Digital Engagement for Lifelong Health

Summary

The DELPHI project (Digital Engagement for Lifelong Prevention and Health Improvement) aims to develop, implement, and validate an advanced digital platform for promoting well-being and personalized prevention of chronic non-communicable diseases in healthy adults. By integrating wearable sensors, artificial intelligence, federated learning, and the Human Digital Twin (HDT) paradigm, the DELPHI platform is designed to collect, analyze, and interpret multidimensional data in order to deliver dynamic and personalized recommendations for healthy lifestyles.

The study adopts a multicenter, randomized controlled pilot design, with a maximum duration of 12 months per participant. A total of 200 healthy adults aged 18-65 will be recruited in Southern Italy (Sicily, Campania, and Basilicata) and randomly assigned to either: (1) an experimental group using the full DELPHI platform, including personalized recommendations, adaptive content, and continuous feedback; or (2) a control group using a basic version limited to passive monitoring.

As a non-clinical primary prevention pilot study, DELPHI aims to assess the operational feasibility, usability, and acceptability of the platform in real-world settings, while also exploring preliminary signals of impact on health and lifestyle domains without confirmatory purposes. Secondary objectives include monitoring physiological indicators, adherence to the app and wearable devices, and evaluating the feasibility of implementing the platform in workplace environments.

Data collection will rely on wearable devices, digital questionnaires, and behavioral analysis, with strong safeguards for personal data protection in compliance with GDPR and advanced security approaches such as federated learning and encryption.

Specific subgroups, including workers from the Fondazione Don Carlo Gnocchi (FDG) as well as university staff and students, will be involved in targeted assessments related to mental well-being and distress. In addition, workers from the FDG will test a virtual reality module designed to evaluate biomechanical overload risks during manual handling activities in simulated environments. These additional physiological and virtual reality components are exploratory and non-diagnostic.

Overall, DELPHI seeks to provide a solid foundation for the adoption of predictive and personalized models in digital health, contributing to the development of a sustainable and accessible prevention ecosystem, particularly in Southern Italy.

Conditions

• Life Style, Healthy
• Risk Reduction
• Health Promotion

Interventions

OTHER

DELPHI Personalized Digital Prevention Platform

the full version of the DELPHI digital platform, designed to support personalized primary prevention and health promotion. The intervention includes continuous monitoring through wearable sensors (Fitbit Inspire 3), mobile app-based data collection, and adaptive lifestyle recommendations generated by artificial intelligence algorithms within a Human Digital Twin framework. Participants will receive personalized feedback and notifications related to physical activity, sleep, nutrition, hydration, stress management, and psychological well-being. The platform also delivers multimedia educational content, including guided exercises, mindfulness and breathing practices, wellness educational videos, and behavioral micro-actions. Data collected through wearable devices, digital questionnaires, and behavioral monitoring are used to dynamically tailor recommendations and preventive strategies throughout the study period.

OTHER

Passive Digital Monitoring Control

Participants assigned to the control group will use a limited version of the DELPHI application restricted to passive monitoring functions. The application will collect data from wearable devices and questionnaires related to physical activity, sleep, nutrition, and well-being, but participants will not receive personalized recommendations, adaptive educational content, interactive feedback, or behavioral notifications. The control condition is intended to provide observational digital monitoring only, without active preventive intervention or AI-based personalization.

Sponsors & Collaborators

• Fondazione Don Carlo Gnocchi Onlus

  collaborator OTHER

• Universita degli Studi di Palermo

  collaborator OTHER

• Medilink s.r.l.

  collaborator UNKNOWN

• Istituto per la Ricerca e l'Innovazione Biomedica

  lead OTHER

Principal Investigators

• Gennaro Tartarisco · Institute for Biomedical Research and Innovation (IRIB)-National Reasearch Council (CNR)

Study Design

Allocation

RANDOMIZED

Purpose

PREVENTION

Masking

NONE

Model

PARALLEL

Eligibility

Min Age

18 Years

Max Age

65 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2026-05-04

Primary Completion

2026-11-30

Completion

2027-03-30

Countries

• Italy

Study Locations