Designing Adaptive User Interfaces for mHealth Applications Targeting Chronic Disease: A User-Centered Approach

TL;DR

The paper tackles the low engagement and long-term adherence challenges of mHealth for chronic disease by developing actionable Adaptive User Interface (AUI) guidelines. Through a two-stage process, it combines qualitative and quantitative studies to generate, refine, and validate nine guidelines, culminating in a case study across four diabetes apps and end-user reviews. The work provides a structured, evidence-based framework for designers and developers to tailor mHealth UIs to diverse patient needs, conditions, and contexts, with demonstrated improvements over generic usability guidelines. This approach offers practical tools to enhance accessibility, personalization, and sustained use in chronic-disease self-management technologies.

Abstract

Mobile Health (mHealth) applications have demonstrated considerable potential in supporting chronic disease self-management; however, they remain under-utilised due to low engagement, limited accessibility, and poor long-term adherence. These issues are particularly prominent among users with chronic disease, whose needs and capabilities vary widely. To address this, Adaptive User Interfaces (AUIs) offer a dynamic solution by tailoring interface features to users' preferences, health status, and contexts. This paper presents a two-stage study to develop and validate actionable AUI design guidelines for mHealth applications. In stage one, an AUI prototype was evaluated through focus groups, interviews, and a standalone survey, revealing key user challenges and preferences. These insights informed the creation of an initial set of guidelines. In stage two, the guidelines were refined based on feedback from 20 end users and evaluated by 43 software practitioners through two surveys. This process resulted in nine finalized guidelines. To assess real-world relevance, a case study of four mHealth applications was conducted, with findings supported by user reviews highlighting the utility of the guidelines in identifying critical adaptation issues. This study offers actionable, evidence-based guidelines that help software practitioners design AUIs in mHealth to better support individuals managing chronic diseases

Figures (14)

• Figure 1: Examples of adaptive user interfaces.
• Figure 2: Research methodology.
• Figure 3: Process of applying STGT for data analysis in the focus group and interview study.
• Figure 4: Memo example
• Figure 5: An overview of challenges and recommendations for designing adaptation.