importance of conceptual framework in a research study

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base
• Methodology
• What Is a Conceptual Framework? | Tips & Examples

What Is a Conceptual Framework? | Tips & Examples

Published on August 2, 2022 by Bas Swaen and Tegan George. Revised on March 18, 2024.

A conceptual framework illustrates the expected relationship between your variables. It defines the relevant objectives for your research process and maps out how they come together to draw coherent conclusions.

Keep reading for a step-by-step guide to help you construct your own conceptual framework.

Table of contents

Developing a conceptual framework in research, step 1: choose your research question, step 2: select your independent and dependent variables, step 3: visualize your cause-and-effect relationship, step 4: identify other influencing variables, frequently asked questions about conceptual models.

A conceptual framework is a representation of the relationship you expect to see between your variables, or the characteristics or properties that you want to study.

Conceptual frameworks can be written or visual and are generally developed based on a literature review of existing studies about your topic.

Your research question guides your work by determining exactly what you want to find out, giving your research process a clear focus.

However, before you start collecting your data, consider constructing a conceptual framework. This will help you map out which variables you will measure and how you expect them to relate to one another.

In order to move forward with your research question and test a cause-and-effect relationship, you must first identify at least two key variables: your independent and dependent variables .

• The expected cause, “hours of study,” is the independent variable (the predictor, or explanatory variable)
• The expected effect, “exam score,” is the dependent variable (the response, or outcome variable).

Note that causal relationships often involve several independent variables that affect the dependent variable. For the purpose of this example, we’ll work with just one independent variable (“hours of study”).

Now that you’ve figured out your research question and variables, the first step in designing your conceptual framework is visualizing your expected cause-and-effect relationship.

We demonstrate this using basic design components of boxes and arrows. Here, each variable appears in a box. To indicate a causal relationship, each arrow should start from the independent variable (the cause) and point to the dependent variable (the effect).

It’s crucial to identify other variables that can influence the relationship between your independent and dependent variables early in your research process.

Some common variables to include are moderating, mediating, and control variables.

Moderating variables

Moderating variable (or moderators) alter the effect that an independent variable has on a dependent variable. In other words, moderators change the “effect” component of the cause-and-effect relationship.

Let’s add the moderator “IQ.” Here, a student’s IQ level can change the effect that the variable “hours of study” has on the exam score. The higher the IQ, the fewer hours of study are needed to do well on the exam.

Let’s take a look at how this might work. The graph below shows how the number of hours spent studying affects exam score. As expected, the more hours you study, the better your results. Here, a student who studies for 20 hours will get a perfect score.

But the graph looks different when we add our “IQ” moderator of 120. A student with this IQ will achieve a perfect score after just 15 hours of study.

Below, the value of the “IQ” moderator has been increased to 150. A student with this IQ will only need to invest five hours of study in order to get a perfect score.

Here, we see that a moderating variable does indeed change the cause-and-effect relationship between two variables.

Mediating variables

Now we’ll expand the framework by adding a mediating variable . Mediating variables link the independent and dependent variables, allowing the relationship between them to be better explained.

Here’s how the conceptual framework might look if a mediator variable were involved:

In this case, the mediator helps explain why studying more hours leads to a higher exam score. The more hours a student studies, the more practice problems they will complete; the more practice problems completed, the higher the student’s exam score will be.

Moderator vs. mediator

It’s important not to confuse moderating and mediating variables. To remember the difference, you can think of them in relation to the independent variable:

• A moderating variable is not affected by the independent variable, even though it affects the dependent variable. For example, no matter how many hours you study (the independent variable), your IQ will not get higher.
• A mediating variable is affected by the independent variable. In turn, it also affects the dependent variable. Therefore, it links the two variables and helps explain the relationship between them.

Control variables

Lastly,  control variables must also be taken into account. These are variables that are held constant so that they don’t interfere with the results. Even though you aren’t interested in measuring them for your study, it’s crucial to be aware of as many of them as you can be.

A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship.

A confounding variable is closely related to both the independent and dependent variables in a study. An independent variable represents the supposed cause , while the dependent variable is the supposed effect . A confounding variable is a third variable that influences both the independent and dependent variables.

Failing to account for confounding variables can cause you to wrongly estimate the relationship between your independent and dependent variables.

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

A control variable is any variable that’s held constant in a research study. It’s not a variable of interest in the study, but it’s controlled because it could influence the outcomes.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

Swaen, B. & George, T. (2024, March 18). What Is a Conceptual Framework? | Tips & Examples. Scribbr. Retrieved April 16, 2024, from https://www.scribbr.com/methodology/conceptual-framework/

Is this article helpful?

Other students also liked

Independent vs. dependent variables | definition & examples, mediator vs. moderator variables | differences & examples, control variables | what are they & why do they matter, unlimited academic ai-proofreading.

✔ Document error-free in 5minutes ✔ Unlimited document corrections ✔ Specialized in correcting academic texts

• Privacy Policy

Buy Me a Coffee

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

You may also like

Data Collection – Methods Types and Examples

Delimitations in Research – Types, Examples and...

Research Process – Steps, Examples and Tips

Research Design – Types, Methods and Examples

Institutional Review Board – Application Sample...

Evaluating Research – Process, Examples and...

What is a good example of a conceptual framework?

Last updated

18 April 2023

Reviewed by

Miroslav Damyanov

A well-designed study doesn’t just happen. Researchers work hard to ensure the studies they conduct will be scientifically valid and will advance understanding in their field.

Make research less tedious

Dovetail streamlines research to help you uncover and share actionable insights

• The importance of a conceptual framework

The main purpose of a conceptual framework is to improve the quality of a research study. A conceptual framework achieves this by identifying important information about the topic and providing a clear roadmap for researchers to study it.

Through the process of developing this information, researchers will be able to improve the quality of their studies in a few key ways.

Clarify research goals and objectives

A conceptual framework helps researchers create a clear research goal. Research projects often become vague and lose their focus, which makes them less useful. However, a well-designed conceptual framework helps researchers maintain focus. It reinforces the project’s scope, ensuring it stays on track and produces meaningful results.

Provide a theoretical basis for the study

Forming a hypothesis requires knowledge of the key variables and their relationship to each other. Researchers need to identify these variables early on to create a conceptual framework. This ensures researchers have developed a strong understanding of the topic before finalizing the study design. It also helps them select the most appropriate research and analysis methods.

Guide the research design

As they develop their conceptual framework, researchers often uncover information that can help them further refine their work.

Here are some examples:

Confounding variables they hadn’t previously considered

Sources of bias they will have to take into account when designing the project

Whether or not the information they were going to study has already been covered—this allows them to pivot to a more meaningful goal that brings new and relevant information to their field

• Steps to develop a conceptual framework

There are four major steps researchers will follow to develop a conceptual framework. Each step will be described in detail in the sections that follow. You’ll also find examples of how each might be applied in a range of fields.

Step 1: Choose the research question

The first step in creating a conceptual framework is choosing a research question . The goal of this step is to create a question that’s specific and focused.

By developing a clear question, researchers can more easily identify the variables they will need to account for and keep their research focused. Without it, the next steps will be more difficult and less effective.

Here are some examples of good research questions in a few common fields:

Natural sciences: How does exposure to ultraviolet radiation affect the growth rate of a particular type of algae?

Health sciences: What is the effectiveness of cognitive-behavioral therapy for treating depression in adolescents?

Business: What factors contribute to the success of small businesses in a particular industry?

Education: How does implementing technology in the classroom impact student learning outcomes?

Step 2: Select the independent and dependent variables

Once the research question has been chosen, it’s time to identify the dependent and independent variables .

The independent variable is the variable researchers think will affect the dependent variable . Without this information, researchers cannot develop a meaningful hypothesis or design a way to test it.

The dependent and independent variables for our example questions above are:

Natural sciences

Independent variable: exposure to ultraviolet radiation

Dependent variable: the growth rate of a particular type of algae

Health sciences

Independent variable: cognitive-behavioral therapy

Dependent variable: depression in adolescents

Independent variables: factors contributing to the business’s success

Dependent variable: sales, return on investment (ROI), or another concrete metric

Independent variable: implementation of technology in the classroom

Dependent variable: student learning outcomes, such as test scores, GPAs, or exam results

Step 3: Visualize the cause-and-effect relationship

This step is where researchers actually develop their hypothesis. They will predict how the independent variable will impact the dependent variable based on their knowledge of the field and their intuition.

With a hypothesis formed, researchers can more accurately determine what data to collect and how to analyze it. They will then visualize their hypothesis by creating a diagram. This visualization will serve as a framework to help guide their research.

The diagrams for our examples might be used as follows:

Natural sciences : how exposure to radiation affects the biological processes in the algae that contribute to its growth rate

Health sciences : how different aspects of cognitive behavioral therapy can affect how patients experience symptoms of depression

Business : how factors such as market demand, managerial expertise, and financial resources influence a business’s success

Education : how different types of technology interact with different aspects of the learning process and alter student learning outcomes

Step 4: Identify other influencing variables

The independent and dependent variables are only part of the equation. Moderating, mediating, and control variables are also important parts of a well-designed study. These variables can impact the relationship between the two main variables and must be accounted for.

A moderating variable is one that can change how the independent variable affects the dependent variable. A mediating variable explains the relationship between the two. Control variables are kept the same to eliminate their impact on the results. Examples of each are given below:

Moderating variable: water temperature (might impact how algae respond to radiation exposure)

Mediating variable: chlorophyll production (might explain how radiation exposure affects algae growth rate)

Control variable: nutrient levels in the water

Moderating variable: the severity of depression symptoms at baseline might impact how effective the therapy is for different adolescents

Mediating variable: social support might explain how cognitive-behavioral therapy leads to improvements in depression

Control variable: other forms of treatment received before or during the study

Moderating variable: the size of the business (might impact how different factors contribute to market share, sales, ROI, and other key success metrics)

Mediating variable: customer satisfaction (might explain how different factors impact business success)

Control variable: industry competition

Moderating variable: student age (might impact how effective technology is for different students)

Mediating variable: teacher training (might explain how technology leads to improvements in learning outcomes)

Control variable: student learning style

• Conceptual versus theoretical frameworks

Although they sound similar, conceptual and theoretical frameworks have different goals and are used in different contexts. Understanding which to use will help researchers craft better studies.

Conceptual frameworks describe a broad overview of the subject and outline key concepts, variables, and the relationships between them. They provide structure to studies that are more exploratory in nature, where the relationships between the variables are still being established. They are particularly helpful in studies that are complex or interdisciplinary because they help researchers better organize the factors involved in the study.

Theoretical frameworks, on the other hand, are used when the research question is more clearly defined and there’s an existing body of work to draw upon. They define the relationships between the variables and help researchers predict outcomes. They are particularly helpful when researchers want to refine the existing body of knowledge rather than establish it.

Get started today

Go from raw data to valuable insights with a flexible research platform

Editor’s picks

Last updated: 21 December 2023

Last updated: 16 December 2023

Last updated: 6 October 2023

Last updated: 5 March 2024

Last updated: 25 November 2023

Last updated: 15 February 2024

Last updated: 11 March 2024

Last updated: 12 December 2023

Last updated: 6 March 2024

Last updated: 10 April 2023

Last updated: 20 December 2023

Latest articles

Related topics, log in or sign up.

Get started for free

What is a Conceptual Framework?

A conceptual framework sets forth the standards to define a research question and find appropriate, meaningful answers for the same. It connects the theories, assumptions, beliefs, and concepts behind your research and presents them in a pictorial, graphical, or narrative format.

Updated on August 28, 2023

What are frameworks in research?

Both theoretical and conceptual frameworks have a significant role in research.  Frameworks are essential to bridge the gaps in research. They aid in clearly setting the goals, priorities, relationship between variables. Frameworks in research particularly help in chalking clear process details.

Theoretical frameworks largely work at the time when a theoretical roadmap has been laid about a certain topic and the research being undertaken by the researcher, carefully analyzes it, and works on similar lines to attain successful results. 

It varies from a conceptual framework in terms of the preliminary work required to construct it. Though a conceptual framework is part of the theoretical framework in a larger sense, yet there are variations between them.

The following sections delve deeper into the characteristics of conceptual frameworks. This article will provide insight into constructing a concise, complete, and research-friendly conceptual framework for your project.

Definition of a conceptual framework

True research begins with setting empirical goals. Goals aid in presenting successful answers to the research questions at hand. It delineates a process wherein different aspects of the research are reflected upon, and coherence is established among them. 

A conceptual framework is an underrated methodological approach that should be paid attention to before embarking on a research journey in any field, be it science, finance, history, psychology, etc. 

A conceptual framework sets forth the standards to define a research question and find appropriate, meaningful answers for the same. It connects the theories, assumptions, beliefs, and concepts behind your research and presents them in a pictorial, graphical, or narrative format. Your conceptual framework establishes a link between the dependent and independent variables, factors, and other ideologies affecting the structure of your research.

A critical facet a conceptual framework unveils is the relationship the researchers have with their research. It closely highlights the factors that play an instrumental role in decision-making, variable selection, data collection, assessment of results, and formulation of new theories.

Consequently, if you, the researcher, are at the forefront of your research battlefield, your conceptual framework is the most powerful arsenal in your pocket.

What should be included in a conceptual framework?

A conceptual framework includes the key process parameters, defining variables, and cause-and-effect relationships. To add to this, the primary focus while developing a conceptual framework should remain on the quality of questions being raised and addressed through the framework. This will not only ease the process of initiation, but also enable you to draw meaningful conclusions from the same. 

A practical and advantageous approach involves selecting models and analyzing literature that is unconventional and not directly related to the topic. This helps the researcher design an illustrative framework that is multidisciplinary and simultaneously looks at a diverse range of phenomena. It also emboldens the roots of exploratory research. 

Fig. 1: Components of a conceptual framework

How to make a conceptual framework

The successful design of a conceptual framework includes:

• Selecting the appropriate research questions
• Defining the process variables (dependent, independent, and others)
• Determining the cause-and-effect relationships

This analytical tool begins with defining the most suitable set of questions that the research wishes to answer upon its conclusion. Following this, the different variety of variables is categorized. Lastly, the collected data is subjected to rigorous data analysis. Final results are compiled to establish links between the variables. 

The variables drawn inside frames impact the overall quality of the research. If the framework involves arrows, it suggests correlational linkages among the variables. Lines, on the other hand, suggest that no significant correlation exists among them. Henceforth, the utilization of lines and arrows should be done taking into cognizance the meaning they both imply.

Example of a conceptual framework

To provide an idea about a conceptual framework, let’s examine the example of drug development research. 

Say a new drug moiety A has to be launched in the market. For that, the baseline research begins with selecting the appropriate drug molecule. This is important because it:

• Provides the data for molecular docking studies to identify suitable target proteins
• Performs in vitro (a process taking place outside a living organism) and in vivo (a process taking place inside a living organism) analyzes

This assists in the screening of the molecules and a final selection leading to the most suitable target molecule. In this case, the choice of the drug molecule is an independent variable whereas, all the others, targets from molecular docking studies, and results from in vitro and in vivo analyses are dependent variables.

The outcomes revealed by the studies might be coherent or incoherent with the literature. In any case, an accurately designed conceptual framework will efficiently establish the cause-and-effect relationship and explain both perspectives satisfactorily.

If A has been chosen to be launched in the market, the conceptual framework will point towards the factors that have led to its selection. If A does not make it to the market, the key elements which did not work in its favor can be pinpointed by an accurate analysis of the conceptual framework.

Fig. 2: Concise example of a conceptual framework

Important takeaways

While conceptual frameworks are a great way of designing the research protocol, they might consist of some unforeseen loopholes. A review of the literature can sometimes provide a false impression of the collection of work done worldwide while in actuality, there might be research that is being undertaken on the same topic but is still under publication or review. Strong conceptual frameworks, therefore, are designed when all these aspects are taken into consideration and the researchers indulge in discussions with others working on similar grounds of research.

Conceptual frameworks may also sometimes lead to collecting and reviewing data that is not so relevant to the current research topic. The researchers must always be on the lookout for studies that are highly relevant to their topic of work and will be of impact if taken into consideration. 

Another common practice associated with conceptual frameworks is their classification as merely descriptive qualitative tools and not actually a concrete build-up of ideas and critically analyzed literature and data which it is, in reality. Ideal conceptual frameworks always bring out their own set of new ideas after analysis of literature rather than simply depending on facts being already reported by other research groups.

So, the next time you set out to construct your conceptual framework or improvise on your previous one, be wary that concepts for your research are ideas that need to be worked upon. They are not simply a collection of literature from the previous research.

Final thoughts

Research is witnessing a boom in the methodical approaches being applied to it nowadays. In contrast to conventional research, researchers today are always looking for better techniques and methods to improve the quality of their research. 

We strongly believe in the ideals of research that are not merely academic, but all-inclusive. We strongly encourage all our readers and researchers to do work that impacts society. Designing strong conceptual frameworks is an integral part of the process. It gives headway for systematic, empirical, and fruitful research.

Vridhi Sachdeva, MPharm

See our "Privacy Policy"

Get an overall assessment of the main focus of your study from AJE

Our Presubmission Review service will provide recommendations on the structure, organization, and the overall presentation of your research manuscript.

The Ultimate Guide to Qualitative Research - Part 1: The Basics

• Introduction and overview
• What is qualitative research?
• What is qualitative data?
• Examples of qualitative data
• Qualitative vs. quantitative research
• Mixed methods
• Qualitative research preparation
• Theoretical perspective
• Theoretical framework
• Literature reviews
• Research question
• Introduction

Understanding conceptual frameworks

Selecting and developing your framework, variables in a conceptual framework.

• Conceptual vs. theoretical framework
• Data collection
• Qualitative research methods
• Focus groups
• Observational research
• Case studies
• Ethnographical research
• Ethical considerations
• Confidentiality and privacy
• Power dynamics
• Reflexivity

Conceptual framework: Definition and theory

Theoretical and conceptual frameworks ultimately go hand in hand, but while there is significant overlap with theoretical perspectives and theoretical frameworks, understanding the essential differences is important when designing your research project.

Let's explore the idea of a conceptual framework, provide a few common examples, and discuss how to choose a framework for your study. Keep in mind that a conceptual framework will differ from a theoretical framework and that we will explore these differences in the next section.

In this section, we'll delve into the intricacies of conceptual frameworks and their role in qualitative research . They are essentially the scaffolding on which you hang your research questions and analysis . They define the concepts that you'll study and articulate the relationships among them.

Developing conceptual frameworks in research

At the most basic level, a conceptual framework is a visual or written product that explains, either graphically or in narrative form, the main things to be studied, the key factors, variables, or constructs, and any presumed relationships among them. It acts as a road map guiding the course of your research, directing what will be studied, and helping to organize and analyze the data.

The purpose of a conceptual framework

A conceptual framework serves multiple functions in a research project. It helps in clarifying the research problem and purpose, assists in refining the research questions, and guides the data collection and analysis process. It's the tool that ties all aspects of the study together, offering a coherent perspective for the researcher and readers to understand the research more holistically.

Relation between theoretical perspectives and conceptual frameworks

Theoretical perspectives offer overarching philosophies and assumptions that guide the research process, while conceptual frameworks are the specific devices that are derived from these perspectives to operationalize the study. If a theoretical perspective is the broad philosophical underpinning, a conceptual framework is a pragmatic approach that puts that philosophy into practice in the context of the study.

For instance, if you're working from a feminist theoretical perspective, your conceptual framework might involve specific constructs like gender roles, power dynamics , and societal norms, as well as the relationships between these constructs. The conceptual framework would be the lens through which you examine and interpret your data, guided by your theoretical perspective.

Critical theory

Critical theory is a theoretical perspective that seeks to confront social, historical, and ideological forces and structures that produce and constrain social problems. The corresponding conceptual framework might focus on constructs like power relations, historical context, and societal structures. For instance, a study on income inequality might have a conceptual framework involving constructs of socioeconomic status, institutional policies, and the distribution of resources.

Feminist theory

Feminist theory emphasizes the societal roles of gender and power relationships. A conceptual framework derived from this theory might involve constructs like gender roles, power dynamics, and societal norms. In a study about gender representation in media, a feminist conceptual framework could involve constructs such as stereotyping, representation, and societal expectations of gender.

Design your study with ATLAS.ti

Data analysis starts with a solid study design. Make it happen with ATLAS.ti, starting with a free trial.

Choosing and developing your conceptual framework is a pivotal process in your research design. This framework will help guide your study, inform your methodology , and shape your analysis .

Factors to consider when choosing a framework

Your conceptual framework should be derived from and align with your chosen theoretical perspective , but there are other considerations as well. It should resonate with your research question , problem, or purpose and be applicable to the specific context or population you are studying. You should also consider the feasibility of operationalizing the constructs in your framework.

When selecting a conceptual framework, consider the following questions:

1. How does this framework relate to my research topic? 2. Can I use this framework to effectively address my research question(s)? 3. Does this framework resonate with the population and context I'm studying? 4. Can the constructs in this framework be feasibly operationalized in my study?

Steps in developing a conceptual framework

Developing your conceptual framework involves a few key steps:

1. Identify key constructs: Based on your theoretical perspective and research question(s) , what are the main constructs or variables that you need to explore in your study? 2. Clarify relationships among constructs: How do these constructs relate to each other? Are there presumed causal relationships, correlations, or other types of associations? 3. Define each construct: Clearly define what each construct means in the context of your study. This might also involve operationalizing each construct or defining the indicators you will use to measure or identify each construct. 4. Create a visual representation : It is often extremely helpful to create a visual representation of your conceptual framework to illustrate the constructs and their relationships. Map out the relationships among constructs to develop a holistic understanding of what you want to study.

Remember, your conceptual framework is not set in stone. You can start creating your conceptual framework based on your literature review and your own critical reflections. As you proceed with your study, you might need to refine or adapt your conceptual framework based on what you're learning from your data. Developing a robust framework is an iterative process that requires critical thinking, creativity, and flexibility.

A strong conceptual framework includes variables that refer to the constructs or characteristics that are being studied. They are the building blocks of your research study. It might be helpful to think about how the variables in your conceptual framework could be categorized as independent and dependent variables, which respectively influence and are influenced within the research study.

Independent variables and dependent variables

An independent variable is the characteristic or condition that is manipulated or selected by the researcher to determine its effect on the dependent variable. For example, in a study exploring the impact of classroom size on student engagement, classroom size would be the independent variable.

The dependent variable is the main outcome that the researcher is interested in studying or explaining. In the example given above, student engagement would be the dependent variable, as it's the outcome being observed for any changes in response to the independent variable (classroom size). In essence, defining these variables can help you identify the cause-and-effect relationships in your study. While it might be difficult to know beforehand exactly which variables will be important and how they relate to one another, this is a helpful thought exercise to flesh out potential relationships among variables you may want to study.

Relationships among variables

Within a conceptual framework, the dependent and independent variables are listed in addition to their proposed relationships to each other. The ways in which these variables influence one another form the crux of the propositions or assumptions that guide your research.

In a conceptual framework based on the theoretical perspective of constructivism, for instance, the independent variable might be a teaching method (as constructivists would argue that methods of instruction can shape learning), and the dependent variable could be the depth of student understanding. The proposed relationship between these variables might be that student-centered teaching methods lead to a deeper understanding, which would guide the data collection and analysis such that this proposition could be explored.

However, it is important to note that the terminology of independent and dependent variables is more typical of quantitative research , in which independent and dependent variables are operationalized in hypotheses that will be tested based on pre-established theory. In qualitative research , the relationships between variables are more fluid and open-ended because the focus is often more on understanding the phenomenon as a whole and building a contextualized understanding of the research problem. This can involve including new or unexpected variables and interrelationships that emerge during the study, thus extending previous theory or understanding that didn’t initially predict these relationships.

Thus, in your conceptual framework, rather than solely focusing on identifying independent and dependent variables, consider how various factors interact and influence one another within the context of your study. Your conceptual framework should provide a holistic picture of the complexity of the phenomenon you are studying.

Ready to jumpstart your research with ATLAS.ti?

Conceptualize your research project with our intuitive data analysis interface. Download a free trial today.

The Significance of Conceptual Framework in Research

Craft a strong conceptual framework in research with our comprehensive guide. Learn the essential steps to create an effective framework!

Research is a systematic process of inquiry that involves gathering and analyzing information to answer questions and solve problems. Conducting research is an essential activity in various fields, including business, education, healthcare, and social sciences. In research, a conceptual framework is a critical element that guides the study and helps to organize and interpret the collected data. In this article, we will discuss the definition of a conceptual framework, its purpose and importance in research, and the steps involved in developing a conceptual framework.

What is Conceptual Framework

A conceptual framework is a structure that provides a theoretical or conceptual foundation for research, allowing researchers to examine and analyze complex phenomena. It is a tool that researchers use to guide the research process by defining the key concepts, ideas, and theories that underpin their study. The conceptual framework can help to identify the research questions, the variables that will be studied, and the relationships between them. It can also provide a way to visualize the research problem, clarify the research methodology, and explain the research findings.

Purpose and Importance of a Conceptual Framework in Research

The purpose of a conceptual framework in research.

The purpose of a conceptual framework in research is to provide a clear and concise understanding of the key concepts, variables, relationships, and assumptions that underlie a research study. Specifically, a conceptual framework serves several purposes:

Helps to clarify research questions: A well-developed conceptual framework helps to define the research problem and the specific research questions that the study seeks to answer.

Provides a theoretical basis for the study: The conceptual framework provides a theoretical foundation for the study, drawing on existing theories and concepts to guide the research process.

Guides data collection and analysis: The conceptual framework helps to identify the relevant variables and relationships that need to be studied, and guides the collection and analysis of data.

Ensures research validity and reliability: The conceptual framework helps to ensure that the study is focused, relevant, and valid, and that the data collected is reliable.

Helps to make conclusions and recommendations: The conceptual framework provides a basis for making conclusions and recommendations based on the collected data, contributing to the existing body of knowledge in the field.

The Importance of a Conceptual Framework in Research

Provide a basis for research design: The conceptual framework provides a blueprint for the research study, outlining the key concepts, variables, and relationships between them. This helps researchers to design a study that is logical, structured, and focused.

Guide data collection and analysis: The conceptual framework helps to identify the variables and relationships that will be examined in the study. This helps researchers to collect and analyze data that is relevant to the research question and hypothesis.

Ensure validity and reliability: A well-developed conceptual framework helps to ensure that the research is valid and reliable. It ensures that the research is measuring what it intends to measure and that the results are consistent over time.

Facilitate communication: The conceptual framework provides a common language and understanding for researchers, facilitating communication and collaboration among team members.

Identify gaps in existing knowledge: The conceptual framework helps to identify gaps in existing knowledge and to develop new insights and theories.

A well-developed conceptual framework is crucial to the success of a research study. It provides a clear and logical structure for the study, helps to ensure validity and reliability, and facilitates communication and collaboration among researchers.

Steps to Developing a Conceptual Framework

Developing a conceptual framework involves several steps. These steps are outlined below:

1. Choose a research question

The first step in developing a conceptual framework is to identify the research question. This question should be clear, specific, and relevant to the study. It should be formulated based on a review of the existing literature and the identification of gaps in knowledge or areas where further research is needed. Read our Research Question article to learn more about it. 

2. Identify the main variables

The next step is to identify the main variables that will be studied. These variables should be measurable, observable, and relevant to the research question. The independent variable is the variable that is manipulated or controlled in the study, while the dependent variable is the variable that is measured or observed. The independent variable is usually the cause, while the dependent variable is the effect. Read our Research Variables content to understand it better.

3. Visualize the cause-and-effect relationship

The next step is to visualize the cause-and-effect relationship between the independent and dependent variables. This can be done by creating a diagram or a flowchart that illustrates the relationship between the variables. The diagram or flowchart should clearly show the direction of the relationship, whether it is positive or negative, and the strength of the relationship.

4. Identify other influencing variables

The researcher should also identify other variables that may influence the relationship between the main variables. These variables can be included in the conceptual framework, they are known as confounding variables and should be identified and controlled in the study.

5. Include moderating and mediating variables

Moderating and mediating variables should be included in the conceptual framework if they are relevant to the study. Moderating variables affect the strength or direction of the relationship between the main variables while mediating variables explain the relationship between the main variables.

6. Consider control variables

Control variables are variables that are held constant in the study to ensure that the results are valid and reliable. These variables should be included in the conceptual framework to ensure that the study is well-controlled.

7. Revise and refine the conceptual framework

Once the conceptual framework has been developed, the researcher should revise and refine it to ensure that it is clear, concise, and comprehensive. The conceptual framework should be reviewed to ensure that it accurately represents the research question and the variables involved in the study.

Moderating Variables

Moderating variables are variables that can modify or change the strength or direction of the relationship between the independent and dependent variables. These variables can be included in the conceptual framework to help explain the results of the study. For example, in a study on the effects of exercise on weight loss, age, and gender may be moderating variables that can affect the strength of the relationship between exercise and weight loss.

Mediating Variables

Mediating variables are variables that help to explain the relationship between the independent and dependent variables. These variables may be included in the conceptual framework to help identify the mechanisms through which the independent variable affects the dependent variable. For example, in a study on the effects of exercise on weight loss, metabolism, and calorie intake may be mediating variables that help to explain how exercise affects weight loss.

Moderator vs Mediator

It is essential to understand the difference between a moderator and a mediator in research. Here is a table that highlights the differences between moderators and mediators in a theoretical framework:

Control Variables

Control variables are factors that are held constant or unchanged in a study or experiment. In a conceptual framework, control variables refer to the variables that are kept constant or held fixed during the study to ensure that the effect of other independent variables on the dependent variable is not confounded or influenced by any other factor.  For example, in a study on the effects of exercise on weight loss, the type of exercise, duration of exercise, and frequency of exercise may be control variables that are held constant to ensure that the results are not affected by these factors.

The Final Analysis

A conceptual framework is a critical element in research that provides a theoretical basis for the study and guides the research process. Developing a conceptual framework involves several steps, including choosing a research question, selecting independent and dependent variables, visualizing cause-and-effect relationships, identifying other influencing variables, including moderating and mediating variables, and controlling variables. It also provides a basis for making conclusions and recommendations based on the collected data. Researchers should pay close attention to developing a robust conceptual framework to ensure that their research is of high quality and contributes to existing knowledge.

Beautiful templates of infographics for every subject

Mind the Graph offers beautiful and easy-to-use templates of infographics for every subject to help scientists and researchers communicate their work effectively. Infographics are an effective tool for presenting complex scientific data in a visual and engaging way, and the platform provides researchers with the means to create them quickly and easily. 

Subscribe to our newsletter

Exclusive high quality content about effective visual communication in science.

Content tags

Conceptual Framework - Meaning, Importance and How to Write it

Ideally a concept is an abstract idea which forms a basis for learning or argument. In this article, it is a part of the research process where ideas on the subject topic are studied. It is also an analytical tool used for comprehensive understanding of the subject topic for the readers of a research work.

Why do we use conceptual frameworks in research papers?

A conceptual framework is used in a research paper to explain the key concepts or variables and the relationships between them that need to be studied. Simply put, conceptual framework is the way ideas are organised to achieve a research project's purpose and explanation is the most common method employed.

While a conceptual framework means a researcher's perception about the research problem, it is still an arranged and self-explanatory method drafted for the readers.

In this article, we will examine:

• the process of conceptual framework
• the types of conceptual framework
• the components of a good conceptual framework
• the guidelines to writing a good conceptual framework

Process of Creating a Conceptual Framework.

Firstly, it is worthy to note that a conceptual framework is a structure. The researcher uses that structure to best explain the natural progression of the phenomenon to be studied ( Camp, 2001 ). It is linked with the concepts, empirical research and important theories used in promoting and systemising the knowledge gathered by the researcher in the course of the study. The process of conceptual framework includes;

• Choose your topic: You have to decide on what will be your research topic. This should be based on your interest and available resources.
• Do a literature review: Visit relevant and updated researches on similar  topics to learn past used conceptual frameworks.
• Earmark the important variables (dependent and independent variables) in your study then use it to generate your conceptual framework.
• Expand your conceptual framework by identifying other variables (mediator, moderator, control variables) that might influence the relationship between your independent and dependent variables.

NB: Conceptual framework includes one or more formal theories (in part or whole) as well as other concepts and empirical findings from the literature. It is used to show relationships among these ideas and how they relate to the research study.

Having gone through the  process of writing a conceptual framework, the types may interest you. There are various types of conceptual framework employed by researchers depending on their choice and the design of study. They are listed below.

The Types of Conceptual Frameworks are:

• Visual representation
• Mathematical description

Taxonomy :  This is a verbal description which categorises phenomena into classes. Relationships are evident inasmuch as those items within a class are alike; but the relationships among the classes are either weak or nonexistent. This type of conceptual framework doesn’t show relationships between classes.

The scope of the phenomena described may be narrow, but it is often broad. Evidence for the phenomena may be a result of direct experience, or developed from, logical reasoning, or developed empirically. Thus the source may be described as lacking rigor from a scientific viewpoint. Examples of taxonomies would include Barrett's (1968) Taxonomy of Comprehension, the descriptions of the reading process of. Fries (1962) or Lefevre (1964), and the lists of reading objectives often found in curriculum guides and basal reader guidebooks.

Visual Representation : This type of conceptual framework provides a picture of the phenomena, it shows that relationships between classes exist without showing the extent of the relationship. Relationships are shown between classes, whereas in the taxonomy no such relationships are usually  made. The phenomena presented may be as broad as the total reading situation or as narrow as a single grapheme-phoneme correspondence (GPC). The evidence must be at least logical and may have empirical support. It may come from authority opinion or research. From a scientific viewpoint evidence may or may not be rigorous. Examples of visual representations include the work of Gray (1960) and Robinson (1966) illustrating the major aspects of reading; the Goodman (1970) diagram of the reading process; and the work of Smith and Carrigan (1959).

Mathematical Description : This is a type of conceptual framework in which the phenomena can be expressed in some type of mathematical equation, although verbal description and pictorial representation are also possible. The relationships between phenomena are quantified with specific weights given to each; which clearly differentiates this type of conceptual framework from the visual representation which only shows that a relationship exists, but not the degree; and the taxonomy which may not show any relationship between the classes presented. The phenomena represented can probably be described as narrow in respect to reading; but this may change.

In this type, empirical evidence from research is required; but logical explanation may not be required since such frameworks may only represent what is, rather than why. Mathematical descriptions tend to be narrow in scope because only evidence that can be empirically gathered is included. An example of this type of conceptual framework is the work of Holmes (1960, 1965) and Singer (1965).

Note: There is no specific demarcation among the three types of conceptual frameworks. A mathematical description may be visually represented or verbally described. Likewise, a visual representation may be described verbally; and a picture of a taxonomy may be drawn although the relationship among the various classes would not be clearly evident. A taxonomy or visual representation could eventually become a mathematical description if the appropriate empirical evidence was gathered and analysed. It should not be assumed that one type of conceptual framework is inherently superior to another.

More Advanced Types of Conceptual Framework includes:

• Working hypothesis – exploration or exploratory research.
• Pillar questions – exploration or exploratory research.
• Descriptive categories – description or descriptive research.
• Practical ideal type – analysis.
• Models of operations research – decision making.
• Formal hypothesis – explanation and prediction.

However, in qualitative research, conceptual framework can be developed based on the research problem, objective and questions. The main goal of the conceptual framework is to illustrate your research approach in some pictorial or text form to ease reader's understanding. Generally, the type employed is usually picked in resonance with the research topic itself, a conceptual framework should be constructed before collecting data and this is done in chapter two.

Components of a Conceptual Framework.

• Definition of the topic.
• Qualitative characteristics and useful information on the topic.
• The elements of the topic
• Components of the topic.
• Presentation and closure.

Guidelines to Writing a Good Conceptual Framework.

• Select a topic for your research and carry out a literature review.
• Understand what research has already been carried out on the subject matter.
• Look for the specific variables explained in the literature and examine the relationship between them.
• Fill in the gap in knowledge.
• Create your conceptual framework; it can be in the form of a flowchart, mind map or concept map and explain thereafter.

[1] Camp, W. G. (2001). Formulating and Evaluating Theoretical Frameworks for Career and Technical Education Research. Journal of Vocational Educational Research, 26 (1), 27-39.

[2] Robert E (1970) A Schema for the Classification of Conceptual Frameworks Involving Reading . Journal of Reading Behavior, Vol. 3, No. 2, Spring, 16-18

• Skip to main content
• Skip to primary sidebar
• Skip to footer
• QuestionPro

• Solutions Industries Gaming Automotive Sports and events Education Government Travel & Hospitality Financial Services Healthcare Cannabis Technology Use Case NPS+ Communities Audience Contactless surveys Mobile LivePolls Member Experience GDPR Positive People Science 360 Feedback Surveys
• Resources Blog eBooks Survey Templates Case Studies Training Help center

Home Market Research

Conceptual Research: Definition, Framework, Example and Advantages

Conceptual Research: Definition

Conceptual research is defined as a methodology wherein research is conducted by observing and analyzing already present information on a given topic. Conceptual research doesn’t involve conducting any practical experiments. It is related to abstract concepts or ideas. Philosophers have long used conceptual research to develop new theories or interpret existing theories in a different light.

For example, Copernicus used conceptual research to come up with the concepts of stellar constellations based on his observations of the universe. Down the line, Galileo simplified Copernicus’s research by making his own conceptual observations which gave rise to more experimental research and confirmed the predictions made at that time.

The most famous example of conceptual research is Sir Issac Newton. He observed his surroundings to conceptualize and develop theories about gravitation and motion.

Einstein is widely known and appreciated for his work on conceptual research. Although his theories were based on conceptual observations, Einstein also proposed experiments to come up with theories to test the conceptual research.

Nowadays, conceptual research is used to answer business questions and solve real-world problems. Researchers use analytical research tools called conceptual frameworks to make conceptual distinctions and organize ideas required for research purposes.

Conceptual Research Framework

Conceptual research framework constitutes of a researcher’s combination of previous research and associated work and explains the occurring phenomenon. It systematically explains the actions needed in the course of the research study based on the knowledge obtained from other ongoing research and other researchers’ points of view on the subject matter.

Here is a stepwise guide on how to create the conceptual research framework:

01. Choose the topic for research

Before you start working on collecting any research material, you should have decided on your topic for research. It is important that the topic is selected beforehand and should be within your field of specialization.

02. Collect relevant literature

Once you have narrowed down a topic, it is time to collect relevant information about it. This is an important step, and much of your research is dependent on this particular step, as conceptual research is mostly based on information obtained from previous research. Here collecting relevant literature and information is the key to successfully completing research.

The material that you should preferably use is scientific journals , research papers published by well-known scientists , and similar material. There is a lot of information available on the internet and in public libraries as well. All the information that you find on the internet may not be relevant or true. So before you use the information, make sure you verify it.  

03. Identify specific variables

Identify the specific variables that are related to the research study you want to conduct. These variables can give your research a new scope and can also help you identify how these can be related to your research design . For example, consider hypothetically you want to conduct research about the occurrence of cancer in married women. Here the two variables that you will be concentrating on are married women and cancer.

While collecting relevant literature, you understand that the spread of cancer is more aggressive in married women who are beyond 40 years of age. Here there is a third variable which is age, and this is a relevant variable that can affect the end result of your research.  

04. Generate the framework

In this step, you start building the required framework using the mix of variables from the scientific articles and other relevant materials. The research problem statement in your research becomes the research framework. Your attempt to start answering the question becomes the basis of your research study. The study is carried out to reduce the knowledge gap and make available more relevant and correct information.

Example of Conceptual Research Framework

Thesis statement/ Purpose of research: Chronic exposure to sunlight can lead to precancerous (actinic keratosis), cancerous (basal cell carcinoma, squamous cell carcinoma, and melanoma), and even skin lesions (caused by loss of skin’s immune function) in women over 40 years of age.

The study claims that constant exposure to sunlight can cause the precancerous condition and can eventually lead to cancer and other skin abnormalities. Those affected by these experience symptoms like fatigue, fine or coarse wrinkles, discoloration of the skin, freckles, and a burning sensation in the more exposed areas.

Note that in this study, there are two variables associated- cancer and women over 40 years in the African subcontinent. But one is a dependent variable (women over 40 years, in the African subcontinent), and the other is an independent variable (cancer). Cumulative exposure to the sun till the age of 18 years can lead to symptoms similar to skin cancer. If this is not taken care of, there are chances that cancer can spread entirely.

Assuming that the other factors are constant during the research period, it will be possible to correlate the two variables and thus confirm that, indeed, chronic exposure to sunlight causes cancer in women over the age of 40 in the African subcontinent. Further, correlational research can verify this association further.

Advantages of Conceptual Research

1. Conceptual research mainly focuses on the concept of the research or the theory that explains a phenomenon. What causes the phenomenon, what are its building blocks, and so on? It’s research based on pen and paper.

2. This type of research heavily relies on previously conducted studies; no form of experiment is conducted, which saves time, effort, and resources. More relevant information can be generated by conducting conceptual research.

3. Conceptual research is considered the most convenient form of research. In this type of research, if the conceptual framework is ready, only relevant information and literature need to be sorted.

QuestionPro for Conceptual Research

QuestionPro offers readily available conceptual frameworks. These frameworks can be used to research consumer trust, customer satisfaction (CSAT) , product evaluations, etc. You can select from a wide range of templates question types, and examples curated by expert researchers.

We also help you decide which conceptual framework might be best suited for your specific situation.

FREE TRIAL         LEARN MORE

MORE LIKE THIS

The Power of AI in Customer Experience — Tuesday CX Thoughts

Apr 16, 2024

Employee Lifecycle Management Software: Top of 2024

Apr 15, 2024

Top 15 Sentiment Analysis Software That Should Be on Your List

Top 13 A/B Testing Software for Optimizing Your Website

Apr 12, 2024

Other categories

• Academic Research
• Artificial Intelligence
• Assessments
• Brand Awareness
• Case Studies
• Communities
• Consumer Insights
• Customer effort score
• Customer Engagement
• Customer Experience
• Customer Loyalty
• Customer Research
• Customer Satisfaction
• Employee Benefits
• Employee Engagement
• Employee Retention
• Friday Five
• General Data Protection Regulation
• Insights Hub
• Life@QuestionPro
• Market Research
• Mobile diaries
• Mobile Surveys
• New Features
• Online Communities
• Question Types
• Questionnaire
• QuestionPro Products
• Release Notes
• Research Tools and Apps
• Revenue at Risk
• Survey Templates
• Training Tips
• Uncategorized
• Video Learning Series
• What’s Coming Up
• Workforce Intelligence

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Methodology
• What Is a Conceptual Framework? | Tips & Examples

What Is a Conceptual Framework? | Tips & Examples

Published on 4 May 2022 by Bas Swaen and Tegan George. Revised on 18 March 2024.

A conceptual framework illustrates the expected relationship between your variables. It defines the relevant objectives for your research process and maps out how they come together to draw coherent conclusions.

Keep reading for a step-by-step guide to help you construct your own conceptual framework.

Table of contents

Developing a conceptual framework in research, step 1: choose your research question, step 2: select your independent and dependent variables, step 3: visualise your cause-and-effect relationship, step 4: identify other influencing variables, frequently asked questions about conceptual models.

A conceptual framework is a representation of the relationship you expect to see between your variables, or the characteristics or properties that you want to study.

Conceptual frameworks can be written or visual and are generally developed based on a literature review of existing studies about your topic.

Your research question guides your work by determining exactly what you want to find out, giving your research process a clear focus.

However, before you start collecting your data, consider constructing a conceptual framework. This will help you map out which variables you will measure and how you expect them to relate to one another.

In order to move forward with your research question and test a cause-and-effect relationship, you must first identify at least two key variables: your independent and dependent variables .

• The expected cause, ‘hours of study’, is the independent variable (the predictor, or explanatory variable)
• The expected effect, ‘exam score’, is the dependent variable (the response, or outcome variable).

Note that causal relationships often involve several independent variables that affect the dependent variable. For the purpose of this example, we’ll work with just one independent variable (‘hours of study’).

Now that you’ve figured out your research question and variables, the first step in designing your conceptual framework is visualising your expected cause-and-effect relationship.

It’s crucial to identify other variables that can influence the relationship between your independent and dependent variables early in your research process.

Some common variables to include are moderating, mediating, and control variables.

Moderating variables

Moderating variable (or moderators) alter the effect that an independent variable has on a dependent variable. In other words, moderators change the ‘effect’ component of the cause-and-effect relationship.

Let’s add the moderator ‘IQ’. Here, a student’s IQ level can change the effect that the variable ‘hours of study’ has on the exam score. The higher the IQ, the fewer hours of study are needed to do well on the exam.

Let’s take a look at how this might work. The graph below shows how the number of hours spent studying affects exam score. As expected, the more hours you study, the better your results. Here, a student who studies for 20 hours will get a perfect score.

But the graph looks different when we add our ‘IQ’ moderator of 120. A student with this IQ will achieve a perfect score after just 15 hours of study.

Below, the value of the ‘IQ’ moderator has been increased to 150. A student with this IQ will only need to invest five hours of study in order to get a perfect score.

Here, we see that a moderating variable does indeed change the cause-and-effect relationship between two variables.

Mediating variables

Now we’ll expand the framework by adding a mediating variable . Mediating variables link the independent and dependent variables, allowing the relationship between them to be better explained.

Here’s how the conceptual framework might look if a mediator variable were involved:

In this case, the mediator helps explain why studying more hours leads to a higher exam score. The more hours a student studies, the more practice problems they will complete; the more practice problems completed, the higher the student’s exam score will be.

Moderator vs mediator

It’s important not to confuse moderating and mediating variables. To remember the difference, you can think of them in relation to the independent variable:

• A moderating variable is not affected by the independent variable, even though it affects the dependent variable. For example, no matter how many hours you study (the independent variable), your IQ will not get higher.
• A mediating variable is affected by the independent variable. In turn, it also affects the dependent variable. Therefore, it links the two variables and helps explain the relationship between them.

Control variables

Lastly,  control variables must also be taken into account. These are variables that are held constant so that they don’t interfere with the results. Even though you aren’t interested in measuring them for your study, it’s crucial to be aware of as many of them as you can be.

A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship.

No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both.

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

A control variable is any variable that’s held constant in a research study. It’s not a variable of interest in the study, but it’s controlled because it could influence the outcomes.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

Swaen, B. & George, T. (2024, March 18). What Is a Conceptual Framework? | Tips & Examples. Scribbr. Retrieved 15 April 2024, from https://www.scribbr.co.uk/research-methods/conceptual-frameworks/

Is this article helpful?

Other students also liked

Mediator vs moderator variables | differences & examples, independent vs dependent variables | definition & examples, what are control variables | definition & examples.

• Section 1: Home
• Narrowing Your Topic
• Problem Statement
• Purpose Statement

Defining The Conceptual Framework

Making a conceptual framework, conceptual framework for dmft students, conceptual framework guide, example frameworks, additional framework resources.

• Student Experience Feedback Buttons
• Avoiding Common Mistakes
• Synthesis and Analysis in Writing Support This link opens in a new window
• Qualitative Research Questions This link opens in a new window
• Quantitative Research Questions This link opens in a new window
• Qualitative & Quantitative Research Support with the ASC This link opens in a new window
• Library Research Consultations This link opens in a new window
• Library Guide: Research Process This link opens in a new window
• ASC Guide: Outlining and Annotating This link opens in a new window
• Library Guide: Organizing Research & Citations This link opens in a new window
• Library Guide: RefWorks This link opens in a new window
• Library Guide: Copyright Information This link opens in a new window

What is it?

• The researcher’s understanding/hypothesis/exploration of either an existing framework/model or how existing concepts come together to inform a particular problem. Shows the reader how different elements come together to facilitate research and a clear understanding of results.
• Informs the research questions/methodology (problem statement drives framework drives RQs drives methodology)
• A tool (linked concepts) to help facilitate the understanding of the relationship among concepts or variables in relation to the real-world. Each concept is linked to frame the project in question.
• Falls inside of a larger theoretical framework (theoretical framework = explains the why and how of a particular phenomenon within a particular body of literature).
• Can be a graphic or a narrative – but should always be explained and cited
• Can be made up of theories and concepts

What does it do?

• Explains or predicts the way key concepts/variables will come together to inform the problem/phenomenon
• Gives the study direction/parameters
• Helps the researcher organize ideas and clarify concepts
• Introduces your research and how it will advance your field of practice. A conceptual framework should include concepts applicable to the field of study. These can be in the field or neighboring fields – as long as important details are captured and the framework is relevant to the problem. (alignment)

What should be in it?

• Variables, concepts, theories, and/or parts of other existing frameworks

How to make a conceptual framework

• With a topic in mind, go to the body of literature and start identifying the key concepts used by other studies. Figure out what’s been done by other researchers, and what needs to be done (either find a specific call to action outlined in the literature or make sure your proposed problem has yet to be studied in your specific setting). Use what you find needs to be done to either support a pre-identified problem or craft a general problem for study. Only rely on scholarly sources for this part of your research.
• Begin to pull out variables, concepts, theories, and existing frameworks explained in the relevant literature.
• If you’re building a framework, start thinking about how some of those variables, concepts, theories, and facets of existing frameworks come together to shape your problem. The problem could be a situational condition that requires a scholar-practitioner approach, the result of a practical need, or an opportunity to further an applicational study, project, or research. Remember, if the answer to your specific problem exists, you don’t need to conduct the study.
• The actionable research you’d like to conduct will help shape what you include in your framework. Sketch the flow of your Applied Doctoral Project from start to finish and decide which variables are truly the best fit for your research.
• Create a graphic representation of your framework (this part is optional, but often helps readers understand the flow of your research) Even if you do a graphic, first write out how the variables could influence your Applied Doctoral Project and introduce your methodology. Remember to use APA formatting in separating the sections of your framework to create a clear understanding of the framework for your reader.
• As you move through your study, you may need to revise your framework.
• Note for qualitative/quantitative research: If doing qualitative, make sure your framework doesn’t include arrow lines, which could imply causal or correlational linkages.
• Conceptural and Theoretical Framework for DMFT Students This document is specific to DMFT students working on a conceptual or theoretical framework for their applied project.
• Conceptual Framework Guide Use this guide to determine the guiding framework for your applied dissertation research.

Let’s say I’ve just taken a job as manager of a failing restaurant. Throughout first week, I notice the few customers they have are leaving unsatisfied. I need to figure out why and turn the establishment into a thriving restaurant. I get permission from the owner to do a study to figure out exactly what we need to do to raise levels of customer satisfaction. Since I have a specific problem and want to make sure my research produces valid results, I go to the literature to find out what others are finding about customer satisfaction in the food service industry. This particular restaurant is vegan focused – and my search of the literature doesn’t say anything specific about how to increase customer service in a vegan atmosphere, so I know this research needs to be done.

I find out there are different types of satisfaction across other genres of the food service industry, and the one I’m interested in is cumulative customer satisfaction. I then decide based on what I’m seeing in the literature that my definition of customer satisfaction is the way perception, evaluation, and psychological reaction to perception and evaluation of both tangible and intangible elements of the dining experience come together to inform customer expectations. Essentially, customer expectations inform customer satisfaction.

I then find across the literature many variables could be significant in determining customer satisfaction. Because the following keep appearing, they are the ones I choose to include in my framework: price, service, branding (branched out to include physical environment and promotion), and taste. I also learn by reading the literature, satisfaction can vary between genders – so I want to make sure to also collect demographic information in my survey. Gender, age, profession, and number of children are a few demographic variables I understand would be helpful to include based on my extensive literature review.

Note: this is a quantitative study. I’m including all variables in this study, and the variables I am testing are my independent variables. Here I’m working to see how each of the independent variables influences (or not) my dependent variable, customer satisfaction. If you are interested in qualitative study, read on for an example of how to make the same framework qualitative in nature.

Also note: when you create your framework, you’ll need to cite each facet of your framework. Tell the reader where you got everything you’re including. Not only is it in compliance with APA formatting, but also it raises your credibility as a researcher. Once you’ve built the narrative around your framework, you may also want to create a visual for your reader.

See below for one example of how to illustrate your framework:

If you’re interested in a qualitative study, be sure to omit arrows and other notations inferring statistical analysis. The only time it would be inappropriate to include a framework in qualitative study is in a grounded theory study, which is not something you’ll do in an applied doctoral study.

A visual example of a qualitative framework is below:

Some additional helpful resources in constructing a conceptual framework for study:

• Problem Statement, Conceptual Framework, and Research Question. McGaghie, W. C.; Bordage, G.; and J. A. Shea (2001). Problem Statement, Conceptual Framework, and Research Question. Retrieved on January 5, 2015 from http://goo.gl/qLIUFg
• Building a Conceptual Framework: Philosophy, Definitions, and Procedure
• https://www.scribbr.com/dissertation/conceptual-framework/
• https://www.projectguru.in/developing-conceptual-framework-in-a-research-paper/

Conceptual Framework Research

A conceptual framework is a synthetization of interrelated components and variables which help in solving a real-world problem. It is the final lens used for viewing the deductive resolution of an identified issue (Imenda, 2014). The development of a conceptual framework begins with a deductive assumption that a problem exists, and the application of processes, procedures, functional approach, models, or theory may be used for problem resolution (Zackoff et al., 2019). The application of theory in traditional theoretical research is to understand, explain, and predict phenomena (Swanson, 2013). In applied research the application of theory in problem solving focuses on how theory in conjunction with practice (applied action) and procedures (functional approach) frames vision, thinking, and action towards problem resolution. The inclusion of theory in a conceptual framework is not focused on validation or devaluation of applied theories. A concise way of viewing the conceptual framework is a list of understood fact-based conditions that presents the researcher’s prescribed thinking for solving the identified problem. These conditions provide a methodological rationale of interrelated ideas and approaches for beginning, executing, and defining the outcome of problem resolution efforts (Leshem & Trafford, 2007).

The term conceptual framework and theoretical framework are often and erroneously used interchangeably (Grant & Osanloo, 2014). Just as with traditional research, a theory does not or cannot be expected to explain all phenomenal conditions, a conceptual framework is not a random identification of disparate ideas meant to incase a problem. Instead it is a means of identifying and constructing for the researcher and reader alike an epistemological mindset and a functional worldview approach to the identified problem.

Grant, C., & Osanloo, A. (2014). Understanding, Selecting, and Integrating a Theoretical Framework in Dissertation Research: Creating the Blueprint for Your “House. ” Administrative Issues Journal: Connecting Education, Practice, and Research, 4(2), 12–26

Imenda, S. (2014). Is There a Conceptual Difference between Theoretical and Conceptual Frameworks? Sosyal Bilimler Dergisi/Journal of Social Sciences, 38(2), 185.

Leshem, S., & Trafford, V. (2007). Overlooking the conceptual framework. Innovations in Education & Teaching International, 44(1), 93–105. https://doi-org.proxy1.ncu.edu/10.1080/14703290601081407

Swanson, R. (2013). Theory building in applied disciplines . San Francisco: Berrett-Koehler Publishers.

Zackoff, M. W., Real, F. J., Klein, M. D., Abramson, E. L., Li, S.-T. T., & Gusic, M. E. (2019). Enhancing Educational Scholarship Through Conceptual Frameworks: A Challenge and Roadmap for Medical Educators . Academic Pediatrics, 19(2), 135–141. https://doi-org.proxy1.ncu.edu/10.1016/j.acap.2018.08.003

Was this resource helpful?

• << Previous: Alignment
• Next: Avoiding Common Mistakes >>
• Last Updated: Jun 21, 2023 12:28 PM
• URL: https://resources.nu.edu/c.php?g=1013602

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• J Patient Cent Res Rev
• v.11(1); Spring 2024
• PMC11000705

Research Frameworks: Critical Components for Reporting Qualitative Health Care Research

Qualitative health care research can provide insights into health care practices that quantitative studies cannot. However, the potential of qualitative research to improve health care is undermined by reporting that does not explain or justify the research questions and design. The vital role of research frameworks for designing and conducting quality research is widely accepted, but despite many articles and books on the topic, confusion persists about what constitutes an adequate underpinning framework, what to call it, and how to use one. This editorial clarifies some of the terminology and reinforces why research frameworks are essential for good-quality reporting of all research, especially qualitative research.

Qualitative research provides valuable insights into health care interactions and decision-making processes – for example, why and how a clinician may ignore prevailing evidence and continue making clinical decisions the way they always have. 1 The perception of qualitative health care research has improved since a 2016 article by Greenhalgh et al. highlighted the higher contributions and citation rates of qualitative research than those of contemporaneous quantitative research. 2 The Greenhalgh et al. article was subsequently supported by an open letter from 76 senior academics spanning 11 countries to the editors of the British Medical Journal . 3 Despite greater recognition and acceptance, qualitative research continues to have an “uneasy relationship with theory,” 4 which contributes to poor reporting.

As an editor for the Journal of Patient-Centered Research and Reviews , as well as Human Resources for Health , I have seen several exemplary qualitative articles with clear and coherent reporting. On the other hand, I have often been concerned by a lack of rigorous reporting, which may reflect and reinforce the outdated perception of qualitative research as the “soft option.” 5 Qualitative research is more than conducting a few semi-structured interviews, transcribing the audio recordings verbatim, coding the transcripts, and developing and reporting themes, including a few quotes. Qualitative research that benefits health care is time-consuming and labor-intensive, requires robust design, and is rooted in theory, along with comprehensive reporting. 6

What Is “Theory”?

So fundamental is theory to qualitative research that I initially toyed with titling this editorial, “ Theory: the missing link in qualitative health care research articles ,” before deeming that focus too broad. As far back as 1967, Merton 6 warned that “the word theory threatens to become meaningless.” While it cannot be overstated that “atheoretical” studies lack the underlying logic that justifies researchers’ design choices, the word theory is so overused that it is difficult to understand what constitutes an adequate theoretical foundation and what to call it.

Theory, as used in the term theoretical foundation , refers to the existing body of knowledge. 7 , 8 The existing body of knowledge consists of more than formal theories , with their explanatory and predictive characteristics, so theory implies more than just theories . Box 1 9 – 12 defines the “building blocks of formal theories.” 9 Theorizing or theory-building starts with concepts at the most concrete, experiential level, becoming progressively more abstract until a higher-level theory is developed that explains the relationships between the building blocks. 9 Grand theories are broad, representing the most abstract level of theorizing. Middle-range and explanatory theories are progressively less abstract, more specific to particular phenomena or cases (middle-range) or variables (explanatory), and testable.

The Building Blocks of Formal Theories 9

The importance of research frameworks.

Researchers may draw on several elements to frame their research. Generally, a framework is regarded as “a set of ideas that you use when you are forming your decisions and judgements” 13 or “a system of rules, ideas, or beliefs that is used to plan or decide something.” 14 Research frameworks may consist of a single formal theory or part thereof, any combination of several theories or relevant constructs from different theories, models (as simplified representations of formal theories), concepts from the literature and researchers’ experiences.

Although Merriam 15 was of the view that every study has a framework, whether explicit or not, there are advantages to using an explicit framework. Research frameworks map “the territory being investigated,” 8 thus helping researchers to be explicit about what informed their research design, from developing research questions and choosing appropriate methods to data analysis and interpretation. Using a framework makes research findings more meaningful 12 and promotes generalizability by situating the study and interpreting data in more general terms than the study itself. 16

Theoretical and Conceptual Frameworks

The variation in how the terms theoretical and conceptual frameworks are used may be confusing. Some researchers refer to only theoretical frameworks 17 , 18 or conceptual frameworks, 19 – 21 while others use the terms interchangeably. 7 Other researchers distinguish between the two. For example, Miles, Huberman & Saldana 8 see theoretical frameworks as based on formal theories and conceptual frameworks derived inductively from locally relevant concepts and variables, although they may include theoretical aspects. Conversely, some researchers believe that theoretical frameworks include formal theories and concepts. 18 Others argue that any differences between the two types of frameworks are semantic and, instead, emphasize using a research framework to provide coherence across the research questions, methods and interpretation of the results, irrespective of what that framework is called.

Like Ravitch and Riggan, 22 I regard conceptual frameworks (CFs) as the broader term. Including researchers’ perspectives and experiences in CFs provides valuable sources of originality. Novel perspectives guard against research repeating what has already been stated. 23 The term theoretical framework (TF) may be appropriate where formal published and identifiable theories or parts of such theories are used. 24 However, existing formal theories alone may not provide the current state of relevant concepts essential to understanding the motivation for and logic underlying a study. Some researchers may argue that relevant concepts may be covered in the literature review, but what is the point of literature reviews and prior findings unless authors connect them to the research questions and design? Indeed, Sutton & Straw 25 exclude literature reviews and lists of prior findings as an adequate foundation for a study, along with individual lists of variables or constructs (even when the constructs are defined), predictions or hypotheses, and diagrams that do not propose relationships. One or more of these aspects could be used in a research framework (eg, in a TF), and the literature review could (and should) focus on the theories or parts of theories (constructs), offer some critique of the theory and point out how they intend to use the theory. This would be more meaningful than merely describing the theory as the “background” to the study, without explicitly stating why and how it is being used. Similarly, a CF may include a discussion of the theories being used (basically, a TF) and a literature review of the current understanding of any relevant concepts that are not regarded as formal theory.

It may be helpful for authors to specify whether they are using a theoretical or a conceptual framework, but more importantly, authors should make explicit how they constructed and used their research framework. Some studies start with research frameworks of one type and end up with another type, 8 , 22 underscoring the need for authors to clarify the type of framework used and how it informed their research. Accepting the sheer complexity surrounding research frameworks and lamenting the difficulty of reducing the confusion around these terms, Box 2 26 – 31 and Box 3 offer examples highlighting the fundamental elements of theoretical and conceptual frameworks while acknowledging that they share a common purpose.

Examples of How Theoretical Frameworks May Be Used

Examples of how conceptual frameworks may be used, misconceptions about qualitative research.

Qualitative research’s “uneasy relationship with theory” 4 may be due to several misconceptions. One possible misconception is that qualitative research aims to build theory and thus does not need theoretical grounding. The reality is that all qualitative research methods, not just Grounded Theory studies focused on theory building, may lead to theory construction. 16 Similarly, all types of qualitative research, including Grounded Theory studies, should be guided by research frameworks. 16

Not using a research framework may also be due to misconceptions that qualitative research aims to understand people’s perspectives and experiences without examining them from a particular theoretical perspective or that theoretical foundations may influence researchers’ interpretations of participants’ meanings. In fact, in the same way that participants’ meanings vary, qualitative researchers’ interpretations (as opposed to descriptions) of participants’ meaning-making will differ. 32 , 33 Research frameworks thus provide a frame of reference for “making sense of the data.” 34

Studies informed by well-defined research frameworks can make a world of difference in alleviating misconceptions. Good qualitative reporting requires research frameworks that make explicit the combination of relevant theories, theoretical constructs and concepts that will permeate every aspect of the research. Irrespective of the term used, research frameworks are critical components of reporting not only qualitative but also all types of research.

Acknowledgments

In memory of Martie Sanders: supervisor, mentor, and colleague. My deepest gratitude for your unfailing support and guidance. I feel your loss.

Conflicts of Interest: None.

Log in using your username and password

• Search More Search for this keyword Advanced search
• Latest content
• Current issue
• Write for Us
• BMJ Journals More You are viewing from: Google Indexer

You are here

• Volume 22, Issue 2
• Integration of a theoretical framework into your research study
• Article Text
• Article info
• Citation Tools
• Rapid Responses
• Article metrics

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

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

Statistics from Altmetric.com

Request permissions.

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

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

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

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

What is a theory?

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

Using a theoretical framework in a research study

Example 1: the big five theoretical framework.

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

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

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

Example 2: the Health Decisions Model

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

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

Example 3: the nursing role effectiveness model

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

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

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

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

Competing interests None declared.

Provenance and peer review Not commissioned; internally peer reviewed.

Patient and public involvement Not required.

Read the full text or download the PDF:

• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

• Theoretical Framework
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

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.

• << Previous: The Research Problem/Question
• Next: 5. The Literature Review >>
• Last Updated: Apr 16, 2024 10:20 AM
• URL: https://libguides.usc.edu/writingguide

• Open access
• Published: 26 April 2022

Definition and conceptualization of the patient-centered care pathway, a proposed integrative framework for consensus: a Concept analysis and systematic review

• Jean-Baptiste Gartner 1 , 2 , 3 , 4 , 5 ,
• Kassim Said Abasse 1 , 2 , 3 , 5 ,
• Frédéric Bergeron 6 ,
• Paolo Landa 3 , 7 ,
• Célia Lemaire 8 &
• André Côté 1 , 2 , 3 , 4 , 5  

BMC Health Services Research volume  22 , Article number:  558 ( 2022 ) Cite this article

7165 Accesses

18 Citations

1 Altmetric

Metrics details

Confusion exists over the definition of the care pathway concept and existing conceptual frameworks contain various inadequacies which have led to implementation difficulties. In the current global context of rapidly changing health care systems, there is great need for a standardized definition and integrative framework that can guide implementation. This study aims to propose an accurate and up-to-date definition of care pathway and an integrative conceptual framework.

An innovative hybrid method combining systematic review, concept analysis and bibliometric analysis was undertaken to summarize qualitative, quantitative, and mixed-method studies. Databases searched were PubMed, Embase and ABI/Inform. Methodological quality of included studies was then assessed.

Forty-four studies met the inclusion criteria. Using concept analysis, we developed a fine-grained understanding, an integrative conceptual framework, and an up-to-date definition of patient-centered care pathway by proposing 28 subcategories grouped into seven attributes. This conceptual framework considers both operational and social realities and supports the improvement and sustainable transformation of clinical, administrative, and organizational practices for the benefit of patients and caregivers, while considering professional experience, organizational constraints, and social dynamics. The proposed attributes of a fluid and effective pathway are (i) the centricity of patients and caregivers, (ii) the positioning of professional actors involved in the care pathway, (iii) the operation management through the care delivery process, (iv) the particularities of coordination structures, (v) the structural context of the system and organizations, (vi) the role of the information system and data management and (vii) the advent of the learning system. Antecedents are presented as key success factors of pathway implementation. By using the consequences and empirical referents, such as outcomes and evidence of care pathway interventions, we went beyond the single theoretical aim, proposing the application of the conceptual framework to healthcare management.

Conclusions

This study has developed an up-to-date definition of patient-centered care pathway and an integrative conceptual framework. Our framework encompasses 28 subcategories grouped into seven attributes that should be considered in complex care pathway intervention. The formulation of these attributes, antecedents as success factors and consequences as potential outcomes, allows the operationalization of this model for any pathway in any context.

Peer Review reports

While having a performant healthcare system is a crucial issue for every country, the health sector operates in silos that need to be challenged. Indeed, many authors have pointed to fragmented care processes as a cause of breakdowns in the continuity of healthcare services [ 1 ], unnecessary waiting times [ 2 , 3 ], flaws in the flow of information between the different episodes [ 4 ] and the realization of exams that may be superfluous [ 5 ]. This fragmentation results in a sub-optimal use of material and financial resources and unsatisfactory team management [ 4 ]. Based on this observation, several repeated calls to improve the quality and performance of healthcare services have been made since 2001 by national and international institutions such as the Institute of Medicine of America (IOM) in 2001 [ 6 ] and 2013 [ 7 ], the National Academies of Sciences, Engineering, Medicine in 2018 [ 8 ] and the World Health Organization (WHO) in 2016 [ 9 ] and 2020 [ 10 ]. These calls have progressively shifted from an injunction to improve quality based on criteria to provide safe, effective, efficient, timely, equitable and patient-centered care [ 6 ], to the development of models for the organization of health care and services that meet the current challenges of effectiveness and efficiency in healthcare systems. The WHO urges member countries to base their quality improvement policies on the entire continuum of care, taking into account at least the criteria of effectiveness, safety, equity, efficiency, integrated care and timeliness [ 11 ]. These calls also emphasize the need to improve care pathways by focusing on outcomes that matter to the patient from a clinical, quality of life and health system experience perspective [ 12 , 13 , 14 , 15 ], rather than on the needs of the production units. This change of perspective leads to the study of the redesign of performance evaluation models by focusing on the needs and expectations of the patient [ 16 , 17 ]. The problem is that there is confusion about the definition and characterization of a care and health service pathway. Indeed, Bergin et al. [ 2 ] identified 37 different definitions of the term care pathway based on a review of the literature. Definitions and characteristics vary across countries and include multiple phases ranging from prevention or screening to cure or palliative care. This confusion has led to wide variability in the outcomes of these interventions, resulting in underutilization of care pathway improvement programs [ 2 ]. Furthermore, such confusion leads to great variability in the analysis and modeling of care pathways. For example, in their scoping review, Khan et al. [ 18 ] showed the great variability that exists among studies of oncology care pathways in both the phases of care represented, and their characteristics. The lack of a common definition and clearly defined criteria leads to a lack of standardization, resulting in an inability to conduct reliable comparative studies of care pathway programs internationally [ 19 ].

The Oxford Concise Medical Dictionary 10th ed. [ 20 ] and the Oxford Dictionary of Nursing 8th ed. [ 21 ] define, in a concise way, care pathway as “a multidisciplinary plan for delivering health and social care to patients with a specific condition or set of symptoms. Such plans are often used for the management of common conditions and are intended to improve patient care by reducing unnecessary deviation from best practice”. The concept of a care pathway is one originally used in the field of Health Operations Management, whose definition was proposed by Vissers and Beech [ 22 ]. However, these definitions seem to be too imprecise and address neither the aim nor the social reality of implementing such pathways. The European Pathway Association (EPA) adopts the more precise definition from the 2007 thesis of Vanhaecht [ 23 ]. However this has not yet led to an international consensus, as confusion over the concepts remains high. Moreover, this definition does not clearly define the antecedents or factors favoring the success of such interventions, the means by which to implement them or the best practices through which to support them; nor does it sufficiently take into account the importance of the patient-centered care and patient-centered services approach. Similarly, the proposed implementation models largely neglected the social reality and the social dynamic of organizations [ 24 ], resulting in major implementation difficulties, as care pathways still being considered as complex interventions [ 25 , 26 ].

However, care pathway programs have recently demonstrated encouraging results in terms of reduced variation in care, improved accessibility, quality, sustainability, and cost effectiveness of care [ 2 ]. The definition we aim to develop through this research is significant and timely, in that it has the potential to guide the ongoing development, implementation, monitoring and evaluation of care pathway programs within the rapidly changing service and system contexts that we are experiencing. For example, the following initial barriers to the systemic and holistic implementation of care pathways have recently been removed. Firstly, limited access to valid and reliable data from multiple organizations [ 27 ] has been offset by a massive investment in Electronic Medical Records [ 28 ]. Secondly, the main difficulties in highlighting the complexity of the referral trajectory [ 29 ], frequently resulting from the clinicians’ perspective, have been overcome by proposing new approaches such as data mining or qualitative methods, focusing on the real care trajectory and the qualitative part of the patients’ experience [ 16 , 17 , 30 ]. Therefore, the evolution of knowledge and information technology and the investment of health systems in data-sharing infrastructure, as well as a definition of the levers of patient engagement and the advent of patient-centered-care and patient-centered services, make it possible to define a powerful model for improving them by placing the patient’s needs and expectations at the center of the care pathway. It is therefore the right time to define a recognized definition and an integrative conceptual framework that meets the demand for sharing knowledge internationally regarding the development, implementation, and evaluation of care pathways.

The concept of patient-centered care is defined as “care provision that is consistent with the values, needs, and desires of patients and is achieved when clinicians involve patients in healthcare discussions and decisions” [ 31 ]. This approach is known to provide benefits by improving health outcomes, patient satisfaction, but also to reducing health costs [ 32 ].

A preliminary search for existing reviews was conducted in Cochrane Database, JBI Database of Systematic Reviews and Implementation Reports and PROSPERO. Care pathways have been the subject of few reviews, but these were limited to a single pathology such as cancer in general [ 33 ], blunt thoracic injury [ 34 ], cardiovascular disease [ 35 ], adolescent idiopathic scoliosis [ 36 ] or for particular pathway phases [ 37 ]. In the end, focusing on a single condition is not entirely consistent with a patient-centered approach to care insofar as patients often have comorbidities. The only review that did not focus on one specific pathology was made in 2006 [ 38 ] and was interested in the concept of clinical pathway. Authors reviewed literature published within 3 years using only one bibliographic database. Therefore, the aim of this article is to propose an accurate and up-to-date definition of care pathway and to develop an integrative conceptual framework for the patient-centered care pathway concept in a holistic operational approach of the concept.

Combining systematic review, concept analysis and bibliometric analysis

To achieve a fine-grained understanding of the concept, we have chosen a hybrid method combining the systematic review, the concept analysis and the bibliometric analysis methodologies. We followed the latest PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) statement for conducting and reporting a systematic review [ 39 ]. However, the systematic review methodology presents some limitations on the qualitative analysis of literature, hence derives our interest to use Concept analysis. Concept analysis [ 40 ] aims specifically to clarify a specific concept including a semantic field linked to a specific theoretical framework. This approach is based on eight steps allowing to: (1) select the concept, (2) determine the aims or purposes of the analysis, (3) identify all uses of the concept, (4) determine the defining attributes, (5) identify a model case, (6) identify additional cases, (7) identify antecedents and consequences and (8) define empirical referents. However, this method does not provide a systematic and rigorous procedure for identifying and selecting relevant literature. Therefore, we decided to combine the strengths of both methods to overcome the limitations of each. In order to make our analysis more robust and to base our inferences, specifically in the comparative analysis of the related concepts, we performed a bibliometric analysis allowing us to link the attributes of each of the concepts to make a comparison.

Information sources and search strategy

We developed a search strategy, in collaboration with a Health Sciences Librarian who specializes in systematic literature review in healthcare, to identify relevant peer-reviewed studies. An initial limited search of MEDLINE and CINAHL was conducted, followed by analysis of the text words containing title and abstract and index terms used to describe the article. This informed the development of a search strategy that was tailored toward each information source. The search strategy was applied to the following databases: PubMed, Embase and ABI/Inform. The complete search strategy is provided in Additional file  1 .

Eligibility criteria

This review considers studies that focus on quantitative and/or qualitative data, with no limitation in terms of methodology. Our search focused on peer-reviewed scientific articles. Therefore, books, doctoral or master’s theses were excluded due to time and resource limitations. In order to guide the selection, we chose the Population, Context, Concept (PCC) mnemonic criteria [ 41 ]. The population considers all types of patients managed by healthcare delivery systems. The context studied is composed of healthcare providers in any geographic area, including all providers of primary, secondary, tertiary, and quaternary care. For the concept, this review focuses on theoretical and empirical studies that contribute to the definition and conceptualization of the different related concepts of care processes at the organizational or system level, such as care pathway, clinical pathway, patient journey and care processes. Quantitative, qualitative and mixed method studies involving a single episode of care limited in time (a one-time treatment) or space (a single hospital service/department) were excluded to the extent that care pathway involves multiple points of interaction over time [ 13 , 42 ] and multiple organizational structures or intra-organizational entities along the care continuum [ 43 ]. In addition, studies with no theoretical or conceptual input were excluded. Finally, there was no language or geographic restrictions applied to the search, and the study period was limited from 1995 to 2020.

These studies were imported into the Covidence® software (version 2020). The team developed screening questions and forms for levels 1 (abstract) and 2 (full text) screening based on the inclusion and exclusion criteria. Two reviewers independently screened the titles and abstracts. In case of disagreement, two senior reviewers decided after analysis and discussion. Review author pairs then screened the full-text articles against inclusion and exclusion criteria. In case of disagreement, the same process as for the title and abstract selection was implemented. Reasons for excluding studies were recorded.

Assessment of methodological quality

Because of the heterogeneity of the methods used in the selected articles, we decided to use a separate appraisal tool for each study type. The following appraisal tools were selected for their clarity, relevance, and because their items covered the most common assessment criteria comparing to other tools:

For qualitative studies: the JBI Qualitative Assessment Research Instrument (QARI) [ 41 ]

For surveys: the Center for Evidence Based Management (CEBMa) Appraisal Questions for a Survey [ 44 ]

For descriptive cross-sectional studies: the Institute for Public Health Sciences 11 questions to help you make sense of descriptive/cross-sectional studies [ 45 ]

For mixed-method: the scoring system for appraising mixed methods research [ 46 ]

No articles were excluded from this systematic review due to the weaknesses of their methodological quality, so as not to exclude valuable information [ 47 ].

Data extraction and analysis

Descriptive numerical summary analysis followed the systematic review guidelines, and the following items were systematically extracted: Reference, Title, First Author country, Case country, Year of publication, Type of publication, Target patient population, Phases of the pathway included, People involved in the modeling process, Study parameters and level of analysis.

Qualitative data were extracted using MaxQDA® software (version 2020) by two independent analysts. The data extraction followed the concept analysis guideline [ 40 ] and the following items were systematically extracted: Variant concept studied, Concept uses, Concept definition, Concept attributes, Antecedents, Consequences and empirical referents. In order to develop a detailed analysis and arrive at a robust theoretical framework, we relied on general inductive analysis [ 48 ], consisting of coding, categorization, linking, integration and modeling. Each step has been validated by at least two senior authors.

A bibliometric analysis was performed with the complete texts of the 44 selected studies using Vosviewer® software (version 2020).

The systematic review was reported following the latest PRISMA statement for conducting and reporting a systematic review [ 39 ] and mobilized the PRISMA 2020 checklist (see Additional file  2 ).

The interrogation of the three databases resulted in 15,281 articles. Figure  1 details the selection process following the PRISMA 2020 statement [ 39 ]. After deleting the duplicates, 15,072 records were reviewed but only 44 publications ultimately met the inclusion and exclusion criteria.

PRISMA 2020 flow diagram of the systematic review process

Description and methodological quality appraisal of studies

A summary table containing a brief description of selected studies and their evaluation results for methodological quality is presented in Table  1 . Quality appraisal of selected studies is presented in Additional file  3 .

Published articles, describing care pathways as multiple points, in time and space, of patient interaction appeared in the early 2000s. However, most of this work has been published since 2010, with a progressive and growing interest, whatever the theoretical position, to reach 22 articles in the last 3 years (see Fig.  2 ).

Frequency of selected publications over time

The countries of the first authors interested in this concept are predominantly anglophone such as the United Kingdom (k = 9), Australia (k = 5), the United States (k = 4), and Canada (k = 3). Researchers from other countries are less represented.

Three types of publications were found; 34 were original research studies, eight were literature reviews and two were perspective studies. In the original research studies, 23 used a qualitative approach to study either the implementation of a care pathway program or patient experience of a care pathway, four used a descriptive cross-sectional approach, four used a mix-method approach and three used a survey.

Since the definition of the concept is still unclear and terminology is important, the studies meeting the selection criteria reported several terminologies. The most frequently used terms in the selected studies were the patient journey (k = 14) and the care pathway (k = 13) with their some country-specific modifications namely integrated care pathway mainly in the United Kingdom [ 73 , 74 ], optimal care pathway in Australia [ 2 ] and standardized care pathway in Sweden [ 15 ]. The other terms used were clinical pathway (k = 8), patient-centered care (k = 4), care process (k = 3), disease pathway management (k = 1) and value-based integrated care (k = 1).

Studies focused mainly on the care of chronic conditions (k = 24), followed by acute diseases (k = 11). Of those with a chronic care focus, cancer was by far the most studied disease (k = 10), followed by stroke, hearing impairment and mental disease. Acute care studies covered, articular pathologies of the hip and knee, and pregnancy.

Concerning the level of the study, most addressed the systemic (k = 31) rather than the organizational (k = 13) level. Most authors, in their approach to the concept, largely focused on the treatment phase (k = 39), but some included, more or less, pretreatment and subsequent phases. Only seven articles took a global approach starting from the prevention phase and screening to survivorship or palliative care phase.

Concept analysis results

The conceptual analysis followed an automatic data extraction method in the proposed main categories and then, after several iterations, resulted in a coding of subcategories grouped into main themes. The detailed results of the coding are presented in Additional file  4 .

Concept uses

Uses of the concepts of care pathway have evolved in the literature over time with a strong tendency to focus on the care pathway at the systemic level. Main objectives have been improving quality and safety (k = 26), improving efficiency in the delivery of care (k = 24), optimizing the delivery process through an operation management point of view (k = 22) and integrating best practices through guidelines and evidence-based medicine (k = 17). These objectives were widely shared and present throughout the period. However, interest emerged in 2009 and quickly grew, in improving the patient experience through the analysis of the patient journey (k = 17). To a lesser extent, the goals of developing patient-centered care (k = 13), improving patient outcomes (k = 13), improving coordination of service delivery (k = 13), and standardizing care delivery (k = 12) were also present. Beyond standardization, reduced variation in care practices (k = 9) was not well addressed, nor was continuous performance assessment (k = 8). The aim of meeting the patient’s needs (k = 6) has been addressed more frequently in recent years, since its first appearance in 2011 [ 71 ], and is considered of crucial importance by some authors. Other concept uses were proposed, such as to improve interprofessional collaboration (k = 5), support changes (k = 5), support clinical decision making (k = 4), improve communication (k = 3), consider needs of healthcare workers, improve referral system, define shared purposes and meaningful objectives (k = 2), monitor staff compliance, support the knowledge management, improve patient and family member access to information, adopt a system approach and understanding power dynamics and relational factors (k = 1). As described previously, these concept uses came mainly from the chronic disease care context, although acute care was also represented.

Defining attributes

Definitional attributes are features commonly encountered in definitions of the concept or frequently used to describe it [ 40 ]. Twenty-eight attributes were inductively extracted and categorized into seven main themes, ordered by level of empirical importance: (1) The centricity of patients and caregivers; (2) the positioning of professional actors involved in the care pathway; (3) the operation management through the care delivery process; (4) the particularities of coordination structures; (5) the structural context of the system and organizations; (6) the special role of the information system and data management; and (7) the advent of the learning system (k = 3).

Attribute theme 1: The centricity of patients and caregivers

Firstly, there has been a growing interest in the patient experience (k = 15), mainly through the concept of the patient journey [ 5 , 13 , 14 , 15 , 24 , 30 , 42 , 51 , 52 , 58 ], which has progressively emerged as the third pillar of quality in healthcare with clinical effectiveness and patient quality and safety [ 30 ]. It is formed by all the interactions at the meeting point, or point of contact, between health services and patient [ 14 , 30 , 42 , 51 ]. However, taking the patient experience into account is complex insofar as it requires a detailed understanding of what influences it. Therefore, some authors have defined the dimensions that can influence the patient experience as the temporal dimension, meaning that accessibility and short waiting times are valued [ 13 , 15 , 30 , 42 , 51 ], the spatial dimension [ 30 ], and the geographical position of the services [ 42 ], the emotional dimension [ 13 , 30 , 42 ] and the social and cognitive dimensions [ 13 , 42 ]. All these dimensions can be the source of both positive outcomes [ 13 , 30 ] and negative outcomes [ 15 ] or for socio-political authors, a feeling of considerable disempowerment [ 53 ]. Although authors are increasingly interested in it, the patient experience is still sometimes overlooked [ 14 ].

Patient information and education (k = 15) were addressed in numerous studies. Patient information contributes to the quality of the patient experience [ 3 , 15 , 36 , 42 , 53 , 64 , 71 , 75 ]. Beyond the simple satisfaction, the provision of information, at an appropriate health literacy level, increases patient awareness [ 36 , 51 ] and thus increases patient education. This results in a better detection of the symptoms at an early stage by the patient [ 3 , 36 ], the development of the “expert patient” [ 51 , 57 , 58 , 71 ], which aids adherence to treatment, supports shared decision-making [ 57 ] and improves self-management [ 51 , 58 ]. However, many empirical studies showed there to be a lack of patient information throughout patient journeys [ 5 , 14 , 15 , 42 , 51 , 53 , 64 ].

Patient engagement (k = 15) was an important attribute of this theme in the more recent literature. The management by the patient of his or her care treatment plan has become increasingly important [ 24 , 50 , 51 , 53 , 67 ]. This translates into shared decision-making on care and treatment [ 3 , 14 , 24 , 35 , 51 , 53 , 55 , 54 , 55 , 58 , 64 , 65 ]. According to Devi et al. [ 51 ], this process can only be viable if supported by good information about treatment possibilities and possible outcomes. However, socio-political authors see this as a major issue of patient empowerment, which is “seen as a solution to many of the most pressing problems facing modern healthcare” [ 53 ].

Proposed only since 2014, and strongly present in the last 3 years, relationship as the basic need (k = 9) is also a subject of interest. Part of the patient experience, the relational quality reflects how patients perceive their interactions [ 13 , 42 ]. Some empirical studies have shown that a poor relationship can negatively affect other processes and tasks [ 3 , 5 ]. Therefore, quality of the relationship seems a fundamental prerequisite [ 14 , 64 ]. For this reason, some authors have placed the notion of trust as essential to the quality of interactions and to the patient’s follow-up through the care pathway [ 3 , 12 , 58 ].

Patient and Public Involvement (k = 9) is part of these new topics. Its importance in the design and improvement of the care pathway is supported by some international organizations [ 9 ]. The objective is to improve the quality of care provided by assessing patients’ perceptions [ 12 , 13 ]. In this way, the design of care delivery can be based on the real needs and expectations of patients [ 12 , 13 , 51 , 56 , 62 ]. However, some models have been criticized as tokenistic rather than being viable solution for balancing power between patients and health care providers [ 53 ].

Although the stated goal of care pathways incorporates an approach aimed at standardizing care practices, several authors have raised the need for individualized care (k = 8). Joosten et al. [ 74 ] saw a potential conflict between standardization and the demand for a personalized approach to healthcare. However, several authors have subsequently agreed that there is still room for individualization of care beyond the standardization [ 55 ], in particular through the definition of personalized treatment goals [ 51 ], or even maintaining flexibility in the interaction to better adapt to the patient’s specific needs [ 64 , 65 ].

Developed only since 2016, the importance of psychosocial support (k = 8) has increased rapidly. Although the need has been clearly identified and documented [ 5 , 15 , 42 , 58 ] and many international guidelines have integrated it, it seems that its translation within the care pathway is still complex [ 62 ] and no obvious answer was provided.

The inclusion of family and caregiver (k = 8) is also a new topic of the last 5 years which highlights the potential of family or caregivers involvement in decision-making [ 50 , 51 , 57 , 65 ]; notably by supporting both the integration of information and personal decision-making [ 14 , 15 ].

Attribute theme 2: The positioning of professional actors involved in the care pathway

Firstly, most authors consider the care pathway as a tool to develop patient-centered care (k = 18). The patient-centered care approach has a disease-specific orientation [ 25 ] and considers the patient as a real partner [ 51 , 25 ]. In doing so, this approach recognizes an individual’s specific health needs and preferences as the driving force in all healthcare decisions [ 13 , 51 , 65 , 67 ]. Thus, professional actors emphasize their accessibility and their attitudes and behaviors towards patients [ 13 ]. In addition, this approach considers the importance of integrating family and caregivers and is recognized as a necessary attribute of healthcare quality [ 65 ]. Finally, its implementation seems to improve patient satisfaction by moving toward an individualized therapy approach and personalized treatment goals [ 51 ].

Not surprisingly, multidisciplinary team-working (k = 17), and attribute which is consistent with previous definitions, is supported by several authors. The enrollment of all professional categories involved directly or indirectly in the care pathway at all steps is valued [ 2 , 50 , 75 ]. The multidisciplinary teamwork allows tackling the complexity of patient care across the pathway and developing a shared understanding supported by knowledge sharing among professionals [ 53 , 72 ]. In addition, it allows outlining the optimal sequence and timing of interventions [ 38 , 59 ] and to focus only on patient needs and engagement rather than on problems of a particular profession [ 56 ]. From an operational view, multidisciplinary care teams make it possible to share formal screening between disciplines [ 62 ]. Recently, multidisciplinary engagement was identified as a mandatory prerequisite for successful care pathway programs [ 24 , 50 ].

Staff skills (k = 10) could be considered equally important for care pathways. However, they were not addressed in this literature before 2014. Authors gave little attention to technical skills, except to point out possible deficiencies, particularly in diagnosis [ 3 , 13 ], but also in training [ 3 ]. Rather, authors focused almost exclusively on interpersonal skills [ 3 , 12 , 13 , 15 , 51 , 64 ], which were considered critical, both in the relations between professionals [ 12 , 15 , 51 , 56 , 64 ] as well as those with patients and their caregivers [ 15 , 51 , 64 ]. Interpersonal skills could be seen as facilitators or barriers to the patient experience [ 64 ]. Some authors have recently suggested that peer cooperation was critical [ 5 , 50 , 56 ] and that creating a culture of mutual respect among both medical and administrative colleagues can ultimately improve the fluidity of care [ 3 , 5 ].

Few authors have highlighted that the implementation of a care pathway leads professionals to examine their roles and responsibilities (k = 6). The need to define each step in the care process requires professionals to describe precisely the tasks and roles of professional actors [ 25 ]. In doing so, it creates a rare opportunity to step back from daily tasks and reassess competences, roles and responsibilities [ 12 , 51 , 73 ].

Finally, very recently, authors have been interested in the experience of staff (k = 2) in care pathway programs. These authors have demonstrated the link between staff experiences and their individual performance [ 24 , 53 ]. They therefore support the idea that staff well-being is directly related to engagement and performance and, thus, a negative staff experience can influence patient, clinician, and organizational outcomes.

Attribute theme 3: The operation management through the care delivery process

This analysis has shown, unsurprisingly, that the process approach to care delivery (k = 23) was the core of the care pathway approach across the literature to date. From an engineering perspective, as define by the International Organization for Standardization, a process is “a set of interrelated or interacting activities that transforms inputs into outputs” (ISO 9000:2000 clause 3.4.1). Through this approach, the care process can be defined as an arrangement of tasks or actions sequenced in time resulting in a time matrix [ 24 , 30 , 38 , 52 , 60 , 68 , 25 , 73 ]. What distinguishes the different process approaches to care delivery are the tasks and actions included with them. Some authors tend to focus on operational planning by treating tasks, actions and their timing through business processes [ 43 , 49 , 54 , 60 , 69 ], while other authors consider both the context of action through the physical and organizational environment [ 24 , 30 ] and social dynamic through the experience of actors [ 24 , 52 , 53 ]. Through this approach to care processes, some authors focus on patients and caregivers [ 52 ] and other authors focus on human actors, both patients and caregivers and the professional actors involved in the care pathway [ 24 ]. In 2018, Ponsignon et al. [ 13 ] proposed to differentiate the direct, indirect and independent interactions (those disconnected from the delivery system), in care processes. Direct interactions constitute the points of contact between patients and the system, and so are responsible, along with indirect interactions, for the patient version of the pathway that some authors call the patient journey [ 5 , 13 , 30 , 51 , 53 ]. More recently, the complexity of the care process has led some authors to consider that the care pathway should involve pathway rules which control the process [ 70 ]. Thus, decision-making becomes a central element in the smooth running of the care pathway [ 60 ]. In addition, many authors consider that healthcare decisions and care pathways are intertwined so that it becomes imperative to co-design both care pathways and the decision-making activities [ 60 ].

The issue of process management for the delivery of care naturally raises the question of process modeling methods (k = 18). In the empirical articles, the use of the Business Process Modeling Notation (BPMN) developed by the Object Management Group seems to be progressively imposed, sometimes improved by decision modeling [ 4 , 43 , 54 , 60 , 68 , 69 ]. The use of process mapping or flowcharts with sometimes less formal rules seems to be favored for global approaches to processes, especially for the patient journey, although some authors such as Combi et al. [ 60 ], have demonstrated that BPMN modeling was quite compatible with the systemic approach.

For healthcare service designers, the methods for building care pathways are important considerations. Several methods exist, but all involve the discovery of a different path, thus change is inevitable and change management a necessity. The initial method came mainly from the expertise of professionals through interviews, focus groups or Delphi methods [ 49 , 59 ]. The advantage of collaboration with staff and experts is that more information can be gathered about certain decisions and possible variances from the pathway [ 49 ]. However, this method did not consider the real trajectory or the ideal pathway but rather the one integrating the constraints of the professionals. Since these early efforts, data driven approaches has developed considerably [ 43 , 49 ]. Their advantage is that they inform pathway development from data derived factually and objectively from actual occurrences of the pathway [ 49 ]. Moreover, data on the perspectives of patients through experience mapping, interviews, focus groups or observations [ 5 , 13 , 30 ], and patient shadowing [ 53 ] can be integrated to better reflect the real trajectory and to define the ideal pathway according to the needs and expectations of patients and caregivers. However, this approach does not allow for the integration of context and organizational constraints. Finally, few authors adopt an approach that consists of comparing the experience of professionals and patients, making it possible to define the lived experience, the patient’s journey, and its confrontation with operational realities and constraints through the experience of professionals [ 1 , 3 , 4 , 15 , 65 , 71 ].

Regarding the process of care delivery, the management of operations aims to integrate the organization of the delivery process with its ongoing improvement (k = 11) by focusing as much on analyzing the variations as on eliminating the wastes [ 74 ]. Process improvement tools serve as much to redesign the processes as define a workflow management system to monitor the care pathway [ 4 ]. The information generated [ 60 , 61 , 63 ] can be used for process re-engineering, objective reassessment or supporting non-clinical decision-making [ 60 ], such as the identification of bottlenecks [ 61 , 67 ] or highlighting interfacing problems between organizations [ 61 ]. The output generated by the analysis of the process-related data allows defining standardized expedited diagnostic processes [ 4 , 60 ]. Finally, the data obtained allows the use of simulation and optimization models. On this subject, Aspland et al.’s literature review [ 49 ] provides an exhaustive review of available methods.

Attribute theme 4: The particularities of coordination structures

In line with most of the definitions, the integration of the clinical practice guidelines, based on evidenced-based medicine, into the care pathway (k = 24) has been accepted since the beginning of such programs. The clinical decisions directly affect the flow of the care delivery process and thus the process performance and the quality of outcomes [ 60 ]. Therefore, the adherence to clinical practice guidelines must support decision-making [ 70 , 73 ] and aid diagnosis and treatment in order to improve patient outcomes [ 50 , 51 , 58 ]. In 2010, Vanhaecht et al. [ 25 ] expressed concern about a lack of evidence-based key interventions within care pathways. The care pathway can be an effective method to integrate and guarantee the appropriate use of evidence-based interventions and clinical practice guidelines [ 55 ] and may help to overcome two limitations of clinical practice guideline use, which are emerging as key issues [ 60 , 66 ]. Firstly, that they should not be followed blindly as they represent only explicit medical knowledge [ 67 ], but rather require integration of the contextual knowledge of healthcare professionals for appropriate use [ 72 ]. Secondly, it has been shown that physicians can be unaware of updates and changes to clinical guidelines [ 3 ], and so, integrating them into care pathway maps may improve guideline use and adherence. Finally, collectively integrating and discussing clinical practice guidelines appears to improve interprofessional collaboration and clarify roles [ 36 ], but also could benefit the involvement of patients in the co-design of the care pathway [ 35 ].

Some authors consider information continuity (k = 13) as a key factor. Not only because sharing information must support decision-making [ 60 , 75 ] and facilitate communication [ 2 , 12 , 38 ], but more broadly because the disruption of the information flow can lead to coordination problems and easily avoidable costs linked to the repetition of examinations [ 5 , 56 , 59 ]. Therefore, the continuity of information must be supported to ensure sustainable health improvements [ 51 , 70 ]. Some authors insist on the importance of defining an information medium throughout the pathway which is as accessible to care professionals as it is to patients and caregivers [ 65 ].

Recently, some authors have dealt with the subject of leadership of the care pathway (k = 9). The importance of defining a leader for each step of the care pathway was noted [ 25 ]. The lack of coordination without a responsible actor has been shown, especially when the care pathway includes actors in several contexts such as primary care [ 3 ]. Thus, new roles have been defined, such as case managers, joint program or nurse coordinators [ 4 , 15 , 42 , 65 ], roles that enhance coordination among providers through the improvement of the continuity and quality of the information as well as communication [ 15 ].

More recently, the integration of services (k = 9) has been addressed. Because the care pathway approach can involve multiple partnerships between organizations and primary care, it is essential to integrate all stakeholders. The integration needs to be both organizational, at the macro and meso-level through shared purpose and priorities [ 4 , 57 , 25 ] and shared governance mechanisms [ 4 , 12 , 14 , 59 ], and functional at the micro level through communication mechanisms and tools [ 4 , 12 , 14 ]. The unifying element is discussed between the shared interest for the patient [ 56 , 57 ] or the outcomes [ 12 ] to align strategic goals. For Louis et al. [ 56 ], achieving shared purpose is part of the structural context.

Finally, the care pathway is seen as a means of health knowledge management (k = 7) that optimizes quality, efficiency, and organization [ 68 , 70 , 72 ]. But this topic, although strongly addressed between 2011 and 2012, did not seem to be unanimously agreed upon because it was not very well addressed afterwards. However, particular attention can be paid to the elicitation and integration of the contextual knowledge of the various actors involved throughout the care pathway into daily healthcare routine [ 3 , 70 , 72 ].

Attribute theme 5: The structural context of the system and organizations

Firstly, the local physical context (k = 10), topical in the recent literature, includes both the number of units and their positions [ 12 , 67 ], but also the variety of services offered [ 13 ], and can be either an asset in terms of choice and accessibility or a constraint becoming a source of delay [ 14 ]. These barriers are important as the pathway crosses several formal healthcare organizations or informal care settings [ 24 ]. Therefore, the challenge of service integration has become essential [ 51 ].

Secondly, the availability of resources (k = 10) (human, material and financial) has a direct impact on the care pathway and the ability to meet the needs of the population [ 2 , 62 , 25 ]. A lack of adequate resources is an obvious obstacle to care pathways [ 50 ]. A lack of material and human resources, such as the availability of time at each service point [ 52 , 53 ], or the lack of an electronic medical record [ 5 ], meant the unnecessary repetition of history taking, examinations and full investigations. From a financial point of view, the financial and personal resources that people have, are also key to determinants of the care pathways followed by patients [ 51 ].

Thirdly, the social context (k = 7) is less addressed in the current literature but has shown rapid growth in recent years. Social structure includes material and social resources including roles, rules, norms, and values [ 3 , 24 , 53 , 68 ]. Some authors consider the social context as regularities of perception, behavior, belief and value that are expressed as customs, habits, patterns of behavior and other cultural artifacts [ 68 ]. Other authors consider that social structures shape people’s actions and that through people’s interactions they can then reproduce or change these social structures [ 53 ]. While others consider, for their part, that social and physical contexts can be at the origin of boundaries that mitigate against collaboration, adding to the complexity of shared clinical practices in this field [ 3 , 24 ].

Attribute theme 6: The special role of the information system and data management

Data management (k = 14) plays an increasingly important role in the analysis and improvement of care pathways. The implementation of a care flow management system aligned to clinical workflows [ 67 , 69 ], allows real-world data to be used [ 51 ], and visualized through performance dashboards to generate timely corrective action [ 4 ]. It also enables the analysis and monitoring of the variance in time and space within care pathways [ 43 ]. It is considered responsible for the rise of accountability [ 12 , 75 ].

The Electronic Health Record system is a support tool (k = 13) in several aspects. Numerous authors consider that it supports the patient-centered approach [ 51 , 67 ]. In particular, it has the capacity to support communication between health professionals, and between them and the patient [ 5 , 12 , 65 , 67 , 73 , 75 ], but also to support healthcare knowledge learning [ 67 , 73 ], and integrate clinical decision support into IT applications and clinical workflows [ 70 ]. This support throughout the care pathway can improve the quality of care and health outcomes by reducing medication errors and unnecessary investigations [ 5 ]. As stated by Fung-Kee-Fung et al. [ 4 ], the information system provides the fundamental connectivity across silos and professional groups to support the creation of care pathways and sustainable change at the system level.

The issue of digitalization (k = 5) has been treated very recently. It raises the issue of system integration throughout the care pathway. Despite the technological advances and the support of international organizations such as the guidelines on evidence-based digital health interventions for health system strengthening released by the WHO [ 76 ], there are still inefficiencies associated with trying to integrate EHRs across organizations [ 56 ]. These are frequently due to the use of different technological solutions by different stakeholders [ 30 ]. The challenge is therefore to propose a model for integrating information systems throughout the care pathway that are accessible to all stakeholders including patients themselves [ 4 , 50 , 51 , 65 ].

Attribute theme 7: The advent of the learning system

Although it was not frequently addressed, some authors have developed, very recently, the importance of setting up a learning system (k = 3) to support the care pathway. Resulting from the work of Quinn [ 77 ] and Senge [ 78 ], it consists of the development of a system to learn from itself and its past experience and improve the effectiveness, efficiency, safety, and patient and family/caregiver experiences [ 65 ] through a feedback loop [ 24 ]. Data on outcomes can be used as feedback to identify improvement opportunities at various stages of the process or at specific interfaces between stakeholders. The learning system promotes “individual competence, systems thinking, cohesive vision, team learning, and integrating different perspectives” [ 4 ].

Related concepts

The related concepts are confusingly close or even integrated with the main concept studied [ 40 ]. Given the complexity of the use of concepts, we have relied, in addition to definitions found on an analysis of a bibliometric network by integrating all 44 articles, excluding abstracts and bibliographies, into the Vosviewer® software (version 2020). The results help us to refine our understanding of the concepts which define the links between the different keywords. The care pathway bibliometric links are provided as a comparator (see Fig.  3 ).

Care pathway bibliometric links

Clinical pathway (Fig.  4 ) was initially defined by De Bleser et al. [ 38 ]. It is a multidisciplinary intervention that aims to integrate the guidelines into daily routine and manage medical activities in order to improve the quality of service and optimize the use of resources [ 70 ]. It integrates a process of care approach [ 72 ] and aims at standardize care on a procedure or an episode of care [ 38 , 49 , 68 ], integrating decision-making supported by knowledge. What differentiates it from the care pathway is that it is restrained in time and is anchored in an organization [ 25 ], or even a service, and does not deal with the patient experience in any way. Clinical pathways are thus integrated in care pathways at the local level and focus on a single phase of care.

Clinical pathway bibliometric links

Patient journey (Fig.  5 ) consisted of sequential steps in the clinical process of the patient through their experience. It can be defined as “the spatiotemporal distribution of patients’ interactions with multiple care settings over time” [ 24 ]. By analyzing and mapping the patient experience from their perspective [ 5 , 14 , 57 , 58 , 71 ], the objective is to improve the quality of the service provided [ 14 , 52 ]. In this approach, the patient journey is an integral part, and an essential component, of the care pathway. Although it also integrates the process approach, it is not linked to decision-making or knowledge management and does not consider structural constraints or the perception of the providers.

Patient journey bibliometric links

Finally, the care process (Fig.  6 ) is involved across the care continuum to standardize and streamline end-to-end care using management tools [ 4 ]. It is directly linked to the care pathway, the clinical pathway and the patient journey. However, although it supports coordination through decision-making and knowledge management, it does not consider the patient experience, the social relationships and the social dynamics. So, the care process is an integral part of the care pathway but does not consider all the characteristics of the latter.

Care process bibliometric links

Antecedents of the concept

Antecedents are events occurring or in place before the concept can emerge [ 40 ]. Our analysis has highlighted several prerequisites for care pathway implementation (see Additional file 4 ).

Firstly, several authors have stressed the importance of the availability of managerial skills (k = 10). They recommend the creation of a change management team [ 49 , 55 ] consisting of a multidisciplinary team integrating not only knowledge about care pathways [ 60 , 70 ], but also knowledge about operations research, information systems and industrial engineering [ 49 , 55 ]. In addition, some authors advocate the presence of key change leaders in the group included clinicians, administrators, IT leaders, process experts, data analysts, nurses, and patient and family members [ 4 , 24 ]. The project leaders must be available on a long-term basis [ 50 , 75 ], have the ability to understand system interdependencies [ 24 ] and have the ability to create a safe learning environment in which openness is encouraged and everyone’s opinion is valued [ 3 , 50 ]. This could be achieved by using consensus-driven approaches that could address institutional process barriers, resistance to change, and conflicting targets and priorities [ 4 ].

Secondly, care pathway projects should have a priori the adequate resources (k = 4), but their availability must be verified [ 62 , 75 ]. The presence of an EHR is necessary to have access to reliable data at the pre-analysis phase and during the implementation phase to identify the relationships between the context, the mechanisms and the results obtained [ 2 , 73 ].

Finally, other key success factors emerged from the literature (k = 10). Some authors noted that rules of co-involvement and a bottom-up strategy was needed [ 55 ]. Other authors emphasized that the selection of areas where there were clearly established deficiencies was essential given the cost of such projects, but also that the identification of any subgroups for whom its use may not be appropriate, was also required [ 73 ]. They highlighted the importance of following guidelines to achieve professional adherence [ 2 , 50 , 62 , 72 , 73 ], while maintaining flexibility in the approach to implementing a care pathway improvement program [ 62 ]. They also pointed to the importance of communicating on the progress of the project [ 50 ] and of monitoring the applicability of daily work tasks [ 73 ]. Finally, they consider it essential to embed the pathway into policy and strategy [ 2 , 50 , 72 , 75 ]. While others, for their part, highlighted the importance of defining an iterative feedback loop for individuals and aggregated operational and clinical data [ 4 , 24 ].

Consequences (outcomes) and identification of empirical referents

Consequences are events that are the results of the mobilization of the concept [ 40 ] and empirical referents, for their part, consist of observable phenomena by which defining attributes are recognized [ 40 ] (see Additional file 4 ). In a larger sense, this could be the Key Performance Indicators (KPIs) by which one can recognize the defining attributes and their outcomes.

Although the terms of quality and safety, efficiency and process improvement were the first themes in terms of aims, the most frequently occurring theme in the findings pertained to effects on the patient experience (k = 16). These were measured in different ways, including the impact of waiting times (k = 10), patient satisfaction (k = 7) and the patient quality of life (QALYs) (k = 4). There were also attempts to analyze the patient experience more broadly (k = 5), and to integrate patient needs into the redesign of the care pathway [ 5 , 13 , 56 ].

Efficiency of care (k = 15) was strongly supported by some authors as a desired outcome in care pathways. This outcome was first seen, as an objective, through the costs and cost effectiveness of programs [ 49 , 55 , 61 , 70 ], however, more recently it has been considered a consequence of process improvements, rather than a program objective. It has been clearly defined as the reduction of costs through the reduction of the use of healthcare services [ 57 ]. Moreover, reduction in time spent in care, such as the length of stay or cycle time [ 2 , 55 ], is commonly the consequence of process improvements.

Quality of care (k = 11) was addressed but much less frequently than expected. In the global approach, time to diagnostic is a good empirical referent to analyze the capacity of the first steps of the care pathway [ 4 , 69 ]. Other referents such as reduction of unnecessary investigations and medication errors are also addressed but the number and types of complaints were addressed only by socio-political authors [ 53 ].

Health outcomes (k = 11) were also proposed but only since 2009 [ 73 ]. Clinical outcomes and mortality rates are empirical referents that are unanimously accepted. Recovery time and readmission rates were less frequently considered. Single disease index evaluation was proposed by very few authors [ 49 , 70 ].

Process metrics and patient flow (k = 11) was addressed but only the execution time was unanimously accepted as an empirical referent. Apart from the process variance which is shared, only few authors have developed other KPIs such as the percentage of pathway completion [ 70 ], and evaluation for the reasons of pathway failure [ 70 ].

The variance of practices (k = 9) was not frequently addressed as an empirical referent; however, this is one of the objectives of the care pathway addressed in the literature. The introduction of guidelines [ 2 ] aims to decrease the variation within or between practices (k = 3).

Continuity of care (k = 6) was poorly addressed, even though we might assume that this is one of the primary objectives of the care pathway. This may be due to the difficulty of providing tangible results given the duration of such interventions.

Some authors noted an improvement in documentation and data collection (k = 5), measured by rate of documentation [ 54 ], the ability to better understand resource adequacy (k = 3) and a better comprehension of the links between decision outcomes and process performance (k = 2).

Not defined as an outcome, the Human Resources metrics are proposed by some authors and notably diagnostic quality and referral appropriateness, professional competences and staffing levels. Only Carayon et al. [ 24 ] proposed to integrate the quality of working life as an indicator, based on the principle that well-being at work has a direct impact on individual performance and on the results of the care pathway.

Moreover, not present in the empirical references, the measure of the team relationship and coordination (k = 4) has been proposed by some authors, however, the type of indicator has not been clearly explained.

An integrative definition and conceptual framework of patient-centered care pathways

Given the results of our systematic review and concept analysis and our main objective of defining an integrative framework, we suggest the following definition:

“A patient-centered care pathway is a long-term and complex managerial intervention adopting a systemic approach, for a well-defined group of patients who journey across the entire continuum of care, from prevention and screening to recovery or palliative care. This intervention:

prioritizes the centricity of patients and caregivers by analyzing the patient experience through their needs and expectations, taking into account the need for information, education, engagement and involvement and integrates the patient relationships as a fundamental need.

supports the roles of professional actors involved in the care pathway by developing adherence to the patient-centered care approach; working on interdisciplinarity through the development of skills, both technical and above all relational; the clarification of roles and responsibilities; and by taking into account the experience of professionals both in understanding the organizational constraints and their well-being at work.

integrates a process of care approach through the modeling and improvement of the care pathway by continuously integrating the latest knowledge and information to support clinical decision-making and by defining feedback loops to continuously improve clinical and non-clinical process supported by operation management contained within process improvement methodology approaches;

embeds coordination structures through: the implementation of best practices and the translation of guidelines into daily practice; the support of informational continuity through the integration of services at the systemic level; the implementation of knowledge management along the care continuum; and the identification of leaders at each step of the care pathway;

adapts to the contexts of both the physical and social structures by integrating the human, material, economic and financial resource constraints, as well as the social dynamics of power and trust relationships;

is supported by information systems and data management, enabled by digitalization, which ensure the flow of information within the right context at the right time and place, and allows the continuous integration of the latest knowledge into the care flow and the management of accessible data in real time to monitor and evaluate variances in practices and outcomes;

promotes the development of a learning health system to support the care pathway.

The aim and shared goal of a care pathway is to meet the needs and expectations of patients through continuous improvement of patient experience, patient outcomes, quality and safety while taking into account operational and social realities of the system.”

We know that this definition is important but feel that there is a great need for clarification of this concept and how these interventions can be successful given the costs involved. Furthermore, we consider that the proper sequencing of the care pathway should be defined according to the following eight phases: (1) Prevention and screening; (2) Signs and symptoms; (3) Early detection; (4) Diagnostic; (5) Referral systems; (6) Treatment; (7) Follow-ups; (8) Reeducation or Palliative care. In this way, the development of recognized KPIs enabling international comparisons of care pathways should finally make it possible to share knowledge and improve care pathways.

According to this definition and based on the literature review, we propose the following integrative conceptual framework illustrated in Fig.  7 .

Integrative conceptual framework of care pathway

Using systematic review, concept analysis and bibliometric analysis, it was possible to develop a detailed understanding of the care pathway concept enabling us to propose an integrative conceptual framework and definition to try to meet the need for an international consensus and thus enabling international comparisons and improvement of care pathways.

The results of our work have highlighted the evolution and advances of the various uses of care pathways. Initially focused more on an organizational approach, there is growing support in the literature for a holistic approach that addresses the entire care across the continuum at the system level [ 4 , 24 , 42 , 60 ]. Thus, patient centeredness has become the primary focus as more and more authors focus on the patient experience as the unit of quality analysis. In doing so, they have given greater importance to social relationships and especially to the relationship as a basic need and highlighted the need to design the service line structures mirroring patients’ needs [ 56 ]. They therefore approach the patient, not only as the individual who follows the pathway, but as a social being who has needs and expectations to fulfill, making meeting the needs and expectations of the patient and caregivers the core of the care pathway [ 24 , 50 , 51 , 57 ]. However, the evaluation of the quality of healthcare services by the patient still raises several methodological questions to finally go beyond the simple consideration of satisfaction. Finally, patient and public involvement and patient engagement are also important issues to the point that some authors see a real power struggle between patients and clinicians [ 53 ] that can lead to tokenistic involvement.

The professional actors involved in the care pathway are naturally essential players, both because of their professional competencies and their ability to orient themselves towards the needs of the patient. However, they are also often part of a neglected factor. Some authors have shown one of the key criteria for the potential failure of care pathways is a failure to take into account the prevailing social dynamics and the importance of the buy-in of all stakeholders [ 65 ]. Moreover, some authors insist on the importance of the actors involved in the pathway to both integrate the social dynamics and confront the patient’s needs with operational realities and organizational constraints [ 24 ].

The operation management of process approach to care delivery also raises many challenges. Thus, some authors have developed tools for modeling and improving care processes by applying them in a systemic approach to incorporate clinical decision support into the modeling method [ 60 ]. This issue of continuous integration of updated guidelines into care pathways is indeed a major challenge given the rapid evolution of knowledge and the limited capacity of professionals to continuously integrate new knowledge. In addition, data simulation and data analysis methods coupled with process improvement methods are undeniable contributions to improve the issue of fluidity of processes and therefore the overall performance [ 49 ]. However, one of the pitfalls of staying focused on the process would be a failure to consider the social dimension, particularly the prevailing social dynamics.

Coordination structures are one of the points of improvement in the systemic approach. Ensuring the continuity of information along the care pathway, as well as having a formal leader for each portion of the pathway, would solve many of the problems of path breaks or unnecessary repetition of exams that cause unnecessary costs [ 5 , 56 , 59 ]. This begins with the implementation of a single information system and the integration of IT infrastructures across the entire care pathway at the system level and accessible to care professionals as well as patients and caregivers [ 4 , 50 , 51 , 65 ].

The structural context of the system and organizations cannot be neglected because it directly impacts the results of the implementation of the care pathway. Firstly, because some physical constraints such as distances between several organizational entities [ 12 , 14 ] can only be solved by major transformations in the infrastructures or in the initial process. Secondly, because failing to consider the dominant social dynamics could immediately call into question the entire care pathway intervention [ 3 , 24 ] by implementing only cosmetic changes and not transforming clinical, administrative and organizational practices in a sustainable manner.

The information system plays a special role in care pathway, not only because it is the support of the informational continuity, but also because it enables real-time data analysis to support decision-making within the care pathway in the form of feedback loops [ 4 , 24 , 51 ].

Finally, it seems clear that care pathway programs at the systemic level are one potential intervention which could benefit from the implementation of a learning system [ 4 ]. Care pathway outcome data can be used as feedback to identify improvement opportunities at various stages of the process or at specific interfaces between stakeholders. This approach makes it possible to support the continuous improvement of the care process.

Given the richness of the contributions of the last 20 years, we advocate an integrated approach resulting in a fine-grained and comprehensive understanding of care pathway. Our proposal is compatible with the definition of Vanhaecht et al. [ 25 ] currently used by the EPA, but in our opinion, enriches it. It allows users to specify the operational realities to which stakeholders should pay attention. Moreover, it insists on adaptation to the social realities and the changes that inevitably accompany it and directly impact the success or failure. However, we were surprised that the approach to managing organizational change and transformation of practices were little addressed. Only Van Citters et al. [ 65 ] had noted that change management approaches were critical for successful care transformation and that they had been largely neglected in care pathways. We share this point of view and believe that care pathway intervention leaders must develop communicative action skills to support practices transformation. Not mentioned in the selected literature, we propose to enrich our conceptual framework of communicative action proposed by Habermas [ 79 ]. From our point of view, this dimension could explain the failures of such interventions or at least the difficulty in developing sustainable transformations in practices.

In general, the concept analysis approach has raised several questions about the depth of concept analysis and its place in knowledge advancement [ 80 ]. However, we believe that the combination of systematic review rigor and concept analysis richness, was necessary to meet the aims of this study and produced an integrated conceptual framework which is ready for use. However, this research has some limitations. Although interest is growing, few studies offer comprehensive empirical results on the deployment of a care pathway and its outcomes in a global systemic approach over the entire continuum of care. Moreover, there are a few examples of in-depth analysis of car pathways over a long period of time. Together, this means that the literature still offers little insight into potential outcomes of care pathways. Lastly, our analysis was limited to peer-reviewed articles; including other contributions such as theses and dissertations as well as grey literature could have brought out other categories or themes.

This study has resulted in a fine-grained understanding of care pathways and in a clear definition relying on a powerful conceptual framework. It responds to a strong need for conceptual precision, as previous reviews have not addressed the care pathway on a systemic scale and in a holistic manner. In addition, our framework offers a holistic view of the pathway without being specific to a particular condition or context. Our framework encompasses 28 subcategories grouped into seven care pathway attributes that should be considered in complex care pathway intervention. It considers both operational and social realities and supporting the improvement and sustainable transformation of clinical, administrative, and organizational practices for the benefit of patients and caregivers, while taking into account professional experience, organizational constraints, and social dynamics. The formulation of these attributes, antecedents as success factors and consequences as potential outcomes, linked to their KPIs, allows the operationalization of this model for any pathway in any context. We believe that these results are of particular interest to policymakers, decision makers, managers and researchers alike, and that they could lead to an international consensus that would finally allow comparison of care pathway improvement programs. However, we consider that the development of a framework for analyzing the performance of such an intervention has yet to be developed in a more in-depth manner, such as by focusing on certain particularities of each phase so that managers and decision makers can rely on validated dashboards and KPIs. More empirical work needs to be done on the comprehensive approach, as defined in our proposed definition, to provide reliable results on the ability of these interventions to result in an overall improvement. In addition, the question of the understanding of social evaluation of the quality of care by the patient remains an open question, as the patient experience does not yet have conclusive KPIs as it is too often limited to patient satisfaction or QALYs.

Availability of data and materials

This systematic review is based on an analysis of 44 published papers which are all referenced within this manuscript. Data supporting our findings are included in the form of additional files.

Abbreviations

European Pathway Association

Institute of Medicine of America

Key Performance Indicator

Preferred Reporting Items for Systematic reviews and Meta-Analyses

Quality Adjusted Life Year

World Health Organization

Kelly J, Dwyer J, Mackean T, O’Donnell K, Willis E. Coproducing Aboriginal patient journey mapping tools for improved quality and coordination of care. Aust J Prim Health. 2018;23(6):536–42. https://doi.org/10.1071/PY16069 .

Article   Google Scholar  

Bergin RJ, Whitfield K, White V, et al. Optimal care pathways: a national policy to improve quality of cancer care and address inequalities in cancer outcomes. J Cancer Policy. 2020;25:100245. https://doi.org/10.1016/j.jcpo.2020.100245 .

Hutchinson K, Herkes G, Shih P, et al. Identification and referral of patients with refractory epilepsy from the primary to the tertiary care interface in New South Wales, Australia. Epilepsy Behav. 2020;111:107232. https://doi.org/10.1016/j.yebeh.2020.107232 .

Article   PubMed   Google Scholar  

Fung-Kee-Fung M, Maziak D, Pantarotto J, et al. Regional process redesign of lung cancer care: a learning health system pilot project. Curr Oncol. 2018;25(1):59–66. https://doi.org/10.3747/co.25.3719 .

Article   CAS   PubMed   PubMed Central   Google Scholar  

Alkandari M, Ryan K, Hollywood A. The experiences of people living with peripheral neuropathy in Kuwait-a process map of the patient journey. Pharmacy (Basel, Switzerland). 2019;7(3):127. https://doi.org/10.3390/pharmacy7030127 .

Institute of Medicine of America. Committee on quality of health Care in a. crossing the quality chasm: a new health system for the 21st century. Washington, D.C.: National Academy Press; 2001. https://doi.org/10.1136/bmj.323.7322.1192 .

Book   Google Scholar  

Institute of Medicine of America. Committee on improving the quality of cancer care: addressing the challenges of an aging population, board on healthcare services, Institute of Medicine, delivering high-quality Cancer care: charting a new course for a system in crisis. Washington, D.C.: National Academy Press; 2013. https://doi.org/10.17226/18359 .

National Academies of sciences, engineering, medicine. Committee on improving the quality of health care globally. Crossing the global quality chasm: improving healthcare worldwide. Washington (DC): National Academies Press (US); 2018. https://doi.org/10.17226/25152 .

World Health Organization. Framework on integrated, people-centered health services: report by the secretariat. Geneva, Switzerland: World Health Organization; 2016. https://apps.who.int/gb/ebwha/pdf_files/WHA69/A69_39-en.pdf . Accessed June 16, 2020

Google Scholar  

World Health Organization. Report on Cancer: setting priorities, investing wisely and providing Care for all. Geneva, Switzerland: World Health Organization; 2020. https://apps.who.int/iris/handle/10665/330745 . Accessed June 20, 2020

World Health Organization. Guide to developing a national quality policy and strategy: a practical approach to formulating a policy and strategy for quality of care improvement. Geneva, Switzerland: World Health Organization; 2020. https://www.who.int/publications/i/item/9789241565561 . Accessed June 21, 2020

Valentijn PP, Biermann C, Bruijnzeels MA. Value-based integrated (renal) care: setting a development agenda for research and implementation strategies. BMC Health Serv Res. 2016;16(1):1–11. https://doi.org/10.1186/s12913-016-1586-0 .

Ponsignon F, Smart A, Phillips L. A customer journey perspective on service delivery system design: insights from healthcare. Int J Qual Relia Manag. 2018;35(10):2328–47. https://doi.org/10.1108/IJQRM-03-2018-0073 .

Gualandi R, Masella C, Viglione D, Tartaglini D. Exploring the hospital patient journey: what does the patient experience? PLoS One. 2019;14(12):1–15. https://doi.org/10.1371/journal.pone.0224899 .

Article   CAS   Google Scholar  

Schildmeijer K, Frykholm O, Kneck Å, Ekstedt M. Not a straight line-Patients' experiences of prostate Cancer and their journey through the healthcare system. Cancer Nurs. 2019;42(1):E36–43. https://doi.org/10.1097/NCC.0000000000000559 .

Burns K. ISQUA18-2613Patients measuring their experiences with their healthcare system: targeting improvement in access, quality, safety and patient and family Centred care outcomes. Int J Qual Health Care. 2018;30((suppl_2):22–3. https://doi.org/10.1093/intqhc/mzy167.29 .

Nuti S, De Rosis S, Bonciani M, Murante AM. Rethinking healthcare performance evaluation systems towards the people-Centredness approach: their pathways, their experience, their evaluation. Healthc Pap. 2018;17(2):56–64. https://doi.org/10.12927/hcpap.2017.25408 .

Khan AI, Arthurs E, Gradin S, MacKinnon M, Sussman J, Kukreti V. Integrated care planning for cancer patients: a scoping review. Int J Integr Care. 2017;17(6):5. https://doi.org/10.5334/ijic.2543 .

Article   PubMed   PubMed Central   Google Scholar  

Ran T, Cheng C-Y, Misselwitz B, Brenner H, Ubels J, Schlander M. Cost-effectiveness of colorectal cancer screening strategies—a systematic review. Clin Gastroenterol Hepatol. 2019;17(10):1969–1981. e1915. https://doi.org/10.1016/j.cgh.2019.01.014 .

Oxford Dictionaries. Concise medical dictionary: Main edition (10th edition). Oxford University Press. 2020. https://www.oxfordreference.com/view/10.1093/acref/9780198836612.001.0001/acref-9780198836612 . Accessed June 18, 2020.

Oxford Dictionaries. A dictionary of nursing (8th edition). Oxford University Press 2021. https://www.oxfordreference.com/view/10.1093/acref/9780198864646.001.0001/acref-9780198864646 . Accessed June 18, 2020.

Visser J, Beech R. Health operations management: patient flow logistics in health care. Psychol Press. 2005. https://doi.org/10.4324/9780203356791 .

Vanhaecht K. The impact of clinical pathways on the organisation of care processes. [PhD Thesis, Katholieke Universiteit Leuven]. 2007; https://lirias.kuleuven.be/1718750?limo=0 . Accessed January 18, 2020.

Carayon P, Wooldridge A, Hoonakker P, Hundt AS, Kelly MM. SEIPS 3.0: human-centered design of the patient journey for patient safety. Appl Ergon. 2020;84:103033. https://doi.org/10.1016/j.apergo.2019.103033 .

Vanhaecht K, Panella M, van Zelm R, Sermeus W. An overview on the history and concept of care pathways as complex interventions. Int J Care Coord. 2010;14(3):117–23. https://doi.org/10.1016/j.apergo.2019.103033 .

Seys D, Panella M, VanZelm R, et al. Care pathways are complex interventions in complex systems: new European pathway association framework. Int J Care Coord. 2019;22(1):5–9. https://doi.org/10.1177/2053434519839195 .

Solomon R, Damba C, Bryant S. Measuring quality at a system level: an impossible task? The Toronto central LHIN experience. Healthc Q. 2013;16(4):36–42.

Rayner J, Khan T, Chan C, Wu C. Illustrating the patient journey through the care continuum: leveraging structured primary care electronic medical record (EMR) data in Ontario, Canada using chronic obstructive pulmonary disease as a case study. Int J Med Inform. 2020;140:104159. https://doi.org/10.1016/j.ijmedinf.2020.104159 .

Galvin M, Madden C, Maguire S, et al. Patient journey to a specialist amyotrophic lateral sclerosis multidisciplinary clinic: an exploratory study. BMC Health Serv Res. 2015;15(1):1–8. https://doi.org/10.1186/s12913-015-1229-x .

McCarthy S, O'Raghallaigh P, Woodworth S, Lim YL, Kenny LC, Adam F. An integrated patient journey mapping tool for embedding quality in healthcare service reform. J Decis Syst. 2016;25:354–68. https://doi.org/10.1080/12460125.2016.1187394 .

Mead N, Bower P. Patient-centredness: a conceptual framework and review of the empirical literature. Soc Sci Med. 2000;51(7):1087–110. https://doi.org/10.1016/S0277-9536(00)00098-8 .

Article   CAS   PubMed   Google Scholar  

Stewart M, Brown JB, Weston W, McWhinney IR, McWilliam CL, Freeman T. Patient-centered medicine: transforming the clinical method. Abingdon: Radcliffe Medical Press; 2003.

Van Hoeve JC, Vernooij RW, Fiander M, Nieboer P, Siesling S, Rotter T. Effects of oncological care pathways in primary and secondary care on patient, professional and health systems outcomes: a systematic review and meta-analysis. Syst Rev. 2020;9(1):1–15. https://doi.org/10.1186/s13643-018-0693-x .

Baker E, Woolley A, Xyrichis A, Norton C, Hopkins P, Lee G. How does the implementation of a patient pathway-based intervention in the acute care of blunt thoracic injury impact on patient outcomes? A systematic review of the literature. Injury. 2020;51(8):1733–43. https://doi.org/10.1016/j.injury.2020.06.002 .

Seguin ML, Rangnekar A, Renedo A, Palafox B, McKee M, Balabanova D. Systematic review of frameworks used to conceptualise health pathways of individuals diagnosed with cardiovascular diseases. BMJ Glob Health. 2020;5(9):e002464. https://doi.org/10.1136/bmjgh-2020-002464 .

Beausejour M, Goulet L, Debbie Ehrmann F, et al. Pathways of healthcare utilisation in patients with suspected adolescent idiopathic scoliosis: a cross-sectional study. BMC Health Serv Res. 2015;15:500. https://doi.org/10.1186/s12913-015-1152-1 .

Chan RJ, Webster J, Bowers A. End-of-life care pathways for improving outcomes in caring for the dying. Cochrane Database Syst Rev. 2016;2(2):CD008006. https://doi.org/10.1002/14651858.CD008006.pub4 .

De Bleser L, Depreitere R, Waele KD, Vanhaecht K, Vlayen J, Sermeus W. Defining pathways. J Nurs Manag. 2006;14(7):553–63. https://doi.org/10.1111/j.1365-2934.2006.00702.x .

Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 Statement: an updated guideline for reporting systematic reviews. BMJ. 2021:372. https://doi.org/10.1136/bmj.n71 .

Walker L, Avant K, Concept analysis. Strategies for theory construction in nursing (pp. 157–179). Upper Saddle River: Pearson; 2011.

Aromataris E, Munn Z (Editors). Joanna Briggs Institute Reviewer’s Manual (pp. 1-487). The Joanna Briggs Institute; 2017. Available from: https://reviewersmanual.joannabriggs.org/ .

Cherif E, Martin-Verdier E, Rochette C. Investigating the healthcare pathway through patients’ experience and profiles: implications for breast cancer healthcare providers. BMC Health Serv Res. 2020;20:1–11. https://doi.org/10.1186/s12913-020-05569-9 .

Kempa-Liehr AW, Lin CY-C, Britten R, et al. Healthcare pathway discovery and probabilistic machine learning. Int J Med Inform. 2020;137:104087. https://doi.org/10.1016/j.ijmedinf.2020.104087 .

Center for Evidence-Based Management. Critical appraisal of a survey [Available from: https://www.cebma.org/wp-content/uploads/Critical-Appraisal-Questions-for-a-Survey.pdf ]. Accessed September 27, 2020.

Institute for Public Health Sciences. 11 questions to help you make sense of descriptive/cross-sectional studies. Yeshiva University New York; 2002. [Available from: https://reache.files.wordpress.com/2010/03/cross-sectional-appraisal-tool.pdf ]. Accessed October 03, 2020.

Pluye P, Gagnon M-P, Griffiths F, Johnson-Lafleur J. A scoring system for appraising mixed methods research, and concomitantly appraising qualitative, quantitative and mixed methods primary studies in mixed studies reviews. Int J Nurs Stud. 2009;46(4):529–46. https://doi.org/10.1016/j.ijnurstu.2009.01.009 .

Hannes K, Booth A, Harris J, et al. Celebrating methodological challenges and changes: reflecting on the emergence and importance of the role of qualitative evidence in Cochrane reviews. Syst Rev. 2013;2:84. https://doi.org/10.1186/2046-4053-2-84 .

Thomas DR. A general inductive approach for analyzing qualitative evaluation data. Am J Eval. 2006;27(2):237–46. https://doi.org/10.1177/1098214005283748 .

Aspland E, Gartner D, Harper P. Clinical pathway modelling: a literature review. Health Syst. 2020;10(1):1–23. https://doi.org/10.1080/20476965.2019.1652547 .

Busari JO, Yaldiz H, Gans RO, Duits AJ. Clinical leadership as an agent for change: a health system improvement intervention in Curaçao. J Multidiscip Healthc. 2020;13:787–98. https://doi.org/10.2147/JMDH.S262415 .

Devi R, Kanitkar K, Narendhar R, Sehmi K, Subramaniam K. A narrative review of the patient journey through the Lens of non-communicable diseases in low- and middle-income countries. Adv Ther. 2020;37(12):4808–30. https://doi.org/10.1007/s12325-020-01519-3 .

Elkhuizen SG, Vissers JM, Mahdavi M, Van De Klundert JJ. Modeling patient journeys for demand segments in chronic care, with an illustration to type 2 diabetes. Front. Public Health. 2020;8:428. https://doi.org/10.3389/fpubh.2020.00428 eCollection 2020.

Ocloo J, Goodrich J, Tanaka H, Birchall-Searle J, Dawson D, Farr M. The importance of power, context and agency in improving patient experience through a patient and family centred care approach. Health Res Policy Syst. 2020;18(1):10. https://doi.org/10.1186/s12961-019-0487-1 .

Ayachi FL, Rahmouni HB, Ammar MB, Mahjoubi H. A reverse-engineering methodology for medical enhancement processes. Proc Comput Sci. 2019;164:714–23. https://doi.org/10.1016/j.procs.2019.12.240 .

De Belvis AG, Lohmeyer FM, Barbara A, et al. Ischemic stroke: clinical pathway impact. Int J Health Care Qual Assur. 2019;32(3):588–98. https://doi.org/10.1108/IJHCQA-05-2018-0111 .

Louis CJ, Clark JR, Gray B, Brannon D, Parker V. Service line structure and decision-maker attention in three health systems: implications for patient-centered care. Health Care Manag Rev. 2019;44(1):41–56. https://doi.org/10.1097/HMR.0000000000000172 .

Meyer MA. Mapping the patient journey across the continuum: lessons learned from one Patient's experience. J Patient Exp. 2019;6(2):103–7. https://doi.org/10.1177/2374373518783763 .

Mohr P, Galderisi S, Boyer P, et al. Value of schizophrenia treatment I: The patient journey. Eur Psychiatry. 2018;53:107–15. https://doi.org/10.1016/j.eurpsy.2018.06.007 .

Aziz AFA, Nordin NAM, Ali MF, Abd Aziz NA, Sulong S, Aljunid SM. The integrated care pathway for post stroke patients (iCaPPS): a shared care approach between stakeholders in areas with limited access to specialist stroke care services. BMC Health Serv Res. 2017;17(1):35. https://doi.org/10.1186/s12913-016-1963-8 .

Combi C, Oliboni B, Zardini A, Zerbato F. Ieee Seamless Design of Decision-Intensive Care Pathways. 2016:35–45. https://doi.org/10.1109/ICHI.2016.9 .

Gillespie J, McClean S, Garg L, Barton M, Scotney B, Fullerton K. A multi-phase DES modelling framework for patient-centred care. J Oper Res Soc. 2016;67(10):1239–49. https://doi.org/10.1057/jors.2015.114 .

Shaw JM, Price MA, Clayton JM, et al. Developing a clinical pathway for the identification and management of anxiety and depression in adult cancer patients: an online Delphi consensus process. Support Care Cancer. 2016;24(1):33–41. https://doi.org/10.1007/s00520-015-2742-5 .

Walker C, O’Sullivan M, Ziedins I, Furian N. Faster Cancer treatment: using timestamp data to improve patient journeys. Healthc. 2016;4:252–8. https://doi.org/10.1016/j.hjdsi.2016.04.012 .

Grenness C, Hickson L, Laplante-Lévesque A, Davidson B. Patient-centred audiological rehabilitation: perspectives of older adults who own hearing aids. Int J Audiol. 2014;53(sup1):S68–75. https://doi.org/10.3109/14992027.2013.866280 .

Van Citters AD, Fahlman C, Goldmann DA, et al. Developing a pathway for high-value, patient-centered Total joint Arthroplasty. Clin Orthop Relat Res. 2014;472(5):1619–35. https://doi.org/10.1007/s11999-013-3398-4 .

Evans WK, Ung YC, Assouad N, Chyjek A, Sawka C. Improving the quality of lung cancer care in Ontario: the lung cancer disease pathway initiative. J Thorac Oncol. 2013;8(7):876–82. https://doi.org/10.1097/JTO.0b013e31828cb548 .

Huang B, Zhu P, Wu C. Customer-centered careflow modeling based on guidelines. J Med Syst. 2012;36(5):3307–19. https://doi.org/10.1007/s10916-012-9823-5 .

Tehrani J, Liu K, Michel V. Ontology modeling for generation of clinical pathways. J Ind Eng Manag. 2012;5(2):442–56. https://doi.org/10.3926/jiem.586 .

Vandborg MP, Edwards K, Kragstrup J, Vedsted P, Hansen DG, Mogensen O. A new method for analyzing diagnostic delay in gynecological cancer. Int J Gynecol Cancer. 2012;22(5):712–7. https://doi.org/10.1097/IGC.0b013e31824c6d0e .

Yang H, Li W, Liu K, Zhang J. Knowledge-based clinical pathway for medical quality improvement. Inf Syst Front. 2012;14(1):105–17. https://doi.org/10.1007/s10796-011-9307-z .

Manchaiah VK, Stephens D, Meredith R. The patient journey of adults with hearing impairment: the patients’ views. Clin Otolaryngol. 2011;36(3):227–34. https://doi.org/10.1111/j.1749-4486.2011.02320.x .

Yamazaki T, Ikeda M, Umemoto K. Enhancement of healthcare quality using clinical-pathways activities. Vine. 2011;41(1):63–71. https://doi.org/10.1108/03055721111115557 .

Allen D, Gillen E, Rixson L. Systematic review of the effectiveness of integrated care pathways: what works, for whom, in which circumstances? Int J Evid Based Healthc. 2009;7(2):61–74. https://doi.org/10.1111/j.1744-1609.2009.00127.x .

Joosten TC, Bongers IM, Meijboom IBR. Care programmes and integrated care pathways. Int J Health Care Qual Assur. 2008;21(5):472–86. https://doi.org/10.1108/09526860810890440 .

Bond S, Balogh R, McKeever M. Care pathways: integrated clinical record or management information tool? J Integr Care Pathways. 2001;5(2):54–63. https://doi.org/10.1177/147322970100500204 .

World Health Organization. WHO guideline: recommendations on digital interventions for health system strengthening. Geneva: World Health Organization; 2019.

Quinn JB. Intelligent Enterprise: a knowledge and service based paradigm for Industr: Simon and Schuster; 1992.

Senge PM. The fifth discipline: The art and practice of the learning organization (pp. 1-464). Currency; 2006[1990].

Habermas J. The theory of communicative action: Reason and the rationalization of society. Vol 1: Beacon press; 1984.

Lam Wai Shun P, Swaine B, Bottari C. Combining scoping review and concept analysis methodologies to clarify the meaning of rehabilitation potential after acquired brain injury. Disabil Rehabil. 2020:1–9. https://doi.org/10.1080/09638288.2020.1779825 .

Download references

Acknowledgements

Not applicable.

No funding.

Author information

Authors and affiliations.

Département de management, Faculté des sciences de l’administration, Université Laval, 2325 rue de la Terrasse, Québec, QC, G1V 0A6, Canada

Jean-Baptiste Gartner, Kassim Said Abasse & André Côté

Centre de recherche en gestion des services de santé, Université Laval, Québec, QC, Canada

Centre de recherche du CHU de Québec, Université Laval, Québec, QC, Canada

Jean-Baptiste Gartner, Kassim Said Abasse, Paolo Landa & André Côté

Centre de recherche du CISSS de Chaudière-Appalaches, Québec, QC, Canada

Jean-Baptiste Gartner & André Côté

VITAM, Centre de recherche en santé durable, Université Laval, Québec, QC, Canada

Bibliothèque-Direction des services-conseils, Université Laval, Québec, QC, Canada

Frédéric Bergeron

Département d’opérations et systèmes de décision, Université Laval, Québec, QC, Canada

Paolo Landa

Université de Strasbourg, EM Strasbourg-Business School, HuManiS, Strasbourg, France

Célia Lemaire

You can also search for this author in PubMed   Google Scholar

Contributions

JBG study selection, appraisal and analysis, review design, manuscript writing, KSA study selection, study appraisal, review design, content discussion and manuscript review, FB review design, content discussion, critical input and manuscript review, PL study analysis, content discussion, critical input and manuscript review, CL study analysis, content discussion, critical input and manuscript review, and AC study analysis, review design, content discussion and manuscript review. All authors read and approved the final manuscript.

Authors’ information

JBG: MSc, PhD candidate in the Department of Management, Laval University; KSA: PhD, Post-doctoral researcher in the Department of Management, Laval University; Frédéric Bergeron: Health Sciences Librarian, Laval University; PL: PhD, Assistant Professor in the Department of Operations and Decision Systems, Laval University; CL: PhD, Associate Professor at the EM Strasbourg Business School, Strasbourg University and AC: PhD, Full Professor & Director of the Centre for Health Services Management Research, Laval University.

Corresponding author

Correspondence to Jean-Baptiste Gartner .

Ethics declarations

Ethics approval and consent to participate, consent for publication, competing interests.

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

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

Supplementary Information

Additional file 1..

Search strategy.

Additional file 2.

PRISMA 2020 checklist.

Additional file 3.

Quality appraisal of studies.

Additional file 4.

Concept analysis coding.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Gartner, JB., Abasse, K.S., Bergeron, F. et al. Definition and conceptualization of the patient-centered care pathway, a proposed integrative framework for consensus: a Concept analysis and systematic review. BMC Health Serv Res 22 , 558 (2022). https://doi.org/10.1186/s12913-022-07960-0

Download citation

Received : 06 February 2022

Accepted : 13 April 2022

Published : 26 April 2022

DOI : https://doi.org/10.1186/s12913-022-07960-0

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Care pathway
• Patient journey
• Care process
• Patient-centered
• Healthcare management
• Sustainable transformation
• Learning health system
• Concept analysis
• Systematic review

BMC Health Services Research

ISSN: 1472-6963

• General enquiries: [email protected]

• Reference Manager
• Simple TEXT file

People also looked at

Original research article, analyzing the relationship between consumers’ and entrepreneurs’ food waste and sustainable development using a bibliometric approach.

• 1 Department of Economics and Sustainable Development, School of Environment, Geography and Applied Economics, Harokopio University of Athens, Kallithea, Greece
• 2 Department of Public and Community Health, University of West Attica, Athens, Greece

The present study investigates the relationship between food waste and sustainable development, aiming to reveal contextual insights and present novel findings regarding the pivotal importance of waste and environmental strategies toward a circular economy. This research represents an effort to delineate methodological and thematic contributions, thoroughly analyze key themes, examine co-citation patterns, assess collaboration among countries, and identify current knowledge gaps in the literature. As waste management takes precedence within the framework of sustainable development goals, policymakers, and academia will better understand how effective food waste management can contribute to environmental sustainability. Methodologically, we employ systematic review, employing the PRISMA approach, analyzing 761 final papers, and investigating the relationship between food waste and sustainable development. We delve deeper to reveal contextual insights and present empirical findings that underscore the critical role of food waste in the economy and environment. Furthermore, guided by the identified knowledge gaps, we illuminate potential future research avenues that hold immense promise for advancing our understanding of food waste and its impact on sustainable development.

1 Introduction

Sustainable Development Goals centered on food security, environmental preservation, and optimizing material and energy usage are significant motivators for effectively managing the overuse of food waste ( Kaur et al., 2021 ). Food waste is a pressing global issue that squanders valuable resources and exacerbates challenges related to food security, environmental sustainability, and economic efficiency. Food waste, as defined by the Waste and Resources Action Programme, 1 “ is any food and inedible parts sent to a specified list of food waste destinations, where “food” is defined as any substance that was at some point intended for human consumption.”

A critical issue facing our global food system is the enormous amounts of food wasted yearly, leaving millions hungry. In order to resolve this contradiction, it is essential to comprehend the complex relationship between food waste and consumption patterns. This comprehensive investigation explores the different ways that consuming habits, from meal preparation and disposal to planning and purchasing, contribute to the creation of food waste. By looking at these relationships, we hope to pinpoint important intervention areas and create plans to encourage ethical and sustainable food consumption habits, ultimately reducing waste and guaranteeing everyone fair access to wholesome food. Approximately one-third of the food produced for human consumption goes to waste ( Schanes et al., 2018 ). This phenomenon leads to several environmental issues, such as soil erosion, deforestation, water and air pollution, and the release of greenhouse gases during various stages of food production ( Mourad, 2016 ). Thus, most developed countries have witnessed growing awareness and concern regarding the magnitude of food waste within their borders in recent years. Understanding food waste’s intricate parameters and dynamics becomes paramount as we strive to become more environmentally conscious and sustainable.

The current study broadly examines the available literature and discusses the interdisciplinary nature of food waste and its role in sustainable development ( Buczacki et al., 2021 ). Our investigation seeks to unravel the main findings of the current research on sustainable development and SDGs. In doing so, we aim to shed light on the extent of the problem, the societal, economic, and environmental repercussions, and the potential strategies and interventions that can be adopted to mitigate food waste. The world, characterized by its cultural diversity, varying consumption patterns, and dynamic economies, presents a unique and complex landscape for studying food waste. Our investigation extends academic discussion on the association between food waste and sustainability.

More specifically, this study highlights the countries, the authors, and the sources that decidedly investigate the relationship between food waste and sustainable development. By analyzing the successes and challenges faced in the region, we aim to provide valuable insights that can underline possible scientific gaps, inform policy development, and encourage cross-border collaboration in the fight against food waste. In conclusion, this research contributes to the growing knowledge surrounding food waste. By examining the shape of food waste dynamics, we hope to provide food of thought for a foundation for evidence-based policies and practices to minimize food waste’s detrimental impact on society, the environment, and the economy. Pursuing a more sustainable and food-secure future for Europe necessitates a deeper understanding of food waste, making this study an essential step toward that goal.

In sum, the main contribution of this systematic literature review is twofold. Firstly, it serves as a tool for pinpointing areas where scholarly evidence remains insufficient, highlighting the need for further research to expand our understanding of food waste behavior. Secondly, it establishes a knowledge repository that can offer valuable insights for evidence-based decision-making and policy formulation. This, in turn, can enhance the quality and efficacy of policy measures and technological innovations to reduce food waste. However, several objectives and research questions should be addressed and responded to achieve these goals. The main objectives are as follows:

• To investigate the relationship between food waste and sustainable development through a bibliometric analysis.

• To identify key themes, trends, and knowledge gaps in the existing research on food waste and its connection to sustainability within the framework of a circular economy and

• To provide valuable insights for policymakers, academics, and stakeholders working toward reducing food waste and achieving sustainable development goals.

After that, the research questions that are necessary to be addressed and be able to achieve the objectives of the current research are as follows:

• RQ1: What are the dominant themes and research trends in the literature on food waste and sustainable development within a circular economy framework, as revealed by a bibliometric analysis?

• RQ2: What key methodological approaches are employed in the existing research on food waste and sustainable development?

• RQ3: What are the prominent countries, institutions, and authors contributing to the field, and how do they collaborate on research related to food waste and sustainable development?

• RQ4: What are the critical knowledge gaps and potential future research avenues identified in the current body of literature on food waste and sustainable development?

By addressing these research questions, this study aims to offer a comprehensive and data-driven understanding of the current knowledge surrounding food waste and its connection to achieving sustainable development within a circular economy. This understanding can inform future research efforts and guide the development of effective strategies to address this pressing global challenge.

The remaining components are organized as follows: Section 2 summarizes the research methodology and data selection. Section 3 delves into the empirical findings, exploring their connections to the article’s conceptual, intellectual, and social framework. Section 4 presents the conclusion and implications for policy.

2 Scheme of the research and empirical methodology

2.1 bibliometric data.

The bibliometrics approach assesses information trends to emphasize the contributions of both individuals and research groups. We also utilize review processes to synthesize content and generate innovative policy recommendations concerning the relationship between food waste and sustainable development. For the subsequent procedures, we exclusively rely on the Scopus database, which is recognized as one of the most reliable and comprehensive sources. We used “ food waste ” and “ sustainable development ” to pinpoint publications. After that, we eliminated non-relevant publications to exclude irrelevant studies ( Shahbaz et al., 2021 ) following the PRISMA methodology ( Page et al., 2021 ).

In particular, a comprehensive search string in Scopus combined relevant keywords related to food waste and sustainable development. The exclusion criteria were as follows: duplicates were removed, non-English language articles were excluded, and conference materials, editorials, and letters to maintain focus on in-depth research were also removed. Following data extraction using a standardized form, we employed a multifaceted approach. Bibliometric software like VOSviewer and bibliometrix facilitated co-citation analysis, keyword clustering, and citation network visualization are also employed. Additionally, text analysis techniques complemented our understanding of key themes and emerging trends within the selected publications. This process narrows our selection to a final set of 761 studies from 214 sources for further examination.

A compilation of 1,480 research publications published between 2003 and 2023 is the outcome of our first search. We chose this time frame with significant consideration for the reasons listed below. First, we want to highlight some recent developments. There has been much advancement in food waste and its relationship to sustainable development in recent years. With an emphasis on studies released after 2003, we sought to encompass the most recent findings and patterns in this quickly developing subject. Second, it is critical to comprehend the most recent research findings and their implications for current policy and practice as the urgency of tackling food waste and reaching sustainable development goals increases.

2.2 Bibliometric analysis

Researchers can use quantitative and qualitative methodologies to identify gaps in the scientific literature by using the bibliometrics methodology to track trends in academic research ( Siddiqui et al., 2023 ). We have used bibliometric tools like VOSviewer, the R-package, and Biblioshiny to analyze publications about food waste ( Aria and Cuccurullo, 2017 ). The VOSviewer is a tool that uses a two-dimensional map to show the relationships between co-citation data, geographic locations, research journals, and keywords. Their proximity shows the degree of link or similarity between nodes in this visualization. More specifically, this software is excellent at producing two-dimensional maps showing the connections between various items in a dataset. The most popular keywords and how they gathered together are shown in the visualization, which sheds light on the recurring themes in food waste. In addition, VOSviewer assists us in recognizing significant research and schools of thinking that have shaped our current comprehension of food waste and its relationship to sustainability.

On the other hand, R-package and Biblioshiny utilize a diverse set of bibliometric tools that serve as visualization functions for conducting information analysis and generating scientific maps related to the intersection of food waste and sustainability ( da Silva Duarte et al., 2021 ; Srinivas, 2022 ). The package facilitates efficient data processing and transformation, ensuring the accuracy and consistency of the analysis. Biblioshiny provides advanced functions for constructing and analyzing bibliographic networks, allowing us to explore the intricate relationships between different entities within the food waste literature.

3 Empirical results

3.1 publication output and citation growth.

Figure 1 presents a per annum publication and citation growth trend since 2003, with an average of 75.6 citations per document. Notably, interdisciplinary research on food waste has received significant attention recently ( Dhir et al., 2020 ). There has been an exponential increase in publications in recent years, with 2023 having the highest number of publications (146 articles).

Figure 1 . Publication output.

Document-citation analysis was also performed using the “document” unit from the downloaded publications to create a table based on citation data by selecting the first ten documents as a threshold. For each of the ten documents, the number of citations and doi number are presented in the following Table 1 . For brevity, most citations reported by Papargyropoulou et al. (2014) (910 citations) have investigated the factors that increase food waste through several channels of the food supply chain and propose a framework for appropriately managing food waste. Guo et al. (2010) (636 citations) focused their interest on agricultural production and the degradation of the natural environment due to the energy crisis. Authors propose hydrogen as one of the most promising substitutes for fossil fuels. After that, a group of authors with around 300 citations consists of Notarnicola et al. (2017) , who has a total of 383 citations; Williams et al. (2012) , with 360 citations, and Xue et al. (2017) , who has 359 citations. Next, Alexander et al. (2017) , Mourad, Garrone et al. (2014) , Sharma P. et al. (2020) , and Sharma S. et al. (2020) papers have more than 200 citations, but less than 300 completed the first ten high-cited documents.

Table 1 . Top 10 most cited documents.

3.2 Countries’ collaboration networks

Next, Figures 2 , 3 visually represent global research collaboration among countries, displaying the collaboration network and the volume of publications contributed by each country.

Figure 2 . Country scientific production.

Figure 3 . Countries’ collaboration network.

In Figure 2 , the research output is presented with varying shades of color, wherein the darker colors represent the regions with the highest frequency of publications. Notably, China is the global leader in research publications, with an impressive count of 481, showcasing its substantial contribution to the academic landscape. Following closely behind are other key players in the research arena, with Italy contributing 442 publications, the United Kingdom with 246, India with 215, and the United States with 208, all demonstrating their significant presence in the global research community. Additionally, several other highly productive economies, such as Spain, Sweden, Germany, Malaysia, and Australia, are notable contributors, further enriching the global research output landscape.

Moving on to Figure 3 , it describes the collaborative aspect of research on a global scale, shedding light on the interconnections and partnerships between various countries in the pursuit of knowledge and academic advancement.

A compelling pattern emerges when examining collaborations between authors and countries in food waste. Notably, China, Italy, and the United Kingdom substantially collaborate. This outcome highlights their proactive stance in fostering international partnerships to tackle food waste and sustainability nexus. Following closely behind are the United States and Spain, both of which also participate actively in collaborative initiatives. These findings underscore the global significance of addressing food waste and the willingness of these nations to join forces in addressing this critical challenge.

3.3 Keywords, authors, and key countries framework

The upcoming section aims to reveal how researchers have documented various research streams across different countries. To achieve this, we employ the CAK framework to introduce innovative visualizations that portray the amalgamation of authors, research themes, and countries.

It is evident from Figure 4 that Italy, China, and the UK are the most prominent geographical locations. Likewise, the most dominant research themes are food waste, sustainable development, waste management, and waste disposal. It is worth noting that the smaller size of countries with limited contributions suggests that the current state of research is in its early stages. Additional research, mainly from European economies with substantial food demands, should shed light on recent research developments and explore new avenues of inquiry.

Figure 4 . CAK framework. Authors, keywords, countries.

Figure 5 , depicted as a tree diagram, visually represents the keywords extensively employed in the array of previously studied records. A closer examination of the results illuminates the prominent themes authors have chosen to emphasize in their works.

Figure 5 . Keywords tree-map.

Notably, “food waste” takes the lead, featuring in approximately 36% of the articles. This underscores the paramount significance of addressing food waste within the scope of the research, signifying its pervasive relevance in current academic discourse. Sustainability is another crucial focus in 18% of the articles, highlighting the shared commitment to promoting sustainable practices and environmental responsibility within food waste management. Furthermore, the concept of a “circular economy” garners notable attention, being employed as a keyword in 10% of the publications, reflecting the growing interest in developing circular and resource-efficient systems to combat food waste. The utilization of “life cycle assessment” as a keyword in 8% of the articles underscores the methodological approach many authors took, emphasizing the importance of assessing environmental impacts across the entire life cycle of food products. Finally, the notion of “sustainable development” is reflected in 7% of the works, signifying the broader context in which food waste mitigation is situated, emphasizing the pursuit of development that satisfies current requirements without jeopardizing those of coming generations. This breakdown of prevalent keywords offers valuable insights into the thematic and methodological orientations of the scholarly discourse surrounding food waste. It underscores the critical areas of focus within this research domain.

3.4 Co-citation analysis of authors – intellectual structure

Afterward, we utilize co-citation analysis to understand better how literature has evolved in recent decades. The extent to which studies reference one another indicates the interrelatedness within the scientific literature. Co-citation analysis is a constantly changing metric that aids in recognizing emerging paradigms within a selected body of academic literature ( Buczacki et al., 2021 ). In our present study, we refer to Figure 6 (co-citation analysis), where the number of citations is represented, and the relatedness of topics is indicated by the distance between these nodes, shedding light on academic discourse. The visualization in Figure 6 reveals two distinct clusters.

Figure 6 . Co-citations analysis of authors.

The first group of publications delves into the importance of food waste as a critical element in developing a sustainable food system ( Quested et al., 2011 ). They also attempt to identify the losses occurring along the entire food chain and identify the causes of food losses and possible ways of preventing them ( Quested et al., 2011 ; Falasconi et al., 2015 ; Eriksson et al., 2020 ). Conversely, a second cluster examines food issues in a more global scale analysis linked to sustainable development goals ( Liu et al., 2022 ) introducing, for instance, the effects of international food trade on the food system ( Wang et al., 2022 ). Smaller groups use a more quantitative analysis highlighting possible environmental and socio-economic impacts of food waste ( Albizzati et al., 2021 ) and policies at a micro level ( Lassen et al., 2019 ).

3.5 Conceptual structure of the publications

Recently, keyword co-occurrence networks have become increasingly popular in systematic review-based studies, offering a means to harness knowledge mapping and uncover associations among research themes in research management ( Bashir et al., 2021 ). This approach empowers researchers to comprehensively understand a specific field within the amassed knowledge, harnessing the associations between keywords to reveal insights in economic literature. In our current research, we utilize a keyword co-occurrence network approach, setting a threshold of at least five occurrences for a word to be included. Consequently, out of a total of 1,136 keywords, 113 satisfied this requirement (see Figures 7 , 8 ).

Figure 7 . Keywords co-occurrence network.

Figure 8 . Keywords co-occurrence network.

Notably, keywords like “food waste,” “sustainability,” “waste management,” “environmental impact,” and “waste disposable” are the most frequently occurring. Furthermore, as depicted in Figure 7 , three separate groups of keywords are evident (green, red, and blue). Looking at the blue cluster, the keywords “sustainability,” “food supply,” “food security,” “nutrition” and “supply chain” exhibit close associations. As far as the red cluster is concerned, the keywords “article,” “waste disposal,” “fertilizer,” “biogas,” and “nitrogen” indicate a group of research that investigates the concept of food waste from a different perspective. An interesting observation is that keywords (green cluster) such as “life cycle assessment,” “gas emissions,” “anaerobic digestion,” “municipal waste,” and “climate change” have small node sizes but remain interconnected in terms of links.

After that, we expanded the keywords’ co-occurrence network by exploring its time evolution. The connection between food waste and sustainability is relatively recent, with most publications emerging after 2019. Even more recently, authors have also incorporated into their analysis the “circular economy,” “sustainable development goals,” “waste management,” and “food supply.” These keywords provide more information on the trend already in process around the relationship between food waste management and sustainability in the future. A notable trend is observed, with most publications centered around food waste, sustainability, environmental impact assessment, food supply, and climate change.

We further employ Figure 9 to explore thematic mapping from the perspective of four distinct subdivisions, which aids in comprehending the diversity and significance of sub-components within the scientific literature ( Buczacki et al., 2021 ). We have established the maximum number of keywords at 119 and the minimum cluster frequency at 3.

Figure 9 . Thematic map.

The upper right section encompasses “motor themes,” representing research topics with the highest density and centrality, such as “food waste,” “sustainability,” “circular economy,” “life cycle assessment,” and “waste management.” In the lower-right quadrant, we find “food security” characterized by low density, discussing topics like “recycling,” “climate change,” “food waste management,” and “food supply chain.” These transversal themes hold significant importance in the research, contributing to discussions on various research directions. Lastly, “declining or emerging themes” and “niche themes” encompass research topics related to “household food waste” and “co-digestion.” In summary, Figure 9 serves as a valuable tool for understanding the current academic discourse and the potential role of food waste in future waste management policies.

4 Discussion

The present work aims to offer researchers and policymakers a toolbox of organized ideas to tackle food waste. Simultaneously, to achieve the objectives outlined in the Sustainable Development Goals, the target of reducing food waste and adopting a comprehensive strategy incorporating various measures is domineering. These efforts rectify informational gaps already highlighted by previous systematic literature review works ( Schanes et al., 2018 ).

Besides, similar to previous studies ( Principato et al., 2021 ) our research sheds light on the complex sides of the food waste phenomenon, highlighting the trend of research on this topic ( Zhang et al., 2018 ; Vásquez Neyra et al., 2022 ; D'Adamo et al., 2023 ). More specifically, our study provides an essential segment of information presenting the issues around food waste that are denoted as the motor themes with a critical role of food waste in future food waste management and policies, such as the concept of circular economy ( de Oliveira et al., 2021 ; Nikolaou and Tsagarakis, 2021 ; Santagata et al., 2021 ). In this direction, the European Food Safety Authority (2020) highlights that circular economy initiatives are increasing attention to food waste as a food and feed source.

Furthermore, our review, concentrating on strategies to reduce food waste and promote sustainability, dovetails with the Green Deal’s priorities, such as resource efficiency, waste reduction, and sustainable consumption. By positioning the study within the broader context of global sustainability challenges, it becomes evident that addressing food waste is integral to achieving the Green Deal’s ambitious targets. In this direction, according to FAO (2021) one of the ways toward more sustainable agriculture and food production is to manage food production systems sustainably through significant reductions in food loss and waste.

5 Concluding remarks and policy implications

The central objective of our research is to investigate the relationship between food waste and sustainability through a review of academic literature. Our study thoroughly examines all pertinent publications on the nexus between food waste and sustainable development. Given the pivotal role of food waste in the context of Sustainable Development Goals (SDGs), it becomes crucial for policymaking institutions to evaluate socio-economic and policy variables.

This evaluation is essential for harmonizing food consumption and environmental sustainability via several policy implications. For instance, policymakers should prioritize integrating food waste reduction strategies into the broader framework of SDGs. This approach ensures a more holistic and sustainable approach to addressing food waste while advancing the global sustainability agenda. Also, at a microeconomic level, governments must focus on socio-economic and policy factors that directly influence food waste. By designing policies that incentivize food waste reduction at the individual, household, and industrial levels, they can contribute to achieving both economic and environmental goals. On a more global-scale and macroeconomic level, collaboration among countries, mainly focusing on emerging economies, is essential to address the multifaceted challenges posed by food waste. Policymakers should explore international partnerships to facilitate knowledge sharing, best practices, and innovative strategies in mitigating food waste.

In a more specific and focused aspect, our analysis identifies key themes and research areas related to food waste and sustainability. European and national policy measures should emphasize the need to integrate specific food waste reduction strategies into national SDG goals such as Goal 2 (zero hunger) and Goal 12 (responsible consumption and production). Moreover, governments and policymakers can identify specific socio-economic and policy factors that significantly influence food waste at individual, household, and industrial levels. These policy interventions could include consumer awareness campaigns, incentivizing food waste reduction within entrepreneurs, exploring policies like tax breaks for businesses implementing waste reduction strategies, or introducing waste disposal fees based on waste generation. Financially, the public sector could also encourage policies that facilitate the redistribution of surplus food to those in need, reducing waste and promoting social welfare. That can be done by promoting the establishment of international funding mechanisms to support emerging economies in implementing effective food waste reduction strategies.

However, it is noteworthy that conducting country-specific analyses can offer valuable insights and potentially address limitations associated with quantitative data and analysis. Understanding the specific dynamics of food waste in different nations is crucial for tailoring effective policies and interventions. In addition, we urge future research to delve into the role of addressing food waste issues, particularly in emerging economies. Such research endeavors have the potential to yield diverse policy insights. By examining the unique challenges and opportunities food waste presents in these regions, policymakers can better understand the evolving issues in developing and developed nations. This knowledge is invaluable for shaping effective strategies to reduce food waste and promote sustainable practices worldwide.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author contributions

IK: Conceptualization, Investigation, Software, Visualization, Supervision, Visualization, Writing – original draft, Writing – review & editing. SP: Investigation, Software, Visualization, Writing – original draft, Writing – review & editing. GM: Investigation, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing.

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

1. ^ https://wrap.org.uk/

Albizzati, P. F., Tonini, D., and Astrup, T. F. (2021). High-value products from food waste: an environmental and socio-economic assessment. Sci. Total Environ. 755:142466. doi: 10.1016/j.scitotenv.2020.142466

PubMed Abstract | Crossref Full Text | Google Scholar

Alexander, P., Brown, C., Arneth, A., Finnigan, J., Moran, D., and Rounsevell, M. D. (2017). Losses, inefficiencies and waste in the global food system. Agric. Syst. 153, 190–200. doi: 10.1016/j.agsy.2017.01.014

Aria, M., and Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics , 11, 959–975. doi: 10.1016/j.joi.2017.08.007

Crossref Full Text | Google Scholar

Bashir, M. F., Ma, B., Qin, Y., and Bashir, M. A. (2021). Evaluation of one belt one road publications: a bibliometric and literature review analysis. Environ. Sci. Pollut. Res. 28, 37016–37030. doi: 10.1007/s11356-021-14621-y

Buczacki, A., Gładysz, B., and Palmer, E. (2021). HoReCa food waste and sustainable development goals—a systemic view. Sustain. For. 13:5510. doi: 10.3390/su13105510

D'Adamo, I., Desideri, S., Gastaldi, M., and Tsagarakis, K. P. (2023). Sustainable food waste management in supermarkets. Sustain. Prod. Consum. 43, 204–216. doi: 10.1016/j.spc.2023.11.005

de Oliveira, M. M., Lago, A., and Dal’Magro, G. P. (2021). Food loss and waste in the context of the circular economy: a systematic review. J. Clean. Prod. 294:126284. doi: 10.1016/j.jclepro.2021.126284

da Silva Duarte, K. S., Lima, T. A. C., Alves, L. R., Rios, P. A. P., and Motta, W. H. (2021). The circular economy approach for reducing food waste: a systematic review. Revista Produção e desenvolvimento 7. doi: 10.32358/rpd.2021.v7.572

Dhir, A., Talwar, S., Kaur, P., and Malibari, A. (2020). Food waste in hospitality and food services: A systematic literature review and framework development approach. Journal of Cleaner Production , 270, 122861. doi: 10.1016/j.jclepro.2020.122861

Eriksson, M., Malefors, C., Bergström, P., Eriksson, E., and Persson Osowski, C. (2020). Quantities and quantification methodologies of food waste in Swedish hospitals. Sustain. For. 12:3116. doi: 10.3390/su12083116

European Food Safety AuthorityMaggiore, A., Afonso, A., Barrucci, F., and Sanctis, G. D. (2020). Climate change as a driver of emerging risks for food and feed safety, plant, animal health and nutritional quality. EFSA Support. Publ. 17:1881E. doi: 10.2903/sp.efsa.2020.EN-1881

Falasconi, L., Vittuari, M., Politano, A., and Segrè, A. (2015). Food waste in school catering: an Italian case study. Sustain. For. 7, 14745–14760. doi: 10.3390/su71114745

FAO. (2021) In Brief to The State of Food and Agriculture “ Making agrifood systems more resilient to shocks and stresses .” Rome, FAO.

Google Scholar

Garrone, P., Melacini, M., and Perego, A. (2014). Opening the black box of food waste reduction. Food Policy 46, 129–139. doi: 10.1016/j.foodpol.2014.03.014

Guo, X. M., Trably, E., Latrille, E., Carrère, H., and Steyer, J. (2010). Hydrogen production from agricultural waste by dark fermentation: a review. Int. J. Hydrog. Energy 35, 10660–10673. doi: 10.1016/j.ijhydene.2010.03.008

Kaur, G., Lasaridi, K., and Wong, J. (2021). “Sustainable food waste management: an introduction” in Current developments in biotechnology and bioengineering (Elsevier), 1–10.

Lassen, A. D., Christensen, L. M., Spooner, M. P., and Trolle, E. (2019). Characteristics of canteens at elementary schools, upper secondary schools and workplaces that comply with food service guidelines and have a greater focus on food waste. Int. J. Environ. Res. Public Health 16:1115. doi: 10.3390/ijerph16071115

Liu, Y., Tan, Q., Chen, J., Pan, T., Penuelas, J., Zhang, J., et al. (2022). Dietary transition determining the tradeoff between global food security and sustainable development goals varied in regions. Earth's Future 10:e2021EF002354 doi: 10.1029/2021EF002354

Mourad, M. (2016). Recycling, recovering and preventing “food waste”: competing solutions for food systems sustainability in the United States and France. J. Clean. Prod. 126, 461–477. doi: 10.1016/j.jclepro.2016.03.084

Nikolaou, I. E., and Tsagarakis, K. P. (2021). An introduction to circular economy and sustainability: some existing lessons and future directions. Sustain. Prod. Consum. 28, 600–609. doi: 10.1016/j.spc.2021.06.017

Notarnicola, B., Sala, S., Anton, A., McLaren, S. J., Saouter, E., and Sonesson, U. (2017). The role of life cycle assessment in supporting sustainable Agri-food systems: a review of the challenges. J. Clean. Prod. 140, 399–409. doi: 10.1016/j.jclepro.2016.06.071

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Journal of Clinical Epidemiology , 134, 178–89. https://www.ncbi.nlm.nih.gov/pubmed/33789819

Papargyropoulou, E., Lozano, R., Steinberger, J. K., Wright, N., and bin Ujang, Z. (2014). The food waste hierarchy as a framework for the management of food surplus and food waste. J. Clean. Prod. 76, 106–115. doi: 10.1016/j.jclepro.2014.04.020

Principato, L., Mattia, G., Di Leo, A., and Pratesi, C. A. (2021). The household wasteful behaviour framework: a systematic review of consumer food waste. Ind. Mark. Manag. 93, 641–649. doi: 10.1016/j.indmarman.2020.07.010

Quested, T. E., Parry, A. D., Easteal, S., and Swannell, R. (2011). Food and drink waste from households in the UK , vol. 36, 460–467.

Santagata, R., Ripa, M., Genovese, A., and Ulgiati, S. (2021). Food waste recovery pathways: challenges and opportunities for an emerging bio-based circular economy. A systematic review and an assessment. J. Clean. Prod. 286:125490 doi: 10.1016/j.jclepro.2020.125490

Schanes, K., Dobernig, K., and Gözet, B. (2018). Food waste matters-a systematic review of household food waste practices and their policy implications. J. Clean. Prod. 182, 978–991. doi: 10.1016/j.jclepro.2018.02.030

Siddiqui, A., Altekar, S., Kautish, P., Fulzele, S., Kulkarni, N., Siddiqui, M., et al. (2023). Review of measurement of sustainable development goals: A comprehensive bibliometric and visualized analysis. Environmental Science and Pollution Research , 30, 91761–91779. doi: 10.1007/s11356-023-28887-x

Shahbaz, M., Bashir, M. F., Bashir, M. A., and Shahzad, L. (2021). A bibliometric analysis and systematic literature review of tourism-environmental degradation nexus. Environ. Sci. Pollut. Res. 28, 58241–58257. doi: 10.1007/s11356-021-14798-2

Sharma, S., Basu, S., Shetti, N. P., and Aminabhavi, T. M. (2020). Waste-to-energy nexus for circular economy and environmental protection: recent trends in hydrogen energy. Sci. Total Environ. 713:136633. doi: 10.1016/j.scitotenv.2020.136633

Sharma, P., Gaur, V. K., Kim, S., and Pandey, A. (2020). Microbial strategies for bio-transforming food waste into resources. Bioresour. Technol. 299:122580. doi: 10.1016/j.biortech.2019.122580

Srinivas, H. (2022). “Nexus in green economics for Asian countries” in Progress in green economics , 1–16.

Vásquez Neyra, J. M., Cequea, M. M., Gomes Haensel Schmitt, V., and Ferasso, M. (2022). Food consumption and food waste behaviour in households in the context of the COVID-19 pandemic. Br. Food J. 124, 4477–4495. doi: 10.1108/BFJ-07-2021-0798

Wang, J. M., Liu, Q., Hou, Y., Qin, W., Bai, Z. H., Zhang, F. S., et al. (2022). Impacts of international food and feed trade on nitrogen balances and nitrogen use efficiencies of food systems. Sci. Total Environ. 838:156151. doi: 10.1016/j.scitotenv.2022.156151

Williams, H., Wikström, F., Otterbring, T., Löfgren, M., and Gustafsson, A. (2012). Reasons for household food waste with special attention to packaging. J. Clean. Prod. 24, 141–148. doi: 10.1016/j.jclepro.2011.11.044

Xue, L., Liu, G., Parfitt, J., Liu, X., Van Herpen, E., Stenmarck, Å., et al. (2017). Missing food, missing data? A critical review of global food losses and food waste data. Environ. Sci. Technol. 51, 6618–6633. doi: 10.1021/acs.est.7b00401

Zhang, M., Gao, M., Yue, S., Zheng, T., Gao, Z., Ma, X., et al. (2018). Global trends and future prospects of food waste research: a bibliometric analysis. Environ. Sci. Pollut. Res. 25, 24600–24610. doi: 10.1007/s11356-018-2598-6

Keywords: food waste, sustainability, behavior, bibliometric analysis, VOSviewer, bibliometrix

Citation: Kostakis I, Papadaki S and Malindretos G (2024) Analyzing the relationship between consumers’ and entrepreneurs’ food waste and sustainable development using a bibliometric approach. Front. Sustain . 5:1373802. doi: 10.3389/frsus.2024.1373802

Received: 20 January 2024; Accepted: 15 March 2024; Published: 04 April 2024.

Reviewed by:

Copyright © 2024 Kostakis, Papadaki and Malindretos. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Ioannis Kostakis, [email protected]

This article is part of the Research Topic

Innovation in Sustainable Food

Improving the hydrostability of zeolitic imidazolate framework coatings using a facile silk fibroin protein modification method

• Research Article
• Open access
• Published: 15 April 2024

Cite this article

You have full access to this open access article

• Xiuming Wei 1 ,
• Ting Chen 1 ,
• Siyu Chen 1 ,
• Qian Jia 2 ,
• Nurul Ain Mazlan 1 ,
• Allana Lewis 1 ,
• Nobert Radacsi 1 &
• Yi Huang 1  

20 Accesses

Explore all metrics

Zeolitic imidazolate frameworks (ZIFs) are an important subclass of metal-organic frameworks (MOFs) with zeolite-type topology, which can be fabricated under ambient synthesis conditions. However, the applications of ZIFs are commonly limited due to the weak hydrostability of their metal–ligand coordination bonds, particularly under humid and aqueous conditions. In this work, as an example, the hydrolysis behaviours of ZIF-L with a special focus on ZIF-L coatings were tested at aqueous conditions with a wide range of pHs to systematically study and fundamentally understand their structural stability and degradation mechanism. Pristine ZIF-L powder and ZIF-L coatings were severely damaged after only 24 h in aqueous media. Interestingly, the ZIF-L coatings showed two distinct hydrolyzation pathways regardless of pH conditions, exhibiting either a ring-shaped etching or unfolding behaviours. While the ZIF-L powders were hydrolyzed almost identically across all pH conditions. With this new understanding, a facile silk fibroin (SF) protein modification method was developed to enhance the hydrostability of ZIF-L coatings in aqueous media. The effect of protein concentration on surface coating was systemically studied. ZIF-L coating retained its surface morphology after soaking in water and demonstrated switchable super wetting properties and superior separation performance for oil/water mixture. As a result, the quick SF protein modification significantly enhanced the stability of ZIF-L coatings under various pHs, while retaining their switchable wetting property and excellent separation performance.

Article PDF

Download to read the full article text

Avoid common mistakes on your manuscript.

Zhou, H. C. J.; Kitagawa, S. Metal-organic frameworks (MOFs). Chem. Soc. Rev. 2014 , 43 , 5415–5418.

Article   CAS   PubMed   Google Scholar  

Seetharaj, R.; Vandana, P. V.; Arya, P.; Mathew, S. Dependence of solvents, pH, molar ratio and temperature in tuning metal-organic framework architecture. Arab. J. Chem. 2019 , 12 , 295–315.

Article   CAS   Google Scholar  

Pan, Y. C.; Liu, Y. Y.; Zeng, G. F.; Zhao, L.; Lai, Z. P. Rapid synthesis of zeolitic imidazolate framework-8 (ZIF-8) nanocrystals in an aqueous system. Chem. Commun. 2011 , 47 , 2071–2073.

Cacho-Bailo, F.; Seoane, B.; Téllez, C.; Coronas, J. ZIF-8 continuous membrane on porous polysulfone for hydrogen separation. J. Memb. Sci. 2014 , 464 , 119–126.

Lei, Z. W.; Deng, Y. H.; Wang, C. Y. Multiphase surface growth of hydrophobic ZIF-8 on melamine sponge for excellent oil/water separation and effective catalysis in a Knoevenagel reaction. J. Mater. Chem. A 2018 , 6 , 3258–3263.

Zheng, H. Q.; Zhang, Y. N.; Liu, L. F.; Wan, W.; Guo, P.; Nyström, A. M.; Zou, X. D. One-pot synthesis of metal-organic frameworks with encapsulated target molecules and their applications for controlled drug delivery. J. Am. Chem. Soc. 2016 , 138 , 962–968.

Xiao, H.; Zhou, H. X.; Feng, S. S.; Gore, D. B.; Zhong, Z. X.; Xing, W. H. In situ growth of two-dimensional ZIF-L nanoflakes on ceramic membrane for efficient removal of iodine. J. Memb. Sci. 2021 , 619 , 118782.

Yuan, S. S.; Zhu, J. Y.; Li, Y.; Zhao, Y.; Li, J.; Van Puyvelde, P.; Van Der Bruggen, B. Structure architecture of micro/nanoscale ZIF-L on a 3D printed membrane for a superhydrophobic and underwater superoleophobic surface. J. Mater. Chem. A 2019 , 7 , 2723–2729.

Ding, M. L.; Cai, X. C.; Jiang, H. L. Improving MOF stability: Approaches and applications. Chem. Sci. 2019 , 10 , 10209–10230.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Leus, K.; Bogaerts, T.; De Decker, J.; Depauw, H.; Hendrickx, K.; Vrielinck, H.; Van Speybroeck, V.; Van Der Voort, P. Systematic study of the chemical and hydrothermal stability of selected “stable” metal-organic frameworks. Microporous Mesoporous Mater. 2016 , 226 , 110–116.

Park, K. S.; Ni, Z.; Côté, A. P.; Choi, J. Y.; Huang, R. D.; Uribe-Romo, F. J.; Chae, H. K.; O’Keeffe, M.; Yaghi, O. M. Exceptional chemical and thermal stability of zeolitic imidazolate frameworks. Proc. Natl. Acad. Sci. USA 2006 , 103 , 10186–10191.

Bhattacharyya, S.; Pang, S. H.; Dutzer, M. R.; Lively, R. P.; Walton, K. S.; Sholl, D. S.; Nair, S. Interactions of SO 2 -containing acid gases with ZIF-8: Structural changes and mechanistic investigations. J. Phys. Chem. C 2016 , 120 , 27221–27229.

Mottillo, C.; Friščić, T. Carbon dioxide sensitivity of zeolitic imidazolate frameworks. Angew. Chem., Int. Ed. 2014 , 53 , 7471–7474.

Chen, T.; Lewis, A.; Chen, Z. P.; Fan, X. F.; Radacsi, N.; Semiao, A. J. C.; Wang, H. T.; Huang, Y. Smart ZIF-L mesh films with switchable superwettability synthesized via a rapid energy-saving process. Sep. Purif. Technol. 2020 , 240 , 116647.

Yuan, S.; Feng, L.; Wang, K. C.; Pang, J. D.; Bosch, M.; Lollar, C.; Sun, Y. J.; Qin, J. S.; Yang, X. Y.; Zhang, P. et al. Stable metal-organic frameworks: Design, synthesis, and applications. Adv. Mater. 2018 , 30 , 1704303.

Article   Google Scholar  

Qadir, N. U.; Said, S. A. M.; Bahaidarah, H. M. Structural stability of metal-organic frameworks in aqueous media—Controlling factors and methods to improve hydrostability and hydrothermal cyclic stability. Microporous Mesoporous Mater. 2015 , 201 , 61–90.

Gao, S.; Hou, J. W.; Deng, Z. Y.; Wang, T. S.; Beyer, S.; Buzanich, A. G.; Richardson, J. J.; Rawal, A.; Seidel, R.; Zulkifli, M. Y. et al. Improving the acidic stability of zeolitic imidazolate frameworks by biofunctional molecules. Chem 2019 , 5 , 1597–1608.

Liu, X. L.; Li, Y. S.; Ban, Y. J.; Peng, Y.; Jin, H.; Bux, H.; Xu, L. Y.; Caro, J.; Yang, W. S. Improvement of hydrothermal stability of zeolitic imidazolate frameworks. Chem. Commun. 2013 , 49 , 9140–9142.

Shih, Y. H.; Kuo, Y. C.; Lirio, S.; Wang, K. Y.; Lin, C. H.; Huang, H. Y. A simple approach to enhance the water stability of a metal-organic framework. Chem.—Eur. J. 2017 , 23 , 42–46.

Zu, D. D.; Lu, L.; Liu, X. Q.; Zhang, D. Y.; Sun, L. B. Improving hydrothermal stability and catalytic activity of metal-organic frameworks by graphite oxide incorporation. J. Phys. Chem. C 2014 , 118 , 19910–19917.

Yang, S. J.; Choi, J. Y.; Chae, H. K.; Cho, J. H.; Nahm, K. S.; Park, C. R. Preparation and enhanced hydrostability and hydrogen storage capacity of CNT@MOF-5 hybrid composite. Chem. Mater. 2009 , 21 , 1893–1897.

Zhang, W.; Hu, Y. L.; Ge, J.; Jiang, H. L.; Yu, S. H. A facile and general coating approach to moisture/water-resistant metal-organic frameworks with intact porosity. J. Am. Chem. Soc. 2014 , 136 , 16978–16981.

Zhang, F.; You, X. R.; Dou, H.; Liu, Z.; Zuo, B. Q.; Zhang, X. G. Facile fabrication of robust silk nanofibril films via direct dissolution of silk in CaCl 2 -formic acid solution. ACS Appl. Mater. Interfaces 2015 , 7 , 3352–3361.

Wang, X. Q.; Yucel, T.; Lu, Q.; Hu, X.; Kaplan, D. L. Silk nanospheres and microspheres from silk/PVA blend films for drug delivery. Biomaterials 2010 , 31 , 1025–1035.

Jin, H. J.; Kaplan, D. L. Mechanism of silk processing in insects and spiders. Nature 2003 , 424 , 1057–1061.

Zhang, L.; Hu, Y. H. Strong effects of higher-valent cations on the structure of the zeolitic Zn(2-methylimidazole) 2 framework (ZIF-8). J. Phys. Chem. C 2011 , 115 , 7967–7971.

Lee, S.; Oh, S.; Oh, M. Atypical hybrid metal-organic frameworks (MOFs): A combinative process for MOF-on-MOF growth, etching, and structure transformation. Angew. Chem., Int. Ed. 2020 , 59 , 1327–1333.

Chen, R. Z.; Yao, J. F.; Gu, Q. F.; Smeets, S.; Baerlocher, C.; Gu, H. X.; Zhu, D. R.; Morris, W.; Yaghi, O. M.; Wang, H. T. A two-dimensional zeolitic imidazolate framework with a cushion-shaped cavity for CO 2 adsorption. Chem. Commun. 2013 , 49 , 9500–9502.

Low, Z. X.; Yao, J. F.; Liu, Q.; He, M.; Wang, Z. Y.; Suresh, A. K.; Bellare, J.; Wang, H. T. Crystal transformation in zeolitic-imidazolate framework. Cryst. Growth Des. 2014 , 14 , 6589–6598.

Ding, B.; Wang, X. B.; Xu, Y. F.; Feng, S. J.; Ding, Y.; Pan, Y.; Xu, W. F.; Wang, H. T. Hydrothermal preparation of hierarchical ZIF-L nanostructures for enhanced CO 2 capture. J. Colloid Interface Sci. 2018 , 519 , 38–43.

Lo, Y.; Lam, C. H.; Chang, C. W.; Yang, A. C.; Kang, D. Y. Polymorphism/pseudopolymorphism of metal-organic frameworks composed of zinc(II) and 2-methylimidazole: Synthesis, stability, and application in gas storage. RSC Adv. 2016 , 6 , 89148–89156.

Zhang, H. F.; Zhao, M.; Yang, Y.; Lin, Y. S. Hydrolysis and condensation of ZIF-8 in water. Microporous Mesoporous Mater. 2019 , 288 , 109568.

Hu, Y.; Kazemian, H.; Rohani, S.; Huang, Y. N.; Song, Y. In situ high pressure study of ZIF-8 by FTIR spectroscopy. Chem. Commun. 2011 , 47 , 12694–12696.

Zhang, H. F.; Zhao, M.; Lin, Y. S. Stability of ZIF-8 in water under ambient conditions. Microporous Mesoporous Mater. 2019 , 279 , 201–210.

Mita, K.; Ichimura, S.; James, T. C. Highly repetitive structure and its organization of the silk fibroin gene. J. Mol. Evol. 1994 , 38 , 583–592.

Zhou, C. Z.; Confalonieri, F.; Medina, N.; Zivanovic, Y.; Esnault, C.; Yang, T.; Jacquet, M.; Janin, J.; Duguet, M.; Perasso, R. et al. Fine organization of Bombyx mori fibroin heavy chain gene. Nucleic Acids Res. 2000 , 28 , 2413–2419.

Lu, Q.; Zhu, H. S.; Zhang, C. C.; Zhang, F.; Zhang, B.; Kaplan, D. L. Silk self-assembly mechanisms and control from thermodynamics to kinetics. Biomacromolecules 2012 , 13 , 826–832.

Hu, Y.; Zhang, Q.; You, R.; Wang, L.; Li, M. The relationship between secondary structure and biodegradation behavior of silk fibroin scaffolds. Adv. Mater. Sci. Eng. 2012 , 2012

Kundu, J.; Chung, Y. I.; Kim, Y. H.; Tae, G.; Kundu, S. C. Silk fibroin nanoparticles for cellular uptake and control release. Int. J. Pharm. 2010 , 388 , 242–250.

Zhang, Y. Q.; Shen, W. D.; Xiang, R. L.; Zhuge, L. J.; Gao, W. J.; Wang, W. B. Formation of silk fibroin nanoparticles in water-miscible organic solvent and their characterization. J. Nanopart. Res. 2007 , 9 , 885–900.

Li, Q. Q.; Deng, W. J.; Li, C. H.; Sun, Q. Y.; Huang, F. Z.; Zhao, Y.; Li, S. K. High-flux oil/water separation with interfacial capillary effect in switchable superwetting Cu(OH) 2 @ZIF-8 nanowire membranes. ACS Appl. Mater. Interfaces 2018 , 10 , 40265–40273.

Download references

Acknowledgements

This work was supported by start-up funding from the School of Engineering, at the University of Edinburgh. X. M. W. thanks the University of Edinburgh for Principal’s Career Development Ph.D. Scholarships and the School of Engineering for Edinburgh Global Research Scholarship. The authors would like to thank Fergus Dingwall for his laboratory assistance.

Author information

Authors and affiliations.

School of Engineering, Institute for Materials & Processes, The University of Edinburgh, Robert Stevenson Road, Edinburgh, EH9 3FB, UK

Xiuming Wei, Ting Chen, Siyu Chen, Nurul Ain Mazlan, Allana Lewis, Nobert Radacsi & Yi Huang

EASTCHEM School of Chemistry, The University of St Andrews, Purdie Building, North Haugh, St Andrews, KY16 9ST, UK

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Yi Huang .

Electronic Supplementary Material

12274_2024_6586_moesm1_esm.pdf, rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Wei, X., Chen, T., Chen, S. et al. Improving the hydrostability of zeolitic imidazolate framework coatings using a facile silk fibroin protein modification method. Nano Res. (2024). https://doi.org/10.1007/s12274-024-6586-5

Download citation

Received : 07 January 2024

Revised : 23 February 2024

Accepted : 25 February 2024

Published : 15 April 2024

DOI : https://doi.org/10.1007/s12274-024-6586-5

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• zeolitic imidazole framework-L (ZIF-L)
• ZIF-L coatings
• silk fibroin protein
• hydrostability enhancement
• oil/water separation
• Find a journal
• Publish with us
• Track your research