Evidence map›Paper›PMID 32406857›Full record

ArticleJournal of medical Internet research2020

Health Care Employees' Perceptions of the Use of Artificial Intelligence Applications: Survey Study.

Rana Abdullah, Bahjat Fakieh

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 113 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
113citing papers in PubMed, 4 pooled it
6.4field-weighted citation impact, top 4% 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

113 citing papers in PubMed, 4 syntheses or guidelines pooled it, 265 citations in OpenAlex.

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53 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

2 authors at 1 institution in 1 country.

Rana Abdullah *Information Systems Department, King Abdulaziz University, Jeddah, Saudi Arabia.ORCID 0000-0002-6507-2844
Bahjat Fakieh *Information Systems Department, King Abdulaziz University, Jeddah, Saudi Arabia.ORCID 0000-0003-2793-1238
King Abdulaziz University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe advancement of health care information technology and the emergence of artificial intelligence has yielded tools to improve the quality of various health care processes. Few studies have investigated employee perceptions of artificial intelligence implementation in Saudi Arabia and the Arabian world. In addition, limited studies investigated the effect of employee knowledge and job title on the perception of artificial intelligence implementation in the workplace.

objectiveThe aim of this study was to explore health care employee perceptions and attitudes toward the implementation of artificial intelligence technologies in health care institutions in Saudi Arabia.

methodsAn online questionnaire was published, and responses were collected from 250 employees, including doctors, nurses, and technicians at 4 of the largest hospitals in Riyadh, Saudi Arabia.

resultsThe results of this study showed that 3.11 of 4 respondents feared artificial intelligence would replace employees and had a general lack of knowledge regarding artificial intelligence. In addition, most respondents were unaware of the advantages and most common challenges to artificial intelligence applications in the health sector, indicating a need for training. The results also showed that technicians were the most frequently impacted by artificial intelligence applications due to the nature of their jobs, which do not require much direct human interaction.

conclusionsThe Saudi health care sector presents an advantageous market potential that should be attractive to researchers and developers of artificial intelligence solutions.

Indexed as

AdultArtificial IntelligenceCross-Sectional StudiesFemaleHealth PersonnelHumansMaleMiddle AgedSurveys and QuestionnairesWorkplaceYoung Adultartificial intelligenceemployeeshealthcare sectorperceptionSaudi Arabia

Identifiers

PMID32406857
PMCPMC7256754
OpenAlexW3012391191

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.