mixed methods research dissertation

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Ten steps to producing a successful mixed methods dissertation in Evidence-Based Health Care

9 June 2017

Tips for students

This blog is part of a series for Evidence-Based Health Care MSc students undertaking their dissertations, by Research Assistant Alice Tompson.

I thought Margaret Głogowska would be a great person to chat to about the opportunities and challenges of writing a mixed-methods thesis. Margaret has loads of research experience and co-coordinates the  Mixed Methods  Evidence-Based Health Care module.

Here are her top tips for writing a successful mixed methods dissertation:

1) Start writing as soon as you can

Beginning to write your dissertation can be daunting – a blank screen can be very intimidating! Margaret suggests the methods section can be a good place to start. Writing what you are doing, and how to you are doing it is, often more straightforward than writing why you’re doing it or describing or discussing your results. Plus it’ll help you identify any holes in your research plans.

2) Mixed methods isn’t a game of two halves

Margaret explains that a common mistake is to think of mixed methods studies as having to have two components. In fact, they have three: in addition to the quantitative and qualitative strands, successful dissertations will pull these together to provide insight greater than the sum of the parts. This doesn’t only relate to the results: be sure to include your plans for integration in your methods section too. This article by  Jenny Burt  gives some further advice on “ following the mixed methods trail ”.

3) Think about the structure

When writing up her own work, Margaret reflects on,  “What’s a good way to bring this together to answer my research question? ” You could follow a typical quantitative approach where each component is reported sequentially (i.e. quantitative, qualitative, integration). However, you could adopt a more qualitative approach organising your results by themes, each illustrated with qualitative and quantitative data. Think about which structure will enable you to present the fullest picture of the issue you are investigating.  In this article,  Alicia O’Cathain  and colleagues describe three approaches to integrating mixed methods data.

4) It’s not about the “right answer”

Don’t be disheartened if the results from the different components of your study are not in agreement. Instead of attempting to establish which is more valid, use dissonant findings as an opportunity to return to your datasets to explore the reasons for these differences. This will enrich your understanding and enable a full account to be presented.

5) Embrace the flexibility

Mixed methods studies are a relatively recent development that can take many forms. As a result, there are not currently any reporting standards that students can use to structure their work. Although this can be daunting, Margaret encourages students to use this freedom to work to their advantage. Be creative and flexible to enable you to present a rich, complete account of your work.

6) Be systematic and rigorous

Although mixed methods offer flexibility, this must not be at the expense of rigor or transparency.  When writing up provide enough detail for your examiners/ readers to be able to replicate your methods and analyses. Justify the approaches you took and the decisions you made.  Enable them to follow the story.

7) Read the literature

The field of mixed methods is advancing all the time. Refer to the literature for methodological developments, for example how to display data, and also to see how published studies reported their mixed method projects.

To get you started, here are three helpful papers Margaret uses as teaching examples:

• Van den Bruel et al  (2016) C-reactive protein point-of-care testing in acutely ill children: a mixed methods study in primary care. Archives of Disease in Childhood 10.1136/archdischild-2015-309228
• Moffat et al  (2006) Using quantitative and qualitative data in health services research – what happens when mixed method findings conflict? BMC Health Services Research, 6:28 doi:10.1186/1472-6963-6-28
• Casey et al  (2014) A mixed methods study exploring the factors and behaviours that affect glycemic control following a structured education program: the Irish DAFNE study. Journal of Mixed Methods Research 10(2):182-203

She also recommends the work of  Alan Bryman , a pioneer in combining qualitative and quantitative research.

8) Fortune favours the prepared!

Keep your research notebook with you: it will allow you to keep track of ideas, useful references, and helpful conversations. Fortune favours the prepared so always keep your notebook close to hand!

9) Be concise

Word limits are a perennial issue in mixed methods research. Two methods plus integration means there is a lot of information to convey. No word can be superfluous and it may take several drafts to cut out the clutter. Use tables and appendices to  “make the most of your precious word count”.

10) Final steps – publishing your thesis

The value of mixed methods, particularly in applied health research, is increasingly being recognised.  Based on her own experience, Margaret suggests contacting journal editors for advice on how to tailor your manuscript for their particular audience to increase your chances of it being accepted.

  If you are interested in learning more about the Evidence-Based Health Care module: “Mixed- Methods in Health Research” take a look  here .

Dissertation Research—Planning, Researching, Publishing

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Mixed methods research is an approach that combines both quantitative and qualitative forms. It involves philosophical assumptions, and the mixing of qualitative and quantitative approaches in tandem so that the overall strength of a study is greater than either qualitative or quantitative methods ( Creswell, 2007 ) .

Video: Mixed Methods Research

Below is a sampling of books on the subject of "mixed methods research" owned by GW and consortium libraries. Click the book image and it will take you to the item in the library catalog, where you can request it.

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Mixed methods research: what it is and what it could be

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• Published: 29 March 2019
• Volume 48 , pages 193–216, ( 2019 )

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Combining methods in social scientific research has recently gained momentum through a research strand called Mixed Methods Research (MMR). This approach, which explicitly aims to offer a framework for combining methods, has rapidly spread through the social and behavioural sciences, and this article offers an analysis of the approach from a field theoretical perspective. After a brief outline of the MMR program, we ask how its recent rise can be understood. We then delve deeper into some of the specific elements that constitute the MMR approach, and we engage critically with the assumptions that underlay this particular conception of using multiple methods. We conclude by offering an alternative view regarding methods and method use.

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Mixed Methods

Avoid common mistakes on your manuscript.

The interest in combining methods in social scientific research has a long history. Terms such as “triangulation,” “combining methods,” and “multiple methods” have been around for quite a while to designate using different methods of data analysis in empirical studies. However, this practice has gained new momentum through a research strand that has recently emerged and that explicitly aims to offer a framework for combining methods. This approach, which goes by the name of Mixed Methods Research (MMR), has rapidly become popular in the social and behavioural sciences. This can be seen, for instance, in Fig.  1 , where the number of publications mentioning “mixed methods” in the title or abstract in the Thomson Reuters Web of Science is depicted. The number increased rapidly over the past ten years, especially after 2006. Footnote 1

Fraction of the total of articles mentioning Mixed Method Research appearing in a given year, 1990–2017 (yearly values sum to 1). See footnote 1

The subject of mixed methods thus seems to have gained recognition among social scientists. The rapid rise of the number of articles mentioning the term raises various sociological questions. In this article, we address three of these questions. The first question concerns the degree to which the approach of MMR has become institutionalized within the field of the social sciences. Has MMR become a recognizable realm of knowledge production? Has its ascendance been accompanied by the production of textbooks, the founding of journals, and other indicators of institutionalization? The answer to this question provides an assessment of the current state of MMR. Once that is determined, the second question is how MMR’s rise can be understood. Where does the approach come from and how can its emergence and spread be understood? To answer this question, we use Pierre Bourdieu’s field analytical approach to science and academic institutions (Bourdieu 1975 , 1988 , 2004 , 2007 ; Bourdieu et al. 1991 ). We flesh out this approach in the next section. The third question concerns the substance of the MMR corpus seen in the light of the answers to the previous questions: how can we interpret the specific content of this approach in the context of its socio-historical genesis and institutionalization, and how can we understand its proposal for “mixing methods” in practice?

We proceed as follows. In the next section, we give an account of our theoretical approach. Then, in the third, we assess the degree of institutionalization of MMR, drawing on the indicators of academic institutionalization developed by Fleck et al. ( 2016 ). In the fourth section, we address the second question by examining the position of the academic entrepreneurs behind the rise of MMR. The aim is to understand these agents’ engagement in MMR, as well as its distinctive content as being informed by their position in this field. Viewing MMR as a position-taking of academic entrepreneurs, linked to their objective position in this field, allows us to reflect sociologically on the substance of the approach. We offer this reflection in the fifth section, where we indicate some problems with MMR. To get ahead of the discussion, these problems have to do with the framing of MMR as a distinct methodology and its specific conceptualization of data and methods of data analysis. We argue that these problems hinder fruitfully combining methods in a practical understanding of social scientific research. Finally, we conclude with some tentative proposals for an alternative view on combining methods.

A field approach

Our investigation of the rise and institutionalization of MMR relies on Bourdieu’s field approach. In general, field theory provides a model for the structural dimensions of practices. In fields, agents occupy a position relative to each other based on the differences in the volume and structure of their capital holdings. Capital can be seen as a resource that agents employ to exert power in the field. The distribution of the form of capital that is specific to the field serves as a principle of hierarchization in the field, differentiating those that hold more capital from those that hold less. This principle allows us to make a distinction between, respectively, the dominant and dominated factions in a field. However, in mature fields all agents—dominant and dominated—share an understanding of what is at stake in the field and tend to accept its principle of hierarchization. They are invested in the game, have an interest in it, and share the field’s illusio .

In the present case, we can interpret the various disciplines in the social sciences as more or less autonomous spaces that revolve around the shared stake in producing legitimate scientific knowledge by the standards of the field. What constitutes legitimate knowledge in these disciplinary fields, the production of which bestows scholars with prestige and an aura of competence, is in large part determined by the dominant agents in the field, who occupy positions in which most of the consecration of scientific work takes place. Scholars operating in a field are endowed with initial and accumulated field-specific capital, and are engaged in the struggle to gain additional capital (mainly scientific and intellectual prestige) in order to advance their position in the field. The main focus of these agents will generally be the disciplinary field in which they built their careers and invested their capital. These various disciplinary spaces are in turn part of a broader field of the social sciences in which the social status and prestige of the various disciplines is at stake. The ensuing disciplinary hierarchy is an important factor to take into account when analysing the circulation of new scientific products such as MMR. Furthermore, a distinction needs to be made between the academic and the scientific field. While the academic field revolves around universities and other degree-granting institutions, the stakes in the scientific field entail the production and valuation of knowledge. Of course, in modern science these fields are closely related, but they do not coincide (Gingras and Gemme 2006 ). For instance, part of the production of legitimate knowledge takes place outside of universities.

This framework makes it possible to contextualize the emergence of MMR in a socio-historical way. It also enables an assessment of some of the characteristics of MMR as a scientific product, since Bourdieu insists on the homology between the objective positions in a field and the position-takings of the agents who occupy these positions. As a new methodological approach, MMR is the result of the position-takings of its producers. The position-takings of the entrepreneurs at the core of MMR can therefore be seen as expressions in the struggles over the authority to define the proper methodology that underlies good scientific work regarding combining methods, and the potential rewards that come with being seen, by other agents, as authoritative on these matters. Possible rewards include a strengthened autonomy of the subfield of MMR and an improved position in the social-scientific field.

The role of these entrepreneurs or ‘intellectual leaders’ who can channel intellectual energy and can take the lead in institution building has been emphasised by sociologists of science as an important aspect of the production of knowledge that is visible and recognized as distinct in the larger scientific field (e.g., Mullins 1973 ; Collins 1998 ). According to Bourdieu, their position can, to a certain degree, explain the strategy they pursue and the options they perceive to be viable in the trade-off regarding the risks and potential rewards for their work.

We do not provide a full-fledged field analysis of MMR here. Rather, we use the concept as a heuristic device to account for the phenomenon of MMR in the social context in which it emerged and diffused. But first, we take stock of the current situation of MMR by focusing on the degree of institutionalization of MMR in the scientific field.

The institutionalization of mixed methods research

When discussing institutionalization, we have to be careful about what we mean by this term. More precisely, we need to be specific about the context and distinguish between institutionalization in the academic field and institutionalization within the scientific field (see Gingras and Gemme 2006 ; Sapiro et al. 2018 ). The first process refers to the establishment of degrees, curricula, faculties, etc., or to institutions tied to the academic bureaucracy and academic politics. The latter refers to the emergence of institutions that support the autonomization of scholarship such as scholarly associations and scientific journals. Since MMR is still a relatively young phenomenon and academic institutionalization tends to lag scientific institutionalization (e.g., for the case of sociology and psychology, see Sapiro et al. 2018 , p. 26), we mainly focus here on the latter dimension.

Drawing on criteria proposed by Fleck et al. ( 2016 ) for the institutionalization of academic disciplines, MMR seems to have achieved a significant degree of institutionalization within the scientific field. MMR quickly gained popularity in the first decade of the twenty-first century (e.g., Tashakkori and Teddlie 2010c , pp. 803–804). A distinct corpus of publications has been produced that aims to educate those interested in MMR and to function as a source of reference for researchers: there are a number of textbooks (e.g., Plowright 2010 ; Creswell and Plano Clark 2011 ; Teddlie and Tashakkori 2008 ); a handbook that is now in its second edition (Tashakkori and Teddlie 2003 , 2010a ); as well as a reader (Plano Clark and Creswell 2007 ). Furthermore, a journal (the Journal of Mixed Methods Research [ JMMR] ) was established in 2007. The JMMR was founded by the editors John Creswell and Abbas Tashakkori with the primary aim of “building an international and multidisciplinary community of mixed methods researchers.” Footnote 2 Contributions to the journal must “fit the definition of mixed methods research” Footnote 3 and explicitly integrate qualitative and quantitative aspects of research, either in an empirical study or in a more theoretical-methodologically oriented piece.

In addition, general textbooks on social research methods and methodology now increasingly devote sections to the issue of combining methods (e.g., Creswell 2008 ; Nagy Hesse-Biber and Leavy 2008 ; Bryman 2012 ), and MMR has been described as a “third paradigm” (Denscombe 2008 ), a “movement” (Bryman 2009 ), a “third methodology” (Tashakkori and Teddlie 2010b ), a “distinct approach” (Greene 2008 ) and an “emerging field” (Tashakkori and Teddlie 2011 ), defined by a common name (that sets it apart from other approaches to combining methods) and shared terminology (Tashakkori and Teddlie 2010b , p. 19). As a further indication of institutionalization, a research association (the Mixed Methods International Research Association—MMIRA) was founded in 2013 and its inaugural conference was held in 2014. Prior to this, there have been a number of conferences on MMR or occasions on which MMR was presented and discussed in other contexts. An example of the first is the conference on mixed method research design held in Basel in 2005. Starting also in 2005, the British Homerton School of Health Studies has organised a series of international conferences on mixed methods. Moreover, MMR was on the list of sessions in a number of conferences on qualitative research (see, e.g., Creswell 2012 ).

Another sign of institutionalization can be found in efforts to forge a common disciplinary identity by providing a narrative about its history. This involves the identification of precursors and pioneers as well as an interpretation of the process that gave rise to a distinctive set of ideas and practices. An explicit attempt to chart the early history of MMR is provided by Johnson and Gray ( 2010 ). They frame MMR as rooted in the philosophy of science, particularly as a way of thinking about science that has transcended some of the most salient historical oppositions in philosophy. Philosophers like Aristotle and Kant are portrayed as thinkers who sought to integrate opposing stances, forwarding “proto-mixed methods ideas” that exhibited the spirit of MMR (Johnson and Gray 2010 , p. 72, p. 86). In this capacity, they (as well as other philosophers like Vico and Montesquieu) are presented as part of MMR providing a philosophical validation of the project by presenting it as a continuation of ideas that have already been voiced by great thinkers in the past.

In the second edition of their textbook, Creswell and Plano Clark ( 2011 ) provide an overview of the history of MMR by identifying five historical stages: the first one being a precursor to the MMR approach, consisting of rather atomised attempts by different authors to combine methods in their research. For Creswell and Plano Clark, one of the earliest examples is Campbell and Fiske’s ( 1959 ) combination of quantitative methods to improve the validity of psychological scales that gave rise to the triangulation approach to research. However, they regard this and other studies that combined methods around that time, as “antecedents to (…) more systematic attempts to forge mixed methods into a complete research design” (Creswell and Plano Clark 2011 , p. 21), and hence label this stage as the “formative period” (ibid., p. 25). Their second stage consists of the emergence of MMR as an identifiable research strand, accompanied by a “paradigm debate” about the possibility of combining qualitative and quantitative data. They locate its beginnings in the late 1980s when researchers in various fields began to combine qualitative and quantitative methods (ibid., pp. 20–21). This provoked a discussion about the feasibility of combining data that were viewed as coming from very different philosophical points of view. The third stage, the “procedural development period,” saw an emphasis on developing more hands-on procedures for designing a mixed methods study, while stage four is identified as consisting of “advocacy and expansion” of MMR as a separate methodology, involving conferences, the establishment of a journal and the first edition of the aforementioned handbook (Tashakkori and Teddlie 2003 ). Finally, the fifth stage is seen as a “reflective period,” in which discussions about the unique philosophical underpinnings and the scientific position of MMR emerge.

Creswell and Plano Clark thus locate the emergence of “MMR proper” at the second stage, when researchers started to use both qualitative and quantitative methods within a single research effort. As reasons for the emergence of MMR at this stage they identify the growing complexity of research problems, the perception of qualitative research as a legitimate form of inquiry (also by quantitative researchers) and the increasing need qualitative researchers felt for generalising their findings. They therefore perceive the emergence of the practice of combining methods as a bottom up process that grew out of research practices, and at some point in time converged towards a more structural approach. Footnote 4 Historical accounts such as these add a cognitive dimension to the efforts to institutionalize MMR. They lay the groundwork for MMR as a separate subfield with its own identity, topics, problems and intellectual history. The use of terms such as “third paradigm” and “third methodology” also suggests that there is a tendency to perceive and promote MMR as a distinct and coherent way to do research.

In view of the brief exploration of the indicators of institutionalisation of MMR, it seems reasonable to conclude that MMR has become a recognizable and fairly institutionalized strand of research with its own identity and profile within the social scientific field. This can be seen both from the establishment of formal institutions (like associations and journals) and more informal ones that rely more on the tacit agreement between agents about “what MMR is” (an example of this, which we address later in the article, is the search for a common definition of MMR in order to fix the meaning of the term). The establishment of these institutions supports the autonomization of MMR and its emancipation from the field in which it originated, but in which it continues to be embedded. This way, it can be viewed as a semi-autonomous subfield within the larger field of the social sciences and as the result of a differentiation internal to this field (Steinmetz 2016 , p. 109). It is a space that is clearly embedded within this higher level field; for example, members of the subfield of MMR also qualify as members of the overarching field, and the allocation of the most valuable and current form of capital is determined there as well. Nevertheless, as a distinct subfield, it also has specific principles that govern the production of knowledge and the rewards of domination.

We return to the content and form of this specific knowledge later in the article. The next section addresses the question of the socio-genesis of MMR.

Where does mixed methods research come from?

The origins of the subfield of MMR lay in the broader field of social scientific disciplines. We interpret the positions of the scholars most involved in MMR (the “pioneers” or “scientific entrepreneurs”) as occupying particular positions within the larger academic and scientific field. Who, then, are the researchers at the heart of MMR? Leech ( 2010 ) interviewed 4 scholars (out of 6) that she identified as early developers of the field: Alan Bryman (UK; sociology), John Creswell (USA; educational psychology), Jennifer Greene (USA; educational psychology) and Janice Morse (USA; nursing and anthropology). Educated in the 1970s and early 1980s, all four of them indicated that they were initially trained in “quantitative methods” and later acquired skills in “qualitative methods.” For two of them (Bryman and Creswell) the impetus to learn qualitative methods was their involvement in writing on, and teaching of, research methods; for Greene and Morse the initial motivation was more instrumental and related to their concrete research activity at the time. Creswell describes himself as “a postpositivist in the 1970s, self-education as a constructivist through teaching qualitative courses in the 1980s, and advocacy for mixed methods (…) from the 1990s to the present” (Creswell 2011 , p. 269). Of this group, only Morse had the benefit of learning about qualitative methods as part of her educational training (in nursing and anthropology; Leech 2010 , p. 267). Independently, Creswell ( 2012 ) identified (in addition to Bryman, Greene and Morse) John Hunter, Allen Brewer (USA; Northwestern and Boston College) and Nigel Fielding (University of Surrey, UK) as important early movers in MMR.

The selections that Leech and Creswell make regarding the key actors are based on their close involvement with the “MMR movement.” It is corroborated by a simple analysis of the articles that appeared in the Journal of Mixed Methods Research ( JMMR ), founded in 2007 as an outlet for MMR.

Table 1 lists all the authors that have published in the issues of the journal since its first publication in 2007 and that have either received more than 14 (4%) of the citations allocated between the group of 343 authors (the TLCS score in Table 1 ), or have written more than 2 articles for the Journal (1.2% of all the articles that have appeared from 2007 until October 2013) together with their educational background (i.e., the discipline in which they completed their PhD).

All the members of Leech’s selection, except for Morse, and the members of Creswell’s selection (except Hunter, Brewer, and Fielding) are represented in the selection based on the entries in the JMMR . Footnote 5 The same holds for two of the three additional authors identified by Creswell. Hunter and Brewer have developed a somewhat different approach to combining methods that explicitly targets data gathering techniques and largely avoids epistemological discussions. In Brewer and Hunter ( 2006 ) they discuss the MMR approach very briefly and only include two references in their bibliography to the handbook of Tashakkori and Teddlie ( 2003 ), and at the end of 2013 they had not published in the JMMR . Fielding, meanwhile, has written two articles for the JMMR (Fielding and Cisneros-Puebla 2009 ; Fielding 2012 ). In general, it seems reasonable to assume that a publication in a journal that positions itself as part of a systematic attempt to build a research tradition, and can be viewed as part of a strategic effort to advance MMR as a distinct alternative to more “traditional” academic research—particularly in methods—at least signals a degree of adherence to the effort and acceptance of the rules of the game it lays out. This would locate Fielding closer to the MMR movement than the others.

The majority of the researchers listed in Table 1 have a background in psychology or social psychology (35%), and sociology (25%). Most of them work in the United States or are UK citizens, and the positions they occupied at the beginning of 2013 indicates that most of these are in applied research: educational research and educational psychology account for 50% of all the disciplinary occupations of the group that were still employed in academia. This is consistent with the view that MMR originated in applied disciplines and thematic studies like education and nursing, rather than “pure disciplines” like psychology and sociology (Tashakkori and Teddlie ( 2010b ), p. 32). Although most of the 20 individuals mentioned in Table 1 have taught methods courses in academic curricula (for 15 of them, we could determine that they were involved in the teaching of qualitative, quantitative, or mixed methods), there are few individuals with a background in statistics or a neighbouring discipline: only Amy Dellinger did her PhD in “research methodology.” In addition, as far as we could determine, only three individuals held a position in a methodological department at some time: Dellinger, Tony Onwuegbuzie, and Nancy Leech.

The pre-eminence of applied fields in MMR is supported when we turn our attention to the circulation of MMR. To assess this we proceeded as follows. We selected 10 categories in the Web of Science that form a rough representation of the space of social science disciplines, taking care to include the most important so-called “studies.” These thematically orientated, interdisciplinary research areas have progressively expanded since they emerged at the end of the 1960s as a critique of the traditional disciplines (Heilbron et al. 2017 ). For each category, we selected the 10 journals with the highest 5-year impact factor in their category in the period 2007–2015. The lists were compiled bi-annually over this period, resulting in 5 top ten lists for the following Web of Science categories: Economics, Psychology, Sociology, Anthropology, Political Science, Nursing, Education & Educational Research, Business, Cultural Studies, and Family Studies. After removing multiple occurring journals, we obtained a list of 164 journals.

We searched the titles and abstracts of the articles appearing in these journals over the period 1992–2016 for occurrences of the terms “mixed method” or “multiple methods” and variants thereof. We chose this particular period and combination of search terms to see if a shift from a more general use of the term “multiple methods” to “mixed methods” occurred following the institutionalization of MMR. In total, we found 797 articles (out of a total of 241,521 articles that appeared in these journals during that time), published in 95 different journals. Table 2 lists the 20 journals that contain at least 1% (8 articles) of the total amount of articles.

As is clear from Table 2 , the largest number of articles in the sample were published in journals in the field of nursing: 332 articles (42%) appeared in journals that can be assigned to this category. The next largest category is Education & Educational Research, to which 224 (28 percentage) of the articles can be allocated. By contrast, classical social science disciples are barely represented. In Table 2 only the journal Field Methods (Anthropology) and the Journal of Child Psychology and Psychiatry (Psychology) are related to classical disciplines. In Table 3 , the articles in the sample are categorized according to the disciplinary category of the journal in which they appeared. Overall, the traditional disciplines are clearly underrepresented: for the Economics category, for example, only the Journal of Economic Geography contains three articles that make a reference to mixed methods.

Focusing on the core MMR group, the top ten authors of the group together collect 458 citations from the 797 articles in the sample, locating them at the center of the citation network. Creswell is the most cited author (210 citations) and his work too receives most citations from journals in nursing and education studies.

The question whether a terminological shift has occurred from “multiple methods” to “mixed methods” must be answered affirmative for this sample. Prior to 2001 most articles (23 out of 31) refer to “multiple methods” or “multi-method” in their title or abstract, while the term “mixed methods” gains traction after 2001. This shift occurs first in journals in nursing studies, with journals in education studies following somewhat later. The same fields are also the first to cite the first textbooks and handbooks of MMR.

Taken together, these results corroborate the notion that MMR circulates mainly in nursing and education studies. How can this be understood from a field theoretical perspective? MMR can be seen as an innovation in the social scientific field, introducing a new methodology for combining existing methods in research. In general, innovation is a relatively risky strategy. Coming up with a truly rule-breaking innovation often involves a small probability of great success and a large probability of failure. However, it is important to add some nuance to this general observation. First, the risk an innovator faces depends on her position in the field. Agents occupying positions at the top of their field’s hierarchy are rich in specific capital and can more easily afford to undertake risky projects. In the scientific field, these are the agents richest in scientific capital. They have the knowledge, authority, and reputation (derived from recognition by their peers; Bourdieu 2004 , p. 34) that tends to decrease the risk they face and increase the chances of success. Moreover, the positions richest in scientific capital will, by definition, be the most consecrated ones. This consecration involves scientific rather than academic capital (cf. Wacquant 2013 , p. 20) and within disciplines these consecrated positions often are related to orthodox position-takings. This presents a paradox: although they have the capital to take more risks, they have also invested heavily in the orthodoxy of the field and will thus be reluctant to upset the status quo and risk destroying the value of their investment. This results in a tendency to take a more conservative stance, aimed at preserving the status quo in the field and defending their position. Footnote 6

For agents in dominated positions this logic is reversed. Possessing less scientific capital, they hold less consecrated positions and their chances of introducing successful innovations are much lower. This leaves them too with two possible strategies. One is to revert to a strategy of adaptation, accepting the established hierarchy in the field and embarking on a slow advancement to gain the necessary capital to make their mark from within the established order. However, Bourdieu notes that sometimes agents with a relatively marginal position in the field will engage in a “flight forward” and pursue higher risk strategies. Strategies promoting a heterodox approach challenge the orthodoxy and the principles of hierarchization of the field, and, if successful (which will be the case only with a small probability), can rake in significant profits by laying claim to a new orthodoxy (Bourdieu 1975 , p. 104; Bourdieu 1993 , pp. 116–117).

Thus, the coupling of innovative strategies to specific field positions based on the amount of scientific capital alone is not straightforward. It is therefore helpful to introduce a second differentiation in the field that, following Bourdieu ( 1975 , p. 103), is based on the differences between the expected profits from these strategies. Here a distinction can be made between an autonomous and a heteronomous pole of the field, i.e., between the purest, most “disinterested” positions and the most “temporal” positions that are more pervious to the heteronomous logic of social hierarchies outside the scientific field. Of course, this difference is a matter of degree, as even the works produced at the most heteronomous positions still have to adhere to the standards of the scientific field to be seen as legitimate. But within each discipline this dimension captures the difference between agents predominantly engaged in fundamental, scholarly work—“production solely for the producers”—and agents more involved in applied lines of research. The main component of the expected profit from innovation in the first case is scientific, whereas in the second case the balance tends to shift towards more temporal profits. This two-fold structuring of the field allows for a more nuanced conception of innovation than the dichotomy “conservative” versus “radical.” Holders of large amounts of scientific capital at the autonomous pole of the field are the producers and conservators of orthodoxy, producing and diffusing what can be called “orthodox innovations” through their control of relatively powerful networks of consecration and circulation. Innovations can be radical or revolutionary in a rational sense, but they tend to originate from questions raised by the orthodoxy of the field. Likewise, the strategy to innovate in this sense can be very risky in that success is in no way guaranteed, but the risk is mitigated by the assurance of peers that these are legitimate questions, tackled in a way that is consistent with orthodoxy and that does not threaten control of the consecration and circulation networks.

These producers are seen as intellectual leaders by most agents in the field, especially by those aspiring to become part of the specific networks of production and circulation they maintain. The exception are the agents located at the autonomous end of the field who possess less scientific capital and outright reject this orthodoxy produced by the field’s elite. Being strictly focused on the most autonomous principles of legitimacy, they are unable to accommodate and have no choice but to reject the orthodoxy. Their only hope is to engage in heterodox innovations that may one day become the new orthodoxy.

The issue is less antagonistic at the heteronomous side of the field, at least as far as the irreconcilable position-takings at the autonomous pole are concerned. The main battle here is also for scientific capital, but is complemented by the legitimacy it brings to gain access to those who are in power outside of the scientific field. At the dominant side, those with more scientific capital tend to have access to the field of power, agents who hold the most economic and cultural capital, for example by holding positions in policy advisory committees or company boards. The dominated groups at this side of the field will cater more to practitioners or professionals outside of the field of science.

Overall, there will be fewer innovations on this side. Moreover, innovative strategies will be less concerned with the intricacies of the pure discussions that prevail at the autonomous pole and be of a more practical nature, but pursued from different degrees of legitimacy according to the differences in scientific capital. This affects the form these more practical, process-orientated innovations take. At the dominant side of this pole, agents tend to accept the outcome of the struggles at the autonomous pole: they will accept the orthodoxy because mastery of this provides them with scientific capital and the legitimacy they need to gain access to those in power. In contrast, agents at the dominated side will be more interested in doing “what works,” neutralizing the points of conflict at the autonomous pole and deriving less value from strictly following the orthodoxy. This way, a four-fold classification of innovative strategies in the scientific field emerges (see Fig.  2 ) that helps to understand the context in which MMR was developed.

Scientific field and scientific innovation

In summary, the small group of researchers who have been identified as the core of MMR consist predominantly of users of methods, who were educated and have worked exclusively at US and British universities. The specific approach to combining methods that is proposed by MMR has been successful from an institutional point of view, achieving visibility through the foundation of a journal and association and a considerable output of core MMR scholars in terms of books, conference proceedings, and journal articles. Its origins and circulation in vocational studies rather than classical academic disciplines can be understood from the position these studies occupy in the scientific field and the kinds of position-taking and innovations these positions give rise to. This context allows a reflexive understanding of the content of MMR and the issues that are dominant in the approach. We turn to this in the next section.

Mixed methods research: Position-taking

The position of the subfield of MMR in the scientific field is related to the position-takings of agents that form the core of this subfield (Bourdieu 1993 , p. 35). The space of position takings, in turn, provides the framework to study the most salient issues that are debated within the subfield. Since we can consider MMR to be an emerging subfield, where positions and position takings are not as clearly defined as in more mature and settled fields, it comes as no surprise that there is a lively discussion of fundamental matters. Out of the various topics that are actively discussed, we have distilled three themes that are important for the way the subfield of MMR conveys its autonomy as a field and as a distinct approach to research. Footnote 7 In our view, these also represent the main problems with the way MMR approaches the issue of combining methods.

Methodology making and standardization

The first topic is that the approach is moving towards defining a unified MMR methodology. There are differences in opinion as to how this is best achieved, but there is widespread agreement that some kind of common methodological and conceptual foundation of MMR is needed. To this end, some propose a broad methodology that can serve as distinct marker of MMR research. For instance, in their introduction to the handbook, Tashakkori and Teddlie ( 2010b ) propose a definition of the methodology of mixed methods research as “the broad inquiry logic that guides the selection of specific methods and that is informed by conceptual positions common to mixed methods practitioners” (Tashakkori and Teddlie 2010b , p. 5). When they (later on in the text) provide two methodological principles that differentiate MMR from other communities of scholars, they state that they regard it as a “crucial mission” for the MMR community to generate distinct methodological principles (Tashakkori and Teddlie 2010b , pp. 16–17). They envision an MMR methodology that can function as a “guide” for selecting specific methods. Others are more in favour of finding a philosophical foundation that underlies MMR. For instance, Morgan ( 2007 ) and Hesse-Biber ( 2010 ) consider pragmatism as a philosophy that distinguishes MMR from qualitative (constructivism) and quantitative (positivist) research and that can provide a rationale for the paradigmatic pluralism typical of MMR.

Furthermore, there is wide agreement that some unified definition of MMR would be beneficial, but it is precisely here that there is a large variation in interpretations regarding the essentials of MMR. This can be seen in the plethora of definitions that have been proposed. Johnson et al. ( 2007 ) identified 19 alternative definitions of MMR at the time, out of which they condensed their own:

[MMR] is the type of research in which a researcher or team of researchers combines elements of qualitative and quantitative research approaches (e.g., use of qualitative and quantitative viewpoints, data collection, analysis, inference techniques) for the broad purpose of breath and depth of understanding and corroboration. Footnote 8

Four years later, the issue is not settled yet. Creswell and Plano Clark ( 2011 ) list a number of authors who have proposed a different definition of MMR, and conclude that there is a common trend in the content of these definitions over time. They take the view that earlier texts on mixing methods stressed a “disentanglement of methods and philosophy,” while later texts locate the practice of mixing methods in “all phases of the research process” (Creswell and Plano Clark 2011 , p. 2). It would seem, then, that according to these authors the definitions of MMR have become more abstract, further away from the practicality of “merely” combining methods. Specifically, researchers now seem to speak of mixing higher order concepts: some speak of mixing methodologies, others refer to mixing “research approaches,” or combining “types of research,” or engage in “multiple ways of seeing the social world” (Creswell and Plano Clark 2011 ).

This shift is in line with the direction in which MMR has developed and that emphasises practical ‘manuals’ and schemas for conducting research. A relatively large portion of the MMR literature is devoted to classifications of mixed methods designs. These classifications provide the basis for typologies that, in turn, provide guidelines to conduct MMR in a concrete research project. Tashakkori and Teddlie ( 2003 ) view these typologies as important elements of the organizational structure and legitimacy of the field. In addition, Leech and Onwuegbuzie ( 2009 ) see typologies as helpful guides for researchers and of pedagogical value (Leech and Onwuegbuzie 2009 , p. 272). Proposals for typologies can be found in textbooks, articles, and contributions to the handbook(s). For example, Creswell et al. ( 2003 , pp. 169-170) reviewed a number of studies and identified 8 different ways to classify MMR studies. This list was updated and extended by Creswell and Plano Clark ( 2011 , pp. 56-59) to 15 typologies. Leech and Onwuegbuzie ( 2009 ) identified 35 different research designs in the contributions to Teddlie and Tashakkori (2003) alone, and proposed their own three-dimensional typology that resulted in 8 different types of mixed methods studies. As another example of the ubiquity of these typologies, Nastasi et al. ( 2010 ) classified a large number of existing typologies in MMR into 7”meta-typologies” that each emphasize different aspects of the research process as important markers for MMR. According to the authors, these typologies have the same function in MMR as the more familiar names of “qualitative” or “quantitative” methods (e.g., “content analysis” or “structural equation modelling”) have: to signal readers of research what is going on, what procedures have been followed, how to interpret results, etc. (see also Creswell et al. 2003 , pp. 162–163). The criteria underlying these typologies mainly have to do with the degree of mixing (e.g., are methods mixed throughout the research project or not?), the timing (e.g., sequential or concurrent mixing of methods) and the emphasis (e.g., is one approach dominant, or do they have equal status?).

We find this strong drive to develop methodologies, definitions, and typologies of MMR as guides to valid mixed methods research problematic. What it amounts to in practice is a methodology that lays out the basic guidelines for doing MMR in a “proper way.” This entails the danger of straight-jacketing reflection about the use of methods, decoupling it from theoretical and empirical considerations, thus favouring the unreflexive use of a standard methodology. Researchers are asked to make a choice for a particular MMR design and adhere to the guidelines for a “proper” MMR study. Such methodological prescription diametrically opposes the initial critique of the mechanical and unreflexive use of methods. The insight offered by Bourdieu’s notion of reflexivity is, on the contrary, that the actual research practice is fundamentally open in terms of being guided by a logic of practice that cannot be captured by a preconceived and all-encompassing logic independent of that practice. Reflexivity in this view cannot be achieved by hiding behind the construct of a standardized methodology—of whatever signature—it can only be achieved by objectifying the process of objectification that goes on within the context of the field in which the researcher is embedded. This reflexivity, then, requires an analysis of the position of the researcher as a critical component of the research process, both as the embodiment of past choices that have consequences for the strategic position in the scientific field, and as predispositions regarding the choice for the subject and content of a research project. By adding the insight of STS researchers that the point of deconstructing science and technology is not so much to offer a new best way of doing science or technology, but to provide insights into the critical moments in research (for a take on such a debate, see, for example, Edge 1995 , pp. 16–20), this calls for a sociology of science that takes methods much more seriously as objects of study. Such a programme should be based on studying the process of codification and standardization of methods in their historical context of production, circulation, and use. It would provide a basis for a sociological understanding of methods that can illuminate the critical moments in research alluded to above, enabling a systematic reflection on the process of objectification. This, in turn, allows a more sophisticated validation of using—and combining—methods than relying on prescribed methodologies.

The role of epistemology

The second theme discussed in a large number of contributions is the role epistemology plays in MMR. In a sense, epistemology provides the lifeblood for MMR in that methods in MMR are mainly seen in epistemological terms. This interpretation of methods is at the core of the knowledge claim of MMR practitioners, i.e., that the mixing of methods means mixing broad, different ways of knowing, which leads to better knowledge of the research object. It is also part of the identity that MMR consciously assumes, and that serves to set it apart from previous, more practical attempts to combine methods. This can be seen in the historical overview that Creswell and Plano Clark ( 2011 ) presented and that was discussed above. This reading, in which combining methods has evolved from the rather unproblematic level (one could alternatively say “naïve” or “unaware”) of instrumental use of various tools and techniques into an act that requires deeper thinking on a methodological and epistemological level, provides the legitimacy of MMR.

At the core of the MMR approach we thus find that methods are seen as unproblematic representations of different epistemologies. But this leads to a paradox, since the epistemological frameworks need to be held flexible enough to allow researchers to integrate elements of each of them (in the shape of methods) into one MMR design. As a consequence, the issue becomes the following: methods need to be disengaged from too strict an interpretation of the epistemological context in which they were developed in order for them to be “mixable,”’, but, at the same time, they must keep the epistemology attributed to them firmly intact.

In the MMR discourse two epistemological positions are identified that matter most: a positivist approach that gives rise to quantitative methods and a constructivist approach that is home to qualitative methods. For MMR to be a feasible endeavour, the differences between both forms of research must be defined as reconcilable. This position necessitates an engagement with those who hold that the quantitative/qualitative dichotomy is unbridgeable. Within MMR an interesting way of doing so has emerged. In the first issue of the Journal of Mixed Methods Research, Morgan ( 2007 ) frames the debate about research methodology in the social sciences in terms of Kuhnian paradigms, and he argues that the pioneers of the emancipation of qualitative research methods used a particular interpretation of the paradigm-concept to state their case against the then dominant paradigm in the social sciences. According to Morgan, they interpreted a paradigm mainly in metaphysical terms, stressing the connections among the trinity of ontology, epistemology, and methodology as used in the philosophy of knowledge (Morgan 2007 , p. 57). This allowed these scholars to depict the line between research traditions in stark, contrasting terms, using Kuhn’s idea of “incommensurability” in the sense of its “early Kuhn” interpretation. This strategy fixed the contrast between the proposed alternative approach (a “constructivist paradigm”), and the traditional approach (constructed as “the positivist paradigm”) to research as a whole, and offered the alternative approach as a valid option rooted in the philosophy of knowledge. Morgan focuses especially on the work of Egon Guba and Yvonne Lincoln who developed what they initially termed a “naturalistic paradigm” as an alternative to their perception of positivism in the social sciences (e.g., Guba and Lincoln 1985 ). Footnote 9 MMR requires a more flexible or “a-paradigmatic stance” towards research, which would entail that “in real-world practice, methods can be separated from the epistemology out of which they emerged” (Patton 2002 , quoted in Tashakkori and Teddlie 2010b , p. 14).

This proposal of an ‘interpretative flexibility’ (Bijker 1987 , 1997 ) regarding paradigms is an interesting proposition. But it immediately raises the question: why stop there? Why not take a deeper look into the epistemological technology of methods themselves, to let the muted components speak up in order to look for alternative “mixing interfaces” that could potentially provide equally valid benefits in terms of the understanding of a research object? The answer, of course, was already seen above. It is that the MMR approach requires situating methods epistemologically in order to keep them intact as unproblematic mediators of specific epistemologies and, thus, make the methodological prescriptions work. There are several problems with this. First, seeing methods solely through an epistemological lens is problematic, but it would be less consequential if it were applied to multiple elements of methods separately. This would at least allow a look under the hood of a method, and new ways of mixing methods could be opened up that go beyond the crude “qualitative” versus “quantitative” dichotomy. Second, there is also the issue of the ontological dimension of methods that is disregarded in an exclusively epistemological framing of methods (e.g., Law 2004 ). Taking this ontological dimension seriously has at least two important facets. First, it draws attention to the ontological assumptions that are woven into methods in their respective fields of production and that are imported into fields of users. Second, it entails the ontological consequences of practising methods: using, applying, and referring to methods and the realities this produces. This latter facet brings the world-making and boundary-drawing capacities of methods to the fore. Both facets are ignored in MMR. We say more about the first facet in the next section. With regard to the second facet, a crucial element concerns the data that are generated, collected, and analysed in a research project. But rather than problematizing the link between the performativity of methods and the data that are enacted within the frame of a method, here too MMR relies on a dichotomy: that between quantitative and qualitative data. Methods are primarily viewed as ways of gathering data or as analytic techniques dealing with a specific kind of data. Methods and data are conceptualised intertwiningly: methods too are seen as either quantitative or qualitative (often written as QUANT and QUAL in the literature), and perform the role of linking epistemology and data. In the final analysis, the MMR approach is based on the epistemological legitimization of the dichotomy between qualitative and quantitative data in order to define and combine methods: data obtain epistemological currency through the supposed in-severable link to certain methods, and methods are reduced to the role of acting as neutral mediators between them.

In this way, methods are effectively reduced to, on the one hand, placeholders for epistemological paradigms and, on the other hand, mediators between one kind of data and the appropriate epistemology. To put it bluntly, the name “mixed methods research” is actually a misnomer, because what is mixed are paradigms or “approaches,” not methods. Thus, the act of mixing methods à la MMR has the paradoxical effect of encouraging a crude black box approach to methods. This is a third problematic characteristic of MMR, because it hinders a detailed study of methods that can lead to a much richer perspective on mixing methods.

Black boxed methods and how to open them

The third problem that we identified with the MMR approach, then, is that with the impetus to standardize the MMR methodology by fixing methods epistemologically, complemented by a dichotomous view of data, they are, in the words of philosopher Bruno Latour, “blackboxed.” This is a peculiar result of the prescription for mixing methods as proposed by MMR that thus not only denies practice and the ontological dimensions of methods and data, but also casts methods in the role of unyielding black boxes. Footnote 10 With this in mind, it will come as no surprise that most foundational contributions to the MMR literature do not explicitly define what a method is, nor that they do not provide an elaborative historical account of individual methods. The particular framing of methods in MMR results in a blind spot for the historical and social context of the production and circulation of methods as intellectual products. Instead it chooses to reify the boundaries that are drawn between “qualitative” and “quantitative” methods and reproduce them in the methodology it proposes. Footnote 11 This is an example of “circulation without context” (Bourdieu 2002 , p. 4): classifications that are constructed in the field of use or reception without taking the constellation within the field of production seriously.

Of course, this does not mean that the reality of the differences between quantitative and qualitative research must be denied. These labels are sticky and symbolically laden. They have come, in many ways, to represent “two cultures” (Goertz and Mahony 2012 ) of research, institutionalised in academia, and the effects of nominally “belonging” to (or being assigned to) one particular category have very real consequences in terms of, for instance, access to research grants and specific journals. However, if the goal of an approach such as MMR is to open up new pathways in social science research, (and why should that not be the case?) it is hard to see how that is accomplished by defining the act of combining methods solely in terms of reified differences between research using qualitative and quantitative data. In our view, methods are far richer and more interesting constructs than that, and a practice of combining methods in research should reflect that. Footnote 12

Addressing these problems entices a reflection on methods and using (multiple) methods that is missing in the MMR perspective. A fruitful way to open up the black boxes and take into account the epistemological and ontological facets of methods is to make them, and their use, the object of sociological-historical investigation. Methods are constituted through particular practices. In Bourdieusian terms, they are objectifications of the subjectively understood practices of scientists “in other fields.” Rather than basing a practice of combining methods on an uncritical acceptance of the historically grown classification of types of social research (and using these as the building stones of a methodology of mixing methods), we propose the development of a multifaceted approach that is based on a study of the different socio-historical contexts and practices in which methods developed and circulated.

A sociological understanding of methods based on these premises provides the tools to break with the dichotomously designed interface for combining methods in MMR. Instead, focusing on the historical and social contexts of production and use can reveal the traces that these contexts leave, both in the internal structure of methods, how they are perceived, how they are put into practice, and how this practice informs the ontological effects of methods. Seeing methods as complex technologies, with a history that entails the struggles among the different agents involved in their production, and use opens the way to identify multiple interfaces for combining them: the one-sided boxes become polyhedra. The critical study of methods as “objects of objectification” also entices analyses of the way in which methods intervene between subject (researcher) and object and the way in which different methods are employed in practice to draw this boundary differently. The reflexive position generated by such a systematic juxtaposition of methods is a fruitful basis to come to a richer perspective on combining methods.

We critically reviewed the emerging practice of combining methods under the label of MMR. MMR challenges the mono-method approaches that are still dominant in the social sciences, and this is both refreshing and important. Combining methods should indeed be taken much more seriously in the social sciences.

However, the direction that the practice of combining methods is taking under the MMR approach seems problematic to us. We identified three main concerns. First, MMR scholars seem to be committed to designing a standardized methodological framework for combining methods. This is unfortunate, since it amounts to enforcing an unnecessary codification of aspects of research practices that should not be formally standardized. Second, MMR constructs methods as unproblematic representations of an epistemology. Although methods must be separable from their native epistemology for MMR to work, at the same time they have to be nested within a qualitative or a quantitative research approach, which are characterized by the data they use. By this logic, combining quantitative methods with other quantitative methods, or qualitative methods with other qualitative methods, cannot offer the same benefits: they originate from the same way of viewing and knowing the world, so it would have the same effect as blending two gradations of the same colour paint. The importance attached to the epistemological grounding of methods and data in MMR also disregards the ontological aspects of methods. In this article, we are arguing that this one-sided perspective is problematic. Seeing combining methods as equivalent to combining epistemologies that are somehow pure and internally homogeneous because they can be placed in a qualitative or quantitative framework essentially amounts to reifying these categories.

It also leads to the third problem: the black boxing of methods as neutral mediators between these epistemologies and data. This not only constitutes a problem for trying to understand methods as intellectual products, but also for regarding the practice of combining methods, because it ignores the social-historical context of the development of individual methods and hinders a sociologically grounded notion of combining methods.

We proceed from a different perspective on methods. In our view, methods are complex constructions. They are world-making technologies that encapsulate different assumptions on causality, rely on different conceptual relations and categorizations, allow for different degrees of emergence, and employ different theories of the data that they internalise as objects of analysis. Even more importantly, their current form as intellectual products cannot be separated from the historical context of their production, circulation, and use.

A fully developed exposition of such an approach will have to await further work. Footnote 13 So far, the sociological study of methods has not (yet) developed into a consistent research programme, but important elements can be derived from existing contributions such as MacKenzie ( 1981 ), Chapoulie ( 1984 ), Platt ( 1996 ), Freeman ( 2004 ), and Desrosières ( 2008a , b ). The work on the “social life of methods” (e.g., Savage 2013 ) also contains important leads for the development of a systematic sociological approach to method production and circulation. Based on the discussion in this article and the contributions listed above, some tantalizing questions can be formulated. How are methods and their elements objectified? How are epistemology and ontology defined in different fields and how do those definitions feed into methods? How do they circulate and how are they translated and used in different contexts? What are the main controversies in fields of users and how are these related to the field of production? What are the homologies between these fields?

Setting out to answer these questions opens up the possibility of exploring other interesting combinations of methods that emerge from the combination of different practices, situated in different historical and epistemological contexts, and with their unique set of interpretations regarding their constituent elements. One of these must surely be the data-theoretical elements that different methods incorporate. The problematization of data has become all the more pressing now that the debate about the consequences of “big data” for social scientific practices has become prominent (Savage and Burrows 2007 ; Levallois et al. 2013 ; Burrows and Savage 2014 ). Whereas MMR emphasizes the dichotomy between qualitative and quantitative data, a historical analysis of the production and use of methods can explore the more subtle, different interpretations and enactments of the “same” data. These differences inform method construction, controversies surrounding methods and, hence, opportunities for combining methods. These could then be constructed based on alternative conceptualisations of data. Again, while in some contexts it might be enlightening to rely on the distinction between data as qualitative or quantitative, and to combine methods based on this categorization, it is an exciting possibility that in other research contexts other conceptualisations of data might be of more value to enhance a specific (contextual) form of knowledge.

Change history

06 may 2019.

Unfortunately, figure 2 was incorrectly published.

The search term used was “mixed method*” in the “topic” search field of SSCI, A&HCI, and CPCI-SSH as contained in the Web of Science. A Google NGram search (not shown) confirmed this pattern. The results of a search for “mixed methods” and “mixed methods research” showed a very steep increase after 1994: in the first case, the normalized share in the total corpus increased by 855% from 1994 till 2008. Also, Creswell ( 2012 ) reports an almost hundred-fold increase in the number of theses and dissertations with mixed methods’ in the citation and abstract (from 26 in 1990–1994 to 2524 in 2005–2009).

Retrieved from https://uk.sagepub.com/en-gb/eur/journal-of-mixed-methods-research/journal201775#aims-and-scope on 1/17/2019.

In terms of antecedents of mixed methods research, it is interesting to note that Bourdieu, whose sociology of science we draw on, was, from his earliest studies in Algeria onwards, a strong advocate of combining research methods. He made it into a central characteristic of his approach to social science in Bourdieu et al. ( 1991 [1968]). His approach, as we see below, was very different from the one now proposed under the banner of MMR. Significantly, there is no mention of Bourdieu’s take on combining methods in any of the sources we studied.

Morse’s example in particular warns us that restricting the analysis to the authors that have published in the JMMR runs the risk of missing some important contributors to the spread of MMR through the social sciences. On her website, Morse lists 11 publications (journal articles, book chapters, and books) that explicitly make reference to mixed methods (and a substantial number of other publications are about methodological aspects of research), so the fact that she has not (yet) published in the JMMR cannot, by itself, be taken as an indication of a lesser involvement with the practice of combining methods. See the website of Janice Morse at https://faculty.utah.edu/u0556920-Janice_Morse_RN,_PhD,_FAAN/hm/index.hml accessed 1/17/2019.

Bourdieu ( 1999 , p. 26) mentions that one has to be a scientific capitalist to be able to start a scientific revolution. But here he refers explicitly to the autonomy of the scientific field, making it virtually impossible for amateurs to stand up against the historically accumulated capital in the field and incite a revolution.

The themes summarize the key issues through which MMR as a group comes “into difference” (Bourdieu 1993 , p. 32). Of course, as in any (sub)field, the agents identified above often differ in their opinions on some of these key issues or disagree on the answer to the question if there should be a high degree of convergence of opinions at all. For instance, Bryman ( 2009 ) worried that MMR could become “a ghetto.” For him, the institutional landmarks of having a journal, conferences, and a handbook increase the risk of “not considering the whole range of possibilities.” He added: “I don’t regard it as a field, I kind of think of it as a way of thinking about how you go about research.” (Bryman, cited in Leech 2010 , p. 261). It is interesting to note that Bryman, like fellow sociologists Morgan and Denscombe, had published only one paper in the JMMR by the end of 2016 (Bryman passed away in June of 2017). Although these papers are among the most cited papers in the journal (see Table 1 ), this low number is consistent with the more eclectic approach that Bryman proposed.

Johnson, Onwuegbuzie, and Turner ( 2007 , p. 123).

Guba and Lincoln ( 1985 ) discuss the features of their version of a positivistic approach mainly in ontological and epistemological terms, but they are also careful to distinguish the opposition between naturalistic and positivist approaches from the difference between what they call the quantitative and the qualitative paradigms. Since they go on to state that, in principle, quantitative methods can be used within a naturalistic approach (although in practice, qualitative methods would be preferred by researchers embracing this paradigm), they seem to locate methods on a somewhat “lower,” i.e., less incommensurable level. However, in their later work (both together as well as with others or individually) and that of others in their wake, there seems to have been a shift towards a stricter interpretation of the qualitative/quantitative divide in metaphysical terms, enabling Teddlie and Tashakkori (2010b) to label this group “purists” (Tashakkori and Teddlie 2010b , p. 13).

See, for instance, Onwuegbuzie et al.’s ( 2011 ) classification of 58 qualitative data analysis techniques and 18 quantitative data analysis techniques.

This can also be seen in Morgan’s ( 2018 ) response to Sandelowski’s ( 2014 ) critique of the binary distinctions in MMR between qualitative and quantitative research approaches and methods. Morgan denounces the essentialist approach to categorizing qualitative and quantitative research in favor of a categorization based on “family resemblances,” in which he draws on Wittgenstein. However, this denies the fact that the essentialist way of categorizing is very common in the MMR corpus, particularly in textbooks and manuals (e.g., Plano Clark and Ivankova 2016 ). Moreover, and more importantly, he still does not extend this non-essentialist model of categorization to the level of methods, referring, for instance, to the different strengths of qualitative and quantitative methods in mixed methods studies (Morgan 2018 , p. 276).

While it goes beyond the scope of this article to delve into the history of the qualitative-quantitative divide in the social sciences, some broad observations can be made here. The history of method use in the social sciences can briefly be summarized as first, a rather fluid use of what can retrospectively be called different methods in large scale research projects—such as the Yankee City study of Lloyd Warner and his associates (see Platt 1996 , p. 102), the study on union democracy of Lipset et al. ( 1956 ), and the Marienthal study by Lazarsfeld and his associates (Jahoda et al. 1933 ); see Brewer and Hunter ( 2006 , p. xvi)—followed by an increasing emphasis on quantitative data and the objectification and standardization of methods. The rise of research using qualitative data can be understood as a reaction against this use and interpretation of method in the social sciences. However, out of the ensuing clash a new, still dominant classification of methods emerged, one that relies on the framing of methods as either “qualitative” or “quantitative.” Moreover, these labels have become synonymous with epistemological positions that are reproduced in MMR.

A proposal to come to such an approach can be found in Timans ( 2015 ).

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Acknowledgments

This research is part of the Interco-SSH project, funded by the European Union under the 7th Research Framework Programme (grant agreement no. 319974). Johan Heilbron would like to thank Louise and John Steffens, members of the Friends Founders’ Circle, who assisted his stay at the Princeton Institute for Advanced Study in 2017-18 during which he completed his part of the present article.

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Timans, R., Wouters, P. & Heilbron, J. Mixed methods research: what it is and what it could be. Theor Soc 48 , 193–216 (2019). https://doi.org/10.1007/s11186-019-09345-5

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The Growing Importance of Mixed-Methods Research in Health

Sharada prasad wasti.

1,2 School of Human and Health Sciences, University of Huddersfield, United Kingdom

Padam Simkhada

3 Centre for Midwifery, Maternal and Perinatal Health, Bournemouth University, Bournemouth, United Kingdom

Edwin R. van Teijlingen

Brijesh sathian.

4 Geriatrics and long term care Department, Rumailah Hospital, Hamad Medical Corporation, Doha, Qatar

Indrajit Banerjee

5 Sir Seewoosagur Ramgoolam Medical College, Belle Rive, Mauritius

All authors have made substantial contributions to all of the following: (1) the conception and design of the study (2) drafting the article or revising it critically for important intellectual content, (3) final approval of the version to be submitted

There is no conflict of interest for any author of this manuscript.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sector.

This paper illustrates the growing importance of mixed-methods research to many health disciplines ranging from nursing to epidemiology. Mixed-methods approaches requires not only the skills of the individual quantitative and qualitative methods but also a skill set to bring two methods/datasets/findings together in the most appropriate way. Health researchers need to pay careful attention to the ‘best’ approach to designing, implementing, analysing, integrating both quantitative (number) and qualitative (word) information and writing this up in a way offers greater insights and enhances its applicability. This paper highlights the strengths and weaknesses of mixed-methods approaches as well as some of the common mistakes made by researchers applying mixed-methods for the first time.

Quantitative and qualitative research methods each address different types of questions, collect different kinds of data and deliver different kinds of answers. Each set of methods has its own inherent strengths and weaknesses, and each offers a particular approach to address specific types of research questions (and agendas). Health disciplines such as dentistry, nursing, speech and language therapy, and physiotherapy often use either quantitative or qualitative research methods on their own. However, there is a steadily growing literature showing the advantages of mixed-methods research is used in the health care and health service field [ 1-2 ]. Although we have advocated the use of mixed-methods in this journal eight years ago [ 3 ], there is still not enough mixed-methods research training in the health research field, particularly for health care practitioners, such as nurses, physiotherapists, midwives, and doctors, wanting to do research. Mixed-methods research has been popular in the social sciences since the twentieth century [ 4 ], and it has been growing in popularity among healthcare professionals [ 5 ], although it is still underdeveloped in disciplines such nursing and midwifery [ 6 , 7 ].

Underpinning philosophies

To help understand that mixed-methods research is not simply employing two different methods in the same study, one needs to consider their underpinning research philosophies (also called paradigms). First, quantitative research is usually underpinned by positivism. This includes most epidemiological studies; such research is typically based on the assumption that there is one single real world out there that can be measured. For example, quantitative research would address the question “What proportion of the population of India drinks coffee?” Secondly, qualitative research is more likely to be based on interpretivism. This includes research based on interviews and focus groups, research which us is typically based on the assumption that we all experience the world differently. Since we all live in a slightly different world in our heads the task of qualitative research is to analyse the interpretations of the people in the sample. For example, qualitative research would address the question “How do people experience drinking coffee in India?”, and “What does drinking coffee mean to them?”

Mixed-methods research brings together questions from two different philosophies in what is being referred to as the third path [ 8 ], third research paradigm [ 9 , 10 ], the third methodology movement [ 11 , 12 ] and pragmatism [ 5 ]. The two paradigms differ in key underlying assumptions that ultimately lead to choices in research methodology and methods and often give a breadth by answering more complicated research questions [ 4 ]. The roles of mixed-methods are clear in an understanding of the situation (the what), meaning, norms, values (the why or how) within a single research question which combine the strength of two different method and offer multiple ways of looking at the research question [ 13 ]. Epidemiology sits strongly in the quantitative research corner, with a strong emphasis on large data sets and sophisticated statistical analysis. Although the use of mixed methods in health research has been discussed widely researchers raised concerns about the explanation of why and how mixed methods are used in a single research question [ 5 ].

The relevance of mixed-methods in health research

The overall goal of the mixed-methods research design is to provide a better and deeper understanding, by providing a fuller picture that can enhance description and understanding of the phenomena [ 4 ]. Mixed-methods research has become popular because it uses quantitative and qualitative data in one single study which provides stronger inference than using either approach on its own [ 4 ]. In other words, a mixed-methods paper helps to understand the holistic picture from meanings obtained from interviews or observation to the prevalence of traits in a population obtained from surveys, which add depth and breadth to the study. For example, a survey questionnaire will include a limited number of structured questions, adding qualitative methods can capture other unanticipated facets of the topic that may be relevant to the research problem and help in the interpretation of the quantitative data. A good example of a mixed-methods study, it one conducted in Australia to understand the nursing care in public hospitals and also explore what factors influence adherence to nursing care [ 14 ]. Another example is a mixed-methods study that explores the relationship between nursing care practices and patient satisfaction. This study started with a quantitative survey to understand the general nursing services followed by qualitative interviews. A logistic regression analysis was performed to quantify the associations between general nursing practice variables supplemented with a thematic analysis of the interviews [ 15 ]. These research questions could not be answered if the researchers had used either qualitative or quantitative alone. Overall, this fits well with the development of evidence-based practice.

Despite the strengths of mixed-methods research but there is not much of it in nursing and other fields [ 7 ]. A recent review paper shows that the prevalence of mixed-methods studies in nursing was only 1.9% [ 7 ]. Similarly, a systematic review synthesised a total of 20 papers [ 16 ], and 16 papers [ 17 ] on nursing-related research paper among these only one mixed-methods paper was identified. Worse, a further two mixed-methods review recently revealed that out of 48 [ 18 , 19 ] synthesised nursing research papers, not one single mixed-methods paper was identified. This clearly depicts that mixed-methods research is still in its infancy stage in nursing but we can say there is huge scope to implement it to understand research questions on both sides of coin [ 4 ]. Therefore, there is a great need for mixed-methods training to enhance the evidence-based decision making in health and nursing practices.

Strengths and weaknesses of mixed-methods

There are several challenges in identifying expertise of both methods and in working with a multidisciplinary, interdisciplinary, or transdisciplinary team [ 20 ]. It increases costs and resources, takes longer to complete as mixed-methods design often involves multiple stages of data collection and separate data analysis [ 4 , 5 ]. Moreover, conducting mixed-methods research does not necessarily guarantee an improvement in the quality of health research. Therefore, mixed-methods research is only appropriate when there are appropriate research questions [ 4 , 6 ].

Identifying an appropriate mixed-methods journal can also be challenging when writing mixed-methods papers [ 21 ]. Mixed-methods papers need considerably more words than single-methods papers as well as sympathetic editors who understand the underlying philosophy of a mixed-methods approach. Such papers, simply require more words. The mixed-methods researcher must be reporting two separate methods with their own characteristics, different samples, and ways of analysing, therefore needs more words to describe both methods as well as both sets of findings. Researcher needs to find a journal that accepts longer articles to help broaden existing evidence-based practice and promote its applicability in the nursing field [ 22 ].

Common mistakes in applying mixed-methods

Not all applied researchers have insight into the underlying philosophy and/or the skills to apply each set of methods appropriately. Younas and colleagues’ review identified that around one-third (29%) of mixed-methods studies did not provide an explicit label of the study design and 95% of studies did not identify the research paradigm [ 7 ]. Whilst several mixed-methods publications did not provide clear research questions covering both quantitative and qualitative approaches. Another common issue is how to collect data either concurrent or sequential and the priority is given to each approach within the study where equal or dominant which are not clearly stated in writing which is important to mention while writing in the methods section. Similarly, a commonly overlooked aspect is how to integrate both findings in a paper. The responsibility lies with the researcher to ensure that findings are sufficiently plausible and credible [ 4 ]. Therefore, intensive mixed-methods research training is required for nursing and other health practitioners to ensure its appropriate.

The way forward

Despite the recognised strengths and benefits of doing mixed-methods research, there is still only a limited number of nursing and related-health research publications using such this approach. Researchers need training in how to design, conduct, analyse, synthesise and disseminate mixed-methods research. Most importantly, they need to consider appropriate research questions that can be addressed using a mixed methods approach to add to our knowledge in evidence-based practice. In short, we need more training on mixed-methods research for a range of health researchers and health professionals.

Acknowledgement

Library Guides

Dissertations 4: methodology: methods.

• Introduction & Philosophy
• Methodology

Primary & Secondary Sources, Primary & Secondary Data

When describing your research methods, you can start by stating what kind of secondary and, if applicable, primary sources you used in your research. Explain why you chose such sources, how well they served your research, and identify possible issues encountered using these sources.  

Definitions  

There is some confusion on the use of the terms primary and secondary sources, and primary and secondary data. The confusion is also due to disciplinary differences (Lombard 2010). Whilst you are advised to consult the research methods literature in your field, we can generalise as follows:  

Secondary sources 

Secondary sources normally include the literature (books and articles) with the experts' findings, analysis and discussions on a certain topic (Cottrell, 2014, p123). Secondary sources often interpret primary sources.  

Primary sources 

Primary sources are "first-hand" information such as raw data, statistics, interviews, surveys, law statutes and law cases. Even literary texts, pictures and films can be primary sources if they are the object of research (rather than, for example, documentaries reporting on something else, in which case they would be secondary sources). The distinction between primary and secondary sources sometimes lies on the use you make of them (Cottrell, 2014, p123). 

Primary data 

Primary data are data (primary sources) you directly obtained through your empirical work (Saunders, Lewis and Thornhill 2015, p316). 

Secondary data 

Secondary data are data (primary sources) that were originally collected by someone else (Saunders, Lewis and Thornhill 2015, p316).   

Comparison between primary and secondary data   

Use  

Virtually all research will use secondary sources, at least as background information. 

Often, especially at the postgraduate level, it will also use primary sources - secondary and/or primary data. The engagement with primary sources is generally appreciated, as less reliant on others' interpretations, and closer to 'facts'. 

The use of primary data, as opposed to secondary data, demonstrates the researcher's effort to do empirical work and find evidence to answer her specific research question and fulfill her specific research objectives. Thus, primary data contribute to the originality of the research.    

Ultimately, you should state in this section of the methodology: 

What sources and data you are using and why (how are they going to help you answer the research question and/or test the hypothesis. 

If using primary data, why you employed certain strategies to collect them. 

What the advantages and disadvantages of your strategies to collect the data (also refer to the research in you field and research methods literature). 

Quantitative, Qualitative & Mixed Methods

The methodology chapter should reference your use of quantitative research, qualitative research and/or mixed methods. The following is a description of each along with their advantages and disadvantages. 

Quantitative research 

Quantitative research uses numerical data (quantities) deriving, for example, from experiments, closed questions in surveys, questionnaires, structured interviews or published data sets (Cottrell, 2014, p93). It normally processes and analyses this data using quantitative analysis techniques like tables, graphs and statistics to explore, present and examine relationships and trends within the data (Saunders, Lewis and Thornhill, 2015, p496). 

Qualitative research  

Qualitative research is generally undertaken to study human behaviour and psyche. It uses methods like in-depth case studies, open-ended survey questions, unstructured interviews, focus groups, or unstructured observations (Cottrell, 2014, p93). The nature of the data is subjective, and also the analysis of the researcher involves a degree of subjective interpretation. Subjectivity can be controlled for in the research design, or has to be acknowledged as a feature of the research. Subject-specific books on (qualitative) research methods offer guidance on such research designs.  

Mixed methods 

Mixed-method approaches combine both qualitative and quantitative methods, and therefore combine the strengths of both types of research. Mixed methods have gained popularity in recent years.  

When undertaking mixed-methods research you can collect the qualitative and quantitative data either concurrently or sequentially. If sequentially, you can for example, start with a few semi-structured interviews, providing qualitative insights, and then design a questionnaire to obtain quantitative evidence that your qualitative findings can also apply to a wider population (Specht, 2019, p138). 

Ultimately, your methodology chapter should state: 

Whether you used quantitative research, qualitative research or mixed methods. 

Why you chose such methods (and refer to research method sources). 

Why you rejected other methods. 

How well the method served your research. 

The problems or limitations you encountered. 

Doug Specht, Senior Lecturer at the Westminster School of Media and Communication, explains mixed methods research in the following video:

LinkedIn Learning Video on Academic Research Foundations: Quantitative

The video covers the characteristics of quantitative research, and explains how to approach different parts of the research process, such as creating a solid research question and developing a literature review. He goes over the elements of a study, explains how to collect and analyze data, and shows how to present your data in written and numeric form.

Link to quantitative research video

Some Types of Methods

There are several methods you can use to get primary data. To reiterate, the choice of the methods should depend on your research question/hypothesis. 

Whatever methods you will use, you will need to consider: 

why did you choose one technique over another? What were the advantages and disadvantages of the technique you chose? 

what was the size of your sample? Who made up your sample? How did you select your sample population? Why did you choose that particular sampling strategy?) 

ethical considerations (see also tab...)  

safety considerations  

validity  

feasibility  

recording  

procedure of the research (see box procedural method...).  

Check Stella Cottrell's book  Dissertations and Project Reports: A Step by Step Guide  for some succinct yet comprehensive information on most methods (the following account draws mostly on her work). Check a research methods book in your discipline for more specific guidance.  

Experiments 

Experiments are useful to investigate cause and effect, when the variables can be tightly controlled. They can test a theory or hypothesis in controlled conditions. Experiments do not prove or disprove an hypothesis, instead they support or not support an hypothesis. When using the empirical and inductive method it is not possible to achieve conclusive results. The results may only be valid until falsified by other experiments and observations. 

For more information on Scientific Method, click here . 

Observations 

Observational methods are useful for in-depth analyses of behaviours in people, animals, organisations, events or phenomena. They can test a theory or products in real life or simulated settings. They generally a qualitative research method.  

Questionnaires and surveys 

Questionnaires and surveys are useful to gain opinions, attitudes, preferences, understandings on certain matters. They can provide quantitative data that can be collated systematically; qualitative data, if they include opportunities for open-ended responses; or both qualitative and quantitative elements. 

Interviews  

Interviews are useful to gain rich, qualitative information about individuals' experiences, attitudes or perspectives. With interviews you can follow up immediately on responses for clarification or further details. There are three main types of interviews: structured (following a strict pattern of questions, which expect short answers), semi-structured (following a list of questions, with the opportunity to follow up the answers with improvised questions), and unstructured (following a short list of broad questions, where the respondent can lead more the conversation) (Specht, 2019, p142). 

This short video on qualitative interviews discusses best practices and covers qualitative interview design, preparation and data collection methods. 

Focus groups   

In this case, a group of people (normally, 4-12) is gathered for an interview where the interviewer asks questions to such group of participants. Group interactions and discussions can be highly productive, but the researcher has to beware of the group effect, whereby certain participants and views dominate the interview (Saunders, Lewis and Thornhill 2015, p419). The researcher can try to minimise this by encouraging involvement of all participants and promoting a multiplicity of views. 

This video focuses on strategies for conducting research using focus groups.  

Check out the guidance on online focus groups by Aliaksandr Herasimenka, which is attached at the bottom of this text box. 

Case study 

Case studies are often a convenient way to narrow the focus of your research by studying how a theory or literature fares with regard to a specific person, group, organisation, event or other type of entity or phenomenon you identify. Case studies can be researched using other methods, including those described in this section. Case studies give in-depth insights on the particular reality that has been examined, but may not be representative of what happens in general, they may not be generalisable, and may not be relevant to other contexts. These limitations have to be acknowledged by the researcher.     

Content analysis 

Content analysis consists in the study of words or images within a text. In its broad definition, texts include books, articles, essays, historical documents, speeches, conversations, advertising, interviews, social media posts, films, theatre, paintings or other visuals. Content analysis can be quantitative (e.g. word frequency) or qualitative (e.g. analysing intention and implications of the communication). It can detect propaganda, identify intentions of writers, and can see differences in types of communication (Specht, 2019, p146). Check this page on collecting, cleaning and visualising Twitter data.

Extra links and resources:  

Research Methods  

A clear and comprehensive overview of research methods by Emerald Publishing. It includes: crowdsourcing as a research tool; mixed methods research; case study; discourse analysis; ground theory; repertory grid; ethnographic method and participant observation; interviews; focus group; action research; analysis of qualitative data; survey design; questionnaires; statistics; experiments; empirical research; literature review; secondary data and archival materials; data collection. 

Doing your dissertation during the COVID-19 pandemic  

Resources providing guidance on doing dissertation research during the pandemic: Online research methods; Secondary data sources; Webinars, conferences and podcasts; 

• Virtual Focus Groups Guidance on managing virtual focus groups

5 Minute Methods Videos

The following are a series of useful videos that introduce research methods in five minutes. These resources have been produced by lecturers and students with the University of Westminster's School of Media and Communication. 

Case Study Research

Research Ethics

Quantitative Content Analysis 

Sequential Analysis 

Qualitative Content Analysis 

Thematic Analysis 

Social Media Research 

Mixed Method Research 

Procedural Method

In this part, provide an accurate, detailed account of the methods and procedures that were used in the study or the experiment (if applicable!). 

Include specifics about participants, sample, materials, design and methods. 

If the research involves human subjects, then include a detailed description of who and how many participated along with how the participants were selected.  

Describe all materials used for the study, including equipment, written materials and testing instruments. 

Identify the study's design and any variables or controls employed. 

Write out the steps in the order that they were completed. 

Indicate what participants were asked to do, how measurements were taken and any calculations made to raw data collected. 

Specify statistical techniques applied to the data to reach your conclusions. 

Provide evidence that you incorporated rigor into your research. This is the quality of being thorough and accurate and considers the logic behind your research design. 

Highlight any drawbacks that may have limited your ability to conduct your research thoroughly. 

You have to provide details to allow others to replicate the experiment and/or verify the data, to test the validity of the research. 

Bibliography

Cottrell, S. (2014). Dissertations and project reports: a step by step guide. Hampshire, England: Palgrave Macmillan.

Lombard, E. (2010). Primary and secondary sources.  The Journal of Academic Librarianship , 36(3), 250-253

Saunders, M.N.K., Lewis, P. and Thornhill, A. (2015).  Research Methods for Business Students.  New York: Pearson Education. 

Specht, D. (2019).  The Media And Communications Study Skills Student Guide . London: University of Westminster Press.  

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• Introduction
• FUNDAMENTALS

Qualitative, quantitative and mixed methods dissertations

What are they and which one should i choose.

In the sections that follow, we briefly describe the main characteristics of qualitative, quantitative and mixed methods dissertations. Rather than being exhaustive, the main goal is to highlight what these types of research are and what they involve. Whilst you read through each section, try and think about your own dissertation, and whether you think that one of these types of dissertation might be right for you. After reading about these three types of dissertation, we highlight some of the academic, personal and practical reasons why you may choose to take on one type over another.

• Types of dissertation: Qualitative, quantitative and mixed methods dissertations
• Choosing between types: Academic, personal and practical justifications

Types of dissertation

Whilst we describe the main characteristics of qualitative, quantitative and mixed methods dissertations, the Lærd Dissertation site currently focuses on helping guide you through quantitative dissertations , whether you are a student of the social sciences, psychology, education or business, or are studying medical or biological sciences, sports science, or another science-based degree. Nonetheless, you may still find our introductions to qualitative dissertations and mixed methods dissertations useful, if only to decide whether these types of dissertation are for you. We discuss quantitative dissertations , qualitative dissertations and mixed methods dissertations in turn:

Quantitative dissertations

When we use the word quantitative to describe quantitative dissertations , we do not simply mean that the dissertation will draw on quantitative research methods or statistical analysis techniques . Quantitative research takes a particular approach to theory , answering research questions and/or hypotheses , setting up a research strategy , making conclusions from results , and so forth. Classic routes that you can follow include replication-based studies , theory-driven research and data-driven dissertations . However, irrespective of the particular route that you adopt when taking on a quantitative dissertation, there are a number of core characteristics to quantitative dissertations:

They typically attempt to build on and/or test theories , whether adopting an original approach or an approach based on some kind of replication or extension .

They answer quantitative research questions and/or research (or null ) hypotheses .

They are mainly underpinned by positivist or post-positivist research paradigms .

They draw on one of four broad quantitative research designs (i.e., descriptive , experimental , quasi-experimental or relationship-based research designs).

They try to use probability sampling techniques , with the goal of making generalisations from the sample being studied to a wider population , although often end up applying non-probability sampling techniques .

They use research methods that generate quantitative data (e.g., data sets , laboratory-based methods , questionnaires/surveys , structured interviews , structured observation , etc.).

They draw heavily on statistical analysis techniques to examine the data collected, whether descriptive or inferential in nature.

They assess the quality of their findings in terms of their reliability , internal and external validity , and construct validity .

They report their findings using statements , data , tables and graphs that address each research question and/or hypothesis.

They make conclusions in line with the findings , research questions and/or hypotheses , and theories discussed in order to test and/or expand on existing theories, or providing insight for future theories.

If you choose to take on a quantitative dissertation , go to the Quantitative Dissertations part of Lærd Dissertation now. You will learn more about the characteristics of quantitative dissertations, as well as being able to choose between the three classic routes that are pursued in quantitative research: replication-based studies , theory-driven research and data-driven dissertations . Upon choosing your route, the Quantitative Dissertations part of Lærd Dissertation will help guide you through these routes, from topic idea to completed dissertation, as well as showing you how to write up quantitative dissertations.

Qualitative dissertations

Qualitative dissertations , like qualitative research in general, are often associated with qualitative research methods such as unstructured interviews, focus groups and participant observation. Whilst they do use a set of research methods that are not used in quantitative dissertations, qualitative research is much more than a choice between research methods. Qualitative research takes a particular approach towards the research process , the setting of research questions , the development and use of theory , the choice of research strategy , the way that findings are presented and discussed, and so forth. Overall, qualitative dissertations will be very different in approach, depending on the particular route that you adopt (e.g., case study research compared to ethnographies). Classic routes that you can follow include autoethnographies , case study research , ethnographies , grounded theory , narrative research and phenomenological research . However, irrespective of the route that you choose to follow, there are a number of broad characteristics to qualitative dissertations:

They follow an emergent design , meaning that the research process , and sometimes even the qualitative research questions that you tackle, often evolve during the dissertation process.

They use theory in a variety of ways - sometimes drawing on theory to help the research process; on other occasions, using theory to develop new theoretical insights ; sometimes both - but the goal is infrequently to test a particular theory from the outset.

They can be underpinned by one of a number of research paradigms (e.g., interpretivism , constructivism , critical theory , amongst many other research paradigms).

They follow research designs that heavily influence the choices you make throughout the research process, as well as the analysis and discussion of 'findings' (i.e., such research designs differ considerably depending on the route that is being followed, whether an autoethnography , case study research , ethnography , grounded theory , narrative research , phenomenological research , etc.).

They try to use theoretical sampling - a group of non-probability sampling techniques - with the goal of studying cases (i.e., people or organisations) that are most appropriate to answering their research questions.

They study people in-the-field (i.e., in natural settings ), often using multiple research methods , each of which generate qualitative data (e.g., unstructured interviews , focus groups , participant observation , etc.).

They interpret the qualitative data through the eyes and biases of the researcher , going back-and-forth through the data (i.e., an inductive process ) to identify themes or abstractions that build a holistic/gestalt picture of what is being studied.

They assess the quality of their findings in terms of their dependability , confirmability , conformability and transferability .

They present (and discuss ) their findings through personal accounts , case studies , narratives , and other means that identify themes or abstracts , processes , observations and contradictions , which help to address their research questions.

They discuss the theoretical insights arising from the findings in light of the research questions, from which tentative conclusions are made.

If you choose to take on a qualitative dissertation , you will be able to learn a little about appropriate research methods and sampling techniques in the Fundamentals section of Lærd Dissertation. However, we have not yet launched a dedicated section to qualitative dissertations within Lærd Dissertation. If this is something that you would like us to do sooner than later, please leave feedback .

Mixed methods dissertations

Mixed methods dissertations combine qualitative and quantitative approaches to research. Whilst they are increasingly used and have gained greater legitimacy, much less has been written about their components parts. There are a number of reasons why mixed methods dissertations are used, including the feeling that a research question can be better addressed by:

Collecting qualitative and quantitative data , and then analysing or interpreting that data, whether separately or by mixing it.

Conducting more than one research phase ; perhaps conducting qualitative research to explore an issue and uncover major themes, before using quantitative research to measure the relationships between the themes.

One of the problems (or challenges) of mixed methods dissertations is that qualitative and quantitative research, as you will have seen from the two previous sections, are very different in approach. In many respects, they are opposing approaches to research. Therefore, when taking on a mixed methods dissertation, you need to think particularly carefully about the goals of your research, and whether the qualitative or quantitative components (a) are more important in philosophical, theoretical and practical terms, and (b) should be combined or kept separate.

Again, as with qualitative dissertations, we have yet to launch a dedicated section of Lærd Dissertation to mixed methods dissertations . However, you will be able to learn about many of the quantitative aspects of doing a mixed methods dissertation in the Quantitative Dissertations part of Lærd Dissertation. You may even be able to follow this part of our site entirely if the only qualitative aspect of your mixed methods dissertation is the use of qualitative methods to help you explore an issue or uncover major themes, before performing quantitative research to examine such themes further. Nonetheless, if you would like to see a dedicated section to mixed methods dissertations sooner than later, please leave feedback .

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• Knowledge Base
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• Mixed Methods Research | Definition, Guide, & Examples

Mixed Methods Research | Definition, Guide, & Examples

Published on 4 April 2022 by Tegan George . Revised on 25 October 2022.

Mixed methods research combines elements of quantitative research and qualitative research in order to answer your research question . Mixed methods can help you gain a more complete picture than a standalone quantitative or qualitative study, as it integrates benefits of both methods.

Mixed methods research is often used in the behavioral, health, and social sciences, especially in multidisciplinary settings and complex situational or societal research.

• To what extent does the frequency of traffic accidents ( quantitative ) reflect cyclist perceptions of road safety ( qualitative ) in Amsterdam?
• How do student perceptions of their school environment ( qualitative ) relate to differences in test scores ( quantitative ) ?
• How do interviews about job satisfaction at Company X ( qualitative ) help explain year-over-year sales performance and other KPIs ( quantitative ) ?
• How can voter and non-voter beliefs about democracy ( qualitative ) help explain election turnout patterns ( quantitative ) in Town X?
• How do average hospital salary measurements over time (quantitative) help to explain nurse testimonials about job satisfaction (qualitative) ?

Table of contents

When to use mixed methods research, mixed methods research designs, benefits of mixed methods research, disadvantages of mixed methods research, frequently asked questions about mixed methods research.

Mixed methods research may be the right choice if your research process suggests that quantitative or qualitative data alone will not sufficiently answer your research question. There are several common reasons for using mixed methods research:

• Generalisability : Qualitative research usually has a smaller sample size , and thus is not generalisable . In mixed methods research, this comparative weakness is mitigated by the comparative strength of ‘large N’, externally valid quantitative research.
• Contextualisation: Mixing methods allows you to put findings in context and add richer detail to your conclusions. Using qualitative data to illustrate quantitative findings can help ‘put meat on the bones’ of your analysis.
• Credibility: Using different methods to collect data on the same subject can make your results more credible. If the qualitative and quantitative data converge, this strengthens the validity of your conclusions. This process is called triangulation .

As you formulate your research question , try to directly address how qualitative and quantitative methods will be combined in your study. If your research question can be sufficiently answered via standalone quantitative or qualitative analysis, a mixed methods approach may not be the right fit.

Keep in mind that mixed methods research doesn’t just mean collecting both types of data; you need to carefully consider the relationship between the two and how you’ll integrate them into coherent conclusions. Mixed methods can be very challenging to put into practice, so it’s a less common choice than standalone qualitative or qualitative research.

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There are different types of mixed methods research designs . The differences between them relate to the aim of the research, the timing of the data collection , and the importance given to each data type.

As you design your mixed methods study, also keep in mind:

• Your research approach ( inductive vs deductive )
• Your research questions
• What kind of data is already available for you to use
• What kind of data you’re able to collect yourself.

Here are a few of the most common mixed methods designs.

Convergent parallel

In a convergent parallel design, you collect quantitative and qualitative data at the same time and analyse them separately. After both analyses are complete, compare your results to draw overall conclusions.

• On the qualitative side, you analyse cyclist complaints via the city’s database and on social media to find out which areas are perceived as dangerous and why.
• On the quantitative side, you analyse accident reports in the city’s database to find out how frequently accidents occur in different areas of the city.

In an embedded design, you collect and analyse both types of data at the same time, but within a larger quantitative or qualitative design. One type of data is secondary to the other.

This is a good approach to take if you have limited time or resources. You can use an embedded design to strengthen or supplement your conclusions from the primary type of research design.

Explanatory sequential

In an explanatory sequential design, your quantitative data collection and analysis occurs first, followed by qualitative data collection and analysis.

You should use this design if you think your qualitative data will explain and contextualise your quantitative findings.

Exploratory sequential

In an exploratory sequential design, qualitative data collection and analysis occurs first, followed by quantitative data collection and analysis.

You can use this design to first explore initial questions and develop hypotheses. Then you can use the quantitative data to test or confirm your qualitative findings.

‘Best of both worlds’ analysis

Combining the two types of data means you benefit from both the detailed, contextualised insights of qualitative data and the generalisable, externally valid insights of quantitative data. The strengths of one type of data often mitigate the weaknesses of the other.

For example, solely quantitative studies often struggle to incorporate the lived experiences of your participants, so adding qualitative data deepens and enriches your quantitative results.

Solely qualitative studies are often not very generalisable, only reflecting the experiences of your participants, so adding quantitative data can validate your qualitative findings.

Method flexibility

Mixed methods are less tied to disciplines and established research paradigms. They offer more flexibility in designing your research, allowing you to combine aspects of different types of studies to distill the most informative results.

Mixed methods research can also combine theory generation and hypothesis testing within a single study, which is unusual for standalone qualitative or quantitative studies.

Mixed methods research is very labour-intensive. Collecting, analysing, and synthesising two types of data into one research product takes a lot of time and effort, and often involves interdisciplinary teams of researchers rather than individuals. For this reason, mixed methods research has the potential to cost much more than standalone studies.

Differing or conflicting results

If your analysis yields conflicting results, it can be very challenging to know how to interpret them in a mixed methods study. If the quantitative and qualitative results do not agree or you are concerned you may have confounding variables , it can be unclear how to proceed.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organisations.

Triangulation in research means using multiple datasets, methods, theories and/or investigators to address a research question. It’s a research strategy that can help you enhance the validity and credibility of your findings.

Triangulation is mainly used in qualitative research , but it’s also commonly applied in quantitative research . Mixed methods research always uses triangulation.

These are four of the most common mixed methods designs :

• Convergent parallel: Quantitative and qualitative data are collected at the same time and analysed separately. After both analyses are complete, compare your results to draw overall conclusions. 
• Embedded: Quantitative and qualitative data are collected at the same time, but within a larger quantitative or qualitative design. One type of data is secondary to the other.
• Explanatory sequential: Quantitative data is collected and analysed first, followed by qualitative data. You can use this design if you think your qualitative data will explain and contextualise your quantitative findings.
• Exploratory sequential: Qualitative data is collected and analysed first, followed by quantitative data. You can use this design if you think the quantitative data will confirm or validate your qualitative findings.

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Tegan George

WHY VARIANCE MATTERS: A MIXED-METHODS APPROACH TO MICROCREDIT IMPACT EVALUATION

Research on microcredit overwhelmingly focuses on its average or typical impact on socio-economic development (SED), but it needs to delve deeper because impact is heterogeneous in nature. By understanding why credit affects people differently, one can better understand the various needs of and design better financial products for those living in poverty. Using a mixed methods approach, this dissertation seeks to explain the impact of microcredit on SED and what is driving the variance therein at the level of the borrower. To these ends, the dissertation utilizes a randomized controlled trial (RCT) to compare villages that received credit to similar community members who did not. This process determined the impact of microcredit loans on borrowers of the Buseesa Community Development Centre in Buyanja County, Uganda. The dissertation then employs participant observation, semi-structured interviews, and process tracing to analyze how shocks and household factors promote diverse SED outcomes. Participant observation informs more contextualized questions and decreases interviewee bias. Semi-structured interviews analyze borrowers' experience with credit and process tracing helps construct typologies of factors that influence variation in impact. Using this framework, the dissertation found that microcredit's impact is concentrated in farming inputs and outputs. It discovered that borrowers mitigate the risk of taking on loans by substituting away from the area's main commercial crop - tobacco - into expanded staple crop sales. The impact was found to be small due to the confluence of the market structure - e.g., the supply glut of low-valued staple crops - the geography, and ways in which traders manipulate prices, diminish the ability of families to benefit from access to credit. Within this impact, however, there is divergence in outcomes caused by shocks and household factors. Shocks - weather, health, and other - disrupt economic inputs and outputs. Finally, household factors -ability to negotiate the price of crops, timing of agricultural sales, having a diversified income, and loan misuse - impact investment, revenues, and livelihood strategies

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