We examined the physical, visual, health, and cognitive abilities of 1,656 older adults as prospective predictors of self-reported driving cessation over a 5-year period. We examined the time to driving cessation across 5 years after we controlled for days driven per week at baseline and any cognitive intervention participation. Older age, congestive heart failure, and poorer physical performance (according to the Turn 360 Test) were statistically significant risk factors for driving cessation. Slower speed of processing (according to the Digit Symbol Substitution and Useful Field of View tests) was a significant risk factor even after we took baseline driving, age, health, vision, and physical performance into consideration. Implications are that assessments of cognitive speed of processing can provide valuable information about the subsequent risk of driving cessation.

Previous studies have suggested that 4 latent constructs (depressed affect, well-being, interpersonal problems, somatic symptoms) underlie the item responses on the Center for Epidemiological Studies Depression (CES-D) Scale. This instrument has been widely used in dementia caregiving research, but the fit of this multifactor model and the explanatory contributions of multifactor models have not been sufficiently examined for caregiving samples. The authors subjected CES-D data (N = 1,183) from the initial Resources for Enhancing Alzheimer’s Caregiver Health Study to confirmatory factor analysis methods and found that the 4-factor model provided excellent fit to the observed data. Invariance analyses suggested only minimal item-loading differences across race subgroups and supported the validity of race comparisons on the latent factors. Significant race differences were found on 3 of the 4 latent factors both before and after controlling for demographic covariates. African Americans reported less depressed affect and better well-being than White caregivers, who reported better well-being and fewer interpersonal problems than Hispanic caregivers. These findings clarify and extend previous studies of race differences in depression among diverse samples of dementia caregivers.

Purpose The purpose of this study was to prospectively examine the role of cognitive and instrumental functional performance in driving cessation while simultaneously accounting for any contributions of demographics, vision, physical performance, and health among a sample of older adults without dementia. Design and Methods Included in the analyses were 1,838 participants from the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) study who were drivers at baseline and completed the third-year assessment. Participants completed baseline assessments of sociodemographic characteristics, health, sensory function, physical function, cognitive abilities, instrumental functional performance, and depressive symptoms. Driving status was again ascertained 3 years later. Results We used Cox proportional hazard analyses to examine prospective predictors of driving cessation over a 3-year period. The final model indicated four significant risk factors for driving cessation: older age (hazard ratio [HR] = 1.06, p =.009), poorer balance as measured by the Turn 360° test (HR = 1.17, p =.002), slower cognitive speed of processing as measured by the Useful Field of View test (HR = 1.37, p =.004), and poorer instrumental functional performance as assessed by the Everyday Problems Test (HR = 1.59, p <.001). Implications Although vision, health, and physical abilities are commonly considered when determining driving capacity, cognitive speed of processing and instrumental functional performance may be better indicators of subsequent likelihood of driving cessation across 3 years among older adults. Poor health and vision may only impact driving cessation to the extent that cognitive speed of processing and instrumental functioning are affected.

In 129 community-dwelling older adults, feedback regarding qualification for an insurance discount (based on a visual speed of processing test; Useful Field of View) was examined as a prospective predictor of change in self-reported driving ability, driving avoidance, and driving exposure over 3 months, along with physical, visual, health, and cognitive variables. Multiple regression models indicated that after controlling for baseline scores on the outcome measures, failure to qualify was a significant predictor of increased avoidance over 3 months (p = .02) but not change in self-rated driving ability or exposure. Female gender (p = .03) was a significant predictor of subsequent lower self-rated driving ability. Overall, the findings of this study provide support for the role of feedback in the self-monitoring of older adults' driving behavior through avoidance of challenging driving situations but not through driving exposure or self-rated driving ability.

Many U.S. states rely on older adults to self-regulate their driving and determine when driving is no longer a safe option. However, the relationship of older adults’ self-rated driving in terms of actual driving competency outcomes is unclear. The current study investigates self-rated driving in terms of (1) systematic differences between older adults with high (good/excellent) versus low (poor/fair/average) self-ratings, and (2) the predictive nature of self-rated driving to adverse driving outcomes in older drivers (n=350; mean age 73.9, SD=5.25, range 65–91). Adverse driving outcomes included self-reported incidences of (1) being pulled over by the police, (2) receiving a citation, (3) receiving a recommendation to cease or limit driving, (4) crashes, and (5) state-reported crashes. Results found that older drivers with low self-ratings reported more medical conditions, less driving frequency, and had been given more suggestions to stop/limit their driving; there were no other significant differences between low and high self-raters. Logistic regression revealed older drivers were more likely to have a state-reported crash and receive a suggestion to stop or limit driving. Men were more likely to report all adverse driving outcomes except for receiving a suggestion to stop or limit driving. Regarding self-rated driving, older adults with high ratings were 66% less likely (OR=0.34, 95% CI=0.14–0.85) to have received suggestions to limit or stop driving after accounting for demographics, health and driving frequency. Self-ratings were not predictive of other driving outcomes (being pulled over by the police, receiving a citation, self-reported crashes, or state-reported crashes, ps>.05). Most older drivers (85.14%) rated themselves as either good or excellent drivers regardless of their actual previous citation or crash rates. Self-rated driving is likely not related to actual driving proficiency as indicated by previous crash involvement in older adults. Suggestions from other individuals to limit or cease driving may be more influential on self-ratings.