Can Qualitative Research Have Variables?

Does Qualitative Research Have Independent and Dependent Variables?

Students are often taught to identify the variables in a study before doing almost anything else. That makes sense for many quantitative designs. Then they encounter a qualitative question such as: “How do first-generation university students experience the transition to higher education?”

Which part is the independent variable? Which is the dependent variable?

The difficulty may not be that the variables are hidden. The problem may be that the study is not organized around variables at all.

Qualitative research can certainly examine characteristics that differ across participants, cases, settings, or time. Qualitative datasets can also contain demographic and other variables. But many qualitative methodologies organize inquiry around experiences, meanings, practices, processes, cases, narratives, or concepts rather than relationships among predefined variables.

Qualitative Research Can Include Variables, but It Does Not Always Need Them

Variables Are One Way of Organizing Research, Not a Requirement for Every Study

Why variables are so prominent in quantitative research

A variable represents a characteristic that can take different values or categories across observations. Quantitative research frequently asks how variables are distributed, whether they differ among groups, or how they relate statistically to one another.

A study might ask whether academic self-efficacy predicts persistence, whether an instructional intervention affects examination performance, or whether engagement differs among academic programs. In each case, identifying the variables helps specify the analysis.

This logic fits naturally with research questions framed around measurable variation. The broader distinction among concepts, constructs, and variables helps explain how theoretical ideas can become empirical quantities or categories in such studies.

Many qualitative questions are asking something different

Qualitative research often seeks detailed understanding of how people experience, interpret, negotiate, construct, or respond to phenomena in particular contexts.

Consider the question:

How do doctoral students describe their experiences of receiving critical feedback during dissertation supervision?

The purpose is not necessarily to estimate the statistical effect of “critical feedback” on a dependent variable called “doctoral experience.” The researcher may instead investigate how participants interpret feedback, how supervisory relationships shape those interpretations, how responses develop over time, and what meanings participants attach to the experience.

Forcing these elements into independent-dependent terminology could impose an analytical structure that the study was not designed to use.

This is not an absolute quantitative-versus-qualitative divide. Research questions are more diverse than two sentence templates. The distinction simply illustrates why variable language fits some questions better than others.

Qualitative data can still contain variables

A qualitative dataset can contain characteristics that vary among participants or cases. An interview study might record age, academic discipline, years of experience, employment status, institution type, or other participant characteristics.

These are variables in the ordinary methodological sense. They may help researchers describe the sample, examine patterns across cases, or make purposive sampling decisions.

For example, a qualitative researcher studying teachers' experiences with generative AI might intentionally recruit teachers from different disciplines and career stages. Discipline and career stage can be recorded as variables even though the primary qualitative analysis is not a statistical model relating them to a dependent variable.

Having variables does not make a study quantitative

A common misconception is that the presence of variables automatically makes research quantitative.

Methodological classification depends on the research purpose, design, evidence, and analytical approach rather than the mere existence of participant characteristics that can vary.

A qualitative interview study does not become quantitative because the sample includes participants of different ages. Nor does a case study become quantitative because cases are classified by institution type.

Likewise, qualitative researchers can use counts or descriptive numbers without transforming the entire study into quantitative research. The methodological role of those numbers matters.

Independent and dependent variables are often particularly unsuitable

The strongest confusion usually concerns the expectation that every study must contain an independent variable and a dependent variable.

Those labels describe particular explanatory or analytical roles. They are especially intuitive in experiments and in quantitative models that designate explanatory and response variables.

Many qualitative designs do not seek to estimate this kind of relationship. Asking researchers to identify an independent and dependent variable can therefore distort the study before data collection even begins.

The broader question of whether independent and dependent labels are always appropriate applies even within quantitative research, and the limitation is still more obvious when the inquiry is qualitative and interpretive.

Qualitative methodologies organize inquiry differently

There is no single qualitative vocabulary because qualitative research includes diverse methodological traditions.

Phenomenological studies may focus on lived experience and its meaning. Grounded theory approaches investigate processes and develop theoretical categories through analysis. Ethnographic research may examine cultural practices, meanings, interactions, and social organization. Case study research investigates bounded cases in depth and in context. Narrative inquiry may center on stories and how experiences are constructed through them.

These traditions have their own methodological concepts. Replacing them indiscriminately with variable terminology can erase distinctions that matter to the design.

A theme is not simply a qualitative variable

A theme generally represents a patterned meaning identified through qualitative analysis. Depending on the analytical approach, themes may organize important aspects of participants' accounts in relation to the research question.

A theme is not automatically equivalent to a variable. Variables are typically defined in terms of values or categories that vary across observations. Themes may capture meanings that cut across accounts, operate at different levels, overlap, or depend heavily on context.

Researchers can sometimes transform qualitative codes or categories into variables for further analysis, but that is an additional analytical step. The original qualitative theme does not become a variable merely because both are ways of organizing information.

Codes and categories are not automatically variables either

Qualitative coding assigns labels to segments of data to support organization and interpretation. Categories may then bring related codes or observations together conceptually.

Researchers can quantify coded data, for example by creating a binary variable indicating whether a particular code appeared in each case. Once that transformation occurs, the resulting representation can function as a variable.

But the transformation changes what is being analyzed. Rich contextual material has been reduced to a structured representation for a particular purpose. That may be useful, but researchers should not confuse the representation with the full qualitative meaning from which it was derived.

Qualitative comparative analysis can use variable-like conditions without becoming conventional variable-centered research

Some qualitative and case-oriented approaches explicitly compare conditions across cases. Qualitative Comparative Analysis, for example, examines configurations of conditions associated with outcomes using set-theoretic logic.

This illustrates why statements such as “qualitative research does not have variables” are too absolute. Methodological traditions differ considerably.

The better question is whether variable terminology accurately represents the analytical logic of the specific approach being used.

Mixed-methods research may use both variable-oriented and qualitative representations

Mixed-methods research makes the distinction particularly visible. A study might administer a survey measuring self-efficacy and then conduct interviews exploring how participants understand experiences that shaped their confidence.

The survey component may represent self-efficacy as a measured variable. The qualitative component may explore experiences, meanings, and processes that are not reduced to variable values.

Integration can then examine how the two forms of evidence relate. Researchers do not need to force one vocabulary onto both strands merely for terminological symmetry.

A Qualitative Study Without Independent and Dependent Variables

Academic rank and teaching experience can reasonably be called variables if the researcher needs that terminology. But the study does not therefore require a dependent variable called “AI adoption.” Doing so would impose a relationship that the research question did not specify.

A subsequent quantitative study might operationalize AI adoption as a variable and examine whether it differs by rank or teaching experience. That would be a different research question and analytical design using some of the same substantive concepts.

Common Misunderstandings About Variables in Qualitative Research

Should You Identify Variables in a Qualitative Study?

Use terminology that matches your methodology. If variables genuinely help describe the design, there is no prohibition against the word. If the study is not organized around variable relationships, however, there is little benefit in inventing them.

Methodological vocabulary should clarify the study rather than satisfy a checklist detached from the design. If removing the words “independent variable” and “dependent variable” makes your qualitative research question more accurate rather than less precise, that tells you something useful.

Before Using Variable Terminology in Qualitative Research

Questions About Variables in Qualitative Research

Do Not Force Variable Logic Onto a Study That Is Asking a Different Kind of Question

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