Prediction of Mental Health Disorder in IT Sector Employees Using Machine Learning Models

It is the era of technology. Today most people hold a job in the IT sector. The life of any IT sector employee is tightly packed with less to no time for self-care. They are constantly hustling to meet deadlines, to understand the need of the hour and deliver solutions to new problems. As time progresses, these employees are diagnosed with mental health disorders owing to multiple factors. Some of the factors include working style, working mode, gender, family history, etc. This research paper aims to identify and help prevent mental health disorder issues by building a state-of-the-art prediction model using supervised learning algorithms. The best model is chosen by comparing the results of classification models like Decision Tree, Naïve Bayes, Random Forest and Quantum Support Vector Classifier. This model can further be deployed to aid detection and prevention of mental disorders.