Glaucomatous visual fields and neurocognitive function are independently associated with poor lane maintenance during driving simulation.

BACKGROUND: Driving simulators are a safe alternative to on-road vehicles for studying driving behavior in glaucoma drivers. Visual field (VF) loss severity is associated with higher driving simulator crash risk, though mechanisms explaining this relationship remain unknown. Furthermore, associations between driving behavior and neurocognitive performance in glaucoma are unexplored. Here, we evaluated the hypothesis that VF loss severity and neurocognitive performance interact to influence simulated vehicle control in glaucoma drivers. METHODS: Glaucoma patients (n = 25) and suspects (n = 18) were recruited into the study. All had > 20/40 corrected visual acuity in each eye and were experienced field takers with at least three stable (reliability > 20%) fields over the last 2 years. Diagnosis of neurological disorder or cognitive impairment were exclusion criteria. Binocular VFs were derived from monocular Humphrey VFs to estimate a binocular VF index (OU-VFI). Montreal Cognitive Assessment (MoCA) was administered to assess global and sub-domain neurocognitive performance. National Eye Institute Visual Function Questionnaire (NEI-VFQ) was administered to assess peripheral vision and driving difficulties sub-scores. Driving performance was evaluated using a driving simulator with a 290° panoramic field of view constructed around a full-sized automotive cab. Vehicle control metrics, such as lateral acceleration variability and steering wheel variability, were calculated from vehicle sensor data while patients drove on a straight two-lane rural road. Linear mixed models were constructed to evaluate associations between driving performance and clinical characteristics. RESULTS: Patients were 9.5 years older than suspects (p = 0.015). OU-VFI in the glaucoma group ranged from 24 to 98% (85.6 ± 18.3; M ± SD). OU-VFI (p = .0066) was associated with MoCA total (p = .0066) and visuo-spatial and executive function sub-domain scores (p = .012). During driving simulation, patients showed greater steering wheel variability (p = 0.0001) and lateral acceleration variability (p < .0001) relative to suspects. Greater steering wheel variability was independently associated with OU-VFI (p = .0069), MoCA total scores (p = 0.028), and VFQ driving sub-scores (p = 0.0087), but not age (p = 0.61). CONCLUSIONS: Poor vehicle control was independently associated with greater VF loss and worse neurocognitive performance, suggesting both factors contribute to information processing models of driving performance in glaucoma. Future research must demonstrate the external validity of current findings to on-road performance in glaucoma.

Using Topic Modeling to Develop Multi-level Descriptions of Naturalistic Driving Data from Drivers with and without Sleep Apnea.

One challenge in using naturalistic driving data is producing a holistic analysis of these highly variable datasets. Typical analyses focus on isolated events, such as large g-force accelerations indicating a possible near-crash. Examining isolated events is ill-suited for identifying patterns in continuous activities such as maintaining vehicle control. We present an alternative approach that converts driving data into a text representation and uses topic modeling to identify patterns across the dataset. This approach enables the discovery of non-linear patterns, reduces the dimensionality of the data, and captures subtle variations in driver behavior. In this study topic models are used to concisely described patterns in trips from drivers with and without untreated obstructive sleep apnea (OSA). The analysis included 5000 trips (50 trips from 100 drivers; 66 drivers with OSA; 34 comparison drivers). Trips were treated as documents, and speed and acceleration data from the trips were converted to "driving words." The identified patterns, called topics, were determined based on regularities in the co-occurrence of the driving words within the trips. This representation was used in random forest models to predict the driver condition (i.e., OSA or comparison) for each trip. Models with 10, 15 and 20 topics had better accuracy in predicting the driver condition, with a maximum AUC of 0.73 for a model with 20 topics. Trips from drivers with OSA were more likely to be defined by topics for smaller lateral accelerations at low speeds. The results demonstrate topic modeling as a useful tool for extracting meaningful information from naturalistic driving datasets.

Electrophysiological Measure of Impaired Information Processing in Drivers with Hematological Malignancy.

The broad goal of this study is to measure remote effects of cancer on brain physiology and behaviors that underpin instrumental activities of daily living such as automobile driving. Studies of hematological malignancies (HM) have demonstrated impairments in multiple brain functions shown to be critical for safe automobile driving. In the current pilot study, brain physiology during driving simulation was examined in 14 HM patients and 13 healthy comparison drivers. Electroencephalography was used to measure the eye fixation-related potential (EFRP)-a positive amplitude deflection evoked approximately 100 milliseconds after eye movement termination. Previous studies have demonstrated sensitivity of EFRP activity to information-processing capacity. All drivers completed visual search tasks to evaluate the relationship between driving-related changes in performance and EFRP activity. Results showed smaller EFRP amplitudes in drivers who had: (1) greater driving-related changes in visual search performance (p = 0.03, Cohen's d = 0.91); and (2) HM diagnosis (p = 0.18, Cohen's d = 0.54). Extending previous studies, these results provide neural evidence of reduced information-processing capacity associated with cancer diagnosis. Future large-scale studies are needed to confirm these results, given the high level of uncertainty and small sample size. This study provides a novel platform for linking changes in brain physiology and safety-critical driving behaviors.

The Case for Enrolling High-Cost Patients in an ACO.

Though accountable care organizations (ACOs) are increasingly important to American healthcare, ethical inquiry into ACOs remains in its nascent stages. Several articles have raised the concern that ACOs have an incentive to avoid enrolling high-cost patients and, thereby, have an incentive to deny care to those who need it the most. This concern is borne out by the reports of consultants working with newly formed ACOs. This paper argues that, contra initial appearances, there is no financial incentive for ACOs to avoid enrolling high-cost patients.

Ethical Practice Under Accountable Care.

Accountable Care Organizations (ACOs) are a key mechanism of the Patient Protection and Affordable Care Act (PPACA). ACOs will influence incentives for providers, who must understand these changes to make well-considered treatment decisions. Our paper defines an ethical framework for physician decisions and action within ACOs. Emerging ethical pressures providers will face as members of an ACO were classified under major headings representing three of the four principles of bioethics: autonomy, beneficence, and justice (no novel conflicts with non-maleficence were identified). Conflicts include a bias against transient populations, a motive to undertreat conditions lacking performance measures, and the mandate to improve population health incentivizing life intrusions. After introducing and explaining each conflict, recommendations are offered for how providers ought to precede in the face of novel ethical choices. Our description of novel ethical choices will help providers know what to expect and our recommendations can guide providers in choosing well.

Measuring listening effort: driving simulator versus simple dual-task paradigm.

OBJECTIVES: The dual-task paradigm has been widely used to measure listening effort. The primary objectives of the study were to (1) investigate the effect of hearing aid amplification and a hearing aid directional technology on listening effort measured by a complicated, more real world dual-task paradigm and (2) compare the results obtained with this paradigm to a simpler laboratory-style dual-task paradigm. DESIGN: The listening effort of adults with hearing impairment was measured using two dual-task paradigms, wherein participants performed a speech recognition task simultaneously with either a driving task in a simulator or a visual reaction-time task in a sound-treated booth. The speech materials and road noises for the speech recognition task were recorded in a van traveling on the highway in three hearing aid conditions: unaided, aided with omnidirectional processing (OMNI), and aided with directional processing (DIR). The change in the driving task or the visual reaction-time task performance across the conditions quantified the change in listening effort. RESULTS: Compared to the driving-only condition, driving performance declined significantly with the addition of the speech recognition task. Although the speech recognition score was higher in the OMNI and DIR conditions than in the unaided condition, driving performance was similar across these three conditions, suggesting that listening effort was not affected by amplification and directional processing. Results from the simple dual-task paradigm showed a similar trend: hearing aid technologies improved speech recognition performance, but did not affect performance in the visual reaction-time task (i.e., reduce listening effort). The correlation between listening effort measured using the driving paradigm and the visual reaction-time task paradigm was significant. The finding showing that our older (56 to 85 years old) participants' better speech recognition performance did not result in reduced listening effort was not consistent with literature that evaluated younger (approximately 20 years old), normal hearing adults. Because of this, a follow-up study was conducted. In the follow-up study, the visual reaction-time dual-task experiment using the same speech materials and road noises was repeated on younger adults with normal hearing. Contrary to findings with older participants, the results indicated that the directional technology significantly improved performance in both speech recognition and visual reaction-time tasks. CONCLUSIONS: Adding a speech listening task to driving undermined driving performance. Hearing aid technologies significantly improved speech recognition while driving, but did not significantly reduce listening effort. Listening effort measured by dual-task experiments using a simulated real-world driving task and a conventional laboratory-style task was generally consistent. For a given listening environment, the benefit of hearing aid technologies on listening effort measured from younger adults with normal hearing may not be fully translated to older listeners with hearing impairment.

Tourette Syndrome: A Catalyst for Operationalizing Neurodiversity.

Our goal, taking Tourette syndrome as a case example, is to introduce neurologists to, and motivate discussion on, the neurodiversity paradigm. This philosophical construct considers some neurologic conditions in diversity, instead of simply disease. Moving from philosophical idea to empirical construct draws from patient and family perspectives on (1) quality of life and discrimination, (2) disability pride, and (3) unique profiles of different patient cohorts. Listening to patient voices, attending to family, advocacy group, and societal views on neurologic disorders can strengthen precision neurology practice. Dialogs on neurodiversity, including antitherapy sentiments, offer to enhance neurologic care, patient agency, and autonomy; encourage respectful communications with patients who challenge the idea their condition is pathologic; and to set the stage for future empirical investigations and practice guidelines.

Evaluating governance in a clinical and translational research organization.

Institutional Development Awards for Clinical and Translational Research (IDeA-CTR) networks, funded by NIH/NIGMS, aim to advance CTR infrastructure to address historically unmet state and regional health needs. Success depends on the response to actionable feedback to IDeA-CTR leadership from network partners and governance groups through annual surveys, interviews, and governance body recommendations. The Great Plains IDeA-CTR applied internal formative meta-evaluation to evaluate dispositions of 172 governance recommendations from 2017 to 2021. Results provided insights to improve the classification and quality of recommendations, credibility of evaluation processes, responsiveness to recommendations, and communications and governance in a complex CTR network comprising multiple coalitions.

Digital driving data can track driving exposure and quality of life in Parkinson's disease.

OBJECTIVE: Parkinson's disease (PD) impairs motor and non-motor functions. Driver strategies to compensate for impairments, like avoiding driving in risky environments, may reduce on-road risk at the cost of decreasing driver mobility, independence, and quality of life (QoL). It is unclear how PD symptoms link to driving risk exposure, strategies, and QoL. We assessed associations between PD symptoms and driving exposure (1) overall, (2) in risky driving environments, and (3) in relationship to QoL. METHODS: Twenty-eight drivers with idiopathic PD were assessed using the Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and RAND 36-Item Short Form Health Survey (SF-36). Real-world driving was monitored for 1 month. Overall driving exposure (miles driven) and risky driving exposure (miles driven in higher risk driving environments) were assessed across PD symptom severity. High traffic, night, and interstate roads were considered risky environments. RESULTS: 18,642 miles (30,001 km) driven were collected. Drivers with PD with worse motor symptoms (MDS-UPDRS Part III) drove more overall (b = 0.17, P < .001) but less in risky environments (night: b = -0.35, P < .001; interstate roads: b = -0.23, P < .001; high traffic: b = -0.14, P < .001). Worse non-motor daily activities symptoms (MDS-UPDRS Part I) did not affect overall driving exposure (b = -0.05, P = .43) but did affect risky driving exposure. Worse non-motor daily activities increased risk exposure to interstate (b = 0.36, P < .001) and high traffic (b = 0.09, P = .03) roads while reducing nighttime risk exposure (b = -0.15, P = .01). Daily activity impacts from motor symptoms (MDS-UPDRS Part II) did not affect distance driven. Reduced driving exposure (number of drives per day) was associated with worse physical health-related QoL (b = 2.87, P = .04). CONCLUSIONS: Results provide pilot data revealing specific PD symptom impacts on driving risk exposure and QoL. Drivers with worse non-motor impairments may have greater risk exposure. In contrast, drivers with worse motor impairments may have reduced driver risk exposure. Reduced driving exposure may worsen physical health-related QoL. Results show promise for using driving to inform clinical care.

Directing driver attention with augmented reality cues.

This simulator study evaluated the effects of augmented reality (AR) cues designed to direct the attention of experienced drivers to roadside hazards. Twenty-seven healthy middle-aged licensed drivers with a range of attention capacity participated in a 54 mile (1.5 hour) drive in an interactive fixed-base driving simulator. Each participant received AR cues to potential roadside hazards in six simulated straight (9 mile long) rural roadway segments. Drivers were evaluated on response time for detecting a potentially hazardous event, detection accuracy for target (hazard) and non-target objects, and headway with respect to the hazards. Results showed no negative outcomes associated with interference. AR cues did not impair perception of non-target objects, including for drivers with lower attentional capacity. Results showed near significant response time benefits for AR cued hazards. AR cueing increased response rate for detecting pedestrians and warning signs but not vehicles. AR system false alarms and misses did not impair driver responses to potential hazards.

The Language of Driving: Advantages and Applications of Symbolic Data Reduction for Analysis of Naturalistic Driving Data.

Recent advances in onboard vehicle data recording devices have created an abundance of naturalistic driving data. The amount of data exceeds the resources available for analysis; this situation forces researchers to focus on analyses of critical events and to use simple heuristics to identify those events. Critical event analysis eliminates the context that can be critical in understanding driver behavior and can reduce the generalizability of the analysis. This work introduced a method of naturalistic driving data analysis that would allow researchers to examine entire data sets by reducing the sets by more than 90%. The method utilized a symbolic data reduction algorithm, symbolic aggregate approximation (SAX), which reduced time series data to a string of letters. SAX can be applied to any continuous measurement, and SAX output can be reintegrated into a data set to preserve categorical information. This work explored the application of SAX to speed and acceleration data from a naturalistic driving data set and demonstrated SAX's integration with other methods that could begin to tame the complexity of naturalistic data.

Real-World Driving Data Indexes Dopaminergic Treatment Effects in Parkinson's Disease.

Background: Driving is a complex, everyday task that impacts patient agency, safety, mobility, social connections, and quality of life. Digital tools can provide comprehensive real-world (RW) data on driver behavior in patients with Parkinson's disease (PD), providing critical data on disease status and treatment efficacy in the patient's own environment. Objective: This pilot study examined the use of driving data as a RW digital biomarker of PD symptom severity and dopaminergic therapy effectiveness. Methods: Naturalistic driving data (3974 drives) were collected for 1 month from 30 idiopathic PD drivers treated with dopaminergic medications. Prescriptions data were used to calculate levodopa equivalent daily dose (LEDD). The association between LEDD and driver mobility (number of drives) was assessed across PD severity, measured by the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Results: PD drivers with worse motor symptoms based on self-report (Part II: P = 0.02) and clinical examination (Part III: P < 0.001) showed greater decrements in driver mobility. LEDD levels >400 mg/day were associated with higher driver mobility than those with worse PD symptoms (Part I: P = 0.02, Part II: P < 0.001, Part III: P < 0.001). Conclusions: Results suggest that comprehensive RW driving data on PD patients may index disease status and treatment effectiveness to improve patient symptoms, safety, mobility, and independence. Higher dopaminergic treatment may enhance safe driver mobility in PD patients with worse symptom severity.

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.

Vehicle Control as a Measure of Real-World Driving Performance in Patients With Rheumatoid Arthritis.

OBJECTIVE: To quantify vehicle control as a metric of automobile driving performance in patients with rheumatoid arthritis (RA). METHODS: Naturalistic driving assessments were completed in patients with active RA and controls without disease. Data were collected using in-car, sensor-based instrumentation installed in the participants' own vehicles to observe typical driving habits. RA disease status, disease activity, and functional status were associated with vehicle control (lateral [steering] and longitudinal [braking/accelerating] acceleration variability) using mixed-effect linear regression models stratified by road type (defined by roadway speed limit). RESULTS: Across 1,292 driving hours, RA drivers (n = 33) demonstrated differences in vehicle control compared to controls (n = 23), with evidence of significant statistical interaction between disease status and road type (P < 0.001). On residential roads, participants with RA demonstrated overall lower braking/accelerating variability than controls (P ≤ 0.004) and, when disease activity was low, lower steering variability (P = 0.03). On interstates/highways, RA was associated with increased steering variability among those with moderate/high Clinical Disease Activity Index scores (P = 0.04). In models limited to RA, increases in disease activity and physical disability over 12 weeks of observation were associated with a significant increase in braking/accelerating variability on interstate/highways (both P < 0.05). CONCLUSION: Using novel naturalistic assessments, we linked RA and worsening RA disease severity with aberrant vehicle control. These findings support the need for further research to map these observed patterns in vehicle control to metrics of driver risk and, in turn, to link patterns of real-world driving behavior to diagnosis and disease activity.

Visual search for features and conjunctions following declines in the useful field of view.

UNLABELLED: BACKGROUND/STUDY CONTEXT: Typical measures for assessing the useful field (UFOV) of view involve many components of attention. The objective of the current experiment was to examine differences in visual search efficiency for older individuals with and without UFOV impairment. METHODS: The authors used a computerized screening instrument to assess the useful field of view and to characterize participants as having an impaired or normal UFOV. Participants also performed two visual search tasks, a feature search (e.g., search for a green target among red distractors) or a conjunction search (e.g., a green target with a gap on its left or right side among red distractors with gaps on the left or right and green distractors with gaps on the top or bottom). RESULTS: Visual search performance did not differ between UFOV impaired and unimpaired individuals when searching for a basic feature. However, search efficiency was lower for impaired individuals than unimpaired individuals when searching for a conjunction of features. CONCLUSION: The results suggest that UFOV decline in normal aging is associated with conjunction search. This finding suggests that the underlying cause of UFOV decline may arise from an overall decline in attentional efficiency. Because the useful field of view is a reliable predictor of driving safety, the results suggest that decline in the everyday visual behavior of older adults might arise from attentional declines.

Sugar and stops in drivers with insulin-dependent type 1 diabetes.

BACKGROUND: Diabetes is a major public health challenge, affecting millions of people worldwide. Abnormal physiology in diabetes, particularly hypoglycemia, can cause driver impairments that affect safe driving. While diabetes driver safety has been previously researched, few studies link real-time physiologic changes in drivers with diabetes to objective real-world driver safety, particularly at high-risk areas like intersections. To address this, we investigated the role of acute physiologic changes in drivers with type 1 diabetes mellitus (T1DM) on safe stopping at stop intersections. METHODS: 18 T1DM drivers (21-52 years, µ = 31.2 years) and 14 controls (21-55 years, µ = 33.4 years) participated in a 4-week naturalistic driving study. At induction, each participant's personal vehicle was instrumented with a camera and sensor system to collect driving data (e.g., GPS, video, speed). Video was processed with computer vision algorithms detecting traffic elements (e.g., traffic signals, stop signs). Stop intersections were geolocated with clustering methods, state intersection databases, and manual review. Videos showing driver stop intersection approaches were extracted and manually reviewed to classify stopping behavior (full, rolling, and no stop) and intersection traffic characteristics. RESULTS: Mixed-effects logistic regression models determined how diabetes driver stopping safety (safe vs. unsafe stop) was affected by 1) disease and 2) at-risk, acute physiology (hypo- and hyperglycemia). Diabetes drivers who were acutely hyperglycemic (≥ 300 mg/dL) had 2.37 increased odds of unsafe stopping (95% CI: 1.26-4.47, p = 0.008) compared to those with normal physiology. Acute hypoglycemia did not associate with unsafe stopping (p = 0.537), however the lower frequency of hypoglycemia (vs. hyperglycemia) warrants a larger sample of drivers to investigate this effect. Critically, presence of diabetes alone did not associate with unsafe stopping, underscoring the need to evaluate driver physiology in licensing guidelines. CONCLUSION: This study links acute, abnormal physiologic fluctuations in drivers with diabetes to driver safety based on unsafe stopping at stop-controlled intersections, providing recommendations for clinicians aimed at improving patient safety, fair licensing guidelines, and targets for developing advanced driver assistance systems.

Impaired driving from medical conditions: a 70-year-old man trying to decide if he should continue driving.

Some medical disorders can impair performance, increasing the risk of driving safety errors that can lead to vehicle crashes. The causal pathway often involves a concatenation of factors or events, some of which can be prevented or controlled. Effective interventions can operate before, during, or after a crash occurs at the levels of driver capacity, vehicle and road design, and public policy. A variety of systemic, neurological, psychiatric, and developmental disorders put drivers at potential increased risk of a car crash in the short or long term. Medical diagnosis and age alone are usually insufficient criteria for determining fitness to drive. Strategies are needed for determining what types and levels of reduced function provide a threshold for disqualification in drivers with medical disorders. Evidence of decreased mileage, self-restriction to driving in certain situations, collisions, moving violations, aggressive driving, sleepiness, alcohol abuse, metabolic disorders, and multiple medications may trigger considerations of driver safety. A general framework for evaluating driver fitness relies on a functional evaluation of multiple domains (cognitive, motor, perceptual, and psychiatric) that are important for safe driving and can be applied across many disorders, including conditions that have rarely been studied with respect to driving, and in patients with multiple conditions and medications. Neurocognitive tests, driving simulation, and road tests provide complementary sources of evidence to evaluate driver safety. No single test is sufficient to determine who should drive and who should not.

Vision, attention, and driving.

Safe driving demands the coordination of multiple sensory and cognitive functions, such as vision and attention. Patients with neurologic or ophthalmic disease are exposed to selective pathophysiologic insults to driving-critical systems, placing them at a higher risk for unsafe driving and restricted driving privileges. Here, we evaluate how vision and attention contribute to unsafe driving across different patient populations. In ophthalmic disease, we focus on macular degeneration, glaucoma, diabetic retinopathy, and cataract; in neurologic disease, we focus on Alzheimer's disease, Parkinson's disease, and multiple sclerosis. Unsafe driving is generally associated with impaired vision and attention in ophthalmic and neurologic patients, respectively. Furthermore, patients with ophthalmic disease experience some degree of impairment in attention. Similarly, patients with neurologic disease experience some degree of impairment in vision. While numerous studies have demonstrated a relationship between impaired vision and unsafe driving in neurologic disease, there remains a dearth of knowledge regarding the relationship between impaired attention and unsafe driving in ophthalmic disease. In summary, this chapter confirms-and offers opportunities for future research into-the contribution of vision and attention to safe driving.

Visual and Cognitive Impairments Differentially Affect Speed Limit Compliance in Older Drivers.

OBJECTIVES: We test the hypothesis that clinical measures of age-related cognitive, visual, and mobility impairments negatively impact older driver speed limit compliance to advance method developments that improve older patient care and screen, identify, and advise at-risk older drivers. DESIGN: Real-world driver behaviors of older adults who had a range of cognitive, visual, and mobility abilities (measured with standardized, clinical tests) were assessed in environmental context (e.g., speed limit, traffic density, roadway type). Older driver speed limit compliance was measured in constant speed limit zones and at transition zones, where speed limits changed. SETTING: A naturalistic driving study of older adults living around Omaha, Nebraska. PARTICIPANTS: Seventy-seven, legally licensed, active, and typically aging older drivers (65-90 years) who had a range of cognitive and visual abilities. MEASUREMENTS: Drivers typical, daily driving was continuously monitored for 3 months using sensor instrumentation installed in their own vehicles. At study start, each participant completed a comprehensive, standardized, clinical assessment of cognitive, visual, and mobility abilities relevant to aging and driving. RESULTS: Older drivers with greater cognitive impairment (P = .10) drove slower than drivers with less cognitive impairment, linking cognitive impairment to speed control. Drivers with greater visual impairment overall complied less with speed limit changes at transition zones (P = .01) and were more likely to comply with speed limit transitions when they occurred concurrently with changes in roadway features (P < .01). CONCLUSION: Results link clinical measures of age-related cognitive and visual impairment to impaired driver safety in real-world contexts. Real-world sensor data coupled with detailed, personalized older driver profiles can inform patients, caregivers, interventions, policy, and the design of supportive in-vehicle technology for at-risk older drivers.

Driving Ability and Safety in Rheumatoid Arthritis: A Systematic Review.

OBJECTIVE: To identify whether rheumatoid arthritis (RA) is associated with driving ability and/or the use of assistive devices or modifications to improve driving ability. METHODS: We conducted a systematic literature review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines of RA and driving ability/adaptations by searching multiple databases from inception to April 2018. Eligible studies were original articles in the English language that had quantitative data regarding the study objective and at least 5 RA patients. Similar outcomes were extracted across studies and grouped into categories for review. RESULTS: Our search yielded 1,935 potential reports, of which 22 fulfilled eligibility criteria, totaling 6,285 RA patients. The prevalence of driving issues in RA was highly variable among the studies. Some of the shared themes addressed in these publications included RA in association with rates of motor vehicle crashes, self-reported driving difficulty, inability to drive, use of driving adaptations, use of assistance by other people for transport, and difficulty with general transportation. CONCLUSION: Despite variability among individual reports, driving difficulties and the use of driving adaptations are relatively common in individuals with RA. Given the central importance of automobile driving for the quality of life of RA patients, further investigations of driving ability and potential driving adaptations that can help overcome barriers to safe driving are needed.