Evidence map›Paper›PMID 36723822›Full record

ArticleCognitive research: principles and implications2023

Multiple expressions of "expert" abnormality gist in novices following perceptual learning.

Gregory J DiGirolamo, Megan DiDominica, Muhammad A J Qadri, Philip J Kellman, Sally Krasne, Christine Massey, Max P Rosen

Open access · goldAbstract read
In one paragraph

Article in Cognitive research: principles and implications, 2023. 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
0.5field-weighted citation impact, top 36% of its field
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, 2 citations in OpenAlex.

  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

7 authors at 4 institutions in 1 country.

Gregory J DiGirolamoDepartment of Psychology, College of the Holy Cross, 1 College Street, Worcester, MA, 01610, USA. gdigirol@holycross.edu.ORCID 0000-0001-8443-2115
Megan DiDominicaDepartment of Psychology, College of the Holy Cross, 1 College Street, Worcester, MA, 01610, USA.
Muhammad A J QadriDepartment of Psychology, College of the Holy Cross, 1 College Street, Worcester, MA, 01610, USA.
Philip J KellmanDepartment of Psychology, UCLA, Los Angeles, CA, USA.
Sally KrasneDepartment of Surgery, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
Christine MasseyDepartment of Psychology, UCLA, Los Angeles, CA, USA.
Max P RosenDepartment of Radiology, University of Massachusetts, Chan Medical School, Worcester, MA, USA.
College of the Holy Cross · USUniversity of California, Los Angeles · USUCLA Health · USUniversity of Massachusetts Chan Medical School · US

Funding

Perceptual and Adaptive Learning in Cancer Image InterpretationR01CA236791 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KELLMAN, PHILIP J · 2019 to 2022
$2.0M
NCI NIH HHS R01 CA236791
6 · The paper itself

Abstract

With a brief half-second presentation, a medical expert can determine at above chance levels whether a medical scan she sees is abnormal based on a first impression arising from an initial global image process, termed "gist." The nature of gist processing is debated but this debate stems from results in medical experts who have years of perceptual experience. The aim of the present study was to determine if gist processing for medical images occurs in naïve (non-medically trained) participants who received a brief perceptual training and to tease apart the nature of that gist signal. We trained 20 naïve participants on a brief perceptual-adaptive training of histology images. After training, naïve observers were able to obtain abnormality detection and abnormality categorization above chance, from a brief 500 ms masked presentation of a histology image, hence showing "gist." The global signal demonstrated in perceptually trained naïve participants demonstrated multiple dissociable components, with some of these components relating to how rapidly naïve participants learned a normal template during perceptual learning. We suggest that multiple gist signals are present when experts view medical images derived from the tens of thousands of images that they are exposed to throughout their training and careers. We also suggest that a directed learning of a normal template may produce better abnormality detection and identification in radiologists and pathologists.

Indexed as

LearningRadiologistsFemaleHumansAbnormalityDetectionGistHistopathologyPerceptual learning

Identifiers

PMID36723822
PMCPMC9892374
OpenAlexW4318755458

What OpenQuestion holds

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LicenceCC BY
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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.