What Works for Whom in School-Based Anti-bullying Interventions? An Individual Participant Data Meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The prevalence of bullying worldwide is high (UNESCO, 2018). Over the past decades, many anti-bullying interventions have been developed to remediate this problem. However, we lack insight into for whom these interventions work and what individual intervention components drive the total intervention effects. We conducted a large-scale individual participant data (IPD) meta-analysis using data from 39,793 children and adolescents aged five to 20 years ( M age = 12.58, SD = 2.34) who had participated in quasi-experimental or randomized controlled trials of school-based anti-bullying interventions (i.e., 10 studies testing nine interventions). Multilevel logistic regression analyses showed that anti-bullying interventions significantly reduced self-reported victimization ( d = − 0.14) and bullying perpetration ( d = − 0.07). Anti-bullying interventions more strongly reduced bullying perpetration in younger participants (i.e., under age 12) and victimization for youth who were more heavily victimized before the intervention. We did not find evidence to show that the inclusion of specific intervention components was related to higher overall intervention effects, except for an iatrogenic effect of non-punitive disciplinary methods–which was strongest for girls. Exploratory analyses suggested that school assemblies and playground supervision may have harmful effects for some, increasing bullying perpetration in youth who already bullied frequently at baseline. In conclusion, school-based anti-bullying interventions are generally effective and work especially well for younger children and youth who are most heavily victimized. Further tailoring of interventions may be necessary to more effectively meet the needs and strengths of specific subgroups of children and adolescents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it