Physiologically informed predictability of a teammate’s future actions forecasts team performance

In collaborative environments, a deep understanding of multi-human teaming dynamics is essential for optimizing performance. However, the relationship between individuals' behavioral and physiological markers and their combined influence on overall team performance remains poorly understood. To explore this, we designed a triadic human-collaborative sensorimotor task in virtual reality (VR) and introduced a predictability metric to examine team dynamics and performance. Our findings reveal a strong connection between team performance and the predictability of a team member's future actions based on other team members' behavioral and physiological data. Contrary to conventional wisdom that high-performing teams are highly synchronized, our results suggest that physiological and behavioral synchronizations among team members have a limited correlation with team performance. These insights provide a quantitative framework for understanding multi-human team dynamics, paving the way for deeper insights into team dynamics and performance.

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Publication Details

Journal
iScience
Published
2025-04-17
DOI
https://doi.org/10.1016/j.isci.2025.112429
Citations
3
Primary Topic
Team Dynamics and Performance
Type
article
Field-Weighted Citation Impact
7.32

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article

Physiologically informed predictability of a teammate’s future actions forecasts team performance

Richard Lee, Yinuo Qin, Paul Sajda, Xiaoxiao Sun et al.
3 citations
iScience
Team Dynamics and Performance
7.32
article

Physiologically informed predictability of a teammate’s future actions forecasts team performance

Richard Lee, Yinuo Qin, Paul Sajda, Xiaoxiao Sun, Weijia Zhang
article en
3 citations

Abstract

In collaborative environments, a deep understanding of multi-human teaming dynamics is essential for optimizing performance. However, the relationship between individuals' behavioral and physiological markers and their combined influence on overall team performance remains poorly understood. To explore this, we designed a triadic human-collaborative sensorimotor task in virtual reality (VR) and introduced a predictability metric to examine team dynamics and performance. Our findings reveal a strong connection between team performance and the predictability of a team member's future actions based on other team members' behavioral and physiological data. Contrary to conventional wisdom that high-performing teams are highly synchronized, our results suggest that physiological and behavioral synchronizations among team members have a limited correlation with team performance. These insights provide a quantitative framework for understanding multi-human team dynamics, paving the way for deeper insights into team dynamics and performance.

iScienceVol. 28(5)
Columbia University (US)
National Science Foundation, U.S. Department of Defense, Air Force Office of Scientific Research, Army Research Laboratory
Openalex Percentile: Top 4%
Team Dynamics and Performance
7.32
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