Research Papers (2009 – 2013)

BACKGROUND

Tests of attention and cognition are frequently used to predict driving outcomes and have been proposed as a means for screening older adults for potential impairment in driving abilities. One frequently used and well-established test is the Useful Field of View (UFOV©). However, the UFOV requires proprietary software and individuals who use it frequently express frustration at “failing” the test. We have been seeking alternatives to the UFOV for some time. One recently developed test that is relatively unknown to driving researchers is the Attention Network Test (ANT). The ANT is based on a model that postulates three relatively independent neural networks, each sub-serving a different function of attention (alerting, orienting, and executive function). The ANT measures the efficiency of each network plus overall mean response time (RT) and % errors. The aim of this study was to explore the feasibility of using the ANT to predict driving outcomes by comparing it to results obtained with the UFOV and performance on a simulated driving course.

Bruce Weaver, Michel Bédard, Jim McAuliffe, Marie Parkkari