Credibility

Research Integrity & a Total Quality Framework Approach to Qualitative Data Sharing

The September 2021 issue of Monitor on Psychology from the American Psychological Association includes an article “Leading the Charge to Address Research Misconduct” by Stephanie Pappas. The article discusses the various Qualitative data sharingcircumstances or “pressures” that may lead researchers towards weak research practices that result in anything from “honest” mistakes or errors (e.g., due to insufficient training or oversight) to deliberate “outright misconduct” (e.g., falsifying data, dropping outliers from the analysis and reporting). The article goes on to talk about what psychologists are doing to tackle the problem.

One of those psychologists is James DuBois, DSc, PhD at Washington University School of Medicine. Dr. DuBois and his colleague Alison Antes PhD direct the P.I. (professionalism and integrity in research) Program at Washington University. This program offers one-on-one coaching to researchers who are challenged by the demands of balancing scientific and compliance requirements, as well as researchers who have (or have staff who have) been investigated for noncompliance or misconduct. The P.I. Program also conducts an On the Road Workshop which is an onsite session for researchers “doing empirical research in funded research environments” covering such areas as decision-making strategies, effective communication, and professional growth goals.

Another approach to the problem of misconduct and the goal of research integrity is transparency by way of sharing data (and other elements of design), allowing other researchers the opportunity to examine research practices and substantiate the reported results. Dr. DuBois and his co-authors discuss this and other advantages to sharing qualitative data in their 2018 article “Is It Time to Share Qualitative Research Data?” The authors assert that allowing other researchers to assess supporting evidence and “comprehensiveness by examining our data may improve the quality of research by enabling correction and increasing attention to detail” (p. 384).

In response to DuBois et al., Roller and Lavrakas (2018) published a commentary expressing Read Full Text

Elevating Qualitative Design to Maximize Research Integrity

The following is a modified excerpt from Applied Qualitative Research Design: A Total Quality Framework Approach (Roller & Lavrakas, 2015, pp. 9-10).

All research that is aimed at understanding how people think and behave requires a principled approach to research design that is likely to maximize data quality and to instill users’ confidence in the research outcomes. This is no less so in qualitative than it is in quantitative research; and, in fact, the distinctive attributes and underlying complexities in qualitative research necessitate a quality approach to qualitative research design. This approach requires qualitative researchers to build certain principles into their research studies by way of incorporating and practicing fundamental research standards.

Total Quality FrameworkTo that end, the Total Quality Framework (TQF) was devised to provide a basis by which researchers can develop critical thinking skills necessary to the execution of qualitative designs that maximize the integrity of the research outcomes. This framework is not intended to prescribe a formula or specific procedure by which qualitative researchers should conduct qualitative inquiry. Rather, the TQF provides researchers with a flexible way to focus on quality issues, examine the sources of variability and possible bias in their qualitative methods, and incorporate features into their designs that mitigate these effects and maximize quality outcomes. Integral to the TQF is the idea that all qualitative research must be Credible, Analyzable, Transparent, and Useful. These four components are fundamental to the TQF and its ability to help researchers identify the strengths and limitations of their qualitative methods while also guiding them in the qualitative research design process.

By holding the quality of qualitative research design to a deep level of scrutiny when applied across the diverse, multidisciplinary fields utilizing qualitative methods — e.g., education; psychology; anthropology; sociology; nursing, public health, and medicine; communication; information management; business; geography and environmental science; and program evaluation — the discussion of qualitative research is significantly elevated and enables students, faculty, and practitioners to design and interpret qualitative research studies based on the quality standards that are the hallmark of the TQF.

 

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

The TQF Qualitative Research Proposal: Credibility of Design

A Total Quality Framework (TQF) approach to the qualitative research proposal has been discussed in articles posted elsewhere in Research Design Review, notably “A Quality Approach to the Qualitative Research Proposal” (2015) and “Writing Ethics Into Your Qualitative Proposal” (2018). The article presented here focuses on the Research Design section of the TQF proposal and, specifically, the Credibility component of the TQF. The Credibility component has to do with Scope and Data Gathering. This is a modified excerpt from Applied Qualitative Research Design: A Total Quality Framework Approach (Roller & Lavrakas, 2015, pp. 339-340).

TQF Proposal Image-DesignScope

A TQF research proposal clearly defines the target population for the proposed research, the target sample (if the researcher is interested in a particular subgroup of the target population, e.g., only African American and Hispanic high school seniors in the district who anticipate graduating in the coming spring), how participants will be selected for the study, what they will be asked to do (e.g., set aside school time for an in-depth interview [IDI]), and the general types of questions to which they will be asked to respond (i.e., the content areas of the interview). In discussing Scope, the researcher proposing an IDI study with African American and Hispanic high school students would identify the list that will be used to select participants (e.g., the district’s roster of seniors who are expected to graduate); the advantages and drawbacks to using this list (e.g., not everyone on the roster may consider themselves to be African American or Hispanic); the systematic (preferably random) procedure that will be used to select the sample; and the number of students that will be selected as participants, including the rationale for that number and the steps that will be taken to gain cooperation from the students and thereby ideally ensure that everyone selected actually completes an interview (e.g., gaining permission from the school principal to allow students to take school time to participate in the IDI, and from parents/guardians for students under 18 years of age who cannot give informed consent on their own behalf).

Data Gathering

The data-gathering portion of the Research Design section of the proposal highlights the constructs and issues that will be examined in the proposed research. This discussion should provide details of the types of questions that will be asked, observations that will be recorded, or areas of interest Read Full Text