Google Trends Data About Mental Health During COVID-19 Pandemic Using Time Series Regression

Along with the increasing number of COVID-19 sufferers during the Pandemic period, there was also an increase in searches related to mental health. Researchers have used a lot of Google Trends (GT) data to predict disease. However, researchers dissatisfied with the normalized index of GT began turning to Google Extended Trends for Health (GETH). Permissions and coding skills are needed to be able to access data from GETH. We have made one of the more friendly user interfaces for users without qualified coding skills. Using Google application programming interface (API), the data needed can quickly be taken according to the date parameter and the keywords required. We used 13 keywords using Indonesian to get search data on Google, as well as the number of positive COVID-19 sufferers in Indonesia released by the government. The regression analysis results show that the influence of the thirteen variables related to mental health on the positive cases of COVID-19 is 68.1%. In comparison, the most significant variables of the regression coefficient are cemas (anxiety), bunuh diri (suicide), and insomnia. The most partial variable is insomnia.

I. Introduction

World Health Organization (WHO) declared Corona virus disease 2019 (COVID-19) as a pandemic in March 2020 [1]. Since then, COVID-19 cases have soared and become a pandemic in many countries, including Indonesia [2]. The social restriction followed by the socio-economic shutdown related to COVID-19 has an impact on all life aspects and is a perfect trajectory for a mental health pandemic [3], as reported by research from several countries. A study in India reported anxiety, worry, paranoia about contracting infections, and sleep disturbances during the COVID-19 pandemic. More than 80 percent of respondents considered mental health services necessary to deal with their problems during the COVID-19 pandemic [4]. A Chinese study found that negative emotions (anxiety, depression, and anger) and sensitivity to social risk increased [5]. Anxiety, social isolation, fear of transmission, uncertainty, and economic hardship, especially in populations living in areas of high COVID-19 prevalence, lead to the development or worsening of depression, drug use, and other psychiatric disorders. Moreover, the mass media and psychiatric literature have reported cases of suicide caused by COVID-19 in the US, UK, Italy, Germany, Bangladesh, India, and other countries [6]. Therefore, mental health literacy is important to train people's sensitivity and increase their knowledge. As a result, communities can access the help they need, easily recognize signs of stress and eliminate community stigma and discrimination against mental health survivors. People generally use Google search engine facilities for mental health literacy. During COVID-19, information seeking via the internet and Google Trends (GT)-based research is also growing [7], [8] including questing about mental illnesses such as depression [9]. In addition, GT provides a relative search volume (RSV) to represent the popularity of a specific search word in a specific geographic area over time. However, GT has several limitations due to the normalized data ranging from 1–100, representing the lowest to the highest RSV [10].