Sample Size In Qualitative Research Research Articles

Sample Size in Qualitative Research Using In-Depth Interviews: A View from The Associate Editor 12 Years Later.

Sample Size in Qualitative Research Using In-Depth Interviews: A View from The Associate Editor 12 Years Later.

Filipino Teachers’ Revelations in Working Abroad

This study explored the reasons and lived experiences of 20 Filipino teacher respondents in the school year 2023-2024. The qualitative method through phenomenological research was adopted. It is the method of discovering and structuring the meaning of human incidents through interviews with people involved in the real-life experience (Creswell, 2007; Polit & Beck, 2012). Patton (2002) describes that determining sample size in qualitative research does not follow one rule. There is no one rule related to sample size when using a qualitative research design. The respondents expressed heart-warming and overwhelming insights into their acculturation in the USA and Southeast Asian countries. Homesickness was the only negative thought, but it was easily overcome due to the availability of social media, which established the communication link with family members. Teaching abroad served as the turning point as their personal and professional “inputs” were outweighed by the “outputs” in terms of financial benefits, perks, and other work-life balance initiatives by schools abroad. Hence, the Department of Education should improve the economic conditions of teachers to avoid the exodus of a greater number of trained teachers in the service years ahead.

Nitel Araştırmalarda Örneklem Büyüklüğünün Belirlenmesi: Veri Doygunluğu

Nitel araştırmalarda (derinlemesine ve odak grup görüşmelerinde), araştırmacının aynı yorumları tekrar tekrar duymaya başlaması, veri doygunluğuna ulaşıldığı anlamına gelmektedir. Doygunluk yaklaşımı, nitel araştırmada veri toplama ve / veya analizinin durdurulması için bir kriter olarak kullanılmaktadır. Bu yaklaşımda, katılımcıların bakış açıları tam anlaşılana kadar görüşmeler araştırmacılar tarafından devam ettirilmektedir. Diğer yandan, kaç katılımcı ya da kaç odak grupta doygunluk sağlandığına dair farklı araştırmalar bulunmaktadır. Bu çalışmada, nitel araştırmalardaki örneklem büyüklüğünün belirlenmesinde kullanılan doygunluk kavramının incelenmesi ve Türkiye’de sağlık çalışanları ile ilgili doktora düzeyinde yapılan lisansüstü tezlerin değerlendirilmesi hedeflenmiştir. Çalışmaya dahil edilecek araştırmaların belirlenmesinde "Ulusal Tez Merkezi" veri tabanı kullanılmıştır. Araştırmaların belirlenmesinde bazı kısıtlılıklar dikkate alınmış, derinlemesine ve odak grup görüşme tekniklerinin kullanıldığı sağlık alanında yapılmış 45 doktora tezi çalışmanın kapsamını oluşturmuştur. Bu araştırmaların incelenmesinde doküman incelemesi tekniği kullanılmıştır. Araştırmaların %51,1’inde doygunluk yaklaşımının kullanıldığı gözlemlenmiştir. Araştırmaların sadece %17,8’inde referans gösterilerek doygunluk yaklaşımının detaylı bir şekilde açıklandığı belirlenmiştir. Aynı şekilde, derinlemesine görüşmelerin (%84,4) odak grup görüşmelerine (%15,6) göre daha fazla kullanıldığı ve derinlemesine görüşmelerde daha hızlı bir şekilde doygunluğa ulaşıldığı tespit edilmiştir. Ayrıca, odak grup görüşmelerinin kullanıldığı araştırmalarda dört ya da beş odak grup oluşturulduğu ve gruplardaki kişi sayısının da beş ile on arasında değiştiği görülmüştür. Elde ettiğimiz bulgular ve yapılan araştırmalar, doygunluk noktasının nitel araştırmalarda yaygın olarak kullanıldığını göstermektedir. Buradaki tartışılan temel husus, doygunluk noktasının araştırmalarda kullanılıp kullanılmaması değil, doğru ve şeffaf bir şekilde kullanılması gerektiği üzerine olmuştur.

Less is More? Review and Recommendations for Qualitative Sampling Strategy using the S.C.A.D.E Approach

The determination of sample size in qualitative research introduces a unique and multifaceted challenge, setting it apart from the more structured methodology of quantitative research. Contrary to sampling methods in quantitative research, which primarily aim to secure random and statistically representative samples that facilitate the generalisation of findings to broader populations, sampling in qualitative research requires a distinct set of considerations in its pursuit of a deeper understanding of specific phenomena. The objective of this editorial is to provide qualitative researchers with clear and foundational guidance for effectively communicating the methodological aspects of their research papers, particularly pertaining to sample size justification. Building on this, we present S.C.A.D.E, an acronym comprising five key actionable elements—Selecting, Clarifying, Aligning, Deploying and Evaluating—to guide researchers in determining the appropriate sample size and ensuring that data saturation is achieved as they plan their qualitative exploration.

Problem areas of determining the sample size in qualitative research: a model proposal

PurposeThe lack of a definite standard for determining the sample size in qualitative research leaves the research process to the initiative of the researcher, and this situation overshadows the scientificity of the research. The primary purpose of this research is to propose a model by questioning the problem of determining the sample size, which is one of the essential issues in qualitative research. The fuzzy logic model is proposed to determine the sample size in qualitative research.Design/methodology/approachConsidering the structure of the problem in the present study, the proposed fuzzy logic model will benefit and contribute to the literature and practical applications. In this context, ten variables, namely scope of research, data quality, participant genuineness, duration of the interview, number of interviews, homogeneity, information strength, drilling ability, triangulation and research design, are used as inputs. A total of 20 different scenarios were created to demonstrate the applicability of the model proposed in the research and how the model works.FindingsThe authors reflected the results of each scenario in the table and showed the values for the sample size in qualitative studies in Table 4. The research results show that the proposed model's results are of a quality that will support the literature. The research findings show that it is possible to develop a model using the laws of fuzzy logic to determine the sample size in qualitative research.Originality/valueThe model developed in this research can contribute to the literature, and in any case, it can be argued that determining the sample volume is a much more effective and functional model than leaving it to the initiative of the researcher.

Sample Size for Interview in Qualitative Research in Social Sciences: A Guide to Novice Researchers

This review aimed to answer the question of how many interviews are enough for one qualitative research? The question ‘how many interviews are enough for one qualitative research is persistently controversial among qualitative researchers in social science. For this frequently occurring question especially among novice practitioners, the majority of scholars are opted to say no universally guiding rule to decide on a required number of sample for qualitative research rather ‘it depends’. But, this also raises another insight among researchers urging them to look for different things, i.e., on what circumstance would be making a decision about the required number of respondents depend? Though we lack one guideline dictating researchers how to decide on the number of sample size, the majority of researchers agree on one reasonable answer this is ‘it depends’. Indeed, in our work, we endeavor to identify, on what it depends? We also attempted to figure out or indicate the commonly referred range of sample size in qualitative research. Generally when we sum up our review work, the decision on “How many” is depended on several factors among which the following are some; the focus of the research, the type of research question, available resource and time, institutional committee requirements, the judgments of epistemic community in which a researcher is located, the nature of the selected group, the domain of inquiry, the experience of the researcher with qualitative research, and so on. Specific to number 20-60 is the most frequently observed range of sample size in qualitative research which of course is determined by the aforementioned factors.

Sample sizes for saturation in qualitative research: A systematic review of empirical tests

ObjectiveTo review empirical studies that assess saturation in qualitative research in order to identify sample sizes for saturation, strategies used to assess saturation, and guidance we can draw from these studies. MethodsWe conducted a systematic review of four databases to identify studies empirically assessing sample sizes for saturation in qualitative research, supplemented by searching citing articles and reference lists. ResultsWe identified 23 articles that used empirical data (n = 17) or statistical modeling (n = 6) to assess saturation. Studies using empirical data reached saturation within a narrow range of interviews (9–17) or focus group discussions (4–8), particularly those with relatively homogenous study populations and narrowly defined objectives. Most studies had a relatively homogenous study population and assessed code saturation; the few outliers (e.g., multi-country research, meta-themes, “code meaning” saturation) needed larger samples for saturation. ConclusionsDespite varied research topics and approaches to assessing saturation, studies converged on a relatively consistent sample size for saturation for commonly used qualitative research methods. However, these findings apply to certain types of studies (e.g., those with homogenous study populations). These results provide strong empirical guidance on effective sample sizes for qualitative research, which can be used in conjunction with the characteristics of individual studies to estimate an appropriate sample size prior to data collection. This synthesis also provides an important resource for researchers, academic journals, journal reviewers, ethical review boards, and funding agencies to facilitate greater transparency in justifying and reporting sample sizes in qualitative research. Future empirical research is needed to explore how various parameters affect sample sizes for saturation.

PNS217 Bootstrap Saturation: A Quantitative Approach for Supporting DATA Saturation in Sample Sizes in Qualitative Research

PNS217 Bootstrap Saturation: A Quantitative Approach for Supporting DATA Saturation in Sample Sizes in Qualitative Research

DETERMINING THE SAMPLE SIZE IN QUALITATIVE RESEARCH

According to most researchers carrying out qualitative researches, adequacy of sample size is a key marker for the research’s quality. However, there is no consensus with respect to the exact size of a proper sample. For some authors, the count of investigated units is irrelevant when they assess the sample size’s adequacy, as they emphasize the abundance of data submitted by the units included in the sample. Other researchers deem the sample size all-important in order to reach reliable outputs and to ensure the reliability of qualitative researches. No clear methods and rules are given for qualitative investigation in order to guide researches in establishing the sample’s proper size. Size determination is a matter of consideration, as the researchers follow various guidelines in order to assess whether their own research sample is proper or not. This paper aims to identify the main external guidelines for a qualitative research project allowing researchers to determine the proper sample size in qualitative research..

A simple method to assess and report thematic saturation in qualitative research.

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.

Saturation controversy in qualitative research: Complexities and underlying assumptions. A literature review

Judgement of quality in qualitative has been a contested and controversial issue amongst researchers. Contention has always emanated from the subjective nature of qualitative studies, absence of clear guidelines in sampling as well as the lack of generalisability of findings. Numerous avenues have been suggested to improve qualitative research quality and key amongst the suggestions is the concept of saturation. It is viewed as a contemporary measure to alleviate the subjectivity in qualitative research, a yardstick for estimating sample sizes in qualitative research as well as an assurance for rigour and quality. Despite its recognition as a vital tool, it has its own fair share of controversies and contradictions. This research, through a comprehensive and evaluative literature review sought to unpack the saturation puzzle, controversies in definitions and underlying assumptions. The objective was to make a contribution to the contemporary but growing body of knowledge on the saturation conundrum. The study found out that there are various forms of saturation and with varying underlying propositions, therefore in order to meaningfully apply the concept, researchers have to appreciate the forms of saturation, link the appropriate form to their qualitative research design. It is undoubtedly important for research to define fully the form adopted, explicate the steps followed to achieve it and how it was ultimately achieved. In short, narrow the scope of saturation and contextualise it to your research.

Quantos participantes são necessários para um estudo qualitativo? Linhas práticas de orientação

Uma das dificuldades associadas à realização de investigação qualitativa remete para a dimensão das amostras. Com alguma frequência, os investigadores não justificam a sua escolha de N e são por isso criticados. Este artigo apresenta linhas de orientação para a determinação e justificação do número de casos a usar numa investigação qualitativa. Defende que (a) o aumento da dimensão da amostra não é, em si, uma vantagem, e (b) a quantidade desejável de casos da amostra depende da pergunta de investigação e da declinação da mesma numa série de linhas orientadoras.

What Influences Saturation? Estimating Sample Sizes in Focus Group Research.

Saturation is commonly used to determine sample sizes in qualitative research, yet there is little guidance on what influences saturation. We aimed to assess saturation and identify parameters to estimate sample sizes for focus group studies in advance of data collection. We used two approaches to assess saturation in data from 10 focus group discussions. Four focus groups were sufficient to identify a range of new issues (code saturation), but more groups were needed to fully understand these issues (meaning saturation). Group stratification influenced meaning saturation, whereby one focus group per stratum was needed to identify issues; two groups per stratum provided a more comprehensive understanding of issues, but more groups per stratum provided little additional benefit. We identify six parameters influencing saturation in focus group data: study purpose, type of codes, group stratification, number of groups per stratum, and type and degree of saturation.

Characterising and justifying sample size sufficiency in interview-based studies: systematic analysis of qualitative health research over a 15-year period

BackgroundChoosing 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.MethodsA 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.ResultsOur 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.ConclusionsWe 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.

Confounding issues related to determining sample size in qualitative research

ABSTRACTThe debate on determining sample size in qualitative research is confounded by four fundamental methodological issues: the exclusive focus on theme analysis; the diverse and imprecise use of ‘qualitative’; a reliance on only two logics of inquiry, induction and deduction, and the occasional confusion of abduction with induction; and a general lack of recognition of the importance of differences in ontological assumptions. Embedded in these issues is an unwarranted acceptance of limited associations between certain assumptions, logics, forms of data, and methods of data collection/generation and analysis. What is required is a reformulation of the problem and its discussion with reference to ontological assumptions and logics of inquiry.

The sample size debate: response to Norman Blaikie

ABSTRACTIn his detailed response to our paper on sample size in qualitative research, Norman Blaikie raises important issues concerning conceptual definitions and taxonomy. In particular, he points out the problems associated with a loose, generic application of adjectives such as ‘qualitative’ or ‘inductive’. We endorse this concern, though we suggest that in some specific contexts a broad categorization may be more appropriate than a more nuanced distinction – provided that it is clear in which sense the terms are employed. However, other concepts, such as saturation, do not lend themselves to generic use, and require a more detailed conceptualization. Blaikie’s analysis also makes it clear that meaningful discussion of sample size in qualitative research cannot occur with reference to an undifferentiated conception of the nature of qualitative research; clear distinctions need to be made within this approach in terms of methodology, ontological and epistemological assumptions and broader research paradigms.

Can sample size in qualitative research be determined a priori?

ABSTRACTThere has been considerable recent interest in methods of determining sample size for qualitative research a priori, rather than through an adaptive approach such as saturation. Extending previous literature in this area, we identify four distinct approaches to determining sample size in this way: rules of thumb, conceptual models, numerical guidelines derived from empirical studies, and statistical formulae. Through critical discussion of these approaches, we argue that each embodies one or more questionable philosophical or methodological assumptions, namely: a naïve realist ontology; a focus on themes as enumerable ‘instances’, rather than in more conceptual terms; an incompatibility with an inductive approach to analysis; inappropriate statistical assumptions in the use of formulae; and an unwarranted assumption of generality across qualitative methods. We conclude that, whilst meeting certain practical demands, determining qualitative sample size a priori is an inherently problematic approach, especially in more interpretive models of qualitative research.

(I Can't Get No) Saturation: A simulation and guidelines for sample sizes in qualitative research.

I explore the sample size in qualitative research that is required to reach theoretical saturation. I conceptualize a population as consisting of sub-populations that contain different types of information sources that hold a number of codes. Theoretical saturation is reached after all the codes in the population have been observed once in the sample. I delineate three different scenarios to sample information sources: “random chance,” which is based on probability sampling, “minimal information,” which yields at least one new code per sampling step, and “maximum information,” which yields the largest number of new codes per sampling step. Next, I use simulations to assess the minimum sample size for each scenario for systematically varying hypothetical populations. I show that theoretical saturation is more dependent on the mean probability of observing codes than on the number of codes in a population. Moreover, the minimal and maximal information scenarios are significantly more efficient than random chance, but yield fewer repetitions per code to validate the findings. I formulate guidelines for purposive sampling and recommend that researchers follow a minimum information scenario.

Code Saturation Versus Meaning Saturation: How Many Interviews Are Enough?

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.

Sample size for qualitative research

Purpose Qualitative researchers have been criticised for not justifying sample size decisions in their research. This short paper addresses the issue of which sample sizes are appropriate and valid within different approaches to qualitative research. Design/methodology/approach The sparse literature on sample sizes in qualitative research is reviewed and discussed. This examination is informed by the personal experience of the author in terms of assessing, as an editor, reviewer comments as they relate to sample size in qualitative research. Also, the discussion is informed by the author’s own experience of undertaking commercial and academic qualitative research over the last 31 years. Findings In qualitative research, the determination of sample size is contextual and partially dependent upon the scientific paradigm under which investigation is taking place. For example, qualitative research which is oriented towards positivism, will require larger samples than in-depth qualitative research does, so that a representative picture of the whole population under review can be gained. Nonetheless, the paper also concludes that sample sizes involving one single case can be highly informative and meaningful as demonstrated in examples from management and medical research. Unique examples of research using a single sample or case but involving new areas or findings that are potentially highly relevant, can be worthy of publication. Theoretical saturation can also be useful as a guide in designing qualitative research, with practical research illustrating that samples of 12 may be cases where data saturation occurs among a relatively homogeneous population. Practical implications Sample sizes as low as one can be justified. Researchers and reviewers may find the discussion in this paper to be a useful guide to determining and critiquing sample size in qualitative research. Originality/value Sample size in qualitative research is always mentioned by reviewers of qualitative papers but discussion tends to be simplistic and relatively uninformed. The current paper draws attention to how sample sizes, at both ends of the size continuum, can be justified by researchers. This will also aid reviewers in their making of comments about the appropriateness of sample sizes in qualitative research.