Evidence map›Paper›PMID 36293874›Full record

ArticleInternational journal of environmental research and public health2022

Internal or External Word-of-Mouth (WOM), Why Do Patients Choose Doctors on Online Medical Services (OMSs) Single Platform in China?

Jiang Shen, Bang An, Man Xu, Dan Gan, Ting Pan

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
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

5 authors.

Jiang ShenCollege of Management and Economy, Tianjin University, Tianjin 300072, China.
Bang AnCollege of Management and Economy, Tianjin University, Tianjin 300072, China.ORCID 0000-0002-2268-6010
Man XuBusiness School, Nankai University, Tianjin 300071, China.
Dan GanSchool of Economics and Management, Hebei University of Technology, Tianjin 300071, China.
Ting PanCollege of Management and Economy, Tianjin University, Tianjin 300072, China.

Funding

the Fundamental Research Funds for Hebei University of Technology JBKYXX2205the Funded by Science and Technology Project of Hebei Education Department ZD2022077the National Natural Science Foundation of China 71971123the Scientific Research Projects of the Liberal Arts Development Fund of Nankai University ZB22BZ0324
6 · The paper itself

Abstract

(1) Background: Word-of-mouth (WOM) can influence patients' choice of doctors in online medical services (OMSs). Previous studies have explored the relationship between internal WOM in online healthcare communities (OHCs) and patients' choice of doctors. There is a lack of research on external WOM and position ranking in OMSs. (2) Methods: We develop an empirical model based on the data of 4435 doctors from a leading online healthcare community in China. We discuss the influence of internal and external WOM on patients' choice of doctors in OMSs, exploring the interaction between internal and external WOM and the moderation of doctor position ranking. (3) Results: Both internal and external WOM had a positive impact on patients' choice of doctors; there was a significant positive interaction between internal and third-party generated WOM, but the interaction between internal and relative-generated WOM, and the interaction between internal and doctor-generated WOM were both nonsignificant. The position ranking of doctors significantly enhanced the impact of internal WOM, whereas it weakened the impact of doctor recommendations on patients' choice of doctors. (4) The results emphasize the importance of the research on external WOM in OMSs, and suggest that the moderation of internal WOM may be related to the credibility and accessibility of external WOM, and the impact of doctor position ranking can be explained by information search costs.

Indexed as

PhysiciansChinaHumansMouthexternal word-of-mouthonline medical serviceoptimal sequential searchposition ranking

Identifiers

PMID36293874
PMCPMC9603608

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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.