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
The Total Quality Framework (TQF)* contributes to the conversation in the qualitative research community by providing researchers with a way to think about their qualitative designs – along with strategies or techniques – for the purpose of enhancing the quality of research outcomes. The TQF is a comprehensive approach that considers all stages of the research process – from data collection to the final “product.” Recent articles in Research Design Review discussed two of the four components of the TQF – specifically, the Credibility component and the Analyzability component. The Credibility component pertains to data collection and consists of Scope (having to do with sampling and coverage) and Data Gathering (having to do with minimizing potential bias, nonresponse, and other factors that may weaken the validity of the data). The Analyzability component of the TQF is focused on the Processing of qualitative data (e.g., the quality by which the initial “raw” data is transformed) as well as Verification of research findings and interpretations (e.g., by way of deviant cases, peer debriefs, the reflexive journal).
The third component of the TQF has to do with the next phase in a qualitative research design – that is, reporting. When the data has been collected and thoroughly processed and verified, the qualitative researcher Read Full Text
A March 2017 article in Research Design Review discussed the Credibility component of the Total Quality Framework (TQF). As stated in the March article, the TQF “offers qualitative researchers a way to think about the quality of their research designs across qualitative methods and irrespective of any particular paradigm or theoretical orientation” and revolves around the four phases of the qualitative research process – data collection, analysis, reporting, and doing something of value with the outcomes (i.e., usefulness). The Credibility piece of the TQF has to do with data collection. The main elements of Credibility are Scope and Data Gathering – i.e., how well the study is inclusive of the population of interest (Scope) and how well the data collected accurately represent the constructs the study set out to investigate (Data Gathering).
The present article briefly describes the second TQF component – Analyzability. Analyzability is concerned with the “completeness and accuracy of the analysis and interpretations” of the qualitative data derived in data collection and consists of two key parts – Processing and Verification. Processing involves the careful consideration of: Read Full Text