A Novel Work on Analyzing STRESS and Depression level of Indian Population During COVID-19

被引:0
作者
Gupta A.K. [1 ]
Mathur P. [2 ]
Bijawat S. [3 ]
Dadhich A. [3 ]
机构
[1] Department of Computer Science & Engineering, Amity School of Engineering & Technology, Amity University, Rajasthan, Jaipur
[2] Department of Mathematics, Poornima Institute of Engineering & Technology, Rajasthan, Jaipur
[3] Department of Computer Science & Engineering, Poornima Institute of Engineering & Technology, Rajasthan, Jaipur
来源
Recent Advances in Computer Science and Communications | 2022年 / 15卷 / 06期
关键词
COVID-19; DASS-21; depression; Machine Learning; mental state; Multiple Linear regressions; stress;
D O I
10.2174/2666255813999201022113918
中图分类号
学科分类号
摘要
Objective: The world is facing the pandemic of COVID-19, which has led to a considerable level of stress and depression in mankind as well as in society. Statistical measurements can be made for early identification of the stress and depression level and prevention of the pre-vailing stressful conditions. Several studies have been carried out in this regard. The Machine learning model is the best way to predict the level of stress and depression in humankind by statistically analyzing the behavior of humans which helps in the early detection of stress and de-pression. This helps to prevent society from psychological pressures from any disaster like COVID-19. COVID-19 pandemic is one of the public health emergencies that are of great international concern. It imposes a great physiological burden and challenges on the population of the country facing the calamity caused by this disease. Methods: In this paper, the authors conducted a survey based on some questionnaires related to depression and stress and used the machine learning approach to predict the stress and depression level of humankind in the pandemic of COVID-19. The data sets were analyzed using the Multiple Linear Regression Model. The predicted score of stress and depression was mapped into DASS-21. The predictions have been made over different age groups, gender, and categories. The machine learning model is the best way to predict the level of stress and depression in humans by statistically analyzing their behavior which helps in the early detection of stress and depression. Results: Women, in general, were more stressed and depressed than men. Moreover, the people who are 45+ years of age were found to be more stressed and depressed, including male and fe-male students. The overall analysis showed that the people of India were stressed and depressed at “Serve” level due to COVID-19. It may be because students were more depressed about their study and career, women were stressed about their business as well as their salary and aged people were depressed due to their health concerns in COVID-19 disaster. Conclusion: The researchers conducted an analysis of data based on DASS-21 parameters defined for anxiety, depression, and stress at the global level. By the analysis defined in section 5, researchers concluded that the people of India are more stressed and depressed at Serve" level due to COVID-19. © 2022 Bentham Science Publishers."
引用
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页码:822 / 831
页数:9
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