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• Roberta Heale 1 ,
• Helen Noble 2
• 1 Laurentian University , School of Nursing , Sudbury , Ontario , Canada
• 2 Queens University Belfast , School of Nursing and Midwifery , Belfast , UK
• Correspondence to Dr Roberta Heale, School of Nursing, Laurentian University, Ramsey Lake Road, Sudbury, P3E2C6, Canada; rheale{at}laurentian.ca

https://doi.org/10.1136/ebnurs-2019-103077

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Often the most difficult part of a research study is preparing the proposal based around a theoretical or philosophical framework. Graduate students ‘…express confusion, a lack of knowledge, and frustration with the challenge of choosing a theoretical framework and understanding how to apply it’. 1 However, the importance in understanding and applying a theoretical framework in research cannot be overestimated.

The choice of a theoretical framework for a research study is often a reflection of the researcher’s ontological (nature of being) and epistemological (theory of knowledge) perspective. We will not delve into these concepts, or personal philosophy in this article. Rather we will focus on how a theoretical framework can be integrated into research.

The theoretical framework is a blueprint for your research project 1 and serves several purposes. It informs the problem you have identified, the purpose and significance of your research demonstrating how your research fits with what is already known (relationship to existing theory and research). This provides a basis for your research questions, the literature review and the methodology and analysis that you choose. 1 Evidence of your chosen theoretical framework should be visible in every aspect of your research and should demonstrate the contribution of this research to knowledge. 2

What is a theory?

A theory is an explanation of a concept or an abstract idea of a phenomenon. An example of a theory is Bandura’s middle range theory of self-efficacy, 3 or the level of confidence one has in achieving a goal. Self-efficacy determines the coping behaviours that a person will exhibit when facing obstacles. Those who have high self-efficacy are likely to apply adequate effort leading to successful outcomes, while those with low self-efficacy are more likely to give up earlier and ultimately fail. Any research that is exploring concepts related to self-efficacy or the ability to manage difficult life situations might apply Bandura’s theoretical framework to their study.

Using a theoretical framework in a research study

Example 1: the big five theoretical framework.

The first example includes research which integrates the ‘Big Five’, a theoretical framework that includes concepts related to teamwork. These include team leadership, mutual performance monitoring, backup behaviour, adaptability and team orientation. 4 In order to conduct research incorporating a theoretical framework, the concepts need to be defined according to a frame of reference. This provides a means to understand the theoretical framework as it relates to a specific context and provides a mechanism for measurement of the concepts.

In this example, the concepts of the Big Five were given a conceptual definition, that provided a broad meaning and then an operational definition, which was more concrete. 4 From here, a survey was developed that reflected the operational definitions related to teamwork in nursing: the Nursing Teamwork Survey (NTS). 5 In this case, the concepts used in the theoretical framework, the Big Five, were the used to develop a survey specific to teamwork in nursing.

The NTS was used in research of nurses at one hospital in northeastern Ontario. Survey questions were grouped into subscales for analysis, that reflected the concepts of the Big Five. 6 For example, one finding of this study was that the nurses from the surgical unit rated the items in the subscale of ’team leadership' (one of the concepts in the Big Five) significantly lower than in the other units. The researchers looked back to the definition of this concept in the Big Five in their interpretation of the findings. Since the definition included a person(s) who has the leadership skills to facilitate teamwork among the nurses on the unit, the conclusion in this study was that the surgical unit lacked a mentor, or facilitator for teamwork. In this way, the theory of teamwork was presented through a set of concepts in a theoretical framework. The Theoretical Framework (TF)was the foundation for development of a survey related to a specific context, used to measure each of the concepts within the TF. Then, the analysis and results circled back to the concepts within the TF and provided a guide for the discussion and conclusions arising from the research.

Example 2: the Health Decisions Model

In another study which explored adherence to intravenous chemotherapy in African-American and Caucasian Women with early stage breast cancer, an adapted version of the Health Decisions Model (HDM) was used as the theoretical basis for the study. 7 The HDM, a revised version of the Health Belief Model, incorporates some aspects of the Health Belief Model and factors relating to patient preferences. 8 The HDM consists of six interrelated constituents that might predict how well a person adheres to a health decision. These include sociodemographic, social interaction, experience, knowledge, general and specific health beliefs and patient preferences, and are clearly defined. The HDM model was used to explore factors which might influence adherence to chemotherapy in women with breast cancer. Sociodemographic, social interaction, knowledge, personal experience and specific health beliefs were used as predictors of adherence to chemotherapy.

The findings were reported using the theoretical framework to discuss results. The study found that delay to treatment, health insurance, depression and symptom severity were predictors to starting chemotherapy which could potentially be adapted with clinical interventions. The findings from the study contribute to the existing body of literature related to cancer nursing.

Example 3: the nursing role effectiveness model

In this final example, research was conducted to determine the nursing processes that were associated with unexpected intensive care unit admissions. 9 The framework was the Nursing Role Effectiveness Model. In this theoretical framework, the concepts within Donabedian’s Quality Framework of Structure, Process and Outcome were each defined according to nursing practice. 10 11  Processes defined in the Nursing Role Effectiveness Model were used to identify the nursing process variables that were measured in the study.

A theoretical framework should be logically presented and represent the concepts, variables and relationships related to your research study, in order to clearly identify what will be examined, described or measured. It involves reading the literature and identifying a research question(s) while clearly defining and identifying the existing relationship between concepts and theories (related to your research questions[s] in the literature). You must then identify what you will examine or explore in relation to the concepts of the theoretical framework. Once you present your findings using the theoretical framework you will be able to articulate how your study relates to and may potentially advance your chosen theory and add to knowledge.

• Kalisch BJ ,
• Parent M , et al
• Strickland OL ,
• Dalton JA , et al
• Eraker SA ,
• Kirscht JP ,
• Lightfoot N , et al
• Harrison MB ,
• Laschinger H , et al

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Provenance and peer review Not commissioned; internally peer reviewed.

Patient and public involvement Not required.

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The Distinctions Between Theory, Theoretical Framework, and Conceptual Framework

Varpio, Lara PhD; Paradis, Elise PhD; Uijtdehaage, Sebastian PhD; Young, Meredith PhD

L. Varpio is professor and associate director of research, Graduate Programs in Health Professions Education in the Department of Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland; ORCID: https://orcid.org/0000-0002-1412-4341 .

E. Paradis is assistant professor, University of Toronto, Toronto, Ontario, Canada, scientist, Wilson Centre, Toronto, Ontario, Canada, and researcher, Facebook, Menlo Park, California; ORCID: https://orcid.org/0000-0001-9103-4721 .

S. Uijtdehaage is professor and associate director, Graduate Programs in Health Professions Education, Department of Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland; ORCID: https://orcid.org/0000-0001-8598-4683 .

M. Young is associate professor, Institute of Health Sciences Education, McGill University, Montreal, Quebec, Canada; ORCID: http://orcid.org/0000-0002-2036-2119 .

Editor’s Note: This article is part of a collection of Invited Commentaries exploring the Philosophy of Science.

Funding/Support: None reported.

Other disclosures: None reported.

Ethical approval: Reported as not applicable.

Disclaimers: The views expressed herein are those of the authors and do not necessarily reflect those of the Uniformed Services University of the Health Sciences, the United States Department of Defense, or other federal agencies.

Correspondence should be addressed to Lara Varpio, F. Edward Hébert School of Medicine, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Rd., Bethesda, MD 20814; email: [email protected] ; Twitter: @LaraVarpio.

Written work prepared by employees of the Federal Government as part of their official duties is, under the U.S. Copyright Act, a “work of the United States Government” for which copyright protection under Title 17 of the United States Code is not available. As such, copyright does not extend to the contributions of employees of the Federal Government.

Health professions education (HPE) researchers are regularly asked to articulate their use of theory, theoretical frameworks, and conceptual frameworks in their research. However, all too often, these words are used interchangeably or without a clear understanding of the differences between these concepts. Further problematizing this situation is the fact that theory , theoretical framework , and conceptual framework are terms that are used in different ways in different research approaches. In this article, the authors set out to clarify the meaning of these terms and to describe how they are used in 2 approaches to research commonly used in HPE: the objectivist deductive approach (from theory to data) and the subjectivist inductive approach (from data to theory). In addition to this, given that within subjectivist inductive research theory , theoretical framework , and conceptual framework can be used in different ways, they describe 3 uses that HPE researchers frequently rely on: fully inductive theory development , fully theory-informed inductive , and theory-informing inductive data analysis.

Researchers working in health professions education (HPE) are often advised to address one, some, or all of the following concepts: theory , theoretical framework , and conceptual framework . For instance, HPE scholars are advised to integrate theory into research. 1–5 Granting bodies ask that a project’s theoretical framework be articulated in funding requests. 6 Review criteria for research reports prompt reviewers to assess whether the study’s conceptual framework is explicitly described and justified. 7 Meeting these mandates requires HPE community members to know the answers to some foundational questions: What is theory ? How is a theory distinct from a theoretical framework ? Does the term conceptual framework refer to something altogether different from a theory or theoretical framework ? Unfortunately, clear answers to these questions are not readily available. After searching the literature, we were disappointed to realize that few publications explicitly answer these questions. Furthermore, those publications that do provide answers rarely pay attention to how definitions can differ across the variety of research approaches represented within HPE scholarship. If HPE scholars are to effectively work with theory , theoretical frameworks , and conceptual frameworks , we need to clarify these terms.

HPE is a vibrant multidisciplinary and paradigmatically eclectic domain where scholars bring their varied disciplinary traditions and vocabularies to the research endeavor. 8–10 Since the terms theory , theoretical framework , and conceptual framework can have different interpretations and applications across paradigms, our eclecticism sometimes finds HPE scholars working at cross-purposes. Indeed, a lack of appreciation of the differences between these terms can have detrimental consequences. Without clarity, we risk falsely assuming shared interpretations and applications of these terms. We risk naively labeling some research designs as faulty, poorly executed, or lacking in rigor, when in fact those designs are employing different paradigmatically informed interpretations of these terms. We also risk impeding our collective efforts to build on the knowledge generated across paradigms. In other words, without clarity, we risk doing consequential harm to our own field. Therefore, in this paper, we set out to clarify the differences and relationships between the terms theory , theoretical framework , and conceptual framework.

There are many ways to articulate these different understandings. For instance, we could offer a historical description of how each term’s definition and application evolved over time; however, this could falsely imply that the more modern descriptions should replace older interpretations. Alternatively, we could frame our descriptions across the qualitative/quantitative divide; however, this dichotomy describes only the type of data being collected rather than usefully informing when and how to use a theory , a theoretical framework , or a conceptual framework . To avoid these and other pitfalls, we constructed a way of describing these terms that highlights the similarities across paradigms but that also respects important paradigmatic differences. We structure this article around 2 approaches to research commonly used in HPE: the objectivist deductive approach and the subjectivist inductive approach. While research exists across a continuum from inductive to deductive, and from subjective to objective, offering descriptions across these continua is beyond the scope of this article. Therefore, we adopt archetypal stances for each approach to make our descriptions more accessible. First, we define the terms theory , theoretical framework , and conceptual framework . Then, we describe how objectivist deductive researchers and subjectivist inductive researchers engage with these terms.

Defining the Terms

In both objectivist deductive and subjectivist inductive research, the term theory holds largely the same meaning. A theory is a set of propositions that are logically related, expressing the relation(s) among several different constructs and propositions. 11 In other words, a theory is an abstract description of the relationships between concepts that help us to understand the world. A theory can be supported by preliminary data or by a vast body of research—the more data supporting the theory, the stronger it becomes.

Theories can be descriptive (i.e., naming and characterizing a phenomenon), explanatory (i.e., clarifying the relationships between phenomena), emancipatory (i.e., articulating the oppression of a people), disruptive (i.e., extending existing knowledge or refuting it), or predictive (i.e., predicting an outcome based on specific inputs). Theories can also have different levels of explanatory power. There are grand theories that are highly abstract and that tend to be concerned with broad natural or social patterns (e.g., Marxist theories of society), middle-range theories that address more specific aspects of human interactions (e.g., actor–network theory), and microtheories that focus on individual-level phenomena (e.g., symbolic interactionism).

There are often multiple theories that inform our understanding of a single phenomenon. For example, there are many theories of human agency (i.e., agency can be defined as the extent to which individuals are able to exert control in their personal and social lives). These theories offer abstract conceptualizations of whether a person has agency, how that agency exists, how it is supported and/or obstructed, and how an individual’s agency exists in a larger social context (e.g., in a team, an organization, or a society). As Varpio et al 12 point out, theorists such as Giddens, Bourdieu, Butler, McNay, and Bandura have all addressed different aspects of agency, each offering different insights into the phenomenon. As this example illustrates, many scholars offer competing theories explaining phenomena. Therefore, HPE researchers must read broadly to select the theory that can best inform their research into a particular phenomenon.

Theoretical framework

A theoretical framework is a logically developed and connected set of concepts and premises—developed from one or more theories—that a researcher creates to scaffold a study. * To create a theoretical framework, the researcher must define any concepts and theories that will provide the grounding of the research, unite them through logical connections, and relate these concepts to the study that is being carried out. 13 In short, a theoretical framework is a reflection of the work the researcher engages in to use a theory in a given study.

Conceptual framework

A conceptual framework is the justification for why a given study should be conducted. The conceptual framework (1) describes the state of known knowledge, usually through a literature review; (2) identifies gaps in our understanding of a phenomenon or problem; and (3) outlines the methodological underpinnings of the research project. It is constructed 14 to answer 2 questions: “Why is this research important?” and “What contributions might these findings make to what is already known?”

How Objectivist Deductive and Subjectivist Inductive Research Approaches Apply These Concepts

While the terms theory , theoretical framework , and conceptual framework share common meanings across different research approaches, the ways in which they are applied vary greatly between objectivist deductive and subjectivist inductive approaches. We developed Figure 1 to illustrate key distinctions and relationships across these terms and their applications.

The objectivist deductive approach to research

Deductive research involves going from general, abstract conceptualizations to observable and measurable data within a specific context. It is a top-down approach. From abstract conceptualizations, a hypothesis is derived and tested. Findings may falsify, support, refine, challenge, or extend the conceptualizations. Paradigms that often use an objectivist deductive approach include positivism 15 and postpositivism. 16

Objectivist deductive research rests on the assumptions that (1) there is an external reality (i.e., a real world that exists independent of the researcher) and (2) reality can be understood by collecting objective, unbiased data about that reality. Research in this approach builds knowledge by developing increasingly better understandings of, and insights into, the causal workings of the world. † One of the most common approaches to objectivist deductive work is the use of experiments—whether in a lab, in a classroom, or naturalistic. Research questions in this approach tend to focus on testing underlying assumptions about how something works by testing a cause-and-effect relationship underpinning a phenomenon.

How objectivist deductive researchers use theory.

When a researcher engages in objectivist deductive research, a theory is generally the starting point for the research project. The theory offers testable components including, for example: the cause-and-effect relationships that can be examined, the concepts that should be operationalized, and the variables that are relevant to control. These testable components are used to generate specific hypotheses which are the foundation for a study. In this approach, a central assumption is that the theory is part of the object of research. In other words, the hypothesis being tested is an aspect of the theory of interest. Thus, the study is simultaneously testing a hypothesis derived from theory and the accompanying theory underlying that hypothesis.

There are 2 key characteristics of theory shared by all research conducted from an objectivist deductive approach: a theory must (1) be testable and (2) be open to being falsified. A good theory, in this approach, typically builds on previous work. A study adds new knowledge by adding another building block of evidence to support, refine, or challenge a theory. This approach to research builds knowledge slowly—incremental studies in programs of theory-oriented work construct ever more refined understandings of phenomena, which allow for better future predictions and/or a more robust theory.

In a purely objectivist deductive approach, a researcher would rarely combine multiple theories in a single study. Starting with multiple theories makes the creation of a single, theory-informed hypothesis difficult. The combination of theories makes it hard to identify the specific causal nature of the relationship under study and would break the chain of inferences available from the progressive testing and refinement of a theory. In an objectivist deductive approach, there is a linear progression that needs to be followed: from theory, to hypothesis development, to data collection, to interpretation of findings, to the refinement of theory or the generation of new causal explanations. The revised or new theory developed through research can become the start of a new study.

How objectivist deductive researchers use a theoretical framework.

The objectivist deductive researcher begins by identifying the theory from which to build the study’s theoretical framework. The researcher puts the theory into action as a theoretical framework by: articulating why the current context is a legitimate area of study for a given theory, shaping the constructs of interest, articulating the specific language and assumptions of the research question, identifying the variables and conditions of interest, and orienting the approach to analysis. This is the work the theoretical framework presents to readers to render a theory operational, testable, and able to be used to predict, test a hypothesis, or explain a phenomenon.

In the objectivist deductive tradition, a theoretical framework is typically constructed before data collection and is fixed—meaning that a theoretical framework is written before the study beings and remains largely unchanged throughout the research process. After choosing a theory, the researcher can construct the theoretical framework that turns the theory into the object of study. Thanks to this work, the study is well positioned to advance knowledge because it puts the theory to the test and unites findings across research contexts. Not surprisingly, then, peer reviewers of objectivist deductive research look for a theoretical framework to be made explicit because the framework shapes the design of the study and describes how the current research joins a lineage of inquiry done using the same theory.

How objectivist deductive researchers use a conceptual framework.

In objectivist deductive research, a conceptual framework typically includes a description of relevant literature, a summary of the relevant theory, an explanation of why this theory could be informative to this context, a specific research question that likely contains a hypothesis, a rationale for the research methodology adopted, and a series of outcomes or variables of interest. A conceptual framework is finalized before the study and is rarely modified once data collection has started.

The subjectivist inductive approach to research

Inductive research involves going from specific data relating to a particular phenomenon to a general or abstract conceptualization of the phenomenon. It is a bottom-up approach (i.e., working from data up to abstract conceptualizations). Subjectivist inductive research does not begin with a hypothesis; instead, this research begins with a desire to understand or explain a particular phenomenon. The researcher collects data of and/or about this phenomenon and searches for patterns across the data to generate an understanding of the phenomenon. Paradigms that often use the subjectivist inductive approach include constructionism 17 and critical theory. 18

Subjectivist inductive research rests on the assumptions that (1) reality is socially and experientially constructed (i.e., reality is an unsteady social construction that exists not because there is a natural, external reality but because individuals and social groups share interpretations and understandings of reality) and (2) to understand these realities, researchers need to explore the meanings constructed by individuals and groups. This means that knowledge is subjective—one person’s understanding of a phenomenon may not be the same as another person’s understanding. By collecting data from a multitude of perspectives, we can gain a richer and more nuanced understanding of the phenomenon. A common approach to subjectivist inductive research involves exploring a phenomenon in a specific context, often via interviews, focus groups, and/or observations. Researchers actively and subjectively construct research findings in collaboration with study participants. ‡ Research questions in this approach explore phenomena or assumptions to increase our understanding of them.

How subjectivist inductive researchers use theory.

In the subjectivist inductive approach, theory not only exists as an abstract description that researchers read and debate, but it can also reside within the researcher as a cognitive frame that shapes his or her thinking and research design choices. In this approach, theory is not stable. It is constantly evolving, informed by researchers’ experience, values, and perceptions. Furthermore, the subjectivist inductive researcher can engage with a single theory or with several theories in a single study or across a program of research.

There are 3 main ways that theory is used by subjectivist inductive researchers. 19 First, theory can be the product of research. Some subjectivist inductive research—notably researchers working in Glaser and Strauss’s grounded theory tradition 20 —generates theory from the data. Thus, theory is not used to inform study design but is the major output of the research project and evolves out of a systematic inductive approach to data analysis. This approach represents the most fully inductive approach to subjectivist inductive research. We label this the fully inductive theory development study design.

Second, one or more theories can inform the entire research process. Here, theory shapes every stage of the research process, including the development of a research question, methodological choices, data collection, data analysis, and study conclusions. 21–23 The theories informing research are articulated at the outset of the investigation, and all parts of the study design are justified in relation to how they align with the theories. In other words, theory is an all-informing conceptualization that permeates all facets of the study. 24 In this approach, the refinement of these existing theories or the development of a new theory may be a major output of the research project. We call this the fully theory-informed inductive study design.

Third, theory can be an interpretive tool. For some researchers, the decision as to which theory or theories will inform the final interpretations of the data is a choice that can only be finalized during the data collection and analysis cycles. The researcher holds many theories in mind when designing the study and engaging in data collection. It is not until data analysis processes are underway that the researcher will determine which theory or theories should shape the final study interpretations and conclusions. Consequently, the researcher may have to modify the study design partway through data analysis when he or she realizes that a particular theory is relevant. For instance, if during early cycles of data collection and analysis the researcher realizes that a particular theory can help elucidate the data, later cycles of data collection and analysis might seek to specifically consider data that will confirm, refute, or offer new insights into the theory. This is not a study design flaw. Instead, it is the result of deep exploration of data that reveals a particular theory to be relevant to the study findings. Here again, development and refinement of theory can come as the end result of the research. We label this the theory-informing inductive data analysis study design.

These 3 ways of engaging with theory are all equally valid. To be rigorous, however, researchers must make an early, explicit decision as to when and how they will use theory in their research. Often, revisions to the theory will be part of the contributions made to knowledge by the research project. Indeed, theoretical contributions are highly valued in inductive research; developing a new theory or challenging, adding to, or refining a preexisting theory is met with high regard.

How subjectivist inductive researchers use a theoretical framework.

To create a theoretical framework, the subjectivist inductive researcher must first decide which of the 3 study designs described above he or she will be using (i.e., fully inductive theory development , fully theory-informed inductive , or theory-informing inductive data analysis ). This decision will guide the development of the theoretical framework, including practical decisions of research design (e.g., the design of interview or focus group questions, study participant selection, the sensitizing concepts [if applicable]).

If using a fully inductive theory development study design, theory will not shape the study design. There is no theoretical framework to develop because there is no theory to build into the structure of the research. Instead, the study will depend on a robustly developed conceptual framework (see below).

If using a fully theory-informed inductive study design, the researcher must decide which theory or theories will be used as the lens and then transform the theory into a framework that explains how theory shapes the research questions, the way the research context is approached, the concepts that underpin the study design, the choice of methodology, the data collection, the interactions with study participants, the analysis processes, and the conclusions drawn. If more than one theory is used, the researcher must also describe how the theories inform each other and how they inform all aspects of the study. This is the work the researcher engages in to demonstrate how theory informs all aspects of the study design. In this design, the researcher develops the theoretical framework before the study is carried out; however, the theoretical framework can be adjusted during the research processes in response to the insights and understandings being developed. For instance, many research questions asked in this study design are broad and open ended (e.g., in a study using sociomateriality theory, a researcher might ask, What is a resident’s experience of interprofessional collaboration in clinical learning environments? ). But as the study develops and insights are generated, the research question might need to be modified to better align with the data that the participants and researcher are cocreating (e.g., realizing that the electronic health record has significant impact on team interactions, the research question might change to ask, What is a resident’s experience of interprofessional collaboration in clinical learning environments as it is negotiated through patients’ electronic health records? ).

If using a theory-informing inductive data analysis study design, the researcher will wait until data analysis is underway to decide which theory or theories can be used to inform data interpretations. The theoretical framework of the study is, therefore, developed during the data analysis processes (which may include cycles of data collection and analysis). When the theory is selected, that choice may impact several aspects of the study. 25 While the theory is selected only when some (or possibly all) data are in hand, the framework can describe how theory shapes the way the research context is approached, the concepts that underpin the evolving study design, the choice of methodology, the data collection, the interactions with study participants, the analysis processes, and the conclusions drawn (e.g., the theory chosen to inform a study using interviews to explore residents’ perception of interprofessional collaboration might highlight the importance of group processes, therefore requiring additional data collection via focus groups to explore group interactions). Not all aspects of the study are shaped by theory in the theory-informing inductive data analysis study design. Instead, only some aspects of the study design are informed by theory. In this design, the theoretical framework offers a description of which elements of the study are theory informed and how they are informed. The researcher thus has to work to translate insights from theory into specific contributions to elements of the theoretical framework and of the research design.

How subjectivist inductive researchers use a conceptual framework.

In a subjectivist inductive approach, the conceptual framework will likely need to evolve during a study as new ideas, insights, and knowledge are developed. As a result, a researcher will often construct a tentative conceptual framework at the beginning of the study, knowing that it will likely need to be adjusted as data transform the researcher’s understanding of the phenomenon. That framework will include a description of relevant literature, a summary of relevant theory (if using fully theory-informed inductive or theory-informing inductive data analysis study designs), an explanation of why the research should be carried out in the selected context, research question(s), and justification for the research methodology selected.

Our descriptions of theory , theoretical framework , and conceptual framework are simplified. To craft these descriptions, we had to wrestle with the foundational elements of research. Despite this effort, the result remains incomplete, undernuanced, and full of compromises. Indeed, descriptions of the use of theory , theoretical frameworks , and conceptual frameworks are usually written in book—rather than article—form, and we consequently needed to abbreviate and distill philosophical arguments at every turn. We explored the similarities and differences across objectivist deductive approaches and subjectivist inductive approaches. Our descriptions of objectivist deductive and subjectivist inductive approaches are not tied to specific paradigms. Instead, these research approaches can be used across paradigms. 26 Our descriptions should act as guideposts for when and how to engage with theory , theoretical frameworks , and conceptual frameworks . The real work of research is negotiating across these terms when we put them into action in our projects.

In this article, we highlight the transformative work that is needed for a theory to appropriately and meaningfully influence research studies that will help deepen our understanding of problems, contexts, and even the theories themselves important to HPE. But, to do this, we need to have a common understanding of the language we use and an appreciation of the different ways these terms can be applied. This language can help us better report the in-depth analytical work involved in research—a theoretical frame work articulates the logic of why we are using a particular theory; a conceptual frame work justifies why this problem/context/phenomenon is relevant to the field. These frameworks represent one of the most challenging aspects of research—turning a hunch, an observation, or a meandering thought into a logical, evidence-informed, theory-refining, impactful, and meaningful argument suitable for peer review and publication.

* For studies that seek to develop theory, these concepts and premises may be taken from a theoretical tradition.

† This is a general description of the objectivist epistemology. It is more nuanced when it is used in individual research paradigms. For example, positivists embrace a radical objectivist epistemology, 15 while postpositivists embrace a relative objectivist epistemology. 16

‡ This is a general description of the subjectivist epistemology. Is it more nuanced when it is used in a specific paradigm. For instance, critical theory embraces a relative subjectivist epistemology, 18 while constructionists adhere to a radical subjectivist epistemology. 17

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Using the framework method for the analysis of qualitative data in multi-disciplinary health research

• Nicola K Gale 1 ,
• Gemma Heath 2 ,
• Elaine Cameron 3 ,
• Sabina Rashid 4 &
• Sabi Redwood 2  

BMC Medical Research Methodology volume  13 , Article number:  117 ( 2013 ) Cite this article

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The Framework Method is becoming an increasingly popular approach to the management and analysis of qualitative data in health research. However, there is confusion about its potential application and limitations.

The article discusses when it is appropriate to adopt the Framework Method and explains the procedure for using it in multi-disciplinary health research teams, or those that involve clinicians, patients and lay people. The stages of the method are illustrated using examples from a published study.

Used effectively, with the leadership of an experienced qualitative researcher, the Framework Method is a systematic and flexible approach to analysing qualitative data and is appropriate for use in research teams even where not all members have previous experience of conducting qualitative research.

The Framework Method for the management and analysis of qualitative data has been used since the 1980s [ 1 ]. The method originated in large-scale social policy research but is becoming an increasingly popular approach in medical and health research; however, there is some confusion about its potential application and limitations. In this article we discuss when it is appropriate to use the Framework Method and how it compares to other qualitative analysis methods. In particular, we explore how it can be used in multi-disciplinary health research teams. Multi-disciplinary and mixed methods studies are becoming increasingly commonplace in applied health research. As well as disciplines familiar with qualitative research, such as nursing, psychology and sociology, teams often include epidemiologists, health economists, management scientists and others. Furthermore, applied health research often has clinical representation and, increasingly, patient and public involvement [ 2 ]. We argue that while leadership is undoubtedly required from an experienced qualitative methodologist, non-specialists from the wider team can and should be involved in the analysis process. We then present a step-by-step guide to the application of the Framework Method, illustrated using a worked example (See Additional File 1 ) from a published study [ 3 ] to illustrate the main stages of the process. Technical terms are included in the glossary (below). Finally, we discuss the strengths and limitations of the approach.

Glossary of key terms used in the Framework Method

Analytical framework: A set of codes organised into categories that have been jointly developed by researchers involved in analysis that can be used to manage and organise the data. The framework creates a new structure for the data (rather than the full original accounts given by participants) that is helpful to summarize/reduce the data in a way that can support answering the research questions.

Analytic memo: A written investigation of a particular concept, theme or problem, reflecting on emerging issues in the data that captures the analytic process (see Additional file 1 , Section 7).

Categories: During the analysis process, codes are grouped into clusters around similar and interrelated ideas or concepts. Categories and codes are usually arranged in a tree diagram structure in the analytical framework. While categories are closely and explicitly linked to the raw data, developing categories is a way to start the process of abstraction of the data (i.e. towards the general rather than the specific or anecdotal).

Charting: Entering summarized data into the Framework Method matrix (see Additional File 1 , Section 6).

Code: A descriptive or conceptual label that is assigned to excerpts of raw data in a process called ‘coding’ (see Additional File 1 , Section 3).

Data: Qualitative data usually needs to be in textual form before analysis. These texts can either be elicited texts (written specifically for the research, such as food diaries), or extant texts (pre-existing texts, such as meeting minutes, policy documents or weblogs), or can be produced by transcribing interview or focus group data, or creating ‘field’ notes while conducting participant-observation or observing objects or social situations.

Indexing: The systematic application of codes from the agreed analytical framework to the whole dataset (see Additional File 1 , Section 5).

Matrix: A spreadsheet contains numerous cells into which summarized data are entered by codes (columns) and cases (rows) (see Additional File 1 , Section 6).

Themes: Interpretive concepts or propositions that describe or explain aspects of the data, which are the final output of the analysis of the whole dataset. Themes are articulated and developed by interrogating data categories through comparison between and within cases. Usually a number of categories would fall under each theme or sub-theme [ 3 ].

Transcript: A written verbatim (word-for-word) account of a verbal interaction, such as an interview or conversation.

The Framework Method sits within a broad family of analysis methods often termed thematic analysis or qualitative content analysis. These approaches identify commonalities and differences in qualitative data, before focusing on relationships between different parts of the data, thereby seeking to draw descriptive and/or explanatory conclusions clustered around themes. The Framework Method was developed by researchers, Jane Ritchie and Liz Spencer, from the Qualitative Research Unit at the National Centre for Social Research in the United Kingdom in the late 1980s for use in large-scale policy research [ 1 ]. It is now used widely in other areas, including health research [ 3 – 12 ]. Its defining feature is the matrix output: rows (cases), columns (codes) and ‘cells’ of summarised data, providing a structure into which the researcher can systematically reduce the data, in order to analyse it by case and by code [ 1 ]. Most often a ‘case’ is an individual interviewee, but this can be adapted to other units of analysis, such as predefined groups or organisations. While in-depth analyses of key themes can take place across the whole data set, the views of each research participant remain connected to other aspects of their account within the matrix so that the context of the individual’s views is not lost. Comparing and contrasting data is vital to qualitative analysis and the ability to compare with ease data across cases as well as within individual cases is built into the structure and process of the Framework Method.

The Framework Method provides clear steps to follow and produces highly structured outputs of summarised data. It is therefore useful where multiple researchers are working on a project, particularly in multi-disciplinary research teams were not all members have experience of qualitative data analysis, and for managing large data sets where obtaining a holistic, descriptive overview of the entire data set is desirable. However, caution is recommended before selecting the method as it is not a suitable tool for analysing all types of qualitative data or for answering all qualitative research questions, nor is it an ‘easy’ version of qualitative research for quantitative researchers. Importantly, the Framework Method cannot accommodate highly heterogeneous data, i.e. data must cover similar topics or key issues so that it is possible to categorize it. Individual interviewees may, of course, have very different views or experiences in relation to each topic, which can then be compared and contrasted. The Framework Method is most commonly used for the thematic analysis of semi-structured interview transcripts, which is what we focus on in this article, although it could, in principle, be adapted for other types of textual data [ 13 ], including documents, such as meeting minutes or diaries [ 12 ], or field notes from observations [ 10 ].

For quantitative researchers working with qualitative colleagues or when exploring qualitative research for the first time, the nature of the Framework Method is seductive because its methodical processes and ‘spreadsheet’ approach seem more closely aligned to the quantitative paradigm [ 14 ]. Although the Framework Method is a highly systematic method of categorizing and organizing what may seem like unwieldy qualitative data, it is not a panacea for problematic issues commonly associated with qualitative data analysis such as how to make analytic choices and make interpretive strategies visible and auditable. Qualitative research skills are required to appropriately interpret the matrix, and facilitate the generation of descriptions, categories, explanations and typologies. Moreover, reflexivity, rigour and quality are issues that are requisite in the Framework Method just as they are in other qualitative methods. It is therefore essential that studies using the Framework Method for analysis are overseen by an experienced qualitative researcher, though this does not preclude those new to qualitative research from contributing to the analysis as part of a wider research team.

There are a number of approaches to qualitative data analysis, including those that pay close attention to language and how it is being used in social interaction such as discourse analysis [ 15 ] and ethnomethodology [ 16 ]; those that are concerned with experience, meaning and language such as phenomenology [ 17 , 18 ] and narrative methods [ 19 ]; and those that seek to develop theory derived from data through a set of procedures and interconnected stages such as Grounded Theory [ 20 , 21 ]. Many of these approaches are associated with specific disciplines and are underpinned by philosophical ideas which shape the process of analysis [ 22 ]. The Framework Method, however, is not aligned with a particular epistemological, philosophical, or theoretical approach. Rather it is a flexible tool that can be adapted for use with many qualitative approaches that aim to generate themes.

The development of themes is a common feature of qualitative data analysis, involving the systematic search for patterns to generate full descriptions capable of shedding light on the phenomenon under investigation. In particular, many qualitative approaches use the ‘constant comparative method’ , developed as part of Grounded Theory, which involves making systematic comparisons across cases to refine each theme [ 21 , 23 ]. Unlike Grounded Theory, the Framework Method is not necessarily concerned with generating social theory, but can greatly facilitate constant comparative techniques through the review of data across the matrix.

Perhaps because the Framework Method is so obviously systematic, it has often, as other commentators have noted, been conflated with a deductive approach to qualitative analysis [ 13 , 14 ]. However, the tool itself has no allegiance to either inductive or deductive thematic analysis; where the research sits along this inductive-deductive continuum depends on the research question. A question such as, ‘Can patients give an accurate biomedical account of the onset of their cardiovascular disease?’ is essentially a yes/no question (although it may be nuanced by the extent of their account or by appropriate use of terminology) and so requires a deductive approach to both data collection and analysis (e.g. structured or semi-structured interviews and directed qualitative content analysis [ 24 ]). Similarly, a deductive approach may be taken if basing analysis on a pre-existing theory, such as behaviour change theories, for example in the case of a research question such as ‘How does the Theory of Planned Behaviour help explain GP prescribing?’ [ 11 ]. However, a research question such as, ‘How do people construct accounts of the onset of their cardiovascular disease?’ would require a more inductive approach that allows for the unexpected, and permits more socially-located responses [ 25 ] from interviewees that may include matters of cultural beliefs, habits of food preparation, concepts of ‘fate’, or links to other important events in their lives, such as grief, which cannot be predicted by the researcher in advance (e.g. an interviewee-led open ended interview and grounded theory [ 20 ]). In all these cases, it may be appropriate to use the Framework Method to manage the data. The difference would become apparent in how themes are selected: in the deductive approach, themes and codes are pre-selected based on previous literature, previous theories or the specifics of the research question; whereas in the inductive approach, themes are generated from the data though open (unrestricted) coding, followed by refinement of themes. In many cases, a combined approach is appropriate when the project has some specific issues to explore, but also aims to leave space to discover other unexpected aspects of the participants’ experience or the way they assign meaning to phenomena. In sum, the Framework Method can be adapted for use with deductive, inductive, or combined types of qualitative analysis. However, there are some research questions where analysing data by case and theme is not appropriate and so the Framework Method should be avoided. For instance, depending on the research question, life history data might be better analysed using narrative analysis [ 19 ]; recorded consultations between patients and their healthcare practitioners using conversation analysis [ 26 ]; and documentary data, such as resources for pregnant women, using discourse analysis [ 27 ].

It is not within the scope of this paper to consider study design or data collection in any depth, but before moving on to describe the Framework Method analysis process, it is worth taking a step back to consider briefly what needs to happen before analysis begins. The selection of analysis method should have been considered at the proposal stage of the research and should fit with the research questions and overall aims of the study. Many qualitative studies, particularly ones using inductive analysis, are emergent in nature; this can be a challenge and the researchers can only provide an “imaginative rehearsal” of what is to come [ 28 ]. In mixed methods studies, the role of the qualitative component within the wider goals of the project must also be considered. In the data collection stage, resources must be allocated for properly trained researchers to conduct the qualitative interviewing because it is a highly skilled activity. In some cases, a research team may decide that they would like to use lay people, patients or peers to do the interviews [ 29 – 32 ] and in this case they must be properly trained and mentored which requires time and resources. At this early stage it is also useful to consider whether the team will use Computer Assisted Qualitative Data Analysis Software (CAQDAS), which can assist with data management and analysis.

As any form of qualitative or quantitative analysis is not a purely technical process, but influenced by the characteristics of the researchers and their disciplinary paradigms, critical reflection throughout the research process is paramount, including in the design of the study, the construction or collection of data, and the analysis. All members of the team should keep a research diary, where they record reflexive notes, impressions of the data and thoughts about analysis throughout the process. Experienced qualitative researchers become more skilled at sifting through data and analysing it in a rigorous and reflexive way. They cannot be too attached to certainty, but must remain flexible and adaptive throughout the research in order to generate rich and nuanced findings that embrace and explain the complexity of real social life and can be applied to complex social issues. It is important to remember when using the Framework Method that, unlike quantitative research where data collection and data analysis are strictly sequential and mutually exclusive stages of the research process, in qualitative analysis there is, to a greater or lesser extent depending on the project, ongoing interplay between data collection, analysis, and theory development. For example, new ideas or insights from participants may suggest potentially fruitful lines of enquiry, or close analysis might reveal subtle inconsistencies in an account which require further exploration.

Procedure for analysis

Stage 1: transcription.

A good quality audio recording and, ideally, a verbatim (word for word) transcription of the interview is needed. For Framework Method analysis, it is not necessarily important to include the conventions of dialogue transcriptions which can be difficult to read (e.g. pauses or two people talking simultaneously), because the content is what is of primary interest. Transcripts should have large margins and adequate line spacing for later coding and making notes. The process of transcription is a good opportunity to become immersed in the data and is to be strongly encouraged for new researchers. However, in some projects, the decision may be made that it is a better use of resources to outsource this task to a professional transcriber.

Stage 2: Familiarisation with the interview

Becoming familiar with the whole interview using the audio recording and/or transcript and any contextual or reflective notes that were recorded by the interviewer is a vital stage in interpretation. It can also be helpful to re-listen to all or parts of the audio recording. In multi-disciplinary or large research projects, those involved in analysing the data may be different from those who conducted or transcribed the interviews, which makes this stage particularly important. One margin can be used to record any analytical notes, thoughts or impressions.

Stage 3: Coding

After familiarization, the researcher carefully reads the transcript line by line, applying a paraphrase or label (a ‘code’) that describes what they have interpreted in the passage as important. In more inductive studies, at this stage ‘open coding’ takes place, i.e. coding anything that might be relevant from as many different perspectives as possible. Codes could refer to substantive things (e.g. particular behaviours, incidents or structures), values (e.g. those that inform or underpin certain statements, such as a belief in evidence-based medicine or in patient choice), emotions (e.g. sorrow, frustration, love) and more impressionistic/methodological elements (e.g. interviewee found something difficult to explain, interviewee became emotional, interviewer felt uncomfortable) [ 33 ]. In purely deductive studies, the codes may have been pre-defined (e.g. by an existing theory, or specific areas of interest to the project) so this stage may not be strictly necessary and you could just move straight onto indexing, although it is generally helpful even if you are taking a broadly deductive approach to do some open coding on at least a few of the transcripts to ensure important aspects of the data are not missed. Coding aims to classify all of the data so that it can be compared systematically with other parts of the data set. At least two researchers (or at least one from each discipline or speciality in a multi-disciplinary research team) should independently code the first few transcripts, if feasible. Patients, public involvement representatives or clinicians can also be productively involved at this stage, because they can offer alternative viewpoints thus ensuring that one particular perspective does not dominate. It is vital in inductive coding to look out for the unexpected and not to just code in a literal, descriptive way so the involvement of people from different perspectives can aid greatly in this. As well as getting a holistic impression of what was said, coding line-by-line can often alert the researcher to consider that which may ordinarily remain invisible because it is not clearly expressed or does not ‘fit’ with the rest of the account. In this way the developing analysis is challenged; to reconcile and explain anomalies in the data can make the analysis stronger. Coding can also be done digitally using CAQDAS, which is a useful way to keep track automatically of new codes. However, some researchers prefer to do the early stages of coding with a paper and pen, and only start to use CAQDAS once they reach Stage 5 (see below).

Stage 4: Developing a working analytical framework

After coding the first few transcripts, all researchers involved should meet to compare the labels they have applied and agree on a set of codes to apply to all subsequent transcripts. Codes can be grouped together into categories (using a tree diagram if helpful), which are then clearly defined. This forms a working analytical framework. It is likely that several iterations of the analytical framework will be required before no additional codes emerge. It is always worth having an ‘other’ code under each category to avoid ignoring data that does not fit; the analytical framework is never ‘final’ until the last transcript has been coded.

Stage 5: Applying the analytical framework

The working analytical framework is then applied by indexing subsequent transcripts using the existing categories and codes. Each code is usually assigned a number or abbreviation for easy identification (and so the full names of the codes do not have to be written out each time) and written directly onto the transcripts. Computer Assisted Qualitative Data Analysis Software (CAQDAS) is particularly useful at this stage because it can speed up the process and ensures that, at later stages, data is easily retrievable. It is worth noting that unlike software for statistical analyses, which actually carries out the calculations with the correct instruction, putting the data into a qualitative analysis software package does not analyse the data; it is simply an effective way of storing and organising the data so that they are accessible for the analysis process.

Stage 6: Charting data into the framework matrix

Qualitative data are voluminous (an hour of interview can generate 15–30 pages of text) and being able to manage and summarize (reduce) data is a vital aspect of the analysis process. A spreadsheet is used to generate a matrix and the data are ‘charted’ into the matrix. Charting involves summarizing the data by category from each transcript. Good charting requires an ability to strike a balance between reducing the data on the one hand and retaining the original meanings and ‘feel’ of the interviewees’ words on the other. The chart should include references to interesting or illustrative quotations. These can be tagged automatically if you are using CAQDAS to manage your data (N-Vivo version 9 onwards has the capability to generate framework matrices), or otherwise a capital ‘Q’, an (anonymized) transcript number, page and line reference will suffice. It is helpful in multi-disciplinary teams to compare and contrast styles of summarizing in the early stages of the analysis process to ensure consistency within the team. Any abbreviations used should be agreed by the team. Once members of the team are familiar with the analytical framework and well practised at coding and charting, on average, it will take about half a day per hour-long transcript to reach this stage. In the early stages, it takes much longer.

Stage 7: Interpreting the data

It is useful throughout the research to have a separate note book or computer file to note down impressions, ideas and early interpretations of the data. It may be worth breaking off at any stage to explore an interesting idea, concept or potential theme by writing an analytic memo [ 20 , 21 ] to then discuss with other members of the research team, including lay and clinical members. Gradually, characteristics of and differences between the data are identified, perhaps generating typologies, interrogating theoretical concepts (either prior concepts or ones emerging from the data) or mapping connections between categories to explore relationships and/or causality. If the data are rich enough, the findings generated through this process can go beyond description of particular cases to explanation of, for example, reasons for the emergence of a phenomena, predicting how an organisation or other social actor is likely to instigate or respond to a situation, or identifying areas that are not functioning well within an organisation or system. It is worth noting that this stage often takes longer than anticipated and that any project plan should ensure that sufficient time is allocated to meetings and individual researcher time to conduct interpretation and writing up of findings (see Additional file 1 , Section 7).

The Framework Method has been developed and used successfully in research for over 25 years, and has recently become a popular analysis method in qualitative health research. The issue of how to assess quality in qualitative research has been highly debated [ 20 , 34 – 40 ], but ensuring rigour and transparency in analysis is a vital component. There are, of course, many ways to do this but in the Framework Method the following are helpful:

Summarizing the data during charting, as well as being a practical way to reduce the data, means that all members of a multi-disciplinary team, including lay, clinical and (quantitative) academic members can engage with the data and offer their perspectives during the analysis process without necessarily needing to read all the transcripts or be involved in the more technical parts of analysis.

Charting also ensures that researchers pay close attention to describing the data using each participant’s own subjective frames and expressions in the first instance, before moving onto interpretation.

The summarized data is kept within the wider context of each case, thereby encouraging thick description that pays attention to complex layers of meaning and understanding [ 38 ].

The matrix structure is visually straightforward and can facilitate recognition of patterns in the data by any member of the research team, including through drawing attention to contradictory data, deviant cases or empty cells.

The systematic procedure (described in this article) makes it easy to follow, even for multi-disciplinary teams and/or with large data sets.

It is flexible enough that non-interview data (such as field notes taken during the interview or reflexive considerations) can be included in the matrix.

It is not aligned with a particular epistemological viewpoint or theoretical approach and therefore can be adapted for use in inductive or deductive analysis or a combination of the two (e.g. using pre-existing theoretical constructs deductively, then revising the theory with inductive aspects; or using an inductive approach to identify themes in the data, before returning to the literature and using theories deductively to help further explain certain themes).

It is easy to identify relevant data extracts to illustrate themes and to check whether there is sufficient evidence for a proposed theme.

Finally, there is a clear audit trail from original raw data to final themes, including the illustrative quotes.

There are also a number of potential pitfalls to this approach:

The systematic approach and matrix format, as we noted in the background, is intuitively appealing to those trained quantitatively but the ‘spreadsheet’ look perhaps further increases the temptation for those without an in-depth understanding of qualitative research to attempt to quantify qualitative data (e.g. “13 out of 20 participants said X). This kind of statement is clearly meaningless because the sampling in qualitative research is not designed to be representative of a wider population, but purposive to capture diversity around a phenomenon [ 41 ].

Like all qualitative analysis methods, the Framework Method is time consuming and resource-intensive. When involving multiple stakeholders and disciplines in the analysis and interpretation of the data, as is good practice in applied health research, the time needed is extended. This time needs to be factored into the project proposal at the pre-funding stage.

There is a high training component to successfully using the method in a new multi-disciplinary team. Depending on their role in the analysis, members of the research team may have to learn how to code, index, and chart data, to think reflexively about how their identities and experience affect the analysis process, and/or they may have to learn about the methods of generalisation (i.e. analytic generalisation and transferability, rather than statistical generalisation [ 41 ]) to help to interpret legitimately the meaning and significance of the data.

While the Framework Method is amenable to the participation of non-experts in data analysis, it is critical to the successful use of the method that an experienced qualitative researcher leads the project (even if the overall lead for a large mixed methods study is a different person). The qualitative lead would ideally be joined by other researchers with at least some prior training in or experience of qualitative analysis. The responsibilities of the lead qualitative researcher are: to contribute to study design, project timelines and resource planning; to mentor junior qualitative researchers; to train clinical, lay and other (non-qualitative) academics to contribute as appropriate to the analysis process; to facilitate analysis meetings in a way that encourages critical and reflexive engagement with the data and other team members; and finally to lead the write-up of the study.

We have argued that Framework Method studies can be conducted by multi-disciplinary research teams that include, for example, healthcare professionals, psychologists, sociologists, economists, and lay people/service users. The inclusion of so many different perspectives means that decision-making in the analysis process can be very time consuming and resource-intensive. It may require extensive, reflexive and critical dialogue about how the ideas expressed by interviewees and identified in the transcript are related to pre-existing concepts and theories from each discipline, and to the real ‘problems’ in the health system that the project is addressing. This kind of team effort is, however, an excellent forum for driving forward interdisciplinary collaboration, as well as clinical and lay involvement in research, to ensure that ‘the whole is greater than the sum of the parts’, by enhancing the credibility and relevance of the findings.

The Framework Method is appropriate for thematic analysis of textual data, particularly interview transcripts, where it is important to be able to compare and contrast data by themes across many cases, while also situating each perspective in context by retaining the connection to other aspects of each individual’s account. Experienced qualitative researchers should lead and facilitate all aspects of the analysis, although the Framework Method’s systematic approach makes it suitable for involving all members of a multi-disciplinary team. An open, critical and reflexive approach from all team members is essential for rigorous qualitative analysis.

Acceptance of the complexity of real life health systems and the existence of multiple perspectives on health issues is necessary to produce high quality qualitative research. If done well, qualitative studies can shed explanatory and predictive light on important phenomena, relate constructively to quantitative parts of a larger study, and contribute to the improvement of health services and development of health policy. The Framework Method, when selected and implemented appropriately, can be a suitable tool for achieving these aims through producing credible and relevant findings.

The Framework Method is an excellent tool for supporting thematic (qualitative content) analysis because it provides a systematic model for managing and mapping the data.

The Framework Method is most suitable for analysis of interview data, where it is desirable to generate themes by making comparisons within and between cases.

The management of large data sets is facilitated by the Framework Method as its matrix form provides an intuitively structured overview of summarised data.

The clear, step-by-step process of the Framework Method makes it is suitable for interdisciplinary and collaborative projects.

The use of the method should be led and facilitated by an experienced qualitative researcher.

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Acknowledgments

All authors were funded by the National Institute for Health Research (NIHR) through the Collaborations for Leadership in Applied Health Research and Care for Birmingham and Black Country (CLAHRC-BBC) programme. The views in this publication expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.

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Authors’ contributions

All authors were involved in the development of the concept of the article and drafting the article. NG wrote the first draft of the article, GH and EC prepared the text and figures related to the illustrative example, SRa did the literature search to identify if there were any similar articles currently available and contributed to drafting of the article, and SRe contributed to drafting of the article and the illustrative example. All authors read and approved the final manuscript.

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Additional file 1: illustrative example of the use of the framework method.(docx 167 kb), authors’ original submitted files for images.

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Gale, N.K., Heath, G., Cameron, E. et al. Using the framework method for the analysis of qualitative data in multi-disciplinary health research. BMC Med Res Methodol 13 , 117 (2013). https://doi.org/10.1186/1471-2288-13-117

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Educational resources and simple solutions for your research journey

What is a Theoretical Framework? How to Write It (with Examples) 

Theoretical framework 1,2 is the structure that supports and describes a theory. A theory is a set of interrelated concepts and definitions that present a systematic view of phenomena by describing the relationship among the variables for explaining these phenomena. A theory is developed after a long research process and explains the existence of a research problem in a study. A theoretical framework guides the research process like a roadmap for the research study and helps researchers clearly interpret their findings by providing a structure for organizing data and developing conclusions.   

A theoretical framework in research is an important part of a manuscript and should be presented in the first section. It shows an understanding of the theories and concepts relevant to the research and helps limit the scope of the research.  

Table of Contents

What is a theoretical framework ?  

A theoretical framework in research can be defined as a set of concepts, theories, ideas, and assumptions that help you understand a specific phenomenon or problem. It can be considered a blueprint that is borrowed by researchers to develop their own research inquiry. A theoretical framework in research helps researchers design and conduct their research and analyze and interpret their findings. It explains the relationship between variables, identifies gaps in existing knowledge, and guides the development of research questions, hypotheses, and methodologies to address that gap.  

Now that you know the answer to ‘ What is a theoretical framework? ’, check the following table that lists the different types of theoretical frameworks in research: 3

Developing a theoretical framework in research can help in the following situations: 4

• When conducting research on complex phenomena because a theoretical framework helps organize the research questions, hypotheses, and findings  
• When the research problem requires a deeper understanding of the underlying concepts  
• When conducting research that seeks to address a specific gap in knowledge  
• When conducting research that involves the analysis of existing theories  

Summarizing existing literature for theoretical frameworks is easy. Get our Research Ideation pack  

Importance of a theoretical framework  

The purpose of theoretical framework s is to support you in the following ways during the research process: 2  

• Provide a structure for the complete research process  
• Assist researchers in incorporating formal theories into their study as a guide  
• Provide a broad guideline to maintain the research focus  
• Guide the selection of research methods, data collection, and data analysis  
• Help understand the relationships between different concepts and develop hypotheses and research questions  
• Address gaps in existing literature  
• Analyze the data collected and draw meaningful conclusions and make the findings more generalizable  

Theoretical vs. Conceptual framework  

While a theoretical framework covers the theoretical aspect of your study, that is, the various theories that can guide your research, a conceptual framework defines the variables for your study and presents how they relate to each other. The conceptual framework is developed before collecting the data. However, both frameworks help in understanding the research problem and guide the development, collection, and analysis of the research.  

The following table lists some differences between conceptual and theoretical frameworks . 5

How to write a theoretical framework  

The following general steps can help those wondering how to write a theoretical framework: 2

• Identify and define the key concepts clearly and organize them into a suitable structure.  
• Use appropriate terminology and define all key terms to ensure consistency.  
• Identify the relationships between concepts and provide a logical and coherent structure.  
• Develop hypotheses that can be tested through data collection and analysis.  
• Keep it concise and focused with clear and specific aims.  

Write a theoretical framework 2x faster. Get our Manuscript Writing pack  

Examples of a theoretical framework  

Here are two examples of a theoretical framework. 6,7

Example 1 .   

An insurance company is facing a challenge cross-selling its products. The sales department indicates that most customers have just one policy, although the company offers over 10 unique policies. The company would want its customers to purchase more than one policy since most customers are purchasing policies from other companies.  

Objective : To sell more insurance products to existing customers.  

Problem : Many customers are purchasing additional policies from other companies.  

Research question : How can customer product awareness be improved to increase cross-selling of insurance products?  

Sub-questions: What is the relationship between product awareness and sales? Which factors determine product awareness?  

Since “product awareness” is the main focus in this study, the theoretical framework should analyze this concept and study previous literature on this subject and propose theories that discuss the relationship between product awareness and its improvement in sales of other products.  

Example 2 .

A company is facing a continued decline in its sales and profitability. The main reason for the decline in the profitability is poor services, which have resulted in a high level of dissatisfaction among customers and consequently a decline in customer loyalty. The management is planning to concentrate on clients’ satisfaction and customer loyalty.  

Objective: To provide better service to customers and increase customer loyalty and satisfaction.  

Problem: Continued decrease in sales and profitability.  

Research question: How can customer satisfaction help in increasing sales and profitability?  

Sub-questions: What is the relationship between customer loyalty and sales? Which factors influence the level of satisfaction gained by customers?  

Since customer satisfaction, loyalty, profitability, and sales are the important topics in this example, the theoretical framework should focus on these concepts.  

Benefits of a theoretical framework  

There are several benefits of a theoretical framework in research: 2  

• Provides a structured approach allowing researchers to organize their thoughts in a coherent way.  
• Helps to identify gaps in knowledge highlighting areas where further research is needed.  
• Increases research efficiency by providing a clear direction for research and focusing efforts on relevant data.  
• Improves the quality of research by providing a rigorous and systematic approach to research, which can increase the likelihood of producing valid and reliable results.  
• Provides a basis for comparison by providing a common language and conceptual framework for researchers to compare their findings with other research in the field, facilitating the exchange of ideas and the development of new knowledge.  

Frequently Asked Questions 

Q1. How do I develop a theoretical framework ? 7

A1. The following steps can be used for developing a theoretical framework :  

• Identify the research problem and research questions by clearly defining the problem that the research aims to address and identifying the specific questions that the research aims to answer.
• Review the existing literature to identify the key concepts that have been studied previously. These concepts should be clearly defined and organized into a structure.
• Develop propositions that describe the relationships between the concepts. These propositions should be based on the existing literature and should be testable.
• Develop hypotheses that can be tested through data collection and analysis.
• Test the theoretical framework through data collection and analysis to determine whether the framework is valid and reliable.

Q2. How do I know if I have developed a good theoretical framework or not? 8

A2. The following checklist could help you answer this question:  

• Is my theoretical framework clearly seen as emerging from my literature review?  
• Is it the result of my analysis of the main theories previously studied in my same research field?  
• Does it represent or is it relevant to the most current state of theoretical knowledge on my topic?  
• Does the theoretical framework in research present a logical, coherent, and analytical structure that will support my data analysis?  
• Do the different parts of the theory help analyze the relationships among the variables in my research?  
• Does the theoretical framework target how I will answer my research questions or test the hypotheses?  
• Have I documented every source I have used in developing this theoretical framework ?  
• Is my theoretical framework a model, a table, a figure, or a description?  
• Have I explained why this is the appropriate theoretical framework for my data analysis?  

Q3. Can I use multiple theoretical frameworks in a single study?  

A3. Using multiple theoretical frameworks in a single study is acceptable as long as each theory is clearly defined and related to the study. Each theory should also be discussed individually. This approach may, however, be tedious and effort intensive. Therefore, multiple theoretical frameworks should be used only if absolutely necessary for the study.  

Q4. Is it necessary to include a theoretical framework in every research study?  

A4. The theoretical framework connects researchers to existing knowledge. So, including a theoretical framework would help researchers get a clear idea about the research process and help structure their study effectively by clearly defining an objective, a research problem, and a research question.  

Q5. Can a theoretical framework be developed for qualitative research?  

A5. Yes, a theoretical framework can be developed for qualitative research. However, qualitative research methods may or may not involve a theory developed beforehand. In these studies, a theoretical framework can guide the study and help develop a theory during the data analysis phase. This resulting framework uses inductive reasoning. The outcome of this inductive approach can be referred to as an emergent theoretical framework . This method helps researchers develop a theory inductively, which explains a phenomenon without a guiding framework at the outset.  

Q6. What is the main difference between a literature review and a theoretical framework ?  

A6. A literature review explores already existing studies about a specific topic in order to highlight a gap, which becomes the focus of the current research study. A theoretical framework can be considered the next step in the process, in which the researcher plans a specific conceptual and analytical approach to address the identified gap in the research.  

Theoretical frameworks are thus important components of the research process and researchers should therefore devote ample amount of time to develop a solid theoretical framework so that it can effectively guide their research in a suitable direction. We hope this article has provided a good insight into the concept of theoretical frameworks in research and their benefits.  

References  

• Organizing academic research papers: Theoretical framework. Sacred Heart University library. Accessed August 4, 2023. https://library.sacredheart.edu/c.php?g=29803&p=185919#:~:text=The%20theoretical%20framework%20is%20the,research%20problem%20under%20study%20exists .  
• Salomao A. Understanding what is theoretical framework. Mind the Graph website. Accessed August 5, 2023. https://mindthegraph.com/blog/what-is-theoretical-framework/  
• Theoretical framework—Types, examples, and writing guide. Research Method website. Accessed August 6, 2023. https://researchmethod.net/theoretical-framework/  
• Grant C., Osanloo A. Understanding, selecting, and integrating a theoretical framework in dissertation research: Creating the blueprint for your “house.” Administrative Issues Journal : Connecting Education, Practice, and Research; 4(2):12-26. 2014. Accessed August 7, 2023. https://files.eric.ed.gov/fulltext/EJ1058505.pdf  
• Difference between conceptual framework and theoretical framework. MIM Learnovate website. Accessed August 7, 2023. https://mimlearnovate.com/difference-between-conceptual-framework-and-theoretical-framework/  
• Example of a theoretical framework—Thesis & dissertation. BacherlorPrint website. Accessed August 6, 2023. https://www.bachelorprint.com/dissertation/example-of-a-theoretical-framework/  
• Sample theoretical framework in dissertation and thesis—Overview and example. Students assignment help website. Accessed August 6, 2023. https://www.studentsassignmenthelp.co.uk/blogs/sample-dissertation-theoretical-framework/#Example_of_the_theoretical_framework  
• Kivunja C. Distinguishing between theory, theoretical framework, and conceptual framework: A systematic review of lessons from the field. Accessed August 8, 2023. https://files.eric.ed.gov/fulltext/EJ1198682.pdf  

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• Systematic review
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• Published: 07 August 2024

Models and frameworks for assessing the implementation of clinical practice guidelines: a systematic review

• Nicole Freitas de Mello   ORCID: orcid.org/0000-0002-5228-6691 1 , 2 ,
• Sarah Nascimento Silva   ORCID: orcid.org/0000-0002-1087-9819 3 ,
• Dalila Fernandes Gomes   ORCID: orcid.org/0000-0002-2864-0806 1 , 2 ,
• Juliana da Motta Girardi   ORCID: orcid.org/0000-0002-7547-7722 4 &
• Jorge Otávio Maia Barreto   ORCID: orcid.org/0000-0002-7648-0472 2 , 4  

Implementation Science volume  19 , Article number:  59 ( 2024 ) Cite this article

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The implementation of clinical practice guidelines (CPGs) is a cyclical process in which the evaluation stage can facilitate continuous improvement. Implementation science has utilized theoretical approaches, such as models and frameworks, to understand and address this process. This article aims to provide a comprehensive overview of the models and frameworks used to assess the implementation of CPGs.

A systematic review was conducted following the Cochrane methodology, with adaptations to the "selection process" due to the unique nature of this review. The findings were reported following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guidelines. Electronic databases were searched from their inception until May 15, 2023. A predetermined strategy and manual searches were conducted to identify relevant documents from health institutions worldwide. Eligible studies presented models and frameworks for assessing the implementation of CPGs. Information on the characteristics of the documents, the context in which the models were used (specific objectives, level of use, type of health service, target group), and the characteristics of each model or framework (name, domain evaluated, and model limitations) were extracted. The domains of the models were analyzed according to the key constructs: strategies, context, outcomes, fidelity, adaptation, sustainability, process, and intervention. A subgroup analysis was performed grouping models and frameworks according to their levels of use (clinical, organizational, and policy) and type of health service (community, ambulatorial, hospital, institutional). The JBI’s critical appraisal tools were utilized by two independent researchers to assess the trustworthiness, relevance, and results of the included studies.

Database searches yielded 14,395 studies, of which 80 full texts were reviewed. Eight studies were included in the data analysis and four methodological guidelines were additionally included from the manual search. The risk of bias in the studies was considered non-critical for the results of this systematic review. A total of ten models/frameworks for assessing the implementation of CPGs were found. The level of use was mainly policy, the most common type of health service was institutional, and the major target group was professionals directly involved in clinical practice. The evaluated domains differed between the models and there were also differences in their conceptualization. All the models addressed the domain "Context", especially at the micro level (8/12), followed by the multilevel (7/12). The domains "Outcome" (9/12), "Intervention" (8/12), "Strategies" (7/12), and "Process" (5/12) were frequently addressed, while "Sustainability" was found only in one study, and "Fidelity/Adaptation" was not observed.

Conclusions

The use of models and frameworks for assessing the implementation of CPGs is still incipient. This systematic review may help stakeholders choose or adapt the most appropriate model or framework to assess CPGs implementation based on their specific health context.

Trial registration

PROSPERO (International Prospective Register of Systematic Reviews) registration number: CRD42022335884. Registered on June 7, 2022.

Peer Review reports

Contributions to the literature

Although the number of theoretical approaches has grown in recent years, there are still important gaps to be explored in the use of models and frameworks to assess the implementation of clinical practice guidelines (CPGs). This systematic review aims to contribute knowledge to overcome these gaps.

Despite the great advances in implementation science, evaluating the implementation of CPGs remains a challenge, and models and frameworks could support improvements in this field.

This study demonstrates that the available models and frameworks do not cover all characteristics and domains necessary for a complete evaluation of CPGs implementation.

The presented findings contribute to the field of implementation science, encouraging debate on choices and adaptations of models and frameworks for implementation research and evaluation.

Substantial investments have been made in clinical research and development in recent decades, increasing the medical knowledge base and the availability of health technologies [ 1 ]. The use of clinical practice guidelines (CPGs) has increased worldwide to guide best health practices and to maximize healthcare investments. A CPG can be defined as "any formal statements systematically developed to assist practitioner and patient decisions about appropriate health care for specific clinical circumstances" [ 2 ] and has the potential to improve patient care by promoting interventions of proven benefit and discouraging ineffective interventions. Furthermore, they can promote efficiency in resource allocation and provide support for managers and health professionals in decision-making [ 3 , 4 ].

However, having a quality CPG does not guarantee that the expected health benefits will be obtained. In fact, putting these devices to use still presents a challenge for most health services across distinct levels of government. In addition to the development of guidelines with high methodological rigor, those recommendations need to be available to their users; these recommendations involve the diffusion and dissemination stages, and they need to be used in clinical practice (implemented), which usually requires behavioral changes and appropriate resources and infrastructure. All these stages involve an iterative and complex process called implementation, which is defined as the process of putting new practices within a setting into use [ 5 , 6 ].

Implementation is a cyclical process, and the evaluation is one of its key stages, which allows continuous improvement of CPGs development and implementation strategies. It consists of verifying whether clinical practice is being performed as recommended (process evaluation or formative evaluation) and whether the expected results and impact are being reached (summative evaluation) [ 7 , 8 , 9 ]. Although the importance of the implementation evaluation stage has been recognized, research on how these guidelines are implemented is scarce [ 10 ]. This paper focused on the process of assessing CPGs implementation.

To understand and improve this complex process, implementation science provides a systematic set of principles and methods to integrate research findings and other evidence-based practices into routine practice and improve the quality and effectiveness of health services and care [ 11 ]. The field of implementation science uses theoretical approaches that have varying degrees of specificity based on the current state of knowledge and are structured based on theories, models, and frameworks [ 5 , 12 , 13 ]. A "Model" is defined as "a simplified depiction of a more complex world with relatively precise assumptions about cause and effect", and a "framework" is defined as "a broad set of constructs that organize concepts and data descriptively without specifying causal relationships" [ 9 ]. Although these concepts are distinct, in this paper, their use will be interchangeable, as they are typically like checklists of factors relevant to various aspects of implementation.

There are a variety of theoretical approaches available in implementation science [ 5 , 14 ], which can make choosing the most appropriate challenging [ 5 ]. Some models and frameworks have been categorized as "evaluation models" by providing a structure for evaluating implementation endeavors [ 15 ], even though theoretical approaches from other categories can also be applied for evaluation purposes because they specify concepts and constructs that may be operationalized and measured [ 13 ]. Two frameworks that can specify implementation aspects that should be evaluated as part of intervention studies are RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) [ 16 ] and PRECEDE-PROCEED (Predisposing, Reinforcing and Enabling Constructs in Educational Diagnosis and Evaluation-Policy, Regulatory, and Organizational Constructs in Educational and Environmental Development) [ 17 ]. Although the number of theoretical approaches has grown in recent years, the use of models and frameworks to evaluate the implementation of guidelines still seems to be a challenge.

This article aims to provide a complete map of the models and frameworks applied to assess the implementation of CPGs. The aim is also to subside debate and choices on models and frameworks for the research and evaluation of the implementation processes of CPGs and thus to facilitate the continued development of the field of implementation as well as to contribute to healthcare policy and practice.

A systematic review was conducted following the Cochrane methodology [ 18 ], with adaptations to the "selection process" due to the unique nature of this review (details can be found in the respective section). The review protocol was registered in PROSPERO (registration number: CRD42022335884) on June 7, 2022. This report adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 19 ] and a completed checklist is provided in Additional File 1.

Eligibility criteria

The SDMO approach (Types of Studies, Types of Data, Types of Methods, Outcomes) [ 20 ] was utilized in this systematic review, outlined as follows:

Types of studies

All types of studies were considered for inclusion, as the assessment of CPG implementation can benefit from a diverse range of study designs, including randomized clinical trials/experimental studies, scale/tool development, systematic reviews, opinion pieces, qualitative studies, peer-reviewed articles, books, reports, and unpublished theses.

Studies were categorized based on their methodological designs, which guided the synthesis, risk of bias assessment, and presentation of results.

Study protocols and conference abstracts were excluded due to insufficient information for this review.

Types of data

Studies that evaluated the implementation of CPGs either independently or as part of a multifaceted intervention.

Guidelines for evaluating CPG implementation.

Inclusion of CPGs related to any context, clinical area, intervention, and patient characteristics.

No restrictions were placed on publication date or language.

Exclusion criteria

General guidelines were excluded, as this review focused on 'models for evaluating clinical practice guidelines implementation' rather than the guidelines themselves.

Studies that focused solely on implementation determinants as barriers and enablers were excluded, as this review aimed to explore comprehensive models/frameworks.

Studies evaluating programs and policies were excluded.

Studies that only assessed implementation strategies (isolated actions) rather than the implementation process itself were excluded.

Studies that focused solely on the impact or results of implementation (summative evaluation) were excluded.

Types of methods

Not applicable.

All potential models or frameworks for assessing the implementation of CPG (evaluation models/frameworks), as well as their characteristics: name; specific objectives; levels of use (clinical, organizational, and policy); health system (public, private, or both); type of health service (community, ambulatorial, hospital, institutional, homecare); domains or outcomes evaluated; type of recommendation evaluated; context; limitations of the model.

Model was defined as "a deliberated simplification of a phenomenon on a specific aspect" [ 21 ].

Framework was defined as "structure, overview outline, system, or plan consisting of various descriptive categories" [ 21 ].

Models or frameworks used solely for the CPG development, dissemination, or implementation phase.

Models/frameworks used solely for assessment processes other than implementation, such as for the development or dissemination phase.

Data sources and literature search

The systematic search was conducted on July 31, 2022 (and updated on May 15, 2023) in the following electronic databases: MEDLINE/PubMed, Centre for Reviews and Dissemination (CRD), the Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), EMBASE, Epistemonikos, Global Health, Health Systems Evidence, PDQ-Evidence, PsycINFO, Rx for Change (Canadian Agency for Drugs and Technologies in Health, CADTH), Scopus, Web of Science and Virtual Health Library (VHL). The Google Scholar database was used for the manual selection of studies (first 10 pages).

Additionally, hand searches were performed on the lists of references included in the systematic reviews and citations of the included studies, as well as on the websites of institutions working on CPGs development and implementation: Guidelines International Networks (GIN), National Institute for Health and Care Excellence (NICE; United Kingdom), World Health Organization (WHO), Centers for Disease Control and Prevention (CDC; USA), Institute of Medicine (IOM; USA), Australian Department of Health and Aged Care (ADH), Healthcare Improvement Scotland (SIGN), National Health and Medical Research Council (NHMRC; Australia), Queensland Health, The Joanna Briggs Institute (JBI), Ministry of Health and Social Policy of Spain, Ministry of Health of Brazil and Capes Theses and Dissertations Catalog.

The search strategy combined terms related to "clinical practice guidelines" (practice guidelines, practice guidelines as topic, clinical protocols), "implementation", "assessment" (assessment, evaluation), and "models, framework". The free term "monitoring" was not used because it was regularly related to clinical monitoring and not to implementation monitoring. The search strategies adapted for the electronic databases are presented in an additional file (see Additional file 2).

Study selection process

The results of the literature search from scientific databases, excluding the CRD database, were imported into Mendeley Reference Management software to remove duplicates. They were then transferred to the Rayyan platform ( https://rayyan.qcri.org ) [ 22 ] for the screening process. Initially, studies related to the "assessment of implementation of the CPG" were selected. The titles were first screened independently by two pairs of reviewers (first selection: four reviewers, NM, JB, SS, and JG; update: a pair of reviewers, NM and DG). The title screening was broad, including all potentially relevant studies on CPG and the implementation process. Following that, the abstracts were independently screened by the same group of reviewers. The abstract screening was more focused, specifically selecting studies that addressed CPG and the evaluation of the implementation process. In the next step, full-text articles were reviewed independently by a pair of reviewers (NM, DG) to identify those that explicitly presented "models" or "frameworks" for assessing the implementation of the CPG. Disagreements regarding the eligibility of studies were resolved through discussion and consensus, and by a third reviewer (JB) when necessary. One reviewer (NM) conducted manual searches, and the inclusion of documents was discussed with the other reviewers.

Risk of bias assessment of studies

The selected studies were independently classified and evaluated according to their methodological designs by two investigators (NM and JG). This review employed JBI’s critical appraisal tools to assess the trustworthiness, relevance and results of the included studies [ 23 ] and these tools are presented in additional files (see Additional file 3 and Additional file 4). Disagreements were resolved by consensus or consultation with the other reviewers. Methodological guidelines and noncomparative and before–after studies were not evaluated because JBI does not have specific tools for assessing these types of documents. Although the studies were assessed for quality, they were not excluded on this basis.

Data extraction

The data was independently extracted by two reviewers (NM, DG) using a Microsoft Excel spreadsheet. Discrepancies were discussed and resolved by consensus. The following information was extracted:

Document characteristics : author; year of publication; title; study design; instrument of evaluation; country; guideline context;

Usage context of the models : specific objectives; level of use (clinical, organizational, and policy); type of health service (community, ambulatorial, hospital, institutional); target group (guideline developers, clinicians; health professionals; health-policy decision-makers; health-care organizations; service managers);

Model and framework characteristics : name, domain evaluated, and model limitations.

The set of information to be extracted, shown in the systematic review protocol, was adjusted to improve the organization of the analysis.

The "level of use" refers to the scope of the model used. "Clinical" was considered when the evaluation focused on individual practices, "organizational" when practices were within a health service institution, and "policy" when the evaluation was more systemic and covered different health services or institutions.

The "type of health service" indicated the category of health service where the model/framework was used (or can be used) to assess the implementation of the CPG, related to the complexity of healthcare. "Community" is related to primary health care; "ambulatorial" is related to secondary health care; "hospital" is related to tertiary health care; and "institutional" represented models/frameworks not specific to a particular type of health service.

The "target group" included stakeholders related to the use of the model/framework for evaluating the implementation of the CPG, such as clinicians, health professionals, guideline developers, health policy-makers, health organizations, and service managers.

The category "health system" (public, private, or both) mentioned in the systematic review protocol was not found in the literature obtained and was removed as an extraction variable. Similarly, the variables "type of recommendation evaluated" and "context" were grouped because the same information was included in the "guideline context" section of the study.

Some selected documents presented models or frameworks recognized by the scientific field, including some that were validated. However, some studies adapted the model to this context. Therefore, the domain analysis covered all models or frameworks domains evaluated by (or suggested for evaluation by) the document analyzed.

Data analysis and synthesis

The results were tabulated using narrative synthesis with an aggregative approach, without meta-analysis, aiming to summarize the documents descriptively for the organization, description, interpretation and explanation of the study findings [ 24 , 25 ].

The model/framework domains evaluated in each document were studied according to Nilsen et al.’s constructs: "strategies", "context", "outcomes", "fidelity", "adaptation" and "sustainability". For this study, "strategies" were described as structured and planned initiatives used to enhance the implementation of clinical practice [ 26 ].

The definition of "context" varies in the literature. Despite that, this review considered it as the set of circumstances or factors surrounding a particular implementation effort, such as organizational support, financial resources, social relations and support, leadership, and organizational culture [ 26 , 27 ]. The domain "context" was subdivided according to the level of health care into "micro" (individual perspective), "meso" (organizational perspective), "macro" (systemic perspective), and "multiple" (when there is an issue involving more than one level of health care).

The "outcomes" domain was related to the results of the implementation process (unlike clinical outcomes) and was stratified according to the following constructs: acceptability, appropriateness, feasibility, adoption, cost, and penetration. All these concepts align with the definitions of Proctor et al. (2011), although we decided to separate "fidelity" and "sustainability" as independent domains similar to Nilsen [ 26 , 28 ].

"Fidelity" and "adaptation" were considered the same domain, as they are complementary pieces of the same issue. In this study, implementation fidelity refers to how closely guidelines are followed as intended by their developers or designers. On the other hand, adaptation involves making changes to the content or delivery of a guideline to better fit the needs of a specific context. The "sustainability" domain was defined as evaluations about the continuation or permanence over time of the CPG implementation.

Additionally, the domain "process" was utilized to address issues related to the implementation process itself, rather than focusing solely on the outcomes of the implementation process, as done by Wang et al. [ 14 ]. Furthermore, the "intervention" domain was introduced to distinguish aspects related to the CPG characteristics that can impact its implementation, such as the complexity of the recommendation.

A subgroup analysis was performed with models and frameworks categorized based on their levels of use (clinical, organizational, and policy) and the type of health service (community, ambulatorial, hospital, institutional) associated with the CPG. The goal is to assist stakeholders (politicians, clinicians, researchers, or others) in selecting the most suitable model for evaluating CPG implementation based on their specific health context.

Search results

Database searches yielded 26,011 studies, of which 107 full texts were reviewed. During the full-text review, 99 articles were excluded: 41 studies did not mention a model or framework for assessing the implementation of the CPG, 31 studies evaluated only implementation strategies (isolated actions) rather than the implementation process itself, and 27 articles were not related to the implementation assessment. Therefore, eight studies were included in the data analysis. The updated search did not reveal additional relevant studies. The main reason for study exclusion was that they did not use models or frameworks to assess CPG implementation. Additionally, four methodological guidelines were included from the manual search (Fig.  1 ).

PRISMA diagram. Acronyms: ADH—Australian Department of Health, CINAHL—Cumulative Index to Nursing and Allied Health Literature, CDC—Centers for Disease Control and Prevention, CRD—Centre for Reviews and Dissemination, GIN—Guidelines International Networks, HSE—Health Systems Evidence, IOM—Institute of Medicine, JBI—The Joanna Briggs Institute, MHB—Ministry of Health of Brazil, NICE—National Institute for Health and Care Excellence, NHMRC—National Health and Medical Research Council, MSPS – Ministerio de Sanidad Y Política Social (Spain), SIGN—Scottish Intercollegiate Guidelines Network, VHL – Virtual Health Library, WHO—World Health Organization. Legend: Reason A –The study evaluated only implementation strategies (isolated actions) rather than the implementation process itself. Reason B – The study did not mention a model or framework for assessing the implementation of the intervention. Reason C – The study was not related to the implementation assessment. Adapted from Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. https://doi.org/10.1136/bmj.n71 . For more information, visit:

According to the JBI’s critical appraisal tools, the overall assessment of the studies indicates their acceptance for the systematic review.

The cross-sectional studies lacked clear information regarding "confounding factors" or "strategies to address confounding factors". This was understandable given the nature of the study, where such details are not typically included. However, the reviewers did not find this lack of information to be critical, allowing the studies to be included in the review. The results of this methodological quality assessment can be found in an additional file (see Additional file 5).

In the qualitative studies, there was some ambiguity regarding the questions: "Is there a statement locating the researcher culturally or theoretically?" and "Is the influence of the researcher on the research, and vice versa, addressed?". However, the reviewers decided to include the studies and deemed the methodological quality sufficient for the analysis in this article, based on the other information analyzed. The results of this methodological quality assessment can be found in an additional file (see Additional file 6).

Documents characteristics (Table  1 )

The documents were directed to several continents: Australia/Oceania (4/12) [ 31 , 33 , 36 , 37 ], North America (4/12 [ 30 , 32 , 38 , 39 ], Europe (2/12 [ 29 , 35 ] and Asia (2/12) [ 34 , 40 ]. The types of documents were classified as cross-sectional studies (4/12) [ 29 , 32 , 34 , 38 ], methodological guidelines (4/12) [ 33 , 35 , 36 , 37 ], mixed methods studies (3/12) [ 30 , 31 , 39 ] or noncomparative studies (1/12) [ 40 ]. In terms of the instrument of evaluation, most of the documents used a survey/questionnaire (6/12) [ 29 , 30 , 31 , 32 , 34 , 38 ], while three (3/12) used qualitative instruments (interviews, group discussions) [ 30 , 31 , 39 ], one used a checklist [ 37 ], one used an audit [ 33 ] and three (3/12) did not define a specific instrument to measure [ 35 , 36 , 40 ].

Considering the clinical areas covered, most studies evaluated the implementation of nonspecific (general) clinical areas [ 29 , 33 , 35 , 36 , 37 , 40 ]. However, some studies focused on specific clinical contexts, such as mental health [ 32 , 38 ], oncology [ 39 ], fall prevention [ 31 ], spinal cord injury [ 30 ], and sexually transmitted infections [ 34 ].

Usage context of the models (Table  1 )

Specific objectives.

All the studies highlighted the purpose of guiding the process of evaluating the implementation of CPGs, even if they evaluated CPGs from generic or different clinical areas.

Levels of use

The most common level of use of the models/frameworks identified to assess the implementation of CPGs was policy (6/12) [ 33 , 35 , 36 , 37 , 39 , 40 ]. In this level, the model is used in a systematic way to evaluate all the processes involved in CPGs implementation and is primarily related to methodological guidelines. This was followed by the organizational level of use (5/12) [ 30 , 31 , 32 , 38 , 39 ], where the model is used to evaluate the implementation of CPGs in a specific institution, considering its specific environment. Finally, the clinical level of use (2/12) [ 29 , 34 ] focuses on individual practice and the factors that can influence the implementation of CPGs by professionals.

Type of health service

Institutional services were predominant (5/12) [ 33 , 35 , 36 , 37 , 40 ] and included methodological guidelines and a study of model development and validation. Hospitals were the second most common type of health service (4/12) [ 29 , 30 , 31 , 34 ], followed by ambulatorial (2/12) [ 32 , 34 ] and community health services (1/12) [ 32 ]. Two studies did not specify which type of health service the assessment addressed [ 38 , 39 ].

Target group

The focus of the target group was professionals directly involved in clinical practice (6/12) [ 29 , 31 , 32 , 34 , 38 , 40 ], namely, health professionals and clinicians. Other less related stakeholders included guideline developers (2/12) [ 39 , 40 ], health policy decision makers (1/12) [ 39 ], and healthcare organizations (1/12) [ 39 ]. The target group was not defined in the methodological guidelines, although all the mentioned stakeholders could be related to these documents.

Model and framework characteristics

Models and frameworks for assessing the implementation of cpgs.

The Consolidated Framework for Implementation Research (CFIR) [ 31 , 38 ] and the Promoting Action on Research Implementation in Health Systems (PARiHS) framework [ 29 , 30 ] were the most commonly employed frameworks within the selected documents. The other models mentioned were: Goal commitment and implementation of practice guidelines framework [ 32 ]; Guideline to identify key indicators [ 35 ]; Guideline implementation checklist [ 37 ]; Guideline implementation evaluation tool [ 40 ]; JBI Implementation Framework [ 33 ]; Reach, effectiveness, adoption, implementation and maintenance (RE-AIM) framework [ 34 ]; The Guideline Implementability Framework [ 39 ] and an unnamed model [ 36 ].

Domains evaluated

The number of domains evaluated (or suggested for evaluation) by the documents varied between three and five, with the majority focusing on three domains. All the models addressed the domain "context", with a particular emphasis on the micro level of the health care context (8/12) [ 29 , 31 , 34 , 35 , 36 , 37 , 38 , 39 ], followed by the multilevel (7/12) [ 29 , 31 , 32 , 33 , 38 , 39 , 40 ], meso level (4/12) [ 30 , 35 , 39 , 40 ] and macro level (2/12) [ 37 , 39 ]. The "Outcome" domain was evaluated in nine models. Within this domain, the most frequently evaluated subdomain was "adoption" (6/12) [ 29 , 32 , 34 , 35 , 36 , 37 ], followed by "acceptability" (4/12) [ 30 , 32 , 35 , 39 ], "appropriateness" (3/12) [ 32 , 34 , 36 ], "feasibility" (3/12) [ 29 , 32 , 36 ], "cost" (1/12) [ 35 ] and "penetration" (1/12) [ 34 ]. Regarding the other domains, "Intervention" (8/12) [ 29 , 31 , 34 , 35 , 36 , 38 , 39 , 40 ], "Strategies" (7/12) [ 29 , 30 , 33 , 35 , 36 , 37 , 40 ] and "Process" (5/12) [ 29 , 31 , 32 , 33 , 38 ] were frequently addressed in the models, while "Sustainability" (1/12) [ 34 ] was only found in one model, and "Fidelity/Adaptation" was not observed. The domains presented by the models and frameworks and evaluated in the documents are shown in Table  2 .

Limitations of the models

Only two documents mentioned limitations in the use of the model or frameworks. These two studies reported limitations in the use of CFIR: "is complex and cumbersome and requires tailoring of the key variables to the specific context", and "this framework should be supplemented with other important factors and local features to achieve a sound basis for the planning and realization of an ongoing project" [ 31 , 38 ]. Limitations in the use of other models or frameworks are not reported.

Subgroup analysis

Following the subgroup analysis (Table  3 ), five different models/frameworks were utilized at the policy level by institutional health services. These included the Guideline Implementation Evaluation Tool [ 40 ], the NHMRC tool (model name not defined) [ 36 ], the JBI Implementation Framework + GRiP [ 33 ], Guideline to identify key indicators [ 35 ], and the Guideline implementation checklist [ 37 ]. Additionally, the "Guideline Implementability Framework" [ 39 ] was implemented at the policy level without restrictions based on the type of health service. Regarding the organizational level, the models used varied depending on the type of service. The "Goal commitment and implementation of practice guidelines framework" [ 32 ] was applied in community and ambulatory health services, while "PARiHS" [ 29 , 30 ] and "CFIR" [ 31 , 38 ] were utilized in hospitals. In contexts where the type of health service was not defined, "CFIR" [ 31 , 38 ] and "The Guideline Implementability Framework" [ 39 ] were employed. Lastly, at the clinical level, "RE-AIM" [ 34 ] was utilized in ambulatory and hospital services, and PARiHS [ 29 , 30 ] was specifically used in hospital services.

Key findings

This systematic review identified 10 models/ frameworks used to assess the implementation of CPGs in various health system contexts. These documents shared similar objectives in utilizing models and frameworks for assessment. The primary level of use was policy, the most common type of health service was institutional, and the main target group of the documents was professionals directly involved in clinical practice. The models and frameworks presented varied analytical domains, with sometimes divergent concepts used in these domains. This study is innovative in its emphasis on the evaluation stage of CPG implementation and in summarizing aspects and domains aimed at the practical application of these models.

The small number of documents contrasts with studies that present an extensive range of models and frameworks available in implementation science. The findings suggest that the use of models and frameworks to evaluate the implementation of CPGs is still in its early stages. Among the selected documents, there was a predominance of cross-sectional studies and methodological guidelines, which strongly influenced how the implementation evaluation was conducted. This was primarily done through surveys/questionnaires, qualitative methods (interviews, group discussions), and non-specific measurement instruments. Regarding the subject areas evaluated, most studies focused on a general clinical area, while others explored different clinical areas. This suggests that the evaluation of CPG implementation has been carried out in various contexts.

The models were chosen independently of the categories proposed in the literature, with their usage categorized for purposes other than implementation evaluation, as is the case with CFIR and PARiHS. This practice was described by Nilsen et al. who suggested that models and frameworks from other categories can also be applied for evaluation purposes because they specify concepts and constructs that may be operationalized and measured [ 14 , 15 , 42 , 43 ].

The results highlight the increased use of models and frameworks in evaluation processes at the policy level and institutional environments, followed by the organizational level in hospital settings. This finding contradicts a review that reported the policy level as an area that was not as well studied [ 44 ]. The use of different models at the institutional level is also emphasized in the subgroup analysis. This may suggest that the greater the impact (social, financial/economic, and organizational) of implementing CPGs, the greater the interest and need to establish well-defined and robust processes. In this context, the evaluation stage stands out as crucial, and the investment of resources and efforts to structure this stage becomes even more advantageous [ 10 , 45 ]. Two studies (16,7%) evaluated the implementation of CPGs at the individual level (clinical level). These studies stand out for their potential to analyze variations in clinical practice in greater depth.

In contrast to the level of use and type of health service most strongly indicated in the documents, with systemic approaches, the target group most observed was professionals directly involved in clinical practice. This suggests an emphasis on evaluating individual behaviors. This same emphasis is observed in the analysis of the models, in which there is a predominance of evaluating the micro level of the health context and the "adoption" subdomain, in contrast with the sub-use of domains such as "cost" and "process". Cassetti et al. observed the same phenomenon in their review, in which studies evaluating the implementation of CPGs mainly adopted a behavioral change approach to tackle those issues, without considering the influence of wider social determinants of health [ 10 ]. However, the literature widely reiterates that multiple factors impact the implementation of CPGs, and different actions are required to make them effective [ 6 , 46 , 47 ]. As a result, there is enormous potential for the development and adaptation of models and frameworks aimed at more systemic evaluation processes that consider institutional and organizational aspects.

In analyzing the model domains, most models focused on evaluating only some aspects of implementation (three domains). All models evaluated the "context", highlighting its significant influence on implementation [ 9 , 26 ]. Context is an essential effect modifier for providing research evidence to guide decisions on implementation strategies [ 48 ]. Contextualizing a guideline involves integrating research or other evidence into a specific circumstance [ 49 ]. The analysis of this domain was adjusted to include all possible contextual aspects, even if they were initially allocated to other domains. Some contextual aspects presented by the models vary in comprehensiveness, such as the assessment of the "timing and nature of stakeholder engagement" [ 39 ], which includes individual engagement by healthcare professionals and organizational involvement in CPG implementation. While the importance of context is universally recognized, its conceptualization and interpretation differ across studies and models. This divergence is also evident in other domains, consistent with existing literature [ 14 ]. Efforts to address this conceptual divergence in implementation science are ongoing, but further research and development are needed in this field [ 26 ].

The main subdomain evaluated was "adoption" within the outcome domain. This may be attributed to the ease of accessing information on the adoption of the CPG, whether through computerized system records, patient records, or self-reports from healthcare professionals or patients themselves. The "acceptability" subdomain pertains to the perception among implementation stakeholders that a particular CPG is agreeable, palatable or satisfactory. On the other hand, "appropriateness" encompasses the perceived fit, relevance or compatibility of the CPG for a specific practice setting, provider, or consumer, or its perceived fit to address a particular issue or problem [ 26 ]. Both subdomains are subjective and rely on stakeholders' interpretations and perceptions of the issue being analyzed, making them susceptible to reporting biases. Moreover, obtaining this information requires direct consultation with stakeholders, which can be challenging for some evaluation processes, particularly in institutional contexts.

The evaluation of the subdomains "feasibility" (the extent to which a CPG can be successfully used or carried out within a given agency or setting), "cost" (the cost impact of an implementation effort), and "penetration" (the extent to which an intervention or treatment is integrated within a service setting and its subsystems) [ 26 ] was rarely observed in the documents. This may be related to the greater complexity of obtaining information on these aspects, as they involve cross-cutting and multifactorial issues. In other words, it would be difficult to gather this information during evaluations with health practitioners as the target group. This highlights the need for evaluation processes of CPGs implementation involving multiple stakeholders, even if the evaluation is adjusted for each of these groups.

Although the models do not establish the "intervention" domain, we thought it pertinent in this study to delimit the issues that are intrinsic to CPGs, such as methodological quality or clarity in establishing recommendations. These issues were quite common in the models evaluated but were considered in other domains (e.g., in "context"). Studies have reported the importance of evaluating these issues intrinsic to CPGs [ 47 , 50 ] and their influence on the implementation process [ 51 ].

The models explicitly present the "strategies" domain, and its evaluation was usually included in the assessments. This is likely due to the expansion of scientific and practical studies in implementation science that involve theoretical approaches to the development and application of interventions to improve the implementation of evidence-based practices. However, these interventions themselves are not guaranteed to be effective, as reported in a previous review that showed unclear results indicating that the strategies had affected successful implementation [ 52 ]. Furthermore, model domains end up not covering all the complexity surrounding the strategies and their development and implementation process. For example, the ‘Guideline implementation evaluation tool’ evaluates whether guideline developers have designed and provided auxiliary tools to promote the implementation of guidelines [ 40 ], but this does not mean that these tools would work as expected.

The "process" domain was identified in the CFIR [ 31 , 38 ], JBI/GRiP [ 33 ], and PARiHS [ 29 ] frameworks. While it may be included in other domains of analysis, its distinct separation is crucial for defining operational issues when assessing the implementation process, such as determining if and how the use of the mentioned CPG was evaluated [ 3 ]. Despite its presence in multiple models, there is still limited detail in the evaluation guidelines, which makes it difficult to operationalize the concept. Further research is needed to better define the "process" domain and its connections and boundaries with other domains.

The domain of "sustainability" was only observed in the RE-AIM framework, which is categorized as an evaluation framework [ 34 ]. In its acronym, the letter M stands for "maintenance" and corresponds to the assessment of whether the user maintains use, typically longer than 6 months. The presence of this domain highlights the need for continuous evaluation of CPGs implementation in the short, medium, and long term. Although the RE-AIM framework includes this domain, it was not used in the questionnaire developed in the study. One probable reason is that the evaluation of CPGs implementation is still conducted on a one-off basis and not as a continuous improvement process. Considering that changes in clinical practices are inherent over time, evaluating and monitoring changes throughout the duration of the CPG could be an important strategy for ensuring its implementation. This is an emerging field that requires additional investment and research.

The "Fidelity/Adaptation" domain was not observed in the models. These emerging concepts involve the extent to which a CPG is being conducted exactly as planned or whether it is undergoing adjustments and adaptations. Whether or not there is fidelity or adaptation in the implementation of CPGs does not presuppose greater or lesser effectiveness; after all, some adaptations may be necessary to implement general CPGs in specific contexts. The absence of this domain in all the models and frameworks may suggest that they are not relevant aspects for evaluating implementation or that there is a lack of knowledge of these complex concepts. This may suggest difficulty in expressing concepts in specific evaluative questions. However, further studies are warranted to determine the comprehensiveness of these concepts.

It is important to note the customization of the domains of analysis, with some domains presented in the models not being evaluated in the studies, while others were complementarily included. This can be seen in Jeong et al. [ 34 ], where the "intervention" domain in the evaluation with the RE-AIM framework reinforced the aim of theoretical approaches such as guiding the process and not determining norms. Despite this, few limitations were reported for the models, suggesting that the use of models in these studies reflects the application of these models to defined contexts without a deep critical analysis of their domains.

Limitations

This review has several limitations. First, only a few studies and methodological guidelines that explicitly present models and frameworks for assessing the implementation of CPGs have been found. This means that few alternative models could be analyzed and presented in this review. Second, this review adopted multiple analytical categories (e.g., level of use, health service, target group, and domains evaluated), whose terminology has varied enormously in the studies and documents selected, especially for the "domains evaluated" category. This difficulty in harmonizing the taxonomy used in the area has already been reported [ 26 ] and has significant potential to confuse. For this reason, studies and initiatives are needed to align understandings between concepts and, as far as possible, standardize them. Third, in some studies/documents, the information extracted was not clear about the analytical category. This required an in-depth interpretative process of the studies, which was conducted in pairs to avoid inappropriate interpretations.

Implications

This study contributes to the literature and clinical practice management by describing models and frameworks specifically used to assess the implementation of CPGs based on their level of use, type of health service, target group related to the CPG, and the evaluated domains. While there are existing reviews on the theories, frameworks, and models used in implementation science, this review addresses aspects not previously covered in the literature. This valuable information can assist stakeholders (such as politicians, clinicians, researchers, etc.) in selecting or adapting the most appropriate model to assess CPG implementation based on their health context. Furthermore, this study is expected to guide future research on developing or adapting models to assess the implementation of CPGs in various contexts.

The use of models and frameworks to evaluate the implementation remains a challenge. Studies should clearly state the level of model use, the type of health service evaluated, and the target group. The domains evaluated in these models may need adaptation to specific contexts. Nevertheless, utilizing models to assess CPGs implementation is crucial as they can guide a more thorough and systematic evaluation process, aiding in the continuous improvement of CPGs implementation. The findings of this systematic review offer valuable insights for stakeholders in selecting or adjusting models and frameworks for CPGs evaluation, supporting future theoretical advancements and research.

Availability of data and materials

Abbreviations.

Australian Department of Health and Aged Care

Canadian Agency for Drugs and Technologies in Health

Centers for Disease Control and

Consolidated Framework for Implementation Research

Cumulative Index to Nursing and Allied Health Literature

Clinical practice guideline

Centre for Reviews and Dissemination

Guidelines International Networks

Getting Research into Practice

Health Systems Evidence

Institute of Medicine

The Joanna Briggs Institute

Ministry of Health of Brazil

Ministerio de Sanidad y Política Social

National Health and Medical Research Council

National Institute for Health and Care Excellence

Promoting action on research implementation in health systems framework

Predisposing, Reinforcing and Enabling Constructs in Educational Diagnosis and Evaluation-Policy, Regulatory, and Organizational Constructs in Educational and Environmental Development

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

International Prospective Register of Systematic Reviews

Reach, effectiveness, adoption, implementation, and maintenance framework

Healthcare Improvement Scotland

United States of America

Virtual Health Library

World Health Organization

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This study is supported by the Fundação de Apoio à Pesquisa do Distrito Federal (FAPDF). FAPDF Award Term (TOA) nº 44/2024—FAPDF/SUCTI/COOBE (SEI/GDF – Process 00193–00000404/2024–22). The content in this article is solely the responsibility of the authors and does not necessarily represent the official views of the FAPDF.

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NFM and JOMB conceived the idea and the protocol for this study. NFM conducted the literature search. NFM, SNS, JMG and JOMB conducted the data collection with advice and consensus gathering from JOMB. The NFM and JMG assessed the quality of the studies. NFM and DFG conducted the data extraction. NFM performed the analysis and synthesis of the results with advice and consensus gathering from JOMB. NFM drafted the manuscript. JOMB critically revised the first version of the manuscript. All the authors revised and approved the submitted version.

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13012_2024_1389_moesm1_esm.docx.

Additional file 1: PRISMA checklist. Description of data: Completed PRISMA checklist used for reporting the results of this systematic review.

Additional file 2: Literature search. Description of data: The search strategies adapted for the electronic databases.

13012_2024_1389_moesm3_esm.doc.

Additional file 3: JBI’s critical appraisal tools for cross-sectional studies. Description of data: JBI’s critical appraisal tools to assess the trustworthiness, relevance, and results of the included studies. This is specific for cross-sectional studies.

13012_2024_1389_MOESM4_ESM.doc

Additional file 4: JBI’s critical appraisal tools for qualitative studies. Description of data: JBI’s critical appraisal tools to assess the trustworthiness, relevance, and results of the included studies. This is specific for qualitative studies.

13012_2024_1389_MOESM5_ESM.doc

Additional file 5: Methodological quality assessment results for cross-sectional studies. Description of data: Methodological quality assessment results for cross-sectional studies using JBI’s critical appraisal tools.

13012_2024_1389_MOESM6_ESM.doc

Additional file 6: Methodological quality assessment results for the qualitative studies. Description of data: Methodological quality assessment results for qualitative studies using JBI’s critical appraisal tools.

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Freitas de Mello, N., Nascimento Silva, S., Gomes, D.F. et al. Models and frameworks for assessing the implementation of clinical practice guidelines: a systematic review. Implementation Sci 19 , 59 (2024). https://doi.org/10.1186/s13012-024-01389-1

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Theoretical Framework Example for a Thesis or Dissertation

Published on October 14, 2015 by Sarah Vinz . Revised on July 18, 2023 by Tegan George.

Your theoretical framework defines the key concepts in your research, suggests relationships between them, and discusses relevant theories based on your literature review .

A strong theoretical framework gives your research direction. It allows you to convincingly interpret, explain, and generalize from your findings and show the relevance of your thesis or dissertation topic in your field.

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Sample problem statement and research questions, sample theoretical framework, your theoretical framework, other interesting articles.

Your theoretical framework is based on:

• Your problem statement
• Your research questions
• Your literature review

A new boutique downtown is struggling with the fact that many of their online customers do not return to make subsequent purchases. This is a big issue for the otherwise fast-growing store.Management wants to increase customer loyalty. They believe that improved customer satisfaction will play a major role in achieving their goal of increased return customers.

To investigate this problem, you have zeroed in on the following problem statement, objective, and research questions:

• Problem : Many online customers do not return to make subsequent purchases.
• Objective : To increase the quantity of return customers.
• Research question : How can the satisfaction of the boutique’s online customers be improved in order to increase the quantity of return customers?

The concepts of “customer loyalty” and “customer satisfaction” are clearly central to this study, along with their relationship to the likelihood that a customer will return. Your theoretical framework should define these concepts and discuss theories about the relationship between these variables.

Some sub-questions could include:

• What is the relationship between customer loyalty and customer satisfaction?
• How satisfied and loyal are the boutique’s online customers currently?
• What factors affect the satisfaction and loyalty of the boutique’s online customers?

As the concepts of “loyalty” and “customer satisfaction” play a major role in the investigation and will later be measured, they are essential concepts to define within your theoretical framework .

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Below is a simplified example showing how you can describe and compare theories in your thesis or dissertation . In this example, we focus on the concept of customer satisfaction introduced above.

Customer satisfaction

Thomassen (2003, p. 69) defines customer satisfaction as “the perception of the customer as a result of consciously or unconsciously comparing their experiences with their expectations.” Kotler & Keller (2008, p. 80) build on this definition, stating that customer satisfaction is determined by “the degree to which someone is happy or disappointed with the observed performance of a product in relation to his or her expectations.”

Performance that is below expectations leads to a dissatisfied customer, while performance that satisfies expectations produces satisfied customers (Kotler & Keller, 2003, p. 80).

The definition of Zeithaml and Bitner (2003, p. 86) is slightly different from that of Thomassen. They posit that “satisfaction is the consumer fulfillment response. It is a judgement that a product or service feature, or the product of service itself, provides a pleasurable level of consumption-related fulfillment.” Zeithaml and Bitner’s emphasis is thus on obtaining a certain satisfaction in relation to purchasing.

Thomassen’s definition is the most relevant to the aims of this study, given the emphasis it places on unconscious perception. Although Zeithaml and Bitner, like Thomassen, say that customer satisfaction is a reaction to the experience gained, there is no distinction between conscious and unconscious comparisons in their definition.

The boutique claims in its mission statement that it wants to sell not only a product, but also a feeling. As a result, unconscious comparison will play an important role in the satisfaction of its customers. Thomassen’s definition is therefore more relevant.

Thomassen’s Customer Satisfaction Model

According to Thomassen, both the so-called “value proposition” and other influences have an impact on final customer satisfaction. In his satisfaction model (Fig. 1), Thomassen shows that word-of-mouth, personal needs, past experiences, and marketing and public relations determine customers’ needs and expectations.

These factors are compared to their experiences, with the interplay between expectations and experiences determining a customer’s satisfaction level. Thomassen’s model is important for this study as it allows us to determine both the extent to which the boutique’s customers are satisfied, as well as where improvements can be made.

Figure 1 Customer satisfaction creation 

Of course, you could analyze the concepts more thoroughly and compare additional definitions to each other. You could also discuss the theories and ideas of key authors in greater detail and provide several models to illustrate different concepts.

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The Difference Between Theory, Theoretical, and Conceptual Frameworks

Authors: Geoffrey V. Stetson, MD Editors: Gregory Ow, MD

Read Time: 7 min

Unlock expert-endorsed insights for free. Or read on and we'll meet you at the end!

Introduction, what's the buzz about.

The terms "theory," "theoretical framework," and "conceptual framework" are often used interchangeably, yet they have different meanings depending on who you ask.

In medical education research, these terms play a critical role in research and scholarly discussions.

Two main camps: Lumpers and Splitters

There are generally two schools of thought regarding these terms:

• The Lumpers : This camp, which created by Dr. Georges Bordage, believes that all these terms can be encompassed within the idea of "conceptual frameworks." Bordage's approach refrains from making clear distinctions between these terms.
• The Splitters : This camp, represented by scholars like Varpio et al., put forward distinct definitions for each term and how they contribute differently to research and problem-solving.

Both camps agree on one thing: the significance of having an organizing principle in the realm of medical education research.

The purpose of this lesson

This lesson will dive into these two perspectives, explore their implications, and offer guidance on which approach might be best suited for you, depending on your level of expertise in medical education research.

Understanding the "Lumpers": the Bordage approach

The bordage approach: all under one roof.

Dr. Georges Bordage authored a seminal paper titled "Conceptual Frameworks to Illuminate and Magnify." In this paper, he avoids making a sharp distinction between theory, theoretical framework, and conceptual framework.

In Bordage's view, everything falls into the bucket of "conceptual frameworks." According to his paper, these frameworks serve two primary functions: they act as "lighthouses and lenses."

Lighthouses and lenses: an analogy

Dr. Bordage uses vivid metaphors to describe conceptual frameworks. He likens them to lighthouses that illuminate specific parts of the academic "ocean," highlighting certain issues while leaving others in the dark.

Similarly, conceptual frameworks also act like magnifying glasses, zeroing in on specific elements of a research question or problem. (See Why Your Medical Education Research Needs Theory )

What does this mean for you?

At MedEdMENTOR, we find Bordage's metaphors so compelling that they inspired our logo—a telescope, representing a series of lenses aimed at helping you navigate the universe of medical education.

If you're a beginner in medical education research, Bordage's approach provides a simplified, unified way to structure your academic inquiries. (However, note that we are actually Splitters here, since we have a Theory Database , not a "Conceptual Frameworks Database")

Introducing the "Splitters": the need for distinction

The alternative camp.

Welcome to the camp of the "Splitters," the group of scholars and educators who seek to differentiate between theory, theoretical framework, and conceptual framework. This camp aims to provide more nuanced tools for the design and interpretation of research in medical education.

The gold standard: Varpio et al.

In the paper "The Distinctions Between Theory, Theoretical Framework, and Conceptual Framework," Varpio et al. have set what is currently considered the gold standard for understanding these differences. This work is highly revered at MedEdMENTOR, and we recommend it as essential reading for anyone deeply involved in medical education research.

Breaking down the distinctions

Varpio and colleagues offer clear definitions for each term:

• Theory : An abstract set of interrelated ideas and concepts that help to organize the complexities of our reality. (e.g. Theory Database )
• Theoretical Framework : The application of that abstract mental model (i.e., theory) to a real-world problem. It is what happens when you "map" a theory onto a specific research question or phenomenon.
• Conceptual Framework : This is the rationale for applying a particular theory to a particular problem. It provides the argument, backed by literature review and methodology, to persuade an audience that the chosen approach is sound.

Why is this important?

We won't speak for everyone, but generally the "Splitters" believe that by distinguishing between these elements, you can achieve greater clarity in your research endeavors. This enables not just rigorous analysis but also enhances the communicative power of your work, making it easier for peers to engage with and build upon it.

What both camps agree on: the importance of organizing principles

A universal agreement.

Despite differences in their approaches to delineating theory, theoretical framework, and conceptual framework, both the "Lumpers" and "Splitters" agree on one crucial point: the importance of having some form of organizing principle in your research.

Why organizing principles matter

In the complex field of medical education, a set of organizing principles is indispensable for two main reasons:

• Complexity of research problems : The issues addressed in medical education research are complex, necessitating a structure to ensure that research intentions are well-organized and reasonable.
• Clear communication : These principles, whether you call them theories or frameworks, help scholars communicate more clearly, allowing for the construction of a communal body of literature that advances the field.

Navigating your path: practical advice

For beginners: start simple.

If you are new to medical education research, it might be best to start by aligning with the "Lumpers." At this stage, it may be more practical to refer to everything as a conceptual framework as you get your footing.

For the experienced: seek refinement

For those who are more comfortable with these terms and have some experience in medical education research, revisiting this topic with the distinctions offered by the "Splitters," can add nuanced understanding and precision to your work.

(At MedEdMENTOR we're splitters, which is why we have a Theory Database and not a "Conceptual Frameworks Database.")

Consult a mentor

If you have a research mentor, don't hesitate to consult them on this matter. They can provide valuable insights based on their own experience and the prevailing views in your specific research community.

A walkthrough of applying these terms in research

Introduction to the example.

Let's consider a real-world example to better understand how these terms—theory, theoretical framework, and conceptual framework—come into play during the research process.

Step 1: Identifying the problem

Suppose an internal medicine clerkship director wants to improve medical students' oral presentation skills. Identifying a clear problem or issue is the starting point for any research endeavor.

Step 2: Selecting a theory

Before diving into possible solutions, our clerkship director consults existing theories to guide her approach. She turns to MedEdMENTOR and finds a list of theories that might be relevant. As she reads the summaries of the various frameworks, she found many that might be applicable, including:

• 4-Component Instructional Design Model
• Cognitive Load Theory
• ADDIE Model
• Kern's Model of Curriculum Development
• Bloom's Taxonomy
• Deliberate Practice Theory
• Dreyfus (Five-Stage) Model of Skill Acquisition
• Joplin’s Five-Stage Model of Experiential Learning
• Communities of practice
• Mastery Learning
• Miller’s Pyramid of Skill Development
• R2C2 Feedback Model
• Zone of Proximal Development

She found a few that she found most appealing and dove deeper into reading about them from the resources she found on their theory pages.

Step 3: Crafting the theoretical framework

After some reading and consideration, the director designed the following curriculum:

• A peer-to-peer teaching and learning model built upon the concepts of Communities of practice , Andragogy , and Peer Assessment .
• The learners are given the basic structure of a group that is tasked with raising the skill level of every member. They are expected to set their own group and individual goals, support one another, and give each other meaningful feedback.
• To assist with setting goals and making meaningful progress, the learners are introduced to the concepts of Deliberate Practice Theory and Dreyfus (Five-Stage) Model of Skill Acquisition .
• Along with the explanation of the Drefyus Model, students are also provided with a clinical case as well as video examples of oral presentations based on the clinical case representing the 5 different stages of skill level (novice, advanced beginner, competent, proficient, and expert).

This is her theoretical framework—applying theories to a real-world problem.

Step 4: Developing the conceptual framework

To justify her approach, the director crafts her conceptual framework—the argument for why her chosen theoretical framework is both relevant and effective. Her rationale:

• She chose Communities of practice , Andragogy , and Peer Assessment because she finds that students learn very well from one another, and they seem to be much more motivated when they are setting their own goals and working towards something they care about. The papers she read on these topics supported these ideas.
• She chose Deliberate Practice Theory and Dreyfus (Five-Stage) Model of Skill Acquisition because these two models seemed particularly relevant to help provide these students with scaffolding to approach their work with intent. The deliberate practice theory seemed appropriate to help the students break down the tasks into pieces and focus on specific goals as opposed to blind repetition of tasks. The Dreyfus Model and the video examples provide tangible targets that learners can use to benchmark their learning objectives.

Step 4: Executing the research

With a well-defined problem, theory, theoretical framework, and conceptual framework, our clerkship director is ready to begin her research.

Learners are told they will not be evaluated based on any of their work in these groups, however, they are asked if they are willing to have their group work videotaped and analyzed to see if the theories that were employed to create this curricular approach are apparent in practice. She begins her research project.

Elevating educational interventions into scholarly work

The power of theory.

Our example highlights how systematically applying theories, theoretical frameworks, and conceptual frameworks to your educational interventions elevates them into scholarly activities.

Beyond technique

While educational techniques are important, the depth provided by a solid theoretical and conceptual grounding ensures the research has both methodological rigor and conceptual depth.

Practical implications

By adhering to these principles, the internal medicine clerkship director succeeded in transforming what could have been a simple intervention into a scholarly project that contributes to the medical education literature.

The ongoing debate: Lumpers or Splitters?

The choice is yours.

When it comes to choosing between lumping all organizing principles into the bucket of conceptual frameworks (Bordage approach) or making clear distinctions between theory, theoretical framework, and conceptual framework (Varpio et al), there is no one-size-fits-all answer.

Consulting mentors and experts

If you're new to this field, or even if you're a seasoned researcher, it might be useful to consult a research mentor or colleagues to gain more perspectives. MedEdMENTOR encourages dialogue and learning from one another in this evolving field.

Evolving your stance

As you gain more experience and familiarity with educational theory, you may find yourself transitioning from one camp to the other. For beginners, sticking to calling everything a conceptual framework might be a good starting point, but as you grow, making these distinctions can add depth and specificity to your research.

Take home points

• Importance of organizing principles - Regardless of your stance, both camps agree on the need for organizing principles in the field of medical education research.
• Advice for beginners - If you're new to the field, consider starting with Camp #1's approach of calling everything a conceptual framework. As you gain more experience, you may find it beneficial to make distinctions as in Camp #2.
• Theory Database as a resource - MedEdMENTOR's Theory Database can be a helpful tool for both beginners and experts, helping you find and select appropriate theories (aka conceptual frameworks if you're a Lumper!)
• Scholarly engagement is key - The ultimate goal is to engage with medical education research in a scholarly manner, underpinned by theory, theoretical frameworks, and conceptual frameworks, no matter which camp you belong to.

Made it to the end? Want more? Get full access to MedEdMentor's exclusive education resources.

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Home » Theoretical Framework – Types, Examples and Writing Guide

Theoretical Framework – Types, Examples and Writing Guide

Table of Contents

Theoretical Framework

Definition:

Theoretical framework refers to a set of concepts, theories, ideas , and assumptions that serve as a foundation for understanding a particular phenomenon or problem. It provides a conceptual framework that helps researchers to design and conduct their research, as well as to analyze and interpret their findings.

In research, a theoretical framework explains the relationship between various variables, identifies gaps in existing knowledge, and guides the development of research questions, hypotheses, and methodologies. It also helps to contextualize the research within a broader theoretical perspective, and can be used to guide the interpretation of results and the formulation of recommendations.

Types of Theoretical Framework

Types of Types of Theoretical Framework are as follows:

Conceptual Framework

This type of framework defines the key concepts and relationships between them. It helps to provide a theoretical foundation for a study or research project .

Deductive Framework

This type of framework starts with a general theory or hypothesis and then uses data to test and refine it. It is often used in quantitative research .

Inductive Framework

This type of framework starts with data and then develops a theory or hypothesis based on the patterns and themes that emerge from the data. It is often used in qualitative research .

Empirical Framework

This type of framework focuses on the collection and analysis of empirical data, such as surveys or experiments. It is often used in scientific research .

Normative Framework

This type of framework defines a set of norms or values that guide behavior or decision-making. It is often used in ethics and social sciences.

Explanatory Framework

This type of framework seeks to explain the underlying mechanisms or causes of a particular phenomenon or behavior. It is often used in psychology and social sciences.

Components of Theoretical Framework

The components of a theoretical framework include:

• Concepts : The basic building blocks of a theoretical framework. Concepts are abstract ideas or generalizations that represent objects, events, or phenomena.
• Variables : These are measurable and observable aspects of a concept. In a research context, variables can be manipulated or measured to test hypotheses.
• Assumptions : These are beliefs or statements that are taken for granted and are not tested in a study. They provide a starting point for developing hypotheses.
• Propositions : These are statements that explain the relationships between concepts and variables in a theoretical framework.
• Hypotheses : These are testable predictions that are derived from the theoretical framework. Hypotheses are used to guide data collection and analysis.
• Constructs : These are abstract concepts that cannot be directly measured but are inferred from observable variables. Constructs provide a way to understand complex phenomena.
• Models : These are simplified representations of reality that are used to explain, predict, or control a phenomenon.

How to Write Theoretical Framework

A theoretical framework is an essential part of any research study or paper, as it helps to provide a theoretical basis for the research and guide the analysis and interpretation of the data. Here are some steps to help you write a theoretical framework:

• Identify the key concepts and variables : Start by identifying the main concepts and variables that your research is exploring. These could include things like motivation, behavior, attitudes, or any other relevant concepts.
• Review relevant literature: Conduct a thorough review of the existing literature in your field to identify key theories and ideas that relate to your research. This will help you to understand the existing knowledge and theories that are relevant to your research and provide a basis for your theoretical framework.
• Develop a conceptual framework : Based on your literature review, develop a conceptual framework that outlines the key concepts and their relationships. This framework should provide a clear and concise overview of the theoretical perspective that underpins your research.
• Identify hypotheses and research questions: Based on your conceptual framework, identify the hypotheses and research questions that you want to test or explore in your research.
• Test your theoretical framework: Once you have developed your theoretical framework, test it by applying it to your research data. This will help you to identify any gaps or weaknesses in your framework and refine it as necessary.
• Write up your theoretical framework: Finally, write up your theoretical framework in a clear and concise manner, using appropriate terminology and referencing the relevant literature to support your arguments.

Theoretical Framework Examples

Here are some examples of theoretical frameworks:

• Social Learning Theory : This framework, developed by Albert Bandura, suggests that people learn from their environment, including the behaviors of others, and that behavior is influenced by both external and internal factors.
• Maslow’s Hierarchy of Needs : Abraham Maslow proposed that human needs are arranged in a hierarchy, with basic physiological needs at the bottom, followed by safety, love and belonging, esteem, and self-actualization at the top. This framework has been used in various fields, including psychology and education.
• Ecological Systems Theory : This framework, developed by Urie Bronfenbrenner, suggests that a person’s development is influenced by the interaction between the individual and the various environments in which they live, such as family, school, and community.
• Feminist Theory: This framework examines how gender and power intersect to influence social, cultural, and political issues. It emphasizes the importance of understanding and challenging systems of oppression.
• Cognitive Behavioral Theory: This framework suggests that our thoughts, beliefs, and attitudes influence our behavior, and that changing our thought patterns can lead to changes in behavior and emotional responses.
• Attachment Theory: This framework examines the ways in which early relationships with caregivers shape our later relationships and attachment styles.
• Critical Race Theory : This framework examines how race intersects with other forms of social stratification and oppression to perpetuate inequality and discrimination.

When to Have A Theoretical Framework

Following are some situations When to Have A Theoretical Framework:

• A theoretical framework should be developed when conducting research in any discipline, as it provides a foundation for understanding the research problem and guiding the research process.
• A theoretical framework is essential when conducting research on complex phenomena, as it helps to organize and structure the research questions, hypotheses, and findings.
• A theoretical framework should be developed when the research problem requires a deeper understanding of the underlying concepts and principles that govern the phenomenon being studied.
• A theoretical framework is particularly important when conducting research in social sciences, as it helps to explain the relationships between variables and provides a framework for testing hypotheses.
• A theoretical framework should be developed when conducting research in applied fields, such as engineering or medicine, as it helps to provide a theoretical basis for the development of new technologies or treatments.
• A theoretical framework should be developed when conducting research that seeks to address a specific gap in knowledge, as it helps to define the problem and identify potential solutions.
• A theoretical framework is also important when conducting research that involves the analysis of existing theories or concepts, as it helps to provide a framework for comparing and contrasting different theories and concepts.
• A theoretical framework should be developed when conducting research that seeks to make predictions or develop generalizations about a particular phenomenon, as it helps to provide a basis for evaluating the accuracy of these predictions or generalizations.
• Finally, a theoretical framework should be developed when conducting research that seeks to make a contribution to the field, as it helps to situate the research within the broader context of the discipline and identify its significance.

Purpose of Theoretical Framework

The purposes of a theoretical framework include:

• Providing a conceptual framework for the study: A theoretical framework helps researchers to define and clarify the concepts and variables of interest in their research. It enables researchers to develop a clear and concise definition of the problem, which in turn helps to guide the research process.
• Guiding the research design: A theoretical framework can guide the selection of research methods, data collection techniques, and data analysis procedures. By outlining the key concepts and assumptions underlying the research questions, the theoretical framework can help researchers to identify the most appropriate research design for their study.
• Supporting the interpretation of research findings: A theoretical framework provides a framework for interpreting the research findings by helping researchers to make connections between their findings and existing theory. It enables researchers to identify the implications of their findings for theory development and to assess the generalizability of their findings.
• Enhancing the credibility of the research: A well-developed theoretical framework can enhance the credibility of the research by providing a strong theoretical foundation for the study. It demonstrates that the research is based on a solid understanding of the relevant theory and that the research questions are grounded in a clear conceptual framework.
• Facilitating communication and collaboration: A theoretical framework provides a common language and conceptual framework for researchers, enabling them to communicate and collaborate more effectively. It helps to ensure that everyone involved in the research is working towards the same goals and is using the same concepts and definitions.

Characteristics of Theoretical Framework

Some of the characteristics of a theoretical framework include:

• Conceptual clarity: The concepts used in the theoretical framework should be clearly defined and understood by all stakeholders.
• Logical coherence : The framework should be internally consistent, with each concept and assumption logically connected to the others.
• Empirical relevance: The framework should be based on empirical evidence and research findings.
• Parsimony : The framework should be as simple as possible, without sacrificing its ability to explain the phenomenon in question.
• Flexibility : The framework should be adaptable to new findings and insights.
• Testability : The framework should be testable through research, with clear hypotheses that can be falsified or supported by data.
• Applicability : The framework should be useful for practical applications, such as designing interventions or policies.

Advantages of Theoretical Framework

Here are some of the advantages of having a theoretical framework:

• Provides a clear direction : A theoretical framework helps researchers to identify the key concepts and variables they need to study and the relationships between them. This provides a clear direction for the research and helps researchers to focus their efforts and resources.
• Increases the validity of the research: A theoretical framework helps to ensure that the research is based on sound theoretical principles and concepts. This increases the validity of the research by ensuring that it is grounded in established knowledge and is not based on arbitrary assumptions.
• Enables comparisons between studies : A theoretical framework provides a common language and set of concepts that researchers can use to compare and contrast their findings. This helps to build a cumulative body of knowledge and allows researchers to identify patterns and trends across different studies.
• Helps to generate hypotheses: A theoretical framework provides a basis for generating hypotheses about the relationships between different concepts and variables. This can help to guide the research process and identify areas that require further investigation.
• Facilitates communication: A theoretical framework provides a common language and set of concepts that researchers can use to communicate their findings to other researchers and to the wider community. This makes it easier for others to understand the research and its implications.

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Chapter 4: Theoretical frameworks for qualitative research

Tess Tsindos

Learning outcomes

Upon completion of this chapter, you should be able to:

• Describe qualitative frameworks.
• Explain why frameworks are used in qualitative research.
• Identify various frameworks used in qualitative research.

What is a Framework?

A framework is a set of broad concepts or principles used to guide research.  As described by Varpio and colleagues 1 , a framework is a logically developed and connected set of concepts and premises – developed from one or more theories – that a researcher uses as a scaffold for their study. The researcher must define any concepts and theories that will provide the grounding for the research and link them through logical connections, and must relate these concepts to the study that is being carried out. In using a particular theory to guide their study, the researcher needs to ensure that the theoretical framework is reflected in the work in which they are engaged.

It is important to acknowledge that the terms ‘theories’ ( see Chapter 3 ), ‘frameworks’ and ‘paradigms’ are sometimes used interchangeably. However, there are differences between these concepts. To complicate matters further, theoretical frameworks and conceptual frameworks are also used. In addition, quantitative and qualitative researchers usually start from different standpoints in terms of theories and frameworks.

A diagram by Varpio and colleagues demonstrates the similarities and differences between theories and frameworks, and how they influence research approaches. 1(p991) The diagram displays the objectivist or deductive approach to research on the left-hand side. Note how the conceptual framework is first finalised before any research is commenced, and it involves the articulation of hypotheses that are to be tested using the data collected. This is often referred to as a top-down approach and/or a general (theory or framework) to a specific (data) approach.

The diagram displays the subjectivist or inductive approach to research on the right-hand side. Note how data is collected first, and through data analysis, a tentative framework is proposed. The framework is then firmed up as new insights are gained from the data analysis. This is referred to as a specific (data) to general (theory and framework) approach .

Why d o w e u se f rameworks?

A framework helps guide the questions used to elicit your data collection. A framework is not prescriptive, but it needs to be suitable for the research question(s), setting and participants. Therefore, the researcher might use different frameworks to guide different research studies.

A framework informs the study’s recruitment and sampling, and informs, guides or structures how data is collected and analysed. For example, a framework concerned with health systems will assist the researcher to analyse the data in a certain way, while a framework concerned with psychological development will have very different ways of approaching the analysis of data. This is due to the differences underpinning the concepts and premises concerned with investigating health systems, compared to the study of psychological development. The framework adopted also guides emerging interpretations of the data and helps in comparing and contrasting data across participants, cases and studies.

Some examples of foundational frameworks used to guide qualitative research in health services and public health:

• The Behaviour Change Wheel 2
• Consolidated Framework for Implementation Research (CFIR) 3
• Theoretical framework of acceptability 4
• Normalization Process Theory 5
• Candidacy Framework 6
• Aboriginal social determinants of health 7(p8)
• Social determinants of health 8
• Social model of health 9,10
• Systems theory 11
• Biopsychosocial model 12
• Discipline-specific models
• Disease-specific frameworks

E xamples of f rameworks

In Table 4.1, citations of published papers are included to demonstrate how the particular framework helps to ‘frame’ the research question and the interpretation of results.

Table 4.1. Frameworks and references

As discussed in Chapter 3, qualitative research is not an absolute science. While not all research may need a framework or theory (particularly descriptive studies, outlined in Chapter 5), the use of a framework or theory can help to position the research questions, research processes and conclusions and implications within the relevant research paradigm. Theories and frameworks also help to bring to focus areas of the research problem that may not have been considered.

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Qualitative Research – a practical guide for health and social care researchers and practitioners Copyright © 2023 by Tess Tsindos is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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Theoretical Frameworks in Medical Education: Using a Systematic Review of Ophthalmology Education Research to Create a Theory of Change Model

Affiliations.

• 1 is a Medical Student, Warren Alpert Medical School, Brown University.
• 2 is a Research Librarian, University of Maryland School of Pharmacy and University of Maryland Health and Human Services Library.
• 3 is a Professor of Ophthalmology and Public Health Sciences, Penn State College of Medicine.
• 4 is Deputy Chief Academic Affiliations Officer, Office of Academic Affiliations, United States Department of Veterans Affairs, and Professor of Surgery (Ophthalmology), Warren Alpert Medical School, Brown University.
• PMID: 36274766
• PMCID: PMC9580314
• DOI: 10.4300/JGME-D-22-00115.1

Background: Theoretical frameworks provide a lens to examine questions and interpret results; however, they are underutilized in medical education.

Objective: To systematically evaluate the use of theoretical frameworks in ophthalmic medical education and present a theory of change model to guide educational initiatives.

Methods: Six electronic databases were searched for peer-reviewed, English-language studies published between 2016 and 2021 on ophthalmic educational initiatives employing a theoretical framework. Quality of studies was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach; risk of bias was evaluated using the Medical Education Research Study Quality Instrument (MERSQI) and the Accreditation Council for Graduate Medical Education (ACGME) guidelines for evaluation of assessment methods. Abstracted components of the included studies were used to develop a theory of change model.

Results: The literature search yielded 1661 studies: 666 were duplicates, 834 studies were excluded after abstract review, and 132 after full-text review; 29 studies (19.2%) employing a theoretical framework were included. The theories used most frequently were the Dreyfus model of skill acquisition and Messick's contemporary validity framework. GRADE ratings were predominantly "low," the average MERSQI score was 10.04, and the ACGME recommendation for all assessment development studies was the lowest recommendation. The theory of change model outlined how educators can select, apply, and evaluate theory-based interventions.

Conclusions: Few ophthalmic medical education studies employed a theoretical framework; their overall rigor was low as assessed by GRADE, MERSQI, and ACGME guidelines. A theory of change model can guide integration of theoretical frameworks into educational initiatives.

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• v.21(3); Fall 2022

Literature Reviews, Theoretical Frameworks, and Conceptual Frameworks: An Introduction for New Biology Education Researchers

Julie a. luft.

† Department of Mathematics, Social Studies, and Science Education, Mary Frances Early College of Education, University of Georgia, Athens, GA 30602-7124

Sophia Jeong

‡ Department of Teaching & Learning, College of Education & Human Ecology, Ohio State University, Columbus, OH 43210

Robert Idsardi

§ Department of Biology, Eastern Washington University, Cheney, WA 99004

Grant Gardner

∥ Department of Biology, Middle Tennessee State University, Murfreesboro, TN 37132

Associated Data

To frame their work, biology education researchers need to consider the role of literature reviews, theoretical frameworks, and conceptual frameworks as critical elements of the research and writing process. However, these elements can be confusing for scholars new to education research. This Research Methods article is designed to provide an overview of each of these elements and delineate the purpose of each in the educational research process. We describe what biology education researchers should consider as they conduct literature reviews, identify theoretical frameworks, and construct conceptual frameworks. Clarifying these different components of educational research studies can be helpful to new biology education researchers and the biology education research community at large in situating their work in the broader scholarly literature.

INTRODUCTION

Discipline-based education research (DBER) involves the purposeful and situated study of teaching and learning in specific disciplinary areas ( Singer et al. , 2012 ). Studies in DBER are guided by research questions that reflect disciplines’ priorities and worldviews. Researchers can use quantitative data, qualitative data, or both to answer these research questions through a variety of methodological traditions. Across all methodologies, there are different methods associated with planning and conducting educational research studies that include the use of surveys, interviews, observations, artifacts, or instruments. Ensuring the coherence of these elements to the discipline’s perspective also involves situating the work in the broader scholarly literature. The tools for doing this include literature reviews, theoretical frameworks, and conceptual frameworks. However, the purpose and function of each of these elements is often confusing to new education researchers. The goal of this article is to introduce new biology education researchers to these three important elements important in DBER scholarship and the broader educational literature.

The first element we discuss is a review of research (literature reviews), which highlights the need for a specific research question, study problem, or topic of investigation. Literature reviews situate the relevance of the study within a topic and a field. The process may seem familiar to science researchers entering DBER fields, but new researchers may still struggle in conducting the review. Booth et al. (2016b) highlight some of the challenges novice education researchers face when conducting a review of literature. They point out that novice researchers struggle in deciding how to focus the review, determining the scope of articles needed in the review, and knowing how to be critical of the articles in the review. Overcoming these challenges (and others) can help novice researchers construct a sound literature review that can inform the design of the study and help ensure the work makes a contribution to the field.

The second and third highlighted elements are theoretical and conceptual frameworks. These guide biology education research (BER) studies, and may be less familiar to science researchers. These elements are important in shaping the construction of new knowledge. Theoretical frameworks offer a way to explain and interpret the studied phenomenon, while conceptual frameworks clarify assumptions about the studied phenomenon. Despite the importance of these constructs in educational research, biology educational researchers have noted the limited use of theoretical or conceptual frameworks in published work ( DeHaan, 2011 ; Dirks, 2011 ; Lo et al. , 2019 ). In reviewing articles published in CBE—Life Sciences Education ( LSE ) between 2015 and 2019, we found that fewer than 25% of the research articles had a theoretical or conceptual framework (see the Supplemental Information), and at times there was an inconsistent use of theoretical and conceptual frameworks. Clearly, these frameworks are challenging for published biology education researchers, which suggests the importance of providing some initial guidance to new biology education researchers.

Fortunately, educational researchers have increased their explicit use of these frameworks over time, and this is influencing educational research in science, technology, engineering, and mathematics (STEM) fields. For instance, a quick search for theoretical or conceptual frameworks in the abstracts of articles in Educational Research Complete (a common database for educational research) in STEM fields demonstrates a dramatic change over the last 20 years: from only 778 articles published between 2000 and 2010 to 5703 articles published between 2010 and 2020, a more than sevenfold increase. Greater recognition of the importance of these frameworks is contributing to DBER authors being more explicit about such frameworks in their studies.

Collectively, literature reviews, theoretical frameworks, and conceptual frameworks work to guide methodological decisions and the elucidation of important findings. Each offers a different perspective on the problem of study and is an essential element in all forms of educational research. As new researchers seek to learn about these elements, they will find different resources, a variety of perspectives, and many suggestions about the construction and use of these elements. The wide range of available information can overwhelm the new researcher who just wants to learn the distinction between these elements or how to craft them adequately.

Our goal in writing this paper is not to offer specific advice about how to write these sections in scholarly work. Instead, we wanted to introduce these elements to those who are new to BER and who are interested in better distinguishing one from the other. In this paper, we share the purpose of each element in BER scholarship, along with important points on its construction. We also provide references for additional resources that may be beneficial to better understanding each element. Table 1 summarizes the key distinctions among these elements.

Comparison of literature reviews, theoretical frameworks, and conceptual reviews

This article is written for the new biology education researcher who is just learning about these different elements or for scientists looking to become more involved in BER. It is a result of our own work as science education and biology education researchers, whether as graduate students and postdoctoral scholars or newly hired and established faculty members. This is the article we wish had been available as we started to learn about these elements or discussed them with new educational researchers in biology.

LITERATURE REVIEWS

Purpose of a literature review.

A literature review is foundational to any research study in education or science. In education, a well-conceptualized and well-executed review provides a summary of the research that has already been done on a specific topic and identifies questions that remain to be answered, thus illustrating the current research project’s potential contribution to the field and the reasoning behind the methodological approach selected for the study ( Maxwell, 2012 ). BER is an evolving disciplinary area that is redefining areas of conceptual emphasis as well as orientations toward teaching and learning (e.g., Labov et al. , 2010 ; American Association for the Advancement of Science, 2011 ; Nehm, 2019 ). As a result, building comprehensive, critical, purposeful, and concise literature reviews can be a challenge for new biology education researchers.

Building Literature Reviews

There are different ways to approach and construct a literature review. Booth et al. (2016a) provide an overview that includes, for example, scoping reviews, which are focused only on notable studies and use a basic method of analysis, and integrative reviews, which are the result of exhaustive literature searches across different genres. Underlying each of these different review processes are attention to the s earch process, a ppraisa l of articles, s ynthesis of the literature, and a nalysis: SALSA ( Booth et al. , 2016a ). This useful acronym can help the researcher focus on the process while building a specific type of review.

However, new educational researchers often have questions about literature reviews that are foundational to SALSA or other approaches. Common questions concern determining which literature pertains to the topic of study or the role of the literature review in the design of the study. This section addresses such questions broadly while providing general guidance for writing a narrative literature review that evaluates the most pertinent studies.

The literature review process should begin before the research is conducted. As Boote and Beile (2005 , p. 3) suggested, researchers should be “scholars before researchers.” They point out that having a good working knowledge of the proposed topic helps illuminate avenues of study. Some subject areas have a deep body of work to read and reflect upon, providing a strong foundation for developing the research question(s). For instance, the teaching and learning of evolution is an area of long-standing interest in the BER community, generating many studies (e.g., Perry et al. , 2008 ; Barnes and Brownell, 2016 ) and reviews of research (e.g., Sickel and Friedrichsen, 2013 ; Ziadie and Andrews, 2018 ). Emerging areas of BER include the affective domain, issues of transfer, and metacognition ( Singer et al. , 2012 ). Many studies in these areas are transdisciplinary and not always specific to biology education (e.g., Rodrigo-Peiris et al. , 2018 ; Kolpikova et al. , 2019 ). These newer areas may require reading outside BER; fortunately, summaries of some of these topics can be found in the Current Insights section of the LSE website.

In focusing on a specific problem within a broader research strand, a new researcher will likely need to examine research outside BER. Depending upon the area of study, the expanded reading list might involve a mix of BER, DBER, and educational research studies. Determining the scope of the reading is not always straightforward. A simple way to focus one’s reading is to create a “summary phrase” or “research nugget,” which is a very brief descriptive statement about the study. It should focus on the essence of the study, for example, “first-year nonmajor students’ understanding of evolution,” “metacognitive prompts to enhance learning during biochemistry,” or “instructors’ inquiry-based instructional practices after professional development programming.” This type of phrase should help a new researcher identify two or more areas to review that pertain to the study. Focusing on recent research in the last 5 years is a good first step. Additional studies can be identified by reading relevant works referenced in those articles. It is also important to read seminal studies that are more than 5 years old. Reading a range of studies should give the researcher the necessary command of the subject in order to suggest a research question.

Given that the research question(s) arise from the literature review, the review should also substantiate the selected methodological approach. The review and research question(s) guide the researcher in determining how to collect and analyze data. Often the methodological approach used in a study is selected to contribute knowledge that expands upon what has been published previously about the topic (see Institute of Education Sciences and National Science Foundation, 2013 ). An emerging topic of study may need an exploratory approach that allows for a description of the phenomenon and development of a potential theory. This could, but not necessarily, require a methodological approach that uses interviews, observations, surveys, or other instruments. An extensively studied topic may call for the additional understanding of specific factors or variables; this type of study would be well suited to a verification or a causal research design. These could entail a methodological approach that uses valid and reliable instruments, observations, or interviews to determine an effect in the studied event. In either of these examples, the researcher(s) may use a qualitative, quantitative, or mixed methods methodological approach.

Even with a good research question, there is still more reading to be done. The complexity and focus of the research question dictates the depth and breadth of the literature to be examined. Questions that connect multiple topics can require broad literature reviews. For instance, a study that explores the impact of a biology faculty learning community on the inquiry instruction of faculty could have the following review areas: learning communities among biology faculty, inquiry instruction among biology faculty, and inquiry instruction among biology faculty as a result of professional learning. Biology education researchers need to consider whether their literature review requires studies from different disciplines within or outside DBER. For the example given, it would be fruitful to look at research focused on learning communities with faculty in STEM fields or in general education fields that result in instructional change. It is important not to be too narrow or too broad when reading. When the conclusions of articles start to sound similar or no new insights are gained, the researcher likely has a good foundation for a literature review. This level of reading should allow the researcher to demonstrate a mastery in understanding the researched topic, explain the suitability of the proposed research approach, and point to the need for the refined research question(s).

The literature review should include the researcher’s evaluation and critique of the selected studies. A researcher may have a large collection of studies, but not all of the studies will follow standards important in the reporting of empirical work in the social sciences. The American Educational Research Association ( Duran et al. , 2006 ), for example, offers a general discussion about standards for such work: an adequate review of research informing the study, the existence of sound and appropriate data collection and analysis methods, and appropriate conclusions that do not overstep or underexplore the analyzed data. The Institute of Education Sciences and National Science Foundation (2013) also offer Common Guidelines for Education Research and Development that can be used to evaluate collected studies.

Because not all journals adhere to such standards, it is important that a researcher review each study to determine the quality of published research, per the guidelines suggested earlier. In some instances, the research may be fatally flawed. Examples of such flaws include data that do not pertain to the question, a lack of discussion about the data collection, poorly constructed instruments, or an inadequate analysis. These types of errors result in studies that are incomplete, error-laden, or inaccurate and should be excluded from the review. Most studies have limitations, and the author(s) often make them explicit. For instance, there may be an instructor effect, recognized bias in the analysis, or issues with the sample population. Limitations are usually addressed by the research team in some way to ensure a sound and acceptable research process. Occasionally, the limitations associated with the study can be significant and not addressed adequately, which leaves a consequential decision in the hands of the researcher. Providing critiques of studies in the literature review process gives the reader confidence that the researcher has carefully examined relevant work in preparation for the study and, ultimately, the manuscript.

A solid literature review clearly anchors the proposed study in the field and connects the research question(s), the methodological approach, and the discussion. Reviewing extant research leads to research questions that will contribute to what is known in the field. By summarizing what is known, the literature review points to what needs to be known, which in turn guides decisions about methodology. Finally, notable findings of the new study are discussed in reference to those described in the literature review.

Within published BER studies, literature reviews can be placed in different locations in an article. When included in the introductory section of the study, the first few paragraphs of the manuscript set the stage, with the literature review following the opening paragraphs. Cooper et al. (2019) illustrate this approach in their study of course-based undergraduate research experiences (CUREs). An introduction discussing the potential of CURES is followed by an analysis of the existing literature relevant to the design of CUREs that allows for novel student discoveries. Within this review, the authors point out contradictory findings among research on novel student discoveries. This clarifies the need for their study, which is described and highlighted through specific research aims.

A literature reviews can also make up a separate section in a paper. For example, the introduction to Todd et al. (2019) illustrates the need for their research topic by highlighting the potential of learning progressions (LPs) and suggesting that LPs may help mitigate learning loss in genetics. At the end of the introduction, the authors state their specific research questions. The review of literature following this opening section comprises two subsections. One focuses on learning loss in general and examines a variety of studies and meta-analyses from the disciplines of medical education, mathematics, and reading. The second section focuses specifically on LPs in genetics and highlights student learning in the midst of LPs. These separate reviews provide insights into the stated research question.

Suggestions and Advice

A well-conceptualized, comprehensive, and critical literature review reveals the understanding of the topic that the researcher brings to the study. Literature reviews should not be so big that there is no clear area of focus; nor should they be so narrow that no real research question arises. The task for a researcher is to craft an efficient literature review that offers a critical analysis of published work, articulates the need for the study, guides the methodological approach to the topic of study, and provides an adequate foundation for the discussion of the findings.

In our own writing of literature reviews, there are often many drafts. An early draft may seem well suited to the study because the need for and approach to the study are well described. However, as the results of the study are analyzed and findings begin to emerge, the existing literature review may be inadequate and need revision. The need for an expanded discussion about the research area can result in the inclusion of new studies that support the explanation of a potential finding. The literature review may also prove to be too broad. Refocusing on a specific area allows for more contemplation of a finding.

It should be noted that there are different types of literature reviews, and many books and articles have been written about the different ways to embark on these types of reviews. Among these different resources, the following may be helpful in considering how to refine the review process for scholarly journals:

• Booth, A., Sutton, A., & Papaioannou, D. (2016a). Systemic approaches to a successful literature review (2nd ed.). Los Angeles, CA: Sage. This book addresses different types of literature reviews and offers important suggestions pertaining to defining the scope of the literature review and assessing extant studies.
• Booth, W. C., Colomb, G. G., Williams, J. M., Bizup, J., & Fitzgerald, W. T. (2016b). The craft of research (4th ed.). Chicago: University of Chicago Press. This book can help the novice consider how to make the case for an area of study. While this book is not specifically about literature reviews, it offers suggestions about making the case for your study.
• Galvan, J. L., & Galvan, M. C. (2017). Writing literature reviews: A guide for students of the social and behavioral sciences (7th ed.). Routledge. This book offers guidance on writing different types of literature reviews. For the novice researcher, there are useful suggestions for creating coherent literature reviews.

THEORETICAL FRAMEWORKS

Purpose of theoretical frameworks.

As new education researchers may be less familiar with theoretical frameworks than with literature reviews, this discussion begins with an analogy. Envision a biologist, chemist, and physicist examining together the dramatic effect of a fog tsunami over the ocean. A biologist gazing at this phenomenon may be concerned with the effect of fog on various species. A chemist may be interested in the chemical composition of the fog as water vapor condenses around bits of salt. A physicist may be focused on the refraction of light to make fog appear to be “sitting” above the ocean. While observing the same “objective event,” the scientists are operating under different theoretical frameworks that provide a particular perspective or “lens” for the interpretation of the phenomenon. Each of these scientists brings specialized knowledge, experiences, and values to this phenomenon, and these influence the interpretation of the phenomenon. The scientists’ theoretical frameworks influence how they design and carry out their studies and interpret their data.

Within an educational study, a theoretical framework helps to explain a phenomenon through a particular lens and challenges and extends existing knowledge within the limitations of that lens. Theoretical frameworks are explicitly stated by an educational researcher in the paper’s framework, theory, or relevant literature section. The framework shapes the types of questions asked, guides the method by which data are collected and analyzed, and informs the discussion of the results of the study. It also reveals the researcher’s subjectivities, for example, values, social experience, and viewpoint ( Allen, 2017 ). It is essential that a novice researcher learn to explicitly state a theoretical framework, because all research questions are being asked from the researcher’s implicit or explicit assumptions of a phenomenon of interest ( Schwandt, 2000 ).

Selecting Theoretical Frameworks

Theoretical frameworks are one of the most contemplated elements in our work in educational research. In this section, we share three important considerations for new scholars selecting a theoretical framework.

The first step in identifying a theoretical framework involves reflecting on the phenomenon within the study and the assumptions aligned with the phenomenon. The phenomenon involves the studied event. There are many possibilities, for example, student learning, instructional approach, or group organization. A researcher holds assumptions about how the phenomenon will be effected, influenced, changed, or portrayed. It is ultimately the researcher’s assumption(s) about the phenomenon that aligns with a theoretical framework. An example can help illustrate how a researcher’s reflection on the phenomenon and acknowledgment of assumptions can result in the identification of a theoretical framework.

In our example, a biology education researcher may be interested in exploring how students’ learning of difficult biological concepts can be supported by the interactions of group members. The phenomenon of interest is the interactions among the peers, and the researcher assumes that more knowledgeable students are important in supporting the learning of the group. As a result, the researcher may draw on Vygotsky’s (1978) sociocultural theory of learning and development that is focused on the phenomenon of student learning in a social setting. This theory posits the critical nature of interactions among students and between students and teachers in the process of building knowledge. A researcher drawing upon this framework holds the assumption that learning is a dynamic social process involving questions and explanations among students in the classroom and that more knowledgeable peers play an important part in the process of building conceptual knowledge.

It is important to state at this point that there are many different theoretical frameworks. Some frameworks focus on learning and knowing, while other theoretical frameworks focus on equity, empowerment, or discourse. Some frameworks are well articulated, and others are still being refined. For a new researcher, it can be challenging to find a theoretical framework. Two of the best ways to look for theoretical frameworks is through published works that highlight different frameworks.

When a theoretical framework is selected, it should clearly connect to all parts of the study. The framework should augment the study by adding a perspective that provides greater insights into the phenomenon. It should clearly align with the studies described in the literature review. For instance, a framework focused on learning would correspond to research that reported different learning outcomes for similar studies. The methods for data collection and analysis should also correspond to the framework. For instance, a study about instructional interventions could use a theoretical framework concerned with learning and could collect data about the effect of the intervention on what is learned. When the data are analyzed, the theoretical framework should provide added meaning to the findings, and the findings should align with the theoretical framework.

A study by Jensen and Lawson (2011) provides an example of how a theoretical framework connects different parts of the study. They compared undergraduate biology students in heterogeneous and homogeneous groups over the course of a semester. Jensen and Lawson (2011) assumed that learning involved collaboration and more knowledgeable peers, which made Vygotsky’s (1978) theory a good fit for their study. They predicted that students in heterogeneous groups would experience greater improvement in their reasoning abilities and science achievements with much of the learning guided by the more knowledgeable peers.

In the enactment of the study, they collected data about the instruction in traditional and inquiry-oriented classes, while the students worked in homogeneous or heterogeneous groups. To determine the effect of working in groups, the authors also measured students’ reasoning abilities and achievement. Each data-collection and analysis decision connected to understanding the influence of collaborative work.

Their findings highlighted aspects of Vygotsky’s (1978) theory of learning. One finding, for instance, posited that inquiry instruction, as a whole, resulted in reasoning and achievement gains. This links to Vygotsky (1978) , because inquiry instruction involves interactions among group members. A more nuanced finding was that group composition had a conditional effect. Heterogeneous groups performed better with more traditional and didactic instruction, regardless of the reasoning ability of the group members. Homogeneous groups worked better during interaction-rich activities for students with low reasoning ability. The authors attributed the variation to the different types of helping behaviors of students. High-performing students provided the answers, while students with low reasoning ability had to work collectively through the material. In terms of Vygotsky (1978) , this finding provided new insights into the learning context in which productive interactions can occur for students.

Another consideration in the selection and use of a theoretical framework pertains to its orientation to the study. This can result in the theoretical framework prioritizing individuals, institutions, and/or policies ( Anfara and Mertz, 2014 ). Frameworks that connect to individuals, for instance, could contribute to understanding their actions, learning, or knowledge. Institutional frameworks, on the other hand, offer insights into how institutions, organizations, or groups can influence individuals or materials. Policy theories provide ways to understand how national or local policies can dictate an emphasis on outcomes or instructional design. These different types of frameworks highlight different aspects in an educational setting, which influences the design of the study and the collection of data. In addition, these different frameworks offer a way to make sense of the data. Aligning the data collection and analysis with the framework ensures that a study is coherent and can contribute to the field.

New understandings emerge when different theoretical frameworks are used. For instance, Ebert-May et al. (2015) prioritized the individual level within conceptual change theory (see Posner et al. , 1982 ). In this theory, an individual’s knowledge changes when it no longer fits the phenomenon. Ebert-May et al. (2015) designed a professional development program challenging biology postdoctoral scholars’ existing conceptions of teaching. The authors reported that the biology postdoctoral scholars’ teaching practices became more student-centered as they were challenged to explain their instructional decision making. According to the theory, the biology postdoctoral scholars’ dissatisfaction in their descriptions of teaching and learning initiated change in their knowledge and instruction. These results reveal how conceptual change theory can explain the learning of participants and guide the design of professional development programming.

The communities of practice (CoP) theoretical framework ( Lave, 1988 ; Wenger, 1998 ) prioritizes the institutional level , suggesting that learning occurs when individuals learn from and contribute to the communities in which they reside. Grounded in the assumption of community learning, the literature on CoP suggests that, as individuals interact regularly with the other members of their group, they learn about the rules, roles, and goals of the community ( Allee, 2000 ). A study conducted by Gehrke and Kezar (2017) used the CoP framework to understand organizational change by examining the involvement of individual faculty engaged in a cross-institutional CoP focused on changing the instructional practice of faculty at each institution. In the CoP, faculty members were involved in enhancing instructional materials within their department, which aligned with an overarching goal of instituting instruction that embraced active learning. Not surprisingly, Gehrke and Kezar (2017) revealed that faculty who perceived the community culture as important in their work cultivated institutional change. Furthermore, they found that institutional change was sustained when key leaders served as mentors and provided support for faculty, and as faculty themselves developed into leaders. This study reveals the complexity of individual roles in a COP in order to support institutional instructional change.

It is important to explicitly state the theoretical framework used in a study, but elucidating a theoretical framework can be challenging for a new educational researcher. The literature review can help to identify an applicable theoretical framework. Focal areas of the review or central terms often connect to assumptions and assertions associated with the framework that pertain to the phenomenon of interest. Another way to identify a theoretical framework is self-reflection by the researcher on personal beliefs and understandings about the nature of knowledge the researcher brings to the study ( Lysaght, 2011 ). In stating one’s beliefs and understandings related to the study (e.g., students construct their knowledge, instructional materials support learning), an orientation becomes evident that will suggest a particular theoretical framework. Theoretical frameworks are not arbitrary , but purposefully selected.

With experience, a researcher may find expanded roles for theoretical frameworks. Researchers may revise an existing framework that has limited explanatory power, or they may decide there is a need to develop a new theoretical framework. These frameworks can emerge from a current study or the need to explain a phenomenon in a new way. Researchers may also find that multiple theoretical frameworks are necessary to frame and explore a problem, as different frameworks can provide different insights into a problem.

Finally, it is important to recognize that choosing “x” theoretical framework does not necessarily mean a researcher chooses “y” methodology and so on, nor is there a clear-cut, linear process in selecting a theoretical framework for one’s study. In part, the nonlinear process of identifying a theoretical framework is what makes understanding and using theoretical frameworks challenging. For the novice scholar, contemplating and understanding theoretical frameworks is essential. Fortunately, there are articles and books that can help:

• Creswell, J. W. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Los Angeles, CA: Sage. This book provides an overview of theoretical frameworks in general educational research.
• Ding, L. (2019). Theoretical perspectives of quantitative physics education research. Physical Review Physics Education Research , 15 (2), 020101-1–020101-13. This paper illustrates how a DBER field can use theoretical frameworks.
• Nehm, R. (2019). Biology education research: Building integrative frameworks for teaching and learning about living systems. Disciplinary and Interdisciplinary Science Education Research , 1 , ar15. https://doi.org/10.1186/s43031-019-0017-6 . This paper articulates the need for studies in BER to explicitly state theoretical frameworks and provides examples of potential studies.
• Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice . Sage. This book also provides an overview of theoretical frameworks, but for both research and evaluation.

CONCEPTUAL FRAMEWORKS

Purpose of a conceptual framework.

A conceptual framework is a description of the way a researcher understands the factors and/or variables that are involved in the study and their relationships to one another. The purpose of a conceptual framework is to articulate the concepts under study using relevant literature ( Rocco and Plakhotnik, 2009 ) and to clarify the presumed relationships among those concepts ( Rocco and Plakhotnik, 2009 ; Anfara and Mertz, 2014 ). Conceptual frameworks are different from theoretical frameworks in both their breadth and grounding in established findings. Whereas a theoretical framework articulates the lens through which a researcher views the work, the conceptual framework is often more mechanistic and malleable.

Conceptual frameworks are broader, encompassing both established theories (i.e., theoretical frameworks) and the researchers’ own emergent ideas. Emergent ideas, for example, may be rooted in informal and/or unpublished observations from experience. These emergent ideas would not be considered a “theory” if they are not yet tested, supported by systematically collected evidence, and peer reviewed. However, they do still play an important role in the way researchers approach their studies. The conceptual framework allows authors to clearly describe their emergent ideas so that connections among ideas in the study and the significance of the study are apparent to readers.

Constructing Conceptual Frameworks

Including a conceptual framework in a research study is important, but researchers often opt to include either a conceptual or a theoretical framework. Either may be adequate, but both provide greater insight into the research approach. For instance, a research team plans to test a novel component of an existing theory. In their study, they describe the existing theoretical framework that informs their work and then present their own conceptual framework. Within this conceptual framework, specific topics portray emergent ideas that are related to the theory. Describing both frameworks allows readers to better understand the researchers’ assumptions, orientations, and understanding of concepts being investigated. For example, Connolly et al. (2018) included a conceptual framework that described how they applied a theoretical framework of social cognitive career theory (SCCT) to their study on teaching programs for doctoral students. In their conceptual framework, the authors described SCCT, explained how it applied to the investigation, and drew upon results from previous studies to justify the proposed connections between the theory and their emergent ideas.

In some cases, authors may be able to sufficiently describe their conceptualization of the phenomenon under study in an introduction alone, without a separate conceptual framework section. However, incomplete descriptions of how the researchers conceptualize the components of the study may limit the significance of the study by making the research less intelligible to readers. This is especially problematic when studying topics in which researchers use the same terms for different constructs or different terms for similar and overlapping constructs (e.g., inquiry, teacher beliefs, pedagogical content knowledge, or active learning). Authors must describe their conceptualization of a construct if the research is to be understandable and useful.

There are some key areas to consider regarding the inclusion of a conceptual framework in a study. To begin with, it is important to recognize that conceptual frameworks are constructed by the researchers conducting the study ( Rocco and Plakhotnik, 2009 ; Maxwell, 2012 ). This is different from theoretical frameworks that are often taken from established literature. Researchers should bring together ideas from the literature, but they may be influenced by their own experiences as a student and/or instructor, the shared experiences of others, or thought experiments as they construct a description, model, or representation of their understanding of the phenomenon under study. This is an exercise in intellectual organization and clarity that often considers what is learned, known, and experienced. The conceptual framework makes these constructs explicitly visible to readers, who may have different understandings of the phenomenon based on their prior knowledge and experience. There is no single method to go about this intellectual work.

Reeves et al. (2016) is an example of an article that proposed a conceptual framework about graduate teaching assistant professional development evaluation and research. The authors used existing literature to create a novel framework that filled a gap in current research and practice related to the training of graduate teaching assistants. This conceptual framework can guide the systematic collection of data by other researchers because the framework describes the relationships among various factors that influence teaching and learning. The Reeves et al. (2016) conceptual framework may be modified as additional data are collected and analyzed by other researchers. This is not uncommon, as conceptual frameworks can serve as catalysts for concerted research efforts that systematically explore a phenomenon (e.g., Reynolds et al. , 2012 ; Brownell and Kloser, 2015 ).

Sabel et al. (2017) used a conceptual framework in their exploration of how scaffolds, an external factor, interact with internal factors to support student learning. Their conceptual framework integrated principles from two theoretical frameworks, self-regulated learning and metacognition, to illustrate how the research team conceptualized students’ use of scaffolds in their learning ( Figure 1 ). Sabel et al. (2017) created this model using their interpretations of these two frameworks in the context of their teaching.

Conceptual framework from Sabel et al. (2017) .

A conceptual framework should describe the relationship among components of the investigation ( Anfara and Mertz, 2014 ). These relationships should guide the researcher’s methods of approaching the study ( Miles et al. , 2014 ) and inform both the data to be collected and how those data should be analyzed. Explicitly describing the connections among the ideas allows the researcher to justify the importance of the study and the rigor of the research design. Just as importantly, these frameworks help readers understand why certain components of a system were not explored in the study. This is a challenge in education research, which is rooted in complex environments with many variables that are difficult to control.

For example, Sabel et al. (2017) stated: “Scaffolds, such as enhanced answer keys and reflection questions, can help students and instructors bridge the external and internal factors and support learning” (p. 3). They connected the scaffolds in the study to the three dimensions of metacognition and the eventual transformation of existing ideas into new or revised ideas. Their framework provides a rationale for focusing on how students use two different scaffolds, and not on other factors that may influence a student’s success (self-efficacy, use of active learning, exam format, etc.).

In constructing conceptual frameworks, researchers should address needed areas of study and/or contradictions discovered in literature reviews. By attending to these areas, researchers can strengthen their arguments for the importance of a study. For instance, conceptual frameworks can address how the current study will fill gaps in the research, resolve contradictions in existing literature, or suggest a new area of study. While a literature review describes what is known and not known about the phenomenon, the conceptual framework leverages these gaps in describing the current study ( Maxwell, 2012 ). In the example of Sabel et al. (2017) , the authors indicated there was a gap in the literature regarding how scaffolds engage students in metacognition to promote learning in large classes. Their study helps fill that gap by describing how scaffolds can support students in the three dimensions of metacognition: intelligibility, plausibility, and wide applicability. In another example, Lane (2016) integrated research from science identity, the ethic of care, the sense of belonging, and an expertise model of student success to form a conceptual framework that addressed the critiques of other frameworks. In a more recent example, Sbeglia et al. (2021) illustrated how a conceptual framework influences the methodological choices and inferences in studies by educational researchers.

Sometimes researchers draw upon the conceptual frameworks of other researchers. When a researcher’s conceptual framework closely aligns with an existing framework, the discussion may be brief. For example, Ghee et al. (2016) referred to portions of SCCT as their conceptual framework to explain the significance of their work on students’ self-efficacy and career interests. Because the authors’ conceptualization of this phenomenon aligned with a previously described framework, they briefly mentioned the conceptual framework and provided additional citations that provided more detail for the readers.

Within both the BER and the broader DBER communities, conceptual frameworks have been used to describe different constructs. For example, some researchers have used the term “conceptual framework” to describe students’ conceptual understandings of a biological phenomenon. This is distinct from a researcher’s conceptual framework of the educational phenomenon under investigation, which may also need to be explicitly described in the article. Other studies have presented a research logic model or flowchart of the research design as a conceptual framework. These constructions can be quite valuable in helping readers understand the data-collection and analysis process. However, a model depicting the study design does not serve the same role as a conceptual framework. Researchers need to avoid conflating these constructs by differentiating the researchers’ conceptual framework that guides the study from the research design, when applicable.

Explicitly describing conceptual frameworks is essential in depicting the focus of the study. We have found that being explicit in a conceptual framework means using accepted terminology, referencing prior work, and clearly noting connections between terms. This description can also highlight gaps in the literature or suggest potential contributions to the field of study. A well-elucidated conceptual framework can suggest additional studies that may be warranted. This can also spur other researchers to consider how they would approach the examination of a phenomenon and could result in a revised conceptual framework.

It can be challenging to create conceptual frameworks, but they are important. Below are two resources that could be helpful in constructing and presenting conceptual frameworks in educational research:

• Maxwell, J. A. (2012). Qualitative research design: An interactive approach (3rd ed.). Los Angeles, CA: Sage. Chapter 3 in this book describes how to construct conceptual frameworks.
• Ravitch, S. M., & Riggan, M. (2016). Reason & rigor: How conceptual frameworks guide research . Los Angeles, CA: Sage. This book explains how conceptual frameworks guide the research questions, data collection, data analyses, and interpretation of results.

CONCLUDING THOUGHTS

Literature reviews, theoretical frameworks, and conceptual frameworks are all important in DBER and BER. Robust literature reviews reinforce the importance of a study. Theoretical frameworks connect the study to the base of knowledge in educational theory and specify the researcher’s assumptions. Conceptual frameworks allow researchers to explicitly describe their conceptualization of the relationships among the components of the phenomenon under study. Table 1 provides a general overview of these components in order to assist biology education researchers in thinking about these elements.

It is important to emphasize that these different elements are intertwined. When these elements are aligned and complement one another, the study is coherent, and the study findings contribute to knowledge in the field. When literature reviews, theoretical frameworks, and conceptual frameworks are disconnected from one another, the study suffers. The point of the study is lost, suggested findings are unsupported, or important conclusions are invisible to the researcher. In addition, this misalignment may be costly in terms of time and money.

Conducting a literature review, selecting a theoretical framework, and building a conceptual framework are some of the most difficult elements of a research study. It takes time to understand the relevant research, identify a theoretical framework that provides important insights into the study, and formulate a conceptual framework that organizes the finding. In the research process, there is often a constant back and forth among these elements as the study evolves. With an ongoing refinement of the review of literature, clarification of the theoretical framework, and articulation of a conceptual framework, a sound study can emerge that makes a contribution to the field. This is the goal of BER and education research.

Supplementary Material

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• Open access
• Published: 14 August 2024

Investigating the implementation challenges of the research doctoral program and providing related solutions: a qualitative study

• Alireza Koohpaei 1 ,
• Maryam Hoseini Abardeh 2 ,
• Shahnaz Sharifi 3 ,
• Majid Heydari 2 &
• Zeynab Foroughi 4  

BMC Medical Education volume  24 , Article number:  878 ( 2024 ) Cite this article

Metrics details

Doctoral programs have consistently garnered the attention of policymakers in medical education systems due to their significant impact on the socio-economic advancement of countries. Therefore, various doctoral programs have been implemented with diverse goals. In Iran, a research doctorate program, known as PhD by Research, was introduced primarily to engage in applied research related to healthcare needs. Nevertheless, the achievement of the program’s goals has been questioned. This study aimed to identify the implementation challenges of the Research Doctorate Program and its solutions in Iran.

This descriptive qualitative study followed the Standards for Reporting Qualitative Research: A Synthesis of Recommendations and was conducted in two steps. Firstly, the challenges of the Iranian Ph.D. by research program were identified through the perspectives of the program’s students and graduates. In the second step, relevant solutions to these challenges were determined by focus groups of key informant experts. The transcripts were analyzed using qualitative content analysis.

Five students and six graduates were interviewed in the first step and seven experts participated in the second one. The challenges and related solutions are explored in four main themes, including: (1) admission criteria, (2) program goals and expected outcomes, (3) curricula, and (4) financial and human resources. The study showed that various dimensions of the doctoral program are not aligned with each other and how to adapt the program in these dimensions.

The study revealed the importance of a systematic approach in defining various dimensions of doctoral programs according to program goals and provided specific solutions for defining a research doctorate program in the context of a low- and middle-income country.

Peer Review reports

Doctoral education plays a strategic role in national and regional economic, scientific, technological, and social development [ 1 ]. It lies at the heart of a university’s research capacity, which is also recognized as the primary source for research productivity and innovation in the global knowledge economy [ 2 ]. Hence, the significance of doctoral education captures the interest of policymakers at both international and national levels, as well as institutional leaders [ 3 , 4 ].

Over the past decades, doctoral education has witnessed a profound transformation [ 5 ] and takes various forms that can impact the quality and success of doctoral programs [ 6 ]. Doctoral programs offer students a study plan in their chosen field, which helps them gain a broad understanding of their discipline, develop expertise in the fundamental knowledge and methodologies, and acquire competencies to contribute to meaningful and practical scientific advancements [ 7 ]. Also, it prepares candidates for their various academic tasks [ 8 ].

Around the world, universities and medical education systems have established various types of doctoral programs tailored to their unique goals and requirements. Therefore, there is a wide range of doctoral programs. The most prevalent form of doctoral degree is the ‘Doctor of Philosophy’ or Ph.D., which signifies the recognition of students’ expertise in conducting research and contributing to generating novel knowledge [ 3 ]. In addition, the highest level of formal education belongs to the Doctor of Philosophy (Ph.D.) degree, because it equips individuals with the necessary knowledge and skills to push forward the boundaries of knowledge in a specific field [ 9 ]. Traditional Ph.D. programs typically center around dissertations. Additionally, there are also taught Ph.D. and Ph.D. by publication models, which respectively emphasize coursework and publications. Also, to enhance graduates’ preparation for the work environment, there are various types of work-based and professional doctoral programs [ 10 ]. The most important reasons for reforming traditional doctoral programs and creating diversity within them include: increasing the employment opportunities for graduates in the private sector [ 11 ], heightened focus on commercializing research outcomes [ 12 ], fostering competition and enhancing skills among graduates, facilitating a transition in career paths from academia to industry through collaborations between industry and universities [ 13 ], and aligning with market demands in the context of a competitive and dynamic knowledge-based economy [ 14 ].

Extensive research has been conducted on doctoral programs, resulting in a substantial amount of literature available. Some studies focused on students ‘experiences during the doctorate journey, because students go through an emotionally and intellectually demanding journey that encompasses a diverse range of both positive and negative experiences [ 15 ]. As well as, their live truly is a ‘constant juggling act’ and they may encounter different challenges and experiences that undergraduate may not come across [ 16 , 17 ]. From this perspective, Pyhältö and his et al. (2012) reported doctoral students’ problems which were related to supervision, the research community, domain specific, the general working process and resources [ 17 ]. Prendergast et al. studied the well-being of doctoral students [ 16 ].

Other studies are concentrated on the evaluation of doctoral programs. For example, Cross and Backhouse conducted a comprehensive investigation of the various limitations, obstacles, and possibilities within African doctoral education. They also proposed a framework for evaluating these programs which consisted of six elements including (1) expected outcomes, (2) candidates in context, (3) curriculum, (4) structures, (5) resources, and (6) funding, and partnership opportunities [ 18 ]. Meuleners et al. evaluated five aspects of the 82 life science doctoral programs in Germany, including (1) interdisciplinary, (2) the international orientation of these programs, (3) courses offered, (4) formal characteristics of supervision, and (5) examination regulations of the doctoral programs (6).

Assessment of research-doctorate programs have been conducted in different regions such as the United States [ 19 ] and Africa [ 20 ]. The University of Pennsylvania School of Nursing revised research-focused doctorate programs in October 2019. Some of the proposed changes involve enhancing the readiness of Ph.D. program graduates to connect research with practical applications, redesigning funding and support systems for students on an accelerated Ph.D. track, and developing ways to measure and evaluate the achievements of graduates [ 21 ].

In research-focused doctorate, it is crucial for doctoral students to gain a deep understanding of specific concepts in order to become independent researchers [ 22 ]. Studies in this area have demonstrated that traditional Ph.D. programs may not adequately provide graduates with the essential skills and knowledge they need [ 23 ]. To ensure the successful completion and achievement of doctoral graduates, it is important to consistently work towards developing doctoral programs that are adaptable to the learning needs of doctoral candidates and to overcome any barriers to desired outcomes [ 8 ].

In 2008, Iranian educational policymakers in the Ministry of Health and Medical Education (MoHME) made the decision to design a research-focused doctorate program (Ph.D. by research) to enhance the practicality of doctoral education and make a connection between doctoral education and job requirements. The purpose of this program was to educate candidates who can meet the needs of the country and expand the boundaries of knowledge by using advanced research methods and the latest research for problem solving [ 24 ]. This program consists of two parts, in the first part (M.Phil.), candidates learn research and technology theoretical and scientific skills, and in the second one, they should conduct a thesis and they are supported by a supervisory team which typically consists of two supervisors. The program was revised in 2013, 2014, and 2020. However, it appears that the program has not effectively achieved its intended goal. The evidence regarding the situation of graduates in the job market and their struggles in finding suitable employment confirms several obstacles within the program. Therefore, the aim of this study was to detect the implementation challenges of the Research Doctorate Programs from the students and graduates’ perspectives.

Materials and methods

This study was conducted according to the Standards for Reporting Qualitative Research: A Synthesis of Recommendations [ 25 ].

Study design

We applied a qualitative descriptive methodology to achieve an in-depth and rigorous description of the challenges of the research-focused doctorate program and relevant solutions. The study was conducted in two steps. Firstly, the challenges of the Iranian Ph.D. by research program were identified, and in the second step, relevant solutions to these challenges were determined.

Participant and sampling

Participants were selected based on their direct experience and knowledge of the Iranian Ph.D. by research program. Therefore, purposeful sampling was used to select participants, including students and graduates (P) from various fields in the doctoral program (first step). The purposeful sampling was of the maximum diversity type. This means that the students were selected from different fields so that the type of field does not lead to bias in available data. Also, information-rich experts were invited to participate in focus groups to propose solutions regarding the identified challenges (second step). In this step, experts (E) were selected from decision makers and policymakers in the doctorate program, medical education experts and researchers, professors and directors from academic institutions that conducted the program. In the first step, two participants were selected according to program records and the further participants were selected through snowball sampling technique. The interview guide and informed consent form were sent to potential research participants via email. If they agree, schedule the interview with them.

The inclusion criteria for the first step were students enrolled in a research doctorate program who were at least in their third year of study or had graduated from the program and had signed the informed consent form to participate in the research. The exclusion criteria included students who were below the third year of their study and those who did not wish to participate in the interview. For the second step, the inclusion criteria were decision-makers and policymakers in the doctorate program, medical education experts and researchers, faculty members, and directors from academic institutions who had been involved with the program for at least five years and had also signed the informed consent form to participate in the research. The exclusion criteria were experts who did not want to participate and did not have at least five years of experience with this program.

Data collection

For the first step, data collection was conducted through in-depth interviews with students and graduates (one in-depth interview with each participant). Data saturation determined the size of the study sample and the number of interviews. There are various models of saturation in qualitative studies. Saunders et al. identified four main saturation models including data saturation, a priori thematic saturation, Theoretical saturation and Inductive thematic saturation [ 26 ]. Data saturation implies on situation when data collection doesn’t provide any new data [ 27 , 28 ]. The interview guide was developed by conducting three pilot interviews. Transcripts of pilot interviews were included in the study analysis. The semi-structured interview was done face-to-face by MHA and ShSh and audio recorded with the participants’ permission. The interviews were transcribed verbatim from the audio recordings. The mean length of interviews was 45 min.

To addressing the identified challenges, we conducted semi-structured focus groups with experts. Data saturation was achieved by conducting five focus group sessions, each with an average of five participants. The team of facilitators included a discussion facilitator who motivated participants to engage in conversations with one another. The second one was responsible for taking notes and documenting the responses and memos. The third facilitator guided the focus group in answering the questions on the interview guide. Data was collected through audio recording and note-taking during the focus group sessions. The average duration of focus groups was 60 min. We have provided the study scripts in Supplementary files 1 & 2 .

Data analysis

The transcribed recorded in-depth and focus group interviews, as well as the notes of facilitators, were managed and organized using MAXQDA 20 software. The transcripts of in-depth interviews with students and graduates were analyzed conventionally. Accordingly, the transcripts were read word by word and key concept were highlighted where appropriate. In this step, three researchers independently analyzed the data, and the final codes, categories, and themes were discussed to achieve consensus. The analysis process includes repeatedly reading the transcripts, assigning meaning to each phrase, labeling the meaning units with codes, reviewing the codes, and organizing them into categories based on their similarities. Finally, the main themes are identified by interconnecting the categories.

In the second step, the focus group transcripts were analyzed using directed content analysis. In fact, the passages were coded using primary codes and categories from the first step.

Trustworthiness

This study describes the experience of conducting a doctoral program, including its challenges and solutions. Therefore, the study can provide guiding principles to consider when conducting any doctoral program. The credibility of study is confirmed by its adherence to the steps of the inductive content analysis method. Also, conformity was achieved by introducing the background of the researchers, who have various experiences and knowledge to analyze data from different perspectives. Additionally, the researchers confirmed the participants’ responses by transcribing the interviews and sharing the transcriptions with them. The interviewees confirmed that the transcripts contain their own words.

Description of participants

In the first step, out of the 15 individuals initially contacted, 11 agreed to participate and signed the consent form. Among the participants, five were actively enrolled in Ph.D. programs, while six had already graduated. Three participants self-identified as male (27%) and eight as female (73%). The backgrounds of the participants were illustrated in Table  1 . The shortest interview lasted 20 min, while the longest interview lasted 60 min. This phase was conducted from September 21, 2023, to December 10, 2024, at the research centers and their workplaces.

At the second stage, the invitation emails were sent to 10 experts and seven agreed to participate in this phase. The focus groups were conducted on January 2024, at the National Agency for Strategic Research in Medical Sciences Education.

Description of experts

Seven experts, including the program’s decision makers (2 participants, 28.5%), directors (2 participants, 28.5%), and medical education experts (3 participants, 43%) were emailed and recruited to discuss about the potential solutions in dealing with detected challenges (Table  2 ). Four experts were male (57%) and three as female (43%). The interview guide constitutes four main questions based on the detected challenges at the first step.

The authors concluded that data saturation had been achieved, indicating that additional interviews would not have resulted in new or distinctive findings.

The explored themes were related to: (1) unspecified admission criteria, (2) deviation from defined goals and expected outcomes, (3) ineffective curriculum to achieve program goals, (4) financial and human resources challenges. Detected themes, their classes and sub-classes are presented in Table  3 . As the focus groups were conducted based on the identified challenges in the first step, the solutions were categorized and presented within each theme as subcategories (Table  4 ).

Theme 1: unspecified admission criteria

Our analysis revealed some issues related to admission criteria, such as admission bias and special requirement.

1–1: admission bias

In many interviews selection based on supervisor ‘s preferences emerged: “ Since the acceptance (at the interview stage) is based on the supervisor’s opinion , the interest of the professors will play an important role in this process (P2). “Most centers choose candidates based on previous acquaintance with students. Personally , I was introduced to several centers based on my selection priorities , and later I found out that in the centers where I was not accepted , the accepted student had already been selected and the professor and student knew each other perfectly (P4)”.

1–2: special requirement

Our data illustrate that the specialized requirement of research institutes and the professional and occupational records of candidates in the specific field are not considered in admission process: “Most centers choose candidates based on previous acquaintance with students. Personally , I was introduced to several centers based on my selection priorities , and later I found out that in the centers where I was not accepted , the accepted student had already been selected and the professor and student knew each other perfectly (P4)”. “ In my opinion , that is better to admit candidates who have worked in the healthcare system for some time , they have known the problems of the system , and they can better solve system problems with their research projects (P6)”.

1–3: solutions

Adapting admission criteria based on program goals.

Experts emphasized the importance of redefining criteria for student admissions. According to their opinions, the criteria should be aligned with the institution’s mission and defined specific to program goal. In fact, students should be selected according to their potential to be a good fit for job in their expertise.

They reached a consensus on considering relevant work experience and published research in the field of study and alignment with the institution’s mission as effective criteria for achieving the objectives of the doctoral program. “ In fact , it is better that the students’ articles be related to the mission of the institution because it is effective in achieving the objective of conducting applied research and increasing the employability of the students (E1)”. “ The mission of the institution where the student is going to spend his/her education should be considered when choosing a student (E2)”.

Theme 2: deviation from defined goals and expected outcomes

This theme includes two classes (1) objectives unrelated to the program and (2) implementation barriers.

2–1: objectives unrelated to the program

This class includes two subclasses: 1) increase the ranks of the center,2) employment of graduates.

Candidates and graduates brought up how the goals and expected outcomes did change because the centers follow objectives which are not related to the goals and objectives of the program: “Many research centers accept Ph.D. students because they only want to increase the ranks of the center in the ranking systems , by implementing research projects that do not consider as the priority of the health system (P2)”. “ The goal of this initiative is to facilitate the employment of graduates in the job market , rather than solely focusing on training a few research doctoral students. (P7)”.

2–2: implementation barriers

This class is related to the providing working opportunities as an important goal of the program which are not reached because of various implementation barriers. Moreover, they acknowledge that the defined purposes and outcomes did not reach: “ No thought for recruitment after graduation. The decision makers should have thought about the working opportunities of the graduates , from the beginning (P5)”.

2–3: solutions

Clarifying students’ future duties and expectations during admission.

Regarding increasing commitment and adherence to the objectives of the institution and the field of study, it is also important for participants to be aware of the program goals, their duties, and the expectations placed on them during and after completing the program. “ At the beginning , we must clarify for the student what we want from her/him during the education , many times neither the student knows what we want from her nor we ourselves (E4)”.

Creating a robust control and evaluation system

Institutions should be continually monitored and evaluate regarding their adherence to the program goals. This requires the creation of a monitoring and evaluation system and the definition of indicators for successful performance in inputs, processes, and outputs. “ Research centers should admit students in a purposeful manner and their performance should be continuously evaluated and monitored by the Ministry of Health and Medical Education (E5)”.

Theme 3: ineffective curriculum to achieve program goals

This theme captured specific ideas and recommendations for the curriculum and includes two classes: (1) inefficient courses, (2) lack of priority setting.

3–1: inefficient courses

The non-applicable courses were emerged in this class. According to the results, the training methods and material of courses are not up to date and based on current relevant issues in field of studies: “ the lessons were not useful at all. We didn’t learn anything new in the general courses , which should have taught us about research , statistics , and epidemiology (P5)”.

3–2: lack of priority setting

Irrelevant lessons to fields priorities was proposed by the participants. Further, the thesis topics and research institutes’ priorities are not consistent: “ At least some theoretical courses should be customized for the scientific field of the student. All students pass shared courses in all research centers with different fields of activity (P1)”.

Curiously, most students suggested that the curriculum should be revised according to the candidates’ learning needs, current issues, and the competencies which they are required in their future jobs.

3–3: solutions

Aligning curriculums with program goals and structure.

Experts stated that the program structure and courses’ curriculums should be adjusted based on the fields of studies. “ Conducting need-based applied research requires students to have relevant professional skills and knowledge in their field of study (E3)”.

In addition, they believed that the program contents are needed to revise based on the program objectives. “ Currently , all students in different research centers study the same courses , while the needs of each center and field must be identified first , and then courses based on them should be defined (E6)”.

Theme 4: financial and human resources challenges

This theme consisted of two classes, (1) human resources problems and (2) financial issues.

4–1: human resources problems

Faculties are not able to prepare students for job market and conducting need-based researches. This might be due to the lack of sufficient faculty members in the educational system and their high workload which are stated by candidates. “ Supervisors need to dedicate more time to their students , but they are primarily focused on administrative tasks. (P1)”. In addition, faculty members have poor understanding of the program, have not sufficient practical experience in their field of expertise and they restrict candidates’ freedom of action. “ My supervisor did not have any learning program or research idea (P5)”. “ The supervisors turn the student into a task-fulfilling machine , and the student has no authority in any of the academic fields , including the courses and even the title of the thesis , and only says yes , sir! (P7)”. Many respondents mentioned unprepared faculty members as a challenge of the program. “ The professors themselves have not been well explained about the program and it seems that the professors are still not aware of the requirements of Ph.D. by research program (P3)”.

4–2: financial resources problems

Another aspect is the financial resources issues. Lack of financial support and failure in timely funding were defined as two subclasses.

Another aspect is the Lack of financial resources. This challenge is related to student perspective and suggestions about financial problems: “ Don’t talk about financial support! As much as the university gave a grant , I also spend additional cost for the thesis! (P5)”. “ Due to the high cost of the thesis , the payments were not made on time (P9)”. In addition, students noted the importance of timely funding in completion of their applied research: “ The professor admitted the student , then applied for a grant or research budget. It’s very late! (P5)”.

4–3: solutions

Providing additional supervisor with relevant practical experience.

Another important aspect of achieving the objective of conducting need-based applied research is to ensure that supervisors possess relevant practical experience and knowledge in the field of study. According to participants’ opinions, this achievement can be accomplished through collaboration between relevant academic institutions, health service providers, and product provision institutions in the introduction of supervisors. “ One important aspect to take into account in this program is the utilization of faculty members who have expertise in research and possess teaching relevant skills . (E4)”.

Clarity of duties and performance criteria

Lack of sufficient faculty members and their high workload necessitate managing them by standardizing and documenting their duties and clearly defining expectations. “ It is important to distribute students to supervisors based on their workload , such as assigning fewer students to professors with administrative responsibilities. (E5) ”.

Sustaining financial resources

Diversifying financial resources through collaboration with relevant public or private academic, health service, and product provision institutions was the main recommendation of experts to provide sustainable funding for the doctorate program. “ Faculty members should try to obtain national and international research grants such as World Health Organization grants (E7)”.

This study aimed to detect implementation challenges and relevant solutions of the research doctorate program in context of a low-middle income country from the perspectives of its beneficiary including students, graduates and key informants.

Based on the analysis of semi-structured interviews, four challenges were identifying, including unspecified admission criteria, deviation from defined goals and expected outcomes, ineffective curriculum to achieve program goals, financing and human resources.

Challenge 1: unspecified admission criteria

As Burford noted the doctoral admissions process is a subject of intense global discussion [ 29 ] and a wide range of admission criteria has been observed in doctoral programs which are encompass various aspects such as academic preparation, potentialities, attitudes, and competences [ 30 ]. Meanwhile, admission involves evaluative processes that are frequently unclear to those outside the system, but are considered routine by those within. In this regard professors play an important role as gatekeepers of the profession [ 31 ]. According to our findings, selection between applicants was based on supervisor ‘s preferences and previous acquaintance with applicants, and they were led to a decrease in the quality of research doctorate program. In addition, the lack of transparency in the terms and conditions for entering the program were reported by participants. These criteria should be clearly defined during the student recruitment process [ 32 , 33 ]. Therefore, admission criteria for research doctorate programs should be adjusted to ensure the admission of students with the necessary ability, motivation, and commitment to conduct problem-based research. It is essential to consider the diversity (geographical, racial, and ethnic) within the admitted groups.

In addition, having relevant work experience in the specialized field facilitates conducting applied research and enables teaching the course on a part-time basis. As well as ensuring the employability of students for related jobs is guaranteed [ 34 ].

Challenge 2: deviation from defined goals and expected outcomes

This issue emerged as the second challenge of the program. In Iran, the goal of establishing a research doctorate program is to maximize the benefits influenced by stakeholders and beneficiaries, including individuals, groups, parties, and institutions. Meanwhile, students and graduates of the program face some challenges as they are not trained according to the needs of research institutes. Additionally, they struggle to find suitable job positions and encounter issues related to academic-family integration which are consistence whit Rockinson-Szapkiw findings [ 35 ]. In general, the continuation of this process can lead to a lack of motivation among the beneficiaries of the research doctorate program, including professors and students. Urgent reforms should be implemented in this program. In accordance with our results, other researchers have also addressed this issue [ 8 , 36 , 37 ]. It is necessary to identify the potential success metrics of the doctoral program, collect information related to the results of each metric, and standardize them based on the reports provided by various higher education institutions [ 16 ].

Challenge 3: ineffective curriculum to achieve program goals

According to the results, students and graduates of research doctorate program in Iran are studying and working in ambiguous and ineffective conditions. The results of this research are in line with the results of studies by Anderson et al. [ 38 ], Keshmiri et al. [ 39 ], and Shin et al. [ 40 ], but there are differences in Iran. The main difference is that in research doctorate programs in Iran, special skills such as commercialization or other market skills are not included in the curriculum. There are no differences in terms of the designed and offered characteristics between research-oriented and education-oriented curriculums. Additionally, a significant aspect of the program is based on research. In fact, this program trains professional experts who are also researchers. Unlike the education-based doctorate, its goal is not to train researchers in a specific specialty. The various countries analyzed in this research follow two approaches: (1) Offering professional doctorate programs to managers, senior employees, and individuals with extensive experience, or (2) mandating a master’s degree, relevant work experience, and a concurrent affiliation with the relevant work environment [ 6 ].

As a result, the curriculum should primarily focus on new scientific topics, expanding current fields of knowledge, and the emergence of new fields that are influenced by economic, cultural, and technological conditions, as well as the provision of healthcare services and policies [ 41 ].

Challenge 4: financing and human resources

In relation to this problem, participants mentioned that they had various roles and responsibilities beyond those of a doctoral student, indicating that they are “more than just a doctoral student.”

They also expressed dissatisfaction with the low quality of student guidance programs and described mentorships as below average. In various countries, the standards of doctoral programs in medical sciences regarding mentoring activities are reviewed and presented in a consolidated format [ 42 ]. In this regard, the following principles are recommended: (1) Establish quality standards for student guidance activities (2). Create a guideline that supervisors and students can follow. Professors and students should be aware of the standards of student guidance activities. Additionally, providing incentives can enhance the productivity of the relationship between the supervisor and the students.

Students and candidates noted that their supervisors are busy and do not spend enough time on their duties as a supervisor. To address this issue, the following solutions are recommended based on expert feedback: (1) Establishing internal and external collaborations among various specialties and institutions, (2) Taking into account the professors’ workloads, (3) Sharing responsibilities and fostering participation, and (4) Providing flexibility in selecting supervisors.

Based on the study by Meuleners et al., it has been determined that assigning a single supervisor is usually not favourable for students. Instead, the use of a number of supervisors/mentors or a supervision team is recommended [ 6 ]. In this situation, it is possible to develop efficient projects based on the up-to-date needs of society. In Iran, although this possibility exists, the shortage of professors and various problems and challenges within academic groups prevent it. In the research- doctorate program, it is necessary for each student to have one or more senior researchers to guide, help, and support the student in developing their research skills. In fact, the vital role of authentic mentorship is to guide doctoral students through designing their career development plans, assisting in overcoming challenges in doctoral studies, and facilitating professional networking. This can lead to significant job opportunities not only during the doctoral program but also after graduation [ 43 ].

Financial resources also play a crucial role in the success of doctoral programs [ 15 ]. Based on our results, the limitation of financial resources for research doctorate education was another challenge. Therefore, it is recommended to develop a strategy on the best approach to ensure the resources required by the faculty. Utilizing the partnership method is an effective way to maximize resources through collaboration. Partnership is the process of collaborating with other institutions and individuals to achieve shared goals. Therefore, the partners share the same risks and benefits. The use of private financing programs can lead to increased initiatives in specialized doctoral education.

Based on our findings, it seems that in Iran, similar to East Asian countries, a hybrid system combining elements from the USA and European models has been utilized in designing research doctorate programs. This approach emphasizes both supervision and coursework components. On the one hand, this system reduces the level of creativity due to excessive supervision of students’ activities and emphasizes passing certain courses, thus limiting opportunities for defining problem-oriented projects. These conditions can be altered by transitioning to the European system and thoroughly evaluating the goals and anticipated results. Therefore, based on the results of this study, it is suggested to develop competency based curriculum or to reform the current program in order to solve its current problems. Future research is suggested to examine the practicality and effectiveness of the policy options proposed in the present study and prioritize them in terms of efficacy and effectiveness.

This study acknowledges a potential limitation in the alignment of proposed solutions with the actual challenges faced by students. While solutions are derived from experts’ interpretations of student-reported problems, there may be an inadvertent overlap of differing rationalities. This suggests a need for a more nuanced explanation of the contrasting perspectives between students and experts in the analysis. By analyzing the challenges raised by the students, the solutions proposed by experts, and reviewing similar studies in the discussion section, we aimed to elucidate this difference of opinion for the readers of the article.

This study proposes evidence-based solutions for a research doctorate program tailored to the specific context of Iran’s medical education system. Since the majority of researches on doctoral programs are grounded in Western perspectives on students, faculty, resources, and cultural contexts, this study has the potential to offer valuable insights and fresh perspectives.

The proposed framework is based on the outcome-based curriculum approach, which focuses on the essential competencies that students should achieve by the end of the program. The solutions consist of four main themes: admission criteria, goals and outcomes, curriculum, and resources, which aim to develop the technical and practical competencies of the students and graduates.

Research doctorate program graduates can play a vital role in improving the quality and performance of healthcare services by pursuing various career pathways and job categories that align with their skills and qualifications. However, to achieve this, they need to be supported by the MoHME, which should review and update the curriculum according to the program goals and international best practices. Additionally, redefining admission criteria, clarifying future duties, managing human and financial resources, and providing effective mentoring are essential. Moreover, graduates of research doctorate programs should collaborate with other health professionals, policymakers, and stakeholders to promote inter-professional collaboration and enhance integrated health system improvement.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Ministry of Health and Medical Education

Doctor of Philosophy

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Acknowledgements

The authors extend their appreciation to the National Agency for Strategic Research in Medical Sciences Education (NASR) for funding this research work.

This project was funded by the National Agency for Strategic Research in Medical Sciences Education (NASR). Tehran. Iran. Grant NO. 4020154.

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Maryam Hoseini Abardeh & Majid Heydari

Critical Care Quality Improvement Research Center, Shahid Modarres Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Shahnaz Sharifi

Education Development Center, Iran University of Medical Sciences, Tehran, Iran, Islamic Republic of

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A.K. conceived the study and contributed to the study design, data analysis, drafting, and finalizing of the paper. Z.F., M.H.A. contributed to the data analysis and drafted the paper. Sh. Sh. contributed to data gathering and data entry. M.H.A., A.K., and Z.F. contributed to the study design, interpretation of data and intellectual development of the manuscript as well as critically reviewed the manuscript. MH contributed in writing, critical review and editing of manuscript. All authors read and approved the final version of the paper.

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Koohpaei, A., Abardeh, M.H., Sharifi, S. et al. Investigating the implementation challenges of the research doctoral program and providing related solutions: a qualitative study. BMC Med Educ 24 , 878 (2024). https://doi.org/10.1186/s12909-024-05815-2

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Genuine Chinese dance therapy is in the ascendant and psychiatric approaches that involve a broad spectrum of principles such as ontological identity, social inclusion and collective support, aestheticisation and expressive catharsis, symbolic exorcism, trance and Buddhist mindfulness. Its models are based on a wealth of Chinese dance genres originating from various dynasties as well as cultural traditions of ethnic minorities. Due to different epistemological backgrounds of Western diagnostic manuals and traditional Chinese views of mental diseases, complex understanding of pathologies and therapeutic dynamics is needed. Therefore, this opinion piece suggests a theoretical framework that encourages interdisciplinary approaches as well as inclusive transcultural psychiatry and related philosophy of science.

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Mastnak, W. A Chinese Dance Therapy Framework. Cult Med Psychiatry (2024). https://doi.org/10.1007/s11013-024-09875-3

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DOI : https://doi.org/10.1007/s11013-024-09875-3

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Blockchain projects in environmental sector: theoretical and practical analysis.

1. Introduction

2. related works, 3. methodology, 3.1. dataset overview and statistics, 3.2. theoretical project analysis, 3.3. practical project analysis, 5. discussion, 6. threats to validity.

• Sampling Bias: Our analysis primarily draws from data collected from the Scopus database and GitHub. This sample may not reflect the full diversity of blockchain’s scientific articles and applications in environmental management. This limitation could influence the extent to which our results can be generalised.
• Technological Evolution: The swift advancement in blockchain technology may render our findings less relevant as new platforms or methodologies emerge that were not included in our initial analysis.
• Analytical Limitations: The use of bibliometric analysis and BERTopic for topic modelling introduces inherent biases. These methodologies might impose constraints on the data that could overlook subtle or emerging themes. The interpretation of the topics through Chat-GPT 4 and the subsequent check by the authors may also introduce a potential bias due to their background and expertise.

7. Conclusions and Future Works

Author contributions, data availability statement, acknowledgments, conflicts of interest.

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Vaccargiu, M.; Tonelli, R. Blockchain Projects in Environmental Sector: Theoretical and Practical Analysis. Earth 2024 , 5 , 354-370. https://doi.org/10.3390/earth5030020

Vaccargiu M, Tonelli R. Blockchain Projects in Environmental Sector: Theoretical and Practical Analysis. Earth . 2024; 5(3):354-370. https://doi.org/10.3390/earth5030020

Vaccargiu, Matteo, and Roberto Tonelli. 2024. "Blockchain Projects in Environmental Sector: Theoretical and Practical Analysis" Earth 5, no. 3: 354-370. https://doi.org/10.3390/earth5030020

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