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Motivational influences of monetary reward and performance feedback on dual-target search performance

Optimizing employee performance is of general importance, but it is particularly pertinent for socially critical jobs that are especially error prone. For example, it is vital to understand how visual search performance can be maximized for radiologists, baggage screeners, and military personnel. These professions are notable in that they ask individuals to search displays for more than one possible target (e.g., a water bottle and a gun in a x-ray baggage image), and such multiple-target searches are known to be problematic in that finding one target often makes identification of a second target less likely. Multiple-target search is sensitive to top-down influences such as anticipatory anxiety (Cain, Dunsmoor, LaBar, & Mitroff, under review), and here we explore the impact of reward motivation and feedback. Participants completed a paradigm that reliably produces dual-target errors (Fleck, Samei, & Mitroff, 2010, Experiment 3). When we simply motivated participants with a performance-based, ten-percent chance of winning an additional $50 in compensation (Experiment 1), the performance decline on dual-target trials was eliminated. Without monetary motivation, adding trial-by-trial feedback (Experiment 2) did not significantly improve dual-target accuracy; however, the presence of both monetary motivation and feedback (Experiment 3) resulted in performance benefits for both single- and dual-target conditions compared to Experiments 1 and 2. Collectively, these experiments and others that will be discussed demonstrate that motivation alone is sufficient to enhance dual-target search performance, and that such benefits are enhanced when paired with trial-by-trial feedback. Several other influences will be discussed as well, including the impact of various performance goals (e.g., completing as many correct trials as possible in a set time frame) on strategy choice. These findings provide key information about the role of top-down motivation on performance and how this can improve dual-target search accuracy.