Back to Search Start Over

How do older adult drivers self-regulate? Characteristics of self-regulation classes defined by latent class analysis

Authors :
Richard H. Fortinsky
Bethany A. West
Katherine Freund
Loren Staplin
Feijun Luo
Gwen Bergen
Donna Bird
Source :
Journal of Safety Research. 61:205-210
Publication Year :
2017
Publisher :
Elsevier BV, 2017.

Abstract

Problem Motor-vehicle crashes were the second leading cause of injury death for adults aged 65–84 years in 2014. Some older drivers choose to self-regulate their driving to maintain mobility while reducing driving risk, yet the process remains poorly understood. Methods Data from 729 older adults (aged ≥ 60 years) who joined an older adult ride service program between April 1, 2010 and November 8, 2013 were analyzed to define and describe classes of driving self-regulation. Latent class analysis was employed to characterize older adult driving self-regulation classes using driving frequency and avoidance of seven driving situations. Logistic regression was used to explore associations between characteristics affecting mobility and self-regulation class. Results Three classes were identified (low, medium, and high self-regulation). High self-regulating participants reported the highest proportion of always avoiding seven risky driving situations and the lowest driving frequency followed by medium and low self-regulators. Those who were female, aged 80 years or older, visually impaired, assistive device users, and those with special health needs were more likely to be high self-regulating compared with low self-regulating. Conclusions and practical applications Avoidance of certain driving situations and weekly driving frequency are valid indicators for describing driving self-regulation classes in older adults. Understanding the unique characteristics and mobility limitations of each class can guide optimal transportation strategies for older adults.

Details

ISSN :
00224375
Volume :
61
Database :
OpenAIRE
Journal :
Journal of Safety Research
Accession number :
edsair.doi.dedup.....5145f740764f225a87ad569706829cc3