Abstract
INTRODUCTION: With population aging, the burden of chronic diseases is increasing, placing substantial pressure on individuals and health systems. Poor medication adherence remains a major barrier to effective chronic disease management and the efficient use of healthcare resources. Existing interventions rely largely on education or single-modality reminders, and systematic empirical research on interface design, wearable integration, and environmental adaptation remains limited. METHODS: To address this gap, this study employed an extended discrete choice experiment (DCE) framework to quantify the preference structures of older users regarding reminder modality, confirmation method, font and layout, wearable integration, and environmental adaptation strategies. A total of 203 valid responses were collected, and overall trends and group differences were examined using a mixed logit model and latent class analysis. RESULTS: The mixed logit model showed that older adults exhibited positive utility estimates for several interface attributes, including multimodal reminders, adaptive font and layout, and single-tap confirmation. They also preferred coordinated smartphone-smartwatch use under the wearable integration attribute. For environmental factors, both context-adaptive and biophilic themes were associated with positive utility estimates. These themes were implemented through interface-level visual cues, including natural color palettes, background imagery, and context-responsive visual adjustments, suggesting that alignment between interface cues and environmental elements can enhance adherence motivation. The latent class analysis further identified two user groups. The Efficiency-Context group (84.2%) preferred simple, efficient, and low-burden interactions, while the Cue-Wearable group (15.8%) valued multimodal prompting and device coordination but showed limited responsiveness to layout or environmental themes. DISCUSSION: Overall, the findings suggest that optimizing interface and environmental elements can support medication adherence among older adults and provide quantitative design evidence for age-friendly digital health systems.