Analyzing data generated through deliberative dialogue

Deliberative dialogue (DD) is a knowledge translation strategy that can serve to generate rich data and bridge health research with action. An intriguing alternative to other modes of generating data, the purposeful and evidence-informed conversations characteristic of DD generate data inclusive of collective interpretations. These data are thus dialogic, presenting complex challenges for qualitative analysis. In this article, we discuss the nature of data generated through DD, orienting ourselves toward a theoretically grounded approach to analysis. We offer an integrated framework for analysis, balancing analytical strategies of categorizing and connecting with the use of empathetic and suspicious interpretive lenses. In this framework, data generation and analysis occur in concert, alongside engaging participants and synthesizing evidence. An example of application is provided, demonstrating nuances of the framework. We conclude with reflections on the strengths and limitations of the framework, suggesting how it may be relevant in other qualitative health approaches.