%0 Journal Article
%@ 1438-8871
%I JMIR Publications
%V 27
%N 
%P e57122
%T Identifying Profiles of Digital Literacy Among Community-Dwelling Korean Older Adults: Latent Profile Analysis
%A Shin,Jiyoung
%A Kang,Hun
%A Choi,Seongmi
%A Chu,Sang Hui
%A Choi,JiYeon
%+ Mo-Im Kim Nursing Research Institute, College of Nursing, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea, 82 2 2228 3301, jychoi610@yuhs.ac
%K digital literacy
%K digital divide
%K older adults
%K South Korea
%K latent profile analysis
%D 2025
%7 19.2.2025
%9 Original Paper
%J J Med Internet Res
%G English
%X Background: The digital divide is apparent not only between older and younger generations but also within the older adult population itself. Identifying digital literacy profiles among older adults is crucial for developing targeted strategies to narrow this divide. Objective: This study aimed to identify profiles of digital literacy among community-dwelling older adults and to examine factors associated with these profiles. Methods: Data were collected from community-dwelling older adults in South Korea through a nationwide cross-sectional survey that assessed digital literacy and related factors. Digital literacy was evaluated across 3 domains: information and communication (9 items), content creation and management (4 items), and safety and security (9 items). Latent profile analysis was used to identify profiles of digital literacy among community-dwelling older adults, and multinomial logistic regression was used to identify predictors of profile membership. Results: A total of 1016 older adults completed structured questionnaires (average age 68, SD 6.5 years; 486/1016, 47.8% men). Three digital literacy profiles were identified (P<.001): “low level” (346/1016, 34.1%), “middle level” (374/1016, 36.8%), and “high level” (296/1016, 29.1%). With the “middle-level” digital literacy group as the reference group, older adult participants (odds ratio [OR] 1.11, 95% CI 1.07-1.15) with less than a middle school education (vs with a college degree or higher; OR 7.22, 95% CI 2.31-22.54), who needed help with one of the 10 instrumental daily activities (vs ≥2 activities; OR 3.06, 95% CI 1.11-8.40) and who did not engage in in-person social activities (OR 1.81, 95% CI 1.07-3.07), were more likely to be in the “low-level” group. Women were less likely to be in the “high-level” digital literacy group than men (OR 0.45, 95% CI 0.25-0.80). Participants with less than a college education were also less likely to be in the “high-level” group, with those having less than a middle school education showing the lowest OR (OR 0.17, 95% CI 0.07-0.41). Those who had never worked (OR 0.23, 95% CI 0.06-0.90) and those not engaging in regular physical exercise (OR 0.58, 95% CI 0.40-0.84) were also less likely to be in the “high-level” digital literacy group. Participants with greater social support were more likely to be in the “high-level” digital literacy group (OR 1.70, 95% CI 1.22-2.37). Conclusions: These findings underscore the characteristics linked to lower digital literacy and suggest a tailored approach to meet the needs of diverse groups of older adults in a digitalizing society. To promote digital literacy among older adults, potential strategies include improving access to and guidance for using digital devices, specifically designed for this demographic, as well as promoting social support and encouraging participation in social activities. 
%M 39969960
%R 10.2196/57122
%U https://www.jmir.org/2025/1/e57122
%U https://doi.org/10.2196/57122
%U http://www.ncbi.nlm.nih.gov/pubmed/39969960