AUTHOR=Vu Thao Hanh , Tagliabue Marco 

TITLE=Active nudging towards digital well-being: reducing excessive screen time on mobile phones and potential improvement for sleep quality

JOURNAL=Frontiers in Psychiatry

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2025.1602997

DOI=10.3389/fpsyt.2025.1602997

ISSN=1664-0640

ABSTRACT=IntroductionOur society’s reliance on smartphones is a growing phenomenon. Misuse or overuse of smartphones has been associated with negative effects on physical health and psychological functioning, including reduced quality of sleep when used before bedtime. Increasingly, digital users are becoming more aware of how smartphone use impacts their productivity and well-being. Consequently, several digital detox interventions incorporating digital nudges have been introduced to help users reduce their smartphone usage. Digital nudges are freedom-preserving behavior-altering mechanisms that utilize user-interface design. MethodsIn this exploratory study, we examine the effectiveness of a digital nudge—in the form of tracked screen time—as a behavioral intervention to mitigate excessive smartphone use. Secondarily, we explore the potential relationship between screen time and sleep quality. A within-group experimental design, using a randomized controlled trial with a sample of 17 participants, was conducted over 7 days to compare the effectiveness of a tracking-only condition with an active digital nudge condition. ResultsNo significant evidence was found to support the impact of the active digital nudge on reducing screen time (primary outcome). There was a direct correlation between screen time reduction and improved sleep quality (secondary outcome), along with a significant effect of reduced frequency of sleep delay in the active nudge condition (p = 0.026). DiscussionNonetheless, the findings of this study contribute to our understanding of the mechanisms underlying digital nudges and offer valuable insights into how their effectiveness can be improved and optimized from a behavior-analytic perspective.