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January 26, 2022
This systematic review of the literature identified seven studies addressing ADHD and sexuality.
Sexual function
A Dutch study compared 136 persons with ADHD with two large surveys of the general Dutch population. They used both a self-report questionnaire, the Questionnaire for screening Sexual Dysfunction and a non-validated questionnaire especially constructed for the study. They found that males with ADHD reported a 50 percent higher rate of frequent masturbation than males in the general population. Both males and females were less than half as likely to be satisfied with their sex life. That was almost certainly linked to the fact that ADHD participants in the sample were less likely to be in a relationship.
A second study compared 79 ADHD participants with controls. Using a validated questionnaire, the Diagnostic Interview Schedule, to assess sexual function, they found a significant positive correlation between ADHD and the items "sex drive more than the average" and "recurrent thoughts about sex' by comparison with the control group.
A third study used two validated inventories “ the Derogates Sexual Functioning Inventory and the Social Sexual Orientation Inventory“ to assess sexual function among 27 young adult males. They found their sex drive to be higher than in the control group.
Another study, also with 27 ADHD patients, compared them with two other groups, one with fiber mitosis (benign connective tissue cancers), and the other with both ADHD and fibromatosis. They used the validated Life Satisfaction Questionnaire to assess sexual function and found that those with ADHD reported lower sex life satisfaction.
On the other hand, the only large study, with over 14,000 participants, using a non-validated questionnaire to assess sexual function, found negligible associations between ADHD and the number of sexual partners, the frequency of having sex with one's partner, and the frequency of masturbation.
Sexual dysfunctions
The Dutch study mentioned above, comparing 136 ADHD outpatients with two large surveys of the general Dutch population, used a validated self-report questionnaire, the Questionnaire for screening Sexual Dysfunctions, and a non-validated questionnaire, specially designed for the study, the Questionnaire for screening Sexual Problems. It found the rate of sexual dysfunction among both males and females with ADHD to be over twice the level in the general population. Men were four times as likely to report problems with orgasm, 50 percent more likely to report premature ejaculation, and over ten times as likely to report sexual aversion. Women were over three times as likely to report sexual excitement problems, over twice as likely to report problems with orgasm, and over three times as likely to report sexual aversion. No significant differences existed between patients treated with psychostimulants and those without such treatment.
A second study, which used a validated questionnaire to compare 79 ADHD participants with controls, found significant correlations between ADHD and aversion to sex for men but none for women.
On the other hand, a third study, comparing 32 subjects with ADHD with 293 controls, found no significant difference in the prevalence of sexual dysfunctions. It used clinical interviews to assess ADHD, and a non-validated questionnaire to assess sexual dysfunctions.
A fourth study took a very different approach. It compared 38 individuals with premature ejaculation to 27 controls. It found more than ten times the rate of ADHD symptoms among those with premature ejaculation than in the control group. Significantly, it measures premature ejaculation directly, with a stopwatch.
Conclusion
The authors concluded, "This article provides the first systematic review of sexual health among subjects with ADHD and shows that the quality of sexual health among subjects with ADHD seems poor," but acknowledged "several limitations to our review. There are only a few studies for the topics we reviewed. For many studies, the sample size was small. The methodology and measurement instruments differed, which created a potential bias."
Indeed, the study with the largest sample size found negligible associations between ADHD and sexual function, contradicting studies with small sample sizes.
Only four of the studies, all with small sample sizes, examined sexual dysfunctions. Two found strong associations with ADHD, one found none, and the fourth had mixed results.
This points to a compelling need for further research on ADHD and sexuality, with larger sample sizes.
Lorenzo Soldati, MD, Francesco Bianchi-Demicheli, MD, Pauline Schockaert, MAS, John Köhl, MAS, MylèneBolmont, Ph.D., Roland Hasler, Ph.D., and Nader Perroud, MD, “SexualFunction, Sexual Dysfunctions, and ADHD: A Systematic Literature Review,” Journal of Sexual Medicine(2020),https://doi.org/10.1016/j.jsxm.2020.03.019.
Although ADHD was conceived as a childhood disorder, we now know that many cases persist into adulthood. My colleagues and I charted the progression of ADHD through childhood, adolescence, and adulthood in our "Primer" about ADHD,http://rdcu.be/gYyV. Although the lifetime course of ADHD varies among adults with the disorder, there are many consistent themes, which we described in the accompanying infographic. Most cases of ADHD startin uterobefore the child is born. As a fetus, the future ADHD person carries versions of genes that increase the risk for the disorder. At the same time, they are exposed to toxic environments. These genetic and environmental risks change the developing brain, setting the foundation for the future emergence of ADHD.
In preschool, early signs of ADHD are seen in emotional lability, hyperactivity, disinhibited behavior, and speech, language, and coordination problems. The full-blown ADHD syndrome typically occurs in early childhood, but can be delayed until adolescence. In some cases, the future ADHD person is temporarily protected from the emergence of ADHD due to factors such as high intelligence or especially supportive family and/or school environments. But as the challenges of life increase, this social, emotional, and intellectual scaffolding is no longer sufficient to control the emergence of disabling ADHD symptoms. Throughout childhood and adolescence, the emergence and persistence of the disorder are regulated by additional environmental risk factors such as family chaos along with the age-dependent expression of risk genes that exert different effects at different stages of development. During adolescence, most cases of ADHD persist and by the teenage years, many youths with ADHD have onset with a mood, anxiety, or substance use disorder. Indeed, parents and clinicians need to monitor ADHD youth for early signs of these disorders. Prompt treatment can prevent years of distress and disability. By adulthood, the number of comorbid conditions has increased, including obesity, which likely has effects on future medical outcomes.
The ADHD adult tends to be very inattentive by showing fewer symptoms of hyperactivity and impulsivity. They remain at risk for substance abuse, low self-esteem, occupational failure, and social disability, especially if they are not treated for the disorder. Fortunately, there are several classes of medications available to treat ADHD that are safe and effective. And the effects of these medications are enhanced by cognitive behavior therapy, as I've written about in prior blogs.
Although there has been much research documenting that ADHD adults are at risk for other psychiatric and substance use disorders, relatively little is known about whether ADHD puts adults at risk specifically for somatic medical disorders.
Given that people with ADHD tend toward being disorganized and inattentive, and that they tend to favor short-term over long-term rewards, it seems logical that they should be at higher risk for adverse medical outcomes. But what does the data say?
In a systematic review of the literature, Instances and colleagues have provided a thorough overview of this issue. Although they found 126 studies, most were small and were of "modest quality". Thus, their results must be considered to be suggestive, not definitive for most of the somatic conditions they studied.
Also, they excluded articles about traumatic injuries because the association between ADHD and such injuries is well established. Using qualitative review methods, they classified associations as being a) well-established; b) tentative, or c) lacking sufficient data.
Only three conditions met their criteria for being a well-established association: asthma, sleep disorders, and obesity.
They found tentative evidence implicating ADHD as a risk factor for three conditions: migraine headaches, celiac disease, and diseases of the circulatory system.
These data are intriguing, but cannot tell us why ADHD people are at increased risk for somatic conditions. One possibility is that suffering from ADHD symptoms can lead to an unhealthy lifestyle, which leads to increased medical risk. Another possibility is that the biological systems that are dysregulated in ADHD are also dysregulated in some medical disorders. For example, we know that there is some overlap between the genes that increase the risk for ADHD and those that increase the risk for obesity. We also know that the dopamine system has been implicated in both disorders.
Instances and colleagues also point out that some medical conditions might lead to symptoms that mimic ADHD. They give sleep-disordered breathing as an example of a condition that can lead to the symptom of inattention.
But this seems to be the exception, not the rule. Other medical conditions co-occurring with ADHD seem to be true comorbidities, rather than the case of one disorder causing the other. Thus, primary care clinicians should be alert to the fact that many of their patients with obesity, asthma, or sleep disorders might also have ADHD.
By screening such patients for ADHD and treating that disorder, you may improve their medical outcomes indirectly via increased compliance with your treatment regime and an improvement in health behaviors. We don't yet have data to confirm these latter ideas, as the relevant studies have not yet been done.
There is a growing interest (and controversy) in 'adult-onset ADHD. No current diagnostic system allows for the diagnosis of ADHD in adulthood, yet clinicians sometimes face adults who meet all criteria for ADHD, except for age at onset. Although many of these clinically referred adult-onset cases may reflect poor recall, several recent longitudinal population studies have claimed to detect cases of adult-onset ADHD that showed no signs of ADHD as a youth (Agnew-Blais, Polanczyk et al. 2016, Caye, Rocha, et al. 2016). They conclude, not only that ADHD can onset in adulthood, but that childhood-onset and adult-onset ADHD may be distinct syndromes(Moffitt, Houts, et al. 2015)
In each study, the prevalence of adult-onset ADHD was much larger than the prevalence of childhood-onset adult ADHD). These estimates should be viewed with caution. The adults in two of the studies were 18-19 years old. That is too small a slice of adulthood to draw firm conclusions. As discussed elsewhere (Faraone and Biederman 2016), the claims for adult-onset ADHD are all based on population as opposed to clinical studies.
Population studies are plagued by the "false positive paradox", which states that, even when false positive rates are low, many or even most diagnoses in a population study can be false.
Another problem is that the false positive rate is sensitive to the method of diagnosis. The child diagnoses in the studies claiming the existence of adult-onset ADHDused reports from parents and/or teachers but the adult diagnoses were based on self-report. Self-reports of ADHD in adults are less reliable than informant reports, which raises concerns about measurement error. Another longitudinal study found that current symptoms of ADHD were under-reported by adults who had had ADHD in childhood and over-reported by adults who did not have ADHD in childhood(Sibley, Pelham, et al. 2012). These issues strongly suggest that the studies claiming the existence of adult-onset ADHD underestimated the prevalence of persistent ADHD and overestimated the prevalence of adult-onset ADHD. Thus, we cannot yet accept the conclusion that most adults referred to clinicians with ADHD symptoms will not have a history of ADHD in youth.
The new papers conclude that child and adult ADHD are "distinct syndromes", "that adult ADHD is more complex than a straightforward continuation of the childhood disorder" and that adult ADHD is "not a neurodevelopmental disorder". These conclusions are provocative, suggesting a paradigm shift in how we view adulthood and childhood ADHD. Yet they seem premature. In these studies, people were categorized as adult-onset ADHD if full-threshold add had not been diagnosed in childhood. Yet, in all of these population studies, there was substantial evidence that the adult-onset cases were not neurotypical in adulthood (Faraone and Biederman 2016). Notably, in a study of referred cases, one-third of late adolescent and adult-onset cases had childhood histories of ODD, CD, and school failure(Chandra, Biederman, et al. 2016). Thus, many of the "adult onsets" of ADHD appear to have had neurodevelopmental roots.
Looking through a more parsimonious lens, Faraone and Biederman(2016)proposed that the putative cases of adult-onset ADHD reflect the existence of subthreshold childhood ADHD that emerges with full threshold diagnostic criteria in adulthood. Other work shows that subthreshold ADHD in childhood predicts onsets of full-threshold ADHD in adolescence(Lecendreux, Konofal, et al. 2015). Why is onset delayed in subthreshold cases? One possibility is that intellectual and social supports help subthreshold ADHD youth compensate in early life, with decompensation occurring when supports are removed in adulthood or the challenges of life increase. A related possibility is that the subthreshold cases are at the lower end of a dimensional liability spectrum that indexes risk for onset of ADHD symptoms and impairments. This is consistent with the idea that ADHD is an extreme form of a dimensional trait, which is supported by twin and molecular genetic studies(Larsson, Anckarsater, et al. 2012, Lee, Ripke, et al. 2013). These data suggest that disorders emerge when risk factors accumulate over time to exceed a threshold. Those with lower levels of risk at birth will take longer to accumulate sufficient risk factors and longer to onset.
In conclusion, it is premature to accept the idea that there exists an adult-onset form of ADHD that does not have its roots in neurodevelopment and is not expressed in childhood. It is, however, the right time to carefully study apparent cases of adult-onset ADHD to test the idea that they are late manifestations of a subthreshold childhood condition.
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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.
Background:
One of the more persistent concerns among parents of children with ADHD is whether stimulant medications will stunt their child's growth. A large Israeli cohort study now offers some of the most rigorous reassurance to date, and its methodology sets it apart from earlier research.
The question has long been complicated by a more fundamental uncertainty: do growth differences in children with ADHD stem from the condition itself, from stimulant treatment, or from factors present before any medication is ever prescribed? Without a clear answer, clinicians and families have faced a genuine dilemma when weighing the benefits of stimulant therapy against potential long-term physical costs.
Most previous studies compounded this difficulty by comparing group-average heights, which ignores the crucial variable of genetic potential. A child who is short relative to the general population may simply have short parents. Failing to account for this introduces systematic bias and can make medications appear more harmful than they are.
The Study:
The Israeli research team addressed this directly. Using health records from a nationwide provider, they assembled a retrospective cohort of children born between 1995 and 2003, following them through 2023. This amount of time was long enough for all participants to have reached adult stature (defined as 17 or older for females, 19 or older for males). Their sample included 5,671 children with untreated ADHD, 11,846 who received stimulant treatment, and 47,258 non-ADHD controls. Children who took stimulants for only one to two months, or who had chronic medical conditions requiring long-term medication, were excluded to avoid confounding the results.
Crucially, adult height was evaluated not against population norms but against each individual's expected height, calculated from parental heights using the Tanner-Goldstein-Whitehouse method, a standard approach for estimating genetic height potential via mid-parental height.
When the researchers compared adult heights across the three groups using analysis of variance (ANOVA), they did find statistically significant differences. But statistical significance, particularly in studies with tens of thousands of participants, does not automatically translate into clinical significance. The effect sizes were consistently very small, and the absolute differences were under one centimeter, which is a margin considered clinically negligible.
Their conclusion is measured but clear: after accounting for genetic growth potential, neither an ADHD diagnosis nor stimulant treatment was associated with meaningful reductions in adult height. The findings, they argue, support prioritizing behavioral and functional outcomes when making treatment decisions, since the risk of clinically significant height loss appears to be minimal.
The Take-Away:
For families navigating ADHD treatment, the practical implication is significant: concerns about permanent growth suppression, while understandable, should not be the primary driver of whether or how long a child receives stimulant therapy.
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