Publications by authors named "Anthony F Peressini"

Emergent phenomena exhibit interesting dynamics when considered individually. The present article examines two emergent processes that could be occurring simultaneously in an intense team interaction: the emergence of leaders and the emergence of autonomic synchrony within teams making dynamic decisions. In the framework of panarchy theory and related studies on complex systems, autonomic synchrony would be a fast dynamic that is shaped or controlled by leadership emergence, which is a slower dynamic.

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Situation awareness (SA) is a mental state that is instrumental to performance of complex dynamic tasks. SA within teams is thought to be supported by favorable social conditions within the team. The present study was organized in two parts: (a) causal relationships among SA, group cohesion, and autonomic synchrony, the latter being a fundamentally nonlinear process, and (b) the combined impact of the three variables on performance in a dynamic decisions task.

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Objective: This study evaluated the causal relationships among situation awareness (SA), cohesion, and autonomic synchrony () within teams. SA is often a team effort and should be more accurate in better-functioning teams.

Background: Cohesive teams perform better overall, although the relationship appears reciprocal; the relationship to SA has not been considered previously.

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To further the understanding of how to build or reduce synchrony in a work team, we examined two principles for defining the optimal condition to produce or limit synchrony: (a) the empath-driver ratio (relative strength of the stronger influencer compared to the receptive strength of any member in the group), and (b) the balance between autocorrelated autonomic arousal (degree to which members' signals are independent of other group members) and the degree of influence that transfers from each group member to other group members. In study 1, we employed a series of computational simulations designed to manipulate the four variables. The results indicated that there is a four-way balance between driver strength, empath strength, autocorrelational and transfer effects among team members.

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Synchronization is a special case of self-organization in which one can observe close mimicry in behavior of the system components. Synchrony in body movements, autonomic arousal, and EEG activity among human individuals has attracted considerable attention for their possible roles in social interaction. This article is specifically concerned with autonomic synchrony and finding the best model for the dyadic relationships, with regard to both theoretical and empirical accuracy, that could be extrapolated to synchrony levels for groups and teams of three or more people.

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Synchronization of autonomic arousal levels within dyads and larger teams has been associated with several types of social-behavioral outcome. One previous study reported greater physiological influence (brain activity in one area of the parietal lobe associated with verbal activity) of leaders on followers than of followers on leaders; influence was measured pairwise within triadic problem solving groups. The present study explored synchronized autonomic arousal with leadership outcomes in two experiments with group sizes of three to eight members.

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Psychologists have had a long-standing interest in the connections between group processes and team performance. The biopsychosocial perspective has piqued an interest in the connection between team processes and performance and coordinated and synchronized physiological arousal levels among team members. Studies of synchronization in work teams have been stalled by the lack of a metric that captures the total synchronization within teams of three or more people.

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Human dyads and larger teams tend to acquire synchronized movements and autonomic arousal levels while working together or simply socializing. The synchronization of arousal patterns is of theoretical interest for group dynamics because they may add predictive value to the dynamics of group cohesion and team performance. This study examined the four-way relationship among experimental conditions: team size, task difficulty, time pressure (between-subjects) and subsequent experimental sessions (within-subjects).

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The synchronization of autonomic arousal levels within dyads and larger teams has become a potentially important variable in the explanation of team performance and group processes. Synchronization research with groups of three or more members has been challenging because of limited means for quantifying relationships that are more extensive than dyads. This article presents an empirical investigation of group performance and participation using a new synchronization coefficient that is grounded in nonlinear dynamical systems theory.

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This study investigated the stationarity of electrodermal time series collected in situations where turn taking in human interactions are involved. In this context, the stationarity of the time series is the extent to which a simple model can be used to fit the entire time series. The experiment involved seven participants in an emergency response simulation against one opponent.

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Behavioral and physiological synchronization have important implications for work teams with regard to workload management, coordinated behavior and overall functioning. This study extended previous work on the nonlinear statistical structure of GSR series in dyads to larger teams and included subjective ratings of workload and contributions to problem solving. Eleven teams of 3 or 4 people played a series of six emergency response (ER) games against a single opponent.

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Time series analysis is often challenged by the presence of transient functions. We examined some types of transients found in time series of events that lend themselves to symbolic dynamics analysis through the method of orbital decomposition, which is based on the principle that chaotic series arise from coupled oscillators. Synthetic data sets were constructed to study the impact of intrusive events, intrusive series, merged functions, non-coupled oscillators, and driving oscillations on the patterns of final statistics obtained from orbital decomposition analysis.

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