Revealing the nuances of ‘Grey Digital Divide’ in Hong Kong: A latent profile analysis - Bobo Hi-Po Lau; Eric Ngai-Yin Shum; Alex Pak-Ki Kwok; Ben Chi-Pun Liu; Alex Chi-Keung Chan; Rick Yiu-Cho Kwan; Steve Fu-Fai Fong; Gigi Lam; Chung-Kin Tsang; Daniel Dick-Man Leung; Johnson Chun-Sing Cheung; Jason Tak-Sang Chow; et al. (PLoS ONE, 2025)
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. (200 words).