Previously submitted to: Journal of Medical Internet Research (no longer under consideration since Nov 04, 2024)
Date Submitted: Apr 9, 2024
Open Peer Review Period: Apr 12, 2024 - Jun 7, 2024
(closed for review but you can still tweet)
NOTE: This is an unreviewed Preprint
Warning: This is a unreviewed preprint (What is a preprint?). Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn (a note "no longer under consideration" will appear above).
Peer review me: Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period (in this case, a "Peer Review Me" button to sign up as reviewer is displayed above). All preprints currently open for review are listed here. Outside of the formal open peer-review period we encourage you to tweet about the preprint.
Citation: Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author).
Final version: If our system detects a final peer-reviewed "version of record" (VoR) published in any journal, a link to that VoR will appear below. Readers are then encourage to cite the VoR instead of this preprint.
Settings: If you are the author, you can login and change the preprint display settings, but the preprint URL/DOI is supposed to be stable and citable, so it should not be removed once posted.
Submit: To post your own preprint, simply submit to any JMIR journal, and choose the appropriate settings to expose your submitted version as preprint.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Exploring the Digital Health Divide and Determinants among Urban and Rural Elderly in China: Empirical Evidence Based on Capital Theory
ABSTRACT
Background:
The aging population in China is becoming increasingly severe, and there is a health inequality phenomenon among urban and rural elderly. With the development of ICT, eHealth has become one of the important factors affecting health. Urban elderly could more conveniently access health information and medical services, while rural elderly may have difficulty enjoying the digital dividends brought by eHealth, highlighting the phenomenon of the “digital health divide”.
Objective:
This study analyzes the digital health divide and determinants among urban and rural elderly from the perspective of capital theory.
Methods:
The model for analyzing the digital health divide among urban and rural elderly is constructed based on capital theory. Analysis of variance is used to verify the digital health divide among urban and rural elderly. Structural equation modeling is used to analyze the factors, and the Blinder-Oaxaca decomposition method is used to analyze the main causes.
Results:
There are three levels of digital health divide among urban and rural elderly, namely digital access divide (F=11.39, P<.01), digital usage divide (F=39.53, P<.001), and digital outcome divide (F=30.20, P<.001). The influence of different levels of divide is transmitted along the digital chain, the impact coefficient of digital access divide on digital usage divide is β=0.060 (P<.05), and digital usage divide on digital outcome divide is β=0.363 (P<.001). The digital usage divide is the most significant level, and cultural capital (β=0.221, P<.001), social support (β=0.361, P<.001), economic capital (β=0.111, P<.01), and habits (β=0.248, P<.001) are most dominant factors contributing to the rural-urban digital usage divide. The Blinder-Oaxaca decomposition results further indicate that cultural capital (33.9%) and social capital (22.5%) are the main factors influencing digital usage divide among urban and rural elderly.
Conclusions:
here exists digital health divide among urban and rural elderly, and the influence of three level of divide is transmitted along the digital chain. The digital usage divide is the main level, cultural capital and social capital are the main reasons for its formation. To against these divides among urban and rural elderly, interventions in policy, society, technology, and economics are recommended.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.