https://orcid.org/0000-0002-6267-337X
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ABSTRACT
Objective
To evaluate empirically the degree of content overlap between four self-report measures of fear of childbirth (FoC) identified as ‘best in class’ by a recent review.
Background
FoC and tokophobia is an area of increasing clinical concern and has been linked to poor maternal and neonatal outcomes. Clinical pathways have been established to improve care and interventions for FoC however, ambiguity and inconsistency remain regarding the most appropriate assessment measures.
Method
A multi-rater and consensus content analysis was undertaken to determine the degree of overlap between four ‘best in class’ measures of FoC/tokophobia.
Results
The Slade-Pais expectations of childbirth scale (SPECS) was found to be the preferred measure in terms of symptom overlap of the tools evaluated, however, the overall level of overlap among these measures was weak.
Conclusion
Limitations inherent to the current battery of preferred measures of FoC suggests both the desirability and urgency to develop a theoretically-grounded, psychometrically robust and accurate FoC assessment measure. Current measures of FoC are not interchangeable.
Acknowledgments
The first author is extremely grateful to Dr Eiko Fried, Department of Clinical Psychology, Leiden University, for helpful advice and suggestions regarding the statistical analysis and discussion around statistical coding and code modification and also to both Dr Fried and Dr Jana Jarecki, Department of Economic Psychology, University of Basel for the original base coding that was used for . We are grateful also for the expert opinion and advice of two anonymous reviewers of the manuscript.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1. The use of the 26-items from the SPECS for FoC assessment and the use of the measure in one site in the UK comes from personal communication with the SPECS study lead author.
2. Personal communication with Dr Fried supported the adoption of multiple content analyses to offer enhanced rigour in terms of inter-rater reliability.