Unveiling the complexity of Italian NEET status through Latent Class Analysis: Examining NEET profiles and their engagement with Public Employment Services (PES)

dc.contributor.authorEllena, A. M.
dc.contributor.authorRocca, A.
dc.contributor.authorMazzocchi, P.
dc.contributor.authorZambelli, M.
dc.contributor.authorMarzana, D.
dc.contributor.authorPizzolante, F.
dc.contributor.authorSimões, F.
dc.contributor.authorDe Luca, G.
dc.contributor.authorMarta, E.
dc.date.accessioned2025-10-09T08:30:51Z
dc.date.available2025-10-09T08:30:51Z
dc.date.issued2025
dc.date.updated2025-10-10T15:59:45Z
dc.description.abstractThis study delves into the complex issue of NEET (Not in Employment, Education, or Training) status in Italy, using Latent Class Analysis (LCA) to identify distinct profiles within this heterogeneous group. The research, based on a survey of 970 young Italian NEETs, goes beyond broad categorizations to explore the socio-demographic, economic, and motivational factors that contribute to their situations. Six distinct classes of NEETs were identified, each with unique characteristics, including “Affluent Rural Caregivers in Northern Italy,” “Young Educated Unemployed,” “Long-Term NEETs in Southern Italy,” “Disadvantaged Caregivers in Southern Italy,” “Disadvantaged Rural Men in Northern Italy,” and “Affluent Discouraged NEETs”. The study investigates the relationship of these profiles with Public Employment Services (PES), revealing different motivations for seeking assistance and varied willingness to accept employment conditions such as relocation or temporary work. Significant associations were found between NEET class and the motivation for economic support, willingness to move abroad or within Italy, and acceptance of part-time or temporary work. The findings emphasize the need for tailored interventions that address the specific needs and barriers of each NEET subgroup, rather than a one-size-fits-all approach. The research highlights the complex interplay of geographic, economic, educational, and gender factors in shaping NEET status in Italy.eng
dc.description.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.citationEllena, A. M., Rocca, A., Mazzocchi, P., Zambelli, M., Marzana, D., Pizzolante, F., Simões, F., De Luca, G., & Marta, E. (2025). Unveiling the complexity of Italian NEET status through Latent Class Analysis: Examining NEET profiles and their engagement with Public Employment Services (PES). Social Indicators Research, 179(3), 1665-1686. https://doi.org/10.1007/s11205-025-03684-w
dc.identifier.doi10.1007/s11205-025-03684-w
dc.identifier.issn0303-8300
dc.identifier.urihttp://hdl.handle.net/10071/35316
dc.language.isoeng
dc.number3
dc.pagination1665 - 1686
dc.peerreviewedyes
dc.publisherSpringer
dc.rightsopen access
dc.subjectNEET (Not in educationeng
dc.subjectemployment either training)eng
dc.subjectPublic employment serviceseng
dc.subjectPolicieseng
dc.subjectLatent class analysiseng
dc.subject.fosDomínio/Área Científica::Ciências Sociais::Psicologiapor
dc.subject.fosDomínio/Área Científica::Ciências Sociais::Sociologiapor
dc.subject.fosDomínio/Área Científica::Ciências Sociais::Outras Ciências Sociaispor
dc.subject.fosDomínio/Área Científica::Humanidades::Outras Humanidadespor
dc.titleUnveiling the complexity of Italian NEET status through Latent Class Analysis: Examining NEET profiles and their engagement with Public Employment Services (PES)eng
dc.typearticle
dc.volume179
dspace.entity.typePublicationen
iscte.alternateIdentifiers.scopus2-s2.0-105011397696
iscte.alternateIdentifiers.wosWOS:WOS:001534682900001
iscte.identifier.cienciahttps://ciencia.iscte-iul.pt/id/ci-pub-113178
iscte.journalSocial Indicators Research
iscte.subject.odsTrabalho digno e crescimento económicopor
iscte.subject.odsReduzir as desigualdadespor

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