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April 12, 2022
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.
The likelihood of being diagnosed with ADHD dropped sharply with age.
(When compared to 18-24-year-olds):
This matches findings from other studies showing that ADHD diagnoses become less common with age.
Other Factors:
Adults with ADHD were more likely to have other mental health conditions:
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 notable differences by ethnicity, 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 non-medical 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.”
The study highlights that many cases of adult ADHD go undiagnosed. Research shows about 3% of adults worldwide have ADHD, but this study found that less than 1% are diagnosed by doctors. This points to the need for better training for clinicians to recognize, diagnose, and treat ADHD in adults. It also emphasizes the importance of understanding cultural factors that affect how people seek and receive care.
Winston Chung, MD, MS; Sheng-Fang Jiang, MS; Diana Paksarian, MPH, PhD; Aki Nikolaidis, PhD; F. Xavier Castellanos, MD; Kathleen R. Merikangas, PhD; Michael P. Milham, MD, PhD, “Trends in the Prevalence and Incidence of Attention-Deficit/Hyperactivity Disorder Among Adults and Children of Different Racial and Ethnic Groups,” JAMA Network Open (2019) 2(11): e1914344. DOI:10.1521/adhd.2019.27.4.8.
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.
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 …”
Typically, clinicians rely on both subjective and objective observations, patient interviews and questionnaires, as well as reports from family and (in the case of children) parents and teachers, in order to diagnose ADHD.
A group of researchers are aiming to find a diagnostic test that is purely objective and utilizes recent technological advancements. The method they developed involves analyzing videos of children in outpatient settings, focusing on their movements. The study included 96 children, half of whom had ADHD and half who did not.
This new method could potentially provide a more objective way to diagnose ADHD, reducing the reliance on subjective observations and reports. It can help doctors make more accurate diagnoses, ensuring that those who need help get it and that those who don't aren't misdiagnosed.
Stimulant medications have long been considered the default first-line treatment for attention-deficit/hyperactivity disorder (ADHD). Clinical guidelines, prescribing practices, and public narratives all reinforce the idea that stimulants should be tried first, with non-stimulants reserved for cases where stimulants fail or are poorly tolerated.
I recently partnered with leading ADHD researcher Jeffrey Newcorn for a Nature Mental Health commentary on the subject. We argue that this hierarchy deserves reexamination. It is important to note that our position is not anti-stimulant. Rather, we call into question whether the evidence truly supports treating non-stimulants as secondary options, and we propose that both classes should be considered equal first-line treatments.
Stimulants have earned their reputation as the go-to drug of choice for ADHD. They are among the most effective medications in psychiatry, reliably reducing core ADHD symptoms and improving daily functioning when properly titrated and monitored. However, when stimulant and non-stimulant medications are compared more closely, the gap between them appears smaller than commonly assumed.
Meta-analyses often report slightly higher average response rates for stimulants, but head-to-head trials where patients are directly randomized to one medication versus another frequently find no statistically significant differences in symptom improvement or tolerability. Network meta-analyses similarly show that while some stimulant formulations have modest advantages, these differences are small and inconsistent, particularly in adults.
When translated into clinical terms, the advantage of stimulants becomes even more modest. Based on existing data, approximately eight patients would need to be treated with a stimulant rather than a non-stimulant for one additional person to experience a meaningful benefit. This corresponds to only a 56% probability that a given patient will respond better to a stimulant than to a non-stimulant. This difference is not what we would refer to as “clinically significant.”
One reason non-stimulants may appear less effective is the way efficacy is typically reported. Most comparisons rely on standardized mean differences, a method of averages that may mask heterogeneity of treatment effects. In reality, ADHD medications do not work uniformly across patients.
For example, evidence suggests that response to some non-stimulants, such as atomoxetine, is bimodal: this means that many patients respond extremely well, while others respond poorly, with few in between. When this happens, average effect sizes can obscure the fact that a substantial subgroup benefits just as much as they would from a stimulant. In other words, non-stimulants are not necessarily less effective across the board, but that they are simply different in who they help.
In our commentary, we also highlight structural issues in ADHD research. Stimulant trials are particularly vulnerable to unblinding, as their immediate and observable physiological effects can reveal treatment assignment, potentially inflating perceived efficacy. Non-stimulants, with slower onset and subtler effects, are less prone to this bias.
Additionally, many randomized trials exclude patients with common psychiatric comorbidities such as anxiety, depression, or substance-use disorders. Using co-diagnoses as exclusion criteria for clinical trials on ADHD medications is nonviable when considering the large number of ADHD patients who also have other diagnoses. Real-world data suggest that a large proportion of individuals with ADHD would not qualify for typical trials, limiting how well results generalize to everyday clinical practice.
Standard evaluations of medication tolerability focus on side effects experienced by patients, but this narrow lens misses broader societal consequences. Stimulants are Schedule II controlled substances, which introduces logistical barriers, regulatory burdens, supply vulnerabilities, and administrative strain for both patients and clinicians.
When used as directed, stimulant medications do not increase risk of substance-use disorders (and, in fact, tend to reduce these rates); however, as ADHD awareness has spread and stimulants are more widely prescribed, non-medical use of prescription stimulants has become more widespread, particularly among adolescents and young adults. Non-stimulants do not carry these risks.
Non-stimulants are not without drawbacks themselves, however. They typically take longer to work and have higher non-response rates, making them less suitable in situations where rapid results are essential. These limitations, however, do not justify relegating them to second-line status across the board.
This is a call for abandoning a one-size-fits-all approach. Instead, future guidelines should present stimulant and non-stimulant medications as equally valid starting points, clearly outlining trade-offs related to onset, efficacy, misuse risk, and practical burden.
The evidence already supports this shift. The remaining challenge is aligning clinical practice and policy with what the data, and patient-centered care, are increasingly telling us.
Today, most treatment guidelines recommend starting ADHD treatment with stimulant medications. These medicines often work quickly and can be very effective, but they do not help every child, and they can have bothersome side effects, such as appetite loss, sleep problems, or mood changes. Families also worry about long-term effects, the possibility of misuse or abuse, as well as the recent nationwide stimulant shortages. Non-stimulant medications are available, but they are usually used only after stimulants have not been effective.
This stimulant-first approach means that many patients who would respond well to a non-stimulant will end up on a stimulant medication anyway. This study addresses this issue by testing two different ways of starting medication treatment for school-age children with attention-deficit/hyperactivity disorder (ADHD). We want to know whether beginning with a non-stimulant medicine can work as well as the “stimulant-first” approach, which is currently used by most prescribers.
From this study, we hope to learn:
Our goal is to give families and clinicians clear, practical evidence to support a truly shared decision: “Given this specific child, should we start with a stimulant or a non-stimulant?”
Who will be in the study?
We will enroll about 1,000 children and adolescents, ages 6 to 16, who:
We will include children with common co-occurring conditions (such as anxiety, depression, learning or developmental disorders) so that the results reflect the “real-world” children seen in clinics, not just highly selected research volunteers.
How will the treatments be assigned?
This is a randomized comparative effectiveness trial, which means:
Parents and clinicians will know which type of medicine the child is taking, as in usual care. However, the experts who rate how much each child has improved using our main outcome measure will not be told which treatment strategy the child received. This helps keep their ratings unbiased.
What will participants be asked to do?
Each family will be followed for 12 months. We will collect information at:
At these times:
We will also track:
Data will be entered into a secure, HIPAA-compliant research database. Study staff at each site will work closely with families to make participation as convenient as possible, including offering flexible visit schedules and electronic options for completing forms when feasible.
How will we analyze the results?
Using standard statistical methods, we will:
All analyses will follow the “intention-to-treat” principle, meaning we compare children based on the strategy they were originally assigned to, even if their medication is later changed. This mirrors real-world decision-making: once you choose a starting strategy, what tends to happen over time?
Why is this study necessary now?
This study addresses a critical, timely gap in ADHD care:
In short, this study is needed now to move ADHD medication decisions beyond “one-size-fits-all.” By rigorously comparing stimulant-first and non-stimulant-first strategies in real-world settings, and by focusing on what matters most to children and families overall functioning, side effects, and long-term well-being, we aim to give patients, parents, and clinicians the information they need to choose the best starting treatment for each child.
This project was conceived by Professor Stephen V. Faraone, PhD (SUNY Upstate Medical University, Department of Psychiatry, Syracuse, NY) and Professor Jeffrey H. Newcorn, MD (Icahn School of Medicine at Mount Sinai, Department of Psychiatry, New York, NY). It will be conducted at nine sites across the USA.
EBI-ADHD:
If you live with ADHD, treat ADHD, or write about ADHD, you’ve probably run into the same problem: there’s a ton of research on treatments, but it’s scattered across hundreds of papers that don’t talk to each other. The EBI-ADHD website fixes that.
EBI-ADHD (Evidence-Based Interventions for ADHD) is a free, interactive platform that pulls together the best available research on how ADHD treatments work and how safe they are. It’s built for clinicians, people with ADHD and their families, and guideline developers who need clear, comparable information rather than a pile of PDFs. EBI-ADHD Database The site is powered by 200+ meta-analyses covering 50,000+ participants and more than 30 different interventions. These include medications, psychological therapies, brain-stimulation approaches, and lifestyle or “complementary” options.
The heart of the site is an interactive dashboard. You can:
The dashboard then shows an evidence matrix: a table where each cell is a specific treatment–outcome–time-point combination. Each cell tells you two things at a glance:
Clicking a cell opens more detail: effect sizes, the underlying meta-analysis, and how the certainty rating was decided.
EBI-ADHD is not just a curated list of papers. It’s built on a formal umbrella review of ADHD interventions, published in The BMJ in 2025. That review re-analyzed 221 meta-analyses using a standardized statistical pipeline and rating system.
The platform was co-created with 100+ clinicians and 100+ people with lived ADHD experience from around 30 countries and follows the broader U-REACH framework for turning complex evidence into accessible digital tools.
Why it Matters
ADHD is one of the most studied conditions in mental health, yet decisions in everyday practice are still often driven by habit, marketing, or selective reading of the literature. EBI-ADHD offers something different: a transparent, continuously updated map of what we actually know about ADHD treatments and how sure we are about it.
In short, it’s a tool to move conversations about ADHD care from “I heard this works” to “Here’s what the best current evidence shows, and let’s decide together what matters most for you.”
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