Understanding the Impact of Time Pressure and Automation Support in a Visual Search Task

• Published in: Human factors Vol. 66; no. 3; pp. 770 - 786
• Main Authors: Rieger, Tobias, Manzey, Dietrich
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.03.2024; Human Factors and Ergonomics Society
• Subjects: Artificial intelligence; Automation; Decision Making; Decision support systems; Exploratory behavior; Humans; Man-Machine Systems; Medical imaging; Medical research; Pressure; Pressure effects; Receiving; Searching; Sensitivity; Signal detection; Task complexity; Task Performance and Analysis; Time Pressure; Visual perception; Visual tasks; stress; compliance and reliance; human-automation interaction; trust in automation; visual search; decision making
• ISSN: 0018-7208; 1547-8181; 1547-8181
• DOI: 10.1177/00187208221111236

Objective To understand the impact of time pressure and automated decision support systems (DSS) in a simulated medical visual search task. Background Time pressure usually impairs manual performance in visual search tasks, but DSS support might neutralize this negative effect. Moreover, understanding the impact of time pressure and DSS support seems relevant for many real-world applications of visual search. Method We used a visual search paradigm where participants had to search for target letters in a simulated medical image. Participants performed the task either manually or with support of a highly reliable DSS. Time pressure was varied within-subjects by either a trialwise time–pressure manipulation (Experiment 1) or a blockwise manipulation (Experiment 2). Performance was assessed based on signal detection measures. To further analyze visual search behavior, a mouse-over approach was used. Results In both experiments, results showed impaired sensitivity under high compared to low time pressure in the manual condition, but no negative effect of time pressure when working with a highly reliable DSS. Moreover, participants searched less under time pressure and when receiving DSS support, indicating participants followed the automation without thoroughly checking recommendations. However, the human-DSS team’s sensitivity was always worse than that of the DSS alone, independent of the strength of time pressure. Conclusion Negative effects of time pressure can be ameliorated when receiving support by a DSS, but joint overall performance remains below DSS-alone performance. Application Highly reliable DSS seem capable of ameliorating the negative impact of time pressure in complex detection tasks.