Burnout Syndrome and Coping Strategies among Nursing Staff: Modeling and Prototyping a Smart Prevention System Using the Internet of Medical Things

The aim of this research is to propose a prototype mobile recommendation system that leverages exploiting the Internet of Medical Things (IoMT) for real-time health monitoring and burnout assessment among healthcare professionals. The system is designed not only to assess burnout, but also to provide personalized coping strategies. The system architecture was conceptualized using the Unified Modeling Language (UML). The prototype integrates various biometric sensors such as, including electrocardiogram (ECG), blood pressure, blood oxygen saturation and temperature, in conjunction with psychometric tests to assess burnout syndrome. By continuously monitoring physiological and psychological parameters, this system offers significant benefits for promoting the general well-being of healthcare professionals. In addition to its real-time monitoring capabilities, it serves as a preventive tool to alleviate stress, detect early signs of burnout and reduce the risk of developing chronic illnesses. This holistic approach addresses both mental and physical health, providing a comprehensive solution to the growing problem of burnout in the healthcare sector. The proposed system aims to improve the quality of life and job satisfaction of healthcare professionals, by strengthening their resilience in the face of professional stress factors.