Development and psychometric evaluation of the artificial intelligence attitude scale for nurses

Area of Science:

• Nursing Informatics
• Healthcare Technology Integration
• Artificial Intelligence in Healthcare

Background:

• Artificial intelligence (AI) is increasingly transforming healthcare delivery.
• Effective integration of AI in clinical settings necessitates understanding healthcare professionals' perspectives.
• Assessing nurses' attitudes towards AI is crucial for optimizing its adoption and impact.

Purpose of the Study:

• To develop a psychometrically sound Artificial Intelligence Attitude Scale (AIAS).
• To validate the AIAS specifically for application among Turkish nurses.
• To provide a reliable instrument for evaluating nurses' perceptions of AI in healthcare.

Main Methods:

• Methodological study conducted with 678 nurses in Turkey (October-December 2024).
• Item pool generated from a comprehensive literature review.
• Rigorous data analysis including EFA, CFA, validity (convergent, divergent), and reliability (internal consistency, test-retest) assessments.

Main Results:

• The developed scale demonstrated high content validity (CVI 0.85-1.00).
• Exploratory factor analysis identified four factors explaining 77.28% of the variance.
• Confirmatory factor analysis indicated acceptable model fit (GFI=0.921, RMSEA=0.064) and high reliability (Cronbach's alpha 0.93-0.95).

Conclusions:

• The validated Artificial Intelligence Attitude Scale for Nurses is a reliable and valid instrument.
• Findings offer valuable insights into nurses' attitudes towards digital technologies in healthcare.
• The scale can inform strategies for successful digital transformation in healthcare services.