Prevalence effects in visual search: Theoretical and practical implications

描述（由申请人提供）：项目概述：在视觉搜索任务中，观察者（O）在包含分散注意力的刺激的视觉场景中寻找目标。一些医学筛查任务（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普及率低。也就是说，与许多其他真实的世界搜索任务（例如，在水果货架上寻找香蕉）不同，也与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，在常规的乳房X光检查中，病理学存在于不到1%的乳房图像上。我们已经发现，这种低目标流行率本身可能是视觉搜索中错过错误的一个潜在来源（Wolfe等人，2005）。在实验室里。在一系列不同的搜索刺激下，我们发现，当这些目标只出现在1-2%的搜索试验中时，Os会错过0.30到0.40个目标。当这些目标出现在50%的搜索试验中时，OS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。操作系统试图区分包含目标信号的显示器和仅包含噪声的显示器。未命中错误可能是由于对目标缺乏灵敏度，或者由于将决策标准设置到导致可检测目标被分类为非目标的位置。在其他情况下（例如警戒和分类文献），对目标频率变化的反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，这在视觉搜索中也是如此。流行率低导致标准发生很大变化，令人惊讶地难以抵消（例如，通过操纵不同类型对策的成本和效益）。相关性：医学筛查任务（如乳房X光检查和子宫颈抹片检查）是搜索罕见目标的示例。我们的基础研究表明，这种罕见性本身就使得目标更难找到。由于实验室检索任务和临床筛查任务之间的差异，并且由于临床任务是由训练有素的专业人员执行的，因此从现有数据中概括出有关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，测试基于理论的解决方案。拟议的研究有三个具体目标：1）检验流行率效应是乳腺癌和宫颈癌筛查中错误的潜在来源的假设，2）开发和测试视觉搜索中流行率效应的模型和3）测试减少错过错误的理论和临床策略。

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.