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3 Research Approaches in Applied Linguistics

Patricia Duff is professor of language and literacy education and Distinguished University Scholar at the University of British Columbia. She is also director of the newly established Centre for Research in Chinese Language and Literacy Education there. Her main areas of interest are language acquisition and language socialization, qualitative research methods, classroom discourse in a variety of educational contexts, including second/foreign language courses, mainstream and L2-immersion content-based courses, and the teaching, learning, and use of English and Chinese as international languages. Her recent work includes three books and many book chapters and articles primarily dealing with language socialization across bilingual and multilingual settings; quantitative research methods (especially employing case study and ethnography) and generalizability in applied linguistics; issues in teaching and learning English, Mandarin and other international languages; the integration of second-language learners in high schools, universities and society; multilingualism at work; and sociocultural sociolinguistics and sociopolitical aspects of language(s) in education. She can be reached at http://[email protected].

• Published: 18 September 2012
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In a field as vast as applied linguistics (AL), representing the range of topics featured in this volume and across the many fascinating subdisciplines in the field, an overview of research approaches must be highly selective. This revised and updated article discusses recent quantitative, qualitative, and mixed-method approaches to AL research, especially in the areas of second language learning and education. It also highlights important new ways of conceptualizing, analyzing, and/or representing knowledge about language issues and at the same time embracing new contexts of language learning and use and a wider range of research populations in the twenty-first century. This article further discuses the various research approaches involved in applied linguistics. Contrasting, combining, and expanding paradigms all are taken into consideration and explained in details. Quantitative research is often associated with experiments, surveys, and other research, whereas qualitative research is associated with ethnography, case study, and narrative inquiry in applied linguistics

Introduction

In a field as vast as applied linguistics (AL), representing the range of topics featured in this volume and across the many fascinating subdisciplines in the field, an overview of research approaches must be highly selective. Duff ( 2002a ) described many of the developments in research approaches in AL in the 1990s and early 2000s. In this revised and updated chapter, I discuss recent quantitative, qualitative, and mixed-method approaches to AL research, especially in the areas of second language learning and education. I also highlight important new ways of conceptualizing, analyzing, and/or representing knowledge about language issues and at the same time embracing new contexts of language learning and use and a wider range of research populations in the twenty-first century.

More comprehensive and in-depth recent discussions of research methods in AL can be found in recent volumes by Dörnyei 2007 ), King and Hornberger 2008 ), A. Mackey and Gass 2005 ), and Wei and Moyer 2007 ), with respect to second-language acquisition (SLA), bilingualism, and language education in particular. Many other publications have highlighted specific analytical approaches or methods for conducting research, typically within a particular realm of AL, such as the following:

L2 classroom research and classroom-based discourse analysis (McKay, 2006 ; Zuengler and Mori, 2002 )

Ethnomethodology and conversation analysis (Markee, 2000 , 2004 ; Seedhouse, 2004 )

Case study research (Duff, 2008 )

Corpus linguistics (Barlow, 2005 ; Biber, Conrad, and Reppen, 1998 ; Myles, 2005 ; Gries, 2008 )

Ethnography (Duff, 2002b ; Hammersley and Atkinson, 2007 ; Toohey, 2008 )

Language analysis (R. Ellis and Barkhuizen, 2005 )

Stimulated recall (Gass and Mackey, 2000 )

Data elicitation methods (Gass and Mackey, 2007a )

Discourse analysis and critical discourse analysis (Fairclough, 1989 , 2003 ; Wooffitt, 2005 )

Critical applied linguistics more generally (Pennycook, 2001 )

Multimodal semiotic analysis (Kress and Van Leeuwen, 2002 )

Complex systems approaches (Larsen-Freeman and Cameron, 2008a , 2008b )

Survey methods (C. Baker, 2008 )

Scholars have also given careful consideration to the processes of drawing inferences or making generalizations in applied linguistics research:

Across a variety of types of research (Chalhoub-Deville, Chapelle, and Duff, 2006 )

To meta-analysis and other important approaches to research synthesis regardless of paradigm (Norris and Ortega, 2006a , 2006b , 2007 )

To the benefits of longitudinal research (Ortega and Byrnes, 2008 ; Ortega and Iberri-Shea, 2005 )

J. D. Brown ( 2004 ) produced a recent overview chapter on the theme of research approaches in AL in another handbook in applied linguistics, and Hinkel's ( 2005 ) Handbook also reflects the current range of approaches to second-language/AL research. Finally, a number of journals and handbooks are also dedicated to such particular research methods or approaches as critical discourse analysis or narrative research. In addition, the recently revised 10-volume Springer Encyclopedia of Language and Education contains many chapters on current or emerging approaches to research in language and education.

Research Approaches: Contrasting, Combining, and Expanding Paradigms

Most research methodology textbooks in education and the social sciences (e.g., Cresswell, 2005 ; J. P. Gall, M. D. Gall, and Borg, 2005 ; M. D. Gall, J. P. Gall, & Borg, 2003 ), as well as in some of the AL overview textbooks referred to above, continue to distinguish between quantitative (nomothetic) and qualitative (hermeneutic) research, as two distinct but by no means mutually exclusive approaches to systematic and rigorous inquiry in the social sciences. They also emphasize that the approach or method is crucially linked to the kind of research question or problem under investigation, to the purpose of the study (e.g., exploratory, interpretive, descriptive, explanatory, confirmatory, predictive), and to the type of data and population one is working with. Quantitative research is often associated with experiments, surveys, and other research with large samples of people or observations, whereas qualitative research is associated with ethnography, case study, and narrative inquiry, often with a smaller number of participants but fuller and more holistic accounts from (or of) each one. However, each paradigm actually represents a collection of approaches to research that share some common principles but at the same time reflect major differences.

Any research paradigm or approach reflects a number of components:

A philosophical basis or belief system regarding epistemology, or the nature of truth and of knowing (e.g., that research is ideally objective, unbiased, and value free versus more subjective)

An ideology concerning ontology, or the nature of reality (e.g., that an objective reality exists, or that reality is constructed socially and multiple perspectives on reality exist)

A corresponding methodology (e.g., one that is experimental/manipulative and hypothesis testing, or is not) with various designs, methods, techniques, and devices for eliciting and analyzing phenomena (Denzin and Lincoln, 2005a , 2005b ; Duff, 2008 )

Therefore, there are many levels at which research can be analyzed and categorized. Comparison and categorization in AL has traditionally been based primarily on methods or techniques, with less reflection on epistemological and ontological issues. Quantitative approaches tend to be associated with a positivist or postpositivist orientation, a realist ontology, an objectivist epistemology, and an experimental, manipulative methodology. Qualitative approaches, on the other hand, are more often associated with an interpretive, humanistic orientation, an ontology of multiple realities, a nonobjectivist epistemology and a naturalistic, nonmanipulative methodology (Guba and Lincoln, 1994 ). However, what is ostensibly quantitative research may involve qualitative analysis (e.g., discourse analysis) and vice versa. Case study, for example, normally considered qualitative research, may actually reflect a more positivist approach than an interpretive one, or it may be part of a quantitative one-shot (experimental) case study or a single- or multiple-case time series design (Duff, 2008 ). Similarly, statistical techniques can be used in both quantitative and qualitative research, but inferential statistics are mostly associated with quantitative research (Gall et al., 2003 , 2005 ).

Quantitative research includes a variety of approaches and designs, as well as such tools as correlations, surveys, and multifactorial studies, in addition to experimental or quasi-experimental studies. Qualitative research, on the other hand, encompasses a broad, expanding assortment of approaches, including narrative research, life history, autobiographical or biographical accounts, content analysis, historical and archival studies, conversation analysis, microethnography, and discourse analysis. These types of research draw on a variety of theoretical traditions as well, such as ethnomethodology, symbolic interactionism, structuralism, interpretivism and social constructivism, poststructuralism, phenomenology, hermeneutics, feminism, social/educational anthropology, and cultural studies (Denzin and Lincoln, 2005b ).

In recent years, government-funded quantitative research in the United States has enjoyed a privileged status within education and the social sciences because it is considered by some authorities to be more robust, rigorous, “scientific,” theoretical, and generalizable and, therefore, it is argued to have more to contribute to knowledge, theory, and policy than qualitative research (Freeman et al., 2007 ). Of course, claims of rigor or generalizability should not be taken for granted in quantitative research—they must, rather, be demonstrated by the researcher. Neither should it be assumed that qualitative research is atheoretical, unscientific, lacking in rigor or generalizability (transferability), or intellectually insignificant. However, again, the onus is on the researcher to demonstrate the credibility and importance of the methods and findings (Duff, 2006 ). Fortunately, qualitative research of different types has gained a major foothold in AL in the past 10 years, creating a better balance between quantitative and qualitative publications in the major AL journals than had been reported earlier (Lazaraton, 2000 ).

Critical (or “ideological”) research is sometimes accorded a category of its own, separate from quantitative and qualitative paradigms. According to Pennycook ( 2008 ), critical applied linguistics is

an emergent approach to language use and education that seeks to connect the local conditions of language to broader social formations, drawing connections between classrooms, conversations, textbooks, tests or translations and issues of gender, class, sexuality, race, ethnicity, culture, identity, politics, ideology or discourse. (p. 169)

Perhaps critical research is considered an independent category because certain approaches to research constitute explicitly ideological lenses or frames (e.g., critical or feminist) through which any data or situation can be analyzed using a variety of methods, quantitative or qualitative. Thus, critical perspectives can be applied to ethnography or to census data, and feminist perspectives can be applied to test score data or case studies. Alternatively, it could be claimed that these overtly ideological perspectives constitute different approaches, purposes, underlying assumptions, methods, subject matter, and reporting styles and that they are therefore not simply new lenses, frames, or values to be applied to otherwise orthodox academic pursuits with reified categories and objectification.

Such other types of research as program evaluation research and action research can take the form of either—or both—quantitative and qualitative research.

Developments in Quantitative Research

The last 3 decades have been very productive for the development, explanation, and application of quantitative research design and statistics and other analytical techniques in AL research using a variety of types of research: experimental, quasi-experimental, correlational, survey, and other carefully controlled, sometimes multivariate designs. As a result, careful attention has been paid to the reliability and validity of research constructs, instruments, scales, rating protocols, and analytical procedures; sampling procedures; measurement; variables and parametric and nonparametric statistics and power effects (Hatch and Lazaraton, 1991 ; Lazaraton, 2000 ). Some additional developments are reported in this section.

N. C. Ellis ( 1999 ) discusses three quantitative approaches to cognitive and psycholinguistic research: observational research (e.g., using language corpora), experimentation (e.g., in studies on form-focused instruction and SLA; Doughty and Williams, 1998 ), and simulations (e.g., connectionist models of SLA; Kempe and MacWhinney, 1998 ). Although there is a greater understanding among applied linguists of the criteria of good quantitative research currently, it is also evident that true experimental research is often difficult to conduct for logistical and ethical reasons, particularly in research with children or adults in educational contexts. In many institutions, for example, pretesting, random assignment to treatment types (e.g., instructional interventions or experimental stimuli), and control or normative/baseline groups may be difficult to arrange. Norgate ( 1997 ) provides an interesting example of this dilemma in research on the L1 development of blind children. Rather, quasi-experimental research examining cause-effect relationships among independent and dependent variables and research looking for other kinds of relationships among variables predominate. Experimental SLA laboratory studies are an exception; that research often involves artificial or semi-artificial L2 structures, control groups, random assignment, and pre- and posttesting (e.g., Hulstijn and DeKeyser, 1997 ). The downside of this carefully controlled research is that it lacks ecological validity because the language(s), contexts, and activities do not represent those ordinarily encountered by language learners and users.

In another area of AL, language testing, which has made great strides in tackling issues of validation, ethics, and psychometric precision in recent years, Kunnan ( 1999 ) describes new quantitative methods, such as structured equation modeling, that permit sophisticated analyses of relationships among groups of learner (test taker) variables such as L2 proficiency, language aptitude, and intelligence. Chalhoub-Deville and Deville ( 2008 ) also note developments in testing based on generalizability theory, multidimensional scaling, multifaceted Rasch analysis, rule-space methodology, and computer-based and computer-adaptive testing, typically found in articles in the journal Language Testing .

In L1/L2 survey research, C. Baker ( 2008 ) describes large-scale and small-scale initiatives in Europe, South America, and elsewhere, dealing with such issues as language vitality among minority language groups and social-psychological variables (e.g., attitudes and motivation) connected with successful L2 learning. He also illustrates how more readily available census data with specific items about language has facilitated certain kinds of analysis for language policy and planning purposes. Finally, Baker notes that a growing trend in European research lies in examining practices related to community (heritage) language schooling and surveying attitudes toward trilingualism and multilingualism (which others might refer to as language ideologies).

Developments in Qualitative Research

Whereas qualitative AL research in the past may have leaned toward (post)positivism and structuralism, relying on researchers' structured elicitations, analyses, and interpretations of a relatively narrow band of observed linguistic (or other) behavior sometimes designed to test specific hypotheses, current strands of research lean toward more unapologetically subjective, dialectical accounts, incorporating different, sometimes contradictory perspectives of the same phenomenon and grappling more intentionally with issues of positioning, voice, and representation (Duff, 2008 ; Edge and Richards, 1998 ). The omission of qualitative research methodologies from many textbooks, key journals, graduate courses, and programs in applied linguistics even a decade ago has been corrected to a significant degree in the interim (K. Richards, 2003 , 2009 ), particularly with the social and narrative turns that applied linguistics has witnessed during this decade in second language learning research as well as in language testing. Baker ( 2008 ), the researcher in bilingualism referred to above, dryly observes, “within language and education, the methodological pendulum has partly swung towards a preference for qualitative, ethnographic and phenomenological types of approach. Although quantitative approaches have been much criticized within the study of language and education, it is unlikely that they will disappear” (p. 65).

A growing enthusiasm for qualitative poststructural, postcolonial, and critical L2 research (e.g., Pennycook, 1999 , 2008 ) is indeed evident in many areas of AL. Critical and poststructural perspectives have been applied to ethnographies (e.g., T. Goldstein, 1997 , 2001 ; Madison, 2005 ; Talmy, 2008 ), to in-depth studies of language and social identity (e.g., Norton, 2000 ), and to research on language and gender (e.g., Cameron, 1992 ; Ehrlich, 1997 ; R. D. Freeman, 1997 ; Mills, 1995 ), some of which is explicitly feminist, emancipatory, reflexive, and postmodern. Yet a comprehensive overview textbook of qualitative research approaches in AL still seems to be lacking, though a plethora of generic qualitative textbooks exist in education and the social sciences.

The “Research Issues” section of the TESOL Quarterly , which I edited for 12 years, featured many qualitative developments: in narrative research, interview and focus group research, corpus research, classroom observation, testing, research guidelines, and software tools for qualitative data analysis. Special issues of the Modern Language Journal in 1997 and 2007, centering on the so-called Firth and Wagner debates, also marked salient turning points in both theory and methodology in AL. The current expansion of qualitative approaches in AL reflects trends across the health sciences, social sciences, humanities, and education in recent years (Denzin and Lincoln, 2005a , 2005b ) and a growing interest in ecological validity and the social, cultural, situational, embodied, and performative nature of language, knowledge, representation, and learning. Journals that have been established in AL this decade, such as the Journal of Language, Identity and Education , as well as many other journals with qualitative or narrative in their titles, are further evidence of the emphasis on more subjective, discursive aspects of learning that are often approached through interpretive, inductive, and sometimes critical methods. I have observed, however, that in many parts of the world (e.g., in East Asia and Central Europe) the status of qualitative research is still considerably lower (and often poorly understood) in comparison with quantitative research, a situation that has fortunately changed in North American AL. Sociocultural research in those same geographical domains also seems to have had less visibility or traction than it has, for example, in the United Kingdom, Canada, United States, and Australia.

However, in such traditionally very quantitative subfields as language testing, more nonpsychometric and qualitative studies have been published in recent years in the English-speaking world, particularly in such journals as Language Assessment Quarterly (Chalhoub-Deville and Deville, 2008 ). Lazaraton ( 2008 ) describes the kinds of (qualitative) discourse or conversation analysis that have been done of transcribed oral-proficiency interview talk (including her research) and especially of interviewers' accommodations of interviewees (test takers), based on such factors as the test takers' proficiency level or the familiarity of test takers and testers. Other studies she reviews deal with test takers' discourse and their negotiation for meaning, the dynamics of interaction and discourse in tests that pair up test-takers, or use group formats (e.g., on Cambridge ESOL proficiency tests). The qualitative analyses prove very useful for test validation and especially to ascertain whether the interaction during testing has an inadvertent effect on test takers' scores. Other research that Lazaraton reviews describes the use of think-aloud protocols (verbal reports) by test raters and of research that looks at the impact or consequences of testing through ethnographic observation or case study.

Ethnography, Case Study, and Interview Research

Ethnographies of language learning and teaching, literacy practices, and workplace encounters, as well as methodological discussions about cultural aspects of knowledge and behavior, have become more prominent and commonplace since Watson-Gegeo's influential (1988) article first appeared in the TESOL Quarterly . Harklau ( 2005 ), Heath and Street 2008 ), and Toohey ( 2008 ) provide recent reviews of ethnographic research in AL. Ethnographic research typically describes the cultural patterns of groups as they evolve and settle over time, such as language learners in a class or workers at job sites. It aims to elicit insiders' ( emic ) perspectives as well as those of the researcher, undertaking participant observation ( etic ) perspectives. Increasingly, too, this research looks at the positioning of research participants not only by the others they interact with in their natural settings but also by how the researcher herself positions the participants and their behaviors—and herself. Harklau noted that relatively little ethnographic research has been conducted outside of the United Kingdom or North America by non-White, non-Anglophone researchers on languages other than English and their cultures. However, L. C. Moore ( 2008 ) subsequently described numerous ethnographic accounts of multilingual socialization in a variety of non-Western, non-English-dominant settings, including her own work in French postcolonial Africa. Indeed, many of the other invited chapters in the Springer 2008 Encyclopedia of Language and Education series likewise involved researchers reviewing describing practices in communities where various languages are spoken.

Case studies remain one of the most common forms of qualitative research in AL, on their own or in combination with quantitative research (Duff, 2008 ; Gomm, Hammersley, and Foster, 2000 ; Merriam 1998 ; Yin, 2009 ). Like ethnographic research, case studies typically place great importance on contextualization and holistic accounts of individuals, groups, or events. In some instances researchers are also able to track participants longitudinally, as Kanno 2003 ) did with several Japanese students who had previously studied English and other curriculum content abroad and then returned to Japan. Morita 2004 ), in her multiple-case study of Japanese women studying at a Canadian university, documented their academic and linguistic socialization as well as the meanings and factors behind, and social construction of, their apparent silence in some of their classes. The study revealed that far from representing a monolithic group based on ethnicity, gender, first-language, and academic status, each woman's experience in her new English-speaking academic environment was highly situated, contingent, and unique and also changed over time.

Another common approach to research at present concerns involved interviews as an important mediating tool and site for linguistic processes and for social semiotic action. Although interviews are used in many kinds of research for different purposes, the actual interactional structures, positioning, footings, framing, and so on are commanding renewed attention by AL researchers and others in the social sciences, in medicine, and in other fields (Campbell and Roberts, 2007 ; Kvale, 2006 ; Talmy and Richards, forthcoming; Gubrium and Holstein, 2002 ; Silverman, 2001 ). Some of the work compares a content analysis of interview discourse with other kinds of analyses of the interview itself as a speech event.

Narrative Inquiry and Art-Based Research

Personal accounts and narratives of the experiences of language teachers, learners, and others—often across a broad span of time, space, experience, and languages—have increasingly become a major focus in some qualitative research. Evidence includes first-person narratives, diary studies, autobiographies, and life histories of learning, teaching, or losing aspects of one's language and identity (e.g., Belcher and Connor, 2001 ; Kouritzen, 1999 ; Pavlenko and Lantolf, 2000 ; Schumann, 1997 ). At present, studies also examine individuals using language in and across social contexts that had been investigated to a lesser degree in the past (e.g., in professional or academic settings, in the home/family, in the community, in the workplace, and in other social institutions). New meta-methodological discussions about the range of directions, data collection approaches, forms of analysis, and criteria for good narrative research are presently abundant both in AL (Coffey and Street, 2008 ; Pavlenko, 2007a , 2007b ) and in the social sciences and education (Atkinson and Delamont, 2006 ; Clandinin, 2007 ; Clandinin and Connelly, 2000 ; Polkinghorne, 2007 ; Riessman, 2008 ). In addition to these narrative approaches to exploring linguistic experience, other important but less emic accounts of language and behavior have attracted renewed attention from scholars across disciplines, particularly in studies of the discursive structure and social-interactional accomplishment of narrative texts (e.g., Bamberg, 1998 ). Arts-based research involving dramatic enactments, representations through nonprint visual modes of representation, multimodal analysis, poetics, and fictionalized accounts are gradually gaining visibility in AL as well (e.g., T. Goldstein, 2001 ; M. C. Taylor, 2008 ).

Although often compelling and highly engaging as both a process and as research output, these emerging approaches do not supplant existing ones (whether quantitative or qualitative) but rather complement them and provide new topics, genres, analyses, and conclusions, as well as different notions of authenticity and legitimacy (Edge and Richards, 1998 ). There is a growing emphasis on social, cultural, political, and historical aspects of language and language research, in addition to narrative aspects (Creese, Martin, and Hornberger, 2008 ; Hinkel, 1999 ; McKay and Hornberger, 1996 ; Norton and Toohey, 2004 ; Duff and Hornberger, 2008 ). Categorical labels and unacknowledged bias have therefore been the subject of analysis and critique (in connection with race, class, culture, language, gender, heterosexism, native versus nonnative speakers, inner and outer circle in World Englishes [or Chineses], and indigenous versus nonindigenous voices and knowledge[s]). Drawing on different (psychological) traditions but also concerned with social aspects of language and literacy are neo-Vygotskyan, sociocultural, and constructivist accounts, which have been adopted by growing numbers of applied linguists over the past decade (Lantolf, 2000 ; Lantolf and Thorne, 2006 , 2007 ), particularly in research in classrooms, in therapeutic, counseling, or dynamic assessment encounters, and in community settings. Like other primarily qualitative approaches, sociocultural research often involves conversation analysis, discourse analysis, narrative analysis, and microethnography, and examines language and content in an integrated manner.

Reflecting another change in AL research approaches and objects of study, at the present time text and discourse analyses investigate not only the structure of, say, scientific research articles, but also the linguistic messages, symbols, and genres associated with ostensibly nonscientific media and interactions—for example, in popular culture, mass media, and everyday social encounters (e.g., dinnertime discussions). Some of this research is framed in terms of critical or poststructural theory and the constructs of literacy and discourse like that of identity have been theorized and analyzed as plural—not singular—entities, and as social, multifaceted, and fluid (Gee, 1996 ; Norton, 2000 ). Finally, the concern for understanding contextual features of linguistic phenomena—the hallmark of much qualitative (or at least nonquantitative) AL research—has also been applied to analyses of the historical, political, social, cultural, rhetorical, and intellectual contexts and consequences of AL theories, research, and practice/praxis (Rampton, 1995 ; Thomas, 1998 ).

Developments in Mixed-Method Research

Quantitative and qualitative approaches are currently viewed as complementary rather than fundamentally incompatible, and more mixed-paradigm research is recommended (Bergman, 2008 ; Dörnyei, 2007 ; Tashakkori and Teddlie, 1998 , 2003 ; Teddlie and Tashakkori, 2009 ). However, a balanced combination of the two is not yet commonplace in AL research. According to Denzin 2008 ) and Lincoln and Guba ( 2000 ), the paradigm “wars” of the last two decades have transformed into paradigm “dialogs.”

An example of mixed-method research in foreign language learning is the full-length research monograph by Kinginger 2008 ), a multiple-case study of American students in French-language study abroad programs in France. Another example is an evaluation of a Japanese foreign-language elementary school program by Antonek, Donato, and Tucker ( 2000 ) in the United States. Both studies provided measurement (test) data for students at different points in their programs but also included case studies of focal participants as well as the students' experiences and perspectives together with an analysis of their narrative or interview data to help shed light on the quantitative findings.

The Impact of Technological Advances on Research Approaches in Al

At the present time, technological and computational advances play a crucial role in most AL research, whether for collecting, inputting, managing, coding, storing, and retrieving data or for analyzing it. The availability of high-quality, affordable tape recorders, digital video cameras, personal and handheld computers, scanners, smart pens/boards, wikis, and means of incorporating data of different types from multiple sources in computer files and in publications (e.g., with accompanying compact disks or linked websites) has major practical and theoretical implications for education, testing, and research. Developments in digital technologies have been particularly useful in applied psycholinguistics, corpus linguistics, discourse analysis, and testing (N. C. Ellis, 1999 ; Markee, 2007 ). Videotaped data or other audiovisual representations of data can presently be posted online, can be linked to more traditional print-based reports, or can appear in stand-alone online publications. In research involving graphic imaging or analyses of the intersection of sound and image or multimodal analysis, this development is very important and enriches what would otherwise be limited to static, black-and-white, print- and transcript-based written accounts of linguistic phenomena that are often primarily oral but are represented through writing. New technologies have also enhanced research with minority populations in AL, such as the blind and deaf (Hornberger and Corson, 1997 ) and have enabled diaspora communities to remain connected and able to communicate freely using the languages and sometimes hybrid symbol systems at their disposal (Lam, 2008 ). Technology has also facilitated the documentation of endangered languages. Increasingly AL research involving computer-mediated communication conceives of language and literacy as social practice in which linguistic, social, and other identities can be constructed, displayed, and transformed (or resisted) and in which rich intertextuality, multimodality, and creativity are the norm and are the object of analysis (Snyder, 2008 ).

In addition, the use of data management and analysis software designed specifically for qualitative research has become more accessible and more widely used in AL than it had been earlier (e.g., Dörnyei, 2007 ; Séror, 2005 ). Furthermore, the development and accessibility of such L1 and L2 databases as TalkBank by MacWhinney ( 2001 ) at Carnegie Mellon University ( http://www.talkbank.org ) represent a significant language database of vocal interactions of humans and animals that is continually being updated and currently incorporates child language data (CHILDES) and data related to aphasia, conversation analysis, bilingualism, and second language acquisition, with linked digital audio and video data. This electronic database provides a tremendous resource for researchers as well as tools for analyzing their own and others' data. In addition, corpora and concordances for collecting and analyzing oral and written texts (Biber, Conrad and Reppen, 1998 ; Thomas and Short, 1996 ) and new databases resulting from the use of computers in language testing, as well as online language interactions in CALL or other electronic networks, have also engendered new possibilities for AL research. Thus, such diverse subfields as language acquisition, text analysis, syntax and semantics, assessment, sociolinguistics, and language policy are affected. Research involving functional neuroimaging tools (e.g., functional magnetic resonance imaging, fMRI) and positron emission tomography (PET) provide valuable real-time information about the inner workings of the brain, especially in relation to different languages and tasks among monolinguals, bilinguals, and multilinguals (Wattendorf and Festman, 2008 ). The relationships between age of additional-language acquisition, proficiency level, and differential cortical functioning and localization of functions have long been of interest to neurolinguists and neurobiologists, and these new technologies literally provide a window into the brain's inner workings.

In addition to the Journal of Language Learning and Technology , which has become one of the most respected journals for digital technologies in applied linguistics, the recent survey of research across applied linguistics mediated by technology in Markee's ( 2007 ) special issue of the Annual Review of Applied Linguistics is particularly helpful. Possibilities are changing almost daily with what is presently known as Web 2.0 and the many other applications and tools for linguistic research in laboratories and in natural everyday settings and texts. Digital tools are ubiquitous for conversation analysis, teleconferencing, self-access podcasting, detecting plagiarism, modeling pronunciation and other aspects of speech or writing, tracking one's own or others' activities and progress online, text messaging, and test taking, and scoring tests.

Future AL research will no doubt continue to be greatly influenced by ongoing technical developments in natural language processing, machine and other translation systems, artificial intelligence, brain imaging techniques, CALL, gaming, aural/visual recognition, (eye gaze and other) tracking, and transcription devices. AL-tailored statistical packages and procedures will also become more sophisticated. Also, as more research focuses on languages other than English—including signed languages and those with different orthographies or with no orthographies at all—and seeks to accommodate a greater range of information about messages (e.g., phonetic, temporal, visual, contextual, material, embodied), new electronic tools and theoretical insights are bound to result.

Participants and Populations in Applied Linguistic Research

Although the populations that are the focus of applied linguistics are distinct from research approaches , the characteristics of groups under investigation certainly have implications for both methodology and theory. For example, work about/with indigenous language learners, their communities and cultures, and their languages, literacies, and other symbol systems, long underrepresented in applied linguistics, is currently beginning to flourish. Important developments have also occurred in the past decade in indigenous and postcolonial/decolonizing epistemologies and knowledges (e.g., Denzin, Lincoln, and Smith, 2008 ; L. T. Smith, 1999 ). Expanding the research participant pool and the languages they represent has implications for the way the research is theorized, conducted, interpreted, and disseminated with these populations as well as the form it ultimately takes. Given the endangered status of many such indigenous languages and related cultures and ideologies, this work is urgently needed.

However, just as great care is being taken to expand the collective research agenda to include a wider range of language users and geolinguistic contexts and to reflect on their experiences, poststructural and critical scholars remind us not to essentialize or reify these same populations. Applied linguistic and sociolinguistic research on gender and language, for example, has been carried out for more than a generation. But many scholars are at present very cautious about making grand claims based on gender (or sexuality, race, ability/disability, nativeness, etc.) as a set of predetermined, stable, always relevant, mutually exclusive categories (e.g., male/female) to which certain behaviors and perspectives can be uniquely ascribed (e.g., Bucholtz, 2003 ; Kyratzis and Cook-Gumperz, 2008 ). Rather, scholars are at present increasingly seeking evidence of how membership in such categories is socially coconstructed and performed through discourse not as a “preformed” category (Pennycook, 2008 ) but as a situated identity and by the various ways in which interlocutors position one another and themselves through their interactions and other behaviors and discourse and how they may also negotiate and transgress the expectations placed on them in relation to these social categories (Cameron and Kulick, 2003 ; Pavlenko, 2008b ; Pavlenko and Piller, 2007 ).

Elderly learners and users of language are also being included in more AL research as are people with degenerative cognitive or physical conditions affecting their language and communication capacities. Groups that in the past were not given special attention, such as generation 1.5 learners, heritage-language learners, transnationals, asylum seekers or refugees, very young or very old language learners/users, multilingual/multiliterate people, and the so-called generation of digital natives (youth and young adults immersed in new digital information and communication technologies) have, when included as research participants in AL (e.g., in SLA, language testing, language policy, sociolinguistics, and language/literacy education), yielded important new theoretical understandings that have often required new methodological approaches not previously used because these populations were excluded from earlier research.

In this chapter, I have provided a brief overview of both dominant and emerging approaches to AL research, particularly those typically described as quantitative, qualitative, or mixed-method, and as how these have been discussed and utilized in the field. The research topics and approaches discussed, much like the field of AL, involve various philosophical and theoretical commitments as well as methodological preferences and practices. AL research this past decade has demonstrated greater pluralism and rigor, an increased sensitivity to the contexts of research, the characteristics and diversity of research participants, the need to draw meaningful theoretical insights from findings and to consider carefully constraints on generalizability (or transferability) of results. Explicit discussion and reflection on researchers' own histories, investments, and roles in the research process are also expected to a greater degree than before not only in AL but across the humanities and social sciences more generally (Duff, 2008 ). Explicit discussion of criteriology in the assessment of research has underscored the responsibility that scholars have to know not only how to conduct and assess work in their own immediate areas of scholarship but also the different criteria, norms, genres, and expectations in other areas in AL (Edge and Richards, 1998 ; Lazaraton, 2003 ; cf. M. Freeman et al., 2007 ). There is a growing recognition of and respect for fundamental issues of ethics, fairness, and validity in AL research and practice (e.g., Cameron et al., 1992 ; Davies, 1997 ; Davis, 1995 ; Ortega, 2005 ), attention to the consequences of research for educational policy and practice, and an awareness that some issues, populations, languages, and geographic areas have received considerable research attention (and funding) whereas others have remained invisible or on the margins. This last point not only suggests imbalances in the global research enterprise, but also has implications regarding the limitations of the theoretical conclusions drawn from work confined to particular areas, languages, and participants at the expense of others.

The development of criteria for exemplary quantitative, qualitative, and mixed-method research and reporting has resulted in many carefully conceived studies and programs of research. In addition, a greater collective awareness and understanding of different research methods and areas of study is occurring. Collaboration among researchers looking at similar phenomena in different (socio)linguistic, cultural, and geographical contexts (as in earlier work by Blum-Kulka, House, and Kasper, 1989 , with respect to interlanguage pragmatics) would certainly benefit theory development and practical applications. Combining the expertise of applied linguists espousing different research paradigms in complementary types of analysis of the same phenomenon would also yield richer analyses of complex issues (Koshmann, 1999). One recent project reflecting multiperspectival research was undertaken by Barnard and Torres-Guzman 2009 ), who had chapter authors present their own analyses of classroom discourse and language socialization in schools in various parts of the world and then asked other researchers to do a “second take” (an independent analysis) of the same data to see how their analyses and interpretations differed. More multiperspectival research and theoretical triangulation involving researchers either from the same or from different traditions and disciplines (e.g., anthropology, psychology, education, and linguistics) examining the same data from their own frames of reference would enrich applied linguistics.

Although much AL research is chiefly concerned with abilities, behaviors, or sociolinguistic conditions and phenomena at one point in time (typically the present and/or immediate past), research sustained over larger periods of time, space, and activities is also needed, especially in developmental studies, studies trying to establish the long-term effectiveness of particular interventions, or those related to (academic) language socialization or language loss (Heath, 2000 ). Ortega and Byrnes's ( 2008 ) study represents a real contribution to AL precisely because it deals with both longitudinal research and research on advanced language learners. Replication studies, meta-analyses, cross-linguistic, cross-generational, and cross-medium (e.g., oral/written) studies have been used in limited ways in AL, with particular combinations of languages, media, and age groups. Recent work by Tarone, Bigelow, and Hansen ( 2009 ) highlights the theoretical benefits for SLA of examining alphabetic literacy levels of learners in studies of oral language development and processing. Thus, looking beyond one modality of language ability and use to see connections across modalities is very important.

More multimethod AL research would provide a greater triangulation of findings and help identify and interpret “rich points” in research (Hornberger, 2006a ). Research has started to take into account in more significant ways not only individual (e.g., cognitive, linguistic, affective) and (social) group aspects of language behavior and knowledge, but also sociocultural, historical, political, and ideological aspects. Consequently, more emphasis is being placed on the multiple, sometimes shifting identities, perspectives, and competencies of research participants and researchers, as well as the multiple contexts in which language is learned, produced, interpreted, translated, forgotten, and even eliminated (Norton, 2000 ; Duff, 2008 ).

Finally, all basic or pure research is meant to contribute to the knowledge base and theoretical growth of a field; thus, with more conceptually sound research, new discoveries, insights, and applications are certainly in store for the field of AL. In applied research that aims to yield a greater understanding of phenomena in the mind/world and also help to improve some aspect of the human condition, increased social and political intervention and advocacy is required. These, then, are just some of the issues and challenges that applied linguists must address in the future from different perspectives and using a variety of approaches. Indeed, as new perspectives, genres, and media for reporting and disseminating research are transformed, new areas for AL research and new challenges, too, will surface for the evaluation of innovative, nontraditional forms of research.

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Identifying and Avoiding Bias in Research

Christopher j pannucci , md, edwin g wilkins , md ms.

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Correspondence: Christopher Pannucci, MD Section of Plastic Surgery Department of Surgery 2130 Taubman Center, Box 0340 1500 East Medical Center Drive Ann Arbor, MI 48109 Phone: 734 936 5895 Fax: 734 763 5354 [email protected]

This narrative review provides an overview on the topic of bias as part of Plastic and Reconstructive Surgery 's series of articles on evidence-based medicine. Bias can occur in the planning, data collection, analysis, and publication phases of research. Understanding research bias allows readers to critically and independently review the scientific literature and avoid treatments which are suboptimal or potentially harmful. A thorough understanding of bias and how it affects study results is essential for the practice of evidence-based medicine.

The British Medical Journal recently called evidence-based medicine (EBM) one of the fifteen most important milestones since the journal's inception 1 . The concept of EBM was created in the early 1980's as clinical practice became more data-driven and literature based 1 , 2 . EBM is now an essential part of medical school curriculum 3 . For plastic surgeons, the ability to practice EBM is limited. Too frequently, published research in plastic surgery demonstrates poor methodologic quality, although a gradual trend toward higher level study designs has been noted over the past ten years 4 , 5 . In order for EBM to be an effective tool, plastic surgeons must critically interpret study results and must also evaluate the rigor of study design and identify study biases. As the leadership of Plastic and Reconstructive Surgery seeks to provide higher quality science to enhance patient safety and outcomes, a discussion of the topic of bias is essential for the journal's readers. In this paper, we will define bias and identify potential sources of bias which occur during study design, study implementation, and during data analysis and publication. We will also make recommendations on avoiding bias before, during, and after a clinical trial.

I. Definition and scope of bias

Bias is defined as any tendency which prevents unprejudiced consideration of a question 6 . In research, bias occurs when “systematic error [is] introduced into sampling or testing by selecting or encouraging one outcome or answer over others” 7 . Bias can occur at any phase of research, including study design or data collection, as well as in the process of data analysis and publication ( Figure 1 ). Bias is not a dichotomous variable. Interpretation of bias cannot be limited to a simple inquisition: is bias present or not? Instead, reviewers of the literature must consider the degree to which bias was prevented by proper study design and implementation. As some degree of bias is nearly always present in a published study, readers must also consider how bias might influence a study's conclusions 8 . Table 1 provides a summary of different types of bias, when they occur, and how they might be avoided.

Major Sources of Bias in Clinical Research

Tips to avoid different types of bias during a trial.

Chance and confounding can be quantified and/or eliminated through proper study design and data analysis. However, only the most rigorously conducted trials can completely exclude bias as an alternate explanation for an association. Unlike random error, which results from sampling variability and which decreases as sample size increases, bias is independent of both sample size and statistical significance. Bias can cause estimates of association to be either larger or smaller than the true association. In extreme cases, bias can cause a perceived association which is directly opposite of the true association. For example, prior to 1998, multiple observational studies demonstrated that hormone replacement therapy (HRT) decreased risk of heart disease among post-menopausal women 8 , 9 . However, more recent studies, rigorously designed to minimize bias, have found the opposite effect (i.e., an increased risk of heart disease with HRT) 10 , 11 .

II. Pre-trial bias

Sources of pre-trial bias include errors in study design and in patient recruitment. These errors can cause fatal flaws in the data which cannot be compensated during data analysis. In this section, we will discuss the importance of clearly defining both risk and outcome, the necessity of standardized protocols for data collection, and the concepts of selection and channeling bias.

Bias during study design

The definition of risk and outcome should be clearly defined prior to study implementation. Subjective measures, such as the Baker grade of capsular contracture, can have high inter-rater variability and the arbitrary cutoffs may make distinguishing between groups difficult 12 . This can inflate the observed variance seen with statistical analysis, making a statistically significant result less likely. Objective, validated risk stratification models such as those published by Caprini 13 and Davison 14 for venous thromboembolism, or standardized outcomes measures such as the Breast-Q 15 should have lower inter-rater variability and are more appropriate for use. When risk or exposure is retrospectively identified via medical chart review, it is prudent to crossreference data sources for confirmation. For example, a chart reviewer should confirm a patient-reported history of sacral pressure ulcer closure with physical exam findings and by review of an operative report; this will decrease discrepancies when compared to using a single data source.

Data collection methods may include questionnaires, structured interviews, physical exam, laboratory or imaging data, or medical chart review. Standardized protocols for data collection, including training of study personnel, can minimize inter-observer variability when multiple individuals are gathering and entering data. Blinding of study personnel to the patient's exposure and outcome status, or if not possible, having different examiners measure the outcome than those who evaluated the exposure, can also decrease bias. Due to the presence of scars, patients and those directly examining them cannot be blinded to whether or not an operation was received. For comparisons of functional or aesthetic outcomes in surgical procedures, an independent examiner can be blinded to the type of surgery performed. For example, a hand surgery study comparing lag screw versus plate and screw fixation of metacarpal fractures could standardize the surgical approach (and thus the surgical scar) and have functional outcomes assessed by a blinded examiner who had not viewed the operative notes or x-rays. Blinded examiners can also review imaging and confirm diagnoses without examining patients 16 , 17 .

Selection bias

Selection bias may occur during identification of the study population. The ideal study population is clearly defined, accessible, reliable, and at increased risk to develop the outcome of interest. When a study population is identified, selection bias occurs when the criteria used to recruit and enroll patients into separate study cohorts are inherently different. This can be a particular problem with case-control and retrospective cohort studies where exposure and outcome have already occurred at the time individuals are selected for study inclusion 18 . Prospective studies (particularly randomized, controlled trials) where the outcome is unknown at time of enrollment are less prone to selection bias.

Channeling bias

Channeling bias occurs when patient prognostic factors or degree of illness dictates the study cohort into which patients are placed. This bias is more likely in non-randomized trials when patient assignment to groups is performed by medical personnel. Channeling bias is commonly seen in pharmaceutical trials comparing old and new drugs to one another 19 . In surgical studies, channeling bias can occur if one intervention carries a greater inherent risk 20 . For example, hand surgeons managing fractures may be more aggressive with operative intervention in young, healthy individuals with low perioperative risk. Similarly, surgeons might tolerate imperfect reduction in the elderly, a group at higher risk for perioperative complications and with decreased need for perfect hand function. Thus, a selection bias exists for operative intervention in young patients. Now imagine a retrospective study of operative versus non-operative management of hand fractures. In this study, young patients would be channeled into the operative study cohort and the elderly would be channeled into the nonoperative study cohort.

III. Bias during the clinical trial

Information bias is a blanket classification of error in which bias occurs in the measurement of an exposure or outcome. Thus, the information obtained and recorded from patients in different study groups is unequal in some way 18 . Many subtypes of information bias can occur, including interviewer bias, chronology bias, recall bias, patient loss to follow-up, bias from misclassification of patients, and performance bias.

Interviewer bias

Interviewer bias refers to a systematic difference between how information is solicited, recorded, or interpreted 18 , 21 . Interviewer bias is more likely when disease status is known to interviewer. An example of this would be a patient with Buerger's disease enrolled in a case control study which attempts to retrospectively identify risk factors. If the interviewer is aware that the patient has Buerger's disease, he/she may probe for risk factors, such as smoking, more extensively (“Are you sure you've never smoked? Never? Not even once?”) than in control patients. Interviewer bias can be minimized or eliminated if the interviewer is blinded to the outcome of interest or if the outcome of interest has not yet occurred, as in a prospective trial.

Chronology bias

Chronology bias occurs when historic controls are used as a comparison group for patients undergoing an intervention. Secular trends within the medical system could affect how disease is diagnosed, how treatments are administered, or how preferred outcome measures are obtained 20 . Each of these differences could act as a source of inequality between the historic controls and intervention groups. For example, many microsurgeons currently use preoperative imaging to guide perforator flap dissection. Imaging has been shown to significantly reduce operative time 40 . A retrospective study of flap dissection time might conclude that dissection time decreases as surgeon experience improves. More likely, the use of preoperative imaging caused a notable reduction in dissection time. Thus, chronology bias is present. Chronology bias can be minimized by conducting prospective cohort or randomized control trials, or by using historic controls from only the very recent past.

Recall bias

Recall bias refers to the phenomenon in which the outcomes of treatment (good or bad) may color subjects' recollections of events prior to or during the treatment process. One common example is the perceived association between autism and the MMR vaccine. This vaccine is given to children during a prominent period of language and social development. As a result, parents of children with autism are more likely to recall immunization administration during this developmental regression, and a causal relationship may be perceived 22 . Recall bias is most likely when exposure and disease status are both known at time of study, and can also be problematic when patient interviews (or subjective assessments) are used as a primary data sources. When patient-report data are used, some investigators recommend that the trial design masks the intent of questions in structured interviews or surveys and/or uses only validated scales for data acquisition 23 .

Transfer bias

In almost all clinical studies, subjects are lost to follow-up. In these instances, investigators must consider whether these patients are fundamentally different than those retained in the study. Researchers must also consider how to treat patients lost to follow-up in their analysis. Well designed trials usually have protocols in place to attempt telephone or mail contact for patients who miss clinic appointments. Transfer bias can occur when study cohorts have unequal losses to follow-up. This is particularly relevant in surgical trials when study cohorts are expected to require different follow-up regimens. Consider a study evaluating outcomes in inferior pedicle Wise pattern versus vertical scar breast reductions. Because the Wise pattern patients often have fewer contour problems in the immediate postoperative period, they may be less likely to return for long-term follow-up. By contrast, patient concerns over resolving skin redundancies in the vertical reduction group may make these individuals more likely to return for postoperative evaluations by their surgeons. Some authors suggest that patient loss to follow-up can be minimized by offering convenient office hours, personalized patient contact via phone or email, and physician visits to the patient's home 20 , 24 .

Bias from misclassification of exposure or outcome

Misclassification of exposure can occur if the exposure itself is poorly defined or if proxies of exposure are utilized. For example, this might occur in a study evaluating efficacy of becaplermin (Regranex, Systagenix Wound Management) versus saline dressings for management of diabetic foot ulcers. Significantly different results might be obtained if the becaplermin cohort of patients included those prescribed the medication, rather than patients directly observed to be applying the medication. Similarly, misclassification of outcome can occur if non-objective measures are used. For example, clinical signs and symptoms are notoriously unreliable indicators of venous thromboembolism. Patients are accurately diagnosed by physical exam less than 50% of the time 25 . Thus, using Homan's sign (calf pain elicited by extreme dorsi-flexion) or pleuritic chest pain as study measures for deep venous thrombosis or pulmonary embolus would be inappropriate. Venous thromboembolism is appropriately diagnosed using objective tests with high sensitivity and specificity, such as duplex ultrasound or spiral CT scan 26 - 28 .

Performance bias

In surgical trials, performance bias may complicate efforts to establish a cause-effect relationship between procedures and outcomes. As plastic surgeons, we are all aware that surgery is rarely standardized and that technical variability occurs between surgeons and among a single surgeon's cases. Variations by surgeon commonly occur in surgical plan, flow of operation, and technical maneuvers used to achieve the desired result. The surgeon's experience may have a significant effect on the outcome. To minimize or avoid performance bias, investigators can consider cluster stratification of patients, in which all patients having an operation by one surgeon or at one hospital are placed into the same study group, as opposed to placing individual patients into groups. This will minimize performance variability within groups and decrease performance bias. Cluster stratification of patients may allow surgeons to perform only the surgery with which they are most comfortable or experienced, providing a more valid assessment of the procedures being evaluated. If the operation in question has a steep learning curve, cluster stratification may make generalization of study results to the everyday plastic surgeon difficult.

IV. Bias after a trial

Bias after a trial's conclusion can occur during data analysis or publication. In this section, we will discuss citation bias, evaluate the role of confounding in data analysis, and provide a brief discussion of internal and external validity.

Citation bias

Citation bias refers to the fact that researchers and trial sponsors may be unwilling to publish unfavorable results, believing that such findings may negatively reflect on their personal abilities or on the efficacy of their product. Thus, positive results are more likely to be submitted for publication than negative results. Additionally, existing inequalities in the medical literature may sway clinicians' opinions of the expected trial results before or during a trial. In recognition of citation bias, the International Committee of Medical Journal Editors(ICMJE) released a consensus statement in 2004 29 which required all randomized control trials to be pre-registered with an approved clinical trials registry. In 2007, a second consensus statement 30 required that all prospective trials not deemed purely observational be registered with a central clinical trials registry prior to patient enrollment. ICMJE member journals will not publish studies which are not registered in advance with one of five accepted registries. Despite these measures, citation bias has not been completely eliminated. While centralized documentation provides medical researchers with information about unpublished trials, investigators may be left to only speculate as to the results of these studies.

Confounding

Confounding occurs when an observed association is due to three factors: the exposure, the outcome of interest, and a third factor which is independently associated with both the outcome of interest and the exposure 18 . Examples of confounders include observed associations between coffee drinking and heart attack (confounded by smoking) and the association between income and health status (confounded by access to care). Pre-trial study design is the preferred method to control for confounding. Prior to the study, matching patients for demographics (such as age or gender) and risk factors (such as body mass index or smoking) can create similar cohorts among identified confounders. However, the effect of unmeasured or unknown confounders may only be controlled by true randomization in a study with a large sample size. After a study's conclusion, identified confounders can be controlled by analyzing for an association between exposure and outcome only in cohorts similar for the identified confounding factor. For example, in a study comparing outcomes for various breast reconstruction options, the results might be confounded by the timing of the reconstruction (i.e., immediate versus delayed procedures). In other words, procedure type and timing may have both have significant and independent effects on breast reconstruction outcomes. One approach to this confounding would be to compare outcomes by procedure type separately for immediate and delayed reconstruction patients. This maneuver is commonly termed a “stratified” analysis. Stratified analyses are limited if multiple confounders are present or if sample size is small. Multi-variable regression analysis can also be used to control for identified confounders during data analysis. The role of unidentified confounders cannot be controlled using statistical analysis.

Internal vs. External Validity

Internal validity refers to the reliability or accuracy of the study results. A study's internal validity reflects the author's and reviewer's confidence that study design, implementation, and data analysis have minimized or eliminated bias and that the findings are representative of the true association between exposure and outcome. When evaluating studies, careful review of study methodology for sources of bias discussed above enables the reader to evaluate internal validity. Studies with high internal validity are often explanatory trials, those designed to test efficacy of a specific intervention under idealized conditions in a highly selected population. However, high internal validity often comes at the expense of ability to be generalized. For example, although supra-microsurgery techniques, defined as anastamosis of vessels less than 0.5mm-0.8mm in diameter, have been shown to be technically possible in high volume microsurgery centers 31 - 33 (high internal validity), it is unlikely that the majority of plastic surgeons could perform this operation with an acceptable rate of flap loss.

External validity of research design deals with the degree to which findings are able to be generalized to other groups or populations. In contrast with explanatory trials, pragmatic trials are designed to assess the benefits of interventions under real clinical conditions. These studies usually include study populations generated using minimal exclusion criteria, making them very similar to the general population. While pragmatic trials have high external validity, loose inclusion criteria may compromise the study's internal validity. When reviewing scientific literature, readers should assess whether the research methods preclude generalization of the study's findings to other patient populations. In making this decision, readers must consider differences between the source population (population from which the study population originated) and the study population (those included in the study). Additionally, it is important to distinguish limited ability to be generalized due to a selective patient population from true bias 8 .

When designing trials, achieving balance between internal and external validity is difficult. An ideal trial design would randomize patients and blind those collecting and analyzing data (high internal validity), while keeping exclusion criteria to a minimum, thus making study and source populations closely related and allowing generalization of results (high external validity) 34 . For those evaluating the literature, objective models exist to quantify both external and internal validity. Conceptual models to assess a study's ability to be generalized have been developed 35 . Additionally, qualitative checklists can be used to assess the external validity of clinical trials. These can be utilized by investigators to improve study design and also by those reading published studies 36 .

The importance of internal validity is reflected in the existing concept of “levels of evidence” 5 , where more rigorously designed trials produce higher levels of evidence. Such high-level studies can be evaluated using the Jadad scoring system, an established, rigorous means of assessing the methodological quality and internal validity of clinical trials 37 . Even so-called “gold-standard” RCT's can be undermined by poor study design. Like all studies, RCT's must be rigorously evaluated. Descriptions of study methods should include details on the randomization process, method(s) of blinding, treatment of incomplete outcome data, funding source(s), and include data on statistically insignificant outcomes 38 . Authors who provide incomplete trial information can create additional bias after a trial ends; readers are not able to evaluate the trial's internal and external validity 20 . The CONSORT statement 39 provides a concise 22-point checklist for authors reporting the results of RCT's. Manuscripts that conform to the CONSORT checklist will provide adequate information for readers to understand the study's methodology. As a result, readers can make independent judgments on the trial's internal and external validity.

Bias can occur in the planning, data collection, analysis, and publication phases of research. Understanding research bias allows readers to critically and independently review the scientific literature and avoid treatments which are suboptimal or potentially harmful. A thorough understanding of bias and how it affects study results is essential for the practice of evidence-based medicine.

Acknowledgments

Dr. Pannucci receives salary support from the NIH T32 grant program (T32 GM-08616).

Meeting disclosure:

This work was has not been previously presented.

None of the authors has a financial interest in any of the products, devices, or drugs mentioned in this manuscript.

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Language and Scientific Research

• © 2021
• Wenceslao J. Gonzalez 0

Center for Research in Philosophy of Science and Technology, University of A Coruña, Ferrol, Spain

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• Provides a comprehensive exploration of the semantics of science
• Covers both basic scientific research and the development of applied science
• Argues that language affects the structure and dynamics of science and is therefore not a mere expressive instrumental sign

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About this book

This book analyzes the role of language in scientific research and develops the semantics of science from different angles. The philosophical investigation of the volume is divided into four parts, which covers both basic science and applied science: I) The Problem of Reference and Potentialities of the Language in Science; II) Language and Change in Scientific Research: Evolution and Historicity; III) Scientific Language in the Context of Truth and Fiction; and IV) Language in Mathematics and in Empirical Sciences.

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• Historicity
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Table of contents (9 chapters)

Front matter, the relevance of language for scientific research.

Wenceslao J. Gonzalez

The Problem of Reference and Potentialities of the Language in Science

Semantics of science and theory of reference: an analysis of the role of language in basic science and applied science, on the role of language in scientific research: language as analytic, expressive, and explanatory tool.

• Ladislav Kvasz

Language and Change in Scientific Research: Evolution and Historicity

Scientific inquiry and the evolution of language.

• Jeffrey Barrett

Language, History and the Making of Accurate Observations

• Anastasios Brenner

Scientific Language in the Context of Truth and Fiction

The evolution of truth and belief, models, fictions and artifacts.

• Tarja Knuuttila

Language in Mathematics and in Empirical Sciences

On mathematical language: characteristics, semiosis and indispensability.

• Jesus Alcolea

Characterization of Scientific Prediction from Language: An Analysis of Nicholas Rescher’s Proposal

• Amanda Guillan

Back Matter

Editors and affiliations, about the editor, bibliographic information.

Book Title : Language and Scientific Research

Editors : Wenceslao J. Gonzalez

DOI : https://doi.org/10.1007/978-3-030-60537-7

Publisher : Palgrave Macmillan Cham

eBook Packages : Religion and Philosophy , Philosophy and Religion (R0)

Copyright Information : The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Hardcover ISBN : 978-3-030-60536-0 Published: 28 April 2021

Softcover ISBN : 978-3-030-60539-1 Published: 28 April 2022

eBook ISBN : 978-3-030-60537-7 Published: 27 April 2021

Edition Number : 1

Number of Pages : XI, 285

Number of Illustrations : 15 b/w illustrations

Topics : Philosophy of Science , Philosophy of Language

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