It is easy to fall into the trap of relying on the “why” question when conducting qualitative research. After all, the use of qualitative research is often supported with the claim that qualitative methods enable the researcher to reach beyond quantitative numerical data to grasp the meaning and motivations – that is, the why – associated with particular attitudes and behavior. And it is in this spirit that researchers frequently find themselves with interview and discussion guides full of “why” questions – Why do you say you are happy? Why do you prefer one political candidate over another? Why do you diet? Why do you believe in God? Why do you use a tablet rather than a laptop computer?
Yet “why” is rarely the question worth asking. In fact, asking “why” questions can actually have a negative effect on data collection (i.e., Credibility) and contribute bias to qualitative data. This happens for many reasons, here are just four:
The “why” question potentially
• Evokes rationality. By asking the “why” question, researchers are in essence asking participants to justify their attitudes and behavior. In contemplating a justification, it is not unusual for participants to seek Read Full Text
The Total Quality Framework (TQF) (Roller & Lavrakas, 2015) offers researchers a way to think about qualitative research design from the vantage point of core principles. It is an approach that helps qualitative researchers develop critical thinking skills by giving explicit attention to the quality of the conceptualization and implementation of their qualitative studies. The TQF is composed of four components, each pertaining to a phase of the research process – data collection (Credibility), analysis (Analyzability), reporting (Transparency), and the ability to do something of value with the outcomes (Usefulness).
Qualitative research is most often conducted as a standalone study but frequently conducted in conjunction with quantitative methods. A mixed methods research (MMR) design involves collecting both qualitative and quantitative data, then integrating or connecting the two datasets to draw interpretations derived from the combined strengths of both sets of data (Creswell, 2015). The integration of, or making the connection between, the qualitative and quantitative components is fundamental to MMR and distinguishes it from a multi-method approach that simply utilizes different methods. In contrast, a mixed methods design incorporates any number of qualitative and quantitative methods (and modes) with the specific intention of blending the data in some fashion. Mixed methods research is the subject of an earlier article in Research Design Review.
So, how do we apply the TQF to a MMR design? It is not good enough to simply think of the qualitative component Read Full Text
Our research is of little value if the outcomes are not deemed useful in some way. This is true for all types of research. Whether it is qualitative, quantitative, or a mixed methods approach, the “carrot” that dangles ahead of the research team is the promise of reaching worthwhile, actionable conclusions and recommendations for the users and sponsors of the research. Achieving this objective – reaching the “carrot” of useful research – is the product of the quality measures put into place at the data collection, analysis, and reporting phases of the research design.
The Total Quality Framework (TQF)* offers a way of thinking about these quality measures in a qualitative research design. The TQF is comprised of four inter-related components, each having to do with a stage of the research process. Recent articles in Research Design Review have discussed three of these components – Credibility pertaining to data collection, Analyzability having to do with the processing and verification of qualitative data, and Transparency relating to the reporting of details associated with data collection, analysis, and the drawing of interpretations.
The fourth component of the TQF is Usefulness or the “ability to do something of value with the outcomes.” The ultimate strength of the Usefulness component is a function of the vigor – the attention to quality – within the Credibility (data collection), Analyzability (analysis), and Transparency (reporting) components. In this way, the Usefulness component relies on each of the other components independently as well as collectively. The goal is to maximize the value of a qualitative research study for Read Full Text