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Executive Functioning in Adults with Down Syndrome: Machine-Learning-Based Prediction of Inhibitory Capacity

Author

Listed:
  • Mario Fernando Jojoa-Acosta

    (eVIDA—Lab, Faculty of Engineering, Deusto University, 48007 Bilbao, Spain)

  • Sara Signo-Miguel

    (Faculty of Psychology, Education and Sports Sciences Blanquerna, Ramon Llull University, 08022 Barcelona, Spain)

  • Maria Begoña Garcia-Zapirain

    (eVIDA—Lab, Faculty of Engineering, Deusto University, 48007 Bilbao, Spain)

  • Mercè Gimeno-Santos

    (Faculty of Psychology, Education and Sports Sciences Blanquerna, Ramon Llull University, 08022 Barcelona, Spain)

  • Amaia Méndez-Zorrilla

    (eVIDA—Lab, Faculty of Engineering, Deusto University, 48007 Bilbao, Spain)

  • Chandan J. Vaidya

    (Department of Psychology, Georgetown University, Washington, DC 20057, USA)

  • Marta Molins-Sauri

    (Faculty of Psychology, Education and Sports Sciences Blanquerna, Ramon Llull University, 08022 Barcelona, Spain)

  • Myriam Guerra-Balic

    (Faculty of Psychology, Education and Sports Sciences Blanquerna, Ramon Llull University, 08022 Barcelona, Spain)

  • Olga Bruna-Rabassa

    (Faculty of Psychology, Education and Sports Sciences Blanquerna, Ramon Llull University, 08022 Barcelona, Spain)

Abstract

The 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.

Suggested Citation

  • Mario Fernando Jojoa-Acosta & Sara Signo-Miguel & Maria Begoña Garcia-Zapirain & Mercè Gimeno-Santos & Amaia Méndez-Zorrilla & Chandan J. Vaidya & Marta Molins-Sauri & Myriam Guerra-Balic & Olga Bruna, 2021. "Executive Functioning in Adults with Down Syndrome: Machine-Learning-Based Prediction of Inhibitory Capacity," IJERPH, MDPI, vol. 18(20), pages 1-17, October.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:20:p:10785-:d:656148
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    References listed on IDEAS

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    1. Benchong Li & Liya Fu, 2018. "Exact test of goodness of fit for binomial distribution," Statistical Papers, Springer, vol. 59(3), pages 851-860, September.
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    Cited by:

    1. S. Shapoval & Mercé Gimeno-Santos & Amaia Mendez Zorrilla & Begoña Garcia-Zapirain & Myriam Guerra-Balic & Sara Signo-Miguel & Olga Bruna-Rabassa, 2022. "Serious Games for Executive Functions Training for Adults with Intellectual Disability: Overview," IJERPH, MDPI, vol. 19(18), pages 1-20, September.

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