Older Drivers Research Articles

Driving competence in older age: psychological assessment and interventions

The article introduces the issue of psychological assessment and training for driving safety, driving competence, and the mobility of older drivers. The psychological methods for assessing driving competence and the training approaches for maintaining mobility in old age are outlined and illustrated with examples. Preserving driving ability in old age remains atask for which development needs and research gaps must be specified. Although periodic mandatory examinations based on age do not yield any relevant improvement in enhancing traffic safety, they do not cause harm and are widely accepted. It is desirable to move away from atheory focusing on deficits of older age and instead develop an assessment of the comprehensive functions, abilities, and resources of elderly drivers to help preserve the mobility and participation of that specific demographic in traffic.

Identification of Risk Factors for Severe Younger and Older Driver Crashes in Massachusetts

Systemic safety analysis is a comprehensive and proactive approach to identifying and addressing high-risk roadway features and crash types that contribute to severe crashes. The Massachusetts Department of Transportation identified 14 emphasis areas for systemic improvement, including younger and older driver crashes. Research was undertaken to conduct separate comprehensive analyses of fatal and serious injury crashes involving younger and older drivers, using a systemic safety approach to develop risk factors and identify critical locations within the state. The study utilized crash, roadway, driver’s license, citation, healthy aging, and environmental justice data from various sources. Negative binomial regression models were developed to relate crash frequency with town-specific traffic, behavior, and site characteristics, considering exposure and spatial variance. The findings highlighted the significance of multiple risk factors contributing to severe crash frequency. For younger drivers, the presence of young drivers in the town, risk-taking behaviors such as unbelted and impaired driving, and infrastructure characteristics, particularly high-speed facilities and historically underinvested infrastructure, were key contributors to crash frequency. Older drivers’ crash frequency was influenced by the presence of older drivers, healthy aging indicators, risk-taking behaviors, and high-speed facilities. Based on the model results, risk scores were developed for each variable in the model and applied to each town. Towns were ranked using percentile ranking to classify them into primary and secondary risk categories. The towns identified in the primary risk category (18 towns in the top 5 percentiles) captured approximately 13.5% of severe younger driver crashes and 14.5% of severe older driver crashes.

Enhancing road safety: In-vehicle sensor analysis of cognitive impairment in older drivers

Enhancing road safety: In-vehicle sensor analysis of cognitive impairment in older drivers

Does exposure to online content encouraging illegal driving influence behaviour? Exploring perspectives of different age groups

A substantial amount of online content on illegal driving behaviours is shared on social media platforms. Yet, the influence of online content on behaviours remains unclear. Accordingly, this qualitative study explored perspectives across different age groups on a) the nature and extent of social media content that encourages illegal driving behaviours and b) whether such content influences engagement in these behaviours. Sixty-six licenced drivers within Queensland, Australia, participated in a focus group. The sessions were conducted with three different age groups: younger drivers (17–25 years), middle-aged drivers (26–49 years), and older drivers (50 + years). Data was analysed using reflexive thematic analysis, resulting in three recognised themes: 1) exposure to online illegal driving behaviours on social media, 2) the influence of online illegal driving content on behaviour, and 3) drivers’ engagement with online content that encourages illegal driving behaviours. A key finding was that young drivers are frequently exposed to online content encouraging illegal driving behaviours, whereas middle-aged and older drivers are rarely exposed to this content. Opinions surrounding the influence of online content on illegal driving behaviours was varied, yet across ages it was believed that young drivers may be most susceptible to this content. The findings from this study provide support for the potential link between social media exposure and illegal driving behaviours. Implications for future research are discussed, with an emphasis on longitudinal research to examine the impact of social media content on changes in behaviour, specifically for younger drivers.

Analysis of driving left-turn errors of young and older drivers at urban intersections

Numerous traffic crashes occur at intersections in urban areas. Understanding the mechanism of driving errors at intersections and providing effective solutions will significantly reduce traffic injuries. The objective of this study is to examine the age and hazard level’s effects on driver left-turn errors at urban intersections. In order to achieve this goal, this study customized the cognitive reliability and error analysis method (CREAM) for left-turn driving task at intersections, and driver error profiles were investigated using a driving simulation experiment as a case study. The results showed that age did not significantly affect drivers’ left turn error probability, while the error probability of both groups of drivers increased with the hazard level. Drivers were most likely to have inadequate monitoring and misjudgment in left-turn maneuvers, more so in the older group. Young drivers were more likely to make planning, decision-making, and adjustment errors compared to older drivers. In addition, observation errors were the most likely cognitive (74.5%). This study achieves the common and characteristic performance of human errors under the three hazardous intersections for the two age groups, and provides a basis for the design of effective training modules and driver assistance systems.

Transferability of Effective Consultation Skills for Decision-Making Support in the Voluntary Surrender of Older Adult Drivers' Licences in Super-Aged Japan.

Previously, we identified eight effective consultation skills to support decision-making in the voluntary surrender of older adult drivers' licences in super-aged Japan. This study aimed to clarify the transferability of these skills. We collected text data by interviewing 11 safe-driving counsellors (four police officers, four clerical staff and three nurses) in the License Division of the National Police Agency from February to March 2022. Interviews were semi-structured and conducted by telephone or email. During the interview, participants were asked to recall their experiences as counsellors providing decision-making support to older drivers and to compare their experiences with the eight consultation skills. We analysed the content of the responses by quantitative text analysis with KH Coder 3 software. As a characteristic of the words and phrases used by counsellors in their narratives about consultation skills, the most frequently extracted words from among 3147 words were think, parties and family, and promote had the highest mediation centrality. The eight subgraphs were 'Respecting the will of relevant parties from their standpoint is natural', 'Listening attentively and empathetically to relevant parties is effective', 'Presenting objective data to guide decisions is successful', 'Showing cognitive functioning test results is often effective', 'Counselors with medical expertise can elicit positive counseling outcomes', 'Intervention by medical or police counselors facilitates the decision to surrender voluntarily', 'Counseling skills need to be improved' and 'A diagram of the 8 skills is helpful for inexperienced counselors'. The results suggest that the eight consultation skills have similarities and are transferable. This transferability might contribute to practical application or cohort follow-up study research. These skills can be incorporated into counsellor training, and counsellors can be expected to use these skills in the future. Regardless of the safe-driving counsellor's years of experience, the skills can help them provide uniform and accurate support in decision-making regarding the voluntary surrender of older adult drivers' licences. These skills are a promising approach to help older adults lead safe and secure lives as they age.

High-speed train drivers’ human error under fatigue and stress: the role of situation awareness and individual differences

Fatigue and stress are critical variables that impair railway train drivers’ safety performance, and individual differences may influence these effects. This study investigates how fatigue and stress affect high-speed train drivers’ human error and the role of individual differences. We hypothesised that situation awareness (SA) mediates the effects of fatigue and stress on human error, and individual differences (age and work experience) moderate these effects. We surveyed 1,391 male drivers from eight Chinese railway bureaus and used PROCESS Macro for data analysis. The results revealed that fatigue and stress increased human error, directly and indirectly through SA. Age and work experience moderated the effect of fatigue and stress on SA, respectively. Older drivers had better SA under high fatigue, while more experienced drivers had better SA under high stress. These findings can inform more tailored safety management strategies to lower human error and enhance the safety of high-speed train operations.

Visual Function and Driving Performance Under Different Lighting Conditions in Older Drivers: Preliminary Results From an Observational Study.

Age-related vision changes significantly contribute to fatal crashes at night among older drivers. However, the effects of lighting conditions on age-related vision changes and associated driving performance remain unclear. This pilot study examined the associations between visual function and driving performance assessed by a high-fidelity driving simulator among drivers 60 and older across 3 lighting conditions: daytime (photopic), nighttime (mesopic), and nighttime with glare. Active drivers aged 60 years or older participated in visual function assessments and simulated driving on a high-fidelity driving simulator. Visual acuity (VA), contrast sensitivity function (CSF), and visual field map (VFM) were measured using quantitative VA, quantitative CSF, and quantitative VFM procedures under photopic and mesopic conditions. VA and CSF were also obtained in the presence of glare in the mesopic condition. Two summary metrics, the area under the log CSF (AULCSF) and volume under the surface of VFM (VUSVFM), quantified CSF and VFM. Driving performance measures (average speed, SD of speed [SDspeed], SD of lane position (SDLP), and reaction time) were assessed under daytime, nighttime, and nighttime with glare conditions. Pearson correlations determined the associations between visual function and driving performance across the 3 lighting conditions. Of the 20 drivers included, the average age was 70.3 years; 55% were male. Poor photopic VA was significantly correlated with greater SDspeed (r=0.26; P<.001) and greater SDLP (r=0.31; P<.001). Poor photopic AULCSF was correlated with greater SDLP (r=-0.22; P=.01). Poor mesopic VUSFVM was significantly correlated with slower average speed (r=-0.24; P=.007), larger SDspeed (r=-0.19; P=.04), greater SDLP (r=-0.22; P=.007), and longer reaction times (r=-0.22; P=.04) while driving at night. For functional vision in the mesopic condition with glare, poor VA was significantly correlated with longer reaction times (r=0.21; P=.046) while driving at night with glare; poor AULCSF was significantly correlated with slower speed (r=-0.32; P<.001), greater SDLP (r=-0.26; P=.001) and longer reaction times (r=-0.2; P=.04) while driving at night with glare. No other significant correlations were observed between visual function and driving performance under the same lighting conditions. Visual functions differentially affect driving performance in different lighting conditions among older drivers, with more substantial impacts on driving during nighttime, especially in glare. Additional research with larger sample sizes is needed to confirm these results.

Different deployments of attentional breadth selectively predict UFOV task performance in older adults

The Useful Field of View task (UFOV) is a strong and reliable predictor of crash risk in older drivers. However, while the functional domain of attention is clearly implicated in UFOV performance, the potential role of one specific attentional process remains unclear: attentional breadth (the spatial extent of the attended region around the point of visual fixation). The goal of the present study was to systematically test the role of two distinct aspects of attentional breadth, maintaining a specific breadth of attention and resizing the attended region, in UFOV performance. To this end, 135 older adults completed the UFOV and modified Navon tasks to measure their efficiency in maintaining, contracting, and expanding the breadth of attention. We then examined individual-difference associations between these aspects of attentional breadth deployment and UFOV performance. We found that performance on UFOV Subtask 2 was associated with efficient contraction of attentional breadth (i.e., resizing the attended region to a smaller area), while Subtask 3 performance was associated with the efficiency of expanding attentional breadth (i.e., resizing the attended region to a larger area). The selectivity of these relationships appears to implicate these specific deployments of attentional breadth in how people complete the task, as it suggests that these relationships are not simply attributable to shared variance in a broader domain of cognitive functioning. The implications of these results for our understanding of UFOV, as well as future research directions that test the relative contributions of different cognitive processes in predicting task performance, are discussed.

Predicting Driving Cessation Among Cognitively Normal Older Drivers: The Role of Alzheimer Disease Biomarkers and Clinical Assessments.

With the aging US population and increasing incidence of Alzheimer disease (AD), understanding factors contributing to driving cessation among older adults is crucial for clinicians. Driving is integral for maintaining independence and functional mobility, but the risk factors for driving cessation, particularly in the context of normal aging and preclinical AD, are not well understood. We studied a well-characterized community cohort to examine factors associated with driving cessation. This prospective, longitudinal observation study enrolled participants from the Knight Alzheimer Disease Research Center and The DRIVES Project. Participants were enrolled if they were aged 65 years or older, drove weekly, and were cognitively normal (Clinical Dementia Rating [CDR] = 0) at baseline. Participants underwent annual clinical, neurologic, and neuropsychological assessments, including β-amyloid PET imaging and CSF (Aβ42, total tau [t-Tau], and phosphorylated tau [p-Tau]) collection every 2-3 years. The primary outcome was time from baseline visit to driving cessation, accounting for death as a competing risk. The cumulative incidence function of driving cessation was estimated for each biomarker. The Fine and Gray subdistribution hazard model was used to examine the association between time to driving cessation and biomarkers adjusting for clinical and demographic covariates. Among the 283 participants included in this study, there was a mean follow-up of 5.62 years. Driving cessation (8%) was associated with older age, female sex, progression to symptomatic AD (CDR ≥0.5), and poorer performance on a preclinical Alzheimer cognitive composite (PACC) score. Aβ PET imaging did not independently predict driving cessation, whereas CSF biomarkers, specifically t-Tau/Aβ42 (hazard ratio [HR] 2.82, 95% CI 1.23-6.44, p = 0.014) and p-Tau/Aβ42 (HR 2.91, 95% CI 1.28-6.59, p = 0.012) ratios, were independent predictors in the simple model adjusting for age, education, and sex. However, in the full model, progression to cognitive impairment based on the CDR and PACC score across each model was associated with a higher risk of driving cessation, whereas AD biomarkers were not statistically significant. Female sex, CDR progression, and neuropsychological measures of cognitive functioning obtained in the clinic were strongly associated with future driving cessation. The results emphasize the need for early planning and conversations about driving retirement in the context of cognitive decline and the immense value of clinical measures in determining functional outcomes.

Impact of cognitive impairment on driving behaviour and route choices of older drivers: a real-world driving study

Maintaining driving independence is important for older adults. However, cognitive decline, a common issue in older populations, can impair older adults’ driving abilities and overall safety on the roads. This study explores how cognitive impairment influences driving patterns and driving choices among older adults. We analyzed real-world driving patterns of 246 older adults using GPS dataloggers. Our sample included 230 cognitively normal older adults (CN; Clinical Dementia RatingR\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^R$$\\end{document} [CDR] = 0) and 16 older adults with incident cognitive impairment (ICI; CDR = 0.5). The CN group had an average age of 68.2 years, with 46% females and an average of 16.5 years of education, while the ICI group’s average age was 69.2 years, with 36% females and an average of 16.0 years of education. We employed spatial clustering and hashing algorithms to evaluate driving behaviours. Significant differences emerged: The ICI group used fewer distinct routes to their most common destination. These differences can be leveraged to develop driving as a digital biomarker for the early detection and continuous monitoring of cognitive impairment.

Changes in older drivers’ risky driving behavior over time: Insights from a naturalistic study

This study aimed to investigate changes in the risky driving behavior of older drivers with age using naturalistic driving data. The driving behaviors of 44 drivers aged 60 years or older at baseline were tracked for two to five years. Harsh events characterized by elevated g-forces were used as driving outcomes. A multilevel modeling approach was used to examine (1) the heterogeneity in individual trajectories of risky driving behaviors and (2) the factors associated with the average risky driving behavior over the study period and changes in risky driving behavior over time. The results indicated that there was heterogeneity in individual trajectories of risky driving behaviors. Older female drivers and a higher level of sensation seeking (i.e., the tendency to pursue new and different sensations, feelings, and experiences) were associated with higher rates of harsh events over the study period. A reduction in driving exposure was associated with an increase in harsh event rates, and driving exposure can partly explain the sex difference in risky driving behaviors. The cluster analysis indicated that the heterogeneity in individual trajectories of risky driving behaviors can be explained by the presence of three subgroups of drivers, with each group exhibiting specific trajectories. Initial levels of risky driving behaviors were much more important than time slopes in identifying subgroups of drivers, indicating that differences between drivers existed early and remained relatively consistent over the study period. A multinomial logistic regression was used to examine the predictors of class membership identified by the clustering algorithm, and the findings were similar to those from the multilevel regression analysis. The findings of this study enhance our understanding of how older drivers’ risky driving behaviors change with age and indicate the distinctive individual processes of change in driving behaviors with age.

Somatic Factors Predict On-Road Driving Skills in Older Drivers and Drivers with Mild Cognitive Impairment.

On-road driving skills can be impaired in older drivers and drivers with mild cognitive impairment (MCI) due to different driving-relevant deficits. Among these deficits, somatic factors have received little attention so far. In a prospective observational on-road driving study, we examined whether somatic factors can predict on-road driving skills in a mixed sample of healthy older drivers and drivers with MCI (n = 99) and whether the inclusion of age explains additional variance. Somatic factors included the number of prescribed drugs, visual acuity, peripheral visual field integrity, mobility of the cervical spine, and hearing impairment. A hierarchical regression analysis was used to predict on-road driving skills by adding the somatic factors in the first step and age in the second step. Results revealed that the combination of somatic factors significantly predicted on-road driving skills (R2adjusted = 0.439). The inclusion of age led to a significant increase of explained variance (R2adjusted = 0.466). Our results suggest that somatic factors can accurately predict on-road driving skills in healthy older drivers and drivers with MCI. In addition, our results suggest that there is a significant but rather small effect of age beyond somatic changes.

Cultural implications on driver behaviour and road safety: insights from Kano State, Nigeria

This study investigates the cultural implications of driver behaviour and its impact on road safety through the lens of Driver Behaviour Questionnaire (DBQ). The survey includes 741 drivers aged 18 and above from Kano State, Nigeria. Our analysis identifies a three-factor model: Violations, Errors, and Aggressive Violations. The study compares these findings with two others from different regions and state in Nigeria, revealing significant differences in driver behaviour, thereby highlighting the influence of cultural factors. Our analysis finds significant correlations between driver demographics and risky behaviours, with older drivers showing a higher risk of crashes. This indicates the importance of tailored road safety measures for different demographics. Efforts to curb risky behaviours encompass a multi-faceted approach. Improvements in road infrastructure, including lane expansion and pedestrian-friendly designs, foster safety while discouraging violations. Addressing factors like hawking and trading on roads is paramount to maintain driver focus. Furthermore, investment in comprehensive driver education, awareness campaigns, and advanced training programs is vital to reduce errors and aggressive driving behaviours. Recognising the cultural differences that influence driver behaviour in Nigeria is vital for creating a safer and more respectful traffic environment. Interventions tailored to specific cultural contexts are likely to be more effective than one-size-fits-all approaches. In conclusion, this study advocates for a holistic approach, integrating law enforcement, infrastructure enhancements, and driver education campaigns, to mitigate risky behaviours among drivers and enhance road safety.

Metacognitive Awareness of Older Adult Drivers with Mild Cognitive Impairment: Relationships with Demographics, Subjective Evaluation of Cognition, and Driving Self-Efficacy.

(1) Self-regulation of driving is a means of maintaining one's driving identity. The purpose of this study was to investigate the extent to which older drivers with Mild Cognitive Impairment (MCI) are metacognitively aware of the requirements of specific demanding driving conditions and whether this awareness is linked to subjective assessments of cognition. (2) One hundred seventeen (117) older MCI drivers participated in a telephone survey in which they reported their metacognitive experiences in nine driving conditions, listed as an aim of self-regulation. The analyses included the participants' subjective cognitive assessments, both in terms of their cognitive state and their perceived driving self-efficacy. (3) The analyses pointed out a direct and negative effect of age on the formation of the metacognitive feeling of certainty. Furthermore, an indirect effect of sex through driving self-efficacy was established. This effect was negative in the case of the metacognitive feeling of difficulty and the estimation of effort and positive in the case of the metacognitive feeling of certainty. (4) This position points out the need to establish appropriate levels of the perceived self-efficacy of older drivers with MCI, and it raises issues when it moves to fictitious levels.

Investigating older driver crashes on high-speed roadway segments: a hybrid approach with extreme gradient boosting and random parameter model

Older drivers are often more susceptible to crashes due to age-related physical and cognitive limitations, particularly in complex driving environments. Considering the limited research in this area, this study focuses on investigating crashes involving older drivers on high-speed roadways (≥ 45 mph). The analysis is based on data collected from Louisiana State, encompassing 18,300 older driver-involved crashes (2017-2021). For analysis, a two-step hybrid modelling approach is employed: a) Extreme Gradient Boosting (XGBoost) is used to classify top variable features and b) Correlated Random Parameter Ordered Probit with Heterogeneity in Means (CRPOP-HM) is used to predict the likelihood of crash injury severity. . Some of the critical factors increasing the likelihood of fatal-severe or injury crashes involving older drivers on high-speed segments include the manner of collision (rear-end, right-angle, single-vehicle), primary contributing factor (violation, pedestrian action), presence of passenger (s), location type (open country, residential, business with mixed residential), and weekend.

Revisiting Older Drivers' Risks of At-fault Motor Vehicle Collisions in Japan.

In Japan, older drivers have been encouraged to surrender their driving licenses for traffic safety, despite the potential adverse social and health outcomes of driving cessation. We reconsidered such policies and social pressure by comparing the risk of at-fault motor vehicle collisions (MVCs) across the age groups of drivers. Using the national data of police-reported MVCs that occurred between 2016 and 2020, we examined the number of at-fault MVCs per licensed driver (MVC rate) and the number of fatally and non-fatally injured persons per at-fault MVC by the sex and age groups of at-fault drivers. The MVC rate of older drivers was higher than that of middle-aged drivers but lower than that of young drivers. The number of injured persons among the collided counterparts (collided car occupants, motorcyclists, bicyclists, and pedestrians) per MVC caused by older drivers was not greater than that by drivers in other age groups. In fatal MVCs caused by older drivers, drivers themselves or their passengers tend to be killed rather than their collided counterparts. Overall, the results were mostly consistent between male and female drivers. The risk of at-fault MVCs increased with the advancing age of drivers after middle age; however, this risk among older drivers did not exceed that among young drivers, without posing a high risk of injuries to their collided counterparts.

Diabetes mellitus and hard braking events in older adult drivers

BackgroundDiabetes 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.MethodsData 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.ResultsOf 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).ConclusionOlder 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.

Fit2Drive: Screening Older Drivers with Cognitive Concerns

ObjectivesThe purpose of this study was to identify the most parsimonious combination of cognitive tests that accurately predicts the likelihood of passing an on-road driving evaluation in order to develop a screening measure that can be administered as an in-office test. DesignThis was a psychometric study of the new test's diagnostic accuracy. Settings and ParticipantsThe study was conducted at the Florida Atlantic University's Memory Center and Clinical Research Unit, both easily accessible to older drivers. Participants were older drivers who received a driving evaluation at the Memory Center and agreed to have their results included in the Driving Repository and community-based older drivers who volunteered to participate. MethodsMini-Mental State Exam (MMSE), Trail Making Tests A and B, Clock Test, Hopkins Verbal Learning Test, and Driving Health Inventory results were compared with an on-road driving evaluation to identify those tests that best predict the ability to pass the on-road evaluation. ResultsAltogether, 412 older drivers, 179 men and 233 women, were included in the analysis. Fifty-four percent of Driving Repository participants failed the on-road evaluation compared with 8% of the community sample. The highest correlation to the on-road evaluation was Trails B time in seconds r = −0.713 (P < .001). Variables with high multicollinearity and/or low correlation with the on-road evaluation were eliminated and sets of receiver operating characteristics curves were generated to assess the predictive accuracy of the remaining tests. A linear combination of Trails B in seconds and MMSE using the highest of the Serial 7s or WORLD spelled backward scores accounted for the highest area under the curve of 0.915. Finally, an algorithm was created to rapidly generate the prediction for an individual patient. Conclusions and ImplicationsThe Fit2Drive algorithm demonstrated a strong 91.5% predictive accuracy. Usefulness in office-based patient consultations is promising but remains to be rigorously tested.

Social and Environmental Characteristics Associated With Older Drivers' Use of Non-driving Transportation Modes.

Objective: We examined associations between older drivers' social and environmental characteristics and odds of using non-driving transportation modes. Methods: Using 2015 National Health and Aging Trends Study data for community-dwelling drivers (n = 5102), we estimated logistic regression models of associations between social characteristics, environmental characteristics, and odds of using non-driving transportation modes three years later. Results: Drivers had 20% increase in odds of getting rides three years later for each additional confidante (adjusted odds ratio [aOR] = 1.20, 95% confidence interval [CI]: 1.11-1.30). Drivers living in more walkable neighborhoods were more likely to walk to get places (National Walkability Index [NWI] score of 18 vs. 2 aOR = 1.71, 95% CI: 1.02-2.90) and take public transit three years later (NWI 18 vs. 2 aOR = 7.47, 95% CI: 1.69-33.0). Discussion: Identifying modifiable social and environmental characteristics can inform future interventions supporting older adults' health during the transition to non-driving.