Physiologically informed predictability of a teammate’s future actions forecasts team performance
Year: 2025
Type: article
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.
Source: iScience
Authors: Yinuo Qin, Richard T. Lee, Weijia Zhang, Xiaoxiao Sun, Paul Sajda
Institution: Columbia University
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $3,240
Awards: G3884088288, GCR: Emotionally Responsive Computation and Communication, G5259331294, MEASURING, TRACKING AND MODULATING HUMAN DECISION-MAKING NEURAL CIRCUITS "IN THE WILD", G56008422, CHS: Small: Optimizing Human-Machine Performance via Neurofeedback and Adaptive Autonomy, G6002470426, G608057831, G7375395331, G8787749906
OpenAlex ID: W4409534716