There is good reason to wonder what researchers mean when they talk about “qualitative research.” This is not a trite bemusement. Indeed, there is often an unspoken underlying premise in most discussions of “qualitative research” that researchers harbor a mutually agreed-to concept of what qualitative research is, when in fact this is not the case. Attend a qualitative research conference session and you will find that the presenter predictably delves into the particular subject matter without a hint of the researcher’s definition of “qualitative research,” leaving attendees with the arduous (and misguided) task of linking their own concept of qualitative research with the presenter’s discussion.
There are a number of ways that researchers may conceptualize or define qualitative research. For instance, some may define qualitative research simply by its unique set of methods, e.g., focus group discussions, in-depth interviews, ethnography; whereby, a focus group study is deemed qualitative research regardless of the skills of the moderator or how the data are treated or reported to end users. Similarly, qualitative research may be understood solely by the interview format, e.g., a semi-structured in-depth interview (IDI) constitutes qualitative research while a structured IDI not so much (and actually leans towards a more quantitative approach).
Another understanding of qualitative research may center on the intent or types of questions being asked. For example, I have heard quantitative researchers refer to their design decisions (such as weighing project costs with research quality) as qualitative research. And some researchers may think that any approach that is self-reflective in nature (such as autoethnography) is qualitative research. Some researchers also use labels such as “qualitative survey” or “qualitative questionnaire” which serves to brand their study “qualitative research.”
And yet another definition of qualitative research resides in the data itself; that is, any non-numerical dataset may be deemed qualitative research. This includes the many researchers who believe the use of open-ended questions in a survey questionnaire is the qualitative component of their research. This also includes the researcher who associates any text and/or image research data as qualitative data and, ipso facto, qualitative research. An important but unfortunate consequence of these data-driven interpretations of qualitative research is the tendency for the researcher to treat qualitative data as discrete bits of information to be pushed around and manipulated much like survey data.
What is missing from all these interpretations of qualitative research is the essence of what qualitative research is. The methods that are used, the questions that are asked, and the resulting data make qualitative research unique but they don’t define what qualitative research is. Qualitative is not one (or more) of these almost tangible things but rather an intricate approach that respects the fundamental truism that conducting research with human beings is complicated.
“Qualitative research is about making connections. It is about understanding that good research involving human beings cannot be anything but complex, and that delving beyond the obvious or the expedient is a necessary tactic in order to understand how one facet of something adds meaning to some other facet, both of which lead the researcher to insights on this complexity… Qualitative research celebrates the fact that the complexities and intricacies—the connections—revealed at any one moment may or may not exist in another moment in time, reflecting the ever-changing reality of being human.” (Roller & Lavrakas, 2015, p. 2).
To ignore this basic tenet of qualitative research is to ignore why we conduct qualitative research in the first place. Here, I am not talking about the need for a particular theoretical orientation to qualitative research or personal paradigms but rather the importance of paying attention to the raison d’être for qualitative research itself.
For instance, calling open-ended questions/responses “qualitative research” overlooks the fact that these open-ended questions/responses exist within the confined context of a highly structured survey questionnaire. Similarly, performing statistical manipulations (e.g., correlations) and building data visuals (e.g., bar graphs), based on rating scales or frequencies, rests on certain assumptions such as normality and independence; thereby ignoring sample design issues in qualitative research, the less structured nature of qualitative research methods, as well as the contextual and nuance qualities associated with qualitative data.
This is why I begin all my qualitative presentations and workshops with a discussion of what I believe qualitative is.* It is not just a distinctive set of methods or formats, it is not just the intent or types of questions we want to ask, and it is not just non-numerical data. Underlying all of that is the “messy” reality of qualitative research’s unique attributes. To understand that is to understand my approach to qualitative research which in turn frames the context for thinking about how to apply basic research principles to qualitative research design.
*And I encourage other researchers to define their meaning of “qualitative research” at the outset of their presentations in order to help frame their discussions.
Roller, M. R., & Lavrakas, P. J. (2015). Applied qualitative research design: A total quality framework approach. New York: Guilford Press.
Image captured from: https://fineartamerica.com/art/abstract