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ID 70756
フルテキストURL
著者
Hanzawa, Mana Department of Pediatrics, Okayama University Hospital Medical Center for Children
Hasei, Joe Department of Medical Informatics and Clinical Support Technology Development, Faculty of Medicine, Dentistry and Pharmaceutical Sciences
Okada, Ayumi Department of Pediatrics, Okayama University Hospital Medical Center for Children
Tanaka, Chie Department of Pediatrics, Okayama University Hospital Medical Center for Children
Shigeyasu, Yoshie Department of Pediatrics, Okayama University Hospital Medical Center for Children
Fujii, Chikako Department of Pediatrics, Okayama University Hospital Medical Center for Children
Horiuchi, Makiko Clinical Psychology Section, Department of Medical Support, Okayama University Hospital
Sugihara, Akiko Department of Pediatrics, Okayama University Hospital Medical Center for Children
Takeuchi, Koichi Life Natural Science and Technology, Graduate School of Environmental, Okayama University Kaken ID publons researchmap
Nakahara, Ryuichi Department of Musculoskeletal Health Promotion, Faculty of Medicine, Dentistry and Pharmaceutical Sciences
Katayama, Hideki Department of Palliative and Supportive Care, Okayama University Hospital
Takahashi, Yasushi NEC Corporation
Ozaki, Toshifumi Department of Orthopaedic Surgery, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University Kaken ID publons researchmap
Tsukahara, Hirokazu Department of Pediatrics, Okayama University Hospital Medical Center for Children Kaken ID publons researchmap
抄録
Introduction: Family-based treatment (FBT) is a first-line psychotherapy for children and adolescents with anorexia nervosa (AN). However, families must understand the principles of FBT, provide meal support, and manage their children's pathological behaviors. Difficulties occur outside clinic hours when it is impossible to consult professionals. This “support gap” increases caregivers’ psychological distress and threatens their treatment continuity. To the best of our knowledge, this is the first domain-specific generative artificial intelligence (AI) agent designed to provide situation-specific, FBT-concordant advice and psychological support.
Methods: The system integrates three components: (1) an FBT-specific knowledge base constructed from treatment manuals, family guides, guideline-compliant resources, and a clinical Q&A corpus; (2) a multistage natural language processing pipeline using Retrieval-Augmented Generation (RAG), with intent and sentiment analyses; and (3) safety guardrails that prohibit unsolicited numerical goals or direct hospitalization recommendations and standardized escalation to clinicians. When strong negative emotions are detected, empowerment messages are dynamically incorporated to maintain caregivers’ confidence. Six clinicians with expertise with pediatric mental health authored queries that simulated common FBT-related concerns and evaluated each response for clinical appropriateness and safety, and classified problems as information insufficiency, not FBT concordant, or escalation insufficiency.
Results: Of the 477 queries, 57.0% were FBT-related, 24.5% were general AN, 16.5% were parental psychological distress, and 1.8% were related to other topics. The clinically appropriate response rate was 91.6% (437/477), including 92.3% for FBT-related questions, 88.0% for general knowledge, 93.7% for psychological distress, and 100.0% for other questions. Clinically inappropriate responses (8.4%) were mainly attributable to information insufficiency; not FBT concordant (1.8% of FBT-related responses) and escalation insufficiency (0.6% of all dialogs) rarely occurred.
Discussion: 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.
キーワード
anorexia nervosa
caregiver burden
family support
family-based treatment
generative AI agent
large language model
retrieval-augmented generation
発行日
2026-03-09
出版物タイトル
Frontiers in Digital Health
8巻
出版者
Frontiers Media SA
開始ページ
1759690
ISSN
2673-253X
資料タイプ
学術雑誌論文
言語
英語
OAI-PMH Set
岡山大学
著作権者
© 2026 Hanzawa, Hasei, Okada, Tanaka, Shigeyasu, Fujii, Horiuchi, Sugihara, Takeuchi, Nakahara, Katayama, Takahashi, Ozaki and Tsukahara.
論文のバージョン
publisher
PubMed ID
DOI
Web of Science KeyUT
関連URL
isVersionOf https://doi.org/10.3389/fdgth.2026.1759690
ライセンス
https://creativecommons.org/licenses/by/4.0/
Citation
Hanzawa M, Hasei J, Okada A, Tanaka C, Shigeyasu Y, Fujii C, Horiuchi M, Sugihara A, Takeuchi K, Nakahara R, Katayama H, Takahashi Y, Ozaki T and Tsukahara H (2026) Development of a generative AI agent for family support in implementing family-based treatment for children and adolescents with anorexia nervosa. Front. Digit. Health 8:1759690. doi: 10.3389/fdgth.2026.1759690
助成情報
( 公益財団法人明治安田こころの健康財団 / Meiji Yasuda Mental Health Foundation )
( 公益財団法人三島海雲記念財団 / Mishima Kaiun Memorial Foundation )
PSI2025_S2B71: ( 国立研究開発法人科学技術振興機構 / Japan Science and Technology Agency )
( 公益財団法人橋本財団 / Hashimoto Foundation Inc. )