Reducing the low-prevalence effect with probe trials

TL;DR

This paper shows that using probe trials with feedback can reduce the tendency to miss rare targets in visual search tasks.

Contribution

The study introduces probe trials as a novel method to mitigate the low-prevalence effect in visual search.

Findings

Probe trials reduced the low-prevalence effect in a T-among-Ls task.

Probe benefits scaled with the frequency of matching targets in dual-target searches.

Probes altered top-down guidance without affecting inspection counts or decision criteria.

Abstract

As targets become rare in visual search tasks, the likelihood of missing them increases—a phenomenon known as the low-prevalence effect (LPE). This has important implications for real-world searches, but reducing the LPE has proven challenging. In Experiment 1, we used a low-prevalence T-among-Ls task and found that distributing “probe” trials—trials with known targets and post-response feedback—reduced the LPE. In Experiment 2, participants searched for two low-prevalence targets (T and O among Ls and Qs), and we varied how often each appeared in probe trials. The probe benefit scaled with the frequency of the matching target, suggesting limited generalizability to non-probed targets. Experiment 3 used eye tracking to examine whether probes affected quitting thresholds, decision criteria, or guidance. Results showed that probes biased top-down guidance toward features of frequently probed targets, without affecting the number of items inspected or the decision criterion. In Experiment 4, we tested whether feedback was necessary for the probe benefit. Findings suggest that probes improve rare-target search by altering perceived prevalence, not through feedback alone. Overall, probes may reduce the LPE by increasing perceived prevalence and thereby increasing search guidance, but only when probe targets closely match actual search targets.

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