Before You Scroll Again: Predicting Regretful Social Media Sessions from In-the-Wild Contextual and Wearable Sensing

2026-06-07

AI Summary

This study addresses the challenge of predicting regret over social media use in real-world settings. Through a seven-day in-the-wild experience sampling study integrating smartphone usage logs, physiological sensing via Bangle.js 2 smartwatches, and session-level questionnaires and interviews (N=21 participants, 1,445 sessions), it demonstrates for the first time that the discrepancy between intended and actual usage is a stronger predictor of regret than conventional duration-based metrics. Regret is found to be more likely following nighttime use or use after productivity-related applications. The work further reveals the influence of perceived alternative activity value on regret and proposes a two-tier intervention framework that combines general contextual features—exhibiting cross-user generalizability—with personalized physiological signals, which enhance individualized prediction accuracy.

Abstract

Users often feel regret after using social media, making regret a more ecologically valid target than screen time for understanding when phone use becomes problematic. Existing self-monitoring tools cannot anticipate regret before it occurs, and prior physiological work on social media use has been confined to the lab with research-grade sensors and curated content, leaving the question of in-the-wild prediction open. We deployed a 7-day in-the-wild experience sampling study with 21 participants, combining passive smartphone logging, a low-cost consumer smartwatch (Bangle.js 2, \$80), session-level surveys (1,445 sessions), and exit interviews to investigate when and why social media sessions become regretful, and whether regret can be anticipated before a session begins. Three findings stand out: (i) the gap between intended and actual use predicts regret far more strongly than session duration, with duration's apparent effect collapsing once intention is modeled; (ii) regret is amplified when sessions displace a valued alternative, particularly at night and following productivity-app use; and (iii) pre-session contextual features generalize across participants while physiological signals add person-specific lift, pointing toward a two-layer architecture for just-in-time adaptive interventions. Interview themes of scrolling-as-avoidance and time blindness contextualize these patterns and surface design opportunities beyond timer-based interventions.

Problem

• social media regret
• in-the-wild prediction
• problematic phone use
• just-in-time intervention
• behavioral sensing

Innovation

• regret prediction
• in-the-wild sensing
• just-in-time adaptive intervention
• social media overuse
• wearable physiology