A simple method to assess and report thematic saturation in qualitative research
Open accessAbstract
Data saturation is the most commonly employed concept for estimating sample sizes in qualitative research. Over the past 20 years, scholars using both empirical research and mathematical/statistical models have made significant contributions to the question: How many qualitative interviews are enough? This body of work has advanced the evidence base for sample size estimation in qualitative inquiry during the design phase of a study, prior to data collection, but it does not provide qualitative researchers with a simple and reliable way to determine the adequacy of sample sizes during and/or after data collection. Using the principle of saturation as a foundation, we describe and validate a simple-to-apply method for assessing and reporting on saturation in the context of inductive thematic analyses. Following a review of the empirical research on data saturation and sample size estimation in qualitative research, we propose an alternative way to evaluate saturation that overcomes the shortcomings and challenges associated with existing methods identified in our review. Our approach includes three primary elements in its calculation and assessment: Base Size, Run Length, and New Information Threshold. We additionally propose a more flexible approach to reporting saturation. To validate our method, we use a bootstrapping technique on three existing thematically coded qualitative datasets generated from in-depth interviews. Results from this analysis indicate the method we propose to assess and report on saturation is feasible and congruent with findings from earlier studies.
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The planned sample sizes are based on empirical results that show that most new information in a data set is obtained in the first five to six interviews, that 92% data saturation occurs after 10 interviews, and that negligible new information is obtained after 20 interviews at the latest.
“The planned sample sizes are based on empirical results that show that most new information in a data set is obtained in the first five to six interviews, that 92 % data saturation occurs after 10 interviews and negligible new information is obtained after 20 interviews at the latest (Guest et al., 2020).”
From TONI - One for all? Participatory development of a transtheoretic and transdiagnostic online intervention for blended care (2024) · cites this paper as Guest et al., 2020
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Experimental — accuracy not yet measuredSaturation occurred when incoming data points contained little to no new useful information in relation to the study objectives.
“Saturation occurred when incoming data points contained little to no new useful information in relation to the study objectives (Guest et al., 2020).”
From Ethical Veganism as the Future of Tourist Consumption (2026) · cites this paper as Guest et al., 2020
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- Authors
- Guest, G., Namey, E., & Chen, M.
- Affiliations
- Family Health International 360 (US)
- Corresponding author
- Namey, Emily
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2020-05-05
- Volume
- 15
- Issue
- 5
- Pages
- e0232076
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC7200005
- OpenAlex
- W3023639742
- Cited by
- 2,929
- References
- 38
- Citations by year
- 2026: 755 · 2025: 691 · 2024: 555 · 2023: 427 · 2022: 325 · 2021: 152 · 2020: 23 · 2017: 1
- FWCI
- 351.24
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Education › Qualitative Research Methods and Applications
- Social Sciences › Sociology and Political Science › Focus Groups and Qualitative Methods
- Social Sciences › Sociology and Political Science › Qualitative Research Methods and Ethics
- Keywords
- data saturation, sample size determination, qualitative research, base size, run length, bootstrapping validation, in-depth interviews
- MeSH terms
- Data Collection, Humans, Research Design, Sample Size, Qualitative Research
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