Predicting Resilience Losses in Dyadic Team Performance

Hill, Y., Hartigh, den, R., Cox, R. F. A., Jonge, de, P. & Van Yperen, N. W., 2019, (Accepted/In press) In : Nonlinear dynamics, psychology, and life sciences.

Research output: Contribution to journalArticleAcademicpeer-review

In the current study, we applied the dynamical systems approach to obtain novel insights into resilience losses. Dyads (n = 42) performed a lateral rhythmical pointing (i.e., Fitts) task. To induce resilience losses and transitions in performance, dyads were exposed to positive and negative scoring scenarios. To assess the complexity of the dyadic performance, reflecting their resilience, we performed cross-recurrence quantification analyses. Then, we tested for temporal patterns indicating resilience losses. Specifically, we applied lag-1 autocorrelations to assess critical slowing down and mean squared successive differences (MSSD) to assess critical fluctuations. Although we did not find evidence that scoring scenarios produce performance transitions across individuals, we did observe transitions in each condition. Contrary to the lag-1 autocorrelations, results suggest that increases in the MSSD signal transitions in human performance. Moreover, the MSSD show increases in fluctuations in performance, but stable levels of complexity for positive transitions. For negative transitions fluctuations increase for both performance and complexity, suggesting resilience losses. Together, the results suggest that combining information of critical fluctuations in a system’s performance and its complexity can predict both positive and negative performance transitions following resilience losses within the system.
Original languageEnglish
JournalNonlinear dynamics, psychology, and life sciences
Publication statusAccepted/In press - 2019


  • Complexity, Critical Slowing Down, Cross-recurrence Quantification Analysis (CRQA), Dynamical Systems, Transitions

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