Obesity (Disorder)PeerMentorOBCVNCT07505459
AI-INFORMED PEER-MENTORING BEHAVIORAL INTERVENTION FOR OBESITY AND CARDIOVASCULAR DISEASE PRIMARY PREVENTION IN YOUTH
A study testing AI-informed behavioral intervention, Standard behavioral intervention and Health Education in people with Obesity (Disorder), run by Aikaterini Karaivazoglou at 3 sites in 3 countries.
Trial summary
The goal of this clinical trial is to learn if an AI-based peer-mentoring works to prevent obesity in adolescents and young adults. The main questions it aims to answer are: Does the AI-based peer-mentoring improve dietary habits and increase physical activity in healthy individuals 12-25 yrs old? Does the AI-based… Read more about this study
- Who is it for?
- Ages 12 to 25 yearsHealthy volunteers can take part
- Conditions the study is for
- Obesity (Disorder)
- What is being tested?
- AI-informed behavioral intervention, Standard behavioral intervention and Health Education
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 840 participants
- Where
- 3 sitesin 3 countries
- Study dates
- 1 Sep 2027to 30 Dec 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
- Healthy individuals aged 12-25 yrs -
Who cannot join
- Obesity Severe cognitive and communication deficits
- -
Trial locations and contacts
3 sites in 3 countries. Contact the study team or a site near you to ask about taking part.
3 sites in 3 countries
Greece1 site
University Hospital of Patras
Pátrai, Achaia, 26500
Aikaterini Karaivazoglou, PhD, Assistant Professor, 00306977711259, karaivaz@hotmail.com
Italy1 site
University of Bologna
Modena, Emilia-Romagna
Eliana Tossani, Professor, +39 3290743408, eliana.tossani2@unibo.it
Sweden1 site
Lulea Technical University
Luleå
Anna-Karin Lindqvist, Professor, 0046703611507, anna-karin.lindqvist@ltu.se
About this study
The goal of this clinical trial is to learn if an AI-based peer-mentoring works to prevent obesity in adolescents and young adults. The main questions it aims to answer are:
Does the AI-based peer-mentoring improve dietary habits and increase physical activity in healthy individuals 12-25 yrs old? Does the AI-based peer-mentoring reduces the risk of obesity?
Read more
Researchers will compare the AI-based behavioral peer-mentoring intervention to traditional peer-mentoring and to health education intervention to see if AI-based peer-mentoring is more effective.
Participants will:
Follow either a structured AI-based peer-mentoring program or a traditional peer-mentoring program or health education sessions focusing on diet and physical activity They will be evaluated at baseline, at 6 months and at 12 months
Read the detailed description
Adolescence and young adulthood (12-25 years) represent critical developmental periods during which lifestyle patterns related to nutrition, physical activity, sleep, digital media use, social interaction, and stress regulation are consolidated and often persist into adulthood. Preventive interventions targeting these stages therefore offer substantial potential for long-term reduction of non-communicable disease (NCD) burden.
Although young people are often perceived as generally healthy, epidemiological evidence indicates a growing burden of NCD-related conditions in this population. Adolescent obesity has quadrupled in recent decades, affecting over 160 million children and adolescents worldwide (World Health Organization, 2021; Halilagic et al., 2025), and is strongly associated with increased risk of metabolic syndrome, type 2 diabetes, hypertension, cardiovascular disease (CVD), and certain cancers later in life (Shi et al., 2024).
A substantial body of evidence links obesity risk to modifiable lifestyle factors established early in life (Arnason et al., 2020; Zaman et al., 2019; Singh et al., 2025; Parvin et al., 2025), and behavioural interventions addressing these factors have demonstrated promising effects in young populations (Pastor et al., 2020; Ashton et al., 2019). However, existing interventions often show wide variability in design and outcomes and face persistent challenges related to long-term adherence, scalability, and equitable access (Melo et al., 2025; Talens et al., 2025). Many rely on professional-led delivery models requiring substantial human and financial resources, limiting their sustainability and reach, particularly in low-resource or geographically remote settings.
Digital health interventions have emerged as a promising means to improve accessibility and engagement while supporting self-monitoring and feedback. Digital approaches have demonstrated positive effects on behaviours related to physical activity, diet, and sleep (Singh et al., 2025). Nevertheless, many digital interventions remain largely individualised and screen-centric, insufficiently leveraging the social environments in which young people's behaviours are embedded, which may limit sustained engagement and long-term behaviour change.
In this context, peer mentoring represents a promising, yet, underutilised approach for strengthening behavioural self-management and primary NCD prevention among adolescents and young adults. Peer mentoring involves structured, supportive relationships in which individuals with shared or similar lived experiences provide guidance, encouragement, and role modelling. During adolescence and young adulthood, peers exert a strong influence on attitudes, norms, motivation, and behaviour. Peer-led approaches are often perceived as more relatable, credible, and emotionally safe than authority- or expert-led interventions, fostering trust, social connectedness, and intrinsic motivation (DuBois \& Karcher, 2014; Smith et al., 2016). Peer mentoring programs have demonstrated effectiveness in promoting healthy behaviours and psychosocial outcomes in youth, particularly in school-based and community settings (Lavelle et al., 2023).
For these reasons, the aim of the current study will be to implement and evaluate a hybrid, human-delivered peer-mentoring intervention, combining in-person and remote interactions and supported by AI-informed tools that provide mentors with access to ethically governed, privacy-preserving participant indicators. More specifically, the intervention will include a structured school-based (adolescents) or campus- or community- based (young adults) behavioral change program delivered through peer-mentoring focusing on physical activity and nutrition in order to reduce obesity risk. The intervention' s content will be based on existing evidence-based interventions with a solid theoretical foundation (namely the Health Belief Model and Social Cognitive Theory). The program will recruit and appropriately train young mentors aged 14-25 years old. Mentors' training curriculum will be designed by experts in youth health (pediatrics, endocrinology), nutrition science, physiotherapy and behavioral science based on the aforementioned interventions and training will be performed through a pre-defined number of group sessions and is expected to be completed within a month. Subsequently, mentors will be matched with slightly younger peers (aged 12-23 years old) and they will deliver the intervention through structured weekly meetings and activities throughout the academic year. Each mentor-mentee pair will be supervised and supported by a qualified supervisor (psychologist or social worker) which will conduct regular meetings (twice a month) with each pair, will be available to support them during the study period and will ensure the program's implementation fidelity. The meetings and shared activities will take place at schools during the school curriculum for adolescents and at campuses or community centers for young adults. The program will be coordinated by a qualified professional which will support supervisors and will act as liaison between school and university personnel and supervisors.
- Conditions
- Obesity (Disorder)
- Being tested
- AI-informed behavioral intervention, Standard behavioral intervention, Health Education
- Keywords
- Peer-mentoring, Obesity, Behavioral change, Nutrition, Physical activity, Youth, Digital health, prevention
- Medical subject headings
- Obesity, Motor Activity
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-informed behavioral interventionBehavioural
A hybrid, human-delivered peer-mentoring intervention, combining in-person and remote interactions and supported by AI-informed tools that provide mentors with access to ethically governed, privacy-preserving participant indicators. The intervention will operate under a supervisor-in-the-loop model, ensuring participant safety, intervention quality and ethical compliance, mentor support, and timely escalation to professional care when risks exceed the scope of peer support.
Standard behavioral interventionBehavioural
Standard in-person behavioral intervention
Health EducationOther
Regular professional-delivered health educational sessions on nutrition and physical activity
| Study group | Role | What they receive |
|---|---|---|
| AI-informed peer-mentoring behavioral intervention | Experimental | AI-informed peer-mentoring program combining digitally facilitated peer mentoring, evidence-based behavioural interventions, and non-invasive self-monitoring technologies to support self-management, improve diet quality, increase physical activity and reduce the risk of obesity Receives: Behavioral: AI-informed behavioral intervention |
| Standard peer-mentoring | Active comparator | Standard peer-mentoring program aiming at improving diet quality, increasing physical activity and reducing obesity risk Receives: Other: Health Education |
| Health educational intervention | Active comparator | Regular health education sessions delivered by professional educators which focus on nutrition and physical activity Receives: Behavioral: Standard behavioral intervention |
What is being measured
The primary outcome is the main question the study is designed to answer.
Food Frequency Questionnaire
Self- or parent-reported questionnaire on the consumption of several food categories
Measured: From study enrollment to study completion at 12 months
KIDMED INDEX
A questionnaire used to measure adherence to the Mediterranean diet in children and adolescents
Measured: From study enrollment to study completion at 12 months
Accelerations measurement
Measurement of accelerations through an accelerometer to evaluate the degree of physical activity
Measured: From study enrollment to study completion at 12 months
Healthy Diet Index
It is a measure of diet quality
Measured: From study enrollment to study completion at 12 months
Steps measurement
Number of steps per dayy measured by an accelerometer
Measured: From study enrollment to study completion at 12 months
International Physical Activity Questionnaire (IPAQ)
It is an instrument that assesses the level of physical activity
Measured: From study enrollment to study completion at 12 months
PACER
Measurement of cardiorespiratory fitness
Measured: From study enrollment to study completion at 12 months
Secondary outcomes (18)
BMI
Measurement of body mass index
Measured: From study enrollment to study completion at 12 months
Waist circumference
Measurement of waist circumference
Measured: From study enrollment to study completion at 12 months
Lipidemic profile
Measurement of plasma total cholesterol, TGs, LDL, HDL, non-HDL, ApoB levels
Measured: From study enrollment to study completion at 12 months
Skin carotenoid levels
Spectroscopy-based measurement of skin carotenoid levels with the use of Veggie-Meter
Measured: From study enrollment to study completion at 12 months
25-OH D3
Measurement of 25-OH D3 plasma levels
Measured: From study enrollment to study completion at 12 months
KIDSCREEN-27
Assessment of quality of life
Measured: From study enrollment to study completion at 12 months
SF36
Assessment of quality of life
Measured: From study enrollment to study completion at 12 months
Pittsburgh Sleep Quality Index AYA
Self -reported questionnaire to assess of sleep quality
Measured: From study enrollment to study completion at 12 months
Screen-time Questionnaire
Self-reported questionnaire to assess screen-time
Measured: From study enrollment to study completion at 12 months
Multidimensional Scale of Perceived Social Support
It is a valid innstrument measuring support across three sources (family, friends, significant other)
Measured: From study enrollment to study completion at 12 months
General Self-Efficacy Scale
It is a questionnaire designed to measure an individual's belief in their ability to manage difficult tasks and unforeseen situations
Measured: From study enrollment to study completion at 12 months
Emotional Regulation Questionnaire, adults and children & adolescent versions
It is a valid and reliable instrument that assesses how people manage emotions
Measured: From study enrollment to study completion at 12 months
Primarily fat mass
It is an analysis of primarily fat mass with the use of bioelectrical impedance analysis
Measured: From study enrollment to study completion at 12 months
Lean muscle mass
It is the measurement of the body lean muscle mass with the use of bioelectrical impedance analysis
Measured: From study enrollment to study completion at 12 months
Body water
It is the measurement of body water with the use of bioelectrical impedance analysis
Measured: From study enrollment to study completion at 12 months
Bone density
It is the measurement of bone density with the use of bioelectrical impedance analysis
Measured: From study enrollment to study completion at 12 months
Arterial Blood Pressure
Measurement of arterial blood pressure
Measured: From study enrollment to study completion at 12 months
Heart Rate Variability
Measurement of heart rate and heart rate variability
Measured: From study enrollment to study completion at 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted1 Apr 2026
- Study start1 Sep 2027 (estimated)
- Primary completion30 Dec 2028 (estimated)
- Study completion30 Dec 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Obesity (Disorder)Studies 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
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 840 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Aikaterini Karaivazoglou
- Sponsor type
- University, hospital or other
- Collaborators
- University of Eastern Finland, Savonia University of Applied Sciences
- Responsible party
- Sponsor-investigator, Aikaterini Karaivazoglou, University of Patras
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07505459
- Sponsor's protocol ID
- PMOBES140326
- Acronym
- PeerMentorOBCV
- Status last verified
- Apr 2026
- First submitted
- 21 Mar 2026
- Last updated
- 14 Apr 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Anonymized data regarding behaviors, medical information
Study at a glance
From the registry record, last updated by the sponsor on 14 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- AI-INFORMED PEER-MENTORING BEHAVIORAL INTERVENTION FOR OBESITY AND CARDIOVASCULAR DISEASE PRIMARY PREVENTION IN YOUTH
- ClinicalTrials.gov ID
- NCT07505459
- Acronym / sponsor ID
- PeerMentorOBCV / PMOBES140326
- Conditions
- Obesity (Disorder)
- Keywords
- Peer-mentoring, Obesity, Behavioral change, Nutrition, Physical activity, Youth, Digital health, prevention
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 840 participants (estimated)
- Lead sponsor
- Aikaterini KaraivazoglouUniversity, hospital or other
- Collaborators
- University of Eastern Finland, Savonia University of Applied Sciences
- Study start
- 1 Sep 2027 (estimated)
- Primary completion
- 30 Dec 2028 (estimated)
- Study completion
- 30 Dec 2028 (estimated)
- First posted
- 1 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.
The goal of this clinical trial is to learn if an AI-based peer-mentoring works to prevent obesity in adolescents and young adults. The main questions it aims to answer are:
Does the AI-based peer-mentoring improve dietary habits and increase physical activity in healthy individuals 12-25 yrs old? Does the AI-based peer-mentoring reduces the risk of obesity?
Researchers will compare the AI-based behavioral peer-mentoring intervention to traditional peer-mentoring and to health education intervention to see if AI-based peer-mentoring is more effective.
Participants will:
Follow either a structured AI-based peer-mentoring program or a traditional peer-mentoring program or health education sessions focusing on diet and physical activity They will be evaluated at baseline, at 6 months and at 12 months
Detailed description
Adolescence and young adulthood (12-25 years) represent critical developmental periods during which lifestyle patterns related to nutrition, physical activity, sleep, digital media use, social interaction, and stress regulation are consolidated and often persist into adulthood. Preventive interventions targeting these stages therefore offer substantial potential for long-term reduction of non-communicable disease (NCD) burden.
Although young people are often perceived as generally healthy, epidemiological evidence indicates a growing burden of NCD-related conditions in this population. Adolescent obesity has quadrupled in recent decades, affecting over 160 million children and adolescents worldwide (World Health Organization, 2021; Halilagic et al., 2025), and is strongly associated with increased risk of metabolic syndrome, type 2 diabetes, hypertension, cardiovascular disease (CVD), and certain cancers later in life (Shi et al., 2024).
A substantial body of evidence links obesity risk to modifiable lifestyle factors established early in life (Arnason et al., 2020; Zaman et al., 2019; Singh et al., 2025; Parvin et al., 2025), and behavioural interventions addressing these factors have demonstrated promising effects in young populations (Pastor et al., 2020; Ashton et al., 2019). However, existing interventions often show wide variability in design and outcomes and face persistent challenges related to long-term adherence, scalability, and equitable access (Melo et al., 2025; Talens et al., 2025). Many rely on professional-led delivery models requiring substantial human and financial resources, limiting their sustainability and reach, particularly in low-resource or geographically remote settings.
Digital health interventions have emerged as a promising means to improve accessibility and engagement while supporting self-monitoring and feedback. Digital approaches have demonstrated positive effects on behaviours related to physical activity, diet, and sleep (Singh et al., 2025). Nevertheless, many digital interventions remain largely individualised and screen-centric, insufficiently leveraging the social environments in which young people's behaviours are embedded, which may limit sustained engagement and long-term behaviour change.
In this context, peer mentoring represents a promising, yet, underutilised approach for strengthening behavioural self-management and primary NCD prevention among adolescents and young adults. Peer mentoring involves structured, supportive relationships in which individuals with shared or similar lived experiences provide guidance, encouragement, and role modelling. During adolescence and young adulthood, peers exert a strong influence on attitudes, norms, motivation, and behaviour. Peer-led approaches are often perceived as more relatable, credible, and emotionally safe than authority- or expert-led interventions, fostering trust, social connectedness, and intrinsic motivation (DuBois \& Karcher, 2014; Smith et al., 2016). Peer mentoring programs have demonstrated effectiveness in promoting healthy behaviours and psychosocial outcomes in youth, particularly in school-based and community settings (Lavelle et al., 2023).
For these reasons, the aim of the current study will be to implement and evaluate a hybrid, human-delivered peer-mentoring intervention, combining in-person and remote interactions and supported by AI-informed tools that provide mentors with access to ethically governed, privacy-preserving participant indicators. More specifically, the intervention will include a structured school-based (adolescents) or campus- or community- based (young adults) behavioral change program delivered through peer-mentoring focusing on physical activity and nutrition in order to reduce obesity risk. The intervention' s content will be based on existing evidence-based interventions with a solid theoretical foundation (namely the Health Belief Model and Social Cognitive Theory). The program will recruit and appropriately train young mentors aged 14-25 years old. Mentors' training curriculum will be designed by experts in youth health (pediatrics, endocrinology), nutrition science, physiotherapy and behavioral science based on the aforementioned interventions and training will be performed through a pre-defined number of group sessions and is expected to be completed within a month. Subsequently, mentors will be matched with slightly younger peers (aged 12-23 years old) and they will deliver the intervention through structured weekly meetings and activities throughout the academic year. Each mentor-mentee pair will be supervised and supported by a qualified supervisor (psychologist or social worker) which will conduct regular meetings (twice a month) with each pair, will be available to support them during the study period and will ensure the program's implementation fidelity. The meetings and shared activities will take place at schools during the school curriculum for adolescents and at campuses or community centers for young adults. The program will be coordinated by a qualified professional which will support supervisors and will act as liaison between school and university personnel and supervisors.
Study design
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| AI-informed peer-mentoring behavioral intervention | Experimental | Behavioral: AI-informed behavioral interventionAI-informed peer-mentoring program combining digitally facilitated peer mentoring, evidence-based behavioural interventions, and non-invasive self-monitoring technologies to support self-management, improve diet quality, increase physical activity and reduce the risk of obesity |
| Standard peer-mentoring | Active comparator | Other: Health EducationStandard peer-mentoring program aiming at improving diet quality, increasing physical activity and reducing obesity risk |
| Health educational intervention | Active comparator | Behavioral: Standard behavioral interventionRegular health education sessions delivered by professional educators which focus on nutrition and physical activity |
Who may qualify
- Ages
- 12 to 25 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult
Key inclusion criteria (1 listed)
- Healthy individuals aged 12-25 yrs -
Key exclusion criteria (2 listed)
- Obesity Severe cognitive and communication deficits
- -
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 |
|---|---|---|
| AI-informed behavioral interventionA hybrid, human-delivered peer-mentoring intervention, combining in-person and remote interactions and supported by AI-informed tools that provide mentors with access to ethically governed, privacy-preserving participant indicators. The intervention will operate under a supervisor-in-the-loop model, ensuring participant safety, intervention quality and ethical compliance, mentor support, and timely escalation to professional care when risks exceed the scope of peer support. | Behavioural | AI-informed peer-mentoring behavioral intervention |
| Standard behavioral interventionStandard in-person behavioral intervention | Behavioural | Health educational intervention |
| Health EducationRegular professional-delivered health educational sessions on nutrition and physical activity | Other | Standard peer-mentoring |
Primary outcome
Food Frequency Questionnaire
Time frame: From study enrollment to study completion at 12 months
Self- or parent-reported questionnaire on the consumption of several food categories
KIDMED INDEX
Time frame: From study enrollment to study completion at 12 months
A questionnaire used to measure adherence to the Mediterranean diet in children and adolescents
Accelerations measurement
Time frame: From study enrollment to study completion at 12 months
Measurement of accelerations through an accelerometer to evaluate the degree of physical activity
Healthy Diet Index
Time frame: From study enrollment to study completion at 12 months
It is a measure of diet quality
Steps measurement
Time frame: From study enrollment to study completion at 12 months
Number of steps per dayy measured by an accelerometer
International Physical Activity Questionnaire (IPAQ)
Time frame: From study enrollment to study completion at 12 months
It is an instrument that assesses the level of physical activity
PACER
Time frame: From study enrollment to study completion at 12 months
Measurement of cardiorespiratory fitness
18 secondary outcomes
BMI
Time frame: From study enrollment to study completion at 12 months
Waist circumference
Time frame: From study enrollment to study completion at 12 months
Lipidemic profile
Time frame: From study enrollment to study completion at 12 months
Skin carotenoid levels
Time frame: From study enrollment to study completion at 12 months
25-OH D3
Time frame: From study enrollment to study completion at 12 months
KIDSCREEN-27
Time frame: From study enrollment to study completion at 12 months
SF36
Time frame: From study enrollment to study completion at 12 months
Pittsburgh Sleep Quality Index AYA
Time frame: From study enrollment to study completion at 12 months
Screen-time Questionnaire
Time frame: From study enrollment to study completion at 12 months
Multidimensional Scale of Perceived Social Support
Time frame: From study enrollment to study completion at 12 months
General Self-Efficacy Scale
Time frame: From study enrollment to study completion at 12 months
Emotional Regulation Questionnaire, adults and children & adolescent versions
Time frame: From study enrollment to study completion at 12 months
Primarily fat mass
Time frame: From study enrollment to study completion at 12 months
Lean muscle mass
Time frame: From study enrollment to study completion at 12 months
Body water
Time frame: From study enrollment to study completion at 12 months
Bone density
Time frame: From study enrollment to study completion at 12 months
Arterial Blood Pressure
Time frame: From study enrollment to study completion at 12 months
Heart Rate Variability
Time frame: From study enrollment to study completion at 12 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 14 Apr 2026.
- Individual participant dataSharing planned: Yes. Anonymized data regarding behaviors, medical information
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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.
3 sites in 3 countries: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-informed behavioral intervention, Standard behavioral intervention and Health Education in people with Obesity (Disorder), run by Aikaterini Karaivazoglou at 3 sites in 3 countries.
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 1 inclusion and 2 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 14 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 3 sites in Greece, Italy, Sweden. Whether a site is taking part right now should be confirmed with that site. See every site.
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 Luca Arcangeli, Dr (00393290743408, pm@innovate.clust-er.it), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Food Frequency Questionnaire (time frame: From study enrollment to study completion at 12 months). The study lists 7 primary outcomes in all. 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 14 Apr 2026.