Abstract
BACKGROUND: New mothers frequently encounter postpartum depression, anxiety, and stress symptoms, which pose challenges in diagnosis and treatment owing to their intricate interplay. This study employs network analysis to explore the interconnections between these symptoms and identify potential intervention points. METHODS: The study was carried out from December 2023 to June 2024 at the postpartum clinics of three representative tertiary hospitals in Nantong City. The participants were mothers undergoing their 42-day postpartum check-up. Participants completed the Edinburgh Postnatal Depression Scale (EPDS), the Depression, Anxiety, and Stress Scales (DASS-21), and the Maternal postpartum stress scale (MPSS). The R language was used to construct the network. Network analysis was also carried out to explore the network structure, centrality indices (strength, closeness, betweenness, and expected influence), and the stability of the network. RESULTS: A total of 625 women were included. The resulting network indicates a close interconnection between communities associated with depression, anxiety, and stress. As assessed on the centrality index, "I have felt sad or miserable" (EPDS-8), "Baby's irregular patterns of daily sleep" (MPSS-9), "lack of time for myself" (MPSS-19), "I have been so unhappy that I have been crying" (EPDS-4), and "Physical appearance after childbirth" (MPSS-20) are the five most important nodes of these three network structures. High network stability (> 0.7). CONCLUSION: Postpartum-specific stress symptoms play a significant role in the network of postpartum depression, anxiety, and stress, and identifying the central symptoms of depression, anxiety, and stress can provide a scientific basis for the development of precise interventions. CLINICAL TRIAL NUMBER: Not Applicable.