Evidence map›Paper›PMID 39425151›Full record

ArticleBMC medical education2024

Shaping the future: perspectives on the Integration of Artificial Intelligence in health profession education: a multi-country survey.

Wegdan Bani Issa, Ali Shorbagi, Alham Al-Sharman, Mohammad Rababa, Khalid Al-Majeed, Hadia Radwan, Fatma Refaat Ahmed, Nabeel Al-Yateem, Richard Mottershead, Dana N Abdelrahim and 5 more

Abstract read
In one paragraph

Article in BMC medical education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

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  17. Digital Health Education for Chronic Lung Disease: Scoping Review.Journal of medical Internet research · 2025
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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

15 authors.

Wegdan Bani Issa *Department of Nursing, College of Health Sciences, University of Sharjah, Sharjah, UAE. wbaniissa@sharjah.ac.ae.
Ali Shorbagi *College of Medicine, Clinical Sciences Department , University of Sharjah, Sharjah, UAE.
Alham Al-Sharman *Department of Physiotherapy, College of Health Sciences, University of Sharjah, Sharjah, UAE.
Mohammad Rababa *Adult Health Nursing Department, Faculty of Nursing/WHO Collaborating Center, Jordan University of Science and Technology, Irbid, Jordan.
Khalid Al-Majeed *Critical Health Nursing, College of Nursing, Riyadh Elm University, Riyadh, Saudi Arabia.
Hadia Radwan *Department of Clinical Nutrition and Dietetics, College of Health Sciences, University of Sharjah, Sharjah, UAE.
Fatma Refaat Ahmed *Department of Nursing, College of Health Sciences, University of Sharjah, Sharjah, UAE.
Nabeel Al-Yateem *Department of Nursing, College of Health Sciences, University of Sharjah, Sharjah, UAE.
Richard Mottershead *Department of Nursing, College of Health Sciences, University of Sharjah, Sharjah, UAE.
Dana N Abdelrahim *Research Institute for Medical and Health Sciences, University of Sharjah, Sharjah, UAE.
Heba Hijazi *Department of Health Care Management, College of Health Sciences, University of Sharjah, Sharjah, UAE.
Wafa Khasawneh *California State University, Dominguez Hills, San Diego, CA, USA.
Ibrahim Ali *Department of Entrepreneurship, Innovation and Marketing, United Arab Emirates University, Al Ain, UAE.
Nada Abbas *Department of Clinical Nutrition and Dietetics, College of Health Sciences, University of Sharjah, Sharjah, UAE.
Randa Fakhry *Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) is transforming health profession education (HPE) through personalized learning technologies. HPE students must also learn about AI to understand its impact on healthcare delivery. We examined HPE students' AI-related knowledge and attitudes, and perceived challenges in integrating AI in HPE.

methodsThis cross-sectional included medical, nursing, physiotherapy, and clinical nutrition students from four public universities in Jordan, the Kingdom of Saudi Arabia (KSA), the United Arab Emirates (UAE), and Egypt. Data were collected between February and October 2023 via an online survey that covered five main domains: benefits of AI in healthcare, negative impact on patient trust, negative impact on the future of healthcare professionals, inclusion of AI in HPE curricula, and challenges hindering integration of AI in HPE.

resultsOf 642 participants, 66.4% reported low AI knowledge levels. The UAE had the largest proportion of students with low knowledge (72.7%). The majority (54.4%) of participants had learned about AI outside their curriculum, mainly through social media (66%). Overall, 51.2% expressed positive attitudes toward AI, with Egypt showing the largest proportion of positive attitudes (59.1%). Although most participants viewed AI in healthcare positively (91%), significant variations were observed in other domains. The majority (77.6%) supported integrating AI in HPE, especially in Egypt (82.3%). A perceived negative impact of AI on patient trust was expressed by 43.5% of participants, particularly in Egypt (54.7%). Only 18.1% of participants were concerned about the impact of AI on future healthcare professionals, with the largest proportion from Egypt (33.0%). Some participants (34.4%) perceived AI integration as challenging, notably in the UAE (47.6%). Common barriers included lack of expert training (53%), awareness (50%), and interest in AI (41%).

conclusionThis study clarified key considerations when integrating AI in HPE. Enhancing students' awareness and fostering innovation in an AI-driven medical landscape are crucial for effectively incorporating AI in HPE curricula.

Indexed as

Artificial IntelligenceCurriculumAdultAttitude of Health PersonnelCross-Sectional StudiesEgyptFemaleHealth Knowledge, Attitudes, PracticeHealth OccupationsHumansJordanMaleSaudi ArabiaStudents, Health OccupationsSurveys and QuestionnairesUnited Arab EmiratesArtificial IntelligenceDeep learningHealth sciences educationMachine learningMedical educationUndergraduate education

Identifiers

PMID39425151
PMCPMC11488068

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.