TY - GEN
T1 - Towards Hormone Health
T2 - 2025 CHI Conference on Human Factors in Computing Systems, CHI 2025
AU - Kang, Daye
AU - Li, Jingjin
AU - Leshed, Gilly
AU - Rzeszotarski, Jeffrey M.
AU - Lu, Xi
N1 - Publisher Copyright:
© 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.
PY - 2025/4/26
Y1 - 2025/4/26
N2 - 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.
AB - 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.
KW - PCOS
KW - autoethnography
KW - hormone health
KW - self-tracking
KW - women's health
UR - https://www.scopus.com/pages/publications/105005771844
U2 - 10.1145/3706598.3713619
DO - 10.1145/3706598.3713619
M3 - Conference contribution
AN - SCOPUS:105005771844
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2025 - Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
Y2 - 26 April 2025 through 1 May 2025
ER -