• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

建模可穿戴健身设备的使用意愿和采用:基于 SEM-PLS 分析的研究。

Modeling the Intention and Adoption of Wearable Fitness Devices: A Study Using SEM-PLS Analysis.

机构信息

UKM Graduate School of Business, Universiti Kebangsaan Malaysia, Bangi, Malaysia.

Global Entrepreneurship Research and Innovation Centre, Universiti Malaysia Kelantan, Kota Bharu, Malaysia.

出版信息

Front Public Health. 2022 Jul 6;10:918989. doi: 10.3389/fpubh.2022.918989. eCollection 2022.

DOI:10.3389/fpubh.2022.918989
PMID:35875013
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9301884/
Abstract

Wearable fitness devices (WFDs) are prevalent personal technology that empowers the users' management and supervision of their personal health. The current study explored the impact of health consciousness, health motivation, perceived cost, compatibility, usefulness, and perceived technology accuracy with the intention to use the WFDs. Furthermore, the users' conspicuous consumption and intention promote the usage of WFDs. A cross-sectional and quantitative research design was utilized for the current study, followed by data collection through social media and a final analysis with 1,071 samples data. The data analysis was accomplished with the partial least square regression structural equation modeling. The findings of this study revealed that the users' level of health consciousness, perceived compatibility, usefulness, perceived cost, and technology accuracy significantly influenced the intention to use WFDs. However, the conspicuous consumption and intention indicated the support for the usage behavior of the WFDs. This behavior significantly moderated the relationship between the intention and usage behavior for the WFDs. This study contributed to the theoretical realm for prompting the intention to use the WFDs with personal protection motivation that depicts the coping strategy and technology level attributes that form the intention to use WFDs. The WFDs manufacturers should therefore focus on developing WFDs features that harness usage behavior among the adults. Developing the personal responsibility to reduce the burden of the healthcare system and taking care of personal health could promote the usage of the WFDs.

摘要

可穿戴健身设备 (WFD) 是一种流行的个人技术,可以帮助用户管理和监督个人健康。本研究探讨了健康意识、健康动机、感知成本、兼容性、有用性和感知技术准确性对使用 WFD 的意图的影响。此外,用户的炫耀性消费和意图促进了 WFD 的使用。本研究采用了横断面和定量研究设计,通过社交媒体收集数据,最后对 1071 个样本数据进行了分析。数据分析采用偏最小二乘回归结构方程模型完成。研究结果表明,用户的健康意识水平、感知兼容性、有用性、感知成本和技术准确性显著影响了使用 WFD 的意图。然而,炫耀性消费和意图表明支持 WFD 的使用行为。这种行为显著调节了 WFD 意图和使用行为之间的关系。本研究为促进个人保护动机的 WFD 使用意图做出了理论贡献,描述了构成使用 WFD 意图的应对策略和技术水平属性。因此,WFD 制造商应专注于开发能够利用成年人使用行为的 WFD 功能。培养减轻医疗体系负担和关注个人健康的个人责任感可以促进 WFD 的使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68e4/9301884/fe721e4f4394/fpubh-10-918989-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68e4/9301884/6f7b6b25cc43/fpubh-10-918989-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68e4/9301884/86244d090163/fpubh-10-918989-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68e4/9301884/fe721e4f4394/fpubh-10-918989-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68e4/9301884/6f7b6b25cc43/fpubh-10-918989-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68e4/9301884/86244d090163/fpubh-10-918989-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68e4/9301884/fe721e4f4394/fpubh-10-918989-g0003.jpg

相似文献

1
Modeling the Intention and Adoption of Wearable Fitness Devices: A Study Using SEM-PLS Analysis.建模可穿戴健身设备的使用意愿和采用:基于 SEM-PLS 分析的研究。
Front Public Health. 2022 Jul 6;10:918989. doi: 10.3389/fpubh.2022.918989. eCollection 2022.
2
Exploring the mass adoption potential of wearable fitness devices in Malaysia.探索可穿戴健身设备在马来西亚的大规模采用潜力。
Digit Health. 2023 Jun 4;9:20552076231180728. doi: 10.1177/20552076231180728. eCollection 2023 Jan-Dec.
3
How health motivation moderates the effect of intention and usage of wearable medical devices? An empirical study in Malaysia.健康动机如何调节可穿戴医疗设备的使用意图和使用的影响?马来西亚的实证研究。
Front Public Health. 2022 Aug 15;10:931557. doi: 10.3389/fpubh.2022.931557. eCollection 2022.
4
Modelling the significance of value-belief-norm framework to predict mass adoption potentials of internet of things-enabled wearable fitness devices.建模价值-信念-规范框架对预测物联网支持的可穿戴健身设备大规模采用潜力的重要性。
Heliyon. 2024 Apr 28;10(9):e30179. doi: 10.1016/j.heliyon.2024.e30179. eCollection 2024 May 15.
5
Predicting the Mass Adoption of eDoctor Apps During COVID-19 in China Using Hybrid SEM-Neural Network Analysis.利用混合 SEM-神经网络分析预测 COVID-19 期间中国电子医生应用程序的大规模采用。
Front Public Health. 2022 Apr 28;10:889410. doi: 10.3389/fpubh.2022.889410. eCollection 2022.
6
Technical attributes, health attribute, consumer attributes and their roles in adoption intention of healthcare wearable technology.技术属性、健康属性、消费者属性及其在可穿戴医疗技术采用意愿中的作用。
Int J Med Inform. 2017 Dec;108:97-109. doi: 10.1016/j.ijmedinf.2017.09.016. Epub 2017 Oct 12.
7
Research on elderly users' intentions to accept wearable devices based on the improved UTAUT model.基于改进的 UTAUT 模型的老年用户接受可穿戴设备意愿的研究。
Front Public Health. 2023 Jan 9;10:1035398. doi: 10.3389/fpubh.2022.1035398. eCollection 2022.
8
Modelling the mass adoption potential of wearable medical devices.可穿戴医疗设备大规模采用潜力的建模。
PLoS One. 2022 Jun 8;17(6):e0269256. doi: 10.1371/journal.pone.0269256. eCollection 2022.
9
Smart technology for healthcare: Exploring the antecedents of adoption intention of healthcare wearable technology.医疗保健领域的智能技术:探索可穿戴医疗技术采纳意愿的影响因素
Health Psychol Res. 2019 Sep 24;7(1):8099. doi: 10.4081/hpr.2019.8099. eCollection 2019 Mar 11.
10
Modeling the adoption of medical wearable devices among the senior adults: Using hybrid SEM-neural network approach.建模老年人对医疗可穿戴设备的采用:使用混合 SEM-神经网络方法。
Front Public Health. 2022 Oct 28;10:1016065. doi: 10.3389/fpubh.2022.1016065. eCollection 2022.

引用本文的文献

1
Identifying factors shaping the behavioural intention of Nepalese youths to adopt digital health tools.识别影响尼泊尔青年采用数字健康工具行为意向的因素。
Healthc Technol Lett. 2025 Feb 7;12(1):e70005. doi: 10.1049/htl2.70005. eCollection 2025 Jan-Dec.
2
Willingness to use smart fetal heart rate monitoring devices among pregnant women: an extension of the technology acceptance model.孕妇使用智能胎儿心率监测设备的意愿:技术接受模型的扩展
Front Psychol. 2024 Jul 12;15:1400720. doi: 10.3389/fpsyg.2024.1400720. eCollection 2024.
3
Why do generation X customers use wearable fitness technology equipment after recovering from coronavirus? The role of perceived health risks.

本文引用的文献

1
Predicting the Mass Adoption of eDoctor Apps During COVID-19 in China Using Hybrid SEM-Neural Network Analysis.利用混合 SEM-神经网络分析预测 COVID-19 期间中国电子医生应用程序的大规模采用。
Front Public Health. 2022 Apr 28;10:889410. doi: 10.3389/fpubh.2022.889410. eCollection 2022.
2
The effect of perceived risks and perceived cost on using online learning by high school students.感知风险和感知成本对高中生使用在线学习的影响。
Procedia Comput Sci. 2022;197:477-483. doi: 10.1016/j.procs.2021.12.164. Epub 2022 Jan 13.
3
Understanding consumer acceptance of healthcare wearable devices: An integrated model of UTAUT and TTF.
为什么X世代客户在从新冠病毒感染中康复后会使用可穿戴健身技术设备?感知健康风险的作用。
Heliyon. 2024 Jun 13;10(12):e32978. doi: 10.1016/j.heliyon.2024.e32978. eCollection 2024 Jun 30.
4
Modelling the significance of value-belief-norm framework to predict mass adoption potentials of internet of things-enabled wearable fitness devices.建模价值-信念-规范框架对预测物联网支持的可穿戴健身设备大规模采用潜力的重要性。
Heliyon. 2024 Apr 28;10(9):e30179. doi: 10.1016/j.heliyon.2024.e30179. eCollection 2024 May 15.
5
Workout with a Smartwatch: A Cross-Sectional Study of the Effects of Smartwatch Attributes on Flow Experience and Exercise Intentions Depending on Exercise Involvement.使用智能手表进行锻炼:一项关于智能手表属性对心流体验和锻炼意图的影响的横断面研究,该影响取决于锻炼参与度。
Healthcare (Basel). 2023 Nov 30;11(23):3074. doi: 10.3390/healthcare11233074.
6
Relationship chains of subhealth physical examination indicators: a cross-sectional study using the PLS-SEM approach.亚健康体检指标的关系链:基于偏最小二乘法结构方程模型的横断面研究。
Sci Rep. 2023 Aug 22;13(1):13640. doi: 10.1038/s41598-023-39934-5.
7
Web-Based Patient Recommender Systems for Preventive Care: Protocol for Empirical Research Propositions.基于网络的预防性医疗患者推荐系统:实证研究命题方案
JMIR Res Protoc. 2023 Mar 30;12:e43316. doi: 10.2196/43316.
8
Predicting the intention and adoption of hydroponic farming among Chinese urbanites.预测中国城市居民对水培农业的意向和采用情况。
Heliyon. 2023 Mar 9;9(3):e14420. doi: 10.1016/j.heliyon.2023.e14420. eCollection 2023 Mar.
9
Research on elderly users' intentions to accept wearable devices based on the improved UTAUT model.基于改进的 UTAUT 模型的老年用户接受可穿戴设备意愿的研究。
Front Public Health. 2023 Jan 9;10:1035398. doi: 10.3389/fpubh.2022.1035398. eCollection 2022.
理解消费者对可穿戴医疗设备的接受度:UTAUT 和 TTF 的综合模型。
Int J Med Inform. 2020 Jul;139:104156. doi: 10.1016/j.ijmedinf.2020.104156. Epub 2020 Apr 24.
4
Using the Technology Acceptance Model to Explore Adolescents' Perspectives on Combining Technologies for Physical Activity Promotion Within an Intervention: Usability Study.利用技术接受模型探索青少年对干预中结合技术促进身体活动的看法:可用性研究
J Med Internet Res. 2020 Mar 6;22(3):e15552. doi: 10.2196/15552.
5
The Association between Health Beliefs and Fall-Related Behaviors and Its Implication for Fall Intervention among Chinese Elderly.健康信念与跌倒相关行为的关系及其对中国老年人跌倒干预的启示。
Int J Environ Res Public Health. 2019 Nov 28;16(23):4774. doi: 10.3390/ijerph16234774.
6
Factors Affecting Caregivers' Acceptance of the Use of Wearable Devices by Patients With Dementia: An Extension of the Unified Theory of Acceptance and Use of Technology Model.影响照顾者接受痴呆症患者使用可穿戴设备的因素:对技术接受模型统一理论的扩展。
Am J Alzheimers Dis Other Demen. 2020 Jan-Dec;35:1533317519883493. doi: 10.1177/1533317519883493. Epub 2019 Nov 3.
7
The malleable morality of conspicuous consumption.炫耀性消费的可塑道德观。
J Pers Soc Psychol. 2020 Mar;118(3):562-583. doi: 10.1037/pspp0000237. Epub 2019 Feb 14.
8
The usefulness and actual use of wearable devices among the elderly population.可穿戴设备在老年人群体中的实用性和实际使用情况。
Comput Methods Programs Biomed. 2018 Jan;153:137-159. doi: 10.1016/j.cmpb.2017.10.008. Epub 2017 Oct 14.
9
Moderating factors influencing adoption of a mobile chronic disease management system in China.影响中国移动慢性病管理系统采用的调节因素。
Inform Health Soc Care. 2018 Jan;43(1):22-41. doi: 10.1080/17538157.2016.1255631. Epub 2017 Jan 9.
10
Analyzing older users' home telehealth services acceptance behavior-applying an Extended UTAUT model.分析老年用户对家庭远程医疗服务的接受行为——应用扩展的UTAUT模型
Int J Med Inform. 2016 Jun;90:22-31. doi: 10.1016/j.ijmedinf.2016.03.002. Epub 2016 Mar 15.