Digital Engagement for Lifelong Prevention and Health Improvement
Trial Snapshot
- Phase
- Not Applicable
- Status
- Recruiting
- Sponsor
- Enrollment
- 200
- Locations
- 1
Study Overview
Brief 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.
Study Design
- Study Type
- Interventional
- Allocation
- Randomized
- Intervention Model
- Parallel
- Primary Purpose
- Prevention
- Masking
- None
Eligibility Criteria
- Ages
- 18 Years to 65 Years (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- Yes
Inclusion Criteria
- •Apparent good general health status, confirmed by medical history and initial self-assessment.
- •Ability to understand the study information and provide informed consent.
- •Availability and motivation to participate for the entire duration of the study (12 months).
- •Access to a smartphone compatible with the DELPHI application.
- •Willingness to wear the wearable devices for continuous monitoring of physiological parameters.
- •Basic familiarity with mobile applications or willingness to receive training on their use.
- •Signed informed consent.
Exclusion Criteria
- •Presence of severe chronic diseases in active phase (e.g., oncological, cardiovascular, or neurological diseases).
- •Acute or unstable conditions that could compromise participation in the protocol.
- •Current pregnancy.
- •Diagnosed major cognitive or psychiatric disorders that hinder understanding of or adherence to the protocol.
- •Current use of medications that significantly affect the parameters being monitored (e.g., psychotropic drugs, beta-blockers).
- •Simultaneous participation in other clinical studies.
- •Logistical difficulties that prevent frequent interaction with the platform (e.g., lack of connection, unwillingness to attend periodic follow-ups).
Investigators
Gennaro Tartarisco
Head of Unit
Istituto per la Ricerca e l'Innovazione Biomedica