Evidence map›Paper›PMID 39160388›Full record

ArticleAttention, perception & psychophysics2024

In simple but challenging search tasks, most errors are stochastic.

Jeremy M Wolfe, Johan Hulleman, Ava Mitra, Wentao Si

Abstract read
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In one paragraph

Article in Attention, perception & psychophysics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jeremy M WolfeBrigham and Women's Hospital, 900 Commonwealth Ave, 3rd Floor, Boston, MA, 02215, USA. jwolfe@bwh.harvard.edu.ORCID https://orcid.org/0000-0002-6475-1984
Johan HullemanUniversity of Manchester, Manchester, UK.ORCID https://orcid.org/0000-0001-6900-5190
Ava MitraBrigham and Women's Hospital, 900 Commonwealth Ave, 3rd Floor, Boston, MA, 02215, USA.
Wentao SiDartmouth College, Hanover, NH, USA.

Funding

Prevalence effects in visual search: Theoretical and practical implicationsR01EY017001 · NEI · BRIGHAM AND WOMEN'S HOSPITAL · PI Jeremy M Wolfe · 2007 to 2026
$8.2M
National Science Foundation 2146617NEI NIH HHS EY017001NIH (NCI) CA207490UK Research and Innovation (UKRI) ES/X000443/1
6 · The paper itself

Abstract

In visual search tasks in the lab and in the real world, people routinely miss targets that are clearly visible: so-called look but fail to see (LBFTS) errors. If search displays are shown to the same observer twice, we can ask about the probability of joint errors, where the target is missed both times. If errors are "deterministic," then the probability of a second error on the same display-given that the target was missed the first time-should be high. If errors are "stochastic," the probability of joint errors should be the product of the error rate for first and second appearances. Here, we report on two versions of a T among Ls search with somewhat degraded letters to make search more difficult. In Experiment 1, Ts could either appear amidst crowded "clumps" of Ls or more in isolation. Observers made more errors when the T was in a clump, but these errors were mainly stochastic. In Experiment 2, the task was made harder by making Ts and Ls more similar. Again, errors were predominantly stochastic. If other, socially important errors are also stochastic, this would suggest that "double reading," where two observers (human or otherwise) look at each stimulus, could reduce overall error rates.

Indexed as

AttentionPattern Recognition, VisualStochastic ProcessesFemaleHumansMaleOrientationReaction TimeYoung AdultErrorStochastic and deterministic errorsVisual attentionVisual search

Identifiers

PMID39160388

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.