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October 21, 2025
Children and adolescents with ADHD tend to be less active and more sedentary than their typically developing peers. This is concerning, since physical activity benefits mental, physical, and social development. For youth with ADHD, being active can improve symptoms like inattention, working memory, and inhibitory control.
A major barrier to physical activity for children and adolescents with ADHD is limited motor competence. This stems from challenges in developing basic motor skills and more complex abilities needed for sports and advanced movements.
Difficulties in developing fundamental movement skills – such as locomotor (running, jumping), object-control (throwing, catching), and stability skills (balancing, turning) – can reduce motor competence and limit physical activity. These basic movements are learned and refined with practice and age, not innate abilities.
To date, research on the link between ADHD and motor competence has remained inconclusive. This systematic review and meta-analysis by a Spanish research team therefore aimed to determine whether children and adolescents with ADHD differ in motor competence from those with typical development (TD).
Studies had to include children and adolescents diagnosed with ADHD. They had to involve a full motor assessment battery, not just one test, and present motor competence data for both ADHD and TD groups.
The team excluded studies involving participants with other neurodevelopmental disorders or cognitive impairments, unless separate data for the ADHD subgroup were reported.
Meta-analysis of six studies combining 323 children and adolescents found that typically developing individuals were twelve times more likely to score in the 5th percentile of the Movement Assessment Battery for Children as their peers diagnosed with ADHD. They were also three times more likely to score in the 15th percentile (five studies, 289 participants). Results were consistent across the studies (low heterogeneity). All included studies were randomized.
Meta-analysis of five studies totaling 198 participants using the Test of Gross Motor Development reported significant deficits in both locomotor skills and object control skills among children and adolescents diagnosed with ADHD relative to their typically developing peers. In this case, however, results were inconsistent across studies (very high heterogeneity), and one of the studies was unrandomized. Because the team published only unstandardized mean differences, there was no indication of effect sizes.
Meta-analysis of two studies encompassing 164 participants using the Bruininks-Oseretsky Test of Motor Proficiency similarly yielded significant deficits among children and adolescents diagnosed with ADHD relative to their typically developing peers, but in this case with low heterogeneity. Notably, one of the two studies was not randomized.
Moreover, the team made no assessment of publication bias.
The team concluded, “The findings of this review indicate that children and adolescents with ADHD show significantly lower levels of motor competence compared to their TD peers. This trend was evident across a range of validated assessment tools, including the MABC, BOT, TGMD, and other standardized test batteries. Future research should aim to reduce methodological heterogeneity and further investigate the influence of factors such as ADHD subtypes and comorbid conditions on motor development trajectories.”
However, without a publication bias assessment, reliance on unrandomized studies in two of the tests, no indication of effect size in the same two tests, and small sample sizes, these results are at best suggestive, and will require further research to confirm.
Nerea Blanco-Martínez, Daniel González-Devesa, Carlos Ayán-Pérez, and José Carlos Diz-Gómez, “Differences in Motor Competence Between Children and Adolescents With and Without ADHD: Findings from a Systematic Review and Meta-analysis,” Journal of Autism and Developmental Disorders (2025), https://doi.org/10.1007/s10803-025-07033-1.
Computerized cognitive training (CCT) uses computers to try to strengthen cognitive skills and processes, reduce ADHD symptoms, and improve executive functioning. Executive functions are cognitive processes and mental skills that help individuals plan, monitor, and successfully execute their goals.
CCT programs target one or more cognitive processes such as motor inhibition, interference inhibition, sustained attention, and working memory. They ramp up task difficulty as performance improves. The goal is to harness the brain’s inherent adaptability (neuroplasticity) to boost performance.
A European study team that previously probed the efficacy of CCT through meta-analysis had been unable to provide a robust estimate of effect size due to an insufficient number of high-quality trials with probably blinded outcomes. Noting that “there have been a considerable number of new RCTs [randomized controlled trials] published, many with larger samples, well-controlled designs and blinded outcomes,” the team performed an updated systematic review and meta-analysis.
They included RCTs with participants of any age who either had a clinical diagnosis of ADHD or were above cut-off on validated ADHD rating scales. RCTs had to have been peer-reviewed and published in an academic journal, and to have reported a validated outcome measure of ADHD symptoms, neuropsychological processes, and/or academic outcomes.
Fourteen RCTs with a combined total of 631 participants had probably blinded outcomes. Meta-analysis of these studies yielded no significant effect on either overall ADHD symptoms or hyperactivity/impulsivity symptoms. There was a marginally significant reduction in inattention symptoms, but the effect size was small. Between-study variation (heterogeneity) was negligible and there was no sign of publication bias.
Regarding academic outcomes, meta-analyses revealed no gain in arithmetic ability or reading fluency. There was a small but not statistically significant improvement in reading comprehension. Heterogeneity was minimal, with no indication of publication bias.
With two related exceptions, meta-analyses of RCTs measuring executive functions likewise reported no significant improvements in attention, interference inhibition (initial stage in controlling impulsive behavior), motor inhibition (follow-up stage in controlling impulsive behavior), non-verbal reasoning, processing speed, and set shifting (the ability to unconsciously shift attention between one task and another).
The exceptions were for working memory tasks. Meta-analysis of 15 RCTs with a combined 753 participants reported a highly significant small-to-medium effect size improvement in verbal working memory. A separate meta-analysis of nine RCTs with a total of 441 participants similarly reported a highly significant improvement in visuospatial working memory, this time with medium effect size.
The team concluded, “There was no empirical support for the use of CCT as a stand-alone intervention for ADHD symptoms based on the largest and most comprehensive meta-analysis of RCTs conducted to date. Small effects, of likely limited clinical importance, on inattention symptoms were found – but these were limited to the setting in which the intervention was delivered. Robust evidence of small- to-moderate improvements in visual-spatial and verbal STM/WM tasks did not transfer to other domains of executive functions or academic outcomes.”
ADHD treatment usually involves a combination of medication and behavioral therapy. However, medication can cause side effects, adherence problems, and resistance from patients or caregivers.
Numerous systematic reviews and meta-analyses have evaluated the effects of non-pharmacological interventions on ADHD. With little research specifically examining game-based interventions for children and adolescents with ADHD or conducting meta-analyses to quantify their treatment effectiveness, a Korean study team performed a systematic search of the peer-reviewed medical literature to do just that.
The Study:
To be included, studies had to be randomized controlled trials (RCTs) that involved children and adolescents diagnosed with ADHD. The team excluded RCTs that included participants with psychiatric conditions other than ADHD.
Eight studies met these standards. Four had a high risk of bias.
Meta-analysis of four RCTs with a combined total of 481 participants reported no significant improvements in either working memory or inhibition from game-based digital interventions relative to controls.
Likewise, meta-analysis of three RCTs encompassing 160 children and adolescents found no significant improvement in shifting tasks relative to controls.
And meta-analysis of two RCTs combining 131 participants reported no significant gains in initiating, planning, organizing, and monitoring abilities, nor in emotional control.
The only positive results were from two RCTs with only 90 total participants that indicated some improvement in visuospatial short-term memory and visuospatial working memory.
There was no indication of effect size, because the team used mean differences instead of standardized mean differences.
Conclusion:
The team concluded, “The meta-analysis revealed that game-based interventions significantly improved cognitive functions: (a) visuospatial short-term memory … and (b) visuospatial working memory … However, effects on behavioral aspects such as inhibition and monitoring … were not statistically significant, suggesting limited behavioral improvement following the interventions.”
Simply put, the current evidence does not support the effectiveness of game-based interventions in improving behavioral symptoms of ADHD in children and adolescents. The only positive results were from two studies with a small combined sample size, which does not qualify as a genuine meta-analysis. All the other meta-analyses performed with larger sample sizes reported no benefits.
Youths with ADHD are known to be more prone to language problems when compared with typically developing peers. To what extent does that affect their ability to share a narrative with others?
A Danish research team conducted a systematic review and meta-analysis of the peer-reviewed medical literature to explore this question. They stressed that this ability is important because "a narrative is a genre of discourse - a form of social communication used to derive meaning from experiences and to construct a shared understanding of events. In other words, it is the fundamental ability of orally producing a coherent story." They focused on the production of narratives rather than comprehension.
Studies had to have a minimum of 10 participants. They had to compare aspects of oral narrative production in children and adolescents with either a formal ADHD diagnosis or a score above a clinical cut-off on a validated ADHD rating scale to a control group of typically developing youths. Youths with confirmed autism spectrum disorder (ASD) or language impairment diagnoses were excluded. There were no constraints on IQ.
The team found sixteen studies with a combined total of 1,015 youths that met these criteria and were suitable for meta-analysis.
They examined seven aspects of oral narrative production:
· Coherence: A story structure that is logical and easy to follow in cause and sequence. There is a clear beginning, middle, and end. There are goals, attempts, and outcomes. A meta-analysis of nine studies with a combined total of 750 participants found youths with ADHD less coherent than their typically developing peers, with a medium effect size. There was virtually no between-study heterogeneity and no sign of publication bias.
· Cohesion: This ensures referencing of events and characters in a manner that enables the listener to grasp how characters, events, and ideas in a story are related. Ambiguous or contradictory references get in the way of this. A meta-analysis of eight studies with a combined total of 501 participants found youths with ADHD showed less cohesion than their typically developing peers, with a medium effect size. Again, with virtually no between-study heterogeneity, and no sign of publication bias.
· Disruptions: These can be sequence errors, misinterpretations, embellishments, or confabulations - fabricating imaginary experiences as compensation for loss of memory. A meta-analysis of six studies with 389 participants found youths with ADHD had more disruptions than their typically developing peers, with a small-to-medium effect size. There was virtually no between-study heterogeneity and no sign of publication bias.
· Fluency: Best explained in terms of errors that interfere with this quality, such as false starts, repeating words or sentences, and abandoning sentences without completing them. A meta-analysis of four studies with 220 participants found no difference in fluency between youths with ADHD and their typically developing peers.
· Production: This is a measure of output -overall length of the story, number of sentences, number of words. After adjusting for evidence of publication bias, a meta-analysis of twelve studies with 645 participants found no difference here.
· Syntactic complexity: This includes the extent of vocabulary and the use of proper grammar. A meta-analysis of six studies with 272 participants found youths with ADHD displayed less syntactic complexity than their typically developing peers, with a small-to-medium effect size. There was virtually no between-study heterogeneity and no sign of publication bi
· Internal state language: References to perceptions, thoughts, beliefs, and feelings. There were only two studies with 130 participants, so no meta-analysis was performed.
The authors concluded, "the results from the current meta-analysis suggest that children with ADHD have impairments in their narrative language. In particular, children with ADHD produce narratives that are less coherent, less cohesive, less syntactically complex, and include more disruptive errors than typically developing children do."
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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