Executive functioning in adults with down syndrome: machine-learning-based prediction of inhibitory capacity

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dc.contributor.authorJojoa Acosta, Mario Fernando
dc.contributor.author Signo, Sara
dc.contributor.authorGarcía-Zapirain, Begoña
dc.contributor.author Gimeno-Santos, Mercè
dc.contributor.authorMéndez Zorrilla, Amaia
dc.contributor.authorVaidya, Chandan
dc.contributor.authorMolins Sauri, Marta
dc.contributor.authorGuerra-Balic, Myriam
dc.contributor.authorBruna i Rabassa, Olga
dc.date.accessioned2025-08-11T10:10:56Z
dc.date.available2025-08-11T10:10:56Z
dc.date.issued2021-10-14
dc.date.updated2025-08-11T10:10:56Z
dc.description.abstractThe study of executive function decline in adults with Down syndrome (DS) is important, because it supports independent functioning in real-world settings. Inhibitory control is posited to be essential for self-regulation and adaptation to daily life activities. However, cognitive domains that most predict the capacity for inhibition in adults with DS have not been identified. The aim of this study was to identify cognitive domains that predict the capacity for inhibition, using novel data-driven techniques in a sample of adults with DS (n = 188; 49.47% men; 33.6 ± 8.8 years old), with low and moderate levels of intellectual disability. Neuropsychological tests, including assessment of memory, attention, language, executive functions, and praxis, were submitted to Random Forest, support vector machine, and logistic regression algorithms for the purpose of predicting inhibition capacity, assessed with the Cats-and-Dogs test. Convergent results from the three algorithms show that the best predictors for inhibition capacity were constructive praxis, verbal memory, immediate memory, planning, and written verbal comprehension. These results suggest the minimum set of neuropsychological assessments and potential intervention targets for individuals with DS and ID, which may optimize potential for independent living.en
dc.description.sponsorshipThis research was funded by Aristos Campus Mundus Research Projects for the Year 2019 (Ramon Llull University, Deusto University and Georgetown University) (Grant Number: ACM2019_11).en
dc.identifier.citationJojoa-Acosta, M. F., Signo-Miguel, S., Garcia-Zapirain, M. B., Gimeno-Santos, M., Méndez-Zorrilla, A., Vaidya, C. J., Molins-Sauri, M., Guerra-Balic, M., & Bruna-Rabassa, O. (2021). Executive functioning in adults with down syndrome: machine-learning-based prediction of inhibitory capacity. International Journal of Environmental Research and Public Health, 18(20). https://doi.org/10.3390/IJERPH182010785
dc.identifier.doi10.3390/IJERPH182010785
dc.identifier.eissn1660-4601
dc.identifier.issn1661-7827
dc.identifier.urihttps://hdl.handle.net/20.500.14454/3346
dc.language.isoeng
dc.publisherMDPI
dc.rights© 2021 by the authors
dc.subject.otherAging
dc.subject.otherArtificial intelligence
dc.subject.otherCognition
dc.subject.otherDown syndrome
dc.subject.otherExecutive functions
dc.subject.otherFeature selection
dc.subject.otherInhibition
dc.subject.otherMachine learning
dc.subject.otherNeuropsychology
dc.titleExecutive functioning in adults with down syndrome: machine-learning-based prediction of inhibitory capacityen
dc.typejournal article
dcterms.accessRightsopen access
oaire.citation.issue20
oaire.citation.titleInternational Journal of Environmental Research and Public Health
oaire.citation.volume18
oaire.licenseConditionhttps://creativecommons.org/licenses/by/4.0/
oaire.versionVoR
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