Care in Pieces
Unpacking Experiences of Using LLMs for Self-management of Endometriosis and PCOS
Ariane Lucchini (TU Delft - Industrial Design Engineering)
Catalina Lagos Rojas (TU Delft - Industrial Design Engineering)
Alessandro Bozzon (TU Delft - Industrial Design Engineering)
Sara Colombo (TU Delft - Industrial Design Engineering)
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Abstract
Women with endometriosis and Polycystic Ovary Syndrome (PCOS) require individualized, long-term, holistic care, yet systemic healthcare barriers leave many managing independently. Increasingly, women are turning to Large Language Models (LLMs), such as ChatGPT, for support in self-management. However, little is understood about how people use and experience LLMs in this context. We employed a feminist participatory approach to collective knowledge production and situated expertise to explore participants' motivations and expectations in using LLMs for self-management. We engaged in co-annotation of personal ChatGPT conversations and collage-making sessions with 8 women living with endometriosis and/or PCOS, centering their lived experiences. We surfaced the layered experiences of self-managing endometriosis and/or PCOS with LLMs and how these compare and contrast with their ideal visions of care. We contribute empirical insights and design considerations for LLM systems providing support in this context.
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