Ethical Framework for Health Data Privacy Protection in Smart Elderly Care: A Grounded Theory Approach
DOI:
https://doi.org/10.54097/6k0hbw69Keywords:
Smart Elderly Care, Data Governance, Privacy Protection, Ethical Framework, Grounded TheoryAbstract
As the trend of population aging is accelerating, health data privacy protection in smart elderly care has gained more significance to resolve ethical issues and contribute to the sustainable development of digital elderly care. This paper will review the literature, policies, regulations and technical standards and use grounded theory using open, axial and selective coding to determine major ethical aspects and develop a theoretical framework. The results indicate that the framework can be divided into four dimensions: compliance governance and risk control, individual rights and dignity protection, structural fairness and procedural justice, and collaborative governance with trusted innovation. The institutional base is compliance governance, the fundamental value is rights protection, balanced governance is facilitated by structural fairness, and continuous improvement is facilitated by collaborative innovation. Combined, these dimensions constitute an ethical system of governance that incorporates institutional regulation, rights protection, equitable governance, and technological innovation. This paper offers a theoretical approach to privacy protection of health data in smart elderly care. Nevertheless, additional empirical studies should be conducted to evaluate the applicability of the framework in various practical contexts.
Downloads
References
[1] Yao, L. Y. (2025). Identification, system architecture, and scenario-based applications of data resources for smart elderly care. Information and Documentation Services, 46(1), 21.
[2] Zuo, M. Y., & Zhang, C. M. (2023). Smart elderly care in the digital intelligence era: Concepts, development, and prospects—An interview with professor Meiyun Zuo, a pioneer of smart elderly care.Journal of Intelligent Society Studies, 2(2), 203–216.
[3] Liu, S. Q., Luo, Y., & Fu, J. J. (2021). Current status of digital health literacy among older adults and corresponding strategies under the background of active aging. Chinese Nursing Research, 35(2), 250–254.
[4] Xu, Z. H. (2025). Risks and regulation of brain–computer interface technology empowering smart elderly care. Journal of Hohai University (Philosophy and Social Sciences), 27(4), 148–164.
[5] Cun, H. B., Yang, Z. W., & Deng, Y. J. (2025). Ethical risks of artificial intelligence-based elderly care services from the perspective of responsibility ethics and their mitigation strategies. Journal of Hohai University (Philosophy and Social Sciences), 27(3), 100–108.
[6] He, M., Hou, R. Y., & Yin, M. (2024). Reflections on the ethical dilemmas of artificial intelligence in elderly care. Medicine and Philosophy, 45(6), 27–30, 41.
[7] Li, J., & Li, Z. (2019). Dilemmas and governance of information ethics in the intelligent era. Information Science, 37(12), 118–122, 133.
[8] Zhu, B., & Wang, C. Q. (2020). Privacy governance in scientific data sharing in China. Library and Information Service, 64(22), 37–47.
[9] Bugeja, J., Jacobsson, A., & Davidsson, P. (2022). The ethical smart home: Perspectives and guidelines. IEEE Security & Privacy, 20(1), 72–80.
[10] Wang, X., Wang, J. X., & Gong, B. L. (2024). Text analysis and optimization of privacy policies in health apps for health information governance. Information Science, 42(8), 174–183.
[11] Yao, L. Y., & Zhang, Y. X. (2025). Construction and implementation path of a data sharing model for smart elderly care institutions from the perspective of information ecosystems. Information Studies: Theory & Application, 48(3), 1–9.
[12] Ellis, C. (1992). Basics of qualitative research: Grounded theory procedures and techniques. Contemporary Sociology: A Journal of Reviews, 21(1), 138–139.
[13] The State Council of the People’s Republic of China. (2021, August 20). Personal information protection law of the People's Republic of China. Retrieved March 26, 2025, from https://www.gov.cn/xinwen/2021-08/20/content_5632486.htm.
[14] Zhu, Y., & Li, X. T. (2021). An analytical framework for personal data privacy protection in the era of big data. Journal of Intelligence, 40(1), 165–170.
[15] European Union. (2016, May 4). General data protection regulation (GDPR): Legal text. Retrieved March 26, 2025, from https://gdpr-info.eu/.
[16] Xinhua News Chongqing Channel. (2024, August 21). Fake volunteer service, real information trap: Why were the personal data of 317 rural older adults stolen? Retrieved May 12, 2025, from http://cq.news.cn/ 20240821/ c191d7b437 b348ff8d2 b2747f031d84b/c.html.
[17] Asia-Pacific Economic Cooperation. (2015). APEC privacy framework. Retrieved May 12, 2025, from https://www. apec. org/publications/2017/08/apec-privacy-framework-.
[18] National Institute of Standards and Technology. (n.d.). Privacy framework. Retrieved May 12, 2025, from https://www. nist. gov/privacy-framework/privacy-framework.
[19] Zhang, L. M., & Zhong, X. K. (2024). Research on data privacy protection technologies in medical information systems. China Informatization, (12), 97–98.
[20] National People’s Congress of China. (2021, June 10). Data security law of the People's Republic of China. Retrieved May 12, 2025, from http://www.npc. gov.cn/c2/ c30834/ 202106/ t20210610_311888.html.
[21] Peng, H., Gu, J., & Ye, X. (2009). Towards compliance and accountability: A framework for privacy online. Journal of Computers, 4(6), 494–501.
[22] Smith, M., Torres-Aguero, A., Grossman, R., et al. (2024). A study of GDPR compliance under the transparency and consent framework. In Proceedings of the ACM Web Conference 2024 (pp. 1227–1236).
[23] China National Committee on Ageing. (2024, March 21). Typical cases of protecting the rights and interests of older adults in China in 2023. Retrieved May 12, 2025, from https://www.chinanews.com.cn/gn/2024/03-21/ 10184 406. Shtml.
[24] Zhang, M. G., & Zhang, Q. M. (2025). Personal information protection mechanisms for public space data in the era of artificial intelligence. Information Science. Retrieved August 29, 2025, from 1–20.
[25] Bookert, N., Almousa, M., & Anwar, M. (2022). Inclusive privacy design for older adults living in ambient assisted living. arXiv, abs/2207.09592.
[26] Lorenzen-Huber, L., Boutain, M., & Camp, L. J. (2011). Privacy, technology, and aging: A proposed framework. Ageing International, 36(2), 232–252.
[27] Gjermundrod, H., Dionysiou, I., & Costa, K. (2016). PrivacyTracker: A privacy-by-design GDPR-compliant framework with verifiable data traceability controls. In Proceedings of the 2016 International Conference (pp. 3–15). Lugano, Switzerland.
[28] Barth, A., Datta, A., Mitchell, J., et al. (2006). Privacy and contextual integrity: Framework and applications. In Proceedings of the 2006 ACM Conference (p. 184). Berkeley, CA, USA.
[29] Baloukas, C., Papadopoulos, L., & Demestichas, K. (2024). A risk assessment and legal compliance framework for supporting personal data sharing with privacy preservation for scientific research. In Proceedings of the 2024 International Conference. Vienna, Austria.
[30] State Administration for Market Regulation of China. (n.d.). Information security technology—Personal information security specification. Retrieved May 13, 2025, from https:// openstd.samr.gov.cn/bzgk/gb/newGbInfo?hcno=4568F276E0F8346EB0FBA097AA0CE05E.
[31] Mahindrakar, A., & Joshi, K. (2020). Automating GDPR compliance using policy integrated blockchain. In Proceedings of the 2020 International Conference (pp. 86–93). Baltimore, MD, USA.
[32] Mordini, E., Wright, D., & Wadhwa, K. (2009). Senior citizens and the ethics of e-inclusion. Ethics and Information Technology, 11(3), 203–220.
[33] Zhao, S. J. (2024). Privacy protection and benefit enhancement in authorized public data operation: Based on the institutional analysis and development (IAD) framework. Cyber Security and Data Governance, 43(10), 68–74.
[34] Lorenzen-Huber, L., Boutain, M., & Camp, L. J. (2011). Privacy, technology, and aging: A proposed framework. Ageing International, 36(2), 232–252.
[35] Thapa, C., & Camtepe, S. (2021). Precision health data: Requirements, challenges and existing techniques for data security and privacy. Computers in Biology and Medicine, 129, 104130.
[36] Zhang, L., Zhang, J. C., & Xu, H. K. (2025). Artificial intelligence ethics: System construction and governance quality. Macro Quality Research, 13(1), 40–56.
[37] Dong, X. Y., & Duan, Y. B. (2024). Mechanisms and optimization paths for privacy protection from the perspective of digital governance. Information Technology and Management Applications, 3(2), 9–19.
[38] Li, Y., & Yang, R. (2023). Privacy protection dilemmas and management framework for government open data in China. Journal of Intelligence, 42(1), 152–157.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Academic Journal of Management and Social Sciences
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
