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

Unique attributes of qualitative research-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 for clarification, and ultimately coming away with an accurate “picture” of that participant in relationship to the topic as communicated in that particular space and time.

This pursuit of accuracy is no less evident in the in-depth interview (IDI) method. By attending to the potential for interviewer bias – from question wording, imposing personal beliefs or values into the conversation, physical appearance in face-to-face IDIs – as well as the seemingly contradictory statements made by interviewees, the qualitative researcher is focused on securing an accurate portrayal of how that participant thinks and behaves in association with the research objective. It is not uncommon, for instance, for an IDI participant to state one thing at the beginning of an interview but to make one or more outwardly conflicting statements later in the interview. Why is that? Which statement is accurate? Do the statements really contradict each other? What more does the interviewer need to learn about the interviewee? These are the questions the interviewer must address throughout the IDI in the quest for accurate data.

Achieving accuracy in the data collection process is, like all aspects of qualitative research, a nuanced and often difficult mission. It is, however, a mission worth pursuing because, unlike absolute “truth,” it is an obtainable and necessary ingredient to deriving outcomes that enable consumers of the research to actually do something meaningful with the findings.


  1. I think I disagree. To me qualitative research is relative to the interpretations the researcher makes from the data collected. I agree that qualitative research does not provide absolute truth regarding the meaningfulness of data. Rather, it depends on the way the negotiated nature of others coming to agreement that the interpretations rendered and the reasoning offered resonates credibility. There is always a community of practice that qualitative research must engage in order to maintain credibility. We cannot subjectively define data as credible. The process is relative to a community of practitioners.


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