Farnaz Asghari, Rasoul Hemmatjou, Abolfazl Ghahramani,
Volume 15, Issue 3 (10-2025)
Abstract
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.
Hakimeh Vahedparast, Sedigheh Peykar, Farahnaz Kamali, ,
Volume 15, Issue 3 (10-2025)
Abstract
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.
Fatemeh Paridokht, Akram Tabrizi, Yaser Khorshidi Behzadi, Somayeh Farhang Dehghan,
Volume 15, Issue 3 (10-2025)
Abstract
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.
Roghayeh Esmali, Elham Akhlaghi Pirposhteh, Ali Askari, Mohsen Poursadeghiyan,
Volume 15, Issue 3 (10-2025)
Abstract
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.
