Individual Differences in the Movement-Mood Relationship in Digital Life Data
Our increasingly digitized lives generate troves of data that reflect our behavior, beliefs, mood, and wellbeing. Such “digital life data” provides crucial insight into the lives of patients outside the healthcare setting that has long been lacking, from a better understanding of mundane patterns of exercise and sleep routines to harbingers of emotional crisis. Moreover, information about individual differences and personalities is encoded in digital life data. In this paper we examine the relationship between mood and movement using linguistic and biometric data, respectively. Does increased physical activity (movement) have an effect on a person’s mood (or vice-versa)? We find that weak group-level relationships between movement and mood mask interesting and often strong relationships between the two for individuals within the group. We describe these individual differences, and argue that individual variability in the relationship between movement and mood is one of many such factors that ought be taken into account in wellbeing-focused apps and AI systems.
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