1,721,016 research outputs found
Visual Attention Cut Points Predicting Fitness to Drive in People With Parkinson’s Disease
No full textAbstract
Date Presented 4/1/2017
People with Parkinson’s disease (PD) have impaired visual attention affecting driver fitness. This study presents cut points to demonstrate that visual attention is an early and persistent impairment in PD drivers and accurately predicts failing or passing an on-road assessment.
Primary Author and Speaker: Sherrilene Classen
Contributing Authors: Karla Crawford, Sarah Jenniex</jats:p
Relationships Among Vision, Visual Attention, and Fitness to Drive in Adults With Multiple Sclerosis
No full textAbstract
Date Presented 4/1/2017
We quantified the relationships among visual abilities, visual attention, and fitness to drive in 30 adults with multiple sclerosis. Visual acuity and visual processing speed correlated with critical driving errors (predictive of crashes) may be useful to identify potential at-risk drivers.
Primary Author and Speaker: Sarah Krasniuk
Contributing Authors: Sherrilene Classen, Sarah A. Morrow</jats:p
Driving Intervention for Returning Combat Veterans: Interim Analysis of a Randomized Controlled Trial
No full textAbstract
Date Presented 3/31/2017
Motor vehicle collisions are a leading cause of deaths for combat veterans, and effective occupational therapy driving interventions (OT–DIs) are needed. We conducted an analysis of an efficacy trial comparing an OT–DI with traffic safety education and demonstrated a reduction in driving errors for the OT–DI group.
Primary Author and Speaker: Sherrilene Classen
Additional Authors and Speakers: Sandra Winter
Contributing Authors: Charles Levy, Abraham Yarney, Miriam Monahan</jats:p
Grounded Theory Focus Group Findings in Combat Veterans With Driving Performance Issues
No full textAbstract
Date Presented 3/30/2017
Combat veterans (CVs) face an increased risk of motor vehicle crash and report driving difficulty that impacts community reintegration. Grounded theory methods were used to examine CVs’ driving perception and behaviors. Clinicians working with this population can use findings to tailor interventions.
Primary Author and Speaker: Sherrilene Classen
Additional Authors and Speakers: Sandra Winter
Contributing Authors: Cassie McGowan, Charles Levy, Miriam Monahan, Abraham Yarney</jats:p
An Open-Road Driving Performance Task to Examine Long-Term Medical Marijuana Use and Prescription Opioid Positivity Among Adults Aged 50 Years and Older: Protocol for an Observational Trial
No full textBackgroundDriving performance involves multiple underlying components of psychomotor functioning, such as attention, executive functions, and vehicle control. While the effects of acute medical marijuana and prescription opioid intoxication are known, how long-term use of medical marijuana under real-world conditions affects driving performance is unknown. Additionally, there are numerous ongoing physical and cognitive changes that affect driving performance with age. Given the proliferation of medical marijuana and prescription opioid use in adults aged 50 years and older, the prevalence of polypharmacy, and declining functional abilities, it is imperative to understand the long-term effects of daily medical marijuana use. Further, we need to understand how co-occurring use of medical marijuana and prescription opioids, in the presence of comorbidities such as chronic pain, affects real-world driving outcomes.
ObjectiveThis study aims to document the observational trial protocol. The primary goal of this study is to identify the effects of daily long-term (ie, use for >12 months daily or most days of the week) medical marijuana use on driving performance outcomes using an open-road driving performance task under real-world conditions in adults aged 50 years and older who endorse chronic or severe nonmalignant pain and to examine the combined effect of daily long-term medical marijuana use and prescription opioid use on driving outcomes. A secondary goal is to qualitatively explore self-regulation of medical marijuana and prescription opioid use in this population.
MethodsWe plan to test medical marijuana use as the exposure variable in adults aged 50 years and older on an open-road driving task performance as the primary outcome. The study will detail tetrahydrocannabinol exposure through ecological momentary assessment and urinalysis and will compare performance with a race-sex–matched group of non–marijuana users.
ResultsThis study is funded by a grant from the National Institute on Drug Abuse (5R01DA057965). Recruitment began on May 19, 2025. As of November 2025, a total of 30 participants had been enrolled. Recruitment is anticipated to be completed by 2029. Publication of the complete results and data from this study is expected by 2030.
ConclusionsData from this study will identify the effects of long-term medical marijuana use and the combined effect of that use with prescription opioids to develop risk screening protocols and intervention targets for this population. The development and dissemination of screening and intervention guidelines will be the next step in this work.
Trial RegistrationClinicalTrials.gov NCT06995937; https://www.clinicaltrials.gov/study/NCT06995937
International Registered Report Identifier (IRRID)DERR1-10.2196/7794
Driving with Parkinson’s disease: Cut points for clinical predictors of on-road outcomes
No full textBackground. Parkinson’s disease (PD) is a common neurodegenerative disorder that impacts a person’s fitness to drive. Practitioners require a sensitive and predictive battery of clinical tests to identify at-risk drivers. Purpose. This study aimed to identify clinical predictors and their optimal cut points, sensitivity, specificity, and predictive values of on-road outcomes in drivers with PD. Method. Participants ( N = 101) underwent a comprehensive driving evaluation. We identified predictors of pass/fail outcomes through logistic regression and computed optimal cut points through receiver operating characteristic curves and corresponding Youden indexes. Findings. The Trail Making Test Part B (Trails B; sensitivity = .89, specificity = .74; positive predictive value [PPV] = .71; negative predictive value [NPV] = .91) and contrast sensitivity (sensitivity = .82, specificity = .63; PPV = .61; NPV = .84) emerged as significant predictors. The optimal cut point for the Trails B was 108 s (area under the curve = .86). Implications. Occupational therapists can benefit from implementing Trails B and contrast sensitivity screening as part of in-office screening of potentially at-risk drivers with PD. </jats:sec
Develop and Validate a Survey to Assess Adult’s Perspectives on Autonomous Ridesharing and Ridehailing Services
No full textAutonomous vehicles (AVs) have generated excitement for the future of transportation. Public transit agencies and companies (i.e., Uber) have begun developing shared autonomous transportation services. Most AV surveys focus on public opinion of perceived benefits and concerns of AVs but are not directly tied to field implementation of AVs. Experience and exposure to new technology affect adults’ perceptions and level of technology acceptance. As such, the Autonomous RideShare Services Survey (ARSSS) was developed to assess adults’ perceptions of AVs before and after being exposed to AVs. Face validity and content validity were established via focus groups and subject-matter experts (CVI = 0.95). Adults in the U.S. (N = 553) completed the ARSSS, and a subsample (N = 100) completed the survey again after two weeks. An exploratory and confirmatory factor analysis demonstrated that the ARSSS consists of three factors that can be used to reliably quantify users’ perceptions of AVs: (a) Intention to Use, Trust, and Safety (r = 0.85, p p p < 0.001, ICC = 0.96) of AVs. These are key factors in predicting intention to use and acceptance of AVs. Results from the ARSSS may inform the acceptance among users of these AV technologies
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