Literature DB >> 22864899

False feedback increases detection of low-prevalence targets in visual search.

Jeremy Schwark1, Joshua Sandry, Justin Macdonald, Igor Dolgov.   

Abstract

Many critical search tasks, such as airport and medical screening, involve searching for targets that are rarely present. These low-prevalence targets are associated with extremely high miss rates Wolfe, Horowitz, & Kenner (Nature, 435, 439-440, 2005). The inflated miss rates are caused by a criterion shift, likely due to observers attempting to equate the numbers of misses and false alarms. This equalizing strategy results in a neutral criterion at 50 % target prevalence, but leads to a higher proportion of misses for low-prevalence targets. In the present study, we manipulated participants' perceived number of misses through explicit false feedback. As predicted, the participants in the false-feedback condition committed a higher number of false alarms due to a shifted criterion. Importantly, the participants in this condition were also more successful in detecting targets. These results highlight the importance of perceived prevalence in target search tasks.

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Mesh:

Year:  2012        PMID: 22864899     DOI: 10.3758/s13414-012-0354-4

Source DB:  PubMed          Journal:  Atten Percept Psychophys        ISSN: 1943-3921            Impact factor:   2.199


  8 in total

1.  Analog Computer-Aided Detection (CAD) information can be more effective than binary marks.

Authors:  Corbin A Cunningham; Trafton Drew; Jeremy M Wolfe
Journal:  Atten Percept Psychophys       Date:  2017-02       Impact factor: 2.199

2.  Failures of perception in the low-prevalence effect: Evidence from active and passive visual search.

Authors:  Michael C Hout; Stephen C Walenchok; Stephen D Goldinger; Jeremy M Wolfe
Journal:  J Exp Psychol Hum Percept Perform       Date:  2015-04-27       Impact factor: 3.332

3.  Influence of being videotaped on the prevalence effect during visual search.

Authors:  Yuki Miyazaki
Journal:  Front Psychol       Date:  2015-05-06

4.  Individual differences predict low prevalence visual search performance.

Authors:  Chad Peltier; Mark W Becker
Journal:  Cogn Res Princ Implic       Date:  2017-01-30

5.  Great expectations: minor differences in initial instructions have a major impact on visual search in the absence of feedback.

Authors:  Patrick H Cox; Dwight J Kravitz; Stephen R Mitroff
Journal:  Cogn Res Princ Implic       Date:  2021-03-19

6.  Feedback moderates the effect of prevalence on perceptual decisions.

Authors:  Wanyi Lyu; David E Levari; Makaela S Nartker; Daniel S Little; Jeremy M Wolfe
Journal:  Psychon Bull Rev       Date:  2021-06-25

7.  Eye movement feedback fails to improve visual search performance.

Authors:  Chad Peltier; Mark W Becker
Journal:  Cogn Res Princ Implic       Date:  2017-11-22

8.  How one block of trials influences the next: persistent effects of disease prevalence and feedback on decisions about images of skin lesions in a large online study.

Authors:  Jeremy M Wolfe
Journal:  Cogn Res Princ Implic       Date:  2022-02-02
  8 in total

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