Author(s): Griffiths Mark*
This study presents a comprehensive examination of anxiety propagation in response to threat stimuli flow, utilizing hybrid models that integrate insights from psychology, sociology, data analytics, and computational science. Anxiety, a dynamic emotional response to perceived threats, exhibits complex patterns of spread influenced by individual differences, social interactions, media exposure, and threat characteristics. Traditional research methods often struggle to capture the multifaceted nature of anxiety propagation.
Hybrid models offer a multifaceted approach, combining diverse data sources and computational techniques to provide a holistic understanding of anxiety propagation. This research leverages psychological insights to model individual anxiety responses, integrates social network analysis to comprehend the role of interpersonal connections, employs data analytics to extract patterns from vast datasets, and utilizes computational simulations to explore and predict anxiety dissemination scenarios.
Through case studies in pandemic response, natural disaster preparedness, and cyber security, we highlight the practical applications of hybrid models in understanding and mitigating anxiety propagation. These models contribute valuable insights for policymakers, healthcare professionals, and society at large, aiding in the development of targeted interventions to address anxiety in the face of evolving threats. As our world continues to confront various challenges, the comprehensive study of anxiety propagation using hybrid models becomes an indispensable tool for informed decision-making and societal resilience.
The Journal of International Social Research received 7760 citations as per Google Scholar report
