Future directions in aggression research: the contribution of technology-integrated operationalizations

Aggression is a complex behavior that is difficult to capture using traditional methods, such as questionnaires and lab-based aggression tasks. These methods present challenges due to social desirability bias and limitations in translating findings to real-world situations. In this review, we discuss how emerging technologies, including virtual reality, video games, hyperscanning, biosignal recording, ecological momentary assessment and social media analysis, offer improved construct and ecological validity and can contribute to the refinement of integrative theoretical models of aggression. We comprehensively address advantages (e.g., immersion, realistic simulation, real-time and context-sensitive data collection and interpersonal dynamics) and limitations of each technology compared to traditional methods and highlight remaining gaps in aggression research. Additionally, we examine aggressive behavior related to the emergence of new technologies in digital spaces, focusing particularly on cyberbullying and the metaverse. We also review machine learning approaches for detecting cyber-aggression on social media platforms. We propose shifting from static, individual-level assessments to dynamic, context-sensitive frameworks that capture aggression in real time, in more ecological settings and digital environments. This shift in operationalization holds the potential to advance theoretical understanding, guide future research and inform clinical and forensic interventions.