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August 15, 2024
A placebo is a pill that does not contain any active medication. It is given to patients who form the control group in clinical trials. Comparing the effects of a treatment with placebo is essential because some patients will improve with the passage of time and some will get better due to the expectation of benefit they have from being enrolled in a clinical trial.
In studies of psychiatric conditions, patients in placebo groups typically show improvement. This can be induced by combinations of hope, suggestion, expectation, and consumption of what are presented as medications. It is reinforced by the context of receiving compassionate care from others, with supportive conversations.
A 2005 study found that placebo response is unequally distributed across psychiatric disorders, but did not address several disorders (including bipolar disorder) examined in the present meta-analysis conducted by a German research team.
Using only high-quality randomized clinical trials (RCTs) across major psychiatric diagnoses, the team quantified differences in the change of disorder symptoms within placebo groups.
They selected nine common and clinically significant psychiatric conditions: major depressive disorder (MDD), mania (bipolar disorder), schizophrenia, obsessive-compulsive disorder (OCD), attention-deficit/hyperactivity disorder (ADHD), generalized anxiety disorder (GAD), panic disorder, posttraumatic stress disorder (PTSD), and social phobia. For each of these, they selected the ten most recent high-quality RCTs of medicationsfor meta-analysis.
Of the ninety included RCTs, the team only looked at placebo groups. Because RCTs for the different diagnoses used differing established psychopathology rating scales, standardized pre-post effect sizes were used to compare outcomes across diagnoses.
Meta-analysis of the ten ADHD RCTs with a combined total of 1,189 participants reported large effect size improvements in symptoms, with no variation (heterogeneity) across RCTs and no sign of publication bias.
By contrast, the placebo effect size improvements in symptoms of major depressive disorder (10 RCTs, 1,598 participants) and generalized anxiety disorder (10 RCTs, 1,457 participants) were very large, well above those for ADHD, and with no overlap of 95% confidence intervals.
At the other end of the spectrum, the placebo effect size improvements in symptoms of schizophrenia (10 RCTs, 888 participants) were moderate, well below those for ADHD, and with no overlap of 95% confidence intervals.
There were absolutely no indications of publication bias.
The team noted, “In all diagnoses, there were improvements in symptom severity during placebo treatment (ie, the lower limit of the 95% CIs of the pooled pre-post placebo effect sizes were >0).” Although they stated, “The large and robust improvements observed in ADHD studies have not been reported to our knowledge.” they seemed to have missed this article by me and my colleagues: https://pubmed.ncbi.nlm.nih.gov/34232582/.
They also concluded, “Comparing the courses of different disorders under placebo indirectly may assist in understanding disease etiology, possibly providing insights into the proportionate influence of organic and psychogenic factors. Conditions with presumed substantial hereditary and biological components, such as schizophrenia, exhibited modest placebo responses in our analysis. Conversely, disorders with potentially less biological contribution, eg, depression and GAD, showed stronger responses. Our study may serve as an initial framework for incorporating the comprehensive insights derived from placebo groups of controlled trials into the etiopathogenetic exploration of mental illnesses.”
Yanli Zhang-James, John W.S. Clay, Rachel B. Aber, Hilary M. Gamble, Stephen V. Faraone,
Post–COVID-19 Mental Health Distress in 13 Million Youth: A Retrospective Cohort Study of Electronic Health Records,
Journal of the American Academy of Child & Adolescen
Tom Bschor, Lea Nagel, Josephine Unger, Guido Schwarzer, and Christopher Baethge, “Differential Outcomes of Placebo Treatment Across 9 Psychiatric Disorders: A Systematic Review and Meta-Analysis,” JAMA Psychiatry (2024), https://doi.org/10.1001/jamapsychiatry.2024.0994.
Faraone, S. V., Newcorn, J. H., Cipriani, A., Brandeis, D., Kaiser, A., Hohmann, S., Haege, A. & Cortese, S. (2021). Placebo and nocebo responses in randomised, controlled trials of medications for ADHD: a systematic review and meta-analysis. Mol Psychiatry 27, 212-219.
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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