Understanding How Programs Work to Prevent Overt Aggressive Behaviors: A Meta-analysis of Mediators of Elementary School–Based Programs
Bibliographic record
Abstract
Several recent meta-analyses of universal school-based violence prevention studies indicate the overall positive impacts of these approaches on aggression. These studies, however, assess impacts on broadly defined measures of aggression. Furthermore, little research has analyzed the mechanisms through which these programs attempt to reduce overt aggressive behavior. The current study analyzed overall impacts on a more narrowly defined outcome—overt aggressive behavior—and identified associated mediators in 36 universal prevention studies conducted with kindergarten through fifth-grade students. Programs were associated with a significant, although small, reduction in overt aggression behavior. Three types of mediators were identified: measures of skill acquisition, social-cognitive processes, and classroom characteristics. Using MacKinnon's joint significance test to test for mediation, four measures of skill acquisition, two measures of social cognitive, and one measure of classroom characteristics were identified as significant mediating variables. Implications for the design of effective violence prevention programs and mediators to assess in future research are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.038 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".