Driving errors that predict simulated rear-end collisions in drivers with multiple sclerosis. (26th March 2021)
- Record Type:
- Journal Article
- Title:
- Driving errors that predict simulated rear-end collisions in drivers with multiple sclerosis. (26th March 2021)
- Main Title:
- Driving errors that predict simulated rear-end collisions in drivers with multiple sclerosis
- Authors:
- Krasniuk, Sarah
Classen, Sherrilene
Morrow, Sarah A. - Abstract:
- Abstract: Objective: Drivers with Multiple Sclerosis (MS) may have an increased crash risk. However, the driving performance deficits that contribute to crashes are not fully understood. Based on the extant literature, adjustment to stimuli errors indicate failing an on-road assessment. This study examines whether adjustment to stimuli errors can detect the occurrence of collisions in a driving simulator in drivers with MS. Methods: As part of a quasi-experiment, 38 participants with MS and 21 participants without MS completed visual-cognitive and driving simulator assessments, which also recorded their adjustment to stimuli maneuvers. We quantified participants' adjustment to stimuli maneuvers via initial pedal reaction time (seconds), time to collision (seconds), mean speed (meters per second), and the occurrence of rear-end collisions (collide vs. did not collide) when a simulated vehicle cut across the lane in front of them. Results: Logistic regression analyses indicated that, compared to drivers without MS, those with MS had a shorter time to collision (OR= .04, p = .001, 95% CI= [.006, .27]) and a faster mean speed (OR= 1.32, p = .04, 95% CI= [1.01, 1.74]) which increased the odds of experiencing a rear-end collision. Receiver operating characteristic curve analyses indicated that, for MS and control groups, time to collision (MS group = AUC= .94, p <.0001, Control group = AUC= .86, p <.0001) and mean speed (MS group = AUC= .76, p =.005, Control group = AUC = .78, p =Abstract: Objective: Drivers with Multiple Sclerosis (MS) may have an increased crash risk. However, the driving performance deficits that contribute to crashes are not fully understood. Based on the extant literature, adjustment to stimuli errors indicate failing an on-road assessment. This study examines whether adjustment to stimuli errors can detect the occurrence of collisions in a driving simulator in drivers with MS. Methods: As part of a quasi-experiment, 38 participants with MS and 21 participants without MS completed visual-cognitive and driving simulator assessments, which also recorded their adjustment to stimuli maneuvers. We quantified participants' adjustment to stimuli maneuvers via initial pedal reaction time (seconds), time to collision (seconds), mean speed (meters per second), and the occurrence of rear-end collisions (collide vs. did not collide) when a simulated vehicle cut across the lane in front of them. Results: Logistic regression analyses indicated that, compared to drivers without MS, those with MS had a shorter time to collision (OR= .04, p = .001, 95% CI= [.006, .27]) and a faster mean speed (OR= 1.32, p = .04, 95% CI= [1.01, 1.74]) which increased the odds of experiencing a rear-end collision. Receiver operating characteristic curve analyses indicated that, for MS and control groups, time to collision (MS group = AUC= .94, p <.0001, Control group = AUC= .86, p <.0001) and mean speed (MS group = AUC= .76, p =.005, Control group = AUC = .78, p = .005) differentiated between participants who collided vs. did not collide. For drivers with MS, a time to collision of ≤ 1.81 seconds (85% sensitivity, 100% specificity, 15% error rate), and a mean speed of ≥ 7.83 meters per second (77% sensitivity, 76% specificity, 47% error rate) predicted the occurrence of collisions with the lowest error rate. Conclusions: During a driving simulator assessment, adjustment to stimuli errors predicted the occurrence of rear-end collisions in drivers with MS (vs. without MS). Driving assessors may target scenarios that measure participants' adjustment to stimuli, via time to collision and mean speed, to make decisions about their visual–cognitive deficits and driving performance. … (more)
- Is Part Of:
- Traffic injury prevention. Volume 22:Number 3(2021)
- Journal:
- Traffic injury prevention
- Issue:
- Volume 22:Number 3(2021)
- Issue Display:
- Volume 22, Issue 3 (2021)
- Year:
- 2021
- Volume:
- 22
- Issue:
- 3
- Issue Sort Value:
- 2021-0022-0003-0000
- Page Start:
- 212
- Page End:
- 217
- Publication Date:
- 2021-03-26
- Subjects:
- Multiple sclerosis -- computer simulation -- driver behavior -- crash -- screening
Traffic safety -- Periodicals
Traffic accidents -- Periodicals
Wounds and injuries -- Prevention -- Periodicals
363.125 - Journal URLs:
- http://www.tandfonline.com/toc/gcpi20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/15389588.2021.1883008 ↗
- Languages:
- English
- ISSNs:
- 1538-9588
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8882.133000
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