Peer-reviewed article
Digital Humanities in Child and Adolescent Mental Health Services: A Review.
Hong S, Walton B, Kim HW ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This scoping review examines how digital humanities approaches have been integrated into artificial intelligence systems used in mental health services for children and adolescents. The review of 17 studies identified six key themes: engagement, participatory co-design, human oversight, equity, ethical governance, and implementation. The findings suggest that humanities-informed approaches lead to greater attention to relational engagement, stakeholder participation, transparency, and culturally responsive implementation. The review concludes that integrating humanities perspectives into AI-enabled youth mental health interventions may create systems that are more ethical, equitable, and developmentally appropriate.
Key points
- Six recurring themes emerged across reviews: engagement, participatory co-design, human oversight, equity, ethical governance, and implementation
- Humanities-informed approaches were associated with greater attention to relational engagement and stakeholder participation
- Evidence supporting intervention effectiveness was strongest in systematic reviews and meta-analyses
- Findings related to ethics, governance, equity, and implementation were primarily from scoping reviews and conceptual syntheses
- The current evidence base remains heterogeneous and future research should evaluate these approaches through empirical implementation studies
Limitations
This is a scoping review of reviews rather than an evaluation of a specific intervention, so it does not provide direct evidence of which AI-enabled interventions are most effective for children's mental health. The review acknowledges that the evidence base is heterogeneous and does not establish causal links between humanities-informed design and improved outcomes.
Abstract
Background/objectives Artificial intelligence (AI) is increasingly used in youth mental health services, including clinical decision support, risk prediction, and digital therapeutics. However, existing frameworks provide limited guidance for integrating ethical, cultural, and relational considerations into the design, governance, and implementation of AI-enabled mental health technologies. This scoping review examined how digital humanities-informed approaches have been incorporated into AI-supported mental health interventions for children and adolescents. Methods A scoping review was conducted following the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guidelines. Peer-reviewed literature published between 2015 and 2025 was searched using PubMed and supplemented by semantic searches through Elicit. Systematic reviews, scoping reviews, and meta-analyses examining AI-enabled digital mental health interventions and digital humanities perspectives were included. Data were synthesized using inductive thematic analysis. Results Seventeen review-level studies met the inclusion criteria. Six recurring themes were identified: engagement, participatory co-design, human oversight, equity, ethical governance, and implementation. Across the included reviews, humanities-informed approaches were associated with greater attention to relational engagement, stakeholder participation, transparency, contextual adaptation, and culturally responsive implementation. Evidence supporting intervention effectiveness was strongest in systematic reviews and meta-analyses, whereas findings related to ethics, governance, equity, and implementation were derived primarily from scoping reviews and conceptual syntheses. Conclusions This review suggests that digital humanities provides a valuable interdisciplinary perspective for informing the design, governance, and implementation of AI-enabled youth mental health interventions. Although the current evidence base remains heterogeneous, integrating humanities-informed approaches may support the development of AI systems that are more ethical, equitable, and developmentally responsive. Future research should evaluate these approaches through empirical implementation studies and emerging generative AI applications.