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Development of the nursing artificial intelligence readiness scale for nursing students: a validity and reliability
Sümeyye Akçoban1, Gülay Koca2, Soner Berşe3
1Department of Health Services, Kırıkhan Vocational School, Hatay Mustafa Kemal University, Hatay, Turkey.
BMC Nursing
|July 17, 2026
Summary
A new scale, the Nursing Artificial Intelligence Readiness Scale (NAIRS), effectively measures nursing students' AI readiness. This tool assesses knowledge, willingness, self-efficacy, and ethical awareness for AI integration in healthcare education.
Area of Science:
- Nursing Education
- Artificial Intelligence in Healthcare
- Psychometric Scale Development
Background:
- Increasing integration of artificial intelligence (AI) in healthcare necessitates nurses proficient with AI systems.
- Assessing nursing students' AI readiness is crucial for curriculum development and targeted educational interventions.
- A psychometrically sound instrument is needed to evaluate nursing students' preparedness for AI in healthcare.
Purpose of the Study:
- To develop and psychometrically evaluate the Nursing Artificial Intelligence Readiness Scale (NAIRS).
- To assess nursing students' readiness for AI across four key domains: Knowledge/Awareness, Willingness to Use AI, Self-efficacy, and Ethical Awareness.
Main Methods:
- Methodological scale development study involving 416 nursing students in Türkiye.
- Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were used to examine construct validity.
- Content validity, internal consistency (Cronbach's alpha), and test-retest reliability (ICC) were assessed.
Main Results:
- The final 20-item NAIRS demonstrated a robust four-factor structure, explaining 52.08% of the variance.
- CFA confirmed good model fit, with high internal consistency (total scale alpha = 0.911) and strong test-retest reliability (ICC = 0.952).
- The scale showed strong psychometric properties across all assessed domains.
Conclusions:
- The NAIRS is a valid and reliable instrument for measuring nursing students' AI readiness.
- The scale can inform educational needs assessments and curriculum planning in nursing education.
- NAIRS provides a foundation for evaluating and enhancing nursing students' competency in AI-supported healthcare environments.
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