The relationship between difficulties in emotion regulation and alexithymia with anger in male adolescents with bullying behaviors: the mediating role of hostile attribution bias
Bibliographic record
Abstract
INTRODUCTION: The issue of anger in adolescents with bullying behavior is a critical concern in this age group. Understanding the emotions and cognitions involved can provide clearer insights for researchers and practitioners working in this field of inquiry. Therefore, this study aimed to investigate the role of difficulties in emotion regulation (DIER) and alexithymia in anger through hostile attribution bias (HAB) in male adolescents with bullying behaviors. METHODS: This was a descriptive study using the pathway analysis. The statistical population included 332 male adolescents with a high level of bullying behavior living in Zanjan, Iran. Participants completed DIER scale (Gratz and Roemer), Toronto Alexithymia Scale, Social Information Processing-Attribution Bias Questionnaire (Coccaro et al.), Anger Expression Inventory (Spielberger), Aggression Questionnaire (Buss and Perry), and Illinois Bullying Questionnaire. The pathway analysis method was used in Lisrel 8.8 software. RESULTS: The results also revealed a direct and significant relationship of DIER (β = 0.19, p < .05), alexithymia (β = 0.17, p < .05), and HAB (β = 0.32, p < .05) with anger. The mediating role of HAB in the relationship between DIER and anger was significant (β = 0.32). Moreover, the mediating role of HAB in the relationship between alexithymia and anger was significant (β = 0.20). CONCLUSION: This study highlights the role of HAB in exacerbating anger by causing misinterpretations of social cues as hostile, particularly in those with impaired emotion regulation and alexithymia. These findings underscore the importance of interventions aimed at improving DIER and emotional awareness to reduce HAB and subsequent aggressive behaviors in adolescents with bullying tendencies. Addressing these underlying emotional and cognitive biases is crucial for mitigating anger and aggression in this population.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".