Evidence map›Paper›PMID 38470465›Full record

ArticleJournal of medical Internet research2024

Effect of Negative Online Reviews and Physician Responses on Health Consumers' Choice: Experimental Study.

Xi Han, Yongxi Lin, Wenting Han, Ke Liao, Kefu Mei

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2024. 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
4.7field-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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Observational
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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

5 authors at 3 institutions in 1 country.

Xi HanSchool of Business Administration, Guangdong University of Finance & Economics, Guangzhou, China.ORCID 0000-0002-1729-6579
Yongxi LinSchool of Business Administration, Guangdong University of Finance & Economics, Guangzhou, China.ORCID 0009-0008-7354-7871
Wenting Han *School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan, China.ORCID 0000-0002-7690-7990
Ke LiaoSchool of Business Administration, Guangdong University of Finance & Economics, Guangzhou, China.ORCID 0009-0006-1666-9560
Kefu Mei *Department of Internal Neurology, Xiangyang Central Hospital, Xiangyang, China.ORCID 0009-0003-0379-7182
Guangdong University Of Finances and Economics · CNShandong University of Finance and Economics · CNXiangyang Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has highlighted the importance of online medical services. Although some researchers have investigated how numerical ratings affect consumer choice, limited studies have focused on the effect of negative reviews that most concern physicians.

objectiveThis study aimed to investigate how negative review features, including proportion (low/high), claim type (evaluative/factual), and physician response (absence/presence), influence consumers' physician evaluation process under conditions in which a physician's overall rating is high.

methodsUsing a 2×2×2 between-subject decision-controlled experiment, this study examined participants' judgment on physicians with different textual reviews. Collected data were analyzed using the t test and partial least squares-structural equation modeling.

resultsNegative reviews decreased consumers' physician selection intention. The negative review proportion (β=-0.371, P<.001) and claim type (β=-0.343, P<.001) had a greater effect on consumers' physician selection intention compared to the physician response (β=0.194, P<.001). A high negative review proportion, factual negative reviews, and the absence of a physician response significantly reduced consumers' physician selection intention compared to their counterparts. Consumers' locus attributions on the negative reviews affected their evaluation process. Physician attribution mediated the effects of review proportion (β=-0.150, P<.001), review claim type (β=-0.068, P=.01), and physician response (β=0.167, P<.001) on consumer choice. Reviewer attribution also mediated the effects of review proportion (β=-0.071, P<.001), review claim type (β=-0.025, P=.01), and physician response (β=0.096, P<.001) on consumer choice. The moderating effects of the physician response on the relationship between review proportion and physician attribution (β=-0.185, P<.001), review proportion and reviewer attribution (β=-0.110, P<.001), claim type and physician attribution (β=-0.123, P=.003), and claim type and reviewer attribution (β=-0.074, P=.04) were all significant.

conclusionsNegative review features and the physician response significantly influence consumer choice through the causal attribution to physicians and reviewers. Physician attribution has a greater effect on consumers' physician selection intention than reviewer attribution does. The presence of a physician response decreases the influence of negative reviews through direct and moderating effects. We propose some practical implications for physicians, health care providers, and online medical service platforms.

Indexed as

COVID-19PhysiciansData CollectionHealth PersonnelHumansPandemicsattribution theoryclaim typeconsumernegative reviewphysician-rating websitesphysician responseproportion

Identifiers

PMID38470465
PMCPMC10966444
OpenAlexW4391913327

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.