NCT07514312

Sustainable and AI-Enabled Adolescents and Youth-Centred Interventions to Upgrade Food Choices and Promote Healthy, Sustainable Diets

AI-Supported, Context-Aware Digital Nudging Intervention to Reduce Ultra-Processed Food Consumption and Improve Dietary Sustainability Among Adolescents and Young Adults (STAY-UP)

• Status: Not Yet Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 1,000 (estimated)
• Sponsor: Istanbul Gelisim University · Academic / Other
• Sex: All
• Age: 12 Years – 25 Years
• Healthy volunteers: Accepted

Summary

This study aims to evaluate the effectiveness of an artificial intelligence (AI)-supported, context-aware digital nudging intervention designed to reduce ultra-processed food consumption and improve dietary sustainability among adolescents and young adults. The intervention utilizes real-time behavioral data, including image-assisted dietary logging and contextual information, to identify high-risk consumption moments and deliver personalized, non-coercive nudges. The study will assess changes in ultra-processed food intake, contextual consumption patterns, and sustainability-related dietary indicators.

Detailed description

This study investigates the effectiveness of an artificial intelligence (AI)-supported, context-aware digital intervention targeting ultra-processed food (UPF) consumption among adolescents and young adults. UPF consumption has been identified as a major contributor to non-communicable diseases and is associated with significant environmental impacts. However, existing digital nutrition interventions largely rely on static, nutrient-based approaches and do not adequately capture real-life behavioral contexts. The intervention integrates image-assisted dietary logging, contextual data collection (including time, location, and social setting), and explainable artificial intelligence to identify high-risk moments of UPF consumption. Based on these insights, the system delivers adaptive, personalized digital nudges designed to support healthier and more sustainable food choices without restricting user autonomy. The study follows a controlled evaluation design to assess the effectiveness of the intervention. Primary outcomes include changes in context-specific UPF consumption patterns, while secondary outcomes include overall dietary quality, sustainability-related indicators (such as environmental impact proxies), and user engagement metrics. This research aims to provide evidence for scalable, ethically governed digital health interventions that integrate behavioral science, nutrition, and sustainability within real-life settings

Conditions

• Ultra-Processed Food Consumption
• Obesity Prevention
• Dietary Behaviour
• Unhealthy Diet
• Non-Communicable Chronic Diseases

Interventions

Type	Name	Description
BEHAVIORAL	Artificial intelligence-supported digital nudging	A context-aware digital intervention delivering personalized nudges based on real-time dietary behavior and contextual data to reduce ultra-processed food consumption.

Timeline

• Start date: 2026-09-16
• Primary completion: 2027-12-30
• Completion: 2028-06-30
• First posted: 2026-04-07
• Last updated: 2026-04-07