Clinical Modeling of Vaccine Hesitancy with Digital Misinformation Exposure in Social Media Users

Abstract

The rapid proliferation of digital misinformation across online social networks has fundamentally altered the landscape of public health, presenting unprecedented challenges to global immunization initiatives. Vaccine hesitancy, now recognized as a critical threat to global health security, is increasingly driven by algorithmically amplified exposure to unverified or scientifically inaccurate content. This comprehensive study investigates the intricate relationship between social media misinformation exposure and vaccine hesitancy utilizing an advanced clinical modeling framework. By synthesizing behavioral psychology, digital epidemiology, and computational network analysis, we develop a novel quantitative approach to measure the clinical impact of sustained misinformation exposure. The research utilizes large-scale, anonymized digital trace data alongside clinical psychological evaluations of social media users to model the latency, frequency, and emotional resonance of misinformation encounters. The findings indicate a statistically significant dose-response relationship between the volume of misinformation exposure and elevated hesitancy scores on clinical assessments. Furthermore, the modeling reveals that emotional contagion within echo chambers exacerbates resistance to institutional medical guidance. These insights provide a foundational framework for developing targeted, data-driven public health interventions capable of mitigating the adverse effects of digital misinformation and enhancing overall vaccine confidence in highly networked populations.