scholarly journals Immediate Feedback During Multiple-Target Visual Search Improves Accuracy

2014 ◽  
Vol 14 (10) ◽  
pp. 1195-1195
Author(s):  
N. Attar ◽  
C.-C. Wu ◽  
M. Pomplun
2015 ◽  
Vol 2 (1) ◽  
pp. 121-128 ◽  
Author(s):  
Stephen R. Mitroff ◽  
Adam T. Biggs ◽  
Matthew S. Cain

Visual search—the ability to locate visual targets among distractors—is a fundamental part of professional performance for many careers, including radiology, airport security screening, cytology, lifeguarding, and more. Successful execution of visual search in these settings is critically important because the consequences of a missed target can be horrific. Unfortunately, many of these professions place high demands on the people performing the searches, and either the task or the environment (or both) could lead to significant errors. One known source of error that exists across many fields is “multiple-target visual search” errors—a target is less likely to be detected if another target was already found in the same search than if the target was the only one present. These errors have proven to be stubborn and not easily eliminated. This article offers a brief overview of the existing research on multiple-target visual search errors and discusses possible policy implications of the errors for airport security screening. The policy suggestions are based on empirical research, with the hope of providing food for thought on using scientific data and theory to improve performance. Specifically, three policy suggestions are raised: shift screening to a remote location away from the checkpoint, reduce the number of prohibited items to lessen the searchers’ cognitive burden, and emphasize search consistency in the training process. Note that the focus here is on airport security screening, as this is a domain most readers can relate to, but the suggestions can equally apply to many search environments.


2015 ◽  
Vol 77 (3) ◽  
pp. 844-855 ◽  
Author(s):  
Adam T. Biggs ◽  
Stephen H. Adamo ◽  
Emma Wu Dowd ◽  
Stephen R. Mitroff

2020 ◽  
Author(s):  
Patrick Cox ◽  
Dwight Kravitz ◽  
Stephen Mitroff

Professions such as radiology and aviation security screening that rely on visual search— the act of looking for targets among distractors—often cannot provide operators immediate feedback, which can create situations where performance may be largely driven by the searchers’ own expectations. For example, if searchers do not expect relatively hard- to-spot targets to be present in a given search, they may find easy-to-spot targets but systematically quit searching before finding more difficult ones. Without feedback, searchers can create self-fulfilling prophecies where they incorrectly reinforce initial biases (e.g., first assuming and then, perhaps wrongly, concluding hard-to-spot targets are rare). In the current study, two groups of searchers completed an identical visual search task but with just a single difference in their initial task instructions before the experiment started; those in the “high-expectation” condition were told that each trial could have one or two targets present (i.e., implying no target-absent trials) and those in the “low-expectation” condition were told that each trial would have up to two targets (i.e., implying there could be target-absent trials). Compared to the high-expectation group, the low-expectation group had a lower hit rate and quit trials more quickly, consistent with a lower quitting threshold (i.e., performing less exhaustive searches). The expectation effect was present from the start and remained across the experiment—despite exposure to the same true distribution of targets, the groups’ performance remained divergent, primarily driven by the low-expectation group’s self-fulfilling prophecy that stemmed from the simple instructions difference. In sum, initial expectations can have dramatic influences— searchers who do not expect to find a target, are less likely to find a target as they are more likely to quit searching faster.


2014 ◽  
Vol 45 (3) ◽  
pp. 528-533 ◽  
Author(s):  
Kait Clark ◽  
Matthew S. Cain ◽  
R. Alison Adcock ◽  
Stephen R. Mitroff

2017 ◽  
Vol 17 (10) ◽  
pp. 79
Author(s):  
Stephen Adamo ◽  
Joseph Nah ◽  
Andrew Collegio ◽  
Paul Scotti ◽  
Sarah Shomstein

2012 ◽  
Vol 12 (9) ◽  
pp. 1010-1010 ◽  
Author(s):  
M. S. Cain ◽  
S. H. Adamo ◽  
S. R. Mitroff

2014 ◽  
Author(s):  
Adam Biggs ◽  
Stephen H. Adamo ◽  
Emma W. Dowd ◽  
Stephen Mitroff

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