International Journal of Occupational Safety and Ergonomics最新文献

Objectives. Occupational exposure to heavy metals has emerged as a significant public health threat. These metals can induce oxidative stress, a significant risk for green space workers due to frequent exposure to air pollutants in urban areas. Even with these high-risk levels, exposure to heavy metals among this group is understudied. The objective of this study is to investigate the impact of exposure to nickel (Ni), lead (Pb) and manganese (Mn) on oxidative stress among these workers. Methods. Air samples were taken from 88 male participants for Ni, Pb and Mn analysis using NIOSH-7300. Urine samples were taken for heavy metal and 8-hydroxy-2^'-deoxyguanosine (8-OHDG) biomonitoring. Results. The exposed population of green space workers showed significantly elevated levels of airborne Ni and Pb (p ≤ 0.001) and urinary Mn and Ni (p ≤ 0.001) compared with a control group of office workers. The exposed population also had elevated urinary 8-OHDG levels, indicating increased oxidative stress. The strong correlation and regression analysis (R² = 0.7964) confirm that metal exposure had a significant effect on oxidative stress. Conclusion. The study underscores the occupational risk of heavy metal exposure in outdoor settings, emphasizing the need for effective health and safety policies despite limitations such as sample size and city-specific focus.

Objectives. This study aimed to evaluate occupational safety perception and its influencing factors among students in the Department of Occupational Health and Safety at Sinop University, with a particular focus on the impact of socio-demographic variables and participation in occupational health and safety (OHS)-related training. Methods. A cross-sectional study was conducted with 154 OHS students in the 2022-2023 autumn term. Data from 128 students (83.1%) were collected using an informed consent form, a descriptive questionnaire and the occupational safety scale (OSS). The OSS is a 32-item Likert scale with a reliability of 0.75. Data analysis used SPSS version 25, including descriptive statistics, t tests, analysis of variance and Pearson correlation. Results. Participants had a mean age of 21.72 ± 1.33 years, 50.8% were male and 43% were second-year students. Most (73.4%) reported middle-income levels, and 66.4% had not received personal protective equipment (PPE) training. No significant correlation was found between socio-demographic factors and OHS perception scores (p > 0.05). However, students who received PPE training or participated in OHS activities had significantly higher perception scores (p = 0.018 and p = 0.002). Conclusion. OHS-related training, particularly in PPE and OHS activities, significantly improves safety perception. Expanding such training in educational settings can enhance future professionals' safety awareness.

Objectives. This study evaluates the effectiveness of safety indicators in the mining sector, questioning their ability to accurately represent the risks of severe and catastrophic accidents. Indicators such as the frequency rate, severity rate and Bird's pyramid suggest a correlation between events of varying severity, creating the perception of a safe environment when their metrics are low. However, disasters such as the explosions at the BP Texas refinery and the Deepwater Horizon platform occurred despite seemingly ideal safety indicators. Despite the relevance of this topic, there are few systematic investigations into the effectiveness of these indicators, particularly in the mining industry. Methods. To bridge this gap, the study analyzed public and private data from four companies in the sector, using a mixed-methods approach to examine the relationship between frequent, less severe events and rare, more severe incidents. Results. No significant correlation between these events was indicated, contradicting Bird's pyramid logic. Furthermore, the analyzed safety data exhibit biases that compromise their reliability. Conclusion. This study suggests replacing traditional indicators with new management metrics and incorporating activity analysis to enhance accident prevention and minimize catastrophic risks.

This study delves into the intricacies of work-life balance among the self-employed, a rapidly growing segment in the global workforce. Acknowledging a gap in the existing literature which predominantly focuses on employees in organizational settings, this research aims to understand the unique challenges faced by individuals managing their businesses single-handedly. Employing partial least squares structural equation modeling, the study analyzes data from 12,703 respondents from the Sixth Korean Working Conditions Survey conducted between 2020 and 2021. The findings indicate that work-life conflict was associated with increased sleep disorders and burnout, and also had a negative relationship with mental health. Life-work conflict had a negative association with sleep disorders. This suggests a complex interplay between professional demands and personal well-being among the solo self-employed. Moreover, the multi-group analysis reveals that the solo self-employed experience work-life conflict, life-work conflict and job burnout differently compared to regular employees.

Objectives. This study evaluated occupational health and safety prevention and control technologies (OHS-PCTs) within the scope of the unified theory of acceptance and use of technology-2 in the context of preventing occupational accidents and diseases and supporting safe behavior changes. Methods. The data collected from this study using OHS-PCT tools, which included 607 employees, were analyzed using descriptive statistics, normality tests, item analyses, correlation analyses, confirmatory factor analysis, reliability analysis and mediation methods. Results. The findings revealed that emotional intelligence (EQ) partially mediated the effects of the sub-dimensions of the OHS-PCT tool acceptance and use models, such as performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value and habituation, on behavioral intention. The effective adoption and use of OHS-PCT tools in reducing workplace risks depended on their technical features and employees' attitudes, intentions and behaviors. Conclusions. The study reveals the role of EQ, which interacts with psychological and emotional processes in the workplace, in enhancing OHS-PCT acceptance and safety performance. This study fills an important gap in the existing literature on the role of EQ in adopting OHS-PCT to prevent occupational accidents and diseases. This provides a new and holistic perspective to this field.

Objectives. Professionals in the perfume industry are routinely exposed to numerous chemical substances during olfactory evaluations, some of which may pose inhalation hazards. Existing qualitative risk assessment tools, such as Control of Substances Hazardous to Health (COSHH) Essentials, provide approximate estimates and may not be well suited to industries with highly specific exposure conditions like perfumery. This study evaluates the applicability and limitations of COSHH Essentials in perfume laboratories and proposes an improved qualitative framework tailored to perfumers' exposure scenarios. Methods. A total of 626 substances from a perfumer's palette were assessed using COSHH Essentials, which classifies substances into risk levels based on hazard, volatility and quantity. A complementary method incorporating molecular-level hazard analysis, exposure patterns, occupational exposure limits and conservative inhalation dose estimations was developed. Statistical agreement between both methods was examined using Cohen's κ, and McNemar's test assessed significant differences. Results. COSHH Essentials identified 76 hazardous substances, while the enhanced method identified 81 substances, including five additional requiring local exhaust ventilation. Agreement was moderate (κ = 0.58; p = 0.031). Conclusion. COSHH Essentials provides a useful baseline but lacks the specificity needed in industries with intentional close-range exposure. The enhanced method enables more precise, context-sensitive assessment and better protection in fragrance laboratories.

Frequent unsafe behaviors in construction projects, such as unauthorized operations, neglect of safety equipment and violation of safety regulations, pose serious threats to both site safety and project timelines. This study offers a novel approach by integrating contextual and individual factors into a model designed to enhance safety behaviors. Drawing on the ability-motivation-opportunity (AMO) theory, the study applies structural equation modeling to empirically analyze data from 350 experienced construction employees. The findings reveal that safety climate and safety cognition positively impact safety behavior, with cognition mediating the connection between safety climate and behavior. Additionally, psychological capital is found to positively moderate the relationship between safety climate and performance. This research contributes new empirical evidence by offering a deeper understanding of the mechanisms influencing safety behavior, providing actionable recommendations to mitigate unsafe actions and improve safety management in construction projects.

Objectives. The mining sector is a hazardous work environment with high accident rates, causing human suffering and financial losses. Examining incident reports is crucial for preventing comparable events; however, manual classification of large accident datasets is labour-intensive and time-consuming. Methods. This work presents a novel methodology for classifying fatal accident reports using text-mining techniques. It uses natural language processing techniques to transform textual data into a vector representation. Stratified 10-fold cross-validation ensures training and test sets maintain equivalent class distributions from the original dataset, improving model performance. Six supervised machine learning models - logistic regression, support vector machine (SVM), random forest, naïve Bayes, decision tree and multilayer perceptron (MLP) - were employed to classify 1308 fatal accident records into eight accident types. Results. The analysis demonstrates strong model accuracy. The MLP model achieved superior overall performance with a 0.84 weighted average F1 score, followed by logistic regression (0.83), SVM (0.81), random forest (0.73), naïve Bayes (0.65) and decision tree (0.57). Conclusion. This study presents an automated system for identifying accident types from incident reports. The proposed approach reduces misclassifications and mitigates human biases in incident report analysis, offering a reliable tool for mining safety management.

Objectives. As social competition intensifies and 'involution' (a state of inefficient competition) rises in China, job satisfaction (JS) has become a key indicator of workers' quality of life. Methods. Using data from the China General Social Survey (CGSS) 2021, a sample of 1152 employed individuals were analyzed. Multiple linear regression and structural equation modeling (SEM) tested the direct and indirect relationships. Heterogeneity analyses were conducted across gender, household economic status and region. Results. Physical exercise (PE) demonstrated a significant positive direct effect on JS (β = 0.119, p < 0.01). Significant indirect effects were found through social justice perception (β = 0.014, 95% confidence interval [CI] [0.004, 0.033]), happiness (β = 0.046, 95% CI [0.023, 0.081]) and their chain-mediating pathway (β = 0.010, 95% CI [0.003, 0.020]). The total indirect effect accounted for 37.37% of the total effect. Heterogeneity tests revealed the impact was more pronounced among female workers, those with medium household economic status and residents in the eastern region. Conclusions. PE directly enhances JS and indirectly improves it by fostering social justice perception and increasing happiness. Employers should implement tailored and accessible exercise programs, while policymakers should provide targeted support for workplace physical activity.

Objectives. Assessing psychosocial risks in the workplace is essential for promoting employee well-being and occupational safety. This study validates the psychosocial risk factors scale (INSAT_ERPS), a comprehensive instrument developed to identify and measure diverse psychosocial risks in occupational settings. Methods. A cross-sectional study was conducted between February 2023 and May 2024 with 1739 Portuguese workers from various sectors. Data analysis included descriptive statistics, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Missing data were imputed using the expectation-maximization algorithm. EFA employed maximum likelihood extraction with oblimin rotation and Kaiser normalization, supported by a Bartlett Kaiser-Meyer-Olkin value of 0.961 (p < 0.001). Results. CFA confirmed the seven-factor structure identified in EFA, encompassing 44 items across key dimensions: 'Work Intensity', 'Working Hours', 'Autonomy and Initiative', 'Social Work Relations', 'Employment Relations', 'Emotional Demands', and 'Work Values'. The model demonstrated strong psychometric properties, with Cronbach's α ranging from 0.851 to 0.917. Factor loadings (0.422-0.911) indicated statistically significant and meaningful contributions to their respective dimensions. Conclusions. Despite minor cross-loadings, the factorial structure was robust, confirming the INSAT_ERPS as a valid and reliable tool for diagnosing and managing psychosocial risks in occupational health.