Driver drowsiness has been one of the main causes of on-road crashes which can lead to death, physical injuries and impose significant costs on the societies. The development of non-intrusive methods to be able to detect driver drowsiness in the early stages of drowsiness is great of importance. This is an educational review and its purpose is to provide recent achievements about non-intrusive techniques used to detect driver drowsiness. Recently published related articles were searched in the scientific databases such as Web of Sciences, Scoupous, Pubmed and Google scholar. By studying the articles and extracting the important information, non-intrusive drowsiness detection methods has classified in three distinct categories: Vehicle based measures, behavioral measures and non-intrusive physiologic methods. Each of mentioned categories has its own advantages and limitations. Vehicle based methods are strongly influenced by the road geometry, whether condition and lighting. By tracking the facial expression of the driver, drowsiness can be detected. The main limitation of this method is lighting, because the cameras do not function well at night. However, physiological parameters such as electroencephalography are more reliable than vehicle and behavioral measures, the intrusive nature of these methods limit their applications. In summary, combination of the mentioned method can reliably detect the drowsiness of the driver and further studies about the efficiency of the mentioned techniques in real environments are required.

Background: The implementation of HSE programs is so complicated in tunneling industry which is considered as one of the risky industries. This study aims at investigating the relationship between employees' safety attitudes and status of their belief in destiny, chance and perceived importance of HSE programs in occurrence of occupational accidents.
Methods: This research is a cross-sectional and descriptive-analytical study on a contracting company specialized in tunneling, and investigates a total of 689 subjects. A standard 25-item questionnaire is used to assess safety attitude; and three researcher-made questions are utilized to evaluate the subjects' belief in destiny, chance and perceived importance of HSE programs in occurrence of occupational accidents. The reliability and validity of these questions are obtained by Cronbach's alpha test (α=0.76). All analyses are done at the significance level of 0.05 by the help of SPSS 16 software.
Results: There is a significant direct relationship between belief in chance in occurrence of occupational accidents with subjects' safety attitudes (P-value<0.05 and r=0.76), and also between belief in absolute destiny in occurrence of occupational accidents (P-value<0.05 and r=0.59). Furthermore, there is a significant direct relationship between status of acceptance and perceived importance of HSE unit programs in reducing the occupational accidents with subjects' safety attitudes (P-value<0.01 and r=0.51), and also between belief in chance in occurrence of occupational accidents (P-value<0.05 and r=0.68).
Conclusion: According to the results of this study, the employees, who consider external factors such as chance and destiny as the main and absolute reasons for occurrence of occupational accidents, believe less in controlling accidents by looking for solution and scientific and educational methods such as prevention programs of HSE to cope with event.

Traffic accident is one of the most important challenges of public hygiene that needs global attention and effort. This research was conducted to determine the crash trend and develop the accident prediction model that leads to death. This descriptive analysis was performed by using the statistical data related to death caused by driving accidents in Ilam, western Iran during 2010 to 2014. In order to determine the related factors to accident death during the years of interest, the time series was used and the ARIMA model was utilized for analyzing the time series. The data was analyzed by STATA 11. During the five years of study, 21.3% of the death people were female while the 78.7% were male from aspect of gender. The results of time series model showed that among all considered variables there was a significant relationship between the type of passageway, situation of deceased person by car accident, accident type, and vehicle type, with fatal accidents (P<0.05). Since the persons died in traffic accidents are mostly men in young ages, so organizing and policy making is considered as a health priority in preventing the accidents and injuries. It is also a key tool for safety improvement in Iran.

Drivers are vulnerable to musculoskeletal and psychological disorders because of substantially harmful agents in this stressful occupation. This study aimed to investigate the influence of driver’s physical and psychological health on the risk of road accidents using fuzzy logic approach. Two input variables including musculoskeletal disorders (MSDs) and mental health, alongside accident risk levels as output variables were fuzzed using a fuzzy inference system (FIS). Triangular and trapezoid membership functions were used to graphically define outputs related to low, moderate, high and very high, in fuzzy sets. A Mamdani-type FIS was applied to represent all the rules in the IF-THEN format and the patterns of linguistic variables were designed using AND, OR and NOT operators. There was significant relationship between MSDs and psychological health with road accidents involving drivers of heavy vehicles (P<0.05). Besides, surface graphs illustrated the relationship between MSDs, psychological health and accident risks. FIS as a novel approach was used for predication of accident risk levels involving drivers of heavy vehicles based on health factors. Physical and psychological health can influence the safe operation of heavy vehicle drivers. The fuzzy inference system provided a method that is advantageous and with promising results for modeling of road accident risk levels on the basis of driver’s physical and mental health.

Occupational stress and employee's health status can affect their productiveness and quality of services. This study was conducted in order to evaluate the relation between psychological health and occupational stress among midwives employed at the governmental and private hospitals of Neyshabur, Iran. In this cross-sectional (descriptive and analytical) study conducted in 2015, all of the employed midwives in the governmental and private hospitals of Neyshabur (78 people) were enrolled. Data were gathered through the Goldberg General Health and the Altmaier's Occupational Stress Questionnaire. Data analysis was done with SPSS 20. Only 14% of the midwives were psychologically healthy, and 86% had some degrees of psychological disorders. In addition, 54% of them were averagely stressed and 46% suffered from severe stress. The results of this research showed an opposite and significant association between psychological health and occupational stress in midwives (P=0.049). Most midwives working in these hospitals suffered from psychological disorders. Probably occupational stress was involved in deteriorating their psychological health.

Spreading wood particles and attached colored materials in workplaces can cause many problems for woodworking industry workers. The aim of this study was to design and implement a local exhaust ventilation system to control wood dust and toluene diisocyanate simultaneously. The study was conducted on 18 workstations in the paint plant of a wood door industry in west Azarbaijan, 2015. The National Institute for Occupational Safety and Health (NIOSH) 500 and 5522 methods were used to measure the concentration of wood dust and TDI (2, 4-toluenediisocyanate), respectively. In order to control the worker exposure to the pollutants, a semi-downdraft spray chamber was chosen and implemented based on American Conference of Government Industrial Hygienists (ACGIH) control air pollution method. Finally, after the establishment of a new ventilation system, the emissions were re-measured and the results were evaluated. Before design and implementation of local exhaust ventilation system, the emissions in workstations were measured as 0.0165 ± 0.0025 ppm for TDI and 0.42±0.01 mg/m3 for total dust. The concentration of TDI and total dust after implementing the local exhaust ventilation system were measured respectively as 0.003± 0.0007 ppm and 0.15± 0.07, which had a significant (P˂0.05) lower concentration than before the implementation. In addition, the measured concentrations after the implementation had met the ACGIH limits. The system efficiency for wood dust and TDI were 64% and 82% respectively. After design and implementation of the spray chamber, both pollutants were significantly decreased (P<0.05).

Shift work is an important factor influencing the sleep quality and sleepiness of nurses. The aim of the present research was to compare sleep quality in three groups: 1) nurses with shift work SN), 2) nurses without shift work (DN) as a control group for evaluating the effects of shift work, 3) regular non-shift employees (DE) who were not nurses, as a control group for the nursing job; to evaluate the effect of shift work and the nursing job in regard to sleep quality. The present cross-sectional study was carried out in 2013. The research participants were 326 nurses without shift work and with shift work and employees from one of Kerman University of Medical Sciences’ hospitals, Kerman, Iran. Data were gathered via the Pittsburgh Sleep Quality Questionnaire and the Epworth Sleepiness Questionnaire. Data were analyzed by SPSS 18. Overall, 91.2% of nurses (SN & DN) and 79.6% of employees (DE) had poor sleep quality. The sleep quality (P=0.013) and sleepiness (P=0.005) of all hospital nurses were significantly different from that of the university employees. However, there was not a significant difference between the nurses without and with shift work in terms of sleep quality (P=0.87) and sleepiness (P=0.41). Almost all nurses and most university employees suffer from poor sleep quality. Daily average sleep hours and shift work are among the influencing factors causing sleepiness and poor sleep quality.