Abstract 21029: Achieving High Retention in Mobile Health Research Using Design Principles Adopted From Widely Popular Consumer Mobile Apps
Introduction: While mHealth platforms can enable rapid participant recruitment, the first 5 ResearchKit apps retained less than 10% of daily participants after the first 90 days, whereas well-optimized consumer mobile apps like Instagram and Twitter retain 31% and 48%, respectively. We proposed to apply design principles from the world of consumer internet to achieve high engagement and retention in a mHealth study.
Methods: We enrolled 14,011 users of Cardiogram for Apple Watch app into the Health eHeart Study, an IRB-approved study at UCSF. We applied 3 key design principles to drive engagement and retention. First, give valuable insights back to user—e.g., notify users of abnormal heart rate spikes, and show when exercise caused a lower resting heart rate trend—using Gottman’s ratio: for every negative insight, give 5 positive ones. Second, minimize latency so users’ data updates many times per day. Third, use simple user interfaces that easily visualize trends and provide insights in small digestible formats.
Results: Mean age was 42.3 ± 12.1, 31% were women. Seven days after app install, 64% of participants were active; 63% were active after 30 days, and 54% after 90 days. Retention was consistent across age groups—day 90 retention was 52% for 20-40 y.o., 55% for 40-60, and 49% for above 60. Refreshing data as frequently as possible had the highest impact on user engagement—in A/B testing, where heart rate visualizations were updated less frequently, we saw 20.9% drop in daily active users (51951 to 41094) within 7 days. The ratio of daily to monthly active users, a key measure of engagement, is 69.8% in our study, while average mHealth app is 8%.
Conclusions: By applying design techniques from consumer mobile apps, we achieved day 90 retention 5x higher than the best ResearchKit app, showing that mHealth studies can retain large cohorts of participants and collect unique ambulatory health data with high engagement, improving the impact of mobile health interventions.
- Heart rate/Heart rate variability
- Cardiovascular health
- Cardiovascular disease prevention
- Big Data
Author Disclosures: G.H. Tison: Consultant/Advisory Board; Significant; Cardiogram Inc. K. Hsu: Employment; Significant; Cardiogram Inc. Ownership Interest; Significant; Cardiogram Inc. J.T. Hsieh: Employment; Significant; Cardiogram Inc. Ownership Interest; Significant; Cardiogram Inc. B.M. Ballinger: Employment; Significant; Cardiogram Inc. Ownership Interest; Significant; Cardiogram Inc. M.J. Pletcher: None. G.M. Marcus: Research Grant; Significant; Cardiogram Inc. J.E. Olgin: Consultant/Advisory Board; Significant; Cardiogram Inc.
- © 2017 by American Heart Association, Inc.