Burnout syndrome has become one of the most visible challenges in contemporary occupational health. To date, the WHO has recognized it as an occupational phenomenon that affects the psychological well-being of workers and the sustainability of organizations. In a world where work paces are increasingly fast-lived and productivity demands never stop growing, chronic exhaustion emerges as a clear symptom that something is wrong with the way we conceive of work.

The root of the problem lies in organizational factors: long hours, constant pressure for results, a lack of autonomy, and, in many cases, an absence of institutional support. All of this creates a breeding ground for professionals to feel demotivated, distanced from their tasks, and burdened by a growing sense of inefficacy.

Solving this problem is crucial not only from an individual health perspective but also from a social and economic one. Burned-out workers are more vulnerable to making mistakes, developing emotional issues, or leaving their positions, which directly impacts productivity and corporate cohesion. On the contrary, preventing and treating burnout early could translate into promoting healthier work environments, retaining talent, and ensuring that organizations can thrive sustainably. If left unaddressed, the consequences spread in several directions: deterioration of employees’ mental and physical health, increased absenteeism, a drop in productivity, and, ultimately, a significant economic impact.

The objective of this project is to address burnout syndrome prevention from a technological perspective, proposing the design and development of a digital solution oriented toward early detection. The proposal is based on the application of the validated BAT questionnaire (Burnout Assessment Tool), a brief instrument that allows for the identification of signs of exhaustion, mental distancing, and cognitive or emotional impairment in employees across different sectors.

You can test the application by clicking on this LINK.

To access use the following credentials:

• User: employee-catedraIRSST@example.com
• Password: 123456