Predictive Analysis of Child’s Mental Health/Psychology During the COVID-19 Pandemic

ABSTRACT

The Covid-19 pandemic coupled with lockdown has nearly brought the world to a standstill. It has left both short and long-term impacts on the mental health of the children. The goal of this paper is to predict the changes in various mental health parameters such as health, emotion, behavior, maturity, and education. Our target research group is the children of West Bengal, India belonging to the age group of 0–18. An exclusive set of a questionnaire prepared by a team of psychologists was delivered to parents of students in a few schools. The data received from the survey was then processed and cleaned. Using standard machine learning models like k-NN(k = 5), MLP and SVM we analyzed the survey data and performed a comparative prediction of the probabilistic changes of the aforementioned mental health attributes. SVM reported an accuracy of 82.75%, 72.41%, 65.51%, 58.62% and 72.41% in prediction of the mentioned attributes. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.