Driving Distractions Among Public Health Center Clients: A Look at Local Patterns During the Infancy of Distracted Driving Laws in California

Abstract

Objective: To provide a baseline of various driving behaviors and to identify opportunities for prevention of distracted driving during the infancy of state laws that prohibited cellphone use while operating a motor vehicle, the 2010–2011 Distracted Driving Survey collected information on multiple distracted driving behaviors from lower-income clients of three designated, multi-purpose public health centers in Los Angeles County. Methods: Descriptive and multivariable negative binomial regression analyses were performed to examine patterns of driving distractions using the Distracted Driving Survey dataset ( n = 1,051). Results: The most common distractions included talking to other passengers ( n = 912, 86.8%); adjusting the radio, MP3, or cassette player ( n = 873, 83.1%); and adjusting other car controls ( n = 838, 79.7%). The median number of distinct distractions per survey participant was 11 (range: 0–32). Factors predicting the number of distinct distractions included being male [incidence rate ratio (IRR): 1.14; 95% confidence interval (CI): 1.06, 1.23], having a lower education (IRR: 0.73; 95% CI: 0.62, 0.84), and having more years of driving experience (IRR: 1.67; 95% CI: 1.33, 2.11). A variety of distractions, including cellphone use and texting, were predictive of increased motor vehicle crashes in the prior 12 months ( p < 0.05). Conclusions: Distracted driving beyond cellphone use and texting were common in the survey sample, suggesting a need for additional public education and more inclusive distracted driving laws that cover these other activity types.

A hybrid of regularization method and generalized path analysis: modeling single-vehicle run-off-road crashes in a cross-sectional study

“…In addition to unwanted distractions from conversations or verbal exchanges, passengers can create further distractions for drivers by altering the radio, using drugs, physically interfering with or tickling the driver, or attempting to manipulate vehicle controls [ 30 ]. Moreover, another study identified the male gender, lower education levels, and an increased number of years of driving experience as factors predicting the occurrence of distinct distractions [ 31 ].…”

Music Distraction among Young Drivers: Analysis by Gender and Experience

“…In recent years, the use of driving simulators for the training purposes has become trendy aiming for improving knowledge associated with driving. Moreover, as driving simulators are risk-free and time and cost-effective [25,26], they can be used to simulate the real situation and investigate the impact of drug consumption [26], drowsiness [27], mobile phone [28], adjusting the radio, and searching music on portable devices such as an MP3 [29][30][31][32] on driving style. Observing the behavior of the driver, designing/controlling the vehicle and testing drive systems for driving are amongst the most important investigations performed through employing driving simulators.…”