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城市老年人使用远程健康管理服务意向的决定因素:接受和使用技术的统一理论视角。

Determinants of intention with remote health management service among urban older adults: A Unified Theory of Acceptance and Use of Technology perspective.

机构信息

College of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai, China.

School of Creativity and Art, Shanghai Tech University, Shanghai, China.

出版信息

Front Public Health. 2023 Jan 26;11:1117518. doi: 10.3389/fpubh.2023.1117518. eCollection 2023.

DOI:10.3389/fpubh.2023.1117518
PMID:36778558
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9909471/
Abstract

BACKGROUND

Although older adults health management systems have been shown to have a significant impact on health levels, there remains the problem of low use rate, frequency of use, and acceptance by the older adults. This study aims to explore the significant factors which serve as determinants of behavioral intention to use the technology, which in turn promotes actual use.

METHODS

This study took a total of 402 urban older adults over 60 years to explore the impact of the use behavior toward remote health management (RHM) through an online questionnaire. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT), the author adds four dimensions: perceived risk, perceived value, perceived interactivity and individual innovation, constructed an extended structural equation model of acceptance and use of technology, and analyzed the variable path relationship.

RESULTS

In this study, the factor loading is between 0.61 and 0.98; the overall Cronbach's Alpha coefficients are >0.7; The composite reliability ranges from 0.59 to 0.91; the average variance extraction ranges from 0.51 to 0.85, which shows the good reliability, validity, and discriminant validity of the constructed model. The influencing factors of the behavioral intention of the older adults to accept the health management system are: effort expectation, social influences, perceived value, performance expectation, perceived interactivity and perceived risk. Effort expectation has a significant positive impact on performance expectation. Individual innovation positively impacts performance expectation and perceived interactivity. Perceived interactivity and behavioral intention have a significant positive effect on the use behavior of the older adults, while the facilitating conditions have little effect on the use behavior.

CONCLUSIONS

This paper constructs and verifies the extended model based on UTAUT, fully explores the potential factors affecting the use intention of the older adult users. According to the research findings, some suggestions are proposed from the aspects of effort expectation, performance expectation, perceived interaction and perceived value to improve the use intention and user experience of Internet-based health management services in older adults.

摘要

背景

尽管老年人健康管理系统已被证明对健康水平有重大影响,但仍存在使用率低、使用频率低以及老年人接受度低的问题。本研究旨在探讨影响老年人使用远程健康管理(RHM)技术的行为意向的重要因素,进而促进实际使用。

方法

本研究共选取了 402 名 60 岁以上的城市老年人,通过在线问卷探索他们对远程健康管理的使用行为的影响。基于统一技术接受和使用模型(UTAUT),作者增加了四个维度:感知风险、感知价值、感知互动性和个体创新性,构建了接受和使用技术的扩展结构方程模型,并分析了变量路径关系。

结果

在本研究中,因子载荷在 0.61 到 0.98 之间;整体克朗巴哈α系数大于 0.7;组合可靠性范围在 0.59 到 0.91 之间;平均方差提取范围在 0.51 到 0.85 之间,这表明构建模型具有良好的可靠性、有效性和判别有效性。影响老年人接受健康管理系统行为意向的因素有:努力期望、社会影响、感知价值、绩效期望、感知互动性和感知风险。努力期望对绩效期望有显著的正向影响。个体创新性对绩效期望和感知互动性有正向影响。感知互动性和行为意向对老年人的使用行为有显著的正向影响,而促进条件对使用行为的影响较小。

结论

本文在 UTAUT 的基础上构建和验证了扩展模型,充分探讨了影响老年人用户使用意向的潜在因素。根据研究结果,从努力期望、绩效期望、感知互动和感知价值等方面提出了一些建议,以提高老年人对基于互联网的健康管理服务的使用意向和用户体验。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eed4/9909471/7e29e47812ca/fpubh-11-1117518-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eed4/9909471/92e3e3c1c407/fpubh-11-1117518-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eed4/9909471/de6a6cfae55e/fpubh-11-1117518-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eed4/9909471/36e0a01535ad/fpubh-11-1117518-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eed4/9909471/7e29e47812ca/fpubh-11-1117518-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eed4/9909471/92e3e3c1c407/fpubh-11-1117518-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eed4/9909471/de6a6cfae55e/fpubh-11-1117518-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eed4/9909471/36e0a01535ad/fpubh-11-1117518-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eed4/9909471/7e29e47812ca/fpubh-11-1117518-g0004.jpg

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