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.
Age range
18 Years – 65 Years
Sex
ALL
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A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
World Health Organization Quality of Life (WHOQoL)
Timeframe: Baseline and 6 months
Depression, Anxiety, and Stress Symptoms (DASS-21)
Timeframe: Baseline and 6 months
Beck Depression Inventory-II (BDI-II)
Timeframe: Baseline and 6 months
International Physical Activity Levels (IPAQ)
Timeframe: Baseline and 6 months
Prevention with Mediterranean Diet (PREDIMED)
Timeframe: Baseline and 6 months