Mixed methods in Research

 

MIXED METHOD RESEARCH DESIGN

Introduction:

Research design is the procedure of inquiry that comprises the steps from broad assumptions to in-depth data collection methods, analysis and interpretation. This article deliberates the key factors involved in mixed-method research design. The selection of a research approach is also based on the nature of the research problem or issue being addressed, the researchers’ personal experiences, and the audiences for the study. The function of a research design is to ensure that the data obtained enables us to effectively address the research problem logically and as unambiguously as possible. A mixed-methods design is characterized by the combination of at least one qualitative and one quantitative research component. Research designs are types of inquiry within qualitative, quantitative, and mixed methods approach that provide specific direction for procedures in a research design. Others have called them strategies of inquiry (Denzin & Lincoln, 2011). 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.

Mixed method research design:

Mixed methods research is an approach to an inquiry involving collecting both quantitative and qualitative data, integrating the two forms of data, and using distinct designs that may involve philosophical assumptions and theoretical frameworks. The core assumption of this form of inquiry is that the combination of qualitative and quantitative approaches provides a more complete understanding of a research problem than either approach alone. Mixed methods involve combining or integration of qualitative and quantitative research and data in a research study. Qualitative data tends to be open-ended without predetermined responses while quantitative data usually includes closed-ended responses such as found on questionnaires or psychological instruments. The field of mixed methods research is relatively new with major work in developing it stemming from the middle to late 1980s.

The core characteristics of a well-designed mixed methods study include the following:

1. Collecting and analyzing both quantitative (closed-ended) and qualitative (open-ended) data.
2. Using meticulous procedures in data collection, analyzing data using appropriate statistical methods, ensuring the appropriate sample size for quantitative and qualitative analysis.
3. Integrating the data during data collection, analysis, or discussion.
4. Using procedures that implement qualitative and quantitative components either concurrently or sequentially, with the same sample or with different samples.
5. Framing the procedures within philosophical/theoretical models of research, such as within a social constructionist model that seeks to understand multiple perspectives on a single issue.

Comparative analysis of the three research designs:

Popular classification of purposes of mixed methods research was first introduced in 1989 by Greene, Caracelli, and Graham, based on an analysis of published mixed methods studies. This classification is still in use (Greene 2007). Greene et al. (1989, p. 259) distinguished the following five purposes for mixing in mixed methods research:

1. Triangulation- seeks convergence, corroboration, correspondence of results from different methods;

2. Complementarity - seeks elaboration, enhancement, illustration, clarification of the results from one method with the results from the other method;

3. Development- seeks to use the results from one method to help develop or inform the other method, where development is broadly construed to include sampling and implementation, as well as measurement decisions;

4. Initiation - seeks the discovery of paradox and contradiction, new perspectives of frameworks, the recasting of questions or results from one method with questions or results from the other method;

5. Expansion - seeks to extend the breadth and range of inquiry by using different methods for different inquiry components.

Mixed method 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. 

·        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. 

·        When one wants to develop a theory about a phenomenon of interest and then test it. 

·        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. 

·        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. 

·        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.

1.     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).

2. 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.

3.     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.

4.   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.

 Conclusion:

 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.

 

 

 

 

 

 

 

 

References:

• Greene JC, Valerie J, Caracelli, Graham WF. Toward a conceptual framework for mixed-method evaluation designs. Educational Evaluation and Policy Analysis.  1989;11:255–274. doi: 10.3102/01623737011003255. [CrossRef] [Google Scholar]
• Greene JC. Mixed methods in social inquiry. San Francisco: Jossey-Bass; 2007. [Google Scholar]
• Plano Clark, V. & Ivankova, N. (2016). What is mixed methods research?: considering how mixed methods research is defined. In Mixed methods research: A guide to the field (pp. 55-78). SAGE Publications, Inc., https://www.doi.org/10.4135/9781483398341
• http://resourcecentre.foodrisc.org/mixed-methods-research_185.html