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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/20360

Title: The relations between specific measures of simulated driving ability and functional ability: new insights for assessment and training programs of older drivers
Authors: Cuenen, Ariane
Jongen, Ellen
Brijs, Tom
Brijs, Kris
Lutin, M.
Van Vlierden, Karin
Wets, Geert
Issue Date: 2015
Abstract: To gain new insights for driving assessment and training, this study had two objectives: (1) to investigate the relations between specific measures of older drivers’ driving ability and demographic/functional ability measures, and (2) to verify the explained variance of these relations to determine the strength of these relations. A sample of 55 older drivers (mean age 76 years) completed a set of functional ability tests as well as a driving simulator test. Results indicate that (1) each specific driving measure is related to a specific set of functional abilities, and (2) only a small proportion of the variability observed in the specific driving measures is explained by demographic variables (3–15%) and by functional abilities (7–36%). For driving assessment programs, it will be necessary to assess several functional abilities to cover the complexity of the driving task. Furthermore, an assessment program focusing solely on demographic and/or functional ability measures, will not be successful in discriminating safe from unsafe older drivers. For driving training programs, it will be necessary to focus on the right set of functional abilities given that specific driving measures are related to different functional abilities. Moreover, a training targeting functional abilities might only have marginal effects on driving ability, given the relatively low amount of driving ability variance that is explained by functional abilities.
Notes: Cuenen, A (reprint author), Hasselt Univ, Transportat Res Inst IMOB, B-3590 Diepenbeek, Belgium. ariane.cuenen@uhasselt.be
URI: http://hdl.handle.net/1942/20360
DOI: 10.1016/j.trf.2015.05.007
ISI #: 000375632100007
ISSN: 1369-8478
Category: A1
Type: Journal Contribution
Validation: ecoom, 2017
Appears in Collections: Research publications

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