Accidents in the construction industry in the Netherlands: An analysis of accident reports using Storybuilder

As part of an ongoing effort by the Ministry of Social Affairs and Employment of the Netherlands, a research project is being undertaken to construct a causal model for occupational risk. This model should provide quantitative insight into the causes and consequences of occupational accidents. One of the components of the model is a tool to systematically classify and analyse reports of past accidents. This tool ‘Storybuilder’ was described in earlier papers. In this paper, Storybuilder is used to analyse the causes of accidents reported in the database of the Dutch Labour Inspectorate involving people working in the construction industry. Conclusions are drawn on measures to reduce the accident probability. Some of these conclusions are contrary to common beliefs in the industry.     

Fatalities and injuries in the Kuwaiti construction industry

This paper presents an analysis of construction accidents in Kuwait along with accident causation and injuries that can be considered serious or fatal, so that corrective measures can be taken to decrease casualties, resulting in a safer construction industry. The paper evaluates the existing injury and cost reporting-investigation system of construction accidents in government agencies and private firms.

This research confirms that construction is the most hazardous industry in Kuwait, with accidents accounting for 48%, 38% and 34% of all disabling injuries and 62%, 38% and 42% of all fatalities in 1994, 1995 and 1996, respectively. These rates are considered high and can be compared to construction accident statistics in the U.S.A. which accounted for 14% of all work-related deaths and 9% of disabling injuries in 1993. Based on the study, falling from a height appears to be the major cause of construction injuries and fatalities in Kuwait. Poor accident records and reporting systems hide the extent of the construction safety problem in Kuwait. In addition, many people at management level are unaware of accident-related costs and the effectiveness of a safety program in reducing project costs.     

Strategies for improving safety performance in construction firms

Over the years many prevention management practices have been implemented to prevent and mitigate accidents at the construction site. However, there is little evidence of the effectiveness of individual or combined practices used by companies to manage occupational health and safety issues. The authors selected a sample of 1180 construction firms and 221 individual practices applied in these companies to analyze their effectiveness reducing injury rates over a period of four years in Chile. Different methods were used to study this massive database including: visual analyses of graphical information, statistical analyses and classification techniques. Results showed that practices related to safety incentives and rewards are the most effective from the accident rate viewpoint, even though they are seldom used by companies; on the other hand, practices related to accidents and incidents investigation had a slight negative impact on the accident rate because they are frequently used as a reactive measure. In general, the higher the percentage of prevention practices implemented in a strategy, the lower the accident rate. However, the analysis of the combined effect of prevention practices indicated that the choice of the right combination of practices was more important than just the number of practices implemented.     

Safety climate and safety performance among construction workers in Hong Kong. The role of psychological strains as mediators

This paper examines relations among safety climate (safety attitudes and communication), psychological strains (psychological distress and job satisfaction), and safety performance (self-reported accident rates and occupational injuries). A questionnaire was administered to construction workers from 27 construction sites in Hong Kong (N = 374, M = 366, F = 8, mean age =36.68 years). Data were collected by in-depth interviews and a survey from February to May 2000. A path analysis using the EQS-5 was employed to test the hypothesized model relating safety climate, safety performance, and psychological strains. The results provide partial support for the model, in that safety attitudes predict occupational injuries, and psychological distress predicts accident rates. Furthermore, psychological distress was found to be a mediator of the relationship between safety attitudes and accident rates. The implications of these results for psychological interventions in the construction industry are discussed.     

Occupational injury in the French sea fishing industry: a comparative study between the 1980s and today

This study aims at comparing two data bases related to occupational injuries in the French sea fishing industry: a data base created between 1977 and 1980, a data base created between 1996 and 2001. These bases were made from report forms filled out by fishermen after an accident. The study focuses on the accidents occurring when the vessel is in the process of fishing. In the 1980s, as well as today, the processing of fishing gear seems to be a very dangerous task, correlated with the risk of being "struck by, swept along, pinned" by the elements of the rigging and the risk of serious injuries. The processing and handling of the catch also cause a large amount of accidents; during these tasks, fishermen have to cope with two main risks: being "cut or pricked" and making an "excessive effort, awkward movement". Rate and features of occupational accidents do not show notable evolution. These findings lead us to question the different prevention measures implemented in France during the last few decades and to propose new prevention direction.     

Fuzzy approach for reducing subjectivity in estimating occupational accident severity

Quantifying or, more generally, estimating the severity of the possible consequences of occupational accidents is a decisive step in any occupational risk assessment process. Because of the lack of historic information (accident data collection and recording are incipient and insufficient, particularly in construction) and the lack of practical tools in the construction industry, the estimation/quantification of occupational accident severity is a notably arbitrary process rather than a systematic and rigorous assessment.     

Safety analysis in design—Evaluation of a case study

Safety analysis was applied in the design of a section at a paper mill. The case study involved analysis of layout, transport system, machines, and a number of different activities. The purpose of the analysis was to find measures to decrease occupational accidents. Three years after the installation was finished the occurrence of accidents was investigated. There was a 56% decrease in the number of accidents; the number of working days lost due to accidents was diminished by 75% as compared to 4 years preceding. The results of the safety analysis were also evaluated with respect to the accidents which had occurred. The methods for safety analysis seem to have been efficient in identifying hazards. The general conclusion of the study is that safety analysis can be an effective tool to decrease occupational accident risks.     

Rough set approach for accident chains exploration

This paper presents a novel non-parametric methodology--rough set theory--for accident occurrence exploration. The rough set theory allows researchers to analyze accidents in multiple dimensions and to model accident occurrence as factor chains. Factor chains are composed of driver characteristics, trip characteristics, driver behavior and environment factors that imply typical accident occurrence. A real-world database (2003 Taiwan single auto-vehicle accidents) is used as an example to demonstrate the proposed approach. The results show that although most accident patterns are unique, some accident patterns are significant and worth noting. Student drivers who are young and less experienced exhibit a relatively high possibility of being involved in off-road accidents on roads with a speed limit between 51 and 79 km/h under normal driving circumstances. Notably, for bump-into-facility accidents, wet surface is a distinctive environmental factor.     

The special severity of occupational accidents in the afternoon: "the lunch effect"

The severity of occupational accidents suffered by construction workers at different hours of the day is analyzed in this study. It may be seen that the interval of time between 13:00 and 17:00 has incomprehensibly high rates of severe and fatal accidents in comparison with any other. We associate this higher accident rate with what we have termed the “lunch effect”. We studied 10,239,303 labor accidents in Spain over the period 1990–2002. The relationships between potential risk factors for occupational accidents around lunch in Spain, especially alcohol consumption are studied, using two methods: analysis of national archival data of 2,155,954 occupational accidents suffered by workers in the construction sector over the period 1990–2002 and a survey study. This study also seeks to contribute the opinions of the workers themselves regarding the causes that might explain this situation.     

Bayes classifiers for imbalanced traffic accidents datasets

Traffic accidents data sets are usually imbalanced, where the number of instances classified under the killed or severe injuries class (minority) is much lower than those classified under the slight injuries class (majority). This, however, supposes a challenging problem for classification algorithms and may cause obtaining a model that well cover the slight injuries instances whereas the killed or severe injuries instances are misclassified frequently. Based on traffic accidents data collected on urban and suburban roads in Jordan for three years (2009–2011); three different data balancing techniques were used: under-sampling which removes some instances of the majority class, oversampling which creates new instances of the minority class and a mix technique that combines both. In addition, different Bayes classifiers were compared for the different imbalanced and balanced data sets: Averaged One-Dependence Estimators, Weightily Average One-Dependence Estimators, and Bayesian networks in order to identify factors that affect the severity of an accident. The results indicated that using the balanced data sets, especially those created using oversampling techniques, with Bayesian networks improved classifying a traffic accident according to its severity and reduced the misclassification of killed and severe injuries instances. On the other hand, the following variables were found to contribute to the occurrence of a killed causality or a severe injury in a traffic accident: number of vehicles involved, accident pattern, number of directions, accident type, lighting, surface condition, and speed limit. This work, to the knowledge of the authors, is the first that aims at analyzing historical data records for traffic accidents occurring in Jordan and the first to apply balancing techniques to analyze injury severity of traffic accidents.     

Individual and occupational factors related to fatal occupational injuries: a case-control study

This study has been designed in order to identify factors increasing the risk of a fatal outcome when occupational accidents occur. The aim is to provide further evidence for the design and implementation of preventive measures in occupational settings. The Spanish Ministry of Labour registry of occupational injuries causing absence from work includes information on individual and occupational characteristics of injured workers and events. Registered fatal occupational injuries in 2001 (n = 539) were compared to a sample of non-fatal injuries in the same year (n = 3493). Risks for a fatal result of occupational injuries, adjusted by individual and occupational factors significantly associated, were obtained through logistic regression models. Compared to non-fatal injuries, fatal occupational injuries were mostly produced by trapping or by natural causes, mostly related to elevation and transport devices and power generators, and injured parts of body more frequently affected were head, multiple parts or internal organs. Adjusted analyses showed increased risk of fatality after an occupational injury for males (adjusted odds ratio aOR = 10.92; 95%CI 4.80–24.84) and temporary workers (aOR = 5.18; 95%CI 2.63–10.18), and the risk increased with age and with advancing hour of the work shift (p for trends <0.01). Injuries taking place out of the usual occupational setting (aOR = 2.85, 95%CI 2.27–3.59), or carrying out atypical tasks (aOR = 2.08; 95%CI 1.27–3.39) showed increased risks of a fatal result too, as occupational accidents in agricultural or construction companies. These data can help to select and define priorities for programmes aimed to prevent fatal consequences of occupational injuries.     

The willingness to pay of parties to traffic accidents for loss of productivity and consolation compensation

In this study, willingness to pay (WTP) for loss of productivity and consolation compensation by parties to traffic accidents is investigated using the Tobit model. In addition, WTP is compared to compensation determined by Taiwanese courts. The modelling results showed that variables such as education, average individual monthly income, traffic accident history, past experience of severe traffic accident injuries, the number of working days lost due to a traffic accident, past experience of accepting compensation for traffic accident-caused productivity loss and past experience of accepting consolation compensation caused by traffic accidents have a positive impact on WTP. In addition, average WTP for these two accident costs were obtained. We found that parties to traffic accidents were willing to pay more than 90% of the compensation determined by the court in the scenario of minor and moderate injuries. Parties were willing to pay approximately 80% of the compensation determined by the court for severe injuries, disability and fatality. Therefore, related agencies can use our study findings as the basis for determining the compensation that parties should pay for productivity losses caused by traffic accidents of different types.     

Analysis of traffic injury severity: an application of non-parametric classification tree techniques

Statistical regression models, such as logit or ordered probit/logit models, have been widely employed to analyze injury severity of traffic accidents. However, most regression models have their own model assumptions and pre-defined underlying relationships between dependent and independent variables. If these assumptions are violated, the model could lead to erroneous estimations of injury likelihood. The classification and regression tree (CART), one of the most widely applied data mining techniques, has been commonly employed in business administration, industry, and engineering. CART does not require any pre-defined underlying relationship between target (dependent) variable and predictors (independent variables) and has been shown to be a powerful tool, particularly for dealing with prediction and classification problems. This study uses the 2001 accident data for Taipei, Taiwan. A CART model was developed to establish the relationship between injury severity and driver/vehicle characteristics, highway/environmental variables and accident variables. The results indicate that the most important variable associated with crash severity is the vehicle type. Pedestrians, motorcycle and bicycle riders are identified to have higher risks of being injured than other types of vehicle drivers in traffic accidents.     

Permanent impairments, disabilities and disability pensions related to accidents in Norway

The purpose of this study was to estimate the burden of accidents in terms of new disability pensioners related to accidental injuries in Norway and to use this information to supplement the picture of the epidemiology of accidents in Norway. The basis of the study was 7,241 new disability pensioners due to accidents in the Disability Register of the National Insurance Administration in Norway for 1992-1997. Included in the analyses are some data from health surveys in USA and Norway. The rate of disability pensioners (16-66 years old) due to accidents increased 4% annually during 1992-1997, and in the age group 16-44 years 8% annually. The increase is found in all types of accidents, except for home and the group other accidents, where the rate is constant. 45% had been injured in traffic accidents, 33% in occupational accidents, 16% in leisure accidents, 4% in home accidents and 2% in other accidents. The rates of disability pensionings due to occupational accidents are three to four times higher among 'blue collar' workers than among 'white collar' workers. While disability pensioning rate in the age group 16-66 years due to accidents has increased 4% annually, the accident mortality for the age group 15-64 years has decreased 3% annually. The relationship between disability pensioning and mortality in the age group 15-64 years is found to be approximately 2:1 for all accidents. For occupational accidents the relationship is 5:1, for traffic accidents 2.5:1, for leisure and other accidents 1:1 and for home accidents 1:2.7. The complete epidemiologic picture due to accidents in Norway per 100,000 of population seems to be: medically treated, 10,000; hospitalised, 1,200; permanently impaired, 800 (of whom probably 50% are treated as out-patients); disabled (restricted activity), 400; fatalities, 40; and disability pensioned in the age group 16-66 years, 50. Medically treated and hospitalised patients due to accidents seem to show a slightly decreasing rate, fatalities a higher decreasing rate. This supplement to the epidemiological picture of rates and trends of impairments, disability and disability pensionings (the more serious consequences of accidents), points to the need to focus on the current trends for accident prevention.     

Accident under-reporting among employees: Testing the moderating influence of psychological safety climate and supervisor enforcement of safety practices

We examined accident under-reporting with data from 425 employees employed in 5 industries with above average risk for employee injuries. We expected that rates for unreported accidents would be higher than rates for reported accidents; and that organizational safety climate and perceptions of supervisor enforcement of safety policies would moderate the relationship between unreported accidents and reported accidents. Results showed that the number of unreported accidents was significantly higher than the number of reported accidents. There was an average of 2.48 unreported accidents for every accident reported to the organization. Further, under-reporting was higher in working environments with poorer organizational safety climate or where supervisor safety enforcement was inconsistent. We discuss the implications of these findings for improving accident under-reporting and occupational safety in the workplace.     

A novel framework for improvement of road accidents considering decision-making styles of drivers in a large metropolitan area

Road accidents can be caused by different factors such as human factors. Quality of the decision-making process of drivers could have a considerable impact on preventing disasters. The main objective of this study is the analysis of factors affecting road accidents by considering the severity of accidents and decision-making styles of drivers. To this end, a novel framework is proposed based on data envelopment analysis (DEA) and statistical methods (SMs) to assess the factors affecting road accidents. In this study, for the first time, dominant decision-making styles of drivers with respect to severity of injuries are identified. To show the applicability of the proposed framework, this research employs actual data of more than 500 samples in Tehran, Iran. The empirical results indicate that the flexible decision style is the dominant style for both minor and severe levels of accident injuries.     

Pressure to produce = pressure to reduce accident reporting?

Each year, more than 4 million U.S. workers are injured on the job – several thousand die (Bureau of Labor Statistics, 2008). Despite these staggering numbers, research suggests that they are gross underestimates of the true volume of workplace related illnesses and injuries due to accident under-reporting. Although accident under-reporting has been well-documented, less is known regarding why this occurs. The current study suggests that under-reporting may in part be due to high levels of perceived production pressure. Specifically, this study tested the hypotheses that production pressure would be related to more experienced accidents overall and more negative attitudes toward reporting accidents. Further, we expected that production pressure would exacerbate the under-reporting of accidents. Survey data were collected from a sample of 212 copper mining workers located in the southwestern United States. The survey measured employee perceptions regarding production pressure, attitudes toward reporting accidents, perceived consequences of reporting accidents, and actual reporting behaviors (e.g., types and numbers of accidents experienced vs. reported). As predicted, the average number of experienced accidents per employee was significantly higher (M = 2.84) than the number of reported accidents (M = .49). In addition, production pressure was related to more negative reporting attitudes. Individuals who had positive reporting attitudes were injured less frequently; however, when an incident occurred, they were more likely to report it. Finally, higher levels of production pressure were related to greater accident under-reporting. Additionally, employees who perceived high levels of production pressure not only experienced more accidents overall, they also reported fewer of them to the organization. Implications for occupational safety initiatives – particularly in the current economic climate – are discussed, as are methodological challenges of conducting research in this area.     

A multinomial logit analysis of risk factors influencing road traffic injury severities in the Erzurum and Kars Provinces of Turkey

A retrospective cross-sectional study is conducted analysing 11,771 traffic accidents reported by the police between January 2008 and December 2013 which are classified into three injury severity categories: fatal, injury, and no injury. Based on this classification, a multinomial logit analysis is performed to determine the risk factors affecting the severity of traffic injuries. The estimation results reveal that the following factors increase the probability of fatal injuries: drivers over the age of 65; primary-educated drivers; single-vehicle accidents; accidents occurring on state routes, highways or provincial roads; and the presence of pedestrian crosswalks. The results also indicate that accidents involving cars or private vehicles or those occurring during the evening peak, under clear weather conditions, on local city streets or in the presence of traffic lights decrease the probability of fatal injuries. This study comprises the most comprehensive database ever created for a Turkish sample. This study is also the first attempt to use an unordered response model to determine risk factors influencing the severity of traffic injuries in Turkey.     

Modeling secondary accidents identified by traffic shock waves

The high potential for occurrence and the negative consequences of secondary accidents make them an issue of great concern affecting freeway safety. Using accident records from a three-year period together with California interstate freeway loop data, a dynamic method for more accurate classification based on the traffic shock wave detecting method was used to identify secondary accidents. Spatio-temporal gaps between the primary and secondary accident were proven be fit via a mixture of Weibull and normal distribution. A logistic regression model was developed to investigate major factors contributing to secondary accident occurrence. Traffic shock wave speed and volume at the occurrence of a primary accident were explicitly considered in the model, as a secondary accident is defined as an accident that occurs within the spatio-temporal impact scope of the primary accident. Results show that the shock waves originating in the wake of a primary accident have a more significant impact on the likelihood of a secondary accident occurrence than the effects of traffic volume. Primary accidents with long durations can significantly increase the possibility of secondary accidents. Unsafe speed and weather are other factors contributing to secondary crash occurrence. It is strongly suggested that when police or rescue personnel arrive at the scene of an accident, they should not suddenly block, decrease, or unblock the traffic flow, but instead endeavor to control traffic in a smooth and controlled manner. Also it is important to reduce accident processing time to reduce the risk of secondary accident.