Department of Psychology, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON, L5L 1C6, Canada.
Brigham and Women's Hospital, Boston, MA, USA.
Psychon Bull Rev. 2023 Feb;30(1):212-223. doi: 10.3758/s13423-022-02159-0. Epub 2022 Aug 11.
Previous work has shown that, in many visual search and detection tasks, observers frequently miss rare but important targets, like weapons in bags or abnormalities in radiological images. These prior studies of the low-prevalence effect (LPE) use static stimuli and typically permitted observers to search at will. In contrast, many real-world tasks, like looking for dangerous behavior on the road, only afford observers a brief glimpse of a complex, changing scene before they must make a decision. Can the LPE be a factor in in dynamic, time-limited moments of real driving? To test this, we developed a novel hazard-detection task that preserves much of the perceptual richness and complexity of hazard detection in the real world, while allowing for experimental control over event prevalence. Observers viewed brief video clips of road scenes recorded from dashboard cameras and reported whether they saw a hazardous event. In separate sessions, the prevalence of these events was either high (50% of videos) or low (4%). Under low prevalence, observers missed hazards at more than twice the rate observed in the high-prevalence condition. Follow-up experiments demonstrate that this elevation of miss rate at low prevalence persists when participants were allowed to correct their responses, increases as hazards become increasingly rare (down to 1% prevalence) and is resistant to simple cognitive intervention (participant prebriefing). Together, our results demonstrate that the LPE generalizes to complex perceptual decisions in dynamic natural scenes, such as driving, where observers must monitor and respond to rare hazards.
先前的研究表明，在许多视觉搜索和检测任务中，观察者经常会错过罕见但重要的目标，例如袋子里的武器或放射学图像中的异常。这些关于低发生率效应 (LPE) 的先前研究使用静态刺激，并且通常允许观察者随意搜索。相比之下，许多现实世界的任务，例如在道路上寻找危险行为，仅在观察者必须做出决定之前，为他们提供一个短暂的机会来观察复杂多变的场景。LPE 是否会影响现实驾驶中的动态、限时时刻？为了测试这一点，我们开发了一种新颖的危险检测任务，该任务保留了现实世界中危险检测的大部分感知丰富性和复杂性，同时允许对事件发生率进行实验控制。观察者观看从仪表盘摄像机录制的道路场景的简短视频剪辑，并报告他们是否看到了危险事件。在单独的会议中，这些事件的发生率要么高（50%的视频），要么低（4%）。在低发生率下，观察者错过危险的速度是高发生率条件下观察到的速度的两倍多。后续实验表明，当参与者被允许纠正他们的反应时，这种低发生率下的错误率升高会持续存在，并且当危险变得越来越罕见（低至 1%的发生率）时，这种升高会增加，并且对简单的认知干预（参与者预告知）具有抵抗力。总之，我们的结果表明，LPE 推广到了动态自然场景中的复杂感知决策，例如驾驶，在这种情况下，观察者必须监测和响应罕见的危险。
