Child Mental Health in the Age of AI: Clinical Applications and Ethical Reflections

Artificial Intelligence (AI) is making useful changes in field of child and adolescent mental health. The current review aims to look at use of AI in child psychiatry, with an emphasis on disorders including neurodevelopmental disorders, mood disorders, psychosis and suicide prevention. AI methods like machine learning (ML) and natural language processing (NLP) have shown promise in detecting early behavioral and neurobiological signs using home videos, neuroimaging, wearable technology, and electronic health information. AI-powered chatbots and virtual reality-based tests are already being utilized for diagnosis and treatment. AI has also demonstrated a high degree of predictive accuracy in suicide prevention by analyzing social media content and clinical data. Despite these advances, AI use in child mental health poses significant ethical challenges. For AI to be genuinely transformational, the emphasis on growing research must be accompanied with a high standard of responsibility, patient rights protection, inter-disciplinary collaboration, and clinician oversight.

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Publication Details

Journal
Annals of King Edward Medical University
Published
2025-06-30
DOI
https://doi.org/10.21649/akemu.v31ispl2.6156
Primary Topic
Ethics and Legal Issues in Pediatric Healthcare
Type
article
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article

Child Mental Health in the Age of AI: Clinical Applications and Ethical Reflections

Maryam Ayub, Sania Mumtaz Tahir
Annals of King Edward Medical University
Ethics and Legal Issues in Pediatric Healthcare
article

Child Mental Health in the Age of AI: Clinical Applications and Ethical Reflections

Maryam Ayub, Sania Mumtaz Tahir
article en

Abstract

Artificial Intelligence (AI) is making useful changes in field of child and adolescent mental health. The current review aims to look at use of AI in child psychiatry, with an emphasis on disorders including neurodevelopmental disorders, mood disorders, psychosis and suicide prevention. AI methods like machine learning (ML) and natural language processing (NLP) have shown promise in detecting early behavioral and neurobiological signs using home videos, neuroimaging, wearable technology, and electronic health information. AI-powered chatbots and virtual reality-based tests are already being utilized for diagnosis and treatment. AI has also demonstrated a high degree of predictive accuracy in suicide prevention by analyzing social media content and clinical data. Despite these advances, AI use in child mental health poses significant ethical challenges. For AI to be genuinely transformational, the emphasis on growing research must be accompanied with a high standard of responsibility, patient rights protection, inter-disciplinary collaboration, and clinician oversight.

Annals of King Edward Medical UniversityVol. 31(Spl2)
King Edward Medical University (PK)
Openalex Percentile: Top 71%
Ethics and Legal Issues in Pediatric Healthcare
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