The research explores academia and industry experts’ viewpoints regarding the innovative progression of Virtual Reality (VR)-based safety tools customized for technical and vocational education training (TVET) within commercial kitchen contexts. Developing a VR-based safety tools holistic framework is crucial in identifying constructs to mitigate the risks prevalent in commercial kitchens, encompassing physical, chemical, biological, ergonomic, and psychosocial hazards workers encounter. Introducing VR-based safety training represents a proactive strategy to bolster education and training standards, especially given the historically limited attention directed toward workers’ physical and mental well-being in this sector. This study pursues a primary objective: validating a framework for VR-based kitchen safety within TVET’s hospitality programs. In addition to on-site observations, the research conducted semi-structured interviews with 16 participants, including safety training coordinators, food service coordinators, and IT experts. Participants supplemented qualitative insights by completing a 7-Likert scale survey. Utilizing the Fuzzy Delphi technique, seven constructs were delineated. The validation process underscored three pivotal constructs essential for the VR safety framework’s development: VR kitchen design, interactive applications, and hazard identification. These findings significantly affect the hospitality industry’s safety standards and training methodologies within commercial kitchen environments.

This research explores the advancement of Artificial Intelligence (AI) in Occupational Health and Safety (OHS) across high-risk industries, highlighting its pivotal role in mitigating the global incidence of occupational incidents and diseases, which result in approximately 2.3 million fatalities annually. Traditional OHS practices often fall short in completely preventing workplace incidents, primarily due to limitations in human-operated risk assessments and management. The integration of AI technologies has been instrumental in automating hazardous tasks, enhancing real-time monitoring, and improving decision-making through comprehensive data analysis. Specific AI applications discussed include drones and robots for risky operations, computer vision for environmental monitoring, and predictive analytics to pre-empt potential hazards. Additionally, AI-driven simulations are enhancing training protocols, significantly improving both the safety and efficiency of workers. Various studies supporting the effectiveness of these AI applications indicate marked improvements in risk management and incident prevention. By transitioning from reactive to proactive safety measures, the implementation of AI in OHS represents a transformative approach, aiming to substantially reduce the global burden of occupational injuries and fatalities in high-risk sectors.

Purpose: This study explores the impact of quality of life (QoL) on the happiness of female healthcare professionals, focusing on the moderating roles of family dynamics and education. Method: A descriptive and exploratory design was used with data from 503 female healthcare professionals. Various quantitative analyses, including regression and correlation, were conducted using SPSS and AMOS. Findings: The study found a positive relationship between QoL and happiness. Family dynamics and education significantly moderated this relationship, highlighting the influence of these factors on happiness levels. Implications: The research offers insights into the well-being of female healthcare professionals and calls for policies that support QoL through flexible work arrangements and wellness programs, considering diverse family structures and educational backgrounds. Originality: This study provides a focused analysis of the role of family and education in shaping the relationship between QoL and happiness for female healthcare professionals.

Hazards are the primary cause of occupational accidents, as well as occupational safety and health issues. Therefore, identifying potential hazards is critical to reducing the consequences of accidents. Risk assessment is a widely employed hazard analysis method that mitigates and monitors potential hazards in our everyday lives and occupational environments. Risk assessment and hazard analysis are observing, collecting data, and generating a written report. During this process, safety engineers manually and periodically control, identify, and assess potential hazards and risks. Utilizing a mobile application as a tool might significantly decrease the time and paperwork involved in this process. This paper explains the sequential processes involved in developing a mobile application designed for hazard analysis for safety engineers. This study comprehensively discusses creating and integrating mobile application features for hazard analysis, adhering to the Unified Modeling Language (UML) approach. The mobile application was developed by implementing a 10-step approach. Safety engineers from the region were interviewed to extract the knowledge and opinions of experts regarding the application’s effectiveness, requirements, and features. These interview results are used during the requirement gathering phase of the mobile application design and development. Data collection was facilitated by utilizing voice notes, photos, and videos, enabling users to engage in a more convenient alternative to manual note-taking with this mobile application. The mobile application will automatically generate a report once the safety engineer completes the risk assessment.

Introduction: The heterogeneity of occupational morbidity by gender in those suffering from carpal tunnel syndrome (CTS) has been little studied in the Latin American context. The objective of this study was to estimate the incidence and prevalence of CTS of occupational origin in the Ecuadorian salaried population according to gender, In addition, the differences in risk between women and men are compared. Methods: We use the only administrative registers of CTS qualified as occupational diseases in the country between the years 2017 and 2019. Period incidence rates were estimated to compare the risk in women versus men (RR, CI 95%) by age group and economic activity. Results: CTS is the second most common occupational disease in Ecuador. Women workers are more likely tosuffer from CTS and showed twice the risk compared to men [RR = 2.10 (95%CI: 1.94–2.11); p = 0.000]. This risk increases with age and for the vast majority of economic activities. The occupations of agriculture and warehousing stand out for their importance. Conclusions: The results shown in this study raise the fundamental need to improve epidemiological surveillance systems and occupational health policies by considering gender differences in order to adequately address risks and promote safe and healthy working environments for all.