Methods. Using data from 2014 Health and Retirement Study (n=717), this study conducted a latent class analysis (LCA) based on eight health technology uses using Mplus 8. Five classes were identified with different patterns of health technology use; namely the traditional phone group (only uses phone calls and texting), versatile group (uses all eight technologies in various degrees), health management tools group (mainly uses health management tools and websites), internet-based (mainly searches internet for health information), and brain game focused group (mainly uses brain game or training online). Multinomial logistic regression analysis was performed to examine factors associated with different groups using Stata 15.
Results. Versatile group was the largest (33%), followed by traditional phone (23%), internet-based (18%), health management tools (15%), and brain game focused (12%) group. Diversity existed across groups regarding their socio-demographic and health characteristics. Compared to traditional phone users, other types of digital based health technology users tend to be younger (versatile, health management tools, internet-based), female (internet-based, brain game focused), better educated (versatile, health management tools), whites (health management tools), experience fewer chronic illnesses (versatile, health management tools, brain game focused), and have less difficulty in physical functioning (internet-based, brain game focused).
Discussion. It is important to assist older adults to reap the full benefits of the evolving technology to meet their health management needs. Studies have demonstrated the advantages of health information technologies, including general positive health outcomes, decreased hospitalization rates, and increased patient satisfaction and support system development. While older adults are more inclined to use information and communication technologies than ever before, there is still a large gap in technology use between older adults and their younger counterparts. Intervention strategies should take into account the heterogeneity of technology use behaviors and contextual backgrounds of older adults. The potential link of technology use groups and health outcomes will be discussed.