The Effects of a Clinical Prevention Program on Bullying, Victimization, and Attitudes toward School of Elementary School Students
Bibliographic record
Abstract
The purpose of the present study was to evaluate a bullying prevention program that involved eleven 90-minute, highly structured workshops conducted at the classroom level on a weekly basis. The intervention aimed to increase student awareness of bullying and its impact, increase empathy toward victims, and enhance positive attitudes toward school and academic achievement. Participants were 666 students who were selected from 20 elementary schools using stratified random-sampling procedures from a large metropolitan area of southern Greece. Students were randomly assigned to experimental and control groups and were provided measures of bullying and victimization behaviors at pretest and posttest (Olweus, 1996). Results indicated that there were statistically significant decreases in bullying and victimization behaviors from pretest to posttest. Specifically, victimization rates in the experimental group were reduced from pretest to posttest by 55.4%. The respective decreases in the control group were 23.3%. Similarly, bullying rates decreased by 55.6% at posttest compared with pretest in the experimental group, and the combined type decreased by 66.7%. Furthermore, a latent class analysis provided qualitative means on the specific categories in which decreases of negative behaviors were observed. Additional positive effects were observed with increases in positive attitudes toward school (school liking). We conclude that the current prevention program effectively reduced bullying and victimization in the elementary schools in Greece and holds promise for influencing the overall school experience.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".