Problematic internet use and safety behavior: The moderating role of safety climate.

Problematic internet use (PIU) can cause mental and physical harm to individuals and may be an emerging factor contributing to unsafe work behavior. In this study, the relationship between PIU and safety behavior was investigated. Moreover, it was hypothesized that safety climate can moderate the relationship between PIU and safety behavior. Participants were employees from a mining industry in Iran. Three validated questionnaires were distributed to gather the required data regarding PIU, safety climate, and safety behavior. Hierarchical regression analysis was used to assess the moderating effect of safety climate on the relationship between PIU and safety behavior. The size of moderation effect was assessed using f2 index. Four hundred eighty-five employees participated in this study. The results demonstrated a negative relationship between PIU and safety behavior. The moderating effect of safety climate on the relationship between PIU and safety behavior was supported. The f2 index was 0.027 which demonstrates a small moderation effect. In conclusion, PIU has a significant negative effect on the safety behavior of employees. Providing a strong safety climate can be a long-term solution for reducing the negative effect of PIU on safety behavior.

Analysis of human and organizational factors that influence mining accidents based on Bayesian network.

Purpose. The present study aimed to analyze human and organizational factors involved in mining accidents and determine the relationships among these factors. Materials and methods. In this study, the human factors analysis and classification system (HFACS) was combined with Bayesian network (BN) in order to analyze contributing factors in mining accidents. The BN was constructed based on the hierarchical structure of HFACS. The required data were collected from a total of 295 cases of Iranian mining accidents and analyzed using HFACS. Afterward, prior probability of contributing factors was computed using the expectation-maximization algorithm. Sensitivity analysis was applied to determine which contributing factor had a higher influence on unsafe acts to select the best intervention strategy. Results. The analyses showed that skill-based errors, routine violations, environmental factors and planned inappropriate operation had higher relative importance in the accidents. Moreover, sensitivity analysis revealed that environmental factors, failed to correct known problem and personnel factors had a higher influence on unsafe acts. Conclusion. The results of the present study could provide guidance to help safety and health management by adopting proper intervention strategies to reduce mining accidents.

Analysis of the severity of occupational injuries in the mining industry using a Bayesian network.

OBJECTIVES: Occupational injuries are known to be the main adverse outcome of occupational accidents. The purpose of the current study was to identify control strategies to reduce the severity of occupational injuries in the mining industry using Bayesian network (BN) analysis. METHODS: The BN structure was created using a focus group technique. Data on 425 mining accidents was collected, and the required information was extracted. The expectation-maximization algorithm was used to estimate the conditional probability tables. Belief updating was used to determine which factors had the greatest effect on severity of accidents. RESULTS: Based on sensitivity analyses of the BN, training, type of accident, and activity type of workers were the most important factors influencing the severity of accidents. Of individual factors, workers' experience had the strongest influence on the severity of accidents. CONCLUSIONS: Among the examined factors, safety training was the most important factor influencing the severity of accidents. Organizations may be able to reduce the severity of occupational injuries by holding safety training courses prepared based on the activity type of workers.

Short-term exposure with vibration and its effect on attention.

BACKGROUND: About 20 to 50 percent of accidents are due to some forms of carelessness and mindedness. Studies suggested that vibration is one of the most important physical factors in human performance when traveling on any sort of vehicles. The aim of this study was to investigate the effect of vehicles vibration on cognitive performance (attention and concentration). METHODS: The sample consists of 25 male students who undergone 4 experimental phases: acceleration low vibration (0.53 m/s(2)), medium vibration (0.81 m/s(2)), high vibration (1.12 m/s(2)) and non- exposure to vibration (control phase) according to ISO 2631-1 standard and with fixed frequency between 3 to 7 Hz. Students paired T test was applied to analysis the data, using SPSS software ver. 19. RESULTS: The mean number of correct answers obtained from selective attention test under vibration levels of 0.53 m/s(2) and 0.81 m/s(2) were significantly lower than the condition without vibration. The mean reaction time of divided attention test in three vibration levels was significantly lower than the condition without vibration. Exposing to vibration reduces number of correct answers, selective attention and reaction time. CONCLUSION: In this study, it was found that vibration may disrupt the ability of the participants for sustainability attention. It also changes the precision and speed of humans' information processing systems.