Empowering Users through Feedback-adaptive Personal Informatics Tools to Support Wellbeing and Self-Compassion

Abstract

In this extended abstract for the CHI 2026 Student Mentoring Program, I describe my ongoing PhD research. In my work, I focus on how the design of data visualisations based on personal data (metrics) in Personal Informatics (PI) systems influence user behaviour and wellbeing. PI systems often assume a static ‘default’ body, neglecting the reality that our bodies change across life stages and contexts, and so do our needs and routines. This lack of consideration for life’s dynamics, the tool’s inherent performance-driven narrative, and limitations in transparency, can lead to negative thought cycles, consequently resulting in negative emotions towards oneself. My work is motivated by the societal importance of designing PI technologies that, instead, are more self-compassionate and support user wellbeing. All in all, I aim to explore: (i) how we can design adaptive metrics that support agency; and (ii) empower users in their PI journey accordingly.