Helen Minnis, Alessandro Vinciarelli, Huda Alsofyani
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The use and potential of artificial intelligence for supporting clinical observation of child behaviour
Background
Observation of child behaviour provides valuable clinical information but often requires rigorous, tedious, repetitive and time expensive protocols. For this reason, tests requiring significant time for administration and rating are rarely used in clinical practice, however useful and effective they are. This article shows that Artificial Intelligence (AI), designed to capture and store the human ability to perform standardised tasks consistently, can alleviate this problem.
Case study
We demonstrate how an AI-powered version of the Manchester Child Attachment Story Task can identify, with over 80% concordance, children with insecure attachment aged between 5 and 9 years.
Discussion
We discuss ethical issues to be considered if AI technology is to become a useful part of child mental health assessment and recommend practical next steps for the field.
期刊介绍：
Child and Adolescent Mental Health (CAMH) publishes high quality, peer-reviewed child and adolescent mental health services research of relevance to academics, clinicians and commissioners internationally. The journal''s principal aim is to foster evidence-based clinical practice and clinically orientated research among clinicians and health services researchers working with children and adolescents, parents and their families in relation to or with a particular interest in mental health. CAMH publishes reviews, original articles, and pilot reports of innovative approaches, interventions, clinical methods and service developments. The journal has regular sections on Measurement Issues, Innovations in Practice, Global Child Mental Health and Humanities. All published papers should be of direct relevance to mental health practitioners and clearly draw out clinical implications for the field.
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