February 6, 2021
ADHD is far more prevalent among persons with AUD (roughly 20 percent) than it is in the general population. The most accurate way of identifying ADHD is through structured clinical interviews. Given that this is not feasible in routine clinical settings, ADHD self-report scales offer a less reliable but much less resource-intensive alternative. Could the latter be calibrated in a way that would yield diagnoses that better correspond with the former?
A German team compared the outcomes of both methods on 404 adults undergoing residential treatment for AUD. All were abstinent while undergoing evaluations. First, to obtain reliable ADHD diagnoses, each underwent the Diagnostic Interview for ADHD in Adults, DIVA. If DIVA indicated probable ADHD, two expert clinicians conducted successive follow-up interviews. ADHD was only diagnosed when both experts concurred with the DIVA outcome.
Participants were then asked to use two adult ADHD self-report scales, the six-item Adult ADHD Self Report Scale v1.1 (ASRS) and the 30-item Conners’ Adult ADHD Rating Scale (CAARS-S-SR). The outcomes were then compared with the expert interview diagnoses.
Using established cut-off values for the ASRS, less than two-thirds of patients known to have ADHD were scored as having ADHD by the test. In other words, there was a very high rate of false negatives. Lowering the cut-off to a sum score ≥ 11 resulted in a correct diagnosis of more than seven out of eight. But the rate of false positives soared to almost two in five. Similarly, the CAARS-S-SR had its greatest sensitivity (ability to accurately identify those with ADHD) at the lowest threshold of ≥ 60, but at a similarly high cost in false positives (more than a third).
The authors found it was impossible to come anywhere near the precision of the expert clinical interviews. Nevertheless, they judged the best compromise to be to use the lowest thresholds on both tests and then require positive determinations from both. That led to successfully diagnosing more than three out of four individuals known to have ADHD, with a false positive rate of just over one in five.
Using this combination of the two self-reporting questionnaires with lower thresholds, they suggest, could substantially reduce the under-diagnosis of ADHD in alcohol-dependent patients.
Mathias Luderer, Nurcihan Kaplan-Wickel, Agnes Richter, Iris Reinhard, Falk Kiefer, Tillmann Weber, “Screening for adult attention-deficit/hyperactivity disorder in alcohol dependent patients: Underreporting of ADHD symptoms in self-report scales,” Drug and Alcohol Dependence (2019), 195:52-58.
There has been consistent evidence of an association between ADHD and subjectively reported sleep problems even in patients not medicated for the disorder. There have also been studies using wrist-worn actigraphy (a wrist watch-like device that measures gross motor activity) and sleep lab-based polysomnography that measure objective sleep parameters.
What has been missing are large population-based cohort studies to explore the prevalence rates of different sleep disorders and medical prescriptions in ADHD.
Methods Used:
Sweden has a single-payer health insurance system and a series of national population registers that track virtually its entire population. Using the Swedish Total Population Register, a local research team created a cohort of all 6,470,658 persons born between 1945 and 2008. They linked this to the Swedish National Patient Register, which includes inpatient hospitalizations from 1975 to 2013, and outpatient specialist diagnoses from 2001 to 2013, to identify diagnoses of sleep disorders. They also linked to the Prescribed Drug Register, covering 2005 to 2013, to identify prescriptions for sleep medications.
Summary of Findings:
Overall, persons with ADHD were eight times more likely to be diagnosed with any sleep disorder relative to normally developing peers. Broken down by age, adolescents with ADHD were 16 times more likely to receive such diagnoses, young adults (18-30) twelve times more likely, children and mid-age adults (31-45) eight times more likely, and older adults six times more likely.
Broken down by specific sleep disorder diagnoses, relative to normally developing peers, persons with ADHD were:
As for sleep medication, relative to normally developing peers, persons with ADHD were:
Conclusion:
The team concluded, “Our findings also suggest that greater clinical attention should be directed towards addressing sleep problems in individuals with ADHD. This entails implementing proactive measures through sleep education programmes and providing both pharmacological and non-pharmacological approaches such as cognitive behavioural therapy and parental sleep training.”
Attention is a critical determinant of academic achievement, influencing domains such as language, literacy, and mathematics. To explore whether physical activity can improve attention in children with ADHD, an international team conducted a meta-analysis of peer-reviewed studies. The goal was to evaluate the impact of various physical activity regimens on attention-related outcomes in this population.
The researchers performed a comprehensive search of the medical literature to identify studies examining the effects of physical activity on attention in schoolchildren with ADHD. They included 10 studies with a total of 474 participants in their meta-analysis. The studies evaluated two main types of physical activity:
Additionally, they examined variations based on the frequency, duration, and type of control groups used in the studies. To assess consistency, they also analyzed heterogeneity (variability of outcomes) and checked for potential publication bias.
Key findings from the meta-analysis include:
The authors concluded that mentally engaging exercise is more effective than aerobic exercise in improving attention problems in schoolchildren with ADHD. Furthermore, higher frequency and longer duration of physical activity do not necessarily yield better outcomes.
This research underscores the importance of tailoring physical activity interventions to emphasize cognitive engagement over intensity or duration. By refining strategies, educators and parents can better support children with ADHD in achieving academic success. But take note: given the results from controlled studies, it seems clear that if there is a positive effect of exercise, it is very small so should not replace standard treatments for ADHD.
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Previous studies have examined how stimulant medications affect the brain in controlled settings, but less is known about their impact in real-world conditions, where children may not always take their medication consistently or may combine it with other treatments. A new study leverages data from the Adolescent Brain Cognitive Development (ABCD) study to explore how real-world stimulant use impacts brain connectivity and ADHD symptoms over two years.
Changes in Brain Connectivity Researchers used brain imaging data from the ABCD study to examine the functional connectivity—communication between brain areas—of six regions within the striatum, a brain area involved in motivation and movement control. They focused on how stimulant use influenced connectivity between the striatum and other networks involved in executive functioning and visual-motor control.
The study found that stimulant exposure was linked to reduced connectivity between key striatal areas (such as the caudate and putamen) and large brain networks, including the frontoparietal and visual networks. These changes were more pronounced in children taking stimulants compared to those who were not medicated, as well as compared to typically developing children. Importantly, this reduction in connectivity seemed to regulate certain brain networks that are typically altered in children with ADHD.
Symptom Improvement In addition to brain changes, 14% of children taking stimulants experienced a significant reduction in ADHD symptoms over the two-year period. These children showed the strongest connectivity reductions between the right putamen and the visual network, suggesting that stimulant-induced connectivity changes may contribute to improvements in visual attentional control, which is a common challenge for children with ADHD.
Why This Matters This study is one of the first to examine how stimulant use in real-world conditions affects brain networks in children with ADHD over time. The findings suggest that stimulants may help normalize certain connectivity patterns associated with ADHD, particularly in networks related to attention and control. These insights could help clinicians better understand the potential long-term effects of stimulant treatment and guide personalized approaches to ADHD management.
Conclusion Stimulant medications appear to alter striatal-cortical connectivity in children with ADHD, with some changes linked to symptom improvement. This research highlights the potential for stimulant medications to impact brain networks in ways that support attention and control, highlighting the importance of understanding how real-world medication use influences ADHD treatment outcomes.
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