Adaptive user interfaces in systems targeting chronic disease: a systematic literature review

TL;DR

This systematic review analyzes 48 studies on adaptive user interfaces in eHealth systems for chronic disease management, highlighting current approaches, limitations, and research trends to guide future development.

Contribution

It categorizes key adaptive interface approaches, data sources, techniques, and elements, providing a comprehensive overview of the field and identifying research gaps.

Findings

Various data sources and collection techniques are used for adaptation.

Multiple adaptive mechanisms and interface elements are identified.

Gaps and trends in adaptive UI research for chronic diseases are highlighted.

Abstract

eHealth technologies have been increasingly used to foster proactive self-management skills for patients with chronic diseases. However, it is challenging to provide each user with their desired support due to the dynamic and diverse nature of the chronic disease and its impact on users. Many such eHealth applications support aspects of `adaptive user interfaces' -- interfaces that change or can be changed to accommodate the user and usage context differences. To identify the state-of-art in adaptive user interfaces in the field of chronic diseases, we systematically located and analysed 48 key studies in the literature with the aim of categorising the key approaches used to date and identifying limitations, gaps and trends in research. Our data synthesis is based on the data sources used for interface adaptation, the data collection techniques used to extract the data, the adaptive mechanisms used to process the data and the adaptive elements generated at the interface. The findings of this review will aid researchers and developers in understanding where adaptive user interface approaches can be applied and necessary considerations for employing adaptive user interfaces to different chronic disease-related eHealth applications.