Abstract
The ‘grey digital divide’ deprives older adults’ equitable access to information and support, and thereby, their well-being. Policies including subsidies for internet access and devices, digital literacy classes, and telehealth support attempted to close the divide. Yet, it remains doubtful whether the discrepancy could be narrowed, or simply transformed. The mandatory COVID track-and-trace policy, the government’s decade-long digital inclusivity initiatives and the city’s high degree of digitization makes Hong Kong an exemplar for exploring the post-pandemic digital divide. Utilizing a person-centered approach, this study elaborated the intergenerational differences in digital engagement with a random sample of 870 younger (aged 18–54 years) and older (aged 55 years or above) adults (52.1% female) via phone interviews. With 16 indicators of digital motivation, access, digital skills, and usage, latent profile analysis (LPA) yielded three profiles – Proficient, Intermediate, and Novice, with disparate patterns between the younger (90.2%, 8.8%, 0.9%) and the older (59.2%, 35.5%, 5.2%) groups, demonstrating a clear intergenerational divide. Socio-economic status influenced profile membership regardless of age, and that profile membership relates to the frequencies of various social contacts except with family/relatives. Our findings demonstrate how typology defines the needs and assists formulation of segmented interventions toward digital inclusivity.
| Original language | English |
|---|---|
| Article number | e0326413 |
| Number of pages | 31 |
| Journal | PLoS ONE |
| Volume | 20 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 9 Jul 2025 |
Bibliographical note
Publisher Copyright:© 2025 Lau et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding
BHPL is the author who received the funding. This project is funded by the Institutional Development Scheme Collaborative Research Grant of University Grants Committee, Hong Kong (Ref No.: UGC/IDS(C)15/H01/22). The URL of the funder website is: https://www. ugc.edu.hk/eng/rgc/funding_opport/ids_crg/. The funder did not play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.