Scalable, Clinician-Supervised Generative-AI Food-Chaining Assistant for Pediatric ARFID
Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age3-17
SponsorBoston Children's Hospital
About this trial
Children with Avoidant/Restrictive Food Intake Disorder (ARFID) often lack access to specialty dietitians, and scalable nutritional guidance/food chaining tools are currently not available. The investigators will evaluate a web-based, clinician-supervised, generative-AI assistant that produces individualized food-chaining plans.
Develop an AI assistant that generates ≥15 allergy-safe, evidence-based chaining steps per participant and meets ≥90 % expert agreement for safety/appropriateness.
Validate the assistant against gold-standard clinician recommendations (Cohen's κ ≥ 0.80).
Test clinical impact in a three-month pilot RCT (n = 96) by comparing change in Nine-Item ARFID Screen (NIAS) scores between intervention and usual-care groups.
Hypothesis: AI-generated plans will reduce NIAS scores by ≥3 points relative to controls.
Eligibility criteria
Qualifiers
Children must be aged 3-17 years
Children must have caregiver- or participant-reported DSM-5 ARFID diagnosis and/or EDYQ-screen-positive Avoidant Restrictive Food Intake Disorder
English proficiency.
Disqualifiers
Lack of English proficiency [As there is no validated non-English version of the NIAS, we must exclude caregivers who do not have English proficiency]
Participants must not have been previously treated at Boston Children's for ARFID
Trial design
Treatments tested in this trial
- Generative AI-based food chaining device
Treatment groups
125 Participants
are divided into 2 treatment groupsLocations
Sponsors and collaborators
Source ClinicalTrials.gov