Information overload regarding COVID-19: Adaptation and validation of the cancer information overload scale

Sujit Sarkhel, Ajay Kumar Bakhla, Samir Kumar Praharaj, Malay Kumar Ghosal

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Access to excessive information from multiple sources relating to COVID-19 in a short span of time can have detrimental effects on individuals. Aim: The study aims to validate Corona Information Overload Scale (CoIOS) by adaptation of Cancer Information Overload scale (CIOS) on English speaking Indian citizens. Materials and Methods: An online survey was carried out using Google Form on 300 individuals out of whom 183 responded. The CoIOS was to be filled up. It was an 8 item Likert type scale with responses ranging from “strongly agree” to “strongly disagree.” Results: Principal components analysis showed two components with an initial eigenvalue > unity (3.38 and 1.09), with 42.33% and 13.64% of variance, respectively, making a total of 55.97% variance. The composite reliability value was also found to be 0.789 and 0.815 for factors I and II, respectively, convergent validity and discriminant validity calculation also affirmed good construct reliability. Conclusion: CoIOS appears to be a valid and reliable scale for measuring health information overload in relation to COVID-19. However, it has a two factor component, namely “excessiveness of information” and “rejection of information. .

Original languageEnglish
Pages (from-to)481-487
Number of pages7
JournalIndian Journal of Psychiatry
Volume62
Issue number5
DOIs
Publication statusPublished - 01-09-2020

All Science Journal Classification (ASJC) codes

  • Psychiatry and Mental health

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