So far in this textbook, we have talked about quantitative and qualitative research methods as separate choices, however researchers often use both methods in their research projects. For example, I recently completed a study with people who administer state-level services to people with intellectual and developmental disabilities. I studied a program they implemented called self-direction, which allows people with disabilities to have greater self-determination over their supports. In this study, my research partners and I used a mixed methods approach to understand the implementation of the program. The goal of our project was to describe the implementation of self-direction across the United States. We distributed a short, written survey and also conducted phone interviews with program administrators. While we could have just sent out a questionnaire that asked states to provide basic information on their program (size, qualifications, services offered, etc.), that would not provide us much information about the implementation issues faced by administrators. Similarly, we could have interviewed program administrators without the questionnaire, but then we wouldn’t know enough about the programs to ask good questions. Instead, we chose to use both qualitative and quantitative methods.

Sequence and emphasis

There are many different mixed methods designs, each with their own strengths. However, a more simplified synthesis of mixed methods approaches is provided by Engel and Schutt (2016) ^[1] using two key terms. Sequence refers to the order that each method is used. Researchers can use both methods at the same time or concurrently. Or, they can use one and then the other, or sequentially. For our study of self-direction, we used a sequential design by sending out a questionnaire first, conducing some analysis, and then conducting the interview. We used the quantitative questionnaire to gather basic information about the programs before we began the interviews, so our questions were specific to the features of each program. If we wanted to use a concurrent design for some reason, we could have asked quantitative questions during the interview. However, we felt this would waste the administrators’ time and would break up the conversation and rhythm of the interviews.

The other key term in mixed methods research is emphasis. In our mixed methods study, the qualitative data was the most important data. The quantitative data was mainly used to provide background information for the qualitative interviews, and our write up of the study focused mostly on the qualitative information. Thus, qualitative methods were prioritized in our study, however quantitative methods may be emphasized in other studies. In this case, qualitative data is primarily used to provide context for the quantitative findings. For example, researchers could quantitatively demonstrate the effectiveness of a particular therapy and add a qualitative component to find out how the participants experienced the intervention, how they understood its effects, and the meaning it had on their lives. This data would add depth and context to the findings and allow researchers to improve the therapeutic technique in the future.

A similar practice is when researchers use qualitative methods to solicit feedback on a quantitative scale or measure. The experiences of individuals allow researchers to refine the measure before they do the quantitative component of their study. Finally, it is possible that researchers are equally interested in qualitative and quantitative information. In studies of equal emphasis, researchers consider both methods as the focus of the research project.

Why researchers use mixed methods

Mixed methods research is more than just sticking an open-ended question at the end of a quantitative survey. Researchers choose to utilize a mixed methods approach for both pragmatic and synergistic reasons. That is, they use both methods because it makes sense with their research questions and because they will get the answers they want by combining the two approaches.

Mixed methods also allows you to use both inductive and deductive reasoning. As we’ve discussed, qualitative research follows inductive logic, moving from data to empirical generalizations or theory. In a mixed methods study, a researcher could use the results from a qualitative component to inform a subsequent quantitative component. The quantitative component would use deductive logic, using the theory derived from qualitative data to create and test a hypothesis. In this way, mixed methods use the strengths of both research methods, using each method to understand different parts of the same phenomenon. Quantitative allows the researcher to test new ideas. Qualitative allows the researcher to create new ideas.

With these two concepts in mind, we can start to see why researchers use mixed methods in the real world. Previously, I mentioned that our research project used a sequential design because we wanted to use our quantitative data to shape what qualitative questions we asked our participants. Mixed methods are often employed to initiate ideas with one method so that they can be studied with another method. For example, researchers could begin a mixed methods project by using qualitative methods to interview or conduct a focus group with participants. Based on their responses, the researchers could then formulate a quantitative project to follow up on the results. This is the inverse of what we did in our project, which was use a quantitative survey to inform a more detailed qualitative interview.

In addition to providing information for subsequent investigation, using both quantitative and qualitative information provides additional context for the data. For example, in our questionnaire for the study on self-direction, we asked participants to list what services people could purchase. The qualitative data followed up by asking whether the administrators had added or taken away any services, how they decided that these services would be covered and not others, and problems that arose around providing these services. With that information, we could analyze what services were offered, why they were offered, and how administrators made those decisions. In this way, we learned the lived experience of program administrators, not just the basic information about their programs.

Finally, another purpose of mixed methods research is corroborating data from both quantitative and qualitative sources. Ideally, your qualitative and quantitative results should support each other. For example, if interviews with participants showed a relationship between two concepts, that relationship should also be present in the qualitative data you collected. Differences between quantitative and qualitative data require an explanation. Perhaps there are outliers or extreme cases that pushed your data in one direction or another, for example.

In summary, these are a few of the many reasons researchers use mixed methods. They are summarized below:

1. Triangulation or convergence on the same phenomenon to improve validity
2. Complementarity, which aims to get at related but different facets of a phenomenon
3. Development or the use of results from one phase or a study to develop another phase
4. Initiation or the intentional analysis of inconsistent qualitative and quantitative findings to derive new insights
5. Expansion or using multiple components to extend the scope of a study (Burnett, 2012, p. 77). ^[2]

A word of caution

The use of mixed methods has many advantages, however undergraduate researchers should approach mixed methods with caution. Conducting a mixed methods study may mean doubling or even tripling your work. You must conceptualize how to use one method, another method, and how they fit together. This may mean operationalizing and creating a questionnaire, then writing an interview guide, and thinking through how the data on each measure relate to one another. Essentially, this will amount to more work than using one quantitative or qualitative method alone. Similarly, in sequential studies, the researcher must collect and analyze data from one component and then conceptualize and conduct the second component. This may also impact how long a project may take. Before beginning a mixed methods project, you should have a clear vision for what the project will entail and how each methodology will contribute to that vision.