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NCT Number: NCT07514312

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

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.

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Key information

Conditions

Ultra-Processed Food Consumption Dietary Behaviour Disease Attributes Non-Communicable Chronic Diseases Noncommunicable Diseases Obesity Prevention Pathologic Processes Pathological Conditions, Signs and Symptoms Unhealthy Diet

Age range

12 year–25 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

About this study

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

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Adolescents aged 12 to 25 years
  • Ownership of a smartphone or regular access to a digital device
  • Ability to use the digital intervention platform
  • Willingness to provide informed consent (and parental consent where applicable)
  • Regular consumption of ultra-processed foods at baseline

Exclusion criteria

  • Presence of medical conditions requiring a specific therapeutic diet
  • Participation in another dietary or behavioral intervention study
  • Severe cognitive or psychological conditions that may impair participation
  • Inability to use digital tools or applications

Treatment and study plan

Artificial intelligence-supported digital nudging

Behavioral

A context-aware digital intervention delivering personalized nudges based on real-time dietary behavior and contextual data to reduce ultra-processed food consumption.

Primary outcomes

  1. Change in ultra-processed food consumption (servings per day)

    Time frame: From baseline to 10 months and 20 months

    Change in ultra-processed food consumption, expressed as servings per day, assessed using dietary intake data collected via a digital dietary assessment platform (food diary-based tracking system). Consumption will be quantified based on reported frequency and portion size.

Secondary outcomes

  1. Change in frequency of ultra-processed food consumption (times per day)

    Time frame: From baseline to 10 months and 20 months

    Change in the frequency of ultra-processed food consumption, expressed as times per day, assessed using a digital dietary tracking platform (food diary-based system).

  2. Change in proportion of ultra-processed food consumption (% of total intake)

    Time frame: From baseline to 10 months and 20 months

    Change in the proportion of ultra-processed food consumption, expressed as percentage of total dietary intake, derived from dietary tracking data collected via a digital dietary assessment platform.

  3. Change in temporal eating patterns (eating occasions per day and timing)

    Time frame: From baseline to 10 months and 20 months

    Change in temporal eating patterns, including number of eating occasions per day and timing of meals, assessed using time-stamped dietary records collected via a digital dietary tracking platform.

  4. Change in context-specific dietary behaviours (categorical variables)

    Time frame: From baseline to 10 months and 20 months

    Change in context-specific dietary behaviours, including eating location and social context, assessed as categorical variables using data recorded via a digital dietary tracking platform.

Study contacts

Contact information is provided by the study sponsor or research team.

Arda OZTURKCAN, PhD

CONTACT

[email protected]

05356068687

HATİCE MERVE BAYRAM, PhD

CONTACT

[email protected]

+905549915658

Sponsors and collaborators

Lead sponsor

Istanbul Gelisim University

Other

Registry information

Official study title

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

Acronym: STAY-UP

Important dates

Study start
2026
Primary completion
2027
Study completion
2028
First posted
Apr 7, 2026
Registry last updated
Apr 7, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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