Background: Work-related injuries data analysis helps the choice of measures to prevent accidents, therefore, the information and data of occupational injuries were analyzed to identify the overall trend of occupational injuries, and develop a forecasting model of lost workdays and provinces clustering.
Methods: To achieve the first goal, we calculated NFIR and FIR per 100000 workers and injury indices (including AFR, ASR, FSI, Safe T-Score, IR, MDR, and LTIR). To reach the second purpose, the FEE, FTE, FETE, and RE linear models and supervised machine learning alongside linear models (Random Forest, Extra trees, XG Boost, G Boost) were used. Finally, the AP clustering algorithm for provinces clustering, time series clustering (DTW method), and the KNN forecasting algorithm were applied. Data for 378826 occupational injuries, which occurred from 2001 to 2019, were extracted from the publications of the ISSO. Industries data were extracted from the Ministry of Industry publications.
Results: NFIR to FIR ratio ranged between 60 to 265.35 and injuries indices increase from 2001 to 2008 and then experienced a decline. In linear models, OLS and RE had the best performance in forecasting the loss days and the extra trees method had better performance as a blender than random forest method. The clustering results showed that Khuzestan, Markazi, Mazandaran, Qazvin, and Tehran provinces are in cluster 1 and other provinces are in cluster 2.
Conclusion: This study can be regarded to forecast occupational injuries and safety promotion planning.

Background: Welding workshops play a vital role in various industrial sectors and are associated with multiple hazards that can lead to occupational injuries and health issues. In many small-scale welding workshops, safety measures are often insufficient, increasing the likelihood of preventable accidents. This study focuses on assessing the risks present in a welding workshop using the William Fine risk assessment method to identify and prioritize potential hazards, as well as to propose and evaluate appropriate control measures.
Methods: The William Fine method was applied to evaluate risks based on their probability, exposure, and potential consequences. Data were collected through direct observations, interviews with workers, and analysis of workshop conditions. Risks were categorized and scored to determine their severity and prioritize mitigation measures.
Results: Our findings reveal that about 41% of the hazards were in the high category. Entanglement of workers’ hands/clothes, awkward posture, grindstone breakage, metal fume, and falling work pieces were in the high-risk category. The highest and lowest number of risks were related to the tasks of welding operation and connecting the electrode, respectively.
Conclusion: This study underscores the importance of risk assessment in welding workshops to mitigate occupational hazards. Applying the William Fine method provided a clear framework for identifying and addressing risks to enhance safety in small-scale welding operations. The findings emphasize the need for regulatory compliance, worker education, and investment in safety infrastructure to reduce accidents and promote a safer working environment. Furthermore, ergonomic principles and load-carrying techniques are crucial for mitigating risks in these workshops.

Background: Work related musculoskeletal disorders and exposure to thermal stress are considered as some of the most significant challenges for workers in the tire manufacturing industry, which can lead to decreased human performance and work capacity, as well as increased physical and psychological burden during the execution of tasks. Therefore, the aim of this study is to determine the simultaneous effects of thermal stress and postural stress on the occupational strain index of workers employed in a tire manufacturing company.
Methods: In this descriptive-analytical (cross-sectional) study, 147 individuals with at least one year of work experience were selected as the sample based on the inclusion criteria. Participants in the study were divided into three groups: the postural stress exposure group (n = 49), the group exposed simultaneously to thermal and postural stress (n = 49), and the control group (n = 49). For data collection, the Nordic questionnaire and a demographic questionnaire were used. Additionally, the REBA (Rapid Entire Body Assessment) observational method was utilized to determine the postural stress score, while the WBGT (Wet Bulb Globe Temperature) index was employed to assess the thermal stress of the workers. The occupational strain index was determined using JSI 2001 software, and statistical analyses were conducted using SPSS version 16.
Results: More than 60% of the production line workers at the tire company reported suffering from one or more musculoskeletal disorders in the past nine months. The average strain index in the first exposure group (postural stress exposure) was 32.80 ± 4.212, while in the second exposure group (simultaneous exposure to postural and thermal stress), it was 33.50 ± 2.801. According to the strain index standard, all individuals in the second exposure group and 90% of those in the first exposure group were classified as being at a dangerous level of risk. Additionally, a significant positive correlation was found between the strain index score and the REBA (Rapid Entire Body Assessment) score (r = 0.646), whereas no significant correlation was observed between the strain index and the WBGT (Wet Bulb Globe Temperature) index (p > 0.05).
Conclusion: In the tire manufacturing workers studied, the strain index level ranged from “moderate” to “high-risk strain levels”, with most reporting musculoskeletal disorders in the lower back and spine. There was a significant relationship between the strain index and the final REBA score, while no significant relationship was found between the strain index and the WBGT index.

Background: Computers are an essential part of daily life. However, their usage can lead to vision issues, such as Computer Vision Syndrome (CVS). Accordingly, this study examines the syndrome among employees of Sabzevar University of Medical Sciences and explores the factors contributing to its occurrence.
Methods: This study examined 86 employees from three areas: students, education, and research. It was descriptive and analytical. A validated questionnaire was used to gather data on demographics and CVS symptoms. Screen and room brightness were measured using a Hagner S4 photometer. Data analysis was performed using t-tests and descriptive statistics in Stata.
Results: Among the 86 employees, 51 were female and 35 were male. The majority of individuals affected by CVS aged between 30 and 40. Thirty-one employees exhibited early signs of CVS, with the highest prevalence seen in the research department (46.15%). Gender was the sole contributing variable, with a higher prevalence among women (p = 0.035). The overall prevalence of CVS was 34.88%.
Conclusion: CVS is a prevalent syndrome among employees. Furthermore, female employees displayed a higher prevalence of CVS. To improve employee well-being and performance, ergonomic training and visual exercises should be trained and implemented in the workplaces.

Background: Usability, as defined by ISO 9241-11, refers to the extent to which a system can be used effectively, efficiently, and with satisfaction in a specified context. Web-based academic research management platforms require high usability to ensure user satisfaction and productivity. This study aimed to evaluate the usability of the Integrated Research Automation System (Syat) at Mazandaran University of Medical Sciences. To the best of our knowledge, this study is among the first to systematically assess the usability of the Syat system in a medical academic setting.
Methods: A cross-sectional, descriptive-analytical study was conducted among 130 faculty members who had used Syat at least five times for research-related activities. Six primary tasks were assessed: registering a thesis as a research project, granting and restricting student access to theses, submitting evaluations, editing thesis information, and overall system interaction. Effectiveness was measured by error rates, efficiency by task completion time, and satisfaction by the System Usability Scale (SUS). Statistical analysis included descriptive statistics, one-way ANOVA with Bonferroni post-hoc tests, and chi-square tests for associations between demographic factors and error rates.
Results: The proportion of error-free performance ranged from 57.0% to 64.7%, with “Restrict Access” being the most error-prone (mean errors = 0.57). Task completion times varied significantly (F(5,1414) = 12.091, p < 0.001), with “Submit Evaluation” being the longest (mean = 79.80 s). SUS scores were low across all tasks (overall mean = 28.86), far below the benchmark of 68. Gender, education level, and work experience had a significant influence on error rates (p < 0.05).
Conclusion: Although Syat allows task completion, low satisfaction and efficiency issues indicate the need for interface simplification, targeted training for less experienced users, and iterative user-centered design improvements.

  Background: Prolonged exposure to work-related stressors in office environments can elevate physiological indicators such as blood pressure and heart rate. While music has been shown to reduce stress, it may interfere with cognitive performance. Colored noises—such as white, pink, and violet—are emerging as potential alternatives for promoting relaxation without compromising concentration. This study aimed to evaluate the effects of exposure to three types of colored noise (white, pink, and violet) on systolic and diastolic blood pressure and heart rate among healthy office workers.

  Methods: This experimental research was conducted in 2024 on 43 office employees without a history of cardiovascular disease to evaluate the effects of 4 colored noises on blood pressure and heart rate. Participants were exposed to each noise type at 65 dB for 30 minutes on separate days. Baseline and post-exposure measurements of blood pressure and heart rate were recorded and analyzed by ANNOVA Test by SPSS-27. The ambient noise level of the testing room was 44.8 dB.

  Results: The findings showed that both systolic and diastolic blood pressure significantly decreased only after exposure to pink noise (p < 0.05). Although the heart rate also decreased following exposure to pink noise, the reduction was not statistically significant. No significant changes in blood pressure or heart rate were observed after exposure to white or violet noise.

  Conclusion: Exposure to colored noise, particularly pink noise, may help reduce physiological stress responses such as elevated heart rate and diastolic blood pressure in healthy office workers. These findings support the potential use of colored noise as a simple, non-invasive intervention for stress management in workplace settings.

  Keywords: Stress, Blood Pressure, Heart Rate, White Noise, Pink Noise, Violet Noise

Background: Occupational Health and Safety deals with hazards in the workplace through Anticipation, Recognition, Evaluation, and Control (AREC). Modern workplaces are given considerable digital makeovers, trying to integrate AI, IoT, robotics, and VR/AR, which from a wide perspective really distort OHS approaches in their being. These technologies put forth expectations of miraculous improvements but also pose newer risks.
Methods: A narrative review was conducted to systematically examine the changes brought by AI and digitalization to the OHS missions. Searches were made through PubMed, Scopus and the Web of Science, while Google was also used to retrieve organizational reports. Information was grouped and analyzed within the AREC framework, detailing the newest achievements as well as challenges.
Results: Exoskeletons prevent musculoskeletal injuries; UAVs inspect inaccessible areas; IoT enables real-time monitoring; VR/AR offers immersive training and hazard recognition; AI and robots predict hazards and automate dangerous tasks; and advanced technologies improve OHS across AREC. However, in addition to new physical risks from human-machine interaction, this adoption brings with it cybersecurity threats, data privacy issues, the possibility of job displacement, the risk that an over-reliance on technology will erode human skills, and complex ethical implications.
Conclusion: In conclusion, digitalization has revolutionary OHS benefits, but it also necessitates a worker-centered, ethical, and balanced approach. Companies need to make training investments, make sure that data is used ethically, conduct in-depth risk assessments, and promote ongoing development. To guarantee safe, and efficient technology integration, policymakers and researchers play a critical role in revising laws, creating ethical frameworks, and examining long-term impacts.

Background: Given the increasing prevalence of modern artificial light sources and electronic displays in work environments, exposure to blue light has emerged as a significant environmental factor. Moreover, studies have demonstrated that blue light contributes to enhanced alertness and the improvement of cognitive functions, including selective attention.
Methods: This narrative review was conducted with the aim of providing a synthesis of the existing scientific literature on the effects of blue-enriched light on selective attention. The study commenced with a search of PubMed, Web of Science, Scopus, and SID databases. The search was conducted by utilizing “blue light” or “short-wavelength light” and “attention” or “alertness” keywords from 2010 to June 2025.
Results: By outlining the underlying physiological and neural mechanisms—particularly the role of ipRGCs and the melanopsin pigment—this study illustrates how blue light influences circadian rhythms, alertness, and cognitive performance. Empirical evidence consistently indicates that blue light can enhance alertness, reaction time, and performance on specific cognitive tasks such as working memory and sustained attention. However, its effects on memory and sleep remain variable, and inappropriate exposure, particularly during nighttime, may disrupt circadian rhythms and lead to adverse health outcomes.
Conclusion: The strategic management of blue-enriched light in occupational environments holds potential for enhancing selective attention, improving overall cognitive performance, and contributing to a safer, more productive, and healthier workforce. Realizing this potential requires rigorous and ongoing scientific research, along with a comprehensive approach to workplace lighting that integrates both visual and non-visual biological considerations.