The Digital Bridge: using Digital Intervention to Understand Psychosocial Correlation between COVID-19 Stress and Sleep Quality in Undergraduate Students Before and After COVID-19

Abstract

Introduction: With the onset of the pandemic and the reopening of institutions, we are all undergoing a new normal, and educators and students are attempting to adjust to keep close ties to the core principles of the educational system. Existing studies have limited analysis on temporal dynamics and causal links between psychosocial factors, COVID-19-related stress, and sleep quality. Moreover, the studies rely on self-reported data, which introduces potential biases. Therefore, the current study employs a mixed-method approach that combines thematic analysis with both inferential and descriptive statistics. Methods: The first part of this study, which is split into two phases, focuses on identifying the stress that COVID-19 students experience and how it affects other behavioural, psychological, and social factors, as well as sleep. It then examined the significance of these factors for students' academic performance during the current transition from offline to online teaching and hybrid modes. Understanding the importance of Digital technology and, using AI-based intervention to address underlying problems, and determining the impact of chatbots on underlying causes is discussed in the second phase of the study. Results: The information was gathered from 214 undergraduate students enrolled in different programmes in the University of Delhi using a self-designed, extensive questionnaire that included demographic questions, the Pittsburgh Sleep Index, and the COVID-19 Student Stress Questionnaire (CSSQ). To assess and forecast a student's academic performance based on psychosocial indicators, the data was examined using techniques such as feature selection, regression, neural networks, the Naïve Bayes machine learning algorithm, and multi-dimensional analysis. To determine the link between the variables before and after the intervention, statistical tools, including SPSS, were used to calculate mean, SD, t, and correlation. Conclusion: The results of the present study show that stress associated with COVID-19 was affecting undergraduate students' sleep, as well as their psychological, behavioural, social, and cognitive functioning. Additionally, research indicated that AI-based intervention chatbots significantly improved undergraduate students' general learning capacity, reduced stress connected to COVID-19, and improved sleep.