Towards Hormone Health: An Autoethnography of Long-Term Holistic Tracking to Manage PCOS

要旨

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.

受賞
Best Paper
著者
Daye Kang
Cornell, Ithaca, New York, United States
Jingjin Li
AImpower.org, Mountain View, California, United States
Gilly Leshed
Cornell University, Ithaca, New York, United States
Jeffrey M. Rzeszotarski
Cornell University, Ithaca, New York, United States
Xi Lu
University at Buffalo,SUNY, Buffalo, New York, United States
DOI

10.1145/3706598.3713619

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713619

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Digital Health for Different User Needs

G314+G315
7 件の発表
2025-04-30 20:10:00
2025-04-30 21:40:00
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