Infodemiology : Studying rhythmicity in online health information behaviour

Abstract

The aim of this thesis is to examine the rhythmicity and temporal variations of online health information behaviour. Time and temporal aspects have previously been neglected in information science, as well as in research on health information behaviour. Yet, these aspects are of great significance, as health is a dynamic process bound by rhythmicity and temporal structures. The health related issues and threats, or knowledge gaps, that individuals face, might rise, change and intensify at any time of the day, week, month or year, and have been suggested to trigger health information behaviour. Health information behaviour is defined as how people seek, obtain, evaluate, categorise and use health-related information in relation to their health. This behaviour is rather extensive, and today individuals are able to make sense of their situation and engage in health information behaviour online, anywhere and at any time. People frequently try to find out about and treat symptoms, diagnose themselves, or manage illness before or even without the involvement of health professionals. This means that much of this behaviour fall outside the scope of traditional healthcare systems, and leaves a substantial amount of relevant data about different health behaviours unexplored. Today however, a majority of this health information behaviour happens online, leaving vast amounts of digital traces behind. Aggregating and analysing these digital traces to study online health behaviours has been dubbed infodemiology, and is rooted in the idea that there is a relationship between population health on one hand, and information and communication patterns on the internet, on the other. This thesis aims to answer if the infodemiology approach and metrics can be utilised to study rhythmicity and temporal aspects of online health information behaviour in relation to different health issues. Answering these questions not only allows us to gain insights into a new contextual aspect of health information behaviour, it also allows us to understand the multidimensional relationship between time and health. Individuals and their health status are different at different times, and health related behaviours follow these rhythmical and cyclical patterns and variations, which can have practical implications for many disciplines. This is especially relevant in an era where individuals are expected to take greater responsibility for their health with the help of an abundance of digital means. Turning the focus to time and studying when health information behaviour happens can have far-reaching consequences.