Characteristics of Mixed Methods Design Process

Several primary characteristics that should be considered during a mixed methods design process include as follows: the purpose of mixing, theoretical drive, timing, point of integration, typological use, and degree of complexity (Schoonenboom & Johnson, 2017, p. 109).

Purpose: the overall goal of a mixed methods design is to expand and strengthen the conclusions of a study, thus making a contribution to the existing literature. A mixed methods research study should be of sufficient quality to answer the research questions, and achieve ‘multiple validation legitimation’ (Johnson & Christensen, 2017) by meeting the relevant combination of quantitative, qualitative and mixed methods validities in each research study. Based on an analysis of mixed methods designs, Green, Caracelli, and Graham (1989) proposed a classification of purposes, which is still popular, and includes as follows:

• triangulation – seeking convergence, corroboration, correspondence of results of different methods;
• complementarity – seeking elaboration, enhancement, illustration, clarification of the results from one method with the results from the other method;
• development – seeking to use the results of one method to help develop or inform the other method with regard to sampling, implementation, measurement decisions;
• initiation – seeking to discover the paradox and contradiction, new perspectives of frameworks, the recasting of questions and results from one method with questions or results from the other method;
• expansion – seeking to extend the breadth and range of inquiry by using different methods for different inquiry components (Schoonenboom & Johnson, 2017, p. 110).

It is important for a researcher to begin a study with at least one research question, and then carefully consider what the purposes of mixing are. One can use mixed methods to examine different aspects of a single research question, or one can use separate but related qualitative and quantitative research questions. Nevertheless, the mixing of methods, methodologies, and/or paradigms will help to answer the research questions, and make improvements over a more basic study design. Fuller and richer information will be obtained in a mixed methods study.

Theoretical drive: mixed methods research can have three different drives, as formulated by Johnson et al. (2007):

• qualitative dominant (or qualitatively driven) mixed methods research is the type of mixed research in which one relies on a qualitative view of the research process, while concurrently recognizing that the addition of quantitative data and approaches are likely to benefit the research project.
• quantitative dominant (or quantitatively driven) mixed methods research is the type of mixed research in which one relies on a quantitative view of the research process, while concurrently recognizing that the addition of qualitative data and approaches are likely to benefit the research project.
• the area around the center of the (qualitative-quantitative) continuum, i.e. equal status, is convenient for the person that self-identifies as a mixed methods researcher. This researcher takes as his or her starting point the logic and philosophy of mixed methods research. These mixed methods researchers are likely to believe that qualitative and quantitative data and approaches will add insights into most, if not all, research questions. The equal status research is most easily conducted when a research team is composed of qualitative, quantitative, and mixed methods researchers, who interact continually, and conduct a study to address one superordinate goal (Schoonenboom & Johnson, 2017, p. 113).

Timing: it has two aspects: simultaneity and dependence (Guest, 2013). Simultaneity forms the basis of the distinction between concurrent and sequential designs. In a sequential design, the quantitative component precedes the qualitative one, or vice versa. In a concurrent design, both components are executed (almost) simultaneously. In the notation of Morse (1991), concurrence is indicated by ‘+’ between components (e.g. QUAL + quan), while sequentiality is indicated with ‘→’ (QUAL → quan). It is possible to collect interview data and survey data of one inquiry simultaneously, and in that case, the research activities would be concurrent. It is also possible to conduct interviews after the survey data have been collected (or vice versa), and in that case, research activities are performed sequentially. The second aspect of timing is dependence. Two research components are dependent if the implementation of the second component depends on the results of data analysis in the first component. Two research components are independent if their implementation does not depend on the results of data analysis in the other component. A researcher can often choose whether to perform data analyses independently or not. A researcher can analyse interview data and questionnaire data of one inquiry independently, and in that case, the research activities would be independent. It is also possible to let the interview questions depend upon the outcomes of the analysis of the questionnaire data (or vice versa), and in that case, the research activities are performed dependently. It is up to the researcher to determine whether a concurrent-dependent design, a concurrent-independent design, a sequential-dependent design, or a sequential-independent design is needed to answer a particular research question or set of research questions in a given situation.

Point of integration: each true mixed methods study has at least one point of integration called the point of interface by Morse and Niehaus (2009) and Guest (2013), at which the qualitative and quantitative components are brought together. Having one or more points of integration is the distinguishing feature of a design based on multiple components. It is at this point that the components are ’mixed’, and hence the label ’mixed methods designs’. The term ’mixing’, however, is misleading as the components are not simply mixed, but have to be integrated very carefully. Determining where the point of integration will be, and how the results will be integrated, is an important, if not the most important, decision in the design of mixed methods research (Schoonenboom & Johnson, 2017, p. 115). Some primary ways of integrating the components are as follows:

• merging the two data sets,
• connecting from the analysis of one set of data to the collection of a second set of data,
• embedding one form of data within a larger design or procedure, and
• using a framework (theoretical or programme) to bind together the data sets (Creswell & Clark, 2011, p. 76).