Abstract

The COVID-19 pandemic used to be a major public health emergency which affected people worldwide, and it affected individuals' body, mood, work and lifestyle to some extent. The pregnant woman affected by the unstable hormone will be more sensitive than normal ones. Long-term depression and anxiety could feedback on their body and lead to a host of pregnancy complications. Because pregnant women who choose cesarean section are awake during the perioperative period, to ensure safety, the degree of cooperation about psychology and behavior is relatively high, so we should know the psychological state of such a group of people. This study aims to explore psychological experience and influential factors of pregnant women who decided elective caesarean section after the COVID-19 pandemic. This is a cross-sectional study carried out in a hospital in Shanghai, according to the inclusion and exclusion criteria, we selected pregnant women who selected elective cesarean section as the study objects, all participants provided informed consent and completed questionnaires, including sociodemographic questionnaire, Generalized Anxiety Disorder scale (GAD-7) and General Well-Being Schedule (GWBS). Software SPSS 23.0 was used to analyze and explore the influencing factors. Eligible 595 questionnaires were included in the study, the mean score of GAD-7 was 4.855 ± 3.254 and 90.699 ± 13.807 of GWBS. Generalized linear regression analysis revealed several factors that were statistically significant with the two scales, including birthplace, average monthly income, number of abortion and pregnancy complication (p < 0.01). The COVID-19 infection status and symptoms around infection have no statistical difference in anxiety level and general well-being after they experience the COVID-19 pandemic. However, through this study, we found some influencing factors that worth further exploration. In the future, we will expand the sample size to explore the different situation of multi-center, and we hope provide psychological nursing interventions based on existing results to offer a better delivery experience.

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