Back in 2018, Research Design Review posted an article titled “Five Tech Solutions to Qualitative Data Collection: What Strengthens or Weakens Data Quality?” The focus of this article is on a presentation given in May 2018 concerning technological alternatives to qualitative research data collection. Importantly, the aim of the presentation was, not to simply identify different approaches to data collection beyond the in-person and telephone modes but rather, to examine the strengths and limitations of these technological solutions from a data quality – specifically, Credibility – standpoint.
Broadly speaking, technological approaches to qualitative research data gathering offer clear advantages over in-person methods, particularly in the areas of:
Representation, e.g., geographic coverage, potential access to hard-to-reach population segments;
Cooperation, e.g., convenience and flexibility of time and place for participants, appropriateness for certain demographic segments (18-49 year olds*);
Validity associated with data accuracy, e.g., research capturing in-the-moment experiences do not rely on memory recall;
Validity associated with the depth of data, e.g., capturing multiple contextual dimensions through text, video, and images;
Validity associated with data accuracy and depth allowing for the triangulation of data;
Researcher effects, e.g., mitigated by the opportunity for greater reflection and consistency across research events;
Participant effects, e.g., mitigated by the multiple ways to express thoughts, willingness to discuss sensitive issues, and (possibly) a lower tendency for social desirability responding; and
Efficient use of resources (i.e., time, money, and staff).
There are also potential drawbacks to any technological solution, including those associated with:
Uneven Internet access and comfort with technology among certain demographic groups (e.g., sampling favors “tech savvy” individuals), hard-to-reach and marginalized segments of the population;
Difficulty in managingengagement, including the unique researcher skills and allocation of time required;
Potential participant burnout from researcher’s requests for multiple input activities and/or days of engagement. This is a type of participant effect that negatively impacts validity;
Nonresponse due to mode, e.g., unwillingness or inability to participate to a mostly text-based discussion;
Data accuracy, e.g., participant alters behavior in a study observing in-home meal preparation;
Missing important visual &/or verbal cues which may interfere with rapport building and an in-depth exploration of responses;
Difficulty managing analysis due to lots and lots of data (in volume & formats);
Fraud, misrepresentation – “Identity is fluid and potentially multiple on the Internet” (James and Bushner, 2009, p. 35) and people may not share certain images or video that reveal something “embarrassing” about themselves**; and
Security, confidentiality, anonymity (e.g., data storage, de-identification).
Data quality matters. Regardless of the research method or approach, our ability to say anything meaningful about our research outcomes hinges on the integrity of the data. The greater care the researcher takes to ensure the basic ingredients of “good” research design, the more confident the researcher and importantly the user of the research will be in the recommendations drawn from the research and its ultimate usefulness.
This focus on data quality applies to all research. And although it is most often a topic of discussion among survey researchers, data quality considerations are increasingly (I hope!) a discussion among qualitative researchers as well. Indeed, the underlying validity of our qualitative data is an important consideration regardless of the researcher’s paradigm orientation or the qualitative method, including the more recent methodological options – that is, mobile and online qualitative research.
Mobile and online technology – in particular, tech solutions that combine observation with a multimethod/mode approach – offer qualitative researchers new ways to investigate a variety of situations that give them a closer understanding of participants’ lived experiences as never before possible. Three such situations are: Read Full Text
Qualitative researchers have increasingly new ways to engage with their participants. Beyond the traditional and still most frequent approach of the in-person mode, qualitative researchers have a host of technological solutions at their disposal. Instead of in-person focus group discussions, for instance, the researcher might opt for asynchronous focus groups. Or rather than in-person multiple methods qualitative research, the researcher might design an all-tech solution that blends online observation with asynchronous groups or any one of several technological options for the in-depth interview method such as mobile video or the email IDI.
The following is a presentation given at the2018 annual conference of the American Association for Public Opinion Research. This presentation discusses five tech solutions to qualitative research data collection with particular consideration given to the aspects of these approaches that strengthen or weaken data quality. These quality considerations are discussed from the perspective of the Total Quality Framework and, specifically, the Credibility component which has to do with qualitative data collection.
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