mixedmethodsDesigns

Mixed methods designs refer to research strategies that deliberately combine quantitative and qualitative approaches within a single study or program of research. The goal is to leverage the strengths of both paradigms—statistical generalizability and rich contextual understanding—to address complex research questions. Mixed methods designs can be used across disciplines and in various stages of inquiry, including exploration, measurement, and theory development.

Common designs include convergent parallel, explanatory sequential, exploratory sequential, embedded, multiphase, and transformative designs. In a convergent parallel design, quantitative and qualitative data are collected concurrently, analyzed separately, and then merged to interpret results. In an explanatory sequential design, quantitative data are collected first, followed by qualitative data to explain or elaborate the quantitative results. In an exploratory sequential design, qualitative data guide subsequent quantitative data collection and analysis. An embedded design uses one data type to address a component of a larger design, such as qualitative data collected within a primarily quantitative study. A multiphase design extends the approach across several phases over time, often in program evaluation. A transformative design is guided by a theoretical or advocacy framework, aligning methods with social justice or equity considerations.

Data integration is central to mixed methods work and may occur at the design, data collection, analysis, and interpretation stages. Techniques include merging data during analysis, connecting results across studies, or embedding qualitative findings within quantitative results via joint displays or narrative integration.

Advantages of mixed methods designs include broader explanatory power, validation through convergence, and instrument development or refinement. Challenges include greater complexity, higher resource demands, longer timelines, potential misalignment of samples or timing, and the need for researchers to be proficient in multiple methods and paradigms.