ADAM- Anxiety Detection and Management: a Solution to Manage Anxiety at Workplaces and Improve Productivity

摘要

This paper documents the research conducted for an application aiming to help employees from the IT industry in Sri Lanka to manage their anxiety. Anxiety in workplaces burdens a significant number of employees around the world, making it challenging to reach their goals and increase their productivity. In Sri Lanka where mental illnesses are considered a social stigma, there is a lack of mental health applications. The application, ADAM (Anxiety Detection and Management), will help employees facing anxiety to realise the severity of their condition and encourage them to seek professional help, while also providing a few self-managing activities they can follow. The Hamilton Anxiety Rating Scale (HAM - A) was utilised with questions modified to help employees understand their triggers at work. A Rule-based machine learning model is used to allocate appropriate anxiety-management activities according to the employees’ gender, age and severity. This model was implemented for the scale to help collect data and identify patterns of the severity. The application helps achieve sustainability in terms of increased productivity amongst employees, as a result of better managed anxiety and falls under the Sustainable Development Goal (SDG) of ‘Good Health and Well-being".