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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01ns0649417
Title: Investigating the Predictive Role of Language Development for Symptoms of ADHD
Authors: Parra Rodriguez, Silvana
Advisors: Hasson, Uri
Department: Neuroscience
Class Year: 2024
Abstract: Attention-deficit hyperactivity disorder (ADHD) is one of the two most common neurodevelopmental disorders that affect millions of children worldwide, and it is known to affect a variety of cognitive functions, including executive functioning, inhibitory control, and goal-directed behavior (Faraone et al., 2003). Previous studies have drawn a link between language development impairments, such as issues with phonology, vocabulary, and syntax, and the onset of ADHD-like symptoms in children. However, it is unclear if language difficulties precede attention deficits similar to those found in ADHD or if they are byproducts of executive dysfunction associated with the disorder. Therefore, this work aims to provide a comprehensive review of the current discourse surrounding the potential predictive role of early language development markers for determining ADHD-like symptoms and even the condition itself in children. This work provides a review of the literature on the neural and behavioral aspects of ADHD, highlighting how impairments in language have been found to co-occur with the disorder's behavioral manifestations. Using the First 1,000 Days (1kD) Project as a framework, which collects naturalistic, longitudinal data on children's development and language exposure from birth through their first three years of life, this thesis proposes several avenues through which early language development markers can potentially be evaluated as indicators of later cognitive challenges associated with ADHD. This thesis aims to theorize how early language deficits could precede and predict ADHD, offering potential pathways for earlier diagnosis and intervention. Furthermore, this work argues for the potential for incorporating measures of early language development into machine learning models, such as those used in the 1kD Project, that could predict diagnostic accuracy for ADHD and allow for unprecedented intervention in early childhood.
URI: http://arks.princeton.edu/ark:/88435/dsp01ns0649417
Type of Material: Princeton University Senior Theses
Language: en
Appears in Collections:Neuroscience, 2017-2024

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