What Is a Conceptual Framework? | Examples & Tips

A conceptual framework identifies different variables in a study and illustrates the relationship between them.

Variables are quantities, traits, or conditions that can take on different values. An experiment tests the cause-and-effect relationship between an independent variable and a dependent variable, but it may also contain control variables, mediator variables, moderator variables, and confounding variables.

What Is a Conceptual Framework?

What is a conceptual framework in research?

A conceptual framework identifies the factors or variables that are relevant to a study and the relationship you expect to see between them.

Conceptual frameworks can be written out or illustrated visually. They are generally developed using information from a literature review and their structure may depend on your theoretical framework.

Conceptual frameworks should be created early in the research process, before you begin collecting data.

How to create a conceptual framework

Follow these steps to create your own conceptual framework.

Step 1: Choose your research question

A research question captures what you hope to learn through your study or experiment. Research questions often emerge through a literature review: as you describe the current state of your field or area of interest, you may start to identify gaps or open questions that you’d like to address.

Research question example
You’re reviewing literature on the positive impact of movement on well-being. However, you notice that much of this literature focuses on adults. You decide to investigate whether participation in a yoga program impacts self-esteem in teenagers.

Step 2: Select your independent and dependent variables

In order to test a cause-and-effect relationship related to your research question, you must identify the independent and dependent variables in your study. A study may include several independent variables that influence a dependent variable. However, we’ll focus on an example that includes only one of each for simplicity.

Independent and dependent variables example
Consider our previous example:

The independent variable is participation in a yoga program—you expect this “cause” to influence changes in the dependent variable.

The dependent variable, or the “effect,” is change in self-esteem. You expect participants who complete a yoga program to experience an increase in self-esteem compared to a control group that does not.

Step 3: Visualize your cause-and-effect relationship

Once you’ve determined your independent and dependent variables, you must describe how you expect them to interact.

A cause-and-effect relationship can be visualized in a diagram using boxes and arrows. Each variable is included in a box. An arrow is drawn pointing from the “cause” to the “effect.”

Illustrating a cause-and-effect relationship

Step 4: Identify any other relevant variables

It’s important to identify any variables beyond the independent variable that could influence your results. Variables that should be considered include mediator, moderator, and control variables.

Mediator variables connect the independent and dependent variables. A mediator variable helps to better explain how an independent variable impacts a dependent variable. The mediator is affected by the independent variable and, in turn, impacts the dependent variable.

Mediator variable example
In our example, we predict that the independent variable, participation in a yoga program, influences the dependent variable, self-esteem. However, the mediating variable “mindfulness” lies between them. Participating in yoga increases mindfulness, which in turn improves self-esteem.

In a conceptual framework, you can illustrate the relationship between independent and dependent variables and a mediator variable. A mediator variable is included in a separate box, with an arrow pointing from the independent variable to it and from it to the dependent variable.

Mediator variable example

Moderator variables change the relationship between the independent and dependent variables. How the independent variable impacts the dependent variable changes depending on the value of the moderator variable. Unlike a mediator variable, a moderator variable is not influenced by the value of the independent variable.

Moderator variable example
Consider our example again. We’ve predicted that there is a relationship between participation in a yoga program and self-esteem. However, this relationship might be moderated by gender, with teenagers of different genders experiencing different effects from the program.

You can include moderator variables in a conceptual framework. A moderator variable is included in its own box, with an arrow pointing from it to the arrow connecting the independent and dependent variable. This emphasizes its effect on the cause-and-effect relationship.

Moderator variable example

Control variables are variables that are held constant so they don’t influence the study results. By keeping control variables the same, we can try to ensure that any changes to the dependent variable are actually caused by changes to the independent variable. A variable that is not controlled for and unintentionally influences study outcomes is called a confounding variable or confound.

Control variable example
In our example, it’s possible that previous yoga experience may impact our results. To prevent this, we can include only participants who have never done yoga before. By doing so, we effectively keep the control variable “yoga experience” set to “0” for all participants.

Control variables can be illustrated in a conceptual framework simply by including them in a box with an arrow pointing from them to the dependent variable.

Control variable example

Once you’ve illustrated all variables in a conceptual framework, you’re left with a diagram e that represents the predicted relationship between all relevant variables in your study.

Conceptual framework example

Frequently asked questions about conceptual frameworks

What is the difference between a conceptual framework, a theoretical framework, and a literature review?

The literature review, conceptual framework, and theoretical framework are all important steps in defining a research project.

A literature review is conducted early in the research process. Its purpose is to describe the current state of a research area, identify gaps, and emphasize the relevance of your own research question or study.

A theoretical framework is the lens through which a research question is viewed and answered. Different fields have their own assumptions, methods, and interpretations related to the same phenomenon that influence the choice of a theoretical framework.

Consider a neuroscientist and a social psychologist studying the construct “love.” They will each take a different approach, applying specialized methods and interpretations. In other words, they each use a unique theoretical framework that is guided by the existing theories of their field.

A conceptual framework describes the variables relevant to a study and how they relate to one another. This may include dependent and independent variables as well as any confounding variables that could influence results.

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

A variable is something that can take on different values. A study contains independent and dependent variables, control variables, and confounding variables that influence its results.

Dependent variables represent the outcome of a study. Researchers measure how they change under different values of the independent variable(s).

Independent variables are manipulated by the researcher to observe their effect on dependent variables.

Control variables are variables that are held constant to isolate the effect of the independent variable.

Confounding variables are variables that have not been controlled for that may influence a study’s results.

The expected relationship between these variables can be illustrated using a conceptual framework.

What is the difference between mediator and moderator variables?

A mediator (or mediating variable) is a variable that falls between a dependent and independent variable; that is, it connects them.

For example, the dependent variable “academic performance” is influenced by the independent variable “exercise” via the mediator variable “stress.” Exercise reduces stress, which in turn improves academic performance. Stress therefore mediates the relationship.

A moderator (or moderating variable) influences how an independent variable influences a dependent variable; in other words, it impacts their relationship.

For example, the relationship between the dependent variable “mental health” and the independent variable “social media use” may be influenced by the moderator “age.” The impact that social media has on mental health depends on someone’s age.

The expected influence of mediator and moderator variables can be captured in a conceptual framework.

Is this article helpful?
Emily Heffernan, PhD

Emily has a bachelor's degree in electrical engineering, a master's degree in psychology, and a PhD in computational neuroscience. Her areas of expertise include data analysis and research methods.