Should a Conceptual Framework Show Only Relationships You Plan to Examine?

Does Every Relationship in Your Framework Have to Be Tested?

Your literature review suggests that several concepts are connected. Your conceptual framework could show all of those relationships, producing a rich picture of the phenomenon.

But your study will examine only some of them.

Should the remaining relationships stay in the framework because they matter conceptually, or should you remove anything your research questions and analysis will not directly address?

The answer depends on what your framework is intended to do. A study-specific framework should remain closely aligned with the research, but conceptual frameworks can sometimes provide context beyond the relationships directly examined. The problem arises when the diagram makes those two roles indistinguishable.

Emphasize What the Study Examines, but Broader Relationships Can Sometimes Remain

Decide What Job Each Relationship Is Doing in the Framework

A Conceptual Framework Should Align With the Research Questions

A conceptual framework is not independent of the rest of the research design. It helps organize the concepts and relationships through which the research problem is understood, so the framework, research questions, and methodological choices should fit together coherently.

If your research question asks whether perceived usefulness predicts intention to adopt generative AI, a relationship between those concepts would naturally appear in a framework designed around that question.

If the diagram also contains ten other arrows that never appear in the research questions, hypotheses, data collection, or analysis, readers may reasonably wonder what those arrows are doing there.

This does not make every additional relationship automatically wrong. It means each relationship needs an identifiable function.

Some Relationships Are Focal and Others Are Contextual

A useful distinction is between relationships the study is designed to investigate and relationships included to explain the broader conceptual setting.

For example, a researcher examining faculty AI adoption may focus empirically on the relationships among AI self-efficacy, perceived usefulness, and adoption intention. The researcher might nevertheless acknowledge that institutional policy shapes the broader environment in which these relationships operate.

Whether institutional policy belongs in the figure depends on how important that contextual relationship is to understanding the framework and whether its inclusion can be communicated without implying that it will be directly tested.

Not Every Known Relationship Needs to Be Drawn

The literature may describe many relationships surrounding your phenomenon. A conceptual framework does not need to reproduce the entire literature as a network diagram.

Selection is part of framework construction. Jabareen describes conceptual frameworks as networks of interlinked concepts that provide an interpretive understanding of phenomena, while broader methodological treatments emphasize that frameworks should be constructed in relation to the particular research problem and inquiry.

Including every relationship encountered during the literature review can obscure rather than clarify the study's conceptual argument.

The same principle applies when deciding which concepts deserve to appear in the framework. Relevance to the broader topic is not identical to necessity in the study-specific model.

A Framework Is Not Necessarily the Same Thing as a Statistical Model

This distinction is especially important in quantitative research.

A conceptual framework expresses the researcher's conceptual understanding or propositions about a phenomenon. A statistical model specifies relationships among measured variables for estimation under particular assumptions.

The two should be aligned, but they need not always be visually identical.

A conceptual framework might acknowledge a contextual influence that is not included in a particular regression model. Conversely, a statistical model may include control variables for estimation purposes even when those variables are not central enough to appear prominently in the conceptual framework.

Treating the conceptual framework as a screenshot of the eventual statistical equation can therefore be unnecessarily restrictive.

But Unexamined Relationships Can Create False Expectations

Imagine a framework showing:

Institutional support → AI self-efficacy → perceived usefulness → adoption intention

A reader would reasonably expect the study to address this pathway in some meaningful way. If the researcher measures only perceived usefulness and adoption intention, the first two relationships become difficult to justify as focal parts of the study-specific framework.

The issue is not merely graphical. The diagram communicates scope.

Different Visual Treatments Can Clarify Different Roles

When contextual relationships genuinely need to remain, visual conventions can distinguish them from focal relationships.

For example, a researcher might use solid arrows for relationships directly examined and dotted lines for contextual relationships discussed but not tested. Another framework might place broader contextual factors around the focal model rather than connecting them with identical directional arrows.

There is no universal visual convention requiring a particular line style. Whatever convention you choose should be explained explicitly and used consistently.

This follows the broader principle that an arrow needs an explicitly interpretable meaning. A dotted arrow is no more self-explanatory than a solid one unless you define what the difference represents.

The Appropriate Boundary Depends on the Type of Study

In a tightly specified hypothesis-testing study, the framework may reasonably focus almost entirely on relationships that will be tested.

An exploratory qualitative study may use a conceptual framework differently. The framework may contain sensitizing concepts and possible connections that guide data collection without assuming that each relationship will be formally tested. Indeed, qualitative inquiry may investigate how relationships emerge, change, or acquire meaning rather than begin with a fixed set of hypotheses.

Mixed-methods research may occupy another position. Some relationships might be tested quantitatively while others are explored qualitatively.

Accordingly, “Will this relationship be statistically tested?” is too narrow a criterion. A better question is: “What role does this relationship play in the inquiry, and will the study meaningfully address that role?”

There Is a Difference Between Not Testing and Not Examining

The word test can cause unnecessary confusion.

Not all research tests hypotheses. A qualitative study may examine a proposed relationship through interviews, observations, documents, or interpretive analysis. An exploratory study may investigate whether a presumed connection is even meaningful to participants.

For this reason, the broader standard is whether the relationship forms part of what the study intends to examine, not whether a statistical significance test will be performed.

Every Additional Relationship Adds an Interpretive Obligation

Each arrow introduces another proposition that readers may expect you to explain.

You need to clarify what supports the relationship, what the connection means, and whether it is focal or contextual.

As relationships accumulate, those obligations multiply. A framework containing six concepts can potentially contain many pairwise connections, but showing all possible links rarely improves understanding.

Conceptual completeness is therefore not the same as graphical completeness. A framework can acknowledge that reality is more complicated than the model while deliberately representing only the relationships necessary for the study.

Separating the Relationships You Examine From the Ones That Provide Context

Both decisions can be defensible. What would be misleading is to draw institutional policy with the same type of arrow as the two focal predictors and then leave that relationship completely unaddressed in the study.

Common Mistakes When Choosing Which Relationships to Show

Give Every Relationship a Clear Status

For every relationship you plan to show, ask whether it is focal, contextual, exploratory, or otherwise necessary to the framework.

Framework boundaries are therefore methodological decisions as much as graphical ones. The goal is not to draw everything that might be true. It is to represent enough of the conceptual structure for readers to understand what the study is actually doing and why.

Does Every Relationship Have a Clear Role?

Questions About Relationships Included in Conceptual Frameworks

Show What the Study Needs, Not Every Relationship the Literature Can Imagine

How to Cite This Guide

This guide is intended to be read, shared, and used in research, teaching, and academic work. If you draw on its ideas, explanations, or other content, please acknowledge the source by citing the guide. Doing so gives appropriate credit and helps your readers locate the original resource.