Evidence map›Paper›PMID 40909183›Full record

ArticleProceedings of the ACM on human-computer interaction2025

Eye-Tracking as a Lens into Expertise Development in Visual Search.

Megan H Papesh, Michael C Hout, Giovanna C Del Sordo, Bryan L White, Ashley P Mathis

Abstract read
In one paragraph

Article in Proceedings of the ACM on human-computer interaction, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Megan H PapeshUniversity of Massachusetts Lowell, United States.
Michael C HoutNew Mexico State University, United States.
Giovanna C Del SordoNew Mexico State University, United States.
Bryan L WhiteNew Mexico State University, United States.
Ashley P MathisNew Mexico State University, United States.

Funding

NM-INBRE Sequencing and Bioinformatics CoreP20GM103451 · NIGMS · NEW MEXICO STATE UNIVERSITY LAS CRUCES · PI Charlotte C. Gard · 2012 to 2026
$61.2M
NIGMS NIH HHS P20 GM103451
6 · The paper itself

Abstract

Visual search professionals frequently examine complex images in which they must locate and identify anomalies (e.g., tumors or lesions in medical images, hostile territories in maps) indicating the presence of important information. This is a difficult perceptual and cognitive challenge that requires years of experience even beyond domain-specific training. We developed a laboratory analogue of this task to examine how people development expertise over time and the changes that occur in visual scanning behaviors as this expertise accrues. Participants' eyes were tracked as they searched for subtle anomalies during and after different forms of training. Anomaly detection improved with experience and this improvement occurred more quickly in perceptual training conditions. Eye movement analyses revealed that participants' expertise conferred benefits in both scanning and recognition times. These results suggest that simple perceptual training methods can affect both cognitive and oculomotor components of visual search.

Indexed as

ACM proceedingsClutterExpertiseImage PerceptionVisual Search

Identifiers

PMID40909183
PMCPMC12407182

What OpenQuestion holds

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LicenceCC BY
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.