Code Saturation Versus Meaning Saturation: How Many Interviews Are Enough?
TL;DR: In this article, the authors compared two approaches to assess saturation: code saturation and meaning saturation, and examined sample sizes needed to reach saturation in each approach, what saturation meant, and how to assess it.
Abstract: 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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TL;DR: It is concluded that saturation should be operationalized in a way that is consistent with the research question(s), and the theoretical position and analytic framework adopted, but also that there should be some limit to its scope, so as to risk saturation losing its coherence and potency if its conceptualization and uses are stretched too widely.
Abstract: Saturation has attained widespread acceptance as a methodological principle in qualitative research. It is commonly taken to indicate that, on the basis of the data that have been collected or analysed hitherto, further data collection and/or analysis are unnecessary. However, there appears to be uncertainty as to how saturation should be conceptualized, and inconsistencies in its use. In this paper, we look to clarify the nature, purposes and uses of saturation, and in doing so add to theoretical debate on the role of saturation across different methodologies. We identify four distinct approaches to saturation, which differ in terms of the extent to which an inductive or a deductive logic is adopted, and the relative emphasis on data collection, data analysis, and theorizing. We explore the purposes saturation might serve in relation to these different approaches, and the implications for how and when saturation will be sought. In examining these issues, we highlight the uncertain logic underlying saturation—as essentially a predictive statement about the unobserved based on the observed, a judgement that, we argue, results in equivocation, and may in part explain the confusion surrounding its use. We conclude that saturation should be operationalized in a way that is consistent with the research question(s), and the theoretical position and analytic framework adopted, but also that there should be some limit to its scope, so as not to risk saturation losing its coherence and potency if its conceptualization and uses are stretched too widely.
4,750 citations
TL;DR: It is argued that although the concepts of data-, thematic- or code-saturation, and even meaning-s saturation, are coherent with the neo-positivist, discovery-oriented, meaning excavation project of coding reliability types of TA, they are not consistent with the values and assumptions of reflexive TA.
Abstract: The concept of data saturation, defined as ‘information redundancy’ or the point at which no new themes or codes ‘emerge’ from data, is widely referenced in thematic analysis (TA) research in sport...
1,090 citations
TL;DR: It is recommended that qualitative health researchers be more transparent about evaluations of their sample size sufficiency, situating these within broader and more encompassing assessments of data adequacy.
Abstract: Choosing a suitable sample size in qualitative research is an area of conceptual debate and practical uncertainty. That sample size principles, guidelines and tools have been developed to enable researchers to set, and justify the acceptability of, their sample size is an indication that the issue constitutes an important marker of the quality of qualitative research. Nevertheless, research shows that sample size sufficiency reporting is often poor, if not absent, across a range of disciplinary fields. A systematic analysis of single-interview-per-participant designs within three health-related journals from the disciplines of psychology, sociology and medicine, over a 15-year period, was conducted to examine whether and how sample sizes were justified and how sample size was characterised and discussed by authors. Data pertinent to sample size were extracted and analysed using qualitative and quantitative analytic techniques. Our findings demonstrate that provision of sample size justifications in qualitative health research is limited; is not contingent on the number of interviews; and relates to the journal of publication. Defence of sample size was most frequently supported across all three journals with reference to the principle of saturation and to pragmatic considerations. Qualitative sample sizes were predominantly – and often without justification – characterised as insufficient (i.e., ‘small’) and discussed in the context of study limitations. Sample size insufficiency was seen to threaten the validity and generalizability of studies’ results, with the latter being frequently conceived in nomothetic terms. We recommend, firstly, that qualitative health researchers be more transparent about evaluations of their sample size sufficiency, situating these within broader and more encompassing assessments of data adequacy. Secondly, we invite researchers critically to consider how saturation parameters found in prior methodological studies and sample size community norms might best inform, and apply to, their own project and encourage that data adequacy is best appraised with reference to features that are intrinsic to the study at hand. Finally, those reviewing papers have a vital role in supporting and encouraging transparent study-specific reporting.
1,052 citations
TL;DR: This work describes and validate a simple-to-apply method for assessing and reporting on saturation in the context of inductive thematic analyses and proposes a more flexible approach to reporting saturation.
Abstract: 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.
640 citations
13 May 2021
TL;DR: Thematic analysis (TA) is widely used in qualitative psychology as mentioned in this paper, where researchers must choose between a diverse range of approaches that can differ considerably in their underlying conceptualizations of qualitative research, meaningful knowledge production and key constructs such as themes.
Abstract: Thematic analysis (TA) is widely used in qualitative psychology. In using TA, researchers must choose between a diverse range of approaches that can differ considerably in their underlying (but often implicit) conceptualizations of qualitative research, meaningful knowledge production and key constructs such as themes, as well as analytic procedures. This diversity within the method of TA is typically poorly understood and rarely acknowledged, resulting in the frequent publication of research lacking in design coherence. Furthermore, because TA offers researchers something closer to a method (a trans-theoretical tool or technique) rather than a methodology (a theoretically-informed framework for research), one with considerable theoretical and design flexibility, researchers need to engage in careful conceptual and design thinking to produce TA research with methodological integrity. In this paper, we support researchers in their conceptual and design thinking for TA, and particularly for the reflexive approach we have developed, by guiding them through the conceptual underpinnings of different approaches to TA, and key design considerations. We outline our typology of three main “schools” of TA – coding reliability, codebook and reflexive – and consider how these differ in their conceptual underpinnings, with a particular focus on the distinct characteristics of our reflexive approach. We discuss key areas of design – research questions, data collection, participant/data item selection strategy and criteria, ethics, and quality standards and practices – and end with guidance on reporting standards for reflexive TA.
419 citations
References
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Book•
12 Oct 2017
TL;DR: The Discovery of Grounded Theory as mentioned in this paper is a book about the discovery of grounded theories from data, both substantive and formal, which is a major task confronting sociologists and is understandable to both experts and laymen.
Abstract: Most writing on sociological method has been concerned with how accurate facts can be obtained and how theory can thereby be more rigorously tested. In The Discovery of Grounded Theory, Barney Glaser and Anselm Strauss address the equally Important enterprise of how the discovery of theory from data--systematically obtained and analyzed in social research--can be furthered. The discovery of theory from data--grounded theory--is a major task confronting sociology, for such a theory fits empirical situations, and is understandable to sociologists and laymen alike. Most important, it provides relevant predictions, explanations, interpretations, and applications. In Part I of the book, "Generation Theory by Comparative Analysis," the authors present a strategy whereby sociologists can facilitate the discovery of grounded theory, both substantive and formal. This strategy involves the systematic choice and study of several comparison groups. In Part II, The Flexible Use of Data," the generation of theory from qualitative, especially documentary, and quantitative data Is considered. In Part III, "Implications of Grounded Theory," Glaser and Strauss examine the credibility of grounded theory. The Discovery of Grounded Theory is directed toward improving social scientists' capacity for generating theory that will be relevant to their research. While aimed primarily at sociologists, it will be useful to anyone Interested In studying social phenomena--political, educational, economic, industrial-- especially If their studies are based on qualitative data.
53,267 citations
"Code Saturation Versus Meaning Satu..." refers background in this paper
...The concept of saturation was originally developed by Glaser and Strauss (1967) as part of their influential grounded theory approach to qualitative research, which focuses on developing sociological theory from textual 1Emory University, Atlanta, Georgia, USA 2Duke University, Durham, North…...
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44,847 citations
Book•
01 Jan 2002
TL;DR: In this paper, conceptual issues and themes on qualitative research and evaluaton methods including: qualitative data, triangulated inquiry, qualitative inquiry, constructivism, constructionism, complexity (chaos) theory, qualitative designs and data collection, fieldwork strategies, interviewing, tape-recording, ethical issues, analysis, interpretation and reporting, observations vs. perceived impacts and utilisation-focused evaluation reporting.
Abstract: This book explains clearly conceptual issues and themes on qualitative research and evaluaton methods including: qualitative data, triangulated inquiry, qualitative inquiry, constructivism, constructionism, Complexity (chaos) theory, qualitative designs and data collection, fieldwork strategies, interviewing, tape-recording, ethical issues, analysis, interpretation and reporting, observations vs. perceived impacts and utilisation-focused evaluation reporting.
13,768 citations
"Code Saturation Versus Meaning Satu..." refers background in this paper
...Qualitative studies typically use purposively selected samples (as opposed to probability-driven samples), which seek a diverse range of “information-rich” sources (Patton, 1990) and focus more on the quality and richness of data rather than the number of participants....
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TL;DR: The authors operationalize saturation and make evidence-based recommendations regarding nonprobabilistic sample sizes for interviews and found that saturation occurred within the first twelve interviews, although basic elements for metathemes were present as early as six interviews.
Abstract: Guidelines for determining nonprobabilistic sample sizes are virtually nonexistent. Purposive samples are the most commonly used form of nonprobabilistic sampling, and their size typically relies on the concept of “saturation,” or the point at which no new information or themes are observed in the data. Although the idea of saturation is helpful at the conceptual level, it provides little practical guidance for estimating sample sizes, prior to data collection, necessary for conducting quality research. Using data from a study involving sixty in-depth interviews with women in two West African countries, the authors systematically document the degree of data saturation and variability over the course of thematic analysis. They operationalize saturation and make evidence-based recommendations regarding nonprobabilistic sample sizes for interviews. Based on the data set, they found that saturation occurred within the first twelve interviews, although basic elements for metathemes were present as early as six...
12,951 citations
"Code Saturation Versus Meaning Satu..." refers background or methods or result in this paper
...Our study responds to calls for more methodological research on operationalizing saturation (by Francis et al., 2010; Guest et al., 2006; Morse, 2015)....
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...Most sample size recommendations for qualitative research are thus experiential or “rules of thumb” (Bryman, 2012; Guest et al., 2006; Kerr et al., 2010; Morse, 1995; Sandelowski, 1995)....
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...These results are remarkably similar to those of Guest et al. (2006), who identified that data saturation occurred between seven and 12 interviews, with many of the basic elements of themes present between Interviews 1 and 6....
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...A decade later, this situation remains, as confirmed by Guest et al. (2006), who reviewed 24 qualitative research textbooks and seven databases and found no guidelines on how to achieve saturation in purposive samples....
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...The authors concluded that the literature does a “poor job of operationalizing the concept of saturation, providing no description of how saturation might be determined and no practical guidelines for estimating sample sizes for purposively sampled interviews” (Guest et al., 2006, p. 60)....
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University of North Carolina at Chapel Hill1, Fred Hutchinson Cancer Research Center2, FHI 3603, University of Zimbabwe4, Johns Hopkins University5, Oswaldo Cruz Foundation6, Chiang Mai University7, Fenway Health8, Harvard University9, Kenya Medical Research Institute10, University of the Witwatersrand11, University of California, San Francisco12, University of Nebraska Medical Center13, National Institutes of Health14, University of California, Los Angeles15, University of Washington16
TL;DR: In this article, Antiretroviral therapy that reduces viral replication could limit the transmission of human immunodeficiency virus type 1 (HIV-1) in serodiscordant couples.
Abstract: Background Antiretroviral therapy that reduces viral replication could limit the transmission of human immunodeficiency virus type 1 (HIV-1) in serodiscordant couples. Methods In nine countries, we...
5,871 citations