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Factors associated with childbirth readiness among pregnant women: a Bayesian network analysis
Ningying Zhou1, Feng Zhang2, Min Liu1
1Department of Nursing, Wuxi Maternal and Child Health Hospital, Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, China.
Background:
Inadequate childbirth readiness can adversely affect the birthing experience of pregnant women and may even influence their willingness to have further children. This study aimed to explore the determinants of childbirth readiness and the network relationships among these factors, thereby providing evidence to improve childbirth readiness.
Methods:
This cross-sectional study surveyed 350 pregnant women attending Wuxi Maternity and Child Health Care Hospital. Latent profile analysis (LPA) was first performed using the four domains of the Childbirth Readiness Scale to identify subgroups of childbirth readiness, and potential associated factors were then screened using univariate analysis and multinomial logistic regression. A Bayesian network model was employed to construct the structural relationships of factors influencing childbirth readiness.
Results:
Childbirth readiness was categorised into three levels: poor (26%), good (30.9%), and complete (43.1%). Univariate analysis revealed significant differences across the three categories in relation to age, parity, pregnancy complications, antenatal exercise, planned pregnancy, self-efficacy, eHealth literacy, fear of childbirth, and family support (pā<ā0.2). Multinomial logistic regression indicated that parity, self-efficacy, and eHealth literacy were important predictors of childbirth readiness. The Bayesian model identified self-efficacy, fear of childbirth, eHealth literacy, and parity as the nodes most closely associated with childbirth readiness, while planned pregnancy, antenatal exercise, family support, and age were linked indirectly through other nodes.
Conclusions:
Previous studies on childbirth readiness have mainly relied on regression models, which are unable to elucidate the intrinsic interconnections among influencing factors. By constructing a Bayesian model, this study demonstrated that women with high self-efficacy, no fear of childbirth, high eHealth literacy, and multiparity had the highest probability of achieving complete childbirth readiness (83.3%).
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