JMIR Publications

ABSTRACT

Background:

There are demonstrated associations between the use of information communication technologies (ICTs), such as smartphones, tablets, computers, and the internet, and demographic variables including age, gender, and educational attainment. Less explored are relationships among ethnicity, English proficiency, and ICT use, particularly among older Asian Americans. The Technology Acceptance Model (TAM) suggests two 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 older Asian Americans, a population that is heterogenous and experiences language barriers in the US.

Objective:

This study purpose was 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; both incorporating years’ experience and current frequency of use.

Methods:

This was a secondary data analysis from a cross-sectional baseline survey of The Lighthouse Project for Older Adults, which provided free broadband, ICT devices, and digital literacy training to residents living in eight affordable senior housing communities across California. This analysis focused on Asian participants aged 62 and older (N=392) representing Korean, Chinese, Vietnamese, Filipino, and other Asian ethnicities (e.g., Hmong, 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; English proficiency: β =.124, P =.048) and ICT use (age: β =-.157, P =.002; education: β =.215, P <.001; English proficiency: β =.152, P =.014). Male gender was positively associated with PEOU (β =.111, P =.047), but not with PU (β =-.031, P =.589), smartphone use (β =.023, P =.672), or ICT use (β =.078, P =.156). 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 =0.014), 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 (95% CI)= .139 (.037, .237), P =.007), and both were significant predictors of smartphone use (PU: β =.158, P =.002; PEOU: β =.166, P =.002) and ICT use (PU: β =.117, P =.022; PEOU: β =.221, P <.001), even when controlling for demographic variables.

Conclusions:

The findings support the TAM among low-income, Asian American older adults. Additionally, 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.