Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Oct 4, 2025
Date Accepted: Apr 13, 2026
Health Information Adoption Among Chronic Disease Patients in China: A Qualitative Interview Study of Patient–Platform Co-shaping
ABSTRACT
Background:
Chronic disease management increasingly relies on digital health information. Traditional health information adoption models predominantly emphasize individual rationality and linear decision-making processes. In the platform era, patients' health information behaviors are increasingly influenced by algorithmic recommendations, interactive design, and platform governance mechanisms—emerging phenomena that existing frameworks inadequately explain.
Objective:
This study aims to construct a theoretical model of health information adoption among patients with chronic diseases that reflects the dynamic influence of digital platform characteristics.
Methods:
This study employs grounded theory methodology, conducting in-depth semi-structured interviews with chronic disease patients in Chengdu, Sichuan, China. Through open coding, axial coding, and selective coding, we systematically analyze data to inductively construct a conceptual model, with particular attention to how patients interpret, evaluate, and integrate digital health information through continuous interaction with platform technologies and governance structures.
Results:
The research developed a model comprising four core categories: (1) Adoption Propensity (motivational, behavioral, and attitudinal layers); (2) Platform Field (information field and institutional field); (3) Moderating Factors (individual and environmental); and (4) Health Outcome. The model reveals a cyclical process wherein patient behaviors continuously shape and are reshaped by the platform field.
Conclusions:
This study proposes a theoretical model that explores how the interaction between digital platforms and patients influences health information adoption among individuals with chronic diseases. The model highlights the crucial role of platform fields in health information behaviors, expanding theoretical understanding of health information behaviors while providing practical insights for the design, governance, and optimization of digital health platforms.
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Copyright
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