Mixed methods refers to a relatively new research methodology seeking to capitalize on the strengths of quantitative and qualitative data within a single study by integrating the 2 data types.^1,2 Mixing data allows for a more comprehensive and enhanced understanding of a research question than either method could provide alone. Importantly, mixed methodology is not only about using both quantitative and qualitative methods to explore the same study topic (ie, multiple methods). Instead, methods should be combined in a way that creates complementary strengths and nonoverlapping weaknesses through data integration at 1 or more study phases.³

The use of mixed methods in the health sciences has rapidly expanded as investigators have looked to explain patient or clinician behavior, determine the determinants to best practice, or evaluate the implementation of evidenced-based interventions. The 3 main reasons to consider mixed methods are to (1) obtain convergence or corroboration of main findings, (2) eliminate or minimize alternative explanations from the conclusions drawn from the data, and (3) explain divergent aspects of a phenomenon.