High-risk Tasks Research Articles

Implementation of Occupational Safety Standards by Public Area Attendants at Department Style Hotels in Bali

This study aims to examine the implementation of occupational safety standards by public area attendants, Department Style Hotel X. Data collection techniques include observation, interviews, and documentation studies. Data analysis was carried out using descriptive comparative qualitative methods between high-risk occupational safety standards (High Risk Task) and their implementation by public area attendants, Department Style. The results of the study showed that full compliance (100%) in maintaining cleanliness and dryness of the floor, installing "wet floor" signs, using stairs in hard-to-reach areas, understanding the use of machines, and managing the area by two public area attendants. However, compliance with the use of masks, gloves, checking cables and machines before use, and using safety equipment was still below 100%. Factors that influence this non-compliance include haste, discomfort in using PPE (Personal Protective Equipment), and lack of inspection of the condition of the equipment.

Motion priority optimization framework towards automated and teleoperated robot cooperation in industrial recovery scenarios

In this study, we introduce an optimization framework to enhance the efficiency of motion priority design in scenarios involving automated and teleoperated robots within an industrial recovery context. The increasing utilization of industrial robots at manufacturing sites has been instrumental in reducing human workload. Nevertheless, achieving effective human–robot collaboration/cooperation (HRC) remains a challenge, especially when human workers and robots share a workspace for collaborative tasks. For instance, when an industrial robot encounters a failure, such as dropping an assembling part, it triggers the suspension of the corresponding factory cell for safe recovery. Given the limited capacity of pre-programmed robots to rectify such failures, human intervention becomes imperative, requiring entry into the robot workspace to address the dropped object while the robot system is halted. This discontinuous manufacturing process results in productivity loss. Robotic teleoperation has emerged as a promising technology enabling human workers to undertake high-risk tasks remotely and safely. Our study advocates for the incorporation of robotic teleoperation in the recovery process during manufacturing failure scenarios, which is referred to as “Cooperative Tele-Recovery”. Our proposed approach involves formulating priority rules designed to facilitate collision avoidance between manufacturing and recovery robots. This, in turn, ensures a continuous manufacturing process with minimal production loss within a configurable risk limitation. We present a comprehensive motion priority optimization framework composed of an HRC simulator and a cooperative multi-robot controller to identify optimal parameters for the priority function. The framework dynamically adjusts the allocation of motion priorities for manufacturing and recovery robots while adhering to predefined risk limitations. Through quantitative and qualitative assessments, we validate the novelty of our concept and demonstrate its feasibility.

Understanding Musculoskeletal Risks in Retail Workers: An Ergonomic Assessment of Store 24H

Musculoskeletal disorders (MSDs) are prevalent in retail environments, often resulting from repetitive tasks, awkward postures, and prolonged standing. This study examined musculoskeletal discomfort and ergonomic risk factors within the retail environment of convenience stores, focusing on the prevalence of MSDs among employees of Store 24H, Dungun, Terengganu, Malaysia. The assessment began with a job task description, followed by workplace observation and worker input. Utilising a systematic approach, the research integrated two standardized assessment tools; the Cornell Musculoskeletal Questionnaire (CMQ) and the Initial Ergonomic Risk Assessment (ERA) Form Checklist, to identify the discomfort area and ergonomic risk factors associated with job tasks. Three job tasks were identified in the Store 24H environment; operating cash registers, customer service and restocking. The findings indicate a notable prevalence of MSDs associated with the identified high-risk tasks. Repetitive motions, awkward postures, prolonged standing, and forceful exertion were observed as primary ergonomic risk factors for these tasks which contribute to musculoskeletal discomfort in the neck, shoulder, back, hip, and knee. Additionally, forceful exertion and vibration exhibit high risks towards restocking tasks, resulting in restocking as the top contributor towards the MSDs. Hence, the findings highlight the need for advanced ERA and mitigation strategies, including workstation redesign, task rotation, ergonomic training and accessories, to promote employee well-being and reduce the incidence of MSDs among employees of Store 24H. Implementing these measures is essential for promoting the health and well-being of employees, decreasing the occurrence of musculoskeletal disorders, and improving overall safety and productivity in the workplace.

Reassuring, Misleading, Debunking: Comparing Effects of XAI Methods on Human Decisions

Trust calibration is essential in AI-assisted decision-making. If human users understand the rationale on which an AI model has made a prediction, they can decide whether they consider this prediction reasonable. Especially in high-risk tasks such as mushroom hunting (where a wrong decision may be fatal), it is important that users make correct choices to trust or overrule the AI. Various explainable AI (XAI) methods are currently being discussed as potentially useful for facilitating understanding and subsequently calibrating user trust. So far, however, it remains unclear which approaches are most effective. In this article, the effects of XAI methods on human AI-assisted decision-making in the high-risk task of mushroom picking were tested. For that endeavor, the effects of (i) Grad-CAM attributions, (ii) nearest-neighbor examples, and (iii) network-dissection concepts were compared in a between-subjects experiment with \(N=501\) participants representing end-users of the system. In general, nearest-neighbor examples improved decision correctness the most. However, varying effects for different task items became apparent. All explanations seemed to be particularly effective when they revealed reasons to (i) doubt a specific AI classification when the AI was wrong and (ii) trust a specific AI classification when the AI was correct. Our results suggest that well-established methods, such as Grad-CAM attribution maps, might not be as beneficial to end users as expected and that XAI techniques for use in real-world scenarios must be chosen carefully.

A qualitative exploration and a Fuzzy Delphi validation of high-risk scaffolding tasks and fatigue-related safety behavioural deviation among scaffolders

BackgroundMost construction mishaps were caused by scaffolding incidents despite implementing various safety measures, and the association with human factors like fatigue has been widely reported. This study aims to identify all high-risk task sequences involved during the erection of the most commonly used scaffold; the deviation from the standard protocol led to a substandard fatigue state, followed by content validation using the Fuzzy Delphi Method. MethodsQualitative exploration was conducted via focal group discussions (FGDs) involving 30 certified experts. The findings generated from FGDs were further validated by utilising the Fuzzy Delphi Method (FDM) by consulting 19 experts with extensive practical experience and leadership roles in scaffolding safety. ResultsThe FGDs identified a total of 7 constructs and 50 items for task sequences involved in the tubular scaffold erection, namely construct Instruction (3 items), Preparation (3 items), Foundation (10 items), First Lift (8 items), Working Platform (7 items), Guardrails (5 items) and Second Lift (14 items). In the FDM validation process, the experts' consensus for each construct was fulfilled with a threshold value (d) ≤ 0.2; thus, all constructs were accepted. Experts' consensus for all items achieved an expert agreement of 75 % and above. Items ranking was conducted using average fuzzy numbers. The highest average fuzzy number documented was 0.8, while the lowest was 0.588. None of the items with the lowest ranking was discarded as all items perfectly fulfilled the second prerequisite and obtained excellent experts’ agreement. ConclusionsThe tool generated will help guide the development of a protocol for scaffolding safety management.

Robot control system based on deep learning and RPA

Robots can help people complete repetitive and high-risk tasks, such as industrial production, medical care, environmental monitoring, etc. The control system of robots is the key to their ability to complete tasks, and studying robot control systems is of great significance. This article used Convolutional Neural Network (CNN) and Robotic Process Automation (RPA) technologies to optimize and train the robot control system and constructed a robot control system. This article conducts perception and decision-making experiments and execution experiments in the experimental section. According to the experimental results, it can be concluded that the average image recognition accuracy of the robot control system in perception and decision-making experiments was 94.62%. The average decision accuracy was 87.5%, and the average time efficiency was 176 seconds. During the execution of the experiment, the deviation of the motion trajectory shall not exceed 5 cm, and the oscillation amplitude shall not exceed 6°; the distance from the obstacle shall not exceed 20 cm, and the movement speed shall not exceed 0.6 m/s; the operating time shall not exceed 25 hours, and the number of faults shall not exceed 0.2 times per hour, all within the normal range. The robot control system based on Deep Learning (DL) and RPA has broad application prospects and research value, which would bring new opportunities and challenges to the development and application of robot technology.

Global-Position Tracking Control for Multi-Domain Bipedal Walking with Underactuation

Abstract Accurate control of a humanoid robot's global position (i.e., its three-dimensional position in the world) is critical to the reliable execution of high-risk tasks such as avoiding collision with pedestrians in a crowded environment. This paper introduces a time-based nonlinear control method that achieves accurate global-position tracking (GPT) for multi-domain bipedal walking. Deriving a tracking controller for bipedal robots is challenging due to the highly complex robot dynamics that are time-varying and hybrid, especially for multi-domain walking that involves multiple phases/domains of full actuation, over actuation, and underactuation. To tackle this challenge, we introduce a continuous-phase GPT control law for multi-domain walking, which provably ensures the exponential convergence of the entire error state within the full and over actuation domains and that of the directly regulated error state within the underactuation domain. We then construct sufficient multiple-Lyapunov stability conditions for the hybrid multi-domain tracking error system under the proposed GPT control law. We illustrate the proposed controller design through both three-domain walking with all motors activated and two-domain gait with inactive ankle motors. Simulations of a ROBOTIS OP3 bipedal humanoid robot demonstrate the satisfactory accuracy and convergence rate of the proposed control approach under two different cases of multi-domain walking as well as various walking speeds and desired paths.

Impact of Uncertain Flight Time on Heterogeneous UAVs’ Task Planning with Temporal Constraints

Heterogeneous multi-UAV systems offer distinct advantages through their complementary and coordinated use of their diverse capabilities. However, this complexity poses significant challenges in task planning, particularly in considering temporal constraints among tasks. As task dependencies evolve from simple linear chains to complex networked associations, uncertainties in flight times can have a substantial impact on the overall schedule. To address these challenges, this study introduces a rapid estimation method that recursively calculates task completion times, derives their probability distributions, and assesses the robustness of the plan. Furthermore, a neighborhood search algorithm guided by dynamic time windows is designed to effectively evaluate the consequences of task insertions, precisely to adjust high-risk tasks, and reduce blindness in enumerative neighborhood exploration. Simulation results demonstrate that the proposed approach effectively accounts for inherent randomness in the problem and exhibits strong adaptability to changes in the problem scale, flight time fluctuations, and variations in time window constraints.

Use, failure, and non-compliance of respiratory personal protective equipment and risk of upper respiratory tract infections-A longitudinal repeated measurement study during the COVID-19 pandemic among healthcare workers in Denmark.

Upper respiratory tract infections (URTI) are common and a common cause of sick-leave for healthcare workers, and furthermore pose a threat especially for patients susceptible to other diseases. Sufficient use of respiratory protective equipment (RPE) may protect both the workers and the patients. The COVID-19 pandemic provided a unique opportunity to study the association between use of RPE and URTI in a real-life setting. The aim of this study was to examine if failure of RPE or non-compliance with RPE guidelines increases the risk of non-COVID-19 URTI symptoms among healthcare workers. In a longitudinal cohort study, we collected self-reported data daily on work tasks, use of RPE, and URTI symptoms among healthcare workers with patient contact in 2 Danish Regions in 2 time periods during the COVID-19 pandemic. The association between failure of RPE or non-compliance with RPE guidelines and URTI symptoms was analyzed separately by generalized linear models. Persons tested positive for severe acute respiratory syndrome coronavirus 2 were censored from the analyses. The 2 waves of data collection were analyzed separately, as there were differences in recommendations of RPE during the 2 waves. We found that for healthcare workers performing work tasks with a risk of transmission of viruses or bacteria, failure of RPE was associated with an increased risk of URTI symptoms, RR: 1.65[0.53-5.14] in wave 1 and RR: 1.30[0.56-3.03] in wave 2. Also non-compliance with RPE guidelines was associated with an increased risk of URTI symptoms compared to the use of RPE in wave 1, RR: 1.28[0.87-1.87] and wave 2, RR: 1.39[1.01-1.91]. Stratifying on high- versus low-risk tasks showed that the risk related to failure and non-compliance was primarily associated with high-risk tasks, although not statistically significant. The study was conducted during the COVID-19 pandemic and thus may be affected by other preventive measures in society. However, this gave the opportunity to study the use of RPE in a real-life setting, also in departments that did not previously use RPE. The circumstances in the 2 time periods of data collection differed and were analyzed separately and thus the sample size was limited and affected the precision of the estimates. Failures of RPE and non-compliance with RPE guidelines may increase the risk of URTI, compared to those who reported use of RPE as recommended. The implications of these findings are that the use of RPE to prevent URTI could be considered, especially while performing high-risk tasks where other prevention strategies are not achievable.

Use of Computerized Physician Order Entry with Clinical Decision Support to Prevent Dose Errors in Pediatric Medication Orders: A Systematic Review.

Prescribing is a high-risk task within the pediatric medication-use process and requires defenses to prevent errors. Such system-centric defenses include electronic health record systems with computerized physician order entry (CPOE) and clinical decision support (CDS) tools that assist safe prescribing. The objective of this study was to examine the effects of CPOE systems with CDS functions in preventing dose errors in pediatric medication orders. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 criteria and Synthesis Without Meta-Analysis (SWiM) items. The study protocol was registered in PROSPERO (CRD42021277413). The final literature search on MEDLINE (Ovid), Scopus, Web of Science, and EMB Reviews was conducted on 10 September 2023. Only peer-reviewed studies considering both CPOE and CDS systems in pediatric inpatient or outpatient settings were included. Study selection, data extraction, and evidence quality assessment (JBI critical appraisal tool assessment and GRADE approach) were carried out by two individual reviewers. Vote counting method was used to evaluate the effects of CPOE-CDS systems on dose errors rates. A total of 17 studies published in 2007-2021 met the inclusion criteria. The most used CDS tools were dose range check (n = 14), dose calculator (n = 8), and dosing frequency check (n = 8). Alerts were recorded in 15 studies. A statistically significant reduction in dose errors was found in eight studies, whereas an increase of dose errors was not reported. The CPOE-CDS systems have the potential to reduce pediatric dose errors. Most beneficial interventions seem to be system customization, implementing CDS alerts, and the use of dose range check. While human factors are still present within the medication use process, further studies and development activities are needed to optimize the usability of CPOE-CDS systems.

Exploring the Current Status and Future Potential of Robot, Artificial Intelligence, and Service Automation in the Indonesian Tourism Industry

This paper examines the current state and potential future applications of robots, artificial intelligence, and service automation (RAISA) in the hospitality, travel, and tourism industry, with a focus on Indonesia. The study utilizes a comprehensive review of literature and empirical data, including case studies, industry reports, and scholarly articles, to gather relevant information. The findings reveal that while the implementation of RAISA in the Indonesian tourism industry is still in its introductory stage, advancements in RAISA technology and decreasing costs make it increasingly viable for substituting human labor in repetitive and high-risk tasks. However, it is important to consider that not all service processes are suitable for automation or delegation to robots. The decision to automate or retain human labor depends on factors such as economic efficiency, customer satisfaction, company competitiveness, and other internal and external considerations. This research contributes to the existing literature by addressing the specific context of Indonesia and providing insights into the current state and potential future applications of RAISA in the hospitality, travel, and tourism industry. It highlights the scarcity of research in this area and emphasizes the need for further investigation, particularly in areas such as the economic rationale of service automation, the readiness of businesses to adopt RAISA, stakeholder attitudes towards service robots, the impact of RAISA on service quality and company competitiveness, and the ethical considerations associated with its implementation. The findings of this study offer valuable insights for industry practitioners, policymakers, and researchers aiming to understand the benefits, challenges, and implications of integrating RAISA in the Indonesian tourism industry.

IoT System for Monitoring of Workers at Height

Work at height is considered a high-risk task due to the exposure of personnel to non-daily or natural factors for the human being, such as changes in temperature, position and limited displacement, which might affect the person’s metabolism. In Colombia, over the years, this activity has represented a significant number of accidents and deaths. In order to be able to detect a possible eventuality or issue with the worker at height, this project proposed and developed an IoT prototype system to monitor biological variables, such as, heart rate and blood oxygen level, and variables of protection for the worker, such as the securing of the carabiner on the line of life and the height at which the worker is positioned. In the materials and methods section, the system architecture and its connections are explained. To measure heart rate and blood oxygen level, the plethysmography technique is selected, a high-resolution barometer is selected to measure the worker's height, and a pressure sensor is selected to measure carabiner securing. This section also explains the development of electronic instrumentation and the connection of the different modules to guarantee the acquisition of information and its sending to the cloud. The results of the characterization of the prototype indicated errors of 3.56% for the heart rate, 1.1% for the blood oxygen level and 10% for the carabiner securing measurement. As a conclusion the IoT system was designed, implemented and verified for the proposed variables. The system allows real-time measurements and connectivity between physical variables and the cloud.

The use of mobile electronic prescribing to drive quality of oncology care delivery.

586 Background: This pilot technology enhancement project set out to improve the quality of care for oncology patients by developing a mobile application for writing prescriptions (non-chemotherapy) and narcotics. We describe usage of this new mobile application and associated timeliness of care delivery, provider workflow efficiencies and patient safety metrics. Methods: Agile methodology was used to develop the workflow and software for the mobile application. Internal Patient Safety Usability Testing (PSUT) was used to assess high-risk tasks amongst potential users (n = 7). High-risk tasks were defined as those which, based on human error, could lead to potential patient harm or unsafe conditions. High-risk tasks included the ability for users to understand/acknowledge allergy and drug interactions, edit a selection, select and send to the appropriate pharmacy, and locate the record of the completed prescription within the patient’s chart through the mobile application. A pilot study was also conducted among oncologists (n = 14). A quantitative metric was measured to understand the adoption and usability of the mobile application. Qualitative feedback was also obtained. Results: 1. PSUT identified a need for improvement with recognition of interaction severity and differentiating an allergy versus a drug interaction. A design modification was also made to introduce a three-second hold to acknowledge an allergy. This was done to encourage users to take appropriate time to visualize and comprehend allergy and interaction information before advancing the workflow. 2. During the pilot study, 400 mobile prescriptions were written. After-hours writing of prescriptions in the mobile application increased (11.8%) compared to the EMR (3.5%). The average amount of time from initiation of writing a prescription to completion was 62 seconds in the mobile application. There were no high-risk patient safety incidents observed during the pilot study. Qualitative data from participants included themes around convenience, feasibility, improved access to care, and safety. Conclusions: Usage of the pilot mobile application demonstrated a safe and efficient approach to increase the quality of care delivery for oncology patients. Usage also suggests an increase in patient access to care after hours.

Implementing bedside handover in neurological rehabilitation: An Action Research Approach in Practice Development

Implementing bedside handover in neurological rehabilitation: An Action Research Approach in Practice Development Abstract. Background: Nursing handovers are considered high-risk tasks but are also an important resource for conveying pertinent insights in the patients' situation and engaging them in the care process. As part of a broader action research project, a participatory approach was used to implement bedside handovers. Aims: It seemed central to sustainable change to gain insights which underlying factors motivate nurses to change handover practices. Methods: A qualitative design was chosen, in which five exploratory interviews were conducted with nurses. Results: The biggest challenges are privacy concerns and dealing with cognitively impaired patients. The motivations for bedside handover are a less error-prone transfer of information and a more accurate impression of the patient, in addition to a patient contact which is experienced as valuable. Discussion: The change in handover structure is accompanied by changes in the ward culture. The challenges faced by the staff require high communication skills to bridge them. The main factor for the preference of the handover form is the effect on the patients. Limitations: Transferability is limited due to the high contextual relevance. Transfer: With the help of a structured implementation strategy, even rituals can be modified. The bedside handover has a beneficial influence on patient-centredness.

Maritime patrol tasks assignment optimization of multiple USVs under endurance constraint

Unmanned surface vehicles (USVs) are economic, have good maneuverability, and can perform some complex and high-risk tasks such as maritime supervision, leading to reduced costs and casualties. In this study, we investigate the application of USVs in maritime patrols, considering the endurance constraints of the USVs and the time constraints. Additionally, we establishes a mathematical model for optimizing the patrol path of multiple USVs under the endurance and time constraints. Considering the complexity of the model, the logistic map is introduced into the immune algorithm (IA) to improve the optimization. Then according to the relevant constraints, the corresponding coding and decoding methods are designed. Finally, the mutation and crossover operators of the genetic algorithm (GA) are combined with the designed IA to improve the diversity of antibodies in the iterative process, thereby improving the optimization ability of the algorithm. In the final numerical simulation experiment verification, the improved IA with GA (IA–GA) is compared with the traditional IA, GA, PSO-GA (Particle Swarm and Genetic hybrid algorithm) and IA–GA-greedy (IA–GA with greedy attribute) through simulations and case analysis. The results show that the improved IA can find a better solution than other algorithms in a reasonable time, which proves the superiority of the proposed algorithm.

Multi-use Intelligent Automaton for Fire-Detection

Abstract: In some critical situations, human faces challenges especially in the field of nuclear power plants, gas stations, oil rigs etc to control fire. Manual handling will become a high-risk task and sometimes result may involve loss of life, property damage and also cause severe attack to environment. As technology develops, solution to protect human and environment is not a hectic task. Here a multi-purpose fire extinguishing robot is proposed which can carry out fire extinguishing operations as well as reconnaissance missions. Proposed system can search the area, locate the fire and extinguish the fire before it comes out of control. Robot is able to navigate through the building while actively scanning for the flame. It can send various data from the sensors to the cloud technologies and received data on mobile phone. With the help of Internet of Things, it can send alert and notifications to the user about the status of the fire. The robot proposed found its application in fire extinguishing operations during fire accidents where the possibility of the servicemen to enter the fire prone area is very less.

경찰활동에서의 성별통합

In this study, previous studies related to gender integration were reviewd and the actual situation was analyzed through a survey of police officers(N=473) working in Daegu and Gyeongsangbuk-Do. The results are as follows. First, Korean police officers most preferred female police officers performing the same tasks as male police officers except for high-risk tasks(Modified role, M=3.61). The preference for performing the same task regardless of risk(Integrated role, M=3.34) was higher than average(M=3.00), but the consent to performing specialized tasks, such as female offeders or children/juvenile work,(Traditional role, M=2.63) level was low. Second, the background variables and working environment variables of police officers had a certain influence on the attitude toward gender integration. The recently appointed police officers(20s and 30s, less than 10 years of service experience et al.) showed a different attitude from the other police officers, such as preferring a Unified role the most. Third, gender integration is affected by various factors, and self-efficacy has a positive effct on the Unified role attitude and a negative effect on the Traditional role attitude. Fourth, the preference for the Unified role of police officers had a significant positive effect on their job satisfaction. Based on these analysis results, the task of the Korean police for gender integration and the direction of follow-up research were examined.

Explainable Artificial Intelligence Improves Human Decision-Making: Results from a Mushroom Picking Experiment at a Public Art Festival

Explainable Artificial Intelligence (XAI) enables Artificial Intelligence (AI) to explain its decisions. This holds the promise of making AI more understandable to users, improving interaction, and establishing an adequate level of trust. We tested this claim in the high-risk task of AI-assisted mushroom hunting, where people had to decide whether a mushroom was edible or poisonous. In a between-subjects experiment, 328 visitors of an Austrian media art festival played a tablet-based mushroom hunting game while walking through a highly immersive artificial indoor forest. As part of the game, an artificially intelligent app analyzed photos of the mushrooms they found and recommended classifications. One group saw the AI’s decisions only, while a second group additionally received attribution-based and example-based visual explanations of the AI’s recommendation. The results show that participants with visual explanations outperformed participants without explanations in correct edibility assessments and pick-up decisions. This exhibition-based experiment thus replicated the decision-making results of a previous online study. However, unlike in the previous study, the visual explanations did not significantly affect levels of trust or acceptance measures. In a direct comparison, we consequently discuss the findings in terms of generalizability. Besides the scientific contribution, we discuss the direct impact of conducting XAI experiments in immersive art- and game-based environments in exhibition contexts on visitors and local communities by triggering reflection and awareness for psychological issues of human–AI interaction.

Ashes to eye: A skilled snake handler's experience with ophthalmic envenomation.

With the continued growth of human populations, rural urbanisation and habitat degradation are on the rise, resulting in the displacement of native wildlife and an increase in human-wildlife conflicts. The presence of human habitation and waste often attracts rodents and thereby, snakes, leading to increased snake sightings in homes. To address this problem, snake handlers, who are volunteers that remove and relocate snakes away from human development areas, are called upon. However, snake removal is a high-risk task that poses a risk of envenomation, particularly when dealing with spitting snakes. Several cobra species have the ability to spit venom. If the venom enters a person's eye, it can result in ophthalmic envenomation, which can have serious consequences for their eyesight. Therefore, snake handlers should take precautions, wear suitable eye protection, and use appropriate tools to ensure their safety and that of the snake. In this case, an experienced snake handler was called to remove a spitting cobra, but they were ill-equipped. During the removal, the venom was sprayed across the handler's face, and some of it entered their eye, resulting in ophthalmic envenomation. The handler promptly irrigated their eye, but medical treatment was still necessary. This report highlights the risks and consequences of ophthalmic injury and the importance of wearing appropriate eye protection and taking due care when dealing with venomous species, particularly those that can spit venom. It serves as a reminder that accidents can happen at any time and experienced snake handlers are not exempt from the risks.

Vasovagal Syncope at Work: A Narrative Review for an Occupational Management Proposal.

Syncope is a complex clinical manifestation that presents considerable diagnostic difficulties and, consequently, numerous critical issues regarding fitness for work, especially for high-risk tasks. To date, it is impossible to quantify the exact impact of syncope on work and public safety since it is highly improbable to identify loss of consciousness as the fundamental cause of work or driving-related accidents, especially fatal injuries. Working at high-risk jobs such as public transport operators, in high elevations, or with exposure to moving parts, construction equipment, fireworks, or explosives demand attention and total awareness. Currently, no validated criteria or indicators are available for occupational risk stratification of a patient with reflex syncope to return to work. By drawing inspiration from the updated literature, this narrative review intends to summarise the leading knowledge required regarding the return to work for subjects affected by syncope. According to the available data, the authors highlighted some key findings, summarised in macro-items, such as defined risk stratification for vasovagal accidents, return to work after a critical event, and a focus on pacemaker (PM) implementation. Lastly, the authors proposed a flowchart for occupational physicians to help them manage the cases of workers affected by syncope and exposed to levels of risk that could represent a danger to the workers' health.