DeLange Martinez Pauline, Tancredi Daniel, Pavel Misha, Garcia Lorena, Young Heather M
Betty Irene Moore School of Nursing, University of California, Davis, Sacramento, CA, United States.
Department of Pediatrics, University of California, Davis, Sacramento, CA, United States.
JMIR Aging. 2025 Jan 8;8:e63856. doi: 10.2196/63856.
Loneliness is a significant issue among older Asian Americans, exacerbated by the COVID-19 pandemic. Older age, lower income, limited education, and immigrant status heighten loneliness risk. Information communication technologies (ICTs) have been associated with decreased loneliness among older adults. However, older Asian Americans are less likely to use ICTs, particularly if they are immigrants, have limited English proficiency, or are low income. The Technology Acceptance Model posits that perceived usefulness (PU), and perceived ease of use (PEOU) are key factors in predicting technology use.
This study aimed to examine associations between PU, PEOU, ICT use, and loneliness among low-income, older Asian Americans.
Cross-sectional survey data were gathered from predominately older Asian Americans in affordable senior housing (N=401). Using exploratory factor analysis and Horn parallel analysis, we examined 12 survey items to identify factors accounting for variance in ICT use. We deployed structural equation modeling to explore relationships among the latent factors and loneliness, adjusting for demographic and cognitive factors.
Exploratory factor analysis and Horn parallel analysis revealed 3 factors that accounted for 56.48% (6.78/12) total variance. PEOU combined items from validated subscales of tech anxiety and comfort, accounting for a 28.44% (3.41/12) variance. ICT use combined years of technological experience, computer, tablet, and smartphone use frequency, accounting for 15.59% (1.87/12) variance. PU combined 2 items assessing the usefulness of technology for social connection and learning and accounted for a 12.44% (1.49/12) variance. The 3-factor structural equation modeling revealed reasonable fit indexes (χ=345.132; P<.001, chi-square minimum (CMIN)/df = 2595, comparative fit index (CFI)=0.93, Tucker-Lewis Index (TLI)=0.88). PEOU was positively associated with PU (β=.15; P=.01); PEOU and PU were positive predictors of ICT use (PEOU β=.26, P<.001; PU β=.18, P=.01); and ICT use was negatively associated with loneliness (β=-.28, P<.001). Demographic and health covariates also significantly influenced PU, PEOU, ICT use, and loneliness. English proficiency and education positively predicted PEOU (r=0.25, P<.001; r=0.26, P<.001) and ICT use (β=1.66, P=.03; β=.21, P<.001), while subjective cognitive decline and Asian ethnicity were positively associated with loneliness (β=.31, P<.001; β=.25, P<.001).
This study suggests that targeted interventions enhancing PU or PEOU could increase ICT acceptance and reduce loneliness among low-income Asian Americans. Findings also underscore the importance of considering limited English proficiency and subjective cognitive decline when designing interventions and in future research.
孤独是美国亚裔老年人中的一个重要问题，新冠疫情使其更加严重。年长、低收入、受教育程度有限以及移民身份会增加孤独风险。信息通信技术（ICT）与老年人孤独感的降低相关。然而，美国亚裔老年人使用ICT的可能性较小，尤其是那些移民、英语水平有限或低收入者。技术接受模型认为，感知有用性（PU）和感知易用性（PEOU）是预测技术使用的关键因素。
本研究旨在探讨低收入美国亚裔老年人中PU、PEOU、ICT使用与孤独感之间的关联。
横断面调查数据主要来自居住在经济适用型老年住房中的美国亚裔老年人（N = 401）。通过探索性因素分析和霍恩平行分析，我们对12个调查项目进行了检验，以确定解释ICT使用差异的因素。我们采用结构方程模型来探索潜在因素与孤独感之间的关系，并对人口统计学和认知因素进行了调整。
探索性因素分析和霍恩平行分析揭示了3个因素，它们解释了总方差的56.48%（6.78/12）。PEOU合并了来自经过验证的技术焦虑和舒适度子量表的项目，解释了28.44%（3.41/12）的方差。ICT使用合并了技术经验年限、计算机、平板电脑和智能手机的使用频率，解释了15.59%（1.87/12）的方差。PU合并了2个评估技术对社交联系和学习有用性的项目，解释了12.44%（1.49/12）的方差。三因素结构方程模型显示出合理的拟合指数（χ = 345.132；P <.001，卡方最小值（CMIN）/自由度 = 2.595，比较拟合指数（CFI）= 0.93，塔克 - 刘易斯指数（TLI）= 0.88）。PEOU与PU呈正相关（β =.15；P =.01）；PEOU和PU是ICT使用的正向预测因素（PEOU β =.26，P <.001；PU β =.18，P =.01）；ICT使用与孤独感呈负相关（β = -.
