Learning from Interviews On the Go

MCL Guidance

By Sarah Garrett

Occasionally, MCL members receive requests for advice on qualitative and mixed methods studies. Here we will occasionally provide guidance from these conversations.

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Recently, a clinician investigator came to us to ask about what to do now that they were a few interviews into their study. They felt they had learned a lot in the first four interviews, and they recognized that this was a moment when they could assess and refine their approach. This is absolutely a best practice in qualitative research. There are a few things I like to think about at this stage of an applied or clinical research project like theirs.

1. Evaluate whether your data collection is generating both what you need now and what you’ll need later. These interviews show you to what extent recruiting and conducting your envisioned interviews is feasible. That's important information. But it’s also important to assess whether these early interviews are generating sufficiently relevant and high-quality data for the manuscripts you plan to write. This concerns whether the data are directly related to the research questions you are trying to answer. Writing a summary/reflection memo after each interview, or at least after every few, can be very useful for this evaluation. Have you been able to learn something from each interview related to your main questions? Are your observations telling you something about the setting you need to understand?

Related but distinct is the issue of whether the on-topic data you’re collecting is of sufficient depth. If someone is talking about a phenomenon of interest, are you probing or investigating enough to get meaningful and nuanced information about it? For example, the respondent might identify the location of a clinic as a barrier to their attending their appointment. Do you dig enough to know whether that's about transportation? Or the safety of the clinic neighborhood? Or about fatigue that limits how far they stray from home? Small and Calarco’s 2022 Qualitative Literacy(especially Chapter 1) provide excellent examples of the payoffs of attentive and empathic probing. Early interviews can give you a signal whether your collection approach is giving you sufficiently targeted and sufficiently thick information.

2. Early in data collection is also a good time to assess whether you are leveraging the strengths of the method. Are you getting insights that are worth the time, cost, and other burdens of qualitative research? If not, how can you better leverage your approach? If you are discovering some topics can be covered using a series of structured questions, you might consider constructing and fielding a close-ended survey to cover them. If it looks like your participants’ experiences are already well-documented in the literature, this is a great time to recognize that there is no need to continue re-discovering what is already known – you can embrace the opportunity and challenge of considering how your study can ‘go deeper.’ For example, if other studies have already documented the existence of the transportation barriers you keep hearing about from your participants, you could revise data collection to give more time to unpacking the mechanisms or mindsets underlying how different respondents experience these barriers.

Similarly, are you eliciting and making space for insights and stories that you didn’t anticipate? Most experienced qualitative researchers have a question they love to ask toward the end of interviews and focus groups, like What else should I have asked about this topic? What do you wish more people understood about this? What surprised you about x?

Finally, now is also a good time to check that you’re building in opportunities for your participants—people closer to the problem or phenomenon that you’re researching—to think and problem-solve alongside you and your colleagues. This is a central feature of some approaches such as community-engaged and participatory action research, but it can be fruitful in any qualitative study. What do you think [decision-makers] should do about this? If you were in charge, how would you approach this problem?

 3. Practically, this is an important moment to assess what is working vs. what needs refining in the project’s operations and data management processes. Some processes you can expect to get smoother and smoother as you do more data collection e.g., talking through the consent form or coordinating the transfer of audio recordings to a secure server. Other processes, however, may require intervention and redesign. To detect these, it is wise to have everyone involved in data collection and data management keep a log of problems and challenges, particularly in these early weeks of the study. Watch for where it feels easy to get something wrong, to lose some data, to mislabel files. 

Consider also whether there are opportunities to build in fail-safes or redundancies. For example, many MCL investigators include several pieces of information in transcript file names (e.g. ID number, site number, participant gender, date of interview) to facilitate checking the categorization of transcripts into groupings for analysis. Having these data visible in the qualitative database has allowed us to quickly catch errors in, for example, the classification and titling of transcripts.  

Once you establish the solutions, updates, and improvements, ensure they are clearly documented in your team protocols or “standard operating procedures.” 

4. Finally, this is an excellent moment to assess whether your research practices are aligned with the principles underlying your work. Many of us are motivated to contribute to the greater good via our work. Among my MCL colleagues this includes, for example, conducting research that could help to reduce suffering in patients and families, reduce moral distress and burnout in healthcare providers, advance health equity, and promote humanizing and respectful healthcare, among other commitments. You likely share one or more of these goals as well.

Early in the research study is an important moment to evaluate opportunities to better align the project with such principles. For those conducting community-engaged research, you can assess whether you are recognizing and fully leveraging participants’ expertise, e.g., by soliciting their recommendations and their interpretation of problems. You may now also identify new opportunities for members of the community to participate in the project as collaborators. If recruitment is going more slowly than you anticipated, consider how well your approaches align with the priorities and realities of the community/population you’re targeting. Does your study investigate something this community finds worthwhile?

All of us can assess whether our data collection activities express respect for our research participants. In those early interviews and observations, for example, you can feel out whether participants feel comfortable and respected in the research engagement—and what adjustments should be made if needed. Review whether your data collection logistics are indeed well-matched to the lives of your participants in terms of its timing (during vs. outside of business hours), location, accessibility. Are there early signals that you are compensating the participants in ways that recognize their wisdom and value to the study? These considerations are invaluable to address during study design, but sometimes you may discover missteps only once you’ve launched the research. 

Being a few interviews into a research study is a great moment to take stock of how your research approach is working for your team, your data, your scientific goals, and the population it is ultimately supposed to benefit. Consider building in time into your study’s plans to make sure you make the most of it.