A Companion to Medical Anthropology - Группа авторов

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would help to generate theory. This approach is appropriate whenever there is insufficient existing theory or evidence to establish expectations.

      Exploratory questions are also apt for centering people’s expertise about their own lives, which can challenge dominant narratives, existing theory, or researchers’ preconceptions. For example, Reese (2019) begins her ethnography of racialized food apartheid and Black self-reliance in Washington, DC, by recounting a “conversation on Mr. Johnson’s front porch.” Reese chose this starting point because of the way it and other conversations “changed what I was listening for” (p. 2). Her initial concern was the influence of the built environment, a theoretical orientation “heavily influenced by anthropology, food studies, and sociology.” But Mr. Johnson had other stories to tell, and by “listening to him more than doing much talking” (p. 1), Reese left with a new set of questions that framed the rest of the work.

      The flow of his storytelling revealed what Zora Neale Hurston wrote about in Dust Tracks on the Road: that research was the blessing through which I could formalize the curiosities that emerged on Mr. Johnson’s porch, and that if I got out of the way, Black people would tell their stories how and when they wanted. It was not my job to dictate which stories should be told, but if I let them, Black storytelling would lead me places that I had not planned to go. (Reese 2019, pp. 2–3)

      Reese exemplifies the power of listening to generate theory. Although she “had not planned to go” where she ended up, she had, undoubtedly, made a choice to respect people’s experience. And so she entered the field with a fundamentally exploratory question: What is going on here? Her decision to listen allowed people to define what matters on their own terms; her job, then, was to “formalize the curiosities that emerged.” Reese did so primarily using methods that prioritize discovery: participant observation, archival research, and semistructured interviews.

      When prior theory and evidence warrant specific expectations, confirmatory research questions are appropriate. One distinctive feature of confirmatory research in medical anthropology is that it often builds on an exploratory phase in the same study. We see that progression in Reese’s work. Toward the end of her fieldwork, Reese and a community collaborator conducted a survey designed to place the ethnographic findings in context. Part of the purpose was strategic: “The hope was that this data would put some numbers behind the anecdotal experiences that we all knew were true but were not always heard by those in power” (p. 15). But there is also an implicit confirmatory question: To what extent do the stories of Mr. Johnson and others characterize a broader geographic and social context?

      Similarly, in their exploratory work, Chavez et al. (1995) found that Latinas’ beliefs about cervical and breast cancer differed from biomedical models more than Anglo women’s beliefs did. “We were left wondering,” they later wrote (Chavez et al. 2001, p. 1114), “to what extent these patterns of belief were associated with behavior, specifically the use of Pap exams, a screening test for cervical cancer. In other words, to what degree do cultural beliefs matter in the use of medical services?” Chavez et al. (2001) combined ethnographic interviews and survey research to address this question and found that, under certain circumstances, beliefs matter a lot.

      Unstructured–Structured Methods

      The continuum of exploratory to confirmatory questions is useful because it informs the choice of methods for data collection and analysis. One approach is to strive for a fit between exploratory–confirmatory questions and unstructured–structured methods (Figure 4.2). By “structure,” I mean the amount of control researchers impose on data collection. The difference between a structured and unstructured interview, for example, is the likelihood that all participants respond to the same questions in the same order. The basic principle for matching methods and questions is that the less we know about any given phenomenon, the less structure we ought to impose, so that we remain open to discovery. As we learn more and begin to develop hunches about what’s going on, we often want to impose more structure to test our ideas (Weller 2015).

      Note that “structure” does not mean “qualitative” or “quantitative”; qualitative and quantitative data and analysis cut across the continuum. For example, informal interviews conducted during participant observation – Reese’s (2019) “conversation with Mr. Johnson” – generate qualitative data and fall at the unstructured end of the continuum. But we could also obtain qualitative data from more structured methods, such as an open-ended survey that poses the same questions to each respondent in the same way, as Reese (2019, pp. 52–55) also did. The choice between these methods depends on the balance between exploratory and confirmatory objectives. Informal interviews would remain open to discovery, whereas an open-ended survey would permit systematic comparisons between respondents.

      We can also place both qualitative and quantitative methods of data analysis along the entire spectrum. Both grounded theory (Charmaz 2014) and semantic network analysis (Doerfel 1998) could be described as unstructured methods, in the sense that researchers try not to impose a prior theoretical framework about the concepts and relations in a given corpus of text. Both approaches are appropriate for exploratory aims. Yet grounded theory relies only on words, whereas semantic network analysis relies on turning words into numbers and on mathematical processing.

      Figure 4.3 Inductive and deductive modes of reasoning in the cycle of research.

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