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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.
For centuries, we’ve called the eyes the "windows to the soul," but for modern neurologists, they are quite literally a window into the brain. The retina and the central nervous system share the same embryonic origins, developing from the same neural tissue in the womb. Because of this deep biological connection, the back of your eye acts as a non-invasive map of your brain's health, displaying a complex web of nerves and blood vessels that can (theoretically!) mirror certain neurodevelopmental conditions.
Recently, a buzz rippled through the mental health community when a study published in partnership with Seoul National University Bundang Hospital claimed a massive breakthrough. Researchers developed an Artificial Intelligence (AI) model that could screen children for Attention-Deficit/Hyperactivity Disorder (ADHD) using nothing more than a simple retinal photograph. The study, which prospectively recruited children from Severance Hospital and Eunpyeong St. Mary’s Hospital, produced results that were staggering: the AI reportedly achieved an accuracy rate of 96.9%!
In the world of medical testing, scientists use a metric called AUROC (Area Under the Receiver Operating Characteristic) to measure how well a test works.
An AUROC of 96.9% is a near-perfect score, suggesting a tool is ready for immediate, real-world deployment. While headlines promised a revolution in mental health screening, a deeper look into this research and the study’s design has exposed that this 96.9% AUROC was more likely evidence of a flawed methodology rather than a biological reality.
To build their screening tool, researchers analyzed over 1,100 retinal images using a digital pipeline called AutoMorph and a machine-learning model known as XGBoost. The AI was trained to hunt for physical signals of the "Dopamine Connection." Dopamine is the primary neurotransmitter involved in ADHD, but it is also essential to the eye. It regulates synaptic formation, retinal blood flow, and vascular endothelial regulation. Because dopamine dysregulation influences how blood vessels grow and remodel, the study hypothesized that an ADHD brain would leave a unique "fingerprint" on the retinal vasculature, resulting in denser, thicker vessel structures.
On paper, the logic was sound: use AI to spot the subtle vascular remodeling caused by dopaminergic shifts. But a closer look at the investigation revealed that the AI wasn't just spotting ADHD; it was over-indexing on technical noise.
The most significant "smoking gun" flagged by critics is a massive temporal mismatch. In other words, there was a severe disparity in the timeframes and conditions under which the retinal images for the two comparison groups were collected. For an AI to learn a biological condition, it must compare groups under identical technical conditions. Instead, this study created a time-traveling dataset:
A scientific study is only as reliable as its control group. The control in any experiment acts as a baseline against which the study group is compared. In this case, the control group should be composed of children without any neurodevelopmental disorders, or of “typically developing” children.
In this study, the control group wasn't composed of healthy children from the community. Instead, they were patients visiting a tertiary ophthalmology clinic. Children visiting a specialist eye hospital are rarely "typical." They are there because they have symptomatic eye issues. This introduced a massive selection bias involving three major confounders:
When training AI, you must never allow the "test questions" to leak into the "study material." The researchers, however, committed a fundamental violation of machine learning hygiene known as Eye-to-Eye Data Leakage. The study split the data by the eye rather than by the participant.
Human eyes are highly correlated; the left eye is a near-mirror of the right. If a child's left eye was used for training and their right eye was used for testing, the AI was effectively "cheating." Instead of learning the general traits of ADHD, the model was potentially memorizing individuals. This error artificially balloons accuracy metrics.
The true test of medical AI is diagnostic specificity, or differential diagnosis. This refers to the ability to tell one condition apart from another. While the model claimed 96.9% accuracy against a flawed control group, its performance collapsed when faced with real-world complexity.
When the researchers asked the AI to differentiate between ADHD and Autism Spectrum Disorder (ASD), the accuracy plummeted to a poor 63% AUROC. In real-world clinical settings, an accuracy of 63% is dangerously close to a 50% coin flip. Since ADHD frequently co-occurs with ASD, anxiety, or intellectual disabilities, an AI that cannot handle these "clinical differentials" is functionally useless in a doctor's office. The failure at this stage proves the model was likely detecting technical quirks of the dataset rather than a unique biological marker for ADHD.
To move from the lab to the clinic, we must establish a foundation built on rigor rather than high-speed data scraping. Moving forward, we must demand these 3 Pillars of Trusted Medical AI :
The dream of a quick eye scan to diagnose ADHD is not dead, but it must be rescued from "fast science" shortcuts and buzzy headlines.
Background:
One of the more persistent concerns among parents of children with ADHD is whether stimulant medications will stunt their child's growth. A large Israeli cohort study now offers some of the most rigorous reassurance to date, and its methodology sets it apart from earlier research.
The question has long been complicated by a more fundamental uncertainty: do growth differences in children with ADHD stem from the condition itself, from stimulant treatment, or from factors present before any medication is ever prescribed? Without a clear answer, clinicians and families have faced a genuine dilemma when weighing the benefits of stimulant therapy against potential long-term physical costs.
Most previous studies compounded this difficulty by comparing group-average heights, which ignores the crucial variable of genetic potential. A child who is short relative to the general population may simply have short parents. Failing to account for this introduces systematic bias and can make medications appear more harmful than they are.
The Study:
The Israeli research team addressed this directly. Using health records from a nationwide provider, they assembled a retrospective cohort of children born between 1995 and 2003, following them through 2023. This amount of time was long enough for all participants to have reached adult stature (defined as 17 or older for females, 19 or older for males). Their sample included 5,671 children with untreated ADHD, 11,846 who received stimulant treatment, and 47,258 non-ADHD controls. Children who took stimulants for only one to two months, or who had chronic medical conditions requiring long-term medication, were excluded to avoid confounding the results.
Crucially, adult height was evaluated not against population norms but against each individual's expected height, calculated from parental heights using the Tanner-Goldstein-Whitehouse method, a standard approach for estimating genetic height potential via mid-parental height.
When the researchers compared adult heights across the three groups using analysis of variance (ANOVA), they did find statistically significant differences. But statistical significance, particularly in studies with tens of thousands of participants, does not automatically translate into clinical significance. The effect sizes were consistently very small, and the absolute differences were under one centimeter, which is a margin considered clinically negligible.
Their conclusion is measured but clear: after accounting for genetic growth potential, neither an ADHD diagnosis nor stimulant treatment was associated with meaningful reductions in adult height. The findings, they argue, support prioritizing behavioral and functional outcomes when making treatment decisions, since the risk of clinically significant height loss appears to be minimal.
The Take-Away:
For families navigating ADHD treatment, the practical implication is significant: concerns about permanent growth suppression, while understandable, should not be the primary driver of whether or how long a child receives stimulant therapy.
A recent meta-analysis examined how well cognitive behavioral therapy (CBT) improves not just symptoms, but everyday functioning and quality of life in adults with ADHD.
The Background:
ADHD in adults affects far more than attention or impulsivity. It often disrupts key areas of life:
These broad impacts highlight a key issue: reducing symptoms does not automatically translate into better day-to-day functioning.
CBT is a structured, skills-based therapy that helps people:
While both medication (especially stimulants) and CBT improve core ADHD symptoms, CBT is particularly aimed at improving real-world functioning.
The Study:
The researchers analyzed studies involving adults diagnosed with ADHD (or showing clinically significant symptoms). They included:
They focused specifically on outcomes beyond symptoms:
The Results:
1. Strongest Effects: Occupational functioning
CBT showed consistently strong improvements in work-related functioning compared to control groups, both immediately after treatment and at follow-up. This was the most robust finding across domains.
2. Moderate Improvement: Global Functional Impairment
CBT led to moderate improvements in overall daily functioning, with some evidence that gains persist over time. In studies tracking individuals over time, improvements were even stronger at follow-up.
3. Modest Gains: Social Relationships
CBT produced small to moderate improvements in social functioning. Benefits were present both after treatment and at follow-up, but were less pronounced than in work-related outcomes.
4. Limited Effects: Academic Functioning
There were moderate short-term gains when CBT was compared to control groups, but these did not persist at follow-up. Within-subject studies showed only small improvements overall.
5. Modest and Inconsistent Effects: Quality of Life
Improvements in quality of life were small when compared to control groups and often did not last. However, studies tracking individuals over time showed moderate improvements, suggesting some benefit that may not always show up clearly in between-group comparisons.
Overall, the findings suggest:
One notable nuance: CBT did not always outperform other active treatments (like medication or other therapies). This suggests that while CBT is effective, its benefits may partly overlap with broader therapeutic or support effects rather than relying on a single, unique mechanism.
The Take-Away:
CBT is a valuable, evidence-based treatment for adults with ADHD, especially for improving work functioning and overall daily life management. However, its impact on relationships, academic outcomes, and quality of life is more limited and less consistent, pointing to the need for more targeted or combined approaches in those areas.
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