Does Personalized Nudging Wear Off? A Longitudinal Study of AI Self-Modeling for Behavioral Engagement

TL;DR

This longitudinal study investigates how AI self-modeling influences sustained fitness engagement, revealing initial gains from visual self-modeling that diminish over time, emphasizing the importance of understanding temporal effects in personalized nudging.

Contribution

It provides one of the first long-term evaluations of AI self-modeling for behavior change, highlighting the dynamics of motivation and habituation over several weeks.

Findings

Visual self-modeling initially boosts performance

Auditory self-modeling shows no significant effect

Performance stabilizes after two weeks due to habituation

Abstract

Sustaining the effectiveness of behavior change technologies remains a key challenge. AI self-modeling, which generates personalized portrayals of one's ideal self, has shown promise for motivating behavior change, yet prior work largely examines short-term effects. We present one of the first longitudinal evaluations of AI self-modeling in fitness engagement through a two-stage empirical study. A 1-week, three-arm experiment (visual self-modeling (VSM), auditory self-modeling (ASM), Control; N=28) revealed that VSM drove initial performance gains, while ASM showed no significant effects. A subsequent 4-week study (VSM vs. Control; N=31) demonstrated that VSM sustained higher performance levels but exhibited diminishing improvement rates after two weeks. Interviews uncovered a catalyst effect that fostered early motivation through clear, attainable goals, followed by habituation and internalization which stabilized performance. These findings highlight the temporal dynamics of personalized nudging and inform the design of behavior change technologies for long-term engagement.