Evidence map›Paper›PMID 35463243›Full record

ArticleComputational intelligence and neuroscience2022

Role of Human-Computer Interaction Healthcare System in the Teaching of Physiology and Medicine.

Xiuhong Li, Yubo Xu

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 9% 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, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Xiuhong LiLinfen Vocational and Technical College, Linfen 041000, Shanxi, China.
Yubo XuSchool of Information Science and Technology, Xiamen University Tan Kah Kee College, Zhangzhou 363000, Fujian, China.ORCID https://orcid.org/0000-0002-4036-8665
Taizhou Vocational and Technical College · CNXiamen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the increasingly severe aging of the population, the difficult and expensive medical treatment problems are becoming more and more prominent; the salary level of domestic doctors is not high, but the cost of training doctors is high, coupled with doctors' work pressure and mental pressure; the number of candidates for medical school is decreasing year by year; medical talent is rare; and the allocation of medical staff is scarce. Health care is the basic guarantee for people's good life, and the shortage of medical staff will have many impacts on health care. Human-computer interaction (HCI) is the study of people, computers, and their interaction. HCI refers to the communication between the user and the computer system, which is the two-way information exchange of various symbols and actions between the human and the computer. The purpose of this paper is to study a healthcare system with human-computer interaction through the client, apply the system to the teaching of physiology and medicine, and analyze its effects and functions in combination with various evaluation indicators. This paper selects teaching content, ease of use of human-computer interaction design, technical services, and user subjective satisfaction as evaluation indicators, and constructs an evaluation model for this. And it builds the physiology and medicine teaching system framework and healthcare system, and conducts tests and statistics on the teaching system. This paper combines online questionnaires, in-app survey feedback, and field visits to collect feedback from users and administrators. The final data show that the teaching system meets the requirements in four evaluation indicators: teaching content, ease of use of human-computer interaction design, technical services, and user subjective satisfaction. User satisfaction with these four aspects reached 86.33%, 95.17%, 63.83%, and 81.87%, respectively. It shows that the system is more popular and can meet the needs of most users.

Indexed as

CommunicationComputersDelivery of Health CareFeedbackHumansSurveys and Questionnaires

Identifiers

PMID35463243
PMCPMC9020908
OpenAlexW4223984103

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.