Abstract
To Our Readers:
This issue of the journal contains many interesting articles. I would like to draw your attention to one letter that is extremely relevant as our young people emerge from the disruption of the coronavirus pandemic, and one article that presents exciting findings about the biomarker potential of electroencephalography (EEG) for depression in adolescents.
In their letter “Transition to In-Person School After Remote Learning: Mental Health Concerns in Youth with Developmental Disabilities,” Valicenti-McDermott et al. describe the pandemic-related experiences of an important demographic: children with developmental disabilities. The authors performed a small cross-sectional study (n = 50) based on a convenience sample of parents with school-aged children visiting a developmental pediatrician or psychologist at a university medical center in a large urban area.
“Parents of most children reported they were comfortable returning to school in person,” Valicenti-McDermott et al. write, “but 18 (36%) had increased mental health concerns, including anxiety in 14 (28%), externalizing behaviors in 6 (12%), sleep disturbances in 4 (8%).” The authors note that the findings are in line with the experience of typically developing children returning to in-person learning postlockdowns. But even though the general outlook for these youth is good, this study reiterates how important it is to provide at-risk populations with mental health support in the postpandemic period.
In their article “A Predictive Biomarker Model Using Quantitative Electroencephalography in Adolescent Major Depressive Disorder,” McVoy et al. describe their promising work toward the practical application of quantitative EEG (qEEG) in diagnosis and treatment. I recommend close reading of this well-considered article. Study participants include youth aged 14–17 years (n = 35) with major depressive disorder (MDD) along with 14 age- and gender-matched healthy controls (HCs).
“We utilized our previous findings of brain connectivity differences between youth with MDD and HCs to develop a single-variable, robust qEEG predictive model with an ROC area of over 0.8,” the authors write. “Given qEEG's ease of large-scale utilization and relatively low cost further makes it a highly promising MDD biomarker for this at-risk and frequently underserved population.” Results like these, if replicated, lay the groundwork with other imaging and behavioral approaches to biomarker modeling that are reshaping our field's approach to intervention and prevention.
Elsewhere, Shang et al. present their findings on functional magnetic resonance imaging correlates of stimulant medication effects in children with attention-deficit/hyperactivity disorder (ADHD), and Matthijssen et al. look at ADHD assessment and treatment guidelines in the Netherlands. I hope you will give them your attention.