Who is online? A latent class analysis of internet activities and determinant characteristics of older people

Pantelaki, Evangelia; Maggi, Elena; Crotti, Daniele

Abstract

As Italy is the European country with the highest percentage of adults aged over 60, growing concerns have emerged about how the ageing population is living in an era of increasing digitalisation. According to the capability approach framework, Internet services can enable older adults to achieve social inclusiveness and independence, only if the variety of digital activities includes a large number of active ageing parameters. This is the first study that explores Internet use by Italian older adults and identifies latent groups of Internet users. We elaborated 13,597 responses from an Italian representative annual population survey and 40 different online activities were analysed using an Exploratory Factor Analysis and further elaborated together with sociodemographic variables in a Latent Class Analysis. Three classes of older Internet users were identified: Utilitarian, Familiar and Enjoyment users. The findings support the existence of heterogeneous older Internet users, at the same time showing the importance of personal characteristics to predict class membership. Being female, widowed, having a low income, being poorly educated, living alone, and having various comorbidities predicted fewer online activities. From a policy perspective, this study highlights that targeted training programmes together with improvements to digital infrastructures are essential to increase the level of Internet activities in later life as is the need for policies in favour of the disadvantaged groups in the older population.

Citation

Pantelaki, E., Maggi, E., & Crotti, D. (2023). Who is online? A latent class analysis of internet activities and determinant characteristics of older people. Computers in Human Behavior, 147, Article 107830. https://doi.org/10.1016/j.chb.2023.107830

• Journal Article Type: Article
• Acceptance Date: Jun 3, 2023
• Online Publication Date: Jun 15, 2023
• Publication Date: Oct 1, 2023
• Deposit Date: Jul 2, 2023
• Publicly Available Date: Jun 16, 2025
• Journal: Computers in Human Behavior
• Print ISSN: 0747-5632
• Electronic ISSN: 1873-7692
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 147
• Article Number: 107830
• DOI: https://doi.org/10.1016/j.chb.2023.107830
• Keywords: Aging Internet use; Digital inclusiveness; Exploratory factor analysis; Latent class analysis; Capability approach
• Public URL: https://uwe-repository.worktribe.com/output/10900825
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0747563223001814?via%3Dihub