February 17, 2020

Evaluation of Participation in Digital Health Studies

Abhishek Pratap

Evaluation of Participation in Digital Health Studies

The widespread use of smartphones has offered a valuable opportunity to biomedical researchers. Using mobile apps, scientists are now able to design large-scale health research studies in a cost-effective way and, importantly, gather diverse real-world lived experiences of disease over time by recruiting participants from broader geographic regions – at least that is the hope. The real-world data (RWD) gathered through the health research apps also complements traditional research by capturing disease fluctuations at important moments that are often missed between periodic in-person clinic visits.

Title: Indicators of retention in remote digital health studies: across-study evaluation of 100,000 participants
Journal: Nature Digital Medicine
Authors: Abhishek Pratap, Elias Chaibub Neto, Phil Snyder, Carl Stepnowsky, Noémie Elhadad, Daniel Grant, Matthew H. Mohebbi, Sean Mooney, Christine Suver, John Wilbanks, Lara Mangravite, Patrick J. Heagerty, Pat Areán, and Larsson Omberg
Link: https://www.nature.com/articles/s41746-020-0224-8

In the last five years, several digital health studies, including remote interventions and clinical trials, have been conducted using smartphone technology. Despite the success where researchers were able to enroll thousands of research participants in a short amount of time, participant retention and long-term engagement in fully remote research remain a significant barrier for generating robust real-world evidence from RWD. In the study Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants, published in the journal Nature Digital Medicine on Feb. 17, researchers pooled data from eight digital health studies across nearly 110,000 study participants and discovered key factors that affect participant retention.

To avoid collecting biased real-world data there is an urgent need to assess underlying patterns in people’s participation in fully remote studies. If you can’t measure it, you can’t fix it.

A screenshot of a table that shows data from a collection of 8 digital health studies. The table comes from the paper Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants.

The study compiled user-engagement data from eight digital health studies that targeted different diseases ranging from asthma, endometriosis, heart disease, depression, sleep health, and neurological diseases. The compilation of individualized user-level engagement data is one of the largest and most diverse user-engagement datasets to date and has been made publicly available for the broad research community. The data analysis surfaced two key results 1) Half of the participants dropped out of studies within the first week and 2) most studies ultimately weren’t able to recruit demographically or geographically representative participants.

Despite the limitations, several factors, such as partnerships with clinicians and providing research participants fair compensation for their time in the study, could help researchers retain diverse participants in future digital health studies. Unsupervised analysis of engagement data also revealed broadly consistent underlying patterns of participation in remote research. App-usage behavior fell into four clusters, with distinct differences that have semantic and demographic ramifications.

The insights from this research have the potential to inform user enrollment and engagement strategies for improving retention and engagement in future digital health studies.

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Abhishek Pratap

Dr. Abhishek Pratap is a Principal Scientist at Sage Bionetworks. His research focuses on designing effective mobile apps and analytical workflows that will ultimately empower people in assessing their health symptoms and share its management with their care providers.