Honglin Chen

Selected Journal Papers:

1. Bražinová, I., Kalenda Vávrová, S., Chen, H., Li, Y., & Kocvarová, I. (2026). Social robots in Czech residential care services: Comparing the perspectives of social work students and workers in homes for the older people. The British Journal of Social Work. https://doi.org/10.1093/bjsw/bcaf297
   
2. Li, Y., Chen, H. (corresponding), Hämäläinen, J., & An, N. (2026). Improving gerontological social work students’ digital competence: A pilot study of a teaching practice guided by DigComp 2.2. Social Work Education. https://doi.org/10.1080/02615479.2026.2616489
3. Li, Y., Chen, H.L., Hämäläinen, J., & An, N. (2025). Exploring essential digital competencies for gerontological social workers: A case study in China. Educational Gerontology, 1–15. https://doi.org/10.1080/03601277.2025.2535494
4. Chen, H., Zhang, S., & Shardlow, S. M. (2025). Developing “self-efficacy” as an outcome measure in capacity building among social work practice educators in China. The British Journal of Social Work. https://doi.org/10.1093/bjsw/bcaf250
5. Yang, T., Hagedorn, A., Xu, W., Lee, S., Kanda, M., Yun, S., & Chen, H. (corresponding) (2025). Multi-sector collaboration to promote healthy ageing: A comparative case study of national policy responses in the Western Pacific Region. Health Policy, 105501. https://doi.org/10.1016/j.healthpol.2025.105501
6. Chen, H.L., Wong, Y., & To, S.-M. (2025). Editorial: Technological advancement and global ageing in digital society: Opportunities, innovations and new practices. Asia Pacific Journal of Social Work and Development, 33(1), 1–4. https://doi.org/10.1080/02185385.2023.2171234
7. Yuan, Y., Gu, D., Chen, H. (corresponding), & Yang, H. (2025). Delivering an online multi-component non-pharmacological intervention approach for family caregivers of dementia patients: A pilot service-learning program. Asia Pacific Journal of Social Work and Development. Advance online publication. https://doi.org/10.1080/29949769.2025.2576033
8. Chen, H.L., Liu, W., Xu, X., Xiao, M., & Yin, Y. (2024). The Effects of a Nonpharmacological Intervention Practice for Older Adults with Mild Cognitive Impairment and Their Family Caregivers in China. Journal of Gerontological Social Work, 1-20, https://doi.org/10.1080/01634372.2024.2355152
9. Li, Y.J. & Chen, H.L.(2024) Does childhood parental death impact late life health directly and indirectly? Evidence from a National Survey in China, Death Studies, DOI: 1080/07481187.2024.2306471
10. Yang, H., Lv, Z., Zhang, Y., Cui, T., & Chen, H. (2024). Considerations beyond salary: study of job satisfaction among Chinese social work practitioners in different positions. Asia Pacific Journal of Social Work and Development, 1–20.  https://doi.org/10.1080/29949769.2024.2374295
11. H.L. Chen, Y. Chen, Y.Wang, H.T. Chen, S. Levkoff , T.S. Pan, Y.Y. Wang, Y.L. He (2023) A Study on Mental Health Service Needs among Older Adults and the Policy Response in China: Experiences in Urban Shanghai, Ageing International, 10.1007/s12126-022-09516-3
12. H.L. Chen, A. Hagedorn, N. An (2022) The development of smart eldercare in China, The Lancet Regional Health – Western Pacific, https://doi.org/10.1016/j.lanwpc.2022.100547.

AI for Mindful Care and Aging

project in process 20261.1.-2029,12,30

AI is viewed as a promising and inevitable development in home care, with potential to tackle challenges linked to societal aging—such as diverse care needs, workforce shortages, and inefficiencies in welfare systems. However, its implementation raises ethical concerns about how AI may produce or exacerbate vulnerability through exclusion, marginalization, labor exploitation, and emerging risks for older adults and care workers. This project examines how vulnerability is constructed, manifested, and negotiated in the use and implementation of AI-automated home care in Finland, Norway, Sweden, and Lithuania. It focuses on four empirical dimensions: (1) how AI, aging, and care are represented in policy discourse; (2) how innovation leaders frame user needs, opportunities, risks, and worst-case scenarios; (3) how older adults perceive and experience AI in home care; and (4) how care workers respond to AI integration in the workplace. We propose “vulnerability intersections” as a conceptual approach to examine how vulnerability emerges at the intersection of biographical histories, social identities, and shifting structural conditions. The project draws on political economy, life course theory, intersectionality, and the sociology of translation to enable a multi-level understanding of vulnerability as socially and institutionally produced. Empirically, the study examines policy texts, expert interviews with innovation leaders, and life course narratives of older adults and care workers, using qualitative methods. A critical and comparative perspective informs analysis, ensuring sensitivity to cross-country variations in welfare arrangements, digital infrastructures, and sociocultural norms. The project will generate new knowledge on how AI-driven automation shapes care experiences, labor, inequality, and welfare systems, while informing policy and practice by identifying structural disadvantages and highlighting promising and problematic responses to vulnerability. To maximize societal impact, we will implement a targeted communication and dissemination strategy to engage policymakers, practitioners, and the public in support of equitable care systems that strengthen the resilience of older adults and care workers amid AI-driven change. An interdisciplinary team of early-stage, junior, and senior researchers will conduct the research, supported by cross-national training and academic exchange activities.