Evidence map›Paper›PMID 34068291›Full record

ArticleInternational journal of environmental research and public health2021

The Impact of Signals Transmission on Patients' Choice through E-Consultation Websites: An Econometric Analysis of Secondary Datasets.

Adnan Muhammad Shah, Rizwan Ali Naqvi, Ok-Ran Jeong

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Using Telemedicine during the COVID-19 Pandemic: How Service Quality Affects Patients' Consultation.International journal of environmental research and public health · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. 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

3 authors.

Adnan Muhammad ShahDepartment of Information Technology, University of Sialkot, Sialkot 51310, Pakistan.ORCID 0000-0002-9638-3514
Rizwan Ali NaqviDepartment of Unmanned Vehicle Engineering, Sejong University, Seoul 05006, Korea.ORCID 0000-0002-7473-8441
Ok-Ran JeongSchool of Computing, Gachon University, Seongnam 13120, Korea.

Funding

NRF (National Research Foundation of Korea), funded by the MSIT (Ministry of Science and ICT), Korea NRF2019R1A2C1008412
6 · The paper itself

Abstract

(1) Background: The COVID-19 pandemic has dramatically and rapidly changed the overall picture of healthcare in the way how doctors care for their patients. Due to the significant strain on hospitals and medical facilities, the popularity of web-based medical consultation has drawn the focus of researchers during the deadly coronavirus disease (COVID-19) in the United States. Healthcare organizations are now reacting to COVID-19 by rapidly adopting new tools and innovations such as e-consultation platforms, which refer to the delivery of healthcare services digitally or remotely using digital technology to treat patients. However, patients' utilization of different signal transmission mechanisms to seek medical advice through e-consultation websites has not been discussed during the pandemic. This paper examines the impact of different online signals (online reputation and online effort), offline signals (offline reputation) and disease risk on patients' physician selection choice for e-consultation during the COVID-19 crisis. (2) Methods: Drawing on signaling theory, a theoretical model was developed to explore the antecedents of patients' e-consultation choice toward a specific physician. The model was tested using 3-times panel data sets, covering 4231 physicians on Healthgrades and Vitals websites during the pandemic months of January, March and May 2020. (3) Results: The findings suggested that online reputation, online effort and disease risk were positively related to patients' online physician selection. The disease risk has also affected patients' e-consultation choice. A high-risk disease positively moderates the relationship between online reputation and patients' e-consultation choice, which means market signals (online reputation) are more influential than seller signals (offline reputation and online effort). Hence, market signals strengthened the effect in the case of high-risk disease. (4) Conclusions: The findings of this study provide practical suggestions for physicians, platform developers and policymakers in online environments to improve their service quality during the crisis. This article offers a practical guide on using emerging technology to provide virtual care during the pandemic. This study also provides implications for government officials and doctors on the potentials of consolidating virtual care solutions in the near future in order to contribute to the integration of emerging technology into healthcare.

Indexed as

COVID-19PhysiciansHumansPandemicsReferral and ConsultationSARS-CoV-2COVID-19e-consultationpanel data analysispatients’ choicesignaling theory

Identifiers

PMID34068291
PMCPMC8153351

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.