Relationship Between Motor Vehicle Collisions and Results of Perimetry, Useful Field of View, and Driving Simulation in Drivers With Glaucoma.
Summary
Reaction times to low contrast divided attention tasks during driving simulation were significantly associated with history of MVC, performing better than conventional perimetric tests and UFOV.
Abstract
PURPOSE
To examine the relationship between Motor Vehicle Collisions (MVCs) in drivers with glaucoma and standard automated perimetry (SAP), Useful Field of View (UFOV), and driving simulator assessment of divided attention.
METHODS
A cross-sectional study of 153 drivers from the Diagnostic Innovations in Glaucoma Study. All subjects had SAP and divided attention was assessed using UFOV and driving simulation using low-, medium-, and high-contrast peripheral stimuli presented during curve negotiation and car following tasks. Self-reported history of MVCs and average mileage driven were recorded.
RESULTS
Eighteen of 153 subjects (11.8%) reported a MVC. There was no difference in visual acuity but the MVC group was older, drove fewer miles, and had worse binocular SAP sensitivity, contrast sensitivity, and ability to divide attention (UFOV and driving simulation). Low contrast driving simulator tasks were the best discriminators of MVC (AUC 0.80 for curve negotiation versus 0.69 for binocular SAP and 0.59 for UFOV). Adjusting for confounding factors, longer reaction times to driving simulator divided attention tasks provided additional value compared with SAP and UFOV, with a 1 standard deviation (SD) increase in reaction time (approximately 0.75 s) associated with almost two-fold increased odds of MVC.
CONCLUSIONS
Reaction times to low contrast divided attention tasks during driving simulation were significantly associated with history of MVC, performing better than conventional perimetric tests and UFOV.
TRANSLATIONAL RELEVANCE
The association between conventional tests of visual function and MVCs in drivers with glaucoma is weak, however, tests of divided attention, particularly using driving simulation, may improve risk assessment.
Keywords
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