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Articles

Fine tuning fear of childbirth: the relationship between Childbirth Fear Questionnaire subscales and demographic and reproductive variables

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Pages 15-29 | Received 09 Jun 2016, Accepted 18 Oct 2017, Published online: 30 Nov 2017
 

Abstract

Objective: The objective of the current study was to investigate the relationship between the newly developed Childbirth Fear Questionnaire (CFQ) and demographic and reproductive variables.

Background: The CFQ was developed in an effort to improve measurement and understanding of women’s childbirth fears. To our knowledge the CFQ is the only multidimensional measure of childbirth fears in which (a) multiple domains of childbirth fear are assessed and (b) individual subscales have been psychometrically developed.

Methods: Participants were 643 pregnant women residing in English-speaking countries, recruited via online forums. Participants completed a set of questionnaires, including the multidimensional CFQ, via an online survey. Given the differences in childbirth fear between nulliparous and multiparous women, findings are stratified by parity.

Results: Gestational age was largely unrelated to fear of childbirth. Age, income and education were negatively related to fear of childbirth. Assisted vaginal delivery and episiotomy in a previous pregnancy were positively associated with a fear of pain. Self-reported history of traumatic vaginal birth was associated with higher scores on all aspects of fear of childbirth. History of caesarean birth was not generally associated with increased childbirth fears, but women with a prior, self-reported traumatic caesarean birth reported more fear of future caesarean births.

Conclusions: Findings are consistent with previous reports of fear of childbirth. However, the CFQ provides increased specificity with respect to women’s childbirth fears. This information is relevant to both education and treatment planning for pregnant women and women wishing to reproduce.

Acknowledgements

The authors wish to thank the study participants for their time and thoughtful engagement. We would especially like to thank Jessica Gaiptman and Stephanie Poje for their invaluable contribution to participant recruitment and data management.

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