Identification and comparison of pandemic-to-symptom networks of South Korea and the United States

Abstract

BackgroundThe Coronavirus (COVID-19) pandemic resulted in a dramatic increase in the prevalence of anxiety and depression globally. Although the impact on the mental health of young adults was especially strong, its underlying mechanisms remain elusive.Materials and methodsUsing a network approach, the present study investigated the putative pathways between pandemic-related factors and anxiety and depressive symptoms among young adults in South Korea and the U.S. Network analyses were conducted on cross-country data collected during the COVID-19 lockdown period (n = 1,036). Our model included depression symptoms (PHQ-9), generalized anxiety symptoms (GAD-7), and COVID-19-related factors (e.g., COVID-19-related traumatic stress, pandemic concerns, access to medical/mental health services).ResultsThe overall structure of pandemic-to-symptom networks of South Korea and the U.S. were found to be similar. In both countries, COVID-related stress and negative future anticipation (an anxiety symptom) were identified as bridging nodes between pandemic-related factors and psychological distress. In addition, worry-related symptoms (e.g., excessive worry, uncontrollable worry) were identified as key contributors in maintaining the overall pandemic-to-symptom network in both countries.ConclusionThe similar network structures and patterns observed in both countries imply that there may exist a stable relationship between the pandemic and internalizing symptoms above and beyond the sociocultural differences. The current findings provide new insights into the common potential pathway between the pandemic and internalizing symptoms in South Korea and in the U.S. and inform policymakers and mental health professionals of potential intervention targets to alleviate internalizing symptoms.

Fear of disease in patients with epilepsy – a network analysis

“…When nodes with high centrality are activated, they are likely to propagate activation across the network by connecting to other nodes through edges ( 16 ). This offers essential potential targets for relevant intervention measures ( 17 ). In recent years, network analysis has garnered widespread attention and application across various domains of psychology, such as depression ( 18 ), anxiety ( 19 ), acute stress reactions ( 20 ), eating disorders symptoms ( 21 ), and more.…”