Clarifying Relations Between ADHD and Functional Impairment in Adulthood: Utilization of Network and Machine Learning Approaches

Patrick K. Goh, Michelle M. Martel, Payton J. Jones, Pevitr S. Bansal, Ashley G. Eng, Anjeli R. Elkins, Melina H. Thaxton, Russell A. Barkley

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Using network analysis and random forest regression, this study identified attention-deficit/hyperactivity disorder (ADHD) symptoms most important for indicating impairment in various functional domains. Participants comprised a nationally representative sample of 1249 adults in the United States. Bridge symptoms were identified as those demonstrating unique relations with impairment domains that, in total, were stronger than those involving other symptoms. Results suggested three inattentive (i.e., difficulty organizing; does not follow through; makes careless mistakes) and one hyperactive (difficulty engaging in leisure activities) bridge symptoms. Random forest regression results supported bridge symptoms as most important (compared to other symptoms) for predicting global and specific impairment domains. Hyperactive/impulsive symptoms appeared more strongly related to impairment in women, whereas difficulty organizing and easily distracted appeared more related to impairment in men. Clarification of bridge symptoms may help identify core characteristics of ADHD in adulthood and specify screening and intervention targets to reduce risk for related impairment.

Original languageEnglish
Pages (from-to)316-331
Number of pages16
JournalAssessment
Volume30
Issue number2
DOIs
StatePublished - Mar 2023

Bibliographical note

Publisher Copyright:
© The Author(s) 2021.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by a grant from Guilford Publications.

FundersFunder number
Guilford Publications Inc.

    Keywords

    • ADHD
    • bridge items
    • impairment
    • machine learning
    • network analysis

    ASJC Scopus subject areas

    • Clinical Psychology
    • Applied Psychology

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