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.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
PREVENTION
Masking
SINGLE
Enrollment
840
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 in-person behavioral intervention
Regular professional-delivered health educational sessions on nutrition and physical activity
University Hospital of Patras
Pátrai, Achaia, Greece
University of Bologna
Modena, Emilia-Romagna, Italy
Lulea Technical University
Luleå, Sweden
Food Frequency Questionnaire
Self- or parent-reported questionnaire on the consumption of several food categories
Time frame: 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
Time frame: From study enrollment to study completion at 12 months
Accelerations measurement
Measurement of accelerations through an accelerometer to evaluate the degree of physical activity
Time frame: From study enrollment to study completion at 12 months
Healthy Diet Index
It is a measure of diet quality
Time frame: From study enrollment to study completion at 12 months
Steps measurement
Number of steps per dayy measured by an accelerometer
Time frame: 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
Time frame: From study enrollment to study completion at 12 months
PACER
Measurement of cardiorespiratory fitness
Time frame: From study enrollment to study completion at 12 months
BMI
Measurement of body mass index
Time frame: From study enrollment to study completion at 12 months
Waist circumference
Measurement of waist circumference
Time frame: From study enrollment to study completion at 12 months
Lipidemic profile
Measurement of plasma total cholesterol, TGs, LDL, HDL, non-HDL, ApoB levels
Time frame: 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
Time frame: From study enrollment to study completion at 12 months
25-OH D3
Measurement of 25-OH D3 plasma levels
Time frame: From study enrollment to study completion at 12 months
KIDSCREEN-27
Assessment of quality of life
Time frame: From study enrollment to study completion at 12 months
SF36
Assessment of quality of life
Time frame: From study enrollment to study completion at 12 months
Pittsburgh Sleep Quality Index AYA
Self -reported questionnaire to assess of sleep quality
Time frame: From study enrollment to study completion at 12 months
Screen-time Questionnaire
Self-reported questionnaire to assess screen-time
Time frame: 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)
Time frame: 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
Time frame: 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
Time frame: 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
Time frame: 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
Time frame: 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
Time frame: 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
Time frame: From study enrollment to study completion at 12 months
Arterial Blood Pressure
Measurement of arterial blood pressure
Time frame: From study enrollment to study completion at 12 months
Heart Rate Variability
Measurement of heart rate and heart rate variability
Time frame: From study enrollment to study completion at 12 months
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