Hospitalized Children

Severe bacterial infections are a worldwide scourge. However, the epidemiology of this type of infection varies over time. It is therefore essential to monitor them in order to prevent them more effectively. At this time, in France, no monitoring exists for this kind of infections.

This study examines how different robot dialogue systems (rule-based vs. large language model-based) and content types (emotional support vs. safety education) affect pediatric patients' responses during hospital-based robot-mediated interventions. Approximately 60 pediatric patients aged 2-9 years will be randomly assigned to interact with a social robot (LIKU) using either rule-based or LLM-based dialogue. Each child will participate in two activity sessions (emotional content and safety content) in randomized order. Primary outcomes include child engagement, emotional responses, robot perception, and activity preferences, assessed through standardized questionnaires (UEQ, Godspeed), child interviews, and behavioral observations. Additionally, 5 experts will evaluate content appropriateness and safety. This pilot study aims to provide foundational data for developing personalized pediatric robot programs in hospital settings, optimizing both dialogue approaches and content design based on individual child characteristics.

This multi-center quality improvement project aims to enhance gastric tube placement practices for children by systematically reviewing the latest evidence. The project team will identify gaps between current practices and best evidence, analyze barriers to implementing evidence-based guidelines, and develop strategies to facilitate their integration into clinical settings. The focus will also be on improving the knowledge and skills of pediatric nurses through targeted education and support. Ultimately, this initiative seeks to ensure the safety and effectiveness of gastric tube placement in the pediatric population, leading to better patient outcomes and higher standards of care.