Personalized Nudging in Healthcare to Drive Patient Compliance

Patient compliance is critical for positive health outcomes, particularly given the current strain on healthcare systems and the growing need for patients to actively manage their health. Digital nudges—subtle interventions designed to influence behavior without restricting choice—offer a promising avenue to support ongoing adherence to treatment and health behaviors. This research will explore the potential of cognitively, affectively, and behaviorally oriented nudges in healthcare, focusing on how each type can enhance patient compliance. We will also examine the role of machine learning (ML) and artificial intelligence (AI) in enhancing nudge personalization, and, in turn, patient compliance. Through this study, we aim to understand which types of nudges, or combinations thereof, are most effective in promoting patient adherence. Our future field experiment leverages a 2x3 design to test “smart” and “dumb” versions of a variety of digital nudges. We contribute to digital health and nudge theory by demonstrating how personalized, context-aware “smart” nudges can optimize patient engagement and improve health outcomes.