From user feedback to iterative decision-making: A low-burden multi-channel feedback framework for mobile health applications targeting non-communicable diseases

Abstract

Mobile health applications (mHealth Apps) can support the long-term management of non-communicable diseases (NCDs). However, their practical value is commonly limited by low user dropout rates and declining engagement over time. To identify meaningful directions for further improvement, a more comprehensive user evaluation is needed. Existing evaluation methods generally rely on questionnaires and interviews, which can provide valuable quantitative and qualitative evidence. At the same time, studies on user-generated content (UGC) show that free-text feedback can also reveal specific directions for product iteration. Yet these sources of feedback are often collected and analysed separately. Further exploration is required on how to integrate multiple feedback sources while minimising the burden on users with limited time and energy, thereby generating actionable evidence to support subsequent iterations. Therefore, this study proposes a low-burden, multi-channel user feedback framework for NCDs mHealth Apps. It integrates three types of feedback—questionnaires, interviews, and UGC—to obtain more comprehensive user feedback evidence and provide a basis for subsequent iterations. The framework comprises three stages: feedback collection and problem identification, cross-source evidence collation, and iteration-oriented outcome delivery. It aims to gather more comprehensive, timely user feedback, facilitating product iterations that better align with user needs and laying the groundwork for future validation in real-world settings.