July 2019
Volume 60, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2019
How do simulated central vision loss and distraction affect the detection of hazards by older and younger drivers?
Author Affiliations & Notes
  • Ting Zhang
    Schepens Eye Research Institute of Mass Eye and Ear, Dept Ophthalmology, Harvard Medical School, Boston, Massachusetts, United States
    New England College of Optometry, Boston, Massachusetts, United States
  • Steven Savage
    Schepens Eye Research Institute of Mass Eye and Ear, Dept Ophthalmology, Harvard Medical School, Boston, Massachusetts, United States
  • Alex R Bowers
    Schepens Eye Research Institute of Mass Eye and Ear, Dept Ophthalmology, Harvard Medical School, Boston, Massachusetts, United States
  • Footnotes
    Commercial Relationships   Ting Zhang, None; Steven Savage, None; Alex Bowers, None
  • Footnotes
    Support  NIH grants R01-EY025677, S10-RR028122 and P30-EY003790, and New England College of Optometry, Internal Research Funds for Pilot Projects
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 1055. doi:
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      Ting Zhang, Steven Savage, Alex R Bowers; How do simulated central vision loss and distraction affect the detection of hazards by older and younger drivers?. Invest. Ophthalmol. Vis. Sci. 2019;60(9):1055.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Driving is crucial for maintaining independence in older age. At the same time, there are increasing numbers of older drivers with central vision loss (CVL) and increasing amounts of auditory distractions when driving. Both CVL and distraction could impair hazard detection. Older drivers may be particularly at risk because CVL and distraction may deplete their already limited cognitive resource pool to a greater extent than in younger drivers. We therefore evaluated the effects of age and auditory distraction on pedestrian hazard detection when driving without and with a simulation of CVL that reduced VA to a level eligible for a restricted license in MA.

Methods : Sixteen older (60 – 82 years) and sixteen younger (20 – 37 years) normally-sighted current drivers drove on a rural highway in our simulator and pressed the horn whenever they detected a pedestrian (12 per drive) that ran toward the road on a collision course. Subjects completed four drives (orders counterbalanced): 1) normal vision without distraction, 2) normal vision with distraction, 3) simulated CVL without distraction, and 4) simulated CVL with distraction. CVL was simulated by attaching diffusing filters to safety goggles, which reduced VA to mean 20/80 (both age groups) and letter contrast sensitivity to 1.43 (young) and 1.34 (older) log units. For drives with distraction, subjects listened to an audiobook, repeating out loud key words to ensure task engagement.

Results : Distraction and simulated CVL each significantly increased reaction times (RT; p<0.001). However, the increase in RT due to simulated CVL was far greater than that due to distraction (increase of 660 vs. 161 ms). Simulated CVL interacted with age increasing RT in older subjects by 828 ms compared to 492 ms in younger subjects (p= 0.003), but distraction did not interact with age. The rate of unsafe responses (unable to avoid a collision) increased significantly from 5% without to 22% with simulated CVL (data pooled across all subjects).

Conclusions : Simulated CVL impaired hazard detection to a much greater extent in older than younger drivers, despite similar levels of VA, suggesting older drivers with CVL may be at greater risk for potential accidents. Distraction can further heighten this risk; however, simulated CVL was found to have a greater adverse effect on responses to hazards than distraction from listening to an audiobook.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

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