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Updated: May 5, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Classifying and visualizing medication use in the ABCD study
Daniel A Lopez1,2, L Nate Overholtzer3, Kyung E Rhee4
1Department of Psychiatry, Oregon Health and Science University, Portland, OR, United States of America. lopdanie@ohsu.edu.
Abstract:
Medication use during adolescence provides important insight into current health and treatment patterns. However, these data are often difficult to analyze due to the complexity of medication labeling and classification. We present a reproducible framework that standardizes medication categorization in the Adolescent Brain Cognitive Development Study (ABCD Study), improving analytic consistency and enabling more reliable findings across the research community. Parent-reported data on youth prescription and over-the-counter medication use from baseline through Year 6 of the ABCD Study were reviewed and harmonized. Medications were categorized using a combination of the Anatomical Therapeutic Chemical (ATC) Classification System, artificial intelligence-assisted methods, and expert clinical input. A case study illustrated the utility of this tool by examining longitudinal associations between antidepressant use and youth-reported internalizing symptoms on the Brief Problem Monitor (BPM-Y). More than 6,300 unique medication entries were consolidated into 95 clinically meaningful categories, each coded across three recall periods (past 24 h, past 2 weeks, past year). The most common unique medication labels were for cold/flu/allergy (553) and acne treatments (355). In the case study, adolescents taking antidepressants showed a significantly greater reduction in BPM-Y internalizing scores over time compared to nonusers. This study introduces a standardized and reproducible classification of prescription and over-the-counter medication use in the ABCD Study. The resulting framework-accompanied by an interactive dashboard and publicly available code-facilitates new opportunities for researchers to examine how medication exposure relates to adolescent brain, neurocognitive behavior, and developmental outcomes.
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