accuracy vs. “truth”

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 subjective 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 attitude or experience on a given issue or topic at a particular moment.

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