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

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

Understanding conceptual frameworks

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

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

Conceptual framework: Definition and theory

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

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

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

Developing conceptual frameworks in research

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

The purpose of a conceptual framework

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

Relation between theoretical perspectives and conceptual frameworks

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

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

Critical theory

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

Feminist theory

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

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

Factors to consider when choosing a framework

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

When selecting a conceptual framework, consider the following questions:

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

Steps in developing a conceptual framework

Developing your conceptual framework involves a few key steps:

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

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

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

Independent variables and dependent variables

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

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

Relationships among variables

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

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

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

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

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Development of Conceptual Models to Guide Public Health Research, Practice, and Policy: Synthesizing Traditional and Contemporary Paradigms

Sonya s. brady.

Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis, MN, 55454, USA

Linda Brubaker

Department of Obstetrics, Gynecology and Reproductive Sciences, University of California San Diego, La Jolla, California, 92037, USA

Cynthia S. Fok

Department of Urology, University of Minnesota Medical School, Minneapolis, MN, 55454, USA

Sheila Gahagan

Division of Academic General Pediatrics, University of California San Diego, San Diego, CA, 92093, USA

Cora E. Lewis

Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, 35294, USA

Jessica Lewis

Yale School of Public Health, New Haven, CT, 06520, USA

Jerry L. Lowder

Division of Female Pelvic Medicine and Reconstructive Surgery, Washington University in St. Louis School of Medicine, St. Louis, MO, 63110, USA

Jesse Nodora

Department of Family Medicine and Public Health and Moores UC San Diego Cancer Center, University of California San Diego, La Jolla, CA, 92161, USA

Ann Stapleton

Department of Medicine, University of Washington, Seattle, WA, 98195, USA

Mary H. Palmer

School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA

This applied paper is intended to serve as a “how to” guide for public health researchers, practitioners, and policy makers who are interested in building conceptual models to convey their ideas to diverse audiences. Conceptual models can provide a visual representation of specific research questions. They also can show key components of programs, practices, and policies designed to promote health. Conceptual models may provide improved guidance for prevention and intervention efforts if they are based on frameworks that integrate social ecological and biological influences on health and incorporate health equity and social justice principles. To enhance understanding and utilization of this guide, we provide examples of conceptual models developed by the P revention of L ower U rinary Tract S ymptoms (PLUS) Research Consortium. PLUS is a transdisciplinary U.S. scientific network established by the National Institutes of Health in 2015 to promote bladder health and prevent lower urinary tract symptoms, an emerging public health and prevention priority. The PLUS Research Consortium is developing conceptual models to guide its prevention research agenda. Research findings may in turn influence future public health practices and policies. This guide can assist others in framing diverse public health and prevention science issues in innovative, potentially transformative ways.

Public health and prevention science students, researchers, practitioners, and policy makers all stand to benefit by becoming skilled in the development of conceptual models. Over 25 years ago, Jo Anne Earp and Susan Ennett (1991) described how a conceptual model could be used to depict the mechanisms by which a selected set of risk and protective factors may be associated with a health behavior or outcome of interest, as well as the conditions under which such associations are typically observed. This work demonstrated how conceptual models can be used to provide a visual representation of specific research questions and display the key components of prevention and intervention programs, practices, and policies designed to promote health. Since Earp and Ennett’s contribution, many publications that can be used to generate conceptual models have been introduced to the public health sphere. These writings describe frameworks that integrate social ecological and biological influences on health and highlight the potential for health equity and social justice principles to guide public health research, practice, and policy. By integrating diverse perspectives, those who design conceptual models can consider a wide range of factors that may influence health. A better understanding of what influences health can lead to the development of more effective health promotion programs, practices, and policies, as well as more efficient use of limited public health resources. Conceptual model development is an increasingly valued skill. For example, the National Institutes of Health have called for the inclusion of conceptual models when teams of researchers and practitioners respond to specific requests for proposals to conduct research on health promotion, including mental health (RFA-MH-18-705), bladder health (RFA-DK-19-015), and shared decision-making between patients and providers (PA-16-424; NIH, n.d. ).

This paper is intended to serve as a contemporary guide for building conceptual models. It is consistent with the mission of Health Promotion Practice to publish practical tools that advance the science and art of health promotion and disease prevention, particularly with respect to achieving health equity, addressing social determinants of health, and advancing evidence-based health promotion practice. To enhance understanding, examples of conceptual model development are provided from the P revention of L ower U rinary Tract S ymptoms (PLUS) Research Consortium, a transdisciplinary scientific network established by the National Institute of Diabetes and Digestive and Kidney Diseases in 2015 to study bladder health and prevention of lower urinary tract symptoms (LUTS) in girls and women ( Harlow et al., 2018 ). LUTS encompass a variety of bothersome bladder symptoms, including urgency urinary incontinence (i.e., strong urge “to go” with urine loss before reaching a toilet), stress urinary incontinence (i.e., urine loss with physical activity or increases in abdominal pressure such as a cough or sneeze), bothersome frequent and/or urgent urination, nocturnal enuresis (i.e., bed-wetting), difficulty urinating, dribbling after urination, and bladder or urethral pain before, during, or after urination ( Abrams et al., 2010 ; Haylen et al., 2010). LUTS are common. For example, more than 200 million people worldwide and over 15% of women aged 40 years or older experience urinary incontinence, one of the most prevalent LUTS ( Minassian, Bazi, & Stewart, 2017 ; Norton & Brubaker, 2006 ).

While many multidisciplinary research networks focus on clinical treatment of LUTS, the PLUS Consortium stands alone in its focus on bladder health promotion and prevention of LUTS. Consistent with the World Health Organization’s (WHO) definition of health (WHO, 2006), the PLUS Consortium conceptualizes bladder health as “a complete state of physical, mental, and social well-being related to bladder function, and not merely the absence of LUTS,” with function that “permits daily activities, adapts to short term physical or environmental stressors, and allows optimal well-being (e.g., travel; exercise; social, occupational, or other activities)” ( Lukacz et al., 2018 ).

Conceptual models are different from other tools and concepts.

Table 1 highlights the distinction between conceptual models and closely related visual tools and concepts. The contrast between conceptual frameworks and conceptual models is of particular relevance to the present guide. A research-oriented conceptual framework encapsulates what is possible to study and is intentionally comprehensive; in contrast, a research-oriented conceptual model encapsulates what a team has prioritized and chosen to study and is intentionally focused in scope ( Earp & Ennett, 1991 ; Brady et al., 2018 ). Similarly, conceptual frameworks and models may depict the “universe” and selected focus, respectively, of public health practices and policies. The contrast between a theory and conceptual model is also of particular relevance to the present guide. While both theories and conceptual models describe associations among constructs in order to explain or predict outcomes, a theory is intentionally broad with respect to application. It can guide the development of one or more conceptual models to address a specific public health behavior or outcome. While a review of prominent theories is beyond the scope of this paper, several public health textbooks provide an overview of theories that may be used to guide etiologic research and health promotion programs, practices, and policies (e.g., DiClemente, Salazar, & Crosby, 2019 ; Edberg, 2015 ; Glanz, Rimer, & Viswanath, 2015 ; Simons-Morton, McLeroy, & Wedndel, 2012 ).

Distinctions between conceptual models and other visual tools and concepts used in public health and related disciplines.

Traditional and contemporary conceptualizations of public health can identify a broad range of factors that may function as determinants of health.

Traditional conceptual frameworks include social ecological and biopsychosocial models. Social ecological models , a foundation of public health approaches for more than 40 years ( McLeroy, Bibeau, Steckler, & Glanz, 1988 ; Sallis & Owen, 2015 ; Richard, Gauvin, & Raine, 2011 ), situate individuals within an ecosystem of risk and protective factors that extend outward from the intrapersonal level (e.g., biology, psychology) through the interpersonal (e.g., family, peers, partner), institutional (e.g., school, workplace, health clinic), community (e.g., cultural norms), and societal (e.g., policies, laws, economics) levels. These nested spheres of influence interact to produce individual and population health. Similarly, the biopsychosocial model posits that health is defined by a complex reciprocal interaction of biological, psychological, and social factors ( Engel, 1981 ). Given the focus of this paper, we note that both social ecological and biopsychosocial models are more consistent with the definition of a conceptual framework than a conceptual model (see Table 1 ).

Contemporary conceptualizations of public health enhance traditional frameworks by more explicitly integrating biology and social ecology, adopting life course perspectives, and incorporating health equity, social justice, and community engagement principles to guide research, practice, and policy. The Society-Behavior-Biology Nexus depicts nested spheres of influences both within and outside of an individual, who moves through life stages from infancy to old age ( Glass & McAtee, 2006 ). Systems of biological organization include multi-organ systems, cellular and molecular influences, and the genomic substrate. Levels of ecology include the micro (e.g., family, social networks), mezzo (e.g., schools, worksites, communities, healthcare systems), macro (e.g., states, nations), and global (e.g., geopolitics, environment). Biology and social ecology are integrated through the multi-level concept of embodiment (e.g., gene-environment interactions; impact of varying social-ecological resources on biology within and across populations) ( Glass & McAtee, 2006 ; Krieger, 2005 ). Social determinants are framed as societal constraints against and opportunities for health – risk regulators – which include material conditions; discriminatory practices, policies, and attitudes; neighborhood and community conditions; behavioral norms, rules, and expectations; conditions of work; and laws, policies, and regulations. Risk regulators can impact behavior or become embodied with respect to biological function ( Glass & McAtee, 2006 ; Krieger, 2005 ).

The WHO Conceptual Framework for Action on Social Determinants of Health describes how the structure of societies (i.e., governance, policies, values) determines population health ( Solar & Irwin, 2010 ). Social stratification by race, ethnicity, sex, gender, social class, and other factors leads to social hierarchies, which in turn shape social determinants of health. Distal structural determinants of health inequities (e.g., public policy, macroeconomics) are distinguished from more proximal social determinants of health (e.g., living and working conditions). The WHO framework asserts that societies produce health and disease, obligating policy makers to promote health equity and redress structural factors that produce under-resourced communities. Without such attention, health inequities evolve, often widening over time and across generations. The WHO framework can inform conceptual model development by encouraging the consideration of determinants at distal, structural levels (e.g., national policies).

Research teams have utilized contemporary conceptualizations of public health to promote health equity and social justice ( Warnecke et al., 2008 ; Balazs & Ray, 2014 ). For example, the National Institutes of Health (NIH) sponsored Centers for Population Health and Health Disparities developed a framework to show how distal factors (population-level policies and social conditions, institutional contexts) influence intermediate social context (e.g., collective efficacy, social capital), social relationships (e.g., networks, support, and influence), and physical context (e.g., building quality, neighborhood stability), which in turn influence factors that are more proximal to health (individual demographics and risk behaviors, biologic responses and pathways) ( Warnecke et al., 2008 ). The Energy and Resources Group at the University of California, Berkeley developed a framework to display mechanisms through which natural, built, and sociopolitical factors, along with state, county, and community actors, can create drinking water disparities ( Balazs & Ray, 2014 ). These frameworks highlight the key role of distal structural factors in both generating health inequities and remedying them.

Community partners can aid in developing conceptual models.

Increasingly, teams are incorporating community-engaged approaches in the development of research, practice, and policy (e.g., community members actively contributing to problem definition, agenda setting, implementation, and dissemination) ( Warnecke et al., 2008 ; O’Mara-Eves et al., 2013 ). Different resources exist to guide community engagement and enhance the likelihood of sustained, relevant action. For example, Lezine and Reed (2007) outlined different steps to build and apply political will in the development and implementation of public health policy; their approach integrates scientific evidence and community participation. Cacari-Stone and colleagues (2014) developed a conceptual model to show how community-based participatory research (CBPR), one approach to community engagement, can lead to policy change.

Three Steps of Conceptual Model Development.

The development of conceptual models can be divided into three basic steps: (1) identify resources for idea generation; (2) consider risk and protective factors; and (3) select factors for inclusion in the conceptual model. First, team members identify existing conceptual frameworks and models, theories, and key stakeholders (e.g., practitioners, policy makers, community members) that will serve as resources for idea generation. This step defines the “universe” of factors that can be studied in relation to specific health behaviors or outcomes of interest. Second, team members systematically consider risk and protective factors suggested by resources. This step highlights the importance of carefully selecting resources for idea generation; the risk and protective factors considered by a team will be constrained by its selected frameworks and models, theories, and stakeholders. Existing evidence linking risk and protective factors to the health behaviors or outcomes under study, as well as potential effect modifiers and confounders, can be identified through literature reviews. When data are insufficient, a team may wish to conduct key stakeholder interviews, focus groups, and other forms of hypothesis-generating data collection. The third step in the development of conceptual models is to narrow down considered risk and protective factors to those that will be included in the conceptual model. This can be achieved through a combination of theoretically-based, key stakeholder-based, and evidence-based rationales. Theories point to clusters of risk and protective factors that could be studied in relation to health behaviors or outcomes of interest, or targeted through prevention or intervention efforts. Key stakeholders can assess the relevance of different theories to a given public health context and suggest additional risk and protective factors that seem critical to the context. Findings from the extant literature can provide evidence in support of different links in the conceptual model.

If the intent of building a conceptual model is to develop an evidence-based program, practice, or policy, a team can conduct a literature review to answer the following “narrowing down” questions: (a) Is the risk or protective factor strongly linked to the health behavior or outcome of interest? (b) Have previous prevention or intervention programs, practices, or policies shown that the risk or protective factor is feasible to modify? (c) Was health improved as a result of modifying the risk or protective factor? Risk and protective factors can be retained in the conceptual model if they are strongly supported by evidence and judged highly relevant to context.

When the intent of building a conceptual model is to conduct research to better understand a health behavior or outcome, a team may choose to consult existing theories, key stakeholders, and the evidence-base for guidance in selecting risk and protective factors. To maximize potential public health impact, a team can answer the following “narrowing down” question: What potential risk and protective factors are judged to be highly likely to influence health behaviors or outcomes of interest? Ideally, the answers to public health research questions will expand the evidence base in a way that can directly inform programs, practices, and policies. Expansion of the evidence-base can be accomplished in a variety of potentially transformative ways, including the synthesis of ideas from more than one discipline and the application of paradigms from one discipline to another.

Regardless of the approach and rationale used to select risk and protective factors, the utility of the conceptual model may be enhanced by answering the final three sets of questions: (a) Have key “mechanistic factors” been considered and included in the model? What biological, psychological, and social processes might explain links between identified risk and protective factors and health behaviors or outcomes of interest? (b) Have key “upstream factors” been considered and included in the model? For example, are there societal and institutional policies and practices that serve as facilitators or barriers to health? (c) Have key “effect modifiers” been considered and included in the model? For example, are there factors that might make prevention or intervention programs, practices, or policies more or less effective among specific communities and populations?

Examples from the PLUS Research Consortium.

The PLUS Consortium is comprised of a transdisciplinary network of professionals, including community advocates, health care professionals, and scientists specializing in pediatrics, adolescent medicine, gerontology and geriatrics, nursing, midwifery, behavioral medicine, preventive medicine, psychiatry, neuroendocrinology, reproductive medicine, female pelvic medicine and reconstructive surgery, urology, infectious diseases, clinical and social epidemiology, prevention science, medical sociology, psychology, women’s studies, sexual and gender minority health, community-engaged research, community health promotion, scale development, research methods, and biostatistics. The PLUS Consortium has developed several conceptual models to guide research questions that will test whether specific risk and protective factors contribute to LUTS and bladder health.

Because the evidence-base for LUTS prevention is sparse, the traditional and contemporary conceptualizations of public health reviewed above, as well as expertise of PLUS investigators, were used as key resources to identify potential risk and protective factors for study (Step 1). Traditional and contemporary conceptualizations of public health encouraged consortium members to step outside of their disciplinary “comfort zones” to integrate social ecological and biological influences on health across the life course and consider the potential for health equity and social justice principles to guide the consortium’s prevention research agenda. While all of the conceptualizations reviewed above were considered, Glass and McAtee’s Society-Behavior-Biology Nexus was particularly influential because it visually represented different levels of social ecology and biology across the life course, as well as the process of embodiment. PLUS members served as an initial key stakeholder group that generated a conceptual framework and over 400 risk and protective factors prioritized for study in relation to bladder health and LUTS (Step 2) ( Brady et al., 2018 ). The conceptual models presented in this paper represent the work of subsets of consortium members who designed models to guide specific research questions (Step 3). Models were designed with the assistance of public health and prevention science team members who were familiar with social ecological frameworks and the development of conceptual models. Initial development of models occurred in real time during in-person and virtual (WebEx) meetings. This was often followed by revision of models via emailed chains of conversation. One person with experience in conceptual model development was responsible for integrating and communicating comments and mutual decisions, as well as revising the models.

Each conceptual model featured in this paper represents hypothesized associations between constructs; some links in each model are supported by existing evidence, while others are based on theoretical or biological plausibility. Figure 1 highlights institutional-level factors in relation to bladder health and LUTS, while Figure 2 highlights family- and community-level factors and Figure 3 highlights societal and commercial factors.

Work-related structural and social influences on musculoskeletal function and bladder health: Hypothesized mechanisms.

Explanation of Pathways: Four different work-related factors (shaded boxes) affect different aspects of musculoskeletal function, which in turn affect bladder health and LUTS. Workplace physical and psychological demands directly affect musculoskeletal function. Workplace ergonomics and travel/commute patterns indirectly affect musculoskeletal function through prolonged sitting or standing and posture (mediation pathways).

Trajectories of risk and resilience among individuals and communities exposed to ACEs and traumatic stressors: Hypothesized mechanisms.

Explanation of Pathways: Executive functioning difficulties and central nervous system dysregulation are shown in a single, partitioned box because these constructs are hypothesized to covary in their manifestation. Direct effects between two adjacent constructs are shown by solid lines (1a, 2a, 3a, 4, 5); effect modification by resources for resilience (shaded box) is shown by dashed lines (1b, 2b, 3b). ADHD: Attention-Deficit/Hyperactivity Disorder.

Societal and commercial influences on bladder health and LUTS: Hypothesized mechanisms involving fast food and soda.

Explanation of Pathways: This conceptual model highlights hypothesized mechanisms (mediators) that can explain associations between societal and commercial factors (shaded boxes) and bladder health and LUTS. This model can guide a set of statistical analyses that require the identification of predictor, mediating, and outcome variables. The model does not reflect the full complexity of associations that likely exist among constructs (e.g., bi-directional associations, feedback loops; see Systems Model entry in Table 1 ).

Figure 1 depicts a basic conceptual model showing how specific work-related structural and social factors may influence musculoskeletal function, which in turn may impact bladder health and LUTS development. Four key aspects of musculoskeletal dysfunction are overuse injury, strain, pain, and weakness (see center-right of Figure 1 ), which may be directly and indirectly influenced by work-related factors. The top, bottom, and left-most boxes depict work-related factors that are external to the individual and arguably imposed by society and institutions. Workplace physical and psychological demands are shown to directly impact musculoskeletal function. Workplace physical demands (e.g., repetitive heavy lifting) may result in musculoskeletal dysfunction, which in turn may lead to LUTS ( Park & Palmer, 2015 ). In addition, workplace psychological demands (e.g., job performance pressures, conflict with coworkers, inequitable expectations and evaluations of work) may be accompanied by stress, anxiety, and other forms of negative affect ( Larsman, Kadefors, & Sandsjö, 2013 ), which may lead to chronically increased pelvic floor muscle dysfunction and LUTS ( van der Velde, Laan, & Everaerd, 2001 ). Workplace ergonomics (e.g., improper chair or desk height) and travel/commute patterns (e.g., daily, long commutes and long airplane flights) may indirectly impact musculoskeletal dysfunction through prolonged sitting or standing and poor posture ( Barone Gibbs et al., 2018 ).

Additional research is needed to support hypothesized associations in Figure 1 , which are based in large part on the authors’ clinical and community-based observations. If different links are supported, corresponding workplace policies and practices can be promoted to ensure that physical demands are offset by varying the type and intensity of activity and providing breaks; psychological demands are fair, reasonable, and offset by supports; and workplace ergonomics are conducive to the health of all employees, regardless of status within the organization. In addition, local and state governments can support policies and practices that ensure adequate access to acceptable bathroom facilities along transportation routes and when possible, within public transportation conveyances.

Figure 2 shows an example of a more complex conceptual model. A trajectory of risk among individuals or communities exposed to adverse childhood experiences (ACEs) (e.g., abuse, neglect, household disruptions) (Felitti et al., 1998) and other traumatic stressors can be seen by following the solid lines from left to right. ACEs and traumatic stressors indirectly affect local dysregulation through two potential pathways: (I) development of executive functioning difficulties and central nervous system dysregulation (shown by 1a links) ( Nusslock & Miller, 2016 ; Smith et al., 2016 ), which in turn lead to local dysregulation (shown by link 4) ( Kanter et al., 2016 ); and (II) development of depression, anxiety, and ADHD symptoms (shown by 2a links), which in turn lead to executive functioning difficulties and central nervous system dysregulation (shown by link 3a) ( Nusslock & Miller, 2016 ), which then leads to local dysregulation (shown by link 4) ( Kanter et al., 2016 ; Yousefichaijan, Sharafkhah, Rafiei, & Salehi, 2016 ). Constructs that explain associations between stressful life circumstances and LUTS may collectively be thought of as a “chain of mediation,” in that they lie along a hypothesized causal, sequential pathway. Figure 2 also shows how a trajectory of risk/chain of mediation may be weakened or broken at different points along the pathway. The dashed lines of Figure 2 show modification of effects (“effect modification”) by resources for resilience (i.e., coping, social support). Effects of stressful life circumstances on LUTS are weakened in the presence of resources for resilience (shown by the dashed lines 1b, 2b, and 3b).

Although several of the links in Figure 2 are supported by evidence, additional research is needed. Figure 2 illustrates the importance of structural factors that stratify the citizens of a society into communities that are more or less likely to experience adverse childhood experiences and traumatic stressors, and have more or less opportunities to garner resources for resilience ( Glass & McAtee, 2006 ; Solar & Irwin, 2010 ; Warnecke et al., 2008 ). Policies attempting to ensure equitable allocation of resources, including but not limited to health care, are essential to preventing and weakening trajectories of risk that disproportionately impact under-resourced communities and families.

Figure 3 , our final example, highlights broader, societal and commercial influences on bladder health and LUTS, along with environmental, behavioral, and biological mechanisms specific to fast food and soda consumption. Consistent with the WHO Conceptual Framework for Action on Social Determinants of Health ( Solar & Irwin, 2010 ), Figure 3 begins with societal structures. Governance and policies shape the built environments of communities, in part through zoning of fast food restaurants, convenience stores, grocery stores, and farmers markets; these, in turn, impact the availability of fast food and soda in communities ( Sallis & Glanz, 2009 ). Additional policies can impact the affordability of fast food and soda relative to healthy products (e.g., taxation of sugar-sweetened beverages; subsidies for fresh produce) ( Franck, Grandi, & Eisenberg, 2013 ), as well as the advertising and marketing of fast food and beverages, especially towards children ( Harris et al., 2015 ). Low-income communities of color in the United States have historically received fewer resources as a result of inequitable policies; they have also been targeted by the fast food and soda industries ( Sallis & Glanz, 2009 ; Harris et al., 2015 ).

Availability, relative affordability, advertising, and marketing of fast food and soda within a community increase the likelihood that residents will consume “super-sized” food portions and soda, which contributes to obesity ( Sallis & Glanz, 2009 ; Harris et al., 2015 ). Obesity may directly impact LUTS by intra-abdominal pressure on the bladder ( Bavendam et al., 2016 ); it may also impact LUTS through diabetes-related mechanisms, including neurogenic bladder and urinary tract infections ( Bavendam et al., 2016 ; Podnar & Vodusek, 2015 ). Diet soda, which many individuals embrace as a means to reduce caloric intake and combat obesity, contains components that may increase urine volume (caffeine) and harm the health of the bladder lining (artificial sweeteners, carbonation/acidity) (Robinson, Hanna-Mitchell, Rantell, Thiagamoorthy, & Cardozo, 2015). A healthy bladder may be maintained or restored by healthy food and beverage choices; Figure 3 highlights constraints on healthy choices that are determined by upstream, societal factors.

Because the PLUS Research Consortium is just beginning its prevention research agenda, its current models are intended to guide etiologic research, as opposed to selection, implementation, and evaluation of health promotion and prevention strategies. Broader planning frameworks exist for this purpose, including PRECEDE-PROCEED and intervention mapping ( Bartholomew, Markham, Mullen, & Fernández, 2015 ; Bartholomew, Parcel, & Kok, 1998 ; Green & Kreuter, 2005 ), the Substance Abuse and Mental Health Services Administration’s (SAMHSA) Strategic Prevention Framework (2017) , and the Center for Disease Control and Prevention’s (CDC) Framework for Program Evaluation in Public Health (1999) . These frameworks not only guide practitioners in assessing risk and protective factors at different levels of social ecology that may influence health, but also provide a structure for applying theories and conceptual models to the planning and evaluation of health promotion programs, practices, and policies. The PLUS Research Consortium will utilize existing planning frameworks when its work progresses to the point of designing, implementing, and evaluating bladder health promotion and LUTS prevention strategies through research.

Lessons Learned and Recommendations for Other Conceptual Model Development Teams.

After developing the conceptual models and supporting materials presented in this paper, authors reflected on lessons they had learned and what they would recommend to other teams.

Recommendation 1: Develop a shared language.

Students, researchers, practitioners, and policy makers interested in developing conceptual models may benefit from reviewing the terms in Table 1 , determining what is consistent with and distinct from their own discipline and training, and identifying additional tools and concepts that could aid in conceptual model development. Few of this paper’s authors were initially familiar with all of the visual tools and related concepts defined in Table 1 . Terms were added not only by authors, but also by other PLUS Consortium members (e.g., epidemiologists recommended the inclusion of “directed acyclic graph” and “systems model”). Teams who are developing conceptual models may develop a shared language through the process of reviewing, adding, and defining terms.

Recommendation 2: Establish a conceptual framework before developing a conceptual model.

Authors appreciated the distinction between conceptual frameworks and models, particularly with respect to how a framework could be a starting point to broaden one’s conceptualization of health beyond one’s own disciplinary training. Consortium members valued the integration of social ecological, behavioral, and biological perspectives of what influences health, as well as the opportunity to incorporate multiple levels of influence into a single conceptual model and corresponding set of research questions. Consortium members appreciated how the creation and refinement of conceptual models could then assist in clarifying specific research questions; identifying potential pathways through which different risk and protective factors may influence a health outcome; examining and challenging one’s own disciplinary assumptions; and articulating what is known or speculative with respect to the factors that influence health.

Recommendation 3: Seek to develop a diverse team and solicit input from others.

Authors appreciated how steps of conceptual model development included the consideration of how community partners and other key stakeholders can become involved in the process of development. By design, the PLUS Research Consortium includes community advocates, community-engaged researchers, and health care professionals and scientists representing a broad array of disciplines. Authors did not reach beyond the PLUS Consortium to develop the conceptual models featured in this paper, in part because the present paper was intended to describe the process of conceptual model development, rather than to present definitive models. Other conceptual model development teams may benefit from soliciting the input of individuals who are not well represented on their team, including community members, researchers, practitioners, and policy makers.

Recommendation 4: Anticipate and embrace the iterative, “trial and error” nature of conceptual model development.

Early in the process of developing conceptual models, authors developed a shared understanding that it was not necessary for all proposed links in a conceptual model to be informed by existing evidence. Theory, clinical observations, and the lived experience of community members are valid sources of information, as well. Authors also came to appreciate that it was not necessary to develop the “perfect” model during a first attempt to understand a health behavior or outcome, or to select the key components of an evidence-based program, practice, or policy. Indeed, attempting to achieve perfection may stifle creativity and innovation. The conceptual models presented in this paper were developed iteratively, both within the team of authors and consortium members who assisted in their development (see Acknowledgements ). Conceptual models should be evaluated through research, which may support or fail to support proposed links in a model. Conceptual models are meant to be refined, not only during their initial stage of development, but also in response to new information that is gleaned through subsequent research.

Summary and Conclusion.

Researchers, practitioners, and policy makers can use conceptual models to convey ideas to diverse audiences. We posit that conceptual models may have the greatest impact on public health if they integrate social ecological and biological influences on health and highlight the potential for health equity and social justice principles to guide public health research, practice, and policy. To illustrate this point, we have provided examples of conceptual model development from the P revention of L ower U rinary Tract S ymptoms (PLUS) Research Consortium, a transdisciplinary scientific network established in the United States in 2015 to promote bladder health and prevent lower urinary tract symptoms, an emerging public health and prevention priority. The PLUS Consortium is developing conceptual models to guide its bladder health promotion and LUTS prevention research agenda. In concert with other researchers and community partners, the PLUS Consortium will be poised to inform future public health practices and policies. We hope our shared work will assist others in framing diverse public health matters in innovative, potentially transformative ways.

Acknowledgements

The authors acknowledge special contributions to featured conceptual models by the following PLUS Research Consortium members: Amanda Berry, Neill Epperson, Colleen Fitzgerald, Missy Lavender, Ariana Smith, and Beverly Williams. The authors also acknowledge the foundational work of Jo Anne Earp, Professor Emerita, and Susan T. Ennett, Professor, Department of Health Behavior, Gillings School of Public Health, University of North Carolina, Chapel Hill. Dr. Earp and Dr. Ennett’s pioneering “how to” guide for building conceptual models, published in 1991, inspired the present guide. In addition, the authors acknowledge Kenneth L. McLeroy, Professor Emeritus and retired Regents and Distinguished Professor, School of Public Health, Texas A&M University, for helpful discussion about manuscript content.

Participating PLUS research centers at the time of this writing are as follows:

Loyola University Chicago - 2160 S. 1 st Avenue, Maywood, Il 60153-3328

Linda Brubaker, MD, MS, Multi-PI; Elizabeth Mueller, MD, MSME, Multi-PI; Colleen M. Fitzgerald, MD, MS, Investigator; Cecilia T. Hardacker, RN, MSN, Investigator; Jeni Hebert-Beirne, PhD, MPH, Investigator; Missy Lavender, MBA, Investigator; David A. Shoham, PhD, Investigator

University of Alabama at Birmingham - 1720 2nd Ave South, Birmingham, AL 35294

Kathryn Burgio, PhD, PI; Cora E. Lewis, MD, MSPH, Investigator; Alayne Markland, DO, MSc, Investigator; Gerald McGwin, PhD, Investigator; Beverly Williams, PhD, Investigator

University of California San Diego - 9500 Gilman Drive, La Jolla, CA 92093-0021

Emily S. Lukacz, MD, PI; Sheila Gahagan, MD, MPH, Investigator; D. Yvette LaCoursiere, MD, MPH, Investigator; Jesse N. Nodora, DrPH, Investigator

University of Michigan - 500 S. State Street, Ann Arbor, MI 48109

Janis M. Miller, PhD, MSN, PI; Lawrence Chin-I An, MD, Investigator; Lisa Kane Low, PhD, MS, CNM, Investigator

University of Pennsylvania – Urology, 3rd FL West, Perelman Bldg, 34th & Spruce St, Philadelphia, PA 19104

Diane Kaschak Newman, DNP, ANP-BC, FAAN PI; Amanda Berry, PhD, CRNP, Investigator; C. Neill Epperson, MD, Investigator; Kathryn H. Schmitz, PhD, MPH, FACSM, FTOS, Investigator; Ariana L. Smith, MD, Investigator; Ann Stapleton, MD, FIDSA, FACP, Investigator; Jean Wyman, PhD, RN, FAAN, Investigator

Washington University in St. Louis - One Brookings Drive, St. Louis, MO 63130

Siobhan Sutcliffe, PhD, PI; Colleen McNicholas, DO, MSc, Investigator; Aimee James, PhD, MPH, Investigator; Jerry Lowder, MD, MSc, Investigator;

Yale University - PO Box 208058 New Haven, CT 06520-8058

Leslie Rickey, MD, PI; Deepa Camenga, MD, MHS, Investigator; Shayna D. Cunningham, PhD, Investigator; Toby Chai, MD, Investigator; Jessica B. Lewis, PhD, MFT, Investigator

Steering Committee Chair: Mary H. Palmer, PhD, RN: University of North Carolina

NIH Program Office: National Institute of Diabetes and Digestive and Kidney Diseases, Division of Kidney, Urologic, and Hematologic Diseases, Bethesda, MD

NIH Project Scientist: Tamara Bavendam MD, MS; Project Officer: Ziya Kirkali, MD; Scientific Advisors: Chris Mullins, PhD and Jenna Norton, MPH; Scientific and Data Coordinating Center (SDCC): University of Minnesota - 3 Morrill Hall, 100 Church St. S.E., Minneapolis MN 55455

Bernard Harlow, PhD, Multi-PI; Kyle Rudser, PhD, Multi-PI; Sonya S. Brady, PhD, Investigator; John Connett, PhD, Investigator; Haitao Chu, MD, PhD, Investigator; Cynthia Fok, MD, MPH, Investigator; Todd Rockwood, PhD, Investigator; Melissa Constantine, PhD, MPAff, Investigator

This work of the Prevention of Lower Urinary Tract Symptoms (PLUS) Research Consortium was supported by the National Institutes of Health (NIH) through cooperative agreements (grant numbers U01DK106786, U01DK106853, U01DK106858, U01DK106898, U01DK106893, U01DK106827, U01DK106908, U01DK106892). Additional support was provided by the National Institute on Aging, NIH Office of Research on Women’s Health, and NIH Office of Behavioral and Social Sciences Research. The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of NIH.

Contributor Information

Sonya S. Brady, Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis, MN, 55454, USA.

Linda Brubaker, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California San Diego, La Jolla, California, 92037, USA.

Cynthia S. Fok, Department of Urology, University of Minnesota Medical School, Minneapolis, MN, 55454, USA.

Sheila Gahagan, Division of Academic General Pediatrics, University of California San Diego, San Diego, CA, 92093, USA.

Cora E. Lewis, Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, 35294, USA.

Jessica Lewis, Yale School of Public Health, New Haven, CT, 06520, USA.

Jerry L. Lowder, Division of Female Pelvic Medicine and Reconstructive Surgery, Washington University in St. Louis School of Medicine, St. Louis, MO, 63110, USA.

Jesse Nodora, Department of Family Medicine and Public Health and Moores UC San Diego Cancer Center, University of California San Diego, La Jolla, CA, 92161, USA.

Ann Stapleton, Department of Medicine, University of Washington, Seattle, WA, 98195, USA.

Mary H. Palmer, School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.

• Abrams P, Andersson KE, Birder L, Brubaker L, Cardozo L, Chapple C, … & Wyndaele JJ (2010). Fourth International Consultation on Incontinence Recommendations of the International Scientific Committee: Evaluation and treatment of urinary incontinence, pelvic organ prolapse, and fecal incontinence . Neurourology and Urodynamics: Official Journal of the International Continence Society , 29 ( 1 ), 213–240. [ PubMed ] [ Google Scholar ]
• Balazs CL, & Ray I (2014). The drinking water disparities framework: On the origins and persistence of inequities in exposure . American Journal of Public Health , 104 ( 4 ), 603–611. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Baron RM, & Kenny DA (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations . Journal of Personality and Social Psychology , 51 ( 6 ), 1173. [ PubMed ] [ Google Scholar ]
• Bartholomew LK, ., Markham C, Mullen P, & Fernández ME. (2015). Planning models for theory-based health promotion interventions In Glanz K, Rimer BK, & Viswanath K. (Eds.) Health Behavior: Theory, Research, and Practice (5th ed., pp. 359–387). San Francisco, CA: Jossey Bass. [ Google Scholar ]
• Bartholomew LK, Parcel GS, & Kok G (1998). Intervention mapping: A process for developing theory- and evidence-based health education programs . Health Education & Behavior , 25 ( 5 ), 545–563. [ PubMed ] [ Google Scholar ]
• Bavendam TG, Norton JM, Kirkali Z, Mullins C, Kusek JW, Star RA, & Rodgers GP (2016). Advancing a comprehensive approach to the study of lower urinary tract symptoms . The Journal of Urology, 196 ( 5 ), 1342–1349. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Brady SS, Bavendam TG, Berry A, Fok CS, Gahagan S, Goode PS, … & Lukacz ES. (2018). The Prevention of Lower Urinary Tract Symptoms (PLUS) in girls and women: Developing a conceptual framework for a prevention research agenda . Neurourology and Urodynamics , 37 ( 8 ), 2951–2964. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Cacari-Stone L, Wallerstein N, Garcia AP, & Minkler M (2014). The promise of community-based participatory research for health equity: a conceptual model for bridging evidence with policy . American Journal of Public Health , 104 ( 9 ), 1615–1623. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Centers for Disease Control and Prevention. (2004). Evaluation guide: Developing and using a logic model . Atlanta, GA: Division of Heart Disease and Stroke Prevention. [ Google Scholar ]
• Centers for Disease Control and Prevention. (1999). Framework for program evaluation in public health . MMWR , 48 (No. RR-11 ). Retrieved June 2, 2019 from https://www.cdc.gov/eval/framework/index.htm [ Google Scholar ]
• Coie JD, Watt NF, West SG, Hawkins JD, Asarnow JR, Markman HJ, … & Long B (1993). The science of prevention: A conceptual framework and some directions for a national research program . American Psychologist , 48 ( 10 ), 1013. [ PubMed ] [ Google Scholar ]
• Definition of conceptual framework. Mosby’s Medical Dictionary , 8th edition The Free Dictionary by Farlex; Retrieved January 31, 2018 from https://medical-dictionary.thefreedictionary.com/conceptual+framework Accessed [ Google Scholar ]
• DiClemente RJ, Salazar LF, & Crosby RA (2019). Health Behavior Theory for Public Health: Principles, Foundations, and Applications (2nd ed.). Burlington, MA: Jones & Bartlett Learning. [ Google Scholar ]
• Earp JA, & Ennett ST (1991). Conceptual models for health education research and practice . Health Education Research , 6 ( 2 ), 163–171. [ PubMed ] [ Google Scholar ]
• Edberg M (2015). Essentials of Health Behavior: Social and Behavioral Theory in Public Health (2nd ed.). In Riegelman R (Series Ed.), Essential Public Health . Burlington, MA: Jones & Bartlett Learning. [ Google Scholar ]
• Engel GL (1981, January). The clinical application of the biopsychosocial model . In The Journal of Medicine and Philosophy: A Forum for Bioethics and Philosophy of Medicine , 6 ( 2 ), 101–124. [ PubMed ] [ Google Scholar ]
• Fairchild AJ, & MacKinnon DP (2009). A general model for testing mediation and moderation effects . Prevention Science , 10 ( 2 ), 87–99. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Franck C, Grandi SM, & Eisenberg MJ (2013). Taxing junk food to counter obesity . American Journal of Public Health , 103 ( 11 ), 1949–1953. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Gibbs BB, Hergenroeder AL, Perdomo SJ, Kowalsky RJ, Delitto A, & Jakicic JM (2018). Reducing sedentary behaviour to decrease chronic low back pain: the stand back randomised trial . Occup Environ Med , 75 ( 5 ), 321–327. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Glanz K, Rimer BK, & Viswanath K (Eds.). (2015). Health Behavior: Theory, Research, and Practice (5th ed.). San Francisco, CA: Jossey Bass. [ Google Scholar ]
• Glanz K, Rimer BK, & Viswanath K (2015). Theory, research, and practice in health behavior In: Glanz K, Rimer BK, & Viswanath K. (Eds.). Health Behavior: Theory, Research, and Practice . 5th ed. (pp. 23–41). San Francisco, CA: Jossey Bass. [ Google Scholar ]
• Glass TA, & McAtee MJ (2006). Behavioral science at the crossroads in public health: extending horizons, envisioning the future . Social Science & Medicine , 62 ( 7 ), 1650–1671. [ PubMed ] [ Google Scholar ]
• Glymour MM (2006). Using causal diagrams to understand common problems in social epidemiology In Oakes JM & Kaufman JS (Eds.), Methods in social epidemiology (1st ed., pp. 393–428). San Francisco, CA: Jossey-Bass. [ Google Scholar ]
• Green LW. , & Kreuter MW. (2005). Health program planning: An educational and ecological approach (4th ed.). New York: McGraw-Hill. [ Google Scholar ]
• Greenland S, Pearl J, & Robins JM (1999). Causal diagrams for epidemiologic research . Epidemiology , 37–48. [ PubMed ] [ Google Scholar ]
• Halen BT, de Ridder D, Freeman R, Swift S, Berghmans B, & Lee J (2010). An International Urogynecology Association (IUGA)/International Continence Society (ICS) joint report on the terminology for female pelvic floor dysfunction . Neurourol Urodyn , 29 , 4–20. [ PubMed ] [ Google Scholar ]
• Harlow BL, Bavendam TG, Palmer MH, Brubaker L, Burgio KL, Lukacz ES, … & Simons-Morton D. (2018). The prevention of lower urinary tract symptoms (PLUS) research consortium: A transdisciplinary approach toward promoting bladder health and preventing lower urinary tract symptoms in women across the life course . Journal of Women’s Health , 27 ( 3 ), 283–289. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Harris JL, Shehan C, Gross R, Kumanyika S, Lassiter V, Ramirez AG, & Gallion K (2015). Food advertising targeted to Hispanic and Black youth: Contributing to health disparities . Rudd Center for Food Policy & Obesity. [ Google Scholar ]
• Joffe M, & Mindell J (2006). Complex causal process diagrams for analyzing the health impacts of policy interventions . American Journal of Public Health , 96 ( 3 ), 473–479. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Johnston LM, Matteson CL, & Finegood DT (2014). Systems science and obesity policy: a novel framework for analyzing and rethinking population-level planning . American Journal of Public Health , 104 ( 7 ), 1270–1278. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Kanter G, Komesu YM, Qaedan F, Jeppson PC, Dunivan GC, Cichowski SB, & Rogers RG (2016). Mindfulness-based stress reduction as a novel treatment for interstitial cystitis/bladder pain syndrome: a randomized controlled trial . International Urogynecology Journal , 27 ( 11 ), 1705–1711. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Kia-Keating M, Dowdy E, Morgan ML, & Noam GG (2011). Protecting and promoting: An integrative conceptual model for healthy development of adolescents . Journal of Adolescent Health , 48 ( 3 ), 220–228. [ PubMed ] [ Google Scholar ]
• Krieger N (2005). Embodiment: a conceptual glossary for epidemiology . Journal of Epidemiology & Community Health , 59 ( 5 ), 350–355. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Larsman P, Kadefors R, & Sandsjö L (2013). Psychosocial work conditions, perceived stress, perceived muscular tension, and neck/shoulder symptoms among medical secretaries . International Archives of Occupational and Environmental Health , 86 ( 1 ), 57–63. [ PubMed ] [ Google Scholar ]
• Leischow SJ, & Milstein B (2006). Systems thinking and modeling for public health practice . American Journal of Public Health , 96 ( 3 ) 403–405. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Lezine DA, & Reed GA (2007). Political will: a bridge between public health knowledge and action . American Journal of Public Health , 97 ( 11 ), 2010–2013. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Lukacz ES, Bavendam TG, Berry A, Fok CS, Gahagan S, Goode PS, … & Brady SS. (2018). Defining bladder health in women and girls: Implications for research, clinical practice, and public health promotion . Journal of Women’s Health , 27 ( 8 ) 974–981. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• McLeroy KR, Bibeau D, Steckler A, & Glanz K (1988). An ecological perspective on health promotion programs . Health Education Quarterly , 15 ( 4 ), 351–377. [ PubMed ] [ Google Scholar ]
• Minassian VA, Bazi T, & Stewart WF (2017). Clinical epidemiological insights into urinary incontinence . International Urogynecology Journal , 28 ( 5 ), 687–696. [ PubMed ] [ Google Scholar ]
• National Institutes of Health (n.d.). Find Funding: NIH Guide for Grants and Contracts . Retrieved September 10, 2019 from https://grants.nih.gov/funding/searchguide/index.html#/
• Norton P, & Brubaker L (2006). Urinary incontinence in women . The Lancet , 367 ( 9504 ), 57–67. [ PubMed ] [ Google Scholar ]
• Nusslock R, & Miller GE (2016). Early-life adversity and physical and emotional health across the lifespan: A neuroimmune network hypothesis . Biological Psychiatry , 80 ( 1 ), 23–32. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• O’Mara-Eves A, Brunton G, McDaid G, Oliver S, Kavanagh J, Jamal F, … & Thomas J. (2013). Community engagement to reduce inequalities in health: a systematic review, meta-analysis and economic analysis . Public Health Research , 1 ( 4 ). [ PubMed ] [ Google Scholar ]
• Park J, & Palmer MH (2015). Factors associated with incomplete bladder emptying in older women with overactive bladder symptoms . Journal of the American Geriatrics Society , 63 ( 7 ), 1426–1431. [ PubMed ] [ Google Scholar ]
• Podnar S, & Vodušek DB (2015). Lower urinary tract dysfunction in patients with peripheral nervous system lesions . Handbook of Clinical Neurology , 130 , 203. [ PubMed ] [ Google Scholar ]
• Richard L, Gauvin L, & Raine K (2011). Ecological models revisited: their uses and evolution in health promotion over two decades . Annual Review of Public Health , 32 , 307–326. [ PubMed ] [ Google Scholar ]
• Robinson D, Hanna-Mitchell A, Rantell A, Thiagamoorthy G, & Cardozo L (2017). Are we justified in suggesting change to caffeine, alcohol, and carbonated drink intake in lower urinary tract disease? Report from the ICI-RS 2015 . Neurourology and Urodynamics , 36 ( 4 ), 876–881. [ PubMed ] [ Google Scholar ]
• Sallis JF, & Glanz K (2009). Physical activity and food environments: solutions to the obesity epidemic . The Milbank Quarterly , 87 ( 1 ), 123–154. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Sallis JF, Owen N. Ecological models of health behavior In Glanz K, Rimer BK, Viswanath K, eds. Health Behavior: Theory, Research, and Practice . 5th ed. San Francisco, CA: Jossey Bass; 2015: 43–64. [ Google Scholar ]
• Simons-Morton B, McLeroy KR, & Wedndel ML (2012). Behavior Theory in Health Promotion Practice and Research . Burlington, MA: Jones & Bartlett Learning. [ Google Scholar ]
• Smith AL, Hantsoo L, Malykhina AP, File DW, Valentino R, Wein AJ, … &Epperson CN (2016). Basal and stress-activated hypothalamic pituitary adrenal axis function in postmenopausal women with overactive bladder . International Urogynecology Journal , 27 ( 9 ), 1383–1391. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Solar O, & Irwin A A conceptual framework for action on the social determinants of health . Social Determinants of Health Discussion Paper 2 (Policy and Practice) . 2010. [02/08/2015] [ Google Scholar ]
• Substance Abuse and Mental Health Services Administration (SAMHSA). (2017). Strategic Prevention Framework . Retrieved June 2, 2019 from https://www.gaspsdata.net/sites/default/files/spf_brochure_1.12.17_approved.pdf
• Van der Velde J, Laan E, & Everaerd W (2001). Vaginismus, a component of a general defensive reaction. An investigation of pelvic floor muscle activity during exposure to emotion-inducing film excerpts in women with and without vaginismus . International Urogynecology Journal , 12 ( 5 ), 328–331. [ PubMed ] [ Google Scholar ]
• Van Ryn M, & Heaney CA (1992). What’s the use of theory? Health Education Quarterly , 19 ( 3 ), 315–330. [ PubMed ] [ Google Scholar ]
• Vandenbroeck P, Goossens J & Clemens M (2007). Foresight, Tackling Obesities: Future Choices – Obesity System Atlas . Retrieved June 2, 2019 from https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/295153/07-1177-obesity-system-atlas.pdf
• Warnecke RB, Oh A, Breen N, Gehlert S, Paskett E, Tucker KL, … & Hiatt RA. (2008). Approaching health disparities from a population perspective: the National Institutes of Health Centers for Population Health and Health Disparities . American Journal of Public Health , 98 ( 9 ), 1608–1615. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• W. K. Kellogg Foundation. (2004). Using logic models to bring together planning, evaluation, and action: logic model development guide . Michigan: Kellogg Foundation. [ Google Scholar ]
• World Health Organization, Regional Office for the Eastern Mediterranean . (1995). Constitution of the World Health Organization; https://apps.who.int/iris/handle/10665/121457 [ Google Scholar ]
• Yousefichaijan P, Sharafkhah M, Rafiei M, & Salehi B (2016). Attention-deficit/hyperactivity disorder in children with overactive bladder; a case-control study . Journal of Renal Injury Prevention , 5 ( 4 ), 193. [ PMC free article ] [ PubMed ] [ Google Scholar ]

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 ...

19 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

Very educating and fantastic,good to be part of you guys,I appreciate your enlightened concern.

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!

Thank you great insight

Superb. Thank you so much.

Hello Gradcoach! I’m excited with your fantastic educational videos which mainly focused on all over research process. I’m a student, I kindly ask and need your support. So, if it’s possible please send me the PDF format of all topic provided here, I put my email below, thank you!

I am really grateful I found this website. This is very helpful for an MPA student like myself.

I’m clear with these two terminologies now. Useful information. I appreciate it. Thank you

I’m well inform about these two concepts in research. Thanks

I found this really helpful. It is well explained. Thank you.

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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

Last Updated May 6, 2023 10:37 AM

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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Conceptual Framework – How to Develop it for Research

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In academic writing, a conceptual framework serves as a key component of the research methodology , providing a schematic representation of the concepts and their proposed relationships. This tool not only guides data collection and interpretation but also clarifies the research question and hypothesis. The conceptual framework aims to make research conclusions more meaningful and generalizable. It outlines the purpose and the importance of the research topic .

Inhaltsverzeichnis

• 1 Conceptual Framework – In a Nutshell
• 2 Definition: Conceptual framework
• 3 Conceptual framework: Independent vs. Dependent variables
• 4 Conceptual framework: Moderating variables
• 5 Conceptual framework: Mediating variables
• 6 Conceptual framework: Control variables

Conceptual Framework – In a Nutshell

• The conceptual framework is a model used to show the relationship between the independent vs. dependent variables in a research problem .
• Researchers consider several variables in a conceptual framework, including control variables, mediating variables, and monitoring variables.
• It is important to identify control variables in a conceptual framework to minimize their effect on the findings of a study.

Definition: Conceptual framework

A conceptual framework is a visual model that illustrates the anticipated relationship between the cause and effect variables. It highlights the research goals and creates a layout of their relationship to form meaningful conclusions. The conceptual framework is usually drawn from the literature review during the early stages of research to form appropriate research questions .

Conceptual framework: Independent vs. Dependent variables

Researchers define independent vs. dependent variables to test for cause and effect when developing a conceptual framework.

Example of dependent vs. independent variables

You want to investigate whether drivers with more experience are involved in fewer accidents.

• Hypothesis: The more experience a driver has, the fewer accidents they are likely to be involved in .
• Independent variable:  The  years of experience
• Dependent variable:  The expected cause and the number of accidents

Unlike above, causal relationships in a conceptual framework usually have more than one independent variable .

Conceptual framework: Moderating variables

Moderating variables influence the strength of the relationship between two variables in a conceptual framework. They are used to determine the external validity of the research conclusions based on their ability to strengthen, negate or otherwise affect the association between the independent vs. dependent variables.

Moderating variables are helpful in a conceptual framework because they illustrate the relationship between different variables in a research topic .

Income levels can predict general happiness, although the relationship may be stronger for younger people than for older workers. Age is the moderating variable in this conceptual framework.

Moderators can be divided into categorical variables such as religion, blood group, or race and quantitative variables like height, age, and income.

In our study of drivers’ experience and accidents, we can introduce age as the moderating variable. In this case, a driver’s age can influence the effect of years of experience on the number of accidents. The researcher expects that ‘age’ moderates the effect of experience on road safety.

Conceptual framework: Mediating variables

A conceptual framework also takes mediating variables into account. They illustrate the impact of an independent variable on a dependent variable by showing how and why the effect occurs. A variable is considered a mediator if:

• It is caused by an independent variable.
• It affects the dependent variable.
• The statistical correlation between the dependent and the independent variable is more significant when it is considered than when it’s not.

Researchers use mediation analysis to test if a variable is a mediator using ANOVA and linear regression analysis. ANOVA (Analysis of Variance) tests the presence and strength of the statistical differences between the means calculated from several independent samples.

ANOVA: Determines the effects of age, gender, and disposable income on average consumer spending per month.

Linear regression: Predicts the value of a dependent variable based on the value of the independent variable.

The main aims of linear regression in a conceptual framework are to test the effectiveness of a group of predictor values in predicting a result and identifying the significant predictors of the outcome.

An individual’s body weight has a linear relationship with their weight. The researcher expects that as the height of the person increases, their weight increases. A set of observations can be plotted on a scatter plot to illustrate the strength of the correlation between the variables.

Conceptual framework: Control variables

Control variables are also considered in the conceptual framework. They define factors controlled by the researcher as it may affect the findings of a study even though it is of no interest to the researcher when designing a conceptual framework.

Control variables are used to improve the validity of a research study by reducing the effect of other variables outside the scope of the study. They help researchers to determine the relationship between the key variables under observation.

Control variables can be managed directly by keeping them constant, for instance choosing participants within the same age group. They can also be managed indirectly by using random samples to reduce their effect.

Example of control variables in the conceptual framework

In our study of driver’s experience and accident rates, the weather may affect the rate of accidents. However, our primary focus is not on the relationship between the weather and accident rates, although it may affect the findings of our study. Therefore, The ‘weather’ is added as a control variable in our conceptual framework.

If a researcher fails to control some variables, it may be difficult to prove that they did not affect the research outcome. Control variables are used in experimental research to guarantee that the observable results are exclusively caused by the experimental design.

Variables in a conceptual framework can be controlled by:

• Random assignment – Selecting random groups ensures there are no identifiable differences, which may skew your conclusions.
• Statistical controls – You can isolate the effects of the control variable by measuring and controlling it.
• Standardized procedures – Researchers should ensure the same methods are applied in all the groups in a study. Only the independent variables should be altered across groups to observe how they affect the dependent variable.

What is the conceptual framework in research?

It is an illustration of the relationship between variables in a study. It is used to form the hypothesis that guides the methods of research.

What are control variables?

Control variables are factors that are directly or indirectly controlled by the researchers. They are extraneous variables that may affect the observations in a study.

Where are conceptual frameworks used?

Conceptual frameworks are used in multiple social sciences and humanities. They help in formulating and investigating the research problem.

What is a moderating variable in a conceptual framework?

A moderating variable influences the effect of an independent variable on a dependent variable. It is used to measure the impact of an additional variable on the dependent-independent variable relationship.

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