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Citation
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Bhattacharya S, Devos H, Lemke C, Branstetter C, Jenkins R, Rooker J, Kranick M, Patel N, Gibson R, Díaz J, Golshani M, Akinwuntan A. Accid. Anal. Prev. 2023; 184: e106994. |
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Abstract
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BACKGROUND: Driving commercial vehicles requires intact visuo-cognitive skills. Approximately 13% of all fatal motor vehicle crashes in the United States involve commercial drivers. The ability to accurately predict risk factors for unsafe commercial driving is essential for public safety. Accurate prediction tools will advance the field of commercial driver science, provide policy guidance for driver testing and assist healthcare providers during testing. Prior studies have correlated clinical tools to roadway safety; translating these results to commercial drivers has not yet been done.
OBJECTIVE: This study aimed to identify specific demographic, driving history and visuo-cognitive test results that correlate with driving simulator performance. Using the Cumulative Simulator Score (CSS) as a surrogate for driving ability, the objective was to correlate both sets of data (self-reported and visuo-cognitive testing) with the CSS to identify screening tools for unsafe driving in commercial drivers. PRINCIPAL RESULTS: Baseline assessments of 120 variables were collected from October 2020 to January 2022. Of the 31 participants, 3 were female and 28 were male with a mean age of 53 years. Average BMI was 32, blood pressure 136/84, 32 years of CDL driving experience, 36,500 annual CDL mileage, 11,000 annual personal mileage, 14 years of education, average number of medications: 2, average number of medical conditions: 2, six participants with personal and/or commercial crashes or tickets in past five years, MOCA 27/30, Trails B time 66 s, UFOV Speed of Processing 15 ms, Stroke Disease Severity Assessment pass rate 94 %. The Cumulative Simulator Score (CSS), correlated significantly with education (r = 0.42; p = 0.02), commercial driving experience (r = 0.42; 0 = 0.02), and number of tickets as a commercial driver (Spearman rho = 0.40; p = 0.02). In a stepwise multivariable linear regression analysis, the number of tickets as a CDL driver in the past five years and years of education were retained as significant variables in the multivariable linear regression model, explaining 38 % of the variance of total scores on the CSS. MAJOR CONCLUSIONS: Descriptive and self-reported driving characteristics correlate better with the Cumulative Simulator Score in CDL drivers than visuo-cognitive tests. Since simulator performance has been shown to be a reliable surrogate for driving performance, the number of tickets as a CDL driver in the past five years and years of education can be considered as additions to annual physicals for policy makers and health care providers to help assess their on-the-road safety.
Language: en |