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Theories are formulated to explain, predict, and understand phenomena and, in many cases, to challenge and extend existing knowledge within the limits of critical bounded assumptions or predictions of behavior. The theoretical framework is the structure that can hold or support a theory of a research study. The theoretical framework encompasses not just the theory, but the narrative explanation about how the researcher engages in using the theory and its underlying assumptions to investigate the research problem. It is the structure of your paper that summarizes concepts, ideas, and theories derived from prior research studies and which was synthesized in order to form a conceptual basis for your analysis and interpretation of meaning found within your research.

Abend, Gabriel. "The Meaning of Theory." Sociological Theory 26 (June 2008): 173–199; Kivunja, Charles. "Distinguishing between Theory, Theoretical Framework, and Conceptual Framework: A Systematic Review of Lessons from the Field." International Journal of Higher Education 7 (December 2018): 44-53; Swanson, Richard A. Theory Building in Applied Disciplines . San Francisco, CA: Berrett-Koehler Publishers 2013; Varpio, Lara, Elise Paradis, Sebastian Uijtdehaage, and Meredith Young. "The Distinctions between Theory, Theoretical Framework, and Conceptual Framework." Academic Medicine 95 (July 2020): 989-994.

Importance of Theory and a Theoretical Framework

Theories can be unfamiliar to the beginning researcher because they are rarely applied in high school social studies curriculum and, as a result, can come across as unfamiliar and imprecise when first introduced as part of a writing assignment. However, in their most simplified form, a theory is simply a set of assumptions or predictions about something you think will happen based on existing evidence and that can be tested to see if those outcomes turn out to be true. Of course, it is slightly more deliberate than that, therefore, summarized from Kivunja (2018, p. 46), here are the essential characteristics of a theory.

• It is logical and coherent
• It has clear definitions of terms or variables, and has boundary conditions [i.e., it is not an open-ended statement]
• It has a domain where it applies
• It has clearly described relationships among variables
• It describes, explains, and makes specific predictions
• It comprises of concepts, themes, principles, and constructs
• It must have been based on empirical data [i.e., it is not a guess]
• It must have made claims that are subject to testing, been tested and verified
• It must be clear and concise
• Its assertions or predictions must be different and better than those in existing theories
• Its predictions must be general enough to be applicable to and understood within multiple contexts
• Its assertions or predictions are relevant, and if applied as predicted, will result in the predicted outcome
• The assertions and predictions are not immutable, but subject to revision and improvement as researchers use the theory to make sense of phenomena
• Its concepts and principles explain what is going on and why
• Its concepts and principles are substantive enough to enable us to predict a future

Given these characteristics, a theory can best be understood as the foundation from which you investigate assumptions or predictions derived from previous studies about the research problem, but in a way that leads to new knowledge and understanding as well as, in some cases, discovering how to improve the relevance of the theory itself or to argue that the theory is outdated and a new theory needs to be formulated based on new evidence.

A theoretical framework consists of concepts and, together with their definitions and reference to relevant scholarly literature, existing theory that is used for your particular study. The theoretical framework must demonstrate an understanding of theories and concepts that are relevant to the topic of your research paper and that relate to the broader areas of knowledge being considered.

The theoretical framework is most often not something readily found within the literature . You must review course readings and pertinent research studies for theories and analytic models that are relevant to the research problem you are investigating. The selection of a theory should depend on its appropriateness, ease of application, and explanatory power.

The theoretical framework strengthens the study in the following ways :

• An explicit statement of  theoretical assumptions permits the reader to evaluate them critically.
• The theoretical framework connects the researcher to existing knowledge. Guided by a relevant theory, you are given a basis for your hypotheses and choice of research methods.
• Articulating the theoretical assumptions of a research study forces you to address questions of why and how. It permits you to intellectually transition from simply describing a phenomenon you have observed to generalizing about various aspects of that phenomenon.
• Having a theory helps you identify the limits to those generalizations. A theoretical framework specifies which key variables influence a phenomenon of interest and highlights the need to examine how those key variables might differ and under what circumstances.
• The theoretical framework adds context around the theory itself based on how scholars had previously tested the theory in relation their overall research design [i.e., purpose of the study, methods of collecting data or information, methods of analysis, the time frame in which information is collected, study setting, and the methodological strategy used to conduct the research].

By virtue of its applicative nature, good theory in the social sciences is of value precisely because it fulfills one primary purpose: to explain the meaning, nature, and challenges associated with a phenomenon, often experienced but unexplained in the world in which we live, so that we may use that knowledge and understanding to act in more informed and effective ways.

The Conceptual Framework. College of Education. Alabama State University; Corvellec, Hervé, ed. What is Theory?: Answers from the Social and Cultural Sciences . Stockholm: Copenhagen Business School Press, 2013; Asher, Herbert B. Theory-Building and Data Analysis in the Social Sciences . Knoxville, TN: University of Tennessee Press, 1984; Drafting an Argument. Writing@CSU. Colorado State University; Kivunja, Charles. "Distinguishing between Theory, Theoretical Framework, and Conceptual Framework: A Systematic Review of Lessons from the Field." International Journal of Higher Education 7 (2018): 44-53; Omodan, Bunmi Isaiah. "A Model for Selecting Theoretical Framework through Epistemology of Research Paradigms." African Journal of Inter/Multidisciplinary Studies 4 (2022): 275-285; Ravitch, Sharon M. and Matthew Riggan. Reason and Rigor: How Conceptual Frameworks Guide Research . Second edition. Los Angeles, CA: SAGE, 2017; Trochim, William M.K. Philosophy of Research. Research Methods Knowledge Base. 2006; Jarvis, Peter. The Practitioner-Researcher. Developing Theory from Practice . San Francisco, CA: Jossey-Bass, 1999.

Strategies for Developing the Theoretical Framework

I.  Developing the Framework

Here are some strategies to develop of an effective theoretical framework:

• Examine your thesis title and research problem . The research problem anchors your entire study and forms the basis from which you construct your theoretical framework.
• Brainstorm about what you consider to be the key variables in your research . Answer the question, "What factors contribute to the presumed effect?"
• Review related literature to find how scholars have addressed your research problem. Identify the assumptions from which the author(s) addressed the problem.
• List  the constructs and variables that might be relevant to your study. Group these variables into independent and dependent categories.
• Review key social science theories that are introduced to you in your course readings and choose the theory that can best explain the relationships between the key variables in your study [note the Writing Tip on this page].
• Discuss the assumptions or propositions of this theory and point out their relevance to your research.

A theoretical framework is used to limit the scope of the relevant data by focusing on specific variables and defining the specific viewpoint [framework] that the researcher will take in analyzing and interpreting the data to be gathered. It also facilitates the understanding of concepts and variables according to given definitions and builds new knowledge by validating or challenging theoretical assumptions.

II.  Purpose

Think of theories as the conceptual basis for understanding, analyzing, and designing ways to investigate relationships within social systems. To that end, the following roles served by a theory can help guide the development of your framework.

• Means by which new research data can be interpreted and coded for future use,
• Response to new problems that have no previously identified solutions strategy,
• Means for identifying and defining research problems,
• Means for prescribing or evaluating solutions to research problems,
• Ways of discerning certain facts among the accumulated knowledge that are important and which facts are not,
• Means of giving old data new interpretations and new meaning,
• Means by which to identify important new issues and prescribe the most critical research questions that need to be answered to maximize understanding of the issue,
• Means of providing members of a professional discipline with a common language and a frame of reference for defining the boundaries of their profession, and
• Means to guide and inform research so that it can, in turn, guide research efforts and improve professional practice.

Adapted from: Torraco, R. J. “Theory-Building Research Methods.” In Swanson R. A. and E. F. Holton III , editors. Human Resource Development Handbook: Linking Research and Practice . (San Francisco, CA: Berrett-Koehler, 1997): pp. 114-137; Jacard, James and Jacob Jacoby. Theory Construction and Model-Building Skills: A Practical Guide for Social Scientists . New York: Guilford, 2010; Ravitch, Sharon M. and Matthew Riggan. Reason and Rigor: How Conceptual Frameworks Guide Research . Second edition. Los Angeles, CA: SAGE, 2017; Sutton, Robert I. and Barry M. Staw. “What Theory is Not.” Administrative Science Quarterly 40 (September 1995): 371-384.

Structure and Writing Style

The theoretical framework may be rooted in a specific theory , in which case, your work is expected to test the validity of that existing theory in relation to specific events, issues, or phenomena. Many social science research papers fit into this rubric. For example, Peripheral Realism Theory, which categorizes perceived differences among nation-states as those that give orders, those that obey, and those that rebel, could be used as a means for understanding conflicted relationships among countries in Africa. A test of this theory could be the following: Does Peripheral Realism Theory help explain intra-state actions, such as, the disputed split between southern and northern Sudan that led to the creation of two nations?

However, you may not always be asked by your professor to test a specific theory in your paper, but to develop your own framework from which your analysis of the research problem is derived . Based upon the above example, it is perhaps easiest to understand the nature and function of a theoretical framework if it is viewed as an answer to two basic questions:

• What is the research problem/question? [e.g., "How should the individual and the state relate during periods of conflict?"]
• Why is your approach a feasible solution? [i.e., justify the application of your choice of a particular theory and explain why alternative constructs were rejected. I could choose instead to test Instrumentalist or Circumstantialists models developed among ethnic conflict theorists that rely upon socio-economic-political factors to explain individual-state relations and to apply this theoretical model to periods of war between nations].

The answers to these questions come from a thorough review of the literature and your course readings [summarized and analyzed in the next section of your paper] and the gaps in the research that emerge from the review process. With this in mind, a complete theoretical framework will likely not emerge until after you have completed a thorough review of the literature .

Just as a research problem in your paper requires contextualization and background information, a theory requires a framework for understanding its application to the topic being investigated. When writing and revising this part of your research paper, keep in mind the following:

• Clearly describe the framework, concepts, models, or specific theories that underpin your study . This includes noting who the key theorists are in the field who have conducted research on the problem you are investigating and, when necessary, the historical context that supports the formulation of that theory. This latter element is particularly important if the theory is relatively unknown or it is borrowed from another discipline.
• Position your theoretical framework within a broader context of related frameworks, concepts, models, or theories . As noted in the example above, there will likely be several concepts, theories, or models that can be used to help develop a framework for understanding the research problem. Therefore, note why the theory you've chosen is the appropriate one.
• The present tense is used when writing about theory. Although the past tense can be used to describe the history of a theory or the role of key theorists, the construction of your theoretical framework is happening now.
• You should make your theoretical assumptions as explicit as possible . Later, your discussion of methodology should be linked back to this theoretical framework.
• Don’t just take what the theory says as a given! Reality is never accurately represented in such a simplistic way; if you imply that it can be, you fundamentally distort a reader's ability to understand the findings that emerge. Given this, always note the limitations of the theoretical framework you've chosen [i.e., what parts of the research problem require further investigation because the theory inadequately explains a certain phenomena].

The Conceptual Framework. College of Education. Alabama State University; Conceptual Framework: What Do You Think is Going On? College of Engineering. University of Michigan; Drafting an Argument. Writing@CSU. Colorado State University; Lynham, Susan A. “The General Method of Theory-Building Research in Applied Disciplines.” Advances in Developing Human Resources 4 (August 2002): 221-241; Tavallaei, Mehdi and Mansor Abu Talib. "A General Perspective on the Role of Theory in Qualitative Research." Journal of International Social Research 3 (Spring 2010); Ravitch, Sharon M. and Matthew Riggan. Reason and Rigor: How Conceptual Frameworks Guide Research . Second edition. Los Angeles, CA: SAGE, 2017; Reyes, Victoria. Demystifying the Journal Article. Inside Higher Education; Trochim, William M.K. Philosophy of Research. Research Methods Knowledge Base. 2006; Weick, Karl E. “The Work of Theorizing.” In Theorizing in Social Science: The Context of Discovery . Richard Swedberg, editor. (Stanford, CA: Stanford University Press, 2014), pp. 177-194.

Writing Tip

Borrowing Theoretical Constructs from Other Disciplines

An increasingly important trend in the social and behavioral sciences is to think about and attempt to understand research problems from an interdisciplinary perspective. One way to do this is to not rely exclusively on the theories developed within your particular discipline, but to think about how an issue might be informed by theories developed in other disciplines. For example, if you are a political science student studying the rhetorical strategies used by female incumbents in state legislature campaigns, theories about the use of language could be derived, not only from political science, but linguistics, communication studies, philosophy, psychology, and, in this particular case, feminist studies. Building theoretical frameworks based on the postulates and hypotheses developed in other disciplinary contexts can be both enlightening and an effective way to be more engaged in the research topic.

CohenMiller, A. S. and P. Elizabeth Pate. "A Model for Developing Interdisciplinary Research Theoretical Frameworks." The Qualitative Researcher 24 (2019): 1211-1226; Frodeman, Robert. The Oxford Handbook of Interdisciplinarity . New York: Oxford University Press, 2010.

Another Writing Tip

Don't Undertheorize!

Do not leave the theory hanging out there in the introduction never to be mentioned again. Undertheorizing weakens your paper. The theoretical framework you describe should guide your study throughout the paper. Be sure to always connect theory to the review of pertinent literature and to explain in the discussion part of your paper how the theoretical framework you chose supports analysis of the research problem or, if appropriate, how the theoretical framework was found to be inadequate in explaining the phenomenon you were investigating. In that case, don't be afraid to propose your own theory based on your findings.

Yet Another Writing Tip

What's a Theory? What's a Hypothesis?

The terms theory and hypothesis are often used interchangeably in newspapers and popular magazines and in non-academic settings. However, the difference between theory and hypothesis in scholarly research is important, particularly when using an experimental design. A theory is a well-established principle that has been developed to explain some aspect of the natural world. Theories arise from repeated observation and testing and incorporates facts, laws, predictions, and tested assumptions that are widely accepted [e.g., rational choice theory; grounded theory; critical race theory].

A hypothesis is a specific, testable prediction about what you expect to happen in your study. For example, an experiment designed to look at the relationship between study habits and test anxiety might have a hypothesis that states, "We predict that students with better study habits will suffer less test anxiety." Unless your study is exploratory in nature, your hypothesis should always explain what you expect to happen during the course of your research.

The key distinctions are:

• A theory predicts events in a broad, general context;  a hypothesis makes a specific prediction about a specified set of circumstances.
• A theory has been extensively tested and is generally accepted among a set of scholars; a hypothesis is a speculative guess that has yet to be tested.

Cherry, Kendra. Introduction to Research Methods: Theory and Hypothesis. About.com Psychology; Gezae, Michael et al. Welcome Presentation on Hypothesis. Slideshare presentation.

Still Yet Another Writing Tip

Be Prepared to Challenge the Validity of an Existing Theory

Theories are meant to be tested and their underlying assumptions challenged; they are not rigid or intransigent, but are meant to set forth general principles for explaining phenomena or predicting outcomes. Given this, testing theoretical assumptions is an important way that knowledge in any discipline develops and grows. If you're asked to apply an existing theory to a research problem, the analysis will likely include the expectation by your professor that you should offer modifications to the theory based on your research findings.

Indications that theoretical assumptions may need to be modified can include the following:

• Your findings suggest that the theory does not explain or account for current conditions or circumstances or the passage of time,
• The study reveals a finding that is incompatible with what the theory attempts to explain or predict, or
• Your analysis reveals that the theory overly generalizes behaviors or actions without taking into consideration specific factors revealed from your analysis [e.g., factors related to culture, nationality, history, gender, ethnicity, age, geographic location, legal norms or customs , religion, social class, socioeconomic status, etc.].

Philipsen, Kristian. "Theory Building: Using Abductive Search Strategies." In Collaborative Research Design: Working with Business for Meaningful Findings . Per Vagn Freytag and Louise Young, editors. (Singapore: Springer Nature, 2018), pp. 45-71; Shepherd, Dean A. and Roy Suddaby. "Theory Building: A Review and Integration." Journal of Management 43 (2017): 59-86.

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What is a framework? Understanding their purpose, value, development and use

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• Open access
• Published: 14 April 2023
• Volume 13 , pages 510–519, ( 2023 )

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• Stefan Partelow   ORCID: orcid.org/0000-0002-7751-4005 1 , 2  

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Many frameworks exist across the sciences and science-policy interface, but it is not always clear how they are developed or can be applied. It is also often vague how new or existing frameworks are positioned in a theory of science to advance a specific theory or paradigm. This article examines these questions and positions the role of frameworks as integral but often vague scientific tools, highlighting benefits and critiques. While frameworks can be useful for synthesizing and communicating core concepts in a field, they often lack transparency in how they were developed and how they can be applied. Positioning frameworks within a theory of science can aid in knowing the purpose and value of framework use. This article provides a meta-framework for visualizing and engaging the four mediating processes for framework development and application: (1) empirical generalization, (2) theoretical fitting, (3) application, and (4) hypothesizing. Guiding points for scholars and policymakers using or developing frameworks in their research are provided in closing.

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…it is not clear what the role of a scientific framework should be, and relatedly, what makes for a successful scientific framework. Ban and Cox, 2017

Introduction

Frameworks are important research tools across nearly all fields of science. They are critically important for structuring empirical inquiry and theoretical development in the environmental social sciences, governance research and practice, the sustainability sciences and fields of social-ecological systems research in tangent with the associated disciplines of those fields (Binder et al. 2013 ; Pulver et al. 2018 ; Colding and Barthel 2019 ). Many well-established frameworks are regularly applied to collect new data or to structure entire research programs such as the Ecosystem Services (ES) framework (Potschin-Young et al. 2018 ), the Social-Ecological Systems Framework (SESF) (McGinnis and Ostrom 2014a ), Earth Systems Governance (ESG) (Biermann et al. 2010 ), the Driver-Impact-Pressure-State-Response (DIPSR) framework, and the Life Cycle Assessment (LCA) framework. Frameworks are also put forth by major scientific organizing bodies to steer scientific and policy agendas at regional and global levels such as the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) (Díaz et al. 2015 ) and the Global Sustainable Development Report’s transformational levers and fields (UN 2019 ).

Despite the countless frameworks, it is not always clear how a framework can be developed or applied (Ban and Cox 2017 ; Partelow 2018 ; Nagel and Partelow 2022 ). Development may occur through empirically backed synthesis or by scholars based on their own knowledge, values, or interests. These diverse development pathways do, however, result in common trends. The structure of most frameworks is the identification of a set of concepts and their general relationships — often in the form box-and-arrow diagrams — that are loosely defined or unspecified. This hallmark has both benefits and challenges. On one hand, this is arguably the purpose of frameworks, to structure the basic ideas of theory or conceptual thinking, and if they were more detailed they would be models. On the other hand, there is often a “black box” nature to frameworks. It is often unclear why some sets of concepts and relationships are chosen for integration into frameworks, and others not. As argued below, these choices are often the result of the positionality of the framework’s creators. Publications of frameworks, furthermore, often lack descriptions of their value and potential uses compared to other frameworks or analytical tools that exist in the field.

Now shifting focus to how frameworks are applied. Some frameworks provide measureable indicators as the key variables in the framework, but many only suggest general concepts. This creates the need to link concepts and their relationships to data through other more tangible indicators. Methods to measure such indicators will also be needed in new empirical studies. These methodological and study design steps necessary to associate data to framework concepts is often referred to as “operationalizing” a framework. However, without guidance on how to do this, scholars are often left with developing their own strategies, which can lead to heterogeneous and idiosyncratic methods and data. These challenges can be referred to as methodological gaps (Partelow 2018 ), where the details of how to move from concept to indicator to measurement to data transformation, are not always detailed in a way that welcomes replicability or learning. This is not necessarily a problem if the purpose of a framework is to only guide the analysis of individual cases or synthesis activities in isolation, for example to inform local management, but it hinders meta-analyses, cross-case learning and data interpretability for others.

In this article, a brief overview of framework definitions and current synthesis literature are reviewed in the “ What is a framework? ” section. This is coupled with the argument that frameworks often lack clarity in their development and application because their positioning within a theory of science is unclear. In the “ Mechanisms of framework development and use: a meta-framework ” section, a meta-framework is proposed to assist in clarifying the four major levers with which frameworks are developed and applied: (1) empirical generalization, (2) theoretical fitting, (3) hypothesizing, and (4) application. The meta-framework aims to position individual frameworks into a theory of science, which can enable scholars to take a conceptual “step back” in order to view how their engagement with a framework contributes to their broader scientific goal and field. Two case studies of different frameworks are provided to explore how the meta-framework can aid in comparing them. This is followed by a discussion of what makes a good framework, along with explicit guiding points for the use of frameworks in research and policy practice.

What is a framework?

The definition and purpose of a framework is likely to vary across disciplines and thematic fields (Cox et al. 2016 ). There is no universal definition of a framework, but it is useful to provide a brief overview of different definitions for orientation. The Cambridge Dictionary states that frameworks are “a supporting structure around which something can be built; a system of rules, ideas, or beliefs that is used to plan or decide something.” Schlager ( 2007 , 293) states that “frameworks provide a foundation for inquiry,” and Cumming ( 2014 , 5) adds that this “does not necessarily depend on deductive logic to connect different ideas.” Importantly, Binder et al., ( 2013 , 2) note that “a framework provides a set of assumptions, concepts, values and practices,” emphasizing the normative or inherently subjective logic to framework development. A core theme being plurality and connectivity. Similarly, McGinnis and Ostrom ( 2014a , 1) define frameworks as “the basic vocabulary of concepts and terms that may be used to construct the kinds of causal explanations expected of a theory. Frameworks organize diagnostic, descriptive, and prescriptive inquiry.” In a review comparing ten commonly used frameworks in social-ecological systems (SES) research, Binder et al., ( 2013 , 1) state that frameworks are useful for developing “a common language, to structure research on SES, and to provide guidance toward a more sustainable development of SES.” In a similar review, Pulver et al., ( 2018 , 1) suggest that frameworks “assist scholars and practitioners to analyze the complex, nonlinear interdependencies that characterize interactions between biophysical and social arenas and to navigate the new epistemological, ontological, analytical, and practical horizons of integrating knowledge for sustainability solutions.” It is important to recognize that the above claims often suggest the dualistic or bridging positions held by frameworks, in both theory building and for guiding empirical observations. However, there is relatively little discussion in the above literature on how frameworks act as bridging tools within a theory of science or how frameworks add value as positioning tools in a field.

Every framework has a position, meaning it is located within a specific context of a scientific field. As positioning tools, frameworks seem to “populate the scientist’s world with a set of conceptual objects and (non-causal) relationships among them,” shaping (and sometimes limiting) the way we think about problems and potential solutions (Cox et al. 2016 , 47). Thus, using a specific framework helps in part to position the work of a researcher in a field and its related concepts, theories and paradigms.

Four factors can be considered to evaluate the positioning of a framework: (a) who developed it, (b) the values being put forth by those researchers, (c) the research questions engaged with, and (d) the field in which it is embedded. For example, the Social-Ecological Systems Framework (SESF) (Ostrom 2009 ) was developed by (a) Elinor Ostrom who developed the framework studying common-pool resource and public goods governance from the 1960s until the 2000s. Ostrom’s overall goal was (b) to examine the hindering and enabling conditions for governance to guide the use and provision common goods towards sustainability outcomes. Her primary research questions (c) related to collective action theory, unpacking how and why people cooperate with each other or not. The field her work is embedded in (d) is an interdisciplinary mix between public policy, behavioral and institutional economics. Scholars who use Ostrom’s SESF today, carry this history with them and therefore position themselves, whether implicitly or explicitly, as part of this research landscape as systems thinkers and interdisciplinarians, even if they have other scholarly positions.

Frameworks are positioned within a theory of science. Understanding this positioning can guide scholars in comprehending how their engagement with frameworks contributes to the overall advancement of their field. To do this, taking a conceptual “step back” is necessary, to distinguish between different levels of theory in science. From the conceptually broadest to the most empirically specific, we can identify the following levels of theory: paradigms, frameworks, specific theories, models/archetypes and cases (Table 1 ). Knowledge production processes flow up and down these levels of theory. For example, as argued by Kuhn ( 1962 ), the purpose of a scientific field is to advance its paradigm. Thus, the study of empirical observations (e.g., case studies) — and the development of models or theories resulting from those data — are aimed at advancing the overarching paradigm. Such paradigms could be conservation, democracy, sustainable development or social-ecological systems.

There is a need to connect cases, models and specific theory up to the overall paradigms of a field to make aggregate knowledge gains. Here, the role of frameworks becomes more clear, as bridging tools that enable connections between levels of knowledge. From the top down, frameworks can specify paradigms with more tangible conceptual features and relationships, which can then guide empirical inquiry. For example, the Driver-Pressure-State-Impact-Response (DPSIR) framework (Smeets and Weterings 1999 ; Ness, Anderberg, and Olsson 2010 ) specifies how to evaluate policy options and their effects by focusing on the five embedded concepts in a relational order. Scholars can then generate more specific indicators and methods to measure the five specified features of the framework, and their relationships, to generate empirical insights that now have a direct link to the paradigm of sustainable policy development via the framework.

Furthermore, frameworks can also emerge from the bottom up, by distilling empirical data across cases and thus creating a knowledge bridge of more specified conceptual features and relationships that connect to a paradigm. In both top-down and bottom-up mechanism, frameworks can play a vital role in synthesizing and communicating ideas among scholars in a field — from empirical data to a paradigm. A challenge may be, however, that multiple frameworks have emerged attempting to specify the core conceptual features and relationships in a paradigm. A mature scientific field is likely to have many frameworks to guide research and debate. There is, however, a lack of research and tools available to compare frameworks and their added value.

Beyond their use as positioning tools, frameworks make day-to-day science easier. They can guide researchers in designing new empirical research by indicating which core concepts and relationships are of interest to be measured and compared. Scientific fields also need common fires to huddle around, meaning that we need reference points to initiate scholarly debates, coordinate disparate empirical efforts and to communicate findings and novel advancements through a common language (McGinnis and Ostrom 2014a ; Ban and Cox 2017 ). As such, frameworks are useful for synthesis research, focusing the attention of reviews and meta-analyses around core sets of concepts and relationships.

There is, however, a tension between frameworks that aim to capture complexity and those that aim to simplify core principles. Complexity oriented frameworks often advance systems thinking at the risk of including too many variables. They often have long lists of variables which makes empirical orientation and synthesis difficult. On the other hand, simplification frameworks face the challenge of leaving important things out, with the benefit of clarifying what may be important and giving clear direction.

From a more critical perspective, the “criteria for comparing frameworks are not well developed,” (Schlager, 2007 , 312), and the positionality of frameworks has not been rigorously explored outside of smaller studies. Nonetheless, numerous classifications or typologies of frameworks within specific fields have been suggested (Table 2 ), although not with reference to positionality (Spangenberg 2011 ; Binder et al. 2013 ; Cumming 2014 ; Schlager 2007 ; Ness et al. 2007 ; Potschin-Young et al. 2018 ; Cox et al. 2021 ; Louder et al. 2021 ; Chofreh and Goni 2017 ; Alaoui et al. 2022 ; Tapio and Willamo 2008 ). These studies point to the question of: what makes a good framework? Are there certain quality criteria that make some frameworks more useful than others? There has undoubtedly been a rise in the number of frameworks, but as expressed by Ban and Cox ( 2017 , 2), “it is not clear what the role of a scientific framework should be, and relatedly, what makes for a successful scientific framework. Although there are many frameworks […] there is little discussion on what their scientific role ought to be, other than providing a common scientific language.” The meta-framework presented below serves as a tool for answering these questions and provides guidance for developing and implementing frameworks in a range of settings.

Mechanisms of framework development and use: a meta-framework

This section presents a meta-framework detailing the mechanisms of framework development and use (Fig. 1 ). The meta-framework illustrates the role of frameworks as bridging tools for knowledge synthesis and communication. Therefore, the purpose of the meta-framework is to demonstrate how the mechanisms of framework development and use act as levers of knowledge flow across levels within a theory of science, doing so by enabling the communication and synthesis of knowledge. Introducing the meta-framework has two parts, outlined below.

A meta-framework outlining the central role frameworks play in scientific advancement through their development and use. In the center, frameworks provide two core bridging values: knowledge synthesis and knowledge communication. Three modes of logical reasoning contribute to framework development: induction, deduction and abduction. Frameworks are used and developed through four mediating processes: (1) empirical generalization, (2) theoretical fitting, (3) application, and (4) hypothesizing

First, the meta-framework visualizes the levels along the scale of scientific theory including paradigms, frameworks, specific theory and empirical observations, introduced above. Along this scale, three mechanisms of logical reasoning are typical: induction, deduction, and abduction. Induction is a mode of logical reasoning based on sets of empirical observations, which, when patterns within those observations emerge, can inform more generalized theory formation. Induction, in its pure form, is reasoning without prior assumptions about what we think is happening. In contrast, deduction is a mode of logical reasoning based on testing a claim or hypothesis, often based on a body of theory, against an observation to infer whether or not a claim is true. In contrast to induction, which always leads to probable or fuzzy conclusions, deductive logic provides true or false conclusions. A third mode of logical reasoning is abduction. Abduction starts with a single or limited set of observations, and assumes the most likely cause as a conclusion. Abduction can only provide probable conclusions. Knowledge claims from all three modes of logical reasoning are part of the nexus of potential framework creation or modification.

Second, the meta-framework has four iterative mediating processes that directly enable the development and/or application of frameworks (Fig. 1 ). Two of the four mediating processes relate to framework development: (1) empirical generalization and (2) theoretical fitting. The other two relate to framework application: (3) hypothesizing, and (4) application (Fig. 1 , Table 3 ). The details of the specific mediating pathways are outlined in Table 3 , including the processes involved in each. There are numerous potential benefits and challenges associated with each (Table 3 ).

The value of a meta-framework

The presented meta-framework (Fig. 1 ) allows us to assess the values different frameworks can provide. If a framework provides a novel synthesis of key ideas or new developments in a field, and communicates those insights well in its composition, it likely adds notable value. If a framework coordinates scientific inquiry across the 1 or more of the four mediating processes, it likely acts as an important gatekeeper and boundary object for what may otherwise be disparate or tangential research. If it contributes substantial advances in 3 or 4 of the mediating processes, the value of the framework is likely higher.

The meta-framework can further help identify the positioning of framework such as the type of logical reasoning processes used to create it, as well as help clarify the role of a framework along the scale of knowledge production (i.e., from data to paradigm). It might be clear, for example, what paradigm or specific theory a framework contributes to. The meta-framework can add value by guiding the assessment of how frameworks fit into the bigger picture of knowledge contribution in their field. Furthermore, many scholars and practitioners are interested in developing new frameworks. The meta-framework outlines the mechanisms that can be considered in creating the framework as well as help developers of new frameworks communicate how their frameworks add value. For example, to link empirical data collection to theoretical work in their field.

The meta-framework can help compare frameworks, to assess strengths and weaknesses in terms of their positioning and knowledge production mechanisms. It can also help elucidate the need for, or value of, new frameworks. This challenge is noted by Cumming ( 2014 , 18) in the field of social-ecological systems, reflecting that “the tendency of researchers to develop “new” frameworks without fully explaining how they relate to other existing frameworks and what new elements they bring to the problem is another obvious reason for the lack of a single dominant, unifying framework.” To showcase such as comparison, two brief examples are provided. The first example features the Driver-Pressure-State-Impact-Response (DPSIR) framework developed by the European Environmental Agency (EEA) (Box 1 ) (Smeets and Weterings 1999 ; Ness, Anderberg, and Olsson 2010 ). The DPSIR framework exemplifies a framework developed from the top-down (theoretical fitting) approach, to better organize the policy goal and paradigm of environmental sustainability to the indicators collected by EU member states. The second example highlights the Social-Ecological Systems Framework (SESF) developed by Elinor Ostrom (Box 2 ) (Ostrom 2009 ; McGinnis and Ostrom 2014a ). The SESF exemplifies a framework developed from the bottom up (empirical generalization) to aggregate data into common variables to enable data standardization and comparison towards theory building to improve environmental governance. In the case examples (Box 1 ; Box 2 ), we can see the value of both frameworks from different perspectives. The examples briefly illustrate how the positionality of each framework dictates how others use them to produce knowledge towards a paradigm. In the case of the DPSIR framework, from the top-down towards a policy goal, and with the SESF, from the bottom-up towards a theoretical goal.

Drivers – Pressures – State – Impact - Response (DPSIR) framework

Social-Ecological Systems Framework (SESF)

Discussion and directions forward

Frameworks are commons objects to huddle around in academic and practitioner communities, providing identity and guiding our effort. They focus scholarly attention on important issues, stimulate cognitive energy and provide fodder for discussion. However, reflection on the role and purpose of the frameworks we use needs to be a more common practice in science. The proposed meta-framework aims to showcase the role of frameworks as boundary objects that connect ideas and concepts to data in constructive and actionable ways, enabling knowledge to be built up and aggregated within scientific fields through using common languages and concepts (Mollinga 2008 ; Klein 1996 ).

Boundary objects such as frameworks can be especially important for inter- and transdisciplinary collaboration, where there may be few prior shared points of conceptual understanding or terminology beyond a problem context. Mollinga ( 2008 , 33) reflects that “frameworks are typical examples of boundary objects, building connections between the worlds of science and that of policy, and between different knowledge domains,” and that “the development of frameworks is at present probably the most common strategy in the field of natural resources management to achieve integration and interdisciplinarity,” (Mollinga, 2008 , 31). They are, however, critically important for both disciplinary specific fundamental research, as well as for bridging science-society gaps through translating often esoteric academic concepts and findings into digestible and often visual objects. For example, the DPSIR framework (Box 1 ) attempts to better organize the analysis of environmental indicators for policy evaluation processes in the EU. Furthermore, Partelow et al., ( 2019 ) and Gurney et al., ( 2019 ) both use Ostrom’s SESF (Box 2 ) as a boundary object at the science-society interface to visually communicate systems thinking and social-ecological interactions to fishers and coastal stakeholders involved in local management decision-making.

An important feature of frameworks is that the very contestation over their nature is perhaps their main value. A framework can only be an effective boundary object if it catalyzes deliberation and scholarly debate — thus contestation over what it is and its value is seeded into the toolbox and identity of a scholarly field. Although most frameworks are likely to have shortcomings, flaws or controversial features, the fact that they motivate engagement around common problems and stimulate scholarly engagement is a value of its own. In doing so, frameworks often become symbols of individual and community identity in contested spaces. This is evidenced in how frameworks are often used to stamp our research as valid, relevant and important to the field, even if done passively. Citing a framework both communicates the general purpose of what a scholar is attempting to achieve to others, and orients science towards a common synthetic object for future knowledge synthesis and debate. These positioning actions are essential for science and practitioner communities to understand a research or policy project, its aims and assumptions. Historically, disciplines have provided this value – signaling the problems, methods and theories one is likely to engage with. Frameworks can act as tools for bridging disciplines, helping to catalyze interdisciplinary engagement (Mollinga 2008 ; Klein 1996 ). As many scientific communities shift focus towards solving real-world problems (e.g., climate change, gender equality), tools that can help scientists’ cooperate and communicate, such as a framework, will continue to play a vital role in achieving knowledge co-production goals.

Guiding points for framework engagement

An aim of this article is not only to reflect on the purpose, value and positioning of frameworks, but to provide some take-away advice for engaging with frameworks in current or future work. Over the course of this article, the question of “What makes a good framework?” has been explored. The meta-framework outlines mechanisms of useful frameworks and can help understand the positioning of frameworks. Nonetheless, more detailed guiding points can be specified for both the use and development of frameworks going forward. A series of guiding points are outlined in Table 4 , generated from the literature cited throughout this article, feedback from colleagues and personal experiences applying and developing numerous frameworks. The guiding points focus on the two types of mediating processes, framework development and use (Table 4 ).

In conclusion, we need to know our academic tools in order make the best use of them in our own research, practice and knowledge communities. Frameworks have gained substantial popularity for the communication and synthesis of academic ideas, and as tools we all have the ability to create and perhaps the responsibility to steward. However, frameworks have struggled to find roots in a theory of science which grounds their contributions in relation to other scientific tools such as models, specific theories and empirical data. There is also a lack of discussion about what makes a good framework and how to apply frameworks in a way to makes those applications of integrative value to an overall community of scholars positioned around it. The meta-framework provided in this article offers insights into how to understand the purpose and positionality of frameworks, as well as the mechanisms for understanding the creation and application of frameworks. The meta-framework further allows for the comparison of frameworks to assess their value.

Alaoui A, Barão L, Ferreira CSS, Hessel R (2022) An Overview of sustainability assessment frameworks in agriculture. Land 11(4):1–26. https://doi.org/10.3390/land11040537

Article   Google Scholar  

Ban NC, Cox M (2017) Advancing social-ecological research through teaching: summary, observations, and challenges. Ecol Soc 22(1):1–3

Biermann F, Betsill MM, Gupta J, Kanie N, Lebel L, Liverman D, Schroeder H, Siebenhüner B, Zondervan R (2010) Earth system governance: a research framework. Int Environ Agreem Polit 10(4):277–298. https://doi.org/10.1007/s10784-010-9137-3

Binder CR, Hinkel J, Bots PWG, Pahl-Wostl C (2013) Comparison of Frameworks for analyzing social-ecological systems. Ecol Soc 18(4):26. https://doi.org/10.5751/ES-05551-180426

Chofreh AG, Goni FA (2017) Review of frameworks for sustainability implementation. Sustain Dev 25(3):180–188. https://doi.org/10.1002/sd.1658

Colding J, Barthel S (2019) Exploring the social-ecological systems discourse 20 years later. Ecol Soc 24(1). https://doi.org/10.5751/es-10598-240102

Cox M, Gurney GG, Anderies JM, Coleman E, Darling E, Epstein G, Frey UJ (2021) Lessons learned from synthetic research projects based on the ostrom workshop frameworks. Ecol Soc 26(1)

Cox M, Villamayor-tomas S, Epstein G, Evans L, Ban NC, Fleischman F, Nenadovic M, Garcia-lopez G (2016) Synthesizing theories of natural resource management and governance. Glob Environ Chang 39(January):45–56. https://doi.org/10.1016/j.gloenvcha.2016.04.011

Cumming GS (2014) Theoretical Frameworks for the analysis of social-ecological systems. In: Sakai S, Umetsu C (eds) Social-Ecological Systems in Transition . Springer, Japan. https://doi.org/10.1007/978-4-431-54910-9

Chapter   Google Scholar  

Díaz S, Demissew S, Carabias J, Joly C, Lonsdale M, Ash N, Larigauderie A et al (2015) The IPBES conceptual framework - connecting nature and people. Curr Opin Environ Sustain 14:1–16. https://doi.org/10.1016/j.cosust.2014.11.002

Gurney GG, Darling ES, Jupiter SD, Mangubhai S, McClanahan TR, Lestari P, Pardede S et al (2019) Implementing a social-ecological systems framework for conservation monitoring: lessons from a multi-country coral reef program. Biol Conserv 240(August). https://doi.org/10.1016/j.biocon.2019.108298

Kuhn T (1962) The structure of scientific revolutions (University of Chicago Press)

Klein JT (1996) Crossing boundaries: knowledge, disciplinarities, and interdisciplinarities . University of Virginia Press, Charlottesville and London

Google Scholar  

Louder E, Wyborn C, Cvitanovic C, Bednarek AT (2021) A Synthesis of the frameworks available to guide evaluations at the interface of environmental science on policy and practice. Environ Sci Policy 116(July 2020):1–27. https://doi.org/10.1016/j.envsci.2020.12.006

McGinnis MD, Ostrom E (2014a) Social-Ecological system framework: initial changes and continuing challenges. Ecol Soc 19(2). https://doi.org/10.5751/ES-06387-190230

Mollinga PP (2008) In: Evers H-D, Gerke S, Mollinga P, Schetter C (eds) The rational organisation of dissent: boundary concepts, boundary objects and boundary settings in the interdisciplinary Study of Natural Resources Management. University of Bonn, Bonn

Nagel B, Partelow S (2022) A methodological guide for applying the ses framework: a review of quantitative approaches. Ecol Soc

Ness B, Anderberg S, Olsson L (2010) Structuring problems in sustainability science: the multi-Level DPSIR framework. Geoforum 41(3):479–488. https://doi.org/10.1016/j.geoforum.2009.12.005

Ness B, Urbel-Piirsalu E, Anderberg S, Olsson L (2007) Categorising tools for sustainability assessment. Ecol Econ 60(3):498–508. https://doi.org/10.1016/j.ecolecon.2006.07.023

Ostrom E (2009) A general framework for analyzing sustainability of social-ecological systems. Science 325(5939):419–422. https://doi.org/10.1126/science.1172133

Article   CAS   Google Scholar  

Partelow S (2018) A review of the social-ecological systems framework: applications, methods, modifications and challenges. Ecol Soc

Partelow S, Fujitani M, Soundararajan V, Schlüter A (2019) Transforming the social-ecological systems framework into a knowledge exchange and deliberation tool for comanagement. Ecol Soc 24(1). https://doi.org/10.5751/ES-10724-240115

Potschin-Young M, Haines-Young R, Görg C, Heink U, Jax K, Schleyer C (2018) Understanding the role of conceptual frameworks: reading the ecosystem service cascade. Ecosyst Serv. https://doi.org/10.1016/j.ecoser.2017.05.015

Pulver S, Ulibarri N, Sobocinski KL, Alexander SM, Johnson ML, Mccord PF (2018) Frontiers in socio-environmental research: components, connections, scale, and context. Ecol Soc 23(3)

Schlager E (2007) A Comparison of frameworks, theories, and models of policy processes. In: Sabatier PA (ed) Theories of the Policy Process , 1st edn. Routledge, pp 293–319

Smeets E, Weterings R (1999) Environmental indicators: typology and overview. In: Bosch P, Büchele M, Gee D (eds) European Environment Agency (EEA) , vol 50. European Environment Agency, Copenhagan

Spangenberg JH (2011) Sustainability Science: a review, an analysis and some empirical lessons. Environ Conserv 38(3):275–287. https://doi.org/10.1017/S0376892911000270

Tapio P, Willamo R (2008) Developing Interdisciplinary environmental frameworks. Ambio 37(2):125–133. https://doi.org/10.1579/0044-7447(2008)37[125:DIEF]2.0.CO;2

UN (2019) Independent Group of Scientists appointed by the Secretary-General, Global Sustainable Development Report 2019: The Future is Now – Science for Achieving Sustainable Development. United Nations, New York

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Acknowledgements

I would like to thank Michael Cox and Achim Schlüter for their helpful feedback on previous versions of the manuscript and the ideas within it. I am grateful to the Leibniz Centre for Tropical Marine Research (ZMT) in Bremen, and the Center for Life Ethics at the University of Bonn for support.

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Partelow, S. What is a framework? Understanding their purpose, value, development and use. J Environ Stud Sci 13 , 510–519 (2023). https://doi.org/10.1007/s13412-023-00833-w

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Organizing Academic Research Papers: Theoretical Framework

• Purpose of Guide
• Design Flaws to Avoid
• Glossary of Research Terms
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Choosing a Title
• Making an Outline
• Paragraph Development
• Executive Summary
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tertiary Sources
• What Is Scholarly vs. Popular?
• Qualitative Methods
• Quantitative Methods
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Annotated Bibliography
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• How to Manage Group Projects
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• Reviewing Collected Essays
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Research Proposal
• Acknowledgements

Theories are formulated to explain, predict, and understand phenomena and, in many cases, to challenge and extend existing knowledge, within the limits of the critical bounding assumptions. The theoretical framework is the structure that can hold or support a theory of a research study. The theoretical framework introduces and describes the theory which explains why the research problem under study exists.

Importance of Theory

A theoretical framework consists of concepts, together with their definitions, and existing theory/theories that are used for your particular study. The theoretical framework must demonstrate an understanding of theories and concepts that are relevant to the topic of your  research paper and that will relate it to the broader fields of knowledge in the class you are taking.

The theoretical framework is not something that is found readily available in the literature . You must review course readings and pertinent research literature for theories and analytic models that are relevant to the research problem you are investigating. The selection of a theory should depend on its appropriateness, ease of application, and explanatory power.

The theoretical framework strengthens the study in the following ways .

• An explicit statement of  theoretical assumptions permits the reader to evaluate them critically.
• The theoretical framework connects the researcher to existing knowledge. Guided by a relevant theory, you are given a basis for your hypotheses and choice of research methods.
• Articulating the theoretical assumptions of a research study forces you to address questions of why and how. It permits you to move from simply describing a phenomenon observed to generalizing about various aspects of that phenomenon.
• Having a theory helps you to identify the limits to those generalizations. A theoretical framework specifies which key variables influence a phenomenon of interest. It alerts you to examine how those key variables might differ and under what circumstances.

By virtue of its application nature, good theory in the social sciences is of value precisely because it fulfills one primary purpose: to explain the meaning, nature, and challenges of a phenomenon, often experienced but unexplained in the world in which we live, so that we may use that knowledge and understanding to act in more informed and effective ways.

The Conceptual Framework. College of Education. Alabama State University; Drafting an Argument . Writing@CSU. Colorado State University; Trochim, William M.K. Philosophy of Research. Research Methods Knowledge Base. 2006.

Strategies for Developing the Theoretical Framework

I.  Developing the Framework

Here are some strategies to develop of an effective theoretical framework:

• Examine your thesis title and research problem . The research problem anchors your entire study and forms the basis from which you construct your theoretical framework.
• Brainstorm on what you consider to be the key variables in your research . Answer the question, what factors contribute to the presumed effect?
• Review related literature to find answers to your research question.
• List  the constructs and variables that might be relevant to your study. Group these variables into independent and dependent categories.
• Review the key social science theories that are introduced to you in your course readings and choose the theory or theories that can best explain the relationships between the key variables in your study [note the Writing Tip on this page].
• Discuss the assumptions or propositions of this theory and point out their relevance to your research.

A theoretical framework is used to limit the scope of the relevant data by focusing on specific variables and defining the specific viewpoint (framework) that the researcher will take in analyzing and interpreting the data to be gathered, understanding concepts and variables according to the given definitions, and building knowledge by validating or challenging theoretical assumptions.

II.  Purpose

Think of theories as the conceptual basis for understanding, analyzing, and designing ways to investigate relationships within social systems. To the end, the following roles served by a theory can help guide the development of your framework.*

• Means by which new research data can be interpreted and coded for future use,
• Response to new problems that have no previously identified solutions strategy,
• Means for identifying and defining research problems,
• Means for prescribing or evaluating solutions to research problems,
• Way of telling us that certain facts among the accumulated knowledge are important and which facts are not,
• Means of giving old data new interpretations and new meaning,
• Means by which to identify important new issues and prescribe the most critical research questions that need to be answered to maximize understanding of the issue,
• Means of providing members of a professional discipline with a common language and a frame of reference for defining boundaries of their profession, and
• Means to guide and inform research so that it can, in turn, guide research efforts and improve professional practice.

*Adapted from: Torraco, R. J. “Theory-Building Research Methods.” In Swanson R. A. and E. F. Holton III , editors. Human Resource Development Handbook: Linking Research and Practice . (San Francisco, CA: Berrett-Koehler, 1997): pp. 114-137; Sutton, Robert I. and Barry M. Staw. “What Theory is Not.” Administrative Science Quarterly 40 (September 1995): 371-384.

Structure and Writing Style

The theoretical framework may be rooted in a specific theory , in which case, you are expected to test the validity of an existing theory in relation to specific events, issues, or phenomena. Many social science research papers fit into this rubric. For example, Peripheral Realism theory, which categorizes perceived differences between nation-states as those that give orders, those that obey, and those that rebel, could be used as a means for understanding conflicted relationships among countries in Africa. A test of this theory could be the following: Does Peripheral Realism theory help explain intra-state actions, such as, the growing split between southern and northern Sudan that may likely lead to the creation of two nations?

However, you may not always be asked by your professor to test a specific theory in your paper, but to develop your own framework from which your analysis of the research problem is derived . Given this, it is perhaps easiest to understand the nature and function of a theoretical framework if it is viewed as the answer to two basic questions:

• What is the research problem/question? [e.g., "How should the individual and the state relate during periods of conflict?"]
• Why is your approach a feasible solution? [I could choose to test Instrumentalist or Circumstantialists models developed among Ethnic Conflict Theorists that rely upon socio-economic-political factors to explain individual-state relations and to apply this theoretical model to periods of war between nations].

The answers to these questions come from a thorough review of the literature and your course readings [summarized and analyzed in the next section of your paper] and the gaps in the research that emerge from the review process. With this in mind, a complete theoretical framework will likely not emerge until after you have completed a thorough review of the literature .

In writing this part of your research paper, keep in mind the following:

• Clearly describe the framework, concepts, models, or specific theories that underpin your study . This includes noting who the key theorists are in the field who have conducted research on the problem you are investigating and, when necessary, the historical context that supports the formulation of that theory. This latter element is particularly important if the theory is relatively unknown or it is borrowed from another discipline.
• Position your theoretical framework within a broader context of related frameworks , concepts, models, or theories . There will likely be several concepts, theories, or models that can be used to help develop a framework for understanding the research problem. Therefore, note why the framework you've chosen is the appropriate one.
• The present tense is used when writing about theory.
• You should make your theoretical assumptions as explicit as possible . Later, your discussion of methodology should be linked back to this theoretical framework.
• Don’t just take what the theory says as a given! Reality is never accurately represented in such a simplistic way; if you imply that it can be, you fundamentally distort a reader's ability to understand the findings that emerge. Given this, always note the limitiations of the theoretical framework you've chosen [i.e., what parts of the research problem require further investigation because the theory does not explain a certain phenomena].

The Conceptual Framework. College of Education. Alabama State University; Conceptual Framework: What Do You Think is Going On? College of Engineering. University of Michigan; Drafting an Argument . Writing@CSU. Colorado State University; Lynham, Susan A. “The General Method of Theory-Building Research in Applied Disciplines.” Advances in Developing Human Resources 4 (August 2002): 221-241; Tavallaei, Mehdi and Mansor Abu Talib. A General Perspective on the Role of Theory in Qualitative Research. Journal of International Social Research 3 (Spring 2010); Trochim, William M.K. Philosophy of Research. Research Methods Knowledge Base. 2006.

Writing Tip

Borrowing Theoretical Constructs from Elsewhere

A growing and increasingly important trend in the social sciences is to think about and attempt to understand specific research problems from an interdisciplinary perspective. One way to do this is to not rely exclusively on the theories you've read about in a particular class, but to think about how an issue might be informed by theories developed in other disciplines. For example, if you are a political science student studying the rhetorical strategies used by female incumbants in state legislature campaigns, theories about the use of language could be derived, not only from political science, but linguistics, communication studies, philosophy, psychology, and, in this particular case, feminist studies. Building theoretical frameworks based on the postulates and hypotheses developed in other disciplinary contexts can be both enlightening and an effective way to be fully engaged in the research topic.

Another Writing Tip

Don't Undertheorize!

Never leave the theory hanging out there in the Introduction never to be mentioned again. Undertheorizing weakens your paper. The theoretical framework you introduce should guide your study throughout the paper. Be sure to always connect theory to the analysis and to explain in the discussion part of your paper how the theoretical framework you chose fit the research problem, or if appropriate, was inadequate in explaining the phenomenon you were investigating. In that case, don't be afraid to propose your own theory based on your findings.

Still Another Writing Tip

What's a Theory? What's a Hypothesis?

The terms theory and hypothesis are often used interchangeably in everyday use. However, the difference between them in scholarly research is important, particularly when using an experimental design. A theory is a well-established principle that has been developed to explain some aspect of the natural world. Theories arise from repeated observation and testing and incorporates facts, laws, predictions, and tested hypotheses that are widely accepted [e.g., rational choice theory; grounded theory].

A hypothesis is a specific, testable prediction about what you expect to happen in your study. For example, an experiment designed to look at the relationship between study habits and test anxiety might have a hypothesis that states, "We predict that students with better study habits will suffer less test anxiety." Unless your study is exploratory in nature, your hypothesis should always explain what you expect to happen during the course of your research.

The key distinctions are:

• A theory predicts events in a broad, general context;  a hypothesis makes a specific prediction about a specified set of circumstances.
• A theory has been extensively tested and is generally accepted among scholars; a hypothesis is a speculative guess that has yet to be tested.

Cherry, Kendra. Introduction to Research Methods: Theory and Hypothesis . About.com Psychology; Gezae, Michael et al. Welcome Presentation on Hypothesis . Slideshare presentation.

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Home » Conceptual Framework – Types, Methodology and Examples

Conceptual Framework – Types, Methodology and Examples

Table of Contents

Conceptual Framework

Definition:

A conceptual framework is a structured approach to organizing and understanding complex ideas, theories, or concepts. It provides a systematic and coherent way of thinking about a problem or topic, and helps to guide research or analysis in a particular field.

A conceptual framework typically includes a set of assumptions, concepts, and propositions that form a theoretical framework for understanding a particular phenomenon. It can be used to develop hypotheses, guide empirical research, or provide a framework for evaluating and interpreting data.

Conceptual Framework in Research

In research, a conceptual framework is a theoretical structure that provides a framework for understanding a particular phenomenon or problem. It is a key component of any research project and helps to guide the research process from start to finish.

A conceptual framework provides a clear understanding of the variables, relationships, and assumptions that underpin a research study. It outlines the key concepts that the study is investigating and how they are related to each other. It also defines the scope of the study and sets out the research questions or hypotheses.

Types of Conceptual Framework

Types of Conceptual Framework are as follows:

Theoretical Framework

A theoretical framework is an overarching set of concepts, ideas, and assumptions that help to explain and interpret a phenomenon. It provides a theoretical perspective on the phenomenon being studied and helps researchers to identify the relationships between different concepts. For example, a theoretical framework for a study on the impact of social media on mental health might draw on theories of communication, social influence, and psychological well-being.

Conceptual Model

A conceptual model is a visual or written representation of a complex system or phenomenon. It helps to identify the main components of the system and the relationships between them. For example, a conceptual model for a study on the factors that influence employee turnover might include factors such as job satisfaction, salary, work-life balance, and job security, and the relationships between them.

Empirical Framework

An empirical framework is based on empirical data and helps to explain a particular phenomenon. It involves collecting data, analyzing it, and developing a framework to explain the results. For example, an empirical framework for a study on the impact of a new health intervention might involve collecting data on the intervention’s effectiveness, cost, and acceptability to patients.

Descriptive Framework

A descriptive framework is used to describe a particular phenomenon. It helps to identify the main characteristics of the phenomenon and to develop a vocabulary to describe it. For example, a descriptive framework for a study on different types of musical genres might include descriptions of the instruments used, the rhythms and beats, the vocal styles, and the cultural contexts of each genre.

Analytical Framework

An analytical framework is used to analyze a particular phenomenon. It involves breaking down the phenomenon into its constituent parts and analyzing them separately. This type of framework is often used in social science research. For example, an analytical framework for a study on the impact of race on police brutality might involve analyzing the historical and cultural factors that contribute to racial bias, the organizational factors that influence police behavior, and the psychological factors that influence individual officers’ behavior.

Conceptual Framework for Policy Analysis

A conceptual framework for policy analysis is used to guide the development of policies or programs. It helps policymakers to identify the key issues and to develop strategies to address them. For example, a conceptual framework for a policy analysis on climate change might involve identifying the key stakeholders, assessing their interests and concerns, and developing policy options to mitigate the impacts of climate change.

Logical Frameworks

Logical frameworks are used to plan and evaluate projects and programs. They provide a structured approach to identifying project goals, objectives, and outcomes, and help to ensure that all stakeholders are aligned and working towards the same objectives.

Conceptual Frameworks for Program Evaluation

These frameworks are used to evaluate the effectiveness of programs or interventions. They provide a structure for identifying program goals, objectives, and outcomes, and help to measure the impact of the program on its intended beneficiaries.

Conceptual Frameworks for Organizational Analysis

These frameworks are used to analyze and evaluate organizational structures, processes, and performance. They provide a structured approach to understanding the relationships between different departments, functions, and stakeholders within an organization.

Conceptual Frameworks for Strategic Planning

These frameworks are used to develop and implement strategic plans for organizations or businesses. They help to identify the key factors and stakeholders that will impact the success of the plan, and provide a structure for setting goals, developing strategies, and monitoring progress.

Components of Conceptual Framework

The components of a conceptual framework typically include:

• Research question or problem statement : This component defines the problem or question that the conceptual framework seeks to address. It sets the stage for the development of the framework and guides the selection of the relevant concepts and constructs.
• Concepts : These are the general ideas, principles, or categories that are used to describe and explain the phenomenon or problem under investigation. Concepts provide the building blocks of the framework and help to establish a common language for discussing the issue.
• Constructs : Constructs are the specific variables or concepts that are used to operationalize the general concepts. They are measurable or observable and serve as indicators of the underlying concept.
• Propositions or hypotheses : These are statements that describe the relationships between the concepts or constructs in the framework. They provide a basis for testing the validity of the framework and for generating new insights or theories.
• Assumptions : These are the underlying beliefs or values that shape the framework. They may be explicit or implicit and may influence the selection and interpretation of the concepts and constructs.
• Boundaries : These are the limits or scope of the framework. They define the focus of the investigation and help to clarify what is included and excluded from the analysis.
• Context : This component refers to the broader social, cultural, and historical factors that shape the phenomenon or problem under investigation. It helps to situate the framework within a larger theoretical or empirical context and to identify the relevant variables and factors that may affect the phenomenon.
• Relationships and connections: These are the connections and interrelationships between the different components of the conceptual framework. They describe how the concepts and constructs are linked and how they contribute to the overall understanding of the phenomenon or problem.
• Variables : These are the factors that are being measured or observed in the study. They are often operationalized as constructs and are used to test the propositions or hypotheses.
• Methodology : This component describes the research methods and techniques that will be used to collect and analyze data. It includes the sampling strategy, data collection methods, data analysis techniques, and ethical considerations.
• Literature review : This component provides an overview of the existing research and theories related to the phenomenon or problem under investigation. It helps to identify the gaps in the literature and to situate the framework within the broader theoretical and empirical context.
• Outcomes and implications: These are the expected outcomes or implications of the study. They describe the potential contributions of the study to the theoretical and empirical knowledge in the field and the practical implications for policy and practice.

Conceptual Framework Methodology

Conceptual Framework Methodology is a research method that is commonly used in academic and scientific research to develop a theoretical framework for a study. It is a systematic approach that helps researchers to organize their thoughts and ideas, identify the variables that are relevant to their study, and establish the relationships between these variables.

Here are the steps involved in the conceptual framework methodology:

Identify the Research Problem

The first step is to identify the research problem or question that the study aims to answer. This involves identifying the gaps in the existing literature and determining what specific issue the study aims to address.

Conduct a Literature Review

The second step involves conducting a thorough literature review to identify the existing theories, models, and frameworks that are relevant to the research question. This will help the researcher to identify the key concepts and variables that need to be considered in the study.

Define key Concepts and Variables

The next step is to define the key concepts and variables that are relevant to the study. This involves clearly defining the terms used in the study, and identifying the factors that will be measured or observed in the study.

Develop a Theoretical Framework

Once the key concepts and variables have been identified, the researcher can develop a theoretical framework. This involves establishing the relationships between the key concepts and variables, and creating a visual representation of these relationships.

Test the Framework

The final step is to test the theoretical framework using empirical data. This involves collecting and analyzing data to determine whether the relationships between the key concepts and variables that were identified in the framework are accurate and valid.

Examples of Conceptual Framework

Some realtime Examples of Conceptual Framework are as follows:

• In economics , the concept of supply and demand is a well-known conceptual framework. It provides a structure for understanding how prices are set in a market, based on the interplay of the quantity of goods supplied by producers and the quantity of goods demanded by consumers.
• In psychology , the cognitive-behavioral framework is a widely used conceptual framework for understanding mental health and illness. It emphasizes the role of thoughts and behaviors in shaping emotions and the importance of cognitive restructuring and behavior change in treatment.
• In sociology , the social determinants of health framework provides a way of understanding how social and economic factors such as income, education, and race influence health outcomes. This framework is widely used in public health research and policy.
• In environmental science , the ecosystem services framework is a way of understanding the benefits that humans derive from natural ecosystems, such as clean air and water, pollination, and carbon storage. This framework is used to guide conservation and land-use decisions.
• In education, the constructivist framework is a way of understanding how learners construct knowledge through active engagement with their environment. This framework is used to guide instructional design and teaching strategies.

Applications of Conceptual Framework

Some of the applications of Conceptual Frameworks are as follows:

• Research : Conceptual frameworks are used in research to guide the design, implementation, and interpretation of studies. Researchers use conceptual frameworks to develop hypotheses, identify research questions, and select appropriate methods for collecting and analyzing data.
• Policy: Conceptual frameworks are used in policy-making to guide the development of policies and programs. Policymakers use conceptual frameworks to identify key factors that influence a particular problem or issue, and to develop strategies for addressing them.
• Education : Conceptual frameworks are used in education to guide the design and implementation of instructional strategies and curriculum. Educators use conceptual frameworks to identify learning objectives, select appropriate teaching methods, and assess student learning.
• Management : Conceptual frameworks are used in management to guide decision-making and strategy development. Managers use conceptual frameworks to understand the internal and external factors that influence their organizations, and to develop strategies for achieving their goals.
• Evaluation : Conceptual frameworks are used in evaluation to guide the development of evaluation plans and to interpret evaluation results. Evaluators use conceptual frameworks to identify key outcomes, indicators, and measures, and to develop a logic model for their evaluation.

Purpose of Conceptual Framework

The purpose of a conceptual framework is to provide a theoretical foundation for understanding and analyzing complex phenomena. Conceptual frameworks help to:

• Guide research : Conceptual frameworks provide a framework for researchers to develop hypotheses, identify research questions, and select appropriate methods for collecting and analyzing data. By providing a theoretical foundation for research, conceptual frameworks help to ensure that research is rigorous, systematic, and valid.
• Provide clarity: Conceptual frameworks help to provide clarity and structure to complex phenomena by identifying key concepts, relationships, and processes. By providing a clear and systematic understanding of a phenomenon, conceptual frameworks help to ensure that researchers, policymakers, and practitioners are all on the same page when it comes to understanding the issue at hand.
• Inform decision-making : Conceptual frameworks can be used to inform decision-making and strategy development by identifying key factors that influence a particular problem or issue. By understanding the complex interplay of factors that contribute to a particular issue, decision-makers can develop more effective strategies for addressing the problem.
• Facilitate communication : Conceptual frameworks provide a common language and conceptual framework for researchers, policymakers, and practitioners to communicate and collaborate on complex issues. By providing a shared understanding of a phenomenon, conceptual frameworks help to ensure that everyone is working towards the same goal.

When to use Conceptual Framework

There are several situations when it is appropriate to use a conceptual framework:

• To guide the research : A conceptual framework can be used to guide the research process by providing a clear roadmap for the research project. It can help researchers identify key variables and relationships, and develop hypotheses or research questions.
• To clarify concepts : A conceptual framework can be used to clarify and define key concepts and terms used in a research project. It can help ensure that all researchers are using the same language and have a shared understanding of the concepts being studied.
• To provide a theoretical basis: A conceptual framework can provide a theoretical basis for a research project by linking it to existing theories or conceptual models. This can help researchers build on previous research and contribute to the development of a field.
• To identify gaps in knowledge : A conceptual framework can help identify gaps in existing knowledge by highlighting areas that require further research or investigation.
• To communicate findings : A conceptual framework can be used to communicate research findings by providing a clear and concise summary of the key variables, relationships, and assumptions that underpin the research project.

Characteristics of Conceptual Framework

key characteristics of a conceptual framework are:

• Clear definition of key concepts : A conceptual framework should clearly define the key concepts and terms being used in a research project. This ensures that all researchers have a shared understanding of the concepts being studied.
• Identification of key variables: A conceptual framework should identify the key variables that are being studied and how they are related to each other. This helps to organize the research project and provides a clear focus for the study.
• Logical structure: A conceptual framework should have a logical structure that connects the key concepts and variables being studied. This helps to ensure that the research project is coherent and consistent.
• Based on existing theory : A conceptual framework should be based on existing theory or conceptual models. This helps to ensure that the research project is grounded in existing knowledge and builds on previous research.
• Testable hypotheses or research questions: A conceptual framework should include testable hypotheses or research questions that can be answered through empirical research. This helps to ensure that the research project is rigorous and scientifically valid.
• Flexibility : A conceptual framework should be flexible enough to allow for modifications as new information is gathered during the research process. This helps to ensure that the research project is responsive to new findings and is able to adapt to changing circumstances.

Advantages of Conceptual Framework

Advantages of the Conceptual Framework are as follows:

• Clarity : A conceptual framework provides clarity to researchers by outlining the key concepts and variables that are relevant to the research project. This clarity helps researchers to focus on the most important aspects of the research problem and develop a clear plan for investigating it.
• Direction : A conceptual framework provides direction to researchers by helping them to develop hypotheses or research questions that are grounded in existing theory or conceptual models. This direction ensures that the research project is relevant and contributes to the development of the field.
• Efficiency : A conceptual framework can increase efficiency in the research process by providing a structure for organizing ideas and data. This structure can help researchers to avoid redundancies and inconsistencies in their work, saving time and effort.
• Rigor : A conceptual framework can help to ensure the rigor of a research project by providing a theoretical basis for the investigation. This rigor is essential for ensuring that the research project is scientifically valid and produces meaningful results.
• Communication : A conceptual framework can facilitate communication between researchers by providing a shared language and understanding of the key concepts and variables being studied. This communication is essential for collaboration and the advancement of knowledge in the field.
• Generalization : A conceptual framework can help to generalize research findings beyond the specific study by providing a theoretical basis for the investigation. This generalization is essential for the development of knowledge in the field and for informing future research.

Limitations of Conceptual Framework

Limitations of Conceptual Framework are as follows:

• Limited applicability: Conceptual frameworks are often based on existing theory or conceptual models, which may not be applicable to all research problems or contexts. This can limit the usefulness of a conceptual framework in certain situations.
• Lack of empirical support : While a conceptual framework can provide a theoretical basis for a research project, it may not be supported by empirical evidence. This can limit the usefulness of a conceptual framework in guiding empirical research.
• Narrow focus: A conceptual framework can provide a clear focus for a research project, but it may also limit the scope of the investigation. This can make it difficult to address broader research questions or to consider alternative perspectives.
• Over-simplification: A conceptual framework can help to organize and structure research ideas, but it may also over-simplify complex phenomena. This can limit the depth of the investigation and the richness of the data collected.
• Inflexibility : A conceptual framework can provide a structure for organizing research ideas, but it may also be inflexible in the face of new data or unexpected findings. This can limit the ability of researchers to adapt their research project to new information or changing circumstances.
• Difficulty in development : Developing a conceptual framework can be a challenging and time-consuming process. It requires a thorough understanding of existing theory or conceptual models, and may require collaboration with other researchers.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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• Open access
• Published: 02 May 2024

Use of the International IFOMPT Cervical Framework to inform clinical reasoning in postgraduate level physiotherapy students: a qualitative study using think aloud methodology

• Katie L. Kowalski 1 ,
• Heather Gillis 1 ,
• Katherine Henning 1 ,
• Paul Parikh 1 ,
• Jackie Sadi 1 &
• Alison Rushton 1  

BMC Medical Education volume  24 , Article number:  486 ( 2024 ) Cite this article

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Metrics details

Vascular pathologies of the head and neck are rare but can present as musculoskeletal problems. The International Federation of Orthopedic Manipulative Physical Therapists (IFOMPT) Cervical Framework (Framework) aims to assist evidence-based clinical reasoning for safe assessment and management of the cervical spine considering potential for vascular pathology. Clinical reasoning is critical to physiotherapy, and developing high-level clinical reasoning is a priority for postgraduate (post-licensure) educational programs.

To explore the influence of the Framework on clinical reasoning processes in postgraduate physiotherapy students.

Qualitative case study design using think aloud methodology and interpretive description, informed by COnsolidated criteria for REporting Qualitative research. Participants were postgraduate musculoskeletal physiotherapy students who learned about the Framework through standardized delivery. Two cervical spine cases explored clinical reasoning processes. Coding and analysis of transcripts were guided by Elstein’s diagnostic reasoning components and the Postgraduate Musculoskeletal Physiotherapy Practice model. Data were analyzed using thematic analysis (inductive and deductive) for individuals and then across participants, enabling analysis of key steps in clinical reasoning processes and use of the Framework. Trustworthiness was enhanced with multiple strategies (e.g., second researcher challenged codes).

For all participants ( n  = 8), the Framework supported clinical reasoning using primarily hypothetico-deductive processes. It informed vascular hypothesis generation in the patient history and testing the vascular hypothesis through patient history questions and selection of physical examination tests, to inform clarity and support for diagnosis and management. Most participant’s clinical reasoning processes were characterized by high-level features (e.g., prioritization), however there was a continuum of proficiency. Clinical reasoning processes were informed by deep knowledge of the Framework integrated with a breadth of wider knowledge and supported by a range of personal characteristics (e.g., reflection).

Conclusions

Findings support use of the Framework as an educational resource in postgraduate physiotherapy programs to inform clinical reasoning processes for safe and effective assessment and management of cervical spine presentations considering potential for vascular pathology. Individualized approaches may be required to support students, owing to a continuum of clinical reasoning proficiency. Future research is required to explore use of the Framework to inform clinical reasoning processes in learners at different levels.

Peer Review reports

Introduction

Musculoskeletal neck pain and headache are highly prevalent and among the most disabling conditions globally that require effective rehabilitation [ 1 , 2 , 3 , 4 ]. A range of rehabilitation professionals, including physiotherapists, assess and manage musculoskeletal neck pain and headache. Assessment of the cervical spine can be a complex process. Patients can present to physiotherapy with vascular pathology masquerading as musculoskeletal pain and dysfunction, as neck pain and/or headache as a common first symptom [ 5 ]. While vascular pathologies of the head and neck are rare [ 6 ], they are important considerations within a cervical spine assessment to facilitate the best possible patient outcomes [ 7 ]. The International IFOMPT (International Federation of Orthopedic Manipulative Physical Therapists) Cervical Framework (Framework) provides guidance in the assessment and management of the cervical spine region, considering the potential for vascular pathologies of the neck and head [ 8 ]. Two separate, but related, risks are considered: risk of misdiagnosis of an existing vascular pathology and risk of serious adverse event following musculoskeletal interventions [ 8 ].

The Framework is a consensus document iteratively developed through rigorous methods and the best contemporary evidence [ 8 ], and is also published as a Position Statement [ 7 ]. Central to the Framework are clinical reasoning and evidence-based practice, providing guidance in the assessment of the cervical spine region, considering the potential for vascular pathologies in advance of planned interventions [ 7 , 8 ]. The Framework was developed and published to be a resource for practicing musculoskeletal clinicians and educators. It has been implemented widely within IFOMPT postgraduate (post-licensure) educational programs, influencing curricula by enabling a comprehensive and systemic approach when considering the potential for vascular pathology [ 9 ]. Frequently reported curricula changes include an emphasis on the patient history and incorporating Framework recommended physical examination tests to evaluate a vascular hypothesis [ 9 ]. The Framework aims to assist musculoskeletal clinicians in their clinical reasoning processes, however no study has investigated students’ use of the Framework to inform their clinical reasoning.

Clinical reasoning is a critical component to physiotherapy practice as it is fundamental to assessment and diagnosis, enabling physiotherapists to provide safe and effective patient-centered care [ 10 ]. This is particularly important for postgraduate physiotherapy educational programs, where developing a high level of clinical reasoning is a priority for educational curricula [ 11 ] and critical for achieving advanced practice physiotherapy competency [ 12 , 13 , 14 , 15 ]. At this level of physiotherapy, diagnostic reasoning is emphasized as an important component of a high level of clinical reasoning, informed by advanced use of domain-specific knowledge (e.g., propositional, experiential) and supported by a range of personal characteristics (e.g., adaptability, reflective) [ 12 ]. Facilitating the development of clinical reasoning improves physiotherapist’s performance and patient outcomes [ 16 ], underscoring the importance of clinical reasoning to physiotherapy practice. Understanding students’ use of the Framework to inform their clinical reasoning can support optimal implementation of the Framework within educational programs to facilitate safe and effective assessment and management of the cervical spine for patients.

To explore the influence of the Framework on the clinical reasoning processes in postgraduate level physiotherapy students.

Using a qualitative case study design, think aloud case analyses enabled exploration of clinical reasoning processes in postgraduate physiotherapy students. Case study design allows evaluation of experiences in practice, providing knowledge and accounts of practical actions in a specific context [ 17 ]. Case studies offer opportunity to generate situationally dependent understandings of accounts of clinical practice, highlighting the action and interaction that underscore the complexity of clinical decision-making in practice [ 17 ]. This study was informed by an interpretive description methodological approach with thematic analysis [ 18 , 19 ]. Interpretive description is coherent with mixed methods research and pragmatic orientations [ 20 , 21 ], and enables generation of evidence-based disciplinary knowledge and clinical understanding to inform practice [ 18 , 19 , 22 ]. Interpretive description has evolved for use in educational research to generate knowledge of educational experiences and the complexities of health care education to support achievement of educational objectives and professional practice standards [ 23 ]. The COnsolidated criteria for REporting Qualitative research (COREQ) informed the design and reporting of this study [ 24 ].

Research team

All research team members hold physiotherapy qualifications, and most hold advanced qualifications specializing in musculoskeletal physiotherapy. The research team is based in Canada and has varying levels of academic credentials (ranging from Clinical Masters to PhD or equivalent) and occupations (ranging from PhD student to Director of Physical Therapy). The final author (AR) is also an author of the Framework, which represents international and multiprofessional consensus. Authors HG and JS are lecturers on one of the postgraduate programs which students were recruited from. The primary researcher and first author (KK) is a US-trained Physical Therapist and Postdoctoral Research Associate investigating spinal pain and clinical reasoning in the School of Physical Therapy at Western University. Authors KK, KH and PP had no prior relationship with the postgraduate educational programs, students, or the Framework.

Study setting

Western University in London, Ontario, Canada offers a one-year Advanced Health Care Practice (AHCP) postgraduate IFOMPT-approved Comprehensive Musculoskeletal Physiotherapy program (CMP) and a postgraduate Sport and Exercise Medicine (SEM) program. Think aloud case analyses interviews were conducted using Zoom, a viable option for qualitative data collection and audio-video recording of interviews that enables participation for students who live in geographically dispersed areas across Canada [ 25 ]. Interviews with individual participants were conducted by one researcher (KK or KH) in a calm and quiet environment to minimize disruption to the process of thinking aloud [ 26 ].

Participants

AHCP postgraduate musculoskeletal physiotherapy students ≥ 18 years of age in the CMP and SEM programs were recruited via email and an introduction to the research study during class by KK, using purposive sampling to ensure theoretical representation. The purposive sample ensured key characteristics of participants were included, specifically gender, ethnicity, and physiotherapy experience (years, type). AHCP students must have attended standardized teaching about the Framework to be eligible to participate. Exclusion criteria included inability to communicate fluently in English. As think-aloud methodology seeks rich, in-depth data from a small sample [ 27 ], this study sought to recruit 8–10 AHCP students. This range was informed by prior think aloud literature and anticipated to balance diversity of participant characteristics, similarities in musculoskeletal physiotherapy domain knowledge and rich data supporting individual clinical reasoning processes [ 27 , 28 ].

Learning about the IFOMPT Cervical Framework

CMP and SEM programs included standardized teaching of the Framework to inform AHCP students’ clinical reasoning in practice. Delivery included a presentation explaining the Framework, access to the full Framework document [ 8 ], and discussion of its role to inform practice, including a case analysis of a cervical spine clinical presentation, by research team members AR and JS. The full Framework document that is publicly available through IFOMPT [ 8 ] was provided to AHCP students as the Framework Position Statement [ 7 ] was not yet published. Discussion and case analysis was led by AHCP program leads in November 2021 (CMP, including research team member JS) and January 2022 (SEM).

Think aloud case analyses data collection

Using think aloud methodology, the analytical processes of how participants use the Framework to inform clinical reasoning were explored in an interview with one research team member not involved in AHCP educational programs (KK or KH). The think aloud method enables description and explanation of complex information paralleling the clinical reasoning process and has been used previously in musculoskeletal physiotherapy [ 29 , 30 ]. It facilitates the generation of rich verbal [ 27 ]as participants verbalize their clinical reasoning protocols [ 27 , 31 ]. Participants were aware of the aim of the research study and the research team’s clinical and research backgrounds, supporting an open environment for depth of data collection [ 32 ]. There was no prior relationship between participants and research team members conducting interviews.

Participants were instructed to think aloud their analysis of two clinical cases, presented in random order (Supplementary  1 ). Case information was provided in stages to reflect the chronology of assessment of patients in practice (patient history, planning the physical examination, physical examination, treatment). Use of the Framework to inform clinical reasoning was discussed at each stage. The cases enabled participants to identify and discuss features of possible vascular pathology, treatment indications and contraindications/precautions, etc. Two research study team members (HG, PP) developed cases designed to facilitate and elicit clinical reasoning processes in neck and head pain presentations. Cases were tested against the research team to ensure face validity. Cases and think aloud prompts were piloted prior to use with three physiotherapists at varying levels of practice to ensure they were fit for purpose.

Data collection took place from March 30-August 15, 2022, during the final terms of the AHCP programs and an average of 5 months after standardized teaching about the Framework. During case analysis interviews, participants were instructed to constantly think aloud, and if a pause in verbalizations was sustained, they were reminded to “keep thinking aloud” [ 27 ]. As needed, prompts were given to elicit verbalization of participants’ reasoning processes, including use of the Framework to inform their clinical reasoning at each stage of case analysis (Supplementary  2 ). Aside from this, all interactions between participants and researchers minimized to not interfere with the participant’s thought processes [ 27 , 31 ]. When analysis of the first case was complete, the researcher provided the second case, each lasting 35–45 min. A break between cases was offered. During and after interviews, field notes were recorded about initial impressions of the data collection session and potential patterns appearing to emerge [ 33 ].

Data analysis

Data from think aloud interviews were analyzed using thematic analysis [ 30 , 34 ], facilitating identification and analysis of patterns in data and key steps in the clinical reasoning process, including use of the Framework to enable its characterization (Fig.  1 ). As established models of clinical reasoning exist, a hybrid approach to thematic analysis was employed, incorporating inductive and deductive processes [ 35 ], which proceeded according to 5 iterative steps: [ 34 ]

Data analysis steps

Familiarize with data: Audio-visual recordings were transcribed verbatim by a physiotherapist external to the research team. All transcripts were read and re-read several times by one researcher (KK), checking for accuracy by reviewing recordings as required. Field notes supported depth of familiarization with data.

Generate initial codes: Line-by-line coding of transcripts by one researcher (KK) supported generation of initial codes that represented components, patterns and meaning in clinical reasoning processes and use of the Framework. Established preliminary coding models were used as a guide. Elstein’s diagnostic reasoning model [ 36 ] guided generating initial codes of key steps in clinical reasoning processes (Table  1 a) [ 29 , 36 ]. Leveraging richness of data, further codes were generated guided by the Postgraduate Musculoskeletal Physiotherapy Practice model, which describes masters level clinical practice (Table  1 b) [ 12 ]. Codes were refined as data analysis proceeded. All codes were collated within participants along with supporting data.

Generate initial themes within participants: Coded data was inductively grouped into initial themes within each participant, reflecting individual clinical reasoning processes and use of the Framework. This inductive stage enabled a systematic, flexible approach to describe each participant’s unique thinking path, offering insight into the complexities of their clinical reasoning processes. It also provided a comprehensive understanding of the Framework informing clinical reasoning and a rich characterization of its components, aiding the development of robust, nuanced insights [ 35 , 37 , 38 ]. Initial themes were repeatedly revised to ensure they were grounded in and reflected raw data.

Develop, review and refine themes across participants: Initial themes were synthesized across participants to develop themes that represented all participants. Themes were reviewed and refined, returning to initial themes and codes at the individual participant level as needed.

Organize themes into established models: Themes were deductively organized into established clinical reasoning models; first into Elstein’s diagnostic reasoning model, second into the Postgraduate Musculoskeletal Physiotherapy Practice model to characterize themes within each diagnostic reasoning component [ 12 , 36 ].

Trustworthiness of findings

The research study was conducted according to an a priori protocol and additional steps were taken to establish trustworthiness of findings [ 39 ]. Field notes supported deep familiarization with data and served as a means of data source triangulation during analysis [ 40 ]. One researcher coded transcripts and a second researcher challenged codes, with codes and themes rigorously and iteratively reviewed and refined. Frequent debriefing sessions with the research team, reflexive discussions with other researchers and peer scrutiny of initial findings enabled wider perspectives and experiences to shape analysis and interpretation of findings. Several strategies were implemented to minimize the influence of prior relationships between participants and researchers, including author KK recruiting participants, KK and KH collecting/analyzing data, and AR, JS, HG and PP providing input on de-identified data at the stage of synthesis and interpretation.

Nine AHCP postgraduate level students were recruited and participated in data collection. One participant was withdrawn because of unfamiliarity with the standardized teaching session about use of the Framework (no recall of session), despite confirmation of attendance. Data from eight participants were used for analysis (CMP: n  = 6; SEM: n  = 2; Table  2 ), which achieved sample size requirements for think aloud methodology of rich and in-depth data [ 27 , 28 ].

Diagnostic reasoning components

Informed by the Framework, all components of Elstein’s diagnostic reasoning processes [ 36 ] were used by participants, including use of treatment with physiotherapy interventions to aid diagnostic reasoning. An illustrative example is presented in Supplement  3 . Clinical reasoning used primarily hypothetico-deductive processes reflecting a continuum of proficiency, was informed by deep Framework knowledge and breadth of prior knowledge (e.g., experiential), and supported by a range of personal characteristics (e.g., justification for decisions).

Cue acquisition

All participants sought to acquire additional cues early in the patient history, and for some this persisted into the medical history and physical examination. Cue acquisition enabled depth and breadth of understanding patient history information to generate hypotheses and factors contributing to the patient’s pain experience (Table  3 ). All participants asked further questions to understand details of the patients’ pain and their presentation, while some also explored the impact of pain on patient functioning and treatments received to date. There was a high degree of specificity to questions for most participants. Ongoing clinical reasoning processes through a thorough and complete assessment, even if the patient had previously received treatment for similar symptoms, was important for some participants. Cue acquisition was supported by personal characteristics including a patient-centered approach (e.g., understanding the patient’s beliefs about pain) and one participant reflected on their approach to acquiring patient history cues.

Hypothesis generation

Participants generated an average of 4.5 hypotheses per case (range: 2–8) and most hypotheses (77%) were generated rapidly early in the patient history. Knowledge from the Framework about patient history features of vascular pathology informed vascular hypothesis generation in the patient history for all participants in both cases (Table  4 ). Vascular hypotheses were also generated during the past medical history, where risk factors for vascular pathology were identified and interpreted by some participants who had high levels of suspicion for cervical articular involvement. Non-vascular hypotheses were generated during the physical examination by some participants to explain individual physical examination or patient history cues. Deep knowledge of the patient history section in the Framework supported high level of cue identification and interpretation for generating vascular hypotheses. Initial hypotheses were prioritized by some participants, however the level of specificity of hypotheses varied.

Cue evaluation

All participants evaluated cues throughout the patient history and physical examination in relationship to hypotheses generated, indicating use of hypothetico-deductive reasoning processes (Table  5 ). Framework knowledge of patient history features of vascular pathology was used to test vascular hypotheses and aid differential diagnosis. The patient history section supported high level of cue identification and interpretation of patient history features for all but one participant, and generation of further patient history questions for all participants. The level of specificity of these questions was high for all but one participant. Framework knowledge of recommended physical examination tests, including removal of positional testing, supported planning a focused and prioritized physical examination to further test vascular hypotheses for all participants. No participant indicated intention to use positional testing as part of their physical examination. Treatment with physiotherapy interventions served as a form of cue evaluation, and cues were evaluated to inform prognosis for some participants. At times during the physical examination, some participants demonstrated occasional errors or difficulty with cue evaluation by omitting key physical exam tests (e.g., no cranial nerve assessment despite concerns for trigeminal nerve involvement), selecting physical exam tests in advance of hypothesis generation (e.g., cervical spine instability testing), difficulty interpreting cues, or late selection of a physical examination test. Cue acquisition was supported by a range of personal characteristics. Most participants justified selection of physical examination tests, and some self-reflected on their ability to collect useful physical examination information to inform selection of tests. Precaution to the physical examination was identified by all participants but one, which contributed to an adaptable approach, prioritizing patient safety and comfort. Critical analysis of physical examination information aided interpretation within the context of the patient for most participants.

Hypothesis evaluation

All participants used the Framework to evaluate their hypotheses throughout the patient history and physical examination, continuously shifting their level of support for hypotheses (Table  6 , Supplement  4 ). This informed clarity in the overall level of suspicion for vascular pathology or musculoskeletal diagnoses, which were specific for most participants. Response to treatment with physiotherapy interventions served as a form of hypothesis evaluation for most participants who had low level suspicion for vascular pathology, highlighting ongoing reasoning processes. Hypotheses evaluated were prioritized by ranking according to level of suspicion by some participants. Difficulties weighing patient history and physical examination cues to inform judgement on overall level of suspicion for vascular pathology was demonstrated by some participants who reported that incomplete physical examination data and not being able to see the patient contributed to difficulties. Hypothesis evaluation was supported by the personal characteristic of reflection, where some students reflected on the Framework’s emphasis on the patient history to evaluate a vascular hypothesis.

The Framework supported all participants in clinical reasoning related to treatment (Table  7 ). Treatment decisions were always linked to the participant’s overall level of suspicion for vascular pathology or musculoskeletal diagnosis. Framework knowledge supported participants with high level of suspicion for vascular pathology to refer for further investigations. Participants with a musculoskeletal diagnosis kept the patient for physiotherapy interventions. The Framework patient history section supported patient education about symptoms of vascular pathology and safety netting for some participants. Framework knowledge influenced informed consent processes and risk-benefit analysis to support the selection of musculoskeletal physiotherapy interventions, which were specific and prioritized for some participants. Less Framework knowledge related to treatment was demonstrated by some students, generating unclear recommendations regarding the urgency of referral and use of the Framework to inform musculoskeletal physiotherapy interventions. Treatment was supported by a range of personal characteristics. An adaptable approach that prioritized patient safety and was supported by justification was demonstrated in all participants except one. Shared decision-making enabled the selection of physiotherapy interventions, which were patient-centered (individualized, considered whole person, identified future risk for vascular pathology). Communication with the patient’s family doctor facilitated collaborative patient-centered care for most participants.

This is the first study to explore the influence of the Framework on clinical reasoning processes in postgraduate physiotherapy students. The Framework supported clinical reasoning that used primarily hypothetico-deductive processes. The Framework informed vascular hypothesis generation in the patient history and testing the vascular hypothesis through patient history questions and selection of physical examination tests to inform clarity and support for diagnosis and management. Most postgraduate students’ clinical reasoning processes were characterized by high-level features (e.g. specificity, prioritization). However, some demonstrated occasional difficulties or errors, reflecting a continuum of clinical reasoning proficiency. Clinical reasoning processes were informed by deep knowledge of the Framework integrated with a breadth of wider knowledge and supported by a range of personal characteristics (e.g., justification for decisions, reflection).

Use of the Framework to inform clinical reasoning processes

The Framework provided a structured and comprehensive approach to support postgraduate students’ clinical reasoning processes in assessment and management of the cervical spine region, considering the potential for vascular pathology. Patient history and physical examination information was evaluated to inform clarity and support the decision to refer for further vascular investigations or proceed with musculoskeletal physiotherapy diagnosis/interventions. The Framework is not intended to lead to a vascular pathology diagnosis [ 7 , 8 ], and following the Framework does not guarantee vascular pathologies will be identified [ 41 ]. Rather, it aims to support a process of clinical reasoning to elicit and interpret appropriate patient history and physical examination information to estimate the probability of vascular pathology and inform judgement about the need to refer for further investigations [ 7 , 8 , 42 ]. Results of this study suggest the Framework has achieved this aim for postgraduate physiotherapy students.

The Framework supported postgraduate students in using primarily hypothetico-deductive diagnostic reasoning processes. This is expected given the diversity of vascular pathology clinical presentations precluding a definite clinical pattern and inherent complexity as a potential masquerader of a musculoskeletal problem [ 7 ]. It is also consistent with prior research investigating clinical reasoning processes in musculoskeletal physiotherapy postgraduate students [ 12 ] and clinical experts [ 29 ] where hypothetico-deductive and pattern recognition diagnostic reasoning are employed according to the demands of the clinical situation [ 10 ]. Diagnostic reasoning of most postgraduate students in this study demonstrated features suggestive of high-level clinical reasoning in musculoskeletal physiotherapy [ 12 ], including ongoing reasoning with high-level cue identification and interpretation, specificity and prioritization during assessment and treatment, use of physiotherapy interventions to aid diagnostic reasoning, and prognosis determination [ 12 , 29 , 43 ]. Expert physiotherapy practice has been further described as using a dialectical model of clinical reasoning with seamless transitions between clinical reasoning strategies [ 44 ]. While diagnostic reasoning was a focus in this study, postgraduate students considered a breadth of information as important to their reasoning (e.g., patient’s perspectives of the reason for their pain). This suggests wider reasoning strategies (e.g., narrative, collaborative) were employed to enable shared decision-making within the context of patient-centered care.

Study findings also highlighted a continuum of proficiency in use of the Framework to inform clinical reasoning processes. Not all students demonstrated all characteristics of high-level clinical reasoning and there are suggestions of incomplete reasoning processes, for example occasional errors in evaluating cues. Some students offered explanations such as incomplete case information as factors contributing to difficulties with clinical reasoning processes. However, the ability to critically evaluate incomplete and potentially conflicting clinical information is consistently identified as an advanced clinical practice competency [ 14 , 43 ]. A continuum of proficiency in clinical reasoning in musculoskeletal physiotherapy is supported by wider healthcare professions describing acquisition and application of clinical knowledge and skills as a developmental continuum of clinical competence progressing from novice to expert [ 45 , 46 ]. The range of years of clinical practice experience in this cohort of students (3–14 years) or prior completed postgraduate education may have contributed to the continuum of proficiency, as high-quality and diverse experiential learning is essential for the development of high-level clinical reasoning [ 14 , 47 ].

Deep knowledge of the Framework informs clinical reasoning processes

Postgraduate students demonstrated deep Framework knowledge to inform clinical reasoning processes. All students demonstrated knowledge of patient history features of vascular pathology, recommended physical examination tests to test a vascular hypothesis, and the need to refer if there is a high level of suspicion for vascular pathology. A key development in the recent Framework update is the removal of the recommendation to perform positional testing [ 8 ]. All students demonstrated knowledge of this development, and none wanted to test a vascular hypothesis with positional testing. Most also demonstrated Framework knowledge about considerations for planning treatment with physiotherapy interventions (e.g., risk-benefit analysis, informed consent), though not all, which underscores the continuum of proficiency in postgraduate students. Rich organization of multidimensional knowledge is a required component for high level clinical reasoning and is characteristic of expert physiotherapy practice [ 10 , 48 , 49 ]. Most postgraduate physiotherapy students displayed this expert practice characteristic through integration of deep Framework knowledge with a breadth of prior knowledge (e.g., experiential, propositional) to inform clinical reasoning processes. This highlights the utility of the Framework in postgraduate physiotherapy education to develop advanced level evidence-based knowledge informing clinical reasoning processes for safe assessment and management of the cervical spine, considering the potential for vascular pathology [ 9 , 8 , 50 , 51 , 52 ].

Framework supports personal characteristics to facilitate integration of knowledge and clinical reasoning

The Framework supported personal characteristics of postgraduate students, which are key drivers for the complex integration of advanced knowledge and high-level clinical reasoning [ 10 , 12 , 48 ]. For all students, the Framework supported justification for decisions and patient-centered care, emphasizing a whole-person approach and shared decision-making. Further demonstrating a continuum of proficiency, the Framework supported a wider breadth of personal characteristics for some students, including critical analysis, reflection, self-analysis, and adaptability. These personal characteristics illustrate the interwoven cognitive and metacognitive skills that influence and support a high level of clinical reasoning [ 10 , 12 ] and the development of clinical expertise [ 48 , 53 ]. For example [ 54 ], reflection is critical to developing high-level clinical reasoning and advanced level practice [ 12 , 55 ]. Postgraduate students reflected on prior knowledge, experiences, and action within the context of current Framework knowledge, emphasizing active engagement in cognitive processes to inform clinical reasoning processes. Reflection-in-action is highlighted by self-analysis and adaptability. These characteristics require continuous cognitive processing to consider personal strengths and limitations in the context of the patient and evidence-based practice, adapting the clinical encounter as required [ 53 , 55 ]. These findings highlight use of the Framework in postgraduate education to support development of personal characteristics that are indicative of an advanced level of clinical practice [ 12 ].

Synthesis of findings

Derived from synthesis of research study findings and informed by the Postgraduate Musculoskeletal Physiotherapy Practice model [ 12 ], use of the Framework to inform clinical reasoning processes in postgraduate students is illustrated in Fig.  2 . Overlapping clinical reasoning, knowledge and personal characteristic components emphasize the complex interaction of factors contributing to clinical reasoning processes. Personal characteristics of postgraduate students underpin clinical reasoning and knowledge, highlighting their role in facilitating the integration of these two components. Bolded subcomponents indicate convergence of results reflecting all postgraduate students and underscores the variability among postgraduate students contributing to a continuum of clinical reasoning proficiency. The relative weighting of the components is approximately equal to balance the breadth and convergence of subcomponents. Synthesis of findings align with the Postgraduate Musculoskeletal Physiotherapy Practice model [ 12 ], though some differences exist. Limited personal characteristics were identified in this study with little convergence across students, which may be due to the objective of this study and the case analysis approach.

Use of the Framework to inform clinical reasoning in postgraduate level musculoskeletal physiotherapy students. Adapted from the Postgraduate Musculoskeletal Physiotherapy Practice model [ 12 ].

Strengths and limitations

Think aloud case analyses enabled situationally dependent understanding of the Framework to inform clinical reasoning processes in postgraduate level students [ 17 ], considering the rare potential for vascular pathology. A limitation of this approach was the standardized nature of case information provided to students, which may have influenced clinical reasoning processes. Future research studies may consider patient case simulation to address this limitation [ 30 ]. Interviews were conducted during the second half of the postgraduate educational program, and this timing could have influenced clinical reasoning processes compared to if interviews were conducted at the end of the program. Future research can explore use of the Framework to inform clinical reasoning processes in established advanced practice physiotherapists. The sample size of this study aligns with recommendations for think aloud methodology [ 27 , 28 ], achieved rich data, and purposive sampling enabled wide representation of key characteristics (e.g., gender, ethnicity, country of training, physiotherapy experiences), which enhances transferability of findings. Students were aware of the study objective in advance of interviews which may have contributed to a heightened level of awareness of vascular pathology. The prior relationship between students and researchers may have also influenced results, however several strategies were implemented to minimize this influence.

Implications

The Framework is widely implemented within IFOMPT postgraduate educational programs and has led to important shifts in educational curricula [ 9 ]. Findings of this study support use of the Framework as an educational resource in postgraduate physiotherapy programs to inform clinical reasoning processes for safe and effective assessment and management of cervical spine presentations considering the potential for vascular pathology. Individualized approaches may be required to support each student, owing to a continuum of clinical reasoning proficiency. As the Framework was written for practicing musculoskeletal clinicians, future research is required to explore use of the Framework to inform clinical reasoning in learners at different levels, for example entry-level physiotherapy students.

The Framework supported clinical reasoning that used primarily hypothetico-deductive processes in postgraduate physiotherapy students. It informed vascular hypothesis generation in the patient history and testing the vascular hypothesis through patient history questions and selection of physical examination tests, to inform clarity and support for diagnosis and management. Most postgraduate students clinical reasoning processes were characterized as high-level, informed by deep Framework knowledge integrated with a breadth of wider knowledge, and supported by a range of personal characteristics to facilitate the integration of advanced knowledge and high-level clinical reasoning. Future research is required to explore use of the Framework to inform clinical reasoning in learners at different levels.

Data availability

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

Safiri S, Kolahi AA, Hoy D, Buchbinder R, Mansournia MA, Bettampadi D et al. Global, regional, and national burden of neck pain in the general population, 1990–2017: systematic analysis of the global burden of Disease Study 2017. BMJ. 2020;368.

Stovner LJ, Nichols E, Steiner TJ, Abd-Allah F, Abdelalim A, Al-Raddadi RM, et al. Global, regional, and national burden of migraine and tension-type headache, 1990–2016: a systematic analysis for the global burden of Disease Study 2016. Lancet Neurol. 2018;17:954–76.

Article   Google Scholar  

Cieza A, Causey K, Kamenov K, Hanson SW, Chatterji S, Vos T. Global estimates of the need for rehabilitation based on the Global Burden of Disease study 2019: a systematic analysis for the global burden of Disease Study 2019. Lancet. 2020;396:2006–17.

Côté P, Yu H, Shearer HM, Randhawa K, Wong JJ, Mior S et al. Non-pharmacological management of persistent headaches associated with neck pain: A clinical practice guideline from the Ontario protocol for traffic injury management (OPTIMa) collaboration. European Journal of Pain (United Kingdom). 2019;23.

Diamanti S, Longoni M, Agostoni EC. Leading symptoms in cerebrovascular diseases: what about headache? Neurological Sciences. 2019.

Debette S, Compter A, Labeyrie MA, Uyttenboogaart M, Metso TM, Majersik JJ, et al. Epidemiology, pathophysiology, diagnosis, and management of intracranial artery dissection. Lancet Neurol. 2015;14:640–54.

Rushton A, Carlesso LC, Flynn T, Hing WA, Rubinstein SM, Vogel S, et al. International Framework for examination of the Cervical Region for potential of vascular pathologies of the Neck Prior to Musculoskeletal intervention: International IFOMPT Cervical Framework. J Orthop Sports Phys Therapy. 2023;53:7–22.

Rushton A, Carlesso LC, Flynn T, Hing WA, Kerry R, Rubinstein SM, et al. International framework for examination of the cervical region for potential of vascular pathologies of the neck prior to orthopaedic manual therapy (OMT) intervention: International IFOMPT Cervical Framework. International IFOMPT Cervical Framework; 2020.

Hutting N, Kranenburg R, Taylor A, Wilbrink W, Kerry R, Mourad F. Implementation of the International IFOMPT Cervical Framework: a survey among educational programmes. Musculoskelet Sci Pract. 2022;62:102619.

Jones MA, Jensen G, Edwards I. Clinical reasoning in physiotherapy. In: Campbell S, Watkins V, editors. Clinical reasoning in the health professions. Third. Philadelphia: Elsevier; 2008. pp. 245–56.

Google Scholar  

Fennelly O, Desmeules F, O’Sullivan C, Heneghan NR, Cunningham C. Advanced musculoskeletal physiotherapy practice: informing education curricula. Musculoskelet Sci Pract. 2020;48:102174.

Rushton A, Lindsay G. Defining the construct of masters level clinical practice in manipulative physiotherapy. Man Ther. 2010;15.

Rushton A, Lindsay G. Defining the construct of masters level clinical practice in healthcare based on the UK experience. Med Teach. 2008;30:e100–7.

Noblet T, Heneghan NR, Hindle J, Rushton A. Accreditation of advanced clinical practice of musculoskeletal physiotherapy in England: a qualitative two-phase study to inform implementation. Physiotherapy (United Kingdom). 2021;113.

Tawiah AK, Stokes E, Wieler M, Desmeules F, Finucane L, Lewis J, et al. Developing an international competency and capability framework for advanced practice physiotherapy: a scoping review with narrative synthesis. Physiotherapy. 2023;122:3–16.

Williams A, Rushton A, Lewis JJ, Phillips C. Evaluation of the clinical effectiveness of a work-based mentoring programme to develop clinical reasoning on patient outcome: a stepped wedge cluster randomised controlled trial. PLoS ONE. 2019;14.

Miles R. Complexity, representation and practice: case study as method and methodology. Issues Educational Res. 2015;25.

Thorne S, Kirkham SR, MacDonald-Emes J. Interpretive description: a noncategorical qualitative alternative for developing nursing knowledge. Res Nurs Health. 1997;20.

Thorne S, Kirkham SR, O’Flynn-Magee K. The Analytic challenge in interpretive description. Int J Qual Methods. 2004;3.

Creswell JW. Research design: qualitative, quantitative, and mixed methods approaches. Sage; 2003.

Dolan S, Nowell L, Moules NJ. Interpretive description in applied mixed methods research: exploring issues of fit, purpose, process, context, and design. Nurs Inq. 2023;30.

Thorne S. Interpretive description. In: Routledge International Handbook of Qualitative Nursing Research. 2013. pp. 295–306.

Thompson Burdine J, Thorne S, Sandhu G. Interpretive description: a flexible qualitative methodology for medical education research. Med Educ. 2021;55.

Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus group. Int J Qual Health Care. 2007;19:349–57.

Archibald MM, Ambagtsheer RC, Casey MG, Lawless M. Using zoom videoconferencing for qualitative data Collection: perceptions and experiences of researchers and participants. Int J Qual Methods. 2019;18.

Van Someren M, Barnard YF, Sandberg J. The think aloud method: a practical approach to modelling cognitive. Volume 11. London: Academic; 1994.

Fonteyn ME, Kuipers B, Grobe SJ. A description of think aloud Method and Protocol Analysis. Qual Health Res. 1993;3:430–41.

Lundgrén-Laine H, Salanterä S. Think-Aloud technique and protocol analysis in clinical decision-making research. Qual Health Res. 2010;20:565–75.

Doody C, McAteer M. Clinical reasoning of expert and novice physiotherapists in an outpatient orthopaedic setting. Physiotherapy. 2002;88.

Gilliland S. Physical therapist students’ development of diagnostic reasoning: a longitudinal study. J Phys Therapy Educ. 2017;31.

Ericsson KA, Simon HA. How to study thinking in Everyday Life: contrasting think-aloud protocols with descriptions and explanations of thinking. Mind Cult Act. 1998;5:178–86.

Dwyer SC, Buckle JL. The space between: on being an insider-outsider in qualitative research. Int J Qual Methods. 2009;8.

Shenton AK. Strategies for ensuring trustworthiness in qualitative research projects. Educ Inform. 2004;22:63–75.

Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3:77–101.

Fereday J, Muir-Cochrane E. Demonstrating Rigor using thematic analysis: a Hybrid Approach of Inductive and deductive coding and theme development. Int J Qual Methods. 2006;5.

Elstein ASLSS. Medical problem solving: an analysis of clinical reasoning. Harvard University Press; 1978.

Proudfoot K. Inductive/Deductive Hybrid Thematic Analysis in mixed methods research. J Mix Methods Res. 2023;17.

Charters E. The use of think-aloud methods in qualitative research an introduction to think-aloud methods. Brock Educ J. 2003;12.

Nowell LS, Norris JM, White DE, Moules NJ. Thematic analysis: striving to meet the trustworthiness Criteria. Int J Qual Methods. 2017;16:1–13.

Thurmond VA. The point of triangulation. J Nurs Scholarsh. 2001;33.

Hutting N, Wilbrink W, Taylor A, Kerry R. Identifying vascular pathologies or flow limitations: important aspects in the clinical reasoning process. Musculoskelet Sci Pract. 2021;53:102343.

de Best RF, Coppieters MW, van Trijffel E, Compter A, Uyttenboogaart M, Bot JC, et al. Risk assessment of vascular complications following manual therapy and exercise for the cervical region: diagnostic accuracy of the International Federation of Orthopaedic Manipulative physical therapists framework (the Go4Safe project). J Physiother. 2023;69:260–6.

Petty NJ. Becoming an expert: a masterclass in developing clinical expertise. Int J Osteopath Med. 2015;18:207–18.

Edwards I, Jones M, Carr J, Braunack-Mayer A, Jensen GM. Clinical reasoning strategies in physical therapy. Phys Ther. 2004;84.

Carraccio CL, Benson BJ, Nixon LJ, Derstine PL. Clinical teaching from the Educational Bench to the clinical Bedside: Translating the Dreyfus Developmental Model to the Learning of Clinical Skills.

Benner P. Using the Dreyfus Model of Skill Acquisition to describe and interpret Skill Acquisition and Clinical Judgment in nursing practice and education. Bull Sci Technol Soc. 2004;24:188–99.

Benner P. From novice to expert: Excellence and power in clinical nursing practice. Upper Saddle River, New Jersey: Prentice Hall;: Commemorative Ed; 2001.

Jensen GM, Gwyer J, Shepard KF, Hack LM. Expert practice in physical therapy. Phys Ther. 2000;80.

Huhn K, Gilliland SJ, Black LL, Wainwright SF, Christensen N. Clinical reasoning in physical therapy: a Concept Analysis. Phys Ther. 2019;99.

Hutting N, Kranenburg HA, Rik KR. Yes, we should abandon pre-treatment positional testing of the cervical spine. Musculoskelet Sci Pract. 2020;49:102181.

Kranenburg HA, Tyer R, Schmitt M, Luijckx GJ, Schans C, Van Der, Hutting N, et al. Effects of head and neck positions on blood flow in the vertebral, internal carotid, and intracranial arteries: a systematic review. J Orthop Sports Phys Ther. 2019;49:688–97.

Hutting N, Kerry R, Coppieters MW, Scholten-Peeters GGM. Considerations to improve the safety of cervical spine manual therapy. Musculoskelet Sci Pract. 2018;33.

Wainwright SF, Shepard KF, Harman LB, Stephens J. Novice and experienced physical therapist clinicians: a comparison of how reflection is used to inform the clinical decision-making process. Phys Ther. 2010;90:75–88.

Dy SM, Purnell TS. Key concepts relevant to quality of complex and shared decision-making in health care: a literature review. Soc Sci Med. 2012;74:582–7.

Christensen N, Jones MA, Higgs J, Edwards I. Dimensions of clinical reasoning capability. In: Campbell S, Watkins V, editors. Clinical reasoning in the health professions. 3rd edition. Philadelphia: Elsevier; 2008. pp. 101–10.

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Acknowledgements

The authors would like to acknowledge study participants and the transcriptionist for their time in completing and transcribing think aloud interviews.

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Katie L. Kowalski, Heather Gillis, Katherine Henning, Paul Parikh, Jackie Sadi & Alison Rushton

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Katie Kowalski: Conceptualization, methodology, validation, formal analysis, investigation, data curation, writing– original draft, visualization, project administration. Heather Gillis: Validation, resources, writing– review & editing. Katherine Henning: Investigation, formal analysis, writing– review & editing. Paul Parikh: Validation, resources, writing– review & editing. Jackie Sadi: Validation, resources, writing– review & editing. Alison Rushton: Conceptualization, methodology, validation, writing– review & editing, supervision.

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Author AR is an author of the IFOMPT Cervical Framework. Authors JS and HG are lecturers on the AHCP CMP program. AR and JS led standardized teaching of the Framework. Measures to reduce the influence of potential competing interests on the conduct and results of this study included: the Framework representing international and multiprofessional consensus, recruitment of participants by author KK, data collection and analysis completed by KK with input from AR, JS and HG at the stage of data synthesis and interpretation, and wider peer scrutiny of initial findings. KK, KH and PP have no potential competing interests.

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Kowalski, K.L., Gillis, H., Henning, K. et al. Use of the International IFOMPT Cervical Framework to inform clinical reasoning in postgraduate level physiotherapy students: a qualitative study using think aloud methodology. BMC Med Educ 24 , 486 (2024). https://doi.org/10.1186/s12909-024-05399-x

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Study Suggests Genetics as a Cause, Not Just a Risk, for Some Alzheimer’s

People with two copies of the gene variant APOE4 are almost certain to get Alzheimer’s, say researchers, who proposed a framework under which such patients could be diagnosed years before symptoms.

By Pam Belluck

Scientists are proposing a new way of understanding the genetics of Alzheimer’s that would mean that up to a fifth of patients would be considered to have a genetically caused form of the disease.

Currently, the vast majority of Alzheimer’s cases do not have a clearly identified cause. The new designation, proposed in a study published Monday, could broaden the scope of efforts to develop treatments, including gene therapy, and affect the design of clinical trials.

It could also mean that hundreds of thousands of people in the United States alone could, if they chose, receive a diagnosis of Alzheimer’s before developing any symptoms of cognitive decline, although there currently are no treatments for people at that stage.

The new classification would make this type of Alzheimer’s one of the most common genetic disorders in the world, medical experts said.

“This reconceptualization that we’re proposing affects not a small minority of people,” said Dr. Juan Fortea, an author of the study and the director of the Sant Pau Memory Unit in Barcelona, Spain. “Sometimes we say that we don’t know the cause of Alzheimer’s disease,” but, he said, this would mean that about 15 to 20 percent of cases “can be tracked back to a cause, and the cause is in the genes.”

The idea involves a gene variant called APOE4. Scientists have long known that inheriting one copy of the variant increases the risk of developing Alzheimer’s, and that people with two copies, inherited from each parent, have vastly increased risk.

The new study , published in the journal Nature Medicine, analyzed data from over 500 people with two copies of APOE4, a significantly larger pool than in previous studies. The researchers found that almost all of those patients developed the biological pathology of Alzheimer’s, and the authors say that two copies of APOE4 should now be considered a cause of Alzheimer’s — not simply a risk factor.

The patients also developed Alzheimer’s pathology relatively young, the study found. By age 55, over 95 percent had biological markers associated with the disease. By 65, almost all had abnormal levels of a protein called amyloid that forms plaques in the brain, a hallmark of Alzheimer’s. And many started developing symptoms of cognitive decline at age 65, younger than most people without the APOE4 variant.

“The critical thing is that these individuals are often symptomatic 10 years earlier than other forms of Alzheimer’s disease,” said Dr. Reisa Sperling, a neurologist at Mass General Brigham in Boston and an author of the study.

She added, “By the time they are picked up and clinically diagnosed, because they’re often younger, they have more pathology.”

People with two copies, known as APOE4 homozygotes, make up 2 to 3 percent of the general population, but are an estimated 15 to 20 percent of people with Alzheimer’s dementia, experts said. People with one copy make up about 15 to 25 percent of the general population, and about 50 percent of Alzheimer’s dementia patients.

The most common variant is called APOE3, which seems to have a neutral effect on Alzheimer’s risk. About 75 percent of the general population has one copy of APOE3, and more than half of the general population has two copies.

Alzheimer’s experts not involved in the study said classifying the two-copy condition as genetically determined Alzheimer’s could have significant implications, including encouraging drug development beyond the field’s recent major focus on treatments that target and reduce amyloid.

Dr. Samuel Gandy, an Alzheimer’s researcher at Mount Sinai in New York, who was not involved in the study, said that patients with two copies of APOE4 faced much higher safety risks from anti-amyloid drugs.

When the Food and Drug Administration approved the anti-amyloid drug Leqembi last year, it required a black-box warning on the label saying that the medication can cause “serious and life-threatening events” such as swelling and bleeding in the brain, especially for people with two copies of APOE4. Some treatment centers decided not to offer Leqembi, an intravenous infusion, to such patients.

Dr. Gandy and other experts said that classifying these patients as having a distinct genetic form of Alzheimer’s would galvanize interest in developing drugs that are safe and effective for them and add urgency to current efforts to prevent cognitive decline in people who do not yet have symptoms.

“Rather than say we have nothing for you, let’s look for a trial,” Dr. Gandy said, adding that such patients should be included in trials at younger ages, given how early their pathology starts.

Besides trying to develop drugs, some researchers are exploring gene editing to transform APOE4 into a variant called APOE2, which appears to protect against Alzheimer’s. Another gene-therapy approach being studied involves injecting APOE2 into patients’ brains.

The new study had some limitations, including a lack of diversity that might make the findings less generalizable. Most patients in the study had European ancestry. While two copies of APOE4 also greatly increase Alzheimer’s risk in other ethnicities, the risk levels differ, said Dr. Michael Greicius, a neurologist at Stanford University School of Medicine who was not involved in the research.

“One important argument against their interpretation is that the risk of Alzheimer’s disease in APOE4 homozygotes varies substantially across different genetic ancestries,” said Dr. Greicius, who cowrote a study that found that white people with two copies of APOE4 had 13 times the risk of white people with two copies of APOE3, while Black people with two copies of APOE4 had 6.5 times the risk of Black people with two copies of APOE3.

“This has critical implications when counseling patients about their ancestry-informed genetic risk for Alzheimer’s disease,” he said, “and it also speaks to some yet-to-be-discovered genetics and biology that presumably drive this massive difference in risk.”

Under the current genetic understanding of Alzheimer’s, less than 2 percent of cases are considered genetically caused. Some of those patients inherited a mutation in one of three genes and can develop symptoms as early as their 30s or 40s. Others are people with Down syndrome, who have three copies of a chromosome containing a protein that often leads to what is called Down syndrome-associated Alzheimer’s disease .

Dr. Sperling said the genetic alterations in those cases are believed to fuel buildup of amyloid, while APOE4 is believed to interfere with clearing amyloid buildup.

Under the researchers’ proposal, having one copy of APOE4 would continue to be considered a risk factor, not enough to cause Alzheimer’s, Dr. Fortea said. It is unusual for diseases to follow that genetic pattern, called “semidominance,” with two copies of a variant causing the disease, but one copy only increasing risk, experts said.

The new recommendation will prompt questions about whether people should get tested to determine if they have the APOE4 variant.

Dr. Greicius said that until there were treatments for people with two copies of APOE4 or trials of therapies to prevent them from developing dementia, “My recommendation is if you don’t have symptoms, you should definitely not figure out your APOE status.”

He added, “It will only cause grief at this point.”

Finding ways to help these patients cannot come soon enough, Dr. Sperling said, adding, “These individuals are desperate, they’ve seen it in both of their parents often and really need therapies.”

Pam Belluck is a health and science reporter, covering a range of subjects, including reproductive health, long Covid, brain science, neurological disorders, mental health and genetics. More about Pam Belluck

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• Published: 09 May 2024

Facilitators of and barriers to County Behavioral Health System Transformation and Innovation: an interview study

• Xin Zhao 1 , 2 ,
• Rachel Varisco 3 ,
• Judith Borghouts 3 ,
• Elizabeth V. Eikey 4 , 5 ,
• David Safani 6 ,
• Dana B. Mukamel 3 ,
• Stephen M. Schueller 7 &
• Dara H. Sorkin 3  

BMC Health Services Research volume  24 , Article number:  604 ( 2024 ) Cite this article

Metrics details

Inadequate and inequitable access to quality behavioral health services and high costs within the mental health systems are long-standing problems. System-level (e.g., fee-for-service payment model, lack of a universal payor) and individual factors (e.g., lack of knowledge of existing resources) contribute to difficulties in accessing resources and services. Patients are underserved in County behavioral health systems in the United States. Orange County’s (California) Behavioral Health System Transformation project sought to improve access by addressing two parts of their system: developing a template for value-based contracts that promote payor-agnostic care (Part 1); developing a digital platform to support resource navigation (Part 2). Our aim was to evaluate facilitators of and barriers to each of these system changes.

We collected interview data from County or health care agency leaders, contracted partners, and community stakeholders. Themes were informed by the Consolidated Framework for Implementation Research.

Five themes were identified related to behavioral health system transformation, including 1) aligning goals and values, 2) addressing fit, 3) fostering engagement and partnership, 4) being aware of implementation contexts, and 5) promoting communication. A lack of fit into incentive structures and changing state guidelines and priorities were barriers to contract development. Involving diverse communities to inform design and content facilitated the process of developing digital tools.

Conclusions

The study highlights the multifaceted factors that help facilitate or hinder behavioral health system transformation, such as the need for addressing systematic and process behaviors, leveraging the knowledge of leadership and community stakeholders, fostering collaboration, and adapting to implementation contexts.

Peer Review reports

In the United States, the system of providing and coordinating behavioral health services is inefficient. Health care systems are largely paid via a “fee-for-service” model that incentivizes increasing the number of billable hours rather than improving patient outcomes and quality of care [ 1 ]. At the system level, provider shortage, disparities in insurance coverage, and the existing fee-for-service reimbursement model contributed to longstanding unmet service needs [ 2 , 3 , 4 , 5 ]. At the individual level, behavioral health stigma, limited mental health literacy, and lack of knowledge about appropriate resources challenge people’s ability to navigate and access behavioral health resources, especially among historically marginalized and uninsured groups [ 3 ].

In light of the multilevel barriers hindering access to behavioral health services, system transformation is needed. According to California Health Interview Survey reports, one in five Orange County residents reported they needed, but did not receive, behavioral health support [ 6 ]. Those from disadvantaged socioeconomic backgrounds were less likely to access behavioral health support than those with more resources. The unmet need within the County behavioral health system can be improved if providers and patients have access to information about care (efficient resource navigation) and patients get linked with value-based behavioral health services regardless of their insurance status (payor-agnostic care). Orange County’s Behavioral Health System Transformation (BHST) Innovation Project in California aims to create a patient-centered system where all residents in Orange County can be served regardless of their insurance status and clinical needs. An innovation project introduces a new practice or approach in the field of behavioral health with a primary focus on learning or process change. The BHST Innovation Project includes two parts: developing a template for value-based payment contracts that promote payor-agnostic care (Part 1) and developing a public-facing digital platform (OC Navigator) to increase access to information and support resource navigation (Part 2) [ 6 ]. Innovation projects are limited to a maximum of five years, with the expectation that successful projects should transition to integration into standard practices and sustainment. The data for this paper come from the first half of a five-year innovation project. Thus, the current paper focuses on early lessons learned regarding facilitators and barriers.

Backgrounds for components of the BHST Innovation Project

Part 1. developing a template for value-based payment contracts that promote payor-agnostic care.

Value-based payment models tie payments for services to the quality of care and patients’ clinical outcomes rather than the volume of services delivered [ 7 ]. Since 2016, several states in the US, such as Washington, New York, Minnesota, Maine, and Massachusetts, made attempts to implement value-based care [ 1 , 8 , 9 , 10 , 11 , 12 ]. In Washington and New York, transitioning to value-based care improved the quality of behavioral health services. In Washington State, a value-based care initiative targeted the implementation of the Collaborative Care Model, an evidence-based team approach to behavioral health interventions in primary care. In this program, 25% of funding to participating community clinics was contingent on meeting value-based payment targets (i.e., providing evidence-based care) and active participation in the program [ 8 ]. Compared to patients enrolling in the program without the value-based components, those enrolling in the program with value-based components were more likely to have depression outcomes that improved in a shorter amount of time (Bao et al., 2017). New York State Collaborative Care Medicaid also used a value-based program. In this program, 25% of the monthly, patient-level case-rate payment was withheld each month and was paid retroactively after six months for patients who had clinical improvement or had their treatment plan adjusted in response to a lack of clinical improvement [ 12 , 13 ]. This program led to an increase in the proportion of patients screened for depression and patients who showed clinical improvement after 10 weeks of treatment at participating sites, compared to before launching the program. In addition to improving the quality of care, value-based payment models also have the potential to help address challenges faced by the traditional fee-for-service model, such as overutilization of services and high costs [ 7 , 14 ].

Despite the reported positive implementation outcomes of the value-based payment initiatives, the process of implementing and sustaining value-based payment models is often challenging and varies largely by state [ 7 , 10 ]. In the United States, buy-in of value-based payment models from commercial payors is challenging. For example, qualitative analyses of interview data revealed limited interest in adopting value-based contracts with providers among commercial payors in Arkansas, Maine, and Minnesota [ 10 ]. Specifically, commercial payors expressed concerns about (1) the need for tailoring a value-based contract to align with just one state when they have business in multiple states; and (2) market competition, such as subsidizing the care of patients covered by other payors who did not make similar investments to adopt value-based payment models [ 10 ].

Payor-agnostic care allows all patients to be served regardless of their insurance status and clinical needs, as it prioritizes patient needs and outcomes above financial profitability. A payor-agnostic model typically includes supporting uninsured individuals. Funding sources for uninsured individuals might include self-pay options, philanthropic donations, and government grants. The barriers to and facilitators of multi-payor alignment have been more studied in primary care settings. One notable effort is the Comprehensive Primary Care (CPC) initiative launched by Centers for Medicare & Medicaid Services (CMS), which is one of the largest multi-payor initiatives [ 15 ]. Interviews from CMS staff, CPC-participating payors, and stakeholder organizations described that competitive market dynamics and competing institutional priorities were barriers to multi-payor and multi-sector collaboration. Leveraging champion support and seeking input on decisions related to system transformation from key community stakeholders helped build trusting relationships and align different payors. In the sphere of behavioral health, emerging efforts of moving towards payor-agnostic care hold great potential in ensuring equitable health care access. However, barriers to and facilitators of implementing payor agnostic behavioral health care are less known. One example was the Blue Shield Health Reimagined pilot program. In this program, Blue Shield embedded Community Health Advocates in ten primary and specialty care practices to provide payor-agnostic care to support individuals who were not Blue Shield members to receive services [ 16 ]. In the first fourteen months of the program, a large and diverse population was served (i.e., N  > 1,900 patients, > 30% Latinx/Hispanic) across four participating regions in California (Paulson et al., 2021). Paulson et al. (2021) analyzed focus group and interview data to identify facilitators of and barriers to embedding Community Health Advocates within primary and specialty care practices to provide payor-agnostic care, with a focus on intervention implementation. Overall, to improve access to behavioral health care access, additional work is needed to understand facilitators of and barriers to promoting payor-agnostic care.

Part 2. Developing a digital platform to increase access to information and support resource navigation

A digital resource navigator is a public-facing digital platform that serves as a resource directory. A great digital resource navigator can improve the efficiency of resource navigation, care coordination, and knowledge sharing by speeding up communication among different sectors and reducing the need for human labor. Past work on digital resource navigation has mostly focused on supporting care coordination for patients and providers who are already situated in the care system, such as through the use of the electronic health record and web-based communications [ 17 ]. Much less work has focused on knowledge sharing and information exchange of service options before patients connect with a provider in the behavioral health sphere. One exception was the M ental health I ntelligent information R esource A ssistant (MIRA), a web-based conversational chatbot developed in Canada during the COVID-19 global pandemic [ 18 ]. MIRA was developed to provide individuals with (1) information on substance use and mental health and (2) information on behavioral health services in Canada. This digital resource navigation tool is publicly available and informed by subject experts. As described by their published protocol, data collection was anticipated to take place from May 2022 to May 2023 [ 18 ]. However, no published work is available regarding provider and stakeholder perceptions of such tools. A digital resource navigator presents a scalable opportunity to streamline information sharing and improve access to care, although further exploration of facilitators of and barriers to developing and implementing such tools is needed.

Consolidated Framework for Implementation Research (CFIR) framework

CFIR is a comprehensive framework that can capture innovation-related factors and the complicated contextual factors that may influence implementation of an innovation. The initial version of CFIR comprised 39 subdomains grouped into the following five broad domains, including (1) innovation characteristics, (2) inner setting, (3) outer setting, (4) individual characteristics, and (5) process factors [ 19 ]. Innovation characteristics refer to characteristics of the template for value-based contracts (Part 1) and the digital resource navigator (Part 2), such as the perceived innovation source, complexity, evidence strength and quality, and relative advantage. Inner setting refers to the context in which the innovation takes place (in this study the Orange County Public Behavioral Healthcare System) including factors such as compatibility, leadership engagement, and networks and communication. Outer setting refers to the wider economic and social context that influences the innovation, such as federal and state policies and external incentives. Process refers to the steps taken during the innovation and implementation process, such as engaging and planning. Individual characteristics refer to the values and views of individual users of the innovation. Adapted definitions of CFIR constructs are presented in Table  1 .

Researchers have used CFIR to understand complicated system transformation efforts within organizations and health care systems [ 20 , 21 , 22 ]. For example, Kilaru et al. (2022) interviewed regulators and health care agency leaders about the all-payor global budget system in Maryland; their analyses using CFIR revealed factors that facilitated the design, implementation, and sustainability of system transformation efforts, such as clear and reasonable expectations, the appropriate amount of autonomy within the global budget, close communication, actionable data, and shared commitment and readiness for change. As such, CFIR has demonstrated its applicability when evaluating system transformation in different settings.

Evaluation context and aims

The BHST Innovation Project, approved by the Mental Health Services Oversight and Accountability Commission (MHSOAC), is a five-year Mental Health Services Act (MHSA) Project with a total budget of approximately $18 million. California uses innovation projects as part of their Mental Health Services Act (MHSA) program to provide resources for mental health. The goal of Orange County’s BHST Innovation Project is a system transformation effort to enable access to behavioral health services regardless of insurance status, insurance type, and/or level of clinical need. Specifically, this project included two parts:

Part 1: leveraging a value-based contract to align legal, fiscal, and regulatory requirements to improve the quality of behavioral health services, and implementing payor-agnostic care to improve access to care; and.

Part 2: developing a digital resource navigator to improve resource sharing and behavioral health service navigation.

The aim of this paper is to use the CFIR framework to evaluate facilitators of and barriers to the success of a behavioral health system transformation project. This paper fills a gap in knowledge by sharing learnings from the early stages of innovation in behavioral health payment and care and organizing these learnings in the CFIR model to promote their application to other projects. Although many systems are exploring such models, the learnings in county behavioral health settings from such explorations are too rarely shared. Moving towards value-based payor agnostic behavioral health care (Part 1) and improving access to information about care (Part 2) can help alleviate the unmet need within the County behavioral health system.

Participants

As part of an evaluation of the BHST Innovation Project, 29 individuals participated in key informant interviews between May and August 2022. Participant information is available in Table  2 . Seven individuals who had leadership roles at the County or a participating health care agency (L) participated in interviews that included both Part 1 and Part 2. Staff who only have knowledge about one part of the project participated in part-specific interviews, including eight contracted partners in Part 1 (CP1), four contracted partners in Part 2 (CP2), three community members and County stakeholders in Part 1 (CS1), and seven community members and County stakeholders in Part 2 (CS2). These interviewees were recruited due to their knowledge and involvement in the BHST Innovation Project.

The Consolidated Framework for Implementation Research (CFIR) was selected to guide the evaluation of both Part 1 and Part 2 in a consistent and systematic way.

Data collection

Our institutional review board deemed that this work was exempt from human participant research approval (University of California, Irvine Institutional Review Board (IRB)# #20,195,406). All participants provided verbal consent prior to participating in the interviews.

We developed a semi-structured interview guide based on relevant constructs from the CFIR model (Damschroder et al., 2009). The interview guide included a set of general questions for all interviewees with additional tailored questions for interviewees with different project roles (e.g., CP1, CP2, CS1, CS2, L). Interview guides are available in the supplementary material (Supplement 1 ). Each interview question was anchored to a CFIR construct. All interviewers had expertise in program evaluation or implementation science (DS, RV, SMS). Interviews were a mix of one interviewer, two interviewers, and two interviewers and a notetaker. Each interview lasted approximately 30 to 60 min. A total of 29 interviews were conducted, auto-transcribed by Zoom, and then the transcripts were verified and cleaned by the evaluation team.

Data analyses

We conducted thematic analyses following Braun and Clarke’s recommendation (2006). We outline how we follow their 6 proposed phases of analysis below.

Phase 1–2 (being familiar with data and initial coding)

XZ and RV were both trained in the CFIR framework, qualitative coding best practices, and use of the coding software (ATLAS.ti, version 22) prior to conducting data analyses. All data cleaning and analyses were completed using ATLAS.ti. We developed an initial draft of the codebook with adapted definitions of the CFIR constructs (Table  1 ). We used the five broad CFIR domains (intervention characteristics, outer setting, inner setting, characteristics of individuals, and process) and identified relevant subdomains. We completed initial coding, adapted the general CFIR definitions to be project-specific, and added a subdomain (i.e., COVID-19 as a factor in the outer setting). A total of 29 codes derived from the CFIR, including CFIR domains and subdomains, were included in the final codebook. Adapted definitions of the CFIR codes for both Part 1 and Part 2 of the project are presented in Table  2 .

Phase 3–5 (searching for, reviewing, defining, and naming themes)

XZ and RV double coded all transcripts. Initial percentages of agreement between two coders at the transcript level ranged from 46 to 74%. XZ and RV met weekly to review discrepancies and discuss revisions of the codebook (e.g., clarification of domain and subdomain definitions, addition of relevant subdomains). Coding was discussed during weekly team meetings to support consistency and resolve any discrepancies. These meetings were attended by the two coders and two other members of our research team (DS and SMS). Through discussion, final codes were decided for any discrepancies. Thus, our codes used for data analysis were codes with initial agreement or codes with discrepancies resolved through discussion with the broader research team.

We used ATLAS.ti software to calculate the frequency of the codes by CFIR domain and project aspect (Part 1 vs. Part 2) to obtain an overview of code distribution. This allowed an initial overview of codes and identification of which codes were more common for Part 1 and/or Part 2. We followed best practices in qualitative analyses mentioned by Braun and Clarke (2006) and constructed salient themes that “capture something important about the data in relation to the research and represents some level of patterned response or meaning within the data set.”

Phase 6 (locating exemplars and producing the report)

XZ, RV, and SMS engaged in documenting the themes described in this paper. XZ built a narrative of the data and selected illustrative example quotes under each theme. XZ labeled individual participants; for example, an example quote from the first contracted partner in Part 1 (CP1) was labeled “CP1.1”. RV and SMS reviewed the themes and examples and provided feedback.

Guided by CFIR, we examined facilitators and barriers related to behavioral health care system transformation efforts in Orange County separately for each of the two parts: (Part 1) developing a template for value-based payment contracts that promote payor-agnostic care, and (Part 2) creating a digital resource navigator. Overall, five themes were identified from the key informant interviews including (1) aligning goals and values (2) assessing and addressing fit, (3) fostering partnership and engagement, (4) being aware of implementation contexts, and (5) promoting communication. In Table  3 , we presented barriers and facilitators along with their CFIR domains related to each of the five themes. Different barriers and facilitators were identified for Part 1 and Part 2. Some barriers in the outer setting, such as changing state guidelines and priorities and fostering partnerships with private and nonprofit sectors, were unique to developing a template for value-based contracts that move toward payor-agnostic care. Engaging diverse communities to inform the design and content, mostly innovation characteristics, was a key facilitator for developing the digital resource navigator.

Part 1: Develop a Template for Value-Based Payment Contracts That Promote Payor-Agnostic Care

Themes and example quotes for facilitators of and barriers to developing a template for value-based payment contracts that promote payor-agnostic care are presented in Table  4 .

Aligning goals and values

Despite shared enthusiasm about value-based payment models that promote payor-agnostic care, misalignment in vision and scope was a barrier (inner setting, compatibility). For example, CP1.1 shared their excitement for increasing access to care and expressed a desire for payor-agnostic care (e.g., “From a clinician standpoint, it’s so much easier when a clinician can just treat the client and not have to worry about what type of insurance do they have, what can I not and what can I, and can I not do. What can or can they not receive for resources referrals”). Despite the shared enthusiasm among contracted partners and County health care agency leaders about increasing access to care via payor-agnostic care, perceptions of vision and scope of the contract varied, posing barriers in the inner setting. A County health care agency leader (L.1) described this barrier: “I would say that I think that there has not been alignment and agreement on the focus or the vision or the purpose and it’s felt like a kind of ongoing debate in terms of whether we want a liberal or conservative interpretation of the Constitution. It’s just fundamental disagreement on how to come to what that approved proposal was and how lenient and open to interpretation that approval is, and therefore we have not been able to get on the same page.” Confusion about the scope of the current project vision (e.g., L.2: “How it’s going to happen, I have no idea”) and skepticism about its feasibility (e.g., L.1: “Payor-agnostic… too ambitious and it’s certainly not doable or feasible in the time left on the project”) were barriers that tempered the enthusiasm for the project. Leveraging strong management and leadership (inner setting, leadership) as internal champions facilitated the process of aligning visions within the organization (e.g., “… the previous Health Care Agency Director was a champion and then the previous Behavioral Health Director was a champion… just having external subcontractors moving it forward isn’t enough to be able to realize the full value of the planning project or… to be able to support what the resulting plan would be.”).

Assessing and addressing fit

Lack of fit with existing health care system infrastructure was identified as a barrier to developing a template for value-based payment contracts that move toward payor-agnostic care. County health care agency leaders mentioned that private and public payors had different priorities and incentives within their organizations (outer setting, external policies and incentives). When describing challenges of bringing the private sector to the table, county health care agency leaders (L.2, L.4) used words such as “profit” and “return on investment.” L.2 described that a lack of incentives for commercial plans and private companies was a key challenge to engaging commercial payors: “It’s really hard to bring all the insurance companies to the table and say, ‘hey forget your profits, let’s just provide services at any cost’… the number one obstacle is getting those people to the table and questioning their profit level”. In contrast, the public sector had a bigger focus on compliance. For example, certified public expenditures (CPE) in the public sector were described as very specific (L.3). As described by L.5, the lack of flexibility of CPE suggested a poor fit between the value-based contracting and public funding structure: “So, I think for the Medi-Cal payment, I don’t think that we’re there, and we can’t gift public funds as a reward or an incentive to providers. It’s not laid out there. I know there are conversations at the state, but I think we’re [Orange County] so far ahead, as I understand it, and we don’t have the ability to just pay people extra, let them keep things that …there’s not a cost to it.”

Foster partnership

Strong cross-sector partnerships facilitated the process of braiding different funding streams. The importance of private-public payor partnership was recognized, especially related to factors in the outer setting. For instance, staff members and community stakeholders reported successful buy-in from commercial plans (outer setting, cosmopolitanism). CP1.2, CP1.3, and CS1.1 mentioned Kaiser Permanente as an example. CP1.2 stated: “Some of them [Commercial Plans] were already there. I mean Kaiser was a very early participant. They were an investor…They’re a big component of the… ecosystem, and they’re very much there”). This indicated a clear need for more efforts to facilitate the partnership with private insurance companies. CP1.2 also shared that their team’s cross-sector background and expertise facilitated establishing relationships and building cross-sector partnerships: “I come from a place of cross-sector, cross-organizational collaboration, and I think we can only improve what we’re doing if we learn what’s happening in other people’s backyards in like… how hard their jobs are”. Additionally, L.3 mentioned partnering with philanthropic organizations to obtain funding that aligns with the project mission (i.e., being able to serve everyone regardless of insurance status and clinical needs) could facilitate moving the County behavioral health system towards payor-agnostic care: “bring philanthropy to the table as well, because we really have a lot of wealth in our county. Philanthropy and some sort of a fund that accrues good interest, and we could utilize that as a stopgap between someone who doesn’t have payment and someone who does.” Participants with different roles on the project (CP1.1, CP1.3, L.3, L.4, CS1.2) described the COVID-19 global pandemic as disruptive to partnership relationship building and capacity of community members and staff members (outer setting, COVID-19). For example, CP1.3 stated: “We also had COVID, a lot of that [collaboration] got disrupted.”

Being aware of implementation contexts

A multitude of barriers influenced implementation contexts, including workforce challenges, the impact of COVID-19, and state-level policies. Workforce challenges were related to barriers in both inner and outer settings. Staff turnover and limited time and bandwidth were noted challenges in the inner setting and oftentimes led to de-prioritization of value-based contracting over other initiatives, particularly within the context of various state regulations (outer setting, external incentives and policies). For example, CP1.3 stated: “When there was turnover… that’s where kind of some of the thread may have gotten lost a little bit…. the focus of [value-based contracting] …was diminished…”. Relatedly, health care agencies had to shift their priorities due to COVID-19 related disruptions (e.g., CP1.3: “COVID changed things…there’s been a huge amount of distraction from the focus on COVID, and COVID response and vaccine, and response to COVID response… the transformation in the Community that happened from the CARES [The Coronavirus Aid, Relief, and Economic Security] Act dollars and other things getting poured in. It really took up a whole lot of time and space from elected officials to County staff to providers to take that in beyond what the usual kind of extravaganza of MHSA funding does every year. It really took all of that and poured gasoline on that fire, so it really changed the capacity of folks to engage in the work that we were trying to do.”). In addition to COVID-19 related disruptions and initiatives, state-level policies and the current CA health care infrastructure, such as the “carve-out” (the separation of mental health and substance use treatment services from the broader health care system), were mentioned by staff members and community stakeholders as barriers (CS1.3, CP1.2, CP1.3, CP1.4). CP1.2 described: “…in California, as long as the carve-out remains, there’re only so many levers you can pull.”

Promoting transparent and efficient communication

The complexity of developing a template for value-based contracts requires transparent and efficient communication. The need for promoting communication was identified as a theme related to building trust and relationships within a team (inner setting, networks and communication) and cultivating external partnerships (outer setting, cosmopolitism). A lack of transparent communication was identified as a barrier in both inner and outer settings. For example, L.2 described that the lack of communication could lead to a lack of shared understanding and trust within the project team (inner setting). L.4 mentioned that open communication with the state about the project progress was necessary to obtain state support and guidance (outer setting). To enhance communication among diverse stakeholders, the need for tailoring communication styles was mentioned. Participants (CP1.5, CS1.2, CS1.3) implied that using academic and technical jargon could be a barrier to communicating with community members and the lay workforce. For example, CS1.2 stated: “I looked at the summary of the survey and I said ‘…we are not baking a cake, so stop using the word measure. This is technical jargon; this is behind-the-scenes jargon. If you’re giving this to the Community, it should be as simple as I’m talking to you right now’.

Part 2: develop a Digital Resource Navigator (OC Navigator)

Themes and example quotes for facilitators of and barriers to developing a digital resource navigator to improve resource sharing and behavioral health service navigation are presented in Table  5 .

Shared enthusiasm was a facilitator for the development of the digital resource navigator. Specifically, its clear fit with County values and workflows in the inner setting and its relative advantages (innovation characteristics) contributed to the shared enthusiasm. Participants with different roles shared the same goal of improving existing workflows and increasing patient care in Orange County (inner setting, compatibility). As described by CP2.1: “It’s like knowing that the people that I’m interfacing with, the people that I’m like bothering and requesting meetings for, they all have the same like… we all share the same goal of like wanting to help people, and improve services, and improve access to services.” Multiple community stakeholders (CS2.1, CS2.5) described the strong fit between the digital resource navigator and the County’s equity-driven values. For instance, CS2.1 described the digital resource navigator as in line with the equity-driven values of the County: “One of our [Orange County Health Care Agency’s] key focuses was decreasing inequity, increasing equity… this is going to the next step on bringing more resources… I would say absolutely [the digital resource navigator] fits with Orange County’s values and workflows”. In addition to the clear fit between the digital resource navigator and County values, the strong fit between the digital resource navigator and existing workflows also contributed to enthusiasm among providers and community members. L.2 described that the digital resource navigator improved the efficiency of day-to-day tasks of County staff: “It’s helping the workflows [at OCHCA] be more efficient and cut out the extra unnecessary steps. It definitely is working to improve the system at the County.” Despite its fit into the larger values and workflows of Orange County Health Care Agency, not everyone deemed the digital resource navigator as a current need. For example, CP2.2 raised the question about whether the digital resource navigator was a redundant resource in the community: “We got a lot of comments and there’s a lot of chatter in the Community about is this [digital resource navigator] a waste of money because it’s a redundant resource?”.

The clear relative advantages (innovation characteristics) of the digital resource navigator contributed to shared enthusiasm among stakeholders and contracted partners. One relative advantage (innovation characteristics) was implementing a more centralized information-sharing, compared to the traditional paper-pencil format and other existing online tools. For example, L.1 stated: “ I would say it’s changed workflows in terms of centralizing and digitizing what used to be manual paper notes, post-it notes, some documentation here, some documentation there. They’ve digitized and in some cases automated a lot of the workflows for our telephone-based navigation line”. The increased efficiency in referral workflow was described as another relative advantage of the digital resource navigator. CP2.2 stated: “…you get to a point [when using other applications to find behavioral health resources] and you’d be stuck, and you just have to call the agency. You might have a list of twenty agencies, and you have to call them all before you can get some real basic information. But ours has… the way that they’re [the digital resource navigator] setting up the information cards. They give a lot of information, and then it just seems to be more robust and user-friendly.”

Fostering Engagement

Community engagement was identified as a process factor that facilitated the development and improvement of the digital resource navigator. Outreach efforts to community organizations facilitated the process of gathering feedback from community members and raising awareness about the digital resource navigator, as described by a community stakeholder (CS2.2) and multiple contracted partners (e.g., CP2.1, CP2.2, CP2.3). CP2.2 described: “… we have been successful in this sense where we’ve been talking to organizations and collaboratives and coalitions. Our pitch has been… give us your resource directory. We will highlight it on the website [the digital resource navigator]. You can correct it. We’ll tell you who authored it. We will give you a link that highlights your website, and these resource directories on the site and just let us help us help you, and then do your job better.” CP2.3 and CS2.2 identified connections with external networks as an important innovation source (e.g., National Council of Negro Women, National Alliance on Mental Illness (NAMI)) because they increased the team’s knowledge base about available resources and community needs. For example, CS2.2 described that conversations with NAMI informed the design, content, and implementation of the digital resource navigator: “So it was really great to be able to sit with [the technology vendor team] and have them ask sort of what [NAMI’s] vision was for the database and search platform to be, how we wanted it implemented, and just even how it looks so it’s not so scary” (innovation source, innovation characteristics).

Engaging community members, such as individuals with lived experiences and from marginalized groups, facilitated the improvement of design features. CP2.4 recommended leveraging community champions as a way of reaching historically marginalized groups: “Have [County leaders] help us identify champions in the community that might be good representatives for different sorts of things. So that kind of got us started. I remember a couple of years ago… they said, ‘this group is working on this, and this group is working on that’. They kind of helped with some initial introductions.” Despite the support from champions, engaging community members was especially challenging in the context of the COVID-19 global pandemic. COVID-19 lockdowns disrupted engagement with consumers who needed or preferred in-person engagement, as described by CP2.1: “At the beginning of the project, it was definitely like come one come all because we were getting started, it was COVID and really hard to engage.” (COVID, outer setting).

Lack of connections with historically marginalized communities was a barrier to curating multilinguistic and culturally relevant content on the digital resource navigator. The contracted partner’s team (e.g., CP2.3) commented on the earlier challenges of connecting with the Spanish-speaking community: “…not having been able to connect with more Spanish-speaking populations than we have. Along with that, having all the other languages that we represent on the Navigator… Not really having that much direct access to folks in that community”. Additionally, CP2.2 described that community engagement could have been more helpful in the early planning process of the project: “…we recently had a couple work groups with… a group of Latinas. They were Spanish-speaking only and they actually had a lot of suggestions because they actually have their own Facebook group, but these are the conversations I wish we’d had a little bit earlier. But better late than never.” In addition to engaging Latinx and Spanish-speaking populations through Spanish work groups (CS2.3, CS2.4), multiple participants (CP2.2, CP2.3, CS2.3, CS2.5) also mentioned that effective marketing and outreach efforts might facilitate the process of connecting with other historically underrepresented groups, such as veteran communities, faith-based organizations, individuals with special needs, and Korean and Chinese communities.

Transparent and open communication between County, contracted partners, and community partners was the most highlighted facilitator. CP2.1 described that a trusting relationship allowed more time and resources to be allocated to innovation development and community engagement: “There’s a very wide level of trust within everybody in the team to making the best decisions as possible for the project and for staff, so less checks and balances there, and more like this is what the Community wants. This is what we’re going to try to do as much as possible.” Multiple participants across different roles on the project (CP2.1, CP2.4, L.6) expressed that they were able to build trusting and collaborative relationships with proactive communication. Regularly scheduled meetings with clear agenda items, openness to feedback, active incorporation of feedback from community members, and discussions about specific design features and usefulness of the content improved design and feature development of the digital resource navigator. For example, CP2.2 described the process of engaging community co-chairs in the decision making around the need for broader community outreach, “for short things we run it by them [community co-chairs] and sort of get their temperature about if we should ask a broader group. Then, of course, we asked the County…it’s not a perfect process…and it’s iterative but we try our best….”.

This paper fills a literature gap by disseminating insights garnered from the initial phases of innovation in behavioral health payment and care. Applying the CFIR framework, we identified important facilitators of and barriers to Orange County’s behavioral health system transformation efforts under several key themes in the context of an innovation project. Specifically, aligning goals and values, fostering engagement and partnership, and promoting communication were all highlighted as important factors related to developing a template for value-based contracts that promote payor-agnostic care (Part 1) and creating a digital resource navigator (Part 2). Changing state guidelines and priorities, different incentive structures within the US health care system, and difficulties in braiding public and private funds (e.g., private insurance companies, philanthropic organizations) were unique barriers to developing a template for value-based contracts that promote payor-agnostic care. Leveraging diverse communities to inform the design and content of the digital platform, mostly in the domain of innovation characteristics, was a facilitator of creating the resource navigator.

Part 1. Develop a template for value-based payment contracts that promote payor-agnostic care

Misalignment in incentives, values, and goals posed barriers to developing a template for value-based contracts. Value-based payment models and payor-agnostic care are a disruption to the status quo of fee-for-service predominance and service fragmentation by payor source. Thus, the change to value-based payments could be perceived as adding regulatory and financial risks for both public and private sectors. Similar to challenges identified in our study, in a study of value-based care for substance use disorder treatment, researchers identified providers’ buy-in to value-based concepts as a key workforce challenge [ 11 ]. Additionally, we found developing a template for value-based contracts was perceived as a lower priority compared to other organizational and state initiatives due to limited agency bandwidth and competing priorities during the COVID-19 global pandemic. This was not unique in this implementation context. Delayed transition to value-based payments has been common in many hospital settings. For example, the Centers for Medicare and Medicaid Services (CMS) stopped accepting applications for new Accountable Care Organizations (a type of value-based contract) in 2021 [ 23 ].

Providing financial incentives may increase the acceptability of value-based contracts that promote payor-agnostic care. Existing financial strategies often rely on public funds, such as increased pay-for-service, grants, and cost-sharing, which may not be a sustainable and scalable solution [ 1 ]. Braiding public and private funding streams may help change the current incentive structure and provide sustainable resources for implementing value-based payment and payor-agnostic care. Funding from philanthropic organizations may be a potential funding source to fill some gaps in the behavioral healthcare sphere, and venture capital firms are getting involved in creating new innovations that may increase access to behavioral health services [ 24 ]. With both private and public sectors around the table, long-term cost-saving potentials of a value-based contract may act as a shared motive towards creating momentum that is needed to facilitate system transformation efforts [ 25 ].

Our work furthers the understanding of factors influencing the development of a digital resource navigator. We find that aligning goals and values, fostering engagement, and promoting transparent and efficient communication were important to the development and implementation of a digital resource navigator in Orange County. In our analyses, the perceived compatibility between the digital resource navigator and the extent to which it improved the current referral process workflow impacted the enthusiasm about the digital resource navigator. Consistent with our findings, past research has also found that providers were more likely to implement a technology-enabled tool when the tool could fit into or improve the existing workflow [ 26 , 27 ]. Our data also revealed that some interviewees did not deem the digital resource navigator as a priority. Similarly, Zhao et al. (2022) found that some providers perceived implementing a technology-enabled tool as a low priority, especially considering that there were limited resources in their organizations.

Inclusive design, communication and engagement strategies allowed the contracted partners to better align a digital resource navigator with the needs and priorities of the diverse communities in Orange County. In particular, it is important to understand the unique needs for information and resources among marginalized and underrepresented populations (e.g., monolingual communities, faith-based organizations) [ 28 ]. The design of technology-enabled behavioral health tools, including the digital resource navigator that was evaluated in this study, needs feedback from diverse community stakeholders. In our analyses, staff members and community champions shared their wishes for engaging diverse community members early in the iterative design process of the digital resource navigator. This cross-sector collaboration process requires inclusive communication strategies, as contracted partners, community stakeholders, and academic evaluators often speak different languages and have different levels of technological understanding. It was highlighted in our data that leveraging connections and knowledge of community champions not only facilitated communication but also outreach to the broader community. However, it is also worth noting that centering community voice and consistent outreach activities often required additional staff time and bandwidth, which could be challenging within the constraints of the County’s resources and regulations. Additionally, ongoing tailoring and adaptation of existing resources on the digital resource navigator are necessary. For example, community members shared frustration when resources on the platform were outdated. The process of sustaining timely updates of platform content may be costly and create workforce challenges.

Limitations

As found in the current study, external state policies and financial incentives in the outer setting were barriers to the acceptance of value-based and payor-agnostic care; although, government initiatives, such as California Advancing and Innovating Medi-Cal (CalAIM), could also facilitate the process. Attitudes and approaches towards system transformation may differ by state due to different state initiatives. It is important to note this project, along with a few mentioned past studies [ 8 , 9 ] relied on public funding, which could be even more limited in lower-resourced states and counties. This project was conducted in the state of California, which has more resources than other states, as evidenced by higher income and higher GDP. Substantial variations in resources (e.g., provider availability, funding) at the County and state level may also impact agency bandwidth to pilot value-based payment contracts [ 25 ] and develop and sustain a digital resource navigator. Additionally, we did not conduct consumer interviews and observations. Consumer perspectives and outcomes can be particularly helpful in curating inclusive content and improving the user interface of the digital resource navigator. However, it is worth noting that we included a diverse group of interviewees, including staff members, leadership, and community stakeholders. Some of the interviewees worked closely with the community being served in this early stage of the grant. Additionally, the data were from an early stage (first 2.5 years) of a five-year grant-funded project in Orange County; some identified facilitators (e.g., shared enthusiasm about a new and exciting project) and barriers (e.g., COVID-19) may be related to the time point.

Future directions

First, given the influence of external state policies, financial incentives, and County resources on the acceptability of value-based and payor-agnostic care, further investigation is needed to understand the impact of a specific County health care initiative on behavioral health care system transformation efforts. Comparative evaluation of barriers to and facilitators of various system transformation efforts across states and counties can provide valuable insights into policy implications and guide tailored support for local stakeholders. Second, centering the voices and experiences of consumers can be particularly helpful in ensuring the inclusivity of the content and design of the digital resource navigator. Collecting data from consumers through interviews and surveys can facilitate understanding the perceived usefulness and usability of the platform and content on the digital resource navigator.

We analyzed 29 key informant interviews to provide insight into the barriers and facilitators related to County behavioral health system transformation in a state-funded project. Overall, aligning goals and values, fostering engagement and partnership, and promoting communication were important factors to consider when developing a template for value-based contracts that promote payor-agnostic care (Part 1) and developing a digital resource navigator (Part 2). Being aware of changing state guidelines and priorities, having cross-sector specialty knowledge about incentive structures in the public and private sectors, and braiding public and private funds were important to developing a template for value-based contracts that promote payor-agnostic care. Leveraging diverse communities to inform the design and content and incorporating their timely feedback was particularly important to the development of the resource navigator. As these insights were drawn from diverse perspectives within the County Behavioral Health system, we hope that our research will prove invaluable to similar transformation endeavors in the future.

Availability of data and materials

The data collected and analyzed for this study are not publicly available because this was not a requirement of the project’s funder, and the verbal consent process did not elicit participants’ consent for their data to be publicly shared.

Dopp AR, Narcisse MR, Mundey P, et al. A scoping review of strategies for financing the implementation of evidence-based practices in behavioral health systems: state of the literature and future directions. Implement Res Pract. 2020;1:263348952093998. https://doi.org/10.1177/2633489520939980 .

Article   Google Scholar  

Porter ME, Kaplan RS. How to pay for health care. Harv Bus Rev. 2016;94(7–8):88–98.

PubMed   Google Scholar  

Priester MA, Browne T, Iachini A, Clone S, DeHart D, Seay KD. Treatment access barriers and disparities among individuals with co-occurring mental health and substance use disorders: an integrative literature review. J Subst Abuse Treat. 2016;61:47–59. https://doi.org/10.1016/j.jsat.2015.09.006 .

Article   PubMed   Google Scholar  

U.S. Department of Health and Human Services, Health Resources and Services Administration, National Center for Health Workforce Analysis. State-level projections of supply and demand for behavioral health occupations: 2016–2030. Published online 2018. https://bhw.hrsa.gov/sites/default/files/bureau-health-workforce/data-research/state-level-estimates-report-2018.pdf . Accessed 15 Aug 2023.

Walker ER, Cummings JR, Hockenberry JM, Druss BG. Insurance status, use of mental health services, and unmet need for mental health care in the United States. Psychiatr Serv. 2015;66(6):578–84. https://doi.org/10.1176/appi.ps.201400248 .

Article   PubMed   PubMed Central   Google Scholar  

Sorkin DH, Mukamel DB, Eikey EV, et al. Behavioral health system transformation innovation project – MHSA innovation report. In: Program of research in translational technology enabling high quality care. Irvine: University of California; 2022.

Google Scholar  

Hyatt AS, Tepper MC, O’Brien CJ. Recognizing and seizing the opportunities that value-based payment models offer behavioral health care. Psychiatr Serv. 2021;72(6):732–5. https://doi.org/10.1176/appi.ps.202000044 .

Bao Y, McGuire TG, Chan YF, et al. Value-based payment in implementing evidence-based care: the mental health integration program in Washington state. Am J Manag Care. 2017;23(1):48–53.

PubMed   PubMed Central   Google Scholar  

Goff SL, Gurewich D, Alcusky M, Kachoria AG, Nicholson J, Himmelstein J. Barriers and facilitators to implementation of value-based care models in new Medicaid accountable care organizations in Massachusetts: a study protocol. Front Public Health. 2021;9:645665. https://doi.org/10.3389/fpubh.2021.645665 .

Kissam SM, Beil H, Cousart C, Greenwald LM, Lloyd JT. States encouraging value-based payment: lessons from CMS’s state innovation models initiative. Milbank Q. 2019;97(2):506–42. https://doi.org/10.1111/1468-0009.12380 .

O’Grady MA, Lincourt P, Gilmer E, et al. How are substance use disorder treatment programs adjusting to value-based payment? A statewide qualitative study. Subst Abuse Res Treat. 2020;14:117822182092402. https://doi.org/10.1177/1178221820924026 .

Sederer LI, Derman M, Carruthers J, Wall M. The New York state collaborative care initiative: 2012–2014. Psychiatr Q. 2016;87(1):1–23. https://doi.org/10.1007/s11126-015-9375-1 .

American Psychiatric Association. Case studies: New York State Collaborative Care Initiative: 2012–20141. https://www.psychiatry.org/getmedia/b684932c-c994-4125-abee-165d7082ed1a/Case-Study-Collaborative-Care-Model-NewYork.pdf . Accessed 1 Aug 2023.

Cattel D, Eijkenaar F. Value-based provider payment initiatives combining global payments with explicit quality incentives: a systematic review. Med Care Res Rev. 2020;77(6):511–37. https://doi.org/10.1177/1077558719856775 .

Anglin G, Tu H, Liao K, Sessums L, Taylor EF. Strengthening multipayer collaboration: lessons from the comprehensive primary care initiative. Milbank Q. 2017;95(3):602–33. https://doi.org/10.1111/1468-0009.12280 .

Paulson CA, Durazo EM, Purry LD, et al. Adding a seat at the table: a case study of the provider’s perspective on integrating community health workers at provider practices in California. Front Public Health. 2021;9:690067. https://doi.org/10.3389/fpubh.2021.690067 .

Falconer E, Kho D, Docherty JP. Use of technology for care coordination initiatives for patients with mental health issues: a systematic literature review. Neuropsychiatr Dis Treat. 2018;14:2337–49. https://doi.org/10.2147/NDT.S172810 .

Noble JM, Zamani A, Gharaat M, et al. Developing, implementing, and evaluating an artificial intelligence–guided mental health resource navigation chatbot for health care workers and their families during and following the COVID-19 pandemic: protocol for a cross-sectional study. JMIR Res Protoc. 2022;11(7):e33717. https://doi.org/10.2196/33717 .

Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009;4(1):50. https://doi.org/10.1186/1748-5908-4-50 .

Hill JN, Locatelli SM, Bokhour BG, et al. Evaluating broad-scale system change using the consolidated framework for implementation research: challenges and strategies to overcome them. BMC Res Notes. 2018;11(1):560. https://doi.org/10.1186/s13104-018-3650-9 .

Kilaru AS, Crider CR, Chiang J, Fassas E, Sapra KJ. Health care leaders’ perspectives on the Maryland All-Payer Model. JAMA Health Forum. 2022;3(2):e214920. https://doi.org/10.1001/jamahealthforum.2021.4920 .

Safaeinili N, Brown-Johnson C, Shaw JG, Mahoney M, Winget M. CFIR simplified: Pragmatic application of and adaptations to the Consolidated Framework for Implementation Research (CFIR) for evaluation of a patient‐centered care transformation within a learning health system. Learn Health Syst. 2020;4(1). https://doi.org/10.1002/lrh2.10201 .

Feeley TW. Covid-19 hasn’t been a tipping point for value-based care, but it should be. NEJM Catal. 2021;2(1):CAT.20.0641. https://doi.org/10.1056/CAT.20.0641 .

Shah RN, Berry OO. The rise of venture capital investing in mental health. JAMA Psychiat. 2021;78(4):351. https://doi.org/10.1001/jamapsychiatry.2020.2847 .

Conrad DA, Grembowski D, Hernandez SE, Lau B, Marcus-Smith M. Emerging lessons from Regional and State Innovation in Value-based payment reform: balancing collaboration and disruptive innovation: emerging lessons from Innovation in Value-based payment reform. Milbank Q. 2014;92(3):568–623. https://doi.org/10.1111/1468-0009.12078 .

Lattie EG, Nicholas J, Knapp AA, Skerl JJ, Kaiser SM, Mohr DC. Opportunities for and tensions surrounding the use of technology-enabled mental health services in community mental health care. Adm Policy Ment Health Ment Health Serv Res. 2020;47(1):138–49. https://doi.org/10.1007/s10488-019-00979-2 .

Zhao X, Stadnick NA, Ceballos-Corro E, et al. Facilitators of and barriers to integrating digital mental health into county mental health services: qualitative interview analyses. JMIR Form Res. 2023;7:e45718. https://doi.org/10.2196/45718 .

Ramos G, Ponting C, Labao JP, Sobowale K. Considerations of diversity, equity, and inclusion in mental health apps: a scoping review of evaluation frameworks. Behav Res Ther. 2021;147:103990. https://doi.org/10.1016/j.brat.2021.103990 .

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This work was funded by the Orange County Health Care Agency, Mental Health and Recovery Services, Innovation Projects, Mental health Services Act/Prop 63 (contract number MA-042-21011324). This work was also supported by the Institute for Clinical and Translational Sciences (ICTS) under Grant (UL1TR001414). The information or content and conclusions presented here are those of the authors and should not be construed as official position or policy of, nor should any endorsements be inferred by, the participating partners and/or the Orange County Health Care Agency.

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XZ contributed to the conceptualization of the work, analysis and interpretation of data, and writing the original draft, and writing-review and editing. RV contributed to conceptualization of the work, collection analysis, interpretation of the data and writing-review and editing. JB, EE, DS, and DM contributed to writing-review and editing. SS contributed to the conceptualization of the work, collection and interpretation of the data, and writing-review and editing. DHS contributed to funding acquisition, conceptualization of the work, collection and interpretation of the data, and writing-review and editing.

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Zhao, X., Varisco, R., Borghouts, J. et al. Facilitators of and barriers to County Behavioral Health System Transformation and Innovation: an interview study. BMC Health Serv Res 24 , 604 (2024). https://doi.org/10.1186/s12913-024-11041-9

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DOE inks research deal with UP on strengthening market, regulatory frameworks for LNG

At a glance.

To date, it is apparent that there is still very lax oversight on the LNG and overall gas infrastructure development in the country – and that gap peddles ‘monopolistic tendency’ of some players in what could have been intended as a competitive marketplace for gas.

The approach of the Philippines on regulation as well as gas market development has also been standing on a very antiquated ledge – a system that is already being wiped off the map by cutting edge solutions and developments prevailing in more mature markets, primarily on the incursion of artificial intelligence (AI) and machine learning advancements across the LNG development value chain.

To guarantee that all players in the flourishing liquefied natural gas (LNG) industry of the country will all play by the same rules, the Department of Energy (DOE) has inked a ‘research study pact’ with the University of the Philippines (UP) on drawing up regulatory toolboxes and standards that shall be enforced in the sector.

The memorandum of agreement (MOA) that was cemented with the University of the Philippines Statistical Center Research Foundation, Inc. (UPSCRFI) covers the third phase of the Gas Policy Development Project (GPDP-3) spearheaded by the DOE. Energy Secretary Raphael P.M. Lotilla and UPSCRFI Executive Director Dr. Joseph Ryan Lansangan had been the signatories in the deal.

“This significant collaboration underscores the government’s thrust of establishing a regulatory framework, building the capacity of regulators, and providing evidence-based data and technical inputs for policymaking and sectoral planning related to downstream natural gas industry,” the DOE said.

Through the years, drawing up ‘evidence-based’ data has always been the ‘weak link’ not just of the Philippine policymakers and regulators, but even for many of the industry stakeholders – and in the ‘guessing game proclivity’ of market players, it’s the consumers who would often suffer not just from inferior services, but also high energy tariffs.

In the newly inked research pact with UP, it was emphasized that the study is anchored on a technical assistance extended by foreign development partners to the DOE – and primarily intended on crafting “the codes of standard, rules and regulations governing the country’s downstream natural gas industry.” Technical assistance for the study has been extended by  Economic Research Institute for ASEAN and East Asia (ERIA) and the government of Japan.

Lotilla conveyed that “as we enter the third phase, I am optimistic that we will achieve more sustained programs. The DOE stands ready to provide all necessary support to ensure its successful implementation. No efforts laid in previous phases will go to waste.”

Specifically, the regulatory framework shall underpin “the design, construction, operation, and maintenance of facilities for LNG storage and regasification terminal, transmission and distribution system and third party-access.”

The DOE noted the research will delve with “LNG market development and technology and strengthening the capacity of agency regulators.”

On third party access, in particular, there is no existing regulation yet on the throughput fee if an industry player with LNG import facility will be delivering gas to customers outside of its own requirements. 

• Open access
• Published: 06 May 2024

Lipids, apolipoproteins and gestational diabetes mellitus: a Mendelian randomization study

• Dan Shan 1 ,
• Ao Wang 1 &

BMC Pregnancy and Childbirth volume  24 , Article number:  347 ( 2024 ) Cite this article

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Metrics details

This study investigates the causal relationship between lipid traits and GDM in an effort to better understand the aetiology of GDM.

Employing a two-sample Mendelian Randomization (MR) framework, we used Single Nucleotide Polymorphisms (SNPs) as instrumental variables to examine the impact of lipids and apolipoproteins on GDM. The research comprised univariable and multivariable MR analyses, with a prime focus on individual and combined effects of lipid-related traits. Statistical techniques included the fixed-effect inverse variance weighted (IVW) method and supplementary methods such as MR-Egger for comprehensive assessment.

Our findings revealed the following significant associations: apoA-I and HDL cholesterol were inversely correlated with GDM risk, while triglycerides showed a positive correlation. In multivariable analysis, apoA-I consistently exhibited a strong causal link with GDM, even after adjusting for other lipids and Body Mass Index (BMI).

The study demonstrates a significant causal relationship between apoA-I and GDM risk.

Peer Review reports

Introduction

Gestational Diabetes Mellitus (GDM) represents a major public health concern due to its increasing prevalence and profound effects on both maternal and foetal health [ 1 , 2 ]. Approximately 5–7% of pregnancies are estimated to be impacted by GDM, with variations depending on the population studied and diagnostic standards [ 3 ]. Characterised by glucose intolerance first identified during pregnancy, GDM is linked to an elevated risk of various adverse outcomes [ 4 ]. These include a higher likelihood of cesarean delivery, pre-eclampsia, and the development of type 2 diabetes in later life for mothers [ 5 , 6 , 7 ]. For infants, the risks extend to macrosomia, hypoglycaemia, and a predisposition to obesity [ 8 , 9 ].

Effective strategies for prevention, early detection, as well as management of GDM can mitigate short-term complications and offer a chance to improve long-term health outcomes [ 10 , 11 ]. This underscores the need for continued research into its pathophysiology, risk factors, and effective interventions. Environmental factors, lifestyle choices, and genetics all have a role in the pathophysiology of GDM [ 12 , 13 ]. Research into the role of lipid metabolism in GDM highlights its significance in the pathogenesis of this condition. Observational studies have demonstrated that dysregulated lipid profiles, including elevated triglycerides and low HDL cholesterol levels, are commonly observed in GDM. These lipid imbalances contribute to insulin resistance, a hallmark of GDM [ 14 ]. Additionally, a lot of attention has been given to the role of specific apolipoproteins, particularly Apolipoprotein A-I (apoA-I) and Apolipoprotein B(apoB), in modulating lipid metabolism and influencing GDM risk. Wu et al. found that apoA-I protects rats from pregnancy-induced insulin resistance by increasing insulin sensitivity and inhibiting inflammation in adipose tissue and skeletal muscle [ 15 ]. Zheng et al. reported that the serum levels of triglycerides, LDL cholesterol, and Apolipoprotein B during the first trimester of pregnancy have important clinical value in predicting GDM [ 16 ]. However, the causal nature of this association is yet unclear and requires further investigation.

Mendelian Randomization (MR) is a method that leverages genetic variations as tools to infer causal relationships between risk factors and diseases [ 17 ]. In MR studies, genetic variants known to affect lipid levels (such as those affecting HDL cholesterol, LDL cholesterol, and triglyceride levels) are employed as instrumental variables. These variants are generally unaltered by environmental factors and disease states, making them ideal for examining the causal effect of lipid levels on GDM risk. This robust methodology may provide valuable insights into the underlying mechanisms while shedding light on the biological pathways linking lipid-related traits to GDM.

Materials and methods

Study design.

In this research, we conducted a two-sample Mendelian randomization (MR) analysis in order to assess the causal link between lipids and apolipoproteins and GDM. SNPs served as instrumental variables (IVs) [ 18 ]. To enhance result accuracy, validating three key hypotheses throughout the entire process is crucial [ 19 ]. We identified genetic variants significantly associated with lipid levels and calculated the corresponding F-statistics to assess the strength of each variant as an instrumental variable. We conducted an analysis of confounding factors to ensure that the selected variants are not associated with known confounders, such as BMI. We also used methods such as MR-Egger regression to evaluate the potential pleiotropy of the genetic variants, further confirming that their effects on GDM are primarily mediated through lipid levels (Fig.  1 ).

Overview of the MR analysis process. Abbreviations: MR, mendelian randomization; IVs, instrumental variables; IVW, Inverse variance weighted; HDL-C, High density lipoprotein cholesterol; LDL-C, Low density lipoprotein cholesterol

The univariable MR analysis sought to analyse the correlation between specific lipid-related traits and GDM. The multivariable MR analysis, on the other hand, aimed to assess the individual impacts of interrelated lipid-related traits on GDM [ 20 ]. Both analyses aimed to comprehend the relationship between lipid-related traits and the risk of GDM, with the univariable focusing on individual traits and the multivariable concentrating on their interactions. All original studies obtained ethical review approval and informed consent. Genetic instruments for apoA-I, apoB, LDL cholesterol, HDL cholesterol, and triglycerides were extracted from the IEU Open GWAS database (Supplementary Table S1 ).

Statistical analyses

Our main approach for MR analysis was the fixed-effect inverse variance weighted (IVW) method. In cases where potential heterogeneity among selected SNPs was present, random effects modelling was employed [ 21 ]. Additionally, we utilised four other effective methods—MR-Egger, weighted median, weighted mode, and simple mode—to comprehensively analyse the potential relationship. It is noteworthy that although these methods offer a comprehensive evaluation, they might have less statistical power compared to the IVW test. We employed Cochran’s Q statistic and the MR-Egger test for assessing heterogeneity and pleiotropy, respectively.

Genetic instrument selection

In univariable MR analysis, independent SNPs linked to apoA-I, apoB, LDL cholesterol, HDL cholesterol, and triglycerides were isolated using a threshold of linkage disequilibrium clumping (r 2  = 0.001) and a window size of 10 megabases. Specifically, we focused on genome-wide significant SNPs ( p  < 5e-8) associated with each trait so as to reduce redundancy.

Sensitivity analyses

To ensure the reliability of the identified causal effect of lipids and apolipoproteins on GDM, we carried out a thorough set of sensitivity analyses. Cochran’s Q statistic was utilised to assess potential heterogeneity within the data [ 22 ]. The MR-Egger intercept analysis was employed to investigate horizontal pleiotropy [ 23 ]. We also conducted a Leave-one-out analysis to examine if any single SNP substantially affected the outcomes by systematically removing SNPs individually. Additionally, reverse MR analyses were performed to explore the potential reverse causal link between lipids and apolipoproteins (as seen in the forward MR analysis) and GDM.

For multivariable MR analysis, we applied two models to further understand the connection between lipid-related traits and GDM risk. In Model 1, five lipid-related traits (apoA-I, apoB, LDL cholesterol, HDL cholesterol, and triglycerides) were included in multivariable analysis.

In Model 2, we included BMI for analysis, along with the three traits that showed positive associations in univariable analysis: apoA-I, HDL cholesterol, and triglycerides.

All analyses were performed using R (version 4.2.0) and RStudio, employing the R packages “TwoSampleMR” and “MR-PRESSO”.

Univariable Mendelian randomization analysis

After excluding SNPs associated with confounders, we identified 261 instrumental variables for apoA-I, 179 IVs for apoB, 86 IVs for HDL cholesterol, 147 IVs for LDL cholesterol, and 216 IVs for triglycerides. F-statistics of Instrument Variables for lipids and apolipoproteins are shown in Supplementary Table S7.

A significant correlation between apoA-I and the risk of GDM was determined through the IVW technique (OR [95%CI] = 0.76 [0.68–0.86]; p  < 0.001). Moreover, HDL cholesterol was found to be significantly associated with a lower risk of GDM (OR [95%CI] = 0.79[0.69–0.89]; p  < 0.001). Triglycerides were found to be significantly linked to an elevated risk of GDM (OR [95%CI] = 1.28[1.12–1.46]; p  < 0.001). (Fig.  2 and Supplementary Table S3).

Univariable Mendelian randomization results using different methods. Abbreviations: SNP, Single nucleotide polymorphism; HDL-C, High density lipoprotein cholesterol; LDL-C, Low density lipoprotein cholesterol; OR, Odds ration; CI, Confidence interval

A reverse MR analysis was conducted to explore the potential causal effect of GDM on lipid-related traits. The findings suggested no reverse causal relationship between GDM and each trait (Supplementary Table S4).

Multivariable Mendelian randomization analysis

Figure  3 presents the outcomes of the multivariable MR analysis in model 1. When adjusting simultaneously for apoA-I, apoB, LDL cholesterol, HDL cholesterol, and triglycerides, apoA-I continued to have a strong causal link with GDM; the OR was 0.59 (95% CI = 0.38, 0.91). However, the effects for HDL cholesterol and triglycerides were greatly reduced (Supplementary Table S5).

Multivariable Mendelian randomization using the inverse-variance weighted method in model 1. Model 1 included Apolipoprotein A-I, Apolipoprotein B, LDL cholesterol, HDL cholesterol and triglycerides. Abbreviations: SNP, Single nucleotide polymorphism; HDL-C, High density lipoprotein cholesterol; LDL-C, Low density lipoprotein cholesterol; OR, Odds ration; CI, Confidence interval

Figure  4 exhibits the outcomes of the multivariable MR analysis in model 2. Body mass index is known as a risk factor for GDM. For model 2, the subjects included the three traits with positive results in univariable analysis (apoA-I, HDL cholesterol, and triglycerides) and BMI. When adjusting simultaneously for apoA-I, HDL cholesterol and triglycerides, and BMI, apoA-I consistently showed a strong causal association with GDM; the OR was 0.59 (95% CI = 0.38, 0.92). However, the estimates of HDL cholesterol and triglycerides were significantly reduced (Supplementary Table S6).

Multivariable Mendelian randomization using the inverse-variance weighted method in model 2. Model 2 included Apolipoprotein A-I, HDL cholesterol, triglycerides and Body mass index. Abbreviations: SNP, Single nucleotide polymorphism; HDL-C, High density lipoprotein cholesterol; OR, Odds ration; CI, Confidence interval

Sensitivity analysis

In our analysis of apoB and HDL cholesterol causal impacts on GDM, instrumental heterogeneity was detected (Cochran’s Q test, p  < 0.05; Supplementary Table S2), leading us to employ the random-effects IVW method. On the other hand, for other analyses where no heterogeneity was observed (Cochran’s Q test, p  > 0.05), the fixed-effects IVW method was applied.

There was no evidence of horizontal pleiotropy in the MR-Egger intercept analysis results. Scatter plots illustrated the causal effect of lipid-related traits on GDM across the five MR methods; a positive relationship is indicated by a slope greater than zero, and vice versa (Supplementary Figure S1 ). Furthermore, no discernible heterogeneity was shown by the Funnel plot symmetry (Supplementary Figure S2).

The incidence of gestational diabetes mellitus (GDM) is increasing worldwide and poses a major concern for the health of pregnant women and their fetuses [ 24 , 25 ]. Our comprehensive investigation into the role of lipids and apolipoproteins in GDM is essential because they play a key role in metabolic pathways that may have an important impact on pregnancy outcomes [ 26 ].

Our study explored the intricate interplay between lipids, apolipoproteins, and GDM. ApoA-I is the major protein component of HDL and plays a critical role in reverse cholesterol transport, a key process in removing cholesterol from tissues and returning it to the liver for excretion. Conversely, apoB is a primary component of LDL, very-low-density lipoprotein, and intermediate-density lipoprotein, which are involved in the transport of cholesterol and triglycerides from the liver to peripheral tissues.

The noteworthy associations revealed between these biomarkers and GDM provide novel insights into their potential roles in the pathogenesis of this condition. In the univariable Mendelian randomization analysis, compelling associations were discovered between lipid and apolipoprotein levels and the risk of GDM. Importantly, apoA-I has demonstrated an inverse correlation with GDM risk, suggesting its potential protective role. This is consistent with the established function of apoA-I in facilitating reverse cholesterol transport and its anti-inflammatory properties, which could potentially mitigate GDM risk through enhanced lipid metabolism as well as reduced inflammation [ 27 , 28 ]. Similarly, the inverse association between HDL cholesterol and the risk of GDM is indicative of the protective role of high-density lipoproteins in cardiovascular health, potentially exerting a similar influence on GDM by modulating lipid homeostasis and insulin sensitivity [ 29 , 30 ]. On the other hand, dysregulated triglyceride levels may increase vulnerability to GDM, as suggested by the positive connection found between triglycerides and GDM risk. This relationship highlights the effect of high triglyceride levels on insulin resistance and impaired glucose metabolism.

In multivariable Mendelian randomization analyses, two distinct models provided intriguing insights into the relationship between lipid profiles and gestational diabetes mellitus (GDM). Model 1, which encompassed adjustments for all pertinent lipid and apolipoprotein features, notably highlighted apoA-I’s sustained significant association with GDM. This reinforces the robustness of apoA-I’s impact on GDM risk independent of other lipid factors. Interestingly, although there were initial significant correlations between HDL cholesterol and triglycerides in the univariable analysis, their effects diminished in Model 1, suggesting a potential attenuation or mediation of their individual associations with GDM when adjusting for other lipid factors.

The critical role of apoA-I in GDM was further highlighted in Model 2 by the inclusion of BMI. Even after adjusting for BMI, apoA-I maintained a robust association with GDM, emphasising its independent contribution to GDM risk [ 31 ]. However, the effects of HDL cholesterol and triglycerides were notably attenuated in this adjusted model, suggesting a potential interplay between these lipid traits and BMI in influencing GDM susceptibility. These findings underscore apoA-I’s consistent and considerable relationship with GDM, irrespective of BMI adjustments, while also pointing to the need for deeper exploration into the complex interrelationships among lipids, BMI, and GDM susceptibility to gain a more comprehensive understanding of their collective impact.

Our study has identified a robust causal association between apoA-I and GDM, wherein elevated levels of apoA-I correspond to a significant reduction in GDM risk. This is partly in line with previous research. Metformin is a widely used insulin sensitizer [ 32 ]. As claimed by Karavia et al., the sensitizing effect of metformin is diminished in mice with apoA-I gene knock-down (apoA-I (-/-)), revealing that apoA-I may be involved in insulin sensitization [ 33 ]. A cross-sectional study found that low apoA-I was associated with insulin resistance in patients with impaired glucose tolerance [ 27 ]. However, Retnakaran et al. found no significant association between serum apoa-1 levels and the risk of insulin resistance or GDM in pregnant women in an observational study [ 34 ]. This discrepancy may be attributed to variations in study design and methodology, underlining the complexity involved in determining the precise role of apoA-I in GDM pathogenesis.

Our study uncovers a potential causal relationship between apoA-I levels and the risk of gestational diabetes, which could facilitate early prediction of GDM, inform prevention strategies and treatment interventions, and promote the advancement of personalized medicine.

It is important to note that our study has a number of limitations. Firstly, MR studies rely on certain assumptions, such as the absence of pleiotropy and horizontal pleiotropy, which could have an effect on the validity of the causal inference. While employing robust genetic instruments and sensitivity analyses to mitigate these concerns, complete elimination of residual confounding remains challenging. Secondly, our research also concentrated on the genetic effects of lipid-related traits on GDM risk. Although we adjusted for BMI in multivariable MR analysis, other factors, including environmental and lifestyle factors, were not taken into account. Subsequent studies should strive to incorporate these elements into their analyses, contributing to a more holistic comprehension of the causal mechanisms underlying the relationship between lipid-related traits and GDM. Thirdly, the summary statistics used in our study encompass data from both male and female participants and do not distinguish between lipid levels or BMI measured before and after pregnancy. This limitation may impact the specificity of our findings related to the risk of GDM, as the physiological conditions of these distinct groups can differ substantially. Additionally, a significant limitation of this study is the reliance on summary statistics, which restricts our ability to investigate non-linear relationships between lipid levels and the risk of GDM. The analysis operates under the assumption that these relationships are linear, which may not adequately capture the complexities inherent in lipid metabolism. This methodological simplification might fail to detect clinically significant non-linear effects, indicating that future research would benefit from employing more sophisticated methods capable of exploring these dynamics in greater detail.

In conclusion, our study strongly suggests a potential causal relationship between genetic susceptibility to apoA-I and a reduced risk of GDM. Further validation of our findings and investigation into the underlying biological mechanisms warrant additional research, which may advance personalised approaches to GDM prevention and management.

Availability of data and materials

Original data generated and analyzed during this study are included in this published article or supplementary material.

Abbreviations

Gestational Diabetes Mellitus

Apolipoprotein A-I

Apolipoprotein B

High-density lipoprotein cholesterol

Low-density lipoprotein cholesterol

Body mass index

Genome-wide association study

• Mendelian randomization

Single nucleotide polymorphism

Instrumental variable

Inverse variance weighted

Mendelian randomization pleiotropy residual sum and outlier

Linkage disequilibrium

Odds ration

Confidence interval

High density lipoprotein

Low-density lipoprotein

Johns EC, Denison FC, Norman JE, Reynolds RM. Gestational diabetes mellitus: mechanisms, treatment, and complications. Trends Endocrinol Metab. 2018;29(11):743–54.

Article   CAS   PubMed   Google Scholar  

McIntyre HD, Catalano P, Zhang C, Desoye G, Mathiesen ER, Damm P. Gestational diabetes mellitus. Nat Rev Dis Primers. 2019;5(1):47.

Article   PubMed   Google Scholar  

Sweeting A, Wong J, Murphy HR, Ross GP. A clinical update on gestational diabetes mellitus. Endocr Rev. 2022;43(5):763–93.

Article   PubMed   PubMed Central   Google Scholar  

Choudhury AA, Devi RV. Gestational diabetes mellitus - a metabolic and reproductive disorder. Biomed Pharmacother. 2021;143:112183.

Buchanan TA, Xiang AH, Page KA. Gestational diabetes mellitus: risks and management during and after pregnancy. Nat Rev Endocrinol. 2012;8(11):639–49.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Kim C. Maternal outcomes and follow-up after gestational diabetes mellitus. Diabet Med. 2014;31(3):292–301.

Yang Y, Wu N. Gestational diabetes mellitus and preeclampsia: correlation and influencing factors. Front Cardiovasc Med. 2022;9:831297.

Monteiro LJ, Norman JE, Rice GE, Illanes SE. Fetal programming and gestational diabetes mellitus. Placenta. 2016;48 Suppl 1:S54-s60.

Kautzky-Willer A, Harreiter J, Winhofer-Stöckl Y, Bancher-Todesca D, Berger A, Repa A, et al. Gestational diabetes mellitus (Update 2019). Wien Klin Wochenschr. 2019;131(Suppl 1):91–102.

Kintiraki E, Goulis DG. Gestational diabetes mellitus: multi-disciplinary treatment approaches. Metabolism. 2018;86:91–101.

Simmons D, Immanuel J, Hague WM, Teede H, Nolan CJ, Peek MJ, et al. Treatment of gestational diabetes mellitus diagnosed early in pregnancy. N Engl J Med. 2023;388(23):2132–44.

Plows JF, Stanley JL, Baker PN, Reynolds CM, Vickers MH. The pathophysiology of gestational diabetes mellitus. Int J Mol Sci. 2018;19(11):3342.

Hu G, Liu H, Leng J, Wang L, Li W, Zhang S, et al. Effects of a lifestyle intervention in young women with GDM and subsequent diabetes. Nutrients. 2022;14(24):5232.

Layton J, Powe C, Allard C, Battista MC, Doyon M, Bouchard L, et al. Maternal lipid profile differs by gestational diabetes physiologic subtype. Metabolism. 2019;91:39–42.

Wu BJ, Sun Y, Ong KL, Li Y, Tang S, Barter PJ, et al. Apolipoprotein A-I protects against pregnancy-induced insulin resistance in rats. Arterioscler Thromb Vasc Biol. 2019;39(6):1160–71.

Zheng Y, Hou W, Xiao J, Huang H, Quan W, Chen Y. Application value of predictive model based on maternal coagulation function and glycolipid metabolism indicators in early diagnosis of gestational diabetes mellitus. Front Public Health. 2022;10:850191.

Emdin CA, Khera AV, Kathiresan S. Mendelian randomization. JAMA. 2017;318(19):1925–6.

Lawlor DA, Harbord RM, Sterne JA, Timpson N, Davey SG. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med. 2008;27(8):1133–63.

Davies NM, Holmes MV, Davey SG. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ. 2018;362:k601.

Sanderson E. Multivariable Mendelian randomization and mediation. Cold Spring Harb Perspect Med. 2021;11(2):984.

Article   Google Scholar  

Burgess S, Dudbridge F, Thompson SG. Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods. Stat Med. 2016;35(11):1880–906.

Bowden J, Del Greco MF, Minelli C, Zhao Q, Lawlor DA, Sheehan NA, et al. Improving the accuracy of two-sample summary-data Mendelian randomization: moving beyond the NOME assumption. Int J Epidemiol. 2019;48(3):728–42.

Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44(2):512–25.

Vince K, Perković P, Matijević R. What is known and what remains unresolved regarding gestational diabetes mellitus (GDM). J Perinat Med. 2020;48(8):757–63.

Giuliani C, Sciacca L, Biase ND, Tumminia A, Milluzzo A, Faggiano A, et al. Gestational diabetes mellitus pregnancy by pregnancy: early, late and nonrecurrent GDM. Diabetes Res Clin Pract. 2022;188:109911.

O’Malley EG, Reynolds CME, Killalea A, O’Kelly R, Sheehan SR, Turner MJ. Maternal obesity and dyslipidemia associated with gestational diabetes mellitus (GDM). Eur J Obstet Gynecol Reprod Biol. 2020;246:67–71.

Feng X, Gao X, Yao Z, Xu Y. Low apoA-I is associated with insulin resistance in patients with impaired glucose tolerance: a cross-sectional study. Lipids Health Dis. 2017;16(1):69.

Tang S, Tabet F, Cochran BJ, Cuesta Torres LF, Wu BJ, Barter PJ, et al. Apolipoprotein A-I enhances insulin-dependent and insulin-independent glucose uptake by skeletal muscle. Sci Rep. 2019;9(1):1350.

O’Mara AE, Johnson JW, Linderman JD, Brychta RJ, McGehee S, Fletcher LA, et al. Chronic mirabegron treatment increases human brown fat, HDL cholesterol, and insulin sensitivity. J Clin Invest. 2020;130(5):2209–19.

Chung ST, Katz LEL, Stettler-Davis N, Shults J, Sherman A, Ha J, et al. The relationship between lipoproteins and insulin sensitivity in youth with obesity and abnormal glucose tolerance. J Clin Endocrinol Metab. 2022;107(6):1541–51.

King TW, Cochran BJ, Rye KA. ApoA-I and diabetes. Arterioscler Thromb Vasc Biol. 2023;43(8):1362–8.

Madiraju AK, Qiu Y, Perry RJ, Rahimi Y, Zhang XM, Zhang D, et al. Metformin inhibits gluconeogenesis via a redox-dependent mechanism in vivo. Nat Med. 2018;24(9):1384–94.

Karavia EA, Hatziri A, Kalogeropoulou C, Papachristou NI, Xepapadaki E, Constantinou C, et al. Deficiency in apolipoprotein A-I ablates the pharmacological effects of metformin on plasma glucose homeostasis and hepatic lipid deposition. Eur J Pharmacol. 2015;766:76–85.

Retnakaran R, Ye C, Connelly PW, Hanley AJ, Sermer M, Zinman B. Serum apoA1 (Apolipoprotein A-1), insulin resistance, and the risk of gestational diabetes mellitus in human pregnancy-brief report. Arterioscler Thromb Vasc Biol. 2019;39(10):2192–7.

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Shan, D., Wang, A. & Yi, K. Lipids, apolipoproteins and gestational diabetes mellitus: a Mendelian randomization study. BMC Pregnancy Childbirth 24 , 347 (2024). https://doi.org/10.1186/s12884-024-06556-2

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Received : 22 January 2024

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DOI : https://doi.org/10.1186/s12884-024-06556-2

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