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Aim of this paper is to describe the protocol of the study "Impact of a Community-based Program on Prevention and Mitigation of Frailty in community-dwelling older adults" developed in the framework of the European Innovation Partnership on Active and Healthy Ageing. This proposal has been developed by the Partnership Action groups on frailty, fall prevention and polypharmacy in older. The proposal wants to assess the impact of community-based programs aimed to counteract three main outcomes related to frailty: hospitalization, institutionalization and death. Bringing together researchers from seven European countries, the proposal aims to achieve the critical mass and the geographical extension enough to provide information useful to all older European citizens. An observational study will be carried out to calculate the incidence of the different outcomes in relation to the various interventions that will be assessed; results will be compared with data coming from already established national, regional and local dataset using the observed/expected approach. The sample will be made up by at least 2000 citizens for each outcome. All the citizens will be assessed at the baseline with two multidimensional questionnaires: the RISC questionnaire and the Short Functional Geriatric Evaluation questionnaire. The outcomes will be assessed every six-twelve months.

Preclinical studies are essentially based on animal models of a particular disease. The primary purpose of preclinical efficacy studies is to support generalization of treatment-effect relationships to human subjects. Researchers aim to demonstrate a causal relationship between an investigational agent and a disease-related phenotype in such models. Numerous factors can muddle reliable inferences about such cause-effect relationships, including biased outcome assessment due to experimenter expectations. For instance, responses in a particular inbred mouse might be specific to the strain, limiting generalizability. Selecting well-justified and widely acknowledged model systems represents the best start in designing preclinical studies, especially to overcome any potential bias related to the model itself. This is particularly true in the research that focuses on aging, which carries unique challenges, mainly attributable to the fact that our already long lifespan makes designing experiments that use people as subjects extremely difficult and largely impractical.