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Methylphenidate is known as the gold-standard treatment for ADHD, increasing dopamine concentrations and helping to focus. However, these psychostimulants may be less well-tolerated in adults. Adverse effects include decreased appetite, nausea, racing heartbeat, restlessness, nervousness, and insomnia.
Neurofeedback is a non-pharmaceutical treatment that combines cognitive behavioral therapy techniques like conditioning and positive reinforcement with electroencephalography (EEG) feedback. Electrodes are placed on specific brain areas, guiding patients to regulate their brainwave activity.
Repetitive transcranial magnetic stimulation (rTMS) uses electromagnetism to induce an electric field by passing a magnetic field through the scalp. Transcranial direct current stimulation (tDCS), on the other hand, directly applies an electric current through the scalp. Both repetitive transcranial magnetic stimulation (rTMS) and tDCS primarily target the outermost layers of neurons, as they are non-invasive methods. Nevertheless, both techniques are believed to affect deeper layers through interconnected neuronal networks.
A French research team conducted a systematic search of the peer-reviewed medical literature to perform a meta-analysis to explore the efficacy of these experimental treatment techniques.
Eight studies – four using rTMS and another four using tDCS – met the inclusion criteria. Studies had to be randomized controlled trials (RCTs), and had to involve multiple sessions of treatment. Participants had to be adults previously diagnosed with ADHD.
Outcomes were measured through self-rated scales, neuropsychological tests, and electrophysiological pre-post evaluations.
Separate meta-analyses of the four tDCS RCTs combining 154 participants and of the four rTMS RCTs encompassing 149 participants likewise reported no significant improvements. In all cases variation in outcomes between studies was moderate, and there were no signs of publication bias.
Meta-analysis of all eight studies with a combined total of 421 participants reported no significant improvements over controls. Narrowing down to studies that used sham controls likewise produced no significant improvements. So, despite the title of this study, these neuromechanistic treatments do not appear to be the future of treatment for adult ADHD.
Margaux Courrèges, Marie Hoareau, Carole Levenes, and Hassan Rahioui, “Comparative efficacy of neurofeedback, tDCS, and TMS: The future of therapy for adults with ADHD. A systematic review and meta-analysis,” Journal of Affective Disorders (2025), 388: 119585, https://doi.org/10.1016/j.jad.2025.119585.
ADHD is hypothesized to arise from 1) poor inhibitory control resulting from impaired executive functions which are associated with reduced activation in the dorsolateral prefrontal cortex and increased activation of some subcortical regions; and 2)hyperarousal to environmental stimuli, hampering the ability of the executive functioning system, particularly the medial frontal cortex, orbital and ventromedial prefrontal areas, and subcortical regions such as the caudate nucleus, amygdala, nucleus accumbens, and thalamus, to control the respective stimuli.
These brain anomalies, rendered visible through magnetic resonance imaging, have led researchers to try new means of treatment to directly address the deficits. Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique that uses a weak electrical current to stimulate specific regions of the brain.
Efficacy:
A team of researchers from Europe and ran performed a systematic search of the literature and identified fourteen studies exploring the safety and efficacy of tDCS. Three of these studies examined the effects on ADHD symptoms. They found a large effect size for the inattention subscale and a medium effect size for the hyperactivity/impulsivity. Yet, as the authors cautioned, "a definite conclusion concerning the clinical efficacy of tDCS based on the results of these three studies is not possible."
The remaining studies investigated the effects on specific neuropsychological and cognitive deficits in ADHD:
The fact that heterogeneity in the methodology of these studies made meta-analysis impossible means these results, while promising, cannot be seen as in any way definitive.
Safety:
Ten studies examined childhood ADHD. Three found no adverse effects either during or after tDCS. One study reported a feeling of "shock" in a few patients during tDCS. Several more reported skin tingling and itching during tDCS. Several also reported mild headaches.
The four studies of adults with ADHD reported no major adverse events. One study reported a single incident of acute mood change, sadness, diminished motivation, and tension five hours after stimulation. Another reported mild instances of skin tingling and burning sensations.
To address side effects such as tingling and itching, the authors suggested reducing the intensity of the electrical current and increasing the duration. They also suggested placing electrodes at least 6 cm apart to reduce current shunting through the ski. For children, they recommended the use of smaller electrodes for better focus in smaller brains.
The authors concluded, "The findings of this systematic review suggest at least a partial improvement of symptoms and cognitive deficits in ADHD by tDCS. They further suggest that stimulation parameters such as polarity and site are relevant to the efficacy of tDCS in ADHD. Compared to cathodal stimulation, Anodal tDCS seems to have a superior effect on both the clinical symptoms and cognitive deficits. However, the routine clinical application of this method as an efficient therapeutic intervention cannot yet be recommended based on these studies ..."
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The U.S. government released a sweeping document titled The MAHA Report: Making Our Children Healthy Again, developed by the President’s “Make America Healthy Again” Commission. Chaired by public figures and physicians with ties to the current administration, the report presents a broad diagnosis of what it calls a national health crisis among children. It cites rising rates of obesity, diabetes, allergies, mental illness, neurodevelopmental disorders, and chronic disease as signs of a generation at risk.
The report's overarching goal is to shift U.S. health policy away from reactive, pharmaceutical-based care and toward prevention, resilience, and long-term well-being. It emphasizes reforming the food system, reducing environmental chemical exposure, addressing lifestyle factors like physical inactivity and screen overuse, and rethinking what it calls the “overmedicalization” of American children.
While some of the report’s arguments are steeped in political rhetoric and controversial claims—particularly around vaccines and mental health diagnoses—others are rooted in well-established public health science. This blog aims to highlight where the MAHA Report gets the science right, especially as it relates to childhood health and ADHD.
Although the MAHA Report contains several debatable assertions, it also outlines six key public health priorities that are well-supported by decades of research. If implemented thoughtfully, these recommendations might make a meaningful difference in the health of American children:
Reduce Ultra-Processed Food (UPF) Consumption
UPFs now make up nearly 70% of children’s daily calories. These foods are high in added sugars, refined starches, unhealthy fats, and chemical additives, but low in nutrients. Studies—including a 2019 NIH-controlled feeding study—show that UPFs promote weight gain, overeating, and metabolic dysfunction. What can help: Tax incentives for fresh food retailers, improved school meals, front-of-pack labeling, and food industry regulation.
Promote Physical Activity and Limiting Sedentary Time
Most American children don’t get the recommended 60 minutes of physical activity per day. This contributes to obesity, cardiovascular risk, and even mental health issues. Physical activity is known to improve attention, mood, sleep, and self-regulation. What can help: Mandatory daily PE, school recess policies, walkable community infrastructure, and screen-time education.
Addressing Sleep Deprivation
Teens today sleep less than they did a decade ago, in part due to screen use and early school start times. Sleep loss is linked to depression, suicide risk, poor academic performance, and metabolic problems. What can help: Later school start times, family education about sleep hygiene, and limits on evening screen exposure.
Improving Maternal and Early Childhood Nutrition
The report indirectly supports actions that are backed by strong evidence: encouraging breastfeeding, supporting maternal whole-food diets, and improving infant nutrition. These are known to reduce chronic disease risk later in life.
ADHD is one of the most discussed neurodevelopmental disorders in the MAHA Report, but many of its claims about ADHD are misleading, oversimplified, or inconsistent with decades of scientific evidence, much of which is described in the International Consensus Statement on ADHD, and other references given below.
This is true. Diagnosis rates have risen over the past two decades, due in part to better recognition, broadened diagnostic criteria, and changes in healthcare access. Diagnosis rates in some parts of the country are too high, but we don’t know why. That should be addressed and investigated. MAHA attributes increasing diagnoses to ‘overmedicalization’. That is a hypothesis worth testing but not a conclusion we can draw from available data.
These have been associated with ADHD but have not been documented as causes. ADHD is highly heritable, with genetic factors accounting for 70–80% of the risk. Unlike genetic studies, environmental risk studies are compromised by confounding variables. There are good reasons to address these issues but doing so is unlikely to reduce diagnostic rates of ADHD.
❌ Inaccurate: ADHD medications don’t work long-term.
The report criticizes stimulant use but fails to note that ADHD medications are among the most effective psychiatric treatments, especially when consistently used. They cite the MTA study’s long term outcome study of kids assigned to medication vs. placebo as showing medications don’t work in the long term. But that comparison is flawed because during the follow-up period, many kids on medication stopped taking them and many on placebo started taking medications. Many studies document that medications for ADHD protect against many real-world outcomes such as accidental injuries, substance abuse and even premature death.
Despite the issues discussed above, the MAHA Report can indirectly help children and adults with ADHD by pushing for systemic changes that reduce ultra-processed food consumption, increase physical activity, and motivate better sleep practices.
In other words, you don’t need to reject the diagnosis of ADHD to support broader changes in how we feed, educate, and care for children. A more supportive, less toxic environment benefits everyone—including those with ADHD.
ADHD is associated with impaired executive functioning. Executive functions are a set of mental skills that include working memory, flexible thinking, and self-control. These are skills we use every day to learn, work, and manage daily life. Trouble with executive function can make it hard to focus, follow directions, and handle emotions.
A Chinese study team searched for studies on non-pharmacological treatments of children and adolescents with ADHD aged 5 to 18 years intended to improve their executive functioning.
An initial methodological weakness was the decision to combine studies using formal ADHD diagnoses based on professional psychiatric manuals (DSM 3/4/5 and ICD 10/11) and studies relying on other methods such as parent reports.
This lack of rigor in identifying ADHD is surprising given that the team used studies that directly measured executive functioning through neurocognitive tasks, excluding those that relied on parent- or teacher-reported questionnaires.
67 studies involving 74 training interventions met the criteria. Meta-analysis of all these studies, encompassing a total of 3,101 participants, suggested medium-to-large effect size improvements in executive functioning. There was evidence of publication bias, but trim-and-fill adjustment increased the estimated effect size to large.
Nevertheless, there were further methodological shortcomings:
In this case, subgroup analysis mostly failed to explain the heterogeneity, with a single exception. Meta-analysis of the 16 studies with 744 participants that explored executive function-specific curriculum found small-to-medium effect size improvements, with no heterogeneity.
Unfortunately, the team did not perform a separate publication bias analysis on this subgroup, just as it failed to do so on any of the other subgroups.
By far the strongest evidence of benefit came from meta-analysis of the 17 studies with 558 participants evaluating physical exercise. Here the outcome pointed to very large effect size improvements in executive functioning. Yet once again, heterogeneity was extremely high. Breaking this down further between aerobic exercise and cognitively engaged physical exercise made no difference. Both types had the same very high effect size, with very wide heterogeneity. Again, there was no separate evaluation of publication bias on this group.
Meta-analyses of thirteen studies of neurofeedback combining 444 participants, and fifteen studies of cognitive training encompassing 727 participants, both pointed to just-short-of-large effect size improvements in executive function. Meta-analysis of twelve studies of game-based training with 598 participants indicated medium effect size gains. But again, in all three subgroups there was great variation between studies, and no analysis of publication bias.
While these meta-analyses are suggestive of efficacy, especially for physical exercise interventions, their methodological shortcomings mean we will have to await more rigorous meta-analyses to draw any more settled conclusions. Moreover, these meta-analyses did not evaluate the adequacy of the control groups used in the trials, which is a big shortcoming given prior work showing that the effect of non-pharmacologic treatments are very weak or non-existent when adequate controls are used.
ADHD is one of the most common neurodevelopmental disorders in children, yet anyone familiar with this disorder, from clinicians and researchers to parents and patients, knows how differently it can manifest from one individual to the next. One person diagnosed with ADHD may primarily struggle with focus and staying on-task; another may find it nearly impossible to regulate their impulses or even start tasks; a third may frequently find themselves frozen with overwhelm and subject to emotional reactivity…
These are not just variations in severity; they may reflect genuinely different patterns of brain organization.
Our current diagnostic system groups all of these presentations under a single label (ADHD), with three behavioral subtypes (Hyperactive, Inattentive, and Combined) defined by symptom checklists. This framework has real clinical value of course, but it was built from behavioral observation rather than neurobiology, and may leave room for substantial heterogeneity to remain unexplained. In a new study, published in JAMA Psychiatry, researchers asked whether it’s possible to identify distinct neurobiologically subgroups within ADHD by analyzing patterns of brain structure, and whether those subgroups would map onto meaningful clinical differences.
How the Brain Was Analyzed
Researchers analyzed structural MRI scans from 446 children with ADHD and 708 typically-developing children across multiple research sites. From each scan, they constructed a morphometric similarity network; that is, a map of how different brain regions resemble one another in their structural properties. These networks reflect underlying biological organization, including shared patterns of cellular architecture and gene expression across brain regions.
From each individual's network, the research team calculated three properties that capture how each brain region functions within the broader network: how many connections it has, how efficiently it communicates with other regions, and how well it bridges different functional communities in the brain. Regions that score highly on these measures are sometimes called "hubs" and they play particularly influential roles in how information is integrated across the brain.
Rather than comparing the ADHD group to controls as a whole and looking for average differences, they used a normative modeling approach. This works similarly to a growth chart in pediatric medicine: instead of asking whether a child is above or below the group average, it asks how much a given child deviates from the expected range for their age and sex. This allows for individual variation across the ADHD group rather than flattening it into a single average profile.
The team then applied a data-driven clustering algorithm to these individual deviation profiles, allowing the data to reveal whether subgroups of children with ADHD shared similar patterns of brain network atypicality, without using any clinical symptom information to guide the clustering.
The Results:
Three stable, reproducible subtypes emerged from this analysis.
The first subtype was characterized by the most widespread differences from the normative range, particularly in regions connecting the medial prefrontal cortex to the pallidum (a deep brain structure involved in motivation and emotional regulation). Children in this group had the highest levels of both inattention and hyperactivity/impulsivity, and over a four-year follow-up period showed more persistent difficulties with emotional self-regulation than the other groups. They also had a higher rate of mood disorder comorbidity during follow-up, though this difference did not reach statistical significance given the sample size. The brain deviation patterns of this subtype showed correspondence with the spatial distributions of several neurotransmitter systems, including serotonin, dopamine, and acetylcholine, all of which have been previously implicated in ADHD pathophysiology.
The second subtype showed alterations concentrated in the anterior cingulate cortex and pallidum, a circuit involved in action control and response selection. This subtype had a predominantly hyperactive/impulsive profile, and its brain deviation patterns were associated with glutamate and cannabinoid receptor distributions.
The third subtype showed more focal differences in the superior frontal gyrus, a region involved in sustained attention. This subtype had a predominantly inattentive profile, with brain patterns linked to a specific serotonin receptor subtype.
A particularly important observation was that these brain-derived groupings aligned with clinically meaningful symptom differences, even though no symptom information was used in the clustering process. The fact that an analysis of brain structure alone arrived at groupings that correspond to recognizable clinical patterns is meaningful evidence that these subtypes reflect genuine neurobiological differences rather than statistical noise.
Replication in an Independent Sample
Scientific findings are only as trustworthy as their ability to replicate. The research team tested this clustering model in an entirely independent cohort of 554 children with ADHD from the Healthy Brain Network, a large, publicly available dataset collected under different conditions. The three subtypes were successfully identified in this new sample, with strong correlations between the brain deviation patterns observed in the original and validation cohorts. Differences in hyperactivity/impulsivity across subtypes were consistent with the discovery cohort, providing meaningful external validation of the approach.
What This Does and Doesn't Mean
It is important to be clear about what these findings do and do not imply. This study does not establish that these three subtypes are categorically distinct biological entities with sharp boundaries. They probably represent distinguishable regions along an underlying continuum of neurobiological variation. The neurochemical associations reported are exploratory and spatial in nature; they describe correspondences between brain deviation maps and neurotransmitter receptor density maps derived from separate imaging studies, and do not directly establish that any particular neurotransmitter system is altered in each subtype, nor do they currently inform treatment decisions.
The samples were not entirely medication-naive, and the strict comorbidity exclusion criteria may limit how well these findings generalize to typical clinical populations where comorbidities are the rule rather than the exception. All data came from research sites in the United States and China, and broader generalizability remains to be established.
What the study does demonstrate is that structured neurobiological heterogeneity exists within the ADHD diagnosis, that it can be reliably detected using brain imaging and data-driven methods, and that it aligns with meaningful clinical differences. The subtype defined by the most extensive brain network differences and the most severe, persistent clinical profile may be of particular importance, representing a group that could benefit most from early identification and targeted support.
The longer-term goal of this line of research is to move toward a more biologically grounded understanding of ADHD that complements existing diagnostic approaches and that may ultimately help guide more individualized treatment decisions. That goal, for now, remains a research ambition rather than a clinical reality, but this study takes a meaningful step in that direction.
Managing high blood pressure requires more than just getting a prescription; it means taking medication consistently, day after day, often for years. For people with ADHD, that kind of routine can be genuinely difficult. In our new study, published in BMC Medicine, we set out to understand just how much ADHD affects whether people stick with their blood pressure medication, and whether ADHD treatment itself might make a difference.
Why This Question Matters
Hypertension affects nearly a third of adults worldwide and is one of the leading drivers of heart disease and stroke. At the same time, ADHD, long thought of as a childhood disorder, affects around 2.5% of adults and is increasingly recognized as a risk factor for cardiovascular problems, including high blood pressure. Yet no large-scale study had ever examined whether having ADHD affects how well people follow through with their blood pressure treatment. We wanted to fill that gap.
What We Did
We analyzed health records from over 12 million adults across seven countries, Australia, Denmark, the Netherlands, Norway, Sweden, the UK, and the US, who had started antihypertensive (blood pressure-lowering) medication between 2010 and 2020. About 320,000 of them had ADHD. We tracked two things: whether they stopped their blood pressure medication entirely within five years, and whether they were taking it consistently enough (covering at least 80% of days) over one, two, and five years of follow-up.
What We Found
Across nearly all countries, adults with ADHD were more likely to stop their blood pressure medication and less likely to take it consistently. Overall, those with ADHD had about a 14% higher rate of discontinuing treatment within five years, and were 45% more likely to have poor adherence in the first year, a gap that widened to 64% by the five-year mark. These patterns were most pronounced in middle-aged and older adults.
Interestingly, young adults with ADHD were actually slightly less likely to discontinue treatment than their peers without ADHD, a finding we think may reflect the fact that younger people with ADHD are often more actively engaged with healthcare systems, especially given the cardiovascular monitoring that comes with ADHD medication use.
Perhaps the most encouraging finding was this: among people with ADHD who were also taking ADHD medication, adherence to blood pressure treatment was substantially better. Those on ADHD medication were about 38% less likely to have poor adherence at one year, and nearly 50% less likely at five years. While we can't establish causation from this type of study, one plausible explanation is that treating ADHD, reducing inattention and impulsivity, makes it easier to maintain the routines that consistent medication use requires. It's also possible that people on ADHD medication simply have more regular contact with healthcare providers, which keeps other health problems better monitored and managed.
What This Means in Practice
The core ADHD symptoms of inattention and poor organization are precisely the traits that make long-term medication adherence difficult. Add in the complexity of managing multiple disorders and medications, and it's easy to see why people with ADHD face extra challenges. Our findings suggest that clinicians treating adults with ADHD for cardiovascular disorders should be aware of these challenges and consider tailored support strategies, things like regular follow-up appointments, patient education, and tools that help with routine and organization.
There's also a broader message here about the potential ripple effects of treating ADHD well. Supporting someone in managing their ADHD may not just improve their attention and daily functioning; it may also help them take better care of their physical health, including disorders as serious as hypertension.
Future research should explore which specific support strategies are most effective, and whether these findings hold in lower- and middle-income countries where the data don't yet exist.
If you or someone you know has ADHD, you may be familiar with the challenge of staying on medication. Stimulants like methylphenidate (Ritalin) are the most common and effective treatment for ADHD, but a surprisingly large number of people stop taking them within the first year. In our new study, published in Translational Psychiatry, we sought to determine whether a person's genetic makeup plays a role in the development of the disorder.
What We Did
We analyzed data from over 18,000 people with ADHD in Denmark, all of whom had started stimulant medication. We tracked whether they stopped treatment within the first year, defined as going more than six months without filling a prescription. Nearly 4 in 10 (39%) had discontinued by that point. We then looked at their genetic data to see whether DNA differences could help explain who was more likely to stop.
What We Found
The short answer is: genetics does play a role, but it's modest. No single gene had a dramatic effect. Instead, we found that a collection of small genetic influences—distributed across the genome—contributed to the likelihood of stopping treatment early.
One of the most consistent findings was that people with a higher genetic predisposition for psychiatric disorders like schizophrenia, depression, or general mental health difficulties were more likely to discontinue their medication. This was true across all age groups. Interestingly, having a higher genetic risk for ADHD itself was not associated with stopping treatment, suggesting that the genetics of having ADHD and the genetics of staying on medication are quite different things.
We also found that the genetic picture looks different depending on age. In children under 16, body weight genetics (BMI) played a surprising role, children with a genetic tendency toward higher weight were actually less likely to stop, possibly because stimulant-related appetite suppression is less of a problem for them. In older adolescents and adults, higher genetic potential for educational attainment and IQ was linked to staying on treatment, possibly reflecting better access to information and healthcare support.
On the rare variant side, we found a tentative signal that people who stopped treatment had fewer disruptive variants in genes involved in dopamine, the brain chemical that stimulants work on. This might mean that those who continue on medication genuinely have more disruption in their dopamine system and benefit more from stimulant treatment.
What This Means
Our findings suggest that stopping ADHD medication early isn't simply a matter of willpower or forgetting to take a pill. Biology matters. A person's broader genetic vulnerabilities, particularly for other psychiatric disorders, may make it harder to stay on treatment, perhaps because of side effects, poor response, or the complexity of managing multiple mental health challenges at once.
We're still far from being able to use genetics to predict who will stop their medication, the effects we found are real but small, and much of the variation in treatment persistence remains unexplained. But this work is a step toward understanding the biological foundations of treatment challenges in ADHD, and hopefully toward more personalized approaches to care in the future.
Larger studies and research that can distinguish why people stop (side effects versus poor response versus practical barriers), will be the next steps.
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