Journal Description
Safety
Safety
is an international, peer-reviewed, open access journal on industrial and human health safety published quarterly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), SafetyLit, and other databases.
- Journal Rank: CiteScore - Q2 (Safety Research)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 29.6 days after submission; acceptance to publication is undertaken in 4.6 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
1.9 (2022);
5-Year Impact Factor:
1.8 (2022)
Latest Articles
Navigating the Power of Artificial Intelligence in Risk Management: A Comparative Analysis
Safety 2024, 10(2), 42; https://doi.org/10.3390/safety10020042 - 26 Apr 2024
Abstract
This study presents a responsive analysis of the role of artificial intelligence (AI) in risk management, contrasting traditional approaches with those augmented by AI and highlighting the challenges and opportunities that emerge. AI, intense learning methodologies such as convolutional neural networks (CNNs), have
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This study presents a responsive analysis of the role of artificial intelligence (AI) in risk management, contrasting traditional approaches with those augmented by AI and highlighting the challenges and opportunities that emerge. AI, intense learning methodologies such as convolutional neural networks (CNNs), have been identified as pivotal in extracting meaningful insights from image data, a form of analysis that holds significant potential in identifying and managing risks across various industries. The research methodology involves a strategic selection and processing of images for analysis and introduces three case studies that serve as benchmarks for evaluation. These case studies showcase the application of AI, in place of image processing capabilities, to identify hazards, evaluate risks, and suggest control measures. The comparative evaluation focuses on the accuracy, relevance, and practicality of the AI-generated findings alongside the system’s response time and comprehensive understanding of the context. Results reveal that AI can significantly enhance risk assessment processes, offering rapid and detailed insights. However, the study also recognises the intrinsic limitations of AI in contextual interpretation, advocating for a synergy between technological and domain-specific expertise. The conclusion underscores the transformative potential of AI in risk management, supporting continued research to further integrate AI effectively into risk assessment frameworks.
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Open AccessArticle
A Risk Assessment Framework Based on Fuzzy Logic for Automotive Systems
by
Francesco Merola, Cinzia Bernardeschi and Giuseppe Lami
Safety 2024, 10(2), 41; https://doi.org/10.3390/safety10020041 - 25 Apr 2024
Abstract
Recent advancements in the automotive field have significantly increased the level of complexity and connectivity of modern vehicles. In this context, the topic of cybersecurity becomes extremely relevant, as a successful attack can have an impact in terms of safety on the car
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Recent advancements in the automotive field have significantly increased the level of complexity and connectivity of modern vehicles. In this context, the topic of cybersecurity becomes extremely relevant, as a successful attack can have an impact in terms of safety on the car navigation, potentially leading to harmful behavior. Risk assessment is typically performed using discrete input and output scales, which can often lead to an identical output in terms of risk evaluation despite the inputs presenting non-negligible differences. This work presents a novel fuzzy-logic-based methodology to assess cybersecurity risks which takes attack feasibility and safety impact as input factors. This technique allows us explicitly model the uncertainty and ambiguousness of input data, which is typical of the risk assessment process, providing an output on a more detailed scale. The fuzzy inference engine is based on a set of control rules expressed in natural language, which is crucial to maintaining the interpretability and traceability of the risk calculation. The proposed framework was applied to a case study extracted from ISO/SAE 21434. The obtained results are in line with the traditional methodology, with the added benefit of also providing the scatter around the calculated value, indicating the risk trend. The proposed method is general and can be applied in the industry independently from the specific case study.
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Open AccessArticle
Occupational Safety Assessment for Surface Mine Systems: The Case in Jordan
by
Samir K. Khrais, Tamer Elia Yared, Noor Majid Saifan, Tarek H. Al-Hawari and Fikri Dweiri
Safety 2024, 10(2), 40; https://doi.org/10.3390/safety10020040 - 25 Apr 2024
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Surface mining is one of the hazardous industries that have several risky operations, including transportation, treatment, and mineral extraction. To avoid the risk of disaster, it is important to evaluate safety procedures and determine expected hazards. The aim of this study is to
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Surface mining is one of the hazardous industries that have several risky operations, including transportation, treatment, and mineral extraction. To avoid the risk of disaster, it is important to evaluate safety procedures and determine expected hazards. The aim of this study is to develop a thorough safety evaluation model for the surface mining industry based on the analytic hierarchy process (AHP), one important multi-criteria decision-making approach. A total of 11 criteria and 36 sub-criteria that are both independent and homogeneous were involved in the decision problem. Further, a deep sensitivity analysis was conducted to assess the stability of the ranking preference. The findings indicate that four out of the eleven criteria are particularly significant. To test the model’s applicability and effectiveness, a case study was conducted involving three surface mining companies located in the north of Jordan. The results demonstrate that the model is reliable, applicable, and effective in addressing real-world problems.
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Open AccessCommunication
Nose-Over and Nose-Down Accidents in General Aviation: Tailwheels and Aging Airplanes
by
Alex de Voogt and Kayla Louteiro
Safety 2024, 10(2), 39; https://doi.org/10.3390/safety10020039 - 13 Apr 2024
Abstract
Safety in General Aviation has been a continuous concern. About 12% of all airplane accidents in General Aviation involve nose-overs and nose-down events. A total of 134 accidents reported by the National Transportation Safety Board that include nose-overs and nose-downs were analyzed for
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Safety in General Aviation has been a continuous concern. About 12% of all airplane accidents in General Aviation involve nose-overs and nose-down events. A total of 134 accidents reported by the National Transportation Safety Board that include nose-overs and nose-downs were analyzed for their main causes. It was found that 35% of the defining events involved a loss of control on the ground while 58% of the total dataset involved tailwheel-type aircraft. A relatively high proportion of aircraft built before 1950 were found, which are also aircraft that have tailwheel-type landing gear, and thereby a higher propensity for ground loops and nose-overs. It is shown that the high accident rate in General Aviation, especially for accidents that did not result in a fatality, was, to an important extent, explained by tailwheel and older aircraft in the US General Aviation airplane fleet struggling with controlling the aircraft on the ground. Attention to this group of aircraft in future studies may help to more effectively address the relatively high accident rates in General Aviation.
Full article
(This article belongs to the Special Issue Aviation Safety—Accident Investigation, Analysis and Prevention)
Open AccessArticle
Altered Haematological Parameters in Gasoline Station Workers Due to Benzene Exposure
by
Sunisa Chaiklieng, Umakorn Tongsantia, Pornnapa Suggaravetsiri and Herman Autrup
Safety 2024, 10(2), 38; https://doi.org/10.3390/safety10020038 - 12 Apr 2024
Abstract
Benzene is harmful to human health and early detection of haematological alterations is important in preventing adverse health effects. This study aimed to investigate the biomarkers of benzene exposure and its effects due to haematological alterations. Gasoline station workers with potential risks according
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Benzene is harmful to human health and early detection of haematological alterations is important in preventing adverse health effects. This study aimed to investigate the biomarkers of benzene exposure and its effects due to haematological alterations. Gasoline station workers with potential risks according to the biomatrix concerning benzene exposure underwent blood and urine evaluation for the biological monitoring of urinary trans, trans-muconic acid (tt-MA), and haematological and biochemical parameter evaluation. The results were analysed for correlations between biological and haematological effects. The tt-MA biomarker was detected in some workers and approximately 50% of workers had a blood profile that showed abnormal parameters with respect to the haemoglobin (Hb), haematocrit (Hct) and white blood cell parameters, which were outside the normal range. A significant correlation was observed between the tt-MA biomarker’s level and the levels of the haematological and biochemical parameters, which were Hb, Hct, eosinophil, neutrophil, SGOT and blood creatinine. The level of urinary tt-MA as a marker of benzene exposure correlated with haematological and biochemical changes in the blood, suggesting that the gasoline station workers were affected by benzene exposure. Moreover, the current study suggests that early detection of haematological abnormalities may be possible by analysing biomarkers of their effects through regular health surveillance of workers.
Full article
(This article belongs to the Collection Occupational Health and Safety in A Changing World: Realities, Challenges and Perspectives)
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Open AccessArticle
Tailored Incident Investigation Protocols: A Critically Needed Practice
by
Ahmed Jalil Al-Bayati
Safety 2024, 10(2), 37; https://doi.org/10.3390/safety10020037 - 11 Apr 2024
Abstract
Construction scholars and practitioners have identified a repetitive pattern of direct causes leading to both fatal and non-fatal injuries among construction workers. Over the years, direct causes such as falls, electrocutions, and being struck have consistently represented a substantial proportion of recorded and
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Construction scholars and practitioners have identified a repetitive pattern of direct causes leading to both fatal and non-fatal injuries among construction workers. Over the years, direct causes such as falls, electrocutions, and being struck have consistently represented a substantial proportion of recorded and reported injuries in the United States. One potential factor contributing to this repetition is the absence of root cause investigations for incidents. Incident investigations should focus on system deficiencies and shortcomings instead of individual behaviors. While the identification of incident root causes provides the needed information to eliminate the direct causes, it is inherently complex. Recently, the use of tailored incident investigation protocols as a practical and systematically conducted method was suggested to uncover the root causes of incidents, subsequently assisting in reducing their recurrence. To illustrate the feasibility of such an approach, this article provides a step-by-step guide to creating a tailored investigation protocol for revealing the root causes of arc flash incidents by utilizing a panel of safety experts. In addition, this study demonstrates the feasibility of developing tailored investigation protocols for other common causes, such as falls and electrocutions. Tailored investigation protocols streamline the identification of potential root causes to a manageable number, relying on subject matter experts. Consequently, they enhance learning from incidents by mitigating investigators’ biases and potential lack of experience. Safety practitioners can use the method presented in this article to create tailored investigation protocols based on their working environment to improve learning for occupational injuries.
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(This article belongs to the Special Issue Safety Performance Assessment and Management in Construction)
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Open AccessArticle
Bio-Risk Management Systems: Biosafety Assessment in COVID-19 Referral Hospitals in Indonesia
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Windri Handayani, Anom Bowolaksono, Fatma Lestari, Abdul Kadir, Saraswati Andani Satyawardhani, Duta Liana, Alyssa Zahwa Ananda and Saravanan Gunaratnam
Safety 2024, 10(2), 36; https://doi.org/10.3390/safety10020036 - 08 Apr 2024
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Numerous hospital laboratories in Indonesia need to implement improved bio-risk management (BRM) systems. There are many potential biohazards in laboratory activities that can impact health and the environment, leading to laboratory incidents. To minimize the impact and occurrence of such incidents, it is
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Numerous hospital laboratories in Indonesia need to implement improved bio-risk management (BRM) systems. There are many potential biohazards in laboratory activities that can impact health and the environment, leading to laboratory incidents. To minimize the impact and occurrence of such incidents, it is necessary to evaluate the implementation of BRM in every hospital laboratory that uses biological agents. This study was conducted in eight COVID-19 reference hospitals in Indonesia in the regions of Sumatra, Kalimantan, and Java, which have committed to implementing BRM systems in their laboratory activities. This research employed a descriptive study design and quantitative methods, with the aim of analyzing and evaluating the implementation of BRM systems in laboratories by assessing the achievements and gap analysis obtained from each laboratory. This research utilized primary data in the form of checklist forms referencing ISO 35001:2019 for the laboratory BRM system. Then, the assessments were based on virtual interviews conducted by the researcher with laboratory personnel as the primary data. The evaluation conducted on gap analysis from the seven clauses in ISO 35001:2019 across all hospitals revealed large gaps, particularly in three clauses: leadership, support, and performance. However, the aspects concerning organization, improvement, and performance evaluation were relatively satisfactory. Hence, there is a need for further improvement in leadership, support, and performance evaluation clauses. Additionally, it is essential to highlight the importance of comprehensive performance assessment, including proactive audits and continuous enhancements to achieve optimal bio-risk management.
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Open AccessArticle
Monitoring Occupational Radiation Dose in Radiography Students: Implications for Safety and Training
by
Mohamed Abuzaid, Zarmeena Noorajan, Wiam Elshami and Manal Ibham
Safety 2024, 10(2), 35; https://doi.org/10.3390/safety10020035 - 04 Apr 2024
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Background: This study aimed to investigate the occupational exposure of undergraduate radiography students to ionising radiation and evaluate the effectiveness of safety protocols and training in reducing radiation exposure. Methods: This study tracked undergraduate radiography students from the University of Sharjah, UAE, using
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Background: This study aimed to investigate the occupational exposure of undergraduate radiography students to ionising radiation and evaluate the effectiveness of safety protocols and training in reducing radiation exposure. Methods: This study tracked undergraduate radiography students from the University of Sharjah, UAE, using thermoluminescent dosimeters (TLDs) from 2015 to 2023. TLD readings were conducted every 15 weeks during 384 h of clinical placement. This study encompassed various radiographic procedures, and the TLDs were used to measure shallow (HP (0.07)) and deep doses (HP (10)). Results: A data analysis from 599 dosimeters revealed an average of 74 students annually. The average effective doses for HP (10) and HP (0.07) were 0.227 mSv and 0.222 mSv, respectively. These doses were well-below the recommended annual limits. Conclusion: This study’s results indicated that radiography students’ occupational radiation exposure during clinical training was within the safe limits, demonstrating the effectiveness of training and safety protocols. A comparison with international data corroborated the low exposure levels. Clinical training is essential for radiography students, and this study highlights the success of safety protocols in minimising occupational radiation exposure. Continuous monitoring and education are crucial to sustaining these positive outcomes.
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Open AccessArticle
The BowTie as a Digital Twin: How a BowTie Looks Different from a Data Perspective
by
Paul Singh, Coen van Gulijk and Neil Sunderland
Safety 2024, 10(2), 34; https://doi.org/10.3390/safety10020034 - 31 Mar 2024
Abstract
This work follows from a research project for safety management system re-engineering that turned a safety BowTie into a digital twin. A digital twin is a model embedded in software that mirrors a specific aspect of a real system; the aspect in this
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This work follows from a research project for safety management system re-engineering that turned a safety BowTie into a digital twin. A digital twin is a model embedded in software that mirrors a specific aspect of a real system; the aspect in this case is the risk space associated with a process. The well-known BowTie is the model that turns out to be singularly well suited as a digital twin from the risk perspective as it maps out the risk space together with real-life controls. However, for a BowTie to be a high-fidelity digital twin of a real system, the rules and processes for designing and operating a BowTie are changed.
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(This article belongs to the Special Issue Safety and Risk Management in Process Industries)
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Open AccessArticle
Socio-Cognitive Determinants of Pedestrians’ Intention to Cross on a Red Light Signal: An Application of the Theory of Planned Behaviour
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Boško Matović, Aleksandra Petrović, Milanko Damjanović, Aleksandar Bulajić and Vladimir Ilić
Safety 2024, 10(1), 33; https://doi.org/10.3390/safety10010033 - 21 Mar 2024
Abstract
The present research describes the development and validation of a self-reported instrument that measures the determinants of pedestrians’ intention to violate traffic rules, based on the theory of planned behaviour. Moreover, the research deals with the analysis of the predictive validity of an
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The present research describes the development and validation of a self-reported instrument that measures the determinants of pedestrians’ intention to violate traffic rules, based on the theory of planned behaviour. Moreover, the research deals with the analysis of the predictive validity of an extended theoretical framework of the theory of planned behaviour in relation to pedestrians’ intention to violate. Based on the quota sample, adult pedestrian respondents (n = 383) completed a questionnaire assessing the relevant variables. Valid and reliable scales were developed, and they measure subjective, descriptive, normative, and personal norms, cognitive and affective attitudes, perceived behavioural control, habit formation, and behavioural intention concerning pedestrians’ misdemeanour. Hierarchical regression analysis indicated that all components, except descriptive norms, were significant simultaneous predictors of pedestrians’ intention to violate. The most powerful predictor is the personal norm. Overall, the findings considerably support the concept of the extended theoretical framework of the theory of planned behaviour.
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Open AccessPerspective
Robotics, Artificial Intelligence, and Drones in Solar Photovoltaic Energy Applications—Safe Autonomy Perspective
by
Olufemi Olayiwola, Miles Elsden and Mahmoud Dhimish
Safety 2024, 10(1), 32; https://doi.org/10.3390/safety10010032 - 18 Mar 2024
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While there is evidence of substantial improvement in efficiency and cost reduction from the integration of Robotics, Artificial Intelligence, and Drones (RAID) in solar installations; it is observed that there is limited oversight by international standards such as the International Electrotechnical Commission (IEC)
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While there is evidence of substantial improvement in efficiency and cost reduction from the integration of Robotics, Artificial Intelligence, and Drones (RAID) in solar installations; it is observed that there is limited oversight by international standards such as the International Electrotechnical Commission (IEC) in terms of the hazards and untapped potentials. This is partly because it is an emerging application and generally burdened with social acceptability issues. Thus, the safety regulations applied are adaptations of device-specific regulations as deemed fit by individual companies. Also, due to the fast-paced technological development of these platforms, there is huge potential for applications that are not currently supported by the device-specific regulations. This creates a multi-faceted demand for the establishment of standardized, industry-wide polices and guidelines on the use of RAID platforms for Solar PV integrations. This work aims to address critical safety concerns by conducting a comprehensive high-level system examination applicable to the monitoring and maintenance of Solar PV systems. Standard safety assurance models and approaches are examined to provide a safe autonomy perspective for Solar PVs. It is considered that, as RAID applications continue to evolve and become more prevalent in the Solar PV industry, standardized protocols or policies would be established to ensure safe and reliable operations.
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Open AccessArticle
A Comparative Approach Study on the Thermal and Calorimetric Analysis of Fire-Extinguishing Powders
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An-Chi Huang, Fang-Chao Cao and Xin-Yue Ma
Safety 2024, 10(1), 31; https://doi.org/10.3390/safety10010031 - 15 Mar 2024
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This study offers a comprehensive evaluation of the effectiveness of expansible graphite (EG) and potassium bicarbonate (KHCO3) in suppressing metal fires, which are known for their high intensity and resistance. Our assessment, utilizing thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR),
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This study offers a comprehensive evaluation of the effectiveness of expansible graphite (EG) and potassium bicarbonate (KHCO3) in suppressing metal fires, which are known for their high intensity and resistance. Our assessment, utilizing thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM), revealed that compositions of EG–KHCO3 can endure temperatures of up to 350 °C, indicating their thermal resilience. The 3:1 EG–KHCO3 mixture demonstrated exceptional performance in fire suppression tests by extinguishing sodium flames in a mere 20 s, using approximately 50 g of the agent. This highlights a substantial improvement in efficiency. In addition, FTIR analysis identified important gaseous compounds released during decomposition, while XRD and SEM techniques confirmed the advantageous insertion of KHCO3 into the EG matrix, enhancing its resistance to heat and chemical reactions. The mixture with a ratio of 3:1 also demonstrated a higher cooling rate of 2.34 °C/s within the temperature range of 350 to 200 °C. The results emphasize the potential of EG–KHCO3 compositions, specifically in a 3:1 ratio, for efficient fire management by integrating fire suppression, heat resistance, and quick cooling. Subsequent investigations will prioritize the evaluation of these compositions across different circumstances and the assessment of their environmental and industrial viability.
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Open AccessArticle
Determination of Occupational Exposure to Ultrafine Particles in Different Sectors of Activity
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Fernando Miguel Moreira, Ana Ferreira and Nelson Barros
Safety 2024, 10(1), 30; https://doi.org/10.3390/safety10010030 - 15 Mar 2024
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The primary sources of ultrafine particulate matter are linked to human activity. Certain particulate emissions, particularly those of a finer nature, can significantly impact human health, making them one of the most concerning pollutants. Ultrafine particles (UFPs), which have a diameter of less
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The primary sources of ultrafine particulate matter are linked to human activity. Certain particulate emissions, particularly those of a finer nature, can significantly impact human health, making them one of the most concerning pollutants. Ultrafine particles (UFPs), which have a diameter of less than 100 nm, are of particular concern due to their impact on human health and the difficulty in controlling them. The concentration of ultrafine particles (UFPs) in the workplace is a growing concern and is classified as an emerging risk. Workers may be exposed to UFPs through inhalation, skin absorption, ingestion, or a combination of these routes. This study aims to determine the levels of UFP exposure among workers in environments with varying direct particle emission patterns. Measurements were conducted to compare the results with the levels recommended by the WHO. The study monitored industrial workplaces with direct particulate matter emissions, such as a carpentry workshop and a bakery, as well as social sector sites without or almost without direct particle emissions, such as a school and a health clinic. One conclusion drawn from this study is that all tasks and occupations are susceptible to high levels of UFPs, exceeding WHO recommended values in virtually all monitored environments. Therefore, monitoring and controlling UFPs is crucial. Further in-depth studies on this subject are also necessary.
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(This article belongs to the Collection Occupational Health and Safety in A Changing World: Realities, Challenges and Perspectives)
Open AccessArticle
Development and Reliability Review of an Assessment Tool to Measure Competency in the Seven Elements of the Risk Management Process: Part Three—Evaluation of the Group Results from the RISK Tool
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Garry Marling, Tim Horberry and Jill Harris
Safety 2024, 10(1), 29; https://doi.org/10.3390/safety10010029 - 14 Mar 2024
Abstract
This study used ratings to form teams of participants with different risk management competence levels to determine if a collectively optimised team performed a risk management exercise better than a marginally or a sub-optimised team. This paper also determined whether team performance was
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This study used ratings to form teams of participants with different risk management competence levels to determine if a collectively optimised team performed a risk management exercise better than a marginally or a sub-optimised team. This paper also determined whether team performance was better than individual performance on a risk management exercise. An experimental group was split into three teams of six participants based on their individual risk scenario exercise outcomes. The collectively optimised team had at least one member rated as having some high-level or expert competency in one of the seven risk management process elements. So, jointly, the group had this competency level in all elements. Similarly, the marginally optimised team’s members were rated as having just above average or high-level competency in the seven elements. Likewise, the sub-optimised team’s members were rated as having just above average competency, just below average, or no competency in the seven elements. Each team undertook the risk scenario exercise, and two observers rated their performances, as recorded on a video camera. The results were that the collectively optimised team performed better in each of the seven risk management elements than the other teams (the marginally optimised or the sub-optimised team). However, a significant difference was only evident between the collectively optimised and sub-optimised teams across all elements. Also, the teams performed better in each of the seven elements than individuals. These results imply that a team collectively optimised in the seven elements of the risk management process can better perform a risk management process than a sub-optimised team. These competency outcomes could be used to assemble risk management teams that are collectively optimised, leading to better results from the risk management process.
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(This article belongs to the Special Issue Risk and Safety Analysis of Industry)
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Open AccessArticle
Personal Competencies for Work–Family Integration and Its Relationship with Productivity and Comprehensive Health in Salaried Professionals
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Crisdalith Cachutt-Alvarado, Ignacio Méndez-Gómez-Humaran and Jonás Velasco-Álvarez
Safety 2024, 10(1), 28; https://doi.org/10.3390/safety10010028 - 14 Mar 2024
Abstract
Work–Family Integration (WFI) is the decision-making process that enables an individual to effectively balance work, family, and personal responsibilities, generating a level of personal satisfaction aligned with the management of these demands. This research aims to explore the potential links between personal competencies
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Work–Family Integration (WFI) is the decision-making process that enables an individual to effectively balance work, family, and personal responsibilities, generating a level of personal satisfaction aligned with the management of these demands. This research aims to explore the potential links between personal competencies facilitating work and family integration (WFI Competencies), employer-provided support (WFI Support), perceived satisfaction in role integration (WFI Satisfaction), and their association with organizational performance indicators and the overall health of professionals in dependent employment. Data were obtained via an online questionnaire administered to 270 professionals possessing a university education or higher, employed in public or private organizations spanning various sectors in Venezuela. The data were subsequently analyzed utilizing Structural Equation Modeling (SEM). The study was divided into two main parts: the factorial analysis (both exploratory and confirmatory) of measurement models and the analysis of the relationships and modeling inherent to the structural model. Initially, two diagnostic instruments were developed, one for WFI Competencies and another for WFI Indicators; though applied simultaneously, their structuring and validation were conducted separately. In the subsequent phase, conceptual models for structural analysis were defined. A positive relationship was observed between WFI Support and WFI Satisfaction, corroborating findings from previous research. The relationships between WFI Competencies and Satisfaction led to insights into the necessity of training to strengthen the personal decision-making process under the dual pressures of work and family roles. Future longitudinal studies could elucidate the effects of relationships within such programs on WFI Satisfaction. Concerning organizational indicators, this study found that WFI Satisfaction positively correlates with organizational commitment, enhancing work productivity and mitigating negative health effects. This research presents a model that could be replicated in other countries and with various sample types, facilitating comparative analyses that enrich the body of knowledge on this subject.
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(This article belongs to the Collection Occupational Health and Safety in A Changing World: Realities, Challenges and Perspectives)
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Cognitive and Motivational Antecedents of Different Driving Styles in a Sample of Lithuanian Drivers
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Justina Slavinskienė and Auksė Endriulaitienė
Safety 2024, 10(1), 27; https://doi.org/10.3390/safety10010027 - 13 Mar 2024
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The aim of this study was to assess whether road risk, road hazard perception skills, and attitudes towards risky driving are significant psychological antecedents of different driving styles. The study sample consisted of 446 non-professional drivers (with an average age of 32.6 years)
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The aim of this study was to assess whether road risk, road hazard perception skills, and attitudes towards risky driving are significant psychological antecedents of different driving styles. The study sample consisted of 446 non-professional drivers (with an average age of 32.6 years) and 200 professional drivers (with an average age of 47.7 years) from Lithuania. The study questionnaire included demographic questions, a multidimensional driving style assessment, a Lithuanian version of a hazard prediction test, a risk perception scale, and a subjective evaluation of driving competenc3 (perceptual, motor, and safety driving skills), as well as an evaluation of attitudes towards risky driving. The results confirmed that cognitive factors, together with attitudes towards driving and demographic factors, are important for understanding the origins of different driving styles. Cognitive factors like hazard perception and risk perception skills were found to be significant predictors of anxious, careless, and angry driving styles, mainly for professional drivers. Attitudes towards risky driving together with demographic characteristics and cognitive factors were found to important in predicting anxious, careless, and angry driving styles among professional as well as non-professional drivers. The subjective evaluation of driving competence (driving skills) was found to be crucial in predicting all four driving styles, but only in the non-professional drivers sample.
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(This article belongs to the Special Issue Traffic Safety Culture)
Open AccessArticle
Deep Learning for Detection of Proper Utilization and Adequacy of Personal Protective Equipment in Manufacturing Teaching Laboratories
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Adinda Sekar Ludwika and Achmad Pratama Rifai
Safety 2024, 10(1), 26; https://doi.org/10.3390/safety10010026 - 07 Mar 2024
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Occupational sectors are perennially challenged by the potential for workplace accidents, particularly in roles involving tools and machinery. A notable cause of such accidents is the inadequate use of Personal Protective Equipment (PPE), essential in preventing injuries and illnesses. This risk is not
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Occupational sectors are perennially challenged by the potential for workplace accidents, particularly in roles involving tools and machinery. A notable cause of such accidents is the inadequate use of Personal Protective Equipment (PPE), essential in preventing injuries and illnesses. This risk is not confined to workplaces alone but extends to educational settings with practical activities, like manufacturing teaching laboratories in universities. Current methods for monitoring and ensuring proper PPE usage especially in the laboratories are limited, lacking in real-time and accurate detection capabilities. This study addresses this gap by developing a visual-based, deep learning system specifically tailored for assessing PPE usage in manufacturing teaching laboratories. The method of choice for object detection in this study is You Only Look Once (YOLO) algorithms, encompassing YOLOv4, YOLOv5, and YOLOv6. YOLO processes images in a single pass through its architecture, in which its efficiency allows for real-time detection. The novel contribution of this study lies in its computer vision models, adept at not only detecting compliance but also assessing adequacy of PPE usage. The result indicates that the proposed computer vision models achieve high accuracy for detection of PPE usage compliance and adequacy with a mAP value of 0.757 and an F1-score of 0.744, obtained with the YOLOv5 model. The implementation of a deep learning system for PPE compliance in manufacturing teaching laboratories could markedly improve safety, preventing accidents and injuries through real-time compliance monitoring. Its effectiveness and adaptability could set a precedent for safety protocols in various educational settings, fostering a wider culture of safety and compliance.
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Open AccessArticle
Effective Trigger Speeds for Vehicle Activated Signs on 20 mph Roads in Rural Areas
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Adebola Olowosegun, Grigorios Fountas and Adrian Davis
Safety 2024, 10(1), 25; https://doi.org/10.3390/safety10010025 - 06 Mar 2024
Abstract
This paper aims to offer novel empirical evidence as to the identification of the most effective Trigger Speeds (TS) for Vehicle-Activated Signs (VAS) in rural areas. To achieve this, an experimental study was carried out in the area of Scottish Borders, UK, in
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This paper aims to offer novel empirical evidence as to the identification of the most effective Trigger Speeds (TS) for Vehicle-Activated Signs (VAS) in rural areas. To achieve this, an experimental study was carried out in the area of Scottish Borders, UK, in settlements with 20 mph speed limits. To determine the effective trigger speeds for VAS, in terms of reducing vehicle speeds, a comparative quantitative analysis was conducted using traffic and speed data collected during different waves of a traffic survey, for which various TS settings were deployed (24 mph, 28 mph and 35 mph). The descriptive analysis showed that the 24 mph TS threshold seems to be more effective compared to the other TS settings considered, mainly in terms of reducing the 85th percentile speeds. The 28 mph threshold was identified to yield slightly lower mean speeds compared to the other TS settings. Non-parametric and parametric statistical tests were conducted on the basis of approximately 2.8 million speed observations to identify any statistically significant speed differences under various TS settings. Overall, the findings of this study show that the application of VAS in addition to 20 mph speed limits helps reduce vehicle speeds. In particular, setting a TS to remind drivers, especially those driving between 21–24 mph, that they should slow down has led to statistically significant reductions in speeds driven. This provides road safety benefits both from the reduction in kinetic energy in the transport system, any consequent crash-related outcomes, and also by improving perceived safety for all who use and live close to roads where 20 mph speed limits augmented with VAS have been implemented.
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(This article belongs to the Special Issue Human Factors in Road Safety and Mobility)
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Effects of Behavior-Based Driver Feedback Systems on the Speeding Violations of Commercial Long-Haul Truck Drivers
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Anuj K. Pradhan, Brian T. W. Lin, Claudia Wege and Franziska Babel
Safety 2024, 10(1), 24; https://doi.org/10.3390/safety10010024 - 04 Mar 2024
Abstract
A third of large truck crashes are associated with driver-related factors, especially speeding. This study aimed to examine the impact of behavior-based safety (BBS) programs on speeding. Speeding data were examined from a trucking fleet that had incorporated a BBS program using in-vehicle
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A third of large truck crashes are associated with driver-related factors, especially speeding. This study aimed to examine the impact of behavior-based safety (BBS) programs on speeding. Speeding data were examined from a trucking fleet that had incorporated a BBS program using in-vehicle data recorders (IVDR) and post hoc feedback. Speeding events were examined over 37 weeks in two stages—an initial 4-week period (Stage 1), and the final 30 weeks (Stage 2). In Stage 1, data were collected without any feedback. In Stage 2, a subset of the drivers received feedback. A cluster analysis was performed based on the speeding event rate from Stage 1. The analysis yielded two clusters per group based on risk. The higher-risk cluster contained fewer drivers and showed a greater reduction in speeding with the BBS program, compared to the lower-risk cluster. Both clusters showed significant decreases in speeding across Stage 2. The BBS program was associated with reduced speeding, with a more pronounced reduction for the higher-risk drivers, highlighting the role of BBS programs in trucking and underscoring the importance of driver sub-groups. Targeted safety approaches may be more efficient and yield higher safety benefits than a one-size fits all approach.
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Which Technologies Make Australian Farm Machinery Safer? A Decision Support Tool for Agricultural Safety Effectiveness
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Amity Latham, Zoran Najdovski, Rebecca Bartel and Jacqueline Cotton
Safety 2024, 10(1), 23; https://doi.org/10.3390/safety10010023 - 26 Feb 2024
Abstract
This project combined systems engineers, farm safety researchers, work health and safety inspectorate and policymakers with the aim of designing a way in which to reduce fatal farm injury caused by run-overs and roll-overs by tractors and side-by-side vehicles. The team made comparisons
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This project combined systems engineers, farm safety researchers, work health and safety inspectorate and policymakers with the aim of designing a way in which to reduce fatal farm injury caused by run-overs and roll-overs by tractors and side-by-side vehicles. The team made comparisons between farm machinery and powered mobile plant that is used in the industrial manufacturing, warehousing and logistics, mining, and construction sectors. Current and emerging safety technologies and engineering solutions were collated. Safety standards, legislated engineering controls, retrofit designs, and known ways in which farmers’ workaround safety features were considered. These elements were used as criteria to propose a way to resolve which safety technologies or engineering controls should be recommended for aftermarket retrofitting or incorporated at the original equipment manufacturer design stage. The concept of measuring safety effectiveness to prevent fatal farm injury emerged. This developed into a score sheet and a corresponding matrix to highlight engineering strength and industry acceptance. The project resulted in the conceptual design of the agricultural safety effectiveness score (ASES). The next phase is a multi-stakeholder validation process and a protocol for the scoring system. It requires a hypothesis to test the theory that when safety technologies and engineering solutions are mature in other industries or if they are associated with agricultural productivity gains, their adoption into the agricultural sector is more likely, which in turn will reduce the incidence of tractor and side-by-side run-overs and roll-overs on farms.
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(This article belongs to the Special Issue Farm Safety II)
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