Gan, Xiaobing

Guo, Ting

Wang, Yang

Zhou, Yongjie

Zhu, Zhenzhen

English

AIS Electronic Library (AISeL)

Association for Information Systems AIS Electronic Library (AISeL) WHICEB 2023 Proceedings Wuhan International Conference on e-Business Summer 5-28-2023 Examining the relative importance of factors influencing perinatal anxiety in different perinatal periods during the Covid-19 pandemic: a random forest-based approach Xiaobing Gan College of Management, Shenzhen University, China Ting Guo College of Management, Shenzhen University, China Yang Wang College of Management, Shenzhen University, China, wangyanghim@szu.edu.cn Zhenzhen Zhu College of Management, Shenzhen University, China Yongjie Zhou Shenzhen Kangning Hospital, China Follow this and additional works at: https://aisel.aisnet.org/whiceb2023 Recommended Citation Gan, Xiaobing; Guo, Ting; Wang, Yang; Zhu, Zhenzhen; and Zhou, Yongjie, "Examining the relative importance of factors influencing perinatal anxiety in different perinatal periods during the Covid-19 pandemic: a random forest-based approach" (2023). WHICEB 2023 Proceedings . 48. https://aisel.aisnet.org/whiceb2023/48 This material is brought to you by the Wuhan International Conference on e-Business at AIS Electronic Library (AISeL). It has been accepted for inclusion in WHICEB 2023 Proceedings by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact elibrary@aisnet.org. Examining the relative importance of factors influencing perinatal anxietyin different perinatal periods during the Covid-19 pandemic: a randomforest-based approachXiaobing Gan1, Ting Guo1, Yang Wang1*, Zhenzhen Zhu1, Yongjie Zhou21 College of Management, Shenzhen University, China2 Shenzhen Kangning Hospital, China*wangyanghim@szu.edu.cn1. INTRODUCTIONAND RESEARCH QUESTIONSSince December 2019, Covid-19 has spread rapidly and widely around the world and quickly became a globalpandemic. In a high-risk and stressful environment caused by infectious disease outbreaks, people tend to feel fear anduncertainty and are prone to a range of psychological problems and physical symptoms [1]. During the Covid-19 pandemic,the public was found to have more severe mental health problems than before, with a relatively high prevalence [2]. Due tochanges in the level and function of the endocrine system during pregnancy, pregnant women are prone to physical andpsychological stress reactions, and psychological stress reactions will lead to different degrees of fear, tension, and otheremotions, and these negative emotions will make pregnant women more psychological disorders such as stress, anxiety, anddepression are prone to occur, which have a great impact on the physical and mental health of pregnant women and fetuses.Mei et al. [3] found a higher prevalence of anxiety and depression in pregnant women during the Covid-19 epidemic thanbefore the epidemic. In contrast, a cross-sectional study of 156 participants showed that pregnant women had the same ratesof anxiety as before the pandemic and significantly higher rates of depression; Pregnant women living in Wuhan have nohigher levels of depression or anxiety than those in other areas [4]. The impact of the COVID-19 pandemic on maternalmental health outcomes has not been fully elucidated.Therefore, after the outbreak of the new coronavirus, we conducted a survey of maternal mental health in differentprovinces in China, including Wuhan (the first city of the outbreak, with the largest number of confirmed cases), Beijing (thenumber of confirmed cases was moderate), Lanzhou (the number of confirmed cases was relatively less). Demographic andCOVID-19-related characteristics, such as age, degree of education, and economic loss, were also collected to analyze themental health status of pregnant women during the Covid-19 pandemic.2. THEORYAND RESEARCH FRAMEWORKIn this study, four random forest models were established for samples of different gestational periods toidentify the influencing factors of maternal anxiety. Use the open-source sci-kit-learn library in Python toimplement the random forest algorithm and train the model. Random forests can automatically generaterelatively important scores for features, but this score can only be used for variable interpretation, and the extentand direction of the impact of features cannot be known. Therefore, an interpretable machine learning SHAPmethod is introduced to further explain random forest results.3. RESULTSAND MAJOR FINDINGSThe study shows that the total anxiety rate of pregnant women is 21.23%, and the anxiety rates of the fourpregnancy periods are 21.5%, 19.2%, 21.6%, and 27.2%, respectively. Anxiety prevalence was lowest in thesecond trimester and highest in postpartum women. For different pregnancy periods, depression and insomniaare the most important factors affecting maternal anxiety, and they all have a positive impact on anxiety, that is,the higher the scores of depression and insomnia, the higher the risk of maternal anxiety. The study found thatthe feature importance of maternal anxiety is different in different gestational periods. In addition to depression,insomnia, and any worries or fears during childbirth, attention needs to be paid to women in the first trimesterwho live in areas with relatively backward economic development (such as Lanzhou) and whose pregnancystatus has a greater impact on their actions. For women in the second trimester, special attention needs to be paidto women who have suffered greater economic losses due to the epidemic, live in areas with severe epidemics(such as Wuhan), and younger women who have drinking habits. For women in the third trimester, it is alsonecessary to pay attention to the impact of pregnancy on the action， greater losses due to the epidemic， andincreased frequency of contractions have a greater risk of anxiety. Among postpartum women, the moreworries or fears of childbirth, the greater the economic loss, and the older they are, the more likely they are tosuffer from anxiety disorders. The results of the study show that there are similarities and differences in thefeature importance of maternal anxiety during different pregnancy periods, and more attention should be paid toimportant factors (such as depression, insomnia, and worries or fears during childbirth) for intervention.4. CONTRIBUTIONSUnlike previous studies on a certain period of pregnancy, our study analyzes maternal anxiety throughout the prenataland postpartum periods, which has stronger integrity and generalization. Second, this study uses a random forest model toanalyze maternal anxiety, which enriches the research in this field. Our study also introduced the SHAP method to furtherexplain the precise impact of each factor on maternal anxiety at different gestational trimesters. This study has somelimitations. First of all, this study adopts a cross-sectional design, which makes it difficult to compare thechanges in the incidence of anxiety before and after the outbreak of Covid-19. At the same time, thecross-sectional design can only explore relevant factors, but it is difficult to draw causal conclusions. Secondly,this study uses Chinese multi-center data samples, which can provide some references for related research inChina, but cannot provide sufficient reference significance for other regions. Finally, the postpartum datacollected in this study are relatively small, and there may be insufficient research on postpartum anxiety.ACKNOWLEDGEMENTThis research was supported by the National Natural Science Foundation of China under Grant 72004072.REFERENCES1. Usher, K., J. Durkin, and N. Bhullar. "The COVID-19 pandemic and mental health impacts." International Journalof Mental Health Nursing Early View.1(2020).2. Heymann, D. L., et al. "COVID-19: what is next for public health?." The Lancet 10224(2020):395.3. Mei, Hong, et al. "Depression, anxiety, and stress symptoms in pregnant women before and during the COVID-19pandemic." Journal of Psychosomatic Research 149(2021):110586-.4. Dong, Haoxu, et al. "Investigation on the mental health status of pregnant women in China during the PandemicCOVID-19." Archives of Gynecology and Obstetrics 303.2(2021).

Examining the relative importance of factors influencing perinatal anxiety in different perinatal periods during the Covid-19 pandemic: a random forest-based approach

https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1024&context=whiceb2023

Examining the relative importance of factors influencing perinatal anxiety in different perinatal periods during the Covid-19 pandemic: a random forest-based approach

Abstract

Similar works

Full text

Available Versions

AIS Electronic Library (AISeL)