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.

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.

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.

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.

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.

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.

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.

Participatory needs assessment and action planning for a clinical and translational research network.

The goal of this study was to assess the utility of participatory needs assessment processes for continuous improvement of developing clinical and translational research (CTR) networks. Our approach expanded on evaluation strategies for CTR networks, centers, and institutes, which often survey stakeholders to identify infrastructure or resource needs, using the case example of the Great Plains IDeA-CTR Network. Our 4-stage approach (i.

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.

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.

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.

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.

Neurophysiologic and ophthalmic markers of chemotherapy-related cognitive impairment in patients diagnosed with hematologic cancer: A feasibility study.

Background: Biomarkers of chemotherapy-related cognitive impairment (CRCI) in hematologic cancer are understudied and underdeveloped. We evaluated the feasibility of using ophthalmic and neurophysiologic markers to assess CRCI in hematologic cancer.

Methods: Hematologic cancer patients either receiving (Ctx+) or not receiving (Ctx-) chemotherapy were recruited from a tertiary medical center.

Real-world risk exposure in older drivers with cognitive and visual dysfunction.

This study addresses the need to measure and monitor objective, real-world driver safety behavior in at-risk drivers with age-related dysfunction. Older drivers are at risk for age-related cognitive and visual dysfunction, which may reduce mobility and increase errors that lead to crashes. Understanding patterns of real-world behavior, exposure, and cognitive-perceptual processes underlying risk in environmental context and in older drivers requires new approaches.

Quantifying vehicle control from physiology in type 1 diabetes.

Our goal is to measure real-world effects of at-risk driver physiology on safety-critical tasks like driving by monitoring driver behavior and physiology in real-time. Drivers with type 1 diabetes (T1D) have an elevated crash risk that is linked to abnormal blood glucose, particularly hypoglycemia. We tested the hypotheses that (1) T1D drivers would have overall impaired vehicle control behavior relative to control drivers without diabetes, (2) At-risk patterns of vehicle control in T1D drivers would be linked to at-risk, in-vehicle physiology, and (3) T1D drivers would show impaired vehicle control with more recent hypoglycemia prior to driving.

Road Weather Condition Estimation Using Fixed and Mobile Based Cameras.

Automated interpretation and understanding of the driving environment using image processing is a challenging task, as most current vision-based systems are not designed to work in dynamically-changing and naturalistic real-world settings. For instance, road weather condition classification using a camera is a challenge due to high variance in weather, road layout, and illumination conditions. Most transportation agencies, within the U.

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.

Driving Safety and Real-Time Glucose Monitoring in Insulin-Dependent Diabetes.

Our goal is to address the need for driver-state detection using wearable and in-vehicle sensor measurements of driver physiology and health. To address this goal, we deployed in-vehicle systems, wearable sensors, and procedures capable of quantifying real-world driving behavior and performance in at-risk drivers with insulin-dependent type 1 diabetes mellitus (DM). We applied these methodologies over 4 weeks of continuous observation to quantify differences in real-world driver behavior profiles associated with physiologic changes in drivers with DM (N=19) and without DM (N=14).

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.

CONTEXTUALIZING NATURALISTIC DRIVING DATA IN A RURAL STATE AMONG DRIVERS WITH AND WITHOUT OBSTRUCTIVE SLEEP APNEA.

In naturalistic studies, Global Positioning System (GPS) data and date/time stamps can link driver exposure to specific environments (e.g., road types, speed limits, night driving, etc.

Data and methods for studying commercial motor vehicle driver fatigue, highway safety and long-term driver health.

This article summarizes the recommendations on data and methodology issues for studying commercial motor vehicle driver fatigue of a National Academies of Sciences, Engineering, and Medicine study. A framework is provided that identifies the various factors affecting driver fatigue and relating driver fatigue to crash risk and long-term driver health. The relevant factors include characteristics of the driver, vehicle, carrier and environment.

DRIVING PERFORMANCE AND DRIVER STATE IN OBSTRUCTIVE SLEEP APNEA: WHAT CHANGES WITH POSITIVE AIRWAY PRESSURE?

We evaluated naturalistic driving in 65 drivers with obstructive sleep apnea (OSA) before and after positive airway pressure (PAP) therapy and in 43 comparison drivers. Driving performance metrics included speed (mean, variability), and lateral, and longitudinal acceleration (g's). Driver state measures included sleepiness and attention to the driving task based on sampled trigger and baseline video clips.