Artigo em revista científica Q1
A manifest against the homogenisation of childbirth experiences: Preserving subjectiveness in a large dataset of the «Babies Born Better» survey
Mário JDS Santos (Santos, M.); Dulce Morgado Neves (Neves, D. M.);
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Social Sciences
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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.
Portugal,Birth experience,Maternity care,Subjectivity,Intersectionality,Online survey,Qualitative data analysis,CAQDAS
  • Sociologia - Ciências Sociais
  • Outras Ciências Sociais - Ciências Sociais
Registos de financiamentos
Referência de financiamento Entidade Financiadora
IS1405 COST Action
SFRH/BD/99993/2014 Fundação para a Ciência e Tecnologia
SFRH/BPD/94537/2013 Fundação para a Ciência e Tecnologia
UIDB/03126/2020 Fundação para a Ciência e Tecnologia