Wearable Technology Acceptance in Health Care Based on National Culture Differences: Cross-Country Analysis Between Chinese and Swiss Consumers
- PMID: 33090108
- PMCID: PMC7644382
- DOI: 10.2196/18801
Wearable Technology Acceptance in Health Care Based on National Culture Differences: Cross-Country Analysis Between Chinese and Swiss Consumers
Abstract
Background: The advancement of wearable devices and growing demand of consumers to monitor their own health have influenced the medical industry. Health care providers, insurers, and global technology companies intend to develop more wearable devices incorporating medical technology and to target consumers worldwide. However, acceptance of these devices varies considerably among consumers of different cultural backgrounds. Consumer willingness to use health care wearables is influenced by multiple factors that are of varying importance in various cultures. However, there is insufficient knowledge of the extent to which social and cultural factors affect wearable technology acceptance in health care.
Objective: The aims of this study were to examine the influential factors on the intention to adopt health care wearables, and the differences in the underlying motives and usage barriers between Chinese and Swiss consumers.
Methods: A new model for acceptance of health care wearables was conceptualized by incorporating predictors of different theories such as technology acceptance, health behavior, and privacy calculus based on an existing framework. To verify the model, a web-based survey in both the Chinese and German languages was conducted in China and Switzerland, resulting in 201 valid Chinese and 110 valid Swiss respondents. A multigroup partial least squares path analysis was applied to the survey data.
Results: Performance expectancy (β=.361, P<.001), social influence (β=.475, P<.001), and hedonic motivation (β=.111, P=.01) all positively affected the behavioral intention of consumers to adopt wearables, whereas effort expectancy, functional congruence, health consciousness, and perceived privacy risk did not demonstrate a significant impact on behavioral intention. The group-specific path coefficients indicated health consciousness (β=.150, P=.01) as a factor positively affecting only the behavior intention of the Chinese respondents, whereas the factors affecting only the behavioral intention of the Swiss respondents proved to be effort expectancy (β=.165, P=.02) and hedonic motivation (β=.212, P=.02). Performance expectancy asserted more of an influence on the behavioral intention of the Swiss (β=.426, P<.001) than the Chinese (β=.271, P<.001) respondents, whereas social influence had a greater influence on the behavioral intention of the Chinese (β=.321, P<.001) than the Swiss (β=.217, P=.004) respondents. Overall, the Chinese consumers displayed considerably higher behavioral intention (P<.001) than the Swiss. These discrepancies are explained by differences in national culture.
Conclusions: This is one of the first studies to investigate consumers' intention to adopt wearables from a cross-cultural perspective. This provides a theoretical and methodological foundation for future research, as well as practical implications for global vendors and insurers developing and promoting health care wearables with appropriate features in different countries. The testimonials and support by physicians, evidence of measurement accuracy, and easy handling of health care wearables would be useful in promoting the acceptance of wearables in Switzerland. The opinions of in-group members, involvement of employers, and multifunctional apps providing credible health care advice and solutions in cooperation with health care institutions would increase acceptance among the Chinese.
Keywords: Chinese; Swiss; cross culture; digital health; health care wearables; health technology acceptance; moderator; national culture; smartwatch; wearables; wearables acceptance.
©Dong Yang Meier, Petra Barthelmess, Wei Sun, Florian Liberatore. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.10.2020.
Conflict of interest statement
Conflicts of Interest: None declared.
Similar articles
-
Investigating older adults users' willingness to adopt wearable devices by integrating the technology acceptance model (UTAUT2) and the Technology Readiness Index theory.Front Public Health. 2024 Sep 25;12:1449594. doi: 10.3389/fpubh.2024.1449594. eCollection 2024. Front Public Health. 2024. PMID: 39421816 Free PMC article.
-
Understanding consumer acceptance of healthcare wearable devices: An integrated model of UTAUT and TTF.Int J Med Inform. 2020 Jul;139:104156. doi: 10.1016/j.ijmedinf.2020.104156. Epub 2020 Apr 24. Int J Med Inform. 2020. PMID: 32387819
-
Patterns of Use and Key Predictors for the Use of Wearable Health Care Devices by US Adults: Insights from a National Survey.J Med Internet Res. 2020 Oct 16;22(10):e22443. doi: 10.2196/22443. J Med Internet Res. 2020. PMID: 33064083 Free PMC article.
-
Mobile Apps and Wearable Devices for Cardiovascular Health: Narrative Review.JMIR Mhealth Uhealth. 2025 Apr 4;13:e65782. doi: 10.2196/65782. JMIR Mhealth Uhealth. 2025. PMID: 40184552 Free PMC article. Review.
-
Wearing the Future-Wearables to Empower Users to Take Greater Responsibility for Their Health and Care: Scoping Review.JMIR Mhealth Uhealth. 2022 Jul 13;10(7):e35684. doi: 10.2196/35684. JMIR Mhealth Uhealth. 2022. PMID: 35830222 Free PMC article.
Cited by
-
Mobile Sensing in the COVID-19 Era: A Review.Health Data Sci. 2022 Aug 8;2022:9830476. doi: 10.34133/2022/9830476. eCollection 2022. Health Data Sci. 2022. PMID: 36408201 Free PMC article. Review.
-
Frameworks for Implementation, Uptake, and Use of Cardiometabolic Disease-Related Digital Health Interventions in Ethnic Minority Populations: Scoping Review.JMIR Cardio. 2022 Aug 11;6(2):e37360. doi: 10.2196/37360. JMIR Cardio. 2022. PMID: 35969455 Free PMC article.
-
Patterns of Ownership and Usage of Wearable Devices in the United States, 2020-2022: Survey Study.J Med Internet Res. 2024 Jul 26;26:e56504. doi: 10.2196/56504. J Med Internet Res. 2024. PMID: 39058548 Free PMC article.
-
Clinical Validation of Respiratory Rate Estimation Using Acoustic Signals from a Wearable Device.J Clin Med. 2024 Nov 27;13(23):7199. doi: 10.3390/jcm13237199. J Clin Med. 2024. PMID: 39685655 Free PMC article.
-
The moderating effect of economic development levels on the adoption of eNutrition technologies in medical education: A multinational survey across six Asian countries.Digit Health. 2025 Jun 25;11:20552076251350805. doi: 10.1177/20552076251350805. eCollection 2025 Jan-Dec. Digit Health. 2025. PMID: 40585052 Free PMC article.
References
-
- Framingham M. IDC Reports Strong Growth in the Worldwide Wearables Market, Led by Holiday Shipments of Smartwatches, Wrist Bands, and Ear-Worn Devices. IDC. 2019. Mar, [2019-04-25]. https://www.idc.com/getdoc.jsp?containerId=prUS44901819.
-
- Tuzovic K, Mathews M. Points for Fitness – How Smart Wearable Technology Transforms Loyalty Programs. In: Bruhn M, Hadwich K, editors. Dienstleistungen 4.0: Geschäftsmodelle—Wertschöpfung—Transformation Band 2. Forum Dienstleistungsmanagement (S. 445–463) Switzerland: Springer; 2017. Jul, pp. 445–463.
-
- Alagöz F, Ziefle M, Wilkowska W, Valdez A. Openness to accept medical technology - a cultural view. Information Quality in e-Health; 7th Conference of the Workshop Human Computer Interaction; November 2011; Graz, Austria. Berlin, Heidelberg: Springer; 2011. pp. 151–170. - DOI
-
- Sun Y, Wang N, Guo X, Peng Z. Understanding the acceptance of mobile health services: a comparison and integration of alternative models. J Electron Commer Res. 2012 Dec;14(2):183–200.
MeSH terms
LinkOut - more resources
Full Text Sources