A Research Agenda to Apply a User-as-Learner Perspective to Digital Health Interventions

Abstract

Several decades of accumulated evidence highlights that digital health interventions (DHIs) can improve symptoms of eating disorders, but that DHIs may also suffer from issues of engagement and dropout. To date, a number of patient- and design-specific predictors of engagement, efficacy, and dropout have been proposed, yet the evidence base for these variables is weak and inconsistent. In this spotlight article, we propose an entirely new class of predictors premised on the notion that successful use of DHIs requires active learning, and consequently that researchers and DHI developers should focus on the integral roles of learning and learner capability for ensuring benefits of DHI for users. Our user-as-learner perspective posits that: (1) knowledge transmission via DHIs does not guarantee that users appropriately understand and apply this content, (2) the dynamics of effective learning established in other learner contexts may also apply to successful engagement with DHIs, yet (3) the characteristics that ensure this success may not be common and consistent among those who sign up to DHIs. We highlight a small yet emerging body of literature in the context of eating disorder-focused DHIs that provide preliminary support for these postulations, and conclude with a series of recommendations to shape a research agenda that places learning dynamics at the heart of DHI design and engagement.