Measures and interpretations of vigilance performance: Evidence against the detection criterion

Measures and interpretations of vigilance performance: Evidence against the detection criterion
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DOI:
10.1518/001872098779649337
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发表时间:
1998-12-01
期刊:
影响因子:
3.3
通讯作者:
Balakrishnan, JD
Balakrishnan, JD
中科院分区:
心理学3区
文献类型:
--
作者:
Balakrishnan, JD

文献摘要

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操作员在警戒任务中的表现通常被认为取决于他们对检测标准的选择。当信号速率低时,该标准被设置为高,从而导致命中率和误报警率低。随着任务时间的增加,该标准可能会进一步增加,从而进一步降低命中率和误报率。几乎所有的经验证据,这个简单的解释是基于估计的偏差测量β从信号检测理论。在这篇文章中,我描述了一种新的方法来研究决策,不需要信号检测理论的技术假设。这项新分析的结果表明,检测标准永远不会偏向任何一种反应,即使信号速率很低,任务时间很长。两个修改的信号检测理论框架被认为是占这个看似矛盾的结果。第一个假设信号速率影响信息分布方差的相对大小;第二个假设信号速率影响运算符停止规则的逻辑。这项研究的实际或潜在应用包括改进产品质量控制、空中交通管制以及医疗和临床诊断等领域的操作员培训和绩效评估。
Operators' performance in a vigilance task is often assumed to depend on their choice of a detection criterion. When the signal rate is low this criterion is set high, causing the hit and false alarm rates to be low. With increasing time on task the criterion presumably tends to increase even further, thereby further decreasing the hit and false alarm rates. Virtually all of the empirical evidence for this simple interpretation is based on estimates of the bias measure beta from signal detection theory. In this article, I describe a new approach to studying decision making that does not require the technical assumptions of signal detection theory. The results of this new analysis suggest that the detection criterion is never biased toward either response, even when the signal rate is low and the time on task is long. Two modifications of the signal detection theory framework are considered to account for this seemingly paradoxical result. The first assumes that the signal rate affects the relative sizes of the variances of the information distributions; the second assumes that the signal rate affects the logic of the operator's stopping rule. Actual or potential applications of this research include the improved training and performance assessment of operators in areas such as product quality control, air traffic control, and medical and clinical diagnosis.