Title:Psychological network analysis of COVID-19 related datasets

Abstract

During the last year, the COVID-19 outbreak has caused worldwide challenges. Not only the virus threatened people’s health and overwhelmed the healthcare system, generating insecurity and fear, but also, the application of social distancing regulations to control the number of infections resulted in financial damage, loss of freedom, disruption of daily activities, and social isolation. This is expected to cause an increase in mental health symptoms, which should be addressed and, when possible, prevented. To investigate the impact of COVID-19 on mental health, and to suggest possible protective factors, we have investigated interrelationships of psychological factors together with medical factors in three datasets: one dataset of hospitalized COVID-19 patients from the original outbreak in Wuhan, China, one longitudinal dataset of Dutch students during the first Dutch lockdown period, and one dataset of students measured before and during the first Dutch lockdown period. We discuss findings from novel network estimation techniques applied to these datasets.