Sampling: How does it set qualitative research apart?

Hello Qualitative Minds,

I recently delivered three webinars covering “The Five Mistakes That Lead to Unpublishable Qualitative Health Research”, and one of the mistakes was about sampling. Sampling is such an important procedure in qualitative health research that I saw fitting to explore it here as well.

I have many quotes inside QRB (Qualitative Research Blueprint) that come from my mentor and former PhD supervisor, Dr. Maria Mayan, and a few of them relate to sampling. They’re short yet self-explanatory, and in my opinion, utterly powerful.So I’ll start our conversation with them. Maria says in her book The Essentials of Qualitative Inquiry:

“Nothing highlights the difference between quantitative and qualitative methods more explicitly than the logic that underlies sampling.” (Mayan, 2009. p. 61)

“Bias in qualitative research is a sampling strength.” (Mayan, 2009. p. 61)

Qualitative research is made possible, and enriched, by participants and data (e.g., documents, art, text, etc.) that help us, as researchers, to deeply understand the phenomenon of interest. Randomly sampling participants and data does not lead qualitative researchers down the path of richly exploring the phenomenon of interest (usually guided by a thoughtfully designed research question and/or overall purpose). In contrast, randomization in qualitative research might lead to large amount of data that will make no contribution to the qualitative findings. It means wasted resources and frustration for all.

Numerous sampling strategies exist within qualitative methods. Michael Quinn Patton in his book Qualitative Research & Evaluation Methods has a list sampling strategies that might slightly boggle your mind. However, the most commonly used ones are purposive, theoretical, convenience and snowball sampling. I won’t explain each sampling strategy but will say that yours must align with your qualitative paradigm, research question and methods of data generation and analysis. Sampling is a key component of what Jan Morse and Maria Mayan describe as methodological congruence, which basically refers to aligning all the components of the research process when striving for the best end product.

I’ve witnessed, more than once, qualitative health researchers (often graduate students) being asked by academics or peers if their samples were “biased”given that participants were purposefully selected. Unfortunately, in most cases, that question causes discomfort when in fact it could be an opportunity for qualitative health researchers to bolster their confidence in their research paradigm and knowledge of their own research. Instead of “caught in the act” and “now what?” reactions, the question should be seen as an unsolicited invitation for qualitative researchers to shine, especially in health sciences.

I’m giving you full permission to memorize Maria’s quote and repeat it with pride. It’s a good way to start an answer that should also include your sampling strategy, and its appropriateness for the methods that you used in your project.

If you didn’t attend the webinar I mentioned in the opening paragraph, you might be asking yourself, “How does sampling lead to unpublishable qualitative health research?” Well, a sampling mistake can negatively shape generated and analyzed data. It may result in something that isn’t substantial enough to be published or, maybe worse, something that won’t make a contribution to your field and area of study. As researchers, we want to make a positive impact in the communities touched by our work; therefore, thinking through our sampling strategy is essential and undoubtedly something that sets qualitative research apart!

Talk soon,

Maira