Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), School of Medicine, Universidad Complutense, Madrid, Spain.
Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain.
JAMA Pediatr. 2021 Jan 1;175(1):44-55. doi: 10.1001/jamapediatrics.2020.3541.
Bullying is a prevalent and modifiable risk factor for mental health disorders. Although previous studies have supported the effectiveness of anti-bullying programs; their population impact and the association of specific moderators with outcomes are still unclear.
To assess the effectiveness of school anti-bullying interventions, their population impact, and the association between moderator variables and outcomes.
A search of Ovid MEDLINE, ERIC, and PsycInfo databases was conducted using 3 sets of search terms to identify randomized clinical trials (RCTs) assessing anti-bullying interventions published from database inception through February 2020. A manual search of reference lists of articles included in previous systematic reviews and meta-analyses was also performed.
The initial literature search yielded 34 798 studies. Included in the study were articles that (1) assessed bullying at school; (2) assessed the effectiveness of an anti-bullying program; (3) had an RCT design; (4) reported results; and (5) were published in English. Of 16 707 studies identified, 371 met the criteria for review of full-text articles; 77 RCTs were identified that reported data allowing calculation of effect sizes (ESs). Of these, 69 independent trials were included in the final meta-analysis database.
Random-effects and meta-regression models were used to derive Cohen d values with pooled 95% CIs as estimates of ES and to test associations between moderator variables and ES estimates. Population impact number (PIN), defined as the number of children in the total population for whom 1 event may be prevented by an intervention, was used as an estimate of the population impact of universal interventions targeting all students, regardless of individual risk.
The main outcomes are the effectiveness (measured by ES) and the population impact (measured by the PIN) of anti-bullying interventions on the following 8 variable categories: overall bullying, bullying perpetration, bullying exposure, cyberbullying, attitudes that discourage bullying, attitudes that encourage bullying, mental health problems (eg, anxiety and depression), and school climate as well as the assessment of potential assocations between trial or intervention characteristics and outcomes.
This study included 77 samples from 69 RCTs (111 659 participants [56 511 in the intervention group and 55 148 in the control group]). The weighted mean (range) age of participants in the intervention group was 11.1 (4-17) years and 10.8 (4-17) years in the control group. The weighted mean (range) proportion of female participants in the intervention group was 49.9% (0%-100%) and 50.5% (0%-100%) in the control group. Anti-bullying interventions were efficacious in reducing bullying (ES, -0.150; 95% CI, -0.191 to -0.109) and improving mental health problems (ES, -0.205; 95% CI, -0.277 to -0.133) at study end point, with PINs for universal interventions that target the total student population of 147 (95% CI, 113-213) and 107 (95% CI, 73-173), respectively. Duration of intervention was not statistically significantly associated with intervention effectiveness (mean [range] duration of interventions, 29.4 [1 to 144] weeks). The effectiveness of anti-bullying programs did not diminish over time during follow-up (mean [range] follow-up, 30.9 [2-104] weeks).
Despite the small ESs and some regional differences in effectiveness, the population impact of school anti-bullying interventions appeared to be substantial. Better designed trials that assess optimal intervention timing and duration are warranted.
欺凌是心理健康障碍的普遍且可改变的风险因素。虽然先前的研究支持了反欺凌计划的有效性;但其人群影响以及特定调节变量与结果之间的关联仍不清楚。
评估学校反欺凌干预的效果、其人群影响以及调节变量与结果之间的关联。
使用三套搜索词对 Ovid MEDLINE、ERIC 和 PsycInfo 数据库进行了搜索,以确定从数据库开始到 2020 年 2 月发表的评估反欺凌干预的随机对照试验 (RCT)。还对以前系统评价和荟萃分析中包含的文章的参考文献列表进行了手动搜索。
初始文献搜索产生了 34798 项研究。包括在研究中的文章有:(1)在学校评估欺凌;(2)评估反欺凌计划的有效性;(3)具有 RCT 设计;(4)报告结果;以及(5)以英文发表。在确定的 16707 项研究中,有 371 项符合全文文章审查标准;确定了 77 项 RCT,报告了可计算效应大小 (ES) 的数据。其中,69 项独立试验被纳入最终的荟萃分析数据库。
使用随机效应和荟萃回归模型得出 Cohen d 值,并使用汇总的 95%置信区间作为 ES 的估计值,并测试调节变量与 ES 估计值之间的关联。人口影响数 (PIN),定义为通过干预可能预防 1 起事件的总人群中儿童的数量,被用作针对所有学生(无论个体风险如何)的普遍干预的人群影响的估计值。
主要结果是反欺凌干预对以下 8 个变量类别的有效性(通过 ES 衡量)和人群影响(通过 PIN 衡量):总体欺凌、欺凌行为、欺凌暴露、网络欺凌、劝阻欺凌的态度、鼓励欺凌的态度、心理健康问题(例如焦虑和抑郁)和学校氛围,以及评估试验或干预特征与结果之间的潜在关联。
本研究包括 69 项 RCT 中的 77 个样本(111659 名参与者[干预组 56511 名,对照组 55148 名])。干预组参与者的加权平均(范围)年龄为 11.1(4-17)岁,对照组为 10.8(4-17)岁。干预组中女性参与者的加权平均(范围)比例为 49.9%(0%-100%),对照组为 50.5%(0%-100%)。反欺凌干预在研究结束时减少欺凌行为(ES,-0.150;95%CI,-0.191 至-0.109)和改善心理健康问题(ES,-0.205;95%CI,-0.277 至-0.133),针对总学生群体的普遍干预的 PIN 分别为 147(95%CI,113-213)和 107(95%CI,73-173)。干预的持续时间与干预效果没有统计学显著关联(干预的平均[范围]持续时间,29.4[1 至 144]周)。在随访期间,反欺凌计划的效果并没有随着时间的推移而减弱(平均[范围]随访时间,30.9[2-104]周)。
尽管 ES 较小,并且在有效性方面存在一些区域差异,但学校反欺凌干预的人群影响似乎很大。需要进行更好设计的试验,以评估最佳的干预时间和持续时间。