ARTICLE | doi:10.20944/preprints201912.0116.v1
Online: 9 December 2019 (04:05:48 CET)
Many accidents, such as those involving collisions or trips, appear to involve failures of vision; but the association between accident risk and vision as conventionally assessed, is weak or absent. We addressed this conundrum by embracing the distinction inspired by neuroscientific research, between vision for perception and vision for action. A dual-process perspective predicts that accident vulnerability will be associated more strongly with vision for action than vision for perception. Older and younger adults, with relatively high and relatively low self-reported accident vulnerability (Accident Proneness Questionnaire), completed three behavioural assessments targeting: vision for perception (Freiburg Visual Acuity Test); vision for action (Vision for Action Test - VAT); and the ability to perform physical actions involving balance, walking and standing (Short Physical Performance Battery). Accident vulnerability was not associated with visual acuity or with performance of physical actions; but was associated with VAT performance. VAT assesses the ability to link visual input with a specific action –launching a saccadic eye movement as rapidly as possible, in response to shapes presented in peripheral vision. The predictive relationship between VAT performance and accident vulnerability was independent of age, visual acuity and physical performance scores. Applied implications of these findings are considered.
ARTICLE | doi:10.20944/preprints201807.0259.v1
Online: 16 July 2018 (07:54:19 CEST)
Resilience embodies the personal qualities that enable one to thrive in the face of adversity. A previous Italian study showed that injured workers had a lower level of resilience than non-injured workers. The aim of this paper is to examine the relationship between occupational injuries and psychological resilience. The subjects were 197 drivers from two Finnish waste transport companies. As a part of larger questionnaire, they fulfilled the Connor-Davidson Resilience Scale, which consisted of 25 items. Drivers reported their occupational injuries during the last three years. The drivers involved in occupational injuries had higher score (average 69.3) on Connor-Davidson Resilience Scale than drivers avoided injuries (67.7). According to Student’s t-test the difference between groups was highly significant (t = 40.44, df = 196, p<0.001). The result of this study was contradictory to earlier Italian study. One explanation may be that the Italian study was done with traumatic context with seriously injured patients. Waste transport drivers were rather young and fit males, who had suffered only minor injuries.
ARTICLE | doi:10.20944/preprints202105.0698.v1
Subject: Mathematics & Computer Science, Information Technology & Data Management Keywords: Accidents, Data Analysis, Machine Learning, Transport
Online: 28 May 2021 (11:59:24 CEST)
Daily thousands of people and goods move along Brazilian Federal highways. Traffic accidents are numerous on these highways and have a significant impact, whether on the economy or the health system. Identifying predictor variables, the probability of an event occurring and how to mitigate them are of paramount importance for the actions of the transit authorities that manage these roads. The main contribution of this study is the development of a predictive machine learning model which uses open data to shows graphically the critical points in the highways. This model is fully reproducible and can be applied to any region worldwide helping to minimize the number of accidents and to prevent deaths by automotive collisions. For this study, 43 variables were analyzed supporting the identification of the causes of accidents with fatal victims on the main highways in the south of Brazil. RoadLytics is proposed as a supervised machine learning model, using the Random Forest algorithm to analyze about 33 thousand occurrences between 2017 and 2020. An exploratory analysis of the data was carried out to support the modeling and to facilitate data visualization. In this sense, heat maps were developed to support the analysis and identification of potential risk areas. The results show that BR386 highway registers the highest number of fatal occurrences, regardless of the season. Additionally, concerning the weather conditions, the analysis shows that 52% of accidents occurred in favorable conditions, such as clear skies, victimizing 501 people. The driver’s lack of attention is the main reason for the accidents’ occurrences. Applying the developed model, an accuracy of 77% was achieved for the classification of fatal accidents.
ARTICLE | doi:10.20944/preprints202206.0003.v1
Subject: Engineering, Civil Engineering Keywords: accidents; geographic information system; highway; hotspots; identification
Online: 1 June 2022 (03:58:13 CEST)
This study identified high-risk locations (hotspots), using geographic information systems (GIS) and spatial analysis. Five years of accident data (2013-2017) for the Lokoja-Abuja-Kaduna highway in Nigeria were used. Accident concentration analysis was carried out using the mean center analysis and Kernel density estimation method. These locations were further verified using Moran’s I Statistics (Spatial Autocorrelation) to determine their clustering with statistical significance. Fishnet polygon and Network spatial weight matrix approaches of Getis-Ord Gi* statistic for hotspot analysis were used for the hotspot analysis. Hotspots exist for 2013, 2014, and 2017 with a significance level between 95% - 99%. However, no hotspots exist for 2014 and 2015 since the pattern is random. The spatial autocorrelation analysis of the overall accident locations with a z-score = 0.0575, p-value = 0.9542, and Moran's I statistic = -0.0089 showed that the distribution of accidents on the study route is random. Thus, preventive measures for hotspot locations should be based on a yearly hotspot analysis. The average daily traffic values of 31,270 and 16,303 were obtained for the Northbound and Southbound directions of the Abaji-Abuja section. The results show that hotspot locations with high confidence levels are at points where there are geometric features.
ARTICLE | doi:10.20944/preprints202201.0270.v1
Subject: Mathematics & Computer Science, Other Keywords: Road accidents; Brazil; fractional integration; long memory
Online: 19 January 2022 (11:45:26 CET)
This paper deals with the analysis of trends in road accidents on major highways in Brazil. Using updated time series techniques, our results indicate that a low degree of long memory was detected in the series with shocks having transitory effects over time. We further find that the number of accidents taking place in Brazil has been reducing over time, though in the presence of negative shocks, the recovery is not going to be immediate due to the long memory nature of the data. Despite the absence of relevant investment relating to infrastructure expansion, it is worth mentioning the consolidation of a nationwide tolled road system in Brazil involving concessions to private administrators, alongside more severe traffic laws that can impose limitations on driving licences.
REVIEW | doi:10.20944/preprints202209.0338.v1
Subject: Mathematics & Computer Science, Information Technology & Data Management Keywords: Road; Accidents; Black spots; spatial analysis; Factor analysis
Online: 22 September 2022 (09:41:07 CEST)
This paper deals with identifying the accident black spots and the influencing factors causing accidents using factored analysis in the medium-sized city (Tirunelveli) in India. From the literature review, the geospatial technique to identify the black spots and the factors causing accidents was used for analysis. The most influencing factors driving the accident were identified and ranked based on the repetitive occurrence of accidents in the black spot area. The spearman ranking system obtained the correlation among the factors causing accidents. The factor analysis technique was utilized to identify the key factors driving the repetitive accidents and group them. This study will help transportation planners to understand the factors causing accidents and take appropriate measures to reduce the casualties in the road construction planning stage and existing conditions.
ARTICLE | doi:10.20944/preprints202103.0252.v1
Subject: Medicine & Pharmacology, Allergology Keywords: prevention; road-traffic-accidents; education-health; schoolchildren; change-attitude
Online: 9 March 2021 (09:54:27 CET)
Introduction: Road traffic accidents are a real pandemic and incur expenses amounting to 1-2% of every country’s GDP. AESLEME (Association for the Study of Spinal Cord Injuries) – devoted to teaching road safety and health to prevent road accidents – has celebrated its 30th anniversary. AESLEME’s instructors are health workers and people with spinal cord injuries caused by road accidents: their presentations – teaching road safety and sharing information on irreversible injuries – are enhanced by personal stories that help schoolchildren to acquire knowledge on this matter. However, until now, we had not assessed how far this acquisition of knowledge had reached. Methods used: Two multiple-choice tests were given to each of the 8,106 students (12-14 years) who took part. Of the four possible answers, only one of them was correct. The first multiple-choice test was taken before the presentation and the second was taken one month later. Results: After assessing the answers, there was a change in the tendency of the number of correct answers before/after answers for the multiple-choice test, and the number of correct one´s rose one month after the presentation. This increase is statistically significant (p<0.01) and represents a national increase of 61% in the number of correct answers, although this varies from 8% to 278% depending on the region. Conclusions: The assessment, involving over 8,000 people, showed that there has been an improvement in road safety knowledge thanks to education provided by AESLEME’s instructors, and a statistically significant increase was obtained throughout Spain, with an average of 61% (confidence level 95: 53% and 64%).
ARTICLE | doi:10.20944/preprints202012.0482.v1
Subject: Earth Sciences, Atmospheric Science Keywords: nuclear accidents; decision support; protective measures, LPM, PTM, CBRN.
Online: 18 December 2020 (16:33:16 CET)
The systems ESTE are running in nuclear crisis centers at various levels of emergency preparedness and response in Slovakia, the Czech Republic, Austria, Bulgaria, and Iran (at NPP monitored by International Atomic Energy Agency, IAEA). ESTE is a decision support system, running 24/7, and serves the crisis staff to propose actions to protect inhabitants against radiation in case of a nuclear accident. ESTE is also applicable as decision support system in case of a malicious act with radioactive dispersal device in an urban or industrial environment. Dispersion models implemented in ESTE are Lagrangean particle model (LPM) and Puff trajectory model (PTM). Described are models approaches as implemented in ESTE. PTM is applied in ESTE for the dispersion calculation near the point of release, up to 100 km from the point of nuclear accident. LPM for general atmospheric transport is applied for short-range, meso-scale and large-scale dispersion, up to dispersion on the global scale. Additionally, a specific micro-scale implementation of LPM is applied for urban scale dispersion modelling too. Dispersion models of ESTE are joined with radiological consequences models to calculate a complete spectrum of radiological parameters - effective doses, committed doses and dose rates by various irradiation pathways and by various radionuclides. Finally, radiation protective measures, like sheltering, iodine prophylaxis, or evacuation, evaluated on the base of predicted radiological impacts are proposed. Dispersion and radiological models of the state-of-the-art ESTE systems are described. Results of specific analyses, like number of particles applied, initial spatial distribution of the source, height of the bottom reference layer, are presented and discussed.
ARTICLE | doi:10.20944/preprints202001.0146.v1
Subject: Engineering, Automotive Engineering Keywords: child seats; car accidents; car crash analyses; children safety
Online: 15 January 2020 (07:30:38 CET)
The study presents a comparison of the common Child Restraint Systems (CRS) which reduces the value of dynamic loads affecting the child's body during car accidents. The analyzed systems were: child seats, Combi Booster Seats, and straps adjusting vehicle seat belts to children's sizes. The effectiveness of the analyzed devices was assessed on the basis of experimental tests carried out in the accredited laboratory approving the Child Restraint Systems. The tests were carried out accordingly to the new Regulation No. 129 UN / ECE. Whether the tested devices meet the guidelines of the new Regulations No. 129 despite approval in accordance with Regulation No. 44. Based on the research result, better safety parameters of some new solutions dedicated to children’s safety could be observed. The final results show that there is still space for improving the safety of young vehicle passengers.
ARTICLE | doi:10.20944/preprints201912.0098.v1
Subject: Engineering, Automotive Engineering Keywords: child seats; car accidents; car crash analyses; children safety
Online: 8 December 2019 (15:45:04 CET)
The study presents a comparison of the common Child Restraint Systems (CRS) which reduces the value of dynamic loads affecting the child's body during car accidents. The analyzed systems were: child seats, Combi Booster Seats, and straps adjusting vehicle seat belts to children's sizes. The effectiveness of the analyzed devices was assessed on the basis of experimental tests carried out in the accredited laboratory approving the Child Restraint Systems. The tests were carried out accordingly to the new Regulation No. 129 UN / ECE. Whether the tested devices meet the guidelines of the new Regulations No. 129 despite approval in accordance with Regulation No. 44. Based on the research result, better safety parameters of some new solutions dedicated to children's safety could be observed. The final results show that there is still space for improving the safety of young vehicle passengers.
ARTICLE | doi:10.20944/preprints202103.0713.v1
Subject: Social Sciences, Accounting Keywords: Road crashes; fatalities; casualties; persons killed in road accidents; South Africa
Online: 29 March 2021 (22:28:04 CEST)
Globally, there are 1.35 million road fatalities every year, which are estimated to cost governments approximately US$ 518 billion, making road fatalities the 8th leading cause of death across all age groups and the leading cause of death of children and young adults. In South Africa, despite tremendous governmental efforts to curb the soaring trajectory of road accidents, the annual number of road fatalities has increased by 26% in recent years. By fitting a structural equation model (SEM) and a GARCH Model (Generalized Auto-Regressive Conditional Heteroskedastic-ity) to analyze and predict future trend of road accidents (number of road accidents, number of casualties, number of fatal crashes and number of persons killed) in South Africa, we propose and test a complex metamodel that integrates multiple causality relationships. We show an increasing trend of road accidents over time, a trend that is predictable by number of vehicles in the country, the population of the country and the total distance travelled by vehicles. We further show that death rate linked to road accidents is on average 23.14 deaths per 100,000 persons and is pre-dictable following the equation: y = -0.0114x2+1.2378x-2.2627 (R2=0.76) with y = death rate and x = year. Finally, in the next decade, the number of road accidents is predicted to be roughly constant at 617,253 accidents but can reach 1 896 667 accidents in the worst-case scenario. The number of casualties was also predicted to be roughly constant at 93 531 over time, although this number may reach 661 531 in the worst-case scenario. However, although the number of fatal crashes may decrease in the next decade, it is forecasted to reach 11 241 within the next 10 years with the worse scenario estimated at 19 034 within the same period. At the same time, the number of persons killed in fatal crashes is also predicted to be roughly constant at 14 739 but may also reach 172 784 in the worse scenario. Overall, the present study reveals perhaps the positive effects of government initiatives to curb road accidents and their consequences; we call for more stronger actions for a drastic reduction in road accident events in South Africa.
ARTICLE | doi:10.20944/preprints201804.0371.v1
Subject: Engineering, Civil Engineering Keywords: economic regions; regional classification; classification methodology; construction industry; cluster analysis; accidents in construction
Online: 28 April 2018 (12:14:29 CEST)
The article presents the methodology for classifying economic regions with regards to selected factors that characterize a region, such as: the economic structure of the region, and thus the share of individual sectors in the economy; employment; the dynamics of the development of individual sectors expressed as an increase or decrease in production value; the population density in the region and also the level of occupational safety. Cluster analysis, which is a method of multidimensional statistical analysis available in Statistica software, was used to solve the task. The proposed methodology was used to group Polish voivodships with regards to the speed of economic development and occupational safety in the construction industry. Data published by the Central Statistical Office was used for this purpose, such as the value of construction and assembly production, the number of people employed in the construction industry, the population of an individual region and the number of people injured in occupational accidents.
ARTICLE | doi:10.20944/preprints202011.0211.v1
Subject: Engineering, Automotive Engineering Keywords: Climate Change; Occupational Accidents; Weather Circumstances; Heat Stress; Precipitation; Accident Mortality; time-series analyses
Online: 5 November 2020 (12:26:54 CET)
In the steel industries, workers are exposed to heat and ambient thermal stresses on a daily basis, leading to discomfort and limited performance. In this study, the main purpose is to investigate the effect of climate heat stress on the rate of accidents in the workplace for workers for 5 consecutive years. The data of this study were received without any sampling through the HSE Center for Steel Industry and meteorological data from 2015 to 2019 from Isfahan Meteorological station. The daily number of casualties among workers in the steel industry during 2015-2019 by adjusting seasonal patterns, months, effects of the day of the week and other meteorological factors on the average daily temperature using the studied model has a decreasing effect. Eviews software (version 8) was used to model and investigate the relationship between events and meteorological variables. The mean temperature was at least 40.2-2 and at most 70.34 ° C, respectively. In the time-series study for the main model, the number of accidents shows a direct relationship with the average temperature and wind speed. Climatic indices of humidity and rainfall have the least impact on accidents compared to temperature and wind speed. A strong correlation was shown between the increase in average ambient temperature and the rate of accidents over the past 5 years. Given the fundamental differences in studies of environmental exposure and wind speed over heat stress, further analysis in workers should be considered.
ARTICLE | doi:10.20944/preprints201912.0411.v1
Subject: Engineering, Construction Keywords: safety; electrical contractors; construction accidents; nature and outcome of injuries; Chi-square test of independence
Online: 31 December 2019 (11:19:50 CET)
Electrical contractors have experienced a rise in occupational fatalities in recent years. In 2017, electrical contractors also had the second highest number of non-fatal injuries among specialty trade contractors. Identifying statistically significant dependencies between these catastrophic outcomes and a handful of well-defined contributing factors in construction accidents offers a first step in mitigating the risks of construction accidents in this trade. Therefore, this study used methodologies of descriptive and quantitative statistics to identify the contributing factors most affecting occupational accident outcomes among electrical contracting enterprises, given an accident occurred. Accident reports were collected from the Occupational Safety and Health Administration’s fatality and catastrophe database. To ensure the reliability of the data, the team manually codified more than 600 incidents through a comprehensive content analysis using injury-classification standards. Inclusive of both fatal and non-fatal injuries, the results showed that most accidents happened in nonresidential buildings, new construction, and small projects (i.e., $50,000 or less). The main source of injuries manifested in parts and materials (46%), followed by tools, instruments, and equipment (19%), and structure and surfaces (16%). The most frequent types of injuries were fractures (31%), electrocutions (27%), and electrical burns (14%); the main injured body parts were upper extremities (25%), head (23%), and body system (18%). Among non-fatal cases, falls (37%), exposure to electricity (36%), and contact with objects (19%) caused most injuries; among fatal cases, exposure to electricity was the leading cause of death (50%), followed by falls (28%) and contact with objects (19%). The analysis also investigated the impact of several accident factors on the degree of injuries and found significant effects from such factors such as project type, source of injury, cause of injuries, injured part of body, nature of injury, and event type. In other words, the statistical probability of a fatal accident—given an accident occurrence—changes significantly based on the degree of these factors. Beyond these outcomes, the described content-analysis methodology contributes to the accident-analysis body of knowledge by providing a framework for codifying data from accident reports to facilitate future analysis and modeling attempts (e.g., developing logistic regression models) to subsequently mitigate more injuries in other fields.
ARTICLE | doi:10.20944/preprints202010.0256.v1
Subject: Medicine & Pharmacology, Allergology Keywords: workplace health promotion; sleep quality; sleep hygiene; sleepiness; safety; insomnia; sleep deprivation; accidents; near miss; police
Online: 12 October 2020 (16:27:57 CEST)
A workplace sleep health promotion program was implemented in an Italian police unit from 2016 to 2017. Of the 242 police officers in the unit, 218 (90%) agreed to take part in the program. A crossover trial was made in which the police officers were divided into two groups that performed sleep health promotion activities in the first and second year, respectively. The first group of officers showed significant sleep improvements at the end of the first year, while the second group had similar or worse parameters than at baseline. At follow-up, a significant improvement in the quantity and quality of sleep was reported in both groups. Sleep improvements at follow-up were associated with a marked reduction in the frequency of accidents at work and near-misses. All sleep parameters showed a significant association with injuries and near-misses in univariate logistic regression analyses. Before the intervention, sleepiness was the best predictor of injuries (aOR 1.220; CI95% 1.044-1.426) and near-misses (aOR 1.382; CI95% 1.182-1.615). At follow-up, when sleep conditions had improved, insomnia symptoms were the most significant predictors of work accidents (aOR 13.358; CI95% 2.353-75.818). Sleep health promotion can be useful in police officers.
BRIEF REPORT | doi:10.20944/preprints202007.0633.v1
Subject: Medicine & Pharmacology, Pediatrics Keywords: Children; adolescents; post-road traffic accidents; EQ-5D-5L; disability burden; health-related quality of life
Online: 26 July 2020 (03:11:18 CEST)
The objective of the study was to report the health-related quality of life (HRQOL) following road traffic accidents (RTAs) among children. A community-based survey using EuroQol five-dimension questionnaire (EQ-5D-5L) in Hindi was used to collected data from community. The survey included 2620 households from urban and rural areas of Ujjain, India. From these households 229 children aged 5–18 years with a history of RTA in the last 1 year were identified, with 27%, 63%, and 10% children reporting mild, moderate, and severe injury based on length of hospitalization. Motorcycles, bicycles, and pedestrians constituted most RTAs. Helmet use was low (12%). EQ-5D-5L revealed that the most severe and extreme problem was pain and discomfort, whereas the least severe problem was usual activity and self-care. The most common (65%) injuries were either abrasion or fracture and dislocation. EQ-5D-5L severity index was maximum (mean 72) for lower extremity injuries. The results of the present study highlight the ability and requirement for quality of life measurement using EQ-5D-5L among children post-RTA.
ARTICLE | doi:10.20944/preprints201803.0042.v1
Subject: Behavioral Sciences, Applied Psychology Keywords: cognitive bias; organizational bias; decision options; risk; catastrophic, organizational accidents; human error; hierarchy; culture; policy; procedures
Online: 6 March 2018 (05:21:28 CET)
This paper examines cognitive biases which affect the ability of decision makers to make rational decisions in an organizational context. The motivation for this analysis begins with the observation of catastrophic accidents caused by human error but in an organizational context. This paper expands on the concept of cognitive bias to define organizational biases which are the factors that affect decisions in an organizational context. The paper distinguishes between organizational biases, which are the focus of this paper, and individual biases, which are biases experienced by individuals but may have organizational consequences. The purpose of this paper is to identify methods to mitigate the risks of organizational accidents, accidents which involve many people operating at different levels of an organization. The methodology is to identify those decisions that would address the specific organizational biases. The focus of this paper is the decisions for mitigating the risks associated with decisions in an organizational context. Results are shown for seven organizational biases, six specific case studies, and four decision options. This paper concludes that organizational biases are intrinsically different from individual biases and that these differences lead to different decision options from those that mitigate individual biases; however, they may exist concurrently.