Safety, Volume 10, Issue 1 (March 2024) – 33 articles

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

Pile-up (PU) crashes, which involve multiple collisions between more than two vehicles within a brief timeframe, carry substantial consequences, including fatalities and significant damages. This study aims to investigate the real-time traffic, environmental, and crash characteristics and their interactions in terms of their contributions to severe PU crashes, which have been understudied. This study investigates and interprets the effects of Total Volume/Capacity (TV/C), “Heavy Vehicles Volume/Total Volume” (HVV/TV), and average speed. For this purpose, the PU crash severity was modelled and interpreted using the crash and real-time traffic data of Iran’s freeways over a 5-year period. Among six machine learning methods, the CatBoost model demonstrated superior performance, interpreted via the SHAP method. The results indicate that avg.speed > 90 km/h, TV/C < 0.6, HVV/TV ≥ 0.1, horizontal curves, longitudinal grades, nighttime, and the involvement of heavy vehicles are associated with the risk of severe PU crashes. Additionally, several interactions are associated with severe PU crashes, including the co-occurrence of TV/C ≈ 0.1, HVV/TV ≥ 0.25, and nighttime; the interactions between TV/C ≈ 0.1 or 0.45, HVV/TV ≥ 0.25, and avg.speed > 90 km/h; horizontal curves and high average speeds; horizontal curves; and nighttime. Overall, this research provides essential insights into traffic and environmental factors driving severe PU crashes, supporting informed decision-making for policymakers. Full article

Work-related musculoskeletal disorders (WMSD) are highly prevalent among supermarket cashiers. These disorders are frequently related to the adoption of awkward postures and manual materials handling. This study aimed to analyze musculoskeletal loadings in supermarket cashiers, considering the handling of different products and different checkout conditions. To accomplish this, we employed an inertial motion capture system to measure full-body kinematics while simulating 19 cashier tasks. The study included five female cashiers from a supermarket in Northern Portugal, ranging in age from 19 to 61 years old. Using joint angles, material load, and muscle function as input parameters, we conducted the musculoskeletal loadings assessment using the Rapid Upper Limb Assessment (RULA) and Rapid Entire Body Assessment (REBA) methods. Results showed that RULA scores were higher for the microtasks that involved product scanning. Regarding microstasks analyzed by REBA, the replacement of paper rolls for the receipt machine at the checkout counter yields the highest scores. Based on these findings, there is a compelling need to redesign supermarket checkout workstations to alleviate the physical demands placed on cashiers and to ensure organizational sustainability. Full article

Air traffic controllers (ATCOs) play a substantial part in securing the safety of flights, such that a compromise of the ATCOs’ performance may lead to tragedies. Given the mental workload that comes with the nature of ATCOs’ work, this study intends to investigate the impact of mental workload on ATCOs’ job performance and identify conditional factors that could mitigate the mental workload–ATCOs’ job performance relationship. Underpinned by the job demands–resources theory, a framework was developed to investigate the impact of job demands (mental workload) on job performance and whether personal resources (mindfulness and social work support) weaken the relationship. A total of 324 ATCOs across Saudi Arabia responded to the questionnaire. There were three notable findings. First, mental workload was indeed found to bring detrimental effects to ATCOs’ job performance. Second, mindfulness played a mitigating role, where more mindful ATCOs demonstrated less workload effect on performance. Thirdly, social work support also played a mitigating role, where ATCOs who perceived receiving greater job support experienced less detrimental impact from the workload on performance. This study verified the negative linkages between mental workload and job performance and identified the boundary conditions (mindfulness and social work support) that weaken the relationship. The limitations and future research directions are then discussed. Full article

Various jobs, indoors and outdoors, are subjected to severe cold temperatures during daily activities. Extremely low-temperature exposure and work intensity affect health, safety, and occupational performance. This work aimed to assess the physiological and thermal sensation responses before, during, and following a 60 min exposure to cold (−20 °C), during which occupational activities were developed. Using ingestible telemetric temperature pills, eight skin temperature sensors, blood pressure equipment, and the Thermal Sensation Questionnaire, experiments were conducted with 11 healthy male volunteers wearing highly insulating cold protective clothing. The most notorious alterations were reported in mean skin temperatures and thermal sensation responses during the first 20 min of cold exposure. Among the eight skin temperature points, the forehead and left hand showed a higher sensitivity to cold. The mean core temperature reported significant variations throughout the protocol, with decreases during the initial 10 min of cold exposure and posterior increases despite the cold environment. Blood pressure showed slight increases from the initial to the recovery period. Overall, outcomes contribute to current scientific knowledge on physiological and perception responses in extremely cold environments while describing the influence of protective clothing and occupational activities on these responses. Future research should be developed with additional skin temperature measurements in the extremities (fingers, face, and toes) and the analysis of thermal sensation potential associations with performance changes, which can also be of great significance for future thermal comfort models. Full article

As a prominent organizational issue, there was limited evidence in the literature regarding the relationship between organizational strategy, workplace health, safety, and wellbeing, and performance measurements that demonstrate a measurable impact on organizational performances. Based on this gap in the literature, the purpose of the study was to examine business practices, health, safety, and wellbeing practices, and measurement systems to inform the development of a health, safety, and wellbeing strategy and employee engagement framework in order to add strategic value to businesses beyond standard practice. An exploratory mixed methods study, consisting of eight semi structured interviews and ninety-five survey responses from a cross section of private and public sectors leaders and health, safety, and wellbeing and human capital professionals was undertaken. Thematic analyses and exploratory factor analyses revealed a seven-factor health, safety, and wellbeing strategy framework that integrates key concepts, resilience engineering, wellbeing, health and safety management, employee engagement, risk management, and corporate governance. The final strategy framework provides empirical evidence supporting a suitable framework for businesses to improve individual and organizational performance. Full article

Many aspects of society were impacted by the COVID-19 pandemic, including physical health, psychological well-being, social dynamics, and the economy. The construction sector experienced a significant influence from the pandemic. This research aimed to analyze the relationship between psychosocial factors (individual, home, and work factors) and the level of work distress among construction sector workers during the COVID-19 pandemic. This study employed a quantitative analytical approach with a cross-sectional design. Data collection took place in November–December 2021, and the total sample that met the inclusion criteria was 110 respondents. Work distress and psychosocial data were collected using a questionnaire that had undergone validity and reliability tests. Univariate analyses (frequency distribution), bivariate analyses (chi-square test), and multivariate analyses (multiple logistic regression tests) were conducted to analyze the data. The research revealed that the most closely related variables to the work distress levels were work duration, followed by employment status and career opportunities. This study underscores the importance of regulating working hours and providing opportunities for permanent employment and career advancement for the mental health of construction workers. Full article

(1) Background: Mobile movement analysis systems, for example, those based on Inertial Measurement Units (IMUs), enable digital real-time methods of collecting data in workplace ergonomics, but the relationship between observational method scores such as Rapid Upper Limb Assessment (RULA), upper-body posture, and their influence on musculoskeletal discomfort, has not yet been well investigated. This field study aimed to evaluate the relationship of these variables in two different target groups: production and office workers. (2) Methods: There were 64 subjects (44 men and 20 women) participating. Data collection was divided into two categories: (1) Cornell Musculoskeletal Discomfort Questionnaire (CMDQ) (n = 64) and 3D stereophotogrammetric posture analysis (n = 58), and (2) Investigation of workload via IMU-based motion capture (MoCap) and the Borg CR-10 body map (n = 24). Correlation tests and regression analysis were performed using SPSS and MATLAB software to examine the relationship between the upper-body posture and RULA. Multivariate analysis of variance (MANOVA) was applied to examine group differences. (3) Results: The findings did not support the authors’ hypothesis that posture risk at work significantly correlates with static upper-body posture and musculoskeletal discomfort. Pelvic tilt had a weak but significant influence on RULA. The data revealed interesting trends in physical exertion, musculoskeletal discomfort, and differences between production and office workers. However, the statistical analysis did not support this. Such approaches have the potential to enhance the accuracy of assessment outcomes and, in turn, provide a stronger foundation for enhancing ergonomic conditions. Full article

Noise is a major physical hazard in agricultural activities, and numerous research activities have managed to detect its effects, resulting in surveys and measurements which help to define exposure limits, prevention methods, and control strategies. This review aims to collect and analyse the data from research studies and to provide a comprehensive overview on the subject. Thus, a set of 81 papers, gathered from the Scopus and PubMed scientific databases, has been analysed to provide information regarding the evolution of noise exposure levels over time, to highlight findings on noise-induced hearing loss (NIHL), and to list strategies for noise prevention and control in agriculture. Bibliographic research showed that noise measurements between 1991 and 2022, included in scientific research on farming, forestry, and animal husbandry, mainly reported values beyond the threshold of 85 dB(A); furthermore, several research activities on NIHL showed that farmers’ family members and children are often exposed to high levels of noise. Lastly, an analysis of the prevention and control strategies over time is provided, focusing on prevention programmes, screening, and the use of hearing protection devices (HPD). The identified literature suggests that additional efforts are required in regards to machinery design relating to the socio-technical aspects of agricultural activities and that side-effects of NIHL, as well as the negative impact of noise on other risks, might deserve further investigation. Full article

This exploratory study investigated whether using the Pedals Emergency Stop© interactive driving simulator exercise improved the understanding and performance of emergency braking among novice teen drivers. Seventy-one high school driver education students (aged 15–19) participated. All of the teens completed the Pedals Emergency Stop© interactive exercise driving simulator task and then an on-road ABS exercise in a driver’s education vehicle; there was no control group. Students’ ability to complete the simulator-based emergency braking task increased from an initial passing rate of only 18.3% to a maximum of 81.7% by the end of the simulation exercise. A positive trend was observed over successive simulator trials, with the linear effect explaining 51.1% of the variance in emergency stopping “pass” rates using the simulator task. In addition, participants who passed more trials during the Pedals Emergency Stop© simulator exercise were 12.3% more likely to fully activate the ABS during the on-road emergency stop activity using the driver’s education vehicle. Post-study surveys revealed that 95% of the participants improved their understanding of ABS as a result of the simulation-based training, and 98% felt there was a positive impact from the driving simulation exercise on their real-world emergency braking capabilities. Participants highly endorsed the Pedals Emergency Stop© exercise for ABS education and refresher training, with a rating of 4.7 out of 5. This study emphasizes the potential benefits of incorporating simulator-based exercises into driver education and training, with the long-term goal of promoting safe driving behaviors and outcomes. Full article

Background: Given the lack of previous studies on adverse events (AEs) in the area of occupational healthcare in Spain, it is very important to begin to understand this phenomenon in order to act on it. The objective was to accurately quantify AE occurring in occupational healthcare in MC Mutual during May 2021. Methods: We conducted a review of a representative random sample of 250 clinical records to identify AEs through an active search audit, focused on the frequency, type, severity, and preventability of these events, categorized using standardized scales. Results: We detected seven AEs in the sample of clinical records, representing 3% AEs per clinical record, while in the APEAS Spanish Study, they were detected in 10% of patients. The most frequent AE type was postoperative, followed by medication and diagnostic delay. The AEs were of intermediate severity and high severity and with a variable degree of being preventable. Conclusions: The detection of AEs has been useful in the development of projects and action plans such as specific training courses, safety patient newsletters, ambulatory risk maps, and treatment plans framed in the official certification of patient safety. These results should be evaluated in other companies similar to MC Mutual. Full article

Lower back pain (LBP) describes pain of indeterminate duration between the lower edge of the ribs and the buttocks. LBP hinders movement, quality of life, and mental well-being, and limits work activities and engagement with family and friends. LBP represents a public health problem, and most workers are expected to experience LBP symptoms throughout their working lives. The study’s main objective was to characterize LBP in the hospitality population of the province of León, Spain, determining the risk factors. A pilot study with a cross-sectional observational design was developed following the guidelines of Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) for 150 Spanish hotel workers. Sociodemographic and lifestyle, occupational, and clinical data related to LBP were obtained through surveys. The annual prevalence of LBP in this study was 87.1% which was higher in women. A significant relationship (p < 0.05) was obtained between sex, income, smoking, sleep quality, and all labor variables with LBP. In addition, the Fear Avoidance Beliefs Questionnaire (FABQ) results revealed that 49% of the participants had a score > 14. Also, 83.3% of patients with >6 annual LBP crises suffered from sciatica. Once the results were known, preventive intervention would be needed to reduce these main risk factors for LBP for hospitality workers. Full article

This study explores the complex connections among various socioeconomic, demographic, and technological aspects and their impact on fatal traffic accidents. Utilizing the Lasso polynomial regression model, this study explores the impact of demographic variables, including income, education, unemployment rates, and family size. Additionally, socioeconomic factors such as Gross Domestic Product (GDP) per capita, inflation rate, minimum wage, and government spending on transportation and infrastructure are examined for their impact on the occurrence of fatal accidents. This study also investigates the influence of technological advances in vehicles on the outcomes of traffic safety. The findings of this research reveal that certain factors, such as average, alcohol consumption, unemployment rate, minimum wage, and vehicle miles traveled (VMT), among others, have a substantial impact on the multifactorial model and play a considerable role in the frequency of fatal accident rates. The research results have significant implications for policymakers, highlighting the need for a comprehensive approach that accounts for the interdependence of economic indicators, behavioral patterns, and traffic safety outcomes. This study underscores the importance of considering a wide range of socioeconomic, demographic, and technological factors to develop effective policies and strategies to reduce fatal traffic accidents. Full article

Driver mental fatigue is considered a major factor affecting driver behavior that may result in fatal accidents. Several approaches are addressed in the literature to detect fatigue behavior in a timely manner through either physiological or in-vehicle measurement methods. However, the literature lacks the implementation of hybrid approaches that combine the strength of individual approaches to develop a robust fatigue detection system. In this regard, a hybrid temporal approach is proposed in this paper to detect driver mental fatigue through the combination of driver postural configuration with vehicle longitudinal and lateral behavior on a study sample of 34 diverse participants. A novel fully adaptive symbolic aggregate approximation (faSAX) algorithm is proposed, which adaptively segments and assigns symbols to the segmented time-variant fatigue patterns according to the discrepancy in postural behavior and vehicle parameters. These multivariate symbols are then combined to prepare the bag of words (text format dataset), which is further processed to generate a semantic report of the driver’s status and vehicle situations. The report is then analyzed by a natural language processing scheme working as a sequence-to-label classifier that detects the driver’s mental state and a possible outcome of the vehicle situation. The ground truth of report formation is validated against measurements of mental fatigue through brain signals. The experimental results show that the proposed hybrid system successfully detects time-variant driver mental fatigue and drowsiness states, along with vehicle situations, with an accuracy of 99.6% compared to state-of-the-art systems. The limitations of the current work and directions for future research are also explored. Full article

Advanced driver assistance systems (ADASs) have recently gained popularity as they assist vehicle operators in staying within safe boundaries, helping them thereby to prevent possible collisions. However, despite their success and development, most ADAS use common and deterministic warning thresholds for all drivers in all driving environments. This may occasionally lead to the issuance of annoying inadequate warnings, due to the possible differences between drivers, the changing environments and driver statuses, thus reducing their acceptance and effectiveness. To fill this gap, this paper proposes adaptive algorithms for commonly used warnings based on real-time traffic environments and driver status including distraction and fatigue. We proposed adaptive algorithms for headway monitoring, illegal overtaking, over-speeding, and fatigue. The algorithms were then tested using a driving simulator. Results showed that the proposed adaptive headway warning algorithm was able to automatically update the headway warning thresholds and that, overall, the proposed algorithms provided the expected warnings. In particular, three or four different warning types were designed to distinguish different risk levels. The designed real-time intervention algorithms can be implemented in ADAS to provide warnings and interventions tailored to the driver status to further ensure driving safety. Full article

Truck accidents are a prevalent global issue resulting in substantial economic losses and human lives. One of the principal contributing factors to these accidents is driver error. While analysing human error, it is important to thoroughly examine the truck’s condition, the drivers, external circumstances, the trucking company, and regulatory factors. Therefore, this study aimed to illustrate the application of HFACS (Human Factor Classification System) to examine the causal factors behind the unsafe behaviors of drivers and the resulting accident consequences. Bayesian Network (BN) analysis was adopted to discern the relationships between failure modes within the HFACS framework. The result showed that driver violations had the most significant influence on fatalities and multiple-vehicle accidents. Furthermore, the backward inference with BN showed that the mechanical system malfunction significantly impacts driver operating error. The result of this analysis is valuable for regulators and trucking companies striving to mitigate the occurrence of truck accidents proactively. Full article

(1) Background: Fall injuries in the home present a major health burden internationally for all age groups. One effective intervention to prevent falls is home modification, but safety is only increased if opportunities to install safety modifications are taken up. This study sought to identify factors that may lead to a higher uptake of no-cost home modifications when these are offered to people living in the community. (2) Methods: We studied 1283 houses in the New Zealand cities of New Plymouth and Wellington. Using logistic regression, we modelled the odds of uptake according to the number of access steps, the provider who was undertaking the modifications, occupant ethnicity, prior fall injury history, and age group. (3) Results: Homes with older residents (age 65+) had higher uptake rates (35% vs. 27% for other homes). Larger numbers of access steps were associated with higher uptake rates. There was indicative evidence that homes with Indigenous Māori occupants had a higher uptake of the modifications for one of the two providers, but not the other. (4) Conclusions: No-cost home safety modifications offered via cold calling are likely to have relatively low uptake rates but the households that do consent to the modifications may be those who are more likely to benefit from the concomitant increased safety. Full article

Facing the threat of SARS-CoV-2, several countries implemented protective measures to annihilate the waves of the pandemic. Apart from quarantine, social distancing, frequent disinfection, and the use of a face mask, vaccination against COVID-19 soon became available. The measures taken in the workplace to inhibit the spread of the virus were important, as some controversial policies emerged regarding the vaccination status of employees. The “health pass” changed the workplace environment immensely, as in many job sectors vaccination became mandatory. Unvaccinated employees were required to undergo specific COVID-19 tests to access their workplace, while other specialized workers such as health workers were removed from their work altogether. Such measures would be justified if it was certain that vaccinated people cannot transmit the virus, but over the course of years this hypothesis seems to have faded. The main aim of this study is the confirmation (or the non-validation) of this hypothesis and of the specific applied measures through the elaboration and statistical analysis of vaccination data from 35 countries in relation to their daily announced infections over the time frame from the forty-fourth week of 2021 to the fourth week of 2022. This is examined from an occupational safety and health (OSH) perspective (taking into account the three pillars of sustainability) concerning risk management and safety assessment at the workplaces of sustainable engineering systems (SES). The findings imply that this hypothesis is contestable. Therefore, it is doubtful whether workplace segregation measures were socially and economically sustainable. It is deduced that (i) the complete freedom of vaccinated employees was a situation which intensified occupational risk, degraded the safety level at the workplaces of sustainable engineering systems, and increased the OSH risk management difficulties, and, on the other hand, (ii) the financial burden of mandatory unemployment and frequent testing was not justified and economically sustainable for the unvaccinated individuals in the middle of a worldwide economic crisis. Full article

Although notable efforts have been made in the past to improve Occupational Health and Safety (OHS), the overall performance has not significantly improved as high-level injuries, risks, and fatalities continue to occur. Earlier studies have shown that implementing an Occupational Health and Safety Management System (OHSMS) ensures a reduction in accidents on site, which is, however, not easy due to the many challenges arising during its implementation. The research objectives were to identify, in order of importance, factors that affect the implementation of an OHSMS on construction sites and to analyse how an OHSMS can be implemented in the construction industry of the Western Cape, South Africa, using the Plan Do Check Act (PDCA) method. The research questionnaire obtained online opinions from construction professionals. The data were analysed using the Statistical Package for Social Sciences (SPSS) software version 27.0. The data were interpreted through Cronbach’s alpha coefficient, frequencies, descriptive statistics, and a multi-regression analysis. A multi-regression test was conducted to determine the relationship between internal and external factors and the implementation of an OHSMS, including the use of the PDCA method. The findings reveal that both internal and external factors affected the implementation of the OHSMS. The most important internal factors were risk control strategies, senior management commitment, and support and communication channels. The most common external factors were pressure from clients on project delivery, company reputation, OHS enforcement, and government legislation. A framework was developed to outline how an OHSMS can be implemented using the PDCA approach based on the findings from this study. The framework can be adopted by the construction industry to improve effectiveness when implementing their OHSMS. Full article

This study aims to address the limitations of traditional Failure Mode and Effect Analysis (FMEA) in managing safety and reliability within complex systems characterized by interdependent critical factors. We propose an integrated framework that combines FMEA with the strategic decision-making principles of Game Theory, thereby enhancing the assessment and mitigation of risks in intricate environments. The novel inclusion of the Best Worst Method (BWM) and Pythagorean fuzzy uncertain linguistic variables refines the accuracy of risk evaluation by overcoming the inherent deficiencies of conventional FMEA approaches. Through sensitivity analysis, the framework’s efficacy in identifying and prioritizing failure modes is empirically validated, guiding the development of targeted interventions. The practical application of our methodology is demonstrated in a comprehensive healthcare system analysis, showcasing its versatility and significant potential to improve operational safety and reliability across various sectors. This research is particularly beneficial for systems engineers, risk managers, and decision-makers seeking to fortify complex systems against failures and their effects. Full article