Interpersonal Adaptation

Burgoon, Judee K.; Stern, Lesa A.; Dillman, Leesa

doi:10.1017/cbo9780511720314

Cited by 332 publications

(131 citation statements)

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“…Interpersonal interactions are at the core of social relationships between individuals (e.g., Burgoon et al 1995;Hinde 1979a, b;Kelley et al 1983Kelley et al , 2003. ''Each partner's behavior affects the other partner's subsequent behavior within a single interaction episode and each interaction episode influences future episodes'' (Reis et al 2000, pp.…”

Section: Interpersonal Behavior Of Coaches and Clients During The Coamentioning

confidence: 99%

“…In other words, each partner's (verbal and nonverbal) behavior influences the other partner's subsequent behavior (Berscheid and Reis 1998). This results in non-random interaction patterns (e.g., Burgoon et al 1995;Kiesler 1996). Current interaction sequences influence future sequences and the evolving relationship (Hinde 1999).…”

Section: Interpersonal Behavior Of Coaches and Clients During The Coamentioning

confidence: 99%

“…Numerous communication and interpersonal theories have examined how the interaction behavior of one interactant is answered by the interacting partner and how interacting partners adapt to one another over the course of their interaction process (for an overview, see Burgoon et al 1995;Kiesler 1996). A basic assumption of theoretical approaches aiming to understand social interaction processes is that of similar or convergent response behaviors versus dissimilar or divergent response behaviors (Burgoon et al 1993).…”

Section: Interpersonal Behavior Of Coaches and Clients During The Coamentioning

confidence: 99%

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Coaches and Clients in Action: A Sequential Analysis of Interpersonal Coach and Client Behavior

2014

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Purpose Despite calls for studying interaction processes in coaching, little is known about the link between coachclient interactions and coaching success. In particular, interpersonal behavior in coaching remains unexplored, although it is considered highly relevant to social relationships and interaction outcomes. This study takes first steps to address this gap. Design/Methodology/Approach We examined the dynamics of coaches' and clients' interpersonal behavior based on the two basic dimensions affiliation and dominance. Furthermore, we investigated the link between emergent interpersonal behavior patterns and coaching outcomes. To this end, we videotaped and analyzed a total of 11,095 behavioral acts nested in 30 coach-client dyads. Findings Sequential analysis showed that reciprocal friendliness patterns were positively linked to working alliance. Coaches' dominant-friendly interaction behavior particularly activated clients, in terms of showing dominance during the coaching interaction process. Clients' dominance was linked to their overall goal attainment. ImplicationsOur results highlight the importance of interpersonal behavior for coaching success. Specifically, our findings suggest that dominance interaction patterns are context-and relation-specific, offering an explanation for contradicting empirical studies on interpersonal dominance. For coaches, our study implies that high awareness for interpersonal signals can help establish a positive atmosphere and activate clients' dominance. Originality/Value This empirical study uses behavior observation and interaction analysis to understand the interpersonal dynamics during coaching sessions. Our results increase our theoretical understanding of coaching effectiveness by shedding light on the micro-level behavioral dynamics that drive successful coaching processes.

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Section: Interpersonal Behavior Of Coaches and Clients During The Coamentioning

confidence: 99%

Section: Interpersonal Behavior Of Coaches and Clients During The Coamentioning

confidence: 99%

Section: Interpersonal Behavior Of Coaches and Clients During The Coamentioning

confidence: 99%

See 1 more Smart Citation

Coaches and Clients in Action: A Sequential Analysis of Interpersonal Coach and Client Behavior

2014

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“…In most cases, children and adults adapt all aspects of their communicative behavior to converge with those of their partner, including speech amplitude, pitch, rate of articulation, pause structure, response latency, phonological features, gesturing, drawing, body posture, and other aspects (Burgoon et al, 1995;Fay et al, 2010;Giles et al, 1987;Welkowitz et al, 1976). Interpersonal conversation is a dynamic adaptive exchange in which speakers' lexical, syntactic, and speech signal features all are tailored in a moment-by-moment manner to their conversational partner.…”

Section: Communication Accommodation Theory: Multimodal Dialogue Convmentioning

confidence: 99%

The Paradigm Shift to Multimodality in Contemporary Computer Interfaces

Oviatt¹,

Cohen²

2015

Synthesis Lectures on Human-Centered Informatics

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Human-Centered Informatics (HCI) is the intersection of the cultural, the social, the cognitive, and the aesthetic with computing and information technology. It encompasses a huge range of issues, theories, technologies, designs, tools, environments, and human experiences in knowledge work, recreation and leisure activity, teaching and learning, and the potpourri of everyday life. The series publishes state-of-the-art syntheses, case studies, and tutorials in key areas. It shares the focus of leading international conferences in HCI.

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“…The anthropologist Edward T. Hall [1] coined the term "proxemics", and proposed that physiological influences shaped by culture define zones of proxemic distances [2,7]. Mehrabian [5], Argyle and Dean [8], and Burgoon et al [9] analyzed spatial behaviors as a function of the interpersonal relationship between social partners. Schöne [10] was inspired by the spatial behaviors of biological organisms in response to stimuli, and investigated human spatial dynamics from physiological and ethological perspectives; similarly, Hayduk and Mainprize [11] analyzed the personal space requirements of people who are blind.…”

Section: Introductionmentioning

confidence: 99%

Proxemic Feature Recognition for Interactive Robots: Automating Metrics from the Social Sciences

2011

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Abstract. In this work, we discuss a set of metrics for analyzing human spatial behavior (proxemics) motivated by work in the social sciences. Specifically, we investigate individual, attentional, interpersonal, and physiological factors that contribute to social spacing. We demonstrate the feasibility of autonomous realtime annotation of these spatial features during multi-person social encounters. We utilize sensor suites that are non-invasive to participants, are readily deployable in a variety of environments (ranging from an instrumented workspace to a mobile robot platform), and do not interfere with the social interaction itself. Finally, we provide a discussion of the impact of these metrics and their utility in autonomous socially interactive systems.

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Interpersonal Adaptation

Cited by 332 publications

References 0 publications

Coaches and Clients in Action: A Sequential Analysis of Interpersonal Coach and Client Behavior

Coaches and Clients in Action: A Sequential Analysis of Interpersonal Coach and Client Behavior

The Paradigm Shift to Multimodality in Contemporary Computer Interfaces

Proxemic Feature Recognition for Interactive Robots: Automating Metrics from the Social Sciences

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