Literature DB >> 23477415

Findings from the Candrive/Ozcandrive study: Low mileage older drivers, crash risk and reduced fitness to drive.

Jim Langford1, Judith L Charlton, Sjaan Koppel, Anita Myers, Holly Tuokko, Shawn Marshall, Malcolm Man-Son-Hing, Peteris Darzins, Marilyn Di Stefano, Wendy Macdonald.   

Abstract

Previous research has found that only older drivers with low annual driving mileages had a heightened crash risk relative to other age groups. These drivers tend to drive mainly in urban areas, where the prevalence of complex traffic situations increases crash risk. However it might also be that some drivers may have reduced their driving due to perceived or actual declines in driving fitness. This paper uses Canadian and Australian data from the Candrive/Ozcandrive older driver study to investigate the association between annual driving distances and a set of driving-related factors, including fitness to drive. All drivers in the Candrive/Ozcandrive older driver cohort study were allocated to one of three groups according to their self-reported annual driving distances: <5001km; >5000 and <15,000km; and 15,000km or greater. Relationships between these driving-distance categories and: (a) self-reported crash data; (b) various Year 1 'fitness to drive' performance measures; and (c) self-perceptions of driving ability and of comfort while driving, were determined. Results confirmed the previously reported association between low mileage and heightened crash risk. Further, low mileage drivers performed relatively poorly on a wide range of performance measures, perceived their own driving ability as lower, and reported lower comfort levels when driving in challenging situations, compared to the higher mileage drivers. In most instances, these differences were statistically significant. The paper provides further evidence that the so-called 'older driver problem' is most pertinent to low mileage drivers, and that this is due in part to low mileage drivers tending to have reduced fitness to drive. This higher risk group represented a fairly small proportion of the sample in this study.
Copyright © 2013 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Crash risk; Fitness to drive; Low mileage bias; Older drivers

Mesh:

Year:  2013        PMID: 23477415     DOI: 10.1016/j.aap.2013.02.006

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  9 in total

1.  [Mild dementia and driving ability. Part 1: Fundamentals].

Authors:  D K Wolter
Journal:  Z Gerontol Geriatr       Date:  2014-04       Impact factor: 1.281

2.  [Mild dementia and driving ability. Part 2: Assessment and its consequences in practice].

Authors:  D K Wolter
Journal:  Z Gerontol Geriatr       Date:  2014-06       Impact factor: 1.281

3.  Preferred Sources of Information, Knowledge, and Acceptance of Automated Vehicle Systems: Effects of Gender and Age.

Authors:  Pamela M Greenwood; Carryl L Baldwin
Journal:  Front Psychol       Date:  2022-05-23

4.  Longitudinal Research on Aging Drivers (LongROAD): study design and methods.

Authors:  Guohua Li; David W Eby; Robert Santos; Thelma J Mielenz; Lisa J Molnar; David Strogatz; Marian E Betz; Carolyn DiGuiseppi; Lindsay H Ryan; Vanya Jones; Samantha I Pitts; Linda L Hill; Charles J DiMaggio; David LeBlanc; Howard F Andrews
Journal:  Inj Epidemiol       Date:  2017-08-01

Review 5.  Select physical performance measures and driving outcomes in older adults.

Authors:  Thelma J Mielenz; Laura L Durbin; Jodi A Cisewski; Jack M Guralnik; Guohua Li
Journal:  Inj Epidemiol       Date:  2017-05-08

6.  Computer-Based Driving in Dementia Decision Tool With Mail Support: Cluster Randomized Controlled Trial.

Authors:  Mark J Rapoport; Carla Zucchero Sarracini; Alex Kiss; Linda Lee; Anna Byszewski; Dallas P Seitz; Brenda Vrkljan; Frank Molnar; Nathan Herrmann; David F Tang-Wai; Christopher Frank; Blair Henry; Nicholas Pimlott; Mario Masellis; Gary Naglie
Journal:  J Med Internet Res       Date:  2018-05-25       Impact factor: 5.428

7.  Investigating the Significant Individual Historical Factors of Driving Risk Using Hierarchical Clustering Analysis and Quasi-Poisson Regression Model.

Authors:  Hasan A H Naji; Qingji Xue; Ke Zheng; Nengchao Lyu
Journal:  Sensors (Basel)       Date:  2020-04-19       Impact factor: 3.576

8.  Explaining the Association between Driver's Age and the Risk of Causing a Road Crash through Mediation Analysis.

Authors:  Karoline Gomes-Franco; Mario Rivera-Izquierdo; Luis Miguel Martín-delosReyes; Eladio Jiménez-Mejías; Virginia Martínez-Ruiz
Journal:  Int J Environ Res Public Health       Date:  2020-12-04       Impact factor: 3.390

9.  Comparison of physical and psychological health outcomes for motorcyclists and other road users after land transport crashes: an inception cohort study.

Authors:  Lisa N Sharwood; Annette Kifley; Ashley Craig; Bamini Gopinath; Jagnoor Jagnoor; Ian D Cameron
Journal:  BMC Public Health       Date:  2021-11-02       Impact factor: 3.295

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.