Although sleep problems are common in children with ADHD, their extent, preceding risk factors, and the association between neurocognitive performance and neurobiological processes in sleep and ADHD, are still largely unknown. We examined sleep variables in school-aged children with ADHD, addressing their intra-individual variability (IIV) and considering potential precursor symptoms as well as the chronotype. Additionally, in a subgroup of our sample, we investigated associations with neurobehavioral functioning (n = 44). A total of 57 children (6–12 years) with (n = 24) and without ADHD (n = 33) were recruited in one center of the large ESCAlife study to wear actigraphs for two weeks. Actigraphy-derived dependent variables, including IIV, were analyzed using linear mixed models in order to find differences between the groups. A stepwise regression model was used to investigate neuropsychological function. Overall, children with ADHD showed longer sleep onset latency (SOL), higher IIV in SOL, more movements during sleep, lower sleep efficiency, and a slightly larger sleep deficit on school days compared with free days. No group differences were observed for chronotype or sleep onset time. Sleep problems in infancy predicted later SOL and the total number of movements during sleep in children with and without ADHD. No additional effect of sleep problems, beyond ADHD symptom severity, on neuropsychological functioning was found. This study highlights the importance of screening children with ADHD for current and early childhood sleep disturbances in order to prevent long-term sleep problems and offer individualized treatments. Future studies with larger sample sizes should examine possible biological markers to improve our understanding of the underlying mechanisms.

Sleep problems and alterations in circadian rhythmicity have been widely reported in attention-deficit/hyperactivity disorder (ADHD) patients, but studies covering the full 24h-motor-activity patterns to explore whole-day activity cycles are scarce. Furthermore, correlates and predictors of (hyper-)activity patterns are largely unknown. A subsample of 74 children (6–12 years) with ADHD ( n = 35) participating in the multicenter study ESCAlife and n = 39 controls recruited in one center were assessed using 24h-actigraphy for two weeks. Functional linear modeling (FLM) was applied to the actigraphy data and further post-hoc correlational analyses were conducted. FLM revealed no significant differences in 24h-actigraphy profiles between children with and without ADHD, but differentiated between ADHD presentations (combined vs. inattentive) around sleep onset time (around 8:00p.m.) on free days. In the ADHD group, the 24h-actigraphy profiles were associated with measures of the chronotype and early regulation problems in toddler age; in the control group, with daylight exposure. Finding 24h-activity profile differences between ADHD presentations, but not between ADHD and control children as in classical analyses of sleep-onset latency suggests that comprehensive 24h-FLM analyses and focused sleep-related analyses of actigraphy data capture complementary aspects altered in ADHD and its presentations. Another limitation is that the majority of children with ADHD were medicated. However, actigraphy may still prove valuable as a supplementary diagnostic tool in clinical ADHD assessment.