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April 27, 2021
ADHD is a serious disorder that requires treatment to prevent many adverse outcomes. But, because the diagnosis of ADHD is based on how the patient responds to questions, people can pretend that they have ADHD when they do not. If you Google "fake ADHD" you'll get many pages of links, including a Psychology Today article on the topic and bloggers describing how they were able to fool doctors into giving them ADHD medications. Is fake ADHD a serious problem? Not really. The Internetseems to be faking an epidemic of fake ADHD.I say that because we have decades of research that show many objective measures of abnormality and impairment in people who say they have ADHD. These include traffic accidents, abnormalities in brain imaging, and molecular genetic differences. Some studies even suggest that ADHD adults downplay their ADHD symptoms. For example, one study diagnosed ADHD in children and then contacted them many years later when they were young adults.When they were interviewed as young adults, their responses to questions about ADHD suggested that they did not have the disorder. But when the same questions about the patient were asked to someone who lived with the patient as a young adult, it was clear that they still had ADHD. So rather than faking ADHD, many ADHD adults do not recognize that they have symptoms of the disorder. That said, we also know from research studies that, when asked to pretend that they have ADHD, adults can fake the disorder. That means that they can learn about the symptoms of the disorder and makeup examples of how they have had them when they have not. The research discussed above suggests that this is not common, but we do know that some people have motives for faking ADHD.For example, some college students seek special accommodations for taking tests; others may want stimulants for abuse, misuse, or diversion. Fortunately, doctors can detect fake ADHD in several ways. If an adult itself-referred for ADHD and asks specifically for stimulant medication, that raises the possibility of fake ADHD and drug-seeking. Because the issue of stimulant misuse has been mostly a concern on college campuses, many doctors treating college students will require independent verification of the patient's ADHD symptoms by speaking with a parent, even over the phone if an in-person visit is not possible. Using ADHD rating scales will not detect fake ADHD, and it is easy to fake poor performance on tests of reading or math ability. Neuropsychological tests can sometimes be used to detect malingering, but require referral to a specialist. Researchers are developing methods to detect faking ADHD symptoms. These have shown some utility in studies of young adults, but are not ready for clinical practice. So, currently, doctors concerned about fake ADHD should look for objective indicators of impairment (e.g., documented traffic accidents; academic performance below expectation) and speak to a parent of the patient to document that impairing symptoms of the disorder were present before the age of twelve. Because the issue of fake ADHD is of most concern on college campuses, it can also be helpful to speak with a teacher who has had frequent contact with the patient. In an era of large lecture halls and broadcast lectures, that may be difficult. And don't be fooled by the Internet. We don't want to deny treatment to ADHD patients out of undocumented reports of an epidemic of fake ADHD.
Harrison, A. G., Edwards, M. J. & Parker, K. C. (2007).Identifying students faking ADHD: Preliminary findings and strategies fordetection. Arch Clin Neuropsychol 22, 577-88.
Sansone, R. A. & Sansone, L. A. (2011). Faking attentiondeficit hyperactivity disorder. Innov Clin Neurosci 8, 10-3
Loughan, A., Perna, R., Le, J. & Hertza, J. (2014). C-88Abbreviatingthe Test of Memory Malingering: TOMM Trial 1 in Children with ADHD. Arch ClinNeuropsychol 29, 605-6.
Loughan, A. R. & Perna, R. (2014). Performance andspecificity rates in the Test of Memory Malingering: an investigation intopediatric clinical populations. Appl Neuropsychol Child 3, 26-30.
Quinn, C. A. (2003). Detection of malingering in the assessmentof adult ADHD. Arch Clin Neuropsychol 18, 379-95.
Suhr, J., Hammers, D., Dobbins-Buckland, K., Zimak, E. &Hughes, C. (2008). The relationship of malingering test failure toself-reported symptoms and neuropsychological findings in adults referred forADHD evaluation. Arch Clin Neuropsychol 23, 521-30.
Greve, K. W. & Bianchini, K. J. (2002). Using theWisconsin card sorting test to detect malingering: an analysis of thespecificity of two methods in non malingering normal and patient samples. J ClinExp Neuropsychol 24, 48-54.
Killgore, W. D. & Della Pietra, L. (2000). Using theWMS-III to detect malingering: empirical validation of the rarely missed index(RMI). J Clin Exp Neuropsychol 22, 761-71.
Ord, J. S., Greve, K. W. & Bianchini, K. J. (2008).Using the Wechsler Memory Scale-III to detect malingering in mild traumaticbrain injury. Clin Neuropsychol 22, 689-704.
Wisdom, N. M., Callahan, J. L. & Shaw, T. G.(2010). Diagnostic utility of the structured inventory of malingeredsymptomatology to detect malingering in a forensic sample. Arch ClinNeuropsychol 25, 118-25.
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The Background:
Women with polycystic ovary syndrome (PCOS) themselves show higher rates of ADHD. Because ADHD is partly heritable (meaning genes contribute to the condition), some of the increased ADHD seen in children of mothers with PCOS could come from shared genetic factors. In other words, a mother’s and her child’s increased risk might sometimes reflect common genes rather than an effect of the pregnancy itself.
Beyond genetics, growing evidence points to maternal metabolic problems during pregnancy as another important risk factor for neurodevelopmental outcomes. PCOS is one of these conditions and is considered both potentially modifiable (treatable or manageable) and biologically plausible as a contributor to risk. PCOS affects an estimated 5–10% of women of reproductive age worldwide and is characterized by signs such as hyperandrogenism (higher-than-normal levels of “male” hormones), insulin resistance (poorer ability to use the hormone insulin, which can affect blood sugar and metabolism), and chronic low-grade inflammation.
However, studies to date have not all reached the same conclusions. Some research suggests the association between maternal PCOS and offspring ADHD is stronger for girls, while other studies did not analyze results by child sex. Methodological differences make it harder to draw clear conclusions.
The Study:
It’s important to note that the studies included in this meta-analysis were observational (cohort studies and case-control studies). Observational studies can identify associations (that two things occur together) but cannot prove that one causes the other. A cohort study follows people over time, and a case-control study compares people with a condition to similar people without it.
The pooled results came from six studies that together included almost 1.4 million mother–child pairs and that adjusted for confounders (other factors that might influence the result, such as maternal age or socioeconomic status). After statistical adjustment, children of mothers with PCOS had about 40% greater odds of ADHD than children of mothers without PCOS. The analysis reported no evidence of publication bias (no clear sign that only positive studies were published) and zero heterogeneity (the results were consistent across the studies).
There was no meaningful difference in results between cohort and case-control studies, and the meta-analysis did not find a significant difference in the association when comparing male and female offspring.
The Take-Away:
The research team concluded that this large-scale synthesis found an association between maternal PCOS and higher odds of ADHD and other neuropsychiatric conditions in children. They suggested that children born to mothers with PCOS may benefit from developmental monitoring to identify and address problems early, while emphasizing that causal relationships have not been established. They called for further studies to confirm these findings and to investigate the biological and environmental mechanisms that might explain the association. Indeed, because women with PCOS show higher rates of ADHD than other women, we need genetically informed research designs to see if the reported association is confounded.
The Background:
Food insecurity is a widespread public‑health problem. Food insecurity refers to limited or uncertain access to enough safe, nutritious food. This term is used to describe households that sometimes or often can’t afford enough food or can only buy cheaper, less‑healthy options.
In the United States, almost eleven million children and teens (14%) lived in food‑insecure households in 2019. By 2023, the share of households with food‑insecure children and adolescents was estimated to have risen to about 18%.
Food insecurity is linked to worse physical health in children, including conditions like anemia (low red‑blood‑cell count), asthma, and delays in physical or mental development. It is also associated with problems in thinking and conduct (for example, aggressive behavior, anxiety, depression, and trouble concentrating or sitting still).
Those thinking and behavior problems can look a lot like ADHD (persistent patterns of inattention, hyperactivity, and impulsivity. This can make it hard for clinicians to tell whether symptoms come from ADHD itself, from the stress of poverty and food insecurity, or a mix of both. That overlap can complicate diagnosis and sometimes lead to misdiagnosis.
Smaller recent studies have looked at mental‑health links and found higher odds of ADHD and other mental‑health conditions among food‑insecure children aged 5–11 years. In one set of findings, moderate food insecurity was associated with 50% greater odds of an ADHD diagnosis and severe food insecurity with about 67% greater odds relative to food‑secure children.
The Study:
Because many past studies looked at single risk factors or only measured symptom severity, fewer investigations have focused specifically on household food insecurity as it relates to actual ADHD diagnoses and how that might matter for care. To address that gap, researchers used multiple years (2016–2022) of data from the U.S. National Survey of Children’s Health (NSCH). This survey is designed to be nationally representative and asks parents about their child’s health, including whether a doctor or other clinician has diagnosed ADHD.
The study included 232,571 children and adolescents (ages 3–17) and used statistical methods to adjust for other factors that could affect ADHD risk. Those factors included the child’s sex and race/ethnicity; the mother’s age; family income expressed as a percentage of the federal poverty level (a government measure used to classify income groups); the highest level of parent education; adverse childhood experiences (such as exposure to abuse, household substance use, or parental separation); birthweight (for example, low birthweight); and not getting enough sleep. Adjusting for these variables helps isolate the association between food insecurity and ADHD, though it cannot prove cause and effect.
The Results:
In this large, nationally representative sample, the researchers found a clear dose–response relationship: as the level of household food insecurity increased, so did the odds of a child having a clinician‑diagnosed ADHD (as reported by parents). In other words, greater food insecurity was linked to a higher likelihood of ADHD.
Compared with children in households that “could always afford to eat good, nutritious meals” (the reference group), the study found the following increases in odds of ADHD: children in households that “could always afford enough to eat but not always the kinds of food we should eat” had about 30% greater odds; children in households that sometimes “could not afford enough to eat” had about 55% greater odds; and children in households that often “could not afford enough to eat” had about 80% greater odds. (Saying “30% greater odds,” etc., means the odds were 1.30, 1.55, and 1.80 times those of the reference group, respectively — this describes a relative increase, not the absolute percentage of children with ADHD.)
The Take-Away:
The authors conclude that household food insecurity was associated with higher odds of parent‑reported clinician‑diagnosed ADHD in a dose‑response pattern. They suggest that reducing food insecurity (for example, ,by improving access to nutritious food and combining nutritional supports with mental‑health care) may help lower ADHD risk or reduce symptoms in some children. Reducing food insecurity should be a priority for society, but it is premature to conclude it will reduce the risk for ADHD. We know that parents with ADHD are more likely to lose their jobs and have lower incomes compared to parents with ADHD. That might create food insecurity for their children who we know are at high risk for ADHD from genetic studies.
The Background:
Many studies have tried to determine whether exercise improves executive function in children and adolescents with ADHD, but their conclusions have not always agreed. To bring the evidence together more clearly, the research team re-analyzed the available randomized controlled trials using a statistical approach designed to handle the kinds of data common in this field.
Executive functions are skills that help us control attention and behavior. The three core components are inhibitory control (the ability to stop or override impulses), working memory (holding and manipulating information in mind), and cognitive flexibility (switching between tasks or perspectives). Because a single study often reports multiple tests that tap these different skills, one study can contribute several related results (called effect sizes). Traditional meta-analysis typically treats each effect size as independent; when they are actually correlated, that can bias the combined estimate or force reviewers to discard useful data.
To avoid those problems, the team used a three-level meta-analysis. In this model, variance in the data is separated into three sources:
(1) sampling variance: the random error in each measured effect
(2) within-study variance: differences between multiple effect sizes reported in the same study
(3) between-study variance: differences in effects from one study to another
Accounting for all three levels makes it possible to include every eligible effect size from each study, which preserves information and statistical power and reduces the risk that correlations among effect sizes will overstate results.
The Study:
The review focused on long-term exercise interventions and also tested whether certain factors might change (or moderate) the effects. These potential moderators included participant age, which executive-function subcomponent was measured, the type of exercise, how long each session lasted, the total length of the intervention, and how often sessions occurred.
To be included, studies had to be randomized controlled trials (RCTs) of children or adolescents aged 6–18 diagnosed with ADHD. RCTs randomly assign participants to an intervention or a comparison group and are considered a strong design for testing cause-and-effect. The exercise programs had to be structured and last at least six weeks. Comparison groups varied by study and could include usual care, medication, sedentary activities, health education, waiting lists, or everyday life without the specific exercise program. Fifteen studies including 658 participants met these criteria.
The Results:
The three-level meta-analysis showed that long-term exercise interventions were associated with moderate-to-strong improvements in overall executive function. When statistical outliers were removed, the result remained positive: 13 RCTs with 598 participants showed moderate improvements. In plain terms, this suggests improvements that are noticeable and meaningful on average, not just tiny changes that are unlikely to matter in daily life.
Those moderate gains appeared across all three executive-function domains (inhibitory control, working memory, and cognitive flexibility, meaning the benefits were not limited to a single cognitive skill. The authors also examined exercise type:
“Open-skill” activities, which require reacting to changing situations (for example, many team sports, martial arts sparring, or racket sports), produced moderate-to-large improvements.
“Closed-skill” activities, which are more predictable and repetitive (for example, running or stationary cycling), showed only small, non-significant improvements in this analysis.
The review also found dose-related patterns. Interventions lasting at least twelve weeks were about three times more effective than interventions of six to twelve weeks, and sessions longer than an hour were about twice as effective as shorter sessions. Benefits were largest among adolescents aged 13 and older.
These patterns suggest that longer, more intensive programs, and those that involve open-skill activities, may produce larger gains. However, the authors caution that the overall certainty of the evidence was low. “Low certainty” means that limitations in the available studies (for example, small sample sizes, variability in methods, or possible bias) make it difficult to be confident that the observed effects will hold up exactly the same way in future research. Some subgroup findings (age, intervention duration, and others) were based on only a small number of effect sizes, so those moderator results should be treated as exploratory rather than definitive.
The Take-Away:
In short, this three-level meta-analysis suggests that regular, structured exercise (particularly longer programs and open-skill activities) may help improve executive functions in children and adolescents with ADHD. The evidence is promising but not yet strong enough to be considered conclusive, and the authors recommend more, larger randomized trials to confirm specifically which types and doses of exercise are most effective. Moreover, neither this meta-analysis or others show that exercise can replace standard treatments for reducing the core symptoms of ADHD (inattention, hyperactivity, impulsivity).
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