Online Aggression in Czech Adolescents: Prevalence, Demographic Variation, and Platform-Related Risk
Abstract
This study examines the prevalence, patterns, and correlates of online aggression among Czech adolescents, with a particular focus on emerging harms such as AI-generated sexual images. Data were drawn from a population-based, cross-sectional survey of 42,772 pupils aged 13 to 17 years, conducted in primary and secondary schools across the Czech Republic in 2025. The instrument captured thirteen behaviourally specific forms of online aggression experienced in the past 12 months. Descriptive and non-parametric analyses were used to assess prevalence, demographic variation, perpetrator identities, social media use patterns, and coping responses. Verbal aggression was the most common form of harm (58.6%), followed by the sharing of embarrassing photos, threats or intimidation, repeated harassing calls, and embarrassing videos. A notable emerging phenomenon was the misuse of AI-generated nude images (7.3%), which showed a strong co-occurrence with extortion. Girls reported higher overall exposure to verbal aggression, whereas boys more often experienced recurrent forms aligned with cyberbullying criteria. Age differences were statistically detectable but substantively small, while students in vocational schools exhibited higher prevalence rates than those in academic tracks. Intensive use of Instagram, TikTok, and Snapchat was consistently associated with more frequent verbal victimization. Nearly one third of victims did not disclose their experience to anyone. These findings highlight the widespread nature of online aggression and the need for updated prevention, support mechanisms, and regulatory responses addressing emerging technological risks.
Fields of Study & Subjects
Bullying
Victimization
and Aggression
Child Development and Digital Technology
Hate Speech and Cyberbullying Detection
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 6 January 2026
- Document type
- Preprint