Evidence map›Paper›PMID 32250962›Full record

ArticleJournal of medical Internet research2020

Internet Hospitals Help Prevent and Control the Epidemic of COVID-19 in China: Multicenter User Profiling Study.

Kai Gong, Zhong Xu, Zhefeng Cai, Yuxiu Chen, Zhanxiang Wang

Open access · goldAbstract read
In one paragraph

Article 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 93 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
93citing papers in PubMed, 2 pooled it
12.9field-weighted citation impact, top 1% 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

93 citing papers in PubMed, 2 syntheses or guidelines pooled it, 183 citations in OpenAlex.

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33 more citing papers are in PubMed but not listed here.

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 1 institution in 1 country.

Kai GongThe Internet Hospital of the First Affiliated Hospital of Xia'men University, Xia'men City, China.ORCID 0000-0001-8543-0090
Zhong XuThe Internet Hospital of the First Affiliated Hospital of Xia'men University, Xia'men City, China.ORCID 0000-0003-4296-7255
Zhefeng CaiZoenet Health Company Limited, Xia'men City, China.ORCID 0000-0002-1326-422X
Yuxiu ChenZoenet Health Company Limited, Xia'men City, China.ORCID 0000-0003-4280-6275
Zhanxiang WangThe Internet Hospital of the First Affiliated Hospital of Xia'men University, Xia'men City, China.ORCID 0000-0001-7318-1859
First Affiliated Hospital of Xiamen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDuring the spread of the novel coronavirus disease (COVID-19), internet hospitals in China were engaged with epidemic prevention and control, offering epidemic-related online services and medical support to the public.

objectiveThe aim of this study is to explore the role of internet hospitals during the prevention and control of the COVID-19 outbreak in China.

methodsOnline epidemic-related consultations from multicenter internet hospitals in China during the COVID-19 epidemic were collected. The counselees were described and classified into seven type groups. Symptoms were recorded and compared with reported patients with COVID-19. Hypochondriacal suspicion and offline visit motivation were detected within each counselees' group to evaluate the social panic of the epidemic along with the consequent medical-seeking behaviors. The counselees' motivation and the doctors' recommendation for an offline visit were compared. Risk factors affecting the counselees' tendency of hypochondriacal suspicion and offline visit motivation were explored by logistic regression models. The epidemic prevention and control measures based on internet hospitals were listed, and the corresponding effects were discussed.

resultsA total of 4913 consultations were enrolled for analysis with the median age of the counselees at 28 years (IQR 22-33 years). There were 104 (2.12%) healthy counselees, 147 (2.99%) hypochondriacal counselees, 34 (0.69%) exposed counselees, 853 (17.36%) mildly suspicious counselees, 42 (0.85%) moderately suspicious counselees, 3550 (72.26%) highly suspicious counselees, and 183 (3.72%) severely suspicious counselees. A total of 94.20% (n=4628) of counselees had epidemic-related symptoms with a distribution similar to those of COVID-19. The hypochondriacal suspicion (n=2167, 44.11%) was common. The counselees' motivation and the doctors' recommendation for offline visits were inconsistent (P<.001) with a Cohen kappa score of 0.039, indicating improper medical-seeking behaviors. Adult counselees (odds ratio [OR]=1.816, P<.001) with epidemiological exposure (OR 7.568, P<.001), shortness of breath (OR 1.440, P=.001), diarrhea (OR 1.272, P=.04), and unrelated symptoms (OR 1.509, P<.001) were more likely to have hypochondriacal suspicion. Counselees with severe illnesses (OR 2.303, P<.001), fever (OR 1.660, P<.001), epidemiological exposure history (OR 1.440, P=.01), and hypochondriacal suspicion (OR 4.826, P<.001) were more likely to attempt an offline visit. Reattending counselees (OR 0.545, P=.002) were less motivated to go to the offline clinic.

conclusionsInternet hospitals can serve different types of epidemic counselees, offer essential medical supports to the public during the COVID-19 outbreak, reduce the social panic, promote social distancing, enhance the public's ability of self-protection, correct improper medical-seeking behaviors, reduce the chance of nosocomial cross-infection, and facilitate epidemiological screening, thus, playing an important role on preventing and controlling COVID-19.

Indexed as

Coronavirus InfectionsHospitalsInternetPandemicsPneumonia, ViralReferral and ConsultationAdultBetacoronavirusChinaCoronavirusCounselingCOVID-19Disease OutbreaksEpidemicsFemaleHealth StatuscontrolcoronavirusCOVID-19infectious diseaseinternet hospitalnovel coronavirus diseasepandemicpreventionpublic healthtelemedicine

Identifiers

PMID32250962
PMCPMC7159055
OpenAlexW3014694051

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.