Evidence map›Paper›PMID 41878376›Full record

ArticleFrontiers in digital health2026

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

Mana Hanzawa, Joe Hasei, Ayumi Okada, Chie Tanaka, Yoshie Shigeyasu, Chikako Fujii, Makiko Horiuchi, Akiko Sugihara, Koichi Takeuchi, Ryuichi Nakahara and 4 more

Abstract read
In one paragraph

Article in Frontiers in digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Mana HanzawaDepartment of Pediatrics, Okayama University Hospital Medical Center for Children, Okayama, Japan.
Joe HaseiDepartment of Medical Informatics and Clinical Support Technology Development, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan.
Ayumi OkadaDepartment of Pediatrics, Okayama University Hospital Medical Center for Children, Okayama, Japan.
Chie TanakaDepartment of Pediatrics, Okayama University Hospital Medical Center for Children, Okayama, Japan.
Yoshie ShigeyasuDepartment of Pediatrics, Okayama University Hospital Medical Center for Children, Okayama, Japan.
Chikako FujiiDepartment of Pediatrics, Okayama University Hospital Medical Center for Children, Okayama, Japan.
Makiko HoriuchiClinical Psychology Section, Department of Medical Support, Okayama University Hospital, Okayama, Japan.
Akiko SugiharaDepartment of Pediatrics, Okayama University Hospital Medical Center for Children, Okayama, Japan.
Koichi TakeuchiLife Natural Science and Technology, Graduate School of Environmental, Okayama University, Okayama, Japan.
Ryuichi NakaharaDepartment of Musculoskeletal Health Promotion, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan.
Hideki KatayamaDepartment of Palliative and Supportive Care, Okayama University Hospital, Okayama, Japan.
Yasushi TakahashiNEC Corporation, Tokyo, Japan.
Toshifumi OzakiDepartment of Orthopaedic Surgery, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan.
Hirokazu TsukaharaDepartment of Pediatrics, Okayama University Hospital Medical Center for Children, Okayama, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

anorexia nervosacaregiver burdenfamily-based treatmentfamily supportgenerative AI agentlarge language modelretrieval-augmented generation

Identifiers

PMID41878376
PMCPMC13006915

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.