The Influence of the Transportation Environment on Driving Reduction and Cessation

Transition from driving to driving-cessation: experience of older persons and caregivers: a descriptive qualitative design

BACKGROUND

For some older persons, driving is essential to maintain their daily activities and engagement with society. Unfortunately, some will have to stop driving, as they age. Driving-cessation is an important transition for older persons and caregivers, well known to cause significant challenges and consequences. This study aimed to describe the experience of older persons and caregivers in the transition from driving to ceasing to drive.

METHODS

Within a descriptive qualitative design, semi-structured interviews were undertaken with older persons (n = 8) and caregivers (n = 6) from the city of Québec (Quebec, Canada), from November 2020 to March 2021. Using an inductive approach, the qualitative data was analyzed with the content analysis method.

RESULTS

Some older persons had never thought they might someday lose their driver's license. The process of legislative assessment was unknown by almost all older persons and caregivers. The process was therefore very stressful for the research participants. Driving-cessation is a difficult transition that is associated with loss of independence, freedom, spontaneity, and autonomy. Qualitative analysis of data showed different factors that positively or negatively influence the experience of ceasing to drive, such as the older person's ownership of the decision, the presence of a network of friends and family, and self-criticism. There was significant impact related to driving-cessation for caregivers, such as assuming the entire burden of travel, psychologically supporting older persons in their grief, and navigating the driver's licensing system.

CONCLUSIONS

These study results could help organizations and healthcare professionals to better accompany and support older drivers and caregivers in the transition from driving to driving-cessation.

TRIAL REGISTRATION

None.

Planning for Driving Retirement: The Effect of Driving Perceptions, Driving Events, and Assessment of Driving Alternatives

Most older adults will eventually stop driving, but few engage in planning for driving retirement. This study assessed whether driving stress, enjoyment, confidence, concerning driving events, and assessment of driving alternatives influence planning. Demographic factors were also included. Data were collected via a mailed transportation survey, with a final sample of 551 older adults who currently drive. Linear regression analyses revealed that more driving retirement planning was associated with greater driving stress, less driving confidence, and a more positive view of driving alternatives. Driving enjoyment and recent concerning driving events were not significantly related. Among the control variables, race and income were significantly related to planning, suggesting that lower income and identifying as Black race were associated with more planning. Gender only approached significance, suggesting that females may plan more than males. Overall, these findings suggest that more driving retirement planning is warranted. Some of the groups known to be at increased risk for driving reduction and cessation plan more for that eventuality than their counterparts. Implications of the study and suggestions for future research are discussed.

The Predictors of Driving Cessation among Older Drivers in Korea

Background: As the elderly population and the number of older drivers grow, public safety concerns about traffic accidents involving older drivers are increasing. Approaches to reduce traffic accidents involving older drivers without limiting their mobility are needed. This study aimed to investigate the driving cessation (DC) rate among older Korean adults and predictors of DC based on the comprehensive mobility framework. Method: In this cross-sectional study, data from 2970 to 10,062 older adults over 65 years old from the 2017 National Survey of Elderly People were analyzed in April 2020. Multivariate logistic regression analyses were conducted to identify the predictors of DC. Results: Residential area, an environmental factor, was a strong predictor of DC (Odds Ratio (OR) 2.21, 95% Confidential Interval (CI) 1.86–2.62). Older drivers living in an area with a metro system were 2.21 more likely to stop driving than those living in an area without a metro system. Other demographic, financial, psychosocial, physical, and cognitive variables also predicted DC. Conclusion: Environmental factors were strong predictors of older adults’ DC. Therefore, political and environmental support, such as the provision of accessible public transportation, is essential to increase the DC rate among older adults to increase public safety without decreasing their mobility.

Driving Status and Transportation Disadvantage Among Medicare Beneficiaries

Transportation disadvantage may have important implications for the health, well-being, and quality of life of older adults. This study used the 2015 National Health Aging Trends Study, a nationally representative study of Medicare beneficiaries aged 65 and over (N = 7,498), to generate national estimates of transportation modalities and transportation disadvantage among community-dwelling older adults in the United States. An estimated 10.8 million community-dwelling older adults in the United States rarely or never drive. Among nondrivers, 25% were classified as transportation disadvantaged, representing 2.3 million individuals. Individuals with more chronic medical conditions and those reliant on assistive devices were more likely to report having a transportation disadvantage (p < .05). Being married resulted in a 50% decreased odds of having a transportation disadvantage (p < .01). Some individuals may be at higher risk for transportation-related barriers to engaging in valued activities and accessing care, calling for tailored interventions such as ride-share services combined with care coordination strategies.

Differences in Driving Outcomes Among Cognitively Normal African American and Caucasian Older Adults

OBJECTIVE

To examine the effect of race in driving performance and behavior prospectively among cognitively normal older adults.

METHODS

Cognitively normal participants (Clinical Dementia Rating 0), ≥ 65 years of age (n = 177) were selected from prospective, longitudinal studies at the Knight Alzheimer Disease Research Center at Washington University. Self-reported driving behavior (Driving Habits Questionnaire) and driving performance (road test) were annually assessed. Daily driving behavior data were collected using the Driving Real World In-Vehicle Evaluation System (DRIVES). Baseline differences between African Americans and Caucasians were tested using t tests and general linear models. Amyloid imaging and cerebrospinal fluid Alzheimer disease (AD) biomarkers were compared across groups. Linear mixed models examined change in daily driving behavior over time. Survival analyses tested time to a marginal or fail rating on the road test.

RESULTS

There were no differences between African Americans (n = 34) and Caucasians (n = 143) in age, sex, education, or vascular risk factors. Baseline self-reported driving behavior and road test performance were largely similar for both races. Longitudinal analyses using the DRIVES data aggregated monthly showed that African Americans had a greater reduction in number of trips made per month, miles driven per month, and trips with aggressive behavior compared to Caucasians. These effects remained after controlling for AD biomarkers, age, education, and sex.

CONCLUSIONS

In this sample of cognitively normal older adults, African Americans had a greater reduction of daily driving behavior compared to Caucasians. Observed racial differences may reflect differences in environmental/social factors, changes in cognition, and/or physical functioning.

Older Adults' Expectations about Mortality, Driving Life and Years Left without Driving

People are living and driving longer than ever before, with little preparation for transitioning to being non-drivers. We investigated driving expectations among drivers age 65 and older, including sociodemographic and driving context predictors. Cross-sectional data from 349 older drivers were explored to determine variation in how many years they expected to continue driving. General linear models examined predictors of both expectations. In this predominantly Black/African American sample, 76% of older drivers (mean age = 73 ± 5.7 years) expected a non-driving future, forecasting living an average of 5.75 ± 7.29 years after driving cessation. Regression models on years left of driving life and years left to live post-driving cessation predicted nearly half of the variance in older drivers' expectations with five significant predictors: income, current age, age expected to live to, self-limiting driving to nearby places and difficulty, visualizing being a non-driver. Many older drivers expect to stop driving before end of life.

Coming Out of "Retirement"-Predictors of Driving Resumption Among Older Drivers

Background and Objectives

Predictors and consequences of driving cessation in older adults have been studied extensively. This study sought to establish the extent to which former drivers resume driving and identify associated factors.

Research Design and Methods

Descriptive analysis of the 2011–2015 National Health and Aging Trends Study data (Round 1: n = 6,680; Round 5: n = 3,409) characterized the extent of driving resumption through 2015 by baseline driving status (driver, former driver, never driver). Weighted multivariate logistic regression and multilevel longitudinal models examined predictors of driving resumption.

Results

Among drivers who stopped driving during the study, 17%–28% resumed driving. Age, vehicle ownership, stroke, hospitalization, memory, and perceived transportation barriers were associated with resumption in regression analysis. In multilevel analysis stratified by baseline driving status, poor word recall (OR = 0.62; 95% CI = 0.40, 0.95) and use of public transportation (OR = 9.74; 95% CI = 1.54, 61.77) were significantly associated with driving resumption for baseline drivers, while use of taxi (OR < 0.001; 95% CI = <0.001, 0.02) was negatively associated with resumption for baseline former drivers.

Discussion and Implications

This study highlights several factors associated with driving resumption. Uncertainty about the underlying causes for resumption remains, so results should be interpreted with caution. However, predictive factors may help to identify individuals in need of additional mobility transition counseling. Ongoing transportation assessment may be warranted among former drivers.

E-hail (Rideshare) Knowledge, Use, Reliance, and Future Expectations among Older Adults

The goals of this study were to explore e-hail (e.g., Uber/Lyft) knowledge, use, reliance, and future expectations among older adults. Specifically, we aimed to identify factors that were related to e-hail, and how older adults view this mode as a potential future transportation option. Data were collected from a sample of older adults using a pencil-and-paper mailed survey. Univariate, bivariate, and regression techniques were used to assess the relationships among e-hail and several demographic and other factors. Almost three-quarters of the sample (74%) reported no e-hail knowledge. Only 1.7% had used e-hail to arrange a ride,andonly 3.3% reported that they relied on e-hail for any of their transportation needs. Younger age, male gender, more education, higher transportation satisfaction, and discussing transportation options with others were all independently associated with greater e-hail knowledge. Male gender also predicted e-hail use. E-hail was the mode least relied upon by older adults. Current e-hail knowledge was the biggest predictor of anticipated future use. E-hail may be a viable future option for older adults who have limited or stopped driving. More exposure to e-hail and continued evolution of these services is required to overcome older adults' lower internet/smartphone use. Policies could be implemented at departments of motor vehicles to pair information or training on transportation alternatives (like e-hail) with elimination of driving privileges, or at doctors' offices, senior centers, or hospitals. Potential underlying reasons for the findings are also discussed.