Generating or developing grounded theory: methods to understand health and illness

Grounded theory is a qualitative research methodology that aims to explain social phenomena, e.g. why particular motivations or patterns of behaviour occur, at a conceptual level. Developed in the 1960s by Glaser and Strauss, the methodology has been reinterpreted by Strauss and Corbin in more recent times, resulting in different schools of thought. Differences arise from different philosophical perspectives concerning knowledge (epistemology) and the nature of reality (ontology), demanding that researchers make clear theoretical choices at the commencement of their research when choosing this methodology. Compared to other qualitative methods it has ability to achieve understanding of, rather than simply describing, a social phenomenon. Achieving understanding however, requires theoretical sampling to choose interviewees that can contribute most to the research and understanding of the phenomenon, and constant comparison of interviews to evaluate the same event or process in different settings or situations. Sampling continues until conceptual saturation is reached, i.e. when no new concepts emerge from the data. Data analysis focusses on categorising data (finding the main elements of what is occurring and why), and describing those categories in terms of properties (conceptual characteristics that define the category and give meaning) and dimensions (the variations within properties which produce specificity and range). Ultimately a core category which theoretically explains how all other categories are linked together is developed from the data. While achieving theoretical abstraction in the core category, it should be logical and capture all of the variation within the data. Theory development requires understanding of the methodology not just working through a set of procedures. This article provides a basic overview, set in the literature surrounding grounded theory, for those wanting to increase their understanding and quality of research output.