The Problem
Patient education visuals are often created for broad audiences without enough evidence about how people actually interpret them. For patients with low health literacy, complex medical illustrations can become difficult to understand, emotionally overwhelming, and less useful for supporting informed health decisions.
The solution
I developed a mixed-methods UX research framework to evaluate how users attend to, interpret, and emotionally respond to medical illustrations. The approach combines eye tracking, cognitive interviews, survey measures, and comparative design testing to generate actionable recommendations for clearer, more accessible patient education experiences.
Multimodal UX evaluation
Combined behavioral gaze data with qualitative interviews and survey responses to capture both what users looked at and why those elements mattered.
Evidence-based design insight
Identified how specific illustration features shaped comprehension, confusion, anxiety, and perceived usefulness.
Scalable health-tech relevance
Translated findings into design principles that can inform patient portals, digital education tools, clinical decision support interfaces, and AI-generated health content.
Research Strategy
Stimulus & Experience Design
Developed and curated diverse healthcare communication materials through cross-functional collaboration with clinical, design, and technical stakeholders.
Behavioral Interaction Analysis
Captured and analyzed real-time user attention and interaction patterns using eye tracking, gaze analysis, and behavioral metrics.
User Understanding & Emotional Response
Conducted qualitative and quantitative studies to evaluate comprehension, confusion, trust, cognitive load, and emotional response.
Comparative UX Evaluation
Evaluated how design variations and communication strategies impact user understanding, engagement, and decision-making.
Multimodal Insight Generation
Integrated behavioral data, qualitative feedback, and quantitative measures to generate evidence-based UX and healthcare communication insights.
Skills demonstrated
Healthcare UX Research
Designed studies to evaluate comprehension, cognitive load, trust, attention, and emotional response in healthcare communication.
HCI & Behavioral Analysis
Used eye tracking, gaze behavior, and user interviews to understand interaction with complex visual information.
Information Design Strategy
Generated evidence-based design guidance for visual clarity, labeling, hierarchy, and accessibility.
Mixed-Methods Research
Integrated qualitative, quantitative, behavioral, and health literacy data to generate actionable UX insights.
Cross-Functional Collaboration
Collaborated across clinical, research, design, and technical teams to improve usability and communication effectiveness.
Health AI Applications
Produced insights relevant to AI-generated education, adaptive communication systems, and patient-facing health technologies.
Why this matters
Complex health information must be not only medically accurate, but also understandable, accessible, and emotionally appropriate for diverse patient populations.