Self-tracking technologies are reshaping individuals’identity perception, trust patterns, and behavioral decision-making mechanisms，thus putting forward the concepts of digital avatar and digital trust to elucidate how individuals, through the interplay of data, technology, and society, progressively construct a datacentric self-identity. The findings show that the digital avatar proceeds through a trajectory encompassing data externalization, self-datafication, and subsequent behavioral adaptation, ultimately leading individuals to adopt a“data-as-self”cognitive schema. Meanwhile, user trust evolves from verifying data veracity to relying on technological feedback and, ultimately, accepting algorithmic authority, thereby resulting in a relinquishment of judgment to systemic processes. While this trust paradigm optimizes health management and behavioral regulation, it also engenders risks such as cognitive offloading, social pressure, and privacy anxieties. With the growing integration of AI-assisted decision systems, the tendency to“trust technology and offload cognition” becomes increasingly prominent. To address these challenges, the study proposes reconstructing a more explainable and user-sovereign digital trust framework by enhancing data transparency, optimizing feedback mechanisms, and strengthening privacy controls.
