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Background & Objective: The study of academic burnout and its predictors as one of the main challenges of the educational system is of great importance. This research was conducted to investigate and explain the role of hope for employment and its subscales in predicting academic burnout. Materials & Methods: All health sciences students at Ilam, Arak, Birjand, Semnan, and Hamedan Universities of Medical Sciences, Iran, in 2019 were examined in this descriptive-correlation study. The samples were selected using a stratified random sampling method (n=400). The required data were gathered using the Academic Burnout Questionnaire (developed by Berso et al.) and the Qureshi Rad Employment Hope Questionnaire. The collected data were analyzed in the SPSS-20 software using an independent t-test, one-way ANOVA, and simple and multiple linear regressions. Results: The results of the study showed that 2.3%, 61.3%, and 36.5% of students suffered from low, medium, and high levels of academic burnout, respectively. The mean ± SD of the hope for employment score was 55.69±14.61, indicating a moderate level of hope for employment among the study participants. Based on the study results, 8.4% of the variance of academic burnout could be predicted by hope for employment (F=37.58, R=0.298, R2=0.086, adjusted R2=0.084, P

Background: Needlestick and sharps injuries (NSIs) are a major issue in healthcare settings and should be properly managed. As a type of occupational accident, NSIs are rooted in many causes, including poor safety climate. The current study was conducted to find links among safety climate, safety performance, and NSIs. Methods: The study was cross-sectional and all data were collected in 2020. The sample was composed of 221 nurses. Two dimensions of safety performance and six dimensions of safety climate alongside the experience of NSIs in the last year were investigated using validated questionnaires. The path analysis model was built and tested using Mplus software package. Results: The path analysis model was acceptable in terms of goodness-of-fit metrics. The model supported the mediating role of safety performance on the relationship between safety climate and NSIs. Among safety climate dimensions, safety training had the highest relationship with safety performance dimensions, followed by attitude toward error reporting and cumulative fatigue. Safety participation had a stronger effect on NSIs than safety compliance. Conclusion: As all safety climate dimensions were significantly correlated with safety performance dimensions and NSIs, promoting safety climate can be effective in improving safety performance and preventing NSIs among nurses.

Introduction: Recent evidence indicates that lighting can affect physiological and neurobehavioral human functions, referred to as non-image forming (NIF) effects of lighteffects. This study aimed to determine the effects of illumination levels and correlated color temperature (CCT) on alertness and performance under NIF conditions. Material and Methods: In this study, 22 participants were exposed to light at various levels of illumination, including very low illuminance (

Background and Objective: Systematic analysis of accidents in sociotechnical systems, such as mining industry, is very important to reduce accidents. The present study aimed to analyze the relationship among human factors in mining accidents using a systematic approach. Materials and Methods: The accidents occurred during seven years in a large iron ore mine complex in the south of Iran were collected, and the most important events were selected subsequently. Afterward, all contributing factors in each accident were identified using an accident analysis team by Human Factors Analysis and Classification System (HFACS) framework. A total of 154 accidents were collected, and the data were analyzed in SPSS Software (version 16) using logistic regression. Results: Skill-based errors were the most frequent among the unsafe acts. Furthermore, the deficiencies in physical environment, as well as inappropriate operations and organizational procedures were the most frequently identified deficiency in the selected accidents. Throughout the overall system, the existence of some deficiencies in upper levels predicted those in lower levels, which included organizational climate, inadequate supervision, organizational procedures and inappropriate operations, inadequate supervision and physical environment, as well as inappropriate operations and physical environment. Conclusion: Skill-based errors, supervision problems, and organizational procedures are the most common deficiencies in mining industry accidents. Analysis of the relationship among the causal factors at different levels of HFACS is necessary to adopt appropriate strategies to reduce the accidents.

The increasing abundance of fires in industrial buildings has led to the growth of fire risk assessment and protection methods. However, few studies have been performed on the practical application of these risk assessment methods in industrial structures. This study aimed at assessing fire risk and determining the effectiveness of fire control measures to reduce fire-related injuries and fatalities to occupants at a combined-cycle power plant in the northeast of Iran. In the present study, firstly, the fire risk level of the real condition for the occupants, building and contents, and activities were measured using the Fire Risk Assessment Method for Engineering (FRAME). Then, taking into account the fire control measures, the fire risk was recalculated and compared with the acceptable risk level. The results indicated that the occupants’ fire risk level was 1.26 that was above the acceptable level. Furthermore, in the case of a fire, the expected destruction of the control room will be approximately 20%. Assuming a constant fire load modulation via building construction by non-burning materials or up to 10% burning materials, the occupants’ fire risk level will be decreased by 8% compared to the current situation. Also, in the state of designing standard emergency exit routes and using the fire alarm system, the fire risk level will be decreased by 50% and 52%, respectively, compared to the current condition. This study indicated that applying quantitative engineering methods for fire risk assessment can help to find practical solutions to minimize losses and fire-related injuries to industrial building occupants.

Background and aims: Fatigue and sleepiness (decreased alertness), in addition to a negative impact on performance and quality of work, are considered as one of the leading causes of human error and accidents in work environments. There is much evidence indicating that physical factors in the workplace could affect fatigue, vitality, motivation, and productivity of individuals. A physical environment suitable for activity is formed by various factors, among which light is known as an essential element. Recent photobiological advances and recognition of intrinsically photosensitive retinal ganglion cells (ipRGCs) have shown that in addition to improving eyesight, light can affect the circadian and homeostatic regulations and melatonin suppression in human. Furthermore, light can have acute effects on the physiological, psychological, neurobehavioral, and neuroendocrine responses, such as improvement in the alertness and neurobehavioral performance, which are known as the non-visual or non-imaging forming effects (NIF) of light. However, the possible roles of these potential effects in the improvement of human safety and efficiency have not been thoroughly investigated. Some studies have shown that monochromatic blue light or blue-enriched white light (high correlated color temperature white light or high CCT) can enhance levels of alertness, and improve mood and cognitive function. Although recent evidence has indicated that monochromatic red light or red saturated white light (low correlated color temperature white light or low CCT) has also been able to induce such positive effects. There is still an open question left unanswered: “which of these lighting conditions (high CCT vs. low CCT) has a stronger effect on the alertness level and neurobehavioral function?” Therefore, the present study tested this hypothesis in a simulated office workplace environment with the recommended illumination level of 500 lx on the desk for daytime office work environments during the morning hours. Methods: In this study, 20 healthy paid volunteers (male; mean ± SD age, 27.6 ± 3.6 years) were selected and followed the experimental protocol. All participants were interviewed about the quality of sleep, lifestyle habits, and general health. The inclusion criteria were: not having any mental or physical health problem, having a good sleep quality according to the Persian version of Pittsburgh Sleep Quality Index (PSQI score

Background and aims: Human errors are major causes of the accident that occurring in the industries. However, attributing incidents to human error, regardless of the nature of human error, cannot be useful in preventing accidents. Identifying organizational and supervisory factors that affecting human errors, as well as determining the interactions between these factors, can be used in the management of appropriate control strategies to reduce the accidents. The Human Factors Analysis and Classification System framework (HFACS) is one of the most important and comprehensive qualitative tools to identify human and organizational contributing factors involved in an accident. Until now, several studies have tried to integrate the HFACS with a quantitative analysis tool in order to determine the interactions between human and organizational factors to reduce accidents. There are many types of quantitative tools that researchers usually used for this purpose. Fuzzy analytical hierarchy process, analytical network process, and artificial neural network are the most used analytical quantitative tools in this regard. Powerful graphical probability-based modeling approaches have been less well considered for quantitative analysis of the interaction and relationship between different variables. Bayesian network (BN) is one of the most important quantitative tools in this regard. BN is a probabilistic graphical model that uses for various types of inference such as diagnostic and predictive. Belief updating or sensitivity analysis is one of the exclusive feature of BN that researchers using this feature can examine the sensitivity of one “target variable” to changes in other variables. In the modeling, sensitivity analysis is used to rank the influence of input variables on the predicting of output variables. This study aimed to integrate the HFACS framework and BN to identify different factors that influence unsafe acts and determine the relationships and interactions among identified those factors to provide appropriate intervention strategies for preventing accidents in the future. Methods: In this study, the accidents occurred in one of the largest mines in Iran that occurred during a period of 5 years (2011-2015) were collected, and then accidents with serious consequences such as fatalities, disabling injuries, or considerable property damage were screened. In the next step, all contributing factors in each accident were identified using an accident analysis team by root cause analysis (RCA) approach. RCA is a problem-solving approach that is applied to identify the root causes of problems. A total of 250 accidents analysis results were collected and classified in one of the 13 groups of the HFACS framework, and a database was created. According to the structure of the HFACS framework, the BN model was developed. HFACS is a 4 levels hierarchy of human and organizational errors, in which higher levels can influence directly lower levels and this pattern can help to the develop a BN graphical model. Causal factors at the 4 levels of the HFACS consist the nodes of the BN model. In the next step, for each node, states were defined that show different values of the variable. In this study, except for unsafe acts node that had three states (skill based, decision, and perceptual), other nodes had two states; yes (node involved in an accident) and no (node not involved in an accident). The main hypothesis of the HFACS framework is that deficiency at the higher level casual factors can lead to deficiency at the lower level casual factors. Hence, in the present study, all causal factors (parents nodes) at the higher level were connected to the lower level causal factors (child nodes) edge with arcs. For instance, causal factors of unsafe supervision (level 3) that include inadequate supervision, planned inappropriate operations, failure to correct a known problem, and supervisory violations are parents of environmental factors, personnel factors, and condition of operator nods which belong to preconditions for unsafe acts (level 2). After the graphical structure of the BN model was developed, using database that obtained in the previous section and the expectation–maximization (EM) algorithm model was trained. In a BN the conditional probability tables (CPTs) are used to determine quantitative relationships among a set of variables. The EM algorithm is one of the common methods to calculate. There are several approaches for conducting a sensitivity analysis but the mutual information (MI) approach is most common. In order to determine the factors with greatest impact on unsafe acts, the MI approach was used and the sensitivity analysis was performed. In probability theory, the MI of two random variables is a measure of the mutual dependence between the two variables. In the current study, Netica version 5.24 was used to perform calculations and analyses. Results: The results of this study showed that at the level of unsafe acts, skill-based errors (%67.3) had the highest prior probability technique errors were the most skill based errors that were detected. Also at the level of unsafe conditions, environmental factors (%74.8) had the highest prior probability. Inadequate installation and improper housekeeping were the most frequently identified environmental factors that led to accidents. At the levels of unsafe supervision and organizational influences, inappropriate planned operation (%60.6) and organizational processes (%35.3) had the highest prior probability, respectively. Inadequate task/safety plan from unsafe supervision level and lack of standard operation procedures from organizational influences level were the most frequently identified deficiency in the selected accidents. The results of the sensitivity analysis demonstrated that the environmental factors from level 2, inappropriate planned operation from level 3, and organizational processes from level 4 had the greatest impact on unsafe acts. Based on the analysis results, several strategies were made to reduce the unsafe acts of employees. Conclusion: In the current study, by integrating the HFACS framework as a qualitative tool and BN as a powerful quantitative tool, a human factors analysis model was developed. The results of this study indicated that the environmental factors and inappropriate planned operation had the most effect on the unsafe acts. Although organizational influences play a role as indirect factors on the unsafe acts, paying attention to eliminating defects at this level can be useful in reducing accidents. Different forms of unsafe acts require various interventions, therefore, the use of BN model can be helpful in determining strategies tailored to the specificities of the unsafe acts.

Introduction: In recent years, unauthorized disposal of the hazardous wastes has threatened the human health and created many environmental problems in human societies. Given the direct and indirect hazards of these wastes, it is essential to collect information with regard to their appropriate management in Iran. The purpose of this study was to determine the quantity and quality of the hazardous waste and its management in industries of Damghan City in Iran. Methods: Initially, the list of industries in Damghan City was prepared. Later, the necessary coordination was made with the relevant organizations and active units were identified. After the field tours, information on the quality, quantity, and management of the hazardous wastes was collected by a questionnaire. Results: The results showed that the total hazardous waste products in the investigated industries were 4795 kg per month; 36.36% of the industries produced toxic substances, 9.09% created corrosive substances, 36.36% flammable materials, and 18.18% resulted in reactive substances. None of the studied industrial units had a control system after disposal of the industrial hazardous waste. Furthermore, only 36.36% of the industries had specialized staff to collect and dispose the hazardous waste. Conclusion: To prevent environmental pollution and preserve the human health, a proper management system should be established for organizing the industrial wastes. Furthermore, identifying and gathering information about the industrial processes, raw materials, and waste products can be very useful in managing hazardous industrial wastes.

Introduction and purpose: Students’ perceptions of the learning environment play a vital role in the process of education, buoyancy, and academic performance. This study aimed to investigate the capability of explaining the academic buoyancy and academic performance of health students of Semnan University of Medical Sciences, Semnan, Iran, based on their perception of learning environment. Methods: The statistical population of this descriptive-correlational study consisted of all health students who were studying at Semnan University of Medical Sciences, Semnan, Iran, in the academic year 2018-19. A total number of 138 students were selected through systematic random sampling. The data were collected using a Dundee Ready Educational Environment Measure (DREEM), academic buoyancy questionnaires, and grade point average. Moreover, simple and multiple regressions were used for data analysis. Results: The results showed that 16.1% (R=0.408, R2=0.167, Adjusted R2=0.161, F=27.212, P

Introduction: In developing countries, multiple criteria decision-making techniques are important ways to overcome financial, human and information restrictions, and the elimination of existing conflicts in the selection of appropriate solutions in order to increase the level of safety and improve productivity. The aim of this study was to determine and compare the risk calculated by the two methods of multi-criteria decision-making including, TOPSIS and measure of belief approach in fuzzy logic concepts to resolve doubts in selection of control priorities. Methods: In order to identify hazards, the documentation review, interviews with experts, brainstorming sessions, knowledge and experience group of experts in occupational health and safety engineering were used. Then, the real risks of identified hazards were determined using TOPSIS and measure of belief approach in fuzzy logic. Results: In the present study, according to TOPSIS, falling in tanks, reservoirs, and canals with the relative closeness 0.7439 ranked in the first place and explosion with the relative closeness 0.5769 had the second place. Furthermore, in the fuzzy method, firing gas turbines and breakage of high pressure steam pipes, with the measure of belief 0.6, ranked in the first place and falling in tanks, reservoirs, and canals with the measure of belief 0.2 had the second place. The results showed that the two methods have solidarity and are matched in determining the risk of safety hazards in industrial power plants. Conclusion: Using logical and mathematical methods, could manage limited resources and adopting the most appropriate control strategies.

Introduction: Extensive human and economic losses due to the fire accidents shows the necessity of scientifically dealing with major industrial fires, , investing in the development of fire protection technologies and determination of the most effective techniques to limit damages. This study is conducted to evaluate the effect of active and passive protection methods on reducing the level of fire risk, in the control room of a thermal power plant. Material and Method: In the first phase of this study, fire risk level for buildings, goods, occupants and activities was calculated using Fire Risk Assessment Method for Engineering. In the second phase, from 36 sub-factors affecting risk level, three sub-factors of passive protection measures and two sub-factors of active protection measures were analyzed and modified, in reducing the fire risk level of occupants. Result: The results of the present study showed that occupants’ fire risk level (20.64) is above the acceptable level. Correction of three sub-factors, including constant fire load, floor number, and changing the dimensions and area of the control room up to 40% and installing an automatic fire extinguishing system and training the occupants to use fire extinguishing equipment and emergency evacuation up to 33%, is effective in reducing the fire risk level. Conclusion: Passive and active protection methods, despite their impacts on reducing the level of risk, cannot provide an acceptable level of fire safety independently. Therefore, combined use of these methods is essential to protect buildings and people, and prevent any interruption in the system’s activities.

Introduction: The development and growth of industrial activities, has made environmental pollution a global challenge. Environmental assessment is an important approach which in addition to examining the impact of environmental pollutants on human health and other living organisms can provide solutions for optimal decision making and set control priorities. Methods: In this study, due to the importance of the relationship between qualitative criteria, the hierarchical analysis method was conducted to determine the control priorities of gaseous pollutants. Document reviews, results of measuring pollutants at power plant, knowledge and experience of 20 experts in health, environment and industrial safety were utilized in order to select and evaluate SO2, NOX, CO2 and CO2 gases. Then, criteria of permissible exposure limits, social costs and consequences were used for pairwise comparisons. Finally, inconsistency coefficient was calculated to confirm the results and compatibility in assessments. Results: Results of this study showed that NOX with the final weight of 0.58 was regarded as the first priority, SO2 with the weight of 0.32 considered as the second priority, CO2 with the weight of 0.052 was set as the third priority and CO with the weight of 0.038 was regarded as the last priority. Conclusion: Multi criteria decision making techniques, using expert qualitative opinions and converting them into quantitative variables reduces uncertainty in choices and ambiguity in planning, and can be utilized as an acceptable approach in determining control priorities of environmental pollutants

Background and aims: taxi drivers are a large group of professional drivers, who spend so much time in driving. Considering traffic collisions as one of the Traffic Safety System in the country, modification of improper driving behaviors of this group can result in a significant decrease in accidents. Methods: This analytical-descriptive study was conducted on 245 taxi drivers in 2013. A questionnaire aimed into two sections: demographic information and reasons for lack of night use of the automotive lighting system was designed. The content validity of the questionnaire was confirmed by the experts and professors’ comments and its reliability was confirmed by Cronbachchr('39')s coefficient alpha (0.72). Results: It was found that 26.9% of the drivers do not turn on their automotive lighting system over nigh. Most in main squares of the city (46.2%). Forgetfulness in turning car’s light on (14.28%) and depreciation on car lights (13.06%) are the major reasons. Moreover, a significant relationship was observed among variables like working in taxi driving as the main occupation (P-Value= 0.0001), lack of receiving warning from passengers (P-Value= 0.0001), the level of education (P-Value= 0.012) and lack of using automotive lighting system. Conclusion: Considering that forgetfulness was the main reason for lack of using the lighting system and most of the drivers have not been received any warning or punishment from police because of lack of using lights overnight, it is essential to use appropriate training and exertion of regulations, as one of the ways to create correct culture of traffic and improve driver performance.

Introduction: Nanotechnology as a key technology in the 21st century refers to the science of manipulating molecules and atoms in size range of 1 to 100 nanometers. Given the importance of investment in research and development, promoting knowledge and attitude of students can have a positive effect on expanding the scope and use of these emerging technologies. Methods: In this descriptive analytical study, the knowledge and attitudes of 130 students towards the benefits and risks of nanotechnology were investigated through a questionnaire. The participants were studying occupational and environmental health engineering in Hamadan, Ilam, and Semnan Universities of Medical Sciences. Results: The mean score of students' knowledge was 16.08 ± 1.61. A significant difference was observed between the mean scores of knowledge in undergraduate and graduate students (P= 0.001). However, no significant deference was observed in the mean score of knowledge between women and men, different age groups, and the year of entrance to university. Using linear regression equation and by considering knowledge level as a dependent variable, it was indicated that age and educational level were significantly related to the state of knowledge. Conclusion: The results showed that most students did not have an acceptable level of knowledge about nanotechnology. Considering the benefits and risks of this technology, students have a positive attitude to develop use of nanotechnology in Iran.

Fatigue and sleepiness are one of the main causes of human errors and accidents in the workplace. The empirical evidence has approved that, in addition to stimulating the visual system, light elicits brain responses, which affect physiological and neurobehavioral human functions, known as the non-image forming (NIF) effects of light. As recent evidences have shown the positive effects of red or low correlated color temperature white light on alertness and performance, we investigated whether exposure to 2564 K light could improve subjective and objective measures of alertness and performance compared with 7343 K, 3730 K, and dim light (DL) conditions during the daytime. Twenty two healthy participants were exposed to the light while they were performing a sustained attention task and their electroencephalogram (EEG) and electrocardiogram (ECG) were recorded. Both 2564 K and 7343 K conditions significantly reduced EEG alpha-power compared with the DL and 3730 K conditions. Moreover, the 2564 K, 7343 K, and 3730 K conditions significantly reduced subjective fatigue, sleepiness and increased heart rate and performance compared with the DL condition. Furthermore, the effects of light conditions on alertness and performance varied over the day so that more effective responses were observed during the afternoon hours. These findings suggest that light interventions can be applied to improve daytime performance.