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• 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.

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Home » Conceptual Framework – Types, Methodology and Examples

Conceptual Framework – Types, Methodology and Examples

Table of Contents

Conceptual Framework

Definition:

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

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

Conceptual Framework in Research

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

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

Types of Conceptual Framework

Types of Conceptual Framework are as follows:

Theoretical Framework

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

Conceptual Model

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

Empirical Framework

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

Descriptive Framework

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

Analytical Framework

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

Conceptual Framework for Policy Analysis

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

Logical Frameworks

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

Conceptual Frameworks for Program Evaluation

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

Conceptual Frameworks for Organizational Analysis

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

Conceptual Frameworks for Strategic Planning

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

Components of Conceptual Framework

The components of a conceptual framework typically include:

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

Conceptual Framework Methodology

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

Here are the steps involved in the conceptual framework methodology:

Identify the Research Problem

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

Conduct a Literature Review

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

Define key Concepts and Variables

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

Develop a Theoretical Framework

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

Test the Framework

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

Examples of Conceptual Framework

Some realtime Examples of Conceptual Framework are as follows:

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

Applications of Conceptual Framework

Some of the applications of Conceptual Frameworks are as follows:

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

Purpose of Conceptual Framework

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

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

When to use Conceptual Framework

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

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

Characteristics of Conceptual Framework

key characteristics of a conceptual framework are:

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

Advantages of Conceptual Framework

Advantages of the Conceptual Framework are as follows:

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

Limitations of Conceptual Framework

Limitations of Conceptual Framework are as follows:

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

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What is a Conceptual Framework and How to Make It (with Examples)

A strong conceptual framework underpins good research. A conceptual framework in research is used to understand a research problem and guide the development and analysis of the research. It serves as a roadmap to conceptualize and structure the work by providing an outline that connects different ideas, concepts, and theories within the field of study. A conceptual framework pictorially or verbally depicts presumed relationships among the study variables.

The purpose of a conceptual framework is to serve as a scheme for organizing and categorizing knowledge and thereby help researchers in developing theories and hypotheses and conducting empirical studies.

In this post, we explain what is a conceptual framework, and provide expert advice on how to make a conceptual framework, along with conceptual framework examples.

Table of Contents

What is a Conceptual Framework in Research

Definition of a conceptual framework.

A conceptual framework includes key concepts, variables, relationships, and assumptions that guide the academic inquiry. It establishes the theoretical underpinnings and provides a lens through which researchers can analyze and interpret data. A conceptual framework draws upon existing theories, models, or established bodies of knowledge to provide a structure for understanding the research problem. It defines the scope of research, identifying relevant variables, establishing research questions, and guiding the selection of appropriate methodologies and data analysis techniques.

Conceptual frameworks can be written or visual. Other types of conceptual framework representations might be taxonomic (verbal description categorizing phenomena into classes without showing relationships between classes) or mathematical descriptions (expression of phenomena in the form of mathematical equations).

Figure 1: Definition of a conceptual framework explained diagrammatically

Conceptual Framework Origin

The term conceptual framework appears to have originated in philosophy and systems theory, being used for the first time in the 1930s by the philosopher Alfred North Whitehead. He bridged the theological, social, and physical sciences by providing a common conceptual framework. The use of the conceptual framework began early in accountancy and can be traced back to publications by William A. Paton and John B. Canning in the first quarter of the 20 th century. Thus, in the original framework, financial issues were addressed, such as useful features, basic elements, and variables needed to prepare financial statements. Nevertheless, a conceptual framework approach should be considered when starting your research journey in any field, from finance to social sciences to applied sciences.

Purpose and Importance of a Conceptual Framework in Research

The importance of a conceptual framework in research cannot be understated, irrespective of the field of study. It is important for the following reasons:

• It clarifies the context of the study.
• It justifies the study to the reader.
• It helps you check your own understanding of the problem and the need for the study.
• It illustrates the expected relationship between the variables and defines the objectives for the research.
• It helps further refine the study objectives and choose the methods appropriate to meet them.

What to Include in a Conceptual Framework

Essential elements that a conceptual framework should include are as follows:

• Overarching research question(s)
• Study parameters
• Study variables
• Potential relationships between those variables.

The sources for these elements of a conceptual framework are literature, theory, and experience or prior knowledge.

How to Make a Conceptual Framework

Now that you know the essential elements, your next question will be how to make a conceptual framework.

For this, start by identifying the most suitable set of questions that your research aims to answer. Next, categorize the various variables. Finally, perform a rigorous analysis of the collected data and compile the final results to establish connections between the variables.

In short, the steps are as follows:

• Choose appropriate research questions.
• Define the different types of variables involved.
• Determine the cause-and-effect relationships.

Be sure to make use of arrows and lines to depict the presence or absence of correlational linkages among the variables.

Developing a Conceptual Framework

Researchers should be adept at developing a conceptual framework. Here are the steps for developing a conceptual framework:

1. Identify a research question

Your research question guides your entire study, making it imperative to invest time and effort in formulating a question that aligns with your research goals and contributes to the existing body of knowledge. This step involves the following:

• Choose a broad topic of interest
• Conduct background research
• Narrow down the focus
• Define your goals
• Make it specific and answerable
• Consider significance and novelty
• Seek feedback.

 2. Choose independent and dependent variables

The dependent variable is the main outcome you want to measure, explain, or predict in your study. It should be a variable that can be observed, measured, or assessed quantitatively or qualitatively. Independent variables are the factors or variables that may influence, explain, or predict changes in the dependent variable.

Choose independent and dependent variables for your study according to the research objectives, the nature of the phenomenon being studied, and the specific research design. The identification of variables is rooted in existing literature, theories, or your own observations.

3. Consider cause-and-effect relationships

To better understand and communicate the relationships between variables in your study, cause-and-effect relationships need to be visualized. This can be done by using path diagrams, cause-and-effect matrices, time series plots, scatter plots, bar charts, or heatmaps.

4. Identify other influencing variables

Besides the independent and dependent variables, researchers must understand and consider the following types of variables:

• Moderating variable: A variable that influences the strength or direction of the relationship between an independent variable and a dependent variable.
• Mediating variable: A variable that explains the relationship between an independent variable and a dependent variable and clarifies how the independent variable affects the dependent variable.
• Control variable: A variable that is kept constant or controlled to avoid the influence of other factors that may affect the relationship between the independent and dependent variables.
• Confounding variable: A type of unmeasured variable that is related to both the independent and dependent variables.

Example of a Conceptual Framework

Let us examine the following conceptual framework example. Let’s say your research topic is “ The Impact of Social Media Usage on Academic Performance among College Students .” Here, you want to investigate how social media usage affects academic performance in college students. Social media usage (encompassing frequency of social media use, time spent on social media platforms, and types of social media platforms used) is the independent variable, and academic performance (covering grades, exam scores, and class attendance) is the dependent variable.

This conceptual framework example also includes a mediating variable, study habits, which may explain how social media usage affects academic performance. Study habits (time spent studying, study environment, and use of study aids or resources) can act as a mechanism through which social media usage influences academic outcomes. Additionally, a moderating variable, self-discipline (level of self-control and self-regulation, ability to manage distractions, and prioritization skills), is included to examine how individual differences in self-control and discipline may influence the relationship between social media usage and academic performance.

Confounding variables are also identified (socioeconomic status, prior academic achievement), which are potential factors that may influence both social media usage and academic performance. These variables need to be considered and controlled in the study to ensure that any observed effects are specifically attributed to social media usage. A visual representation of this conceptual framework example is seen in Figure 2.

Figure 2: Visual representation of a conceptual framework for the topic “The Impact of Social Media Usage on Academic Performance among College Students”

Key Takeaways

Here is a snapshot of the basics of a conceptual framework in research:

• A conceptual framework is an idea or model representing the subject or phenomena you intend to study.
• It is primarily a researcher’s perception of the research problem. It can be used to develop hypotheses or testable research questions.
• It provides a preliminary understanding of the factors at play, their interrelationships, and the underlying reasons.
• It guides your research by aiding in the formulation of meaningful research questions, selection of appropriate methods, and identification of potential challenges to the validity of your findings.
• It provides a structure for organizing and understanding data.
• It allows you to chalk out the relationships between concepts and variables to understand them.
• Variables besides dependent and independent variables (moderating, mediating, control, and confounding variables) must be considered when developing a conceptual framework.

Frequently Asked Questions

What is the difference between a moderating variable and a mediating variable.

Moderating and mediating variables are easily confused. A moderating variable affects the direction and strength of this relationship, whereas a mediating explains how two variables relate.

What is the difference between independent variables, dependent variables, and confounding variables?

Independent variables are the variables manipulated to affect the outcome of an experiment (e.g., the dose of a fat-loss drug administered to rats). Dependent variables are variables being measured or observed in an experiment (e.g., changes in rat body weight as a result of the drug). A confounding variable distorts or masks the effects of the variables being studied because it is associated both with dependent variable and with the independent variable. For instance, in this example, pre-existing metabolic dysfunction in some rats could interact differently with the drug being studied and also affect rat body weight.

Should I have more than one dependent or independent variable in a study?

The need for more than one dependent or independent variable in a study depends on the research question, study design, and relationships being investigated. Note the following when making this decision for your research:

• If your research question involves exploring the relationships between multiple variables or factors, it may be appropriate to have more than one dependent or independent variable.
• If you have specific hypotheses about the relationships between several variables, it may be necessary to include multiple dependent or independent variables.
• Adequate resources, sample size, and data collection methods should be considered when determining the number of dependent and independent variables to include.

What is a confounding variable?

A confounding variable is not the main focus of the study but can unintentionally influence the relationship between the independent and dependent variables. Confounding variables can introduce bias and give rise to misleading conclusions. These variables must be controlled to ensure that any observed relationship is genuinely due to the independent variable.

What is a control variable?

A control variable is something not of interest to the study’s objectives but is kept constant because it could influence the outcomes. Control variables can help prevent research biases and allow for a more accurate assessment of the relationship between the independent and dependent variables. Examples are (i) testing all participants at the same time (e.g., in the morning) to minimize the potential effects of circadian rhythms, (ii) ensuring that instruments are calibrated consistently before each measurement to minimize the influence of measurement errors, and (iii) randomization of participants across study groups.

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How To Make Conceptual Framework (With Examples and Templates)

We all know that a research paper has plenty of concepts involved. However, a great deal of concepts makes your study confusing.

A conceptual framework ensures that the concepts of your study are organized and presented comprehensively. Let this article guide you on how to make the conceptual framework of your study.

Related: How to Write a Concept Paper for Academic Research

Table of Contents

At a glance: free conceptual framework templates.

Too busy to create a conceptual framework from scratch? No problem. We’ve created templates for each conceptual framework so you can start on the right foot. All you need to do is enter the details of the variables. Feel free to modify the design according to your needs. Please read the main article below to learn more about the conceptual framework.

Conceptual Framework Template #1: Independent-Dependent Variable Model

Conceptual framework template #2: input-process-output (ipo) model, conceptual framework template #3: concept map, what is a conceptual framework.

A conceptual framework shows the relationship between the variables of your study.  It includes a visual diagram or a model that summarizes the concepts of your study and a narrative explanation of the model presented.

Why Should Research Be Given a Conceptual Framework?

Imagine your study as a long journey with the research result as the destination. You don’t want to get lost in your journey because of the complicated concepts. This is why you need to have a guide. The conceptual framework keeps you on track by presenting and simplifying the relationship between the variables. This is usually done through the use of illustrations that are supported by a written interpretation.

Also, people who will read your research must have a clear guide to the variables in your study and where the research is heading. By looking at the conceptual framework, the readers can get the gist of the research concepts without reading the entire study. 

Related: How to Write Significance of the Study (with Examples)

What Is the Difference Between Conceptual Framework and Theoretical Framework?

Both of them show concepts and ideas of your study. The theoretical framework presents the theories, rules, and principles that serve as the basis of the research. Thus, the theoretical framework presents broad concepts related to your study. On the other hand, the conceptual framework shows a specific approach derived from the theoretical framework. It provides particular variables and shows how these variables are related.

Let’s say your research is about the Effects of Social Media on the Political Literacy of College Students. You may include some theories related to political literacy, such as this paper, in your theoretical framework. Based on this paper, political participation and awareness determine political literacy.

For the conceptual framework, you may state that the specific form of political participation and awareness you will use for the study is the engagement of college students on political issues on social media. Then, through a diagram and narrative explanation, you can show that using social media affects the political literacy of college students.

What Are the Different Types of Conceptual Frameworks?

The conceptual framework has different types based on how the research concepts are organized 1 .

1. Taxonomy

In this type of conceptual framework, the phenomena of your study are grouped into categories without presenting the relationship among them. The point of this conceptual framework is to distinguish the categories from one another.

2. Visual Presentation

In this conceptual framework, the relationship between the phenomena and variables of your study is presented. Using this conceptual framework implies that your research provides empirical evidence to prove the relationship between variables. This is the type of conceptual framework that is usually used in research studies.

3. Mathematical Description

In this conceptual framework, the relationship between phenomena and variables of your study is described using mathematical formulas. Also, the extent of the relationship between these variables is presented with specific quantities.

How To Make Conceptual Framework: 4 Steps

1. identify the important variables of your study.

There are two essential variables that you must identify in your study: the independent and the dependent variables.

An independent variable is a variable that you can manipulate. It can affect the dependent variable. Meanwhile, the dependent variable is the resulting variable that you are measuring.

You may refer to your research question to determine your research’s independent and dependent variables.

Suppose your research question is: “Is There a Significant Relationship Between the Quantity of Organic Fertilizer Used and the Plant’s Growth Rate?” The independent variable of this study is the quantity of organic fertilizer used, while the dependent variable is the plant’s growth rate.

2. Think About How the Variables Are Related

Usually, the variables of a study have a direct relationship. If a change in one of your variables leads to a corresponding change in another, they might have this kind of relationship.

However, note that having a direct relationship between variables does not mean they already have a cause-and-effect relationship 2 . It takes statistical analysis to prove causation between variables.

Using our example earlier, the quantity of organic fertilizer may directly relate to the plant’s growth rate. However, we are not sure that the quantity of organic fertilizer is the sole reason for the plant’s growth rate changes.

3. Analyze and Determine Other Influencing Variables

Consider analyzing if other variables can affect the relationship between your independent and dependent variables 3 .

4. Create a Visual Diagram or a Model

Now that you’ve identified the variables and their relationship, you may create a visual diagram summarizing them.

Usually, shapes such as rectangles, circles, and arrows are used for the model. You may create a visual diagram or model for your conceptual framework in different ways. The three most common models are the independent-dependent variable model, the input-process-output (IPO) model, and concept maps.

a. Using the Independent-Dependent Variable Model

You may create this model by writing the independent and dependent variables inside rectangles. Then, insert a line segment between them, connecting the rectangles. This line segment indicates the direct relationship between these variables. 

Below is a visual diagram based on our example about the relationship between organic fertilizer and a plant’s growth rate. 

b. Using the Input-Process-Output (IPO) Model

If you want to emphasize your research process, the input-process-output model is the appropriate visual diagram for your conceptual framework.

To create your visual diagram using the IPO model, follow these steps:

• Determine the inputs of your study . Inputs are the variables you will use to arrive at your research result. Usually, your independent variables are also the inputs of your research. Let’s say your research is about the Level of Satisfaction of College Students Using Google Classroom as an Online Learning Platform. You may include in your inputs the profile of your respondents and the curriculum used in the online learning platform.
• Outline your research process. Using our example above, the research process should be like this: Data collection of student profiles → Administering questionnaires → Tabulation of students’ responses → Statistical data analysis.
• State the research output . Indicate what you are expecting after you conduct the research. In our example above, the research output is the assessed level of satisfaction of college students with the use of Google Classroom as an online learning platform.
• Create the model using the research’s determined input, process, and output.

Presented below is the IPO model for our example above.

c. Using Concept Maps

If you think the two models presented previously are insufficient to summarize your study’s concepts, you may use a concept map for your visual diagram.

A concept map is a helpful visual diagram if multiple variables affect one another. Let’s say your research is about Coping with the Remote Learning System: Anxiety Levels of College Students. Presented below is the concept map for the research’s conceptual framework:

5. Explain Your Conceptual Framework in Narrative Form

Provide a brief explanation of your conceptual framework. State the essential variables, their relationship, and the research outcome.

Using the same example about the relationship between organic fertilizer and the growth rate of the plant, we can come up with the following explanation to accompany the conceptual framework:

Figure 1 shows the Conceptual Framework of the study. The quantity of the organic fertilizer used is the independent variable, while the plant’s growth is the research’s dependent variable. These two variables are directly related based on the research’s empirical evidence.

Conceptual Framework in Quantitative Research

You can create your conceptual framework by following the steps discussed in the previous section. Note, however, that quantitative research has statistical analysis. Thus, you may use arrows to indicate a cause-and-effect relationship in your model. An arrow implies that your independent variable caused the changes in your dependent variable.

Usually, for quantitative research, the Input-Process-Output model is used as a visual diagram. Here is an example of a conceptual framework in quantitative research:

Research Topic : Level of Effectiveness of Corn (Zea mays) Silk Ethanol Extract as an Antioxidant

Conceptual Framework in Qualitative Research

Again, you can follow the same step-by-step guide discussed previously to create a conceptual framework for qualitative research. However, note that you should avoid using one-way arrows as they may indicate causation . Qualitative research cannot prove causation since it uses only descriptive and narrative analysis to relate variables.

Here is an example of a conceptual framework in qualitative research:

Research Topic : Lived Experiences of Medical Health Workers During Community Quarantine

Conceptual Framework Examples

Presented below are some examples of conceptual frameworks.

Research Topic : Hypoglycemic Ability of Gabi (Colocasia esculenta) Leaf Extract in the Blood Glucose Level of Swiss Mice (Mus musculus)

Figure 1 presents the Conceptual Framework of the study. The quantity of gabi leaf extract is the independent variable, while the Swiss mice’s blood glucose level is the study’s dependent variable. This study establishes a direct relationship between these variables through empirical evidence and statistical analysis . 

Research Topic : Level of Effectiveness of Using Social Media in the Political Literacy of College Students

Figure 1 shows the Conceptual Framework of the study. The input is the profile of the college students according to sex, year level, and the social media platform being used. The research process includes administering the questionnaires, tabulating students’ responses, and statistical data analysis and interpretation. The output is the effectiveness of using social media in the political literacy of college students.

Research Topic: Factors Affecting the Satisfaction Level of Community Inhabitants

Figure 1 presents a visual illustration of the factors that affect the satisfaction level of community inhabitants. As presented, environmental, societal, and economic factors influence the satisfaction level of community inhabitants. Each factor has its indicators which are considered in this study.

Tips and Warnings

• Please keep it simple. Avoid using fancy illustrations or designs when creating your conceptual framework. 
• Allot a lot of space for feedback. This is to show that your research variables or methodology might be revised based on the input from the research panel. Below is an example of a conceptual framework with a spot allotted for feedback.

Frequently Asked Questions

1. how can i create a conceptual framework in microsoft word.

First, click the Insert tab and select Shapes . You’ll see a wide range of shapes to choose from. Usually, rectangles, circles, and arrows are the shapes used for the conceptual framework. 

Next, draw your selected shape in the document.

Insert the name of the variable inside the shape. You can do this by pointing your cursor to the shape, right-clicking your mouse, selecting Add Text , and typing in the text.

Repeat the same process for the remaining variables of your study. If you need arrows to connect the different variables, you can insert one by going to the Insert tab, then Shape, and finally, Lines or Block Arrows, depending on your preferred arrow style.

2. How to explain my conceptual framework in defense?

If you have used the Independent-Dependent Variable Model in creating your conceptual framework, start by telling your research’s variables. Afterward, explain the relationship between these variables. Example: “Using statistical/descriptive analysis of the data we have collected, we are going to show how the <state your independent variable> exhibits a significant relationship to <state your dependent variable>.”

On the other hand, if you have used an Input-Process-Output Model, start by explaining the inputs of your research. Then, tell them about your research process. You may refer to the Research Methodology in Chapter 3 to accurately present your research process. Lastly, explain what your research outcome is.

Meanwhile, if you have used a concept map, ensure you understand the idea behind the illustration. Discuss how the concepts are related and highlight the research outcome.

3. In what stage of research is the conceptual framework written?

The research study’s conceptual framework is in Chapter 2, following the Review of Related Literature.

4. What is the difference between a Conceptual Framework and Literature Review?

The Conceptual Framework is a summary of the concepts of your study where the relationship of the variables is presented. On the other hand, Literature Review is a collection of published studies and literature related to your study. 

Suppose your research concerns the Hypoglycemic Ability of Gabi (Colocasia esculenta) Leaf Extract on Swiss Mice (Mus musculus). In your conceptual framework, you will create a visual diagram and a narrative explanation presenting the quantity of gabi leaf extract and the mice’s blood glucose level as your research variables. On the other hand, for the literature review, you may include this study and explain how this is related to your research topic.

5. When do I use a two-way arrow for my conceptual framework?

You will use a two-way arrow in your conceptual framework if the variables of your study are interdependent. If variable A affects variable B and variable B also affects variable A, you may use a two-way arrow to show that A and B affect each other.

Suppose your research concerns the Relationship Between Students’ Satisfaction Levels and Online Learning Platforms. Since students’ satisfaction level determines the online learning platform the school uses and vice versa, these variables have a direct relationship. Thus, you may use two-way arrows to indicate that the variables directly affect each other.

• Conceptual Framework – Meaning, Importance and How to Write it. (2020). Retrieved 27 April 2021, from https://afribary.com/knowledge/conceptual-framework/
• Correlation vs Causation. Retrieved 27 April 2021, from https://www.jmp.com/en_ph/statistics-knowledge-portal/what-is-correlation/correlation-vs-causation.html
• Swaen, B., & George, T. (2022, August 22). What is a conceptual framework? Tips & Examples. Retrieved December 5, 2022, from https://www.scribbr.com/methodology/conceptual-framework/

Written by Jewel Kyle Fabula

in Career and Education , Juander How

Jewel Kyle Fabula

Jewel Kyle Fabula is a Bachelor of Science in Economics student at the University of the Philippines Diliman. His passion for learning mathematics developed as he competed in some mathematics competitions during his Junior High School years. He loves cats, playing video games, and listening to music.

Browse all articles written by Jewel Kyle Fabula

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What is a good example of a conceptual framework?

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18 April 2023

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Miroslav Damyanov

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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.

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• 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.

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How to Make a Conceptual Framework

6-minute read

• 2nd January 2022

What is a conceptual framework? And why is it important?

A conceptual framework illustrates the relationship between the variables of a research question. It’s an outline of what you’d expect to find in a research project.

Conceptual frameworks should be constructed before data collection and are vital because they map out the actions needed in the study. This should be the first step of an undergraduate or graduate research project.

What Is In a Conceptual Framework?

In a conceptual framework, you’ll find a visual representation of the key concepts and relationships that are central to a research study or project . This can be in form of a diagram, flow chart, or any other visual representation. Overall, a conceptual framework serves as a guide for understanding the problem being studied and the methods being used to investigate it.

Steps to Developing the Perfect Conceptual Framework

• Pick a question
• Conduct a literature review
• Identify your variables
• Create your conceptual framework

1. Pick a Question

You should already have some idea of the broad area of your research project. Try to narrow down your research field to a manageable topic in terms of time and resources. From there, you need to formulate your research question. A research question answers the researcher’s query: “What do I want to know about my topic?” Research questions should be focused, concise, arguable and, ideally, should address a topic of importance within your field of research.

An example of a simple research question is: “What is the relationship between sunny days and ice cream sales?”

2. Conduct a Literature Review

A literature review is an analysis of the scholarly publications on a chosen topic. To undertake a literature review, search for articles with the same theme as your research question. Choose updated and relevant articles to analyze and use peer-reviewed and well-respected journals whenever possible.

For the above example, the literature review would investigate publications that discuss how ice cream sales are affected by the weather. The literature review should reveal the variables involved and any current hypotheses about this relationship.

3. Identify Your Variables

There are two key variables in every experiment: independent and dependent variables.

Independent Variables

The independent variable (otherwise known as the predictor or explanatory variable) is the expected cause of the experiment: what the scientist changes or changes on its own. In our example, the independent variable would be “the number of sunny days.”

Dependent Variables

The dependent variable (otherwise known as the response or outcome variable) is the expected effect of the experiment: what is being studied or measured. In our example, the dependent variable would be “the quantity of ice cream sold.”

Next, there are control variables.

Control Variables

A control variable is a variable that may impact the dependent variable but whose effects are not going to be measured in the research project. In our example, a control variable could be “the socioeconomic status of participants.” Control variables should be kept constant to isolate the effects of the other variables in the experiment.

Finally, there are intervening and extraneous variables.

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Intervening Variables

Intervening variables link the independent and dependent variables and clarify their connection. In our example, an intervening variable could be “temperature.”

Extraneous Variables

Extraneous variables are any variables that are not being investigated but could impact the outcomes of the study. Some instances of extraneous variables for our example would be “the average price of ice cream” or “the number of varieties of ice cream available.” If you control an extraneous variable, it becomes a control variable.

4. Create Your Conceptual Framework

Having picked your research question, undertaken a literature review, and identified the relevant variables, it’s now time to construct your conceptual framework. Conceptual frameworks are clear and often visual representations of the relationships between variables.

We’ll start with the basics: the independent and dependent variables.

Our hypothesis is that the quantity of ice cream sold directly depends on the number of sunny days; hence, there is a cause-and-effect relationship between the independent variable (the number of sunny days) and the dependent and independent variable (the quantity of ice cream sold).

Next, introduce a control variable. Remember, this is anything that might directly affect the dependent variable but is not being measured in the experiment:

Finally, introduce the intervening and extraneous variables. 

The intervening variable (temperature) clarifies the relationship between the independent variable (the number of sunny days) and the dependent variable (the quantity of ice cream sold). Extraneous variables, such as the average price of ice cream, are variables that are not controlled and can potentially impact the dependent variable.

Are Conceptual Frameworks and Research Paradigms the Same?

In simple terms, the research paradigm is what informs your conceptual framework. In defining our research paradigm we ask the big questions—Is there an objective truth and how can we understand it? If we decide the answer is yes, we may be working with a positivist research paradigm and will choose to build a conceptual framework that displays the relationship between fixed variables. If not, we may be working with a constructivist research paradigm, and thus our conceptual framework will be more of a loose amalgamation of ideas, theories, and themes (a qualitative study). If this is confusing–don’t worry! We have an excellent blog post explaining research paradigms in more detail.

Where is the Conceptual Framework Located in a Thesis?

This will depend on your discipline, research type, and school’s guidelines, but most papers will include a section presenting the conceptual framework in the introduction, literature review, or opening chapter. It’s best to present your conceptual framework after presenting your research question, but before outlining your methodology.

Can a Conceptual Framework be Used in a Qualitative Study?

Yes. Despite being less clear-cut than a quantitative study, all studies should present some form of a conceptual framework. Let’s say you were doing a study on care home practices and happiness, and you came across a “happiness model” constructed by a relevant theorist in your literature review. Your conceptual framework could be an outline or a visual depiction of how you will use this model to collect and interpret qualitative data for your own study (such as interview responses). Check out this useful resource showing other examples of conceptual frameworks for qualitative studies .

Expert Proofreading for Researchers

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How to Use a Conceptual Framework for Better Research

A conceptual framework in research is not just a tool but a vital roadmap that guides the entire research process. It integrates various theories, assumptions, and beliefs to provide a structured approach to research. By defining a conceptual framework, researchers can focus their inquiries and clarify their hypotheses, leading to more effective and meaningful research outcomes.

What is a Conceptual Framework?

A conceptual framework is essentially an analytical tool that combines concepts and sets them within an appropriate theoretical structure. It serves as a lens through which researchers view the complexities of the real world. The importance of a conceptual framework lies in its ability to serve as a guide, helping researchers to not only visualize but also systematically approach their study.

Key Components and to be Analyzed During Research

• Theories: These are the underlying principles that guide the hypotheses and assumptions of the research.
• Assumptions: These are the accepted truths that are not tested within the scope of the research but are essential for framing the study.
• Beliefs: These often reflect the subjective viewpoints that may influence the interpretation of data.
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Together, these components help to define the conceptual framework that directs the research towards its ultimate goal. This structured approach not only improves clarity but also enhances the validity and reliability of the research outcomes. By using a conceptual framework, researchers can avoid common pitfalls and focus on essential variables and relationships.

For practical examples and to see how different frameworks can be applied in various research scenarios, you can Explore Conceptual Framework Examples .

Different Types of Conceptual Frameworks Used in Research

Understanding the various types of conceptual frameworks is crucial for researchers aiming to align their studies with the most effective structure. Conceptual frameworks in research vary primarily between theoretical and operational frameworks, each serving distinct purposes and suiting different research methodologies.

Theoretical vs Operational Frameworks

Theoretical frameworks are built upon existing theories and literature, providing a broad and abstract understanding of the research topic. They help in forming the basis of the study by linking the research to already established scholarly works. On the other hand, operational frameworks are more practical, focusing on how the study’s theories will be tested through specific procedures and variables.

• Theoretical frameworks are ideal for exploratory studies and can help in understanding complex phenomena.
• Operational frameworks suit studies requiring precise measurement and data analysis.

Choosing the Right Framework

Selecting the appropriate conceptual framework is pivotal for the success of a research project. It involves matching the research questions with the framework that best addresses the methodological needs of the study. For instance, a theoretical framework might be chosen for studies that aim to generate new theories, while an operational framework would be better suited for testing specific hypotheses.

Benefits of choosing the right framework include enhanced clarity, better alignment with research goals, and improved validity of research outcomes. Tools like Table Chart Maker can be instrumental in visually comparing the strengths and weaknesses of different frameworks, aiding in this crucial decision-making process.

Real-World Examples of Conceptual Frameworks in Research

Understanding the practical application of conceptual frameworks in research can significantly enhance the clarity and effectiveness of your studies. Here, we explore several real-world case studies that demonstrate the pivotal role of conceptual frameworks in achieving robust research conclusions.

• Healthcare Research: In a study examining the impact of lifestyle choices on chronic diseases, researchers used a conceptual framework to link dietary habits, exercise, and genetic predispositions. This framework helped in identifying key variables and their interrelations, leading to more targeted interventions.
• Educational Development: Educational theorists often employ conceptual frameworks to explore the dynamics between teaching methods and student learning outcomes. One notable study mapped out the influences of digital tools on learning engagement, providing insights that shaped educational policies.
• Environmental Policy: Conceptual frameworks have been crucial in environmental research, particularly in studies on climate change adaptation. By framing the relationships between human activity, ecological changes, and policy responses, researchers have been able to propose more effective sustainability strategies.

Adapting conceptual frameworks based on evolving research data is also critical. As new information becomes available, it’s essential to revisit and adjust the framework to maintain its relevance and accuracy, ensuring that the research remains aligned with real-world conditions.

For those looking to visualize and better comprehend their research frameworks, Graphic Organizers for Conceptual Frameworks can be an invaluable tool. These organizers help in structuring and presenting research findings clearly, enhancing both the process and the presentation of your research.

Step-by-Step Guide to Creating Your Own Conceptual Framework

Creating a conceptual framework is a critical step in structuring your research to ensure clarity and focus. This guide will walk you through the process of building a robust framework, from identifying key concepts to refining your approach as your research evolves.

Building Blocks of a Conceptual Framework

• Identify and Define Main Concepts and Variables: Start by clearly identifying the main concepts, variables, and their relationships that will form the basis of your research. This could include defining key terms and establishing the scope of your study.
• Develop a Hypothesis or Primary Research Question: Formulate a central hypothesis or question that guides the direction of your research. This will serve as the foundation upon which your conceptual framework is built.
• Link Theories and Concepts Logically: Connect your identified concepts and variables with existing theories to create a coherent structure. This logical linking helps in forming a strong theoretical base for your research.

Visualizing and Refining Your Framework

Using visual tools can significantly enhance the clarity and effectiveness of your conceptual framework. Decision Tree Templates for Conceptual Frameworks can be particularly useful in mapping out the relationships between variables and hypotheses.

Map Your Framework: Utilize tools like Creately’s visual canvas to diagram your framework. This visual representation helps in identifying gaps or overlaps in your framework and provides a clear overview of your research structure.

Analyze and Refine: As your research progresses, continuously evaluate and refine your framework. Adjustments may be necessary as new data comes to light or as initial assumptions are challenged.

By following these steps, you can ensure that your conceptual framework is not only well-defined but also adaptable to the changing dynamics of your research.

Practical Tips for Utilizing Conceptual Frameworks in Research

Effectively utilizing a conceptual framework in research not only streamlines the process but also enhances the clarity and coherence of your findings. Here are some practical tips to maximize the use of conceptual frameworks in your research endeavors.

• Setting Clear Research Goals: Begin by defining precise objectives that are aligned with your research questions. This clarity will guide your entire research process, ensuring that every step you take is purposeful and directly contributes to your overall study aims. \
• Maintaining Focus and Coherence: Throughout the research, consistently refer back to your conceptual framework to maintain focus. This will help in keeping your research aligned with the initial goals and prevent deviations that could dilute the effectiveness of your findings.
• Data Analysis and Interpretation: Use your conceptual framework as a lens through which to view and interpret data. This approach ensures that the data analysis is not only systematic but also meaningful in the context of your research objectives. For more insights, explore Research Data Analysis Methods .
• Presenting Research Findings: When it comes time to present your findings, structure your presentation around the conceptual framework . This will help your audience understand the logical flow of your research and how each part contributes to the whole.
• Avoiding Common Pitfalls: Be vigilant about common errors such as overcomplicating the framework or misaligning the research methods with the framework’s structure. Keeping it simple and aligned ensures that the framework effectively supports your research.

By adhering to these tips and utilizing tools like 7 Essential Visual Tools for Social Work Assessment , researchers can ensure that their conceptual frameworks are not only robust but also practically applicable in their studies.

How Creately Enhances the Creation and Use of Conceptual Frameworks

Creating a robust conceptual framework is pivotal for effective research, and Creately’s suite of visual tools offers unparalleled support in this endeavor. By leveraging Creately’s features, researchers can visualize, organize, and analyze their research frameworks more efficiently.

• Visual Mapping of Research Plans: Creately’s infinite visual canvas allows researchers to map out their entire research plan visually. This helps in understanding the complex relationships between different research variables and theories, enhancing the clarity and effectiveness of the research process.
• Brainstorming with Mind Maps: Using Mind Mapping Software , researchers can generate and organize ideas dynamically. Creately’s intelligent formatting helps in brainstorming sessions, making it easier to explore multiple topics or delve deeply into specific concepts.
• Centralized Data Management: Creately enables the importation of data from multiple sources, which can be integrated into the visual research framework. This centralization aids in maintaining a cohesive and comprehensive overview of all research elements, ensuring that no critical information is overlooked.
• Communication and Collaboration: The platform supports real-time collaboration, allowing teams to work together seamlessly, regardless of their physical location. This feature is crucial for research teams spread across different geographies, facilitating effective communication and iterative feedback throughout the research process.

Moreover, the ability t Explore Conceptual Framework Examples directly within Creately inspires researchers by providing practical templates and examples that can be customized to suit specific research needs. This not only saves time but also enhances the quality of the conceptual framework developed.

In conclusion, Creately’s tools for creating and managing conceptual frameworks are indispensable for researchers aiming to achieve clear, structured, and impactful research outcomes.

Join over thousands of organizations that use Creately to brainstorm, plan, analyze, and execute their projects successfully.

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Chiraag George is a communication specialist here at Creately. He is a marketing junkie that is fascinated by how brands occupy consumer mind space. A lover of all things tech, he writes a lot about the intersection of technology, branding and culture at large.

Theoretical vs Conceptual Framework

What they are & how they’re different (with examples)

By: Derek Jansen (MBA) | Reviewed By: Eunice Rautenbach (DTech) | March 2023

If you’re new to academic research, sooner or later you’re bound to run into the terms theoretical framework and conceptual framework . These are closely related but distinctly different things (despite some people using them interchangeably) and it’s important to understand what each means. In this post, we’ll unpack both theoretical and conceptual frameworks in plain language along with practical examples , so that you can approach your research with confidence.

Overview: Theoretical vs Conceptual

What is a theoretical framework, example of a theoretical framework, what is a conceptual framework, example of a conceptual framework.

• Theoretical vs conceptual: which one should I use?

A theoretical framework (also sometimes referred to as a foundation of theory) is essentially a set of concepts, definitions, and propositions that together form a structured, comprehensive view of a specific phenomenon.

In other words, a theoretical framework is a collection of existing theories, models and frameworks that provides a foundation of core knowledge – a “lay of the land”, so to speak, from which you can build a research study. For this reason, it’s usually presented fairly early within the literature review section of a dissertation, thesis or research paper .

Let’s look at an example to make the theoretical framework a little more tangible.

If your research aims involve understanding what factors contributed toward people trusting investment brokers, you’d need to first lay down some theory so that it’s crystal clear what exactly you mean by this. For example, you would need to define what you mean by “trust”, as there are many potential definitions of this concept. The same would be true for any other constructs or variables of interest.

You’d also need to identify what existing theories have to say in relation to your research aim. In this case, you could discuss some of the key literature in relation to organisational trust. A quick search on Google Scholar using some well-considered keywords generally provides a good starting point.

Typically, you’ll present your theoretical framework in written form , although sometimes it will make sense to utilise some visuals to show how different theories relate to each other. Your theoretical framework may revolve around just one major theory , or it could comprise a collection of different interrelated theories and models. In some cases, there will be a lot to cover and in some cases, not. Regardless of size, the theoretical framework is a critical ingredient in any study.

Simply put, the theoretical framework is the core foundation of theory that you’ll build your research upon. As we’ve mentioned many times on the blog, good research is developed by standing on the shoulders of giants . It’s extremely unlikely that your research topic will be completely novel and that there’ll be absolutely no existing theory that relates to it. If that’s the case, the most likely explanation is that you just haven’t reviewed enough literature yet! So, make sure that you take the time to review and digest the seminal sources.

Need a helping hand?

A conceptual framework is typically a visual representation (although it can also be written out) of the expected relationships and connections between various concepts, constructs or variables. In other words, a conceptual framework visualises how the researcher views and organises the various concepts and variables within their study. This is typically based on aspects drawn from the theoretical framework, so there is a relationship between the two.

Quite commonly, conceptual frameworks are used to visualise the potential causal relationships and pathways that the researcher expects to find, based on their understanding of both the theoretical literature and the existing empirical research . Therefore, the conceptual framework is often used to develop research questions and hypotheses .

Let’s look at an example of a conceptual framework to make it a little more tangible. You’ll notice that in this specific conceptual framework, the hypotheses are integrated into the visual, helping to connect the rest of the document to the framework.

As you can see, conceptual frameworks often make use of different shapes , lines and arrows to visualise the connections and relationships between different components and/or variables. Ultimately, the conceptual framework provides an opportunity for you to make explicit your understanding of how everything is connected . So, be sure to make use of all the visual aids you can – clean design, well-considered colours and concise text are your friends.

Theoretical framework vs conceptual framework

As you can see, the theoretical framework and the conceptual framework are closely related concepts, but they differ in terms of focus and purpose. The theoretical framework is used to lay down a foundation of theory on which your study will be built, whereas the conceptual framework visualises what you anticipate the relationships between concepts, constructs and variables may be, based on your understanding of the existing literature and the specific context and focus of your research. In other words, they’re different tools for different jobs , but they’re neighbours in the toolbox.

Naturally, the theoretical framework and the conceptual framework are not mutually exclusive . In fact, it’s quite likely that you’ll include both in your dissertation or thesis, especially if your research aims involve investigating relationships between variables. Of course, every research project is different and universities differ in terms of their expectations for dissertations and theses, so it’s always a good idea to have a look at past projects to get a feel for what the norms and expectations are at your specific institution.

Want to learn more about research terminology, methods and techniques? Be sure to check out the rest of the Grad Coach blog . Alternatively, if you’re looking for hands-on help, have a look at our private coaching service , where we hold your hand through the research process, step by step.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

23 Comments

Thank you for giving a valuable lesson

good thanks!

VERY INSIGHTFUL

thanks for given very interested understand about both theoritical and conceptual framework

I am researching teacher beliefs about inclusive education but not using a theoretical framework just conceptual frame using teacher beliefs, inclusive education and inclusive practices as my concepts

good, fantastic

great! thanks for the clarification. I am planning to use both for my implementation evaluation of EmONC service at primary health care facility level. its theoretical foundation rooted from the principles of implementation science.

This is a good one…now have a better understanding of Theoretical and Conceptual frameworks. Highly grateful

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Thanks for shedding light on these two t opics. Much clearer in my head now.

Simple and clear!

The differences between the two topics was well explained, thank you very much!

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Wow, great information, clear and concise review of the differences between theoretical and conceptual frameworks. Thank you! keep up the good work.

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Research , Blog

Developing a conceptual framework: a step-by-step guide for researchers.

• By Dr. Marvin L. Smith

In academic research, conceptual frameworks serve as essential blueprints, guiding scholars through the complex landscape of their studies. This article will explore how to construct powerful conceptual frameworks that elevate research design and execution. 

Whether a seasoned researcher or new to academia, you’ll learn to craft frameworks that clarify objectives, map relationships between variables, and provide a solid foundation for data collection and analysis.

Ready to transform your approach to research design?

Let’s explore the critical role of conceptual frameworks in shaping successful research projects!

Definition of a conceptual framework

A conceptual framework is a structured approach to organizing and presenting the key ideas, theories, and relationships that underpin a research study or academic argument. 

It serves as a roadmap for the researcher, guiding the investigation and helping to connect various concepts logically and coherently.

For example, in a study examining the factors influencing student academic performance, a conceptual framework might include concepts such as socioeconomic status, parental involvement, teacher quality, and school resources. The framework would illustrate how these factors are thought to interact and influence the outcome of academic performance.

Developing conceptual framework in research

Developing a conceptual framework is a crucial step in the research process that helps researchers organize their thoughts, identify key variables, and visualize the relationships between different concepts in their study. 

This process involves synthesizing existing literature, personal observations, and theoretical knowledge to create a structured representation of the research problem and its potential solutions.

A well-crafted conceptual framework serves as a roadmap for the entire research project, guiding the researcher through data collection, analysis, and interpretation.

It also helps in communicating complex ideas to readers, making the research more accessible and understandable. 

By clearly defining the key concepts and their interconnections, researchers can ensure that their study remains focused and coherent throughout its execution.

Developing a conceptual framework is an iterative process that often evolves as the research progresses. It requires critical thinking, creativity, and a deep understanding of the subject matter. Researchers must be prepared to revise and refine their framework as they gain new insights or encounter unexpected findings during their study.

Creating a conceptual framework not only benefits the researcher but also adds credibility to the research by demonstrating a thoughtful and systematic approach to addressing the research question. It helps in identifying potential gaps in existing knowledge and can highlight areas where the study may contribute to the broader field of research.

Here’s a step-by-step guide can create a conceptual framework.

Related reading: How to write a research proposal

Step#1: Select your research question

Selecting a research question is the crucial first step in developing a conceptual framework. This step lays the foundation for your entire research project and guides the development of your conceptual framework. 

Here’s a detailed explanation of this step:

The research question is the central inquiry that your study aims to answer. It should be clear, focused, and relevant to your field of study. When selecting your research question:

1. Identify your area of interest:

Begin by considering topics that genuinely interest you within your field. This ensures that you’ll remain motivated throughout the research process.

2. Review existing literature:

Conduct a preliminary literature review to understand what’s already known about your topic and identify gaps in current knowledge.

3. Consider relevance and significance:

Ensure that your question addresses a meaningful issue or problem in your field. It should contribute to existing knowledge or have practical implications.

 4. Assess feasibility:

Consider whether you have access to the necessary resources, data, and time to answer the question effectively.

5. Be specific:

Narrow down your question to make it manageable. Avoid overly broad or vague questions that could lead to unfocused research.

6. Formulate the question:

Craft your question using clear, concise language. It should be open-ended enough to allow for in-depth exploration but specific enough to guide your research.

7. Test your question:

Ask yourself if the question can be researched, analyzed, and potentially answered within the scope of your study.

For example, instead of a broad question like “How does social media affect teenagers?”, you might refine it to “How does daily Instagram use impact self-esteem in female high school students aged 14-18 in urban areas?”

Step#2: Select and define your independent and dependent variables  

This step is crucial in developing your conceptual framework as it helps clarify the relationships you’ll be exploring in your research. Let’s break down each component:

Independent Variables:

These are the factors you manipulate or control in your study. They are presumed to cause or influence the dependent variable. In your conceptual framework, independent variables are typically positioned on the left or at the beginning of your model.

For example, in a study on academic performance, independent variables might include:

• Study hours per week
• Teaching methods

Dependent Variables:

These are the outcomes or effects you’re measuring in your study. They are influenced by the independent variables. In your conceptual framework, dependent variables are usually positioned on the right or at the end of your model.

Using the same example, the dependent variable might be:

• Student grades
• Test scores

Moderator Variables:

These are variables that affect the strength or direction of the relationship between independent and dependent variables. They can amplify or diminish the effect of the independent variable on the dependent variable.

For instance, a moderator in our academic performance study could be:

• Student motivation level

Mediator Variables:

These variables explain how or why an independent variable affects the dependent variable. They serve as a link in the causal chain between the independent and dependent variables.

An example of a mediator in our study might be:

• Student engagement level

Moderator vs. Mediator:

The key difference is that moderators affect the strength of the relationship, while mediators explain the process through which the independent variable influences the dependent variable.

Control Variables:

These are variables that you hold constant or control for in your study to ensure that they don’t interfere with the relationship between your main variables of interest. They help isolate the effects of your independent variables on the dependent variables.

In our academic performance example, control variables might include:

• Socioeconomic status
• Prior academic achievement

When selecting and defining these variables:

• Ensure they are related to your research question.
• Choose variables that can be measured or observed.
• Consider how these variables interact with each other.
• Be precise in your definitions to avoid ambiguity. 

Related reading: How to find research articles

Step#3: Determine your cause-and-effect relationship  

Determining the cause-and-effect relationship is a critical step in developing your conceptual framework. This step involves identifying and clarifying how your independent variables (causes) are expected to influence your dependent variables (effects). 

1. Identify potential causal relationships:

Based on your research question and the variables you’ve selected, hypothesize how your independent variables might affect your dependent variables. Consider both direct and indirect relationships.

2. Review existing theories and literature:

Examine established theories and previous research in your field to support your hypothesized relationships. This helps ground your framework in existing knowledge and can provide insights into potential causal mechanisms.

3. Consider the direction of relationships:

Determine whether the relationships are positive (as one variable increases, the other increases) or negative (as one variable increases, the other decreases).

 4. Account for complexity:

Recognize that cause-and-effect relationships in social sciences are often complex. Multiple causes might lead to a single effect, or a single cause might have multiple effects.

5. Consider time factors:

Think about whether the effects are immediate or if there’s a time lag between the cause and the effect. This is particularly important in longitudinal studies. 

6. Examine potential mediators and moderators:

Consider how mediator variables might explain the mechanism of the cause-effect relationship, and how moderator variables might influence the strength or direction of these relationships.

7. Be aware of spurious relationships:

Consider whether any apparent cause-effect relationships might be due to other, unmeasured variables. This is where your control variables become important.

8. Use logical reasoning:

Ensure that your proposed cause-effect relationships make logical sense and can be explained theoretically.

9. Consider alternative explanations:

Think critically about other possible explanations for the relationships you’re proposing. This helps in developing a more robust framework.

10. Visualize the relationships:

Start sketching out how these cause-and-effect relationships might look in a diagram. This can help you see potential gaps or inconsistencies in your logic.

• In our academic performance study, we might hypothesize that:
• Increased study hours (independent variable) lead to improved grades (dependent variable).
• This relationship might be mediated by an improved understanding of the subject matter.
• The relationship might be moderated by student motivation, where highly motivated students see a stronger effect of study hours on grades.
• Teaching methods (another independent variable) might also influence grades, possibly through increased student engagement.

Remember, at this stage, you’re proposing these relationships based on theory and prior research. Your actual study will test these proposed cause-and-effect relationships. Be prepared to revise your framework if your findings don’t support your initial hypotheses.

Example of a conceptual framework

An example of a conceptual framework can help illustrate how all the elements we’ve discussed come together. 

Let’s use our academic performance study to create a sample conceptual framework.

Research Question:

“How do study hours and teaching methods affect high school students’ academic performance, and what role does student motivation play in this relationship?”

Conceptual Framework Example:

Explanation of the framework:

1. Independent Variables:

• Study Hours per Week
• Teaching Methods (Traditional vs. Interactive)

2. Dependent Variable:

• Academic Performance (measured by GPA and Standardized Test Scores)

3. Mediator:

• Understanding of Subject Matter (explains how study hours and teaching methods affect performance)

4. Moderator:

• Student Motivation (affects the strength of the relationship between independent and dependent variables)

 5. Control Variables:

• Socioeconomic Status
• Prior Academic Achievement

Proposed Relationships:

• Increased study hours are expected to lead to better academic performance.
• Interactive teaching methods are hypothesized to result in higher academic performance compared to traditional methods.
• The effect of study hours and teaching methods on academic performance is mediated by the student’s understanding of the subject matter.
• Student motivation moderates these relationships. For highly motivated students, the positive effects of study hours and interactive teaching methods on academic performance are expected to be stronger.
• The control variables are held constant to isolate the effects of the main variables of interest.

This conceptual framework visually represents the hypothesized relationships between variables. 

It shows how study hours and teaching methods (independent variables) are expected to influence academic performance (dependent variable), with the understanding of the subject matter as a mediator. 

Student motivation serves as a moderator, potentially affecting the strength of these relationships.

The framework also acknowledges the presence of control variables, which are important for the study but not the primary focus of the research question.

Conclusion  

Developing a conceptual framework is a critical step in research, providing structure and clarity to complex investigations. This article has outlined key steps in creating robust frameworks, emphasizing variable selection, relationship determination, and visual representation. 

A well-constructed framework, as illustrated in our academic performance example, integrates various elements into a comprehensive model. 

It’s important to remember that conceptual frameworks are dynamic, evolving with new insights. 

Ultimately, they serve as invaluable tools, guiding research processes and effectively communicating ideas, thus forming a solid foundation for knowledge advancement in any field.

Frequently asked questions  

What is a conceptual framework in research.

A conceptual framework in research is a structured approach to organizing and presenting the theoretical and conceptual underpinnings of a study. It visually or narratively explains the main variables, concepts, or constructs in a research project and how they are expected to relate to one another. Essentially, it’s a researcher’s map of the territory they plan to explore, showing the anticipated relationships between key elements of their study.

What are the 3 components of conceptual framework in research?

The three main components of a conceptual framework in research are:

• Variables: These include independent variables (factors that influence outcomes), dependent variables (outcomes being studied), and potentially mediating or moderating variables.
• Relationships: This component describes how the variables are expected to interact or influence each other, often based on existing theories or previous research.
• Context: This includes the broader theoretical background, assumptions, and limitations that frame the study and help explain why certain variables and relationships are being examined.

What are the three main types of conceptual frameworks for research?

The three main types of conceptual frameworks in research are:

• Descriptive Frameworks: These aim to identify, define, and describe the key concepts or variables in a study without necessarily proposing specific relationships between them.
• Explanatory Frameworks: These go beyond description to propose and explain relationships between variables, often drawing on existing theories to predict how and why certain factors influence outcomes.
• Predictive Frameworks: These frameworks not only describe and explain relationships but also aim to predict outcomes based on specific conditions or interventions.

What is the difference between theoretical and conceptual frameworks?

Theoretical and conceptual frameworks serve different roles in research. A theoretical framework focuses on existing theories relevant to the research topic , providing a broader context for understanding the problem. It draws from multiple theories to explain phenomena and positions the study within the larger body of knowledge in the field.

A conceptual framework, however , is specific to the particular study being conducted. It identifies and defines the key variables and concepts in the study, showing how these variables are expected to relate to each other. While it often incorporates elements from the theoretical framework, it applies them to the specific research context.

The conceptual framework is more practical, serving as a roadmap for the study by guiding data collection, analysis, and interpretation. It helps researchers visualize relationships between variables and clarify their hypotheses, bridging the gap between broad theories and the practical aspects of the research.

Dr. Marvin L. Smith

Dr. Marvin L. Smith, 45, is a tenured professor with over two decades of experience in his field. His research focuses on cutting-edge topics within his area of expertise, contributing significantly to the academic community. Dr. Smith has published numerous peer-reviewed articles in respected journals and authored several widely-used textbooks. Known for his ability to explain complex concepts clearly, he is a frequent contributor to academic and popular science publications. As a recognized expert, Dr. Smith often speaks at international conferences and continues to mentor the next generation of researchers. His work consistently pushes the boundaries of knowledge in his discipline. Dr. Marvin also write useful content on Medium and answer questions of young researchers and students on Quora .

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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

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• 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.

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Conceptual framework: the Basics and an Example

Conceptual Framework: this article explains the conceptual framework , also called a conceptual model , in a practical way. Next to what it is (defintion and theory), also the advantages important variables combined with an example are been shared in this article. After reading it, you will understand the basics of this research and analytic tool. Enjoy reading!

What is a conceptual framework? The theory

A conceptual framework can be defined as a visual representation in research that helps to illustrate the expected relationship between cause and effect . It is also called a conceptual model or research model. That means that different variables and the assumed relationships between those variables are included in the model and reflect the expectations.

This framework is a tool that is used prior to a study. This makes a conceptual framework an analytical tool. It is used to make conceptual distinctions and bring together different ideas. Strong conceptual frameworks lead to an actual realisation of the intended objective.

Origin of the conceptual framework

A conceptual framework originates in the financial reporting of accountancy. This is a default setting for practical problems to be tested objectively.

Thus, in a conceptual framework, fundamental financial issues are dealt with, including:

• What useful features does the accounting need?
• Which basic elements are we dealing with (assets, liabilities, equity, etc.)?
• What variables are needed for the preparation of the financial statements?

A conceptual framework of a research study: purpose and importance

In a conceptual model, the relationships are clearly defined between the different variables and their relationship to each other. Typically, the model is prepared before actual research takes place.

In addition, the type of research determines whether it is wise and useful to work with a conceptual framework. In testing research, the use of a conceptual framework is customary.

Based on hypotheses, a certain idea can be shown. The basis of testing research is to demonstrate the cause effect relationship, which is also reflected in the conceptual framework. In testing research, one works with specific expectations about cause and effect relationships, which are displayed in the schematic model.

Nevertheless, the model is also suitable for exploratory research. This often consists of broadly defined concepts instead of specifically defined variables. In this type of research, the specific relationships are identified afterwards and the variables are directly measurable and formulated fairly concretely.

Research Methods For Business Students Course A-Z guide to writing a rockstar Research Paper with a bulletproof Research Methodology!   More information

A conceptual framework example and its variables

In order to demonstrate the cause and effect relationship well, it is important to first chart the expectations within the conceptual framework and to divide the cause-effect relationship into variables. In this context, the variables are the characteristics that summarise the cause-and-effect relationship.

Suppose it is important for a fashion chain to run more sales through their online shop.

A number of variables come together in the conceptual model: 20% more revenue through the online shop, weekly Facebook promotions, the opportunity to get an additional 10% discount on the purchase within 24 hours after a visit and an improved appearance which allows online visitors to see the clothes from various angles.

In case of the cause-effect relationship, we now deal with two types of variables: the independent variables (Facebook promotion, 10% discount and improved appearance) and the dependent variable (20% more revenue). The dependent variable (result) is determined by the independent variables (causes).

The characteristics can influence each other and be directly related to each other. If the online shop has improved its appearance, visitors will spend more time looking for clothes and they will undoubtedly also see the offer to get 10% off now. Additionally, via Facebook promotions, visitors will be drawn to the online shop.

The only discussion that can arise is which unit can best be chosen to measure the variables. Also, conceptual questions arise, such as “what is meant by Facebook promotion” . To overcome this, it is suggested to make good and clear agreements in advance.

What does that look like?

In fact, the conceptual framework is a representation of a problem statement or research question. It also looks pretty simple. Once the independent and dependent variables have been determined, a conceptual framework can be started:

• Frameworks – The dependent and independent variables are drawn up in the frames.
• Arrows – the arrows between two concepts indicate that there is a causal link; where the arrow comes from influences where the arrow points to.
• Lines – where a relationship (correlation) between 2 variables is expected, but no connection, a line is used.

Figure 1- an example of a conceptual framework

Other influencing variables

Aside from the independent and dependent variables there are other variables that can come into play that influence the relationship between the independent and dependent variables.

Three common influencing variables are moderating variables, mediating variables and control variables. Below we will briefly explain all three of them.

A moderating variable changes the effect that an independent variable has on a dependent variable, making the outcome more or less effective.

In above example, a higher discount may affect the revenue differently when a customer has a lower income, as that customer might be more susceptible to purchase items on sale. ‘Income’ or, perhaps more accurately, ‘spending power’ will then be the moderating variable.

A mediating variable connects the independent and dependent variable as an explaining factor that impacts the outcome. In the example we are using this could be the ‘number of online visitors’ of the webshop. Facebook marketing intends to draw more potential customers to the webshop and the more visitors the online shop has, the greater chance of an increase in revenue.

To help distinguish between moderating and mediating variables, consider them in relation to the independent variable. A moderating variable is namely not affected by the independent variable, whereas a mediating variable is affected by the independent variable.

In our example, ‘spending power’ is not affected by ‘discount’ and the ‘number of online visitors’ is affected by ‘Facebook marketing’ .

A control variable is a variable that could affect the dependent variable, however it is held constant, so it doesn’t interfere with the outcome.

Using the same example, a control variable could be the ‘quality of internet connection’ . For instance, if the website is down or customers suddenly cannot access the webshop due to a bad internet connection, this will affect the revenue.

In this case we are not interested to research the effect of the internet connection, so we keep this control variable constant. This means we only include visitors with a working connection and a webshop that is live.

The advantages of using a conceptual framework

Working with a conceptual model has various advantages. First, the user is “forced” to think carefully about the variables and give them precise descriptions.

Now It’s Your Turn

What do you think? Are you using a conceptual framework in research or problem solving? Can you apply the conceptual model in today’s modern business companies? Do you recognize the practical explanation or do you have more suggestions? What are your success factors for problem analysis and researching?

Share your experience and knowledge in the comments box below.

More information

• Barick, R. (2021). Research Methods For Business Students . Retrieved 02/16/2024 from Udemy.
• Gartner, W. B. (1985). A conceptual framework for describing the phenomenon of new venture creation . Academy of management review , 10(4), 696-706.
• Seuring, S., & Müller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management . Journal of cleaner production, 16(15), 1699-1710.

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Patty Mulder

Patty Mulder is an Dutch expert on Management Skills, Personal Effectiveness and Business Communication. She is also a Content writer, Business Coach and Company Trainer and lives in the Netherlands (Europe). Note: all her articles are written in Dutch and we translated her articles to English!

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Defining The Conceptual Framework

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

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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 the 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

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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
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Revisiting theoretical frameworks

Revisiting conceptual frameworks, differences between conceptual and theoretical frameworks, examples of theoretical and conceptual frameworks, developing frameworks for your study.

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Conceptual vs. theoretical framework

Theoretical and conceptual frameworks are both essential components of research, guiding and structuring the research. Although they are closely related, the conceptual and theoretical framework in any research project serve distinct purposes and have different characteristics. In this section, we provide an overview of the key differences between theoretical and conceptual frameworks.

Theoretical and conceptual frameworks are foundational components of any research study. They each play a crucial role in guiding and structuring the research, from the formation of research questions to the interpretation of results .

While both the theoretical and conceptual framework provides a structure for a study, they serve different functions and can impact the research in distinct ways depending on how they are combined. These differences might seem subtle, but they can significantly impact your research design and outcomes, which is why it is important to think through each one of them.

The theoretical framework describes the broader lens through which the researcher views the topic and guides their overall understanding and approach. It connects the theoretical perspective to the data collection and data analysis strategy and offers a structure for organizing and interpreting the collected data.

On the other hand, the conceptual framework describes in detail and connects specific concepts and variables to illustrate potential relationships between them. It serves as a guide for assessing which aspects of the data are relevant and specifying how the research question is being answered. While the theoretical framework outlines how more abstract-level theories shape the study, the conceptual framework operationalizes the empirical observations that can be connected to theory and broader understanding.

Understanding these differences is crucial when designing and conducting your research study. In this chapter, we will look deeper at the distinctions between these types of frameworks, and how they interplay in qualitative research . We aim to provide you with a solid understanding of both, allowing you to effectively utilize them in your own research.

Theoretical frameworks play a central role in research, serving as the bedrock of any investigation. This section offers a refresher on the essential elements and functions of theoretical frameworks in research.

A theoretical framework refers to existing theory, concepts, and definitions that you use to collect relevant data and offer meaningful empirical findings. Providing an overall orientation or lens, it guides your understanding of the research problem and directs your approach to data collection and analysis .

Your chosen theoretical framework directly influences your research questions and methodological choices . It contains specific theories or sets of assumptions drawn from relevant disciplines—such as sociology, psychology, or economics—that you apply to understand your research topic. These existing models and concepts are tools to help you organize and make sense of your data.

The theoretical framework also plays a key role in crafting your research questions and objectives. By determining the theories that are relevant to your research, the theoretical framework shapes the nature and direction of your study. It's essential to note, however, that the theoretical framework's role in qualitative research is not to predict outcomes. Instead, it offers a broader structure to understand and interpret your data, enabling you to situate your findings within the broader academic discourse in a way that makes your research findings meaningful to you and your research audience.

Conceptual frameworks , though related to theoretical frameworks , serve distinct functions within research. This section reexamines the characteristics and functions of conceptual frameworks to provide a better understanding of their roles in qualitative research .

A conceptual framework, in essence, is a system of concepts, assumptions, and beliefs that supports and informs your research. It outlines the specific variables or concepts you'll examine in your study and proposes relationships between them. It's more detailed and specific than a theoretical framework, acting as a contextualized guide for the collection and interpretation of empirical data.

The main role of a conceptual framework is to illustrate the presumed relationships between the variables or concepts you're investigating. These variables or concepts, which you derive from your theoretical framework, are integral to your research questions , objectives, and hypotheses . The conceptual framework shows how you theorize these concepts are related, providing a visual or narrative model of your research.

A study's own conceptual framework plays a vital role in guiding the data collection process and the subsequent analysis . The conceptual framework specifies which data you need to collect and provides a structure for interpreting and making sense of the collected data. For instance, if your conceptual framework identifies a particular variable as impacting another, your data collection and analysis will be geared towards investigating this relationship.

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Though interconnected, theoretical and conceptual frameworks have distinct roles in research and contribute differently to the research. This section will contrast the two in terms of scope, purpose, their role in the research process, and their relationship to the data analysis strategy and research question .

Scope and purpose of theoretical and conceptual frameworks

Theoretical and conceptual frameworks differ fundamentally in their scope. Theoretical frameworks provide a broad and general view of the research problem, rooted in established theories. They explain phenomena by applying a particular theoretical lens. Conceptual frameworks, on the other hand, offer a more focused view of the specific research problem. They explicitly outline the concrete concepts and variables involved in the study and the relationships between them.

While both frameworks guide the research process, they do so in different ways. Theoretical frameworks guide the overall approach to understanding the research problem by indicating the broader conversation the researcher is contributing to and shaping the research questions.

Conceptual frameworks provide a map for the study, guiding the data collection and interpretation process, including what variables or concepts to explore and how to analyze them.

Study design and data analysis

The two types of frameworks relate differently to the research question and design. The theoretical framework often inspires the research question based on previous theories' predictions or understanding about the phenomena under investigation. A conceptual framework then emerges from the research question, providing a contextualized structure for what exactly the research will explore.

Theoretical and conceptual frameworks also play distinct roles in data analysis. Theoretical frameworks provide the lens for interpreting the data, informing what kinds of themes and patterns might be relevant. Conceptual frameworks, however, present the variables concepts and variables and the relationships among them that will be analyzed. Conceptual frameworks may illustrate concepts and relationships based on previous theory, but they can also include novel concepts or relationships that stem from the particular context being studied.

Finally, the two types of frameworks relate differently to the research question and design. The theoretical framework basically differs from the conceptual framework in that it often inspires the research question based on the theories' predictions about the phenomena under investigation. A conceptual framework, on the other hand, emerges from the research question, providing a structure for investigating it.

Using case studies , we can effectively demonstrate the differences between theoretical and conceptual frameworks. Let’s take a look at some real-world examples that highlight the unique role and function of each framework within a research context.

Consider a study exploring the impact of classroom environments on student learning outcomes. The theoretical framework might be grounded in Piaget's theory of cognitive development, which offers a broad lens for understanding how students learn and process information.

Within this theoretical framework, the researcher formulates the conceptual framework. The conceptual framework identifies specific variables to study such as classroom layout, teacher-student ratio, availability of learning materials, and student performance as the dependent variable. It then outlines the expected relationships between these variables, such as proposing that a lower teacher-student ratio and well-equipped classrooms positively impact student performance.

Another study might aim to understand the factors influencing the job satisfaction of employees in a corporate setting. The theoretical framework could be based on Maslow's hierarchy of needs, interpreting job satisfaction in terms of fulfilling employees' physiological, safety, social, esteem, and self-actualization needs.

From this theoretical perspective, the researcher constructs the conceptual framework, identifying specific variables such as salary (physiological needs), job security (safety needs), teamwork (social needs), recognition (esteem needs), and career development opportunities (self-actualization needs). The conceptual framework proposes relationships among these variables and job satisfaction, such as higher salaries and more recognition being related to higher job satisfaction.

After understanding the unique roles and functions of these types of frameworks, you might ask: How do I develop them for my study? It's essential to remember that it's not a question of choosing one over the other, as both frameworks can and often do coexist within the same research project.

The choice of a theoretical and a conceptual framework often depends on the nature of your research question . If your research question is more exploratory and requires a broad understanding of the problem, a theoretical framework can provide a useful lens for interpretation. However, your conceptual framework may end up looking rather different to previous theory as you collect data and discover new concepts or relationships.

Consider the nature of your research problem as well. If you are studying a well-researched problem and there are established theories about it, using a theoretical framework to interpret your findings in light of these theories might be beneficial. But if your study explores a novel problem or aims to understand specific processes or relationships, developing a conceptual framework that maps these specific elements could prove more effective.

Your research methodology could also inform your choice. If your study is more interpretive and aims to understand people's experiences and perceptions, a theoretical framework can outline broader concepts that are relevant to approaching your study. Your conceptual framework can then shed light on the specific concepts that emerged in your data. By carefully thinking through your theoretical and conceptual frameworks, you can effectively utilize both types of frameworks in your research, ensuring a solid foundation for your study.

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Conceptual Framework in Research

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A conceptual framework in research organizes the key concepts and their relationships for a study, incorporating elements like the “ Theoretical Framework ” and the broader “ Research Framework .” It guides the research design and methodology, clarifying the study’s scope and structure.

What is Conceptual Framework in Research?

A conceptual framework facilitates communication between the researcher and their audience, including other scholars, practitioners, and stakeholders. It helps ensure that the research is coherent, logically structured, and aligned with existing theories and literature. By mapping out the theoretical underpinnings of the research, the framework aids in highlighting the significance of the study, identifying gaps in knowledge, and justifying the research approach. Overall, a well-developed crisis Communication framework enhances the rigor and clarity of a research project, making it a crucial element in the research process.

50 Examples of Conceptual Framework in Research

• Impact of Technology on Student Learning : Technology use, student engagement, academic performance
• Parental Involvement and Student Achievement : Parental involvement, student motivation, academic outcomes
• Teaching Methods and Student Retention : Teaching methods, student retention rates, classroom environment
• Effects of Classroom Environment on Learning : Classroom design, student concentration, learning outcomes
• Teacher-Student Relationships and Academic Success : Teacher-student interaction, student confidence, academic performance
• Diet and Physical Health in Adolescents : Nutritional intake, physical activity, health outcomes
• Mental Health and Academic Performance in College Students : Mental health status, academic performance, stress levels
• Impact of Sleep on Cognitive Functioning : Sleep duration, cognitive performance, mood
• Exercise and Mental Health in Adults : Physical activity, mental well-being, stress levels
• Public Health Interventions and Disease Prevention : Health campaigns, disease incidence, public awareness
• Customer Satisfaction and Brand Loyalty : Customer satisfaction, brand loyalty, purchase behavior
• Impact of Leadership Styles on Employee Performance : Leadership style, employee motivation, performance outcomes
• Corporate Social Responsibility and Brand Image : CSR activities, brand perception, consumer trust
• Digital Marketing and Consumer Engagement : Marketing strategies, consumer interaction, sales
• Workplace Environment and Employee Productivity : Office design, employee satisfaction, productivity levels
• Stress and Coping Mechanisms in Adolescents : Stress levels, coping strategies, psychological outcomes
• Effect of Childhood Trauma on Adult Behavior : Childhood experiences, behavioral patterns, mental health
• Impact of Social Media on Self-Esteem : Social media usage, self-esteem levels, social comparison
• Parenting Styles and Child Development : Parenting techniques, child behavior, developmental milestones
• Relationship Between Personality Traits and Career Success : Personality traits, career advancement, job satisfaction
• Urbanization and Quality of Life : Urban development, living conditions, community satisfaction
• Impact of Immigration on Social Integration : Immigration status, social networks, integration levels
• Gender Roles and Career Choices : Gender expectations, career aspirations, occupational outcomes
• Social Media Influence on Public Opinion : Social media activity, public attitudes, information dissemination
• Poverty and Educational Opportunities : Socioeconomic status, access to education, academic achievement
• Climate Change and Agricultural Productivity : Climate patterns, crop yield, farming practices
• Sustainable Practices and Environmental Conservation : Sustainable methods, environmental impact, conservation success
• Impact of Pollution on Public Health : Pollution levels, health conditions, mortality rates
• Renewable Energy Adoption and Economic Growth : Renewable energy use, economic indicators, employment rates
• Biodiversity Loss and Ecosystem Stability : Species diversity, ecosystem functions, environmental health
• Artificial Intelligence and Job Market Dynamics : AI implementation, job displacement, economic trends
• Cybersecurity and Data Privacy : Security measures, data breaches, user trust
• E-Learning Platforms and Student Performance : Online education, student engagement, academic results
• Impact of Mobile Technology on Communication : Mobile device usage, communication patterns, social relationships
• Smart Homes and Energy Efficiency : Smart technology, energy consumption, cost savings
• Inflation and Consumer Spending : Inflation rates, consumer behavior, economic stability
• Microfinance and Small Business Growth : Microfinance access, business development, income levels
• Globalization and Economic Inequality : Global trade, income disparity, economic policies
• Tax Policies and Business Investment : Tax rates, investment levels, business growth
• Unemployment and Mental Health : Employment status, mental well-being, societal impact
• Democracy and Political Stability : Democratic institutions, political stability, public trust
• Impact of Political Campaigns on Voter Behavior : Campaign strategies, voter turnout, election results
• Public Policy and Social Welfare : Policy initiatives, welfare programs, public health
• International Relations and Peacebuilding : Diplomatic efforts, conflict resolution, peace treaties
• Government Transparency and Public Trust : Transparency measures, corruption levels, civic engagement
• Media Coverage and Public Perception of Events : Media representation, public opinion, event outcomes
• Interpersonal Communication and Relationship Satisfaction : Communication styles, relationship quality, conflict resolution
• Advertising Strategies and Consumer Behavior : Marketing techniques, consumer response, sales impact
• Crisis Communication and Organizational Reputation : Crisis management, communication effectiveness, reputation recovery
• Digital Communication and Information Dissemination : Digital platforms, information spread, public awareness

Conceptual Framework Example in Experimental Research

• Impact of Online Learning Tools on Student Performance
• Effect of Diet on Cognitive Function
• Influence of Exercise on Mental Health
• Effect of Teaching Methods on Student Engagement
• Impact of Sleep on Academic Performance

Conceptual Framework Example in Research Paper

• Effect of Social Media on Academic Performance
• Impact of Workplace Diversity on Employee Productivity
• Influence of Parental Involvement on Children’s Academic Success
• Effect of Marketing Strategies on Consumer Behavior
• Impact of Climate Change on Agricultural Productivity

Types of Conceptual Framework in Research

Descriptive Framework

A descriptive framework outlines the main variables and concepts without specifying the relationships between them. It provides a detailed description of the phenomenon being studied and organizes information logically.

• Use Case : Suitable for exploratory studies where the aim is to understand the characteristics and components of a subject.
• Example : A framework describing the key elements of digital marketing strategies.

Analytical Framework

An analytical framework specifies the relationships between variables and often includes hypotheses or propositions. It helps in analyzing how and why certain variables influence others.

• Use Case : Ideal for studies aiming to test theories or hypotheses.
• Example : A framework analyzing the impact of employee motivation on job performance.

Relational Framework

A relational framework focuses on the connections between variables, illustrating how they interact with each other. It is particularly useful for studies that investigate cause-and-effect relationships.

• Use Case : Suitable for causal studies.
• Example : A framework showing the relationship between social media usage and mental health.

Predictive Framework

A predictive framework uses established theories and empirical data to forecast outcomes based on specific variables. It aims to predict future events or behaviors.

• Use Case : Appropriate for studies intending to predict trends or future developments.
• Example : A framework predicting student success based on study habits and access to resources.

Interpretive Framework

An interpretive framework is based on qualitative data and seeks to understand the meanings and experiences of participants. It is rooted in the interpretive paradigm, focusing on how individuals construct their realities.

• Use Case : Best for qualitative research studies.
• Example : A framework exploring the lived experiences of immigrants in a new country.

Theoretical Framework

A theoretical framework is built upon existing theories and models. It provides a structured approach to examining a research problem, grounding the study in established theoretical constructs.

• Use Case : Essential for research that tests or expands existing theories.
• Example : A framework based on Maslow’s Hierarchy of Needs to study employee satisfaction.

Logical Framework

A logical framework, often used in project management and evaluation studies, outlines the logical relationships between inputs, activities, outputs, outcomes, and impacts. It is also known as a logical framework matrix (logframe).

• Use Case : Common in program evaluation and project planning.
• Example : A framework for evaluating the effectiveness of a community health intervention.

Contextual Framework

A contextual framework considers the broader context within which the research is conducted. It incorporates external factors that might influence the study, such as cultural, social, economic, and environmental conditions.

• Use Case : Useful for research that examines the influence of external factors.
• Example : A framework studying the impact of economic policies on small business growth.

Usage of Conceptual Framework in Research

1. defining the research problem.

• Clarifies the Scope : The conceptual framework helps in narrowing down the research problem by identifying specific variables and their relationships.
• Focuses the Study : It ensures the research stays focused on the key issues and does not deviate into unrelated areas.

2. Organizing Literature Review

• Identifies Key Concepts : Helps in organizing the literature review around the key concepts and theories relevant to the study.
• Guides Literature Search : Directs the search for relevant literature by highlighting the main themes and variables.

3. Guiding Research Design and Methodology

• Informs Methodology : Influences the choice of research design, methods of data collection, and analysis by outlining the relationships between variables.
• Enhances Validity : Ensures that the research design is aligned with the theoretical foundations and objectives of the study.

4. Hypothesis Formulation

• Develops Hypotheses : Assists in formulating clear and testable hypotheses based on the relationships identified in the framework.
• Predicts Relationships : Provides a basis for predicting how variables interact and what outcomes can be expected.

5. Data Collection and Analysis

• Guides Data Collection : Helps in determining what data to collect and from where, ensuring all relevant variables are measured.
• Facilitates Data Analysis : Provides a structure for analyzing data by outlining the expected relationships and interactions between variables.

Differences between Conceptual Framework and Theoretical Framework

How do I write my conceptual framework

Step-by-step guide, 1. identify the research problem.

• Clearly define the problem you aim to investigate.
• Example: “How does online learning impact student performance?”

2. Conduct a Literature Review

• Review existing studies, theories, and models related to your topic.
• Identify key concepts and variables from the literature.

3. Define Key Variables

• Independent Variables : Factors you manipulate or change (e.g., types of online learning tools).
• Dependent Variables : Outcomes you measure (e.g., student grades).
• Moderating Variables : Factors that might influence the relationship (e.g., internet access).
• Mediating Variables : Factors that explain the relationship (e.g., student engagement).

4. Develop Hypotheses

• Formulate statements that predict the relationship between variables.
• Example: “Students using interactive online tools will have higher grades.”

5. Create the Framework

• Visual Representation : Use diagrams to show the relationships between variables.
• Narrative Description : Write a clear explanation of how these variables are connected.

Tips for Conceptual Framework in Research

• Seek Feedback
• Ensure Clarity and Simplicity
• Establish Relationships
• Identify Key Variables
• Review Related Literature:
• Understand Your Research Goals

Why is a conceptual framework important?

A conceptual framework guides the research by defining the scope and focus. It helps to clarify the research questions, hypotheses, and the overall direction of the study.

How is a conceptual framework different from a theoretical framework?

A conceptual framework is more specific and directly related to the research problem, while a theoretical framework is broader, encompassing existing theories relevant to the topic.

What are the main components of a conceptual framework?

The main components include the key variables, their definitions, and the hypothesized relationships between them.

Can a conceptual framework change during the research process?

Yes, a conceptual framework can evolve as new insights are gained during the research process. It should be flexible enough to accommodate changes based on findings.

How detailed should a conceptual framework be?

The level of detail depends on the complexity of the research. It should be comprehensive enough to cover all relevant variables and relationships but not overly complicated.

How do conceptual frameworks aid in data analysis?

Conceptual frameworks help in identifying key variables and their relationships, guiding the data collection and analysis process to ensure alignment with the research objectives.

What is the difference between a model and a conceptual framework?

A model is a specific representation of a concept or system, often used to predict outcomes. A conceptual framework is broader, outlining the relationships between concepts without necessarily predicting specific outcomes.

Can a conceptual framework include hypotheses?

Yes, a conceptual framework can include hypotheses that propose expected relationships between variables.

What challenges might arise when developing a conceptual framework?

Challenges include identifying relevant variables, defining their relationships, and ensuring the framework is comprehensive yet manageable.

Text prompt

• Instructive
• Professional

10 Examples of Public speaking

20 Examples of Gas lighting

An Example of a Conceptual Framework with Statement of the Problem

This article shows an example of a conceptual framework. It demonstrates how a conceptual framework and the corresponding statement of the problem are organized and written in a dissertation. Take a look at how it is done, and try to make one for your paper. You may also use this in your thesis.

You may be thinking about too many theories to base your study on. However, a conceptual framework is inbuilt on a theory or model that serves as the basis for your research. Once you have decided which theory to adopt, try to figure out if that theory can best explain the phenomenon with all the associated variables in your study. The example below illustrates how this works.

Example of a Conceptual Framework

This example of a conceptual framework zeroes in on teachers’ professional development activities by espousing the idea. main argument, or thesis that teachers’ classroom performance is a critical factor for student academic performance. The researcher based her assumption from Weiner’s Attribution Theory that external and internal factors can improve performance.

Statement of the Problem

The purpose of this study is to provide baseline data on in-service training for English, Mathematics, and Science Fourth Year High School teachers from the School Year 2006 up to 2010. Also, a professional development model for teachers is proposed.

Specifically, this study sought answers to the following questions:

Organized Flow of Ideas Characterize a Conceptual Framework

Now, you have learned how a theory is used and how the questions in the problem statement are formulated. Take note that the problem statement questions are arranged according to the flow of the conceptual framework.

First, it has questions on an inventory of in-service training activities , followed by the feedback . The next question is about teacher factors , then the results of student performance . The last question relates to the development of the enhanced professional development model .

Notice that all of the factors identified in the study serve as input to the final outcome of the study which is the enhanced professional development model. It is easy to conceptualize what the researcher is trying to incorporate in the training design for teachers’ professional development. It is a systematic representation of the intention, direction, and outcome of the study.

Can you make it? Yes, you can!

© 2015 January 19 M. G. Alvior Updated: 15 December 2020; 14 October 2023

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Information system and decision making: 3 essential components for effective management, how to slow down your heart rate through aerobics, the essentials of english as a medium of instruction (emi) in ph, about the author, mary g. alvior, phd.

Dr. Mary Gillesania Alvior has PhD in Curriculum Development from West Visayas State University. She earned her Master of Arts in Teaching English from De La Salle University, Manila as Commission on Higher Education (CHED) scholar. As academic advisor, she helps learners succeed in their academic careers by providing them the necessary skills and tips in order to survive in this wobbling financial environment. In 2014, she got involved in the establishment of a language institute in the Middle East, particularly in the use of Common European Framework of Reference for Languages (CEFR). Then she went to Thailand and became a lecturer in the international college and handled English and Graduate Education courses. From 2017 to 2021, she became the Focal Person for the Establishment of a Medical School, Director of Curriculum and Instructional Materials Development Office (CIMDO), Head of BAC Secretariat, Quality Management System (QMS) Leader, and TWG member of the Procurement for Medical Equipment. Currently, she is the coordinator of the Project Management Committee for the Establishment of the Medical School. In spite of numerous tasks, she is into data privacy, quality management system, and space industry.

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• Open access
• Published: 16 August 2024

Exploring community-based participatory research for household and ambient air pollution projects: insights from key informants

• Eunice Phillip 1 ,
• Aisling Walsh 1 ,
• Sarah Jewitt 2 ,
• Farah Elnakoury 3 ,
• Joella Simon 3 ,
• Ronán M Conroy 1 &
• Debbi Stanistreet 1  

BMC Public Health volume  24 , Article number:  2233 ( 2024 ) Cite this article

126 Accesses

Metrics details

Despite the extensive use of community-based participatory research (CBPR) in health-related projects, there is limited work on how CBPR processes result in outcomes, especially in household and ambient air pollution (HAAP) research. This study explores the reflections of key informants on factors that shape the implementation and outcomes of CBPR in HAAP projects.

We conducted semi-structured interviews with 13 key stakeholders, including academic researchers, non-governmental organisation administrators, a policymaker, and community members. All interviewees have experience in CBPR projects. Interviews were analysed using framework analysis, and findings were mapped to Wallerstein et al.’s CBPR conceptual model, which consists of four constructs: context, partnership processes, intervention and research, and outcomes.

The findings are described under two main categories: ‘barriers to participation’ and ‘good practices for effective CBPR design and implementation’. Relevant sub-categories were barriers at the structural, research, community, and individual levels. Suggestions for good practices included respect, cultural humility, trust, effective communication, suitable and affordable interventions such as improved cookstoves, appropriate participatory research tools, and gratuity for the community’s time.

Key informants’ perspectives identified factors supported by the CBPR model to inform the design and implementation of the CBPR approach. The add-ons to some of the model’s factors, such as intra-community dynamics, give value to the informants’ knowledge to support community-research partnerships and improve outcomes in HAAP intervention projects. Addressing these factors at the design stage and reporting CBPR evaluation could deepen the understanding of community-research partnerships.

Peer Review reports

Poor access to, and affordability of clean and modern energy leaves most households in low-income communities/countries (LICs) exposed to pollutants from burning biomass fuels (e.g., wood, charcoal, or dung) on inefficient stoves in poorly ventilated dwellings. The pollutants, which include small particulate matter (PM 2·5 ), carbon monoxide and nitrogen oxides, are linked to ill health and death due to chronic respiratory diseases, cardiovascular diseases, and stillbirth [ 1 , 2 , 3 , 4 ]. They also contribute to climate change [ 4 ]. Studies of uptake and sustained use of interim solutions such as improved biomass cookstoves and kitchen ventilation have identified several barriers. These barriers include cost, effectiveness and, notably, limited user involvement in the design, implementation, and delivery of HAAP interventions [ 5 , 6 ]. Addressing these barriers could improve outcomes of sustainable development goals (SDGs) 7.1 (access to affordable, reliable, and modern energy) [ 7 ], 3.9 (reduce mortality from environmental pollution) [ 8 ], and 13.3 (build knowledge and capacity to meet climate change) [ 9 ].

Evidence suggests that participatory approaches, such as CBPR, participatory action research and community-engaged research, are essential to improving health and power disparities in health research, especially in vulnerable communities [ 10 , 11 ]. Reports show that CBPR contributes to the effective delivery and adoption of complex interventions aimed at improving health outcomes in projects such as HIV/AIDS [ 12 , 13 ], water and sanitation [ 14 , 15 ], and improved cookstoves [ 16 ]. Furthermore, the CBPR approach can lead to community-level systemic changes, enhanced learning opportunities, sustained health efforts, spin-off projects, enhanced community capacity, co-governance, and project sustainability beyond its lifespan [ 17 , 18 , 19 ].

Some of these benefits, such as the sustained use of interventions and systemic changes, suggest that CBPR can durably increase the uptake and adoption of HAAP interventions. For example, Jerneck and Olsson [ 16 ] tied their project’s success to CBPR. Improvements in their cookstove design, production, and adoption were augmented by engaging a small farming community in sub-Saharan Africa (SSA) in cleaner cooking and reducing carbon emissions [ 16 ]. Similarly, in Matavel et al.’s study [ 20 ], the adoption of improved cookstoves in 40 communities in central Mozambique was stimulated by enhancing their capacity-building through training and involving the community in cookstove design, implementation, and maintenance. However, Ronzi et al., found that engaging and incorporating participants’ perspectives at all stages did not necessarily lead to the uptake of cleaner cooking fuels [ 21 ]. Although their study associated the low uptake with socio-economic factors, no link was made between the CBPR approach and the study outcomes, representing a gap in HAAP studies [ 22 ].

An enhanced understanding of participatory factors such as those described in Wallerstein et al.’s CBPR conceptual model could be essential to support equitable community and academic partnerships that inform and improve the sustainability of air pollution interventions. Wallerstein et al.’s CBPR conceptual model [ 10 ] identifies how dynamic interactions across four domains (contexts, partnership processes, intervention and research, and outcomes) facilitate the adaptation of CBPR principles in ways that create equitable partnerships and project outcomes (Fig.  1 ). Empirical testing of this model for its validity and suitability in describing the relational pathway of the CBPR constructs [ 23 , 24 , 25 ] made it suitable for mapping informants’ perceptions of factors that shape the operationalisation of CBPR in health-related projects in LICs. This study drew on the experiences of key informants (KI) of implementing CBPR in low-income contexts to inform the design and implementation of Wallerstein et al.’s CBPR conceptual model for a HAAP study.

Wallerstein et al.‘s CBPR conceptual model. Available at https://engageforequity.org/cbpr-model/full-model/ re-accessed 24/07/2023

This study is part of ‘The Smokeless Village Project’ (TSVP), an intervention project aimed at using a community-led approach to reduce household and ambient pollution in a rural community in Malawi. The project is described here: https://www.rcsi.com/impact/details/2023/03/a-community-led-approach-to-improving-health-in-malawi and further in a previous study which explored existing community practices and their relationship with HAAP [ 26 ].

This paper employed a qualitative method to explore the individual experiences of 13 key informants who had experience in CBPR health intervention projects in LICs.

The study was approved by the College of Medicine Research and Research Ethical Committee , Blantyre, Malawi (P.03/21/3279) and the Research Ethics Committee , Royal College of Surgeons in Ireland (RCSI) , Dublin, Ireland (212558360).

Sampling of participants

Participants were identified using purposive sampling drawn mainly from the TSVP research team and steering group members. For community-member participants, community leaders at the TSVP site suggested members who have been active in community development projects. Additional information on sampling and recruitment is available in Additional File 1.

The study sample ( n  = 13) consisted of six academic researchers (group A), one policymaker and one non-governmental organisation (NGO) leader (group B), and five community members (group C). The five academic researchers were from high-income countries (HICs), while all other participants were from LICs. All group A members had extensive social research experience, and all participants had CBPR experience in LICs (Table  1 ).

Data collection

Between August and November 2021, EP, a PhD researcher, carried out the semi-structured interviews. An interview guide informed by Israel et al.’s nine principles of CBPR [ 27 ] was developed for each participant group by EP under the guidance of experienced qualitative researchers AW, DS, and SJ. The nine principles are a set of guides to facilitate commitment to equity and power sharing in research processes and actions [ 27 ]. The interview guides focused on the following:

Participants’ engagement in, and description of past health-related research or projects.

Reflections of the participatory approach processes, including barriers and facilitators.

Recommendations for designing and implementing the CBPR approach for a planned HAAP project.

All interviews were carried out in the English language except for three community member interviews, which were conducted in the Chichewa language. In this instance, an interpreter who was not a community member (to ensure confidentiality) was hired to assist with translation. All the participants received an information leaflet, and written consent was obtained prior to the interviews. Each interview lasted approximately one hour and was audio (face-to-face) and video (Microsoft Teams ® ) recorded.

Data analysis

We followed Gale et al.’s seven steps to framework analysis method [ 28 ]. A full description of our analysis is provided in Additional file 2 and described briefly here. Analysis included verbatim transcription of all interviews and familiarisation by reading through and cross-checking with the recordings [ 28 ]. Transcripts were open coded inductively and assigned descriptive labels. The labels were reviewed and grouped to form a working analytic framework to code and index the transcripts. Recurring codes were grouped as categories and sub-categories and subsequently merged and/or relabelled as needed (see Additional file 3). Each participant’s responses were summarised and charted in the corresponding cells of the framework matrix (See Additional files 4 and 5). Patterns compared within and across the participant’s groups aided the interpretation and reporting of findings. We subsequently mapped the findings to Wallerstein et al.’s CBPR conceptual model in our discussion session. Analysis was done in NVivo analysis software (Version 12) [ 29 ] and in Excel ® .

The two categories identified are ‘barriers to participation’ and ‘good practices to effective CBPR design and implementation’ (Fig.  2 ). Barriers to participation were captured under four sub-categories at four levels: ‘structural’; ‘research’; ‘community’; and ‘individual’ levels. Subcategories within the CBPR good practices category include ‘promoting participation’ and ‘enhancing sustainability’.

Barriers to participation

Informants were asked about operationalising the CBPR approach based on their experience with health intervention projects. Their responses featured several barriers at the structural, research, community, and personal levels (Fig.  2 )

Barriers to participation and good practice for sustained intervention use and behaviour change: The figure shows the interlinking and multi-level categories and sub-categories of factors associated with operationalising CBBR in health research from participants’ reflections and experiences

Structural level barriers

Informants in groups A and B reflected on the challenges of research funding and the technical difficulties of involving the community at every stage of the research. They emphasised that the funding system and ethical approval requirements sometimes limit active community involvement at certain stages, such as the research proposal stage, as quoted below.

“It’s kind of a chicken and egg situation , really. You want to involve the community from the beginning. It is simply not possible at the proposal stage. From a pragmatic view , you don’t know who the community is going to be , even if you know , not having ethical approval would make it very difficult to have active involvement in project design.” – KI1 .

Limitations could also arise at the analysis level, where potential confidentiality issues may occur with access to other community members’ data. While leveraging existing community skills and providing training in research methods could enhance the community’s capacity to engage with analysis (KI5), barriers such as limited funds, insufficient training time, and a lack of community interest in learning at this research level could limit involvement.

“I think this depends on the nature of the funding, time, the capacity of the community and the extent the people want to be involved.” – KI3.

Other related funding issues include the attention drawn to the appropriateness of offering incentives to participate and the prescriptive nature of many research funding calls.

Research level barriers

At the research level, disregarding the community’s existing social and cultural values (i.e., positions assigned to different people based on their gender or economic status) and leadership and communication structures (i.e., positions accorded to people to communicate on behalf of the community) were viewed by informants as a barrier to effective CBPR implementation and community–research dynamics. According to a group A informant, discounting these community structures could limit communication and sharing of information.

“ …Because once people know that you are an outsider, you’re coming in and denigrating or rejecting their worldview…, it could be disastrous. I don’t think you can effectively engage or collaborate with [the] people” – KI4 .

Similarly, the assumed power and superior knowledge accorded to the research team — mostly from being the custodians of the finances or interventions — can inhibit the community’s contribution to knowledge creation.

“And there’s this kind of big headedness , I suppose , when we design for people that maybe haven’t got as much as we have.” – KI5 .

Another significant barrier at the research level was the introduction of unaffordable and unsuitable interventions to the community, resulting in a lack of interest and engagement with the interventions. An informant from group B exemplified this from his experience in the Malawi rural electrification project. He stated:

“People were not buying it [electricity credit] … We realised that most people in the rural areas could not afford to pay the initial connection fees.” – KI9 .

In addition, the use of non-participatory research tools and communication techniques were highlighted as barriers to the exchange of information and knowledge that inhibit participation. Conflict-related factors such as a mismatch between the research priorities and the community’s needs (KI2, KI5, KI6, KI9, KI10, KI12) and the use of community resources such as land space for research purposes (KI2) were also highlighted as inhibiting participation.

Community level barriers

Regarding community-level barriers, some group A informants mentioned the leaders’ influence on who participates or gets sampled in the community as limiting inclusive participation.

“They [leaders] are going to be the people we engage with initially…But I wonder , and we often wonder , when we’re thinking about community participation , do some people get left behind? Or perhaps not included.” – KI3 .

Notably, all informants described the involvement of community leaders and engagement with insider knowledge as valuable to gaining entry to, and engaging with, the whole community. However, power dynamics and gender imbalances were mostly noted as a hindrance to inclusive community participatory decision-making activities.

“When it comes to men and women , men are always a bit more dominant. They want to speak out more than the women. We had both men and women together , and we noticed women were not speaking up.” – KI8 .

Other barriers at this level include existing friction within the community (KI2, KI6, KI8), mistrust from past research experience or the community’s perception of ulterior research motives (KI1, KI2), and uninterested due to the research burden (KI2).

Individual level barriers

Discussions of barriers to participation in research at the individual level by group A and B informants included limited time to engage (away to earn a living), low capacity to engage (physical illness), and intimidation or self-stigma (from low education or economic status, especially when in groups with educated or affluent community members). However, most informants in group C associated barriers to participation with a lack of motivation linked to the absence of incentives.

“Some will not join in if there is nothing [financial incentives] in it for them. otherwise , some are just lazy to join.” – KI10 .

Good practices for effective CBPR design and implementation in HAAP

The uptake and sustained use of interventions such as improved cookstoves to address air pollution solutions remains a challenge. We asked the key informants to provide suggestions based on their experiences to inform the design and implementation of CBPR in our planned HAAP project [ 26 ]. Their proposed ideas were captured as ‘promoting participation’ and ‘sustainability’. We sub-categorised sustainability as ‘sustained behavioural change’ and ‘sustained use of HAAP interventions’ (See Fig.  2 ).

Promoting participation

This subcategory describes informants’ outlooks on ways to facilitate active and effective community participation and engagement in HAAP research.

The value of not ‘demeaning people’s worldview’ and respecting the community’s culture and values was echoed across the informants as core to reducing conflict and promoting interest and total community participation. To achieve this, several informants recommend being culturally sensitive and addressing one’s bias and preconceived beliefs about the community’s social, cultural, gender, and decision-making structure at household and community levels.

“Even if you find it almost distasteful because it doesn’t sit with your idea of gendered relationships or whatever, and it’s really important that you don’t impose any of your own values. This means recognising and respecting that is the way the community works. “ – KI1 .

Despite this, some group A informants cautioned against associating limited decision-making power only to gender, citing examples of (1) cultural norms, as women may also “shut down” when they are in an all-women group with their ‘apongozi akazi’ (mother-in-law)–KI5, (2) “more influential people pushing the decision-making agenda” –KI2, and (3) people not wanting to be the “dissenting voice” when leaders have spoken–KI8. With these different dimensions of socio-cultural sensitivity, KI1 and KI2 advise “to get a handle” on what the community priorities are and invest time to understand “where the strength lies” , especially in relation to gender roles in HAAP.

Also cited as essential to community participation is effective communication. Informants focused this on ‘who’ is delivering, to ‘whom’, ‘when’, ‘how’, and the content of the message. The informants unanimously believed that ‘who’ delivers the message must be trusted and respected within the community. This supports the importance of insider knowledge (insights gained from individuals who are familiar with the community [ 30 ]) in guiding participatory processes like the provision of a safe place for engagement (KI4). The trusted person could include a religious authority (KI6), influential and/or community leaders (KI11, KI12), and local researchers who are well-placed to lead communication, primarily because of language advantage.

“To some extent , we’ll be relying on the Malawian colleague. By definition , they have a better understanding , particularly through language , of what those issues (cultural , gender issues) are. We need to be guided by them.” – KI1 .

One informant was critical of getting fixated on insider knowledge and highlighted the need to source some outsider perspectives (insights gained from individuals who are external or have no direct affiliation with the community being studied [ 30 ]).

“For that different perspective.you think about things differently from a cultural perspective. You think of asking some of the questions that people who were very close to the community might not think of asking , and I think that set of external eyes is really important.” – KI3 .

All group A informants judged who gets the messages and when as being essential to effective collaboration and project buy-ins. They drew attention to the importance of addressing the entire community at an early stage, irrespective of the community segment with the highest HAAP health burden or those being targeted for the interventions.

“One of the important things to do is make sure you’ve got everybody on your side. It’s not enough to convince the women about a cleaner stove… that message needs to get through to everybody so that everybody understands the impact of household air pollution and how engaging can benefit everyone.” – KI1.

In addition to communicating the project’s direct benefits, such as improved health outcomes (KI9, KI10), informants mentioned that indirect benefits of participation should also be communicated to motivate and facilitate community engagement. Such messages could include “how the community are an active part of creating solutions to HAAP issues” (KI1) or being employed on the project (KI9). And while knowledge exchange is needed to promote participation, one group A informant cautioned against doing all the talking, but to “use your eyes and ears. You’ll learn a lot that way” (KI6).

Also common among the informant groups was acknowledging and respecting the community’s invested time with monetary or other valuable incentives. This expectation was expressed by a group A informant as a source of caution to avoid conflict and by a group C informant as a source of motivation to engage with the interventions (KI11).

“As a researcher , you kind of feel I’m not an NGO with a big pot of money. But what’s in it for them [community] to give up their time? …having that feeling that research is getting in the way of their lives and they might resent it.” – KI2 .

Once the community is on board, providing a clear definition of their roles within the project can reduce ambiguous boundaries within the community-research partnership. Several informants remarked that definitions should centre on equitable power-sharing partnerships (KI1, KI3, KI11) with the existing community’s skills and knowledge (KI2, KI3, KI5, KI6, KI12) and the community’s capacity to make decisions to engage (KI1, KI3, KI5).

“If you don’t give people any power or ability to make decisions , then they don’t engage the same and they don’t invest in the project. If they have that role within the project , they’re not going to be so invested in either the findings or in the benefits to them.” – KI1 .

Regarding establishing trust, some group A informants suggested creating time to engage with the community beyond the scope of the project to build rapport and trust, which in turn, fosters participation.

“You have to be a more familiar face. Not just go in and do what and then get out. But actually , spending a little bit more time with the community because that is how you get those women that didn’t come out.” – KI2 .

Similarly, creating time “just to hang around and experience people’s lived realities” with HAAP and “share stories… of what life is like” (KI5) was alluded to as a means to foster familiarity and rapport. Engaging with existing skills and resources within the community, e.g., local tradesmen and craftspeople, was also implied by most group A informants as essential to support community-research rapport and partnerships. In connection to fostering a trusting partnership to enhance participation and engagement, group C informants commonly stressed that the research team should place priority on delivering the project’s goal as communicated to the community.

“First , you have to let everybody know and understand how important this is to us all. And then , show us that you will indeed fulfil what you are promising us to happen in this village. And then , we will devote with all our hearts to help in anything that you will ask for.” – KI12 .

Also highlighted as significant in promoting participation are the researchers’ participatory leadership skills within the HAAP project and their ability to operationalise the CBPR components within the community’s available structures and resources.

“In a way , it starts with good leadership. And that’s down to me [KI1] and you [EP]. That means the overall project but also your leadership of the participation aspects. You need to have participative leadership to set the scene and have the right context.” – KI1 .

Another group A informant discussed cultivating the habit of affirming the community’s contributions during the CBPR process to “assist them to see the value in what they are doing , saying , okay , we’re doing a good job” (KI3). She argued that these affirmations could enhance the community’s capability to plan for future projects.

Finally, informants suggested several research tools to facilitate the implementation of an effective CBPR HAAP project of benefit to the research and community. These are summarised in Table  2 below.

Sustainability

Complementary to participation facilitators, this sub-category captures informants’ views on sustaining the use of HAAP interventions and sustaining behaviour change.

Sustaining use of intervention

A group A informant linked the sustained use of HAAP intervention to the community’s understanding of the suitability of that intervention to meet their needs and suggested including a participatory intervention demonstration activity in the HAAP design. As an example, he cited:

“We [researchers] do a water boiling test , we don’t actually cook food on the [improved stove] , so we don’t really appreciate what they’re going to be like in use” –KI5.

Most group C informants mentioned skill enhancement as a tool to achieve sustainability. One participant extended this beyond the sustained use of the intervention to include possible economic gain, suggesting “training them” [the community as entrepreneurs] “so [that] they can save some money” –KI10. On the other hand, some in group A (KI2, KI6) advised making the HAAP interventions “really simple technologies” that the community can build with local and readily available materials. Narrating from a HAAP-related experience, skill enhancement was alluded to as supportive of sustained project outcomes.

“The uptake was pretty high , over 80% , but they [community] felt that once the artisans had gone , they were left a little bit helpless. If the thing broke … they didn’t necessarily know how to do it …. That long – term support or provision of the longer-term support would have probably helped it [project] to be even more successful than it has been.” – KI2 .

Sustaining behaviour change

In addition to enhancing community capacity through skills enhancement, the health surveillance assistant urged researchers to allow the community to be their own change–maker by giving ownership of the intervention monitoring to the community. It was described as an empowerment tool to support a sustained community–level behaviour change. Using an example of a community nutrition screening program where sustained change was achieved, she stated:

“When we are screening nutrition , we use people in the community to go around and see what is happening , to encourage others. They can do that , help each other , and they can see the changes… They can say , oh , this child is speaking up. Now , this child’s wasting is going down. The community can do it , and so , train them , okay , and empower them.” – KI11 .

A similar view was shared by a group A informant (KI2) who described the role of a “village motivator” as one involved in motivating or educating the villagers to adapt to the new intervention.

Finally, a group A informant (KI1) urged sustaining the community–research relationship past the project endline. This was described as a capacity–building measure, “a continuum” , with the outlook of involving current community members in possible scale–up projects with other localities. However, the lack of recurring project funding limits engaging the community in such capacity–building undertakings.

In this section, we discussed the result categories, barriers to participation, and good practices for effective CBPR design and implementation in HAAP projects using Wallerstein et al.’s CBPR model and the published evidence [ 10 , 24 , 25 , 31 ] by the model’s authors. Our aim was not to test the model but to understand where the participatory factors identified from the informants’ experiences fit within the existing CBPR conceptual model. At the time of the study, the model was being proposed for use in designing a CBPR approach for a HAAP intervention project.

The four domains of the CBPR model—‘contexts’, ‘partnership processes’, ‘intervention and research’, and ‘outcomes’—provide the flexibility to adapt and connect CBPR principles to project activities [ 10 ]. Our study findings align with several of the CBPR model domain factors and highlight where barriers could exist in real–life settings and what good practices could enhance the implementation of the CBPR approach. Table  3 shows where our study’s categories fit within the model.

Contexts domain

The contexts domain highlights the social-structural, political and policy, health issues, collaboration, and capacity factors needed to move the other domains forward [ 24 ]. It advocates positioning the CBPR activities in the context of (i) socio-economic status (SES), (ii) historical research collaboration, (iii) politics and policy, (iv) knowledge and perceived severity of health issues, (v) historical collaboration, and (vi) community capacity and readiness to engage, and academic partners’ capacity to support institutional policies and practices. However, issues related to these factors could occur that could impede participation. For example, the level of involvement in research processes, perception of the severity of the health issue, and acceptance of the research aim are all linked to community–level barriers such as level of skills and education, time–constraints and existing trust/mistrust of research from historical collaboration. Equally, inadequate assessment of community health needs and assets (linked in this study to funding, ethical regulations and time constraints) creates research–level barriers, which can widen gaps in the research team’s capacity to recognise and plan for the community-level barriers.

Several good practices mentioned in this study support planning an effective CBPR approach to address some of these issues. These include (i) assessing and implementing affordable HAAP interventions to reduce health disparities (SES), (ii) delivering on the research goals and minimising historical distrust that communities may have experienced with previous top–down or tokenistic research [ 31 ], or a lack of congruence over core values; (iii) respect for community time and a having safe environment to engage (cultural, safety, and environmental); (iv) effective communication strategies (education); (v) skill enhancing activities, and assessing the community’s capacity to engage at all research levels (education, capacity and readiness to engage). The research team’s capacity and readiness to implement an effective CBPR approach (discussed briefly in the study) addresses several of the community-level barriers within the domain and supports setting the foundation for the socioeconomic, structural, and cultural factors [ 24 ]. This is explicit in the capability of the research team to engage the community in effective communication, in addition to assessing the suitability of the research objective to the community’s needs. Although we reported funding, time, and ethical barriers to assessing the community’s capacity to engage, we argue that it falls within the CBPR researchers’ role to report these limitations to the funding and ethical bodies. This can help to facilitate more need–specific funding calls and enhance community-research collaborations.

Partnership processes domain

The partnership processes’ domain relates to how and the extent to which the partners’ voice and knowledge are integrated into the research design, intervention, and activities to create an equitable partnership [ 24 , 25 , 31 ]. Its three factors, partnership structures, individual characteristics, and relational dynamics, are essential to achieving an equitable partnership from design to outcome in a CBPR project [ 24 ].

Our findings within the ‘partnership structures’ factor identified community–level barriers related to who in the community is involved in the community-research partnership and controls the community’s resources. For example, in communities with an autocratic leadership style and in community groups ranked by economic status and academic achievements, higher–status members are likely to dominate discussions, resulting in an unequal distribution of knowledge, power, and voice in decision–making activities. The unequal distribution leads to ‘elite bias’—a higher affinity of the community elite with outsiders— or, in this case, the research team [ 32 ]. Our findings also show that such power imbalances can occur at the research–level. Researchers, either by virtue of being custodians of research funds or being perceived as having higher knowledge, could dominate discussions and make autocratic decisions for the project. Several suggestions to ameliorate these community and research–level barriers strongly echo the model’s outlook of forming CBPR partnerships. Specifically, expanding research communications to the whole community, irrespective of the target intervention group, and instigating gender– inclusive participatory decision–making, mirrors and adds to the model’s diversity of partnership structures beyond place and race/ethnicity [ 24 ]. Additionally, our study emphasised the important role of research-team members who share nationality and language with the community as best suited to act as insiders in facilitating partnership processes. This is similar to the role of a ‘bridge person’, described in the model’s individual factors as an academic team member with shared race/ethnicity to facilitate the integration of local knowledge [ 24 ]. However, we argue that the model’s description of the bridge person’s role does not address intra-community power and status imbalances. Since such imbalances could limit participation, we recommend future studies to explore these intra–community dynamics and the impact, if any, of a bridge person in mitigating them. Further, our findings within the model’s role recognition and formal agreements emphasised the need for clarity around the CBPR project’s role, responsibility, and accountability structure to help reduce conflict with any existing community leadership style and community–group dynamics. However, the need for formal agreements such as memoranda in the partnership structures [ 31 ] was unreported in this study.

Also, our findings advocate for involving local community artisans in research projects and providing gratuity for participation and time invested in the research. This exemplifies the model’s partnership factor, ‘% dollar to community’, described as providing adequate incentives and sharing grant funds to promote marginalised communities’ participation in health research [ 10 , 31 ]. Investing time in community activities to foster equitable partnerships also accords with the model and supports its importance in building trust.

With respect to individual characteristics, we identified individual–level barriers mostly from individuals’ lack of motivation to engage. This can be related to the research team’s individual characteristics, including ethnocentric beliefs and disregard or disrespect for the community’s values. Also, the researcher’s reputation was highlighted as essential to the partnership process, with findings emphasising the importance of researchers’ respect for community values and beliefs, cultural sensitivity, humility, and the need to shelve pre-conceived beliefs. These findings illustrate several of the model’s partnership processes factors, which assert the need for flexibility within the research team to listen and work within the existing community decision-making and power structures to support open communication and mutual learning. In addition, we found consistency in our findings on the delivery of project commitments, with the model’s description of trust as earned by “following through” and “keeping promises” [ 24 ]. This concept of trust is required to mitigate the often complex sources of conflict in the research–community dynamics [ 31 ]. This, in addition to the value of researcher’s reflections on their assumed research power, is posited by the model to circumvent conflicts and maintain positive partnership dynamics [ 25 , 31 ]. Researcher reflexivity was, however, not defined in our findings.

Intervention and research domain

There are similarities between the factors expressed by informants in this study and those described by the CBPR model’s intervention and research domain to design a culturally appropriate project [ 24 ].

The findings placed importance on the extent of, and how, partners’ voices and knowledge are integrated into the project design and interventions. It stresses participatory decision-making and bilateral exchange of information to co-create knowledge. However, we found limitations in the domain’s factor on community member involvement in research activities to reflect the community’s priorities. These limitations, including community skills levels, time to engage, time to train, and community capability to be involved at all research activity levels, could hinder communities’ involvement in some research activities. However, participatory activities that build or enhance capacity could address some of these limitations. For example, knowledge and skill transfer using a train–the–trainer approach (time–to–train), photovoice and participatory transect walks (skill enhancement, time–to–engage), and co-design and participatory decision–making (capability and capacity to engage). Reporting participatory limitations due to funding and ethical barriers to the appropriate authority could instigate the discussion required at the policy and funding level to address the issues.

The most significant finding from our study in this domain was the importance of implementing affordable and suitable interventions to meet the community’s needs. Similar to the domain’s culture-centred factor, planning HAAP interventions informed by user needs and socio-economic and cultural factors accords with our findings on good practices to enhance uptake and sustained use of HAAP interventions.

Outcomes domain

System and capacity changes such as multi-level empowerment and improved health are central to the outcome domain in the CBPR model. Our findings on building trust and enhancing community and project capacity to achieve sustainability beyond the project lifetime through skills training, learnings, bilateral knowledge exchange, equitable partnerships, and empowerment are consistent with the model [ 24 ]. While several feedback loops have been posited within the model for CBPR evaluation, our study found barriers at the research and structural level to conducting participatory evaluation (PE) after the project has ended. Primarily, this was associated with the nature of short-term research funding, which plays into limited or no time to evaluate the implemented CBPR activities within the context, partnership, and research domains to influence immediate and long-term outcomes.

This finding broadly supports Springett and Wallerstein’s discussion of funding and time as a limitation of the PE, amongst others, including the researcher’s skills in conducting the evaluation [ 33 ]. Despite this evaluation constraint, one resonating concept in our study from the informants’ reflective evaluation is CBPR’s outcome as a capacity-building tool for the researcher and the community. However, desirable outcomes—such as enhanced awareness and cultural sensitivity of the researcher and increased community autonomy in decision-making, ownership, and social change—would depend on how effectively the CBPR approach was implemented.

To shape the design and implementation of the CBPR approach in a HAAP project, this study explored key informants’ perspectives and recommendations of their real-life experience of participatory approaches in LICs. The findings provided valuable context to a versatile CBPR conceptual model and supported its domains for use in a complex HAAP intervention study. It informed the design and implementation of the CBPR approach, the evaluation markers of adoption, uptake, and sustained use of HAAP interventions (SDGs 3.9, 7.1), and community capacity outcomes of the household and ambient air pollution (SDG 13.3) project in Malawi.

We conclude that implementing a CBPR approach to improve health outcomes and health equity is multi-faceted and has several interlinking structural, research, community, and individual factors. CBPR’s emphasis on enhancing the community’s voice, knowledge, and skills in the community-research partnership should be the epicentre in implementing the approach. To support this and deepen our understanding of the different domain factors, we recommend using, evaluating, and reporting the approach’s strengths and limitations. The enhanced understanding would inform funding and policy to address structural issues and create a repertoire of findings in different contexts to reinforce our understanding of pathways from design to outcome of CBPR projects.

Data availability

The qualitative dataset generated in this study is not publicly available because the authors do not ethically have participants’ permission to share the data, and there is a risk of deductive disclosure with the dataset. Questions about the study and data can be directed to the corresponding author at [email protected].

Abbreviations

Acquired Immunodeficiency Syndrome

Community–Based Participatory Research

Household and Ambient Air Pollution

High Income Countries

Human Immunodeficiency Virus

Key Informant

Low-Income Communities/Countries

Participatory Evaluation

Particulate Matter of 2.5 micron or less

Sustainable Development Goals

Socio-Economic Status

Sub-Saharan Africa

The Smokeless Village Project

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Acknowledgements

We thank all our informants, including the community members, policymaker, NGO official, and researchers. We acknowledge Dr Vincent Jumbe’s excellent contribution to the community’s gatekeeper activities and recognise Mr Rex Zachariah and Mr Devine Matare’s exceptional contributions to recruiting community members and policymaker informants, respectively. The corresponding author especially appreciates Dr Jacinta Burke and her team at the RCSI academic office for reviewing this manuscript and providing valuable comments.

This study is part of ‘The Smokeless Village Project’ funded by the Irish Research Council, project number: COALESCE/2020/13. We also thank the Royal College of Surgeons University of Medicine and Health Sciences for the PhD Studentship Award for the correspondence author.

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Contributions

EP conceptualised and designed the study, collected and analysed data, and wrote the manuscript. AW, DS, and SJ contributed to the conceptualisation, design, and supervised analysis and writing process. FE and JS contributed to data analysis. RC contributed to the interpretation and writing. All authors read and approved the final manuscript.

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Correspondence to Eunice Phillip .

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The study was conducted in accordance with the Declaration of Helsinki and approved by the College of Medicine Research Ethics Committee (COMREC) in Malawi (P.03/21/3279) and the Research Ethics Committee, Royal College of Surgeons in Ireland (212558360). Informed consent was obtained from all participants.

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Phillip, E., Walsh, A., Jewitt, S. et al. Exploring community-based participatory research for household and ambient air pollution projects: insights from key informants. BMC Public Health 24 , 2233 (2024). https://doi.org/10.1186/s12889-024-19614-3

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DOI : https://doi.org/10.1186/s12889-024-19614-3

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Digital twins verification and validation approach through the quintuple helix conceptual framework.

1. Introduction

1.1. model-based systems engineering, 1.2. digital twins fundamentals, 1.3. digital transformation challenges, 1.4. systems engineering challenges, 1.5. the role of digital twins in verification and validation, 1.6. frameworks and framework-based engineering, 1.7. digital twins application challenges, 1.8. digital twin framework challenges, 2. materials and methods, 3.1. requirements modeling and specification, 3.2. quintuple helix foundation of dt verification and validation conceptual framework.

• Mi—designates the system’s mission (single aim or the collection or related aims that justify the existence of the specified system and answer the question of what the purpose of the specified system is);
• Os—designates the internal organization structure, aka topology or internal architecture of the specified system (system’s structure);
• Fs—designates the system’s functional structure, a set of services it provides (system’s behavior);
• Is—designates the information structure supporting the Fs over the Os to fulfill the Mi;
• Cs—designates the system’s control structure (internal or external forces that manage the systems integrity);
• Ec—designates the external systems connectivity (external topology or system-of-systems configuration).
• Abstraction Interface—that bridges the modeling abstraction layers (instance, model, meta-model, and meta-metamodel);
• Data Structure Interface—that bridges the data structure resource, a complex abstract concept encapsulating dynamic resource collection representing data, information, knowledge, or wisdom abstractions;
• Repository Interface—that bridges the repository resource, a complex abstract concept encapsulating persistent resource collection representing data, information, knowledge, or wisdom abstractions;
• Association Interface—that encapsulates the connectivity mechanisms (connect and disconnect services);
• Accept Visitor Interface—that enables the hosting of external, visiting sets of services attached to the Framework Nucleotide Instance;
• Internal Service Interface—that enables the formation of an extendible set of internally implemented services, accessible through referencing the universal abstract method implemented by an arbitrary implementer deliver (s: Service , o: SelectedObject , f: Filter ). Semantically, run a service (s: Service) on a selected object (o: SelectedObject) and restrict the delivery with security and privacy policy-based dynamic filtering (f: Filter);
• External Service Interface—that enables access to externally offered services by referencing the universal abstract method implemented by an arbitrary external implementer to perform (s: Service, o: SelectedObject, f: Filter). Semantically, execute external service (s: Service) on the selected object (o: SelectedObject) and restrict the execution by the security and privacy policy-based dynamic filtering (f: Filter).

3.3. Quintuple Helix Conceptual Framework for DT Verification and Validation Spots

3.4. quintuple helix conceptual framework mediation, 4. discussion, the exemplary application of proposed generic framework, 5. conclusions.

• The Digital Twin Consortium’s digital twin ecosystem capabilities periodic table, containing a systematic collection of referent capabilities and the associated semantics;
• The generative potentials of the DNA helix model with the built-in combinatorial complexity replicating within two back-bones, coupled with four-dimensional nucleotides;
• The unified conceptualization approach to reasoning about framework entities and stages that relays an applied MOF model to abstracting framework resources;
• The standards and standardization support extendibility;
• Bridging of the abstract specification and the diverse repertoire of implementation platforms favoring the heterogeneity and harmonization of specification, development, modeling, implementation, and execution platforms involved.

Author Contributions

Data availability statement, conflicts of interest.

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Perisic, A.; Perisic, B. Digital Twins Verification and Validation Approach through the Quintuple Helix Conceptual Framework. Electronics 2024 , 13 , 3303. https://doi.org/10.3390/electronics13163303

Perisic A, Perisic B. Digital Twins Verification and Validation Approach through the Quintuple Helix Conceptual Framework. Electronics . 2024; 13(16):3303. https://doi.org/10.3390/electronics13163303

Perisic, Ana, and Branko Perisic. 2024. "Digital Twins Verification and Validation Approach through the Quintuple Helix Conceptual Framework" Electronics 13, no. 16: 3303. https://doi.org/10.3390/electronics13163303

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