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Hajimirzaie, Saiedeh Sadat, Tehranian, Najmeh, Mousavi, Seyed Abbas, Golabpour, Amin, Mirzaii, Mehdi, Keramat, Afsaneh, Khosravi, Ahmad. (1400). Predicting the Relation between Biopsychosocial Factors and Type of Childbirth using the Decision Tree Method: A Cohort Study. سامانه مدیریت نشریات علمی, 46(6), 437-443. doi: 10.30476/ijms.2021.88777.1951
Saiedeh Sadat Hajimirzaie; Najmeh Tehranian; Seyed Abbas Mousavi; Amin Golabpour; Mehdi Mirzaii; Afsaneh Keramat; Ahmad Khosravi. "Predicting the Relation between Biopsychosocial Factors and Type of Childbirth using the Decision Tree Method: A Cohort Study". سامانه مدیریت نشریات علمی, 46, 6, 1400, 437-443. doi: 10.30476/ijms.2021.88777.1951
Hajimirzaie, Saiedeh Sadat, Tehranian, Najmeh, Mousavi, Seyed Abbas, Golabpour, Amin, Mirzaii, Mehdi, Keramat, Afsaneh, Khosravi, Ahmad. (1400). 'Predicting the Relation between Biopsychosocial Factors and Type of Childbirth using the Decision Tree Method: A Cohort Study', سامانه مدیریت نشریات علمی, 46(6), pp. 437-443. doi: 10.30476/ijms.2021.88777.1951
Hajimirzaie, Saiedeh Sadat, Tehranian, Najmeh, Mousavi, Seyed Abbas, Golabpour, Amin, Mirzaii, Mehdi, Keramat, Afsaneh, Khosravi, Ahmad. Predicting the Relation between Biopsychosocial Factors and Type of Childbirth using the Decision Tree Method: A Cohort Study. سامانه مدیریت نشریات علمی, 1400; 46(6): 437-443. doi: 10.30476/ijms.2021.88777.1951

Predicting the Relation between Biopsychosocial Factors and Type of Childbirth using the Decision Tree Method: A Cohort Study

Iranian Journal of Medical Sciences
مقاله 4، دوره 46، شماره 6، بهمن 2021، صفحه 437-443    اصل مقاله (391.09 K)
نوع مقاله: Original Article(s)
شناسه دیجیتال (DOI): 10.30476/ijms.2021.88777.1951
نویسندگان
Saiedeh Sadat Hajimirzaie1؛ Najmeh Tehranian2؛ Seyed Abbas Mousavi3؛ Amin Golabpour4؛ Mehdi Mirzaii5؛ Afsaneh Keramat3؛ Ahmad Khosravi* 6
1Student Research Committee, School of Nursing and Midwifery, Shahroud University of Medical Sciences, Shahroud, Iran
2Department of Reproductive Health and Midwifery, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
3Center for Health Related Social and Behavioral Sciences Research, Shahroud University of Medical Sciences, Shahroud, Iran
4School of Allied Medical Sciences, Shahroud University of Medical Sciences, Shahroud, Iran
5Department of Basic Sciences, School of Medicine, Shahroud University of Medical Sciences, Shahroud, Iran
6Ophthalmic Epidemiology Research Center, Shahroud University of Medical Sciences, Shahroud, Iran
چکیده
Background: With the growing rate of cesarean sections, rising morbidity and mortality thereafter is an important health issue. Predictive models can identify individuals with a higher probability of cesarean section, and help them make better decisions. This study aimed to investigate the biopsychosocial factors associated with the method of childbirth and designed a predictive model using the decision tree C4.5 algorithm.
Methods: In this cohort study, the sample included 170 pregnant women in the third trimester of pregnancy referring to Shahroud Health Care Centers (Semnan, Iran), from 2018 to 2019. Blood samples were taken from mothers to measure the estrogen hormone at baseline. Birth information was recorded at the follow-up time per 30-42 days postpartum. Chi square, independent samples t test, and Mann-Whitney were used for comparisons between the two groups. Modeling was performed with the help of MATLAB software and C4.5 decision tree algorithm using input variables and target variable (childbirth method). The data were divided into training and testing datasets using the 70-30% method. In both stages, sensitivity, specificity, and accuracy were evaluated by the decision tree algorithm.
Results: Previous method of childbirth, maternal body mass index at childbirth, maternal age, and estrogen were the most significant factors predicting the childbirth method. The decision tree model’s sensitivity, specificity, and accuracy were 85.48%, 94.34%, and 89.57% in the training stage, and 82.35%, 83.87%, and 83.33% in the testing stage, respectively.
Conclusion: The decision tree model was designed with high accuracy successfully predicted the method of childbirth. By recognizing the contributing factors, policymakers can take preventive action.
It should be noted that this article was published in preprint form on the website of research square (https://www.researchsquare.com/article/rs-34770/v1).
کلیدواژه‌ها
Cesarean section؛ Estrogens؛ Biological factors؛ Socioeconomic factors
سایر فایل های مرتبط با مقاله
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