Cited by 560Qualitative Research Methods and ApplicationsQualitative Research Methods and EthicsFocus Groups and Qualitative Methods

Saturation in qualitative research: an evolutionary concept analysis

Open access
Rahimi, Sara, khatooni, Marzieh·2024·International Journal of Nursing Studies Advances

Abstract

Background and Aim: Qualitative research plays an important role in improving nursing knowledge. Understanding the concept of saturation is essential to conducting rigorous qualitative research that contributes to evidence-based practice. The purpose of this study is to clarify the concept of saturation in qualitative research. Method: Evolutionary concept analysis was performed. A literature search was conducted using a variety of online databases for the years 2005- 2023. In total, 33 articles and books were analyzed using thematic analysis to identify the attributes, antecedents and consequences of saturation. The validity of the data was obtained by examining the analysis process by two independent researchers. Results: Saturation in qualitative research is a context-dependent, subjective process that requires detailed systematic analysis. Saturation is used in four ways in qualitative research: theoretical saturation, data saturation, code or thematic saturation, and meaning saturation. The antecedents of saturation were classified into two categories: study related factors and researcher related factors. The consequences of saturation were identified as: ensuring credibility and quality in qualitative research and time, energy and budget saving. Conclusion: This concept analysis serves to enhance the understanding of the concept of saturation, thereby offering valuable resources for qualitative researchers. By gaining a profound comprehension of saturation and its various types, researchers can ensure the validity of their studies while also optimizing time and resource allocation by avoiding redundant data collection. Future investigation warranted to elucidate how factors associated with reaching saturation impact estimations sample size.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.ijnsa.2024.100174

Cites

34 of 34 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The number of participating services was determined by theoretical saturation from qualitative analyses, with data collection concluded when information became redundant or repeated.

    “The number of participating services in the research was determined by theoretical saturation from the qualitative analyses (25) in which the data collection was concluded when the information started to become redundant or repeated, even with the inclusion of new participants and services, as detected through a floating reading of the transcripts of the conducted interviews and fields diaries.”

    From A mindfulness-based intervention for Substance Use Disorder in a Brazilian vulnerable population: a feasibility mixed method study (2024) · cites this paper as [25]

    The Results and Discussion section on theoretical saturation describes using iterative sampling and analysis until further data add no theoretical insight; the section on information redundancy describes repetitive data as related to saturation. The paper does not report how the citing study determined its number of participating services or assessed its interview transcripts and field diaries. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 3

  1. Lee Eden B. Research data management and data literacies (chandos information professional series: (2022), by tibor koltay 2022 Taylor & Francis Cambridge, MA: Chandos, xi 184 ISBN 978-0-12-824475-3.
  2. Morse J.M. Data were saturated 25 2015 Sage Publications Sage CA Los Angeles, CA 587 588
  3. Thomson S.B. Sample size and grounded theory. Thomson, SB (2010) Grounded Theory-Sample Size. Journal of Administration and Governance 5 1 2010 45 52

Cited by

Sorted by citations

Authors
Rahimi, S., & khatooni, M.
Affiliations
Qazvin University of Medical Sciences (IR)
Corresponding author
Rahimi, Sara
Venue
International Journal of Nursing Studies Advances
Publisher
Elsevier BV
Published
2024-06
Volume
6
Pages
100174
ISSN
2666-142X (ISSN-L)
OpenAlex
W4390604507
Cited by
560
References
34
Citations by year
2026: 273 · 2025: 236 · 2024: 51
FWCI
704.99
Type
journal article
Language
en
Open access
Locations
  • International Journal of Nursing Studies Advances (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
Qazvin University of Medical Sciences
Topics
  • Social Sciences › Education › Qualitative Research Methods and Applications
  • Social Sciences › Sociology and Political Science › Qualitative Research Methods and Ethics
  • Social Sciences › Sociology and Political Science › Focus Groups and Qualitative Methods
Keywords
saturation, qualitative research, data saturation, theoretical saturation, research credibility, sample size determination, nursing 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 ›

Are you an author, or do you see a problem with this page? Request a review