Determining factors contributing to the psychological impact of the COVID-19 Pandemic using machine learning

Abstract

The COVID-19 pandemic has created a massive impact in the economy, healthcare, education and other aspects of society in each and every respect. Also greatly affected is the mental health of individuals. This study aims to determine the possible contributing factors to stress, anxiety, depression, and adverse psychological impact on the general population of the Philippines using machine learning approaches. The data gathered from 2119 participants who answered an online survey was analyzed using feature selection methods and machine learning classifiers to determine contributing factors to the aforementioned mental health issues. The results show that longer hours at home, on social media, age, how people rate their own health, pre-existence of a neuropsychiatric condition; wanting information on availability and effectiveness of a medicine or vaccine, being concerned for their family, feeling discriminated; and symptoms of body pain, difficulty breathing, and cough were good predictors of individuals being adversely impacted psychologically by the pandemic and others having elevated levels of stress, anxiety, depression.