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Using Statistics New Zealand’s Integrated Data Infrastructure (IDI), a large database of linked de-identified administrative and survey data about people and households, a local study team examined a three-year birth cohort (mid-1992 through mid-1995) totaling 149,076 persons.
The team assessed the presence of ADHD within this cohort through diagnosis codes and inference from medication dispensing, where there was at least one code relating to an ADHD diagnosis in the medication datasets. This subgroup consisted of 3,975 persons.
Next, they related this information to criminal justice system interactions of increasing severity, starting with police proceedings, and continuing with court charges, court convictions, and incarcerations. These interactions were tracked during an eight-year period from participants’ 17th birthday through their 25th birthday.
In this same period the team also tracked types of offenses: against people; against property; against organizations, government, and community; and violent offenses.
In all cases, the study team adjusted for gender, ethnicity, deprivation, and area of residence as potential confounders.
With these adjustments, young adults with ADHD were over twice as likely as their typically developing peers to be proceeded against by police, to be charged with an offense, and to be convicted. They were almost five times as likely to be incarcerated.
With the same adjustments, young adults with ADHD were over twice as likely as their typically developing peers to be convicted of offenses against organizations, government, and community. They were almost three times as likely to be convicted of crimes against persons, and over three and a half times more likely to be convicted of either violent offenses or offenses against property.
The authors noted, “The greater effect size for incarceration observed in our study may be due to the lack of control for comorbid conditions such as CD [conduct disorder], which are known criminogenic risk factors.”
They also noted, “The sharp increase in the risk of incarceration observed may also signal differences in the NZ justice system’s approach to ADHD, which may be less responsive to the condition than other nations, particularly the steps in the justice system between conviction and sentence. This would suggest that the UNCRPD [United Nations Convention on the Rights of Persons with Disabilities] obligations of equal recognition before the law and the elimination of discrimination on the basis of disability are not being met for individuals with ADHD in NZ.”
They concluded, “Our findings revealed that not only were individuals with ADHD overrepresented at all stages of the CJS [criminal justice system] and offense types examined, there was also a pattern of increasing risk for CJS interactions as these individuals moved through the system. These results highlight the importance of early identification and responsivity to ADHD within the CJS and suggest that the NZ justice system may require changes to both of these areas to ensure that young individuals with ADHD receive equitable access to, and treatment within, the CJS.”
Francesca Anns, Stephanie D’Souza, Conrad MacCormick, Brigit Mirfin-Veitch, Betony Clasby, Nathan Hughes, Warren Forster, Eden Tuisaula, and Nicholas Bowden, “Risk of Criminal Justice System Interactions in Young Adults with Attention-Deficit/Hyperactivity Disorder: Findings From a National Birth Cohort,” Journal of Attention Disorders (2023), 1-11, https://doi.org/10.1177/10870547231177469.
Children with disabilities are known to be at heightened risk of violence compared to their non-disabled peers. To what extent does this hold true for ADHD?
Denmark has a single-payer health insurance system through which health data about virtually the entire population can be cross-referenced with population, crime, welfare, and other registers through unique individual person numbers.
A Danish study team accessed national registers to examine the relationship between ADHD and criminal victimhood among nine yearly birth cohorts totaling more than 570,000 children and adolescents.
Of these, 557,521, among them 12,040 with ADHD, were not reported as being exposed to violence, and 12,830, among which 1,179 with ADHD, were exposed to violence.
From the raw data, children and adolescents with ADHD were more than four times as likely to be exposed to violence than their typically developing peers.
The team then adjusted for other disabilities, family risk factors, gender, birth year, and ethnic background.
With these confounders out of the way, children and adolescents with ADHD remained more than twice as likely to be exposed to violence than their typically developing peers.
To place this outcome in further perspective:
Certain family risk factors further aggravated the odds:
Perhaps surprisingly, substance abuse by family members had no effect whatsoever after adjusting for confounders.
Child abuse includes any of the following inflicted on a minor under 18 years old: physical or emotional harm, sexual abuse, or neglect.
It is known to be associated with environmental factors such as poverty, parents or neighbors with a history of violence, and gender inequality.
Chronic mental disorders in minors are also associated with child abuse. To what extent, if any, might that be true of ADHD?
Taiwan has a single-payer national health insurance system that covers more than 99.6% of all residents, enabling nationwide population studies.
A local research team used data from almost two million Taiwanese in their country’s National Health Insurance Research Database (NHIRD) spanning 15 years (2000-2015) to carry out a matched-cohort study.
All diagnoses of ADHD were made by board-certified specialists such as psychiatrists, pediatricians, neurologists, or physiatrists with a specialty in child and adolescent development.
3,540 children and adolescents between 6 and 18 years old with a diagnosis of ADHD were matched on a one-to-three basis with 10,620 peers from the NHIRD without an ADHD diagnosis.
The team adjusted for age, gender, location of residence (Northern, Central, Southern, and Eastern Taiwan), urbanization level of residence, level of hospitals as medical centers, and monthly insured premium. They further adjusted for comorbid conditions: intellectual disability, autistic disorder/pervasive developmental disorder, conduct disorder (CD)/oppositional defiant disorder (ODD), other developmental disorders, childhood emotional disorder, Tourette syndrome/tics disorders, and involuntary urination and defecation.
Overall, children and adolescents with an ADHD diagnosis were 1.8 times as likely to be abused as those without an ADHD diagnosis.
Unmedicated children and adolescents with an ADHD diagnosis were three times more likely to be abused. ADHD medication cut that risk in half.
That held true whether the medication used was methylphenidate or atomoxetine. Methylphenidate appeared to be slightly more effective than atomoxetine, and the combination of methylphenidate and atomoxetine slightly more effective yet, but these differences were not statistically significant.
The team concluded, “The results support that pharmacotherapy may attenuate the risk of child abuse in ADHD patients.”
Taiwan's National Health Insurance program is a single-payer system that covers 99.6% of the island's 23 million residents. It includes family relationships.
This enabled a Taiwanese study team to examine the comorbidity of psychiatric disorders among close relatives in the entire population over eleven years, beginning at the start of 2001 and concluding at the end of2011.
For greater certainty of diagnosis, only persons twice diagnosed with the same psychiatric disorder were included as index individuals. There were 431,887 index patients, 152,443 of whom were ADHD index patients.
These index patients were then compared with all of their first-degree relatives (FDRs): parents, children, siblings, and twins. This produced 1,017,430 patient-FDR pairs, of which 401,301 were ADHD patient-FDR pairs.
Next, four controls were matched by age, gender, and type relative to each case, resulting in 4,069,720 control pairs.
After adjusting for age, gender, urbanization, and income level, ADHD patients were seven times more likely than controls to have first-degree relatives with ADHD. They were also seven times more likely to have FDRs with major depressive disorder, four times more likely to have FDRs with autism spectrum disorder, twice as likely to have FDRs with bipolar disorder, and 80%more likely to have FDRs with schizophrenia.
ADHD is one of the most common neurodevelopmental disorders in children, yet anyone familiar with this disorder, from clinicians and researchers to parents and patients, knows how differently it can manifest from one individual to the next. One person diagnosed with ADHD may primarily struggle with focus and staying on-task; another may find it nearly impossible to regulate their impulses or even start tasks; a third may frequently find themselves frozen with overwhelm and subject to emotional reactivity…
These are not just variations in severity; they may reflect genuinely different patterns of brain organization.
Our current diagnostic system groups all of these presentations under a single label (ADHD), with three behavioral subtypes (Hyperactive, Inattentive, and Combined) defined by symptom checklists. This framework has real clinical value of course, but it was built from behavioral observation rather than neurobiology, and may leave room for substantial heterogeneity to remain unexplained. In a new study, published in JAMA Psychiatry, researchers asked whether it’s possible to identify distinct neurobiologically subgroups within ADHD by analyzing patterns of brain structure, and whether those subgroups would map onto meaningful clinical differences.
How the Brain Was Analyzed
Researchers analyzed structural MRI scans from 446 children with ADHD and 708 typically-developing children across multiple research sites. From each scan, they constructed a morphometric similarity network; that is, a map of how different brain regions resemble one another in their structural properties. These networks reflect underlying biological organization, including shared patterns of cellular architecture and gene expression across brain regions.
From each individual's network, the research team calculated three properties that capture how each brain region functions within the broader network: how many connections it has, how efficiently it communicates with other regions, and how well it bridges different functional communities in the brain. Regions that score highly on these measures are sometimes called "hubs" and they play particularly influential roles in how information is integrated across the brain.
Rather than comparing the ADHD group to controls as a whole and looking for average differences, they used a normative modeling approach. This works similarly to a growth chart in pediatric medicine: instead of asking whether a child is above or below the group average, it asks how much a given child deviates from the expected range for their age and sex. This allows for individual variation across the ADHD group rather than flattening it into a single average profile.
The team then applied a data-driven clustering algorithm to these individual deviation profiles, allowing the data to reveal whether subgroups of children with ADHD shared similar patterns of brain network atypicality, without using any clinical symptom information to guide the clustering.
The Results:
Three stable, reproducible subtypes emerged from this analysis.
The first subtype was characterized by the most widespread differences from the normative range, particularly in regions connecting the medial prefrontal cortex to the pallidum (a deep brain structure involved in motivation and emotional regulation). Children in this group had the highest levels of both inattention and hyperactivity/impulsivity, and over a four-year follow-up period showed more persistent difficulties with emotional self-regulation than the other groups. They also had a higher rate of mood disorder comorbidity during follow-up, though this difference did not reach statistical significance given the sample size. The brain deviation patterns of this subtype showed correspondence with the spatial distributions of several neurotransmitter systems, including serotonin, dopamine, and acetylcholine, all of which have been previously implicated in ADHD pathophysiology.
The second subtype showed alterations concentrated in the anterior cingulate cortex and pallidum, a circuit involved in action control and response selection. This subtype had a predominantly hyperactive/impulsive profile, and its brain deviation patterns were associated with glutamate and cannabinoid receptor distributions.
The third subtype showed more focal differences in the superior frontal gyrus, a region involved in sustained attention. This subtype had a predominantly inattentive profile, with brain patterns linked to a specific serotonin receptor subtype.
A particularly important observation was that these brain-derived groupings aligned with clinically meaningful symptom differences, even though no symptom information was used in the clustering process. The fact that an analysis of brain structure alone arrived at groupings that correspond to recognizable clinical patterns is meaningful evidence that these subtypes reflect genuine neurobiological differences rather than statistical noise.
Replication in an Independent Sample
Scientific findings are only as trustworthy as their ability to replicate. The research team tested this clustering model in an entirely independent cohort of 554 children with ADHD from the Healthy Brain Network, a large, publicly available dataset collected under different conditions. The three subtypes were successfully identified in this new sample, with strong correlations between the brain deviation patterns observed in the original and validation cohorts. Differences in hyperactivity/impulsivity across subtypes were consistent with the discovery cohort, providing meaningful external validation of the approach.
What This Does and Doesn't Mean
It is important to be clear about what these findings do and do not imply. This study does not establish that these three subtypes are categorically distinct biological entities with sharp boundaries. They probably represent distinguishable regions along an underlying continuum of neurobiological variation. The neurochemical associations reported are exploratory and spatial in nature; they describe correspondences between brain deviation maps and neurotransmitter receptor density maps derived from separate imaging studies, and do not directly establish that any particular neurotransmitter system is altered in each subtype, nor do they currently inform treatment decisions.
The samples were not entirely medication-naive, and the strict comorbidity exclusion criteria may limit how well these findings generalize to typical clinical populations where comorbidities are the rule rather than the exception. All data came from research sites in the United States and China, and broader generalizability remains to be established.
What the study does demonstrate is that structured neurobiological heterogeneity exists within the ADHD diagnosis, that it can be reliably detected using brain imaging and data-driven methods, and that it aligns with meaningful clinical differences. The subtype defined by the most extensive brain network differences and the most severe, persistent clinical profile may be of particular importance, representing a group that could benefit most from early identification and targeted support.
The longer-term goal of this line of research is to move toward a more biologically grounded understanding of ADHD that complements existing diagnostic approaches and that may ultimately help guide more individualized treatment decisions. That goal, for now, remains a research ambition rather than a clinical reality, but this study takes a meaningful step in that direction.
Managing high blood pressure requires more than just getting a prescription; it means taking medication consistently, day after day, often for years. For people with ADHD, that kind of routine can be genuinely difficult. In our new study, published in BMC Medicine, we set out to understand just how much ADHD affects whether people stick with their blood pressure medication, and whether ADHD treatment itself might make a difference.
Why This Question Matters
Hypertension affects nearly a third of adults worldwide and is one of the leading drivers of heart disease and stroke. At the same time, ADHD, long thought of as a childhood disorder, affects around 2.5% of adults and is increasingly recognized as a risk factor for cardiovascular problems, including high blood pressure. Yet no large-scale study had ever examined whether having ADHD affects how well people follow through with their blood pressure treatment. We wanted to fill that gap.
What We Did
We analyzed health records from over 12 million adults across seven countries, Australia, Denmark, the Netherlands, Norway, Sweden, the UK, and the US, who had started antihypertensive (blood pressure-lowering) medication between 2010 and 2020. About 320,000 of them had ADHD. We tracked two things: whether they stopped their blood pressure medication entirely within five years, and whether they were taking it consistently enough (covering at least 80% of days) over one, two, and five years of follow-up.
What We Found
Across nearly all countries, adults with ADHD were more likely to stop their blood pressure medication and less likely to take it consistently. Overall, those with ADHD had about a 14% higher rate of discontinuing treatment within five years, and were 45% more likely to have poor adherence in the first year, a gap that widened to 64% by the five-year mark. These patterns were most pronounced in middle-aged and older adults.
Interestingly, young adults with ADHD were actually slightly less likely to discontinue treatment than their peers without ADHD, a finding we think may reflect the fact that younger people with ADHD are often more actively engaged with healthcare systems, especially given the cardiovascular monitoring that comes with ADHD medication use.
Perhaps the most encouraging finding was this: among people with ADHD who were also taking ADHD medication, adherence to blood pressure treatment was substantially better. Those on ADHD medication were about 38% less likely to have poor adherence at one year, and nearly 50% less likely at five years. While we can't establish causation from this type of study, one plausible explanation is that treating ADHD, reducing inattention and impulsivity, makes it easier to maintain the routines that consistent medication use requires. It's also possible that people on ADHD medication simply have more regular contact with healthcare providers, which keeps other health problems better monitored and managed.
What This Means in Practice
The core ADHD symptoms of inattention and poor organization are precisely the traits that make long-term medication adherence difficult. Add in the complexity of managing multiple disorders and medications, and it's easy to see why people with ADHD face extra challenges. Our findings suggest that clinicians treating adults with ADHD for cardiovascular disorders should be aware of these challenges and consider tailored support strategies, things like regular follow-up appointments, patient education, and tools that help with routine and organization.
There's also a broader message here about the potential ripple effects of treating ADHD well. Supporting someone in managing their ADHD may not just improve their attention and daily functioning; it may also help them take better care of their physical health, including disorders as serious as hypertension.
Future research should explore which specific support strategies are most effective, and whether these findings hold in lower- and middle-income countries where the data don't yet exist.
If you or someone you know has ADHD, you may be familiar with the challenge of staying on medication. Stimulants like methylphenidate (Ritalin) are the most common and effective treatment for ADHD, but a surprisingly large number of people stop taking them within the first year. In our new study, published in Translational Psychiatry, we sought to determine whether a person's genetic makeup plays a role in the development of the disorder.
What We Did
We analyzed data from over 18,000 people with ADHD in Denmark, all of whom had started stimulant medication. We tracked whether they stopped treatment within the first year, defined as going more than six months without filling a prescription. Nearly 4 in 10 (39%) had discontinued by that point. We then looked at their genetic data to see whether DNA differences could help explain who was more likely to stop.
What We Found
The short answer is: genetics does play a role, but it's modest. No single gene had a dramatic effect. Instead, we found that a collection of small genetic influences—distributed across the genome—contributed to the likelihood of stopping treatment early.
One of the most consistent findings was that people with a higher genetic predisposition for psychiatric disorders like schizophrenia, depression, or general mental health difficulties were more likely to discontinue their medication. This was true across all age groups. Interestingly, having a higher genetic risk for ADHD itself was not associated with stopping treatment, suggesting that the genetics of having ADHD and the genetics of staying on medication are quite different things.
We also found that the genetic picture looks different depending on age. In children under 16, body weight genetics (BMI) played a surprising role, children with a genetic tendency toward higher weight were actually less likely to stop, possibly because stimulant-related appetite suppression is less of a problem for them. In older adolescents and adults, higher genetic potential for educational attainment and IQ was linked to staying on treatment, possibly reflecting better access to information and healthcare support.
On the rare variant side, we found a tentative signal that people who stopped treatment had fewer disruptive variants in genes involved in dopamine, the brain chemical that stimulants work on. This might mean that those who continue on medication genuinely have more disruption in their dopamine system and benefit more from stimulant treatment.
What This Means
Our findings suggest that stopping ADHD medication early isn't simply a matter of willpower or forgetting to take a pill. Biology matters. A person's broader genetic vulnerabilities, particularly for other psychiatric disorders, may make it harder to stay on treatment, perhaps because of side effects, poor response, or the complexity of managing multiple mental health challenges at once.
We're still far from being able to use genetics to predict who will stop their medication, the effects we found are real but small, and much of the variation in treatment persistence remains unexplained. But this work is a step toward understanding the biological foundations of treatment challenges in ADHD, and hopefully toward more personalized approaches to care in the future.
Larger studies and research that can distinguish why people stop (side effects versus poor response versus practical barriers), will be the next steps.
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