Large Language Model-Driven Personalization of Virtual Reality Interventions to Improve Pediatric Inpatient Experience and Reduce Needle Anxiety

Overview

Hospitalization strips pediatric patients of the environments, objects, and people that shape their daily lives. Hospitalized pediatric patients routinely experience painful procedures, psychological distress, boredom, and a disorienting loss of personal identity. These experiences measurably worsen anxiety, reduce cooperation with care, and diminish the quality of the inpatient experience for both patients and families.1-7 Immersive digital interventions, including VR and tablet-based experiences, have emerged as a promising class of tools for addressing these challenges. Prior studies from The Stanford Chariot Program have demonstrated that digitally delivered, patient-centered experiences can meaningfully reduce procedural anxiety and improve engagement in hospitalized children.8-12 Yet, an important limitation persists in these technologies - current digital interventions largely remain in one-size-fits-all formats. Every child receives the same content, regardless of who they are, what they love, or what makes them feel at home in the world. This design limits therapeutic relevance, constrains engagement, and represents a missed opportunity to engage children, reduce anxiety, and enhance their quality of life during hospital stays.

Conditions