APA
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Wang, W., Khalajzadeh, H., Grundy, J. C., & Madugalla, A. (2023). Adaptive User Interfaces for Software Supporting Chronic Diseases. IEEE Symposium on Visual Languages / Human-Centric Computing Languages and Environments.
Chicago/Turabian
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Wang, Wei, Hourieh Khalajzadeh, John C. Grundy, and Anuradha Madugalla. “Adaptive User Interfaces for Software Supporting Chronic Diseases.” IEEE Symposium on Visual Languages / Human-Centric Computing Languages and Environments (2023).
MLA
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Wang, Wei, et al. “Adaptive User Interfaces for Software Supporting Chronic Diseases.” IEEE Symposium on Visual Languages / Human-Centric Computing Languages and Environments, 2023.
BibTeX Click to copy
@article{wei2023a,
title = {Adaptive User Interfaces for Software Supporting Chronic Diseases},
year = {2023},
journal = {IEEE Symposium on Visual Languages / Human-Centric Computing Languages and Environments},
author = {Wang, Wei and Khalajzadeh, Hourieh and Grundy, John C. and Madugalla, Anuradha}
}
The rising prevalence of chronic diseases necessitates effective self-management strategies. mHealth interventions have shown promise in supporting self-management, but their under-utilization remains a challenge. Individuals with chronic diseases exhibit significant variations in their conditions, severity levels, and associated complications, highlighting the need for more tailored approaches. Adaptive User Interfaces (AUIs) can be used as a solution to address the diverse and dynamic needs of individuals with chronic diseases. We have created an AUI prototype based on existing literature, incorporating presentation, content, and behaviour adaptation. Our user study employs a mixed-method research approach to gather insights from users by interacting with our prototype. The future plans of the study aim to utilise insights obtained from the data analysis to automatically generate AUIs using a model-driven approach.
