| Contributors: |
Okoye, C; Cuffaro, L; Pozzi, F; Ferrara, M; Noale, M; Calciolari, S; Chicco, D; Cincotti, F; Daini, R; Finazzi, A; Francioso, L; Gasparini, F; Pagan, E; Ribino, P; Romeo, Z; Sala, G; Solfrizzi, V; Zambon, A; Maggi, S; Bellelli, G; Ferrarese, C; Airoldi, C; Aloisi, A; Appollonio, I; Bazzini, C; Bochicchio, M; Bologna, M; Brattico, E; Bruno, G; Bulgari, M; Canevelli, M; Capone, S; Ceolin, C; Chiaradonna, F; Colamarino, E; Conti, E; Corsonello, A; Cortelessa, G; Crudele, L; Custodero, C; De Luca, A; Delussi, M; Di Napoli, C; Dibello, V; Franchi, M; Ganora, D; Gesualdo, L; Goldin, E; Grossi, A; Isella, V; Lenti, R; Leone, A; Locati, S; Logrieco, A; Logroscino, G; Macchia, E; Mantuano, P; Massimi, A; Matteini, P; Messina, G; Moretti, L; Natalello, A; Orlandi, I; Paragliola, G; Paparella, G; Pegoraro, S; Pirrelli, V; Quaranta, N; Riccardi, G; Romano, D; Saibene, A; Sala, A; Sciurti, E; Luca, S; Siciliano, P; Silanos, F; Tamburrano, A; Tosi, G; Tratsevich, A; Tremolizzo, L; Villari, P; Vezzoso, A; Zoia, C |
| Description: |
Objectives Preventing age-related complications is a critical priority for health systems. Within the Age-It program, Spoke 8 aims to evaluate scalable, multicomponent, technology-assisted interventions to prevent frailty and mitigate functional and cognitive decline in older adults across different care settings. Methods Spoke 8 includes three clinical studies conducted in community, hospital, and long-term care settings, supported by cross-cutting work packages on digital infrastructure, technology development, and economic evaluation. The intervention model integrates physical, cognitive, nutritional, and psychosocial components, supported by digital tools, biomarkers of aging, and a centralized data platform. Results The project is expected to generate evidence on the effectiveness, feasibility, and cost-effectiveness of multidomain interventions implemented across diverse real-world settings, including community, hospital, and long-term care. Technology-assisted strategies - such as wearable sensors and digital cognitive tools - may enhance adherence and enable remote monitoring, while also supporting more personalized care delivery. The integration of artificial intelligence will facilitate the interpretation of complex clinical and biological data, improving risk stratification and the early identification of individuals most likely to benefit from targeted interventions. Together, these approaches may help reduce hospitalizations, delay functional decline, and promote aging in place. Discussion This initiative supports the transition toward more integrated and equitable care models for older adults. Through the implementation of scalable, person-centered interventions within routine services, the project offers policy-relevant strategies to address frailty and functional decline - contributing to the redesign of aging care in Italy and providing insights applicable across diverse health systems facing the challenges of population aging countries. |