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Background:
Sleep is more than simple rest. When discussing sleep, we tend to focus on the quantity rather than the quality, how many hours of sleep we get versus the quality or depth of sleep. Duration is an important part of the picture, but understanding the stages of sleep and how certain mental health disorders affect those stages is a crucial part of the discussion.
Sleep is an active mental process where the brain goes through distinct phases of complex electrical rhythms. These phases can be broken down into non-rapid eye movement (NREM) and rapid eye movement (REM). The non-rapid eye movement phase consists of three stages of the four stages of sleep, referred to as N1, N2(light sleep), and N3(deep sleep). N4 is the REM phase, during which time vivid dreaming typically occurs.
Two of the most important measurable brain rhythms occur during non-rapid eye movement (NREM) sleep. These electrical rhythms are referred to as slow waves and sleep spindles. Slow waves reflect deep, restorative sleep, while spindles are brief bursts of brain activity that support memory and learning.
The Study:
A new research review has compiled data on how these sleep oscillations differ across psychiatric conditions. The findings suggest that subtle changes in nightly brain rhythms may hold important clues about a range of disorders, from ADHD to schizophrenia.
The Results:
People with ADHD showed increased slow-spindle activity, meaning those brief bursts of NREM activity were more frequent or stronger than in people without ADHD. Why this happens isn’t fully understood, but it may reflect differences in how the ADHD brain organizes information during sleep. Evidence for slow-wave abnormalities was mixed, suggesting that deep sleep disruption is not a consistent hallmark of ADHD.
Among individuals with autism spectrum disorder (ASD), results were less consistent. However, some studies pointed to lower “spindle chirp” (the subtle shift in spindle frequency over time) and reduced slow-wave amplitude. Lower amplitude suggests that the brain’s deep-sleep signals may be weaker or less synchronized. Researchers are still working to understand how these patterns relate to sensory processing, learning differences, or daytime behavior.
People with depression tended to show reduced slow-wave activity and fewer or weaker sleep spindles, but this pattern appeared most strongly in patients taking antidepressant medications. Since antidepressants can influence sleep architecture, researchers are careful not to overinterpret the changes. Nevertheless, these changes raise interesting questions about how both depression and its treatments shape the sleeping brain.
In post-traumatic stress disorder (PTSD), the trend moved in the opposite direction. Patients showed higher spindle frequency and activity, and these changes were linked to symptom severity which suggests that the brain may be “overactive” during sleep in ways that relate to hyperarousal or intrusive memories. This strengthens the idea that sleep physiology plays a role in how traumatic memories are processed.
The clearest and most reliable findings emerged in psychotic disorders, including schizophrenia. Across multiple studies, individuals showed: Lower spindle density (fewer spindles overall), reduced spindle amplitude and duration, correlations with symptom severity, and cognitive deficits.
Lower slow-wave activity also appeared, especially in the early phases of illness. These results echo earlier research suggesting that sleep spindles, which are generated by thalamocortical circuits, might offer a window into the neural disruptions that underlie psychosis.
The Take-Away:
The review concludes with a key message: While sleep disturbances are clearly present across psychiatric conditions, the field needs larger, better-standardized, and more longitudinal studies. With more consistent methods and longer follow-ups, researchers may be able to determine whether these oscillations can serve as reliable biomarkers or future treatment targets.
For now, the take-home message is that the effects of these mental health disorders on sleep are real and measurable.
Mayeli A, Sanguineti C, Ferrarelli F. Recent Evidence of Non-Rapid Eye Movement Sleep Oscillation Abnormalities in Psychiatric Disorders. Curr Psychiatry Rep. 2025 Dec;27(12):765-781. doi: 10.1007/s11920-024-01544-x. Epub 2024 Oct 14. PMID: 39400693.
Sleep disorders are one of the most commonly self-reported comorbidities of adults with ADHD, affecting 50 to 70 percent of them. A team of British researchers set out to see whether this association could be further confirmed with objective sleep measures, using cognitive function tests and electroencephalography (EEG).
Measured as theta/beta ratio, EEG slowing is a widely used indicator in ADHD research. While it occurs normally in non-ADHD adults at the conclusion of a day, during the day it signals excessive sleepiness, whether from obstructive sleep apnea or from neurodegenerative and neurodevelopmental disorders. Coffee reverses EEG slowing, as do ADHD stimulant medications.
Study participants were either on stable treatment with ADHD medication (stimulant or non-stimulant medication), or on no medication. Participants had to refrain from taking any stimulant medications for at least 48 hours prior to taking the tests. Persons with IQ below 80 or with recurrent depression or undergoing a depressive episode were excluded.
The team administered a cognitive function test, The Sustained Attention to Response Task (SART). Observers rated on-task sleepiness using videos from the cognitive testing sessions. They wired participants for EEG monitoring.
Observer-rated sleepiness was found to be moderately higher in the ADHD group than in controls. Although sleep quality was slightly lower in the sleepy group than in the ADHD group, and symptom severity slightly greater in the ADHD group than the sleepy group, neither difference was statistically significant, indicating extensive overlap.
Omission errors in the SART were strongly correlated with sleepiness level, and the strength of this correlation was independent of ADHD symptom severity. EEG slowing in all regions of the brain was more than 50 percent higher in the ADHD group than in the control group and was highest in the frontal cortex.
Treating the sleepy group as a third group, EEG slowing was highest for the ADHD group, followed closely by the sleepy group, and more distantly by the neurotypical group. The gaps between the ADHD and sleepy groups on the one hand, and the neurotypical group on the other, were both large and statistically significant, whereas the gap between the ADHD and sleepy groups was not. EEG slowing was both a significant predictor of ADHD and of ADHD symptom severity.
The authors concluded, These findings indicate that the cognitive performance deficits routinely attributed to ADHD are largely due to on-task sleepiness and not exclusively due to ADHD symptom severity. We would like to propose a simple working hypothesis that daytime sleepiness plays a major role in cognitive functioning of adults with ADHD. As adults with ADHD are more severely sleep deprived compared to neurotypical control subjects and are more vulnerable to sleep deprivation, in various neurocognitive tasks they should manifest larger sleepiness-related reductions in cognitive performance. One clear testable prediction of the working hypothesis would be that carefully controlling for sleepiness, time of day and/or individual circadian rhythms, would result in substantial reduction in the neurocognitive deficits in replications of classic ADHD studies.
A team of Spanish researchers performed a systematic search of the medical literature and found 28 studies that could be included in a series of meta-analyses of specific measures of sleep impairment. Except for a single meta-analysis with eight studies and 1,713 participants, however, all involved just three to five studies apiece, with anywhere from 121 to just over a thousand participants.
The team examined three sorts of measures:
· Subjective measures, based on self-reporting by ADHD patients.
· Polysomnography is an objective sleep study in which the subject is wired up and studied by technicians in a lab, usually overnight, monitoring multiple body functions, such as brain activity, eye movements, muscle activation, and heart rhythm.
· Actigraphy, a non-invasive objective means of monitoring sleep. The subject wears an actimetry monitor, which is usually worn like a wristwatch on the non-dominant arm. Because it is minimally intrusive, the subject may wear it for a week or more while engaging in normal activities.
In the subjective measures, adults with ADHD generally reported substantially higher sleep impairments than non-ADHD controls. In the largest meta-analysis, covering eight studies and 1,713 participants, adults with ADHD reported moderately longer latency times for falling asleep than controls. In meta-analyses of five studies with between 834 and 1,130 participants, they also reported moderately poorer sleep quality, more frequent night awakenings, being moderately less rested upon awakening in the morning, and moderate-to-strongly greater daytime sleepiness. There was no significant difference in perceived sleep duration.
Polysomnography measures, on the other hand, failed to confirm these subjective impressions. No significant differences were found between adults with ADHD and controls for the initial latency period until onset of sleep, sleep efficiency, waking after the onset of sleep, total sleep time, stage one or stage two sleep, slow-wave sleep, REM (rapid eye movement) sleep, and latency period until REM sleep.
As mentioned above, polysomnography is conducted in lab settings, and therefore inevitably diverges from normal patterns of behavior. Actigraphy helps bridge that gap, by monitoring normal behavior, though with more limited types and precision of data analysis.
And indeed, a meta-analysis of four studies with 222 participants confirmed self-reports that sleep efficiency was moderate to strongly lower in adults with ADHD and that the latency period until the onset of sleep was markedly longer. On the other hand, it found no significant difference in true sleep.
The researchers also looked at prevalence statistics. Whereas the prevalence of sleep-onset insomnia in the general population has been reported in the range of 13 to 15 percent, a meta-analysis of four studies with 466 participants found fully two-thirds of adults with ADHD reporting insomnia, a greater than four-to-one ratio. Similarly, a meta-analysis of three studies with 458 participants found one-third reporting daytime sleepiness, which is twice the rate reported in the general population.
There was no sign of publication bias in any of these results. The authors cautioned, however, about the small number of studies involved, stating this "compromises the generalizability of the findings." Also, some studies included patients undergoing pharmacological treatment for ADHD, "increasing the risk of confounding results."
Moreover, "Sleep onset latency and sleep efficiency were not significantly impaired in the polysomnography, which was incongruent with the actigraphy results. This may be due to a difference in the evaluation context. Whereas polysomnography is considered the gold-standard measure to objectively assess sleep architecture, actigraphy shows a more ecological approach, with the evaluation being conducted in a more naturalistic context for a longer period. However, actigraphy has more environmental influence, which can compromise the data recorded and the interpretation of the results, whereas, in polysomnography, multiple variables can be controlled in the laboratory setting to increase the internal validity of the results. On the contrary, polysomnography studies can produce artifacts due to the unusual circumstances in the setting, so results may need to be interpreted with caution."
The authors concluded, "The results found in the present study show the relevance of addressing sleep concerns in adult populations diagnosed with neurodevelopmental conditions."
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.
The Background:
Motor vehicle crashes remain one of the most significant public health challenges in the United States. In 2022 alone, nearly 44,000 people died on American roads, and more than 2.6 million crash-related injuries required emergency care. Most people are familiar with the usual suspects: drunk driving, speeding, and distracted driving from phones. These risks are well-documented and the focus of ongoing public safety campaigns.
But a serious risk factor has been flying under the radar: untreated ADHD. Despite receiving little attention from the public, policymakers, or transportation safety agencies, it may belong in the same conversation as these better-known dangers.
ADHD is not currently recognized by the National Highway Traffic Safety Administration as a driving risk factor; yet inattention and impulsivity, two of its defining features, are consistently cited as common contributors to crashes. Beyond these core symptoms, adults with ADHD may also experience emotional dysregulation, which can further impair driving behavior.
The Research:
Prior studies on ADHD and crash risk have produced estimates ranging from a 5% to a 70% increase. This massive heterogeneity has made it difficult to draw firm conclusions. This new meta-analysis set out to offer some clarity on these numbers.
Researchers focused specifically on adults aged 18 to 65 with a formal ADHD diagnosis who were not receiving treatment, comparing them to controls without ADHD. Four studies met these criteria, collectively covering more than 2.75 million people.
The Results:
The findings were striking: untreated ADHD was associated with a 93% increase in crash risk (95% confidence interval: 88%–99%). There was no evidence of publication bias. Although there was meaningful variation across studies, most of it stemmed from the smallest study (just 36 participants) which reported an outlier estimate of a 16-fold increase.
To put the 93% figure in context: a separate meta-analysis found that alcohol use is associated with a 150% increase in crash risk. Another way to understand just how significant this risk really is, untreated ADHD raises crash risk by more than half as much as alcohol does.
The analysis also found a dose-response relationship between ADHD symptom severity and crash risk: each incremental increase in symptom severity corresponded to a 5–6% higher crash risk. At the highest severity levels, crash risk approached that associated with alcohol use. This gradient reinforces that we're not looking at a binary distinction between “has ADHD” and “doesn’t” — the worse the symptoms, the greater the danger on the road.
The Takeaway:
These findings have practical implications for patients, families, clinicians, and policymakers alike. Untreated ADHD is not a minor footnote in the driving safety literature; rather, it is a substantial, measurable, and potentially modifiable risk factor. The question of whether and how it should be factored into licensing policy, clinical practice, and public health messaging deserves serious attention.
As populations grow, more children are growing up surrounded by traffic noise and polluted air. In most cities, these two factors tend to go hand-in-hand; yet, most previous research has examined these exposures separately. Many reviews focused on a single pollutant (such as fine particulate matter, PM2.5), or on a single developmental window, such as pregnancy or early childhood. Few have asked how noise and air pollution compare as risk factors, or how prenatal and postnatal exposures differ in their effects.
A new meta-analysis set out to address those gaps. It examined evidence on both environmental noise and several major air pollutants in relation to ADHD, compared exposures before versus after birth, and pooled data across countries and regions. Eligible studies involved children and adolescents under 18, used objective measures of environmental exposure, and assessed ADHD using either clinical diagnosis or standardized rating scales.
Noise
Nine studies, combining data from over 100,000 children and adolescents (all in European countries and Canada) found that high noise exposure was associated with 3% greater odds of ADHD. Prenatal noise exposure showed no effect; childhood exposure alone drove the association, at 4% greater odds. This is a negligible effect size that could easily reflect unmeasured confounding factors rather than a true causal relationship.
Nitrogen dioxide
Thirteen studies covering nearly one million children and adolescents in Europe, Canada, China, and South Korea found that nitrogen dioxide (NO₂) exposure was associated with 11% greater odds of ADHD. As with noise, prenatal exposure showed no independent effect. When the analysis was restricted to the five studies that used clinical diagnoses alone — generally considered the most reliable measure — the estimated odds rose to between 20% and 80% higher. The wide range reflects substantial variation across studies.
Pollutants with no significant effect
Four studies (97,500 participants) examining nitric oxide (NO), three studies (over 63,000 participants) on ozone, and three studies (over 28,000 participants) on sulfur dioxide found no significant associations with ADHD.
Particulate matter
The strongest associations emerged for particulate matter. Twelve studies involving nearly 160,000 participants in China, the US, Canada, and Europe found that exposure to fine particles (PM2.5, 2.5 microns in diameter) was associated with 30% greater odds of ADHD. Ten studies covering more than a quarter of a million participants in India, China, South Korea, and Europe found that coarser particles (PM10, 10 microns) were associated with 50% greater odds. In both cases, prenatal exposure showed no association, which is consistent with the fact that fetuses do not breathe air through developed lungs. When restricted to clinically diagnosed ADHD, PM2.5 was associated with roughly 50% greater odds, and PM10 with more than double the odds.
The Results
Across all exposures examined, particulate matter showed the clearest and strongest associations with ADHD, followed by nitrogen dioxide. Noise reached statistical significance but at a trivially small effect size. Nitric oxide, ozone, and sulfur dioxide showed no significant associations.
The authors found no evidence of publication bias which strengthens confidence in the overall pattern. However, there was marked heterogeneity across individual studies: results varied considerably, which urges caution in treating any single estimate as definitive. These are associations, not proven causal relationships, and the possibility that unmeasured factors explain part of the signal cannot be ruled out.
The Background:
Over the past two decades, diagnostic rates for adult ADHD have roughly doubled, and stimulant prescriptions in the United States skyrocketed by more than 50% between 2012 and 2023, particularly among girls and women. While these medications help many individuals manage their symptoms, a landmark 2026 article published in European Neuropsychopharmacology tackles an important question that is rarely discussed: When should doctors and patients consider stopping them?
The Discussion:
To answer this, the American Society of Clinical Psychopharmacology (ASCP) gathered a task force of 45 international experts spanning 12 countries. Through a rigorous evaluation process, they reached an overwhelming agreement on a framework for "deprescribing", the planned, supervised reduction or cessation of a medication. Here are the core insights from these ground-breaking guidelines and what they mean for adults navigating long-term ADHD treatment.
When the Treatment Isn’t Yielding Benefits
One of the most straightforward reasons to consider stopping a stimulant is if it simply isn’t doing its job. The task force agreed that if a patient does not experience an optimal response, measured by actual symptom reduction, improved daily functioning, and a better quality of life, even after trying a high, optimized dose, it may be time to step back and look at alternative options.
Sometimes, the issue goes back to the initial evaluation. The criteria for diagnosing ADHD have expanded over the years, and brief psychiatric evaluations can occasionally lead to diagnostic inaccuracies. If a thorough reevaluation reveals that the original ADHD diagnosis was incorrect, the expert consensus is clear: stimulant deprescribing is appropriate unless another stimulant-responsive condition is evident. Furthermore, if a patient develops a persistent tolerance to the drug that cannot be resolved by safe dose adjustments, a temporary taper or drug holiday may be recommended.
When the Risks to Health Outweigh the Rewards
Our bodies and health needs naturally shift over time, meaning a medication that worked safely years ago might pose a threat to your health today. The experts concluded that deprescribing should be heavily considered if stimulants exacerbate a concurrent medical or psychiatric illness. For example, although rare, stimulants can unintentionally trigger mania or psychosis in adults with unstable or unrecognized comorbid bipolar disorder.
Physical health developments are equally critical. If an adult develops a newly arising or unstable cardiovascular condition, such as a cardiac arrhythmia, ischemia, or cardiomyopathy, the risk-benefit balance changes dramatically. Additionally, if severe side effects occur that cannot be managed by reducing the dosage, or if dangerous new drug-drug interactions emerge, stopping the medication under medical supervision protects the patient's long-term well-being.
Addressing Misuse and the Complex Role of Cannabis
Because stimulant medications target brain reward and wakefulness circuitry, they can foster a propensity for misuse. Studies indicate that more than 1 in 5 adults prescribed stimulants have misused them, and 1 in 6 have diverted their medication to others. The task force emphasizes that deprescribing is warranted if a patient persistently takes doses higher than prescribed against medical advice, uses the medication purely for unauthorized performance enhancement, or has an untreated, coexisting substance use disorder.
And what about cannabis? This topic sparked the most debate among the experts, falling just short of an official consensus with 71% agreement that regular cannabis use alone shouldn't automatically trigger a stimulant stoppage. Recognizing the complexity, such as how chronic cannabis use can overlap with ADHD executive function deficits, the task force proposed a structured monitoring approach instead of an immediate cutoff. Clinicians are encouraged to track the patient every 1 to 3 months using standardized symptom tools and random urine drug screens to verify whether cannabis use is actively neutralizing the stimulant's therapeutic benefits.
The Path Forward: Safe Tapering and Lifestyle Support
If you and your doctor decide that stopping a stimulant is the right path, it shouldn’t happen overnight. The task force strongly recommends that medications be gradually tapered off at a rate tailored to the individual to minimize potential disruptions and distinguish between transient withdrawal and a true return of ADHD symptoms.
Crucially, stopping a medication doesn't mean stopping treatment. The experts highlight that the success of any deprescribing plan is significantly enhanced when patients focus on optimizing modifiable lifestyle factors. Prioritizing sleep hygiene, staying physically active, and implementing structured behavioral strategies can support executive functioning and help sustain your cognitive gains even as the medication is reduced or eliminated.
The Takeaway:
The decision to continue or stop an ADHD medication is a deeply personal one that requires balancing real-world efficacy, safety, and individual health changes. These new consensus recommendations provide an essential roadmap to help adults navigate their long-term mental health journeys safely and effectively.
Are you or a loved one currently evaluating your long-term relationship with ADHD medication? Consider scheduling a check-in with your healthcare provider to discuss whether your current treatment plan still perfectly matches your health needs today.
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