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September 2, 2025
Background:
Children with ADHD often experience deficits in cognitive processes called executive functions. One of the main executive functions is working memory, which is crucial for learning and problem-solving. Issues related to working memory can impact not just academic performance, but also self-esteem, social interactions, and future career prospects. Daily challenges can include completing homework, remembering tasks, and maintaining focus in class, further complicating the learning and social experiences of those with ADHD.
Physical activity boosts blood flow to the brain. It also assists neural plasticity, meaning it enables networks of nerve cells to reorganize their connections and grow new connections. That helps improve physical skills and potentially academic performance. It is an engaging, easy-to-implement intervention that effectively and sustainably increases children’s participation, overcoming many limitations of other methods.
Study:
A Chinese study team set out to perform a systematic search of the published peer-reviewed medical literature to conduct a meta-analysis focusing specifically on the efficacy of physical activity for boosting working memory.
The inclusion criteria were fourfold. Studies had to:
Eleven studies with a combined total of 588 participants met the inclusion criteria. Five were rated high quality. None were rated low quality.
Results:
Meta-analysis of these eleven studies yielded a medium effect size improvement in working memory. Variability in study outcomes was acceptable (low heterogeneity). There was no indication of publication bias.
Combined cognitive and aerobic interventions were associated with more than double the effect size of simple aerobic interventions, reaching large effect size (4 studies, 233 participants).
Subgroup analysis favored a happy medium, suggesting there are points beyond which more is not better:
Take-Away:
Because this work focuses on working memory, not the symptoms of ADHD, one cannot conclude that physical activity could replace current therapies for ADHD. It does, however, provide strong evidence that physical activity interventions can meaningfully improve working memory in children with ADHD. The most consistent benefits were seen with structured programs of moderate duration and frequency. As with previous studies, the results seem to suggest that interventions excessively long in duration may have diminishing results, highlighting the importance of optimizing session length, frequency, and total intervention time. Before recommending very specific exercises and durations, however, further study is still needed. Future research should refine protocols and explore mechanisms that maximize effectiveness.
Gong Cheng, Ce Song, and XiaoQin Hong, “The impact of physical activity on working memory in children with ADHD: a meta-analysis,” Frontiers in Psychiatry (2025), 16:1578614, https://doi.org/10.3389/fpsyt.2025.1578614.
A team of Spanish researchers has published a systematic review of 16 studies with a total of 728 participants exploring the effects of physical exercise on children and adolescents with ADHD. Fourteen studies were judged to be of high quality, and two of medium quality.
Seven studies looked at the acute effects of exercise on eight to twelve-year-old youths with ADHD. Acute means that the effects were measured immediately after periods of exercise lasting up to 30 minutes. Five studies used treadmills and two used stationary bicycles, for periods of five to 30 minutes. Three studies "showed a significant increase in the speed of reaction and precision of response after an intervention of 20-30 min, but at moderate intensity (50-75%)." Another study, however, found no improvement in mathematical problem-solving after 25 minutes using a stationary bicycle at low (40-50%) or moderate intensity (65-75%). The three others found improvements in executive functioning, planning, and organization in children after 20- to 30-minute exercise sessions.
Nine studies examined longer-term effects, following regular exercise over many weeks. One reported that twenty consecutive weekly yoga sessions improved attention. Another found that moderate to vigorous physical activity (MVPA) led to improved behavior beginning in the third week, and improved motor, emotional and attentional control, by the end of five weeks. A third study reported that eight weeks of starting the school day with 30 minutes of physical activity led to improvement in Connor's ADHD scores, oppositional scores, and response inhibition. Another study found that twelve weeks of aerobic activity led to declines in bad mood and inattention. Yet another reported that thrice-weekly 45-minute sessions of MVPA over ten weeks improved not only muscle strength and motor skills, but also attention, response inhibition, and information processing.
Two seventy-minute table tennis per week over twelve weeks improved executive functioning and planning, in addition to locomotor and object control skills.
Two studies found a significant increase in brain activity. One involved two hour-long sessions of rowing per week for eight weeks, the other three 90-minute land-based sessions per week for six weeks. Both studies measured higher activation of the right frontal and right temporal lobes in children, and lower theta/alpha ratios in male adolescents.
All 16 studies found positive effects on cognition. Five of the nine longer-term studies found positive effects on behavior. No study found any negative effects. The authors of the review concluded that physical activity "improves executive functions, increases attention, contributes to greater planning capacity and processing speed and working memory, improves the behavior of students with ADHD in the learning context, and consequently improves academic performance." Although the data are limited by a lack of appropriate controls, they suggest that, in addition to the well-known positive effects of physical activity, one may expect to see improvements in ADHD symptoms and associated features, especially for periods of sustained exercise.
Two recent meta-analyses, one by an Asian team, and the other by a European team, have reported encouraging results on the efficacy of physical exercise in treating ADHD among children and adolescents.
One, a Hong Kong-based team (Liang et al. 2021) looked at the effect of exercise on executive functioning.
The team identified fifteen studies with a combined total, of 493 participants that met the criteria for inclusion. As the authors noted, "only a few studies successfully blinded participants and therapists, due to the challenges associated with executing double-blind procedures in non-pharmacological studies."
After adjusting for publication bias, the meta-analysis of the fifteen studies found a large improvement in overall executive functioning.
The studies varied in which aspects of executive functioning were addressed. A meta-analysis of a subset of eleven studies encompassing 406 participants found a large improvement in inhibitory control. A meta-analysis of another subset, of eight studies with a total of 311 participants, found a large improvement in cognitive flexibility. Finally, a meta-analysis of a subset of five studies encompassing 198 participants found a small-to-medium improvement in working memory.
Nine studies involved acute (singular) exercise interventions lasting 5 to 30 minutes, while twelve studies involved chronic (regular) exercise interventions ranging from 6 to 12 weeks, with a total duration of 12 to 75 hours. The chronic exercise was more than twice as effective as acute exercise. The former resulted in large improvements in overall executive functioning, the latter in small-to-medium improvements.
No significant differences were found between aerobic exercises (such as running and swimming) and cognitively engaging exercises(such as table tennis and other ball games, and exergaming ... video games that are also a form of exercise, relying on technology that tracks body movements).
The authors concluded that "Chronic sessions of exercise interventions with moderate intensity should be incorporated as a treatment for children with ADHD to promote executive functions."
Meanwhile, a German study team (Seiffer et al. 2021) looked at the effects of regular, moderate-to-vigorous physical activity on ADHD symptoms in children and adolescents.
They found eleven studies meeting their criteria, with a combined total of 448 participants. A meta-analysis of all eleven studies found a small-to-moderate decline in ADHD symptoms. However, the three studies with blinded outcome assessors found a large and statistically highly significant decline in symptoms, whereas the eight studies with blinded outcome evaluators found only a small decline that was not statistically significant.
When compared with active controls using pharmacotherapy in a subgroup of two studies with 146 participants, pharmacotherapy held a small-to-moderate advantage that fell just short of statistical significance, most likely because of the relatively small sample size.
The authors concluded that moderate to vigorous physical activity (MVPA) "could serve as an alternative treatment for ADHD," but that additional randomized controlled trials "are necessary to increase the understanding of the effect regarding frequency, intensity, type of MVPA interventions, and differential effects on age groups."
Noting that "Growing evidence shows that moderate physical activity (PA) can improve psychological health through enhancement of neurotransmitter systems," and "PA may play a physiological role similar to stimulant medications by increasing dopamine and norepinephrine neurotransmitters, thereby alleviating the symptoms of ADHD," a Chinese team of researchers performed a comprehensive search of the peer-reviewed journal literature for studies exploring the effects of physical activity on ADHD symptoms.
They found nine before-after studies with a total of 232 participants, and fourteen two-group control studies with a total of 303 participants, that met the criteria for meta-analysis.
The meta-analysis of before-after studies found moderate reductions in inattention and moderate-to-strong reductions in hyperactivity/impulsivity. It also reported moderate reductions in emotional problems and small-to-moderate reductions in behavioral problems.
The effect was even stronger among unmediated participants. There was a very strong reduction in inattention and a strong reduction in hyperactivity/impulsivity.
The meta-analysis of two-group control studies found strong reductions in inattention, but no effect on hyperactivity/impulsivity. It also found no significant effect on emotional and behavioral problems.
There was no sign of publication bias in any of the meta-analyses.
The authors concluded, "Our results suggest that PA intervention could improve ADHD-related symptoms, especially inattention symptoms. However, due to a lot of confounders, such as age, gender, ADHD subtypes, the lack of rigorous double-blinded randomized-control studies, and the inconsistency of the PA program, our results still need to be interpreted with caution."
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Disordered eating (a broad category of persistent, harmful patterns in eating or weight control) affects between 5% and 22% of children and adolescents worldwide, with similar rates seen in the United States. The consequences are far-reaching: these conditions are linked to bone fractures, anemia, malnutrition, dental erosion, obesity, diabetes, hypertension, and elevated cholesterol and triglycerides. They also carry one of the highest mortality rates of any psychiatric illness.
Eating disorders rarely occur in isolation. They frequently arise alongside other psychiatric and neurological conditions. Yet, until now, no large-scale study had examined these co-occurrences in a nationally representative U.S. sample. A new study addresses that gap, focusing on children and adolescents aged 6–17 and the conditions most commonly associated with disordered eating, including ADHD.
The Study:
Researchers drew on data from the 2022–2023 National Survey of Children's Health (NSCH), a nationally representative, cross-sectional survey covering all 50 states and Washington, D.C. Households were selected using stratified, address-based sampling, and parents or guardians completed surveys about one randomly selected child per household. The final sample included 68,000 children and adolescents.
Results:
After accounting for factors including sex, age, race and ethnicity, household income, educational attainment, insurance status, and household language, children and adolescents with ADHD were 2.6 times more likely to have some form of disordered eating compared to their typically developing peers.
The elevated risk appeared across a range of specific behaviors:
A greater tendency toward using diet pills, laxatives, or diuretics was also observed in the ADHD group, though this finding did not reach statistical significance.
The Take-Away:
These findings underscore a need to improve both prevention and treatment strategies for disordered eating, particularly in children and adolescents who have ADHD. Clinicians working with this population are advised to screen for a wide spectrum of disordered eating behaviors.
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.
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