Cyberbullying Detection and Prevention in Childhood Education: A Socio-Ecological Systematic Review

Abstract

Cyberbullying is a growing social-emotional and educational issue that impacts school-age children, and has the potential to significantly impact on wellbeing, peer relationships, school climate, and trust in schools. This systemic review joins together evidence regarding the technologies used to detect, prevention, and ethical governance of cyberbullying in school digital environments, and their implications for the Nigerian context in low and middle-income countries. The literature was retrieved using Google Scholar, SpringerLink, IEEE Xplore, ACM Digital Library and ResearchGate based on the PRISMA 2020 guideline from 2008 to 2025. There were 17 studies included from the 103 identified, after meeting inclusion and quality assessment criteria. The results indicate that AI and machine learning technologies can assist with the early detection of problematic online behaviours, but are constrained by language diversity, cultural differences, privacy concerns, and algorithmic bias. Socio-ecological interventions, in which students, teachers, families and school leadership were engaged, resulted in more sustainable outcomes, such as enhanced digital resilience, empathy and help-seeking behaviour. The review finds that coordinated, ethical, and developmentally appropriate practices are key to developing safer learning environments online in developing contexts of education.