Mental health conditions and unsafe driving behaviors: A naturalistic driving study on ADHD and depression

摘要

Introduction: Road injuries remain a persistent public health concern across the world. The task of driving is complicated by mental health conditions, which may affect drivers' executive functioning and cogni-tive resource allocation. This study examines whether attention-deficit/hyperactivity disorder (ADHD) and depression are associated with unsafe driving behaviors. Method: Generalized linear mixed models were employed to estimate the association of self-reported ADHD and depression with 18 unsafe driving behavior types found prior to at-fault crashes and near-crashes using a large-scale naturalistic driving dataset. Driver demographics, cognitive traits, environmental factors, and driver random effects were included to reduce confounding and biases. Results: Controlling for other covariates, people with self -reported ADHD were more likely to have performed improper braking or stopping (OR = 4.89, 95 CI 1.82-13.17) prior to an at-fault crash or near-crash, while those with self-reported depression did not have a significant association with any unsafe driving behavior. Conclusions: After accounting for demo-graphic, cognitive, and environmental covariates, individuals with ADHD and depression were not prone to purposefully aggressive or reckless driving. Instead, drivers with self-reported ADHD may unintention-ally execute unsafe driving behaviors in particular driving scenarios that require a high level of cognitive judgment. Practical Applications: These findings can inform the curriculum design of driver's education programs that help learners with mental health conditions gain practice in certain road scenarios, for example, more practice on preemptively reducing speed instead of making sudden brakes and smooth turning on curved roads for students with ADHD. Furthermore, specific advanced driver assistance sys-tems may prove particularly helpful for drivers with ADHD, such as detection of leading objects and curve speed warning. (C) 2022 National Safety Council and Elsevier Ltd. All rights reserved.