The panic-sadness bridge: a longitudinal study using undirected and directed network analyses of COVID-19-related...

The comorbidity network between anxiety and depression during COVID-19 has received significant attention. However, existing research has been primarily undirected and cross-sectional, lacking an examination of directional structure and longitudinal progression.

This study employed three complementary network models: the Gaussian Graphical Model (GGM), the Directed Acyclic Graph (DAG), and the Cross-Lagged Panel Network (CLPN). A total of 533 Chinese community participants (mean age = 27.75; 56.3% female) completed the Hospital Anxiety and Depression Scale (HADS). Assessments were conducted at three-month intervals: during the outbreak (February 7 to March 10, 2020) and the post-peak stage (May 8 to June 24, 2020).

Anxiety and depression symptoms were highly interconnected and mutually reinforcing over time. The overall network structure and global strength remained stable. The connection between panic feelings and sad moods emerged as a critical bridge linking anxiety and depression. DAGs suggested that instantaneous associations between panic feelings and sad moods were mutually reinforcing, whereas CLPN revealed that sad moods prospectively predicted subsequent increases in panic feelings.

Anxiety and depression symptoms mutually reinforced each other during the early stage of COVID-19, with the panic-sadness link serving as a central bridge. Addressing this maladaptive interaction may strengthen future interventions.