The Effectiveness of a Self-Assertiveness-Based Counseling Program in Reducing Bullying Fear Symptoms Among a Sample of Elementary School Students
Bibliographic record
Abstract
This study aimed to implement a self-assertiveness-based counseling program and measure its impact on reducing bullying fear symptoms among elementary school students in the Second Amman Directorate of Education. The students' ages ranged from 10 to 12 years, and the sample consisted of 60 male and female students selected purposively from 950 students. They were assessed using a Bullying Fear Questionnaire and randomly divided into control and experimental groups. The counseling program was applied to the experimental group, and the study utilized a quasi-experimental design. The results showed statistically significant differences between the mean scores of the control and experimental groups on the bullying fear questionnaire in favor of the experimental group, which is attributed to the counseling program. There were no differences in the program's effect according to gender, nor were there any differences in bullying fear symptoms. There were also no statistically significant differences attributed to the interaction between gender and group regarding bullying fear symptoms. These findings highlight the program's potential for broad application, providing valuable insights for educators and policymakers aiming to enhance student well-being and safety in schools. The research's regional focus and specific intervention approach add originality and practical value to educational psychology and bullying prevention.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".