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July 12, 2021
An international team of researchers recently published a meta-analysis of randomized controlled trials examining the efficacy of meditation-based therapies. Thirteen randomized controlled clinical trials(RCTs) were included: seven, with 270 participants, focused on children and adolescents; the other six, with 339 participants, were on adults. Because only one of the RCTs was appropriately blinded, the results discussed below, although promising, must be considered preliminary.
Among children and adolescents, the meta-analysis revealed a significant, medium effect size (SMD = -0.44, 95% CI -0.69 to -0.19)on ADHD symptoms for meditation therapy versus no treatment. There were virtually no heterogeneity among studies and no sign of publication bias. Improvements in inattention and hyperactivity/impulsivity had similar effect sizes. Neuropsychological measures of inhibition and attention indicated small-to-medium effect sizes but failed to achieve statistical significance, perhaps due to the small numbers of trials and participants (159 and 179, respectively).
For adults, the significant effect size on ADHD symptoms was medium-to-large (SMD = -.66, 95% CI -1.21 to -0.11). Once again, there was little sign of publication bias. But in this case, there was great heterogeneity among the studies. Improvements in inattention and hyperactivity/impulsivity were again comparable, although they fell just short of statistical significance for the latter. Neuropsychological measures of the efficacy of medication therapy produced statistically significant medium effect sizes for inhibition (SMD = -0.54) and working memory (SMD = - 0.42), with virtually no heterogeneity or sign of publication bias.
Although these results are promising, the authors of the meta-analysis concluded, "Despite statistically significant effects on ADHD combined core symptoms, due to paucity of RCTs, heterogeneity across studies, and lack of studies at low risk of bias, there is insufficient methodologically sound evidence to support meditation-based therapies for ADHD."
Junhua Zhang, Amparo DiÌaz-RomaÌn, Samuele Cortese, "Meditation-based therapies for attention-deficit/hyperactivity disorder in children, adolescents and adults: a systematic review and meta-analysis," Evidence-Based MentalHealth, Published Online First: 10 July 2018. doi:10.1136/elemental-2018-300015(2018).
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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