Cookie Preferences
By clicking, you agree to store cookies on your device to enhance navigation, analyze usage, and support marketing. More Info
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
July 16, 2025
Background Info:
Executive functions include inhibitory control, working memory, and cognitive flexibility. Inhibitory control is the ability to suppress distractions and focus on goals, which is the main deficit in ADHD.
Children and adolescents with ADHD often have off-task, unrelated thoughts and are easily distracted, limiting their sustained attention. This makes it difficult for them to focus on tasks and leads to impulsive behaviors that affect their daily life, academics, and social interactions. Improving inhibitory control in ADHD children and adolescents is essential.
Stimulant medications are commonly used to treat ADHD. However, side effects like insomnia, loss of appetite, and headaches may make parents hesitant to use these medications for their children.
Non-pharmacological treatments like cognitive training, behavior therapy, and physical exercise have gained attention for their lack of side effects. Research shows that some non-pharmacological methods can improve cognitive outcomes significantly, underscoring their potential in treating ADHD.
Study:
A Chinese research team identified four key gaps in current research on non-pharmacological treatments for inhibitory control in children with ADHD:
The team therefore performed a network meta-analysis of long-term randomized controlled trials (RCTs) to assess and rank the effectiveness of various non-pharmacological treatments on inhibitory control in children and adolescents with ADHD.
The team included only RCTs relying on professional diagnoses of ADHD, excluding those based only on parent and teacher rating scales.
The included studies measured inhibitory control using objective neurocognitive tasks, such as the Stroop test and the Go/No-Go test, to reduce potential subjective bias. Studies relying on parent- or teacher-reported questionnaires were excluded.
Controls either received no intervention or placebo, such as watching running videos and attending history classes.
Meta-analysis of 16 studies combining 546 participants found large short-term effect size improvements in inhibitory control from physical exercise. But the two studies with a total of 110 participants that performed a follow-up test reported only a small-to-medium effect size improvement.
For cognitive training, a meta-analysis of fifteen studies totaling 674 participants reported a medium effect size of short-term improvement in inhibitory control. The ten studies with 563 participants that performed a follow-up test found only a small effect size improvement since treatment initiation.
For behavioral therapy, meta-analysis of six studies encompassing 244 individuals likewise found a medium effect size short-term improvement in inhibitory control. In this case, however two studies combining 91 participants that performed a follow-up test reported that the medium effect size improvement was maintained.
For neurofeedback, meta-analysis of seven studies encompassing 186 individuals found a small-to-medium effect size short-term improvement in inhibitory control. The only study that performed a follow-up test reported a small effect size improvement since treatment initiation.
The two studies with a combined 44 individuals exploring board games found no significant improvement in inhibitory control. Likewise, the two studies combining 32 participants that explored meditation found no significant improvement in inhibitory control.
There was no indication of publication bias.
Conclusion:
The team concluded, “Existing evidence shows that physical exercise, behavior therapy, cognitive training, and neurofeedback can effectively improve the inhibitory control of children and adolescents with ADHD. However, meditation, EMG feedback, and board games did not significantly affect inhibitory control. Physical exercise has the best effect among all non-pharmacological treatments, but its impact will be weakened after intervention. Behavior therapy and cognitive training had a slightly lower effect, but they have a better maintenance effect.”
Ultimately, the study results suggest that non-drug treatments can help children and teens with ADHD improve their ability to control their actions and stay focused. Some methods, like physical exercise, work well at first but may fade once the activity stops. Other methods, like behavioral therapy and cognitive training, may take a little longer to show results but can last longer and make a bigger difference over time. Ultimately, and most importantly, because this work did not study the symptoms of ADHD or its real-world impairments, it provides no reason to change current treatment practices for ADHD.
Jingyi Zhou, Wen Jiang, Jingwen Wanga, and Jingjing Dou, “Network meta-analysis of the effects of long-term non-pharmacologic treatment on inhibitory control in children and adolescents with attention deficit hyperactivity disorder,” Journal of Psychiatric Research (2025), 187: 261-276, https://doi.org/10.1016/j.jpsychires.2025.05.028.
A new large-scale study has shed light on which treatments for attention-deficit/hyperactivity disorder (ADHD) in adults are most effective and best tolerated.
Researchers analyzed 113 randomized controlled trials involving nearly 15,000 adults diagnosed with ADHD. These studies included medications (like stimulants and atomoxetine), psychological therapies (such as cognitive behavioral therapy), and newer approaches like neurostimulation.
The Findings
Stimulant medications (lisdexamfetamine and methylphenidate) as well as selective norepinephrine reuptake inhibitors (SNRI) (atomoxetine) were the only treatments that consistently reduced core ADHD symptoms—both from the perspective of patients and clinicians. It may be worth noting that atomoxetine, while effective, was less well tolerated, with more people dropping out due to side effects.
Psychological therapies such as CBT, mindfulness, and psychoeducation showed some benefits, but mainly according to clinician ratings—not necessarily from the patients themselves. Neurostimulation techniques like transcranial direct current stimulation also showed some improvements, but only in limited contexts and with small sample sizes.
Conclusion
So, what does this mean for people navigating ADHD in adulthood? Stimulant medications remain the most effective treatment for managing ADHD symptoms day-to-day but nonstimulant medication are not far behind, which is good given the problems we’ve had with stimulant shortages. This study also supports structured psychotherapy as a viable treatment option, especially when used in conjunction with medication.
The study emphasizes the importance of ongoing, long-term research and the need for treatment plans that are tailored to the individual ADHD patient– Managing adult ADHD effectively calls for flexible, patient-centered care.
-----
Struggling with side effects or not seeing improvement in your day-to-day life? Dive into a step-by-step journey that starts with the basics of screening and diagnosis, detailing the clinical criteria healthcare professionals use so you can be certain you receive an accurate evaluation. This isn’t just another ADHD guide—it’s your toolkit for getting the care you deserve. This is the kind of care that doesn’t just patch up symptoms but helps you unlock your potential and build the life you want. Whether you’ve just been diagnosed or you’ve been living with ADHD for years, this booklet is here to empower you to take control of your healthcare journey.
Proceeds from the sale of this book are used to support www.ADHDevidence.org.
Attention Deficit Hyperactivity Disorder (ADHD) is a common condition affecting children and adolescents worldwide, characterized by symptoms such as hyperactivity, impulsivity, and inattention. While traditional treatments like medication and behavioral therapy are often used, some individuals are turning to complementary and alternative therapies (CAM) for help. One such option gaining attention is acupuncture. But does it really work for ADHD?
A recent comprehensive study aimed to evaluate the effectiveness of acupuncture in treating ADHD symptoms. Here’s a breakdown of the findings, with a focus on the age groups included in the research and what these findings could mean for ADHD treatment options.
The study in question conducted a systematic review and meta-analysis (SR/MA) of acupuncture trials for ADHD, comparing its effects to traditional treatments such as pharmacotherapy and behavioral therapy. The researchers focused on acupuncture’s impact on core ADHD symptoms like hyperactivity, impulsivity, inattention, and conduct problems, while also exploring how acupuncture might help with other issues, such as learning difficulties and psychosomatic symptoms.
One key feature of this study was the inclusion of a broad age range of participants, specifically children and adolescents. These two groups are the most commonly diagnosed with ADHD, and their responses to treatments can vary significantly. Understanding how acupuncture works for these age groups is critical for evaluating its effectiveness as an ADHD treatment.
Here’s what the study found across the different age groups:
Despite these promising results, the study also highlighted several limitations:
In short, and as is so often the way of evidence-based medicine, we still can’t say with absolute certainty one way or the other. These studies may show promise in improving hyperactivity, impulsivity, inattention, and conduct problems– in both children and adolescents. However, the evidence is not yet strong enough to recommend it as a primary treatment. While it may serve as a helpful complement to standard therapies, especially for those struggling with medication side effects or access to behavioral therapy, more research is needed to establish its effectiveness.
A Chinese research team performed two types of meta-analyses to compare the risk of suicide for ADHD patients taking ADHD medication as opposed to those not taking medication.
The first type of meta-analysis combined six large population studies with a total of over 4.7 million participants. These were located on three continents - Europe, Asia, and North America - and more specifically Sweden, England, Taiwan, and the United States.
The risk of suicide among those taking medication was found to be about a quarter less than for unmediated individuals, though the results were barely significant at the 95 percent confidence level (p = 0.49, just a sliver below the p = 0.5 cutoff point). There were no significant differences between males and females, except that looking only at males or females reduced sample size and made results non-significant.
Differentiating between patients receiving stimulant and non-stimulant medications produced divergent outcomes. A meta-analysis of four population studies covering almost 900,000 individuals found stimulant medications to be associated with a 28 percent reduced risk of suicide. On the other hand, a meta-analysis of three studies with over 62,000 individuals found no significant difference in suicide risk for non-stimulant medications. The benefit, therefore, seems limited to stimulant medication.
The second type of meta-analysis combined three within-individual studies with over 3.9 million persons in the United States, China, and Sweden. The risk of suicide among those taking medication was found to be almost a third less than for unmediated individuals, though the results were again barely significant at the 95 percent confidence level (p =0.49, just a sliver below the p = 0.5 cutoff point). Once again, there were no significant differences between males and females, except that looking only at males or females reduced the sample size and made results non-significant.
Differentiating between patients receiving stimulant and non-stimulant medications once again produced divergent outcomes. Meta-analysis of the same three studies found a 25 percent reduced risk of suicide among those taking stimulant medications. But as in the population studies, a meta-analysis of two studies with over 3.9 million persons found no reduction in risk among those taking non-stimulant medications.
A further meta-analysis of two studies with 3.9 million persons found no reduction in suicide risk among persons taking ADHD medications for 90 days or less, "revealing the importance of duration and adherence to medication in all individuals prescribed stimulants for ADHD."
The authors concluded, "exposure to non-stimulants is not associated with a higher risk of suicide attempts. However, a lower risk of suicide attempts was observed for stimulant drugs. However, the results must be interpreted with caution due to the evidence of heterogeneity ..."
.png)
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.
_logo%201.svg)
