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Mixed Methods Research

As a new approach to conducting social and health inquiry research, mixed methods research has attracted substantial interest and followers during the past 20 years. With the current acceptance and legitimacy of qualitative research and the long-term use of quantitative research, mixed methods provides a means for combining the strengths of both approaches to best understand research problems. Researchers need to be aware of the possibility of combining qualitative and quantitative methods when appropriate for addressing their research questions.

A Definition

Mixed methods is defined as research in which the inquirer or investigator collects and analyzes data, integrates the findings, and draws inferences using both qualitative and quantitative approaches or methods in a single study or a program of study. This definition is the current one being used in the call for manuscripts for the Journal of Mixed Methods Research. This definition permits viewing mixed methods as a broad umbrella term encompassing perspectives that see it as a research method of data collection and analysis, a methodology that spans the process of research from philosophical assumptions to interpretations, a philosophy of research, and a set of procedures used within existing research designs such as case studies, experiments, and narrative projects. Overall, this definition has general agreement among leading mixed methods writers today.

When researchers apply this definition, they employ an approach that has several characteristics. They are collecting and analyzing both quantitative and qualitative data. This suggests that two “strands” are implemented in a mixed methods study, and that the researchers have the skills needed in both quantitative and qualitative research to engage in these procedures. It also suggests that the collection of multiple forms of qualitative data (or multiple forms of quantitative data) would not constitute a mixed methods study. This form of research might be considered multimethod research. Also in applying the definition, researchers will mix, combine, or link the data in certain ways. Three ways are apparent in the mixed methods literature for mixing the quantitative and qualitative data: by combining or integrating them, by connecting them from the data analysis step of the first source of data to the data collection step of the second source of data so that one source builds on the other or helps to explain the other, or by embedding one secondary or supporting source of data into a larger source of data to provide additional information in a study. In the process of research, these three forms of mixing—merging, connecting, or embedding—will occur during various stages of the research, such as during data collection, data analysis, or interpretation.

Reasons for Mixing in Different Research Designs

Regardless of the form of mixing, the reasons for mixing the methods in a study need to be clearly identified by researchers. One reason for using mixed methods research is that the use of both qualitative and quantitative approaches will provide a more complete understanding of the research problem than either approach alone. In this case, the researcher might collect both quantitative and qualitative data at the same time (con-currently) and merge the data to form one interpretation of the data. This interpretation would provide both quantitative information about magnitude and frequency as well as qualitative information from individual perspectives from participants and the context in which they were commenting on the research problem. This design is called the triangulation or concurrent mixed methods design. A triangulation design in mixed methods is not the same as the use of the term triangulation in qualitative research in which inquirers draw evidence from different sources or different participants to develop a code or a theme. In mixed methods, it means that the quantitative data and the qualitative data are merged by the researcher in the analysis. Another reason for mixing is to follow up on initial exploratory findings. This reason applies when the researcher seeks to explore first qualitatively and then to test this exploration with a large quantitative sample of a population. For example, the inquirer might collect and analyze qualitative data in the first phase of the study. The results of this analysis might then be used to identify items for a questionnaire or to build a typology of categories to be further tested quantitatively in the second phase. This design is called an exploratory sequential mixed methods design. Another reason for using mixed methods is that the researcher may want to better explain initial quantitative results. This situation occurs when the researcher begins with quantitative data collection and analysis in a first phase and then follows up with a second phase of qualitative data collection and analysis to help explain in more detail the results of the first quantitative phase. This type of design is called an explanatory sequential mixed methods design. A final reason for using mixed methods research is to enhance a larger data set with a smaller, more focused data set. For example, an investigator might conduct an experiment and within that experiment collect qualitative data that provides information as to how the participants experienced the intervention. This design would be called an embedded mixed methods design.

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