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What Is a Case Study?

Weighing the pros and cons of this method of research

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Cara Lustik is a fact-checker and copywriter.

Verywell / Colleen Tighe

• Pros and Cons

What Types of Case Studies Are Out There?

Where do you find data for a case study, how do i write a psychology case study.

A case study is an in-depth study of one person, group, or event. In a case study, nearly every aspect of the subject's life and history is analyzed to seek patterns and causes of behavior. Case studies can be used in many different fields, including psychology, medicine, education, anthropology, political science, and social work.

The point of a case study is to learn as much as possible about an individual or group so that the information can be generalized to many others. Unfortunately, case studies tend to be highly subjective, and it is sometimes difficult to generalize results to a larger population.

While case studies focus on a single individual or group, they follow a format similar to other types of psychology writing. If you are writing a case study, we got you—here are some rules of APA format to reference.  

At a Glance

A case study, or an in-depth study of a person, group, or event, can be a useful research tool when used wisely. In many cases, case studies are best used in situations where it would be difficult or impossible for you to conduct an experiment. They are helpful for looking at unique situations and allow researchers to gather a lot of˜ information about a specific individual or group of people. However, it's important to be cautious of any bias we draw from them as they are highly subjective.

What Are the Benefits and Limitations of Case Studies?

A case study can have its strengths and weaknesses. Researchers must consider these pros and cons before deciding if this type of study is appropriate for their needs.

One of the greatest advantages of a case study is that it allows researchers to investigate things that are often difficult or impossible to replicate in a lab. Some other benefits of a case study:

• Allows researchers to capture information on the 'how,' 'what,' and 'why,' of something that's implemented
• Gives researchers the chance to collect information on why one strategy might be chosen over another
• Permits researchers to develop hypotheses that can be explored in experimental research

On the other hand, a case study can have some drawbacks:

• It cannot necessarily be generalized to the larger population
• Cannot demonstrate cause and effect
• It may not be scientifically rigorous
• It can lead to bias

Researchers may choose to perform a case study if they want to explore a unique or recently discovered phenomenon. Through their insights, researchers develop additional ideas and study questions that might be explored in future studies.

It's important to remember that the insights from case studies cannot be used to determine cause-and-effect relationships between variables. However, case studies may be used to develop hypotheses that can then be addressed in experimental research.

Case Study Examples

There have been a number of notable case studies in the history of psychology. Much of  Freud's work and theories were developed through individual case studies. Some great examples of case studies in psychology include:

• Anna O : Anna O. was a pseudonym of a woman named Bertha Pappenheim, a patient of a physician named Josef Breuer. While she was never a patient of Freud's, Freud and Breuer discussed her case extensively. The woman was experiencing symptoms of a condition that was then known as hysteria and found that talking about her problems helped relieve her symptoms. Her case played an important part in the development of talk therapy as an approach to mental health treatment.
• Phineas Gage : Phineas Gage was a railroad employee who experienced a terrible accident in which an explosion sent a metal rod through his skull, damaging important portions of his brain. Gage recovered from his accident but was left with serious changes in both personality and behavior.
• Genie : Genie was a young girl subjected to horrific abuse and isolation. The case study of Genie allowed researchers to study whether language learning was possible, even after missing critical periods for language development. Her case also served as an example of how scientific research may interfere with treatment and lead to further abuse of vulnerable individuals.

Such cases demonstrate how case research can be used to study things that researchers could not replicate in experimental settings. In Genie's case, her horrific abuse denied her the opportunity to learn a language at critical points in her development.

This is clearly not something researchers could ethically replicate, but conducting a case study on Genie allowed researchers to study phenomena that are otherwise impossible to reproduce.

There are a few different types of case studies that psychologists and other researchers might use:

• Collective case studies : These involve studying a group of individuals. Researchers might study a group of people in a certain setting or look at an entire community. For example, psychologists might explore how access to resources in a community has affected the collective mental well-being of those who live there.
• Descriptive case studies : These involve starting with a descriptive theory. The subjects are then observed, and the information gathered is compared to the pre-existing theory.
• Explanatory case studies : These   are often used to do causal investigations. In other words, researchers are interested in looking at factors that may have caused certain things to occur.
• Exploratory case studies : These are sometimes used as a prelude to further, more in-depth research. This allows researchers to gather more information before developing their research questions and hypotheses .
• Instrumental case studies : These occur when the individual or group allows researchers to understand more than what is initially obvious to observers.
• Intrinsic case studies : This type of case study is when the researcher has a personal interest in the case. Jean Piaget's observations of his own children are good examples of how an intrinsic case study can contribute to the development of a psychological theory.

The three main case study types often used are intrinsic, instrumental, and collective. Intrinsic case studies are useful for learning about unique cases. Instrumental case studies help look at an individual to learn more about a broader issue. A collective case study can be useful for looking at several cases simultaneously.

The type of case study that psychology researchers use depends on the unique characteristics of the situation and the case itself.

There are a number of different sources and methods that researchers can use to gather information about an individual or group. Six major sources that have been identified by researchers are:

• Archival records : Census records, survey records, and name lists are examples of archival records.
• Direct observation : This strategy involves observing the subject, often in a natural setting . While an individual observer is sometimes used, it is more common to utilize a group of observers.
• Documents : Letters, newspaper articles, administrative records, etc., are the types of documents often used as sources.
• Interviews : Interviews are one of the most important methods for gathering information in case studies. An interview can involve structured survey questions or more open-ended questions.
• Participant observation : When the researcher serves as a participant in events and observes the actions and outcomes, it is called participant observation.
• Physical artifacts : Tools, objects, instruments, and other artifacts are often observed during a direct observation of the subject.

If you have been directed to write a case study for a psychology course, be sure to check with your instructor for any specific guidelines you need to follow. If you are writing your case study for a professional publication, check with the publisher for their specific guidelines for submitting a case study.

Here is a general outline of what should be included in a case study.

Section 1: A Case History

This section will have the following structure and content:

Background information : The first section of your paper will present your client's background. Include factors such as age, gender, work, health status, family mental health history, family and social relationships, drug and alcohol history, life difficulties, goals, and coping skills and weaknesses.

Description of the presenting problem : In the next section of your case study, you will describe the problem or symptoms that the client presented with.

Describe any physical, emotional, or sensory symptoms reported by the client. Thoughts, feelings, and perceptions related to the symptoms should also be noted. Any screening or diagnostic assessments that are used should also be described in detail and all scores reported.

Your diagnosis : Provide your diagnosis and give the appropriate Diagnostic and Statistical Manual code. Explain how you reached your diagnosis, how the client's symptoms fit the diagnostic criteria for the disorder(s), or any possible difficulties in reaching a diagnosis.

Section 2: Treatment Plan

This portion of the paper will address the chosen treatment for the condition. This might also include the theoretical basis for the chosen treatment or any other evidence that might exist to support why this approach was chosen.

• Cognitive behavioral approach : Explain how a cognitive behavioral therapist would approach treatment. Offer background information on cognitive behavioral therapy and describe the treatment sessions, client response, and outcome of this type of treatment. Make note of any difficulties or successes encountered by your client during treatment.
• Humanistic approach : Describe a humanistic approach that could be used to treat your client, such as client-centered therapy . Provide information on the type of treatment you chose, the client's reaction to the treatment, and the end result of this approach. Explain why the treatment was successful or unsuccessful.
• Psychoanalytic approach : Describe how a psychoanalytic therapist would view the client's problem. Provide some background on the psychoanalytic approach and cite relevant references. Explain how psychoanalytic therapy would be used to treat the client, how the client would respond to therapy, and the effectiveness of this treatment approach.
• Pharmacological approach : If treatment primarily involves the use of medications, explain which medications were used and why. Provide background on the effectiveness of these medications and how monotherapy may compare with an approach that combines medications with therapy or other treatments.

This section of a case study should also include information about the treatment goals, process, and outcomes.

When you are writing a case study, you should also include a section where you discuss the case study itself, including the strengths and limitiations of the study. You should note how the findings of your case study might support previous research. 

In your discussion section, you should also describe some of the implications of your case study. What ideas or findings might require further exploration? How might researchers go about exploring some of these questions in additional studies?

Need More Tips?

Here are a few additional pointers to keep in mind when formatting your case study:

• Never refer to the subject of your case study as "the client." Instead, use their name or a pseudonym.
• Read examples of case studies to gain an idea about the style and format.
• Remember to use APA format when citing references .

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach .  BMC Med Res Methodol . 2011;11:100.

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach . BMC Med Res Methodol . 2011 Jun 27;11:100. doi:10.1186/1471-2288-11-100

Gagnon, Yves-Chantal.  The Case Study as Research Method: A Practical Handbook . Canada, Chicago Review Press Incorporated DBA Independent Pub Group, 2010.

Yin, Robert K. Case Study Research and Applications: Design and Methods . United States, SAGE Publications, 2017.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

The theory contribution of case study research designs

• Original Research
• Open access
• Published: 16 February 2017
• Volume 10 , pages 281–305, ( 2017 )

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• Hans-Gerd Ridder 1  

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The objective of this paper is to highlight similarities and differences across various case study designs and to analyze their respective contributions to theory. Although different designs reveal some common underlying characteristics, a comparison of such case study research designs demonstrates that case study research incorporates different scientific goals and collection and analysis of data. This paper relates this comparison to a more general debate of how different research designs contribute to a theory continuum. The fine-grained analysis demonstrates that case study designs fit differently to the pathway of the theory continuum. The resulting contribution is a portfolio of case study research designs. This portfolio demonstrates the heterogeneous contributions of case study designs. Based on this portfolio, theoretical contributions of case study designs can be better evaluated in terms of understanding, theory-building, theory development, and theory testing.

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Case Study Research

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1 Introduction

Case study research scientifically investigates into a real-life phenomenon in-depth and within its environmental context. Such a case can be an individual, a group, an organization, an event, a problem, or an anomaly (Burawoy 2009 ; Stake 2005 ; Yin 2014 ). Unlike in experiments, the contextual conditions are not delineated and/or controlled, but part of the investigation. Typical for case study research is non-random sampling; there is no sample that represents a larger population. Contrary to quantitative logic, the case is chosen, because the case is of interest (Stake 2005 ), or it is chosen for theoretical reasons (Eisenhardt and Graebner 2007 ). For within-case and across-case analyses, the emphasis in data collection is on interviews, archives, and (participant) observation (Flick 2009 : 257; Mason 2002 : 84). Case study researchers usually triangulate data as part of their data collection strategy, resulting in a detailed case description (Burns 2000 ; Dooley 2002 ; Eisenhardt 1989 ; Ridder 2016 ; Stake 2005 : 454). Potential advantages of a single case study are seen in the detailed description and analysis to gain a better understanding of “how” and “why” things happen. In single case study research, the opportunity to open a black box arises by looking at deeper causes of the phenomenon (Fiss 2009 ). The case data can lead to the identification of patterns and relationships, creating, extending, or testing a theory (Gomm et al. 2000 ). Potential advantages of multiple case study research are seen in cross-case analysis. A systematic comparison in cross-case analysis reveals similarities and differences and how they affect findings. Each case is analyzed as a single case on its own to compare the mechanisms identified, leading to theoretical conclusions (Vaughan 1992 : 178). As a result, case study research has different objectives in terms of contributing to theory. On the one hand, case study research has its strength in creating theory by expanding constructs and relationships within distinct settings (e.g., in single case studies). On the other hand, case study research is a means of advancing theories by comparing similarities and differences among cases (e.g., in multiple case studies).

Unfortunately, such diverging objectives are often neglected in case study research. Burns ( 2000 : 459) emphasizes: “The case study has unfortunately been used as a ‘catch –all’ category for anything that does not fit into experimental, survey, or historical methods.”

Therefore, this paper compares case study research designs. Such comparisons have been conducted previously regarding their philosophical assumptions and orientations, key elements of case study research, their range of application, and the lacks of methodological procedures in publications. (Baxter and Jack 2008 ; Dooley 2002 ; Dyer and Wilkins 1991 ; Piekkari et al. 2009 ; Welch et al. 2011 ). This paper aims to compare case study research designs regarding their contributions to theory.

Case study research designs will be analyzed regarding their various strengths on a theory continuum. Edmondson and McManus ( 2007 ) initiated a debate on whether the stage of theory fits to research questions, style of data collection, and analyses. Similarly, Colquitt and Zapata-Phelan ( 2007 ) created a taxonomy capturing facets of empirical article’s theoretical contributions by distinguishing between theory-building and theory testing. Corley and Gioia ( 2011 ) extended this debate by focusing on the practicality of theory and the importance of prescience. While these papers consider the whole range of methodological approaches on a higher level, they treat case studies as relatively homogeneous. This paper aims to delve into a deeper level of analysis by solely focusing on case study research designs and their respective fit on this theory continuum. This approach offers a more fine-grained understanding that sheds light on the diversity of case study research designs in terms of their differential theory contributions. Such a deep level of analysis on case study research designs enables more rigor in theory contribution. To analyze alternative case study research designs regarding their contributions to theory, I engage into the following steps:

First, differences between case study research designs are depicted. I outline and compare the case study research designs with regard to the key elements, esp. differences in research questions, frameworks, sampling, data collection, and data analysis. These differences result in a portfolio of various case study research designs.

Second, I outline and substantiate a theory continuum that varies between theory-building, theory development, and testing theory. Based on this continuum, I analyze and discuss each of the case study research designs with regard to their location on the theory continuum. This analysis is based on a detailed differentiation of the phenomenon (inside or outside the theory), the status of the theory, research strategy, and methods.

As a result, the contribution to the literature is a portfolio of case study research designs explicating their unique contributions to theory. The contribution of this paper lies in a fine-grained analysis of the interplay of methods and theory (van Maanen et al. 2007 ) and the methodological fit (Edmondson and McManus 2007 ) of case study designs and the continuum of theory. It demonstrates that different designs have various strengths and that there is a fit between case study designs and different points on a theory continuum. If there is no clarity as to whether a case study design aims at creating, elaborating, extending, or testing theory, the contribution to theory is difficult to identify for authors, reviewers, and readers. Consequently, this paper aims to clarify at which point of the continuum of theory case study research designs can provide distinct contributions that can be identified beyond their traditionally claimed exploratory character.

2 Differences across case study design: a portfolio approach

Only few papers have compared case study research designs so far. In all of these comparisons, the number of designs differs as well as the issues under consideration. In an early debate between Dyer and Wilkins ( 1991 ) and Eisenhardt ( 1991 ), Dyer and Wilkins compared the case study research design by Eisenhardt ( 1989 ) with “classical” case studies. The core of the debate concerns a difference between in-depth single case studies (classical case study) to a focus on the comparison of multiple cases. Dyer and Wilkins ( 1991 : 614) claim that the essence of a case study lies in the careful study of a single case to identify new relationships and, as a result, question the Eisenhardt approach which puts a lot of emphasis on comparison of multiple cases. Eisenhardt, on the contrary, claims that multiple cases allow replication between cases and is, therefore, seen as a means of corroboration of propositions (Eisenhardt 1991 ). Classical case studies prefer deep descriptions of a single case, considering the context to reveal insights into the single case and by that elaborate new theories. The comparison of multiple cases, therefore, tends—in the opinion of Dyer and Wilkens—to surface descriptions. This weakens the possibility of context-related, rich descriptions. While, in classic case study, good stories are the aim, the development of good constructs and their relationships is aimed in Eisenhardt’s approach. Eisenhardt ( 1991 : 627) makes a strong plea on more methodological rigor in case study research, while Dyer and Wilkins ( 1991 : 613) criticize that the new approach “… includes many of the attributes of hypothesis-testing research (e.g., sampling and controls).”

Dooley ( 2002 : 346) briefly takes the case study research designs by Yin (1994) and Eisenhardt ( 1989 ) as exemplars of how the processes of case study research can be applied. The approach by Eisenhardt is seen as an exemplar that advances conceptualization and operationalization in the phases of theory-building, while the approach by Yin is seen as exemplar that advances minimally conceptualized and operationalized existing theory.

Baxter and Jack ( 2008 ) describe the designs by Yin (2003) and Stake ( 1995 ) to demonstrate key elements of qualitative case study. The authors outline and carefully compare the approaches by Yin and Stake in conducting the research process, neglecting philosophical differences and theoretical goals.

Piekkari et al. ( 2009 ) outline the methodological richness of case study research using the approaches of Yin et al. (1998), and Stake. They specifically exhibit the role of philosophical assumptions, establishing differences in conventionally accepted practices of case study research in published papers. The authors analyze 135 published case studies in four international business journals. The analysis reveals that, in contrast to the richness of case study approaches, the majority of published case studies draw on positivistic foundations and are narrowly declared as explorative with a lack of clarity of the theoretical purpose of the case study. Case studies are often designed as multiple case studies with cross-sectional designs based on interviews. In addition to the narrow use of case study research, the authors find out that “… most commonly cited methodological literature is not consistently followed” (Piekkari et al. 2009 : 567).

Welch et al. ( 2011 ) develop a typology of theorizing modes in case study methods. Based on the two dimensions “contextualization” and “causal explanation”, they differentiate in their typology between inductive theory-building (Eisenhardt), interpretive sensemaking (Stake), natural experiment (Yin), and contextualised explanation (Ragin/Bhaskar). The typology is used to analyze 199 case studies from three highly ranked journals over a 10-year period for whether the theorizing modes are exercised in the practice of publishing case studies. As a result, the authors identify a strong emphasis on the exploratory function of case studies, neglecting the richness of case study methods to challenge, refine, verify, and test theories (Welch et al. 2011 : 755). In addition, case study methods are not consistently related to theory contribution: “By scrutinising the linguistic elements of texts, we found that case researchers were not always clear and consistent in the way that they wrote up their theorising purpose and process” (Welch et al. 2011 : 756).

As a result, the comparisons reveal a range of case study designs which are rarely discussed. In contrast, published case studies are mainly introduced as exploratory design. Explanatory, interpretivist, and critical/reflexive designs are widely neglected, narrowing the possible applications of case study research. In addition, comparisons containing an analysis of published case studies reveal a low degree in accuracy when applying case study methods.

What is missing is a comparison of case study research designs with regard to differences in the contribution to theory. Case study designs have different purposes in theory contribution. Confusing these potential contributions by inconsistently utilizing the appropriate methods weakens the contribution of case studies to scientific progress and, by that, damages the reputation of case studies.

To conduct such a comparison, I consider the four case study research approaches of Yin, Eisenhardt, Burawoy, and Stake for the following reasons.

These approaches are the main representatives of case study research design outlined in the comparisons elaborated above (Baxter and Jack 2008 ; Dooley 2002 ; Dyer and Wilkins 1991 ; Piekkari et al. 2009 ; Welch et al. 2011 ). I follow especially the argument by Piekkari et al. ( 2009 ) that these approaches contain a broad spectrum of methodological foundations of exploratory, explanatory, interpretivist, and critical/reflexive designs. The chosen approaches have an explicit and detailed methodology which can be reconstructed and compared with regard to their theory contribution. Although there are variations in the application of the designs, to the best of my knowledge, the designs represent the spectrum of case study methodologies. A comparison of these methodologies revealed main distinguishable differences. To highlight these main differences, I summarized these differences into labels of “no theory first”; “gaps and holes”; “social construction of reality”; and “anomalies”.

I did not consider descriptions of case study research in text books which focus more or less on general descriptions of the common characteristics of case studies, but do not emphasize differences in methodologies and theory contribution. In addition, I did not consider so-called “home grown” designs (Eisenhardt 1989 : 534) which lack a systematic and explicit demonstration of the methodology and where “… the hermeneutic process of inference—how all these interviews, archival records, and notes were assembled into a coherent whole, what was counted and what was discounted—remains usually hidden from the reader” (Fiss 2009 : 425).

Finally, although often cited in the methodological section of case studies, books are not considered which concentrate on data analysis in qualitative research per se (Miles et al. 2014 ; Corbin and Strauss 2015 ). Therefore, to analyze the contribution of case study research to the scientific development, it needs to compare explicit methodology. This comparison will be outlined in the following sections with regard to main methodological steps: the role of the case, the collection of data, and the analysis of data.

2.1 Case study research design 1: no theory first

A popular template for building theory from case studies is a paper by Eisenhardt ( 1989 ). It follows a dramaturgy with a precise order of single steps for constructing a case study and is one of the most cited papers in methods sections (Ravenswood 2011 ). This is impressive for two reasons. On the one hand, Eisenhardt herself has provided a broader spectrum of case study research designs in her own empirical papers, for example, by combining theory-building and theory elaboration (Bingham and Eisenhardt 2011 ). On the other hand, she “updated” her design in a paper with Graebner (Eisenhardt and Graebner 2007 ), particularly by extending the range of inductive theory-building. These developments do not seem to be seriously considered by most authors, as differences and elaborations of this spectrum are rarely found in publications. Therefore, in the following, I focus on the standards provided by Eisenhardt ( 1989 ) and Eisenhardt and Graebner ( 2007 ) as exemplary guidelines.

Eisenhardt follows the ideal of ‘no theory first’ to capture the richness of observations without being limited by a theory. The research question may stem from a research gap meaning that the research question is of relevance. Tentative a priori constructs or variables guide the investigation, but no relationships between such constructs or variables are assumed so far: “Thus, investigators should formulate a research problem and possibly specify some potentially important variables, with some reference to extant literature. However, they should avoid thinking about specific relationships between variables and theories as much as possible, especially at the outset of the process” (Eisenhardt 1989 : 536).

Cases are chosen for theoretical reasons: for the likelihood that the cases offer insights into the phenomenon of interest. Theoretical sampling is deemed appropriate for illuminating and extending constructs and identifying relationships for the phenomenon under investigation (Eisenhardt and Graebner 2007 ). Cases are sampled if they provide an unusual phenomenon, replicate findings from other cases, use contrary replication, and eliminate alternative explanations.

With respect to data collection, qualitative data are the primary choice. Data collection is based on triangulation, where interviews, documents, and observations are often combined. A combination of qualitative data and quantitative data is possible as well (Eisenhardt 1989 : 538). Data analysis is conducted via the search for within-case patterns and cross-case patterns. Systematic procedures are conducted to compare the emerging constructs and relationships with the data, eventually leading to new theory.

A good exemplar for this design is the investigation of technology collaborations (Davis and Eisenhardt 2011 ). The purpose of this paper is to understand processes by which technology collaborations support innovations. Eight technology collaborations among ten firms were sampled for theoretical reasons. Qualitative and quantitative data were used from semi-structured interviews, public and private data, materials provided by informants, corporate intranets, and business publications. The data was measured, coded, and triangulated. Writing case histories was a basis for within-case and cross-case analysis. Iteration between cases and emerging theory and considering the relevant literature provided the basis for the development of a theoretical framework.

Another example is the investigation of what is learned in organizational processes (Bingham and Eisenhardt 2011 ). This paper demonstrates that the case study design is not only used for theory-building, but can also be combined with theory elaboration. Based on the lenses of the organizational knowledge literature, organizational routines literature, and heuristics literature, six technology-based ventures were chosen for theoretical reasons. Several data sources were used, especially quantitative and qualitative data from semi-structured interviews, archival data, observations, e-mails, phone calls, and follow-up interviews. Within-case analysis revealed what each firm has learned from process experience. Cross-case analysis revealed emerging patterns from which tentative constructs and propositions were formed. In replication logic constructs and propositions were refined across the cases. When mirroring the findings with the literature, both the emergences of the constructs were compared and unexpected types were considered. The iteration of theory and data as well as the consideration of related research sharpened the theoretical arguments, eventually leading to a theoretical framework. “Thus, we combined theory elaboration (Lee 1999 ) and theory generation (Eisenhardt 1989 )” (Bingham and Eisenhardt 2011 : 1448).

2.2 Case study research design 2: gaps and holes

Contrary to “No Theory First”, case study research design can also aim at specifying gaps or holes in existing theory with the ultimate goal of advancing theoretical explanations (Ridder 2016 ). A well-known template for this case study research design is the book by Yin ( 2014 ). It is a method-orientated handbook of how to design single and multiple case studies with regard to this purpose. Such a case study research design includes: “A ‘how’ and ‘why’ question” (Yin 2014 : 14). Research questions can be identified and shaped using literature to narrow the interest in a specific topic, looking for key studies and identifying questions in these studies. According to Yin’s design, existing theory is the starting point of case study research. In addition, propositions or frameworks provide direction, reflect the theoretical perspective, and guide the search for relevant evidence.

There are different rationales for choosing a single case design (Yin 2014 : 51). Purposeful sampling is conducted if an extreme case or an unusual case is chosen and if rarely observable phenomena can be investigated with regard to unknown matters and their relationships. Common cases allow conclusions for a broader class of cases. Revelatory cases provide the opportunity to investigate into a previously inaccessible inquiry, and the longitudinal study enables one to investigate a single case at several points in time. A rationale for multiple case designs has its strength in replication logic (Yin 2014 : 56). In the case of literal replication, cases are selected to predict similar results. In the case of theoretical replication, cases are selected to predict contrasting results but for theoretical reasons. Yin provides several tactics to increase the reliability (protocol; data base) of the study.

Yin ( 2014 : 103) emphasizes that interviews are one of the most important sources of data collection but considers other sources of qualitative data as well. Data triangulation is designed to narrow problems of construct validity, as multiple sources of data provide multiple measures of the same phenomenon. Yin ( 2014 : 133) offers a number of data analysis strategies (e.g., case description; examining rival explanations) and analytic techniques which are apt to compare the proposed relationships with empirical patterns. Pattern-matching logic compares empirically based patterns with predicted patterns, enabling further data analysis techniques (explanation building, time series analysis, logic models, and cross-case synthesis). In analytical generalization, the theory is compared with the empirical results, leading to the modification or extension of the theory.

An appropriate model for this case study design can be identified in a paper by Ellonen et al. ( 2009 ). The paper is based on the emerging dynamic capability theory. The four cases were chosen for theoretical reasons to deliver an empirical contribution to the dynamic capability theory by investigating the relationship of dynamic capabilities and innovation outcomes. The authors followed a literal replication strategy and identified patterns between dynamic capabilities of the firms and their innovation outcomes.

Shane ( 2000 ) is an author who developed specific propositions from a framework and examined the propositions in eight entrepreneurial cases. Using several sources of interviews and archival data, the author compared the data with the propositions using the pattern-matching logic, which concluded in developing entrepreneurship theory.

2.3 Case study research design 3: social construction of reality

So far, the outlined case study research designs are based on positivist roots, but there is richness and variety in case study research stemming from different philosophical realms. The case study research design by Stake ( 1995 , 2000 , 2005 ), for example, is based on constructivist assumptions and aims to investigate the social construction of reality and meaning (Schwandt 1994 : 125).

According to this philosophical assumption, there is no unique “real world” that preexists independently of human mental activity and symbolic language. The world is a product of socially and historically related interchanges amongst people (social construction). The access to reality is given through social constructions, such as language and shared meanings: “The meaning-making activities themselves are of central interest to social constructionists/constructivists, simply because it is the meaning-making/sense making attributional activities that shape action or (inaction)” (Guba and Lincoln 2005 : 197). Therefore, the researcher is not looking for objective “facts”, nor does he aim at identifying and measuring patterns which can be generalized. Contrarily, the constructivist is researching into specific actions, in specific places, at specific times. The scientist tries to understand the construction and the sharing of meaning (Schwandt 1994 ).

According to Stake ( 2005 ), the direction of the case study is shaped by the interest in the case. In an intrinsic case study, the case itself is of interest. The purpose is not theory-building but curiosity in the case itself. In an instrumental case study, the case itself is of secondary interest. It plays a supportive role, as it facilitates the understanding of a research issue. The case can be typical of other cases. Multiple or collective case study research designs extend the instrumental case study. It is assumed that a number of cases will increase the understanding and support theorizing by comparison of the cases.

The differentiation by Stake ( 1995 , 2005 ) into intrinsic and instrumental cases guides the purposive sampling strategy. In intrinsic case studies, the case is, by definition, already selected. The researcher looks for specific characteristics, aiming for thick descriptions with the opportunity to learn. Representativeness or generalization is not considered. In instrumental case study design, purposive sampling leads to the phenomenon under investigation. In multiple case study designs, the ability to compare cases enhances the opportunity to theorize.

A case study requires an integrated, holistic comprehension of the case complexity. According to Stake ( 2005 ), the case study is constructed by qualitative data, such as observations, interviews, and documents. Triangulation first serves as clarification of meaning. Second, the researcher is interested in the diversity of perceptions.

Two methods of data analysis are considered in such qualitative case study design: direct interpretation and categorical aggregation (Stake 1995 : 74). The primary task of an intrinsic case study is to understand the case. This interpretation is offered to the reader, but the researcher has to provide the material in a sufficient way (thick descriptions), so that the reader can learn from the case as well as draw his or her own conclusions. Readers can thus make some generalizations based on personal and vicarious experiences (“naturalistic generalization”). In instrumental case studies, the understanding of phenomena and relationships leads to categorical aggregation, and the focus is on how the phenomenon exists across several cases.

Greenwood and Suddaby ( 2006 ), for example, used the instrumental case study design by Stake, combining network location theory and dialectical theory. They identified new dynamics creating a process model of elite institutional entrepreneurship.

Ituma et al. ( 2011 ) highlighted the social construction of reality in their study of career success. The majority of career studies have been conducted in Western countries and findings have been acknowledged as universally applicable. The authors demonstrated that realities of managers in other areas are constructed differently. As a result of their study, they provided a contextually sensitive frame for the analysis of career outcomes.

2.4 Case study research design 4: anomalies

Identifying anomalies as a basis for further research is common in management and organization research (Gilbert and Christensen 2005 ). In case study research, the extended case study method is used for this case study research design (Ridder 2016 ). Following Burawoy ( 1991 , 1998 , 2009 ), the research question derives from curiosity. Researchers normally look at what is “interesting” and what is “surprising” in a social situation that existing theory cannot explain. Initially, it is not important whether the expectations develop from some popular belief, stereotype, or from an academic theory. The extended case study research design is guided by anomalies that the previous theory was not able to explain through internal contradictions of theory, theoretical gaps, or silences. An anomaly does not reject theory, but rather demonstrates that the theory is incomplete. Theory is aimed to be improved by “… turning anomalies into exemplars” (Burawoy 1991 : 10).

The theoretical sampling strategy in this case study research design stems from the theoretical failure in confrontation with the site. According to the reflexive design, such cases do not favour individuals or isolated phenomena, but social situations in which a comparative strategy allows the tracing of differences across the cases to external forces.

In the extended case study, the researcher deals with qualitative data, but also considers the broader complex social situation. The researcher engages into a dialogue with the respondents (Burawoy ( 1991 , 1998 , 2009 ). An interview is an intervention into the life of a respondent. By means of mutual interaction it is possible to discover the social order under investigation. The observer has to unpack those situational experiences by means of participant observation and mutual interpretation. This situational comprehension aims at understanding divergent “voices”, reflecting the variety of respondents’ understandings of the social situation.

As in other sciences, these voices have to be aggregated. This aggregation of multiple readings of a single case is conducted by turning the aggregation into social processes: “The move from situation to process is accomplished differently in different reflexive methods, but it is always reliant on existing theory” (Burawoy 2009 : 41). Social processes are now traced to the external field as the conditions of the social processes. Consequently, this leads to the question concerning “… how those micro situations are shaped by wider structures” (Burawoy 1991 : 282). “Reflexive science insists, therefore, on studying the everyday world from the standpoint of its structuration, that is, by regarding it as simultaneously shaped by and shaping an external field of forces” (Burawoy 2009 : 42). Such social fields cannot be held constant, which undermines the idea of replication. The external field is in continuous flux. Accordingly, social forces that influence the social processes are identified, shaping the phenomenon under investigation. Extension of theory does not target representativeness as a relationship of sample and population. Generality in reflexive science is to reconstruct an existing theory: “We begin with our favorite theory but seek not confirmations but refutations that inspire us to deepen that theory. Instead of discovering grounded theory, we elaborate existing theory. We do not worry about the uniqueness of our case, since we are not as interested in its representativeness as its contribution to reconstructing theory. Our theoretical point of departure can range from the folk theory of participants to any abstract law. We consider only that the scientist consider it worth developing” (Burawoy 2009 : 43). Such elaboration stems from the identification of anomalies and offers new predictions with regard to the theory.

It is somewhat surprising that the extended case study design has been neglected in the management literature so far, and it appears that critical reflexive principles have to be resurrected as they have been in other disciplines (see the overview at Wadham and Warren 2014 ). Examples in the management and organization literature are rare. Danneels ( 2011 ) used the extended case study design to extend the dynamic capabilities theory. In his famous Smith Corona case, Danneels shows how a company tried to change its resource base. Based on detailed data, the Smith Corona case provides insights into the resource alteration processes and how dynamic capabilities operate. As a result, the paper fills a process gap in dynamic capability theory. Iterating between data collection and analysis, Danneels revealed resource cognition as an element not considered so far in dynamic capability theory. The use of the extended case study method is limited to the iteration of data and theory. First, there is “running exchange” (Burawoy 1991 : 10) between field notes and analysis. Second, there is iteration between analysis and existing theory. Unlike Burawoy, who aims to reconstruct existing theory on the basis of “emergent anomalies” (Burawoy 1991 : 11) considering social processes and external forces, Danneels confronts the dynamic capabilities literature with the Smith Corona case to extend the theory of dynamic capabilities.

2.5 A comparison of case study research processes

Commonalities and differences emerged from the comparison of the designs. Table  1 provides a brief summary of these main differences and the resulting portfolio of case study research designs which will be discussed in more detail.

There is an extensive range between the different designs regarding the research processes. In “no theory first”, there is a broad and tentative research question with some preliminary variables at the outset. The research question may be modified during the study as well as the variables. This design avoids any propositions regarding relationships.

On the contrary, the research question in “gaps and holes” is strongly related to existing theory, focusing on “how and why” questions. The existing theory contains research gaps which, once identified within the existing theory, lead accordingly to assumed relationships which are the basis for framework and propositions to be matched by empirical data. This broad difference is even more elaborated by a design that aims the “social construction of reality”. There is no research question at the outset, but a curiosity in the case or the case is a facilitator to understand a research issue. This is far away from curiosity in the “anomaly approach”. Here, the research question is inspired by questioning why an anomaly cannot be explained by the existing theory. What kind of gaps, silences, or internal contradictions demonstrates the insufficiency of the existing theory?

Various sampling strategies are used across these case study research designs, including theoretical sampling and purposeful sampling, which serve different objectives. Theoretical sampling in “no theory first” aims at selecting a case or cases that are appropriate to highlight new or extend preliminary constructs and reveal new relationships. There is a distinct difference from theoretical sampling in the “anomalies” approach. Such a sampling strategy aims to choose a case that is a demonstration of the failure of the theory. In “gaps and holes” sampling is highly focused on the purpose of the case study. Extreme and unusual cases have other purposes compared to common cases or revelatory cases. A single case may be chosen to investigate deeply into new phenomena. A multiple case study may serve a replication logic by which the findings have relevance beyond the cases under investigation. In “social construction of reality”, the sampling is purposeful as well, but for different reasons. Either the case is of interest per se or the case represents a good opportunity to understand a theoretical issue.

Although qualitative data are preferred in all of the designs, quantitative data are seen as a possible opportunity to strengthen cases by such data. Nevertheless, in “social construction of reality”, there is a strong emphasis on thick descriptions and a holistic understanding of the case. This is in contrast to a more construct- and variable- oriented collection of data in “no theory first” and “gaps and holes”. In addition, in contrast to that, the “anomaly” approach is the only design that receives data from dialogue between observer and participants and participant observation.

Finally, data analysis lies within a wide range. In “no theory first”, the research process is finalized by inspecting the emerging constructs within the case or across cases. Based on a priory constructs, systematic comparisons reveal patterns and relationships resulting in a tentative theory. On the contrary, in “gaps and holes”, a tentative theory exists. The final analysis concentrates on the matching of the framework or propositions with patterns from the data. While both of these approaches condense data, the approach of “social construction of reality” ends the research process with thick descriptions of the case to learn from the case or with categorical comparisons. In the “anomaly” approach, the data analysis is aggregation of data, but these aggregated data are related to its external field and their pressures and influences by structuration to reconstruct the theory.

As a result, it is unlikely that the specified case study designs contribute to theory in a homogeneous manner. This result will be discussed in light of the question regarding how these case study designs can inform theory at several points of a continuum of theory. This analysis will be outlined in the following sections. In a first step, I review the main elements of a theory continuum. In a second step, I discuss the respective contribution of the previously identified case study research designs to the theory continuum.

3 Elements of a theory continuum

What a theory is and what a theory is not is a classic debate (Sutton and Staw 1995 ; Weick 1995 ). Often, theories are described in terms of understanding relationships between phenomena which have not been or were not well understood before (Chiles 2003 ; Edmondson and McManus 2007 ; Shah and Corley 2006 ), but there is no overall acceptance as to what constitutes a theory. Theory can be seen as a final product or as a continuum, and there is an ongoing effort to define different stages of this continuum (Andersen and Kragh 2010 ; Colquitt and Zapata-Phelan 2007 ; Edmondson and McManus 2007 ; Snow 2004 ; Swedberg 2012 ). In the following section, basic elements of the theory and the construction of the theory continuum are outlined.

3.1 Basic elements of a theory

Most of the debate concerning what a theory is comprises three basic elements (Alvesson and Kärreman 2007 ; Bacharach 1989 ; Dubin 1978 ; Kaplan 1998 ; Suddaby 2010 ; Weick 1989 , 1995 ; Whetten 1989 ). A theory comprises components (concepts and constructs), used to identify the necessary elements of the phenomenon under investigation. The second is relationships between components (concepts and constructs), explaining the how and whys underlying the relationship. Third, temporal and contextual boundaries limit the generalizability of the theory. As a result, definitions of theory emphasize these components, relationships, and boundaries:

“It is a collection of assertions, both verbal and symbolic, that identifies what variables are important for what reasons, specifies how they are interrelated and why, and identifies the conditions under which they should be related or not related” (Campbell 1990 : 65).

“… a system of constructs and variables in which the constructs are related to each other by propositions and the variables are related to each other by hypotheses” (Bacharach 1989 : 498).

“Theory is about the connections among phenomena, a story about why acts, events, structure, and thoughts occur. Theory emphasizes the nature of causal relationships, identifying what comes first as well as the timing of such events” (Sutton and Staw 1995 : 378).

“… theory is a statement of concepts and their interrelationships that shows how and/or why a phenomenon occurs” (Corley and Gioia 2011 : 12).

The terms “constructs” and “concepts” are either used interchangeably or with different meanings. Positivists use “constructs” as a lens for the observation of a phenomenon (Suddaby 2010 ). Such constructs have to be operationalized and measured. Non-positivists often use the term “concept” as a more value neutral term in place of the term construct (Gioia et al. 2013 ; Suddaby 2010 : 354). Non-positivists aim at developing concepts on the basis of data that contain richness and complexity of the observed phenomenon instead of narrow definitions and operationalizations of constructs. Gioia et al. ( 2013 : 16) clarify the demarcation line between constructs and concepts as follows: “By ‘concept,’ we mean a more general, less well-specified notion capturing qualities that describe or explain a phenomenon of theoretical interest. Put simply, in our way of thinking, concepts are precursors to constructs in making sense of organizational worlds—whether as practitioners living in those worlds, researchers trying to investigate them, or theorists working to model them”.

In sum, theories are a systematic combination of components and their relationships within boundaries. The use of the terms constructs and concepts is related to different philosophical assumptions reflected in different types of case study designs.

3.2 Theory continuum

Weick ( 1995 ) makes an important point that theory is more a continuum than a product. In his view, theorizing is a process containing assumptions, accepted principles, and rules of procedures to explain or predict the behavior of a specified set of phenomena. In similar vein, Gilbert and Christensen ( 2005 ) demonstrate the process character of theory. In their view, a first step of theory building is a careful description of the phenomena. Having already observed and described the phenomena, researchers then classify the phenomena into similar categories. In this phase a framework defines categories and relationships amongst phenomena. In the third phase, researchers build theories to understand (causal) relationships, and in this phase, a model or theory asserts what factors drive the phenomena and under what circumstances. The categorization scheme enables the researchers to predict what they will observe. The “test” offers a confirmation under which circumstances the theory is useful. The early drafts of a theory may be vague in terms of the number and adequateness of factors and their relationships. At the end of the continuum, there may be more precise variables and predicted relationships. These theories have to be extended by boundaries considering time and space.

Across that continuum, different research strategies have various strengths. Several classifications in the literature intend to match research strategies to the different phases of a theory continuum (Andersen and Kragh 2010 ; Colquitt and Zapata-Phelan 2007 ; Edmondson and McManus 2007 ; Snow 2004 ; Swedberg 2012 ). These classifications, although there are differences in terms, comprise three phases with distinguishable characteristics.

3.2.1 Building theory

Here, the careful description of the phenomena is the starting point of theorizing. For example, Snow ( 2004 ) puts this phase as theory discovery, where analytic understandings are generated by means of detailed examination of data. Edmondson and McManus ( 2007 ) state the starting phase of a theory as nascent theory providing answers to new questions revealing new connections among phenomena. Therefore, research questions are open and researchers avoid hypotheses predicting relationships between variables. Swedberg ( 2012 ) highlights the necessity of observation and extensive involvement with the phenomenon at the early stage of theory-building. It is an attempt to understand something of interest by observing and interpreting social facts. Creativity and inspiration are necessary conditions to put observations into concepts and outline a tentative theory.

3.2.2 Developing theory

This tentative theory exists in the second phase of the continuum and has to be developed. Several possibilities exist. In theory extension, the preexisting constructs are extended to other groups or other contexts. In theoretical refinement, a modification of existing theoretical perspectives is conducted (Edmondson and McManus ( 2007 ). New antecedents, moderators, mediators, and outcomes are investigated, enhancing the explanation power of the tentative theory.

3.2.3 Test of theories

Constructs and relationships are well developed to a mature state; measures are precise and operationalized. Such theories are empirically tested with elaborate methods, and research questions are more precise. In the quantitative realm, testing of hypotheses is conducted and statistical analysis is the usual methodological foundation. Recently, researchers criticize that testing theories has become the major focus of scientists today (Delbridge and Fiss 2013 ); testing theories does not only happen to mature theory but to intermediate theory as well. The boundary between theory development and theory testing is not always so clear. While theory development is adding new components to a theory and elaborating the measures, testing a theory implies precise measures, variables, and predicted relationships considering time and space (Gilbert and Christensen ( 2005 ). It will be of interest whether case studies are eligible to test theories as well.

To summarize: there is a conversation as to where on a continuum of theory development, various methods are required to target different contributions to theory (methodological fit). In this discussion, case study research designs have been discussed as a homogeneous set that mostly contributes to theory-building in an exploratory manner. Hence, what is missing is a more differentiated analysis of how case study methodology fits into this conversation, particularly how case study research methodologically fits theory development and theory testing beyond its widely assumed explorative role. In the following section, the above types of case study research designs will be discussed with regard to their positions across the theory continuum.

This distinction adds to existing literature by demonstrating that case study research does not only contribute to theory-building, but also to the development of tentative theories and to the testing of theories. This distinction leads to the next question: is there any interplay between case study research designs and their contributions to the theory continuum? This paper aims at reconciling this interplay with regard to case study design by mirroring phases of a theory continuum with specific types of case study research designs as outlined above. The importance of the interplay between theory and method lies in the capacity to generate and shape theory, while theory can generate and shape method. “In this long march, theory and method surely matter, for they are the tools with which we build both our representations and understandings of organizational life and our reputations” (van Maanen et al. 2007 : 1145). Theory is not the same as methods, but a relationship of this interplay can broaden or restrict both parts of the equation (Swedberg 2012 : 7).

In the following, I discuss how the above-delineated case study research designs unfold their capacities and contribute differently to the theory continuum to build, develop, and test theory.

4 Discussion of the contribution of case study research to a theory continuum

Case study research is diverse with distinct contributions to the continuum of theory. The following table provides the main differences in terms of contributions to theory and specifically locates the case study research designs on the theory continuum (Table  2 ).

In the following, I outline how these specific contributions of case study designs provide better opportunities to enhance the rigor of building theory, developing theory, testing, and reconstructing theory.

4.1 Building theory

In building theory, the phenomenon is new or not understood so far. There is no theory which explains the phenomenon. At the very beginning of the theory continuum, there is curiosity in the phenomenon itself. I focus on the intrinsic case study design which is located in the social construction of reality approach on the very early phase of the theory continuum, as intrinsic case study research design is not theory-building per se but curiosity in the case itself. It is not the purpose of the intrinsic case study to identify abstract concepts and relationships; the specific research strategy lies in the observation and description of a case and the primary method is observation, enabling understanding from personal and vicarious experience. This meets long lasting complaints concerning the lack of (new) theory in management and organization research and signals that the gap between research and management practice is growing. It is argued that the complexity of the reality is not adequately captured (Suddaby et al. 2011 ). It is claimed that management and organization research systematically neglect the dialogue with practice and, as a result, miss new trends or recognize important trends with delay (Corley and Gioia 2011 ).

The specific case study research design’s contribution to theory is in building concrete, context-dependent knowledge with regard to the identification of new phenomena and trends. Openness with regard to the new phenomena, avoiding theoretical preconceptions but building insights out of data, enables the elaboration of meanings and the construction of realities in intrinsic case studies. Intrinsic case studies will enhance the understanding by researcher and reader concerning new phenomena.

The “No Theory First” case study research design is a classic and often cited candidate for building theory. As the phenomenon is new and in the absence of a theory, qualitative data are inspected for aggregation and interpretation. In instrumental case study design, a number of cases will increase the understanding and support building theories by description, aggregation, and interpretation (Stake 2000 ). New themes and concepts are revealed by case descriptions, interviews, documents, and observations, and the analysis of the data enables the specific contribution of the case study design through a constructivist perspective in theory-building.

Although the design by Eisenhardt ( 1989 ) stems from other philosophical assumptions and there are variations and developments in this design, there is still an overwhelming tendency to quote and to stick to her research strategy which aims developing new constructs and new relationships out of real-life cases. Data are collected mainly by interviews, documents, and observations. From within-site analysis and cross-case analysis, themes, concepts, and relationships emerge. Shaping hypotheses comprises: “… refining the definition of the construct and (…) building evidence which measures the construct in each case” (Eisenhardt 1989 : 541). Having identified the emerged constructs, the emergent relationships between constructs are verified in each case. The underlying logic is validation by replication. Cases are treated as experiments in which the hypotheses are replicated case by case. In replication logic cases that confirm the emergent relationships enhance confidence in the validity of the relationships. Disconfirmation of the relationships leads to refinement of the theory. This is similar to Yin’s replication logic, but targets the precision and measurement of constructs and the emerging relationships with regard to the emerging theory. The building of a theory concludes in an understanding of the dynamics underlying the relationship; the primary theoretical reasons for why the relationships exist (Huy 2012 ). Finally, a visual theory with “boxes and arrows” (Eisenhardt and Graebner 2007 ) may visually demonstrate the emerged theory. The theory-building process is finalized by iterating case data, emerging theory, and extant literature.

The “No Theory First” and “Social Construction of Reality” case study research designs, although they represent different philosophical assumptions, adequately fit the theory-building phase concerning new phenomena. The main contribution of case study designs in this phase of the theory continuum lies in the generation of tentative theories.

Case studies at this point of the theory continuum, therefore, have to demonstrate: why the phenomenon is new or of interest; that no previous theory that explains the phenomenon exists; how and why detailed descriptions enhance the understanding of the phenomenon; and how and why new concepts (constructs) and new relationships will enhance our understanding of the phenomenon.

As a result, it has to be demonstrated that the research strategy is in sync with an investigation of a new phenomenon, building a tentative theory.

4.2 Developing theory

In the “Gaps and Holes” case study research design, the phenomenon is partially understood. There is a tentative theory and the research strategy is theory driven. Compared to the theory-building phase, the existence and not the development of propositions differentiate this design along the continuum. The prediction comes first, out of an existing theory. The research strategy and the data have to be confronted by pattern-matching. Pattern-matching is a means to compare the theoretically based predictions with the data in the site: “For case study analysis, one of the most preferred techniques is to use a pattern-matching logic. Such a logic (…) compares an empirically based pattern–that is, one based on the findings from your case study–with a predicted one made before you collected your data (….)” (Yin 2014 : 143). The comparison of propositions and the rich case material is the ground for new elements or relationships within the tentative theory.

Such findings aim to enhance the scientific usefulness of the theory (Corley and Gioia 2011 ). To enhance the validity of the new elements or relationships of the tentative theory, literal replication is a means to confirm the new findings. By that, the theory is developed by new antecedents, moderators, mediators, or outcomes. This modification or extension of the theory contributes to the analytical generalization of the theory.

If new cases provide similar results, the search for regularities is based on more solid ground. Therefore, the strength of case study research in “Gaps and Holes” lies in search for mechanisms in their specific context which can reveal causes and effects more precisely.

The “Gaps and Holes” case study research design is an adequate candidate for this phase of the theory continuum. Case studies at this point of the theory continuum, therefore, have to outline the tentative theory; to demonstrate the lacks and gaps of the tentative theory; to specify how and why the tentative theory is aimed to be extended and/or modified; to develop theoretically based propositions which guide the investigation; and to evaluate new elements, relationships, and mechanisms related to the previous theory (analytical generalization).

As a result and compared to theory-building, a different research strategy exists. While in theory building the research strategy is based on the eliciting of concepts (constructs) and relationships out of data, in theory development, it has to be demonstrated that the research strategy aims to identify new elements and relationships within a tentative theory, identifying mechanisms which explain the phenomenon more precisely.

4.3 Test of theory

In “Gaps and Holes” and “Anomalies”, an extended theory exists. The phenomenon is understood. There is no search for additional components or relationships. Mechanisms seem to explain the functioning or processes of the phenomenon. The research strategy is focused on testing whether the theory holds under different circumstances or under different conditions. Such a test of theories is mainly the domain of experimental and quantitative studies. It is based on previously developed constructs and variables which are the foundation for stating specific testable hypotheses and testing the relations on the basis of quantitative data sets. As a result, highly sophisticated statistical tools enable falsification of the theory. Therefore, testing theory in “Gaps and Holes” is restricted on specific events.

Single case can serve as a test. There is a debate in case study research whether the test of theories is related to the falsification logic of Karl Popper (Flyvbjerg 2006 ; Tsang 2013 ). Another stream of the debate is related to theoretical generalizability (Hillebrand et al. 2001 ; Welch et al. 2011 ). More specifically, test in” Gaps and Holes” is analogous to a single experiment if a single case represents a critical case. If the theory has specified a clear set of propositions and defines the exact conditions within which the theory might explain the phenomena under investigation, a single case study, testing the theory, can confirm or challenge the theory. In sum Yin states: “Overall, the single-case design is eminently justifiable under certain conditions—where the case represents (a) a critical test of existing theory, …” (Yin 2014 : 56). In their survey in the field of International Business, Welch et al. conclude: “In addition, the widespread assumption that the role of the case study lies only in the exploratory, theory-building phase of research downplays its potential to propose causal mechanisms and linkages, and test existing theories” (Welch et al. 2011 : 755).

In multiple case studies, a theoretical replication is a test of theory by comparing the findings with new cases. If a series of cases have revealed pattern-matching between propositions and the data, theoretical replication can be revealed by new waves of cases with contrasting propositions. If the contrasting propositions reveal contrasting results, the findings of the first wave are confirmed. Several possibilities exist to test the initial findings of multiple case studies using different lenses from inside and outside the management realm (Corley and Gioia 2011 ; LePine and Wilcox-King 2010 ; Okhuysen and Bonardi 2011 ; Zahra and Newey 2009 ), but have not become a standard in case study research.

In rival explanations, rival theoretical propositions are developed as a test of the previous theory. This can be distinguished from theoretical replication where contrasting propositions aim to confirm the initial findings. This can, as well, be distinguished from developing theory where rival explanations might develop theory by the elimination of possible influences (interventions, implementations). The rich data enable one to identify internal and external interventions that might be responsible for the findings. Alternative explanations in a new series of cases enable to test, whether a theory “different from the original theory explains the results better (…)” (Yin 2014 : 141).

As a result, it astonishes that theoretical replication and rival explanations, being one of the strengths of case study research, are rarely used. Although the general debate about “lenses” has informed the discussion about theory contributions, this paper demonstrates that there is a wide range of possible integration of vertical or horizontal lenses in case study research design. Case study research designs aiming to test theories have to outline modes of replication and the elimination of rival explanations.

The “anomaly approach” is placed in the final phase of the theory testing, as well. In this approach, a theory exists, but the theory fails to explain anomalies. Burawoy goes a step further. While Yin ( 2014 ) sees a critical case as a test that challenges or contradicts a well formulated theory, in Burawoy’s approach, in contrast to falsification logic (Popper 2002 ), the theory is not rejected but reconstructed. Burawoy relates extended case study design to society and history. Existing theory is challenged by intervention into the social field. Identifying processes of historical roots and social circumstances and considering external forces by structuration lead to the reconstruction of the theory.

It is surprising that this design has been neglected so far in management research. Is there no need to reflect social tensions and distortions in management research? While case study research has, per definition, to investigate phenomena in its natural environment, it is hard to understand why this design has widely been ignored in management and organization research. As a result, testing theory in case study research has to demonstrate that an extended theory exists; a critical case or an anomaly can challenge the theory; theoretical replication and rival explanations will be means to contradict or confirm the theory; and societal circumstances and external forces explain the anomaly.

Compared to theory-building (new concepts/constructs and relationships out of data) and theory development (new elements and relationships within a tentative theory), testing theory challenges extended theory by empirical investigations into failures and anomalies that the current theory cannot explain.

5 Conclusion

Case studies provide a better understanding of phenomena regarding concrete context-dependent knowledge (Andersen and Kragh 2010 ; Flyvbjerg 2006 : 224), but as literature reviews indicate, there is still confusion regarding the adequate utilization of case study methodology (Welch et al. 2011 ). This can be interpreted in a way that authors and even reviewers are not always aware of the methodological fit in case study research. Case study research is mainly narrowed to its “explorative” function, neglecting the scope of possibilities that case study research provides. The claim for more homogeneity of specified rules in case study research misses the important aspect that a method is not a means in itself, but aims at providing improved theories (van Maanen et al. 2007 ). This paper contributes to the fit of case study research designs and the theory continuum regarding the following issues.

5.1 Heterogeneity of case study designs

Although case study research, overall, has similar characteristics, it incorporates various case study research designs that have heterogeneous theoretical goals and use various elements to reach these goals. The analysis revealed that the classical understanding, whereby case study research is adequate for the “exploration” of a theory and quantitative research is adequate for “testing” theory, is oversimplified. Therefore, the theoretical goals of case study research have to be outlined precisely. This study demonstrates that there is variety of case study research designs that have thus far been largely neglected. Case study researchers can utilize the entire spectrum, but have to consider how the phenomenon is related to the theory continuum.

Case study researchers have to demonstrate how they describe new or surprising phenomena, develop new constructs and relationships, add constructs (variables), antecedents, outcomes, moderators, or mediators to a tentative theory, challenge a theory by a critical case, theoretical replication or discarding rival explanations, and reconstruct a theory by tracking failures and anomalies to external circumstances.

5.2 Methodological fit

The rigor of the case study can be enhanced by considering the specific contribution of various case study research designs in each phase of the theory continuum. This paper provides a portfolio of case study research designs that enables researchers and reviewers to evaluate whether the case study arsenal has been adequately located:

At an early phase of the theory continuum, case studies have their strengths in rich descriptions and investigations into new or surprising empirical phenomena and trends. Researchers and readers can benefit from such rich descriptions in understanding and analyzing these phenomena.

Next, on the theory continuum, there is the well-known contribution of case study research in building tentative theory by eliciting constructs or concepts and their relationships out of data.

Third, development of theories is strongly related to literal replication. Strict comparisons, on the one hand, and controlled theoretical advancement, on the other hand, enable the identification of mechanisms, strengthen the notions of causality, and provide generalizable statements.

Fourth, there are specific circumstances under which case study approaches enable one to test theories. This is to confront the theory with a critical case, to test findings of pattern-matching by theoretical replication and discarding rival explanations. Therefore, “Gaps and Holes” provide the opportunity for developing and testing theories through case study design on the theory continuum.

Finally, testing and contradicting theory are not the final rejection of a theory, but is the basis for reconstructing theory by means of case study design. Anomalies can be traced to historical sources, social processes, and external forces.

This paper demonstrates that the precise interplay of case study research designs and theory contributions on the theory continuum is a prerequisite for the contribution of case study research to better theories. If case study research design is differentiated from qualitative research, the intended contribution to theory is stated and designs that fit the aimed contribution to theory are outlined and substantiated; this will critically enhance the rigor of case study research.

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Chapter 3: Research Methods

This study seeks to provide insight into the process of conducting community-based research.  In order to do so, the study utilizes a qualitative case study approach to examine the methodology of community-based research. Two contrasting cases of CBR are described and analyzed in order to understand the issues that arise when conducting CBR, the factors that facilitate or hinder the process, and the benefits of conducting CBR.  Finally, these contrasting cases are considered to determine what this study can contribute to the field of CBR.  This chapter details case study methodology as well as multiple case design.  It also describes the methodology of community-based research, the participants of the study, data collection and analysis, and issues around credibility, including my own subjectivities that may have influenced the research. 

Methodological Framework

In order to explore the collaborative process of conducting community-based research, this study utilizes a qualitative case study approach.  Case studies can be particularly useful for studying a process, program or individual in an in-depth, holistic way that allows for deep understanding (Merriam, 1998).  As Merriam points out,

A case study design is employed to gain an in-depth understanding of the situation and meaning for those involved.  The interest is in process rather than outcomes, in context rather than a specific variable, in discovery rather than confirmation (p. 19).

There are some differences in how researchers define case study.  Some researchers think of case study as the object to be studied (Stake, 2000), while others define case study as a process of investigation (Creswell, 2002).  Creswell defines case study as "an in-depth exploration of a bounded system (e.g., an activity, event, process, or individuals) based on extensive data collection" (p. 485).  Creswell recommends case study as a methodology if the problem to be studied "relates to developing an in-depth understanding of a 'case' or bounded system" (p. 496) and if the purpose is to understand "an event, activity, process, or one or more individuals" (p. 496).  Patton (1990) suggests that case studies are valuable in creating deep understanding of particular people, problems or situations in comprehensive ways.  

This study is particularly suitable for a case study design because it is a bounded system, it is contextual, and it is a study of process (Merriam, 1998).  Like Creswell (2002), Stake (2000) defines case study as the study of a "bounded system" (p. 436).  According to Creswell (2002), "'Bounded' means that the case is separated out for research in terms of time, place, or some physical boundaries" (p. 485).  In other words, it is possible to create limits around the object to be studied (Merriam, 1998).  A case study can focus on a variety of different things.  A case could be an individual, a group, a school, a community (Merriam, 1998), or a case could also include "a program, events, or activities" (Creswell, 2002, p. 485).  The bounded systems in my contrasting case studies are my collaboration with the Coalition for Schools [2] in a western city and my collaboration with community members in a small, rural, mountain community to carry out community-based research.  The boundaries of these two cases are determined by the people and groups that I collaborate with in the CBR process.  

I chose a case study design because it involves "detailed, in-depth data collection involving multiple sources of information rich in context" (Creswell, 1998, p. 61).  Context is a key factor.  According to Merriam (1998), in focusing on a particular phenomenon in a case study, it is impossible to separate the phenomenon from its context.  However, in this study, it is important that the context is understood as part of the process.  As Yin (2003) says, "you would use the case study method because you deliberately wanted to cover contextual conditions-believing that they might be highly pertinent to your phenomenon of study" (p. 13).  Thus, using a case study approach allows for the possibility of gaining significant knowledge about the process of conducting community-based research in particular contexts.   According to Sanders (1981), "Case studies help us to understand processes of events, projects, and programs and to discover context characteristics that will shed light on an issue or object" (p. 44). 

The two case studies each took place over an extended period of time.  The first CBR project lasted nine months, and the second CBR project lasted eight months.  I worked with my collaborative partners to define research problems and questions, develop research designs, collect data, and analyze data.  However, this study does not focus on the data that I collected as part of that CBR work.  Instead, this study focuses on the process of the collaborative experience.  Since the study focuses primarily on the procedures of conducting community-based research, the study is considered a process study.  According to Patton (1990), when carrying out a process study, the "focus is on how something happens rather than on the outcomes or results obtained" (p.94).  And, as Merriam (1998) points out, "Case study is a particularly suitable design if you are interested in process" (p.33).  Therefore, case study was chosen since it allows for detailed monitoring of the collaborative process (Merriam, 1998). 

Types of Case Studies

Stake (2000) delineates three types of case studies: intrinsic, instrumental, and collective.  Intrinsic case studies focus on a case that is unusual and is of particular interest to the researcher (Creswell, 1998; Stake, 2000).  The intent is not to build theory (Stake, 2000).  An instrumental case study is pursued in order to provide insight about a particular issue that may be generalizable (Creswell, 2002).  The primary purpose of an instrumental case study is to help advance understanding (Stake, 2000).  The collective case study encompasses more than one case "in order to investigate a phenomenon, population, or general condition" (Stake, 2000, p. 437).  Since the purpose is to help advance understanding, a collective case study is a grouping of instrumental case studies (Stake, 2000).  Using a collective case study approach can allow for the possibility of stronger interpretation and "perhaps better theorizing" (Stake, 2000, p. 437). 

Though Stake (2000) uses the terminology "collective case study," this approach is known by other names such as, multiple case studies, cross-case studies, comparative case studies, and contrasting cases (Merriam, 1998; Yin, 2003).  With multiple case studies, data are analyzed for insights both within each case and across cases (Merriam, 1998).  Yin (2003) points out that multiple cases may be chosen to try to replicate insights that you find within individuals cases or to represent contrasting situations.  Regardless of whether the purpose is replication or contrast, multiple case studies are "considered more compelling, and the overall study is therefore regarded as more robust" (Yin, 2003, p. 46). 

When this study was first proposed, the original intent was to pursue a single case study of my experience of collaboration in carrying out a community-based research project.  After completing my work with the Coalition for Schools, I felt dissatisfied with the experience in that I did not view it to be a success.  Instead of focusing on that one experience, I decided to pursue another research option in the small town in which I live in order to have a contrasting experience to write about.  It turned out that the project I completed in my small town was more successful, therefore allowing me to present contrasting cases.  Since this study seeks to add insight to the field of methodology in CBR, it is important to understand the factors that impact the process of collaboration and the factors that support successful collaborations (Strand et al., 2003a). 

Methodology of Community-Based Research

Since the purpose of this study is to explore the process of carrying out CBR, it is important to understand the methodology of community-based research.  As mentioned in chapter two, community-based research is not as concerned with methods as it is with methodology (Hills & Mullett, 2000; Strand et al., 2003a).  Either quantitative or qualitative methods may be used; the choice depends on what would obtain the most useful data for the community (Greenwood & Levin, 2000).  The methodology of CBR is guided by the three principles outlined by Strand et al. (2003a): 1) collaboration, 2) validation of the knowledge of community members and the multiple ways of collecting and distributing information, and 3) "social action and social change for the purpose of achieving social justice" (p. 8).  Though community-based research is not limited to specific methods, it does follow the typical stages of research that most traditional academic research would follow: defining the research question, developing a research design, collecting data, analyzing data, and writing up the results.  The difference is that the researcher collaborates closely with the community throughout the research process (Strand et al., 2003a).  The community is involved in determining the problem and research questions, creating the research design, collecting data, analyzing data, and creating a presentation of findings (Strand et al., 2003a).  The researcher also continues to play a role in the final stage by assisting with the enactment of solutions to create change (Greenwood & Levin, 1998). 

Regarding knowledge, community-based research seeks to redefine how we conceptualize knowledge in relation to academic research (Strand et al., 2003a).  Researchers who conduct CBR projects recognize the important knowledge that community members possess on the subject of their environment and the issues they are dealing with (Cordes, 1998a, No Concrete section, para. 2; Hills & Mullett, 2000, p. 1), what Strand (2000) calls "local knowledge" (p. 88).  This knowledge is key throughout the research process.  This acceptance of community knowledge does require the researcher to rethink his or her role.  As Stringer (1996) says, "The role of the researcher is not that of an expert who does research, but that of a resource person" (p. 22).  The expertise that the researcher brings to the equation is still valued; however, the local knowledge that the community brings is recognized as integral to the research process (Strand et al., 2003a). 

I have provided a brief overview of the methodology of CBR.  However, the purpose of this chapter is to describe the case study methods that I used to carry out this process study.  The descriptions of data collection and data analysis that are included in this chapter pertain to the data that were collected and analyzed for the contrasting case studies.  A description of the data collection and analysis that was conducted for the CBR projects in each case study will be included in the case descriptions in chapters four and five. 

Participants and Setting

Though I came into contact with a variety of people in each case study, my primary research collaborators are the main participants of my study.  In the first case study that I carried out, my collaboration with the Coalition for Schools, there were initially two primary collaborators, one of the co-chairs of the Coalition, Marge Bowline, and the director of the Coalition, Lisa Brown.  As my collaboration progressed, I worked primarily with Lisa Brown. 

The Coalition for Schools is an organization that has been created to support greater academic achievement in an urban school district in a western city.  The Coalition has focused its efforts toward a feeder pattern of schools in a quadrant of the city that has a high percentage of students who are eligible for free or reduced lunches, a high percentage of minority students, and a high percentage of English language learners.  This feeder pattern includes five elementary schools, two middle schools, and three small high schools that were originally part of one large high school and that are housed in one building.  The Coalition is an alliance of non-profit organizations, foundations, parent organizations, universities and colleges, and the school district working together to support achievement in these low performing schools.  The Business and Schools United (BSU) organization is the lead partner for the Coalition, and the Coalition is housed at BSU.  Marge Bowline is the director of BSU and one of the co-chairs of the Coalition for Schools.  She helped to create the Coalition and to procure funding for the organization.  The Coalition was a year old when I began my work with them.  Lisa Brown was hired to direct the Coalition and replaced the first director.  She had been in her position for about six months when I began my work with the Coalition. 

The two primary collaborators in my work in a small, western, mountain town are John Brewer and Maria Swenson.  The town is a small rural community that has a rapidly growing immigrant population from Mexico, about half of which are Indians from a remote area of the country.  Both John Brewer and Maria Swenson work in positions that have direct contact with this population.  John Brewer is the director of the literacy program which offers free English courses for English as a Second Language (ESL) students.  He is also a member of the city council.  Marge Swenson, who is herself a former immigrant from South America, is the coordinator of the diversity office which provides services to immigrants in town.  The case descriptions in chapters four and five provide greater detail of the participants and setting. 

Data Collection

As I progressed through each case study, I pursued two streams of data collection; the data collected to pursue the CBR projects and data that were collected as part of this case study to study CBR.  This section describes only the data that were collected for the case studies.  A description of the CBR data that were collected for each collaboration is included in the case descriptions in chapters four and five. 

Since the purpose of case study research is to provide an in-depth exploration of the person, program, or process under study, it requires intensive data collection (Merriam, 1998; Yin, 2003) using "multiple forms of data" (Creswell, 2002, p. 486).  Data collection for case studies usually focuses on three sources of data: observations, interviews, and documents (Merriam, 1998).  Though all qualitative research is to some extent based on the idea of emergent design, this study was truly emergent.  Though the research questions that this study proposed to address did not shift throughout the study, the methods of data collection changed to accommodate emerging issues or ideas.  According to Patton (1990),

What is certain is that different methods produce quite different information.  The challenge is to find out which information is most needed and most useful in a given situation, and then employ those methods best suited to producing the needed information (p. 196).

Though I collected all three forms of data (observations, interviews, and documents) for each study, there are some variations that are detailed in the following sections.  Appendix A provides a list showing the dates of meetings and interviews for each case study. 

Observations

My primary source of data collection for both case studies was observation.  Since I was essentially observing myself as I collaborated with my community partner, all of the observations that I completed for my case study data collection were participant observations.  Creswell (2002) defines participant observation as "an observational role adopted by researchers when they take part in activities in the setting they observe" (p. 200).  In this role, the researcher "actually engages in activities at the site begin studied" (p. 200).  Glesne (1999) describes a continuum of participation that "ranges from mostly observation to mostly participation" (p. 44).  Based on this continuum, I was what Glesne (1999) describes as a "full participant" in every interaction relating to my collaborative work with my community partners since I was concurrently a member of the collaborative partnership as well as the researcher investigating the process.  

In all of the meetings that I conducted with my community partners in relation to our CBR work, I collected data around those interactions.  I utilized Merriam's (1998) checklist of elements to structure my observations: physical setting, participants, activities and interactions, conversation, subtle factors, and my own behavior (pp. 97-98).  When working on my first CBR project with the Coalition, I initially only maintained field notes.  I was concerned that if I taped our meetings that it would be intrusive and would impact the openness of our conversations (Merriam, 1998).  However, as my study progressed I realized that it was difficult to take effective notes while participating in the conversation.  I then asked my community partners if I could tape subsequent meetings.  After that, most of the meetings I had with Lisa Brown or Marge Bowline were taped and then transcribed.  As part of the transcription process, I added notes that clarified or contextualized the dialogue.  When I began my work with my community partners in my small town, I asked during the first meeting if I could tape all of our meetings; both John Brewer and Maria Swenson readily agreed.  I found that after the use of the tape recorder became routine, they did not seem to be inhibited by being recorded.  Using the tape recorder allowed me to collect much more extensive data from my observations of our meetings. 

            Interviews

As part of the data collection for both case studies, I collected both formal and informal interview data (Patton, 1990).  Informal conversational interview questions were interwoven into meetings that we had in relation to ongoing research (Merriam, 1998) and were recorded as part of observation transcriptions.  These informal questions typically addressed how the community partner felt the research process was progressing, whether the research was meeting their needs, or addressed immediate questions that arose through the process of continued interaction. 

I also collected formal interview data for both case studies; however, I conducted fewer formal interviews with my community partners from the Coalition for Schools.  As my work with the Coalition progressed, I sought to determine particular data collection procedures that would address my research questions.  Since I was working within a collaborative relationship, part of the consideration when choosing methods was the impact that various methods would have on the relationship with my community partner.  In this first case study, as I show in more detail in chapter four, it was challenging to develop a collaborative relationship with my community partners.  The lack of trust and communication within this relationship made it difficult to carry out formal interviews discussing our collaboration.  I felt that these kinds of interviews would create greater distance between us.  Instead I relied primarily on other forms of data collection, observations and documents.  However, I did interview both Lisa Brown and Marge Bowline once formally toward the end of our partnership.  This interview included questions about the work of the Coalition as well as questions relating to community-based research (Appendix B).  I also conducted a follow-up email interview with Lisa Brown after beginning the process of data analysis (Appendix B).   

In my collaboration with John Brewer and Maria Swenson in my small town, I was able to develop a much more honest and open relationship from the beginning and felt very comfortable conducting formal interviews about the process.  I interviewed John and Maria individually three times throughout our collaboration (Appendix B).  I used a semi-structured approach (Rubin & Rubin, 1995) when designing the interview protocols.  I prepared questions as a starting point, but allowed the conversation to flow in whatever direction was helpful to providing insight.  The first interview focused on getting a sense of their background and experiences with research, their expectations for our research, and strategies for effective communication.  The second interview focused on their satisfaction with how things were proceeding, whether they felt we were communicating effectively, and whether they were having the input they wanted to have in the process.  The final interview focused primarily on the research questions of the case study: what were the issues that arose, what helped or hindered our collaboration, and what benefits did they receive from the research.  I transcribed each interview and added additional notes for interpretation. 

As part of the data collection process, I also collected or created a variety of documents including: email communications, a reflective journal, a phone call log, and other items that were provided by my community partners such as newsletters and meeting minutes.  As part of my collaboration with the Coalition for Schools, we relied extensively on email for communication since I found it difficult to schedule face-to-face meetings with Marge Bowline and Lisa Brown.  These email conversations are an important source of data in compiling a picture of our collaborative experience.  I also collected email data during my second case study.  However, these email communications focused primarily on setting up logistics.  Most important conversations were conducted face-to-face. 

Throughout both case studies, I sought to engage in a reflective stance toward my role in the research process.  In order to aid my reflection, I maintained a journal in which I transcribed my thinking in relation to my experiences and the perceived experiences of my community partners.  Merriam (1998) expresses some concern about using personal documents such as journals as data.  Merriam (1998) says,

Personal documents are a reliable source of data concerning a person's attitudes, beliefs, and view of the world.  But because they are personal documents, the material is highly subjective in that the writer is the only  one to select what he or she considers important to record.  Obviously these documents are not representative or necessarily reliable accounts of what actually may have occurred (p. 116).

However, Merriam (1998) does point out that one of the goals of qualitative research is to "reflect the participant's perspective" (p. 116).  Since this is a process study, the perceptions of all participants are a key consideration (Patton, 1990).  As I am a participant in this study, my perceptions of my experience of the process are important. 

The other documents I collected consisted of a phone call log and documents obtained when meeting with my community partners.  The phone call log consisted of a brief description of phone calls that were made during the research process.  If the conversation was extensive, I tried to recreate the conversation as closely as possible.  The phone call log was used primarily during my collaboration with John Brewer and Maria Swenson.  I also obtained various documents from my community partners.  These mostly included newsletters, meeting minutes, and data collected from previous research.  Most of the documents related to the CBR work we were conducting; yet some of the documents also provided information for my case study research. 

Data Analysis

After completing both case studies, I had accumulated large volumes of data (more than 500 pages of data for each case study).  I organized the data from both cases into what Yin (2003) calls a case study data base .   I organized my case study data base in a chronological order so that I could move through the data from the beginning to the end of the process.  This allowed me to perceive the progression of the process and my changing views throughout.  However, I felt that I needed an additional frame from which to organize the data. 

Data analysis was an ongoing process throughout the implementation of each case study.  Periodically I composed analytic memos to begin to formulate ideas around particular findings.  As each study progressed, I looked for events with common elements within the data that had "issue-relevant meaning" (Creswell, 1998, p. 154) or significance for the study.  As I recognized these common elements, I focused on determining whether they continued to be supported throughout the data collection process.  Creswell (1998) calls this process categorical aggregation.  As categories within the data began to emerge, I began to look for patterns or themes that connected these categories.  Based on the literature and the categories and themes that emerged while conducting the cases, I created an analytic framework from which to organize and think about the data. 

Analytic Framework      

The analytic framework is composed of four categories: community, collaboration, knowledge creation, and change.  In creating this framework, I was influenced by Stoecker's (2003) delineation of radical and mainstream CBR.  I view each of the four constructs of my framework as existing on a continuum.  At one end, there is radical CBR, in the middle, mainstream CBR, and at the other end the professional expert model or consulting (see Figure 1).  Based on how I conceptualize this framework, the closer on the continuum the researcher moves toward radical CBR, the greater the potential for change that will benefit the community with which the researcher is collaborating. 

When considering the category of community, the goal is to work as closely as possible with the community.  Since the ultimate goal of CBR is "social change for social justice" (Stoecker, 2002a, p. 9), the closer the researcher is to the members of the community who are dealing with the problem (Stoecker, 2003), the greater the potential to empower.  The community continuum includes grassroots organizations on one end and organizations which do not represent the community or use practices that "disempower the community" (Strand et al., 2003a. p. 73) on the other (see Figure 1).  In between are organizations that are a level removed from grassroots organizations but still seek to represent the community democratically, what Strand et al. (2003a) call "midlevel organizations" (p. 74).  Conducting CBR projects with midlevel organizations is what Strand et al. (2003a) label " doing CBR in the middle " (p. 73). 

Within this analytic framework, I conceptualize collaboration as shared decision making.  The goal is that the community should have equal power with the researcher and that decision making should be a shared process throughout (Strand et al., 2003a).  When considering this concept within the continuum, shared decision making is at one end of the continuum and at the other end the decisions are made primarily by the researcher (see Figure 1).  A companion to collaboration is the concept of participation in knowledge creation.  The primary goal in relation to this aspect of the framework is that the community assists in the creation of all knowledge that is generated during the CBR process, thus leading to community empowerment.  This point of the framework is based on the principle that the knowledge of community members is valid (Strand et al., 2003a) and integral to creating strong results.  At one end of the continuum, the community is involved in all aspects of knowledge creation, at the other end, the researcher controls the creation of knowledge (see Figure 1). 

The final point of the analytic framework is change (see Figure 1).  If you consider CBR within the radical framework described by Stoecker (2003), the goal for change is "massive structural changes in the distribution of power and resources through far-reaching changes in governmental policy, economic practices, or cultural norms" (p. 36).  This goal can be difficult to achieve.  More often, CBR work leads to programmatic changes within an organization or other more limited changes (Strand et al., 2003a).  However, each change within a community can have a cumulative effect that can lead to broader change.  Community-based research that does not involve the community in close collaboration and knowledge creation is less likely to create change that benefits the community.

Analysis of Contrasting Cases

Since this study utilizes contrasting cases, data analysis occurs at two levels: within-case and across cases (Merriam, 1998).  Merriam (1998) describes this process:            

For the within-case analysis , each case is first treated as a comprehensive case in and of itself.  Data are gathered so the researcher can learn as much about the contextual variables as possible that might have a bearing on the case...Once the analysis of each case is completed, cross-case analysis begins.  A qualitative, inductive, multicase study seeks to build abstractions across cases (pp. 194-195).

For each case, I analyzed observations, interviews, and documents to develop a description of the case. This description depicts the setting and participants as well as a general chronology of events and provides the reader with an understanding of the particulars of the case (Creswell, 1998).  This allows the reader to develop an understanding of the case within the larger context (Creswell, 2002).  Then using the analytic framework I developed, I did some within-case analysis and organized the categories that emerged during each study around the four constructs of my analytic framework.  This within-case analysis focused on answering the primary research question: What is the process of collaborating with a community partner on a community-based research project?  Thus each case analysis consists of  "both description and thematic development" (Creswell, 2002, p. 486).           

After completing the within-case analysis, I focused on the cross-case analysis to address three of the sub-questions of the study: What kinds of issues arise when collaborating on a community-based research project? What facilitates or hinders the process of collaboration? and, What does the researcher gain through this collaborative process, and what are the benefits for the community?  In the cross-case analysis, I used data from both case studies to address these questions.  I explored the categories that had emerged throughout each case study and then compared to see if these categories were supported in both cases.  I used the categories and themes that emerged during the within-case analysis and the cross-case analysis to determine "naturalistic generalizations" (Creswell, 1998, p. 154) concerning the field of community-based research.  Creswell (1998) defines naturalistic generalizations as "generalizations that people can learn from the case either for themselves or for applying it to a population of cases" (p. 154).  These naturalistic generalizations address the final question of the study: What can we learn from these experiences to inform the field of CBR?

In order to lend credibility to the findings of my study, I incorporated a variety of validity procedures.  The first validity procedure I employed was prolonged engagement in the field (Creswell & Miller, 2000) or what Merriam (1998) calls "long-term observation" (p. 204).  I worked on my case study with the Coalition for a period of nine months, and I worked with John and Maria for a period of eight months.  During each of these case studies, I had consistent contact with my community partners.  Collaborating with my community partners for this length of time allowed me to develop tentative categories in my findings and then follow up on these preliminary findings through observations or interviews (Creswell & Miller, 2000).  Therefore, the length of each case study and the consistent contact I had with my community partners lends credibility to my perceptions of this experience.

In addition to prolonged engagement in the field, another important validity procedure I employed, which is integral to case study design, was triangulation (Creswell, 1998).  Merriam (1998) defines triangulation as "using multiple investigators, multiple sources of data, or multiple methods to confirm the emerging findings" (p. 204).  I employed methodological triangulation (Creswell & Miller, 2000) since I collected three forms of data: observations, interviews, and documents.  I also employed multiple sources of data since interviews were conducted with several participants (Creswell & Miller, 2000).  I used the process of triangulation to seek convergence in the data and to confirm or disconfirm emerging categories and themes (Creswell & Miller, 2000).  As part of this process, I employed another validity strategy, disconfirming evidence (Creswell &  Miller, 2000).  Categories or themes that emerged in the within-case analysis were compared across cases.  If a category did not hold true across cases, it was generally deemed to be unreliable.  However, I did utilize what Creswell (1998) calls direct interpretation.  In direct interpretation, "the case study researcher looks at a single instance and draws meaning from it without looking for multiple instances" (p. 154).  I did recognize that there were single incidents specific to only one case that were significant to the study as well. 

Since this case study focused on the study of process, my perceptions were an integral component of the research.  However, since I did write interpretations of what I considered to be the perceptions of others, I used member checking to ensure accurate portrayal (Creswell & Miller, 2000).  I conducted member checking toward the end of the study so that it would not potentially disrupt the collaborative process.  I shared an outline of findings with Lisa Brown with the Coalition and also John Brewer and Maria Swenson in my small town and allowed them the opportunity to provide feedback.  Lisa Brown responded to the findings through email and said, "Thanks for sharing [these findings].  I feel it is accurate, and that it was a learning experience for all of us."  Maria Swenson also responded to the findings that I shared with she and John.  She said, "I looked at [the findings] and it sounds good.  I agree with all said."  John also said that he thought that the findings looked good. 

Finally, I used the validity procedure of thick description when writing about the study in order to give the reader a sense of being there and to capture the essence of the experience (Creswell & Miller, 2000).  This is an important feature in case study design that is presented to the reader through the case description.  The case description for each contrasting case is included in chapters four and five.  

            Subjectivity

Another method of creditability I used continuously throughout the research process was researcher reflexivity (Creswell & Miller, 2000).  I incorporated researcher reflexivity by constantly questioning my assumptions about what I thought was happening.  I sought to maintain a heightened sense of awareness of the biases that I brought to the study and maintained this awareness when adding contextual data to field notes, observations transcriptions, and interview transcriptions, and also when writing journal entries. 

Since my perceptions of the research process played a major part in the findings of the study, it was important that I attend to the idea of subjectivity.  Peshkin (1988), defines subjectivity as "the quality of the investigator that affects the results of observational investigation" (p. 17).  Peshkin (1988) points out that an individual's subjectivity is not something that can be removed, and it is therefore something researchers need to be aware of throughout the research process.  Peshkin (1988) identified the various facets of his subjectivities through a series of I's, for example, the "justice-seeking I" (p. 18) and "the community-maintenance I" (p. 18).  Though Peshkin does not view subjectivity as necessarily negative, he does feel it is something that researchers need to realize and acknowledge.  It was important to examine my own subjectivities throughout the research process so that I was aware of how these subjectivities could influence my interpretations and portrayal of events.  As Strand (2000) points out, "the researcher's values, experiences, and personal points of view are as much a part of the research process as those of the people studied, and they should be discussed and acknowledged" (p. 91). 

Since the two CBR projects I worked on were in different settings and related to different types of work, I dealt with different subjectivities within each case study.  In my work with the Coalition for Schools many of the subjectivities that I brought to that collaboration arose from my past experience as a classroom teacher.  I hold the perception that people who do not have experience in a K-12 classroom do not generally understand the issues that classroom teachers have to address.  I can be defensive and overly sensitive to criticism that I feel puts the blame on teachers.  There were many times during my partnership with the Coalition that I realized this subjectivity was influencing my reactions to statements made by Lisa Brown or Marge Bowline.  I also think that this perception at times clouded my view of the knowledge that Lisa brought to the equation.  Though I felt that she was very knowledgeable in certain areas, I questioned her understanding of what was actually happening in the schools that are part of the Coalition.  I tried to be aware of my bias in this area, though I do not believe I was always successful in controlling how this bias influenced my work with Lisa. 

Another bias that I brought to my work with the Coalition was the idea that a successful partnership should not have conflict.  I tend to avoid conflict in my personal life.  I have difficulty at times recognizing the benefits that conflict can bring.  Because of this, I did not communicate as effectively with Lisa as I could have.  If had been more willing to risk conflict, we may have been able to develop a more productive working relationship.  When I began my work with John Brewer and Maria Swenson, I determined that I would not avoid conflict in this collaboration.  When a situation did arise where John and I disagreed, I engaged him, and we talked through the matter.  The outcome was that we both were able to see the value of the other's viewpoint. 

Though I was able to address the issue of conflict avoidance in my work in John Brewer and Maria Swenson, there were other subjectivities and biases of which I had to be aware.  I am liable to have the perception that small towns tend to discriminate against minorities.  Since all of the projects that I completed with John and Maria involved the immigrant population in town, I felt at times that I was waiting for someone to say something that would demonstrate their prejudice.  At times, I would jump to the conclusion that a particular statement was pejorative.  When looking back again at the statement in the context of the full conversation, I realized at times that I may have misinterpreted particular statements.  I had to make a concerted effort not to single out statements just because they supported my bias.  Nevertheless, this subjectivity did influence whom I chose to partner with during this case study.  I had originally planned to include Maria's supervisor, Jennifer Payton, in our collaboration.  However, after meeting with Jennifer in October 2003, I decided not to collaborate with her since she made several comments during the meeting that I perceived to be pejorative.  If I had decided to work with Jennifer, I may have found that these comments did not represent discrimination but rather a lack of understanding of the impact of language choices. 

Two other subjectivities that I brought into my work on both projects related to my experience with previous CBR projects.  As I was involved in another community-based research project before working on my dissertation, I already had an initial perception of how the process works.  One concern that arose during my previous experience was the issue of communicating with my community partner.  I had difficulty developing a research question because the conversations that I shared with my community partner seemed circuitous.  We talked around questions during several meetings before I was finally able to gain a sense of what she was hoping to achieve from the research.  Though these past experiences with community-based research helped me to anticipate some of the issues that arose, I tried to make sure that the anticipation of issues did not create issues. 

When entering into CBR projects, it is important to me that I am doing work that I view as meaningful.  Work that is meaningful to me would be research that allows me to consistently interact with members of the community on a personal level.  However, I tried to maintain the awareness that the research that I wished to pursue was not necessarily the research that the people I was collaborating with wished to pursue.  I continued to remind myself that these discrepancies should not interfere with the development of a research design that was beneficial to my community partner and had the potential to bring about effective change.  Since change is the goal of community-based research, I needed to be sure that the change I was assisting to create was the change that the community partner was seeking to make rather than the change that I would have liked to pursue. 

Finally, when a researcher carries out a qualitative study, it is also important to attend to the subjectivities that the researcher brings based on gender, age, ethnicity, and socioeconomic status.  I feel at times that I lack self-awareness of how these orientations impact the way that I view the world.  Though I tried to be conscious of these factors while doing my research, I am not sure that I was successful in completely exploring how these subjectivities may have influenced my research.  I do feel, however, that my status was an issue in the work that I conducted with the Coalition for Schools.  My status in relation to my age (under 40) and my position as a graduate student influenced how my community partners at the Coalition viewed my role, and my socioeconomic background impacted the level of confidence that I felt when working with members of the Coalition.  I come from a working class background while my community partners at the Coalition come from backgrounds of higher status both in relation to levels of education and socioeconomic status.  At times, I did feel out of place moving through the world of the Coalition in that I often felt that I was from a lower class than many of the people with which I came into contact.  I felt most comfortable when interacting with teachers or parents. 

In order to minimize the impact of my subjectivities, I closely monitored my feelings as I carried out my research.  I looked for situations where I felt uncomfortable or that I wanted to avoid as well as situations where I felt comfortable and that I wanted to continue.  When these feelings arose, I realized that I was usually being influenced by subjectivity (Glesne, 1999; Peshkin, 1988).  I analyzed my feelings and considered how they related to my subjectivities, then took note of these occurrences in my journal (Peshkin, 1988).  Throughout the research process, I was mindful of previously identified subjectivities.  I also tried to be aware of newly emerging subjectivities that I may not have considered (Peshkin, 1988) that would potentially influence my research. 

Limitations of This Study

This study seeks to compare two cases of conducting community-based research.  However, there are differences between the two experiences that may have impacted the findings of the study.  In my work with the Coalition, I was a paid employee.  Though I was hired with the understanding that I would be a collaborative researcher, I believe my position as an employee impacted how Marge Bowline and Lisa Brown viewed my role, and it also impacted my reactions to various situations.  The fact that I was an employee in the first case study when collaborating with the Coalition but in the second case study I was independent, may have created some of the differences that were apparent in the two cases. 

Another limitation of this study is that it primarily focuses on the researcher's experience of this process.  Though I did interview my community partners, the number of interviews in the first case study was more limited.  If I had conducted additional interviews throughout the first case study, I might have additional information to support or contradict some of my observations.  However, the purpose of this study is to provide insight into this process for practitioners in the field of community-based research, thus it is beneficial to explore the researcher's perspective of these two experiences. 

The final limitation of this study relates to the timeline of the completion of the study.  Since I only recently finalized data collection in relation to my work with John Brewer and Maria Swenson, I am not really able to make an assessment at this point as to whether any of the work we completed will affect change.  My work with the Coalition was completed almost a year ago so it easier to assess the impact of that work.  However, even with the first case study, there is a possibility that some of the work that I completed could eventually lead to change.  If I were to conduct a long-term case study in relation to either of these collaborations, it would be more feasible to assess the impact of our work. 

This chapter provided an overview to the case study methods that were used to conduct this study.  I detailed a rationale for choosing this method, then described data collection, analysis, and procedures in relation to validity.  Since this is a process study of the methodology of CBR, I also described the foundations of this methodology.  The next three chapters will present the findings of this study.  Chapters four and five provide a synopsis of the within-case analysis of each of the contrasting cases.  I begin each chapter with a chronological overview of the major events of the case and then present within-case analysis organized around the four concepts of my analytic framework.  In chapter six, I present the findings from the cross-case analysis that address the sub-questions of the study and identify the "naturalistic generalizations" (Creswell, 1998, p. 154) that emerged from the study with recommendations for further research. 

Types of Case Studies

There are several different types of case studies, as well as several types of subjects of case studies. We will investigate each type in this article.

Different Types of Case Studies

There are several types of case studies, each differing from each other based on the hypothesis and/or thesis to be proved. It is also possible for types of case studies to overlap each other.

Each of the following types of cases can be used in any field or discipline. Whether it is psychology, business or the arts, the type of case study can apply to any field.

Explanatory

The explanatory case study focuses on an explanation for a question or a phenomenon. Basically put, an explanatory case study is 1 + 1 = 2. The results are not up for interpretation.

A case study with a person or group would not be explanatory, as with humans, there will always be variables. There are always small variances that cannot be explained.

However, event case studies can be explanatory. For example, let's say a certain automobile has a series of crashes that are caused by faulty brakes. All of the crashes are a result of brakes not being effective on icy roads.

What kind of case study is explanatory? Think of an example of an explanatory case study that could be done today

When developing the case study, the researcher will explain the crash, and the detailed causes of the brake failure. They will investigate what actions caused the brakes to fail, and what actions could have been taken to prevent the failure.

Other car companies could then use this case study to better understand what makes brakes fail. When designing safer products, looking to past failures is an excellent way to ensure similar mistakes are not made.

The same can be said for other safety issues in cars. There was a time when cars did not have seatbelts. The process to get seatbelts required in all cars started with a case study! The same can be said about airbags and collapsible steering columns. They all began with a case study that lead to larger research, and eventual change.

Exploratory

An exploratory case study is usually the precursor to a formal, large-scale research project. The case study's goal is to prove that further investigation is necessary.

For example, an exploratory case study could be done on veterans coming home from active combat. Researchers are aware that these vets have PTSD, and are aware that the actions of war are what cause PTSD. Beyond that, they do not know if certain wartime activities are more likely to contribute to PTSD than others.

For an exploratory case study, the researcher could develop a study that certain war events are more likely to cause PTSD. Once that is demonstrated, a large-scale research project could be done to determine which events are most likely to cause PTSD.

Exploratory case studies are very popular in psychology and the social sciences. Psychologists are always looking for better ways to treat their patients, and exploratory studies allow them to research new ideas or theories.

Multiple-Case Studies or Collective Studies

Multiple case or collective studies use information from different studies to formulate the case for a new study. The use of past studies allows additional information without needing to spend more time and money on additional studies.

Using the PTSD issue again is an excellent example of a collective study. When studying what contributes most to wartime PTSD, a researcher could use case studies from different war. For instance, studies about PTSD in WW2 vets, Persian Gulf War vets, and Vietnam vets could provide an excellent sampling of which wartime activities are most likely to cause PTSD.

If a multiple case study on vets was done with vets from the Vietnam War, the Persian Gulf War, and the Iraq War, and it was determined the vets from Vietnam had much less PTSD, what could be inferred?

Furthermore, this type of study could uncover differences as well. For example, a researcher might find that veterans who serve in the Middle East are more likely to suffer a certain type of ailment. Or perhaps, that veterans who served with large platoons were more likely to suffer from PTSD than veterans who served in smaller platoons.

An intrinsic case study is the study of a case wherein the subject itself is the primary interest. The "Genie" case is an example of this. The study wasn't so much about psychology, but about Genie herself, and how her experiences shaped who she was.

Genie is the topic. Genie is what the researchers are interested in, and what their readers will be most interested in. When the researchers started the study, they didn't know what they would find.

They asked the question…"If a child is never introduced to language during the crucial first years of life, can they acquire language skills when they are older?" When they met Genie, they didn't know the answer to that question.

Instrumental

An instrumental case study uses a case to gain insights into a phenomenon. For example, a researcher interested in child obesity rates might set up a study with middle school students and an exercise program. In this case, the children and the exercise program are not the focus. The focus is learning the relationship between children and exercise, and why certain children become obese.

What is an example of an instrumental case study?

Focus on the results, not the topic!

Types of Subjects of Case Studies

There are generally five different types of case studies, and the subjects that they address. Every case study, whether explanatory or exploratory, or intrinsic or instrumental, fits into one of these five groups. These are:

Person – This type of study focuses on one particular individual. This case study would use several types of research to determine an outcome.

The best example of a person case is the "Genie" case study. Again, "Genie" was a 13-year-old girl who was discovered by social services in Los Angeles in 1970. Her father believed her to be mentally retarded, and therefore locked her in a room without any kind of stimulation. She was never nourished or cared for in any way. If she made a noise, she was beaten.

When "Genie" was discovered, child development specialists wanted to learn as much as possible about how her experiences contributed to her physical, emotional and mental health. They also wanted to learn about her language skills. She had no form of language when she was found, she only grunted. The study would determine whether or not she could learn language skills at the age of 13.

Since Genie was placed in a children's hospital, many different clinicians could observe her. In addition, researchers were able to interview the few people who did have contact with Genie and would be able to gather whatever background information was available.

This case study is still one of the most valuable in all of child development. Since it would be impossible to conduct this type of research with a healthy child, the information garnered from Genie's case is invaluable.

Group – This type of study focuses on a group of people. This could be a family, a group or friends, or even coworkers.

An example of this type of case study would be the uncontacted tribes of Indians in the Peruvian and Brazilian rainforest. These tribes have never had any modern contact. Therefore, there is a great interest to study them.

Scientists would be interested in just about every facet of their lives. How do they cook, how do they make clothing, how do they make tools and weapons. Also, doing psychological and emotional research would be interesting. However, because so few of these tribes exist, no one is contacting them for research. For now, all research is done observationally.

If a researcher wanted to study uncontacted Indian tribes, and could only observe the subjects, what type of observations should be made?

Location – This type of study focuses on a place, and how and why people use the place.

For example, many case studies have been done about Siberia, and the people who live there. Siberia is a cold and barren place in northern Russia, and it is considered the most difficult place to live in the world. Studying the location, and it's weather and people can help other people learn how to live with extreme weather and isolation.

Location studies can also be done on locations that are facing some kind of change. For example, a case study could be done on Alaska, and whether the state is seeing the effects of climate change.

Another type of study that could be done in Alaska is how the environment changes as population increases. Geographers and those interested in population growth often do these case studies.

Organization/Company – This type of study focuses on a business or an organization. This could include the people who work for the company, or an event that occurred at the organization.

An excellent example of this type of case study is Enron. Enron was one of the largest energy company's in the United States, when it was discovered that executives at the company were fraudulently reporting the company's accounting numbers.

Once the fraud was uncovered, investigators discovered willful and systematic corruption that caused the collapse of Enron, as well as their financial auditors, Arthur Andersen. The fraud was so severe that the top executives of the company were sentenced to prison.

This type of case study is used by accountants, auditors, financiers, as well as business students, in order to learn how such a large company could get away with committing such a serious case of corporate fraud for as long as they did. It can also be looked at from a psychological standpoint, as it is interesting to learn why the executives took the large risks that they took.

Most company or organization case studies are done for business purposes. In fact, in many business schools, such as Harvard Business School, students learn by the case method, which is the study of case studies. They learn how to solve business problems by studying the cases of businesses that either survived the same problem, or one that didn't survive the problem.

Event – This type of study focuses on an event, whether cultural or societal, and how it affects those that are affected by it. An example would be the Tylenol cyanide scandal. This event affected Johnson & Johnson, the parent company, as well as the public at large.

The case study would detail the events of the scandal, and more specifically, what management at Johnson & Johnson did to correct the problem. To this day, when a company experiences a large public relations scandal, they look to the Tylenol case study to learn how they managed to survive the scandal.

A very popular topic for case studies was the events of September 11 th . There were studies in almost all of the different types of research studies.

Obviously the event itself was a very popular topic. It was important to learn what lead up to the event, and how best to proven it from happening in the future. These studies are not only important to the U.S. government, but to other governments hoping to prevent terrorism in their countries.

Planning A Case Study

You have decided that you want to research and write a case study. Now what? In this section you will learn how to plan and organize a research case study.

Selecting a Case

The first step is to choose the subject, topic or case. You will want to choose a topic that is interesting to you, and a topic that would be of interest to your potential audience. Ideally you have a passion for the topic, as then you will better understand the issues surrounding the topic, and which resources would be most successful in the study.

You also must choose a topic that would be of interest to a large number of people. You want your case study to reach as large an audience as possible, and a topic that is of interest to just a few people will not have a very large reach. One of the goals of a case study is to reach as many people as possible.

Who is your audience?

Are you trying to reach the layperson? Or are you trying to reach other professionals in your field? Your audience will help determine the topic you choose.

If you are writing a case study that is looking for ways to lower rates of child obesity, who is your audience?

If you are writing a psychology case study, you must consider whether your audience will have the intellectual skills to understand the information in the case. Does your audience know the vocabulary of psychology? Do they understand the processes and structure of the field?

You want your audience to have as much general knowledge as possible. When it comes time to write the case study, you may have to spend some time defining and explaining terms that might be unfamiliar to the audience.

Lastly, when selecting a topic you do not want to choose a topic that is very old. Current topics are always the most interesting, so if your topic is more than 5-10 years old, you might want to consider a newer topic. If you choose an older topic, you must ask yourself what new and valuable information do you bring to the older topic, and is it relevant and necessary.

Determine Research Goals

What type of case study do you plan to do?

An illustrative case study will examine an unfamiliar case in order to help others understand it. For example, a case study of a veteran with PTSD can be used to help new therapists better understand what veterans experience.

An exploratory case study is a preliminary project that will be the precursor to a larger study in the future. For example, a case study could be done challenging the efficacy of different therapy methods for vets with PTSD. Once the study is complete, a larger study could be done on whichever method was most effective.

A critical instance case focuses on a unique case that doesn't have a predetermined purpose. For example, a vet with an incredibly severe case of PTSD could be studied to find ways to treat his condition.

Ethics are a large part of the case study process, and most case studies require ethical approval. This approval usually comes from the institution or department the researcher works for. Many universities and research institutions have ethics oversight departments. They will require you to prove that you will not harm your study subjects or participants.

This should be done even if the case study is on an older subject. Sometimes publishing new studies can cause harm to the original participants. Regardless of your personal feelings, it is essential the project is brought to the ethics department to ensure your project can proceed safely.

Developing the Case Study

Once you have your topic, it is time to start planning and developing the study. This process will be different depending on what type of case study you are planning to do. For thissection, we will assume a psychological case study, as most case studies are based on the psychological model.

Once you have the topic, it is time to ask yourself some questions. What question do you want to answer with the study?

For example, a researcher is considering a case study about PTSD in veterans. The topic is PTSD in veterans. What questions could be asked?

Do veterans from Middle Eastern wars suffer greater instances of PTSD?

Do younger soldiers have higher instances of PTSD?

Does the length of the tour effect the severity of PTSD?

Each of these questions is a viable question, and finding the answers, or the possible answers, would be helpful for both psychologists and veterans who suffer from PTSD.

Research Notebook

1. What is the background of the case study? Who requested the study to be done and why? What industry is the study in, and where will the study take place?

2. What is the problem that needs a solution? What is the situation, and what are the risks?

3. What questions are required to analyze the problem? What questions might the reader of the study have? What questions might colleagues have?

4. What tools are required to analyze the problem? Is data analysis necessary?

5. What is your current knowledge about the problem or situation? How much background information do you need to procure? How will you obtain this background info?

6. What other information do you need to know to successfully complete the study?

7. How do you plan to present the report? Will it be a simple written report, or will you add PowerPoint presentations or images or videos? When is the report due? Are you giving yourself enough time to complete the project?

The research notebook is the heart of the study. Other organizational methods can be utilized, such as Microsoft Excel, but a physical notebook should always be kept as well.

Planning the Research

The most important parts of the case study are:

1. The case study's questions

2. The study's propositions

3. How information and data will be analyzed

4. The logic behind the propositions

5. How the findings will be interpreted

The study's questions should be either a "how" or "why" question, and their definition is the researchers first job. These questions will help determine the study's goals.

Not every case study has a proposition. If you are doing an exploratory study, you will not have propositions. Instead, you will have a stated purpose, which will determine whether your study is successful, or not.

How the information will be analyzed will depend on what the topic is. This would vary depending on whether it was a person, group, or organization.

When setting up your research, you will want to follow case study protocol. The protocol should have the following sections:

1. An overview of the case study, including the objectives, topic and issues.

2. Procedures for gathering information and conducting interviews.

3. Questions that will be asked during interviews and data collection.

4. A guide for the final case study report.

When deciding upon which research methods to use, these are the most important:

1. Documents and archival records

2. Interviews

3. Direct observations

4. Indirect observations, or observations of subjects

5. Physical artifacts and tools

Documents could include almost anything, including letters, memos, newspaper articles, Internet articles, other case studies, or any other document germane to the study.

Archival records can include military and service records, company or business records, survey data or census information.

Research Strategy

Before beginning the study you want a clear research strategy. Your best chance at success will be if you use an outline that describes how you will gather your data and how you will answer your research questions.

The researcher should create a list with four or five bullet points that need answers. Consider the approaches for these questions, and the different perspectives you could take.

The researcher should then choose at least two data sources (ideally more). These sources could include interviews, Internet research, and fieldwork or report collection. The more data sources used, the better the quality of the final data.

The researcher then must formulate interview questions that will result in detailed and in-depth answers that will help meet the research goals. A list of 15-20 questions is a good start, but these can and will change as the process flows.

Planning Interviews

The interview process is one of the most important parts of the case study process. But before this can begin, it is imperative the researcher gets informed consent from the subjects.

The process of informed consent means the subject understands their role in the study, and that their story will be used in the case study. You will want to have each subject complete a consent form.

The researcher must explain what the study is trying to achieve, and how their contribution will help the study. If necessary, assure the subject that their information will remain private if requested, and they do not need to use their real name if they are not comfortable with that. Pseudonyms are commonly used in case studies.

Informed Consent

The process by which permission is granted before beginning medical or psychological research

A fictitious name used to hide ones identity

It is important the researcher is clear regarding the expectations of the study participation. For example, are they comfortable on camera? Do they mind if their photo is used in the final written study.

Interviews are one of the most important sources of information for case studies. There are several types of interviews. They are:

Open-ended – This type of interview has the interviewer and subject talking to each other about the subject. The interviewer asks questions, and the subject answers them. But the subject can elaborate and add information whenever they see fit.

A researcher might meet with a subject multiple times, and use the open-ended method. This can be a great way to gain insight into events. However, the researcher mustn't rely solely on the information from the one subject, and be sure to have multiple sources.

Focused – This type of interview is used when the subject is interviewed for a short period of time, and answers a set of questions. This type of interview could be used to verify information learned in an open-ended interview with another subject. Focused interviews are normally done to confirm information, not to gain new information.

Structured – Structured interviews are similar to surveys. These are usually used when collecting data for large groups, like neighborhoods. The questions are decided before hand, and the expected answers are usually simple.

When conducting interviews, the answers are obviously important. But just as important are the observations that can be made. This is one of the reasons in-person interviews are preferable over phone interviews, or Internet or mail surveys.

Ideally, when conducing in-person interviews, more than one researcher should be present. This allows one researcher to focus on observing while the other is interviewing. This is particularly important when interviewing large groups of people.

The researcher must understand going into the case study that the information gained from the interviews might not be valuable. It is possible that once the interviews are completed, the information gained is not relevant.

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• Section 2: Home
• Developing the Quantitative Research Design
• Qualitative Descriptive Design
• Design and Development Research (DDR) For Instructional Design
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• 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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• Open access
• Published: 30 March 2022

A framework to support the progressive implementation of integrated team-based care for the management of COPD: a collective case study

• Shannon L Sibbald 1 , 2 ,
• Vaidehi Misra 1 ,
• Madelyn daSilva 1 &
• Christopher Licskai 3  

BMC Health Services Research volume  22 , Article number:  420 ( 2022 ) Cite this article

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In Canada, there is widespread agreement about the need for integrated models of team-based care. However, there is less agreement on how to support the scale-up and spread of successful models, and there is limited empirical evidence to support this process in chronic disease management. We studied the supporting and mitigating factors required to successfully implement and scale-up an integrated model of team-based care in primary care.

We conducted a collective case study using multiple methods of data collection including interviews, document analysis, living documents, and a focus group. Our study explored a team-based model of care for chronic obstructive pulmonary disease (COPD) known as Best Care COPD (BCC) that has been implemented in primary care settings across Southwestern Ontario. BCC is a quality improvement initiative that was developed to enhance the quality of care for patients with COPD. Participants included healthcare providers involved in the delivery of the BCC program.

We identified several mechanisms influencing the scale-up and spread of BCC and categorized them as Foundational (e.g., evidence-based program, readiness to implement, peer-led implementation team), Transformative (adaptive process, empowerment and collaboration, embedded evaluation), and Enabling Mechanisms (provider training, administrative support, role clarity, patient outcomes). Based on these results, we developed a framework to inform the progressive implementation of integrated, team-based care for chronic disease management. Our framework builds off our empirical work and is framed by local contextual factors.

Conclusions

This study explores the implementation and spread of integrated team-based care in a primary care setting. Despite the study’s focus on COPD, we believe the findings can be applied in other chronic disease contexts. We provide a framework to support the progressive implementation of integrated team-based care for chronic disease management.

Peer Review reports

Integrated team-based models of care have emerged as a means to improve care delivery and promote system sustainability [ 1 ]. Canadian provinces continue to implement integrated models of care; for example, Canada’s most populous province, Ontario, is currently undergoing significant restructuring to better integrate its healthcare system [ 2 ]; interprofessional and integrated team-based care are at the center of the reform. In the past, much of implementation occurred with a short-term focus on local implementation with limited attention to spread, scale-up, or sustainability [ 3 ]. Indeed, there is a lack of guidance in the literature on how to account for, and support, contextual differences while maintaining the fidelity of successful models. It is unclear whether and how these models will work efficiently in different contexts [ 4 ].

The shift towards integrated team-based care can be observed in the management of chronic obstructive pulmonary disease (COPD) [ 5 ]. Globally, COPD is a leading cause of morbidity, mortality, and health resource consumption [ 6 ]. The burden of COPD is compounded by comorbidities (such as cardiac disease, depression, and anxiety), which require unique care interventions tailored to patients’ needs [ 7 ]. The growing prevalence of COPD, and its substantial impact on patients’ quality of life, require collaboration and coordination across the health sector to effectively manage patient health and prevent hospitalizations [ 8 , 9 ]. The Best Care COPD (BCC) program delivers care within a primary care team setting and is built on collaboration between primary and specialist providers to deliver a care pathway tailored to patients’ needs [ 10 ]. Research on BCC has demonstrated the program’s ability to improve patient outcomes and reduce hospitalizations [ 11 ]. The success of the BCC program has led to its progressive implementation at several primary care sites across a geographic region.

Broadly, implementation efforts have been supported through several frameworks including the Consolidated Framework for Implementation Research (CFIR) [ 12 ], the Promoting Action of Research Implementation in Health Services (PARIHS) [ 13 ], and the Exploration, Preparation, Implementation, and Sustainment (EPIS) framework [ 14 ]. CFIR and PARIHS offer valuable insight to identify factors that can potentially have a central role in the implementation of health services [ 12 , 13 ]. EPIS acknowledges the interplay of these factors through different phases of the implementation process and emphasizes the role of context [ 14 ]. While these frameworks have provided important insight, they have not been sufficiently applied to ‘progressive implementation’ [ 15 ] or spread and scale efforts. A recent publication conducted an overview of reviews in which they developed a conceptual framework that highlighted important constructs as the implementation process progresses; however, the authors acknowledged the lack of empirical findings as a limitation [ 16 ]. Most tools and frameworks do not use empirical research to account for the unique challenges of progressive implementation. We consider spread as progressive implementation - it refers to the horizontal expansion of a program to benefit more patients and/or providers [ 15 ]. Scale-up can be thought of as vertical implementation, occurring at the individual level (among patients, providers and staff), internal-setting level (e.g., leadership, resources, and infrastructure within the organization), and external-setting level (e.g., policy, resources, collaboration, and competition exhibited outside of the organization) [ 17 ].

We wanted to understand the progressive implementation of the BCC program across multiple primary care sites within the Southwestern region of Ontario, Canada. A previous phase of this research explored the initial spread of the program into one site [ 10 ]. This current study focuses on the second phase of implementation and includes an analysis across both phases. The progressive implementation of BCC to several primary care sites provided the opportunity to explore factors that impact the spread of integrated models of team-based care for patients with COPD, across diverse contexts.

Aim and design

We conducted a collective case study exploring the progressive implementation of BCC within one geographic region over multiple years (2019–2021) [ 18 ]. Each implementation site represents a single case in our collective case study approach; the phenomenon of interest across sites was the progressive implementation of the BCC program. Our research design and data collection tools were guided by the CFIR [ 10 ]; the Standards for Reporting Qualitative Research: a synthesis of recommendations (SRQR) was used for reporting accuracy [ 19 ].

Sample and setting

Southwestern Ontario is home to nearly 1 million residents; approximately 30% of residents live in rural regions, 3% identify as Aboriginal, and 30% live below the provincial low-income cut-off [ 20 ]. Service delivery in this region is impacted by barriers to access including geography and a lack of after-hours care; these barriers are particularly prevalent when attempting to access primary care [ 21 ]. Southwestern Ontario exhibits a disparity in the distribution of comprehensive primary care physicians, with providers concentrated in densely populated areas and few physicians serving rural communities [ 22 ]. Further, team-based care is available to a minority primary care practices and where present, COPD specific programming is very uncommon. The BCC program aims to mitigate these barriers to access and provide comprehensive guideline-based care for patients.

BCC is a quality improvement initiative developed in 2009 by the Asthma Research Group Inc. (ARGI) to enhance the quality of care delivered to patients with COPD, within a primary care setting. One-on-one consultations with patients with COPD are conducted by a Respiratory Therapist (RT), RN, or other allied health provider. BCC providers hold an additional credential as a Certified Respiratory Educator (CRE). The program is designed to enable the educators to collaborate with the primary care site to proactively search to invite any patient at risk of COPD to the program. BCC providers work closely with the patient’s care team to develop an action plan, coordinate care, and educate patients about self-management.

The BCC program started in one geographic region of Southwestern Ontario, Canada and providers believed that it contributed to remarkable improvements in clinical outcomes, reduced emergency department visits, and improved patient quality of life [ 11 , 23 ]. The program was implemented into a new primary care team (with five sites) in a neighbouring region as a proof-of-concept [ 10 ]. In 2018, the program was progressively implemented across a wider geography within Southwestern Ontario. At the time of our study, the program was comprised of nine educators (who were all RTs) across several sites (nine family health teams, two community health centres, and seven non-team based care clinics) with plans for continued growth within the region and across the province. Several sites were further divided into smaller clinics (or locations).

Data collection processes

Multiple methods of data collection were used to develop an in-depth understanding of the progressive implementation of BCC. These included living documents (LDs), a focus group, interviews, and document analysis. The research team was an independent, objective party and possessed significant experience conducting semi-structured focus groups and interviews, and expertise in qualitative and mixed research methods. Participants were briefed on the purpose of the study and the data collection methodology in Consent Forms.

LDs are a semi-structured journaling approach [ 24 ] for gathering rich descriptions of participants’ experiences [ 25 ]; they provide key experiential knowledge of planned and unplanned implementation elements. Eight LDs with unique questions were distributed to each RT over a 10-week timeframe. Participants had, on average, 2 weeks to complete each LD within the 10-week time frame and received regular reminders.

A focus group was conducted with the nine providers responsible for implementing and delivering the BCC program. Questions were guided by CFIR, and informed by data collected in the LD to explore experiences of the implementation process and provider experience. CFIR provided a strong guiding framework for the focus group as it is a meta-theoretical framework incorporating a combination of constructs from several implementation frameworks [ 12 ]. This framework was able to provide a comprehensive perspective of the potential influences on implementation [ 12 ]. The findings from the LDs were used to further enhance the data collection tools to allow the research team to account for the dynamic and unique challenges of progressive implementation.

Interviews were conducted over the phone with resident primary care providers (physicians and nurse practitioners) from BCC implementation sites, who work collaboratively with the BCC CRE at their site, but that were external to BCC prior to implementation. Interviews explored implementation, provider experience, and impacts on care provision. The focus group and interviews involved the use of guides, spanned 1–2 h in length, and were audio recorded then transcribed for analysis.

Document analysis was used to advance the researchers’ knowledge of the BCC program’s implementation process through the contextual and background data. We collected existing team documents (such as meeting minutes, training documents, and memorandums of understanding) to develop a rich understanding of the context that supported our analysis.

Data analysis

Data analysis was iterative and continuous; the research team relied on a conceptual and theoretical coding approach to identify themes [ 26 ]. Data was first analyzed independently by data source and then cross-analyzed. The first round of coding was done inductively (SLS and VM), looking for conversation, concepts, and ideas related to the implementation process. From this first round, key themes were pulled from the data and a coding framework was created. The second round of coding was conducted using our framework in a deductive approach (SLS, VM, and MD). Analysis was validated through triangulation and member checking [ 27 , 28 ]. Participants and key informants were frequently consulted to discuss the accuracy and reliability of our findings; feedback was discussed when appropriate, and the findings were amended.

In total, there were 11 participants. All invited RTs participated in the LD and focus group ( n  = 9; response rate = 100%). One physician and one nurse practitioner participated in an interview ( n  = 2; response rate = 33%). The response rates for the living documents ( n  = 8) ranged from 44% to 89%. In total, we collected 47 documents. Our results are informed by all data sources across all sites and include verbatim quotes to demonstrate the themes that emerged through analysis.

Progressive implementation of BCC occurred in three phases: pre-implementation, implementation, and spread and sustainability (post-implementation). The phases built on one another and were mutually reinforcing. The success of each implementation phase was dependent on several mechanisms, which were categorized as foundational, transformative, and enabling (Table  1 ). Mechanisms acted as ‘input forces’ to move through implementation phases and reach the desired outcomes.

Foundational mechanisms

Participants acknowledged their pre-implementation decision to implement the BCC program was multi-faceted. Three elements were foundational in pre-implementation: (1) an evidence-based program, (2) readiness to implement, and (3) implementation support. Each mechanism built on and supported the others.

Across sites, participants unanimously described BCC as being developed based on best practices and strong evidence. When creating the program, ARGI first identified existing programs and gaps within the care available to patients within their region. ARGI used this information to create evidence-based solutions to address patient and provider needs. Participants saw BCC as a multifaceted solution to manage care in a resource-strapped system.

“[this strategy was] not just [to reduce] emergency visits, you’ve got to look at the fact that we’ll decrease the amount of spirometry needed at the hospitals, the full pulmonary function if they only want spirometry. The [RTs] that are freed up - Freed up to deal with seeing sick patients.” – Participant 6, Interview

Participants valued the increased access for their patients to COPD-specific care, within a primary care setting.

“A significant barrier to healthcare is access – FHT/FHO/family physician offices are generally more accessible (local) than hospitals or specialized clinics. [The] BCC program benefits patients by offering easier access to another HCP [Health Care Provider] and tools previously unavailable.” – Participant 4, Living Document 1

When asked about their motivation to implement BCC, participants described a need for increased support for patients and providers regarding COPD care. BCC provided patients with more time to both discuss and learn about their disease and treatment options. Providers felt this time was valuable for both themselves and their patients.

“In my opinion, patients are looking for time with HCP’s to explain their concerns and receive education /feedback etc. Time is a luxury in healthcare, and I feel we do offer a lot of time and education to every patient.” – Participant 5, Living Document 1

The quality of the program was often cited by participants as a key benefit of implementation. Participants explained that BCC standardizes the quality of care and ensures that all patients get access to the same care. Providers valued the self-management focus of BCC and described the program as an interactive and engaged relationship between providers and their patients. One participant shared that “[b]y placing a focus on the patient during every appointment. Ensuring that they understand all of the information being discussed, they have opportunity for questions, and that I look at their overall health and seek any opportunity to help” (Participant 2, Living Document 1).

The decision to implement was also influenced by the support and guidance offered by BCC leadership and the implementation team. Participants noticed the interprofessional composition of the implementation team and how it facilitated peer-to-peer learning. From the beginning, healthcare professionals heard and learned from peers (of the same profession) about the goals, challenges, and successes of the program. The leadership team (consisting of RTs, physicians, and administrators) were available throughout implementation, bolstering participants’ readiness to implement. Frontline providers (e.g., physicians and RTs) were integral to the implementation; almost all participants indicated that having an RT as a core member of the implementation team was vital to overall success. A participant discussed that the implementation team supported all clinicians, centralized the information, and ensured that the messaging (program objectives, provider roles) was consistent from the outset. Additionally, participants valued the “physician-to-physician” role and considered it to be integral to growing a common understanding and increasing commitment (and buy-in) to the BCC program.

A key task of the peer-led implementation team was support in patient recruitment. Recruitment was initially led by the BCC implementation team in collaboration with providers at the implementation sites. BCC’s recruitment strategy involved the RTs “proactively searching [the electronic medical records] for patients who would benefit from the program” (Participant 6, Living Document 1). This initiated provider empowerment as well as surfaced possible future barriers to delivery and evaluation. Participants appreciated the proactive approach to patient recruitment as opposed to waiting for referrals.

The majority of the participants stated their readiness to implement was strengthened with the knowledge of the growing evidence of positive outcomes from the BCC program in other sites. As more sites implemented the BCC program, there was a feeling of not wanting to be left behind.

Transformative and enabling mechanisms

Three transformative mechanisms were key to supporting the successful implementation: (1) adaptive process, (2) provider empowerment, and (3) embedded evaluation. These three transformative mechanisms were buttressed by four enabling mechanisms: (1) provider training, (2) administrative support, (3) role clarity, and (4) patient outcomes.

Adaptive Process

An adaptive process was key in supporting implementation. While the structure of the BCC program was largely prescribed, how the program was implemented was flexible and was often adapted to different practice settings. For example, BCC implementation was adapted based on the funding model of the clinic, clinic capacity, and space.

Program delivery needed to adapt to resources such as administrative capacity and space. The administrative staff were key to supporting implementation and embedding the program in usual care. These staff were well-positioned to increase awareness of the program among patients and adapt BCC delivery to improve efficiency based on current work practices.

“even the receptionist at one of my sites, she at first – patients would come up to the window to see social work and they’d be huffing and puffing, and she didn’t really acknowledge it. But before I left there she was saying, ‘Oh my God, are you OK? Do you need to see our RT? We have a RT.” – Participant 5, Focus Group

Primary care providers acknowledged the program’s easy incorporation into the day-to-day workflow and credited the support from administration staff. In the early implementation, participants described having to spend more time with program elements. A few participants felt this occupied a considerable amount of time and was seen as a challenge to the early delivery and workflow of BCC.

One participant expressed that during early implementation, BCC activities absorbed more time than any other resource:

“Finding patients, then booking them (if they answer phone), then the initial appt. is 1.5 hours, which is completely necessary, and the consultation … chasing down doctors, waiting outside of their rooms to get approval or simply discuss appointment and finally charting which takes up quite a lot of time.” – Participant 9, Living Document 4

BCC’s implementation was an evolving process as the program was adapted by the clinic for its unique context; clarity about roles and responsibilities grew as the clinic worked through the implementation process. This adaptive feature of the program meant that the program required an upfront investment of time and resources which was key in facilitating buy-in from different stakeholders as they progressively integrated the program into their routine activities. For example, administrative staff were key in securing role clarity and trust, through methods such as reminder calls (to patients with access to telephone) to minimize last-minute cancellations and no-shows.

As the implementation process progressed, the program was able to adapt to the processes of the site and integrate within the day-to-day practice to reduce this significant time commitment.

Empowerment & Collaboration

Empowerment was embodied and discussed in several ways; namely, the empowerment of staff to deliver the services associated with the program, and the subsequent empowerment of patients and caregivers to better manage their COPD. Interprofessional collaboration was identified as a key strength of the program as it was an opportunity where staff were “working with the doctor rather than against the doctor, and ideally working with respirologists” (Participant 1, Focus Group). This was a function of time (i.e., increased practice with program delivery, and understanding roles within the program) and observing positive patient outcomes. A provider shared that “there’s a lot of … collaboration that didn’t happen before this [program]… [this has] increased our ability to do our jobs better too” (Participant 2, Interview). Document analysis confirmed this collaboration as a priority, and essential in establishing a self-management plan for the patient. One participant shared that “[t]here have been some challenges such as getting all team member[s] on the same page but over time the program has built trust and has proven its worth” (Participant 6, Living Document 1). Lack of role clarity in early implementation was also described as a barrier. For example, participants felt a lack of communication with all clinic providers and staff gave rise to ambiguity about program roles and objectives; “certain health care professionals felt their toes were being stepped on by the BCC program” (Participant 3, Living Document 5). Additionally, this initial lack of role clarity was perceived as a major challenge to the development of trust and professional relationships; “I feel that a major challenge exist[s] in the understanding of “just what we do”. All HCP’s have been supportive of my presence but not always supportive of talking about the patient right away” (Participant 5, Living Document 2).

Participants believed that achieving empowerment and collaboration could have occurred sooner with more up-front provider training related to clarification of roles and purpose of the program. As the BCC program was able to integrate into the site, the roles of BCC and primary care providers evolved. Participants explained how some physicians initially lacked understanding of the RT roles within the program; one participant felt this lack of understanding may lead to physicians being reluctant to refer patients or give RTs patient information. Multiple participants felt all clinic providers and administration should be trained on the program’s offerings early in implementation. Participants noted that there was an increase in engagement at the clinician and administrative level after the program had been operating for some time and they became more familiar with it. For example, physicians started adding patients to the RT’s schedule, making patient recruitment easier. Embedding the RT on-site, co-located with the primary care provider, helped to enhance role clarity during implementation through regular contact and communication.

Participants noticed as administrative staff developed a clearer understanding of their role and the function of the program, they provided increased support through reminder calls and managing appointments. Participants also noted that in early implementation, higher level of no-show and cancellation rates (more common in patients with barriers to access as well as lack of stable housing, internet, and phone) was, in part, attributable to a lack of role clarity of support from administration and other clinicians. When administrative support was strengthened, there was better patient attendance. As the implementation process progressed and the program became aligned with the internal processes of the site, the program as able to utilize the support from staff to ease the delivery of the BCC program.

Embedded Evaluation

Evaluation made providers aware of the value of the educational component of the program; “they’re understanding their disease, they’re understating why they’re in seeing us. And at first they’re hesitant sometimes at an hour-and-a-half appointment, but I’ve never had anybody upset that they came” (Participant 3, Focus Group). One participant noted that they typically see the benefits of the program within a year. Another participant noted that the impact of the program is demonstrated in decreased patient’s COPD Assessment Test (CAT) scores. The CAT score is a validated measure of disease-specific quality of life.

Embedded evaluation meant patient outcomes were constantly and consistently reported. For most participants, the regular appointments allowed for both formal and informal evaluation. Participants were able to see, first-hand, positive improvements. One participant shared that they “measure [patient outcomes] from comparing their knowledge starting the program compared to today. The patients review their action plans and device technique at most follow ups which demonstrates knowledge and understanding of our program” (Participant 9, Living Document 4).

This was coupled with patients’ positive responses to their appointments. Participants described patients as being receptive to the education, recalling for example patients saying “nobody’s ever shown me this, nobody’s ever explained this to me” (Participant 3, Focus Group). Participants also believed that the program empowered patients by improving patients’ self-efficacy by equipping them with the skills, knowledge, and confidence to manage their COPD. One participant noted that BCC “give[s] patients the power and knowledge to understand their disease, symptoms, and management so they can take control of their own health” (Participant 9, Living Document 1).

There were metrics available such as patients’ CAT and the Modified Medical Research Council (mMRC) breathlessness scores (taken at every appointment), and healthcare services utilization data such as hospital admissions, emergency department visits, and consultations with physicians. One participant expressed that “people like data … even if they don’t truly understand it” (Participant 5, Living Document 6). As the program was implemented across the region, there was an increase in the quantity and diversity of the data available, which, in turn, solidified the program in existing sites and further facilitated progressive implementation to new sites.

BCC is understood to be a high-quality program with demonstrated improved patient outcomes and increased provider satisfaction. BCC was implemented in a primary care setting which is a reliable point of intervention for chronic disease management programs, and more specifically, COPD management programs [ 29 ]. The program has improved patients’ ability to access the appropriate care in the appropriate setting [ 30 ]. By equipping patients with the knowledge and skills to manage their COPD, BCC improved health literacy [ 31 ] by empowering patients to be proactive partners in their own care. This approach is increasingly being viewed as a promising solution to address the complex needs of patients with chronic disease as it allows for the creation of care plans informed by patients for patients [ 8 ]. Successful implementation of an integrated team-based care model is a complex and multi-faceted process. Our research explored the progressive implementation of the BCC program and in doing so exposed some of this complexity. We propose a framework to support progressive implementation that is framed by context; it contains three phases and 10 mechanisms observing the interplay between the mechanisms across the three phases of implementation including pre-implementation, implementation, and spread and sustainability (i.e., post-implementation) (Table 1 ; Fig.  1 ).

Implementation phases and mechanisms

Enabling mechanisms (provider training, administrative support, role clarity, and patient outcomes) worked collectively across the transformative mechanisms (adaptive process, provider empowerment, embedded evaluation). Our results suggest that implementation strategies must deviate from the traditional linear approach [ 16 , 32 ]. Instead, successful implementation must encompass interconnected and symbiotic mechanisms that consider the dynamic nature of the system and adapt to unpredictability and uncertainty within the unique context [ 16 , 32 ]. We found that all the mechanisms were at play across all sites in our study and were difficult to tease apart, however, some mechanisms required varying degrees of effort as sites progressed through implementation. Significant effort and time were needed early in implementation to ensure adaptive delivery and embedded evaluation; too often a lack of embedded evaluation can result in inappropriate delivery methods which, in turn, give rise to inconsistent outcomes [ 33 ]. The opposite was true for provider empowerment, where providers reported feeling more empowered as their confidence in the program, its delivery, and outcomes increased; implementation could be described as an ‘inside-out’ approach where sites were the source and destination for a change in care delivery [ 34 ].

Post-implementation refers to the time when providers start to focus more on sustaining the program within the current site and program leaders focus on spreading into new clinics. The foundational, transformative, and enabling mechanisms at play during implementation remain active in post-implementation, although with less effort required. Demonstrated outcomes and word-of-mouth work to increase awareness of the program in other sites which, in turn, contributes to positive staff morale and staff buy-in when implementing in other sites [ 35 , 36 ]. Altogether, there is an improvement in the ease of implementation [ 8 , 29 ].

Adaptive delivery and embedded evaluation both require a high investment of time and resources during the initial stages of implementation when the program is unfamiliar to staff and patients. A flexible approach to implementation has been shown to improve the likelihood of success in implementation [ 37 ]. In our study, once implementation was complete and the program was in full delivery, providers felt more empowered. Early efforts of adaptive delivery and embedded evaluation could be waned, as they became part of regular care. Clinic buy-in peaked in post-implementation as staff assumed day-to-day support of BCC; concurrently, the program’s workflow processes gradually integrated with the clinic activities and clinic staff took on more of the day-to-day support for the program.

During implementation, cancellations and duration of the appointments presented challenges with some sites for program delivery. Participants felt this was especially relevant when working with patients who experience barriers in access to care due to a lack of stable housing, telephone, and/or internet [ 38 ]. Despite these challenges, BCC’s proactive recruitment strategy (i.e., finding patients who would benefit from the program, as opposed to waiting for referrals) was a key strategy to successful implementation. This was crucial during the initial stage of implementation and helped to expose challenges for implementation and delivery.

Embedding evaluation required a significant amount of work during initial implementation however, this effort waned as implementation progressed. Collecting and sharing data from implementation sites is key not only in sustaining program success, but also in laying the foundation for future implementation success [ 39 ]. In this study, this knowledge of improved patient outcomes and provider satisfaction was shared by word-of-mouth and through the peer-to-peer implementation team. These strategies, along with more traditional academic dissemination strategies, supported progressive implementation.

With the BCC program, providers were able to enhance a patients’ self-management and improve access to appropriate care, resulting in overall improved patient care and improved provider satisfaction. This was accomplished with relative ease; participants were supported at each phase of implementation by a peer-led implementation team and continued support was maintained through peer-to-peer learning. Research shows that a program is more likely to be successfully implemented when there is adequate support coupled with relative ease of implementation [ 40 , 41 ].

Participants unanimously agreed that the BCC program was effective in improving the self-efficacy of the patients by supporting the development of their knowledge, skills and ultimately, confidence to manage their condition, and these findings are consistent with the literature [ 42 , 43 , 44 , 45 ]. Interventions that improve self-efficacy have demonstrated success in improving health outcomes, compared to traditional patient education strategies which give patients information about their conditions but fail to give them the skills or confidence to apply this information [ 46 , 47 ].

Role clarity also supported implementation. Clearly defined roles and each team member’s contribution to COPD care are essential to facilitating the collaboration needed for implementation [ 9 ]. This may be an indication that program implementation is especially efficient when implemented in a team that already offers interprofessional care and one that is well integrated with the organization’s structure [ 48 ]. It follows that the implementation of a program into a high-functioning team will require less overall effort [ 49 ]. Having the educators co-located with the primary care providers enhanced the communication and collaboration among the providers, promoting the exchange of knowledge to facilitate the implementation process [ 50 , 51 ]. Interprofessional teams that are able to work together in one location have been seen to optimize role clarification and support integrated health services [ 52 ]. Furthermore, the function of provider empowerment evolved during the course of implementation; as providers became more aware of their roles, their empowerment enabled increased patient recruitment and ease of program delivery coupled with integration within the existing workflow of the clinic [ 53 , 54 ].

Support from the administrative staff was a key resource in overcoming implementation barriers. In addition to facilitating communication (provider-patient and provider-provider), administrative staff understood the flow of resources – notably space, time, and personnel. As administrative staff became more aware of the program, its objectives, and their role within it, this allowed for efficient implementation, program delivery, and integrated workflow.

Limitations

Qualitative research poses unique challenges to the generalizability of findings and this study is no exception. The aim of this study is to share lessons from one example of progressive implementation as opposed to providing overarching recommendations. Accordingly, we believe the lessons learned are transferable to other settings and contexts.

The primary limitation of this study relates to sample size and response rates, and we used a rigorous approach to our case study (multiple methods across multiple sites) to mitigate this limitation. More specifically, we acknowledge that our small sample size and variability in response rates may allow for potential biases to impact the data. For example, the study did not include results from patients and their caregivers, and this can pose the possibility of bias, especially in findings that report success based on perceived patient-centered outcomes. We would like to highlight that these groups were included in our larger research program which may serve to limit the influence of potential bias and its impact on the results.

Among the participants that were included in this study, especially in the focus group, there is a potential for controversial or unpopular views to be suppressed which can give rise to false consensus [ 55 ]. Inclusion of a variety of data collection tools such as LDs and document analysis provided staff with an opportunity to share their individual insights. The data collected through these tools were consistent with the data collected through the focus group, suggesting that the focus group findings were representative of participants’ views. It is important to note that this study also involved member checking to provide another opportunity for the research team to ensure that their analysis of the data was accurate [ 27 , 28 ]. Furthermore, there also may be an increased likelihood of the suppression of negative opinions if participants are direct providers of the BCC program or considered to be ‘insiders’ [ 56 ]; we mitigated the ‘insider effect’ by including the perspective of care providers who, prior to implementation, were external to the BCC program.

Finally, it would be remiss to not mention the impact of the COVID-19 pandemic on this work, however, it is difficult to fully assess its influence. Our data collection was concluding at the beginning of 2020, as the effects of the pandemic were beginning to impact the region. As a result, our study did not explore, nor do we believe it was impacted by the pandemic. The pandemic has shifted how healthcare operates; this may change the focus from co-location to collaboration in regards to integrated team-based care [ 52 ]. Further research is needed to understand how the pandemic has impacted the progressive implementation of BCC and other integrated, team-based models for chronic disease management.

The rapidly increasing prevalence of chronic diseases, and COPD more specifically [ 57 ], emphasizes the need to better support patients and providers in the implementation of appropriate models of care [ 5 ]. The successful implementation of the BCC program led to improved management of COPD, quality of patient care, and patient and provider experience. This case study explored mechanisms that support the progressive implementation of integrated team-based care within the context of COPD. While BCC has been applied within the context of COPD, the insights gained from this study can inform the application of the program in the context of other chronic diseases. The performance of BCC at various sites in Ontario suggests that integrated team-based care has the potential to manage the growing impact of chronic disease on Canadians and subsequent burdens on the healthcare system.

Availability of data and materials

The datasets generated and/or analysed during the current study are not publicly available due to privacy and confidentiality but are available from the corresponding author on reasonable request.

Abbreviations

Asthma Research Group Inc.

Best Care COPD

Consolidated Framework for Implementation Research

• Chronic obstructive pulmonary disease

Exploration, Preparation, Implementation, and Sustainment

Promoting Action of Research Implementation in Health Services

Respiratory therapist

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Acknowledgements

The authors would like to acknowledge the support of the BCC healthcare providers who were generous with their time and insight during their participation in this study. The authors would also like to acknowledge the support from the Asthma Research Group Inc. in conducting this study, analyzing the results, and understanding the implications of this important work.

SLS and MD are supported by the Canadian Institutes of Health Research (CIHR) Operating grant.

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Shannon L Sibbald, Vaidehi Misra & Madelyn daSilva

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Shannon L Sibbald

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The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. SLS conceived the study and designed the methods. SLS prepared and analyzed the data with input from VM, MD, and CL. SLS, VM, and MD drafted the manuscript with substantial input from CL. All authors contributed to and approved the final manuscript.

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This research project received ethics approval from Western University Health Sciences Research Ethics Board (Study IDs 108415 & 116445). The authors can confirm that the study was conducted in accordance with guidelines and regulations relevant to studies involving humans and/or the use of human tissue samples or human data. Informed consent was obtained from all subjects and/or their legal guardian(s).

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SLS, VM, and MD declare that they have no competing interests. CL discloses that he has assumed unpaid leadership or fiduciary roles for the Canadian Thoracic Society and Asthma Research Group Inc. (ARGI). CL also discloses receipt of payment or honoraria from GlaxoSmithKline, AstraZeneca, Boehringer Ingelheim, and Novartis.

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Sibbald, S.L., Misra, V., daSilva, M. et al. A framework to support the progressive implementation of integrated team-based care for the management of COPD: a collective case study. BMC Health Serv Res 22 , 420 (2022). https://doi.org/10.1186/s12913-022-07785-x

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Case study definition

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• Published: 11 April 2024

Dynamics of collective cooperation under personalised strategy updates

• Yao Meng   ORCID: orcid.org/0009-0005-0367-4347 1 ,
• Sean P. Cornelius 2 ,
• Yang-Yu Liu   ORCID: orcid.org/0000-0003-2728-4907 3 , 4 &
• Aming Li   ORCID: orcid.org/0000-0003-4045-8721 1 , 5  

Nature Communications volume  15 , Article number:  3125 ( 2024 ) Cite this article

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• Complex networks
• Cooperation
• Decision making
• Evolutionary theory

Collective cooperation is essential for many social and biological systems, yet understanding how it evolves remains a challenge. Previous investigations report that the ubiquitous heterogeneous individual connections hinder cooperation by assuming individuals update strategies at identical rates. Here we develop a general framework by allowing individuals to update strategies at personalised rates, and provide the precise mathematical condition under which universal cooperation is favoured. Combining analytical and numerical calculations on synthetic and empirical networks, we find that when individuals’ update rates vary inversely with their number of connections, heterogeneous connections actually outperform homogeneous ones in promoting cooperation. This surprising property undercuts the conventional wisdom that heterogeneous structure is generally antagonistic to cooperation and, further helps develop an efficient algorithm OptUpRat to optimise collective cooperation by designing individuals’ update rates in any population structure. Our findings provide a unifying framework to understand the interplay between structural heterogeneity, behavioural rhythms, and cooperation.

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Introduction

Cooperative behaviour—in which individuals pay a cost to confer a benefit to others—is widely and deeply embedded in human and animal societies alike, and has attracted great research interests in studying the underlying mechanisms of favouring the emergence of cooperation 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 . Under the prominent metaphor of the prisoner’s dilemma 16 , without additional mechanisms including direct 17 , 18 or indirect reciprocity 19 , 20 , 21 , 22 , and punishment 23 , 24 , unstructured populations—wherein everyone interacts with everyone else—are known to leave no opportunity for the survival of cooperators 25 , 26 . Thus in recent decades, researchers have been exploring evolutionary game dynamics in structured populations, where who interacts with whom is determined by a network or population structure, with links representing interactions between different individuals (nodes) 4 , 5 , 6 , 27 , 28 , 29 , 30 . The central question is: which population structures promote cooperation, and which hinder it?

In homogeneous networks—where all individuals basically have similar numbers of neighbours—a well-known finding is that cooperation is favoured if the ratio between the benefit ( b ) provided by a cooperator and the associated cost paid ( c ) exceeds the average number of neighbours 〈 k 〉, namely the simple rule 4 b / c  > 〈 k 〉. Similar results can be found in the more general case: Allen et al. analytically calculated the critical benefit-to-cost ratio C * , above which cooperation is promoted for an arbitrary network topology 5 . Apart from confirming C *  = 〈 k 〉 for homogeneous structures, this result informs a higher value of C * for heterogeneous structures 31 , wherein different individuals may have wildly different numbers of neighbours. Accordingly, although heterogeneous structures like scale-free networks 32 are ubiquitous in real systems, they appear to hinder the emergence of cooperation compared to homogeneous structures 31 .

Despite remarkable advances in our understanding of the emergence of cooperation, many studies have confined that individuals update their strategy synchronously 6 , 33 , 34 , 35 —that all individuals update at exactly the same time. However, perfect synchronism is absent from the real world, and it has been shown that asynchronous updating—individuals are allowed to update at different time—can significantly alter the evolution of cooperation 36 , 37 , 38 , 39 , 40 . A typical asynchronous update rule is the death-birth update, where only a single individual is selected uniformly at random to die and their neighbours spread their strategies by competing for the vacant position at each time step 4 , 5 . Alternatively, individuals may change their strategies by mimicking that of their neighbours (imitation 4 , pairwise comparison 12 , 41 ). All these important canonical updating rules have been based on a key assumption: that all individuals update their strategies at the same rate.

In reality, humans behave in more sophisticated ways in decision-making than simple identical updating. An empirical study on evolutionary games uncovered that individuals are observed to have many different possibilities for strategy updating in human behavioural experiments 42 . Indeed, both cognitive processing speed and personality traits can have an impact on the time of individual decision-making. Previous empirical studies have found that individuals vary significantly in cognitive processing speed 43 , 44 , 45 . For example, individuals with greater cognitive abilities have high information processing speed and display a short reaction time. On the other hand, many personality traits are also evidenced to correlate with the decision-making speed 46 . Taken together, the previous assumption of identical update rates for all individuals is too ideal to portray the update event and heterogeneous individual interaction rhythms in realistic scenarios 47 , 48 . This prompts us to ask how this dynamical heterogeneity might interact with structural heterogeneity to alter the evolution of cooperation.

Here we investigate evolutionary game dynamics under non-identical rates of strategy updating. Specifically, we consider the scenario where individuals are allowed to update their strategies at diverse individual rates. We find that non-uniform rates of strategy updating can have profound effects on the emergence of cooperation, especially on heterogeneous structures, and reveal a significant decrease in C * necessary to promote cooperation. Moreover, we develop an efficient algorithm OptUpRat to minimise the threshold for the emergence of cooperation by tuning the update rate of each individual on any network.

We consider evolutionary game dynamics on a structured population of N players, whose interactions are represented by an undirected, unweighted network. At any given time, the state of each node (player) is characterised by a strategy of either cooperation (C) or defection (D) (Fig.  1 a). In each round of the game, every node i plays the game pairwise with its immediate k i neighbours. Specifically, cooperators pay a cost c to provide a benefit b to each of their neighbours, while defectors pay nothing, and thus provide no benefit. In this way, each node i gains an average payoff f i , corresponding to the average benefits received (from neighbouring cooperators) minus its cost.

The interactions between four individuals are depicted in the example network structure in a , where individuals play games with their neighbours and gain the corresponding payoffs. The evolutionary process starts from a population of full defectors (red), and a cooperator (blue) invades the population via the top site. b The update event for each individual occurs as a Poisson process. We indicate on the timeline when each individual is chosen to update its strategy. The colour of the dot indicates the strategy after the update, which may be unchanged. When individuals' update rates are identical, they will have approximately the same number of strategy updates (numbers in orange, left panel), while for non-identical update rates, individuals with higher rates will update their strategies more often (right panel). The update rates for each individual in the right panel are λ 1  = 1,  λ 2  = 1.25,  λ 3  = 1.75 and λ 4  = 2, respectively. The change in the fraction of cooperation throughout the game is illustrated in c , and the evolutionary process ends when the population reaches a state of either full defection (left panel) or full cooperation (right panel).

Traditionally, individuals are assumed to update their strategies following independent Poisson processes with identical rates. Here we depart from this practice: allowing each individual i to update its strategy with personalised rate λ i (Fig.  1 b). When an individual is chosen for an update, it does so by copying the strategy of one of its neighbours j , with probability proportional to the fitness of j , generally defined as F j  = 1 +  δ f j , where δ  > 0 captures the intensity of selection 4 , 5 (see Methods). For strong selection intensity, cooperation is disfavoured since the initial cooperator will not be able to survive or spread its strategy. Thus, to systematically uncover the effects of heterogeneous update rates on the fate of cooperators compared to existing findings, here we focus on the canonical case of weak selection.

To quantify the ability of cooperation to proliferate, we initialise our simulations with a single cooperator placed uniformly at random in a population among N  − 1 defectors. The evolutionary game ends when a state with either all cooperators or all defectors is reached (Fig.  1 c). We define the fixation probability of cooperation ( ρ C ) as the probability of reaching the state of full cooperation over many realisations of this process. We can analogously define a probability ρ D of reaching a full-defection state starting from a single defector planted of N  − 1 cooperators. Our interest in this study is the condition under which cooperation is favoured to replace defection than vice versa 4 , 5 , 26 , namely ρ C  >  ρ D . This condition is equivalent to ρ C  > 1/ N (Supplementary Note  1) , namely that selection favours the emergence of cooperation relative to the neutral drift ( δ  = 0), in which neither cooperation nor defection is favoured ( ρ C  =  ρ D  = 1/ N ).

Evolutionary game dynamics on complex networks

First, we explore how the heterogeneous strategy updating affects the fate of cooperators on four commonly-studied population structures: lattice, small-world, Erdös-Rényi, and scale-free networks (Fig.  2 ). Under the traditional scenario of identical update rates ( λ i  = 1 for all i ), scale-free networks demand the largest critical benefit-to-cost ratio C * , above which cooperation is favoured among all the four structures, and the lattice structure the smallest (Fig.  2 a), consistent with previous findings 4 , 5 . But surprisingly, when a node’s update rate varies inversely with its number of neighbours ( λ i  = 1/ k i ), we find that this trend is reversed (Fig.  2 b). Here, the scale-free network becomes the most amenable to cooperation, and lattice the least. Interestingly, we find that heterogeneous update rates can even improve upon the canonical threshold b / c  > 〈 k 〉 (namely, C *  = 〈 k 〉) for homogeneous populations 4 , allowing cooperation to emerge even when b / c  < 〈 k 〉 (namely, C *  < 〈 k 〉). Furthermore, we find that this pattern is strengthened when the update rate is inversely proportional to higher powers of k i (Fig.  2 d). In contrast, when λ i is positively related to k i , the ordering of C * over different structures matches the identical-rate case, but with the inhibition of cooperation fixation by heterogeneous networks amplified (Fig.  2 c). We show the robustness of our results over different population sizes, average degrees and selection intensities in Supplementary Figs.  1 – 3 .

We show the fixation probability of cooperation ( ρ C ) as a function of the benefit-to-cost ratio ( b / c ) over different settings of the update rate ( λ i ) of individual i , namely identical ( λ i  = 1 for every individual in a ) and heterogeneous ( λ i  = 1/ k i in b where k i is the number of neighbours of i ,  λ i  =  k i in c ) on lattice, Erdös-Rényi 65 (ER), small-world 66 (SW) and scale-free 32 (SF) networks, respectively. The critical benefit-to-cost ratio C * above which the cooperation is favoured for each network occurs when the corresponding curve intersects the horizontal line representing the neutral-drift case ( ρ C  = 1/ N ). C * for the scale-free case (purple) is marked. We demonstrate that the trend of C * reverses when the update rate varies inversely with k i in b , presenting the advantage of SF networks on favouring cooperation. d The ordering of C * for the four networks considered holds with \({\lambda }_{i}=1/{k}_{i}^{\gamma }\) ( γ  = 1, 2, 3, 4). Here we also show that SF networks are the most amenable to cooperation at non-identical update rates compared with other networks. e Simulation results on C * in a– d are in good agreement with our theoretical calculations shown in equation ( 1 ). Numerical values of ρ C are obtained from the fraction of simulations in which the population reaches full cooperation out of 10 7 independent realisations on networks of 98 nodes for lattice and 100 for other networks with an average degree 〈 k 〉 = 6, and δ  = 0.01. Source data are provided as a Source Data file.

We further shed light on our numerical findings by deriving a closed-form expression for the critical benefit-to-cost ratio C * as a function of the network structure (see Methods)

Here, k i  = ∑ j e i j defines the number of neighbours (degree) of individual i , and e i j  =  e j i  = 1 indicates that there is an edge between nodes i and j ( e i j  =  e j i  = 0 otherwise). The probability of a 1-step ( n -step) random walk from i to j is denoted by p i j ( \({p}_{ij}^{(n)}\) ), and η i j is the coalescence time 49 —the expected time for two random walks starting from nodes i and j to meet at a common node. As shown in Fig.  2 e, all numerical results in Fig.  2 a-d are in good agreement with the theoretical prediction of equation ( 1 ).

Role of network hubs

To intuitively understand why heterogeneous update rates can improve the fixation of cooperation in heterogeneous networks, we first consider how the evolutionary dynamics play out on a simple double-star structure (Fig.  3 ). When the fixation of cooperation occurs in this highly heterogeneous structure, it usually does so in four stages: (I) occupation of one of the hubs; (II) formation of a stable cluster of cooperators among that hub and its neighbours; (III) occupation of the other hub; and finally (IV) spread to the remaining nodes. As such, the ultimate triumph of cooperators can be thwarted if a hub imitates defection from even one of its (many) neighbours before stages (II) and (IV) are complete (Fig.  3 c). There are ample opportunities for this to occur under the traditional setting of identical update rates ( λ i  = 1), as illustrated in Fig.  3 b. When λ i  = 1/ k i however (Fig.  3 a), hubs update relatively infrequently. As such, once a hub becomes a cooperator, it is effectively locked-in, giving time for its strategy to spread to the hub’s neighbours. Note that this lock-in effect can facilitate the formation of cooperative clusters to have higher payoffs to resist the invasion of defectors, yet defectors receive a lower payoff after driving their neighbours to defectors and further reduce their survival chances. By the same logic, the preferential updating of hubs ( λ i  =  k i ) usually leads to the extinction of cooperation, as the formation of stable clusters of cooperators and the spread of cooperation is even harder than the traditional scenario of identical updating (Fig.  3 c).

a The hubs, two centres of the double-star structure for example, have low update rates when λ i  = 1/ k i ( k i is the number of connections for each node), which facilitates the formation of local cluster of cooperation (blue dot, Stage II) once it is occupied by a cooperator (Stage I). Likewise, once the left hub spreads cooperation to the right hub (Stage III), the remaining nodes are quickly driven to cooperators (Stage IV). b When the update rates are identical ( λ i  = 1), the hubs have many opportunities to change their strategy to defection before all neighbours become cooperators (Stage IV), making the fixation of cooperation less likely. c The hub switches its strategy quite frequently when λ i  =  k i , which makes it hard to form even the left C-cluster (Stage II), to say nothing of spreading cooperation to the right centre.

In Fig.  4 , we illustrate the fundamental mechanism explaining why infrequent updates of hubs can facilitate cooperation. If an individual (grey node in Fig.  4 a) decides to update its strategy, it will imitate the strategy of its neighbours according to their payoffs. The neighbouring cooperator obtains an average payoff P C  =  b q C ∣ C (〈 k 〉 − 1)/〈 k 〉 −  c and the neighbouring defector obtains P D  =  b q C ∣ D (〈 k 〉 − 1)/〈 k 〉, where q C ∣ C ( q C ∣ D ) represents the conditional probability to find a cooperative neighbour for a given cooperator (defector). The contribution to the neighbouring cooperator and defector from the updating individual is excluded since they are equal. Thus the cooperator is favoured compared to the defector to disperse its strategy if P C  >  P D , namely

with Q  = ( q C ∣ C  −  q C ∣ D )(〈 k 〉 − 1) capturing the average number of cooperative neighbours that a cooperator has more than a defector. For the canonical setting with identical update rates ( λ i  = 1), we know Q  = 1 according to pair approximation (Supplementary Note  2) , namely a cooperator has on average one more cooperative neighbour than a defector (Fig.  4 a). This leads to the conclusion that cooperation is favoured when b / c  > 〈 k 〉 (namely, C *  = 〈 k 〉), which also degenerates to the simple rule 4 for homogeneous networks where k i  = 〈 k 〉.

a– c Illustration on the scenario where a cooperator (blue dot) and a defector (red dot) compete to spread their strategy to the individual (grey dot) selected for strategy update under different update rates λ i . Since behaviour dispersal occurs in the neighbourhood, the cooperator obtains on average b Q /〈 k 〉 −  c more payoff than the defector (equation ( 2 )), and the cooperator is favoured when the above expression is positive. a For identical updating ( λ i  = 1), the cooperator has one more cooperative neighbour than the defector, therefore it receives b /〈 k 〉 more benefit than the defector at a cost of c . b When λ i  = 1/ k i , the net benefit of the cooperator relative to the defector exceeds b /〈 k 〉 because the fraction of cooperative neighbours of the cooperator further increases compared to the defector, offering the cooperator a higher chance for dispersal. c We show that the fast strategy update of hubs ( λ i  =  k i ) reduces the number of cooperative neighbours of the cooperator, which exceeds that of the defector by less than one. This lowers the benefit of the cooperator and reduces the chance to win the empty site. We further compare the state of the hub (grey lines) and the fraction of cooperation among its neighbours (blue lines) of a scale-free network with different settings of update rates ( d– f ). Generally, the hub imitates one of its cooperative neighbours and keeps cooperation for several rounds (light blue shaded region) before switching to defection (light red shaded region) in d . Statistically, we count the fraction of cooperators in the neighbourhood of a cooperative hub ( q C ∣ C for the hub) throughout evolutionary process in g , and q C ∣ C  −  q C ∣ D for nodes with different degrees in h . Numerical calculations confirm the mechanism we present in a– c . Here, we use the same network parameters as Fig.  2 . Source data are provided as a Source Data file.

Next we show how heterogeneous update rate alters the local dispersal of cooperation. When λ i  = 1/ k i , we find that Q  > 1 (Supplementary Note  2) , indicating that the number of cooperative neighbours of a cooperator exceeds that of a defector by more than one (Fig.  4 b). This implies that the net payoff of cooperators relative to defectors is further increased, giving cooperators more advantage in competition and dispersal. Therefore, the critical ratio for λ i  = 1/ k i is smaller than the average degree 〈 k 〉 for a wide range of heterogeneous networks ( C *  < 〈 k 〉). In contrast, when λ i  =  k i , the hubs update frequently and Q  < 1 (Supplementary Note  2) , indicating that on average, the number of cooperative neighbours of a cooperator exceeds that of a defector by less than one (Fig.  4 c). This leads to a larger critical ratio ( C *  > 〈 k 〉) for promoting cooperation compared to the scenario with identical update rates shown in Fig.  4 a.

We have numerically confirmed the above mechanism on larger scale-free networks. Figure  4 d–f show the state of the hub, and the fraction of cooperators among the hub’s neighbours over the course of the game dynamics. For λ i  = 1/ k i , we observe long-lasting periods of cooperation on the hub (Fig.  4 e), with infrequent strategy switches from cooperation to defection, which results in the highest q C ∣ C for the hub (Fig.  4 g) and in turn the highest q C ∣ C  −  q C ∣ D over all nodes with different degrees compared to other settings (Fig.  4 h). In contrast, fast-updating hubs ( λ i  =  k i ) have the lowest average fraction of cooperators among their neighbours (Fig.  4 g), leading to a low fraction of cooperative neighbours for the cooperators relative to defectors over the whole network (Fig.  4 h). This confirms that degree-inverse update rates promote cooperation on heterogeneous networks because a hub with a low update rate is more conducive to driving its neighbours to cooperation, which further enhances the local dispersal of cooperation among nodes with different degrees.

Furthermore, we find that infrequent updates of hubs can also bring long-term advantages to individuals. We could even consider the general evolutionary process with mutation, where a mutant appears with probability u when the population reaches full cooperation or full defection. Each individual accumulates long-term payoffs during a long period of time. Even with a high mutation rate ( u  = 1), we show that the inverse relationship between update rates and nodes’ degrees results in a higher long-term payoff for individuals than identical rates ( λ i  = 1) (Fig.  5 a). In contrast, frequent updates of hubs ( λ i  =  k i ) lead to a lower payoff than the identical settings (Fig.  5 a). This result is also robust over different mutation rates and selection intensities (Fig.  5 b, c). Moreover, when the mutation is rare, the population is almost always in full cooperation or full defection, and the time spent in full cooperation (defection) is proportional to ρ C ( ρ D ) 50 . Therefore, the settings of update rates which promote cooperation further lead to a higher long-term average payoff, since individuals get b  −  c in full cooperation but 0 in full defection.

a We calculate the average long-term individual payoff \({P}_{{\lambda }_{i}=1/{k}_{i}},{P}_{{\lambda }_{i}=1}\) and \({P}_{{\lambda }_{i}={k}_{i}}\) corresponding to different update rates ( λ i  = 1/ k i ,  λ i  = 1,  λ i  =  k i ) for 50 individuals during the evolutionary process with mutation rate u  = 1 on a scale-free network, which are presented as mean values +/- SD. b We present the payoff difference \({P}_{{\lambda }_{i}=1/{k}_{i}}-{P}_{{\lambda }_{i}=1}\) between λ i  = 1/ k i and λ i  = 1 over different selection intensities and mutation rates. Analogously, the long-term payoff difference between identical rates and rates proportional to nodes' degrees \({P}_{{\lambda }_{i}=1}-{P}_{{\lambda }_{i}={k}_{i}}\) is shown in c . The long-term payoff is averaged over 10 3 independent samples, where the average payoff in each run is obtained over 10 6 rounds. Source data are provided as a Source Data file.

Theoretical analyses

In addition to the role of hubs that we uncover for the three specific update rate settings ( λ i  = 1/ k i ,  λ i  = 1,  λ i  =  k i ), can we derive the general rule for promoting cooperation that also applies to other distributions of update rates? We next explore how different distributions of λ i affect C * over five different synthetic networks: lattice, random regular, Erdös-Rényi, small-world, and scale-free. For a given network structure, we theoretically predict C * via equation ( 1 ) for uniform, normal, exponential and power-law distributions of the update rate. We find that the critical threshold of a typical homogeneous network—such as a lattice or random regular network—is almost unaffected by the choice of update rate distribution (Fig.  6 a, Supplementary Fig.  4) . In contrast, heterogeneous structures are quite sensitive, with scale-free networks presenting the most drastic variations in C * among the different update-rate distributions we consider. This malleability of C * in heterogeneous networks suggests the possibility of deliberately tuning the update rates to lower the barrier for the emergence of cooperation in a particular network. But to put this into practice, we must first overcome a computational hurdle.

a Illustration of C * above which cooperation is favoured under uniform (Uni.), normal (Nor.), exponential (Exp.) and power-law (Pow.) distributions of update rates on different structures of networks. Here each dot corresponds to a sample, and the error bars are plotted over 100 samples, indicating the mean values with +/- SD. The robustness of our results with different average degrees is shown in Supplementary Fig.  4 . Note that the coupling of node degree and update rate will not bring quantitatively different results on the average C * . The consistent theoretical evidences and details are given in Supplementary Fig.  5 . b C * obtained from our theory (equation ( 3 )) with various update rate ( λ i ) configurations (different markers) are well-matched with the numerical simulations on empirical networks corresponding to face-to-face contacts in an office building 51 (Off.) and a high school 52 (Stu.). Based on the analytical condition given in equation ( 4 ), we seek to reduce C * on large heterogeneous structures, specifically by letting nodes' update rates vary inversely to their degree k i as shown in c , where the size (colour) of nodes captures the magnitude of k i ( λ i ). Source data are provided as a Source Data file.

In order to calculate C * using equation ( 1 ), one needs to solve a system of N ( N  − 1)/2 linear equations for the recurrence relations between the η i j (equation ( 7 ) in Methods). Unfortunately, this requires an overall complexity of \({{{{{{{\mathcal{O}}}}}}}}({N}^{6})\) , rendering the problem intractable for large networks. To circumvent this, we offer an efficient approximation C * as

This expression obviates the need to solve large systems of linear equations and reduces the computational complexity to \({{{{{{{\mathcal{O}}}}}}}}({N}^{3})\) . Here 〈 k 2 〉 is the second moment of the degree distribution. We have \(\zeta={\sum }_{i,j}\frac{{k}_{i}{k}_{j}\Lambda }{N{K}^{2}({\lambda }_{i}+{\lambda }_{j})}\) , where Λ = ∑ i λ i defines the total rate of update events and K  = ∑ i k i is the summation of all nodes’ degrees. Finally, \({\Delta }_{{\lambda }^{(1)}},{\Delta }_{{\lambda }^{(2)}},{\Delta }_{{\widetilde{\eta }}_{n}}\) and \({\Delta }_{{\widetilde{\eta }}_{d}}\) are constants related to the heterogeneity of update rates and coalescence times, the expressions for which are given in Methods. When the update rates are identical, we have \({\Delta }_{{\lambda }^{(1)}}={\Delta }_{{\lambda }^{(2)}}={\Delta }_{{\widetilde{\eta }}_{n}}={\Delta }_{{\widetilde{\eta }}_{d}}=0\) , and equation ( 3 ) recovers the previous results 4 , 31 .

Figure  6 b compares the value of C * predicted by the approximation in equation ( 3 ) with that of numerical simulation on two empirical social networks 51 , 52 . We see that our approximation is remarkably accurate in both networks, regardless of the distribution of the update rates. Moreover, equation ( 3 ) offers intuition behind our previous observation that homogeneous structures are robust to different update rates (Fig.  6 a). The high symmetry present in these networks means that heterogeneous update rates affect only a limited number of nodes. For such networks, we have \({\Delta }_{{\widetilde{\eta }}_{n}}\approx {\Delta }_{{\widetilde{\eta }}_{d}}\approx 0\) , meaning that C *  → 〈 k 〉 in the limit of large N . This coincides with the classical result 4 ( C *  = 〈 k 〉) regardless of the distribution of update rates.

A simple condition for the emergence of cooperation

Starting from equation ( 3 ) (see Methods), we have the critical benefit-to-cost ratio for large heterogeneous networks

where 〈 k 〉 is the average degree and \({\Delta }_{{\widetilde{\eta }}^{(\infty )}}\approx \frac{\overline{\eta }}{{K}^{2}}{\sum }_{i < j}({k}_{i}-{k}_{j})({\lambda }_{i}-{\lambda }_{j}){e}_{ij}/({\lambda }_{i}+{\lambda }_{j})\) . Note that \({\Delta }_{{\widetilde{\eta }}^{(\infty )}} < 0\) when any pair of nodes i and j satisfies the rule ( k i  −  k j )( λ i  −  λ j ) < 0. When the update rates are identical, we have \({\Delta }_{{\widetilde{\eta }}^{(\infty )}}=0\) and hence C *  ≈ 〈 k 〉 as expected. In contrast, C * is smaller (larger) than 〈 k 〉 when \({\Delta }_{{\widetilde{\eta }}^{(\infty )}} < 0\) ( \({\Delta }_{{\widetilde{\eta }}^{(\infty )}} > 0\) ) (Supplementary Note  3.3) . Table  1 summarises the values of C * predicted by equation ( 4 ) for the combinations of network structure/update-rate settings.

Taken together, we have theoretically motivated an efficient rule of thumb for lowering the threshold for the emergence of cooperation on large heterogeneous structures. Put simply, the order of any pair of nodes’ update rates (for example, λ i  >  λ j ) should be reversed from the order of the nodes’ degrees (for example, k i  <  k j ). That is, the one with larger degree should have smaller update rates and vice versa, as is demonstrated in Fig.  6 c. In other words, the hubs in networks should update infrequently compared to their neighbours with fewer connections to promote the formation of cooperative clusters, which is consistent with the underlying mechanisms shown in Figs.  3 and 4 . A simple but general realisation of this rule is \({\lambda }_{i}=1/{k}_{i}^{\gamma }(\gamma \, > \, 0)\) which we study numerically in Fig.  2 d for different values of γ . This rule can achieve a lower critical ratio C * than identical update rates ( γ  = 0) on both synthetic heterogeneous (Fig.  2 b) and empirical networks ( γ  = 1) (Fig.  6 b and Supplementary Table  1 and Supplementary Figs.  6 and 7) . Meanwhile, the contrary configuration of \({\lambda }_{i}={k}_{i}^{\gamma }\) leads to increases in C * on heterogeneous networks (Figs.  2 c and 6 b and Supplementary Figs.  8 and 9) .

Moreover, we show that our conclusion can also be applied to other social dilemmas (Supplementary Note  4) . For the general two-player game, a cooperator receives rewards R from mutual cooperation, while defectors obtain punishment P from mutual defection. A defector attempting to exploit a cooperator obtains T and leaves S to its opponent cooperator. We show that cooperation is favoured over defection when R  >  P  + ( T  −  S )( C *  − 1)/( C *  + 1), where a lower threshold for R can be achieved with a lower C * . Note that here C * is exactly the critical threshold under the donation game. This indicates our conclusion applies to other social dilemmas, such as the general prisoner’s dilemma ( T  >  R  >  P  >  S ) 16 , snowdrift game ( T  >  R  >  S  >  P ) 3 and stag hunt game ( R  >  T ≥ P  >  S ) 53 .

The optimal update rate on any network

As an engineering application of designing unmanned and autonomous systems, can we adopt the simple heuristic to favour collective cooperation among agents? Specifically, can we find the optimal set of λ i for a given networked system? To answer this question, we develop OptUpRat, an optimisation algorithm, to search for a set of λ i that minimises C * (See Box  1 , Supplementary Note  5 and Supplementary Fig.  10) . Our algorithm OptUpRat is based on RMSProp (root mean square propagation), which is an optimisation algorithm designed for training neural networks 54 . Note that the settings of the learning rate ϵ , decay rate ρ and constant δ opt parameters are the same as those in RMSprop—the learning rate ϵ controls the step size of the iteration; ρ controls the decay rate of the moving average; and δ opt is a small constant added to the denominator to prevent division by zero (see the values of those parameters in Methods). To transform the constrained optimisation with λ i  > 0 for each individual i into an unconstrained optimisation problem, we define \({\lambda }_{i}=\exp ({\theta }_{i})\) to establish a function mapping from θ i to C * . Then the optimal update rate and the corresponding C * can be obtained via iterative gradient descent, where the gradient is computed by solving a system of N ( N  − 1)/2 linear equations after taking the derivative with respect to θ i on both sides of equation ( 7 ) in Methods.

Consistent with our rule, Fig.  7 a shows the scale-free network is more flexible and attain a much smaller threshold at its optimal rate than the lattice. Moreover, the update rates of higher-degree nodes tend to decrease during the optimisation process, while those of smaller-degree nodes increase (Fig.  7 b and Supplementary Fig.  11) . Interestingly, we find that even on homogeneous structures such like lattices, a policy of identical update rates is not the best choice for promoting cooperation. Indeed, the final update rates deviate significantly from the initial conditions (Fig.  7 c and Supplementary Fig.  12) . Figure  7 d shows that the optimal update rates for different network structures are consistent with our rules shown in Fig.  6 c—namely that a node i ’s update rate λ i should vary inversely with its degree k i .

a We present the convergence of the objective function C * for a scale-free network (purple) and a lattice (blue) over 10 3 iterations of our optimisation algorithm OptUpRat. b The corresponding evolution of the (tunable) λ i for all nodes, which are divided into three categories (large, moderate and small), based on the range of degrees in the scale-free network. The mean update rate among individuals in each category is shown with the thicker line. We see that the optimal update rates tend to decrease for large nodes (orange) and generally increase for small nodes (green). c For the lattice, the optimal update rate also presents the deviations from the identical rate. Beyond presenting the detailed process for optimising C * in panels a – c we show the final λ i compared to the nodes' degree for scale-free networks (generated by the configuration model 67 , Barabéasi-Albert model 32 ), small-world network 66 (rewiring probability 0.7) and networks constructed from a uniform attachment model 68 in d , where we normalise the optimal update rate and the node degree. We again observe an inverse relationship between the final update rates and the corresponding nodes' degree, consistent with our rule shown in Fig.  6 c. Here we use the same network parameters as Fig.  2 . Source data are provided as a Source Data file.

Box 1: optimisation algorithm OptUpRat

Input: Adjacent matrix E of any network

Output: the optimal rate λ i for each i and the corresponding critical ratio C *

1. Define \({{{{{{{\boldsymbol{\theta }}}}}}}}={\left({\theta }_{1},{\theta }_{2},...,{\theta }_{N}\right)}^{{{\mbox{T}}}}\) , the update rate λ i  = exp( θ i )

2. Initialise θ  =  0 , learning rate ϵ  = 1, decay rate ρ  = 0.9, constant δ opt  = 10 −6 , squared gradients r  =  0

3. \({k}_{i}\leftarrow {\sum }_{j}{E}_{(i,j)},{p}_{ij}\leftarrow {E}_{(i,j)}/{k}_{i},{p}_{ij}^{(n)}\leftarrow {\sum }_{k}{p}_{ik}^{(n-1)}{p}_{kj}\) for n  = 2, 3 and any i ,  j

4. Compute \(\frac{\partial {C}^{*}}{\partial {\eta }_{jk}}\) for all j ,  k according to equation ( 1 )

5. while \(\frac{1}{N}{\sum }_{i}| \Delta {\theta }_{i}| > 1{0}^{-6}\)

6.       \({\lambda }_{i}\leftarrow \exp ({\theta }_{i})\) for all i

7.      Compute η i j ( i  ≠  j ) by solving the linear system in equation ( 7 )

8.       η i i  ← 0 for all i

9.       \({C}^{*}\leftarrow \frac{{\sum }_{i,j}{k}_{i}{p}_{ij}^{(2)}{\eta }_{ij}}{{\sum }_{i,j}{k}_{i}{p}_{ij}^{(3)}{\eta }_{ij}-{\sum }_{i,j}{k}_{i}{p}_{ij}{\eta }_{ij}}\) according to equation ( 1 )

10.      for i  ← 1 to N

11.            Take the derivative with respect to λ i on both sides of equation ( 7 )

12.            Compute \(\frac{\partial {\eta }_{jk}}{\partial {\lambda }_{i}}\) ( j  ≠  k ) by solving the system of N ( N  − 1)/2 linear equations

13.             \(\frac{\partial {\eta }_{jj}}{\partial {\lambda }_{i}}\leftarrow 0\) for all j

14.             \(\frac{\partial {\lambda }_{i}}{\partial {\theta }_{i}}\leftarrow \exp ({\theta }_{i})\)

15.             \(\frac{\partial {C}^{*}}{\partial {\theta }_{i}}\leftarrow {\sum }_{j,k}\frac{\partial {C}^{*}}{\partial {\eta }_{jk}}\frac{\partial {\eta }_{jk}}{\partial {\lambda }_{i}}\frac{\partial {\lambda }_{i}}{\partial {\theta }_{i}}\)

16.      end for

17.      \({{{{{{{\boldsymbol{g}}}}}}}}\leftarrow {\left(\frac{\partial {C}^{*}}{\partial {\theta }_{1}},\frac{\partial {C}^{*}}{\partial {\theta }_{2}},...,\frac{\partial {C}^{*}}{\partial {\theta }_{N}}\right)}^{{{\mbox{T}}}}\)

18.      r  ←  ρ r  + (1 −  ρ ) g   ⊙   g

19.      \({{{{{{{\boldsymbol{\theta }}}}}}}}\leftarrow {{{{{{{\boldsymbol{\theta }}}}}}}}-\frac{\epsilon }{\sqrt{{\delta }_{{{{{{{{\rm{opt}}}}}}}}}+{{{{{{{\boldsymbol{r}}}}}}}}}}\odot {{{{{{{\boldsymbol{g}}}}}}}}\)

20. end while

21. return λ i ,  C *

Our findings reconcile the past conflicting results on how heterogeneous networks affect the evolution of cooperation. Studies that initialise evolutionary game dynamics with an equal number of cooperators and defectors have found that scale-free networks actually outperform homogeneous networks in promoting the evolution of cooperation, as measured by the average fraction of cooperators 6 . But from the perspective of fixation probability, heterogeneous structures impose a higher benefit-to-cost threshold for a single cooperator to take over a population of defectors, at least when all update rates are identical 4 , 5 , 31 . This predicts that heterogeneous network structures, despite their ubiquity in physical and social systems, tend to hinder the emergence of collective behaviour. By relaxing this assumption and allowing nodes to update their strategies at non-identical rates, we have shown that scale-free networks can in fact facilitate the fixation of cooperation. As such, degree-heterogeneous networks orchestrated by personalised update rates can be unambiguously conducive to cooperation, provided they are doubly heterogeneous—that is, also heterogeneous in update rate. Taken together, we argue that personalised interaction dynamics and network structure combine to shape the collective dynamics.

From the perspective of microscopic mechanism, we unveil that different update rules render the conflict results. Regarding the frequency of cooperators, previous canonical framework and update rule naturally lead to infrequent strategy switching (Supplementary Note  6) 6 , 33 , 34 . This facilitates the formation of cooperative clusters and leads to a high fraction of cooperators on heterogeneous networks. Previous findings are consistent with the underlying microscopic mechanism in our study, namely infrequent updates of hubs facilitate the emergence of cooperation. Indeed, by applying the canonical death-birth update with identical rates in the framework analysing the frequency of cooperators 6 , 33 , 34 , we find that heterogeneous networks impede the average frequency of cooperators compared to homogeneous scenarios (Supplementary Fig.  13) .

Furthermore, we compare our results with experimental studies on cooperation in heterogeneous networks. Consistent with our theoretical findings, there is an insightful experimental study also reporting that heterogeneous networks do not promote cooperation in prisoner’s dilemmas 55 . In this behavioural experiment, a player’s decisions to cooperate or defect are relevant to the level of cooperation in their neighbourhoods, which renders the network irrelevant. Therefore, the main difference between this experimental finding and our study lies in the update rules. Specifically, players are more likely to imitate the strategy from neighbours with higher payoffs in our theoretical framework. To further uncover the behavioural dynamics from the perspective of fixation probability, a promising future application involves the design of human behavioural experiments starting from a single cooperator and ending with full cooperation or defection. Comparing the individual behavioural mode in experiments from these two perspectives will facilitate the understanding of the emergence of cooperation in realistic scenarios.

A natural extension of our findings is exploring the scenario with multiple strategies 56 , 57 , 58 . In this way, the diverse strategy update rhythms may couple multiple strategies with complex dynamics. In addition, our findings may contribute to the study of network formation, elucidating the factors influencing group formation, such as individuals’ propensity to establish connections with those who share similar rhythms. Specifically, discovering the scenarios wherein individuals with similar update rates are allowed to construct a group may provide valuable information regarding the optimal network configuration in the context of heterogeneity.

One promising direction for future research lies in evolutionary dynamics on temporal networks. Time-varying network structure is a recurring theme in social systems, encoding not only who interacts with whom but with when (and how often) these interactions happen 59 . It was recently discovered that temporal networks generally enhance the evolution of cooperation relative to comparable static networks 12 , yet the practical scenarios easily trigger the heterogeneous time rhythm of strategy updating. In real temporal networks, a node’s degree may vary drastically even over short time periods 47 , 48 , 60 . This—in tandem with other temporal effects such as burstiness and multi-frequency interactions 47 , 61 —may lead to more exotic evolutionary dynamics. By regarding a temporal network as a sequence of static snapshots, our theory might be adopted to further tailor individuals’ update rates in temporal evolutionary game dynamics.

Evolutionary process

In each round of the game, individuals interact with their neighbours and accumulate the payoffs accordingly. The payoff matrix of the game is given by

The state of network at any given time can be encoded by a binary vector x   ∈  {0, 1} N , where x i  = 1 denotes that the player i chooses strategy C, otherwise x i  = 0 indicates strategy D. Using this representation of the network state x ,  i ’s average payoff is f i ( x ) = −  c x i  +  b ∑ j p i j x j , where p i j  =  e i j / k i indicates the probability of a single step random walk from i to j on the network. For a node i with update rate λ i , the probability to be chosen for a strategy update is λ i /Λ, where Λ = ∑ i λ i defines the total rate of update events. It follows that at the end of each round, the probability for a player j to transmit its strategy to i is \({r}_{ji}({{{{{{{\bf{x}}}}}}}})=\frac{{\lambda }_{i}}{\Lambda }\frac{{e}_{ij}{F}_{j}({{{{{{{\bf{x}}}}}}}})}{{\sum }_{l}{e}_{il}{F}_{l}({{{{{{{\bf{x}}}}}}}})}\) , where F j ( x ) = 1 +  δ f j ( x ) indicates the fitness of individual j . Note that the fixation probability does not change when the rate of strategy updates for each individual is identical since the normalised update rates are the same.

Fixation probability

As shown in the Supplementary Note  1 , the fixation probability of cooperation is derived by a first-order expression as the neutral fixation probability (1/ N ) plus a correction term due to weak selection, namely

where \(\widehat{\Delta }({{{{{{{\bf{x}}}}}}}})\) denotes the reproductive-value-weighted frequency change of cooperation, which is given by

Here \({\left\langle \varphi \right\rangle }_{{{{{{{{\rm{u}}}}}}}}}^{\circ }\) indicates the summation of the expectation of φ with  φ ( 1 )= φ ( 0 )=0 under neutral drift through time step t  = 0 to infinity, namely \({\langle \varphi ({{{{{{{\bf{x}}}}}}}})\rangle }_{{{{{{{{\rm{u}}}}}}}}}^{\circ }=\mathop{\sum }\nolimits_{t=0}^{\infty }{\sum }_{{{{{{{{\bf{x}}}}}}}}\in {\{0,1\}}^{N}}{{\mathbb{P}}}_{{{{{{{{\rm{u}}}}}}}}}^{\circ }\left[{{{{{{{\bf{X}}}}}}}}(t)={{{{{{{\bf{x}}}}}}}}\right]\varphi ({{{{{{{\bf{x}}}}}}}})\) , where \({{\mathbb{P}}}_{{{{{{{{\rm{u}}}}}}}}}^{\circ }\left[{{{{{{{\bf{X}}}}}}}}(t)={{{{{{{\bf{x}}}}}}}}\right]\) indicates the neutral probability of the system reaching state x at time step t starting from the initial state with a single uniformly selected cooperator in population with N  − 1 defectors. Combining equations ( 5 ) and ( 6 ), the fixation probability can be expressed as

where \({\eta }_{ij}={\left\langle \widehat{x}-{x}_{i}{x}_{j}\right\rangle }_{{{{{{{{\rm{u}}}}}}}}}^{\circ }\) , and \(\hat{x}={\sum }_{i}{\pi }_{i}{x}_{i}\) represents the reproductive-value-weighted frequency of cooperators, where π i is the reproductive value 62 , 63 , 64 uniquely solved by Supplementary equation  (2) , quantifying the expected contribution of site i to the future gene pool under neutral drift. Here η i j satisfies the recurrence relation of

By letting ρ C  > 1/ N , we obtain C * shown in equation ( 1 ).

Calculation of the critical ratio C *

We first define \({\eta }^{(n)}={\sum }_{i,j}{k}_{i}{p}_{ij}^{(n)}{\eta }_{ij}/K\) , where K  = ∑ i k i is the summation of all nodes’ degrees, then equation ( 1 ) can be rewritten as

From the recurrence relation of η i j in equation ( 7 ), we further derive the recurrence relation of η ( n ) with

where \({\widetilde{\eta }}^{(n+1)}={\sum }_{i,j,l}\frac{{k}_{i}}{K}{p}_{ij}^{(n)}\frac{2{\lambda }_{j}}{{\lambda }_{i}+{\lambda }_{j}}{p}_{jl}{\eta }_{il}\) and \({\eta }_{ii}^{+}=\frac{\Lambda }{2N{\lambda }_{i}}+{\sum }_{l}{p}_{il}{\eta }_{il}\) .

By defining the difference \({\Delta }_{{\widetilde{\eta }}^{(n)}}:={\widetilde{\eta }}^{(n)}-{\eta }^{(n)}\) and using the recurrence relation of equation ( 8 ), we obtain the calculation of C * shown in equation ( 3 ) with mean-field approximation, with \({\Delta }_{{\widetilde{\eta }}_{n}}=-{\Delta }_{{\widetilde{\eta }}^{(2)}}+\frac{{K}^{2}}{{\sum }_{i}{k}_{i}^{2}}{\Delta }_{{\widetilde{\eta }}^{(\infty )}}\) and \({\Delta }_{{\widetilde{\eta }}_{d}}=-{\Delta }_{{\widetilde{\eta }}^{(2)}}-{\Delta }_{{\widetilde{\eta }}^{(3)}}+\frac{KN}{{\sum }_{i}{k}_{i}^{2}}{\Delta }_{{\widetilde{\eta }}^{(\infty )}}\) for simplification, where \({\Delta }_{{\lambda }^{(1)}}={\sum }_{i}\frac{{k}_{i}}{2K}\left(1-\frac{\Lambda }{N{\lambda }_{i}} \right)+{\sum }_{i,j}\frac{{k}_{i}}{2K}{p}_{ij}\left(1-\frac{2\Lambda }{N({\lambda }_{i}+{\lambda }_{j})}\right)\) and \({\Delta }_{{\lambda }^{(2)}}={\sum }_{i,j}\frac{{k}_{i}}{2K}({p}_{ij}+{p}_{ij}^{(2)})(1-\frac{2\Lambda }{N({\lambda }_{i}+{\lambda }_{j})})\) . According to Supplementary Note  3 , we further have \({\Delta }_{{\widetilde{\eta }}^{(2)}}\approx N{\Delta }_{{\widetilde{\eta }}^{(\infty )}}/\langle k\rangle\) and \({\Delta }_{{\widetilde{\eta }}^{(3)}}\approx N{\Delta }_{{\widetilde{\eta }}^{(\infty )}}/{\langle k\rangle }^{2}\) for large networks, and hence C * shown in equation ( 4 ) follows immediately.

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

Source data are provided as a Source Data file. Data of empirical networks analysed in Fig.  6 b are publicly available and can be found in the corresponding references 51 , 52 .  Source data are provided with this paper.

Code availability

The codes are written using MathWorks MATLAB R2021a and Python 3.8.5. All source codes related to the work can be found at 69 https://github.com/yaomeng1/PersonalizedStrategyUpdates .

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Acknowledgements

Y.M. and A.L. are supported by National Key Research and Development Program of China (2022YFA1008400), National Natural Science Foundation of China (62173004), Beijing Nova Program (Z211100002121105) and SMP-IDATA Chenxing Youth Fund. Y.-Y.L. is supported by National Institutes of Health (R01AI141529, R01HD093761, RF1AG067744, UH3OD023268, U19AI095219, and U01HL089856).

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Yao Meng & Aming Li

Department of Physics, Toronto Metropolitan University, Toronto, ON, M5B 2K3, Canada

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Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, 02115, USA

Yang-Yu Liu

Center for Artificial Intelligence and Modeling, The Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Champaign, IL, 61801, USA

Center for Multi-Agent Research, Institute for Artificial Intelligence, Peking University, Beijing, 100871, China

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Y.M. and A.L. conceived, designed, and performed the research. All authors analysed the results. Y.M. performed mathematical calculations and numerical simulations under the direction of A.L. A.L., S.P.C. and Y.M. wrote the manuscript, and Y.-Y.L. edited the manuscript.

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Correspondence to Aming Li .

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• Research article
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• Published: 28 July 2014

Utilising a collective case study system theory mixed methods approach: a rural health example

• Robyn Adams 1 ,
• Anne Jones 1 ,
• Sophie Lefmann 2 &
• Lorraine Sheppard 1  

BMC Medical Research Methodology volume  14 , Article number:  94 ( 2014 ) Cite this article

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Insight into local health service provision in rural communities is limited in the literature. The dominant workforce focus in the rural health literature, while revealing issues of shortage of maldistribution, does not describe service provision in rural towns. Similarly aggregation of data tends to render local health service provision virtually invisible. This paper describes a methodology to explore specific aspects of rural health service provision with an initial focus on understanding rurality as it pertains to rural physiotherapy service provision.

A system theory-case study heuristic combined with a sequential mixed methods approach to provide a framework for both quantitative and qualitative exploration across sites. Stakeholder perspectives were obtained through surveys and in depth interviews. The investigation site was a large area of one Australian state with a mix of rural, regional and remote communities.

39 surveys were received from 11 locations within the investigation site and 19 in depth interviews were conducted. Stakeholder perspectives of rurality and workforce numbers informed the development of six case types relevant to the exploration of rural physiotherapy service provision. Participant perspective of rurality often differed with the geographical classification of their location. The numbers of onsite colleagues and local access to health services contributed to participant perceptions of rurality.

Conclusions

The complexity of understanding the concept of rurality was revealed by interview participants when providing their perspectives about rural physiotherapy service provision. Dual measures, such as rurality and workforce numbers, provide more relevant differentiation of sites to explore specific services, such rural physiotherapy service provision, than single measure of rurality as defined by geographic classification. The system theory-case study heuristic supports both qualitative and quantitative exploration in rural health services research.

Peer Review reports

Aggregation of health service and workforce data can render local rural health service issues virtually invisible. As data is collated from local, regional, state and national data sets, visibility of local service availability and accessibility diminish with each level of data collation. Obtaining insight into local health service provision beyond the data requires a different approach: a framework that can provide insight into service delivery and variability in a way existing statistical data does not. The aim of this paper is to describe a methodology to explore specific aspects of rural health service provision with an initial focus on understanding rurality as it pertains to rural physiotherapy service provision. There is little identified literature which describes decision making in rural physiotherapy service provision. No known study has identified influencing factors and what processes are involved in understanding what physiotherapy services to provide in rural locations. Thus there was a need to identify what methodology to use to investigate this topic.

Defining place

The concept of relational place has been suggested as useful for exploration of the specifics of rural communities and the impact of context [ 1 ] . This concept of place is informed by the relational understanding of space and place advocated by Cummins et al. [ 2 ] and ‘the event of place’ referred to by Massey [ 3 ]. The relational view of place includes elements such as nodes of networks, separated by social relational distance with populations of individuals who are mobile both daily and over their life course [ 2 ]. Definitions of the area of the ‘place’ are relatively fluid, recognising dynamic characteristics of place such as ‘declining’ or ‘advancing’ in contrast to conventional characteristics such as ‘deprived’ or ‘affluent’, which are fixed at points in time [ 2 ].

Distinguishing attributes of cultural divisions, services and infrastructure is important in understanding health service provision. The conventional view of place is one of ‘culturally neutral territorial division, infrastructure and services’ where services are described ‘in terms of fixed locations often providing for territorial jurisdiction and distance decay models’ [ 2 ], p. 1827. This contrasts with the relational view of place which sees ‘territorial divisions, services and infrastructure imbued with social power relations and cultural meaning’ [ 2 ], p. 1827. The conventional view of place as spaces with fixed geographical boundaries and services described in terms of fixed locations [ 2 ] is different to the relational view of ‘nodes of networks’; ‘constellations of connections’ [ 3 ] and complex circuitry with a multiplicity of linkages and feedback loops [ 4 ]. Conceptual representation of conventional and relational space is provided Figure  1 . Thus when exploring rural health service provision an understanding of place and the definition used to identify place will impact on the results of the study. Although a health region has defined boundaries seen in the conventional view of place, it is the relational view of place which shows the interactions between and across boundaries which really matches rural health service provision. The multiple linkages and complex nature of health services influences the methodological approach to researching rural health service provision and decision making.

Conceptual representation of conventional and relational place.

Mixed methods

Combining qualitative and quantitative methods provides possibilities for health researchers to grapple with the complexity of health [ 5 ], and the factors that influence both health care and health service provision. A mixed methods approach allows quantitative data obtained from surveys and health service data to be combined with qualitative data to better inform decisions about health service delivery. A qualitative paradigm supports exploration of issues and factors at local, state and national levels that influence local of health service provision. Obtaining stakeholder perspectives on specific aspects of a health service provides insight into local health service provision beyond the quantitative data. Approaches used within qualitative research enable participants to reveal their thoughts and perceptions within their context [ 6 ]. This is highly relevant to health service research because it supports exploration of the perspectives of multiple stakeholders across different geographical settings and different sized and types of services. Variability and diversity are characteristic of rural Australia [ 7 ], and combine with the unique demography of rural and remote Australia as key determinants of health problems and health service needs [ 8 ]. Thus, a robust methodological approach should consider variability and diversity of different sites, to be consistent with the dynamic characteristics of place.

Adopting a sequential mixed method approach provides a framework for health researchers to investigate an issue of interest in complex organisations by providing structure for obtaining data from multiple sources. A preliminary quantitative component, such as a survey, can precede and guide the main qualitative data collection by informing purposive sampling and establishing preliminary results for further in-depth exploration [ 9 ]. Use of an initial survey, for example, allows the researcher to obtain the perspectives of a broader range of stakeholders than may be feasible if only a qualitative approach is adopted. By analysing the data from the quantitative component groups of interest can be identified. Use of stratified purposive sampling then permits the exploration of ideas by these groups [ 10 ] in the qualitative component. These groups may include service providers, their colleagues, managers, key decision-makers or consumers. This supports a key intent of sampling within qualitative research, which is the selection of information rich cases [ 11 ]. The perspectives of individuals enables the researcher to look for complexity of views and also to address processes of interaction among individuals [ 12 ]. Researchers can focus on the specific context in which people live and work [ 12 ] which is important when seeking to understand the setting in which health services are delivered.

Case study design supports the use of multiple data sources. It is appropriate where the research aim is to explore contextual or complex multivariate conditions and not just isolated variables [ 13 ]. An instrumental case study approach the issue or factor is the focus of the study rather than the case [ 14 ]. Organisational complexity and contextual factors such rurality and service settings are important factors in health service delivery. Adopting an instrumental case study approach is suitable therefore as it allows a focus on the issue of interest across sites. Stake refers to the study of more than one case as collective case studies, each of which is an instrumental study linked by coordination between individual studies [ 14 ]. Collective case study design [ 14 ] provides a structure to gain insight into the issue of interest across settings as it allows comparison within and between cases [ 15 ]. Thus the use of instrumental collective case studies is useful for identifying and studying factors that affect service level decision making in rural health.

• Systems theory

A systems-focused approach is recommended to articulate interdependent components that contribute to or compromise the effectiveness of health care interventions or programs. It provides insight into the questions of ‘why’ , ‘how’ and the ‘what’ of contexts [ 16 ]. ‘The parts do not have to be working well, the purpose may be irrational, but it is a system none the less’ [ 14 ], p. 2. The boundary of a system need not correspond with recognised departmental, institutional or other physical boundaries [ 11 ]. The exchange of inputs and outputs across a boundary indicate boundary permeability. An interaction with the environment is characteristic of systems generally and more specifically of open systems [ 17 , 18 ]. Although boundaries may be clearly defined, they are subject to interaction and influences external to the system. Within an interpretive paradigm it is “acknowledged that a ‘system’ is not a concrete thing but an abstract concept that constitutes particular relationships that can be actualised in a number of ways” [ 18 ], p. 128. Perceiving one aspect or specific issue as a system within a more broadly conceived organisation can generate both a new representation of the issue and variety in the way the issue is thought about [ 11 ]. Choosing to think of a health care organisation as if it were a system is a useful construct and one that is not new in its application to health and health care [ 19 ]. Studies of emergency department physiotherapy [ 20 ] and health promoting environments in a university [ 21 ] for example, have described sets of interrelated elements which, when viewed together, form a ‘whole’. What is new is applying it to service level decision making in the context of rural health.

Combining case study and systems theory

The constructs within the relational view of place suggest the relevance of both case study and systems theory. Both methodologies have been used in health and health care research [ 21 – 24 ]. Combining systems theory and case study methodology offers the opportunity for in-depth exploration as well as comparative analysis between cases in the context of the system [ 20 ]. The combination provides a way of conceptualising complex issues for exploration, and as such has been considered an heuristic model [ 25 ]. This model provides a structure to explore local health service provision whilst recognising the flows and linkages that occur within a relational concept of place. The systems theory-case study heuristic, as part of a framework for this study, acknowledges that a case is also a ‘bounded system’ [ 14 ], p. 2. This notion assists by drawing attention to it as an object rather than a process.

Organisational issues, including how and why health care services are provided, requires recognition of a range of influencing factors. Also important is an understanding of the impact of external factors, such as national and state health policies, on health services provided by an organisation.

Adoption of both a collective instrumental case study design and a systems approach supports the focus on the issue of interest and holistic exploration [ 24 ]. In this study of rural physiotherapy service provision the defined system may include tangible and intangible elements within a broader organisation that are connected to form a system. The application of both case study and a system theory approach supports consideration of a single issue across multiple sites and contextual variations of place. Each of these individual cases exists within larger systems with interactions between cases and is influenced beyond both the boundaries of the single case and the network boundaries (Figure  2 ).

Demonstration of cases within a health system.

The systems theory-case study heuristic supports the use of both qualitative and quantitative approaches and a priori–sequence model [ 5 ] guides the practical integration of both approaches. As part of a larger study seeking to understand how decisions are made about rural physiotherapy service provision, important first steps were to understand participant’s perspectives of rurality and to develop cases for exploration of decision making about physiotherapy service provision.

Context of rurality

Due to the expressed limitations of the application of geographic classifications to health care [ 26 ], the researchers focussed on Participant Perspectives of Rurality(PPR) which were compared with geographical classifications. Many definitions and classifications are used to describe or differentiate rural, regional and remote settings [ 27 , 28 ]. The Australian Standard Geographical Classification Remoteness Areas [ASGC- RA] is recommended by the Australian Institute of Health and Welfare (AIHW) [ 29 ]. Other Australian classifications include Access/Remoteness Index for Australia [ARIA] and Rural, Remote & Metropolitan Areas Classification [RRMA]. As classifications are based on factors such as distance to service centres, population size or density, they may not take into account other contextual factors or accessibility of specific health services such as physiotherapy. Different definitions can lead to different classifications and, in terms of program funding for instance, may alter a community or individual’s entitlement eligibility. The notion of developing a suite of measures [ 26 , 30 ] is important in the exploration of specific issues of health and health service provision in rural settings. The index of access to primary care is one recently described measure [ 30 ]. The development of case sites using PPR combined with key aspects of the research question highlights how utilisation of the described methodological approach may assist in exploring local health service provision in rural communities. The research aims can then be explored within and between identified cases relevant to the research. This is believed to be the first study to utilise this methodical approach to define rurality or relational place.

Research method

The investigation site was a large area of one Australian state with a mix of rural, regional and remote communities with a range of health services of varying sizes. The scope of the study was bounded by the defined geographic area of a rural health service network. This area offered the opportunity to explore rural physiotherapy services across many health service settings. Identification of multiple sites enabled development of rural physiotherapy cases for exploring rural physiotherapy service provision. Ethics approval was obtained from the Human Research Ethics Committee of both James Cook University (approval number H3799) and the health service of the study. Data collection occurred from January to September 2012. Site specific approval was obtained for 25 health facilities employing physiotherapists within the investigation site.

Public sector physiotherapy service provision formed the primary focus of this research. The researchers’ experience as rural physiotherapists and reports of a greater reliance on the public sector for the provision of allied health services, including physiotherapy, in rural and remote regions of Australia [ 31 ] informed this focus. Private physiotherapy services, while limited in some communities, deliver significant services and formed a second focus of this investigation.

A preliminary quantitative component, a survey of public sector physiotherapists in the selected investigation area, preceded and guided the main qualitative data collection by informing purposive sampling and establishing preliminary results for further in-depth exploration [ 9 ]. Public physiotherapists were invited to participate in the initial phase of the research through local professional networks. Senior physiotherapists in the investigation site provided key physiotherapy contacts in the public sector physiotherapy departments. Surveys were mailed to the key physiotherapy contacts for distribution to colleagues in their facility. Participant information and consent forms were included with the survey for distribution. Physiotherapists were invited to complete a survey describing their setting, service and factors influencing their practice.

Results from the survey assisted in identifying a range of stakeholders willing to participate in the second stage of the study. Stakeholders included physiotherapists, their colleagues, managers, key decision-makers and consumers. The second stage of data collection consisted of stakeholder specific surveys. To obtain input from stakeholders, case site physiotherapists who had agreed to participate in follow up interviews, were asked to distribute questionnaires to the stakeholders at their site, including managers, consumers and team members [ 32 ]. The physiotherapists were able to guide or direct this data collection phase to stakeholders they identified as relevant to the decision-making process. Where present, the private physiotherapists were identified from listings in the Yellow Pages phone book of each case site. As the physiotherapy workforce has become increasingly privatised [ 33 ] it was important to consider the contributions to rural physiotherapy service provision made by private physiotherapists. To allow for possible intersectoral comparison of responses from consumer surveys, outpatient services were prioritised in the public health services. Both public and private physiotherapists were asked to place consumer surveys on relevant reception desks with an information sheet describing the study to allow consumers to elect to participate or not. Written consent was obtained from all participants. All surveys were anonymous unless participants agreed to provide their details for subsequent interviews.

In the final stage of data collection the principal researcher conducted face to face semi-structured interviews with a purposive sample of physiotherapists and key decision-makers. The interview questions reflected both the questions and responses of the survey as the researchers sought to obtain greater insight into the issues raised. The interviews occurred in each case site at a location and time convenient to each participant. Written informed consent was gained prior to the interview. All interview participants were informed that they would not be identifiable and that confidentiality would be maintained. This staged approach to data collection is consistent with the funnel analogy described by Bogdan and Biklen [ 34 ]. Interviews were ceased when data saturation occurred.

Data analysis

Initial data analysis of the survey data was undertaken using Microsoft Excel spread sheets. Responses to open ended questions informed the development of initial themes and areas for further exploration in interviews. Manual and electronic recording of data through the use of NVivo version 10 were used to organise the qualitative data. Each interview was recorded and transcribed verbatim and entered into NVivo. Full interview transcripts and a summary developed by the researcher were provided to interview participants for their review and comment. An iterative approach was used to guide the qualitative data analysis [ 35 ]. The principal researcher completed the initial analysis with co-researchers double coding one third of the interviews to add to the depth of analysis. Thematic analysis was undertaken to develop tentative themes and concepts to develop codes, which were then used to frame and account for the remaining data [ 35 ].

Research rigour

The research design included data collection from multiple sources to enable triangulation of data and constant comparison. Interviews were audio taped and transcribed verbatim with full transcripts and summaries provided to each interview participant for verification and additional comments. One third of the interviews (7/19) were coded by a second coder to verify themes. An auditable trail of evidence was maintained throughout the conduct of the research to further add to the credibility of the findings [ 15 , 35 , 36 ].

Physiotherapy surveys were received from 11 of the 25 (44%) public sector facilities identified as providing physiotherapy services in the investigation area. The sixteen completed surveys received from the 11 sites represented a 29.4% response rate as 54 physiotherapy surveys were distributed. From the surveys a matrix was developed to identify cases for purposeful sampling [ 35 ]. The surveys identified two key factors relevant to rural physiotherapy service provision: rurality and the number of physiotherapists. In view of the expressed limitations of geographic classification systems [ 30 ] participant perspectives of rurality (rural, regional or remote) were used to inform cases. The number of co-located colleagues was the second factor identified as a potential differentiating factor of rural physiotherapy service provision. This is consistent with the literature in which workforce and position shortages are recognised as characteristics of rural physiotherapy [ 37 ].

An example of an stratified purposive sampling [ 6 ], the proposed matrix had a potential total of 12 cells although many may not be applicable (Table  1 ). A regional setting with only a part time physiotherapist (less than one Full Time Equivalent (FTE)) is one such example. In addition to informing case site selection, participant perspectives of rurality were compared to current rural classification systems to identify commonalities and differences. Interview responses of participants at identified case sites then further contributed to concepts of rurality relevant to rural physiotherapy service provision.

The initial matrix was revised to reflect stakeholder responses including the larger referral centres and mixed stakeholder responses about the rurality of one location (Table  2 ). Six case types emerging from the physiotherapy responses. A further 23 surveys (five private practitioner, 13 colleague/manager and five consumer) were received from stakeholders at identified case sites. Nineteen interviews were conducted across the sites of the study.

Participant responses highlight the conceptual challenges when describing rurality and defining regional, rural and remote. For example participants who worked in a location with more than ten FTE physiotherapists stated:

“ I suppose regional, yes. I don’t really consider myself to be rural. For me it is, I don’t consider this to be rural just because I can live here and have a city lifestyle without the stress and the traffic and the pollution. I don’t believe I’m living the rural lifestyle. If I had a rural lifestyle I’d have a farm”. [A3]

“ I suppose we’d be regional, I think of myself as rural but I think it’s probably regional”. [D1]

One participant who worked in an area with between four to ten FTE physiotherapists stated that their perception of rurality was to some degree based on patient location.

“And that was the big thing from city versus country physio or rural physio, a lot of my patients travel six hours to see me”. [B4]

Participants also felt that access to services also assisted in defining the rurality of a location. For example a participant from a large country centre noted: “the capacity to access high level services is limited [here] …and so the capacity to access the higher level service I think is one of the things that defines this as remote”. [D4] . This was also reflected in smaller rural locations, adding to the notion of access to services and support as an important consideration in understanding rurality.

“The differences are like in metropolitan – in provincial … we've now got some specialists in most places. Whereas here you're expected to know hands and everything else so at least you’ve got a context. So it’s a video conference with the people for hands in [the capital city] but getting into the video conferences is an issue because that’s in the hold and treat rooms [for mental health patients]”. [A8]

The rurality of the case types reflected the way in which physiotherapists identified the setting in which they practice. Physiotherapy participants described eight of the eleven sites as rural, two as regional and one as remote-rural (Table  2 ). Fulltime equivalent (FTE) physiotherapist numbers ranged from 0.4 FTE (i.e. one physiotherapist working two days per week) to 14 FTE across the sites of this study. Six case types emerged from the responses from the public sector physiotherapists. Physiotherapist perception of rurality (PPR) in sites with four to ten physiotherapists was an important factor in making distinctions between sites, whereas the number of FTE physiotherapists was a greater differentiator in rural and regional sites. Fulltime equivalent categories could be further differentiated, but for the purpose of this study four categories were used.

Fewer case types would have emerged if a single measure of rurality was the only differentiating factor. Three case types would emerge if PPR, RRMA or ARIA were used as a single measure and only two case types if ASGC was to be used as the only differentiating factor. Comparison of rurality for each site using remoteness classifications revealed a variable picture (Table  3 ). The differentiated case types that emerged from the dual measures of PPR and FTE informed the selection of cases for this study.

The complexity of understanding the concept of rurality was revealed by interview participants when discussing perceptions of rurality relevant to their setting. Issues around the concept of rurality include the following:

 Is it the practitioner or the setting that defines rural health;

 is it about distance from a centre or a service provider;

 is it service size including the number of providers or a sole part time worker;

 is it about workforce availability;

 is it about the type of work undertaken such as specialist or generalist skills;

 is it about support available to the health professional;

 is it being visible and accountable to the community;

 is it about local knowledge or

 is it about distance from decision-makers?

Questions such as these reveal the convolutions of rurality and the variability often reported in the literature around rural health service provision [ 31 , 38 , 39 ]. Such variation further reinforces the need for the development of measures that can reflect this complexity and variation. Use of only a geographical classification of rurality is not sufficient to be able to distinguish between sites and thus cases when undertaking rural health service research. Dual measures, such as rurality and workforce numbers, provide more relevant differentiation than a single measure of rurality as defined by geographic classification. Similarly the continued use of catch-all term such as ‘rural health’ can limit the understanding of the similarities and differences found across locations [ 40 ]. Without understanding the associations between the specifics and context of each place, the attributes within the population and individual health services being delivered there is a large gap regarding the understanding of the specifics of health services in local rural communities.

This study adds to the literature describing limitations in the application of geographical classifications for differentiating rural health services. This study revealed that participant perspective of rurality often differed with the geographical classification of their location. For example, one participant expressed a sense of isolation more consistent with remote areas than that of a rural location.

“ in Katherine and things like that, in what's considered remote area and yet [here] I'm the only Allied Health therapist…so I'm actually probably.... professionally more isolated than a lot of these people …at least have teams in more remote areas”. [A8]

Not only does the health professional feel isolated but access to services would be likely to be a key issue for residents in this location. This is consistent with the work of McGrail and Humphreys [ 30 ] which suggests that access to health services is a function of several factors including availability, proximity, health needs and mobility. The effect of distance on the accessibility to health care services has been identified as a key factor differentiating rural and remote from metropolitan health care [ 38 ]. Population size and geographical location then influence the mode and form of service delivery with socio-economic and geographic inequities influencing access to health care [ 38 ]. Implications for provision of health care, particularly primary health care have been discussed in the literature [ 38 ] however implications for provision of specific health services such as physiotherapy in rural settings are less evident.

Variability and diversity are characteristic of rural Australia [ 7 ], and combine with the unique demography of rural and remote Australia as key determinants of health problems and health service needs [ 8 ]. Adopting an approach that enables insight into variability and diversity of different sites is consistent with the dynamic characteristics of place. Health service provision in rural areas is increasingly influenced by networks, connections and linkages that may occur within defined boundaries of a local health system, but are increasingly Examples that emerged in this study include the impact on smaller rural physiotherapy service providers when new regional services are established and how a national decision such as activity based funding influences the health system and service delivery at all levels.

"recently I have told by [the regional centre] that I need to do all these lymphoedema patients and this is the pre assessment in terms of the all the whole population of anyone having breast cancer… to see them all – measure them all up before surgery… I said “I can’t do that” but that’s what I would be expected to do so, that is a direction coming from [the regional centre who are] saying we can’t do all of these". [A5]

"they just send them anywhere they can to get them out of [the regional hospital]…they have to get them out of there… you know within four days....[because of] funding, pressure, bed block … pressure to get them out, get them going, send them home". [A8]

"[Length of stay]…it’s a huge measure and that, with activity based funding, they are going to be huge drivers.... Bed block, length of stay, money, will always stick up in their head and that is the thing that they will see as important … [the national health reform], it sort of sets the big agenda that will trickle down to us in other ways as in if they’ve got a project that they want that has a bucket of money, that will influence some decisions about what services are provided with that bucket of money and it just depends whether we’re in the mix or up in their face or not. Yes, it sets that whole funding agenda that’s going to have a major influence". [A1]

These influences affect health service provision and can be lost when investigating service level decision making in rural health. The combination of missed methods utilising a survey followed by a collective case study and systems theory approach has demonstrated an appropriate framework to identify the issues surrounding rurality. Without further understanding of rurality, investigation into rural health will be lacking. Utilisation of this mixed methods approach could be applied to other rural health issues and may help to add to the research around health service delivery.

Limitations

The research framework described was applied to an investigation of physiotherapy service provision in one area within Australia which had a mixture of remote, rural and regional centres. The framework and results may not be applicable across professions or to other areas with a different mixture of services or locations. Participant perception of rurality and public sector staffing numbers, while relevant to this study to define cases, may not be applicable to other studies.

The framework described provides a structure to gain insight into local health service provision in a way existing statistical data does not. The combination of the systems theory-case study heuristic and a sequential mixed methods approach supported a qualitative exploration of issues identified through initial surveys. Obtaining participant perspectives of issues of interest, such as rurality and physiotherapy service provision, provides local detail often not available or visible. The concept of relational place aligns well to both systems theory and case study to aid exploration of the specifics of rural communities and the impact of context [ 1 ] . Concepts such as rurality and place then inform exploration of a health care issue of interest within and between rural communities. Defining key aspects of the research, such as participant perspectives of rurality and physiotherapy Full Time Equivalent, assist to define cases in which to explore the issue of interest. Adopting a systems approach then allows description of interrelated elements in each individual case while recognising interaction between cases and within the larger health systems.

Abbreviations

Access/remoteness index for Australia

Australian institute of health and welfare

Australian standard geographical classification remoteness areas

Full time equivalent

Participant perception of rurality

Rural, remote & metropolitan areas classification.

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RA: was involved in concept development, study design, data collection, data analysis and interpretation and drafting of the manuscript. AJ: was involved in study design, data analysis and interpretation and drafting the manuscript. SL: was involved in study design, data analysis and interpretation and drafting the manuscript. LS: was involved in study design, data analysis and interpretation and drafting the manuscript. All authors read and approved the final manuscript.

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Adams, R., Jones, A., Lefmann, S. et al. Utilising a collective case study system theory mixed methods approach: a rural health example. BMC Med Res Methodol 14 , 94 (2014). https://doi.org/10.1186/1471-2288-14-94

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A collective case study of the features of impactful dementia training for care home staff

Claire a. surr.

1 Centre for Dementia Research, School of Health and Community Studies, Leeds Beckett University, Leeds, LS1 3HE UK

Michelle Drury

2 Centre for Applied Dementia Studies, University of Bradford, Bradford, UK

Natasha Burnley

Alison dennison, sarah burden, jan oyebode, associated data.

The datasets generated and/or analysed during the current study are not publicly available but are available from the corresponding author on reasonable request.

Up to 80% of care home residents have dementia. Ensuring this workforce is appropriately trained is of international concern. Research indicates variable impact of training on a range of resident and staff outcomes. Little is still known about the most effective approaches to the design, delivery and implementation of dementia training. This study aimed to investigate the features and contextual factors associated with an effective approach to care home staff training on dementia.

An embedded, collective case study was undertaken in three care home provider organisations who had responded to a national training audit. Data collected included individual or small group interviews with training leads, facilitators, staff attending training, managers, residents and their relatives. Observations of care practice were undertaken using Dementia Care Mapping. Training delivery was observed and training materials audited. A within case analysis of each site, followed by cross case analysis using convergence coding was undertaken.

All sites provided bespoke, tailored training, delivered largely using face-to-face, interactive methods, which staff and managers indicated were valuable and effective. Self-study booklets and on-line learning where were used, were poorly completed and disliked by staff. Training was said to improve empathy, knowledge about the lived experience of dementia and the importance of considering and meeting individual needs. Opportunities to continually reflect on learning and support to implement training in practice were valued and felt to be an essential component of good training. Practice developments as a result of training included improved communication, increased activity, less task-focussed care and increased resident well-being. However, observations indicated positive well-being and engagement was not a consistent experience across all residents in all sites. Barriers to training attendance and implementation were staff time, lack of dedicated training space and challenges in gaining feedback on training and its impact. Facilitators included a supportive organisational ethos and skilled training facilitation.

Conclusions

Effective training is tailored to learners’, delivered face-to-face by an experienced facilitator, is interactive and is embedded within a supportive organisational culture/ethos. Further research is needed on the practical aspects of sustainable and impactful dementia training delivery and implementation in care home settings.

Electronic supplementary material

The online version of this article (10.1186/s12877-019-1186-z) contains supplementary material, which is available to authorized users.

Care homes provide care to 19–38% of people with dementia in Western countries [ 1 , 2 ] and up to 80% of people living in care homes are thought to have dementia [ 2 , 3 ]. In order to be able to deliver high quality person-centred care for this group, care home staff need to be provided with appropriate training that supports them to have the right knowledge, skills and attitudes [ 4 , 5 ]. In England, there have been a range of initiatives, led by government over the last ten years to ensure the health and social care workforce receives appropriate dementia training [ 6 – 11 ]. However, in addition to ensuring the availability of training, there is a need to ensure that training is of high quality to provide the best chance of effecting practice change. A number of systematic reviews have examined research on the effectiveness of dementia training for the care home workforce in relation to a range of outcomes including the general benefits of training [ 12 ], impact on resident functional ability and quality of life [ 13 ], improving staff communication skills [ 14 ] and for supporting complex resident behaviours [ 15 , 16 ]. The studies report variable impact of staff training on these outcomes. Training appears to most consistently support improvement of general care home staff skills [ 12 ], communication [ 14 ] and support for residents in activities of daily living [ 13 ]. However, there are inconsistent findings in relation to the impact of training programmes on resident outcomes such as behaviours (e.g. agitation, anxiety, neuropsychiatric symptoms) [ 13 – 16 ] and quality of life [ 13 ]. The reviews generally conclude that there is limited robust evidence for training efficacy due to methodological weaknesses in study designs and lack of follow-up over time. Where studies have included longer follow-up any positive results observed are generally not sustained. Few reviews consider features of effective training. One systematic review examining the challenges to and strategies for implementation of training in practice [ 5 ] identified the key challenges to include low staff attendance, lack of organizational support, and financial limitations. Therefore, there is limited available evidence on the most effective approaches to the design, delivery and implementation of impactful dementia training in care home settings.

The What Works in dementia education and training? (What Works?) study aimed to investigate the elements of an effective approach to dementia training and education for the health and social care workforce. This was achieved through conducting: 1) a systematic literature review of current evidence (see [ 17 ]); 2) a national audit of health and social care providers, commissioners and training providers on currently available dementia training; 3) a survey of staff who had completed programmes reported in the audit to assess their dementia knowledge, attitudes and confidence; 4) multiple case studies [ 18 ] in health and social care settings (general hospitals n  = 3, mental health/community services n  = 3, social care n = 3, general practitioner practices n  = 1) who responded to the audit and whose training met good practice criteria identified from the literature review. In order to ensure enough data could be collected at each site to provide an in-depth picture [ 19 ], we aimed to recruit three case study sites from each setting type. This was deemed feasible within the project resources and timescales but was sufficiently large to permit cross-case comparison.

The study was underpinned by two theoretical models for the evaluation of training. Richards and DeVries’ [ 20 ] Conceptual Model for Dynamic Evaluation of Learning Activities, explores training design and facilitation processes. Kirkpatrick’s [ 21 , 22 ] four-level model for evaluation of training interventions examines 1) learner reaction to training, 2) extent of learning in terms of knowledge, attitudes and confidence, 3) staff behaviour change, and 4) practice results or outcomes.

This paper reports a collective case study of the three social care case studies, which were all undertaken in care home settings.

The case studies aimed to understand the features and contextual factors associated with good practice regarding the design, delivery and implementation of dementia education and training and its impact on care practices.

The research questions addressed were:

• What models of dementia education and training were sites adopting?
• How did staff perceive the training?
• How did the training impact on staff knowledge, attitudes and practices?
• How did people with dementia and their family members experience care in homes/units where staff had received training?
• What were the specific barriers and facilitators to effective training implementation?

We employed an embedded [ 23 ], collective [ 19 ] case study design.

Case selection

A ‘case’ was defined as a care home provider organisation, which could include a single care home or multiple sites, as long as staff at all sites accessed the same training programmes. Eighteen social care providers in England and Scotland, including fourteen care home providers and four domiciliary care organisations who had responded to the audit were considered for inclusion. They were shortlisted using a positive deviance approach [ 24 ] by researchers blinded to site identity, and then ranked against a set of good practice criteria. These criteria were developed from the outcomes of the literature review [ 17 ]. They included how comprehensively training covered subjects and associated learning outcomes within the national Dementia Training Standards Framework for England [ 25 ] alongside training length and delivery methods (see Additional file  1 for full criteria and shortlisting process).

We had aimed to include at least one domiciliary care site in the three case studies. However, neither of the two sites which achieved high ratings against the good practice criteria were able to participate due to staffing issues affecting key individuals who would have needed to support the research. The three top ranking care home sites that were approached all consented to participate.

Data collection

Consistent with a multiple case study approach [ 18 ], a range of data types were collected at each site (see Table  1 ) including semi-structured interviews with the dementia training lead, training facilitators and home managers and semi-structured individual or focus group interviews with staff who had attended training. Interviews were facilitated using a topic guide but conducted flexibly by the researcher to gain a thorough understanding of individuals’ experiences and views. Topic guides were unique for each participant type e.g. managers, training leads, training facilitators, staff, but contained questions based around the Richards and DeVries and Kirkpatrick Frameworks including organisational culture and processes (e.g. Could you tell me a bit about your organisation’s training strategy and the place of dementia training within this?), training design and delivery (e.g. What aspects have gone well in organisation and delivery and what has proved more tricky?), reactions (e.g. You’ve all taken part in [insert description] dementia training recently. Could I ask your opinions on the training you received?), learning and behaviour (e.g. Thinking about those team members who received [insert name of training here], can you identify any changes in their knowledge, or their competency in relation to dementia?) and outcomes (e.g. Do you think the training programme is having the impact you hoped for on care? Can you give us some examples?). They were audio recorded and transcribed verbatim, with interviews lasting for 30–60 min and focus group discussions around 60-min. The focus group discussions used the same topic guide but also included vignettes that presented a short story of the experiences of a person living with dementia in a care home in written and pictorial format. Focus group participants were asked to identify examples of good and poor practice contained within the vignettes, which helped to explore their knowledge and attitudes towards dementia care. The vignettes were developed by members of the project’s expert by experience group, which was comprised of people living with dementia and their family members.

Summary of data collected and the research questions it addressed

Each site provided copies of the training materials, which were audited using a good practice in training tool developed by the research team [ 26 ], based on the findings of the systematic review [ 17 ]. This includes items such as content and how well it mapped to the Dementia Training Standards Framework, whether it used interactive delivery methods, accuracy and readability of materials, tailoring to audience and training length. Researchers observed training sessions being delivered to staff, recording data using a qualitative observational template developed by the study team, based on the underpinning theoretical models. Short satisfaction cards, including three fixed (How satisfied are you with this service? How well did the staff understand your feelings and needs? How well were staff able to answer your questions about dementia?) and one open-response question (Any other comments about your care either positive or negative?), were given to care home residents with dementia and/or relatives. Respondents were also invited to take part in a telephone or face-to-face interview to discuss their care experiences. Only one resident in one of the sites completed an interview.

Care was observed in at least one unit of each participating site using Dementia Care Mapping (DCM) [ 27 ]. DCM collects data on residents’ experiences of care including behaviour (from 23 possible codes; Behaviour Category Code – BCC), level of mood and engagement (from a six-point scale (− 5, − 3, − 1, + 1, + 3, + 5: Mood and Engagement Value – ME)) and the quality of staff interactions with residents (Personal Enhancers and Personal Detractors). Up to eight hours of observation over both morning and afternoon periods were conducted by study researchers trained in DCM in public areas of the care home. As dementia training had been provided in all case study sites for a number of years prior to the study and was ongoing during data collection, no data was able to be collected before dementia training commenced. Therefore, analysis focussed on whether the outcomes the training aimed to achieve e.g. person-centred care, skilled communication, resident well-being, were present in the care homes.

Consent and ethical issues

Ethical approval for the study was given by the Yorkshire and the Humber – Bradford Leeds NHS Research Ethics Committee [REC Ref 15/YH/0488]. The research team made the initial approach to participate to the individual who completed the audit earlier in the project, and arranged to visit the care home to meet with key staff such as the owner, training lead, facilitators and unit managers. Once formal written organisational consent from senior management was gained, the researcher visited each site again and gained written informed consent from all study participants. Where a resident lacked capacity to give informed consent, advice on their participation was gained from a relative or staff consultee in accordance with Mental Capacity Act [ 28 ] guidance. Adopting consent processes utilised in previous studies that have included general observations of care practices with people with dementia [ 29 ], verbal approval to record anonymised data was gained from residents and staff prior to DCM observation. In keeping with the principles of process consent [ 30 ] researchers assessed ongoing consent throughout. To ensure all individuals within the care home were aware of ongoing observations posters were displayed in prominent positions on the units before and during observation period, containing a photograph of the researcher and giving details about the study and how and with whom to ask questions or raise a concern.

Data analysis

The study team undertook analysis of the full set of data for each case study site individually followed by cross-case analysis. Interview, focus group and training observation data were analysed using the thematic analysis method, template analysis [ 31 , 32 ] using NVivo 11 [ 33 ]. Starting with a priori themes drawn from the underpinning theoretical frameworks [ 20 , 22 ] a coding template was developed that underpinned data analysis across the whole study. This was achieved through CAS, JO, CS, MD, SB and NB undertaking collaborative coding of three initial transcripts (one social care, one acute care and one mental health Trust) and discussion of the identified themes. A further six transcripts (representing the range of service settings) were then coded by CS, MD and NB to refine the template. This final template was then used to code the remaining data.

DCM data were analysed using standard DCM guidelines, including preparing summaries of data at an individual resident and group level. Copies of training materials were reviewed and their content mapped against the learning outcomes contained within the Dementia Core Skills Education and Training Framework [ 25 ]. The audit tool [ 26 ] of good practice in dementia training was used to audit each training programme. The responses to patient and carer satisfaction cards were summarised using descriptive statistics and manual thematic analysis.

Once analysis of each data source for a site was complete, a within case analysis [ 19 ] was conducted. This involved summarising each data source, triangulating across sources, and synthesising into a written ‘story of the case’ [ 34 ]. This was followed by cross-case analysis [ 19 ] across the three sites using convergence coding [ 35 ]. Convergence coding involved creation of a data grid highlighting themes and findings, supporting comparison of areas of agreement, partial agreement and dissonance [ 36 ].

The organisations recruited varied in terms of size and number of units participating in the study (Table  2 ), although all were within provider organisations who owned a small number of care homes (≤7) and were located across England and Scotland. All had an internal training lead/trainer who was responsible for delivery of dementia training across all homes within the organisation. The key themes and issues identified in the analysis are presented by site in Table  3 .

Characteristics of case study sites

Summary of key findings and themes across case study sites

Design and delivery

All sites offered a range of training provision (Table ​ (Table2) 2 ) that was mostly bespoke and developed by the training lead. The majority of training was delivered face-to-face in small groups, with some sites including other delivery methods. In one site, a standardised workbook that covered required dementia training content for Scotland was used. However, the training lead had tailored the delivery method by including additional monthly face-to-face discussion groups where staff could reflect on application of learning, recognising the importance of co-learning.

We thought in order to change practice that it has to be facilitated within the team … all the reflective exercises are about people that they actually care for. Thought it was more real … and group facilitation rather than just giving people the folder with the information. (Training Lead SC040)

In another site, a self-directed workbook was also used but the approach was under review due to both the local Council and the training lead identifying this method was not appropriate, as the training was not being completed.

They are given a booklet but basically left with it . (Dementia Lead SC042)

The training facilitator in one site highlighted how she had removed as much written material as possible from the training, upon recognising that staff did not find it helpful to their learning.

Giving lots of hand-outs was not effective because it was just people getting stressed out because they couldn’t find a hand-out or they had too much information to read to process and they weren’t really focussing on the training (SC076 Training Facilitator)

Dementia training was offered to all staff working in the care homes irrespective of role.

You’re not going to have laundry staff that are experts in dementia because they don’t have to be. It’s not their role. But you still want your workforce to be fit for purpose and have an awareness with the client group they’re working with. (Training Lead SC040)

During training observations it was noted that the training leads in each site delivered content flexibly to meet the needs of the group, for example by tailoring examples they provided to the group participants and their role and asking for and responding to learner’s own practice examples to inform discussion. The trainers recognised the importance of tailoring provision to the needs of the organisation and range of staff attending.

Reaction to training

Staff responses to the training were generally positive across the three sites. During focus groups, interviews and immediately following training staff made comments such as interesting (SC040 Staff Member 026), informative (SC040 Staff Member 025) and t he best training I’ve ever been on (SC042 training observation field note). Key themes related to training reaction included the value of small group, face-to-face learning, a dislike for e-learning and the benefits of using case scenarios.

Overwhelmingly staff identified the importance of face-to-face learning and the ongoing support provided by the sites for staff during and after training.

I find personally I understand things better when it’s in a training setting, er, there is a group of you, when you know, er, giving ideas and all talking together about it rather than a question on a page. (SC042 Staff Member 034)

… having people go home and work on it on their own and then come back into the course just to talk about it. (Staff Member SC040 013)

In the other site the delivery approach had not yet been revised and staff commented on how unhelpful they found the method.

because it is how you respond to a person verbally. You can’t do that out of a book can you? (SC042 Focus Group P1)

On-line modules formed a component of induction in one site and had previously been part of training in another, however this was not viewed favourably by those in leadership positions, who saw it as little more than a tick-box exercise.

You know a monkey could sit and do it. (Unit Manager SC040 020). … ‘cause they can copy and they can say just tick tick, tick, that’s fine (SC076 Training Lead).

Staff also noted they found interactive learning activities and the use of video or other forms of case study scenarios particularly helpful in helping them to apply learning to practice.

Mostly the scenarios … . This scenario thing and it was exactly like, exact same as one of the residents in here. (SC040 Staff Member 013).

Videos have worked well … If you could find a decent video that supports a point that you’re trying to make and you can see it in practice it’s really good because issues that we have … role play is wonderful but it doesn’t really…it’s not an accurate simulation of someone with dementia. (SC076 Training Facilitator)

There was evidence from the interviews, focus groups (including vignette-based discussions) and observations of care practice that a range of learning had taken place. Key themes were gaining empathy and knowledge about the lived experience of dementia, and understanding individual needs. These themes were a consistent outcome of training across all three sites.

I feel I’ve gained a lot of understanding about dementia and how it progresses and you’ve sort of put yourself in their shoes and you think well that could be me some day, so I would hope that whoever’s looking after me would give me the care that I would expect and understand. (SC040 Focus Group P4)

… you just feel as though you need to help them more, whereas before I’d have dismissed them. I won’t say I was awful but I would have, I would have thought: Oh silly old fool or … . Whereas now I think I’ve got much more empathy with them and feeling more towards them. (SC042 Focus Group P1)

The importance of understanding and providing care that was person-centred and met individual residents’ needs was identified as a learning point by staff at two sites.

Staff can step back and say ‘that’s why that person does that. Now we know what to do’. (Staff Member SC040 014)

So you’ve got to individualise when you’re caring. (SC076 Focus Group 3 P2)

One staff member reported finding some content during the session overwhelming and that s/he only took in the information upon,

… reflect[ing] on it when you’re on the floor. (SC040 Staff member 026).

The learning that took place ‘on the job’ was also identified as important by a staff member at another site.

I think for training is good in some ways but to be here is more life, true, real-life, the way it is. For me it can be both but to be here you learn more. (SC042 Focus Group, P2).

[It gives me a chance to] go home and it’s good just to sit, relaxing, writing your scenarios. You know what you’ve to do and what you’ve to say and you get time to think about it. (Staff Member SC040 026)

In another site opportunity to continue reflecting in a supported way outside of formal training was also offered through ‘drop-in’ sessions or provision of additional support materials.

They’ve got you in the back of their minds on you, on their radar to help you with other stuff as well as the Booklet. (SC042 Staff Member 033).

While most staff commented positively about the value of training, some of the more experienced staff in two of the sites indicated that for them there had been little new information covered in training they had attended.

With the Induction Training, there was nothing, nothing added to what I already knew. (SC042 Staff Member 034).

Whilst for other less experienced staff coverage of dementia in the initial induction was not in-depth enough to help them feel confident when commencing work in the home, or training content did not provide enough support to help them in the range of often challenging situations they might find themselves.

… how to get out of situations if somebody has got hold of my hair, how do I get out of that? (SC042 Staff Member 033).

Behaviour change

Themes related to behaviour change included adopting a more empathic and understanding approach, improved communication, provision of meaningful activity, a shift from task to person-focussed care.

Staff in two of the care homes (SC040, SC042) identified how training had helped them to deliver care that was more empathic and was understanding of resident behaviours and what they communicated about individual needs.

SC042 Staff Member P2: We’ve got one lady who goes back to when she was in the War and she was deported and she gets terribly upset and she thinks we’re keeping her in. So we just take her outside on the decking for a little bit, then she is okay. She’s not a prisoner of war anymore. ‘Cause she thinks we’re keeping her a prisoner. But I wouldn’t have known to treat her like that unless I’d known that that’s how dementia can affect you.

I: What might you have done before?

P2: Well, probably said, ‘Look you’re okay, sit down, have a cup of tea’ and basically get on with it, which I probably would have.

As a result of improved staff understanding one manager noted there was a demonstrable reduction in drugs used to manage behaviour in people with dementia, due to staff being able to support needs through psychosocial approaches.

There has been a real marked reduction in the number of drugs and that I can prove. That’s documented and it’s easy to do. (Unit Manager Sc040 020)

In two sites (SC040, SC076) improved staff communication was a behavioural outcome of training. Staff gave examples of approaches the training had taught them, such as wording questions so residents can give a yes/no answer. Keeping language simple and using picture prompts. There was also increased confidence in staff to communicate with residents.

I’m having a joke with them you know, talk about their families and they like talking about- you know talking about their families.. (Staff Member SC040 026).

Talk softer, come down to their level. It’s easier just to say ‘here’s your dinner’ you know and put it in front of them. I don’t do that anymore (SC076 Focus Group 1 P1)

The DCM data showed that in four of the five units observed there were more personal enhancers than detractors observed on average, per participant than detractors (see Fig.  1 ) and overall detraction levels were low. In one unit (B) at site SC040, however, more detractors were observed than enhancers during the mapping period. This indicates that in that unit on the days observations took place not all staff were communicating in person-centred ways.

Average number of personal detractors and enhancers observed per participant per hour by site and unit

All three sites indicated that implementing new activities in the home had resulted from staff attending training. In one home (SC040) this included one-to-one engagement, hand massages and cookery classes. They had also arranged visits from external professionals who gave Indian Head Massages, ran dance classes or delivered group music sessions. The latter two were particularly highlighted as being enjoyed by the residents.

You would not believe how good it is [the music session], it’s just amazing, such a good feeling. (Unit Manager SC040 020)

They just get on with it, some of them make themselves a drink and stuff. And I think just not saying: ‘Oh you can’t do that’ is wrong. It’s about observing them doing it, making sure they’re safe. I think that’s a good thing we’ve learnt from training, let them be independent. (SC042 Staff Member 802).

In site SC076 staff used a new SMART TV to look for old films, singers or YouTube clips that residents might enjoy. In site SC040 the maintenance worker had started promoting vegetable-growing amongst the residents after attending training. He understood what the residents needed in order to support them to take part in the project. The residents were able to sow the seeds, care for the potatoes, harvest them and then peel them ready to be eaten.

Making a shift from a task focussed to person-centred care was another behaviour change reported. In site SC040 staff commented that they felt they had ‘permission’ to focus on person-centred care such as activities and spending time with residents, rather than feeling they should be completing tasks. This change in behaviour was noted by the training lead.

[They are no longer focussed on] they have to do this for this time and this for this time and the individual gets lost so I think we’re breaking that down. (Training Lead SC040)

I think people exhibit more patience, more individualised care, more person-centred care. I think that goes for relatives as well. We support relatives in an individualised person-centred way, because some of the relatives need that care (Home Manager SC076)

Staff in one care home noted how training was one part of the bigger picture that had supported a shift in culture.

It validated that for us we were on the right track. Obviously things always need to be tweaked, I know that, but I think it was giving a bit of confidence that we’re on the right track. (SC040 Focus Group P3).

Outcomes and impact

Themes related to outcomes and impact included improved resident well-being and decreased distress; disparities and variability of experience; and high resident and relative satisfaction.

Staff across all three sites consistently stated they felt that, as a result of the changes staff had made to practice, residents were experiencing greater well-being and were less frequently distressed.

I do think the training has impacted on their wellbeing in a positive way [. . . ] The carers take a more, a better interest in, you know, what the person like(s) and needs are and how they can make it a better day for them. (SC040 Staff Member 014)

It made them less agitated, they had something to concentrate on, something to do which improved their mood massively. When you work out what activity is right for the right person you then get a better mood all day. (Home Manager SC042)

Our observations of care showed that while resident well-being was generally moderately good and levels of ill-being were low, this did differ between units within the same organisation and across different residents living in the same unit. Figure  2 presents the average Mood and Engagement Value per resident over the period they were observed, known in DCM as their Individual Well and Ill-being Score.

Individual Well and Ill-being Scores by setting

We found similar results when looking at engagement in activities (see Fig.  3 ). In some units, residents spent more of the observation period in disengaged and distressed behaviours (e.g. passive observation, disengagement, sleep, distress and repetitive behaviours) and less time engaged in active behaviours (e.g. interacting with others, singing, reminiscing, physical exercise, sensory stimulation, work-like activity etc).

Percentage of time spend in different behaviours during DCM observations

The residents’ and relatives’ satisfaction cards showed high overall satisfaction with care received and respondents felt staff understood their/the residents’ feelings and needs and were knowledgeable about dementia. The qualitative comments included positive aspects and some suggestions for ways care could be improved.

We’re only allowed one shower a week. They have a nice way with them. (Respondent 3 SC040)

My mum used to live in another home but since she came here she is much happier. The dementia care staff know their stuff and nothing is too much trouble. (Respondent 1 SC042)

My Auntie is very well cared for and all her needs are met. All the carers are very patient with her. There is always someone who can answer any questions I may have (Respondent 1 SC076)

In one site, a resident chose to take part in an interview. They said that they felt they were given choices at mealtimes through being given a menu with two different meal options to choose between and believed that staff members respected these choices.

Training barriers

Despite the sites being chosen for the positive aspects of their training, all still experienced a range of barriers to delivery and implementation. Common barriers across the sites included staff time, staffing levels and turnover, lack of dedicated training facilities and difficulties in gaining feedback from staff.

Staff time, staffing levels and turnover

In all three sites a lack of time, staffing levels and turnover were a challenge to training delivery and implementation. This included difficulties being able to free up staff to attend training due to difficulties covering shifts, the need to constantly train new staff in the more basic levels of training due to turnover and a lack of time for staff to implement learning in practice.

Eight people is an awful lot of people off the floor, you can’t, it is just impossible to do (SC040 Manager 019)

Turnover at the moment is really quite difficult to manage (SC042 Dementia Lead)

Two sites had previously required staff to undertake learning in their own time either via face-to-face or self-directed means. This had not been successful in terms of staff reaction to training or completion rates. As one manager stated:

You can’t just expect them to pitch up and not be paid (SC040 Manager 020)

P1 It’s not completed by any means. It was meant to be completed ages ago, P2 I’ve lost mine. (SC042 Focus Group)

Lack of dedicated training facilities

In two of the sites there were no dedicated training facilities available, meaning training was delivered in a lounge or other room in the care home that was often cramped and unsuitable.

Venues are normally an issue because you normally get put into a lounge. A lounge doesn’t have a lot of space really. Sometimes the rooms are quite small and that limits the number of people you can have in the room and limits, you might wanna do – can’t really facilitate or there may not be sufficient wi-fi… (Training Facilitator SC076)

Difficulties in getting feedback on training

In two sites the training lead/facilitators mentioned difficulties they experienced in getting honest and practical feedback from staff about how useful the training had been as well as impact on care practice.

It’s difficult to get out because they all say “We enjoy the training”. “Great, ok, what did you like?” You can ask it verbally or you……if you ask it verbally you get a better answer. If you ask them to write it down it doesn’t really come through…all of it. “Which bit was particularly useful for you?” “Yeah, well everything.” Ok. There’s not really real constructive to feed back in. (SC076 Training Facilitator)

I can’t say I’ve had fabulous feedback in terms of change (SC040 Training Facilitator)

Facilitating factors

Common facilitators of training delivery and implementation across the good practice sites included commitment of the organisation and management, skilled training facilitation and strong peer and team support.

Commitment of the organisation and management

The importance of organisational and managerial commitment to dementia training was a strong feature of all of the sites. This included an organisational culture and ethos that valued training, home or unit managers who supported training attendance and implementation in practice, and strong leadership for dementia training via a dementia and/or training lead.

As a company [name] are really, really keen and up there to make sure the staff are fit for purpose, well trained and can deliver good care and they feel quite passionate about it I think (SC040 Training Facilitator)

So, it has to come from the top. You can have the best carers in the world, but it makes no difference if the people at the top don’t want to actually give people time to learn, (SC042 Dementia Lead)

Skilled training facilitation

Skilled and flexible training facilitation was mentioned as a facilitator in all sites. The trainers made learning memorable and managers commented that staff often talked about dementia training when back on the units afterwards.

[The Training Lead] is quite flexible, she will come into the homes if the homes are struggling or short staff and she’s got people that need to do training. She’ll come round here rather than go out there. (SC042 Manager)

Strong peer and team support

Having a staff team who were motivated to learn, supportive of one another and who felt empowered to make suggestions for practice change was a facilitator at all three sites.

[Name of colleague] is really good at raising stuff. Because she’s an admin worker, her perspective is different. And she will quite often say: ‘But, why can’t you? Why?’ and sometimes in an organisation, that is what you need- people that will challenge, because otherwise you end up with, you all do it that way, because you all do it, and that way can lead to stagnation, bad practice. (SC076 Unit Manager)

The case studies identified a range of elements of good practice in relation to training design, delivery and implementation that are applicable not only to dementia training, but to broader training delivery within care home settings. As was reported by Beeber et al. [ 5 ] the design and delivery methods utilised were important and in the case studies particularly impacted on staff reactions to training and subsequent uptake. Findings across the three sites strongly support the use of face-to-face delivery, interactive and engaging teaching methods and the tailoring of training to the setting and staff roles of those attending. The preference for and benefits of face-to-face, interactive training in care home settings are reported in the international research literature see for example [ 37 , 38 ]. This were also a common feature of training delivery preferences of staff in other settings (e.g. acute hospitals [ 39 ]) within the broader What Works study. However, implementation of such methods is pragmatically challenging in light of the staffing and resource barriers that were identified at all sites, as well as the broad range of subjects and learning outcomes that staff training must address in order to meet national standards [ 40 , 41 ] (see for example [ 42 , 43 ]). Staffing issues and having the resources to support staff to attend and implement training have been reported as challenging within social care workforce development and intervention research [ 44 – 47 ]. This suggests that care provider organisations and researchers should consider resource and staffing issues and how they will be addressed or accommodated, before embarking on new programmes of staff training in care home settings.

In the case study sites, an organisational ethos and culture of commitment to dementia training, which was evidenced throughout the management team, helped to overcome some of the resource issues. This, coupled with the presence of dedicated training staff to develop, facilitate and champion training, provided a positive context in which training could be carried out and implemented despite the challenges. The importance of both top-down and bottom-up approaches to changing care practice through educational programmes in care home settings has been reported in other research. This includes active executive and management involvement and the presence of individual(s) to ‘champion’ implementation [ 13 , 38 , 47 ]. Where managers are seen as ‘far removed’ this can be a barrier to training implementation [ 46 ]. The organisational culture was also reflected in the peer support, and staff engagement in training attendance and in subsequent implementation. Resistance to change among staff teams [ 48 ] and the impact that individuals who are ‘rigid’, ‘closed-minded’ or ‘indifferent’ can have on colleagues’ motivation is another potential barrier [ 46 ]. This indicates that in the design of training programmes, trainers and organisations should not only consider the content and delivery but also how to prepare and engage the organisation and individual staff members. Without a team and organisational culture that is largely supportive of training and its implementation, the many barriers that exist are likely to prevent optimal impact [ 49 , 50 ].

It was disappointing that we were not able to recruit any domiciliary/home care organisations into the study. It is likely that some of the issues, barriers and facilitators may be similar to those experienced in care home settings due to the similarities there are in demographics and prior educational experience of both workforces. However, we would also anticipate domiciliary care providers and staff to experience a range of additional challenges associated with lone working, use of zero hours contracts [ 51 ] and a geographically spread workforce.

Limitations

There are a number of limitations in this study. While the case studies were in-depth, we were only able to include the three top-performing audit respondents in ‘best practice’ case studies. Therefore, the sample is not representative of the typical or average care home. Given staff had already accessed a range of dementia training, it was not possible to understand the direct impact on outcomes of individual training packages included in the case study. The respondents to the satisfaction survey for residents with dementia and their family members may reflect participation bias. Residents and family members who are more satisfied may be more likely to respond than others. Relatives who are dissatisfied may be concerned about raising issues if given their loved one is still being cared for in the care home. It is difficult to draw any firm conclusions about the impact of training on staff practice and resident outcomes from the observational data.

Conclusions and recommendations

Despite care homes being one of the most researched settings in terms of dementia training and its impact, relatively little is still known about how the emergent design and delivery features of effective training (e.g. face-to-face, tailored, flexible, interactive) can be implemented practically. Likewise, while an understanding of the ideal setting conditions for training and other psychosocial interventions is evolving, how these can be facilitated and sustained is still poorly understood or implemented. More research is still needed on the practical aspects of sustainable and impactful dementia training delivery and implementation in care home settings.

This study has added to our understanding of effective dementia education and training for care home staff. It suggests that training that is most likely to lead to positive outcomes across staff reactions, learning, behaviour change and outcomes for people with dementia has the following qualities. It:

• Is delivered face-to-face to a small group using interactive methods such as discussion, case studies and practical exercises and activities;
• Is tailored to the setting and role of staff attending and was inclusive of all staff working in direct care and non-care roles;
• Provides ongoing support outside of the training room for staff to reflect on learning and implement training;
• Includes methods that support staff to engage with the lived experience of people with dementia;
• Is delivered by an experienced training facilitator who is able to engage and work flexibly with staff;
• Is one component of achieving an organisational commitment to and culture of person-centred care;
• Is supported by the home owners and management team in terms of resource and development of an organisational culture that values learning.

Additional file

Inclusion criteria and steps for selection of the case study sites. (DOCX 62 kb)

Acknowledgements

We would like to thank all of the participating sites and individuals who gave their time freely to take part in this research. We would like to thank other members of the research team Dr. Sarah Smith, Dr. Sahdia Parveen, Dr. Andrea Capstick and Dr. David Meads, who contributed to study design and implementation. We would like to thank the members of the lay advisory group who provided insight and advice on study design, materials, analysis and dissemination. We would also like to thank Dr. Andrew Hart for his involvement in data analysis.

Abbreviations

Authors’ contributions.

CAS was Chief Investigator of the study and contributed to study design, data analysis and interpretation and drafting this manuscript. CS contributed to data acquisition, data analysis and interpretation and revising the manuscript. MD contributed to data acquisition, data analysis and interpretation and revising the manuscript. NB contributed to data acquisition, data analysis and interpretation and revising the manuscript. AD contributed to study design, data interpretation and revising the manuscript. SB contributed to data analysis, interpretation and revising the manuscript. JO was Lead for the Case study work package and contributed to study design, data analysis and interpretation and revising the manuscript. All authors have read and approved the final manuscript.

This study was funded by the National Institute for Health Research Policy Research Programme (NIHR PRP) under Grant PR-R10–0514-12006. The views expressed in the publication are those of the author(s) and not necessarily those of the NHS, the NIHR, the Department of Health and Social Care, ‘arms’ length bodies or other government departments.

Availability of data and materials

Ethics approval and consent to participate.

Ethical approval for the study was given by the Yorkshire and the Humber – Bradford Leeds NHS Research Ethics Committee [REC Ref 15/YH/0488]. All participants gave informed, written consent to participate.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Claire A. Surr, Phone: 0113 812 4316, Email: [email protected] .

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Five Collective Impact Deep Dive Case Studies

We are happy to share five new case studies featuring a subset of the collaboratives studied by the 2018 research study “ When Collective Impact Has an Impact ,” conducted by ORS Impact and Spark Policy Institute. Each case study takes a deeper look at how the conditions of collective impact contributed to achieving population change.

These initiatives have engaged in city, county, and state-wide collaboration over the past two decades. They have worked to address complex issues like homelessness, prescription drug abuse prevention, juvenile justice, and youth well-being. We invite you to check out how they have established organizational structures, adopted principles of collective impact, and developed strategies toward early and systems changes.

Learn more about how each of these remarkable initiatives have made an impact: • Alignment Nashville • Communities That Care Coalition • Colorado Consortium • Home for Good • Juvenile Justice Alliance

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