Abstract
This study aims to explore the correlation between different social support patterns and perinatal mental health, and the mediating role of social trust in this. A cross-sectional survey was conducted in Jiangsu, China, with a sample size of 1705 pregnant respondents. Latent class analysis (LCA) was utilized to identify various social support patterns, while a multiple regression model was employed to analyze the mediating effect of social trust on the relationship between social support patterns and perinatal mental health. The study found four distinct social support patterns among the respondents: primary relationship-centric support, overall weak support, primary-secondary relationship-balanced support, and overall strong support. In the relationship between social support patterns and perinatal mental health, social trust played both a partial and full mediating role. The findings indicate that a social support system that enhances maternal trust and promotes honest disclosure of symptoms can effectively promote perinatal mental health.
Acknowledgements
We would like to thank the doctors and midwives from the surveyed hospitals, as well as the moms who participated in the study, without whose trust, assistance, and involvement we would not have been able to complete this study. Thanks to our colleagues for their important suggestions on the smooth progression of our project.
Ethical approval
This paper has been approved by Jiangnan University Medical Ethics Committee (JNU20211217IRB01). The participants were informed about the purpose of this research and provided written informed consent before administering the questionnaire. To maintain confidentiality, personal identifiers were omitted from the questionnaires and the collected data were stored in a secure, password-protected database without identifiers.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to their containing information that could compromise the privacy of research participants.