Predicting On-Road Assessment Pass and Fail Outcomes in Older Drivers with Cognitive Impairment Using a Battery of Computerized Sensory-Motor and Cognitive Tests

Authors

  • Petra A. Hoggarth PhD,

    Corresponding author
    1. New Zealand Brain Research Institute, Christchurch, New Zealand
    2. Psychiatric Service for the Elderly, Princess Margaret Hospital, Christchurch, New Zealand
    • Address correspondence to Dr. Petra Hoggarth, New Zealand Brain Research Institute, 66 Stewart Street, Christchurch 8011, New Zealand. E-mail: petra.hoggarth@cdhb.govt.nz

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  • Carrie R. H. Innes PhD,

    1. New Zealand Brain Research Institute, Christchurch, New Zealand
    2. Department of Medical Physics and Bioengineering, Christchurch Hospital, Christchurch, New Zealand
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  • John C. Dalrymple-Alford PhD,

    1. New Zealand Brain Research Institute, Christchurch, New Zealand
    2. Department of Psychology, University of Canterbury, Christchurch, New Zealand
    3. Department of Medicine, University of Otago, Christchurch, New Zealand
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  • Richard D. Jones PhD

    1. New Zealand Brain Research Institute, Christchurch, New Zealand
    2. Department of Medical Physics and Bioengineering, Christchurch Hospital, Christchurch, New Zealand
    3. Department of Psychology, University of Canterbury, Christchurch, New Zealand
    4. Department of Medicine, University of Otago, Christchurch, New Zealand
    5. Departments of Electrical and Computer Engineering, University of Canterbury, Christchurch, New Zealand
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Abstract

Objectives

To generate a robust model of computerized sensory-motor and cognitive test performance to predict on-road driving assessment outcomes in older persons with diagnosed or suspected cognitive impairment.

Design

A logistic regression model classified pass–fail outcomes of a blinded on-road driving assessment. Generalizability of the model was tested using leave-one-out cross-validation.

Setting

Three specialist clinics in New Zealand.

Participants

Drivers (n = 279; mean age 78.4, 65% male) with diagnosed or suspected dementia, mild cognitive impairment, unspecified cognitive impairment, or memory problems referred for a medical driving assessment.

Measurements

A computerized battery of sensory-motor and cognitive tests and an on-road medical driving assessment.

Results

One hundred fifty-five participants (55.5%) received an on-road fail score. Binary logistic regression correctly classified 75.6% of the sample into on-road pass and fail groups. The cross-validation indicated accuracy of the model of 72.0% with sensitivity for detecting on-road fails of 73.5%, specificity of 70.2%, positive predictive value of 75.5%, and negative predictive value of 68%.

Conclusion

The off-road assessment prediction model resulted in a substantial number of people who were assessed as likely to fail despite passing an on-road assessment and vice versa. Thus, despite a large multicenter sample, the use of off-road tests previously found to be useful in other older populations, and a carefully constructed and tested prediction model, off-road measures have yet to be found that are sufficiently accurate to allow acceptable determination of on-road driving safety of cognitively impaired older drivers.

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