Preventing construction worker injury incidents through the management of personal stress and organizational stressors.
Construction workers (CWs) are positioned at the lowest level of an organization and thus have limited control over their work. For this reason, they are often deprived of their due rewards and training or sometimes are even compelled to focus on production at the expense of their own safety. These organizational stressors not only cause the CWs stress but also impair their safety behaviors. The impairment of safety behaviors is the major cause of CW injury incidents. Hence, to prevent injury incidents and enhance safety behaviors of CWs, the current study aimed to identify the impact of various organizational stressors and stress on CW safety behaviors and injury incidents. To achieve this aim, we surveyed 395 CWs. Using factor analysis, we identified five organizational stressors (unfair reward and treatment, inappropriate safety equipment, provision of training, lack of goal setting, and poor physical environment), two types of stress (emotional and physical), and safety behaviors. The results of correlation and regression analyses revealed the following: (1) injury incidents were minimized by safety behaviors but escalated by a lack of goal setting, (2) safety behaviors were maximized by moderate levels of emotional stress (i.e., an inverted U-shape relationship between these two variables) and increased in line with physical stress and inappropriate safety equipment, (3) emotional stress was positively predicted by the provision of training and inappropriate safety equipment, and (4) physical stress was predicted only by inappropriate safety equipment. Based on these results, we suggest various recommendations to construction stakeholders on how to prevent CW injury incidents.
Preventing injuries in children: cluster randomised controlled trial in primary care
Objective: To assess the effectiveness of safety advice at child health surveillance consultations, provision of low cost safety equipment to families receiving means tested state benefits, home safety checks, and first aid training on frequencyand severity of unintentional injuries in children at home. Design: Cluster randomised controlled trial. Setting:36 general practices in Nottingham. Subjects:All children aged 3-12 months registered with participating practices. Interventions: A package of safety advice at child health surveillance consultations at 6-9, 12-15, and 18-24 months;provision of low cost safety equipment to families on means tested state benefits; and home safety checks and first aid training by health visitors. Outcome measures: Primary outcomes measures were frequency and severity of medically attended injuries. Secondary outcome measures were self reported safety practices, possession and use of safety equipment, knowledge and confidence in dealing with first aid, and perceptions of risk of injury and risk of hazards assessed by postalquestionnaire at baseline and follow up at 25 months. Results: At baseline, both groups had similar risk factors for injury, sociodemographic characteristics, safety practices, possession and use of safety equipment, knowledge and confidence in dealing with first aid, and perceptions of risk. No significant difference was found in frequency of at least one medically attended injury (odds ratio 0.97, 95% confidence interval 0.72 to1.30), at least one attendance at an accident and emergency department for injury (, 0.76 to 1.37), at least one primary care attendance for injury (0.75, 0.48 to 1.17), or at least one hospital admission for injury (0.69, 0.42 to 1.12). No significant difference in the secondary outcome measures was found between the intervention and control groups. Conclusions: The intervention package was not effective in reducing the frequency of minor unintentional injuries in children at home, and larger trials are required to assess the effect on more severe injuries.
Providing child safety equipment to prevent injuries: randomised controlled trial
Objective To assess the effectiveness of safety advice and safety equipment in reducing unintentional injuries for families with children aged under 5 years and living in deprived areas. Design Randomised controlled trial. Setting 47 general practices in Nottingham. Participants 3428 families with children under 5. Intervention A standardised safety consultation and provision of free and fitted stair gates, fire guards, smoke alarms, cupboard locks, and window locks. Main outcome measures Primary outcome measures were whether a child in the family had at least one injury that required medical attendance and rates of attendance in primary and secondary care and of hospital admission for injury over a two year period. Secondary outcome measures included possession of safety equipment and safety practices. Results No significant difference was found in the proportion of families in which a child had a medically attended injury (odds ratio 1.14, 95% confidence interval 0.98 to 1.50) or in the rates of attendance in secondary care (incidence rate ratio 1.02, 0.90 to 1.13) or admission to hospital (1.02, 0.70 to 1.48). However, children in the intervention arm had a significantly higher attendance rate for injuries in primary care (1.37, 1.11 to 1.70, P = 0.003). At both one and two years' follow up, families in the intervention arm were significantly more likely to have a range of safety practices, but absolute differences in the percentages were relatively small. Conclusions The intervention resulted in significant improvements in safety practices for up to two years but did not reduce injuries that necessitated medical attendance. Although equipment was provided and fitted free of charge, the observed changes in safety practices may not have been large enough to affect injury rates.
Optimization of safety equipment outages improves safety
Testing and maintenance activities of safety equipment in nuclear power plants are an important potential for risk and cost reduction. An optimization method is presented based on the simulated annealing algorithm. The method determines the optimal schedule of safety equipment outages due to testing and maintenance based on minimization of selected risk measure. The mean value of the selected time dependent risk measure represents the objective function of the optimization. The time dependent function of the selected risk measure is obtained from probabilistic safety assessment, i.e. the fault tree analysis at the system level and the fault tree/event tree analysis at the plant level, both extended with inclusion of time requirements. Results of several examples showed that it is possible to reduce risk by application of the proposed method. Because of large uncertainties in the probabilistic safety assessment, the most important result of the method may not be a selection of the most suitable schedule of safety equipment outages among those, which results in similarly low risk. But, it may be a prevention of such schedules of safety equipment outages, which result in high risk. Such finding increases the importance of evaluation speed versus the requirement of getting always the global optimum no matter if it is only slightly better that certain local one.
Geotechnical and safety protective equipment planning using range point cloud data and rule checking in building information modeling
After experiencing 806 fatalities in 2012, safety continues to be among the top concerns in the US construction industry. Among all construction operations, excavation is one of the most hazardous because of its inherent consequences from potential cave-ins, falls, and contacts of workers-on-foot with equipment or unknown objects. Current design, planning, and inspection of safety equipment at excavation sites is insufficient as it is still done manually, infrequently, time-consuming, and prone to human error. A new method is presented that semi-automatically identifies fall and cave-in hazards related to excavation pits and models, among other temporary geotechnical excavation objects, the required fall protection equipment. The approach first extracts relevant fall risk criteria from safety rules and regulations published by the Occupational Safety and Health Administration (OSHA) and applied in industry best practices. Three-dimensional (3D) range point clouds from the excavated pits are then collected to measure the geometrical properties of the pit. An algorithm extracts height information automatically to identify and locate fall hazards. The integration of geometric parameters with geotechnical and safety regulations finally results in a building information model (BIM) that includes the installation of safety equipment. An experimental field trial demonstrates the applicability of the developed method for successful use by practitioners in the industry.
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