Gwen Bergen1, Bethany A West2, Feijun Luo2, Donna C Bird3, Katherine Freund4, Richard H Fortinsky5, Loren Staplin6. 1. National Center for Injury Prevention and Control, CDC, Atlanta, GA, United States. Electronic address: Gbergen@cdc.gov. 2. National Center for Injury Prevention and Control, CDC, Atlanta, GA, United States. 3. University of Southern Maine, Portland, ME, United States. 4. ITNAmerica, Westbrook, ME, United States. 5. University of Connecticut School of Medicine, Farmington, CT, United States. 6. TransAnalytics, LLC, Quakertown, PA, United States.
Abstract
PROBLEM: Motor-vehicle crashes were the second leading cause of injury death for adults aged 65-84years 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 ≥60years) 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 80years 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. Published by Elsevier Ltd.
PROBLEM: Motor-vehicle crashes were the second leading cause of injury death for adults aged 65-84years 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 ≥60years) 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 80years 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. Published by Elsevier Ltd.
Entities:
Keywords:
Mobility; Motor vehicle; Older adult; Older driver; Self-regulation
Authors: Boon Hong Ang; Jennifer Anne Oxley; Won Sun Chen; Michelle Khai Khun Yap; Keang Peng Song; Shaun Wen Huey Lee Journal: PLoS One Date: 2020-05-15 Impact factor: 3.240