Wei Wang

Research Fellow

“We feel and know that we are eternal”

Baruch Spinoza

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Adaptive user interfaces for software supporting chronic diseases

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Abstract

This paper studies adaptive user interfaces for people managing chronic diseases.

A normal health app often gives every person the same interface. But people have different health needs, abilities, habits, and preferences.

The study used a prototype and gathered feedback from people to understand what kinds of adaptation may help.

The paper gives design ideas for health apps that can better fit different users.

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🔍 Abstract

mHealth interventions hold promise for supporting the self- management of chronic diseases, yet their limited use remains a problem. Given the significant variability among indi- viduals with chronic diseases, tailored approaches are imperative. Adaptive User Interfaces (AUIs) may help to address the diverse and evolving needs of this demographic. To investigate this approach, we developed an AUI prototype informed by existing literature and used it as the basis for a focus group and interview study involving 22 participants. Concurrently, a quantitative survey was carried out to extract preferences for AUIs in chronic disease related applications with 90 participants. Our findings reveal that user engagement with AUIs is influenced by individual capabilities and disease severity. Additionally, we explore user preferences for AUIs, expanding the adaptation literature by uncovering usage challenges, proposing practical strategies for enhanced AUI design, and acknowledging potential trade-offs between usability and adaptation. Lastly, we present design considerations for AUIs in chronic disease applications, aiming to prevent user overload and maintain critical software functionality and usability aspects.

🎤 Talks

Poster Presentations

Wei Wang, Hourieh Khalajzadeh, John Grundy, Anuradha Madugalla and Humphrey O. Obie. "Adaptive user interfaces for software supporting chronic diseases". In 2023 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) (pp. 215-218). IEEE. UPV