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

TL;DR

This paper develops and validates user-centered guidelines for adaptive interfaces in mHealth apps, aiming to improve engagement and adherence among users with chronic diseases through a comprehensive two-stage study.

Contribution

It introduces a set of nine evidence-based guidelines for designing adaptive user interfaces in mHealth applications, developed through user and practitioner feedback.

Findings

Identified key user challenges and preferences for adaptive interfaces.

Refined guidelines based on feedback from 20 end users and 43 practitioners.

Validated guidelines through a case study of four mHealth applications.

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