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February 26, 2021
A Dutch and German team compared the performance of 45 adults with ADHD and 51 normally developing controls on a battery of standardized tests and questionnaires designed to assess competence in financial decision-making (FDM). These were supplemented with neuropsychological tests, as well as evaluations of each participant’s personal financial situation.
The two groups had roughly comparable demographic characteristics. There were no significant differences in age, gender balance, years of education, or work status. Students were excluded from both groups because they tend to be financially dependent and to have little or no income.
The ADHD group scored more than three times higher on self-report questionnaires for both the retrospective assessment of childhood symptoms ( Wender Utah Rating Scale—Childhood) and for evaluating current symptoms of ADHD (ADHD self-report scale). Researchers did not perform clinical evaluations of ADHD.
To determine their personal financial situation, participants were asked about their income range as well as, “Do you have debts other than mortgage or study loans?”;“Do you receive social security?”; “Do you have a savings account?”;“Do you save actively, that is, do you put money in your savings account on a regular basis?”; “Do you save for retirement?”; and “Do you own a house?” They were also asked how much they set aside in monthly savings, and, where applicable, how much they receive in social security.
On five out of nine criteria, significant differences emerged between the two groups. Whereas healthy controls had median incomes in the range of €35,000 to €45,000, for those with ADHD it was dramatically lower, between €15,000 and €25,000. Healthy controls also had twice as much disposable income. Whereas almost half of adults with ADHD reported debts other than mortgage or educational loans, only a third as many healthy adults had such debt. And whereas only slightly over half of those with ADHD reported having savings accounts, among healthy adults it was more than six out of seven. Finally, healthy controls were four times as likely to own a home.
Participants were then given standardized tests to evaluate financial competence, financial decision-making capacity, financial decision styles, the ability to make financial decisions using decision rules, the capacity to make decisions with implications for the future, impulsive buying tendencies, and a gambling task as a measure of emotional decision-making.
Adults with ADHD scored significantly lower than healthy adults on the financial competence test, and in particular, on financial abilities, financial judgment, financial management, and financial support resources. Similar outcomes emerged from the financial decision-making capacity test, especially when it came to identifying and understanding relevant information. Adults with ADHD were also significantly more likely to use avoidant and spontaneous decision styles. They also showed significantly more temporal discounting, meaning they tended to prefer immediate gratification over long-term financial security. That translated into significantly higher propensities to buy on impulse. In all cases these differences had large effect sizes.
Finally, participants were tested on nine cognitive functions: information processing speed, vigilance and selective attention, inhibition, interference, figural fluency, cognitive flexibility, task switching, verbal working memory, and numeracy.
Those with ADHD performed significantly worse, with medium effect sizes, on three cognitive measures: vigilance, interference, and numeracy. There were no significant differences on the other six measures.
The authors concluded, “The results show that the personal financial situation of adults with ADHD was less optimal than the financial situation of healthy controls. Furthermore, adults with ADHD showed significantly decreased performances compared with healthy controls in five out of seven tasks measuring FDM and on measures of vigilance, interference, and numeracy. However, mediation analyses indicated that differences in cognitive functioning cannot fully explain the differences with regard to FDM between adults with ADHD and healthy controls.”
They also pointed to limitations of the study. One is that 19 of the 45 adults with ADHD had comorbid disorders, of which three were substance dependencies. However, removing them had little effect on the outcome. Another limitation was that adults with ADHD were off medication during the testing, so it is unclear how stimulants would affect the test outcomes. The authors state, “The influence of treatment use should, therefore, be explored in future research on FDM and adults with ADHD.”
Dorien F. Bangma, et al., “Financial Decision-Making in Adults With ADHD,” Neuropsychology (2019), http://dx.doi.org/10.1037/neu0000571.
Background:
Despite recommendations for combined pharmacological and behavioral treatment in childhood ADHD, caregivers may avoid these options due to concerns about side effects or the stigma that still surrounds stimulant medications. Alternatives like psychosocial interventions and environmental changes are limited by questionable effectiveness for many patients. Increasingly, patients and caregivers are seeking other therapies, such as neuromodulation – particularly transcranial direct current stimulation (tDCS).
tDCS seeks to enhance neurocognitive function by modulating cognitive control circuits with low-intensity scalp currents. There is also evidence that tDCS can induce neuroplasticity. However, results for ADHD symptom improvement in children and adolescents are inconsistent.
The Method:
To examine the evidence more rigorously, a Taiwanese research team conducted a systematic search focusing exclusively on randomized controlled trials (RCTs) that tested tDCS in children and adolescents diagnosed with ADHD. They included only studies that used sham-tDCS as a control condition – an essential design feature that prevents participants from knowing whether they received the active treatment, thereby controlling for placebo effects.
The Results:
Meta-analysis of five studies combining 141 participants found no improvement in ADHD symptoms for tDCS over sham-TDCS. That held true for both the right and left prefrontal cortex. There was no sign of publication bias, nor of variation (heterogeneity) in outcomes among the RCTs.
Meta-analysis of six studies totaling 171 participants likewise found no improvement in inattention symptoms, hyperactivity symptoms, or impulsivity symptoms for tDCS over sham-TDCS. Again, this held true for both the right and left prefrontal cortex, and there was no sign of either publication bias or heterogeneity.
Most of the RCTs also performed follow-ups roughly a month after treatment, on the theory that induced neuroplasticity could lead to later improvements.
Meta-analysis of four RCTs combining 118 participants found no significant improvement in ADHD symptoms for tDCS over sham-TDCS at follow-up. This held true for both the right and left prefrontal cortex, with no sign of either publication bias or heterogeneity.
Meta-analysis of five studies totaling 148 participants likewise found no improvement in inattention symptoms or hyperactivity symptoms for tDCS over sham-TDCS at follow-up. AS before, this was true for both the right and left prefrontal cortex, with no sign of either publication bias or heterogeneity.
The only positive results came from meta-analysis of the same five studies, which reported a medium effect size improvement in impulsivity symptoms at follow-up. Closer examination showed no improvement from stimulation of the right prefrontal cortex, but a large effect size improvement from stimulation of the left prefrontal cortex.
Interpretation:
It is important to note that the one positive result was from three RCTs combining only 90 children and adolescents, a small sample size. Moreover, when only one of sixteen combinations yields a positive outcome, that begins to look like p-hacking for a positive result.
In research, scientists use something called a “p-value” to determine if their findings are real or just due to chance. A p-value below 0.05 (or 5%) is considered “statistically significant,” meaning there's less than a 5% chance the result happened by pure luck.
When testing twenty outcomes by this standard, one would expect one to test positive by chance even if there is no underlying association. In this case, one in 16 comes awfully close to that.
To be sure, the research team straightforwardly reported all sixteen outcomes, but offered an arguably over-positive spin in their conclusion: “Our study only showed tDCS-associated impulsivity improvement in children/adolescents with ADHD during follow-ups and anode placement on the left PFC. ... our findings based on a limited number of available trials warrant further verification from large-scale clinical investigations.”
Children and adolescents with ADHD tend to be less active and more sedentary than their typically developing peers. This is concerning, since physical activity benefits mental, physical, and social development. For youth with ADHD, being active can improve symptoms like inattention, working memory, and inhibitory control.
A major barrier to physical activity for children and adolescents with ADHD is limited motor competence. This stems from challenges in developing basic motor skills and more complex abilities needed for sports and advanced movements.
Difficulties in developing fundamental movement skills – such as locomotor (running, jumping), object-control (throwing, catching), and stability skills (balancing, turning) – can reduce motor competence and limit physical activity. These basic movements are learned and refined with practice and age, not innate abilities.
To date, research on the link between ADHD and motor competence has remained inconclusive. This systematic review and meta-analysis by a Spanish research team therefore aimed to determine whether children and adolescents with ADHD differ in motor competence from those with typical development (TD).
Studies had to include children and adolescents diagnosed with ADHD. They had to involve a full motor assessment battery, not just one test, and present motor competence data for both ADHD and TD groups.
The team excluded studies involving participants with other neurodevelopmental disorders or cognitive impairments, unless separate data for the ADHD subgroup were reported.
Meta-analysis of six studies combining 323 children and adolescents found that typically developing individuals were twelve times more likely to score in the 5th percentile of the Movement Assessment Battery for Children as their peers diagnosed with ADHD. They were also three times more likely to score in the 15th percentile (five studies, 289 participants). Results were consistent across the studies (low heterogeneity). All included studies were randomized.
Meta-analysis of five studies totaling 198 participants using the Test of Gross Motor Development reported significant deficits in both locomotor skills and object control skills among children and adolescents diagnosed with ADHD relative to their typically developing peers. In this case, however, results were inconsistent across studies (very high heterogeneity), and one of the studies was unrandomized. Because the team published only unstandardized mean differences, there was no indication of effect sizes.
Meta-analysis of two studies encompassing 164 participants using the Bruininks-Oseretsky Test of Motor Proficiency similarly yielded significant deficits among children and adolescents diagnosed with ADHD relative to their typically developing peers, but in this case with low heterogeneity. Notably, one of the two studies was not randomized.
Moreover, the team made no assessment of publication bias.
The team concluded, “The findings of this review indicate that children and adolescents with ADHD show significantly lower levels of motor competence compared to their TD peers. This trend was evident across a range of validated assessment tools, including the MABC, BOT, TGMD, and other standardized test batteries. Future research should aim to reduce methodological heterogeneity and further investigate the influence of factors such as ADHD subtypes and comorbid conditions on motor development trajectories.”
However, without a publication bias assessment, reliance on unrandomized studies in two of the tests, no indication of effect size in the same two tests, and small sample sizes, these results are at best suggestive, and will require further research to confirm.
Executive function impairment is a key feature of ADHD, with its severity linked to the intensity of ADHD symptoms. Executive function involves managing complex cognitive tasks for organized behavior and includes three main areas: inhibitory control (suppressing impulsive actions), working memory (holding information briefly), and cognitive flexibility (switching between different mental tasks). Improving executive functions is a critical objective in the treatment of ADHD.
Amphetamines and methylphenidate are commonly used to treat ADHD, but can cause side effects like reduced appetite, sleep problems, nausea, and headaches. Long-term use may also lead to stunted growth and cardiovascular issues. This encourages the search for non-invasive methods to enhance executive function in children with ADHD.
Neurological techniques like neurofeedback and transcranial stimulation are increasingly used to treat children with neurodevelopmental disorders. Neurofeedback is the most adopted method; it is noninvasive and aims to improve brain function by providing real-time feedback on brainwave activity so participants can self-regulate targeted brain regions.
The systematic search and meta-analysis examined children and adolescents aged 6–18 with ADHD. It included randomized and non-randomized controlled trials, as well as quasi-experimental studies that reported statistical data such as participant numbers, means, and standard deviations. Studies were required to use validated measures of executive function, including neurocognitive tasks or questionnaires. They also had to have control groups.
A meta-analysis of ten studies (539 participants) found a small-to-medium improvement in inhibitory control after neurofeedback training, with no publication bias and minimal study heterogeneity*. Long-term treatment (over 21 hours) showed benefits, while short-term treatment did not. However, publication bias was present in the long-term treatment studies and was not addressed.
A meta-analysis of seven studies with 370 children and adolescents found a small-to-medium improvement in working memory after neurofeedback, with no publication bias overall but high heterogeneity. A dose-response effect was observed: treatments over 21 hours showed benefits, while shorter ones did not. However, publication bias was present in the long-term treatment studies and was not addressed.
The study team also looked at sustained effects six months to a year after conclusion of training. Meta-analysis of two studies totaling 131 participants found a sustained small-to-medium improvement in inhibitory control, with negligible heterogeneity. Meta-analysis of three studies combining 182 participants found a sustained medium improvement in working memory, with moderate heterogeneity and no sign of publication bias.
The team concluded, “NFT is an effective intervention for improving executive function in children with ADHD, specifically inhibitory control and working memory. This approach demonstrates a more pronounced impact on working memory when extended beyond 1000 min [sic], with inhibitory control following closely behind. Furthermore, the evidence suggests that NFT may have sustained effects on both working memory and inhibitory control. Given the relatively small number of studies assessing long-term effects and the potential for publication bias, further research is necessary to confirm these effects.”
Moreover, because 1) RCTs are the gold standard, and the meta-analyses combined RCTs with non-RCTs, and 2) data from neurocognitive tasks was combined with data from more subjective and less accurate questionnaires, these meta-analysis results should be interpreted with further caution.
*Heterogeneity refers to the rate of variation between individual study outcomes. High heterogeneity means that there was substantial variation in the results. When a meta-anaylysis has high heterogeneity, it suggests that the studies differ significantly in their populations, methods, interventions, or outcomes, making the combined result much less reliable.
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