Evidence map›Paper›PMID 42550242›Full record

ArticleEuropean child & adolescent psychiatry2026

Adjunctive utility of gaze-based indices obtained with Gazefinder for ADHD assessment in children.

Masanori Fujieda, Masatoshi Yamashita, Sayo Hamatani, Hitomi Kitagawa, Hideo Matsuzaki, Tokiko Yoshida, Tsuyoshi Sasaki, Yusuke Sudo, Yuko Isobe, Hirotaka Kosaka and 3 more

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Article in European child & adolescent psychiatry, 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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1 · What the graph read from it

What it found

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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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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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5 · Who and what money

Authors and funding

13 authors.

Masanori FujiedaUnited Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Osaka, Japan.ORCID http://orcid.org/0009-0009-1125-5707
Masatoshi YamashitaUnited Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Osaka, Japan.ORCID http://orcid.org/0000-0002-8037-7275
Sayo HamataniUnited Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Osaka, Japan.ORCID http://orcid.org/0000-0001-7847-6381
Hitomi KitagawaResearch Centre for Child Mental Development, Chiba University, Chiba, Japan.
Hideo MatsuzakiUnited Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Osaka, Japan.ORCID http://orcid.org/0000-0002-6869-1261
Tokiko YoshidaUnited Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Osaka, Japan.ORCID http://orcid.org/0000-0002-4410-7163
Tsuyoshi SasakiDepartment of Child Psychiatry and Psychiatry, Chiba University Hospital, Chiba, Japan.ORCID http://orcid.org/0000-0001-8502-6469
Yusuke SudoDivision of Clinical Neuroscience, Center for Forensic Mental Health, Chiba University, Chiba, Japan.ORCID http://orcid.org/0000-0002-7648-9370
Yuko IsobeInstitute for Advanced Academic Research, Chiba University, Chiba, Japan.ORCID http://orcid.org/0009-0004-2811-6977
Hirotaka KosakaUnited Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Osaka, Japan.ORCID http://orcid.org/0000-0003-2210-5025
Kenji J TsuchiyaUnited Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Osaka, Japan.ORCID http://orcid.org/0000-0002-1314-4199
Yoshiyuki HiranoUnited Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Osaka, Japan.ORCID http://orcid.org/0000-0003-3844-3061
Yoshifumi MizunoUnited Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Osaka, Japan. mizunoy@u-fukui.ac.jp.ORCID http://orcid.org/0000-0003-2209-352X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diagnosis of attention-deficit/hyperactivity disorder (ADHD) relies primarily on subjective clinical assessments, necessitating the establishment of objective, low-burden supplementary indicators. While eye-tracking has emerged as a noninvasive method for capturing temporal fluctuations in attentional allocation, its discriminative performance in ADHD remains under-explored. This study examined differences in gaze indices between children with ADHD and typically developing (TD) children using the Gazefinder system and evaluated the utility of these indices in distinguishing diagnostic groups. Participants included 83 children with ADHD and 85 typically developing children (aged 6-17 years). Gaze behavior was recorded during two visual stimuli tasks designed to elicit ADHD characteristics: a classroom animation and a video with increasingly competing stimuli. Six fixation-rate indices and two gaze-shift frequency indices were calculated. Analyses included between-group comparisons, partial correlations with the CANTAB Stop Signal Task and Conners-3, and machine learning-based classification. Fixation-rate indices did not differ significantly between groups; however, under conditions of increasing competing stimuli, children with ADHD exhibited a significantly higher number of gaze shifts between areas of interest (AoIs). Several gaze indices were significantly associated with inhibitory control measures and behavioral symptoms, and select associations remained significant after controlling for diagnosis. Machine learning models incorporating age, sex, and a nested RFE-selected feature subset achieved a maximum area under the curve (AUC) of 0.760. Eye-tracking represents a promising method for quantifying attentional control characteristics associated with ADHD. While gaze indices do not independently replace clinical diagnosis, they may serve as candidate objective supplementary indicators supporting a dimensional understanding of ADHD traits.

Indexed as

ADHDAttentional controlDiagnostic utilityExecutive functionEye-trackingMachine learning

Identifiers

PMID42550242

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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.