Siegle, G. J., Ichikawa, N., & Steinhauer, S. (2008). PubMed Acta Psychologica, 81, 211241. Why verifying diagnostic decisions with a checklist can help: insights from eye tracking. Journal of Experimental Psychology: Human Perception and Performance, 42, 14771481. These include lung x-rays, histology slides, and skin lesions. For instance, an expert may saccade intentionally between features that help the observer effectively discriminate them, possibly helping them form a more thorough understanding of how to distinguish features and associated diagnoses. The Scottish doctorLearning outcomes for the medical undergraduate in Scotland: a foundation for competent and reflective practitioners. Dissociation of spatial attention and saccade preparation. https://doi.org/10.1046/j.1365-2923.2001.00984.x. https://doi.org/10.1177/1049732309354278. Towards a framework for attention cueing in instructional animations: guidelines for research and design. Harden, R. M., Sowden, S., & Dunn, W. R. (1984). Journal of Experimental Psychology: Human Perception and Performance, 24, 14671475. While any such effects appear to be both rare and subtle, they do present a challenge to interpreting whether the effects of EMMEs are at least partially due to the intent of the expert viewer as opposed to being a natural representation of their viewing patterns in normal clinical practice (Ball & Litchfield, 2017).
Psychological Science, 15(5), 302306. Vision Research, 45, 33913401. The authors declare that they have no competing interests. This means that they are quite good at tracking overt central visual attention, but they are not intended for tracking covert peripheral visual attention (Holmqvist et al., 2011). (2005). Is working memory capacity task dependent? In addition to cueing attention during image interpretation, eye tracking can also be used as a feedback mechanism following case interpretation. In this task, radiologists search chest x-ray films for evidence of lung nodules; Kundel and Nodine were interested in whether radiologists were making errors of visual search versus errors of recognition and/or decision-making. (1998).
Itti, L., & Koch, C. (2000). Kundel, H. L., & Nodine, C. F. (1978). As we noted above, medical training frequently involves explicit feedback by instructors on exams and worked examples. Richstone, L., Schwartz, M. J., Seideman, C., Cadeddu, J., Marshall, S., & Kavoussi, L. R. (2010). https://doi.org/10.3758/CABN.10.2.252. Developing and testing hypotheses is a cyclical process that involves identifying features that allow the observer to select a set of candidate hypotheses, gathering data to test each hypothesis, and confirming or disconfirming a hypothesis. NeuroImage, 104, 7988. Rayner, K. (1998). Gaze behavior among experts and trainees during optic disc examination: does how we look affect what we see? (1997). The fovea is a small region in the center of the retina that processes light from the center of the visual field, with a dense concentration of cone receptors that provide high visual acuity (Holmqvist et al., 2011). The ability to maintain performance on a task in the face of distraction is a hallmark characteristic of individuals with high working-memory capacity. While diagnostic performance is routinely evaluated through credentialing and certification, we have very little insight into the underlying interpretive process or the process of skills development over time. Region of interest identification and diagnostic agreement in breast pathology. https://doi.org/10.1002/9781118341544. Feedback-giving behaviour in performance evaluations during clinical clerkships. https://doi.org/10.1007/978-3-642-40942-4-4. The former was considered a failure to disembed the nodule from the background noise (despite fixating on it), and the latter was considered a successful recognition of a nodule without appropriately mapping it to diagnostic criteria. Book The main function of examining a visual image and recognizing features is to develop and test diagnostic hypotheses (Sox, Blatt, Higgins, & Marton, 1988). Voisin, S., Pinto, F., Morin-Ducote, G., Hudson, K. B., & Tourassi, G. D. (2013). Studies of eye movements and visual search in radiology. (2006). Crowley, R. S., Naus, G. J., Stewart, J., & Friedman, C. P. (2003). Other theories suggest that hypotheses are formed early on and then tested during image inspection (Ledley & Lusted, 1959); it is important to point out that novices and experts may reason very differently during case interpretation, and one or both of these approaches may prove appropriate for different observers. Working-memory capacity and the control of attention: the contributions of goal neglect, response competition, and task set to Stroop interference. Berbaum, K. S., Franken, E. A., Dorfman, D. D., Rooholamini, S. A., Kathol, M. H., Barloon, T. J., El-Khoury, G. Y. Exploring the potential of context-sensitive CADe in screening mammography. Privacy Bruny, T. T., Haga, Z. D., Houck, L. A., & Taylor, H. A. Biological Psychology, 121, 6273. Syntactic ambiguity resolution in discourse: modeling the effects of referential context and lexical frequency. B. Opening the black box of clinical skills assessment via observation: a conceptual model. Wolfe, J. M., & Van Wert, M. J. Learning and Instruction, 20(2), 146154. Lundgrn-Laine, H., & Salanter, S. (2010). https://doi.org/10.1016/j.acra.2008.01.023. In Proceedings of the Symposium on Eye Tracking Research and Applications, (pp. In addition to measuring the ballistic movements of the eyes, eye trackers also provide continuous recordings of pupil diameter. Samuel, S., Kundel, H. L., Nodine, C. F., & Toto, L. C. (1995). This is typically considered a major downfall of eye tracking: that many real-world visual tasks likely involve both covert and overt visual attention, though eye tracking can only measure the latter. But we also know that expertise development of medical students and post-graduate resident trainees is a long-term, continuous, and non-linear process. Performance evaluation of several cost variant eye trackers. Calvo-Merino, B., Grzes, J., Glaser, D. E., Passingham, R. E., & Haggard, P. (2006). Kieras, D. E., & Bovair, S. (1984). Journal of the American Medical Informatics Association: JAMIA, 10(1), 3951. ), Machine learning, (pp. In this case, entropy is conceptualized as the degree of energy dispersal of eye fixations across the screen in a relatively random pattern. Applied Cognitive Psychology, 4, 261272. Center for Applied Brain and Cognitive Sciences, Tufts University, 200 Boston Ave., Suite 3000, Medford, MA, 02155, USA, Department of Psychology, University of Utah, 380 1530 E, Salt Lake City, UT, 84112, USA, Department of Pathology and University of Vermont Cancer Center, University of Vermont, 111 Colchester Ave., Burlington, VT, 05401, USA, Department of Medicine, David Geffen School of Medicine at UCLA, University of California at Los Angeles, 10833 Le Conte Ave., Los Angeles, CA, 90095, USA, You can also search for this author in
Cambridge: Cambridge University Press. (2011). In each of these cases, methods were evaluated and implemented for integrating CBME, including new standards for curriculum, teaching, and assessment. In the control condition, there was expert narration during video playback. This is not entirely surprising, as many medical images are indeed static, and interpreting eye movements over dynamic scenes can be very complex and time-consuming (Jacob & Karn, 2003; Jarodzka, Scheiter, Gerjets, & van Gog, 2010). Thus, eye tracking appears to be a valuable tool for augmenting qualitative feedback of trainee performance with concrete examples and guidance to help them attend to appropriate features and incorporate them into diagnoses. https://doi.org/10.1023/A:1011462726040. Journal of Surgical Research, 191(1), 169178.
Medical researchers have increasingly turned to eye-tracking technology to provide more detailed qualitative and quantitative assessments of how and where the eyes move during interpretation, extending research from other high-stakes domains such as air-traffic control (Martin, Cegarra, & Averty, 2011) and airport luggage screening (McCarley & Carruth, 2004; McCarley, Kramer, Wickens, Vidoni, & Boot, 2004). Psychological Science, 23, 10471054. The impact of fatigue on satisfaction of search in chest radiography. Spivey, M. J., & Tanenhaus, M. K. (1998). Aggarwal, R., & Darzi, A. For instance, a breast pathologist examining histological features may categorize a case as benign, atypia, ductal (DCIS) or lobular carcinoma in situ, or invasive carcinoma (Lester & Hicks, 2016). Continued innovations in software for integrating dynamic visual scenes and eye movements will enable this type of research: for instance techniques that parse dynamic video stimuli based on navigation behavior (pause, rewind, play) to identify critical video frames (Yu, Ma, Nahrstedt, & Zhang, 2003). Henderson, J. M., Malcolm, G. L., & Schandl, C. (2009). Washington, D.C.: National Academy Press. There are also cases where images that are usually navigated (panned, zoomed) are artificially restricted, increasing the risk that results are no longer relevant to routine clinical practice. https://doi.org/10.1016/j.acra.2005.03.071. Assessing computerized eye tracking technology for gaining insight into expert interpretation of the 12-lead electrocardiogram: an objective quantitative approach. As described in Kundel and colleagues model, expert diagnosticians are likely to detect cancer on a mammogram before any visual scanning (search) takes place, referred to a an initial holistic, gestalt-like perception of a medical image (Kundel et al., 2008). This progress affords novel insights into how the interpretive process might be improved and sustained during education, training, and clinical practice. The impact of speed and bias on the cognitive processes of experts and novices in medical image decision-making. During patient examinations, image interpretation, and surgical procedures, physicians are constantly accumulating multisensory evidence when inspecting information and ultimately arriving at a diagnostic interpretation. statement and https://doi.org/10.1016/B978-008043361-5/50002-X. Bond, R. R., Zhu, T., Finlay, D. D., Drew, B., Kligfield, P. D., Guldenring, D., Clifford, G. D. (2014). https://doi.org/10.1007/s00464-011-2143-x. A remote eye-tracking system (SensoMotoric Instruments Remote Eye-tracking Device mobile; SMI REDm) mounted to the bottom of a computer monitor. Frank, J. R., & Danoff, D. (2007). Kassirer, J. P., Kopelman, R. I., & Wong, J. In EuroAsianPacific Joint Conference on Cognitive Science. Impact of introducing a diagnostic scheme to medical students in a problem based learning curriculum. https://doi.org/10.1016/j.acra.2005.03.068. Eye-movement study and human performance using telepathology virtual slides. Blondon, K., Wipfli, R., & Lovis, C. (2015). Using gaze-tracking data and mixture distribution analysis to support a holistic model for the detection of cancers on mammograms. Medical Physics, 40, 101906. https://doi.org/10.1118/1.4820536. Wolfe, J. M., Horowitz, T. S., & Kenner, N. M. (2005). Mind over machine. Sibbald, M., de Bruin, A. Yuval-Greenberg, S., Merriam, E. P., & Heeger, D. J. Xu-Wilson, M., Zee, D. S., & Shadmehr, R. (2009). In some cases, a hypothesis may exist prior to visual inspection of an image (Ledley & Lusted, 1959). The earliest research examining eye tracking for feedback in medicine leveraged the concept of perceptual feedback, which involves showing an observer the regions they tended to focus on during an image interpretation (Kundel, Nodine, & Krupinski, 1990). Mechanism of satisfaction of search: eye position recordings in the reading of chest radiographs. Predicting diagnostic error in radiology via eye-tracking and image analytics: preliminary investigation in mammography. An example of relatively far-transfer would be successfully applying knowledge and skill to a novel biopsy with a unique cellular architecture and challenging features that are less clearly indicative of DCIS and are perhaps borderline between atypical ductal hyperplasia (ADH) and DCIS. Eye-tracking research has shed light on the dynamics of this interpretive process, including qualitative and quantitative differences that help distinguish and possibly predict successes and errors. More recently, Berbaum and colleagues demonstrated that satisfaction of search alone may not adequately describe the search process (Berbaum et al., 2015; Krupinski, Berbaum, Schartz, Caldwell, & Madsen, 2017). Elstein, A. S., Shulman, L. S., & Sprafka, S. A. Leff, D. R., James, D. R. C., Orihuela-Espina, F., Kwok, K.-W., Sun, L. W., Mylonas, G., Yang, G.-Z. https://doi.org/10.1016/j.cognition.2007.05.004. https://doi.org/10.1016/0001-6918(92)90019-A. https://doi.org/10.1097/ACM.0b013e3181a8592f. A Bayesian optimal foraging model of human visual search. A taxonomy of errors in multiple-target visual search. On the other hand, this approach could introduce bias in the second physician and unintentionally increase agreement; if the first physician arrived at an incorrect interpretation, such agreement could be detrimental, demonstrating the importance of continuing research in this regard (Gandomkar, Tay, Brennan, Kozuch, & Mello-Thoms, 2018). Differences in eye tracking and gaze patterns between trainees and experts reading plain film bunion radiographs. https://doi.org/10.1111/j.1365-2923.2011.04025.x. Characterizing the development of visual search experience in pathology residents viewing whole slide images. Al-Moteri, M. O., Symmons, M., Plummer, V., & Cooper, S. (2017). Emerging paradigms of cognition in medical decision-making. Higher fixation entropy might indicate relative uncertainty in the diagnostic decision-making process. https://doi.org/10.1037/0096-1523.24.5.1467. Medical Education, 35, 520521. As eye trackers develop more widespread use, however, one can readily envision both automated and instructor-guided feedback techniques to help quantify competency and provide grounded examples for individualized feedback. (2001). https://doi.org/10.1080/01421590220120713. Theoretically, if the diagnostician has not fixated a diagnostically relevant region of a medical image then successful search has not occurred, and without it, recognition and decision-making are not possible. Radiology, 194, 895902. 289300). The CanMEDS initiative: implementing an outcomes-based framework of physician competencies. Hillsdale: Lawrence Erlbaum Associates. Khan, R. S. A., Tien, G., Atkins, M. S., Zheng, B., Panton, O. N. M., & Meneghetti, A. T. (2012). https://doi.org/10.1037/a0030726.
Covert shifts of attention function as an implicit aid to insight. Use of eye-tracking technology in clinical reasoning: a systematic review. Perception, 9, 339344. 115132).
In this method, individual fixation durations are parsed into two categories using a quantitative threshold. Evaluation of two new ecological interface approaches for the anesthesia workplace. Gilzenrat, M. S., Nieuwenhuis, S., Jepma, M., & Cohen, J. D. (2010). https://doi.org/10.1007/s10459-015-9585-1. Committee on Learning Research and Educational Practice. The ACGME outcome project: retrospective and prospective. Bruny, T. T., Carney, P. A., Allison, K. H., Shapiro, L. G., Weaver, D. L., & Elmore, J. G. (2014). Google Scholar. Accessed 1 Feb 2019. Mandatory second opinion surgical pathology at a large referral hospital. Most existing research in this regard leverages the well-established finding that experts move their eyes differently from novices (Bruny et al., 2014; Gegenfurtner, Lehtinen, & Slj, 2011; Krupinski, 2005; Krupinski et al., 2006; Kundel et al., 2008; Lesgold et al., 1988). https://doi.org/10.1007/978-3-642-21741-8_63. Cite this article. (1990). In that study, eye movements were tracked in emergency medicine residents during objective structured clinical examinations in a simulation environment. A., Richter, L., Henderson, J., Bhattacharyya, A. K., Scott, K. M., Weinstein, R. S. (2006). Task-evoked pupillary responses, processing load, and the structure of processing resources. Computers in Human Behavior, 25, 785791. Cognitive Research: Principles and Implications, 2, 36. https://doi.org/10.1186/s41235-017-0073-4. Bligh, J., Prideaux, D., & Parsell, G. (2001). https://doi.org/10.1056/NEJMsr1200117. Provided by the Springer Nature SharedIt content-sharing initiative. In A. Miyake, & P. Shah (Eds. Eye tracker data quality: what it is and how to measure it. https://doi.org/10.1111/j.1553-2712.2008.00148.x. Medical decision making. The present review details some of this research and emphasizes future directions that may prove fruitful for scientists, educators, and clinical practitioners interested in accelerating the transition from novice to expert, monitoring and maintaining competencies, developing algorithms to automate error detection and classification, and informing tractable remediation strategies to train the next generation of diagnosticians. In The Cambridge handbook of thinking and reasoning, (pp. Cambridge: Cambridge University Press. Eye tracking has the potential to revolutionize clinical practice and medical education, with far-reaching implications for the development of automated competency assessments (Bond et al., 2014; Krupinski, Graham, & Weinstein, 2013; Richstone et al., 2010; Tien et al., 2014), advanced clinical tutorials (e.g., watching an experts eye movements over an image; (Khan et al., 2012; OMeara et al., 2015)), biologically inspired artificial intelligence to enhance computer-aided diagnosis (Buettner, 2013; Young & Stark, 1963), and the automated detection and mitigation of emergent interpretive errors during the diagnostic process (Ratwani & Trafton, 2011; Tourassi, Mazurowski, Harrawood, & Krupinski, 2010; Voisin, Pinto, Morin-Ducote, Hudson, & Tourassi, 2013). You look lost: understanding uncertainty and representational flexibility in navigation.
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