Читать книгу A Companion to Medical Anthropology - Группа авторов - Страница 65

Good research design consists of an explicit, logical plan for connecting data and theory. In all types of research – participant observation, surveys, experiments – the major components of this plan are the same:

 Formulating research questions (and hypotheses, if appropriate)

 Selecting a research site where the research questions can be addressed

 Developing a sampling strategy for selecting observations required to answer the research questions or test hypotheses

 Choosing methods to collect data needed to answer research questions

 Creating a plan for managing, documenting, and archiving data

 Selecting methods for analyzing data to answer specific research questions and test hypotheses

This list makes clear how research questions ideally permeate all major components of research design – sampling, data collection, and data analysis. Well-designed studies (and grant proposals) make these links explicit.

Medical anthropologists and others have offered practical advice to enhance the links between different elements of research design. LeCompte and Schensul (2010, p. 188) recommend that researchers use a “data collection matrix” to fit questions to methods. Their matrix involves listing what researchers want to know, what types of data they will need to find out, where and from whom they can find such data, and how they will collect it.

Carey and Gelaude (2008, p. 237) emphasize the logic of design in the development of interview materials. They recommend creating an “intents list” to make explicit the rationale for each question in an interview. In a study of HIV risk, Carey’s team duplicated the semistructured interview guide and, below each question, added a one-line description of why the question was being asked. They also created a spreadsheet with three columns: (1) project objectives, (2) specific interview questions, and (3) citations related to the rationale or design of each question. These tools ensured that the design of interview materials was tightly integrated with the research questions and also proved useful in interviewer training and data monitoring. Powis (2017) described his use of this approach for ethnographic research on the experiences of expectant fathers in Dakar, Senegal (Powis 2020). Carey and Gelaude (2008, pp. 244–252) also recommend applying the logic of an intents list to data management and analysis plans before the project begins.

Having an explicit, logical plan to connect data and theory enhances the validity of all types of research. DeWalt and DeWalt (2011) discuss how to design research with participant observation. Spradley’s (1979, 1980) Developmental Research Sequence is a model for designing ethnographic research with progressively more focused methods of data collection and analysis. Bernard (2018) shows how the logic of experimental design helps researchers avoid common threats to validity – even if you never run an experiment. Johnson (1998) discusses research design in systematic anthropological research, and LeCompte and Schensul (2010) show how the logic of research design cuts across specific methods of data collection and analysis. Each of these sources provides many examples from research in medical anthropology.