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.
We would also like to thank members of the research policy steering group who reviewed the progress of the research and advised and commented on draft materials etc. It is our Policymakers and local authorities will also need to consider such a rebalancing beyond the provision of 'child' services, as many young disabled people move into adulthood whilst still living with their family carers. Such a transition point is often felt as catastrophic by families as an array of family supports, including short breaks, are drastically reduced as their child officially becomes an adult, although the needs of the disabled young person and their family carers may change little over this transition point. Page 12Factors associated with main carer using a narrower range of adult-focused health and welfare services in the last 3 months Univariate Associations (*p<0.05; **p<0.(n=154, % correct classification 87.0%-90.9%, Nagelkerke R 2 =0.36) Child lower SDQ total difficulties Main carer not longstanding illness/disability Household managing better financially Wald (p) 12.69 (p<0.001) 4.79 (p=0.029) 9.17 (p=0.002) Factors associated with main carer greater satisfaction with life Univariate Associations (*p<0.05; **p<0.Table 80 Factors associated with the disabled child's usage of a wider range of child-focused services in the last 3 months, data from respondents to main carer questionnaires Factors associated with disabled child usage of a wider range of child-focused services in the last 3 months Univariate Associations (*p<0.05; **p<0.Short break family experience/satisfaction: Logistic Regression Disabled child usage of a wider range of child-focused services for children in last 3 months (median split, n=191, % correct classification 57.1%-71.7%, Nagelkerke R 2 =0.23) Child not in Target Group A Child needs more supervision 10pm-6am Child uses a wider range of short breaks Wald (p) 9.55 (p=0.002) 16.19 (p<0.001) 5.57 (p=0.018) Logistic Regression Disabled child lower SDQ emotional symptoms (median split, n=240, % correct classification 60.4%-70.0%, Nagelkerke R 2 =0.18) Child not in Target Group D Child in TDC Priority Group B Child uses centre-based short breaks Main carer satisfaction: extent to which short break providers listen to the family Wald (p) 7.86 (p=0.005) 6.93 (p=0.009) 5.13 (p=0.023) 9.04 (p=0.003) Factors associated with disabled child lower SDQ conduct problems Univariate Associations (*p<0.05; **p<0.Disabled child lower SDQ hyperactivity (median split, n=272, % correct classification 71.7%-77.2%, Nagelkerke R 2 =0.31) Child not in Target Group A Child not in Target Group D Child in Target Group E Older main carer age Wald (p) 16.20 (p<0.001) 22.63 (p<0.001) 13.93 (p<0.001) 8.10 (p=0.004) Impact on well-being and behaviour, child using short breaks: qualitative analysisCarers reported increases in children's self esteem and self confidence; these were marked for some children whilst for others these were small but important changes."It has allowed Christopher to have a social life, to interact with his peer...
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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