Interpersonal Communication 9783110276794, 9783110276428

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Charles R. Berger (Ed.) Interpersonal Communication

Handbooks of Communication Science

Edited by Peter J. Schulz and Paul Cobley

Volume 6

Interpersonal Communication Edited by Charles R. Berger

DE GRUYTER MOUTON

The publication of this series has been partly funded by the Università della Svizzera italiana – University of Lugano.

ISBN 978-3-11-027642-8 e-ISBN 978-3-11-027679-4 Library of Congress Cataloging-in-Publication Data A CIP catalog record for this book has been applied for at the Library of Congress. Bibliographic information published by the Deutsche Nationalbibliothek The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data are available in the Internet at http://dnb.dnb.de. © 2014 Walter de Gruyter GmbH, Berlin/Boston Cover image: Oliver Rossi/Photographer’s Choice RF/Gettyimages Typesetting: Meta Systems Publishing & Printservices GmbH, Wustermark Printing and binding: CPI buch bücher.de GmbH, Birkach ♾ Printed on acid-free paper Printed in Germany www.degruyter.com

Preface to Handbooks of Communication Science series This volume is part of the series Handbooks of Communication Science, published from 2012 onwards by de Gruyter Mouton. When our generation of scholars was in their undergraduate years, and one happened to be studying communication, a series like this one was hard to imagine. There was, in fact, such a dearth of basic and reference literature that trying to make one’s way in communication studies as our generation did would be unimaginable to today’s undergraduates in the field. In truth, there was simply nothing much to turn to when you needed to cast a first glance at the key objects in the field of communication. The situation in the United States was slightly different; nevertheless, it is only within the last generation that the basic literature has really proliferated there. What one did when looking for an overview or just a quick reference was to turn to social science books in general, or to the handbooks or textbooks from the neighbouring disciplines such as psychology, sociology, political science, linguistics, and probably other fields. That situation has changed dramatically. There are more textbooks available on some subjects than even the most industrious undergraduate can read. The representative key multi-volume International Encyclopedia of Communication has now been available for some years. Overviews of subfields of communication exist in abundance. There is no longer a dearth for the curious undergraduate, who might nevertheless overlook the abundance of printed material and Google whatever he or she wants to know, to find a suitable Wikipedia entry within seconds. ‘Overview literature’ in an academic discipline serves to draw a balance. There has been a demand and a necessity to draw that balance in the field of communication and it is an indicator of the maturing of the discipline. Our project of a multi-volume series of Handbooks of Communication Science is a part of this coming-of-age movement of the field. It is certainly one of the largest endeavours of its kind within communication sciences, with almost two dozen volumes already planned. But it is also unique in its combination of several things. The series is a major publishing venture which aims to offer a portrait of the current state of the art in the study of communication. But it seeks to do more than just assemble our knowledge of communication structures and processes; it seeks to integrate this knowledge. It does so by offering comprehensive articles in all the volumes instead of small entries in the style of an encyclopedia. An extensive index in each Handbook in the series, serves the encyclopedic task of find relevant specific pieces of information. There are already several handbooks in sub-disciplines of communication sciences such as political communication, methodology, organisational communication – but none so far has tried to comprehensively cover the discipline as a whole.

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Preface to Handbooks of Communication Science series

For all that it is maturing, communication as a discipline is still young and one of its benefits is that it derives its theories and methods from a great variety of work in other, and often older, disciplines. One consequence of this is that there is a variety of approaches and traditions in the field. For the Handbooks in this series, this has created two necessities: commitment to a pluralism of approaches, and a commitment to honour the scholarly traditions of current work and its intellectual roots in the knowledge in earlier times. There is really no single object of communication sciences. However, if one were to posit one possible object it might be the human communicative act – often conceived as “someone communicates something to someone else.” This is the departure point for much study of communication and, in consonance with such study, it is also the departure point for this series of Handbooks. As such, the series does not attempt to adopt the untenable position of understanding communication sciences as the study of everything that can be conceived as communicating. Rather, while acknowledging that the study of communication must be multifaceted or fragmented, it also recognizes two very general approaches to communication which can be distinguished as: a) the semiotic or linguistic approach associated particularly with the humanities and developed especially where the Romance languages have been dominant and b) a quantitative approach associated with the hard and the social sciences and developed, especially, within an Anglo-German tradition. Although the relationship between these two approaches and between theory and research has not always been straightforward, the series does not privilege one above the other. In being committed to a plurality of approaches it assumes that different camps have something to tell each other. In this way, the Handbooks aspire to be relevant for all approaches to communication. The specific designation “communication science” for the Handbooks should be taken to indicate this commitment to plurality; like “the study of communication”, it merely designates the disciplined, methodologically informed, institutionalized study of (human) communication. On an operational level, the series aims at meeting the needs of undergraduates, postgraduates, academics and researchers across the area of communication studies. Integrating knowledge of communication structures and processes, it is dedicated to cultural and epistemological diversity, covering work originating from around the globe and applying very different scholarly approaches. To this end, the series is divided into 6 sections: “Theories and Models of Communication”, “Messages, Codes and Channels”, “Mode of Address, Communicative Situations and Contexts”, “Methodologies”, “Application areas” and “Futures”. As readers will see, the first four sections are fixed; yet it is in the nature of our field that the “Application areas” will expand. It is inevitable that the futures for the field promise to be intriguing with their proximity to the key concerns of human existence on this planet (and even beyond), with the continuing prospect in communication sciences that that future is increasingly susceptible of prediction.

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Note: administration on this series has been funded by the Università della Svizzera italiana – University of Lugano. Thanks go to the president of the university, Professor Piero Martinoli, as well as to the administration director, Albino Zgraggen. Peter J. Schulz, Università della Svizzera italiana, Lugano Paul Cobley, London Metropolitan University

Contents Preface to Handbooks of Communication Science series

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Part I: Interpersonal communication: An introduction

1

Charles R. Berger Interpersonal communication: Historical foundations and emerging directions 3

Part II: Fundamental processes

2

Marko Dragojevic and Howard Giles Language and interpersonal communication: Their intergroup dynamics 29

3

Laura K. Guerrero Interpersonal functions of nonverbal communication

4

Nicholas A. Palomares The goal construct in interpersonal communication

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Part III: Methodological approaches

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John P. Caughlin and Erin D. Basinger Measuring social interaction 103

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Meina Liu Analyzing social interaction data

127

Part IV: Functions of interpersonal communication

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James Price Dillard and Steven R. Wilson Interpersonal influence 155

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Daniel J. Canary and Heather E. Canary 177 Conflict in close relationships

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Contents

Michael E. Roloff Negotiation and communication: Explication and research questions

201

Judee K. Burgoon, Norah E. Dunbar and Cindy H. White 10 Interpersonal adaptation 225 James M. Honeycutt 11 Imagined interactions

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Sally Planalp and Jenny Rosenberg 12 Emotion in interpersonal communication

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Leanne K. Knobloch and Kelly G. McAninch 13 Uncertainty management 297 Aldert Vrij 14 Detecting lies and deceit: Pitfalls and opportunities in nonverbal and verbal 321 lie detection Denise Haunani Solomon and Anita L. Vangelisti 15 Relationship development 347 Susanne M. Jones and Graham D. Bodie 16 Supportive communication 371 Malcolm R. Parks and Meara H. Faw 17 Relationships among relationships: Interpersonal communication and social 395 networks

Part V: Interpersonal communication contexts Ascan F. Koerner 18 Family communication

419

Chris Segrin and Jeanne Flora 19 Marital communication 443 Michael W. Kramer and Patricia M. Sias 20 Interpersonal communication in formal organizations Ashley P. Duggan and Teresa L. Thompson 21 Social interaction processes in healthcare contexts

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Young Yun Kim 22 Interpersonal communication in intercultural encounters Joseph B. Walther and Eun-Ju Lee 23 Computer-mediated communication

Biographical sketches Author index Subject index

573 597

565

541

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Part I: Interpersonal communication: An introduction

Charles R. Berger

1 Interpersonal communication: Historical foundations and emerging directions Abstract: Since its inception in the 1950s, the interpersonal communication subdiscipline has evolved from a research enterprise preoccupied with understanding the role communication plays in the exercise of social influence to a broader purview that seeks to explain the role face-to-face and mediated social interaction play in the achievement of a broad range of instrumental and social goals. This evolution has featured development of theories aimed at explaining a variety of fundamental interpersonal communication processes and functions and the adoption of research methods that capture the dynamic, give-and-take of social interaction. These theories, and the research they have spawned, have been incorporated into such related communication science sub-disciplines as organizational, intercultural, and health communication, as well as research areas that deal with marital and family communication, social support and communication technology. This chapter traces these developments and suggests several future avenues that interpersonal communication theory and research might traverse. Key Words: Historical Foundations, Social Influence, Relationships, Cognitive Processes, Approaches to Inquiry, Levels of Analysis, Future Research Vectors

1 Introduction Interpersonal communication theory and research have shown explosive growth along multiple dimensions since the field’s inception during the post-World War II period. The interpersonal communication domain’s scope of interest has not only broadened immensely since these early days, researchers working in such seemingly unrelated areas of communication science as mass communication, organizational communication and communication technology have drawn heavily on conceptual frameworks and research advanced by interpersonal communication scholars. Moreover, interpersonal communication processes have become significant research foci in several applied areas. This volume’s chapters reflect ongoing research enterprises that exemplify these and other historical developments, and several of the chapters provide a glimpse of theory and research trajectories that are likely to develop more fully during the remainder of the 21st century. The goals of this chapter are to place the contemporary study of interpersonal communication into its historical context and to delineate alternative approaches to interpersonal communication inquiry. An additional aim is to identify paths along which the field is likely to develop in the coming decades. In the process of

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pursuing these three goals, the volume’s chapters will be placed in a broader context that may aid in the identification of new research directions.

2 Historical foundations In order to characterize the present and future landscape of the interpersonal communication sub-discipline as it is represented in this volume, it is necessary to understand its origins and how it has developed from its inception to the present. As will become apparent, choices of focal research areas within the field that were made decades ago are still quite apparent in contemporary interpersonal communication theory and research. Moreover, in all likelihood, these early commitments will continue to be reflected in future incarnations of the interpersonal communication research domain.

2.1 The post-World War II period Interpersonal communication emerged as a research area within the larger project of erecting a social scientific discipline of communication during the years following World War II. This broader communication science initiative was inspired primarily by researchers interested in mass media effects (Schramm 1954) and its roots predated World War II (Bryant and Pribanic-Smith 2010; Delia 1987). Early mass media effects researchers were housed in other social science disciplines. These interdisciplinary origins were highlighted by Schramm (1963) when he designated Harold Lasswell (political science), Paul Lazarsfeld (sociology), Kurt Lewin (psychology) and Carl Hovland (psychology) as the discipline’s “founding fathers.” Lazarsfeld’s pioneering studies of media effects on voting behavior (Benoit and Holbert 2010) and his landmark study of personal influence (Katz and Lazarsfeld 1955) fueled interest in communication research within journalism departments. Lasswell’s work in political communication had a similar effect on the same audience. However, it was Lewin and Hovland’s work, among others, that served as the launching pad for the field of interpersonal communication. Lewin’s interests in group processes and their influence on individual behavior (Lewin 1945) and Hovland’s extensive, experimentally-driven research program focused on communication and persuasion that extended from the late 1940s until the early 1960s (Hovland, Janis and Kelley 1953; Sherif and Hovland 1961) both exerted significant impact on the first generation of interpersonal communication researchers who emerged primarily from speech departments during the late 1950s. Maccoby (1963) characterized Hovland’s communication and persuasion research program as the empirical core of the “new scientific rhetoric,” a label that comported closely with the emerging research orientation of social-scientifically inclined speech communication scholars.

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Given these two, highly influential figures, it is not surprising that the first generation of interpersonal communication researchers who emerged from graduate programs housed in speech communication departments during the 1950s and early 1960s were primarily concerned with the study of communication and social influence processes (Berger 2005; Bryant and Pribanic-Smith 2010). Some of these researchers were inspired by Hovland’s work that focused on the role source, message and individual difference factors play in the process of persuasion, particularly persuasion in one-to-many contexts. Others looked to Lewin’s and other’s (Bales, 1950) group dynamics work to guide their research on influence processes within groups. Characterizations of the communication process reflected these early intellectual influences, for example, Berlo (1960: 12) proclaimed “… we communicate to influence – to affect with intent.”

2.2 Communication and relationships Although these traditions of communication and social influence research continue to be important features of the current interpersonal communication landscape, as evidenced by such chapters as Dillard and Wilson’s (see Chapter 7) in the present volume, a significant turning point in these early lines of research occurred during the late 1960s and early 1970s. The emergence of the human potential movement during the late 1960s with its emphasis on authentic selfpresentation through open and honest communication in some ways constituted a dialectical alternative to the more manipulative aspects of communication aimed at producing persuasive outcomes. In addition to research demonstrating the potential benefits of self-disclosure (Jourard 1971), a topic that continues to receive research attention and theoretical elaboration (Petronio 2002), research dealing with such topics as interpersonal attraction (Byrne 1971) and the development of interpersonal relationships (Altman and Taylor 1973) began to shift interpersonal communication researchers’ interests to the role communication plays in relationship development (Berger 1977). Several of this volume’s chapters reflect the continuing interest in relationship development processes (see Chapter 15, Vangelisti and Solomon) and such closely-related research areas as intergroup communication (see Chapter 2, Dragojevic and Giles), interpersonal conflict (see Chapter 8, Canary and Canary), negotiation (see Chapter 9, Roloff), interpersonal adaptation (see Chapter 10, Burgoon, Dunbar, and White), emotional expression (see Chapter 12, Planalp and Rosenberg), uncertainty management (see Chapter 13, Knobloch and McAninch), social support (see Chapter 16, Jones and Bodie) and social networks (see Chapter 17, Parks and Faw). This shift to relationship developmentrelated research was accompanied by the then-emerging interest in nonverbal communication among interpersonal communication researchers (Knapp 1972), including the area of deceptive communication (Knapp, Hart, and Dennis 1974). These interpersonal communication research domains remain highly active ones

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and are represented in this volume’s chapters (see Chapter 3, Guerrero; Chapter 14, Vrij). During the 1960s, interpersonal communication research concerned with social influence processes was informed by such social psychological theories as social comparison theory (Festinger 1954), dissonance theory (Festinger 1957, 1964), social judgment theory (Sherif and Hovland, 1961) and reactance theory (Brehm 1968). By the 1970s, however, evidence of increased interest in theory development began to manifest itself among interpersonal communication researchers. Formal theories devised by interpersonal communication researchers addressed such issues as the role uncertainty plays in communication during initial encounters between strangers and the development of relationships (Berger and Calabrese 1975; Berger 1979) and the consequences of proximic violations of personal space (Burgoon 1978). These early theoretical forays marked the beginning of a number of subsequent theoretical proposals by other interpersonal communication researchers and helped to establish a strong theory development ethic within the interpersonal communication research community. This volume’s chapters reflect this continuing commitment to theory development and contain lengthy lists of original theories concerned with such phenomena as communication accommodation, interaction adaptation, and uncertainty management.

2.3 The cognitive turn During the 1980s, the cognitive revolution found its way into the communication science discipline in general and the interpersonal communication area in particular. It was heralded by the proclamation “Cognito ergo dico” (Planalp and Hewes 1982) and the individual’s place in communication science was subsequently reinforced by Hewes and Planalp (1987). This move sparked general interest in message production processes and the initial version of Action Assembly Theory (Greene 1984), a general account of action production. The notion that interpersonal communication is a goal-directed, plan-guided process was carried forward in work on Goal-Plan-Action (GPA) models (Dillard 1990), planning theory (Berger 1997), cognitive rules model (Wilson 1990), as well as others (Greene 1997). This research tradition is reflected in the chapters concerned with message production (see Chapter 4, Palomares) and imagined interactions (see Chapter 11, Honeycutt). However, the focus on the individual cognitive processes subserving message production that developed during this period was met with some skepticism because it failed to capture the fundamental dialogic and reciprocal nature of interpersonal communication and the non-linear dynamics of the process entailed by its inherent dialectical tensions (Burgoon and White 1997; Baxter and Braithwaite 2008; Baxter and Montgomery 1996). These critiques notwithstanding, the cognitively-informed message production focus has been carried forward into the new millennium by interpersonal communication researchers interested in such areas as supportive

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communication (Burleson and MacGeorge 2002; MacGeorge, Feng, and Burleson 2011), goal detection and planning (Berger and Palomares 2011), and skilled message production (Greene and Burleson 2003).

2.4 The era of diversification The progressive expansion of the interpersonal communication field’s theoretical purview has naturally led to diversification of the contexts within which interpersonal communication processes are studied. Some of these contexts have become highly active sub-areas of study within their own right. Family communication (see Chapter 18, Koerner) and marital communication (see Chapter 19, Segrin and Flora) represent such sub-specialties within interpersonal communication. In addition, researchers whose primary foci seemingly lie beyond the boundaries of interpersonal communication have found interpersonal communication theory and research to be integral to understanding communication within their particular domains of interest. The chapters concerned with organizational communication (see Chapter 20, Kramer and Sias), health communication (see Chapter 21, Duggan and Thompson), intercultural communication (see Chapter 22, Kim) and technologically-mediated communication (see Chapter 23, Walther and Lee) exemplify the substantial reach and impact interpersonal communication theory and research has exerted well beyond the immediate boundaries of the sub-discipline.

3 Approaches to interpersonal communication inquiry The chapters concerning the measurement of social interaction (see Chapter 5, Caughlin and Basinger) and the analysis of social interaction data (Chapter 6, Liu) each address in detail a number of issues surrounding the collection and analysis of data gathered in interpersonal communication research. Consequently, the discussion of approaches to the study of interpersonal communication that follows will address broader conceptual questions about alternative ways of studying interpersonal communication.

3.1 What is interpersonal communication? Posing this question may seem to be a somewhat odd way to begin a discussion about alternative approaches to interpersonal communication inquiry; however, it is probably the case that the way in which this question is answered has a great deal to do with the way in which one approaches the study of interpersonal communication. Some early interpersonal communication scholars defined interper-

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sonal communication as communication between two people and no more (King 1979; Smith and Williamson 1979). During that same era, others took issue with this numerically-based definition (Berger and Bradac 1982) and still others argued that communication can be predicated on knowledge available at least three different levels: cultural, sociological and psychological (Miller and Steinberg 1975). Individuals may interact with each other primarily based on cultural norms or their membership in particular social-demographic categories such as sex, age or race. When interacting on the basis of cultural and sociological information, individuals do not know each other as individuals, thus their interactions tend to be impersonal or “non-interpersonal” (Miller and Steinberg 1975). When individuals increasingly predicate their behavioral choices during interactions on psychological level knowledge, that is, knowledge about the unique personal characteristics and history of their partners, their interactions become more interpersonal and less impersonal (Miller and Steinberg 1975). Thus, in contrast to the first, numerically-based definition, under this view of interpersonal communication many faceto-face interactions between two people do not entail interpersonal communication at all, for example, routine service-related interactions in which complete strangers use cultural and sociological information to guide their behavior. Although one might view the knowledge-based definition of interpersonal communication to be more useful than the numerically-based definition, questions have been raised about its adequacy (Cappella, 1987). Specifically, the Miller and Steinberg (1975) definition seems to rule out social interaction between those involved in less close relationships as part of interpersonal communication, for example, passing acquaintances, customers and service providers, physicians and patients and teachers and students. This exclusion arises because the definition focuses more on the relationships between the social actors and their knowledge about each other than it does on their communication with each other; yet, communication in these less personal situations can be highly consequential. Thus, as an alternative, Cappella (1987: 189) proposed that in order for interpersonal communication to occur, “… each person must affect the other’s observable behavior patterns relative to their typical or baseline patterns.” That is, each person’s behavior must cause the other person’s behavior to be different than it would have been under ordinary circumstances; in short, their behaviors must mutually influence each other. For example, assume that two people each have characteristic levels of vocal intensity (voice loudness) when they converse with others (a baseline pattern), but as they converse on a particular occasion, one’s person’s increase in vocal intensity is followed by an increase in the other’s vocal intensity and vice versa, as might take place in a debate or an argument. Given such a pattern of reciprocal escalation of vocal intensity, interpersonal communication has taken place because mutual influence has occurred. Under this view, mutual influence along one or more behavioral parameters such as vocal intensity, smiling, speech rate, vocalized pauses, non-vocalized pauses is the sine qua non of

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interpersonal communication. Moreover, this definition places time in a central role in interpersonal communication because patters of action and reaction between social actors are ordered with respect to the time dimension. Cappella (1987) futher suggested that these patterns of mutual influence can be associated with relational states and such outcomes as relationship satisfaction; however, interpersonal communication concerns the patterns of mutual influence between those involved in social interaction. In extending the notion that interpersonal communication involves the mutual exchange of messages and behaviors that eventuate in mutual influence, Burleson (2010: 151) proposed a message-centered approach to characterize interpersonal communication. This perspective posits that messages are exchanged “in an effort to generate shared meanings and to reach social goals.” Under this view, the interpersonal communication process involves message production (encoding), message reception (decoding), interaction coordination and social perception, a process by which individuals make sense of the social world. In seeking to accomplish social goals, message exchanges serve the functions of interaction management (conversational coherence), relationship management (relationship maintenance), and such instrumental functions as gaining compliance, acquiring information and entertaining. This message-centered approach emphasizes the pragmatic nature of interpersonal communication as a goal-satisfying endeavor. Not only do these four approaches to defining interpersonal communication illustrate that definitional choices regarding the nature of interpersonal communication have significant implications for choices of phenomena studied in its name, they also suggest substantial variability in approaches to that study of interpersonal communication. Three of these general approaches are discussed below and each of them is represented in this volume’s chapters.

3.2 The individual level of analysis Although Cappella’s (1987) definition of interpersonal communication hinges on mutual behavioral contingency and mutual influence between co-interlocutors, he recognized that phenomena occurring at other levels of analysis provide vital scaffolding for interpersonal communication as a mutual influence process. One of these levels concerns individual parameters responsible for the generation of observable, baseline behaviors. Individual parameters include biological and genetic factors, individual differences in personality and personal characteristics, emotional states and cognitive structures and processes. Each individual involved in a particular social interaction has some kind of standing on these parameters and their standing can influence their baseline behaviors. For example, individuals who are extraverted may characteristically talk more and be more nonverbally active when conversing with others than their introverted counterparts, and individuals may enter particular encounters with varying levels of uncertainty that

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may influence their behavior during the interaction. Of course, some of these individual parameters may not necessarily be related to the behavior being generated at the time. In a study illustrative of the individual level of analysis, high school students were asked three thought-provoking questions during a videotaped face-to-face interview, for example, “What should be the role of the media, like TV, radio, and newspaper, in today’s world?” (Reynolds and Gifford 2001). Such paralinguistic parameters as speech rate, number of words spoken, pauses, and ease of understanding as well as visual judgments of attractiveness and self-assurance were scored from the videotaped interviews. These parameters and then correlated with their intelligence test scores. The study revealed significant and positive correlations (r) between measured intelligence and number of words spoken (.50), speech rate (.40) and ease of understanding (.33) and significant negative correlations between measured intelligence and rated attractiveness (–.35) and self-assuredness (–.31). However, the degree to which speech was halting and judged to be non-standard was unrelated to measured intelligence. Thus, the intelligence parameter appears to promote different levels of communication-related behaviors; however, before one were to declare that the behavioral differences observed among individuals with different levels of intelligence qualify as “baselines”, one would want to have a wider sampling of communication situations in which the behaviors were elicited. The question is whether the same correlations between measured intelligence and behaviors would be obtained in communication contexts that do not involve answering thought-provoking questions. The crucial point is that individual and situational factors can influence baseline rates of behaviors and must be taken into account in determining whether or not deviations from baselines have occurred. In addition to personality and personal characteristics, individual cognitive structures activated during social interactions significantly influence behavioral output. Ample evidence suggests that when individuals engage in conversations, a relatively large percentage of their utterances are routine and formulaic, for example, “In my opinion …,” “The point is …” and “I understand what you are saying, but …” Some have estimated that up to 70 % of the utterances made during conversations are of this nature (Altenberg, 1990). These formulaic utterances arise because the goals social actors pursue in their daily commerce with each other frequently recur and because preformulated utterances reduce conversationalists’ cognitive load (Coulmas 1981; Smith 2000; Wray and Perkins 2000). This reduction in cognitive load enables conversationalists to deploy scarce attentional resources to such tasks as monitoring progress toward their interaction goals and attending to their partner’s nonverbal behavior. At a more molecular level, in pursuing their everyday goals, individuals’ behavior is guided by scripts (Schank and Abelson 1977) and plans (Berger 1997), cognitive structures that hierarchically organize knowledge about actions that accomplish goals. Thus, many routine social interac-

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tions, such as service encounters, entail the mutual activation of social actors’ scripts that are acted out with minimal conscious attention to interaction details. Such interactions involve the interleaving of social actors’ behaviors and, to the outside observer, are well coordinated with respect to turn-taking; however, they may not necessarily involve mutual influence in the sense that individuals’ behaviors induce deviations from each other’s baseline behavior rates. Social interactions such as these are akin to co-interlocutors’ scripts passing in the night. When enacting such interaction routines, individuals can become attentive to interaction details when there are perceptible deviations from scripted actions or when their goals fail to be realized (Berger 1997). As the above examples make amply clear, individual-level factors cannot be ignored in the study of interpersonal communication. Individual knowledge and the skill sets that social actors bring with them to social interactions, as well as their dispositional and emotional proclivities, together determine the possibilities and constraints they will experience in their social commerce with others. These individual-level factors play a potentially critical role in the degree to which individuals are able to adapt to the contingencies they may encounter during their social interactions with others. Moreover, efforts to improve interpersonal communication are frequently focused on honing individual-level communication skills such as perspective taking (MacGeorge, Feng, and Burleson 2011) and empathic accuracy (Ickes 1997); although, there are interventions, such as conjoint marital and family therapy, that seek to increase communication quality by focusing on social units such as the conjugal dyad or the family.

3.3 The interactional level of analysis Interpersonal communication researchers address the interactional level of analysis in at least two different ways. Consistent with the previous discussion, some researchers examine sequences of behavior that interacting social actors manifest during their encounters. Other researchers ask participants to make individual judgments about past interactions or global judgments that presumably reflect the residues of prior interactions. These two approaches are considered below.

3.3.1 Behavioral interaction The idea that interpersonal communication occurs at a level that transcends that of individuals’ behavior is a common one. In addition to Cappella’s (1987) mutual influence notion explicated previously, others have argued that communicating interpersonally requires that co-interlocutors’ actions be sequentially contingent and thus patterned in some discernible way (Watzlawick, Beavin and Jackson 1967). For example, some have argued that turn-taking is a fundamental mecha-

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nism that provides structure to social interaction (Wiemann and Knapp 1975). Consistent with this view, a study that compared turn-taking conventions in 10 different languages representing five continents revealed strong evidence of a universal tendency to avoid overlapping talk by observing turn-taking protocol (Stivers, et al. 2009). Although there was some evidence of cultural variation in the amount of time elapsed between speaking turns (positive response offset), this variation fell within 250 milliseconds of the overall mean for the 10 languages, suggesting the potential universality of this conversational convention. Thus, speakers of the languages showed the strong proclivity to allow their conversational partners to finish their speaking turns before beginning their speaking turns. It almost goes without saying that repeatedly violating this conversational turn-taking imperative by talking over others before they have finished their turn generally eventuates in negative consequences for its violators. In addition to the ubiquitous turn-taking imperative are other, highly predictable conversational contingencies. For example, a study of get-acquainted conversations between college student stranger dyads revealed that 92 % of the questions that were asked during the interactions were followed by an answer by the partner. Only 3 % of questions were followed by a question from the partner, and only 1 % of the questions were immediately followed by a second question from the question asker (Berger and Kellermann 1983). Question-answer sequences are legion in everyday conversations, as any elementary school child will attest. Conversations that take place between children and their parents just after the child has returned from school frequently begin with the parent asking the child “What did you do at school today?” or some similar query, eventually much to the child’s chagrin. Some have suggested that these question-answer sequences represent more than mere conversational patterns and are indicators of relational control (Mishler 1975). Asking a question “demands” a response from the addressee and the act of answering a question represents compliance with the interrogator’s request. Interruptions have been similarly viewed as dominance-related conversational moves (Zimmerman and West 1975) and have been related to sex differences in conversational behavior. One meta-analysis revealed a weak but discernible tendency for men to interrupt others more in conversations than women; however, the sex difference was substantially more pronounced for intrusive interruptions (Anderson and Leaper 1998). This sex differential has been interpreted as indicating that men assume more dominant roles in conversations than do women. However, from the perspective of interactional level of analysis, just as important are the responses those who are interrupted make to the interrupter. When those who are interrupted “push back,” they may effectively blunt interrupters’ influence attempts and exert significant counter influence in the process; that is, they may become dominant. Thus, the frequency of interruptions, per se, may not be indicative of successful influence or relative power. This “interactional” view of relational control, based on the view that message exchanges involve both content

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and relationship dimensions (Watzlawick, Beavin and Jackson 1967), is explicitly reflected in research based on interaction analysis schemes that code pairs of messages exchanged between relationship partners rather than individual messages (Millar and Rogers, 1976, 1987; Rogers 2008; Rogers and Escudero 2004; Rogers and Farace 1975). In these coding schemes, message pairs are assessed for the degree to which bids for relational control are accepted or challenged by the individual receiving the control attempt. The importance of the conceptual foundations underlying these coding schemes for assessing relational control cannot be overestimated. Subsequent interpersonal communication research in a variety of interest domains has explicitly coded message exchanges or action-reaction sequences in social interaction to great advantage. In particular, marital communication research has used this analytic framework extensively. This research has revealed common patterns of interaction in troubled marriages that involve such phenomena as cross-complaining, an interaction pattern in which a complaint by one spouse is immediately followed by a complaint by the other spouse. Troubled couples also tend to manifest demand-withdraw patterns in which a demand made by one spouse (usually the wife) is met by withdrawal by the other spouse (usually the husband) (see Chapter 19, Segrin and Flora). Surely, complaining and demanding occur in more satisfactory marriages as well; however, the apparent key is the response that is made to such acts by the other spouse. Choosing to address complaints or demands rather than responding by counter-complaining or withdrawing is an apparently more productive way to deal with such contingencies. Such findings have considerable practical significance since it is hardly hyperbolic to assert that these contingencies eventually arise in virtually all marriages, as well as in families, and require some kind of response.

3.3.2 Perceptions of interactions While studies of ongoing interactions seek to discern interaction patterns by observing and coding messages and behavior exchanges and identifying statistical dependencies among the acts generated by social actors, other studies ask individuals to recall specific types of events occurring during previous interactions and then assess them along a variety of dimensions. For example, some studies have shown that even among individuals involved in close relationships in which partners know each other quite well, certain events can increase uncertainties about their relational partners. Among such events are learning that the partner has betrayed one or has engaged in some uncharacteristic behavior (Planalp and Honeycutt 1985; Planalp, Honeycutt and Rutherford 1988). In many instances uncertainty-increasing events provoke negative consequences in the relationships. Other research asked participants to recall instances in which they were rendered speechless. They then responded to a series of questions about the incidents,

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including the question of why the incidents occurred. The most prevalent cause given in response to this open-ended question was the unexpected behavior of someone whom they thought they knew well (Berger 2004). Of course, judgments derived from recalled instances are potentially problematic along a number of dimensions, including the inevitable distortions that arise from memory for such events and the degree to which individuals can provide useful verbal reports about mental processes and judgments they may have made about the events when they occurred (Nisbett and Wilson 1977). Individuals may provide plausible stories about why they behaved in a particular way, stories that are based on culturallyshared, naïve theories; however, these theories and the accounts based on them may not necessarily be accurate. Similar methodological problems may be associated with the use of questionnaires that ask individuals to estimate how frequently they interact with others as a way of mapping communication networks (see Chapter 5, Cauglin and Basinger; Chapter 17, Parks and Faw). In addition to studies that ask participants to recall and assay specific instances that have occurred during previous interactions are studies that request respondents to provide more general characterizations of their social relationships. In such studies, individuals are interviewed and asked to talk about their relationships. Transcripts of interviews are then analyzed to identify dialectical tensions that seemingly exist in the relationship. Such dialectical tensions might entail the simultaneous desires for interdependence with a relationship partner versus autonomy or for predictability in the relationship versus novelty (Baxter and Braithwaite 2008; Baxter and Montgomery 1996). In contrast to studies that code the behaviors of people while engaging in social interaction, these studies entail the interpretation of individually-generated protocols that are based upon perceptions of various kinds of personal relationships such as friendships, romantic and marital relationships. Verbal characterizations of these relationship perceptions are used as a basis for inferring the existence of dialectical polarities and tensions as well as strategies individuals may use to deal with them. However, there seems to be no reason why, in principle, ongoing interactions between relationship partners could not be directly coded for evidence of dialectical tensions in their ongoing discourse.

3.4 The societal level The vast body of theory and research subsumed under the interpersonal communication rubric has been conducted at the individual and interactional levels of analysis. However, it is clear that societal level phenomena impinge on personal relationships in highly significant ways. To cite just a few of many potential examples, consider the impact of increasing participation of married women in the work force on both spousal and family communication patterns over the past 60 years, or the degree to which occupational demands on parents influence interactions

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with their children. Parents who return home from their workplace exhausted by the physical, emotional or intellectual demands of their work may find their interactions with each other and with their children significantly attenuated. Finally, consider the impact of mobile communication technologies on the communication that takes place between spouses and among family members and friends. While one might argue that the use of such mobile technologies enhances communicative opportunities among people and may serve to overcome some of the communicative opportunity costs that have been incurred by large-scale changes in time spent at work, at the same time, these mobile technologies allow employers to keep their employees “on call” 24 hours a day, seven days a week, thus raising the specter of a kind of occupational bondage that may curtail social interaction in the personal sphere. Moreover, the mere threat of such work-related intrusions into the personal domain and the potentially obsessive monitoring of technologies for such intrusions that may be motivated by fear of job loss, may serve to distract parents, even when they are physically, but not psychologically, present with their families. Although interpersonal communication researchers have invested considerable energy in delineating the ways in which the use of technologies that involve computer mediation of interpersonal communication impact the conduct of social interaction and its outcomes (see Chapter 23, Walther and Lee), they have tended not to examine these larger-scale effects. The increased popularity of such methodological developments as multi-level modeling (MLM), a statistical technique that requires researchers to think in multi-level terms and to acquire multi-level data, may encourage interpersonal communication researchers to adopt a more expansive view of their research domain (Hayes 2006; see Chapter 6, Liu). Some movement in the direction of using MLM has occurred among interpersonal communication researchers (Theiss and Solomon 2006), but societal-levels of analyses generally remain unexplored.

4 Future research vectors Divining the future of almost any academic research enterprise involves vagaries that differ little from those associated with long-range weather forecasting. Consequently, prognosticating about future directions that interpersonal communication research might take is an extremely daunting task. Although potential future trends that may influence the nature of both social life and social interaction can be identified, there is no guarantee that interpersonal communication researchers will necessarily undertake the study of such trends and influences. Nonetheless, there are several lines along which interpersonal communication research will probably develop.

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4.1 Blurring individual and interaction levels As previously noted, some interpersonal communication researchers have decried individually-focused approaches to the study of interpersonal communication on such grounds as their failure to deal with behavioral contingencies and mutual influence phenomena that are unique to social interaction (Cappella, 1987) and their failure to capture relationship-level phenomena (Baxter and Montgomery 1996). Although it has been possible in the past to make sharp distinctions between individual and interactional levels of analysis, developments in cognitive and social neuroscience have raised questions about this erstwhile fundamental distinction. Some neuroscientists have argued that rather than being separate processes, perception and action production are intimately intertwined in terms of brain functioning. This idea is embodied in common coding theory which asserts that the same mental representations are involved in observing actions and performing them (Eskenazi et al. 2009). Advocates of this theoretical stance point to evidence suggesting that human and primate brains have mirror neuron systems that are activated both when individuals perceive and when they act, thus raising questions about the traditional distinction between neurons responsible for processing perceptual inputs (afferent neurons) and motor neurons (efferent neurons) responsible for the production of action, including speech and nonverbal behaviors. There is suggestive evidence for such “dual use” neurons in speech perception and production. As people listen to words being uttered one at a time and the level of activity of the motor neurons that control their tongue movements is measured, the level of activity of these motor neurons mimics the specific words to which they are listening. When people hear the words that require more tongue movements to pronounce, they show higher levels of neural activity in their tongue muscles, even though they do not utter the words to which they are listening (Fadiga et al. 2002). Apparently, neural activity germane to speech production mimics what others are saying as they say it. Automatic mimicry and anticipatory neural activity in motor neurons may explain why social interaction can be carried out relatively smoothly and efficiently, even though social actors may speak rapidly and quickly switch conversational roles from speaker to listener (Gallese 2009; Greene 2003; Pezullo & Castelfranchi 2009). Moreover, neurologically-based mimicry could explain why individuals sometimes use the same words and phrases that their co-interlocutors have just uttered when it is their turn to speak in a conversation. While they listen to their conversational partners, social actors neurologically rehearse what it is they have heard. Reciprocity with respect to dialect, accent, speech rate, vocal intensity, vocal intonation and other nonverbal parameters is the rule rather than the exception when humans interact with each other (Burgoon, Stern, and Dillman 1995; see Chapter 10, Burgoon, Dunbar and White). The activity of mirror neurons may be responsible for the reciprocity’s pervasiveness in interpersonal communication. Motor mimicry in speech production may

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be an ongoing, default process but it is generally modulated by the action of other neurological systems to produce unique messages. Although these processes take place within the brains of individual social actors, the fact that automatically-activated mimicry is a ubiquitous feature of social interaction and may serve to explain several phenomena of interest to interpersonal communication researchers, including verbal and nonnverbal reciprocity, conversational coordination and empathic skills, strongly suggests that interpersonal communication researchers of necessity will have to play greater heed to the rapid developments in this area. Furthermore, these advances in understanding the mirror neuron system have significant implications for the way in which interpersonal communication competence or interpersonal communication skill is conceived (Wilson and Sabee 2003). These insights suggest that social interaction skill can be usefully conceptualized as at least two distinct but related levels (Berger and Palomares 2011). The most fundamental of these is concerned with the production of fluent speech and associated nonverbal behaviors as well as the perceptual processes aligned with these motor acts. These Level 1 skills are strongly determined by neurological processes which, if compromised by damage to critical neural circuits, can result in the debilitation of fundamental interpersonal communication capabilities, as manifested in autism spectrum disorders. In the extreme, these disorders can render the accomplishment of even routine social interaction extremely difficult, if not impossible. However, even if these fundamental, Level 1 skills are granted, there can be wide variation in the degree to which social actors are successful in achieving their interaction goals. Variation in Level 2 skills is the product of the degree to which knowledge structures, build mainly thorough experience, are well articulated; that is, the degree to which social actors have detailed funds of knowledge about the goals that individuals pursue and the plans they use to achieve them within social specific domains. Although it may be difficult to ameliorate skill deficits emanating from problems occurring at Level 1, Level 2 many skills can be acquired with sufficient learning practice (Berger and Palomares 2011).

4.2 Societal level influences Just as the study of interpersonal communication is likely to be strongly influenced from the bottom up by individual-level, neuroscience research that elucidates the fundamental structures and processes enabling social interaction, future societallevel phenomena are likely to impinge on communication at the interpersonal level from the top down. Some of these trends are already well in place but their effects are likely to be enhanced in the future. One of these is the use of technologies to mediate social interaction (see Chapter 23, Walther and Lee). Although the use of technologies for social networking and other forms of mediated interpersonal communication is already well established, people may increase their reliance on

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these technologies for reasons that transcend their current novelty. For example, as the cost of fossil fuels rises, thus increasing transportation costs for both longdistance and local travel, individuals may be more motivated to use various communication technologies to interact with those in their social networks (see Chapter 17, Parks and Faw) and within the commercial sphere, on-line shopping and teleconferencing will become even more prevalent. Of course, the development of alternative transportation technologies may allow individuals to maintain their current levels of physical mobility at an acceptable cost. However, developing such alternative, non-fossil fuel technologies for high-speed air travel appears to be a far-off goal and potential alternatives to fossil fuel-burning jet engines may increase significantly the costs of air travel, thus discouraging mobility. In any case, restrictions in physical mobility would almost certainly prompt increased reliance on communication technologies to enable interpersonal communication in both informal and formal social contexts. Moreover, as the communication technology revolution continues to play out, more sophisticated technologies will be placed in the hands of more people. This trend seems destined for a relatively long run. Other societal-level changes may impact communication at the interpersonal level. As the nature of societies change because of socio-demographic changes in the compositions of their populations, interpersonal communication norms and social interaction conventions will also change. As people from various cultural and ethnic backgrounds interact with each other on a daily basis, accommodations in conversational conventions will occur and social actors’ expectations for each other’s interpersonal behavior will change. Of course, such phenomena are hardly new ones in the history of humanity; however, since World War II, the world has become a much smaller place, partially because of developments in communication technologies. International telephone calls that were both expensive and difficult to complete in the 1950s, even with the required assistance of international telephone operators, are now both cheaply and easily accomplished. Continuing increases in the amount of contact between cultural and ethnic groups should motivate greater research interest in the changes that such contact potentiates in interpersonal communication norms and social interaction conventions.

4.3 Finding uniqueness in the mundane As previously discussed, a considerable amount of daily interpersonal commerce is directed at satisfying recurring goals by marshalling efficiently-enacted communication routines that employ formulaic language. Such daily encounters as customer-service provider transactions, greeting rituals and the like readily come to mind as exemplars. Parenthetically, it is these routine commercial encounters that are increasingly being conducted through the use of various technologies such as ATM machines, self-service gas pumps and supermarket check-out lines, as well

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as interactive computer speech systems used to handle telephone inquiries. However, even interpersonal communication episodes that at first blush appear to be somewhat less mundane than the communication that takes place during these routine encounters, for example, episodes involving intense interpersonal conflict, many entail the enactment of routines along at least two dimensions. First, individuals involved in relationships may engage in serial arguing, a phenomenon in which arguments focused on a particular issue are carried out over two or more episodes. Evidence suggests that such patterns of conflict may undermine the physical and mental health of those who engage in them (Malis and Roloff 2006; Roloff and Johnson 2002; Roloff and Reznik 2008). If such arguments are repeated over a number of episodes, there is a significant likelihood that an argument routine will develop that will lead the parties involved to repeat the same complaints, justifications, and demands that they have voiced in previous episodes. For those who have been involved in relationships for long periods of time, such argument routines could be repeated over many years; the argument becomes a well-established interaction routine. Second, even within first-time conflict episodes, communication routines may come into play. Parties involved in the conflict may employ formulaic utterances to achieve various conversational and instrumental goals. For example, after listening to a relationship partner express a complaint with considerable emotional negativity, an individual might utter “I understand where you are coming from” or “I understand your concern” in an attempt to mollify the partner’s negative emotional state. As previously observed, these “off the shelf” pre-formulated utterances can be deployed with minimal conscious calculation and may serve to buy them time to plan more elaborate strategies for dealing with the issue at hand. Of course, there is a host of other accusatory formulaic utterances that individuals may invoke during conflicts such as “You never listen to me”, “You never ask for my opinion about anything”, and “You don’t support me.” The critical point is that seemingly non-routine social interaction that has the apparent earmarks of being “special” and “unique” may be constructed from the conjunction of formulaic utterances and routines. If the reader remains unconvinced of this proposition’s validity based on the examples from interpersonal conflict arena, consider the legion of formulaic utterances that are part and parcel of falling-in-love talk. Such locutions as, “You are wonderful”, “I have never met anyone like you”, “You are really special” and “You are the person of my dreams” should all have a familiar ring to them. Finally, politicians and negotiators frequently conjure such formulaic utterances as “It’s a win-win for everyone”, “We must have all stakeholders on board” and “All options are on the table” to the point that they become tired, hackneyed expressions. Perhaps creatively-crafted communication involves the unique configuration of such formulaic utterances and routines as well as their violation. Given the ubiquity of formulaic utterances, the interweaving of communication routines to accomplish instrumental and com-

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munication goals during social interaction appears to be an area ripe for future investigation.

4.4 Interpersonal communication and personal well-being An important vector along which the aforementioned era of diversification (1.4) has moved is concern for the relationships between the quality of interpersonal communication and a variety of outcomes related to physical and psychological well-being. A substantial amount of research done under the health communication rubric is aimed at improving communication between physicians and patients in the service of several goals (Cegala and Street 2010; see Chapter 21, Duggan and Thompson). Improved communication between physicians and patients not only promotes greater patient satisfaction but also such health-related goals as compliance with treatment regimens. While health communication research focused on physician-patient interaction provides an obvious example of efforts to link interpersonal communication with specific outcomes, there are several other examples of such efforts. Research aimed at increasing marital satisfaction and marital and family stability has provided guidance to those seeking to develop therapies designed to reach these goals (see Chapter 18, Koerner; Chapter 19, Segrin and Flora). Conflict management theory and research (see Chapter 8, Canary and Canary) has also exerted a major influence in the marital and family communication areas. The identification of dysfunctional communication patters in interactions between spouses and among family members has led to more productive interventions to modify them. Efforts to ameliorate inter-ethnic conflicts, some of them highly intense, deeply ingrained and seemingly intractable (Ellis 2010), have drawn heavily upon insights gleaned from the conflict literature, as well as work done under the aegis of intergroup communication (see Chapter 2, Dragojevic and Giles) and bargaining and negotiation (see Chapter 9, Roloff). Finding strategies for bringing conflicting parties together and encouraging them to negotiate with each other in good faith are vital to promoting positive outcomes that prevent or stop hostilities between them. Although communication surely is not a magic elixir that will ensure world peace, functional negotiation strategies are highly significant features of regimens designed to achieve desired outcomes in managing conflict and reducing hostility. Over the past two decades, interpersonal communication research has made valuable contributions to efforts aimed at improving the quality of communication in situations in which individuals seek to provide social and emotional support to those experiencing distress. In particular, research concerned with the construction of comforting messages and their relative effectiveness has shown that messages exhibiting the quality of being person-centered and focused on the distress of the victim are more likely to be effective than comforting messages that attempt

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to minimize the other’s distress or reassure them that they will soon feel better (see Chapter 16, Jones and Bodie). This approach has been augmented by dualprocess theorizing postulating that the more extensively comforting messages are processed by those who receive them the more likely they are to have greater and long-lasting impact (Bodie, Burleson and Jones 2012). The roles played by interpersonal communication in the acculturation of both recently arrived immigrants (see Chapter 22, Kim) and new employees in formal organizations (see Chapter 20, Kramer and Sias) are ones that will continue to receive substantial attention from those interested in understanding communication’s role in adaptation to new environments. The desired outcomes of these acculturation processes are little different from those associated with marital and family communication, supportive communication and the like: a sense of satisfaction and well being.

5 Conclusion The study of interpersonal communication has evolved from a narrow focus on the role communication processes play in persuasion to a more catholic purview that includes an array of processes and outcomes that go beyond those concerned with changing attitudes and behavior. Early studies of influence tended to focus on one-to-many communication contexts that ignored, both theoretically and methodologically, the preconscious and conscious influence-counterinfluence dynamics inherent in ongoing social interaction. As this volumes chapters demonstrate, this critical shift has spawned theory and research that directly addresses such interactive phenomena as interpersonal adaptation, conflict and negotiation and methodological advancements that enable researchers to model them more realistically. The more ambitious scope of interpersonal communication research has also resulted in its theories and findings being used as launching pads for inquiries by those whose interests lie in such communication science domains as organizational, intercultural and health communication, as well as communication technology. The continuing evolution of communication technologies coupled with other global trends ensure that interpersonal communication theory and research will exert ever wide-ranging influence within the larger communication science discipline and will continue to address important social issues in the decades ahead.

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Bryant, Jennings and Erika J. Pribanic-Smith. 2010. A historical overview of research in communication science. In: Charles R. Berger, Michael E. Roloff and David Roskos-Ewoldsen (eds.), Handbook of Communication Science, Second Edition, 21–36. Thousand Oaks, CA: SAGE Publications. Burgoon, Judee K. 1978. A communication model of personal space violations: Explication and an initial test. Human Communication Research 4: 129–142. Burgoon, Judee, K. and Cindy H. White. 1997. Researching nonverbal message production: A view from interaction adaptation theory. In: John O. Greene (ed.), Message Production: Advances in Communication Theory, 279–312. Mahwah, NJ: Lawrence Erlbaum Associates. Burgoon, Judee K., Lesa A. Stern and Leesa Dillman. 1995. Interpersonal adaptation: Dyadic interaction patterns. New York: Cambridge University Press. Burleson, Brant R. 2010. The nature of interpersonal communication: A message-centered approach. In: Charles R. Berger, Michael E. Roloff and David Roskos-Ewoldsen (eds.), Handbook of Communication Science, Second Edition, 145–163. Thousand Oaks, CA: SAGE Publications. Burleson, Brant R. and Erina L. MacGeorge. 2002. Supportive Communication. In: Mark L. Knapp and John A. Daly (eds.), Handbook of Interpersonal Communication, Third Edition, 317–354. Thousand Oaks, CA: Sage. Byrne, Donn. 1971. The Attraction Paradigm. New York: Academic Press. Cappella, Joseph N. 1987. Interpersonal communication: Definitions and fundamental questions. In: Charles R. Berger and Steven H. Chaffee (eds.), Handbook of Communication Science, 184–123. Newbury Park, CA: SAGE Publications. Cegala, Donald J. and Richard l. Street, Jr. 2010. Interpersonal dimensions of health communication. In: Charles R. Berger, Michael E. Roloff and David Roskos-Ewoldsen (eds.), Handbook of Communication Science, Second Edition, 401–417. Thousand Oaks, CA: SAGE Publications. Coulmas, Florian. 1981. Intriduction: Conversational routine. In Florian Coulmas (ed.), Conversational routine: Explorations in standardized communication situations and prepatterned speech, 1–17. The Hague, Netherlands: Mouton. Delia, Jesse G. 1987. Communication research: A history. In: Charles R. Berger and Steven H. Chaffee (eds.), Handbook of Communication Science, 20–98. Newbury Park, CA: SAGE Publications. Dillard, James P. 1990. A goal-driven model of interpersonal influence. In: James P. Dillard (ed.), Seeking Compliance: The Production of Interpersonal Influence Messages, 41–57. Scottsdale, AZ: Gorsuch Scarisbrick. Ellis, Donald G. 2010. Intergroup conflict. In: Charles R. Berger, Michael E. Roloff and David Roskos-Ewoldsen (eds.), Handbook of Communication Science, Second Edition, 291–308. Thousand Oaks, CA: SAGE Publications. Eskenazi, Terry, Marc Grosjean, Glyn W. Humphreys and Guenther Knoblich. 2009. The role of motor simulation in action perception: A neuropsychological case study. Psychological Research 73: 477–485. Fadiga, Luciano, Laila Craighero, Giovanni Buccino and Giacomo Rizzolatti. 2002. Speech listening specifically modulates the excitability of tongue muscles: A TMS study. European Journal of Neuroscience 15: 399–402. Gallese, Vittorio. 2009. Motor abstraction: A neuroscientific account of how action goals and intentions are mapped and understood. Psychological Research 73: 486–498. Greene, John O. 1984. A cognitive approach to human communication: An action assembly theory. Communication Monographs 51: 289–306. Greene, John O. (ed.). 1997. Message Production: Advances in Communication Theory. Mahwah, NJ: Lawrence Erlbaum Associates.

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Part II: Fundamental processes

Marko Dragojevic and Howard Giles

2 Language and interpersonal communication: Their intergroup dynamics Abstract: Intergroup communication occurs when either person in a social interaction defines self or other in terms of their social identity (i.e., as a group member) rather than their personal identity (i.e., as a unique individual). In this chapter, we argue that most interactions traditionally considered interpersonal are actually intergroup in nature. Positioning our argument in light of intergroup theories, we first discuss the dynamic nature of communication, noting how conversation can quickly shift between various degrees of interpersonal and intergroup salience. Second, we describe the social categorization process, with particular emphasis on the ways in which social identities are marked, established, and negotiated communicatively through various verbal (e.g., language, topic) and nonverbal (e.g., clothing, makeup) cues. Next, some of the features that characterize intergroup interactions are developed, focusing on changes in perception, language use, as well as various communicative adjustments and misadjustments. Then, we note some ways in which intergroup encounters may be redefined in more interpersonal terms. Finally, several principles of intergroup communication are proposed and avenues for future research are discussed. Key Words: interpersonal, intergroup, social categorization, language, accommodation

1 Introduction Consider the following exchange between a husband and wife: While eating breakfast, Frank turns to Joanne and says, “There is never a moment when I don’t appreciate you for who you are: so talented, so caring, so different from any other woman I have ever met.” Only seconds later, he asks, “Can you iron my shirt? After all, it is a woman’s thing to do.” Intergroup communication occurs when either person in a social interaction defines self or other in terms of their social identity (i.e., as a group member), rather than their personal identity (i.e., as a unique individual).1 As the above 1 Gudykunst (2005, pp. 283–284) argues that interpersonal and intergroup processes can be differentiated in two primary ways. The first, following the work of Miller and Steinberg (1975), focuses on the type of data people use to make predictions about others’ behavior (i.e., how we define others). When people rely primarily on cultural (e.g., norms, values or rules) or sociological data (e.g., social group memberships) to make predictions about others’ behavior, intergroup communication is likely to occur. In contrast, when their predictions are based primarily on psychological data (e.g., personal information), interpersonal communication tends to occur. The second focuses

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example illustrates, people often communicate with one another in terms of their social group memberships and not purely as individuals. Although Frank is addressing Joanne initially in terms of her unique characteristics, his communication with her in closing is also based on her social group membership (i.e., gender); Joanne’s response to Frank is likely to be so influenced as well. Indeed, intergroup factors are often salient in many contexts typically considered interpersonal, such as interethnic/interracial friendships and romantic relationships (Gaines et al. 1999), cross-faith friendships (Paolini et al. 2004), and heterosexualhomosexual relationships (Vonofakou, Hewstone, and Voci 2007). Relatedly, family communication can be an intergroup domain (Soliz and Rittenour 2012) as it can be infused with group identities, such as gender roles (Tannen 2003), age (Harwood 2000), and racial/ethnic differences (Killian 2001). Although the focus on intergroup processes in the field of communication has grown tremendously in recent years and a number of edited volumes on the subject have appeared (Giles 2012a; Giles, Reid and Harwood 2010; Harwood and Giles 2005), interpersonal scholars have largely overlooked the utility of an intergroup perspective in their own research. In fact, the term intergroup is altogether absent from the indexes of major volumes on interpersonal communication (e.g., Knapp and Daly 2002; Spitzberg and Cupach 1998) and intergroup theories – with the notable exception of communication accommodation theory (CAT: e.g., Gallois, Ogay, and Giles 2005) – have largely been unexploited in empirical studies labeled as “interpersonal” (cf. Braithwaite and Baxter 2008). This is perhaps surprising given that, by some estimates, most interpersonal interactions may actually be intergroup in nature (see Giles 2012b; Petronio et al. 1998). The current chapter intends to bridge this gap and show ways in which intergroup theory and research across a wide variety of intergroup settings can supplement traditional interpersonal research. First, we discuss the dynamic nature of communication, noting how conversation can quickly shift between various degrees of interpersonal and intergroup salience. Second, we describe the social categorization process, noting some of the myriad ways in which group identities are marked communicatively. Next, some of the features that characterize intergroup interactions are developed, focusing on changes in perception, as well as various communicative adjustments and misadjustments. Then, we note some ways in which intergroup encounters may be redefined in more interpersonal terms. Finally, several principles of intergroup communication are proposed and avenues for future research are discussed.

on the identities guiding people’s own behavior (i.e., how we define the self). Specifically, when people’s behavior is guided primarily by their social identities (i.e., social group memberships), intergroup communication tends to occur. In contrast, when people’s behavior is guided primarily by their personal identities (e.g., idiosyncratic characteristics), interpersonal communication tends to occur.

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2 The dynamics of intergroup communication Scholars have often theorized that the distinction between interpersonal and intergroup encounters can be conceptualized along a single continuum (e.g., Tajfel and Turner 1986). Although the degree to which encounters are interpersonal, on the one hand, and intergroup, on the other, are in practice negatively correlated (see Oakes, Haslam, and Turner 1994), we are more inclined to adopt the perspective that communication can simultaneously be high or low on both the interpersonal and intergroup dimensions (Giles and Hewstone 1982; Harwood, Giles, and Palomares 2005). Consequently, we conceive of communication as falling within one of four quadrants defined by the degree of interpersonal and intergroup salience. In Quadrant I, communication may be purely embedded in interactants’ personal identities, where social group memberships are largely irrelevant. A conversation between two adult siblings about a memorable childhood event may be an example of such an interaction. In Quadrant II, people engage one another in terms of both their personal and social identities. An example of this may be an engaging discussion about cultural differences in a multiethnic marriage, or the hypothetical exchange between the married couple described earlier. In Quadrant III, a communicative episode may be entirely defined in terms of peoples’ social identities, as for example an encounter between two men whose nations are at war with one another. Finally, Quadrant IV represents situations low in both interpersonal and intergroup salience. Mindless interactions with service personnel may sometimes constitute such a situation. Although these quadrants may provide a useful heuristic, communication is highly dynamic and rigid classification within one quadrant is often not possible. Indeed, communication may quickly shift from one quadrant to another in only a few short minutes based on numerous factors, such as changing accommodative stance, level of threat, topic of conversation, and so forth (Giles et al. 2007). Moreover, not all interactants may perceive the encounter in the same way and an intergroup interaction may be defined as such only by one interlocutor’s characterization of the other’s identity (Harwood et al. 2005).

3 Social identity salience As noted above, people can define self and others in terms of their personal or social identity. Self-categorization theory (SCT: Turner et al. 1987) explains when and why these different levels of the self-concept become salient (i.e., activated) and how salient social identities influence social perception and behavior. SCT assumes that people have multiple social identities (e.g., gender, ethnicity) and claims that the extent to which a particular social identity becomes salient depends on its accessibility and fit.

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3.1 Accessibility Social categories can become accessible because they are valued or frequently employed (i.e., chronically accessible) and/or because they are perceptually present in the immediate social context (i.e., situationally accessible) (Hogg and Reid 2006). Certain social categories such as gender (Higgins and King 1981), age (Williams and Harwood 2004), and ethnicity (e.g., Mackie et al. 1996) are often both chronically and situationally accessible. Ethnicity, for example, tends to remain accessible even when attempts are made to lower its relevance to the task at hand (Hewstone, Hantzi, and Johnson 1991). The chronic accessibility of some categories is especially pronounced among certain portions of the population as for example, ethnicity being chronically accessible among highly prejudiced people (Stangor et al. 1992) and gender among fraternity and sorority members (DeSantis 2007). Group identities are often marked, established and negotiated communicatively through various verbal (e.g., language) and nonverbal (e.g., dress, makeup) cues (Harwood et al. 2005). Consequently, communication plays a key role in category accessibility.

3.1.1 Verbal cues Language is closely tied to social identity and can be an especially important symbol of identity for minority groups (Giles and Johnson 1981). Because linguistic variability is often systematic (Lippi-Green 1997), one’s language tends to be seen as an indicator of one’s social group membership(s). For example, whereas Irish is associated with Catholic and Nationalist identities in Northern Ireland, English is associated with Protestant and Unionist identities (O’Riagain 2007). As a result, an Irish speaker’s choice of language can make religious and political identities accessible as a basis for social categorization. In Israel, patterns of language use are similarly imbued with political and religious meanings. For example, John et al. (1985) found that the use of Hebrew evoked feelings of nationalism and ingroup solidarity among Jewish high school students, yet ones of oppression for Arab students, as well as increased the salience of interreligious divisions (see Haji and Lalonde 2012) among both groups of students, compared to English, an emotionally neutral language. Variability within the same language can also demarcate different social groups. For example, regional accents and dialects are often seen as indicative of different social identities, such as speakers’ geographic background and social class (for a discussion, see Dragojevic, Giles, and Watson 2013), and can be a more potent cue for social categorization than visual cues of difference, such as ethnicity (Rakić, Steffens, and Mummendey 2011). Interlocutors’ lexical choices (e.g., vocabulary) can also mark social affiliations. For instance, the use of ingroup lan-

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guage, such as technical or domain-specific jargon, has been found to increase group salience in medical (Hewett et al. 2009) as well as academic (Aagaard-Hansen 2007) settings. Speakers may also use more micro-level adjustments, such as pronoun shifts (e.g., I vs. we), to manage footing, or the identity from which they are speaking (Lerner and Kitzinger (2007). Labels represent relatively explicit markers of social identity (Giles 2012-b). The use of particular labels (e.g., “goth,” “brain”) in educational settings often assists in the social categorization of adolescents (Patterson and Bigler 2006). Similarly, Hajek (2012) points to the diverse labels often used to demarcate group boundaries among gay men, such as POZ (i.e., HIV positive men) and circuit boy (i.e., men who regularly travel to dance parties). Labels can also be an important social cue during computer-mediated-communication (CMC). For instance, selflabeling, such as the adoption of particular screen names (e.g., StarTrekFan), can make particular social identities (e.g., Trekkie) more accessible online (Walther and Carr 2010). The nature of conversational topics can also increase the accessibility of particular social categories. For example, Palomares (2009) found that both men and women were more likely to categorize in terms of gender when they read a short passage on a gender-stereotypical topic (e.g., automotive repair), than a genderneutral topic. In a similar vein, the expression of prejudicial views (Soliz and Harwood 2006) and older adults’ painful self-disclosures (e.g., complaints about health, bereavement: Coupland, Coupland, and Giles 1991) are both associated with increased age salience during intergenerational encounters (Harwood, Raman, and Hewstone 2006). During CMC, category accessibility can likewise be influenced by the nature of conversation topics (e.g., political discussion) as well as one’s mere (virtual) presence in a particular online setting (e.g., a discussion forum on a specific topic) (cf. Walther and Carr, 2010). Moreover, identity-threatening topics (e.g., Bourhis et al. 1979), as well as negative encounters more generally (Paolini, Harwood, and Rubin 2010), also tend to increase group salience.

3.1.2 Nonverbal cues Group identities can also be marked through various non-linguistic means, such as clothing and accessories. In a study of religious identity in Canada (Ruby 2006), immigrant Muslim women often reported that wearing the hijab was a positive experience in their lives that not only distinguished them as Muslim, but also served as an important symbol of their religious identity. Relatedly, in a study of Jewish young adults in Canada (Haji et al. 2011), participants frequently reported wearing religious jewelry, such as a Star of David pendant, as an expression of their Jewish identity. In addition to physical artifacts (e.g., jewelry, dress), music and body image can also be cues to social group membership. For example, Mendoza-Denton

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(2008) describes how members of Latina youth gangs in California often use makeup and music to mark their gang affiliations. Specifically, whereas Norteñas wear deep red lipstick and listen to Motown Oldies, Sureñas wear dark brown lipstick and listen to Mexican Banda Music. Physical appearance can also demarcate group boundaries among gay men. For instance, whereas young men with thin bodies and little or no body hair tend to be referred to as “twinks,” heavier, more masculine men with hairy bodies tend to be called “bears” (Hajek 2012). Similarly, physical appearance (e.g., militaristic hairstyles) and professional paraphernalia (e.g., uniforms, badges, and weaponry) often characterize the inherently intergroup nature of police-civilian encounters (Klockars 1985; Molloy and Giles 2002). Although such nonverbal cues may be relatively restricted during CMC, compared to traditional face-to-face (FtF) encounters, other available visual information (e.g., users’ photos, online avatars) can likewise serve as an important cue to interactants’ social group memberships in mediated contexts (Walther 2012).

3.2 Fit Once a particular social category becomes accessible, people evaluate how well it fits the particular social context within which the interaction is imbedded (Turner et al. 1987). Category salience depends on both comparative and normative fit. Comparative fit refers to the extent to which a category accounts for (and maximizes) within-group similarities and between-group differences (Hogg and Reid 2006). Normative fit refers to the extent to which people’s behaviors conform to normative expectations associated with a category (Oakes, Turner, and Haslam 1991). For example, if gender accounts for similarities and differences among a set of people (high comparative fit) and those people behave in gender-stereotypical ways (high normative fit), gender is likely to become salient in that particular context. If, however, a category does not adequately fit the social context (e.g., people behave counter-stereotypically), other accessible categories are evaluated until an optimal level of fit is reached (Turner et al. 1987). In this respect, the salience of a given social category is highly context-dependent (Stangor and Schaller 1996).

4 The nature of intergroup encounters Although at times innocuous and even rewarding (e.g., an engaging discussion about cultural differences in an interethnic friendship), intergroup communication can also be rife with misunderstanding and conflict (Ellis and Maoz, 2012; Hewstone and Giles 1986). The salience of group categories can accentuate the contrast between ingroups (i.e., groups people identify with) and outgroups (i.e., groups people do not identify with) (Tajfel and Turner 1986) and lead to broad misinter-

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pretations of verbal and nonverbal behavior (e.g., LaFrance and Mayo 1976). Communication across group boundaries is often suffused with anxiety and other negative emotions (Stephan and Stephan 2000) which, in turn, can reinforce negative group stereotypes (Islam and Hewstone 1993). When a particular social category becomes salient, it not only changes self- and other-perceptions but also influences how people adjust their communicative behaviors to their interlocutors.

4.1 Social categorization and depersonalization Social categorization fundamentally changes how people perceive and conceptualize self and others. People mentally represent salient social categories in terms of prototypes, or fuzzy sets of attributes (e.g., attitudes, beliefs, dress, language) that define and distinguish one group from another by accentuating intragroup similarities and intergroup differences (Turner et al. 1987). Because group prototypes are influenced by comparisons between groups, they are prone to dynamically change across different contexts depending on which groups are being compared. Once people categorize someone as a group member, they depersonalize their mental representation of that person by viewing them as an embodiment of the salient group prototype rather than as an individual (Hogg and Reid 2006). Just as people categorize others, they also categorize themselves. Self-categorization has the same depersonalizing effect on self-perception, so that people internalize the ingroup prototype and begin to think, feel, and behave in group normative ways (Turner et al. 1987). Consistent with this claim, a number of studies show that men and women use more gender-stereotypical language when they self-categorize in terms of gender (i.e., when gender salience is high). For instance, Palomares (2008, 2009) found that women made more references to emotion and used more tentative language – both stereotypically feminine language features – when gender salience was high. However, when gender salience was low, men and women referenced emotion and used tentative language at similar levels. The depersonalization of self and others, as well as the internalization of salient group norms, tend to be accentuated when individuating information is relatively scarce, a condition that is often characteristic of CMC (Postmes, Spears, and Lea 1998). Specifically, compared to FtF encounters, CMC tends to afford interactants greater anonymity due to increased control over their self-presentation and the ability to conceal aspects of themselves that would normally betray their social group membership(s) (see Amichai-Hamburger 2012). However, although the increased anonymity of CMC may conceal social cues, it also renders individual differences less salient. The social identity model of deindividuation effects (e.g., Reicher, Spears, and Postmes 1995) posits that this lack of individuating information accentuates the depersonalization of self and others, the salience of accessible social identities, and the expression of group-normative behavior in computermediated contexts. In particular, anonymity may grant people more freedom to

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behave in group-normative ways, even when such behavior blatantly violates outgroup norms (e.g., Reicher and Levine 1994).

4.2 Intergroup bias According to social identity theory (SIT: Tajfel and Turner 1986), people have an intrinsic motivation to maintain a positive self-concept. Because part of the selfconcept derives from one’s social group memberships (i.e., social identity), people strive to establish and maintain positive social identities in an effort to enhance their self-esteem (e.g., Tajfel 1974). One way in which people can achieve this is through favorable comparisons of their ingroup against relevant outgroups. This results in intergroup bias, or a systematic tendency to evaluate the ingroup more favorably than outgroups (Hewstone, Rubin, and Willis 2002: 576). Intergroup bias is especially pronounced among those most strongly identified with the ingroup (Branscombe et al. 1999), particularly when they feel that their ingroup identity is threatened by too much similarity to relevant outgroups (Tajfel and Turner 1986). One way in which intergroup bias manifests itself is through ingroup favoritism, or a preference and affinity for the ingroup over outgroups (see Hewstone et al. 2002). For instance, people tend to perceive ingroup members as more likeable and trustworthy than outgroup members (for a discussion, see Hewstone et al., 2002). Moreover, they expect members of their own group to display more socially desirable behaviors than members of other groups (Howard and Rothbart 1980) and tend to make differential attributions about the behavior of ingroup versus outgroup members. In particular, they are more likely to attribute socially desirable behaviors to positive dispositions of ingroup than outgroup members, and socially undesirable behaviors to negative dispositions of outgroup than ingroup members (e.g., Hewstone and Jaspars 1984). Such biased attributions are often reinforced through language. For instance, research using the linguistic category model (Semin and Fiedler 1988) shows that people display a linguistic intergroup bias (Maas et al. 1989) when interpreting the behaviors of ingroup versus outgroup members (for a review, see Sutton and Douglas 2008). Specifically, people tend to describe socially desirable ingroup behaviors and undesirable outgroup behaviors using abstract language (e.g., aggressive), implying dispositional (i.e., stable) attributions. In contrast, people tend to describe socially undesirable ingroup behaviors and desirable outgroup behaviors using more concrete language (e.g., kicked), implying situational (i.e., unstable) attributions. In this way, language use helps to transmit and maintain positive ingroup and negative outgroup stereotypes (Maas, Ceccarelli, and Rudin 1996). At the discursive level, intergroup bias can shape the content and nature of verbal discussions about outgroup members. In particular, people tend to emphasize outgroup members’ stereotypicality and homogeneity by allocating more discussion time to stereotype-congruent versus incongruent information (Ruscher and

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Hammer, 1994), as well as frequently referencing stereotypic “exemplars” that purport to rationalize and justify existing stereotypes (Ruscher 1998). Interactants’ tendency to stereotype outgroup members in conversation may serve a relational function and be used to establish common ground, as well as solidify relational closeness and solidarity. For instance, Ruscher, Cralley, and O’Farrell (2005) found that newly-acquainted dyads who felt closer to one another discussed and agreed about stereotypic outgroup attributes more, referenced more stereotypic exemplars, and formed more shared stereotypic impressions, than less close dyads. Sometimes intergroup bias extends beyond mere ingroup favoritism and takes the form of outgroup derogation and overt aggression (see Hewstone et al. 2002). Such outcomes are likely to occur when people’s social identities are conflicted, as for example the identities of Israeli-Jews and Palestinians being “structured contradictions” of one another (Ellis & Maoz 2012: 154), and when outgroups are associated with strong emotions (Mummendey and Otten 2001). For instance, outgroups that violate ingroup norms may evoke disgust and lead to avoidance, whereas outgroups that are perceived to pose a threat to the ingroup’s social identity or goals may evoke fear and hostility (Smith 1993). In turn, hostility towards the outgroup may lead to hate speech, such as the use of ethnopaulisms, or ethnic slurs (see Roback 1944). Such verbal aggression attempts to marginalize, degrade, and dehumanize outgroup members and can contribute to the perpetuation of stereotypes and prejudice (see Waltman and Haas 2011). Although ingroup members can use hate speech to promote a positive self-identity (Ruscher 2001), prevailing social norms usually deter such explicit expressions of prejudice (Collins and Clément 2012; but see Ellis, 2006).

4.3 Accommodation during intergroup encounters Whereas SIT and SCT explain the socio-psychological processes that underlie the cognitive aspects of intergroup phenomena, CAT provides a comprehensive theoretical framework from which to examine more directly communicative behavior during interpersonal and intergroup encounters. CAT examines the different motives and goals, influenced by personal and social identity, that underlie communicative adjustment and the evaluations and attributions that people make as a result. Interactants can adjust their communicative behavior relative to one another in three basic ways. Convergence refers to a strategy whereby individuals adapt their communicative behaviors to become more similar to one another in terms of a wide range of linguistic (e.g., language), prosodic (e.g., pitch) and nonverbal (e.g., smiling) features (Giles, Coupland, and Coupland 1991). In contrast, divergence refers to a strategy whereby individuals accentuate speech and nonverbal differences between themselves and others to become more dissimilar (e.g., Bourhis et al. 1979). Finally, maintenance is the absence of adjustment and reflects a strategy whereby people sustain their “default” way of communicating (e.g.,

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Bourhis 1979). These strategies are not mutually exclusive and people may, for instance, converge on one level whilst simultaneously diverging on another (Gallois et al. 2005). Moreover, people tend to be more consciously aware of their divergence and maintenance behaviors than convergence (e.g., Street 1982).

4.3.1 Convergence An important motive for convergence is a desire to gain another’s social approval (Giles et al. 1991). In line with the similarity-attraction paradigm (Byrne 1971), CAT argues that individuals can increase the level of interpersonal and/or social attraction by becoming more similar to one another in terms of their communicative behaviors. For instance, speakers may converge to their interlocutors’ accent, dialect, or language to signal that they belong to the same social group (e.g., Marlow & Giles 2008). Similarly, they may converge to their interlocutors’ idiosyncratic communicative characteristics so as to appear more similar to them. Convergence can also be enacted at the discursive level, through topic selection, topic sharing, and turn-taking (see Coupland et al. 1988). For example, Nelson, Dickson, and Hargie (2003) reported that Catholic and Protestant children in Northern Ireland often avoided sensitive topics (e.g., religion, politics) during interreligious conversations, citing this as a way to maintain group harmony and avoid conflict. In general, convergence tends to be evaluated favorably and has been found to increase a speaker’s perceived attractiveness (e.g., Street, Brady, and Putnam 1983), intelligibility (Triandis 1960), and interpersonal involvement (LaFrance 1979). However, such favorable evaluations may be attenuated if convergence is attributed to external pressures rather than the speaker’s intent (Simard, Taylor, and Giles 1976) or if it violates recognized norms (Ball et al. 1984). People converge not only to their interlocutors’ actual characteristics, but also to their perceived and expected characteristics (see Thackerar, Giles, and Cheshire 1982). For example, Bell (1982) reported that New Zealand radio announcers adjusted their speech patterns at different points in the day so as to accommodate their reading pronunciation to what they anticipated were different audiences, without any knowledge of the actual speech patterns of those audiences. Although sometimes speakers’ expectations of others’ behaviors and their actual behaviors may be one and the same, other times they may be incongruent. If erroneous, these expectations may lead speakers to overadjust (i.e., overaccommodate) or not adjust sufficiently (i.e., underaccommodate) their communicative behaviors to their interlocutors. Such erroneous expectations are especially likely to occur when intergroup salience is high – that is, when people engage one another partly (Quadrant II) or fully (Quadrant III) in terms of their social identities. Specifically, because social categorization depersonalizes people’s perceptions of others and leads to stereotyped expectations, speakers tend to converge to a stereotyped

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rather than an individualized view of their interlocutors during intergroup encounters (see Thackerar et al. 1982). Overaccommodation and underaccommodation both represent nonaccommodative behavior, which tends to be perceived negatively by its recipients (Giles and Gasiorek 2013).

4.3.1.1 Overaccommodation Overaccommodation has been examined in a wide range of intergroup settings. For example, communicative behaviors directed at the disabled are often characterized by an over-protective and over-controlling caregiving style that overaccommodates to negative stereotypes of the disabled as frail and incompetent (Thompson et al. 2002); such behavior is not only perceived negatively, but can lead to resentment on the part of the person with a disability. Erroneous expectations can also lead to overaccommodative behaviors during mixed-gender conversations. For example, Bayard (1995) found that women and men swore at similar rates during intragender conversations, but that women swore more than men during intergender conversations, arguably because they expected men to swear more than women. Considerable research has examined overaccommodation in the context of intergenerational communication. When younger people interact with the elderly, they frequently adjust their communicative behaviors to compensate for what they believe are physical or psychological deficiencies in older adults (Giles and Gasiorek 2011). However, these perceptions are often exaggerated and reflect negative age stereotypes, rather than older adults’ actual competencies. Drawing on these stereotypes, younger adults tend to (over)adjust their speech to the elderly by using a simplified grammar and vocabulary, unnecessary repetition, slowed speech rate, and exaggerated intonation (Hummert and Ryan 1996). Variously labeled as patronizing talk, elderspeak, and infantilizing talk (see Giles and Gasiorek 2011), this type of overaccommodation conveys a low assessment of older persons’ competence (Hummert et al. 2004) and tends to be associated with negative attitudes (Harwood and Williams 1998). The communication predicament of aging model (e.g., Ryan et al. 1986) describes how overaccommodation can lead to a negative feedback cycle by constraining older adults’ options in conversation and thus reinforcing negative age stereotypes. Indeed, patronizing talk can leave older adults feeling “infantilized” (Duggan et al. 2011) and lead to functional declines, as well as dependent and disruptive behavior (Baltes and Wahl 1996; Williams et al. 2009). However, age stereotypes need not always be negative. Acknowledging this, the activation of age stereotypes in interaction model (Hummert 1994; Hummert et al. 2004) argues that patronizing talk is more likely to occur in response to negative age stereotypes and considers how the salience of positive and negative age stereotypes may lead to differential outcomes during intergenerational encounters.

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Younger adults may be the recipients of overaccommodation from older adults as well. Older adults may overaccommodate to younger adults by converging to negative stereotypes of the young as naïve, unmotivated, and careless (Matheson, Collins, and Kuehne 2000). This can result in over-parenting, non-listening, and disapproving or disrespectful talk (Giles and Gasiorek 2011). Perhaps not surprisingly then, younger adults frequently characterize their interactions with older adults as problematic (Garrett and Williams 2005) and tend to find peer communication more satisfying (Giles et al. 2010).

4.3.1.2 Underaccommodation Although underaccommodation has been relatively understudied, some research suggests that it not only occurs more frequently but also tends to be perceived more negatively than overaccommodation (Gasiorek and Giles 2012). Excessive talk about one’s ailments (Coupland et al. 1991), as well as a lack of attention or listening to others (Giles and Williams 1994), tend to be characteristic of underaccommodative speech (see Williams and Nussbaum 2001). For example, older adults frequently underaccommodate to younger adults’ communicative preferences through painful self-disclosures and rambling speech (Hummert 2012). Similarly, underaccommodation is prevalent during police-civilian encounters and may be characterized by non-listening, disrespectful behavior, dismissiveness, indifference, and impoliteness (Dixon et al. 2008).

4.3.2 Divergence and maintenance Motivations for a positive social identity and distinctiveness and/or a desire to show disapproval towards one’s interlocutor(s) underlie communicative divergence and maintenance (Giles et al. 1991). In attempts to establish and maintain a positive social identity, people search for and create dimensions on which they can positively distinguish themselves from relevant outgroups (Tajfel 1974). Because communicative behaviors, such as language and speech style, represent important dimensions of social identity (e.g., Fishman 1977), divergence (and maintenance) on these dimensions may be used as a strategy to establish positive intergroup distinctiveness and differentiate oneself from relevant outgroups. One way individuals may differentiate themselves from relevant outgroups is by adopting the communicative behaviors believed to be prototypical of their ingroup (see Gallois and Callan 1988). For example, when gender was made salient, men were perceived to sound more “masculine” in their conversations with women, presumably as a result of converging (i.e., identifying) to their male ingroup prototype (Hogg 1985). Divergence and maintenance are especially likely to occur during intergroup encounters, where social identities are salient (Giles and Hewstone 1982), particu-

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larly when people identify strongly with their ingroup or feel that their identity is threatened. For example, when an English person threatened their ethnolinguistic identity, Welsh speakers broadened their Welsh accent and some even introduced Welsh vocabulary as a way to dissociate themselves from the outgroup speaker and emphasize their ingroup identity (Bourhis and Giles 1977). Similarly, Bourhis et al. (1979) found that when trilingual (Flemish-English-French) Flemish students were asked a content-neutral question by a French confederate in English, they converged to English. However, when the French confederate diverged into French to voice an ethnically threatening question, the Flemish students overwhelmingly diverged into Flemish and vehemently disagreed with the French confederate’s statements. In addition to language, speakers may also diverge on the discursive level by avoiding meaningful self-disclosures to outgroup members (Dovidio et al. 1997), which may preclude the establishment of intimate friendships. Divergence and maintenance tend to be associated with negative relational outcomes and are often characterized as insulting, impolite, or hostile (Deprez and Persoons 1984; Sandilands and Fleury 1979). However, negative evaluations may be attenuated if divergence is attributed to external pressures rather than the speaker’s intent (Simard et al. 1976) or if it is perceived to adhere to valued norms (Ball et al. 1984; Bradac 1990). Moreover, whereas outgroup recipients of divergence may view it as insulting or impolite, ingroup members may evaluate divergence directed at outgroup members positively (e.g., Bourhis 1979). For example, a year prior to Hong Kong’s handover to the People’s Republic of China, ingroup (i.e., Cantonese-speaking) members who diverged from Mandarin-speaking Chinese by emphasizing their Cantonese linguistic identity were evaluated more positively than those who converged to Mandarin (Tong et al. 1999).

5 Redefining intergroup encounters: From intergroup to interpersonal As the foregoing sections attest, intergroup encounters are frequently a site for conflict and misunderstanding. By leading to self- and other-depersonalization, social categorization contributes to intergroup bias and a wide range of nonaccommodative behaviors (e.g., over and underaccommodation, divergence, maintenance) which, in turn, can lead to negative relational outcomes or even hostility towards outgroup members. However, intergroup communication need not always be negative. For instance, research on intergroup contact theory (Allport 1954) shows that increased contact between groups can have a number of positive effects on intergroup encounters, such as more favorable attitudes and increased empathy towards outgroup members, as well as reduced anxiety during intergroup encounters (for an overview, see Harwood and Joyce 2012).

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Relatedly, the common ingroup identity model (Gaertner and Dovidio 2000) argues that an emphasis on a common ingroup identity may help to reduce conflict in intergroup encounters. Specifically, recategorization in terms of a superordinate category (e.g., family, nation, humanity) may reduce the salience of intergroup distinctions by placing self and others into the same category (see Ellis 2006). In turn, because we are more likely to trust people who we believe share our own characteristics (Tam et al. 2009), an emphasis on a common identity may increase empathy, encourage self-disclosure, and lead to more differentiated and personalized impressions of (formerly) outgroup members (Dovidio et al. 1997; Gaertner and Dovidio 2000) – for our purposes, redefining a primarily intergroup encounter (Quadrant III) in more interpersonal terms (Quadrants I, II). Accommodative behaviors can help foster a shared identity by accentuating interlocutors’ similarities and, thus, promoting ingroup solidarity (Giles, Bonilla, and Speer 2012). For instance, accommodative behaviors in families, such as selfdisclosure and social support, can increase perceptions of a shared family identity (Soliz and Harwood 2006). Similarly, in intergroup encounters defined by sexual orientation, respectful accommodation and self-disclosure are negatively associated with intergroup anxiety and positively associated with perceptions of relational solidarity (Soliz et al. 2010). Hornsey and Hogg (2000) caution that the creation of a common ingroup identity may not be ideal in situations where transcendence of group differences creates a loss of one’s own distinctiveness. Rather, a more amiable goal may be to develop a common identity while simultaneously recognizing subgroup differences (Hornsey and Hogg 1999). For example, Killian (2001) reports that black-white interracial romantic couples use a variety of strategies, ranging from direct discussion to more reserved approaches, to incorporate unique cultural aspects of their identities and thus develop a family and unique identity simultaneously. Similarly, Soliz, Thorson, and Rittenour (2007) note that communicatively recognizing and affirming individuals’ backgrounds can minimize group salience in families. In this respect, it may be possible to build unity by recognizing and appropriately addressing differences that make family members unique (Rittenour and Soliz 2009).

6 Conclusion and future directions Social identity salience fundamentally changes the nature of interpersonal communication and in ways mainstream scholars of this tradition might find emancipating in light of the foregoing. In this chapter, we overviewed how group identities can be marked communicatively through various verbal and nonverbal cues and how social categorization can lead to intergroup bias, group-normative behavior, and “misfired” communicative adjustments (i.e., nonaccommodation). We

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positioned our analysis in light of intergroup theories, demonstrating their applicability at different points in an interpersonal encounter. Out of this analysis emerge several principles of intergroup communication: – Social identities are established, negotiated, and made salient through communication (FtF and CMC), via various verbal (e.g., language, topic) and nonverbal cues (e.g., jewelry, music, body image). – Social identity salience contributes to self- and other-depersonalization and intergroup bias, influencing attributions, language use, and communicative adjustments. – Social interaction is dynamic and can quickly shift in its degree of interpersonal and intergroup salience, based on numerous communicative behaviors (e.g., changing accommodative stance, topic of conversation) that interlocutors can manipulate strategically. – Accommodative behavior and the recognition of a common identity may help attenuate intergroup bias, lead to more differentiated and personalized impressions of one’s interlocutor(s), and help redefine the encounter in more interpersonal terms, resulting in increased solidarity and communication satisfaction. At the outset of this chapter, we emphasized the dynamic nature of social interaction and noted that, over the course of only a few short minutes, conversation can quickly shift between various degrees of interpersonal and intergroup salience (e.g., from one quadrant to another). Such shifts are not only “a mechanical product of accessibility and fit” but, rather, can be strategically manipulated by interactants wishing to achieve various social and personal goals (Hogg and Terry 2001: 7). A focus on this dynamic nature of social interaction may provide a fruitful avenue of research for communication scholars, who might examine the multitude of ways in which identities are communicatively negotiated and enacted during conversation, the relative success of such attempts to shift conversational frames of reference, and the ways in which attempts to influence categorization may be constrained and enabled by existing norms (see Hogg and Giles 2012). Relatedly, the extent to which interactants are consciously aware of activated social identities during interaction and whether preconscious category activation is sufficient to produce changes in communicative output both remain intriguing challenges for future research. As we have shown throughout, intergroup processes are an inherently communicative phenomenon. Our communication is not only shaped by our conversational partners’ social identities, but also influences which social identities we and others pay attention to, based on what we say and how we say it. Indeed, the ubiquity of social identity salience in interaction suggests that understanding intergroup processes is fundamental to understanding interpersonal communication, ranging from mundane everyday talk, such as the interaction between the

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married couple in our opening example, to the “darker sides” (cf. Spitzberg and Cupach 1998) of interpersonal relationships. Indeed, relational breakdown may often be nothing to do with personal chemistries being at odds but be significant and wearing contentions due to differing social identities. The mesh of interpersonal and intergroup theories is an exciting prospect for the next decade (see Gallois 2003). Acknowledgement: The authors would like to thank Kimberly A. Williams for her insights and helpful comments on an earlier draft of this chapter.

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Ruscher, Janet B., Cralley, Elizabeth L., and O’Farrell, Kimberly J. 2005. How newly acquainted dyads develop shared stereotypic impressions through conversation. Group Processes and Intergroup Relations 8, 259–270. Ruscher, Janet B., and Hammer, Elliott D. 1994. Revising disrupted impressions through conversation. Journal of Personality and Social Psychology 64, 530–541. Ryan, Ellen B., Giles, Howard, Bartolucci, Giampiero, and Henwood, Karen. 1986. Psycholinguistic and social psychological components of communication by and with the elderly. Language and Communication 6, 1–24. Sandilands, Mark L. and Fleury, Nancy C. 1979. Unilinguals in des milieux bilingues: One analyse of attributions. Canadian Journal of Behavioral Science 11, 168–168. Semin, Gün R. and Fiedler, Klaus. 1988. The cognitive functions of linguistic categories in describing persons: Social cognition and language. Journal of Personality and Social Psychology 54, 558–568. Simard, Lise, Taylor, Donald M., and Giles, Howard. 1976. Attribution processes and interpersonal accommodation in a bilingual setting. Language and Speech 19, 374–387. Smith, Eliot R. 1993. Social identity and social emotions: Towards new conceptualizations of prejudice. In: Diane Mackie and David L. Hamilton (eds.), Affect, cognition, and stereotyping: Interactive processes in group perception (pp. 297–315). San Diego, CA: Academic. Soliz, Jordan and Harwood, Jake. 2006. Shared family identity, age salience, and intergroup contact: Investigation of the grandparent-grandchild relationship. Communication Monographs 73, 87–107. Soliz, Jordan, Ribarsky, Elizabeth, Harrigan, Meredith M., and Tye-Williams, Stacy. 2010. Family communication with gay and lesbian family members: Implications for relational satisfaction and outgroup attitudes. Communication Quarterly 58, 77–95. Soliz, Jordan and Rittenour, Christine E. 2012. Family as an intergroup arena. In: Howard Giles (Ed.), The handbook of intergroup communication (pp. 331–343). New York: Routledge. Soliz, Jordan, Thorson, Allison R., and Rittenour, Christine E. 2009. Communicative correlates of satisfaction, family identity, and group salience in multiracial/ethnic families. Journal of Marriage and Family 71, 819–832. Spitzberg, Brian H. and Cupach, William R. 1998. The dark side of close relationships. Mahwah, NJ: Lawrence Erlbaum. Stangor, Charles, Lynch, Laure, Duan, Changming, and Glass, Beth. 1992. Categorization of individuals on the basis of multiple social features. Journal of Personality and Social Psychology 62, 207–218. Stangor, Charles and Schaller, Mark. 1996. Stereotypes as individual and collective representations. In: C. Neil Macrae, Charles Stangor, and Miles Hewstone (eds.), Foundations of stereotypes and stereotyping (pp. 3–40). New York. Guilford Press. Stephan, Walter G. and Stephan, Cookie W. 2000. An integrated threat theory of prejudice. In: Stuart Oskamp (Ed.), Reducing prejudice and discrimination (pp. 23–46). Mahwah, NJ: Erlbaum. Street, Richard L. Jr. 1982. Evaluation of noncontent speech accommodation. Language and Communication 2, 13–31. Street, Richard L., Jr., Brady, Robert M., and Putnam, William B. 1983. The influence of speech rate stereotypes and rate similarity on listeners’ evaluations of speakers. Journal of Language and Social Psychology 2, 37–56. Sutton, Robbie M. and Douglas, Karen M. (eds.). 2008. Celebrating two decades of linguistic bias research [Special anniversary issue]. Journal of Language and Social Psychology 27(2). Tajfel, Henri. 1974. Social identity and intergroup behavior. Social Science Information 13, 65–93. Tajfel, Henri and Turner, John C. 1986. The social identity theory of intergroup behavior. In: Stephen Worchel and William G. Austin (eds.), Psychology of intergroup relations (pp. 7–24). Chicago: Nelson-Hall.

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Laura K. Guerrero

3 Interpersonal functions of nonverbal communication Abstract: Nonverbal communication helps people accomplish several interpersonal goals, such as: forming first impressions, developing and maintaining relationships, communicating dominance, and expressing emotions. This chapter examines research on these topics, including work on the what-is-beautiful-is-good hypothesis, thin slice impressions, positive involvement (immediacy), flirtation, the bright and dark sides of nonverbal dominance, and the expression of affectionate and hostile emotions. Dyadic patterns related to immediacy, dominance, and emotional expression are also discussed. Key Words: dominance, emotional expression, first impressions, flirting, immediacy, nonverbal communication, physical attractiveness

1 Introduction Playwrights and poets have long understood the critical role nonverbal communication plays in close relationships. In A Winter’s Tale, Shakespeare writes that there was “language in their very gestures” (Act 5, Scene 2) and poet Emily Dickinson declares “I came to buy a smile – today – but just a single smile.” Darwin (1872) was among the first to study nonverbal communication scientifically by observing how humans and other animals express emotion. By the mid-20th century, several prominent scholars in fields such as psychology, anthropology, and ethology conducted groundbreaking work on nonverbal communication (Knapp 2012). Communication scholars also have a history, albeit shorter, of recognizing the importance of nonverbal messages. Watzlawick, Beavin, and Jackson (1967) forwarded three revolutionary propositions that helped launch the study of nonverbal communication within the communication field: (1) one cannot not communicate during interpersonal interaction because any behavior that is perceived by another person, including silence and inaction, can be interpreted as meaningful; (2) people communicate using both digital (primarily verbal) and analogic (primarily nonverbal) codes; and (3) all messages are evaluated at both a content and relational level, with the relational level referring to the meaning that people assign to a message based on the situation, the relationship people share, and the nonverbal cues people exchange. This chapter examines the relational side of messages by summarizing literature on four of the primary functions nonverbal communication serves during

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interpersonal interaction: (1) forming impressions, (2) developing and maintaining relationships, (3) sending messages related to dominance, and (4) expressing emotion. The functional approach focuses on the usage and meanings of various nonverbal behaviors, along with the goals those behaviors fulfill (Burgoon, Guerrero, and White 2013; Patterson 1983). Scholarly knowledge regarding each function is much broader than depicted here since this chapter focuses rather narrowly on nonverbal communication in developing and established relationships.

2 Nonverbal communication: Definition and codes Not all nonverbal actions are associated with relational meanings or even considered to be communication. Most communication scholars regard behaviors that are neither directed toward a receiver nor interpreted as meaningful by a receiver as behavior rather than communication (Guerrero and Floyd 2006). Scholars adopting a message perspective define nonverbal communication as behaviors other than words that form a socially shared coding system, are used regularly and interpreted consensually within a speech community, and are typically sent with intent or interpreted as intentional by receivers (Burgoon, Guerrero and Manusov 2011). A complementary perspective, called the process-based approach (Guerrero & Floyd, 2006), includes as communication any behaviors that are sent with intent or interpreted as meaningful by a receiver. Scholars have also defined nonverbal communication by identifying the codes that constitute it. A code is a channel or systematic means through which meanings are encoded and decoded (Burgoon et al. 2011). Words are one type of code. Nonverbal codes include kinesics (body, face, and eye movement, including gestures, posture, and facial expression), proxemics (human space, including conversational distancing and the use of territories), haptics (touch), vocalics (the way people say words, including pitch, volume, pace, inflection, fluency, and accent; as well as pauses and silences); appearance and adornment (physical features including how attractive someone is, height, and hair color; as well as the way people adorn themselves using clothing, jewelry, body markings, and perfume); environmental features and artifacts (flooring, wall hangings, the shape of a room, and furniture arrangements); and chronemics (elements of time, such as punctuality, talk time, wait time, amount of time spent together, and response time before answering a text message). These codes are all implicated in the functions discussed next, although some codes are more relevant to certain functions than others.

3 Forming impressions Nonverbal communication helps people form impressions of one another. Impression formation, or person-perception, is a decoding activity that involves making

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judgments about a person based on appearance or behavior. These initial impressions often set the stage for developing (or not developing) relationships. When people first meet, they try to fill in information gaps by making attributions about one another’s personality and behavior. One way people do this is by creating a consistent set of perceptions based on external nonverbal cues. These external cues (e.g., smiling) are used to make attributions about internal qualities (e.g., friendliness). Receivers consider both static and dynamic nonverbal cues when forming impressions of others. Physical appearance cues, such as attractiveness and height are static. Although some of these cues can be manipulated in preparation for an interaction (e.g., a woman may apply makeup before going on a date), once an interaction ensues they remain constant. Dynamic cues, such as facial expressions and vocal tone, can change rapidly during an interaction.

3.1 Static cues Physical attractiveness is one of the most commonly studied static cues. According to the what-is-beautiful-is-good hypothesis, people perceive good looking people as possessing an array of positive internal characteristics, such as intelligence, sociability, and trustworthiness (Dion, Berscheid and Walster 1972). Meta-analyses suggest that this beauty bias is stronger for judgments about social attributes, such as confidence and extraversion, than cognitive attributes, such as intelligence and mental health (Eagly et al. 1991). There is also an actual (rather than merely perceived) relationship between social skills and physical attractiveness, with attractive individuals appearing more self-confident than less attractive individuals (Feingold 1992), presumably because people treat attractive people better, leading them to feel more confident. Even in virtual environments, people assigned to be represented by attractive avatars engage in more confident behavior, such as standing closer to other avatars, than do people assigned to less attractive avatars (Yee and Bailenson 2007), which suggests that people believe attractive individuals act differently than unattractive individuals. However, being physically attractive does not lead to uniformly positive perceptions. The what-is-beautiful-is-conceited hypothesis specifies that people who are especially attractive are also perceived as snobby, materialistic, vain, and self-involved (Dermer and Thiel 1975). Given that people associate physical attractiveness with a host of positive internal characteristics, it is not surprising that physical attractiveness often acts as a screening device narrowing the field of potential dating partners. Dating service studies have shown that physical appearance is one of the best predictors of whether people click on someone’s videotaped profile (Woll 1986) or desire further interaction after speed-dating (Kurzban and Weeden 2005). On Facebook, people are especially likely to want to pursue friendships with members of the opposite sex who post attractive pictures of themselves (Wang et al. 2010).

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The most physically attractive people, however, do not always get the most dates. The matching hypothesis suggests that individuals tend to pair up with people who are similar to themselves in terms of level of physical attractiveness (Berscheid and Walster 1974). So people who consider themselves moderately attractive will look for partners who are also moderately attractive rather than looking for the most attractive person available. This is because people worry about being rejected by individuals who are more attractive than themselves. People also generalize similarity in physical attractiveness to similarity in other areas, leading them to think they will be more compatible with someone who possesses a level of physical attractiveness comparable to their own. The matching hypothesis applies to friendships as well as romantic relationships (Feingold 1988), differentiates between people who are really dating versus those who are posing as a couple (Murstein 1972), helps determine who has a good time on a date (Berscheid and Walster 1974), and predicts who will have a happy relationship (Zajonc et al. 1987). In addition to general physical attractiveness, specific nonverbal behaviors such as voice and body type influence initial impressions. The what-sounds-beautiful-is-good hypothesis specifies that people with attractive voices are rated more favorably on characteristics such as agreeability, friendliness, and trustworthiness (Zuckerman and Driver 1989). People also believe themselves to be more similar to individuals with attractive versus unattractive voices (Miyake and Zuckerman 1993). In terms of body type, within the United States, mesomorphs, whose weight and height are in balance, are perceived somewhat more positively than ectomorphs, who are thin in relation to their height, and much more positively than endomorphs, who are heavy in relation to their height (Portnoy 1993). During speed-dating sessions, those with a healthy body mass index are more likely to be regarded favorably and considered for future dates that are those with an unhealthy body mass index (Kurzban and Weeden 2005).

3.2 Dynamic cues Dynamic cues can modify or add to the impressions that people make based on appearance. Albada, Knapp, and Theune (2002) advanced interaction appearance theory to explain how interaction can modify people’s first impressions about attractiveness. This theory rests on four principles: (1) people tend to believe that an ideal partner should be physically attractive and a good communicator; (2) people communicate with a wide range of individuals, including some people whom they do not consider to be optimally physically attractive; (3) when people start to develop a satisfying relationship with a person who is a good communicator but not optimally physically attractive, their beliefs about what constitutes an ideal partner are challenged; and (4) to resolve this inconsistency, they re-evaluate their partner as being more physically attractive. Albana et al. (2002) showed that positive interaction modified original perceptions of physical attractiveness as pre-

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dicted by the theory. Negative interaction had a stronger modifying effect than positive interaction, such that participants downgraded a person’s physical appearance following a negative interaction more than they upgraded a person’s physical appearance following a positive interaction. Thus, physical appearance alone is not enough to shape initial impressions, especially if a person’s communication does not match expectations based on such stereotypes as the what-is-goodis-beautiful hypothesis. Other research has examined specific dynamic cues that are related to receiver judgments of personality. Much of the research in this area has utilized Brunswik’s (1956) lens model as a theoretical framework. This model focuses on encoding (or ecological validity) that displays an element of a sender’s personality. Decoding (or cue utilization) occurs when receivers make inferences about a sender’s personality based upon the sender’s behavior. Both encoding and decoding are influenced by the context in which communication occurs. Research in this area has shown that low levels of smiling are decoded as a sign that someone is a serious person, speaking with a hand over one’s mouth while smiling is decoded as a sign of shyness, and speaking in a tense voice and turning one’s head away while speaking are decoded as signs of being uptight (Ferrari and Swinkels 1996). In initial interactions, these first impressions often affect whether a person wants to get to know someone better. Certain nonverbal cues also make a person appear more agreeable and likable. Of these, smiling is the most important. Compared to people with neutral facial expressions, people who are smiling are perceived as more sincere, sociable, and competent, as well as less independent and masculine (Reis et al. 2012). On Facebook, people who are smiling and engaging in social interaction with others in their photos tend to be rated as more expressive and outgoing than those who are not (Weisbuch, Ivcevic and Ambady 2009). On email, people perceive others as more likable when they include a smiley emoticon in their messages (Byron and Baldridge 2007). These types of associations help explain a phenomenon called thin slice impressions (Ambady, Krabbenhoft and Hogan 2006). Thin slice impressions occur when people base initial judgments about a person on a short sample (less than five minutes long) of dynamic behavior, such as facial expressions, posture, voice, and gesture (Ambady et al. 2006). For example, a person who smiles and expresses vocal warmth is likely judged as friendly. These thin slice impressions are often related to enduring and accurate judgments about people. For example, Ambady and Rosenthal (1993) found that thin slices of teacher behavior sampled at the beginning of the semester predicted student and principal evaluations at the end of the semester. Thin slices of managers’ (DeGroot and Motowidlo 1999) and salespeople’s (Ambady et al. 2006) voices not only predict initial impressions, but are also related to job performance and supervisor evaluations. Some scholars have cautioned that although thin slice impressions are often more accurate than chance, they cannot always be trusted (Ames et al. 2010).

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People vary in their confidence levels when judging people based on nonverbal cues. Those who are confident that their first impressions are right are not necessarily more accurate in their perceptions; however, there is evidence that a lack of confidence in the accuracy of first impressions based on nonverbal cues is indicative of inaccuracy (Ames et al. 2010). At least three factors may influence the accuracy of first impressions based on thin slices of behavior (Human et al. 2012). First, some senders are more transparent and easier to judge. Second, some people are better decoders of nonverbal information. Third, people who are motivated to access someone’s personality are often more accurate, especially in terms of noting the distinctive characteristics of an individual. (See Gifford, 2012, for other conditions that make it difficult to judge personality accurately from nonverbal behavior.)

4 Developing and maintaining relationships The research on impression formation helps explicate how nonverbal communication brings people together by fostering positive person perceptions. Nonverbal communication also helps people develop, intensify, and maintain their relationships. Theory and research on relationship development traditionally focused on self-disclosure as a vehicle for creating and intensifying intimacy. For example, according to Altman and Taylor’s (1973) social penetration theory, relationships become closer as the breadth, frequency, and eventually depth of self-disclosure increase. Many researchers took up this mantle by equating self-disclosure with relational closeness and intimacy. However, in doing so scholars overlooked the role that nonverbal communication plays in the process of relationship development. Indeed, when discussing social penetration theory, many scholars fail to mention that Altman and Taylor (1973) included nonverbal and environmental factors, such as kinesics, touch, distancing, and private spaces, as key components within the process of relationship development. According to the theory, as people get more comfortable with one another, they not only gradually increase their level of self-disclosure, but also their level of nonverbal affiliation. Berger and Calabrese’s (1975) uncertainty reduction theory also highlighted the role nonverbal communication plays in relationship development. This theory is predicated on the assumption that people feel a need to predict and explain the behavior of others. Therefore, they want to reduce uncertainty in initial interactions, especially if they anticipate interacting again in the future. The theory also specified that nonverbal expressions of affiliation are positively associated with low levels of uncertainty and high levels of intimacy, reciprocity, similarity, and liking. Research has confirmed this early theorizing by showing that nonverbal behaviors are related to liking and relationship development, especially when they are reciprocated (Burgoon, Stern, and Dillman 1995).

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4.1 Positive involvement behaviors The nonverbal cues that communicate liking and intimacy have variously been referred to as immediacy or positive involvement behaviors. In line with Mehrabian’s (1981) original conceptualization, Andersen (1985) defined nonverbal immediacy as a set of behaviors that indicate physical and psychological closeness, approachability, sensory stimulation, interest, and interpersonal warmth. Prager and Roberts (2004) used the term positive involvement to describe behaviors that commonly reflect both positive affect and involvement, such as gaze, smiling, forward leans, affectionate touch, and affirming head nods. Some scholars prefer the term positive involvement because they view immediacy and affect as orthogonal dimensions that underlie broad concepts such as intimacy and dominance (Dillard, Solomon, and Palmer 1999). Under this view, affective cues such as smiling, scowling, vocal warmth, and sarcastic tone determine whether immediacy cues (such as forward leans, an animated voice, and eye contact) are interpreted as reflecting liking and intimacy, or something else, like dominance or aggression. Despite the use of different terms, there is consensus regarding the specific nonverbal cues that reflect positive involvement, liking, and intimacy. These include: close proxemic distancing, touch, direct body orientation, open posture, increased or sustained gaze that is evaluated as friendly rather than intimidating, smiling, and vocal qualities that communicate warmth, expressiveness, and relaxation (Andersen 1985; Coker and Burgoon 1987; Patterson 1983). Research on positive involvement or immediacy is also consistent in demonstrating the importance of reciprocity. Indeed, several theories of nonverbal intimacy (see Burgoon, Stern and Dillman 1995; Chapter 10, Burgoon, Dunbar and White) rest on the following related principles: (1) Patterns of reciprocal positive involvement cues produce the most intimate interactions and occur in the closest and most satisfying relationships, and (2) Receivers are most likely to reciprocate or converge to the positive involvement behaviors of senders who they like or consider to be rewarding. In support of these principles, married partners engage in similar levels of public touch toward one another (Guerrero and Andersen 1994), and people who like one another echo each other’s body positions, adopt mirror-image postures, and use similar gestures (Maxwell et al. 1985). Positive involvement behavior also changes as relationships move from casual to close. People are especially affectionate when moving their romantic relationships toward more commitment. Once a couple is fully committed, there is often a drop in immediacy. For example, a study that involved observing people waiting in lines at movie theaters and zoos showed that couples in serious dating relationships touched about twice as much as casually dating or married couples (Guerrero and Andersen 1991). A similar curvilinear relationship emerged in a study looking at level of intimacy and private touch (Emmers and Dindia 1995). These findings support a principle of nonverbal escalation, in that nonverbal immediacy cues tend to increase as a romantic relationship escalates toward commitment and sexual

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involvement, but then decrease and level off after the relationship is fully committed.

4.2 Flirtatious behavior Positive involvement behavior communicates liking, and is therefore used to develop, intensify, and maintain a variety of relationships. Flirtatious behavior, on the other hand, expresses sexual and romantic interest, and is therefore inappropriate in most platonic relationships. Although studied most in the context of courtship, flirting also helps maintain established relationships (Henningsen 2004), including marriages (Frisby 2009). In general, flirtatious behavior is more indirect and ambiguous during the initial stages of an interaction (in part to save face if one’s advances are rejected), and then becomes bolder, more intense, and increasingly synchronized as interaction unfolds (Cunningham and Barbee 2008; Givens 2005). Ambiguous flirtatious behavior includes coy smiles and eye contact that is characterized as darting, fleeting, or room-encompassing rather than focused on the (potential) partner (Coker and Burgoon 1987; Moore 2002). After two people have secured one another’s attention and determined that interest might be mutual, flirtatious behaviors subtly communicate approachability and openness. Specific cues include maintaining an open-stance, directing one’s full body or head and shoulders toward the partner, pointing one’s feet toward the partner, sitting or standing next to the partner, or leaning to decrease the distance between oneself and the partner (Givens 2005; Grammer, Kruck and Magnusson 1998; Moore 2010; Muehlenhard et al. 1986). Men may be more likely to secure and keep a woman’s attention if they have open body positions with legs or arms extended (Renninger and Wade 2004). Eventually, flirtatious behavior may become bolder and less ambiguous. Koeppel et al. (1993) found that behavior moved from being interpreted as friendly, flirtatious, and eventually, seductive, based on increasingly higher levels of smiling, eye contact, and touch. Bold behaviors include extended mutual gaze; wider, larger smiles; and various forms of touch (Givens 2010; Moore 2002). Touch to relatively non-vulnerable areas of the body, such as the forearm, wrist, lower back and shoulders are perceived as less flirtatious than those to more vulnerable areas of the body such as the legs, neck, and face (Muehlenhard et al., 1986). Flirtation also includes unique behaviors that go beyond positive involvement. Preening behaviors, such as holding one’s head and shoulders high, standing upright, sucking in one’s stomach, pushing out one’s chest (Grammer et al. 1998), smoothing or adjusting one’s hair or clothing (Givens 2005), and licking or puckering one’s lips (Moore 2002), help people maximize their attractiveness. Other behaviors fairly unique to flirting include laughing while tossing one’s head back, tossing or playing with one’s hair, and tilting one’s head while looking up or down

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at someone (Givens 2005; Moore 2002, 2010). Men’s voices tend to switch from being high-pitched and animated during the beginning phases of flirtation, to being more low-pitched and monotone as the interaction progresses (Anolli and Ciceri 2002). Finally, flirtatious interaction is often characterized by increasingly synchronized behavior. Cunningham and Barbee (2008) noted that dating rituals such as dancing may help potential partners determine if they are compatible by providing a testing ground for synchronization. When partners flirt, they tend to match one another’s posture, body positioning, vocal behavior, and laughter (e.g., Grammer et al. 1998; Muehlenhard et al. 1986). Thus, just as reciprocity is important for developing and maintaining relationship via positive involvement cues, so is synchronization important for creating intimacy via flirtatious behavior.

5 Communicating dominance Intimacy is only one of the fundamental messages sent by nonverbal communication; dominance is the other (Burgoon and Hale 1984). Communication scholars have conceptualized dominance as a set of interactional behaviors that are used to gain power and influence (Burgoon et al. 2011). Power, which is the ability to influence other people while resisting the influence attempts of others, is based on authority, expertise, and control of valuable resources (Burgoon, Johnson, and Koch 1998). Thus, power gives people more tools with which to enact dominance, but power and dominance are distinct concepts. There is also a distinction between perceived power and actual power. Hall, Coats, and Smith Le Beau’s (2005) meta-analysis revealed that high power individuals (i.e., those who have high status or a dominant personality) use more open body positions, closer interpersonal distances, louder speech, and more interruptions than low-power individuals. Thus, a limited number of nonverbal cues distinguish high- and low-power individuals. However, this same analysis showed that the list of nonverbal behaviors that are perceived as reflecting dominance is longer, and includes being facially expressive, looking at others, gesturing more, smiling less, shifting posture more often, engaging in less self-touch, and speaking louder. Individuals who do not have high status, or are in equal-status relationships, may be able to use these behaviors to wield more influence. Dunbar and Abra (2010) found several nonverbal behaviors to be related to both partner and observer perceptions of dominance, including speech fluency, overall vocal expressiveness, illustrator gestures, facial pleasantness, body movement, and less anxious movement. Within the context of interpersonal relationships, dominance has a bright and dark side. On the bright side, partners can influence one another in ways that help them solve problems and make beneficial changes in their relationship. This type

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of influence is often accomplished by using dominant communication that reflects social skill (Burgoon and Dunbar 2000). On the dark side, imbalances in dominance and power are sometimes related to deeper issues rooted in intimidation, control, and even violence.

5.1 The bright side of nonverbal dominance Relational partners have many verbal and nonverbal behaviors at their disposal when they want to influence one another. Nonverbal cues reflecting both dominance and social skill are especially likely to be successful in gaining compliance, solving problems, and eliciting long-term change. These behaviors can be grouped into three broad categories based on whether they primarily reflect (a) poise and self-assurance, (b) panache or dynamism, or (c) skill in interaction management (Burgoon and Dunbar 2000). Behaviors reflecting poise and self-assurance include: asymmetrical leg and arm positions; sideways leaning; open arm and body positions; kinesic animation; a low amount of swiveling, adaptors, and random movement; fluent speech; facial pleasantness and smiling; eye contact; a moderately fast and loud voice; and relatively high levels talk time (Guerrero and Floyd 2006). People who have panache communicate in a “dramatic, memorable, and attentiongrabbing communication style that is immediate, expressive, and energetic” and includes nonverbal behaviors such as close distancing, gaze and direct body orientation, forward lean, vocal and kinesic expressiveness, and faster, louder speech (Guerrero and Floyd 2006: 156). Finally, nonverbal behaviors that facilitate smooth interaction management and conversational control include speaking fluently, engaging in smooth turn-switching, talking for an extended time, and using eye contact when speaking, all of which can be perceived as socially skilled behaviors that contribute to better problem solving in relationships (Spitzberg and Hecht 1984). Another bright side effect of nonverbal dominance is that, in some cases, appearing dominant leads to attraction. Sadalla, Kenrick, and Vershure (1987) demonstrated that women rated men using dominant nonverbal behavior (i.e., sitting close to a person behind a desk while leaning backward slightly in a relaxed fashion and engaging in frequent gesturing) as more attractive than men using submissive behavior (i.e., looking down, nodding, and sitting farther away). In a study by Ahmetoglu and Swami (2012), low dominance was represented by a closed body position, moderate dominance by an open body position, and high dominance by an open body position and gesturing. Women rated men in the high dominance condition as most attractive. Maner, DeWall and Galliot (2008) found that participants looked longer at male faces that were rated as dominant. Research has qualified these findings by showing that dominance may only be related to attractiveness and dating desirability if a man is also rated as agreeable (Jensen-Campbell, Graziano, and West 1995) and competent (Touhey 2011).

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Thus, nonverbal behaviors that are perceived as a sign of both dominance and social skill are the most effective in fostering positive impressions. Dominant behaviors may also be especially likely to be perceived positively when they reflect prestige rather than aggression and are used in acceptable contexts, such as a game or sports contest (Snyder, Kirkpatrick, and Barrett 2008).

5.2 The dark side of nonverbal dominance Rather than using dominant behaviors that reflect social skill, people sometimes use intimidation or control to get what they want. Intimidating nonverbal behaviors include: a hard stare, angry face, loud voice, extended silence, standing over someone, and encroaching upon someone’s personal space (Dovidio and Ellyson, 1985; Montepare and Dobish 2003). Behaviors perceived as threatening or controlling typically have negative effects on relationships. Ostrov and Collins (2007) found that partners who displayed intrusive touch and resource control (by not letting each other touch or sort the cards during a game), tended to report being more aggressive and having more arguments during a collaborative problem solving task. Raising one’s voice was also associated with intrusive touch for females, and resource control for males. Dominance cues that reflect intimidation and control are sometimes a manifestation of power imbalances within relationships. For example, the chilling effect occurs when the less powerful person in a relationship is silent and withholds complaints because he or she worries that speaking up will produce negative relational consequences, such aggression or breakup (Roloff and Cloven 1990). Several conditions make people more susceptible to the chilling effect, including: being more dependent on, more invested in, and more committed to the relationship than one’s partner; and having less power than one’s partner (Roloff and Solomon 2002; Knobloch, and Fitzpatrick 2004). Intimate terrorism is an enduring and strategic pattern of behavior that involves using threats and violence to control one’s partner (Johnson and Ferraro, 2000), leading to a lopsided power imbalance in a relationship (Olson, 2002). In around 87 % of cases, men are the perpetrators of intimate partner violence and women are the victims (Graham-Kevan and Archer 2003). Johnson (2006) noted that intimate terrorism is related to the chilling effect, in that the individual who is being controlled usually becomes increasingly fearful of speaking out. Intimate terrorism typically increases in severity and frequency over time, and the perpetrators of intimate terrorism usually become more possessive and violent when their partners resist or rebel against their controlling behavior (Graham-Kevan and Archer 2003; Johnson and Ferraro, 2000). Violent tactile behaviors, as well as nonverbal forms of intimidation, are obvious instruments for inflicting intimate terrorism. Yet research has yet to uncover specific nonverbal behaviors that perpetrators use to control their partners.

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Nonverbal behaviors are also implicated in the cycle of intimate terrorism in another way – perpetrators of intimate terrorism not only engage in violent behaviors, they also use especially affectionate, apologetic, and ingratiating behaviors to compensate for their hurtful behavior (Shackelford et al. 2005). These positive behaviors, many of which are undoubtedly nonverbal, such as increased affection, are also controlling because they are designed to keep the partner in the relationship despite its tumultuous nature.

5.3 Relative power As research on the chilling effect and intimate terrorism shows, the power balance in a relationship is negotiated dyadically. Dyadic power theory (Dunbar 2004) helps explain how people negotiate this balance by focusing on relative power, which is the extent to which one partner has power in comparison to the other. According to the theory, people who have high relative power do not need to display dominant behavior because they already have considerable control in their relationships. This theory does not consider cases where power is rooted in intimate terrorism; instead power imbalances stem from one partner caring more, being more invested, having more resources, or depending more on the relationship. Dyadic power theory also predicts that people with low relative power are unlikely to exhibit much dominant behavior, either because of the chilling effect or because they do not believe their attempts at dominance will succeed (Dunbar and Burgoon 2005). Finally, dyadic power theory suggests that partners who have similar levels of power are most likely to engage in high levels of dominant behavior because they need to assert themselves, negotiate terms, and compete for resources. Thus, the theory predicts that there is an inverted u-shaped curvilinear relationship between relative power and nonverbal displays of dominance. Research has shown that nonverbal behavior does indeed differ based on relative power, although not always in the directions originally predicted. In line with dyadic power theory, Dunbar and Burgoon (2005) found that people who perceived themselves as having slightly more or less power than their partners displayed more nonverbal dominance than did people who perceived themselves as having much more or less relative power. Contrary to the theory, however, people who perceived themselves as low in relative power interrupted more and used more illustrator gestures, perhaps as a way to try to gain the power they lack. Other contrary findings surfaced in a study manipulating the degree to which members of an unacquainted dyad had control of a task-related activity (Dunbar and Abra 2010). Participants in the low power position showed the least dominance, whereas those in the equal- and high-power positions did not differ significantly from one another. Research is needed to determine the exact nature of the association between relative power and displays of dominance.

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6 Expressing emotion Aside from the fundamental messages of intimacy and dominance, nonverbal cues also express emotion (see Chapter 12, Planalp and Rosenberg). Emotions are discrete, relatively transitory states, marked by positive or negative affect and changes in physiological activation, which occur in response to a specific precipitating event (Burgoon et al. 2011). Emotions are commonly expressed simultaneously through multiple nonverbal channels, including facial, vocal, bodily, activity (e.g., slamming a door or taking drive), and physiological (e.g., blushing, yawning) cues (Planalp, DeFrancisco, and Rutherford 1996). Emotional expressions are influenced by at least two forces – action tendencies and display rules. Action tendencies are innate, biological impulses that are emotion-specific and have evolved to be adaptive in particular situations (Lazarus, 1991). For example, the action tendency for anger is to attack. Display rules are cultural prescriptions for how people should manage their emotional expression in socially appropriate ways (Ekman 1973). So a mother might curb her expression of anger because she believes that good parents are patient and stay calm. Although some scholars see display rules as ways of modifying one’s expression so that it no longer truly reflects the emotions a person is feeling (e.g., Ekman 1973), scholars adopting a behavioral ecology approach believe that people’s emotional expressions are a true reflection of their social motives (Fridlund and Duchaine 1996). Under this view, a mother who curbs her anger is showing that she cares about her child; her feelings of care and anger combine to shape her expression. Since emotional expression is one of the primary functions of nonverbal communication, it has been studied extensively (see Fridlund and Russell 2006 for a review). This chapter focuses narrowly on research that has implications for interpersonal interaction, including: nonverbal behaviors associated with affectionate and hostile emotions; and patterns of expression related to feedback loops, contagion, and motor mimicry.

6.1 Affectionate emotions: Joy and love Joy and love are affectionate emotions that help sustain healthy relationships. Joy is expressed through many nonverbal cues, especially smiling. Scholars have distinguished between genuine smiles that reflect real happiness and fake smiles that are posed (Ekman, Davidson, and Friesen 1990). In line with the behavioral ecology approach, genuine smiles are also associated with cooperation and prosocial behavior (Brown, Palameta, and Moore 2003; Lakin, Chartrand, and Arkin 2002). In one study, people excluded from a group had more positive reactions to those who exhibited genuine versus fake smiles (Bernstein et al. 2010). Genuine smiling does more than signal that a person is happy, it also signals that a person is cooperative and agreeable, which can pave the way for positive social interaction.

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Joy is also associated with vocal characteristics, body movement, and touch. Vocal characteristics include moderately loud volume, moderately high pitch, vocal animation, rapid and varied tempo, and laughter (see Burgoon et al. 2010 for a review). Joy is also associated with bouncy and bubbly behavior as well as bright, glowing faces (Shaver et al. 1987). When participants judged the emotions of computer-generated mannequins posed in various positions, mannequins with raised arms and a backward head tilt were rated as happy (Coulson 2004). Hertenstein et al. (2006, 2009) investigated how people communicate joy, along with other emotions, via touch. In the 2006 study, encoders from behind a curtain used swinging, shaking, and lifting hands as ways to communicate joy tactilely. In the 2009 study, when encoders and decoders were not separated by a curtain, encoders used squeezing, patting, lifting, shaking and hugging to communicate joy. Joy was decoded from these cues at a rate greater than chance. Expressions of love occur less frequently than expressions of joy. Saying “I love you” is the most common and direct way of expressing love, but people also communicate love nonverbally. Marston and Hecht (1999: 286) noted that, “lovers report roughly equal numbers of verbal and nonverbal behaviors that communicate love in their relationships.” Nonverbal ways of communicating love include spending time together, doing special things for someone, showing affection, using positive forms of touch (such as hugging or kissing), giving gifts, sitting close, exchanging rings, and having sex (Lemieux 1996; Marston and Hecht 1999). Mutual gaze can also temporarily increase feelings of love (Kellerman, Lewis, and Laird 1989). Vocal qualities associated with love include softer voices and vocalizations such as “oooh” and “aaah” (Hatfield et al. 1995). Finally, love is associated with interlocking fingers, stroking and rubbing someone’s hand (Hertenstein et al. 2006), and moderately intense hugging (Hertenstein et al. 2009), with decoders able to interpret touch as reflecting love (rather than a different emotion) at a rate greater than chance.

6.2 Hostile emotions: Anger and contempt People experience hostile emotions in their relationships, including anger, contempt, envy, and resentment. Of these, anger and contempt have received the most research attention. Although people can communicate angry feelings in constructive ways, it can be difficult to do so because of the attack action tendency associated with anger (Lazarus 1991). Body cues associated with anger include walking with stronger, heavier, and longer strides (Montepare, Goldstein, and Clausen 1987), standing with an erect posture, tilting one’s head backward, and raising one’s arms (Coulson 2004). Activity cues such as driving a car fast, clenching one’s fist, stomping, throwing things, and slamming a door are also associated with anger (Planalp et al. 1996; Shaver et al. 1987). Facially, anger is communicated via furrowed eyebrows, lips in a square shape or pressed together, and eyes bulging

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or in a fixed stare (see Burgoon et al. 2010 for a review). An angry voice typically sounds loud and fast, with a rising pitch if the person feels frustrated, or a low pitch if the person feels annoyed or threatened (Scherer and Wallbott 1994). Anger is also expressed using touch. Hertenstein et al. (2006, 2009) found that, from behind a curtain, anger is communicated by squeezing, hitting, and trembling; in open space, anger is encoded and decoded through pushing and shaking that is strong and moderately intense, but of short duration. Violent behavior, including touch, is also related to anger. Among high school students involved in abusive relationships, over 70 percent of victims interpreted their partner’s violent behavior as reflecting anger (Henton et al. 1983). Nearly 54 percent of aggressors also saw their own violent behavior as motivated by anger. Anger is also associated with aggression in adult romantic relationships. Ellis and Malamuth (2000) found that anger/upset shared a .31 correlation with aggression. As of yet, however, little if any research has examined which specific forms of nonverbal aggression are fueled by anger. Expressions of contempt are even more destructive to relationships than are expressions of anger (Gottman and Krokoff 1989). Anger tends to be associated with “short-term attack responses but long-term reconciliation, whereas contempt is characterized by rejection and social exclusion” (Fischer and Roseman 2007: 103). Contempt can be communicated nonverbally by raising and tightening the corner of one’s lip, looking down at someone, furrowing one’s brow as if confused, raising one’s eyebrows as if shocked or surprised, displaying facial expressions that show astonishment, rolling one’s eyes, and speaking in a sarcastic tone (e.g., Ekman and Friesen 1986; Gottman 1994; Scherer and Wallbott 1994). Sarcasm is communicated through speech that is louder, slower, and more low-pitched than normal (Rockwell 2000). These types of nonverbal behaviors can escalate conflict. Indeed, subtle facial expressions that communicate disgust and contempt are among the best predictors of relational dissatisfaction and eventual decline (Gottman 1994). When husbands use contemptuous expressions, wives tend to display less positive affect and believe that relational problems are severe and will be difficult to solve (Gottman, Levenson, and Woodin 2001). Violent husbands use more contemptuous behavior than non-violent husbands (Holtzworth-Munroe et al. 1988). Studies of adolescents have also shown that girls perceive nonverbal expressions of contempt to be especially hurtful because they signal exclusion and imply that they are not as good as others are (Underwood 2004).

6.3 Dyadic patterns of emotional expression In addition to communicating particular emotions, nonverbal expressions of emotion influence how both senders and receivers feel, as well as how they communicate. The facial feedback hypothesis provided the foundation for much of this work

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by showing that the movement of facial muscles sends signals to the brain, which then cause people to experience emotions consistent with the expressions formed by those muscles (Ekman, Levenson and Friesen 1983). Other researchers have proposed and supported similar hypotheses for vocal (Hatfield et al. 1995) and postural (Duclos et al. 1989) behaviors. Cappella (1993) advanced the interpersonal facial feedback hypothesis, which specifies that if a receiver mimics a sender’s expression, the receiver will likely feel some of the same affect that the sender is experiencing. Work on motor mimicry and emotional contagion is based on similar reasoning. Motor mimicry occurs when a receiver reacts nonverbally to something that happens to a sender as if she or he is experiencing it, such as a mom wincing when she watches her son skin his knee (Bavelas et al. 1986). Bavelas and her colleagues found evidence of motor mimicry across emotions ranging from pain, embarrassment and disgust, to laughter, smiling, and affection. Other researchers have focused specifically on facial mimicry, which occurs when a receiver matches the facial expression of a sender (McIntosh 2006). Buck and Powers (2012) noted that neuroscientists emphasize the innate connections between motor mimicry, modeled behavior, and the acquired ability to feel empathy, whereas communication scholars focus on motor mimicry as a way of communicating support and similarity. Motor mimicry is also theorized to promote larger patterns of emotional contagion. Work on the emotional contagion effect (Hatfield, Cacioppo, and Rapson 1994) suggests that people “catch” the emotions of those around them. This is in part because people often mimic the nonverbal cues of those around them. Mimicked facial expressions and body movements are theorized to trigger physiological changes that create a mood-contagion loop, with the changes in facial expression and body movement signaling the brain to feel whichever emotion is consistent with those changes. Motor mimicry and emotional contagion are fairly common occurrences, especially in the context of social and personal relationships. Although some evidence suggests that people are less likely to mimic facial displays that convey low intensity positive emotion compared to high intensity positive emotion, high intensity negative emotion, or low intensity negative emotion (Fujimura, Sato, and Suzuki 2010), other research has demonstrated that people mimic even fleeting and relatively weak emotions similar to those occurring in casual interactions (Hess and Blairy 2001; Wild, Erb, and Bartels 2001). Emotional contagion extends beyond face-to-face interaction. Hancock et al. (2008) induced some participants to feel sad and others to feel neutral before engaging in computer-mediated communication. The participants in the sad condition used more sad words, typed fewer words overall (similar to having less talk time) and engaged in slower message exchange compared to those in the neutral condition. Receivers in the sad condition experienced less positive affect than those in the neutral condition.

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Emotional contagion and facial mimicry may be especially strong when people know and like one another (Kimura, Daibo, and Yogo 2008; McIntosh 2006). These patterns of emotional expression may help people feel comfortable with one another by increasing perceptions of similarity and helping people feel in sync. Hatfield and her colleagues (1994) argued that because emotional contagion leads to more synchronized interaction, it also fosters attraction, liking, and rapport. In group work settings, contagion of positive emotions can reduce conflict and increase cooperation (Barsade 2002).

7 Conclusion Nonverbal communication plays a critical role in interpersonal interaction. Working alone or in concert with verbal cues, nonverbal behaviors fulfill many interpersonal functions, including helping people: form impressions, develop and sustain relationships, negotiate the power balance in their relationships, and express emotion. Although not an exhaustive list of the many functions nonverbal communication serves, these four functions are instrumental in the context of interpersonal interaction. In addition to understanding how nonverbal communication accomplishes these goals, it is imperative for scholars to understand dyadic patterns related to these functions. Relationships are shaped by the reciprocal (or nonreciprocal) exchange of positive involvement behaviors, the negotiation of relative power, and patterns of mimicry and emotional contagion. This research showcases that nonverbal communication is truly an interpersonal phenomenon.

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Nicholas A. Palomares

4 The goal construct in interpersonal communication Abstract: Although scholars invoke the goal construct to understand interpersonal communication, comprehensive and consistent conceptualizations of the construct are difficult to find in the literature. Much research a) does not define the goal construct leaving it as a given or primitive term, b) implicitly suggests a definition, or c) provides only a partial definition. Likewise, scholars often conflate goals with related but conceptually distinct constructs. The current chapter addresses these concerns. First, the goal construct is explicitly defined: Goals are mental representations of a desired end-state that can reside in hierarchies and be set at various levels of specificity. Next, goals are differentiated from related constructs. Finally, three ways in which the goal construct currently resides in interpersonal communication are demonstrated – goal activation, goals and interpersonal relationships, and goal inference processes. Key Words: goals, conversation, social interaction, cognition, relational communication, goal inferences, constraints, goal activation, message production and processing

1 Introduction The goal construct maintains a central place in understanding interpersonal communication. Many scholars invoke the goal construct to elucidate their theoretical and empirical efforts. The prominence of goals in communication is demonstrated by several books (Berger 1997; Wilson 2002) and edited volumes (Cody and McLaughlin 1990; Daly and Wiemann 1994; Greene 1997; Tracy 1991) that showcase the construct. The goal construct has been employed in at least three consequential domains of interpersonal communication. First, goals influence communicative behavior in general (Wilson 2002) and lead to plans, which result in conversational actions (Dillard 2004). For instance, integrative and distributive tactics in serial arguments depend on the goals people pursue in conflict episodes (Hample, Richards, and Na 2012). The level of politeness employed in messages varies across relationship initiation, intensify, and disengagement goals (Wilson et al. 2009); and during computer-mediated communication, people with affinity goals agree more, whereas those with disaffinity goals tended to disagree (Walther et al. 2010). Second, relational processes are also goal contingent. For example, when an achievement goal was primed, people liked their study friends more than their party friends, but when a socializing goal was

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primed, they liked their party friends more (Fitzsimons and Fischbach 2010). Goals have been found to be indirectly associated with increased relational satisfaction through tactic use (Hample et al. 2012), and marital satisfaction depends on whether prioritized marriage goals are reached (Li and Fung 2011). Third, goals play a role in personal well-being (Wiese 2007). For instance, self-esteem decreased upon goal failure but increased with goal achievement (Bongers, Dijksterhuis, and Spears 2009). Likewise, people with an achievement goal were in a relatively better mood when confronted with a situation conducive to fulfilling the goal (Chartrand and Bargh 2002). Also, people unable to obtain an important goal experienced more negative affect than those who reached their goal (Moberly and Watkins 2010). Having conflicting goals is associated with depression (Kelly, Mansell, and Wood 2011). Message production, personal relationships, and well-being are understood with reference to goals. Although the goal construct adds explanatory and predictive utility in efforts to understand various communicative phenomena, such as those described above and others (Liu in press; Park et al. 2011), difficult to pin down is a concise, consistent, and comprehensive answer to a seemingly simple question – what is a goal? Surprisingly, much work a) does not define goals but leaves the construct as a given or a primitive term, b) implicitly suggests a definition, or c) provides only a partial or basic definition. What is more, goals are often conflated with related but conceptually distinct constructs. Thus, whereas the goal construct is prominent in interpersonal communication, without a clear and consensual conceptualization of what constitutes a goal and what does not, contributions of the goal construct are limited. The current chapter addresses this concern. First, the goal construct is explicitly and thoroughly defined. Next, goals are differentiated from related constructs. Finally, three ways in which the goal construct currently resides in interpersonal theory and research are demonstrated. In doing so, the focus of the current chapter is on the goal construct as it pertains to the interpersonal communication literature from the last decade or two. The chapter occasionally draws on work outside interpersonal communication and beyond the time frame, but it primarily does so to facilitate an understanding of the goal construct within the previously delineated scope. The reason for these scope criteria is twofold. First, conceptualizations of the goal construct exist in other disciplines (Aarts 2012; Elliot and Fryer 2008; Fishbach and Ferguson 2007; Moskowitz 2012; see also Aarts and Elliot 2012; Moskowitz and Grant 2009). These explications provide an understanding of the psychological foundations and cognitive mechanisms of goals, but parallel conceptualizations that explicitly articulate a thorough definition from a communication science perspective are virtually nonexistent, although Dillard’s (1997) explication of several questions pertaining to goals is a notable exception. Second, although highly useful and informative accounts of the message production and conversation goals literature exist from interpersonal communication scholars

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(Berger 1997, 2002; Daly and Weiman 1994; Greene 1997; Tracy 1991; Wilson 2002), these accounts vary in the extent to which they explicitly and thoroughly define goals. Thus, the current chapter provides a thorough conceptualization of the goal construct by explicitly articulating a definition, differentiating it from related constructs, and demonstrating its use.

2 The goal construct defined Most definitions of the goal construct include, to varying degrees, some mention of an end-state. For example, goals are “desired states of affairs” (Dillard, Segrin, and Harden 1989: 19), “an individual’s desire about what state of affairs he or she wishes to possess or acquire in the future” (Bates and Samp 2011: 208), “desired end states that motivate participants’ actions” (Wilson et al. 2009: 34), “desired end states” (Caughlin 2010: 826), “ends individuals secure” (Kellermann and Park 2001: 41), or “states of affairs that people wish to attain” (Romo and DonovanKicken 2012: 408). Other definitions are less explicit in their reference to an endstate but nonetheless imply a similar focus on end states: “what people want to accomplish in a situation” (Burleson et al. 2006: 42); “general concerns about accomplishing a task, keeping a relationship together, or pursuing self-interests” (Samp 2013: 87); “a linguistic goal to say a message that will be understood by the hearer as having a particular communicative ‘intent’” (Meyer 2011: 378); a “desired outcome” (Greene and Lindsey 1989: 122); and “highly proximal generative mechanisms for the messages people produce” (Burleson and Gilstrap 2002: 44). Clearly, the goal construct contains some mention of obtaining an end-state or outcome. Simply defining goals as end-states is problematic; goals must have some connection to the psychological processes of the mind, which necessitates defining goals as mentally represented end-states. A longstanding tradition of scholarship is actually consistent with the definition of goals as mental representations of endstates and conceptualizes a goal as a cognitive construct (Berger 1989; Greene and Lindsey 1989; Tolman 1932; Wilson 1990). Unfortunately however, many definitions disregard this and do not explicitly state that goals are mentally represented and therefore reside in memory. With a cognitive conceptualization, the goal construct becomes a mentally represented end-state that agents pursue, maintain, abandon, etc. with intent, which means goals fundamentally exist in memory. Data employing neuroscience techniques are consistent with this conceptualization (Berkman and Lieberman 2009). For example, activity of the dorsolateral prefrontal cortex assessed via EEG was lower when a routine plan to achieve a goal was enacted successfully than when the plan failed and required modification to continue pursuit (Beatty and Heisel 2007); a finding consistent with the proposition that reusing a plan for a goal requires less cognitive effort than altering an

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existing plan (Berger 1997). Research using fMRI found that priming promotion goals (e.g., excel in school) activated an area in the brain associated with dispositional approach/appetitive tendencies and positive affect but is not inherently associated with goal pursuit (Eddington et al. 2007). That goals exhibit signs in brain studies is not surprising in light of evidence that goal processes are likely the result of evolution (Southgate, Johnson, and Csibra 2007; Uller 2004). These and other studies support a conceptualization of goals as mentally represented end-states that have corresponding neural correlates. One implication of this conceptualization is that they can operate consciously, implicitly without awareness of their presence, or somewhere in between (Ferguson and Porter 2010). The extent to which goals can function automatically outside conscious awareness from activation through completion varies (Chartrand and Bargh 1996). People unconsciously primed with, and therefore unaware of, a goal to achieve performed better on an intelligence test than those not primed with the goal (Bargh et al. 2001); however, goals can enter consciousness. People can leave their office and arrive at home deep in thought about unrelated activities and without remembering much of the journey, especially if the path is routinized; on the other hand, travelling home can require conscious thought when a novel path is required. In fact, unconsciously activated goals entered active thought when goal pursuit became difficult or problematic (Bongers, Dijksterhuis, and Spears 2010). That goals are mentally represented also suggests they function like other mentally represented cognitive constructs (Fishbach and Ferguson 2007), such as stereotypes (Sherman 1996), scripts (Schank and Abelson 1977), and relational schemata (Planalp 1985). Goals, therefore, vary in their level of activation or accessibility (Higgins 1996). At any given moment, some goals may be more or less likely to become activated than other goals given the specific circumstances of the situation. Furthermore, goals are connected to other mentally represented constructs. This interconnectivity suggests that the activation of a goal can trigger the activation of other constructs and that other constructs can trigger goals (Collins and Loftus 1975). For example, a professor might pursue an instruct goal with students relatively more than the professor seeks to provide guidance/advice with offspring. Likewise, ordering food is pursued in restaurants more than in offices. As a result, a professor’s contact with children will likely excite different goals than contact with students, just as restaurants trigger ordering food more than do offices. Goals can also be associated among themselves in that goals are hierarchically represented (Dillard 1997). Goal hierarchies are organized collections of superordinate and subordinate goals that are cognitively interconnected to facilitate the achievement of higher-order goals through the precursory achievement of lowerorder goals. Achieving one goal can facilitate another goal. For example, getting to know someone can promote establishing a close friendship, just as securing a

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date can encourage finding a mate or being humorous can facilitate making a good impression. Goal hierarchies can have more than two-levels. For example, purchasing grocery items facilitates cooking a roast, which facilitates eating food, which promotes survival. These goals can have additional subordinate goals; for instance, to cook a roast one must prepare meat and vegetables, get pan, preheat oven, place items into pan, etc. Hierarchies of end-states are a relatively understudied aspect of goals; yet, they are pervasive in social interaction (Berger 2002). Goal hierarchies should not be confused with goal specificity. Goal specificity is the level of precision with which a goal is set (Locke et al. 1981). A goal’s specificity can increase as it is set at progressively finer levels of detail (e.g., find information, find background, find hometown; or cook meal, cook beef, cook chuck roast with potatoes). Goal specificity does not refer to different goals that have facilitative relationships, as hierarchies do. A compliance-gaining goal, for instance, garners specificity as it moves from gain compliance to obtain favor to borrow money to borrow five dollars; each instantiation of the compliance-gaining goal has a greater level of precision or exactitude but the four goals do not reside in a hierarchy. Despite some scholars using concrete and abstract as respective synonyms for subordinate and superordinate, specificity does not imply facilitative relationships among goals. For example, borrow-five-dollars does not promote borrow-money because the goals, in a sense, are one and the same; when one successfully borrows five dollars, in other words, the person can also be said to gain compliance, obtain a favor, or borrow money depending on the level of specificity. Yet, borrow-five-dollars can facilitate buy-lunch, which promotes survival, all of which are distinct goals that reside in a hierarchy. Goal specificity seems to have meaningful effects (e.g., Palomares 2009a). Indeed, goal achievement is more likely for specific than abstract goals (e.g., study for exam two hours a day for week versus study for exam; Locke et al. 1981). Nonetheless, goal specificity is mostly neglected. Up to this point, goals have been conceptualized as mental representations of end-states. Yet, another component is needed. Goals are mentally represented endstates that people desire, which is no surprise given the cited definitions. A motivational element resides in goals (Fishbach and Fersuson 2007). Knowing how to do something does not mean a goal exists to put the procedural knowledge into action (e.g., parents know how to humiliate their children in front of classmates but they usually do not pursue the goal). Positive affect must be associated with the endstate to enlist the knowledge and transition the end-state into a desired outcome. Desire confers goal status onto end-states because people are motivated toward pleasurable and away from unpleasant experiences (Lazarus 1991). The positive affective component of a goal drives people toward the end-state. Goals are mental representations of a desired end-state. These mental representations function similarly to most cognitive structures in terms of their accessibility and interconnectedness with other cognitive representations. Goals can reside in

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hierarchies and be set at various levels of specificity. Positive affect associated with an end-state is what impregnates a goal with its motivational force. Having defined the construct, the next section distinguishing goals from related interpersonal communication constructs.

3 The goal construct differentiated The goal construct is distinct from other constructs that are often theoretically related to goals. Given these ties, confusion often exists between goals and other constructs.

3.1 Goals ≠ behavior Goals are not behavior. When someone tries to initiate a relationship by asking questions and disclosing information, the verbal behavior is goal-directed but not a goal in and of itself. The mental representation of a goal can generate behavioral indicators of goal pursuit. Nonetheless, because goals reside in cognition, they cannot be directly observed in behavior. To say that a goal can be found within a verbal utterance or a written statement is inaccurate. Goals influence behavior, and their influence can be observed in utterances or statements. Many message production theories argue that goals give rise to goal-directed behavior but nonetheless maintain a distinction between goals and behavior (Berger 2002; Dillard 2004; Wilson 2002). For example, when disengaging a relationship, people reported complimenting their partners (Wilson et al. 2009). Compliance gaining goals (e.g., stop annoying habit, get advice) affected the employment of compliance-gaining behaviors (Kellermann 2004). Goals influence behavior, but they do not reside in behavior. Because the goal construct is separate from behavior, assessing goals from behavior is “risky business. In fact, some would call it just plain bad business” (Dillard 1997: 61). Despite this warning, many recent operationalizations use behavior as a surrogate for goals. A study of advice-giver goals measured goals as the amount of effort expended. Focusing on behavior, the goal measures consequently fostered behavior-based conclusions such as, “when advice givers put more effort into certain goals (such as giving advice that is polite), recipients recognize these efforts and rate aspects of the advice accordingly” (Guntzviller and MacGeorge 2013: 96). A study on women’s goal of refusing unwanted sexual advances also conflated goals with behaviors by operationalizing goals as features of messages: “Coders assessed the degree to which the primary goal of clearly refusing the unwanted advance was evident in the women’s refusal messages” (Lannutti and Monahan 2004: 158). Fortunately though, the researchers effectively mitigated this concern with open-ended goal reports to ensure “goals were on

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women’s minds while refusing” (165). A third example states, “the relational and identity considerations that supplemented the topic avoidance were secondary goals that were simultaneously present in some topic-avoidance messages” (Donovan-Kicken et al. in press: 5). In all three examples, goals are, at least implicitly, conceptualized as mental representations, but at times the researchers nonetheless contradict that notion and treat goals as somewhat interchangeable with communicative behavior. The distinction, however, should not be glossed over because even if a goal was accessible enough to generate high levels of goal-directed behavior, it was the mental representation of the goal that produced the overt behavior. Burleson and Gilstrap (2002: 44) argued that in support situations people tend to employ four general message strategies when confronting a distressed other so much so that the “typology of behavioral strategies rather directly suggests a complementary typology of interaction goals.” Nonetheless, the conceptualizations of support strategies and corresponding support goals are distinct and thus consistent with the idea that goals are mental representations that can produce goal-directed behavior. Sometimes a strong, direct relationship exists between goals and behavior; yet at other times, goals are not manifested in overt behavior. Hence, maintaining this theoretical distinction is paramount. Preserving a separation between goals and goal-directed behavior mandates that goals can influence behavior but do not necessarily lead to behavioral changes. For example, someone can have a goal to come out of the closet that is highly accessible and for which the person is expending much cognitive energy to achieve; this same individual, however, could likewise exhibit virtually no behavioral indicators of the goal because the to-be-revealed information is extremely sensitive and difficult to articulate. Thus, goal pursuit might exhibit no behavioral indicators whatsoever. In fact, people can experience unintentional (i.e., non-strategic) speechlessness for reasons such as stress, extreme emotions, or the fear of being judged; despite their goal, people can have difficulty finding the right words and involuntarily remain silent (Berger 2004). Unintentional speechlessness does not imply the person has no goal active in cognitive processes; it merely implies the person sought the goal in a highly inefficient manner. A related construct, therefore, is goal pursuit efficiency (Kellermann 2004; Palomares 2009a), which is the expediency of behaviors executed for goal pursuit. Efficiently pursuing a goal results in delivering a quick succession of straightforward, direct, succinct, persistent, and effortless means of goal achievement; whereas, inefficient goal pursuit exhibits wasteful, roundabout, and infrequent means of goal achievement. Efficiency is not effectiveness, which is the success at achieving a goal (Wilson 2002). A person can efficiently achieve the goal or efficiently fail to reach it. Efficiency, therefore, is not the common understanding found in dictionaries focusing on a ratio between expended effort and outcome. Rather, efficiency is how expeditious people pursue a goal regardless of how successful they are at securing it.

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Goal pursuit efficiency is a meaningful construct that helps differentiate goals from goal-directed behavior. A male, for example, with a goal to secure a date with a friend can do so inefficiently by asking about weekend plans. In contrast, a more efficient male might directly ask to go to dinner on a date. The goal could be strongly activated in both scenarios despite differences in goal pursuit efficiency. Although the goal can be strongly, equally activated in both situations, some might erroneously reach the conclusion that the reduced behavioral goal signals in the former scenario suggest lower goal activation than the latter situation with the efficient goal-directed behavior. This conclusion, however, is not necessarily warranted because there may be separate behavioral constraints limiting the extent to which the goal is efficiently sought. These constraints, which are often confounded with goals, are the focus of the next section.

3.2 Goals ≠ constraints Constraints are not goals; they are ongoing concerns, considerations, and expectations of behavioral or tactical choice that occur across conversations and to which people pay heed when pursuing their goals (Dillard et al. 1989; Kellermann 2004). These concerns, considerations, and expectations “function to shape, and typically to constrain, the behaviors” (Dillard et al. 1989: 21) employed to obtain a goal. For example, regretted messages often conflict with constraints, suggesting that people wish not having said utterances that violated constraints during goal pursuit (Meyer 2011). Constraints are different than goals because goals are end-states that individuals secure, whereas constraints are behavioral expectations. As such, people do not fail to reach constraints, as they can fail to reach a goal. Likewise, people do not satisfy goals, as they satisfy constraints. Goals and constraints also differ in a temporal sense. Goals are end-states that people work to achieve and complete at particular moments in time during conversations, whereas people continuously work to satisfy constraints over time and across conversations. Goal activation can be fleeting; and, depending on the circumstances, an active goal might be replaced with another. Constraints, in contrast, are long lasting and permeate social interaction and goal pursuit. Constraints do not compete with goals; rather, they influence the behaviors enacted in pursuit of a goal. Despite the theoretical distinction between goals and constraints, constraints are often referred to as secondary goals, and primary goals are mental representations of a desired end-state (i.e., goals). Dillard et al., for example, stated that secondary goals “are recurrent in a person’s life” (1989: 20) and argued “the primary goal serves to initiate and maintain the interaction, while the secondary goals act as a set of boundaries which delimit the verbal choices available to sources” (32). Clearly, secondary goals are conceptually identical to constraints, but because constraints are not goals (i.e., mental representations of desired endstates), calling a constraint a goal (secondary or otherwise) is theoretically inaccu-

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rate and semantically confusing. The core problem is semantics. Even recent work makes a conceptual distinction between goals and constraints under the guises of primary and secondary goals: “Goals frameworks also identify…secondary goals, which constrain the pursuit of primary goals” (Donovan-Kicken et al. in press: 4). Nonetheless, maintaining a conceptually accurate and consistent distinction between goals and constraints and employing semantically straightforward terminology are integral for interpersonal communication theory. Constraints can take a variety of forms (Wilson 2002). One constraint is appropriateness or one’s concern with the level of behavioral politeness that should be used in pursuit of goals (how proper, fitting, and courteous versus uncivil, unmannerly, and rude). Appropriateness corresponds to the “interaction” and “relational resources” secondary “goals” of Dillard et al. (1989) and to Kim’s (1994) “feelings,” “avoid negative evaluation,” and “avoid imposition” conversational constraints. Appropriateness constraints are concerned with interaction partners’ face. For example, people tend to find arguing and criticizing as inappropriate means to secure a date and to stop an annoying habit, whereas they find asking and approving appropriate means for the secure-date goal and advising and forgiving appropriate for the stop-habit goal. Similarly, apologizing is polite to end a relationship, but relatively less polite to change someone’s opinion (Kellermann 2004). Appropriateness is a constraint focused on expectations for behavioral politeness that influence peoples’ concern with the degree to which their goaldirected behavior is courteous. Another common constraint is efficiency, which is a concern or need to be expeditious, direct, and straightforward in goal pursuit. The efficiency constraint is similar to, but distinct from, goal pursuit efficiency. As a constraint, efficiency is a concern with being expeditious, persistent, and not wasteful; whereas goal pursuit efficiency is an attribute of goal-directed behavior regarding the extent to which goal striving is expeditious. A strong concern for the efficiency constraint leads to efficient goal pursuit, similar to the way in which a salient appropriateness constraint will lead to appropriate behavior. Efficiency corresponds to the “personal resources” secondary “goal” (Dillard et al. 1989) and “clarity” constraint (Kim 1994). The efficiency constraint affects behavioral choices for goal pursuit by favoring efficient behaviors over inefficient ones. When trying to obtain a favor, for example, the efficiency constraint leads people to ask and suggest but causes them to avoid insulting and blaming (given the former tactics’ high and the latter tactics’ low efficiency for obtaining a favor); whereas suggesting is only moderately efficient but asking is highly efficient to get a date and confessing and apologizing are highly efficient but insulting and blaming are moderately efficient means to end relationship (Kellermann 2004). Efficiency is a constraint focused on expectations for behavioral expediency and directness that influence peoples’ concern with the degree to which their goal-directed behavior is expeditious. Two additional constraints are arousal management and ethical standards. Arousal management deals with behavioral choice restrictions prompted by

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uncomfortable negative arousal (Dillard et al. 1989). For example, if pursuing an information-seeking goal with excessive questioning increases one’s negative affect (e.g., anxiety), then that might limit the extensiveness of queries. A fourth constraint is ethical standards and parallels the “identity” secondary “goal.” These concerns are restrictions placed on tactical selection due to a violation of what is deemed just and right. For example, people might not lie or threaten in pursuit of a goal because they find it morally reprehensible. Arousal management and ethical standards are constraints respectively focused on expectations for negative affect and morals that influence peoples’ concerns with how to achieve their goal comfortably and ethically. These four major constraints are conceptually separate dimensions that influence tactical choice or acceptability. If a means of goal pursuit fits or is suitable for a given situation; if people deem a means of goal achievement as socially legitimate for or approve of its use in a situation, then it is acceptable (Kellermann and Park 2001). As constraints increasingly tighten, the range of acceptable behaviors for goal pursuit narrows. For example, if appropriateness and efficiency constraints are high when trying to obtain a date, then only two behavioral tactics (i.e., ask, compliment) are acceptable for the goal; whereas with looser constraints, more behaviors are acceptable (Kellermann 2004). At times, constraints are orthogonal and function independently, whereas at other times they are correlated. For example, appropriateness is more important than efficiency in nonurgent situations when trying to unilaterally withdraw from conversation, but they are equally important in urgent situations (Kellermann and Park 2001). Regardless, constraints are distinct from goals and influence behavioral acceptability in goal pursuit.

4 The goal construct demonstrated Having defined and differentiated the goal construct, this section demonstrates the significant roles that goals have played in interpersonal communication by highlighting three major research areas.

4.1 Goal activation Goal activation deals with the processes by which goals gain accessibility to the point that they are cognitively operative and will potentially influence behavior. By definition, goals reside in memory, lying dormant until activation; or they are adopted and then stored in memory until activation (Fishbach and Ferguson 2007). Regardless of their origin and length of existence in memory, goals only become active under certain conditions. A fundamental distinction for goal activation deals with individuals’ level of awareness. Sometimes goals are consciously or explicitly set and pursued, whereas at other times goals are automatically or implicitly trig-

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gered (Moskowitz 2012). Conscious goal activation usually occurs because basic needs and general motives trigger goals (Austin and Vancouver 1996). For example, a need for survival will cause people to seek or maintain employment. A discrepancy between one’s actual and idealized selves can also lead to goal activation. Someone who is unhappy with being overweight, for example, can desire to cycle for exercise. Similarly, a lonely individual can seek a friend’s company. Automatic activation, alternatively, occurs when stimuli (e.g., context, person, article, object) trigger a goal. Such stimuli will be associated with the mental representation of a desired end-state, which when exposed to the stimulus results in goal activation if a certain threshold is met. Exposure to the stimulus does not depend on conscious awareness. Undetected stimuli can unconsciously trigger a goal. Subliminally showing names of relational partners to participants activated associated goals and subsequent pursuit (Shah 2003). Likewise, detected stimuli can unconsciously trigger a goal. Compared to a backpack for example, a briefcase in an office increased pursuit of competitive goals without participants’ awareness of the activated goal (Kay et al. 2004). Goal activation can occur at various levels of awareness, and stimuli responsible for triggering a goal can be perceived either implicitly or explicitly. Explicitly activated goals can retain activation even when peoples’ conscious awareness of the goal dissipates. For example, implementation intentions are consciously generated plans that strongly associate a critical cue for the goal with the needed behavior to secure the goal (Bayer et al. 2009). Implementation intentions typically take the form of if-then statements such as, “If I encounter a generous friend, then I will ask for money,” which can serve a borrow-money goal. Compared to people with no goal, people with a goal who consciously generated implementation intentions generated more goal-directed behavior upon subliminal exposure to the stimulus in an ostensibly unrelated setting (Bayer et al. 2009). People who consciously activate a goal and plan a means to achieve the goal can unconsciously seek the goal when certain conditions are met. Chronic accessibility can influence goal activation in at least two ways (Chartrand and Bargh 1996). First, implicit goal activation can occur for people with chronic goals. Chronic goals are those that maintain a relatively high level of activation across contexts because of frequent pursuit, personality or individual differences, cognitive schemata, and other factors. When confronted with situational triggers, for example, people pursued chronically accessible learning or performance goals (Kawada et al. 2004; also see Wilson 1990). Second, goals (chronic or otherwise) can become chronically linked to stimuli in one’s environment. When goals become chronically associated with stimuli, their activation is easily triggered via the stimuli. For example, goals can become chronically associated with relational partners to such an extent that activating mental representations of partners, even if they are absent, triggers the goals and goal-directed behavior (Fitzsimons and Bargh 2003).

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Factors other than accessibility can activate goals. First, particular social contexts can activate goals. For example, first dates tend to trigger the goals of seek information, have a good time, determine romantic potential, develop friendship, and have sex (Mongeau, Jacobsen, and Donnerstein 2007). Features or circumstances of social contexts, such as time, clothing, physical appearance, and location, can also activate goals (Magliano et al. 2008). When alcohol was not available on a first date, a friendship-initiation goal was less important than when alcohol was available (Mongeau, Serewicz, and Therrien 2004). Further, men wanted to have sex on a first date more than women did when they were acquaintances or friends and the male initiated the date regardless of alcohol availability; yet, if the female initiated the date, they were friends, and alcohol was available, then both males and females desired sex. Social contexts and their features can activate goals and produce goal-directed behavior. Second, tactics uttered by conversation partners can activate goals for message recipients. A single word, for example, can trigger a goal given strong associations (Aarts, Custers, and Veltkamp 2008). Because revealing a secret is strongly associated with an information-giving goal, hearing a secret can activate that goal, just as making a claim can activate an information-giving goal or thanking can activate a compliance-gaining goal given strong tactic-goal links (Palomares 2008). As a result, when exposed to utterances containing goal-related words, goals are activated and goal pursuit can commence. Subsequent goal-directed behavior, however, depends on the current situation. In initial conversations between a confederate and a participant, for example, the goal-directed verbal behavior of the confederate who efficiently sought to obtain personal information activated that information-seeking goal for the participant who subsequently also pursued the goal; this effect, however, did not occur for other information-seeking goals because the context was not conducive to goal pursuit (Palomares 2013). Goal activation is a significant consideration for the goal construct because it accounts for how a goal gains excitation, influences cognitive processing, and ultimately affects communicative behavior (Berger 2002; Berger and Palomares 2011). Although recent research found conversation goals evolved over time (minute to minute) in response to interactants’ behavior and thoughts (Samp 2013), most research focuses on fixed points or global assessments, warranting research on how goals adapt to the flow of discourse.

4.2 Goals and interpersonal relationships Communication is primarily goal directed (Berger 2002; Wilson 2002); thus, ignoring the goal construct in personal relationships research would be remiss. Because relational processes are related to goal processes, employing the goal construct to study relational communication can cultivate a better understanding of both relationships and goals. Unfortunately however, relationship research employs the

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goal construct infrequently (see Caughlin 2010). The following points out ways in which the goal construct has been successfully integrated into relationship research. First, relational partners can affect goal pursuit given goals’ cognitive associations with the mental representations of specific relationships and abstract/general relational types (Fitzsimons and Bargh 2003). Goals, the means to achieve them, and various aspects of relationships are cognitively linked because goals are frequently sought in interactions with, in reference to, or with the assistance of relational partners (Shah, Kruglanski, and Friedman 2003). The frequent coactivation of goals and relational partners, for example, fosters associations. The activation of a mental representation of relational information can trigger associated goals, which can generate goal-directed behavior. For instance, when a representation of a friend was activated, participants were more likely to pursue the goal of helping than when the representation of a coworker was activated, even in the absence of the friend, because the help goal is more strongly connected to their friends than coworkers. Parallel effects were found for participants’ mother compared to a friend and a succeed-in-school goal (Fitzsimons and Bargh 2003). Activating a general relational type or category (e.g., parents) can trigger associated goals in ways similar to activating a specific relationship (e.g., someone’s particular parent; Shah 2003). Relationships can also lead to ironic goal pursuit wherein an opposing goal is activated and pursued. This contradictory goal activation usually occurs because the goal is associated with a relational partner who has unpleasant or negative characteristics. For example, upon activating a controlling significant other who wanted participants to pursue a particular goal, participants rejected the goal and instead sought an opposing goal, especially when participants preferred autonomy (Chartrand, Dalton, and Fitzsimons 2007). In other words, a person’s controlling relational partner triggered a goal that directly opposed the partner’s wishes because the person viewed the partner as a threat to freedom. Second, goal pursuit influences perceptions of relational partners. Social categorizations depend on goal instrumentality or the extent to which people facilitate goal achievement (Fitzsimons and Shah 2009). Partners who facilitate goal pursuit are qualitatively distinct from those who are irrelevant to or discourage goal pursuit. This difference in categorization influences relational perceptions beyond instrumentality. For instance, affinity toward relational partners depends on goal instrumentality. Participants with a goal to perform well academically liked their study friends more than their party friends, whereas the reverse was true when they wanted to socialize (Fitzsimons and Fischbach 2010). This effect is sensitive to goal progress because as participants successfully achieved their academic goal they ceased to prefer and feel closer to study friends, whereas poor goal progress increased closeness to study friends. Other goal effects on relational perceptions include satisfaction, conflict rumination, perceived resolvability of conflicts, and

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the likelihood of recurring conflicts (e.g., Hample et al. 2012; Merrill and Afifi 2012). Goal-directed behavior mediates many of these effects, wherein goals generate communicative behavior, which in turn affects relational perceptions. One’s sense of time and what goals are most critical at different stages of life can influence the value placed on relationships. Young people usually perceive time as open-ended and the future as expansive; yet as people age, time is increasingly viewed as finite and the future as constrained (Carstensen 2006). These perspectives affect goal priorities with broad time horizons encouraging goals focused on expanding knowledge and experiences (e.g., gain education, begin career, attend concerts) and constrained horizons emphasizing emotions and psychological well-being (e.g., spend time with family, retire, avoid conflict, volunteer; Charles and Carstensen 2009). The importance people place on goals to engage with and focus on personal relationships is greater in older adulthood, and the significance placed on goals to achieve and prepare for adventurous pursuits is greater at younger ages. Differences in goal priorities do not always vary by age, however. When the fragility of life was made salient, as in the case of global crises (e.g., 9/11 or a flu pandemic), young people prioritized emotional goals at a level similar to older individuals (Carstensen 2006). Likewise, older individuals’ priorities reflected gainknowledge/experience goals when their time horizons were experimentally broadened (e.g., new medical advance increases longevity). Similar effects occurred without changing perceptions of death or age: Young people with impending major life changes (e.g., geographical move, graduation) prioritized emotional goals because of a change in time horizons. Perceptions of time affect goal priorities, which influence the significance of and how people engage in personal relationships. Third, goal pursuit can affect relational quality. The extent to which people can attain goals in committed romantic relationships, for example, is a significant factor for relational quality. Throughout a marriage, people have multiple goals they wish to achieve and goal priorities evolve: Younger married adults prioritize personal growth goals to improve themselves; mature married couples focus on companionship goals to address needs for belonging; and middle-adulthood couples primarily want to secure goals that address the practical aspects of marriage like childrearing, with the other two sets of goals also active but to lesser extents (Li and Fung 2011). Because couples’ effectiveness at achieving goals is not constant, marital quality correspondingly fluctuates. As success for prioritized goals in marriage increased, relational satisfaction increased, for example. Of course, relational partners’ communication patterns (e.g., openness, compromise) will influence goal success, which in turn can influence relational quality. This outcome is especially likely, for example, if partners work together to obtain mutually held goals or they find effective solutions to secure both partners’ unique and incompatible goals. However, relational partners who do not overcome goal

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conflict typically experience lower relational quality than those who effectively confront conflicting goals (Gere et al. 2011). Putting one’s goals and self-interests ahead of a partner’s goals creates a situation in which the partner may experience resentment and low levels of closeness; in contrast, prioritizing a partner’s goals over one’s own goals can demonstrate commitment and lead to beneficial outcomes for the relationship (Gere and Schimmack 2013). A final example of how the goal construct has been effectively used to study relational communication is topic avoidance. A study of friends reported that the tactics employed when pursuing a topic-avoidance goal affected recipients’ perceptions of message quality and emotional reactions (Donovan-Kicken et al. in press). These effects depended on various conversational constraints. For example, a partner seeking to avoid a topic was rated as more competent when tactics addressed appropriateness concerns (e.g., “Thanks for asking, but let’s talk about something else”) than when tactics violated the constraint. Similarly, topic avoidance tactics that attend to appropriateness concerns caused recipients to experience less hurt than if tactics neglected appropriateness to focus on avoiders’ privacy (e.g., “That’s personal.”). In general, this and other research demonstrates a new trend to cast light on goal dynamics in personal relationships; however, an untested assumption is that recipients generate inferences about goal processes in their conversations with relational partners and these inferences lead to different relational perceptions, message quality, or other outcomes. Thus, the next section focuses on how people understand and make inferences of others’ goals.

4.3 Goal inference processes Goal inferences occur when a person considers or understands someone’s objective. Answers to “What is he/she trying to do?” are typically goal inferences (Reeder 2009). Goal inferences are part of a larger set of constructs collectively referred to as goal detection or the processes by which people infer the goals that others pursue (Palomares 2008). Many of the same mechanisms responsible for goal activation play a role in goal inferences (Berger and Palomares 2011). The major symmetry between detection and activation is that goals are cognitively associated with various mentally represented constructs. When a stimulus triggers a construct, associated goals are activated (Chartrand and Bargh 1996). In the case of goal detection, this goal activation populates goal inferences – either explicitly with awareness or automatically outside consciousness (Hassin, Aarts, and Ferguson 2005; Kawada et al. 2004). In other words, the goals people generate to understand others’ behavior are a product of the goals activated in interactions (Palomares 2008). For example, because social settings (e.g., classroom, store, park, plane) are strongly connected to goals, a setting can increase the accessibility of linked goals when interacting with someone in the particular setting, which will increase the

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likelihood that people infer the activated goals. A scenario set at a job fair, for example, led to frequent inferences of a linked provide-information goal compared to other goals, whereas scenarios within other social settings (e.g., cathedral) generated inferences of different goals linked to the settings (Palomares 2008). Further, initial interactions tend to produce inferences of get-to-know-you goals (Palomares 2009a). Social settings are not the only mentally represented constructs that foster particular goal inferences. Relational types (e.g., close friends) lead to inferences of some goals more than others (Fitzsimons and Bargh 2003; Palomares 2009b), just as specific situational cues or circumstances (e.g., nighttime) can generate inferences of certain goals (Magliano et al. 2008). Thus, a contextual factor (e.g., settings, cues, relational types, roles) can encourage an inference of a particular goal because of the strong connection between the two (Aarts 2012; Palomares 2011). Another major determinant of goal inferences is goal-directed behavior (Dik and Aarts 2007). For example, a pursuer’s reveal tactic led to frequent inferences of a provide-information goal more than other goals because the goal and the mental representation of the tactic are strongly associated (Palomares 2008). Communicative behavior is often a strong indicator of people’s objectives because goals are the fundamental driver of such behavior. Yet, contextual factors can be a stronger influence on goal inferences than behavior. That behavior and contextual factors can activate goals and affect goal inferences is clear. Less obvious is determining when goal-directed behavior is a primary influence on goal inferences versus when tactic are less important than or perhaps even superfluous to contextual factors. The integration principle of goal detection provides one explanation (Palomares 2009a, 2009b, 2011). The extent to which tactics predict goal inferences depends on the extent to which contextual factors activate goals. If the context activates an adequately low number of goals so that a goal inference can be generated, then tactics likely have little influence on goal inferences. For example, in highly routinized social settings (e.g., supermarket) goals can be inferred with very little or virtually no goal-directed communicative behavior (Berger 2000). If too many goals are activated or if no goals are activated by the context, then generating goal inferences based on contextual factors alone is problematic such that tactics and the goals they activate will be integrated into the goal inference process (Palomares 2008). For example, when a relational type did not activate the relational partner’s goal, tactics became integral and goal inferences were based on the goal(s) that tactics activated (Palomares 2009b). Another aspect of the integration principle focuses on when the goals activated by the context are different than the goals activated by the tactics. Based on the integration principle, goals mutually activated by a contextual factor and a tactic are more likely inferred than goals activated by either a factor or a tactic alone because the joint activation increases goal accessibility. For example, when a job-

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fair scenario activated a provide-information goal and a reveal tactic suggested the same goal, inferences of the provide-information goal were highly frequent (Palomares 2008). However, if tactic-activated goals are inconsistent with contextactivated goals, then tactics primarily influence goal inferences. For example, if someone sought a political-information-seeking goal in an initial interaction between fellow students, which is a context associated with other goals but not the political goal, then pursuer’s communicative behavior was a strong determinant of goal inferences (Palomares 2009a). Similar effects were demonstrated between close friends (Palomares 2009b). The integration principle is an effective explanation for how contextual factors in relation to communicative behavior affect goal inferences (Palomares 2011). Goal contagion – a perceiver’s adoption of a goal that another person is seeking – is a related process. Goal contagion occurs during negotiations (Liu 2011), in initial interactions (Palomares 2013), when watching videos of others’ competing (Loersch et al. 2008), when reading scenarios of people trying to earn money or woo a potential mate (Aarts, Gollwitzer, and Hassin 2004), and in other settings (e.g., Bouquet et al. 2011). Goal contagion also seems to occur between parents and their school-age children and between teachers and their students; the contagious goals are how students approach school and learning (Friedel et al. 2007). Students with parents and teachers who prioritized learning goals to acquire knowledge reported pursuing similar goals, whereas those students with parents and teachers who valued performance goals to outperform peers were also likely to seek those objectives; goals to learn promote success more than do goals to perform. Whatever the goal, the general contagion process is that a stimulus, which is usually someone else’s goal-directed behavior, activates a goal for a perceiver. This activation leads to an accurate goal inference for the perceiver who subsequently pursues the same goal if certain conditions are met, such as the situation is conducive to goal pursuit (Palomares 2013). Goal inferences and contagion demonstrate how the goal construct is central to interpersonal communication. In fact, goal inferences are consequential. In initial interactions between peers, for example, people who accurately inferred a partner’s goal judged the partner higher in communication competence than those who were relatively inaccurate (Palomares 2009a). Related research confirmed that individuals’ inference accuracy predicted increased ratings of partners’ communication competence but only for highly confident inferences because uncertainty allowed for alternative influences on competence judgments (Palomares 2011).

5 Conclusion Goals are mental representations of desired end-states that are distinct from behavior and constraints. Whereas much is known about goals, much more is yet to

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be known. Three examples close the chapter. First, goal inference processes are undeniable; yet, whether people infer others’ constraints is unknown. People seem to indicate implicit understandings of constraints (e.g., “Why are you being extra nice?”), but research has not examined if people generate inferences for constraints. Given the distinctions between goals and constraints, goal inference processes might be different than possible processes of inferring constraints. A second yet-to-be-studied aspect is the distinction between goals primarily pursued in conversations (e.g., loan money) versus goals that do not require social interaction (e.g., save money). Interpersonal scholars usually and justifiably focus on interaction goals, whereas other scholars do not necessarily emphasize conversation. Arguably, interaction goals are just a specific manifestation of goals, and what we know about one is applicable to the other; research is consistent (Berger and Palomares 2011; Palomares 2013). However, directly comparing interaction goals with other goals might be fruitful. In fact, because goal taxonomies are rare (Chulef, Read, and Walsh 2001), constructing organized lists of goals pursued with and without interaction would be valuable, especially at a level of detail finer than broad swaths (Clark and Delia 1979). Finally, research can continue to examine how goals function in personal relationships. Goal tendencies are of particular interest for relational communication research because most isolated instances of goal pursuit or failure are unlikely consequential for a long-term relationship. Yet, habitually pursuing certain goals (e.g., avoiding a topic, spending time together) are likely greater influences and have more entrenched consequences. The inferences and associated attributions for partners and their goals is likely significant as well (cf., Lakey and Canary 2002).

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Merrill, Anne F. and Tamara D. Afifi. 2012. Examining the bidirectional nature of topic avoidance and relationship dissatisfaction: The moderating role of communication skills. Communication Monographs 79: 499–521. Meyer, Janet R. 2011. Regretted messages: Cognitive antecedents and post hoc reflection. Journal of Language and Social Psychology 30: 376–395. Moberly, Nicholas J. and Edward R. Watkins. 2010. Negative affect and ruminative self- focus during everyday goal pursuit. Cognition and Emotion 24: 729–739. Mongeau, Paul A., Janet Jacobsen and Carolyn Donnerstein. 2007. Defining dates and first date goals: Generalizing from undergraduates to single adults. Communication Research 34: 526–547. Mongeau, Paul A., Mary C. M. Serewicz and Lona F. Therrien. 2004. Goals for cross‐sex first dates: Identification, measurement, and the influence of contextual factors. Communication Monographs 71: 121–147. Moskowitz, Gordon B. 2012. The representation and regulation of goals. In: Henk Aarts and Andrew J. Elliot (eds.), Goal-Directed Behavior, 1–47. New York: Psychology Press. Moskowitz, Gordon B. and Heidi Grant (eds.). 2009. The Psychology of Goals. New York: Guilford Press. Palomares, Nicholas A. 2008. Toward a theory of goal detection in social interaction: Effects of contextual ambiguity and tactical functionality on goal inferences and inference certainty. Communication Research 35: 109–148. Palomares, Nicholas A. 2009a. Did you see it coming? Effects of the specificity and efficiency of goal pursuit on the accuracy and onset of goal detection in social interaction. Communication Research 36: 475–509. Palomares, Nicholas A. 2009b. It’s not just your goal, but also who you know: How the cognitive associations among goals and relationships influence goal detection in social interaction. Human Communication Research 35: 534–560. Palomares, Nicholas A. 2011. The dynamics of goal congruency and cognitive busyness in goal detection. Communication Research 38: 517–542. Palomares, Nicholas A. 2013. When and how goals are contagious in social interaction. Human Communication Research 39: 74–100. Park, Lora E., Ariana F. Young, Jordan D. Troisi and Rebecca T. Pinkus. 2011. Effects of everyday romantic goal pursuit on women’s attitudes toward math and science. Personality and Social Psychology Bulletin 37: 1259–1273. Planalp, Sally. 1985. Relational schemata: A test of alternative forms of relational knowledge as guides to communication. Human Communication Research 12: 3–29. Reeder, Glenn D. 2009. Mindreading: Judgments about intentionality and motives in dispositional inference. Psychological Inquiry 20: 1–18. Romo, Lynsey K. and Erin Donovan-Kicken. 2012. “Actually, I don’t eat meat”: A multiple-goals perspective of communication about vegetarianism. Communication Studies, 63: 405–420. Samp, Jennifer A. 2013. Goal variability and message content during relational discussions: A sequential analysis. Communication Studies 64: 87–106. Schank, Roger C. and Robert P. Abelson. 1977. Scripts, Plans, Goals and Understanding. Hillsdale, NJ: Lawrence Erlbaum. Shah, James. 2003. Automatic for the people: How representations of significant others implicitly affect goal pursuit. Journal of Personality and Social Psychology 84: 661–681. Shah, James Y., Arie W. Kruglanski and Ron Friedman. 2003. In: Steven J. Spencer, Steven Fein, Mark P. Zanna and James M. Olson (eds.), Motivated Social Perception, 247–275. Mahwah, NJ, US: Lawrence Erlbaum. Sherman, Jeffrey W. 1996. Development and mental representation of stereotypes. Journal of Personality and Social Psychology 70: 1126–1141.

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Southgate, Victoria, Mark H. Johnson and Gergely Csibra. 2007. Infants attribute goals even to biomechanically impossible actions. Cognition 107: 1059–1069. Tolman, Edward C. 1932. Purposive Behavior in Animals and Men. New York: Appleton-CenturyCrofts. Tracy, Karen (ed.). 1991. Understanding Face-to-Face Interaction: Issues Linking Goals and Discourse. Hillsdale, NJ: Erlbaum. Uller, Claudia. 2004. Disposition to recognize goals in infant chimpanzees. Animal Cognition 7: 154–161. Walther, Joseph B., Brandon Van Der Heide, Stephanie T. Tong, Caleb T. Carr and Charles K. Atkin. 2010. Effects of interpersonal goals on inadvertent intrapersonal influence in computer-mediated communication. Human Communication Research 36: 323–347. Wiese, Bettina S. 2007 Successful pursuit of personal goals and subjective well-being. In: Brian R. Little, Katariina Salmela-Aro and Susan D. Phillips (eds.), Personal Project Pursuit: Goals, Action, and Human Flourishing, 301–328. Mahwah, NJ, US: Lawrence Erlbaum. Wilson, Steven R. 1990. Development and test of a cognitive rules model of interaction goals. Communication Monographs 57: 81–103. Wilson, Steven R. 2002. Seeking and Resisting Compliance: Why People Say What They Do When Trying to Influence Others. Thousand Oaks, CA: Sage. Wilson, Steven R., Adrianne D. Kunkel, Scott J. Robson, James O. Olufowote and Jordan Soliz. 2009. Identity implications of relationship (re)definition goals: An analysis of face threats and facework as young adults initiate, intensify, and disengage from romantic relationships. Journal of Language and Social Psychology 28: 32–61.

Part III: Methodological approaches

John P. Caughlin and Erin D. Basinger

5 Measuring social interaction Abstract: This chapter concerns the measurement of concepts related to interpersonal communication. We begin with a discussion of general measurement principles and argue that there are multiple useful ways to conceptualize and measure interpersonal communication. We then review strengths and weaknesses of common measurement techniques, including self-reports, observations, in-depth interviews, and physiological measures. Because every measurement technique has limitations with respect to assessing interpersonal communication, we argue that it is often useful for multiple techniques to be used either within or across studies. We conclude with a discussion of special considerations for designing measures in studies of interpersonal communication. Specifically, interpersonal scholars should pay particular attention to: (a) the need to consider a timeframe that provides an adequate sampling of ongoing interaction; (b) the possibility that new communication technologies are changing the nature of interpersonal communication and what should be observed, even in face-to-face settings; (c) the pitfalls of using measures designed for other purposes to assess interpersonal communication constructs; and (d) the potential for confusing statistical information for definitive proof of validity. Key Words: research methods, interpersonal interaction, validity, reliability, measurement, operationalization

1 Introduction Measurement is “the process of determining the existence, characteristics, size, and/or quantity of changes or differences in a variable through systematic recording and organization of the researcher’s observations” (Frey, Botan, and Kreps 2000: 83). The choices we make about how to measure social interactions determine not only the quality of our data, but also the conclusions we can reasonably draw because our methods have assumptions built into them (Duck and Montgomery 1991; Reinard 2008). In fact, Levine (2011: 44) asserts that “the path to verisimilitude in quantitative research always goes through measurement.” Given the significance of measurement in social interaction research, this chapter focuses on issues surrounding the measurement of interpersonal communication concepts. Unfortunately, there are no simple guidelines for creating ideal measures of interpersonal communication. Part of the difficulty in measuring interpersonal communication concepts is that there is no consensus about what even counts as

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interpersonal communication. Over the past several decades, there have been periodic calls to focus on observable behaviors exchanged between people (Knapp and Daly 2011: 12). Implicit in these calls is the idea that one cannot fully know what happened in social interaction just by examining what people think about it. Yet, understanding the significance of those observable behaviors may depend on knowing something about the interactants’ expectations, plans, and interpretations, as well as how those behaviors fit into the history of interactions between the people involved. People involved in interaction often interpret the meaning of such interactions in terms of each other’s plans or goals (Berger and Palomares 2011; Wilson 2002); for example, rather than focusing on the fact that a partner stated “that is your third drink,” a person may describe the partner’s message as “she wants me to stop drinking after this one.” If one focuses only on the observable behaviors and not the meanings attributed to them, would what is communicated be apparent to observers? This query implies that there is no simple answer to the question of whether it is best to conceptualize social interaction as something that happens apart from such inference processes (and is therefore fully observable) or whether such inferences are an inherent part of what it means to have social interaction. Scholars rarely take explicit positions on such issues, but their implicit stances shape what is presumed to be a valid measure of interpersonal communication. For example, some studies use the phrase “actual communication” synonymously with “behavior,” which conceptualizes all the interpretive aspects of interaction as apart from communication (e.g., see Le Poire and Yoshimura 1999). In such studies, what would be considered the most valid communication measures would be different from studies in which communication is conceptualized as inherently involving the meanings of such behaviors to the communicators. Given that communication scholars implicitly disagree about the very nature of what constitutes interpersonal communication, there cannot be complete consensus about the best measurement techniques. Thus, rather than espousing one set of values about measurement, our goal is to familiarize the reader with important issues and conceptual problems that can inform better and worse research practices. That is, even though there are no correct and incorrect ways to measure interpersonal communication, there are nevertheless more and less appropriate choices based on the particular purposes of a given study. Our goal is to make some of the implicit assumptions about measurement more explicit and to encourage a reflective stance toward choosing measures of interpersonal constructs. Toward that end, we begin this chapter by discussing concepts in general and reviewing some traditional measurement concepts and techniques. Then, we consider the use of multiple measurement techniques in assessing social interaction, and we conclude with a discussion of special considerations for studies of interpersonal communication.

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2 Concepts as arbitrary The challenge of not having a definitive consensus about what constitutes interpersonal communication is compounded by the arbitrary nature of interpersonal constructs. Philosophers have long recognized the arbitrary relationship between concepts and the things they represent (Ogden and Richards 1923). Among communication researchers, a range of beliefs about this relationship is represented. Baxter and Babbie (2004: 111) argue that “concepts are only mental creations.” The problem, they say, is that we begin to attach real meaning to our concepts anyway, leading us to measure them in ways that are inaccurate. In addition, Baxter and Babbie (2004: 132) argue that we can “measure anything that exists,” but warn that some of the things we want to measure are concepts that we have just agreed upon as having meaning. In contrast, Reinard (2008) proposes that there are some concepts that we cannot fully capture in measurement because they are too abstract or because they are mental experiences. Cappella (1991) similarly claims that our measurement tools cannot be neutral; rather, they are constructions of the social world. Representing a different perspective, Surra and Ridley (1991) caution that communication has subjective and idiosyncratic meaning, as well as normative and conventionalized meaning, and that our measures ought to be sensitive to these differences. Although each scholar represents a different perspective, all of them recognize that the relationship between measures and the things they represent is somewhat subjective. Even though all constructs relating to interpersonal communication are somewhat arbitrary, that does not mean all constructs and measures thereof are equally useful. O’Keefe (1987) presents a useful way of approaching the problem of arbitrary concepts in measuring interpersonal interaction. He suggests that messages are complex and that there are many concepts that could be used to analyze them; thus, there is no intrinsically correct way to describe a message or segment of social interaction. This adds weight to the choices that researchers inevitably make as they select a system of measurement from an enormously large number of possibilities. O’Keefe draws two conclusions that are particularly relevant to social interaction measurement. First, it is unlikely there can ever be a general interaction coding system that is appropriate or accurate for every given purpose; what may be a perfectly valid measure for one purpose may be invalid for another. This seems to be an obvious point, but it is common to encounter claims that the validity of a key measure has been established in prior studies, even when a close examination reveals that the measure is being used to assess a construct for which it was not originally intended and seems ill-suited. Second, because we make choices each time we measure something, our measurement tools cannot be valid or invalid in an overall sense. Rather, a measure is valid or invalid only with respect to specific purposes.

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3 Traditional concepts of assessing measurement Researchers can make a large number of choices when they measure concepts; however, there is an accessible list of traditional measurement tools and concepts. Although this list is not exhaustive, it is a useful starting point for understanding measurement basics. Because there are many available references for these basic measurement concepts, we provide a very brief review here (for more extensive discussions, see Baxter and Babbie 2004; Frey, Botan, and Kreps 2000; Singleton and Straits 2005).

3.1 Conceptualization and operationalization A fundamental part of measurement is considering a concept carefully and recognizing what is and is not part of that concept. Conceptualization is a mental process of developing concepts and making them more precise. Operationalization is the process of translating concepts into measurable variables and specifying their assessable characteristics. Although conceptualization and operationalization apply to any systematic attempt to measure a construct, there are some particular challenges for scholars studying interpersonal communication. For example, because two people in an interpersonal encounter often influence each other, their behaviors and thoughts can be intertwined; consequently, researchers must think carefully about questions of the proper unit of analysis, such as whether a construct is best thought of as a property of the individual or the dyad (Thompson and Walker 1982; see Chapter 6, Liu). Similarly, interpersonal communication scholars may wish to consider communicators’ subjective perceptions, as well as some of their more objective behaviors. Given these (and many other) unique constraints of studying interpersonal communication, scholars ought to be particularly sensitive to their conceptualization and operationalization processes.

3.2 Reliability and validity Reliability refers to the stability or consistency of a measure and whether a particular measure, administered repeatedly, will yield the same results each time. Often reliability is assessed at a single point in time by examining various indicators of the same construct, with the idea that if multiple items or ratings show similar findings, then the overall measure is probably reliable. As we discuss below, however, concurrent measures of reliability do not always provide a good sense of whether a measure of interpersonal communication behavior would yield similar findings if repeated multiple times. Validity involves the congruence between the conceptual and operational definitions of a concept (Levine 2011). Having true validity in any given study means

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fully reflecting the construct of interest and nothing else (Levine 2011). Measures can only be valid to a certain extent and for a specific purpose because each representation (i.e., measurement) of behavior, communication, or interaction is less complex than the behavior, communication, or interaction itself (Cappella 1991). The translations of those things are what we actually study, and they are more or less inferential depending on how we choose to measure them (Cappella 1991). Assessing validity, then, must necessarily be a complex process that is unique to each particular study and its purpose. Validity cannot be assessed directly. Researchers must either subjectively evaluate whether the operationalization assesses the intended concept or compare the results of a measure to others it should relate to (Singleton and Straits 2005). Moreover, validity is not a binary construct (Levine 2011). That is, a measure is not either valid or invalid; rather any given measure reflects a range of validity. As a result, validity can be threatened in a number of ways including inappropriate sampling, memory distortions affecting recall of events, errors in mental processes by the participant, distortions in judgments, and lumping conceptually distinct constructs together (Huston and Robins 1982). This list of threats is not exhaustive, so we point the reader to Huston and Robins (1982) and Frey, Botan, and Kreps (2000) for a more thorough review of validity threats.

3.3 Assessing measures Considerations of operationalization, reliability, and validity should contribute to the decision of whether a measure is suitable for a specific study. That is, is the operationalization adequate, accurate, and clear (Frey, Botan, and Kreps 2000)? Is the unit of analysis appropriate for the concept of interest? Is the measure reliable? Is it valid for the purpose of this study? It is important to emphasize that the answer to whether a measure is appropriate really does depend on the specifics of a given study. For instance, a measure that is perfectly valid for one sample may not work well with another sample (Reinard 2008).

4 Common measurement techniques in interpersonal communication research There are many options for measuring interpersonal communication constructs. In this section we discuss the common general techniques that interpersonal communication researchers use. Because our goal is to provide an overview, we do not focus on the considerable variation that exists within these categories of measures. For a more thorough discussion of various pertinent measurement techniques see Feeney and Noller (2012).

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4.1 Self-Reports 4.1.1 Retrospective self-reports The most common self-reports involve participants reflecting on and answering questions about their lives or experiences. Researchers have asked people to report on many aspects of interpersonal communication, including their own behaviors, other people’s behaviors, their attributions for their own or other people’s behaviors, and various subjective evaluations of the communication and other communicators. In addition to being used to assess a wide range of constructs, retrospective self-reports can be used to assess interpersonal communication behaviors over various timeframes; for example, Young et al. (2005) asked about a single hurtful experience of family communication whereas Vangelisti and her colleagues (2007) investigated factors that led to a general environment of hurtful family communication. Taken together, these studies point to the range of uses of retrospective self-reports. Given that the focus of self-report measures can vary so widely, scholars should attend closely to exactly what participants were asked when generating their responses. Often measures that are ostensibly assessing the same construct differ in some significant attribute that makes the findings not comparable. For example, Larson and Chastain’s (1990) measure of concealment asks about the tendency of certain individuals to be secretive, and secrecy on this measure is inversely related to relational quality (e.g., Finkenauer et al. 2009). However, that measure of secrecy is not equivalent to those used in other studies that examine people’s decisions and experiences regarding a particular secret (e.g., Caughlin et al. 2005). It is important to keep such differences in mind because even though the general topic of the measures may be the same, the details of the constructs assessed may differ enough that one should be very cautious about making broad claims based on any particular measure. For example, results indicating that being a generally secretive person is associated with dissatisfying relationships do not imply that people in relationships should reveal any particular secret that they have (Caughlin, Petronio, and Middleton 2012). The potential pitfalls highlighted in this example should caution researchers against making overly broad claims based on specific measures.

4.1.2 Diaries or logs Diaries and logs are forms of self-report measures, but they differ from typical retrospective self-reports in that they involve repeated reports of the same behaviors or experiences over some sample of time. The goal of such measures is to study individuals’ everyday experiences, including those with interpersonal relationships and communication (Reis and Gable 2000). Depending on the research

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purposes, diary or log measures can be very broad or more specific. The Rochester Interaction Record (Reis and Wheeler 1991), for example, involves asking research participants to record detailed information about every interpersonal encounter lasting at least ten minutes. Other studies focus on a particular relationship; for example, in the PAIR Project (e.g., Huston et al. 2001) married couples were called on the phone on multiple occasions and asked about daily occurrences of specific behaviors, such as whether one’s spouse had complained or said “I love you.” Data from diaries or logs are often aggregated to provide baseline information about the frequency of interpersonal behaviors or experiences, but they also can be examined for temporal patterns, such as whether marital interaction patterns are influenced by the day of the week (Huston, McHale, and Crouter 1986).

4.1.3 Advantages and disadvantages of self-report measures As Feeney and Noller (2012: 30) noted, “The limitations of self-report questionnaires are well known (in fact, they have been more widely acknowledged than the limitations of other methodologies such as observation)” (also see Metts, Sprecher, and Cupach 1991). The most notable problems with self-report measures are that people may be biased in their reports (e.g., due to social desirability or recall errors) and that there are aspects of interpersonal communication that individuals may not even be aware of, such as many nonverbal behaviors (Baesler and Burgoon 1987). These are necessary issues to consider when using self-report measures, so it is good that they are widely recognized among communication scholars. Yet, scholars should not dismiss self-report measures just because they, like all measures, have limitations. Moreover, just because self-report measures are subject to various biases does not mean that every self-report is equally biased. Instead, it is useful to think about the various threats to validity with respect to particular measures. What people are asked to report on, how questions are worded, the timeframe being assessed, and the accessibility of the information all influence the extent to which a self-report can be trusted (Huston and Robins 1982). For example, if a questionnaire asks an individual to report on a relatively long period of time and do mental calculations, it is likely that the report will be more problematic than one that asks about a recent and narrow timeframe and does not require complicated assessments. To the extent that the recall interval is short and the behavior is easily observable to participants, the report is more likely to be accurate. If a researcher called and asked readers of this chapter if they were reading a book chapter right now, they could probably answer that question accurately. In short, not all self-report measures should be considered equally problematic; it is important to consider what exactly participants are being asked and whether they are in a position to provide accurate information. The main advantage of self-report data is that they provide access to information that would be difficult, if not impossible, to observe. Self-reports can be used

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to gather information about individuals’ cognitions, such as whether they found a conversation enjoyable, their beliefs about why other people said what they did, their beliefs about why they said what they did, and so forth. Diary and log versions of self-reports can be particularly useful for learning about interpersonal communication phenomena in everyday life. For example, a typical observational measurement strategy involves asking dyads to engage in a particular type of interaction (e.g., a conflict), yet such procedures essentially control or eliminate the extent to which dyads vary in how often they engage in that type of interaction. It might be possible to design an observational technique that allowed researchers to independently assess the frequency of everyday interpersonal behaviors, but such a measure would require a level of surveillance that probably would preclude the recruitment of a representative sample of typical dyads. A self-report measure, on the other hand, opens up possibilities for assessing these types of interactions by exploring individuals’ cognitions about a particular type of interaction, as well as its frequency.

4.2 Observations Interpersonal communication can be observed in a number of ways. One common technique for doing so involves bringing people into a laboratory and asking them to engage in some sort of discussion. For example, one could observe married couples discussing conflict issues based on a list of topics researchers select for their discussion (e.g., Gottman 1994; Sanford 2012). Although conflict tasks are by far the most common stimulus for interactions in laboratories, researchers also use other tasks, such as asking partners to comment on each other’s positive or negative qualities (Smith et al. 2011), asking partners to be supportive of each other (Sullivan et al. 2010), or instructing partners to discuss their positive feelings for each other (Graber et al. 2011). Observational studies conducted in laboratory settings are so prominent in the research literature that some researchers have suggested that observing interaction is nearly synonymous with a laboratory or some other artificial setting (e.g., Reis and Gable 2000). However, it is possible to observe naturally occurring interpersonal interactions. Indeed, discourse analysts have observed face-to-face interpersonal interaction during workplace interactions, police interviews, medical encounters, and so forth (Beavin Bavelas, Kenwood, and Phillips 2002). Interpersonal communication sometimes takes place via media that create artifacts that can be observed, such as letters exchanged between relational partners, internet bulletin board discussions, or logs of instant messaging interactions (Beavin Bavelas, Kenwood, and Phillips 2002). Thus, there is a myriad of social contexts in which observational data can be obtained. Regardless of how observational data are gathered, collecting the sample of interaction is only the first step. The researcher must decide which specific behav-

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iors to examine and how to operationalize variables pertaining to the constructs of interest. In some cases, researchers count the frequency of discrete behaviors. In other cases researchers rate the extent to which a segment of talk exemplifies some construct; for example, Christensen and Heavey’s (1993) coding scheme for demanding and withdrawing behaviors relies on ratings of the extent to which interactants are demanding or withdrawing. Sometimes the researcher is interested in particular behaviors, but other times the sequence of the behaviors is also considered important; for instance, Gottman and his colleagues (1998) examined how husbands responded to their wives when the wives expressed modest amounts of negative affect. When researchers study sequences, the implicit theoretical assumption is that the combination of individuals’ behaviors reveals something that cannot be discerned just from the frequencies of each person’s behaviors.

4.2.1 Advantages and disadvantages of observational measures Observational methods are often touted as a means of gathering objective information about actual interpersonal communication. The utility of objective assessments of interpersonal communication is unquestionable given the fact that selfreports of communication may be biased. Despite this obvious strength, however, observational methods also have weaknesses, which are often overlooked or unrecognized, perhaps because so much attention has been paid to the weaknesses of self-report measures (Feeney and Noller 2012). First, the totality of the observed interaction can never be presented in a scholarly manuscript. Instead, researchers must choose something to examine in the data and then interpret what those observations mean. Clearly, choosing what to assess can be a selective process. Researchers often address this potential bias by using established coding systems such as the Specific Affect Coding System (SACS; Gottman 1994). Although choosing an existing coding or rating scheme is useful, it is important to keep in mind that reliance on existing ratings can also introduce bias because it focuses the researchers’ attention on certain aspects of the interaction (and away from others), which is problematic if the rating scheme was not originally developed for precisely the purposes of the current study. Moreover, as a rating or coding scheme becomes firmly established, there may be a tendency for researchers to reify the variables derived from it, forgetting that the particular ratings extracted from the interaction are just one of many possible useful ways of examining the data, and that each particular way was undoubtedly shaped by the original researchers’ views and goals. Given that the creation of such schemes is an inherently interpretive process, all rating schemes have a particular perspective. In other words, the data gathered may be objective, but the process of reducing that data into information that can be studied systematically is inherently an inventive one and therefore biased in some ways.

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Another form of bias inherent in observational research involves the interpretation of the rated interactions. In one study, Gottman et al. (1998) followed 130 newlywed couples over time and reported: “only newlywed men who accept influence from their wives are winding up in happy and stable marriages.” This conclusion was based on observational data that was coded with the SACS and analyzed based on sequences to determine how partners responded to each other. This study was interpreted as meaning that husbands who want happy marriages should do what they are told, and not surprisingly, this study received a great deal of attention in the popular press (for a representative example, see Maugh 1998). Yet a careful reading of exactly what was observed and coded in the Gottman et al. (1998) study reveals multiple possible interpretations of the “accept influence” variable aside from husbands doing what they are told. What the study actually assessed was husbands’ responses when their wives engaged in mildly negative behaviors such as showing anger or whining. In previous research, Gottman and colleagues had found that violent husbands responded to low-level negativity from their wives with very intense negativity (e.g., belligerence, showing contempt). In the current study, the label “accepting influence” was used whenever the wives engaged in low intensity negativity and husbands did not escalate the situation with high intensity negativity. For example, if a husband responded to his wife’s whining by showing that he was angry at her (without expressing contempt or belligerence), this was considered an instance of accepting influence. In addition to the problematic dichotomy of suggesting that all husbands are likely either to accept influence or escalate to violence, it is clear that labeling such a sequence as “accepting influence” is an interpretation. It is accepting of influence in the sense that it is not quashing it strongly, but such a sequence is hardly consistent with the notion that “the newest advice from psychologists is quite simple: Be willing to do what your wife says” (Maugh 1998). This example illustrates the larger point that even when the data allow for direct observations of interpersonal communication, researchers should still be mindful of the fact that the data are interpreted, which is not truly objective. Finally, interpersonal communication scholars should remember that, except in the special case of first encounters, interactions between individuals are shaped by the history of interactions between the individuals involved. It is common for the stream of a conversation to span more than one particular encounter, and multiple periods of interaction across time can be recognized as belonging to the same discussion (Agha 2007). Research by Roloff and his colleagues (e.g., Johnson and Roloff 1998; Reznik and Roloff 2011), for example, illustrates that the impact of serial arguments can really only be understood in the context of the history of the conflict episodes on any particular topic. Whenever researchers observe an interaction segment from an existing relationship, “it is important to remember that outsiders know little about the history of the relationships they observe” (Feeney and Noller 2012: 34). Bringing a dyad into a laboratory may allow research-

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ers to extract a sample of interaction that can be objectively analyzed, but that objective analysis may miss what that interaction actually means.

4.3 In-depth interviews There are a variety of types of interviews. Some interviewing is essentially comparable to questionnaire studies. For example, in the PAIR Project, a longitudinal study of couples first contacted as newlyweds, the follow-up phase conducted 13 years after the initial one was conducted entirely through phone interviews because the researchers and many of the participants had moved from the initial study location (see Huston et al. 2001). Many of the measures were derived from interview questions that were taken from paper and pencil questionnaires. In this instance and in other examples of interviews utilizing primarily closed-ended questions, the data yielded are probably quite comparable to that of standard questionnaires. Yet interviews can also involve various procedures used for different purposes. Interviews composed of open-ended questions typically involve an attempt to gather in-depth information, with the researcher using probing questions to facilitate thoughtful responses. The typical goal of such interviews is to “understand the lived experience of other people and the meaning they make of that experience” (Seidman 2006: 9). The most obvious purpose of such interviews is to investigate phenomena that cannot be observed, but qualitative researchers also strive to treat in-depth interviews as collaborative encounters that can allow important questions and phenomena to emerge as participants and researchers discuss a given topic (Lindlof and Taylor 2011). That is, unlike closed response questionnaires, in-depth interviews have the potential to reveal aspects of communication that the researchers did not even set out to study. Of course, questionnaires can include open-ended questions so they have some potential to reveal unexpected information, but questions typically preclude the interactive and probing aspect of interviews that can elicit subtle insights. Consider, for example, Goldsmith, Lindholm, and Bute’s (2006) study of cardiac patients and their partners. One common communication dilemma for partners that emerged from the interviews involved partners’ desire to encourage healthy lifestyle choices seeming to contradict their desire not to “nag” their partner. Not only is it important to recognize that the understanding of this dilemma emerged from the interviews, but it is worth noting that it could be the defining feature of an encounter while simultaneously being something that could not be understood by even the most well-placed observer. Imagine, for example, that a man recovering from a heart attack is resisting his physicians’ and family’s attempts to increase his activity level. One morning at breakfast, his wife says, “Wow – it’s just a nice day out today. Are you going to walk to work?” This could be the wife’s attempt to suggest that her husband should walk, and depending on

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how often his wife makes similar suggestions and his sensitivity, the husband may even hear that seemingly simple question as nagging. Regardless of how successfully the wife is able to influence without coming across as a nag, understanding the significance of that episode requires understanding what it means to those individuals. Whatever behaviors could be objectively recorded or coded from that interaction may provide other useful information (e.g., about the emotional expressions of both individuals), but observations would be unlikely to reveal why this encounter is important in that particular relationship. Sometimes the meaning that people attribute to their communication is the most meaningful thing one can know about it.

4.4 Physiological measures In recent years, there has been a marked increase in the use of physiological measurement among interpersonal communication researchers (for a review, see Floyd and Afifi 2011). Cardiovascular reactivity, for example, can be measured by assessing participants’ heart rate and blood pressure at baseline, in the presence of a stressor, and during a recovery period. These physiological indicators can be used to assess responses such as being engaged, challenged, or stressed, which can provide insights into individuals’ emotional states, communication experiences, or individual characteristics (Goyal et al. 2008).

4.4.1 Advantages and disadvantages of physiological measures Physiological data reveal information about the internal processes of research participants that cannot be obtained through other techniques (Smith and Uchnio 2008). In some cases, this information may prove crucial to understanding communication; for example, Afifi (2011) noted that some adolescents discussing their parents’ divorce with one of the parents showed marked stress reactions in their cortisol levels, even when they reported that the conversations were not stressful and there were no obvious behavioral manifestations of strain. Such findings suggest that physiological measures sometimes can provide information about processes about which individuals are not consciously aware. Using an entirely different technique, Buck and Powers (2005) explored the use of fMRI measurement to assess biologically based emotions. Their findings revealed that individuals’ internal emotional experiences and their external expressions of those emotional states often differ. Furthermore, McRae and colleagues (2008) conducted a study of gender differences in emotion regulation. They found that, contrary to most communication research, which finds few differences in how males and females express emotion, the physiological responses between genders differed significantly. Taken together, these studies and others using similar fMRI measures (e.g., Ochsner et

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al. 2002) suggest that by not considering physiological responses, our understanding of individuals’ experiences and communication patterns is, at best, incomplete. Although physiological measures promise to add much to our understanding of what people experience during interpersonal communication, these techniques have limitations. Most obviously, interpersonal communication, to a large extent, involves the exchange and negotiation of meaning. Physiological measures can show that individuals are aroused or experiencing some emotional state, but they cannot tell us what those responses mean to the individuals or to the interaction. Moreover, some scholars have argued that the claims made about some physiological data have been oversold. For instance, Legrenzi, Umilta, and Anderson (2011: 17) suggest that brain images have been presented as if the readings are much more precise and objective than they actually are and that scientific descriptions of which parts of brains are involved in certain processes oversimplify the extent to which multiple processes occur simultaneously. We are not suggesting that brain imaging is not useful, but it is worth recognizing that even purported experts are only beginning to understand what such measures really can and cannot tell us. Given that some physiological assessment tools are relatively new and technologically sophisticated, we should be cautious about expecting too much from them. It is important to separate the “gee whiz” aspect of such techniques from what can be learned about the substance of interpersonal communication.

5 The utility of using multiple measurement techniques As argued above, every measurement technique (and every specific measure) has strengths and weaknesses (Feeney and Noller 2012). One response to the realization that different measurement techniques have different strengths is to suggest that researchers try to match techniques to constructs based on these strengths. For instance, it is reasonable to suggest that researchers try to use observational methods when the construct involves overt behaviors and use self-report measures when the construct pertains to individuals’ psychological processes, such as memories, attitudes, or emotions (Levine 2011). There are certainly instances in which the focus of study clearly warrants the use of a particular measurement technique over others. People may not even be aware of many of their nonverbal behaviors, for example, and they would not be able to articulate the intent or purpose of them (Burgoon, Guerrero, and Manusov 2011). Thus, if nonverbal behaviors are important constructs in a study, it would typically be best to use observations and coding rather than self-reports. Although there are plainly instances when one type of measurement is better than another, given that there is no single best way to conceptualize any phenomenon, it is often useful to use multiple measures to assess the same general con-

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struct. Studying the same phenomena with a variety of methods offers different perspectives and insights (Cappella 1991), and examining the same phenomena with different lenses can have various benefits. When various measures of a construct converge, it provides evidence of validity (Campbell and Fiske 1959), and when various methods are triangulated with each other, consistent results provide more confidence in the findings than is possible from any one method (Webb et al. 1966). For example, there are various ways to assess the demand/withdraw pattern of communication, which involves one person nagging or criticizing while the other person tries to avoid discussing the topic of criticism. Researchers can observe indications of demand/withdraw in laboratory conversations, but demand/ withdraw is inherently a subjective pattern – the same behavior that counts as nagging in one couple may be viewed as simply discussing an issue in another. This problem can be addressed by asking participants to self-report on their demand and withdraw in a laboratory conversation, but demand/withdraw often plays out over the course of days, not within a single conversation (Christensen and Heavey 1993). Such lengthy behavioral patterns can be assessed with retrospective reports, but those are susceptible to various biases. None of these measurement strategies is perfect, but if a study includes all three and all three reveal similar results, this lends a level of credibility to the findings that none of the measures could have conferred on its own. Indeed, some of our research has used this strategy, and the results from different assessments of demand/withdraw often evince very similar patterns (e.g., Caughlin and Malis 2004). For communication phenomena like demand/withdraw patterns, different measurement choices may point researchers to similar conclusions. Sometimes, however, data from multiple measures may highlight different patterns. Often this would impugn the validity of one or more of the measures. Alternatively, such discrepancies may be informative, perhaps revealing important conceptual distinctions that were not initially apparent. For example, in the aforementioned PAIR Project (e.g., Huston et al. 2001), there were two assessments of the frequency of conflict, and each was taken when the couples were newlyweds and again shortly after their first and second anniversaries. The first measure of conflict was a retrospective report in which participants were asked to report on the amount of conflict they had in their marriage in the past two months, and the second was based on the aggregated telephone diary reports (Caughlin and Huston 1996). Both the husbands’ and wives’ reports portrayed a similar story. Based on the diary assessments, there was a clear decline in the number of overt conflicts over the first three years of the marriages, and this was true regardless of whether the couples were happy or unhappy, or whether they remained married or divorced by their thirteenth anniversary. The retrospective reports of conflict, however, evinced a different pattern, with these reports of conflict frequently increasing over the first three phases of the study, particularly among couples who ended up divorcing. At first glance, these results may seem puzzling, but taken together they

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suggest that among couples who eventually divorce, the number of times they engage in overt conflicts goes down over time, yet they believe (or feel as if) they are continuing to have intense conflicts often. A likely explanation of this seeming inconsistency is that some couples experience serial arguments (Johnson and Roloff 1998) that do not get resolved, and they think about them, even on days they do not have an overt disagreement. This suggests that there is a potentially important conceptual distinction between the number of ongoing conflicts a couple is experiencing and the frequency at which they overtly engage in communication about these issues. Obviously, neither measure alone could have suggested such a distinction, demonstrating that using multiple assessments of a general construct can provide insights into different aspects of that construct (or suggest that what was thought to be a single construct may more usefully be thought of as two).

6 Special measurement considerations for interpersonal communication scholars In many respects, the principles of sound measurement transcend research areas. Such issues as reliability and validity are not specific to the study of interpersonal communication, and in fact, most writing on these measurement issues has been produced by scholars in other disciplines. This is generally unproblematic, but the fact that much of the received wisdom about measurement is influenced by scholars studying other topics frames the discussion and thinking about measurement in ways that foreground some issues and background others. This implies that there are some particular considerations that scholars of interpersonal communication should be aware of, and we discuss four of these below.

6.1 What constitutes an adequate sampling of ongoing interaction? Interpersonal interaction researchers must choose not only what aspect of interaction to study but also the timeframe to study. Scholars who use observational methods, for example, typically record a sample of interaction that occurs on one occasion, and they usually assess the consistency across coders at that particular time (see e.g., Baesler and Burgoon 1987; Caughlin 2003). This aspect of reliability is important, and if the conceptual interest is in understanding that segment of communication, reliability during that interaction is the main concern. However, there is another aspect of reliability that can be equally important in interpersonal communication but is usually ignored. If one is interested in the communication that occurs in ongoing interpersonal relationships, it is important to ask whether

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the sample of interaction events examined is adequate (Huston and Robins 1982). In close relationships, it is possible to have a measure that evinces the qualities of good reliability at a point in time, but is nevertheless not a reliable indicator of what happens generally, even if the measure itself is otherwise unbiased and valid. Conceptually, single observations are problematic whenever the interest is in how a dyad interacts in general (e.g., the frequency of a particular communication pattern), not just in one encounter. We know that there is variation in how people interact; for example, there is considerable variation in how much negativity spouses express to each other based on their experiences at work (Doumas, Margolin, and John 2003). Scholars must heed these kinds of patterns as they assess interpersonal interaction. In designing a diary study, for instance, researchers should consider how many entries are needed to compose a sufficiently reliable index of the communication variables of interest. As is the case with increasing the number of items on a scale, assessing communication on more occasions tends to increase the reliability of the assessment. Of course, how many samples of communication are needed to compose a reliable index of interpersonal interaction depends on factors such the fluctuation rate of the behaviors. If the behaviors vary greatly, more assessments are necessary for an adequate sampling. If there is little fluctuation, fewer samples of interaction may be sufficient. If couples’ interaction in response to a particular situation is highly routinized, a single assessment may be sufficient to make assessments about what happens in general.

6.2 Is the very nature of interpersonal communication changing? In recent years, there has been a tremendous increase in the use of communication technologies to engage in interpersonal communication. To date, research on the use of those technologies has tended to study face-to-face communication separately from technologically mediated communication, either by focusing on a particular medium (e.g., texting) or by comparing face-to-face to technologically mediated communication (see Chapter 23, Walther and Lee). Yet, there have been recent calls for researchers to begin to study how people use both simultaneously (Baym 2009), and recent evidence suggests that in many close relationships the interconnections between face-to-face encounters and technologically mediated interaction are extensive and complex (Caughlin and Sharabi 2012). These interconnections between online and offline interpersonal communication present some potentially major challenges for current ways of assessing interpersonal communication. If it becomes the norm for relational partners to use their smartphones while interacting face-to-face, would a traditional sample of laboratory interaction (which usually would preclude such technologies) be representative of usual interpersonal communication? Moreover, given that mediated communication allows people to extend streams of conversation even when they

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are apart, this could exacerbate the problem of observing a segment of interaction that is disconnected from the larger conversation about a particular topic. For example, because people in close relationships may have the expectation that they can always get some message through to a partner (even if it is only a brief text), does that change what it means for one person to try avoiding a conflict topic? Can “nagging” now continue remotely? It is not clear how profound these changes ultimately will be, but they do raise questions that interpersonal scholars should be mindful of when they make measurement decisions. It may be that classic observational methods will always tell us something useful, such as how skillful a dyad can be when called on to demonstrate exemplary behavior in a laboratory (Reis and Gable 2000), but we should also recognize that as communication technologies become more embedded into the fabric of interpersonal interaction, the classic laboratory techniques may be less representative of how people actually engage in interpersonal communication.

6.3 Pitfalls of using measures originally developed for other purposes Before using even the most thoroughly-tested existing research measure, it is important to consider whether it is valid for the purposes of a particular investigation. This is always a potential issue, but it appears to be particularly salient for scholars of interpersonal communication because researchers from a number of allied fields have developed pertinent measures, but the purposes of the research often differ enough that the measure is not valid beyond its original use. One example that has been discussed extensively involves two measures that are commonly used to assess marital satisfaction: the Marital Adjustment Test (MAT; Locke and Wallace 1959) and the Dyadic Adjustment Scale (DAS; Spanier 1976). The original purpose of these measures was to assess how well spouses accommodate each other and to provide a tool that could be used to predict marital well-being (see Locke and Wallace 1959). That is, they were originally intended to serve as global indicators of marital functioning; consequently, they include questions on a wide range of topics, including both general questions about how happy spouses are and reports of specific communication behaviors, such as self-disclosure and conflict engagement. This broad scope is probably a valid overall assessment of marital well-being, but it is a valid assessment of marital satisfaction. Marital satisfaction is usually conceptualized as a subjective evaluation of a marriage; that is, it is an attitude toward marriage. Because both the MAT and DAS include a mix of items reporting on such attitudes but also on communication behaviors within the marriage, they are plainly not valid measures of marital satisfaction (Huston, McHale, and Crouter 1986; Norton 1983). Given that these measures confound satisfaction with questions about communication, communication scholars should be

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particularly leery of using the MAT and DAS. Using these measures makes it impossible to assess associations between relational communication and satisfaction because any covariances could be due to the confound in the measures. The MAT and DAS are particularly clear examples of measures that are probably valid for one purpose being misused for other purposes, but they illustrate the point that measures always need to be evaluated with respect to the specific constructs under investigation. Another prominent example of a well-established measure that is misused is the series of FACES (Family Adaptability and Cohesion Evaluation Scales) measures developed by Olson and his colleagues (Olson 2000; Olson et al. 1982). The FACES instrument measures the broad constructs of cohesion and adaptability in families, and there is abundant evidence that it provides useful diagnostic information about the functioning of families. Yet, these measures may not be ideal for use in studies of interpersonal communication in families. The original measure of cohesion, for instance, included assessments of widely varied constructs, including emotional bonding, boundaries, coalitions, and time spent together. This mix of affective, behavioral, and structural concepts is unlikely to be unidimensional; indeed, many of the items for the cohesion measure did not load strongly on a single dimension in Olson et al.’s (1982) original report, with factor loadings as low as .13. Given that at least some of the items involve reports of communication behaviors, communication researchers should be particularly cautious about using this cohesion measure for the same reasons they usually want to avoid the MAT and DAS.

6.4 Confusing statistical evidence with proof of validity Our focus has been on the logic of measurement rather than the details of measurement development. There are, of course, sophisticated statistical tools for gathering evidence that relates to validity. Confirmatory factor analysis provides a technique for deciding whether the empirical findings from a measure are congruent with the conceptualized associations among items (Brown 2006). For instance, items intended to assess the same construct should covary highly with each other but should not vary strongly with items intended to assess conceptually distinct constructs. As useful as such techniques can be, it is important not to apply them blindly or indiscriminately. For example, if a researcher is attempting to index a set of behaviors, such as behaviors that contribute to health risks, factor analyses are inappropriate because they presume that there is some underlying construct that causes the various items to be intercorrelated (Bollen and Lennox 1996). An overall assessment of risky behaviors is composed of a number of specific behaviors, which means that the behaviors are not all caused by an underlying risky lifestyle construct. In such instances, the assumptions behind confirmatory analysis do not apply.

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Even when traditional statistical tools are applicable, empirical findings are only meaningful when used in conjunction with informed and thoughtful conceptualization. Decisions about measurement should always be rooted not only in statistical findings but also in the larger scholarly literature and sound theorizing. For instance, just because items covary highly in a given study with one sample at a particular time does not imply that those items should be considered part of the same construct or that they will always covary highly. Braiker and Kelley (1979), for instance, found that feelings of love and maintenance behaviors were highly and positively correlated early in heterosexual relationships but were empirically distinct in more committed relationships. If Braiker and Kelley had based their measurement on the findings early in the relationships, they may have lumped love and maintenance together into a common index, but the empirical findings from another point in relationships are consistent with a conceptual distinction between love and maintenance. Unfortunately, researchers sometimes make conceptual decisions based purely on the statistical information from a single study. For example, one enduring problem in relationship research is the fact that some scholars use high correlations between spouses’ attitudes as a rationale for combining those attitudes into a single score. Thompson and Walker (1982) long ago pointed out that this is problematic. Consider the case of marital satisfaction. As argued above, marital satisfaction is a subjective evaluation, yet researchers sometimes average the scores of husbands’ and wives’ attitudes toward their marriage. Regardless of how correlated those two values are, we know that husbands and wives sometimes do differ in their attitudes toward marriage, and conceptually, an attitude is a property of an individual; thus, it does not make sense to create a combined measure of satisfaction (Thompson and Walker 1982). Reliance solely on statistical support can lead researchers to make invalid indices. Specific to interpersonal communication, scholars should be particularly mindful of this issue because some behaviors that are known to be conceptually distinct are highly correlated under some conditions. In fact, some studies that base measurement decisions purely on statistical covariance have collapsed an exceedingly wide range of communication behaviors into a single measure. For instance, in a highly cited study by Karney and Bradbury (1997), the covariances among observed behaviors were used to create a single measure of communication, with positive behaviors and negative behaviors simply viewed as two ends of a single dimension. Regardless of how high the correlation between negativity and positivity is in a particular study, there is not a conceptually sound justification for combining these. In addition to reducing the domain of interpersonal research into a single variable, this is problematic because numerous other studies have shown that negative and positive behaviors are often empirically distinct, both in terms of having low covariance and in terms of predicting different outcomes (for reviews, see Caughlin and Huston 2006; Gable and Reis 2001). Not only

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do positive and negative behaviors in relationships have distinct outcomes, but they also appear to moderate each other in some instances (e.g., Huston and Chorost 1994; Smith, Vivian, and O’Leary 1990), a finding that would be obscured if these behaviors were lumped together. Given that positive and negative behaviors are clearly distinct, it is unclear exactly what any findings relating to a combined measure of positive and negative behaviors even mean; are they due to high levels of one set of behaviors, low levels of the other, or some interaction between the two that was not systematically examined? As implied by O’Keefe’s (1987) argument about analyzing messages, there probably is not a right answer to how many constructs should be gleaned from interpersonal communication in dyads, but it is clear that reducing interpersonal interaction to one construct is conceptually indefensible. In short, interpersonal communication researchers should be cautious about forming indices of communication based solely on the statistical information from a single study.

7 Conclusion The goal of this chapter has been to provide a conceptual overview of important issues involved in measuring social interaction. We have argued that there is no single correct or best way to assess interpersonal communication constructs. No measure of interpersonal communication is perfect. Indeed, the only way to make the study of interpersonal communication entirely objective is to ignore the meaning of it. Even when researchers have elaborate and precise coding of actual interaction data, they often end up describing what they observe in subjective terms, such as what the participants are trying to accomplish. Gottman’s interpretation of wives’ and husbands’ behaviors as seeking and accepting influence is just one of many examples (Gottman et al. 1998). Recognizing the inherent weaknesses of all measures does not mean that every assessment is equally useful. There are still better and worse practices, and more and less useful ways to assess social interaction. For example, rather than seeking a single valid measure, we suggest that researchers attempt to use multiple assessments when possible and also remain sensitive to the particular challenges inherent in measuring something as complex and dynamic as interpersonal interaction.

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Meina Liu

6 Analyzing social interaction data Abstract: During the past two decades, methodological advances have allowed interpersonal communication researchers to expand their theoretical understanding of communication processes by testing new relationships within and across dyads, groups, social networks, and through time. This chapter describes several techniques that have been used to analyze social interaction in these settings. Some of the methods are both theoretical and methodological, such as the ActorPartner Interdependence Model for analyzing dyadic data, the Social Relations Model for analyzing group data, and Social Network Analysis for analyzing data from communication networks. Other methods are purely statistical, such as Hierarchical Linear Modeling for analyzing group data, and Lag Sequential Analysis for analyzing time series data. The chapter provides a brief explanation for each method and a research example to demonstrate how it has been utilized in communication research. Finally, the reader is warned of the potential danger of being enamored with statistical techniques at the expense of theoretical advancement. Key Words: social interaction, dyadic data analysis, multi-level modeling, social relations model, network analysis, time series analysis

1 Introduction Although interpersonal communication intrinsically involves interaction between two or more persons (e.g., arguing, giving advice, gaining compliance, seeking or providing emotional support, managing conflict, negotiating), there has been a dearth of research examining the content and function of actual messages between communicants in dyads or groups. Much of social scientific research in communication studies individuals, partly due to the fact that standard statistical methods such as analysis of variance (ANOVA) and multiple regression require independent observations (Kashy and Kenny 2000). The problem of analyzing non-independent data was formally discussed as early as in the 1970s (e.g., Kraemer and Jacklin 1979). Only more recently has there been a resurgence of interest in this issue. As new research methods and statistical techniques have been developed, scholars have begun to expand the way they think theoretically by analyzing interactions taking place in families (Dailey 2008; Honeycutt, Wellman, and Larson 1997), work groups (Bonito 2003; Franz and Jin 1995), medical settings (Garroutte et al. 2006; File and Todman 2002), educational settings (Chiu and Khoo 2005), between couples (Krueger 1983; O’Riordan 2007; Sevier et al. 2008), friends or dating partners (Keck and Samp 2007), ingroup/outgroup members (Reid and Ng 2006), strangers

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(Dindia, Fitzpatrick, and Kenny 1997), and negotiators (Liu 2009, 2011; Liu and Wilson 2011; Putnam and Jones 1982). This chapter describes several statistical techniques that have had a significant impact on the relationships communication scholars have been able to discover through observations of social interaction in various settings. As Caughlin and Basinger (see Chapter 5) explain, observations of social interaction have been coded in terms of both frequencies and sequences of discrete behaviors, as well as using continuous scales, before they are analyzed statistically. Issues concerning the reliability and validity of interaction coding are explicated in detail by Folger, Hewes, and Poole (1984). The goal of this chapter is to provide a survey of a variety of statistical techniques that can be used to analyze social interaction data collected from dyads, groups, social networks, and over time, using illustrative examples.

2 Analyzing dyadic data The dyad is often considered the fundamental unit of interpersonal interaction or interpersonal relations (Kenny, Kashy, and Cook 2006). People involved in interactions may influence how each other thinks, feels, and acts; mutual influence being the sine qua non of interpersonal communication (see Chapter 1, Berger; Cappella 1987). Therefore, dyad members’ responses, whether obtained from self-reports or observational coding, are often nonindependent. If individuals are treated as the unit of analysis when their data in fact are correlated, and traditional statistical methods (e.g., ANOVA, regression analysis) that assume independent observations are used, the estimates for variance or population means can become either too liberal or too conservative (Kashy and Kenny 2000). For this reason, many scholars who examined dyadic interactions perform dyadic level analyses. For example, negotiation research that examined frequencies and sequences of bargaining tactics often treated the dyad as the unit of analysis and predicted their effects on joint gains (e.g., Olekalns and Smith 2000). As a result, little was known about the dynamic interaction process leading to favorable or unfavorable individual outcomes. The Actor-Partner Interdependence Model (APIM) was introduced by Kenny, Kashy, and Cook (2006) to tackle the issue of interdependence in dyadic research. The APIM allows researchers to model and test not only actor effects (i.e., the impact of a person’s independent variable on his or her own dependent variable) but also partner effects (i.e., the impact of the partner’s independent variable on the actor’s dependent variable). This paradigm is bringing the dyad into the mainstream study of interpersonal interactions and relationships. Since its publication, Kenny et al.’s (2006) book Dyadic Data Analysis has been widely cited. An increasing number of articles published in communication journals report studies using

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the APIM approach, ranging from intergroup communication (Reid and Ng 2006), parent-child communication (Dailey 2008), to communication in intimate relationships (Afifi, et al. 2009; Dailey, Romo, and Thompson 2011; Hanzal and Segrin 2009; O’Riordan 2007), friendships (Arroyo and Segrin 2011), and conflict and negotiation (Lakey and Canary 2002; Liu and Wilson 2011). By disentangling actor effects, partner effects, and emergent actor-by-partner “relationship” effects, researchers have been freed from an individualistic orientation to interpersonal communication research and have begun to theorize about genuinely relational and interactive communication processes. Three methods have been introduced to estimate the APIM: pooled regression, multilevel modeling (MLM), and structural equation modeling (SEM). The pooled regression method involves estimating two regression equations (within-dyads and between-dyads regressions) and then pooling the results to estimate the APIM parameters. For example, Lakey and Canary (2002) used this method to assess how conflict parties’ sensitivity to their partners’ goals influenced their own and their partners’ use of conflict management tactics. This method has been the least popular one because (a) it requires cumbersome computations that can easily lead to errors, (b) it cannot be used to estimate unsaturated models (i.e., models in which some variables only have actor effects, whereas others, only partner effects) and (c) it does not allow for missing data (Kenny et al. 2006). Consequently, this chapter focuses on the MLM and SEM approaches.

2.1 Estimating the APIM with MLM Multilevel Modeling (MLM), sometimes used interchangeably with Hierarchical Linear Modeling (HLM), is the most flexible estimation approach for the APIM. It can be used for both distinguishable (e.g., parents-children, husbands-wives, employers-employees, physicians-patients) and indistinguishable (e.g., friends, siblings) dyads, using SPSS, SAS, HLM, or MLwiN. In SPSS and SAS, the data set must be structured in a pairwise fashion so that each individual’s outcome score can be associated with not only his or her own predictor scores, but also his or her partner’s predictor scores. The correlation coefficients between dyad members’ scores indicate the degree of nonindependence, referred to as intraclass correlations. Each individual is treated as one case and there are two cases for each couple; therefore, the sample size is the number of individuals. Within MLM, there are two levels: Level 1 is person and Level 2 is group. MLM treats data from dyad members as individual scores nested within a group that has n = 2. For example, Liu (2009) assessed (a) whether negotiators’ anger would cause themselves to increase distributive bargaining tactics, but it would cause their counterparts to decrease distributive bargaining tactics, and (b) whether such actor and partner effects would be moderated by national culture and bargaining role. The SPSS syntax for assessing these hypotheses are as follows:

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MIXED DistributiveBargaining WITH Aanger Panger culture role /FIXED = Aanger Panger culture role Aanger*culture Panger*culture Aanger*role Panger*role culture*role | SSTYPE(3) /PRINT = SOLUTION TESTCOV /REPEATED = person | SUBJECT(dyad) COVTYPE(CS). The MIXED statement allowed the researcher to assess whether a person’s distributive bargaining tactics (Distributive Bargaining) is a function of (a) his or her own anger (Aanger, the actor effect), (b) his or her partner’s anger (Panger, the partner effect), and (c) whether the actor and partner effects of anger would be moderated by culture (Aanger*culture, Panger*culture) or bargaining role (Aanger*role, Panger*role), after controlling for the main and interaction effects of culture and role. The PRINT option requests that SPSS print the estimates for fixed effects. A fixed effect reveals the effect of an independent variable on a dependent variable for each Level 1 unit (i.e., person) that does not vary across the Level 2 unit (i.e., dyad). The SUBJECT option identifies the level at which there is independence (i.e., the dyad level), and the REPEATED option treats the individual scores as repeated measures in the dyad. CS refers to compound symmetry, which forces the degree of unexplained variance for the dyad members to be equal (see Kenny et al. 2006). The estimates from SPSS are presented in Table 1. Results showed that both actor’s anger, b = .03, t(108) = 2.12, p < .05, and partner’s anger, b = –.02, t(108) = –1.95, p = .05, had significant effects on negotiators’ use of distributive bargaining tactics. In addition, there was a significant interaction effect between actor’s anger and bargaining role, b = .03, t(108) = 2.11, p < .05. Kenny and colleagues (2006) suggest that the effect sizes of the independent variables can be computed from the t values of the parameter estimates: r = . For example, for actor’s anger, r is .20. To use HLM for estimating the APIM, two separate data files need to be created: a level-1 data set similar to the pairwise data structure required in SPSS and SAS where each individual has a record, and a level-2 data set that has one record for each dyad and includes the variables that vary only between dyads. A dyad identification number must be included in both data sets. If analyses involve assessment of interaction effects, interaction terms need to be created and added to the data file, after performing necessary centering in HLM to avoid multicollinearity issues. A case in point is Dailey’s (2008) study of the how parents’ and adolescents’ nonverbal behaviors (i.e., nonverbal involvement, pleasantness, expressiveness, and anxiety) predicted each other’s level of confirmation (i.e., validation, acceptance). Three models were conducted to estimate the APIM effects. First, an initial, unconditional model without any predictors was conducted. The error terms of the baseline model not only provided a measure of partial intraclass correlation on

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Table 1: APIM Results from SPSS for the Anger in Negotiation Study. Estimates of Fixed Effects. Parameter

Intercept Aanger1 Panger1 role culture Aanger1 * role Aanger1 * culture Panger1 * role Panger1 * culture role * culture

Estimate

–.44 .03 –.02 –.01 –.01 .03 .00 .01 –.00 –.02

Std. Error

.02 .01 .01 .01 .01 .01 .01 .01 .01 .01

df

62 108 108 62 62 103 108 103 108 62

t

–30.20 2.12 –1.95 –1.25 –.69 2.11 .41 .97 –.33 –2.02

Sig.

.000 .04 .05 .22 .49 .04 .69 .33 .74 .05

95 % Confidence Interval Lower Bound

Upper Bound

–.468437 .001708 –.048383 –.030842 –.039783 .001530 –.019323 –.012606 –.028366 –.038249

–.410267 .050436 .000345 .007155 .019407 .051078 .029322 .036942 .020279 –.000227

Dependent Variable: Distributive Bargaining

the outcome variable between dyad members (i.e. 11 % of the variance in the dependent variable is between dyads and 89 % is within dyads), which indicated whether MLM was appropriate, but also allowed the researcher to assess the overall variance accounted for by predictor variables added in subsequent models. Second, a model was conducted with member status (parent vs. adolescent), participant sex, and their interaction as predictors of confirmation (the DV). Only member status was found to have a significant influence on confirmation, b = .64, t(108) = 7.29, p < .001, with parents exhibiting more confirmation than adolescents. To determine the amount of variance uniquely accounted for by member status in comparison with the unconditional (baseline) model, a follow-up model was conducted by only including member status as a predictor variable. This comparison showed that member status accounted for 23.9 % of the variance at the individual level and no variance at the dyadic level. Finally, a model was conducted with all actor and partner nonverbal dimensions as predictor variables, along with member status as a control variable. Table 2 summarizes the results. Parents’ and adolescents’ confirmation was found to be associated with both their own nonverbal behaviors (i.e., vocalic involvement and expressiveness, kinesic expressiveness), but also the other party’s nonverbal behaviors (i.e., vocalic involvement, kinesic involvement and pleasantness). The amount of variance in the outcome variable additionally accounted for by the nonverbal predictor variables were computed by comparing the last model with both the baseline, unconditional model, and the member status only model.

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Table 2: APIM Results from HTM for the Nonverbal Behaviors and Confirmation Study. Fixed Effect

Coefficient

SE

t-ratio

df

p-value

Intercept Member (Adolescent vs. Parent) Actor Vocalic Involvement Actor Vocalic Pleasantness Actor Vocalic Expressiveness Actor Kinesic Involvement Actor Kinesic Pleasantness Actor Kinesic Expressiveness Partner Vocalic Involvement Partner Vocalic Pleasantness Partner Vocalic Expressiveness Partner Kinesic Involvement

5.60 0.67 0.64 0.26 –0.46 –0.01 0.21 –0.26 0.58 –0.19 –0.20 –0.31

0.09 0.11 0.22 0.16 0.17 0.15 0.17 0.12 0.26 0.14 0.18 0.15

60.55 6.34 2.98 1.71 –2.67 –0.08 1.25 –2.15 2.23 –1.37 –1.08 –2.04

55 98 98 98 98 98 98 98 98 98 98 98