Gaffney Hannah, Ttofi Maria M, Farrington David P
Institute of Criminology University of Cambridge Cambridge UK.
Campbell Syst Rev. 2021 Apr 5;17(2):e1143. doi: 10.1002/cl2.1143. eCollection 2021 Jun.
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.
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.
Systematic searches were conducted using Boolean combinations of the following keywords: and . 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 Databases of unpublished reports, such as masters' and doctoral theses (e.g., Proquest) were also searched.
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.
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 ( = 45; i.e., randomized controlled trials/RCTs) and nonrandomized ( = 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.
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; = 9.88; < .001) and bullying victimization (RE: OR = 1.244; 95% CI: 1.19-1.31; = 8.92; < .001), under a random effects model of meta-analysis. Mean effects were similar across both models of meta-analysis for bullying perpetration (i.e., MVA: OR = 1,324; 95% CI: 1.27-1.38; = 13.4; < .001) and bullying victimization (i.e., MVA: OR = 1.248; 95% CI: 1.21-1.29; = 12.06; < .001). Under both computational models, primary studies were more effective in reducing bullying perpetration than victimization overall. Effect sizes varied across studies, with significant heterogeneity between studies for both bullying perpetration ( = 323.392; = 85; < .001; = 73.716) and bullying victimization ( = 387.255; = 87; < .001; = 77.534) outcomes. Analyses suggest that publication bias is unlikely. Between-study heterogeneity was expected, given the large number of studies included, and thus, the number of different programs, methods, measures and samples used.
AUTHORS' CONCLUSIONS: We conclude that overall, school-based antibullying programs are effective in reducing bullying perpetration and bullying victimization, although effect sizes are modest. The impact of evaluation methodology on effect size appears to be weak and does not adequately explain the significant heterogeneity between primary studies. Moreover, the issue of the under-/over-estimation of the true treatment effect by different experimental designs and use of self-reported measures is reviewed. The potential explanations for this are discussed, along with recommendations for future primary evaluations. Avenues for future research are discussed, including the need further explain differences across programs by correlating individual effect sizes with varying program components and varying methodological elements available across these 100 evaluations. Initial findings in the variability of effect sizes across different methodological moderators provide some understanding on the issue of heterogeneity, but future analyses based on further moderator variables are needed.
欺凌行为最初在20世纪80年代的挪威成为重要的研究课题(奥尔韦斯),最近的一项荟萃分析表明,这些攻击形式在全球年轻人中仍然普遍存在(莫德斯基等人)。该领域的杰出研究人员将欺凌定义为任何具有三个关键要素的攻击行为,即:(1)伤害意图;(2)本质上具有重复性;(3)加害者与受害者之间存在明显的权力不平衡(疾病控制与预防中心;法林顿)。与欺凌行为相关的负面后果有很多,比如:自杀意念(霍尔特等人)、携带武器(巴尔德贝尼托等人)、吸毒(托菲等人)以及日后的暴力和犯罪行为(托菲等人)。欺凌受害者也会出现一些负面后果,比如:自杀意念(霍尔特等人)、焦虑、自卑和孤独感(霍克和博尔顿)。因此,校园欺凌是有效干预的重要目标,应被视为一个公共卫生问题。
本综述的目的是确定现有的基于学校的反欺凌项目是否能有效减少校园欺凌行为。本报告还更新了法林顿和托菲之前进行的一项荟萃分析。早期的这项综述发现,反欺凌项目在减少欺凌行为和欺凌受害方面是有效的,本报告的一个主要目的是通过对2009年以来进行并发表的评估进行新的检索,更新对53项评估的早期分析。
使用以下关键词的布尔组合进行系统检索:[此处原文缺失关键词内容]。检索了多个在线数据库,包括科学网、心理学文摘数据库(PsycINFO)、荷兰医学文摘数据库(EMBASE)、DARE数据库、教育资源信息中心(ERIC)、谷歌学术和Scopus数据库。还检索了未发表报告的数据库,如硕士和博士论文数据库(如Proquest)。
根据以下纳入标准对系统检索的结果进行了全面筛选。要纳入本综述,一项研究必须具备:(1)描述了对以学龄参与者为对象实施的基于学校的反欺凌项目的评估;(2)采用了与现有定义相符的校园欺凌操作定义;(3)使用定量方法测量校园欺凌行为和/或受害情况,如自我报告、同伴报告或教师报告问卷;(4)采用实验或准实验设计,一组接受干预,另一组不接受干预。
在19877条检索结果中,保留了474条以供进一步筛选。其中大部分被排除,经过多轮筛选后,100项评估被纳入我们的荟萃分析。总共估计了103个独立效应量,每个效应量都针对评估设计中纳入聚类的影响进行了校正。纳入的评估采用了随机(n = 45;即随机对照试验/RCTs)和非随机(n = 44;即采用前后测量的准实验设计;BA/EC)两种方法。所有这些研究都包括了干预实施前后欺凌结果的测量。其余14个效应量是从采用年龄队列设计的评估中估计出来的。在本报告中,使用两种荟萃分析模型来报告结果。计算出的所有平均效应均使用多变量调整模型(MVA)和随机效应模型(RE)呈现。MVA模型与固定效应模型一样,根据研究水平抽样误差的直接比例为主要研究分配权重,但会针对研究异质性调整荟萃分析的标准误差和置信区间。RE模型将研究间异质性纳入为主要研究分配权重的公式中。在当前数据的背景下讨论了两种方法的差异和优缺点。
我们的荟萃分析发现,在荟萃分析的随机效应模型下,反欺凌项目显著减少了欺凌行为(RE:优势比[OR] = 1.309;95%置信区间[CI]:1.24 - 1.38;Z = 9.88;P <.001)和欺凌受害情况(RE:OR = 1.244;95% CI:1.19 - 1.31;Z = 8.92;P <.001)。对于欺凌行为(即MVA:OR = 1.324;95% CI:1.27 - 1.38;Z = 13.4;P <.001)和欺凌受害情况(即MVA:OR = 1.248;95% CI:1.21 - 1.29;Z = 12.06;P <.001),两种荟萃分析模型的平均效应相似。在两种计算模型下,总体而言,主要研究在减少欺凌行为方面比减少受害情况更有效。不同研究的效应量各不相同,对于欺凌行为(Q = 323.392;df = 85;P <. (此处原文缺失数字);I² = 73.716)和欺凌受害情况(Q = 387.255;df = 87;P <.001;I² = 77.534)结果,研究间存在显著异质性。分析表明不太可能存在发表偏倚。鉴于纳入的研究数量众多,以及所使用的不同项目类型、方法、测量方式和样本,研究间异质性是可以预期的。
我们得出结论,总体而言,基于学校的反欺凌项目在减少欺凌行为和欺凌受害方面是有效的,尽管效应量不大。评估方法对效应量的影响似乎较弱,无法充分解释主要研究之间的显著异质性。此外,还审查了不同实验设计和自我报告测量方法对真实治疗效果的低估/高估问题。讨论了对此的潜在解释以及对未来主要评估的建议。讨论了未来的研究方向,包括需要通过将个体效应量与不同项目组成部分以及这100项评估中可用的不同方法学要素相关联,进一步解释不同项目之间的差异。不同方法学调节因素效应量变异性的初步发现为异质性问题提供了一些理解,但需要基于更多调节变量进行未来分析。