Approaches for Inserting Neurodynamics into the Training of Healthcare Teams
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Team neurodynamics is the study of the changing rhythms and organizations of teams from the perspective of neurophysiology. As a discipline, team neurodynamics is located at the intersection of collaborative learning, psychometrics, complexity theory, and neurobiology with the resulting principles and applications both drawing from and contributing to these specialties. This article describes the tools for studying team neurodynamics and illustrates the potential and the challenges these methods and models have for better understanding healthcare team training and performance. The fundamental metric is neurodynamic organization, which is the tendency of teams and its members to enter into prolonged metastable relationships when they experience and resolve uncertainty. The patterns of these relationships are resolved by symbolic modeling of electroencephalographic (EEG) power levels of the team members, and the information in these patterns are calculated using information theory tools. The topics discussed in this chapter anticipate the time when dynamic biometric data can contribute to our understanding of how to rapidly determine a team’s functional status, and how to use this information to optimize outcomes and training. The rapid, dynamic, and task neutral measures make the lessons learned in healthcare applicable to other complex group and team environments, and provide a foundation for incorporating these models into machines to support the training and performance of teams.
KeywordsTeam neurodynamics EEG Debriefing Entropy Information theory
- Abersold, M., (2018). Simulation-based learning: No longer a novelty in undergraduate education. OJIN: The Online Journal of Issues in Nursing 23(2). https://doi.org/10.3912/ojin.vol23no02ppt39.
- Ancona, D., & Chong, C. L. (1999). Cycles and synchrony: The temporal role of context in team behavior. Research on Managing Groups and Teams, 2, 33–48.Google Scholar
- Baker, D. P., Amodeo, A. M., Krokos, K. J., Slonim, A., & Herrera, H. (2010). Assessing teamwork attitudes in healthcare: Development of the TeamSTEPPS® teamwork attitudes questionnaire. Quality and Safety Health Care, 19, e49.Google Scholar
- Cooke, N. J., Gorman, J. C., & Kiekel, P. (2008). Communication as team-level cognitive processing. In M. P. Letsky, N. W. Warner, S. M. Fiore & C. A. P. Smith (Eds.), Macrocognition in teams. Ashgate: Burlington, VT, USA.Google Scholar
- Draschkow, D., Heikel, E., Võ, M., Fiebach, C. J., & Sassenhagen, J., (2018). No evidence from MVPA for different processes underlying the N300 and N400 incongruity effects in object-scene processing. Neuropsychologia, 120, 9–17. ISSN 0028-3932. https://doi.org/10.1016/j.neuropsychologia.
- Farooqui, A. A., & Manly, T. (2018). Hierarchical cognition caused task related deactivations but not just in default mode regions. eNeuro, 5(6), ENEURO.0008-18.2018.Google Scholar
- Flack, J. (2017). Life’s information hierarchy. In S. I. Walker, P. C. W. Davies & G. F. R. Ellis (Eds.), From matter to life: Information and causality. Cambridge: Cambridge University Press.Google Scholar
- Garner, A. J. P., Thompson, J., Vedral, V., & Gu, M. (2017, April 16). Thermodynamics of complexity and pattern manipulation. arXiv:1510:00010v3[quant.ph].
- Grimm, D., Gorman, J. C., Stevens, R. H., Galloway, T., Willemsen-Dunlap, A. M., & Halpin, D. J. (2017). Demonstration of a method for real-time detection of anomalies in team communication. In Proceedings of the Human Factors and Ergonomics Society 59th Annual Meeting (pp. 282–286). Santa Monica, CA: Human Factors and Ergonomics Society.Google Scholar
- Guastello, S. J., & Peressini, A. F. (2018). Development of a synchronization coefficient for biosocial interactions in groups and teams. Nonlinear Dynamics, Psychology, Life Sciences, 48, 3–33.Google Scholar
- James, R. G., Ellison, C. J., & Crutchfield, J. P. (2011). Anatomy of a bit: Information in a time series observation (Santa Fe Institute Working Paper 11–05). arXiv:1105.2988v1[cs.IT].
- Mosier, K. H., & Chidester, T. R. (1991). Situation assessment and situation awareness in a team setting. In Y. Queinnec & F. Daniellou (Eds.), Designing for everyone (pp. 798–800). London: Taylor & Francis.Google Scholar
- Mullen, T. (2012). NITRC: CleanLine: Tool/Resource Info. Retrieved from http://www.nitrc.org/projects/cleanline.
- O’Neil, H. F., Jr., Chung, G. K., & Brown, R. (1997). Use of networked simulations as a context to measure team competencies. In H. F. O’Neil Jr. (Ed.), Workforce readiness: Competencies and assessment (pp. 411–452). Mahwah, NJ: Erlbaum.Google Scholar
- Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001). A default mode of brain function. Proceedings of National Academy of Science of USA, 98, 676–682.Google Scholar
- Salas, E., Stagl, K.C., & Burke, C. S. (2004). 25 Years of team effectiveness in organizations: Research themes and emerging needs. In C. L. Cooper & I. T. Robertson (Eds.), International review of industrial and organizational psychology (Vol. 19, pp. 56–101). New York: Wiley.Google Scholar
- Salas, E., Stevens, R., Gorman, J., Cooke, N. J., Guastello, S., & von Davier, A. (2015, September). What will quantitative measures of teamwork look like in 10 years? In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 59 (1), 235–239 (Sage Publications).Google Scholar
- Sanger, J., Muller, V., & Lindenberger, U. (2012, November). Intra-and interbrain synchronization and network properties when playing guitar in duets. Frontiers in Human Neuroscience, Article 312. https://doi.org/10.3389/fnhum.201200312.
- Schippers, M., Roebroeck, A., Renken, R., Nanetti, L., & Keysers, C. (2010). Mapping the information flows from one brain to another during gestural communication. Proceedings of National Academy of Science of USA, 107, 9388–9393.Google Scholar
- Sedley, W., & Cunningham, M. O. (2013). Do cortical gamma oscillations promote or suppress perception? An under-asked question with an over-assumed answer. Frontiers in Human Neuroscience. 7, Article 595.Google Scholar
- Shockley, K., Santana, M.-V., & Fowler, C. A. (2003). Mutual interpersonal postural constraints are involved in cooperative conversation. Journal of Experimental Psychology: Human Perception and Performance, 29, 326–332.Google Scholar
- Staropoli, P. C., Gregori, N. Z., Junk, A. K., Galor, A., Goldhardt, R., Goldhagen, B. E., et al. (2018). Surgical simulation training reduces intraoperative cataract surgery complications among residents. Simulation in Healthcare, 13, 11–15. https://doi.org/10.1097/SIH.0000000000000255.CrossRefGoogle Scholar
- Stephens, G., Silbert, L., & Hasson, U. (2010). Speaker-listener neural coupling underlies successful communication. Proceedings of the National academy of Sciences of the United States of America. Retrieved from www.pnas.org/cgi/doi/10.1073/pnas.1008662107.
- Stevens, R. H., & Galloway, T. (2017, May). Are neurodynamic organizations a fundamental property of teamwork? Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2017.00644.
- Stevens R. H., Galloway T., Lamb J., Steed R., & Lamb C. (2017). Linking team neurodynamic organizations with observational ratings of team performance. In A. von Davier, M. Zhu & P. Kyllonen (Eds.), Innovative assessment of collaboration. New York, NY: Springer.Google Scholar
- Stevens, R.H., Galloway, T., & Willemsen-Dunlap, A., (2016). Intermediate neurodynamic representations: A pathway towards quantitative measurements of teamwork? Human Factors & Ergonomics National Meeting, 60(1), 1996–2000.Google Scholar
- Stevens, R. H., Galloway, T. & Willemsen-Dunlap, A. (2017). Low level predictors of team dynamics: A neurodynamic approach. In E. Salas, B. Vessey & L. B. Landon (Eds.), Research in managing groups and teams. Research series: Team dynamics over time, Vol. 18, pp. 71–92. Emerald Insight.Google Scholar
- Stevens, R.H., Galloway, T., & Willemsen-Dunlap. (2018). Quantitative modeling of individual, shared and team neurodynamic information. Human Factors, 60, 1022–1034.Google Scholar
- Stevens, R.H., Galloway, T., Gorman, J., Willemsen-Dunlap, A., Halpin, D., & Grimm, D. (2018, October). Making sense of team information. Paper presented at 2018 Human Factors & Ergonomics National Meeting, Philadelphia, PA.Google Scholar
- Stevens, R., Galloway, T. L., & Willemsen-Dunlap, A. (2019). Advancing our understandings of healthcare team dynamics from the simulation room to the operating room: A neurodynamic perspective. Frontiers in Psychology, 10, 1660. https://doi.org/10.3389/fpsyg.2019.01660
- Vergauwe, E., & Cowan, N. (2014, March). A common short-term memory retrieval rate may describe many cognitive procedures. Frontiers of Human Neuroscience, Article 126. https://doi.org/10.3389/fnhum.2014.00126.
- von Davier, A. A., & Halpin, P. F. (2013). Collaborative problem solving and the assessment of cognitive skills: Psychometric considerations. ETS Research Report Series, 2013(2), 1–36. https://doi.org/10.1002/j.2333-8504.2013.tb02348.x.CrossRefGoogle Scholar
- Zenati, M. A., Leissner, K. B., Zorca, S., Kennedy-Metz, L., Yule, S., & Dias, R. (2019). First reported use of team cognitive workload for root cause analysis in cardiac surgery. Seminar Thoracic Surgery.Google Scholar