Chinese pregnant women's knowledge, attitude, and practice of self-protection against coronavirus disease 2019 during the post-pandemic period: A structural equation modeling-based survey.

This study aimed to investigate the Chinese pregnant women's levels of knowledge, attitude, and practice (KAP) of self-protection against coronavirus disease 2019 (COVID-19) during the post-pandemic period, to aid the development of targeted health education. An online questionnaire was conducted for 2156 Chinese pregnant women from October 1, 2021, to December 31, 2021, to collect socio-demographic and KAP information. Structural equation modeling (SEM) was used to determine self-protection-related factors. The mean age of the participants was 30 ± 4.1 years. SEM indicated that pregnant women's level of knowledge can directly and indirectly affect the practice of self-protection (r = 0.23) through their belief, with a correlation coefficient of 0.56 and 0.46 between knowledge and belief and belief and practice, respectively. The "basic protection" and "hospital visits after infection" exerted the greatest impact on knowledge formation, with correlation coefficients of 0.85 and 0.89, respectively. Attitude had a direct effect on practice with a correlation coefficient of 0.46. "Awareness of prevention and control" and "family and social support" had the greatest impact on belief formation, with correlation coefficients of 0.77 and 0.73, respectively. Pregnant Chinese women were generally familiar with COVID-19 knowledge, and their levels of knowledge and beliefs particularly affect the practice of self-protection. Health education aimed at improving pregnant women's knowledge and belief toward self-protection against COVID-19 may be an effective way to guide them toward positive practices and promote their health and that of their babies.
Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(© 2023 Published by Elsevier Ltd.)