Acceptance of Technologies for Aging in Place: A Conceptual Model

被引:39
作者
Jaschinski, Christina [1 ]
Ben Allouch, Somaya [2 ]
Peters, Oscar [3 ]
Cachucho, Ricardo [4 ]
van Dijk, Jan A. G. M. [5 ]
机构
[1] Saxion Univ Appl Sci, Res Grp Technol Hlth & Care, MH Tromplaan 28, NL-7513 AB Enschede, Netherlands
[2] Amsterdam Univ Appl Sci, Digital Life, Amsterdam, Netherlands
[3] Saxion Univ Appl Sci, Enschede, Netherlands
[4] Leiden Univ, Leiden Inst Adv Comp Sci LIACS, Leiden, Netherlands
[5] Univ Twente, Enschede, Netherlands
关键词
ambient assisted living; assistive technology; healthy aging; technology adoption; theory of planned behavior; structural equation modeling; ASSISTED LIVING TECHNOLOGIES; OLDER-ADULTS; INFORMATION-TECHNOLOGY; PLANNED BEHAVIOR; USER ACCEPTANCE; MISSING DATA; HEALTH; HOME; CARE; PERCEPTIONS;
D O I
10.2196/22613
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: Older adults want to preserve their health and autonomy and stay in their own home environment for as long as possible. This is also of interest to policy makers who try to cope with growing staff shortages and increasing health care expenses. Ambient assisted living (AAL) technologies can support the desire for independence and aging in place. However, the implementation of these technologies is much slower than expected. This has been attributed to the lack of focus on user acceptance and user needs. Objective: The aim of this study is to develop a theoretically grounded understanding of the acceptance of AAL technologies among older adults and to compare the relative importance of different acceptance factors. Methods: A conceptual model of AAL acceptance was developed using the theory of planned behavior as a theoretical starting point. A web-based survey of 1296 older adults was conducted in the Netherlands to validate the theoretical model. Structural equation modeling was used to analyze the hypothesized relationships. Results: Our conceptual model showed a good fit with the observed data (root mean square error of approximation 0.04; standardized root mean square residual 0.06; comparative fit index 0.93; Tucker-Lewis index 0.92) and explained 69% of the variance in intention to use. All but 2 of the hypothesized paths were significant at the P<.001 level. Overall, older adults were relatively open to the idea of using AAL technologies in the future (mean 3.34, SD 0.73). Conclusions: This study contributes to a more user-centered and theoretically grounded discourse in AAL research. Understanding the underlying behavioral, normative, and control beliefs that contribute to the decision to use or reject AAL technologies helps developers to make informed design decisions based on users' needs and concerns. These insights on acceptance factors can be valuable for the broader field of eHealth development and implementation.
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页数:16
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