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April 17, 2025
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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.
Li L, Zhu N, Zhang L, et al. ADHD Pharmacotherapy and Mortality in Individuals With ADHD. JAMA. 2024;331(10):850–860. doi:10.1001/jama.2024.0851
Lu Y, Sjölander A, Cederlöf M, et al. Association Between Medication Use and Performance on Higher Education Entrance Tests in Individuals With Attention-Deficit/Hyperactivity Disorder. JAMA Psychiatry. 2017;74(8):815–822. doi:10.1001/jamapsychiatry.2017.1472
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A recent study delved into the connection between fidgeting and cognitive performance in adults with Attention-Deficit/Hyperactivity Disorder. Recognizing that hyperactivity often manifests as fidgeting, the researchers sought to understand its role in attention and performance during cognitively demanding tasks. They designed a framework to quantify meaningful fidgeting variables using actigraphy devices.
(Note: Actigraphy is a non-invasive method of monitoring human rest/activity cycles. It involves the use of a small, wearable device called an actigraph or actimetry sensor, typically worn on the wrist, similar to a watch. The actigraph records movement data over extended periods, often days to weeks, to track sleep patterns, activity levels, and circadian rhythms. In this study, actigraphy devices were used to measure fidgeting by recording the participants' movements continuously during the cognitive task. This data provided objective, quantitative measures of fidgeting, allowing the researchers to analyze its relationship with attention and task performance.)
The study involved 70 adult participants aged 18-50, all diagnosed with ADHD. Participants underwent a thorough screening process, including clinical interviews and ADHD symptom ratings. The analysis revealed that fidgeting increased during correct trials, particularly in participants with consistent reaction times, suggesting that fidgeting helps sustain attention. Interestingly, fidgeting patterns varied between early and later trials, further highlighting its role in maintaining focus over time.
Additionally, a correlation analysis validated the relevance of the newly defined fidget variables with ADHD symptom severity. This finding suggests that fidgeting may act as a compensatory mechanism for individuals with ADHD, aiding in their ability to maintain attention during tasks requiring cognitive control.
This study provides valuable insights into the role of fidgeting in adults with ADHD, suggesting that it may help sustain attention during challenging cognitive tasks. By introducing and validating new fidget variables, the researchers hope to standardize future quantitative research in this area. Understanding the compensatory role of fidgeting can lead to better management strategies for ADHD, emphasizing the potential benefits of movement for maintaining focus.
With the growth of the Internet, we are flooded with information about attention deficit hyperactivity disorder from many sources, most of which aim to provide useful and compelling "facts" about the disorder. But, for the cautious reader, separating fact from opinion can be difficult when writers have not spelled out how they have come to decide that the information they present is factual.
My blog has several guidelines to reassure readers that the information they read about ADHD is up-to-date and dependable. They are as follows:
Nearly all the information presented is based on peer-reviewed publications in the scientific literature about ADHD. "Peer-reviewed" means that other scientists read the article and made suggestions for changes and approved that it was of sufficient quality for publication. I say "nearly all" because in some cases I've used books or other information published by colleagues who have a reputation for high-quality science.
When expressing certainty about putative facts, I am guided by the principles of evidence-based medicine, which recognizes that the degree to which we can be certain about the truth of scientific statements depends on several features of the scientific papers used to justify the statements, such as the number of studies available and the quality of the individual studies. For example, compare these two types of studies. One study gives drug X to 10 ADHD patients and reported that 7 improved. Another gave drug Y to 100 patients and a placebo to 100 other patients and used statistics to show that the rate of improvement was significantly greater in the drug-treated group. The second study is much better and much larger, so we should be more confident in its conclusions. The rules of evidence are fairly complex and can be viewed at the Oxford Center for Evidenced Based Medicine (OCEBM;http://www.cebm.net/).
The evidenced-based approach incorporates two types of information: a) the quality of the evidence and b) the magnitude of the treatment effect. The OCEBM levels of evidence quality are defined as follows (higher numbers are better:
Non-randomized, controlled studies. In these studies, the treatment group is compared to a group that receives a placebo treatment, which is a fake treatment not expected to work.
It is possible to have high-quality evidence proving that a treatment works but the treatment might not work very well. So it is important to consider the magnitude of the treatment effect, also called the "effect size" by statisticians. For ADHD, it is easiest to think about ranking treatments on a ten-point scale. The stimulant medications have a quality rating of 5 and also have the strongest magnitude of effect, about 9 or 10.Omega-3 fatty acid supplementation 'works' with a quality rating of 5, but the score for the magnitude of the effect is only 2, so it doesn't work very well. We have to take into account patient or parent preferences, comorbid conditions, prior response to treatment, and other issues when choosing a treatment for a specific patient, but we can only use an evidence-based approach when deciding which treatments are well-supported as helpful for a disorder.
Adults with ADHD are more likely to have accidents, drive unsafely, have unsafe sex, and abuse substances. These 'real world' impairments suggest that people with ADHD may be predisposed to making risky decisions. Many studies have attempted to address this, but it is only recently that their results have been aggregated into a systematic review and meta-analysis. This paper by Dekkers and colleagues reports 37 laboratory studies of risky decision-making that studied a total of 1175 ADHD patients and 1222 controls. In these laboratory tasks, research participants are given a task to complete which requires that they make choices that have varying degrees of risk and reward. Using the results of such experiments, researchers can score the degree to which participants make risky decisions. When Dekkers and colleagues analyzed the 37 studies together, they found substantial evidence that ADHD people are more likely to make risky decisions than people without ADHD. The tendency to make risky decisions was greatest for those who, in addition to having ADHD, also had conduct or oppositional disorders, which both have features that indicate antisocial behavior and aggressiveness. We can not tell from these studies why ADHD patients make risky decisions. One explanation is that it is simply the impulsivity of ADHD people that leads to rash, unwise decisions. Another theory postulates that risky decisions reflect deficits in one's sensitivity to rewards and punishments. If we are very motivated by reward and not aware of or affected by the possibility of punishment, then risky decisions will be common. The studies analyzed in the meta-analysis were not designed to demonstrate a link between risky decision-making in the lab and the real world, risky decisions that lead to accidents, and other outcomes. It is reasonable to hypothesize such a link, which is why clinicians should consider risky decision-making when planning treatments. If you suspect deficits in this area, it will not change your approach to pharmacologic treatment but, given the potential adverse consequences of risky decisions, you should consider referring such patients to cognitive behavior therapy for adult ADHD as this talk therapy may be able to teach ADHD adults how to cope with their decision-making deficits.
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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