Objective: This article tackles the issue of correct data interpretation when using stimulus detection tasks for determining the operator's workload.
Background: Stimulus detection tasks are a relative simple and inexpensive means of measuring the operator's state. While stimulus detection tasks may be better geared to measure conditions of high workload, adopting this approach for the assessment of low workload may be more problematic.
Method: This mini-review details the use of common stimulus detection tasks and their contributions to the Human Factors practice. It also borrows from the conceptual framework of the inverted-U shape model to discuss the issue of data interpretation.
Results: The evidence being discussed here highlights a clear limitation of stimulus detection task paradigms.
Conclusion: There is an inherent risk in using a unidimensional tool like stimulus detection tasks as the primary source of information for determining the operator's psychophysiological state.
Application: Two recommendations are put forward to Human Factors researchers and practitioners dealing with the interpretation conundrum of dealing with stimulus detection tasks.
Keywords: Drowsiness; Fatigue; ISO DRT; PVT; automated driving systems; automation; detection response task; psychomotor vigilance task; response times; stimulus detection task; vigilance; workload.