Cyberbullying and Gambling Disorder: Associations with Emotion Regulation and Coping Strategies
Bibliographic record
Abstract
The presence of unsuitable coping and emotion regulation strategies in young populations with gambling disorder (GD) and in those who have experienced cyberbullying victimization has been suggested. However, this association has not been explored in depth. In this study, our aim was to analyze individual differences in emotion regulation, coping strategies, and substance abuse in a clinical sample of adolescents and young adult patients with GD (n = 31) and in a community sample (n = 250). Furthermore, we aimed to examine the association between cyberbullying and GD. Participants were evaluated using the Cyberbullying Questionnaire-Victimization, the Canadian Adolescent Gambling Inventory, the Coping Strategies Inventory, the Difficulties in Emotion Regulation Scale, the Alcohol Use Disorders Identification Test and the Drug Use Disorders Identification Test. Structural Equation Modeling was used to explore associations between these factors in a community sample and in a clinical group. In both groups, exposure to cyberbullying behaviors was positively associated with higher emotion dysregulation and the use of maladaptative coping styles. Our findings uphold that adolescents and young adults who were victims of cyberbullying show difficulties in emotion regulation and maladaptive coping strategies when trying to solve problems. The specific contribution of sex, age, gambling severity, emotion regulation, and coping strategies on cyberbullying severity is also discussed. Populations at vulnerable ages could potentially benefit from public prevention policies that target these risk factors.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".