Prevalence effects in visual search: Theoretical and practical implications

项目概述：在视觉搜索任务中，观察者(o)在包含分散注意力刺激的视觉场景中寻找目标。一些医疗筛查任务（例如乳腺癌和宫颈癌）是困难的视觉搜索任务。这些任务的一个特点是目标患病率低。也就是说，与许多其他现实世界的搜索任务（例如，在水果通道中寻找香蕉）和典型的实验室搜索任务不同，这些搜索的目标很少出现。例如，在常规乳房x光检查中，病理显示在不到1%的乳房图像上。我们发现，这种低目标患病率本身可能是视觉搜索中遗漏错误的一个有力来源（Wolfe, et al, 2005）。在实验。通过一系列不同的搜索刺激，我们发现，当目标仅在1-2%的搜索试验中出现时，o会错过0.30 - 0.40个目标。当目标在50%的搜索试验中出现时，o只会错过0.05到0.10个相同的目标。视觉搜索任务可以作为信号检测问题来研究。o试图将包含目标信号的显示器与仅包含噪声的显示器区分开来。脱靶误差的产生可能是由于对目标缺乏敏感性，或者由于对位置设置了决策标准，导致可探测目标被归类为非目标。在其他情况下（例如警惕性和分类文献），对目标频率变化的响应被理解为标准的变化，而不是灵敏度的变化。我们已经证明，在视觉搜索中也是如此。低流行率导致标准发生巨大变化，令人惊讶地难以抵消（例如，通过操纵不同类型应对措施的成本和收益）。相关性：医学筛查任务（如乳房x光检查和巴氏涂片检查）是寻找罕见目标的例子。我们的基础研究表明，这种稀缺性本身就使目标更难找到。由于实验室搜索任务和临床筛查任务之间的差异，并且临床任务是由训练有素的专业人员执行的，因此从现有数据中归纳出医学筛查错误的结论是不明智的。因此，我们建议确定这是否真的适用于医学筛查任务，如果是这样，则测试基于理论的解决方案。该研究有三个具体目标：1)验证流行效应是乳腺癌和宫颈癌筛查错误的潜在来源的假设；2)开发和测试视觉搜索中流行效应的模型；3)验证减少遗漏错误的理论和临床动机策略。

DESCRIPTION (provided by applicant): PROJECT SUMMARY: 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.