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Older adults aged 70 and older who drive have higher crash death rates per mile driven compared to middle aged (35-54 years) adults who drive in the US. Prior studies have found that depression and or antidepressant medication use in older adults are associated with an increase in the vehicular crash rate. Using data from the prospective multi-site AAA Longitudinal Research on Aging Drivers Study, this analysis examined the independent and interdependent associations of self-reported depression and antidepressant use with driving behaviors that can increase motor vehicle crash risk such as hard braking, speeding, and night-time driving in adults over age 65. Of the 2951 participants, 6.4% reported having depression and 21.9% were on an antidepressant medication. Correcting for age, race, gender, and education level, participants on an antidepressant had increased hard braking events (1.22 [1.10-1.34]) but self-reported depression alone was not associated with changes in driving behaviors., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: Polypharmacy (i.e., simultaneous use of two or more medications) poses a serious safety concern for older drivers. This study assesses the association between polypharmacy and hard braking events in older adult drivers., Methods: Data for this study came from a naturalistic driving study of 2990 older adults. Information about medications was collected through the "brown-bag review" method. Primary vehicles of the study participants were instrumented with data recording devices for up to 44 months. Multivariable negative binomial model was used to estimate the adjusted incidence rate ratios (aIRRs) and 95 % confidence intervals (CIs) of hard-braking events (i.e., maneuvers with linear deceleration rates ≥0.4 g) associated with polypharmacy., Results: Of the 2990 participants, 2872 (96.1 %) were eligible for this analysis. At the time of enrollment, 157 (5.5 %) drivers were taking fewer than two medications, 904 (31.5 %) were taking 2-5 medications, 895 (31.2 %) were taking 6-9 medications, 571 (19.9 %) were taking 10-13 medications, and 345 (12.0 %) were taking 14 or more medications. Compared to drivers using fewer than two medications, the risk of hard-braking events increased 8 % (aIRR 1.08, 95 % CI 1.04, 1.13) for users of 2-5 medications, 12 % (aIRR 1.12, 95 % CI 1.08, 1.16) for users of 6-9 medications, 19 % (aIRR 1.19, 95 % CI 1.15, 1.24) for users of 10-13 medications, and 34 % (aIRR 1.34, 95 % CI 1.29, 1.40) for users of 14 or more medications., Conclusions: Polypharmacy in older adult drivers is associated with significantly increased incidence of hard-braking events in a dose-response fashion. Effective interventions to reduce polypharmacy use may help improve driving safety in older adults., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Dietary supplement (DS) use is common and increasing among older adults, though much data available on use frequencies are from surveys and performed cross-sectionally. This paper sought to assess the frequency and pattern of dietary supplement use among older adults over time., Methods: A secondary analysis of data from the AAA LongROAD study, a longitudinal prospective cohort study of older adult drivers, using data from baseline and the first two years of follow up included a total of 2990 drivers aged 65-79 years recruited at five study sites across the US from July 2015 to March 2017. Participants underwent baseline and annual evaluations, which included a "brown bag" medication review. DS were identified and categorized according to type and key components. Prevalence and pattern of DS use over time and relationship to demographics were measured with frequency and Chi squared analyses., Results: 84% of participants took at least one dietary supplement during the 2-year study period, and 55% of participants continually reported use. DS accounted for approximately 30% of the total pharmacologic-pill burden in all years. Participants who were White non-Hispanic, female, 75-79 years of age at baseline, and on more non-supplement medications took significantly more dietary supplements (P < 0.05). Vitamin D, multivitamins, calcium, and omega-3 formulations were the most common supplements, with stable use over time. Use of individual herbal supplements and cannabis products was uncommon (< 1% participants per year)., Conclusions: DS use among older adults is common and relatively stable over time and contributes to polypharmacy. In clinical settings, providers should consider the influence of DS formulations on polypharmacy, and the associated cost, risk of medication interactions, and effect on medication compliance., (© 2024. The Author(s).)

Pose estimation is crucial for ensuring passenger safety and better user experiences in semi- and fully autonomous vehicles. Traditional methods relying on pose estimation from regular color images face significant challenges due to a lack of three-dimensional (3D) information and the sensitivity to occlusion and lighting conditions. Depth images, which are invariant to lighting issues and provide 3D information about the scene, offer a promising alternative. However, there is a lack of strong work in 3D pose estimation from such images due to the time-consuming process of annotating depth images with 3D postures. In this paper, we present a novel approach to 3D human posture estimation using depth and infrared (IR) images. Our method leverages a three-stage fine-tuning process involving simulation data, approximated data, and a limited set of manually annotated samples. This approach allows us to effectively train a model capable of accurate 3D pose estimation with a median error of under 10 cm across all joints, using fewer than 100 manually annotated samples. To the best of our knowledge, this is the first work focusing on vehicle occupant posture detection utilizing only depth and IR data. Our results demonstrate the feasibility and efficacy of this approach, paving the way for enhanced passenger safety in autonomous vehicle systems.

The purpose of this study was to evaluate the efficacy of the Residential Care Transition Module, a six-session, psychosocial, and psychoeducational telehealth intervention for family caregivers of cognitively impaired relatives living in a residential long-term care setting. Eligible participants (including care recipients, regardless of time since admission) were randomized to treatment or usual care control conditions. Survey data were collected at baseline, 4 months, 8 months, and 12 months ( N = 240). Primary analytic outcomes included caregiver subjective stress (a stress process mechanism) and depressive symptoms (a measure of global well-being). Secondary analytic outcomes included secondary role strains, residential care stress, caregiver sense of competence, and self-efficacy (additional mechanisms of action). General linear models tested for the main effects of the intervention at 4 months, and longitudinal mixed models examined the 12-month effects of the intervention. Post hoc analyses also examined the influence of moderators. No significant differences between the treatment and control groups for any primary analytic outcome were apparent. Caregivers in the treatment group whose relatives were admitted to residential long-term care in the prior 3 months were more likely to indicate reductions in depressive symptoms over the first 4 months of participation. Over the 12-month study period, caregivers in the treatment group who were employed reported increased self-efficacy over time. The heterogeneity of dementia care requires a broader consideration of key contextual factors that may influence the efficacy of nonpharmacological interventions. Aligning measures with the preferences, goals, and values of dementia caregivers may further demonstrate the direct benefits of interventions such as the Residential Care Transition Module. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Background: Diabetes mellitus (DM) can impair driving safety due to hypoglycemia, hyperglycemia, diabetic peripheral neuropathy, and diabetic eye diseases. However, few studies have examined the association between DM and driving safety in older adults based on naturalistic driving data., Methods: Data for this study came from a multisite naturalistic driving study of drivers aged 65-79 years at baseline. Driving data for the study participants were recorded by in-vehicle recording devices for up to 44 months. We used multivariable negative binomial modeling to estimate adjusted incidence rate ratios (aIRRs) and 95% confidence intervals (CIs) of hard braking events (HBEs, defined as maneuvers with deceleration rates ≥ 0.4 g) associated with DM., Results: Of the 2856 study participants eligible for this analysis, 482 (16.9%) reported having DM at baseline, including 354 (12.4%) insulin non-users and 128 (4.5%) insulin users. The incidence rates of HBEs per 1000 miles were 1.13 for drivers without DM, 1.15 for drivers with DM not using insulin, and 1.77 for drivers with DM using insulin. Compared to drivers without DM, the risk of HBEs was 48% higher for drivers with DM using insulin (aIRR 1.48; 95% CI: 1.43, 1.53)., Conclusion: Older adult drivers with DM using insulin appear to be at increased proneness to vehicular crashes. Driving safety should be taken into consideration in DM care and management., (© 2024. The Author(s).)

Introduction: Frailty and low physical performance are modifiable factors and, therefore, targets for interventions aimed at delaying driving cessation (DC). The objective was to determine the impact of frailty and physical performance on DC., Methods: Multisite prospective cohort of older drivers. The key inclusion criteria are as follows: active driver age 65-79 years, possessing a valid driver's license, without significant cognitive impairment, and driving a 1996 car or a newer model car. Of the 2,990 enrolled participants, 2,986 (99.9%) had at least one frailty or Short Physical Performance Battery (SPPB) measure and were included in this study. In total, 42% of participants were aged 65-69 years, 86% were non-Hispanic white, 53% were female, 63% were married, and 41% had a high degree of education. The Fried Frailty Phenotype and the Expanded Short Physical Performance Battery (SPPB) from the National Health and Aging Trends Study were utilized. At each annual visit, DC was assessed by the participant notifying the study team or self-reporting after no driving activity for at least 30 days, verified via GPS. Cox proportional hazard models, including time-varying covariates, were used to examine the impact of the SPPB and frailty scores on time to DC. This assessment included examining interactions by sex., Results: Seventy-three participants (2.4%) stopped driving by the end of year 5. Among women with a fair SPPB score, the adjusted hazard ratio (HR) of DC was 0.26 (95% confidence interval (CI) 0.10-0.65) compared to those with a poor SPPB score. For those with a good SPPB score, the adjusted HR of DC had a p -value of <0.001. Among men with a fair SPPB score, the adjusted hazard ratio (HR) of DC was 0.45 (95% CI 0.25-0.81) compared to those with a poor SPPB score. For men with a good SPPB score, the adjusted HR of DC was 0.19 (95% CI 0.10-0.36). Sex was not an effect modifier between frailty and DC. For those who were categorized into pre-frail or frail, the adjusted ratio of HR to DC was 6.1 (95% CI 2.7-13.8) compared to those who were not frail., Conclusion and Relevance: Frailty and poor physical functioning are major risk factors for driving cessation. Staying physically active may help older adults to extend their driving life expectancy and mobility., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Mielenz, Jia, DiGuiseppi, Strogatz, Andrews, Molnar, Eby, Hill and Li.)

Rotator cuff (RC) tears are a common source of pain and decreased shoulder strength. Muscle length is known to affect muscle strength, and therefore evaluating changes in supraspinatus muscle length associated with RC pathology, surgical repair, and post-operative recovery may provide insights into functional deficits. Our objective was to develop a reliable MRI-based approach for assessing supraspinatus muscle length. Using a new semi-automated approach for identifying 3D location of the muscle-tendon junction (MTJ), supraspinatus muscle length was calculated as the sum of MTJ distance (distance between 3D MTJ position and glenoid plane) and supraspinatus fossa length (distance between root of the scapular spine and glenoid plane). Inter- and intra-operator reliability of this technique were assessed with intraclass correlation coefficient (ICC) and found to be excellent (ICCs > 0.96). Muscle lengths of 6 patients were determined before RC repair surgery and at 3- and 12-months post-surgery. Changes in normalized muscle length (muscle length as a percentage of pre-surgical muscle length) at 3 months post-surgery varied considerably across patients (16.1 % increase to 7.0 % decrease) but decreased in all patients from 3- to 12-months post-surgery (0.3 % to 17.2 %). This study developed a novel and reliable approach for quantifying supraspinatus muscle length and provided preliminary demonstration of its utility by assessing muscle length changes associated with RC pathology and surgical repair. Future studies can use this technique to evaluate changes over time in supraspinatus muscle length in response to clinical intervention, and associations between muscle length and shoulder function., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Background: Migraine headache is common in older adults, often causing symptoms that may affect driving safety. This study examined associations of migraine with motor vehicle crashes (MVCs) and driving habits in older drivers and assessed modification of associations by medication use., Methods: In a multi-site, prospective cohort study of active drivers aged 65-79 (53% female), we assessed prevalent migraine (i.e., ever had migraine, reported at enrollment), incident migraine (diagnosis first reported at a follow-up visit), and medications typically used for migraine prophylaxis and treatment. During 2-year follow-up, we recorded self-reported MVCs and measured driving habits using in-vehicle GPS devices. Associations of prevalent migraine with driving outcomes were estimated in multivariable mixed models. Using a matched design, associations of incident migraine with MVCs in the subsequent year were estimated with conditional logistic regression. Interactions between migraine and medications were tested in all models., Results: Of 2589 drivers, 324 (12.5%) reported prevalent migraine and 34 (1.3%) incident migraine. Interactions between migraine and medications were not statistically significant in any models. Prevalent migraine was not associated with MVCs in the subsequent 2 years (adjusted OR [aOR] = 0.98; 95% CI: 0.72, 1.35), whereas incident migraine significantly increased the odds of having an MVC within 1 year (aOR = 3.27; 1.21, 8.82). Prevalent migraine was associated with small reductions in driving days and trips per month and increases in hard braking events in adjusted models., Conclusion: Our results suggest substantially increased likelihood of MVCs in the year after newly diagnosed migraine, indicating a potential need for driving safety interventions in these patients. We found little evidence for MVC risk or substantial changes in driving habits associated with prevalent migraine. Future research should examine timing, frequency, and severity of migraine diagnosis and symptoms, and use of medications specifically prescribed for migraine, in relation to driving outcomes., (© 2023 The American Geriatrics Society.)

Background: The lack of headforms that accurately reflect the head characteristics of Koreans and the demographic composition of the Korean population can lead to inadequate FFR testing and reduced effectiveness of FFRs., Method: Direct measurements of 5,110 individuals and 3D measurements of 2,044 individuals, aged between 9 and 69 years, were sampled from the data pool of Size Korea surveys based on the age and gender ratios of the Korean resident demographics. Seven head dimensions were selected based on the ISO 16976-2, availability of Size Korea measurements, and their relevance to the fit performance of FFRs. A principal component analysis (PCA) was performed using the direct measurements to extract the main factors explaining the head characteristics and then the main factors were standardized and remapped to 3D measurements, creating five size categories representing Korean head shapes. Lastly, representative 3D headforms were constructed by averaging five head shapes for each size category., Results: The study identified two main factors explaining Korean head characteristics by the PCA procedure specified in ISO 16976-2 and developed five representative headforms reflecting the anthropometric features of Korean heads: medium, small, large, short & wide, and long & narrow., Conclusion: This study developed representative headforms tailored to the Korean population for conducting total inward leakage (TIL) tests on filtering facepiece respirators (FFRs). The representative headforms can be used for TIL testing by employing robotic headforms to enhance the performance of FFRs for the Korean target population., Competing Interests: All authors certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers' bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript., (© 2023 The Authors.)

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., Competing Interests: J. Liddle, N.A. Pachana, L. Gustafsson, and T.L. Scott are authors and/or intellectual property contributors of the CarFreeMeTM Programs, which are owned by the University of Queensland (UQ). On behalf of UQ, UniQuest Pty Ltd is responsible for commercializing the CarFreeMeTM Programs worldwide. The authors have no share or ownership of UniQuest. Proceeds from commercialization of the Programs provide funding for continuing development and research of the program at UQ. The authors, IP contributors, and UQ may in the future receive royalties and/or consultancy fees from UniQuest because of the commercialization of the Programs., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Gerontological Society of America.)

Traffic light optimization is known to be a cost-effective method for reducing congestion and energy consumption in urban areas without changing physical road infrastructure. However, due to the high installation and maintenance costs of vehicle detectors, most intersections are controlled by fixed-time traffic signals that are not regularly optimized. To alleviate traffic congestion at intersections, we present a large-scale traffic signal re-timing system that uses a small percentage of vehicle trajectories as the only input without reliance on any detectors. We develop the probabilistic time-space diagram, which establishes the connection between a stochastic point-queue model and vehicle trajectories under the proposed Newellian coordinates. This model enables us to reconstruct the recurrent spatial-temporal traffic state by aggregating sufficient historical data. Optimization algorithms are then developed to update traffic signal parameters for intersections with optimality gaps. A real-world citywide test of the system was conducted in Birmingham, Michigan, and demonstrated that it decreased the delay and number of stops at signalized intersections by up to 20% and 30%, respectively. This system provides a scalable, sustainable, and efficient solution to traffic light optimization and can potentially be applied to every fixed-time signalized intersection in the world., (© 2024. The Author(s).)

Measuring human body dimensions is critical for many engineering and product design domains. Nonetheless, acquiring body dimension data for populations using typical anthropometric methods poses challenges due to the time-consuming nature of manual methods. The measurement process for three-dimensional (3D) whole-body scanning can be much faster, but 3D scanning typically requires subjects to change into tight-fitting clothing, which increases time and cost and introduces privacy concerns. To address these and other issues in current anthropometry techniques, a measurement system was developed based on portable, low-cost depth cameras. Point-cloud data from the sensors are fit using a model-based method, Inscribed Fitting, which finds the most likely body shape in the statistical body shape space and providing accurate estimates of body characteristics. To evaluate the system, 144 young adults were measured manually and with two levels of military ensembles using the system. The results showed that the prediction accuracy for the clothed scans remained at a similar level to the accuracy for the minimally clad scans. This approach will enable rapid measurement of clothed populations with reduced time compared to manual and typical scan-based methods.

Background: Trajectories of health-related quality of life (HRQoL) after driving cessation (DC) are thought to decline steeply, but for some, HRQoL may improve after DC. Our objective is to examine trajectories of HRQoL for individuals before and after DC. We hypothesize that for urban drivers, volunteers and those who access alternative transportation participants' health may remain unchanged or improve., Methods: This study uses data from the AAA Longitudinal Research on Aging Drivers (LongROAD) study, a prospective cohort of 2,990 older drivers (ages 65-79 at enrollment). The LongROAD study is a five-year multisite study and data collection ended October 31, 2022. Participants were recruited using a convenience sample from the health centers roster. The number of participants approached were 40,806 with 7.3% enrolling in the study. Sixty-one participants stopped driving permanently by year five and had data before and after DC. The PROMIS®-29 Adult Profile was utilized and includes: 1) Depression, 2) Anxiety, 3) Ability to Participate in Social Roles and Activities, 4) Physical Function, 5) Fatigue, 6) Pain Interference, 7) Sleep Disturbance, and 8) Numeric Pain Rating Scale. Adjusted (age, education and gender) individual growth models with 2989 participants with up to six observations from baseline to year 5 in the models (ranging from n = 15,041 to 15,300) were utilized., Results: Ability to participate in social roles and activities after DC improved overall. For those who volunteered, social roles and activities declined not supporting our hypothesis. For those who accessed alternative transportation, fatigue had an initial large increase immediately following DC thus not supporting our hypothesis. Urban residents had worse function and more symptoms after DC compared to rural residents (not supporting our hypothesis) except for social roles and activities that declined steeply (supporting our hypothesis)., Conclusions: Educating older adults that utilizing alternative transportation may cause initial fatigue after DC is recommended. Accessing alternative transportation to maintain social roles and activities is paramount for rural older adults after DC especially for older adults who like to volunteer., (© 2024. The Author(s).)

Background: Polypharmacy use among older adults is of increasing concern for driving safety. This study assesses the individual and joint effects of benzodiazepines and prescription opioids on the incidence of hard braking events in older drivers., Methods: Data for this study came from the Longitudinal Research on Aging Drivers project-a multisite, prospective cohort study of 2990 drivers aged 65-79 years at enrollment (2015-2017). Adjusted incidence rate ratios (aIRRs) and 95% confidence intervals (CIs) of hard braking events (defined as maneuvers with deceleration rates ≥0.4 g and commonly known as near-crashes) were estimated through multivariable negative binominal modeling., Results: Of the 2929 drivers studied, 167 (5.7%) were taking benzodiazepines,  163 (5.6%) prescription opioids, and 23 (0.8%) both drugs at baseline. The incidence rates of hard braking events per 1000 miles driven were 1.14 (95% CI 1.10-1.18) for drivers using neither benzodiazepines nor prescription opioids, 1.25 (95% CI 1.07-1.43) for those using benzodiazepines only, 1.55 (95% CI 1.35-1.76) for those using prescription opioids only, and 1.63 (95% CI 1.11-2.16) for those using both medications. Multivariable modeling revealed that the use of prescription opioids was associated with a 19% increased risk of hard braking events (aIRR 1.19, 95% CI 1.03-1.36). There existed a positive interaction between the two drugs on the additive scale but not on the multiplicative scale., Conclusion: Concurrent use of benzodiazepines and prescription opioids by older drivers appears to affect driving safety through increased incidence of hard braking events., (© 2023 The American Geriatrics Society.)

Objective: The advent of automated vehicles (AVs) provides an opportunity to design integrated wheelchair seating stations that provide an equivalent level of safety for occupants using wheelchairs as those using vehicle seating. This study designed a frontal occupant protection system for an integrated second-row wheelchair seating station that includes optimized airbags and seatbelt systems., Methods: MADYMO models were used to optimize belt geometry for a midsized male ATD seated in a surrogate wheelchair fixture, with and without inclusion of a Self Conforming Rearseat Air Bag (SCaRAB). Sled tests were performed to confirm the benefits of airbag use and optimized belt geometry. Additional modeling was performed with commercial manual and power wheelchairs, to identify the effects of wheelchair design and forward clear space on occupant kinematics and injury measures. Additional sled tests were performed with manual and power wheelchairs to demonstrate effectiveness of the restraint system with commercial products., Results: Simulations and tests both showed improved kinematics using an optimized seatbelt system geometry compared to a commonly used suboptimal D-ring location that places the shoulder belt at a more outboard location. Use of the SCaRAB helped compensate for suboptimal geometry. Results include specific recommendations for belt geometry relative to the wheelchair seating station and airbag parameters suitable for protecting occupants seated in wheelchairs. Restraint systems initially optimized using the surrogate wheelchair also performed well with the two commercial wheelchairs. The clear space required for maneuvering a wheelchair will likely prevent injurious head contact in frontal crashes., Conclusions: This study is the first to design a frontal optimal occupant protection system for an integrated second-row wheelchair seating station, demonstrating that it should be feasible once integrated wheelchair seating stations are included in AVs., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background: Nursing home admission remains a central outcome in many healthcare systems and community-based programs. The objective of this meta-analysis was to determine the efficacy of pharmacological and nonpharmacological interventions in preventing nursing home admission for adults aged 65 years or older., Methods: MEDLINE, EMBASE, PsycInfo, CINAHL, and the Cochrane Library were all last searched in March 2022 to identify up-to-date eligible studies for the meta-analysis. Two reviewers screened each abstract independently. In instances where reviewers disagreed as to inclusion, all reviewers convened to review the Abstract to come to a consensus decision regarding inclusion. Two reviewers independently collected data from each report. Disagreements were resolved using group consensus. The first author reviewed the narrative descriptions of intervention components to create a categorization scheme for the various interventions evaluated in selected studies. These categorizations were reviewed with the co-authors (second-fifth) and collapsed to create the final classification of intervention type. Study risk of bias was assessed using an instrument developed based on Agency for Healthcare Research & Quality (AHRQ) guidance. Differences between the percentages of participants in treatment versus control arms was the outcome of interest., Results: Two-hundred and eighty-three studies with a total of 203,735 older persons were included in the meta-analysis. Specialty geriatrics care (OR = 0.77, 95% CI, 0.60-0.99), multicomponent interventions (OR = 0.82, 95% CI, 0.67-0.99), and cognitive stimulation (OR = 0.60, 95% CI, 0.38-0.96) were associated with less frequent nursing home admission. Home-based and inpatient/discharge management interventions approached statistical significance but were not associated with reduced institutionalization., Conclusions: Even in the face of complex care needs, older adults wish to live at home. Effectively disseminating and implementing geriatric care principles across healthcare encounters could achieve a highly valued and preferred outcome in older adulthood: aging in place., (© 2023 The Authors. Journal of the American Geriatrics Society published by Wiley Periodicals LLC on behalf of The American Geriatrics Society.)

Importance: Symptoms of attention-deficit/hyperactivity disorder (ADHD), such as inattentiveness and impulsivity, could affect daily functioning and driving performance throughout the life span. Previous research on ADHD and driving safety is largely limited to adolescents and young adults., Objective: To examine the prevalence of ADHD and the association between ADHD and crash risk among older adult drivers., Design, Setting, and Participants: This prospective cohort study collected data from primary care clinics and residential communities in 5 US sites (Ann Arbor, Michigan; Baltimore, Maryland; Cooperstown, New York; Denver, Colorado; and San Diego, California) between July 6, 2015, and March 31, 2019. Participants were active drivers aged 65 to 79 years at baseline enrolled in the Longitudinal Research on Aging Drivers project who were studied for up to 44 months through in-vehicle data recording devices and annual assessments. The data analysis was performed between July 15, 2022, and August 14, 2023., Exposure: Lifetime ADHD based on an affirmative response to the question of whether the participant had ever had ADHD or had ever been told by a physician or other health professional that he or she had ADHD., Main Outcomes and Measures: The main outcomes were hard-braking events defined as maneuvers with deceleration rates of 0.4g or greater, self-reported traffic ticket events, and self-reported vehicular crashes. Multivariable negative binomial modeling was used to estimate adjusted incidence rate ratios (aIRRs) and 95% CIs of outcomes according to exposure status., Results: Of the 2832 drivers studied, 1500 (53.0%) were women and 1332 (47.0%) were men with a mean (SD) age of 71 (4) years. The lifetime prevalence of ADHD in the study sample was 2.6%. Older adult drivers with ADHD had significantly higher incidence rates of hard-braking events per 1000 miles than those without ADHD (1.35 [95% CI, 1.30-1.41] vs 1.15 [95% CI, 1.14-1.16]), as well as self-reported traffic ticket events per 1 million miles (22.47 [95% CI, 16.06-31.45] vs 9.74 [95% CI, 8.99-10.55]) and self-reported vehicular crashes per 1 million miles (27.10 [95% CI, 19.95-36.80] vs 13.50 [95% CI, 12.61-14.46]). With adjustment for baseline characteristics, ADHD was associated with a significant 7% increased risk of hard-braking events (aIRR, 1.07; 95% CI, 1.02-1.12), a 102% increased risk of self-reported traffic ticket events (aIRR, 2.02; 95% CI, 1.42-2.88), and a 74% increased risk of self-reported vehicular crashes (aIRR, 1.74; 95% CI, 1.26-2.40)., Conclusions and Relevance: As observed in this prospective cohort study, older adult drivers with ADHD may be at a significantly elevated crash risk compared with their counterparts without ADHD. These findings suggest that effective interventions to improve the diagnosis and clinical management of ADHD among older adults are warranted to promote safe mobility and healthy aging.

The objective of this study was to use computational models to study how unconventional seating positions and orientations in vehicles with Automated Driving System (ADS) may affect occupant response metrics of children with various restraint conditions. A literature review was first conducted to frame a simulation plan, including selections of surrogate ADS-equipped vehicles, potential seating arrangements, impact scenarios, anthropomorphic test device (ATD) models, and child restraint system (CRS) models that are relevant to the selected ATD models. Due to the lack of impact tests with child ATDs and CRS in farside, oblique, and rear impacts, 17 sled tests were conducted with CRS harness-restrained ATDs and vehicle belt-restrained ATDs in frontal, farside, oblique, and rear impact conditions. The sled tests were then used to validate a set of MADYMO (MAthematical DYnamic MOdels) v7.7 models. A total of 550 simulations were then conducted with four child ATDs and various CRS conditions across a range of conventional and unconventional seating locations and orientations under five impact directions. We did not find major safety concerns with ATDs restrained by harnessed CRSs based on the nature of ATD contacts. Compared with frontal and rear impacts, CRSs may rotate laterally in farside and oblique impacts, which could result in higher head and chest injury measures than frontal due to inertial loading to the CRS, and the larger lateral rotation of the CRS may lead to a contact between the CRS and vehicle interior. The major safety concern for vehicle belt-restrained ATDs (with and without booster) is that they have the potential to contact the seat next to them or the instrument panel behind them in a farside or oblique impact. Unconventional seating does not necessarily create additional safety concerns beyond what we know with the conventional seating. However, due to the orientation of the unconventional seats, the occupants on those seats may be involved in a higher percentage of oblique and rear-oblique impacts relative to their seating orientations than conventional seats, which may be considered in the future safety design process. This is the first study using different child ATDs and CRSs to investigate child occupant responses in a wide range of impact directions and seating orientations. Results from the sled tests and simulations provide a better understanding of child occupant responses in those crash conditions, but also identified several limitations of using frontal ATDs in other crash directions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Objective: Using population-based simulations and machine-learning algorithms to develop an adaptive restraint system that accounts for occupant anthropometry variations to further enhance safety balance throughout the whole population., Methods: Two thousand MADYMO full frontal impact crash simulations at 35 mph using two validated vehicle/restraint models representing a sedan and an SUV along with a parametric occupant model were conducted based on the maximal projection design of experiments, which considers varying occupant covariates (sex, stature, and body mass index) and vehicle restraint design variables (three for airbag, three for safety belt, and one for knee bolster). A Gaussian-process-based surrogate model was trained to rapidly predict occupant injury risks and the associated uncertainties. An optimization framework was formulated to seek the optimal adaptive restraint design policy that minimizes the population injury risk across a wide range of occupant sizes and shapes while maintaining a low difference in injury risks among different occupant subgroups. The effectiveness of the proposed method was tested by comparing the population-wise injury risks under the adaptive design policy and the traditional state-of-the-art design., Results: Compared to the traditional state-of-the-art design for midsize males, the optimal design policy shows the potential to further reduce the joint injury risk (combining head, chest, and lower extremity injury risks) among the whole population in the sedan and SUV models. Specifically, the two subgroups of vulnerable occupants including tall obese males and short obese females had higher reductions in injury risks., Conclusions: This study lays out a method to adaptively adjust vehicle restraint systems to improve safety balance. This is the first study where population-based crash simulations and machine-learning methods are used to optimize adaptive restraint designs for a diverse population. Nevertheless, this study shows the high injury risks associated with obese and female occupants, which can be mitigated via restraint adaptability., Competing Interests: KS, RZ, and RM were employed by Ford Motor Company. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Sun, Liu, Hu, Jin, Siasoco, Zhou and Mccoy.)

This study compared a sample of Australian drivers aged 77 years and older to participants from an older driver longitudinal cohort study (Ozcandrive) and examined the relationship between resilience and self-reported driving measures within these samples. Using a survey with a subset of questions from Ozcandrive, data were collected from 237 older drivers throughout Australia. The two samples were analyzed for differences in demographics, health, resilience, and self-reported driving behavior. A series of multiple regression models were fit for each driving outcome measure for both samples. The two samples had both similarities and differences, with the largest difference observed for resilience. Strong and consistent associations were found between resilience and driving comfort, abilities, and frequency for the Australian sample. Across samples, resilience remained a significant variable in seven of 10 regression models, more than any other independent variable.

The objectives of this study were to 1) collect and analyze recent pedestrian crash cases for better understanding of the pedestrian injury distribution and mechanism, 2) use computational simulations to reconstruct pedestrian cases and estimate potential benefit of pedestrian automatic emergency braking (PedAEB) in reducing pedestrian injury risks, and 3) estimate how future pedestrian crash distribution might influence priorities for pedestrian protection. Analyses of national crash-injury dataset showed that the overall number of pedestrians in crashes as well as the serious and fatal pedestrian injuries in the U.S. have been increasing in recent years. Striking vehicle type has changed (i.e., decreased proportion of passenger cars and increase of SUVs and pickup trucks) from 20 years ago mirroring changes in the fleet distribution of vehicle sales. A total of 432 pedestrian injury cases were generated by linking the Michigan trauma data and police-reported crash data from 2013 to 2018. Among the linked cases, pickup trucks and SUVs were involved in crashes with more injuries across body regions. Notably, AIS 3+ chest injuries occur at almost the same rate as lower extremity injuries. A method, combining MADYMO simulations (n = 3,500), response surface model, and data mining, was developed to reconstruct 25 linked pedestrian crash cases to estimate the effectiveness of PedAEB. Based on national field data and MADYMO simulations, PedAEB was estimated to be effective in reducing the risk of head and lower extremity injuries but is relatively less effective in reducing the risk of chest injuries. The increased proportions of SUVs and pickup trucks in the vehicle fleet and the higher penetration of PedAEB may highlight the importance of future research into chest injury risk for pedestrian protection., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Recent advancements in vehicle automation and driver-assistance systems that detect pavement markings has increased the importance of the detectability of pavement markings through various sensor modalities across weather and road conditions. Among the sensing techniques, light detection and ranging (LiDAR) sensors have become popular for vehicle-automation applications. This study used low-cost mobile multi-beam LiDAR to assess the performance of several types of pavement marking materials installed on a limited-access highway in various conditions, and quantified the degradation in detection performance over three years. Four marking materials, HPS-8, polyurea, cold plastic, and sprayable thermoplastic, were analyzed in the current study. LiDAR reflectivity data extracted from a total of 210 passes through the test sections were analyzed. A new detectability score based on LiDAR intensity data was proposed to quantify the marking detectability. The results showed that the pavement marking detectability varied across the material types over the years. The results provide guidance for selecting materials and developing maintenance schedules when marking detectability by LiDAR is a concern.

Illegal running into the opposite lane (IROL) on curve sections of two-lane rural roads is a frequently hazardous behavior and highly prone to fatal crashes. Although driving behaviors are always determined by the information from drivers' visual perceptions, current studies do not consider visual perceptions in predicting the occurrence of IROL. In addition, most machine learning methods belong to black-box algorithms and lack the interpretation of prediction results. Therefore, this study aims to propose an interpretable prediction model of IROL on curve sections of two-lane rural roads from drivers' visual perceptions. A new visual road environment model, consisting of five different visual layers, was established to better quantify drivers' visual perceptions by using deep neural networks. In this study, naturalistic driving data was collected on curve sections of typical two-lane rural roads in Tibet, China. There were 25 input variables extracted from the visual road environment, vehicle kinematics, and driver characteristics. Then, XGBoost (eXtreme Gradient Boosting) and SHAP (SHapley Additive exPlanation) methods were combined to build a prediction model. The results showed that our prediction model performed well, with an accuracy of 86.2% and an AUC value of 0.921. The average lead time of this prediction model was 4.4 s, sufficient for drivers to respond. Due to the advantages of SHAP, this study interpreted the impacting factors on this illegal behavior from three aspects, including relative importance, specific impacts, and variable dependency. After offering more quantitative information on the visual road environment, the findings of this study could improve the current prediction model and optimize road environment design, thereby reducing IROL on curve sections of two-lane rural roads., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

For simulation to be an effective tool for the development and testing of autonomous vehicles, the simulator must be able to produce realistic safety-critical scenarios with distribution-level accuracy. However, due to the high dimensionality of real-world driving environments and the rarity of long-tail safety-critical events, how to achieve statistical realism in simulation is a long-standing problem. In this paper, we develop NeuralNDE, a deep learning-based framework to learn multi-agent interaction behavior from vehicle trajectory data, and propose a conflict critic model and a safety mapping network to refine the generation process of safety-critical events, following real-world occurring frequencies and patterns. The results show that NeuralNDE can achieve both accurate safety-critical driving statistics (e.g., crash rate/type/severity and near-miss statistics, etc.) and normal driving statistics (e.g., vehicle speed/distance/yielding behavior distributions, etc.), as demonstrated in the simulation of urban driving environments. To the best of our knowledge, this is the first time that a simulation model can reproduce the real-world driving environment with statistical realism, particularly for safety-critical situations., (© 2023. The Author(s).)

One critical bottleneck that impedes the development and deployment of autonomous vehicles is the prohibitively high economic and time costs required to validate their safety in a naturalistic driving environment, owing to the rarity of safety-critical events 1 . Here we report the development of an intelligent testing environment, where artificial-intelligence-based background agents are trained to validate the safety performances of autonomous vehicles in an accelerated mode, without loss of unbiasedness. From naturalistic driving data, the background agents learn what adversarial manoeuvre to execute through a dense deep-reinforcement-learning (D2RL) approach, in which Markov decision processes are edited by removing non-safety-critical states and reconnecting critical ones so that the information in the training data is densified. D2RL enables neural networks to learn from densified information with safety-critical events and achieves tasks that are intractable for traditional deep-reinforcement-learning approaches. We demonstrate the effectiveness of our approach by testing a highly automated vehicle in both highway and urban test tracks with an augmented-reality environment, combining simulated background vehicles with physical road infrastructure and a real autonomous test vehicle. Our results show that the D2RL-trained agents can accelerate the evaluation process by multiple orders of magnitude (10 3 to 10 5 times faster). In addition, D2RL will enable accelerated testing and training with other safety-critical autonomous systems., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Most human head/brain models represent a generic adult male head/brain. They may suffer in accuracy when investigating traumatic brain injury (TBI) on a subject-specific basis. Subject-specific models can be developed from neuroimages; however, neuroimages are not typically available in practice. In this study, we establish simple and elegant regression models between brain outer surface morphology and head dimensions measured from neuroimages along with age and sex information (N = 191; 141 males and 50 females with age ranging 14-25 years). The regression models are then used to approximate subject-specific brain models by scaling a generic counterpart, without using neuroimages. Model geometrical accuracy is assessed using adjusted [Formula: see text] and absolute percentage error (e.g., 0.720 and 3.09 ± 2.38%, respectively, for brain volume when incorporating tragion-to-top). For a subset of 11 subjects (from smallest to largest in brain volume), impact-induced brain strains are compared with those from "morphed models" derived from neuroimage-based mesh warping. We find that regional peak strains from the scaled subject-specific models are comparable to those of the morphed counterparts but could be considerably different from those of the generic model (e.g., linear regression slope of 1.01-1.03 for gray and white matter regions versus 1.16-1.19, or up to ~ 20% overestimation for the smallest brain studied). These results highlight the importance of incorporating brain morphological variations in impact simulation and demonstrate the feasibility of approximating subject-specific brain models without neuroimages using age, sex, and easily measurable head dimensions. The scaled models may improve subject specificity for future TBI investigations., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Acute cannabis use is associated with a higher risk of motor vehicle crashes (MVC). This study aimed to determine if self-reported past-year cannabis use is associated with MVC or traffic stops among older drivers., Methods: This cross-sectional analysis used data from a multi-center study enrolling active drivers aged 65-79 years. Data regarding cannabis use, MVC, and traffic stops (i.e., being pulled over by police, whether ticketed or not) within the previous 12 months were collected through participant interviews. Log-binomial regression models examined associations of past-year cannabis use with MVC and traffic stops, adjusting for site and sociodemographic and mental health characteristics., Results: Of 2,095 participating older drivers, 186 (8.88%) used cannabis in the past year but only 10 (<0.5%) within an hour before driving in the last 30 days; 11.41% reported an MVC and 9.45% reported a traffic stop. Past-year cannabis users had a higher prevalence of MVC (adjusted prevalence ratio [aPR] = 1.38; 95%CI: 0.96, 2.00; p  = 0.086) and traffic stops (aPR = 1.58; 1.06, 2.35; p  = 0.024)., Conclusions: Past-year cannabis use was associated with increased traffic stops, which are correlated modestly with increased MVC in past studies and may indicate impaired driving performance. We did not find a statistically significant association of past-year cannabis use with MVC, which may indicate limited sustained effects on driving performance from periodic use among older adults, who report rarely driving immediately after use.

Objective: Falls in older adults are associated with increased motor vehicle crash risk, possibly mediated by driving behavior. We examined the relationship of falls and fear of falling (FOF) with subsequent objectively measured driving habits., Methods: This multi-site, prospective cohort study enrolled 2990 active drivers aged 65-79 (53% female). At enrollment, we assessed falls in the past year and FOF (Short Falls Efficacy Scale-International). Driving outcomes included exposure, avoidance of difficult conditions, and unsafe driving during one-year follow-up, using in-vehicle Global Positioning System devices., Results: Past-year falls were associated with more hard braking events (HBE). High FOF was associated with driving fewer days, miles, and trips, driving nearer home and more HBE. Differences were attenuated and not significant after accounting for health, function, medications and sociodemographics., Discussion: Differences in objectively measured driving habits according to past-year fall history and FOF were largely accounted for by differences in health and medications. Rather than directly affecting driving, falls and FOF may serve as markers for crash risk and reduced community mobility due to age-related changes and poor health., Competing Interests: Declaration of interest The authors have no conflicts of interest to declare., (Published by Elsevier Ltd.)

Objective: To explore the effect of personal protective equipment (PPE) fit on functional performance across a range of occupational domains., Background: PPE introduces an ergonomic, human systems integration, and mass burden to the wearer, and these factors are thought to be amplified if PPE is ill-fitting. However, few studies have considered the role of fit (static, dynamic, and cognitive) when evaluating PPE-related performance detriments in occupational settings., Method: A systematic literature review was conducted to identify relevant studies, which were then critically appraised based on methodological quality and collated to compare key findings and present evidence-based recommendations for future research directions across a range of occupational domains., Results: 16 published studies met the inclusion criteria, 88% of which found that the fit of PPE had a statistically significant effect on occupational performance. Poorly sized PPE resulted in slower or increased reaction time; decreased range of motion or mobility; decreased endurance or tolerance; decreased pulmonary function; and altered muscle activation. Limited research met the inclusion criteria and those that did had risks of bias in methodology quality., Conclusion: Future research evaluating the effect of PPE on performance in occupational settings should aim to recruit a more representative population; consider sex as a covariate; quantify and evaluate PPE fit and performance when integrated with all relevant equipment items; include outcome measures related to all three categories of fit (static, dynamic, cognitive); and assess performance of operationally relevant tasks., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Brisbine et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)