Credibility

Qualitative Tech Solutions: Coverage & Validity Considerations

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 TQF Credibilityto 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 managing engagement, 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).

 

 

* https://www.pewresearch.org/internet/fact-sheet/internet-broadband/

** https://www.businesswire.com/news/home/20180409006050/en/Minute-Maid-Debuts-New-Campaign-Celebrates-Good

James, N., & Busher, H. (2009). Online interviewing. London: Sage Publications.

Applying the TQF Credibility Component: An IDI Case Study

The Total Quality Framework (TQF) is an approach to qualitative research design that integrates quality principles without stifling the fundamental and unique attributes of qualitative research. In so doing, the TQF helps qualitative researchers develop critical thinking skills by showing them how to give explicit attention to quality issues related to conceptualization, implementation, analysis, and reporting.

The following case study offers an example of how many of the concerns of the Credibility (or data collection) component of the TQF were applied to an in-depth interview (IDI) study conducted by Roller Research. This case study can be read in its entirety in Roller & Lavrakas (2015, pp. 100-103).

Credibility Component of the Total Quality FrameworkScope

This study was conducted for a large provider of information services associated with nonprofit organizations based in the U.S. The purpose was to investigate the information needs among current and former users of these information services in order to facilitate the development of “cutting edge” service concepts.

Eighty-six (86) IDIs were conducted among individuals within various grant-making and philanthropic organizations (e.g., private foundations, public charities, and education institutions) who are responsible for the decision to purchase and utilize these information services.

There were two important considerations in choosing to complete 86 interviews: (a) the required level of analysis – it was important to be able to analyze the data by the various types of organizations, and (b) practical considerations – the available budget (how much money there was to spend on the research) and time restrictions (the research findings were to be presented at an upcoming board meeting). In terms of mode, 28 IDIs were conducted with the largest, most complex users of these information services, while the remaining 58 interviews were conducted on the telephone.

Participants were stratified by type, size, and geographic location and then selected on an nth-name basis across the entire lists of users and former users provided by the research sponsor.

A high degree of cooperation was achieved during the recruitment process by way of: Read Full Text

Mobile & Online Qualitative Research: The Good, the Bad, & the Ugly

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