How can machine learning be used in stress management: A systematic literature review of applications in workplaces and education

In today's competitive and rival world, stress has emerged to be an integral part of every person's life which affects an individual directly or indirectly in many ways. The COVID-19 pandemic even glorified the importance and cruciality of managing stress, anxiety and depression as these created a massive impact on the economy, education, healthcare, business areas and other aspects of society in every possible manner. This study determines to find all the feasible contributing factors to stress, anxiety and depression which influence individuals coming from vivid occupational backgrounds due to personal, work-related, psychological and interpersonal reasons. Our research aims to define and describe the impact of the rise in technology and the COVID-19 pandemic on the stress levels of an individual. It includes variously supervised and unsupervised machine learning algorithms in detecting stress efficiently and effectively among a huge population. The objective of this paper is to make those millions of people aware of the early detection and treatment of stress before it becomes life-threatening to them. The paper finally throws light on how stress-related research will help policymakers in the education field and general industry sector to rebuild the policies on stress and countermeasures to avoid stress.