Excessive and Unreliable Health Information and Its Predictability for Anxiety: A Cross-Sectional Observational Study

Introduction: Being ignorant or unaware is not expected in a situation like the pandemic of COVID-19 with modern internet connectivity and the era of social media. However, information overload may itself lead to health anxiety. Aims and objectives: This study investigated the predictability of health anxiety with information overload and sociodemographic profiles during the COVID-19 pandemic. Materials and methods: A cross-sectional study was done among 400 caretakers of non-covid patients in a tertiary healthcare medical college. The consenting participants provided their sociodemographic details and responded to the short health anxiety inventory (SHAI), Beck anxiety inventory (BAI) and Information overload scale (IOS) for COVID-19. Results: A total number of 400 participants aged 35.58 ± 10.57 years participated and out of which 88.2% acknowledged health-related anxiety and 56.8% for excessive use of social media. BAI measured anxiety was mild for 19.8%, moderate for 3.5% and severe for 3%. The linear regression analysis predicted health anxiety by three variables only: total anxiety as measured by the Beck anxiety inventory [β = 0.416, t = 9.318, p = 0.000], information overload (rejection of information) [β = 0.171, t = 3.126, p = 0.002], and excessive use of social media [β = 0.124, t = 2.888, p = 0.004]. Conclusion: Information overload, its rejection and excessive use of social media were found to be predictive of health-related anxiety.