Conceptual Framework vs Theoretical Framework: Differences and Examples

By Dr. Zubair Khalid, DVM, MS, PhD · 2026-10-02

A theoretical framework is the borrowed lens a study looks through. A conceptual framework is the researcher's own map of the problem, showing which factors matter, how they relate, and why the study is worth doing at all. The two are related, they inform each other, and they are not the same thing.

You will meet both terms in thesis proposals, grant applications, journal manuscripts, and methods courses. Reviewers ask where your framework is, and a vague answer costs you credibility. This article explains what each framework does, how they differ, how to build them, and how they map onto variables and statistical models, using a worked example from vaccine uptake research.

Quick Answer

A theoretical framework is a logically developed and connected set of concepts and premises, drawn from one or more established theories, that scaffolds a study. The researcher selects the concepts, unites them through logical connections, and relates them to the research problem [2].
A conceptual framework is a description of how the researcher understands the factors or variables involved in the study and their relationships to one another [3]. It also justifies why the study should be conducted: what is known, what is missing, and what the findings might add [2].
Rule of thumb: the theoretical framework supplies the lens and constructs; the conceptual framework supplies the map and the argument for the study [3].
Theoretical frameworks are often taken from established literature. Conceptual frameworks are built by the researchers doing the study [3].
The conceptual framework is broader: it can hold established theories plus the researchers' own emergent ideas, and it is often more mechanistic and malleable than the theoretical framework [3].
Both must connect to your literature review. When the review, theoretical framework, and conceptual framework are disconnected, findings may be unsupported and misalignment can cost time and money [3].

What Is a Theoretical Framework?

A theory is a set of interrelated constructs, definitions, and propositions that present a systematic view of phenomena by specifying relations among variables, with the purpose of explaining and predicting those phenomena [4]. Concepts are the building blocks of a theory, and variables are the operational forms of constructs: they define how a construct is measured in a specific situation [7].

A theoretical framework is the structure that can hold or support a theory of a research study [4]. In practice it is more than naming a theory. It encompasses the theory plus a narrative explanation of how you use that theory and its assumptions to investigate your research problem [5]. It helps explain a phenomenon through a particular lens and challenges and extends existing knowledge within the limits of that lens [3].

The theoretical framework does real work in a study. It shapes the questions you ask, guides how data are collected and analyzed, informs the discussion of results, and reveals your subjectivities as a researcher [3]. It also lets you state your theoretical assumptions clearly and articulate which variables will be analyzed, which focuses your data analysis and interpretation [4]. It limits the scope of relevant data by focusing attention on specific variables [5].

One point that surprises many students: a theoretical framework does not rationalize the need for the study [3]. That job belongs to the conceptual framework.

What Is a Conceptual Framework?

A conceptual framework is a description of the way a researcher understands the factors or variables involved in the study and their relationships to one another [3]. It articulates the phenomenon through written descriptions, a visual diagram, or both, and it should be coherent with the paper's theoretical framing [3]. It should also describe the relationships among the components of the investigation and address gaps or contradictions found in the literature review [3].

Varpio and colleagues frame the conceptual framework as the justification for why a given study should be conducted. It describes the state of known knowledge, usually through a literature review, identifies gaps in understanding, and outlines the methodological underpinnings. It answers two questions: why is this research important, and what contribution might the findings make to what is already known [2].

Definitions here are not standardized across fields. Luft et al. treat the conceptual framework as the researcher's map or argument for the study [3], while Kivunja uses a broader definition: the logical conceptualization of the entire research project, covering topic, problem, questions, literature, theories, methodology, analysis, and conclusions [4]. Kivunja's analogy is that the conceptual framework is the house and the theoretical framework is one room in it, so the two terms should not be used interchangeably [4]. Check which convention your field, journal, or committee expects before you commit to a structure.

How to Build Each Framework

Start with the literature. For a theoretical framework, USC Libraries suggest a sequence: review the literature, list relevant constructs and variables, group them into independent and dependent categories where applicable, choose the theory that best explains the relationships among your key variables, and discuss its assumptions [5].

For the conceptual framework, the work is construction, not selection. Combine the constructs your theory supplies with the gap your literature review identified and with context-specific factors from your own setting [3]. Draw the relationships. State the presumed direction of each arrow. If your theory is too abstract to use directly, it must be operationalized: turn abstract concepts into measurable observations, and building the theoretical framework is that step [2].

Theory, theoretical framework, and conceptual framework inform each other. Researchers may move back and forth among them as a design is refined [2]. There is no single right theory for a research question. Each theory is a lens that shows the phenomenon differently, and the choice should align with the conceptual framework [2].

Independent and Dependent Variables in a Framework

A framework becomes testable when its constructs become variables. An independent variable is the presumed cause, the condition the researcher changes or controls. A dependent variable is the presumed effect, the outcome the researcher measures [6].

A useful test sentence for direction is: "The [independent variable] causes a change in [dependent variable] and it is not possible that [dependent variable] could cause a change in [independent variable]" [6]. If the sentence sounds absurd in reverse, your direction is probably right.

In a regression model, this mapping is direct. For a binary outcome, logistic regression estimates the log odds of the outcome:

$$ \log\left(\frac{p}{1-p}\right) = \beta_0 + \beta_1 x_1 + \beta_2 x_2 + \cdots + \beta_k x_k $$

Here $p$ is the probability that the dependent variable equals 1, $\beta_0$ is the intercept, each $x_i$ is an independent variable, and each $\beta_i$ is the change in log odds associated with a one-unit increase in $x_i$, holding the other variables constant. Exponentiating a coefficient, $e^{\beta_i}$, gives an odds ratio. An odds ratio above 1 means higher odds of the outcome per unit of that variable; below 1 means lower odds. The framework tells you which variables belong in the equation and what sign you expect.

Worked Example

This example is illustrative. The data are simulated, not real, and the numbers show how a framework maps onto variables and a model, not what happens in actual hospitals.

Research question: Which beliefs and workplace factors are associated with whether hospital nurses receive the seasonal influenza vaccine?

Theoretical framework (borrowed lens): the Health Belief Model. The HBM was developed in the 1950s by U.S. Public Health Service social psychologists to explain why few people participated in disease prevention and detection programs such as free tuberculosis chest X-ray screening [7]. Its constructs are perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy [7]. Each construct becomes a measured variable, for example a 1 to 5 Likert score [7].

Conceptual framework (researcher-built map): combines the HBM constructs with the literature gap and the researchers' own context [3]. Diagram in words:

[Perceived susceptibility +] [Perceived severity +] [Perceived benefits +] [Perceived barriers -] [Cue to action: employer reminder email +] -> [Dependent variable: vaccinated this season, yes/no]; covariate: age.

Arrows show presumed direction. The signs are the hypotheses.

Variables: independent variables (presumed causes) are the five belief and cue variables. The dependent variable (presumed effect) is vaccination status [6].

Analysis implied by the framework: logistic regression, vaccinated ~ susceptibility + severity + benefits + barriers + reminder + age.

Simulation to show the mapping (Python, numpy 2.4.4, statsmodels 0.15.0):

import numpy as np
import statsmodels.api as sm

rng = np.random.default_rng(2026)
n = 500
susceptibility = rng.integers(1, 6, n)
severity = rng.integers(1, 6, n)
benefits = rng.integers(1, 6, n)
barriers = rng.integers(1, 6, n)
reminder = rng.integers(0, 2, n)
age = rng.integers(22, 65, n)

linear_predictor = (-2.0 + 0.35 * susceptibility + 0.10 * severity
                    + 0.45 * benefits - 0.50 * barriers
                    + 0.80 * reminder + 0.01 * (age - 40))
prob = 1 / (1 + np.exp(-linear_predictor))
vaccinated = rng.binomial(1, prob)

X = sm.add_constant(np.column_stack([susceptibility, severity, benefits,
                                     barriers, reminder, age]))
model = sm.Logit(vaccinated, X).fit()
print(np.exp(model.params))
print(np.exp(model.conf_int()))

Result: 204 of 500 vaccinated (40.8%). Fitted odds ratios (95% CI): susceptibility 1.28 (1.11 to 1.49), p = 0.001; severity 1.07 (0.93 to 1.23), p = 0.36; benefits 1.47 (1.27 to 1.71), p < 0.001; barriers 0.57 (0.49 to 0.67), p < 0.001; reminder 2.90 (1.92 to 4.39), p < 0.001; age 1.02 per year (1.00 to 1.03), p = 0.027; McFadden pseudo R-squared 0.167.

Reading: the theoretical framework told us which constructs to measure. The conceptual framework told us how we think they connect to the outcome in this setting and which model to fit. An odds ratio of 0.57 for barriers means each one-point increase in the barriers score is associated with 43 percent lower odds of vaccination in this simulated dataset, holding the other variables constant. It does not mean 43 percent of nurses changed their behavior, and it does not establish causation. Swapping the theory, for example to the Theory of Planned Behavior, would change the constructs, and the conceptual framework would be rebuilt around them.

The same pattern applies to an antibiotic-use study: theory equals a behavior theory such as the HBM or the Theory of Planned Behavior; conceptual framework equals a diagram linking prescriber beliefs, patient expectations, and guideline reminders to the outcome "antibiotic prescribed for viral respiratory infection."

How to Read and Interpret Frameworks

Read a theoretical framework by asking which lens the authors chose and what that lens makes visible or hides. The framework shapes the questions asked, how data are collected and analyzed, and how results are discussed [3]. If the authors claim a theory but never use its constructs in measurement or analysis, the framework is decoration.

Read a conceptual framework by tracing the arrows. Which factors are proposed as causes, which as outcomes, and which as covariates or confounders? Does the diagram address the gap the literature review identified [3]? Does the text description match the figure?

For quantitative work, the framework should predict the model. If your diagram shows a moderator or a mediator, your analysis should test one. If your diagram shows five independent variables, a model with two of them is misaligned. When the literature review, theoretical framework, and conceptual framework are disconnected, the study suffers [3].

Common Mistakes

Using the two terms interchangeably. Varpio et al. note the terms are too often used interchangeably or without a clear understanding of their differences [1]. They describe different things: one is a lens, the other is a map and an argument [2][3]. Kivunja's house-and-room analogy makes the containment relationship concrete [4].
Expecting the theoretical framework to justify the study. It does not rationalize the need for the research; the conceptual framework does that [3].
Treating one definition as universal. Varpio et al. and Luft et al. treat the conceptual framework as the researcher's argument or map [2][3], while Kivunja treats it as the umbrella for the whole project [4]. Match the convention of your field.
Naming a theory without operationalizing it. When a theory is too abstract to use directly, its concepts must be turned into measurable observations, and building the theoretical framework is that step [2].
Skipping the diagram. A conceptual framework should articulate the phenomenon through written descriptions, visual representations, or both [3]. Prose alone often hides broken logic.
Letting the review, frameworks, and methods drift apart. Misalignment between these parts can leave findings unsupported [3].
Confusing constructs with variables. Concepts are the building blocks of a theory; variables are their operational forms, defining how a construct is measured in a specific situation [7].
Reversing cause and effect. Use the test sentence to check direction before you write hypotheses [6].

Limitations

Definitions are not standardized. The same phrase can mean the researcher's map in one paper and the umbrella for the entire project in another [3][4]. Read how each source uses the term before comparing them.

The most cited definitions here come from education research. Luft et al. and Varpio et al. write for that field, and their definitions transfer to clinical and life-science research in practice, but those papers do not test that transfer. Treat the transfer as reasonable convention, not as evidence.

The vaccine uptake numbers above are simulated. They illustrate how a framework maps to variables and a model. They are not empirical estimates of anything, and no clinical conclusion should be drawn from them.

Some quantitative fields use "conceptual model" or "directed acyclic graph" for a diagram that plays a similar role. That equivalence is not established here, so check your field's conventions and current guidance.

Finally, the choice of theory is not determined by the research question. Each theory is a lens that shows the phenomenon differently, and the choice should align with the conceptual framework [2]. Two research teams can study the same question with different theories and both be defensible.

Frequently Asked Questions

What is a conceptual framework in research?

It is a description of how the researcher understands the factors or variables in a study and their relationships to one another [3]. It also states why the study matters: what is known, what is missing, and what the findings might contribute [2]. It is usually built by the researchers instead of borrowed from the literature [3].

What is a theoretical framework?

It is a logically developed and connected set of concepts and premises, drawn from one or more theories, that scaffolds a study [2]. It encompasses a theory plus the narrative explanation of how you use that theory and its assumptions to investigate your problem [5]. It shapes your questions, your data collection, your analysis, and your discussion of results [3].

Can you give a conceptual framework example?

In the influenza vaccine example above, the conceptual framework is a diagram linking perceived susceptibility, severity, benefits, barriers, and an employer reminder to the outcome of vaccination status, with age as a covariate. It integrates the Health Belief Model constructs with the study context and the literature gap [3][7]. The arrows and signs encode the hypotheses.

How do you write a conceptual framework?

Review the literature and identify the gap. List the constructs and variables, grouping them into independent and dependent categories where applicable [5]. Choose the theory that best explains the relationships among your key variables; USC Libraries give these steps for the theoretical framework that feeds the conceptual one [5]. Then draw the relationships, state the presumed direction of each one, and write a short narrative that ties the diagram to your research question and methods [3].

How do independent and dependent variables fit into a framework?

The framework's constructs become measured variables. Independent variables are the presumed causes, the conditions you change or control; dependent variables are the presumed effects, the outcomes you measure [6]. In the worked example, the belief and cue variables are independent and vaccination status is dependent. The framework tells you which variables belong in the model and what sign you expect for each.