Journal of Health and Safety at Work

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Introduction: Wearable thermal management systems and phase change materials (PCMs) have emerged as effective solutions for regulating body temperature and storing thermal energy. This study focuses on synthesizing and thermal optimizing a sodium sulfate decahydrate-based nanocomposite incorporating various nanoparticles to improve its performance for personal thermal regulation applications.
Material and Methods: The composite was prepared using sodium sulfate decahydrate as the base PCM. Potassium chloride (KCl) was added to adjust the melting point, borax (STD) served as a nucleating agent, and sodium polyacrylate (SPA) was included as a thickening agent to suppress phase separation. To evaluate the effect of nanoparticle additives, 0.05 wt.% of aluminum oxide (Al₂O₃), iron oxide (Fe₂O₃), graphene oxide (GO), and titanium dioxide (TiO₂) were separately incorporated into the base formulation. A field emission scanning electron microscope (FESEM) was used to analyze the surface morphology of the resulting nanocomposites. Differential scanning calorimetry (DSC) assessed thermal properties, including phase transition temperatures (melting and freezing points) and latent heat.
Results: Differential scanning calorimetry (DSC) analysis indicated that sample S-5-5 comprising sodium sulfate decahydrate with 3 wt.% KCl, 5 wt.% STD and SPA exhibited a melting temperature of 29.5 °C and a latent heat of 120 J/g. This composition remained stable without phase separation. The incorporation of nanoparticles raised the melting point of the base PCM by 0.6 to 1.72 °C. Aluminum oxide (Al₂O₃) and iron oxide (Fe₂O₃) reduced the latent heat of fusion, whereas GO and TiO₂ increased it.
Conclusion: These findings confirm that the thermal properties of sodium sulfate decahydrate-based PCMs can be tailored by including specific additives and nanoparticles. Hydrated salt nanocomposites demonstrate strong potential as PCMs for wearable body temperature regulation.

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Introduction: Measuring and monitoring the process safety management system is essential to reduce the risk of accidents in process industries. For this purpose, lagging and leading process safety performance indicators are utilized. The aim of the present study is to select, validate and prioritize the leading indicators of process safety performance.
Material and Methods: First, the leading indicators associated with risk factors affecting hydrocarbon liquid tanks were identified and selected based on the guidelines provided by the CCPS, HSE UK, OGP, and relevant scholarly articles. After choosing the appropriate indicators, the content validity of the indicators was studied. In the next step, indicators with acceptable content validity were studied by experts in terms of applicability and importance using fuzzy weighting.   
Results: Out of 18 performance indicators related to risk factors influencing the performance of operating personnel, 3 indicators were eliminated due to content validity ratio (CVR) and content validity index (CVI) scores below acceptable levels. The remaining 15 indicators advanced to the next stage of the study. All 4 indicators related to the performance of maintenance personnel achieved acceptable CVR and CVI scores and were also included in the next stage. Of the 13 indicators defined for equipment performance, 3 were excluded due to low CVR or CVI scores, and 10 progressed to the subsequent phase. For firefighters, 9 indicators were identified, of which 2 were eliminated due to low CVR or CVI, and 7 advanced to the next stage. In this stage, all 36 indicators achieved acceptable applicability scores and were subsequently weighted.
Conclusion: The 36 final indicators presented in this study can be used to measure process safety performance in the oil industry. Although the present study was a case study on liquid hydrocarbon tanks, most of the indicators presented can be applied to other sectors of the oil industry. In addition, the weights specified for each of these indicators can be used to prioritize the indicators. 

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Introduction: The rising daily consumption of gasoline has increased human exposure to its vapors. Direct contact with these vapors, due to their toxic properties, can adversely affect various organs, including the heart, lungs, skin, liver, and kidneys. Cinnamon, a widely utilized medicinal plant, is rich in antioxidants and exhibits protective effects on liver and kidney health, alongside therapeutic potential for various diseases. Therefore, this animal study aimed to investigate the protective effects of cinnamon extract against oxidative stress induced by gasoline inhalation in rat kidneys.
Material and Methods: Thirty adult male Wistar rats weighing 160–180 grams were randomly divided into five groups (n=6 per group): (1) Control, (2) Cinnamon extract only, (3) Gasoline exposure only, (4) Gasoline exposure plus 100 mg/kg of cinnamon extract, and (5) Gasoline exposure plus 200 mg/kg of cinnamon extract. After four weeks of exposure, the rats were weighed and euthanized. Serum samples were collected for biochemical, serological, and enzymatic analysis, and kidney tissues were examined for histopathological changes.
Results: Gasoline exposure significantly increased kidney function markers (BUN and cystatin C) and oxidative stress markers (MDA) while reducing endogenous antioxidant activities (GSH and GPx). Histopathological analysis revealed significant kidney damage, including hemorrhage, necrosis, and tubular degeneration in the gasoline-exposed group. Cinnamon extract notably alleviated gasoline-induced kidney toxicity by reducing kidney function markers and MDA levels while enhancing endogenous antioxidant activity. Histopathological findings further confirmed the protective effects of cinnamon extract, showing reduced tissue damage in treated groups.
Conclusion: Cinnamon extract significantly reduces kidney toxicity caused by gasoline, suggesting it may protect against gasoline exposure. Its antioxidant and anti-inflammatory properties likely support this protective effect.

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Introduction: Using leading indicators to determine organizations’ ability and willingness to learn from safety-related events can significantly enhance occupational health and safety management systems and help prevent future incidents.
Material and Methods: This study aimed to assess the psychometric properties of the Persian version of the propensity to learn from experiences related to safety events questionnaire, among 352 operators and managers (92% response rate), using quantitative and qualitative techniques to assess face and content validity, construct validity, and reliability coefficients.
Results: Out of 49 items in the questionnaires, 48 demonstrated acceptable levels of face and content validity, with content validity indices ranging from 0.80 to 1. Reliability scores assessed through internal consistency (Cronbach’s alpha) and intraclass correlation coefficients were reported as 0.80 and 0.95 for the operators’ questionnaire and 0.95 and 0.92 for the managers’ questionnaire, all deemed acceptable. Confirmatory factor analysis indicated that both measurement models for operators and managers, comprising 12 dimensions each, exhibited strong construct validity. Notably, the operators’ measurement model, supported by a larger sample size of 271 compared to 81 for managers, yielded superior results in terms of parsimonious and adaptive fit indices.
Conclusion: The Persian version of learning from experiences related to safety events questionnaire is a valid and reliable instrument for identifying learning weaknesses at both individual and organizational levels and can be utilized as a leading indicator to enhance safety culture and event’s learning processes.

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Introduction: Nanomaterials are widely applied across diverse scientific and industrial sectors; however, their emergence has introduced a new generation of occupational hazards for workers. Concurrent with discussions on the adverse effects of nanomaterials on human health, researchers have sought to develop methods for assessing occupational risks associated with these materials. Accordingly, this study aims to propose a general framework for the development of such methods.
Material and Methods: This is a critical analysis study designed to evaluate existing methods for assessing occupational risks related to nanomaterials and ultimately propose a modified framework for refining these methods. By examining current approaches and identifying their strengths and weaknesses, the authors have proposed an improved framework for occupational risk assessment of nanomaterials.
Results: The proposed framework is based on two key dimensions: “Severity/Hazard” and “Probability/Exposure.” The first dimension determines the potential risk level arising from exposure to nanomaterials, with the most critical factors being the intrinsic properties and toxicology of the nanomaterial itself, parent materials, and similar substances. The second dimension describes the likelihood and nature of exposure to nanomaterials during work activities, with the most influential factors being worker, job tasks, and workplace environment characteristics.
Conclusion: The lack of sufficient data and numerous uncertainties regarding bio-nano interactions make quantitative risk assessment (the traditional occupational health approach) difficult, less reliable, and in some cases unfeasible for nanomaterials—given current knowledge. Qualitative and semi-quantitative approaches, such as Control Banding, despite demonstrating positive aspects, have faced significant criticism. The framework-based method proposed herein appears capable of partially overcoming these challenges.

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Introduction: Nowadays, in order to improve the level of Health, Safety and Environment (HSE) culture of employees, organizations have reached this important conclusion that the weaknesses and strengths of the system should be identified by periodically evaluating the level of HSE culture. On the other hand, Although the social exchange relationships between employers and employees are increasingly important to the performance of safety management systems, the interaction between psychological aspects, workplace safety and its relationship with employees’ HSE citizenship behavior have been less studied. The aim of the present study was to investigate the effect of psychological contract of HSE on the relationship between HSE culture and HSE citizenship behavior among employees in a steel manufacturing industry. 
Material and Methods: In the present study, three questionnaires: Psychological contract of HSE, HSE citizenship behavior and HSE culture were used; the reliability and validity of these questionnaires approved in past studies. The questionnaires were randomly distributed to 434 employees of a steel industry. In order to model structural equations, Smart PLS software was used, the reliability and validity of the models were investigated.
Results: The results of the study showed that HSE culture is a significant predictor of HSE citizenship behavior (P-value<0.001). HSE culture has a positive and significant effect on psychological contract (P-value <0.001), and psychological contract has a mediating role in the relationship between HSE culture and HSE citizenship behavior.
Conclusion: The results of the present study showed that HSE culture and psychological contract directly affect HSE citizenship behavior. Also, based on the findings of this study, HSE culture, in addition to directly affecting HSE citizenship behavior, can also affect HSE citizenship behavior by affecting psychological contract as a mediating variable. 

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Introduction: Demographic changes are an inevitable phenomenon in today’s organizations. By acknowledging the aging of the workforce as a significant organizational challenge, the purpose of this research is to design a structural model of elderly-oriented human resource management measures in public organizations.
Material and Methods: This study is categorized as applied in terms of objective, descriptive-survey in terms of approach, and a mixed-method design (qualitative-quantitative) in terms of data collection. The information gathering tools used to review the research literature were library research methods, while a questionnaire was employed for collecting field data. Initially, the Delphi method was utilized to extract and identify elderly-oriented human resource management practices. In the second phase, a quantitative method was used to validate the model of elderly-oriented practices in public organizations and assess the current status of these practices.
Results: The results obtained from the model’s goodness-of-fit in SmartPls 3 software and confirmatory factor analysis indicated high validity of the elderly-oriented human resource management practice model.
Conclusion: Additionally, the findings revealed that, from the perspective of the study’s employees, the status of elderly-oriented human resource management practices in terms of implementation was not in a desirable state and did not meet employees’ expectations.

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Introduction: With the advancement of industries and increased use of metalworking fluids, controlling pollutants generated by machining operations has become increasingly challenging. This study aimed to address these challenges by designing an air filtration system designed specifically for this purpose.
Material and Methods: A local exhaust ventilation system was developed based on the VS-80-12 ACGIH standard, tailored to the working conditions and air sampling of the environment. The filtration system includes an aluminum pre-filter, an E11 class filter, and a nanofiber filter incorporating a metal-organic framework. The performance of the system was evaluated by measuring the numerical concentration of particles and the mass concentration of oil mist at both the inlet and outlet. The results were then compared to those obtained from an E1 class filter.
Results: The results obtained from XRD and FTIR analyses showed that ZIF-8 had high crystallinity and was successfully incorporated into the structure of the fibrous media filter containing metal-organic framework. The evaluation revealed that the filtration system effectively removed pollutant particles at their source. Notably, the initial efficiency for larger particles reached 100%, while the average removal efficiency for particles smaller than 2.5 microns was 99%.  
Conclusion: In conclusion, the combination of nanofiber filters with a metal-organic framework and aluminum pre-filters presents an effective solution for controlling particulate pollutants from machining operations. However, further research is necessary to comprehensively assess the system’s performance, particularly regarding dust loading capacity. Future studies should also explore the effects of various factors, such as airflow rate and the type of metalworking fluid, on the system’s efficacy.

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Introduction: Relief work is inherently associated with various stress-inducing factors due to the nature of the profession. Among relief-related professions, firefighters, due to the responsibilities related to firefighting and safety services, are exposed to various physical and chemical hazards. Therefore, the primary aim of this research was to compare the effect and practice retention, central and operational and skill-based stability over the balance of the firefighters with and without firefighting and rescue clothing and Hazardous Materials.
Material and Methods: The statistical population consisted of 5500 firefighters from the city of Tehran. As for the intervention, in the first group, central stability exercises, and in the second group, operational and skill-based exercises were performed by the firefighters during their shift days for a period of 6 weeks. The balance of the firefighters in both groups was measured at three stages: at the beginning of the intervention, immediately after the 6-week training period, and one month after the end of the training. The “Y Balance” board was used to assess the firefighters’ balance. Data analysis was performed using repeated measures analysis of variance and the Bonferroni post hoc test at a 5% significance level, using version 26 of the SPSS software.
Results: According to the results of this study, the balance of firefighters in both the right and left legs was significantly greater in the operational and skill-based training group compared to the central stability training group, both immediately after training and one month later (p < 0.05). With performing operational and skill-based training, right leg balance in the rescue suit was significantly higher than in the fire protection and hazmat suits (p < 0.05), while there was no significant difference between the fire protection and hazmat suits (p > 0.05). Left leg balance in the rescue suit was significantly higher than in both the fire protection and hazmat suits, and balance in the fire protection suit was significantly higher than in the hazmat suit (p < 0.05). Additionally, firefighters’ balance significantly improved after balance training (p < 0.05), and there was no significant difference between the balance measured one month after training and immediately after training (p > 0.05).
Conclusion: In addition to the fact that core stability exercises particularly task specific functional training are effective in improving balance and preventing injuries, the retention of these effects over time should be taken into account.

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Introduction: Fumigant gases in maritime and container chains, along with occupational noise in marine and manufacturing industries, are among the most significant chronic risk factors. They are usually assessed separately, despite their simultaneous impact on workers’ health. The importance of this study lies in presenting an integrated approach for real-time monitoring of combined risk and aligning it with occupational exposure limits (OELs). The aim is to develop and validate an interpretable, regulation-oriented framework for predicting combined risk.
Material and Methods: This research integrated and normalized data from the Global Burden of Disease (GBD) 2021 study including age-standardized disability rates (ASDR) and average annual percentage change (AAPC) for 204 countries with occupational exposure limit tables for fumigants. A Sugeno-type fuzzy inference system with three inputs and four rules was designed. Weights and membership function boundaries were optimized using the Prairie Dog Optimization algorithm, and a threshold-based scenario generation module was applied to produce high-risk synthetic data. Model performance was evaluated through an OEL compliance test.
Results: Findings revealed that the proposed optimization reduced the loss function by 42% compared to random search. The mean absolute error (0.028 ± 0.006) and root mean square error (0.041) were obtained. Threshold-based scenario generation improved data coverage in high-risk regions from 0.62 to 0.90 and increased the accuracy of critical condition detection from 0.71 to 0.89. The OEL compliance index reached 0.93, confirming input weighting as the most influential factor.
Conclusion: The proposed framework simultaneously ensures numerical accuracy, interpretability, and regulatory compliance with occupational exposure limits. It can be deployed within real-time monitoring dashboards for ports and factories. Future research should integrate IoT sensors and multi-objective optimization to enable dynamic updates in response to evolving regulations and operational conditions.

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Introduction: Transporting hazardous materials is inherently associated with multiple risks that can threaten human health, the environment, property and infrastructure. The deployment and operation of ammonia tanks in various industrial projects and organizations with diverse objectives present serious safety, health and environmental challenges. Therefore, conducting risk assessment in the chemical sector is essential. This study aimed to evaluate the effectiveness of a pressure sensor in reducing the risk of ammonia cargo release during road transportation, based on Quantitative Risk Assessment (QRA) in a petrochemical transport company.
Material and Methods: This study assessed the risk of ammonia release from a pressurized tanker and investigated the risk-reducing effects of employing a pressure sensor for leak prediction. Consequence modeling and QRA were conducted using SAFETI version 9.
Results: The results showed that the installation of a pressure sensor on the ammonia tanker reduced the gas release duration from 40 to 25 minutes, which consequently decreased the volume of the leaked gas and ultimately reduced the overall risk level of accidents. This risk reduction varied between 55% and 99% under different atmospheric conditions. By decreasing the release time from 40 to 25 minutes, the lethal radius of ammonia was consistently reduced in all weather conditions. The analysis of individual risk contours in the sudden rupture scenario revealed that atmospheric conditions, particularly during winter nights, had the greatest impact on the expansion of lethal zones.
Conclusion: The use of pressure sensors and alert systems can effectively reduce individual risk level. Continuous monitoring of tank conditions and prompt alerts in the event of leaks or pressure drops enable faster response and help prevent escalation of accident consequences.

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Introduction: Fire risk assessment in oil storage tanks faces challenges due to incomplete, conflicting, and uncertain data, particularly when empirical evidence is limited. Traditional point-based likelihood estimates often fail to capture expert doubt and epistemic uncertainty. This study aims to develop and evaluate a novel hybrid framework combining Dempster-Shafer Theory (DST) and Bayesian Networks (BN) to improve the trustworthiness of fire risk prediction in such industrial settings.
Material and Methods: The proposed approach integrates DST to model expert uncertainty through interval probabilities (Bel–Pl) and BN to dynamically update causal relationships as new information appears. The study implements computational coding to enable DST calculations for five expert opinions across 243 scenarios, overcoming prior limitations in multi-expert modeling due to computational complexity.
Results: The hybrid DST-BN framework demonstrated superior ability to incorporate incomplete and conflicting expert data, reducing overconfidence linked to point estimates. Interval probabilities offered more trustworthy representations of epistemic uncertainty, while BN integration allowed traceable and adaptable causal modeling. The computational solution facilitated practical application of DST with multiple experts, enhancing the strength of the risk assessment.
Conclusion: This research provides an effective DST-BN hybrid methodology for assessing fire risk in fixed-roof oil tanks, improving accuracy and trustworthiness in complex industrial environments. By addressing the shortcomings of point-based methods and enabling multi-expert participation, the framework supports clearer and more defensible probabilistic inferences. Future work may focus on integrating real-time sensor data and AI-based decision systems to further strengthen dynamic risk assessment capabilities.
 

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Introduction: Workplace noise is one of the main sources of health problems. Noise can have many direct and indirect effects that threaten human health in various ways. The aim of this study was to investigate the effect of noise annoyance on anxiety among workers.
Material and Methods: This study included 60 workers from a carton manufacturing company, who were divided into two groups based on noise exposure: exposure (noise level more than 85 dB) and control (noise level less than 85 dB). Noise exposure of the individuals at the workplace was measured in accordance with ISO 9612:2009 standard and using a TES-1354 dosimeter. Anxiety levels were assessed using the Spielberger Anxiety Inventory (STAI), and noise annoyance was measured using a 100-point visual analog scale. Statistical analysis was performed using STATA statistical software. 
Results: The mean age and work experience of the study subjects were 35.78 and 10.78 years, respectively. The results indicated a statistically significant difference (P-value < 0.05) in the mean noise annoyance scores between the groups. The mean noise annoyance score in the exposed group was significantly higher (88.03) than in the non-exposed group (47.6). The average anxiety scores in the exposure and control groups were 106.81 and 101.6, respectively. In addition, regression analysis showed that each unit increase in noise annoyance level resulted in a 1.08-fold increase in anxiety in the exposed group.
Conclusion: Noise annoyance is often the most common psychological response to noise exposure and can be a predictor of many mental disorders or illnesses, including anxiety. Therefore, it is important to implement control measures to reduce noise exposure in the workplace.

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Introduction: Commercial trucking is one of the most challenging occupations, with long work hours, short rest periods, and substantial psychological pressures that contribute to fatigue and deterioration at work. Since regular physical activity is one of the pillars of healthy life and can improve physical and mental functioning, the present study investigated the relationship between physical activity and driver performance with occupational fatigue as a possible mediator.
Material and Methods: The study population was intercity commercial truck drivers in several cities of Razavi Khorasan Province. Using Green’s formula, we calculated a sample size of 140 participants. Data were collected with the Swedish Occupational Fatigue Inventory, the Sharkey Physical Activity Questionnaire, and the Driver Performance Questionnaire (unsafe behaviors). Statistical analyses included Pearson correlation coefficients and multiple regression analyses.
Results: Our results showed a significant positive correlation between occupational fatigue and driver performance problems (P=0.001). Both the correlation between physical activity and work fatigue, and the correlation between physical activity and driver performance were significant negative correlations (P=0.001). In addition, the indirect link between physical activity and driver performance via occupational fatigue was also significantly negative (P=0.001).
Conclusion: Based on our research results, enhanced physical activity contributes to enhanced driver performance (decreased unsafe behaviors) of commercial truck operators, directly and indirectly through decreased occupational fatigue. This study provides scientific evidence for the development of safety policy in the transportation industry of Iran.

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Introduction: Job factors play a critical role in shaping employee health and mitigating burnout. Work-family conflict leads to outcomes such as burnout, emotional exhaustion, and decreased performance. Similarly, employees’ perception of job insecurity can negatively affect their burnout, work attitudes, well-being, commitment, and interpersonal relationships. This study investigates the interplay between job security, work-family conflict, and burnout, with a focus on the mediating role of work engagement among office workers.
Material and Methods: This cross-sectional study was conducted in 2024, collecting data from 119 employees in administrative units at a medical university in Iran. Structural equation modeling was employed for data analysis. The measurement tools included standardized questionnaires for work engagement, work-family conflict, job security, and job burnout. The questionnaires were utilized based on a Likert scale, with confirmed validity and reliability.
Results: The findings from the correlation analysis indicated that job security had a significant positive relationship with work engagement. In contrast, burnout showed a negative correlation with job security and work engagement, while it had a positive correlation with work-family conflict. Results from the structural equation modeling revealed that work-family conflict had a direct relationship with burnout but did not significantly affect work engagement. Work engagement acted as a protective factor in reducing burnout and served as a mediator between job security and burnout; however, its mediating role between work-family conflict and burnout was not confirmed.
Conclusion: Numerous factors impact the psychological health of administrative employees. Organizations should tailor their interventions based on these factors and their interrelations. Overall, employee empowerment programs aimed at increasing work engagement and reducing work-family conflict can enhance the quality of working life and decrease burnout within organizations.
 

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Introduction: Occupational exposure to volatile organic compounds (BTEX) and heavy metals in industrial settings poses significant health concerns. These substances may lead to toxic, carcinogenic, and hematobiochemical effects. This study aimed to assess the health risks associated with exposure to these pollutants in a power equipment manufacturing industry over a 10-year period and to compare the accuracy of quantitative (USEPA) and semi-quantitative (Singapore) risk assessment methods.
Material and Methods: This cross-sectional study was conducted across six occupational groups. Personal air sampling of BTEX and heavy metals was performed according to NIOSH protocols. Carcinogenic and non-carcinogenic risks were estimated using the USEPA method and the Singapore semi-quantitative approach. Additionally, hematological and biochemical indicators of exposed workers were analyzed.
Results: Nickel had the highest cancer risk, and the highest hazard quotient (HQ) values were related to xylene, benzene, and nickel. While the semi-quantitative method classified most risks as negligible to low, the USEPA method identified several cases with definite health risks. Significant effects were observed on SGOT, SGPT, fasting blood sugar, creatinine, and blood pressure among exposed groups.
Conclusion: The USEPA method demonstrated higher sensitivity and reliability in identifying occupational chemical hazards and should be prioritized in future assessments. Furthermore, the findings underscore the importance of preventive measures to reduce chronic exposure to BTEX and heavy metals in similar industrial settings.

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Introduction: Unsafe acts are one of the main causes of workplace accidents. Given the critical role of the steel industry in our country, and the limited research on human factors, and the importance of identifying the contributors to accidents, this study was conducted with the aim of identifying human factors influencing accidents and unsafe behaviors using the Human Factors Analysis and Classification System (HFACS). The identified factors were then prioritized using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP) methods. Based on the results, appropriate recommendations were proposed for the prevention of accidents and the reduction of unsafe acts.
Material and Methods: This descriptive-analytical study was carried out in the rebar production unit of a steel manufacturing plant. Among 35 recorded accidents over the past two years, 28 were related to the rebar production unit. Data were collected through review of accident reports, seven on-site observations during high-risk shifts, and interviews with employees. After analyzing the occupational accidents, the rebar production process in the rolling unit was identified as a high-risk area. The HFACS checklist was used to assess this process and classify the human factors contributing to accidents. Subsequently, DEMATEL and ANP methods were applied to determine causal relationships and prioritize the factors.
Results: The HFACS analysis identified 236 human factors, among which the preconditions for unsafe acts and organizational factors had the highest frequency (24.57% each), while external factors had the lowest (8.47%). According to DEMATEL results, organizational influences exerted the greatest impact on other levels, whereas external factors had the least effect. In terms of being influenced by other levels, unsafe acts showed the highest level of susceptibility, whereas unsafe supervision had the lowest levels. Based on ANP findings, the preconditions for unsafe acts had the highest importance, while unsafe supervision had the lowest in contributing to unsafe acts.
Conclusion: The findings of this study suggest that improving safety culture, improving organizational regulations, implementing targeted training programs, and updating equipment can play a significant role in reducing accidents caused by unsafe acts. The results provide practical insights for managers and policymakers and can serve as a useful tool for decision-making in occupational health and safety within the steel industry.

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Introduction: Work-family conflict can lead to negative outcomes such as psychological distress in all employees, especially female nurses, as they face unique occupational challenges. However, the specific aspect of work-family conflict that contributes most significantly to psychological distress, as well as the underlying mechanisms involved, has not been thoroughly examined. The present study aimed to investigate the relationship between work-family conflict dimensions and psychological distress.
Material and Methods: This descriptive-analytical study was conducted in 2022 on 277 female nurses employed at public hospitals in Bushehr Province. The data collection tool consisted of work–family conflict and psychological distress questionnaires. The data were analyzed using SPSS v. 19 and PLS Graph v. 3, with path analysis.
Results: The direct effects of two dimensions of work-family conflict, namely “the interference of work with personal and family life” and “the interference of family life with work,” on psychological distress were found to be statistically significant (p < 0.05). In addition, the mediating effect of the “work interference with personal and family life” on the relationship between “insufficient facilities and support” and psychological distress was statistically significant (p < 0.05). Meanwhile, the mediating effect of the “family dissatisfaction” in the relationship between “the interference of work with personal and family life” and psychological distress was not statistically significant (p > 0.05).
Conclusion: The interference of work with personal and family life, and the interference of family life with work, were identified as significant factors that directly affect psychological distress. In addition, “insufficient support and facilities” can increase “the interference of work with personal and family life”, thereby leading to greater psychological distress among female nurses. Planning to enhance support measures in both the workplace and personal life can help reduce the negative consequences of work-family conflict, such as psychological distress in female nurses. 

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Introduction: Students play a key role in shaping the future of any society and spend a significant amount of time in educational environments. Creating an optimal learning environment requires close attention to factors affecting student well-being, particularly thermal comfort and indoor air quality. This study aims to systematically review the existing literature on thermal comfort and ventilation systems in schools.
Material and Methods: This systematic review was conducted based on the Cochrane methodology, involving a comprehensive search of three major databases — Scopus, Web of Science, and PubMed — for articles published between 2020 and 2024. The inclusion criteria encompassed peer-reviewed, conference, and review articles published in English that included the keywords “thermal comfort,” “ventilation,” and “school” in their title, abstract, or keywords. Studies focusing on preschools, universities, or other non-primary/secondary educational settings, as well as those conducted during the COVID-19 pandemic, were excluded.
Results: A total of 42 articles were selected after a rigorous screening process. The highest number of publications was reported in 2023. Key findings included: Most studies focused on elementary and secondary schools. The majority of research was conducted during the summer season, which may limit generalizability across seasons. There was considerable variation in CO₂ levels, with some exceeding recommended standards. In simulation studies, DesignBuilder and EnergyPlus were the most frequently used software tools. Additionally, results showed that: Indoor air quality and thermal comfort are significantly influenced by the type of ventilation system. Schools using natural ventilation often experienced higher CO₂ concentrations and lower thermal comfort than recommended. Implementation of Demand-Controlled Ventilation (DCV) has shown promise in improving indoor air quality and reducing pollutant levels.
Conclusion: This paper can contribute to the improvement of educational space design, enhancement of student learning, and promotion of indoor environmental health. It also provides insights into the latest methods for measuring and simulating thermal comfort and indoor air quality. For more practical outcomes, long-term studies with larger sample sizes across different seasons and times of day are needed. Combining computer simulations with real-world measurements can support cost-effective and optimized design of educational spaces. Future research should focus on standardizing temperature, humidity, CO₂ levels, and selecting the most appropriate ventilation strategies for classrooms.
 

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Introduction: Artificial Intelligence (AI) and digitalization are pivotal in enhancing Occupational Health and Safety (OHS), reducing workplace accidents, improving conditions, and boosting organizational productivity. This study examines the impacts, challenges, and opportunities of these technologies in workplace safety.  
Material and Methods: A narrative review was conducted via databases (Google Scholar, PubMed, IEEE Xplore, ScienceDirect) using keywords like “AI in occupational safety” (2013–January 2025). After screening 125 articles, 71 met the inclusion criteria (Persian or English publications). Qualitative content analysis identified key challenges and opportunities.  
Results: Artificial intelligence has been used in predicting incidents, monitoring, process optimization, and analyzing OHS challenges. By analyzing historical data and hazard patterns, AI enables proactive risk mitigation. Continuous learning in AI models enhances predictive accuracy and environmental adaptability. However, data quality issues persist; techniques such as transfer learning offer potential solutions. AI-driven automation reduces human error, yet challenges include ethical concerns and infrastructure gaps.
Conclusion: AI and digital technologies are transforming OHS through predictive analytics and real-time surveillance. To fully leverage these benefits, future efforts must focus on addressing data quality issues, establishing robust ethical frameworks, and developing advanced infrastructure. Further research is essential for the practical implementation of AI in a variety of work environments.