InteractOut: Leveraging Interaction Proxies as Input Manipulation Strategies for Reducing Smartphone Overuse
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Abstract (arXiv)
Smartphone overuse poses risks to people's physical and mental health. However, current intervention techniques mainly focus on explicitly changing screen content (i.e., output) and often fail to persistently reduce smartphone overuse due to being over-restrictive or over-flexible. We present the design and implementation of InteractOut, a suite of implicit input manipulation techniques that leverage interaction proxies to weakly inhibit the natural execution of common user gestures on mobile devices. We present a design space for input manipulations and demonstrate 8 Android implementations of input interventions. We first conducted a pilot lab study (N=30) to evaluate the usability of these interventions. Based on the results, we then performed a 5-week within-subject field experiment (N=42) to evaluate InteractOut in real-world scenarios. Compared to the traditional and common timed lockout technique, InteractOut significantly reduced the usage time by an additional 15.6% and opening frequency by 16.5% on participant-selected target apps. InteractOut also achieved a 25.3% higher user acceptance rate, and resulted in less frustration and better user experience according to participants' subjective feedback. InteractOut demonstrates a new direction for smartphone overuse intervention and serves as a strong complementary set of techniques with existing methods.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Jan 2024.
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Citing papers per year: 2024: 1; 2025: 2; 2026: 1.
4 papers.
- 2024Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse Interventioncited by 5
- 2025WatchGuardian: Enabling User-Defined Personalized Just-in-Time Intervention on Smartwatchcited by 4
- 2025Regressor-Guided Image Editing Shifts Emotion and Disengagement Timing in Social Mediacited by 2
- 2026Learned Parametric Emotion Editing: Real-Time Affective Filtering for On-Device Social Media Videocited by 0
- 2026Learned Parametric Emotion Editing: Real-Time Affective Filtering for On-Device Social Media Video18 Sep 2026
- 2025WatchGuardian: Enabling User-Defined Personalized Just-in-Time Intervention on Smartwatch9 Feb 2025
- 2025Regressor-Guided Image Editing Shifts Emotion and Disengagement Timing in Social Media21 Jan 2025
- 2024Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse Intervention3 Mar 2024