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      Saturation in qualitative research: exploring its conceptualization and operationalization

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          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.

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          Most cited references 58

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          How Many Interviews Are Enough?: An Experiment with Data Saturation and Variability

           G Guest (2006)
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            What is an adequate sample size? Operationalising data saturation for theory-based interview studies.

            In interview studies, sample size is often justified by interviewing participants until reaching 'data saturation'. However, there is no agreed method of establishing this. We propose principles for deciding saturation in theory-based interview studies (where conceptual categories are pre-established by existing theory). First, specify a minimum sample size for initial analysis (initial analysis sample). Second, specify how many more interviews will be conducted without new ideas emerging (stopping criterion). We demonstrate these principles in two studies, based on the theory of planned behaviour, designed to identify three belief categories (Behavioural, Normative and Control), using an initial analysis sample of 10 and stopping criterion of 3. Study 1 (retrospective analysis of existing data) identified 84 shared beliefs of 14 general medical practitioners about managing patients with sore throat without prescribing antibiotics. The criterion for saturation was achieved for Normative beliefs but not for other beliefs or studywise saturation. In Study 2 (prospective analysis), 17 relatives of people with Paget's disease of the bone reported 44 shared beliefs about taking genetic testing. Studywise data saturation was achieved at interview 17. We propose specification of these principles for reporting data saturation in theory-based interview studies. The principles may be adaptable for other types of studies.
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              The Significance of Saturation

               J M Morse (1995)
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                Author and article information

                Contributors
                +44 (0)1782 734253 , j.sim@keele.ac.uk
                jwaterfield@qmu.ac.uk
                Journal
                Qual Quant
                Qual Quant
                Quality & Quantity
                Springer Netherlands (Dordrecht )
                0033-5177
                14 September 2017
                14 September 2017
                2018
                : 52
                : 4
                : 1893-1907
                Affiliations
                [1 ]ISNI 0000 0004 0415 6205, GRID grid.9757.c, Institute for Primary Care and Health Sciences, , Keele University, ; Keele, Staffordshire ST5 5BG UK
                [2 ]GRID grid.104846.f, School of Health Sciences, , Queen Margaret University, ; Edinburgh, EH21 6UU UK
                Article
                574
                10.1007/s11135-017-0574-8
                5993836
                © The Author(s) 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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                © Springer Nature B.V. 2018

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