Regression model of fear of childbirth in pregnant women

Abstract Background The concept of fear of childbirth includes various types of anxiety and fears related to pregnancy and delivery. This fear can have a significant impact on women’s health. Therefore, a study was conducted to analyze the regression model of fear of childbirth among pregnant women....

Full description

Saved in:
Bibliographic Details
Main Authors: Farzaneh Rashidi, Nazanin Hesari, Sahar Shariatnia, Abdollah Razi, SeyyedMohammad MohammadiAubi, Fatemeh Gorji, Faezeh Ghanbari
Format: Article
Language:English
Published: BMC 2025-08-01
Series:BMC Public Health
Subjects:
Online Access:https://doi.org/10.1186/s12889-025-24045-9
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849331880023818240
author Farzaneh Rashidi
Nazanin Hesari
Sahar Shariatnia
Abdollah Razi
SeyyedMohammad MohammadiAubi
Fatemeh Gorji
Faezeh Ghanbari
author_facet Farzaneh Rashidi
Nazanin Hesari
Sahar Shariatnia
Abdollah Razi
SeyyedMohammad MohammadiAubi
Fatemeh Gorji
Faezeh Ghanbari
author_sort Farzaneh Rashidi
collection DOAJ
description Abstract Background The concept of fear of childbirth includes various types of anxiety and fears related to pregnancy and delivery. This fear can have a significant impact on women’s health. Therefore, a study was conducted to analyze the regression model of fear of childbirth among pregnant women. Methods This pilot cross-sectional study was conducted from August to November 2023 with 152 pregnant women in Bojnurd, Iran, using a multi-stage sampling method. Data were collected from tools including a personal and obstetric information form, a childbirth attitude questionnaire, social support assessments, and a childbirth self-efficacy scale. Data analysis was performed using SPSS version 24, utilizing descriptive statistics, t-tests, and multiple linear regression. Results The results of multiple linear regression indicate that the variables of age (B = 0.257), women’s education(B = 2.54), spouse’s education (B = 3.87), and preferred delivery(B = 7.097) can significantly predict the variance in fear of childbirth. Conclusion The results of this study can help healthcare providers identify and screen women at risk of experiencing fear of childbirth. By doing so, they can take proactive measures to reduce this fear and its negative effects, thereby easing the delivery process. This can be achieved through counseling sessions and by improving the quality of prenatal care for at-risk women.
format Article
id doaj-art-3d75643c3b0947bc8cc4cbd8fa3725ba
institution Kabale University
issn 1471-2458
language English
publishDate 2025-08-01
publisher BMC
record_format Article
series BMC Public Health
spelling doaj-art-3d75643c3b0947bc8cc4cbd8fa3725ba2025-08-20T03:46:23ZengBMCBMC Public Health1471-24582025-08-012511710.1186/s12889-025-24045-9Regression model of fear of childbirth in pregnant womenFarzaneh Rashidi0Nazanin Hesari1Sahar Shariatnia2Abdollah Razi3SeyyedMohammad MohammadiAubi4Fatemeh Gorji5Faezeh Ghanbari6Addiction and Behavioral Sciences Research Center, North Khorasan University of Medical SciencesDepartment of Midwifery, School of Nursing and Midwifery, North Khorasan University of Medical SciencesMaster of Biostatistics, Addiction and Behavioral Sciences Research Center, North Khorasan University of Medical SciencesDepartment of Urology, School of Medicine, North Khorasan University of Medical SciencesStudent Research Committee, School of Medicine, North Khorasan University of Medical SciencesStudent Research Committee, School of Nursing and Midwifery, North Khorasan University of Medical SciencesStudent Research Committee, School of Nursing and Midwifery, North Khorasan University of Medical SciencesAbstract Background The concept of fear of childbirth includes various types of anxiety and fears related to pregnancy and delivery. This fear can have a significant impact on women’s health. Therefore, a study was conducted to analyze the regression model of fear of childbirth among pregnant women. Methods This pilot cross-sectional study was conducted from August to November 2023 with 152 pregnant women in Bojnurd, Iran, using a multi-stage sampling method. Data were collected from tools including a personal and obstetric information form, a childbirth attitude questionnaire, social support assessments, and a childbirth self-efficacy scale. Data analysis was performed using SPSS version 24, utilizing descriptive statistics, t-tests, and multiple linear regression. Results The results of multiple linear regression indicate that the variables of age (B = 0.257), women’s education(B = 2.54), spouse’s education (B = 3.87), and preferred delivery(B = 7.097) can significantly predict the variance in fear of childbirth. Conclusion The results of this study can help healthcare providers identify and screen women at risk of experiencing fear of childbirth. By doing so, they can take proactive measures to reduce this fear and its negative effects, thereby easing the delivery process. This can be achieved through counseling sessions and by improving the quality of prenatal care for at-risk women.https://doi.org/10.1186/s12889-025-24045-9FearPregnancyChildbirthAnxiety
spellingShingle Farzaneh Rashidi
Nazanin Hesari
Sahar Shariatnia
Abdollah Razi
SeyyedMohammad MohammadiAubi
Fatemeh Gorji
Faezeh Ghanbari
Regression model of fear of childbirth in pregnant women
BMC Public Health
Fear
Pregnancy
Childbirth
Anxiety
title Regression model of fear of childbirth in pregnant women
title_full Regression model of fear of childbirth in pregnant women
title_fullStr Regression model of fear of childbirth in pregnant women
title_full_unstemmed Regression model of fear of childbirth in pregnant women
title_short Regression model of fear of childbirth in pregnant women
title_sort regression model of fear of childbirth in pregnant women
topic Fear
Pregnancy
Childbirth
Anxiety
url https://doi.org/10.1186/s12889-025-24045-9
work_keys_str_mv AT farzanehrashidi regressionmodeloffearofchildbirthinpregnantwomen
AT nazaninhesari regressionmodeloffearofchildbirthinpregnantwomen
AT saharshariatnia regressionmodeloffearofchildbirthinpregnantwomen
AT abdollahrazi regressionmodeloffearofchildbirthinpregnantwomen
AT seyyedmohammadmohammadiaubi regressionmodeloffearofchildbirthinpregnantwomen
AT fatemehgorji regressionmodeloffearofchildbirthinpregnantwomen
AT faezehghanbari regressionmodeloffearofchildbirthinpregnantwomen