A deep learning approach toward prediction of mental health of Indians

ABSTRACT

COVID-19 caused a dramatic change in the lifestyle of people around the globe and has had an impact on all sectors, including mental health, the economy, and social behavior. Mental health is of great concern for the survival of the young people in achieve their goals. This chapter concentrates on mental health in the education sector during the pandemic. Students and faculty members experienced a high amount of frustration, stress, anxiety, fear, and loneliness during the pandemic. The implementation of online classes was a burden to faculty and students and led to an unsatisfactory mode of teaching in which eye-to-eye contact was missing. Although experience was gained for both teacher-centric and student-centric modes of teaching, mental health resulting from online classes is analyzed in this chapter. Mental health during the pandemic period we analyzed by collecting data from students and staff in the higher education sector from the point of view of undergraduates, postgraduates, and research scholars. Deep learning algorithms pave the way to analyzing mental health for people in the education sector. It predicts the percentage of staff and students who are disturbed in their profession and study. This analysis helps to reduce the gap of interaction between staff and students in the blended mode of teaching. It also provides insight into government policies related to future modes of education. © 2022 Elsevier Inc. All rights reserved.