study of stress, depress, and anxiety in secondary school students during COVID-19 lockdown in India by reinforcement learning framework using Q learning algorithm techniques in machine learning
Year: 2021
Type: article
Study design: Observational Study
Abstract: During the lockdown time, schoolchildren experience a variety of psychological difficulties. Stakeholders would be responsible for enlisting mental health specialists to assist in the resolution of such situations. As a result of the epidemic, schooling faces a unique set of challenges. There have been a number of cancellations due to the COVID 19 crisis. It is important for students’ mental health to be taken into consideration when a public health emergency occurs. When it comes to addressing this issue, it is advised that the government and schools work together to find a solution. It was the major goal of this study to determine the levels of stress, anxiety, and depression among high school students. Because of their mental health issues, such as stress, worry, and depression, students require specific treatment, according to the report. Using the Q Learning Algorithms, a model-free learning method followed throughout the survey. Based on the survey, it concludes that students experienced a variety of personal issues, such as boredom, sadness, anxiety, discomfort of staying at home, and problems with not meeting with friends, among other things.
Language: English
Topic: COVID-19 and Mental Health
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4366706059