Elderly HealthMag: Systematic Building and Calibrating a Tool for Identifying and Evaluating Senior User Digital Health Software
Yuqing Xiao, John Grundy, Anuradha Madugalla, Elizabeth Manias
TL;DR
This work introduces Elderly HealthMag, a dual-lens framework that combines HealthMag (a health-condition–aware extension of InclusiveMag) with an age-calibrated Elderly AgeMag to surface and mitigate intersectional biases in digital health software for older adults. Grounded in a broad literature synthesis, HealthMag yields a compact five-facet model that captures how health status affects interaction, while Elderly AgeMag emphasizes vision and motor constraints in older users. The authors generate data-driven personas via LLMs, calibrated by domain experts, and demonstrate the method through cognitive walkthroughs of two medication-management apps, revealing health-, age-, and intersection-driven barriers and actionable design remedies. The study also shows how dual-lens analysis improves attribution of usability issues and supports reusable artefacts for practitioners, contributing a practical, evidence-based workflow for bias-aware requirements engineering in digital health. Overall, Elderly HealthMag offers a portable, adaptable framework to make DH software more inclusive for older adults with health conditions, with clear guidance for adoption and future work across DH domains.
Abstract
Digital health (DH) software is increasingly deployed to populations where many end users live with one or more health conditions. Yet, DH software development teams frequently operate using implicit, incorrect assumptions about these users, resulting in products that under-serve the specific requirements imposed by their age and health conditions. Consequently, while software may meet clinical objectives on paper, it often fails to be inclusive during actual user interaction. To address this, we propose \textbf{\textit{HealthMag}}, a tool inspired by GenderMag designed to help better elicit, model and evaluate requirements for digital health software. We developed HealthMag through systematic mapping and calibration following the InclusiveMag framework. Furthermore, we integrated this with a calibrated version of an existing AgeMag method to create a dual-lens approach: \textbf{\textit{Elderly HealthMag}}, designed to aid requirements, design and evaluation of mHealth software for senior end users. We demonstrate application and utility of Age HealthMag via cognitive walkthroughs in identifying inclusivity biases in current senior user-oriented digital health applications.