Polycystic ovary syndrome (PCOS) is a common hormonal disorder affecting 11-13% of women of reproductive age, characterized by a wide range of symptoms (e.g., menstrual irregularity, acne, and obesity) that varies among individuals. While self-tracking tools help PCOS patients to monitor their symptoms and find personalized treatment, they often focus on regular periods of healthy women with inadequate support for the 1) personalization and 2) long-term holistic tracking necessary for managing complex chronic conditions like PCOS. To bridge this gap, the first author (who has PCOS) conducted an autoethnographic study of holistic self-tracking over a period of ten months in an effort to manage her condition. Our results highlight the challenges of personalized, holistic, long-term tracking in medical, socio-cultural, temporal, technical, and spatial contexts. Based on these insights, we provide design implications for tracking tools that are more inclusive and sustainable.
https://dl.acm.org/doi/10.1145/3706598.3713619
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)