purpose of embedded case study

Embedded Case Study Methods. Integrating Quantitative and Qualitative Knowledge

International Journal of Sustainability in Higher Education

ISSN : 1467-6370

Article publication date: 1 July 2006

Case studies
Qualitative methods

Burger, P. (2006), "Embedded Case Study Methods. Integrating Quantitative and Qualitative Knowledge", International Journal of Sustainability in Higher Education , Vol. 7 No. 3, pp. 352-356. https://doi.org/10.1108/14676370610677892

Emerald Group Publishing Limited

Project courses, case studies, as well as problem‐based learning (PBL) are well‐established didactic means within academic and non‐academic education. PBL, for example, is said to enhance student's learning skills in working cooperatively in groups to seek solutions to real world problems ( Duch, 2001 ). Frey (1993) has proved and compared their learning effectiveness. Accordingly, Scholz and Tietje are able to refer to a number of disciplines with experience in case studies (Chapter 3). Moreover, within academic training in the domain of sustainability science (science understood in the broader non‐Anglo‐Saxon sense of academic endeavours in general) group work, projects and case studies have been looked upon as promising instruments for the special kind of scientific training committed to inter‐ and transdisciplinary scientific practice from the very beginning. In accordance with the variety of what has been subsumed under “inter‐ and transdisciplinary” however, actual educational practice encompasses a heterogeneous set of project‐oriented courses until recently. On the one end of the option continuum there are advocates of a primarily experience‐oriented approach, focussing on practical skills such as communication with actors without using specific scientific, integrative methods (or even more radical: by denying that there are specific integrative methods at hand). At the other extreme there are proponents of project type courses that are primarily oriented towards applying classic (in general disciplinary) methods on a specific subject (for example, modelling the distribution of specific pollutants within the atmosphere). What makes Roland Scholz and Olaf Tietje's book on “Embedded Case Study Methods” a breakthrough is, that it allows avoiding the sketched choice between Scylla and Charybdis. They have formed a basis for a methodologically oriented academic training in case a curriculum contains learning objectives in regard of transdisciplinary‐oriented scientific practice.

As the book title makes clear, there is no point in talking of a method. What the book presents are descriptions of a set of different methods in addition with reflections and proposals how to fit them together. Accordingly, the book does not offer a recipe, but describes methods being in need for adaptation to a given teaching situation. They may be viewed as providing tools regarding specific goals in setting for scientific sustainability education, such as that you want to deal scientifically with “ill‐defined problems” (initial state is not precisely described, target is not sufficiently known, p. 26), that you want to contribute to possible options for handling the problem in question, that you intend to co‐operate with societal actors and to integrate them into the case study (to accept them as subjects within the process, not only as objects of enquiry), and, finally, that you will have a population of students with enough skills and motivation to successfully work within such a setting.

“imported or adapted scientific methods”;

“core area methods”;

“participation tools”; and

“management rules”.

the specific knowledge desiderata and the respective appropriateness of the methods (p. 72); and

the trade off between the specific scientific point of view and the total study team point of view, the latter of course including also societal actors (p. 74).

Innovative and most interesting are the elements within the second group (core area methods). On the one hand the total setting may be said to be a method itself. The setting presupposes the forming up of a transdisciplinary study team, consisting of societal actors and scientists sharing responsibility for the whole process. The existing time resources will normally not allow to include the students from the very beginning and to let them participate in the process of question forming. Thus, students will become part of the team only after the case study team has already been formed. On the other hand the setting involves what may be viewed as the core method of the embedded case study approach, a qualitative scenario analysis (formative scenario analysis). Neither scenario analysis nor the underlying system modelling is really new. There are, however, special features introduced by Scholz and Tietje. Firstly, a computer program has been developed to support both system modelling as well as scenario building. Secondly, the impact matrix represents a qualitative view on the system. Although there may exist well‐founded data and differential equation to calculate the impact of the variables in question, the impact measurement is done qualitatively using a scale from 0 to 5. Thirdly, the same is true for scenario building and its consistency analysis. Fourthly, stakeholders and scientific experts are involved. The system model as well as proposed scenarios are not only assessed but also controlled with respect to their adequacy (Are the chosen impact factors relevant? Does impact estimation correspond to experience or to expertise? Do scenarios look like being at least intuitively consistent?).

The rationale for this approach is quite obvious: If we need a better understanding of options for agents to act, we may represent these options as scenarios. Moreover, since scenarios allow for an assessment of their potential consequences, usefulness, etc. it becomes possible to arrange the traditional methods from group one around the formative scenario analysis with respect to their functional role. Although it will certainly never be the case that a student group will use them all within a single course, the setting provides the teacher with a structure adaptable to the specific case and situation.

The function and the necessity of the participation tools (third group) now also become evident. Participatory instruments are of importance in two respects. Firstly, you need them in order to build the study group. You have to define common guiding questions and goals and to define responsibilities. As far as I can see it, however, the authors understand that stage of the process as part of the case study team methods (e.g. belonging to group iv, see next section). Secondly, you need instruments on the one hand in order to deal with competing interests and on the other hand for constructing scenarios (or at least for defining concrete objectives) by the actors themselves. Accordingly, mediation and future workshops are described as instruments to deal with interests and goal forming, respectively. The book presents mediation as a kind of informed policy process. “Informed” thereby means that negotiation will be supported by case comprehension and assessment tools (such that it will not only be a bargaining, but also a mutual learning process). Additionally, Scholz and Tietje also describe the essentials of future workshop.

Finally, a case study needs structure (project architecture) and management, and hence management rules. If you want societal actors to take responsibility for the case study in question, e.g. for the teaching course it represents, you need more than classical project management instruments. Negotiations on guiding questions (and thus on the content of the case study) will be an important part of the project as well as feedback from stakeholders to student. Chapter 16 together with pp. 55‐60 provide information on structuring and managing such a project. As I already mentioned, management itself is not part of the student's duty, but part of the setting that enables the students to proceed.

The rationale of the Scholz and Tietje's approach is compelling. The formation of scenarios and their analytical evaluation as options for actions can be considered as masterpiece of sustainability science – at least if one is ready to understand sustainability science as means to shape and steer development processes by informed decision making, as I do. Master programs for sustainable development – now emerging at least within Europe in a number of places – without either some sort of embedded case study or an equivalent of it cannot be viewed as displaying the state of the art within higher education. That every teacher has to adopt the setting with respect to her boundary conditions (type of students and expertise – social or natural science or both – number of credit points available, teaching resources, etc.) goes without saying.

There are, however, at least two topics I would like to address in addition. On the one hand, we have to take into consideration at least two potential shortcomings of the approach. On the other hand, I want to scrutinize the availability of potential alternatives.

Let us start with the potential shortcomings. Firstly, the set of methods contains no tools concerning normative issues in sustainability settings (such as environmental ethics or, better, justice, for example). However, difficult it is to operationalize a notion such as intergenerational justice, there can be no doubt that it is a constitutive element of the sustainability concept. A MAUT cannot replace analytic approaches to just distribution of costs and benefits say in regional development processes. According to Grunwald and Lingner (2002, p. 72) it will not be possible to analyse and discuss conflict‐ridden sustainability issues relying but on integrated modelling and scenario building. They explicitly call for normative reflection in order to cope with different options to operationalize the sustainability concept and in order to make the implicit normative assumptions explicit. Moreover, neither MAUT nor the other assessment tools have the strength of the newly developed indicator systems for sustainable development. Although indicator systems certainly do have their weaknesses on their own, they also represent a type of knowledge integration and they become more and more established. In addition, there are economic tools such as cost‐benefit analysis, willingness to pay, etc. Hence, the appropriate assessment tool must be selected, and students within the domain of sustainability should also learn to handle the different options available.

Secondly, viewed from a more social science point of view, some important tools for actor analysis are lacking within the setting. There are many ingredients (such as the agents mind maps, attitudes, expectations, etc.), which researchers or students may use for an actor analysis, but some important methods are missing. Imagine a democratically legitimized group searching for a balancing of interests on a specific topic. Although democracy cannot prevent decision‐making biases based on stakeholder interests, the agents do have more or less well‐defined means such as pressure, public opinion, etc. in order to search for optimized proposals. Democracy has demonstrated to be relatively successful in weighting interests. Now imagine a stakeholder group as part of a case study team. The challenge within this setting is whether the agents will necessarily act the same way within such a case study situation as they would within a real decision making situation. Yes, it may be the case. But, based on what is known as attitude‐acting‐gap, actors within a case study team may abstract from their normal institutional surroundings, i.e. from their normal institutional restrictions. They may act unrealistically. Accordingly, it may be potentially misleading for students to claim that such transdisciplinary case studies (projects) allow per se minimising interest biases by its very setting.

The social sciences know a number of instruments such as qualitative interviews, discourse analysis or structural analysis of social interactions to cope with the sketched potential gap. How they can become integrated in the setting is an open question. Renn (2002) points to other tools from the social sciences to become potentially integrated in modelling and in scenario technique as well. He mentions the consideration of social reaction patterns, the back‐casting variation of scenarios, the analysis of organisational structures and research on participation and governance. Again, I have to concede that we still have to consider on how to integrate these tools from the social science into the specific teaching setting of an embedded case study.

Notwithstanding the sketched problems, Scholz and Tietje gave the scientific community interested in teaching sustainability together with a transdisciplinary approach an important, powerful tool for project courses. Are there any alternatives on the market? Imagine you get the task and the money to accompany a local agenda 21‐process scientifically. You intend to involve your students. What options do you have? Your students will be in need to model the system in question. They will probably not develop scenarios because the local people engaged in the LA21 will already have them constructed. However, they will look for assessment tools in order to evaluate the scenarios. They will also cooperate with the local people. It may be the case that the management setting will be different from the one preferred by Scholz and Tietje. But most of the tools presented within the book are quite appropriate even in what seems to be quite a different situation.

In other words: there are no real substantial alternatives on the market. Given the goals I mentioned at the beginning, the book represents the state of the art. I take it to be a challenge, however, how the tool, especially the scenario analysis, can become adapted to or enriched by tools from the social sciences and hope that colleagues from theses disciplines will also pick up that challenge.

Duch , B.J. , Groh , S.E. and Allen , D.E. (Eds) ( 2001 ), The Power of Problem‐based Learning , Stylus Publishing LLC , Sterling, VA .

Frey , K. and Frey‐Eiling , A. ( 1993 ), Zürich , Allgemeine Didaktik. 6. Auflage, Verlag der Fachvereine an den schweizerischen Hochschulen und Techniken.

Grunwald , A. and Lingner , St. ( 2002 ), “ Nachhaltigkeit und integrative Modellierung ”, in Gethmann , C.F. and Lingner , S. (Eds), Intergrative Modellierung zum Globalen Wandel , Springer , Berlin , pp. 71 ‐ 106 .

Renn , O. ( 2002 ), “ Die Rolle der Sozialwissenschaften für die globale Umweltforschung ”, in Gethmann , C.F. and Lingner , S. (Eds), Intergrative Modellierung zum Globalen Wandel , Springer , Berlin , pp. 53 ‐ 67 .

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"This is an excellent book that serves an important purpose. It should become a valuable resource in research methods courses covering issues of case research. Doctoral students especially, should find the book particularly helpful. The conceptual material and methods of knowledge integration presented in this book provide scholars with the background and tools necessary to conduct case studies that meet the field's most rigorous scientific standards."

This book should be required reading for anyone involved with case study analysis.

This is a bold contribution to case study methodology, perhaps more suitable for postgraduate student considering a mixed methods approach, or a research team collaborating on a new type of project. Scholz and team introduce the transdisciplinary case study approach (TCS), which they developed at the Swiss Federal Institute of Technology (ETH). There are case studies from 5 different disciplines: neuropsychology, education, law, business, and environmental sciences. An excellent guide for any researcher contemplating a trans-disciplinary or complex case study.

The book is at the forefront of assessing good case study approaches, how they can be managed, and the conditions under which they are effective. The book makes academics aware of useful theories to explore ways in which case studies can be useful.

This is a wonderfully in-depth reference for case study research. It does a fine job of presenting the analytic nature of case study research, which is suitable for doctoral level study.

This title is also available on SAGE Research Methods , the ultimate digital methods library. If your library doesn’t have access, ask your librarian to start a trial .

The Advantages and Limitations of Single Case Study Analysis

As Andrew Bennett and Colin Elman have recently noted, qualitative research methods presently enjoy “an almost unprecedented popularity and vitality… in the international relations sub-field”, such that they are now “indisputably prominent, if not pre-eminent” (2010: 499). This is, they suggest, due in no small part to the considerable advantages that case study methods in particular have to offer in studying the “complex and relatively unstructured and infrequent phenomena that lie at the heart of the subfield” (Bennett and Elman, 2007: 171). Using selected examples from within the International Relations literature[1], this paper aims to provide a brief overview of the main principles and distinctive advantages and limitations of single case study analysis. Divided into three inter-related sections, the paper therefore begins by first identifying the underlying principles that serve to constitute the case study as a particular research strategy, noting the somewhat contested nature of the approach in ontological, epistemological, and methodological terms. The second part then looks to the principal single case study types and their associated advantages, including those from within the recent ‘third generation’ of qualitative International Relations (IR) research. The final section of the paper then discusses the most commonly articulated limitations of single case studies; while accepting their susceptibility to criticism, it is however suggested that such weaknesses are somewhat exaggerated. The paper concludes that single case study analysis has a great deal to offer as a means of both understanding and explaining contemporary international relations.

The term ‘case study’, John Gerring has suggested, is “a definitional morass… Evidently, researchers have many different things in mind when they talk about case study research” (2006a: 17). It is possible, however, to distil some of the more commonly-agreed principles. One of the most prominent advocates of case study research, Robert Yin (2009: 14) defines it as “an empirical enquiry that investigates a contemporary phenomenon in depth and within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident”. What this definition usefully captures is that case studies are intended – unlike more superficial and generalising methods – to provide a level of detail and understanding, similar to the ethnographer Clifford Geertz’s (1973) notion of ‘thick description’, that allows for the thorough analysis of the complex and particularistic nature of distinct phenomena. Another frequently cited proponent of the approach, Robert Stake, notes that as a form of research the case study “is defined by interest in an individual case, not by the methods of inquiry used”, and that “the object of study is a specific, unique, bounded system” (2008: 443, 445). As such, three key points can be derived from this – respectively concerning issues of ontology, epistemology, and methodology – that are central to the principles of single case study research.

First, the vital notion of ‘boundedness’ when it comes to the particular unit of analysis means that defining principles should incorporate both the synchronic (spatial) and diachronic (temporal) elements of any so-called ‘case’. As Gerring puts it, a case study should be “an intensive study of a single unit… a spatially bounded phenomenon – e.g. a nation-state, revolution, political party, election, or person – observed at a single point in time or over some delimited period of time” (2004: 342). It is important to note, however, that – whereas Gerring refers to a single unit of analysis – it may be that attention also necessarily be given to particular sub-units. This points to the important difference between what Yin refers to as an ‘holistic’ case design, with a single unit of analysis, and an ’embedded’ case design with multiple units of analysis (Yin, 2009: 50-52). The former, for example, would examine only the overall nature of an international organization, whereas the latter would also look to specific departments, programmes, or policies etc.

Secondly, as Tim May notes of the case study approach, “even the most fervent advocates acknowledge that the term has entered into understandings with little specification or discussion of purpose and process” (2011: 220). One of the principal reasons for this, he argues, is the relationship between the use of case studies in social research and the differing epistemological traditions – positivist, interpretivist, and others – within which it has been utilised. Philosophy of science concerns are obviously a complex issue, and beyond the scope of much of this paper. That said, the issue of how it is that we know what we know – of whether or not a single independent reality exists of which we as researchers can seek to provide explanation – does lead us to an important distinction to be made between so-called idiographic and nomothetic case studies (Gerring, 2006b). The former refers to those which purport to explain only a single case, are concerned with particularisation, and hence are typically (although not exclusively) associated with more interpretivist approaches. The latter are those focused studies that reflect upon a larger population and are more concerned with generalisation, as is often so with more positivist approaches[2]. The importance of this distinction, and its relation to the advantages and limitations of single case study analysis, is returned to below.

Thirdly, in methodological terms, given that the case study has often been seen as more of an interpretivist and idiographic tool, it has also been associated with a distinctly qualitative approach (Bryman, 2009: 67-68). However, as Yin notes, case studies can – like all forms of social science research – be exploratory, descriptive, and/or explanatory in nature. It is “a common misconception”, he notes, “that the various research methods should be arrayed hierarchically… many social scientists still deeply believe that case studies are only appropriate for the exploratory phase of an investigation” (Yin, 2009: 6). If case studies can reliably perform any or all three of these roles – and given that their in-depth approach may also require multiple sources of data and the within-case triangulation of methods – then it becomes readily apparent that they should not be limited to only one research paradigm. Exploratory and descriptive studies usually tend toward the qualitative and inductive, whereas explanatory studies are more often quantitative and deductive (David and Sutton, 2011: 165-166). As such, the association of case study analysis with a qualitative approach is a “methodological affinity, not a definitional requirement” (Gerring, 2006a: 36). It is perhaps better to think of case studies as transparadigmatic; it is mistaken to assume single case study analysis to adhere exclusively to a qualitative methodology (or an interpretivist epistemology) even if it – or rather, practitioners of it – may be so inclined. By extension, this also implies that single case study analysis therefore remains an option for a multitude of IR theories and issue areas; it is how this can be put to researchers’ advantage that is the subject of the next section.

Having elucidated the defining principles of the single case study approach, the paper now turns to an overview of its main benefits. As noted above, a lack of consensus still exists within the wider social science literature on the principles and purposes – and by extension the advantages and limitations – of case study research. Given that this paper is directed towards the particular sub-field of International Relations, it suggests Bennett and Elman’s (2010) more discipline-specific understanding of contemporary case study methods as an analytical framework. It begins however, by discussing Harry Eckstein’s seminal (1975) contribution to the potential advantages of the case study approach within the wider social sciences.

Eckstein proposed a taxonomy which usefully identified what he considered to be the five most relevant types of case study. Firstly were so-called configurative-idiographic studies, distinctly interpretivist in orientation and predicated on the assumption that “one cannot attain prediction and control in the natural science sense, but only understanding ( verstehen )… subjective values and modes of cognition are crucial” (1975: 132). Eckstein’s own sceptical view was that any interpreter ‘simply’ considers a body of observations that are not self-explanatory and “without hard rules of interpretation, may discern in them any number of patterns that are more or less equally plausible” (1975: 134). Those of a more post-modernist bent, of course – sharing an “incredulity towards meta-narratives”, in Lyotard’s (1994: xxiv) evocative phrase – would instead suggest that this more free-form approach actually be advantageous in delving into the subtleties and particularities of individual cases.

Eckstein’s four other types of case study, meanwhile, promote a more nomothetic (and positivist) usage. As described, disciplined-configurative studies were essentially about the use of pre-existing general theories, with a case acting “passively, in the main, as a receptacle for putting theories to work” (Eckstein, 1975: 136). As opposed to the opportunity this presented primarily for theory application, Eckstein identified heuristic case studies as explicit theoretical stimulants – thus having instead the intended advantage of theory-building. So-called p lausibility probes entailed preliminary attempts to determine whether initial hypotheses should be considered sound enough to warrant more rigorous and extensive testing. Finally, and perhaps most notably, Eckstein then outlined the idea of crucial case studies , within which he also included the idea of ‘most-likely’ and ‘least-likely’ cases; the essential characteristic of crucial cases being their specific theory-testing function.

Whilst Eckstein’s was an early contribution to refining the case study approach, Yin’s (2009: 47-52) more recent delineation of possible single case designs similarly assigns them roles in the applying, testing, or building of theory, as well as in the study of unique cases[3]. As a subset of the latter, however, Jack Levy (2008) notes that the advantages of idiographic cases are actually twofold. Firstly, as inductive/descriptive cases – akin to Eckstein’s configurative-idiographic cases – whereby they are highly descriptive, lacking in an explicit theoretical framework and therefore taking the form of “total history”. Secondly, they can operate as theory-guided case studies, but ones that seek only to explain or interpret a single historical episode rather than generalise beyond the case. Not only does this therefore incorporate ‘single-outcome’ studies concerned with establishing causal inference (Gerring, 2006b), it also provides room for the more postmodern approaches within IR theory, such as discourse analysis, that may have developed a distinct methodology but do not seek traditional social scientific forms of explanation.

Applying specifically to the state of the field in contemporary IR, Bennett and Elman identify a ‘third generation’ of mainstream qualitative scholars – rooted in a pragmatic scientific realist epistemology and advocating a pluralistic approach to methodology – that have, over the last fifteen years, “revised or added to essentially every aspect of traditional case study research methods” (2010: 502). They identify ‘process tracing’ as having emerged from this as a central method of within-case analysis. As Bennett and Checkel observe, this carries the advantage of offering a methodologically rigorous “analysis of evidence on processes, sequences, and conjunctures of events within a case, for the purposes of either developing or testing hypotheses about causal mechanisms that might causally explain the case” (2012: 10).

Harnessing various methods, process tracing may entail the inductive use of evidence from within a case to develop explanatory hypotheses, and deductive examination of the observable implications of hypothesised causal mechanisms to test their explanatory capability[4]. It involves providing not only a coherent explanation of the key sequential steps in a hypothesised process, but also sensitivity to alternative explanations as well as potential biases in the available evidence (Bennett and Elman 2010: 503-504). John Owen (1994), for example, demonstrates the advantages of process tracing in analysing whether the causal factors underpinning democratic peace theory are – as liberalism suggests – not epiphenomenal, but variously normative, institutional, or some given combination of the two or other unexplained mechanism inherent to liberal states. Within-case process tracing has also been identified as advantageous in addressing the complexity of path-dependent explanations and critical junctures – as for example with the development of political regime types – and their constituent elements of causal possibility, contingency, closure, and constraint (Bennett and Elman, 2006b).

Bennett and Elman (2010: 505-506) also identify the advantages of single case studies that are implicitly comparative: deviant, most-likely, least-likely, and crucial cases. Of these, so-called deviant cases are those whose outcome does not fit with prior theoretical expectations or wider empirical patterns – again, the use of inductive process tracing has the advantage of potentially generating new hypotheses from these, either particular to that individual case or potentially generalisable to a broader population. A classic example here is that of post-independence India as an outlier to the standard modernisation theory of democratisation, which holds that higher levels of socio-economic development are typically required for the transition to, and consolidation of, democratic rule (Lipset, 1959; Diamond, 1992). Absent these factors, MacMillan’s single case study analysis (2008) suggests the particularistic importance of the British colonial heritage, the ideology and leadership of the Indian National Congress, and the size and heterogeneity of the federal state.

Most-likely cases, as per Eckstein above, are those in which a theory is to be considered likely to provide a good explanation if it is to have any application at all, whereas least-likely cases are ‘tough test’ ones in which the posited theory is unlikely to provide good explanation (Bennett and Elman, 2010: 505). Levy (2008) neatly refers to the inferential logic of the least-likely case as the ‘Sinatra inference’ – if a theory can make it here, it can make it anywhere. Conversely, if a theory cannot pass a most-likely case, it is seriously impugned. Single case analysis can therefore be valuable for the testing of theoretical propositions, provided that predictions are relatively precise and measurement error is low (Levy, 2008: 12-13). As Gerring rightly observes of this potential for falsification:

“a positivist orientation toward the work of social science militates toward a greater appreciation of the case study format, not a denigration of that format, as is usually supposed” (Gerring, 2007: 247, emphasis added).

In summary, the various forms of single case study analysis can – through the application of multiple qualitative and/or quantitative research methods – provide a nuanced, empirically-rich, holistic account of specific phenomena. This may be particularly appropriate for those phenomena that are simply less amenable to more superficial measures and tests (or indeed any substantive form of quantification) as well as those for which our reasons for understanding and/or explaining them are irreducibly subjective – as, for example, with many of the normative and ethical issues associated with the practice of international relations. From various epistemological and analytical standpoints, single case study analysis can incorporate both idiographic sui generis cases and, where the potential for generalisation may exist, nomothetic case studies suitable for the testing and building of causal hypotheses. Finally, it should not be ignored that a signal advantage of the case study – with particular relevance to international relations – also exists at a more practical rather than theoretical level. This is, as Eckstein noted, “that it is economical for all resources: money, manpower, time, effort… especially important, of course, if studies are inherently costly, as they are if units are complex collective individuals ” (1975: 149-150, emphasis added).

Limitations

Single case study analysis has, however, been subject to a number of criticisms, the most common of which concern the inter-related issues of methodological rigour, researcher subjectivity, and external validity. With regard to the first point, the prototypical view here is that of Zeev Maoz (2002: 164-165), who suggests that “the use of the case study absolves the author from any kind of methodological considerations. Case studies have become in many cases a synonym for freeform research where anything goes”. The absence of systematic procedures for case study research is something that Yin (2009: 14-15) sees as traditionally the greatest concern due to a relative absence of methodological guidelines. As the previous section suggests, this critique seems somewhat unfair; many contemporary case study practitioners – and representing various strands of IR theory – have increasingly sought to clarify and develop their methodological techniques and epistemological grounding (Bennett and Elman, 2010: 499-500).

A second issue, again also incorporating issues of construct validity, concerns that of the reliability and replicability of various forms of single case study analysis. This is usually tied to a broader critique of qualitative research methods as a whole. However, whereas the latter obviously tend toward an explicitly-acknowledged interpretive basis for meanings, reasons, and understandings:

“quantitative measures appear objective, but only so long as we don’t ask questions about where and how the data were produced… pure objectivity is not a meaningful concept if the goal is to measure intangibles [as] these concepts only exist because we can interpret them” (Berg and Lune, 2010: 340).

The question of researcher subjectivity is a valid one, and it may be intended only as a methodological critique of what are obviously less formalised and researcher-independent methods (Verschuren, 2003). Owen (1994) and Layne’s (1994) contradictory process tracing results of interdemocratic war-avoidance during the Anglo-American crisis of 1861 to 1863 – from liberal and realist standpoints respectively – are a useful example. However, it does also rest on certain assumptions that can raise deeper and potentially irreconcilable ontological and epistemological issues. There are, regardless, plenty such as Bent Flyvbjerg (2006: 237) who suggest that the case study contains no greater bias toward verification than other methods of inquiry, and that “on the contrary, experience indicates that the case study contains a greater bias toward falsification of preconceived notions than toward verification”.

The third and arguably most prominent critique of single case study analysis is the issue of external validity or generalisability. How is it that one case can reliably offer anything beyond the particular? “We always do better (or, in the extreme, no worse) with more observation as the basis of our generalization”, as King et al write; “in all social science research and all prediction, it is important that we be as explicit as possible about the degree of uncertainty that accompanies out prediction” (1994: 212). This is an unavoidably valid criticism. It may be that theories which pass a single crucial case study test, for example, require rare antecedent conditions and therefore actually have little explanatory range. These conditions may emerge more clearly, as Van Evera (1997: 51-54) notes, from large-N studies in which cases that lack them present themselves as outliers exhibiting a theory’s cause but without its predicted outcome. As with the case of Indian democratisation above, it would logically be preferable to conduct large-N analysis beforehand to identify that state’s non-representative nature in relation to the broader population.

There are, however, three important qualifiers to the argument about generalisation that deserve particular mention here. The first is that with regard to an idiographic single-outcome case study, as Eckstein notes, the criticism is “mitigated by the fact that its capability to do so [is] never claimed by its exponents; in fact it is often explicitly repudiated” (1975: 134). Criticism of generalisability is of little relevance when the intention is one of particularisation. A second qualifier relates to the difference between statistical and analytical generalisation; single case studies are clearly less appropriate for the former but arguably retain significant utility for the latter – the difference also between explanatory and exploratory, or theory-testing and theory-building, as discussed above. As Gerring puts it, “theory confirmation/disconfirmation is not the case study’s strong suit” (2004: 350). A third qualification relates to the issue of case selection. As Seawright and Gerring (2008) note, the generalisability of case studies can be increased by the strategic selection of cases. Representative or random samples may not be the most appropriate, given that they may not provide the richest insight (or indeed, that a random and unknown deviant case may appear). Instead, and properly used , atypical or extreme cases “often reveal more information because they activate more actors… and more basic mechanisms in the situation studied” (Flyvbjerg, 2006). Of course, this also points to the very serious limitation, as hinted at with the case of India above, that poor case selection may alternatively lead to overgeneralisation and/or grievous misunderstandings of the relationship between variables or processes (Bennett and Elman, 2006a: 460-463).

As Tim May (2011: 226) notes, “the goal for many proponents of case studies […] is to overcome dichotomies between generalizing and particularizing, quantitative and qualitative, deductive and inductive techniques”. Research aims should drive methodological choices, rather than narrow and dogmatic preconceived approaches. As demonstrated above, there are various advantages to both idiographic and nomothetic single case study analyses – notably the empirically-rich, context-specific, holistic accounts that they have to offer, and their contribution to theory-building and, to a lesser extent, that of theory-testing. Furthermore, while they do possess clear limitations, any research method involves necessary trade-offs; the inherent weaknesses of any one method, however, can potentially be offset by situating them within a broader, pluralistic mixed-method research strategy. Whether or not single case studies are used in this fashion, they clearly have a great deal to offer.

References

Bennett, A. and Checkel, J. T. (2012) ‘Process Tracing: From Philosophical Roots to Best Practice’, Simons Papers in Security and Development, No. 21/2012, School for International Studies, Simon Fraser University: Vancouver.

Bennett, A. and Elman, C. (2006a) ‘Qualitative Research: Recent Developments in Case Study Methods’, Annual Review of Political Science , 9, 455-476.

Bennett, A. and Elman, C. (2006b) ‘Complex Causal Relations and Case Study Methods: The Example of Path Dependence’, Political Analysis , 14, 3, 250-267.

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[1] The paper follows convention by differentiating between ‘International Relations’ as the academic discipline and ‘international relations’ as the subject of study.

[2] There is some similarity here with Stake’s (2008: 445-447) notion of intrinsic cases, those undertaken for a better understanding of the particular case, and instrumental ones that provide insight for the purposes of a wider external interest.

[3] These may be unique in the idiographic sense, or in nomothetic terms as an exception to the generalising suppositions of either probabilistic or deterministic theories (as per deviant cases, below).

[4] Although there are “philosophical hurdles to mount”, according to Bennett and Checkel, there exists no a priori reason as to why process tracing (as typically grounded in scientific realism) is fundamentally incompatible with various strands of positivism or interpretivism (2012: 18-19). By extension, it can therefore be incorporated by a range of contemporary mainstream IR theories.

— Written by: Ben Willis Written at: University of Plymouth Written for: David Brockington Date written: January 2013

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Section 2: Home
Developing the Quantitative Research Design
Qualitative Descriptive Design
Design and Development Research (DDR) For Instructional Design
Qualitative Narrative Inquiry Research
Action Research Resource
Case Study Design in an Applied Doctorate

Qualitative Research Designs

Case study design, using case study design in the applied doctoral experience (ade), applicability of case study design to applied problem of practice, case study design references.

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The field of qualitative research there are a number of research designs (also referred to as “traditions” or “genres”), including case study, phenomenology, narrative inquiry, action research, ethnography, grounded theory, as well as a number of critical genres including Feminist theory, indigenous research, critical race theory and cultural studies. The choice of research design is directly tied to and must be aligned with your research problem and purpose. As Bloomberg & Volpe (2019) explain:

Choice of research design is directly tied to research problem and purpose. As the researcher, you actively create the link among problem, purpose, and design through a process of reflecting on problem and purpose, focusing on researchable questions, and considering how to best address these questions. Thinking along these lines affords a research study methodological congruence (p. 38).

Case study is an in-depth exploration from multiple perspectives of a bounded social phenomenon, be this a social system such as a program, event, institution, organization, or community (Stake, 1995, 2005; Yin, 2018). Case study is employed across disciplines, including education, health care, social work, sociology, and organizational studies. The purpose is to generate understanding and deep insights to inform professional practice, policy development, and community or social action (Bloomberg 2018).

Yin (2018) and Stake (1995, 2005), two of the key proponents of case study methodology, use different terms to describe case studies. Yin categorizes case studies as exploratory or descriptive . The former is used to explore those situations in which the intervention being evaluated has no clear single set of outcomes. The latter is used to describe an intervention or phenomenon and the real-life context in which it occurred. Stake identifies case studies as intrinsic or instrumental , and he proposes that a primary distinction in designing case studies is between single and multiple (or collective) case study designs. A single case study may be an instrumental case study (research focuses on an issue or concern in one bounded case) or an intrinsic case study (the focus is on the case itself because the case presents a unique situation). A longitudinal case study design is chosen when the researcher seeks to examine the same single case at two or more different points in time or to capture trends over time. A multiple case study design is used when a researcher seeks to determine the prevalence or frequency of a particular phenomenon. This approach is useful when cases are used for purposes of a cross-case analysis in order to compare, contrast, and synthesize perspectives regarding the same issue. The focus is on the analysis of diverse cases to determine how these confirm the findings within or between cases, or call the findings into question.

Case study affords significant interaction with research participants, providing an in-depth picture of the phenomenon (Bloomberg & Volpe, 2019). Research is extensive, drawing on multiple methods of data collection, and involves multiple data sources. Triangulation is critical in attempting to obtain an in-depth understanding of the phenomenon under study and adds rigor, breadth, and depth to the study and provides corroborative evidence of the data obtained. Analysis of data can be holistic or embedded—that is, dealing with the whole or parts of the case (Yin, 2018). With multiple cases the typical analytic strategy is to provide detailed description of themes within each case (within-case analysis), followed by thematic analysis across cases (cross-case analysis), providing insights regarding how individual cases are comparable along important dimensions. Research culminates in the production of a detailed description of a setting and its participants, accompanied by an analysis of the data for themes or patterns (Stake, 1995, 2005; Yin, 2018). In addition to thick, rich description, the researcher’s interpretations, conclusions, and recommendations contribute to the reader’s overall understanding of the case study.

Analysis of findings should show that the researcher has attended to all the data, should address the most significant aspects of the case, and should demonstrate familiarity with the prevailing thinking and discourse about the topic. The goal of case study design (as with all qualitative designs) is not generalizability but rather transferability —that is, how (if at all) and in what ways understanding and knowledge can be applied in similar contexts and settings. The qualitative researcher attempts to address the issue of transferability by way of thick, rich description that will provide the basis for a case or cases to have relevance and potential application across a broader context.

Qualitative research methods ask the questions of "what" and "how" a phenomenon is understood in a real-life context (Bloomberg & Volpe, 2019). In the education field, qualitative research methods uncover educational experiences and practices because qualitative research allows the researcher to reveal new knowledge and understanding. Moreover, qualitative descriptive case studies describe, analyze and interpret events that explain the reasoning behind specific phenomena (Bloomberg, 2018). As such, case study design can be the foundation for a rigorous study within the Applied Doctoral Experience (ADE).

Case study design is an appropriate research design to consider when conceptualizing and conducting a dissertation research study that is based on an applied problem of practice with inherent real-life educational implications. Case study researchers study current, real-life cases that are in progress so that they can gather accurate information that is current. This fits well with the ADE program, as students are typically exploring a problem of practice. Because of the flexibility of the methods used, a descriptive design provides the researcher with the opportunity to choose data collection methods that are best suited to a practice-based research purpose, and can include individual interviews, focus groups, observation, surveys, and critical incident questionnaires. Methods are triangulated to contribute to the study’s trustworthiness. In selecting the set of data collection methods, it is important that the researcher carefully consider the alignment between research questions and the type of data that is needed to address these. Each data source is one piece of the “puzzle,” that contributes to the researcher’s holistic understanding of a phenomenon. The various strands of data are woven together holistically to promote a deeper understanding of the case and its application to an educationally-based problem of practice.

Research studies within the Applied Doctoral Experience (ADE) will be practical in nature and focus on problems and issues that inform educational practice. Many of the types of studies that fall within the ADE framework are exploratory, and align with case study design. Case study design fits very well with applied problems related to educational practice, as the following set of examples illustrate:

Elementary Bilingual Education Teachers’ Self-Efficacy in Teaching English Language Learners: A Qualitative Case Study

The problem to be addressed in the proposed study is that some elementary bilingual education teachers’ beliefs about their lack of preparedness to teach the English language may negatively impact the language proficiency skills of Hispanic ELLs (Ernst-Slavit & Wenger, 2016; Fuchs et al., 2018; Hoque, 2016). The purpose of the proposed qualitative descriptive case study was to explore the perspectives and experiences of elementary bilingual education teachers regarding their perceived lack of preparedness to teach the English language and how this may impact the language proficiency of Hispanic ELLs.

Exploring Minority Teachers Experiences Pertaining to their Value in Education: A Single Case Study of Teachers in New York City

The problem is that minority K-12 teachers are underrepresented in the United States, with research indicating that school leaders and teachers in schools that are populated mainly by black students, staffed mostly by white teachers who may be unprepared to deal with biases and stereotypes that are ingrained in schools (Egalite, Kisida, & Winters, 2015; Milligan & Howley, 2015). The purpose of this qualitative exploratory single case study was to develop a clearer understanding of minority teachers’ experiences concerning the under-representation of minority K-12 teachers in urban school districts in the United States since there are so few of them.

Exploring the Impact of an Urban Teacher Residency Program on Teachers’ Cultural Intelligence: A Qualitative Case Study

The problem to be addressed by this case study is that teacher candidates often report being unprepared and ill-equipped to effectively educate culturally diverse students (Skepple, 2015; Beutel, 2018). The purpose of this study was to explore and gain an in-depth understanding of the perceived impact of an urban teacher residency program in urban Iowa on teachers’ cultural competence using the cultural intelligence (CQ) framework (Earley & Ang, 2003).

Qualitative Case Study that Explores Self-Efficacy and Mentorship on Women in Academic Administrative Leadership Roles

The problem was that female school-level administrators might be less likely to experience mentorship, thereby potentially decreasing their self-efficacy (Bing & Smith, 2019; Brown, 2020; Grant, 2021). The purpose of this case study was to determine to what extent female school-level administrators in the United States who had a mentor have a sense of self-efficacy and to examine the relationship between mentorship and self-efficacy.

Suburban Teacher and Administrator Perceptions of Culturally Responsive Teaching to Promote Connectedness in Students of Color: A Qualitative Case Study

The problem to be addressed in this study is the racial discrimination experienced by students of color in suburban schools and the resulting negative school experience (Jara & Bloomsbury, 2020; Jones, 2019; Kohli et al., 2017; Wandix-White, 2020). The purpose of this case study is to explore how culturally responsive practices can counteract systemic racism and discrimination in suburban schools thereby meeting the needs of students of color by creating positive learning experiences.

As you can see, all of these studies were well suited to qualitative case study design. In each of these studies, the applied research problem and research purpose were clearly grounded in educational practice as well as directly aligned with qualitative case study methodology. In the Applied Doctoral Experience (ADE), you will be focused on addressing or resolving an educationally relevant research problem of practice. As such, your case study, with clear boundaries, will be one that centers on a real-life authentic problem in your field of practice that you believe is in need of resolution or improvement, and that the outcome thereof will be educationally valuable.

Bloomberg, L. D. (2018). Case study method. In B. B. Frey (Ed.), The SAGE Encyclopedia of educational research, measurement, and evaluation (pp. 237–239). SAGE. https://go.openathens.net/redirector/nu.edu?url=https%3A%2F%2Fmethods.sagepub.com%2FReference%2Fthe-sage-encyclopedia-of-educational-research-measurement-and-evaluation%2Fi4294.xml

Bloomberg, L. D. & Volpe, M. (2019). Completing your qualitative dissertation: A road map from beginning to end . (4th Ed.). SAGE.

Stake, R. E. (1995). The art of case study research. SAGE.

Stake, R. E. (2005). Qualitative case studies. In N. K. Denzin and Y. S. Lincoln (Eds.), The SAGE handbook of qualitative research (3rd ed., pp. 443–466). SAGE.

Yin, R. (2018). Case study research and applications: Designs and methods. SAGE.

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Marshall M, Davies H, Ward V, et al. Optimising the impact of health services research on the organisation and delivery of health services: a mixed-methods study. Southampton (UK): NIHR Journals Library; 2022 Feb. (Health and Social Care Delivery Research, No. 10.3.)

Optimising the impact of health services research on the organisation and delivery of health services: a mixed-methods study.

Chapter 5 embedding in practice: cross-case analysis.

Introduction

Chapter 4 presented case-by-case accounts of each of the embedded initiatives studied in depth in workstream 3. The four case study sites (Bridgetown, Coxheath, Porter and Evansville) were introduced, as were their embedded researchers (see Table 10 ). This chapter presents a more thorough cross-case comparison of these four initiatives, informed by the analytic discoveries of workstreams 1 and 2. Specifically, the analysis is guided by the idea that embedded initiatives can vary across three main dimensions: their intent, their structures and their processes (see Chapter 3 ).

Methods and analysis

The methods of data-gathering in the four case studies were set out in Chapter 4 (and are elaborated on further in Appendix 3 ). The data analysis for the cross-case examination outlined here took an interpretative and abductive approach to explore the themes and dynamics in the cases, using the structure developed from the literature review and scoping analysis laid out in Chapter 3 . An abductive approach seeks to combine inductive (grounded) data analysis with elements of more deductive (proposition-driven) analysis, with the goal of fostering close empirical–theoretical dialogue and, ultimately, proposition (theory) refinement. 174 Following Corbin and Strauss 176 and Clarke et al. , 177 standard coding processes are used to generate empirically induced codes and concepts, which are then systematically related back to the concepts and theories derived from the literature, to confirm, clarify and challenge these thematic concepts as a basis for empirically informed theoretical elaboration.

Presentation of findings

In presenting the cross-case analysis, we use the 10 subthemes identified in Chapter 3 that encapsulate the domains of attention required in designing and describing embedded research initiatives.

These subthemes are arranged under the three headings of ‘intent’, ‘structures’ and ‘processes’, and these overarching categories provide the ordering for the findings presented here, with subthemes as follows:

intent – intended outcomes, power dynamics
structures – scale, involvement, proximity, belonging
processes – functional activities, skills and expertise, relational roles, learning mechanisms.

The names and basic contours of the four cases were laid out in Chapter 4 (see Table 7 ). The individual embedded researchers are also described in Chapter 4 , and cross-referencing to Table 10 and the full list of interviewees, including other stakeholders, in Appendix 2 will be necessary to make sense of the findings presented here. Fuller case accounts, with extensive data, are presented in Report Supplementary Material 3 .

Findings 1: cross-case variations in intent

Intended outcomes

Analysing and comparing the case studies in terms of their intended outcomes demonstrated considerable variation between initiatives, and showed that the intended purpose and outcomes of a given initiative are likely to change over time. In all cases, there were important, but often subtle, changes in emphasis between producing knowledge, building capacity and enhancing reputation, which reflected broader transitions in the strategic priorities of NHS organisations and the evolving expertise of the embedded researchers.

Different partner organisations (NHS and university) and key actors (the embedded researcher, line managers, front-line staff) could hold divergent expectations about the purpose and intent of the initiatives. This was a potential source of tension as the researchers tried to meet the expected and preferred outcomes of various parties.

A strong example of this was when embedded researchers faced competing intentions from academic and clinical practice, in terms of which type of outputs were valued: research publications for university assessment or service-facing development outputs. In cases where the researcher had two sets of competing expectations and outputs, they sometimes found creative means to meet multiple requirements at the same event, for example raising the clinical trust profile while presenting to a wholly academic audience:

Interviewer: So, in terms of your week then, 2 days here, 3 days there, does it look like that in practice?

Victoria, embedded researcher, Porter: No [chuckling], no, because I would have only been doing that if I was rigid about it; because the reality is, that there’s always things going on in both organisations that you need to be at, and some of those events actually benefit both organisations and that’s great . . . it makes me happy because that way I can do a bit of both jobs in one afternoon . . . For example, I’m going up to [place] to present to [academic conference] in November. That really benefits the trust – I shall, you know, put the trust banner on my presentation, and it’s all kind of clinically relevant research, but I can also count that as academic work because it’s research, and research is part of my academic job as well . . . So, it has a double benefit.

Interviewer: It sounds like there’s still two sets of priorities then?

Victoria: Oh yeah, very different sets of priorities as well.

For senior NHS managers, the over-riding intention, in many cases, was capacity-building, specifically capacity-building that influenced patient care directly and delivered ‘real cultural change’. The researchers themselves shared similar intentions and were motivated by the potential to grow a research culture, change perceptions of research and ultimately improve staff and patient experience.

In this sense, there was sometimes a sense of superiority associated with the intentions of the embedded researcher, who had different expectations of their work to that of more ‘traditional’ academics:

I don’t want to be a full-time ivory tower academic [who] does research that’s philosophical or abstract or metaphysical or any of those kind of things. I wanted to do research that had some applied meaning, that would mean something to children and families. Victoria, embedded researcher, Porter

The evolving and sometimes competing intentions and motivations of initiatives could put pressure on the embedded researcher, with practical implications for workload and their personal capacity. Anna, the embedded researcher at Bridgetown, was aware of this from the outset, particularly in relation to the work associated with research capacity-building (a strong intention underpinning her NHS support network). She had learned from her predecessor, Jill, that, to influence large-scale change, her approach would need to adapt:

One of the things I learned from Jill’s experience of having done a similar role before, running grant-raising groups . . . [you develop] one or two people who go on to have great careers, but they have great careers from an academic standpoint so they, they move over, they cross that boundary . . . So it doesn’t break down the boundary, it just helps one or two people cross over, as opposed to changing the system and how it works and dismantling the boundary or creating different boundaries. Anna, embedded researcher, Bridgetown

Addressing and balancing multiple intended outcomes was central to these embedded research initiatives. Moreover, what was intended was not always explicit, fixed or even realistic, and the embedded researchers needed to pay close attention to the evolving discourses among partners and to be prepared to flex as appropriate.

Power dynamics

We observed how embedded researchers occupied an arguably unique space between clinical practice and academia. This often meant that the researcher must work across, and sometimes against, existing ‘silos’.

One of many implications of this was the distribution, and sometimes redistribution, of power and control, both for themselves and others. In some examples, such as those noted in the previous section, this redistribution of power and control was intentional; one aim of capacity-building was seen to be for front-line staff to gain more power and control to bring about change in services. There was a general sense that this change in dynamic was needed, although its far-reaching implications were possibly not always fully understood by those endorsing it, and, despite this widespread drive to empower front-line staff, researchers felt that organisational structures were not always ready for this change.

Jane in Coxheath, an experienced embedded researcher, offered her insights into ‘speaking truth to power’ – in this instance, that meaningful culture change (and power shifts) were unobtainable, being restricted by leadership styles and values:

Jane, embedded researcher, Coxheath: There’s no sign-up from the executive team, and the executive teams themselves don’t have the shared values . . . I try and help the organisation to recognise what they’ve got to do to support our front-line teams . . . If you look at [name] report, the [name] report culture is the most frequent work, but they’re talking about organisational culture, not microsystems and I don’t think our chief exec[utive] understands the difference or why one is more important than the other.

Interviewer 1: And the interplay between them?

Jane: Yeah, the interplay between . . . I don’t feel there’s anybody else supporting the microsystems side, so I have to exaggerate their importance to get people to listen.

Interviewer 2: You’re saying things that people necessarily don’t want to hear?

Interviewer 1: Yeah, you’re speaking the truth to power?

‘Speaking truth to power’, in some form, was an established part of the embedded researchers’ role, and the respondents all shared their varied experiences of being a ‘critical friend’. This required a strong interpersonal skill set, contextual understanding and sometimes diplomacy (see Skills and expertise ). It also required the embedded researcher to maintain professional objectivity and avoid ‘capture’ by the settings in which they were embedded.

For example, projects undertaken by the Evansville team regularly involved feeding back findings to senior NHS stakeholders. The tensions involved here were intensified for the researchers when findings were perceived as unexpected and sometimes uncomfortable. In these instances, the researchers shared how crucial it was to have senior support from outside the clinical setting, namely a senior academic to whom they could ‘diffuse’ responsibility when situations became difficult to manage:

I think that’s one of the big things around being an embedded researcher . . . all those relationships, but you need to constantly remind yourself that, you know, you are there to do a particular job. You are not like any other staff member within that organisation, you’re there as a researcher, and there is that kind of academic layer to the work that you’re doing, where you need to maintain that critical point really. Bella, embedded researcher, Evansville

Of course, power was not always addressed directly or raised overtly in the interviews and conversations during site observations. Nevertheless, issues of power – implicit, unspoken, frequently unacknowledged – ran through the data and are touched on in subsequent sections, especially those concerning proximity, belonging and relational roles. In that sense, power, like ideas of identity and boundaries (straddling, crossing, breaching or maintaining), suffused and cut across many of the meaning categories created in the review and scoping work of Chapter 3 .

Findings 2: cross-case variations in structures

The scale of the initiatives ranged from a single embedded researcher to an embedded team of up to five. Some schemes were bounded and time limited; others were more open, emergent and evolving. There were differences in terms of configuration too; for example, the Coxheath initiative was primarily configured and constructed around Jane as an individual, whereas Evansville was configured around an evolving portfolio of projects. Porter was different again, with an overarching strategic priority and focus to the configuration aimed at building research capacity and capability. The descriptive accounts in Chapter 4 outlined some of these differences in more depth.

Despite these differences, there was a sense that, in their timescales and overall life cycles, initiatives had identifiable stages of development: initially an incubation period, followed by formalisation and then a developmental stage, and finally (for fixed-term projects) a conclusion.

In the incubation period, relating to a specific individual, group or intention/idea, the initiative would begin to grow and the foundations would be laid, including the building of important relationships, ‘buy-in’ and extensive discussions over many months or even years. In Bridgetown, for example, this growth started under an earlier role-holder, Jill, developing the intentions of the role and identifying the key academic and practice stakeholders.

The initiative would then be formalised to a certain degree with role specification(s) and appointment(s) to address a given issue or project. This would include many practical considerations and arrangements, surrounding contracts and lines of reporting. At Porter, this phase in Victoria’s role offered helpful insight into the complexities of funding and contractual arrangements, in line with various expectations and intentions of the role:

I was in post for a very long time before I started to work out exactly what I was supposed to be doing, which was . . . kind of typical of the way these structures work; and to some extent, I was involved in writing my own job description . . . I’m employed by one of the directorates, not by the trust per se . . . so, I’m not actually affiliated with the R&D department . . . That made it even more complicated. [It’s] one contract with the university, that the trust buys out for 2 days a week, so it was set up as a university post, with trust partnership. So, the trust pay the university my salary for 2 days a week. Victoria, embedded researcher, Porter

A developmental period would then follow. During this, the embedded researcher would demonstrate their potential and the role would grow; often the details of the role (particularly in terms of the nature of the work) would change and evolve in line with various expectations and demands. In many instances, the role undertaken would be different from that proposed and the overall workload larger than anticipated. Karla’s main duties in Porter related to service evaluation, but, as her role grew, she also became heavily involved in the trust’s quality improvement strategy: extra work that was not part of her original role.

In some instances, the initiative would then come to an end, as in the case of Evansville, where funding stopped at the end of its fixed timescale. Even so, there could be a degree of influence ‘left behind’ by the completed projects, in terms of increased research awareness, cultural change and service improvement. Bella, formerly at Evansville, said she was still contacted by members of the NHS trust for advice and support.

Many initiatives however – like three of the four studied here – would be funded indefinitely, with the embedded researchers on permanent contracts. As a result, the timescale of individual projects and activities would become important, rather than the duration of the overall initiative. Maintaining researcher objectivity over such longer timescales might become a concern. Scale and longevity, then, would sometimes be planned from inception, and, at other times, would emerge contingent on local circumstances.

Involvement

The teams surrounding the initiatives tended to be relatively small, compromising largely line managers and senior academic support, before branching outward to team members. Each initiative and embedded researcher had a distinct configuration or network of relationships. The partner identification tool used in the interviews helped us to identify those involved with the initiative (rather than the projects/work undertaken by the researcher in this instance), and how intrinsic their involvement was. The schematics drawn from use of that tool are displayed in Figure 5 .

Each researcher identified two or three key contacts, often those to whom they reported directly or indirectly and who they felt had fundamental involvement with their work. These individuals often held senior positions in either the academic institution or the NHS, and the embedded researcher often described being ‘accountable’ to these individuals. In line with this seniority, such key contacts usually provided the embedded researcher with a degree of protection and a voice at a senior or strategic level. They were often important in ensuring funding and also access to other areas of the organisation, setting the tone from a senior level. There was universal agreement that, without these individuals and their ‘buy-in’, the embedded roles would be unsustainable.

Moving out from the centre of the partner identification tool, the individuals and groups came from a variety of sectors. Unsurprisingly, other members of the NHS team, often clinical specialties and/or professional group members (managers and department leads), were seen as important. In addition, relationships with members of the trust R&D teams were quite often seen as necessary. Again, these individuals brought access to front-line staff and their knowledge or expertise around each specific clinical context.

Academic colleagues were also identified here, showing collaborative relationships. The degree of importance placed on these formal and informal academic connections differed depending on each role. In some cases, senior academics (at dean or professorial level) were responsible for line management, but many of the academic relationships were with peers and brought shared research interests, support and a critical friend for the embedded researcher. In most instances, these relationships had been built over many years and their involvement and inclusion were of mutual benefit. Karla (Porter) offered her experience of the involvement she shared with colleague Victoria (also embedded at Porter):

So another person that I . . . have quite a bit of contact with, but I don’t know, I don’t know how to put her in terms of influence, is [Victoria] . . . Talking to her, she spans across the trust and [place]. So yeah, I suppose she’s, she’s very much like a partner, partner in crime, I guess.

So, between us we run the quality improvement group for the directorate . . . She was brought in as the strategic lead to basically get research on people’s agendas. So she is, in terms of the pecking order, very high up within the organisation, and it was her job to integrate research into people’s day jobs . . .

I’d say [she provides] peer support to be honest, because we meet every couple of months, and we just chew the fat about life in the different organisations and things . . . Because [Victoria] is still quite active in actually doing research, doing evaluation. So, it’s kind of peer support, that she’s done a PhD, I’ve done a PhD, and there aren’t many of us, what are we doing with that now? So, with that one it is more peer support, I guess, and thinking about and talking about the development of the quality improvement agenda. Karla, embedded researcher, Porter

Other sectors involved with the embedded initiatives included non-profit organisations and wider collaborators including national and international partners (e.g. NHS England and NHS Improvement). In these instances, the embedded initiative might provide consultancy or informal input to other organisations or agencies. Students were also frequently included in the identification tool, their involvement relating to shared interests, capacity- and capability-building, and mentorship.

It is also important to note the involvement of patients. Although patients were noted infrequently during the completion of the partner identification tools, the motivation to improve their experience and the care they received was reiterated often by the embedded researchers and those supporting the initiatives. In terms of formal PPI, the researchers shared diverse experiences, largely related to the nature of their role and the projects in which they were involved.

Generally speaking, PPI was undertaken for specific projects for which it was perceived as relevant, and was accessed through existing PPI groups; this included internal, trust-level service user networks, charity PPI groups (relating to specialism or illness) and national PPI representation through schemes such as NIHR INVOLVE. Other experiences relating to PPI were shared through research capacity-building work; in these examples, the embedded researchers were encouraging and supporting others to employ PPI effectively. Evansville was the only case study to set up a designated PPI panel in relation to the initiative and the role of the embedded researchers more broadly. Despite this variability and the sometimes less tangible examples of patient involvement in initiatives, their inclusion (directly and indirectly) was viewed as fundamental by the embedded researchers.

The networks of involvement then were very specific and bespoke to each initiative and often to each individual embedded researcher. Although some connections were tight (e.g. to line managers and scheme champions), others were loose and informal, forming and reforming as needs were identified and projects developed. In most cases, PPI was limited to projects rather than being linked to the overarching strategic goals of the embedded initiative. In few cases did it seem that the connections described had been fully constructed or specified at scheme inception; instead, they emerged contingently as the schemes evolved.

Each initiative varied in terms of how its relationships and activities afforded contact and proximity with different groups. In more obvious ways, this related to where embedded researchers and research activities were physically located. Researchers at Porter were generally located within the NHS organisation, with allocated desk space, whereas researchers at Coxheath, Bridgetown and Evansville had multiple desks (as did Victoria, the only researcher at Porter with a dual contract). Irrespective of desk space, there was a sense that work location was changeable and flexible:

I have to live my life with a pair of trainers and a rucksack, because I’m never in one building long enough to just be able to settle, I have to, I run round [location] – you know, I walk up to [location A] . . . and [location B] site is right over the other side of the city and I walk there; and the university campus is all spread out over here, and in 1 day I can be in four or five different buildings. Victoria, embedded researcher, Porter

Much of the movement between locations was done in a conscious attempt to be more visible. There was a shared sense among researchers that physical visibility, particularly within the NHS organisation, was crucial to the success of their work. Visibility was seen as intrinsic to informal relationship-building, and generated opportunities to reduce the gap between practice and academia. Karla, at Porter, said she spent most of her time at one main location, ‘the main base [because] I like to be in the thick of things’, and went on to link this to perceptions of ‘embeddedness’:

Through writing these narrative reports I’ve started to get a really, really good understanding of the service . . . I’m visible as well, people have got to know me so people will then contact me and say, ‘oh’, you know, ‘you can you help me with this’. And actually, if I was just a name, people wouldn’t necessarily feel confident to do that . . . I think part of the embeddedness as well is actually like physical proximity . . . their hub is sat sort of probably where that couple are over there [about 5 m away], they’re that close to where I am, so quite often I’ll sort of go over and introduce myself, talk to them, work with them, so it’s sort of getting to know them as well. Karla, embedded researcher, Porter

Embedded researchers in these case studies generally prized close proximity to the organisations in which they were embedded, but often had to work with great flexibility and agility across multiple sites and settings. Being physically co-located and ‘being seen’ were literal manifestations of the metaphorical need to close gaps between research and practice and required considerable effort.

All the initiatives brought to the fore the importance of social, cultural and knowledge boundaries, and the degrees to which actors shared particular ways of thinking, values and norms, and a sense of belonging by virtue of their professional socialisation or organisational affiliation.

Much of the hidden or unseen work of the embedded researcher involved working across and mediating the tensions between these boundaries. At the same time, however, this created certain role ambiguities for the researchers themselves. As discussed previously, the original intention of the role could evolve, resulting in researchers taking on different areas of work. In Porter, Karla’s contracted work related to narrative report writing for local service evaluation, but her role had since grown unexpectedly and she was now also heavily involved in setting up a local, trust-wide quality improvement initiative. This ambiguity of role was experienced across all of the case studies and, in some instances, had significant implications for the number of hours worked, with few boundaries in place to limit this:

Technically [I] devote 16 hours [per week] to [the trust], but the reality is I do a bit at home on top, because you can’t squeeze it into 16 hours, that’s a nonsense . . . The other 24 hours then are university hours, but again, it’s impossible to fit my university job into 24 hours . . . I do an awful lot of the evening work, an awful lot of weekend work, a lot of juggling between posts, and a lot, wherever possible, [of] double-weighting, to try and make up some of the shortfall, because I work about 80 hours a week.

The problem is that both organisations [need you] to do the job properly, and I can’t bear not to, [and I] haven’t got enough time to do either job properly unless I put in extra hours. Karla, embedded researcher, Porter

All of the embedded researchers therefore struggled with role and identity ambiguity relating to their sense of professional self, that is whether they were clinicians or academics (or both), whether they were aligned with the needs of the university or NHS (or both), and how they cultivated relationships with front-line staff or those facing the real-world need for research and evidence.

Each embedded researcher found their own paths to navigate these tensions of belonging, and appeared to find creative ways of resolving, or at least reconciling, multiple competing roles, in turn starting to forge new or distinct identities and belonging. They often found support, and a sense of that belonging, in informal relationships: they spoke at length about these relationships, which were often with other people in hybrid or similarly uncommon roles. These relationships, and even friendships, offered a sense of grounding, and opportunities to work through common problems or difficult experiences. Notably, the workshops and formation of the ‘embedded network’ that formed part of this project (see Chapters 1 and 6 ) seemed to demonstrate the emergence of a distinct occupational identity or sense of belonging around the embedded researcher role itself; for example, the researchers of Bridgetown and Coxheath came to see that they had much in common.

In summary, then, belonging across multiple sites, roles and identities posed specific challenges and additional work burdens. These were often actively managed, more informally than formally, but still left considerable unaddressed challenges and needs.

Findings 3: cross-case variations in processes

Functional activities

There were substantial variations in the nature of the work undertaken by the embedded researchers and in the scale of that work. The purpose of those activities also differed to some degree. Activities and projects included service evaluation, local and regional quality improvement, and small-scale research projects (often as part of research capacity- and capability-building). In those instances, much of the work was undertaken with a smaller, more local team. In some cases, the embedded researcher might even work one to one with an individual to support or guide a specific project.

Timescale similarly depended on the nature of the work. The heavily weighted service evaluation roles were structured around report deadlines (often annual and with accompanying interim reports). Other work, such as that relating to quality improvement, might be more flexible in its time frame and be part of larger, ongoing agendas or change programmes that took place over many years.

Researchers spoke little of formal training associated with their activities. In Porter, Bev and Katrina’s activities related largely to service evaluation, although they were also involved in recruiting for large-scale clinical trials (for which their service was often a patient recruitment site):

So, we’ll do an annual report on inpatient outcomes, outpatient outcomes, which we then share with the team, look at our outcomes, see what we need to be doing better, if we can do anything differently. So, we use that in conjunction with patient experience questionnaires . . . We’ll look at [them] and say ‘is there any way that we can improve on that?’. Katrina, embedded researcher, Porter

Our bread and butter is service evaluation, so we’re getting outcome data for our service – that’s, that is what we have to do on a daily basis, but in conjunction with that, we do have other projects going on. Bev, embedded researcher, Porter

For insight into the sheer range of activities undertaken by the embedded researchers, we can explore the work of Jane (Coxheath) and, to varying degrees, that of Anna (Bridgetown), Bella (Evansville) and Rachel and Victoria (both at Porter). To differing degrees, all five were involved in leading more ‘traditional’, original research, including funding applications, conference presentations and publications. Jane offered the most powerful example, with a helpful contextual insight into her activities and workload. Her work often related to relatively large, regional and national research projects, many of which she had secured funding for and that had been ongoing for months or years:

So, the work in the university, there’s two projects, but they’re not always primary research and they’ve been building on, or implementing or impact-based research . . . I’m now leading the work for Health Education England [relating to the] workforce transformation type agenda . . . that’s by July. The second piece of work is for [organisation name], so they want us to help them to develop a . . . career development framework for their mainly nursing staff at this stage, for health-care support workers across hospices . . . in the trust . . .

Two big things I’m working on, one is a single capability framework across the whole system . . . and then I’ve got three priorities, which is emergency department, general ward and children’s to apply that to, so that’s really important and hopefully will link to an IT [information technology] set-up that can be used . . . by Health Education England.

Then the other thing is . . . [a] collaborative research study across the trust to . . . and then I’ve got the ongoing stuff with the clinical leadership programme and the support of the consultant practitioners . . . There’s a conference that we’ve got in June . . . Jane, embedded researcher, Coxheath

In short, the portfolios of functional activities of these embedded researchers were often sprawling, diverse and sometimes unmanageable, with variable (and often negligible) amounts of formal training. The activities frequently reflected a large span of scale: from local improvement projects to regional or even national initiatives; from the local, informal and unfunded, to generic knowledge generation from funded formal research.

Skills and expertise

As with the portfolio of functional activities, the skills and expertise needed by embedded researchers were many and diverse. The range described tended, in part, to reflect career backgrounds, local initiative specifications and evolving relationships with wider stakeholders.

However, common skill sets were identified, not only by the embedded researchers, but by members of their wider networks. Notably, there was considerable agreement across the varying levels of seniority; for example, managers largely noted the same necessary skills identified by junior members of the team, such as doctoral students. These skill sets could be summarised as follows:

possessing expertise and in-depth research knowledge
making research and research processes accessible
forming complex networks, connections and collaborations
building strong relationships and trust
harnessing the knowledge and potential in others
working across hierarchies
being committed and driven, with great stamina.

Unsurprisingly, research expertise and in-depth research knowledge were seen as central to the embedded researcher role. This assumption was shared across almost all participants in the case studies. Embedded researchers themselves naturally saw this as important, and central to their ability to adapt to new areas of research, specialties and topics. Crucially, their research knowledge gave credibility to their role:

Hannah, AHP lead, Bridgetown: I think that’s where the current knowledge, the current skills, the links, the experience, the knowledge and the credibility comes from; that’s what the clinical teams need, because . . . she’s not just a clinician giving advice on research, she is an active researcher giving advice on research.

Interviewer: So, there’s respect for that?

Hannah: Absolutely, and I think that whilst my focus and priority is on that advice that she gives, I fully get and accept and desperately think we need that half-and-half split because she needs to be a currently credible researcher to give, to give the value to that research advice.

Making research and research processes accessible was also seen as fundamental to the embedded role – particularly when working to change perceptions of research and subsequently build research capacity and capability in the NHS organisation. Research was often seen as ‘out of reach’ for many clinicians and managers, and, in some instances, was deemed irrelevant. The embedded researchers’ ability to change these perceptions was seen as a necessary strength:

Interviewer: You said you called [embedded researcher] an ‘ally’, can you tell me a bit more about that?

Joanne, occupational therapy team lead, Bridgetown: [The research governance teams] are gatekeepers, and the process that you have to go through is very daunting, and the form that I’ve just sort of tried to fill out . . . it’s not the easiest of forms to do. So feeling like you’re on your own again, a barrier that you’ve got to overcome, whereas [name], well she definitely is on my side, because she had e-mailed a quick reply, I was reading it one time, she said ‘Be careful how you word such-and-such or this will happen’, and she helped us a lot, you know. So she’s always there, sort of watching that I don’t trip myself up.

The ability to form complex networks, connections and collaborations was at the heart of the embedded role. Arguably, this work sometimes received too little weight or acknowledgement relative to its importance (and relative to the more concrete and more obvious research skills). The term ‘bridging’ was used, as was ‘conduit’; however, these suggest the forming of a connection between two parties: the reality is that many of the embedded researchers were at the centre of complex webs of relationships and networks:

I can connect those people because I know what’s going on . . . [before] there just hasn’t been the forum to bring people together . . . to make those connections for people . . . I kind of feel like I’m a bit of a matchmaker essentially, because I’m kind of going round getting all this information, putting it in, and then kind of regurgitating it out in a sort of useful manner. Karla, embedded researcher, Porter

The ability to build strong relationships and trust was key to maintaining these complex networks, connections and collaborations. There was a strong sense throughout the data that the embedded researchers were seen (and certainly aspired to be seen) as trustworthy and genuine, with no hidden agenda:

People trust her, they’re not wary of her, they believe that she’s going to be there tomorrow and have that feeling about, you know, that solidarity. And I think I’ve got the ability to give people that feeling because I’m an experienced researcher and a nurse, erm, but [embedded researcher] has it . . . So, I think there’s a level of trust . . .

You know, there are barriers that she doesn’t have to go over because she naturally lives with those barriers. Are you with what I’m saying? It’s like she’s already inside the pen, she lives inside the pen. Peggy, nursing professor and NHS director, Porter

The skill to harness the knowledge and potential in others linked to some of the preceding skills (e.g. building relationships and making research accessible). Drawing out the potential in others and challenging their thinking (with care) were skills that embedded researchers displayed often. This related to the empowerment of others, not just those in junior positions, but also those working in senior management and leadership roles:

So, in establishing all of my ideas, my thinking, I went and sat with [embedded researcher] and we looked at the ideas, and what I was saying, and we, we had a conversation and she was able to support that conversation, that then helped me . . . articulate and reflect on my vision and then develop my thinking, such that I was able to make the pitch for a Darzi Fellow[ship]. Violet, collaborating general practitioner, Coxheath

As the quotation above demonstrates, working across hierarchies was an additional interpersonal skill strongly valued by the embedded researchers and by their wider teams. The ability to work with a variety of individuals, with differing roles and seniority, was important for success. Within this, there was the necessary ability to adapt their approach and communication to differing levels and audiences, so that the embedded researcher was seen as credible, relatable and personable:

With [embedded researcher] they know that she’s there, she was part of them, she has that ownership, that belonging. She recognises their significance; she has that continuity that’s really important . . . and before the post she’s in now really because she was embedded even when she worked for [university] – she was embedded in there. So, it’s been over time, exactly, that she’s known now, and she’s understood . . . And she can talk to people at a whole range of levels and she has that ability as well. Peggy, nursing professor and NHS director, Porter

What has run across the range of skills and expertise noted so far has been the need for embedded researchers to be committed and driven, with great stamina. These characteristics were seen as crucial, largely as a result of the extensive challenges associated with the embedded role (including role creation, development, workload and competing expectations, alongside the cultural and strategic barriers). There was a sense that the embedded researchers needed to be strong, resilient, adaptable and committed to their role. This was voiced by many of the embedded researchers, especially Anna, Jane, Victoria and Karen:

It’s very time-consuming, and having anything that’s a split sort of role it is exhausting. It’s always more than the sum of its parts really, so it is very dependent on someone who has the energy and the drive and the vision to see something – that’s, you know, that’s not so much the norm. Karen, associate dean of research, Bridgetown

Overall, there was broad agreement about the wide and diverse skills needed, but the degree to which each skill was important varied according to how the initiative was configured, particularly when looking at strategic involvement and the need for methodological expertise. For example, those roles that included a high proportion of service evaluation required fewer formal methods training and strategic interpersonal skills – these skills were much more relevant for initiatives that required ‘speaking truth to power’ and working across strategic organisational barriers at senior levels. The soft skills of effective communication and relationship-building, however, were always in demand.

Relational roles

The themes described in Findings 3: cross-case variations in processes show the relevance to embedded initiatives of effective communication and relationship-building. This was seen as a fundamental quality and skill of the researcher: the ability to build and sustain relationships, work across hierarchies (by being relatable and adaptable), harness skill and potential in others, and build trust were all crucial and could be described as skill in creative mediation:

Jane’s very approachable; she doesn’t make you feel stupid, she listens, she’s an active listener and then she helps you assimilate it. So . . . her communication skills are brilliant . . . and obviously the knowledge is there. Sally, former chief nurse, Coxheath

Diplomacy and negotiation formed a large part of this relational work and were also necessary for managing conflict and balancing competing agendas, expectations and priorities.

The key influences on the nature of the embedded researchers’ relational roles were their professional background and, most crucially, the functional contribution expected of them. For example, three embedded researchers in Porter, Katrina, Bev and Karla, whose roles focused largely on service evaluation, spent less time negotiating agendas and experiencing conflict through different priorities. The boundaries and nature of their work were more tightly and clearly defined from the outset. By comparison, Jane in Coxheath was senior in both her past and current roles, and her work had far fewer boundaries and an ever-expanding remit. Within this work, she had to juggle an array of conflicts, perceptions and agendas. As a result, her extensive experience in creative mediation – the ability to relate to others and work across rigid professional and philosophical boundaries and hierarchies – was much more relevant to the success of her role.

Being accessible and relatable was universally seen as important. The researchers had to ensure that they were not ‘too academic’ in their approach, particularly if they were to make research ‘accessible’ (and change perceptions of research). All of the embedded researchers needed this ability, arguably because there was often a sense of unattainability attached to the term ‘research’, rather than a problem with any of the specific processes in ‘doing’ research (i.e. the term itself is intimidating to many people).

Additional relational aspects of the embedded researchers’ roles were covered in Belonging and Skills and expertise .

Learning mechanisms

As noted in Chapter 4 on the formal evaluation and performance monitoring of embedded initiatives, success was seen as largely challenging to measure, partly because of the ambiguity of roles, but also because of the complexity of the work being completed. There was, therefore, variation in terms of achievement and what was subsequently learnt about what was, or was not, achieved.

For work such as service evaluation reports and specific quality improvement projects, the outputs were relatively easy to monitor and evaluate. Similarly, there were individual research projects that had clear aims or objectives and tangible outputs on completion, such as publications. Such achievements were, by nature, more explicit and therefore easier to ‘see’, making it easier to recognise, in the first instance, and learn from them. Jane in Coxheath and Victoria in Porter, for example, published widely and often attended conferences. These achievements were easier to identify, and learning how to make these accomplishments was relatively straightforward.

Less easy to acknowledge, monitor and learn from, however, were projects around research capacity and capability growth. Often there was no baseline of existing understanding or culture. At the same time, measuring cultural change, particularly when it related to changes in perception and engagement, was, by nature, difficult. Much of the work associated with culture change is subtle and even invisible. Subsequent achievements can be difficult to identify and acknowledge, and subtle small-scale changes are likely to be missed.

Anna in Bridgetown was working to establish a baseline of research activity (as shared by a member of her management team, Gillian) to try to mitigate some of these challenges and offer a starting point from which achievement could be measured:

Gillian, AHP lead, Bridgetown: The first instance would be about how we get people being that, as I say, research active.

Interviewer: Is that quite difficult to measure?

Gillian: Absolutely, absolutely . . . That has been quite challenging because we don’t have a baseline to work from, so it’s not something that is routinely gathered, and so it’s . . . a piece of work for [Anna]; she’s been getting ethical approval . . . to do a survey with all the staff . . . It’s a formal piece of research.

As a case study that had ended, Evansville showed that learning could be carried over into new initiatives through the accumulated experience of the embedded researcher (Bella). Bella said one initial goal of the embedded research role had been to disseminate findings beyond the immediate team, to ‘create a kind of a research or an evaluation mindset within the [whole] organisation’:

Many times, [people were] just looking at their daily practice, their work, they’re not considering types of evidence out there, they’re not thinking about evaluating what they’re doing, they’re not thinking about quality improvement. So, part of a deal for our team was, you know, to show them different ways in which they could do that. Bella, embedded researcher, Evansville

It was only when the role was redesigned, however, that the team started sharing its findings widely every 2 months, ‘even . . . emerging findings’:

Our findings [now] are going to different implementation groups across the trusts, it’s not just going to three or four teams, they’re being presented at their group executive level in 2 weeks. So . . . the chief exec[utive] knows exactly what we’re doing, and they know what’s coming out of our evaluation so . . . We learned from that, I think, and now we’re really careful not just to focus on data . . . but actually to be able to use this formative design a bit more practically. So, I think that was one of the big issues we had on the team and one of the reasons why I don’t think we [i.e. the original embedded initiative] were funded beyond the 4 years. Bella, embedded researcher, Evansville

Learning within the embedded research initiatives proved difficult then, not least because of the frequent lack of clarity over intentions and the emerging nature of many of the activities. Formative learning was clearly prioritised, alongside the necessary informal support systems for the embedded researchers. Summative learning was less in evidence, notwithstanding the varied governance and accountability mechanisms that played a role in shaping the overall work programmes and the day-to-day activities.

Concluding remarks

This chapter has dug deeper into the data from the four intensive case studies conducted in workstream 3. This cross-case analysis complements the case descriptions of Chapter 4 , looking at the attributes and dynamics of these diverse schemes. Using the structured framework laid out in Chapter 3 , and the account of knowledge co-production derived from a wide literature summarised in Chapter 2 , we have drawn insights from the messy real-world experience of embedded research. As with Chapter 4 , only interim conclusions are drawn here, with the main discussion of implications for future scheme development to be found in Chapters 6 and 8 .

The analysis in this chapter was arranged under the broad domains of ‘intents’, ‘structures’ and ‘processes’, further broken down into their constituent themes as laid out in Chapter 3 . Of course, there is much interplay and linkage between these domains and themes, and so boundaries between them should not be taken as firm or fixed. Nevertheless, this heuristic allows some degree of order to be placed on what otherwise would be a confusing mass of data.

In terms of intent, our in-depth study amply illustrated that there was often no singular or fixed intent to the schemes; rather, purposes evolved and flexed to reflect the priorities of key partners. Intentions were often shaped around building applicable knowledge (collaboratively, if not always co-productively) for the betterment of front-line services, often alongside the creation of new capacities and capabilities. Often discernible, if not always overt, was a desire to reshape patterns of power, especially the relations between academic and service partners, and sometimes also between different professions in the service settings. Intrinsic to this were ideas around the (re)negotiation of knowledge and the capacity of research to inform what counted as knowledge in context.

The structures created to support embedded research involved various practical configurations, but all had to pay attention to the scale of activity envisaged, the nature of the partners involved, and the importance for the researchers of presence and visibility in service settings. These important and relevant features, in turn, created tensions and dilemmas for the embedded researchers over identities and belonging. It was clear that such tensions, ambiguity and unsettlement were in play for many of the embedded researchers for much of the time. Managing these contradictions and tensions was a major preoccupation, drawing attention to the need for deft supervisory arrangements, careful mentoring and supportive networks.

The incredibly varied range of functional activities for many of these embedded researchers highlighted the complex processes that needed to be ‘designed in’ to embedded research schemes, and the extraordinary array of necessary skills and expertise needed to function effectively. The range of skills and styles we observed to be active in embedded research also suggests that these kinds of projects rarely settle on a single recognisable type of knowledge co-production, but fluctuate between (or sometimes blend) different approaches, sometimes more conventional, sometimes more committed. Nurturing and shaping the relational roles through which knowledge was brought to the fore and used mattered at least as much as, if not more than, standard research or project management skills in this context. Finally, given the often ambiguous and shifting nature of scheme goals, it was unsurprising that learning mechanisms, although much needed, often seemed underdeveloped.

Taken together then, the insights derived from these in-depth case studies suggest many areas of potential discussion, development and learning for stakeholders in embedded research, and it is to these issues that we now turn. Chapter 6 will move away from close-up examination of the dynamics of specific embedded cases to bring together the lessons from all four workstreams and introduce a design framework for the specification, management and assessment of embedded research initiatives. Sitting alongside this, a suite of tools, resources and supporting materials will then be described more fully in Chapter 7 .

Cite this Page Marshall M, Davies H, Ward V, et al. Optimising the impact of health services research on the organisation and delivery of health services: a mixed-methods study. Southampton (UK): NIHR Journals Library; 2022 Feb. (Health and Social Care Delivery Research, No. 10.3.) Chapter 5, Embedding in practice: cross-case analysis.
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Research article
Open access
Published: 23 October 2020

Advancing integrated care evaluation in shifting contexts: blending implementation research with case study design in project SUSTAIN

Jenny Billings ORCID: orcid.org/0000-0002-5660-9478 1 ,
Simone R. de Bruin 2 ,
Caroline Baan 2 &
Giel Nijpels 3

BMC Health Services Research volume 20 , Article number: 971 ( 2020 ) Cite this article

2133 Accesses

4 Citations

Metrics details

Despite many studies evaluating the effectiveness of integrated care, evidence remains inconsistent. There is increasing commentary pointing out the mismatch between the ability to capture the somewhat ‘illusive’ impact of integrated care initiatives and programmes, and the most appropriate way to do this. Focusing on methodology, this paper describes and critically reviews the experiences of SUSTAIN, a Horizon 2020 funded project (2015–2019) with the purpose of advancing knowledge and understanding of cross-European integrated care evaluation. SUSTAIN sought to improve integrated care initiatives for older people in seven countries, and to maximise the potential for knowledge transfer and application across Europe. The methods approach drew from implementation research, employing the participative Evidence Integration Triangle (EIT) and incorporating a mixed method, multiple embedded case study design. A core set of qualitative and quantitative indicators, alongside context and process data, were created and tested within four key project domains (person-centredness, prevention-orientation, safety and efficiency). The paper critically discusses the overall approach, highlighting the value of the EIT and case study design, and signalling the challenges of data collection with frail older people and stakeholder involvement at the sites, as well as difficulties developing the core set of indicators.

Conclusions

Lessons learned and recommendations for advancing integrated care evaluation are put forward that focus on the status of integrated care as a complex intervention and a process. The use of implementation research methods and case study design are recommended as an additional evaluation approach for researchers to consider, alongside suggested ways of improving methods of data collection with frail populations and cost analysis.

Peer Review reports

Despite many studies evaluating the effectiveness of integrated care, evidence remains inconsistent. Increasingly, commentary on the subject of integrated care evaluation is pointing out the mismatch between the ability to capture the impact of integrated care initiatives and programmes, and the selection of the most appropriate methodology to do this. Authors have highlighted a range of evaluation challenges that include the stability and sustainability of initiatives; data collection and the suitability of measures [ 1 , 2 ]; and a lack of appreciation of the complexity [ 3 ]. In addition, the status of integrated care as a ‘process’ must be recognised [ 4 ], meaning it is not a ‘fixed’ intervention, but susceptible to constant development and change. These factors all affect the sturdiness of evaluation designs and what constitutes an outcome. This in turn is prompting the need to fit the evaluation design more with how integrated care is implemented in practice and what integrated care is there to achieve and improve [ 5 , 6 ]. The value of mixed methods studies and suitable frameworks that examine both processes and outcomes has therefore been recognised in this field [ 2 , 7 ].

Regarding the examination of processes, the wide variation in how integrated care is operationalised calls for evaluations that include a range of qualitative methods, so that important contextual information can be examined to identify what seems to work and why. Regarding outcomes, there is a need to ensure that outcome measures have a good pragmatic fit with the shifting context of integrated care interventions and the population group under study. There is a tendency for example for measures for frail older people and people with multimorbidity to focus on general health outcomes (e.g. health status, physical functioning, quality of life), which may not be appropriate to their fluctuating physical and mental status. Outcomes such as experiences of care, independence and autonomy may be more suited to this vulnerable target group, and these inclusions may be more appropriate to ascertain the link between the integrated care processes and what improvements can be expected for the service user in receipt of care.

Given this impetus, researchers are adopting more ‘real world’ methodologies for the evaluation of complex interventions such as integrated care. While mixed methodologies have been advocated for some time to gain a better appreciation of the ‘grass root’ processes involved in integrated care implementation [ 8 ], the emergence of realist approaches drawn from Pawson and Tilley (1997) [ 9 ] has become evident [ 10 , 11 ]. Realist researchers seek to explain the underlying “cause” or mechanisms that generate observed phenomena through the construction of context, mechanism and outcome (CMO) configurations [ 12 ]. To support this, academics are developing frameworks such as the COMIC model for the evaluation of integrated care [ 13 ]. In addition to realist methods, and continuing with the focus on context, researchers are turning to implementation research. This is described as the scientific study of the processes used in the implementation of an initiative alongside the context within which it is taking place [ 14 ]. Its intention is to promote the systematic uptake of research findings and other evidence-based practices into routine practice, and, hence, to improve the quality and effectiveness of health services and care [ 15 ].

This broadening of methods appeal is becoming reflected in funding opportunities. The European Union (EU) funded research initiatives (Horizon 2020) are encouraging the adoption of innovative approaches to the evaluation of integrated care to better understand the impact on vulnerable populations with complex needs. One such project is SUSTAIN – Sustainable Tailored Integrated Care for older people in Europe (2015–2019). This paper focuses on the use of innovative approaches within SUSTAIN, and describes the method by which implementation research and case study design were blended for the evaluation of European integrated care initiatives. The aim is to share methodological experiences and lessons learned with the research community, in order to advance understanding of integrated care evaluation in context and add to the international ‘toolbox’ of methodological approaches. It will commence with a brief introduction to SUSTAIN and an overview of the design. This is followed by a critical discussion of the strengths and weaknesses of our approach and concludes with an assessment of the extent to which we advanced understanding of integrated care evaluation. Lessons learned and recommendations for future integrated care evaluations are put forward.

Overview of the SUSTAIN project

The SUSTAIN project was carried out by thirteen partners from eight European countries: Austria, Belgium, Estonia, Germany, Norway, Spain, the Netherlands, and the United Kingdom. With the exception of Belgium, in all other countries two integrated care initiatives (also referred to as ‘sites’) per country were invited to participate in the SUSTAIN-project, each developing and evaluating two integrated care initiatives ( n = 14) focusing on older people with complex needs. Sites that were recruited needed to have integrated care initiatives in place, but were motivated to improve and adapt their programmes.

The overall aim of SUSTAIN was to improve integrated care for older people, and to maximise the potential for knowledge transfer and application across Europe [ 16 ]. SUSTAIN had four main themes, pre-set by the Horizon 2020 funding programme of person-centredness, prevention-orientation, safety and efficiency in integrated care, which guided the development, implementation and evaluation of the initiatives. The objectives of SUSTAIN were to:

Support and evaluate improvements to established integrated care initiatives for older people over 65 living at home with multiple long-term conditions and complex needs; and.

Contribute to the adoption and application of these improvements to other health and social care systems, and regions in Europe.

The development and evaluation of SUSTAIN initiatives took place over an 18 month time span, with a 6 month phase of identifying the sites and creating improvement plans, followed by a year long implementation and evaluation period. Ethical approval for the evaluations was obtained through the site-specific governance structures. This paper focuses on the evaluation aspect.

Integrated care comes in many forms, and given that our focus was on developing improvements according to local needs, SUSTAIN has not been exempt from this variability in the selection of initiatives. However, despite the considerable differences in structure and context, two common approaches could be identified within our 14 initiatives;

Sites that aimed to improve services to older people and/or expand collaboration, communication and coordination with other care and support organisations, while also enhancing knowledge and understanding of each other’s roles and responsibilities;

Sites that aimed to improve the actual care delivery process to older people, for example providing care in a more person-centred way, or improving case- and discharge management [ 17 ].

The challenge for the evaluation design thus became one of developing a robust and consistent approach applicable across all country sites, in the face of several important variabilities. These included differing integrated care configurations and contexts, the site-specific pace of implementation, the throughput of service users and their length of exposure to the intervention, and the enduring problem of data accessibility and comparability [ 18 ].

Methods: the evaluation design of SUSTAIN

Evidence integration triangle.

The overall approach to the project was guided by the Evidence Integration Triangle (EIT). This participatory approach is derived from implementation research and aims to tackle the process of translating research and best-practice evidence to implementation [ 19 ].

While evidence on the contribution the EIT is making is still emerging, it is claimed that by focusing on the perspective of stakeholders and the context for application of scientific findings, pragmatic approaches can hasten the integration of research, policy, and practice [ 20 ].

There are three main components to the EIT model, namely the evidence-based intervention programme or policy, participatory implementation processes with stakeholder involvement, and practical measures of progress and outcome (Fig. 1 ). These three components enable stakeholders to use scientific evidence to encourage development and sharing of new knowledge to inform decision-making. In SUSTAIN, stakeholders were involved by organising steering group meetings. Steering groups consisted of local stakeholders (e.g. managers, health and social care professionals, representatives of older people and carers, commissioners, local policy officers) considered relevant to the integrated care initiative. These steering groups were created to design and implement improvement plans, that is, sets of improvements that apply to local, site-specific priorities.

Evidence Integration Triangle [ 19 ]

The high participation levels within this model enabled the research to be relevant and applicable from the onset and ensured that indicators and measures generated to gather evidence remain sensitive of the research and practice environment. Qualitative and quantitative evidence is accumulated and used throughout so that the change process remains dynamic and responsive to improvement.

Context is also pivotal to the EIT. Glasgow [ 19 ] describes the multilevel context as the conditions surrounding health problems and intervention opportunities in a particular place with a particular population, and is a key starting point. Context also changes over time, giving a dynamic aspect to the EIT, with context continually informing the other key components. It is clear that this approach was well suited to the fluctuating integrated care environments within which SUSTAIN was taking place.

Case study design

Within the practical measures aspect of the EIT (the focus of the development of our evaluation tools and approach), we adopted Yin’s [ 21 ] case study design. A strength of case study design is its ability to support the analysis of multiple qualitative and quantitative data sources – described as ‘embedded’ - to investigate complex phenomena in their everyday contexts and across different contexts [ 22 ]. It was therefore deemed appropriate for examining implementation processes as they unfolded within the EIT cycle in our differing interventions. In addition, it allowed for multiple cases, taking into account the different types of intervention, data source availability and sample size variations across our study sites. As such, with the case study design we aimed to tackle several of the challenges in integrated care evaluation.

Cases are defined by a unit of analysis, common across all sites. With SUSTAIN, our unit of analysis became ‘set of improvements for integrated care initiatives’, as this was a core objective. In addition, we adopted an explanatory approach to our case study design [ 21 ], as we were seeking to develop explanatory models and greater theoretical understanding around two main propositions linked to the four SUSTAIN themes:

Integrated care activities will maintain or enhance person-centredness, prevention orientation, safety and efficiency in care delivery;

Explanations for succeeding in improving existing integrated care initiatives will be identified.

These propositions were accompanied by a number of analytical questions to support analysis, described in the analysis section. Thus Fig. 2 illustrates our overall approach - multiple embedded case study design that is explanatory in nature . In SUSTAIN we differentiated between qualitative and quantitative indicators, a requirement of the Horizon 2020 call. Both produce quantitative data but the former measures attitudes, perceptions and beliefs, and the latter focuses on audit-style data such as hospital admissions [ 23 ]. In addition, the figure includes the data sources and the minimum anticipated samples that were seen as achievable, gauged through discussion at partner sites and within the consortium as a whole, taking into consideration the variability previously mentioned such as the differing speed of service user throughput and variable length of the intervention.

Multiple Embedded Case study design showing data sources and planned samples per site and overall in 14 sites

Practical measures

A key feature of the design was to develop and test a core set of indicators that could be used across our partner countries and potentially be transferable to other areas. While Fig. 2 maps out the discreet data sources aligned to case study design, Table 1 unpacks our data sources further, describing distinct data items and data collection tools that were core to the evaluation of our sites in more detail. For clarity and linkage to Fig. 2 , qualitative and quantitative indicators are highlighted in colour under the data items column. For data collection tools, instrument selection depended upon the goodness of fit with our objectives and four key themes; availability especially in different languages; validation within our population group; and length. Sites also included some site-specific measures in addition to our core set, that were particular to their interventions, such as audit forms to track new general practice referrals (UK), numbers of GPs, nurses and social workers (Spain), and reasons for not using the integrated care centre for people with dementia (Austria). The selection of our core instruments is elaborated upon and critically reviewed in the discussion.

Data collection

In keeping with the EIT cycles and approach to rapid knowledge transfer, data collection took place over 1 year in two waves following a 6 month development phase where baseline information was collected. Stakeholder reviews of preliminary findings (at the 12 month period) and final findings (at the 18 month period) (Fig. 3 ) were built in through steering groups to ascertain what seemed to be working well, and where solutions to problems needed to be identified. In order to enable comparison, we used uniform procedures for data collection for all initiatives.

Data collection and Feedback plan

Analysis strategies within multiple case study designs are focused on triangulation of data, purported by Yin [ 21 ] to strengthen the construct validity of the research. Each data source became one piece of a jigsaw with each piece contributing to understanding of the whole phenomenon [ 25 ]. In SUSTAIN, within each site, data sources were analysed according to their requirements before proceeding to a specific analytical process [ 26 , 27 ]. Uniform templates for analysis of each data source were generated through a discussion among research partners. All data was entered on a shared anonymised database. Of Yin’s [ 21 ] five techniques for analysis, we adopted pattern-matching, seeking rival explanations, linking data to propositions, and explanation building. Exploring rival explanations is an attempt to scan the data to provide an alternate explanation of a phenomenon. To support this, a number of analytical questions were developed to underpin the propositions and our aims, and aid consistency of analytical focus among our evaluation partners:

What seems to work with what outcomes when making improvements to integrated care?

What are the explanations for succeeding and improving integrated care initiatives?

What are the explanations for NOT succeeding and improving integrated care initiatives?

Are there any factors that can be seen as having an impact on integrated care improvements?

What factors can be identified that could apply to integrated care improvements across the EU, and be transferable?

Once each site analysis was completed, an overarching cross case synthesis took place. Overall, the evidence created from this type of analysis is considered robust and reliable [ 28 ].

Discussion: addressing the challenges

The discussion will critically review the SUSTAIN design and its appropriateness as an approach to integrated care evaluation. It will firstly discuss the overarching evaluation approach that incorporated the EIT and case study design, follow with a critical reflection on the development of a core set of indicators, and debate the choice of our design in the context of other suitable approaches, namely realistic evaluation.

Reflecting on the EIT, it proved to be highly suitable as a framework for implementation and evaluation for SUSTAIN, in its applicability and use in real-life contexts. A key feature was its practical ability to support a participative environment through the steering group meetings. Here, the framework promoted engagement through its ability to portray a logical and straightforward approach to implementation and evaluation, enabling members to proactively deal with contextual and hence evaluation challenges. It also enabled a level of knowledge exchange and action between the researchers and stakeholders. Other studies are similarly incorporating ‘fit for purpose’ research designs that are placed within the EIT framework. Carrieri et al [ 29 ] for example, are undertaking a realist review of interventions to tackle doctors’ mental health, using the EIT to convene a stakeholder group with experts in which research can inform practical decision-making and dissemination of messages. Also Resnik et al [ 30 ] are testing the EIT for implementation of interventions to manage behavioural and psychological symptoms associated with dementia, incorporating a pragmatic trial.

Similarly, case study design with its inherent flexibility provided a sound basis for harmonising the disparities between sites and provided a platform to test our core indicators. Yin [ 21 ] and Cresswell [ 31 ] promote the usefulness of this embedded multi-method design for its ability to add or remove data sources without detriment to the overall analysis. Case study design also gave us a solid data analysis strategy that could accommodate and make comparable and meaningful discrepancies across our partner countries. Case studies have been used in clinical practice and research for a number of decades in complex settings including integrated care [ 27 , 32 ], as well as within an implementation science approach [ 33 ] and in EU studies [ 34 ].

In addition, the incorporation of case study design was a significant addition to theory building opportunities (which is somewhat lacking in EIT – see later discussion), going some way towards assembling a deeper theoretical understanding of integrated care. Eisenhardt & Graebner (2007) [ 35 ] suggest that theory is emergent, situated in and developed by recognising patterns of relationships among constructs within and across cases. The use of replication logic assisted by pattern matching assists with theory building, in that multiple cases serve as replications, contrasts and extension to the emerging theories. Within SUSTAIN, case study design supported the development of our propositions and consequent explanatory models. Theories embodied within the propositions could be tested and expounded, ultimately leading to theory building, in relation to our central concepts of person-centredness, prevention orientation, safety and efficiency in care delivery, and what seems to ‘work’ in integrated care improvements (see SUSTAIN final report De Bruin et al. 2018) [ 36 ].

However our implementation research approach could be described as overly simplistic and lacking clear steps to achieve certain EIT goals, which leaves it open to interpretation. In addition, more guidance is needed regarding how each triangle component relate to each other, as well as how the evidence and stakeholders’ input connect to the triangle individually and as a whole. Importantly, it does not describe sufficiently well how the different context levels should be situated within the triangle and how, within a constantly changing environment, it misses out consideration of sustainability of the intervention. But, the simplicity of the EIT could be described as a strength, in that it is understandable and accessible by participants in the real world, vital in the highly participative stance of the framework. Given the variability within our projects and integrated care interventions generally, the lack of clear process information generated better ‘bottom up’ plans about how the components would work together and relate to the intervention as a whole. Indeed, Glasgow et al. (2012) see other knowledge translation models as too complicated, academic or time consuming for those who wish to use the evidence. In contrast, they purport the EIT to be applicable and usable in a variety of situations, as we found.

With respect to the three key elements within the EIT framework, the practical measures aspect will now be discussed in more detail as it affected the methodological approach. The two other elements, namely evidence-based interventions and the participatory implementation process (including stakeholder involvement), are more concerned with the intervention development and roll out and are reported elsewhere [ 16 , 17 , 37 ]. It is worth, however, mentioning briefly here some experiences with stakeholder involvement as they affected the methodology. In the face of universal health and social care resource constraints, considerable commitment was required for stakeholders not only to develop and implement the improvements with research teams at sites, but also to take part in interviews and assist with obtaining quantitative indicators. Our partnership approach fostered through the EIT approach enabled sustained buy-in to a large extent. However during the course of the implementation plan roll-out, two sites withdrew due to competing priorities and a diversion of resources away from the SUSTAIN initiative. We were able to gather valuable data on the context and reasons for this withdrawal to supplement out analysis. Again, the adoption of case study design overcame these flexes during the data collection period and, overall, helped to create useful and transferable results [ 31 , 38 ].

Moving now to the practical measures, the extent to which we were able to develop a core set of applicable measures needs consideration. Given the difficulties with integrated care evaluation, we made efforts in our design to select meaningful and pragmatic instruments through a wide literature search, particularly with respect to measuring service user impact. A number of considerations resulted in a contraction of suitable instruments; for example, they had to be applicable to each of the very different integrated care improvements set up within the 14 SUSTAIN sites; they had to be suitable for administration to frail older people; and our central concepts of person-centredness, prevention orientation, safety needed to be reflected in the instruments. Authors have usefully illumined on the evaluation of integrated care and the utility of associated instruments, many of which were considered during the selection process [ 39 , 40 ]. However, it became clear early on that several existing and validated indicators for frail older people with multimorbidity would be unsuitable. With quality of life measures for example, this was due to the high possibility that relatively short interventions would have little impact; and recommended instruments such as PACIC (Vrijhoef et al. 2009) were not ‘hitting’ all of our considerations sufficiently closely. We therefore narrowed our focus onto an examination of improvements to care and the personal impact of care delivery, which included degrees of person-centredness, experiences of co-ordination, and perceived control and independence.

With this in mind and after much deliberation within the SUSTAIN consortium, we selected the P3CEQ [ 41 , 42 ], and the PCHC [ 43 ], the latter validated for our population group. At the time of selection, the P3CEQ was relatively new but seemed suitable for administration across all sites and intervention types. We did experience, however, some repetition between these two questionnaires, and in some sites there were significant problems with recruitment and fatigue of older people. In response to this, the PCHC was withdrawn, as the P3CEQ seemed more tuned to the SUSTAIN themes and also included items on control and independence in health and social care. Case study design accommodated this adaptation. The data collection and analysis relating to the P3CEQ was not without its challenges during the course of SUSTAIN however. We found it needed essential preconditions (eg. face-to-face administration, collections of reasons for non-response) and administration and coding guidelines (eg where informal carers support service users to answer questions) [ 44 ]. We conclude through our experiences, that establishing a solid and standard cross-country measure of older service user experiences for integrated care still remains fraught with complexity and somewhat elusive.

Obstacles were more apparent with obtaining quantitative indicators due to the availability, accessibility and reliability of appropriate health and social care data across partner countries. This is due for example to differences in what and how data is collected, variations in the geographical representation of data, and the general lack of social care data, and these problems are persistent. For example, across Europe, data is scattered across systems, is not interoperable, and there are privacy concerns and technical challenges that block effective data recording and sharing at local, national and European levels [ 18 ]. In addressing this somewhat ‘hostile’ environment, we co-created a core list with professionals and managers at the sites of what could be obtained from either routine service level data, clinical notes, care plans or other sources (see Efficiency data in Table 1 for indicators that were deemed common across sites).

Collecting directly from clinical data and care plans had the potential to be a rich source of data [ 45 ] and could overcome the problem of aggregated measures, such as hospital admission data, and their sensitivity to projects where the population group is small and widely dispersed. Similarly, with the cost data, very few sites were able to extract specific costs related directly to the improvement interventions, but an estimate of staff hours was deemed possible, to give some indication of resource use. However using both clinical notes, care plans and staff hours were dependent upon the accurate recording of these events by busy practitioners and managers, which could not be assured, an aspect also acknowledged by Jefferies et al [ 46 ] With clinical notes, this recording was variable and unless prompted, did not always yield the information required. Care plans were not always completed or available; other researchers have had similar experiences and list causes as staff time pressures, poor document construction and communication difficulties with service users, recognised in other studies [ 7 ]. With staff hours, although diaries/templates were made available at sites, staff worked across initiatives and were not always able to separate and accurately record specific hours dedicated to the improvement initiatives. So, in most cases this was estimated, and thus the ability to give a sound cost analysis was greatly reduced.

With this last point, difficulties with the measurement of cost in integrated care is the subject of much debate within the literature. Lack of standardised outcomes and continuous changes in care delivery, for example, render the employment of traditional economic models unusable [ 47 ]. While SUSTAIN was keen to avoid health economic methods that have a poor fit with the nature of integrated care, it was clear that our more pragmatic approach was also not optimal, and the search for a more reliable and attributable method should continue.

Any deficits within quantitative data were however compensated by the richness of our qualitative data sources. As well as service user and carer interviews, we obtained professional, managerial and other stakeholder viewpoints, alongside documentary evidence from care plans (where available), steering group meetings and field notes. These perspectives provided valuable insights into personal impacts of the intervention, contextual influences and more nuanced information about if, how and why improvements made a difference (see De Bruin et al. [ 36 ]).

Having reviewed the relative mertis of the EIT framework, the discussion moves on to a critique of case study design. One of the most commonly cited disadvantages of case studies is that findings can lack generalisability and scientific credibility because replication is difficult [ 37 ]. However, external validity can be stronger in multiple case study designs, which was the choice in SUSTAIN, and can be weak in more highly ranked randomised control trials. Such weaknesses in RCT design have been exposed in a number of systematic reviews and secondary analyses [ 48 ].

In practical terms, there are further difficulties that researchers can encounter. For example, there can be a tendency to become overwhelmed with data and the process can be very time consuming, particularly with regard to developing and blending thematic statements from the analysed data sources. This occurs particularly when propositions are lacking and there has been no attempt to link the data collection with the aims of the study in a focused way, or create some boundaries to data collection [ 26 ]. In SUSTAIN, we established clear objectives and propositions, protocols for every aspect of data collection and management, analytical templates for ensuring consistency with data analysis, and a shared quality-controlled database. Difficulties still arose however, so to supplement this and optimise uniformity of our evaluation approach, we arranged regular one-to-one progress and ‘trouble-shooting’ calls with research teams and devoted space at six monthly consortium meetings to deal with methods issues.

The discussion now moves finally to a consideration of why we selected implementation research over other methods such as realist evaluation. For SUSTAIN, the importance of gaining a consistent and understandable method across different institutions and contexts, as well as involving stakeholders not wholly conversant with research, was paramount. While our approach was not fault-free, realist methods also has its challenges regarding its complexity. For example, Greenhalgh et al. (2009) [ 10 ] noted that a set of more or less well-defined ‘mechanisms of change’ in reality can prove difficult to nail, and the process of developing CMO configurations is an interpretive task, achieved through much negotiation and dispute. In addition, the authors add that while realist evaluation can draw useful lessons about how particular preconditions make certain outcomes more likely, it cannot produce a simple recipe for success. Given that this latter aspect was a significant factor for our aim of promoting good knowledge transfer, the applicability of realist approaches to our design was limited, with implementation research seemingly more suitable.

Nevertheless, similarities are evident between these different evaluation approaches. While realist uses the development of CMO configurations, implementation research also investigates equally important factors affecting implementation (geographical, cultural beliefs, poverty), the processes of implementation themselves (multi-disciplinary working, local resource distribution) and the end product or outcome of the implementation [ 14 ]. Implementation research does not however link the components so strongly, circumnavigating the lengthy interpretation tendency of realist approaches. Nor does it, particularly in the case of EIT, lend itself to so readily to theory generation, unlike realist approaches. Hence combining the EIT framework with case study design as we did in SUSTAIN offered stronger opportunities for theory testing and development, as previously outlined.

Conclusions: lessons learned and recommendations

Overall, in the strive to seek out the answers to ‘what works’ in integrated care provision, SUSTAIN has enabled the identification of different ways to advance integrated care evaluation locally, nationally and across Europe, that fundamentally recognises its status as a complex intervention, and as a process. Operating within this conceptual and theoretical understanding, we were able to apply pre-emptive consideration to the challenges in the evaluation design, obtaining a good pragmatic fit with the objectives of evaluating improvements. It is clear that difficulties with health data continue, which impacted on our ability to provide a robust transferable set of core indicators, highlighting the continuing challenges. However, instruments within this set still are anticipated to be of value and more meaningful to what integrated care should aim to achieve. Integrated care evaluation continues to challenge, and our approach in SUSTAIN was not without its own challenges. However out intention with this paper is to support researchers by adding to the international methodological repertoire of evaluation approaches that encourage a goodness of contextual fit.

The following are key lessons learned and recommendations:

Without doubt, we would advocate a participatory approach to evaluation designs and one set within implementation research. This recognises the dynamic nature of integrated care implementation and keeps pace with its ebbs and flows, thereby strengthening the evaluation approach and potential for knowledge transfer.

Case study design also proved to be highly useful and adaptable to the changes in evaluation requirements, variations between sites, and is pertinent to cross-European comparative research.

With respect to the target group of older people, there is a clear need to employ more innovative data collection techniques that step aside from traditional survey and interview approaches, towards methods that are interactive, engaging and experiential and take account of ageing. Talking Mats, a tested and validated vehicle to support older people to communicate about things that matter to them, is gathering momentum as a research tool [ 49 ] and may be a way forward.

Further research is needed to better understand and measure the relationship between resource and cost changes and integrated care. In keeping with growing opinion, the focus must move away from traditional health economic models towards a more realistic and pragmatic perspective of what can be measured. Rephrasing of cost objectives towards investigating a ‘better use of resources’ within the integrated care environment may be a start.

Availability of data and materials

Researchers can apply for data by submitting a proposal to [email protected] . After agreement of the proposal analysis by the SUSTAIN steering committee, and after ethics approval and a data transfer agreement, collaborative researchers can receive data for a specific research question. Fees will be dependent upon the amount of work needed for data extraction.

Abbreviations

Evidence Integration Triangle

European Union

Person-centred experiences of co-ordinated care questionnaire

Perceived control of health care

Team climate inventory short version

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Acknowledgements

The content of this article reflects only the SUSTAIN consortium members’ views. The European Union is not liable for any use that may be made of the information contained herein. The authors would like to acknowledge the contributions of the SUSTAIN consortium as a whole to the methods development.

The SUSTAIN project was funded under Horizon 2020 – the Framework Programme for Research and Innovation (2014–2020) from the European Commission under grant agreement No. 634144. The funding body had no role in the design of the study, data collection, analysis, and interpretation of data, nor in the writing of this manuscript.

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The authors have read and approved the manuscript. JB was responsible for and led the selection of the methodological approach, its development and the responses to methods challenges as the project evolved. JB also selected suitable instruments and wrote all the internal study protocols and guidelines associated with conducting the evaluation. This was consistently and strongly supported by SdB, and guided by GN and CB. The SUSTAIN consortium contributed through discussion and feedback. All authors contributed towards drafts of the articles.

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Austria . Institution: Osterreichishe Plattform fur Interdisziplinare Alternsfragen. Ethics committee of Vienna.

Catalonia, Spain . Institution: Agencia de Qualitat/Avaluacio Sanitaries de Catalunya. Ethics Committee: Comite Etica D’Investigacio Clinica 2015888.

Estonia . Institution: Sihtasutus Poliitikauuringute Keskus Praxis. Ethics committee: Meditsiiniuuringute Eetikakomitee 1187.

Germany . Institution: Stiftung Gesundheit. Ethics committees: Medical Association of Berlin and Medical Association of Brandenburg.

The Netherlands . Institution: Rijksinstituut voor Volksgezondheit en Milieu Centrum voor Voedin. Ethics committee: Medische Ethische Toetsingscommissie VU Medisch Centrum 2016.507.

Norway . Institution: University of Olso. Ethics Committee: REK Regionale Komiteer for Medisinsk og Helsefaglig Forskningsetikk 2016/2004/REK.

UK . Institution: University of Kent. Health Research Authority approval ref. 16/1EC08/0045.

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Embedded systems are computers designed and programmed to meet the requirements of a specific application. Applications may not require an OS (Operating System) or may rely on a customized OS. The system architecture is usually composed of a low-cost microprocessor, memory and peripherals interconnected through busses. It may also include a coprocessor to speed-up a specific computation.

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How C++ Is Used in Embedded Systems: Applications and Case Studies

Hey there, tech-savvy folks! 👋 Today, we’re going to dive into the intriguing world of embedded systems and explore the fascinating applications and case studies of the C++ programming language within this domain. As a programming enthusiast and code-savvy friend 😋, I’ve always been enthusiastic about exploring the intersection of technology and real-world applications. So, let’s buckle up and delve deep into the realm of embedded systems and how C++ plays a crucial role in this fascinating domain.

Introduction to Embedded Systems and C++

Definition of embedded systems.

Before we jump into the nitty-gritty details, it’s essential to grasp the concept of embedded systems. These systems are specialized computing devices that are designed for specific tasks and are embedded within a larger mechanical or electrical system. From your smartwatch to the complex avionics systems in aircraft, embedded systems are all around us, quietly performing their designated functions.

Overview of C++ Programming Language

Now, let’s talk about our trusty programming language, C++. Known for its efficiency, performance, and versatility, C++ has been a cornerstone in the software development industry. From its robust support for object-oriented programming to its extensive use in system software and game development, C++ has proven its mettle time and again. But how does C++ fit into the world of embedded systems? Let’s find out!

Applications of C++ in Embedded Systems

So, where does C++ shine within the realm of embedded systems? Let’s explore some fascinating applications:

Real-time Operating Systems

In the realm of real-time operating systems (RTOS), C++ has carved out a significant niche for itself. With its ability to manage system resources efficiently and its support for real-time constraints, C++ is the go-to choice for designing and implementing RTOS components. Whether it’s ensuring timely response in automotive control systems or managing critical processes in industrial machinery, C++ proves to be a reliable companion in the RTOS landscape.

Mobile and Wireless Technologies

The ubiquity of mobile and wireless devices underscores the importance of efficient embedded systems. C++ finds its place in this domain by enabling the development of high-performance, low-latency applications for mobile platforms and wireless communication systems. Whether it’s optimizing memory usage or enhancing processing speed, C++ empowers developers to create robust embedded solutions for an increasingly connected world.

Case Studies of C++ in Embedded Systems

Now, let’s take a closer look at some real-world case studies where C++ has made a tangible impact within embedded systems:

Automotive Industry

In the automotive industry, safety, reliability, and performance are paramount. C++ comes to the fore in this domain, playing a key role in the development of embedded systems for vehicle control units, infotainment systems, and advanced driver-assistance systems (ADAS). Its ability to support low-level hardware interactions and real-time processing makes C++ a natural fit for the demanding requirements of automotive embedded systems.

Consumer Electronics Sector

From smart TVs to IoT devices, consumer electronics rely heavily on embedded systems to deliver seamless user experiences. C++ demonstrates its prowess in this sector by enabling the creation of efficient and feature-rich embedded software for a wide range of devices. Whether it’s optimizing battery life in smart gadgets or ensuring smooth multimedia playback, C++ empowers developers to craft sophisticated embedded solutions for the consumer market.

Comparison of C++ with Other Programming Languages in Embedded Systems

Now, let’s tackle the age-old debate of C++ versus other programming languages within the realm of embedded systems. Here’s a quick rundown of the advantages and limitations of using C++:

Advantages of Using C++

Performance Optimization : C++ allows for fine-grained control over system resources, making it ideal for performance-critical embedded applications.
Object-Oriented Approach : The object-oriented nature of C++ facilitates modular and reusable code, enhancing productivity in embedded system development.
Hardware Interaction : With its capability to interact closely with hardware, C++ is well-suited for embedded systems that require low-level control.

Limitations of C++ in Embedded Systems

Memory Management : The manual memory management in C++ can pose challenges in embedded systems where memory constraints are a primary concern.
Complexity : C++’s rich feature set can lead to complex codebases, resulting in potential maintenance and debugging challenges in embedded projects.

Future Prospects of C++ in Embedded Systems

As we gaze into the future, it’s intriguing to ponder the potential advancements and emerging trends in C++ for embedded systems:

Advances in C++ for Embedded Systems

The evolution of C++ standards and tooling continues to bolster its capabilities for embedded development. With features like constexpr, std::span, and modules, C++ is constantly evolving to address the specific needs of embedded systems, providing developers with an array of tools to create efficient and maintainable embedded software.

Emerging Trends in Embedded Systems with C++ Usage

The rise of edge computing, IoT proliferation, and the demand for real-time processing herald a promising landscape for C++ in embedded systems. As the technology ecosystem evolves, C++ is poised to play an integral role in enabling the next generation of intelligent and interconnected embedded solutions.

In Closing… 😊

Overall, the pervasive influence of embedded systems in our daily lives, coupled with the indispensable role of C++ in this domain, underscores the enduring relevance and impact of this programming language. As we continue to witness technological advancements and breakthroughs, C++ remains a stalwart companion for developers delving into the fascinating world of embedded systems.

So, tech aficionados, keep exploring, keep innovating, and remember—when it comes to embedded systems, C++ is the bridge between imagination and implementation! 🚀

Random Fact: Did you know that Bjarne Stroustrup, the creator of C++, initially called it "C with Classes"? Talk about a transformative journey for a programming language! 🌟

Program Code – How C++ Is Used in Embedded Systems: Applications and Case Studies

Code output:.

Imagine a continuous stream of output where sensor values are printed every 500 milliseconds, and a ‘Processing sensor data…’ message appears every second.

Code Explanation:

This program simulates an embedded system application using C++. Embedded systems commonly involve reading from sensors and processing that data. The main components of this simulation are:

Two functions named ReadSensorData and ProcessSensorData are defined at the beginning. ReadSensorData simulates a sensor providing data by generating a random number intended to represent sensor output. ProcessSensorData simulates data processing, which could be anything, such as filtering, scaling, or applying algorithms to interpret the sensor input.

There’s a use of multithreading here, where each core functionality (reading and processing data) runs on its own thread. This is highly relevant in embedded systems to perform concurrent tasks—like reading multiple sensors simultaneously or processing data while another task is ongoing.

main function: Here’s where the two threads are created, with each one running one of our functions. sensorReader , the first thread, introduces concurrency, running ReadSensorData . The sensorProcessor thread does the same for the ProcessSensorData function. By using join on both threads, we ensure that the main thread will wait for these threads to finish before exiting, which, in our case, never happens because of the infinite loop.

In ReadSensorData , a simulated sensor value is generated using rand() % 1024 to get a value in the range 0-1023, typical for a 10-bit sensor. It then simulates a read interval with a delay of 500 milliseconds using std::this_thread::sleep_for() .

In ProcessSensorData , simulated data processing is set up as a task that takes longer than the read operation, as represented by a 1-second sleep. This represents the common scenario in embedded systems where data processing or analysis takes longer than raw data collection.

The use of <chrono> library allows us to simulate real-time constraints, which is a fundamental aspect of embedded system programming, where operations often need to be timed precisely.

The program gives us a simple yet illustrative glimpse into the tasks and challenges faced in embedded systems programming, specifically showing concurrent task handling and pseudo real-time operations.

The significance of ‘c’ in c programming language, c programming languages: understanding the basics and beyond, exploring the c programming language: from basics to advanced concepts, object-oriented programming: the pillar of modern software development, object-oriented coding: best practices and techniques.

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How insurers and new entrants can take advantage of embedded insurance

EY Global Insurance Technology Leader

Managing Director, Digital Strategy, Ernst & Young LLP

Why embedded insurance, why now

Ubiquitous cloud-based digitization, rapidly decreasing cost of sensors and increasingly intelligent automation are driving down the barriers, primarily cost and complexity, to serving insurance customers efficiently and effectively, especially when it comes to simpler risks. By deploying enabling technology more holistically across the enterprise, rather than just via point solutions in specific functions and processes, insurers can become more agile and responsive in dealing with market shifts and evolving customer needs. This level of digitization, when augmented by advanced analytics platforms and design thinking, can give insurers clearer predictive visibility into the solutions that customers will adopt tomorrow.

Of course, other companies outside of insurance can access these capabilities too, which makes it more feasible for nontraditional “insurgent” players to jump into the insurance marketplace. That’s why embedded insurance must be viewed by insurers as both a massive growth opportunity and potentially a severe competitive threat. It naturally follows that insurance leaders must rethink how non-insurers will fit into the market landscape and the impact of embedding insurance on future business and operating models.

Looking at market dynamics, insurers looking for growth are obviously attracted to the upside of new business models, including embedded offerings, partnership-driven ecosystems and usage-based products. Many insurance executives recognize that new offerings and business models are critical to meeting new customer needs and rising expectations for value. In this regard, open digital platform-based curated ecosystems hold potential for insurance carriers to not only launch superior insurance offerings but also as a means for collaborative partnerships with potential insurgents. These potential insurgents, such as large firms in other sectors, are also looking to strengthen their customer relationships with more value-adding services and richer personalized experiences. They view embedded insurance as one such service, linking value propositions seamlessly as well as offering them at point of purchase or interaction, driving higher conversion.

These overlapping interests lay the groundwork for productive partnerships. However, many insurance brands are challenged by low levels of customer trust. Opaque pricing, the emphasis on profitable underwriting over delivering value to customers and the perception that insurers will use shared data against customers contribute to consumer skepticism toward the industry. According to Edelman’s 2022 Trust Barometer, of 16 industries, financial institutions rank near the bottom, above only social media. This, however, is not an insurmountable problem, with consumers across generations indicating and demonstrating in practice a willingness to share data in exchange for value. In 2022, a study by Global Data and Marketing Alliance (GDMA) showed that almost half (48%) of US consumers are data pragmatists — people who are happy to exchange data with businesses so long as there is clear benefit to doing so.

What embedded models can — and should — replace

For decades, insurers have sold their products via joint ventures or other partnerships with manufacturers and other companies. These distribution arrangements have been suboptimal in many ways, due to undifferentiated features, high costs and fragmented customer experiences. Asset owners are increasingly aware of the risk to their brand from the disconnect between business value of their customers and the underwriting risk they represented to an insurer. Because partners’ incentives weren’t necessarily aligned, customers frequently saw limited value; consequently, adoption rates remained low.

Increased digitization has exposed these shortcomings and motivated more non-insurers to explore embedded insurance. Typically, these brands enjoy higher levels of trust, have larger and more loyal customer bases, and face fewer legacy issues than insurers do. These are huge advantages for any company looking to expand its portfolios of offerings.

Ultimately, rather than acting as minor distribution channels for insurers, non-insurers want to take control of the product and overall experience. They have the capacity to build stronger value propositions and orchestrate the necessary ecosystems to deliver higher standards for customer centricity, reduced cost of insurance and increased pricing accuracy. To be clear: These are not InsurTechs; rather, they are well-established and well-capitalized brands accustomed to leading their markets. They will be aggressive in engaging InsurTechs and other partners to access the capabilities they need to succeed.

For insurers to compete with embedded offerings, on their own or with new partners, they will need to address various interconnected concerns and challenges, including:

Undifferentiated products that aren’t based on the latest data or most useful insights, lack key features, or are delivered via subpar experiences
Higher costs, both in core operations and across the value chain, with multiple intermediaries adding 30%–40% to costs
Too little automation and too much manual processing
Limited adoption rather than systemic use of artificial intelligence, machine learning and other enabling technologies
Legacy system limitations in integrating the velocity, variety and volume of new data flows necessary to innovate in the embedded space

There’s no underestimating the last point: Replacing legacy systems is not an option for most insurers, given the high costs, and meeting the pace of market changes on legacy systems simply will not work. Thus, insurers need to develop entirely new ways of engaging in solution design and development, based on modern platforms that provide pre-built capabilities, make it easy to integrate with partners and support fast, secure data exchange.

Other impediments to agility and responsiveness must be addressed. For instance, most property and casualty (P&C) insurers have yet to refine their offerings or underwriting models to account for the dramatic changes in mobility, including the rise of electric and self-driving vehicles. Similarly, relatively few commercial insurers have developed protection solutions that reflect the huge proportion of balance sheet value that is now linked to intangible assets (e.g., brands, patents, intellectual property, networks). Nor have they embraced data streams from sensors to transform their offerings to include sophisticated risk prevention services. The bottom line is that insurers have a great deal of work to do in prepping their tech, teams and operations, regardless of their embedded strategy.

Industries ready to go all in on embedded

The list of sectors and companies that see the appeal of embedded insurance is not short. It includes:

Original equipment manufacturers (OEMs): automotive, agricultural equipment, appliances
Health care and pharmaceuticals: life sciences firms, medical device manufacturers
Real estate: property owners, investors, management firms
Financial services: banks, credit card companies
Travel and hospitality: airlines, cruise lines
Retail: consumer electronics, restaurants

Instead of viewing these firms solely as just another channel, insurers should explore new partnership and collaboration options. Co-opetition is another prerogative to consider. After all, each of these sectors brings unique strengths, including extensive customer relationships and rich data stores, and they are motivated to innovate based on compelling use cases well suited to their customer needs. In automotive, for instance, manufacturers are looking at embedded insurance as just one element of a network of services, including payments, maintenance offerings and mobility subscriptions, rather than traditional ownership models.

Leaders in these sectors are already actively exploring their options and, in some cases, preparing minimally viable offerings. Future articles will take a closer look at each of these sectors to frame the specific opportunities and challenges.

Imperatives for winning in the era of embedded insurance

Insurers have stayed relatively safe from disruptions due to InsurTechs and other new market entrants through regulatory protection, aggressive pricing in startup markets and the acquisition of potential disrupters. The entry of larger firms, including Fortune 500 players with bigger balance sheets, stronger brands and higher degrees of customer trust, is a competitive challenge of much greater magnitude. Indeed, it will force insurers to upgrade their product portfolios with more dynamic offerings, more precise pricing and richer, analytics-enabled experiences. The static, traditional policies that have held sway for the better part of the century are facing the end of their shelf life.

And it’s not just what customers buy that is changing but also the underlying principles for designing insurance products. Insurers will use different data, largely based on actual usage patterns and real-time risk insights, to price products and dynamically adjust premium levels. How customers buy and consume products is also changing. All of these factors explain why the industry has reached a historical crossroads.

So what can insurers do to defend themselves from the heightening disruption, and how can they take advantage of the huge growth opportunity that’s right before them? A few key actions include:

Use advanced analytics to actionably understand drivers of new product adoption and satisfaction and apply such insights into product and experience design on an ongoing basis
Define the offerings and explore new business models based on multiple collaboration options, including B2B2B and B2B2C, and test the concept of OEMs as customers
Own the platform and diversify into asset and service value enablement beyond underwriting
Embrace design thinking to promote high-impact outcomes via new and higher standards for customer experiences
Relentlessly drive out process and administrative costs via automation across the value chain and establish lean operations, with a relentless focus on a handful of core metrics, including pricing accuracy
Honestly assess the culture in terms of readiness to innovate and self-disrupt, then define the necessary capabilities to innovate boldly and at scale — creative ideation, rapid prototyping, rigorous testing, data-driven product management — and make such innovation a repeatable process within ongoing operations
Evaluate potential partners for joint success potential and devise strategies for post-brand futures

Taking these actions will enable insurers to future-proof their business models as they enter the era of ecosystems and embedded insurance.

Taking action now will enable insurers to future-proof their business models as we enter the era of ecosystems and embedded insurance.

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How increased trust and transparency can unlock growth

Explore the EY Global Insurance Industry Outlook. Learn more.

Hero image development engineers are testing driverless autopilot system

How auto insurers can grow as a decade of disruption approaches

The rise of EVs, AVs, telematics and changing customer needs will shrink the market and invite new competition. See how carriers can adapt.

Nine customer types defining the next wave of insurance

Shifting consumer needs are an invitation for insurers to innovate in pursuit of growth and to stay ahead of new competitive threats. Read more.

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PDF Embedded Case Study Methods TYPES OF CASE STUDIES
Page 3 of 7 Embedded Case Study Methods: TYPES OF CASE STUDIES of the case. In case studies on regional or urban planning, the units may be different interest groups that are involved or affected by the project. Table 2.1 Dimensions and Classifications of Case Studies Note that an embedded case study allows for a multiplicity of methods that may be
Embedded case study
An embedded case study is a case study containing more than one sub-unit of analysis (Yin, 2003). Similar to a case study, an embedded case study methodology provides a means of integrating quantitative and qualitative methods into a single research study (Scholz & Tietje, 2002; Yin 2003). However, the identification of sub-units allows for a ...
Embedded Case Study Methods. Integrating Quantitative and Qualitative
What makes Roland Scholz and Olaf Tietje's book on "Embedded Case Study Methods" a breakthrough is, that it allows avoiding the sketched choice between Scylla and Charybdis. They have formed a basis for a methodologically oriented academic training in case a curriculum contains learning objectives in regard of transdisciplinary‐oriented ...
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The qualitative embedded case study method developed in this paper was adapted from Yin's visual structural models to suit the purpose of refining concepts from a qualitative perspective inclusive of older people's experiences (Yin, 2009, Yin, 2012).Key differences exist between Yin's, 2009 embedded case study method, and the non-positivist and reflexive qualitative embedded case study ...
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Embedded Case Study Methods: Integrating Quantitative and Qualitative
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Embedded Case Study Methods: Integrating
In an embedded case study, the starting and ending points are the comprehension of the case as a whole in its real-world context. However, in the course of analysis, the case will be faceted either by different perspectives of inquiry or by several subunits. The multiplicity of evidence is investigated at least partly in subunits, which focus ...
PDF Create a flyer for "Embedded Case Study Methods"
The authors show how embedded case studies can be employed to qualitative, quantitative and mixed research approaches. The text provides examples of how embedded case studies can be used in different fields to solve complex research problems in areas such as: neuropsychology, educational sciences, law, business and environmental science.
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PDF The FACES Embedded Case Study: Documenting the Methodology and Early
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The system's hardware is composed of a general-purpose microprocessor connected to some peripherals through busses. The software development provides the firmware executed by the microprocessor. ... This case study builds a basic embedded system, composed of the MicroBlaze processor , internal memory, and some peripherals. The system controls ...
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Embedded Case Study Methods. Integrating Quantitative and Qualitative Knowledge

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Introduction to Embedded Systems and C++

Overview of C++ Programming Language

Applications of C++ in Embedded Systems

Real-time Operating Systems

Mobile and Wireless Technologies

Case Studies of C++ in Embedded Systems

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Consumer Electronics Sector

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