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June 22, 2021
Several meta-analyses have assessed this question by computing the Standardized Mean Difference or SMD statistic. The SMD is a measure that allows us to compare different studies. For context, the effect of stimulant medication for treating ADHD is about 0.9. SMDs less than 0.3 are considered low, between 0.3 to 0.6 medium, and anything greater than high.
A 2004 meta-analysis combined the results of fifteen studies with a total of 219 participants and found a small association(SMD = .28, 95% CI .08-.49) between consumption of artificial food colors by children and increased hyperactivity. Excluding the smallest and lowest quality studies further reduced the SMD to .21, and a lower confidence limit of .007 also made it barely statistically significant. Publication bias was indicated by an asymmetric funnel plot. No effort was made to correct the bias.
A 2012 meta-analysis by Nigg et al. combined twenty studies with a total of 794 participants and again found a small effect size (SMD =.18, 95% CI .08-.29). It likewise found evidence of publication bias. Correcting for the bias led to a tiny effect size at the outer margin of statistical significance (SMD = .12, 95% CI .01-.23). Restricting the pool to eleven high-quality studies with 619 participants led to a similarly tiny effect size that fell just outside the 95% confidence interval (SMD = .13, CI =0-.25, p = .053). The authors concluded, "Overall, a mixed conclusion must be drawn. Although the evidence is too weak to justify action recommendations absent a strong precautionary stance, it is too substantial to dismiss."
In 2013 a European ADHD Guidelines Group consisting of 21 researchers (Sonuga-Barke et al.) performed a systematic review and meta-analysis that examined the efficacy of excluding artificial colors from the diets of children and adolescents as a treatment for ADHD. While many interventions showed benefits in unblinded assessments, only artificial food color exclusion and, to a lesser extent, free fatty acid supplementation remained effective under blinded conditions. The findings suggest that eliminating artificial food dyes may meaningfully reduce ADHD symptoms in some children, though it should be noted that the positive results were mostly seen in children with other food sensitivities.
The research to date does suggest a small effect of artificial food colors in aggravating symptoms of hyperactivity in children, and a potential beneficial effect of excluding these substances from the diets of children and adolescents, but the evidence is not very robust. More studies with greater numbers of participants, and better control for the effects of ADHD medications, will be required for a more definitive finding.
In the meantime, given that artificial food colors are not an essential part of the diet, parents could consider excluding them from their children's meals, since doing so is risk-free, and the cost (reading labels) is negligible.
Joel T. Nigg, Kara Lewis, Tracy Edinger, Michael Falk, “Meta-Analysis of Attention-Deficit/Hyperactivity Disorder attention-Deficit/Hyperactivity Disorder Symptoms, Restriction Diet, and synthetic Food Color Additives,” Journal of The American Academy of Child & Adolescent Psychiatry (2012), Vol.51, No. 1, 86-97.David W. Schab and Nhi-Ha T. Trinh, “Do Artificial FoodColors Promote Hyperactivity in Children with Hyperactive Syndromes? Aneta-Analysis of Double-Blind Placebo-Controlled Trials,” Developmental and behavioral Pediatrics(2004), Vol. 25, No. 6, 423-434.Edmund J.S. Sonuga-Barke et al., “NonpharmacologicalInterventions for ADHD: Systematic Review and Meta-Analyses of RandomizedControlled Trials of Dietary and Psychological Treatments,” American Journal of Psychiatry(2013), 170:275-289.
If we are to read what we believe on the Internet, dieting can cure many of the ills faced by humans. Much of what is written is true. Changes in dieting can be good for heart disease, diabetes, high blood pressure, and kidney stones to name just a few examples. But what about ADHD? Food elimination diets have been extensively studied for their ability to treat ADHD. They are based on the very reasonable idea that allergies or toxic reactions to foods can have effects on the brain and could lead to ADHD symptoms.
Although the idea is reasonable, it is not such an easy task to figure out what foods might cause allergic reactions that could lead to ADHD symptoms. Some proponents of elimination diets have proposed eliminating a single food, others include multiple foods, and some go as far as to allow only a few foods to be eaten to avoid all potential allergies. Most readers will wonder if such restrictive diets, even if they did work, are feasible. That is certainly a concern for very restrictive diets.
Perhaps the most well-known ADHD diet is the Feingold diet(named after its creator). This diet eliminates artificial food colorings and preservatives that have become so common in the western diet. Some have claimed that the increasing use of colorings and preservatives explains why the prevalence of ADHD is greater in Western countries and has been increasing over time. But those people have it wrong. The prevalence of ADHD is similar around the world and has not been increasing over time. That has been well documented but details must wait for another blog.
The Feingold and other elimination diets have been studied by meta-analysis. This means that someone analyzed several well-controlled trials published by other people. Passing the test of meta-analysis is the strongest test of any treatment effect. When this test is applied to the best studies available, there is evidence that the exclusion of fool colorings helps reduce ADHD symptoms. But more restrictive diets are not effective. So removing artificial food colors seems like a good idea that will help reduce ADHD symptoms. But although such diets ‘work’, they do network very well. On a scale of one to 10where 10 is the best effect, drug therapy scores 9 to 10 but eliminating food colorings scores only 3 or 4. Some patients or parents of patients might want this diet change first in the hopes that it will work well for them. That is a possibility, but if that is your choice, you should not delay the more effective drug treatments for too long in the likely event that eliminating food colorings is not sufficient. You can learn more about elimination diets from Nigg, J. T., and K.Holton (2014). "Restriction and elimination diets in ADHD treatment."Child Adolesc Psychiatr Clin N Am 23(4): 937-953.
Keep in mind that the treatment guidelines from professional organizations point to ADHD drugs as the first-line treatment for ADHD. The only exception is for preschool children where medication is only the first-line treatment for severe ADHD; the guidelines recommend that other preschoolers with ADHD be treated with non-pharmacologic treatments, when available. You can learn more about non-pharmacologic treatments for ADHD from a book I recently edited: Faraone, S. V. &Antshel, K. M. (2014). ADHD: Non-Pharmacologic Interventions. Child AdolescPsychiatr Clin N Am 23, xiii-xiv.
Mindfulness has been defined as “intentionally directing attention to present moment experiences with an attitude of curiosity and acceptance.” Mindfulness-based interventions (MBIs) aim to improve mindfulness skills.
A newly-published meta-analysis of randomized controlled trials (RCTs) by a team of British neurologists and psychiatrists explores the effectiveness of MBIs in treating a variety of mental health conditions in children and adolescents. Among those conditions is the attention deficit component of ADHD.
A comprehensive literature search identified studies that met the following criteria:
1) The effects of mindfulness were compared against a control condition – either no contact, waitlist, active, or attention placebo. The waitlist means the control group receives the same treatment after the study concludes. Active control means that a known, effective treatment (as opposed to a placebo) is compared to an experimental treatment. Attention placebo means that controls receive a treatment that mimics the time and attention received by the treatment group but is believed not to have a specific effect on the subjects. Participants were randomly assigned to the control condition.
2) The MBI was delivered in more than one session by a trained mindfulness teacher, involved sustained meditation practice, and it was not mixed in with another activity such as yoga.
Eight studies evaluating attention deficit symptoms, with a combined total of 1,158 participants, met inclusion criteria. The standardized mean difference (SMD) was 0.19, with a 95% confidence range of 0.04 to 0.34 (p = .02). That indicates a small effect size for MBIs in reducing attention deficit symptoms. Heterogeneity was low (I2 = 35, p =.15), and the Egger test showed little sign of publication bias (p = 0.42).
When looking only at studies with active controls, five studies with a total of 787 participants yielded an SMD of 0.13, with a 95% confidence interval of -0.01 to 0.28 (p = .06), indicating a tiny effect size that failed to reach significance. Active controls most commonly received health education, with a few receiving social responsibility training or Hatha yoga.
Overall, this meta-analysis suggests limited effectiveness, especially when compared with active controls. If MBIs are effective for ADHD, their effect on symptoms is very small. Thus, such treatments should not be used in place of the many well-validated, evidenced-based therapies available. Whether longer periods of MBI (training times varied between 2 and 18 hours spread out over 2 to 24 weeks) might result in greater effect sizes remains unexplored
After noting that the association between ADHD and obesity has been called into question because of small sample sizes, wide age ranges, self-reported assessments, and inadequate attention to potential confounders, an Israeli study team set out "to assess the association between board-certified psychiatrist diagnoses of ADHD and measured adolescent BMI [body mass index] in a nationally represented sample of over one million adolescents who were medically evaluated before mandatory military service."
The team distinguished between severe and mild ADHD. It also focused on a single age group.
All Israelis are subject to compulsory military service. In preparation for that service, military physicians perform a thorough medical evaluation. Trained paramedics recorded every conscript's height and weight.
The study cohort was divided into five BMI percentile groups according to the U.S. Centers for Disease Control and Prevention's BMI percentiles for 17-year-olds, and further divided by sex: <5th percentile (underweight), 5th-49th percentile (low-normal), 50th-84th percentile (high normal), 85th-94th percentile (overweight) and ≥95th (obese). Low-normal was used as the reference group.
Adjustments were made for sex, birth year, age at examination, height, country of birth (Israeli or other), socioeconomic status, and education level.
In the fully adjusted results, those with severe ADHD were 32% more likely to be overweight and 84% more likely to be obese than their typically developing peers. Limiting results to Israeli-born conscripts made a no difference.
Male adolescents with mild ADHD were 24% more likely to be overweight, and 42% more likely to be obese. Females with mild ADHD are 33% more likely to be overweight, and 42% more likely to be obese. Again, the country of birth made no difference.
The authors concluded, that both severe and mild ADHD was associated with an increased risk for obesity in adolescents at the age of 17 years. The increasing recognition of the persistence of ADHD into adulthood suggests that this dual morbidity may have a significant impact on the long-term health of individuals with ADHD, thus early preventive measures should be taken.
Stimulant medications, such as methylphenidate (Ritalin) and amphetamines (Adderall), are among the most widely prescribed drugs in the world. In the United States alone, prescription rates have climbed more than 50% over the past decade, driven largely by growing awareness of ADHD in both children and adults. Yet stimulants also have a long history of non-medical use, and concerns about their psychological risks persist among patients, families, and clinicians alike.
Two major studies now offer the clearest picture yet of what that risk actually looks like, and who it may affect.
The Background:
Before turning to the research, it helps to understand the landscape. A notable share of stimulant users misuse their medication: roughly one in four takes it in ways other than prescribed, and about one in eleven meets criteria for Prescription Stimulant Use Disorder (PSUD). Counterintuitively, most people with PSUD aren’t obtaining drugs illicitly — they’re misusing their own prescriptions.
This distinction between therapeutic and non-therapeutic use turns out to be critical when evaluating psychosis risk.
The Study:
A comprehensive meta-analysis by Jangra and colleagues pooled data across more than a dozen studies to compare psychotic outcomes in people using stimulants therapeutically versus non-therapeutically. The contrast was striking.
Among therapeutic users (more than 220,000 individuals taking stimulants at prescribed doses under medical supervision), psychotic episodes occurred in roughly one in five hundred people. When symptoms did appear, they typically emerged after prolonged treatment or in individuals with pre-existing psychiatric vulnerabilities, and they usually resolved when the medication was stopped.
Among non-therapeutic users (over 8,000 participants across twelve studies, many using methamphetamine or high-dose amphetamines), nearly one in three experienced psychotic symptoms. These episodes tended to be more severe, involving persecutory delusions and hallucinations, with faster onset and a greater likelihood of recurrence or persistence.
The biology underlying this difference is well understood. When stimulants are taken orally at guideline-recommended doses, they produce moderate, gradual changes in neurotransmitter activity central to attention and executive functions. The brain tolerates these changes relatively well. Non-therapeutic use, by contrast, often involves much higher doses that are frequently delivered through non-oral routes such as injection or smoking. This produces a rapid, excessive surge in dopamine activity, which is precisely the neurochemical pattern associated with psychotic symptoms.
The takeaway here is not that therapeutic stimulant use is risk-free, but that risk is strongly modulated by dose, route of administration, and individual psychiatric history. Clinicians are advised to monitor patients with pre-existing mood or psychotic disorders, particularly carefully.
A Nationwide Study Focuses on Methylphenidate Specifically:
Where the meta-analysis cast a wide net, a large-scale population study by Healy and colleagues drilled into a specific and clinically pressing question: does methylphenidate (the most commonly prescribed ADHD medication, also known as Ritalin) increase the risk of developing a psychotic disorder?
To find out, the researchers analyzed Finland's national health insurance database, tracking nearly 700,000 individuals diagnosed with ADHD. Finland's single-payer system made this kind of comprehensive, long-term tracking possible in a way that fragmented healthcare systems rarely allow.
Critically, the team adjusted for a range of confounding factors that have clouded previous research, including sex, parental education, parental history of psychosis, and the number of psychiatric visits and diagnoses prior to the ADHD diagnosis itself (a proxy for illness severity). After these adjustments, they found no significant difference in the risk of schizophrenia or non-affective psychosis between patients treated with methylphenidate and those who remained unmedicated. This held true even among patients with four or more years of continuous methylphenidate use.
The Take-Away:
When considered together, these studies offer meaningful reassurance without encouraging complacency.
For patients and families weighing ADHD treatment, the evidence suggests that methylphenidate used as prescribed does not increase psychosis risk, even over years of use. The rare cases of stimulant-associated psychosis in therapeutic settings are typically linked to high doses, pre-existing vulnerabilities, or both, and tend to resolve with discontinuation.
For clinicians, the findings reinforce the importance of baseline psychiatric assessment before initiating stimulant therapy, ongoing monitoring in patients with mood or psychotic disorder histories, and clear patient education about the risks of dose escalation or non-oral use.
The picture that emerges is one of a meaningful distinction between a medication used carefully within its therapeutic window and a drug misused outside of it. This distinction matters enormously when communicating risk to patients, policymakers, and the public.
ADHD is commonly treated with medication, but these treatments frequently cause side effects such as reduced appetite and disrupted sleep. Psychological and behavioral therapies exist as alternatives, but they tend to be expensive, hard to scale, and generally do little to address the motor difficulties that many children with ADHD experience — things like clumsy movement, poor handwriting, or difficulty with coordination.
Physical exercise has attracted attention as a more accessible option. But research findings have been mixed, partly because studies vary so widely in how exercise is delivered and what outcomes they measure. This meta-analysis, drawing on 21 studies involving 850 children and adolescents aged 5–20 with a clinical ADHD diagnosis, tries to cut through that noise.
Two types of motor skills
The researchers separated motor skills into two broad categories:
The Data:
Gross motor skills (16 studies, 613 participants)
Overall, exercise produced medium-to-large improvements in gross motor skills. The strongest gains were in:
No significant gains were found in balance or flexibility.
Fine motor skills (13 studies, 553 participants):
Exercise also produced medium-to-large improvements in fine motor skills, specifically:
The Results: What Kind of Exercise Works Best?
Two factors stood out consistently across both gross and fine motor skills: session length and frequency.
The type of exercise mattered; structured programs with clear motor-skill components (rather than unstructured physical activity) yielded stronger results.
These results are not without caveats, however. The authors urge caution in interpreting these findings. A few key limitations include:
The Bottom Line
This meta-analysis provides tentative moderate evidence that structured physical exercise can meaningfully support motor skill development in children and adolescents with ADHD — particularly when sessions run longer than 45 minutes and occur at least three times a week. The benefits appear most robust for object control, locomotion, handwriting, and manual dexterity.
That said, the evidence base still has real gaps. The authors call for better-designed, fully randomized controlled trials with consistent methods, standardized ways of measuring exercise intensity, and greater inclusion of children and adolescents who are not on medication — all of which would help clarify when, how, and for whom exercise works best.
Treatment guidelines for childhood ADHD recommend medications as the first-line treatment for most youth with ADHD. Still, concerns about side effects and long-term outcomes have increased interest in non-pharmacological approaches. Researchers at Saudi Arabian Armed Forces hospitals recently conducted a network meta-analysis comparing several interventions, including mindfulness-based therapy, cognitive behavioral therapy, behavioral parent training, neurofeedback, yoga, virtual reality programs, and digital working memory training.
Although the authors aimed to “provide a rigorous methodological approach to combine evidence from multiple treatment comparisons,” the study illustrates several pitfalls that arise when network meta-analysis is applied to a thin and heterogeneous evidence base.
What Network Meta-analysis Can and Cannot Do:
Network meta-analysis extends conventional meta-analysis by combining:
When the evidence network is large and well-connected, this approach can provide useful estimates of comparative effectiveness among many treatments.
This method is not always best, however, as many networks are sparse. This is especially true in areas such as complementary or behavioral therapies. In sparse networks, estimates rely heavily on indirect comparisons, and single studies can exert disproportionate influence over the results.
Conventional meta-analysis focuses on heterogeneity, meaning differences in results across studies within the same comparison.
Network meta-analysis must additionally evaluate consistency, whether the direct and indirect evidence agree.
However, when comparisons are supported by only one or two studies and the network is weakly connected, statistical tests for heterogeneity and consistency have very little power. In practice, this means the analysis often cannot detect problems even if they are present.
Sparse networks also make publication bias difficult to evaluate. This concern is particularly relevant in fields dominated by small trials and emerging therapies.
Why Such Treatment Rankings Are Appealing, but Potentially Problematic:
Many network meta-analyses summarize results using SUCRA, which estimates the probability that each treatment ranks best.
SUCRA, or Surface Under the Cumulative Ranking, is a key statistical metric in network meta-analyses. It is used to rank treatments by efficacy or safety. This is achieved by summarizing the probabilities of a treatment's rank into a single percentage, where a higher SUCRA value indicates a superior treatment. Ultimately, SUCRA helps pinpoint the most effective intervention among the ones compared.
Again, in well-supported networks, SUCRA can provide a useful summary of comparative effectiveness. But in sparse networks, rankings can create an illusion of precision, because treatments supported by a single small study may appear highly ranked simply due to random variation.
What Did this New Network Meta-analysis Study?
The study includes 16 trials with a total of 806 participants. But the structure of the evidence network is far weaker than this headline number suggests.
Based on the underlying studies:
This produces a very thin network, in which several interventions rely entirely on single studies.
Another challenge is that the included trials measure different outcomes. Some evaluate ADHD symptom severity, while others measure parental stress.
When studies use different outcome scales, meta-analysis typically relies on standardized measures such as the standardized mean difference to allow comparisons across studies. However, the analysis reports only mean-average differences, making it difficult to interpret the relative effect sizes.
Study Issues (including Limited Evidence and Risk of Bias):
The intervention supported by the largest number of studies (family mindfulness-based therapy) was one of the two approaches reported as producing statistically significant results. The other was BrainFit, which is supported by only a single previous trial.
Despite this limited evidence base, the study ranks interventions using SUCRA:
Notably, none of the runner-up interventions demonstrated statistically significant efficacy.
The authors acknowledge methodological limitations in the included studies:
“Blinding of participants and personnel (performance bias) exhibited notable concerns, as blinding for active treatment was not applicable in most studies.”
Such limitations are common in behavioral intervention trials, but they further increase uncertainty in already small evidence networks.
Conclusions:
The study ultimately concludes:
“This network meta-analysis supports MBT and BPT as effective non-pharmacological treatments for ADHD.”
However, the evidence underlying these claims is limited. Some analyses rely on very small numbers of studies and participants, and the network structure depends heavily on indirect comparisons.
Network meta-analysis can be a powerful tool when applied to a large, consistent, and well-connected body of evidence. When the evidence base is sparse, however, the resulting rankings and comparisons may appear statistically sophisticated while resting on a fragile evidentiary foundation.
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