Anesthesiologists work in complex work environments where optimal scanning of information is critical for patient safety. The Salience, Effort, Expectancy, Value (SEEV) model can be used to model attention distributions of individuals. We used an existing data set of eye tracking data of anesthesiologists inducing general anesthesia to (1) develop a method for considering the effort parameter in the model in such an environment and (2) investigate the explanatory power of an EEV model compared to an EV model. To operationalize effort, we created a 3D model using Unreal Engine 4. We used Markov Chain Monte Carlo simulations to obtain EV and EEV model predictions. The inclusion of effort did not yield an advantage over the model which did not include effort. We discuss methodological considerations for future research and suggest to simultaneously consider salience and effort to be able to assess the role of effort more accurately.
Get full access to this article
View all access options for this article.
References
1.
BosA. J.RuscioD.CassavaughN. D.LachJ.GunaratneP.BacksR. W. (2015). Comparison of novice and experienced drivers using the SEEV model to predict attention allocation at intersections during simulated driving. Paper presented at the 8th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design, Salt Lake City, UT. https://doi.org/10.17077/drivingassessment.1560.
2.
CassavaughN. D.BosA.McDonaldC.GunaratneP.BacksR. W. (2013). Assessment of the SEEV model to predict attention allocation at intersections during simulated driving. Paper presented at the Proceedings of the 7th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design, Bolton Landing, NY. https://doi.org/10.17077/drivingassessment.1509.
GollanB.FerschaA. (2016). SEEV-Effort-Is it enough to model human attentional behavior in public display settings. Paper presented at the Proceedings of the 8th International Conference on Future Computational Technologies and Applications (FUTURE COMPUTING’16).
5.
GrundgeigerT.KlöffelC.MohmeS.WurmbT.HappelO. (2017). An investigation into the effects of real vs. simulated cases and level of experience on the distribution of visual attention during induction of general anaesthesia. Anaesthesia, 72(5), 624-632. https://doi.org/10.1111/anae.13821.
6.
GrundgeigerT.RoewerN.GrundgeigerJ.HurtienneJ.HappelO. (2015). Body posture during simulated tracheal intubation: GlideScope® videolaryngoscopy vs Macintosh direct laryngoscopy for novices and experts. Anaesthesia, 70(12), 1375-1381. https://doi.org/10.1111/anae.13190.
7.
GrundgeigerT.WurmbT.HappelO. (2020). Modelling visual attention of junior and senior anesthesiologists during the induction of general anesthesia in real and simulated cases. IEEE Transactions on Human- Machine Systems. https://doi.org/10.1109/THMS.2020.2983817.
8.
HastingsW. K. (1970). Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57(1), 97-109. https://doi.org/10.1093/biomet/57.1.97.
9.
HorreyW. J.WickensC. D.ConsalusK. P. (2006). Modeling drivers' visual attention allocation while interacting with in-vehicle technologies. Journal of Experimental Psychology: Applied, 12(2), 67-78. https://doi.org/10.1037/1076-898X.12.2.67.
10.
KahnemanD. (1973). Attention and effort (vol. 1063): Citeseer.
11.
KohR. Y.ParkT.WickensC. D.Teng OngL.Noi ChiaS. (2011). Differences in attentional strategies by novice and experienced operating theatre scrub nurses. Journal of Experimental Psychology: Applied, 17(3), 233-246. https://doi.org/10.1037/a0025171.
12.
Martin-EmersonR.WickensC. D. (1992). The vertical visual field and implications for the head-up display. Paper presented at the Proceedings of the Human Factors and Ergonomics Society Annual Meeting. https://doi.org/10.1177/154193129203601810.
13.
McCluskeyM. K.CullenK. E. (2007). Eye, head, and body coordination during large gaze shifts in rhesus monkeys: Movement kinematics and the influence of posture. Journal of Neurophysiology, 97(4), 2976-2991. https://doi.org/10.1152/jn.00822.2006.
14.
SandersA. F.HoutmansM. J. (1985). Perceptual processing modes in the functional visual field. Acta Psychologica, 58(3), 251-261.
15.
SchulzC. M.EndsleyM. R.KochsE. F.GelbA. W.WagnerK. J. (2013). Situation awareness in anesthesia concept and research. Anesthesiology, 118(3), 729-742. https://doi.org/10.1097/ALN.0b013e318280a40f.
16.
SeagullF. J.WardR.MillsJ.GoodrichC.XiaoY. (2004). Measuring Awkwardness of Workplace Layout: Dispersion of Attentional and Psychomotor Resources within the Anesthesia Workspace. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 48(15), 1755-1758. https://doi.org/10.1177/154193120404801527.
17.
SteelmanK. S.McCarleyJ. S.WickensC. D. (2011). Modeling the control of attention in visual workspaces. Human Factors, 53(2), 142-153. https://doi.org/10.1177/0018720811404026.
18.
SteelmanK. S.McCarleyJ. S.WickensC. D. (2013). Great expectations: Top-down attention modulates the costs of clutter and eccentricity. Journal of Experimental Psychology: Applied, 19(4), 403–419. https://doi.org/10.1037/a0034546.
19.
SteelmanK. S.McCarleyJ. S.WickensC. D. (2017). Theory-based models of attention in visual workspaces. International Journal of Human– Computer Interaction, 33(1), 35-43. https://doi.org/10.1080/10447318.2016.1232228.
20.
WickensC. D. (1993). Cognitive factors in display design. Journal of the Washington Academy of Sciences, 83(4), 179-201.
21.
WickensC. D. (2015). Noticing events in the visual workplace: The SEEV and NSEEV models. In HoffmanR. R.HancockP. A.ScerboM. W.ParasuramanR.SzalmaJ. L. (Eds.), Cambridge handbook of applied perception research (pp. 749–768). New York, NY: Cambridge.
22.
WickensC. D.GohJ.HellebergJ.HorreyW. J.TalleurD. A. (2003). Attentional models of multitask pilot performance using advanced display technology. Human Factors, 45(3), 360-380.
23.
WickensC. D.McCarleyJ. S.AlexanderA. L.ThomasL. C.AmbinderM.ZhengS. (2008). Attention-situation awareness (A-SA) model of pilot error. In FoyleD.HooeyB. (Eds.), Human performance models in aviation (pp. 213-239). Boca Raton, FL: Taylor & Francis.
