Abstract
Metabolic syndrome (MetS) refers to the co-occurrence of health conditions that increase the risk of cardiovascular disease, stroke and type 2 diabetes. It disproportionately affects low socioeconomic (SEP) populations, and traditional healthcare often fails to support lasting lifestyle changes. While eHealth interventions are promising many lack personalization for high-risk, low-SEP groups. To bridge this gap, we developed the HealthBox, a tailored eHealth tool combining tele monitoring and digital coaching to promote healthier habits and reduce chronic disease risk. A key step was understanding user diversity to guide personalization strategies. In this first-phase study, we conducted semi- structured interviews with nine MetS patients, identifying personalization determinants across three categories: personal and health factors, behavioral tendencies, and system-related aspects. These insights highlight user variability in managing MetS and engaging with eHealth, forming a foundation for future personalized interventions.
Keywords
Metabolic Syndrome; E Health; Personalization; Determinants
DOI
https://doi.org/10.21606/iasdr.2025.651
Citation
Faber, J., Van der, S.H., Willems, S.,and Kraal, J.(2025) Designing for diversity: identifying Determinants to Guide Personalization of eHealth Tools, in Chang, C.-Y., and Hsu, Y. (eds.), IASDR 2025: Design Next, 02-05 December, Taiwan. https://doi.org/10.21606/iasdr.2025.651
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Conference Track
Track 9 - Healthcare Design
Designing for diversity: identifying Determinants to Guide Personalization of eHealth Tools
Metabolic syndrome (MetS) refers to the co-occurrence of health conditions that increase the risk of cardiovascular disease, stroke and type 2 diabetes. It disproportionately affects low socioeconomic (SEP) populations, and traditional healthcare often fails to support lasting lifestyle changes. While eHealth interventions are promising many lack personalization for high-risk, low-SEP groups. To bridge this gap, we developed the HealthBox, a tailored eHealth tool combining tele monitoring and digital coaching to promote healthier habits and reduce chronic disease risk. A key step was understanding user diversity to guide personalization strategies. In this first-phase study, we conducted semi- structured interviews with nine MetS patients, identifying personalization determinants across three categories: personal and health factors, behavioral tendencies, and system-related aspects. These insights highlight user variability in managing MetS and engaging with eHealth, forming a foundation for future personalized interventions.