Artificial intelligence in the treatment of eating disorders in teenagers: a novel approach to outpatient care

Background: Eating disorders are serious psychiatric conditions that disproportionately affect adolescents. Although multidisciplinary approaches incorporating psychotherapy, nutritional guidance, and family involvement are recommended, outpatient treatment presents challenges in monitoring nutritional intake across school, social, and home environments. Artificial intelligence (AI) may extend individualized support beyond traditional clinical encounters. Case presentation This report presents a case study of an adolescent girl with anorexia nervosa receiving outpatient psychotherapy, nutritional counseling, and family involvement. An AI-assisted intervention using ChatGPT was implemented through a shared platform involving the patient, parent, and registered dietitian. The dietitian established individualized nutritional parameters and provided instructions regarding appropriate recommendations and language. The AI provided real-time meal and snack guidance using food-neutral language while avoiding discussion of calories, macronutrients, measurements, or quantities. The dietitian maintained oversight of the platform and monitored recommendations created alongside a licensed psychologist. Discussion The AI-assisted approach demonstrated potential feasibility as an adjunct to multidisciplinary outpatient eating disorder treatment. The intervention provided individualized, real-time guidance while reducing reliance on calorie counting and food measurement, which contributes to eating-disorder behaviors and cognitive rumination. The shared-access model allowed the dietitian to monitor progress and maintain fidelity with the treatment. This approach may extend nutritional support into patients' natural environments between clinical appointments. Conclusion AI-assisted interventions may enhance individualized treatment for adolescents with eating disorders. However, this case study cannot establish efficacy, safety, or long-term outcomes. Larger studies are needed to evaluate nutritional outcomes, symptoms, adherence, safety, and risks. AI should complement, rather than replace, multidisciplinary clinical care.