Evidence map›Paper›PMID 41372574›Full record

ArticleBehavior research methods2025

ThreatSim: A novel stimuli database of threatening and nonthreatening image pairs rated for similarity.

Andras N Zsido, Michael C Hout, Eben W Daggett, Julia Basler, Otilia Csonka, Bahtiyar Yıldız, Marko Hernandez, Bryan White, Botond Laszlo Kiss

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Behavior research methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Andras N ZsidoInstitute of Psychology, University of Pécs, 6. Ifjusag Street, Pécs, Baranya, H 7624, Hungary. zsido.andras@pte.hu.ORCID http://orcid.org/0000-0003-0506-6861
Michael C HoutPsychology Department, New Mexico State University, Las Cruces, NM, USA.
Eben W DaggettPsychology Department, New Mexico State University, Las Cruces, NM, USA.
Julia BaslerInstitute of Psychology, University of Pécs, 6. Ifjusag Street, Pécs, Baranya, H 7624, Hungary.
Otilia CsonkaInstitute of Psychology, University of Pécs, 6. Ifjusag Street, Pécs, Baranya, H 7624, Hungary.
Bahtiyar YıldızInstitute of Psychology, University of Pécs, 6. Ifjusag Street, Pécs, Baranya, H 7624, Hungary.
Marko HernandezPsychology Department, New Mexico State University, Las Cruces, NM, USA.
Bryan WhitePsychology Department, New Mexico State University, Las Cruces, NM, USA.
Botond Laszlo KissInstitute of Psychology, University of Pécs, 6. Ifjusag Street, Pécs, Baranya, H 7624, Hungary.

Funding

Magyar Tudományos Akadémia János Bolyai Research ScholarshipNemzeti Kutatási, Fejlesztési és Innovaciós Alap EKÖP-25-3-IINemzeti Kutatási Fejlesztési és Innovációs Hivatal OTKA FK 146604Nemzeti Kutatási Fejlesztési és Innovációs Hivatal OTKA K 143254Nemzeti Kutatási Fejlesztési és Innovációs Hivatal OTKA PD 137588Pécsi Tudományegyetem 009_2025_PTE_RK/4
6 · The paper itself

Abstract

Researchers often require validated and well-rounded sets of image stimuli. For those interested in understanding the various visual attentional biases toward threatening stimuli, a dataset containing a variety of such objects is urgently needed. Here, our goal was to create an image database of animate and inanimate objects, including those that people find threatening and those that are visually similar to them but are not considered threatening. To do this, we recruited participants (N = 77) for an online survey in which they were asked to name threatening objects and try to come up with a visually similar counterpart. We then used the survey results to create a list of 32 objects, including eight from each crossing of threatening versus nonthreatening and animate versus inanimate. We obtained 20 exemplar images from each category (640 unique images in total, all copyright-free and openly shared). An independent sample of participants (N = 191) judged the similarity of these images using the spatial arrangement method. Data were then modeled using multidimensional scaling. Our results present modeling outcomes using a "map" of animate and inanimate objects (separately) that spatially conveys the perceived similarity relationships between them. We expect that this image set will be widely used in future visual attention studies and more.

Indexed as

Databases, FactualFearPattern Recognition, VisualVisual PerceptionAdolescentAdultAttentionFemaleHumansMalePhotic StimulationYoung AdultAnimalImage databaseObjectThreatVisual searchVisual similarity

Identifiers

PMID41372574
PMCPMC12696069

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LicenceCC BY
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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.