Ultra-Processed Food ConsumptionSTAY-UPNCT07514312
Sustainable and AI-Enabled Adolescents and Youth-Centred Interventions to Upgrade Food Choices and Promote Healthy, Sustainable Diets
A study testing Artificial intelligence-supported digital nudging in people with Ultra-Processed Food Consumption and Obesity Prevention, run by Istanbul Gelisim University.
Trial 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. Read more about this study
- Who is it for?
- Ages 12 to 25 yearsHealthy volunteers can take part
- Conditions the study is for
- Ultra-Processed Food Consumption, Obesity Prevention, Dietary Behaviour
- What is being tested?
- Artificial intelligence-supported digital nudging
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 1,000 participants
- Where
- No sites listed yet
- Study dates
- 16 Sep 2026to 30 Jun 2028
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 12 to 25 years
- All sexes
- Healthy volunteers accepted
- Child, Adult
Who may be able to join
- 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
Who cannot join
- 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
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
Official 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)
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.
Read the 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
- Being tested
- Artificial intelligence-supported digital nudging
- Keywords
- Ultra-Processed Food, Digital Intervention, Artificial Intelligence, Dietary Behavior, Adolescents, Young Adults, Nutrition, Sustainability, non-communicable disease
- Medical subject headings
- Noncommunicable Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial intelligence-supported digital nudgingBehavioural
A context-aware digital intervention delivering personalized nudges based on real-time dietary behavior and contextual data to reduce ultra-processed food consumption.
| Study group | Role | What they receive |
|---|---|---|
| Intervention group (artificial intelligence-supported, context-aware digital nudging intervention) | Experimental | Participants receive an artificial intelligence (AI)-supported, context-aware digital nudging intervention designed to reduce ultra-processed food (UPF) consumption. The system uses real-time dietary and contextual data to deliver personalized behavioural prompts. Receives: Behavioral: Artificial intelligence-supported digital nudging |
| Control group (Digital platform without nudging) | No intervention | Participants have access to the digital platform without active nudging components. No personalized behavioural prompts are delivered. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change in ultra-processed food consumption (servings per day)
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.
Measured: From baseline to 10 months and 20 months
Secondary outcomes (4)
Change in frequency of ultra-processed food consumption (times per day)
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).
Measured: From baseline to 10 months and 20 months
Change in proportion of ultra-processed food consumption (% of total intake)
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.
Measured: From baseline to 10 months and 20 months
Change in temporal eating patterns (eating occasions per day and timing)
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.
Measured: From baseline to 10 months and 20 months
Change in context-specific dietary behaviours (categorical variables)
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.
Measured: From baseline to 10 months and 20 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Apr 2026
- Study start16 Sep 2026 (estimated)
- Primary completion30 Dec 2027 (estimated)
- Study completion30 Jun 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Ultra-Processed Food ConsumptionStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Prevention
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 1,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Istanbul Gelisim University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Hatice Merve Bayram, Istanbul Gelisim University
- Investigators
- Elena Milli, PhD, Study chair, Polo Europeo della Conoscenza - Istituto Comprensivo di Bosco ChiesanuovaStefano Cobello, PhD, Study chair, Polo Europeo della Conoscenza - Istituto Comprensivo di Bosco Chiesanuova
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07514312
- Sponsor's protocol ID
- STAYUP-IGU-2026-CT01
- Acronym
- STAY-UP
- Status last verified
- Mar 2026
- First submitted
- 21 Mar 2026
- Last updated
- 7 Apr 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 7 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official 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)
- ClinicalTrials.gov ID
- NCT07514312
- Acronym / sponsor ID
- STAY-UP / STAYUP-IGU-2026-CT01
- Conditions
- Ultra-Processed Food Consumption, Obesity Prevention, Dietary Behaviour, Unhealthy Diet, Non-Communicable Chronic Diseases
- Keywords
- Ultra-Processed Food, Digital Intervention, Artificial Intelligence, Dietary Behavior, Adolescents, Young Adults, Nutrition, Sustainability
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 1,000 participants (estimated)
- Lead sponsor
- Istanbul Gelisim UniversityUniversity, hospital or other
- Study start
- 16 Sep 2026 (estimated)
- Primary completion
- 30 Dec 2027 (estimated)
- Study completion
- 30 Jun 2028 (estimated)
- First posted
- 7 Apr 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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
Study design
- Primary purpose
- Prevention
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Intervention group (artificial intelligence-supported, context-aware digital nudging intervention) | Experimental | Behavioral: Artificial intelligence-supported digital nudgingParticipants receive an artificial intelligence (AI)-supported, context-aware digital nudging intervention designed to reduce ultra-processed food (UPF) consumption. The system uses real-time dietary and contextual data to deliver personalized behavioural prompts. |
| Control group (Digital platform without nudging) | No intervention | –Participants have access to the digital platform without active nudging components. No personalized behavioural prompts are delivered. |
Who may qualify
- Ages
- 12 to 25 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult
Key inclusion criteria (5 listed)
- 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
Key exclusion criteria (4 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Artificial intelligence-supported digital nudgingA context-aware digital intervention delivering personalized nudges based on real-time dietary behavior and contextual data to reduce ultra-processed food consumption. | Behavioural | Intervention group (artificial intelligence-supported, context-aware digital nudging intervention) |
Primary outcome
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.
4 secondary outcomes
Change in frequency of ultra-processed food consumption (times per day)
Time frame: From baseline to 10 months and 20 months
Change in proportion of ultra-processed food consumption (% of total intake)
Time frame: From baseline to 10 months and 20 months
Change in temporal eating patterns (eating occasions per day and timing)
Time frame: From baseline to 10 months and 20 months
Change in context-specific dietary behaviours (categorical variables)
Time frame: From baseline to 10 months and 20 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 Apr 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Elena Milli, PhD study chair
Polo Europeo della Conoscenza - Istituto Comprensivo di Bosco Chiesanuova
Stefano Cobello, PhD study chair
Polo Europeo della Conoscenza - Istituto Comprensivo di Bosco Chiesanuova
Questions about this trial
What is this clinical trial studying?
A study testing Artificial intelligence-supported digital nudging in people with Ultra-Processed Food Consumption and Obesity Prevention, run by Istanbul Gelisim University.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 7 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact HATİCE MERVE BAYRAM, PhD (+905549915658, hmbayram@gelisim.edu.tr), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change in ultra-processed food consumption (servings per day) (time frame: From baseline to 10 months and 20 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 7 Apr 2026.