Safety

22 pages, 1123 KB

Open AccessArticle

Risk Prevention and Safety Management in the Mount Olympus Area: Challenges and Optimal Strategies for Safe Tourism Development

by Georgia Yfantidou, Apostolos Katsivelos, Ioannis Trigonis, Olga Kouli and Charilaos Kouthouris

Safety 2026, 12(1), 19; https://doi.org/10.3390/safety12010019 - 2 Feb 2026

Abstract

This study investigates safety management and risk prevention on Mount Olympus, Greece, focusing on challenges having an impact on visitors and professionals operating in the area. The research is grounded in theories of safety, risk management, and sustainable tourism in mountain environments. A [...] Read more.

This study investigates safety management and risk prevention on Mount Olympus, Greece, focusing on challenges having an impact on visitors and professionals operating in the area. The research is grounded in theories of safety, risk management, and sustainable tourism in mountain environments. A mixed qualitative methodology was applied, including a review of secondary literature, ten semi-structured interviews with key stakeholders, and data triangulation. Results show that, although major trails are well-marked, deficiencies persist in permanent rescue infrastructure, technological support, visitor education, and coordinated communication. Stakeholder collaboration remains fragmented, and the implementation of innovative technologies is limited. The study recommends enhancing inter-agency cooperation, adopting technological tools such as navigation and early warning systems, and promoting active community participation. Overall, the findings highlight the necessity of an integrated safety framework that combines prevention, preparedness, and education to ensure the sustainable development of Mount Olympus as a safe and high-quality outdoor tourism destination. Full article

► Show Figures

Figure 1

19 pages, 1152 KB

Open AccessArticle

by Lilian Dias Pereira, Irenilza de Alencar Nääs, Vando Aparecido Monteiro, Hercules Jose Marzoque and Maria do Carmo Baracho de Alencar

Safety 2026, 12(1), 18; https://doi.org/10.3390/safety12010018 - 2 Feb 2026

Abstract

This study presents a quantitative, cross-sectional analysis of work-related musculoskeletal disorders (WRMSDs) among sick leave recipients in Brazil’s meat production chain, using official surveillance data. A marked temporal shift was observed; women remained more affected by upper limb injuries, such as shoulder and [...] Read more.

This study presents a quantitative, cross-sectional analysis of work-related musculoskeletal disorders (WRMSDs) among sick leave recipients in Brazil’s meat production chain, using official surveillance data. A marked temporal shift was observed; women remained more affected by upper limb injuries, such as shoulder and wrist disorders. In 2022, male notifications surpassed female ones, marking a turning point linked to improved reporting and the inclusion of WRMSDs in Brazil’s compulsory notification list. Workers aged 20–49 were the most impacted group, with diagnoses including shoulder lesions, tenosynovitis, carpal tunnel syndrome, back pain, and occupational risk exposure. The findings highlight systemic barriers, including underreporting, inadequate protection, and weak return-to-work protocols. Implementing gender-differentiated ergonomic protocols is crucial, as it requires reducing repetitive strain for women in line-feeding/cutting roles, and mitigating environmental hazards (such as cold, vibration, and chemical exposure) for men in farming/slaughtering. These results underscore the urgent need for gender-sensitive preventive strategies and occupational health policies tailored to the meat processing industry. Full article

(This article belongs to the Special Issue Women’s Issues in Safety)

► Show Figures

Figure 1

13 pages, 2731 KB

Open AccessArticle

Exploring States’ Department of Transportation’s Safety and Health Prequalification Criteria for Best Practices

by Michael Behm, Robert Ellis, Amin Akhnoukh, Robin Barfield, Kevin Bradshaw and Jarvis Gray

Safety 2026, 12(1), 17; https://doi.org/10.3390/safety12010017 - 1 Feb 2026

Abstract

Performance-based contractor prequalification allows a construction client to evaluate contractors’ past performance on similar work, improving the likelihood of high-quality work being performed. Occupational safety and health criteria are sometimes included in such prequalification criteria. What metrics are predictive of safe future work? [...] Read more.

Performance-based contractor prequalification allows a construction client to evaluate contractors’ past performance on similar work, improving the likelihood of high-quality work being performed. Occupational safety and health criteria are sometimes included in such prequalification criteria. What metrics are predictive of safe future work? The objectives of this research were to (1) understand best practices in safety and health performance measurement, (2) conduct an initial desktop screening of all fifty US state Departments of Transportation (DOTs) for their publicly available safety and health prequalification criteria, and (3) propose a path forward for a state DOT research inquiry to raise the level of safety and health performance of all contractors by understanding their views of the feasibility and effectiveness of a list of possible leading indicators. Lagging indicators (injury rates, experience modification rates, regulatory citations) are traditional measures; they are shown to measure past performance but are not predictive of future safe work. There is no consensus on viable leading indicators in the discipline of safety science. Seventeen state DOTs require safety metrics of some kind as part of their prequalification process. Including safety and health criteria in the prequalification process provides an opportunity to help underperforming contractors, particularly small and historically underutilized businesses, raise the quality of their site safety and health performance. Full article

14 pages, 697 KB

Open AccessArticle

Ergonomic Risk Profiles of Auto Body Specialists: Evidence from Saudi Arabia with Global Lessons for Labor-Intensive Industries

by Ahmed Basager and Abdullah Alrabghi

Safety 2026, 12(1), 16; https://doi.org/10.3390/safety12010016 - 30 Jan 2026

Viewed by 54

Abstract

Musculoskeletal disorders remain a persistent concern in automotive repair, yet empirical evidence on task-specific ergonomic risks in Middle Eastern contexts is limited. This study provides a detailed ergonomic risk profile of auto body specialists in Jeddah, Saudi Arabia, using a mixed-method approach that [...] Read more.

Musculoskeletal disorders remain a persistent concern in automotive repair, yet empirical evidence on task-specific ergonomic risks in Middle Eastern contexts is limited. This study provides a detailed ergonomic risk profile of auto body specialists in Jeddah, Saudi Arabia, using a mixed-method approach that integrates the Rapid Upper Limb Assessment (RULA), Rapid Entire Body Assessment (REBA), and a validated Nordic Musculoskeletal Questionnaire. Twenty-five specialists across diverse tasks including installation, weighing, painting, cutting, and lifting were systematically evaluated to identify both postural and self-reported risk patterns. Results showed a high prevalence of discomfort in the lower back (64%), shoulders (52%), and wrists (48%). Ergonomic assessment revealed that the evaluated tasks were predominantly classified as moderate-to-high-risk, with RULA scores ranging from 6 to 7 and REBA scores ranging from 8 to 11. Beyond confirming the physical strain inherent to auto body work, the study highlights contextual factors such as prolonged static postures, limited use of mechanical aids, and constrained workshop layouts that exacerbate ergonomic risks. Importantly, the findings inform multi-level recommendations ranging from workshop practices to industry standards and policy considerations ensuring that interventions are both practical and scalable. By situating locally grounded results within the broader discourse on musculoskeletal risk prevention, the study offers region-specific evidence while providing globally relevant lessons for labor-intensive industries. Full article

► Show Figures

Figure 1

28 pages, 2816 KB

Open AccessArticle

Ergonomic Optimization of Assembly Workstations: Effects on Productivity and Mental Workload

by Marija Savković, Marko Djapan, Carlo Caiazzo, Miloš Pušica, Arso Vukićević, Dragan Marinković and Nikola Komatina

Safety 2026, 12(1), 15; https://doi.org/10.3390/safety12010015 - 29 Jan 2026

Viewed by 205

Abstract

The main aim of this research paper is to improve the effectiveness of production processes through ergonomic optimization of industrial workstations where workers perform repetitive, monotonous assembly tasks. The study analyzes the impact of applying ergonomic and lean principles, standard of “the golden [...] Read more.

The main aim of this research paper is to improve the effectiveness of production processes through ergonomic optimization of industrial workstations where workers perform repetitive, monotonous assembly tasks. The study analyzes the impact of applying ergonomic and lean principles, standard of “the golden zone standard” in the design of assembly workstations on participants’ brain activity and productivity, as well as on the quality of the final products in traditional (non-ergonomic) and ergonomic scenario. The results indicated significant differences in brain activity patterns between the two scenarios, revealing higher levels of mental workload during assembly tasks in the non-ergonomic scenario for all participants. Furthermore, improvements in production processes were observed, including increased productivity; specifically, the average mental workload was reduced by approximately 35% in the ergonomic scenario, accompanied by an approximately 5% increase in productivity and an approximately 8% reduction in working time. The obtained results provide a foundation for improving the design of assembly workstations in industrial environments, as well as contributing to a broader understanding of the importance of ergonomics in the optimization of industrial processes. Full article

(This article belongs to the Special Issue Advances in Ergonomics and Safety)

► Show Figures

Figure 1

20 pages, 1011 KB

Open AccessArticle

From Perception to Practice: Identifying and Ranking Human Factors Driving Unsafe Industrial Behaviors

by Azim Karimi, Esmaeil Zarei and Ehsanollah Habibi

Safety 2026, 12(1), 14; https://doi.org/10.3390/safety12010014 - 23 Jan 2026

Viewed by 168

Abstract

Unsafe behaviors remain a major contributor to workplace accidents within broader safety-management systems. Acknowledging the essential influence of organizational and leadership factors, this study focuses on systematically identifying and prioritizing individual-level determinants of unsafe behavior through an integrated qualitative–quantitative methodology to clarify their [...] Read more.

Unsafe behaviors remain a major contributor to workplace accidents within broader safety-management systems. Acknowledging the essential influence of organizational and leadership factors, this study focuses on systematically identifying and prioritizing individual-level determinants of unsafe behavior through an integrated qualitative–quantitative methodology to clarify their specific role within the wider safety framework. Grounded Theory analysis of semi-structured interviews with 40 industry professionals yielded a conceptual model encompassing demographic characteristics, general health, individual competencies, personality traits, and psychological factors. Subsequently, the Fuzzy Delphi Method, applied with 20 domain experts, validated and ranked these determinants. The analysis highlighted risk perception as the most influential factor, followed by work experience, skill level, knowledge, and risk-taking propensity, whereas variables such as family welfare, substance use, and self-display exhibited relatively minor effects. These findings reveal the multidimensional nature of unsafe behavior and underscore the importance of focusing on high-impact personal attributes to enhance workplace safety. By recognizing that many individual factors are shaped by organizational and psychosocial conditions, the study provides evidence-based insights for developing integrated safety management and targeted intervention strategies in industrial settings. Full article

► Show Figures

Figure 1

17 pages, 2552 KB

Open AccessReview

Occupational Hazards, Risks and Preventive Measures in Forestry Logging: A Scoping Review of Published Evidence (2015–2025)

by Ana C. Meira Castro, José Mota and João Santos Baptista

Safety 2026, 12(1), 13; https://doi.org/10.3390/safety12010013 - 21 Jan 2026

Viewed by 197

Abstract

Forestry logging is among the most hazardous economic activities, so identifying where hazards and risks concentrate supports targeted prevention. This scoping review mapped evidence on logging hazards and risks, their co-occurrence with operations, and preventive measures. PRISMA-ScR was followed. Only peer-reviewed journal articles [...] Read more.

Forestry logging is among the most hazardous economic activities, so identifying where hazards and risks concentrate supports targeted prevention. This scoping review mapped evidence on logging hazards and risks, their co-occurrence with operations, and preventive measures. PRISMA-ScR was followed. Only peer-reviewed journal articles (2015–2025) in English on occupational hazards/risks, risk-assessment methods or preventive measures in logging were included, found in Scopus, Web of Science, Inspec and Dimensions (last search 15 September 2025). Independent data screening and extraction were performed by two reviewers, with a third reviewer resolving any disagreements. No formal risk-of-bias appraisal was conducted. Forty-two studies were included. Hazards and risks concentrated in three phases—chainsaw/manual cutting, skidding/cable yarding, and loading/short-haul transport—where acute injury mechanisms (struck-by events, slips/trips/falls, rollovers, lacerations) coexisted with chronic exposures (musculoskeletal strain, noise, vibration, diesel exhaust). Preventive measures emphasised engineering and organisational controls, complemented by raining and PPE, but were inconsistently specified and evaluated. Evidence was heterogeneous and geographically concentrated in few countries, limiting generalisability. A small set of tasks consistently concentrates acute and chronic risks; prevention should integrate accident control and health protection, prioritising engineering/organisational measures supported by training and PPE. Future studies should standardise descriptors and outcome metrics to enable comparisons. Full article

► Show Figures

Figure 1

9 pages, 558 KB

Open AccessArticle

Prospective Analysis of the Benefits of Driver Safety Training for e-Scooter Drivers—A Comparison Between First-Time Drivers and Experienced Drivers

by Philipp Zehnder, Frederik Aasen-Hartz, Markus Schwarz, Tobias Resch, Kai von Schwarzenberg, Peter Biberthaler, Chlodwig Kirchhoff and Michael Zyskowski

Safety 2026, 12(1), 12; https://doi.org/10.3390/safety12010012 - 20 Jan 2026

Viewed by 212

Abstract

Background: Since the introduction of rental e-scooters, they have become a popular mode of transportation not only in German cities but in other cities as well. However, this rapid increase in usage has coincided with a significant rise in associated injuries and accidents, [...] Read more.

Background: Since the introduction of rental e-scooters, they have become a popular mode of transportation not only in German cities but in other cities as well. However, this rapid increase in usage has coincided with a significant rise in associated injuries and accidents, outpacing those related to bicycles. A disproportionate number of these incidents involve alcohol consumption and young people under the age of 25, with a low incidence of helmet use. Following the example of driver training for children on bicycles, we carried out driver safety training with e-scooters and examined the results scientifically. Methods: The study conducted three voluntary driving safety training sessions in Berlin and Munich, with participants completing questionnaires before and after the training to measure their knowledge and skills (on a scale between 0 and 5; 0 = totally insecure and 5 = absolutely secure). The training included a technical introduction, practical exercises, and an educational component on injury data and prevention strategies. During the statistical analysis, the novice drivers (group 1) were compared to the non-novice drivers (group 2). Results: Out of 136 participants, 103 completed the training (a response rate of 75.7%). The mean age of the participants was 37.1 years, and 52.4% of them were female. A total of 59% had never used an e-scooter and were therefore assigned to group 1 (group 2 = experienced drivers). Both groups showed significant improvements in both knowledge of traffic laws and driving skills. Conclusions: The findings suggest that driving safety training potentially enhances the safe operation of e-scooters. However, the training demands a high level of time and motivation, making it less attractive for younger drivers who are most prone to accidents. Therefore, we recommend the use of digital driving safety training before the first use of e-scooters. Full article

(This article belongs to the Special Issue Human Factors in Road Safety and Mobility, 2nd Edition)

► Show Figures

Figure 1

21 pages, 279 KB

Open AccessArticle

Occupational Health and Safety in Educational Settings: Barriers, Strategies, and Compliance Using a Mixed-Methods Approach

by Abdul Kadir, Surindar K. Dhesi, Vanisha Dwi Amalinda, Tubagus Dwika Yuantoko, Bangga Agung Satrya and Farhan Fitriadi

Safety 2026, 12(1), 11; https://doi.org/10.3390/safety12010011 - 15 Jan 2026

Viewed by 225

Abstract

Occupational Health and Safety (OHS) in educational settings is a vital responsibility that is often inconsistently implemented. There is a need for research to bridge the gap between policy and practice. This study employed a cross-sectional mixed-methods design in six schools in the [...] Read more.

Occupational Health and Safety (OHS) in educational settings is a vital responsibility that is often inconsistently implemented. There is a need for research to bridge the gap between policy and practice. This study employed a cross-sectional mixed-methods design in six schools in the capital city of Indonesia to identify key implementation barriers, strategies, and compliance levels in OHS. Data were collected from 217 teachers using a structured KPAP (Knowledge, Attitudes, Perceptions, Practices) survey and from an additional 38 teachers via Focus Group Discussions (FGDs). Quantitatively, teachers showed highly positive attitudes (99.4% viewing OHS as a professional duty) and generally positive perceptions but implementation practices were sub-optimal (e.g., low participation in drills and PPE usage), showing a gap between awareness and action. Qualitatively, the main barriers identified were a lack of specific OHS regulation or guidance for schools, limited resources/infrastructure, and the perception of OHS as a low priority. Management strategies focused on external collaboration and ongoing in-school initiatives. In conclusion, a significant gap exists between OHS awareness and its integration into school management, highlighting the urgent need for strengthened governance, comprehensive policies, and sustained capacity-building to ensure a proactive, safe, and sustainable school environment for staff and students. Full article

21 pages, 3188 KB

Open AccessArticle

Bayesian Network-Based Failure Risk Assessment and Inference Modeling for Biomethane Supply Chain

by Yue Wang, Siqi Wang, Xiaoping Jia and Fang Wang

Safety 2026, 12(1), 9; https://doi.org/10.3390/safety12010009 - 14 Jan 2026

Viewed by 213

Abstract

To identify and evaluate the failure issues in the livestock manure-to-biomethane supply chain, this study employs a Bayesian network approach with three inference analysis methods: diagnostic analysis, sensitivity analysis, and maximum causal chain inference. First, the main hazard categories affecting the failure of [...] Read more.

To identify and evaluate the failure issues in the livestock manure-to-biomethane supply chain, this study employs a Bayesian network approach with three inference analysis methods: diagnostic analysis, sensitivity analysis, and maximum causal chain inference. First, the main hazard categories affecting the failure of the supply chain are identified, establishing risk indicators for feedstock collection, pretreatment, anaerobic digestion, purification and upgrading, transportation, and biomethane end-use. Then, the half-interval method and possibility superiority comparison are used to calculate and rank the severity of related accidents, obtaining the severity ranking of secondary indicators as well as the severity ranking of work items and risk items. Finally, Bayesian forward inference is applied to investigate the failure probability of the supply chain, combined with backward inference to identify the risk factors most likely to cause supply chain failures and trace the formation of failure hazards. The Bayesian sensitivity analysis method is ultimately applied to determine the key hazards affecting supply chain failures and the correlations between accident hazards, followed by validation. The results show that the failure probability of the supply chain through causal inference is approximately 54.76%, indicating relatively high failure risk. The three factors with the highest posterior probabilities are mechanical stirring failure C₃ (88.11%), corrosion-induced ammonia leakage poisoning D6, and equipment explosion caused by excessive pressure due to overheating during dehumidification heating D₉, which are the hazards most likely to cause failures in the supply chain. Improper operations and the toxicity of related chemicals are key hazards leading to supply chain failures, with the correlation between accident hazards presented as a hazard chain by integrating severity and accident probability, and the key risk points in the supply chain are identified. Full article

► Show Figures

Figure 1

31 pages, 2530 KB

Open AccessReview

Occupational Exposure to Solar Ultraviolet Radiation: A Systematic Review of Protective Measures

by Ricardo Rocha, Joana Santos, João Santos Baptista, Joana Guedes and Carlos Carvalhais

Safety 2026, 12(1), 10; https://doi.org/10.3390/safety12010010 - 14 Jan 2026

Viewed by 247

Abstract

Solar ultraviolet radiation (UVR) is classified as a Group 1 carcinogen and poses a significant occupational hazard to outdoor workers. Despite preventive guidelines, adherence to protective measures remains inconsistent. This systematic review identified the protective measures adopted by healthy outdoor workers and assessed [...] Read more.

Solar ultraviolet radiation (UVR) is classified as a Group 1 carcinogen and poses a significant occupational hazard to outdoor workers. Despite preventive guidelines, adherence to protective measures remains inconsistent. This systematic review identified the protective measures adopted by healthy outdoor workers and assessed their adherence to and the effectiveness of these measures. Following the PRISMA 2020 statement, the review searched Scopus, Web of Science, and PubMed for peer-reviewed studies published between 2015 and 2025. Eligible studies included at least 100 healthy participants and evaluated preventive or protective measures against solar UVR. Independent reviewers extracted data and assessed risk of bias using the McMaster Critical Review Form. From 17,756 records, 51 studies met the inclusion criteria after screening and a subsequent snowballing process. The identified protective strategies clustered into physical, behavioural, and organisational categories. Adherence ranged from low to moderate, with structured interventions and employer support improving compliance. Sunscreen use remained low due to perceived inconvenience and lack of provision. Overall, the evidence revealed substantial variability in implementation and effectiveness across occupations. Strengthened regulations and integrated interventions combining education, personal protective equipment, and organisational measures are essential. Future research should prioritise longitudinal designs and objective indicators such as biomarkers and dosimetry. Full article

► Show Figures

Figure 1

16 pages, 274 KB

Open AccessArticle

Two Wheels or Four Wheels: A Comparative Study of Police Tasks on Bicycle vs. Car in Saguenay

by Pier-Luc Langlais, Marc-Antoine Masse and Martin Lavallière

Safety 2026, 12(1), 8; https://doi.org/10.3390/safety12010008 - 9 Jan 2026

Viewed by 256

Abstract

Modern police work requires a high degree of versatility, shifting between sedentary tasks and intense physical demands. While bicycle patrols are recognized as a tool for enhancing community policing, few empirical studies have examined the specific nature and frequency of the tasks performed [...] Read more.

Modern police work requires a high degree of versatility, shifting between sedentary tasks and intense physical demands. While bicycle patrols are recognized as a tool for enhancing community policing, few empirical studies have examined the specific nature and frequency of the tasks performed by bicycle patrol officers. This study aims to compare the professional tasks of bicycle and car patrol officers in the city of Saguenay, Québec, over a three-year period. A retrospective analysis of 539 computer-aided dispatch (PCAD) entries was conducted for eight male officers (six on bicycles, two in police cars) during the summer months of 2021 to 2023. We analyzed task frequency, duration, priority, and risk level using descriptive statistics. Results showed that while both patrol types performed similar core tasks, such as citizen assistance, enforcement of municipal regulations, and responses to suspicious individuals, bicycle patrols were associated with significantly longer total PCAD-recorded intervention times (49 ± 47 min vs. 33 ± 29 min). Moreover, the distribution of call types suggests a slightly higher proportion of interventions occurring in public spaces or involving direct citizen contact, although this does not constitute a measure of increased proximity. No significant differences were observed in terms of priority or risk. Because the PCAD system does not systematically record on-scene time, the longer durations observed for bicycle patrols cannot be interpreted as qualitative advantages. Instead, the study reveals operational similarities alongside noteworthy differences between patrol types. As one of the first Canadian CAD-based analyses of bicycle patrol tasks, this research underscores the need for future studies capable of isolating on-scene time and examining the qualitative dimensions of police–citizen interactions. Full article

41 pages, 701 KB

Open AccessReview

New Trends in the Use of Artificial Intelligence and Natural Language Processing for Occupational Risks Prevention

by Natalia Orviz-Martínez, Efrén Pérez-Santín and José Ignacio López-Sánchez

Safety 2026, 12(1), 7; https://doi.org/10.3390/safety12010007 - 8 Jan 2026

Viewed by 347

Abstract

In an increasingly technologized and automated world, workplace safety and health remain a major global challenge. After decades of regulatory frameworks and substantial technical and organizational advances, the expanding interaction between humans and machines and the growing complexity of work systems are gaining [...] Read more.

In an increasingly technologized and automated world, workplace safety and health remain a major global challenge. After decades of regulatory frameworks and substantial technical and organizational advances, the expanding interaction between humans and machines and the growing complexity of work systems are gaining importance. In parallel, the digitalization of Industry 4.0/5.0 is generating unprecedented volumes of safety-relevant data and new opportunities to move from reactive analysis to proactive, data-driven prevention. This review maps how artificial intelligence (AI), with a specific focus on natural language processing (NLP) and large language models (LLMs), is being applied to occupational risk prevention across sectors. A structured search of the Web of Science Core Collection (2013–October 2025), combined OSH-related terms with AI, NLP and LLM terms. After screening and full-text assessment, 123 studies were discussed. Early work relied on text mining and traditional machine learning to classify accident types and causes, extract risk factors and support incident analysis from free-text narratives. More recent contributions use deep learning to predict injury severity, potential serious injuries and fatalities (PSIF) and field risk control program (FRCP) levels and to fuse textual data with process, environmental and sensor information in multi-source risk models. The latest wave of studies deploys LLMs, retrieval-augmented generation and vision–language architectures to generate task-specific safety guidance, support accident investigation, map occupations and job tasks and monitor personal protective equipment (PPE) compliance. Together, these developments show that AI-, NLP- and LLM-based systems can exploit unstructured OSH information to provide more granular, timely and predictive safety insights. However, the field is still constrained by data quality and bias, limited external validation, opacity, hallucinations and emerging regulatory and ethical requirements. In conclusion, this review positions AI and LLMs as tools to support human decision-making in OSH and outlines a research agenda centered on high-quality datasets and rigorous evaluation of fairness, robustness, explainability and governance. Full article

(This article belongs to the Special Issue Advances in Ergonomics and Safety)

► Show Figures

Figure 1

23 pages, 3238 KB

Open AccessArticle

Agricultural Injury Severity Prediction Using Integrated Data-Driven Analysis: Global Versus Local Explainability Using SHAP

by Omer Mermer, Yanan Liu, Charles A. Jennissen, Milan Sonka and Ibrahim Demir

Safety 2026, 12(1), 6; https://doi.org/10.3390/safety12010006 - 8 Jan 2026

Viewed by 248

Abstract

Despite the agricultural sector’s consistently high injury rates, formal reporting is often limited, leading to sparse national datasets that hinder effective safety interventions. To address this, our study introduces a comprehensive framework leveraging advanced ensemble machine learning (ML) models to predict and interpret [...] Read more.

Despite the agricultural sector’s consistently high injury rates, formal reporting is often limited, leading to sparse national datasets that hinder effective safety interventions. To address this, our study introduces a comprehensive framework leveraging advanced ensemble machine learning (ML) models to predict and interpret the severity of agricultural injuries. We use a unique, manually curated dataset of over 2400 agricultural incidents from AgInjuryNews, a public repository of news reports detailing incidents across the United States. We evaluated six ensemble models, including Gradient Boosting (GB), eXtreme Grading Boosting (XGB), Light Gradient Boosting Machine (LightGBM), Adaptive Boosting (AdaBoost), Histogram-based Gradient Boosting Regression Trees (HistGBRT), and Random Forest (RF), for their accuracy in classifying injury outcomes as fatal or non-fatal. A key contribution of our work is the novel integration of explainable artificial intelligence (XAI), specifically SHapley Additive exPlanations (SHAP), to overcome the “black-box” nature of complex ensemble models. The models demonstrated strong predictive performance, with most achieving an accuracy of approximately 0.71 and an F1-score of 0.81. Through global SHAP analysis, we identified key factors influencing injury severity across the dataset, such as the presence of helmet use, victim age, and the type of injury agent. Additionally, our application of local SHAP analysis revealed how specific variables like location and the victim’s role can have varying impacts depending on the context of the incident. These findings provide actionable, context-aware insights for developing targeted policy and safety interventions for a range of stakeholders, from first responders to policymakers, offering a powerful tool for a more proactive approach to agricultural safety. Full article

(This article belongs to the Special Issue Farm Safety, 2nd Edition)

► Show Figures

Figure 1

28 pages, 3549 KB

Open AccessArticle

Identification of Key Contributing Factors and Risk Propagation Paths in Safety Accidents at Chinese Chemical Enterprises

by Zhiheng Ni, Zhen Li, Mingyu Zhang and Otsile Morake

Safety 2026, 12(1), 5; https://doi.org/10.3390/safety12010005 - 5 Jan 2026

Viewed by 254

Abstract

To address the complex and uncertain causes of safety accidents in chemical enterprises, this study applied text mining techniques to systematically extract 29 causative factors from 422 accident reports. These factors were classified into five categories: personnel issues, resource management deficiencies, adverse organizational [...] Read more.

To address the complex and uncertain causes of safety accidents in chemical enterprises, this study applied text mining techniques to systematically extract 29 causative factors from 422 accident reports. These factors were classified into five categories: personnel issues, resource management deficiencies, adverse organizational atmosphere, organizational process flaws, and inadequate supervision. Based on the extracted factors, a complex network model of accident causation was constructed. Using degree centrality, betweenness centrality, and eigenvector centrality, seven core causative factors were identified, along with multiple peripheral factors closely linked to them. Bayesian network-based sensitivity analysis further revealed the factors that exert the greatest influence on accident occurrence, and subsequent path analysis uncovered several critical accident propagation paths. The findings reveal core causative factors and critical propagation paths, which may inform the prioritization of risk control measures under conditions of limited resources. Full article

► Show Figures

Figure 1

10 pages, 1866 KB

Open AccessArticle

Crowding, Risk, and Visitor Use Management on the Angels Landing Trail in Zion National Park

by Jeffrey N. Rose

Safety 2026, 12(1), 4; https://doi.org/10.3390/safety12010004 - 5 Jan 2026

Viewed by 495

Abstract

Zion National Park has seen substantial increased visitor use in recent years, bringing forward a number of visitor use management challenges. Many visitors consider the park’s Angels Landing trail, a steep and relatively challenging hike, a primary destination in the park. A number [...] Read more.

Zion National Park has seen substantial increased visitor use in recent years, bringing forward a number of visitor use management challenges. Many visitors consider the park’s Angels Landing trail, a steep and relatively challenging hike, a primary destination in the park. A number of well documented fatalities have been associated with the Angels Landing trail, prompting substantial risk management concerns. In the context of increased visitor use and increased attention to these fatalities, this research reviews literature on crowding and risk management before using National Park Service and media reports concerning 16 deaths associated with Angels Landing to characterize trends among age, gender, time of day, specific location, and other factors. Findings note that few of the fatalities occurred on the trail itself; those that did were not on the sections of the trail where risk management interventions have been installed, and none were associated with crowding or high visitor use. From these analyses, managers should consider disentangling notions of crowding and risk, particularly in light of new management strategies concerning permitting and limiting hikers on Angels Landing. Full article

► Show Figures

Figure 1

17 pages, 2210 KB

Open AccessArticle

The Use of a Device to Improve the Evacuation Performance of Hospitalized Non-Self-Sufficient Patients in Healthcare Facilities

by Simone Accorsi, Francesco Ottaviani, Aurora Fabiano and Dimitri Sossai

Safety 2026, 12(1), 3; https://doi.org/10.3390/safety12010003 - 24 Dec 2025

Viewed by 382

Abstract

Background: Fire emergency management in healthcare facilities represents a complex challenge, particularly in historic buildings subject to architectural preservation constraints, where progressive horizontal evacuation is objectively difficult. This study analyzes the effectiveness of an evacuation sheet employed by Hospital Policlinico San Martino to [...] Read more.

Background: Fire emergency management in healthcare facilities represents a complex challenge, particularly in historic buildings subject to architectural preservation constraints, where progressive horizontal evacuation is objectively difficult. This study analyzes the effectiveness of an evacuation sheet employed by Hospital Policlinico San Martino to improve the speed of evacuating non-self-sufficient patients in these buildings. Methods: This study involved evacuation simulations in wards previously selected based on structural characteristics. Healthcare personnel (male and female, aged between 30 and 55 years) conducted both horizontal and vertical patient evacuation drills, comparing the performance of the S-CAPEPOD^® Evacuation Sheet (Standard Model) with the conventional method (hospital bed plus and rescue sheet). This study focused on the night shift to evaluate the most critical scenario in terms of human resources. Results: The use of the evacuation sheet proved more efficient than the conventional method throughout the entire evacuation route, especially during the first 15 min of the emergency (the most critical period). Indeed, with an equal number of available personnel, the evacuation sheet enabled an average improvement of 50% in the number of patients evacuated. Conclusions: The data support the effectiveness of the device, confirming the theoretical premise that the introduction of the evacuation sheet—also due to its ease of use—can be an improvement measure for the evacuation performance of non-self-sufficient patients, despite limitations related to structural variability and the simulated nature of the trials. Full article

► Show Figures

Figure 1

23 pages, 1919 KB

Open AccessArticle

Machine Learning Assessment of Crash Severity in ADS and ADAS-L2 Involved Crashes with NHTSA Data

by Nasim Samadi, Ramina Javid, Sanam Ziaei Ansaroudi, Neda Dehestanimonfared, Mojtaba Naseri and Mansoureh Jeihani

Safety 2026, 12(1), 2; https://doi.org/10.3390/safety12010002 - 23 Dec 2025

Viewed by 546

Abstract

As the deployment of Automated Driving Systems (ADS) and Advanced Driver Assistance Systems (ADAS-L2) expands, understanding their real-world safety performance becomes essential. This study examines the severity and contributing factors of crashes involving vehicles equipped with ADS and ADAS-L2 technologies using NHTSA data. [...] Read more.

As the deployment of Automated Driving Systems (ADS) and Advanced Driver Assistance Systems (ADAS-L2) expands, understanding their real-world safety performance becomes essential. This study examines the severity and contributing factors of crashes involving vehicles equipped with ADS and ADAS-L2 technologies using NHTSA data. Using machine learning models on crash datasets from 2021 to 2024, this research identifies patterns and risk factors influencing injury outcomes. After data preprocessing and handling missing values for severity classification, four models were trained: logistic regression, random forest, SVM, and XGBoost. XGBoost outperformed the others for both ADS and ADAS-L2, achieving the highest accuracy and recall. Variable importance analysis showed that for ADS crashes, interactions with other road users and poor lighting were the strongest predictors of injury severity, while for ADAS-L2 crashes, fixed object collisions and low light conditions were most influential. From a policy and engineering perspective, this study highlights the need for standardized crash reporting and improved ADS object detection and pedestrian response. It also emphasizes effective human–machine interface design and driver training for partial automation. Unlike previous research, this study conducts comparative model-based evaluations of both ADS and ADAS-L2 using recent crash reports to inform safety standards and policy frameworks. Full article

► Show Figures

Figure 1

21 pages, 1701 KB

Open AccessArticle

Uncovering the Ergonomic Risks Threatening the Health of Underground Female Coal Mineworkers

by Ouma S. Mokwena, Thabiso J. Morodi and Joyce Shirinde

Safety 2026, 12(1), 1; https://doi.org/10.3390/safety12010001 - 19 Dec 2025

Viewed by 331

Abstract

Women in mining face unique health and safety challenges due to anatomical and physiological differences, making the assessment and management of ergonomic risks in underground coal mines critical. This study examines the ergonomic experiences of female mineworkers through six focus-group discussions, each comprising [...] Read more.

Women in mining face unique health and safety challenges due to anatomical and physiological differences, making the assessment and management of ergonomic risks in underground coal mines critical. This study examines the ergonomic experiences of female mineworkers through six focus-group discussions, each comprising eight participants, using a qualitative research design involving women actively engaged in core mining activities at three South African mines. Findings reveal that mining equipment and work environments often fail to accommodate the physiological needs of female workers, exposing them to a range of ergonomic hazards. Beyond physical risks, the study highlights organizational and systemic shortcomings, including inadequate implementation of existing policies and regulations. Poor hygiene in toilet facilities was also reported, with three out of eight participants taking medication for urinary tract infections, underscoring gaps in occupational health provision. The findings emphasize the urgent need for mine-specific ergonomic programs developed through participatory approaches, as part of a broader strategy to prevent musculoskeletal injuries and improve working conditions for female mineworkers. The establishment of the Women in Mining Forum further indicates that the industry is not yet fully prepared to support women in underground mining, highlighting the need for targeted interventions to create a safer, more inclusive work environment. Full article

► Show Figures

Figure 1

Journal Menu

Journal Browser

Safety, Volume 12, Issue 1 (February 2026) – 19 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI