Objective: Standard deviation of lateral position (SDLP) is often the primary outcome in experimental studies on impaired driving. However, other measures may be easier and more practical to obtain and reflect a broader range of driving-related behaviors. We wanted to assess the validity and sensitivity of a range of measures in a driving simulator as well as during real driving and compare these to SDLP.
Methods: Twenty healthy male volunteers undertook 6 driving trials each, 3 in a regular car on a closed track resembling rural road conditions and 3 in a simulator with an identical driving scenario. Ethanol was used as impairing substance due to its well-characterized effects on driving. The subjects were tested sober and at blood alcohol concentrations (BAC) of approximately 0.5 and 0.9 g/L. We explored dose-response relationships between BAC and a range of driving-related measures, as well as their BAC-dependent effect sizes.
Results: In simulator driving, ethanol intake increased steering wheel reversal frequency, steering wheel movement measures, average speed, standard deviation of speed, and pedal use frequency. At the test track, only steering wheel movement and standard deviation of speed were significantly correlated to BAC. Likewise, reaction to unexpected incidents and observance of red traffic lights were adversely affected by ethanol in the simulator but not at the test track. Whereas SDLP showed a relatively large effect size that was similar in simulated and real driving, all other measures demonstrated smaller effect sizes, with less pronounced BAC effects on the test track than in the simulator.
Conclusions: The results suggest that the driving-related measures explored in this study are less sensitive to alcohol-mediated driving impairment than SDLP, especially during real (test track) driving. The discrepancy in effect sizes between simulated and real driving may imply low external validity of these measures in simulator studies.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1080/15389588.2015.1065975 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Detection of neurologic changes in critically ill infants using deep learning on video data: a retrospective single center cohort study.
EClinicalMedicine
December 2024
Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Background: Infant alertness and neurologic changes can reflect life-threatening pathology but are assessed by physical exam, which can be intermittent and subjective. Reliable, continuous methods are needed. We hypothesized that our computer vision method to track movement, pose artificial intelligence (AI), could predict neurologic changes in the neonatal intensive care unit (NICU).
View Article and Find Full Text PDFDeciphering dengue: novel RNA barcoding segments for enhanced serotype-specific identification and global surveillance of dengue viruses.
Front Microbiol
December 2024
College of Biology, Hunan University, Changsha, China.
Introduction: Dengue viruses (DENVs), the causative agents of dengue hemorrhagic fever and dengue shock syndrome, undergo genetic mutations that result in new strains and lead to ongoing global re-infections.
Objectives: To address the growing complexity of identifying and tracking biological samples, this study screened RNA barcode segments for the four DENV serotypes, ensuring high specificity and recall rates for DENV identification using segments.
Results: Through analyzing complete genome sequences of DENVs, we screened eight barcode segments for DENV, DENV-1, DENV-2, DENV-3, and DENV-4 identification.
Digital health interventions in adult intensive care and recovery after critical illness to promote survivorship care.
J Intensive Care Soc
January 2025
Department of Physiotherapy, Faculty of Medicine, Dentistry and Health Sciences, School of Health Sciences, The University of Melbourne, Melbourne, VIC, Australia.
Digital health refers to the field of using and developing technology to improve health outcomes. Digital health and digital health interventions (DHIs) within the area of intensive care and critical illness survivorship are rapidly evolving. Digital health interventions refer to technologies in clinical interventional format.
View Article and Find Full Text PDFMetyrapone single administration, as a possible predictive tool of its dosage and timing in Cushing's syndrome.
Front Endocrinol (Lausanne)
December 2024
Division of Diabetes and Endocrinology, Department of Internal Medicine, Kobe University Hospital, Kobe, Japan.
Metyrapone is commonly used in the initial management of Cushing's syndrome to reduce hypercortisolemia, but its optimal dosage and timing can vary significantly between patients. Currently, there are limited guidelines on adjustment methods for its administration to individual needs. This study aimed to evaluate responsiveness of each patient to metyrapone and identify the patient characteristics associated with the indices of cortisol responsiveness following a low-dose metyrapone.
View Article and Find Full Text PDFThe current state of mental health treatment for individuals diagnosed with major depressive disorder leaves billions of individuals with first-line therapies that are ineffective or burdened with undesirable side effects. One major obstacle is that distinct pathologies may currently be diagnosed as the same disease and prescribed the same treatments. The key to developing antidepressants with ubiquitous efficacy is to first identify a strategy to differentiate between heterogeneous conditions.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!