Large-scale patterns of self-reported mood and sleep across the day and week on an online cognitive-training platform

Mood follows a well-documented circadian rhythm. Sleep timing and duration are similarly shaped by biological and social factors. However, large-scale, real-world data on how these patterns vary across demographic groups remain limited. Prior studies often rely on laboratory data or social media linguistic analysis, which lack direct self-reports. This study examines hourly, weekly, and demographic trends in mood and sleep duration reports using one of the largest online datasets of directly self-reported behavioral health: 468,092 Lumosity users (aged 20–79) who reported daily mood (−2 to +2 scale) and sleep duration (≤5–9 + hours). We assessed variation by time of day, day of week, and interactions of age, gender, and race/ethnicity using ANOVA and linear regression. Mood was higher among users reporting in the afternoon and evening, and lower from late night through morning. Mood showed a U-shaped pattern with age, consistent throughout the week, and longer sleep duration was linked to better mood reports throughout the day and week. Sleep duration varied by time of report and by day of week, with longer durations in the afternoon/evening and on weekends. Women reported longer sleep overall, Black users reported shorter sleep, and sleep duration declined from young adulthood through midlife before rising slightly among older users. Higher mood was associated with longer sleep, and the weekday-weekend mood difference was larger among users reporting longer sleep. These findings demonstrate the value of large-scale digital data for public health insight, highlighting demographic disparities in sleep and the importance of midlife as a key intervention period. Because the sample is likely skewed toward higher educational attainment and health engagement, disparity estimates may understate true population-level differences. The late-night peak in negative affect aligns with literature on nocturnal suicide risk, though this nonclinical sample cannot directly speak to clinical risk or crisis-service need.