Evidence map›Paper›PMID 41748846›Full record

ArticleScientific reports2026

Exploring early-stage orienting behavior using an eye tracker for attention deficit hyperactivity disorder classification.

Seonmi Lee, Sangil Lee, Inji Jeong, Jaehyun Jeong, Hyoju Park, Mee-Kyoung Kwon, Theodore Zanto, Sunhae Sul, Dooyoung Jung

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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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0citing papers in PubMed
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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

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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

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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

9 authors.

Seonmi LeeSchool of Digital Humanities and Computational Social Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141 , Republic of Korea.
Sangil LeeSchool of Liberal Arts, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea.
Inji JeongGraduate School of Health Science and Technology, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea.
Jaehyun JeongLVIS Korea, Daegu, 42710, Republic of Korea.
Hyoju ParkDepartment of Psychology, Pusan National University, Pusan, 46241, Republic of Korea.
Mee-Kyoung KwonDepartment of Child Studies, Seoul Women's University, Seoul, 01797, Republic of Korea.
Theodore ZantoNeuroscape, Department of Neurology, University of California, San Francisco, CA, 94158, USA.
Sunhae SulDepartment of Data Science, Hanyang University, Seoul, 04763, Republic of Korea.
Dooyoung JungSchool of Digital Humanities and Computational Social Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141 , Republic of Korea. dooyoung@kaist.ac.kr.

Funding

he National Research Foundation of Korea (NRF) NRF-2020M3E5D9080787Korea Health Industry Development Institute HI22C0646National Research Foundation of Korea NRF-2020M3E5D9080787National Research Foundation of Korea (NRF) NRF-2020M3E5D9080787the National Research Foundation of Korea (NRF) NRF-2020M3E5D9080787Ulsan National Institute of Science and Technology 1.230016.01
6 · The paper itself

Abstract

Exploring early-stage orienting behavior is essential for elucidating the behavioral mechanisms underlying attentional shifts in attention deficit hyperactivity disorder (ADHD). However, traditional tasks lacking eye-tracking data often obscure these mechanisms. This study investigates low-level attentional shifting in ADHD using a simplified gaze-cueing task and explores classification markers via eye movement. Eye-tracking data were analyzed from 27 typically developing children and 19 children diagnosed with ADHD. We constructed a logistic regression model for classification purposes. Eye movement data alone yielded an accuracy of 0.84, comparable to the accuracy achieved using combined eye-tracking and behavioral data (0.87), underscoring the sensitivity of gaze-based features. Children with ADHD exhibited significantly prolonged inter-saccadic fixations in non-target regions (p = .02, d = 0.80) and marginally reduced saccade frequency (p = .06, d = − 0.52) during target detection, indicating delayed attentional shifting and diminished goal-directed attention. Prolonged fixation during target detection behavior emerged as the strongest predictor, correlating with both inattention and hyperactivity (r = .46; r = .36; both p < .01). Additionally, children with ADHD demonstrated lower response to joint attention and a greater reliance on peripheral vision. These findings highlight distinct gaze patterns under low cognitive load, revealing subtle mechanisms of executive dysfunction and potential early classification markers.

Indexed as

Attention Deficit Disorder with HyperactivityEye MovementsEye-Tracking TechnologyOrientationAttentionChildFemaleFixation, OcularHumansMaleSaccadesADHDAttention shiftsClassificationEarly-stage orienting behaviorEye movementGaze-cueing task

Identifiers

PMID41748846
PMCPMC12979651

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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.