This study is testing an artificial intelligence (AI) chatbot designed to help adults at risk for type 2 diabetes adopt healthier lifestyles. The chatbot provides personalized and culturally tailored guidance on nutrition, physical activity, resistance training, and goal setting. About 30 adults aged 18 to 55 years will use the chatbot for 6 weeks and provide feedback through surveys and interviews.
Researchers will evaluate whether the chatbot is easy to use, helpful, and trustworthy, and whether data about changes in health behaviors can be feasibly collected, in order to inform larger future studies to improve diabetes prevention.
HbA1C of 5.7-6.4%
BMI of 18.5 - 24.9 kg/m²
Fasting plasma glucose 100 - 125 mg/dL
Family history of type 2 diabetes in first-degree relatives (parents, siblings, or children)
Are diagnosed with type 1 or type 2 diabetics
Have uncontrolled hypertension (higher than 160/100 mmHg)
Have cardiovascular disease
Are pregnant or planning to be pregnant
Single group
AI-Powered Diabetes Prevention Chatbot
BehavioralParticipants will use a generative AI chatbot designed to provide personalized, evidence-based diabetes prevention support. The chatbot delivers culturally tailored nutrition and physical activity recommendations, with an emphasis on high-protein dietary strategies, resistance training, goal setting, motivational support, and healthy lifestyle behaviors. Participants will be encouraged to interact with the chatbot at least three times per week during the 6-week study period. Recommendations are generated using expert-validated diabetes prevention content and personalized according to participant characteristics and preferences.
Feasibility and Acceptability: Task completion rate
The proportion of recommended chatbot activities, goals, or behavioral tasks completed by participants during the 6-week intervention period, as assessed through chatbot analytics. This measure will be used to evaluate participant engagement and adherence to chatbot-delivered recommendations.
Feasibility and Acceptability: Conversation length
Average number of messages exchanged between participants and the AI chatbot during each interaction session over the study period. Conversation length will be obtained from chatbot analytics and used as an indicator of participant engagement with the intervention. Longer conversations may reflect greater interaction with chatbot-delivered nutrition, physical activity, and lifestyle coaching content
Feasibility: Body Mass Index (BMI)
Proportion of participants for whom self-reported body mass index (BMI, kg/m²) is successfully collected at baseline and at the end of the 6-week intervention period. BMI will be calculated using participant-reported height and weight collected through study surveys.
Feasibility: Physical Activity Behaviors
Proportion of participants for whom self-reported physical activity behaviors, including engagement in resistance training and overall activity levels, will be successfully collected through study questionnaires and chatbot interaction data.
Feasibility: Dietary Behaviors
Proportion of participants for whom self-reported dietary intake and nutrition-related behaviors, including the adoption of higher-protein dietary practices and other healthy eating behaviors promoted by the chatbot intervention, are successfully collected. Data will be collected through participant surveys and chatbot interaction records.
Feasibility: Behavioral Intention for Diabetes Prevention
Proportion of participants with successfully recorded self-reported intention and readiness to engage in healthy lifestyle behaviors for diabetes prevention, including dietary modifications and physical activity, as assessed through study questionnaires
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Emory University
Lead sponsor
Georgia Center for Diabetes Translation Research
Collaborator
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