Shared Constructs in Research Design: Part 2 — Bias

Part 1 of the discussion of shared constructs — “Shared Constructs in Research Design: Part 1 – Sampling” — acknowledges the distinctiveness between quantitative and qualitative research while Research biashighlighting the notion that there are fundamental constructs common to a quality approach to research design regardless of method or, in the case of qualitative research, paradigm orientation. Three such constructs are sampling, bias, and validity. Part 1 of this discussion focused on sampling (prefaced by a consideration of paradigms in qualitative research and the importance of quality research design regardless of orientation). This article (Part 2) discusses bias.

Bias in qualitative research design has been the topic of a number of articles in Research Design Review over the years. One of these articles is a broad discussion on paying attention to bias in qualitative research and another explores social desirability bias in online research. An article written in 2014 examines the role of empathy in qualitative research and its potential for enhancing clarity while reducing the bias in qualitative data, and another article in RDR talks about visual cues and the importance of visual cues in mitigating sources of bias in qualitative research. Other articles concerning bias in RDR are specific to methods. For example, a couple of articles discuss mitigating interviewer bias in the in-depth interview method — “In-depth Interviewer Effects: Mitigating Interviewer Bias” and “Interviewer Bias & Reflexivity in Qualitative Research” — while another article focuses on ethnography and mitigating observer bias, and a fourth article considers the potential bias in mobile (smartphone) qualitative research.

Others in the field of psychology have discussed various aspects of bias in qualitative research. For example, Linda Finlay (2002) discusses the value of reflexivity as a tool to, among other things, “open up unconscious motivations and implicit biases in the researcher’s approach” (p. 225). Ponterotto (2005) looks at the varying role and understanding of bias across paradigm orientations in qualitative research among the postpositivists, constructivist–interpretivist researchers, and critical–ideological researchers. In psychiatry, Whitley & Crawford (2005) suggest ways to mitigate investigator bias and thereby increase the rigor in qualitative studies. Morrow (2005) asserts that “all research is subject to researcher bias” and highlights the subjectivity inherent in qualitative research and explores bracketing and reflexivity as a means of “making one’s implicit assumptions and biases overt to self and others” (p. 254). And researcher bias is central to the Credibility component of the Total Quality Framework (Roller & Lavrakas, 2015).

Social scientists such as Williams & Heikes (1993) examine the impact of interviewer gender on social desirability bias in qualitative research; while Armour, Rivaux, and Bell (2009) discuss researcher bias within the context of analysis and interpretation of two phenomenological studies. In a recent paper, Howlett (2021) reflects on the transition to online technical research solutions and the associated methodological considerations, such as the negative impact of selection bias due to weak recruitment and engagement strategies.

Among healthcare researchers, Arcury & Quandt (1999) discuss recruitment with a focus on sampling and the use of gatekeepers, with an emphasis on the potential for selection bias which they monitored by way of reviewing “the type of clients being referred to us, relative to the composition of the site clientele” (p. 131). Whittemore, Chase, & Mandle (2001) define quality in qualitative research by way of validity standards, including investigator bias — “…a phenomenological investigation will need to address investigator bias (explicitness) and an emic perspective (vividness) as well as explicate a very specific phenomenon in depth (thoroughness)” (p. 529). And Morse (2015), who is a pioneer in qualitative health research and has written extensively on issues of quality in qualitative research design, highlights the mitigation of researcher bias as central to the validity of qualitative design, offering “the correction of researcher bias” as one recommended strategy for “establishing rigor in qualitative inquiry” (p. 33).

Another shared and much discussed construct among qualitative researchers — validity — is the focus of Part 3 in this discussion.

Arcury, T. A., & Quandt, S. A. (1999). Participant recruitment for qualitative research: A site-based approach to community research in complex societies. Human Organization, 58(2), 128–133. Retrieved from

Armour, M., Rivaux, S. L., & Bell, H. (2009). Using context to build rigor: Application to two hermeneutic phenomenological studies. Qualitative Social Work, 8(1), 101–122.

Finlay, L. (2002). Negotiating the swamp: The opportunity and challenge of reflexivity in research practice. Qualitative Research, 2(2), 209–230. Retrieved from

Howlett, M. (2021). Looking at the ‘field’ through a Zoom lens: Methodological reflections on conducting online research during a global pandemic. Qualitative Research, 146879412098569.

Morrow, S. L. (2005). Quality and trustworthiness in qualitative research in counseling psychology. Journal of Counseling Psychology, 52(2), 250–260.

Morse, J. M. (2015). Critical analysis of strategies for determining rigor in qualitative inquiry. Qualitative Health Research, 25(9), 1212–1222.

Ponterotto, J. G. (2005). Qualitative research in counseling psychology: A primer on research paradigms and philosophy of science. Journal of Counseling Psychology, 52(2), 126–136.

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

Whitley, R., & Crawford, M. (2005). Qualitative research in psychiatry. Canadian Journal of Psychiatry, 50(2), 108–114. Retrieved from

Whittemore, R., Chase, S. K., & Mandle, C. L. (2001). Validity in qualitative research. Qualitative Health Research, 11(4), 522–537. Retrieved from

Williams, C. L., & Heikes, E. J. (1993). The importance of researcher’s gender in the in-depth interview: Evidence from two case studies of male nurses. Gender and Society, 7(2), 280–291.

Shared Constructs in Research Design: Part 1 — Sampling

Shared constructs: SamplingQuantitative and qualitative research (raison d’etre) and research designs are distinct from each other in many ways and, indeed, much has been written in Research Design Review on the unique attributes of qualitative research. There are, however, commonalities across research methods 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 idea of linking, what many may consider, quantitative concepts with qualitative research may be disconcerting to some who approach qualitative research from a particular stance or paradigm orientation, or believe that quantitative jargon and ideas have no place in qualitative methods. And yet, as stated in “The Transcendence of Quality Over Paradigms in Qualitative Research,”

As important as a theoretical or philosophical orientation may be to serving as the foundation to a qualitative research effort, it need not be tied to the quality measures the researcher utilizes in the actual doing of the research. 

Meaning that a quality approach to design is critical regardless of paradigm orientation, as reinforced in “Distinguishing Qualitative Research Methods from Paradigm Orientation,”

If, philosophically, the goodness of qualitative research is of ultimate concern, and if it is agreed that qualitative research can, in fact, serve worthwhile (i.e., “good”) purposes, then logically it would serve those purposes only to the degree that it is done well, regardless of the specific objectives [or paradigm orientation] that qualitative researchers are striving to address.

A specific example is given in “Social Contructionism & Quality in Qualitative Research Design” which states in part,

Quality considerations walk hand-in-hand with social constructionism (and many theoretical and philosophical orientations), you might even say that they need each other. A quality approach is driven by the researcher’s understanding and utilization of the socially-constructed world (e.g., use of language, the imbalance of power) while the social constructionist ultimately requires research outcomes that are useful.

In the spirit of embracing varying degrees of worldviews associated with qualitative research along with a quality approach to qualitative research design, researchers can turn their attention to fundamental constructs such as sampling. In the field of psychology, researchers such as Robinson (2014) have proposed a four-point “pan-paradigmatic” sampling framework, and Morrow (2005) emphasizes the idea that “purposeful sampling is used to produce information-rich cases, and a combination of sampling strategies may be used to achieve this purpose.” Braun and Clarke (2019) have their “own rules of thumb and make pragmatic decisions around sampling” with attention to sample size, “recognising that sample size alone is not the only factor at play. Getting different stories can require sampling more widely” (p. 11). And O’Reilly and Parker (2013) link quality to sampling, stating that the “defensibility of the quality of qualitative research, to a considerable extent, relates to sampling adequacy” (p.2).

Sampling is central to qualitative design among other social scientists — such as Adler & Adler (2012) who discuss “theoretical sampling, where researchers purposely seek to interview participants who occupy particular niches in their analysis” (p. 9), and Roller & Lavrakas (2015) who have made sampling a main feature of the Total Quality Framework Credibility component — and researchers in the health sciences. Morse (1991, 2000, 2015, 2020) is widely considered the champion of qualitative health research. Back in 1991, Morse argued for greater attention to sampling in qualitative research, emphasizing the need for closer examination of “the principles of sampling in qualitative research and to consider threats to validity and special problems that occur when making sampling decisions” (p. 129). Fast forward nearly 30 years and Morse continues her discussion of sampling strategies, stating “Sampling is…a strategy that must be approached carefully in light of many factors unique to your [qualitative] project, along with anticipating the ramifications of your sampling decision for the entire project” (2020, p. 5).

Another shared construct — bias — is the focus of Part 2 in this discussion.

Adler, P., & Adler P. (2012). In Baker, S., & Edwards, R. (Eds.), How many qualitative interviews is enough?: Expert voices and early career reflections on sampling and cases in qualitative research (pp. 8-11).  National Centre for Research Methods Review Paper.

Braun, V., & Clarke, V. (2019). To saturate or not to saturate? Questioning data saturation as a useful concept for thematic analysis and sample-size rationales. Qualitative Research in Sport, Exercise and Health, 00(00), 1–16.

Morrow, S. L. (2005). Quality and trustworthiness in qualitative research in counseling psychology. Journal of Counseling Psychology, 52(2), 250–260.

Morse, J. M. (1991). Strategies for sampling. In Morse, J. M. (Ed.), Qualitative nursing research: A contemporary dialogue (pp. 127-145). SAGE Publications, Inc.

Morse, J. M. (2000). Determining sample size. Qualitative Health Research, 10(1), 3–5.

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.

Morse, J. M. (2015). Critical analysis of strategies for determining rigor in qualitative inquiry. Qualitative Health Research, 25(9), 1212–1222.

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

O’Reilly, M., & Parker, N. (2013). “Unsatisfactory saturation”: A critical exploration of the notion of saturated sample sizes in qualitative research. Qualitative Research, 13(2), 190–197.

Robinson, O. C. (2014). Sampling in interview-based qualitative research : A theoretical and practical guide. Qualitative Research in Psychology, 11(1), 25–41.

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

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In-depth Interviewer Effects: Mitigating Interviewer Bias

The following is a modified excerpt from Applied Qualitative Research Design: A Total Quality Framework Approach (Roller & Lavrakas, 2015, pp. 83-84).

The outcome of a qualitative in-depth interview (IDI) study, regardless of mode, is greatly affected by the interviewer’s conscious or unconscious influence within the context of the IDIs—that is, the absence or presence of interviewer bias. The interviewer’s Interviewer Effects-Biasdemographic characteristics (e.g., age, race), physical appearance in face-to-face IDIs (e.g., manner of dress), voice in face-to-face and telephone IDIs (e.g., a regional accent), and personal values or presumptions are all potential triggers that may elicit false or inaccurate responses from interviewees. For example, imagine that an IDI study is being conducted with a group of public school teachers who are known to harbor negative feelings toward the district’s superintendent but who express ambivalent attitudes in the interviews as the result of the interviewers’ inappropriate interjection of their own personal positive opinions. In this way, the interviewers have caused the findings to be biased. In order to minimize this potential source of distortion in the data, the researcher can incorporate a number of quality enhancement measures into the IDI study design and interview protocol:

  • The IDI researcher should conduct a pretest phase during which each interviewer practices the interview and learns to anticipate what Sands and Krumer-Nevo (2006) call “master narratives” (i.e., the interviewer’s own predispositions) as well as “shocks” that may emerge from interviewees’ responses. Such an awareness of one’s own predispositions as an interviewer and possible responses from interviewees that might otherwise “jolt” the interviewer will more likely facilitate an uninterrupted interview that can smoothly diverge into other appropriate lines of questioning when the time presents itself. In this manner, the interviewer can build and maintain strong rapport with the interviewee as well as anticipate areas within the interview that might bias the outcome.

For example, Sands and Krumer-Nevo (2006) relate the story of a particular interview in a study among youth who, prior to the study, had been involved in drug use and other criminal behavior. Yami, the interviewer, approached one of the interviews with certain assumptions concerning the interviewee’s educational background and, specifically, the idea that a low-level education most likely contributed to the youth’s illicit activities. Because of these stereotypical expectations, Yami entered the interview with the goal of linking the interviewee’s “past school failures” to his current behavior and was not prepared for a line of questioning that was not aimed at making this connection. As a result Read Full Text