Abstract
Socially important visual search tasks, such as airport baggage screening and tumor detection, place observers in situations where the targets are rare and the consequences of failed detection are substantial. Recent laboratory studies have demonstrated that low target prevalence yields substantially higher miss errors than do high-prevalence conditions, in which the same targets appear frequently (Wolfe, Horowitz, & Kenner, 2005; Wolfe et al., 2007). Under some circumstances, this \ldprevalence effect\rd can be eliminated simply by allowing observers to correct their last response (Fleck & Mitroff, 2007). However, in three experiments involving search of realistic X-ray luggage images, we found that the prevalence effect is eliminated neither by giving observers the choice to correct a previous response nor by requiring observers to confirm their responses. This prevalence effect, obtained when no trial-by-trial feedback was given, was smaller than the effect obtained when observers searched through the same stimuli but were given trial-by-trial feedback about accuracy. We suggest that low prevalence puts pressure on observers in any search task, and that the diverse symptoms of that pressure manifest themselves differently in different situations. In some relatively simple search tasks, misses may result from motor or response errors. In other, more complex tasks, shifts in decision criteria appear to be an important contributor.
Article PDF
Similar content being viewed by others
References
Baddeley, A. D., & Colquhoun, W. P. (1969). Signal probability and vigilance: A reappraisal of the “signal-rate” effect. British Journal of Psychology, 60, 169–178.
Brainard, D. H. (1997). The Psychophysics Toolbox. Spatial Vision, 10, 433–436.
Chun, M. M., & Wolfe, J. M. (1996). Just say no: How are visual searches terminated when there is no target present? Cognitive Psychology, 30, 39–78.
Colquhoun, W. P., & Baddeley, A. D. (1967). Influence of signal probability during pretraining on vigilance decrement. Journal of Experimental Psychology, 73, 153–155.
Cousineau, D., & Shiffrin, R. M. (2004). Termination of a visual search with large display size effects. Spatial Vision, 17, 327–352.
Donaldson, W. (1992). Measuring recognition memory. Journal of Experimental Psychology: General, 121, 275–277.
Fleck, M. S., & Mitroff, S. R. (2007). Rare targets are rarely missed in correctable search. Psychological Science, 18, 943–947.
Green, D. M., & Swets, J. A. (1966). Signal detection theory and psychophysics. New York: Wiley.
Gur, D., Sumkin, J. H., Rockette, H. E., Ganott, M., Hakim, C., Hardesty, L., et al. (2004). Changes in breast cancer detection and mammography recall rates after the introduction of a computer-aided detection system. Journal of the National Cancer Institute, 96, 185–190.
Healy, A. F., & Kubovy, M. (1981). Probability matching and the formation of conservative decision rules in a numerical analog of signal detection. Journal of Experimental Psychology: Human Learning & Memory, 7, 344–354.
Jiang, Y., Miglioretti, D. L., Metz, C. E., & Schmidt, R. A. (2007). Breast cancer detection rate: Designing imaging trials to demonstrate improvements. Radiology, 243, 360–367.
Li, H., Li, F., Gao, H. H., Chen, A., & Lin, C. (2006). Appropriate responding can reduce miss errors in visual search. Unpublished manuscript.
Mackworth, J. F., & Taylor, M. M. (1963). The d’ measure of signal detectability in vigilance-like situations. Canadian Journal of Psychology, 17, 302–325.
Macmillan, N. A., & Creelman, C. D. (2005). Detection theory: A user’s guide (2nd ed.). Mahwah, NJ: Erlbaum.
Maddox, W. T. (2002). Toward a unified theory of decision criterion learning in perceptual categorization. Journal of the Experimental Analysis of Behavior, 78, 567–595.
Palmer, J., Verghese, P., & Pavel, M. (2000). The psychophysics of visual search. Vision Research, 40, 1227–1268.
Pastore, R. E., Crawley, E. J., Berens, M. S., & Skelly, M. A. (2003). “Nonparametric” A’ and other modern misconceptions about signal detection theory. Psychonomic Bulletin & Review, 10, 556–569.
Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics: Transforming numbers into movies. Spatial Vision, 10, 437–442.
Pisano, E. D., Gatsonis, C., Hendrick, E., Yaffe, M., Baum, J. K., Acharyya, S., et al. (2005). Diagnostic performance of digital versus film mammography for breast-cancer screening. New England Journal of Medicine, 353, 1773–1783.
Rich, A. N., Kunar, M. A., Van Wert, M. J., Hidalgo-Sotelo, B., Horowitz, T. S., & Wolfe, J. M. (2008). Why do we miss rare targets? Exploring the boundaries of the low prevalence effect. Journal of Vision, 8(15, Art. 15), 1–17.
Rubenstein, J. (2001). Test and evaluation plan: X-Ray Image Screener Selection Test (No. DOT/FAA/AR-01/47). Washington, DC: Office of Aviation Research.
Smith, P. A., & Turnbull, L. S. (1997). Small cell and “pale” dyskaryosis. Cytopathology, 8, 3–8.
Wolfe, J. M., Horowitz, T. S., & Kenner, N. M. (2005). Rare items often missed in visual searches. Nature, 435, 439–440.
Wolfe, J. M., Horowitz, T. S., Van Wert, M. J., Kenner, N. M., Place, S. S., & Kibbi, N. (2007). Low target prevalence is a stubborn source of errors in visual search tasks. Journal of Experimental Psychology: General, 136, 623–638.
Zenger, B., & Fahle, M. (1997). Missed targets are more frequent than false alarms: A model for error rates in visual search. Journal of Experimental Psychology: Human Perception & Performance, 23, 1783–1791.
Author information
Authors and Affiliations
Corresponding author
Additional information
The work reported here was funded by the Department of Homeland Security’s Transportation Security Laboratory Human Factors Program, Grant DHS 02-G-010 to J.M.W.
Rights and permissions
About this article
Cite this article
Van Wert, M.J., Horowitz, T.S. & Wolfe, J.M. Even in correctable search, some types of rare targets are frequently missed. Attention, Perception, & Psychophysics 71, 541–553 (2009). https://doi.org/10.3758/APP.71.3.541
Received:
Accepted:
Issue Date:
DOI: https://doi.org/10.3758/APP.71.3.541