Background Mental health disorders are a leading cause of medical disabilities across an individual’s lifespan. This burden is particularly substantial in children and adolescents because of challenges in diagnosis and the lack of precision medicine approaches. However, the widespread adoption of wearable devices (eg, smart watches) that are conducive for artificial intelligence applications to remotely diagnose and manage psychiatric disorders in children and adolescents is promising. Objective This study aims to conduct 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 psychiatric disorders in child and adolescent psychiatry. Methods This scoping review used information from the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A comprehensive search of several databases from 2011 to June 25, 2021, limited to the English language and excluding animal studies, was conducted. The databases included Ovid MEDLINE and Epub ahead of print, in-process and other nonindexed 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, from which 19 (5.5%) articles were left on the final source list for this scoping review. Articles were divided into three main groups as follows: studies with the main focus on autism spectrum disorder, attention-deficit/hyperactivity disorder, and internalizing disorders such as anxiety disorders. Most of the studies used either cardio-fitness chest straps with electrocardiogram sensors or wrist-worn biosensors, such as watches by Fitbit. Both allowed passive data collection of the physiological signals. Conclusions Our scoping review found a large heterogeneity of methods and findings in artificial intelligence studies in child psychiatry. Overall, the largest gap identified in this scoping review is the lack of randomized controlled trials, as most studies available were pilot studies and feasibility trials.
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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