Abstract

Burnout is a work-related syndrome that considers depersonalization, emotional exhaustion, and diminished feelings of personal accomplishment. This syndrome can also be observed in university students and produce several health problems. Our work aims to detect premature signs of anxiety, depression, and psychical and physical health perturbances in university students. Mainly, we aim to help students to tackle (and possibly prevent) burnout syndrome symptoms. For this, a questionnaire was designed based on essential instruments used in the literature. We propose to use an ensemble of Artificial Neural Networks to predict a set of four possible disturbances in persons. The proposal will be used in the Human Place project to suggest strategies to tackle four types of disturbances. This work considers a study case of 93 persons from the Valparaiso region, Chile. Experiments show the promising capabilities of our approach, obtaining good accuracy levels and a low number of false negative cases.