AI-Based Screening for Depression and Social Anxiety Through Eye Tracking: An Exploratory Study

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cris.lastimport.scopus2025-12-16T04:16:30Z
dc.abstract.enWell-being is a dynamic construct that evolves over time and fluctuates within individuals, posing challenges in its quantification. Reduced well-being is often associated with depression or anxiety disorders, characterised by biases in visual attention towards specific stimuli, such as human faces. This paper introduces a novel approach to AI-aided screening of these affective disorders by analysing scan paths of visual attention using convolutional neural networks (CNNs). Data were collected during two studies assessing (1) attention tendencies among individuals diagnosed with major depression and (2) social anxiety. These data were applied to residual CNNs through images generated from eye-gaze patterns. The experimental results, obtained using ResNet architectures, demonstrated a promising average accuracy of 48% for a three-class system and 62% for a two-class system. Based on these exploratory findings, we propose that this method could be utilised in rapid, ecological, and effective mental health screening systems to quantify well-being through eye-tracking.
dc.affiliationWydział Psychologii w Warszawie
dc.affiliationInstytut Psychologii
dc.contributor.authorChlasta, Karol
dc.contributor.authorWisiecka, Katarzyna
dc.contributor.authorKrejtz, Krzysztof
dc.contributor.authorKrejtz, Izabela
dc.date.access2024-12
dc.date.accessioned2025-11-07T10:09:58Z
dc.date.available2025-11-07T10:09:58Z
dc.date.created2024
dc.date.issued2024-12
dc.description.accesstimeat_publication
dc.description.issue15
dc.description.physical75-91
dc.description.sdgGenderEquality
dc.description.sdgIndustryInnovationAndInfrastructure
dc.description.sdgGoodHealthAndWellBeing
dc.description.versionfinal_published
dc.identifier.doi10.54663/2182-9306.2024.SpecialIssueMBP.75-91
dc.identifier.issn2182-9306
dc.identifier.urihttps://share.swps.edu.pl/handle/swps/1966
dc.identifier.weblinkhttp://u3isjournal.isvouga.pt/index.php/ijmcnm/article/view/925
dc.languageen
dc.pbn.affiliationpsychologia
dc.rightsCC-BY-NC
dc.rights.questionYes_rights
dc.share.articleOPEN_JOURNAL
dc.subject.enEye-tracking
dc.subject.enArtificial intelligence
dc.subject.enConvolutional neural networks
dc.subject.enDepression
dc.subject.enSocial anxiety
dc.subject.enWell-being
dc.swps.sciencecloudsend
dc.titleAI-Based Screening for Depression and Social Anxiety Through Eye Tracking: An Exploratory Study
dc.title.journalInternational Journal of Marketing, Communication and New Media
dc.typeJournalArticle
dspace.entity.typeArticle