Qualitative Analysis in Health Promotion Research: Extracting Meaning Using NUD*IST and NVivo

This presentation demonstrates the evolution of qualitative analysis in one academic department as use of NUD*IST software increased. Most of the research conducted in the department is funded by federal grants, and thus is very focused on answering specific research questions regarding health behavior and health-related decision making in a short time frame (often less than 12 months from project start-up to project final report). While methodologies commonly used in a grounded theory approach are utilized, the research usually is based on one of a number of theories of health behavior (Social Cognitive Theory, Theory of Planned Behavior, Theory of Reasoned Action, Social Ecological Model, etc.) rather than grounded theory. Thus the researcher undertakes analysis of the focus group transcripts or interviews looking for answers to the research questions and approaches coding initially from the perspective of the theory in use in the study. Using examples from studies of women’s health-related decisions at mid-life, barriers and enablers of women’s participation in physical activity, evaluation of a capacitybuilding intervention, and women’s analysis of HIV risk in sexual relationships, this presentation will examine how the extraction of meaning from data changed as the research teams moved from N4 to NVivo 2. Initially (N4) data were coded at appropriate nodes using the software, but extraction of meaning from the data was regarded as a manual (and quite time-consuming!) process. In the more recent studies, the NVivo Assay tool was used extensively to guide the investigation of specific relationships in the data, making the extraction of meaning from the transcripts much more efficient. In addition, the value of the Attributes in both N6 and NVivo has been more fully explored and has changed the approach to transcription from distinguishing only between moderator and participant in focus groups to identifying each speaker and using the Case function in NVivo to track each participant’s contributions to the discussion. Though evolving, the research teams have not yet utilized the Merge program in NVivo and reasons for this reluctance will be discussed. Actual examples from these projects showing the evolution of our qualitative analysis will be shared in this presentation.