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Advances in consumer wearables and machine learning enable the continuous detection of depression risk through behavioral and physiological data. In this Comment, we emphasize the crucial need to apply these technologies to adolescents, highlighting the potential for early detection and prevention of depression during this pivotal developmental stage.
Conflicts of Interest The authors declare no conflicts of interest. Supporting Information Filename Description dev70080-sup-0001-SupMat.docx2.2 MB The SI document contains the following supplementary information, analyses, and figures: 1) SI Methods: Detailed information regarding study measures and their use. 2) SI Results: Results with log-transformed TESI variable.
The prenatal environment plays an important and enduring role in children’s development. Exposure to adversity during the prenatal period is associated with children’s cognitive and emotional difficulties; the neurobiological pathways underlying these associations, however, are not yet clear.
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