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March 18, 2026
The first few weeks of life are the time when babies are most vulnerable to seizures (known as neonatal seizures). This is partly because of events that can occur during birth, and partly because the newborn brain is naturally in a more excitable state than a mature brain, making it more prone to seizure activity.
Seizures affect roughly 1 to 3 in every 1,000 full-term babies born, and the rate is considerably higher in premature babies, at around 11 to 14 per 1,000. In most cases, seizures at this age are triggered by a specific event or injury affecting the brain. In full-term newborns, the most common cause is a condition called hypoxic-ischemic encephalopathy (HIE), which occurs when the brain is deprived of adequate oxygen and blood flow around the time of birth. Other causes include genetic or metabolic conditions, stroke, bleeding in the brain, and structural abnormalities in how the brain developed. In very premature babies, bleeding into the fluid-filled spaces of the brain (known as intraventricular hemorrhage) is the leading culprit.
Diagnosing seizures in newborns is tricky because many normal or abnormal movements and behaviors in this age group can look like seizures without actually being them. For this reason, monitoring the baby’s brain activity using an electroencephalogram (EEG) – a test that records electrical signals in the brain – is essential to confirm whether a seizure is truly occurring.
Sweden’s single-payer health system provides universal coverage, with national registers linking healthcare and population data. Researchers tracked infants with EEG/aEEG-confirmed seizures born between 2009 and 2020 and compared them to controls without neonatal seizures.
Altogether, 1062 infants with neonatal seizures were matched with 5310 controls.
The team adjusted for birth, mode of delivery, sex, birth weight, and Apgar scores – quick, standardized assessments used to evaluate newborns’ health minutes after birth.
With these adjustments, infants who had neonatal seizures were twice as likely to subsequently be diagnosed with ADHD and three times as likely to be subsequently diagnosed with autism spectrum disorder.
The authors emphasized that because the study was observational, it cannot demonstrate a direct cause-and-effect relationship between neonatal seizures and outcomes. Factors like seizure frequency, genetics, and socioeconomic status are thought to significantly impact the prognosis of affected children, but these could not be included in this study due to data limitations.
Hanna Westergren, Helena Marell Hesla, Maria Altman, and Ronny Wickström, “Neurological outcomes beyond epilepsy following electroencephalographically verified neonatal seizures: A Swedish nationwide cohort study,” Neuroepidemiology (2026), published online, https://doi.org/10.1159/000551055.
A working group of the International League Against Epilepsy(ILAE), consisting of twenty experts spanning the globe (U.S., U.K., France, Germany, Japan, India, South Africa, Kenya, Brazil), recently published "consensus paper" summarizing and evaluating what is currently known about comorbid epilepsy with ADHD, and best practices.
ADHD is two to five times more prevalent among children with epilepsy. The authors suggest that ADHD is underdiagnosed in children with epilepsy because its symptoms are often attributed either to epilepsy itself or to the effects of antiepileptic drugs (AEDs).
The working group did a systematic search of the English-language research literature. It then reached a consensus on practice recommendations, graded on the strength of the evidence.
Three recommendations were graded A, indicating they are well-established by evidence:
· Children with epilepsy with comorbid intellectual and developmental disabilities are at increased risk of ADHD.
· There is no increased risk of ADHD in boys with epilepsy compared to girls with epilepsy.
· The anticonvulsant valproate can exacerbate attentional issues in children with childhood absence epilepsy (absence seizures look like staring spells during which the child is not aware or responsive). Moreover, a single high-quality population-based study indicates that valproate use during pregnancy is associated with inattentiveness and hyperactivity in offspring.
Four more were graded B, meaning they are probably useful/predictive:
· Poor seizure control is associated with an increased risk of ADHD.
· Data support the ability of the Strengths and difficulties questionnaire (SDQ) to predict ADHD diagnosis in children with epilepsy: "Borderline or abnormal SDQ total scores are highly correlated with the presence of a validated psychiatric diagnosis (93.6%), of which ADHD is the most common (31.7%)." The SDQ can therefore be useful as a screening tool.
· Evidence supports the efficacy of methylphenidate in children with epilepsy and comorbid ADHD.
· Methylphenidate is tolerated in children with epilepsy.
At the C level of being possibly useful, there is limited evidence that supports that atomoxetine is tolerated in children with ADHD and epilepsy and that the combined use of drugs for ADHD and epilepsy (polytherapy) is more likely to be associated with behavioral problems than monotherapy. In the latter instance, "Studies are needed to elucidate whether the polytherapy itself has resulted in the behavioral problems, or the combination of polytherapy and the underlying brain problem reflects difficult-to-control epilepsy, which, in turn, has resulted in the prescription of polytherapy."
All other recommendations were graded U (for Unproven), "Data inadequate or conflicting; treatment, test or predictor unproven." These included three where the evidence is ambiguous or insufficient:
· Evidence is conflicted on the impact of early seizure onset on the development of ADHD in children with epilepsy.
· Tolerability for amphetamine in children with epilepsy is not defined.
· Limited evidence exists for the efficacy of atomoxetine and amphetamines in children with epilepsy and ADHD.
There were also nine U-graded recommendations based solely on expert opinion. Most notable among these:
· Screening of children with epilepsy for ADHD beginning at age 6.
· Reevaluation of attention function after any change in antiepileptic drug.
· Screening should not be done within 48 hours following a seizure.
· ADHD should be distinguished from childhood absence epilepsy based on history and an EEG with hyperventilation.
· Multidisciplinary involvement in transition and adult ADHD clinics is essential as many patients experience challenges with housing, employment, relationships, and psychosocial wellbeing.
Although there has been much research documenting that ADHD adults are at risk for other psychiatric and substance use disorders, relatively little is known about whether ADHD puts adults at risk specifically for somatic medical disorders.
Given that people with ADHD tend toward being disorganized and inattentive, and that they tend to favor short-term over long-term rewards, it seems logical that they should be at higher risk for adverse medical outcomes. But what does the data say?
In a systematic review of the literature, Instances and colleagues have provided a thorough overview of this issue. Although they found 126 studies, most were small and were of "modest quality". Thus, their results must be considered to be suggestive, not definitive for most of the somatic conditions they studied.
Also, they excluded articles about traumatic injuries because the association between ADHD and such injuries is well established. Using qualitative review methods, they classified associations as being a) well-established; b) tentative, or c) lacking sufficient data.
Only three conditions met their criteria for being a well-established association: asthma, sleep disorders, and obesity.
They found tentative evidence implicating ADHD as a risk factor for three conditions: migraine headaches, celiac disease, and diseases of the circulatory system.
These data are intriguing, but cannot tell us why ADHD people are at increased risk for somatic conditions. One possibility is that suffering from ADHD symptoms can lead to an unhealthy lifestyle, which leads to increased medical risk. Another possibility is that the biological systems that are dysregulated in ADHD are also dysregulated in some medical disorders. For example, we know that there is some overlap between the genes that increase the risk for ADHD and those that increase the risk for obesity. We also know that the dopamine system has been implicated in both disorders.
Instances and colleagues also point out that some medical conditions might lead to symptoms that mimic ADHD. They give sleep-disordered breathing as an example of a condition that can lead to the symptom of inattention.
But this seems to be the exception, not the rule. Other medical conditions co-occurring with ADHD seem to be true comorbidities, rather than the case of one disorder causing the other. Thus, primary care clinicians should be alert to the fact that many of their patients with obesity, asthma, or sleep disorders might also have ADHD.
By screening such patients for ADHD and treating that disorder, you may improve their medical outcomes indirectly via increased compliance with your treatment regime and an improvement in health behaviors. We don't yet have data to confirm these latter ideas, as the relevant studies have not yet been done.
Roughly five of every thousand women (0.5%) have epilepsy, a neurological disorder characterized by sudden recurrent episodes of sensory disturbance, loss of consciousness, or convulsions, associated with abnormal electrical activity in the brain. Primary treatment consists of anti-seizure medications (ASMs).
Yet, research has shown that ASMs cross the human placenta. In rodents, ASMs have been shown to lead to abnormal neuronal development, and some research has pointed to the risk of adverse birth outcomes and neurodevelopmental disorders in humans. But samples have been too small for reliable conclusions, and in most cases confounding factors are not addressed.
For a more comprehensive evaluation of risk from ASMs, an international team of researchers examined a nationwide cohort using Swedish national registers that track health outcomes for virtually the entire population.
Using the Medical Birth Register, the National Patient Register, and the Multi-Generation Register, they were able to identify 14,614 children born from 1996-to 2011 to mothers with epilepsy.
Through the prescribed Drug Register, they also examined the first-trimester use of anti-seizure medications (ASMs) by these mothers. The three most frequently used ASMs "frequent enough to yield useful data“ were valproic acid, lamotrigine, and carbamazepine.
The researchers identified ADHD in offspring in one of two ways: ICD-10 (international classification of Diseases, 10th Revision) diagnoses, or filled prescriptions of ADHD medication.
Finally, they consulted the Integrated Database for Labor Market Research and the Education Register to explore potential confounding variables. These included maternal and paternal age at birth, the highest education, cohabitation status, and country of origin. They also included maternal and paternal disposable income in the year of birth and a measure of neighborhood deprivation.
Using the medical registers, they considered parental psychiatric and behavioral problems diagnosed before pregnancy, including bipolar disorder, suicide attempt, schizophrenia diagnosis, substance use disorder, and criminal convictions. They adjusted for inpatient diagnosis of seizures in the year before pregnancy to capture and adjust for indication severity.
Other covariates explored included year of birth, birth order, child sex, maternal-reported smoking during pregnancy, and use of other psychotropic medications.
After fully adjusting for all these confounders, children of mothers who were taking valproic acid were more than 70% more likely to develop ADHD than those of mothers not taking an anti-seizure medicine during pregnancy. The sample size was 699, and the 95% confidence interval stretched from 28% to 138% more likely to develop ADHD.
By contrast, children of mothers who were taking lamotrigine were at absolutely no greater risk(Hazard Ratio = 1) of developing ADHD than those of mothers not taking an anti-seizure medicine during pregnancy.
Finally, children of mothers who were taking carbamazepine were 18% more likely to develop ADHD than those of mothers not taking an anti-seizure medicine during pregnancy, but this result was not statistically significant (the 95% confidence interval ranged from 9% less likely to 52% more likely).
The authors concluded, "The present study did not find support for a causal association between maternal use of lamotrigine in pregnancy and ASD [Autism Spectrum Disorder] and ADHD in children. We observed an elevated risk of ASD and ADHD related to maternal use of valproic acid, while associations with carbamazepine were weak and not statistically significant. Although we could not rule out all potential confounding factors, our findings add to a growing body of evidence that suggests that certain ASMs (i.e., lamotrigine) may be safer than others in pregnancy."
Stimulant medications, such as methylphenidate (Ritalin) and amphetamines (Adderall), are among the most widely prescribed drugs in the world. In the United States alone, prescription rates have climbed more than 50% over the past decade, driven largely by growing awareness of ADHD in both children and adults. Yet stimulants also have a long history of non-medical use, and concerns about their psychological risks persist among patients, families, and clinicians alike.
Two major studies now offer the clearest picture yet of what that risk actually looks like, and who it may affect.
The Background:
Before turning to the research, it helps to understand the landscape. A notable share of stimulant users misuse their medication: roughly one in four takes it in ways other than prescribed, and about one in eleven meets criteria for Prescription Stimulant Use Disorder (PSUD). Counterintuitively, most people with PSUD aren’t obtaining drugs illicitly — they’re misusing their own prescriptions.
This distinction between therapeutic and non-therapeutic use turns out to be critical when evaluating psychosis risk.
The Study:
A comprehensive meta-analysis by Jangra and colleagues pooled data across more than a dozen studies to compare psychotic outcomes in people using stimulants therapeutically versus non-therapeutically. The contrast was striking.
Among therapeutic users (more than 220,000 individuals taking stimulants at prescribed doses under medical supervision), psychotic episodes occurred in roughly one in five hundred people. When symptoms did appear, they typically emerged after prolonged treatment or in individuals with pre-existing psychiatric vulnerabilities, and they usually resolved when the medication was stopped.
Among non-therapeutic users (over 8,000 participants across twelve studies, many using methamphetamine or high-dose amphetamines), nearly one in three experienced psychotic symptoms. These episodes tended to be more severe, involving persecutory delusions and hallucinations, with faster onset and a greater likelihood of recurrence or persistence.
The biology underlying this difference is well understood. When stimulants are taken orally at guideline-recommended doses, they produce moderate, gradual changes in neurotransmitter activity central to attention and executive functions. The brain tolerates these changes relatively well. Non-therapeutic use, by contrast, often involves much higher doses that are frequently delivered through non-oral routes such as injection or smoking. This produces a rapid, excessive surge in dopamine activity, which is precisely the neurochemical pattern associated with psychotic symptoms.
The takeaway here is not that therapeutic stimulant use is risk-free, but that risk is strongly modulated by dose, route of administration, and individual psychiatric history. Clinicians are advised to monitor patients with pre-existing mood or psychotic disorders, particularly carefully.
A Nationwide Study Focuses on Methylphenidate Specifically:
Where the meta-analysis cast a wide net, a large-scale population study by Healy and colleagues drilled into a specific and clinically pressing question: does methylphenidate (the most commonly prescribed ADHD medication, also known as Ritalin) increase the risk of developing a psychotic disorder?
To find out, the researchers analyzed Finland's national health insurance database, tracking nearly 700,000 individuals diagnosed with ADHD. Finland's single-payer system made this kind of comprehensive, long-term tracking possible in a way that fragmented healthcare systems rarely allow.
Critically, the team adjusted for a range of confounding factors that have clouded previous research, including sex, parental education, parental history of psychosis, and the number of psychiatric visits and diagnoses prior to the ADHD diagnosis itself (a proxy for illness severity). After these adjustments, they found no significant difference in the risk of schizophrenia or non-affective psychosis between patients treated with methylphenidate and those who remained unmedicated. This held true even among patients with four or more years of continuous methylphenidate use.
The Take-Away:
When considered together, these studies offer meaningful reassurance without encouraging complacency.
For patients and families weighing ADHD treatment, the evidence suggests that methylphenidate used as prescribed does not increase psychosis risk, even over years of use. The rare cases of stimulant-associated psychosis in therapeutic settings are typically linked to high doses, pre-existing vulnerabilities, or both, and tend to resolve with discontinuation.
For clinicians, the findings reinforce the importance of baseline psychiatric assessment before initiating stimulant therapy, ongoing monitoring in patients with mood or psychotic disorder histories, and clear patient education about the risks of dose escalation or non-oral use.
The picture that emerges is one of a meaningful distinction between a medication used carefully within its therapeutic window and a drug misused outside of it. This distinction matters enormously when communicating risk to patients, policymakers, and the public.
ADHD is commonly treated with medication, but these treatments frequently cause side effects such as reduced appetite and disrupted sleep. Psychological and behavioral therapies exist as alternatives, but they tend to be expensive, hard to scale, and generally do little to address the motor difficulties that many children with ADHD experience — things like clumsy movement, poor handwriting, or difficulty with coordination.
Physical exercise has attracted attention as a more accessible option. But research findings have been mixed, partly because studies vary so widely in how exercise is delivered and what outcomes they measure. This meta-analysis, drawing on 21 studies involving 850 children and adolescents aged 5–20 with a clinical ADHD diagnosis, tries to cut through that noise.
Two types of motor skills
The researchers separated motor skills into two broad categories:
The Data:
Gross motor skills (16 studies, 613 participants)
Overall, exercise produced medium-to-large improvements in gross motor skills. The strongest gains were in:
No significant gains were found in balance or flexibility.
Fine motor skills (13 studies, 553 participants):
Exercise also produced medium-to-large improvements in fine motor skills, specifically:
The Results: What Kind of Exercise Works Best?
Two factors stood out consistently across both gross and fine motor skills: session length and frequency.
The type of exercise mattered; structured programs with clear motor-skill components (rather than unstructured physical activity) yielded stronger results.
These results are not without caveats, however. The authors urge caution in interpreting these findings. A few key limitations include:
The Bottom Line
This meta-analysis provides tentative moderate evidence that structured physical exercise can meaningfully support motor skill development in children and adolescents with ADHD — particularly when sessions run longer than 45 minutes and occur at least three times a week. The benefits appear most robust for object control, locomotion, handwriting, and manual dexterity.
That said, the evidence base still has real gaps. The authors call for better-designed, fully randomized controlled trials with consistent methods, standardized ways of measuring exercise intensity, and greater inclusion of children and adolescents who are not on medication — all of which would help clarify when, how, and for whom exercise works best.
Treatment guidelines for childhood ADHD recommend medications as the first-line treatment for most youth with ADHD. Still, concerns about side effects and long-term outcomes have increased interest in non-pharmacological approaches. Researchers at Saudi Arabian Armed Forces hospitals recently conducted a network meta-analysis comparing several interventions, including mindfulness-based therapy, cognitive behavioral therapy, behavioral parent training, neurofeedback, yoga, virtual reality programs, and digital working memory training.
Although the authors aimed to “provide a rigorous methodological approach to combine evidence from multiple treatment comparisons,” the study illustrates several pitfalls that arise when network meta-analysis is applied to a thin and heterogeneous evidence base.
What Network Meta-analysis Can and Cannot Do:
Network meta-analysis extends conventional meta-analysis by combining:
When the evidence network is large and well-connected, this approach can provide useful estimates of comparative effectiveness among many treatments.
This method is not always best, however, as many networks are sparse. This is especially true in areas such as complementary or behavioral therapies. In sparse networks, estimates rely heavily on indirect comparisons, and single studies can exert disproportionate influence over the results.
Conventional meta-analysis focuses on heterogeneity, meaning differences in results across studies within the same comparison.
Network meta-analysis must additionally evaluate consistency, whether the direct and indirect evidence agree.
However, when comparisons are supported by only one or two studies and the network is weakly connected, statistical tests for heterogeneity and consistency have very little power. In practice, this means the analysis often cannot detect problems even if they are present.
Sparse networks also make publication bias difficult to evaluate. This concern is particularly relevant in fields dominated by small trials and emerging therapies.
Why Such Treatment Rankings Are Appealing, but Potentially Problematic:
Many network meta-analyses summarize results using SUCRA, which estimates the probability that each treatment ranks best.
SUCRA, or Surface Under the Cumulative Ranking, is a key statistical metric in network meta-analyses. It is used to rank treatments by efficacy or safety. This is achieved by summarizing the probabilities of a treatment's rank into a single percentage, where a higher SUCRA value indicates a superior treatment. Ultimately, SUCRA helps pinpoint the most effective intervention among the ones compared.
Again, in well-supported networks, SUCRA can provide a useful summary of comparative effectiveness. But in sparse networks, rankings can create an illusion of precision, because treatments supported by a single small study may appear highly ranked simply due to random variation.
What Did this New Network Meta-analysis Study?
The study includes 16 trials with a total of 806 participants. But the structure of the evidence network is far weaker than this headline number suggests.
Based on the underlying studies:
This produces a very thin network, in which several interventions rely entirely on single studies.
Another challenge is that the included trials measure different outcomes. Some evaluate ADHD symptom severity, while others measure parental stress.
When studies use different outcome scales, meta-analysis typically relies on standardized measures such as the standardized mean difference to allow comparisons across studies. However, the analysis reports only mean-average differences, making it difficult to interpret the relative effect sizes.
Study Issues (including Limited Evidence and Risk of Bias):
The intervention supported by the largest number of studies (family mindfulness-based therapy) was one of the two approaches reported as producing statistically significant results. The other was BrainFit, which is supported by only a single previous trial.
Despite this limited evidence base, the study ranks interventions using SUCRA:
Notably, none of the runner-up interventions demonstrated statistically significant efficacy.
The authors acknowledge methodological limitations in the included studies:
“Blinding of participants and personnel (performance bias) exhibited notable concerns, as blinding for active treatment was not applicable in most studies.”
Such limitations are common in behavioral intervention trials, but they further increase uncertainty in already small evidence networks.
Conclusions:
The study ultimately concludes:
“This network meta-analysis supports MBT and BPT as effective non-pharmacological treatments for ADHD.”
However, the evidence underlying these claims is limited. Some analyses rely on very small numbers of studies and participants, and the network structure depends heavily on indirect comparisons.
Network meta-analysis can be a powerful tool when applied to a large, consistent, and well-connected body of evidence. When the evidence base is sparse, however, the resulting rankings and comparisons may appear statistically sophisticated while resting on a fragile evidentiary foundation.
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