Employee Burnout Prediction: A Supervised Learning Approach

Burnout is a mental state caused by excessive stress that results in emotional instability and a reduction in an individual’s performance capacity. Burnout is defined as, among other things, a fear of failure, a sense of powerlessness, and a sense of performance pressure. It has more to do with dealing with one’s conscience than with dealing with society. Tiredness, a lack of sleep, a lack of inspiration and productivity, concentration issues, frequent headaches, and other factors all contribute to burnout. Burnout isn’t just a problem for people in the business world; it can affect anyone, including students, stay-at-home moms, teachers, and others. Many people are affected by this, and they are unaware that they are “burned out,” therefore the symptoms go untreated, which can be problematic in the long term. It is possible to create a model that allows people to assess themselves using a curated set of criteria (factors) and estimate the rate of burnout. This paper gives an overview of various regression models offered in the existing literature for predicting employee burnout, and the best performing model is selected through a comparison based on different evaluation techniques.