Ampel - Artificial Intelligence facing Multidimensional Poverty in Elderly is a research project focused on the use of state-of-the-art technologies to detect multidimensional poverty in a specific vulnerable group: the elderly. The aim of the project is therefore to recognise a set of heterogeneous indicators in order to develop a model capable of defining the risk of poverty. This risk refers not only to income and wealth, but also to material and social deprivation. The data collected serve as input to machine learning models to define three levels of susceptibility to poverty, corresponding to the SEMAPHORE variable. The questionnaire includes the following sections: - socio-demographic questions - socioeconomic conditions: economic stress, material deprivation, housing conditions - difficulty in accessing health care and services - health: general health conditions, physical and sensory functional limitations, chronic diseases and conditions, risk factors, psychologic well-being - daily life: support, generalized trust, safety, social relationships, participation in social activities - subjective well-being. The distributed materials include files and syntaxes that enable reproducibility of the results of the analyses carried out by the research team.

490 individuals. Convenience sample

Computer-Assisted Telephone Interviewing (CATI)