Can we improve clinical prediction of at-risk older drivers?

Abstract

Objectives To conduct a pilot study to evaluate the predictive value of the Montreal Cognitive Assessment test (MoCA) and a brief test of multiple object tracking (MOT) relative to other tests of cognition and attention in identifying at-risk older drivers, and to determine which combination of tests provided the best overall prediction. Methods Forty-seven currently-licensed drivers (58 to 95 years), primarily from a clinical driving evaluation program, participated. Their performance was measured on: (1) a screening test battery, comprising MoCA, MOT, MiniMental State Examination (MMSE), Trail-Making Test, visual acuity, contrast sensitivity, and Useful Field of View (UFOV); and (2) a standardized road test. Results Eighteen participants were rated at-risk on the road test. UFOV subtest 2 was the best single predictor with an area under the curve (AUC) of .84. Neither MoCA nor MOT was a better predictor of the at-risk outcome than either MMSE or UFOV, respectively. The best four-test combination (MMSE, UFOV subtest 2, visual acuity and contrast sensitivity) was able to identify at-risk drivers with 95% specificity and 80% sensitivity (.91 AUC). Conclusions Although the best four-test combination was much better than a single test in identifying at-risk drivers, there is still much work to do in this field to establish test batteries that have both high sensitivity and specificity.

Prediction of driving ability: Are we building valid models?

“…We focused on studies that primarily included drivers with suspected or confirmed cognitive impairment, including dementia. Eight studies, including three from the current authors, were found (Bowers et al, 2013;Carr et al, 2011;Hoggarth et al, 2013;Innes et al, 2007Innes et al, , 2011Lincoln et al, 2006;Ott et al, 2013;Snellgrove, 2000). These studies are summarized in Table 1.…”

“…Two of the eight studies (Bowers et al, 2013;Lincoln et al, 2006) did not report the selection process of the variables used during model construction. One study (Snellgrove, 2000) used an enter approach while the remainder used some type of stepwise procedure (forward or backward).…”

“…Different methods were used to determine the entry of variables to the classification model. Three studies made more than one model by adding or removing variables to arrive upon the one with the most parsimonious fit (Bowers et al, 2013;Carr et al, 2011;Snellgrove, 2000). One study included all the variables following elimination of those with unacceptable levels of skew or kurtosis (Lincoln et al, 2006).…”

“…Of the remaining four studies one offered 57.5 participants per independent variable (Snellgrove, 2000), one offered 25 participants per variable (Innes et al, 2011), one offered 13 participants per variable (Hoggarth et al, 2013), and one offered 8 participants per variable (Bowers et al, 2013). Bowers et al (2013) constructed several models, with one having a ratio of 4.6 participants per variable.…”

The Effects of Task Load and Vehicle Heterogeneity on Performance in the Multiple-Vehicle Tracking Task

“…These declines may be a factor in intersection collisions, and although a variety of measures have been used to predict performance in older drivers, a recent study included multiple-object tracking as one (e.g. Bowers et al 2013). However, the problem with correlational evidence of this type is that if a relationship between tracking and driving performance exists, it is unclear whether it is because multiple-object tracking is actually used in driving or whether it just correlates with other abilities that are used in driving.…”