BACKGROUND
Mental health disorders across the life span are a leading cause of medical disabilities. This burden is particularly significant in children and adolescents due to challenges in diagnoses and lack of precision medicine approaches. The advent and widespread adoption of wearable devices (e.g., smartwatches) that generate large volumes of passively collected data that are conducive for artificial intelligence applications to remotely diagnose and manage child and adolescent mental health disorders is promising.
OBJECTIVE
This study conducted a scoping review to study, characterize and identify areas of innovations with wearable devices that can augment current in-person physician assessments to individualize diagnosis and management of mental health disorders in child and adolescent psychiatry.
METHODS
This scoping review used PRISMA’s information as a guide. A comprehensive search of several databases from 2011 to June 25, 2021, limited to English language and excluding animal studies, was conducted. The databases included Ovid MEDLINE (R) and Epub Ahead of Print, In-Process & Other Non-Indexed Citations and Daily, Ovid Embase, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, Web of Science, and Scopus.
RESULTS
The initial search yielded 344 articles. 19 articles were left on the final source list for this scoping review. Articles were divided into three main groups: Studies with the main focus on Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorders (ADHD) and Internalizing disorders such as anxiety disorders. Majority of the studies used either ECG strap or wrist worn biosensor.
CONCLUSIONS
Our scoping review found large heterogeneity of methods and findings in artificial intelligence studies in child psychiatry. Overall, the largest gaps identified in this scoping review are the lack of randomized control trials, most available studies are pilot feasibility trials.
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