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From awareness to adoption: a panoramic perspective on the utilization of Internet Medical Services among Chinese patients with chronic disease
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From awareness to adoption: a panoramic perspective on the utilization of Internet Medical Services among Chinese patients with chronic disease
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Journal Article
From awareness to adoption: a panoramic perspective on the utilization of Internet Medical Services among Chinese patients with chronic disease
2025
Overview
Background
Chronic diseases pose substantial healthcare burdens globally, notably in aging nations like China. Internet Medical Services (IMS) demonstrate significant potential to mitigate healthcare challenges in chronic disease management through optimized resource allocation and enhanced remote care capabilities. However, persistent adoption disparities and the “high demand–low penetration” paradox highlight persistent barriers stemming from the digital divide. This study aims to investigate factors influencing IMS utilization among chronic disease patients, examining their effects across specific IMS domains and acceptance pathways, thereby offering new insights for optimizing chronic disease management.
Methods
This study extended the Technology Acceptance Model (TAM) by integrating eHealth literacy and Technology anxiety to evaluate the utilization of IMS among 520 patients with chronic diseases in Jinan, China. IMS was categorized by functional domains (Information Access, Convenience Services, Online Health) and utilization stages (Awareness, Want, Adoption). The dual-method analysis: Awareness-Want-Adoption Gap (AWAG) matrix for service-specific disparity mapping and Structural Equation Modeling (SEM) to quantify perceptual drivers, providing a panoramic perspective to deconstruct the complex utilization.
Results
Information Access IMS showed the highest acceptance, while Online Health exhibited severe Want-to-Adoption collapse (71.43% gap). Affluent patients demonstrated paradoxical rejection of Online Health despite high Awareness. SEM confirmed Perceived Usefulness (β = 0.338–0.423,
P
< 0.001) and eHealth literacy (β = 0.184–0.395,
P
< 0.001) are significant and direct drivers of IMS utilization, with stage-specificity observed across the utilization process. Matrix analysis identified critical barriers for vulnerable subgroups: rural residents, elders (≥ 70 years), and low-education (≤ 9 years) patients.
Conclusions
IMS adoption is governed by multidimensional determinants beyond access, including cognitive, socio-economic, and other factors. Counterintuitive patterns (e.g., affluent patients’ rejection of Online Health) necessitate tiered interventions, such as eHealth literacy programs for vulnerable groups, service standardization to mitigate distrust, and regulatory frameworks to ensure data security. This study’s dual-method framework (matrix analysis and SEM) critically delineated barrier typologies through staged decomposition, establishing an evidence-based scaffold for optimizing digital health equity.
