Technology Acceptance Among Low-Income Asian American Older Adults: Cross-Sectional Survey Analysis
Authors: DeLange Martinez Pauline , Tancredi Daniel , Pavel Misha , Garcia Lorena , Young Heather M 
Published: September 2024

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<.001; education: β=.210; P<.001; and English proficiency: β=.124; P=.048) and ICT use (age: β=–.157; P=.002; education: β=.215; P<.001; and English proficiency: β=.152; P=.01). Male gender was positively associated with PEOU (β=.111; P=.047) but not with PU (β=–.031; P=.59), smartphone use (β=.023; P=.67), or ICT use (β=.078; P=.16). Ethnicity was a significant predictor of PU (F4,333=5.046; P<.001), PEOU (F4,345=4.299; P=.002), and ICT use (F4,350=3.177; P=.01), with Chinese participants reporting higher levels than Korean participants, who were the reference group (β=.143; P=.007). PU and PEOU were positively correlated with each other (r=0.139, 95% CI=0.037-0.237; P=.007), and both were significant predictors of smartphone use (PU: β=.158; P=.002 and PEOU: β=.166; P=.002) and ICT use (PU: β=.117; P=.02 and PEOU: β=0.22; P<.001), even when controlling for demographic variables.

Conclusions
The findings support the use of the TAM among low-income Asian American older adults. In addition, ethnicity and English proficiency are significant predictors of smartphone and ICT use among this population. Future interventions should consider heterogeneity and language barriers of this population to increase technology acceptance and use.