Evidence map›Paper›PMID 37089478›Full record

ArticleFrontiers in public health2023

How the use of an online healthcare community affects the doctor-patient relationship: An empirical study in China.

Zhanyou Wang, Xin Zhang, Dongmei Han, Yaopei Zhao, Liang Ma, Feifei Hao

Abstract read
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

6 authors.

Zhanyou WangManagement Science and Engineering, Shandong University of Finance and Economics, Jinan, China.
Xin ZhangManagement Science and Engineering, Shandong University of Finance and Economics, Jinan, China.
Dongmei HanSchool of Information Engineering, Shandong Management University, Jinan, China.
Yaopei ZhaoShandong Labor Vocational and Technical College, Jinan, China.
Liang MaManagement Science and Engineering, Shandong University of Finance and Economics, Jinan, China.
Feifei HaoCollege of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Possible improvements to the doctor-patient relationship are an important subject confronting national healthcare policy and health institutions. In recent years, online healthcare communities have changed the ways in which doctors and patients communicate, especially during the COVID-19 pandemic. However, previous research on how usage of online healthcare communities has affected the doctor-patient relationship is rather limited. This paper proposes a research model to investigate the relationship between online healthcare community usage and the doctor-patient relationship. An analysis of 313 patients' data using structural equation modeling showed the following. First, the use of an online healthcare community has a positive impact on doctor-patient communication, helps improve the performance of healthcare procedures, and reduces healthcare costs. Second, doctor-patient communication and healthcare costs have a positive impact on patients' emotional dependence and patients' perception of healthcare quality, while healthcare procedures do not have this impact. Finally, patients' emotional dependence and perception of healthcare quality have a positive effect on doctor-patient relationship through the mediator of patients' satisfaction.

Indexed as

COVID-19PhysiciansChinaHumansPandemicsPhysician-Patient Relationsdoctor–patient relationshiphealthcare costsonline healthcare communitypatients communicatepatients’ satisfaction

Identifiers

PMID37089478
PMCPMC10117639

What OpenQuestion holds

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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.