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.
October 14, 2024
.png)
The report "Attention-Deficit/Hyperactivity Disorder Diagnosis, Treatment, and Telehealth Use in Adults" published in the CDC's Morbidity and Mortality Weekly Report provides a detailed examination of the prevalence and treatment of ADHD among U.S. adults based on data collected by the National Center for Health Statistics Rapid Surveys System during October–November 2023. This data is crucial as it offers updated estimates on the prevalence of ADHD in adults, a condition often regarded as primarily affecting children, and highlights the ongoing challenges in accessing ADHD-related treatments, including telehealth services and medication availability.
The methods used in this study involved the National Center for Health Statistics (NCHS) Rapid Surveys System (RSS), which gathers data to approximate the national representation of U.S. adults through two commercial survey panels: the AmeriSpeak Panel from NORC at the University of Chicago and Ipsos’s KnowledgePanel. The data were collected via online and telephone interviews from 7,046 adults. The responses were weighted to reflect the total U.S. adult population, ensuring that the results approximate national estimates. In identifying adults with current ADHD, respondents were asked if they had ever been diagnosed with ADHD and, if so, whether they currently had the condition. The study also collected data on treatment types (including stimulant and nonstimulant medications), telehealth use, and demographic variables such as age, education, race, and household income.
The results showed that approximately 6.0% of U.S. adults, or an estimated 15.5 million people, had a current ADHD diagnosis. Notably, more than half of the adults with ADHD reported receiving their diagnosis during adulthood (age ≥18 years), indicating that diagnosis can occur well beyond childhood. Analysis of demographics showed significant differences between adults with ADHD and those without; adults with ADHD were more likely to be younger, with 84.5% under the age of 50. Adults with ADHD were also less likely to have completed a bachelor's degree and more likely to have a household income below the federal poverty level compared to those without ADHD. Regarding treatment, the report found that approximately one-third of adults with ADHD were untreated, and around one-third received both medication and behavioral treatment. Among those receiving pharmacological treatment, 33.4% used stimulant medications, and 71.5% of these individuals reported difficulties in getting their prescriptions filled due to medication unavailability, reflecting recent stimulant shortages in the United States. Additionally, nearly half of adults with ADHD had used telehealth services for ADHD-related care, including obtaining prescriptions and receiving counseling or therapy.
The discussion emphasizes the public health implications of these findings. ADHD is often diagnosed late, with many individuals not receiving a diagnosis until adulthood, which underscores the need for improved awareness and early identification of ADHD symptoms across the life course. Moreover, the high prevalence of untreated ADHD and the barriers to accessing stimulant medications reveal significant gaps in the healthcare system's ability to support adults with ADHD. These gaps can contribute to poorer outcomes, such as increased risk of injury, substance use, and social impairment. The report also highlights the role of telehealth, which became more prominent during the COVID-19 pandemic. Telehealth appears to provide a viable solution for expanding access to ADHD diagnosis and treatment, though challenges remain regarding the quality of care and potential for misuse. The authors suggest that improved clinical care guidelines for adults with ADHD could help reduce delays in diagnosis and treatment access, thus improving long-term outcomes for affected individuals.
In conclusion, the study provides a comprehensive view of the prevalence, treatment, and telehealth use for ADHD among adults in the U.S. These data are crucial for guiding clinical care and shaping policies related to medication access and telehealth services. The findings underscore the importance of ensuring an adequate supply of stimulant medications and reducing barriers to ADHD care, ultimately enhancing the quality of life for adults with this condition. The good news is that many adults with ADHD are being diagnosed and treated. It is, however, concerning that many are not treated and that many of those treated with stimulants were impacted by the stimulant shortage.
For more details, see: https://www.cdc.gov/mmwr/volumes/73/wr/mm7340a1.htm
Staley BS, Robinson LR, Claussen AH, et al. Attention-Deficit/Hyperactivity Disorder Diagnosis, Treatment, and Telehealth Use in Adults — National Center for Health Statistics Rapid Surveys System, United States, October–November 2023. MMWR Morb Mortal Wkly Rep 2024;73:890–895. DOI: http://dx.doi.org/10.15585/mmwr.mm7340a1
Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental condition that is typically diagnosed in childhood but can persist into adulthood. Its symptoms include inattention, hyperactivity, and impulsivity, and it can significantly affect daily life, academic achievement, and professional success. As scientific understanding of the condition continues to evolve, new research is revealing more insights into the prevalence, comorbidity, treatment, and physiological aspects of ADHD in adults. Here's a roundup of some recent findings:
A recent study assessing the prevalence of treatment for ADHD among US college students found that the location of mental health care significantly affects treatment outcomes. Specifically, students receiving mental healthcare on campus were less likely to receive any medication or therapy for ADHD, suggesting the need to evaluate the quality of mental health services available on college campuses and their effectiveness in treating ADHD.
Another study found a correlation between ADHD and the l-Arginine/Nitric oxide (Arg/NO) pathway, a physiological process linked to dopamine release and cardiovascular functioning. The study found that adults with ADHD who were not treated with methylphenidate (a common ADHD medication) showed variations in the Arg/NO pathway. This could have implications for monitoring potential cardiovascular side effects of ADHD medications, as well as for understanding the biochemical changes that occur in ADHD.
ADHD and chronic pain appear to be related, according to a comparative study of clinical and general population samples. Particularly in females with ADHD, the prevalence of chronic and multisite pain was found to be high. This calls for longitudinal studies to understand the complex sex differences of comorbid chronic pain and ADHD in adolescents and the potential impacts of stimulant use on pain.
Finally, a study investigated the comorbidity of ADHD and bipolar disorder (BD) and its potential link to violent behavior. The research revealed a positive effect of ADHD symptoms on violence tendency and aggression scores. Moreover, male gender and young age were also found to have significant positive effects on violence and aggression scores, suggesting an association between these disorders and violent behavior.
There is a growing interest (and controversy) in 'adult-onset ADHD. No current diagnostic system allows for the diagnosis of ADHD in adulthood, yet clinicians sometimes face adults who meet all criteria for ADHD, except for age at onset. Although many of these clinically referred adult-onset cases may reflect poor recall, several recent longitudinal population studies have claimed to detect cases of adult-onset ADHD that showed no signs of ADHD as a youth (Agnew-Blais, Polanczyk et al. 2016, Caye, Rocha, et al. 2016). They conclude, not only that ADHD can onset in adulthood, but that childhood-onset and adult-onset ADHD may be distinct syndromes(Moffitt, Houts, et al. 2015)
In each study, the prevalence of adult-onset ADHD was much larger than the prevalence of childhood-onset adult ADHD). These estimates should be viewed with caution. The adults in two of the studies were 18-19 years old. That is too small a slice of adulthood to draw firm conclusions. As discussed elsewhere (Faraone and Biederman 2016), the claims for adult-onset ADHD are all based on population as opposed to clinical studies.
Population studies are plagued by the "false positive paradox", which states that, even when false positive rates are low, many or even most diagnoses in a population study can be false.
Another problem is that the false positive rate is sensitive to the method of diagnosis. The child diagnoses in the studies claiming the existence of adult-onset ADHDused reports from parents and/or teachers but the adult diagnoses were based on self-report. Self-reports of ADHD in adults are less reliable than informant reports, which raises concerns about measurement error. Another longitudinal study found that current symptoms of ADHD were under-reported by adults who had had ADHD in childhood and over-reported by adults who did not have ADHD in childhood(Sibley, Pelham, et al. 2012). These issues strongly suggest that the studies claiming the existence of adult-onset ADHD underestimated the prevalence of persistent ADHD and overestimated the prevalence of adult-onset ADHD. Thus, we cannot yet accept the conclusion that most adults referred to clinicians with ADHD symptoms will not have a history of ADHD in youth.
The new papers conclude that child and adult ADHD are "distinct syndromes", "that adult ADHD is more complex than a straightforward continuation of the childhood disorder" and that adult ADHD is "not a neurodevelopmental disorder". These conclusions are provocative, suggesting a paradigm shift in how we view adulthood and childhood ADHD. Yet they seem premature. In these studies, people were categorized as adult-onset ADHD if full-threshold add had not been diagnosed in childhood. Yet, in all of these population studies, there was substantial evidence that the adult-onset cases were not neurotypical in adulthood (Faraone and Biederman 2016). Notably, in a study of referred cases, one-third of late adolescent and adult-onset cases had childhood histories of ODD, CD, and school failure(Chandra, Biederman, et al. 2016). Thus, many of the "adult onsets" of ADHD appear to have had neurodevelopmental roots.
Looking through a more parsimonious lens, Faraone and Biederman(2016)proposed that the putative cases of adult-onset ADHD reflect the existence of subthreshold childhood ADHD that emerges with full threshold diagnostic criteria in adulthood. Other work shows that subthreshold ADHD in childhood predicts onsets of full-threshold ADHD in adolescence(Lecendreux, Konofal, et al. 2015). Why is onset delayed in subthreshold cases? One possibility is that intellectual and social supports help subthreshold ADHD youth compensate in early life, with decompensation occurring when supports are removed in adulthood or the challenges of life increase. A related possibility is that the subthreshold cases are at the lower end of a dimensional liability spectrum that indexes risk for onset of ADHD symptoms and impairments. This is consistent with the idea that ADHD is an extreme form of a dimensional trait, which is supported by twin and molecular genetic studies(Larsson, Anckarsater, et al. 2012, Lee, Ripke, et al. 2013). These data suggest that disorders emerge when risk factors accumulate over time to exceed a threshold. Those with lower levels of risk at birth will take longer to accumulate sufficient risk factors and longer to onset.
In conclusion, it is premature to accept the idea that there exists an adult-onset form of ADHD that does not have its roots in neurodevelopment and is not expressed in childhood. It is, however, the right time to carefully study apparent cases of adult-onset ADHD to test the idea that they are late manifestations of a subthreshold childhood condition.
Swedish researchers examined outcomes for adult women who sought treatment at the Stockholm Center for Eating Disorders over two years and nine months. Out of 1,517 women who came to the clinic, 1,143remained eligible for the study, after excluding women whose symptoms did not fulfill the DSM-IV criteria for eating disorders or had incomplete records.
Of these, seven hundred patients could not be reached or declined to participate, leaving 443 for follow-up. To guard against the possibility that the follow-up group might not be representative of the overall treatment group, researchers compared to age, body mass index, and scores on tests for depression, anxiety, compulsively, inattention, and hyperactivity. The only statistically significant differences were small ones. The median age of the group lost to follow-up was one year younger, they were less likely to be living alone, and on average scored a single point higher on the depression test. Otherwise, they were broadly similar.
The one-year follow-up on the study group found a substantial difference in the rate of recovery from eating disorders between those with and without comorbid ADHD. Almost three out of four patients (72%) who scored lower (between 0-17) on the World Health Organization adult ADHD self-report scale had recovered from their eating disorder. Among those scoring18 and higher, on the other hand, it was less than half (47%). This difference was extraordinarily unlikely (one chance in one thousand) to be due to chance(p=.001).
Another way of expressing this is through odds ratios. Those scoring 18 and up on the ADHD self-report scale were about two and a half times less likely to recover from their eating disorders following treatment. More specifically, thy were about three times less likely to recover from the loss of control and binging, and almost three and a half times less likely to recover from purging.
To improve outcomes, the researchers suggest "identifying concomitant ADHD symptoms and customizing treatment interventions based on this." They specifically propose controlled clinical trials to explore the effect of combining stimulant medications with standard treatment for eating disorders
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.
_logo%201.svg)
