Evidence map›Paper›PMID 40919284›Full record

ReviewSAGE open nursing

Knowledge, Attitudes, Practices, and Barriers Regarding the Integration of Artificial Intelligence in Nursing and Health Sciences Education: A Systematic Review.

Nesreen Alqaissi, Mohammed Qtait

Abstract readReview
In one paragraph

Review in SAGE open nursing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Observational
  5. Review
  6. Attitudes and Knowledge Levels of Optometry Students and Educators Towards Artificial Intelligence in Optometric Practice: An Online Cross-Sectional Survey.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
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.

Nesreen AlqaissiNursing College, Palestine Polytechnic University, Hebron, Palestine.ORCID https://orcid.org/0009-0005-5642-8772
Mohammed QtaitNursing College, Palestine Polytechnic University, Hebron, Palestine.ORCID https://orcid.org/0000-0003-2414-7982

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Artificial intelligence (AI) is rapidly transforming healthcare education and practice, making it essential for nursing and health sciences students to develop relevant competencies. However, their preparedness to engage meaningfully with AI in academic and clinical environments remains uncertain. Objectives: This systematic review synthesizes global evidence on the knowledge, attitudes, practices, and barriers (KAPB) related to AI among students in nursing, medicine, pharmacy, and allied health disciplines. Methods: Following PRISMA 2020 guidelines, a systematic search was conducted in PubMed, Scopus, CINAHL, and Google Scholar for peer-reviewed articles published between January 2020 and February 2025. Fourteen studies meeting inclusion criteria were analyzed using narrative synthesis. Both quantitative and qualitative studies were included. The review protocol was not registered. Results: Students generally demonstrated high awareness of AI, but formal training was limited. Knowledge was often acquired informally through social media or peer networks. While attitudes toward AI were largely positive, students expressed ethical concerns and anxiety related to AI use. Practical engagement with AI was mostly restricted to academic writing tasks, with minimal clinical application. Major barriers included the absence of AI-focused curricula, limited faculty expertise, inadequate infrastructure, and concerns over data privacy, ethics, and job displacement. Conclusion: Despite growing interest in AI, significant gaps remain in health sciences education. Comprehensive strategies such as curriculum integration, faculty development, and ethical training are urgently needed to foster responsible, confident, and clinically relevant AI adoption among future healthcare professionals.

Indexed as

AI literacyArtificial intelligenceattitudesbarrierscurriculum integrationhealth sciences studentsknowledgenursing educationpracticessystematic review

Identifiers

PMID40919284
PMCPMC12409032

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.