Objective: A large portion of child restraint systems (car seats) are installed incorrectly, especially when first-time parents install infant car seats. Expert instruction greatly improves the accuracy of car seat installation but is labor intensive and difficult to obtain for many parents. This study was designed to evaluate the efficacy of 3 ways of communicating instructions for proper car seat installation: phone conversation; HelpLightning, a mobile application (app) that offers virtual interactive presence permitting both verbal and interactive (telestration) visual communication; and the manufacturer's user manual.
Methods: A sample of 39 young adults of child-bearing age who had no previous experience installing car seats were recruited and randomly assigned to install an infant car seat using guidance from one of those 3 communication sources.
Results: Both the phone and interactive app were more effective means to facilitate accurate car seat installation compared to the user manual. There was a trend for the app to offer superior communication compared to the phone, but that difference was not significant in most assessments. The phone and app groups also installed the car seat more efficiently and perceived the communication to be more effective and their installation to be more accurate than those in the user manual group.
Conclusions: Interactive communication may help parents install car seats more accurately than using the manufacturer's manual alone. This was an initial study with a modestly sized sample; if results are replicated in future research, there may be reason to consider centralized “call centers” that provide verbal and/or interactive visual instruction from remote locations to parents installing car seats, paralleling the model of centralized Poison Control centers in the United States. 相似文献
Objective: The objective of this study was to describe demographic and injury characteristics of hospitalized injured patients involved in e-bike and motorized scooter accidents at a national level in Israel divided by different road user groups: riders and pedestrians.
Methods: This was a retrospective study based on data from the National Trauma Registry, between January 1, 2013, and December 31, 2015. All hospitalized casualties due to the involvement of an e-bike or motorized scooter were included. The type of hospitalized road user was further categorized and described by different variables.
Results: During the study period, the Israel Trauma Registry identified 795 hospitalized patients due to an e-bike or motorized scooter accident, with a dramatic 6-fold increase from 2013 to 2015. Although the majority of the injured patients were riders, 8% were pedestrians. Among the total casualties, 33% were children aged 0–14 years and among pedestrians 42% were children and 33% were seniors (ages 60+). Five persons died in hospital, 3 riders and 2 pedestrians.
Conclusions: E-bike and motorized scooter riders represent the majority of patients hospitalized due to related traffic incident. This finding questions the social and economic advantages of electric-powered 2-wheeled vehicles. 相似文献
Objective: The objective of this study is to use a validated finite element model of the human body and a certified model of an anthropomorphic test dummy (ATD) to evaluate the effect of simulated precrash braking on driver kinematics, restraint loads, body loads, and computed injury criteria in 4 commonly injured body regions.
Methods: The Global Human Body Models Consortium (GHBMC) 50th percentile male occupant (M50-O) and the Humanetics Hybrid III 50th percentile models were gravity settled in the driver position of a generic interior equipped with an advanced 3-point belt and driver airbag. Fifteen simulations per model (30 total) were conducted, including 4 scenarios at 3 severity levels: median, severe, and the U.S. New Car Assessment Program (U.S.-NCAP) and 3 extra per model with high-intensity braking. The 4 scenarios were no precollision system (no PCS), forward collision warning (FCW), FCW with prebraking assist (FCW+PBA), and FCW and PBA with autonomous precrash braking (FCW + PBA + PB). The baseline ΔV was 17, 34, and 56.4 kph for median, severe, and U.S.-NCAP scenarios, respectively, and were based on crash reconstructions from NASS/CDS. Pulses were then developed based on the assumed precrash systems equipped. Restraint properties and the generic pulse used were based on literature.
Results: In median crash severity cases, little to no risk (<10% risk for Abbreviated injury Scale [AIS] 3+) was found for all injury measures for both models. In the severe set of cases, little to no risk for AIS 3+ injury was also found for all injury measures. In NCAP cases, highest risk was typically found with No PCS and lowest with FCW + PBA + PB. In the higher intensity braking cases (1.0–1.4 g), head injury criterion (HIC), brain injury criterion (BrIC), and chest deflection injury measures increased with increased braking intensity. All other measures for these cases tended to decrease. The ATD also predicted and trended similar to the human body models predictions for both the median, severe, and NCAP cases. Forward excursion for both models decreased across median, severe, and NCAP cases and diverged from each other in cases above 1.0 g of braking intensity.
Conclusions: The addition of precrash systems simulated through reduced precrash speeds caused reductions in some injury criteria, whereas others (chest deflection, HIC, and BrIC) increased due to a modified occupant position. The human model and ATD models trended similarly in nearly all cases with greater risk indicated in the human model. These results suggest the need for integrated safety systems that have restraints that optimize the occupant's position during precrash braking and prior to impact. 相似文献
Introduction: Reducing the severity of crashes is a top priority for safety researchers due to its impact on saving human lives. Because of safety concerns posed by large trucks and the high rate of fatal large truck-involved crashes, an exploration into large truck-involved crashes could help determine factors that are influential in crash severity. The current study focuses on large truck-involved crashes to predict influencing factors on crash injury severity. Method: Two techniques have been utilized: Random Parameter Binary Logit (RPBL) and Support Vector Machine (SVM). Models have been developed to estimate: (1) multivehicle (MV) truck-involved crashes, in which large truck drivers are at fault, (2) MV track-involved crashes, in which large truck drivers are not at fault and (3) and single-vehicle (SV) large truck crashes. Results: Fatigue and deviation to the left were found as the most important contributing factors that lead to fatal crashes when the large truck-driver is at fault. Outcomes show that there are differences among significant factors between RPBL and SVM. For instance, unsafe lane-changing was significant in all three categories in RPBL, but only SV large truck crashes in SVM. Conclusions: The outcomes showed the importance of the complementary approaches to incorporate both parametric RPBL and non-parametric SVM to identify the main contributing factors affecting the severity of large truck-involved crashes. Also, the results highlighted the importance of categorization based on the at-fault party. Practical Applications: Unrealistic schedules and expectations of trucking companies can cause excessive stress for the large truck drivers, which could leads to further neglect of their fatigue. Enacting and enforcing comprehensive regulations regarding large truck drivers’ working schedules and direct and constant surveillance by authorities would significantly decrease large truck-involved crashes. 相似文献