Day-to-Day Circadian Phase Fluctuations Shape Sleep and Behavior in Adolescents with ADHD

Sleep-wake regulation arises from the interaction between homeostatic sleep pressure and circadian timing, yet current assessments evaluate these processes independently and fail to capture their dynamic modulation by environmental pressures. This limitation is particularly relevant in adolescents with attention-deficit/hyperactivity disorder (ADHD), who are at increased risk of circadian delay and sleep disruption. Here, we combined month-long wearable-based physiological monitoring with ecological behavioral assessments in adolescents with ADHD to characterize circadian and homeostatic processes dynamically in real-world settings. Using continuous skin temperature recordings, we derived individualized and day-specific estimates of circadian phase through hierarchical modelling, and integrated these measures with actigraphy-based sleep estimates and daily assessments of neurocognitive functioning and functional impairment. Temperature-derived circadian phase correlated with questionnaire-based chronotype but more accurately predicted sleep patterns. Delayed circadian phase was associated with later sleep onset and greater weekday-weekend variability. Importantly, circadian phase exhibited significant day-to-day fluctuations, particularly in individuals with delayed phase, reflecting interactions with environmental constraints. Sleep latency was jointly determined by homeostatic sleep pressure and day-specific circadian phase, with combined models outperforming either process alone. Crucially, both sleep deprivation and day-specific circadian misalignment independently predicted fluctuations in ADHD symptom severity, perceived stress, and neurocognitive impulsivity. In contrast, mean circadian phase alone did not explain behavioral variability. These findings demonstrate that circadian regulation is a dynamic, environmentally sensitive process rather than a fixed trait. Wearable-based estimation of circadian phase provides a scalable approach to capture these dynamics and may enable personalized interventions targeting sleep and circadian dysregulation.