Work

Exploring digital health user engagement: General app usage patterns from a clinical trial with the mLab App

Year: 2026

Type: article

Abstract: The number of digital health applications has rapidly grown over recent years, but many of them are limited by sustainability and scalability. Paradata, the detailed interactions of a user with a piece of software, is straightforward to collect without disrupting the user-experience, and can provide a nuanced understanding of in-app user behavior. In this work we analyze paradata from the mLab App arm of a three-arm, multi-site randomized clinical trial (NYC and Chicago), in a sub-study that evaluates longitudinal, session-level interaction logs with multiple sessions per participant, (registered with Clinicaltrials.gov as NCT03803683), a mobile health application to facilitate at-home HIV testing in at-risk populations. We investigated application-level usage statistics to identify feature usage, as well as common navigational paths within the application. Temporal patterns were observed for login events and test-taking patterns. Despite being under-collected and underreported, paradata reveal feature gaps, guide targeted revisions for subsequent research and implementation, and deepen understanding of user behavior-enabling digital-health applications with lasting impact.

Source: PLOS Digital Health

DOI: 10.1371/journal.pdig.0001452