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Abstract

Qualitative content analysis (QCA) is a flexible method of analysis, applicable within many epistemologies and on many kinds of data. This makes it suitable as a general introduction to qualitative methods, but students and other beginners sometimes have trouble grasping the associated concepts and ways of thinking. To facilitate their first foray into this new territory, we propose a five-step process of QCA that does not presuppose any foreknowledge of concepts such as levels of abstraction or what coding and categorizing can look like in practice. In our step-by-step guide, we also depart from some staples of QCA, such as likening codes to labels and accepting topic summaries as categories, since this may hamper rather than help beginners’ understanding of the underlying principles. After a concrete how-to section, we offer a brief comparison between QCA and reflexive thematic analysis. To further the pedagogic uses of the article, we also discuss the philosophical underpinnings of the method, focusing on how to handle potential problems of establishing common ground, utterances that contain several ideas, speech acts, and contextuality.

Keywords

qualitative content analysis, how-to, qualitative research methods, teaching qualitative research

Author Bio(s)

Ingela Bohm is a senior lecturer at the Department of Food, Nutrition and Culinary Science at Umeå University, Sweden. Her research interests include home economics, cooking, food sociology, and food culture. ORCiD: 0000-0002-9898-7055. Please direct correspondence to ingela.bohm@umu.se

Joachim Sundqvist is a senior lecturer at the Department of Food, Nutrition and Culinary Science at Umeå University, Sweden. His research interests pertain to the intersection of social theory, philosophy, and practice within the context of consumers’ meal experiences. ORCiD: 0000-0002-8179-4628 Please direct correspondence to joachim.sundqvist@umu.se

Acknowledgements

We wish to thank our colleagues at the Department of Food, Nutrition, and Culinary Science for reading and providing valuable feedback on the first draft of the article.

Publication Date

9-22-2025

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.

DOI

10.46743/2160-3715/2025.7211

ORCID ID

0000-0002-9898-7055

ResearcherID

0000-0002-8179-4628

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