Pupillometry as a tool to study expertise in medicine
Main Article Content
Abstract
Background Pupillometry has been studied as a physiological marker for quantifying cognitive load since the early 1960s. It has been established that small changes in pupillary size can provide an index of the cognitive load of a participant as he/she performs a mental task. The utility of pupillometry as a measure of expertise is less well established, although recent research in the fields of education, medicine and psychology indicates that differences in pupillary size during domain-specific tasks allows differentiation between experts and novices in appropriately designed experiments.
Purpose The goal of this review is to explore the existing body of evidence for the use of pupillometry as a measure of expertise and to identify its strengths and constraints within the context of expertise research in the medical sciences.
Results Pupillometry is a robust metric that allows researchers to better understand cognitive load in medical practitioners with varying levels of expertise. In medical expertise research, it has been used to study surgeons, anesthetists and emergency physicians. Its strengths include its ability to provide quantitative and objective outputs, to be measured unobtrusively with new technology and to be precisely computed as cognitive load changes over the course of completion of a task. Constraints associated with this methodology include its potential inaccuracy with changes in ambient light and pupillary accommodation as well as the need for relatively expensive equipment.
Conclusion With recent technological advances, pupillometry has become a simple and robust method for quantifying physiological changes attributable to cognitive load and is increasingly being utilized in medical education. It can be used as a reliable marker of mental effort and has been shown to differentiate levels of expertise in medical practitioners.
Article Details
FLR adopts the Attribution-NonCommercial-NoDerivs Creative Common License (BY-NC-ND). That is, Copyright for articles published in this journal is retained by the authors with, however, first publication rights granted to the journal. By virtue of their appearance in this open access journal, articles are free to use, with proper attribution, in educational and other non-commercial settings.
References
Aston-Jones, G., & Cohen, J. D. (2005). An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performance. Annu. Rev. Neurosci., 28, 403-450.
Beatty, J. (1982). Task-evoked pupillary responses, processing load, and the structure of processing resources. Psychological bulletin, 91(2), 276.
Beatty, J., & Kahneman, D. (1966). Pupillary changes in two memory tasks. Psychonomic Science, 5(10), 371-372.
Burgess, P. W., & Simons, J. S. (2005). Theories of frontal lobe executive function: clinical application. In P. W. Halligan & D. T. Wade (Eds.), Effecitveness of Rehabiliation for Cognitive Deficits (pp. 211-231). New York: Oxford Univeristy Press.
Diamond, A. (2013). Executive Functions. Annual review of psychology, 64, 135-168. doi: 10.1146/annurev-psych-113011-143750
Ericsson, K. A., & Kintsch, W. (1995). Long-term working memory. Psychological review, 102(2), 211.
Hess, E. H., & Polt, J. M. (1960). Pupil size as related to interest value of visual stimuli. Science, 132(3423), 349-350.
Hess, E. H., & Polt, J. M. (1964). Pupil size in relation to mental activity during simple problem-solving. Science, 143(3611), 1190-1192.
Hicks, C. M., Bandiera, G. W., & Denny, C. J. (2008). Building a Simulation‐based Crisis Resource Management Course for Emergency Medicine, Phase 1: Results from an Interdisciplinary Needs Assessment Survey. Academic Emergency Medicine, 15(11), 1136-1143.
Jiang, X., Zheng, B., Tien, G., & Atkins, M. (2013). Pupil response to precision in surgical task execution. Studies in health technology and informatics, 184, 210.
Kahneman, D., Tursky, B., Shapiro, D., & Crider, A. (1969). Pupillary, heart rate, and skin resistance changes during a mental task. Journal of Experimental Psychology, 79(1p1), 164.
Klingner, J., Kumar, R., & Hanrahan, P. (2008). Measuring the task-evoked pupillary response with a remote eye tracker. Paper presented at the Proceedings of the 2008 symposium on Eye tracking research & applications.
Klingner, J., Tversky, B., & Hanrahan, P. (2011). Effects of visual and verbal presentation on cognitive load in vigilance, memory, and arithmetic tasks. Psychophysiology, 48(3), 323-332.
Laeng, B., Sirois, S., & Gredebäck, G. (2012). Pupillometry a window to the preconscious? Perspectives on psychological science, 7(1), 18-27.
Lang, G. K. (2015). Ophthalmology: Thieme.
Marshall, S. P. (2002). The index of cognitive activity: Measuring cognitive workload. Paper presented at the Human factors and power plants, 2002. proceedings of the 2002 IEEE 7th conference on.
Paas, F., Tuovinen, J. E., Tabbers, H., & Van Gerven, P. W. (2003). Cognitive load measurement as a means to advance cognitive load theory. Educational psychologist, 38(1), 63-71.
Palinko, O., Kun, A. L., Shyrokov, A., & Heeman, P. (2010). Estimating cognitive load using remote eye tracking in a driving simulator. Paper presented at the Proceedings of the 2010 symposium on eye-tracking research & applications.
Richstone, L., Schwartz, M. J., Seideman, C., Cadeddu, J., Marshall, S., & Kavoussi, L. R. (2010). Eye metrics as an objective assessment of surgical skill. Annals of surgery, 252(1), 177-182.
Schulz, C., Schneider, E., Fritz, L., Vockeroth, J., Hapfelmeier, A., Wasmaier, M., . . . Schneider, G. (2011). Eye tracking for assessment of workload: a pilot study in an anaesthesia simulator environment. British journal of anaesthesia, 106(1), 44-50.
Sweller, J. (2010). Element interactivity and intrinsic, extraneous, and germane cognitive load. Educational psychology review, 22(2), 123-138.
Szulewski, A., Fernando, S. M., Baylis, J., & Howes, D. (2014). Increasing pupil size is associated with increasing cognitive processing demands: A pilot study using a mobile eye-tracking device. Open Journal of Emergency Medicine, 2014.
Szulewski, A., Roth, N., & Howes, D. (2015). The Use of Task-Evoked Pupillary Response as an Objective Measure of Cognitive Load in Novices and Trained Physicians: A New Tool for the Assessment of Expertise. Academic Medicine, 90(7), 981-987. doi: 10.1097/acm.0000000000000677
Tien, T., Pucher, P. H., Sodergren, M. H., Sriskandarajah, K., Yang, G.-Z., & Darzi, A. (2015). Differences in gaze behaviour of expert and junior surgeons performing open inguinal hernia repair. Surgical endoscopy, 29(2), 405-413.
Whipple, B., Ogden, G., & Komisaruk, B. R. (1992). Physiological correlates of imagery-induced orgasm in women. Archives of sexual behavior, 21(2), 121-133.
Young, J. Q., Van Merrienboer, J., Durning, S., & Ten Cate, O. (2014). Cognitive load theory: Implications for medical education: AMEE guide no. 86. Medical teacher, 36(5), 371-384.
Zheng, B., Jiang, X., & Atkins, M. S. (2015). Detection of Changes in Surgical Difficulty: Evidence From Pupil Responses. Surgical innovation, 22(6), 629-635. doi: 10.1177/1553350615573582