"Chasing Shadows": Understanding Personal Data Externalization and Self-Tracking for Neurodivergent Individuals

A team of researchers from Chalmers University of Technology and the IT University of Copenhagen has published groundbreaking research on how neurodivergent individuals experience self-tracking, particularly around the complex phenomenon of 'masking'—where individuals suppress neurodivergent traits to fit social norms. Their paper, "Chasing Shadows," accepted to the prestigious 2026 ACM CHI Conference on Human Factors in Computing Systems, challenges the fundamental assumption that personal data collection automatically leads to self-insight. Through a meticulous two-phase qualitative study involving nine participants with autism and/or ADHD, the researchers documented the substantial emotional and interpretive labor required to engage with this data.

The study's first phase involved a workshop where six participants created visual representations of their masking experiences. Three participants then continued to a two-week period where they designed and used personalized self-tracking tools focused on 'unmasking.' Using reflexive thematic analysis, the researchers identified that the context-dependent nature of neurodivergent experiences makes standardized tracking tools inadequate. They developed a working model of emotion in self-tracking with three key dimensions that shape engagement. Crucially, the research suggests that facilitated sharing of experiences with peers can validate emotional responses and support healthier reflection, pointing toward a new design paradigm for assistive technology that centers emotional labor and community support over purely individual data quantification.