Examining individual differences through ‘everyday’ smartphone behaviours: Exploring theories and methods.

The mass adoption of digital technologies has instigated a transition whereby people are no longer ‘independent organic actors’ in society but have amalgamated with the technology they use on a daily basis. Consequently, people leave behind a ‘digital fingerprint’ whenever they use technologies such as smartphones, and the qualities of this trace can predict a variety of characteristics about the user. In this thesis, I explore how individual differences such as personality, demographics, and health relate to directly observable smartphone behaviours, that are logged ‘in situ’ via software installed on the device itself. By adopting an interdisciplinary approach between psychology and computer science, this thesis primarily considers the theoretical (chapter two), ethical (chapter three) and methodological (chapter four) underpinnings required to explore these human-smartphone relationships. Notably, traces of use do not have to be complex, as meta-data such as the smartphone operating system a person uses can reveal information regarding a user’s personality, as long as there is trace-to-trait relevance. Findings from chapters five and six also reveal that some individual differences can be better predicted from objective smartphone use than others. For example, age and gender can be discerned from smartphone usage logs whereas, mental health variables only had small positive correlations with smartphone screen time. However, an important contribution of this thesis resides in its methodological considerations, as self-reports of technology use can impact the relationships with individual differences and cannot be used as a substitute for objective logs. All the above has applied implications for security and health, which can benefit from the ability to infer characteristics about people, when self-reports are arduous, unfeasible or lack scientific rigour