Normal ageing is associated with decline in visual, cognitive, and physical functioning, with concurrent increases in the incidence of chronic medical conditions, including cognitive disorders. Determining when age-related changes have adversely affected a person’s ability to drive safely is a complex task, particularly when cognitive disorders such as mild cognitive impairment and dementia are present.
The aim of this research was to assess the utility of a number of off-road measures in predicting Pass and Fail outcomes for older drivers on a blinded on-road driving assessment with a driving specialist occupational therapist and a driving instructor, which is considered the ‘gold standard’ measure of driving ability. The off-road measures included standardized cognitive tests, computerized sensory-motor & cognitive tests, medical conditions, and
personality measures. The research project comprised three studies.
In Study 1 (Healthy Older Drivers study), 60 drivers with no diagnosed cognitive disorder (‘cognitively-unimpaired’), aged 70-84 years (mean age 76.7, 50% male), completed
standard cognitive tests, computerized sensory-motor and cognitive tests (SMCTests™), and measures of personality. Results were used to form classification models for on-road
assessment Pass and Fail outcome. Sixteen participants failed the on-road assessment. A backwards stepwise binary logistic regression model selected a measure of executive
function and a computerized measure of visuomotor planning and coordination as the best predictors. Following leave-one-out cross-validation, this model was estimated to correctly predict 60% of an independent group of cognitively-unimpaired older drivers into on-road Pass and Fail groups.
In Study 2 (Healthy Driver Follow-up study), 56 participants from the Healthy Older Drivers study were followed for 24 months using annual telephone interviews to assess driving behaviour, driving attitudes, medical conditions, and the occurrence of crashes and receipt of
traffic offences. Official data regarding crashes and traffic offences were also obtained. The aim was to determine whether either the on-road Pass/Fail classification or the off-road measures could predict subsequent crashes and offences. Failing the on-road assessment was not associated with higher crash or offence rates and there were only two baseline measures that predicted crashes or offences (i.e., distance driven at baseline testing and, paradoxically, a lower error score on a measure of visuomotor planning and coordination). However, drivers who reported more distress associated with their medical condition(s) were more likely to have had a crash or offence at 24 months. The outcomes of the Healthy Older Drivers and Healthy Driver Follow-up studies suggest that there is little value in off-road or on-road assessment of cognitively-unimpaired older drivers due to the weak relationship with future negative driving outcomes. However, distress associated with medical conditions may be a useful measure.
Study 3 (Dementia and Driving study) recruited a sample of 60 driving assessment centre referrals with mild cognitive impairment or Alzheimer’s dementia. These participants, aged
58-92 years (mean age 77.9, 60% male), performed a computerized battery of sensory-motor and cognitive tests and a formal blinded on-road driving assessment. A backwards stepwise binary logistic regression model selected measures of reaction time and movement speed of the upper limbs, visuomotor planning and coordination, and sustained attention. Following leave-one-out cross-validation, this model was estimated to correctly predict 68% of an independent group of drivers with mild cognitive impairment and Alzheimer’s dementia into on-road Pass and Fail groups. A subsample of 32 participants completed additional standard cognitive tests and provided information on medical conditions. A binary logistic regression model in this subsample was formed which selected measures of verbal fluency, the presence of heart disease, and a comprehensive cognitive screen. Following leave-one-out crossvalidation, this model would be expected to correctly classify 75% of an independent group of drivers with mild cognitive impairment and Alzheimer’s dementia into on-road Pass and Fail groups. The three measures in this model could be performed in around 35-50 min in a primary health setting.
It is concluded that off-road and on-road assessment of older drivers with no diagnosis of cognitive or neurological disorder is an inaccurate and inefficient use of driving assessment resources, both for the prediction of on-road driving performance and for predicting future crashes and traffic offences. The Dementia and Driving study found a model comprising three measures that could be performed in a primary health setting with reasonable accuracy for correctly classifying people with mild cognitive impairment and Alzheimer’s dementia who go on to Pass and Fail an on-road driving assessment.
| Identifer | oai:union.ndltd.org:canterbury.ac.nz/oai:ir.canterbury.ac.nz:10092/5384 |
| Date | January 2011 |
| Creators | Hoggarth, Petra Ann |
| Publisher | University of Canterbury. Psychology |
| Source Sets | University of Canterbury |
| Language | English |
| Detected Language | English |
| Type | Electronic thesis or dissertation, Text |
| Rights | Copyright Petra Ann Hoggarth, http://library.canterbury.ac.nz/thesis/etheses_copyright.shtml |
| Relation | NZCU |
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