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The operation of a motor vehicle under the influence of alcohol poses a significant risk to the safety of the driver, passengers, and other road users. Electrooculographic (EOG) signal analysis can be used to understand the movements and behavior of the eyes while driving. In our study, we used smart glasses to collect EOG data from nine participants who used a driving simulator. Their level of alcoholic intoxication was simulated by drunk vision goggles at three different levels of inebriation (0, 1, 2, and 3‰ blood alcohol content). We used machine learning algorithms (decision trees, support vector machines, nearest-neighbor classifiers, boosted trees, bagged trees, subspace discriminant classifier, subspace k nearest-neighbor classifier, and RUSBoosted Trees) to analyze the data. The Bagged Trees achieved the highest accuracy of 79%. The most important features to detect simulated alcohol intoxication were the blink rate and the velocity of the saccade, a rapid simultaneous movement of both eyes in the same direction. Our study shows the potential of using smart glasses and machine learning for the automated detection of alcohol intoxication, even when alcohol consumption is simulated.

Vehicular air pollution has created an ongoing air quality and public health crisis. Despite growing knowledge of racial injustice in exposure levels, less is known about the relationship between the production of and exposure to such pollution. This study assesses pollution burden by testing whether local populations' vehicular air pollution exposure is proportional to how much they drive. Through a Los Angeles, California case study we examine how this relates to race, ethnicity, and socioeconomic status---and how these relationships vary across the region. We find that, all else equal, tracts whose residents drive less are exposed to more air pollution, as are tracts with a less-White population. Commuters from majority-White tracts disproportionately drive through non-White tracts, compared to the inverse. Decades of racially-motivated freeway infrastructure planning and residential segregation shape today's disparities in who produces vehicular air pollution and who is exposed to it, but opportunities exist for urban planning and transport policy to mitigate this injustice.

• Acute MA use (but not abuse) may lead to temporary cognitive enhancements. • Chronic MA use is associated with cognitive and self-regulatory impairment. • Chronic MA use may lead to increased hostility and aggression. • MA related psychopathology may increase the effects on cognition and behaviour. • Both driving performance and behaviour are likely impacted by chronic MA use. Methamphetamine (MA) users are over-represented in vehicle crash statistics but under-represented in the road safety research literature. This systematic review evaluates the current research base relating to MA use and its associated cognitive-behavioural outcomes; and aims to discuss the implications that these findings may have towards driving and future road safety research directions. Following PRISMA guidelines, a literature search was conducted on research studies using six different databases. Inclusion criteria were acute and chronic MA use in humans, with outcome variables relating to cognitive performance, behavioural tendencies, or psychopathology. Primary exclusion criteria included outcomes that were not directly translatable to road safety outcomes (e.g., health) or very specific samples that may have confounded the effects of MA use (e.g., prisoners). In total, 101 publications met the criteria for inclusion in the review. The literature showed that firstly, acute use (but not abuse) of MA may lead to cognitive enhancements, although these findings are not likely translatable to real-world use. Secondly, evidence suggested that chronic MA use is associated with cognitive impairments, self-regulatory difficulties, and increased aggression, suggesting that MA users may be at a significantly increased risk on the road, in a variety of domains. In addition, chronic MA use has been linked to a range of psychological issues (e.g., psychosis; anxiety; depression), which may exacerbate the negative cognitive-behavioural effects of MA. Finally, abstinence from MA was shown to reduce the aversive impacts of chronic MA use, although cognitive improvements have been demonstrated to take much longer, compared to behavioural and psychopathology conditions. The limitations associated with the current MA literature base were evaluated and methodological suggestions were made for future research to better understand the effect of MA use patterns on driving performance and behaviour. [ABSTRACT FROM AUTHOR]

• Investigated mental workload and fatigue of the drivers using EEG. • Conducted experiments in authentic driving environments involving 39 participants. • Revealed higher mental workload on local street with heavy traffic and highway. • Mental fatigue index was correlated with the mental workload indexes. • Established that drivers with more experience exhibited lower mental workload. The safety and performance of automobile drivers depend on many factors. The mental status of the drivers is the foremost factor in ensuring driving safety, in addition to physical elements. Studies with drivers are generally conducted in driving simulators or with scenarios close to actual driving. This study investigated the mental workload of drivers by analyzing electroencephalography data recorded in totally spontaneous real driving tasks, to determine the effect of different road conditions and driving experience. Two mental workload indexes (Frontal Theta/Parietal Alpha and Frontal Midline Theta) and a mental fatigue index (Alpha + Theta/Beta) were calculated using the band powers. Drivers were found to experience a higher mental workload in road sections with heavy traffic and variable road parameters by analyzing EEG data in real traffic. The correlation coefficients between the fatigue index and the two workload indexes were found to be 0.577 and 0.678, respectively. The workload decreased with increasing driving experience. Therefore, having experienced drivers perform commercial driving tasks can ensure safer driving. By employing novel methods to handle real-world EEG data, autonomous driving systems can also benefit. [ABSTRACT FROM AUTHOR]

Older adults with type 1 diabetes may face challenges driving safely. Glucose "above-5-to-drive" is often recommended for insulin-treated diabetes to minimize hypoglycemia while driving. However, the effectiveness of this recommendation among older adults has not been evaluated. Older drivers with type 1 diabetes were assessed while using sensor-augmented insulin pumps during a 2-week clinical trial run-in. Twenty-three drivers (median age 69 years [interquartile range; IQR 65–72]; diabetes duration 37 years [20–45]) undertook 618 trips (duration 10 min [5–21]). Most trips (n = 535; 87%) were <30 min duration; 9 trips (1.5%) exceeded 90 min and 3 trips (0.5%) exceeded 120 min. Pre-trip continuous glucose monitoring (CGM) was >5.0 mmol/L for 577 trips (93%) and none of these had CGM <3.9 mmol/L during driving (including 8 trips >90 min and 3 trips >120 min). During 41 trips with pre-trip CGM ≤5.0 mmol/L, 11 trips had CGM <3.9 mmol/L. Seventy-one CGM alerts occurred during 60 trips (10%), of which 54 of 71 alerts (76%) were unrelated to hypoglycemia. Our findings support a glucose "above-5-to-drive" recommendation to avoid CGM-detected hypoglycemia among older drivers, including for prolonged drives, and highlight the importance of active CGM low-glucose alerts to prevent hypoglycemia during driving. Driving-related CGM usability and alert functionality warrant investigation. Clinical trial ACTRN1261900515190 [ABSTRACT FROM AUTHOR]

Summary: The Maintenance of Wakefulness Test is widely used to objectively assess sleepiness and make safety‐related decisions, but its interpretation is subjective and normative values remain debated. Our work aimed to determine normative thresholds in non‐subjectively sleepy patients with well‐treated obstructive sleep apnea, and to assess intra‐ and inter‐scorer variability. We included maintenance of wakefulness tests of 141 consecutive patients with treated obstructive sleep apnea (90% men, mean (SD) age 47.5 (9.2) years, mean (SD) pre‐treatment apnea–hypopnea index of 43.8 (20.3) events/h). Sleep onset latencies were independently scored by two experts. Discordant scorings were reviewed to reach a consensus and half of the cohort was double‐scored by each scorer. Intra‐ and inter‐scorer variability was assessed using Cohen's kappa for 40, 33, and 19 min mean sleep latency thresholds. Consensual mean sleep latencies were compared between four groups according to subjective sleepiness (Epworth Sleepiness Scale score < versus ≥11) and residual apnea–hypopnea index (< versus ≥15 events/h). In well‐treated non‐sleepy patients (n = 76), the consensual mean (SD) sleep latency was 38.4 (4.2) min (lower normal limit [mean – 2SD] = 30 min), and 80% of them did not fall asleep. Intra‐scorer agreement on mean sleep latency was high but inter‐scorer was only fair (Cohen's kappa 0.54 for 33‐min threshold, 0.27 for 19‐min threshold), resulting in changes in latency category in 4%–12% of patients. A higher sleepiness score but not the residual apnea–hypopnea index was significantly associated with a lower mean sleep latency. Our findings suggest a higher than usually accepted normative threshold (30 min) in this context and emphasise the need for more reproducible scoring approaches. [ABSTRACT FROM AUTHOR]

Situation awareness (SA) describes an individual's understanding of their surroundings and actions in the near future based on the individual's comprehension and understanding of the surrounding inputs. SA measurements can be applied to improve system performance or human effectiveness in many fields of study, including driving. However, in some scenarios drivers might need to drive in unfamiliar traffic regulations (UFTRs), where the traffic rules and vehicle configurations are a bit different from what the drivers are used to under familiar traffic regulations. Such driving conditions require drivers to adapt their attention, knowledge, and reactions to safely reach the destination. This ability is influenced by the degree of handedness. In such tasks, mixed-/left-handed people show better performance than strong right-handed people. This paper aims to explore the influence of the degree of handedness on SA when driving under UFTRs. We analyzed the SA of two groups of drivers: strong right-handed drivers and mixed-/left-handed drivers. Both groups were not familiar with driving in keep-left traffic regulations. Using a driving simulator, all participants drove in a simulated keep-left traffic system. The participants' SA was measured using a subjective assessment, named the Participant Situation Awareness Questionnaire PSAQ, and performance-based assessment. The results of the study indicate that mixed-/left-handed participants had significantly higher SA than strong right-handed participants when measured by performance-based assessment. Also, in the subjective assessment, mixed-/left-handed participants had significantly higher PSAQ performance scores than strong right-handed participants. The findings of this study suggest that advanced driver assistance systems (ADAS), which show improvement in road safety, should adapt the system functionality based on the driver's degree of handedness when driving under UFTRs. [ABSTRACT FROM AUTHOR]

Background: Driving is the preferred mode of transportation for adults across the healthy age span. However, motor vehicle crashes are among the leading causes of injury and death, especially for older adults, and under distracted driving conditions. Understanding the neuroanatomical basis of driving may inform interventions that minimize crashes. This exploratory study examined the neuroanatomical correlates of undistracted and distracted simulated straight driving. Methods: One-hundred-and-thirty-eight participants (40.6% female) aged 17-85years old (mean and SD= 58.1± 19.9years) performed a simulated driving task involving straight driving and turns at intersections in a city environment using a steering wheel and foot pedals. During some straight driving segments, participants responded to auditory questions to simulate distracted driving. Anatomical T1-weighted MRI was used to quantify grey matter volume and cortical thickness for five brain regions: the middle frontal gyrus (MFG), precentral gyrus (PG), superior temporal cortex (STC), posterior parietal cortex (PPC), and cerebellum. Partial correlations controlling for age and sex were used to explore relationships between neuroanatomical measures and straight driving behavior, including speed, acceleration, lane position, heading angle, and time speeding or off-center. Effects of interest were noted at an unadjusted p-value threshold of 0.05. Results: Distracted driving was associated with changes in most measures of straight driving performance. Greater volume and cortical thickness in the PPC and cerebellum were associated with reduced variability in lane position and heading angle during distracted straight driving. Cortical thickness of the MFG, PG, PPC, and STC were associated with speed and acceleration, often in an agedependent manner. Conclusion: Posterior regions were correlated with lane maintenance whereas anterior and posterior regions were correlated with speed and acceleration, especially during distracted driving. The regions involved and their role in straight driving may change with age, particularly during distracted driving as observed in older adults. Further studies should investigate the relationship between distracted driving and the aging brain to inform driving interventions. [ABSTRACT FROM AUTHOR]

Objectives To assess if brake response times are altered pre and post CT-guided cervical spine nerve root injections. Methods Brake response times were assessed before and after CT-guided cervical spine nerve root injections in a cohort of patients. The average of 3 brake response times was recorded before and 30 min after injection. Statistical analysis was performed using GraphPad. A paired Student t -test was used to compare the times before and after the injections. Results Forty patients were included in this study. The mean age was 55 years. There were 17 male and 23 female patients. There was no significant difference in the mean pre and post CT-guided cervical spine nerve root injection brake response times; 0.94 s (range 0.4-1.2 s) and 0.93 s (range 0.5-1.25 s), respectively (P  = .77). Conclusions Brake response time did not significantly differ pre and 30 min post CT-guided cervical spine nerve root injections. Advances in knowledge To the authors' best knowledge, there are no current studies assessing brake response times post CT-guided cervical spine nerve root injections. While driving safety cannot be proven by a single metric, it is a useful study in demonstrating that this is not inhibited in a cohort of patients. [ABSTRACT FROM AUTHOR]

• We developed a measure (The DARS) of the ability to regulate attention on the road. • The DARS demonstrated a valid and reliable three factor solution across 15 items. • The DARS was positively associated with driver confidence and attentional control. • The DARS was negatively associated with driver stress and emotion dysregulation. • The DARS predicted driver mistakes but not necessarily risky driving behaviour. The ability to regulate attention while driving is a vital skill for remaining safe on the road. However, there is no current self-report method that measures such a construct, potentially limiting research in the area of attention and distraction. This study aimed to develop and validate a new measure, the Driver Attention Regulation Scale (DARS), that can be used to identify how drivers perceive their ability to regulate attention while driving. To achieve this aim, two online surveys were shared with unique samples of Australian drivers. Following the development of an initial item pool, principal components analysis and follow up confirmatory factor analysis were used to test the structure of the items and revealed that three factors emerged: attentional presence (e.g., focus; vigilance), attentional flexibility (e.g., awareness; shifting), and attentional capacity (e.g., processing speed; cognitive resources). Each of the subscales (α = 0.75–0.88) and the total scale (α = 0.87–0.91) exhibited a good internal consistency across the samples. Evidence of external validity was also demonstrated, as the DARS was positively associated with generalised attention regulation measures, and driver confidence, but negatively associated with emotion regulation difficulties, driver stress, and driving errors/lapses. Mediation analyses also indicated that the attentional constructs measured by the DARS may indirectly influence driving behaviours, via their effect on driver stress and confidence. Overall, the DARS has demonstrated promise as a new measure of driving-related attentional skills that can be used in future research to better understand how situational factors may impact drivers' confidence, and also how confidence may influence driving behaviours (e.g., speeding). [ABSTRACT FROM AUTHOR]

• Readiness for change in mobility may be an important element in promoting smooth transitions to non-driving for older people. • Participants who reported positive attitudes towards driving relative to themselves and others were less ready for mobility transition. • Participants who reported lower agreeableness were less ready for mobility transition. For many older adults, driving is an important means of community mobility. With changes in health, aging increases the likelihood of ceasing to drive. Driving cessation is associated with a host of negative physical and mental health outcomes. Increased readiness to transition to non-driving status may mitigate some of the adverse consequences of driving cessation, making the transition to non-driving a pivotal period for intervention. We examined the relationship between attitudes towards driving (positive and negative) and readiness for mobility transition. Participants (n = 253, mean age = 79.13) completed measures of health, cognition, personality, attitudes towards driving, and readiness for mobility change. The results from the multiple hierarchical regression analysis showed that individuals who reported more positive attitudes towards driving relative to themselves (i.e., pro-self scale) and others (i.e., pro-other scale), as well as scored lower on the personality trait agreeableness, were less ready for mobility transition. The results emphasize the importance of taking into account driver attitudes, in addition to health considerations, when supporting the transition to non-driving. [ABSTRACT FROM AUTHOR]

Background: The advent of industrialization and the invention of the automobile have increased traffic accidents, impacting the quality of life. The purpose of this study is to evaluate the validity of the safe driving self-efficacy tool using confirmatory factor analysis (CFA) to confirm the factors extracted from the exploratory factor analysis stage and also to evaluate the reliability of this tool. Methods: This study involved 600 individuals residing in Tabriz, aged 20-50 years. The questionnaire utilized in this study was a researcher-made tool and evaluated for structural validity, goodness-of-fit, and internal consistency. Construct validity was tested using the first and second-order CFA using AMOS23 software. The internal reliability of the questionnaire was determined based on Cronbach's alpha coefficient (a > 0.7). Results: The study analyzed 589 questionnaires from 600 participants, with a mean age of 35.04 years (SD = 8.367). The majority of respondents had a driving experience and a history of traffic accidents, primarily within urban areas. The CFA also confirmed five factors with 42 questions, which showed positive results. The value of Cronbach's alpha coefficient for all factors was more than 0.7. Conclusion: Out of the 60 items in the questionnaire, 42 items were confirmed with appropriate goodness-of-fit indicators. The amalgamation of these constructs within the model effectively measures the concept of safe driving self-efficacy, thereby establishing the tool's reliability. As a result, this survey can serve as a valuable benchmark for evaluating individuals' self-efficacy concerning safe driving practices. [ABSTRACT FROM AUTHOR]

A major challenge in assessing psychological constructs such as impulsivity is the weak correlation between self-report and behavioral task measures that are supposed to assess the same construct. To address this issue, we developed a real-time driving task called the "highway task," in which participants often exhibit impulsive behaviors mirroring real-life impulsive traits captured by self-report questionnaires. Here, we show that a self-report measure of impulsivity is highly correlated with performance in the highway task but not with traditional behavioral task measures of impulsivity (47 adults aged 18–33 years). By integrating deep neural networks with an inverse reinforcement learning (IRL) algorithm, we inferred dynamic changes of subjective rewards during the highway task. The results indicated that impulsive participants attribute high subjective rewards to irrational or risky situations. Overall, our results suggest that using real-time tasks combined with IRL can help reconcile the discrepancy between self-report and behavioral task measures of psychological constructs. [ABSTRACT FROM AUTHOR]

Background: Decisions about driving for individuals living with dementia (ILWD) can be challenging. There are limited evidence‐based person‐centred interventions in the United Kingdom that support decisions about transitioning to not driving or guidelines for developing decision aids for ILWD. This study aimed to understand the important features of a decision aid through the cultural adaptation of Australian dementia and driving decision aid (DDDA) for ILWD residing in the United Kingdom. Methods: This qualitative study was theoretically underpinned by a person‐centred framework and conducted over three stages: (1) Development of a draft UK‐specific DDDA; (2) semistructured interviews with ILWD and an online survey with stakeholders to obtain their views on a draft UK DDDA and (3) content analysis and synthesis of qualitative data to inform the final version of the decision aid. Results: Eleven ILWD and six of their spouses participated in interviews, and 102 stakeholders responded to an online survey. The four broad features identified as important to include in a decision aid for drivers living with dementia were: a structured and interactive format; positive and supportive messaging and presentation; relevant and concise content and choice‐centred. The perceived benefits of the decision aid were identified as supporting conversations, enhancing collaborative decision making and enabling agency with decisions about driving and future mobility options. Conclusions: Decision aids that are underpinned by interactive choice‐driven questions enhance a person‐centred approach to decisions about driving. Positively framing decision aids through the presentation and content can facilitate engagement with the decision‐making process about driving. The findings have implications for the development of decision aids designed for ILWD on other important health and social topics. Patient and Public Involvement: Advocating for the development of a UK DDDA were ILWD. Healthcare professionals contributed to the development of a draft UK DDDA. Former and current drivers living with dementia, family members, healthcare professionals and other support networks of ILWD participated in interviews or an online survey which informed the final version of the UK DDDA. [ABSTRACT FROM AUTHOR]

Driving requires vision, yet there is little empirical data about how vision and cognition support safe driving. It is difficult to study perception during natural driving because the experimental rigor required would be dangerous and unethical to implement on the road. The driving environment is complex, dynamic, and immensely variable, making it extremely challenging to accurately replicate in simulation. Our proposed solution is to study vision using stimuli which reflect this inherent complexity by using footage of real driving situations. To this end, we curated a set of 750 crowd-sourced video clips (434 hazard and 316 no-hazard clips), which have been spatially, temporally, and categorically annotated. These annotations describe where the hazard appears, what it is, and when it occurs. In addition, perceived dangerousness changes from moment to moment and is not a simple binary detection judgement. To capture this more granular aspect of our stimuli, we asked 48 observers to rate the perceived hazardousness of 1356 brief video clips taken from these 750 source clips on a continuous scale. These ratings span the entire scale, have high interrater agreement, and are robust to driving history. This novel stimulus set is not only useful for understanding drivers' ability to detect hazards, but is also a tool for studying dynamic scene perception and other aspects of visual function. While this stimulus set was originally designed for behavioral studies, researchers interested in other areas such as traffic safety or computer vision may also find this dataset a useful resource. [ABSTRACT FROM AUTHOR]

Driving is a visual task and as such it is essential that drivers have good vision out of their vehicles particularly on today's busy roads. However, rear vision is not always optimum; rear passengers, luggage or the design of the car itself can all impair rear vision. A new camera-based rear view mirror is described in this paper. The system was developed by employing user-centred design methods; requirements for the system were established and a prototype was then tested dynamically with drivers' feedback then used to improve and finalise the design. [ABSTRACT FROM AUTHOR]

Background and Objectives Driving retirement can be a necessary but challenging and emotionally complex transition, especially for people living with dementia. This pilot study evaluated the utility of CarFreeMe™-Dementia (CFM™-D), a telehealth intervention providing tailored education and social support to those living with dementia and their care partners, as they prepare for or adjust to driving retirement. Delivered by empathetic health professionals, CFM™-D is a person-centric, flexible program tailored to address challenges specific to the participants' driving retirement stage and individualized contexts. Research Design and Methods A single-arm, mixed-methods design was used to follow participants over a 6-month period. Participants received CFM™-D, a 7–8-module semistructured intervention, including education and planning support for driving retirement (impact of dementia, transportation options) and emotional adjustment (grief and loss, stress management). Surveys evaluated the perceived utility of intervention components as well as changes in well-being and readiness for driving retirement over time. An open-ended survey item and semistructured interviews provided additional feedback and a contextual understanding of the empirical data. Results A total of 50 families enrolled (17 care partners, 16 retiring/retired drivers with memory loss, and 17 care partner-retiring/retired driver dyads). Nearly all participants would recommend the intervention. Care partners reported significantly reduced (p  < .05) isolation and relationship strain, and retiring drivers reported significant reductions in depressive symptoms. Driving retirement preparedness scores improved. Driving retirement phase, enrolling as a dyad, and retiring driver cognitive/functional impairment were associated with these outcomes. Participants also engaged in more driving retirement activities outside of the intervention (e.g. talking with health professionals). Discussion and Implications CFM™-D is a useful intervention for retiring drivers with dementia and their family members, with preliminary data suggesting it supports improved well-being and driving retirement preparedness. A randomized controlled trial is needed to determine the efficacy of the CFM™-D intervention and future translation needs. [ABSTRACT FROM AUTHOR]

This study examines the relationship of decisional conflict about driving habits between older adult drivers (≥70 years old) and their family members and close friends. This secondary analysis utilizes data originating from a multi-site randomized controlled trial assessing the effect of a driving decision aid (DDA) intervention. Decisional conflict about stopping or changing driving habits for drivers was measured with the Decisional Conflict Scale (DCS). Dyadic associations between drivers' and study partners' (SPs') DCS scores were analyzed using an actor-partner interdependence model. Among 228 driver-SP dyads, Dyadic DCS was correlated at baseline (r =.18, p <.01), and pre-intervention DCS was associated with post-intervention DCS (p <.001 for SPs [β =.73] and drivers [β =.73]). Drivers' baseline DCS and SPs' post-intervention DCS were slighly correlated (β =.10; p =.036). Higher decisional conflict about driving among older drivers is frequently shared by their SPs. Shared decisional conflict may persist beyond intervening to support decision-making about driving cessation. [ABSTRACT FROM AUTHOR]

Background and objectives: Research on driving ability in people with multiple sclerosis (MS) suggests that they might be at risk for unsafe driving due to MSrelated motor, visual, and cognitive impairment. Our first aim was to investigate differences in driving ability and performance between people with MS (PwMS) and those without any neurologic or psychiatric disease ("controls"). Secondly, we determined disease-related factors influencing driving ability in PwMS. Methods: We prospectively compared standardized performance in a driving simulator between 97 persons with early MS [mean (SD) = 6.4 (7.3) years since diagnosis, mean (SD) Expanded Disability Status Scale (EDSS) = 2.5 (1.4)] and 94 group-matched controls. Participants completed an extensive examination comprising questionnaires and assessments regarding driving, cognitive and psychological factors, as well as demographic and disease-related measures. Between-group comparisons of driving-relevant neuropsychological tests and driving performance were done. Correlations were performed to define demographic and disease-related factors on driving performance in MS. Results: In a driving simulator setting, PwMS had more driving accidents [T(188) = 2.762, p = 0.006], reacted slower to hazardous events [T(188) = 2.561, p = 0.011], made more driving errors [T(188) = 2.883, p = 0.004] and had a worse Driving Safety Score (DSS) [T(188) = 3.058, p = 0.003] than controls. The only disease-related measure to be associated with most driving outcomes was the Wechsler Block-Tapping test (WMS-R) backward: number of accidents (r = 0.28, p = 0.01), number of driving errors (r = 0.23, p = 0.05) and DSS (r = -0.23, p = 0.05). Conclusion: Driving performance in a simulator seems to be reduced in PwMS at an early stage of disease compared to controls, as a result of increased erroneous driving, reduced reaction time and higher accident rate. MS-related impairment in mobility, vision, cognition, and in psychological and demographic aspects showed no or only minimal association to driving ability, but impairment in different areas of cognition such as spatial short-term memory, working memory and selective attention correlated with the number of accidents, and might indicate a higher risk for driving errors and worse performance. These results show that driving ability is a complex skill with involvement of many different domains, which need further research. [ABSTRACT FROM AUTHOR]

Drug-impaired driving is a growing problem in the U.S. States regulate drug-impaired driving in different ways. Some do not name specific drugs or amounts. Others do identify specific drugs and may regulate cannabis separately. We provide up-to-date information about these state laws. [ABSTRACT FROM AUTHOR]

Background and objectives: Work addiction (WA), characterized by dimensions such as over-commitment, difficulties in detachment from work, and work-life imbalance, is presumed to be associated with increased smartphone usage, even during risky activities like driving. The study investigated the connection between WA and future problematic and hazardous smartphone use, considering personality factors: anxiety, rumination, and worry. Methods: A three-wave longitudinal study (N 5 1,866) was conducted from March to July 2019, June to September 2020, and June to November 2021, involving a representative sample of 18-34-year-old residents in Hungary's capital. The study employed Hungarian versions of the Bergen Work Addiction Scale, Problematic Mobile Phone Use Questionnaire, Ruminative Response Scale, Anxiety subscale of the Brief Symptom Inventory 18, and Penn-State Worry Questionnaire. Additionally, author-developed questions on mobile phone use while driving were included. Results: At baseline, those at risk for WA showed more frequent mobile phone use while driving at both time points 2 and 3 compared to the non-risk group. Path analyses revealed rumination, anxiety at time 1, and worry at time 2 as significant mediators between baseline WA and mobile phone use while driving at time 3. However, when analyzing all three mediators together, only anxiety at time 1 and worry at time 2 remained significant. Discussion and conclusion: This study demonstrates that WA predicts future mobile phone use while driving through mediation by anxiety and worry. Our findings add to the growing evidence highlighting the detrimental aspects of WA, emphasizing the need for improved prevention and treatment strategies. [ABSTRACT FROM AUTHOR]

Background: Information on recent alcohol-related non-fatal motor vehicle crash (MVC) injuries is limited. Objectives: To analyze alcohol-related non-fatal MVC injuries, 2019–2022, considering COVID-19 and Stay-at-Home policies. Methods: State-level counts of alcohol-related non-fatal MVC injuries (involving individuals age 15+) from Emergency Medical Services data in 18 US states, chosen for comprehensive coverage, were analyzed for the annual rate. The total non-fatal MVC injury count in each state served as the denominator. We used analysis of variance to evaluate annual rate changes from 2019 to 2022 and used robust Poisson regression to compare annual mean rates to the 2019 baseline, pre-pandemic, excluding Quarter 1 due to COVID-19's onset in Quarter 2. Additional Poisson models compared rate changes by 2020 Stay-at-Home policies. Results: Data from 18 states were utilized (N = 1,487,626, 49.5% male). When evaluating rate changes of alcohol-related non-fatal MVC injuries from period 1 (Q2–4 2019) through period 4 (Q2–4 2022), the rate significantly increased from period 1 (2019) to period 2 (2020) by 0.024 (p =.003), then decreased from period 2 to period 4 (2022) by 0.016 (p =.04). Compared to the baseline (period 1), the rate in period 2 was 1.27 times higher. States with a 2020 Stay-at-Home policy, compared to those without, had a 30% lower rate (p =.05) of alcohol-related non-fatal MVC injuries. States with partial and mandatory Stay-at-Home policies had a 5.2% (p =.01) and 10.5% (p <.001) annual rate decrease, respectively. Conclusion: Alcohol-related non-fatal MVC injury rates increased initially (2019–2020) but decreased thereafter (2020–2022). Stay-at-home policies effectively reduced these rates. [ABSTRACT FROM AUTHOR]

Background: Motor/nonmotor symptomatology and antiparkinsonian drugs deteriorate the driving ability of Parkinson's disease (PD) patients. Objectives: Treating neurologists are frequently asked to evaluate driving fitness of their patients and provide evidence‐based consultation. Although several guidelines have been published, the exact procedure along with the neurologist's role in this procedure remains obscure. Methods: We systematically reviewed the existing guidelines, regarding driving fitness evaluation of PD patients. We searched MEDLINE and Google Scholar and identified 109 articles. After specified inclusion criteria were applied, 15 articles were included (nine national guidelines, five recommendation papers, and one consensus statement). Results: The treating physician is proposed as the initial evaluator in 8 of 15 articles (neurologist in 2 articles) and may refer patients for a second‐line evaluation. The evaluation should include motor, cognitive, and visual assessment (proposed in 15, 13, and 8 articles, respectively). Specific motor tests are proposed in eight articles (cutoff values in four), whereas specific neuropsychological and visual tests are proposed in seven articles each (cutoff values in four and three articles, respectively). Conditional licenses are proposed in 11 of 15 articles, to facilitate driving for PD patients. We summarized our findings on a graphic of the procedure for driving fitness evaluation of PD patients. Conclusions: Neurological aspects of driving fitness evaluation of PD patients are recognized in most of the guidelines. Motor, neuropsychological, visual, and sleep assessment and medication review are key components. Clear‐cut instructions regarding motor, neuropsychological, and visual tests and relative cutoff values are lacking. Conditional licenses and periodical reevaluation of driving fitness are important safety measures. [ABSTRACT FROM AUTHOR]

Objectives. This study examines which of the heart rate variability (HRV) and morphologic variability (MV) metrics may have the highest accuracy in different stress detection during real-world driving. Methods. The cross-sectional study was carried out among 93 intercity mini-bus male drivers aged 22–67 years. The Trillium 5000 Holter Recorder and GARMIN Virb Elite camera were used to determine heart rate and vehicle speed measurements along the path, respectively. We considered the HRV and MV metrics of electrocardiogram (ECG) signals including the mean RR interval (mRR), mean heart rate (mHR), normalized low-frequency spectrum (nLF), normalized high-frequency spectrum (nHF), normalized very low-frequency spectrum (nVLF), difference of normalized low-frequency spectrum and normalized high-frequency spectrum (dLFHF), and sympathovagal balance index (SVI). Results. The analysis showed that the HRV metrics mHR, mRR, nVLF, nLF, nHF, dLFHF and SVI are effective in mental stress detection while driving as compared to rest time. We obtained a high accuracy of stress detection for MV metrics as compared to the traditional HRV analysis, of approximately 92%. Conclusions. Our findings indicate that driver stress could be detected with an accuracy of 92% using MV metrics as an accurate physiological index of the driver's state. [ABSTRACT FROM AUTHOR]

The scientific article identifies the problems of documenting an administrative offense, the responsibility for which is provided for by Article 130 of the Code of Ukraine on Аdministrative Оffenses, and proposed ways to solve them. The author carried out an analysis of statistical data based on the results of the courts of first instance regarding the consideration of cases of administrative offenses under Article 130 of the Code of Ukraine on Administrative Offenses for the year 2023. The author has researched and summarized the judicial practice of court consideration of cases on administrative offenses, the responsibility for which is provided for in Article 130 of the Code of Ukraine on Administrative Offenses, in particular, court decisions on closing proceedings in such cases due to the absence of an event and composition of an administrative offense. It has been established that in most cases, the courts state that the police officers did not properly draw up protocols and did not follow the procedure for documenting the violation. Attention is focused on the fact that signs of intoxication must be indicated in the protocol on an administrative offense in order to substantiate the grounds for the inspection. It was established that the presence of a referral for an examination of a person for intoxication from a police officer is mandatory. It has been found that missing the terms of proceedings in such cases is often the reason for closing the case before the judge. It is emphasized that mistakes in police activity occur during video recording of an examination of the state of alcohol, drug or other intoxication or being under the influence of drugs that reduce attention and reaction speed. The author emphasizes that the low legal awareness of individual police officers leads to inaccuracies in the description of the offense in the protocol on the administrative offense and the qualification of the offender's actions. It was found that the police do not always take into account the circumstances that exempt the offender from administrative responsibility. In order to improve the procedure for documenting cases under Article 130 of the Code of Ukraine on Administrative Offenses proposed to conduct an analysis of the decisions made by the courts for such cases, to identify typical errors and to conduct additional training with police officers who document such cases, for example, within the scope of official training. The author concluded that the work on defining the problems of documenting an administrative offense, the responsibility for which is provided by Article 130 of the Code of Ukraine on Administrative Offenses, is not permanent, but should be dynamic under the control of authorized persons of the National Police, who are responsible for personnel training, professional development, and professional training of police officers. [ABSTRACT FROM AUTHOR]

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Abstract Background Functional neurological disorder (FND) is a common neurological diagnosis that encapsulates a range of incapacitating clinical presentations. These include functional seizures, movement disorders, and sensory disturbances. Safe driving requires both cognitive skills and physical abilities, which may be impacted by FND symptoms. The primary objective of this study was to gain deeper insights into the challenges faced by people with FND when driving. Methods A qualitative study and interpretative phenomenological analysis were conducted. Individuals experiencing functional seizures and/or movement disorders completed both questionnaires and semi‐structured interviews about FND symptoms, driving behavior, and crashes. Results A total of 26 patients with FND participated in this study. Based on the interviews, four key themes were identified: (1) driving difficulties experienced by individuals with FND; (2) strategies utilized by people with FND to overcome difficulties experienced while driving; (3) barriers preventing driving challenges being addressed in this population; and (4) crashes and perceived dangerous driving events experienced by individuals with FND. All participants reported that driving a car provoked FND symptoms and this affected their driving ability. FND sufferers reported using a number of strategies such as limiting how far they drive and relying on advanced driver assistance system features to help manage their associated symptoms, such as fatigue and/or pain. Several participants reported crashes and perceived dangerous driving events since developing FND. Conclusion Individuals experiencing FND often employ self‐regulation techniques, yet the extent to which these methods enhance driving safety remains uncertain. The variable nature of the disorder makes judging an individual's driving risk particularly difficult. The themes emerging from the interviews highlighted the need for further empirical research to inform guidelines and best practice when determining the impact of FND on an individual's driving safety .

The diagnosis of attention deficit hyperactivity disorder (ADHD) has been identified as a factor associated with an increased risk of involvement in car crashes. As a result, individuals in the Netherlands who are diagnosed with ADHD are mandated to undergo a psychiatric evaluation before obtaining their driving licence, optionally complemented with a driving test. Recent research has, however, demonstrated that 96% of individuals pass this procedure and can drive unrestrictedly, suggesting that current regulations have a limited impact and that a different regulatory approach may be warranted. This paper addresses three such potential interventions, exploring the scientific basis of implementing mandatory behavioural training programmes, the mandatory installation of driver monitoring systems, and temporary driving restrictions. To initiate this exploration, an analysis is made of the body of literature pointing towards a subpar driving performance in those with ADHD, accompanied by a discussion of the underlying symptoms and behaviours contributing to these findings. Furthermore, between- and within-individual factors affecting ADHD driving performance are reviewed. This examination illuminates a consistent pattern of substandard driving performances among those with ADHD, whereby the period shortly post-licensure stands out as a focal point for regulatory approaches. Following these results, the three potential driving interventions are reviewed to discern their impact on road safety when implemented specifically for drivers with ADHD. Corresponding studies suggest that all these interventions hold promise in improving driving performances, but the analysis is limited by the scarcity of long-term, ADHD-specific research. The paper concludes by discussing the feasibility of these ADHD-specific driving interventions, weighing their potential benefits, e.g., reduced crash rates, along with their associated costs, such as potential stigma and hindrance in societal integration and participation. Additionally, avenues for future research in these domains are outlined.

Background and purpose: Driving is a crucial ability that can impact the quality of life for elderly individuals. Older adults may rely more on driving compared to other age demographics. As individuals age, there are significant changes in physical, cognitive, intellectual, and emotional abilities that are crucial for driving, a skill essential for accessing healthcare, therapy services, work, and social activities, as well as maintaining independence and autonomy in the elderly. Mobility and physical exertion are crucial aspects of health for older individuals, and driving significantly contributes to their ability to move within society. The increase in the elderly population has led to a rise in the number of older drivers. Proficiency in self-efficacy in driving is a crucial ability in this profession that acknowledges the significant aspects of this issue. This study aimed to investigate the correlation between weariness, self-efficacy, and driving behavior among older drivers in an urban setting. Materials and methods: This study was a progressive and descriptive-analysis study conducted among older drivers aged 60 and older who were members of the taxi association. Three hundred and ten eligible participants were chosen using the convenience sampling approach. The data was collected using the demographic data form, the multidimensional fatigue inventory, and Adele's self-efficacy scale. The data was analyzed using descriptive statistics, multiple linear regression, and Pearson correlation tests. Results: The participants had an average age of 28.3 years with a standard deviation of 9.6 years, and their ages ranged from 60 to 75 years. 42% of the participants had university degrees. They mostly had 30 to 50 years of driving experience. The average self-efficiency in driving among older drivers was 101.87±15.74. The Pearson correlation test indicated a significant and inverse relationship between age factors, the history of the driving license, and the self-efficacy score. In other words, as age and years of driving experience increase, the likelihood of self-efficacy driving reduces substantially. The correlation between the fatigue questionnaire scores and self-driving efficiency was significant(P

Yousef D Alqurashi,1 Abdullah S Alqarni,1 Faisal Maher Albukhamsin,1 Abdullah Abdulaziz Alfaris,1 Bader Ibrahim Alhassan,1 Waleed Khalid Ghazwani,1 Abdulaziz Abdulrahman Altammar,1 Mutlaq Eid Aleid,1 Hayfa Almutary,2 Abdulelah M Aldhahir,3 Saleh A Alessy,4 Rayyan Almusally,5 Abir Alsaid,5 Mahmoud Ibrahim Mahmoud,5 Hatem Othman Qutub,5 Tunny Sebastian,6 Suliman Alghnam,7 Michael I Polkey8 1Respiratory Care Department, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia; 2Medical Surgical Nursing Department, King Abdulaziz University, Jeddah, Saudi Arabia; 3Respiratory Therapy Department, Faculty of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia; 4Department of Public Health, College of Health Sciences, Saudi Electronic University, Jeddah, Saudi Arabia; 5Internal Medicine Department, King Fahd Hospital of the University, Imam Abdulrahman Bin Faisal University, Khobar, Saudi Arabia; 6Clinical Nutrition Department, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia; 7Population Health Section-King Abdullah International Medical Research Center (KAIMRC), King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh, Saudi Arabia; 8Royal Brompton Hospital, Guy’s and St Thomas’ NHS Foundation Trust, London, UKCorrespondence: Yousef D Alqurashi, Respiratory Care Department, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, Dammam, 34221, Saudi Arabia, Email ydalqurashi@iau.edu.saIntroduction: Sleepy driving is associated with Motor Vehicles Accidents (MVAs). In Saudi Arabia, previous studies have addressed this association among men only. Therefore, the aim of this study was to compare the prevalence of sleepy driving and associated factors between genders.Methods: In a cross-sectional study design, we offered a self-administered online questionnaire to 3272 participants from different regions of Saudi Arabia. The questionnaire included 46 questions covering sociodemographics, driving habits, sleeping habits, Epworth Sleepiness Scale, and Berlin questionnaire to assess the risk of sleep apnea. Univariable and multivariable logistic regression analyses were used to determine the significant factors associated with self-reported sleepy driving, defined as operating a motor vehicle while feeling sleepy in the preceding six months.Results: Of the 3272 invitees, 2958 (90%) completed the questionnaire, of which 1414 (48%) were women. The prevalence of sleepy driving in the preceding six months was 42% (men: 50% and women 32%, p< 0.001). Specifically, participants reported the following: 12% had had to stop their vehicle due to sleepiness (men: 16.2% and women 7%, p< 0.001), 12.4% reported near-miss accidents (men: 16.2% and women: 8.2%, p< 0.001) and 4.2% reported an accident due to sleepiness (men: 4.3% and women: 4%, p=0.645). In multivariable analysis, being male, younger age, use of any type of medications, shift working, working more than 12 hours per day, driving duration of 3– 5 hours per day, driving experience of more than 2 years, excessive daytime sleepiness and risk of having obstructive sleep apnea were all associated with increased likelihood of falling asleep while driving in the preceding 6 months.Conclusion: Sleepy driving and MVA are prevalent in both gender but was higher in men. Future public health initiatives should particularly focus on men, since men reported a greater likelihood of both sleep-related MVA and “near miss” events.Keywords: sleepiness, driving, obstructive sleep apnea, OSA, gender differences

We aimed to gather evidence on the feasibility of using simulator-based driving assessments for prescribing powered mobility devices (PMDs). Therefore, we compared the driving characteristics of real driving and two types of simulated driving. Thirty participants with difficulty walking more than 100 meters independently were enrolled. We developed a full-cabin and desktop simulator and created driving scenarios that closely resembled a real driving route in a park. They participated in three separate driving sessions, each using a powered wheelchair, full-cabin simulator, and desktop simulator. The driving characteristics, such as driving distance, mean speed, and standard deviation (SD) of speed, were obtained and analyzed to assess differences and correlations. Statistically significant differences were found in the driving distance and the SD of speed, respectively. However, for the mean speed, there was no statistically significant difference among the three types of driving. The intraclass correlation coefficient (ICC) for the driving distance was 0.154, which was not statistically significant. However, for mean speed, the ICC was 0.752, indicating a strong correlation. The ICC for the SD of speed was 0.562, indicating a moderate correlation. We demonstrated that the two types of simulators have characteristics that are similar to real-world driving characteristics. The mean speed showed the highest similarity, and the SD of the speed showed a moderate degree of similarity. These results highlight the significant potential of employing simulator-based driving to evaluate the use of PMDs.

The purpose of this study is to facilitate knowledge discovery about the relationship between driving and health among the elderly. In the Iwaki Health Promotion Project that is an annual project conducted by Hirosaki University, we have included a survey on driving for the first time in 2019. After linking the data obtained from the survey with four years of health data for 2016–2019, we have utilized PLSA as a machine learning method to cluster those data in an integrated manner. As a result, we have found latent classes broadly classified according to whether the health level has been generally high or low. Also, when we have focused on a specific health item, for example, cognitive function, we have found some people with higher and lower maintenance of cognitive function over four years, even if they have belonged to a same latent class. To characterize these differences in detail, we have utilized t-SNE as a machine learning method. As a result, we have found that “I like driving” as a factor related to the Kansei (sensitivity) may characterize the high maintenance of cognitive function. For those who like driving, it is considered that the high maintenance of cognitive function may be occurred because they enjoy driving, have a wider range of activities, and increase the possibility of multitasking.

Driver drowsiness is a major contributor to road traffic accidents. A system capable of detecting drowsiness and consequently warning drivers at an early stage could significantly reduce the number of drowsiness-related road accidents. Although different measures can indicate driver drowsiness, eye activity measures are known to indicate drowsiness in the early stages. This study systematically reviewed empirical studies (with reported performance measures) on driver drowsiness detection (DDD) systems that use eye activities to indicate drowsiness. The objective of this review was to provide researchers and practitioners with in-depth information on DDD systems based on eye activities. Forty-one studies were identified using the preferred reporting items for systematic reviews and meta-analyses methodology. This review investigated various eye activity measures of drowsiness and provides a classification scheme for these measures. In addition, the current technologies used to measure eye activity were examined and a classification scheme for these technologies was formulated. Further, the decision-making algorithms used to classify and predict drowsiness states were investigated using their associated performance measures. Finally, future insights and ideas for utilizing eye activity measures to detect drowsiness at an early stage were discussed. This study forms the basis for future research and development of DDD using eye activities.

In numerous location-based applications, such as the vehicular routing problem, driving distances play a crucial role. However, these driving distances often differ from the direct geographic distance computed using latitude and longitude. Hence, accurately estimating the driving distance between two positions is vital for the success of such services. Researchers have worked on developing efficient methods to estimate driving distances, and it has been reported that the inflation ratio (or detour index) between driving distance and direct distance is approximately 1.3. However, this simple method may not suffice for complex road networks. To address these challenges, other researchers have proposed deep learning based approaches. They show relatively good performance for real road data sets. Even though the deep learning based approach may work for real road data sets, it crucial to fully understand the behavior of the deep neural network (DNN) based approach. Therefore, in this study, We aim to thoroughly examine a deep learning-based road network distance estimation method under controlled conditions. Specifically, we define five different distance types and assess the performance of the DNN-based approach. Subsequently, we analyze the key factors that influence its performance. Through extensive simulations, we demonstrate that the DNN-based method performs well across most distance definitions. After conducting a thorough analysis of the evaluation results, we have identified a key characteristic of the road data sets that significantly impacts the accuracy of the DNN-based method. Specifically, we have found that the “discontinuity” of the distances plays a crucial role in achieving high accuracy. As a result, we propose that future designs of DNN-based road network distance estimation methods should prioritize careful consideration of this “discontinuity” aspect to optimize their performance and ensure better accuracy.

Background: Many studies have assessed the effect of music on driving. However, their results are very scattered and contradictory. Therefore, this systematic review is conducted to determine the effect of music on driving performance and drivers’ physiological and psychological indicators. Methods: Scopus, PubMed, and Web of Science databases were searched until July 2023. A manual search in Google Scholar for gray literature was conducted. The Simulation Research Rubric (SRR) tool was used to assess the reporting quality of the studies. Stata software (StataCorp, version 16) was used to perform a meta-analysis. Results: A total of 2650 records were identified. The findings of 19 studies were analyzed. Most of them were carried out in high-income countries (HICs) using simulators. The most frequently used music style was classic rock. The meta-analysis results indicated that music with high and medium volume increases the average driving speed, and music with low volume decreases it. Although music in every mood reduces the average reaction time, it positively reduces response delay and increases coherence. Music with high volume decreases the heart rate, but music with medium and low volume increases it. Listening to music increases the level of arousal and mental load. Conclusion: It was concluded that, in some indicators, listening to music has adverse effects on driving. However, in many indicators, music has a positive impact on improving driving safety. It is better to choose appropriate music for different driving conditions and to train the drivers about it.

Abstract 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.

OBJECTIVES: To examine how the COVID-19 pandemic affected driving and health outcomes in older adults. METHODS: We compared Advancing Understanding of Transportation Options (AUTO) study participants enrolled before (December 2019 to March 2020) versus during the pandemic (May 2020 to June 2021). Participants were English-speaking, licensed drivers (≥70 years) who drove weekly and had a primary care provider at a study site and ≥1 medical condition potentially associated with driving cessation. We used baseline self-reported measures on mobility and health. RESULTS: Compared to those enrolled pre-COVID-19 (n = 61), more participants enrolled during COVID-19 (n = 240) reported driving reductions (26% vs. 70%, p < .001) and more often for personal preference (vs. medical/emotional reasons). While mean social isolation was higher during than pre-COVID-19, self-reported depression, stress, and overall health PROMIS scores did not differ significantly. DISCUSSION: Our findings highlight the resiliency of some older adults and have implications for mitigating the negative effects of driving cessation.

BACKGROUND: Many older adults face the difficult decision of when to stop driving. We sought to test whether an online driving decision aid (DDA) would improve decision quality. METHODS: This prospective two-arm randomized trial enrolled English-speaking licensed drivers (age ≥70 years) without significant cognitive impairment but with ≥1 diagnosis associated with increased likelihood of driving cessation; all participants received primary care in clinics associated with study sites in three states. The intervention was the online Healthwise® DDA for older adults addressing Is it time to stop driving?; control was web-based information for older drivers only. The primary outcome was decision conflict as estimated by the Decisional Conflict Scale (DCS; lower scores indicate higher quality). Secondary outcomes were knowledge and decision self-efficacy about driving decisions. We examined postrandomization differences in primary and secondary outcomes by study arm using generalized linear mixed-effects models with adjustment for site and prerandomization scores. RESULTS: Among 301 participants (mean age: 77.1 years), 51.2% identified as female and the majority as non-Hispanic (99.0%) and white (95.3%); 98.0% lived in an urban area. Participant characteristics were similar by study arm but differed across sites. Intervention participants had a lower mean DCS score (12.3 DDA vs 15.2 control; adjusted mean ratio [AMR] 0.76, 95%CI 0.61-0.95; p = 0.017). Intervention participants had higher mean knowledge scores (88.9 DDA vs. 79.9 control; OR 1.13, 95%CI 1.01-1.27, p = 0.038); there was no difference between groups in self-efficacy scores. The DDA had high acceptability; 86.9% of those who viewed it said they would recommend it to others in similar situations. CONCLUSIONS: The online Healthwise® DDA decreased decision conflict and increased knowledge in this sample of English-speaking, older adults without significant cognitive impairment, although most chose to continue driving. Use of such resources in clinical or community settings may support older adults as they transition from driving to other forms of mobility. TRIAL REGISTRATION: ClinicalTrials.gov identifier Advancing Understanding of Transportation Options (AUTO) NCT04141891.

We examined the hidden costs of intermittent multitasking. Participants performed a pursuit-tracking task (Experiment 1) or drove in a high-fidelity driving simulator (Experiment 2) by itself or while concurrently performing an easy or difficult backwards counting task that periodically started and stopped, creating on-task and off-task multitasking epochs. A novel application of the Detection Response Task (DRT), a standardized protocol for measuring cognitive workload (ISO 17488, 2016), was used to measure performance in the on-task and off-task intervals. We found striking costs that persisted well after the counting task had stopped. In fact, the multitasking costs dissipated as a negatively accelerated function of time with the largest costs observed immediately after multitasking ceased. Performance in the off-task interval remained above baseline levels throughout the 30-s off-task interval. We suggest that loading new procedures into working memory occurs fairly quickly, whereas purging this information from working memory takes considerably longer. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

AbstractPurposeMaterials and methodsResultsConclusionsStroke can affect driving, an important activity of daily living. Little is known about whether aphasia (language impairment) impacts driving post-stroke. This scoping review explores impacts and perceived impacts of aphasia on driving performance, and the process of returning to driving post-stroke.Scoping review using Arksey and O’Malley’s framework, reported using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Bibliographic databases were searched and international clinical practice guidelines were sourced online. Full-text articles were independently assessed by two reviewers. Results were tabulated and summarised using narrative synthesis.Forty-three literature sources and 17 clinical practice guidelines were identified. Six studies investigated return to driving with aphasia post-stroke; 37 sources from the broader literature contributed to objectives. It remains unclear whether aphasia impacts fitness-to-drive; however, people with aphasia face barriers in returning to driving due to: (1) uncertainty regarding the role of language in driving; (2) poor awareness and knowledge of aphasia, and (3) communication demands in the patient-journey and assessment.The current evidence base is limited, inconsistent, and lacking in quality and recency and there is a lack of guidelines to support clinical practice. People with aphasia face barriers in returning to driving; however, it is unclear if aphasia affects fitness-to-drive post-stroke. Implications for rehabilitationPeople with aphasia, their caregivers and clinicians have identified return to driving as a top 10 research priority.We do not know if aphasia affects fitness-to-drive post-stroke, but communication difficulties can make the process of returning to driving more difficult.Speech pathologists have an important role in ensuring that driving is discussed with people with aphasia post-stroke.Speech pathologists should support the multidisciplinary team to understand and meet the communication needs of people with aphasia throughout the driving evaluation process.People with aphasia, their caregivers and clinicians have identified return to driving as a top 10 research priority.We do not know if aphasia affects fitness-to-drive post-stroke, but communication difficulties can make the process of returning to driving more difficult.Speech pathologists have an important role in ensuring that driving is discussed with people with aphasia post-stroke.Speech pathologists should support the multidisciplinary team to understand and meet the communication needs of people with aphasia throughout the driving evaluation process. [ABSTRACT FROM AUTHOR]

The conceptual framework for assessing the situational awareness (SA) of drivers consists of three hierarchical levels: perception of the elements of the environment, comprehension of the elements, and decision-making in the near future. A common challenge in evaluating SA is the determination of the available subjective and objective techniques and their selection and integration into methodologies. Among the objective techniques, eye tracking is commonly used, considering the influence of gaze behavior on driving. This review is presented as an innovative approach to the subject matter, introducing physiological metrics based on eye tracking and investigating their application in assessing the SA of drivers. In addition, experiments and methodologies that revealed patterns at the three levels of SA were identified. For this purpose, databases were searched, and 38 papers were considered. Articles were clustered according to prevalent themes such as eye-tracking metrics, eye-tracking devices, experiment design, and the relationship between SA and eye-tracking. This review summarizes the main metrics and key findings for each article and reveals a wide relationship between the eye-tracking metrics and SA. The influence of appropriately calibrated equipment, refined data collection protocols, and adequate selection of the eye-tracking metrics was examined. Further reviews are needed to systematically collect more evidence. [ABSTRACT FROM AUTHOR]

Background and purpose: Driving is a crucial ability that can impact the quality of life for elderly individuals. Older adults may rely more on driving compared to other age demographics. As individuals age, there are significant changes in physical, cognitive, intellectual, and emotional abilities that are crucial for driving, a skill essential for accessing healthcare, therapy services, work, and social activities, as well as maintaining independence and autonomy in the elderly. Mobility and physical exertion are crucial aspects of health for older individuals, and driving significantly contributes to their ability to move within society. The increase in the elderly population has led to a rise in the number of older drivers. Proficiency in self-efficacy in driving is a crucial ability in this profession that acknowledges the significant aspects of this issue. This study aimed to investigate the correlation between weariness, self-efficacy, and driving behavior among older drivers in an urban setting. Materials and methods: This study was a progressive and descriptive-analysis study conducted among older drivers aged 60 and older who were members of the taxi association. Three hundred and ten eligible participants were chosen using the convenience sampling approach. The data was collected using the demographic data form, the multidimensional fatigue inventory, and Adele's self-efficacy scale. The data was analyzed using descriptive statistics, multiple linear regression, and Pearson correlation tests. Results: The participants had an average age of 28.3 years with a standard deviation of 9.6 years, and their ages ranged from 60 to 75 years. 42% of the participants had university degrees. They mostly had 30 to 50 years of driving experience. The average self-efficiency in driving among older drivers was 101.87±15.74. The Pearson correlation test indicated a significant and inverse relationship between age factors, the history of the driving license, and the self-efficacy score. In other words, as age and years of driving experience increase, the likelihood of self-efficacy driving reduces substantially. The correlation between the fatigue questionnaire scores and self-driving efficiency was significant(P<0.001). There was an inverse relationship between fatigue and self-efficacy in driving. Higher fatigue levels in older adults led to a decrease in self-activity rates. Multiple linear regression analyses revealed strong associations between educational characteristics, the economic-social status of chronic illness, self-efficiency scores, and fatigue rates. The model indicates that the fatigue score decreases by 0.18 for every one-unit rise in the self-efficiency score. The regression analysis showed that monthly income, vehicle type, and fatigue score were significantly related to driving self-efficacy score(R2=39.5). Conclusion: Researchers recommend implementing a driving rehabilitation program and interventions that provide psychological support in reducing fatigue for older adult drivers based on these findings. The results of the study could assist policymakers in the field of gerontology in planning rehabilitation programs to enhance self-efficacy in driving in older individuals. These programs would consider the factors that contribute to decreased driving efficiency in older drivers and would be implemented in collaboration with welfare organizations and municipalities. [ABSTRACT FROM AUTHOR]

Objectives Baltes and Baltes' "selective optimization with compensation" model is pertinent to driving but evidence about the use of compensation using longitudinal designs is scarce. Therefore, we sought to determine if older drivers reduced their engagement in distracting behaviors while driving, over a 6-year period. Methods We used data captured over several annual assessments from a cohort of 583 drivers aged 70 and older to determine if their engagement in 12 distracting behaviors (e.g. listening to the radio, talking with passengers) declined over time. We adjusted our multivariable model for several potential confounders of the association between our outcome variable and time. Results Overall, and after adjustment for potential confounders, the participants reduced their engagement in distracting behaviors over the study period (odds ratio [OR] = 0.96, 95% confidence interval [CI] = 0.95–0.97). Baseline age was negatively associated with engagement in distracting behaviors (OR = 0.95, 95% CI = 0.94–0.96). Men engaged in more distracting behaviors than women (OR = 1.15, 95% CI = 1.03–1.27), as did participants living in the largest urban centers compared to participants living in the smallest areas (OR = 1.21, 95% CI = 1.04–1.41). The number of kilometers driven per year (for every 10,000 km) was positively associated with the proportion of distracting behaviors drivers engaged in (OR = 1.13, 95% CI = 1.08–1.19). Discussion Drivers in our cohort reduced their engagement in distracting behaviors over the study period. This suggests that older drivers adjust their driving over time, which aligns with age-related theories and models about compensation. [ABSTRACT FROM AUTHOR]

Cannabis is the second most commonly used substance among Canadians for those 18 to 24 years old with the most prominent associated risk of driving under the influence. Cannabis consumption impairs executive functions necessary for driving and increases the likelihood of fatal motor vehicle crashes. The purpose of this study was to explore participant perceptions about the dangerousness and social acceptability of driving under the influence of cannabis (DUIC) compared to alcohol or while tired. Utilizing an experimental vignette design, participants (N = 453) were randomly assigned to one of six vignettes that varied on the substance used by a 22-year-old (cannabis, alcohol, no substance) and driver sex (male, female). Participants responded to a series of questions about the dangerousness and social acceptability of the driving behaviors described. A series of ANOVAs revealed a significant main effect of substance use across all items and a main effect of sex on social acceptability. DUIC was perceived as less dangerous and more socially acceptable than driving under the influence of alcohol. Furthermore, impaired driving was viewed as more acceptable for females than males. Findings help provide further insights into public perceptions of DUIC and highlight the importance of public education on the risks of DUIC. [ABSTRACT FROM AUTHOR]

Purpose: Brain tumours are associated with neurocognitive impairments that are important for safe driving. Driving is vital to maintaining patient autonomy, despite this there is limited research on driving capacity amongst patients with brain tumours. The purpose of this review is to examine MVC risk in patients with brain tumours to inform development of clearer driving guidelines. Methods: A systematic review was performed using Medline and EMBASE. Observational studies were included. The outcome of interest was MVC or measured risk of MVC in patients with benign or malignant brain tumours. Descriptive analysis and synthesis without meta-analysis were used to summarise findings. A narrative review of driving guidelines from Australia, United Kingdom and Canada was completed. Results: Three studies were included in this review. One cohort study, one cross-sectional study and one case–control study were included (19,135 participants) across United States and Finland. One study evaluated the incidence of MVC in brain tumour patients, revealing no difference in MVC rates. Two studies measured MVC risk using driving simulation and cognitive testing. Patients found at higher risk of MVC had greater degrees of memory and visual attention impairments. However, predictive patient and tumour characteristics of MVC risk were heterogeneous across studies. Overall, driving guidelines had clear recommendations on selected conditions like seizures but were vague surrounding neurocognitive deficits. Conclusion: Limited data exists regarding driving behaviour and MVC incidence in brain tumour patients. Existing guidelines inadequately address neurocognitive complexities in this group. Future studies evaluating real-world data is required to inform development of more applicable driving guidelines. Systematic review registration number: PROSPERO 2023 CRD42023434608. [ABSTRACT FROM AUTHOR]

Objective: To examines the driving skills, executive functions, and adaptive behavior of adolescents diagnosed with Attention-deficit/hyperactivity disorder (ADHD) combined with emotional difficulties and/or learning disabilities (complex ADHD), compared to adolescents without ADHD. Method: A cross-sectional study including 30 adolescents with complex ADHD and 33 adolescents without ADHD aged 15 to 18 years. Driving skills on a simulator, executive functions, and adaptive behavior were evaluated. Results: Adolescents without ADHD demonstrated significantly higher total scores on the driving simulator, indicating better driving performance compared to adolescents with complex ADHD. In the complex ADHD group, after controlling for different Conners Comprehensive Behavior Rating Scale-Self Report scales, driving simulator scores were partially correlated with executive functions. Conclusion: These findings emphasize the unique needs of adolescents with complex ADHD. Given the significance of driving in today's society, it is crucial to consider the development of intervention programs to support this population's driving skills. [ABSTRACT FROM AUTHOR]

Introduction. Technological advancements have the potential to enhance people's quality of life, but their misuse can have a detrimental impact on safety. A notable example is the escalating issue of distracted driving resulting from the use of mobile phones behind the wheel, leading to severe crashes and injuries. Despite these concerns, both drivers' usage patterns and their risk-related associations remain scarcely documented in Mexico. Therefore, this descriptive study aimed to examine the mobile phone usage of Mexican drivers, its relationships to risk awareness and near-miss/crash involvement, and the self-reported underlying reasons for this behavior. Methods. This cross-sectional study utilized a sample of 1,353 licensed Mexican drivers who took part in a nationwide series of interviews regarding their onboard phone use settings. Results. A significant percentage of drivers (96.8%) recognize using a mobile phone while driving as high-risk behavior. However, only 7.4% reported completely avoiding its use while driving, with 22.4% identified as high-frequency users. Frequency was also found positively associated with the self-reported rate of near-misses and crashes. Furthermore, qualitative data analysis highlights the emergence of a 'sense of urgency' to attend to phone-related tasks in response to daily demands and life dynamics, offering a potential explanation for this behavior. Conclusion. The results of this study suggest common patterns of onboard mobile use among Mexican drivers concerning driving situations and associated risks. This underscores the need for increased efforts to discourage onboard phone use in the country. [ABSTRACT FROM AUTHOR]