Development of a generative AI agent for family support in implementing family-based treatment for children and adolescents with anorexia nervosa

In this expert review, the safety-gated RAG system predominantly generated FBT-concordant responses that provided meal-level guidance and empathic empowerment-oriented support to families. By proceduralizing complex FBT concepts and presenting multiple response options for pathological behaviors, the system translates FBT principles into practical guidance supporting refeeding adherence, preserving family self-efficacy, and suggesting that domain-specific AI may help bridge structural limitations in FBT. Usability studies and randomized controlled trials are warranted to determine their impact on caregiver burden, self-efficacy, treatment adherence, and clinical outcomes.

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Publication Details

Journal
Frontiers in Digital Health
Published
2026-03-09
DOI
https://doi.org/10.3389/fdgth.2026.1759690
Primary Topic
Digital Mental Health Interventions
Type
article
Field-Weighted Citation Impact
0.00

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article

Development of a generative AI agent for family support in implementing family-based treatment for children and adolescents with anorexia nervosa

Toshifumi Ozaki, Makiko Horiuchi, Chie Tanaka, Joe Hasei et al.
Frontiers in Digital Health
Digital Mental Health Interventions
article

Development of a generative AI agent for family support in implementing family-based treatment for children and adolescents with anorexia nervosa

Toshifumi Ozaki, Makiko Horiuchi, Chie Tanaka, Joe Hasei, Chikako Fujii, Hirokazu Tsukahara, Ayumi Okada, Akiko Sugihara, Yuya Takahashi, Ryuichi Nakahara, Hideki Katayama, Mana Hanzawa, Koichi Takeuchi, Yoshie Shigeyasu
article en

Abstract

In this expert review, the safety-gated RAG system predominantly generated FBT-concordant responses that provided meal-level guidance and empathic empowerment-oriented support to families. By proceduralizing complex FBT concepts and presenting multiple response options for pathological behaviors, the system translates FBT principles into practical guidance supporting refeeding adherence, preserving family self-efficacy, and suggesting that domain-specific AI may help bridge structural limitations in FBT. Usability studies and randomized controlled trials are warranted to determine their impact on caregiver burden, self-efficacy, treatment adherence, and clinical outcomes.

Frontiers in Digital HealthVol. 8
Okayama University of Science (JP), Okayama University (JP), Notre Dame Seishin University (JP), Okayama University Hospital (JP), Institute for Musculoskeletal Health (AU), Okayama Medical Center (JP), Tohoku Medical and Pharmaceutical University (JP)
Mishima Kaiun Memorial Foundation, Japan Science and Technology Agency
Openalex Percentile: Top 36%
Digital Mental Health Interventions
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