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Autores principales: Cao, Yancheng, Ji, Yishu, Fu, Chris Yue, Dharmavaram, Sahiti, Turchioe, Meghan, Benda, Natalie C, Mamykina, Lena, Sun, Yuling, Xu, Xuhai "Orson"
Formato: Preprint
Publicado: 2026
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Acceso en línea:https://arxiv.org/abs/2602.14733
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author Cao, Yancheng
Ji, Yishu
Fu, Chris Yue
Dharmavaram, Sahiti
Turchioe, Meghan
Benda, Natalie C
Mamykina, Lena
Sun, Yuling
Xu, Xuhai "Orson"
author_facet Cao, Yancheng
Ji, Yishu
Fu, Chris Yue
Dharmavaram, Sahiti
Turchioe, Meghan
Benda, Natalie C
Mamykina, Lena
Sun, Yuling
Xu, Xuhai "Orson"
contents Large language models (LLMs) have been increasingly adopted to support patients' healthcare-seeking in recent years. While prior patient-centered studies have examined the capabilities and experience of LLM-based tools in specific health-related tasks such as information-seeking, diagnosis, or decision-supporting, the inherently longitudinal nature of healthcare in real-world practice has been underexplored. This paper presents a four-week diary study with 25 patients to examine LLMs' roles across healthcare-seeking trajectories. Our analysis reveals that patients integrate LLMs not just as simple decision-support tools, but as dynamic companions that scaffold their journey across behavioral, informational, emotional, and cognitive levels. Meanwhile, patients actively assign diverse socio-technical meanings to LLMs, altering the traditional dynamics of agency, trust, and power in patient-provider relationships. Drawing from these findings, we conceptualize future LLMs as a longitudinal boundary companion that continuously mediates between patients and clinicians throughout longitudinal healthcare-seeking trajectories.
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publishDate 2026
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spellingShingle More than Decision Support: Exploring Patients' Longitudinal Usage of Large Language Models in Real-World Healthcare-Seeking Journeys
Cao, Yancheng
Ji, Yishu
Fu, Chris Yue
Dharmavaram, Sahiti
Turchioe, Meghan
Benda, Natalie C
Mamykina, Lena
Sun, Yuling
Xu, Xuhai "Orson"
Human-Computer Interaction
Large language models (LLMs) have been increasingly adopted to support patients' healthcare-seeking in recent years. While prior patient-centered studies have examined the capabilities and experience of LLM-based tools in specific health-related tasks such as information-seeking, diagnosis, or decision-supporting, the inherently longitudinal nature of healthcare in real-world practice has been underexplored. This paper presents a four-week diary study with 25 patients to examine LLMs' roles across healthcare-seeking trajectories. Our analysis reveals that patients integrate LLMs not just as simple decision-support tools, but as dynamic companions that scaffold their journey across behavioral, informational, emotional, and cognitive levels. Meanwhile, patients actively assign diverse socio-technical meanings to LLMs, altering the traditional dynamics of agency, trust, and power in patient-provider relationships. Drawing from these findings, we conceptualize future LLMs as a longitudinal boundary companion that continuously mediates between patients and clinicians throughout longitudinal healthcare-seeking trajectories.
title More than Decision Support: Exploring Patients' Longitudinal Usage of Large Language Models in Real-World Healthcare-Seeking Journeys
topic Human-Computer Interaction
url https://arxiv.org/abs/2602.14733