Practical Qualitative Data Analysis for Public Health Research: A Guide to a Team-Based Approach With Flexible Coding

Abstract

Qualitative research is important to advance health equity as it offers nuanced insights into structural determinants of health inequities, amplifies the voices of communities directly affected by health inequities, and informs community-based interventions. The scale and frequency of public health crises have accelerated in recent years (e.g., pandemic, environmental disasters, climate change). The field of public health research and practice would benefit from timely and time-sensitive qualitative inquiries for which a practical approach to qualitative data analysis (QDA) is needed. One useful QDA approach stemming from sociology is flexible coding. We discuss our practical experience with a team-based approach using flexible coding for qualitative data analysis in public health, illustrating how this process can be applied to address multiple research questions simultaneously or asynchronously. We share lessons from this case study, while acknowledging that flexible coding has broader applicability across disciplines. Flexible coding provides an approachable step-by-step process that enables collaboration among coders of varying levels of experience to analyze large datasets. It also serves as a valuable training tool for novice coders, something urgently needed in public health. The structuring enabled through flexible coding allows for prioritizing urgent research questions, while preparing large datasets to be revisited many times, facilitating secondary analysis. We further discuss the benefit of flexible coding for increasing the reliability of results through active engagement with the data and the production of multiple analytical outputs.