A Manifest against the Homogenisation of Childbirth Experiences: Preserving Subjectiveness in a Large Dataset of the «Babies Born Better» Survey

Mário J. D. S. Santos and Dulce Morgado Neves
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Mário J. D. S. Santos: Comprehensive Health Research Center (CHRC), Universidade NOVA de Lisboa, 1600-560 Lisboa, Portugal
Dulce Morgado Neves: Centro de Investigação e Estudos de Sociologia, ISCTE-Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026 Lisboa, Portugal

Social Sciences, 2021, vol. 10, issue 10, 1-12

Abstract: The Babies Born Better international project aimed at surveying women’s experience in childbirth, privileging the qualitative description of this experience. It was translated into several languages and, in each country, there were different strategies for data analysis. However, analysing a qualitative dataset of this dimension, without completely transforming qualitative into quantitative data, poses practical challenges to researchers. Thus, in this article, we aim to explore the potential of using a qualitative data analysis software to avoid homogenising women’s experiences and preserve the subjectivity of responses in the analysis of open-ended questions of the B3 survey. We focused on the Portuguese version of the survey, reporting a thematic, computer assisted qualitative data analysis of 1348 responses. The software acted as a mediator of the researchers’ analysis and interpretation, beyond classical content analysis, without converting qualitative into quantitative data through plain word count. Exploring new possibilities of interpreting not only the meaning, but the relations between categories, may expand the scope of qualitative data analysis. However, we argue that the use of a software should not be overvalued, as such strategy should always remain as subsidiary to the researcher’s subjective interpretation of data.

Keywords: Portugal; birth experience; maternity care; subjectivity; intersectionality; online survey; qualitative data analysis; CAQDAS (search for similar items in EconPapers)
JEL-codes: A B N P Y80 Z00 (search for similar items in EconPapers)
Date: 2021
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