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Data Science Applications of Post-COVID-19 Psychological Disorders ; : 21-37, 2022.
Article in English | Scopus | ID: covidwho-2126298

ABSTRACT

Background: Earlier this year, the virus COVID-19 was detected for the first time and has since spread worldwide, causing widespread illness and death. A rise in emotional and psychological challenges worldwide has resulted from the disease's direct and indirect effects on individuals and families. It is usual for people to experience worry, tension, and other emotional responses during times of instability. Additional stress can increase symptoms in those already who have a mental illness. Methods: A survey is conducted on selective samples like students-teachers, COVID and non-COVID patients, small-medium scale entrepreneurs. A measurement scale of the WHO-5 Well-Being Index and The Depression, Anxiety, and Stress Scale-21 items (DASS-21) were taken in the questionnaire survey. When it comes to post-COVID mental diseases, data science is usually used to investigate the prevalence of these disorders, with a particular emphasis on their worry and melancholy. WHO-5 well-being index and the DASS-21 have their score calculations carried out in this study. Results: Among the 154 respondents of 77 males and 77 females, the WHO-well-being index has shown an average score of 55 among the sample selected. The male displayed a high score of 100 in 1.94%, and female respondents have reached 92 only. The Happiness index doesn't depend on the infection also. The DASS-21 shows a severity score, more in COVID affected persons than the non-affected ones. The students (COVID), Teachers (COVID), Medium Entrepreneurs (COVID) have shown the value of >60% in Depression and Stress. The anxiety value is comparatively less in both cases. © 2022 Nova Science Publishers, Inc. All rights reserved.

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