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October 29, 2024
Attention-Deficit/Hyperactivity Disorder (ADHD) remains a prevalent condition among children and adolescents in the United States. A recent analysis based on the National Health Interview Survey (NHIS), conducted by the National Center for Health Statistics at the CDC, provides an updated look at ADHD prevalence from 2018 to 2021. Here’s a closer look at what the data reveals.
The NHIS is an annual survey primarily conducted through face-to-face interviews in respondents’ homes. Telephone interviews are used as a substitute in cases where travel is impractical. For each family interviewed, one child aged 3-17 is randomly selected for the survey through a computer program. Over the four years studied (2018-2021), a total of 26,422 households with children or adolescents participated.
The analysis found that 9.5% of children and adolescents in the United States had been diagnosed with ADHD, based on reports from family members. However, the prevalence varied significantly with age:
The increase in ADHD diagnosis with age underscores the importance of monitoring children’s developmental needs as they progress through school and adolescence.
The survey revealed a notable difference in ADHD prevalence between genders, with 12.4% of males diagnosed compared to 6.6% of females—nearly a two-to-one gap. This aligns with previous research indicating that ADHD is more frequently diagnosed in boys than girls, though awareness of how ADHD presents differently across genders is growing.
Family income played a significant role in ADHD prevalence, particularly among lower-income groups:
This pattern suggests that socioeconomic factors might influence the diagnosis and management of ADHD, with lower-income families possibly experiencing greater barriers to early diagnosis or consistent treatment.
Geographic location also impacted ADHD rates. Prevalence was highest in the South (11.3%), followed by the Midwest (10%), the Northeast (9.1%), and significantly lower in the West (6.9%). These variations could reflect regional differences in healthcare access, diagnostic practices, or cultural attitudes towards ADHD.
Despite these variations in demographics, the overall prevalence of ADHD remained relatively stable across the study period from 2018 to 2021, showing no significant changes by year.
The findings from this updated analysis provide a clearer picture of ADHD’s prevalence across different demographic groups in the United States. They highlight the need for tailored approaches to diagnosis and care, taking into account factors like age, gender, income, and geographic location. With ADHD being a common condition affecting nearly 1 in 10 children, ongoing research and support for families are crucial to ensure that those with ADHD receive the care and resources they need.
This study reinforces the importance of awareness and early intervention, especially for families in underserved regions or those facing economic challenges. As clinicians and educators continue to support children with ADHD, understanding these demographic trends can help in creating more equitable access to diagnosis and treatment.
Qian Li, Yanmei Li, Juan Zheng, Xiaofang Yan, Jitian Huang, Yingxia Xu, Xia Zeng, Tianran Shen, Xiaohui Xing, Qingsong Chen, and Wenhan Yang, “Prevalence and trends of developmental disabilities among US children and adolescents aged 3 to 17 years, 2018–2021,” Scientific Reports (2023) 13: 17254, https://doi.org/10.1038/s41598-023-44472-1.
A transcontinental study team (California, Texas, Florida) used a nationally representative sample – the 2018 National Survey of Children’s Health – to query 26,205 caregivers of youth aged 3 to 17 years old to explore inequities in ADHD diagnosis.
With increasing accessibility of the internet in the U.S., more than 80% of adults now search for health information online. Recognizing that search engine data could help clarify patterns of inequity, the team also consulted Google Trends.
The team noted at the outset that “[d]ocumenting the true prevalence of ADHD remains challenging in light of problems of overdiagnosis (e.g., following quick screening rather than full evaluation incorporating multi-informant and multi-method data given limited resources) and underdiagnosis (e.g., reflecting inequities in healthcare and education systems).” Underdiagnosis is known to be influenced by lack or inadequacy of health insurance, inadequate public health funding, stigma, sociocultural expectations in some ethnic groups, and structural racism, among other factors.
After controlling for poverty status, highest education in household, child’s sex, and child’s age, the team reported that Black youth were a quarter (22%) less likely to receive ADHD diagnoses than their white peers. Latino/Hispanic youth were a third (32%) less likely and Asian youth three-quarters (73%) less likely to receive ADHD diagnoses than their white peers.
The team also found that state-level online search interest in ADHD was positively associated with ADHD diagnoses, after controlling for race/ethnicity, poverty status, highest education in household, child’s sex, and child’s age. However, the odds ratio was low (1.01), “suggesting the need for additional evaluation.” Furthermore, “There was no interaction between individual-level racial/ethnic background and state-level information-seeking patterns. … the state-level online information-seeking variation did not affect the odds that youth of color would have a current ADHD diagnosis over and above other included characteristics.”
That could be due in part to the gap in high-speed broadband access between Black and Hispanic in contrast to white populations, but that would not explain the even larger gaps in diagnosis for Asian youth, who tend to come from more prosperous backgrounds.
The team concluded, “Persistent racial/ethnic inequities warrant systematic changes in policy and clinical care that can attend to the needs of underserved communities. The digital divide adds complexity to persistent racial/ethnic and socioeconomic inequities in ADHD diagnosis …”
A cohort study looked at over five million adults, and over 850,000 children between the ages of five and eleven, who received care at Kaiser Permanente Northern California during the ten-year period from the beginning of 2007 through the end of 2016. At any given time, KPNC serves roughly four million persons. It is representative of the population of the region, except for the highest and lowest income strata.
Among adults rates of ADHD diagnosis rose from 0.43% to 0.96%. Among children the diagnosis rates rose from 2.96% to 3.74%, ending up almost four times as high as for adults.
Non-Hispanic whites had the highest adult rates throughout, increasing from 0.67% in 2007 to 1.42% in 2016. American Indian or Alaska Native (AIAN) had the second highest rates, rising from 0.56% to 1.14%. Blacks and Hispanics had roughly comparable rates of diagnosis, the former rising from 0.22% to 0.69%, the latter from 0.25% to 0.65%. The lowest rates were among Asians (rising from 0.11% to 0.35%) and Native Hawaiian or other Pacific Islanders (increasing from 0.11% to 0.39%).
Odds of diagnosis dropped steeply with age among adults. Relative to 18-24-year-olds, 25-34-year-olds were 1/6th less likely to be diagnosed with ADHD, 35-44-year-olds 1/3rd less likely, 45-54-year-olds less than half as likely, 55-64-year-olds less than a quarter as likely, and those over 65 about a twentieth as likely. This is consistent with other studies reporting and age dependent decline in the diagnosis.
Adults with the highest levels of education were twice as likely to be diagnosed as those with the lowest levels. But variations in median household income had almost no effect. Women were marginally less likely to be diagnosed than men.
ADHD is associated with some other psychiatric disorders. Compared with normally developing adults, and adjusted for confounders, those with ADHD were five times as likely to have an eating disorder, over four times as likely to be diagnosed with bipolar disorder or depression, more than twice as likely to suffer from anxiety, but only slightly more likely to abuse drugs or alcohol.
The authors speculate that rising rates of diagnosis could reflect increasing recognition of ADHD in adults by physicians and other clinicians as well as growing public awareness of ADHD during the decade under study. Turning to the strong differences among ethnicities, they note, Racial/ethnic differences could also reflect differential rates of treatment seeking or access to care. Racial/ethnic background is known to play an important role in opinions on mental health services, health care utilization, and physician preferences. In addition, rates of diagnosis- seeking to obtain stimulant medication for nonmedical use may be more common among white vs nonwhite patients. They conclude, greater consideration must be placed on cultural influences on health care seeking and delivery, along with an increased understanding of the various social, psychological, and biological differences among races/ethnicities as well as culturally sensitive approaches to identify and treat ADHD in the total population.
But the main take home message of this work is that most cases of ADHD in adults are not being diagnosed by clinicians. We know from population studies, worldwide, that about three percent of adults suffer from the disorder. This study found that less than 1 percent are diagnosed by their doctors. Clearly, more education is needed to teach clinicians how to identify, diagnose and treat ADHD in adults.
There is a well-documented gap between the known prevalence of adult ADHD and rates of diagnosis and treatment. In Germany, epidemiological studies of nationally representative community samples have found prevalence rates ranging from 3.1% to 4.7%. Yet, studies of publicly insured individuals aged 18 to 69 years old report rates of diagnosed ADHD between 0.04% and 0.4%. So, even in a country with universal health insurance, more than nine out of ten adults with ADHD go undiagnosed.
Many factors contribute to under-diagnosis: stigma, culturally influenced perceptions, and lack of motivation by those affected. Another crucial factor is the lack of recognition of ADHD symptoms by clinicians.
A research team surveyed 144 psychologists, 32 physicians, and two occupational therapists. Almost three in five participants were psychotherapists, a quarter were neuropsychologists, and one in seven were psychiatrists.
Four out of five clinicians stated they had received only a few hours of ADHD-specific training. One in four stated they had not examined guidelines for diagnosing ADHD. A lack of formal training among the vast majority, and unfamiliarity with current diagnostic guidelines in a significant minority, were surprising findings among clinicians who regularly work with adults with ADHD.
Many clinicians had difficulty identifying core features of adult ADHD as defined by the DSM-5 and International Classification of Diseases, Tenth Revision (ICD-10). Roughly one in five stated that hyperactivity had little relevance to adult ADHD. The only core feature correctly identified by more than half the respondents was having difficulties concentrating. Impairments in social behavior or aggression and memory impairment were not identified as being clearly relevant or irrelevant to adult ADHD.
The authors concluded that these findings appear to indicate some uncertainty or at least a lack of consensus among clinicians about what symptoms are relevant to ADHD in adulthood, and it is likely that this uncertainty contributes to diagnostic inaccuracy.
Most respondents reported using self-report scales of ADHD symptoms and using unstructured interviews. While slightly more than half agreed that collateral reports are important to diagnosis, only about a third reported regularly using them. This is a problem given the limited accuracy of self-reported childhood symptoms for documenting the childhood-onset of the disorder. Semi-structured interviews are also known to improve the accuracy of diagnosis, but are rarely used in clinical practice.
Over half of psychologists and a quarter of physicians reported using cognitive or neuropsychological testing, even though this is at variance with German (and other) guidelines, which specify that such testing is suitable for clarifying strengths and weaknesses, but not for ruling out or confirming a diagnosis of ADHD. The European Consensus Statement also states that cognitive/neuropsychological testing should only be used as a secondary or supplementary assessment tool.
While three out of four clinicians recommended stimulant drug treatment, psychologists tended to be more hesitant to do so. This is likely because German psychologists receive little training in pharmacotherapy, and do not have prescription privileges. Given the demonstrated efficacy of stimulant treatment, this points to a need to better educate psychologists in this regard.
Almost three in four respondents cited a lack of clinician knowledge and experience as a barrier to ADHD diagnosis. Most clinicians also stated they were either uncertain or only somewhat certain of their ability to diagnose ADHD. That suggests that more extensive ADHD-specific training is needed.
A limitation of the survey was the relatively low participation by physicians. It is also likely that the findings are not reflective of practices in ADHD specialty clinics.
The authors concluded, Further training is needed to improve clinicians' understanding of ADHD in adulthood and to align diagnostic practices with guideline recommendations. Whereas discrepancies between respondents regarding the relative importance of peripheral symptoms (e.g., memory problems) were most common, a lack of consensus was found even for core symptoms listed by diagnostic criteria. Particularly among psychologists improved awareness regarding the benefits of stimulant medications is needed to bring their treatment recommendations in line with evidence-based guidelines.
Stimulant medications, such as methylphenidate (Ritalin) and amphetamines (Adderall), are among the most widely prescribed drugs in the world. In the United States alone, prescription rates have climbed more than 50% over the past decade, driven largely by growing awareness of ADHD in both children and adults. Yet stimulants also have a long history of non-medical use, and concerns about their psychological risks persist among patients, families, and clinicians alike.
Two major studies now offer the clearest picture yet of what that risk actually looks like, and who it may affect.
The Background:
Before turning to the research, it helps to understand the landscape. A notable share of stimulant users misuse their medication: roughly one in four takes it in ways other than prescribed, and about one in eleven meets criteria for Prescription Stimulant Use Disorder (PSUD). Counterintuitively, most people with PSUD aren’t obtaining drugs illicitly — they’re misusing their own prescriptions.
This distinction between therapeutic and non-therapeutic use turns out to be critical when evaluating psychosis risk.
The Study:
A comprehensive meta-analysis by Jangra and colleagues pooled data across more than a dozen studies to compare psychotic outcomes in people using stimulants therapeutically versus non-therapeutically. The contrast was striking.
Among therapeutic users (more than 220,000 individuals taking stimulants at prescribed doses under medical supervision), psychotic episodes occurred in roughly one in five hundred people. When symptoms did appear, they typically emerged after prolonged treatment or in individuals with pre-existing psychiatric vulnerabilities, and they usually resolved when the medication was stopped.
Among non-therapeutic users (over 8,000 participants across twelve studies, many using methamphetamine or high-dose amphetamines), nearly one in three experienced psychotic symptoms. These episodes tended to be more severe, involving persecutory delusions and hallucinations, with faster onset and a greater likelihood of recurrence or persistence.
The biology underlying this difference is well understood. When stimulants are taken orally at guideline-recommended doses, they produce moderate, gradual changes in neurotransmitter activity central to attention and executive functions. The brain tolerates these changes relatively well. Non-therapeutic use, by contrast, often involves much higher doses that are frequently delivered through non-oral routes such as injection or smoking. This produces a rapid, excessive surge in dopamine activity, which is precisely the neurochemical pattern associated with psychotic symptoms.
The takeaway here is not that therapeutic stimulant use is risk-free, but that risk is strongly modulated by dose, route of administration, and individual psychiatric history. Clinicians are advised to monitor patients with pre-existing mood or psychotic disorders, particularly carefully.
A Nationwide Study Focuses on Methylphenidate Specifically:
Where the meta-analysis cast a wide net, a large-scale population study by Healy and colleagues drilled into a specific and clinically pressing question: does methylphenidate (the most commonly prescribed ADHD medication, also known as Ritalin) increase the risk of developing a psychotic disorder?
To find out, the researchers analyzed Finland's national health insurance database, tracking nearly 700,000 individuals diagnosed with ADHD. Finland's single-payer system made this kind of comprehensive, long-term tracking possible in a way that fragmented healthcare systems rarely allow.
Critically, the team adjusted for a range of confounding factors that have clouded previous research, including sex, parental education, parental history of psychosis, and the number of psychiatric visits and diagnoses prior to the ADHD diagnosis itself (a proxy for illness severity). After these adjustments, they found no significant difference in the risk of schizophrenia or non-affective psychosis between patients treated with methylphenidate and those who remained unmedicated. This held true even among patients with four or more years of continuous methylphenidate use.
The Take-Away:
When considered together, these studies offer meaningful reassurance without encouraging complacency.
For patients and families weighing ADHD treatment, the evidence suggests that methylphenidate used as prescribed does not increase psychosis risk, even over years of use. The rare cases of stimulant-associated psychosis in therapeutic settings are typically linked to high doses, pre-existing vulnerabilities, or both, and tend to resolve with discontinuation.
For clinicians, the findings reinforce the importance of baseline psychiatric assessment before initiating stimulant therapy, ongoing monitoring in patients with mood or psychotic disorder histories, and clear patient education about the risks of dose escalation or non-oral use.
The picture that emerges is one of a meaningful distinction between a medication used carefully within its therapeutic window and a drug misused outside of it. This distinction matters enormously when communicating risk to patients, policymakers, and the public.
ADHD is commonly treated with medication, but these treatments frequently cause side effects such as reduced appetite and disrupted sleep. Psychological and behavioral therapies exist as alternatives, but they tend to be expensive, hard to scale, and generally do little to address the motor difficulties that many children with ADHD experience — things like clumsy movement, poor handwriting, or difficulty with coordination.
Physical exercise has attracted attention as a more accessible option. But research findings have been mixed, partly because studies vary so widely in how exercise is delivered and what outcomes they measure. This meta-analysis, drawing on 21 studies involving 850 children and adolescents aged 5–20 with a clinical ADHD diagnosis, tries to cut through that noise.
Two types of motor skills
The researchers separated motor skills into two broad categories:
The Data:
Gross motor skills (16 studies, 613 participants)
Overall, exercise produced medium-to-large improvements in gross motor skills. The strongest gains were in:
No significant gains were found in balance or flexibility.
Fine motor skills (13 studies, 553 participants):
Exercise also produced medium-to-large improvements in fine motor skills, specifically:
The Results: What Kind of Exercise Works Best?
Two factors stood out consistently across both gross and fine motor skills: session length and frequency.
The type of exercise mattered; structured programs with clear motor-skill components (rather than unstructured physical activity) yielded stronger results.
These results are not without caveats, however. The authors urge caution in interpreting these findings. A few key limitations include:
The Bottom Line
This meta-analysis provides tentative moderate evidence that structured physical exercise can meaningfully support motor skill development in children and adolescents with ADHD — particularly when sessions run longer than 45 minutes and occur at least three times a week. The benefits appear most robust for object control, locomotion, handwriting, and manual dexterity.
That said, the evidence base still has real gaps. The authors call for better-designed, fully randomized controlled trials with consistent methods, standardized ways of measuring exercise intensity, and greater inclusion of children and adolescents who are not on medication — all of which would help clarify when, how, and for whom exercise works best.
Treatment guidelines for childhood ADHD recommend medications as the first-line treatment for most youth with ADHD. Still, concerns about side effects and long-term outcomes have increased interest in non-pharmacological approaches. Researchers at Saudi Arabian Armed Forces hospitals recently conducted a network meta-analysis comparing several interventions, including mindfulness-based therapy, cognitive behavioral therapy, behavioral parent training, neurofeedback, yoga, virtual reality programs, and digital working memory training.
Although the authors aimed to “provide a rigorous methodological approach to combine evidence from multiple treatment comparisons,” the study illustrates several pitfalls that arise when network meta-analysis is applied to a thin and heterogeneous evidence base.
What Network Meta-analysis Can and Cannot Do:
Network meta-analysis extends conventional meta-analysis by combining:
When the evidence network is large and well-connected, this approach can provide useful estimates of comparative effectiveness among many treatments.
This method is not always best, however, as many networks are sparse. This is especially true in areas such as complementary or behavioral therapies. In sparse networks, estimates rely heavily on indirect comparisons, and single studies can exert disproportionate influence over the results.
Conventional meta-analysis focuses on heterogeneity, meaning differences in results across studies within the same comparison.
Network meta-analysis must additionally evaluate consistency, whether the direct and indirect evidence agree.
However, when comparisons are supported by only one or two studies and the network is weakly connected, statistical tests for heterogeneity and consistency have very little power. In practice, this means the analysis often cannot detect problems even if they are present.
Sparse networks also make publication bias difficult to evaluate. This concern is particularly relevant in fields dominated by small trials and emerging therapies.
Why Such Treatment Rankings Are Appealing, but Potentially Problematic:
Many network meta-analyses summarize results using SUCRA, which estimates the probability that each treatment ranks best.
SUCRA, or Surface Under the Cumulative Ranking, is a key statistical metric in network meta-analyses. It is used to rank treatments by efficacy or safety. This is achieved by summarizing the probabilities of a treatment's rank into a single percentage, where a higher SUCRA value indicates a superior treatment. Ultimately, SUCRA helps pinpoint the most effective intervention among the ones compared.
Again, in well-supported networks, SUCRA can provide a useful summary of comparative effectiveness. But in sparse networks, rankings can create an illusion of precision, because treatments supported by a single small study may appear highly ranked simply due to random variation.
What Did this New Network Meta-analysis Study?
The study includes 16 trials with a total of 806 participants. But the structure of the evidence network is far weaker than this headline number suggests.
Based on the underlying studies:
This produces a very thin network, in which several interventions rely entirely on single studies.
Another challenge is that the included trials measure different outcomes. Some evaluate ADHD symptom severity, while others measure parental stress.
When studies use different outcome scales, meta-analysis typically relies on standardized measures such as the standardized mean difference to allow comparisons across studies. However, the analysis reports only mean-average differences, making it difficult to interpret the relative effect sizes.
Study Issues (including Limited Evidence and Risk of Bias):
The intervention supported by the largest number of studies (family mindfulness-based therapy) was one of the two approaches reported as producing statistically significant results. The other was BrainFit, which is supported by only a single previous trial.
Despite this limited evidence base, the study ranks interventions using SUCRA:
Notably, none of the runner-up interventions demonstrated statistically significant efficacy.
The authors acknowledge methodological limitations in the included studies:
“Blinding of participants and personnel (performance bias) exhibited notable concerns, as blinding for active treatment was not applicable in most studies.”
Such limitations are common in behavioral intervention trials, but they further increase uncertainty in already small evidence networks.
Conclusions:
The study ultimately concludes:
“This network meta-analysis supports MBT and BPT as effective non-pharmacological treatments for ADHD.”
However, the evidence underlying these claims is limited. Some analyses rely on very small numbers of studies and participants, and the network structure depends heavily on indirect comparisons.
Network meta-analysis can be a powerful tool when applied to a large, consistent, and well-connected body of evidence. When the evidence base is sparse, however, the resulting rankings and comparisons may appear statistically sophisticated while resting on a fragile evidentiary foundation.
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