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BACKGROUND: Work-related fatigue can cause disruption in mental and physical activities of the workers. Considering the importance of recovery from fatigue in emergency services, as seen in firefighting duties, the preparation and validation of the Need For Recovery Scale (NFRS) questionnaire can be useful and effective. OBJECTIVE: This study assessed the reliability and validity of the Persian version of Need For Recovery Scale among industrial firefighters. METHODS: Need for recovery scale contains 11 questions. First, a questionnaire was translated using backward-forward method. Then, for measuring validity of the questionnaire, the opinions of 10 experts in related fields were obtained. Content Validity Index (CVI) and Content Validity Ratio (CVR) were calculated. The reliability was determined through 107 questionnaires completed by the industrial firefighters. RESULTS: The average age of the firefighters in this study was 37.5 years and they had an average of 10 years of work experience. The mean Need For Recovery Index from fatigue was 33.03 for the study population. Of the first 11 questions, 9 questions in the original NFRS showed a satisfactory level of CVR. The Content Validity Index and Cronbach’s α were 0.89 and 0.77 respectively. CONCLUSION: Based on the results, the Need For Recovery Scale is a reliable tool for assessing fatigue and revealed an acceptable level of validity and reliability that makes it usable for fatigue assessment in the industrial firefighters.

Objective:Crisis management in major accidents requires the collaboration among different organizations. One of the most important problems of crisis management is the lack of coordination between executive organizations. The aim of this study was to examine the structural characters and problems of interorganizational network during crisis in the petrochemical industry and provide solutions to achieve the highest performance in crisis management.Methods:The organizations involved in crisis management were identified through interviews and questionnaires. Gephi (0.9.1) software was used to examine interorganizational relationships.Results:In this study, the crisis management team consisted of 25 public and private organizations and non-governmental organizations. The highest betweenness centrality was observed in Crisis Management of Provincial Government (CMPG) (142.16) and Fire Department of Petrochemical Complex (FDC) (89.3). The highest closeness centrality was observed in FDC (0.77), CMPG (0.7), Shazand Governorate (0.7), and Crisis Management of University of Medical Sciences (0.7).Conclusions:Coordination between organizations plays an important role in crisis and emergency management, and social network analysis helps identify strengths and weaknesses of organizations involved in crisis management, overcome those weaknesses, and consequently achieve the best performance in crisis management.

The present study aimed to investigate fatigue among firefighters and its relationship with their safety behavior. The moderation and mediation effects of perceived safety climate on this relationship were also investigated. Firefighters from 10 petrochemical companies in Iran were investigated. Moderation analysis was performed based on hierarchical regression analyses and mediation effects were studied using structural equation modeling. A total number of 261 firefighters participated in this study. The mean scores of general fatigue, physical fatigue, reduced activity, reduced motivation and mental fatigue were 10.5, 9.0, 8.2, 7.6 and 8.7, respectively. Fatigue had a negative significant effect on firefighters' safety behavior. Perceived safety climate had a mediation but not moderation effect on the relationship between fatigue and safety behavior of firefighters. Generally, the fatigue level among firefighters was fairly low, but had a significant negative effect on firefighter's safety behavior. Perceived safety climate can mediate such a negative effect.

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, ...

Unsafe behavior is closely related to occupational accidents. Work pressure is one the main factors affecting employees' behavior. The aim of the present study was to provide a path analysis model for explaining how work pressure affects safety behavior.Using a self-administered questionnaire, six variables supposed to affect safety employees' behavior were measured. The path analysis model was constructed based on several hypotheses. The goodness of fit of the model was assessed using both absolute and comparative fit indices.Work pressure was determined not to influence safety behavior directly. However, it negatively influenced other variables. Group attitude and personal attitude toward safety were the main factors mediating the effect of work pressure on safety behavior. Among the variables investigated in the present study, group attitude, personal attitude and work pressure had the strongest effects on safety behavior.Managers should consider that in order to improve employees' safety behavior, work pressure should be reduced to a reasonable level, and concurrently a supportive environment, which ensures a positive group attitude toward safety, should be provided. Replication of the study is recommended.

Introduction Unsafe behavior increases the risk of accident at workplaces and needs to be managed properly. The aim of the present study was to provide a model for managing and improving safety behavior of employees using the Bayesian networks approach. Methods The study was conducted in several power plant construction projects in Iran. The data were collected using a questionnaire composed of nine factors, including management commitment, supporting environment, safety management system, employees’ participation, safety knowledge, safety attitude, motivation, resource allocation, and work pressure. In order for measuring the score of each factor assigned by a responder, a measurement model was constructed for each of them. The Bayesian network was constructed using experts’ opinions and Dempster-Shafer theory. Using belief updating, the best intervention strategies for improving safety behavior also were selected. Results The result of the present study demonstrated that the majority of employees do not tend to consider safety rules, regulation, procedures and norms in their behavior at the workplace. Safety attitude, safety knowledge, and supporting environment were the best predictor of safety behavior. Moreover, it was determined that instantaneous improvement of supporting environment and employee participation is the best strategy to reach a high proportion of safety behavior at the workplace. Conclusion The lack of a comprehensive model that can be used for explaining safety behavior was one of the most problematic issues of the study. Furthermore, it can be concluded that belief updating is a unique feature of Bayesian networks that is very useful in comparing various intervention strategies and selecting the best one form them.

Objective: Many scattered resources of knowledge are available to use for chemical accident prevention purposes. The common approach to management process safety, including using databases and referring to the available knowledge has some drawbacks. The main goal of this article was to devise a new emerged knowledge base (KB) for the chemical accident prevention domain. Design: The scattered sources of safety knowledge were identified and scanned. Then, the collected knowledge was formalized through a computerized program. The Protege software was used to formalize and represent the stored safety knowledge. Results: The domain knowledge retrieved as well as data and information. This optimized approach improved safety and health knowledge management (KM) process and resolved some typical problems in the KM process. Conclusion: Upgrading the traditional resources of safety databases into the KBs can improve the interaction between the users and knowledge repository.

Background: Human error is one of the major causes of accidents in the petrochemical industry. Under critical situation, human error is affected by complex factors. Managing such a situation is important to prevent losses and injury. This study aimed to develop a dynamic model of human error assessment in emergencies in the petrochemical industry. Study design: A cross-sectional study. Methods: Fuzzy Bayesian network was used to improve the capabilities of the method for determining the control mode. Fuzzy-AHP-TOPSIS method was also used to prioritize emergency scenarios and human error assessment was applied for the most important emergency condition. Results: Fire in a chemical storage unit was recognized as the most important emergency condition. Common Performance Conditions (CPCs) were determined based on the opinions of a panel of 30 experts and specialists and 7 CPCs were selected for emergencies; then, based on the results of AHP method the relative weights were determined. Finally, membership functions, inputs, and outputs of fuzzy sets, CPC values in 8 emergency response tasks, and the probability of control modes were determined using Bayesian Cognitive Reliability and Error Analysis Method (CREAM) method. Conclusion: This method could be applied to overcome the weaknesses of traditional methods, provide a repeatable method for human error assessment, and manage human error in an emergency.

OBJECTIVES Throughout the world, mines are dangerous workplaces with high accident rates. According to the Statistical Center of Iran, the number of occupational accidents in Iranian mines has increased in recent years. This study investigated and analyzed the human and organizational deficiencies that influenced Iranian mining accidents. METHODS In this study, the data associated with 305 mining accidents were analyzed using a systems analysis approach to identify critical deficiencies in organizational influences, unsafe supervision, preconditions for unsafe acts, and workers' unsafe acts. Partial least square structural equation modeling (PLS-SEM) was utilized to model the interactions among these deficiencies. RESULTS Organizational deficiencies had a direct positive effect on workers' violations (path coefficient, 0.16) and workers' errors (path coefficient, 0.23). The effect of unsafe supervision on workers' violations and workers' errors was also significant, with path coefficients of 0.14 and 0.20, respectively. Likewise, preconditions for unsafe acts had a significant effect on both workers' violations (path coefficient, 0.16) and workers' errors (path coefficient, 0.21). Moreover, organizational deficiencies had an indirect positive effect on workers' unsafe acts, mediated by unsafe supervision and preconditions for unsafe acts. Among the variables examined in the current study, organizational influences had the strongest impact on workers' unsafe acts. CONCLUSIONS Organizational deficiencies were found to be the main cause of accidents in the mining sector, as they affected all other aspects of system safety. In order to prevent occupational accidents, organizational deficiencies should be modified first.

During an unexpected incident, companies should demonstrate appropriate behaviour based on predetermined and rehearsed emergency strategies. This paper describes how to select the proper strategies for emergency situations via means of the AHP-SWOT tool, where the initial SWOT analysis is conducted for the emergency management system, and the final strategies are selected via the analytic hierarchy process (AHP). Alternative response strategies comprise internal, shared and external responses. Most of the scenarios investigated for this study demanded a shared response. These findings highlight the importance of mutual aid agreements, cooperative exercises and the improvement of communication systems. Organisations can take advantage of integrated approaches to select the best strategies and tactics for normal situations in general and emergency situations in particular.

This study investigated the combined effect of firefighting operations and exposure to smoke on physiological responses, cognitive functions and physical performance among firefighters. Each firefighter was engaged in two experimental conditions: (a) without artificial smoke, control (NS); (b) with artificial smoke (WS). The results of data analysis revealed that heart rate and body temperature increased significantly after the firefighting activities in the two conditions relative to baseline. In addition, reaction time (RT) and correct response (CR) decreased after the activity relative to baseline and there was a significant difference in RT and CR between the NS and WS conditions. There was also a significant difference in performance time between the NS and WS conditions. These findings demonstrated that a smoke compound has an insignificant effect on physiological responses during firefighting activity. On the contrary, the smoke compound has a detrimental influence on cognitive and physical performance.

High-risk unsafe behaviors (HRUBs) have been known as the main cause of occupational accidents. Considering the financial and societal costs of accidents and the limitations of available resources, there is an urgent need for managing unsafe behaviors at workplaces. The aim of the present study was to find strategies for decreasing the rate of HRUBs using an integrated approach of safety behavior sampling technique and Bayesian networks analysis.A cross-sectional study.The Bayesian network was constructed using a focus group approach. The required data was collected using the safety behavior sampling, and the parameters of the network were estimated using Expectation-Maximization algorithm. Using sensitivity analysis and belief updating, it was determined that which factors had the highest influences on unsafe behavior.Based on BN analyses, safety training was the most important factor influencing employees' behavior at the workplace. High quality safety training courses can reduce the rate of HRUBs about 10%. Moreover, the rate of HRUBs increased by decreasing the age of employees. The rate of HRUBs was higher in the afternoon and last days of a week.Among the investigated variables, training was the most important factor affecting safety behavior of employees. By holding high quality safety training courses, companies would be able to reduce the rate of HRUBs significantly.

Industrial accidents are among the most known challenges to business continuity. Many organisations have lost their reputation following devastating accidents. To manage the risks of such accidents, it is necessary to accumulate sufficient knowledge regarding their roots, causes and preventive techniques. The required knowledge might be obtained through various approaches, including databases. Unfortunately, many databases are hampered by (among other things) static data presentations, a lack of semantic features, and the inability to present accident knowledge as discrete domains. This paper proposes the use of Protégé software to develop a knowledge base for the domain of explosion accidents. Such a structure has a higher capability to improve information retrieval compared with common accident databases. To accomplish this goal, a knowledge management process model was followed. The ontological explosion knowledge base (EKB) was built for further applications, including process accident knowledge retrieval and risk management. The paper will show how the EKB has a semantic feature that enables users to overcome some of the search constraints of existing accident databases.