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

BACKGROUND: For some older persons, driving is essential to maintain their daily activities and engagement with society. Unfortunately, some will have to stop driving, as they age. Driving-cessation is an important transition for older persons and caregivers, well known to cause significant challenges and consequences. This study aimed to describe the experience of older persons and caregivers in the transition from driving to ceasing to drive. METHODS: Within a descriptive qualitative design, semi-structured interviews were undertaken with older persons (n = 8) and caregivers (n = 6) from the city of Québec (Quebec, Canada), from November 2020 to March 2021. Using an inductive approach, the qualitative data was analyzed with the content analysis method. RESULTS: Some older persons had never thought they might someday lose their driver's license. The process of legislative assessment was unknown by almost all older persons and caregivers. The process was therefore very stressful for the research participants. Driving-cessation is a difficult transition that is associated with loss of independence, freedom, spontaneity, and autonomy. Qualitative analysis of data showed different factors that positively or negatively influence the experience of ceasing to drive, such as the older person's ownership of the decision, the presence of a network of friends and family, and self-criticism. There was significant impact related to driving-cessation for caregivers, such as assuming the entire burden of travel, psychologically supporting older persons in their grief, and navigating the driver's licensing system. CONCLUSIONS: These study results could help organizations and healthcare professionals to better accompany and support older drivers and caregivers in the transition from driving to driving-cessation. TRIAL REGISTRATION: None.

Study protocol for "In-vehicle sensors to detect changes in cognition of older drivers".

BACKGROUND: Driving is a complex behavior that may be affected by early changes in the cognition of older individuals. Early changes in driving behavior may include driving more slowly, making fewer and shorter trips, and errors related to inadequate anticipation of situations. Sensor systems installed in older drivers' vehicles may detect these changes and may generate early warnings of possible changes in cognition. METHOD: A naturalistic longitudinal design is employed to obtain continuous information on driving behavior that will be compared with the results of extensive cognitive testing conducted every 3 months for 3 years. A driver facing camera, forward facing camera, and telematics unit are installed in the vehicle and data downloaded every 3 months when the cognitive tests are administered. RESULTS: Data processing and analysis will proceed through a series of steps including data normalization, adding information on external factors (weather, traffic conditions), and identifying critical features (variables). Traditional prediction modeling results will be compared with Recurring Neural Network (RNN) approach to produce Driver Behavior Indices (DBIs), and algorithms to classify drivers within age, gender, ethnic group membership, and other potential group characteristics. CONCLUSION: It is well established that individuals with progressive dementias are eventually unable to drive safely, yet many remain unaware of their cognitive decrements. Current screening and evaluation services can test only a small number of individuals with cognitive concerns, missing many who need to know if they require treatment. Given the increasing number of sensors being installed in passenger vehicles and pick-up trucks and their increasing acceptability, reconfigured in-vehicle sensing systems could provide widespread, low-cost early warnings of cognitive decline to the large number of older drivers on the road in the U.S. The proposed testing and evaluation of a readily and rapidly available, unobtrusive in-vehicle sensing system could provide the first step toward future widespread, low-cost early warnings of cognitive change for this large number of older drivers in the U.S. and elsewhere.

Determinants of driving among oldest-old Australian women.

This study examined predictors of driving among oldest-old Australian women in their late 80s in accordance with the World Health Organization's healthy aging framework. The study used data from the 1921-26 cohort of the Australian Longitudinal Study on Women's Health, wave-6 (n = 4025). The result of the multivariable logistic regression showed providing care, living alone, volunteering, living in rural/outer regional Australia, having higher educational attainment, and social interactions were associated with driving. The findings indicate driving should not be dismissed based on age alone. Policymakers need to also consider social roles, driving environment and context with the goals of healthy aging.

Predicting the Coping Skills of Older Drivers in the Face of Unexpected Situation.

In recent years, when an older driver who cannot immediately recognize, judge, and operate properly faces an unexpected situation, they often panic, which may cause a traffic accident. However, there has not yet been enough discussion about the coping skills of older drivers in the face of this unexpected situation. Therefore, this study discusses the coping skills of older drivers in the face of unexpected situations. Moreover, we propose a coping skills prediction system (CP system). The CP system predicts coping skills from the tilt angle and angular velocity of the left foot when an older driver is driving or preparing to start a car. The experiment carried out two phases, a phase of driving a car and a phase of preparing to start the car. In the driving phase, the young and older driver drive the car in a driving simulator. The average age of the young driver group was ± standard deviation = 20.6 ± 0.7 years, and the age of the older driver group was 78.5 ± 5.1 years. The driving route included 15 cases in which collision accidents are likely to occur. We analyzed the experimental results of the driving phase and clarified the predictors of coping skills. Moreover, we analyzed the correlation between the left foot movement in driving and the left foot movement during preparing to start the car. As a result of the experiment, there was a 0.84 correlation between the tilt angle of the left foot of the older driver in driving and the tilt angle of the left foot of the older driver in preparing to start the car. The result shows that the coping skills can be predicted from the tilt angle of the left foot of the older driver during preparing to start the car. We showed that the coping skill can be predicted with an accuracy of 92% or 94% on average from the tilt angle and the angular velocity of the left foot while driving or preparing to start the car. Moreover, we clarified that the tilt angle of the left foot of a driver without coping skills is perpendicular to the ground compared to a driver with coping skills. This study is expected to contribute to the prevention of traffic accidents that occur in the face of an unexpected situation.

Review of Studies on Older Drivers' Behavior and Stress-Methods, Results, and Outlook.

This paper presents a review on relevant studies and reports related to older drivers' behavior and stress. Questionnaires, simulators, and on-road/in-vehicle systems are used to collect driving data in most studies. In addition, research either directly compares older drivers and the other drivers or considers participants according to various age groups. Nevertheless, the definition of 'older driver' varies not only across studies but also across different government reports. Although questionnaire surveys are widely used to affordably obtain massive data in a short time, they lack objectivity. In contrast, biomedical information can increase the reliability of a driving stress assessment when collected in environments such as driving simulators and on-road experiments. Various studies determined that driving behavior and stress remain stable regardless of age, whereas others reported degradation of driving abilities and increased driving stress among older drivers. Instead of age, many researchers recommended considering other influencing factors, such as gender, living area, and driving experience. To mitigate bias in findings, this literature review suggests a hybrid method by applying surveys and collecting on-road/in-vehicle data.

Canadian Older Adults' Perceptions of Transitioning from Driver to Non-Driver.

Ceasing driving is associated with many negative outcomes. We examined the perceived impact of driving cessation among current older drivers. Transcripts from 92 interviews with participants from several locations across Canada were analyzed using inductive thematic analysis. We identified five themes: planning for mobility change, mobility supports and neighborhoods, financial security, fearing loss of control and independence, and coping and acceptance as a part of aging. Findings highlight diverse attitudes toward driving cessation, ranging from avoidance to acceptance, and emphasize the importance of tailored resources for drivers at various stages of behavior change.

Driving rehabilitation programs for older drivers in the United States.

The objective of this study was to describe the services, referral and reporting practices, and barriers to utilization of driver rehabilitation programs (DRPs) for older drivers. Identified through two national association databases, 204 DRPs completed an online survey. DRP availability varies, with a median of one program per 64,151 older adults (range: 1,006-676,981). The median cost for a complete evaluation was $400; 36% of DRPs reported no third-party reimbursement. Participants thought barriers to DRP use include cost/reimbursement, lack of program awareness, and issues with evaluator training. Models for insurance reimbursement, and increased awareness of program benefits by healthcare providers and older drivers, are needed.

Fit2Drive: Screening Older Drivers with Cognitive Concerns.

OBJECTIVES: The 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. DESIGN: This was a psychometric study of the new test's diagnostic accuracy. SETTINGS AND PARTICIPANTS: The 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. METHODS: Mini-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. RESULTS: Altogether, 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 IMPLICATIONS: The Fit2Drive algorithm demonstrated a strong 91.5% predictive accuracy. Usefulness in office-based patient consultations is promising but remains to be rigorously tested.

Subjective memory concerns and car collisions: A cross-sectional cohort study among older Japanese drivers.

Background: A previous study suggested older drivers with subjective memory concerns (SMC) had increased odds of experiencing car collisions, but whether SMC in different contexts and the number of SMC applicable items change this association is unknown. The aim of this study was to examine the association between SMC and car collisions among older drivers in Japan. Methods: This cross-sectional study was conducted using data from a Japanese community-based cohort study. Participants were community-dwelling older adults aged ≥60 years. SMC was assessed using five questions: 1) "Do you feel you have more problems with memory than most?" 2) "Do you have any difficulty with your memory?" 3) "Do you forget where you have left things more than you used to?" 4) "Do you forget the names of close friends or relatives?" and 5) "Do other people find you forgetful?" Participants were asked about their experiences with car collisions during the previous two years. Results: A total of 13,137 older drivers (72.1 ± 5.5 years old, and 43.6 % female) were analyzed. Cochran-Armitage trend test showed that as the number of SMC applicable items increased, the percentage of the experiences of car collisions significantly increased (6.8 %-15.8 %, P < 0.001). Logistic regression models showed each SMC question was associated with an increased odds ratio (OR) of car collisions (OR 1.26 to 1.71, all P < 0.001) after adjusting for confounding factors. As the number of SMC applicable items increased, the OR of car collisions significantly increased (OR 1.19 to 2.28, all P < 0.05, P for trend <0.001). Conclusions: This cross-sectional study among community-dwelling older drivers in Japan suggested each SMC question and the number of applicable items were associated with car collisions. SMC may be a sign of increased risk of traffic incidents for older drivers.

Age-related differences in takeover performance: A comparative analysis of older and younger drivers in prolonged partially automated driving.

OBJECTIVE: Vehicle automation technologies have the potential to address the mobility needs of older adults. However, age-related cognitive declines may pose new challenges for older drivers when they are required to take back or "takeover" control of their automated vehicle. This study aims to explore the impact of age on takeover performance under partially automated driving conditions and the interaction effect between age and voluntary non-driving-related tasks (NDRTs) on takeover performance. METHOD: A total of 42 older drivers (M = 65.5 years, SD = 4.4) and 40 younger drivers (M = 37.2 years, SD = 4.5) participated in this mixed-design driving simulation experiment (between subjects: age [older drivers vs. younger drivers] and NDRT engagement [road monitoring vs. voluntary NDRTs]; within subjects: hazardous event occurrence time [7.5th min vs. 38.5th min]). RESULTS: Older drivers exhibited poorer visual exploration performance (i.e., longer fixation point duration and smaller saccade amplitude), lower use of advanced driving assistance systems (ADAS; e.g., lower percentage of time adaptive cruise control activated [ACCA]) and poorer takeover performance (e.g., longer takeover time, larger maximum resulting acceleration, and larger standard deviation of lane position) compared to younger drivers. Furthermore, older drivers were less likely to experience driving drowsiness (e.g., lower percentage of time the eyes are fully closed and Karolinska Sleepiness Scale levels); however, this advantage did not compensate for the differences in takeover performance with younger drivers. Older drivers had lower NDRT engagement (i.e., lower percentage of fixation time on NDRTs), and NDRTs did not significantly affect their drowsiness but impaired takeover performance (e.g., higher collision rate, longer takeover time, and larger maximum resulting acceleration). CONCLUSIONS: These findings indicate the necessity of addressing the impaired takeover performance due to cognitive decline in older drivers and discourage them from engaging in inappropriate NDRTs, thereby reducing their crash risk during automated driving.

Implications of using administrative healthcare data to identify risk of motor vehicle crash-related injury: the importance of distinguishing crash from crash-related injury.

BACKGROUND: Administrative healthcare databases, such as Medicare, are increasingly used to identify groups at risk of a crash. However, they only contain information on crash-related injuries, not all crashes. If the driver characteristics associated with crash and crash-related injury differ, conflating the two may result in ineffective or imprecise policy interventions. METHODS: We linked 10 years (2008-2017) of Medicare claims to New Jersey police crash reports to compare the demographics, clinical diagnoses, and prescription drug dispensings for crash-involved drivers ≥ 68 years with a police-reported crash to those with a claim for a crash-related injury. We calculated standardized mean differences to compare characteristics between groups. RESULTS: Crash-involved drivers with a Medicare claim for an injury were more likely than those with a police-reported crash to be female (62.4% vs. 51.8%, standardized mean difference [SMD] = 0.30), had more clinical diagnoses including Alzheimer's disease and related dementias (13.0% vs. 9.2%, SMD = 0.20) and rheumatoid arthritis/osteoarthritis (69.5% vs 61.4%, SMD = 0.20), and a higher rate of dispensing for opioids (33.8% vs 27.6%, SMD = 0.18) and antiepileptics (12.9% vs 9.6%, SMD = 0.14) prior to the crash. Despite documented inconsistencies in coding practices, findings were robust when restricted to claims indicating the injured party was the driver or was left unspecified. CONCLUSIONS: To identify effective mechanisms for reducing morbidity and mortality from crashes, researchers should consider augmenting administrative datasets with information from police crash reports, and vice versa. When those data are not available, we caution researchers and policymakers against the tendency to conflate crash and crash-related injury when interpreting their findings.

Associations between biopsychosocial factors and transportation patterns of older adults residing in Klang Valley, Malaysia.

Introduction: Aging is associated with physiological changes in multiple systems in the body and may impact the transportation choices of older adults. In this study, we examine the associations between biopsychosocial factors and the transportation choices of Malaysian older adults. Methods: One hundred and nineteen (119) older adults, aged 60 and above, living in Klang Valley, Malaysia were recruited for this cross-sectional study. Participants were interviewed face-to-face to obtain sociodemographic data, health status (whether there were and, if yes, the number of comorbidities), outdoor mobility and transportation patterns, Instrumental Activity Daily Living (IADL) status and cognitive function. Participants' physical performance (dominant handgrip strength, 10-m walk, and timed up and go tests), hearing threshold (pure tone audiometry), and vision function (visual acuity, contrast sensitivity) were measured. Transportation patterns of older adults were categorized into three groups, that is, flexible (using public transport and/or private vehicles), using only private vehicles and restricted (relying on others or walking). Results: Further information is needed to enable such older adults as older women, those with comorbidities and poorer functional status to access transportation, especially to meet their health care needs. Discussion: The majority (51%) of participants were in the 'using only private vehicles' group, followed by the 'flexibles' (25%) and the 'restricted' (24%). Factors significantly associated with the restricted transportation group were: (a) being female (AdjOR 15.39, 95% CI 0.86-23.39, p < 0.001); (b) being Malay (AdjOR 21.72, 95% CI 0.36-16.12, p < 0.001); (c) having higher number of comorbidities (AdjOR 14.01, 95% CI 0.20-13.21, p = 0.007); and (d) being dependent in IADL (AdjOR 13.48, 95% CI 0.51-1.78, p = 0.002).

Older driver at-fault crashes at unsignalized intersections in Alabama: Injury severity analysis with supporting evidence from a deep learning based approach.

INTRODUCTION: The research described in this paper explored the factors contributing to the injury severity resulting from the male and female older driver (65 years and older) at-fault crashes at unsignalized intersections in Alabama. METHOD: Random parameter logit models of injury severity were estimated. The estimated models identified a variety of statistically significant factors influencing the injury severities resulting from older driver at-fault crashes. RESULTS: According to these models, some variables were found to be significant only in one model (male or female) but not in the other one. For example, variables such as driver under the influence of alcohol/drugs, horizontal curve, and stop sign were found significant only in the male model. On the other hand, variables such as intersection approaches on tangents with flat grade, and driver older than 75 years were found significant only in the female model. In addition, variables such as making turning maneuver, freeway-ramp junction, high speed approach, and so forth were found significant in both models. Estimation findings showed that two parameters in the male model and another two parameters in the female model could be modeled as random parameters, indicating their varying influences on the injury severity due to unobserved effects. In addition to the random parameter logit approach, a deep learning approach based on Artificial Neural Networks was introduced to predict the outcome of the crashes based on 164 variables that are listed in the crash database. The artificial intelligence (AI)-based method achieved an accuracy of 76% indicating the role of the variables in deciding the final outcome. PRACTICAL APPLICATIONS: Future plans are set to study the use of AI on large sized datasets to achieve a relatively high-performance, and hence to be able to identify which variables contribute the most to the final outcome.

"The Challenge is Not to Make Her Feel Old and Bad": Exploring Australian Family Member Experiences of Conversations About Driving With Older Adults Using an Online Survey.

This study explored the experiences of Australian family members having conversations about driving with older adults. An exploratory cross-sectional design using an online survey was carried out with Australian family members of current or retired (former) older drivers. One hundred and fifty-six intergenerational family members across Australia completed the survey. Qualitative content analysis of free-text responses identified that the outcomes of conversations were impacted by a range of environmental and individual factors. The essence of conversations centered around two opposing (positive and negative) discourses. The findings highlighted that an individualized approach to the content of conversations is required due to; driver attributes and actions, variations in the level of support experienced by family members, differences in physical and cognitive declines with age, negative perceptions on the impact of driving retirement, and absence of acceptable alternatives to driving. We recommend using positive discourse and reappraisal techniques when initiating driving conversations with older adults.

Strategy and safety at stop intersections in older adults with mild cognitive impairment and visual decline.

This study assessed the impact of age-related cognitive and visual declines on stop-controlled intersection stopping and scanning behaviors across varying roadway, traffic, and environmental challenges. Real-world driver data, collected from drivers' personal vehicles using in-vehicle sensor systems, was analyzed in 68 older adults (65-90 years old) with and without mild cognitive impairment (MCI) and with a range of age-related visual declines. Driver behavior, environmental characteristics, and traffic characteristic were examined across 2,596 approaches at 173 stop-controlled intersections. A mixed-effects logistic regression modeled stopping behavior as a binary response (full stop or rolling/no-stop). Overall, drivers who scanned more on intersection approaches (OR = 0.77) or had more visual decline (OR = 2.28) were more likely to make full stops at a stop-controlled approach. Drivers with a contrast sensitivity logMAR score > 0.8 showed the greatest probability of making a full stop compared across all drivers. Drivers without MCI were ~ 5 times more likely to come to a full stop when they scanned more (23 % versus 5 % when they scanned less) compared to drivers with MCI, who were only twice as likely to stop (14 % versus 6 % when they scanned less). Drivers were more likely to fully stop on two-lane roadways (1.5 %), during night (2.0 %), and at intersections with opposing vehicles (10.4 %). Findings illuminate how driver strategies interact with underlying impairment. While drivers with visual decline adopt strategies that may improve safety, when drivers with MCI adopt strategies it did not result in the same degree of improvement in stopping which may result in greater risk.

Associations of visual functions with attitudes about motor vehicle dashboards among older drivers.

Purpose: Proper understanding and interaction with the dashboard is an essential aspect of safely operating a motor vehicle. A portion of this task is dependent on vision, yet no published information exists regarding dashboard ergonomics and visual function. This study sought to associate visual functions and person abilities of dashboard ergonomic dimensions relevant to older driver design preferences and attitudes. Methods: In this population-based study of drivers, participants completed functional testing for habitual distance visual acuity, contrast sensitivity, visual field sensitivity, visual processing speed, and spatial ability. A questionnaire assessed attitudes and understanding of dashboard design, with questionnaire items generated from the content of focus groups of older drivers. Dashboard design domains identified in Rasch analysis of questionnaire responses were quantified using person ability measures for the cognitive processing, lighting, obstructions, and pattern recognition domains. Visual functions and person abilities were correlated using Spearman partial correlations, adjusting for age and sex. Results: A total of 997 participants completed functional testing and the dashboard questionnaire. The mean age was 77.4 ± 4.6 years, and the majority were male (55%) and white (81%). The sample had a range of person abilities and visual functions. Contrast and visual field sensitivities were significantly associated with the cognitive processing, lighting, and pattern recognition dashboard design dimensions (p ≤ 0.0052). For all significant associations, increased visual function was indicative of better person ability. Visual processing speed, as measured by Trails B and UFOV2, was significantly associated with the lighting domain (p = 0.0008 and p = 0.0007, respectively). The UFOV2 measure was correlated with pattern recognition (p = 0.0165). Spatial ability was the only visual function associated with the visual obstruction dimension (p = 0.0347). Conclusions: Person ability for dashboard design domains are related to visual function in older drivers. Results show person ability for domains increased with improved visual function. Future automotive engineering and design initiatives should consider these associations in improving dashboard designs to increase vehicle utility and accessibility.

Exploration of the longitudinal trend of DUI crashes in Pennsylvania, USA (2008 to 2019).

OBJECTIVE: This study aims to explore the longitudinal trends of DUI crashes in Pennsylvania, USA to provide insights for making the long-term DUI countermeasures. METHODS: Crash data of Pennsylvania from 2008 to 2019 are collected from the Pennsylvania Department of Transportation. DUI crashes are divided into alcohol-impaired, drug-impaired, and alcohol-drug-impaired ones in the analysis. The linear regression models are adopted to check whether traffic crashes had significantly changed over time. RESULTS: Alcohol-impaired crashes decreased but drug-impaired crashes increased in the study period. Drugged driving is increasingly more deadly compared to drunk driving, and alcohol-drug-impaired crashes are the deadliest. Besides, illicit drugs dominate drug-impaired crashes now, drugged driving is increasing in rural areas, and older drivers are overwhelmingly involved in DUI crashes. CONCLUSIONS: The growth of drug-impaired crashes, especially illicit drug-impaired crashes, raises new concerns to the proposal of marijuana legalization in Pennsylvania, where recreational use of marijuana is currently prohibited. The decreasing trend of alcohol-impaired crashes is suggestive of the success of the long-term crackdown to drunk driving and implies the necessity of developing the uniform and handy roadside drug test devices. Besides, rural areas and older drivers should be paid special attention to deter DUI in the context of urbanization and population aging.

On-Road Behavior in Older Drivers With Mild Cognitive Impairment.

OBJECTIVES: Dementia increases the risk of unsafe driving, but this is less apparent in preclinical stages such as mild cognitive impairment (MCI). There is, however, limited detailed data on the patterns of driving errors associated with MCI. Here, we examined whether drivers with MCI exhibited different on-road error profiles compared with cognitively normal (CN) older drivers. DESIGN: Observational. SETTING AND PARTICIPANTS: A total of 296 licensed older drivers [mean age 75.5 (SD = 6.2) years, 120 (40.5%) women] recruited from the community. METHOD: Participants completed a health and driving history survey, a neuropsychological test battery, and an on-road driving assessment including driver-instructed and self-navigation components. Driving assessors were blind to participant cognitive status. Participants were categorized as safe or unsafe based on a validated on-road safety scale, and as having MCI based on International Working Group diagnostic criteria. Proportion of errors incurred as a function of error type and traffic context were compared across safe and unsafe MCI and CN drivers. RESULTS: Compared with safe CN drivers (n = 225), safe MCI drivers (n = 45) showed a similar pattern of errors in different traffic contexts. Compared with safe CN drivers, unsafe CN drivers (n = 17) were more likely to make errors in observation, speed control, lane position, and approach, and at stop/give-way signs, lane changes, and curved driving. Unsafe MCI drivers (n = 9) had additional difficulties at intersections, roundabouts, parking, straight driving, and under self-navigation conditions. A higher proportion of unsafe MCI drivers had multidomain subtype [n = 6 (67%)] than safe MCI drivers [n = 11 (25%)], odds ratio 6.2 (95% confidence interval, 1.4-29.6). CONCLUSION AND IMPLICATIONS: Among safe drivers, MCI and CN drivers exhibit similar on-road error profiles, suggesting driver restrictions based on MCI status alone are unwarranted. However, formal evaluation is recommended in such cases, as there is evidence drivers with multiple domains of cognitive impairment may require additional interventions to support safe driving.

Long-Term Effects of Driving Skill Training on Safe Driving in Older Adults with Mild Cognitive Impairment.

BACKGROUND/OBJECTIVE: A driving skill program had positive effects on safe driving performance in older adults, even those with cognitive impairment. However, the long-term effects of the program remain unclear. The purpose of this study was to examine whether such effects were maintained at 1 year after the intervention in older adults with cognitive impairment who had low driving skills. DESIGN: A secondary analysis of single-blind randomized controlled trial. SETTING: Community setting in Japan. PARTICIPANTS: Community-living adults, aged 65 years or older (n = 159), with mild cognitive impairment (MCI). INTERVENTION: The intervention group completed 10 classroom sessions of 1 hour and 10 on-road sessions of 50 minutes, focusing on common problem areas of older drivers. The control group received one education class about safety driving. MEASUREMENTS: On-road driving performance was assessed by certified driving school instructors in a driving school at preintervention and postintervention, and 1-year follow-up. RESULTS: A total of 159 community-living older drivers participated in this study and were randomized to either an intervention group (n = 71) or a control group (n = 88). One year after the intervention, 104 of 159 community-living older drivers completed the follow-up assessment (intervention group, n = 58). Regarding the safe driving skill score, there was a significant group × time interaction (P < .01), indicating benefits of the intervention over time. Although the intervention group showed a significant decline in the safe driving skill score from postintervention (score = 38.9 ± 46.1) to 1-year follow-up (score = -0.3 ± 55.2), there was a significant difference between the groups at 1-year follow-up (control group score = -148.5 ± 46.4) (P < .05), and between preintervention (score = -132.0 ± 54.6) and 1-year follow-up in the intervention group (P < .05). CONCLUSION: The driving skill program maintained safe driving performance that had been improved by the intervention in older adults with MCI.

Factors associated with driver injury severity of lane changing crashes involving younger and older drivers.

Lane change maneuvers can be a difficult driving task for many drivers, particularly, younger and inexperienced drivers and older drivers. Frequent and improper lane changing has a substantial effect on both traffic operations and safety. This study investigates the factors that contribute to the injury severity of crashes resulting from improper lane change maneuvers involving younger and older drivers in Alabama. Crash data for the study was obtained from the Critical Analysis Reporting Environment (CARE) system developed by the Center for Advanced Public Safety at the University of Alabama. Preliminary data analysis showed that younger drivers were responsible for about 63.1 % of the crashes. Random logit with heterogeneity in means models were developed to identify significant crash factors that were associated with the crash outcomes. The results show that younger male drivers were more likely to be severely injured in lane changing crashes whereas older male drivers were less likely to be severely injured. The results further show that younger drivers were more likely to sustain a major injury on six-lane highways whereas older drivers sustained major injuries from overtaking maneuvers on two-lane highways. It was further found that while younger drivers got into major injury crashes under daylight conditions, older drivers were more likely to be involved in major injury crashes under dark/unlit lighting conditions. Improper lane changing constitutes some form of aggressive driving which needs to be addressed considering that many lives are lost annually from the practice. The findings from this study may be used by road safety advocates and practitioners to identify what and how to target crash countermeasures to the younger and older driver population groups in the state.