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

Association between polypharmacy and hard braking events in older adult drivers

BACKGROUND

Polypharmacy (i.e., simultaneous use of two or more medications) poses a serious safety concern for older drivers. This study assesses the association between polypharmacy and hard braking events in older adult drivers.

METHODS

Data for this study came from a naturalistic driving study of 2990 older adults. Information about medications was collected through the "brown-bag review" method. Primary vehicles of the study participants were instrumented with data recording devices for up to 44 months. Multivariable negative binomial model was used to estimate the adjusted incidence rate ratios (aIRRs) and 95 % confidence intervals (CIs) of hard-braking events (i.e., maneuvers with linear deceleration rates ≥0.4 g) associated with polypharmacy.

RESULTS

Of the 2990 participants, 2872 (96.1 %) were eligible for this analysis. At the time of enrollment, 157 (5.5 %) drivers were taking fewer than two medications, 904 (31.5 %) were taking 2-5 medications, 895 (31.2 %) were taking 6-9 medications, 571 (19.9 %) were taking 10-13 medications, and 345 (12.0 %) were taking 14 or more medications. Compared to drivers using fewer than two medications, the risk of hard-braking events increased 8 % (aIRR 1.08, 95 % CI 1.04, 1.13) for users of 2-5 medications, 12 % (aIRR 1.12, 95 % CI 1.08, 1.16) for users of 6-9 medications, 19 % (aIRR 1.19, 95 % CI 1.15, 1.24) for users of 10-13 medications, and 34 % (aIRR 1.34, 95 % CI 1.29, 1.40) for users of 14 or more medications.

CONCLUSIONS

Polypharmacy in older adult drivers is associated with significantly increased incidence of hard-braking events in a dose-response fashion. Effective interventions to reduce polypharmacy use may help improve driving safety in older adults.

Diabetes mellitus and hard braking events in older adult drivers

BACKGROUND

Diabetes mellitus (DM) can impair driving safety due to hypoglycemia, hyperglycemia, diabetic peripheral neuropathy, and diabetic eye diseases. However, few studies have examined the association between DM and driving safety in older adults based on naturalistic driving data.

METHODS

Data for this study came from a multisite naturalistic driving study of drivers aged 65-79 years at baseline. Driving data for the study participants were recorded by in-vehicle recording devices for up to 44 months. We used multivariable negative binomial modeling to estimate adjusted incidence rate ratios (aIRRs) and 95% confidence intervals (CIs) of hard braking events (HBEs, defined as maneuvers with deceleration rates ≥ 0.4 g) associated with DM.

RESULTS

Of the 2856 study participants eligible for this analysis, 482 (16.9%) reported having DM at baseline, including 354 (12.4%) insulin non-users and 128 (4.5%) insulin users. The incidence rates of HBEs per 1000 miles were 1.13 for drivers without DM, 1.15 for drivers with DM not using insulin, and 1.77 for drivers with DM using insulin. Compared to drivers without DM, the risk of HBEs was 48% higher for drivers with DM using insulin (aIRR 1.48; 95% CI: 1.43, 1.53).

CONCLUSION

Older adult drivers with DM using insulin appear to be at increased proneness to vehicular crashes. Driving safety should be taken into consideration in DM care and management.

Frailty and poor physical functioning as risk factors for driving cessation

Introduction

Frailty and low physical performance are modifiable factors and, therefore, targets for interventions aimed at delaying driving cessation (DC). The objective was to determine the impact of frailty and physical performance on DC.

Methods

Multisite prospective cohort of older drivers. The key inclusion criteria are as follows: active driver age 65-79 years, possessing a valid driver's license, without significant cognitive impairment, and driving a 1996 car or a newer model car. Of the 2,990 enrolled participants, 2,986 (99.9%) had at least one frailty or Short Physical Performance Battery (SPPB) measure and were included in this study. In total, 42% of participants were aged 65-69 years, 86% were non-Hispanic white, 53% were female, 63% were married, and 41% had a high degree of education. The Fried Frailty Phenotype and the Expanded Short Physical Performance Battery (SPPB) from the National Health and Aging Trends Study were utilized. At each annual visit, DC was assessed by the participant notifying the study team or self-reporting after no driving activity for at least 30 days, verified via GPS. Cox proportional hazard models, including time-varying covariates, were used to examine the impact of the SPPB and frailty scores on time to DC. This assessment included examining interactions by sex.

Results

Seventy-three participants (2.4%) stopped driving by the end of year 5. Among women with a fair SPPB score, the adjusted hazard ratio (HR) of DC was 0.26 (95% confidence interval (CI) 0.10-0.65) compared to those with a poor SPPB score. For those with a good SPPB score, the adjusted HR of DC had a p-value of <0.001. Among men with a fair SPPB score, the adjusted hazard ratio (HR) of DC was 0.45 (95% CI 0.25-0.81) compared to those with a poor SPPB score. For men with a good SPPB score, the adjusted HR of DC was 0.19 (95% CI 0.10-0.36). Sex was not an effect modifier between frailty and DC. For those who were categorized into pre-frail or frail, the adjusted ratio of HR to DC was 6.1 (95% CI 2.7-13.8) compared to those who were not frail.

Conclusion and relevance

Frailty and poor physical functioning are major risk factors for driving cessation. Staying physically active may help older adults to extend their driving life expectancy and mobility.

Relationship of Decisional Conflict About Driving Habits Between Older Adult Drivers and Their Family Members and Close Friends

This study examines the relationship of decisional conflict about driving habits between older adult drivers (≥70 years old) and their family members and close friends. This secondary analysis utilizes data originating from a multi-site randomized controlled trial assessing the effect of a driving decision aid (DDA) intervention. Decisional conflict about stopping or changing driving habits for drivers was measured with the Decisional Conflict Scale (DCS). Dyadic associations between drivers' and study partners' (SPs') DCS scores were analyzed using an actor-partner interdependence model. Among 228 driver-SP dyads, Dyadic DCS was correlated at baseline (r = .18, p < .01), and pre-intervention DCS was associated with post-intervention DCS (p < .001 for SPs [β = .73] and drivers [β = .73]). Drivers' baseline DCS and SPs' post-intervention DCS were slighly correlated (β = .10; p = .036). Higher decisional conflict about driving among older drivers is frequently shared by their SPs. Shared decisional conflict may persist beyond intervening to support decision-making about driving cessation.

Association of Depression and Antidepressant Use With Driving Behaviors in Older Adults: A LongROAD Study

Older adults aged 70 and older who drive have higher crash death rates per mile driven compared to middle aged (35-54 years) adults who drive in the US. Prior studies have found that depression and or antidepressant medication use in older adults are associated with an increase in the vehicular crash rate. Using data from the prospective multi-site AAA Longitudinal Research on Aging Drivers Study, this analysis examined the independent and interdependent associations of self-reported depression and antidepressant use with driving behaviors that can increase motor vehicle crash risk such as hard braking, speeding, and night-time driving in adults over age 65. Of the 2951 participants, 6.4% reported having depression and 21.9% were on an antidepressant medication. Correcting for age, race, gender, and education level, participants on an antidepressant had increased hard braking events (1.22 [1.10-1.34]) but self-reported depression alone was not associated with changes in driving behaviors.

Migraine headaches are associated with motor vehicle crashes and driving habits among older drivers: Prospective cohort study

BACKGROUND

Migraine headache is common in older adults, often causing symptoms that may affect driving safety. This study examined associations of migraine with motor vehicle crashes (MVCs) and driving habits in older drivers and assessed modification of associations by medication use.

METHODS

In a multi-site, prospective cohort study of active drivers aged 65-79 (53% female), we assessed prevalent migraine (i.e., ever had migraine, reported at enrollment), incident migraine (diagnosis first reported at a follow-up visit), and medications typically used for migraine prophylaxis and treatment. During 2-year follow-up, we recorded self-reported MVCs and measured driving habits using in-vehicle GPS devices. Associations of prevalent migraine with driving outcomes were estimated in multivariable mixed models. Using a matched design, associations of incident migraine with MVCs in the subsequent year were estimated with conditional logistic regression. Interactions between migraine and medications were tested in all models.

RESULTS

Of 2589 drivers, 324 (12.5%) reported prevalent migraine and 34 (1.3%) incident migraine. Interactions between migraine and medications were not statistically significant in any models. Prevalent migraine was not associated with MVCs in the subsequent 2 years (adjusted OR [aOR] = 0.98; 95% CI: 0.72, 1.35), whereas incident migraine significantly increased the odds of having an MVC within 1 year (aOR = 3.27; 1.21, 8.82). Prevalent migraine was associated with small reductions in driving days and trips per month and increases in hard braking events in adjusted models.

CONCLUSION

Our results suggest substantially increased likelihood of MVCs in the year after newly diagnosed migraine, indicating a potential need for driving safety interventions in these patients. We found little evidence for MVC risk or substantial changes in driving habits associated with prevalent migraine. Future research should examine timing, frequency, and severity of migraine diagnosis and symptoms, and use of medications specifically prescribed for migraine, in relation to driving outcomes.

Impact of driving cessation on health-related quality of life trajectories

BACKGROUND

Trajectories of health-related quality of life (HRQoL) after driving cessation (DC) are thought to decline steeply, but for some, HRQoL may improve after DC. Our objective is to examine trajectories of HRQoL for individuals before and after DC. We hypothesize that for urban drivers, volunteers and those who access alternative transportation participants' health may remain unchanged or improve.

METHODS

This study uses data from the AAA Longitudinal Research on Aging Drivers (LongROAD) study, a prospective cohort of 2,990 older drivers (ages 65-79 at enrollment). The LongROAD study is a five-year multisite study and data collection ended October 31, 2022. Participants were recruited using a convenience sample from the health centers roster. The number of participants approached were 40,806 with 7.3% enrolling in the study. Sixty-one participants stopped driving permanently by year five and had data before and after DC. The PROMIS®-29 Adult Profile was utilized and includes: 1) Depression, 2) Anxiety, 3) Ability to Participate in Social Roles and Activities, 4) Physical Function, 5) Fatigue, 6) Pain Interference, 7) Sleep Disturbance, and 8) Numeric Pain Rating Scale. Adjusted (age, education and gender) individual growth models with 2989 participants with up to six observations from baseline to year 5 in the models (ranging from n = 15,041 to 15,300) were utilized.

RESULTS

Ability to participate in social roles and activities after DC improved overall. For those who volunteered, social roles and activities declined not supporting our hypothesis. For those who accessed alternative transportation, fatigue had an initial large increase immediately following DC thus not supporting our hypothesis. Urban residents had worse function and more symptoms after DC compared to rural residents (not supporting our hypothesis) except for social roles and activities that declined steeply (supporting our hypothesis).

CONCLUSIONS

Educating older adults that utilizing alternative transportation may cause initial fatigue after DC is recommended. Accessing alternative transportation to maintain social roles and activities is paramount for rural older adults after DC especially for older adults who like to volunteer.

In-vehicle Sensing and Data Analysis for Older Drivers with Mild Cognitive Impairment

Driving is a complex daily activity indicating age and disease-related cognitive declines. Therefore, deficits in driving performance compared with ones without mild cognitive impairment (MCI) can reflect changes in cognitive functioning. There is increasing evidence that unobtrusive monitoring of older adults' driving performance in a daily-life setting may allow us to detect subtle early changes in cognition. The objectives of this paper include designing low-cost in-vehicle sensing hardware capable of obtaining high-precision positioning and telematics data, identifying important indicators for early changes in cognition, and detecting early-warning signs of cognitive impairment in a truly normal, day-to-day driving condition with machine learning approaches. Our statistical analysis comparing drivers with MCI to those without reveals that those with MCI exhibit smoother and safer driving patterns. This suggests that drivers with MCI are cognizant of their condition and tend to avoid erratic driving behaviors. Furthermore, our Random Forest models identified the number of night trips, number of trips, and education as the most influential factors in our data evaluation.

Older Adults and Unintentional Injury

Clinicians play an important role in the prevention of unintentional injuries. Falls and motor vehicle crashes (MVC) have predictable and overlapping antecedents. Systematic screening for and management of vision impairment, frailty, cognitive impairment, polypharmacy, and inappropriate medications will reduce both falls and MVC risks. Fall-prevention measures, such as strength training, need to be more widely prescribed by physicians and implemented by older adults. Technologically tailored approaches are needed to leverage fall-reduction programs at home, as well as education of older adults regarding home hazards.

Motor Vehicle Crash Risk in Older Adult Drivers With Attention-Deficit/Hyperactivity Disorder

Importance

Symptoms of attention-deficit/hyperactivity disorder (ADHD), such as inattentiveness and impulsivity, could affect daily functioning and driving performance throughout the life span. Previous research on ADHD and driving safety is largely limited to adolescents and young adults.

Objective

To examine the prevalence of ADHD and the association between ADHD and crash risk among older adult drivers.

Design, Setting, and Participants

This prospective cohort study collected data from primary care clinics and residential communities in 5 US sites (Ann Arbor, Michigan; Baltimore, Maryland; Cooperstown, New York; Denver, Colorado; and San Diego, California) between July 6, 2015, and March 31, 2019. Participants were active drivers aged 65 to 79 years at baseline enrolled in the Longitudinal Research on Aging Drivers project who were studied for up to 44 months through in-vehicle data recording devices and annual assessments. The data analysis was performed between July 15, 2022, and August 14, 2023.

Exposure

Lifetime ADHD based on an affirmative response to the question of whether the participant had ever had ADHD or had ever been told by a physician or other health professional that he or she had ADHD.

Main Outcomes and Measures

The main outcomes were hard-braking events defined as maneuvers with deceleration rates of 0.4g or greater, self-reported traffic ticket events, and self-reported vehicular crashes. Multivariable negative binomial modeling was used to estimate adjusted incidence rate ratios (aIRRs) and 95% CIs of outcomes according to exposure status.

Results

Of the 2832 drivers studied, 1500 (53.0%) were women and 1332 (47.0%) were men with a mean (SD) age of 71 (4) years. The lifetime prevalence of ADHD in the study sample was 2.6%. Older adult drivers with ADHD had significantly higher incidence rates of hard-braking events per 1000 miles than those without ADHD (1.35 [95% CI, 1.30-1.41] vs 1.15 [95% CI, 1.14-1.16]), as well as self-reported traffic ticket events per 1 million miles (22.47 [95% CI, 16.06-31.45] vs 9.74 [95% CI, 8.99-10.55]) and self-reported vehicular crashes per 1 million miles (27.10 [95% CI, 19.95-36.80] vs 13.50 [95% CI, 12.61-14.46]). With adjustment for baseline characteristics, ADHD was associated with a significant 7% increased risk of hard-braking events (aIRR, 1.07; 95% CI, 1.02-1.12), a 102% increased risk of self-reported traffic ticket events (aIRR, 2.02; 95% CI, 1.42-2.88), and a 74% increased risk of self-reported vehicular crashes (aIRR, 1.74; 95% CI, 1.26-2.40).

Conclusions and Relevance

As observed in this prospective cohort study, older adult drivers with ADHD may be at a significantly elevated crash risk compared with their counterparts without ADHD. These findings suggest that effective interventions to improve the diagnosis and clinical management of ADHD among older adults are warranted to promote safe mobility and healthy aging.

Associations of cannabis use with motor vehicle crashes and traffic stops among older drivers: AAA LongROAD study

BACKGROUND

Acute cannabis use is associated with a higher risk of motor vehicle crashes (MVC). This study aimed to determine if self-reported past-year cannabis use is associated with MVC or traffic stops among older drivers.

METHODS

This cross-sectional analysis used data from a multi-center study enrolling active drivers aged 65-79 years. Data regarding cannabis use, MVC, and traffic stops (i.e., being pulled over by police, whether ticketed or not) within the previous 12 months were collected through participant interviews. Log-binomial regression models examined associations of past-year cannabis use with MVC and traffic stops, adjusting for site and sociodemographic and mental health characteristics.

RESULTS

Of 2,095 participating older drivers, 186 (8.88%) used cannabis in the past year but only 10 (<0.5%) within an hour before driving in the last 30 days; 11.41% reported an MVC and 9.45% reported a traffic stop. Past-year cannabis users had a higher prevalence of MVC (adjusted prevalence ratio [aPR] = 1.38; 95%CI: 0.96, 2.00; p = 0.086) and traffic stops (aPR = 1.58; 1.06, 2.35; p = 0.024).

CONCLUSIONS

Past-year cannabis use was associated with increased traffic stops, which are correlated modestly with increased MVC in past studies and may indicate impaired driving performance. We did not find a statistically significant association of past-year cannabis use with MVC, which may indicate limited sustained effects on driving performance from periodic use among older adults, who report rarely driving immediately after use.

Detecting mild cognitive impairment and dementia in older adults using naturalistic driving data and interaction-based classification from influence score

Several recent studies indicate that atypical changes in driving behaviors appear to be early signs of mild cognitive impairment (MCI) and dementia. These studies, however, are limited by small sample sizes and short follow-up duration. This study aims to develop an interaction-based classification method building on a statistic named Influence Score (i.e., I-score) for prediction of MCI and dementia using naturalistic driving data collected from the Longitudinal Research on Aging Drivers (LongROAD) project. Naturalistic driving trajectories were collected through in-vehicle recording devices for up to 44 months from 2977 participants who were cognitively intact at the time of enrollment. These data were further processed and aggregated to generate 31 time-series driving variables. Because of high dimensional time-series features for driving variables, we used I-score for variable selection. I-score is a measure to evaluate variables' ability to predict and is proven to be effective in differentiating between noisy and predictive variables in big data. It is introduced here to select influential variable modules or groups that account for compound interactions among explanatory variables. It is explainable regarding to what extent variables and their interactions contribute to the predictiveness of a classifier. In addition, I-score boosts the performance of classifiers over imbalanced datasets due to its association with the F1 score. Using predictive variables selected by I-score, interaction-based residual blocks are constructed over top I-score modules to generate predictors and ensemble learning aggregates these predictors to boost the prediction of the overall classifier. Experiments using naturalistic driving data show that our proposed classification method achieves the best accuracy (96%) for predicting MCI and dementia, followed by random forest (93%) and logistic regression (88%). In terms of F1 score and AUC, our proposed classifier achieves 98% and 87%, respectively, followed by random forest (with an F1 score of 96% and an AUC of 79%) and logistic regression (with an F1 score of 92% and an AUC of 77%). The results indicate that incorporating I-score into machine learning algorithms could considerably improve the model performance for predicting MCI and dementia in older drivers. We also performed the feature importance analysis and found that the right to left turn ratio and the number of hard braking events are the most important driving variables to predict MCI and dementia.

Association of falls and fear of falling with objectively-measured driving habits among older drivers: LongROAD study

OBJECTIVE

Falls in older adults are associated with increased motor vehicle crash risk, possibly mediated by driving behavior. We examined the relationship of falls and fear of falling (FOF) with subsequent objectively measured driving habits.

METHODS

This multi-site, prospective cohort study enrolled 2990 active drivers aged 65-79 (53% female). At enrollment, we assessed falls in the past year and FOF (Short Falls Efficacy Scale-International). Driving outcomes included exposure, avoidance of difficult conditions, and unsafe driving during one-year follow-up, using in-vehicle Global Positioning System devices.

RESULTS

Past-year falls were associated with more hard braking events (HBE). High FOF was associated with driving fewer days, miles, and trips, driving nearer home and more HBE. Differences were attenuated and not significant after accounting for health, function, medications and sociodemographics.

DISCUSSION

Differences in objectively measured driving habits according to past-year fall history and FOF were largely accounted for by differences in health and medications. Rather than directly affecting driving, falls and FOF may serve as markers for crash risk and reduced community mobility due to age-related changes and poor health.

Improving Our Understanding of Driving Changes in Preclinical and Early Symptomatic Alzheimer’s Disease: The Role of Naturalistic Driving Studies

Research on how preclinical and early symptomatic Alzheimer’s disease (AD) impacts driving behavior is in its infancy, with several important research areas yet to be explored. This paper identifies research gaps and suggests priorities for driving studies over the next few years among those at the earliest stages of AD. These priorities include how individual differences in demographic and biomarker measures of AD pathology, as well as differences in the in-vehicle and external driving environment, affect driving behavior. Understanding these differences is important to developing future interventions to increase driving safety among those at the earliest stages of AD.

Associations of Self-Care Health Behaviors With Driving Cessation Among Older Drivers

Older adults are at risk of driving cessation as they age, which can result in negative health outcomes including loss of independence. This study aimed to investigate the associations of self-care health behaviors with the risk of driving cessation. Demographics, health and driving characteristics were captured from healthcare systems in Denver, CO, San Diego, CA, Ann Arbor, MI, Baltimore, MD and Cooperstown, NY for 2,990 adults at baseline then followed from July 2015 to January 2021 via in-person assessments and questionnaires. The follow-up accumulated a total of 7,348 person-years and 46 driving cessations, yielding an incidence rate of 0.63 per 100 person-years. Multivariable Cox proportional hazards regression was used to evaluate the relationship between self-care behaviors and driving cessation, stratified by gender, and accounting for multiple failure events and clustering by study site. Ability to participate in social roles and activities was associated with an 8% reduction in the risk of driving cessation [adjusted hazard ratio (HR): 0.92; 95% CI: 0.89, 0.94]. Increased participation in social activities and relationships is associated with driving longevity in older adults and should be targeted for interventions to maintain driving mobility.

Driving Performance in Older Adults: Current Measures, Findings, and Implications for Roadway Safety

Background and Objectives

Over 10,000 people a day turn 65 in the United States. For many older adults, driving represents an essential component of independence and is one of the most important factors in overall mobility. Recent survey studies in older adults suggest that up to 60% of older adult drivers with mild cognitive impairment, and up to 30% with dementia, continue to drive. The purpose of this review is to provide a comprehensive and detailed resource on the topics of cognition and driving for clinicians, researchers, and policymakers working on efforts related to older adult drivers.

Research Design and Methods

Publications on PubMed and Medline and discussions with experts working in geriatrics, technology, driving policy, psychology, and diverse aspects of driving performance were utilized to inform the current review.

Results

Research indicates that there is a complex and inverse correlation between multiple cognitive measures, driving performance, and risky driving behaviors. The fragmented nature of available peer-reviewed literature, and a reliance on correlative data, do not currently allow for the identification of the temporal and reciprocal nature of the interplay between cognition and driving endpoints.

Discussion and Implications

There are currently no widely accepted definitions, conceptual models, or uniform set of analyses for conducting geriatric research that is focused on driving. Establishing conventions for conducting research that harmonizes the fields of geriatrics, cognition, and driving research is critical for the development of the evidence base that will inform clinical practice and road safety policy.

Rate of Social Isolation by Geographic Location Among Older Adults: AAA LongROAD Study

Introduction: Social isolation is a modifiable risk factor for negative health outcomes among older adults. This work assessed the relationship between geography (i.e., urban vs. non-urban residence) and social isolation in a cohort of older drivers.

Methods: The AAA LongROAD cohort with 2,989 older adult drivers from across the country were included. Social isolation was measured at baseline and at two subsequent annual follow-ups using PROMIS v2.0 Social Isolation 4a. The effect of geographic location with social isolation was assessed through with multivariable regression using a generalized estimating equation model.

Results: The rate of social isolation in urban areas was 21% lower (adjusted RR 0.79, 95% CI 0.46, 1.36) compared to non-urban areas after adjusting for covariates, though not significant.

Discussion: Social isolation is a predictor of poor health outcomes and geographic considerations have been lacking in the literature. The panel data in this analysis provides more evidence for causality though the under-representation of non-urban areas potentially reduces the power for the results.

Conclusions: It is important to understand the needs and risk of social isolation in various geographic settings to ensure resources and interventions are appropriately modified for a greater public health impact.

Adapted Stopping Elderly Accidents, Deaths, and Injuries Questions for Falls Risk Screening: Predictive Ability in Older Drivers

INTRODUCTION

Fall fatality rates among U.S. older adults increased 30% from 2007 to 2016. In response, the Centers for Disease Control and Prevention developed the Stopping Elderly Accidents, Deaths, and Injuries algorithm for fall risk screening, assessment, and intervention. The current Stopping Elderly Accidents, Deaths, and Injuries algorithm with 2 levels (at risk and not at risk) was adapted to an existing cohort of older adult drivers.

METHODS

A U.S. multisite prospective cohort (N=2,990) of drivers (aged 65-79 years), from 2015 to 2017, was used for these analyses completed in January 2020-October 2020. To measure the adapted Stopping Elderly Accidents, Deaths, and Injuries key questions for fall risk screening performance in predicting future falls, adjusted logistic regression determined the area of the receiver operating characteristic curve. An adjusted mixed logistic regression modeled the association between the adapted Stopping Elderly Accidents, Deaths, and Injuries key questions and future falls.

RESULTS

The adapted Stopping Elderly Accidents, Deaths, and Injuries key questions yielded an area under the curve of 0.65 in determining any fall over 2 years. The adjusted mixed logistic regression model suggests that those at risk for falls at baseline were associated with 2.37 times higher odds of any fall (95% CI=2.00, 2.80) and 3.60 times higher odds of multiple falls (95% CI=2.88, 4.51) over 2 years.

CONCLUSIONS

The adapted Stopping Elderly Accidents, Deaths, and Injuries key questions for fall risk screening yielded fair predictive ability for falls over 2 years and were strongly associated with future falls for older adult drivers. The adapted Stopping Elderly Accidents, Deaths, and Injuries key questions can be applied to existing data in nonclinical settings to strengthen fall screening and prevention at a population level.

The Advancing Understanding of Transportation Options (AUTO) study: design and methods of a multi-center study of decision aid for older drivers

BACKGROUND

Decision-making about when to stop driving for older adults involves assessment of driving risk, availability of support or resources, and strong emotions about loss of independence. Although the risk of being involved in a fatal crash increases with age, driving cessation can negatively impact an older adult's health and well-being. Decision aids can enhance the decision-making process by increasing knowledge of the risks and benefits of driving cessation and improve decision quality. The impact of decision aids regarding driving cessation for older adults is unknown.

METHODS

The Advancing Understanding of Transportation Options (AUTO) study is a multi-site, two-armed randomized controlled trial that will test the impact of a decision aid on older adults' decisions about changes in driving behaviors and cessation. AUTO will enroll 300 drivers age ≥ 70 years with a study partner (identified by each driver); the dyads will be randomized into two groups (n = 150/group). The decision aid group will view the web-based decision aid created by Healthwise at baseline and the control group will review information about driving that does not include evidence-based elements on risks and benefits and values clarification about driving decisions. The AUTO trial will compare the effect of the decision aid, versus control, on a) immediate decision quality (measured by the Decisional Conflict Scale; primary outcome); b) longitudinal psychosocial outcomes at 12 and 24 months (secondary outcomes); and c) longitudinal driving behaviors (including reduction or cessation) at 12 and 24 months (secondary outcomes). Planned stratified analyses will examine the effects in subgroups defined by cognitive function, decisional capacity, and readiness to stop driving.

DISCUSSION

The AUTO study is the first large-scale randomized trial of a driving decision aid for older adults. Results from this study will directly inform clinical practice about how best to support older adults in decision-making about driving.

TRIAL REGISTRATION

ClinicalTrials.gov : NCT04141891 . Registered on October 28, 2019. Located at https://clinicaltrials.gov/ct2/show/NCT04141891.

Using Naturalistic Driving Data to Predict Mild Cognitive Impairment and Dementia: Preliminary Findings from the Longitudinal Research on Aging Drivers (LongROAD) Study

Emerging evidence suggests that atypical changes in driving behaviors may be early signals of mild cognitive impairment (MCI) and dementia. This study aims to assess the utility of naturalistic driving data and machine learning techniques in predicting incident MCI and dementia in older adults. Monthly driving data captured by in-vehicle recording devices for up to 45 months from 2977 participants of the Longitudinal Research on Aging Drivers study were processed to generate 29 variables measuring driving behaviors, space and performance. Incident MCI and dementia cases (n = 64) were ascertained from medical record reviews and annual interviews. Random forests were used to classify the participant MCI/dementia status during the follow-up. The F₁ score of random forests in discriminating MCI/dementia status was 29% based on demographic characteristics (age, sex, race/ethnicity and education) only, 66% based on driving variables only, and 88% based on demographic characteristics and driving variables. Feature importance analysis revealed that age was most predictive of MCI and dementia, followed by the percentage of trips traveled within 15 miles of home, race/ethnicity, minutes per trip chain (i.e., length of trips starting and ending at home), minutes per trip, and number of hard braking events with deceleration rates ≥ 0.35 g. If validated, the algorithms developed in this study could provide a novel tool for early detection and management of MCI and dementia in older drivers.

Use of multilevel modeling to examine variability of distracted driving behavior in naturalistic driving studies

Current methods of analyzing data from naturalistic driving studies provide important insights into real-world safety-related driving behaviors, but are limited in the depth of information they currently offer. Driving measures are frequently collapsed to summary levels across the study period, excluding more fine-grained differences such as changes that occur from trip to trip. By retaining trip-specific data, it is possible to quantify how much a driver differs from trip to trip (within-person variability) in addition to how he or she differs from other drivers (between-person variability). To the authors' knowledge, the current study is the first to use multilevel modeling to quantify variability in distracted driving behavior in a naturalistic dataset of older drivers. The current study demonstrates the utility of examining within-person variability in a naturalistic driving dataset of 68 older drivers across two weeks. First, multilevel models were conducted for three distracted driving behaviors to distinguish within-person variability from between-person variability in these behaviors. A high percentage of variation in distracted driving behaviors was attributable to within-person differences, indicating that drivers' behaviors varied more across their own driving trips than from other drivers (ICCs = .93). Then, to demonstrate the utility of personal characteristics in predicting daily driving behavior, a hypothetical model is presented using simulated daily sleep duration from the previous night to predict distracted driving behavior the following day. The current study demonstrates substantial variability in driving behaviors within an older adult sample and the promise of individual characteristics to provide better prediction of driving behaviors relevant to safety, which can be applied in investigations of current naturalistic driving datasets and in designing future studies.

Potentially Inappropriate Medication Use and Hard Braking Events in Older Drivers

Potentially inappropriate medications (PIMs) identified by the American Geriatrics Society should generally be avoided by older adults because of ineffectiveness or excess risk of adverse effects. Few studies have examined the effects of PIMs on driving safety measured by prospectively and objectively collected driving data. Data for this study came from the Longitudinal Research on Aging Drivers study, a multisite naturalistic driving study of older adults. Multivariable negative binominal modeling was used to estimate incidence rate ratios and 95% confidence intervals of hard braking events (proxies for unsafe driving behavior defined as events with a deceleration rate ≥0.4 g) associated with PIM use among older drivers. The study sample consisted of 2932 drivers aged 65-79 years at baseline, including 542 (18.5%) who used at least one PIM. These drivers were followed through an in-vehicle recording device for up to 44 months. The overall incidence of hard braking events was 1.16 per 1000 miles. Use of PIMs was associated with a 10% increased risk of hard braking events. Compared to drivers who were not using PIMs, the risk of hard braking events increased 6% for those using one PIM, and 24% for those using two or more PIMs. Use of PIMs by older adult drivers is associated in a dose-response fashion with elevated risks of hard braking events. Reducing PIM use in older adults might help improve driving safety as well as health outcomes.

Association of Physical Function With Driving Space and Crashes Among Older Adults

BACKGROUND AND OBJECTIVES

Balancing both driver mobility and safety is important for the well-being of older adults. However, research on the association of physical function with these 2 driving outcomes has yielded inconsistent findings. This study examined whether physical functioning of older drivers, as measured by the Short Physical Performance Battery (SPPB), is associated with either driving space or crash involvement.

METHODS

Using cross-sectional data of active drivers aged 65-79 years from the AAA Longitudinal Research on Aging Drivers (LongROAD) study (n = 2,990), we used multivariate log-binomial and logistic regressions to estimate the associations of the SPPB with either self-reported restricted driving space in the prior 3 months or any crashes in the past year. Interaction with gender was assessed using likelihood ratio tests.

RESULTS

After adjustment, older drivers with higher SPPB scores (higher physical functioning) had lower prevalence of restricted driving space (8-10 vs. 0-7, prevalence ratio [PR] = 0.88, 95% confidence interval [CI]: 0.78-0.99; 11-12 vs. 0-7, PR = 0.78, 95% CI: 0.61-0.99). Fair (8-10), but not good (11-12), scores were significantly associated with reduced crash involvement (8-10 vs. 0-7, odds ratio [OR] = 0.71, 95% CI: 0.60-0.84). Gender was not a significant effect modifier.

DISCUSSION AND IMPLICATIONS

This study provides evidence that higher physical functioning is associated with better driving mobility and safety and that the SPPB may be useful for identifying at-risk drivers. Further research is needed to understand physical functioning's longitudinal effects and the SPPB's role in older driver intervention programs.

Medication use and driving patterns in older drivers: preliminary findings from the LongROAD study

Background

The potential for impaired driving due to medication use can occur at any age, though older adults are more likely to take multiple prescribed medications and experience side effects that may affect driving ability. The purpose of this study was to characterize the relationship between medications and driving safety behaviors.

Methods

Data for this study came from the five-site Longitudinal Research on Aging Drivers (LongROAD) project. Participants were active drivers, age 65–79 years at enrollment, and patients at one of the 5 participating sites. Medication names and doses were obtained at baseline based on the “brown-bag review” method. Medications were coded using the American Hospital Formulary Service system. Driving data were collected by a GPS accelerometer installed in the study participants’ main vehicles.

Results

Medication data were available for 2949 (98.6%) of the 2990 participants, and 2898 (96.9% of all participants) had both medication data and at least 30 recorded days of driving. The median number of medications taken per study participant was seven, with a range of 0–51. Total number of medications was significantly associated with a higher rapid deceleration rate. Certain medication classes were significantly associated with other driving outcomes, including central nervous system agents (more speeding events), hormones and gastrointestinal medications (more rapid decelerations), electrolytes (fewer rapid decelerations), and antihistamines (greater right to left turn ratio).

Conclusions

Older adult drivers are taking large quantities of prescription and non-prescription medications that may affect their driving safety. Certain medication classes are associated with potentially adverse driving patterns, such as speeding and rapid decelerations, while others are associated with potentially protective maneuvers, such as right hand turning. Further research is warranted to identify and mitigate potential adverse effects of such medications on driving safety in older adults.

Self-Reported Opioid Use and Driving Outcomes among Older Adults: The AAA LongROAD Study

BACKGROUND

Opioid medications are important therapeutic options to mitigate the harmful effects of pain but can also impair driving ability. We sought to explore opioid use, pain levels, and driving experiences among older drivers.

METHODS

Cognitively intact drivers ages 65 to 79 years were recruited for the multisite AAA Longitudinal Research on Aging Drivers (LongROAD) study (n = 2990). This cross-sectional analysis used data from the baseline questionnaire and "brown-bag" medication review.

RESULTS

Among LongROAD participants (47% male, 88% white, 41% aged 65 to 69 years), 169 (5.7%) reported currently taking an opioid, with a median daily dose of 20 morphine milligram equivalents. Participants did not differ significantly in opioid use by age, gender, race, or ethnicity (P > .05). After adjustment for age, gender, race and ethnicity, participants who were taking opioids (vs not) were significantly more likely to report self-regulated driving reduction and reduced driving ability. However, these effects became nonsignificant when hospitalization, impaired physical function and other factors associated with opioid use were controlled.

CONCLUSIONS

In this study from a large, geographically diverse sample of older adults, there was an association between opioid use and several self-reported measures of driving behavior and ability. However, future work should clarify the effects on driving of opioid use from the effects of the painful medical conditions for which the opioids are being taken. Clinicians should continue to discuss the risks and benefits of opioid medications with patients, including risks related to driving safety.

The Drives for Driving Simulation: A Scientometric Analysis and a Selective Review of Reviews on Simulated Driving Research

Driving behaviors and fitness to drive have been assessed over time using different tools: standardized neuropsychological, on-road and driving simulation testing. Nowadays, the great variability of topics related to driving simulation has elicited a high number of reviews. The present work aims to perform a scientometric analysis on driving simulation reviews and to propose a selective review of reviews focusing on relevant aspects related to validity and fidelity. A scientometric analysis of driving simulation reviews published from 1988 to 2019 was conducted. Bibliographic data from 298 reviews were extracted from Scopus and WoS. Performance analysis was conducted to investigate most prolific Countries, Journals, Institutes and Authors. A cluster analysis on authors' keywords was performed to identify relevant associations between different research topics. Based on the reviews extracted from cluster analysis, a selective review of reviews was conducted to answer questions regarding validity, fidelity and critical issues. United States and Germany are the first two Countries for number of driving simulation reviews. United States is the leading Country with 5 Institutes in the top-ten. Top Authors wrote from 3 to 7 reviews each and belong to Institutes located in North America and Europe. Cluster analysis identified three clusters and eight keywords. The selective review of reviews showed a substantial agreement for supporting validity of driving simulation with respect to neuropsychological and on-road testing, while for fidelity with respect to real-world driving experience a blurred representation emerged. The most relevant critical issues were the a) lack of a common set of standards, b) phenomenon of simulation sickness, c) need for psychometric properties, lack of studies investigating d) predictive validity with respect to collision rates and e) ecological validity. Driving simulation represents a cross-cutting topic in scientific literature on driving, and there are several evidences for considering it as a valid alternative to neuropsychological and on-road testing. Further research efforts could be aimed at establishing a consensus statement for protocols assessing fitness to drive, in order to (a) use standardized systems, (b) compare systematically driving simulators with regard to their validity and fidelity, and (c) employ shared criteria for conducting studies in a given sub-topic.

The Relationship between in-Vehicle Technologies and Self-Regulation among Older Drivers

The study sought to understand the relationship between in-vehicle technologies (IVTs) and self-regulatory behaviors among older drivers. In a large multi-site study of 2990 older drivers, self-reported data on the presence of IVTs and avoidance of various driving behaviors (talking on a mobile phone while driving, driving at night, driving in bad weather, and making left turns when there is no left turn arrow) were recorded. Self-reports were used to identify whether avoidance was due to self-regulation. Hierarchical logistic regressions were used to determine whether the presence of a particular IVT predicted the likelihood of a given self-regulatory behavior after controlling for other factors. Results suggest that the presence of Integrated Bluetooth/Voice Control systems are related to a reduced likelihood of avoiding talking on a mobile phone while driving due to self-regulation (OR= 0.37, 95% CI= 0.29-0.47). The presence of a Navigation Assistance system was related to a reduced likelihood of avoiding talking on a mobile phone while driving (OR= 0.65, 95% CI= 0.50-0.84) and avoiding driving at night due to self-regulation (OR= 0.80, 95% CI = 0.64-1.00). Present findings suggest in-vehicle technologies may differently influence the self-regulatory behaviors of older drivers.

Associations of Frailty Status with Low-Mileage Driving and Driving Cessation in a Cohort of Older Drivers

The US older adult population is projected to considerably increase in the future, and continued driving mobility is important for health aspects in populations with fewer transportation alternatives. This study evaluated whether frailty is associated with low-mileage driving (<1865 miles per year) and driving cessation among older adults. Baseline demographics and health data were collected for 2990 older drivers via in-person assessments and questionnaires, with 2964 reporting baseline frailty data. Multivariable log-binomial regression models were used to evaluate the association between baseline frailty status and low-mileage driving. Multivariable Cox proportional hazards regression were used to evaluate the association between baseline frailty status and driving cessation. For every unit increase in frailty, the estimated adjusted risk of driving fewer than 1865 miles/year increased by 138% (adjusted risk ratio: 2.38, 95% CI: 1.63-3.46). Relative to older drivers who were not frail, the adjusted hazard ratios of driving cessation were 4.15 (95% CI: 1.89-9.10) for those classified as prefrail and 6.08 (95% CI: 1.36-27.26) for those classified as frail. Frailty is positively associated with low-mileage driving status and driving cessation in a dose-response fashion. Public health interventions that reduce frailty, such as physical activity, may help older drivers maintain safe and independent mobility.

Driving Safety of Cognitively-Impaired Drivers Based on Near Collisions in Naturalistic Driving

Background

Controlled naturalistic driving for examining impacts of cognitive impairment on driving safety is rare.

Objective

Evaluating the safety among drivers with mild cognitive impairment based on near collision incidents using naturalistic driving, and investigating its correlation with cognitive measures.

Methods

Frequency of near collisions of 44 cognitively impaired [Age = 75.1(±6.7), MMSE = 25.5(±2.5)] and 19 control group drivers [Age = 72.5(±7.8), MMSE = 29.3(±0.8)] were obtained from two weeks of recorded driving. Survival time free of predicted collision based on a previously established near-collision to collision estimate ratio of 11 : 1, for 140 hours of driving exposure was calculated. Participants were also tested using Mini-Mental Status Examination (MMSE), Trail A, and Trail B. Spearman correlation and Cox survival analysis were conducted.

Results

Near collision frequency per driving hour was correlated with MMSE (r = -0.258, p = 0.041). Survival analyses showed that cognitively impaired drivers might be prone to higher probability of having collision (p = 0.056) with a hazard ratio of 5.78 (p = 0.092). When all participants were combined, there was a significant difference (p < 0.017) in all the three cognitive measures between drivers with and without predicted collision, which were not significant within patient or control group alone (p > 0.186). Cox regression analysis showed MMSE as the only significant factor (p < 0.025) for survival time of predicted collision, but not age, gender, or driving experience.

Conclusion

The association between driving critical events and cognitive measures suggests that some drivers with mild cognitive impairment might have an elevated driving collision risk compared to control drivers. Standard clinical cognitive measures may be reasonable predictors.

Older Drivers and Their Future Mobility: Views and Involvement of Their Adult Children

In car-dependent societies like New Zealand, getting the right balance between mobility and safety could improve outcomes for older people but will require changes to policy and practice. Driving cessation is a major life transition with many impacts, and adult children are frequently involved in both the transition to non-driving and maintaining mobility afterward. This cross-sectional study (N = 675) sought perspectives of family members of drivers aged 65 or older enrolled in a longitudinal study. Most (94%) were adult children, two thirds were women, and 19% were moderately to extremely anxious about their parent's driving. Loss of independence, driving's role in identity, and reluctance to rely on family were recognized as important barriers to driving cessation. Most (80%) felt that families, as well as older drivers, would be adversely affected by driving cessation. Families identified accessible local information and services, alternative transport, and community-based programs for drivers and families as assistance most needed.

Social Support Moderates the Negative Association Between Reduced Driving and Life Satisfaction in Older Adults

When older adults reduce their driving, there can be subsequent decreases in life satisfaction. In this cross-sectional study, we used baseline data from the multi-site Longitudinal Research on Aging Drivers (LongROAD) study to examine whether social support moderates the negative association between reduced driving and life satisfaction. The outcome variable was life satisfaction, and the main predictor variable was past-year reduced driving (yes/no). Emotional, instrumental, and informational social support were measured using PROMIS v2.0 (Patient-Reported Outcomes Measurement Information System) items. We used generalized linear regression models to examine how social support moderated the association between reduced driving and life satisfaction. Statistical adjustment for social support attenuated the negative effect of reduced driving on life satisfaction by ~10% for all three types of social support.

Cannabis use in older drivers in Colorado: The LongROAD Study

This study examined cannabis use and driving outcomes among older drivers in Colorado, which has legalized medical and recreational use. The associations of self-reported past-year cannabis use with diverse driving outcomes were assessed in 598 drivers aged 65-79 (51% female, 70% with postsecondary education), using regression analysis to adjust for health and sociodemographic characteristics. Two hundred forty four (40.8%) drivers reported ever using cannabis. Fifty-four drivers (9.0%) reported past-year use, ranging from more than once a day (13.0%) to less than once a month (50.0%). Of past-year users, 9.3% reported cannabis use within 1 h of driving in the past year. Past-year users were younger, less highly educated, lower income, and reported significantly worse mental, emotional, social and cognitive health status than drivers without past-year use. Past-year users were four times as likely to report having driven when they may have been over the legal blood-alcohol limit (adjusted OR [aOR] = 4.18; 95% CI: 2.11, 8.25) but were not more likely to report having had a crash or citation (aOR = 1.36; 95% CI: 0.70, 2.66) in the past year. Users and non-users had similar scores on self-rated abilities for safe driving (adjusted beta=-0.04; 95% CI: -0.23, 0.15) and on driving-related lapses, errors and violations in the past year (adjusted beta = 0.04; 95% CI: -0.04, 0.12). Further study is needed to establish driving risks and behaviours related to cannabis use, independent of other associated risk factors, among older adults.

Prevalence of Potentially Inappropriate Medication use in older drivers

Background

Potentially Inappropriate Medication (PIM) use has been studied in a variety of older adult populations across the world. We sought to examine the prevalence and correlates of PIM use in older drivers.

Methods

We applied the American Geriatrics Society 2015 Beers Criteria to baseline data collected from the “brown-bag” review of medications for participants of the Longitudinal Research on Aging Drivers (LongROAD) study to examine the prevalence and correlates of PIM use in a geographically diverse, community-dwelling sample of older drivers (n = 2949). Proportions of participants who used one or more PIMs according to the American Geriatrics Society 2015 Beers Criteria, and estimated odds ratios (ORs) and 95% confidence intervals (CIs) of PIM use associated with participant characteristics were calculated.

Results

Overall, 18.5% of the older drivers studied used one or more PIM. The most commonly used therapeutic category of PIM was benzodiazepines (accounting for 16.6% of the total PIMs identified), followed by nonbenzodiazepine hypnotics (15.2%), antidepressants (15.2%), and first-generation antihistamines (10.5%). Compared to older drivers on four or fewer medications, the adjusted ORs of PIM use were 2.43 (95% CI 1.68–3.51) for those on 5–7 medications, 4.19 (95% CI 2.95–5.93) for those on 8–11 medications, and 8.01 (95% CI 5.71–11.23) for those on ≥12 medications. Older drivers who were female, white, or living in urban areas were at significantly heightened risk of PIM use.

Conclusion

About one in five older drivers uses PIMs. Commonly used PIMs are medications known to impair driving ability and increase crash risk. Implementation of evidence-based interventions to reduce PIM use in older drivers may confer both health and safety benefits.

Trial registration

Not applicable.

Relationship Between Physical Activity and Motor Vehicle Crashes Among Older Adult Drivers

Background: There are approximately 42 million licensed drivers aged 65 years or older in the United States, who face unique age-related risks while driving. While physical activity affects several chronic conditions thought to be associated with motor vehicle crashes (MVCs), it is unclear if increased physical activity leads to fewer MVCs. This study explores whether self-reported vigorous and moderate physical activity is associated with MVCs in the previous year. Methods: Using cross-sectional data from the LongROAD study, a large multisite prospective cohort study of 2990 older adult drivers, we examined variables related to physical activity and performed a multivariate regression analysis to examine the association of physical activity health behaviors with self-reported MVCs. Results: Overall, 41.2% of participants reported vigorous and 69.6% of participants reported moderate exercise at least once per week. Eleven percent of participants reported at least 1 MVC in the previous year. Neither vigorous nor moderate physical activity was significantly associated with self-reported MVCs in the previous year. Select variables that were significantly associated with self-reported MVC included self-reported unsafe driving practices (odds ratio [OR] 1.55, confidence interval [CI] 1.05-2.29), and fall in the past 12 months (OR 1.46, CI 1.14-1.85). Conclusions: We were unable to detect a significant association between self-reported physical activity and MVCs in the past year among this group of older drivers. Use of objective measures of activity may better clarify this relationship.

Physician and Family Discussions about Driving Safety: Findings from the LongROAD Study

BACKGROUND

Older adult drivers may experience decreases in driving safety with age or health status change. Discussing driving safety may help them plan for driving restriction and eventual cessation. Here, we sought to examine conversations between older adults and their family members and physicians.

METHODS

In this multi-site cross-sectional analysis of baseline data from the AAA Longitudinal Research on Aging Drivers (LongROAD) cohort study, we measured the prevalence and characteristics of family and physician driving discussions. We examined associations between having driving discussions and participant characteristics using multivariate logistic regression.

RESULTS

Of 2990 current drivers aged 65 to 79 years (53% female, 85.5% White), only 14.2% reported discussing driving safety with family and 5.5% had discussions with physicians. Men (adjusted OR, 1.32; 95% CI, 1.05 to 1.66) and those with Master's degrees or higher (adjusted OR, 1.65; 95% CI, 1.27 to 2.13) more often had family discussions. Those with at least a Master's degree were also more likely to speak with their physician (adjusted OR, 1.77; 95% CI, 1.17 to 2.68).

CONCLUSION

Few older adults had driving safety conversations with their family or physicians. Practical and effective interventions are needed to engage family and physicians in assisting older adults with risk assessment and driving cessation planning to maintain mobility and well-being.

Patterns of Self-Reported Driving While Intoxicated Among Older Adults

Objective: This study examines the prevalence of self-reported driving while intoxicated (DWI) among drivers aged 65 and older. Method: This cross-sectional study was based on baseline data from the AAA Longitudinal Research on Aging Drivers (LongROAD) study, a multisite prospective cohort study of 2,990 older adult drivers. Alcohol-related variables from the baseline questionnaire were examined in relation to demographics, health status, and driving behaviors. A logistic regression model assessed variables associated with DWI. Results: Of the 2,990 participants, 72.7% reported consuming alcohol, 15.0% reported high-risk drinking, and 3.3% reported DWI. High-risk drinking (OR = 12.01) and risky driving behaviors (OR = 13.34) were significantly associated with at least occasional DWI. Avoidance of hazardous driving conditions (OR = 0.71) and higher level of comfort during challenging driving scenarios (OR = 0.65) were less likely to be associated with DWI. Conclusion: A large number of older adults engage in high-risk drinking and DWI. Public health education and DWI-related interventions should include older adults.

Importance of Driving and Potential Impact of Driving Cessation for Rural and Urban Older Adults

PURPOSE

Analyses compared older drivers from urban, suburban, and rural areas on perceived importance of continuing to drive and potential impact that driving cessation would have on what they want and need to do.

METHODS

The AAA LongROAD Study is a prospective study of driving behaviors, patterns, and outcomes of older adults. A cohort of 2,990 women and men 65-79 years of age was recruited during 2015-2017 from health systems or primary care practices near 5 study sites in different parts of the United States. Participants were classified as living in urban, surburban, or rural areas and were asked to rate the importance of driving and potential impact of driving cessation. Logistic regression models adjusted for sociodemographic and driving-related characteristics.

FINDINGS

The percentages of older drivers rating driving as "completely important" were 76.9%, 79.0%, and 83.8% for urban, suburban, and rural drivers, respectively (P = .009). The rural drivers were also most likely to indicate driving cessation would have a high impact on what they want or need to do (P < .001). After adjustment for sociodemographic and driving-related characteristics, there was a 2-fold difference for rural versus urban older drivers in odds that driving cessation would have a high impact on what they need to do (OR = 2.03; 95% CI: 1.60-2.58).

CONCLUSIONS

Older drivers from rural areas were more likely to rate driving as highly important and the prospect of driving cessation as very impactful. Strategies to enhance both the ability to drive safely and the accessibility of alternative sources of transportation may be especially important for older rural adults.

Improving Safe Mobility: An Assessment of Vehicles and Technologies among a Large Cohort of Older Drivers

Evidence suggests that older driver safety may be improved by good vehicle maintenance, in-vehicle advanced technologies, and proper vehicle adaptations. This study explored the prevalence of several measures of vehicle maintenance and damage among older drivers through inspection of their vehicles. We also investigated the prevalence of in-vehicle technologies and aftermarket adaptations. Vehicle inspections were conducted by trained research staff using an objective, standardized procedure. This procedure, developed by a multidisciplinary team of researchers, was based on a review of inspection checklists used by automobile dealerships and the project team's expertise. The study used baseline data from vehicles of 2988 participants in the multi-site Longitudinal Research on Aging Drivers (LongROAD) study. Among this cohort, vehicles were well maintained, had little damage, and contained a range of advanced technologies but few aftermarket adaptations. Implications of study findings for occupational therapy practice are discussed.

A 2.5-Year Longitudinal Assessment of Naturalistic Driving in Preclinical Alzheimer's Disease

BACKGROUND

Emerging evidence shows that cognitively normal older adults with preclinical Alzheimer's disease (AD) make more errors and are more likely to receive a marginal/fail rating on a standardized road test compared to older adults without preclinical AD, but the extent to which preclinical AD impacts everyday driving behavior is unknown.

OBJECTIVE

To examine self-reported and naturalistic longitudinal driving behavior among persons with and without preclinical AD.

METHOD

We prospectively followed cognitively normal drivers (aged 65 + years) with (n = 10) and without preclinical AD (n = 10) for 2.5 years. Preclinical AD was assessed using amyloid positron emission tomography (PET) with Pittsburgh Compound B. The Driving Habits Questionnaire assessed self-reported driving outcomes. Naturalistic driving was captured using a commercial GPS data logger plugged into the on-board diagnostics II port of each participant's vehicle. Data were sampled every 30 seconds and all instances of speeding, hard braking, and sudden acceleration were recorded.

RESULTS

Preclinical AD participants went to fewer places/unique destinations, traveled fewer days, and took fewer trips than participants without preclinical AD. The preclinical AD group reported a smaller driving space, greater dependence on other drivers, and more difficulty driving due to vision difficulties. Persons with preclinical AD had fewer trips with any aggression and showed a greater decline across the 2.5-year follow-up period in the number of days driving per month and the number of trips between 1-5 miles.

CONCLUSION

Changes in driving occur even during the preclinical stage of AD.

Self-reported health conditions and related driving reduction in older drivers

We surveyed self-reported lifetime health conditions (using National Health and Aging Trends Study questions) and related driving reduction in a large multi-site older driver cohort (n = 2990) from the AAA Longitudinal Research on Aging Drivers (LongROAD) Study's baseline assessment. Those reporting reduced driving (n = 337) largely attributed reduction to musculoskeletal (29%), neurologic (13%), and ophthalmologic (10%) conditions. Women reported health condition-related driving reduction more often than men (14% versus 8%, p<.001). Mobility affects well-being; health professionals should consider that health conditions may cause older adults to reduce driving. Gender differences deserve attention in future research and education efforts.

Louis R, Zanier N, Ryan L, LeBlanc D, Smith J, Yung R, Nyquist L, DiGuiseppi C, Li G, Mielenz T, Strogatz D. The effects of demographics, functioning, and perceptions on the relationship between self-reported and objective measures of driving exposure and patterns among older adults

The exploratory study reported here was intended to examine: how strongly subjectively reported driving avoidance behaviors (commonly referred to as self-regulation) and exposure were related to their objectively measured counterparts and whether it depended on the specific behavior; the extent to which gender and age play a role in the association between subjectively reported driving avoidance behaviors and exposure and their objectively measured counterparts; and the extent to which demographics, health and functioning, driving-related perceptions, and cognition influence the association between subjective and objective driving avoidance behaviors overall. The study used data from the Longitudinal Research on Aging Drivers (LongROAD) study, a multisite, prospective cohort study designed to generate empirical data for understanding the role of medical, behavioral, environmental, and technological factors in driving safety during the process of aging. Objective driving measures were derived from GPS/datalogger data from 2131 LongROAD participants' vehicles. The corresponding subjective measures came from a comprehensive questionnaire administered to participants at baseline that asked them to report on their driving exposure, patterns, and other aspects of driving. Several other variables used in the analyses came from the comprehensive questionnaire and an inperson clinical assessment administered to participants at baseline. A series of simple linear and logistic models were fitted to examine the relationship between the subjective and objective driving measures of interest, and a multivariable analysis was conducted to examine the potential role of selected factors in the relationship between objective and subjective driving avoidance behaviors. Results of the models are presented and overall findings are discussed within the context of the existing research literature.

Prevalence, attitudes, and knowledge of in-vehicle technologies and vehicle adaptations among older drivers

The purpose of the present study was to gain a better understanding of the types of in-vehicle technologies being used by older drivers as well as older drivers' use, learning, and perceptions of safety related to these technologies among a large cohort of older drivers at multiple sites in the United States. A secondary purpose was to explore the prevalence of aftermarket vehicle adaptations and how older adults go about making adaptations and how they learn to use them. The study utilized baseline questionnaire data from 2990 participants from the Longitudinal Research on Aging Drivers (LongROAD) study. Fifteen in-vehicle technologies and 12 aftermarket vehicle adaptations were investigated. Overall, 57.2% of participants had at least one advanced technology in their primary vehicle. The number of technologies in a vehicle was significantly related to being male, having a higher income, and having a higher education level. The majority of respondents learned to use these technologies on their own, with "figured-it-out-myself" being reported by 25%-75% of respondents across the technologies. Overall, technologies were always used about 43% of the time, with wide variability among the technologies. Across all technologies, nearly 70% of respondents who had these technologies believed that they made them a safer driver. With regard to vehicle adaptations, less than 9% of respondents had at least one vehicle adaptation present, with the number of adaptations per vehicle ranging from 0 to 4. A large majority did not work with a professional to make or learn about the aftermarket vehicle adaptation.