Literature DB >> 34173185

Feedback moderates the effect of prevalence on perceptual decisions.

Wanyi Lyu1, David E Levari2, Makaela S Nartker3, Daniel S Little4, Jeremy M Wolfe5,6.   

Abstract

How does the prevalence of a target influence how it is perceived and categorized? A substantial body of work, mostly in visual search, shows that a higher proportion of targets are missed when prevalence is low. This classic low prevalence effect (LPE) involves a shift to a more conservative decision criterion that makes it less likely that observers will call an ambiguous item a target. In contrast, Levari et al. (Science, 360[6396], 1465-1467, 2018) recently reported the opposite effect in a simple categorization task. In their hands, at low prevalence, observers adopted a more liberal criterion, making observers more likely to label ambiguous dots on a blue-purple continuum "blue." They called this "prevalence-induced concept change" (PICC). Here, we report that the presence or absence of feedback is critical. With feedback, observers become more conservative at low prevalence, as in the LPE. Without feedback, they become more liberal, identifying a wider range of stimuli as targets, as in Levari's PICC studies. Stimuli from a shape continuum ranging from rounded ("Bouba") to bumpy ("Kiki") shapes produced similar results. Other variables: response type (2AFC vs. go/no-go), color (blue-purple vs. red-green), and stimuli type (solid color vs. texture) did not influence the criterion shifts. Understanding these effects of prevalence and ways they can be controlled illuminates the context-specific nature of perceptual decisions and may be useful in socially important, low prevalence tasks like cancer screening, airport security, and disease diagnosis in pathology.
© 2021. The Psychonomic Society, Inc.

Entities:  

Keywords:  Categorical perception; Criterion; Decision; Prevalence effects

Mesh:

Year:  2021        PMID: 34173185      PMCID: PMC8932255          DOI: 10.3758/s13423-021-01956-3

Source DB:  PubMed          Journal:  Psychon Bull Rev        ISSN: 1069-9384


  21 in total

1.  Low target prevalence is a stubborn source of errors in visual search tasks.

Authors:  Jeremy M Wolfe; Todd S Horowitz; Michael J Van Wert; Naomi M Kenner; Skyler S Place; Nour Kibbi
Journal:  J Exp Psychol Gen       Date:  2007-11

2.  Rare targets are rarely missed in correctable search.

Authors:  Mathias S Fleck; Stephen R Mitroff
Journal:  Psychol Sci       Date:  2007-11

3.  Prevalence-induced concept change in human judgment.

Authors:  David E Levari; Daniel T Gilbert; Timothy D Wilson; Beau Sievers; David M Amodio; Thalia Wheatley
Journal:  Science       Date:  2018-06-29       Impact factor: 47.728

4.  The VideoToolbox software for visual psychophysics: transforming numbers into movies.

Authors:  D G Pelli
Journal:  Spat Vis       Date:  1997

5.  Assessing the impact of prevalence expectations on radiologists' behavior.

Authors:  Warren M Reed; Suet Ling Candice Chow; Lay Ee Chew; Patrick C Brennan
Journal:  Acad Radiol       Date:  2014-09       Impact factor: 3.173

6.  Rare, but obviously there: effects of target frequency and salience on visual search accuracy.

Authors:  Adam T Biggs; Stephen H Adamo; Stephen R Mitroff
Journal:  Acta Psychol (Amst)       Date:  2014-09-16

7.  Does Expectation of Abnormality Affect the Search Pattern of Radiologists When Looking for Pulmonary Nodules?

Authors:  Stephen Littlefair; Patrick Brennan; Warren Reed; Claudia Mello-Thoms
Journal:  J Digit Imaging       Date:  2017-02       Impact factor: 4.056

8.  Influence of signal probability during pretraining on vigilance decrement.

Authors:  W P Colquhoun; A D Baddeley
Journal:  J Exp Psychol       Date:  1967-01

9.  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

10.  You shall not pass: how facial variability and feedback affect the detection of low-prevalence fake IDs.

Authors:  Dawn R Weatherford; William Blake Erickson; Jasmyne Thomas; Mary E Walker; Barret Schein
Journal:  Cogn Res Princ Implic       Date:  2020-01-28
View more
  1 in total

1.  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
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.