Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Jul 6:25:e46562.
doi: 10.2196/46562.

Factors Influencing the Sharing of Personal Health Data Based on the Integrated Theory of Privacy Calculus and Theory of Planned Behaviors Framework: Results of a Cross-Sectional Study of Chinese Patients in the Yangtze River Delta

Affiliations

Factors Influencing the Sharing of Personal Health Data Based on the Integrated Theory of Privacy Calculus and Theory of Planned Behaviors Framework: Results of a Cross-Sectional Study of Chinese Patients in the Yangtze River Delta

Jingjin Shi et al. J Med Internet Res. .

Abstract

Background: The health care system in China is fragmented, and the distribution of high-quality resources remains uneven and irrational. Information sharing is essential to the development of an integrated health care system and maximizing its benefits. Nevertheless, data sharing raises concerns regarding the privacy and confidentiality of personal health information, which affect the willingness of patients to share information.

Objective: This study aims to investigate patients' willingness to share personal health data at different levels of maternal and child specialized hospitals in China, to propose and test a conceptual model to identify key influencing factors, and to provide countermeasures and suggestions to improve the level of data sharing.

Methods: A research framework based on the Theory of Privacy Calculus and the Theory of Planned Behavior was developed and empirically tested through a cross-sectional field survey from September 2022 to October 2022 in the Yangtze River Delta region, China. A 33-item measurement instrument was developed. Descriptive statistics, chi-square tests, and logistic regression analyses were conducted to characterize the willingness of sharing personal health data and differences by sociodemographic factors. Structural equation modeling was used to assess the reliability and validity of the measurement as well as to test the research hypotheses. The STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist for cross-sectional studies was applied for reporting results.

Results: The empirical framework had a good fit with the chi-square/degree of freedom (χ2/df)=2.637, root-mean-square residual=0.032, root-mean-square error of approximation=0.048, goodness-of-fit index=0.950, and normed fit index=0.955. A total of 2060 completed questionnaires were received (response rate: 2060/2400, 85.83%). Moral motive (β=.803, P<.001), perceived benefit (β=.123, P=.04), and perceived effectiveness of government regulation (β=.110, P=.001) had a significantly positive association with sharing willingness, while perceived risk (β=-.143, P<.001) had a significant negative impact, with moral motive having the greatest impact. The estimated model explained 90.5% of the variance in sharing willingness.

Conclusions: This study contributes to the literature on personal health data sharing by integrating the Theory of Privacy Calculus and the Theory of Planned Behavior. Most Chinese patients are willing to share their personal health data, which is primarily motivated by moral concerns to improve public health and assist in the diagnosis and treatment of illnesses. Patients with no prior experience with personal information disclosure and those who have tertiary hospital visits were more likely to share their health data. Practical guidelines are provided to health policy makers and health care practitioners to encourage patients to share their personal health information.

Keywords: Theory of Planned Behavior; data sharing; influencing factor; personal health data; privacy calculus.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
The proposed research model.
Figure 2
Figure 2
Results of the structural model.

Similar articles

Cited by

References

    1. Widjaja A, Chen J, Sukoco B, Ha Q. Understanding users' willingness to put their personal information on the personal cloud-based storage applications: An empirical study. Computers in Human Behavior. 2019 Feb;91:167–185. doi: 10.1016/j.chb.2018.09.034. doi: 10.1016/j.chb.2018.09.034. - DOI - DOI
    1. Dinev T, Hart P. An Extended Privacy Calculus Model for E-Commerce Transactions. Information Systems Research. 2006 Mar;17(1):61–80. doi: 10.1287/isre.1060.0080. - DOI
    1. Awad. Krishnan The Personalization Privacy Paradox: An Empirical Evaluation of Information Transparency and the Willingness to Be Profiled Online for Personalization. MIS Quarterly. 2006;30(1):13–28. doi: 10.2307/25148715. - DOI
    1. Ozturk AB, Nusair K, Okumus F, Singh D. Understanding mobile hotel booking loyalty: an integration of privacy calculus theory and trust-risk framework. Inf Syst Front. 2017 Feb 3;19(4):753–767. doi: 10.1007/s10796-017-9736-4. - DOI
    1. Shibchurn Joshana, Yan Xiangbin. Information disclosure on social networking sites: An intrinsic–extrinsic motivation perspective. Computers in Human Behavior. 2015 Mar;44:103–117. doi: 10.1016/j.chb.2014.10.059. doi: 10.1016/j.chb.2014.10.059. - DOI - DOI

Publication types