Gender Blindness by Design. How Interaction Design Shapes Care Labour through Digital Health Technology in Diabetes Management.

Digital health technologies increasingly mediate the everyday management of chronic conditions, promising personalised, data-driven, and empowering forms of care. However, these systems do not emerge as neutral tools. They inherit assumptions from long-standing biomedical paradigms that privilege standardised and implicitly male physiological norms. While gender bias in healthcare has been partly examined at the level of clinical protocols and datasets, the role of interaction design in avoiding gender blindness remains underexplored. This paper explores how gender-indifferent interaction design shapes daily care practices through a qualitative study of Continuous Glucose Monitoring (CGM) systems used in diabetes management. Drawing on a feminist new materialist perspective, we conceptualise digital health technologies as active participants in care practices that co-produce meanings, responsibilities, and agential capacities through their affordances. Empirically, the study combines a series of research activities including embodied autoethnography, semi-structured interviews, and cultural probes with people living with diabetes. Our findings show that CGM systems often function as “silent companions”: while continuously present on the body, they provide limited contextual or interpretive support. Fixed thresholds, standardised visualisations, and non-communicative interaction patterns displace the work of sense-making onto users. This burden is unevenly distributed, particularly affecting women and girls experiencing hormonal variability, which remains invisible in CGM interaction logic despite its clinical relevance. As a result, users perform additional cognitive, emotional, and relational labour to interpret data, justify bodily fluctuations, and manage social expectations. We argue that gender blindness in digital health is materially enacted through interaction design choices, not only through data or representation. By reframing gender bias as an interactional problem, this paper contributes to Interactive Health research by highlighting how design decisions redistribute care labour and shape lived experiences of chronic care beyond measures of usability or clinical accuracy.