contributions to the qualitative research knowledge base

What is Qualitative in Research

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• Published: 28 October 2021
• Volume 44 , pages 599–608, ( 2021 )

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In this text we respond and elaborate on the four comments addressing our original article. In that piece we define qualitative research as an “iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied.” In light of the comments, we identify three positions in relation to our contribution: (1) to not define qualitative research; (2) to work with one definition for each study or approach of “qualitative research” which is predominantly left implicit; (3) to systematically define qualitative research. This article elaborates on these positions and argues that a definition is a point of departure for researchers, including those reflecting on, or researching, the fields of qualitative and quantitative research. The proposed definition can be used both as a standard of evaluation as well as a catalyst for discussions on how to evaluate and innovate different styles of work.

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What is Qualitative in Qualitative Research

What is “qualitative” in qualitative research why the answer does not matter but the question is important, unsettling definitions of qualitative research.

Avoid common mistakes on your manuscript.

The editors of Qualitative Sociology have given us the opportunity not only to receive comments by a group of particularly qualified scholars who engage with our text in a constructive fashion, but also to reply, and thereby to clarify our position. We have read the four essays that comment on our article What is qualitative in qualitative research (Aspers and Corte 2019 ) with great interest. Japonica Brown-Saracino, Paul Lichterman, Jennifer Reich, and Mario Luis Small agree that what we do is new. We are grateful for the engagement that the four commenters show with our text.

Our article is based on a standard approach: we pose a question drawing on our personal experiences and knowledge of the field, make systematic selections from existing literature, identify, collect and analyze data, read key texts closely, make interpretations, move between theory and evidence to connect them, and ultimately present a definition: “ qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied” (Aspers and Corte 2019 , 139) . We acknowledge that there are different qualitative characteristics of research, meaning that we do not merely operate with a binary code of qualitative versus non-qualitative research. Our definition is an attempt to make a new distinction that clarifies what is qualitative in qualitative research and which is useful to the scientific community. Consequently, our work is in line with the definition that we have proposed.

Given the interest that our contribution has already generated, it is reasonable to argue that the new distinction we put forth is also significant . As researchers we make claims about significance, but it is always the audience—other scientists—who decide whether the contribution is significant or not. Iteration means that one goes back and forth between theory and evidence, and improved understanding refers to the epistemic gains of a study. To achieve this improved understanding by pursuing qualitative research, it is necessary that one gets close to the empirical material. When these four components are combined, we speak of qualitative research.

The four commentators welcome our text, which does not imply that they agree with all of the arguments we advance. In what follows, we single out some of the most important critiques we received and provide a reply aiming to push the conversation about qualitative research forward.

Why a Definition?

We appreciate that all critics have engaged closely with our definition. One main point of convergence between them is that one should not try to define qualitative research. Small ( Forthcoming ) asks rhetorically: “Is producing a single definition a good idea?” He justifies his concern by pointing out that the term is used to describe both different practices (different kinds of studies) and three elements (types of data; data collection, and analysis). Similarly, both Brown-Saracino ( Forthcoming ) and Lichterman, ( Forthcoming ) argue that not only there is no single entity called qualitative research—a view that we share, but instead, that definitions change over time. For Small, producing a single definition for a field as diverse as sociology, or the social sciences for that matter, is restrictive, a point which is also, albeit differently, shared by Brown-Saracino. Brown-Saracino asserts that our endeavor “might calcify boundaries, stifle innovation, and prevent recognition of areas of common ground across areas that many of us have long assumed to be disparate.” Hence, one should not define what is qualitative, because definitions may harm development. Both Small and Brown-Saracino say that we are drawing boundaries between qualitative and quantitative approaches and overstate differences between them. Yet, part of our intent was the opposite: to build bridges between different approaches by arguing that the ‘qualitative’ feature of research pertains both quantitative and qualitative methodologies, which may use and even combine different methods.

In light of these comments we need to elaborate our argument. Moreover, it is important not to maintain hard lines that may lead to scientific tribalism. Nonetheless, the critique of our—or any other definition of qualitative research—typically implies that there is something “there,” but that we have not captured it correctly with our definition. Thus, the critique that we should not define qualitative research comes with an implicit contradiction. If all agree that there is something called “qualitative research,” even if it is only something that is not quantitative, this still presumes that there is something called “qualitative.” Had we done research on any other topic it would probably have been requested by reviewers to define what we are talking about. The same criteria should apply also when we turn the researcher’s gaze on to our own practice.

Moreover, it is doubtful that our commentators would claim that qualitative research can be “anything,” as the more Dadaistic interpretation by Paul Feyerabend ( 1976 ) would have it. But without referring to the realist view of Karl Popper ( 1963 , 232–3) and his ideas of verisimilitude (i.e., that we get close to the truth) we have tried to spell out what we see as an account of the phenomenology of “qualitative.” We identify three positions in relation to the issue of definition of qualitative research:

We should not define qualitative research.

We can work with one definition for each study or approach of “qualitative research,” which is predominantly left implicit.

We can try to systematically define qualitative research.

Obviously, we have embraced and practiced position 3 in reaction to the current state of the field which is largely dominated by position 2--namely that what is qualitative research is open to a large variety of “definitions.” The critical points of our commentators explicitly or implicitly argue in favor of position 1, or perhaps position 2. Our claim that a definition can help researchers sort good from less good research has triggered criticism. Below, we elaborate on this issue.

We maintain that a definition is a valid starting point useful for junior scholars to learn more about what is qualitative and what is quantitative, and for more advanced researchers it may feature as a point of departure to make improvements, for instance, in clarifying their epistemological positions and goals. But we could have done a better job in clarifying our position. Nonetheless, we contend that change and improvement at this late stage of development in social sciences is partially related to and dependent upon pushing against or building upon clear benchmarks, such as the definition that we have formulated. We acknowledge that “definitions might evolve or diversify over time,” as Brown-Saracino suggests. Still, surely social scientists can keep two things in mind at the same time: an existing definition may be useful, but new research may change it. This becomes evident if one applies our definition to the definition itself: our definition is not immune to work that leads to new qualitative distinctions! Having said this, we are happy to see that all four comments profit from getting in close contact with the definition. This means that our definition and the article offer the reader an opportunity to think with (Fine and Corte 2022 ) or, as Small writes, “forces the reader to think.” We believe that both in principle and in practice, we all agree that clarity and definitions are scientific virtues.

What can a Definition Enable?

While we agree with several points in Small’s essay, we disagree on others. Our underlying assumption is that we can build on existing knowledge, albeit not in the way positivism envisioned it. It follows that work which is primarily descriptive, evocative, political, or generally aimed at social change may entail new knowledge, but it does not fit well within the frame within which we operate in this piece. The existence of different kinds of work, each of which relies on different standards of evaluation—which are often unclear and consequential, especially to graduate students and junior scholars (see Corte and Irwin 2017 )—brings us to another point highlighted by both Small and Lichterman: can the definition be used to differentiate good from lesser good kinds of work?

Small argues that while our article promises to develop a standard of evaluation, it fails to do so. We agree: our definition does not specify the exact criteria of what is good and what is poor research. Our definition demarcates qualitative research from non-qualitative by spelling out the qualitative elements of research, which advances a criterion of evaluation. In addition, there is definitely research that meets the characteristics of being qualitative, but that is uninteresting, irrelevant, or essentially useless (see Alvesson et al. 2017 on “gap spotting,” for instance). What is good or not good research  is to be decided in an ongoing scientific discussion led by those who actively contribute to the development of a field. A definition, nonetheless, can serve as a point of reference to evaluate scholarly work, and it can also serve as a guideline to demarcate what is qualitative from what it is not.

A Good Definition?

Even if one accepts that there should be a definition of qualitative research, and thinks that such a definition could be useful, it does not follow that one must accept our definition. Small identifies what he sees a paradox in our text, namely that we both speak of qualitative research in general and of qualitative elements in different research activities. The term qualitative, as we note and as Small specifies, is used to describe different things: from small n studies to studies of organizations, states, or other units conceptualized as case studies and analyzed quantitatively as well as qualitatively. We are grateful for this observation, which is correct. We failed to properly address this issue in the original text.

As we discuss in the article, the elements used in our definitions (distinctions, process, closeness, and improved understanding) are present in all kinds of research, even quantitative. Perhaps the title of our article should have been: “What is Qualitative in Research?” Our position is that only when all the elements of the definition are applied can one speak of qualitative research. Hence, the first order constructs (i.e., the constructs the actors in the field have made) (Aspers 2009 ) of, for example, “qualitative observations,” may indeed refer to observations that make qualitative distinction in the Aristotelian sense on which we rely. Still, if these qualitative observations are commensurated with a ratio-scale (i.e., get reduced to numbers) this research can no longer be called “qualitative.” It is for this reason that we say that, to refer to first order constructs, “quantitative” research processes entail “qualitative” elements. This research is, as it were, partially qualitative, but it is not, taken together, qualitative research. Brown-Saracino raises a similar point in relation to her own and others works that combine “qualitative” and “quantitative” research. We do not think that one is inherently better, yet we agree with the general idea that qualitative research is particularly useful in identifying research questions and formulating theories (distinctions) that, at a later point should, when possible, be tested quantitatively on larger samples (cf. Small 2005 ). It is our hope that, with our clarification above, it will be easier for researchers to understand what one is and what one is not doing. We also hope that our study will stimulate further dialogue and collaboration between researchers who primarily work within different traditions.

Small wonders if a researcher who tries to replicate a “qualitative” study (according to our definition) is doing qualitative research. The person is certainly doing research, and some elements are likely conducted in a qualitative fashion according to our definition, for example if the method of in-depth fieldwork is employed. But regardless of the method used, and regardless of whether the person finds new things, if the result is binary coded as either confirming or disconfirming existing research, qualitative research is not being conducted because no new distinction is offered. Imagine the same study being replicated for the 20 th time. Surely the researcher must use the same “qualitative” methods (to use the first order construct). It may even excite a large academic audience, but it would not count as qualitative research according to our definition. Our definition requires both that the research process has made use of all its elements, but it also requires the acceptance by the audience. Having said this, in practice, it is more likely that such a study would also report new distinctions that are acknowledged by an audience. If such a study is reviewed and published, these are additional indicators that the new distinctions are considered significant, at least to some extent: how much research space it opens up, and how much it helps other researchers continue the discussion by formulating their own questions and making their own claims (Collins 1998 , 31), whether by agreeing with it by applying it, by refining it (Snow et al. 2003 ), or by disagreeing and identifying new ways forward. There are two key characteristics that make a contribution relevant: newness and usefulness (Csikszentmihalyi 1996 ), both of which are related to the established state of knowledge within a field. Relatedly, Small asks: “Is newness enough? What does a new distinction that does not improve understanding look like?” There are also other indicators that demarcate whether a contribution is significant and to what extent. Some of these indicators include the number of citations a piece of work generates, the reputation of the journal or press where the work is published, and how widely the contribution is used—for instance, across specializations within the same discipline, or across different fields (i.e., different ways of valuation and evaluation) (Aspers and Beckert 2011 ) of scientific output. In principle, if a contribution ends up being used in an area where it would have unlikely been used, then one may further argue for its significance.

As it is implicit in our work when we talk about distinctions, we refer to theory building, albeit appreciating different conceptualizations and uses of the term theory (Abend 2008 ) and ways to achieve it (e.g., Zerubavel 2020 ). Brown-Saracino writes that our project may hold “the unintended consequence of limiting exploratory research designs and methodological innovations.” While we cannot predict the impact of our research, we are certainly in favor of experimentation and different styles of work. In line with David Snow, Calvin Morrill and Leon Anderson ( 2003 , 184), we argue that many qualitative researchers start their projects being underprepared in theory and theory development, oftentimes with the goal of describing, and leaving alone the black box of theory, or postponing it to later phases of the project. Our definition, along with the work by those authors and others on theory development, can be one way to heighten the chances researchers can make distinctions and develop theory.

Lichterman argues that we are not giving enough weight to interpretation and that we should relate more strongly to the larger project of the Geistenwissenschaften . We agree that interpretation is a key element in qualitative research, and we draw on Hans-Georg Gadamer ( 1988 ) who refined the idea of the hermeneutic circle.

Another critique, raised by Reich ( Forthcoming ), is that positionality is a key element of qualitative research. That in working towards a definition, we have “overlooked much of the methodological writings and contributions of women, scholars of color, and queer scholars” that could have enriched our definition, especially regarding “getting closer to the phenomenon studied.” Surely, the way we have searched for and included references means that we have ‘excluded’ the vast majority of research and researchers who do qualitative work. However, we have not included texts by some authors in our sample based on any specific characteristics or according to any specific position. This critique is valid only if Reich shows more explicitly what this inclusion would add to our definition.

Though we agree with much of what Reich says, for example about the role of bodies and reflexivity in ethnographic work, the idea of positionality as a normative notion is problematic. At least since Gadamer wrote in the early 1960s (1988), it is clear that there are no interpretations ‘from nowhere.’ Who one is cannot be bracketed in an interpretation of what has occurred. The scientific value of this more identity- and positionality-oriented research that accounts also of the positionality of the interpreter, is essentially already well acknowledged. Reflection is not just something that qualitative researcher do; it is a general aspect of research. Ethnographic researchers may need certain skills to get close and understand the phenomenon they study, yet they also need to maintain distance. As Fine and Hallett write: “The ethnographic stranger is uniquely positioned to be a broker in connecting the field with the academy, bringing the site into theory and, perhaps, permitting the academy to consider joint action with previously distant actors” (Fine and Hallett 2014 , 195). Moreover, Brown-Saracino illustrates well what it means to get close, and we too see that ethnography, in various forms and ways, is useful as other qualitative activities. Though ethnographic research cannot be quantitative, qualitative work is broader than solely ethnographic research. Furthermore, reflexivity is not something that one has to do when doing qualitative research, but something one does as a researcher.

Reich’s second point is more important. The claim is that if the standpoint-oriented argument is completely accepted, it will most likely violate what we see as the essence of research. We warned in our article that qualitative research may be treated as less scientific than quantitative within academia, but also in the general public, if too many in academia claim to be doing “qualitative research” while they are in fact telling stories, engaging in activism, or writing like journalists. Such approaches are extra problematic if only some people with certain characteristics are viewed as the only legitimate producers of certain types of knowledge. If these tendencies are fueled, it is not merely the definition of “qualitative” that is at stake, but what the great majority see as research in general. Science cannot reach “The Truth,” but if one gives up the idea communal and universal nature of scientific knowledge production and even a pragmatic notion of truth, much of its value and rationale of science as an independent sphere in society is lost (Merton 1973 ; Weber 1985 ). Ralf Dahrendorf framed this form of publicness by writing that: “Science is always a concert, a contrapuntal chorus of the many who are engaged in it. Insofar as truth exists at all, it exists not as a possession of the individual scholar, but as the net result of scientific interchange” (1968, 242–3). The issue of knowledge is a serious matter, but it is also another debate which relates to social sciences being low consensus fields (Collins 1994 ; Fuchs 1992 ; Parker and Corte 2017 , 276) in which the proliferation of journals and lack of agreement about common definitions, research methods, and interpretations of data contributes to knowledge fragmentation. To abandon the idea of community may also cause confusion, and piecemeal contributions while affording academics a means to communicate with a restricted in-group who speak their own small language and share their views among others of the same tribe, but without neither the risk nor possibility of gaining general public recognition. In contrast, we see knowledge as something public, that, ideal-typically, “can be seen and heard by everybody” (Arendt 1988 , 50), reflecting a pragmatic consensual approach to knowledge, but with this argument we are way beyond the theme of our article.

Our concern with qualitative research was triggered by the external critique of what is qualitative research and current debates in social science. Our definition, which deliberately tries to avoid making the use of a specific method or technique the essence of qualitative, can be used as a point of reference. In all the replies by Brown-Saracino, Lichterman, Reich, and Small, several examples of practices that are in line with our definition are given. Thus, the definition can be used to understand the practice of research, but it would also allow researchers to deliberately deviate from it and develop it. We are happy to see that all commentators have used our definition to move further, and in this pragmatic way the definition has already proved its value.

New research should be devoted to delineating standards and measures of evaluation for different kinds of work such as the those we have identified above: theoretical, descriptive, evocative, political, or aimed at social change (see Brady and Collier 2004; Ragin et al. 2004 ; Van Maanen 2011 ). And those standards could respectively be based upon scientific or stylistic advancement and social and societal impact. Footnote 1 Different work should be evaluated in relation to their respective canons, goals, and audiences, and there is certainly much to gain from learning from other perspectives. Relatedly, being fully aware of the research logics of both qualitative and quantitative traditions (Small 2005 ) is also an advantage for improving both of them and to spur further collaboration. Bringing further clarity on these points will ultimately improve different traditions, foster creativity potentially leading to innovative projects, and be useful both to younger researchers and established scholars.

The last two terms refer to whether the impacts are more micro as related to agency, or macro, as related to structural changes. An example of the latter kind is Matthew Desmond’s Eviction (2016) having substantial societal impact on public policy discussions, raising and researching a broader range of housing issues in the US. A case of the former is Arlie Hochchild’s studies on emotional labor of women in the workplace (1983) and her more recent book on the alienation of white, working-class Americans (2016).

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Acknowledgements

The authors are grateful for comments by Gary Alan Fine, Jukka Gronow, and John Parker.

Open access funding provided by University of St. Gallen. The research reported here is funded by University of St. Gallen, Switzerland and University of Stavanger, Norway.

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Aspers, P., Corte, U. What is Qualitative in Research. Qual Sociol 44 , 599–608 (2021). https://doi.org/10.1007/s11133-021-09497-w

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Accepted : 12 October 2021

Published : 28 October 2021

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DOI : https://doi.org/10.1007/s11133-021-09497-w

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The contribution of case study research to knowledge of how to improve quality of care

Efforts to improve the implementation of effective practice and to speed up improvements in quality and patient safety continue to pose challenges for researchers and policy makers. Organisational research, and, in particular, case studies of quality improvement, offer methods to improve understanding of the role of organisational and microsystem contexts for improving care and the development of theories which might guide improvement strategies.

This paper reviews examples of such research and details the methodological issues in constructing and analysing case studies. Case study research typically collects a wide array of data from interviews, documents and other sources.

Advances in methods for coding and analysing these data are improving the quality of reports from these studies.

The gap between the knowledge of what works and the widespread adoption of those practices has become a major preoccupation of researchers and a challenge for funders and policy makers. 1–3 Recognition of this ‘quality chasm’ (the term that the US Institute of Medicine used to describe the distance ‘between the healthcare we have and the care we could have’ 4 ) has led to an increased focus on quality improvement and implementation science to advance understanding of how to promote evidence-based practice. In turn, the focus on implementation has led to the development of multiple theories and frameworks to guide implementation, 5–7 but no framework has demonstrated widespread results in practice.

There seems to be no immutable formula for successful implementation of innovations. While rational decision-makers would like the effectiveness of new technologies (including new work routines, devices and medications) to be the primary determinant of their adoption, research suggests otherwise. Healthcare systems are complex and variable. While some teams or organisations provide a ‘receptive context’ for innovation, 8 others resist, having limited interest or abilities to implement new ideas. Decades of research in organisational and social sciences suggest that the nature of the innovation and the organisational, professional and health system contexts into which they are introduced influence their adoption. 7 9–11 Thus, creating more effective, evidence-based care relies not just on developing and disseminating the evidence, but also on building knowledge of the ways in which innovations can be embedded into ongoing practice. Understanding the structures and processes of change is as critical as the knowledge of what works. In this paper, we outline how case study research can contribute a more detailed understanding of how to improve care. Case study methods are underutilised in quality improvement research, and given the growing calls to understand how innovation works in different contexts 12–14 these methods could be a valuable addition to current approaches. We begin by illustrating the insights from case study research, and then examine the contribution of case study research to theory. Next we discuss strategies for analysing case study data and the scientific soundness of such information, ending with a discussion of the need for case studies to enhance the scientific understanding of quality improvement.

Insights from case study research

Three examples of how qualitative organisational research informs our understanding of the adoption of healthcare innovations illustrate the value of this research. Denis and colleagues 15 studied the adoption of four innovations in several Quebec hospitals. They found that the strength of evidence of the innovation was not the only factor influencing adoption. Organisational arrangements, clinical skills and other more ambiguous elements that were open to interpretation and negotiation were also critical. In another study examining innovations in acute care and primary care settings in the UK, Ferlie 16 identified the critical role of boundaries between professional groups. Unlike some prior studies where high levels of professionalisation facilitated adoption of innovations, Ferlie's research found that the varying roles, social boundaries and distinctive cognitive styles of different professional groups can limit the adoption of new technologies. For example, the introduction of an anticoagulation service was slowed by disagreements between cardiologists, primary care physicians, nurses and IT system designers about the appropriate indications for treatment.

The adoption of minimally invasive cardiac surgery for coronary artery bypass graft or valve replacement surgery in 16 US hospitals provides a third example. Edmondson and colleagues 17 found that successful implementation depended on team learning processes rather than resources, academic status or innovation history. Innovative procedures like minimally invasive cardiac surgery disrupt established work routines. Establishing the necessary new routines for minimally invasive cardiac surgery depended on staff perceptions of psychological safety (the sense that ‘well-intentioned interpersonal risks will not be punished’), team stability and a collective learning process supported by leaders.

Each of these research projects used case study methods to identify the novel aspects of the process of implementing innovation. The research teams collected and analysed data from interviews, clinical data and documents. These research projects examined individuals or teams in context; they were embedded multiple case designs. 18 Although the researchers had detailed knowledge of potentially relevant factors, these were primarily exploratory studies, examining which aspects of the innovation, the individuals and teams and the larger organisations influenced the adoption of the innovation.

The case study methods used in these three studies offer valuable tools in exploring the effectiveness of quality improvement more broadly. While case study research is a well-established method in organisational research, it appears to be less common in organisational health services research. Case study research designs involve the collection of qualitative (and often quantitative) data from various sources to explore one or more organisations or parts of organisations and the characteristics of these contexts. 19 Some criticise case study research because they believe that the small sample size and lack of controls undermine the ability to generalise, 20 while others worry that the analysis of case study data is often unsystematic. 21 Yet case studies, because they detail specific experiences in particular contexts, offer the opportunity to learn more about the relationship of organisational processes and context to the success or failure of quality improvement efforts.

Contributions of case studies to theory

Case studies can inform the development of more robust theory that identifies the links between problem, intervention and outcome. Robert Yin, in his classic book, 22 notes that case study research is particularly helpful when researchers want to answer questions of how or why things work in real life contexts. Theory generated from cases may help to make sense of the complex relationships that underline healthcare practice and elucidate why efforts to improve care succeed in some circumstances, but not in others.

Christensen and Carlile 23 note that theory building (the creation of a ‘body of knowledge’ or understanding) occurs in two ways or stages; first there is a descriptive or inductive stage where researchers observe phenomena and describe and measure what they see (see figure 1 ). Based on these observations, researchers develop constructs that abstract the essence of what has been observed, classify or categorise these observations, and identify relationships between them. Through these activities, researchers develop theories or models which organise the aspects of the world they study. Second, in a deductive process, researchers test and improve these theories by exploring whether the same correlations exist in different data sets. This hypothesis testing allows the theory to be confirmed or rejected, and it also permits further specification of the theory to define the phenomena more precisely or specify the circumstances under which correlations hold. Where the goal of research is discovery or new explanations, case studies may offer a more powerful research design than experimental methods. 24 25

Process of building theory.

Edmondson and McManus 26 add to Christensen and Carlile's outline of the process of theory building and testing by identifying the importance of ‘methodological fit’ between theory building and different research methods. They suggest the appropriateness of different types of data varies depending on the research questions posed, the current state of the literature and the contribution envisaged from the research. Qualitative data, including interviews, observation and document analysis, are most appropriate for research where theory is nascent, and the research questions are exploratory. On the other hand, where theory is mature, survey methods and statistical testing focused on confirmation of hypotheses are more appropriate.

Organisational case studies have been an effective way to build theory in organisational research. 18 Eisenhardt and Graebner 27 note that ‘[a] major reason for the popularity and relevance of theory building from case studies is that it is one of the best (if not the best) of the bridges from rich qualitative evidence to mainstream deductive research. Its emphasis on developing constructs, measures and testable theoretical propositions makes inductive case research consistent with the emphasis on testable theory within mainstream deductive research.’ Some authors 28 argue that single case studies provide more detail and offer ‘better stories’ which are helpful in describing phenomena. But others assert that multiple case studies provide a stronger base for theory building. 22 27 Multiple case studies are powerful, since they permit replication and extension among individual cases. Replication enables a researcher to perceive the patterns in the cases more easily and to separate out patterns from change occurrences. Different cases can emphasise varying aspects of a phenomenon and enable researchers to develop a fuller theory. Fitzgerald and Dopson 19 identify four common types of multiple case study designs, each based on a different logic. These include (1) matching or replication designs intended to explore or verify ideas; (2) comparison of differences, including cases selected for their different characteristics; (3) outliers, comparison of extremes to delineate key factors and the shape of a field; and (4) embedded case study designs where multiple units are examined to identify similarities and differences.

Despite growing numbers of studies on quality improvement in healthcare, there is limited growth in a more general theory about improvement. For example, there is a growing view that improvement interventions should be tailored to potential barriers. Yet, as Bosch notes, 29 in many cases it is difficult to assess whether such tailoring was done based on a priori barrier identification, and explicit use of theory to match the intervention to the identified barriers. Bosch adds that ‘the translation of identified barriers into tailor-made [quality improvement] interventions [and their] implementation is still a black box for both educational and organisational interventions’ (p. 161). Case studies might contribute useful information to develop relevant theory. More broadly, case study research provides methods to examine organisational processes over time, examining the interplay of interventions with team dynamics or leadership strategy. For example, studies by Baker 30 and Bate 31 of high-performing healthcare organisations illustrate the challenges of creating, spreading and sustaining effective practice in organisations. Some case study research has followed organisations over extended time periods repeating interviews with key informants (eg, Denis' work on strategic change 40 41 ). Unlike survey research and RCTs, case study research can analyse the process of implementation and unpack the dynamics of change.

Data collection and analysis

Organisational case studies can include a wide array of data, including interviews, documents, ethnography, survey data and observations. Although the case study is generally viewed as a qualitative method, it may include quantitative data. For example, Greenhalgh's study of the impact of ‘modernisation initiatives’ of the delivery of care in London 42 used a wide range of methods and data, including interviews, document analysis and ethnography. Other organisational case study research 17 32 40 43 has adopted a similar mix of data sources.

Case study research typically generates large quantities of data, which makes analysis critical, but complex. Moreover, the methods for aggregating data across projects are not well developed. Coffey and Atkinson note that the use of coding and sorting, and the identification of themes are ‘an important, even an indispensable, part of the qualitative research process.’ 44 Yet, there are challenges to such methods, since coding individual experiences can lead to ‘decontextualisation,’ fragmenting such meanings and making them difficult to identify. 45 These problems are accentuated in multiple cases where results may reflect differences between the methods used, or the interests and orientation of various researchers. Even within the same research project, different investigators may take the lead in different cases. Dopson adds several other considerations about chronology: ‘Were the studies synchronous? Were they prospective or retrospective? Were they longitudinal or cross-sectional? How variable were the political and organisational contexts?’ (p. 6). 32 Multiple case studies are difficult to report, given the space constraints for journal publication, 27 and the use of extensive tables risks mimicking the presentation of quantitative data, stripping the illustrative detail from the case presentations. 19

Synthesis across studies can help to build a more generalisable understanding of organisational strategies to support improvement. Yet views vary on whether we can synthesise research from multiple case studies undertaken independently. In their review of studies examining efforts to integrate evidence into clinical decision-making in UK healthcare, Dopson and colleagues 32 compared and synthesised their findings reanalysing the original studies to identify themes, recoding their reports and then assessing the outputs generated by the five researchers involved (see table 1 ). Such tables offer a bird's-eye view of the extent to which common themes inform different case studies, but such summaries are divorced from understanding how these issues are inter-related within each case.

Identifying research themes across studies of innovation diffusion 32

1, Theme is present; 2, strong evidence of theme; 3, very strong evidence of presence.

Methodological rigour

Efforts to create such syntheses raise issues about methodological rigour. For those researchers who adopt a positivist framework, the test of good case studies builds on four criteria used to assess the rigour of field research: internal validity, construct validity, external validity and reliability. 22 These criteria might be applied to case studies in the following ways (see table 2 ).

Framework for an investigation of the methodological rigour of case studies 40

Gibbert and colleagues 46 reviewed case studies published in the organisation/management literature between 1995 and 2000. They found research procedures enhancing external validity in 82 of 159 papers, and procedures supporting reliability in 27 of these papers. Few papers provided evidence of internal or construct validity. Yin proposes pattern matching; explanation building; addressing rival explanations and using logic models as strategies to address internal validity. 22 Eisenhardt offers a series of questions that reflect on the match between method and results: ‘Have the investigators followed a careful analytical procedure? Does the evidence support the theory? Have the investigators ruled out rival explanations?’ 18 (p. 548). Non-positivist researchers employ other methods to ensure the soundness of their findings; for example, see Lincoln and Guba. 47

An alternative measure of the rigour of case study research focuses on how good the theory is that emerges from this research. Pfeffer 48 suggests that good theory is parsimonious, testable and logically coherent. Good theory should also address critical issues of interest to organisations and interested parties. Insights from other disciplines and attempts to seek out anomalies in other authors' work that might inform research in different areas are other strategies that may enrich the quality of case study research, improving the theory that results. 48

Despite the need for more robust theory, why are there so few organisational case studies of quality improvement? Some candidate explanations might include: (1) the limited number of organisational scholars working in this area; (2) the dominance of alternative research paradigms that dismiss case study research; (3) difficulties in securing funding; (4) the lack of publication outlets; and (5) the absence of a clear understanding of the relationship of case study research to the development of theory, and the testing of theory using randomised control trials and other methods. Still, the emergence of several strong research groups in the UK, Canada and the USA, and growing numbers of high-quality publications offer hope. What is missing in quality improvement research is a clear understanding of how case study research could contribute to the broader research enterprise, enriching the qualitative understanding of the complex processes of improving healthcare delivery.

Conclusions

Comparative case study research provides useful methods for identifying the factors facilitating and impeding improvement. Although valuable in their own right, such methods also offer the opportunity to enrich more traditional approaches to assessing interventions, helping to explain why some interventions are unsuccessful, or why they seem to work effectively in some contexts but not in others. Efforts to improve patient safety and quality of care need to take into account the complexities of the systems in which these improvements are being introduced. Case study methods provide a robust means to guide implementation of effective practices.

Competing interests: None.

Provenance and peer review: Not commissioned; externally peer reviewed.

Contributions of qualitative research to evidence-based practice in nursing

Affiliation.

• 1 College of Nursing and Health Science, George Mason University. [email protected]
• PMID: 12958629
• DOI: 10.1590/s0104-11692003000300002

Aim: This article aims to identify the contributions of qualitative research to evidence-based practice in nursing.

Background: Qualitative research dates back to the 1920s and 1930s, when anthropologists and sociologists used qualitative research methods to study human phenomena in naturalistic settings and from a holistic viewpoint. Afterwards, other subject matters, including nursing, adopted qualitative methods to answer their research questions. The restructuring of health care over the past decade has brought about increased accountability in nursing research. One method for increasing this accountability is evidence-based practice.

Method: The method used was a search in the Cumulative Index to Nursing and Allied Health Literature database from 1999-present. The search resulted in 61 citations for evidence-based practice in nursing research; however, only 5 citations focused on evidence-based practice and qualitative research.

Findings: The authors' findings revealed six contributions of qualitative research to evidence-based practice: generation of hypotheses; development and validation of instruments; provision of context for evaluation; development of nursing interventions; development of new research questions; and application of Qualitative Outcome Analysis.

Conclusion: Qualitative research makes important contributions to the quality of evidence-based practice.

Publication types

• Evidence-Based Medicine*
• Nursing Process*
• Nursing Research*

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Contributions of qualitative research to the knowledge base of normal communication Journal Article

Cu boulder authors.

• Damico, Jack S

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• May 1, 2003

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• Behavior - Communication
• Behavior and Behavior Mechanisms - Human Development
• Cooperative Behavior
• Growth and Development - Human Development
• Information Science - Communication
• Qualitative Research
• Social Behavior
• Speech-Language Pathology

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Date in cu experts.

• September 23, 2019 11:58 AM

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• Simmons-Mackie NN; Damico JS

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• American Journal of Speech-Language Pathology  

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• https://doi.org/10.1044/1058-0360(2003/061)

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Contributions of qualitative research to the knowledge base of normal communication

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