IDEAS home Printed from https://ideas.repec.org/a/wly/camsys/v17y2021i2ne1143.html

Some searches may not work properly. We apologize for the inconvenience.

   My bibliography  Save this article

Effectiveness of school‐based programs to reduce bullying perpetration and victimization: An updated systematic review and meta‐analysis

Author

Listed:
  • Hannah Gaffney
  • Maria M. Ttofi
  • David P. Farrington

Abstract

Background Bullying first emerged as an important topic of research in the 1980s in Norway (Olweus), and a recent meta‐analysis shows that these forms of aggression remain prevalent among young people globally (Modecki et al.). Prominent researchers in the field have defined bullying as any aggressive behavior that incorporates three key 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; Farrington). There are many negative outcomes associated with bullying perpetration, such as: suicidal ideation (Holt et al.), weapon carrying (Valdebenito et al.), drug use (Ttofi et al.), and violence and offending in later life (Ttofi et al.). Bullying victimization too is associated with negative outcomes such as: suicidal ideation (Holt et al.), anxiety, low self‐esteem and loneliness (Hawker& Boulton). Therefore, school bullying is an important target for effective intervention, and should be considered a matter of public health concern. Objectives The objective of this review is to establish whether or not existing school‐based antibullying programs are effective in reducing school‐bullyng behaviors. This report also updates a previous meta‐analysis conducted by Farrington and Ttofi. This earlier review found that antibullying programs are effective in reducing bullying perpetration and victimization and a primary objective of the current report is to update the earlier analysis of 53 evaluations by conducting new searches for evaluations conducted and published since 2009. Search Methods Systematic searches were conducted using Boolean combinations of the following keywords: bully*; victim*; bully‐victim; school; intervention; prevention; program*; evaluation; effect*; and anti‐bullying. Searches were conducted on several online databases including, Web of Science, PscyhINFO, EMBASE, EMBASE, DARE, ERIC, Google Scholar, and Scopus. Databases of unpublished reports, such as masters' and doctoral theses (e.g., Proquest) were also searched. Selection Criteria Results from systematic searches were screened thoroughly against the following inclusion criteria. To be included in this review, a study must have: (1) described an evaluation of a school‐based antibullying program implemented with school‐age participants; (2) utilized an operational definition of school‐bullying that coincides with existing definitions; (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 not receiving the intervention. Data Collection and Analysis Of the 19,877 search results, 474 were retained for further screening. The majority of these were excluded, and after multiple waves of screening, 100 evaluations were included in our meta‐analysis. A total of 103 independent effect sizes were estimated and each effect size was corrected for the impact of including clusters in evaluation designs. Included evaluations were conducted using both randomized (n = 45; i.e., randomized controlled trials/RCTs) and nonrandomized (n = 44; i.e., quasi‐experimental designs with before/after measures; BA/EC) methodologies. All of these studies included measures of bullying outcomes before and after implementation of an intervention. The remaining 14 effect sizes were estimated from evaluations that used age cohort designs. Two models of meta‐analysis are used to report results in our report. All mean effects computed are presented using both the multivariance adjustment model (MVA) and random effects model (RE). The MVA model assigns weights to primary studies in direct proportion to study level sampling error as with the fixed effects model but adjusts the meta‐analytic standard error and confidence intervals for study heterogeneity. The RE model incorporates between‐study heterogeneity into the formula for assigning weights to primary studies. The differences and strengths/limitations of both approaches are discussed in the context of the present data. Results Our meta‐analysis identified that bullying programs significantly reduce bullying perpetration (RE: odds ratio [OR] = 1.309; 95% confidence interval [CI]: 1.24–1.38; z = 9.88; p

Suggested Citation

  • Hannah Gaffney & Maria M. Ttofi & David P. Farrington, 2021. "Effectiveness of school‐based programs to reduce bullying perpetration and victimization: An updated systematic review and meta‐analysis," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(2), June.
  • Handle: RePEc:wly:camsys:v:17:y:2021:i:2:n:e1143
    DOI: 10.1002/cl2.1143
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/cl2.1143
    Download Restriction: no

    File URL: https://libkey.io/10.1002/cl2.1143?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Şahin, Mustafa, 2012. "An investigation into the efficiency of empathy training program on preventing bullying in primary schools," Children and Youth Services Review, Elsevier, vol. 34(7), pages 1325-1330.
    2. Baldry, Anna Costanza & Sorrentino, Anna & Farrington, David P., 2019. "Cyberbullying and cybervictimization versus parental supervision, monitoring and control of adolescents' online activities," Children and Youth Services Review, Elsevier, vol. 96(C), pages 302-307.
    3. Sara Valdebenito & Manuel Eisner & David P. Farrington & Maria M. Ttofi & Alex Sutherland, 2018. "School‐based interventions for reducing disciplinary school exclusion: a systematic review," Campbell Systematic Reviews, John Wiley & Sons, vol. 14(1), pages -216.
    4. Howard S. Bloom & Carolyn J. Hill & James A. Riccio, 2003. "Linking program implementation and effectiveness: Lessons from a pooled sample of welfare-to-work experiments," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 22(4), pages 551-575.
    5. David P. Farrington & Maria M. Ttofi, 2009. "School‐Based Programs to Reduce Bullying and Victimization," Campbell Systematic Reviews, John Wiley & Sons, vol. 5(1), pages -148.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Almudena Castellanos & Beatriz Ortega-Ruipérez & David Aparisi, 2021. "Teachers’ Perspectives on Cyberbullying: A Cross-Cultural Study," IJERPH, MDPI, vol. 19(1), pages 1-12, December.
    2. Kim, Jun Hyung & Hahlweg, Kurt & Schulz, Wolfgang, 2021. "Early childhood parenting and adolescent bullying behavior: Evidence from a randomized intervention at ten-year follow-up," Social Science & Medicine, Elsevier, vol. 282(C).
    3. Jacinta Francis & Gina Trapp & Natasha Pearce & Sharyn Burns & Donna Cross, 2022. "School Built Environments and Bullying Behaviour: A Conceptual Model Based on Qualitative Interviews," IJERPH, MDPI, vol. 19(23), pages 1-16, November.
    4. Francis, Jacinta & Strobel, Natalie & Trapp, Gina & Pearce, Natasha & Vaz, Sharmila & Christian, Hayley & Runions, Kevin & Martin, Karen & Cross, Donna, 2022. "How does the school built environment impact students’ bullying behaviour? A scoping review," Social Science & Medicine, Elsevier, vol. 314(C).
    5. Patrick Chanda & Masauso Chirwa & Ackson Tyson Mwale & Kalunga Cindy Nakazwe & Ireen Manase Kabembo & Bruce Nkole, 2024. "Perceived Social Support and Health Care Spending as Moderators in the Association of Traditional Bullying Perpetration with Traditional Bullying and Cyberbullying Victimisation among Adolescents in 2," IJERPH, MDPI, vol. 21(7), pages 1-25, June.
    6. Howard White, 2022. "Getting evidence into use: The experience of the Campbell Collaboration," Campbell Systematic Reviews, John Wiley & Sons, vol. 18(1), March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sesha Kethineni & Susan Frazier‐Kouassi & Yuki Shigemoto & Wesley Jennings & Stephanie M. Cardwell & Alex R. Piquero & Kimberly Gay & Dayanand Sundaravadivelu, 2021. "PROTOCOL: Effectiveness of parent‐engagement programs to reduce truancy and juvenile delinquency: A systematic review," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(3), September.
    2. Geoffrey L. Wallace & Robert Haveman, 2007. "The implications of differences between employer and worker employment|earnings reports for policy evaluation," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 26(4), pages 737-754.
    3. Benjamin Lu & Eli Ben-Michael & Avi Feller & Luke Miratrix, 2023. "Is It Who You Are or Where You Are? Accounting for Compositional Differences in Cross-Site Treatment Effect Variation," Journal of Educational and Behavioral Statistics, , vol. 48(4), pages 420-453, August.
    4. Helen Lee & Sarah Shea Crowne & Melanie Estarziau & Keith Kranker & Charles Michalopoulos & Anne Warren & Tod Mijanovich & Jill H. Filene & Anne Duggan & Virginia Knox, "undated". "The Effects of Home Visiting on Prenatal Health, Birth Outcomes, and Health Care Use in the First Year of Life: Final Implementation and Impact Findings from the Mother and Infant Home Visiting Progra," Mathematica Policy Research Reports a9626a8d90bf4f01811d0c9d7, Mathematica Policy Research.
    5. Stefanie Behncke & Markus Frölich & Michael Lechner, 2010. "Unemployed and their caseworkers: should they be friends or foes?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(1), pages 67-92, January.
    6. repec:mpr:mprres:7520 is not listed on IDEAS
    7. Park, Sora & Na, Eun-Yeong & Kim, Eun-mee, 2014. "The relationship between online activities, netiquette and cyberbullying," Children and Youth Services Review, Elsevier, vol. 42(C), pages 74-81.
    8. Liu, Yanhong & Carney, JoLynn V. & Kim, Hyunhee & Hazler, Richard J. & Guo, Xiuyan, 2020. "Victimization and students’ psychological well-being: The mediating roles of hope and school connectedness," Children and Youth Services Review, Elsevier, vol. 108(C).
    9. Adam M. Butz, 2015. "Administrative Privatization and Employment Outcomes in the Implementation of Temporary Assistance to Needy Families," Evaluation Review, , vol. 39(4), pages 363-394, August.
    10. Andrew McEachin & Thurston Domina & Andrew Penner, 2020. "Heterogeneous Effects of Early Algebra across California Middle Schools," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(3), pages 772-800, June.
    11. Nozaki, Yuko, 2019. "Why do bullies matter?: The impacts of bullying involvement on Adolescents' life satisfaction via an adaptive approach," Children and Youth Services Review, Elsevier, vol. 107(C).
    12. Ida Risanger Sjursø & Hildegunn Fandrem & James O’Higgins Norman & Erling Roland, 2019. "Teacher Authority in Long-Lasting Cases of Bullying: A Qualitative Study from Norway and Ireland," IJERPH, MDPI, vol. 16(7), pages 1-9, March.
    13. Stephen Bell & Daniel Gubits & David Stapleton & David Wittenburg & Michelle Derr & Arkadipta Ghosh & Sara Ansell & David Greenberg, 2011. "BOND Implementation and Evaluation: Evaluation Analysis Plan," Mathematica Policy Research Reports 795952932ec747588c128efa0, Mathematica Policy Research.
    14. Jessica Ortega-Barón & Sofía Buelga & Ester Ayllón & Belén Martínez-Ferrer & María-Jesús Cava, 2019. "Effects of Intervention Program Prev@cib on Traditional Bullying and Cyberbullying," IJERPH, MDPI, vol. 16(4), pages 1-13, February.
    15. Sarah Croake & Priyanka Anand & Christopher Jones & Katherine Morrison & Cara Orfield & David Stapleton & Denise Hoffman & David R. Mann & Judy Geyer & Daniel Gubits & Stephen Bell & Andrew McGuirk & , "undated". "BOND Implementation and Evaluation: 2017 Stage 1 Interim Process, Participation, and Impact Report," Mathematica Policy Research Reports b00eb83020fb42e185d69f979, Mathematica Policy Research.
    16. Charles Michalopoulos & Kristen Faucetta & Carolyn J. Hill & Zimena A. Portilla & Lori Burrell & Helen Lee & Anne Duggan & Virginia Knox, "undated". "Impacts on Family Outcomes of Evidence-Based Early Childhood Home Visiting: Results from the Mother and Infant Home Visiting Program Evaluation," Mathematica Policy Research Reports 3adcbd3368c545679a6784b8a, Mathematica Policy Research.
    17. Virginia Knox & Carolyn J. Hill & Gordon Berlin, 2018. "Can Evidence-Based Policy Ameliorate the Nation’s Social Problems?," The ANNALS of the American Academy of Political and Social Science, , vol. 678(1), pages 166-179, July.
    18. David Greenberg & Burt S. Barnow, 2014. "Flaws in Evaluations of Social Programs," Evaluation Review, , vol. 38(5), pages 359-387, October.
    19. Tanrikulu, Ibrahim & Campbell, Marilyn, 2015. "Correlates of traditional bullying and cyberbullying perpetration among Australian students," Children and Youth Services Review, Elsevier, vol. 55(C), pages 138-146.
    20. Kennedy, Reeve S., 2020. "Gender differences in outcomes of bullying prevention programs: A meta-analysis," Children and Youth Services Review, Elsevier, vol. 119(C).
    21. Jon Baron, 2018. "A Brief History of Evidence-Based Policy," The ANNALS of the American Academy of Political and Social Science, , vol. 678(1), pages 40-50, July.

    More about this item

    Keywords

    bully*; victim*; bully‐victim; school; intervention; prevention; program*; evaluation; effect*; and anti‐bullying. searches were conducted on several online databases including; web of science; pscyhinfo; embase; embase; dare; eric; google scholar; and scopus. databases of unpublished reports; such as masters' and doctoral theses (e.g.; proquest) were also searched. selection criteria results from systematic searches were screened thoroughly against the following inclusion criteria. to be included in this review; a study must have: (1) described an evaluation of a school‐based antibullying program implemented with school‐age participants; (2) utilized an operational definition of school‐bullying that coincides with existing definitions; (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 not receiving the intervention. data collection and analysis of the 19; 877 search results; 474 were retained for further screening. the majority of these were excluded; and after multiple waves of screening; 100 evaluations were included in our meta‐analysis. a total of 103 independent effect sizes were estimated and each effect size was corrected for the impact of including clusters in evaluation designs. included evaluations were conducted using both randomized (n = 45; i.e.; randomized controlled trials/rcts) and nonrandomized (n = 44; i.e.; quasi‐experimental designs with before/after measures; ba/ec) methodologies. all of these studies included measures of bullying outcomes before and after implementation of an intervention. the remaining 14 effect sizes were estimated from evaluations that used age cohort designs. two models of meta‐analysis are used to report results in our report. all mean effects computed are presented using both the multivariance adjustment model (mva) and random effects model (re). the mva model assigns weights to primary studies in direct proportion to study level sampling error as with the fixed effects model but adjusts the meta‐analytic standard error and confidence intervals for study heterogeneity. the re model incorporates between‐study heterogeneity into the formula for assigning weights to primary studies. the differences and strengths/limitations of both approaches are discussed in the context of the present data. results our meta‐analysis identified that bullying programs significantly reduce bullying perpetration (re: odds ratio [or] = 1.309; 95% confidence interval [ci]: 1.24–1.38; z = 9.88; p;
    All these keywords.

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:camsys:v:17:y:2021:i:2:n:e1143. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1891-1803 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.