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Presenting Critical Realist Discourse Analysis as a Tool for Making Sense of Service Users' Accounts of Their Mental Health Problems.

Wendy Sims-SchoutenSarah Riley
Published in: Qualitative health research (2018)
Making sense of service users' accounts of their mental health problems requires a method able to deal with complexity. Yet the different underlying epistemological and ontological positions of the methods researchers use, based, for example, on biomedicine or social constructionism, produce highly partial analyses. Addressing this problem, this article offers a method of Critical Realist Discourse Analysis (CRDA) that employs a synthesized discourse analysis, informed by critical realism, to examine the discursive, material, embodied, and institutional factors that might inform how mental health service users make sense of their mental health problems and associated service use. The article describes the epistemological/ontological underpinnings of CRDA and its three-phase methodology, before showcasing the method using, as examples, two data sets from care leavers and mothers. With our CRDA, we demonstrate a method for analyzing the complexity of interacting factors informing service users' understanding of their mental health problems.
Keyphrases
  • mental health
  • mental illness
  • healthcare
  • machine learning
  • big data
  • chronic pain