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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.

Figure 4.1 illustrates the point (Bernard 1996). The stereotypes of qualitative and quantitative research are depicted in cells A and D, respectively. Cell A captures interpretive approaches to text, including traditions such as grounded theory (Charmaz 2014) and discourse analysis (Farnell and Graham 2015). Cell D captures the statistical analysis of numerical data, such as from closed-ended survey research. But these combinations don’t exhaust the possibilities. In cell B, the qualitative analysis of quantitative data refers to the act of extracting meaning from the results of statistical analysis or mathematical processing. All so-called quantitative research involves this interpretive act; without it, there would be little point in running a regression model or producing a scatterplot. Last, methods in cell C generally involve turning words – or images or photos or artifacts – into numbers to look for patterns. That’s the essence of classic content analysis (Krippendorff 2018). We can also place methods for cultural domain analysis like free listing and pile sorting in this cell (Dengah et al. 2021; Weller and Romney 1988).

Figure 4.1 Qualitative and quantitative data and analysis (adapted from Bernard 1996).

The point is that medical anthropologists, like all social scientists, have access to many tools for data collection and analysis, and we ought to use the right ones for a given research question. Dividing the toolkit of social science into qualitative and quantitative methods tends to obscure that point.