Examination of personality traits and social problem-solving skills of individuals whose driving licenses have been confiscated due to drunk driving

Objective: Drunk driving is one of the major behavioral issues connected with problematic alcohol consumption. The objective of this study was to evaluate the relationship between personality traits and social problem-solving skills of individuals who drive while intoxicated.

Method: One hundred forty-four individuals apprehended twice while driving drunk and sent to a driver behavior training program (9 females and 135 males) participated in our study. The Eysenck Personality Questionnaire Revised–Abbreviated (EPQ-RA) composed of 4 subscales (Extroversion, Neuroticism, Psychoticism, and Lying) and the Social Problem Solving Inventory (SPSI) composed of 7 subscales (Cognitive, Emotion, Behavior, Problem Definition and Formulation, Creating Solution Options, Solution Implementation and Verification, and Decision Making) were used to evaluate the participants.

Results: A positive relationship was found between the Extroversion subscale of the EPQ-RA and the Cognition subscale (P <.01), Emotion subscale (P <.01), Behavior subscale (P <.01), Generation of Alternatives subscale (P <.01), Decision Making subscale (P <.05), and Solution Implementation and Verification subscale (P <.01). For individuals who repeated intoxicated driving, all subscales of the EPQ-RA (Extroversion, Lying, Neuroticism, and Psychoticism subscales) explained 12% of the scores of the Cognition subscale and 16.2% (P <.001) of the Emotion subscale of the SPSI. There was no significant relationship between the first and second incident alcohol blood levels (P >.05).

Conclusion: Drinking and driving behaviors appear to be negative or maladaptive behaviors closely related to personality traits and may represent an effort to avoid negative emotions. Evaluation of negative emotions may have an important place in training programs intended to change drunk driving behavior.     

Virtual street-crossing performance in persons with multiple sclerosis: Feasibility and task performance characteristics

Objectives: Multiple sclerosis (MS) is a neurological disease that commonly results in physical and cognitive dysfunction. Accordingly, MS might impact the ability to safely cross the street. The purpose of this study was to examine the feasibility of a simulated street-crossing task in persons with MS and to determine differences in street-crossing performance between persons with MS and non-MS controls.

Methods: 26 participants with MS (median Expanded Disability Status Scale [EDSS] score = 3.5) and 19 controls completed 40 trials of a virtual street-crossing task. There were 2 crossing conditions (i.e., no distraction and phone conversation), and participants performed 20 trials per condition. Participants were instructed that the goal of the task was to cross the street successfully (i.e., without being hit be a vehicle). The primary outcome was task feasibility, assessed as completion and adverse events. Secondary outcomes were measures of street-crossing performance.

Results: Overall, the simulated street-crossing task was feasible (i.e., 90% completion, no adverse events) in participants with MS. Participants with MS waited longer and were less attentive to traffic before entering the street compared with controls (all P < .05). Participants with MS also took longer to cross the street and were closer to oncoming vehicles when exiting the street compared to controls (all P < .05). When distracted, all participants took longer to initiate crossing, took longer to cross the street, and made more head turns while crossing (all P < .05). There were no significant group by condition interaction effects (all P > .05).

Conclusions: A virtual street-crossing task is feasible for studying street-crossing behavior in persons with mild MS and most individuals with moderate MS. Virtual street-crossing performance is impaired in persons with MS compared to controls; however, persons with MS do not appear to be more vulnerable to a distracting condition. The virtual reality environment presents a safe and useful setting for understanding pedestrian behavior in persons with MS.     

Driving violations and health promotion behaviors among undergraduate students: Self-report of on-road behavior

Introduction: The purposes of this study are to characterize Israeli undergraduate students' driving violations in the terms of problem behavior theory and to identify whether there is any relationship between driving violations and health risk behaviors, daring behaviors, excitement seeking, and health promotion behaviors.

Methods: This study is based on a structured self-reported anonymous questionnaire distributed to undergraduate students in an academic institution. The sample included 533 undergraduate students (374 females and 159 males). The mean age was 23.4 (SD = 1.4, range = 5).

Results: A higher prevalence of self-reported driving violations was found among males in comparison to females. All substance use measures were positively related to driving violations; for example, use of cigarettes (OR = 4.287, P <.001) and water pipes (odds ratio [OR] = 3.000, P <.001) as well as binge drinking (OR = 5.707, P <.001) and regular cannabis smoking (OR = 5.667, P <.001) raise the probability of committing rare driving violations. The strongest predictive factors for the frequent driving violations group were alcohol consumption–related variables: binge drinking (OR = 2.560, P <.01) and drunkenness (OR = 2.284, P <.05). Strong odd ratios were also found between the frequent driving violations group and selling or dealing drugs (12.143, P <.001), and stealing something valuable (13.680, P <.001). The strongest predicted variable for the rare driving violations group was physical confrontation due to verbal disagreement (3.439, P <.05) and the concept that selling or dealing drugs is socially acceptable (2.521, P <.05). The probability of executing rare driving violations was higher for subjects who reported intense physical workout regimens (OR = 1.638, P <.05).

Conclusions: Problem behavior theory succeeded in explaining health risk behavior and driving violations. This study shows that bachelors tend to be more involved in risk behaviors, such as substance use, excitement-seeking behaviors, and daring behaviors and are active physically and thus constitute a risk group for driving violations. As such, intervention resources should be directed toward this group.     

State helmet laws and helmet use among fatally injured moped riders in the United States, 2011–2015

Objective: Research has found that mandatory motorcycle helmet laws increase helmet use and reduce motorcycle-related fatalities. However, the association between state moped helmet laws and helmet use in the United States has not been examined. This study investigated this association among a census of fatally injured moped riders in the United States.

Methods: A logistic regression model was constructed to analyze data extracted from the Fatality Analysis Reporting System (FARS) to examine risk factors for helmet nonuse among 572 moped riders fatally injured between 2011 and 2015.

Results: Fatally injured moped riders in states with universal helmet laws had 69 times the odds of wearing a helmet (P < .001).

Conclusions: Findings suggest that universal moped helmet laws increase helmet use. However, additional research is needed to examine helmet laws and use among nonfatally injured moped riders.     

Drink driving and risky behavior among university students in southwestern Nigeria—Implications for policy development

Background: Drink driving contributes significantly to road traffic injuries. Little is known about the relationship between drink driving and other high-risk behaviors in non-Western countries. The study aimed to assess the relationship between drink driving and other risky behaviors including making phone calls, sending text messages, nonuse of protective gear, and driving against traffic.

Methods: A cross-sectional survey of risky behavior among undergraduates was conducted. A stratified random sampling method was used to identify young undergraduates who had driven a motorized vehicle in the past year. The Alcohol Use Disorder Identification Test (AUDIT) and other tools developed by researchers were used to identify the risky behaviors.

Results: Of 431 respondents, 10.7% had engaged in drink driving in the past 12 months. The most common risky behavior was making phone calls (63.7%), followed by nonuse of helmets (54.7%), driving against traffic (49.2%), nonuse of seat belts (46.8%), and sending text messages (26.1%). Alcohol use was significantly associated with making phone calls (U = 1.148; P < .0001), sending text messages (U = 1.598; P = .021), nonuse of helmets (U = 1.147; P < .0001), driving against traffic (U = 1.234; P < .0001), and nonuse of seat belts (U = 3.233; P = .001). Drink driving was associated with all risky behaviors except nonuse of seat belts (U = 1.842; P = .065).

Conclusion: Alcohol use and drink driving were associated with multiple risky driving behaviors. This provides useful insight for policy development and presents additional challenges for traffic injury prevention.     

Covariability in three dimensions of teenage driving risk behavior: impaired driving,risky and unsafe driving behavior,and secondary task engagement

Objective: This research examined the extent to which teenagers who engaged in one form of risky driving also engaged in other forms and whether risky driving measures were reciprocally associated over time.

Methods: The data were from waves 1, 2, and 3 (W1, W2, and W3) of the NEXT Generation study, with longitudinal assessment of a nationally representative sample starting with 10th graders starting in 2009–2010. Three measures of risky driving were assessed in autoregressive and cross-lagged analyses: driving while alcohol/drug impaired (DWI), Checkpoints Risky Driving Scale (risky and unsafe driving), and secondary task engagement while driving.

Results: In adjusted autoregression models, the risk variables demonstrated high levels of stability, with significant associations observed across the 3 waves. However, associations between variables were inconsistent. DWI at W2 was associated with risky and unsafe driving at W3 (β = 0.21, P < .01); risky and unsafe driving at W1 was associated with DWI at W2 (β = 0.20, P < .01); and risky and unsafe driving at W2 is associated with secondary task engagement at W3 (β = 0.19, P < .01). Over time, associations between DWI and secondary task engagement were not significant.

Conclusions: Our findings provide modest evidence for the covariability of risky driving, with prospective associations between the Risky Driving Scale and the other measures and reciprocal associations between all 3 variables at some time points. Secondary task engagement, however, appears largely to be an independent measure of risky driving. The findings suggest the importance of implementing interventions that addresses each of these driving risks.     

Crash risk perception of sleepy driving and its comparisons with drink driving and speeding: Which behavior is perceived as the riskiest?

Objective: Driver sleepiness is a major crash risk factor but may be underrecognized as a risky driving behavior. Sleepy driving is usually rated as less of a road safety issue than more well-known risky driving behaviors, such as drink driving and speeding. The objective of this study was to compare perception of crash risk of sleepy driving, drink driving, and speeding.

Methods: Three hundred Australian drivers completed a questionnaire that assessed crash risk perceptions for sleepy driving, drink driving, and speeding. Additionally, the participants' perceptions of crash risk were assessed for 5 different contextual scenarios that included different levels of sleepiness (low, high), driving duration (short, long), and time of day/circadian influences (afternoon, nighttime) of driving.

Results: The analysis confirmed that sleepy driving was considered a risky driving behavior but not as risky as high levels of speeding (P < .05). Yet, the risk of crashing at 4 a.m. was considered as equally risky as low levels of speeding (10 km over the limit). The comparisons of the contextual scenarios revealed driving scenarios that would arguably be perceived as quite risky because time of day/circadian influences were not reported as high risk.

Conclusions: The results suggest a lack of awareness or appreciation of circadian rhythm functioning, particularly the descending phase of circadian rhythm that promotes increased sleepiness in the afternoon and during the early hours of the morning. Yet, the results suggested an appreciation of the danger associated with long-distance driving and driver sleepiness. Further efforts are required to improve the community's awareness of the impairing effects from sleepiness and, in particular, knowledge regarding the human circadian rhythm and the increased sleep propensity during the circadian nadir.     

Helmet retention system types as a risk factor to properly attach the chin strap

Objectives: This study aimed to determine the factors associated with the incorrect use of a helmet retention system (loose or open) and how often this happens.

Methods: This was an observational transversal study conducted in Curitiba, Brazil. Trained observers positioned at traffic lights collected information about the helmet fixation mode, the helmet model (full-face, open-face, modular, half), and the helmet retention system model (micrometric, double-D, fast-release). Additional data including position on the motorcycle, gender, and function of the motorcycle (as a work vehicle) were collected. The observers, collection site, and periods were randomly selected by lots.

Results: From a total of 3,050 motorcyclists, 1,807 (59.2%) had their helmets fastened correctly, 907 (29.7%) had the retention system fastened loosely, and in 336 (11.0%), the retention system was completely open. Increased odds of incorrect use were observed for the fast-release and double-D buckles compared to the micrometrics buckles, with a fixed odds ratio (OR) of 4.62 (95% confidence interval [CI], 3.89–5.51) and 3.54 (95% CI, 2.46–5.09), respectively (P <.0001). Full-face helmets had a higher chance of incorrect use (P <.0001), and passengers had a higher incidence of incorrect use of the helmet than drivers (P <.0001).

Conclusion: An important risk factor related to the incorrect use of the helmet was the type of retention system. The helmet model and being a passenger had a secondary influence on incorrect use of helmets.     

Potentially preventable prehospital deaths from motor vehicle collisions

Background: In 2011, about 30,000 people died in motor vehicle collisions (MVCs) in the United States. We sought to evaluate the causes of prehospital deaths related to MVCs and to assess whether these deaths were potentially preventable.

Methods: Miami–Dade Medical Examiner records for 2011 were reviewed for all prehospital deaths of occupants of 4-wheeled motor vehicle collisions. Injuries were categorized by affected organ and anatomic location of the body. Cases were reviewed by a panel of 2 trauma surgeons to determine cause of death and whether the death was potentially preventable. Time to death and hospital arrival times were determined using the Fatality Analysis Reporting System (FARS) data from 2002 to 2012, which allowed comparison of our local data to national prevalence estimates.

Results: Local data revealed that 39% of the 98 deaths reviewed were potentially preventable (PPD). Significantly more patients with PPD had neurotrauma as a cause of death compared to those with a nonpreventable death (NPD) (44.7% vs. 25.0%, P =.049). NPDs were significantly more likely to have combined neurotrauma and hemorrhage as cause of death compared to PPDs (45.0% vs. 10.5%, P <.001). NPDs were significantly more likely to have injuries to the chest, pelvis, or spine. NPDs also had significantly more injuries to the following organ systems: lung, cardiac, and vascular chest (all P <.05). In the nationally representative FARS data from 2002 to 2012, 30% of deaths occurred on scene and another 32% occurred within 1 h of injury. When comparing the 2011 FARS data for Miami–Dade to the remainder of the United States in that year, percentage of deaths when reported on scene (25 vs. 23%, respectively) and within 1 h of injury (35 vs. 32%, respectively) were similar.

Conclusions: Nationally, FARS data demonstrated that two thirds of all MVC deaths occurred within 1 h of injury. Over a third of prehospital MVC deaths were potentially preventable in our local sample. By examining injury patterns in PPDs, targeted intervention may be initiated.     

The effect of helmets on motorcycle outcomes in a level I trauma center in Connecticut

Objective: The State of Connecticut has a partial motorcycle helmet law, which has been linked to one of the lowest helmet compliance rates in the Northeast. We examine the clinical and financial impact of low motorcycle helmet use in the State of Connecticut.

Methods: A retrospective cohort study comparing the outcomes between helmeted and nonhelmeted motorcycle crash victims over a 12.5-year period, from July 2, 2002, to December 31, 2013. All patients who were admitted to the hospital after a motorcycle crash were included in the study. Patients were stratified into helmeted and nonhelmeted cohorts. Group differences were compared using t-test or Wilcoxon rank test for continuous variables and chi-square test for dichotomous outcomes. Regression models were created to evaluate predictors of helmet use, alcohol and drugs as confounding variables, and factors that influenced hospital costs.

Results: The registry included 986 eligible patients. Of this group, 335 (34%) were helmeted and 651 (66%) were nonhelmeted. Overall, nonhelmeted patients had a worse clinical presentation, with lower Glasgow Coma Scale (GCS; P <.01), higher Injury Severity Score (ISS; P <.01), higher incidence of loss of consciousness (LOC; P <.01), longer intensive care unit (ICU; P <.01) admissions, and higher incidence of head (P <.01) or face injuries (P <.01). Nonhelmeted patients were also twice as more likely to die from their injuries (P =.04, odds ratio [OR] = 1.89, 95% confidence interval [CI], 1.02–3.45). Financially, nonhelmeted patients incurred mean hospital costs of $18,458, whereas helmeted patients incurred $14,970 (P =.18). ISS, GCS, and ICU length of stay were significantly correlated with increased hospital costs (P <.01). Not using a helmet was a significant predictor of mortality (P =.04) after adjusting for alcohol/drug use and age.

Conclusions: Helmet use is associated with lower injury severity and increased survival after a motorcycle crash. These outcomes remained consistent even after controlling for age and alcohol and drug use. The medical and financial impact of Connecticut's partial helmet law should be carefully evaluated to petition for increased education and enforcement of helmet use.     

Analysis of naturalistic driving videos of fleet services drivers to estimate driver error and potentially distracting behaviors as risk factors for rear-end versus angle crashes

Objective: The objective of this study was to estimate the prevalence and odds of fleet driver errors and potentially distracting behaviors just prior to rear-end versus angle crashes.

Methods: Analysis of naturalistic driving videos among fleet services drivers for errors and potentially distracting behaviors occurring in the 6 s before crash impact. Categorical variables were examined using the Pearson's chi-square test, and continuous variables, such as eyes-off-road time, were compared using the Student's t-test. Multivariable logistic regression was used to estimate the odds of a driver error or potentially distracting behavior being present in the seconds before rear-end versus angle crashes.

Results: Of the 229 crashes analyzed, 101 (44%) were rear-end and 128 (56%) were angle crashes. Driver age, gender, and presence of passengers did not differ significantly by crash type. Over 95% of rear-end crashes involved inadequate surveillance compared to only 52% of angle crashes (P < .0001). Almost 65% of rear-end crashes involved a potentially distracting driver behavior, whereas less than 40% of angle crashes involved these behaviors (P < .01). On average, drivers spent 4.4 s with their eyes off the road while operating or manipulating their cell phone. Drivers in rear-end crashes were at 3.06 (95% confidence interval [CI], 1.73–5.44) times adjusted higher odds of being potentially distracted than those in angle crashes.

Conclusions: Fleet driver driving errors and potentially distracting behaviors are frequent. This analysis provides data to inform safe driving interventions for fleet services drivers. Further research is needed in effective interventions to reduce the likelihood of drivers' distracting behaviors and errors that may potentially reducing crashes.     

High-risk behaviors while driving: A population-based study from Iran

Objective: Traffic injuries are becoming one of the most important challenges of public health systems. Because these injuries are mostly preventable, the aim of this study is to evaluate the four main high-risk behaviors while driving.

Methods: This cross-sectional study was conducted on a random sample from the population of Mashhad, Iran, in 2014. A checklist and a previously validated questionnaire for the transtheoretical stages of change model (TTM) were used for data collection. Statistical analyses were performed using SPSS 11.5 software with P <.05 statistically significant.

Results: Totally 431 individuals were included with a mean age of 30 ± 11.3 years. Forty-three percent (183) were male. The TTM model revealed that participants were mostly in pre-actional phases regarding not using a cell phone while driving (80%), fastening the driver's seat belt (66%), front seat belt (68%), and rear seat belt (85%) The penalty was a protective factor only for using cellphone (odd ratio [OR] = 0.82, 95% confidence interval [CI], 0.68–0.98). Lower education (OR = 0.12, 95% CI, 0.01–0.94) and male gender (OR = 0.35, 95% CI, 0.14–0.83) were indicative of lower rates of fastening the front and rear seat belts.

Conclusion: The stages of change model among study participants is a proper reflection of the effectiveness of the current policies. More serious actions regarding these high-risk behaviors should be considered in legislation.     

Evaluation of give kids a boost: A school-based program to increase booster seat use among urban children in economically disadvantaged areas

Objective: This study evaluated the effectiveness of a series of 1-year multifaceted school-based programs aimed at increasing booster seat use among urban children 4–7 years of age in economically disadvantaged areas.

Methods: During 4 consecutive school years, 2011–2015, the Give Kids a Boost (GKB) program was implemented in a total of 8 schools with similar demographics in Dallas County. Observational surveys were conducted at project schools before project implementation (P₀), 1–4 weeks after the completion of project implementation (P₁), and 4–5 months later (P₂). Changes in booster seat use for the 3 time periods were compared for the 8 project and 14 comparison schools that received no intervention using a nonrandomized trial process.

The intervention included (1) train-the-trainer sessions with teachers and parents; (2) presentations about booster seat safety; (3) tailored communication to parents; (4) distribution of fact sheets/resources; (5) walk-around education; and (6) booster seat inspections.

The association between the GKB intervention and proper booster seat use was determined initially using univariate analysis. The association was also estimated using a generalized linear mixed model predicting a binomial outcome (booster seat use) for those aged 4 to 7 years, adjusted for child-level variables (age, sex, race/ethnicity) and car-level variables (vehicle type). The model incorporated the effects of clustering by site and by collection date to account for the possibility of repeated sampling.

Results: In the 8 project schools, booster seat use for children 4–7 years of age increased an average of 20.9 percentage points between P₀ and P₁ (P₀ = 4.8%, P₁ = 25.7%; odds ratio [OR] = 6.9; 95% confidence interval [CI], 5.5, 8.7; P < .001) and remained at that level in the P₂ time period (P₂ = 25.7%; P < .001, for P₀ vs. P₂) in the univariate analysis. The 14 comparison schools had minimal change in booster seat use. The multivariable model showed that children at the project schools were significantly more likely to be properly restrained in a booster seat after the intervention (OR = 2.7; 95% CI, 2.2, 3.3) compared to the P₀ time period and compared to the comparison schools.

Conclusion: Despite study limitations, the GKB program was positively associated with an increase in proper booster seat use for children 4–7 years of age in school settings among diverse populations in economically disadvantaged areas. These increases persisted into the following school year in a majority of the project schools. The GKB model may be a replicable strategy to increase booster seat use among school-age children in similar urban settings.     

Driving performance comparing older versus younger drivers

Objectives: A cross-sectional study was conducted at the Touro University California campus to compare differences in reaction times and driving performance of younger adult drivers (18–40 years) and older adult drivers (60 years and older). Each test group consisted of 38 participants.

Methods: A Simple Visual Reaction Test (SVRT) tool was used to measure reaction times. The STISIM Drive M100 driving simulator was used to assess driving parameters. Driving performance parameters included mean lane position, standard deviation of mean lane position measured, mean speed, standard deviation of mean speed, car-following delay, car-following modulus, car-following coherence, off-road accidents, collisions, pedestrians hit, and traffic light tickets.

Results: Compared to younger participants, older drivers experienced significantly slower reaction times (510.0 ± 208.8 vs. 372.4 ± 96.1 ms, P =.0004), had more collisions (0.18 ± 0.39 vs. none, P =.0044), drove slower (44.6 ± 6.6 vs. 54.9 ± 11.7 mph, P <.0001), deviated less in speed (12.6 ± 4.3 vs. 16.8 ± 6.3, P =.0011), and were less able to maintain a constant distance behind a pace car (0.42 ± 0.23 vs. 0.59 ± 0.24; P =.0025).

Conclusions: Differences exist in driving patterns of older and younger drivers as measured by reaction times and driving simulator outcomes. These results are the first to compare these 2 specific adult age groups' driving performance as measured by a standardized driving simulator scenario. Identifying these differences is essential in addressing them and preventing future traffic injuries.     

Exploring the association between working memory and driving performance in Parkinson's disease

Objective: The aim of this study was to explore whether varying levels of operational and tactical driving task demand differentially affect drivers with Parkinson's disease (PD) and control drivers in their sign recall.

Methods: Study participants aged between 50 and 70 years included a group of drivers with PD (n = 10) and a group of age- and sex-matched control drivers (n = 10). Their performance in a sign recall task was measured using a driving simulator.

Results: Drivers in the control group performed better than drivers with PD in a sign recall task, but this trend was not statistically significant (P =.43). In addition, regardless of group membership, subjects' performance differed according to varying levels of task demand. Performance in the sign recall task was more likely to drop with increasing task demand (P =.03). This difference was significant when the variation in task demand was associated with a cognitive task; that is, when drivers were required to apply the instructions from working memory.

Conclusions: Although the conclusions drawn from this study are tentative, the evidence presented here is encouraging with regard to the use of a driving simulator to examine isolated cognitive functions underlying driving performance in PD. With an understanding of its limitations, such driving simulation in combination with functional assessment batteries measuring physical, visual, and cognitive abilities could comprise one component of a multitiered system to evaluate medical fitness to drive.     

Experimental investigation of the effect of occupant characteristics on contemporary seat belt payout behavior in frontal impacts

Objective: The goal of this study was to investigate the influence of the occupant characteristics on seat belt force vs. payout behavior based on experiment data from different configurations in frontal impacts.

Methods: The data set reviewed consists of 58 frontal sled tests using several anthropomorphic test devices (ATDs) and postmortem human subjects (PMHS), restrained by different belt systems (standard belt, SB; force-limiting belt, FLB) at 2 impact severities (48 and 29 km/h). The seat belt behavior was characterized in terms of the shoulder belt force vs. belt payout behavior. A univariate linear regression was used to assess the factor significance of the occupant body mass or stature on the peak tension force and gross belt payout.

Results: With the SB, the seat belt behavior obtained by the ATDs exhibited similar force slopes regardless of the occupant size and impact severities, whereas those obtained by the PMHS were varied. Under the 48 km/h impact, the peak tension force and gross belt payout obtained by ATDs was highly correlated to the occupant stature (P =.03, P =.02) and body mass (P =.05, P =.04), though no statistical difference with the stature or body mass were noticed for the PMHS (peak force: P =.09, P =.42; gross payout: P =.40, P =.48). With the FLB under the 48 km/h impact, highly linear relationships were noticed between the occupant body mass and the peak tension force (R² = 0.9782) and between the gross payout and stature (R² = 0.9232) regardless of the occupant types.

Conclusions: The analysis indicated that the PMHS characteristics showed a significant influence on the belt response, whereas the belt response obtained with the ATDs was more reproducible. The potential cause included the occupant anthropometry, body mass distribution, and relative motion among body segments specific to the population variance. This study provided a primary data source to understand the biomechanical interaction of the occupant with the restraint system. Further research is necessary to consider these effects in the computational studies and optimized design of the restraint system in a more realistic manner.     

The use and safety of medications known to affect driving in Jordan: A cross-sectional study

Objectives: The aim of this study was to estimate the main driving-impairing medications used by drivers in Jordan, the reported frequency of medication side effects, the frequency of motor vehicle crashes (MVCs) while using driving-impairing medicines, as well as factors associated with MVCs.

Methods: A cross-sectional study involving 1,049 individuals (age 18–75 years) who are actively driving vehicles and taking at least one medication known to affect driving (anxiolytics, antidepressants, hypnotics, antiepileptics, opioids, sedating antihistamines, hypoglycemic agents, antihypertensives, central nervous system [CNS] stimulants, and herbals with CNS-related effects) was conducted in Amman, Jordan, over a period of 8 months (September 2013–May 2014) using a structured validated questionnaire.

Results: Sixty-three percent of participants noticed a link between a medicine taken and feeling sleepy and 57% stated that they experience at least one adverse effect other than sleepiness from their medication. About 22% of the participants reported having a MVC while on medication. Multiple logistic regression analysis showed that among the participants who reported having a crash while taking a driving-impairing medication, the odds ratios were significantly higher for the use of inhalant substance (odds ratio [OR] = 2.787, P = .014), having chronic conditions (OR = 1.869, P = .001), and use of antiepileptic medications (OR = 2.348, P = .008) and significantly lower for the use of antihypertensives (OR = 0.533, P = .008).

Conclusion: The study results show high prevalence of adverse effects of medications with potential for driving impairment, including involvement in MVCs. Our findings highlight the types of patient-related and medication-related factors associated with MVCs in Jordan, such as inhalant use, presence of chronic conditions, and use of antiepileptics.     

Prevalence of alcohol-impaired driving and riding in northern Ghana

Objective: The objective of this study was to determine the roadside prevalence of alcohol-impaired driving among drivers and riders in northern Ghana. The study also verifies motorists' perceptions of their own alcohol use and knowledge of the legal blood alcohol concentration (BAC) limit in Ghana.

Method: With the assistance of police, systematic random sampling was used to collect data at roadblocks using a cross-sectional study design. Breathalyzers were used to screen whether motorists had detectable alcohol in their breath and follow-up breath tests were conducted to measure the actual breath alcohol levels among positive participants.

Results: In all, 9.7% of the 789 participants had detectable alcohol, among whom 6% exceeded the legal BAC limit of 0.08%. The prevalence of alcohol-impaired driving/riding was highest among cyclists (10% of all cyclists breath-tested) followed by truck drivers (9%) and motorcyclists (7% of all motorcyclists breath-tested). The occurrence of a positive BAC among cyclists was about 8 times higher (odds ratio [OR] = 7.73; P < .001) and it was 2 times higher among motorcyclists (OR = 2.30; P = .039) compared to private car drivers. The likelihood for detecting a positive BAC among male motorists/riders was higher than that among females (OR = 1.67; P = .354). The odds for detecting a positive BAC among weekend motorists/riders was significantly higher than on weekdays (OR = 2.62; P = .001).

Conclusion: Alcohol-impaired driving/riding in Ghana is high by international standards. In order to attenuate the harmful effects of alcohol misuse such as alcohol-impaired driving/riding, there is the need to educate road users about how much alcohol they can consume and stay below the legal limit. The police should also initiate random breath testing to instill the deterrence of detection, certainty of apprehension and punishment, and severity and celerity of punishment among drink-driving motorists and riders.     

The on-road experiences and awareness of sleepiness in a sample of Australian highway drivers: A roadside driver sleepiness study

Objective: Driver sleepiness contributes substantially to road crash incidents. Simulator and on-road studies clearly reveal an impairing effect from sleepiness on driving ability. However, the degree to which drivers appreciate the dangerousness of driving while sleepy is somewhat unclear. This study sought to determine drivers' on-road experiences of sleepiness, their prior sleep habits, and personal awareness of the signs of sleepiness.

Methods: Participants were a random selection of 92 drivers traveling on a major highway in the state of Queensland, Australia, who were stopped by police as part of routine drink driving operations. Participants completed a brief questionnaire that included demographic information, sleepy driving experiences (signs of sleepiness and on-road experiences of sleepiness), and prior sleep habits. A modified version of the Karolinska Sleepiness Scale (KSS) was used to assess subjective sleepiness in the 15 min prior to being stopped by police.

Results: Participants' ratings of subjective sleepiness were quite low, with 90% reporting being alert to extremely alert on the KSS. Participants were reasonably aware of the signs of sleepiness, with many signs of sleepiness associated with on-road experiences of sleepiness. Additionally, the number of hours spent driving was positively correlated with the drivers' level of sleep debt.

Conclusions: The results suggest that participants had moderate experiences of driving while sleepy and many were aware of the signs of sleepiness. The relationship between driving long distances and increased sleep debt is a concern for road safety. Increased education regarding the dangers of sleepy driving seems warranted.