Evidence map›Paper›PMID 41234270›Full record

ArticleJournal of family & community medicine

Medical students' beliefs, behaviors, and ease with artificial intelligence in education: A study in Eastern Province, Saudi Arabia.

Khalid S Alharkan, Ahmed M Almukahhil, Hassan R Alfardan, Mohamed A Albaqshi, Maytham A Aldajani, Yousef D Alqurashi, Tajammal Mustafa, Saleh A Alqahtani, Kholoud S Al Ghamdi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of family & community medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

9 authors.

Khalid S AlharkanDepartment of Family and Community Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Ahmed M AlmukahhilDepartment of College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Hassan R AlfardanDepartment of College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Mohamed A AlbaqshiDepartment of College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Maytham A AldajaniDepartment of College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Yousef D AlqurashiDepartment of Respiratory Care, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Tajammal MustafaDepartment of Family and Community Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Saleh A AlqahtaniDepartment of Pediatrics, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Kholoud S Al GhamdiDepartment of Physiology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) is increasingly being utilized in education to enhance learning experiences through proactive and reactive engagements. This study's aim was to measure medical students' perceptions and self-efficacy regarding the use of AI in their educational journeys. MATERIALS AND

methodsA cross-sectional study was conducted on undergraduate students in a College of Medicine in the Eastern Province of Saudi Arabia. Data was collected by sharing an online survey link on QuestionPro through an instant messaging app. The survey consisted of general questions (such as age and gender), and the AI Self-Efficacy Scale (AISE) that assesses four distinct domains. Data were categorized and analyzed using SPSS version 29. An independent sample

resultsA total of 525 out of 1198 undergraduate medical students participated in this study. More than half of the participants (61%) reported familiarity with AI, and 66% of them had used ChatGPT. About 45-60% participants responded "Agree" or "Strongly agree" that they can happily, smoothly, and easily interact with AI. Pre-clinical students had significantly higher mean score for anthropomorphic domain than clinical medical students (

conclusionAI tools could significantly enhance efficiency and serve as effective learning aids. Medical students found easy to interact with AI. If utilized properly, AI may improve education and make learning more engaging.

Indexed as

Artificial intelligenceartificial intelligence self-efficacy scalemedical educationmedical studentsSaudi Arabia

Identifiers

PMID41234270
PMCPMC12611057

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.