Digital Engagement for Lifelong Health

Official title

Digital Engagement for Lifelong Prevention and Health Improvement

Overview

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.

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
• 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 monitori

Primary outcome measures

• World Health Organization Quality of Life (WHOQoL) [Time frame: Baseline and 6 months]
• Depression, Anxiety, and Stress Symptoms (DASS-21) [Time frame: Baseline and 6 months]
• Beck Depression Inventory-II (BDI-II) [Time frame: Baseline and 6 months]
• International Physical Activity Levels (IPAQ) [Time frame: Baseline and 6 months]
• Prevention with Mediterranean Diet (PREDIMED) [Time frame: Baseline and 6 months]

Secondary outcome measures (6)

• Heart Rate [Time frame: Continuously monitored from baseline to 6 months]
• Heart Rate Variability (HRV) [Time frame: Continuously monitored from baseline to 6 months]
• Body Weight [Time frame: Baseline, every 2 weeks during the 6-month intervention period and 6 months]
• Body Mass Index (BMI) [Time frame: Baseline and 6 months]
• Nutritional Intake [Time frame: Weekly monitoring from baseline to 6 months]
• Mental Well-Being Weekly Check-in Scores [Time frame: Weekly from baseline to 6 months]

Eligibility criteria

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).

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Allocation

Randomized

Model

Parallel assignment

Masking

Open label

Primary purpose

Prevention

Study locations

Italy · 1 center

• Institute for Biomedical Research and Innovation (IRIB)-National Reasearch Council (CNR) — Messina

Publications

• Moon J, Ju BK. Wearable sensors for healthcare of industrial workers: a scoping review. Electronics. 2024;13(19):3849. doi:10.3390/electronics13193849.
• Gray R, Indraratna P, Lovell N, Ooi SY. Digital health technology in the prevention of heart failure and coronary artery disease. Cardiovasc Digit Health J. 2022 Dec 15;3(6 Suppl):S9-S16. doi: 10.1016/j.cvdhj.2022.09.002. eCollection 2022 Dec. PMID 36589760
• Takahashi S, Yamamoto T. [apoE receptor 2]. Nihon Rinsho. 2001 Feb;59 Suppl 2:325-8. No abstract available. Japanese. PMID 11351599
• Brough P, Timms C, Chan XW, et al. Work-life balance: definitions, causes, and consequences. In: Theorell T, ed. Handbook of Socioeconomic Determinants of Occupational Health. Springer; 2020. doi:10.1007/978-3-030-05031-3_20-1
• Zangger M, Wälchli C, Stefenelli U, et al. The use of mobile health applications for the prevention of non-communicable diseases. Health Technol. 2021; 11: 585-593. doi:10.1007/s12553-021-00536-8.
• Marcolino MS, Oliveira JAQ, D'Agostino M, Ribeiro AL, Alkmim MBM, Novillo-Ortiz D. The Impact of mHealth Interventions: Systematic Review of Systematic Reviews. JMIR Mhealth Uhealth. 2018 Jan 17;6(1):e23. doi: 10.2196/mhealth.8873. PMID 29343463
• Choe EK, Klasnja P, Pratt W. mHealth and applications. In: Shortliffe EH, Cimino JJ, eds. Biomedical Informatics. Springer; 2021. doi:10.1007/978-3-030-58721-5_19.
• Eurofound. Psychosocial risks to workers' well-being: lessons from the COVID-19 pandemic. European Working Conditions Telephone Survey 2021 series. Publications Office of the European Union; 2023.

Identifiers

NCT: NCT07612852 · CNR-IRIB-PRO-2026-004

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗