Doing classic grounded theory: the data analysis process

This case study shares some of the methodological challenges I faced during my PhD research from 2007 to 2010. My study focused on Condition Management Programmes, part of the UK Government's Pathways to Work initiative, which provided work-focused interventions for people claiming health-related benefits. In 2007, there had been very little research on Condition Management Programmes, and there was little understanding about how they were actually being delivered at a ground level. As an inductive methodology suited to researching new areas, I decided to use classic grounded theory. The aim of classic grounded theory is to identify participants? main concern and develop a theory that explains their behaviour. I interviewed health-care practitioners working in Condition Management Programmes and observed their treatment sessions with clients. By following the key stages of classic grounded theory (theoretical sampling, substantive coding, memo writing and theoretical coding), I developed a theory that explained practitioners? decision-making processes. This case study provides a detailed account of some of the difficulties I encountered as I analysed my data and how these were resolved. I address the five key areas of data analysis that I found challenging: getting conceptual, choosing a core category, recognising theoretical saturation, achieving theoretical integration and manual versus computer-assisted analysis