Case Study-Based Predictive Linear Regression Model to Measure Anxiety and Depression as the Impact of COVID- 19 among Students in Higher Education

Abstract

Students in the age group of 18–25 years witnessed their first pandemic in the form of the coronavirus (COVID-19). This had negative effects on their mental health, ranging from mild to severe. These effects also affected their personal and professional lives. The purpose of this study is to measure the anxiety and depression levels in college students due to COVID-19, along with the significant factors that contribute to that effect. We use the benchmark Hospital Anxiety and Depression Scale [HADS] questionnaire, as the basis of an online survey to capture the anxiety and depression levels amongst college students in various disciplines and at different levels. This survey was circulated through social media networks such as Facebook, WhatsApp, and so on. The responses were collected and analysed using Linear Regression and Random Forest algorithms for understanding the significant factors leading to the anxiety and depression of college students between ages 20 and 24.