1. Introduction - what is going to discuss, questionnaire, this about 500 words not more than that2. Main body - Difference between quantitative and qualitative research - Data collection - interviews
Management Research:
Research Title: Journal of Mixed Methods Research (JMMR):
Abstract:
Although in the last 25 years the methodology of mixed research (also known as mixed methods research) has developed substantially, there are still many vocal critics at both ends of the methodological spectrum (i.e., at the extreme quantitative and qualitative ends). Some of these critics attempt to continue the paradigm wars. Yet, as a collection of research communities, what is needed is mutual respect among all researchers, regardless of epistemological orientation.
Mixed researchers can play an important role in promoting this mutual respect. However, it is not enough for mixed methodology researchers to exist in an epistemological space that lies somewhere between the quantitative and qualitative epistemological spaces. Rather, mixed researchers should strive for what is the radical middle, which should not be a passive and comfortable middle space wherein the status quo among quantitative and qualitative epistemologies is maintained, but rather a new theoretical and methodological space in which a socially just and productive coexistence among all research traditions is actively promoted, and in which mixed research is consciously local, dynamic, interactive, situated, contingent, fluid, strategic, and generative. In this editorial, research will identify mental models that problematize the current methodological divide. In so doing, research contends that moving toward the radical middle represents an important step in uniting research communities. In this research will challenge mixed researchers to guide researchers from other communities toward a more constructivist view of epistemological spaces. To this end the research will outline five themes – represented by the acronym MIXED – for promoting the radical middle.
Keywords:
Mixed methods research, mixed methods; triangulation, quantitative research, qualitative research, critically identify and explore the range of issues, controversies surrounding triangulation.
Introduction:
Mixed methods research is defined as research in which the investigator collects and analyzes data, integrates the findings, and draws inferences using both qualitative and quantitative approaches or methods in a single study or program of inquiry.
The Journal of Mixed Methods Research (JMMR) is an innovative, quarterly, international publication that focuses on empirical, methodological, and theoretical articles about mixed methods research across the social, behavioral, health, and human sciences.
Over the past 20 years, there has been increasing recognition that focusing on either quantitative or qualitative research techniques alone leads researchers to miss important parts of a story.
Researchers have found that better results are often achieved through combined approaches. In line with this observation, an increase in so-called mixed methods studies and research designs as well as in work providing overviews and systematic accounts of such research has been witnessed in various disciplines and fields of study since the early 1990s (Morse 1991; Creswell 1994; Greene/Caracelli 1997; Tashakkori/Teddlie 2003; Axinn/Pearce 2006; Bryman 2006; Creswell/Plano Clark 2007; Bergman 2008; Teddlie/Tashakkori 2008).
Of course, the combination of different methodical approaches is anything but a recent phenomenon in field research – one might think of the Marienthal study (Jahoda et al 1933), the Hawthorne studies (Roethlisberger/Dickson 1939), as well as of several studies by the Chicago School. In many areas of research, the combined application of different methods goes back a long time without being explicitly referred to as a mixed methods design2.
However, the increased interest in and the systematic review of mixed methods designs and the results they yield are indeed new aspects in this development.
This interest in mixed methods designs can probably be explained in that their bringing together the strengths of both quantitative and qualitative strategies holds the promise of compensating the respective weaknesses of both approaches.
In view of the usually small sample sizes, so called qualitative (or interpretive, less standardized) research faces criticism for an allegedly arbitrary selection of samples and a lack of representativity, which in turn is said to raise questions as to the generalizability of results and to cause difficulties in the systematic comparison of cases and testing of causal models.
Skepticism towards so-called quantitative research, on the other hand, is mainly voiced with respect to its apparent neglect of the particular social context in which actors attribute meaning to their actions and to its potentially lower sensitivity to new, unexplored, or marginal social phenomena and developments.
Mixed methods designs attempt at engaging quantitative and qualitative research strategies in an intelligent dialogue that benefits both sides.
In their definition of mixed methods, Johnson et al. aptly describe the aim and motivation underlying the mixed method approach: “Mixed methods research is the type of research in which a researcher or team of researchers combines elements of qualitative and quantitative approaches (e.g., use of qualitative and quantitative viewpoints, data collection, analysis, inference techniques) for the purpose of breadth and depth of understanding and corroboration” a wide range of different approaches fall within this definition.
It seems safe to say that their definition represents the smallest common denominator of a variety of different definitions used to describe mixed methods.
The various definitions offered by Johnson et al.‘s respondents, which give a quite accurate picture of the definitions also found in the literature, can be distinguished as to what precisely is combined (methods, methodologies, or types of research), at what stages of the research process methods are combined (formulation of the research question, data collection, data analysis, data interpretation or inference), and to what end methods are combined (e.g., to achieve breadth or for corroboration or triangulation).
In any case, when we speak of combining approaches, this refers to more than a simple process of mere addition. As Creswell et al. put it, “A mixed methods study involves the collection or analysis of both quantitative and/or qualitative data in a single study in which the data are collected concurrently or sequentially, are given a priority, and involve the integration of the data at one or more stages in the process” (Creswell et al. 2003: 212; emphasis added by BH). Instead of simple addition, the task is to systematically relate quantitative and qualitative strategies or data at at least one stage of the research process.
Due to this systematic integration of qualitative and quantitative strategies, mixed methods designs create special opportunities for improving data quality, qualitative data. In reviewing network research, we notice that there has been no systematic consideration of mixed methods studies so far, neither with regard to possible research designs nor their potential for the study of social networks. Although there is a significant number of network studies that combine qualitative and quantitative methods of data collection and analysis.
The present volume shall contribute to this end as it is the first systematic overview on the use of mixed methods for investigating social networks. We will present different ways of mixing qualitative and quantitative strategies and discuss the challenges and
Benefits for research on social networks. The articles assembled in this book illustrate that the application of such designs can improve the quality of data and enhance the explanatory power and generalizability of results. Moreover, with respect to social network research, mixed methods studies promise to provide empirically sound contributions to current issues, especially concerning the processes, dynamics and consequences of social networks. We will take a closer look at these issues later on. Before we do so, we will first give a brief overview of the objects, questions, and approaches of network research. We must also clarify what the terms “quantitative,” “qualitative,” and “mixed methods” actually mean in the context of social networks.
Critically Explore By Mixed Methods Research:
Original mixed methods research that fits the definition of mixed methods research; explicitly integrates the quantitative and qualitative aspects of the study; adds to the literature on mixed methods research; and makes a contribution to a substantive area in the scholar’s field of inquiry; and
Methodological/theoretical topics that advance knowledge about mixed methods research, such as:
Type of research/evaluation questions
Types of designs
Sampling and/or measurement procedures
Approaches to data analysis
Validity
Software applications
Paradigm stance
Writing structures
The value and use of mixed methods research:
Not only does JMMR offer original mixed methods research and methodological/theoretical discussions, it also includes insightful reflections by the distinguished editors on important issues in mixed methods research and extensive book and software reviews with practical applications.
The Journal of Mixed Methods Research's scope includes
Explore terminology and nomenclature used in mixed methods research
Providing a forum for discussion of parameters effecting mixed methods research
Creating the paradigmatic and philosophical foundations for mixed methods research
Illuminating design and procedure issues
Determining the logistics of conducting mixed methods research
Let us now turn to the question of how network research can be positioned in relation to both quantitative and qualitative methods and what “mixed methods” means precisely in social network research.
Clearly positioning network research in the spectrum of empirical methods is no easy task if we rely on the common systems for the classification of methodology offered in the literature. Or in the words of Peter Carrington, “Social network analysis itself is neither quantitative nor qualitative, nor a combination of the two.
Like qualitative methods, network research places special emphasis on the contextuality or “embeddedness” of social action. Yet unlike qualitative methods, network research employs established standardized instruments to this end, and network structures are typically described in terms of measured values and numbers, thus in a formalized or quantified manner.
Nevertheless, the concept of representativity can usually not be applied to network studies – at least not without some restrictions. That, of course, rules out the use of inferential statistics, and reliable statements on the prevalence of networks and network structures can only be made to a limited extent.
We also have to consider that we are often dealing with relatively small sample sizes, especially in case of investigating whole networks. In the following, we distinguish quantitative and qualitative network data and quantitative and qualitative strategies of network analysis.
In line with a commonly made distinction, we understand by quantitative data numerical data and by qualitative data in text form (cf. Bernard 1994). Accordingly, what we call quantitative network data refers to all data describing relations, interactions, and structures of networks in formal terms using numbers (e.g., the number of relationships between the members of a network).
We speak of qualitative network data when aspects of networks are described in text form (e.g., when actors explain the strategies of action adopted vis-à-vis other members of a network). Quantitative strategies of analysis are defined as strategies of data analysis to describe in quantitative terms empirical regularities, the frequency and prevalence of social phenomena, as well as causal mechanisms and processes.
The basic strategies of data analysis consist of descriptive measures, statistical methods, and path or causal models. More recently, we also observe an increasing trend towards computer simulations. In network research, quantitative methods are geared toward mathematical descriptions and analyses of interactions, relations, and network structures.
Measured values and numbers, for instance, are density and centrality measures or the triad census (e.g., Gluesing et al., this volume). More sophisticated analyses apply formal models and statistical procedures, such as block model analysis, exponential random graph models, or regression analysis (cf. Wasserman/Faust 1994; Carrington/Scott/ Wasserman 2005; Scott/Carrington 2011). In this sense, we consider most of the methods used in social network analysis to be “quantitative.”
Triangulation of mixed methods research:
Triangulation is a measurement technique often used by surveyors to locate an object in space by relying on two known points in order to “triangulate” on an unknown fixed point in that same space. Early on, social scientists borrowed the concept of triangulation to argue for its use in the validation process in assessing the veracity of social science research results. There are alternative perspectives on the use of triangulation that argue for its usefulness as a “dialectical” process whose goals seek a more in-depth nuanced understanding of research findings and clarifying disparate results by placing them in dialogue with one another. This special issue of the Journal of Mixed Methods Research (JMMR) analyzes and explores the variety of ways triangulation is used in mixed methods research and the range of issues and controversies surrounding triangulation praxis.
To date, there are few scholarly in-depth discussions of its deployment in mixed methods research. The choice of triangulation as the topic for this first special issue of JMMR is based on the claims made by many scholars in the field that triangulation provides a justification for the use of mixed methods. The contributors to this volume raise many questions about the meaning of triangulation, its philosophical positioning in the mixed methods community, and strategies for using triangulation in the design of mixed methods studies, analysis and interpretation of data, and making visible subjugated voices.
They take provocative positions, suggesting that qualitative, constructivist, and interpretive pathways provide greater potential for research to address the social good than has been possible using mixed methods approaches that are more closely aligned with the post positivist paradigm.
They revisit the “paradigm wars” and ask this question: Are we still stuck with the incompatibility thesis that paralyzed advances in mixed methods in past decades? They explore and critique the potential of alternative methodologies for harnessing the synergy that is said to lie in the application of mixed methods research designs by asking another set of questions.
Have members of the mixed methods community done an injustice to pragmatism as a philosophical frame for mixed methods? Is qualitatively framed mixed methods the way forward? Is it possible that qualitatively framed mixed methods are better suited to the ability of mixed methods researchers to demonstrate a causal relationship between variables? How and when should triangulation be brought into mixed methods research to obtain a more nuanced understanding of the phenomenon we study, especially as that applies to the experiences of women and members of other marginalized groups? These are some of the intriguing questions raised in this special issue, which we hope will contribute to an on-going rich conversation in the mixed methods research community.
Published by Routledge
6 issues per year
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From this chapter, readers should obtain:
a current understanding of the field of mixed methods research that has developed, especially within the last 7 years;
a view of varied perspectives on the essence of mixed methods, its definitions, and the language that has developed about the field;
an overview of the current discussion about the philosophical assumptions and theoretical lenses used in mixed methods research;
a perspective about the emerging detailed procedures for conducting mixed methods; and
knowledge about recent developments in the field of mixed methods, including disciplinary, international, and funding initiatives.
Issues and controversies surrounding triangulation:
The idea for a text on issues and controversies surrounding Posttraumatic Stress Disorder originated at the 2002 annual conference of the Association for Advancement of behavior Therapy.
Throughout the development of this book, Richard McNally provided invaluable guidance and support for which I am deeply grateful.
I think Chris Frueh for switching roles and serving as editor on the chapter authored. Finally. I extend my sincere gratitude, to the authors who contributed their expertise, insights, and considerable expenditures of time, to make this text possible.
There are no universally accepted definitions for the captioned condition, but investigators seem to agree that it involves problematic computer usage that is time-consuming and causes distress or impairs functioning in important life domains.
Several aetiological models have been proposed, from the diverse perspectives of learning theory, cognitive behavioural theory, social learning, reward deficiency, culture, genetics and neurobiology.
Controversies abound, ranging from conceptual (whether behavioural addictions are true addictions), technical (which component of Internet use is a person 'addicted' to), and practical (how should Internet addiction be diagnosed, if it exists at all).
However, using various instruments and populations, Internet addiction has been suggested as having a prevalence of 0.3 to 38%, with a young male preponderance. Several screening, diagnostic, and severity assessment instruments are now available, but few have been subjected to rigorous psychometric testing.
Psychiatric co-morbidity is common. Treatment modalities lack a firm evidence base, but antidepressants, mood stabilisers, and cognitive behavioural therapy and other psychotherapies have been used.
Recently, the American Psychiatric Association recommended including Internet addiction in its forthcoming 5th edition of the Diagnostic and Statistical Manual of Mental Disorders, but only as an appendix and not in the main body of the addictive disorders. This appears to be a fairly balanced and cautious approach, which can hopefully give rise to more meaningful research in this important but controversial area.
The controversy concerning the value of qualitative, quantitative and triangulation approaches to nursing research for understanding human behaviour and increasing nursing knowledge has been an increasing source of debate among nurse scholars. However, the differences and similarities of these three perspectives have not been fully compared as either philosophies or methodologies. The purposes of this paper are to provide an understanding of the origin and development of the triangulation research method, clarify major sources of confusion in the presentation of a triangulation study, and discuss the problems and possible solutions of a triangulation study.
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