ENHANCING HEALTH OUTCOMES THROUGH DIGITAL NUDGING: A STUDY OF BEHAVIORAL INTERVENTIONS IN MEDICINE

Abstract

The concept of "nudging"—subtle, non-coercive interventions designed to steer decision-making—has gained significant traction in healthcare, particularly with the advent of digital technologies. This paper explores the emerging field of digital nudging, which leverages interface design and user data to influence health-related behaviors across diverse populations. Grounded in psychological frameworks such as Kahneman’s dual-process theory and behavioral principles like loss aversion and framing effects, digital nudges aim to target intuitive decision-making (System 1) to encourage healthier choices. Using a systematic literature review (SLR) methodology guided by PRISMA and structured through the Antecedents-Decisions-Outcomes (ADO) model, this study synthesizes evidence across digital health interventions. A quantitative comparison using Absolute Effect Size (AES) and Relative Effect Size (RES) metrics identifies framing, social norms, and default settings as the most frequently employed and effective nudge strategies. Notably, multicomponent nudges combining framing, social norms, and loss aversion demonstrated high efficacy (RES up to 33.13%), while default-based interventions showed the highest impact (RES up to 82%). The effectiveness of digital nudges was found to be moderated by contextual and environmental factors, including population health status, digital literacy, and situational barriers such as decision fatigue and engagement variability. For instance, interventions among digitally literate users or in time-sensitive contexts (e.g., sedentary behavior reduction) yielded higher behavioral outcomes, while populations with chronic conditions such as diabetes responded less favorably to generic nudges. This review underscores the importance of tailoring digital nudges to individual and contextual characteristics and offers insights into optimizing design for greater impact in healthcare settings.