Evidence map›Paper›PMID 36248622›Full record

ArticleFrontiers in artificial intelligence2022

Knowledge, attitude, and practice of artificial intelligence among doctors and medical students in Syria: A cross-sectional online survey.

Sarya Swed, Hidar Alibrahim, Nashaat Kamal Hamdy Elkalagi, Mohamad Nour Nasif, Mohammed Amir Rais, Abdulqadir J Nashwan, Ahmed Aljabali, Mohamed Elsayed, Bisher Sawaf, Mhd Kutaiba Albuni and 7 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in artificial intelligence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
89citing papers in PubMed, 3 pooled it
8.3field-weighted citation impact, top 2% 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

89 citing papers in PubMed, 3 syntheses or guidelines pooled it, 148 citations in OpenAlex.

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29 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

17 authors at 12 institutions in 8 countries.

Sarya SwedFaculty of Medicine, Aleppo University, Aleppo, Syria.
Hidar AlibrahimFaculty of Medicine, Aleppo University, Aleppo, Syria.
Nashaat Kamal Hamdy ElkalagiInternal and Tropical Medicine, Faculty of Medicine, Arish University, Al Arish, Egypt.
Mohamad Nour NasifFaculty of Medicine, Aleppo University, Aleppo, Syria.
Mohammed Amir RaisFaculty of Medicine of Algiers, University of Algiers, Algiers, Algeria.
Abdulqadir J NashwanNursing Department, Hamad Medical Corporation, Doha, Qatar.
Ahmed AljabaliFaculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan.
Mohamed ElsayedDepartment of Psychiatry and Psychotherapy III, University of Ulm, Ulm, Germany.
Bisher SawafDepartment of Internal Medicine, Hamad Medical Corporation, Doha, Qatar.
Mhd Kutaiba AlbuniDepartment of Internal Medicine, Hamad Medical Corporation, Doha, Qatar.
Elias BattikhDepartment of Internal Medicine, Hamad Medical Corporation, Doha, Qatar.
Leena Abdelwahab Mohamed ElsharifFaculty of Medicine, Red Sea University, Port Sudan, Sudan.
Safaa Mohamed Alsharief AhmedFaculty of Medicine, Shendi University, Shendi, Sudan.
Eman Mohammed Sharif AhmedDepartment of Obstetrics and Gynecology, Nile Valley University, Khartoum, Sudan.
Zain Alabdeen OthmanFaculty of Dentistry, Albaath University, Homs, Syria.
Ahmad AlsalehFaculty of Medicine, Damascus University, Damascus, Syria.
Sheikh ShoibJLNM Hospital, Rainawari, Srinagar, J&K, India.
Hamad Medical Corporation · QAUniversity of Aleppo · SYAl-Baath University · SYArish University · EGCarl von Ossietzky Universität Oldenburg · DEDamascus University · SYJordan University of Science and Technology · JONile Valley University · SDRed Sea University · SDShendi University · SDShri Maharaja Hari Singh Hospital · INUniversity of Algiers 3 · DZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence has been prevalent recently as its use in the medical field is noticed to be increased. However, middle east countries like Syria are deficient in multiple AI implementation methods in the field of medicine. So, holding these AI implementation methods in the medical field is necessary, which may be incredibly beneficial for making diagnosis more accessible and help in the treatment. This paper intends to determine AI's knowledge, attitude, and practice among doctors and medical students in Syria. A questionnaire conducted an online cross-sectional study on the google form website consisting of demographic data, knowledge, and perception of AI. There were 1,494 responses from both doctors and medical students. We included Syrian medical students and doctors who are currently residing in Syria. Of the 1,494 participants, 255 (16.9%) are doctors, while the other 1,252 (83.1%) are undergraduate medical students. About 1,055 (70%) participants have previous knowledge about AI. However, only 357 (23.7%) participants know about its application in the medical field. Most have shown positive attitudes toward its necessity in the medical field; 689 (45.7%) individuals strongly agree, and 628 (41.7%) agree. The undergraduate students had 3.327 times more adequate knowledge of AI than students in the first year. In contrast, the undergraduate 6th-year students had 2.868 times the attitude toward AI higher than students in the first year. The residents and assistant professors had 2.371 and 4.422 times the practice of AI higher than students, respectively. Although most physicians and medical students do not sufficiently understand AI and its significance in the medical field, they have favorable views regarding using AI in the medical field. Syrian medical authorities and international organizations should suggest including artificial intelligence in the medical field, particularly when training residents and fellowship physicians.

Indexed as

artificial intelligenceattitudedoctorknowledgemedical studentpracticeSyria

Identifiers

PMID36248622
PMCPMC9558737
OpenAlexW4298006199

What OpenQuestion holds

Textmetadata
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.