Neurocognitive Differences Between Drivers with Type 1 Diabetes with and without a Recent History of Recurrent Driving Mishaps

On the importance of working memory in the driving safety field: A systematic review

In recent years, many studies have used poor cognitive functions to explain risk safety differences among drivers. Working memory is a cognitive function with information storage and attentional control that plays a crucial role in driver information processing. Furthermore, it is inextricably linked to parameters such as driving performance, driving eye movements and driving neurophysiology, which have a significant impact on drivers' risky behavior and crash risk. In particular, crash risk is a serious risk to social safety and economic development. For this reason, it is necessary to understand how risk-related working memory affects driving so that pre-driving safety pre-training programs and in-vehicle safety assistance systems for driving can be developed accordingly, contributing to the development of semi-autonomous vehicles and even autonomous vehicles. In this paper, a systematic search of the literature over the past 23 years resulted in 78 articles that met the eligibility criteria and quality assessment. The results show that higher working memory capacity, as measured neuropsychologically, is associated with more consistent and safer driving-related parameters for drivers (e.g., lane keeping) and may be related to pupil dilation during risk perception while driving, which is associated with driving outcomes (tickets, pull-overs, penalty points and fines,and driving accidents) is closely related to the perceived usefulness of the human-machine interface, reaction time, standard deviation of steering wheel corners, etc. when the autonomous driving takes over. In addition, higher working memory load interference was associated with more inconsistent and unsafe driving-related parameters (including but not limited to eye movements, electrophysiology, etc.), with higher working memory load being associated with easier driver concentration on the road, faster heart rate, lower heart rate variability, and lower oxyhemoglobin (OxyHb) and deoxyhemoglobin (DeoxyHb). Only a limited number of studies have simultaneously investigated the relationship between working memory capacity, working memory load and driving, showing an interaction between working memory capacity and working memory load on lane change initiation and lane change correctness, with working memory capacity acting as a covariate that mediated the effect of working memory load on braking reaction time. In addition, working memory-related cognitive training had a transfer effect on improving driving ability. Overall, working memory capacity determines the upper limit of the number of working memory attention resources, while working memory load occupies part of the working memory attention resources, thus influencing information perception, decision judgment, operational response, and collision avoidance in driving. Future effective interventions for safe driving can be combined with capacity training and load alerting. These findings contribute to our understanding of the role of working memory in driving and provide new insights into the design of driver safety training programs and automated driving personalized in-vehicle safety systems and roadside devices such as signage.

Age-Related Diseases and Driving Safety

Due to demographic changes, the number of older drivers is steadily increasing. Mobility is highly relevant for leading an independent life in the elderly. It largely depends on car driving, which is a complex task requiring a multitude of cognitive and motor skills vulnerable to age- related functional deterioration. The almost inevitable effects of senescence may be potentiated by age-related diseases, such as stroke or diabetes mellitus. Respective pharmacological treatment may cause side effects, additionally affecting driving safety. The present article reviews the impact of age-related diseases and drug treatment of these conditions on driving fitness in elderly drivers. In essence, we focus on diseases of the visual and auditory systems, diseases of the central nervous system (i.e., stroke, depression, dementia and mild cognitive disorder, and Parkinson's disease), sleep disorders, as well as cardiovascular diseases, diabetes mellitus, musculoskeletal disorders, and frailty. We will outline the role of functional tests and the assessment of driving behavior (by a driving simulator or in real traffic), as well as the clinical interview including questions about frequency of (near) accidents, etc. in the evaluation of driving fitness of the elderly. We also address the impact of polypharmacy on driving fitness and end up with recommendations for physicians caring for older patients.

Type 2 diabetes can undermine driving performance of middle-aged male drivers through its deterioration of perceptual and cognitive functions

It has been widely agreed that it is risky for patients with diabetes to drive during hypoglycemia. However, driving during non-hypoglycemia may also bring certain safety hazards for some patients with diabetes. Based on previous studies on diabetes-related to early aging effect, as well as gender differences in health belief and driving behavior, we have hypothesized that middle-aged male drivers with type 2 diabetes, compared with the control healthy ones, may experience a decline in driving performance without awareness. And the decline is caused by impaired perceptual and cognitive driving-related functions. To verify these hypotheses, we recruited 56 non-professional male drivers aged between 40 and 60 (27 patients with type 2 diabetes and 29 healthy controls) to perform a simulated car-following task and finish behavioral tests of proprioception, visual search, and working memory abilities during non-hypoglycemia. They also reported their hypoglycemia experience and perceived driving skills. We found that the patients had equal confidence in their driving skills but worse driving performance as shown in larger centerline deviation (t = 2.83, p = .006), longer brake reaction time (t = 3.77, p = .001) and shorter minimum time-to-collision (t = -3.27, p = .002). Such between-group differences in driving performance could be fully mediated by proprioception, visual search ability, and working memory capacity but not by hypoglycemia experience. Regarding the effect sizes of the mediation, the visual search ability played the most important role, and then followed the working memory and the proprioception. This initial study provides original and first-hand evidence demonstrating that the middle-aged male drivers with type 2 diabetes have deteriorated driving performance, but they are unaware of it. We will also discuss the possible measures to identify people of the highest risk and improve their safety awareness by using the findings of the current study.

Predicting and Reducing Driving Mishaps Among Drivers With Type 1 Diabetes

OBJECTIVE

Two aims of this study were to develop and validate A) a metric to identify drivers with type 1 diabetes at high risk of future driving mishaps and B) an online intervention to reduce mishaps among high-risk drivers.

RESEARCH DESIGN AND METHODS

To achieve aim A, in study 1, 371 drivers with type 1 diabetes from three U.S. regions completed a series of established questionnaires about diabetes and driving. They recorded their driving mishaps over the next 12 months. Questionnaire items that uniquely discriminated drivers who did and did not have subsequent driving mishaps were assembled into the Risk Assessment of Diabetic Drivers (RADD) scale. In study 2, 1,737 drivers with type 1 diabetes from all 50 states completed the RADD online. Among these, 118 low-risk (LR) and 372 high-risk (HR) drivers qualified for and consented to participate in a 2-month treatment period followed by 12 monthly recordings of driving mishaps. To address aim B, HR participants were randomized to receive either routine care (RC) or the online intervention "DiabetesDriving.com" (DD.com). Half of the DD.com participants received a motivational interview (MI) at the beginning and end of the treatment period to boost participation and efficacy. All of the LR participants were assigned to RC. In both studies, the primary outcome variable was driving mishaps.

RESULTS

Related to aim A, in study 1, the RADD demonstrated 61% sensitivity and 75% specificity. Participants in the upper third of the RADD distribution (HR), compared with those in the lower third (LR), reported 3.03 vs. 0.87 mishaps/driver/year, respectively (P < 0.001). In study 2, HR and LR participants receiving RC reported 4.3 and 1.6 mishaps/driver/year, respectively (P < 0.001). Related to aim B, in study 2, MIs did not enhance participation or efficacy, so the DD.com and DD.com + MI groups were combined. DD.com participants reported fewer hypoglycemia-related driving mishaps than HR participants receiving RC (P = 0.01), but more than LR participants receiving RC, reducing the difference between the HR and LR participants receiving RC by 63%. HR drivers differed from LR drivers at baseline across a variety of hypoglycemia and driving parameters.

CONCLUSIONS

The RADD identified higher-risk drivers, and identification seemed relatively stable across time, samples, and procedures. This 11-item questionnaire could inform patients at higher risk, and their clinicians, that they should take preventive steps to reduce driving mishaps, which was accomplished in aim B using DD.com.

Diabetes and collision risk. A meta-analysis and meta-regression

AIMS

The main objective of this study was to see whether diabetes is associated with an increased collision risk and to test the effect of age and gender on the overall collision risk for diabetes drivers.

MATERIALS AND METHODS

Twenty-eight studies were included in meta-analysis, using mean age, gender, continent and the prevalence of fatal road incidents as covariates.

RESULTS

The collision risk for diabetes drivers was small and not statistically significant - RR = 1.11 (1.01-1.23) with a prediction interval (PI) or 0.77-1.65. Age and gender were not associated with an increased overall risk. Insulin-dependent diabetes patients had a slightly increased effect size compared with the overall diabetes population, but the effect was not statistically significant. European diabetes drivers had a lower collision risk compared with their North American counterparts, the main cause being the difference of collision risk in the countries in which the studies were performed.

CONCLUSIONS

Overall, diabetes patients do not have a statistically significant increased risk for unfavourable traffic events. Old age and insulin-dependent patients tend to have a higher risk. Advances in diabetes care, associated with advances in road safety regulations, and automotive industry have not decreased significantly the collision risk in the last 50 years for drivers with diabetes.

Traumatic injuries in patients with diabetes mellitus

Diabetes mellitus (DM) is associated with increased in-hospital morbidity and mortality in patients sustained traumatic injuries. Identification of risk factors of traumatic injuries that lead to hospital admissions and death in DM patients is crucial to set effective preventive strategies. We aimed to conduct a traditional narrative literature review to describe the role of hypoglycemia as a risk factor of driving and fall-related traumatic injuries. DM poses significant burden as a risk factor and predictor of worse outcomes in traumatic injuries. Although there is no consensus on the impact and clear hazards of hyperglycemia in comparison to the hypoglycemia, both extremes of DM need to be carefully addressed and taken into consideration for proper management. Moreover, physicians, patients, and concerned authorities should be aware of all these potential hazards to share and establish the right management plans.

Driving and diabetes: problems, licensing restrictions and recommendations for safe driving

Driving is a complex process that places considerable demands on cognitive and physical functions. Many complications of diabetes can potentially impair driving performance, including those affecting vision, cognition and peripheral neural function. Hypoglycemia is a common side-effect of insulin and sulfonylurea therapy, impairing many cognitive domains necessary for safe driving performance. Driving simulator studies have demonstrated how driving performance deteriorates during hypoglycemia. Driving behavior that may predispose to hypoglycemia while driving is examined. Studies examining the risk of road traffic accidents in people with insulin-treated diabetes have produced conflicting results, but the potential risk of hypoglycemia-related road traffic accidents has led to many countries imposing restrictions on the type and duration of driving licenses that can be issued to drivers with diabetes. Guidance that promotes safe driving practice has been provided for drivers with insulin-treated diabetes, which is the group principally addressed in this review.

Diabetes and driving safety: science, ethics, legality and practice

Diabetes affects over 25 million people in the United States, most of whom are over the age of 16 and many of whom are licensed to drive a motor vehicle. Safe operation of a motor vehicle requires complex interactions of cognitive and motor functions and medical conditions that affect these functions often will increase the risk of motor vehicle accidents (MVA). In the case of diabetes, hypoglycemia is the most common factor that has been shown to increase MVA rates. When people with diabetes are compared with nondiabetic controls, systematic analyses show that the relative risk of MVA is increased by between 12% and 19% (Relative Risk Ratio 1.12-1.19). In comparison, the RRR for attention deficit hyperactivity disorder is 4.4 and for sleep apnea is 2.4. Epidemiologic research suggests that patients at risk for hypoglycemia-related MVAs may have some characteristics in common, including a history of severe hypoglycemia or of hypoglycemia-related driving mishaps. Experimental studies also have shown that people with a history of hypoglycemia-related driving mishaps have abnormal counter-regulatory responses to hypoglycemia and greater cognitive impairments during moderate hypoglycemia.

Islet transplantation in type 1 diabetes: ongoing challenges, refined procedures, and long-term outcome

Remarkable progress has been made in islet transplantation over a span of 40 years. Once just an experimental curiosity in mice, this therapy has moved forward, and can now provide robust therapy for highly selected patients with type 1 diabetes (T1D), refractory to stabilization by other means. This progress could not have occurred without extensive dynamic international collaboration. Currently, 1,085 patients have undergone islet transplantation at 40 international sites since the Edmonton Protocol was reported in 2000 (752 allografts, 333 autografts), according to the Collaborative Islet Transplant Registry. The long-term results of islet transplantation in selected centers now match registry data of pancreas-alone transplantation, with 6 sites reporting five-year insulin independence rates ≥50%. Islet transplantation has been criticized for the use of multiple donor pancreas organs, but progress has also occurred in single-donor success, with 10 sites reporting increased single-donor engraftment. The next wave of innovative clinical trial interventions will address instant blood-mediated inflammatory reaction (IBMIR), apoptosis, and inflammation, and will translate into further marked improvements in single-donor success. Effective control of auto- and alloimmunity is the key to long-term islet function, and high-resolution cellular and antibody-based assays will add considerable precision to this process. Advances in immunosuppression, with new antibody-based targeting of costimulatory blockade and other T-B cellular signaling, will have further profound impact on the safety record of immunotherapy. Clinical trials will move forward shortly to test out new human stem cell derived islets, and in parallel trials will move forward, testing pig islets for compatibility in patients. Induction of immunological tolerance to self-islet antigens and to allografts is a difficult challenge, but potentially within our grasp.

Driving safety: concerns and experiences of parents of adolescent drivers with type 1 diabetes

Driving is a dangerous activity for adolescents, perhaps being even more precarious for adolescents with type 1 diabetes due to the possibility of extreme blood glucose (BG). There is no available data on adolescent driving safety concerns and type 1 diabetes. To begin addressing this issue, we surveyed parents regarding their observations and concerns. Seventy-two parents (87.5% mothers) of adolescent drivers aged 16-19 with type 1 diabetes provided analyzable data. Females comprised 36% of their adolescents, with 74% using pump therapy. In the past year, 13 and 84% of parents reported that their adolescent had experienced severe or moderate disruptive hypoglycemia, respectively. Over half (56%) of the parents reported moderate to extreme worry about how diabetes impacted their adolescent's driving, while only 21% of parents thought their adolescents had similar concerns (p = 0.037). Almost one third (31%) of parents thought their adolescent need not treat low BG until it fell below 70 mg/dL, 13% thought their adolescent could safely drive with BG below 65 mg/dL. And, 31 and 14% of parents, respectively, reported their adolescent had been in a collision or stopped by the police in the past year, which they attributed to both hypo- and hyperglycemia. Adolescents reportedly took steps to prevent hypo- and hyperglycemia while driving, but more aggressively avoided hypoglycemia (p < 0.001). While this data is limited, lacking a non-diabetic control group and randomized sample, it does suggest that driving and adolescent type 1 diabetes deserve further attention and investigation.

Metabolic Demand of Driving Among Adults with Type 1 Diabetes Mellitus (T1DM)

Recent research suggests that the frequency of driving mishaps is increased in people with Type 1 diabetes (T1DM) as compared to those with Type 2 diabetes or their non-diabetic spouses. This study involved a sample of T1DM drivers and was designed to investigate the metabolic and physiologic demands of driving compared to sitting passively. Participants (N=38) were divided into two groups: the -History group included those reporting no driving mishaps in the past two years, and the +History group included participants reporting at least two such mishaps in the past two years. Glucose utilization rates were determined in participants while: (a) they were driving a virtual reality driving simulator for 30 minutes, and (b) watching a 30-minute video. Blood glucose (BG) levels were maintained at similar levels during both procedures. Other biological variables including heart rate (HR) were monitored. Participants rated their hypoglycemia (low BG) symptoms before and after each of the two procedures. . Participants could self-treat if they perceived they were experiencing hypoglycemia. There were no differences between the two groups. However, glucose utilization rates were significantly higher during the driving scenario (3.83mg/kg/min + 1.7 vs. 3.37 mg/kg/min + 1.6, p=0.047). HR was significantly higher during the driving scenario. Drivers reported more autonomic symptoms during driving and 32% treated perceived hypoglycemia during driving. Driving a virtual reality simulator is associated with increased glucose utilization rates suggesting that driving per se has a metabolic cost and that BG should be measured prior to driving and periodically during long drives.