Prevalence and predictors of cyberchondria and depression amid COVID-19 pandemic in adult population of Uttar Pradesh, India

Abstract

Background and Aim: COVID-19 pandemic and related measures of containment such as lockdown led to heavy reliance on Internet for education and leisure activities. This study aimed to assess the prevalence and predictors of cyberchondria and depression amid COVID-19 pandemic among adult population of Uttar Pradesh, India. Materials and Methods: A web-based study was conducted among 236 adult participants of Uttar Pradesh during August–November 2021. Standardized tools including Cyberchondria Severity Scale-short version (CSS-SV) and Patient Health Questionnaire-9 were used for eliciting details about cyberchondria and depression. Results: The study highlighted that the cyberchondria cluster comprised 45.3% of participants. Subscale score distribution of CSS-SV was found to be the highest (7.53 ± 2.98) for excessiveness and the lowest (6.40 ± 2.93) for compulsion subscale. Furthermore, majority (56.4%) of the participants had depression in various severities. Multivariate logistic regression analysis predicted factors such as female gender, health-care worker, and duration of watching TV and smartphone usage to be influencing cyberchondria. Strong influence of duration spent (>6 h/day) in watching TV, etc., was found on depression. Conclusion: Cyberchondria and its association with depression are indeed growing health concerns; efforts should be directed toward controlled Internet usage, which involves adhering to credible sources for authentic health-related information.

Keywords

• adult population
• covid-19
• cyberchondria
• depression
• predictors
• prevalence