Abstract
Background: Studies show that the use of information and communications technologies (ICTs), including smartphones, tablets, computers, and the internet, varies by demographic factors such as age, gender, and educational attainment. However, the connections between ICT use and factors such as ethnicity and English proficiency, especially among Asian American older adults, remain less explored. The technology acceptance model (TAM) suggests that 2 key attitudinal factors, perceived usefulness (PU) and perceived ease of use (PEOU), influence technology acceptance. While the TAM has been adapted for older adults in China, Taiwan, Singapore, and Korea, it has not been tested among Asian American older adults, a population that is heterogeneous and experiences language barriers in the United States. Objective: This study aims to examine the relationships among demographics (age, gender, educational attainment, ethnicity, and English proficiency), PU, PEOU, and ICT use among low-income Asian American older adults. Two outcomes were examined: smartphone use and ICT use, each measured by years of experience and current frequency of use. Methods: This was a secondary data analysis from a cross-sectional baseline survey of the Lighthouse Project, which provided free broadband, ICT devices, and digital literacy training to residents living in 8 affordable senior housing communities across California. This analysis focused on Asian participants aged ≥62 years (N=392), specifically those of Korean, Chinese, Vietnamese, Filipino, and other Asian ethnicities (eg, Hmong and Japanese). Hypotheses were examined using descriptive statistics, correlation analysis, and hierarchical regression analysis. Results: Younger age, higher education, and greater English proficiency were positively associated with smartphone use (age: β=–.202; P
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Martinez, P. D. L., Tancredi, D., Pavel, M., Garcia, L., & Young, H. M. (2024). Technology Acceptance Among Low-Income Asian American Older Adults: Cross-Sectional Survey Analysis. Journal of Medical Internet Research, 26(1). https://doi.org/10.2196/52498
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