Total Quality Framework

Exploring Human Realities: A Quality & Fair Approach

The following incorporates modified excerpts from Applied Qualitative Research Design: A Total Quality Framework Approach (Roller & Lavrakas, 2015, pp. 2-3).

Quality and fairness to explore human realitiesAs the channel by which researchers explore the depths of human realities, qualitative research has gained prominent status that is accelerating over time as quantitatively trained mentors in academia are increasingly asked to assist in students’ qualitative research designs, and as the volume of published works in qualitative research aggressively grows (cf. Charmaz, 2008; Lincoln, Lynham, & Guba, 2011; Silverman, 2013). Even psychology, a discipline that has traditionally dismissed qualitative research as “subjective” and “unscientific,” has come of age with slow but continued growth in the field of qualitative psychology (cf. Wertz, 2014). These advances have given rise to a vibrant array of scholars and practitioners who harbor varying perspectives on how to approach qualitative research.

These differing perspectives are best exemplified by the paradigm debates among qualitative researchers. The focus of these debates is on the underlying belief or orientation the researcher brings to any given qualitative study. In particular, these discussions center on the philosophical constructs related to the nature of reality (ontology) and that of knowledge (epistemology). It is the researchers’ sometimes divergent views on the presence and extent of a “true” reality—for example, whether it is the (post)positivism view that there is a single objective reality that can be found in a controlled scientific method, or the constructivism–interpretivism paradigm that emphasizes the idea of multiple realities existing in the context of social interactions and subjective meanings—as well as the source of this knowledge—for example, the dominant role of the researcher in critical theory—that have fueled an ongoing dialogue concerning paradigms within the qualitative research arena.

And yet, regardless of the philosophical or theoretical paradigms that may guide researchers in their qualitative inquiries, qualitative researchers are united in the fundamental and common goal of unraveling the convoluted and intricate world of the human experience.

The complexities of the human experience present unique challenges to qualitative researchers who strive to develop research designs that result in contextual data while incorporating basic standards of good research. To that end, many qualitative researchers, routinely focus their attention on the importance of methodically rigorous data collection practices and verification checks (Creswell, 2013; Marshall & Rossman, 2011; Morse, Barrett, Mayan, Olson, & Spiers, 2002); well-thought-out procedures and analytic rigor (Atkinson & Delamont, 2006; Berg & Lune, 2012), and frameworks that promote critical thinking throughout the research process (Levitt, Motulsky, Wertz, Morrow, & Ponterotto, 2017; Roller & Lavrakas, 2015).

By transcending the paradigm debates, a quality approach to qualitative research fosters the essential element of fairness while maximizing the ultimate usefulness of the research. Fairness means giving participants a fair voice in the research.  A “fair voice” is not a small q positivist-Big Q non-positivist issue (see Braun & Clarke, 2022) but rather the researcher’s quality approach to data collection and analysis that gives careful consideration to the scope of the sample design, researchers’ skills that prioritize inclusion, ongoing reflexivity, and other quality research strategies that embrace diversity in our participants and our methods.

A quality approach that promotes fairness to explore the complexity of human realities is a non-debatable goal of the qualitative researcher.

Atkinson, P., & Delamont, S. (2006). Rescuing narrative from qualitative research. Narrative Inquiry, 16(1), 164–172. https://doi.org/10.1075/ni.16.1.21atk

Berg, B. L., & Lune, H. (2012). Qualitative research methods for the social sciences (8th ed.). Boston: Pearson.

Braun, V., & Clarke, V. (2022). Toward good practice in thematic analysis: Avoiding common problems and be(com)ing a knowing researcher. International Journal of Transgender Health. https://doi.org/10.1080/26895269.2022.2129597

Charmaz, K. (2008). Views from the margins: Voices, silences, and suffering. Qualitative Research in Psychology, 5(1), 7–18. https://doi.org/10.1080/14780880701863518

Creswell, J. W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). Thousand Oaks, CA: Sage Publications.

Levitt, H. M., Motulsky, S. L., Wertz, F. J., Morrow, S. L., & Ponterotto, J. G. (2017). Recommendations for designing and reviewing qualitative research in psychology: Promoting methodological integrity. Qualitative Psychology, 4(1), 2–22. https://doi.org/10.1037/qup0000082

Lincoln, Y. S., Lynham, S. A., & Guba, E. G. (2011). Paradigmatic controversies, contradictions, and emerging confluences, revisited. In N. K. Denzin & Y. S. Lincoln (Eds.), The Sage handbook of qualitative research (pp. 97–128). Sage Publications.

Marshall, C., & Rossman, G. B. (2011). Designing qualitative reserach. Thousand Oaks, CA: Sage Publications.

Morse, J. M., Barrett, M., Mayan, M., Olson, K., & Spiers, J. (2002). Verification strategies for establishing reliability and validity in qualitative research. International Journal of Qualitative Methods, 1(2), 13–22.

Roller, M. R., & Lavrakas, P. J. (2015). Applied qualitative research design: A total quality framework approach. New York: Guilford Press.

Silverman, D. (2013). What counts as qualitative research? Some cautionary comments. Qualitative Sociology Review, IX(2), 48–55.

Wertz, F. J. (2014). Qualitative inquiry in the history of psychology. Qualitative Psychology, 1(1), 4–16.

Qualitative Research Participants: Gaining Access & Cooperation

The following is a modified excerpt from Applied Qualitative Research Design: A Total Quality Framework Approach (Roller & Lavrakas, 2015, p. 28).

Gaining cooperationWhen developing the sample design, including the sample size for a qualitative study, careful attention needs to be paid to how the researcher will gain access to individuals in the sample and then gain their cooperation to participate in the research.

In doing a company-sponsored in-depth interview study of employees, for example, gaining access to the employees who have been sampled may be as simple as sending each of them a notification that their employer has authorized the researcher to contact them to request their participation in the research study. Or it may be as challenging as gaining permission from “gatekeepers” who have the right to deny access to the individuals the researcher wants to study — e.g., parents of the children who will be studied, presidents of the professional organizations whose members will be studied, wardens of prisons whose inmates will be studied, etc. The challenge of gaining access from gatekeepers is essentially finding successful strategies that (a) provide guarantees to the gatekeepers that no harm will come to the participants, (b) communicate the worthiness of the research study, and (c) offer some benefit to the gatekeeper or the organization.

Once access to the sampled participants has been granted, the researcher must use strategies to gain cooperation from those who have been chosen. Ideally a very large portion of those who have been sampled will agree to participate. Gaining cooperation is important. This is because, from a Total Quality Framework standpoint, individuals who are chosen to be included in the study but do not participate (e.g., because they refused to cooperate) may differ in important ways from those who do participate, jeopardizing the integrity of the data  which can lower or even undermine the credibility of the qualitative study. If, for example, a disproportionately greater number of males, compared to females, who have been sampled from a list of college freshmen can never be contacted or refuse to participate, and if these sampled males would have provided data that are materially different from the data provided by the other freshmen on the list who did participate in the study, then the research findings will be biased because of the data missing from a major subgroup of the population.

To avoid these problems, qualitative researchers need to utilize strategies meant to overcome the reason(s) that causes some people who are sampled to not cooperate and fail to participate. Such strategies include:

  • Building rapport early with the participants, thereby gaining their trust.
  • Assuring the participants of complete confidentiality.
  • Explaining the non-material benefits to be gained by participating (e.g., helping to raise the quality of life in the neighborhood).
  • Explaining the material benefits, if any, to be gained by participating (e.g., the offer of an Amazon gift card).

Whichever strategies the researchers choose to deploy, ideally they will be tailored (at the individual level) to appeal to the particular types of participants in the sample in order to overcome reluctance or unequivocal refusal during the recruiting process.

A TQF Approach to Construct Validity

TQF approach to construct validity

Construct validity plays an important role in the design, implementation, analysis, and ultimate usefulness of qualitative research methods. The construct of validity itself in qualitative research is discussed in this article and cites qualitative researchers across disciplines who explore “unique dimensions” and other considerations  relating to validity in qualitative research.

The Total Quality Framework (TQF) relies heavily on construct validity in its quality approach to each phase of the qualitative research process. At each phase, the researcher must ask “Am I gaining real knowledge about the core concepts that are the focus of this research?” For example,

  • An important step when developing a research design is to identify the key constructs associated with the research objectives to investigate, and the particular attributes of each construct that the researcher wants to explore. So, for example, a researcher conducting a study on dietary behavior may have interest in “health consciousness,” including shopping behavior related to organic and fresh foods.
  • In the in-depth interview and focus group discussion methods, careful attention needs to be paid to guide development and the inclusion of questions relevant to the constructs of interest. When developing the guide, the researcher needs to ask “Is this [topic, question, technique] relevant to the construct we are investigating?”, and “Does this [topic, question, technique] provide us with knowledge about the aspect of the construct that we intended to explore in the interviews/discussions?”
  • In ethnography, the observation guide and observation grid are important tools. “The grid is similar to the guide in that it helps to remind the observer of the events and issues of most import; however, the observation grid is a spreadsheet or log of sorts that enables the observer to actually record and reflect on observable events in relationship to the research constructs of interest” (Roller & Lavrakas, 2015, p. 206).
  • The quality of qualitative data analysis hinges on the researcher’s ability to effectively identify, analyze, and develop valid interpretations of the data around the important constructs associated with the research objectives. To assist the researcher, a TQF approach to analysis recommends a codebook format and coding form (which is basically a reflexive journal for the coder[s] to record thoughts and justifications for their coding decisions) that highlights constructs of interest. For example,

TQF codebook and coding form

  • Construct validity also plays an important role in the transparency of the final research document. In the study report, the researcher can (and should) elaborate on the design, data gathering, and analysis decisions that were made pertaining to the key constructs, as well as the main themes that were derived from the data — i.e., the knowledge that was gained from the research — concerning these constructs.

Roller, M. R., & Lavrakas, P. J. (2015). Applied qualitative research design: A total quality framework approach. New York: Guilford Press.

 

Photo by Bon Vivant