Evaluation of future nurses' knowledge, attitudes and anxiety levels about artificial intelligence applications

Area of Science:

• Nursing Education
• Health Informatics
• Artificial Intelligence in Healthcare

Background:

• Assessing future nurses' understanding and anxiety concerning artificial intelligence (AI) is crucial for advancing technology-based healthcare.
• Identifying knowledge gaps and emotional responses to AI among nursing students informs educational strategies.

Purpose of the Study:

• To evaluate the knowledge, attitude, and anxiety levels of nursing students regarding AI applications.
• To understand the current preparedness of future nurses for AI integration in healthcare.

Main Methods:

• A descriptive study involving 552 nursing students.
• Data collected using a "Data collection form" and the "Artificial Intelligence Anxiety Scale" (AIAS).
• Statistical analyses included descriptive statistics and various non-parametric tests (Kolmogorov-Smirnov, Shapiro-Wilk, Spearman, Mann-Whitney U, Kruskal-Wallis).

Main Results:

• The average AIAS score indicated high anxiety levels among students (51.68 ± 12.32).
• A significant majority (95.3%) had no AI training, and 94.0% lacked AI in their coursework.
• Over three-quarters (79.2%) expressed a desire for AI-related subjects in their curriculum.

Conclusions:

• Nursing students demonstrate elevated anxiety concerning AI, often linked to negative perceptions.
• There is a clear need to incorporate AI education into nursing programs.
• Early exposure and integration of AI concepts into student nurses' learning and clinical experiences are recommended.