Evidence map›Paper›PMID 41122431›Full record

ArticleDigital health

eHealth literacy and doctor-inpatient relationships: The mediating role of eHealth utilization and the moderating role of age.

Yi Huang, Wen Wen, Shiju Dong, Jiajia Li

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

4 authors.

Yi HuangSchool of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.ORCID https://orcid.org/0009-0006-9757-6605
Wen WenSchool of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.ORCID https://orcid.org/0000-0001-7348-1077
Shiju DongSchool of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.ORCID https://orcid.org/0009-0004-3403-3895
Jiajia LiSchool of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.ORCID https://orcid.org/0000-0001-7458-7682

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Information asymmetry remains a critical challenge in doctor-patient relationships. Although the adoption of eHealth technologies has substantially improved patients' access to medical information, the extent of these benefits largely depends on individuals' levels of eHealth literacy. This study aims to investigate the association between inpatients' eHealth literacy and doctor-patient relationships, while exploring the mediating role of eHealth utilization and the moderating effect of age. Methods: In 2023, a cross-sectional study was conducted among 1307 inpatients, selected through simple random sampling from three tertiary hospitals in Jinan, Shandong Province, China. The Patient-Doctor Relationship Questionnaire-9 (PDRQ-9) was employed to assess the quality of doctor-patient relationships, while the eHealth Literacy Scale was used to evaluate participants' levels of eHealth literacy. Stepwise and bootstrap tests were applied to examine the mediation effect, and hierarchical regression analysis combined with bootstrap testing was used to assess the moderating role of age. Results: eHealth literacy was significantly positively correlated with eHealth utilization (β=0.150, Conclusion: Bridging the digital divide among elderly patients is essential for mitigating information asymmetry and promoting more harmonious doctor-patient relationships.

Indexed as

doctor–patient relationshipeHealth literacyeHealth utilizationmediation analysismoderation effectolder inpatients

Identifiers

PMID41122431
PMCPMC12536205

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.