Technology Acceptance Among Low-Income Asian American Older Adults: Cross-Sectional Survey Analysis
- PMID: 39576987
- PMCID: PMC11624446
- DOI: 10.2196/52498
Technology Acceptance Among Low-Income Asian American Older Adults: Cross-Sectional Survey Analysis
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<.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.
Keywords: Asian American; ICT; aged; digital divide; immigrant; information and communications technology; internet; mobile phone; older adults; technology acceptance model; vulnerable populations.
©Pauline DeLange Martinez, Daniel Tancredi, Misha Pavel, Lorena Garcia, Heather M Young. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 22.11.2024.
Conflict of interest statement
Conflicts of Interest: None declared.
Figures
Similar articles
-
Adapting the Technology Acceptance Model to Examine the Use of Information Communication Technologies and Loneliness Among Low-Income, Older Asian Americans: Cross-Sectional Survey Analysis.JMIR Aging. 2025 Jan 8;8:e63856. doi: 10.2196/63856. JMIR Aging. 2025. PMID: 39778204 Free PMC article.
-
The Role of Health in the Technology Acceptance Model Among Low-Income Asian American Older Adults: Cross-Sectional Survey Analysis.JMIR Form Res. 2024 Dec 3;8:e57009. doi: 10.2196/57009. JMIR Form Res. 2024. PMID: 39625744 Free PMC article.
-
Prescription of Controlled Substances: Benefits and Risks.2025 Jul 6. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 Jan–. 2025 Jul 6. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 Jan–. PMID: 30726003 Free Books & Documents.
-
Comparison of self-administered survey questionnaire responses collected using mobile apps versus other methods.Cochrane Database Syst Rev. 2015 Jul 27;2015(7):MR000042. doi: 10.1002/14651858.MR000042.pub2. Cochrane Database Syst Rev. 2015. PMID: 26212714 Free PMC article.
-
Computer and mobile technology interventions for self-management in chronic obstructive pulmonary disease.Cochrane Database Syst Rev. 2017 May 23;5(5):CD011425. doi: 10.1002/14651858.CD011425.pub2. Cochrane Database Syst Rev. 2017. PMID: 28535331 Free PMC article.
Cited by
-
Experiences and Expectations of Immigrant and Nonimmigrant Older Adults Regarding eHealth Services: Qualitative Interview Study.J Med Internet Res. 2025 Mar 14;27:e64249. doi: 10.2196/64249. J Med Internet Res. 2025. PMID: 40085846 Free PMC article.
-
Adapting the Technology Acceptance Model to Examine the Use of Information Communication Technologies and Loneliness Among Low-Income, Older Asian Americans: Cross-Sectional Survey Analysis.JMIR Aging. 2025 Jan 8;8:e63856. doi: 10.2196/63856. JMIR Aging. 2025. PMID: 39778204 Free PMC article.
-
The Role of Health in the Technology Acceptance Model Among Low-Income Asian American Older Adults: Cross-Sectional Survey Analysis.JMIR Form Res. 2024 Dec 3;8:e57009. doi: 10.2196/57009. JMIR Form Res. 2024. PMID: 39625744 Free PMC article.
-
Climbing the ladder of health technology utilization: facilitators and dynamic mechanism of clinicians' contrast-enhanced ultrasound utilization in China.BMC Cancer. 2025 Jul 4;25(1):1142. doi: 10.1186/s12885-025-14537-7. BMC Cancer. 2025. PMID: 40616003 Free PMC article.
References
-
- Chan DY, Lee SW, Teh PL. Factors influencing technology use among low-income older adults: a systematic review. Heliyon. 2023 Sep;9(9):e20111. doi: 10.1016/j.heliyon.2023.e20111. https://linkinghub.elsevier.com/retrieve/pii/S2405-8440(23)07319-X S2405-8440(23)07319-X - DOI - PMC - PubMed
-
- Anderson M, Perrin A. Tech adoption climbs among older adults. Pew Research Center. 2017. [2021-03-20]. https://www.pewresearch.org/internet/2017/05/17/tech-adoption-climbs-amo...
-
- Vogels EA. Digital divide persists even as Americans with lower incomes make gains in tech adoption. Pew Research Center. 2021. [2021-12-30]. https://www.pewresearch.org/fact-tank/2021/06/22/digital-divide-persists...
-
- Tran V. Asian American seniors are often left out of the national conversation on poverty. Urban Institute. 2017. [2022-01-21]. https://www.urban.org/urban-wire/asian-american-seniors-are-often-left-o... .