Data-Informed and Accessibility-Oriented Motion Graphics for Depression-Related Health Communication in Aging Populations

Background/Objectives: Short-form motion graphics are increasingly used in digital health communication. However, limited research has examined their accessibility, interaction quality, and usability for older adults. This study explores the design and evaluation of short-form motion graphics as human–computer interaction systems for depression-related health communication in aging populations. Methods: A data-informed and human-centered approach was adopted, integrating clustering-based analysis, expert evaluation, and user-based assessment. Short-form motion graphics videos and user-generated comments were analyzed to identify design-related themes associated with accessible digital health communication. These insights informed the development of motion graphics prototypes. The evaluation involved independent expert groups and 200 older adult participants. Cognitive load and usability were assessed using a structured questionnaire. Results: The clustering analysis showed moderate cluster separation and provided an exploratory source of design insights. Expert evaluation highlighted the importance of visual clarity, structured content organization, and appropriate motion pacing. User evaluation yielded a mean usability score of 3.95 and a mean cognitive load score of 3.72, indicating generally positive perceptions of the developed motion graphics among participants. Conclusions: The findings suggest that combining data-informed analysis, expert review, and user evaluation may be useful for designing and assessing digital health communication systems for older adults. As this study was exploratory and did not include a control group, the findings should be interpreted within the context of the study and should not be considered evidence of causal relationships.