Evidence map›Paper›PMID 39188810›Full record

ArticleJournal of multidisciplinary healthcare2024

Perceptions of Artificial Intelligence Among Otolaryngologists in Saudi Arabia: A Cross-Sectional Study.

Salma S AlSharhan, Wasan F AlMarzouq, Hamzah K Alshaikh, Hussain J Aljubran, Rizam Alghamdi, Sarah M AlQahtani, Aseel F Almarzouq, Naheel A AlAmer

Abstract read
In one paragraph

Article in Journal of multidisciplinary healthcare, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

8 authors.

Salma S AlSharhanDepartment of Otorhinolaryngology Head & Neck Surgery, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.ORCID 0000-0002-7708-8368
Wasan F AlMarzouqDepartment of Otorhinolaryngology Head & Neck Surgery, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Hamzah K AlshaikhDepartment of Otorhinolaryngology Head & Neck Surgery, King Fahd Military Medical Complex, Dhahran, Saudi Arabia.
Hussain J AljubranCollege of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Rizam AlghamdiDepartment of Otorhinolaryngology Head & Neck Surgery, Dammam Medical Complex, Dammam, Saudi Arabia.
Sarah M AlQahtaniDepartment of Otorhinolaryngology Head & Neck Surgery, Dammam Medical Complex, Dammam, Saudi Arabia.
Aseel F AlmarzouqCollege of Medicine, King Faisal University, Al-Ahsa, Saudi Arabia.
Naheel A AlAmerDepartment of Family and Community Medicine, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.ORCID 0000-0003-2700-5197

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Otolaryngology has experienced notable advancements and growth in the application of artificial intelligence (AI). However, otolaryngologists' perception of these tools are lacking. This study aims to assess the knowledge and attitudes of otolaryngologists toward AI. Patients and Methods: A cross-sectional study was conducted among 110 otolaryngologists in the Eastern Province of Saudi Arabia. A piloted questionnaire was used to gather information on knowledge, attitude, and opinions regarding AI. Data analysis was conducted using SPSS version 26. Results: Of the sample, 60% indicated average perceived knowledge of AI, while approximately 44.5% perceived their AI knowledge in the field of otolaryngology to be below average. A significant positive correlation was identified between knowledge and attitude scores. It was found that a higher knowledge score was more closely associated with seeing more than 15 patients per day, while a higher attitude score was more closely associated with being older, being a consultant, and having more years of professional experience. Of the sample, 38.2% strongly agreed that the application of AI in scientific research should be included in the residency training program. Conclusion: These findings underscore the importance of incorporating AI tools into certain aspects of the otolaryngology residency training program, highlighting their significance.

Indexed as

artificial intelligenceattitudeknowledgemachine learningotolaryngology

Identifiers

PMID39188810
PMCPMC11346474

What OpenQuestion holds

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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.