academic articles about research methods

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• Published: 11 October 2016

Reviewing the research methods literature: principles and strategies illustrated by a systematic overview of sampling in qualitative research

• Stephen J. Gentles 1 , 4 ,
• Cathy Charles 1 ,
• David B. Nicholas 2 ,
• Jenny Ploeg 3 &
• K. Ann McKibbon 1  

Systematic Reviews volume  5 , Article number:  172 ( 2016 ) Cite this article

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Overviews of methods are potentially useful means to increase clarity and enhance collective understanding of specific methods topics that may be characterized by ambiguity, inconsistency, or a lack of comprehensiveness. This type of review represents a distinct literature synthesis method, although to date, its methodology remains relatively undeveloped despite several aspects that demand unique review procedures. The purpose of this paper is to initiate discussion about what a rigorous systematic approach to reviews of methods, referred to here as systematic methods overviews , might look like by providing tentative suggestions for approaching specific challenges likely to be encountered. The guidance offered here was derived from experience conducting a systematic methods overview on the topic of sampling in qualitative research.

The guidance is organized into several principles that highlight specific objectives for this type of review given the common challenges that must be overcome to achieve them. Optional strategies for achieving each principle are also proposed, along with discussion of how they were successfully implemented in the overview on sampling. We describe seven paired principles and strategies that address the following aspects: delimiting the initial set of publications to consider, searching beyond standard bibliographic databases, searching without the availability of relevant metadata, selecting publications on purposeful conceptual grounds, defining concepts and other information to abstract iteratively, accounting for inconsistent terminology used to describe specific methods topics, and generating rigorous verifiable analytic interpretations. Since a broad aim in systematic methods overviews is to describe and interpret the relevant literature in qualitative terms, we suggest that iterative decision making at various stages of the review process, and a rigorous qualitative approach to analysis are necessary features of this review type.

Conclusions

We believe that the principles and strategies provided here will be useful to anyone choosing to undertake a systematic methods overview. This paper represents an initial effort to promote high quality critical evaluations of the literature regarding problematic methods topics, which have the potential to promote clearer, shared understandings, and accelerate advances in research methods. Further work is warranted to develop more definitive guidance.

Peer Review reports

While reviews of methods are not new, they represent a distinct review type whose methodology remains relatively under-addressed in the literature despite the clear implications for unique review procedures. One of few examples to describe it is a chapter containing reflections of two contributing authors in a book of 21 reviews on methodological topics compiled for the British National Health Service, Health Technology Assessment Program [ 1 ]. Notable is their observation of how the differences between the methods reviews and conventional quantitative systematic reviews, specifically attributable to their varying content and purpose, have implications for defining what qualifies as systematic. While the authors describe general aspects of “systematicity” (including rigorous application of a methodical search, abstraction, and analysis), they also describe a high degree of variation within the category of methods reviews itself and so offer little in the way of concrete guidance. In this paper, we present tentative concrete guidance, in the form of a preliminary set of proposed principles and optional strategies, for a rigorous systematic approach to reviewing and evaluating the literature on quantitative or qualitative methods topics. For purposes of this article, we have used the term systematic methods overview to emphasize the notion of a systematic approach to such reviews.

The conventional focus of rigorous literature reviews (i.e., review types for which systematic methods have been codified, including the various approaches to quantitative systematic reviews [ 2 – 4 ], and the numerous forms of qualitative and mixed methods literature synthesis [ 5 – 10 ]) is to synthesize empirical research findings from multiple studies. By contrast, the focus of overviews of methods, including the systematic approach we advocate, is to synthesize guidance on methods topics. The literature consulted for such reviews may include the methods literature, methods-relevant sections of empirical research reports, or both. Thus, this paper adds to previous work published in this journal—namely, recent preliminary guidance for conducting reviews of theory [ 11 ]—that has extended the application of systematic review methods to novel review types that are concerned with subject matter other than empirical research findings.

Published examples of methods overviews illustrate the varying objectives they can have. One objective is to establish methodological standards for appraisal purposes. For example, reviews of existing quality appraisal standards have been used to propose universal standards for appraising the quality of primary qualitative research [ 12 ] or evaluating qualitative research reports [ 13 ]. A second objective is to survey the methods-relevant sections of empirical research reports to establish current practices on methods use and reporting practices, which Moher and colleagues [ 14 ] recommend as a means for establishing the needs to be addressed in reporting guidelines (see, for example [ 15 , 16 ]). A third objective for a methods review is to offer clarity and enhance collective understanding regarding a specific methods topic that may be characterized by ambiguity, inconsistency, or a lack of comprehensiveness within the available methods literature. An example of this is a overview whose objective was to review the inconsistent definitions of intention-to-treat analysis (the methodologically preferred approach to analyze randomized controlled trial data) that have been offered in the methods literature and propose a solution for improving conceptual clarity [ 17 ]. Such reviews are warranted because students and researchers who must learn or apply research methods typically lack the time to systematically search, retrieve, review, and compare the available literature to develop a thorough and critical sense of the varied approaches regarding certain controversial or ambiguous methods topics.

While systematic methods overviews , as a review type, include both reviews of the methods literature and reviews of methods-relevant sections from empirical study reports, the guidance provided here is primarily applicable to reviews of the methods literature since it was derived from the experience of conducting such a review [ 18 ], described below. To our knowledge, there are no well-developed proposals on how to rigorously conduct such reviews. Such guidance would have the potential to improve the thoroughness and credibility of critical evaluations of the methods literature, which could increase their utility as a tool for generating understandings that advance research methods, both qualitative and quantitative. Our aim in this paper is thus to initiate discussion about what might constitute a rigorous approach to systematic methods overviews. While we hope to promote rigor in the conduct of systematic methods overviews wherever possible, we do not wish to suggest that all methods overviews need be conducted to the same standard. Rather, we believe that the level of rigor may need to be tailored pragmatically to the specific review objectives, which may not always justify the resource requirements of an intensive review process.

The example systematic methods overview on sampling in qualitative research

The principles and strategies we propose in this paper are derived from experience conducting a systematic methods overview on the topic of sampling in qualitative research [ 18 ]. The main objective of that methods overview was to bring clarity and deeper understanding of the prominent concepts related to sampling in qualitative research (purposeful sampling strategies, saturation, etc.). Specifically, we interpreted the available guidance, commenting on areas lacking clarity, consistency, or comprehensiveness (without proposing any recommendations on how to do sampling). This was achieved by a comparative and critical analysis of publications representing the most influential (i.e., highly cited) guidance across several methodological traditions in qualitative research.

The specific methods and procedures for the overview on sampling [ 18 ] from which our proposals are derived were developed both after soliciting initial input from local experts in qualitative research and an expert health librarian (KAM) and through ongoing careful deliberation throughout the review process. To summarize, in that review, we employed a transparent and rigorous approach to search the methods literature, selected publications for inclusion according to a purposeful and iterative process, abstracted textual data using structured abstraction forms, and analyzed (synthesized) the data using a systematic multi-step approach featuring abstraction of text, summary of information in matrices, and analytic comparisons.

For this article, we reflected on both the problems and challenges encountered at different stages of the review and our means for selecting justifiable procedures to deal with them. Several principles were then derived by considering the generic nature of these problems, while the generalizable aspects of the procedures used to address them formed the basis of optional strategies. Further details of the specific methods and procedures used in the overview on qualitative sampling are provided below to illustrate both the types of objectives and challenges that reviewers will likely need to consider and our approach to implementing each of the principles and strategies.

Organization of the guidance into principles and strategies

For the purposes of this article, principles are general statements outlining what we propose are important aims or considerations within a particular review process, given the unique objectives or challenges to be overcome with this type of review. These statements follow the general format, “considering the objective or challenge of X, we propose Y to be an important aim or consideration.” Strategies are optional and flexible approaches for implementing the previous principle outlined. Thus, generic challenges give rise to principles, which in turn give rise to strategies.

We organize the principles and strategies below into three sections corresponding to processes characteristic of most systematic literature synthesis approaches: literature identification and selection ; data abstraction from the publications selected for inclusion; and analysis , including critical appraisal and synthesis of the abstracted data. Within each section, we also describe the specific methodological decisions and procedures used in the overview on sampling in qualitative research [ 18 ] to illustrate how the principles and strategies for each review process were applied and implemented in a specific case. We expect this guidance and accompanying illustrations will be useful for anyone considering engaging in a methods overview, particularly those who may be familiar with conventional systematic review methods but may not yet appreciate some of the challenges specific to reviewing the methods literature.

Results and discussion

Literature identification and selection.

The identification and selection process includes search and retrieval of publications and the development and application of inclusion and exclusion criteria to select the publications that will be abstracted and analyzed in the final review. Literature identification and selection for overviews of the methods literature is challenging and potentially more resource-intensive than for most reviews of empirical research. This is true for several reasons that we describe below, alongside discussion of the potential solutions. Additionally, we suggest in this section how the selection procedures can be chosen to match the specific analytic approach used in methods overviews.

Delimiting a manageable set of publications

One aspect of methods overviews that can make identification and selection challenging is the fact that the universe of literature containing potentially relevant information regarding most methods-related topics is expansive and often unmanageably so. Reviewers are faced with two large categories of literature: the methods literature , where the possible publication types include journal articles, books, and book chapters; and the methods-relevant sections of empirical study reports , where the possible publication types include journal articles, monographs, books, theses, and conference proceedings. In our systematic overview of sampling in qualitative research, exhaustively searching (including retrieval and first-pass screening) all publication types across both categories of literature for information on a single methods-related topic was too burdensome to be feasible. The following proposed principle follows from the need to delimit a manageable set of literature for the review.

Principle #1:

Considering the broad universe of potentially relevant literature, we propose that an important objective early in the identification and selection stage is to delimit a manageable set of methods-relevant publications in accordance with the objectives of the methods overview.

Strategy #1:

To limit the set of methods-relevant publications that must be managed in the selection process, reviewers have the option to initially review only the methods literature, and exclude the methods-relevant sections of empirical study reports, provided this aligns with the review’s particular objectives.

We propose that reviewers are justified in choosing to select only the methods literature when the objective is to map out the range of recognized concepts relevant to a methods topic, to summarize the most authoritative or influential definitions or meanings for methods-related concepts, or to demonstrate a problematic lack of clarity regarding a widely established methods-related concept and potentially make recommendations for a preferred approach to the methods topic in question. For example, in the case of the methods overview on sampling [ 18 ], the primary aim was to define areas lacking in clarity for multiple widely established sampling-related topics. In the review on intention-to-treat in the context of missing outcome data [ 17 ], the authors identified a lack of clarity based on multiple inconsistent definitions in the literature and went on to recommend separating the issue of how to handle missing outcome data from the issue of whether an intention-to-treat analysis can be claimed.

In contrast to strategy #1, it may be appropriate to select the methods-relevant sections of empirical study reports when the objective is to illustrate how a methods concept is operationalized in research practice or reported by authors. For example, one could review all the publications in 2 years’ worth of issues of five high-impact field-related journals to answer questions about how researchers describe implementing a particular method or approach, or to quantify how consistently they define or report using it. Such reviews are often used to highlight gaps in the reporting practices regarding specific methods, which may be used to justify items to address in reporting guidelines (for example, [ 14 – 16 ]).

It is worth recognizing that other authors have advocated broader positions regarding the scope of literature to be considered in a review, expanding on our perspective. Suri [ 10 ] (who, like us, emphasizes how different sampling strategies are suitable for different literature synthesis objectives) has, for example, described a two-stage literature sampling procedure (pp. 96–97). First, reviewers use an initial approach to conduct a broad overview of the field—for reviews of methods topics, this would entail an initial review of the research methods literature. This is followed by a second more focused stage in which practical examples are purposefully selected—for methods reviews, this would involve sampling the empirical literature to illustrate key themes and variations. While this approach is seductive in its capacity to generate more in depth and interpretive analytic findings, some reviewers may consider it too resource-intensive to include the second step no matter how selective the purposeful sampling. In the overview on sampling where we stopped after the first stage [ 18 ], we discussed our selective focus on the methods literature as a limitation that left opportunities for further analysis of the literature. We explicitly recommended, for example, that theoretical sampling was a topic for which a future review of the methods sections of empirical reports was justified to answer specific questions identified in the primary review.

Ultimately, reviewers must make pragmatic decisions that balance resource considerations, combined with informed predictions about the depth and complexity of literature available on their topic, with the stated objectives of their review. The remaining principles and strategies apply primarily to overviews that include the methods literature, although some aspects may be relevant to reviews that include empirical study reports.

Searching beyond standard bibliographic databases

An important reality affecting identification and selection in overviews of the methods literature is the increased likelihood for relevant publications to be located in sources other than journal articles (which is usually not the case for overviews of empirical research, where journal articles generally represent the primary publication type). In the overview on sampling [ 18 ], out of 41 full-text publications retrieved and reviewed, only 4 were journal articles, while 37 were books or book chapters. Since many books and book chapters did not exist electronically, their full text had to be physically retrieved in hardcopy, while 11 publications were retrievable only through interlibrary loan or purchase request. The tasks associated with such retrieval are substantially more time-consuming than electronic retrieval. Since a substantial proportion of methods-related guidance may be located in publication types that are less comprehensively indexed in standard bibliographic databases, identification and retrieval thus become complicated processes.

Principle #2:

Considering that important sources of methods guidance can be located in non-journal publication types (e.g., books, book chapters) that tend to be poorly indexed in standard bibliographic databases, it is important to consider alternative search methods for identifying relevant publications to be further screened for inclusion.

Strategy #2:

To identify books, book chapters, and other non-journal publication types not thoroughly indexed in standard bibliographic databases, reviewers may choose to consult one or more of the following less standard sources: Google Scholar, publisher web sites, or expert opinion.

In the case of the overview on sampling in qualitative research [ 18 ], Google Scholar had two advantages over other standard bibliographic databases: it indexes and returns records of books and book chapters likely to contain guidance on qualitative research methods topics; and it has been validated as providing higher citation counts than ISI Web of Science (a producer of numerous bibliographic databases accessible through institutional subscription) for several non-biomedical disciplines including the social sciences where qualitative research methods are prominently used [ 19 – 21 ]. While we identified numerous useful publications by consulting experts, the author publication lists generated through Google Scholar searches were uniquely useful to identify more recent editions of methods books identified by experts.

Searching without relevant metadata

Determining what publications to select for inclusion in the overview on sampling [ 18 ] could only rarely be accomplished by reviewing the publication’s metadata. This was because for the many books and other non-journal type publications we identified as possibly relevant, the potential content of interest would be located in only a subsection of the publication. In this common scenario for reviews of the methods literature (as opposed to methods overviews that include empirical study reports), reviewers will often be unable to employ standard title, abstract, and keyword database searching or screening as a means for selecting publications.

Principle #3:

Considering that the presence of information about the topic of interest may not be indicated in the metadata for books and similar publication types, it is important to consider other means of identifying potentially useful publications for further screening.

Strategy #3:

One approach to identifying potentially useful books and similar publication types is to consider what classes of such publications (e.g., all methods manuals for a certain research approach) are likely to contain relevant content, then identify, retrieve, and review the full text of corresponding publications to determine whether they contain information on the topic of interest.

In the example of the overview on sampling in qualitative research [ 18 ], the topic of interest (sampling) was one of numerous topics covered in the general qualitative research methods manuals. Consequently, examples from this class of publications first had to be identified for retrieval according to non-keyword-dependent criteria. Thus, all methods manuals within the three research traditions reviewed (grounded theory, phenomenology, and case study) that might contain discussion of sampling were sought through Google Scholar and expert opinion, their full text obtained, and hand-searched for relevant content to determine eligibility. We used tables of contents and index sections of books to aid this hand searching.

Purposefully selecting literature on conceptual grounds

A final consideration in methods overviews relates to the type of analysis used to generate the review findings. Unlike quantitative systematic reviews where reviewers aim for accurate or unbiased quantitative estimates—something that requires identifying and selecting the literature exhaustively to obtain all relevant data available (i.e., a complete sample)—in methods overviews, reviewers must describe and interpret the relevant literature in qualitative terms to achieve review objectives. In other words, the aim in methods overviews is to seek coverage of the qualitative concepts relevant to the methods topic at hand. For example, in the overview of sampling in qualitative research [ 18 ], achieving review objectives entailed providing conceptual coverage of eight sampling-related topics that emerged as key domains. The following principle recognizes that literature sampling should therefore support generating qualitative conceptual data as the input to analysis.

Principle #4:

Since the analytic findings of a systematic methods overview are generated through qualitative description and interpretation of the literature on a specified topic, selection of the literature should be guided by a purposeful strategy designed to achieve adequate conceptual coverage (i.e., representing an appropriate degree of variation in relevant ideas) of the topic according to objectives of the review.

Strategy #4:

One strategy for choosing the purposeful approach to use in selecting the literature according to the review objectives is to consider whether those objectives imply exploring concepts either at a broad overview level, in which case combining maximum variation selection with a strategy that limits yield (e.g., critical case, politically important, or sampling for influence—described below) may be appropriate; or in depth, in which case purposeful approaches aimed at revealing innovative cases will likely be necessary.

In the methods overview on sampling, the implied scope was broad since we set out to review publications on sampling across three divergent qualitative research traditions—grounded theory, phenomenology, and case study—to facilitate making informative conceptual comparisons. Such an approach would be analogous to maximum variation sampling.

At the same time, the purpose of that review was to critically interrogate the clarity, consistency, and comprehensiveness of literature from these traditions that was “most likely to have widely influenced students’ and researchers’ ideas about sampling” (p. 1774) [ 18 ]. In other words, we explicitly set out to review and critique the most established and influential (and therefore dominant) literature, since this represents a common basis of knowledge among students and researchers seeking understanding or practical guidance on sampling in qualitative research. To achieve this objective, we purposefully sampled publications according to the criterion of influence , which we operationalized as how often an author or publication has been referenced in print or informal discourse. This second sampling approach also limited the literature we needed to consider within our broad scope review to a manageable amount.

To operationalize this strategy of sampling for influence , we sought to identify both the most influential authors within a qualitative research tradition (all of whose citations were subsequently screened) and the most influential publications on the topic of interest by non-influential authors. This involved a flexible approach that combined multiple indicators of influence to avoid the dilemma that any single indicator might provide inadequate coverage. These indicators included bibliometric data (h-index for author influence [ 22 ]; number of cites for publication influence), expert opinion, and cross-references in the literature (i.e., snowball sampling). As a final selection criterion, a publication was included only if it made an original contribution in terms of novel guidance regarding sampling or a related concept; thus, purely secondary sources were excluded. Publish or Perish software (Anne-Wil Harzing; available at http://www.harzing.com/resources/publish-or-perish ) was used to generate bibliometric data via the Google Scholar database. Figure  1 illustrates how identification and selection in the methods overview on sampling was a multi-faceted and iterative process. The authors selected as influential, and the publications selected for inclusion or exclusion are listed in Additional file 1 (Matrices 1, 2a, 2b).

Literature identification and selection process used in the methods overview on sampling [ 18 ]

In summary, the strategies of seeking maximum variation and sampling for influence were employed in the sampling overview to meet the specific review objectives described. Reviewers will need to consider the full range of purposeful literature sampling approaches at their disposal in deciding what best matches the specific aims of their own reviews. Suri [ 10 ] has recently retooled Patton’s well-known typology of purposeful sampling strategies (originally intended for primary research) for application to literature synthesis, providing a useful resource in this respect.

Data abstraction

The purpose of data abstraction in rigorous literature reviews is to locate and record all data relevant to the topic of interest from the full text of included publications, making them available for subsequent analysis. Conventionally, a data abstraction form—consisting of numerous distinct conceptually defined fields to which corresponding information from the source publication is recorded—is developed and employed. There are several challenges, however, to the processes of developing the abstraction form and abstracting the data itself when conducting methods overviews, which we address here. Some of these problems and their solutions may be familiar to those who have conducted qualitative literature syntheses, which are similarly conceptual.

Iteratively defining conceptual information to abstract

In the overview on sampling [ 18 ], while we surveyed multiple sources beforehand to develop a list of concepts relevant for abstraction (e.g., purposeful sampling strategies, saturation, sample size), there was no way for us to anticipate some concepts prior to encountering them in the review process. Indeed, in many cases, reviewers are unable to determine the complete set of methods-related concepts that will be the focus of the final review a priori without having systematically reviewed the publications to be included. Thus, defining what information to abstract beforehand may not be feasible.

Principle #5:

Considering the potential impracticality of defining a complete set of relevant methods-related concepts from a body of literature one has not yet systematically read, selecting and defining fields for data abstraction must often be undertaken iteratively. Thus, concepts to be abstracted can be expected to grow and change as data abstraction proceeds.

Strategy #5:

Reviewers can develop an initial form or set of concepts for abstraction purposes according to standard methods (e.g., incorporating expert feedback, pilot testing) and remain attentive to the need to iteratively revise it as concepts are added or modified during the review. Reviewers should document revisions and return to re-abstract data from previously abstracted publications as the new data requirements are determined.

In the sampling overview [ 18 ], we developed and maintained the abstraction form in Microsoft Word. We derived the initial set of abstraction fields from our own knowledge of relevant sampling-related concepts, consultation with local experts, and reviewing a pilot sample of publications. Since the publications in this review included a large proportion of books, the abstraction process often began by flagging the broad sections within a publication containing topic-relevant information for detailed review to identify text to abstract. When reviewing flagged text, the reviewer occasionally encountered an unanticipated concept significant enough to warrant being added as a new field to the abstraction form. For example, a field was added to capture how authors described the timing of sampling decisions, whether before (a priori) or after (ongoing) starting data collection, or whether this was unclear. In these cases, we systematically documented the modification to the form and returned to previously abstracted publications to abstract any information that might be relevant to the new field.

The logic of this strategy is analogous to the logic used in a form of research synthesis called best fit framework synthesis (BFFS) [ 23 – 25 ]. In that method, reviewers initially code evidence using an a priori framework they have selected. When evidence cannot be accommodated by the selected framework, reviewers then develop new themes or concepts from which they construct a new expanded framework. Both the strategy proposed and the BFFS approach to research synthesis are notable for their rigorous and transparent means to adapt a final set of concepts to the content under review.

Accounting for inconsistent terminology

An important complication affecting the abstraction process in methods overviews is that the language used by authors to describe methods-related concepts can easily vary across publications. For example, authors from different qualitative research traditions often use different terms for similar methods-related concepts. Furthermore, as we found in the sampling overview [ 18 ], there may be cases where no identifiable term, phrase, or label for a methods-related concept is used at all, and a description of it is given instead. This can make searching the text for relevant concepts based on keywords unreliable.

Principle #6:

Since accepted terms may not be used consistently to refer to methods concepts, it is necessary to rely on the definitions for concepts, rather than keywords, to identify relevant information in the publication to abstract.

Strategy #6:

An effective means to systematically identify relevant information is to develop and iteratively adjust written definitions for key concepts (corresponding to abstraction fields) that are consistent with and as inclusive of as much of the literature reviewed as possible. Reviewers then seek information that matches these definitions (rather than keywords) when scanning a publication for relevant data to abstract.

In the abstraction process for the sampling overview [ 18 ], we noted the several concepts of interest to the review for which abstraction by keyword was particularly problematic due to inconsistent terminology across publications: sampling , purposeful sampling , sampling strategy , and saturation (for examples, see Additional file 1 , Matrices 3a, 3b, 4). We iteratively developed definitions for these concepts by abstracting text from publications that either provided an explicit definition or from which an implicit definition could be derived, which was recorded in fields dedicated to the concept’s definition. Using a method of constant comparison, we used text from definition fields to inform and modify a centrally maintained definition of the corresponding concept to optimize its fit and inclusiveness with the literature reviewed. Table  1 shows, as an example, the final definition constructed in this way for one of the central concepts of the review, qualitative sampling .

We applied iteratively developed definitions when making decisions about what specific text to abstract for an existing field, which allowed us to abstract concept-relevant data even if no recognized keyword was used. For example, this was the case for the sampling-related concept, saturation , where the relevant text available for abstraction in one publication [ 26 ]—“to continue to collect data until nothing new was being observed or recorded, no matter how long that takes”—was not accompanied by any term or label whatsoever.

This comparative analytic strategy (and our approach to analysis more broadly as described in strategy #7, below) is analogous to the process of reciprocal translation —a technique first introduced for meta-ethnography by Noblit and Hare [ 27 ] that has since been recognized as a common element in a variety of qualitative metasynthesis approaches [ 28 ]. Reciprocal translation, taken broadly, involves making sense of a study’s findings in terms of the findings of the other studies included in the review. In practice, it has been operationalized in different ways. Melendez-Torres and colleagues developed a typology from their review of the metasynthesis literature, describing four overlapping categories of specific operations undertaken in reciprocal translation: visual representation, key paper integration, data reduction and thematic extraction, and line-by-line coding [ 28 ]. The approaches suggested in both strategies #6 and #7, with their emphasis on constant comparison, appear to fall within the line-by-line coding category.

Generating credible and verifiable analytic interpretations

The analysis in a systematic methods overview must support its more general objective, which we suggested above is often to offer clarity and enhance collective understanding regarding a chosen methods topic. In our experience, this involves describing and interpreting the relevant literature in qualitative terms. Furthermore, any interpretative analysis required may entail reaching different levels of abstraction, depending on the more specific objectives of the review. For example, in the overview on sampling [ 18 ], we aimed to produce a comparative analysis of how multiple sampling-related topics were treated differently within and among different qualitative research traditions. To promote credibility of the review, however, not only should one seek a qualitative analytic approach that facilitates reaching varying levels of abstraction but that approach must also ensure that abstract interpretations are supported and justified by the source data and not solely the product of the analyst’s speculative thinking.

Principle #7:

Considering the qualitative nature of the analysis required in systematic methods overviews, it is important to select an analytic method whose interpretations can be verified as being consistent with the literature selected, regardless of the level of abstraction reached.

Strategy #7:

We suggest employing the constant comparative method of analysis [ 29 ] because it supports developing and verifying analytic links to the source data throughout progressively interpretive or abstract levels. In applying this approach, we advise a rigorous approach, documenting how supportive quotes or references to the original texts are carried forward in the successive steps of analysis to allow for easy verification.

The analytic approach used in the methods overview on sampling [ 18 ] comprised four explicit steps, progressing in level of abstraction—data abstraction, matrices, narrative summaries, and final analytic conclusions (Fig.  2 ). While we have positioned data abstraction as the second stage of the generic review process (prior to Analysis), above, we also considered it as an initial step of analysis in the sampling overview for several reasons. First, it involved a process of constant comparisons and iterative decision-making about the fields to add or define during development and modification of the abstraction form, through which we established the range of concepts to be addressed in the review. At the same time, abstraction involved continuous analytic decisions about what textual quotes (ranging in size from short phrases to numerous paragraphs) to record in the fields thus created. This constant comparative process was analogous to open coding in which textual data from publications was compared to conceptual fields (equivalent to codes) or to other instances of data previously abstracted when constructing definitions to optimize their fit with the overall literature as described in strategy #6. Finally, in the data abstraction step, we also recorded our first interpretive thoughts in dedicated fields, providing initial material for the more abstract analytic steps.

Summary of progressive steps of analysis used in the methods overview on sampling [ 18 ]

In the second step of the analysis, we constructed topic-specific matrices , or tables, by copying relevant quotes from abstraction forms into the appropriate cells of matrices (for the complete set of analytic matrices developed in the sampling review, see Additional file 1 (matrices 3 to 10)). Each matrix ranged from one to five pages; row headings, nested three-deep, identified the methodological tradition, author, and publication, respectively; and column headings identified the concepts, which corresponded to abstraction fields. Matrices thus allowed us to make further comparisons across methodological traditions, and between authors within a tradition. In the third step of analysis, we recorded our comparative observations as narrative summaries , in which we used illustrative quotes more sparingly. In the final step, we developed analytic conclusions based on the narrative summaries about the sampling-related concepts within each methodological tradition for which clarity, consistency, or comprehensiveness of the available guidance appeared to be lacking. Higher levels of analysis thus built logically from the lower levels, enabling us to easily verify analytic conclusions by tracing the support for claims by comparing the original text of publications reviewed.

Integrative versus interpretive methods overviews

The analytic product of systematic methods overviews is comparable to qualitative evidence syntheses, since both involve describing and interpreting the relevant literature in qualitative terms. Most qualitative synthesis approaches strive to produce new conceptual understandings that vary in level of interpretation. Dixon-Woods and colleagues [ 30 ] elaborate on a useful distinction, originating from Noblit and Hare [ 27 ], between integrative and interpretive reviews. Integrative reviews focus on summarizing available primary data and involve using largely secure and well defined concepts to do so; definitions are used from an early stage to specify categories for abstraction (or coding) of data, which in turn supports their aggregation; they do not seek as their primary focus to develop or specify new concepts, although they may achieve some theoretical or interpretive functions. For interpretive reviews, meanwhile, the main focus is to develop new concepts and theories that integrate them, with the implication that the concepts developed become fully defined towards the end of the analysis. These two forms are not completely distinct, and “every integrative synthesis will include elements of interpretation, and every interpretive synthesis will include elements of aggregation of data” [ 30 ].

The example methods overview on sampling [ 18 ] could be classified as predominantly integrative because its primary goal was to aggregate influential authors’ ideas on sampling-related concepts; there were also, however, elements of interpretive synthesis since it aimed to develop new ideas about where clarity in guidance on certain sampling-related topics is lacking, and definitions for some concepts were flexible and not fixed until late in the review. We suggest that most systematic methods overviews will be classifiable as predominantly integrative (aggregative). Nevertheless, more highly interpretive methods overviews are also quite possible—for example, when the review objective is to provide a highly critical analysis for the purpose of generating new methodological guidance. In such cases, reviewers may need to sample more deeply (see strategy #4), specifically by selecting empirical research reports (i.e., to go beyond dominant or influential ideas in the methods literature) that are likely to feature innovations or instructive lessons in employing a given method.

In this paper, we have outlined tentative guidance in the form of seven principles and strategies on how to conduct systematic methods overviews, a review type in which methods-relevant literature is systematically analyzed with the aim of offering clarity and enhancing collective understanding regarding a specific methods topic. Our proposals include strategies for delimiting the set of publications to consider, searching beyond standard bibliographic databases, searching without the availability of relevant metadata, selecting publications on purposeful conceptual grounds, defining concepts and other information to abstract iteratively, accounting for inconsistent terminology, and generating credible and verifiable analytic interpretations. We hope the suggestions proposed will be useful to others undertaking reviews on methods topics in future.

As far as we are aware, this is the first published source of concrete guidance for conducting this type of review. It is important to note that our primary objective was to initiate methodological discussion by stimulating reflection on what rigorous methods for this type of review should look like, leaving the development of more complete guidance to future work. While derived from the experience of reviewing a single qualitative methods topic, we believe the principles and strategies provided are generalizable to overviews of both qualitative and quantitative methods topics alike. However, it is expected that additional challenges and insights for conducting such reviews have yet to be defined. Thus, we propose that next steps for developing more definitive guidance should involve an attempt to collect and integrate other reviewers’ perspectives and experiences in conducting systematic methods overviews on a broad range of qualitative and quantitative methods topics. Formalized guidance and standards would improve the quality of future methods overviews, something we believe has important implications for advancing qualitative and quantitative methodology. When undertaken to a high standard, rigorous critical evaluations of the available methods guidance have significant potential to make implicit controversies explicit, and improve the clarity and precision of our understandings of problematic qualitative or quantitative methods issues.

A review process central to most types of rigorous reviews of empirical studies, which we did not explicitly address in a separate review step above, is quality appraisal . The reason we have not treated this as a separate step stems from the different objectives of the primary publications included in overviews of the methods literature (i.e., providing methodological guidance) compared to the primary publications included in the other established review types (i.e., reporting findings from single empirical studies). This is not to say that appraising quality of the methods literature is not an important concern for systematic methods overviews. Rather, appraisal is much more integral to (and difficult to separate from) the analysis step, in which we advocate appraising clarity, consistency, and comprehensiveness—the quality appraisal criteria that we suggest are appropriate for the methods literature. As a second important difference regarding appraisal, we currently advocate appraising the aforementioned aspects at the level of the literature in aggregate rather than at the level of individual publications. One reason for this is that methods guidance from individual publications generally builds on previous literature, and thus we feel that ahistorical judgments about comprehensiveness of single publications lack relevance and utility. Additionally, while different methods authors may express themselves less clearly than others, their guidance can nonetheless be highly influential and useful, and should therefore not be downgraded or ignored based on considerations of clarity—which raises questions about the alternative uses that quality appraisals of individual publications might have. Finally, legitimate variability in the perspectives that methods authors wish to emphasize, and the levels of generality at which they write about methods, makes critiquing individual publications based on the criterion of clarity a complex and potentially problematic endeavor that is beyond the scope of this paper to address. By appraising the current state of the literature at a holistic level, reviewers stand to identify important gaps in understanding that represent valuable opportunities for further methodological development.

To summarize, the principles and strategies provided here may be useful to those seeking to undertake their own systematic methods overview. Additional work is needed, however, to establish guidance that is comprehensive by comparing the experiences from conducting a variety of methods overviews on a range of methods topics. Efforts that further advance standards for systematic methods overviews have the potential to promote high-quality critical evaluations that produce conceptually clear and unified understandings of problematic methods topics, thereby accelerating the advance of research methodology.

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Gentles, S.J., Charles, C., Nicholas, D.B. et al. Reviewing the research methods literature: principles and strategies illustrated by a systematic overview of sampling in qualitative research. Syst Rev 5 , 172 (2016). https://doi.org/10.1186/s13643-016-0343-0

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A Correction to this article was published on 06 May 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

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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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Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

• Qualitative vs. quantitative : Will your data take the form of words or numbers?
• Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
• Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

• For quantitative data, you can use statistical analysis methods to test relationships between variables.
• For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Table of contents

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.

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Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

• From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
• Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

• During an experiment .
• Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Chi square test of independence
• Statistical power
• Descriptive statistics
• Degrees of freedom
• Pearson correlation
• Null hypothesis
• Double-blind study
• Case-control study
• Research ethics
• Data collection
• Hypothesis testing
• Structured interviews

Research bias

• Hawthorne effect
• Unconscious bias
• Recall bias
• Halo effect
• Self-serving bias
• Information bias

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

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

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

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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Functional connectivity changes in the brain of adolescents with internet addiction: A systematic literature review of imaging studies

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation Child and Adolescent Mental Health, Department of Brain Sciences, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom

Roles Conceptualization, Supervision, Validation, Writing – review & editing

* E-mail: [email protected]

Affiliation Behavioural Brain Sciences Unit, Population Policy Practice Programme, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom

• Max L. Y. Chang, 
• Irene O. Lee

• Published: June 4, 2024
• https://doi.org/10.1371/journal.pmen.0000022
• Peer Review
• Reader Comments

Internet usage has seen a stark global rise over the last few decades, particularly among adolescents and young people, who have also been diagnosed increasingly with internet addiction (IA). IA impacts several neural networks that influence an adolescent’s behaviour and development. This article issued a literature review on the resting-state and task-based functional magnetic resonance imaging (fMRI) studies to inspect the consequences of IA on the functional connectivity (FC) in the adolescent brain and its subsequent effects on their behaviour and development. A systematic search was conducted from two databases, PubMed and PsycINFO, to select eligible articles according to the inclusion and exclusion criteria. Eligibility criteria was especially stringent regarding the adolescent age range (10–19) and formal diagnosis of IA. Bias and quality of individual studies were evaluated. The fMRI results from 12 articles demonstrated that the effects of IA were seen throughout multiple neural networks: a mix of increases/decreases in FC in the default mode network; an overall decrease in FC in the executive control network; and no clear increase or decrease in FC within the salience network and reward pathway. The FC changes led to addictive behaviour and tendencies in adolescents. The subsequent behavioural changes are associated with the mechanisms relating to the areas of cognitive control, reward valuation, motor coordination, and the developing adolescent brain. Our results presented the FC alterations in numerous brain regions of adolescents with IA leading to the behavioural and developmental changes. Research on this topic had a low frequency with adolescent samples and were primarily produced in Asian countries. Future research studies of comparing results from Western adolescent samples provide more insight on therapeutic intervention.

Citation: Chang MLY, Lee IO (2024) Functional connectivity changes in the brain of adolescents with internet addiction: A systematic literature review of imaging studies. PLOS Ment Health 1(1): e0000022. https://doi.org/10.1371/journal.pmen.0000022

Editor: Kizito Omona, Uganda Martyrs University, UGANDA

Received: December 29, 2023; Accepted: March 18, 2024; Published: June 4, 2024

Copyright: © 2024 Chang, Lee. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting information files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The behavioural addiction brought on by excessive internet use has become a rising source of concern [ 1 ] since the last decade. According to clinical studies, individuals with Internet Addiction (IA) or Internet Gaming Disorder (IGD) may have a range of biopsychosocial effects and is classified as an impulse-control disorder owing to its resemblance to pathological gambling and substance addiction [ 2 , 3 ]. IA has been defined by researchers as a person’s inability to resist the urge to use the internet, which has negative effects on their psychological well-being as well as their social, academic, and professional lives [ 4 ]. The symptoms can have serious physical and interpersonal repercussions and are linked to mood modification, salience, tolerance, impulsivity, and conflict [ 5 ]. In severe circumstances, people may experience severe pain in their bodies or health issues like carpal tunnel syndrome, dry eyes, irregular eating and disrupted sleep [ 6 ]. Additionally, IA is significantly linked to comorbidities with other psychiatric disorders [ 7 ].

Stevens et al (2021) reviewed 53 studies including 17 countries and reported the global prevalence of IA was 3.05% [ 8 ]. Asian countries had a higher prevalence (5.1%) than European countries (2.7%) [ 8 ]. Strikingly, adolescents and young adults had a global IGD prevalence rate of 9.9% which matches previous literature that reported historically higher prevalence among adolescent populations compared to adults [ 8 , 9 ]. Over 80% of adolescent population in the UK, the USA, and Asia have direct access to the internet [ 10 ]. Children and adolescents frequently spend more time on media (possibly 7 hours and 22 minutes per day) than at school or sleeping [ 11 ]. Developing nations have also shown a sharp rise in teenage internet usage despite having lower internet penetration rates [ 10 ]. Concerns regarding the possible harms that overt internet use could do to adolescents and their development have arisen because of this surge, especially the significant impacts by the COVID-19 pandemic [ 12 ]. The growing prevalence and neurocognitive consequences of IA among adolescents makes this population a vital area of study [ 13 ].

Adolescence is a crucial developmental stage during which people go through significant changes in their biology, cognition, and personalities [ 14 ]. Adolescents’ emotional-behavioural functioning is hyperactivated, which creates risk of psychopathological vulnerability [ 15 ]. In accordance with clinical study results [ 16 ], this emotional hyperactivity is supported by a high level of neuronal plasticity. This plasticity enables teenagers to adapt to the numerous physical and emotional changes that occur during puberty as well as develop communication techniques and gain independence [ 16 ]. However, the strong neuronal plasticity is also associated with risk-taking and sensation seeking [ 17 ] which may lead to IA.

Despite the fact that the precise neuronal mechanisms underlying IA are still largely unclear, functional magnetic resonance imaging (fMRI) method has been used by scientists as an important framework to examine the neuropathological changes occurring in IA, particularly in the form of functional connectivity (FC) [ 18 ]. fMRI research study has shown that IA alters both the functional and structural makeup of the brain [ 3 ].

We hypothesise that IA has widespread neurological alteration effects rather than being limited to a few specific brain regions. Further hypothesis holds that according to these alterations of FC between the brain regions or certain neural networks, adolescents with IA would experience behavioural changes. An investigation of these domains could be useful for creating better procedures and standards as well as minimising the negative effects of overt internet use. This literature review aims to summarise and analyse the evidence of various imaging studies that have investigated the effects of IA on the FC in adolescents. This will be addressed through two research questions:

• How does internet addiction affect the functional connectivity in the adolescent brain?
• How is adolescent behaviour and development impacted by functional connectivity changes due to internet addiction?

The review protocol was conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (see S1 Checklist ).

Search strategy and selection process

A systematic search was conducted up until April 2023 from two sources of database, PubMed and PsycINFO, using a range of terms relevant to the title and research questions (see full list of search terms in S1 Appendix ). All the searched articles can be accessed in the S1 Data . The eligible articles were selected according to the inclusion and exclusion criteria. Inclusion criteria used for the present review were: (i) participants in the studies with clinical diagnosis of IA; (ii) participants between the ages of 10 and 19; (iii) imaging research investigations; (iv) works published between January 2013 and April 2023; (v) written in English language; (vi) peer-reviewed papers and (vii) full text. The numbers of articles excluded due to not meeting the inclusion criteria are shown in Fig 1 . Each study’s title and abstract were screened for eligibility.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pmen.0000022.g001

Quality appraisal

Full texts of all potentially relevant studies were then retrieved and further appraised for eligibility. Furthermore, articles were critically appraised based on the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework to evaluate the individual study for both quality and bias. The subsequent quality levels were then appraised to each article and listed as either low, moderate, or high.

Data collection process

Data that satisfied the inclusion requirements was entered into an excel sheet for data extraction and further selection. An article’s author, publication year, country, age range, participant sample size, sex, area of interest, measures, outcome and article quality were all included in the data extraction spreadsheet. Studies looking at FC, for instance, were grouped, while studies looking at FC in specific area were further divided into sub-groups.

Data synthesis and analysis

Articles were classified according to their location in the brain as well as the network or pathway they were a part of to create a coherent narrative between the selected studies. Conclusions concerning various research trends relevant to particular groupings were drawn from these groupings and subgroupings. To maintain the offered information in a prominent manner, these assertions were entered into the data extraction excel spreadsheet.

With the search performed on the selected databases, 238 articles in total were identified (see Fig 1 ). 15 duplicated articles were eliminated, and another 6 items were removed for various other reasons. Title and abstract screening eliminated 184 articles because they were not in English (number of article, n, = 7), did not include imaging components (n = 47), had adult participants (n = 53), did not have a clinical diagnosis of IA (n = 19), did not address FC in the brain (n = 20), and were published outside the desired timeframe (n = 38). A further 21 papers were eliminated for failing to meet inclusion requirements after the remaining 33 articles underwent full-text eligibility screening. A total of 12 papers were deemed eligible for this review analysis.

Characteristics of the included studies, as depicted in the data extraction sheet in Table 1 provide information of the author(s), publication year, sample size, study location, age range, gender, area of interest, outcome, measures used and quality appraisal. Most of the studies in this review utilised resting state functional magnetic resonance imaging techniques (n = 7), with several studies demonstrating task-based fMRI procedures (n = 3), and the remaining studies utilising whole-brain imaging measures (n = 2). The studies were all conducted in Asiatic countries, specifically coming from China (8), Korea (3), and Indonesia (1). Sample sizes ranged from 12 to 31 participants with most of the imaging studies having comparable sample sizes. Majority of the studies included a mix of male and female participants (n = 8) with several studies having a male only participant pool (n = 3). All except one of the mixed gender studies had a majority male participant pool. One study did not disclose their data on the gender demographics of their experiment. Study years ranged from 2013–2022, with 2 studies in 2013, 3 studies in 2014, 3 studies in 2015, 1 study in 2017, 1 study in 2020, 1 study in 2021, and 1 study in 2022.

https://doi.org/10.1371/journal.pmen.0000022.t001

(1) How does internet addiction affect the functional connectivity in the adolescent brain?

The included studies were organised according to the brain region or network that they were observing. The specific networks affected by IA were the default mode network, executive control system, salience network and reward pathway. These networks are vital components of adolescent behaviour and development [ 31 ]. The studies in each section were then grouped into subsections according to their specific brain regions within their network.

Default mode network (DMN)/reward network.

Out of the 12 studies, 3 have specifically studied the default mode network (DMN), and 3 observed whole-brain FC that partially included components of the DMN. The effect of IA on the various centres of the DMN was not unilaterally the same. The findings illustrate a complex mix of increases and decreases in FC depending on the specific region in the DMN (see Table 2 and Fig 2 ). The alteration of FC in posterior cingulate cortex (PCC) in the DMN was the most frequently reported area in adolescents with IA, which involved in attentional processes [ 32 ], but Lee et al. (2020) additionally found alterations of FC in other brain regions, such as anterior insula cortex, a node in the DMN that controls the integration of motivational and cognitive processes [ 20 ].

https://doi.org/10.1371/journal.pmen.0000022.g002

The overall changes of functional connectivity in the brain network including default mode network (DMN), executive control network (ECN), salience network (SN) and reward network. IA = Internet Addiction, FC = Functional Connectivity.

https://doi.org/10.1371/journal.pmen.0000022.t002

Ding et al. (2013) revealed altered FC in the cerebellum, the middle temporal gyrus, and the medial prefrontal cortex (mPFC) [ 22 ]. They found that the bilateral inferior parietal lobule, left superior parietal lobule, and right inferior temporal gyrus had decreased FC, while the bilateral posterior lobe of the cerebellum and the medial temporal gyrus had increased FC [ 22 ]. The right middle temporal gyrus was found to have 111 cluster voxels (t = 3.52, p<0.05) and the right inferior parietal lobule was found to have 324 cluster voxels (t = -4.07, p<0.05) with an extent threshold of 54 voxels (figures above this threshold are deemed significant) [ 22 ]. Additionally, there was a negative correlation, with 95 cluster voxels (p<0.05) between the FC of the left superior parietal lobule and the PCC with the Chen Internet Addiction Scores (CIAS) which are used to determine the severity of IA [ 22 ]. On the other hand, in regions of the reward system, connection with the PCC was positively connected with CIAS scores [ 22 ]. The most significant was the right praecuneus with 219 cluster voxels (p<0.05) [ 22 ]. Wang et al. (2017) also discovered that adolescents with IA had 33% less FC in the left inferior parietal lobule and 20% less FC in the dorsal mPFC [ 24 ]. A potential connection between the effects of substance use and overt internet use is revealed by the generally decreased FC in these areas of the DMN of teenagers with drug addiction and IA [ 35 ].

The putamen was one of the main regions of reduced FC in adolescents with IA [ 19 ]. The putamen and the insula-operculum demonstrated significant group differences regarding functional connectivity with a cluster size of 251 and an extent threshold of 250 (Z = 3.40, p<0.05) [ 19 ]. The molecular mechanisms behind addiction disorders have been intimately connected to decreased striatal dopaminergic function [ 19 ], making this function crucial.

Executive Control Network (ECN).

5 studies out of 12 have specifically viewed parts of the executive control network (ECN) and 3 studies observed whole-brain FC. The effects of IA on the ECN’s constituent parts were consistent across all the studies examined for this analysis (see Table 2 and Fig 3 ). The results showed a notable decline in all the ECN’s major centres. Li et al. (2014) used fMRI imaging and a behavioural task to study response inhibition in adolescents with IA [ 25 ] and found decreased activation at the striatum and frontal gyrus, particularly a reduction in FC at inferior frontal gyrus, in the IA group compared to controls [ 25 ]. The inferior frontal gyrus showed a reduction in FC in comparison to the controls with a cluster size of 71 (t = 4.18, p<0.05) [ 25 ]. In addition, the frontal-basal ganglia pathways in the adolescents with IA showed little effective connection between areas and increased degrees of response inhibition [ 25 ].

https://doi.org/10.1371/journal.pmen.0000022.g003

Lin et al. (2015) found that adolescents with IA demonstrated disrupted corticostriatal FC compared to controls [ 33 ]. The corticostriatal circuitry experienced decreased connectivity with the caudate, bilateral anterior cingulate cortex (ACC), as well as the striatum and frontal gyrus [ 33 ]. The inferior ventral striatum showed significantly reduced FC with the subcallosal ACC and caudate head with cluster size of 101 (t = -4.64, p<0.05) [ 33 ]. Decreased FC in the caudate implies dysfunction of the corticostriatal-limbic circuitry involved in cognitive and emotional control [ 36 ]. The decrease in FC in both the striatum and frontal gyrus is related to inhibitory control, a common deficit seen with disruptions with the ECN [ 33 ].

The dorsolateral prefrontal cortex (DLPFC), ACC, and right supplementary motor area (SMA) of the prefrontal cortex were all found to have significantly decreased grey matter volume [ 29 ]. In addition, the DLPFC, insula, temporal cortices, as well as significant subcortical regions like the striatum and thalamus, showed decreased FC [ 29 ]. According to Tremblay (2009), the striatum plays a significant role in the processing of rewards, decision-making, and motivation [ 37 ]. Chen et al. (2020) reported that the IA group demonstrated increased impulsivity as well as decreased reaction inhibition using a Stroop colour-word task [ 26 ]. Furthermore, Chen et al. (2020) observed that the left DLPFC and dorsal striatum experienced a negative connection efficiency value, specifically demonstrating that the dorsal striatum activity suppressed the left DLPFC [ 27 ].

Salience network (SN).

Out of the 12 chosen studies, 3 studies specifically looked at the salience network (SN) and 3 studies have observed whole-brain FC. Relative to the DMN and ECN, the findings on the SN were slightly sparser. Despite this, adolescents with IA demonstrated a moderate decrease in FC, as well as other measures like fibre connectivity and cognitive control, when compared to healthy control (see Table 2 and Fig 4 ).

https://doi.org/10.1371/journal.pmen.0000022.g004

Xing et al. (2014) used both dorsal anterior cingulate cortex (dACC) and insula to test FC changes in the SN of adolescents with IA and found decreased structural connectivity in the SN as well as decreased fractional anisotropy (FA) that correlated to behaviour performance in the Stroop colour word-task [ 21 ]. They examined the dACC and insula to determine whether the SN’s disrupted connectivity may be linked to the SN’s disruption of regulation, which would explain the impaired cognitive control seen in adolescents with IA. However, researchers did not find significant FC differences in the SN when compared to the controls [ 21 ]. These results provided evidence for the structural changes in the interconnectivity within SN in adolescents with IA.

Wang et al. (2017) investigated network interactions between the DMN, ECN, SN and reward pathway in IA subjects [ 24 ] (see Fig 5 ), and found 40% reduction of FC between the DMN and specific regions of the SN, such as the insula, in comparison to the controls (p = 0.008) [ 24 ]. The anterior insula and dACC are two areas that are impacted by this altered FC [ 24 ]. This finding supports the idea that IA has similar neurobiological abnormalities with other addictive illnesses, which is in line with a study that discovered disruptive changes in the SN and DMN’s interaction in cocaine addiction [ 38 ]. The insula has also been linked to the intensity of symptoms and has been implicated in the development of IA [ 39 ].

“+” indicates an increase in behaivour; “-”indicates a decrease in behaviour; solid arrows indicate a direct network interaction; and the dotted arrows indicates a reduction in network interaction. This diagram depicts network interactions juxtaposed with engaging in internet related behaviours. Through the neural interactions, the diagram illustrates how the networks inhibit or amplify internet usage and vice versa. Furthermore, it demonstrates how the SN mediates both the DMN and ECN.

https://doi.org/10.1371/journal.pmen.0000022.g005

(2) How is adolescent behaviour and development impacted by functional connectivity changes due to internet addiction?

The findings that IA individuals demonstrate an overall decrease in FC in the DMN is supported by numerous research [ 24 ]. Drug addict populations also exhibited similar decline in FC in the DMN [ 40 ]. The disruption of attentional orientation and self-referential processing for both substance and behavioural addiction was then hypothesised to be caused by DMN anomalies in FC [ 41 ].

In adolescents with IA, decline of FC in the parietal lobule affects visuospatial task-related behaviour [ 22 ], short-term memory [ 42 ], and the ability of controlling attention or restraining motor responses during response inhibition tests [ 42 ]. Cue-induced gaming cravings are influenced by the DMN [ 43 ]. A visual processing area called the praecuneus links gaming cues to internal information [ 22 ]. A meta-analysis found that the posterior cingulate cortex activity of individuals with IA during cue-reactivity tasks was connected with their gaming time [ 44 ], suggesting that excessive gaming may impair DMN function and that individuals with IA exert more cognitive effort to control it. Findings for the behavioural consequences of FC changes in the DMN illustrate its underlying role in regulating impulsivity, self-monitoring, and cognitive control.

Furthermore, Ding et al. (2013) reported an activation of components of the reward pathway, including areas like the nucleus accumbens, praecuneus, SMA, caudate, and thalamus, in connection to the DMN [ 22 ]. The increased FC of the limbic and reward networks have been confirmed to be a major biomarker for IA [ 45 , 46 ]. The increased reinforcement in these networks increases the strength of reward stimuli and makes it more difficult for other networks, namely the ECN, to down-regulate the increased attention [ 29 ] (See Fig 5 ).

Executive control network (ECN).

The numerous IA-affected components in the ECN have a role in a variety of behaviours that are connected to both response inhibition and emotional regulation [ 47 ]. For instance, brain regions like the striatum, which are linked to impulsivity and the reward system, are heavily involved in the act of playing online games [ 47 ]. Online game play activates the striatum, which suppresses the left DLPFC in ECN [ 48 ]. As a result, people with IA may find it difficult to control their want to play online games [ 48 ]. This system thus causes impulsive and protracted gaming conduct, lack of inhibitory control leading to the continued use of internet in an overt manner despite a variety of negative effects, personal distress, and signs of psychological dependence [ 33 ] (See Fig 5 ).

Wang et al. (2017) report that disruptions in cognitive control networks within the ECN are frequently linked to characteristics of substance addiction [ 24 ]. With samples that were addicted to heroin and cocaine, previous studies discovered abnormal FC in the ECN and the PFC [ 49 ]. Electronic gaming is known to promote striatal dopamine release, similar to drug addiction [ 50 ]. According to Drgonova and Walther (2016), it is hypothesised that dopamine could stimulate the reward system of the striatum in the brain, leading to a loss of impulse control and a failure of prefrontal lobe executive inhibitory control [ 51 ]. In the end, IA’s resemblance to drug use disorders may point to vital biomarkers or underlying mechanisms that explain how cognitive control and impulsive behaviour are related.

A task-related fMRI study found that the decrease in FC between the left DLPFC and dorsal striatum was congruent with an increase in impulsivity in adolescents with IA [ 26 ]. The lack of response inhibition from the ECN results in a loss of control over internet usage and a reduced capacity to display goal-directed behaviour [ 33 ]. Previous studies have linked the alteration of the ECN in IA with higher cue reactivity and impaired ability to self-regulate internet specific stimuli [ 52 ].

Salience network (SN)/ other networks.

Xing et al. (2014) investigated the significance of the SN regarding cognitive control in teenagers with IA [ 21 ]. The SN, which is composed of the ACC and insula, has been demonstrated to control dynamic changes in other networks to modify cognitive performance [ 21 ]. The ACC is engaged in conflict monitoring and cognitive control, according to previous neuroimaging research [ 53 ]. The insula is a region that integrates interoceptive states into conscious feelings [ 54 ]. The results from Xing et al. (2014) showed declines in the SN regarding its structural connectivity and fractional anisotropy, even though they did not observe any appreciable change in FC in the IA participants [ 21 ]. Due to the small sample size, the results may have indicated that FC methods are not sensitive enough to detect the significant functional changes [ 21 ]. However, task performance behaviours associated with impaired cognitive control in adolescents with IA were correlated with these findings [ 21 ]. Our comprehension of the SN’s broader function in IA can be enhanced by this relationship.

Research study supports the idea that different psychological issues are caused by the functional reorganisation of expansive brain networks, such that strong association between SN and DMN may provide neurological underpinnings at the system level for the uncontrollable character of internet-using behaviours [ 24 ]. In the study by Wang et al. (2017), the decreased interconnectivity between the SN and DMN, comprising regions such the DLPFC and the insula, suggests that adolescents with IA may struggle to effectively inhibit DMN activity during internally focused processing, leading to poorly managed desires or preoccupations to use the internet [ 24 ] (See Fig 5 ). Subsequently, this may cause a failure to inhibit DMN activity as well as a restriction of ECN functionality [ 55 ]. As a result, the adolescent experiences an increased salience and sensitivity towards internet addicting cues making it difficult to avoid these triggers [ 56 ].

The primary aim of this review was to present a summary of how internet addiction impacts on the functional connectivity of adolescent brain. Subsequently, the influence of IA on the adolescent brain was compartmentalised into three sections: alterations of FC at various brain regions, specific FC relationships, and behavioural/developmental changes. Overall, the specific effects of IA on the adolescent brain were not completely clear, given the variety of FC changes. However, there were overarching behavioural, network and developmental trends that were supported that provided insight on adolescent development.

The first hypothesis that was held about this question was that IA was widespread and would be regionally similar to substance-use and gambling addiction. After conducting a review of the information in the chosen articles, the hypothesis was predictably supported. The regions of the brain affected by IA are widespread and influence multiple networks, mainly DMN, ECN, SN and reward pathway. In the DMN, there was a complex mix of increases and decreases within the network. However, in the ECN, the alterations of FC were more unilaterally decreased, but the findings of SN and reward pathway were not quite clear. Overall, the FC changes within adolescents with IA are very much network specific and lay a solid foundation from which to understand the subsequent behaviour changes that arise from the disorder.

The second hypothesis placed emphasis on the importance of between network interactions and within network interactions in the continuation of IA and the development of its behavioural symptoms. The results from the findings involving the networks, DMN, SN, ECN and reward system, support this hypothesis (see Fig 5 ). Studies confirm the influence of all these neural networks on reward valuation, impulsivity, salience to stimuli, cue reactivity and other changes that alter behaviour towards the internet use. Many of these changes are connected to the inherent nature of the adolescent brain.

There are multiple explanations that underlie the vulnerability of the adolescent brain towards IA related urges. Several of them have to do with the inherent nature and underlying mechanisms of the adolescent brain. Children’s emotional, social, and cognitive capacities grow exponentially during childhood and adolescence [ 57 ]. Early teenagers go through a process called “social reorientation” that is characterised by heightened sensitivity to social cues and peer connections [ 58 ]. Adolescents’ improvements in their social skills coincide with changes in their brains’ anatomical and functional organisation [ 59 ]. Functional hubs exhibit growing connectivity strength [ 60 ], suggesting increased functional integration during development. During this time, the brain’s functional networks change from an anatomically dominant structure to a scattered architecture [ 60 ].

The adolescent brain is very responsive to synaptic reorganisation and experience cues [ 61 ]. As a result, one of the distinguishing traits of the maturation of adolescent brains is the variation in neural network trajectory [ 62 ]. Important weaknesses of the adolescent brain that may explain the neurobiological change brought on by external stimuli are illustrated by features like the functional gaps between networks and the inadequate segregation of networks [ 62 ].

The implications of these findings towards adolescent behaviour are significant. Although the exact changes and mechanisms are not fully clear, the observed changes in functional connectivity have the capacity of influencing several aspects of adolescent development. For example, functional connectivity has been utilised to investigate attachment styles in adolescents [ 63 ]. It was observed that adolescent attachment styles were negatively associated with caudate-prefrontal connectivity, but positively with the putamen-visual area connectivity [ 63 ]. Both named areas were also influenced by the onset of internet addiction, possibly providing a connection between the two. Another study associated neighbourhood/socioeconomic disadvantage with functional connectivity alterations in the DMN and dorsal attention network [ 64 ]. The study also found multivariate brain behaviour relationships between the altered/disadvantaged functional connectivity and mental health and cognition [ 64 ]. This conclusion supports the notion that the functional connectivity alterations observed in IA are associated with specific adolescent behaviours as well as the fact that functional connectivity can be utilised as a platform onto which to compare various neurologic conditions.

Limitations/strengths

There were several limitations that were related to the conduction of the review as well as the data extracted from the articles. Firstly, the study followed a systematic literature review design when analysing the fMRI studies. The data pulled from these imaging studies were namely qualitative and were subject to bias contrasting the quantitative nature of statistical analysis. Components of the study, such as sample sizes, effect sizes, and demographics were not weighted or controlled. The second limitation brought up by a similar review was the lack of a universal consensus of terminology given IA [ 47 ]. Globally, authors writing about this topic use an array of terminology including online gaming addiction, internet addiction, internet gaming disorder, and problematic internet use. Often, authors use multiple terms interchangeably which makes it difficult to depict the subtle similarities and differences between the terms.

Reviewing the explicit limitations in each of the included studies, two major limitations were brought up in many of the articles. One was relating to the cross-sectional nature of the included studies. Due to the inherent qualities of a cross-sectional study, the studies did not provide clear evidence that IA played a causal role towards the development of the adolescent brain. While several biopsychosocial factors mediate these interactions, task-based measures that combine executive functions with imaging results reinforce the assumed connection between the two that is utilised by the papers studying IA. Another limitation regarded the small sample size of the included studies, which averaged to around 20 participants. The small sample size can influence the generalisation of the results as well as the effectiveness of statistical analyses. Ultimately, both included study specific limitations illustrate the need for future studies to clarify the causal relationship between the alterations of FC and the development of IA.

Another vital limitation was the limited number of studies applying imaging techniques for investigations on IA in adolescents were a uniformly Far East collection of studies. The reason for this was because the studies included in this review were the only fMRI studies that were found that adhered to the strict adolescent age restriction. The adolescent age range given by the WHO (10–19 years old) [ 65 ] was strictly followed. It is important to note that a multitude of studies found in the initial search utilised an older adolescent demographic that was slightly higher than the WHO age range and had a mean age that was outside of the limitations. As a result, the results of this review are biased and based on the 12 studies that met the inclusion and exclusion criteria.

Regarding the global nature of the research, although the journals that the studies were published in were all established western journals, the collection of studies were found to all originate from Asian countries, namely China and Korea. Subsequently, it pulls into question if the results and measures from these studies are generalisable towards a western population. As stated previously, Asian countries have a higher prevalence of IA, which may be the reasoning to why the majority of studies are from there [ 8 ]. However, in an additional search including other age groups, it was found that a high majority of all FC studies on IA were done in Asian countries. Interestingly, western papers studying fMRI FC were primarily focused on gambling and substance-use addiction disorders. The western papers on IA were less focused on fMRI FC but more on other components of IA such as sleep, game-genre, and other non-imaging related factors. This demonstrated an overall lack of western fMRI studies on IA. It is important to note that both western and eastern fMRI studies on IA presented an overall lack on children and adolescents in general.

Despite the several limitations, this review provided a clear reflection on the state of the data. The strengths of the review include the strict inclusion/exclusion criteria that filtered through studies and only included ones that contained a purely adolescent sample. As a result, the information presented in this review was specific to the review’s aims. Given the sparse nature of adolescent specific fMRI studies on the FC changes in IA, this review successfully provided a much-needed niche representation of adolescent specific results. Furthermore, the review provided a thorough functional explanation of the DMN, ECN, SN and reward pathway making it accessible to readers new to the topic.

Future directions and implications

Through the search process of the review, there were more imaging studies focused on older adolescence and adulthood. Furthermore, finding a review that covered a strictly adolescent population, focused on FC changes, and was specifically depicting IA, was proven difficult. Many related reviews, such as Tereshchenko and Kasparov (2019), looked at risk factors related to the biopsychosocial model, but did not tackle specific alterations in specific structural or functional changes in the brain [ 66 ]. Weinstein (2017) found similar structural and functional results as well as the role IA has in altering response inhibition and reward valuation in adolescents with IA [ 47 ]. Overall, the accumulated findings only paint an emerging pattern which aligns with similar substance-use and gambling disorders. Future studies require more specificity in depicting the interactions between neural networks, as well as more literature on adolescent and comorbid populations. One future field of interest is the incorporation of more task-based fMRI data. Advances in resting-state fMRI methods have yet to be reflected or confirmed in task-based fMRI methods [ 62 ]. Due to the fact that network connectivity is shaped by different tasks, it is critical to confirm that the findings of the resting state fMRI studies also apply to the task based ones [ 62 ]. Subsequently, work in this area will confirm if intrinsic connectivity networks function in resting state will function similarly during goal directed behaviour [ 62 ]. An elevated focus on adolescent populations as well as task-based fMRI methodology will help uncover to what extent adolescent network connectivity maturation facilitates behavioural and cognitive development [ 62 ].

A treatment implication is the potential usage of bupropion for the treatment of IA. Bupropion has been previously used to treat patients with gambling disorder and has been effective in decreasing overall gambling behaviour as well as money spent while gambling [ 67 ]. Bae et al. (2018) found a decrease in clinical symptoms of IA in line with a 12-week bupropion treatment [ 31 ]. The study found that bupropion altered the FC of both the DMN and ECN which in turn decreased impulsivity and attentional deficits for the individuals with IA [ 31 ]. Interventions like bupropion illustrate the importance of understanding the fundamental mechanisms that underlie disorders like IA.

The goal for this review was to summarise the current literature on functional connectivity changes in adolescents with internet addiction. The findings answered the primary research questions that were directed at FC alterations within several networks of the adolescent brain and how that influenced their behaviour and development. Overall, the research demonstrated several wide-ranging effects that influenced the DMN, SN, ECN, and reward centres. Additionally, the findings gave ground to important details such as the maturation of the adolescent brain, the high prevalence of Asian originated studies, and the importance of task-based studies in this field. The process of making this review allowed for a thorough understanding IA and adolescent brain interactions.

Given the influx of technology and media in the lives and education of children and adolescents, an increase in prevalence and focus on internet related behavioural changes is imperative towards future children/adolescent mental health. Events such as COVID-19 act to expose the consequences of extended internet usage on the development and lifestyle of specifically young people. While it is important for parents and older generations to be wary of these changes, it is important for them to develop a base understanding of the issue and not dismiss it as an all-bad or all-good scenario. Future research on IA will aim to better understand the causal relationship between IA and psychological symptoms that coincide with it. The current literature regarding functional connectivity changes in adolescents is limited and requires future studies to test with larger sample sizes, comorbid populations, and populations outside Far East Asia.

This review aimed to demonstrate the inner workings of how IA alters the connection between the primary behavioural networks in the adolescent brain. Predictably, the present answers merely paint an unfinished picture that does not necessarily depict internet usage as overwhelmingly positive or negative. Alternatively, the research points towards emerging patterns that can direct individuals on the consequences of certain variables or risk factors. A clearer depiction of the mechanisms of IA would allow physicians to screen and treat the onset of IA more effectively. Clinically, this could be in the form of more streamlined and accurate sessions of CBT or family therapy, targeting key symptoms of IA. Alternatively clinicians could potentially prescribe treatment such as bupropion to target FC in certain regions of the brain. Furthermore, parental education on IA is another possible avenue of prevention from a public health standpoint. Parents who are aware of the early signs and onset of IA will more effectively handle screen time, impulsivity, and minimize the risk factors surrounding IA.

Additionally, an increased attention towards internet related fMRI research is needed in the West, as mentioned previously. Despite cultural differences, Western countries may hold similarities to the eastern countries with a high prevalence of IA, like China and Korea, regarding the implications of the internet and IA. The increasing influence of the internet on the world may contribute to an overall increase in the global prevalence of IA. Nonetheless, the high saturation of eastern studies in this field should be replicated with a Western sample to determine if the same FC alterations occur. A growing interest in internet related research and education within the West will hopefully lead to the knowledge of healthier internet habits and coping strategies among parents with children and adolescents. Furthermore, IA research has the potential to become a crucial proxy for which to study adolescent brain maturation and development.

Supporting information

S1 checklist. prisma checklist..

https://doi.org/10.1371/journal.pmen.0000022.s001

S1 Appendix. Search strategies with all the terms.

https://doi.org/10.1371/journal.pmen.0000022.s002

S1 Data. Article screening records with details of categorized content.

https://doi.org/10.1371/journal.pmen.0000022.s003

Acknowledgments

The authors thank https://www.stockio.com/free-clipart/brain-01 (with attribution to Stockio.com); and https://www.rawpixel.com/image/6442258/png-sticker-vintage for the free images used to create Figs 2 – 4 .

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A Comprehensive Guide to Different Types of Research

Updated: June 19, 2024

Published: June 15, 2024

When embarking on a research project, selecting the right methodology can be the difference between success and failure. With various methods available, each suited to different types of research, it’s essential you make an informed choice. This blog post will provide tips on how to choose a research methodology that best fits your research goals .

We’ll start with definitions: Research is the systematic process of exploring, investigating, and discovering new information or validating existing knowledge. It involves defining questions, collecting data, analyzing results, and drawing conclusions.

Meanwhile, a research methodology is a structured plan that outlines how your research is to be conducted. A complete methodology should detail the strategies, processes, and techniques you plan to use for your data collection and analysis.

Research Methods

The first step of a research methodology is to identify a focused research topic, which is the question you seek to answer. By setting clear boundaries on the scope of your research, you can concentrate on specific aspects of a problem without being overwhelmed by information. This will produce more accurate findings. 

Along with clarifying your research topic, your methodology should also address your research methods. Let’s look at the four main types of research: descriptive, correlational, experimental, and diagnostic.

Descriptive Research

Descriptive research is an approach designed to describe the characteristics of a population systematically and accurately. This method focuses on answering “what” questions by providing detailed observations about the subject. Descriptive research employs surveys, observational studies , and case studies to gather qualitative or quantitative data. 

A real-world example of descriptive research is a survey investigating consumer behavior toward a competitor’s product. By analyzing the survey results, the company can gather detailed insights into how consumers perceive a competitor’s product, which can inform their marketing strategies and product development.

Correlational Research

Correlational research examines the statistical relationship between two or more variables to determine whether a relationship exists. Correlational research is particularly useful when ethical or practical constraints prevent experimental manipulation. It is often employed in fields such as psychology, education, and health sciences to provide insights into complex real-world interactions, helping to develop theories and inform further experimental research.

An example of correlational research is the study of the relationship between smoking and lung cancer. Researchers observe and collect data on individuals’ smoking habits and the incidence of lung cancer to determine if there is a correlation between the two variables. This type of research helps identify patterns and relationships, indicating whether increased smoking is associated with higher rates of lung cancer.

Experimental Research

Experimental research is a scientific approach where researchers manipulate one or more independent variables to observe their effect on a dependent variable. This method is designed to establish cause-and-effect relationships. Fields like psychology , medicine, and social sciences frequently employ experimental research to test hypotheses and theories under controlled conditions. 

A real-world example of experimental research is Pavlov’s Dog experiment. In this experiment, Ivan Pavlov demonstrated classical conditioning by ringing a bell each time he fed his dogs. After repeating this process multiple times, the dogs began to salivate just by hearing the bell, even when no food was presented. This experiment helped to illustrate how certain stimuli can elicit specific responses through associative learning.

Diagnostic Research

Diagnostic research tries to accurately diagnose a problem by identifying its underlying causes. This type of research is crucial for understanding complex situations where a precise diagnosis is necessary for formulating effective solutions. It involves methods such as case studies and data analysis and often integrates both qualitative and quantitative data to provide a comprehensive view of the issue at hand. 

An example of diagnostic research is studying the causes of a specific illness outbreak. During an outbreak of a respiratory virus, researchers might conduct diagnostic research to determine the factors contributing to the spread of the virus. This could involve analyzing patient data, testing environmental samples, and evaluating potential sources of infection. The goal is to identify the root causes and contributing factors to develop effective containment and prevention strategies.

Using an established research method is imperative, no matter if you are researching for marketing , technology , healthcare , engineering, or social science. A methodology lends legitimacy to your research by ensuring your data is both consistent and credible. A well-defined methodology also enhances the reliability and validity of the research findings, which is crucial for drawing accurate and meaningful conclusions. 

Additionally, methodologies help researchers stay focused and on track, limiting the scope of the study to relevant questions and objectives. This not only improves the quality of the research but also ensures that the study can be replicated and verified by other researchers, further solidifying its scientific value.

How to Choose a Research Methodology

Choosing the best research methodology for your project involves several key steps to ensure that your approach aligns with your research goals and questions. Here’s a simplified guide to help you make the best choice.

Understand Your Goals

Clearly define the objectives of your research. What do you aim to discover, prove, or understand? Understanding your goals helps in selecting a methodology that aligns with your research purpose.

Consider the Nature of Your Data

Determine whether your research will involve numerical data, textual data, or both. Quantitative methods are best for numerical data, while qualitative methods are suitable for textual or thematic data.

Understand the Purpose of Each Methodology

Becoming familiar with the four types of research – descriptive, correlational, experimental, and diagnostic – will enable you to select the most appropriate method for your research. Many times, you will want to use a combination of methods to gather meaningful data. 

Evaluate Resources and Constraints

Consider the resources available to you, including time, budget, and access to data. Some methodologies may require more resources or longer timeframes to implement effectively.

Review Similar Studies

Look at previous research in your field to see which methodologies were successful. This can provide insights and help you choose a proven approach.

By following these steps, you can select a research methodology that best fits your project’s requirements and ensures robust, credible results.

Completing Your Research Project

Upon completing your research, the next critical step is to analyze and interpret the data you’ve collected. This involves summarizing the key findings, identifying patterns, and determining how these results address your initial research questions. By thoroughly examining the data, you can draw meaningful conclusions that contribute to the body of knowledge in your field. 

It’s essential that you present these findings clearly and concisely, using charts, graphs, and tables to enhance comprehension. Furthermore, discuss the implications of your results, any limitations encountered during the study, and how your findings align with or challenge existing theories.

Your research project should conclude with a strong statement that encapsulates the essence of your research and its broader impact. This final section should leave readers with a clear understanding of the value of your work and inspire continued exploration and discussion in the field.

Now that you know how to perform quality research , it’s time to get started! Applying the right research methodologies can make a significant difference in the accuracy and reliability of your findings. Remember, the key to successful research is not just in collecting data, but in analyzing it thoughtfully and systematically to draw meaningful conclusions. So, dive in, explore, and contribute to the ever-growing body of knowledge with confidence. Happy researching!

At UoPeople, our blog writers are thinkers, researchers, and experts dedicated to curating articles relevant to our mission: making higher education accessible to everyone.

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Methodology for research II

S bala bhaskar.

Department of Anaesthesiology, Vijayanagar Institute Medical Sciences, Bellary, Karnataka, India

M Manjuladevi

1 Department of Anaesthesiology, St. John's Medical College, Bengaluru, Karnataka, India

Research is a systematic process, which uses scientific methods to generate new knowledge that can be used to solve a query or improve on the existing system. Any research on human subjects is associated with varying degree of risk to the participating individual and it is important to safeguard the welfare and rights of the participants. This review focuses on various steps involved in methodology (in continuation with the previous section) before the data are submitted for publication.

INTRODUCTION

Research uses a systematic approach to generate new knowledge to answer questions based on needs of patient health and practice. The investigator identifies research question, examines the ethical implications, describes the research design and collects appropriate data[ 1 , 2 , 3 ] which is evaluated by statistical tests before it can be published.[ 4 ] Before putting this to use in clinical practice, the relevant data are critically appraised for validity and reliability.[ 1 ] This review covers these aspects of the research methodology, in continuation with the first part by Garg et al . published in this issue of Indian Journal of Anaesthesia (IJA).[ 5 ]

REGULATORY AND ETHICAL CONSIDERATIONS

The Indian Council of Medical Research (ICMR) is the apex body in India responsible for the formulation, coordination and promotion of biomedical research. The International Committee of Medical Journal Editors (ICMJE) makes it mandatory for clinical trials to be included in a clinical trials registry for acceptance for publication. Clinical Trials.gov, run by the United States National Library of Medicine, was the first online registry established in 2005 and is widely used today. All trials to be conducted in India should have mandatory prospective registration with the Clinical Trial Registry of India (CTRI- www.ctri.in ). Good clinical practice (GCP) guidelines is a set of guidelines for biomedical studies which encompasses the design, conduct, termination, audit, analysis, reporting and documentation of the studies involving human subjects. It protects rights of human subjects and the authenticity of biomedical data. ( www.cdsco.nic.in/html/GCP1.html ). Table 1 lists the type of the research involved and their regulatory bodies.[ 6 ]

Research involved and their regulatory bodies

The International Standard Randomised Controlled Trial Number (ISRCTN) registry is a primary clinical trial registry recognised by the World Health Organization. The ICMJE provides content validation of all submitted studies (proposed, ongoing or completed). The study is assigned a unique identification number, and records of the study in the database can be easily accessed ( www.isrctn.com ).

To conduct a clinical trial in India, Institution Ethics Committee (IEC) approval is mandatory, and it must be registered with CTRI- www.ctri.nic.in .[ 2 , 6 ] When ‘off-label’ use of a drug (drug being used for a new indication/new dose/formulation/route) is tested for purely academic purposes and not for commercial use, currently there is no requirement of regulator approval.[ 2 , 6 ] However, the IEC has to consider the risks-benefits and ethical basis for approval of the research.

Drugs Controller General of India (DCGI) in India insists on registration and approval of clinical trials through CTRI and ensures scientific and safe conduct of the study. Most of the academic medical centres have Institutional Review Board (IRB) or IEC. They (‘internal’ Ethics Committees) can assess research proposals first and approve before submitting to national bodies. The approval may also go in parallel with DCGI approval. It is responsible for the supervision and protection of rights, safety and welfare of human subjects. During the progress of the trial, the IEC reviews safety reports, any significant violation/deviations in the protocol and for any amendments in the study protocol or informed consent.[ 2 , 7 ]

If IEC is not available in the institution, proposals can be sent independent ethics committee outside the institution (‘external’ Ethics Committees).[ 2 ] The ICMR suggests the establishment of registered Independent Ethics Committees (I nd EC) without institutional affiliation, functioning as per national guidelines. Proposals can also be sent to another institution, following established protocol, including providing a ‘no objection certificate’ and allow the external IEC necessary access.[ 2 ] When there is a large load of research, multiple ECs can function in the same institution as also subcommittees (e.g., subcommittees on adverse event, data safety monitoring, expedited review, etc.,).

The IRB consists of 7–15 members and at least five members are required to form the quorum to make a decision on the research [ Table 2 ].[ 2 ]

Composition of Institution Ethics Committee

All the research involving human participants should follow four basic ethical principles;[ 2 ] (a) Respect for persons autonomy, (b) beneficence (balance the risks against benefits bearing in mind the welfare of the research participant[s]), (c) nonmaleficence (no harm or reduce exposure to greater harm) and (d) Justice (distribution of research subjects equitably in all groups, for example, social, economic demographic, etc).

Informed consent is a process by which a subject confirms his/her willingness to participate in a clinical study.[ 4 ] It protects the individual's freedom of choice and respect for individual's autonomy. It ensures proper regulations in clinical trials and assures patient safety by dealing with both legal and ethical basis.[ 7 ] The process of informed consent consists of providing relevant information, its comprehension and voluntariness.[ 2 ] The details of the clinical study are explained to the subject in a simple and easily understandable language. The ‘subject/participant information sheet’ should include research aspect of the study, sponsor of the study, purpose and procedure, side effects, risks and discomforts, benefits, compensation for any study-related injury, alternatives to participation, right to withdraw, confidentiality of records and contact information of the investigators and IRB.[ 2 , 6 ] The informed and written consent form is duly signed by the subject in a document called ‘informed consent form’.[ 1 , 2 , 3 ] The documents consisting of patient/participant information sheet and informed consent form should be reviewed and approved by the IEC before enrolment of the participants.

A legal authorised representative (LAR) should be involved in the decision-making of vulnerable subjects who lack the ability to consent. The consent is taken from parent/LAR (in kids <7 years) and consent of parent/LAR along with assent form (oral/written) in children aged 7–18 years.[ 2 ] Audio/audio-visual recording of the informed consent process may be required in case of certain regulatory, clinical trials.[ 2 ] After the completion/termination of the study, all records within the IEC must be archived for at least 3 years; those related to regulatory, clinical trials must be archived for 5 years as per CDSCO regulation. Longer preservation may be needed as required by the sponsors/regulatory bodies.

Many finer aspects of the legal and ethical issues in research are discussed by Yip et al in this issue of IJA.[ 8 ]

The ethical duty of confidentiality refers to the obligation of an individual or organisation to safeguard entrusted information of the research data. It is essential for the integrity of the research project and protects information from unauthorised access, use, disclosure, modification, loss or theft.[ 6 , 7 ]

Data related to any of the studies of individual participant can be disclosed only under the following circumstances:

(a) Threat to a person's life, (b) Communication with drug registration authority in cases of severe adverse reaction, (c) Communication to health authority whenever there is risk to public health, (d) In a court of law under the orders of the presiding judge and (e) As a requirement for government agencies or regulatory authorities.[ 2 ]

DATA COLLECTION

‘Data’ includes the information that is systematically collected by the investigator during the study. The primary data are those which are originally done for the first time. The secondary data are a compilation of information done by someone else and have already been passed through the statistical process. A Data Monitoring Committee or Data and Safety Monitoring Board may be appointed, independent of IEC for interim analysis; their report forms the basis for early termination of planned study when there is compelling evidence of beneficial effectiveness or harmful side effects or for major flaws in the study.

The two main types of data are qualitative and quantitative, and most studies will have a combination of both. While quantitative data are easy to analyse and fairly reliable, qualitative data provide more depth in the description of the sample.[ 9 ]

Data collection methods [ Figure 1 ]:

Methods of data collection

• Interview: This method allows face to face contact with respondents, exploring the topic in depth. It allows the interviewer to explain or help to clarify questions increasing the usefulness of a response. It can be of different types-structured, unstructured (informal, conversational approach), semi-structured, focused and standardised.[ 9 , 10 , 11 ] There can be disadvantages-interviewer clarifications can lead to inconsistencies and influence the responses; the subject may distort information through recall error, selective perceptions and in the desire to please the interviewer.[ 10 ] Sometimes, the data may be too voluminous to record or reduce it
• Observation: This method provides direct information about the behaviour of individuals and groups. It allows the investigator to understand the situation and context. It could be ‘Participant’ observation: The observer takes part in the situation he or she observes or ‘Nonparticipant’ observation: The observer watches the situation, openly or concealed, but does not participate[ 9 , 10 , 11 ]
• Questionnaire: It is a simple and inexpensive method not even requiring any research assistants. More honest responses may be available when anonymity is provided. Written questions are presented that are to be answered by the respondents. A written questionnaire can be administered in different ways, such as by sending questionnaires by mail with clear instructions on how to answer the questions and asking for mailed responses; gathering all or part of the respondents in one place at one time, giving oral or written instructions, and letting the respondents fill out the questionnaires; or hand-delivering questionnaires to respondents and collecting them later.[ 10 , 11 ] The disadvantage of this method are observer bias and breach in confidentiality; also, this cannot be used on illiterate subjects. As with other types of outcome measurements, questionnaires and interviews are to be assessed for validity (accuracy) and for reproducibility (precision)-using ‘face validity, content validity and construct validity’
• Documents: It is an inexpensive and unobtrusive method of data collection from locally available records or documents (existing research, hospital records, databases, videotapes, etc.).[ 9 , 10 , 11 ] There is disadvantage of accuracy, authenticity and availability (missing data/omission of needed data). Anaesthesia information management systems used in modern practice have the ability to collect data automatically, in large volumes, which can be converted for specific, focused outcome assessments for research purposes.

Compilation of data includes systematic arrangement of data to facilitate the presentation and analysis.[ 12 ] The data collected are entered in a database where the information about subjects and variables are stored. Simple study database can be maintained in a spreadsheet (MS Excel © ) or statistical software (e.g., Statistical Analysis System (SAS ® ) (NC, USA), IBM SPSS (Statistical Package for the Social Sciences) Statistics ® (IBM Inc., NY, USA). More complex database require integrated database management software (e.g., Access © (Windows) and Filemaker © Pro (Apple Inc.,).[ 13 ] Database ‘queries’ sort and filter the data as well as calculate values based on the raw data fields.[ 12 , 13 ] Queries are used to monitor data entry, report on study progress and format the results for analysis. Data must be stored in ‘secure servers’ so that confidentiality is maintained.[ 13 ] Backup files and off-site storage may be necessary to prevent any data loss. Common methods of summarising and presenting data are tables, pie charts, bar charts, histograms, frequency and cumulative frequency curves, dot plots and x-y scatterplots.[ 13 , 14 , 15 ]

RESEARCH TOOLS: DEVELOPMENT AND VALIDATION

‘Research tool’ is the means of collecting information for the purpose of a study. Observation forms, interview schedules, questionnaires are all classified as research tools. The first practical step in doing a research process is to construct a research tool. Four stage process is involved in developing a research tool.[ 9 , 10 , 11 , 12 ]

• Concept development: The researcher should understand the basic knowledge pertaining to the study
• Specification of concept dimensions: The researcher should be able to build in a dimension based on the concept of the study
• Selection of indicators: Once the concept and its dimensions are developed, each concept element is measured by indicators (respondent's knowledge, opinion, expectation, etc., are measured with scales, devices). More than one indicator increases the score and validity of the study
• Formation of index: Dimension of a concept or different measurements of a dimension are then put into an overall index.

The error may occur at any stage of research, i.e., from selection to interpretation of data to conclusion. Two types of error can occur – random and systematic error. The random error must be reduced as far as possible, and the systemic error should be eliminated. Errors can occur from three sources:[ 16 , 17 , 18 , 19 ]

• Investigator: Due to ignorance, incompetence and bias
• Instrument: Due to variability, calibration, problems and malfunctioning
• Subject: Due to bias, noncompliance and biological variation in response.

Any research can be affected by factors that can invalidate the findings. A good research tool should meet the tests of validity, reliability and practicality.

Validity refers to the extent to which a test measures what we actually wish to measure. Reliability refers to accuracy and precision of a measurement procedure.

The practicality characteristic of a measuring instrument can be judged in terms of economy, convenience and interpretability.

Determining validity can be viewed as constructing an evidence-based argument regarding how well a tool measures what it is supposed to do.

USES OF VALIDITY IN SCIENTIFIC METHODS

External validity refers to generalising the study results to other population groups with similar risk factors, settings, measurement and treatment variables.

Internal validity implies that the differences observed between the treatment groups, apart from random error, are only due to the treatments under investigation.[ 9 ]

Validity assessment can be performed in three ways:

• Content validity is the extent to which a measuring tool provides adequate coverage of all the aspects of the topic under study. (e.g., quality of pain relief to include measurement of analgesia, haemodynamics, sedation, etc.). ‘Face validity’ assesses whether the measurements appear reasonable; a measure of how representative a research project is ‘at face value’, and whether it appears to be a good project
• Construct validity refers to the degree to which a measurement conforms to theoretical constructs. Convergent validity tests whether and how well those ‘constructs’ that are expected to be related are, in fact, related. Discriminant validity or divergent validity tests those ‘constructs’ that should have no relationship do, in fact, not have any relationship
• Criterion validity assesses the degree to which a new measurement correlates with well-accepted existing measures. Predictive validity is a strong variety of criterion validity, representing the ability of the measurement to predict an outcome.

Other Types: Concurrent validity refers to the degree of correlation of two measures of the same concept administered at the same time. Consensual validity is a process by which a panel of experts judge the validity.[ 1 , 16 , 17 , 18 , 19 ]

A measuring instrument is reliable if it provides consistent results.[ 1 , 11 ]

The stability aspect refers to securing consistent results with repeated measurements of the same person and with the same instrument. Determination of the degree of stability by comparing the results of repeated measurements.

The equivalence aspect considers how much error may get introduced by different investigators or different samples of the items being studied.

PRACTICALITY

Measuring instrument practicality is tested in terms of economy, convenience and interpretability.

Economy consideration suggests that some trade-off is needed between the ideal research project and that which the budget can afford.

Convenience test suggests that the measuring instrument should be easy to administer. Interpretability consideration is especially important when persons other than the designers of the test are to interpret the results.

ANALYSIS PLAN: QUALITY AND APPROPRIATENESS OF ANALYSIS

The statistics in research functions as a tool in designing research, analysing its data and drawing conclusions from it.[ 20 , 21 ] Descriptive statistics are the development of certain indices from the raw data, summarised in tables, charts or numerical forms. The inferential analysis is undertaken to apply various tests of significance to test hypotheses of a research question so as to validate conclusions. An essential part of presenting any type of inferential data is by probability ( P value) which reassures the reader that the outcome was secondary to the effect of the studied variable and has not occurred purely by chance.[ 22 ] P < 5% is considered statistically significant. Statistical tests are used for testing the significance. Various parametric tests (variable normally distributed) and nonparametric tests (variables are not normally distributed) are used to meet the objective of the study [ Table 3 ].[ 19 , 20 ] ‘Basic Statistical Tools in Research and Data analysis’ in this issue of IJA by Zulfiqar Ali describe these tests in detail.[ 23 ]

Tests of significance

The ‘methodology’ in a research strategy outlines the steps involved in research process. The research problem is identified, aims and objectives are formulated, sample size is calculated; Ethics Committee approval and informed consent from the subject are taken; data collected are summarised. The research design is planned, and the collected data are then analysed using appropriate statistical tests. The derived evidence is put into clinical practice once the reader is convinced that the clinical study is valid and reliable.

Financial support and sponsorship

Conflicts of interest.

There are no conflicts of interest.