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Whole books have been written about research design, and several extended treatments discuss applications to anthropology in particular (Bernard 2018; Brim and Spain 1974; Johnson 1998; LeCompte and Schensul 2010; Pelto and Pelto 1996). This work is essential reading for medical anthropologists. Here I outline some basic ideas for connecting data and theory through research design.

Medical anthropology, like the social sciences generally, is often described in terms of a dichotomy between “qualitative” and “quantitative” methods of social research. However, a growing number of methodologists across the social sciences advocate “taking the ‘Q’ out of research” (Onwuegbuzie and Leech 2005; Sobo 2009).

There are at least two reasons why the qualitative–quantitative distinction is usually counterproductive. First, the collection and analysis of both qualitative and quantitative data are compatible with the same logic of inquiry (Keohane et al. 2021; Teddlie and Tashakkori 2009). From this perspective, researchers should use whichever methods work best for a particular research question. Second, the qualitative–quantitative distinction conflates data collection and data analysis. Bernard (1996) identified this problem by noting the ambiguity of the phrase “qualitative data analysis.” From the syntax alone, we cannot tell whether the phrase means the analysis of qualitative data or the qualitative analysis of data. We can avoid this ambiguity by using “qualitative” and “quantitative” to modify specific types of data and types of analysis – not types of research.