Abstract

Cyberchondria is defined as excessive online health research followed by distress. Theoretical models of cyberchondria suggest that it can be influenced by both characteristics of the internet (content, information ranking, amount and quality of information) and individual vulnerability factors (general health anxiety or COVID-19 fear). In order to simultaneously explore the role of both factors, an innovative search engine software (Foogle) was developed and used in the present study that enables manipulation of the presented content and content ranking while also recording users’ online behavior. A total of 36 participants with high and 28 participants with low COVID-19 fear searched for the long-term health effects of COVID-19 using Foogle. They were presented with search engine results that rank long-term health effects of COVID-19 from more to less severe or vice versa (randomized). Results revealed that participants who were presented with articles describing more to less severe long-term COVID-19 health effects accessed articles with a higher mean severity index. In general, participants spent more time on articles depicting more severe content. Participants with high COVID-19 fear felt more anxious post-search than those with low COVID-19 fear and expressed a greater wish to continue searching.

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