Abstract:
The importance of mental health in achieving global sustainable development goals has gained significant attention in recent years. Various factors, including work-related stress, can impact an individual's emotions, thoughts, attitude, and decision-making process. Mental health issues among employees are on the rise, encompassing disorders such as anxiety, depression, eating disorders, and more. This study aims to identify the root causes of mental illnesses in the workforce by analyzing data from the Open Sourcing Mental Illness (OSMI) Mental Health in Tech Survey. Machine learning algorithms are utilized to assess the severity of mental illness among working employees based on factors such as self-employment, family history of mental health, availability of health benefits from the company, and whether the employee is undergoing treatment for mental illness, among others. The primary objective of this data analysis is to raise awareness about mental health in the workplace and mitigate the associated challenges. By understanding the influence of external factors like location, company size, and consideration of mental health, we can address and enhance employees' mental and physical well-being in various sectors.
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