one increasingly common site of development in qualitative research is a search for ways to blur the boundaries between qualitative and quantitative approaches. Some researchers do this by translating qualitative data from text into numerical data that can be analyzed statistically. Content analysis is especially amenable to this quantification process, but it can be used with any of the qualitative techniques discussed above. Analyses using fuzzy-set Qualitative Comparative Analysis requires the researcher to take complex qualitative data and classify cases by their degree of membership in a set of conceptual categories. The researcher then analyzes the combinations of concepts that produce a particular outcome. For example, one group of researchers defined different health care service contexts and patient characteristics as concepts and coded those concepts from interviews with vulnerable patients (Vickery et al. 2018). They then analyzed which service contexts and patient characteristics combined to produce the highest levels of improvement in quality of life. The focus on rich in-depth data and combinations of factors can be especially helpful for improving health policies or practices in the administration of care.
CONCLUSION
Like many other academic disciplines, consensus among medical sociologists is built from an accumulation of evidence from accepted research methods. On the one hand, the breadth of sociological methods available to study a topic is at times overwhelming. On the other hand, the triangulation of findings from multiple methods is a critical part of establishing consensus on sociological phenomenon as it relates to health and health systems. Throughout the chapters that follow in this volume, the integration of results from a variety of research methods will often offer answers to contemporary questions in medical sociology that no single study is able to provide. Thus, in our chapter of methods, we’ve tried to unpack some of the basic information about doing medical sociology research that can easily be skipped if one is too focused on pure statistical estimation.
We believe that doing good research is important beyond simply the improvement of science. Medical sociology has always had a more applied focus than other sub-disciplines of sociology, making it imperative that we use strong methodological approaches to answer a range of questions that also serve the public good. Some of these questions will take on the testing, refining, and creation of general social theory. Other questions will be more focused on using sociological insights to solve pressing problems in health and medicine. Both intentions are improved by attention to the issues we discuss here.
To end on a practical note, we’d like to take a moment to emphasize that a major component of both qualitative and quantitative analysis should be careful data management. The bulk of day-to-day work on research projects is keeping data organized and preparing it for analysis. Unfortunately, even the most cutting-edge methods can’t overcome the errors created by incorrectly coded variables or misplaced field notes. This adds organizational pitfalls to the already difficult process of empirically testing a theoretical model. Although we won’t advocate strongly for any specific one, we strongly suggest investing the time and energy to establish a good workflow of data analysis with your preferred method of analysis [e.g. see Long (2009) for an excellent approach integrated with Stata and Wickham and Grolemund (2017) for one using R].
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