Verification: Looking Beyond the Data in Qualitative Data Analysis

It is a common misperception among researchers that the analysis of research data is a process that is confined to the data itself. This is probably truer among qualitative researchers than Looking beyondsurvey researchers given that the latter frequently publish their work in the literature comparing and contrasting their data with relevant earlier studies. Qualitative research, on the other hand, is typically held up to less scrutiny; and, except for the usual comparisons of populations segments, it is rare to find an analytical discussion that goes beyond the patterns and themes derived from the qualitative data itself. This may be for any number of reasons. It may be associated with the idea that qualitative research by definition is chock full of uncontrollable variables that vary from study to study making data comparisons across studies unreliable, or it may be researchers’ unfamiliarity with the concept of data verification in qualitative research, or it may be a function of limited resources (i.e., time and research budget), or qualitative researchers may simply be unwilling to expend the extra effort to broaden their analyses.

Yet looking outside the data we gather in in-depth interviews, group discussions, or observations is important to the integrity of our qualitative research designs. The consideration of alternative sources of information serves to verify the study data while giving the researcher a different, more enriched perspective on study outcomes.  It is not important whether this additional input supports the researcher’s conclusions from the primary data; and, indeed, contradictions in the verification process do not necessarily invalidate the study’s findings. What is important, however, is that the researcher recognizes how other points of view can contribute to a more balanced as well as more robust and meaningful analysis rather than relying on study data alone.

There are many proposed approaches to the verification of qualitative research data. Three of the most useful are:

  • Triangulation: The use of multiple sources to contrast and compare study data to establish supporting and/or contradictory information. A few common forms of triangulation are those that compare study data with data obtained from other sources (e.g., comparing the IDI transcripts from interviews with environmental activists with those from conservationists), a different method (e.g., comparing results from an IDI study to focus group results on the same subject matter), and another researcher (e.g., using multiple researchers in the analysis phase to compare interpretations of the data).
  • Negative-case (or “deviant”) analysis: The researcher actively seeks instances in the study data that contradict or otherwise conflict with the prevailing evidence in the data, i.e., looks for outliers. This analysis compels the researcher to develop an understanding about why outliers exist, leading to a greater comprehension as to the strengths and limits of the research data.
  • Reflexive journal: A diary kept by the researcher to provide personal thoughts and insights on what happened during the study. It is an invaluable resource that the researcher can use to review and judge the quality of data collection as well as the soundness of the researcher’s interpretations during the analysis phase. This blog has discussed reflexive journals in many posts, including the most recent article “Reflections from the Field: Questions to Stimulate Reflexivity Among Qualitative Researchers.”

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