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March 31, 2026
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.
Pan N, Long Y, Qin K, et al. Mapping ADHD Heterogeneity and Biotypes by Topological Deviations in Morphometric Similarity Networks. JAMA Psychiatry. Published online February 25, 2026. doi:10.1001/jamapsychiatry.2026.0001
Centanafadine, which is currently under investigation as a treatment for ADHD, will be the first triple reuptake inhibitor for the disorder if it is approved by the FDA. It improves norepinephrine, dopamine and serotonin levels. This new medication is not a stimulant, but due to the dopamine component, it has a stimulant-like effect in patients. In adults, two phase 3 trials and a year-long extension have shown sustained benefits and a tolerable safety profile, laying the groundwork for pediatric research.
Based on this study, improvement was already noticeable after the first week and held steady through week 6. The lower dose (164.4 mg) didn’t separate from placebo, reminding us that getting the dose right will be critical. The effect size was smaller than what is seen for stimulants but 50% of patients had excellent outcomes as indicated by reductions in the ADHD-RS of 50% or more.
Side effect patterns look familiar to anyone who prescribes ADHD medications; loss of appetite, nausea and headaches topped the list. About half of teens on the higher dose reported at least one treatment-emergent adverse event, compared with a quarter of those on placebo. Severe reactions were rare but did include isolated liver enzyme spikes, rash, and a few reports of aggression or somnolence. For everyday practice, that translates to routine growth checks, a look at baseline liver function, and clear guidance to families about reporting rashes or mood changes promptly.
The researchers noted that the study had certain limitations, including limited generalizability to adolescents beyond North America, the exclusion of teacher ratings on the ADHD-RS-5 scale and the study’s short duration. They added that future studies should explore long-term treatment outcomes and efficacy compared with other ADHD treatments, as well as its effect on treating ADHD with comorbid conditions.
First, speed. Centanafadine separated from placebo within a week. In this regard, it might be closer to stimulants than to the multi-week ramp-up we expect from current non-stimulants. Second, it offers another option when stimulants are contraindicated or poorly tolerated, or when they raise diversion concerns. Its mechanism also makes it intriguing for patients who need both norepinephrine and dopamine coverage but prefer to avoid schedule II drugs. Because it also improves serotonergic transmission, it may be useful for some of ADHD’s comorbidities (see our new article for evidence about serotonin’s role in these disorders).
Keep in mind that centanafadine for ADHD is still investigational, so participation in clinical trials remains the only access route.
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This New York Times article, “5 Takeaways from New Research about ADHD”, earns a poor grade for accuracy. Let’s break down their (often misleading and frequently inaccurate) claims about ADHD.
The Claim: A.D.H.D. is hard to define/ No ADHD Biomarkers exist
The Reality: The claim that ADHD is hard to define “because scientists haven’t found a single biological marker” is misleading at best. While it is true that no biomarker exists, decades of rigorous research using structured clinical interviews and standardized rating scales show that ADHD is reliably diagnosed. Decades of validation research consistently show that ADHD is indeed a biologically-based disorder. One does not need a biomarker to draw that conclusion and recent research about ADHD has not changed that conclusion.
Additionally, research has in fact confirmed that genetics do play a role in the development of ADHD and several genes associated with ADHD have been identified.
The Claim: The efficacy of medication wanes over time
The Reality: The article’s statement that medications like Adderall or Ritalin only provide short-term benefits that fade over time is wrong. It relies almost entirely on one study—the Multimodal Treatment Study of ADHD (MTA). In the MTA study, the relative advantage of medication over behavioral treatments diminished after 36 months. This was largely because many patients who had not initially been given medication stopped taking it and many who had only been treated with behavior therapy suddenly began taking medication. The MTA shows that patients frequently switched treatments. It does not overturn other data documenting that these medications are highly effective. Moreover, many longitudinal studies clearly demonstrate sustained benefits of ADHD medications in reducing core symptoms, psychiatric comorbidity, substance abuse, and serious negative outcomes, including accidents, and school dropout rates. A study of nearly 150,000 people with ADHD in Sweden concluded “Among individuals diagnosed with ADHD, medication initiation was associated with significantly lower all-cause mortality, particularly for death due to unnatural causes”. The NY Times’ claim that medications lose their beneficial effects over time ignores compelling evidence to the contrary.
The Claim: Medications don’t help children with ADHD learn
The Reality: ADHD medications are proven to reliably improve attention, increase time spent on tasks, and reduce disruptive behavior, all critical factors directly linked to better academic performance.The article’s assertion that ADHD medications improve only classroom behavior and do not actually help students learn also oversimplifies and misunderstands the research evidence. While medication alone might not boost IQ or cognitive ability in a direct sense, extensive research confirms significant objective improvements in academic productivity and educational success—contrary to the claim made in the article that the medication’s effect is merely emotional or perceptual, rather than genuinely educational.
For example, a study of students with ADHD who were using medication intermittingly concluded “Individuals with ADHD had higher scores on the higher education entrance tests during periods they were taking ADHD medication vs non-medicated periods. These findings suggest that ADHD medications may help ameliorate educationally relevant outcomes in individuals with ADHD.”
The Claim: Changing a child’s environment can change his or her symptoms.
The Reality: The Times article asserts that ADHD symptoms are influenced by environmental fluctuations and thus might not have their roots in neurobiology. We have known for many years that the symptoms of ADHD fluctuate with environmental demands. The interpretation of this given by the NY Times is misleading because it confuses symptom variability with underlying causes. Many disorders with well-established biological origins are sensitive to environmental factors, yet their biology remains undisputed.
For example, hypertension is unquestionably a biologically based condition involving genetic and physiological factors. However, it is also well-known that environmental stressors, dietary
habits, and lifestyle factors can significantly worsen or improve hypertension. Similarly, asthma is biologically rooted in inflammation and airway hyper-reactivity, but environmental triggers such as allergens, pollution, or even emotional stress clearly impact symptom severity. Just as these environmental influences on hypertension or asthma do not negate their biological basis, the responsiveness of ADHD symptoms to environmental fluctuations (e.g., improvements in classroom structure, supportive home life) does not imply that ADHD lacks neurobiological roots. Rather, it underscores that ADHD, like many medical conditions, emerges from the interplay between underlying biological vulnerabilities and environmental influences.
Claim: There is no clear dividing line between those who have A.D.H.D. and those who don’t.
The Reality: This is absolutely and resoundingly false. The article’s suggestion that ADHD diagnosis is arbitrary because ADHD symptoms exist on a continuum rather than as a clear-cut, binary condition is misleading. Although it is true that ADHD symptoms—like inattention, hyperactivity, and impulsivity—do vary continuously across the population, the existence of this continuum does not make the diagnosis arbitrary or invalidate the disorder’s biological basis. Many well-established medical conditions show the same pattern. For instance, hypertension (high blood pressure) and hypercholesterolemia (high cholesterol) both involve measures that are continuously distributed. Blood pressure and cholesterol levels exist along a continuum, yet clear diagnostic thresholds have been carefully established through decades of clinical research. Their continuous distribution does not lead clinicians to question whether these conditions have biological origins or whether diagnosing an individual with hypertension or hypercholesterolemia is arbitrary. Rather, it underscores that clinical decisions and diagnostic thresholds are established using evidence about what levels lead to meaningful impairment or increased risk of negative health outcomes. Similarly, the diagnosis of ADHD has been meticulously defined and refined over many decades using extensive empirical research, structured clinical interviews, and validated rating scales. The diagnostic criteria developed by experts carefully delineate the point at which symptoms become severe enough to cause significant impairment in an individual’s daily functioning. Far from being arbitrary, these thresholds reflect robust scientific evidence that individuals meeting these criteria face increased risks for the serious impairments in life including accidents, suicide and premature death.
The existence of milder forms of ADHD does not undermine the validity of the diagnosis; rather, it emphasizes the clinical reality that people experience varying degrees of symptom severity.
Moreover, acknowledging variability in severity has always been a core principle in medicine. Clinicians routinely adjust treatments to meet individual patient needs. Not everyone diagnosed with hypertension receives identical medication regimens, nor does everyone with elevated cholesterol get prescribed the same intervention. Similarly, people with ADHD receive personalized treatment plans tailored to the severity of their symptoms, their specific impairments, and their individual circumstances. This personalization is not evidence of arbitrariness; it is precisely how evidence-based medicine is practiced. In sum, the continuous nature of ADHD symptoms is fully compatible with a biologically-based diagnosis that has substantial evidence for validity, and acknowledging symptom variability does not render diagnosis arbitrary or diminish its clinical importance.
In sum, readers seeking a balanced, evidence-based understanding of ADHD deserve clearer, more careful reporting. By overstating diagnostic uncertainty, selectively interpreting research about medication efficacy, and inaccurately portraying the educational benefits of medication, this article presents an overly simplistic, misleading picture of ADHD.
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The Neuroeconomic Perspective
Neuroeconomics combines neuroscience, psychology, and economics to understand how people make decisions. Neuroeconomic studies suggest that brain regions responsible for evaluating risk and reward, including the prefrontal cortex and dopamine pathways, function differently in individuals with ADHD. These insights are crucial for developing more tailored interventions. For example, understanding how ADHD affects reward processing might inform strategies that help individuals resist impulsive choices or increase motivation for delayed rewards.
Understanding Decision-Making in ADHD
We know that decision-making is a sophisticated process involving various cognitive procedures. It’s not just about choosing between options but also about how to weigh risks, rewards, and potential future outcomes; Attention, motivation, and cognitive control are core to this process. For individuals with ADHD, however, this neural framework is affected by impairments in attention and impulse control, often resulting in “delay discounting”—the tendency to prefer smaller, immediate rewards over larger, delayed ones.
This propensity for impulsive decisions is more than a personal challenge; it has broader societal and economic implications. Previous studies have shown that these tendencies in ADHD can lead to issues in academics, work, finances, and personal relationships, emphasizing the need for targeted support and interventions.
Implications and Future Directions
This review highlights a need for continued research to bridge the gaps in understanding how ADHD-specific cognitive deficits influence decision-making. Viewing ADHD through a neuroeconomic lens clarifies how cognitive and neural differences affect decision-making, often leading to impulsive choices with economic and social impacts. This perspective opens doors to more effective interventions, improving decision-making for individuals with ADHD. Future policies informed by this approach could enhance support and reduce associated societal costs.
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The Background:
Women with polycystic ovary syndrome (PCOS) themselves show higher rates of ADHD. Because ADHD is partly heritable (meaning genes contribute to the condition), some of the increased ADHD seen in children of mothers with PCOS could come from shared genetic factors. In other words, a mother’s and her child’s increased risk might sometimes reflect common genes rather than an effect of the pregnancy itself.
Beyond genetics, growing evidence points to maternal metabolic problems during pregnancy as another important risk factor for neurodevelopmental outcomes. PCOS is one of these conditions and is considered both potentially modifiable (treatable or manageable) and biologically plausible as a contributor to risk. PCOS affects an estimated 5–10% of women of reproductive age worldwide and is characterized by signs such as hyperandrogenism (higher-than-normal levels of “male” hormones), insulin resistance (poorer ability to use the hormone insulin, which can affect blood sugar and metabolism), and chronic low-grade inflammation.
However, studies to date have not all reached the same conclusions. Some research suggests the association between maternal PCOS and offspring ADHD is stronger for girls, while other studies did not analyze results by child sex. Methodological differences make it harder to draw clear conclusions.
The Study:
It’s important to note that the studies included in this meta-analysis were observational (cohort studies and case-control studies). Observational studies can identify associations (that two things occur together) but cannot prove that one causes the other. A cohort study follows people over time, and a case-control study compares people with a condition to similar people without it.
The pooled results came from six studies that together included almost 1.4 million mother–child pairs and that adjusted for confounders (other factors that might influence the result, such as maternal age or socioeconomic status). After statistical adjustment, children of mothers with PCOS had about 40% greater odds of ADHD than children of mothers without PCOS. The analysis reported no evidence of publication bias (no clear sign that only positive studies were published) and zero heterogeneity (the results were consistent across the studies).
There was no meaningful difference in results between cohort and case-control studies, and the meta-analysis did not find a significant difference in the association when comparing male and female offspring.
The Take-Away:
The research team concluded that this large-scale synthesis found an association between maternal PCOS and higher odds of ADHD and other neuropsychiatric conditions in children. They suggested that children born to mothers with PCOS may benefit from developmental monitoring to identify and address problems early, while emphasizing that causal relationships have not been established. They called for further studies to confirm these findings and to investigate the biological and environmental mechanisms that might explain the association. Indeed, because women with PCOS show higher rates of ADHD than other women, we need genetically informed research designs to see if the reported association is confounded.
The Background:
Food insecurity is a widespread public‑health problem. Food insecurity refers to limited or uncertain access to enough safe, nutritious food. This term is used to describe households that sometimes or often can’t afford enough food or can only buy cheaper, less‑healthy options.
In the United States, almost eleven million children and teens (14%) lived in food‑insecure households in 2019. By 2023, the share of households with food‑insecure children and adolescents was estimated to have risen to about 18%.
Food insecurity is linked to worse physical health in children, including conditions like anemia (low red‑blood‑cell count), asthma, and delays in physical or mental development. It is also associated with problems in thinking and conduct (for example, aggressive behavior, anxiety, depression, and trouble concentrating or sitting still).
Those thinking and behavior problems can look a lot like ADHD (persistent patterns of inattention, hyperactivity, and impulsivity. This can make it hard for clinicians to tell whether symptoms come from ADHD itself, from the stress of poverty and food insecurity, or a mix of both. That overlap can complicate diagnosis and sometimes lead to misdiagnosis.
Smaller recent studies have looked at mental‑health links and found higher odds of ADHD and other mental‑health conditions among food‑insecure children aged 5–11 years. In one set of findings, moderate food insecurity was associated with 50% greater odds of an ADHD diagnosis and severe food insecurity with about 67% greater odds relative to food‑secure children.
The Study:
Because many past studies looked at single risk factors or only measured symptom severity, fewer investigations have focused specifically on household food insecurity as it relates to actual ADHD diagnoses and how that might matter for care. To address that gap, researchers used multiple years (2016–2022) of data from the U.S. National Survey of Children’s Health (NSCH). This survey is designed to be nationally representative and asks parents about their child’s health, including whether a doctor or other clinician has diagnosed ADHD.
The study included 232,571 children and adolescents (ages 3–17) and used statistical methods to adjust for other factors that could affect ADHD risk. Those factors included the child’s sex and race/ethnicity; the mother’s age; family income expressed as a percentage of the federal poverty level (a government measure used to classify income groups); the highest level of parent education; adverse childhood experiences (such as exposure to abuse, household substance use, or parental separation); birthweight (for example, low birthweight); and not getting enough sleep. Adjusting for these variables helps isolate the association between food insecurity and ADHD, though it cannot prove cause and effect.
The Results:
In this large, nationally representative sample, the researchers found a clear dose–response relationship: as the level of household food insecurity increased, so did the odds of a child having a clinician‑diagnosed ADHD (as reported by parents). In other words, greater food insecurity was linked to a higher likelihood of ADHD.
Compared with children in households that “could always afford to eat good, nutritious meals” (the reference group), the study found the following increases in odds of ADHD: children in households that “could always afford enough to eat but not always the kinds of food we should eat” had about 30% greater odds; children in households that sometimes “could not afford enough to eat” had about 55% greater odds; and children in households that often “could not afford enough to eat” had about 80% greater odds. (Saying “30% greater odds,” etc., means the odds were 1.30, 1.55, and 1.80 times those of the reference group, respectively — this describes a relative increase, not the absolute percentage of children with ADHD.)
The Take-Away:
The authors conclude that household food insecurity was associated with higher odds of parent‑reported clinician‑diagnosed ADHD in a dose‑response pattern. They suggest that reducing food insecurity (for example, ,by improving access to nutritious food and combining nutritional supports with mental‑health care) may help lower ADHD risk or reduce symptoms in some children. Reducing food insecurity should be a priority for society, but it is premature to conclude it will reduce the risk for ADHD. We know that parents with ADHD are more likely to lose their jobs and have lower incomes compared to parents with ADHD. That might create food insecurity for their children who we know are at high risk for ADHD from genetic studies.
The Background:
Many studies have tried to determine whether exercise improves executive function in children and adolescents with ADHD, but their conclusions have not always agreed. To bring the evidence together more clearly, the research team re-analyzed the available randomized controlled trials using a statistical approach designed to handle the kinds of data common in this field.
Executive functions are skills that help us control attention and behavior. The three core components are inhibitory control (the ability to stop or override impulses), working memory (holding and manipulating information in mind), and cognitive flexibility (switching between tasks or perspectives). Because a single study often reports multiple tests that tap these different skills, one study can contribute several related results (called effect sizes). Traditional meta-analysis typically treats each effect size as independent; when they are actually correlated, that can bias the combined estimate or force reviewers to discard useful data.
To avoid those problems, the team used a three-level meta-analysis. In this model, variance in the data is separated into three sources:
(1) sampling variance: the random error in each measured effect
(2) within-study variance: differences between multiple effect sizes reported in the same study
(3) between-study variance: differences in effects from one study to another
Accounting for all three levels makes it possible to include every eligible effect size from each study, which preserves information and statistical power and reduces the risk that correlations among effect sizes will overstate results.
The Study:
The review focused on long-term exercise interventions and also tested whether certain factors might change (or moderate) the effects. These potential moderators included participant age, which executive-function subcomponent was measured, the type of exercise, how long each session lasted, the total length of the intervention, and how often sessions occurred.
To be included, studies had to be randomized controlled trials (RCTs) of children or adolescents aged 6–18 diagnosed with ADHD. RCTs randomly assign participants to an intervention or a comparison group and are considered a strong design for testing cause-and-effect. The exercise programs had to be structured and last at least six weeks. Comparison groups varied by study and could include usual care, medication, sedentary activities, health education, waiting lists, or everyday life without the specific exercise program. Fifteen studies including 658 participants met these criteria.
The Results:
The three-level meta-analysis showed that long-term exercise interventions were associated with moderate-to-strong improvements in overall executive function. When statistical outliers were removed, the result remained positive: 13 RCTs with 598 participants showed moderate improvements. In plain terms, this suggests improvements that are noticeable and meaningful on average, not just tiny changes that are unlikely to matter in daily life.
Those moderate gains appeared across all three executive-function domains (inhibitory control, working memory, and cognitive flexibility, meaning the benefits were not limited to a single cognitive skill. The authors also examined exercise type:
“Open-skill” activities, which require reacting to changing situations (for example, many team sports, martial arts sparring, or racket sports), produced moderate-to-large improvements.
“Closed-skill” activities, which are more predictable and repetitive (for example, running or stationary cycling), showed only small, non-significant improvements in this analysis.
The review also found dose-related patterns. Interventions lasting at least twelve weeks were about three times more effective than interventions of six to twelve weeks, and sessions longer than an hour were about twice as effective as shorter sessions. Benefits were largest among adolescents aged 13 and older.
These patterns suggest that longer, more intensive programs, and those that involve open-skill activities, may produce larger gains. However, the authors caution that the overall certainty of the evidence was low. “Low certainty” means that limitations in the available studies (for example, small sample sizes, variability in methods, or possible bias) make it difficult to be confident that the observed effects will hold up exactly the same way in future research. Some subgroup findings (age, intervention duration, and others) were based on only a small number of effect sizes, so those moderator results should be treated as exploratory rather than definitive.
The Take-Away:
In short, this three-level meta-analysis suggests that regular, structured exercise (particularly longer programs and open-skill activities) may help improve executive functions in children and adolescents with ADHD. The evidence is promising but not yet strong enough to be considered conclusive, and the authors recommend more, larger randomized trials to confirm specifically which types and doses of exercise are most effective. Moreover, neither this meta-analysis or others show that exercise can replace standard treatments for reducing the core symptoms of ADHD (inattention, hyperactivity, impulsivity).
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