Study on the formation mechanism of the digital health information divide and capital-driven pathways among the older adults
5 affiliations
- 1Nanjing Medical University Library
- 2School of Pharmacy, Nanjing Medical University
- 3Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University
- 4Institute of Science and Technology, Nanjing Medical University
- 5The Affiliated Taizhou People’s Hospital of Nanjing Medical University
Abstract
Background: Artificial intelligence and digital health services have expanded access to health information, yet older adults remain vulnerable to a digital health information divide due to unequal digital literacy, resource access, social support, and psychological readiness. However, the multi-capital mechanisms underlying this divide remain insufficiently explained.
Objective: Grounded in structural poverty theory and Wilson’s information behavior model, this study examines how economic, cultural, social, political, and psychological capital shape older adults’ health information behavior and contribute to the digital health information divide.
Methods: Questionnaire data were collected on older adults’ demographic characteristics, five forms of structural capital, and 13 information behavior variables. A Bayesian network model was used to identify inter-capital relationships, behavioral pathways, and key nodes within the information behavior chain.
Results: Different forms of capital affected health information behavior through direct, indirect, and cross-capital pathways. Cultural capital occupied a central position, improving self-efficacy and information source evaluation while promoting active and continuous information seeking through the accumulation of social and political capital. Psychological capital occupied an intermediate position across multiple network connections involving capital and information behavior variables. Social and political capital provided interpersonal support and institutional safeguards, whereas economic capital mainly influenced access and channel diversification indirectly. Accordingly, governance should combine capital empowerment, pathway-based precision intervention, and institutionalized long-term support.
Conclusion: This study constructs a network-based framework linking multi-capital, behavioral pathways, and divide risk, offering theoretical and practical guidance for improving older adults’ digital health literacy and reducing the health information divide.
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BibTeX
@article{yang2026study,
title = {{Study on the formation mechanism of the digital health information divide and capital-driven pathways among the older adults}},
author = {Xiaowen Yang and Biao Wang and Mai Xu and Haibo Chen and Li Huang and Haoxiang Wang and Wanchao Chen and Qinhui Fan and Xiaoning Yu and Shenzhong Zhang and Sipeng Shen and Huiling Pan},
journal = {Frontiers in Public Health},
year = {2026},
month = oct,
doi = {10.3389/fpubh.2026.1913689},
url = {https://www.frontiersin.org/articles/10.3389/fpubh.2026.1913689/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Study on the formation mechanism of the digital health information divide and capital-driven pathways among the older adults
AU - Xiaowen Yang
AU - Biao Wang
AU - Mai Xu
AU - Haibo Chen
AU - Li Huang
AU - Haoxiang Wang
AU - Wanchao Chen
AU - Qinhui Fan
AU - Xiaoning Yu
AU - Shenzhong Zhang
AU - Sipeng Shen
AU - Huiling Pan
PY - 2026
DA - 2026/10/29
JO - Frontiers in Public Health
DO - 10.3389/fpubh.2026.1913689
UR - https://www.frontiersin.org/articles/10.3389/fpubh.2026.1913689/full
AB - Background: Artificial intelligence and digital health services have expanded access to health information, yet older adults remain vulnerable to a digital health information divide due to unequal digital literacy, resource access, social support, and psychological readiness. However, the multi-capital mechanisms underlying this divide remain insufficiently explained. Objective: Grounded in structural poverty theory and Wilson’s information behavior model, this study examines how economic, cultural, social, political, and psychological capital shape older adults’ health information behavior and contribute to the digital health information divide. Methods: Questionnaire data were collected on older adults’ demographic characteristics, five forms of structural capital, and 13 information behavior variables. A Bayesian network model was used to identify inter-capital relationships, behavioral pathways, and key nodes within the information behavior chain. Results: Different forms of capital affected health information behavior through direct, indirect, and cross-capital pathways. Cultural capital occupied a central position, improving self-efficacy and information source evaluation while promoting active and continuous information seeking through the accumulation of social and political capital. Psychological capital occupied an intermediate position across multiple network connections involving capital and information behavior variables. Social and political capital provided interpersonal support and institutional safeguards, whereas economic capital mainly influenced access and channel diversification indirectly. Accordingly, governance should combine capital empowerment, pathway-based precision intervention, and institutionalized long-term support. Conclusion: This study constructs a network-based framework linking multi-capital, behavioral pathways, and divide risk, offering theoretical and practical guidance for improving older adults’ digital health literacy and reducing the health information divide.
SN - 2296-2565
ER -