Code Saturation Versus Meaning Saturation: How Many Interviews Are Enough?
Open accessAbstract
Saturation is a core guiding principle to determine sample sizes in qualitative research, yet little methodological research exists on parameters that influence saturation. Our study compared two approaches to assessing saturation: code saturation and meaning saturation. We examined sample sizes needed to reach saturation in each approach, what saturation meant, and how to assess saturation. Examining 25 in-depth interviews, we found that code saturation was reached at nine interviews, whereby the range of thematic issues was identified. However, 16 to 24 interviews were needed to reach meaning saturation where we developed a richly textured understanding of issues. Thus, code saturation may indicate when researchers have “heard it all,” but meaning saturation is needed to “understand it all.” We used our results to develop parameters that influence saturation, which may be used to estimate sample sizes for qualitative research proposals or to document in publications the grounds on which saturation was achieved.
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A master codebook was created until meaning saturation was reached.
“A master codebook was created until meaning saturation was achieved.24”
From Mechanisms of mindfulness in patients with migraine: Results of a qualitative study. (2023) · cites this paper as [24]
The Method sections (pages unavailable in our copy) describe creating a codebook and refining it through all 25 interviews. They assess meaning saturation separately for individual codes, rather than saying the codebook was created until meaning saturation was achieved. The Discussion notes that some code dimensions were still emerging at 25 interviews. (LLM, conf=0.87)
Experimental — accuracy not yet measuredSome authors combine two or more models of saturation, making its conceptualization less distinct.
“Some authors appear to espouse interpretations of saturation that combine two or more of the models defined above, making its conceptualization less distinct.”
From Saturation in qualitative research: exploring its conceptualization and operationalization (2018) · cites this paper as Hennink et al. (2017)
The Introduction (‘Challenges in Applying Saturation’; page unavailable) says saturation is used beyond grounded theory and that, without adequate guidance, its meaning becomes unclear. This supports the claim about a less distinct conceptualization, but the paper does not say that authors combine two or more models of saturation. (LLM, conf=0.84)
Experimental — accuracy not yet measuredSaturation is generally reached between 9 and 17 interviews.
“Based on previous studies, saturation is generally reached between 9 and 17 interviews, with 10–15 in-depth interviews planned for this study.54”
From Determinants of the choice of delivery mode in pregnant women: a convergent parallel mixed-methods study protocol (2026) · cites this paper as [54]
The Results (Code Saturation) report code saturation at nine interviews, and the Introduction (Assessing Saturation) describes a prior study that reached overall saturation at 17. But this paper distinguishes code from meaning saturation, reports that meaning saturation required 16–24 interviews, and cautions against treating a particular interview count as a general rule. It therefore does not support the unqualified claim that saturation is generally reached between 9 and 17 interviews. (LLM, conf=0.89)
Experimental — accuracy not yet measuredTwelve to fifteen participants for each qualitative study will be interviewed, which is regarded as adequate to achieve code saturation.
“As for the qualitative studies, twelve to fifteen participants for each study will be interviewed, which is regarded as adequate to achieve code saturation in the qualitative analysis (Hennink et al., 2017).”
From A study protocol of a randomized controlled study of internet-based cognitive behavioral therapy for adult attention deficit hyperactivity disorder (2023) · cites this paper as Hennink et al., 2017
The Results (Code Saturation) report that code saturation was reached after nine interviews in the authors’ data, so 12–15 interviews is consistent with that finding. The Discussion cautions that the sample needed depends on study purpose, population, and the types of codes; it does not establish 12–15 as adequate for each qualitative study. (LLM, conf=0.87)
Experimental — accuracy not yet measuredA sample of N = 20 was aimed for based on general recommendation and experience in the field, with the potential for further recruitment if deemed necessary.
“A sample of N = 20 was aimed for based on general recommendation (Francis et al., 2010; Hennink et al., 2017) and experience in the field with the potential for further recruitment if deemed necessary (e.g. because of low saturation).”
From How to promote usage of telehealth interventions for farmers' mental health? A qualitative study on supporting and hindering aspects for acceptance and satisfaction with a personalized telephone coaching for depression prevention (2023) · cites this paper as Hennink et al., 2017
The Introduction (‘Challenges in Applying Saturation’; page unavailable) says researchers must estimate sample size in advance and that most recommendations are experiential rules of thumb. The Discussion says the sample needed depends on the study and may expand with iterative sampling. These passages support planning a sample with room to recruit further, but not a general recommendation to aim for N = 20. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Meaning saturation was used as a stopping criterion, which meant that new participants would not be enrolled once novel fieldwork insights stopped changing analysis significantly.
“Meaning saturation was used as a stopping criterion, which meant that new participants would not be enrolled once novel fieldwork insights stopped changing analysis significantly [55].”
From Development and Evaluation of the Usefulness, Usability, and Feasibility of iNNOV Breast Cancer: Mixed Methods Study (2022) · cites this paper as [55]
The Results (Meaning Saturation; page unavailable) define meaning saturation as the last interview in which a novel code dimension is identified. The Discussion links it to iterative sampling and deciding whether enough data have been collected. The paper does not define the stopping point by whether new insights change the analysis significantly; its criterion concerns novel dimensions of the issues studied. (LLM, conf=0.83)
Experimental — accuracy not yet measuredThemes derived from only one participant might encompass the theme less comprehensively, diminishing meaning saturation.
“This diminishes meaning saturation since themes derived from only one participant might encompass it less comprehensive (Fusch and Ness, 2015; Hennink et al., 2017).”
Many prior models have been developed to understand the mechanisms of mindfulness, and these are summarized in a review.
“A multitude of prior models have been developed to understand the mechanisms of mindfulness, which are well-summarized in this review.24”
From Mechanisms of mindfulness in patients with migraine: Results of a qualitative study. (2023) · cites this paper as [24]
The Introduction’s Study Aims and the Results sections address saturation in qualitative interviews, not mindfulness. Searches for mindfulness models and reviews of mindfulness mechanisms found no passage in our copy addressing the attributed claim. Page numbers were not available. (LLM, conf=0.78)
Experimental — accuracy not yet measuredData collection was completed when the results generated meanings to understand the phenomena in depth, richness and complexity (data saturation).
“Being a qualitative research, the search and inclusion of participants was completed when the results generated meanings to understand the phenomena in depth, richness and complexity( 14 ).”
From Care opportunities for premature infants: home visits and telephone support (2020) · cites this paper as [14]
The 12 IDIs with girls and the 25 KIIs yielded rich information, consistent with studies reporting on expected information saturation.
“However, the 12 IDIs with girls and the 25 KIIs yielded rich information, which is consistent with studies reporting on expected information saturation [42, 43].”
From Menstrual hygiene management in rural schools of Zambia: a descriptive study of knowledge, experiences and challenges faced by schoolgirls (2019) · cites this paper as [42]
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- Authors
- Hennink, M. M., Kaiser, B. N., & Marconi, V. C.
- Affiliations
- Emory University (US)
- Duke University (US)
- Corresponding author
- Hennink, Monique M.
- Venue
- Qualitative Health Research
- Publisher
- SAGE Publications
- Published
- 2016-09-26
- Volume
- 27
- Issue
- 4
- Pages
- 591-608
- ISSN
- 1049-7323 (ISSN-L)
- 1552-7557
- PMC
- PMC9359070
- OpenAlex
- W2524597629
- Cited by
- 4,597
- References
- 25
- Citations by year
- 2026: 1096 · 2025: 933 · 2024: 700 · 2023: 538 · 2022: 482 · 2021: 379 · 2020: 219 · 2019: 125 · 2018: 92 · 2017: 30 · 2016: 1 · 2013: 1
- FWCI
- 365.33
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Qualitative Health Research (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Emory University
- Center for AIDS Research, University of Washington
- National Institute of Allergy and Infectious Diseases (P30AI050409)
- 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
- saturation, sample size determination, qualitative research, in-depth interviews
- MeSH terms
- Humans, Interviews as Topic, Research Design, Sample Size, Qualitative Research
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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