Evidence map›Paper›PMID 32687480›Full record

ArticleJMIR mHealth and uHealth2020

User Perceptions of Virtual Hospital Apps in China: Systematic Search.

Yuan Wang, Yuqiao Liu, Yancui Shi, Yanjun Yu, Jucheng Yang

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Application and challenges of a metaverse in medicine.Frontiers in robotics and AI · 2023
    Review
  7. Article
  8. 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.

Yuan WangCollege of Artificial Intelligence, Tianjin University of Science and Technology, Tianjin, China.ORCID 0000-0002-5735-8711
Yuqiao LiuCollege of Artificial Intelligence, Tianjin University of Science and Technology, Tianjin, China.ORCID 0000-0001-5168-6688
Yancui ShiCollege of Artificial Intelligence, Tianjin University of Science and Technology, Tianjin, China.ORCID 0000-0002-1048-5932
Yanjun YuCollege of Artificial Intelligence, Tianjin University of Science and Technology, Tianjin, China.ORCID 0000-0002-8398-9816
Jucheng YangCollege of Artificial Intelligence, Tianjin University of Science and Technology, Tianjin, China.ORCID 0000-0002-5046-2663

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVirtual hospital apps are mobile apps that offer functionalities of online consultation, medical guidance, health community forums, referrals, outpatient appointments or virtual hospital-to-home care services. With an increasing number of online medical and health care consulting services, virtual hospital apps have made health care more accessible and fairer for all, especially in China. However, they have occurred without control or regulation. User evaluation can provide directions to help apps optimize identification, lower risks, and guarantee service quality.

objectiveWe aimed to conduct a systematic search for virtual hospital apps in China. To get a global view, virtual hospital apps were assessed and characterized by means of quantitative analysis. To get a local view, we conducted a content feedback analysis to explore user requirements, expectations, and preferences.

methodsA search was conducted of the most popular Apple and Android app stores in China. We characterized and verified virtual hospital apps and grouped apps according to quantification analysis. We then crawled apps and paid attention to corresponding reviews to incorporate users' involvement, and then performed aspect-based content labeling and analysis using an inductive approach.

resultsA total of 239 apps were identified in the virtual hospital app markets in China, and 2686 informative corresponding reviews were analyzed. The evidence showed that usefulness and ease of use were vital facts for engagement. Users were likely to trust a consulting service with a high number of downloads. Furthermore, users expected frequently used apps with more optimization to improve virtual service. We characterized apps according to 4 key features: (1) app functionalities, including online doctor consultation, in-app purchases, tailored education, and community forums; (2) security and privacy, including user data management and user privacy; (3) health management, including health tracking, reminders, and notifications; and (4) technical aspects, including user interface and equipment connection.

conclusionsVirtual hospitals relying on the mobile internet are growing rapidly. A large number of virtual hospital apps are available and accessible to a growing number of people. Evidence from this systematic search can help various types of virtual hospital models enhance virtual health care experiences, go beyond offline hospitals, and continuously meet the needs of individual end users.

Indexed as

Mobile ApplicationsChinaHospitalsHumansPerceptionPrivacyapp review analysisChinamHealthmobile appsremote consultationuser intent

Identifiers

PMID32687480
PMCPMC7450379

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.