Generating best evidence from qualitative research: the role of data analysis

TLDR

Rigorous and systematic analysis of qualitative data is essential for producing high‑quality research. The authors aim to demonstrate that clear, transparent data analysis in interview‑based qualitative research is crucial for generating robust evidence. They describe an iterative process where data analysis runs concurrently with collection, testing fit, and follows four thematic steps—immersion, coding, categorizing, and theme generation. Explicit accounts of the analysis process reveal how conclusions are reached, and studies that anchor themes to data and theory yield the strongest evidence.

Abstract

To outline the importance of the clarity of data analysis in the doing and reporting of interview‐based qualitative research. We explore the clear links between data analysis and evidence. We argue that transparency in the data analysis process is integral to determining the evidence that is generated. Data analysis must occur concurrently with data collection and comprises an ongoing process of 'testing the fit' between the data collected and analysis. We discuss four steps in the process of thematic data analysis: immersion, coding, categorising and generation of themes. Rigorous and systematic analysis of qualitative data is integral to the production of high‐quality research. Studies that give an explicit account of the data analysis process provide insights into how conclusions are reached while studies that explain themes anchored to data and theory produce the strongest evidence.