[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100593478":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":18,"centralContacts":24,"locations":18,"responsibleParty":30,"collaborators":18,"id":34,"slug":35,"hasResults":36,"nctId":37,"briefTitle":38,"officialTitle":39,"acronym":18,"eligibilityCriteria":40,"healthyVolunteers":36,"sex":41,"minAge":42,"maxAge":43,"enrollmentInfo":44,"targetDuration":18,"studyType":47,"phases":48,"briefSummary":50,"conditions":51,"keywords":53,"overallStatus":57,"whyStopped":18,"lastUpdateSubmitDate":58,"lastUpdatePostDateStruct":59,"startDateStruct":62,"completionDateStruct":64,"leadSponsor":66,"locationsCount":18},{"fullName":5,"class":6},"Boston Children's Hospital","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Intervention","EXPERIMENTAL","Arm 1 participants will be provided with 15 food chaining recommendations based on individual child dietary preferences, and will be assessed at the one month point to identify the number of food chaining interventions that have been undertaken and the number of recommendations that have been successful, along with a follow-up NIAS survey to determine differences in pre- and post-intervention ARFID severity. Arm 1 participants will exit the study at this point.",[13],"Other: Generative AI-based food chaining device",{"label":15,"type":16,"description":17,"interventionNames":18},"Control","NO_INTERVENTION","Arm 2 participants at the time of enrollment will not be provided food chaining recommendations, but will be assessed at the one month point to identify the number of food chaining interventions\u002Fnew foods that have been introduced, along with a follow-up NIAS survey to determine baseline ARFID severity. At the one month point, Arm 2 participants will be provided with 15 food chaining recommendations based on individual child dietary preferences, and will be assessed after one month to identify the number of food chaining interventions that have been undertaken and the number of recommendations that have been successful, along with a follow-up NIAS survey to determine differences in pre- and post-intervention ARFID severity. Arm 2 participants will exit the study at this point.",null,[20],{"type":6,"name":21,"description":22,"armGroupLabels":23,"otherNames":18},"Generative AI-based food chaining device","Our group has developed the only generative-AI tool that produces allergy-safe food-chaining recommendations, but it has not yet been clinically tested. This proposal builds on that proof of concept to evaluate its effectiveness in a broader pediatric ARFID population.",[9],[25],{"name":26,"role":27,"phone":28,"phoneExt":18,"email":29},"PAUL CROWLEY, MD","CONTACT","16177106519","paul.crowley@childrens.harvard.edu",{"type":31,"investigatorFullName":32,"investigatorTitle":33,"investigatorAffiliation":5,"oldNameTitle":18,"oldOrganization":18},"PRINCIPAL_INVESTIGATOR","Paul Crowley","Attending Gastroenterologist, Instructor in Pediatrics","100593478","scalable-clinician-supervised-generative-ai-food-chaining-assistant-for-pediatric-arfid-100593478",false,"NCT07006961","Scalable, Clinician-Supervised Generative-AI Food-Chaining Assistant for Pediatric ARFID","Scalable, Clinician-Supervised Generative-AI Food-Chaining Assistant for Pediatric ARFID: A Pilot Randomized Controlled Trial","Inclusion Criteria:\n\n* Children must be aged 3-17 years\n* Children must have caregiver- or participant-reported DSM-5 ARFID diagnosis and\u002For EDYQ-screen-positive Avoidant Restrictive Food Intake Disorder\n* English proficiency.\n\nExclusion Criteria:\n\n* 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\\]\n* Participants must not have been previously treated at Boston Children's for ARFID","ALL","3 Years","17 Years",{"count":45,"type":46},125,"ESTIMATED","INTERVENTIONAL",[49],"NA","Children with Avoidant\u002FRestrictive Food Intake Disorder (ARFID) often lack access to specialty dietitians, and scalable nutritional guidance\u002Ffood chaining tools are currently not available. The investigators will evaluate a web-based, clinician-supervised, generative-AI assistant that produces individualized food-chaining plans.\n\nDevelop an AI assistant that generates ≥15 allergy-safe, evidence-based chaining steps per participant and meets ≥90 % expert agreement for safety\u002Fappropriateness.\n\nValidate the assistant against gold-standard clinician recommendations (Cohen's κ ≥ 0.80).\n\nTest 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.\n\nHypothesis: AI-generated plans will reduce NIAS scores by ≥3 points relative to controls.",[52],"Avoidant Restrictive Food Intake Disorder",[54,55,56],"ARFID","artificial intelligence","food chaining","NOT_YET_RECRUITING","2025-06-04",{"date":60,"type":61},"2025-06-06","ACTUAL",{"date":63,"type":46},"2025-06-15",{"date":65,"type":46},"2025-10-31",{"name":5,"class":6}]