Daily Fluctuations in Delay Discounting and Smartphone-Based Multimodal Measures Track Nighttime Drinking in Alcohol Use Disorder: A 28-Day Monitoring Study

Background and Aims: Alcohol use disorder (AUD) involves day-to-day fluctuations in cognitive, psychological, and contextual factors that are difficult to fully capture using retrospective or cross-sectional assessment alone. Computational markers, such as discounting rate, ambiguity tolerance, and risk preference, may provide useful indicators of day-level drinking risk, but have rarely been assessed repeatedly in real-world settings or examined together with daily app-based self-reports and passive smartphone-derived measures. This study examined whether these multimodal day-level measures were associated with same-day nighttime drinking, focusing on whether within-person changes in computational markers remained associated with drinking after accounting for concurrent self-reported and contextual measures. Design: A 28-day longitudinal observational study using repeated smartphone-based assessments and passive sensing. Setting: Daily-life smartphone-based monitoring of community-recruited participants in the Republic of Korea. Participants: The final analytic sample included 143 adults meeting DSM-5 criteria for AUD. Measurements: The primary outcome was same-day nighttime drinking, assessed using daily app-based self-reports. Daily predictors covered three domains. App-based self-reports included mood, alcohol craving, meal intake, and sleep-related variables. Computational predictors were derived from delay discounting and choice under risk and ambiguity tasks. Passive smartphone-derived predictors included time spent at home, calls, steps, and foreground app use. Generalized linear mixed-effects models examined associations between nighttime drinking and multimodal predictors decomposed into within-person and between-person components. Findings: A multimodal model integrating computational parameters, daily app-based self-reports, and passive smartphone-derived measures showed the highest explanatory power for same-day nighttime drinking (marginal R² = 0.22). In this final model, higher within-person delay discounting [log(k)], alcohol craving, and positive mood, as well as lower meal intake and percent time at home, were associated with a higher likelihood of nighttime drinking. At the between-person level, only lower average meal intake was associated with a higher likelihood of nighttime drinking. Within-person fluctuations in log(k) were largely uncorrelated with other day-level predictors and showed no clear next-day association. Conclusions: Associations with same-day nighttime drinking were observed primarily at the within-person level, suggesting that day-level changes may be more informative than stable individual differences. Within-person increases in delay discounting remained associated with nighttime drinking after accounting for other modalities, suggesting that multimodal monitoring may help identify periods of elevated drinking risk.