ABSTRACT
The mobility restrictions due to COVID-19 lockdown impositions have forced people to stay at home in lieu of face-to-face activities. In effect, it has increased people's exposure to the Internet and its perils, brought by excessive information from different media that may lead to the development of health-related anxiety. This phenomenon is known as cyberchondria, where people may have experienced extreme anxiety about their physical health because of repeated internet searches concerning their medical conditions. This paper investigates the possible relationship between health anxiety, information anxiety, and computer self-efficacy toward cyberchondria. Data from a cross-sectional method using online surveys among fresh graduates aged 21-24 in several Philippine higher education institutions were analyzed. The results of the structural model test reveal that both health anxiety and information anxiety may contribute to cyberchondria. The study discusses the implication of the results and offers fruitful research directions for further studies. © ICCE 2022.All rights reserved.
ABSTRACT
This article examines the Google Trends data related to the second COVID-19 wave in India. We investigate the phenomenon of cyberchondria, which potentially causes individuals to avoid getting tested and quarantined directly upon experiencing symptoms for fear of losing their salaries or jobs. We utilize Google Trends data to predict future disease statistics, like the pandemic's impact on human activities and health-related issues in India. By means of a bootstrapped Pearson correlation, a time-lead correlation, and a quantile regression, we found a strong relationship between Google Trend searches and COVID-19 cases. Contextualizing the second COVID-19 wave in India through the lenses of cyberchondria and protection motivation theory, our article notes that, when people develop COVID-19 symptoms, they turn to Google for confirmation and treatment, rather than getting themselves checked early, only getting medically tested, and treated when their health deteriorates. At that stage, given the patients’critical conditions, hospitalization is the only option. This places an unsustainable burden on hospitals, resulting in capacity constraints and increased mortality rates. We suggest using Google Trends data to forecast COVID-19 waves and mobilize the health infrastructure to save lives and facilitate friction-free growth. IEEE