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Mixed methods research

What is it?

Mixed methods research is a methodology for conducting research that involves collecting, analysing and integrating quantitative (e.g., experiments, surveys) and qualitative (e.g., focus groups, interviews) research. This approach to research is used when this integration provides a better understanding of the research problem than either of each alone.

Quantitative data includes close-ended information such as that found to measure attitudes (e.g., rating scales), behaviours (e.g., observation checklists), and performance instruments. The analysis of this type of data consists of statistically analysing scores collected on instruments (e.g., questionnaires) or checklists to answer research questions or to test hypotheses.

Qualitative data consists of open-ended information that the researcher usually gathers through interviews, focus groups and observations. The analysis of the qualitative data (words, text or behaviours) typically follows the path of aggregating it into categories of information and presenting the diversity of ideas gathered during data collection.

 

By mixing both quantitative and qualitative research and data, the researcher gains in breadth and depth of understanding and corroboration, while offsetting the weaknesses inherent to using each approach by itself. One of the most advantageous characteristics of conducting mixed methods research is the possibility of triangulation, i.e., the use of several means (methods, data sources and researchers) to examine the same phenomenon. Triangulation allows one to identify aspects of a phenomenon more accurately by approaching it from different vantage points using different methods and techniques. Successful triangulation requires careful analysis of the type of information provided by each method, including its strengths and weaknesses.

 

 

When to use it?

Mixed methods research is particularly suited:

  • When one wants to validate or corroborate the results obtained from other methods.
  • When one needs to use one method to inform another method. For instance, when little is known about a topic and it is necessary to first learn about what variables to study through qualitative research, and then study those variables with a large sample of individuals using quantitative research.
  • When one wants to continuously look at a research question from different angles, and clarify unexpected findings and/or potential contradictions.
  • When one wants to elaborate, clarify, or build on findings from other methods. For instance, if a causal relationship has being established through experimental research but one wants to understand and explain the causal processes involved through qualitative research.
  • When one wants to develop a theory about a phenomenon of interest and then test it. Usually, qualitative research is more suitable to build theory, while quantitative research provides a better way of testing theories.
  • When one wants to generalize findings from qualitative research.

 

 

Advantages

The use of mixed method research provides a number of advantages, namely:

  • Provides strengths that offset the weaknesses of both quantitative and qualitative research. For instance, quantitative research is weak in understanding the context or setting in which people behave, something that qualitative research makes up for. On the other hand, qualitative research is seen as deficient because of the potential for biased interpretations made by the researcher and the difficulty in generalizing findings to a large group. Quantitative research does not have these weaknesses. Thus, by using both types of research, the strengths of each approach can make up for the weaknesses of the other.
  • Provides a more complete and comprehensive understanding of the research problem than either quantitative or qualitative approaches alone.
  • Provides an approach for developing better, more context specific instruments. For instance, by using qualitative research it is possible to gather information about a certain topic or construct in order to develop an instrument with greater construct validity, i.e., that measures the construct that it intends to measure.
  • Helps to explain findings or how causal processes work.

 

 

Disadvantages and limitations

Mixed method research has some disadvantages and limitations, namely:

  • The research design can be very complex.
  • Takes much more time and resources to plan and implement this type of research.
  • It may be difficult to plan and implement one method by drawing on the findings of another.
  • It may be unclear how to resolve discrepancies that arise in the interpretation of the findings.

 

 

Types of mixed methods research designs

When deciding what type of mixed methods design to use, it is important to take into account the overall purpose of the research (e.g., exploration or generalization), the specific research questions, and the strengths and weaknesses of each design.

The four major mixed methods designs are identified below and compared in terms of their purposes, strengths and weaknesses. Examples of each design are also described.
 

 

Sequential explanatory design

This design involves the collection and analysis of quantitative data followed by the collection and analysis of qualitative data. The priority is given to the quantitative data, and the findings are integrated during the interpretation phase of the study.

 

When to use it?

  • To help explain, interpret or contextualize quantitative findings.
  • To examine in more detail unexpected results from a quantitative study.

 

Strengths:

  • Easy to implement because the steps fall into clear separate stages.
  • The design is easy to describe and the results easy to report.

 

Weaknesses:

  • Requires a substantial length of time to complete all data collection given the two separate phases.

 

Example:

The researcher collects data about people’s risk and benefit perceptions of red meat using a survey and follows up with interviews with a few individuals who participated in the survey to learn in more detail about their survey responses (e.g., to understand the thought process of people with low risk perceptions).

 

 

Sequential exploratory design

In this design, qualitative data collection and analysis is followed by quantitative data collection and analysis. The priority is given to the qualitative aspect of the study, and the findings are integrated during the interpretation phase of the study.

 

When to use it?

  • To explore a phenomenon and to expand on qualitative findings.
  • To test elements of an emergent theory resulting from the qualitative research.
  • To generalize qualitative findings to different samples in order to determine the distribution of a phenomenon within a chosen population.
  • To develop and test a new instrument

 

Strengths:

  • Easy to implement because the steps fall into clear, separate stages.
  • The design is easy to describe and the results easy to report.

 

Weaknesses:

  • Requires a substantial length of time to complete all data collection given the two separate phases.
  • It may be difficult to build from the qualitative analysis to the subsequent data collection.

 

Example:

The researcher explores people's beliefs and knowledge regarding nutritional information by starting with in-store interviews and then uses an analysis of the information to develop a survey instrument that is administered later to a sample from a population.

 

 

Concurrent triangulation

In this design only one data collection phase is used, during which quantitative and qualitative data collection and analysis are conducted separately yet concurrently. The findings are integrated during the interpretation phase of the study. Usually, equal priority is given to both types of research.

 

When to use it?

  • To develop a more complete understanding of a topic or phenomenon.
  • To cross-validate or corroborate findings.

 

Strengths:

  • Provides well-validated and substantiated findings.
  • Compared to sequential designs, data collection takes less time.

 

Weaknesses:

  • Requires great effort and expertise to adequately use two separate methods at the same time.
  • It can be difficult to compare the results of two analysis using data of different forms.
  • It may be unclear how to resolve discrepancies that arise while comparing the results.
  • Given that data collection is conducted concurrently, results of one method (e.g., interview) cannot be integrated in the other method (e.g., survey).

 

Example:

The researcher uses a survey to assess people’s self-reported food safety practices and also observes those practices in their natural environment. By comparing the two types of data, the researcher can see if there is a match between what people think they are doing and what they are actually doing in terms of food safety practices.

 

 

Concurrent nested

In this design only one data collection phase is used, during which a predominant method (quantitative or qualitative) nests or embeds the other less priority method (qualitative or quantitative, respectively). This nesting may mean that the embedded method addresses a different question than the dominant method or seeks information from different levels. The data collected from the two methods are mixed during the analysis phase of the project.

 

When to use it?

  • To gain broader and in-depth perspectives on a topic.
  • To offset possible weaknesses inherent to the predominant method.

 

Strengths:

  • Two types of data are collected simultaneously, reducing time and resources (e.g., number of participants).
  • Provides a study with the advantages of both quantitative and qualitative data.
     

Weaknesses:

  • The data needs to be transformed in some way so that both types of data can be integrated during the analysis, which can be difficult.
  • Inequality between different methods may result in unequal evidence within the study, which can be a disadvantage when interpreting the results.

 

Example:

The researcher collects data to assess people’s knowledge and risk perceptions about genetically modified food by using a survey instrument that mixes qualitative (open-ended) and quantitative (closed-ended) questions, and both forms of data are integrated and analysed.

 

 

Once a mixed methods research design has been selected, one has to decide which specific research methods and instruments/measures should be incorporated/mixed in the research program. This decision should be determined by the overall purpose of the research (e.g., exploration, explanation, theory-building, theory-testing, and generalization), the specific research questions, and the advantages and disadvantages of each research method.