Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| University of Eastern Finland | OTHER |
| Savonia University of Applied Sciences | OTHER |
Not provided
Not provided
Not provided
Not provided
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
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.
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| 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 |
|
| Standard peer-mentoring | Active Comparator | Standard peer-mentoring program aiming at improving diet quality, increasing physical activity and reducing obesity risk |
|
| Health educational intervention | Active Comparator | Regular health education sessions delivered by professional educators which focus on nutrition and physical activity |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AI-informed behavioral intervention | Behavioral | 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. |
| Measure | Description | Time Frame |
|---|---|---|
| Food Frequency Questionnaire | Self- or parent-reported questionnaire on the consumption of several food categories | 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 | From study enrollment to study completion at 12 months |
| Accelerations measurement | Measurement of accelerations through an accelerometer to evaluate the degree of physical activity | From study enrollment to study completion at 12 months |
| Healthy Diet Index | It is a measure of diet quality | From study enrollment to study completion at 12 months |
| Steps measurement | Number of steps per dayy measured by an accelerometer | 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 | From study enrollment to study completion at 12 months |
| PACER | Measurement of cardiorespiratory fitness | From study enrollment to study completion at 12 months |
| Measure | Description | Time Frame |
|---|---|---|
| BMI | Measurement of body mass index | From study enrollment to study completion at 12 months |
| Waist circumference | Measurement of waist circumference |
Not provided
Inclusion Criteria:
Healthy individuals aged 12-25 yrs -
Exclusion Criteria:
Obesity Severe cognitive and communication deficits
-
Not provided
Not provided
Not provided
Not provided
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Luca Arcangeli, Dr | Contact | 00393290743408 | pm@innovate.clust-er.it |
Not provided
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University Hospital of Patras | Pátrai | Achaia | 26500 | Greece |
Anonymized data regarding behaviors, medical information
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
|
| Standard behavioral intervention | Behavioral | Standard in-person behavioral intervention |
|
| Health Education | Other | Regular professional-delivered health educational sessions on nutrition and physical activity |
|
| From study enrollment to study completion at 12 months |
| Lipidemic profile | Measurement of plasma total cholesterol, TGs, LDL, HDL, non-HDL, ApoB levels | 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 | From study enrollment to study completion at 12 months |
| 25-OH D3 | Measurement of 25-OH D3 plasma levels | From study enrollment to study completion at 12 months |
| KIDSCREEN-27 | Assessment of quality of life | From study enrollment to study completion at 12 months |
| SF36 | Assessment of quality of life | From study enrollment to study completion at 12 months |
| Pittsburgh Sleep Quality Index AYA | Self -reported questionnaire to assess of sleep quality | From study enrollment to study completion at 12 months |
| Screen-time Questionnaire | Self-reported questionnaire to assess screen-time | 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) | 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 | 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 | 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 | 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 | 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 | 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 | From study enrollment to study completion at 12 months |
| Arterial Blood Pressure | Measurement of arterial blood pressure | From study enrollment to study completion at 12 months |
| Heart Rate Variability | Measurement of heart rate and heart rate variability | From study enrollment to study completion at 12 months |
| University of Bologna | Modena | Emilia-Romagna | Italy |
|
| Lulea Technical University | Luleå | Sweden |
|
| ID | Term |
|---|---|
| D009765 | Obesity |
| D009043 | Motor Activity |
| ID | Term |
|---|---|
| D050177 | Overweight |
| D044343 | Overnutrition |
| D009748 | Nutrition Disorders |
| D009750 | Nutritional and Metabolic Diseases |
| D001835 | Body Weight |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D001519 | Behavior |
Not provided
Not provided