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Design of an experimental protocol to examine medication non-adherence among young drivers diagnosed with ADHD: A driving simulator study
Journal article   Open access   Peer reviewed

Design of an experimental protocol to examine medication non-adherence among young drivers diagnosed with ADHD: A driving simulator study

Yi-Ching Lee, Chelsea Ward McIntosh, Flaura Winston, Thomas Power, Patty Huang, Santiago Ontañón and Avelino Gonzalez
Contemporary clinical trials communications, v 11
Sep 2018
DOI: https://doi.org/10.1016/j.conctc.2018.07.007
PMID: 30101205
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://doi.org/10.1016/j.conctc.2018.07.007View
Published, Version of Record (VoR)CC BY-NC-ND V4.0,  Open

Abstract

Attention-deficit/hyperactivity disorder (ADHD) Driving Driving simulator Machine learning Medication adherence
The diagnosis of ADHD among teens and young adults has been associated with a higher likelihood of motor vehicle crashes. Some studies suggest a beneficial effect of ADHD medication but the exact efficacy is still being debated. Further, medication adherence, which is low in this age group, can further reduce effectiveness. Our long-term objective is to reduce unsafe driving among drivers with ADHD by detecting medication non-adherence through driver behavior modeling and monitoring. As a first step, we developed the described lab study protocol to obtain reliable driver behavior data that will then be used to design and train behavior models built through machine learning. This experimental study protocol was developed to systematically compare driving behaviors under two medication conditions (before and after intake of medication) among young adults with ADHD and a control group of non-ADHD. A driving simulator was used to examine driving behaviors and interactions with traffic. The primary outcome was speed management for two comparisons (ADHD vs. non-ADHD and before vs. after medication), and secondary objectives involved understanding differences among the participants utilizing self-reported surveys about ADHD symptoms, drivers' knowledge, and perception about safety. The study protocol was designed to maximize participant safety and efficiency of data collection, as multiple measures were collected over two 2-h study visits. The sampled ADHD drivers were demographically and psychosocially similar but clinically different from the non-ADHD group. Overall, this protocol was effective in participant recruitment and retention, allowed staggered data collection, and can be incorporated in a subsequent clinical trial that examines the efficacy of a machine-learning based driver monitoring intervention.

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5 Record Views
8 citations in Web of Science
7 citations in Scopus

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

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Collaboration types
Domestic collaboration
Web of Science research areas
Medicine, Research & Experimental
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