Cocreating the Visualization of Digital Mobility Outcomes: Delphi-Type Process With Patients.

Area of Science:

• Digital Health
• Wearable Technology
• Data Visualization

Background:

• Wearable devices offer new ways to measure real-world mobility.
• The Mobilise-D project validated digital mobility outcomes for Parkinson disease, multiple sclerosis, COPD, and hip fracture.
• Optimal visualization of patient mobility data is underexplored.

Purpose of the Study:

• To identify meaningful mobility outcomes for specific long-term health conditions.
• To determine the best methods for visualizing patient mobility data from an end-user perspective.

Main Methods:

• A Delphi-type protocol with patients as experts was used over three questionnaire rounds.
• Round 1 gathered qualitative feedback on mobility aspects influenced by health conditions.
• Subsequent rounds involved co-creating and refining visualizations based on patient and expert feedback, rating usefulness and clarity.

Main Results:

• Key outcomes like walking speed and step count were identified for different conditions.
• Patient feedback guided the development of visualizations for mobility data.
• While consensus on specific visualizations wasn't reached, participants generally found them understandable.

Conclusions:

• Recommendations for future mobility data visualizations were developed.
• Visualizations should prioritize readability, accessibility (e.g., for color blindness), and incorporate patient-specific factors.
• Close patient collaboration is essential for creating meaningful and effective data representations.