In visual search tasks, observers (Os) look for a target in a visual scene containing distracting stimuli. Some medical screening tasks (e.g. breast cancer &cervical cancer) are difficult visual search tasks. A characteristic of these tasks is low target prevalence. That is, unlike many other real world search tasks (e.g. finding bananas in the fruit aisle) and unlike typical laboratory search tasks, these are searches for targets that appear only rarely. In routine mammography, for example, pathology is present on less than 1% of breast images. We have found that this low target prevalence, by itself, can be a potent source of miss errors in visual search (Wolfe, et al, 2005). In exps. with a range of different search stimuli, we have found that Os miss 0.30 to 0.40 of targets when those targets are present on only 1-2% of search trials. Os miss only 0.05 to 0.10 of the same targets when those targets are present on 50% of search trials. Visual search tasks can be studied as signal detection problems. Os are trying to distinguish displays containing a target signal from those containing only noise. Miss errors can arise from a lack of sensitivity to the target or from setting a decision criterion to a position that causes detectable targets to be classified as non-targets. In other contexts (e.g. vigilance &categorization literatures), the response to a change in target frequency is understood as a shift in criterion, not in sensitivity. We have shown that this is also true in visual search. Low prevalence produces a large shift in criterion that is surprisingly hard to counteract (e.g. by manipulations of costs and benefits for different types of response). Relevance: Medical screening tasks (such as mammograms and pap smears) are examples of searches for rare targets. Our basic research suggests that this rarity, by itself, makes targets more difficult to find. Because of differences between laboratory search tasks and clinical screening tasks and because clinical tasks are performed by highly trained professionals, it would be unwise to generalize from the existing data to the conclusions about errors in medical screening. Therefore, we propose to determine whether this is really true for medical screening tasks, and, if so, test theory-based solutions. The proposed research has three specific aims: 1) to test the hypothesis that prevalence effects are a potential source of errors in breast cancer and cervical cancer screening, 2) to develop and test a model of the effects of prevalence in visual search and 3) to test theoretically and clinically motivated strategies to reduce miss errors.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
5R01EY017001-03
Application #
7583907
Study Section
Cognition and Perception Study Section (CP)
Program Officer
Wiggs, Cheri
Project Start
2007-04-01
Project End
2011-02-28
Budget Start
2009-03-01
Budget End
2010-02-28
Support Year
3
Fiscal Year
2009
Total Cost
$411,250
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
Chin, Michael D; Evans, Karla K; Wolfe, Jeremy M et al. (2018) Inversion effects in the expert classification of mammograms and faces. Cogn Res Princ Implic 3:31
Wolfe, Jeremy M; Utochkin, Igor S (2018) What is a preattentive feature? Curr Opin Psychol 29:19-26
Boettcher, Sage E P; Drew, Trafton; Wolfe, Jeremy M (2018) Lost in the supermarket: Quantifying the cost of partitioning memory sets in hybrid search. Mem Cognit 46:43-57
Kok, Ellen M; Aizenman, Avi M; Võ, Melissa L-H et al. (2017) Even if I showed you where you looked, remembering where you just looked is hard. J Vis 17:2
Wolfe, Jeremy M; Alaoui Soce, Abla; Schill, Hayden M (2017) How did I miss that? Developing mixed hybrid visual search as a 'model system' for incidental finding errors in radiology. Cogn Res Princ Implic 2:35
Cunningham, Corbin A; Drew, Trafton; Wolfe, Jeremy M (2017) Analog Computer-Aided Detection (CAD) information can be more effective than binary marks. Atten Percept Psychophys 79:679-690
Drew, Trafton; Boettcher, Sage E P; Wolfe, Jeremy M (2017) One visual search, many memory searches: An eye-tracking investigation of hybrid search. J Vis 17:5
Aizenman, Avi; Drew, Trafton; Ehinger, Krista A et al. (2017) Comparing search patterns in digital breast tomosynthesis and full-field digital mammography: an eye tracking study. J Med Imaging (Bellingham) 4:045501
Sareen, Preeti; Ehinger, Krista A; Wolfe, Jeremy M (2016) CB Database: A change blindness database for objects in natural indoor scenes. Behav Res Methods 48:1343-1348
Josephs, Emilie L; Draschkow, Dejan; Wolfe, Jeremy M et al. (2016) Gist in time: Scene semantics and structure enhance recall of searched objects. Acta Psychol (Amst) 169:100-108

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