researcher bias

Paying Attention to Bias in Qualitative Research: A Message to Marketing Researchers (& Clients)

Researchers of all ilk care about bias and how it may creep into their research designs resulting in measurement error.  This is true among quantitative researchers as well as among qualitative researchers who routinely head-in-the-sand-2demonstrate their sensitivity to potential bias in their data by way of building interviewer training, careful recruitment screening, and appropriate modes into their research designs.  It is these types of measures that acknowledge qualitative researchers’ concerns about quality data; and yet, there are many other ways to mitigate bias in qualitative research that are often overlooked.

Marketing researchers (and marketing clients) in particular could benefit from thinking more deeply about bias and measurement error.  In the interest of “faster, cheaper, better” research solutions, marketing researchers often lose sight of quality design issues, not the least of which concern bias and measurement error in the data.  If marketing researchers care enough about mitigating bias to train interviewers/moderators, develop screening questions that effectively target the appropriate participant, and carefully select the suitable mode for the population segment, then it is sensible to adopt broader design standards that more fully embrace the collecting of quality data.

An example of a tool that serves to raise the design standard is the reflexive journal.  The reflexive journal has been the subject (in whole or in part) of many articles in Research Design Review, most notably Read Full Text

Qualitative Data: Achieving Accuracy in the Absence of “Truth”

One of the 10 unique attributes of qualitative research is the “absence of truth.” This refers to the idea that the highly contextual and social constructionist nature of qualitative research renders data that is, not absolute “truth” but, useful knowledge that is the matter of the researcher’s own 10 Unique Attributes of Qualitative Researchsubjective interpretation. For all these reasons – contextuality, social constructionism, and subjectivity – qualitative researchers continually question their data, scrutinize outliers (negative cases), and implement other steps towards verification.

Qualitative researchers also conduct their research in such a way as to maximize the accuracy of the data. Accuracy should not be confused with “truth.” Accuracy in the data refers to gaining information that comes as close as possible to what the research participant is thinking or experiencing at any moment in time. This information may be the product of any number of contextual (situational) and co-constructed factors – i.e., the absence of “truth” – yet an accurate account of a participant’s stance on a given issue or topic.

It is accuracy that qualitative researchers strive for when they craft their research designs to mitigate bias and inconsistency. For example, focus group moderators are trained to give equal attention to their group participants – allowing everyone an opportunity to communicate their thoughts – rather than bias the data – i.e., leading to inaccurate information – by favoring more attention on some participants than on others. A trained moderator is also skilled at listening for inconsistencies or contradictions throughout a discussion in order to follow up on each participant’s comments, asking Read Full Text

Seeing Without Knowing: Potential Bias in Mobile Research

Mobile research – specifically, research by way of smartphone technology – has become a widely used and accepted design option for conducting qualitative and survey research.  The advantages of the mobile mode are many, not the least of which thought-bubbleare: the high incidence of smartphone ownership in the U.S. (more than 60% in 2015), the ubiquitous influence smartphones have on our lives, the dependence people have on their smartphones as their go-to channel for communicating and socializing, and the features of the smartphone that offer a variety of response formats (e.g., text, video, image) and location-specific (e.g., geo-targeting, geo-fencing) capabilities.

From a research design perspective, there are also several limitations to the mobile mode, including: the small screen of the smartphone (making the design of standard scale and matrix questionnaire items – as well as the user experience overall – problematic), the relatively short attention span of the respondent or participant precipitated by frequent interruptions, the potential for errors due to the touch screen technology, and connectivity issues.

Another important yet often overlooked concern with mobile research is the potential for bias associated with the smartphone response format and location features mentioned earlier.  Researchers have been quick to embrace the ability to capture video and photographs as well as location information yet they have not universally exercised caution when integrating these features into their research designs.  For example, a recent webinar in which a qualitative researcher presented the virtues of mobile qualitative research – esp., for documenting in-the-moment experiences – espoused the advantages of Read Full Text