Dataset

Prediction of Fitness To Drive in Patients with Alzheimer’s Dementia

Piersma, D. (Creator), Fuermaier, A. (Creator), Waard, de, D. (Creator), Davidse, R. J. (Creator), De Groot, J. (Creator), Bredewoud, R. A. (Creator), Claesen, R. (Creator), Lemstra, A. (Creator), Vermeeren, A. (Creator), Ponds, R. (Creator), Verhey, F. (Creator), Brouwer, W. (Creator), Tucha, O. (Creator), University of Groningen, 21-Jan-2016

Dataset

  • SWOV Institute for Road Safety Research, The Hague
  • CBR Dutch driving test organisation, Rijswijk
  • Alzheimer Center, Department of Neurology, VU University Medical Center, Amsterdam, The Netherlands.
  • Department of Psychiatry and Neuropsychology, School of Mental Health and Neurosciences (MHeNS), Maastricht University, Maastricht

Description

The number of patients with Alzheimer’s disease (AD) is increasing and so is the number of patients driving a car. To enable patients to retain their mobility while at the same time not endangering public safety, each patient should be assessed for fitness to drive. The aim of this study is to develop a method to assess fitness to drive in a clinical setting, using three types of assessments, i.e. clinical interviews, neuropsychological assessment and driving simulator rides. The goals are (1) to determine for each type of assessment which combination of measures is most predictive for on-road driving performance, (2) to compare the predictive value of clinical interviews, neuropsychological assessment and driving simulator evaluation and (3) to determine which combination of these assessments provides the best prediction of fitness to drive. Eighty-one patients with AD and 45 healthy individuals participated. All participated in a clinical interview, and were administered a neuropsychological test battery, and a driving simulator ride (predictors). The criterion fitness to drive was determined in an on-road driving assessment by experts of the CBR Dutch driving test organisation according to their official protocol. The validity of the predictors to determine fitness to drive was explored by means of logistic regression analyses, discriminant function analyses, as well as receiver operating curve analyses. We found that all three types of assessments are predictive of on-road driving performance. Neuropsychological assessment had the highest classification accuracy followed by driving simulator rides and clinical interviews. However, combining all three types of assessments yielded the best prediction for fitness to drive in patients with AD with an overall accuracy of 92.7%, which makes this method highly valid for assessing fitness to drive in AD. This method may be used to advise patients with AD and their family members about fitness to drive.
Date made available21-Jan-2016
PublisherUniversity of Groningen
Temporal coverage2013 - 2014
Date of data production2013 - 2014
Geographical coverageThe Netherlands
Access to the dataset Open
Contact researchdata@rug.nl

    Keywords on Datasets

  • Alzheimer’s disease, car driving , fitness-to-drive assessment
Related Publications
  1. Prediction of Fitness to Drive in Patients with Alzheimer's Dementia

    Piersma, D., Fuermaier, A. B. M., de Waard, D., Davidse, R. J., de Groot, J., Doumen, M. J. A., Bredewoud, R. A., Claesen, R., Lemstra, A. W., Vermeeren, A., Ponds, R., Verhey, F., Brouwer, W. H. & Tucha, O., 24-Feb-2016, In : PLoS ONE. 11, 2, 29 p., e0149566.

    Research output: Contribution to journalArticleAcademicpeer-review

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