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.
Обзор исследования
Статус
Тип исследования
Регистрация (Оцененный)
Фаза
- Непригодный
Контакты и местонахождение
Контакты исследования
- Имя: Maria Valeria Maiorana
- Электронная почта: mariavaleria.maiorana@irib.cnr.it
Учебное резервное копирование контактов
- Имя: Gennaro Tartarisco
- Номер телефона: +393283377046
- Электронная почта: gennaro.tartarisco@irib.cnr.it
Места учебы
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Messina, Италия, 98164
- Рекрутинг
- Institute for Biomedical Research and Innovation (IRIB)-National Reasearch Council (CNR)
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Младший исследователь:
- Roberta Bruschetta
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Младший исследователь:
- Simona Campisi
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Младший исследователь:
- Maria Valeria Maiorana
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Главный следователь:
- Gennaro Tartarisco
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Младший исследователь:
- Serena Iacono Isidoro
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Младший исследователь:
- Concetta Polizzi
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Младший исследователь:
- Renato Tino
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Младший исследователь:
- Marco Germanotta
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Контакт:
- Serena Iacono Isidoro
- Номер телефона: +393281655820
- Электронная почта: serena.iaconoisidoro@irib.cnr.it
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Младший исследователь:
- Irene Aprile
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Младший исследователь:
- Mariacristina Siotto
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Младший исследователь:
- Alessandro Guerrini
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Младший исследователь:
- Monia Andrea Papa
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Младший исследователь:
- Giorgia Bruschetta
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Младший исследователь:
- Barbara Caci
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Младший исследователь:
- Maria Cocchiara
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Младший исследователь:
- Flavia Altavilla
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Младший исследователь:
- Alessia Valdesi
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Младший исследователь:
- Chiara Urone
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Младший исследователь:
- Giulia Giordano
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Критерии участия
Критерии приемлемости
Возраст, подходящий для обучения
- Взрослый
- Пожилой взрослый
Принимает здоровых добровольцев
Описание
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).
Учебный план
Как устроено исследование?
Детали дизайна
- Основная цель: Профилактика
- Распределение: Рандомизированный
- Интервенционная модель: Параллельное назначение
- Маскировка: Нет (открытая этикетка)
Оружие и интервенции
Группа участников / Армия |
Вмешательство/лечение |
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Экспериментальный: 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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Другой: 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. |
Что измеряет исследование?
Первичные показатели результатов
Мера результата |
Мера Описание |
Временное ограничение |
|---|---|---|
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World Health Organization Quality of Life (WHOQoL)
Временное ограничение: 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)
Временное ограничение: 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)
Временное ограничение: 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)
Временное ограничение: 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)
Временное ограничение: 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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Вторичные показатели результатов
Мера результата |
Мера Описание |
Временное ограничение |
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Heart Rate
Временное ограничение: 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)
Временное ограничение: 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
Временное ограничение: 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)
Временное ограничение: 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
Временное ограничение: 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
Временное ограничение: 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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Соавторы и исследователи
Следователи
- Главный следователь: Gennaro Tartarisco, Institute for Biomedical Research and Innovation (IRIB)-National Reasearch Council (CNR)
Публикации и полезные ссылки
Общие публикации
- 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
Даты записи исследования
Изучение основных дат
Начало исследования (Действительный)
Первичное завершение (Оцененный)
Завершение исследования (Оцененный)
Даты регистрации исследования
Первый отправленный
Впервые представлено, что соответствует критериям контроля качества
Первый опубликованный (Действительный)
Обновления учебных записей
Последнее опубликованное обновление (Действительный)
Последнее отправленное обновление, отвечающее критериям контроля качества
Последняя проверка
Дополнительная информация
Термины, связанные с этим исследованием
Ключевые слова
Дополнительные соответствующие термины MeSH
Другие идентификационные номера исследования
- CNR-IRIB-PRO-2026-004
Планирование данных отдельных участников (IPD)
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Изучает продукт устройства, регулируемый Управлением по санитарному надзору за качеством пищевых продуктов и медикаментов США.
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