July 24, 2021
We are only beginning to explore how ADHD affects sleep in adults. A team of European researchers recently published the first meta-analysis on the subject, drawing on thirteen studies with 1,439 participants. They examined both subjective evaluations from sleep questionnaires and objective measurements from actigraphy and polysomnography. However, due to differences among the studies, only two to seven could be combined for any single topic, generally with considerably fewer participants (88 to 873).
Several patterns emerged. Looking at results from sleep questionnaires, they found that adults with ADHD were far more likely to report general sleep problems (very large SMD effect size 1.55). Getting more specific, they were also more likely to report frequent night awakenings(medium effect size 0.56), taking longer to get to sleep (medium-to-large effect size 0.67), lower sleep quality (medium-to-large effect size 0.69), lower sleep efficiency (medium effect size 0.55), and feeling sleepy during the daytime(large effect size 0.75).
There was little to no sign of publication bias, though considerable heterogeneity on all but night awakenings and sleep quality.
Actigraphy readings confirmed some subjective reports. On average, adults with ADHD took longer to get to sleep (large effect size 0.80) and had lower sleep efficiency (medium-to-large effect size 0.68). They also spent more time awake (small-to-medium effect size 0.40). There was little to no sign of publication bias and there was little heterogeneity among studies.
None of the polysomnography measurements, however, found any significant differences between adults with and without ADHD. All effect sizes were small (under 0.20), and none came close to being statistically significant.
There were four instances where measurement criteria overlapped those from actigraphy and self-reporting, with varying degrees of agreement and divergence. There was no significant difference in total sleep time, matching findings from both the questionnaires and actigraphy. On percent time spent awake, polysomnography found little to no effect size with no statistical significance, whereas actigraphy found a small-to-medium effect size that did not quite reach significance, and self-reporting came up with a medium effect size that was statistically significant. Sleep onset latency and sleep efficiency, for which questionnaires and actigraphy found medium-to-large effects, the polysomnography measurements found little to none, with no statistical significance.
Polysomnography found no significant differences in stage 1-sleep, stage 2-sleep, slow-wave sleep, and REM sleep. Except for slow-wave sleep, there was no sign of publication bias. Heterogeneity was generally minimal.
One problem with the extant literature is that many studies did not take medication status into account.
The authors concluded, "future studies should be conducted in medicatio- naïve samples of adults with and without ADHD matched for comorbid psychiatric disorders and other relevant demographic variables."
In summary, these findings provide robust evidence that ADHD adults report a variety of sleep problems. In contrast, objective demonstrations of sleep abnormalities have not been consistently demonstrated. More work in medication-naïve samples is needed to confirm these conclusions.
Amparo DiÌaz-RomaÌn, Raziya Mitchell, SamueleCortese, "Sleep in adults with ADHD: Systematic review and meta-analysis of subjective and objective studies," Neuroscience and biobehavioral reviews, vol. 89, p. 61-71(2018).
There has been consistent evidence of an association between ADHD and subjectively reported sleep problems even in patients not medicated for the disorder. There have also been studies using wrist-worn actigraphy (a wrist watch-like device that measures gross motor activity) and sleep lab-based polysomnography that measure objective sleep parameters.
What has been missing are large population-based cohort studies to explore the prevalence rates of different sleep disorders and medical prescriptions in ADHD.
Methods Used:
Sweden has a single-payer health insurance system and a series of national population registers that track virtually its entire population. Using the Swedish Total Population Register, a local research team created a cohort of all 6,470,658 persons born between 1945 and 2008. They linked this to the Swedish National Patient Register, which includes inpatient hospitalizations from 1975 to 2013, and outpatient specialist diagnoses from 2001 to 2013, to identify diagnoses of sleep disorders. They also linked to the Prescribed Drug Register, covering 2005 to 2013, to identify prescriptions for sleep medications.
Summary of Findings:
Overall, persons with ADHD were eight times more likely to be diagnosed with any sleep disorder relative to normally developing peers. Broken down by age, adolescents with ADHD were 16 times more likely to receive such diagnoses, young adults (18-30) twelve times more likely, children and mid-age adults (31-45) eight times more likely, and older adults six times more likely.
Broken down by specific sleep disorder diagnoses, relative to normally developing peers, persons with ADHD were:
As for sleep medication, relative to normally developing peers, persons with ADHD were:
Conclusion:
The team concluded, “Our findings also suggest that greater clinical attention should be directed towards addressing sleep problems in individuals with ADHD. This entails implementing proactive measures through sleep education programmes and providing both pharmacological and non-pharmacological approaches such as cognitive behavioural therapy and parental sleep training.”
Attention is a critical determinant of academic achievement, influencing domains such as language, literacy, and mathematics. To explore whether physical activity can improve attention in children with ADHD, an international team conducted a meta-analysis of peer-reviewed studies. The goal was to evaluate the impact of various physical activity regimens on attention-related outcomes in this population.
The researchers performed a comprehensive search of the medical literature to identify studies examining the effects of physical activity on attention in schoolchildren with ADHD. They included 10 studies with a total of 474 participants in their meta-analysis. The studies evaluated two main types of physical activity:
Additionally, they examined variations based on the frequency, duration, and type of control groups used in the studies. To assess consistency, they also analyzed heterogeneity (variability of outcomes) and checked for potential publication bias.
Key findings from the meta-analysis include:
The authors concluded that mentally engaging exercise is more effective than aerobic exercise in improving attention problems in schoolchildren with ADHD. Furthermore, higher frequency and longer duration of physical activity do not necessarily yield better outcomes.
This research underscores the importance of tailoring physical activity interventions to emphasize cognitive engagement over intensity or duration. By refining strategies, educators and parents can better support children with ADHD in achieving academic success. But take note: given the results from controlled studies, it seems clear that if there is a positive effect of exercise, it is very small so should not replace standard treatments for ADHD.
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Previous studies have examined how stimulant medications affect the brain in controlled settings, but less is known about their impact in real-world conditions, where children may not always take their medication consistently or may combine it with other treatments. A new study leverages data from the Adolescent Brain Cognitive Development (ABCD) study to explore how real-world stimulant use impacts brain connectivity and ADHD symptoms over two years.
Changes in Brain Connectivity Researchers used brain imaging data from the ABCD study to examine the functional connectivity—communication between brain areas—of six regions within the striatum, a brain area involved in motivation and movement control. They focused on how stimulant use influenced connectivity between the striatum and other networks involved in executive functioning and visual-motor control.
The study found that stimulant exposure was linked to reduced connectivity between key striatal areas (such as the caudate and putamen) and large brain networks, including the frontoparietal and visual networks. These changes were more pronounced in children taking stimulants compared to those who were not medicated, as well as compared to typically developing children. Importantly, this reduction in connectivity seemed to regulate certain brain networks that are typically altered in children with ADHD.
Symptom Improvement In addition to brain changes, 14% of children taking stimulants experienced a significant reduction in ADHD symptoms over the two-year period. These children showed the strongest connectivity reductions between the right putamen and the visual network, suggesting that stimulant-induced connectivity changes may contribute to improvements in visual attentional control, which is a common challenge for children with ADHD.
Why This Matters This study is one of the first to examine how stimulant use in real-world conditions affects brain networks in children with ADHD over time. The findings suggest that stimulants may help normalize certain connectivity patterns associated with ADHD, particularly in networks related to attention and control. These insights could help clinicians better understand the potential long-term effects of stimulant treatment and guide personalized approaches to ADHD management.
Conclusion Stimulant medications appear to alter striatal-cortical connectivity in children with ADHD, with some changes linked to symptom improvement. This research highlights the potential for stimulant medications to impact brain networks in ways that support attention and control, highlighting the importance of understanding how real-world medication use influences ADHD treatment outcomes.
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