Evidence map›Paper›PMID 32936080›Full record

Observational studyJournal of medical Internet research2020

Exploring Types of Information Sources Used When Choosing Doctors: Observational Study in an Online Health Care Community.

Shuang Zhang, Jying-Nan Wang, Ya-Ling Chiu, Yuan-Teng Hsu

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.5field-weighted citation impact, top 6% of its field
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

5 citing papers in PubMed, 21 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Shuang Zhang *College of International Finance and Trade, Zhejiang Yuexiu University of Foreign Languages, Zhejiang, China.ORCID 0000-0003-4246-2839
Jying-Nan Wang *College of International Finance and Trade, Zhejiang Yuexiu University of Foreign Languages, Zhejiang, China.ORCID 0000-0002-2315-2520
Ya-Ling Chiu *Research Institute for Modern Economics and Management, Zhejiang Yuexiu University of Foreign Languages, Zhejiang, China.ORCID 0000-0001-5466-0993
Yuan-Teng Hsu *Research Center of Finance, Shanghai Business School, Shanghai, China.ORCID 0000-0001-8805-3964
Zhejiang Yuexiu UniversityShanghai Business School · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients attempt to make appropriate decisions based on their own knowledge when choosing a doctor. In this process, the first question usually faced is that of how to obtain useful and relevant information. This study investigated the types of information sources that are used widely by patients in choosing a doctor and identified ways in which the preferred sources differ in various situations.

objectiveThis study aims to address the following questions: (1) What is the proportion in which each of the various information sources is used? (2) How does the information source preferred by patients in choosing a doctor change when there is a difference in the difficulty of medical decision making, in the level of the hospital, or in a rural versus urban situation? (3) How do information sources used by patients differ when they choose doctors with different specialties?

methodsThis study overcomes a major limitation in the use of the survey technique by employing data from the Good Doctor website, which is now China's leading online health care community, data which are objective and can be obtained relatively easily and frequently. Multinomial logistic regression models were applied to examine whether the proportion of use of these information sources changes in different situations. We then used visual analysis to explore the question of which type of information source patients prefer to use when they seek medical assistance from doctors with different specialties.

resultsThe 3 main information sources were online reviews (OR), family and friend recommendations (FR), and doctor recommendations (DR), with proportions of use of 32.93% (559,345/1,698,666), 23.68% (402,322/1,698,666), and 17.48% (296,912/1,698,666), respectively. Difficulty in medical decision making, the hospital level, and rural-urban differences were significantly associated with patients' preferred information sources for choosing doctors. Further, the sources of information that patients prefer to use were found to vary when they looked for doctors with different medical specialties.

conclusionsPatients are less likely to use online reviews when medical decisions are more difficult or when the provider is not a tertiary hospital, the former situation leading to a greater use of online reviews and the latter to a greater use of family and friend recommendations. In addition, patients in large cities are more likely to use information from online reviews than family and friend recommendations. Among different medical specialties, for those in which personal privacy is a concern, online reviews are the most common source. For those related to children, patients are more likely to refer to family and friend recommendations, and for those related to surgery, they value doctor recommendations more highly. Our results can not only contribute to aiding government efforts to further promote the dissemination of health care information but may also help health care industry managers develop better marketing strategies.

Indexed as

Delivery of Health CareFemaleHumansMalePhysiciansTelemedicinedecision makingdoctorhealth informationinformation sourceonline health care communityonline reviews

Identifiers

PMID32936080
PMCPMC7527935
OpenAlexW3047622862

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.