Schema Analysis of Qualitative Data: A Team-Based Approach

Abstract

Schema analysis is a novel, qualitative data analysis technique that uses a summative approach to make sense of complex, nuanced, textual data. It aims to ensure that key features of a text, or “essential elements,” are revealed before any interpretation of those key elements takes place, based on the assertion that data should be handled in a principled, informed, and strategic manner to achieve phenomenal clarity. Teamwork is a central element of schema analysis, enabling researchers to effectively co-create meaning across disciplinary boundaries through consensus-driven strategies. The research team’s shared accountability for interpretive decisions is clearly linked to a study’s original questions and the research team’s desire to be rigorous in their collaborative stance and equally vocal. Schema analysis can be used in the context of a wide range of qualitative studies or can sit alongside outputs from other mixed-methods studies to add substance to their findings. The technique has been successfully developed and refined by the lead author, to suit a wide variety of healthcare scenarios, evidenced by published research projects from UK and Australian contexts. In this chapter, the method is presented in detail, step by step. An example of the use of schema analysis in practice is offered up from a recent Australian study that examined multidisciplinary team-working practices in oncology. Study data from an interview with an oncology psychologist working as part of an oncological multidisciplinary team is considered, to reveal how healthcare professionals present information about risk to women with breast cancer. The chapter considers methodological implications for achieving validity and rigor, upholding trustworthiness in data, and creating data that are transferable to different settings. To conclude, the chapter reflects on future opportunities for the method’s use in qualitative research.