Cognitive load theory and its applications in emergency medicine education

Throughout my medical education thus far, I have been very drawn to simulation and cognitive load research related to emergency medicine. This has provided me with an appreciation for the applications of cognitive load theory to diverse areas within the specialty, including medical education.

What is cognitive load?

The cognitive load theory was developed in the late 1980s and explores the ways in which the amount of mental effort affects your working memory, and subsequently, learning (1). Specifically, learning involves processing sensory stimuli through various forms of memory, until the stimuli are encoded into your long-term memory. When the working memory capacity is surpassed, the ability to acquire or learn new information can become limited and may lead to poor performance or errors. Since the development of this theory, research in this area has been expanding to enhance instructional design to optimize learning.

Fig. 1. The basic structure of memory, extending from sensory input to encoding of long-term memory (obtained from Mancinetti et al. (2019)) - (2)

Objective and subjective measures of cognitive load

Global collaborative and independent research initiatives have identified an array of objective physiologic measures (e.g. pupillometry, heart rate, galvanic skin response and EEG parameters), subjective psychometric measures (e.g. Paas, NASA Task Load Index (NASA-TLX)) and secondary task measures that are indicative of an individual’s cognitive load (3). Current research has been investigating the validity of these physiologic metrics beyond a controlled laboratory setting, in order to determine accurate measures that can be applied within dynamic and real-life settings. This can potentially allow us to monitor learners’ cognitive load in real-time and adjust teaching strategies accordingly to optimize learning.

Fig. 2. NASA-TLX cognitive load scale (obtained from Shively, J, NASA-Ames Research Center (2016)) and the Paas rating scale (obtained from Paas et al. (2008)) - (4-5)

Applications of cognitive load theory to emergency medicine education

A paper by Croskerry (2014) highlighted various factors that can influence cognitive load in the emergency department setting and lead to clinical errors, including overcrowding, and fatigue and circadian dyssynchronization secondary to shiftwork (6). Of relevance, a previous post on emDocs explored numerous strategies for emergency providers to mitigate some of this cognitive load (link here: http://www.emdocs.net/cognitiveload/). Furthermore, experienced emergency physicians have developed strategies to better manage their cognitive resources, effectively reducing their cognitive load relative to trainees in similar clinical scenarios. Therefore, there are many ways in which cognitive load theory can be implicated in emergency medicine and used to not only enhance the functional and spatial design of the emergency department, but to also optimize simulation training and other areas of learning for emergency medicine trainees. For example, Johannessen et al. (2019) evaluated the association between physiologic measures and the Paas scale in trauma team leaders using wearable technology during the resuscitation response, in order to better understand cognitive load expression in emergency physicians during traumas (7). Additionally, another study used galvanic skin response, heart rate and a modified Paas scale to assess the “Beat the Stress Fool” protocol in reducing mental effort during clinical simulation (7). Fraser et al. (2018) investigated the link between the cognitive load theory and debriefing simulations. Specifically, they evaluated whether the categorization of mental loads during debriefing can improve learning of this vital and complex skill, and they additionally discussed strategies to alleviate some of the associated cognitive load (8).  

Overall, cognitive load is an exciting and evolving area in research and has many diverse applications in emergency medicine and medical education as a whole. 

References and Further Reading

  1. Sweller, J. (1988). Cognitive Load During Problem Solving: Effects on Learning. Cognitive Science, 12, 257-285.
  2. Mancinetti, M., Guttormsen, S., Berendonk, C. (2019). Cognitive load in internal medicine: What every clinical teacher should know about cognitive load theory. European Journal of Internal Medicine, 60, 4-8. 
  3. Paas, Fred, et al. (2003). Cognitive Load Measurement as a Means to Advance Cognitive Load Theory. Educational Psychologist, 38(1), 63–71.
  4. Shively, J, NASA-Ames Research Center. (2016). Workload Measurement in Human Autonomy Teaming: How and Why? National Aeronautics and Space Administration. Accessed May 2020 at https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20160008388.pdf
  5. Paas, F., Ayres, P., Pachman, M. (2008). Assessment of cognitive load in multimedia learning therory, methods and applications. Recent Innovations in Educational Technology that Facilitate Student Learning, Chapter 2, pg.11-35. 
  6. Croskerry, P. (2014). ED cognition: any decision by anyone at any time. CJEM, 16(1), 13-9.
  7. Johannessen, E., Szulewski, A., Radulovic, N., Gilic, F., Braund, H., Wu, K., White, M., Rodenburg, D., Howes, D., Davies, C. (2019). Measuring cognitive load in a clinical setting: Medical learning and practice. (M.A.Sc thesis), Queen’s University, Kingston, Canada. 
  8. Fraser, K.L. et al. (2018). Cognitive Load Theory for debriefing simulations: implications for faculty development. Advances in Simulation, 3, 1-8.
Cite this article as: Nada Radulovic, Canada, "Cognitive load theory and its applications in emergency medicine education," in International Emergency Medicine Education Project, August 23, 2021, https://iem-student.org/2021/08/23/cognitive-load-theory/, date accessed: October 18, 2021

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