Summary information

Study title

AMPEL. Artificial intelligence facing Multidimensional Poverty in ELderly (2022-2023)

Creator

Gasparini, Francesca (Università degli Studi di Milano-Bicocca)

Study number / PID

SN257 (UniData)

10.20366/unimib/unidata/SN257-1.0 (DOI)

Data access

Information not available

Series

Not available

Abstract

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.

Methodology

Data collection period

22/06/2022 - 09/07/2023

Country

Italy

Time dimension

cross-section

Analysis unit

individual

Universe

residents in Lombardy aged 50 years and over

Sampling procedure

490 individuals. Convenience sample

Kind of data

individual data

Data collection mode

Computer-Assisted Telephone Interviewing (CATI)

Access

Publisher

UniData - Bicocca Data Archive

Publication year

2024

Terms of data access

Data are released for research and teaching purposes only. The redistribution to the third party, even in partial form, of data is not allowed.