[Isc Medical Interviews 25.pdf
Amancio Mccrae
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.
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.
Sample size in qualitative research has been the subject of enduring discussions [4, 10, 11]. Whilst the quantitative research community has established relatively straightforward statistics-based rules to set sample sizes precisely, the intricacies of qualitative sample size determination and assessment arise from the methodological, theoretical, epistemological, and ideological pluralism that characterises qualitative inquiry (for a discussion focused on the discipline of psychology see [12]). This mitigates against clear-cut guidelines, invariably applied. Despite these challenges, various conceptual developments have sought to address this issue, with guidance and principles [4, 10, 11, 13,14,15,16,17,18,19,20], and more recently, an evidence-based approach to sample size determination seeks to ground the discussion empirically [21,22,23,24,25,26,27,28,29,30,31,32,33,34,35].
Focusing on single-interview-per-participant qualitative designs, the present study aims to further contribute to the dialogue of sample size in qualitative research by offering empirical evidence around justification practices associated with sample size. We next review the existing conceptual and empirical literature on sample size determination.
In terms of principles, Lincoln and Guba [17] proposed that sample size determination be guided by the criterion of informational redundancy, that is, sampling can be terminated when no new information is elicited by sampling more units. Following the logic of informational comprehensiveness Malterud et al. [18] introduced the concept of information power as a pragmatic guiding principle, suggesting that the more information power the sample provides, the smaller the sample size needs to be, and vice versa.
Critiquing the concept of saturation, Nelson [19] proposes five conceptual depth criteria in grounded theory projects to assess the robustness of the developing theory: (a) theoretical concepts should be supported by a wide range of evidence drawn from the data; (b) be demonstrably part of a network of inter-connected concepts; (c) demonstrate subtlety; (d) resonate with existing literature; and (e) can be successfully submitted to tests of external validity.
Other work has sought to examine practices of sample size reporting and sufficiency assessment across a range of disciplinary fields and research domains, from nutrition [34] and health education [32], to education and the health sciences [22, 27], information systems [30], organisation and workplace studies [33], human computer interaction [21], and accounting studies [24]. Others investigated PhD qualitative studies [31] and grounded theory studies [35]. Incomplete and imprecise sample size reporting is commonly pinpointed by these investigations whilst assessment and justifications of sample size sufficiency are even more sporadic.
Similarly, fewer than 10% of articles in organisation and workplace studies provided a sample size justification relating to existing recommendations by methodologists, prior relevant work, or saturation [33], whilst only 17% of focus groups studies in health-related journals provided an explanation of sample size (i.e. number of focus groups), with saturation being the most frequently invoked argument, followed by published sample size recommendations and practical reasons [22]. The notion of saturation was also invoked by 11 out of the 51 most highly cited studies that Guetterman [27] reviewed in the fields of education and health sciences, of which six were grounded theory studies, four phenomenological and one a narrative inquiry. Finally, analysing 641 interview-based articles in accounting, Dai et al. [24] called for more rigor since a significant minority of studies did not report precise sample size.
Despite increasing attention to rigor in qualitative research (e.g. [52]) and more extensive methodological and analytical disclosures that seek to validate qualitative work [24], sample size reporting and sufficiency assessment remain inconsistent and partial, if not absent, across a range of research domains.
A structured search for articles reporting cross-sectional, interview-based qualitative studies was carried out and eligible reports were systematically reviewed and analysed employing both quantitative and qualitative analytic techniques.
A data extraction form was developed (see Additional File 3) recording three areas of information: (a) information about the article (e.g. authors, title, journal, year of publication etc.); (b) information about the aims of the study, the sample size and any justification for this, the participant characteristics, the sampling technique and any sample-related observations or comments made by the authors; and (c) information about the method or technique(s) of data analysis, the number of researchers involved in the analysis, the potential use of software, and any discussion around epistemological considerations. The Abstract, Methods and Discussion (and/or Conclusion) sections of each article were examined by one author (KV) who extracted all the relevant information. This was directly copied from the articles and, when appropriate, comments, notes and initial thoughts were written down.
To examine the kinds of sample size justifications provided by articles, an inductive content analysis [54] was initially conducted. On the basis of this analysis, the categories that expressed qualitatively different sample size justifications were developed.
A thematic analysis [55] was then performed on all scientific narratives that discussed or commented on the sample size of the study. These narratives were evident both in papers that justified their sample size and those that did not. To identify these narratives, in addition to the methods sections, the discussion sections of the reviewed articles were also examined and relevant data were extracted and analysed.
Number of eligible articles published each year per journalFootnote The publication of qualitative studies in the BMJ was significantly reduced from 2012 onwards and this appears to coincide with the initiation of the BMJ Open to which qualitative studies were possibly directed.
The qualitative content analysis of the scientific narratives identified eleven different sample size justifications. These are described below and illustrated with excerpts from relevant articles. By way of a summary, the frequency with which these were deployed across the three journals is indicated in Table 3.
No new topics were identified following analysis of approximately two thirds of the interviews; however, all interviews were coded in order to develop a better understanding of how characteristic the views and reported behaviours were, and also to collect further examples of unusual/deviant observations. (BMJ13).
The final sample size was determined by thematic saturation, the point at which new data appears to no longer contribute to the findings due to repetition of themes and comments by participants (Morse, 1995). At this point, data generation was terminated. (BJHP31).
Furthermore, data collection ceased on pragmatic grounds rather than at the point when saturation point was reached. Despite this, although nuances within sub-themes were still emerging towards the end of data analysis, the themes themselves were being replicated indicating a level of completeness. (BJHP27).
Finally, one article criticised and explicitly renounced the notion of data saturation claiming that, on the contrary, the criterion of theoretical sufficiency determined its sample size (BJHP16).
Overall, it is clear that the concept of saturation encompassed a wide range of variants expressed in terms such as saturation, data saturation, thematic saturation, theoretical saturation, category saturation, saturation of coding, saturation of discursive themes, theme completeness. It is noteworthy, however, that although these various claims were sometimes supported with reference to the literature, they were not evidenced in relation to the study at hand.
The determination of sample size on the basis of pragmatic considerations was the second most frequently invoked argument (9.6% of all justifications) appearing in all three journals. In the BMJ, one article (BMJ15) appealed to pragmatic reasons, relating to time constraints and the difficulty to access certain study populations, to justify the determination of its sample size.
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