Acceptance of technology related to healthcare among older Korean adults in rural areas: A mixed-method study |
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Affiliation: | 1. Elaine Marieb College of Nursing, University of Massachusetts Amherst, 651 North Pleasant Street, Amherst, MA, 01003, United States;2. College of Nursing and Research Institute of Nursing Science, Ajou University, 164, World Cup-ro, Yeongtong-gu, Suwon-si, 16499, Gyeonggi-do, Republic of Korea |
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Abstract: | Many older adults find it difficult to accept new forms of information and communication technology (ICT), despite its advantages such as convenience and efficiency. It is necessary to identify the reasons for low ICT use among older people—even among those with positive attitudes toward ICT—to help older adults cope with social changes and bridge the digital divide. This study explored technology acceptance and related factors among older Korean adults living in rural areas. Based on an existing model (the senior technology acceptance model), a new conceptual framework for technology acceptance was proposed, and the framework was tested using pathway analysis. Semi-structured interviews were conducted in three focus groups (n = 15), and a survey questionnaire was administered to older Korean adults living in a rural area (n = 233) from 17 January 2021 to 18 February 2021. Qualitative data were analyzed using directed content analysis, and quantitative data were analyzed using pathway analysis. Four categories, 11 subcategories, and 18 codes were identified, and a new conceptual framework was proposed based on the qualitative findings. The results of the model revealed significant positive direct paths from external controls (β = 0.45, p < .001), attitudinal beliefs (β = 0.33, p < .001), and cognitive health (β = 0.10, p = .040) to internal abilities. It is necessary to develop and apply a targeted and tailored ICT education program to improve self-efficacy and reduce anxiety regarding technology use among older Korean adults living in rural areas. |
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Keywords: | Technology Information technology Community health services Aged Rural population ICT"} {"#name":"keyword" "$":{"id":"pc_YX4WgoKe7b"} "$$":[{"#name":"text" "_":"Information and Communication Technology STAM"} {"#name":"keyword" "$":{"id":"pc_jDAcIVlbiT"} "$$":[{"#name":"text" "_":"Senior Technology Acceptance Model IRB"} {"#name":"keyword" "$":{"id":"pc_mw55WRvpYJ"} "$$":[{"#name":"text" "_":"Institutional Review Board CFI"} {"#name":"keyword" "$":{"id":"pc_aL6Rt69lVK"} "$$":[{"#name":"text" "_":"Comparative Fit Index TLI"} {"#name":"keyword" "$":{"id":"pc_B6pikBLCN3"} "$$":[{"#name":"text" "_":"Tucker–Lewis Index RMSEA"} {"#name":"keyword" "$":{"id":"pc_pZ5euIIP5h"} "$$":[{"#name":"text" "_":"Root Mean Squared Error of Approximation SRMR"} {"#name":"keyword" "$":{"id":"pc_mPvyJSFe6A"} "$$":[{"#name":"text" "_":"Standardized Root Mean squared Residual COVID-19"} {"#name":"keyword" "$":{"id":"pc_2zbNheoplv"} "$$":[{"#name":"text" "_":"Coronavirus Desease of 2019 |
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