REDESIGNING
WEARABLE UX
UX Research, Mixed-Methods Study
What health and fitness features on smartwatches do older adults use most frequently, and in what contexts?
What usability, accessibility, and interaction barriers do older adults face when using advanced smartwatch features, and how can these barriers be mitigated?
We will discuss how I came up with these research questions in the Define section below.
1. Discover
Before jumping into solutions, I needed to understand why older adults were not fully engaging with smartwatch health features. I began by exploring existing research, adoption trends, and gaps in current wearable design for this demographic.
To understand the broader landscape, I began with a literature review on wearable technology use among older adults. Research showed that while smartwatches have the potential to support preventive care, adoption remains low in users aged 50–65 due to:
Small screen sizes and cluttered interfaces
Difficulty interpreting health metrics like sleep and calories, leading to confusion and low confidence in the data
Limited customization and accessibility options
Concerns about how clearly and transparently the device presents personal health insights
Reports also indicated that only 14–25% of older adults actively use wearable health devices, despite a growing market. These insights highlighted a significant gap between product capabilities and user needs in aging populations.
This exploration made it clear that the problem wasn’t just about adoption, but about continued engagement and usability. Most existing solutions were not designed with older adults in mind, overlooking age-related changes in vision, cognition, and tech confidence.
These findings shaped the motivation for this project: to uncover real-world interaction challenges older adults face with smartwatches and propose design improvements rooted in their needs.
2. Define
After exploring the broader landscape in the Discover phase, I arrived at a critical turning point: defining the core problem. As shown in the Double Diamond above, this marks the point where broad exploration gives way to focused inquiry.
Synthesizing insights from secondary research and adoption trends, I narrowed my focus to the most pressing issues: usability challenges, engagement drop-off, and lack of clarity in interpreting health data. These themes shaped the foundation of the next phase, guided by two key research questions:
What health and fitness features on smartwatches do older adults use most frequently, and in what contexts?
What usability, accessibility, and interaction barriers do older adults face when using advanced smartwatch features, and how can these barriers be mitigated?
These questions helped frame a research direction that prioritized real-world usage, task-level pain points, and personalization needs — while also probing confidence and trust in how health data is presented.
3. Develop
With clearly defined research questions, I moved into the exploratory phase—using mixed-methods research to understand how older adults actually interact with their smartwatches, where they succeed, and where they struggle.
To answer the research questions and explore how older adults interact with smartwatch health features, I conducted a mixed-methods study that included surveys, contextual inquiries, post-task surveys, and in-depth interviews.
🧾 Survey (n = 30)
Designed a 19-question survey using Qualtrics, targeting adults aged 50–65 who use smartwatches for health. Questions focused on feature usage, satisfaction, navigation, and customization preferences.
Distribution: Reddit forums, flyers, word of mouth
Screening ensured participants were in the target age range and active smartwatch users
👀 Contextual Inquiry (n = 7)
Observed participants performing 7 tasks (e.g., setting goals, checking sleep data) over Zoom. Used a structured script and visual prompts to ensure consistency.
Conducted a pilot with 2 participants to refine task flow
Measured task completion, effort, and interface interaction patterns
✅ Post-Task Surveys
After each task, participants completed a short survey via Google Forms to capture satisfaction, effort, confidence, problems faced and task relevance.
🗣Interviews
This was followed by semi-structured interviews to explore deeper insights into their experiences, frustrations, and expectations
4. Deliver
Transitioning into the Solution Space: The second half of the Double Diamond guided the synthesis of research findings into actionable design.
After analyzing survey results, task performance, and interview responses, I identified patterns that directly answered my research questions. These findings revealed both what users valued and what design gaps limited their experience—guiding clear, evidence-based design recommendations.
🔍 Key Insights
This phase revealed both what older adults value in smartwatch health features and where design breakdowns occur—directly answering the research questions.
🧠 What Users Valued Most (RQ1)
Heart rate monitoring (90%) and step counting (87%) were the most trusted and frequently used features.
These features were seamlessly integrated into daily routines and promoted healthy habits.
Users preferred simple, passive tracking that required minimal interaction.
⚠️ Where Users Struggled (RQ2)
Small screens, low readability, and multi-layered menus made navigation difficult.
Features like sleep tracking, health tips, and medication reminders had poor discoverability and unclear outputs.
Users expressed low confidence in interpreting complex metrics, which reduced trust and engagement.
To validate these usability challenges, I compared expected vs. actual time and post-task confidence scores. Key breakdowns occurred in sleep tracking and health tips.
🎯 What Users Wanted (RQ2)
Simplified customization workflows — users wanted to easily adjust alerts, personalize dashboards, and hide non-relevant features.
Natural language feedback and visual trends to better understand health data.
A more holistic health experience with tools for stress, nutrition, and long-term goal setting.
💡 Design Recommendations
Based on the research findings, I proposed the following:
⚙️ Guided Onboarding
Streamline goal and dashboard setup — 50% rated customization “extremely important” (avg. 4.5/5)🔋 Battery Optimization
Add low-power modes for overnight features — 43% cited battery drain as a barrier🧘 Wellness Features
Integrate nutrition tracking, stress tools, and multi-activity logging — frequently requested in interviews📊 Visual Insights
Use clear trend visuals (e.g., sleep graphs, activity progress) — users struggled with complex summaries📬 Contextual Health Tips
Personalize suggestions based on behavior — feature had lowest task scores and poor relevance🔐 Metric Transparency
Add tooltips or trend explanations to show how health data is calculated — builds user trust
This project demonstrated how structured, user-centered research can surface meaningful design opportunities that directly improve usability and engagement for older adults. By connecting observed user behavior to specific design solutions, I was able to deliver actionable outcomes grounded in real needs. These findings offer a foundation for creating more inclusive, trustworthy health tech moving forward.
Gained hands-on experience managing a full end-to-end UX research process independently
Learned to adapt research methods for older adults with varying levels of digital literacy
Improved my ability to synthesize qualitative and quantitative data to identify actionable insights
Discovered the importance of data trust and transparency in health tech adoption
Strengthened my skills in turning user needs into validated design recommendations
Practiced storytelling with research, making complex findings clear and engaging for diverse audiences
