Artificial Intelligence and Digital Therapy for Adolescent Mental Health in the UK: Opportunities, Barriers and Ethical Consideration
Kelechi Nelson ADINDU
*
School of Allied and Public Health, University of Chester, England.
Nnaemeka AKUBUE
School of Allied and Public Health, University of Chester, England.
Nnorom Obioma JUDE
Department of General Medicine, Holt Doctors/Royal Stoke University Hospital, England.
Ademola ONAKOYA
Department of Primary Care, Old Catton Medical Practice (NHS), England.
Chisom CHUKWUNONYE
Department of General Medicine, Betsi Cadwaladr University Health Board, Wales.
Oisedebame ODION
Department of General Practice, NHS Education, England.
Chinelo Grace OKENGWU
Department of General Medicine, The Royal Shrewsbury and Telford (NHS), England.
Nwudele Uchechukwu
Accident and Emergency Department, Doncaster Royal Infirmary, England.
Philip Zikora OSITA-OBASI
Department of General Medicine, EMEL Hospital, Nigeria.
Adanna EZIKE
Department of Geriatrics, NHS Forth Valley, England.
Ismail BELLO
Department of General Medicine, St. Helens and Knowsley University Teaching Hospital NHS Foundation Trust, England.
Emmanuella OLENLOA
School of Allied and Public Health, University of Chester, United Kingdom.
Oghenevbede Ogaga ERUTEYA
School of Allied and Public Health, University of Chester, United Kingdom.
Sherriff Abiodun OYEWOLE
Department of Nursing, Impression Health and Support LTD, United Kingdom.
*Author to whom correspondence should be addressed.
Abstract
Background: Adolescence constitutes a critical developmental stage marked by the onset of mental health difficulties, yet timely access to effective mental health care remains a significant challenge for many adolescents in the United Kingdom (UK). Artificial intelligence (AI)-enabled digital therapies present innovative opportunities to address these gaps.
Objective: This systematic review critically assesses current evidence on AI-driven digital interventions for adolescent mental health within the UK, highlighting their potential opportunities, barriers to implementation, and pertinent ethical considerations.
Methods: Employing a mixed-methods design, a systematic literature review adhering to PRISMA guidelines was combined with thematic analysis of semi-structured interviews. Comprehensive database searches (MEDLINE, PsycINFO, Web of Science; 2013–2023) targeted studies involving UK adolescents (ages 11–19) using AI-based mental health technologies. Included studies underwent rigorous quality appraisal (Cochrane RoB 2.0, ROBINS-I, CASP). Additional insights were gathered through stakeholder interviews (clinicians, AI developers, adolescent users).
Results: Twenty-seven studies met inclusion criteria, investigating interventions such as AI chatbots, predictive analytics, mobile apps, and virtual environments targeting anxiety and depression. Key opportunities identified include enhanced accessibility for underserved populations, personalization through adaptive algorithms, proactive early-risk detection, scalability, cost-efficiency, and improved engagement via interactive interfaces. Significant implementation barriers encompassed technical infrastructure limitations, data security concerns, insufficient longitudinal efficacy data, socioeconomic disparities, and clinician scepticism. Ethical challenges emphasized informed consent, algorithm transparency, potential biases, unclear accountability, and clinician deskilling risks.
Conclusions: AI-driven digital interventions offer substantial promise for augmenting adolescent mental health services in the UK. However, realizing their full potential necessitates addressing infrastructural, ethical, and evidentiary challenges through robust governance frameworks and continued rigorous research.
Keywords: Adolescent mental health, artificial intelligence, digital therapy, accessibility, ethics