Pauline DeLange Martinez, Daniel Tancredi, Misha Pavel, Lorena Garcia, Heather M Young
{"title":"美国低收入亚裔老年人对科技的接受程度:横断面调查分析。","authors":"Pauline DeLange Martinez, Daniel Tancredi, Misha Pavel, Lorena Garcia, Heather M Young","doi":"10.2196/52498","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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 (F<sub>4,333</sub>=5.046; P<.001), PEOU (F<sub>4,345</sub>=4.299; P=.002), and ICT use (F<sub>4,350</sub>=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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"26 ","pages":"e52498"},"PeriodicalIF":5.8000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Technology Acceptance Among Low-Income Asian American Older Adults: Cross-Sectional Survey Analysis.\",\"authors\":\"Pauline DeLange Martinez, Daniel Tancredi, Misha Pavel, Lorena Garcia, Heather M Young\",\"doi\":\"10.2196/52498\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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 (F<sub>4,333</sub>=5.046; P<.001), PEOU (F<sub>4,345</sub>=4.299; P=.002), and ICT use (F<sub>4,350</sub>=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.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":16337,\"journal\":{\"name\":\"Journal of Medical Internet Research\",\"volume\":\"26 \",\"pages\":\"e52498\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2024-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Medical Internet Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2196/52498\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Medical Internet Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2196/52498","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Technology Acceptance Among Low-Income Asian American Older Adults: Cross-Sectional Survey Analysis.
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.
期刊介绍:
The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades.
As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor.
Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.