Abstract
The rapid evolution of digital technologies has led to the widespread adoption of digital health services, including telemedicine, e-health, and m-health. However, the sustainability of these services relies heavily on users' intention to continue using them over time-known as Continuance Use Intention (CUI). This study aims to systematically review the application of the Expectation Confirmation Model (ECM) in analyzing CUI within digital health contexts. Using a Systematic Literature Review (SLR) approach, 17 peer-reviewed studies published between 2019 and 2024 were examined. The review identifies key factors influencing CUI, including confirmation of initial expectations, perceived usefulness, and user satisfaction. Findings reveal that ECM is the most widely used theoretical framework to explain continuance behavior in digital health, often extended with models such as TAM, UTAUT, and trustbased theories to provide a more holistic analysis. Future research is encouraged to further explore contextual factors such as digital literacy, trust in technology, and types of health conditions, which may moderate the relationships among ECM variables, including self-efficacy and service quality. The results of this review offer both theoretical and practical implications for enhancing the sustainability of digital health platforms.
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