Brain activity measured with an electroencephalograph (EEG) can predict how 7- to 19-year-old youth respond to treatments for anxiety, according to research published in the Journal of Abnormal Child Psychology.
The study found a neural measure of emotional face processing predicted how well 35 anxious youth responded to cognitive-behavioral therapy and medication. Greater neural reactivity to angry faces was associated with a better treatment response.
PsyPost interviewed the study’s corresponding author, Nora Bunford of the University of Illinois at Chicago. Read her responses below:
PsyPost: Why were you interested in this topic?
Bunford: My colleagues and I were interested in improving the science-base on characteristics that predict treatment response among youth with anxiety disorders for a number of reasons.
We are aware, based on prior studies, that although we have interventions for paediatric anxiety with strong empirical evidence, there is still quite a large portion of youth who do not respond to these treatments. With progression of the treatment literature, our field has uncovered that this may not necessarily be because the treatments are “bad” but because different people respond differently to different interventions.
So, there has been emphasis on better identifying the characteristics that predispose a person to respond well or less well to a given intervention.
As a result of this emphasis, there was early focus on clinical and demographic characteristics as predictors of response but these appear to be inconsistent and sometimes weak predictors. It was to advance this aspect of clinical science that we examined whether differences in brain activation can better predict the degree to which youth with paediatric anxiety respond to medical and psychosocial treatments.
What should the average person take away from your study?
Not all youth with a similar or the same condition will respond similarly well to the same intervention. Thus, it is important to know what intervention will work for a given child so as to ensure that resources are well spent and that recovery is as fast as possible.
Based on our results, differences in the way in which a child’s brain activates to socio-emotional stimuli appear to be an important factor in determining whether or not and the degree to which he or she stands to benefit from two of the evidence-based treatments for youth with anxiety disorders.
Are there any major caveats? What questions still need to be addressed?
As with any research, there are a number of caveats, and replication is always key. Nevertheless, this is one of a many studies whose findings indicate that differences in brain activation may be very useful in differentiating patients who are likely to benefit from interventions from patients who are less likely to benefit. As such, it is paramount to identify ways in which measurement of brain activation can be used in real-world clinics by real-world clinicians so as to improve practical relevance of this body of work.
Is there anything else you would like to add?
We measured electrocortical activity via electroencephalograph (EEG) as predicting treatment response. Measuring this activity is certainly more complex and time-consuming than administering clinical interviews or questionnaires and there may be concern related to the availability and cost of the neuroscience measures.
It is thus important to note that EEG is relatively cost efficient and transportable. Also, any economic analysis has to take into account the costs of current practices where patients are often inadvertently directed to treatments to which they will likely not respond. Thus, the potential benefits of EEG measurements, in combination with enlightened advances to further improving their user-friendliness for real-world clinicians, indicate that this method may be promising.
The study, “Neural Reactivity to Angry Faces Predicts Treatment Response in Pediatric Anxiety“, was co-authored by Autumn Kujawa, Kate D. Fitzgerald, James E. Swain, Gregory L. Hanna, Elizabeth Koschmann, David Simpson, Sucheta Connolly, Christopher S. Monk and K. Luan Phan.
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