Do digital technologies improve the health of urban and rural residents? — Empirical evidence from China

Against the backdrop of the digital economy and the 'Healthy China' initiative, clarifying the mechanisms through which digital technologies influence public health can help improve public health governance. Drawing on panel data from 30 Chinese provinces covering the period 2012-2024, this paper employs the Critic-entropy weighting method and a dual machine learning model to address the shortcomings of existing research in causal identification, mechanism decomposition and boundary analysis. The results indicate that digital technologies significantly improve public health; per capita healthcare expenditure plays a partial mediating role; the empowerment effect exhibits a regional gradient, being strongest in the central regions, followed by the western regions, and relatively weaker in the eastern regions; and the number of outpatient visits exerts a positive moderating effect. These findings provide empirical guidance for the differentiated advancement of digital health initiatives in China.

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Publication Details

Journal
Acta Psychologica
Published
2026-08-27
DOI
https://doi.org/10.1016/j.actpsy.2026.107660
Primary Topic
Healthcare Systems and Reforms
Type
article
Field-Weighted Citation Impact
0.00

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article

Do digital technologies improve the health of urban and rural residents? — Empirical evidence from China

Yongshan Chen, Qiao Quan, Feng Xie, Ketao Lin et al.
Acta Psychologica
Healthcare Systems and Reforms
article

Do digital technologies improve the health of urban and rural residents? — Empirical evidence from China

Yongshan Chen, Qiao Quan, Feng Xie, Ketao Lin, Jie Ye
article en

Abstract

Against the backdrop of the digital economy and the 'Healthy China' initiative, clarifying the mechanisms through which digital technologies influence public health can help improve public health governance. Drawing on panel data from 30 Chinese provinces covering the period 2012-2024, this paper employs the Critic-entropy weighting method and a dual machine learning model to address the shortcomings of existing research in causal identification, mechanism decomposition and boundary analysis. The results indicate that digital technologies significantly improve public health; per capita healthcare expenditure plays a partial mediating role; the empowerment effect exhibits a regional gradient, being strongest in the central regions, followed by the western regions, and relatively weaker in the eastern regions; and the number of outpatient visits exerts a positive moderating effect. These findings provide empirical guidance for the differentiated advancement of digital health initiatives in China.

Acta PsychologicaVol. 270
Quanzhou Normal University (CN), Fujian Agriculture and Forestry University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Fujian Province, Fujian Provincial Federation of Social Sciences
Sustainable cities and communities
Openalex Percentile: Top 7%
Healthcare Systems and Reforms
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