Wolfe Jeremy M, Alaoui Soce Abla, Schill Hayden M
Ophthalmology and Radiology Departments, Harvard Medical School, 64 Sidney St. Suite 170, Cambridge, MA 02139 USA.
Visual Attention Lab, Brigham and Women's Hospital, 64 Sidney St. Suite 170, Cambridge, MA 02139 USA.
Cogn Res Princ Implic. 2017;2(1):35. doi: 10.1186/s41235-017-0072-5. Epub 2017 Aug 23.
In a real world search, it can be important to keep 'an eye out' for items of interest that are not the primary subject of the search. For instance, you might look for the exit sign on the freeway, but you should also respond to the armadillo crossing the road. In medicine, these items are known as "incidental findings," findings of possible clinical significance that were not the main object of search. These errors (e.g., missing a broken rib while looking for pneumonia) have medical consequences for the patient and potential legal consequences for the physician. Here we report three experiments intended to develop a 'model system' for incidental findings - a paradigm that could be used in the lab to develop strategies to reduce incidental finding errors in the clinic. All the experiments involve 'hybrid' visual search for any of several targets held in memory. In this 'mixed hybrid search task,' observers search for any of three specific targets (e.g., this rabbit, this truck, and this spoon) and three categorical targets (e.g., masks, furniture, and plants). The hypothesis is that the specific items are like the specific goals of a real world search and the categorical targets are like the less well-defined incidental findings that might be present and that should be reported. In all these experiments, varying target prevalence, number of targets, etc., the categorical targets are missed at a much higher rate than the specific targets. This paradigm shows promise as a model of the incidental finding problem.
在现实世界的搜索中，留意那些并非搜索主要对象但却令人感兴趣的项目可能很重要。例如，你可能在高速公路上寻找出口标志，但你也应该对横穿马路的犰狳做出反应。在医学领域，这些项目被称为“偶然发现”，即具有潜在临床意义但并非搜索主要目标的发现。这些错误（例如，在寻找肺炎时漏诊一根肋骨骨折）会给患者带来医疗后果，给医生带来潜在法律后果。在此，我们报告三项实验，旨在开发一种用于偶然发现的“模型系统”——一种可在实验室中用于制定策略以减少临床中偶然发现错误的范式。所有实验都涉及对记忆中多个目标中的任意一个进行“混合”视觉搜索。在这个“混合搜索任务”中，观察者要搜索三个特定目标（例如，这只兔子、这辆卡车和这个勺子）以及三个类别目标（例如，面具、家具和植物）。假设是特定项目类似于现实世界搜索的特定目标，而类别目标类似于可能存在且应报告的定义不太明确的偶然发现。在所有这些实验中，改变目标出现频率、目标数量等，类别目标的漏检率比特定目标高得多。这种范式有望成为偶然发现问题的一种模型。
