مجله بهداشت و ایمنی کار
سال چهاردهم شماره 1 (بهار 1403)

The purpose of occupational health is to maintain and improve the health of employees and improve their physical, mental and social well-being through the prevention, control and elimination of occupational hazards. It is necessary to integrate educational, research and health service activities to prevent and control potential occupational health hazards in the community. This study aimed to develop a Joint Comprehensive Plan Of Action (JCPOA) for occupational health at Tehran University of Medical Sciences (TUMS).

In this participatory action research, a strategic planning committee was established, whose members were professors of the occupational health department in the school of public health and managers of the occupational health department in the health deputy of TUMS. The strategic planning committee carried out a strategic evaluation of the internal and external environments of both occupational health deprtments of TUMS and identified the strengths, weaknesses, opportunities and threats. Then, the strategic direction of JCPOA including the vision, mission, values, goals and objectives was determined. Also, the strategies and actions to achieve the goals and objectives were identified. Finally, the action plan to achieve these objectives was developed.

This applied research led to the strategic evaluation of the internal and external environments of the occupational health depratment of the School of Public Health and the occupational health depratment of the Health deputy of TUMS, determining the strategic direction, and finally, developing an action plan to achieve the goals and objectives.

The JCPOA for occupational health was developed using a collaborative and systemic approach. The proper implementation of this plan can lead to the improvement of occupational health indicators in the community. Cooperation between university and industry is necessary for the sustainable development of society.

The design of traffic signs should consider human cognitive abilities to enhance drivers’ understanding of the signs. Cognitive features, as one of the crucial principles of ergonomics, are among the influential factors in the design of signs. The present study aimed to evaluate the effect of graphic elements of eight new sign designs based on cognitive features on conveying the message “prohibition of using mobile phones.”

This study was conducted in six driving schools in Tehran in 2013. One hundred seventy-four participants, with an average age of 23.5 and a standard deviation of six years, participated in this study. Participants were then presented with the designed signs through a colored questionnaire. They were instructed to evaluate the signs’ cognitive features including simplicity, concreteness, meaningfulness, and semantic closeness—using a Likert scale ranging from 0 to 100. 

The results revealed that the average score of the cognitive features of the designed signs is higher than other traffic, industrial and pharmaceutical signs. In this study, “semantic closeness” was the best cognitive feature for predicting the message of the signs. The sign with the “hands-free” element had the best performance in transferring the message.

This research aimed to identify the most effective of eight proposed signs for banning mobile phone use while driving. Participants rated the sign featuring a button phone with a hands-free symbol as the top choice. Although most of the mobile phones in the market are of the touch screen type and the use of button phones has decreased a lot, the symbol of these phones as the dominant symbol still effectively conveys messages.

Disturbing noise can cause physical and mental illnesses among workers; for this reason, it is necessary to restrain it, especially in workplaces. Using sound-absorbing materials with suitable acoustic properties has been a growing trend in mitigating noise. This study aimed to improve the acoustic properties of polyurethane foam (PUF) as a sound absorber.

In the present study, PUF was synthesized with different percentages of clay nanoparticles (0 -1.2 wt.%), and then the Sound Absorption Coefficient (SAC) of the synthesized PUF was measured by the acoustic impedance tube in the frequency range of 63 to 6400 Hz according to the ISIRI 9803 standard without an air gap behind the sample. The morphology of the foam was also investigated by Scanning Electron Microscope (SEM).

The results showed that the addition of clay nanoparticles to PUF improved the sound absorption behavior of the samples, and the best sound absorption behavior was for PUF with 1.2% weight of nanoparticles at low frequencies (500-2600 Hz). This increase in the absorption coefficient can be due to the increase in the number and smaller size of the pores with the increase in the amount of nanoparticles in PUF.

This study illustrates that the incorporation of clay nanoparticles into PUF at varying percentages results in an enhanced absorption coefficient. The presence of clay nanoparticles leads to a reduction in cell size and an increase in the number of pores, consequently enhancing surface friction. The absorption coefficient was observed to increase with the growing concentration of clay nanoparticles in PUF.

People’s risk perception in an emergency situation affects how they behave. During the pandemic of a disease like COVID-19, the fear of the disease and its consequences causes people to deal with anxiety. The present study was conducted with the aim of determining the relationship between the perception of the risk of COVID-19 and the experience of anxiety caused by it among workers in manufacturing industries. 

The present descriptive-analytical study was conducted cross-sectionally in 2022 among 545 workers of manufacturing industries located in Tehran, Mazandaran and North-Khorasan provinces. In the study, data collection was conducted using three questionnaires: a demographic information questionnaire, the COVID-19 Disease Anxiety Scale (CDAS), and the COVID-19 Risk Perception and Psychological Predictors against COVID-19 questionnaire. Data analysis was done using descriptive (mean and standard deviation) and analytical statistics (Canonical Correlation Coefficients or CCC) in SPSS V25 software.

The mean ± SD of the workers’ age was 35.98 ± 7.58 years, while the scores for risk perception and anxiety were 12.89 ± 3.31 and 4.51 ± 1.51, respectively. The Concordance Correlation Coefficient (CCC) between risk perception and anxiety caused by the COVID-19 disease in the first Canonical point was 0.734, and in the second Canonical point, it was 0.229. The corresponding p-value was found to be less than 0.01. Psychological symptoms (Canonical loading = -0.725) and physical symptoms (Canonical loading = -0.421) played a significant role in predicting the variability of the risk perception of COVID-19.

The perception of risk related to the COVID-19 disease resulted in a decrease in anxiety, having a more pronounced effect on psychological symptoms compared to physical symptoms. Therefore, in times of pandemic outbreaks similar to COVID-19, implementing measures that enhance workers’ awareness and understanding of the disease risks can prove effective in managing anxiety.

The prevalence of COVID-19 has significantly impacted work environments and the workforce. Therefore, identifying the most important preventive and control strategies, as well as assessing their effectiveness, is of paramount importance. Various studies have shown that machine learning algorithms can be used to predict complex and nonlinear issues, including predicting the behavior of various diseases such as COVID-19 and the parameters affecting it, and can be beneficial. The purpose of this study has been to examine the importance of preventive measures and hygiene behaviors in preventing COVID-19 in the oil refining industry using various machine learning models.

For this purpose, demographic information and health behaviors of individuals were collected. Subsequently, a multi-layer perceptron (MLP), radial basis function (RBF), and support vector machine (SVM) models were compared to enhance the analysis of the effects of preventive measures on COVID-19 infection. Finally, the most influential factors affecting the likelihood of COVID-19 infection were determined using sensitivity analysis.

The results showed that the accuracies achieved in predicting the impact of preventive measures and health behaviors on COVID-19 in occupational settings were 78.1%, 81.2%, and 78.1% by MLP, RBF, and SVM respectively. The RBF model was identified as the most accurate model for predicting the impact of health behaviors on COVID-19 disease Additionally, the level of social distancing with customers, handwashing frequency and disinfection, the availability of cleansing and disinfecting agents for hands and surfaces in the workplace, and gatherings for eating meals and snacks were identified as the most significant health behaviors influencing the prevalence of COVID-19 in the workplace.

Studies of this nature can underscore the importance of attention to preventive measures and health behaviors in unprecedented circumstances. Furthermore, the utilization of artificial intelligence models and tools such as DSS (Decision Support Systems) can serve as powerful tools for optimizing control measures in work environments.

The goal of this study is to investigate how the development of technology has affected the industry (especially the mining industry). For this purpose, this paper examines the impact of intelligent mining machinery systems, including tire pressure monitoring systems (TPMS), dispatching systems, and vehicle health monitoring systems (VHMS), on health, safety, and environmental parameters and preventative maintenance.

This study is descriptive-analytical research that was conducted between time intervals before and after employing the intelligent mining machinery systems. Initially, parameters were identified using the Delphi method. These parameters include human accidents, equipment accidents, environmental incidents, warnings and fines in the domains of health, safety, and the environment, tire usage parameters, the shelf life of the tire, oil overfill, fuel consumption, failure rate, mean time between failures, and preventive maintenance compliance schedules in the domain of preventative maintenance. The effectiveness of using these systems was then assessed by comparing the state of the specified parameters before and after the introduction of the intelligent mining machinery systems.

The findings of this research indicate that using intelligent mining machinery systems will decrease equipment accidents by 33.3%, extend the useful life of tires by 7.1%, reduce fuel consumption by 14.6%, cut the mean time required to repair by 25.5%, and enhance preventive maintenance compliance schedules by 5.7%.The findings showed the effectiveness of the use of intelligent systems of mining machines was obtained as follows: reduction of equipment accidents by 33.3%, increasing the useful life of tires by 7.1%, reducing fuel consumption by 14.6%, reducing the average downtime of the car for repair by 25.5% and increasing compliance with the maintenance program by 5.7%.

Utilizing intelligent mining machinery systems might have a positive impact on the safety of machines, reduce negative environmental effects like fuel consumption, and improve the maintenance of heavy machinery, which would lead to better mining conditions and lower costs.

Emergency technicians face workplace violence and increasing occupational stress. The purpose of this study was to investigate the impact of a virtual self-management training in communication skills on occupational stress and the degree of aggression among emergency technicians.

This study involved 60 emergency technicians randomly assigned to either the intervention or control group. They completed surveys on workplace violence and occupational stress. The intervention group received six weeks of a virtual self-management training in communication skills. Data was collected after two months and analyzed using SPSS software.

The findings showed that there was no statistically significant difference between the control group (110.08±11.92) and the two intervention groups (114.39±11.25) in terms of the average occupational stress before the intervention; The average job stress score between the intervention (94.0±12,70) and control (98.81± 20,81) groups significantly differed following the intervention (p=0.034); After the intervention, the intervention group had lower verbal and physical abuse frequencies compared to the control group.

The virtual self-management communication training demonstrated the potential to reduce occupational stress but did not significantly decrease the violence towards the emergency technicians. A comprehensive training program addressing violence factors and communication techniques, implemented over a longer period, is recommended.

Steel erection is known as one of the most hazardous construction activities. From an occupational health and safety perspective, this process carries high risk. Therefore, this study aims to conduct a qualitative risk analysis of steel structure assembly and model it using the Functional Resonance Analysis Method (FRAM).

In this cross-sectional study, the construction site of a high-rise building steel structure was first visited to identify the main processes involved. Then, semi-structured and open-ended interviews were conducted with 33 workers partaking in this process. Data from the interviews and process identification were entered into FRAM Model Visualiser (FMV) software to investigate and model complex relationships and interactions between daily tasks.

Of the 19 major system component functions identified, four functions had potential instability and defects due to complex human, organizational, and technological function interactions. By intensifying the FRAM graphic model, risks may be imposed on the system if the interactions of these four functions are neglected. These include coordination with the experienced rigger, preparation of the tower crane, attachment of parts at the installation site, and execution of the rescue rope.

The findings demonstrate that conducting qualitative risk assessment and modeling the steel frame construction process using FRAM allows for an in-depth understanding of nonlinear conditions and dynamics resulting from escalating technical-social interactions. This approach enables a comprehensive analysis of system safety status.

Acceptance of Health, Safety, and Environment (HSE) rules plays a crucial role in determining the performance of employees in HSE-related areas at the workplace. This study aimed to design a questionnaire to investigate influential factors on acceptance of HSE rules among employees.

The face validity of the survey was assessed by ten individuals from the target population, while content validity was evaluated by ten HSE experts using both quantitative and qualitative methods. The impact scores were calculated for the quantitative assessment of face validity, and the Content Validity Ratio (CVR) and Content Validity Index (CVI) values were used to assess content validity. Construct validity was determined through Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) involving 506 participants. The reliability of the survey was evaluated using Cronbach’s alpha and the Intraclass Correlation Coefficient (ICC).

All items in the survey showed satisfactory levels of impact score (>1.5), CVR (>0.69), and CVI (>0.79). The mean values for the Impact score, CVI, CVR, and S-CVI-UA were 4.26, 0.963, 0.944, and 0.62, respectively. The survey and its dimensions demonstrated strong reliability, as indicated by Cronbach’s alpha and ICC values exceeding 0.70. Additionally, EFA successfully identified the structure of the questionnaire, and CFA confirmed its goodness of fit.

The Persian version of the questionnaire demonstrated satisfactory validity and reliability. This instrument can be effectively used to assess the factors that influence the acceptance of HSE rules among employees in various workplace settings.

The accurate evaluation of error probability and risk is important. Accordingly, this Comparative study was conducted to evaluate the risk of human error in emergency situations using SLIM and Fuzzy SLIM techniques in fierfighting tasks.

This cross-sectional and descriptive-analytical study was conducted among 12, using Fuzzy SLIM and SLIM techniques. 39 sub-tasks were studied in 4 phases (Awareness, Evaluation, Egress and Recovery). Considering the advantages of the Fuzzy SLIM method, fuzzy logic was used in weighting of performance shaping factors (PSF). Excel software was used to calculate the probability of error. Also, correlation and kappa statistical tests were used for data analysis in SPSS software.

The mean and standard deviation of human error probability in different sub-tasks of firefighting in SLIM and Fuzzy SLIM methods were 0.095357 ± 0.026193 and 0.06490 ± 0.051748, respectivly. In 48.7 percent of the sub-tasks, the probability category of human error and the assessed risk were the same; however, in 89.7 percent of the sub-tasks, the estimated level of risk was the same in both methods. Correlation test showed that the correlation coefficient of error probability values between the two methods was 0.32, which indicated a moderate correlation in this regard. Additionally, the results of kappa statistical test for the estimated level of risk showed that there is a high agreement between Fuzzy SLIM and SLIM (P value <0.05).

The results of the study indicated meaningful agreement and a moderate correlation between Fuzzy SLIM and SLIM. Therefore, due to the relatively high accuracy of Fuzzy logic methods, and also the long steps of implementing the SLIM method, the Fuzzy SLIM method can be a good alternative to this method.

Due to uncertainties regarding the risks of engineered nanomaterials for human health and the environment, different organizations and researchers have developed various management frameworks and assessment tools to mitigate hazards during the procedures and applications of engineered nanomaterials. However, most of these techniques do not meet all the individual requirements. This study provides a review and introduction to the techniques developed for the management of safety, health, and environmental risks associated with engineered nanomaterials.

In order to find pertinent documents on the safe handling of engineered nanomaterials, a search was conducted using the following keywords: “Engineered nanomaterials”, “Framework”, “Tool”, “Risk management”, “Occupational exposure”, “Environment”, “Risk assessment”, and “Nanotechnology”. The search was conducted on various databases, including Scopus, Web of Science, NIOSH, ECHA, and ISO. Among the search results, tools and frameworks that specifically focus on the safety, health, and environmental risk management or assessment of engineered nanomaterials were selected.

Among the search results, 17 frameworks and 11 developments in the field of managing occupational, environmental, and toxicological risks associated with engineered nanomaterials were discussed. Various frameworks and tools for identifying, evaluating, and managing the potential risks of engineered nanomaterials vary in terms of their scope, goals, risk assessment approaches, and output, offering diverse applications.

Various tools and frameworks, each with unique properties, applications, and limitations, can assist organizations in achieving their goals related to safety, health, and environmental issues in the field of nanotechnology. Currently, there is no consensus on the optimal approach for assessing the risks of nanomaterials, underscoring the necessity for additional research, development, and collaboration in this field.

Lung cancer is the second most common cancer in the world. Smoking occupational and environmental exposures are the most important causes of lung cancer. Cadmium is known as a human carcinogen due to its ability to increase lung cancer risk. This study estimates the general results of all studies on the relationship between cadmium and lung cancer.

In the present study, studies that evaluated the relationship between cadmium and lung cancer until May 2022 were searched and retrieved. From the funnel plot to determine the existence of diffusion skew, from the statistical tests Chi-squared test (x2) and I2 to determine heterogeneity, from the meta-regression method to identify the root of heterogeneity, and from the sensitivity analysis approach to identify the effect of each study on the result, it was generally used. This study performed all analyses with Stata statistical software version 15.

In this study, it was observed that the chance of developing lung cancer compared to the base group, in the people exposed to a higher dose than the base level of cadmium is equal to 1.31 (95% CI: 1.06-1.62; p-value = 0.024), which is statistically significant. Based on Egger’s test (p-value = 0.178) and Begg’s (p-value = 0.276), no diffusion bias was observed in this study.

ccording to the final results of this review research, exposure to cadmium leads to a 31% increase in lung cancer risk, which is statistically significant. Therefore, cadmium is a risk factor for lung cancer.