The Sort and Sift, Think and Shift qualitative data analysis approach is an iterative process where analysts dive into data to understand its content, dimensions, and properties, and then step back to assess what they have learned and to determine next steps. Researchers move from establishing an understanding of what is in the data (“Diving In”) to exploring their relationship to the data (“Stepping Back”). This process of “Diving In” and “Stepping Back” is repeated throughout analysis. To conclude, researchers arrive at an evidence-based meeting point that is a hybrid story of data content and researcher knowledge. To illustrate core tenets of Sort and Sift, Think and Shift, we analyzed three focus group transcripts from a study of postnatal care referral behavior by traditional birth attendants in Nigeria; these transcripts came from Syracuse University’s Qualitative Data Repository and were unfamiliar to the analytic team prior to this exercise. We focused on letting the data be our guide into not only the explicit purpose of the interviews, but also into the unexpected discoveries that arise when inquiring about people’s lived experiences. Situating our efforts within an Initial Learning Period, each member of the team closely read each transcript, and then identified powerful quotations that made us pause and take note. We documented what we learned from each transcript in an episode profile which contained diagrams and memos. Episode profiles were shared and discussed across the team to identify key points of interest, such as the role of faith in women’s decision-making processes related to their pregnancy and delivery preferences, and concepts of who bears what knowledge about reproductive health. Our engagement in this analytic exercise demonstrates the applicability of qualitative inquiry and Sort and Sift as flexible approaches for applied research.


Sort and Sift, Think and Shift, qualitative inquiry, applied research, Qualitative Data Repository

Author Bio(s)

Raymond Maietta, Ph.D., is President of ResearchTalk Inc., a qualitative research consulting and professional development company he founded in 1996. More than 30 years of consultation with qualitative researchers informs Dr. Maietta’s publications and his team’s design of the Sort and Sift, Think and Shift qualitative inquiry approach.

Paul Mihas, M.A., is the Assistant Director of Qualitative Research at the Odum Institute for Research in Social Science at UNC-Chapel Hill and a senior consultant with ResearchTalk Inc. Recent (2019) publications include chapters in the Oxford Encyclopedia of Qualitative Research Methods in Education and Research Design and Methods (SAGE).

Kevin Swartout, Ph.D., is a Professor of Psychology and Public Health at Georgia State University (GSU) and a senior consultant with ResearchTalk Inc. He directs the Violence Against Women Prevention Lab at GSU and conducts research on aggression, violence, and victimization.

Jeff Petruzzelli, B.A., is a Qualitative Research Specialist at ResearchTalk Inc., a qualitative research consulting company. 2021 marks his 20th year at ResearchTalk. He co-teaches professional development workshops and works on a range of qualitative projects, and is a co-designer of the Sort and Sift, Think and Shift qualitative inquiry approach.

Alison Hamilton, Ph.D., M.P.H., is a VA Health Services Research & Development Research Career Scientist, a Professor-in-Residence in the UCLA Department of Psychiatry and Biobehavioral Sciences, and a senior consultant with ResearchTalk Inc. Her work focuses on improving quality and experiences of health care among underrepresented populations. Please direct correspondence to alisonh@ucla.edu.


The authors would like to thank Alexandra Bailey for her contributions to the analytic process. Dr. Hamilton was partially supported by the VA Quality Enhancement Research Initiative (QUERI; QUE 15-272, QUE 20-028), VA Health Services Research & Development (HSR&D; SDR 10-012), and NIH/National Heart, Lung, and Blood Institute (NHLBI; U01HL142109).

Publication Date


Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 International License.





To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.