Healthcare Teams Neurodynamically Reorganize When Resolving Uncertainty

Abstract

Abstract:Research on the microscale neural dynamics of social interactions has yet to be translated into improvements in the assembly, training and evaluation of teams. This is partially due to the scale of neural involvements in team activities, spanning the millisecond oscillations in individual brains to the minutes/hours performance behaviors of the team. We have used intermediate neurodynamic representations to show that healthcare teams enter persistent (50-100 s) neurodynamic states when they encounter and resolve uncertainty while managing simulated patients. Each of the second symbols was developed situating the electroencephalogram (EEG) power of each team member in the contexts of those of other team members and the task. These representations were acquired from EEG headsets with 19 recording electrodes for each of the 1-40 Hz frequencies. Estimates of the information in each symbol stream were calculated from a 60 s moving window of Shannon entropy that was updated each second, providing a quantitative neurodynamic history of the team's performance. Neurodynamic organizations fluctuated with the task demands with increased organization (i.e., lower entropy) occurring when the team needed to resolve uncertainty. These results show that intermediate neurodynamic representations can provide a quantitative bridge between the micro and macro scales of teamwork.

Foliage Plants Improve Concentration and Emotional Condition of Elementary School Students Performing an Intensive Assignment

“…The potential difference is determined by placing the dry electrode in contact with the scalp, amplifying the measured electric signals, and collecting the processed data. This device is mainly used in the field of neuroscience (Onton et al, 2016;Stevens et al, 2016) and has been certified for safety by the European Commission and Federal Communications Commission. A brain-mapping program (Bio-scan; Bio-Tech, Daejeon, Korea) was used to map the mean EEG measurements to the subject's brain during the experiment.…”

Advancing Our Understandings of Healthcare Team Dynamics From the Simulation Room to the Operating Room: A Neurodynamic Perspective

“…While we have reported neurodynamic analyses of over a dozen healthcare team performances (Stevens et al, 2016, 2018b; Stevens and Galloway, 2017), in this paper, we highlight the dynamics of two, as the same anesthesiologist who performed the intubation during the live patient surgery performed two previous simulations with three intubation events.…”

Using Communication to Modulate Neural Synchronization in Teams

“…Another possible reason for the null results may be because the teams were coordinating during “typical conditions.” Other research has used neural measures of entropy as an indicator of uncertainty, where high entropy represents high uncertainty or “surprise” that needs to be resolved by the team (Stevens and Galloway, 2017 ). Prior research has found that teams tend to have low-to-average neural entropy as they work in typical conditions and that entropy increases with uncertainty and decreases after uncertainty reach a tipping point, or threshold, where the team needs to resolve the uncertainty during the task session (e.g., Stevens et al, 2016 ). Uncertainty can be inherent to the task setting, task performance, or introduced artificially in the task session by perturbing the team during task performance.…”

“…We did not include perturbations in this study, which may have resulted in a lack of variability in neural entropy. Also, both the NEO and Minecraft tasks have less uncertainty, or surprise, built into them than more realistic tasks, such as medical simulations (e.g., Stevens et al, 2016 ). It may also be plausible that the relationship between entropy and uncertainty is mediated by attention, where entropy is an indicator of when joint attention is needed from the team to resolve uncertainty in the task.…”

“…Prior research usually inserts identifiable events meant to disrupt the team’s coordination to induce changes in dynamical parameters in the time series (e.g., Gorman et al, 2016 ). Future research should perturb the team as the team members are coordinating to induce variability in neural dynamics or use tasks with more built-in uncertainty (e.g., during healthcare simulation training; Stevens et al, 2016 ).…”