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

2024-05-14

ACM Transactions on Software Engineering and Methodology

AI Summary

Low adherence to and poor accessibility of mHealth applications among patients with chronic diseases stem primarily from static user interfaces that fail to dynamically adapt to users’ health status, functional capabilities, and contextual usage conditions. To address this, this study proposes a user-centered Adaptive User Interface (AUI) design methodology. Employing a two-phase mixed-methods empirical approach—including patient focus groups, dual-cohort surveys targeting healthcare professionals and developers (n=20 and n=43, respectively), comparative analysis of four widely used mHealth apps, and large-scale user review mining—we systematically derived nine evidence-based, high-consensus, and actionable AUI design guidelines. These guidelines effectively bridge the gap between end-user needs and software development practice. Validation through real-world app case studies demonstrates their capacity to accurately identify interface adaptation deficiencies and significantly improve both accessibility and long-term user adherence.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Knowledge Representation and Reasoning: Diagnosis and Abductive Reasoning

Application Category

• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

Mobile Health (mHealth) applications have demonstrated considerable potential in supporting chronic disease self-management; however, they remain underutilized 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 AUI in mHealth to better support individuals managing chronic diseases.

Problem

• Designing adaptive interfaces for mHealth chronic disease apps
• Improving user engagement and adherence in mHealth applications
• Creating evidence-based guidelines for dynamic user interface adaptation

Innovation

• Adaptive User Interfaces tailor to user needs
• Two-stage study develops actionable AUI guidelines
• Guidelines validated by end users and practitioners