Neurophysiological estimation of team psychological metrics

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Abstract

The goal of this study was to explore the feasibility of continuous neurophysiological assessment of different psychological aspects of a team process. The teams consisted of the MBA students who discussed and attempted to solve a case problem dealing with corporate social responsibility (i.e. child labor). At the end of the team process, two types of psychological metrics (i.e., engagement and leadership) were assessed by team members, both at the individual and team levels. These metrics showed significant correlations with the team performance scores derived by four trained coders. Two of them rated the teams' solutions in terms of effective problem solving, decisiveness, and creativity. The other two coders rated the level of moral reasoning displayed in the solutions. The psychological metrics were then estimated based on quantitative electroencephalography (qEEG). Different modeling techniques, such as linear and quadratic discriminant function analysis (DFA) and linear regression were applied to the processed qEEG data. The models were evaluated through auto-validation, but also through cross-validation to test stability of the models in the team-independent training setting. The experimental results suggested that qEEG could be effectively used in the team settings as an estimator of individual and team engagement, as well as the leadership qualities shown by team members. Our findings suggest that qEEG can help in understanding, and perhaps building, optimal teams and team processes. © 2013 Springer-Verlag Berlin Heidelberg.

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APA

Stikic, M., Berka, C., Waldman, D., Balthazard, P., Pless, N., & Maak, T. (2013). Neurophysiological estimation of team psychological metrics. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8027 LNAI, pp. 209–218). https://doi.org/10.1007/978-3-642-39454-6_22

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