Evidence map›Paper›PMID 41584158›Full record

ArticleFrontiers in public health2025

Can internet usage reduce health inequality among rural residents? Evidence from China.

Yanlin Peng, Jingjing Deng

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yanlin PengSchool of Economics, Hunan Agricultural University, Changsha, China.
Jingjing DengCollege of Business, Hunan First Normal University, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The widespread adoption of the internet has made its role in reducing health inequalities within the digital health domain increasingly clear. Using data from six waves of the China Family Panel Studies (CFPS) spanning 2012-2022, this study employs a two-way fixed effects model to systematically examine the impact of internet usage on health inequalities among Chinese farmers. The findings reveal three key insights: (1) the empirical results indicate that internet usage contributes to both improved health outcomes and greater health equity among farmers. Specifically, internet usage not only enhances farmers' overall health status but also reduces health disparities. (2) Mechanism analysis demonstrates that the health-equity effect of internet usage operates through two primary pathways: narrowing health gaps by improving access to healthcare services and reducing health inequalities by increasing the affordability of these services. (3) Heterogeneity analysis reveals significant group-specific variations in the effect of internet usage on health inequality. Notably, the mitigating effect is more pronounced among young adults, those with moderate educational levels, and those with low healthcare expenditures, while its influence is relatively limited in other farmer groups. This study provides robust evidence that internet usage can reduce health inequalities among farmers and offers important insights for developing targeted policies to reduce health disparities.

Indexed as

FarmersHealth Status DisparitiesInternetInternet UseRural PopulationAdultChinaDigital HealthFemaleHealth Services AccessibilityHumansMaleMiddle AgedSocioeconomic Disparities in HealthSocioeconomic FactorsYoung Adultaccessibility of healthcare servicesaffordability of healthcare serviceshealth inequalityinternet usagerural residents

Identifiers

PMID41584158
PMCPMC12827751

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.