Improving Diabetes Education and Metabolic Control in Children Using Social Robots: A Randomized Trial

Robot engagement in healthcare has the potential to alleviate medical personnel workload while improving efficiency in managing various health conditions. This study evaluates the impact of robot-assisted education on knowledge acquisition and metabolic control in children with Type 1 Diabetes Mellitus (T1DM) compared to traditional education methods. A randomized controlled trial was conducted at the pediatric diabetes clinic of the University of Tabuk Medical Center, Saudi Arabia. Thirty children aged 5–15 years with T1DM were randomly divided into two groups: the robot education (intervention) group and the control education group. Both groups participated in six weekly one-hour educational sessions, with the intervention group interacting with a Pepper robot assistant and the control group receiving education from a qualified diabetes educator nurse. Knowledge was assessed using a 12-item questionnaire before and after the intervention, while metabolic control was evaluated through weekly mean home blood glucose measurements and HbA1c levels before and three months post intervention. The intervention group demonstrated a significantly greater improvement in knowledge scores compared to the control group (p < 0.05). Weekly mean blood glucose levels were consistently lower in the intervention group throughout the study period (p < 0.05 for all samples). Both groups showed a reduction in HbA1c levels after three months, with the intervention group exhibiting a greater mean decrease. The engagement of the Pepper robot in T1DM education for children resulted in improved knowledge acquisition and better metabolic control compared to traditional education methods. This approach may establish a foundation for “learning by interacting with robots” in long-term diabetes management. Further research with larger sample sizes and longer follow-up periods is warranted to confirm these findings and explore the long-term benefits of robot-assisted education in pediatric diabetes care.