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August 29, 2025
The Background:
Randomized clinical trials have shown ADHD medications are effective in reducing core ADHD symptoms. Moreover, large observational studies indicate that these medications are associated with lower risks of real-world outcomes, including injuries, crime, transport crashes, suicide attempts, and unnatural-cause mortality.
Sweden’s ADHD medication use has soared. From 2006 to 2020, children’s use rose almost fivefold, and adults' use more than tenfold. This places Sweden among the highest globally in ADHD prescriptions.
Research indicates that rising prescription rates are due to changes in diagnostic criteria and their interpretation, parental perception, and greater awareness of ADHD, rather than an actual increase in its prevalence.
Sweden has a single-payer health insurance system that covers virtually its entire population, as well as a system of national registers that link health care records to other population databases.
The Study:
A research team based in Sweden used that data to explore how the impact of ADHD medication on self-harm, injuries, traffic crashes, and crime has evolved with the dramatic increase in ADHD prescription rates. The team hypothesized that effects would decrease as medications were prescribed to a broader group of patients, including those with fewer impairments and risky behaviors who might not derive as much benefit from pharmacotherapy.
The team identified all individuals aged 4 to 64 who were prescribed ADHD medication and living in Sweden in the fifteen years from 2006 through 2020. From this base cohort, they selected four specific cohorts for self-harm, unintentional injury, traffic crashes, and crime, consisting of individuals who experienced at least one relevant event during the study period.
They used a self-controlled case series (SCCS) design to explore the link between ADHD medication use and outcomes. This approach allows individuals to serve as their own controls, accounting for confounders like genetics, socioeconomic status, or other constant characteristics during follow-up.
A non-treatment period was defined as a gap of 30 days or more between two consecutive treatment periods. To examine the link between ADHD medication use and outcomes, the team divided follow-up time into consecutive periods for each individual. A new period began after a treatment switch. They estimated incidence rate ratios (IRRs) to compare the outcome event rates during medicated periods with non-medicated periods for the same individual.
The team examined how ADHD medication outcomes varied with prescription prevalence across three periods: 2006-2010, 2011-2015, and 2016-2020, during which ADHD medication use continuously increased.
The overall cohort encompassed almost a quarter million ADHD medication users: just over 57,000 for 2006-2010, just over 127,000 for 2011-2015, and slightly over 200,000 for 2016-2020.
The Results:
ADHD medication use was linked to significantly lower rates of all studied outcomes during the study period. However, as prescription rates increased five to tenfold in the population, the strongest association for reduction in self-harm was observed between 2006 to 2010 (23% reduction in incidence rate) and was slightly reduced (below 20%) in the two more recent periods, though this change was not statistically significant.
On the other hand, there was a significant decreasing trend in the reduction of incidence rate ratios for unintentional injury, with a 13% reduction in incidence rate in 2006-2010 decreasing over the two more recent periods to half that amount, 7%. For traffic crashes, a 29% reduction in incidence rate significantly diminished by more than half, to 13%. For crime, a 27% reduction in incidence rate from medication use significantly declined to 16%.
When considering methylphenidate prescriptions only, these effects were partially attenuated for crime. A 28% reduction in the incidence rate for crime in 2006-2010 dropped to 19% in the two most recent periods, but the trend was not statistically significant. Nevertheless, there were no significant differences from the results in the larger cohort in any of the other categories.
The Interpretation:
These outcomes were consistent with the team’s hypothesis. The researchers concluded, “While ADHD medications are consistently associated with reduced risk of serious real-world outcomes, the magnitude of these associations have decreased over time alongside rising prescription rates. This underscores the importance of continuously evaluating medication use in different patient populations.”
Lin Li, David Coghill, Arvid Sjölander, Honghui Yao, Le Zhang, Ralf Kuja-Halkola, Isabell Brikell, Paul Lichtenstein, Brian M. D’Onofrio, Henrik Larsson, and Zheng Chang, “Increased Prescribing of Attention-Deficit/Hyperactivity Disorder Medication and Real-World Outcomes Over Time,” JAMA Psychiatry (2025), https://doi.org/10.1001/jamapsychiatry.2025.1281.
With the growth of the Internet, we are flooded with information about attention deficit hyperactivity disorder from many sources, most of which aim to provide useful and compelling "facts" about the disorder. But, for the cautious reader, separating fact from opinion can be difficult when writers have not spelled out how they have come to decide that the information they present is factual.
My blog has several guidelines to reassure readers that the information they read about ADHD is up-to-date and dependable. They are as follows:
Nearly all the information presented is based on peer-reviewed publications in the scientific literature about ADHD. "Peer-reviewed" means that other scientists read the article and made suggestions for changes and approved that it was of sufficient quality for publication. I say "nearly all" because in some cases I've used books or other information published by colleagues who have a reputation for high-quality science.
When expressing certainty about putative facts, I am guided by the principles of evidence-based medicine, which recognizes that the degree to which we can be certain about the truth of scientific statements depends on several features of the scientific papers used to justify the statements, such as the number of studies available and the quality of the individual studies. For example, compare these two types of studies. One study gives drug X to 10 ADHD patients and reported that 7 improved. Another gave drug Y to 100 patients and a placebo to 100 other patients and used statistics to show that the rate of improvement was significantly greater in the drug-treated group. The second study is much better and much larger, so we should be more confident in its conclusions. The rules of evidence are fairly complex and can be viewed at the Oxford Center for Evidenced Based Medicine (OCEBM;http://www.cebm.net/).
The evidenced-based approach incorporates two types of information: a) the quality of the evidence and b) the magnitude of the treatment effect. The OCEBM levels of evidence quality are defined as follows (higher numbers are better:
Non-randomized, controlled studies. In these studies, the treatment group is compared to a group that receives a placebo treatment, which is a fake treatment not expected to work.
It is possible to have high-quality evidence proving that a treatment works but the treatment might not work very well. So it is important to consider the magnitude of the treatment effect, also called the "effect size" by statisticians. For ADHD, it is easiest to think about ranking treatments on a ten-point scale. The stimulant medications have a quality rating of 5 and also have the strongest magnitude of effect, about 9 or 10.Omega-3 fatty acid supplementation 'works' with a quality rating of 5, but the score for the magnitude of the effect is only 2, so it doesn't work very well. We have to take into account patient or parent preferences, comorbid conditions, prior response to treatment, and other issues when choosing a treatment for a specific patient, but we can only use an evidence-based approach when deciding which treatments are well-supported as helpful for a disorder.
A Chinese research team performed two types of meta-analyses to compare the risk of suicide for ADHD patients taking ADHD medication as opposed to those not taking medication.
The first type of meta-analysis combined six large population studies with a total of over 4.7 million participants. These were located on three continents - Europe, Asia, and North America - and more specifically Sweden, England, Taiwan, and the United States.
The risk of suicide among those taking medication was found to be about a quarter less than for unmediated individuals, though the results were barely significant at the 95 percent confidence level (p = 0.49, just a sliver below the p = 0.5 cutoff point). There were no significant differences between males and females, except that looking only at males or females reduced sample size and made results non-significant.
Differentiating between patients receiving stimulant and non-stimulant medications produced divergent outcomes. A meta-analysis of four population studies covering almost 900,000 individuals found stimulant medications to be associated with a 28 percent reduced risk of suicide. On the other hand, a meta-analysis of three studies with over 62,000 individuals found no significant difference in suicide risk for non-stimulant medications. The benefit, therefore, seems limited to stimulant medication.
The second type of meta-analysis combined three within-individual studies with over 3.9 million persons in the United States, China, and Sweden. The risk of suicide among those taking medication was found to be almost a third less than for unmediated individuals, though the results were again barely significant at the 95 percent confidence level (p =0.49, just a sliver below the p = 0.5 cutoff point). Once again, there were no significant differences between males and females, except that looking only at males or females reduced the sample size and made results non-significant.
Differentiating between patients receiving stimulant and non-stimulant medications once again produced divergent outcomes. Meta-analysis of the same three studies found a 25 percent reduced risk of suicide among those taking stimulant medications. But as in the population studies, a meta-analysis of two studies with over 3.9 million persons found no reduction in risk among those taking non-stimulant medications.
A further meta-analysis of two studies with 3.9 million persons found no reduction in suicide risk among persons taking ADHD medications for 90 days or less, "revealing the importance of duration and adherence to medication in all individuals prescribed stimulants for ADHD."
The authors concluded, "exposure to non-stimulants is not associated with a higher risk of suicide attempts. However, a lower risk of suicide attempts was observed for stimulant drugs. However, the results must be interpreted with caution due to the evidence of heterogeneity ..."
Noting that “the association between adult ADHD and dementia risk remains a topic of interest because of inconsistent results,” an Israeli study team tracked 109,218 members of a nonprofit Israeli health maintenance organization born between 1933 and 1952 who entered the cohort on January 1, 2003, without an ADHD or dementia diagnosis and were followed up to February 28, 2020.
Israeli law forbids nonprofit HMOs from turning anyone away based on demographic factors, health conditions, or medication needs, thereby limiting sample selection bias.
The estimated prevalence of dementia in this HMO, as diagnosed by geriatricians, neurologists, or psychiatrists, is 6.6%. This closely matches estimates in Western Europe (6.9%) and the United States (6.5%).
The team considered, and adjusted for, numerous covariates: age, sex, socioeconomic status, smoking, depression, obesity, chronic obstructive pulmonary disease, hypertension, atrial fibrillation, heart failure, ischemic heart disease, cerebrovascular disease, diabetes, Parkinson’s disease, traumatic brain injury, migraine, mild cognitive impairment, psychostimulants.
With these adjustments, individuals diagnosed with ADHD were almost three times as likely to be subsequently diagnosed with dementia as those without ADHD. Men with ADHD were two and a half times more likely to be diagnosed with dementia, whereas women with ADHD were over three times more likely, than non-ADHD peers.
More concerning still, persons with ADHD were 5.5 times more likely to be subsequently diagnosed with early onset dementia, as opposed to 2.4 times more likely to be diagnosed with late onset dementia.
On the other hand, the team found no significant difference in rates of dementia between individuals with ADHD who were being treated with stimulant medications and individuals without ADHD. Those with untreated ADHD had three times the rate of dementia. The team nevertheless cautioned, “Due to the underdiagnosis of dementia as well as bidirectional misdiagnosis, this association requires further study before causal inference is plausible.”
Conclusions and Relevance:
This study reinforces existing evidence that adult ADHD is associated with an increased risk of dementia. Notably, the increased risk was not observed in individuals receiving psychostimulant medication, however the mechanism behind this association is not clear.
These findings underscore the importance of reliable ADHD assessment and management in adulthood. They also highlight the need for further study into the link between stimulant medications and the decreased risk of dementia.
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A recent Wall Street Journal article raised alarms by concluding that many children who start medication for ADHD will later end up on several psychiatric drugs. It’s an emotional topic that will make many parents, teachers, and even doctors worry: “Are we putting kids on a conveyor belt of medications?”
The article seeks to shine a light on the use of more than one psychiatric medication for children with ADHD. My biggest worry about the article is that it presents itself as a scientific study because they analyzed a database. It is not a scientific study. It is a journalistic investigation that does not meet the standards of a scientific report..
The WJS brings attention to several issues that parents and prescribers should think about. It documents that some kids with ADHD are on more than one psychiatric medication, and some are receiving drugs like antipsychotics, which have serious side effects. Is that appropriate? Access to good therapy, careful evaluation, and follow-up care can be lacking, especially for low-income families. Can that be improved? On that level, the article is doing something valuable: it’s shining a spotlight on potential problems.
It is, of course, fine for a journalist to raise questions, but it is not OK for them to pretend that they’ve done a scientific investigation that proves anything. Journalism pretending to be science is both bad science and bad journalism.
Journalism vs. Science: Why Peer Review Matters
Journalists can get big datasets, hire data journalists, and present numbers that look scientific. But consider the differences between Journalism and Science. These types of articles are usually checked by editors and fact-checkers. Their main goals are:
Is this fact basically correct?
Are we being fair?
Are we avoiding legal problems?
But editors are not qualified to evaluate scientific data analysis methods. Scientific reports are evaluated by experts who are not part of the project. They ask tough questions like:
Exactly how did you define ADHD?
How did you handle missing data?
Did you address confounding?
Did you confuse correlation with causation?
If the authors of the study cannot address these and other technical issues, the paper is rejected.
The WSJ article has the veneer of science but lacks its methodology.
Correlation vs. Causation: A Classic Trap
The article’s storyline goes something like this: A kid starts ADHD medication. She has additional problems or side effects caused by the ADHD medications. Because of that, the prescriber adds more drugs. That leads to the patient being put on several drugs. Although it is true that some ADHD youth are on multiple drugs, the WSJ is wrong to conclude that the medications for ADHD cause this to occur. That simply confuses correlation with causation, which only the most naïve scientist would do.
In science, this problem is called confounding. It means other factors (like how severe or complex a child’s condition is) explain the results, not just the thing we’re focused on (medication for ADHD).
The WSJ analyzed a database of prescriptions. They did not survey the prescribers who made the prescriptions of the patients who received them. So they cannot conclude that ADHD medication caused the later prescriptions, or that the later medications were unnecessary or inappropriate.
Other explanations are very likely. It has been well documented that youth with ADHD are at high risk for developing other disorders such as anxiety, depression, and substance use. The kids in the WSJ database might have developed these disorders and needed several medications. A peer-reviewed article in a scientific journal would be expected to adjust for other diagnoses. If that is not possible, as it is in the case of the WSJ’s database, a journal would not allow the author to make strong conclusions about cause-and-effect.
Powerful Stories Don’t Always Mean Typical Stories
The article includes emotional accounts of children who seemed harmed by being put on multiple psychiatric drugs. Strong, emotional stories can make rare events feel common. They also frighten parents and patients, which might lead some to decline appropriate care.
These stories matter. They remind us that each data point is a real person. But these stories are the weakest form of data. They can raise important questions and lead scientists to design definitive studies, but we cannot use them to draw conclusions about the experiences of other patients. These stories serve as a warning about the importance of finding a qualified provider, not as against the use of multiple medications. That decision should be made by the parent or adult patient based on an informed discussion with the prescriber.
Many children and adults with ADHD benefit from multiple medications. The WSJ does not tell those stories, which creates an unbalanced and misleading presentation.
Newspapers frequently publish stories that send the message: “Beware! Doctors are practicing medicine in a way that will harm you and your family.” They then use case studies to prove their point. The title of the article is, itself, emotional clickbait designed to get more readers and advertising revenue. Don’t be confused by such journalistic trickery.
What Should We Conclude?
Here’s a balanced way to read the article. It is true that some patients are prescribed more than one medication for mental health problems. But the article does not tell us whether this prescribing practice is or is not warranted for most patients. I agree that the use of antipsychotic medications needs careful justification and close monitoring. I also agree that patients on multiple medications should be monitored closely to see if some of the medications can be eliminated. Many prescribers do exactly that, but the WSJ did not tell their stories.
It is not appropriate to conclude that ADHD medications typically cause combined pharmacotherapy or to suggest that combined pharmacotherapy is usually bad. The data presented by the WSJ does not adequately address these concerns. It does not prove that medications for ADHD cause dangerous medication cascades.
We have to remember that even when a journalist analyzes data, that is not the same as a peer-reviewed scientific study. Journalism pretending to be science is both bad science and bad journalism.
Oppositional Defiant Disorder (ODD)—a pattern of chronic irritability, anger, arguing, or defiance—is one of the most challenging behavioral conditions families and clinicians face.
A new study involving 2,400 children ages 3–17 offers one of the clearest pictures yet. Using parent-reported data from the Pediatric Behavior Scale, researchers compared how often ODD appears in Autism spectrum disorder (ASD), ADHD-Combined presentation (ADHD-C), ADHD-Inattentive presentation (ADHD-I), and those with both ASD and ADHD.
Results:
Children with ADHD-Combined presentation show both hyperactivity/impulsivity and inattention. They had the highest ODD rates of any single diagnosis: 53% of kids with ADHD-Combined met criteria for ODD.
But when autism was added to ADHD-Combined, the prevalence jumped to 62%. This group also had the highest overall ODD scores, suggesting more severe or more impairing symptoms.
This synergy matters: while autism alone increases ODD risk, the presence of ADHD-Combined is what pushes prevalence into the majority range. Other groups showed lower, but still significant, rates of ODD:
These findings echo what clinicians often see: children with inattentive ADHD, while struggling significantly with attention and learning, tend to show fewer behavioral conflict patterns than those with hyperactive/impulsive symptoms.
It is important to note that ODD is considered to have two main components. Across all diagnostic groups, ODD consistently broke down into these two components: either Irritable/Angry (emotion-based) or Oppositional/Defiant (behavior-based). But the balance between these components differed depending on diagnosis. Notably, Autism + ADHD-Combined showed higher levels of the irritable/angry component than ADHD-Combined alone. The oppositional/defiant component did not differ much between groups. This suggests that autism elevates the emotional side of ODD more than the behavioral side, which is important for clinicians to note before tailoring interventions.
The study notes that autism, ADHD, and ODD often cluster together, with 55–90% comorbidity in some combinations.
As the authors explain, “The high co-occurrence of ADHD-Combined in autism (80% in our study) largely explains the high prevalence of ODD in autism.”
Clinical Implications: Why This Study Matters
The researchers point to a straightforward recommendation: clinicians shouldn’t evaluate these conditions in isolation. A child referred for autism concerns might also be struggling with ADHD. A child referred for ADHD might have undiagnosed ODD. And ignoring one disorder can undermine treatment for the others.
Evidence-based interventions (behavioral therapy, parent training, school supports, and/or medication) can reduce symptoms across all three diagnoses while improving long-term outcomes, including overall quality of life.
Background:
Sleep is more than simple rest. When discussing sleep, we tend to focus on the quantity rather than the quality, how many hours of sleep we get versus the quality or depth of sleep. Duration is an important part of the picture, but understanding the stages of sleep and how certain mental health disorders affect those stages is a crucial part of the discussion.
Sleep is an active mental process where the brain goes through distinct phases of complex electrical rhythms. These phases can be broken down into non-rapid eye movement (NREM) and rapid eye movement (REM). The non-rapid eye movement phase consists of three stages of the four stages of sleep, referred to as N1, N2(light sleep), and N3(deep sleep). N4 is the REM phase, during which time vivid dreaming typically occurs.
Two of the most important measurable brain rhythms occur during non-rapid eye movement (NREM) sleep. These electrical rhythms are referred to as slow waves and sleep spindles. Slow waves reflect deep, restorative sleep, while spindles are brief bursts of brain activity that support memory and learning.
The Study:
A new research review has compiled data on how these sleep oscillations differ across psychiatric conditions. The findings suggest that subtle changes in nightly brain rhythms may hold important clues about a range of disorders, from ADHD to schizophrenia.
The Results:
People with ADHD showed increased slow-spindle activity, meaning those brief bursts of NREM activity were more frequent or stronger than in people without ADHD. Why this happens isn’t fully understood, but it may reflect differences in how the ADHD brain organizes information during sleep. Evidence for slow-wave abnormalities was mixed, suggesting that deep sleep disruption is not a consistent hallmark of ADHD.
Among individuals with autism spectrum disorder (ASD), results were less consistent. However, some studies pointed to lower “spindle chirp” (the subtle shift in spindle frequency over time) and reduced slow-wave amplitude. Lower amplitude suggests that the brain’s deep-sleep signals may be weaker or less synchronized. Researchers are still working to understand how these patterns relate to sensory processing, learning differences, or daytime behavior.
People with depression tended to show reduced slow-wave activity and fewer or weaker sleep spindles, but this pattern appeared most strongly in patients taking antidepressant medications. Since antidepressants can influence sleep architecture, researchers are careful not to overinterpret the changes. Nevertheless, these changes raise interesting questions about how both depression and its treatments shape the sleeping brain.
In post-traumatic stress disorder (PTSD), the trend moved in the opposite direction. Patients showed higher spindle frequency and activity, and these changes were linked to symptom severity which suggests that the brain may be “overactive” during sleep in ways that relate to hyperarousal or intrusive memories. This strengthens the idea that sleep physiology plays a role in how traumatic memories are processed.
The clearest and most reliable findings emerged in psychotic disorders, including schizophrenia. Across multiple studies, individuals showed: Lower spindle density (fewer spindles overall), reduced spindle amplitude and duration, correlations with symptom severity, and cognitive deficits.
Lower slow-wave activity also appeared, especially in the early phases of illness. These results echo earlier research suggesting that sleep spindles, which are generated by thalamocortical circuits, might offer a window into the neural disruptions that underlie psychosis.
The Take-Away:
The review concludes with a key message: While sleep disturbances are clearly present across psychiatric conditions, the field needs larger, better-standardized, and more longitudinal studies. With more consistent methods and longer follow-ups, researchers may be able to determine whether these oscillations can serve as reliable biomarkers or future treatment targets.
For now, the take-home message is that the effects of these mental health disorders on sleep are real and measurable.
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