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TRUVACE RECORD VERSION
record: TRV-2026-2826
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:31:15.126732Z
status: published
lens: p_space
sector: education
headline: AI literacy and competency in nursing education: preparing students and faculty members for an AI-enabled future-a systematic review and meta-analysis
dek: Introduction: Artificial Intelligence (AI) has made its way into every dimension of human life, and its impact is significant and multifaceted. Specifically, the effect of AI in nursing education has reshaped the healthcare system. However, this technological shift in nursing and the healthcare system still needs to be evaluated in multiple aspects to ensure the effective use of AI and to prepare future professionals. Methods: This PROSPERO-registered systematic literature review and meta-analysis explored the i…
gain_title: (none)
problem_title: A systematic review and meta-analysis of 18 quantitative studies found a pooled AI implementation rate of 67% in nursing groups, but only 55% among working nurses against 78% among students.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: A systematic review and meta-analysis of 18 quantitative studies found a pooled AI implementation rate of 67% in nursing groups, but only 55% among working nurses against 78% among students.
problem_evidence: The implementation of AI-related skills remains highly variable (67%, 95% CI: 55-78%), especially in low-resource settings | Pooled estimates of nursing students were 78%, which is significantly higher than the nursing staff (55%).
quick_read: A PROSPERO-registered systematic review covered 111 peer-reviewed articles from January 2020 to June 2025, 18 of them quantitative studies pooled in a meta-analysis. Pooled AI-related awareness among nursing students, faculty and nurses was 73%, positive attitudes 71% and implementation of AI-related skills 67%.

The averages hide a split. Nursing students scored higher than working nurses on awareness (79% vs 65%) and implementation (78% vs 55%), and the review links the gap to nurses' lack of formal AI training.

The review also found that many nursing programs lack standardized curricula, faculty training and infrastructure, especially in low-resource settings. Variation between studies was very high (I2 above 97%), so the authors treat the pooled figures as directional rather than definitive.
limitation: Variation between studies was extreme (I2 above 97%), and most included studies came from high- and middle-income countries, so the pooled percentages may not reflect global readiness.
tag: Evidence-backed problem
key_points: The review screened 54,780 records across eight databases and included 111 articles; 18 quantitative studies went into the meta-analysis. | Pooled AI awareness was 73% (95% CI 64-80%), attitudes 71% (63-78%) and implementation 67% (55-78%). | Faculty (82%) and students (79%) showed higher AI awareness than hospital nursing staff (65%), a statistically significant difference. | Students had a pooled implementation rate of 78% against 55% for working nurses. | Thematic synthesis found AI teaching often limited to elective modules or broad informatics courses, with faculty lacking AI training and confidence. | Programs in countries such as Palestine, Pakistan and the United Arab Emirates lagged on curriculum reform because of weak policy direction and incentives. | Nursing students and faculty raised concerns about data privacy, algorithmic bias and over-reliance on AI at the expense of human judgment. | The authors recommend that nursing councils and health ministries mandate core AI competencies, fund faculty development and close the digital divide.
rundown: The authors followed PRISMA 2020 guidelines and searched Medline via PubMed, Web of Science, Cochrane, Scopus, CINAHL and other databases using four progressively broader search levels. After screening, 111 articles were included, covering nursing students, faculty and practicing nurses; both traditional and generative AI were counted.

Quality checks found the 16 cross-sectional studies mostly at low to moderate risk of bias, and the single randomized trial at low risk. Random-effects models pooled awareness, attitude and implementation, with Egger's tests showing no strong publication bias. Meta-regression found year of publication significant only for attitudes.

Attitudes among students (74%) were higher than among nursing staff (63%), though that difference was not significant at the 5% level. The thematic synthesis identified five themes: curriculum integration, faculty readiness, student perception, innovative pedagogy and ethics.

The authors tie the weaker implementation to unprepared faculty, limited funding, inadequate digital infrastructure and a resistant academic community, and say students in urban, high-income regions had far better access to AI tools. They call for mandatory AI competencies, faculty development programs and funded simulation labs.
sources:
- peer_reviewed | Frontiers in Medicine | https://doi.org/10.3389/fmed.2025.1681784 | 2025-11-26
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