Predicting Melancholy risk among IT professionals using Modified Deep Learning Neural Network (MDLNN)
S. Rosaline, M. Ayeesha Nasreen, P. Suganthi, C. T. Manimegalai, G. Ramkumar
Abstract
Stress disorders are a widespread problem among IT workers who are now employed in the business. Changing lifestyles and workplace cultures, according to study, increase the likelihood of employees experiencing stress at their jobs. However, regardless of the fact that many companies and sectors provide mental wellbeing system and make attempts to enhance the workplace environment, the problem is far from under control. It is our goal in this paper to employ modified deep learning neural network (MDLNN) approaches to assess stress patterns in IT professionals and to identify the components that are most strongly associated with stress levels. It was decided to use data from the OSMI mental health survey 2017, which included responses from working professionals in the technology industry, to achieve this goal. After thorough data cleaning and preparation, we used a modified deep learning neural network to train our model. The correctness of the models mentioned above was determined and compared to one another. Gender, history of family, and the availability of health benefits in the employment were found to be the most significant factors influencing stress, according to the DLMNN model. Industries may now refine their strategy to stress reduction and create a far more comfortable work environment for their employees as a result of the findings of this study.