Written by Adriana BĂBAN on . Posted in Special issue: Mixed Methods Research, Guest Editor: Adriana BĂBAN, Volume XII, Nr. 4

As a reaction to this artificial tension induced by traditional departments, programs, journals and researchers, the applied disciplines began to work in conjunction to break down the barriers and to build a better understanding of social, psychological, and health issues. Academic research started to show an increased openness to work collaboratively, multi and interdisciplinary, with different strategies and methods for addressing different research questions. Over the last years, a growing number of researchers have been calling for studies that combine qualitative and quantitative research methods (Creswell, 2003; Brewer & Hunter, 2006; Morgan, 1998; Greene & Caracelli, 1997; Tashakkori & Teddlie, 1998, 2003; Morse, 1991; Newman & Benz, 1998). The rejection of the dichotomy between qualitative and quantitative paradigms is based on the grounds that research is complex and diversified in practice (Brannen, 2005). The qualitative or quantitative approaches are not good or bad paradigms per se, each of them posing different strengths and weaknesses.
Although the qualitative–quantitative debate in psychology is slowly moving beyond the tension between these two strategies, recently we are witnessing a growing interest in combining the two approaches and the recognition that mixed methods research becomes the third methodological movement in social and behavioral sciences (Tashakkori & Teddlie, 2008). Johnson and Onwuegbuzie (2004) refer to Mixed Methods Research as a research paradigm whose time has come, while Guba and Lincoln (1994) argue that a mixed methods paradigm can bridge epistemological, ontological and axiological differences between qualitative and quantitative methods.
The popularity of Mixed Methods Research is reflected by an increased number of papers and projects employing this design, of textbooks teaching how to use Mixed Methods Research, of conferences and workshops dealing with this topic. The founding of the Journal of Mixed Methods Research by Sage Publications in 2007 started “a new era” in the conceptualization and utilization of integrated approaches across social and behavioral sciences, as Tashakkori and Creswell (2007) called it, and created a forum for sharing ideas and discuss important issues in MMR.
Mixed method research (MMR) is defined as a combination of at least one qualitative and one quantitative component in a single research design, aiming to include the benefits of each method by combining them. This strategy is consistent with the principle of triangulation, in which the combination of two or more methods are used to gain “added-value” and to produce more valid results than would be obtained by using only one research strategy (Denzin & Lincoln, 2000). The notion of triangulation uses a metaphor borrowed from navigation science, with the idea that having two perspectives enables us to see the “reality” more accurately than a single one would (Green & Thorogood, 2005). The use of triangulation can also provide another perspective on a particular phenomenon, or bring the “object” more sharply into focus. Thus, through MMR we do not aim to produce a consistent version of the subject of study (as that object is always socially constructed) but to challenge the biases that could come from only one perspective, and to widen the framework of data analysis and interpretation (Green & Thorogood, 2005). According to Denzin (1970), qualitative and quantitative data may be treated as complementary, though not necessarily as compatible.
MMR can simultaneously address both exploratory and confirmatory research questions (Bergman, 2008). The quality of MMR is directly dependent on the purpose on which the mixed approach was chosen in that particular study.
Seven reasons for conducting a MMR have been identified by Tashakkori and Teddlie, (2008):
(1) complementarity: to address different but complementary aspects of an investigation; to get different perspectives about the same phenomenon.
(2) completeness: to be certain that a complete picture of the phenomenon is obtained.
(3) developmental: questions from one type of research emerge from the inferences of a previous one; or one strategy provides hypothesis to be tested in the second one.
(4) expansion: to expand the understanding obtained by one strategy.
(5) corroboration/confirmation: to assess the credibility of inferences obtained from one approach.
(6) compensation: to compensate the weaknesses of one approach by using the other.
(7) diversity: to obtain divergent pictures of the same phenomenon; the quantitative and qualitative findings can be compared and contrasted.
In the literature of MMR considerable attention has been directed towards what strategy constitutes the best option. According to Brannen (2008), the MMR can be categorized in three types:
(i) MMR where the quantitative component (usually, large-scale longitudinal research) is dominant; most of the time it precedes the qualitative component, which has the role of provide explanations for the statistical results;
(ii) MMR where the qualitative component has priority, and it is followed by the quantitative component (e.g., qualitative data generate themes to be incorporated in a survey);
(iii) MMR where neither approach appears to be dominant (the use of qualitative work to test quantitative evidence, that in turn may be refuted by the qualitative evidence).
Creswell (2008) named two major strategies which can be used in MMR: a parallel/ concurrent strategy, in which the purpose of design is to merge (or bring together) the qualitative and quantitative data; and a sequential strategy, meaning to have one type of data (qualitative or quantitative) built on the other type of data (quantitative or qualitative). These two major options determine whether the research takes the form of a single study, or a multi-phases project.
According to Creswell (2008) the concurrent strategy of conducting MMR can be done through:
(1) triangulation design, a one-phase study in which quantitative and qualitative data are collected and analyzed in parallel and then merged together to develop a more complete understanding or to compare the different results; and
(2) embedded design, used by researchers who want to enhance a study based on one method by including a secondary dataset from the other method.
The sequential strategy can be conducted in 3 different ways:
(1) explanatory design is selected by researchers when they start with quantitative methods and then follow up with qualitative methods, usually to help explain the initial quantitative results;
(2) exploratory design begins by exploring the topic with qualitative methods and then builds to a second quantitative phase where the initial results may be tested or generalized;
(3) sequential embedded design involves collecting qualitative data before an intervention begins (e.g., to select participations) or after it is complete (e.g., to explain why the results are different).
Yardley and Bishop (2008) consider that the ways of doing MMR are virtually limitless.
It is not entirely clear what is involved in bringing quantitative and qualitative research together. Concerns have arisen about wheather MMR has just become fashionable, or if it goes beyond what each strategy can offer independently. Combining methods in a study is not simple and does involve difficult decisions and careful planning. There are researchers who emphasis that MMR is not without costs. Epistemological differences between qualitative research approaches and other, more positivist, approaches may pose particular challenges for researchers. There are several questions about the risk of mixing research methods: is it possible to mix different theoretical approaches and epistemologies? Does MMR not push researchers to a “schizophrenic position” (Bergman, 2008, p.14) by, on the one hand, accepting the divergent qualities attributed to each paradigm, which on ontological, epistemological and axiological grounds, are incompatible, and on the other hand, by emphasizing the fruitful combination of these two positions within one single research design? Will a MMR design bring us closer to conducting better research? Should we mix different types of data or should we mix different findings? In other words, how far do mixed methods researchers analyze, interpret, and write up their research in such a way that the quantitative and qualitative components are mutually illuminating? In order to overcome these concerns, MMR needs to reconcile two sets of standards (quantitative and qualitative) for assessing the credibility of results and interpretation.
Given the increasing acceptability of MMR, there is a need for developing a set of standards for quality assessment that goes beyond the standards of quantitative and qualitative approaches. MMR is not just an exercise in testing findings against each other. Instead, it is about building an overall account of the findings that bring together both components of research. The challenge is to find ways of creating such accounts when there are no clear rules for doing so. Examples of good MMR are not yet common in the literature (Yardley & Bishop, 2008). This may be due to the fact that MMR is not easy to be done well. Nevertheless, we can find today an increased number of studies which demonstrate various possibilities to combine qualitative and quantitative aspects into articulate research designs.
When considering whether to undertake MMR it is important to take into account the research questions we seek to address. We also should keep in mind our methodological resources, expertise and experience, and how far these are likely to support the use of such a strategy. Another important factor which should influence us upon the kind of research strategy we use is the practical context in which the study is carried out. As Brennen (2008) notes, a MMR strategy offers different opportunities for science and researchers: first, it provides researchers with a good context for skill enhancement in methodology; second, it encourages researchers to think flexibly, and “outside the box”; third, it informs the public policy and practice and offers the appropriate frame and language to communicate with policy makers; forth, it allows to include in the same study, large-scale crossnational research and culturally contextualized one, as well; finally, MMR allows for the use of both languages in dissemination: the technical language of research and a language which makes research findings accessible to a wide variety of audiences.
The value of any study is not given by the methods used, but whether it has or not a few fundamental characteristics that describe good research: commitment and rigor in execution; analytic sensitivity to theory and data; transparency and coherence in findings presentation; and importance for social world and human activity (Yardley & Bishop, 2008).
In conclusion, today the problem in social sciences research is not that the distinction between qualitative and quantitative research methods does not exist. On the contrary, there are many types of differences between them. The point is that these differences have been greatly exaggerated, and that it was assumed that these dissimilarities are creating impermeable boundaries which can not be overcome. The focus on fundamental differences between qualitative and quantitative research methods has reached its zenith (Bergman, 2008, p.12). Through challenging our “classical” assumptions about the “best way” of doing research we should identify how the integration of quantitative and qualitative approaches can contribute to improving social and behavioral sciences. Fielding (2008, p.47) noted that the world of multiple method research oddly combines orthodoxies and heresies. If the combination of orthodoxies and heresies has the potential to increase the sophistication of our understanding of social and individual phenomena, and if it can strengthen the ecological dimension of our studies, we can just applaud it.
We hope the papers included in this special issue of Cognition, Brain, Behavior. An Interdisciplinary Journal will stimulate our thinking about Mixed Methods Research and promote it within the social sciences.
Bergman, M. M. (2008). Advances in Mixed Methods Research. Los Angeles: Sage.
Brannen, J. (2005). Working qualitatively and quantitatively. In C. Seale, G. Gobo, J. Gubrium, & D. Silverman (Eds.). (pp. 312-326). Qualitative Research in Practice. London: Sage. Brewer, J., & Hunter, A. (2006). Foundations of multimethod research: Synthesizing styles (2nd Ed.). Thousand Oaks, CA: Sage.
Creswell, J. W. (2003). Research design: Qualitative, quantitative, and mixed methods approaches (2nd Ed.). Thousand Oaks, CA: Sage.
Creswell, J. W. (2008). Methodological issues in conducting mixed methods research design. In M. M. Bergman (Ed.). Advances in Mixed Methods Research. (pp. 66- 86). Los Angeles: Sage.
Denzin, N. (1970). The research Act in Sociology. London: Butterworths.
Denzin, N., & Lincoln, Y. S. (2000). Handbook of Qualitative Research (2nd Ed). Thousand Oaks, CA: Sage.
Fielding, N. (2008). Analytic density, postmodernism, and applied multiple method research. In M. M. Bergman (Ed.). Advances in Mixed Methods Research. (pp. 37- 52). Los Angeles: Sage.
Green, J., & Thorogood, N. (2005). Qualitative Methods for Health Research. London: Sage.
Greene, J. C., & Caracelli, V. J. (Eds.). (1997). Advances in mixed-method evaluation: The challenges and benefits of integrating diverse paradigms. San Francisco: Jossey- Bass.
Guba, E. G., & Lincoln, Y. S. (1994). Competing paradigms in qualitative research. In N. K. Denzin, & Y. S.
Lincoln (Eds.). Handbook of Qualitative Research. (pp. 105- 117). Thousand Oaks, CA: Sage.
Johnson, B., & Onwuegbuzie, A. (2004). Mixed methods research: a research paradigm whose time has come. Educational Researcher, 7, 14-26.
Lincoln, Y. S., & Guba, E. G. (2000). Paradigmatic controversies, contradictions and emerging confluences. In N. K. Denzin, & Y. S. Lincoln (Eds.). Handbook of Qualitative Research, 2nd ed. (pp. 163-188 ). Thousand Oaks, CA: Sage.
Morgan, D. L. (1998). Practical strategies for combining qualitative and quantitative methods: Applications to health research. Qualitative Health Research, 8, 362– 376.
Morse, J. (1991). Approaches to qualitative-quantitative methodological triangulation. Nursing Research, 40, 120-123.
Newman, I., & Benz, C. R. (1998). Qualitative-quantitative research methodology: Exploring the interactive continuum. Carbondale: University of Illinois Press.
Tashakkori, A., & Teddlie, C. (1998). Mixed methodology: Combining qualitative and quantitative approaches. Thousand Oaks, CA: Sage.
Tashakkori, A., & Teddlie, C. (2003). Handbook of mixed methods in social & behavioral research. Thousand Oaks, CA: Sage.
Tashakkori, A., & Creswell, J. W. (2007). The new era of mixed methods. Journal of Mixed Methods Research, 1, 3-7.
Tashakkori, A., & Teddlie, C. (2008). Quality of inferences in mixed methods research: calling for an integrative framework. In M. M. Bergman (Ed.). Advances in Mixed Methods Research. (pp. 53-65). Los Angeles: Sage.
Yardley, L., & Bishop, F. (2008). Mixing qualitative and quantitative methods: a pragmatic approach. In C. Willig, & W. Stainton-Rogers (Eds.). Qualitative Research in Psychology. (pp.313-326). Los Angels: Sage.