Cookie Preferences
By clicking, you agree to store cookies on your device to enhance navigation, analyze usage, and support marketing. More Info
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
June 20, 2021
This research study investigates the consistency of medication adherence among adolescents and young adults diagnosed with ADHD. Conducted at Auburn University in Alabama, researchers recruited 54 college students to address this question. All had previously been diagnosed with ADHD. All lived independently, and all were taking prescribed ADHD medication. Students with severe comorbid psychiatric conditions were excluded. Three students dropped out, leaving a final sample size of 51.
The Study:
Each student completed a total of four half-hour assessments, scheduled at monthly intervals. At each first assessment, researchers counted the participant's ADHD medication pills and transferred them to an electronic monitoring bottle-a bottle with a microchip sensor in the cap that automatically tracks the date and time of every opening. This enabled them to compare students' subjective estimates at subsequent assessments with the objective evidence from pill counts and the data output from the electronic monitoring bottles.
The Results:
Overall, students reported missing about one in four (25 percent) of their prescribed doses. But the objective measures showed they were skipping closer to half their doses. According to pill counts, they were missing 40 percent of their doses, and according to the electronic monitoring bottles, 43 percent. The odds of obtaining such a result due to chance with a sample of size were less than one in a hundred (p < 0.01).
In other words, college students with ADHD significantly overestimate their adherence rates to their medications. The authors concluded, "without additional strategies in place, expecting adolescents and young adults with ADHD to remember a daily task that requires no more than a few seconds to accomplish, such as medication taking, is unrealistic. They suggest using smartphone reminder applications ("apps") and text messaging services.
Conclusion:
The authors point out that this study had a small sample size and that interpretations should be considered with caution. Moreover, the study was not randomized. Students responded to advertisements posted on campus, and thus self-selected. Pending the outcome of larger studies with randomization, the authors suggest that wherever possible, prescribing physicians adopt objective measures of medication adherence, as an aid in ensuring greater efficacy of treatment.
Megan R. Schaefer, Scott T. Wagoner, Margaret E. Young, Alana Resmini Rawlinson, Jan Kavookjian, Steven K. Shapiro, Wendy N. Gray, "SubjectiveVersus Objective Measures of Medication Adherence in Adolescents/Young Adults with Attention-Deficit Hyperactivity Disorder," Journal of Developmental& Behavioral Pediatrics, Published online July 11, 2018, DOI:10.1097/DBP.0000000000000602.
Raising children is not easy. I should know.
As a clinical psychologist, I've helped parents learn the skills they need to be better parents. And my experience raising three children confirmed my clinical experience.
Parenting is a tough job under the best of circumstances, but it is even harder if the parent has ADHD.
For example, an effective parent establishes rules and enforces them systematically. This requires attention to detail, self-control, and good organizational skills. Given these requirements, it is easy to see how ADHD symptoms interfere with parenting. These observations have led some of my colleagues to test the theory that treating ADHD adults with medication would improve their parenting skills. I know about two studies that tested this idea.
In 2008, Dr. Chronis-Toscano and colleagues published a study using a sustained-release form of methylphenidate for mothers with ADHD. As expected, the medication decreased their symptoms of inattention and hyperactivity/impulsivity. The medication also reduced the mother's use of inconsistent discipline and corporal punishment and improved their monitoring and supervision of their children.
In a 2014 study, Waxmonsky and colleagues observed ADHD adults and their children in a laboratory setting once when the adults were off medication and once when they were on medication. They used the same sustained-release form of amphetamine for all the patients. As expected, the medications reduced ADHD symptoms in the parents. This laboratory study is especially informative because the researchers made objective ratings of parent-child interactions, rather than relying on the parents' reports of those interactions. Twenty parents completed the study. The medication led to less negative talk and commands and more praise by parents. It also reduced negative and inappropriate behaviors in their children.
Both studies suggest that treating ADHD adults with medication will improve their parenting skills. That is good news. But they also found that not all parenting behaviors improved. That makes sense. Parenting is a skill that must be learned. Because ADHD interferes with learning, parents with the disorder need time to learn these skills. Medication can eliminate some of the worst behaviors, but doctors should also provide adjunct behavioral or cognitive-behavioral therapies that could help ADHD parents learn parenting skills and achieve their full potential as parents.
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 ..."
ADHD is a neurodevelopmental condition rooted in delayed or atypical maturation of the prefrontal cortex (the brain region that governs self-regulation). This maturational lag underlies the hallmark difficulties with attention, hyperactivity, and impulsivity, and also impairs what researchers call executive function: the cognitive toolkit we rely on for working memory, impulse control, mental flexibility, emotional regulation, and the ability to tolerate delays in reward.
The Background:
Standard treatments work through two main routes. Stimulant and non-stimulant medications are considered very safe and effective treatments, but are not without risk of side effects and are not appropriate for every ADHD patient. Behavioral and psychosocial interventions can improve self-regulation and social functioning, but they require sustained effort and produce variable results. These limitations have kept the search for better alternatives active.
One candidate that has drawn growing attention is transcranial direct current stimulation (tDCS). The technique is appealingly simple: a weak electrical current is applied to the scalp through small electrodes, modulating the excitability of neurons in the underlying cortex without requiring surgery, anesthesia, or significant discomfort. Its safety profile and ease of use have made it attractive to researchers.
The Study:
A newly published meta-analysis set out to give the technique its most rigorous test yet, pooling results from randomized controlled trials, including crossover designs, that compared active tDCS against sham stimulation in people with ADHD across all age groups.
The Results:
The findings were consistently null. Across seven trials enrolling 303 participants, tDCS produced no significant reduction in overall ADHD symptom severity compared with sham. Breaking symptoms into their components made no difference: neither hyperactivity/impulsivity nor inattention improved. Turning to executive function, 18 studies with 872 participants found no meaningful gain in inhibitory control, and 12 studies with 506 participants found the same for working memory. Smaller bodies of evidence, including three studies on cognitive flexibility (122 participants) and two on hot executive function, the motivational and emotional dimension of self-regulation (86 participants), similarly came up empty. Variation in outcomes across studies was small to moderate, and there was no evidence of publication bias skewing the picture.
The authors’ conclusion was succinct: tDCS was well tolerated but “did not demonstrate significant overall efficacy for core ADHD symptoms or executive functions.”
.png)
Disordered eating (a broad category of persistent, harmful patterns in eating or weight control) affects between 5% and 22% of children and adolescents worldwide, with similar rates seen in the United States. The consequences are far-reaching: these conditions are linked to bone fractures, anemia, malnutrition, dental erosion, obesity, diabetes, hypertension, and elevated cholesterol and triglycerides. They also carry one of the highest mortality rates of any psychiatric illness.
Eating disorders rarely occur in isolation. They frequently arise alongside other psychiatric and neurological conditions. Yet, until now, no large-scale study had examined these co-occurrences in a nationally representative U.S. sample. A new study addresses that gap, focusing on children and adolescents aged 6–17 and the conditions most commonly associated with disordered eating, including ADHD.
The Study:
Researchers drew on data from the 2022–2023 National Survey of Children's Health (NSCH), a nationally representative, cross-sectional survey covering all 50 states and Washington, D.C. Households were selected using stratified, address-based sampling, and parents or guardians completed surveys about one randomly selected child per household. The final sample included 68,000 children and adolescents.
Results:
After accounting for factors including sex, age, race and ethnicity, household income, educational attainment, insurance status, and household language, children and adolescents with ADHD were 2.6 times more likely to have some form of disordered eating compared to their typically developing peers.
The elevated risk appeared across a range of specific behaviors:
A greater tendency toward using diet pills, laxatives, or diuretics was also observed in the ADHD group, though this finding did not reach statistical significance.
The Take-Away:
These findings underscore a need to improve both prevention and treatment strategies for disordered eating, particularly in children and adolescents who have ADHD. Clinicians working with this population are advised to screen for a wide spectrum of disordered eating behaviors.
For centuries, we’ve called the eyes the "windows to the soul," but for modern neurologists, they are quite literally a window into the brain. The retina and the central nervous system share the same embryonic origins, developing from the same neural tissue in the womb. Because of this deep biological connection, the back of your eye acts as a non-invasive map of your brain's health, displaying a complex web of nerves and blood vessels that can (theoretically!) mirror certain neurodevelopmental conditions.
Recently, a buzz rippled through the mental health community when a study published in partnership with Seoul National University Bundang Hospital claimed a massive breakthrough. Researchers developed an Artificial Intelligence (AI) model that could screen children for Attention-Deficit/Hyperactivity Disorder (ADHD) using nothing more than a simple retinal photograph. The study, which prospectively recruited children from Severance Hospital and Eunpyeong St. Mary’s Hospital, produced results that were staggering: the AI reportedly achieved an accuracy rate of 96.9%!
In the world of medical testing, scientists use a metric called AUROC (Area Under the Receiver Operating Characteristic) to measure how well a test works.
An AUROC of 96.9% is a near-perfect score, suggesting a tool is ready for immediate, real-world deployment. While headlines promised a revolution in mental health screening, a deeper look into this research and the study’s design has exposed that this 96.9% AUROC was more likely evidence of a flawed methodology rather than a biological reality.
To build their screening tool, researchers analyzed over 1,100 retinal images using a digital pipeline called AutoMorph and a machine-learning model known as XGBoost. The AI was trained to hunt for physical signals of the "Dopamine Connection." Dopamine is the primary neurotransmitter involved in ADHD, but it is also essential to the eye. It regulates synaptic formation, retinal blood flow, and vascular endothelial regulation. Because dopamine dysregulation influences how blood vessels grow and remodel, the study hypothesized that an ADHD brain would leave a unique "fingerprint" on the retinal vasculature, resulting in denser, thicker vessel structures.
On paper, the logic was sound: use AI to spot the subtle vascular remodeling caused by dopaminergic shifts. But a closer look at the investigation revealed that the AI wasn't just spotting ADHD; it was over-indexing on technical noise.
The most significant "smoking gun" flagged by critics is a massive temporal mismatch. In other words, there was a severe disparity in the timeframes and conditions under which the retinal images for the two comparison groups were collected. For an AI to learn a biological condition, it must compare groups under identical technical conditions. Instead, this study created a time-traveling dataset:
A scientific study is only as reliable as its control group. The control in any experiment acts as a baseline against which the study group is compared. In this case, the control group should be composed of children without any neurodevelopmental disorders, or of “typically developing” children.
In this study, the control group wasn't composed of healthy children from the community. Instead, they were patients visiting a tertiary ophthalmology clinic. Children visiting a specialist eye hospital are rarely "typical." They are there because they have symptomatic eye issues. This introduced a massive selection bias involving three major confounders:
When training AI, you must never allow the "test questions" to leak into the "study material." The researchers, however, committed a fundamental violation of machine learning hygiene known as Eye-to-Eye Data Leakage. The study split the data by the eye rather than by the participant.
Human eyes are highly correlated; the left eye is a near-mirror of the right. If a child's left eye was used for training and their right eye was used for testing, the AI was effectively "cheating." Instead of learning the general traits of ADHD, the model was potentially memorizing individuals. This error artificially balloons accuracy metrics.
The true test of medical AI is diagnostic specificity, or differential diagnosis. This refers to the ability to tell one condition apart from another. While the model claimed 96.9% accuracy against a flawed control group, its performance collapsed when faced with real-world complexity.
When the researchers asked the AI to differentiate between ADHD and Autism Spectrum Disorder (ASD), the accuracy plummeted to a poor 63% AUROC. In real-world clinical settings, an accuracy of 63% is dangerously close to a 50% coin flip. Since ADHD frequently co-occurs with ASD, anxiety, or intellectual disabilities, an AI that cannot handle these "clinical differentials" is functionally useless in a doctor's office. The failure at this stage proves the model was likely detecting technical quirks of the dataset rather than a unique biological marker for ADHD.
To move from the lab to the clinic, we must establish a foundation built on rigor rather than high-speed data scraping. Moving forward, we must demand these 3 Pillars of Trusted Medical AI :
The dream of a quick eye scan to diagnose ADHD is not dead, but it must be rescued from "fast science" shortcuts and buzzy headlines.
_logo%201.svg)
