- ICH GCP
- Registro degli studi clinici negli Stati Uniti
- Sperimentazione clinica NCT07612852
Digital Engagement for Lifelong Health (DELPHI)
Digital Engagement for Lifelong Prevention and Health Improvement
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.
Panoramica dello studio
Stato
Intervento / Trattamento
Tipo di studio
Iscrizione (Stimato)
Fase
- Non applicabile
Contatti e Sedi
Contatto studio
- Nome: Maria Valeria Maiorana
- Email: mariavaleria.maiorana@irib.cnr.it
Backup dei contatti dello studio
- Nome: Gennaro Tartarisco
- Numero di telefono: +393283377046
- Email: gennaro.tartarisco@irib.cnr.it
Luoghi di studio
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Messina, Italia, 98164
- Reclutamento
- Institute for Biomedical Research and Innovation (IRIB)-National Reasearch Council (CNR)
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Sub-investigatore:
- Roberta Bruschetta
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Sub-investigatore:
- Simona Campisi
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Sub-investigatore:
- Maria Valeria Maiorana
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Investigatore principale:
- Gennaro Tartarisco
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Sub-investigatore:
- Serena Iacono Isidoro
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Sub-investigatore:
- Concetta Polizzi
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Sub-investigatore:
- Renato Tino
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Sub-investigatore:
- Marco Germanotta
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Contatto:
- Serena Iacono Isidoro
- Numero di telefono: +393281655820
- Email: serena.iaconoisidoro@irib.cnr.it
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Sub-investigatore:
- Irene Aprile
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Sub-investigatore:
- Mariacristina Siotto
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Sub-investigatore:
- Alessandro Guerrini
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Sub-investigatore:
- Monia Andrea Papa
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Sub-investigatore:
- Giorgia Bruschetta
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Sub-investigatore:
- Barbara Caci
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Sub-investigatore:
- Maria Cocchiara
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Sub-investigatore:
- Flavia Altavilla
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Sub-investigatore:
- Alessia Valdesi
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Sub-investigatore:
- Chiara Urone
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Sub-investigatore:
- Giulia Giordano
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Criteri di partecipazione
Criteri di ammissibilità
Età idonea allo studio
- Adulto
- Adulto più anziano
Accetta volontari sani
Descrizione
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).
Piano di studio
Come è strutturato lo studio?
Dettagli di progettazione
- Scopo principale: Prevenzione
- Assegnazione: Randomizzato
- Modello interventistico: Assegnazione parallela
- Mascheramento: Nessuno (etichetta aperta)
Armi e interventi
Gruppo di partecipanti / Arm |
Intervento / Trattamento |
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Sperimentale: Experimental group
Participants will use the full version of the DELPHI platform, including wearable sensors, mobile app-based data collection, personalized recommendations generated through artificial intelligence algorithms, multimedia content (physical exercises, mindfulness activities, and educational videos), as well as interactive notifications and feedback.
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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. |
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Altro: Control group
Participants will access a limited version of the application restricted to passive monitoring functions only, without personalized recommendations, adaptive content, or interactive notifications.
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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. |
Cosa sta misurando lo studio?
Misure di risultato primarie
Misura del risultato |
Misura Descrizione |
Lasso di tempo |
|---|---|---|
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World Health Organization Quality of Life (WHOQoL)
Lasso di tempo: Baseline and 6 months
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The World Health Organization Quality of Life (WHOQoL) is a questionnaire used to assess quality of life.The WHOQOL-BREF, its short form, includes 26 items and evaluates four domains: physical health, psychological health, social relationships, and environment.
It does not generate a single total score; instead, it provides separate domain scores, with higher values indicating better quality of life
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Baseline and 6 months
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Depression, Anxiety, and Stress Symptoms (DASS-21)
Lasso di tempo: Baseline and 6 months
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The Depression, Anxiety and Stress Scales-21 (DASS-21) is a 21-item self-report instrument designed to assess the severity of depression, anxiety, and stress symptoms. It consists of three subscales, each containing 7 items, and uses a 4-point response format. The scale provides separate scores for depression, anxiety, and stress rather than a single diagnostic score.
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Baseline and 6 months
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Beck Depression Inventory-II (BDI-II)
Lasso di tempo: Baseline and 6 months
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The Beck Depression Inventory-II (BDI-II) is a 21-item self-report instrument designed to measure the severity of depressive symptoms over the past two weeks. Each item is rated on a 0 to 3 scale, and the total score ranges from 0 to 63. The total BDI-II score is calculated by summing all 21 items, giving a range from 0 to 63. Common interpretive cut-offs are: minimal depression 0-13, mild 14-19, moderate 20-28, and severe 29-63 |
Baseline and 6 months
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International Physical Activity Levels (IPAQ)
Lasso di tempo: Baseline and 6 months
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The International Physical Activity Questionnaire (IPAQ) is a self-report instrument designed to assess physical activity levels over the previous 7 days. It provides both a categorical score, classifying individuals as low, moderate, or high active, and a continuous score expressed as MET-minutes per week.
The continuous score is calculated using standard MET values:
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Baseline and 6 months
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Prevention with Mediterranean Diet (PREDIMED)
Lasso di tempo: Baseline and 6 months
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The Prevention with Mediterranean Diet (PREDIMED) questionnaire is a 14-item tool designed to assess adherence to the Mediterranean diet.
Each item is scored as 0 or 1, and the total score ranges from 0 to 14, with higher scores indicating greater adherence to the Mediterranean dietary pattern.
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Baseline and 6 months
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Misure di risultato secondarie
Misura del risultato |
Misura Descrizione |
Lasso di tempo |
|---|---|---|
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Heart Rate
Lasso di tempo: Continuously monitored from baseline to 6 months
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Average heart rate measured through wearable sensors in beats per minute (bpm).
Normal resting heart rate in adults is commonly about 60 to 100 bpm
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Continuously monitored from baseline to 6 months
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Heart Rate Variability (HRV)
Lasso di tempo: Continuously monitored from baseline to 6 months
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Nocturnal heart rate variability measured in milliseconds using wearable sensors.
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Continuously monitored from baseline to 6 months
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Body Weight
Lasso di tempo: Baseline, every 2 weeks during the 6-month intervention period and 6 months
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Change in body weight measured in kilograms (kg).
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Baseline, every 2 weeks during the 6-month intervention period and 6 months
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Body Mass Index (BMI)
Lasso di tempo: Baseline and 6 months
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adults, BMI is usually interpreted as follows: Underweight: below 18.5 Healthy weight: 18.5 to 24.9 Overweight: 25.0 to 29.9 Obesity: 30.0 or above
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Baseline and 6 months
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Nutritional Intake
Lasso di tempo: Weekly monitoring from baseline to 6 months
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Daily caloric, macronutrient, and micronutrient intake measured through in-app food diary records.
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Weekly monitoring from baseline to 6 months
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Mental Well-Being Weekly Check-in Scores
Lasso di tempo: Weekly from baseline to 6 months
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Weekly emotional well-being indicators measured through a 6-item Likert-scale in-app questionnaire assessing mood, calmness, energy, tension, and distress.
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Weekly from baseline to 6 months
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Collaboratori e investigatori
Investigatori
- Investigatore principale: Gennaro Tartarisco, Institute for Biomedical Research and Innovation (IRIB)-National Reasearch Council (CNR)
Pubblicazioni e link utili
Pubblicazioni generali
- Bull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G, Carty C, Chaput JP, Chastin S, Chou R, Dempsey PC, DiPietro L, Ekelund U, Firth J, Friedenreich CM, Garcia L, Gichu M, Jago R, Katzmarzyk PT, Lambert E, Leitzmann M, Milton K, Ortega FB, Ranasinghe C, Stamatakis E, Tiedemann A, Troiano RP, van der Ploeg HP, Wari V, Willumsen JF. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med. 2020 Dec;54(24):1451-1462. doi: 10.1136/bjsports-2020-102955.
- 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.
- 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.
- Takahashi S, Yamamoto T. [apoE receptor 2]. Nihon Rinsho. 2001 Feb;59 Suppl 2:325-8. No abstract available. Japanese.
- 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.
- 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.
- Jakob R, Harperink S, Rudolf AM, Fleisch E, Haug S, Mair JL, Salamanca-Sanabria A, Kowatsch T. Factors Influencing Adherence to mHealth Apps for Prevention or Management of Noncommunicable Diseases: Systematic Review. J Med Internet Res. 2022 May 25;24(5):e35371. doi: 10.2196/35371.
- Debon R, Coleone JD, Bellei EA, De Marchi ACB. Mobile health applications for chronic diseases: A systematic review of features for lifestyle improvement. Diabetes Metab Syndr. 2019 Jul-Aug;13(4):2507-2512. doi: 10.1016/j.dsx.2019.07.016. Epub 2019 Jul 9.
- Laffond A, Rivera-Picon C, Rodriguez-Munoz PM, Juarez-Vela R, Ruiz de Vinaspre-Hernandez R, Navas-Echazarreta N, Sanchez-Gonzalez JL. Mediterranean Diet for Primary and Secondary Prevention of Cardiovascular Disease and Mortality: An Updated Systematic Review. Nutrients. 2023 Jul 28;15(15):3356. doi: 10.3390/nu15153356.
- WHO global status report on alcohol and health and treatment of substance use disorders. Geneva: World Health Organization; 2024
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Primo Inserito (Effettivo)
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Maggiori informazioni
Termini relativi a questo studio
Parole chiave
Termini MeSH pertinenti aggiuntivi
Altri numeri di identificazione dello studio
- CNR-IRIB-PRO-2026-004
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Queste informazioni sono state recuperate direttamente dal sito web clinicaltrials.gov senza alcuna modifica. In caso di richieste di modifica, rimozione o aggiornamento dei dettagli dello studio, contattare register@clinicaltrials.gov. Non appena verrà implementata una modifica su clinicaltrials.gov, questa verrà aggiornata automaticamente anche sul nostro sito web .
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