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Motivitify - Assessing the Economic Effects of Employee Mental Health Challenges on Organizations

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dc.contributor.author De Silva, Kalsha
dc.date.accessioned 2025-05-23T04:01:38Z
dc.date.available 2025-05-23T04:01:38Z
dc.date.issued 2024
dc.identifier.citation De Silva, Kalsha (2024) Motivitify - Assessing the Economic Effects of Employee Mental Health Challenges on Organizations. BSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 2017149
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/2354
dc.description.abstract "Background: The COVID-19 pandemic has significantly exacerbated the issue of declining employee mental health. This has manifested in increased employee turnover, sick leave usage, and a decrease in overall motivation. Companies are facing substantial challenges due to the loss of talented employees, operational inefficiencies leading to financial losses, and rising operational costs. These negative consequences can all be attributed to the decline in employee well-being. In today's workplace, prioritizing employee mental health is no longer optional. Companies that fail to address this critical issue risk facing a multitude of problems, including employee burnout, presenteeism, absenteeism, and high turnover rates. Purpose and Aim: This study aims to analyze inefficiencies in current company work patterns and investigate their impact on employee mental health. By identifying these factors, the study will inform the design of a web-based system architecture. This prototype will support employees and, consequently, boost their productivity and motivation. Ultimately, the goal is to enhance overall organizational productivity and financial stability. Methods: This research employed a multifaceted approach to understand employee mental health concerns and predict potential burnout risk. A pilot study was conducted in Sri Lanka, involving a survey distributed to a sample of 30 employees and interviews with managers. Additionally, a literature review was conducted to gather relevant insights. Custom machine learning models were developed based on the analysis and comparison of similar research and applications. These models aim to predict the future risk of burnout, a significant factor in employee turnover. Employees will be required to complete a self-assessment form on a weekly basis to provide data for the model and predict their mental health status and burnout risk. Results: Pilot Study proves that 33.3% of employees are taking sick leave due to mental health concerns while the 83.3% of managers are not aware about their employees conditions." en_US
dc.language.iso en en_US
dc.subject Mental Health en_US
dc.subject Employee mental wellbeing en_US
dc.subject Organization Financial status en_US
dc.title Motivitify - Assessing the Economic Effects of Employee Mental Health Challenges on Organizations en_US
dc.type Thesis en_US


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