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.


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Shared Constructs in Research Design

Shared constructs

In 2021, a three-part series appeared in Research Design Review concerning three shared constructs in quantitative and qualitative research design — sampling, bias, and validity. Although quantitative and qualitative research, and the respective research designs, are distinct from each other in many ways, there are commonalities across research methodologies that cannot be ignored in quality research design. These commonalities include fundamental constructs that further a principled approach to research design, such as the notion of sampling, bias, and validity.

The three articles posted in 2021 devoted to these shared constructs — Part 1-Sampling, Part 2-Bias, and Part 3-Validity — have been compiled into this single document “Shared Constructs in Research Design,” available for download.

Shared Constructs in Research Design: Part 3 — Validity

validity in research designNot unlike Part 1 (concerning sampling) and Part 2 (concerning bias) of the discussion that began earlier, the shared construct of validity in research design has also been an area of focus in several articles posted in Research Design Review. Most notable is “Quality Frameworks in Qualitative Research” posted in February 2021 in which validity is discussed within the context of the parameters or strategies various researchers use to define and think about the dimensions of rigor in qualitative research design. This article uses the Total Quality Framework (Roller & Lavrakas, 2015) and criteria of Lincoln and Guba (1985) to underscore the idea that quality approaches to design cuts across paradigm orientation, leading to robust and valid interpretations of the data.

Many other qualitative researchers, across disciplines, believe in the critical role that the shared construct of validity plays in research design. Joseph Maxwell, for example, discusses validity in association with his realism approach to causal explanation in qualitative research (Maxwell, 2004); and discusses in detail five unique dimensions of validity, including descriptive validity, interpretative validity, theoretical validity, evaluative validity, and generalizability (Maxwell, 1992). And of course, Miles & Huberman were promoting greater rigor by way of validity more than three decades ago (Miles & Huberman, 1984).

More recently, Koro-Ljungberg (2010) takes an in-depth look at validity in qualitative research and, with extensive literature as the backdrop, makes the case that “validity is in doing, as well as its (un)making, and it exhibits itself in the present paradox of knowing and unknowing, indecision, and border crossing” (p. 609). Matteson & Lincoln (2008) remind educational researchers that validity does not solely concern the analysis phase of research design but “the data collection method must also address validity” (p. 672). Creswell & Miller (2000) discuss different approaches to determine validity across three paradigm orientations — postpositivist, constructivist, and critical — and “lens” of the researcher, participants, and researchers external to the study.

Among qualitative health researchers, Morse (2020) emphasizes the potential weakness in validity when confusing the analysis of interpretative inquiry with that associated with “hard, descriptive data” (p. 4), and Morse et al. (2002) present five verification strategies and argue that validity (as well as reliability) is an “overarching” construct that “can be appropriately used in all scientific paradigms” (p. 19).

These researchers, and those discussed in Part 1 – Sampling and Part 2 – Bias, are admittedly a small share of those who have devoted a great deal of thought and writing concerning these shared constructs. The reader is encouraged to utilize these references to build on their understanding of these constructs in qualitative research and to grow their own library of knowledge.


Creswell, J. W., & Miller, D. L. (2000). Determining validity in qualitative inquiry. Theory into Practice, 39(3), 124–130.

Koro-Ljungberg, M. (2010). Validity, responsibility, and aporia. Qualitative Inquiry, 16(8), 603–610.

Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Beverly Hills, CA: Sage Publications.

Matteson, S. M., & Lincoln, Y. S. (2008). Using multiple interviewers in qualitative research studies: The influence of ethic of care behaviors in research interview settings. Qualitative Inquiry, 15(4), 659–674. Retrieved from

Maxwell, J. A. (1992). Understanding and validity in qualitative research. Harvard Educational Review, 62(3), 279–300.

Maxwell, J. A. (2004). Casual explanation, qualitative research, and scientific inquiry in education. Educational Researcher, 33(2), 3–11.

Miles, M. B., & Huberman, A. M. (1984). Drawing valid meaning from qualitative data: Toward a shared craft. Educational Researcher, 13(5), 20–30.

Morse, J. (2020). The changing face of qualitative inquiry. International Journal for Qualitative Methods, 19, 1–7.

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.