimization (random effects OR = 1.244). These results suggest that anti-bullying programs reduce school-bullying perpetration by approximately 19–20% ad school-bullying victimization by approximately 15–16%. Effect sizes vary greatly across studies, with a significant heterogeneity between studies for both bullying perpetration bullying victimization outcomes. This is anticipated given the variability in a range of moderators, for example, methodological designs, type of program used, or place of implementation. Analyses suggest no publication bias for either meta-analysis.

Variability in effect sizes across different methodological designs is investigated. Primary studies employing age cohort designs (n = 14) provide the largest effects in reducing both bullying perpetration (OR = 1.474) and victimization (OR = 1.302). In relation to bullying victimization outcomes, before-after/experimental-control designs provide similar effects (OR = 1.225) to randomized controlled trials (OR = 1.21). Randomized controlled trials (OR = 1.244) are more effective in reducing bullying perpetration than before-after/experimental-control designs (OR = 1.187). In future, we aim to further explain differences across programs by correlating individual effect sizes with varying program components and varying methodological elements available across these 100 evaluations.

Introduction

Bullying first emerged as an important topic of research in western hemisphere in the 1980s, following the tragic suicides of young boys in Norway, the reason for which was attributed to bullying victimization (Olweus, 1993). Interestingly, around the same time in Japan, researchers defined the term ‘ijime’, which describes behaviors similar to bullying, as a cause for public concern (Morita, 1996; Morita, Soeda, Soeda, & Taki, 1999; Smith, Cowie, Olafsson, & Liefooghe, 2002). Today, this form of aggressive behavior remains a prevalent problem amongst young people globally. For example, a recent meta-analysis of 80 international studies discovered prevalence levels of 34.5% and 36% for bullying perpetration and bullying victimization respectively (Modecki, Minchin, Harbaugh, Guerra, & Runions, 2014).

In order to adequately determine which interventions will effectively reduce bullying behaviors, it is important that researchers and educators start by accurately assessing the prevalence of involvement in school bullying (Swearer, Siebecker, Johnsen-Frerichs, & Wang, 2010). There remains some degree of disagreement in relation to definitive cut-off points for involvement in bullying (Solberg & Olweus, 2003; Swearer et al., 2010) and methods utilized for the assessment of bullying (Smith et al., 2002; Swearer et al., 2010). However, there is better agreement in regard to the defining criteria for school bullying.

Prominent researchers in the field have defined bullying as any aggressive behavior that incorporates 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, 1991). In other words, bullies are individuals who intend to cause harm to their victims through their actions, over a long period of time. Furthermore, victims of bullying are typically less powerful than bullies, or groups of bullies, and feel that they cannot easily defend themselves. This may be due to a physical or social power imbalance.

Bullying behaviors can occur in many contexts, for example, in schools, in the workplace, between siblings, and most recently, online. The present review is concerned only with school-bullying, namely, bullying that occurs in schools between individuals, usually aged between 4 and 18 years old. In the school context, bullying is a complex social phenomenon, that often does not happen between the bully and victim in isolation (Salmivalli, 2010). For example, individuals can be involved in bullying, not only as bullies, victims, or bully-victims, but also as bystanders, defenders, or reinforcers (Zych, Farrington, Llorent, & Ttofi, 2017).

Notably, bullying is a matter of public health, impacting the life outcomes of both bullies and victims, in varying ways (Arseneault, Bowes, & Shakoor, 2010; Masiello & Schroeder, 2014; Ttofi, Farrington, & Lösel, 2012). School-bullying is a strong risk marker for several negative behavioral, health, social, and/or emotional problems. A recent comprehensive review of systematic reviews highlighted that the impact of school-bullying can occur concurrently with perpetration and/or victimization, but also later in life (Zych, Ortega-Ruiz, & Del Rey, 2015). Previous studies have found that bullying victimization is often followed by negative mental health outcomes such as: increased suicidal ideation (e.g., Holt et al., 2015); generalized or social anxiety, low self-esteem and loneliness (e.g., Hawker & Boulton, 2000); psychotic symptoms (e.g., van Dam et al., 2012); depression (e.g., Ttofi, Farrington, Lösel, & Loeber, 2011); sleeping problems (van Geel, Goemans, & Vedder, 2016); and other psychosomatic symptoms (Gini & Pozzoli, 2013).

Bullying perpetration, on the other hand, has been linked to several negative outcomes such as: suicidal ideation and suicidal attempts (Holt et al., 2015); weapon carrying (Valdebenito, Ttofi, Eisner, & Gaffney, 2017; van Geel et al., 2014); drug use (Ttofi, Farrington, Lösel, Crago, & Theodorakis, 2016); and violence and offending in later life (Farrington et al., 2012; Ttofi et al., 2012; Ttofi, Farrington, Lösel, & Loeber, 2011b). Although involvement in school bullying is not necessarily a causal factor for undesirable life outcomes, research has found that there is an apparent association. It may be the case that the experience of school bullying functions as a stepping stone towards undesirable life outcomes (Arseneault et al., 2010).

Given its long-term effects, it is imperative that effective intervention efforts are put in place in order to alleviate this troubling school phenomenon (Ttofi, 2015). Moreover, involvement in school bullying has been found to correlate with factors such as low academic achievement (Strøm, Thoresen, Wentzel-Larsen, & Dyb, 2013), truancy from school (Gastic, 2008), and drug use (Valdebenito, Ttofi, & Eisner, 2015). Such factors are common risk factors for youth offending and delinquency (Farrington & Welsh, 2013). Therefore, a bullying prevention program could serve as a crime prevention program, as well as a form of promoting public health.

It is clear that school bullying is an important target for effective intervention and prevention. Bullying is an ethical problem as well as a developmental one: targeting school bullying facilitates the process of optimal psychological development but it also addresses the question of human rights, especially the rights of the child (Sercombe & Donnelly, 2013). Previous attempts to evaluate the effectiveness of anti-bullying programs have shown that intervention attempts thus far are effective. For example, Farrington and Ttofi's (2009) review concluded that school-based anti-bullying programs are effective in reducing both bullying perpetration (OR = 1.36; 95% CI: 1.26–1.47; z = 7.86; p < 0.0001) and bullying victimization (OR = 1.29; 95% CI: 1.18–1.42; z = 5.61; p < 0.0001). This review had a major impact on the field of bullying intervention and prevention. However, in the nine years that have passed since its publication, there has been a wealth of new research that needs to be evaluated. More recent meta-analyses have also found anti-bullying programs to be effective, but they have been limited in different ways. For example: (1) Jiménez-Barbero et al. (2016) only included randomized controlled trials; (2) Jiménez-Barbero, Ruiz-Hernández, Llor-Esteban, and Pérez-Garcia (2012) restricted studies to those published after 2000 and with participants aged 6 to 16 years of age; (3) Cantone, Piras, Vellante, Preti, Daníelsdóttir, D'Aloja et al. (2015) only included randomized controlled trials did not conduct a meta-analysis; (4) Chalamandaris & Piette (2015) report a systematic review of the methodologies used to evaluate anti-bullying programs; and (5) Evans, Fraser, and Cotter (2014) did not conduct a meta-analysis of the effectiveness of included evaluations of anti-bullying programs.

Hence, the aim of this paper is to conduct an up-to-date and thorough systematic review and meta-analysis of the effectiveness of school-based anti-bullying programs. Using an earlier systematic and meta-analytic review as a guideline (i.e., Farrington & Ttofi, 2009; Ttofi & Farrington, 2011) it is proposed that the present report will provide the most informative insight as to ‘what works’ in school-bullying intervention and prevention programs. Thus, the present analysis includes the 53 evaluations included by Farrington and Ttofi (2009), and also describes detailed systematic searches of the literature to identify evaluations of school-based anti-bullying programs published since 2009. It is hoped that this new evidence base will assist policy-makers and practitioners working in the field of bullying prevention.

Section snippets

Systematic review

The initial stage of any meta-analysis typically involves conducting a thorough and systematic search of all the existing and relevant literature (Lipsey & Wilson, 2001; Littell, Corcoran, & Pillai, 2008). Using predetermined keywords and strict inclusion/exclusion criteria, a systematic review aims to identify, screen, appraise, and synthesize all relevant empirical studies (Zych et al., 2017). In this way, systematic bias is avoided.

Analyses

A meta-analysis aims to estimate comparable effect sizes from multiple primary studies. The choice of effect size depends on how statistical information is reported by primary studies (Borenstein et al., 2009). In meta-analyses such as this one, the data is largely presented in continuous (e.g., means, standard deviations, sample sizes) or dichotomous (e.g., prevalence or percentages) forms (Wilson, 2010). Thus, the estimated effect sizes estimated were Cohen's d and odds ratios. As previously

Results of the meta-analysis

In total, 100 studies were included in our meta-analysis of the effectiveness of school-based anti-bullying programs. From these evaluations, we were able to estimate 103 independent effect sizes. These are presented for bullying perpetration and bullying victimization outcomes in Table 2, Table 3 respectively. The majority of these effect sizes were estimated from studies that used RCT designs (n = 45 effect sizes) or BA/EC designs (n = 44 effect sizes). We estimated the remaining 14 effect

Discussion

Overall, our updated meta-analysis found that school-based anti-bullying programs are effective in reducing both school-bullying perpetration and victimization. For school-bullying perpetration the weighted mean OR = 1.324 under a fixed effects model (FE) or OR = 1.309 under a random effects model (RE). To give a clearer example (see also Ttofi & Farrington, 2011), if we assume equal allocation of participants to experimental and control condition, and there were around 55 bullies and around

Acknowledgements

This research has been kindly supported by the Jacobs Foundation, Switzerland, and the UK Economic and Social Research Council.

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⁶: * = Included in meta-analysis. References for evaluations of the Olweus Bullying Prevention Program, e.g., Bergen 1/Olso 2 etc. Complete and included data was received in email communication between Professor Dan Olweus and Dr. Maria Ttofi in preparation of Farrington and Ttofi's (2009) Campbell report on the effectiveness of school-based bullying prevention programs.

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