Watching diagnoses develop: Eye movements reveal symptom processing during diagnostic reasoning
Finding a probable explanation for observed symptoms is a highly complex task that draws on information retrieval from memory. Recent research suggests that observed symptoms are interpreted in a way that maximizes coherence for a single likely explanation. This becomes particularly clear if symptom sequences support more than one explanation. However, there are no existing process data available that allow coherence maximization to be traced in ambiguous diagnostic situations, where critical information has to be retrieved from memory. In this experiment, we applied memory indexing, an eye-tracking method that affords rich time-course information concerning memory-based cognitive processing during higher order thinking, to reveal symptom processing and the preferred interpretation of symptom sequences. Participants first learned information about causes and symptoms presented in spatial frames. Gaze allocation to emptied spatial frames during symptom processing and during the diagnostic response reflected the subjective status of hypotheses held in memory and the preferred interpretation of ambiguous symptoms. Memory indexing traced how the diagnostic decision developed and revealed instances of hypothesis change and biases in symptom processing. Memory indexing thus provided direct online evidence for coherence maximization in processing ambiguous information.
KeywordsEye movements Process tracing Memory indexing Diagnostic reasoning Coherence maximization
This research was supported by the Swiss National Science Foundation (SNF) Grant PP00P1_157432 to the first author and German Research Foundation (DFG) Grants KR 1057/17-1 and JA 1761/7-1 to the second and third authors. The authors would like to thank Ricarda Fröde and Claudia Dietzel for their help in conducting the experiment, and Bettina von Helversen, Peter Shepherdson, Yvonne Oberholzer, and Tibor Petzoldt for helpful comments on an earlier version of the manuscript.
- Amaya, A. (2015). The tapestry of reason: An inquiry into the nature of coherence and its role in legal argument. Oxford: Hart.Google Scholar
- R Core Team. (2016). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. Available from https://www.R-project.org/.
- DeKay, M. L., Stone, E. R., & Sorenson, C. M. (2011). Sizing up information distortion: Quantifying its effect on the subjective values of choice options. Psychonomic Bulletin & Review, 19, 349–356. doi: 10.3758/s13423-011-0184-8.
- Glöckner, A., & Betsch, T. (2008). Modeling option and strategy choices with connectionist networks: Towards an integrative model of automatic and deliberate decision making. Judgment and Decision Making, 3, 215–228.Google Scholar
- Hagmayer, Y., & Kostopoulou, O. (2013). A parallel constraint satisfaction model of information distortion in diagnostic reasoning. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th annual conference of the cognitive science society (pp. 531–536). Austin: Cognitive Science Society.Google Scholar
- Horstmann, N., Ahlgrimm, A., & Glöckner, A. (2009). How distinct are intuition and deliberation? An eye-tracking analysis of instruction-induced decision modes. Judgment and Decision Making, 4, 335-354. http://papers.ssrn.com/abstract=1393729.
- JASP Team. (2016). JASP (Version 0.8.0.0)[Computer software]. Available from https://jasp-stats.org/
- Johansson, R., Holsanova, J., Dewhurst, R., & Holmqvist, K. (2012). Eye movements during scene recollection have a functional role, but they are not reinstatements of those produced during encoding. Journal of Experimental Psychology: Human Perception and Performance, 38, 1289–1314. doi: 10.1037/a0026585 PubMedGoogle Scholar
- Klichowicz, A., Scholz, A., Strehlau, S., & Krems, J. F. (2016). Differentiating between encoding and processing during sequential diagnostic reasoning: An eye-tracking study. In D. Papafragou, D. Grodner, D. Mirman, & J. C. Trueswell (Eds.), Proceedings of the 38th annual conference of the cognitive science society (pp. 129–134). Austin: Cognitive Science Society.Google Scholar
- Martarelli, C. S., Mast, F. W., & Hartmann, M. (2017). Time in the eye of the beholder: Gaze position reveals spatial-temporal associations during encoding and memory retrieval of future and past. Memory & Cognition, 45, 40-48. doi: 10.3758/s13421-016-0639-2.
- McClelland, J. L., & Rumelhart, D. E. (1981). An interactive model of context effects in letter perception. Part 1. An account of basic findings. Psychological Review, 88, 375-407.Google Scholar
- Mehlhorn, K., & Jahn, G. (2009). Modeling sequential information integration with parallel constraint satisfaction. In N. A. Taatgen & H. van Rijn (Eds.), Proceedings of the 31st annual conference of the cognitive science society (pp. 2469–2474). Austin: Cognitive Science Society.Google Scholar
- Patel, V. L., Arocha, J. F., & Zhang, J. (2005). Thinking and reasoning in medicine. In K. J. Holyoak & R. G. Morrison (Eds.), The Cambridge handbook of thinking and reasoning (pp. 727–750). New York: Cambridge University Press.Google Scholar
- Read, S. J., Vanman, E. J., & Miller, L. C. (1997). Connectionism, parallel constraint satisfaction processes, and gestalt principles: (Re)introducing cognitive dynamics to social psychology. Personality and Social Psychology Review, 1, 26–53. doi: 10.1207/s15327957pspr0101_3.
- Rebitschek, F., Krems, J. F., & Jahn, G. (2015). Memory activation of multiple hypotheses in sequential diagnostic reasoning. Journal of Cognitive Psychology, 6, 780–796. doi: 10.1080/20445911.2015.1026825.
- Rebitschek, F., Scholz, A., Bocklisch, F., Krems, J. F., & Jahn, G. (2012). Order effects in diagnostic reasoning with four candidate hypotheses. In N. Miyake, D. Peebles, & R. P. Cooper (Eds.), Proceedings of the 34th annual conference of the cognitive science society (pp. 905–910). Austin: Cognitive Science Society.Google Scholar
- Renkewitz, F., & Jahn, G. (2010). Tracking memory search for cue information. In A. Glöckner & C. Witteman (Eds.), Foundations for tracing intuition: Challenges and methods (pp. 199–218). New York: Psychology Press.Google Scholar
- Rumelhart, D. E., Smolensky, P., McClelland, J. L., & Hinton, G. E. (1986). Schemata and sequential thought processes in PDP models. In J. L. McClelland, D. E. Rumelhart, & The PDP Research Group (Eds.), Parallel distributed processing: Explorations in the microstructure of cognition, (Vol. 2, pp. 7–57). Cambridge, MA: MIT Press.Google Scholar
- Scholz, A., Mehlhorn, K., & Krems, J. F. (2016). Listen up, eye movements play a role in verbal memory retrieval. Psychological Research, 80, 149–158. doi: 10.1007/s00426-014-0639-4.
- Schulte-Mecklenbeck, M., Kühberger, A., & Ranyard, R. (2011). The role of process data in the development and testing of process models of judgment and decision making. Judgment and Decision Making, 6, 733–739.Google Scholar
- Simon, D., Snow, C. J., & Read, S. J. (2004). The redux of cognitive consistency theories: Evidence judgments by constraint satisfaction. Journal of Personality and Social Psychology, 86, 814–837. doi: 10.1037/0022-35220.127.116.114.
- Simon, D., Stenstrom, D. M., & Read, S. J. (2015). The coherence effect: Blending cold and hot cognitions. Journal of Personality and Social Psychology, 109, 369–394. doi: 10.1037/pspa0000029.
- Spivey, M. J., & Dale, R. (2011). Eye movements both reveal and influence problem solving. In S. P. Liversedge, I. Gilchrist, & S. Everling (Eds.), The Oxford handbook of eye movements (pp. 551–562). New York: Oxford University Press.Google Scholar
- Stewart, N., Hermens, F., & Matthews, W. J. (2015). Eye movements in risky choice. Journal of Behavioral Decision Making, 29, 116–136. doi: 10.1002/bdm.1854.
- Thagard, P. (1989). Explanatory coherence. Behavioral and Brain Sciences, 12, 435–467. doi: 10.1017/S0140525X00057046.
- Weber, E. U., Böckenholt, U., Hilton, D. J., & Wallace, B. (1993). Determinants of diagnostic hypothesis generation: Effects of information, base rates, and experience. Journal of Experimental Psychology: Learning, Memory, and Cognition, 19, 1151–1164. doi: 10.1037/0278-7318.104.22.1681 PubMedGoogle Scholar