Patrick Cox¹; ¹Lehigh University

When a target is rarely present in visual search, it is more likely to be missed—this is the Low-Prevalence Effect (LPE; Wolfe et al., 2005). Low prevalence typically reduces both hits and false alarms, suggesting that observers adopt a more conservative target-present decision criterion and shorten their search on target-absent trials, consistent with a lower quitting threshold (Wolfe & Van Wert, 2010). In contrast, other work shows that when examples of a category become rarer, the boundaries of that category expand—a phenomenon known as Prevalence-Induced Concept Change (PICC; Levari et al., 2018). These two effects appear to pull in opposite directions. How can they be reconciled? Prior work using single-item categorization tasks suggests that feedback plays a decisive role (Lyu et al., 2021). Here, I extend this idea to visual search, showing that feedback again determines whether lowering target prevalence produces the LPE or PICC. In Experiment 1, participants (N = 106) completed a T-among-Ls search task with trial-level feedback in blocks of 80% and 20% target prevalence (block order counterbalanced). Results revealed a classic LPE: increased miss rates and reduced target-absent search times under low prevalence. Experiment 2 used the same design but without feedback. Participants (N = 98) showed no reliable effect of prevalence on miss rates or target-absent search times. Instead, they exhibited increased false alarms at low prevalence, consistent with PICC. These results suggest that with feedback, observers are confident in their knowledge of the underlying low-prevalence distribution and shift toward a more conservative target-present criterion (i.e., the LPE). However, without feedback, observers may believe they are missing targets and instead adopt a more liberal criterion (i.e., the PICC).