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Educational and experiential factors influence registered nurses' attitudes toward and literacy in artificial intelligenceFactors Influencing Registered Nurses' Attitudes Toward Artificial Intelligence

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Key Takeaway
Note that educational and experiential factors, rather than demographics, primarily influence nurse AI literacy.

This systematic review synthesizes evidence from 30 studies to identify factors influencing registered nurses' attitudes toward and literacy in artificial intelligence. The review focuses on how professional and personal attributes impact the adoption and understanding of AI technologies in nursing practice.

Findings indicate that attitudes toward artificial intelligence are influenced by educational attainment, age, length of service, gender, professional title, hospital tier, AI awareness, training experience, usage experience, AI anxiety, and digital leadership. For artificial intelligence literacy specifically, the synthesis identifies leadership style, AI training experience, and usage experience as the primary influencing factors.

Evidence suggests that educational and experiential interventions are more effective in enhancing AI literacy than demographic characteristics. These findings suggest that nursing managers should implement structured training programs and provide more opportunities for nurses to apply new technologies in clinical settings. The results are a synthesis of existing literature rather than primary trial data.

A systematic review of 30 different studies looked at what influences the attitudes and literacy of 12,958 registered nurses regarding artificial intelligence. The researchers wanted to see what factors help nurses feel more comfortable and capable when using AI technologies in healthcare.

The findings show that personal characteristics like age, gender, and years of service do not have as much impact as practical experience. Instead, factors such as specific AI training, actual usage experience, and a nurse's level of AI awareness are key drivers of their attitudes. For literacy, leadership style and hands-on experience were the main factors identified.

Because this is a review of existing studies rather than a new trial, the results show links rather than direct causes. The evidence suggests that for hospitals to improve how staff use technology, they should focus on practical training programs and leadership. These interventions are more effective at improving literacy than a nurse's demographic background.

What this means for you:
Training and hands-on experience are more important than age or gender in shaping how nurses use AI technology.

Common questions

What factors influence how nurses feel about AI?

Several factors influence how registered nurses feel about artificial intelligence. These include educational attainment, age, length of service, gender, professional title, and hospital category. Additionally, a nurse's level of AI awareness, training experience, usage experience, and digital leadership also play significant roles in shaping their attitudes.

What helps improve a nurse's AI literacy?

A nurse's ability to understand and use artificial intelligence, known as literacy, is primarily influenced by leadership style, specific AI training experience, and the frequency of their usage. The study suggests that these practical and educational interventions are more effective for improving literacy than demographic characteristics.

How can hospitals better prepare staff for AI?

The research suggests that nursing managers should implement smart training programs and create more opportunities for nurses to actually use new technologies. These practical experiences and educational interventions are more effective at improving literacy than factors like a nurse's age or gender.

Study Details

Study typeMeta analysis
EvidenceLevel 1
PublishedOct 2026
View Original Abstract ↓
BackgroundPresently, artificial intelligence technology is being extensively applied across clinical nursing practice. However, whether this technology can be deeply integrated into clinical workflows depends largely on nurses’ attitudes and literacy regarding artificial intelligence. Consequently, conducting an in depth exploration of core factors shaping registered nurses’ artificial intelligence attitudes and literacy holds significant importance for driving the rapid development of intelligent nursing.MethodsThis study strictly adhered to PRISMA guidelines. Systematic searches were conducted across seven English databases, namely PubMed, Web of Science, Medline, Embase, The Cochrane Library, IEEE Xplore, and CINAHL, alongside three Chinese databases, including China National Knowledge Infrastructure (CNKI), Wanfang Data, and VIP Database. The search timeframe ranged from database inception through May 30, 2026. Following screening according to inclusion and exclusion criteria, independent factors influencing attitudes and literacy were extracted. Employing a narrative synthesis approach, these influencing factors were categorized, summarized, and narratively integrated across distinct thematic domains.ResultsA total of 30 studies involving 12,958 registered nurses were included in this systematic review. The majority of the studies were conducted in China and Turkey. The independent factors influencing registered nurses’ attitudes toward artificial intelligence included educational attainment, age, length of service, gender, professional title/nursing level, hospital tier/category, AI awareness/understanding/knowledge, AI training experience, AI usage experience, artificial intelligence anxiety, and digital leadership. The factors independently affecting nurses’ artificial intelligence literacy included leadership style, AI training experience, and usage experience/frequency.ConclusionCurrent evidence indicates that key modifiable factors to improve nurses’ attitudes toward and literacy in artificial intelligence include AI-related training, practical hands-on experience, and organizational leadership, while technical anxiety should not be overlooked. Compared with demographic characteristics, educational and experiential interventions appear more effective in enhancing nurses’ artificial intelligence literacy levels. Nursing managers should actively implement smart training programs, increase opportunities for nurses to apply new technologies in clinical practice, and formulate relevant policies regarding data privacy protection and accountability division, thereby promoting the safe and effective integration of AI technology into patient care.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/recorddashboard
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