Mental Health Analysis of Employees using Machine Learning Techniques

In recent years, there has been increasing research and analysis on the importance of mental health in achieving global sustainable development goals. Mental stability can be affected by different situations - illness can affect the individual's emotion, thoughts, attitude and decision making. Mental disorders are becoming more common for the employees due to stress in their workplace. Mental illness may cause Personality Disorder, Anxiety Disorder, Phobias, Psychotic disorders, Depression, mood disorders, eating disorders and a few more. In this paper, we analyzed the cause of mental health disorders among the employees from the Open Sourcing Mental Illness (OSMI) Mental Health in Tech Survey dataset. Here we analyzed the severity of mental illness for working employees based on different factors or attributes which includes self-employed, mental health history in employees family, company offering beneficial health effects, whether the employee is in treatment for mental illness and much more using Machine Learning algorithms. The main objective for analyzing such data is to educate the public about mental illness in a working environment, thus it helps in lowering the problems with mental disorders. This paper supports and advises about the cause of severe mental health behaviours, and to prevent any unfortunate happenings due to various factors in a working atmosphere. Hence, this provides an estimation of how employees are affected in both Tech and Non-Tech companies. This analysis brings us to a conclusion of answering questions of whether the location matters, the number of employees in a company matters, whether mental health is taken into consideration or not and how these external factors affect one's mental health and physical well-being in the working sectors.