A Study on the Mental Health Among Indian Population in the Post COVID-19 Pandemic Using Computational Intelligence

Preventing mental health problems is an essential task for national and international organizations. Such entails the establishment of active information network indicators to assess the mental health of populations. About 21% of the global people suffering from depression, anxiety, isolation, loss of income, and fear are triggering mental health problems due to the COVID-19 pandemic. Therefore, it is essential to find out various factors that affect the mental health of people in India the post COVID-19 pandemic. A hybridized rough and whale optimization technique is used to study the mental health of people in the post pandemic of India. The proposed design contains three stages of implementation. In the very beginning, the data collected from primary sources are validated using structural equation modeling and partial least square. Further, in the second phase, the proposed rough whale optimization is employed to identify the chief parameters of the decision system. The reduced decision system is analyzed further using a rough set in the final phase. It is observed that the evaluations have drawn attention to the importance of mental disorders for public health. It, in turn, helps to reduce the risk of getting a mental disorder.